ALBERT

Description: Under the potential to reconstruct the past climatic and atmospheric conditions from a deep ice core in the coastal Antarctic site (Styx Glacier), an 8.84 m long firn core (73°50.975′ S, 163°41.640′ E; 1623 m a.s.l.) was initially studied to propose a reliable age scale for the local estimation of snow accumulation rate. The seasonal variations of δ18O, methanesulfonic acid (MSA) and non-sea-salt sulfate (nssSO42–) were used for the firn core dating and revealed 25 annual peaks (from 1990 to 2014) with volcanic sulfate signal. The observed declining trend in annual accumulation rate with a mean value of 146 ± 60 kg m–2 a–1 is likely to be linked to the changes of sea-ice extent in the Ross Sea region. Moreover, the temporal variation of the annual mean δ18O, an annual flux of MSA and nssSO42– also likely to be under the influence of ice-covered and open water area. This study suggests a potential to recover past changes in an oceanic environment and will be useful for the interpretation of the long ice core drilled at the same site.

Description: Clouds play an important role in the Arctic surface radiative budget, impacting the seasonal evolution of Arctic sea-ice cover. We explore the large-scale impacts of springtime and early summer (March through July) cloud and radiative fluxes on sea ice by comparing these fluxes to seasonal ice volume losses over the central Arctic basin, calculated for available observational years 2004–2007 (ICESat) and 2011–2017 (CryoSat-2). We also supplement observation data with sea-ice volume computed from the Pan-Arctic Ice–Ocean Modeling and Assimilation System (PIOMAS) during summer months. We find that the volume of sea ice lost over the melt season is most closely related to observed downwelling longwave radiation in March and early summer (June and July) longwave cloud radiative forcing, which together explain a large fraction of interannual variability in seasonal sea-ice volume loss (R2 = 0.71, p = 0.007). We show that downwelling longwave fluxes likely impact the timing of melt onset near the sea-ice edge, and can limit the magnitude of ice thickening from March to April. Radiative fluxes in June and July are likely critical to seasonal volume loss because modeled data show the greatest ice volume reductions occur during these months.

Description: Ghana is urbanising rapidly, and over half of the country’s population have lived in urban areas since 2010. Although research has proliferated to explore Ghana’s urbanisation, there is a dearth of research that holistically explores the wider sustainability implications of urbanisation, offers comparative perspectives in the context of large and smaller urban areas, and provides a perspective of local level urbanisation in the context of resource extraction (mining). This study comparatively assesses two urban areas in Ghana (Kumasi and Obuasi), by conducting a spatio-temporal analysis of land cover change through remote sensing and by analysing demographic change through a synthesis of published population data, in order to highlight the sustainability implications of urbanisation. The results show that urbanisation has been rapid, and has resulted in changes in land cover and demography in Kumasi and Obuasi. The sustainability implications of urbanisation are identified to include limited economic opportunities, socio-spatial segregation, and destruction of natural vegetation. The evidence in this study provides insights into urbanisation in Ghana, and suggests that the positive sustainability impacts of urbanisation may be eroded by how factors such as market forces and land tenure interact at the local level.

Description: The optimization of ecological resource allocation is increasingly seen as a potential solution for urban revitalization and sustainable land use planning, and the key point is to assess and simulate the spatial arrangement of the ecological land. In this study, we proposed a conceptual framework with the aim of reoccupying ecological resources for rust belt cities from the perspective of eco-economic trade-offs. The ecological security pattern, the urban development pattern, and the ecological quality of cropland were constructed and evaluated to measure the development level of an ecological system and a socio-economic system. Furthermore, the results were used as the constraints that influenced land use distribution to simulate the ecological land reoccupation pattern. The suitable area, the preservation area, the configurable area, and the unsuitable area in the reoccupation pattern accounted for 6.94%, 49.97%, 28.17%, and 0.69%, respectively. Significantly, under strict cropland protection policies, the available space for ecological land expansion was heavily compressed. Therefore, the emphasis on agricultural production should be reexamined to release more space for ecological resources. This method could be an effective pathway to alleviate the pressures on urban and natural space caused by the competition between land-use activities, such as economic development, agricultural production, and ecological conservation. The findings are expected to promote urban revitalization, green agriculture, and sustainable social development in rust belt cities, and provide certain references for the utilization of land resources and regional policy making.

Description: As acidic deposition has decreased across Eastern North America, forest soils at some sites are beginning to show reversal of soil acidification. However, the degree of recovery appears to vary and is not fully explained by deposition declines alone. To assess if other site and soil factors can help to explain degree of recovery from acid deposition, soil resampling chemistry data (8- to 24-year time interval) from 23 sites in the United States and Canada, located across 25° longitude from Eastern Maine to Western Ontario, were explored. Site and soil factors included recovery years, sulfate (SO42−) deposition history, SO42− reduction rate, C horizon pH and exchangeable calcium (Ca), O and B horizon pH, base saturation, and exchangeable Ca and aluminum (Al) at the time of the initial sampling. We found that O and B horizons that were initially acidified to a greater degree showed greater recovery and B horizon recovery was further associated with an increase in recovery years and lower initial SO42− deposition. Forest soils that seemingly have low buffering capacity and a reduced potential for recovery have the resilience to recover from the effects of previous high levels of acidic deposition. This suggests, that predictions of where forest soils acidification reversal will occur across the landscape should be refined to acknowledge the importance of upper soil profile horizon chemistry rather than the more traditional approach using only parent material characteristics.

Description: The genus Thujopsis (Cupressaceae) comprises monoecious coniferous trees endemic to Japan. This genus includes two varieties: Thujopsis dolabrata (L.f.) Siebold et Zucc. var. dolabrata (southern variety, Td) and Thujopsis dolabrata (L.f.) Siebold et Zucc. var. hondae Makino (northern variety, Th). The aim of this study is to understand the phylogeographic and genetic population relationships of the genus Thujopsis for the conservation of genetic resources and future breeding. A total of 609 trees from 22 populations were sampled, including six populations from the Td distribution range and 16 populations from the Th distribution range. The genotyping results for 19 expressed sequence tag (EST)-based simple sequence repeat (SSR) markers, followed by a structure analysis, neighbor-joining tree creation, an analysis of molecular variance (AMOVA), and hierarchical F statistics, supported the existence of two genetic clusters related to the distribution regions of the Td and Th varieties. The two variants, Td and Th, could be defined by their provenance, in spite of the ambiguous morphological differences between the varieties. The distribution ranges of both variants, which have been defined from their morphology, was confirmed by genetic analysis. The Th populations exhibited relatively uniform genetic diversity, most likely because Th refugia in the glacial period were scattered throughout their current distribution area. On the other hand, there was a tendency for Td’s genetic diversity to decrease from central to southern Honshu island. Notably, the structure analysis and neighbor-joining tree suggest the hybridization of the two varieties in the contact zone. More detailed studies of the genetic structure of Td are required in future analyses.

Description: Ice accretion is a phenomenon whereby super-cooled water droplets impinge and accrete on wall surfaces. It is well known that the icing may cause severe accidents via the deformation of airfoil shape and the shedding of the growing adhered ice. To prevent ice accretion, electro-thermal heaters have recently been implemented as a de- and anti-icing device for aircraft wings. In this study, an icing simulation method for a two-dimensional airfoil with a heating surface was developed by modifying the extended Messinger model. The main modification is the computation of heat transfer from the airfoil wall and the run-back water temperature achieved by the heater. A numerical simulation is conducted based on an Euler–Lagrange method: a flow field around the airfoil is computed by an Eulerian method and droplet trajectories are computed by a Lagrangian method. The wall temperature distribution was validated by experiment. The results of the numerical and practical experiments were in reasonable agreement. The ice shape and aerodynamic performance of a NACA 0012 airfoil with a heater on the leading-edge surface were computed. The heating area changed from 1% to 10% of the chord length with a four-degree angle of attack. The simulation results reveal that the lift coefficient varies significantly with the heating area: when the heating area was 1.0% of the chord length, the lift coefficient was improved by up to 15%, owing to the flow separation instigated by the ice edge; increasing the heating area, the lift coefficient deteriorated, because the suction peak on the suction surface was attenuated by the ice formed. When the heating area exceeded 4.0% of the chord length, the lift coefficient recovered by up to 4%, because the large ice near the heater vanished. In contrast, the drag coefficient gradually decreased as the heating area increased. The present simulation method using the modified extended Messinger model is more suitable for de-icing simulations of both rime and glaze ice conditions, because it reproduces the thin ice layer formed behind the heater due to the runback phenomenon.

Description: The lack of a universal simulation method for triboelectric nanogenerator (TENG) makes the device design and optimization difficult before experiment, which protracts the research and development process and hinders the landing of practical TENG applications. The existing electrostatic induction models for TENGs have limitations in simulating TENGs with complex geometries and their dynamic behaviors under practical movements due to the topology change issues. Here, a dynamic finite element method (FEM) model is proposed. The introduction of air buffer layers and the moving mesh method eliminates the topology change issues during practical movement and allows simulation of dynamic and time-varying behaviors of TENGs with complex 2D/3D geometries. Systematic investigations are carried out to optimize the air buffer thickness and mesh densities, and the optimized results show excellent consistency with the experimental data and results based on other existing methods. It also shows that a 3D disk-type rotating TENG can be simulated using the model, clearly demonstrating the capability and superiority of the dynamic FEM model. Moreover, the dynamic FEM model is used to optimize the shape of the tribo-material, which is used as a preliminary example to demonstrate the possibility of designing a TENG-based sensor.

Description: In agricultural science, the establishment of a given cropping system in mountainous areas is often understood from the relationship between differences of altitude-specific, agroecological conditions and crop cultivation characteristics. However, social factors can also play a role. We aimed to clarify how the cropping system is maintained through examining sociocultural factors, specifically land tenure and marriage systems, in an agricultural community in rural mountainous Africa. Several surveys based on participatory observation accompanied by home stays were conducted to determine people who participated in cropping systems and to understand which social system maintained the cropping system. We found that around 70% of target households in Kiboguwa village cultivated three staple crops (maize, cassava and rice) using the same cropping system and almost no farmers outside the village used the village’s sloped fields, meaning that the villagers maintained the cropping system. Households acquired nearby sloped fields by various means such as inheriting land through maternal lineage of household heads or wives. We observed virilocal and uxorilocal residence at similar degrees—and if either the husband or wife was from outside the village, that household would also have fields outside the village. However, nearly 80% of marriages were intravillage and villagers predominantly used fields located within the village limits regardless of the residence type, which helped maintain the cropping system.

Description: In this paper, 3D-printed electromagnetic (or microwave) encoders with synchronous reading based on permittivity contrast, and devoted to the measurement of displacements and velocities, are reported for the first time. The considered encoders are based on two chains of linearly shaped apertures made on a 3D-printed high-permittivity dielectric material. One such aperture chain contains the identification (ID) code, whereas the other chain provides the clock signal. Synchronous reading is necessary in order to determine the absolute position if the velocity between the encoder and the sensitive part of the reader is not constant. Such absolute position can be determined as long as the whole encoder is encoded with the so-called de Bruijn sequence. For encoder reading, a splitter/combiner structure with each branch loaded with a series gap and a slot resonator (each one tuned to a different frequency) is considered. Such a structure is able to detect the presence of the apertures when the encoder is displaced, at short distance, over the slots. Thus, by injecting two harmonic signals, conveniently tuned, at the input port of the splitter/combiner structure, two amplitude modulated (AM) signals are generated by tag motion at the output port of the sensitive part of the reader. One of the AM envelope functions provides the absolute position, whereas the other one provides the clock signal and the velocity of the encoder. These synchronous 3D-printed all-dielectric encoders based on permittivity contrast are a good alternative to microwave encoders based on metallic inclusions in those applications where low cost as well as major robustness against mechanical wearing and aging effects are the main concerns.

Description: This paper presents a vulnerable road user (VRU) tracking algorithm capable of handling noisy and missing detections from heterogeneous sensors. We propose a cooperative fusion algorithm for matching and reinforcing of radar and camera detections using their proximity and positional uncertainty. The belief in the existence and position of objects is then maximized by temporal integration of fused detections by a multi-object tracker. By switching between observation models, the tracker adapts to the detection noise characteristics making it robust to individual sensor failures. The main novelty of this paper is an improved imputation sampling function for updating the state when detections are missing. The proposed function uses a likelihood without association that is conditioned on the sensor information instead of the sensor model. The benefits of the proposed solution are two-fold: firstly, particle updates become computationally tractable and secondly, the problem of imputing samples from a state which is predicted without an associated detection is bypassed. Experimental evaluation shows a significant improvement in both detection and tracking performance over multiple control algorithms. In low light situations, the cooperative fusion outperforms intermediate fusion by as much as 30%, while increases in tracking performance are most significant in complex traffic scenes.

Description: Failures of marine propulsion components or systems can lead to serious consequences for a vessel, cargo and the people onboard a ship. These consequences can be financial losses, delay in delivery time or a threat to safety of the people onboard. This is why it is necessary to learn about marine propulsion failures in order to prevent worst-case scenarios. This paper aims to provide a review of experimental, analytical and numerical methods used in the failure analysis of ship propulsion systems. In order to achieve that, the main causes and failure mechanisms are described and summarized. Commonly used experimental, numerical and analytical tools for failure analysis are given. Most indicative case studies of ship failures describe where the origin of failure lies in the ship propulsion failures (i.e., shaft lines, crankshaft, bearings, foundations). In order to learn from such failures, a holistic engineering approach is inevitable. This paper tries to give suggestions to improve existing design procedures with a goal of producing more reliable propulsion systems and taking care of operational conditions.

Description: East Asia is the most complex region in the world for aerosol studies, as it encounters a lot of varieties of aerosols, and aerosol classification can be a challenge in this region. In the present study, we focused on the relationship between aerosol types and aerosol optical properties. We analyzed the long-term (2005–2012) data of vertical profiles of aerosol extinction coefficients, lidar ratio (Sp), and other aerosol optical properties obtained from a NASA Micro-Pulse Lidar Network and Aerosol Robotic Network site in northern Taiwan, which frequently receives Asian continental outflows. Based on aerosol extinction vertical profiles, the profiles were classified into two types: type 1 (single-layer structure) and type 2 (two-layer structure). Fall season (October–November) was the prevailing season for the Type 1, whereas type 2 mainly happened in spring (March–April). In type 1, air masses normally originated from three regional sectors, i.e., Asia continental (AC), Pacific Ocean (PO), and Southeast Asia (SA). The mean Sp values were 39 ± 17 sr, 30 ± 12 sr, and 38 ± 18 sr for the AC, PO, and SA sectors, respectively. The Sp results suggested that aerosols from the AC sector contained dust and anthropogenic particles, and aerosols from the PO sector were most likely sea salts. We further combined the EPA dust event database and backward trajectory analysis for type 2. Results showed that Sp was 41 ± 14 sr and 53 ± 21 sr for dust storm and biomass-burning events, respectively. The Sp for biomass-burning events in type 2 showed two peaks patterns. The first peak occurred within range of 30–50 sr corresponding to urban pollutant, and the second peak occurred within range of 60–80 sr in relation to biomass burning. Finally, our study summarized the Sp values for four major aerosol types over northern Taiwan, viz., urban (42 ± 18 sr), dust (34 ± 6 sr), biomass-burning (69 ± 12 sr), and oceanic (30 ± 12 sr). Our findings provide useful references for aerosol classification and air pollution identification over the western North Pacific.

Description: Urbanization is a complex process closely involving the economy, society, and population. While monitoring urban development and exploring the industry-driving force in a real-time and effective way are the prerequisites for optimizing industry structure, narrowing the urban development gap, and achieving sustainable development. Nighttime light is an effective tool to monitor urban development from a macro perspective. However, the systematic research of nighttime light spatiotemporal variation modes and the industry-driving force of urban nighttime light are still unknown. Considering these issues, this paper analyzes the spatiotemporal variation modes of the average light index (ALI) and investigates the industry-driving force of ALI in 100 major prefecture-level cities across China mainland based on National Polar-Orbiting Partnership Satellite Visible Infrared Imaging Radiometer Suite (NPP VIIRS). The conclusions are as following three aspects. First, ALI is observed a funnel pattern among four regions in spatial dimension, with low in center and high in the surrounding, and it shows 5 variation modes (“W,” “√,” “Exponent,” “Logarithm,” and “N”) in temporal dimension, of which the “√” mode accounts for the highest proportion (60%). Second, the industry structure is closely related to ALI. Besides, the factor analysis result illustrates that the secondary and tertiary industry are the driving industries of ALI. Third, the classification result based on the industry contribution rate indicates that cities driven by different industries show significant spatial distribution differences. The three major industry-driving cities are mainly distributed in central and western regions, the secondary and tertiary industry-driving cities are evenly distributed, and the tertiary industry-driving cities are mainly distributed in provincial capitals. From 2013 to 2018, the fluctuation of city distribution driven by different industries changes obviously. The number of tertiary industry-driving cities increases steadily and the three major industry-driving cities are distributed wider spatially. Additionally, the impacts of location and raw coal on ALI are discussed. In general, these findings are essential to further research urban development mode and can be considered as the reference to narrow urban development gap.

Description: Flat surfaces captured by 3D point clouds are often used for localization, mapping, and modeling. Dense point cloud processing has high computation and memory costs making low-dimensional representations of flat surfaces such as polygons desirable. We present Polylidar3D, a non-convex polygon extraction algorithm which takes as input unorganized 3D point clouds (e.g., LiDAR data), organized point clouds (e.g., range images), or user-provided meshes. Non-convex polygons represent flat surfaces in an environment with interior cutouts representing obstacles or holes. The Polylidar3D front-end transforms input data into a half-edge triangular mesh. This representation provides a common level of abstraction for subsequent back-end processing. The Polylidar3D back-end is composed of four core algorithms: mesh smoothing, dominant plane normal estimation, planar segment extraction, and finally polygon extraction. Polylidar3D is shown to be quite fast, making use of CPU multi-threading and GPU acceleration when available. We demonstrate Polylidar3D’s versatility and speed with real-world datasets including aerial LiDAR point clouds for rooftop mapping, autonomous driving LiDAR point clouds for road surface detection, and RGBD cameras for indoor floor/wall detection. We also evaluate Polylidar3D on a challenging planar segmentation benchmark dataset. Results consistently show excellent speed and accuracy.

Description: A low-mass and low-volume dual-polarization L-band radiometer is introduced that has applications for ground-based remote sensing or unmanned aerial vehicle (UAV)-based mapping. With prominent use aboard the ESA Soil Moisture and Ocean Salinity (SMOS) and NASA Soil Moisture Active Passive (SMAP) satellites, L-band radiometry can be used to retrieve environmental parameters, including soil moisture, sea surface salinity, snow liquid water content, snow density, vegetation optical depth, etc. The design and testing of the air-gapped patch array antenna is introduced and is shown to provide a 3-dB full power beamwidth of 37°. We present the radio-frequency (RF) front end design, which uses direct detection architecture and a square-law power detector. Calibration is performed using two internal references, including a matched resistive source (RS) at ambient temperature and an active cold source (ACS). The radio-frequency (RF) front end does not require temperature stabilization, due to characterization of the ACS noise temperature by sky measurements. The ACS characterization procedure is presented. The noise equivalent delta (Δ) temperature (NEΔT) of the radiometer is ~0.14 K at 1 s integration time. The total antenna temperature uncertainty ranges from 0.6 to 1.5 K.

Description: In this study, the environmental impacts of various alternative ship fuels for a coastal ferry were assessed by the life cycle assessment (LCA) analysis. The comparative study was performed with marine gas oil (MGO), natural gas, and hydrogen with various energy sources for a 12,000 gross tonne (GT) coastal ferry operating in the Republic of Korea (ROK). Considering the energy imports of ROK, i.e., MGO from Saudi Arabia and natural gas from Qatar, these countries were chosen to provide the MGO and the natural gas for the LCA. The hydrogen is considered to be produced by steam methane reforming (SMR) from natural gas with hard coal, nuclear energy, renewable energy, and electricity in the ROK model. The lifecycles of the fuels were analyzed in classifications of Well-to- Tank, Tank-to-Wake, and Well-to-Wake phases. The environmental impacts were provided in terms of global warming potential (GWP), acidification potential (AP), photochemical potential (POCP), eutrophication potential (EP), and particulate matter (PM). The results showed that MGO and natural gas cannot be used for ships to meet the International Maritime Organization’s (IMO) 2050 GHG regulation. Moreover, it was pointed out that the energy sources in SMR are important contributing factors to emission levels. The paper concludes with suggestions for a hydrogen application plan for ships from small, nearshore ships in order to truly achieve a ship with zero emissions based on the results of this study.

Description: In this study, we proposed a semi-automated and interactive scheme for organ contouring in radiotherapy planning for patients with non-small cell lung cancers. Several organs were contoured, including the lungs, airway, heart, spinal cord, body, and gross tumor volume (GTV). We proposed some schemes to automatically generate and vanish the seeds of the random walks (RW) algorithm. We considered 25 lung cancer patients, whose computed tomography (CT) images were obtained from the China Medical University Hospital (CMUH) in Taichung, Taiwan. The manual contours made by clinical oncologists were taken as the gold standard for comparison to evaluate the performance of our proposed method. The Dice coefficient between two contours of the same organ was computed to evaluate the similarity. The average Dice coefficients for the lungs, airway, heart, spinal cord, and body and GTV segmentation were 0.92, 0.84, 0.83, 0.73, 0.85 and 0.66, respectively. The computation time was between 2 to 4 min for a whole CT sequence segmentation. The results showed that our method has the potential to assist oncologists in the process of radiotherapy treatment in the CMUH, and hopefully in other hospitals as well, by saving a tremendous amount of time in contouring.

Description: We compared the catalytic effects of two polymers (soluble starch and apple pectin) on the flocculation of kaolinite suspension. Moreover, the relationship between the zeta potential value and the time when kaolin particle sedimentation occurred was verified, and the mechanism of flocculation was analyzed. Additionally, a constitutive model was proposed to simulate the non-ideal sedimentation of clay particles in an aqueous system under constant gravity. This model not only considers the inhomogeneity of the solute but also simulates the change in clay concentration with time during the deposition process. This model proposes a decay constant (α) and sedimentation coefficient (s). The model can also be used to calculate the instantaneous sedimentation rate of the clay suspensions at any time and any depth for the settling cylinder. These sedimentary characteristics were simulated by adopting the established deposition model. The results show that the model is capable of predicting the time required for the complete sedimentation of particles in the aqueous system, suggesting the feasibility of engineering wastewater treatment, site dredging, etc.

Description: An essential aspect in the interaction between people and computers is the recognition of facial expressions. A key issue in this process is to select relevant features to classify facial expressions accurately. This study examines the selection of optimal geometric features to classify six basic facial expressions: happiness, sadness, surprise, fear, anger, and disgust. Inspired by the Facial Action Coding System (FACS) and the Moving Picture Experts Group 4th standard (MPEG-4), an initial set of 89 features was proposed. These features are normalized distances and angles in 2D and 3D computed from 22 facial landmarks. To select a minimum set of features with the maximum classification accuracy, two selection methods and four classifiers were tested. The first selection method, principal component analysis (PCA), obtained 39 features. The second selection method, a genetic algorithm (GA), obtained 47 features. The experiments ran on the Bosphorus and UIVBFED data sets with 86.62% and 93.92% median accuracy, respectively. Our main finding is that the reduced feature set obtained by the GA is the smallest in comparison with other methods of comparable accuracy. This has implications in reducing the time of recognition.

Description: Avalanche disasters are extremely destructive and catastrophic, often causing serious casualties, economic losses and surface erosion. However, far too little attention has been paid to utilizing remote sensing mapping avalanches quickly and automatically to mitigate calamity. Such endeavors are limited by formidable natural conditions, human subjective judgement and insufficient understanding of avalanches, so they have been incomplete and inaccurate. This paper presents an objective and widely serviceable method for regional auto-detection using the scattering and interference characteristics of avalanches extracted from Sentinel-1 SLC images. Six indices are established to distinguish avalanches from surrounding undisturbed snow. The active avalanche belts in Kizilkeya and Aktep of the Western TianShan Mountains in China lend urgency to this research. Implementation found that smaller avalanches can be consistently identified more accurately in descending images. Specifically, 281 and 311 avalanches were detected in the ascending and descending of Kizilkeya, respectively. The corresponding numbers on Aktep are 104 and 114, respectively. The resolution area of single avalanche detection can reach 0.09 km2. The performance of the model was excellent in all cases (areas under the curve are 0.831 and 0.940 in descending and ascending of Kizilkeya, respectively; and 0.807 and 0.938 of Aktep, respectively). Overall, the evaluation of statistical indices are POD 〉 0.75, FAR 〈 0.34, FOM 〈 0.13 and TSS 〉 0.75. The results indicate that the performance of the innovation proposed in this paper, which employs multivariate comprehensive descriptions of avalanche characteristics to actualize regional automatic detection, can be more objective, accurate, applicable and robust to a certain extent. The latest and more complete avalanche inventory generated by this design can effectively assist in addressing the increasingly severe avalanche disasters and improving public awareness of avalanches in alpine areas.

Description: Automated tracking of physical fitness has sparked a health revolution by allowing individuals to track their own physical activity and health in real time. This concept is beginning to be applied to tracking of cognitive load. It is well known that activity in the brain can be measured through changes in the body’s physiology, but current real-time measures tend to be unimodal and invasive. We therefore propose the concept of a wearable educational fitness (EduFit) tracker. We use machine learning with physiological data to understand how to develop a wearable device that tracks cognitive load accurately in real time. In an initial study, we found that body temperature, skin conductance, and heart rate were able to distinguish between (i) a problem solving activity (high cognitive load), (ii) a leisure activity (moderate cognitive load), and (iii) daydreaming (low cognitive load) with high accuracy in the test dataset. In a second study, we found that these physiological features can be used to predict accurately user-reported mental focus in the test dataset, even when relatively small numbers of training data were used. We explain how these findings inform the development and implementation of a wearable device for temporal tracking and logging a user’s learning activities and cognitive load.

Description: An extremely heavy rainfall event hit Guangdong province, China, from 27 August to 1 September 2018. There were two different extreme rain regions, respectively, at the Pearl River estuary and eastern Guangdong, and a record-breaking daily precipitation of 1056.7 mm was observed at Gaotan station on 30 August. This paper utilizes a suite of observations from soundings, a gauge network, disdrometers, and polarimetric radars to gain insights to the two rainfall centers. The large-scale meteorological forcing, rainfall patterns, and microphysical processes, as well as radar-based precipitation signatures are investigated. It is concluded that a west-moving monsoon depression played a critical role in sustaining the moisture supply to the two extreme rain regions, and the combined orographic enhancement further contributed to the torrential rainfall over Gaotan station. The raindrop size distributions (DSD) observed at Zhuhai and Huidong stations, as well as the observed polarimetric radar signatures indicate that the rainfall at Doumen region was characterized by larger raindrops but a lower number concentration compared with that at Gaotan region. In addition, the dual-polarization radars are used to quantify precipitation intensity during this extreme event, providing timely information for flood warning and emergency management decision-making.

Description: Dense β-SiC coating with 3C-structure was utilized as a dry cold forging punch and core-die. Pure titanium T328H wires of industrial grade II were employed as a work material. No adhesion or galling of metallic titanium was detected on the contact interface between this β-SiC die and titanium work, even after this continuous forging process, up to a reduction in thickness by 70%. SEM (Scanning Electron Microscopy) and EDX (Electron Dispersive X-ray spectroscopy) were utilized to analyze this contact interface. A very thin titanium oxide layer was in situ formed in the radial direction from the center of the contact interface. Isolated carbon from β-SiC agglomerated and distributed in dots at the center of the initial contact interface. Raman spectroscopy was utilized, yielding the discovery that this carbon is unbound as a free carbon or not bound in SiC or TiC and that intermediate titanium oxides are formed with TiO2 as a tribofilm.

Description: Earth remote sensing optical satellite systems are often divided into two categories—geosynchronous and sun-synchronous. Geosynchronous systems essentially rotate with the Earth and continuously observe the same region of the Earth. Sun-synchronous systems are generally in a polar orbit and view differing regions of the Earth at the same local time. Although similar in instrument design, there are enough differences in these two types of missions that often the calibration of the instruments can be substantially different. Thus, respective calibration teams develop independent methods and do not interact regularly or often. Yet, there are numerous areas of overlap and much to learn from one another. To address this issue, a panel of experts from both types of systems was convened to discover common areas of concern, areas where improvements can be made, and recommendations for the future. As a result of the panelist’s efforts, a set of eight recommendations were developed. Those that are related to improvements of current technologies include maintaining sun-synchronous orbits (not allowing orbital decay), standardization of spectral bandpasses, and expanded use of well-developed calibration techniques such as deep convective clouds, pseudo invariant calibration sites, and lunar methodologies. New techniques for expanded calibration capability include using geosynchronous instruments as transfer radiometers, continued development of ground-based prelaunch calibration technologies, expansion of RadCalNet, and development of space-based calibration radiometer systems.

Description: The manufacturing of parts from nickel-based superalloy Alloy 247LC by laser powder bed fusion (L-PBF) is challenging, primarily owing to the alloy’s susceptibility to cracks. Apart from the cracks, voids created during the L-PBF process should also be minimized to produce dense parts. In this study, samples of Alloy 247LC were manufactured by L-PBF, several of which could be produced with voids and crack density close to zero. A statistical design of experiments was used to evaluate the influence of the process parameters, namely laser power, scanning speed, and hatch distance (inherent to the volumetric energy density) on void formation, crack density, and microhardness of the samples. The window of process parameters, in which minimum voids and/or cracks were present, was predicted. It was shown that the void content increased steeply at a volumetric energy density threshold below 81 J/mm3. The crack density, on the other hand, increased steeply at a volumetric energy density threshold above 163 J/mm3. The microhardness displayed a relatively low value in three samples which displayed the lowest volumetric energy density and highest void content. It was also observed that two samples, which displayed the highest volumetric energy density and crack density, demonstrated a relatively high microhardness; which could be a vital evidence in future investigations to determine the fundamental mechanism of cracking. The laser power was concluded to be the strongest and statistically most significant process parameter that influenced void formation and microhardness. The interaction of laser power and hatch distance was the strongest and most significant factor that influenced the crack density.

Description: : The main purpose of this work is to study the effectiveness of using FeCeOx nanocomposites doped with Nb2O5 for the purification of aqueous solutions from manganese. X-ray diffraction, energy–dispersive analysis, scanning electron microscopy, vibrational magnetic spectroscopy, and mössbauer spectroscopy were used as research methods. It is shown that an increase in the dopant concentration leads to the transformation of the shape of nanoparticles from spherical to cubic and rhombic, followed by an increase in the size of the nanoparticles. The spherical shape of the nanoparticles is characteristic of a structure consisting of a mixture of two phases of hematite (Fe2O3) and cerium oxide CeO2. The cubic shape of nanoparticles is typical for spinel-type FeNbO4 structures, the phase contribution of which increases with increasing dopant concentration. It is shown that doping leads not only to a decrease in the concentration of manganese in model solutions, but also to an increase in the efficiency of adsorption from 11% to 75%.

Description: A common design concept of the piezoelectric force sensor, which is to assemble a bump structure from a flat or fine columnar piezoelectric structure or to use a specific type of electrode, is quite limited. In this paper, we propose a new design of cylindrical piezoelectric sensors that can detect multidirectional forces. The proposed sensor consists of four row and four column sensors. The design of the sensor was investigated by the finite element method. The response of the sensor to various force directions was observed, and it was demonstrated that the direction of the force applied to the sensor could be derived from the signals of one row sensor and three column sensors. As a result, this sensor proved to be able to detect forces in the area of 225° about the central axis of the sensor. In addition, a cylindrical sensor was fabricated to verify the proposed sensor and a series of experiments were performed. The simulation and experimental results were compared, and the actual sensor response tended to be similar to the simulation.

Description: As satellite observation technology improves, the number of remote sensing images significantly and rapidly increases. Therefore, a growing number of studies are focusing on remote sensing image retrieval. However, having a large number of remote sensing images considerably slows the retrieval time and takes up a great deal of memory space. The hash method is being increasingly used for rapid image retrieval because of its remarkably fast performance. At the same time, selecting samples that contain more information and greater stability to train the network has gradually become the key to improving retrieval performance. Given the above considerations, we propose a deep hash remote sensing image retrieval method, called the hard probability sampling hash retrieval method (HPSH), which combines hash code learning with hard probability sampling in a deep network. Specifically, we used a probability sampling method to select training samples, and we designed one novel hash loss function to better train the network parameters and reduce the hashing accuracy loss due to quantization. Our experimental results demonstrate that HPSH could yield an excellent representation compared with other state-of-the-art hash approaches. For the university of California, merced (UCMD) dataset, HPSH+S resulted in a mean average precision (mAP) of up to 90.9% on 16 hash bits, 92.2% on 24 hash bits, and 92.8% on 32 hash bits. For the aerial image dataset (AID), HPSH+S achieved a mAP of up to 89.8% on 16 hash bits, 93.6% on 24 hash bits, and 95.5% on 32 hash bits. For the UCMD dataset, with the use of data augmentation, our proposed approach achieved a mAP of up to 99.6% on 32 hash bits and 99.7% on 64 hash bits.

Description: Laser-based technologies are extensively used for polymer surface patterning and/or texturing. Different micro- and nanostructures can be obtained thanks to a wide range of laser types and beam parameters. Cell behavior on various types of materials is an extensively investigated phenomenon in biomedical applications. Polymer topography such as height, diameter, and spacing of the patterning will cause different cell responses, which can also vary depending on the utilized cell types. Structurization can highly improve the biological performance of the material without any need for chemical modification. The aim of the study was to evaluate the effect of CO2 laser irradiation of poly(L-lactide) (PLLA) thin films on the surface microhardness, roughness, wettability, and cytocompatibility. The conducted testing showed that CO2 laser texturing of PLLA provides the ability to adjust the structural and physical properties of the PLLA surface to the requirements of the cells despite significant changes in the mechanical properties of the laser-treated surface polymer.

Description: The research presented in the paper intends to overcome an information gap on the evolution of urbanized surfaces in Italy which in the studies carried out so far have never been available. The only historical data on this form of land use date back to the 1950s, and were extracted from a national cartography created by the Military Geographic Institute. The next chronological section available was then that of the noughties, already digital. However, much more frequent data were processed by the ten-year censuses by the National Institute of Statistics, but concerning buildings and not urbanized areas. By processing building census data, this study has put together some novel information on land take dynamics between the end of World War II and the year 2000, highlighting the more intensive processes that occurred at an extraordinary rate in the ‘70′s and ‘80′s, obtaining unprecedented information on the speed of transformation of the territory in these decades of economic boom. Through this method, we were able to obtain numerous geographical indications previously lacking on a national scale, highlight the yet significant vigor of this phenomenon and develop an inferential scenario.

Description: Access and use of seed of improved varieties of groundnut among farmers can improve farmers’ livelihoods and contribute to the potential of crop production in Tanzania. This paper analyzes factors underpinning the adoption of improved groundnut varieties among farmers to pave the way for upscaling quality seed used for increased production and commodity business in farming communities. A four-stage stratified sampling was used to collect data from 300 groundnut farmers in seven agro-ecological zones through individual interviews. Secondary data were collected from the literature and the Tanzania Agricultural Research Institute at Naliendele centre (TARI–Naliendele). Descriptive statistics and Probit regression model were used for data analysis. The empirical results showed that Johari 1985, Pendo 1998, Naliendele 2009, Mnanje 2009, Mangaka 2009 and Nachi 2015, are the main six improved groundnut varieties used by farmers, with Pendo 1998 having the highest adoption rate (17.1%). In the grain market, four varieties, namely Pendo 1998, Mnanje 2009, Nachi 2015 and Johari 1985, were observed to be highly preferred by grain off-takers. Furthermore, among the adopted improved varieties, Nachi 2015, is observed to be the most consistent high yielding variety, ranging from 1100 kg/ha to 1500 kg/ha in all agro-ecological zones. A farmer’s decision to adopt new varieties is affected by age and gender, farmer group membership, availability of improved seed and seed cost. Overall, male farmers are more likely to adopt improved varieties of groundnut than female farmers. The implications of these findings are also discussed, in particular in the area of policy support.

Description: This study presents an integrated examination of both the ecosystem services (ES) and ecosystem disservices (EDS) associated with smallholder animal husbandry in rural livelihoods in three villages in southeast South Africa. It recognises the contribution of ES supporting and resulting from smallholder livestock and poultry production, but also details the limiting factors or EDS, such as tick-borne disease, birds of prey or unpalatable rangeland, produced by the same system. Using a mixed-methods approach, including focus group discussions with various Participatory Learning and Action (PLA) activities, key informant interviews, household surveys and land-use change mapping on GIS, we consider the relative value and benefits from ES after the effects of EDS, as well as the management and strategies that households adopt to minimise EDS. The effects of ES and EDS were expressed in economic terms to provide a common framework to assess the magnitude of their contribution or effect. Although animal husbandry made measurable contributions to households, with an average gross value of between R2605–R9753 across villages, EDS undermined the meaningful production of livestock and poultry goods and services. The average EDS-induced economic loss in households was between R8289–R22,426 per annum. Despite active management, often at substantial cost to the household, EDS undermined the health of livestock which resulted in a loss of the animal or potential goods and services produced. We emphasise the need to recognise both the positive and negative contributions of ecosystems to identify the complex feedbacks between ES and EDS which interact to determine local ways of doing things.

Description: Species with wide geographical ranges exhibit specific adaptations to local climates, which may result in diverging responses among populations to changing conditions. Climate change has advanced spring phenology worldwide, but questions of whether and how the phenological responses to warming differ among individuals across the natural range of a species remain. We conducted two experiments in January and April 2019, and performed daily observations of the timings of bud break in 1-year-old seedlings of sugar maple (Acer saccharum Marshall) from 25 Canadian provenances at two thermal conditions (14/10 and 18/14 °C day/night temperature) in a controlled environment. Overall, bud break started 6 days from the beginning of the experiments and finished after 125 days. The earlier events were observed in seedlings originating from the colder sites. Bud break was delayed by 4.8 days per additional degree Celsius in the mean annual temperature at the origin site. Warming advanced the timing of bud break by 17–27 days in January and by 3–8 days in April. Similar advancements in bud break were observed among provenances under warming conditions, which rejected our hypothesis that sugar maple populations have different phenological responses to warming. Our findings confirm the differentiation in ecotypes for the process of bud break in sugar maple. In cases of homogenous spring warming across the native range of sugar maple, similar advancements in bud phenology can be expected in different populations.

Description: This case study from Stockholm County, Sweden, explores practitioners’ experiences of barriers and bridges in municipal planning practices to support actions for ecosystem services. This qualitative study is based on information gathered from a focus group, workshops, and semi-structured interviews, which aided in identifying key factors for integrating ecosystem services in municipal planning. We identified 10 key factors divided into three themes: (i) regulatory framework and political support, (ii) local organizational capacity, and (iii) local adaptation of tools and practices. In particular, the practitioners pointed to the need for the development of legal support and regulations for ecosystem services on the national and EU policy levels. Furthermore, the need for local capacity building and understanding of ecosystem services as well as increased regional support to enhance local knowledge exchange and learning was emphasized. Also, in a decentralized local governance system such as in Sweden, to fully implement ecosystem services in urban planning for sustainable development, locally adapted practical tools and monitoring procedures were considered important.

Description: Sugarcane is an important industrial crop because it is the major source of white sugar. It is also one of the crops for the alcohol and biofuel industries. Disease-causing organisms can significantly decrease the productivity of sugarcane plants and sugar quality. Among the disease-causing organisms, Colletotrichum falcatum Went causes the most significant economic loss (5–50%) in the sugarcane production due to red rot disease. This loss results in only 31% sugar recovery. It is reported that C. falcatum can kill sugarcane plants. Currently, there is no sustainable way of preventing red rot disease from spreading in sugarcane plantations. Many popular sugarcane varieties are no longer used in sugarcane cultivation because of their susceptibility to C. falcatum. The objectives of this manuscript were to: (i) summarize existing approaches for the early detection of red rot disease and controlling techniques of red rot disease in the field and laboratory and (ii) assess red rot disease control effectiveness so as to propose better methods for mitigating the spread C. falcatum. If our proposition is adopted or practiced, it could significantly contribute to the mitigation of C. falcatum infection in the sugarcane industry. This could enable achieving sustainable cultivation of sugarcanes to guarantee the sustainability of the sugar industry in the tropics and the subtropics.

Description: The transition from intensive conventional agriculture to sustainable agriculture has become a global priority. This is due to the need for environmentally friendly agriculture to ensure sufficient food for a rapidly growing population. The bioeconomy is essential to progress in the field of sustainable agriculture. It contributes to the conservation of biological resources through circular and comprehensive management. The bioeconomy prioritizes the reduction and reuse of materials and products. The focus of this study is the use of biodegradable/compostable raffia in protected horticultural crops in the Province of Almería (Spain). The analysis and evaluations, based on an extensive literature review and information given by stakeholders, determined that biodegradable raffia use significantly improves the management of residual biomass in Almería. However, biodegradable raffia is only used in a small percentage of crops even though it is a sustainable alternative and profitable for farmers. The economic analysis incorporates the higher cost of recycling non-biodegradable raffia.

Description: Sustainable agricultural production is endangered by several ecological factors, such as drought, extreme temperatures, excessive salts, parasitic ailments, and insect pest infestation. These challenging environmental factors may have adverse effects on future agriculture production in many countries. In modern agriculture, conventional crop-breeding techniques alone are inadequate for achieving the increasing population’s food demand on a sustainable basis. The advancement of molecular genetics and related technologies are promising tools for the selection of new crop species. Gene pyramiding through marker-assisted selection (MAS) and other techniques have accelerated the development of durable resistant/tolerant lines with high accuracy in the shortest period of time for agricultural sustainability. Gene stacking has not been fully utilized for biotic stress resistance development and quality improvement in most of the major cultivated crops. This review emphasizes on gene pyramiding techniques that are being successfully deployed in modern agriculture for improving crop tolerance to biotic and abiotic stresses for sustainable crop improvement.

Description: Upwelling and downwelling processes play a critical role in the connectivity between offshore waters and coastal ecosystems, having relevant implications in terms of intense biogeochemical activity and global fisheries production. A variety of in situ and remote-sensing networks were used in concert with the Iberia–Biscay–Ireland (IBI) circulation forecast system, in order to investigate two persistent upwelling and downwelling events that occurred in the Northwestern (NW) Iberian coastal system during summer 2014. Special emphasis was placed on quality-controlled surface currents provided by a high-frequency radar (HFR), since this land-based technology can effectively monitor the upper layer flow over broad coastal areas in near-real time. The low-frequency spatiotemporal response of the ocean was explored in terms of wind-induced currents’ structures and immediacy of reaction. Mean kinetic energy, divergence and vorticity maps were also calculated for upwelling and downwelling favorable events, in order to verify HFR and IBI capabilities, to accurately resolve the prevailing surface circulation features, such as the locus of a persistent upwelling maximum in the vicinity of Cape Finisterre. This integrated approach proved to be well-founded to efficiently portray the three-dimensional characteristics of the NW Iberian coastal upwelling system regardless of few shortcomings detected in IBI performance, such as the misrepresentation of the most energetic surface dynamics or the overestimation of the cooling and warming associated with upwelling and downwelling conditions, respectively. Finally, the variability of the NW Iberian upwelling system was characterized by means of the development of a novel ocean-based coastal upwelling index (UI), constructed from HFR-derived hourly surface current observations (UIHFR). The proposed UIHFR was validated against two traditional UIs for 2014, to assess its credibility. Results suggest that UIHFR was able to adequately categorize and characterize a wealth of summer upwelling and downwelling events of diverse length and strength, paving the way for future investigations of the subsequent biophysical implications.

Description: Research Highlights: The informed decisions on land use require assessment of the impacts of these decisions on the supply of different ecosystem services. Background and Objectives: Scenario modeling can be used to provide harmonized and quantitative information on the impacts of various zoning decisions on the provision of various ecosystem services. In this study, we explored the effects of land-use zoning decisions on the provision of roundwood and energy wood, carbon stock of living tree components, berry yields, scenic beauty and recreation. Materials and Methods: Three alternative forest scenarios were formulated in terms of restrictions on forest management for already established land-use zones by the provinces in Finland. These data were integrated with the National Forest Inventory (NFI) plot data for forest dynamics modeling. Results: In Finland, 9% of the forest land was protected and 9% was under restricted forest management due to legislative decisions, forest owners’ decisions, or regional land use plans in 2016. These established zoning decisions resulted in an estimated 17% smaller roundwood and energy wood removals per year in 2016–2025 compared to the estimated wood removals in the scenario without any restrictions. The decrease in annual gross stumpage earnings was EUR 775 million per year. The carbon stock of living tree components in 2025 was 12% larger than in the scenario without any restrictions. Bilberry yield increased due to the restrictions considered in our study, while the restrictions had only a slight effect on cowberry yield at province and country levels. The restrictions increased the recreation value, particularly in Lapland, but only slightly affected scenic beauty at province and country levels. Conclusions: Scenario analyses support informed decision making and the balancing of different forest uses. Harmonized translation of restrictions and the use of standard indicators to model the impacts also support comparisons between the regions.

Description: Shore-based phased-array HF radars have been widely used for remotely sensing ocean surface current, wave, and wind around the world. However, phase uncertainties, especially phase distortions, in receiving elements significantly degrade the performance of beam forming and direction-of-arrival (DOA) estimation for phased-array HF radar. To address this problem, the conventional array signal model is modified by adding a direction-based phase error matrix. Subsequently, an array phase manifold calibration method using antenna responses of incoming ship echoes is proposed. Later, an assessment on the proposed array calibration method is made based on the DOA estimations and current measurements that are obtained from the datasets that were collected with a multi-frequency HF (MHF) radar. MHF radar-estimated DOAs using three calibration strategies are compared with the ship directions that are provided by an Automatic Identification System (AIS). Additionally, comparisons between the MHF radar-derived currents while using three calibration strategies and Acoustic Doppler Current Profilers (ADCP)-measured currents are made. The results indicate that the proposed array calibration method is effective in DOA estimation and current measurement for phased-array HF radars, especially in the phase distortion situation.

Description: Many human activities are tactile. Recognizing how a person touches an object or a surface surrounding them is an active area of research and it has generated keen interest within the interactive surface community. In this paper, we compare two machine learning techniques, namely Artificial Neural Network (ANN) and Hidden Markov Models (HMM), as they are some of the most common techniques with low computational cost used to classify an acoustic-based input. We employ a small and low-cost hardware design composed of a microphone, a stethoscope, a conditioning circuit, and a microcontroller. Together with an appropriate surface, we integrated these components into a passive gesture recognition input system for experimental evaluation. To perform the evaluation, we acquire the signals using a small microphone and send it through the microcontroller to MATLAB’s toolboxes to implement and evaluate the ANN and HMM models. We also present the hardware and software implementation and discuss the advantages and limitations of these techniques in gesture recognition while using a simple alphabet of three geometrical figures: circle, square, and triangle. The results validate the robustness of the HMM technique that achieved a success rate of 90%, with a shorter training time than the ANN.

Description: In this study we (1) mapped the areal extent of current dust sources over Northern Africa between 8°W–31°E and 22°N - Mediterranean coast; and (2) identified and characterized the geomorphic units and soil types that emit dust from these areas. We used the full resolution (3 km) data from the MSG-SEVIRI to map dust sources over a 2-year period between 2005–2006, and examined these regions with remotely sensed images and geomorphic and soil maps. A total of 〉2600 individual dust emission events were mapped; with frequency up to 34 events in the 2-year study period. The areal extent of dust emission sources exhibited a lognormal distribution with most sources ranging from 20 to 130 km2. Most dust events were singular and related to a variety of specific geomorphic units. Dust events that created hotspots were mostly located over playas and fluvial landforms, and to a lesser extent over sand dunes and anthropogenic affected regions. About 20% of dust hotspots were offset a few kilometers from clear geomorphic units. Quantitative analysis of emissions revealed that dust sourced from various geomorphic units, among them playas (12%) and fluvial systems (10%). The importance of sand dunes as dust-emission sources greatly differs between examined datasets (7% vs. 30%). Our study emphasizes the importance of scattered dust emission events that are not considered as hotspots, as these sources are usually neglected in dust emission modeling.

Description: In recent years, field-effect transistors (FETs) have been very promising for biosensor applications due to their high sensitivity, real-time applicability, scalability, and prospect of integrating measurement system on a chip. Non-carbon 2D materials, such as transition metal dichalcogenides (TMDCs), hexagonal boron nitride (h-BN), black phosphorus (BP), and metal oxides, are a group of new materials that have a huge potential in FET biosensor applications. In this work, we review the recent advances and remarkable studies of non-carbon 2D materials, in terms of their structures, preparations, properties and FET biosensor applications. We will also discuss the challenges facing non-carbon 2D materials-FET biosensors and their future perspectives.

Description: In this study, dynamic hardness tests on solid and engineered wood flooring specimens of Eucalyptus globulus Labill. and Eucalyptus grandis W. Hill ex Maiden hardwoods were performed because nowadays, these fast-growing hardwoods are still scarcely employed for this use. Furthermore, another two examples of hardwood commonly applied on wood flooring, Quercus robur L. and Hymenaea courbaril L., were also tested. To compare their properties, a dynamic impact hardness test based on the impact of steel balls, with several diameters, and drop heights was developed. Accordingly, 120 solid wood flooring specimens and 120 engineering wood flooring specimens were producing with these four hardwood species. Dynamic impact tests were made with three steel balls of different diameters (30–40–50 mm), and they were carried out from five different drop heights (0.60–0.75–0.90–1.05–1.20 m). The impact of the steel ball drew the size of the footprint on the surface and this mark was measured with a digital caliper for both dimensions, diameter and depth, as footprint diameter (FD) and indentation depth (ID). Data from 3000 samples, corresponding to 120 different individual groups (4 species × 3 ball diameters × 5 drop height × 2 floor type) were analyzed. Results indicated that the variability of ID (CV between 19.25–25.61%) is much greater than the values achieved for FD (CV between 6.72–7.91%). Regarding the fast-growing hardwood species tested, E. globulus showed a similar behavior to traditional hardwood applied on wood flooring in Europe, Q. robur, and it could be a promising growth in the flooring industry. However, E. grandis showed the worst values compared to traditional hardwood in all test configurations.

Description: Siamese network-based trackers consider tracking as features cross-correlation between the target template and the search region. Therefore, feature representation plays an important role for constructing a high-performance tracker. However, all existing Siamese networks extract the deep but low-resolution features of the entire patch, which is not robust enough to estimate the target bounding box accurately. In this work, to address this issue, we propose a novel high-resolution Siamese network, which connects the high-to-low resolution convolution streams in parallel as well as repeatedly exchanges the information across resolutions to maintain high-resolution representations. The resulting representation is semantically richer and spatially more precise by a simple yet effective multi-scale feature fusion strategy. Moreover, we exploit attention mechanisms to learn object-aware masks for adaptive feature refinement, and use deformable convolution to handle complex geometric transformations. This makes the target more discriminative against distractors and background. Without bells and whistles, extensive experiments on popular tracking benchmarks containing OTB100, UAV123, VOT2018 and LaSOT demonstrate that the proposed tracker achieves state-of-the-art performance and runs in real time, confirming its efficiency and effectiveness.

Description: The Internet of Medical Things (IoMT) couples IoT technologies with healthcare services in order to support real-time, remote patient monitoring and treatment. However, the interconnectivity of critical medical devices with other systems in various network layers creates new opportunities for remote adversaries. Since most of the communication protocols have not been specifically designed for the needs of connected medical devices, there is a need to classify the available IoT communication technologies in terms of security. In this paper we classify IoT communication protocols, with respect to their application in IoMT. Then we describe the main characteristics of IoT communication protocols used at the perception, network and application layer of medical devices. We examine the inherent security characteristics and limitations of IoMT-specific communication protocols. Based on realistic attacks we identify available mitigation controls that may be applied to secure IoMT communications, as well as existing research and implementation gaps.

Description: Monitoring biomass of forages in experimental plots and livestock farms is a time-consuming, expensive, and biased task. Thus, non-destructive, accurate, precise, and quick phenotyping strategies for biomass yield are needed. To promote high-throughput phenotyping in forages, we propose and evaluate the use of deep learning-based methods and UAV (Unmanned Aerial Vehicle)-based RGB images to estimate the value of biomass yield by different genotypes of the forage grass species Panicum maximum Jacq. Experiments were conducted in the Brazilian Cerrado with 110 genotypes with three replications, totaling 330 plots. Two regression models based on Convolutional Neural Networks (CNNs) named AlexNet and ResNet18 were evaluated, and compared to VGGNet—adopted in previous work in the same thematic for other grass species. The predictions returned by the models reached a correlation of 0.88 and a mean absolute error of 12.98% using AlexNet considering pre-training and data augmentation. This proposal may contribute to forage biomass estimation in breeding populations and livestock areas, as well as to reduce the labor in the field.

Description: Highly controlled biomineralization of calcium carbonate is via non-classical mesocrystallization of amorphous precursors. In the present study, a simple in vitro assay was developed to mimic the biological process, which involved stabilized amorphous calcium carbonate and a single crystal substrate of calcite. The microcoating layer formed on the calcite substrate displayed mesocrystalline characteristics, and the layers near the substrate were strongly influenced by the epitaxy to the substrate. This behavior was preserved even when the morphology of the coating layer was modified with poly(acrylic acid), a model anionic macromolecule. Interestingly, the extent of the epitaxy increased substantially with poly(ethylene imine), which barely affected the crystal morphology. The in vitro assay in the present study will be useful in the investigations of the biomineralization and bioinspired crystallization of calcium carbonate in general.

Description: Bioelectrocatalysis provides the intrinsic catalytic functions of redox enzymes to nonspecific electrode reactions and is the most important and basic concept for electrochemical biosensors. This review starts by describing fundamental characteristics of bioelectrocatalytic reactions in mediated and direct electron transfer types from a theoretical viewpoint and summarizes amperometric biosensors based on multi-enzymatic cascades and for multianalyte detection. The review also introduces prospective aspects of two new concepts of biosensors: mass-transfer-controlled (pseudo)steady-state amperometry at microelectrodes with enhanced enzymatic activity without calibration curves and potentiometric coulometry at enzyme/mediator-immobilized biosensors for absolute determination.

Description: Physical rehabilitation therapies for children present a challenge, and its success—the improvement of the patient’s condition—depends on many factors, such as the patient’s attitude and motivation, the correct execution of the exercises prescribed by the specialist or his progressive recovery during the therapy. With the aim to increase the benefits of these therapies, social humanoid robots with a friendly aspect represent a promising tool not only to boost the interaction with the pediatric patient, but also to assist physicians in their work. To achieve both goals, it is essential to monitor in detail the patient’s condition, trying to generate user profile models which enhance the feedback with both the system and the specialist. This paper describes how the project NAOTherapist—a robotic architecture for rehabilitation with social robots—has been upgraded in order to include a monitoring system able to generate user profile models through the interaction with the patient, performing user-adapted therapies. Furthermore, the system has been improved by integrating a machine learning algorithm which recognizes the pose adopted by the patient and by adding a clinical reports generation system based on the QUEST metric.

Description: The Karlsruhe Tritium Neutrino (KATRIN) experiment aims at measuring the effective electron neutrino mass with a sensitivity of 0.2 eV/c2, i.e., improving on previous measurements by an order of magnitude. Neutrino mass data taking with KATRIN commenced in early 2019, and after only a few weeks of data recording, analysis of these data showed the success of KATRIN, improving on the known neutrino mass limit by a factor of about two. This success very much could be ascribed to the fact that most of the system components met, or even surpassed, the required specifications during long-term operation. Here, we report on the performance of the laser Raman (LARA) monitoring system which provides continuous high-precision information on the gas composition injected into the experiment’s windowless gaseous tritium source (WGTS), specifically on its isotopic purity of tritium—one of the key parameters required in the derivation of the electron neutrino mass. The concentrations cx for all six hydrogen isotopologues were monitored simultaneously, with a measurement precision for individual components of the order 10−3 or better throughout the complete KATRIN data taking campaigns to date. From these, the tritium purity, εT, is derived with precision of

Description: In this paper, we present a navigation strategy exclusively designed for social robots with limited sensors for applications in homes. The overall system integrates a reactive design based on subsumption architecture and a knowledge system with learning capabilities. The component of the system includes several modules, such as doorway detection and room localization via convolutional neural network (CNN), avoiding obstacles via reinforcement learning, passing the doorway via Canny edge’s detection, building an abstract map called a Directional Semantic Topological Map (DST-Map) within the knowledge system, and other predefined layers within the subsumption architecture. The individual modules and the overall system are evaluated in a virtual environment using Webots simulator.

Description: In multi-target tracking scenarios with dense and heterogeneous clutter, there is a substantial increase in the false measurements that originated from the clutter within the validation gate, and consequently, the number of measurement-to-track association hypothesis grows rapidly in traditional multiple hypothesis tracker (MHT), leading to a sharp decrease in data association accuracy and tracking performance. A new multiple hypothesis tracker using validation gate with motion direction constraint (MHT-MDC) is proposed to solve these problems. In the MHT-MDC, a motion direction constraint (MDC) gate is designed by considering the prior target maneuvering information, which effectively reduces the volume of validation gate and, thus, diminishes the number of false measurements in the gate when the innovation covariance is large. Subsequently, the clutter density in the MDC gate is adaptively estimated by the conditional mean estimator of clutter density (CMECD), based on which the score functions in the MDC gate can be calculated. The MHT-MDC is compared with the MHT algorithm in simulations, and the experimental results demonstrate its superior tracking performance for weakly maneuvering targets in high clutter density scenarios.

Description: Over the last decade, video surveillance systems have become a part of the Internet of Things (IoT). These IP-based surveillance systems now protect industrial facilities, railways, gas stations, and even one’s own home. Unfortunately, like other IoT systems, there are inherent security risks which can lead to significant violations of a user’s privacy. In this review, we explore the attack surface of modern surveillance systems and enumerate the various ways they can be compromised with real examples. We also identify the threat agents, their attack goals, attack vectors, and the resulting consequences of successful attacks. Finally, we present current countermeasures and best practices and discuss the threat horizon. The purpose of this review is to provide researchers and engineers with a better understanding of a modern surveillance systems’ security, to harden existing systems and develop improved security solutions.

Description: Ti6Al4V alloy is still attracting great interest because of its application as an implant material for hard tissue repair. This research aims to produce and investigate in-situ chitosan/hydroxyapatite (CS/HA) nanocomposite coatings based on different amounts of HA (10, 50 and 60 wt.%) on alkali-treated Ti6Al4V substrate through the sol-gel process to enhance in vitro bioactivity. The influence of different contents of HA on the morphology, contact angle, roughness, adhesion strength, and in vitro bioactivity of the CS/HA coatings was studied. Results confirmed that, with increasing the HA content, the surface morphology of crack-free CS/HA coatings changed for nucleation modification and HA nanocrystals growth, and consequently, the surface roughness of the coatings increased. Furthermore, the bioactivity of the CS/HA nanocomposite coatings enhanced bone-like apatite layer formation on the material surface with increasing HA content. Moreover, CS/HA nanocomposite coatings were biocompatible and, in particular, CS/10 wt.% HA composition significantly promoted human mesenchymal stem cells (hMSCs) proliferation. In particular, these results demonstrate that the treatment strategy used during the bioprocess was able to improve in vitro properties enough to meet the clinical performance. Indeed, it is predicted that the dense and crack-free CS/HA nanocomposite coatings suggest good potential application as dental implants.

Description: Surface all-wave net radiation (Rn) is a crucial variable driving many terrestrial latent heat (LE) models that estimate global LE. However, the differences between different Rn products and their impact on global LE estimates still remain unclear. In this study, we evaluated two Rn products, Global LAnd Surface Satellite (GLASS) beta version Rn and Modern-Era Retrospective Analysis for Research and Applications-version 2 (MERRA-2) Rn, from 2007–2017 using ground-measured data from 240 globally distributed in-situ radiation measurements provided by FLUXNET projects. The GLASS Rn product had higher accuracy (R2 increased by 0.04–0.26, and RMSE decreased by 2–13.3 W/m2) than the MERRA-2 Rn product for all land cover types on a daily scale, and the two Rn products differed greatly in spatial distribution and variations. We then determined the resulting discrepancies in simulated annual global LE using a simple averaging model by merging five diagnostic LE models: RS-PM model, SW model, PT-JPL model, MS-PT model, and SIM model. The validation results showed that the estimated LE from the GLASS Rn had higher accuracy (R2 increased by 0.04–0.14, and RMSE decreased by 3–8.4 W/m2) than that from the MERRA-2 Rn for different land cover types at daily scale. Importantly, the mean annual global terrestrial LE from GLASS Rn was 2.1% lower than that from the MERRA-2 Rn. Our study showed that large differences in satellite and reanalysis Rn products could lead to substantial uncertainties in estimating global terrestrial LE.

Description: The work investigates the application of artificial neural networks and logistic regression for the recognition of activities performed by room occupants. KNX (Konnex) standard-based devices were selected for smart home automation and data collection. The obtained data from these devices (Humidity, CO2, temperature) were used in combination with two wearable gadgets to classify specific activities performed by the room occupant. The obtained classifications can benefit the occupant by monitoring the wellbeing of elderly residents and providing optimal air quality and temperature by utilizing heating, ventilation, and air conditioning control. The obtained results yield accurate classification.

Description: This paper presents the studies of the development of a high-performance epoxy coating for steel substrates. To this end, it investigated the synergistic effect of incorporating zinc oxide (ZnO) nanoparticles into nanosilica containing epoxy formulations. The mechanical properties of the epoxy coating formulations were improved by modifying the surfaces of the silica nanoparticles (5 wt.%) with 3-glycidoxypropyl trimethoxysilane, which ensured their dispersal through the material. Next, the ZnO nanoparticles (1, 2, or 3 wt.%) were incorporated to improve the corrosion performance of the formulations. The anticorrosive properties of the coatings were examined by electrochemical impedance spectroscopy (EIS) of coated mild steel specimens immersed in 3.5% NaCl solution over different time intervals (1 h to 30 days). Incorporation of the ZnO nanoparticles and the nanosilica into the coating formulation improved the corrosion resistance of the epoxy coating even after long-term exposure to saline test solutions. Finally, to evaluate how the nanoparticles affected the chemical and morphological properties of the prepared coatings, the coatings were characterized by scanning electron microscopy (SEM), Fourier transform infrared (FTIR) spectroscopy, and X-ray diffraction (XRD).

Description: The aim of the study was to evaluate the changes in glomalin-related soil proteins (GRSP) content, microbial diversity and soil physical quality depending on the type of soil measures of soil improvement and changes in soil health. The study was based on a 100-year stationary field microplot experiment where the soil profiles were collected with preserving the natural soil horizons. The microplot experiment was carried out on eight different soil types: Brunic Arenosol (Dystric I), Rendzic Leptosol, Fluvic Cambisol, Haplic Cambisol (Eutric), Gleyic Phaeozem, Brunic Arenosol (Dystric II), Haplic Cambisol (Eutric II) and Haplic Cambisol (Dystric). These soils are the most common types of agricultural soils in Poland. Relatively significant correlations with the soil quality, physical parameters and the glomalin-related soil proteins have been found. The study determined the total GRSP (T-GRSP) and easily extractable GRSP (EE-GRSP) levels in soils as well as the soil physical quality index and soil’s microbial biodiversity. The GRSP depended on the type of soil and correlated with S-Index and also was responsible for the unique chemical and physical properties of soils. Soils characterized by the highest T-GRSP content belonged to the group of very good and good soil physical quality characterized also by high biological activity, for which there were strong correlations with such parameters as dehydrogenase activity (DHA), microbial biomass content (MBC), microbial nitrogen content (MBN) and total bacteria number (B). The highest T-GRSP content and higher microbial diversity were found in Gleyic Phaeozem, Rendzic Leptosol and Fluvic Cambisol. The T-GRSP and EE-GRSP content were additionally correlated with the number of AMF spores. Very poor and poor soil physical quality according to S-Index characterized Brunic Arenosol (Dystric I) and Haplic Cambisol (Dystric). This research indicates that a specific edaphone of soil microorganisms and GRSP content may be of great importance when assessing a soil’s quality and improvements in soil health. The abundance of glomalin-producing fungi significantly affects the quality of the soil. This effect is particularly important for agricultural soils are threatened by ongoing land degradation.

Description: In the present paper, the identification of the material parameters of a masonry lighthouse is discussed. A fully non-invasive method was selected, in which the material properties were determined via numerical model validation applied to the first pair of natural frequencies and their related mode shapes, determined experimentally. The exact structural model was built by means of the finite element method. To obtain experimental data for the inverse analysis, operational modal analysis was applied to the structure. Three methods were considered: peak picking (PP), eigensystem realization algorithm (ERA) and natural excitation technique with ERA (NExT-ERA). The acceleration’s responses to environmental excitations, enhanced in some periods of time by sheet piling hammering or by sudden interruptions like wind stroke, were assumed within the analysis input. Different combinations of the input were considered in the PP and NExT-ERA analysis to find the most reasonable modal forms. A number of time periods of a free-decay character were considered in the ERA technique to finally calculate the averaged modal forms. Finally, the elastic modulus, Poisson’s ratio and material density of brick, sandstone and granite masonry were determined. The obtained values supplement the state of the art database concerning historic building materials. In addition, the numerical model obtained in the analysis may be used in further cases of structural analysis.

Description: Land-based sources are the key sources of plastic debris, and mismanaged plastic debris can eventually enter the ocean via marine beaches. In this study, the spatial distribution and amount of plastic debris in the land-based source input zone of First Long Beach (FLB), China, which is a major tourist attraction, were first investigated. By using field investigation, sand samples were collected from two sections on FLB adjacent to land-based sources in December 2019, and the plastic debris in the sand samples was quantified and characterized in the laboratory. The amount of plastic debris ranged from 2 to 82 particles/m2 on this marine sand beach. There was a significant difference in plastic debris amount between the transects along the land-based source input zone (p 〈 0.05) due to the impacts of wind, ocean currents, and waves. The most abundant size of plastics was 0.5–2.5 cm (44.4%). Moreover, the most common color was white (60.9%). The most abundant shape of plastic debris fell into the fragment category (76.2%). The plastic debris amounts were significantly correlated with multiple sizes. Our results show that land-based wastewater discharge is a large plastic debris source on FLB under coastal water tide variation. Reduction strategies should be carried out by tracing the various land-based sources of plastic debris.

Description: Detection of terrain features (ridges, spurs, cliffs, and peaks) is a basic research topic in digital elevation model (DEM) analysis and is essential for learning about factors that influence terrain surfaces, such as geologic structures and geomorphologic processes. Detection of terrain features based on general geomorphometry is challenging and has a high degree of uncertainty, mostly due to a variety of controlling factors on surface evolution in different regions. Currently, there are different computational techniques for obtaining detailed information about terrain features using DEM analysis. One of the most common techniques is numerically identifying or classifying terrain elements where regional topologies of the land surface are constructed by using DEMs or by combining derivatives of DEM. The main drawbacks of these techniques are that they cannot differentiate between ridges, spurs, and cliffs, or result in a high degree of false positives when detecting spur lines. In this paper, we propose a new method for automatically detecting terrain features such as ridges, spurs, cliffs, and peaks, using shaded relief by controlling altitude and azimuth of illumination sources on both smooth and rough surfaces. In our proposed method, we use edge detection filters based on azimuth angle on shaded relief to identify specific terrain features. Results show that the proposed method performs similar to or in some cases better (when detecting spurs than current terrain features detection methods, such as geomorphon, curvature, and probabilistic methods.

Description: The shipborne high-frequency surface wave radar (HFSWR) platform produces six degrees of freedom (DOF) motion at sea, which affects the performance of radar target detection and remote sensing of ocean surface dynamics parameters. Motion compensation can mitigate the effect of six-DOF motion, but motion parameters (including amplitude and angular frequency) need to be known. Motion parameters obtained by using high precision sensors are affected by the precision error and time delay, thus affecting the effect of motion compensation. To obtain the motion parameters accurately and in real time, a method of identifying the motion parameters by using an artificially transmitted reference radio frequency (RF) signal generated at the shore is proposed. Based on the results of the parameter identification, the reference RF signal and the first-order radar cross-sections (RCSs) modulated by six-DOF motion of the shipborne HFSWR platform can be compensated. The identification of angular frequency is divided into two steps: (1) Preliminary identification results are obtained by using the reference RF signal; (2) the pattern search method is used to further improve the identification accuracy of angular frequency. The amplitude of translation (including surge and sway) can be identified accurately through the reference RF signal. Due to the small amplitude of rotation (including roll, pitch, and yaw), it needs to be identified by the reference RF signal and pattern search method. After identifying the motion parameters, division in the time domain is used for motion compensation. Through the simulation results, both translation and rotation have good motion compensation effects. In addition, the method of using high precision sensors to obtain motion parameters and compensation is compared with the method in this paper, the simulation results of motion compensation show that the latter is better.

Description: Some special conditions are important for chemical syntheses, such as high temperature and the medium used; unfortunately, uncontrollable influences are introduced during the process, resulting in unexpectedly low repeatability. Herein, we report a facile, environmentally friendly, stable, and repeatable methodology for synthesizing silver nanoplates (SNPs) at 0 °C that overcomes these issues and dramatically increases the yield. This method mainly employs sodium dodecyl sulfate (SDS) and sodium alginate (SA) as the surface stabilizer and assistant, respectively. Consequently, we produced hexagonal nanoplates and tailed nanoplates, and the characterization showed that SA dominates the clear and regular profiles of nanoplates at 0 °C. The tailed nanoplates, over time, showed the growth of heads and the dissolving of tails, and inclined to the nanoplates without tails. The synthesis method for SNPs used in this study—0 °C without media—showed high repeatability. We confirmed that these special conditions are not required for the synthesis of silver nanostructures (SNSs). Furthermore, we constructed a new method for preparing noble metal nanostructures and proved the possibility of preparing metal nanostructures at 0 °C.

Description: The information of building types is highly needed for urban planning and management, especially in high resolution building modeling in which buildings are the basic spatial unit. However, in many parts of the world, this information is still missing. In this paper, we proposed a framework to derive the information of building type using geospatial data, including point-of-interest (POI) data, building footprints, land use polygons, and roads, from Gaode and Baidu Maps. First, we used natural language processing (NLP)-based approaches (i.e., text similarity measurement and topic modeling) to automatically reclassify POI categories into which can be used to directly infer building types. Second, based on the relationship between building footprints and POIs, we identified building types using two indicators of type ratio and area ratio. The proposed framework was tested using over 440,000 building footprints in Beijing, China. Our NLP-based approaches and building type identification methods show overall accuracies of 89.0% and 78.2%, and kappa coefficient of 0.83 and 0.71, respectively. The proposed framework is transferrable to other China cities for deriving the information of building types from web mapping platforms. The data products generated from this study are of great use for quantitative urban studies at the building level.

Description: Eucalyptus grandis and E. dunnii have high productive potential in the South of Brazil, Uruguay, and central Argentina. This is based on the similarity of the climate and soil of these areas, which form an eco-region called Campos. However, previous results show that these species have differences in their distribution caused by the prioritization of Uruguayan soils for forestry, explained by the particular conditions of each site. In this study, the site variables (climate, soil, and topography) that better explain the distribution of both species were identified, and prediction models of current and future distribution were adjusted for different climate change scenarios (years 2050 and 2070). The distribution of E. grandis was associated with soil parameters, whereas for E. dunnii a greater effect of the climatic variables was observed. The ensemble biomod2 model was the most precise with regard to predicting the habitat for both species with respect to the simple models evaluated. For E. dunnii, the average values of the AUC, Kappa, and TSS index were 0.98, 0.88, and 0.77, respectively. For E. grandis, their values were 0.97, 0.86, and 0.80, respectively. In the projections of climatic change, the distribution of E. grandis occurrence remains practically unchanged, even in the scenarios of temperature increase. However, current distribution of E. dunnii shows high susceptibility in a scenario of increased temperature, to the point that most of the area currently planted may be at risk. Our results might be useful to political government and foresters for decision making in terms of future planted areas.

Description: This research group has recently used the new technology Distributed Acoustic Sensing (DAS) for the monitoring and the measurement of airplane flutter. To the authors’ knowledge, this is the first such use for this new technology. Traditionally, the measurement of airplane flutter requires the mounting of a very large number of sensors on the wing being monitored, and extensive wiring must be connected to all these sensors. The new system and technology introduced in this paper dramatically reduces the hardware requirements in such an application: all the traditional sensors and wiring are replaced with one fiber optic cable with a diameter of 2 mm. An electro-optical system with the size of a desktop PC monitors simultaneously one or more of such fiber optic cables and detects/characterizes any mechanical disturbances on the cables. Theoretical and experimental results are given.

Description: Landscape connectivity is increasingly promoted as a conservation tool to combat the negative effects of habitat loss, fragmentation, and climate change. Given its importance as a key conservation strategy, connectivity science is a rapidly growing discipline. However, most landscape connectivity models consider connectivity for only a single snapshot in time, despite the widespread recognition that landscapes and ecological processes are dynamic. In this paper, we discuss the emergence of dynamic connectivity and the importance of including dynamism in connectivity models and assessments. We outline dynamic processes for both structural and functional connectivity at multiple spatiotemporal scales and provide examples of modeling approaches at each of these scales. We highlight the unique challenges that accompany the adoption of dynamic connectivity for conservation management and planning in the context of traditional conservation prioritization approaches. With the increased availability of time series and species movement data, computational capacity, and an expanding number of empirical examples in the literature, incorporating dynamic processes into connectivity models is more feasible than ever. Here, we articulate how dynamism is an intrinsic component of connectivity and integral to the future of connectivity science.

Description: Despite the potential implications of a cropland canopy water content (CCWC) thematic product, no global remotely sensed CCWC product is currently generated. The successful launch of the Landsat-8 Operational Land Imager (OLI) in 2012, Sentinel-2A Multispectral Instrument (MSI) in 2015, followed by Sentinel-2B in 2017, make possible the opportunity for CCWC estimation at a spatial and temporal scale that can meet the demands of potential operational users. In this study, we designed and tested a novel radiative transfer model (RTM) inversion technique to combine multiple sources of a priori data in a look-up table (LUT) for inverting the NASA Harmonized Landsat Sentinel-2 (HLS) product for CCWC estimation. This study directly builds on previous research for testing the constraint of the leaf parameter (Ns) in PROSPECT, by applying those constraints in PRO4SAIL in an agricultural setting where the variability of canopy parameters are relatively minimal. In total, 225 independent leaf measurements were used to train the LUTs, and 102 field data points were collected over the 2015–2017 growing seasons for validating the inversions. The results confirm increasing a priori information and regularization yielded the best performance for CCWC estimation. Despite the relatively low variable canopy conditions, the inclusion of Ns constraints did not improve the LUT inversion. Finally, the inversion of Sentinel-2 data outperformed the inversion of Landsat-8 in the HLS product. The method demonstrated ability for HLS inversion for CCWC estimation, resulting in the first HLS-based CCWC product generated through RTM inversion.

Description: The intrinsic heterogeneity property of concrete causes strong multiple scatterings during wave propagation, forming coda wave that follows very complex trajectories. As a superposition of multiply scattered waves, coda wave shows great sensitivity to subtle changes, but meanwhile lose spatial resolution. To make use of its sensitivity and turn the limitation into advantage, this paper presents an experimental study of three-dimensionally imaging local changes in concrete by application of inverse algorithms to coda wave measurements. Load tests are performed on a large reinforced concrete beam that contains multiple pre-existing millimeter-scale cracks in order to match real life situation. The joint effects of cracks and stresses on coda waves have been monitored using a network of fixed transducers placed at the surface. The global waveform decorrelations and velocity variations are firstly quantified through coda wave interferometry technique. Subsequently, two inverse algorithms are independently applied to map the densities of changes at each localized position. Using this methodology, the stress changes and subtle cracks in the concrete beam are detected and imaged for both temporal and spatial domains.

Description: The technological growth and accessibility of Unoccupied Aerial Systems (UAS) have revolutionized the way geographic data are collected. Digital Surface Models (DSMs) are an integral component of geospatial analyses and are now easily produced at a high resolution from UAS images and photogrammetric software. Systematic testing is required to understand the strengths and weaknesses of DSMs produced from various UAS. Thus, in this study, we used photogrammetry to create DSMs using four UAS (DJI Inspire 1, DJI Phantom 4 Pro, DJI Mavic Pro, and DJI Matrice 210) to test the overall accuracy of DSM outputs across a mixed land cover study area. The accuracy and spatial variability of these DSMs were determined by comparing them to (1) 12 high-precision GPS targets (checkpoints) in the field, and (2) a DSM created from Light Detection and Ranging (LiDAR) (Velodyne VLP-16 Puck Lite) on a fifth UAS, a DJI Matrice 600 Pro. Data were collected on July 20, 2018 over a site with mixed land cover near Middleton, NS, Canada. The study site comprised an area of eight hectares (~20 acres) with land cover types including forest, vines, dirt road, bare soil, long grass, and mowed grass. The LiDAR point cloud was used to create a 0.10 m DSM which had an overall Root Mean Square Error (RMSE) accuracy of ±0.04 m compared to 12 checkpoints spread throughout the study area. UAS were flown three times each and DSMs were created with the use of Ground Control Points (GCPs), also at 0.10 m resolution. The overall RMSE values of UAS DSMs ranged from ±0.03 to ±0.06 m compared to 12 checkpoints. Next, DSMs of Difference (DoDs) compared UAS DSMs to the LiDAR DSM, with results ranging from ±1.97 m to ±2.09 m overall. Upon further investigation over respective land covers, high discrepancies occurred over vegetated terrain and in areas outside the extent of GCPs. This indicated LiDAR’s superiority in mapping complex vegetation surfaces and stressed the importance of a complete GCP network spanning the entirety of the study area. While UAS DSMs and LiDAR DSM were of comparable high quality when evaluated based on checkpoints, further examination of the DoDs exposed critical discrepancies across the study site, namely in vegetated areas. Each of the four test UAS performed consistently well, with P4P as the clear front runner in overall ranking.

Description: The heat-exchanger/reactor (HEX reactor) is a kind of plug-flow chemical reactor which combines high heat transfer ability with good chemical performances. It was designed under the popular trend of process intensification in chemical engineering. Previous studies have investigated its characteristics and developed its nominal model. This paper is concerned with its fault tolerant control (FTC) applications. To avoid the difficulties and nonlinearities of this HEX reactor under chemical reactions, a two-layer, multiple-model structure is proposed for designing the FTC scheme. The first layer focuses on representing the nonlinear system with a bank of local linear models while the second layer uses model banks for approaching faulty situations. Model banks are achieved by system identification, and the corresponding controller banks are designed using model predictive control (MPC). The unscented Kalman filter (UKF) is introduced to estimate the states and form the fault detection and isolation (FDI) section. Finally, the FTC simulation and validation results are presented. The idea of a two-layer, multiple-model structure presents a general framework for FTC design of complex and highly nonlinear systems, such as the HEX reactor, whose mathematical model has been created. It implements the design process in an unusual way and is also worth trying on other cases.

Description: Although compacted soil can be recovered through root development of planted seedlings, the relationship between root morphologies and soil physical properties remain unclear. We investigated the impacts of soil compaction on planted hybrid larch F1 (Larix gmelinii var. japonica×L. kaempferi, hereafter F1) seedlings with/without N loading. We assumed that N loading might increase the fine root proportion of F1 seedlings under soil compaction, resulting in less effects of root development on soil recovery. We established experimental site with different levels of soil compaction and N loading, where two-year-old F1 seedlings were planted. We used a hardness change index (HCI) to quantify a degree of soil hardness change at each depth. We evaluated root morphological responses to soil compaction and N loading, focusing on ectomycorrhizal symbiosis. High soil hardness reduced the total dry mass of F1 seedlings by more than 30%. Significant positive correlations were found between HCI and root proportion, which indicated that F1 seedling could enhance soil recovery via root development. The reduction of fine root density and its proportion due to soil compaction was observed, while these responses were contrasting under N loading. Nevertheless, the relationships between HCI and root proportion were not changed by N loading. The relative abundance of the larch-specific ectomycorrhizal fungi under soil compaction was increased by N loading. We concluded that the root development of F1 seedling accelerates soil recovery, where N loading could induce root morphological changes under soil compaction, resulting in the persistent relationship between root development and soil recovery.

Description: Leaf rust (LR) and stem rust (SR) pose serious challenges to wheat production in Kazakhstan. In recent years, the susceptibility of local wheat cultivars has substantially decreased grain yield and quality. Therefore, local breeding projects must be adjusted toward the improvement of LR and SR disease resistances, including genetic approaches. In this study, a spring wheat segregating population of Pamyati Azieva (PA) × Paragon (Par), consisting of 98 recombinant inbred lines (RILs), was analyzed for the resistance to LR and SR at the seedling and adult plant-growth stages. In total, 24 quantitative trait loci (QTLs) for resistance to rust diseases at the seedling and adult plant stages were identified, including 11 QTLs for LR and 13 QTLs for SR resistances. Fourteen QTLs were in similar locations to QTLs and major genes detected in previous linkage mapping and genome-wide association studies. The remaining 10 QTLs are potentially new genetic factors for LR and SR resistance in wheat. Overall, the QTLs revealed in this study may play an important role in the improvement of wheat resistance to LR and SR per the marker-assisted selection approach.

Description: Radar images suffer from the impact of sidelobes. Several sidelobe-suppressing methods including the convolutional neural network (CNN)-based one has been proposed. However, the point spread function (PSF) in the radar images is sometimes spatially variant and affects the performance of the CNN. We propose the spatial-variant convolutional neural network (SV-CNN) aimed at this problem. It will also perform well in other conditions when there are spatially variant features. The convolutional kernels of the CNN can detect motifs with some distinctive features and are invariant to the local position of the motifs. This makes the convolutional neural networks widely used in image processing fields such as image recognition, handwriting recognition, image super-resolution, and semantic segmentation. They also perform well in radar image enhancement. However, the local position invariant character might not be good for radar image enhancement, when features of motifs (also known as the point spread function in the radar imaging field) vary with the positions. In this paper, we proposed an SV-CNN with spatial-variant convolution kernels (SV-CK). Its function is illustrated through a special application of enhancing the radar images. After being trained using radar images with position-codings as the samples, the SV-CNN can enhance the radar images. Because the SV-CNN reads information of the local position contained in the position-coding, it performs better than the conventional CNN. The advance of the proposed SV-CNN is tested using both simulated and real radar images.

Description: The range of applications of electromyography-based gesture recognition has increased over the last years. A common problem regularly encountered in literature is the inadequate data availability. Data augmentation, which aims at generating new synthetic data from the existing ones, is the most common approach to deal with this data shortage in other research domains. In the case of surface electromyography (sEMG) signals, there is limited research in augmentation methods and quite regularly the results differ between available studies. In this work, we provide a detailed evaluation of existing (i.e., additive noise, overlapping windows) and novel (i.e., magnitude warping, wavelet decomposition, synthetic sEMG models) strategies of data augmentation for electromyography signals. A set of metrics (i.e., classification accuracy, silhouette score, and Davies–Bouldin index) and visualizations help with the assessment and provides insights about their performance. Methods like signal magnitude warping and wavelet decomposition yield considerable increase (up to 16%) in classification accuracy across two benchmark datasets. Particularly, a significant improvement of 1% in the classification accuracy of the state-of-the-art model in hand gesture recognition is achieved.

Description: Chili pepper (Capsicum spp.) is one of the most economically important horticultural crops in the world; its production for the food and pharmaceutical industries has been increasing worldwide. The economic importance of this crop is due, in part, to the nutraceutical properties derived from its secondary metabolism. Drought is the main environmental factor that affects crop production. Nevertheless, studies involving water deficit have considered short-term responses to sharp water deficit rather than long-term acclimation processes through moderate and gradually increasing water deficits, which omitted the dynamics and profile of the secondary metabolism that are part of the plant’s defence system against this stress factor. The present study aimed to identify the different mechanisms that chili pepper plants use to cope with drought stress using a progressive decrease and increase of water availability, conditions that commonly occur for crops in open fields. Four treatments were applied as follows: gradual water deficit (GWD), initial waterlogging with gradual water deficit (IWGD), sudden water deficit with gradual recovery (SWDR), and no deficit of water (NDW). These conditions should represent a more real situation similar to that faced by plants in the agricultural environment. In order to evaluate the response mechanisms associated with these water deficits, changes in phenological variables, proline accumulation, and the gene expression of phenylalanine ammonia-lyase (PAL), chalcone synthase (CHS), peroxidase (POD), and superoxide dismutase (SOD) were measured in chili pepper plants growing on land under different irrigation regimes in two contrasting soil types in areas where chili pepper plants are cultivated in central Mexico. The variables evaluated showed a differentiated response of the mechanisms in plants growing under different levels of water deficit. Given the differential response observed for the gene expression and morphological and biochemical variables studied in chili pepper plants against different water regimes, in this work, this may have implications for more efficient use of water in crops with high nutraceutical content, in addition to prospects for using products derived from secondary metabolism in the pharmaceutical industry.

Description: Climate change has the potential to disrupt ecosystem services and further exacerbate the effects of human activities on natural resources. This has significant implications for educational institutions and the populations they serve. As the current crop of landscape architecture students struggles to define its role within the climate crisis and its related social and political underpinnings, a core mission of colleges and universities moving forward should be to provide students with applied knowledge about how climate change affects the landscape. This goes beyond coursework in climate science or policy; for landscape architecture students to be leaders in the response to climate change, they need applied, practical skills. An ever-growing body of the literature focuses on landscape design strategies for climate change adaptation; however, few frameworks integrate these strategies with the hands-on experience students will need to face real-world challenges after graduation. Educational institutions have the potential to utilize their campuses as demonstration sites for applied ecosystem research programs and actively engage students with the design, implementation, politics, and ongoing stewardship of these landscapes. This paper uses a case study methodology to understand how experiential and public-engaged learning pedagogies contribute to student preparedness to address climate change. It examines three cases of engaged learning at the University of California, Davis campus and attributes their impact to intentional connections with research, to the delegation of responsibility; to the openness of spaces for experimentation, and to self-reflection that connects climate with everyday behavior. By promoting experiential learning programs that require students to actively use their heads and their hands to construct and sustainably manage their own campus landscapes, service-learning studios and internships can provide opportunities for students to address the real scenarios of climate crisis and resilience.

Description: Emotion recognition has been gaining attention in recent years due to its applications on artificial agents. To achieve a good performance with this task, much research has been conducted on the multi-modality emotion recognition model for leveraging the different strengths of each modality. However, a research question remains: what exactly is the most appropriate way to fuse the information from different modalities? In this paper, we proposed audio sample augmentation and an emotion-oriented encoder-decoder to improve the performance of emotion recognition and discussed an inter-modality, decision-level fusion method based on a graph attention network (GAT). Compared to the baseline, our model improved the weighted average F1-scores from 64.18 to 68.31% and the weighted average accuracy from 65.25 to 69.88%.

Description: The objective of our research is to improve the properties of calcium-sulphate hemihydrate parts printed by binder jetting. In this paper, we show the thermal treatment results when using temperature time ramps on binder-jetted ceramic parts without infiltrating. The results show that the mechanical properties of printed parts are improved substantially. Two different thermal cycles were investigated for their effect on the dehydration process of CaSO4·½H2O using infrared analysis. The thermal-treated samples were compared with respect to porosity, surface roughness, compression strength and dimensional and weight variation. The proposed thermal treatment significantly improves the compression strength in a short time, guaranteeing dimensional stability while providing a good surface. This improvement in mechanical properties offers a great chance for using binder-jetted parts as functional components, for example, in the casting field or the medical sector (scaffolds).

Description: In this paper we document the design, development, results, performance and field applications of a compact directive transmit antenna for the long-range High Frequency ocean RADAR (HFR) systems operating in the International Telecommunication Union (ITU) designated 4MHz and 5MHz radiodetermination bands. The antenna design is based on the combination of the concepts of an electrically small loop with that of travelling wave antenna. This has the effect of inducing a radiated wave predominantly in a direction opposed to that of energy flow on the antenna structures. We demonstrate here that travelling wave design allows for a more compact antenna than other directive options, it has straightforward feed-point matching arrangements, and a flat frequency and phase response over an entire radiodetermination band. In situ measurements of the antenna radiation pattern, obtained with the aid of a drone, correlate well with those obtained from simulations, and show between 8dB and 30dB front-to-back suppression, with a 3dB beam width in the forward lobe of 100∘ or more. The broad-beam radiation pattern ensures proper illumination over the ocean and the significant front-to-back suppression guarantees reduced interference to terrestrial services. The proposed antenna design is compact and straight forward and can be easily deployed by minimal modifications of an existing transmission antenna. The design may be readily adapted to different environments due to the relative insensitivity of its radiation pattern and frequency response to geometric detail. The only downside to these antennas is their relatively low radiation efficiency which, however, may easily be compensated for by the available power output of a typical HFR transmitter. Antennas based on this design are currently deployed at the SeaSonde HFR sites in New South Wales, Australia, with operational ranges up to 200 km offshore despite their low radiating efficiency and the extremely low output power in use at these installations. Due to their directional pattern, it is also planned to test these antennas in phased-array Wellen RADAR (WERA) systems in both the standard receive arrays: where in-band radio frequency noise of terrestrial origin is impacting on data quality, and in the transmit array: to possibly simplify splitting, phasing and tuning requirements.

Description: Supraglacial liquid water at the margins of ice sheets has an important impact on the surface energy balance and can also influence the ice flow when supraglacial lakes drain to the bed. Optical imagery is able to monitor supraglacial lakes during the summer season. Here we developed an alternative method using polarimetric SAR from Sentinel-1 during 2017–2020 to distinguish between liquid water and other surface types at the margin of the Northeast Greenland Ice Stream. This allows the supraglacial hydrology to be monitored during the winter months too. We found that the majority of supraglacial lakes persist over winter. When comparing our results to optical data, we found significantly more water. Even during summer, many lakes are partly or fully covered by a lid of ice and snow. We used our classification results to automatically map the outlines of supraglacial lakes, create time series of water area for each lake, and hence detect drainage events. We even found several winter time drainages, which might have an important effect on ice flow. Our method has problems during the peak of the melt season, but for the rest of the year it provides crucial information for better understanding the component of supraglacial hydrology in the glaciological system.

Description: As the use of continuous fiber polymer matrix composites expands into new fields, there is a growing need for more sustainable manufacturing processes. An integrated computational material design framework has been developed, which enables the design of tailored manufacturing systems for polymer matrix composite materials as a sustainable alternative to achieving high-quality components in high-rate production. Trapped rubber processing achieves high pressures during polymer matrix composite processing, utilizing the thermally induced volume change of a nearly incompressible material inside a closed cavity mold. In this interdisciplinary study, the structural analysis, material science and manufacturing engineering perspectives are all combined to determine the mold mechanics, and the manufacturing process in a cohesive and iterative design loop. This study performs the coupled thermo-mechanical analysis required to simulate the transients involved in composite manufacturing and the results are compared with a previously developed test method. The internal surface pressure and temperatures are computed, compared with the experimental results, and the resulting design process is simulated. Overall, this approach maintains high-quality consolidation during curing while allowing for the possibility for custom distributions of pressures and temperatures. This can lead to more sustainable manufacturing by reducing energy consumption and improving throughput.

Description: The aim of this study was to investigate the impact of distributed propulsion systems used on inland and coastal navigation in shallow water. Five layouts were assessed by computational fluid dynamics (CFD) simulation. The hull/propulsion layout cases have been analyzed for discrete flow speed values in the range 0–6 m/s. All cases have been examined under restricted draft conditions in shallow water with a minimum of 0.3 m under keel clearance (UKC) and under unrestricted draft conditions in deep water. The results show that distributed propulsion consisting of 6 or 8 (in some cases, even more) units produces noticeable higher thrust effects in shallow water than the traditional layout. Under restricted conditions, the thrust increase between two distributed layouts with different numbers of propulsors is higher, in contrast to deep water, where differences in performance are not so significant.

Description: Xenogenic collagen-based matrices represent an alternative to subepithelial palatal connective tissue autografts in periodontal and peri-implant soft tissue reconstructions. In the present study, we aimed to investigate the migratory, adhesive, proliferative, and wound-healing potential of primary human oral fibroblasts (hOF) and periodontal ligament cells (hPDL) in response to four commercially available collagen matrices. Non-crosslinked collagen matrix (NCM), crosslinked collagen matrix (CCM), dried acellular dermal matrix (DADM), and hydrated acellular dermal matrix (HADM) were all able to significantly enhance the ability of hPDL and hOF cells to directionally migrate toward the matrices as well as to efficiently repopulate an artificially generated wound gap covered by the matrices. Compared to NCM and DADM, CCM and HADM triggered stronger migratory response. Cells grown on CCM and HADM demonstrated significantly higher proliferative rates compared to cells grown on cell culture plastic, NCM, or DADM. The pro-proliferative effect of the matrices was supported by expression analysis of proliferative markers regulating cell cycle progression. Upregulated expression of genes encoding the adhesive molecules fibronectin, vinculin, CD44 antigen, and the intracellular adhesive molecule-1 was detected in hPDL and hOF cells cultured on each of the four matrices. This may be considered as a prerequisite for good adhesive properties of the four scaffolds ensuring proper cell–matrix and cell–cell interactions. Upregulated expression of genes encoding TGF-β1 and EGF growth factors as well as MMPs in cells grown on each of the four matrices provided support for their pro-proliferative and pro-migratory abilities. The expression of genes encoding the angiogenic factors FGF-2 and VEGF-A was dramatically increased in cells grown on DADM and HADM only, suggesting a good basis for accelerated vascularization of the latter. Altogether, our results support favorable influence of the investigated collagen matrices on the recruitment, attachment, and growth of cell types implicated in oral soft tissue regeneration. Among the four matrices, HADM has consistently exhibited stronger positive effects on the oral cellular behavior. Our data provide solid basis for future investigations on the clinical application of the collagen-based matrices in surgical periodontal therapy.

Description: In recent years, a series of matching pursuit and hard thresholding algorithms have been proposed to solve the sparse representation problem with ℓ0-norm constraint. In addition, some stochastic hard thresholding methods were also proposed, such as stochastic gradient hard thresholding (SG-HT) and stochastic variance reduced gradient hard thresholding (SVRGHT). However, each iteration of all the algorithms requires one hard thresholding operation, which leads to a high per-iteration complexity and slow convergence, especially for high-dimensional problems. To address this issue, we propose a new stochastic recursive gradient support pursuit (SRGSP) algorithm, in which only one hard thresholding operation is required in each outer-iteration. Thus, SRGSP has a significantly lower computational complexity than existing methods such as SG-HT and SVRGHT. Moreover, we also provide the convergence analysis of SRGSP, which shows that SRGSP attains a linear convergence rate. Our experimental results on large-scale synthetic and real-world datasets verify that SRGSP outperforms state-of-the-art related methods for tackling various sparse representation problems. Moreover, we conduct many experiments on two real-world sparse representation applications such as image denoising and face recognition, and all the results also validate that our SRGSP algorithm obtains much better performance than other sparse representation learning optimization methods in terms of PSNR and recognition rates.

Description: To investigate the effect of wave-induced mixing on the upper ocean structure, especially under typhoon conditions, an ocean-wave coupled model is used in this study. Two physical processes, wave-induced turbulence mixing and wave transport flux residue, are introduced. We select tropical cyclone (TC) Nepartak in the Northwest Pacific ocean as a TC example. The results show that during the TC period, the wave-induced turbulence mixing effectively increases the cooling area and cooling amplitude of the sea surface temperature (SST). The wave transport flux residue plays a positive role in reproducing the distribution of the SST cooling area. From the intercomparisons among experiments, it is also found that the wave-induced turbulence mixing has an important effect on the formation of mixed layer depth (MLD). The simulated maximum MLD is increased to 54 m and is only 1 m less than the observed value. The wave transport flux residue shows a dominant role in the mixed layer temperature (MLT) changing. The mean error of the MLT is reduced by 0.19 °C compared with the control experiment without wave mixing effects. The study shows that the effect of wave mixing should be included in the upper ocean structure modeling.

Description: We evaluated surface-based analysis for assessing the possible relationship between the microstructural properties and particulate matter (i.e., two size fractions of PM2.5 and PM10) adsorption efficiencies of their leaf surfaces on ten woody species. We focused on the effect of PM adsorption capacity between micro-morphological features on leaf surfaces using a scanning electron microscope and a non-contact surface profiler as an example. The species with higher adsorption of PM10 on leaf surfaces were Korean boxwood (Buxus koreana Nakai ex Chung & al.) and evergreen spindle (Euonymus japonicus Thunb.), followed by yulan magnolia (Magnolia denudata Desr.), Japanese yew (Taxus cuspidata Siebold & Zucc.), Japanese horse chestnut (Aesculus turbinata Blume), retusa fringetree (Chionanthus retusus Lindl. & Paxton), maidenhair tree (Ginkgo biloba L.), and royal azalea (Rhododendron schlippenbachii Maxim.). There was a higher capacity for the adsorption of PM2.5 on the leaf surfaces of B. koreana and T. cuspidata, followed by A. turbinata, C. retusus, E. japonicus, G. biloba, and M. denudata. In wax layer tests, T. cuspidata, A. turbinata, R. schlippenbachii, and C. retusus showed a statistically higher PM2.5 capturing capacity than the other species. Different types of trichomes were distributed on the adaxial and abaxial leaves of A. turbinata, C. retusus, M. denudata, pagoda tree (Styphnolobium japonicum (L.) Schott), B. koreana, and R. schlippenbachii; however, these trichomes were absent on both sides of the leaves of G. biloba, tuliptree (Liriodendron tulipifera L.), E. japonicus, and T. cuspidata. Importantly, leaf surfaces of G. biloba and S. japonicum with dense or thick epicuticular leaf waxes and deeper roughness revealed lower PM adsorption. Based on the overall performance of airborne PM capture efficiency, evergreen species such as B. koreana, T. cuspidata, and E. japonicus showed the best results, whereas S. japonicum and L. tulipifera had the lowest capture. In particular, evergreen shrub species showed higher PM2.5 depositions inside the inner wall of stomata or the periphery of guard cells. Therefore, in leaf microstructural factors, stomatal size may be related to notably high PM2.5 holding capacities on leaf surfaces, but stomatal density, trichome density, and roughness had a limited effect on PM adsorption. Finally, our findings indicate that surface-based microstructures are necessarily not a correlation for corresponding estimates with leaf PM adsorption.

Description: The current techniques used for monitoring the blasting process in open pit mines are manual, intermittent and inefficient and can expose technical manpower to hazardous conditions. This study presents the application of unmanned aerial vehicle (UAV) systems for monitoring and improving the blasting process in open pit mines. Field experiments were conducted in different open pit mines to assess rock fragmentation, blast-induced damage on final pit walls, blast dynamics and the accuracy of blastholes including production and pre-split holes. The UAV-based monitoring was done in three different stages, including pre-blasting, blasting and post-blasting. In the pre-blasting stage, pit walls were mapped to collect structural data to predict in situ block size distribution and to develop as-built pit wall digital elevation models (DEM) to assess blast-induced damage. This was followed by mapping the production blasthole patterns implemented in the mine to investigate drillhole alignment. To monitor the blasting process, a high-speed camera was mounted on the UAV to investigate blast initiation, sequencing, misfired holes and stemming ejection. In the post-blast stage, the blasted rock pile (muck pile) was monitored to estimate fragmentation and assess muck pile configuration, heave and throw. The collected aerial data provide detailed information and high spatial and temporal resolution on the quality of the blasting process and significant opportunities for process improvement. The current challenges with regards to the application of UAVs for blasting process monitoring are discussed, and recommendations for obtaining the most value out of an UAV application are provided.

Description: Concrete wastewater infrastructures are important to modern society but are susceptible to sulfuric acid attack when exposed to an aggressive environment. Fibre-reinforced mortar has been adopted as a promising coating and lining material for degraded reinforced concrete structures due to its unique crack control and excellent anti-corrosion ability. This paper aims to evaluate the performance of polyethylene (PE) fibre-reinforced calcium aluminate cement (CAC)–ground granulated blast furnace slag (GGBFS) blended strain-hardening mortar after sulfuric acid immersion, which represented the aggressive sewer environment. Specimens were exposed to 3% sulfuric acid solution for up to 112 days. Visual, physical and mechanical performance such as water absorption ability, sorptivity, compressive and direct tensile strength were evaluated before and after sulfuric acid attack. In addition, micro-structure changes to the samples after sulfuric acid attack were also assessed by X-Ray Diffraction (XRD) and Scanning Electron Microscopy (SEM) to further understand the deterioration mechanism. The results show that overall fibre-reinforced calcium aluminate cement (CAC)-based samples performed significantly better than fibre-reinforced ordinary Portland cement (OPC)-based samples as well as mortar samples in sulfuric acid solution in regard to visual observations, penetration depth, direct tensile strength and compressive reduction. Gypsum generation in the cementitious matrix of both CAC and OPC-based systems was the main reason behind the deterioration mechanism after acid attack exposure. Moreover, laboratory sulfuric acid testing has been proven for successfully screening the cementitious material against an acidic environment. This method can be considered to design the service life of concrete wastewater pipes.

Description: At present, the state-of-the-art approaches of Visual Question Answering (VQA) mainly use the co-attention model to relate each visual object with text objects, which can achieve the coarse interactions between multimodalities. However, they ignore the dense self-attention within question modality. In order to solve this problem and improve the accuracy of VQA tasks, in the present paper, an effective Dense Co-Attention Networks (DCAN) is proposed. First, to better capture the relationship between words that are relatively far apart and make the extracted semantics more robust, the Bidirectional Long Short-Term Memory (Bi-LSTM) neural network is introduced to encode questions and answers; second, to realize the fine-grained interactions between the question words and image regions, a dense multimodal co-attention model is proposed. The model’s basic components include the self-attention unit and the guided-attention unit, which are cascaded in depth to form a hierarchical structure. The experimental results on the VQA-v2 dataset show that DCAN has obvious performance advantages, which makes VQA applicable to a wider range of AI scenarios.

Description: Present-day science indicates that developing sensors with excellent sensitivity and selectivity for detecting early signs of diseases is highly desirable. Electrochemical sensors offer a method for detecting diseases that are simpler, faster, and more accurate than conventional laboratory analysis methods. Primarily, exploiting non-noble-metal nanomaterials with excellent conductivity and large surface area is still an area of active research due to its highly sensitive and selective catalysts for electrochemical detection in enzyme-free sensors. In this research, we successfully fabricate Metal-Organic Framework (MOF) FeBDC-derived Fe3O4 for non-enzymatic electrochemical detection of glucose. FeBDC synthesis was carried out using the solvothermal method. FeCl2.4H2O and Benzene-1,4-dicarboxylic acid (H2BDC) are used as precursors to form FeBDC. The materials were further characterized utilizing X-ray Powder Diffraction (XRD), Scanning Electron Microscopy (SEM), and Fourier-Transform Infrared Spectroscopy (FTIR). The resulting MOF yields good crystallinity and micro-rod like morphology. Electrochemical properties were tested using Cyclic Voltammetry (CV) and Differential Pulse Voltammetry (DPV) with a 0.1 M of Phosphate Buffer Saline (PBS pH 7.4) solution as the supporting electrolyte. The measurement results show the reduction and oxidation peaks in the CV curve of FeBDC, as well as Fe3O4. Pyrolysis of FeBDC to Fe3O4 increases the peak of oxidation and reduction currents. The Fe3O4 sample obtained has a sensitivity of 4.67 µA mM−1.cm−2, a linear range between 0.0 to 9.0 mM, and a glucose detection limit of 15.70 µM.

Description: In this work, we present a network architecture with parallel convolutional neural networks (CNN) for removing perspective distortion in images. While other works generate corrected images through the use of generative adversarial networks or encoder-decoder networks, we propose a method wherein three CNNs are trained in parallel, to predict a certain element pair in the 3×3 transformation matrix, M^. The corrected image is produced by transforming the distorted input image using M^−1. The networks are trained from our generated distorted image dataset using KITTI images. Experimental results show promise in this approach, as our method is capable of correcting perspective distortions on images and outperforms other state-of-the-art methods. Our method also recovers the intended scale and proportion of the image, which is not observed in other works.