ALBERT

Description: Organic and low-input food systems are emerging worldwide in answer to the sustainability crisis of the conventional agri-food sector. “Alternative” systems are based on local, decentralized approaches to production and processing, regarding quality and health, and short supply-chains for products with strong local identities. Diversity is deeply embedded in these food systems, from the agrobiodiversity grown in farmers’ fields, which improves resilience and adaptation, to diverse approaches, contexts and actors in food manufacturing and marketing. Diversity thus becomes a cross-sectoral issue which acknowledges consumers’ demand for healthy products. In the framework of the European project “CERERE, CEreal REnaissance in Rural Europe: embedding diversity in organic and low-input food systems”, the paper aims at reviewing recent research on alternative and sustainable food systems by adopting an innovative and participatory multi-actor approach; this has involved ten practitioners and twenty-two researchers from across Europe and a variety of technical backgrounds in the paper and analysis stages. The participatory approach is the main innovation and distinctive feature of this literature review. Partners selected indeed what they perceived as most relevant in order to facilitate a transition towards more sustainable and diversity based cereal systems and food chains. This includes issues related to alternative food networks, formal and informal institutional settings, grass root initiatives, consumer involvement and, finally, knowledge exchange and sustainability. The review provides an overview of recent research that is relevant to CERERE partners as well as to anyone interested in alternative and sustainable food systems. The main objective of this paper was indeed to present a narrative of studies, which can form the foundation for future applied research to promote alternative methods of cereal production in Europe.

Description: Peak flows values (Q) and hydrograph volumes (V) are obtained from a selected family of historical flood events (period 1957–2017), for two neighboring mountain catchments located in the Ebro river basin, Spain: rivers Ésera and Isábena. Barasona dam is located downstream of the river junction. The peaks over threshold (POT) method is used for a univariate frequency analysis performed for both variables, Q and V, comparing several suitable distribution functions. Extreme value copulas families have been applied to model the bivariate distribution (Q, V) for each of the rivers. Several goodness-of-fit tests were used to assess the applicability of the selected copulas. A similar copula approach was carried out to model the dependence between peak flows of both rivers. Based on the above-mentioned statistical analysis, a Monte Carlo simulation of synthetic design flood hydrographs (DFH) downstream of the river junction is performed. A gamma-type theoretical pattern is assumed for partial hydrographs. The resulting synthetic hydrographs at the Barasona reservoir are finally obtained accounting for flow peak time lag, also described in statistical terms. A 50,000 hydrographs ensemble was generated, preserving statistical properties of marginal distributions as well as statistical dependence between variables. The proposed method provides an efficient and practical modeling framework for the hydrological risk assessment of the dam, improving the basis for the optimal management of such infrastructure.

Description: Nitrogen oxides are emitted in large quantities by vehicles, and solutions to the problem are sought after. Efforts towards abatement include Selective Catalytic Reduction, catalytic converters, and redesigning engines to make them more efficient. This article focuses on the photocatalytic oxidation, which involves the use of titanium dioxide and ultraviolet radiation to oxidise nitrogen oxides to nitrates. To test this, the interior of a serpentine reactor was coated with titanium dioxide and irradiated with various intensities of ultraviolet light, and the photocatalytic abatement was monitored for the exhaust fumes from a standalone 4-stroke test diesel engine. The conversion rates were calculated using the entering concentration and the concentration after a certain time increment. The rates varied between 13.7% and 37.3% and depended strongly on the relative humidity, as a higher relative humidity directly correlated with a better conversion. The irradiance was also varied, and a decline in the conversion rate occurred when the irradiance was increased.

Description: Accurate 3D computer models of the brain, and also of parts of its structure such as the corpus callosum (CC) are increasingly used in routine clinical diagnostics. This study presents comparative research to assess the utility and performance of three active contour methods (ACMs) for segmenting the CC from magnetic resonance (MR) images of the brain, namely: an edge-based active contour model using an inflation/deflation force with a damping coefficient (EM), the Selective Binary and Gaussian Filtering Regularized Level Set (SBGFRLS) method and the Distance Regularized Level Set Evolution (DRLSE) method. The pre-processing methods applied during research work were to improve the contrast, reduce noise and thus help segment the CC better. In this project, 3D CC models reconstructed based on the segmentations of cross-sections of MR images were also visualised. The results, as measured by quantitative tests of the similarity indice (SI) and overlap value (OV) are the best for the EM model (SI = 92%, OV = 82%) and are comparable to or better than those for other methods taken from a literature review. Furthermore, the properties of the EM model consisting in its ability to both expand and shrink at the same time allow segmentations to be better fitted in subsequent CC slices then in state-of-the art ACMs such as DRLSE or SBGFRLS. The CC contours from previous and subsequent iterations produced by the EM model can be used for initiation in subsequent or previous frames of MR images, which makes the segmentation process easier, particularly as the CC area can increase or decrease in subsequent MR image frames.

Description: In this study, we apply a robust optimization approach to a p-center facility location problem under uncertainty. Based on a symmetric interval and a multiple allocation strategy, we use three types of uncertainty sets to formulate the robust problem: box uncertainty, ellipsoidal uncertainty, and cardinality-constrained uncertainty. The equivalent robust counterpart models can be solved to optimality using Gurobi. Comprehensive numerical experiments have been conducted by comparing the performance of the different robust models, which illustrate the pattern of robust solutions, and allocating a demand node to multiple facilities can reduce the price of robustness, and reveal that alternative models of uncertainty can provide robust solutions with different conservativeness.

Description: As one of the key crop traits, plant height is traditionally evaluated manually, which can be slow, laborious and prone to error. Rapid development of remote and proximal sensing technologies in recent years allows plant height to be estimated in more objective and efficient fashions, while research regarding direct comparisons between different height measurement methods seems to be lagging. In this study, a ground-based multi-sensor phenotyping system equipped with ultrasonic sensors and light detection and ranging (LiDAR) was developed. Canopy heights of 100 wheat plots were estimated five times during a season by the ground phenotyping system and an unmanned aircraft system (UAS), and the results were compared to manual measurements. Overall, LiDAR provided the best results, with a root-mean-square error (RMSE) of 0.05 m and an R2 of 0.97. UAS obtained reasonable results with an RMSE of 0.09 m and an R2 of 0.91. Ultrasonic sensors did not perform well due to our static measurement style. In conclusion, we suggest LiDAR and UAS are reliable alternative methods for wheat height evaluation.

Description: In this paper, the smart management of buildings energy use by means of an innovative renewable micro-cogeneration system is investigated. The system consists of a concentrated linear Fresnel reflectors solar field coupled with a phase change material thermal energy storage tank and a 2 kWe/18 kWth organic Rankine cycle (ORC) system. The microsolar ORC was designed to supply both electricity and thermal energy demand to residential dwellings to reduce their primary energy use. In this analysis, the achievable energy and operational cost savings through the proposed plant with respect to traditional technologies (i.e., condensing boilers and electricity grid) were assessed by means of simulations. The influence of the climate and latitude of the installation was taken into account to assess the performance and the potential of such system across Europe and specifically in Spain, Italy, France, Germany, U.K., and Sweden. Results show that the proposed plant can satisfy about 80% of the overall energy demand of a 100 m2 dwelling in southern Europe, while the energy demand coverage drops to 34% in the worst scenario in northern Europe. The corresponding operational cost savings amount to 87% for a dwelling in the south and at 33% for one in the north.

Description: For the purpose of reducing noise from grain flow signal, this paper proposes a filtering method that is on the basis of empirical mode decomposition (EMD) and artificial bee colony (ABC) algorithm. At first, decomposing noise signal is performed adaptively into intrinsic mode functions (IMFs). Then, ABC algorithm is utilized to determine a proper threshold shrinking IMF coefficients instead of traditional threshold function. Furthermore, a neighborhood search strategy is introduced into ABC algorithm to balance its exploration and exploitation ability. Simulation experiments are conducted on four benchmark signals, and a comparative study for the proposed method and state-of-the-art methods are carried out. The compared results demonstrate that signal to noise ratio (SNR) and root mean square error (RMSE) are obtained by the proposed method. The conduction of which is finished on actual grain flow signal that is with noise for the demonstration of the effect in actual practice.

Description: Efficient matching of incoming events of data streams to persistent queries is fundamental to event stream processing systems in wireless sensor networks. These applications require dealing with high volume and continuous data streams with fast processing time on distributed complex event processing (CEP) systems. Therefore, a well-managed parallel processing technique is needed for improving the performance of the system. However, the specific properties of pattern operators in the CEP systems increase the difficulties of the parallel processing problem. To address these issues, a parallelization model and an adaptive parallel processing strategy are proposed for the complex event processing by introducing a histogram and utilizing the probability and queue theory. The proposed strategy can estimate the optimal event splitting policy, which can suit the most recent workload conditions such that the selected policy has the least expected waiting time for further processing of the arriving events. The proposed strategy can keep the CEP system running fast under the variation of the time window sizes of operators and the input rates of streams. Finally, the utility of our work is demonstrated through the experiments on the StreamBase system.

Description: In this article, we explore the opportunities and challenges of landscape approaches through the lens of responsible research and innovation (RRI). We use the case of transport biofuels to reflect on the capacity of landscape approaches to support the governance of emerging technologies. The case study, developed in the region of Sardinia, Italy, consists of a landscape design process for the implementation of biofuel technologies that rely on the use of non-food dedicated crops and agricultural residues. By using non-food feedstocks, the biofuel project aims to avoid competition with food production and achieve sustainability goals. Through the discussion of key dimensions of RRI in relation to this case, the article puts forward a set of critical aspects of landscape design processes that require further attention from theorists and practitioners in the field of landscape-based planning. These include the power imbalance that exists between the diverse actors involved in project activities, a need for improving the flexibility of the configuration of socio-technical systems, revising assumptions on ‘valid’ knowledge, and improving the deliberative component of planning processes.

Description: This paper presents the resistivity and piezoresistivity behavior of cement-based mortars manufactured with graphene nanoplatelet filler (GNP), virgin carbon fibers (VCF) and recycled carbon fibers (RCF). GNP was added at 4% of the cement weight, whereas two percentages of carbon fibers were chosen, namely 0.05% and 0.2% of the total volume. The combined effect of both filler and fibers was also investigated. Mortars were studied in terms of their mechanical properties (under flexure and compression) and electrical resistivity. Mortars with the lowest electrical resistivity values were also subjected to cyclic uniaxial compression to evaluate the variations in electrical resistivity as a function of strain. The results obtained show that mortars have piezoresistive behavior only if they are subjected to a prior drying process. In addition, dry specimens exhibit a high piezoresistivity only when loaded with 0.2 vol.% of VCF and 0.4 wt.% of GNP plus 0.2 vol.% RCF, with a quite reversible relation between their fractional change in resistivity (FCR) and compressive strain.

Description: The application of predictive analytics in higher education has increasingly gained acceptance and interest over the years. In this study, a predictive model is developed to map students’ non-cognitive skills against their class performance. Our predictive analytics model identified the non-cognitive skills that predicted new students’ class performance based on the dataset collected early in the semester. Based on the predictive analytics results, tailored teaching to improve students’ non-cognitive skills was offered in a required class designed for undergraduate business students. The improvement in the average final semester grade for students in the tailored-taught classes based on our predicted analytics approach was 9%, which was higher than that of the class grade taught without the approach. The study finding also demonstrates a long-term, sustainable positive effect to the students with the predictive analytics approach.

Description: In this paper, we study various cosmological models involving new nonlinear forms of interaction between cold dark matter (DM) and dark energy (DE) assuming that DE is a barotropic fluid. The interactions are nonlinear either due to log ( ρ d e / ρ d m ) or log ( ρ d m / ρ d e ) parameterizations, respectively. The main purpose of this paper is to demonstrate the applicability of the forms of suggested interactions to the problem of modern cosmology known as accelerated expansion of the Universe. Using the differential age of old galaxies expressed in terms of H ( z ) data, the peak position of baryonic acoustic oscillations (known as BAO data), the SN Ia data with strong gravitational lensing data, we obtain the best fit values of the model parameters for each case. Besides, using O m analysis and S 3 parameter from the statefinder hierarchy analysis, we also demonstrate that the considered models are clearly different from the Λ CDM model. We obtain that the models predict Hubble parameter values consistent to the estimations from gravitational lensing, which probes the expansion out to z ≤ 1.7 . We show that, with considered models, we can also explain PLANCK 2015 and PLANCK 2018 experiment results.

Description: Recrystallization and solid-solution formation with barite is considered as relevant retention mechanism for 226Ra in long-term scenarios of nuclear waste management. Here, we studied the effect of ionic strength and the presence of Sr in solution upon the Ra-uptake kinetics and final Ra concentrations in solution by recrystallizing barite in solution with varying Sr and NaCl concentration and temperature for up to 1000 days. Final Ra-concentrations were interpreted based on thermodynamic modelling. Our results indicate a slight decrease of the retention potential of barite for Ra but little effect on the uptake kinetics due to the increase of ionic strength from. 0.1 mol/kg to 1.0 mol/kg of NaCl. The final concentrations at solid/liquid ratio of 0.5 g/kg are well described based on available thermodynamic models whereas at 5 g/kg additional Ra uptake probably due to kinetic effects was observed. On the contrary, the presence of Sr in solution can have a significant inhibiting kinetic effect on the uptake kinetics and lower the final Ra-uptake. In some cases, with low solid/liquid ratio or at ambient conditions, Sr completely inhibits barite recrystallization. In all other cases, Ra, Ba and Sr were taken up as thermodynamically predicted at the end of the experiments.

Description: Skeletons of hermatypic corals (e.g., Porites) might have enormous potential as a high-resolution paleomagnetic recorder owing to their rapid and continuous growth over hundreds of years at a rate of up to 2 cm/year, although typical corals show an extremely weak intensity of remanence and low stability. We found that coral tsunami boulders with negligible amounts of calcite on Ishigaki Island show a measurable intensity of remanence; thus, we attempted to characterize the magnetic assemblages in this coral skeleton to determine whether it is of biogenic or detrital magnetite using first-order reversal curve (FORC) measurements, ferromagnetic resonance (FMR) spectroscopy, and petrological observations through field-emission type scanning electron microscope (FE-SEM) with an acid treatment. The FMR derivative spectra of coral skeleton samples represent multiple derivative maxima and extended low-field absorption, indicating the presence of intact biogenic magnetite chains. FORC diagrams represent a “central ridge” signature with a vertical spread. These FMR and FORC features indicate the magnetization of these coral skeletons that are mainly created using intact biogenic magnetites and mixtures of grains from collapsed biogenic magnetites, pseudo-single domain grains, and multi-domain grains such as detrital magnetite. FE-SEM observations confirm the presence of a chain-like structure of iron oxides corresponding to the features of biogenic magnetite. Therefore, the magnetic mineral assemblage in coralline boulders from Ishigaki Island consists of dominant biogenic-origin single-domain magnetite and a trace amount of detrital component, indicating that fossil coral skeletons in Ishigaki Island have potential for utilization in paleomagnetic studies.

Description: 360-degree video streaming for high-quality virtual reality (VR) is challenging for current wireless systems because of the huge bandwidth it requires. However, millimeter wave (mmWave) communications in the 60 GHz band has gained considerable interest from the industry and academia because it promises gigabit wireless connectivity in the huge unlicensed bandwidth (i.e., up to 7 GHz). This massive unlicensed bandwidth offers great potential for addressing the demand for 360-degree video streaming. This paper investigates the problem of 360-degree video streaming for mobile VR using the SHVC, the scalable of High-Efficiency Video Coding (HEVC) standard and PC offloading over 60 GHz networks. We present a conceptual architecture based on advanced tiled-SHVC and mmWave communications. This architecture comprises two main parts. (1) Tile-based SHVC for 360-degree video streaming and optimizing parallel decoding. (2) Personal Computer (PC) offloading mechanism for transmitting uncompressed video (viewport only). The experimental results show that our tiled extractor method reduces the bandwidth required for 360-degree video streaming by more than 47% and the tile partitioning mechanism was improved by up to 25% in terms of the decoding time. The PC offloading mechanism was also successful in offloading 360-degree decoded (or viewport only) video to mobile devices using mmWave communication and the proposed transmission schemes.

Description: The concept of quantum B-algebra was introduced by Rump and Yang, that is, unified algebraic semantics for various noncommutative fuzzy logics, quantum logics, and implication logics. In this paper, a new notion of q-filter in quantum B-algebra is proposed, and quotient structures are constructed by q-filters (in contrast, although the notion of filter in quantum B-algebra has been defined before this paper, but corresponding quotient structures cannot be constructed according to the usual methods). Moreover, a new, more general, implication algebra is proposed, which is called basic implication algebra and can be regarded as a unified frame of general fuzzy logics, including nonassociative fuzzy logics (in contrast, quantum B-algebra is not applied to nonassociative fuzzy logics). The filter theory of basic implication algebras is also established.

Description: Suicide is the leading cause of death among young men aged 15–29 in Greenland, but few epidemiological studies have described this problem. We aimed to summarise descriptive epidemiological studies of suicide in young men in Greenland compared with other demographic groups in Denmark and Greenland to inform future suicide prevention strategy. We searched PubMed, PsycINFO, and Embase using an agreed search strategy to identify English-language papers describing suicide epidemiology in Greenlandic men aged 15–29. We followed PRISMA guidelines in screening and appraising eligible publications. Eight articles fulfilled inclusion criteria of 64 meeting search criteria. Findings covering 1970–2011 supported a dramatic rise in suicide rates in Greenlandic men aged 15–24 from 1976, who remained the highest-ranking demographic group over 1976–2011 compared with men and women of all age groups in Denmark and Greenland. Highest rates recorded were almost 600 per 100,000 per year in men aged approximately 20–23 over 1977–1986. No studies described suicide epidemiology after 2011, and no studies described risk factors for suicide in young men. Given the very high suicide rates recorded for young men over 1976–2011, such studies will be essential for informing the development and evaluation of appropriate preventive interventions.

Description: Elastic nails made of the nickel-titanium shape memory alloy (Nitinol) have been reported to control bone modeling in animal studies. However, the mechanical stability of the Nitinol nail in the fixation of long bone fractures remains unclear. This study compared mechanical stability among nails made of three materials, namely Nitinol, titanium, and stainless steel, in the fixation of long bone fractures. These three materials had identical shapes (arc length: π/2 and radius: 260 mm). A cylindrical sawbone with a 10-mm gap and fixed with two C-shaped elastic nails was used to examine the stability of the nails. A finite element (FE) model was developed based on the sawbone model. The end cap for elastic nails was not used in the sawbone test but was considered based on a constraint equation in FE simulation. The results of stability tests appeared to depend on the presence or absence of the end cap. In the sawbone test, the titanium nail yielded a higher ultimate force against the applied load than did the stainless steel and Nitinol nails before the gap completely closed; the difference in linear stiffness between the nails was nonsignificant. In FE simulation, the titanium nail produced smaller gap shortening than did stainless steel and Nitinol nails without the end cap; the difference in gap shortening between the nails was minor with the end cap. The titanium elastic nail should be a better choice in managing diaphyseal long bone fractures when the end cap is not used. For Nitinol and stainless steel nails, the end cap should be used to stop the nail from dropping out and to stabilize the fractured bone.

Description: Frequent food quality and safety issues result in various food inspection measures in China, while some are not widely acknowledged by the public and are less efficient. Consumer demand is significant for priority setting in food policy. This study investigates Chinese consumers’ heterogeneous preferences for selected food inspection measures and estimates welfare effects based on willingness-to-pay (WTP) calculation. Rice consumption data from a 2018 nationwide consumer survey designed using the real choice experiment is analyzed by the random parameters logit and the latent class model. The findings reveal that consumers place a high value on government certification, and brand is valuable especially when public management is perceived as weak. However, the insufficient market demand for third-party certification may increase transaction costs due to overlapping functions and consumers’ distrust. Moreover, there should be a need to broaden consumers’ understanding of traceability and grading systems. This study emphasizes the necessity of direct governmental involvement and the existence of unnecessary policy cost.

Description: In this paper, we extended the Hamy mean (HM) operator, the Dombi Hamy mean (DHM) operator, the Dombi dual Hamy mean (DDHM), with the intuitionistic fuzzy numbers (IFNs) to propose the intuitionistic fuzzy Dombi Hamy mean (IFDHM) operator, intuitionistic fuzzy weighted Dombi Hamy mean (IFWDHM) operator, intuitionistic fuzzy Dombi dual Hamy mean (IFDDHM) operator, and intuitionistic fuzzy weighted Dombi dual Hamy mean (IFWDDHM) operator. Following this, the multiple attribute group decision-making (MAGDM) methods are proposed with these operators. To conclude, we utilized an applicable example for the selection of a car supplier to prove the proposed methods.

Description: Benthic algae, especially diatoms, are commonly used to assess water quality in rivers. However, algal-based assessments are challenging at the river system scale because longitudinal variation in physical habitat conditions may obscure algal responses to changes in water quality. In the present study, we surveyed benthic diatoms and environmental variables from a mountainous Chinese river system. Hierarchical clustering, discrimination analysis, and indicator species analysis were used together to explore associations between distribution patterns of diatom assemblages and water quality variables. Study sites were clustered into five groups based on their diatom community composition, with sites grouped by the sampling months. Chemical oxygen demand (COD), elevation, and total nitrogen (TN) were the most important predictors for site classification. Site groups with higher elevations had higher TN concentrations; however, COD concentrations were higher in lower elevation groups. Moreover, COD concentrations significantly differed between temporally separated groups. In total, 49 indicator species were identified for individual groups, with most taxa indicating the eutrophic condition. Additionally, we found that European diatom indices are not closely associated with water quality variables. We conclude that the identification of algal patterns and their driving forces can provide valuable information to aid bioassessment at the river system scale.

Description: Strontium ferrite was compounded with acrylonitrile butadiene rubber to prepare rubber magnetic composites. For cross-linking of the prepared materials, peroxide curing systems consisting of dicumyl peroxide as curing agent and zinc salts of acrylic and methacrylic acids as co-agents were used. The amount of strontium ferrite was kept constant in all experiments, while the main objective of the work was to investigate the composition of curing system and both types of co-agents on the cross-linking, physical-mechanical, dynamic and magnetic properties of the rubber magnets. The results showed that the change in composition of curing system has significant influence on cross-link density and properties of the tested composite materials. With an increasing amount of zinc based co-agents, significant improvement of tensile strength was achieved. The application of zinc based co-agents in peroxide vulcanization of rubber magnetic composites leads to the preparation of rubber magnets with not only good magnetic properties, but also with improved physical-mechanical characteristics.

Description: A coupled macro-meso-scale numerical simulation is applied to investigate the friction effect on texture evolution during uniaxial compression of NiTi shape memory alloy at 400 °C. In this approach, macroscale finite element simulations in consideration of various friction coefficient are conducted and then the corresponding velocity gradients in various regions are extracted mainly based on the delivery deformation gradient in the user-defined material subroutine (UMAT) in ABAQUS code. These velocity gradients are regarded as the deformation conditions applied in the mesoscale VPSC model. Simulation results in terms of macroscale finite element modeling demonstrate that only within the region of minimum deformation zone which is close to the die, friction effect has a nonnegligible influence on the velocity gradient. Simulation results with respect to the mesoscale VPSC modeling show that the affine and Neff = 10 linearization schemes provide the best predictions for NiTi shape memory alloy with cubic structure. Furthermore, the friction effect does have an influence on the evolution of slip mode activities in various deformation zones and therefore results in the inhomogeneous texture evolution within the deformed sample during uniaxial compression.

Description: Since the 1990s, the Two Major Environmental Value model (2-MEV) has been applied to measure adolescent environmental attitudes by covering two higher order factors: (i) Preservation of Nature (PRE) which measures protection preferences and (ii) Utilization of Nature (UTL) which quantifies preferences towards exploitation of nature. In addition to the 2-MEV scale, we monitored the Appreciation of Nature (APR) which, in contrast to the UTL, monitors the enjoyable utilization of nature. Finally, we employed the Morningness–Eveningness Scale for Children (MESC) which monitors the diurnal preferences and associates with personality and behavioral traits. In this study, we analyzed data from 429 Irish students (14.65 years; ±1.89 SD) with the aim of reconfirming the factor structure of the 2-MEV+APR and monitoring the relationship between the MESC and the environmental values (PRE, UTL, APR). Our findings identified a significant association between PRE and APR with MESC. In addition, we observed a gender difference. Our results suggest that morningness preference students are more likely to be protective of and appreciative towards nature. Recommendations for outreach programs as well as conclusions for environmental education initiatives in general are discussed.

Description: Peak current-mode control is widely used in power converters and involves the use of an external compensation ramp to suppress undesired behaviors and to enhance the stability range of the Period-1 orbit. A boost converter uses an analytical expression to find a compensation ramp; however, other more complex converters do not use such an expression, and the corresponding compensation ramp must be computed using complex mechanisms. A boost-flyback converter is a power converter with coupled inductors. In addition to its high efficiency and high voltage gains, this converter reduces voltage stress acting on semiconductor devices and thus offers many benefits as a converter. This paper presents an analytical expression for computing the value of a compensation ramp for a peak current-mode controlled boost-flyback converter using its simplified model. Formula results are compared to analytical results based on a monodromy matrix with numerical results using bifurcations diagrams and with experimental results using a lab prototype of 100 W.

Description: We investigated the ammonium removal abilities of natural and synthetic zeolites with distinct Si/Al ratios and various surface areas to study how adsorption and ion exchange processes in zeolites perform under different ammonium concentrations and different temperatures. Five zeolites—natural mordenite, chabazite, erionite, clinoptilolite, and synthetic merlinoite—were immersed in 20, 50, and 100 mg/kg ammonium solutions. The results demonstrate that zeolites under high ammonium concentrations (100 mg/kg) possess higher physical adsorption capacity (0.398–0.468 meq/g), whereas those under lower ammonium concentrations (20 mg/kg) possess greater ion exchange properties (64–99%). The ion exchange ability of zeolites is extremely dependent on the cation content of the zeolites, and the cation content is affected by the Si/Al ratio. The surface area of zeolites also has a partial influence on its physical adsorption ability. When the surface area is less than 100 m2/g, the adsorption ability of zeolite increases obviously with surface area; however, adsorption ability is saturated as the surface area becomes larger than this critical value of 100 m2/g. When we placed the zeolites in 50 mg/kg ammonium concentration at different temperatures (5–50 °C), we found that the zeolites exhibited the highest ammonium removal ability at 30 °C and the potassium release was enhanced at 30–40 °C.

Description: The shadow-mapping and ray-tracing algorithms are the two popular approaches used in visibility handling for multi-view based texture reconstruction. Visibility testing based on the two algorithms needs a user-defined bias to reduce computation error. However, a constant bias does not work for every part of a geometry. Therefore, the accuracy of the two algorithms is limited. In this paper, we propose a high-precision graphics pipeline-based visibility classification (GPVC) method without introducing a bias. The method consists of two stages. In the first stage, a shader-based rendering is designed in the fixed graphics pipeline to generate initial visibility maps (IVMs). In the second stage, two algorithms, namely, lazy-projection coverage correction (LPCC) and hierarchical iterative vertex-edge-region sampling (HIVERS), are proposed to classify visible primitives into fully visible or partially visible primitives. The proposed method can be easily implemented in the graphics pipeline to achieve parallel acceleration. With respect to efficiency, the proposed method outperforms the bias-based methods. With respect to accuracy, the proposed method can theoretically reach a value of 100%. Compared with available libraries and software, the textured model based on our method is smoother with less distortion and dislocation.

Description: We mapped native, endemic, and introduced (i.e., exotic) tree species counts, relative basal areas of functional groups, species basal areas, and forest biomass from forest inventory data, satellite imagery, and environmental data for Puerto Rico and the Virgin Islands. Imagery included time series of Landsat composites and Moderate Resolution Imaging Spectroradiometer (MODIS)-based phenology. Environmental data included climate, land-cover, geology, topography, and road distances. Large-scale deforestation and subsequent forest regrowth are clear in the resulting maps decades after large-scale transition back to forest. Stand age, climate, geology, topography, road/urban locations, and protection are clearly influential. Unprotected forests on more accessible or arable lands are younger and have more introduced species and deciduous and nitrogen-fixing basal areas, fewer endemic species, and less biomass. Exotic species are widespread—except in the oldest, most remote forests on the least arable lands, where shade-tolerant exotics may persist. Although the maps have large uncertainty, their patterns of biomass, tree species diversity, and functional traits suggest that for a given geoclimate, forest age is a core proxy for forest biomass, species counts, nitrogen-fixing status, and leaf longevity. Geoclimate indicates hard-leaved species commonness. Until global wall-to-wall remote sensing data from specialized sensors are available, maps from multispectral image time series and other predictor data should help with running ecosystem models and as sustainable development indicators. Forest attribute models trained with a tree species ordination and mapped with nearest neighbor substitution (Phenological Gradient Nearest Neighbor method, PGNN) yielded larger correlation coefficients for observed vs. mapped tree species basal areas than Cubist regression tree models trained separately on each species. In contrast, Cubist regression tree models of forest structural and functional attributes yielded larger such correlation coefficients than the ordination-trained PGNN models.

Description: This paper develops a bias compensation-based parameter and state estimation algorithm for the observability canonical state-space system corrupted by colored noise. The state-space system is transformed into a linear regressive model by eliminating the state variables. Based on the determination of the noise variance and noise model, a bias correction term is added into the least squares estimate, and the system parameters and states are computed interactively. The proposed algorithm can generate the unbiased parameter estimate. Two illustrative examples are given to show the effectiveness of the proposed algorithm.

Description: The energy management system (EMS) of a microgrid often presents a complex structure and a large number of control functions, which must be validated to ensure a reliable and optimal operation of the microgrid. Control system validation is typically performed by using hardware-in-the-loop (HIL) architectures in which the microgrid is simulated in real time and interfaced with the actual system under test. The simulation must ensure both an accurate representation of the microgrid and a reliable replica of the field communication of the EMS with all the control devices. In this paper, an overview of the various HIL architectures proposed in the literature is firstly outlined. Then, an HIL validation facility is presented and used to validate the EMS of an industrial microgrid. Finally, some results of the validation tests are reported to give evidence of the effectiveness of the proposed facility. In the proposed architecture, the soft real-time digital simulator of the microgrid is interfaced with the actual EMS using the same communication system and protocol as on the field. The main advantages of the proposed testing facility are: (i) the use of commercial PCs and the absence of dedicated interface modules, resulting in inexpensive hardware components; (ii) the capability to validate both control and communication functions of the EMS; (iii) the applicability to microgrids of different types (industrial, commercial, residential), as well as of various dimensions, including large microgrids; (iv) the easiness in changing the microgrid and the EMS under validation by only software modifications of the simulator tasks and of the exchange interface. As drawbacks, the proposed testing facility presents the need to adapt the software interface between EMS and the field to the EMS under test and the possibility of testing only the EMS functions and not fast-acting local controllers of the microgrid such as the protection systems.

Description: The building sector is responsible for a substantial part of the energy consumption and corresponding CO2 emissions. The European Union has consequently developed various directives, among which the updated Energy Performance of Buildings Directive 2018/844/EU stands out, aiming at minimizing the energy demand in buildings, improving the energy efficiency of their facilities and integrating renewable energies. The objective of the present study was to develop an analysis on the energy performance, related CO2 emissions and operating costs of the renewable energy technologies implemented within a multipurpose near Zero Energy Building (nZEB). The target building is an existing nZEB called LUCIA, located in Valladolid (Spain). Monitoring data provides the required information on the actual needs for electricity, cooling and heating. It is equipped with solar energy photovoltaic systems, a biomass boiler and a geothermal Earth to Air Heat Exchanger (EAHX) intended for meeting the ventilation thermal loads. All systems studied show favourable performances, but depend significantly on the particular characteristics of the building, the control algorithm and the climate of the location. Hence, design of these strategies for new nZEBs must consider all these factors. The combined use of the PhotoVoltaic PV System, the biomass and the EAHX reduces the CO2 emissions up to 123 to 170 tons/year in comparison with other fuels, entailing economic savings from the system operation of up to 43,000–50,000 €/year.

Description: Recent advances in modeling primary atomization in order to enable accurate practical-scale jet spray simulation are reviewed. Since the Eulerian–Lagrangian method is most widely used in academic studies and industrial applications, in which the continuous gas phase is treated in the Eulerian manner and droplets are calculated as Lagrangian point particles, the main focus is placed on improvement within this framework, especially focusing on primary atomization where modeling is the weakest. First, limitations of the conventional methods are described and then novel modeling proposals intended to tackle these issues are covered. These new modeling proposals include the Eulerian surface density approach, and the hybrid Eulerian surface/Lagrangian subgrid droplet generation approach. Compared to conventional simple yet sometimes non-physical models, recent models try to include more physical findings in primary atomization which have been obtained through experiments or direct numerical simulation (DNS). Model accuracy ranges from one that still needs some adjustment using experimental or DNS data to one which is totally self-closed so that no parameter tuning is necessary. These models have the potential to overcome the long-recognized bottleneck in primary atomization modeling and thus to improve the accuracy of whole spray simulation, and may greatly help to improve the spray design for higher combustion efficiency.

Description: China faces significant challenges related to global warming caused by CO2 emissions, and the power industry is a large CO2 emitter. The decomposition and accurate forecasting of CO2 emissions in China’s power sector are thus crucial for low-carbon outcomes. This paper selects seven socio-economic and technological drivers related to the power sector, and decomposes CO2 emissions based on two models: the extended stochastic impacts by regression on population, affluence and technology (STIRPAT) model and the partial least square (PLS) model. Distinguished from previous research, our study first compares the effects of eliminating the multicollinearity of the PLS model with stepwise regression and ridge regression, finding that PLS is superior. Further, the decomposition results show the factors’ absolute elasticity coefficients are population (2.58) 〉 line loss rate (1.112) 〉 GDP per capita (0.669) 〉 generation structure (0.522) 〉 the urbanization level (0.512) 〉 electricity intensity (0.310) 〉 industrial structure (0.060). Meanwhile, a novel hybrid PLS-Grey-Markov model is proposed, and is verified to have better precision for the CO2 emissions of the power sector compared to the selected models, such as ridge regression-Grey-Markov, PLS-Grey-Markov, PLS-Grey and PLS-BP (Back propagation neutral network model). The forecast results suggest that CO2 emissions of the power sector will increase to 5102.9 Mt by 2025. Consequently, policy recommendations are proposed to achieve low-carbon development in aspects of population, technology, and economy.

Description: Accurate wind speed forecasting is a significant factor in grid load management and system operation. The aim of this study is to propose a framework for more precise short-term wind speed forecasting based on empirical mode decomposition (EMD) and hybrid linear/nonlinear models. Original wind speed series is decomposed into a finite number of intrinsic mode functions (IMFs) and residuals by using the EMD. Several popular linear and nonlinear models, including autoregressive integrated moving average (ARIMA), support vector machine (SVM), random forest (RF), artificial neural network with back propagation (BP), extreme learning machines (ELM) and convolutional neural network (CNN), are utilized to study IMFs and residuals, respectively. An ensemble forecast for the original wind speed series is then obtained. Various experiments were conducted on real wind speed series at four wind sites in China. The performance and robustness of various hybrid linear/nonlinear models at two time intervals (10 min and 1 h) are compared comprehensively. It is shown that the EMD based hybrid linear/nonlinear models have better accuracy and more robust performance than the single models with/without EMD. Among the five hybrid models, EMD-ARIMA-RF has the best accuracy on the whole for 10 min data, and the mean absolute percentage error (MAPE) is less than 0.04. However, for the 1 h data, no model can always perform well on the four datasets, and the MAPE is around 0.15.

Description: Overtime, in the electricity sector, there has been a technological transfer to renewable electricity generation. With this change, processes, in the economic and availability terms, are expected to improve. In this new paradigm, society demands electricity without an impact on the environment and with the lowest possible cost. The wind power (WP) integration appears in this evolution process by achieving important technological advances, supporting in 2017 a growth of 44% of new projects in Europe, higher than any other renewable technology. However, the renewable energy sources (RES) integration in the electricity networks still presents technical difficulties and challenges, leading to challenges in the electricity markets (EMs). Therefore, this work evaluates the importance of WP and its influence on the Iberian Electricity Market (MIBEL), at the level of the intraday electricity spot market (IESM). This is an innovative study because literature usually focuses on day-ahead WP impact and this study focuses on intraday markets, which are closer to the consumption periods. The goal was to make an analysis on the impacts when betting on WP sources, in order to improve the market interaction with WP integration, considering as criteria the consumer satisfaction, in terms of lower electricity prices and WP availability. For this study, the market bids registered by the Iberian Electricity Market Operator (OMIE), from 2015 to 2017, ran over a new market simulator, specially developed for this proposal, considering a virtual market condition, but not considering the bids made by WP producers. The comparison of the results allowed the evaluation of the WP influence on the EM quantitative, which is noteworthy.

Description: Recently, integrated energy systems have become a new type of energy supply model. It is clear that integrated energy systems can improve energy efficiency and reduce costs. However, the use of a battery energy storage system (BESS) as a backup power source will affect the operating costs of a regional integrated energy system (RIES) in different situations. In this paper, a regional integrated energy system including wind turbines, photovoltaics, gas turbines and battery energy storage was introduced. In order to obtain the minimum operation cost, an operation optimization model was built. The schedule plans of each unit were optimized by a moth flame optimization (MFO) algorithm. Finally, three different scenarios were proposed for the simulation optimization. The simulation optimization results show that when the BESS is used as a backup power source, the operating cost of the system and the resulting pollutant emissions are less than the diesel generator (DG) set. Therefore, it is worthwhile to use BESS instead of DG as the backup power source in RIES.

Description: Solar power’s variability makes managing power system planning and operation difficult. Facilitating a high level of integration of solar power resources into a grid requires maintaining the fundamental power system so that it is stable when interconnected. Accurate and reliable forecasting helps to maintain the system safely given large-scale solar power resources; this paper therefore proposes a probabilistic forecasting approach to solar resources using the R statistics program, applying a hybrid model that considers spatio-temporal peculiarities. Information on how the weather varies at sites of interest is often unavailable, so we use a spatial modeling procedure called kriging to estimate precise data at the solar power plants. The kriging method implements interpolation with geographical property data. In this paper, we perform day-ahead forecasts of solar power based on the probability in one-hour intervals by using a Naïve Bayes Classifier model, which is a classification algorithm. We augment forecasting by taking into account the overall data distribution and applying the Gaussian probability distribution. To validate the proposed hybrid forecasting model, we perform a comparison of the proposed model with a persistence model using the normalized mean absolute error (NMAE). Furthermore, we use empirical data from South Korea’s meteorological towers (MET) to interpolate weather variables at points of interest.

Description: Sustainable mobility has received increasing attention in recent years. The transport sector contributes to almost a quarter of Europe’s greenhouse gas emissions. The development of electric vehicles (EVs) may help the shift toward sustainable mobility, reducing oil vulnerability and greenhouse gas emissions in road transport. Poor penetration of EVs might be explained, moreover, by consumer resistance to EVs. The aim of our paper is to determine consumers’ attitude and preferences for EVs, investigating which conditions influence consumer decision-making to purchase an EV. Using a fuzzy set qualitative comparative analysis of 421 highly-educated individuals, involving students and faculty members, we identify several configurations of conditions of the variables which lead to the outcomes, supporting their equifinality and asymmetric nature. Our findings indicate attitudes related to EVs differ across age and groups. Our paper offers public decision makers new useful insights for understanding the importance of specific determinants, and for designing effective strategies for EVs’ development worldwide.

Description: In an attempt to ensure sustainable water resource development, this paper constructs a comprehensive scientific index evaluation system focused on the macro socio-economic-ecological environment. Inspired by the theory of dissipative structure, the sustainable development system of water resources is regarded as a complex and huge dissipative system. In order to effectively measure the coordinated development status and orderly evolution trend of the system, this paper uses the information entropy method to construct the measurement model of the water resources system and analyze its internal entropy flow changes. The empirical analysis of the water resources in China from 2007 to 2016 found that coordinated water resource subsystem development could achieve sustainable development, and that over the examined period, the sustainable water resource development system in China became more orderly and coordinated; therefore, the sustainable development aim is gradually being achieved.

Description: This article discusses the main issues associated with waste from mining activity, which is the largest group of combined waste in Poland. A series of domestic and foreign solutions (practical and laboratory solutions) were indicated here, aimed at the management of waste in accordance with the tendency of circular economy (CE). In connection with the legislative changes, there is a need to resign from storage of the waste that is recyclable. The authors indicate mining waste as a potential for further studies, searching for solutions in regard to the use of waste as a raw material for sustainable, secondary use/reuse. Based on EUROSTAT data, the types of waste from mining and quarrying were grouped and the juxtaposition of all waste generated in Poland was implemented in the context of selected European economies. It was indicated which types of waste can be identified for reuse and management in accordance with CE. Rational management of mineral raw materials and therefore, maintaining of the level of extraction of domestic natural resources will contribute to maintaining not only energy independence, but also the leading position of Polish mining in the international aspect in the scope of extraction of metallic and rock raw materials. Mining waste can be and is reused in accordance with the concept of CE, which was showed through the example of domestic industry enterprises and their business models.

Description: The ternary pH buffer system with ammonia-carbonates-volatile fatty acids (VFAs) is essential to anaerobes for bioenergy recovery via anaerobic digestion (AD). However, ammonia and VFAs are recognized as potential inhibitors that depress methanogenesis. In this study, biochemical conversion and the microbial community in batch AD at total solid (TS) from 4% to 14% were investigated to reveal their response to the ternary pH buffer system. The rapid ammonia release, probably promoted by Anaerosphaera and Eubacterium inferred from the concurrent peak of their relative abundance, triggered total ammonia (TAN) inhibition with the accumulation of VFAs in the start-up stage of high solid AD (HSAD, TS ≥ 8%). Along with evolution of the microbial community to resist high TAN and VFAs, methanogenesis recovered with improved degradation of VFAs and reduction of COD. When exposed to 3500 mg·N·L−1 TAN at 8% TS, aceticlastic Methanosarcina became dominant first and then together with hydrogenotrophic Methanoculleus, achieved the optimal biochemical conversion. While in HSAD at 11–14% TS, the main pathway of methanogenesis appeared to have shifted from the aceticlastic pathway to the hydrogenotrophic pathway, as inferred by changes in the relative abundance of methanogens, and this could have been induced by the increasing concentration of high free ammonia (FAN, ≥588 mg·N·L−1). Although the anaerobes had acclimatized to high TAN, the propionate-oxidizing bacteria and acetate-oxidizing bacteria might have again been inhibited by high FAN, frustrating the H2 supply for FAN-tolerant Methanoculleus and causing an 8.2–11.3% depression of COD reduction (mainly propionate residual).

Description: Occlusion over ear surfaces results in performance degradation of ear registration and recognition systems. In this paper, we propose an occlusion-resistant three-dimensional (3D) ear recognition system consisting of four primary components: (1) an ear detection component, (2) a local feature extraction and matching component, (3) a holistic matching component, and (4) a decision-level fusion algorithm. The ear detection component is implemented based on faster region-based convolutional neural networks. In the local feature extraction and matching component, a symmetric space-centered 3D shape descriptor based on the surface patch histogram of indexed shapes (SPHIS) is used to generate a set of keypoints and a feature vector for each keypoint. Then, a two-step noncooperative game theory (NGT)-based method is proposed. The proposed symmetric game-based method is effectively applied to determine a set of keypoints that satisfy the rigid constraints from initial keypoint correspondences. In the holistic matching component, a proposed variant of breed surface voxelization is used to calculate the holistic registration error. Finally, the decision-level fusion algorithm is applied to generate the final match scores. Evaluation results from experiments conducted show that the proposed method produces competitive results for partial occlusion on a dataset consisting of natural and random occlusion.

Description: (1) Background: Several researches have shown the relationship between healthy habits and physical and mental health. Thus, it is essential to study how some psychosocial factors can promote positive behaviours in university students, specifically in those who will be teachers of Physical Education. (2) Methods: This descriptive and cross-sectional research was conducted on 775 university students of Physical Education from Spain. This study aims to develop an explanatory model for the relationships between motivational climate, healthy habits (Mediterranean Diet (MD), Physical Activity (PA) and substance consumption) and some indicators of physical health (oxygen consumption (VO2MAX)) and mental health (self-concept) according to gender, using structural equations analysis. (3) Results: The motivational climate was positively associated with PA, showing a stronger relationship for ego-oriented climate in women. The adherence to MD showed a positive association with PA and self-concept, while it is negative for the consumption of tobacco in men. Likewise, PA was directly related to VO2MAX with a higher regression weight for women. The ego-oriented motivational climate was negatively related to tobacco consumption in women. (4) Conclusions: Task-oriented goals are related to more positive and healthy behaviours such as PA, although it was no association was found with MD. Therefore, we can conclude the importance of promoting task-oriented goals in educational contexts linked to Physical Education in order to avoid negative behaviours.

Description: In the experiment of inertial confinement fusion, soft X-ray spectrum unfolding can provide important information to optimize the design of the laser and target. As the laser beams increase, there are limited locations for installing detection channels to obtain measurements, and the soft X-ray spectrum can be difficult to recover. In this paper, a novel recovery method of soft X-ray spectrum unfolding based on compressive sensing is proposed, in which (1) the spectrum recovery is formulated as a problem of accurate signal recovery from very few measurements (i.e., compressive sensing), and (2) the proper basis atoms are selected adaptively over a Legendre orthogonal basis dictionary with a large size and Lasso regression in the sense of ℓ1 norm, which enables the spectrum to be accurately recovered with little measured data from the limited detection channels. Finally, the presented approach is validated with experimental data. The results show that it can still achieve comparable accuracy from only 8 spectrometer detection channels as it has previously done from 14 detection channels. This means that the presented approach is capable of recovering spectrum from the data of limited detection channels, and it can be used to save more space for other detectors.

Description: Digital volume correlation (DVC), combined with in situ synchrotron microcomputed tomography (SR-microCT) mechanics, allows for 3D full-field strain measurement in bone at the tissue level. However, long exposures to SR radiation are known to induce bone damage, and reliable experimental protocols able to preserve tissue properties are still lacking. This study aims to propose a proof-of-concept methodology to retain bone tissue integrity, based on residual strain determination using DVC, by decreasing the environmental temperature during in situ SR-microCT testing. Compact and trabecular bone specimens underwent five consecutive full tomographic data collections either at room temperature or 0 °C. Lowering the temperature seemed to reduce microdamage in trabecular bone but had minimal effect on compact bone. A consistent temperature gradient was measured at each exposure period, and its prolonged effect over time may induce localised collagen denaturation and subsequent damage. DVC provided useful information on irradiation-induced microcrack initiation and propagation. Future work is necessary to apply these findings to in situ SR-microCT mechanical tests, and to establish protocols aiming to minimise the SR irradiation-induced damage of bone.

Description: The exploration of new food sources and natural products is the result of the increase in world population as well as the need for a healthier diet; in this context, microalgae are undoubtedly an interesting solution. With the intent to enhance their value in new commercial applications, this paper aims to characterize microalgae that have already been recognized as safe or authorized as additives for humans and animals (Chlorella vulgaris, Arthrospira platensis, Haematococcus pluvialis, Dunaliella salina) as well as those that have not yet been marketed (Scenedesmus almeriensis and Nannocholoropsis sp.). In this scope, the content of proteins, carbohydrates, lipids, total dietary fiber, humidity, ash, and carotenoids has been measured via standard methods. In addition, individual carotenoids (beta-carotene, astaxanthin, and lutein) as well as individual saturated, monounsaturated, and polyunsaturated fatty acids have been identified and quantified chromatographically. The results confirm the prerogative of some species to produce certain products such as carotenoids, polyunsaturated fatty acids, and proteins, but also show how their cellular content is rich and diverse. H. pluvialis green and red phases, and Nannochloropsis sp., in addition to producing astaxanthin and omega-3, contain about 25–33% w/w proteins on a dry basis. D. salina is rich in beta-carotene (3.45% w/w on a dry basis), S. Almeriensis is a source of lutein (0.30% w/w on a dry basis), and the C. vulgaris species is a protein-based microalgae (45% w/w on a dry basis). All, however, can also produce important fatty acids such as palmitic acid, γ-linolenic acid, and oleic acid. Considering their varied composition, these microalgae can find applications in multiple sectors. This is true for microalgae already on the market as well as for promising new sources of bioproducts such as S. almeriensis and Nannochloropsis sp.

Description: The study assessed changes in water quality between the water source and the tap of locally produced low cost ceramic water filters used by a community living in hygienically critical conditions in a remote mountainous area in Western Nepal. Data was collected from 42 rural households during two visits. The effectiveness of filter handling on its performance was assessed through microbiological analysis, structured household interviews and structured observations. Water quality decreased significantly when source water was filled into transport containers, while the use of the filters improved drinking water quality for about 40% of the households. Highly inadequate filter cleaning practices involving the use of contaminated raw water, hands (geo mean = 110 E. coli CFU/100 mL) and cleaning tools (geo mean = 80 E. coli CFU/100 mL) stained hygienic parts of the filter. The use of boiling water to disinfect the filters was significantly correlated with improved filter performance and should be further promoted. However, even disinfected filters achieved a very low average LRV for E. coli of 0.4 in the field and performed worse than during laboratory tests (LRV for E. coli of 1.5–2). Comprehensive training on adequate filter handling, as well as better filter products, are required to improve the impact of filter use.

Description: Understanding the amount of degradation using nondestructive evaluation (NDE) methods provides an effective way of determining the fitness to service and the residual life of structural components. Due to uncertainties introduced by the single NDE method, a combined damage index using multi-sensor data increases the reliability of damage assessment. In this paper, the outputs of three NDE methods including acoustic emission (AE), linear ultrasonics (LUT), and nonlinear ultrasonics (NLUT) are merged to identify the amount of plastic deformation in aluminum 1100. The sensitivities of individual and combined methods to microstructural changes are evaluated. The coupon samples are loaded up to different strain levels and then unloaded. AE data is recorded in real time and ultrasonic data is recorded from the unloaded samples. The major features combined in the damage index are cumulative AE absolute energy and nonlinear coefficient. The microstructural state is verified with microscopic analysis and hardness testing. The developed damage index can nondestructively assess the amount of plastic deformation with higher reliability.

Description: The relationship between energy drink (ED) use and risky behaviours has not been explored in the Caribbean, where youth risky behaviours are prevalent. This paper examines the relationship between ED use and risky behaviours and the moderating effect of gender among 1994 undergraduate students in Trinidad and Tobago. Analyses examined the association between ED use and risky behaviours, and the significant predictors of risky behaviours. Analysis of variance determined whether there were differences in risky behaviours between those who used only alcohol or EDs, both alcohol and EDs, alcohol mixed with EDs and neither alcohol nor EDs; and the difference between those with high and low intensity of ED use. In both males and females current use of energy drinks was positively associated with harmful substance use, risky sexual behaviours, and risky non-sexual behaviours, more strongly for males. The strongest predictor of risky behaviours was gender. Males consuming both alcohol and EDs, independently or mixed, were most likely to have risky behaviours. Consistent with previous reports, harmful alcohol use and other risk taking health behaviours appear to be predicted by a combination of high intensity use of EDs and alcohol. In countries like Trinidad and Tobago where violence, alcohol use disorders, STI/HIV infection and teenaged pregnancy are prevalent, the assessment of consumption of EDs and alcohol may be an important potential predictor of health compromising behaviours.

Description: We show that, based on important reasons, differently from some recent claim in the literature, the YARK theory of gravity can reproduce neither the LIGO “GW150914 signal”, nor the other LIGO detections of gravitational waves (GWs).

Description: In this study, we derive, in the framework of mimetic theory, charged and non-charged black hole solutions for spherically symmetric as well as flat horizon spacetimes. The asymptotic behavior of those black holes behave as flat or (A)dS spacetimes and coincide with the solutions derived before in general relativity theory. Using the field equations of non-linear electrodynamics mimetic theory we derive new black hole solutions with monopole and quadrupole terms. The quadruple term of those black holes is related by a constant so that its vanishing makes the solutions coincide with the linear Maxwell black holes. We study the singularities of those solutions and show that they possess stronger singularity than the ones known in general relativity. Among many things, we study the horizons as well as the heat capacity to see if the black holes derived in this study have thermodynamical stability or not.

Description: Recently, the emergence of low-cost sensors have allowed electronic noses to be considered for densifying the actual air pollution monitoring networks in urban areas. Electronic noses are affected by changes in environmental conditions and sensor drifts over time. Therefore, they need to be calibrated periodically and also individually because the characteristics of identical sensors are slightly different. For these reasons, the calibration process has become very expensive and time consuming. To cope with these drawbacks, calibration transfer between systems constitutes a satisfactory alternative. Among them, direct standardization shows good efficiency for calibration transfer. In this paper, we propose to improve this method by using kernel SPXY (sample set partitioning based on joint x-y distances) for data selection and support vector machine regression to match between electronic noses. The calibration transfer approach introduced in this paper was tested using two identical electronic noses dedicated to monitoring nitrogen dioxide. Experimental results show that our method gave the highest efficiency compared to classical direct standardization.

Description: The application of paper sludge ash as an additive in controlling the leaching of trace elements has been satisfactorily effective to date. Previous studies have found that paper sludge ash has a promising effect in controlling the leaching of arsenic, selenium and boron. The content of calcium oxide in paper sludge ash is believed to be one of the important factors in decreasing the concentration of trace elements in leachate. Therefore, this study aimed to verify the effect of paper sludge ash in the leaching process and to propose an effective and applicable suppressing material that can control the leaching of As, Se, B and F simultaneously. In light of this aim, Ca(OH)2, PS ash 8 and blast furnace cement (BF cement) were tested as single and mixed additives in two different coal fly ashes (FA C and FA H). The results indicate that the application of a mixture of additives is necessary to control the leaching of trace elements. A mixture of PS ash 8, Ca(OH)2 and blast furnace cement (BF cement) was proposed to be an applicable and suitable additive that could suppress arsenic, selenium, boron, and fluorine leaching simultaneously.

Description: This paper assesses the long-term wind energy potential at three selected sites, namely Mersing and Kijal on the east coast of peninsular Malaysia and Kudat in Sabah. The influence of the El Niño-Southern Oscillation on reanalysis and meteorological wind data was assessed using the dimensionless median absolute deviation and wavelet coherency analysis. It was found that the wind strength increases during La Niña events and decreases during El Niño events. Linear sectoral regression was used to predict the long-term wind speed based on the 35 years of extended Climate Forecast System Reanalysis data and 10 years of meteorological wind data. The long-term monthly energy production was computed based on the 1.5 MW Goldwind wind turbine power curve. The measured wind data were extrapolated to the selected wind turbine default hub height (70 m.a.s.l) by using the site-specific power law indexed. The results showed that the capacity factor is higher during the Northeast monsoon (21.32%) compared to the Southwest monsoon season (3.71%) in Mersing. Moreover, the capacity factor in Kijal is also higher during the Northeast monsoon (10.66%) than during the Southwest monsoon (5.19%). However, in Kudat the capacity factor during the Southwest monsoon (36.42%) is higher compared to the Northeast monsoon (24.61%). This is due to the tail-effect of tropical storms that occur during this season in the South China Sea and Pacific Ocean.

Description: Background: People on long-term sick leave often have a long-lasting process back to work, where the individuals may be in multiple and recurrent states; i.e., receiving different social security benefits or working, and over time they may shift between these states. The purpose of this study was to evaluate the effects of two vocational rehabilitation programs, compared to a control, on return-to-work (RTW) or increased employability in patients on long-term sick leave due to mental illness and/or chronic pain. Methods: In this randomized controlled study, 427 women and men were allocated to either (1) multidisciplinary team management, i.e., multidisciplinary assessments and individual rehabilitation management, (2) acceptance and commitment therapy (ACT), or (3) control. A positive outcome was defined as RTW or increased employability. The outcome was considered negative if the (part-time) wage was reduced or ceased, or if there was an indication of decreased employability. The outcome was measured one year after entry in the project and analyzed using binary and multinomial logistic regressions. Results: Participants in the multidisciplinary team group reported having RTW odds ratio (OR) 3.31 (95% CI 1.39–7.87) compared to the control group in adjusted models. Participants in the ACT group reported having increased employability OR 3.22 (95% CI 1.13–9.15) compared to the control group in adjusted models. Conclusions: This study of vocational rehabilitation in mainly female patients on long-term sick leave due to mental illness and/or chronic pain suggests that multidisciplinary team assessments and individually adapted rehabilitation interventions increased RTW and employability. Solely receiving the ACT intervention also increased employability.

Description: Decreasing trends in birth rates in developed countries during the past decades, which threaten the sustainability of their populations, raise concerns in the areas of employment and social security, among others. A decrease in willingness to bear children has been examined in the international literature from several (biological, socio-cultural, economic, and spatial, etc.) aspects. Among these, the question of the effectiveness of fiscal incentives has been raised, with arguments that these are positive, but not significant, to birth rates; our study also concludes this. In Hungary, from 2010 onwards, the government has introduced very high tax allowances for families and, from 2015, has provided direct subsidies for housing purposes, all within a framework of a new family policy regime. This paper presents an evaluation of family policy interventions (e.g., housing support, tax allowances, other child-raising benefits), with the conclusion that fiscal incentives cannot be effective by themselves; a sustainable level of birth rates can only be maintained, but not necessarily increased, with an optimal design of family policy incentives. By studying the Hungarian example of pro-birth policies there is shown to be a policy gap in housing subsidies.

Description: In recent years, China has been vigorously carrying out the planning and implementation of Sponge City. Since the implementation of Sponge City projects involves substantial materials and energy consumption, it is significant to account corresponding carbon emissions and sinks. The existed studies about carbon emission of stormwater management measures, however, are not able to take the whole life cycle and different facilities into consideration. Therefore, this study develops a comprehensive accounting model based on Intergovernmental Panel on Climate Change (IPCC) guidelines and life cycle assessment (LCA) method to predict carbon emissions and carbon sinks of Sponge City projects more comprehensively and accurately. The model is applied to an actual residential community in Shanghai as a case study. Results show that the total indirect carbon emission is estimated to be 774,277 kg CO2 eq during a 30-year lifespan, among which carbon emissions from operation and maintenance phases are 2570 kg CO2 eq/year and 7309 kg CO2 eq/year, respectively, both directly proportional to the service life of the facilities. Three kinds of achievable carbon sinks are carbon sequestration in green space (5450 kg CO2 eq/year), carbon sink from rainwater utilization (15,379 kg CO2 eq/year) and carbon sink from runoff pollutant removal (19,552 kg CO2 eq/year). Carbon neutrality is expected to be reached after approximately 19 years. The established carbon emission accounting model can contribute to better planning and construction of Sponge City in China and enhance further energy conservation and carbon emission reduction.

Description: European countries are split over the appreciation of wild berries, fruits, mushrooms, and herbs. While some countries provide public statistics on wild plants, others seem to neglect wild plant gathering and commercialization. In this study, we aimed to understand if wild plant commercialization is neglected or irrelevant in Austria, a country that does not provide statistics. We focus on organic producers, because organic certification of wild plant gathering might have potential for countering frequent concerns about commercial gathering, including destructive gathering and overharvesting. Using a mixed-methods approach with a concurrent triangulation design, databases of six organic certification bodies were analysed concurrently with semi-structured expert interviews of their representatives. We found that organic certification for gathering was issued to 1.5% of organic producers in the year 2016 in Austria and is relevant for three distinct gatherer types: regular, diversified, and single-plant gatherers. Organic gathering is most frequently part of agricultural or horticultural farms and rarely an isolated commercial activity. It is related to mixed farming, deepening on-farm diversification, and contributes to maintaining traditions, as well as the local socio-ecological memory of wild plant products. Organic wild plants are directly marketed to consumers as traditional and innovative products, but also supplied to mass markets. We conclude that from a socio-cultural perspective and a focus on regional economies, organic gathering is neglected in Austria, whereas from an income perspective, wild plant gathering seems to be indeed relevant for few organic producers, although exhibiting potential.

Description: Changes in the flow regime of the Yangtze River were investigated using an efficient framework that combined the eco-flow metrics (ecosurplus and ecodeficit) and Indicators of Hydrologic Alteration (IHA) metrics. A distributed hydrological model was used to simulate the natural flow regime and quantitatively separate the impacts of reservoir operation and climate variation on flow regime changes. The results showed that the flow regime changed significantly between the pre-dam and post-dam periods in the main channel and major tributaries. Autumn streamflow significantly decreased in the main channel and in the tributaries of the upper Yangtze River, as a result of a precipitation decrease and reservoir water storage. The release of water from reservoirs to support flood regulation resulted in a significant increase in winter streamflow in the main channel and in the Minjiang, Wujiang, and Hanjiang tributaries. Reservoir operation and climate variation caused a significant reduction in low flow pulse duration in the middle reach of the Yangtze River. Reservoir operation also led to an increase in the frequency of low flow pulses, an increase in the frequency of flow variation and a decrease in the rate of rising flow in most of the tributaries. An earlier annual minimum flow date was detected in the middle and lower reaches of the Yangtze River due to reservoir operation. This study provides a methodology that can be implemented to assess flow regime changes caused by dam construction in other large catchments.

Description: In the second decade of the 21st century, social media changed the nature of communication and cooperation between participants of the culture services market. They became, among other things, an important marketing instrument in the area of contact with the customers of the cultural offer. However, despite their growing importance in various areas of activity of organisations in the cultural sector, the issue of building the cultural institution’s brand equity by social media users is relatively seldom raised. Research on the impact of online consumer activity on brand equity is at an early stage of development. Therefore, this article is an attempt to fill the research gap in this area. The article presents the results of a survey that was conducted in 2018 on a group of 1021 consumers of cultural services, who at the same time regularly used social media. The statistical analysis carried out and the research results obtained prove that the 3C sustainable system (3C means: consumer Consumption, Contribution, Creation) developed by the authors, concerning the activity of consumers of cultural services in social media, stimulates the consumer-based brand equity (CBBE). Statistically significant relations have been observed in particular for CBBE components that are related to the awareness of a cultural institution’s brand and for the relationship related to the perception of its quality.

Description: By means of the time derivatives of Global Navigation Satellite System (GNSS) carrier-phase measurements, the instantaneous velocity of a stand-alone, single GNSS receiver can be estimated with a high precision of a few mm/s; it is feasible to even obtain the level of tenths of mm/s. Therefore, only data from the satellite navigation message are needed, thus discarding any data from a reference network. Combining this method with an efficient movement-detection algorithm opens some interesting applications for geohazard monitoring; an example is the detection of strong earthquakes. This capability is demonstrated for a case study of the 6.5 Mw earthquake of October 30, 2016, near the city of Norcia in Italy; in that region, there are densely deployed GNSS stations. It is shown that GNSS sensors can detect seismic compressional (P) waves, which are the first to arrive at a measurement station. These findings are substantiated by a comparison with data of strong-motion (SM) seismometers. Furthermore, it is shown that the GNSS-only hypocenter localization comes close (less than a kilometer) to the solutions provided by official seismic services. Finally, we conclude that this method can provide important contributions to a real-time geohazard early-warning system.

Description: A numerical method is applied here to simulate the unstable flow and the vibration of a plane gate. A combination of the large eddy simulation (LES) method and the volume of fluid (VOF) model is used to predict the three-dimensional flow field in the vicinity of a plane gate with submerged discharge. The water surface profile, the streamline diagrams, the distribution of turbulent kinetic energy, the power spectrum density curve of the fluctuating pressure coefficient at typical points underneath the gate, and the complete vortex distribution around the gate are obtained by LES-VOF numerical calculation. The vibration parameters of the gate are calculated by the fluid-structure coupling interface transferring the hydrodynamic load. A simultaneous sampling experiment is performed to verify the validity of the algorithm. The calculated results are then compared with experimental data. The difference between the two is acceptable and the conclusions are consistent. In addition, the influence of the vortex in the slot on the flow field and the vibration of the gate are investigated. It is feasible to replace the experiment with the fluid-structure coupling computational method, which is useful for studying the flow-induced vibration mechanism of plane gates.

Description: Since the 1940s, infrared (IR) detection and imaging at wavelengths in the two atmospheric windows of 3 to 5 and 8 to 14 μm has been extensively researched. Through several generations, these detectors have undergone considerable developments and have found use in various applications in different fields including military, space science, medicine and engineering. For the most recently proposed generation, these detectors are required to achieve high-speed detection with spectral and polarization selectivity while operating at room temperature. Antenna coupled IR detectors appear to be the most promising candidate to achieve these requirements and has received substantial attention from research in recent years. This paper sets out to present a review of the antenna coupled IR detector family, to explore the main concepts behind the detectors as well as outline their critical and challenging design considerations. In this context, the design of both elements, the antenna and the sensor, will be presented individually followed by the challenging techniques in the impedance matching between both elements. Some hands-on fabrication techniques will then be explored. Finally, a discussion on the coupled IR detector is presented with the aim of providing some useful insights into promising future work.

Description: The publication presents a comparative study of two fibre-optic sensors in the application of heart rate (HR) and respiratory rate (RR) monitoring of the human body. After consultation with clinical practitioners, two types of non-invasive measuring and analysis systems based on fibre Bragg grating (FBG) and fibre-optic interferometer (FOI) have been designed and assembled. These systems use probes (both patent pending) that have been encapsulated in the bio-compatible polydimethylsiloxane (PMDS). The main advantage of PDMS is that it is electrically non-conductive and, as well as optical fibres, has low permeability. The initial verification measurement of the system designed was performed on four subjects in a harsh magnetic resonance (MR) environment under the supervision of a senior radiology assistant. A follow-up comparative study was conducted, upon a consent of twenty volunteers, in a laboratory environment with a minimum motion load and discussed with a head doctor of the Radiodiagnostic Institute. The goal of the laboratory study was to perform measurements that would simulate as closely as possible the environment of harsh MR or the environment of long-term health care facilities, hospitals and clinics. Conventional HR and RR measurement systems based on ECG measurements and changes in the thoracic circumference were used as references. The data acquired was compared by the objective Bland–Altman (B–A) method and discussed with practitioners. The results obtained confirmed the functionality of the designed probes, both in the case of RR and HR measurements (for both types of B–A, more than 95% of the values lie within the ±1.96 SD range), while demonstrating higher accuracy of the interferometric probe (in case of the RR determination, 95.66% for the FOI probe and 95.53% for the FBG probe, in case of the HR determination, 96.22% for the FOI probe and 95.23% for the FBG probe).

Description: Polar mesocyclones (MCs) are small marine atmospheric vortices. The class of intense MCs, called polar lows, are accompanied by extremely strong surface winds and heat fluxes and thus largely influencing deep ocean water formation in the polar regions. Accurate detection of polar mesocyclones in high-resolution satellite data, while challenging, is a time-consuming task, when performed manually. Existing algorithms for the automatic detection of polar mesocyclones are based on the conventional analysis of patterns of cloudiness and they involve different empirically defined thresholds of geophysical variables. As a result, various detection methods typically reveal very different results when applied to a single dataset. We develop a conceptually novel approach for the detection of MCs based on the use of deep convolutional neural networks (DCNNs). As a first step, we demonstrate that DCNN model is capable of performing binary classification of 500 × 500 km patches of satellite images regarding MC patterns presence in it. The training dataset is based on the reference database of MCs manually tracked in the Southern Hemisphere from satellite mosaics. We use a subset of this database with MC diameters falling in the range of 200–400 km. This dataset is further used for testing several different DCNN setups, specifically, DCNN built “from scratch”, DCNN based on VGG16 pre-trained weights also engaging the Transfer Learning technique, and DCNN based on VGG16 with Fine Tuning technique. Each of these networks is further applied to both infrared (IR) and a combination of infrared and water vapor (IR + WV) satellite imagery. The best skills (97% in terms of the binary classification accuracy score) is achieved with the model that averages the estimates of the ensemble of different DCNNs. The algorithm can be further extended to the automatic identification and tracking numerical scheme and applied to other atmospheric phenomena that are characterized by a distinct signature in satellite imagery.

Description: Three-dimensional (3D) imaging has attracted more and more interest because of its widespread applications, especially in information and life science. These techniques can be broadly divided into two types: ray-based and wavefront-based 3D imaging. Issues such as imaging quality and system complexity of these techniques limit the applications significantly, and therefore many investigations have focused on 3D imaging from depth measurements. This paper presents an overview of 3D imaging from depth measurements, and provides a summary of the connection between the ray-based and wavefront-based 3D imaging techniques.

Description: China has accelerated the pace of shale gas development from 2010. A series of policies were issued by the Chinese government to motivate and regulate shale gas exploration and exploitation. In order to investigate the effectiveness of these policies and provide reference to the policymakers, the most relevant policies from 2010 to 2016 were collected and analyzed. Our study summarized that, in total, eight government agencies issued 25 related policies, which cover all the main problems that impede China’s shale gas industry. With the aid of these policies, the approved research and development (R&D) funds exceed 350 million Chinese yuan (CNY) ($55 million), and over 80 domestic companies participated in exploration rights bidding and nine foreign companies initiated thirteen international cooperation projects. In 2016, China’s shale gas production reached 7.88 × 109 m3, ranking third in the world. However, these policies still have some shortcomings, such as low environmental concerns, weak financial stimulus, and inefficient implementation. Therefore, we suggest that future policy should put particular emphasis on (1) formulating special environmental regulations and determining development scale based on water resource; (2) providing detailed implementation plans and maintaining stable subsidy; (3) enhancing communication and supervision; and (4) establishing a public big data platform.

Description: Optical communication promises to be a high-rate supplement for acoustic communication in short-range underwater applications. In the photic zone of oceanic and coastal waters, underwater optical communication systems are exposed by remaining sunlight. This ambient light generates additional noise in photodetectors, thus degrading system performance. This effect can be diminished by the use of optical filters. This paper investigates light field characteristics of different water types and potential interactions with optical underwater communication. A colored glass and different thin film bandpass filters are examined as filter/detector combinations under varying light and water conditions, and their physical constraints are depicted. This is underlined by various spectral measurements as well as optical signal-to-noise ratio calculations. The importance of matching the characteristics of the light emitting diode (LED) light source, the photodetector, and the filter on the ambient conditions using wider angle of incidents is emphasized.

Description: Thermal and catalytic pyrolysis of virgin low-density polyethylene (LDPE), high-density polyethylene (HDPE), polypropylene (PP) and mixtures of LDPE/PP were carried out in a 200 mL laboratory scale batch reactor at 460 °C in a nitrogen atmosphere. Thermogravimetric analysis (TGA) was carried out to study the thermal and catalytic degradation of the polymers at a heating rate of 10 °C/min. The amount of PP was varied in the LDPE/PP mixture to explore its effect on the reaction. In thermal degradation (TGA) of LDPE/PP blends, a lower decomposition temperature was observed for LDPE/PP mixtures compared to pure LDPE, indicating interaction between the two polymer types. In the presence of a catalyst (CAT-2), the degradation temperatures for the pure polymers were reduced. The TGA results were validated in a batch reactor using PP and LDPE, respectively. The result from thermal pyrolysis showed that the oil product contained significant amounts of hydrocarbons in the ranges of C7–C12 (gasoline range) and C13–C20 (diesel range). The catalyst enhanced cracking at lower temperatures and narrowed the hydrocarbon distribution in the oil towards the lower molecular weight range (C7–C12). The result suggests that the oil produced from catalytic pyrolysis of waste plastics has a potential as an alternative fuel.

Description: Background: All of society is affected by mental health problems, not just a minor, isolated part. Mental health problems represent a major challenge to the global development of community health. This study examined the community health knowledge, perceived beliefs, and associated factors of mental distress (MD) in Mekelle city in Northern Ethiopia. Methods: The current study used a cross-sectional approach calculating a sample of 260 adults living in the two sub-cities of Mekelle city. To select the sample households in each sub-city, systematic random sampling was used. Self-reported questionnaire (SRQ-20 with a cutoff point of 7), and Mental Health Knowledge Schedule (MAKS) instruments were included within the structured questionnaire tool to clarify community occurrence and the level of health mental knowledge. Results: The likelihood of having MD was higher among the study participants who were female, employed, self-employed, and daily alcohol and khat users. The results also showed that the level of mental health knowledge among the participants was low. Conclusions: Factors such as being male, having a higher level of education, and having strong levels of social support were found to be the independent predictors of good mental health and community mental health knowledge.

Description: In this paper, we present a case study of community heritage resources investigation and management, which was a collaborative project conducted by researchers and participants from rural communities. Geotagged photos were obtained using smart phones, and 360-degree panoramas were acquired using a robotic camera system. These images were then uploaded to a web-based GIS (WebGIS) developed using Arches-Heritage Inventory Package (HIP), an open-source geospatial software system for cultural heritage inventory and management. By providing various tools for resources annotation, data exploration, mapping, geovisualization, and spatial analysis, the WebGIS not only serves as a platform for heritage resources database management, but also empowers the community residents to acquire, share, interpret, and analyze the data. The results show that this type of collaborative working model between researcher and community can promote public awareness of the importance of heritage conservation and achieve the research goal more effectively and efficiently.

Description: Growing a second generation energetic plant Miscanthus x giganteus (Mxg) in former military sites appears to be a promising way to use such areas with synergic phytoremediation of contaminants (organic pollutants, potential toxic metals). Effect of Mxg growth on soil microbial communities during a two-year pot experiment with real post-military soil (Sliač, Slovakia) and the effect of potential toxic metal concentration was studied by analyses of microbial activities and phospholipid fatty acids (PLFA). Year-on-year positive changes in microbial community structure and state were detected (higher ratios of G+/G− bacteria and fungal/bacterial PLFA, and a decrease of stress indicators trans/cis and cy/pre PLFA). Portion of gram-positive bacteria correlated negatively with potential toxic metal concentrations; however, the concentration of potential toxic metals was not identified as the main stress factor—the access to bioavailable nutrients was more important. Overall, Mxg growth generally exhibited a positive effect on soil microorganisms.

Description: Large price fluctuations have become a significant character and impede resource allocation in the electricity market. Negative prices and peak load spike prices coexist and represent over-supply and over-demand, respectively. It is important to interpret the impact of these extreme prices on sustainable power management from the perspective of economics. In this paper, we build a principal component analysis (PCA) to assess the impact of the two opposite phenomena on the smart grid electricity system. We perform a big-data study using intra-day data from the Pennsylvania, New Jersey, and Maryland (PJM) electricity system with over 11,000 transmission lines. As the contribution, this paper (1) measures the price fluctuations from the perspective of economics, (2) captures and observes the full-length behavior of negative and spike pricing in a modern smart grid system with multi-transmission lines and high-frequency price updates, and (3) employs methods with distinctive advantages to bring more in-depth findings to interpret the smart grid system. We find that spike prices hold the principal explanatory power for electricity market fluctuation in all the transmission lines. The results are consistent with previous studies about resolutions such as electrical energy storage, transmission capacity upgrade, and demand response.

Description: This paper examined impacts of drought on both physiological and dry matter characteristics of spring maize grown in Liaoning, China in 2016. We compared responses of dry matters of various parts, yield components, leaf photosynthesis, and transpiration to four drought levels: RD (no drought treatment), D1 (drought treatment between the 38th and 65th day after sowing), D2 (drought treatment between the 38th and 79th day after sowing), and D3 (drought treatment between the 53rd and 93rd day after sowing). Results indicate that the long-term drought in either jointing period or tasseling period had a severer impact on the dry matters and yield components than the short-term drought in jointing period. Moreover, the dry matters and the corresponding partitioning coefficients of different parts were distinct. The yield reduction was caused by the decreases of ear length and bald tip ratio during the short-term drought at jointing period, while it was caused by the reductions of ear length, ear diameter, and grain number per spike during the long-term drought in jointing and tasseling periods. Responses of leaf photosynthesis and transpiration to drought were lagging, but reactions of tasseling drought were faster. Leaf photosynthesis and transpiration after a short-term drought in jointing period could recover to an average level but that after the long-term drought in either jointing or tasseling period could not, after irrigation.

Description: In this paper, we study the way the symmetries of a given graph are reflected in its characteristic polynomials. Our aim is not only to find obstructions for graph symmetries in terms of its polynomials but also to measure how faithful these algebraic invariants are with respect to symmetry. Let p be an odd prime and Γ be a finite graph whose automorphism group contains an element h of order p. Assume that the finite cyclic group generated by h acts semi-freely on the set of vertices of Γ with fixed set F. We prove that the characteristic polynomial of Γ , with coefficients in the finite field of p elements, is the product of the characteristic polynomial of the induced subgraph Γ [ F ] by one of Γ \ F . A similar congruence holds for the characteristic polynomial of the Laplacian matrix of Γ .

Description: Uncertainty should be taken into account when establishing multiobjective task assignment models for multiple unmanned combat aerial vehicles (UCAVs) due to errors in the target information acquired by sensors, implicit preferences of the commander for operational objectives, and partially known weights of sensors. In this paper, we extend the stochastic multicriteria acceptability analysis-2 (SMAA-2) method and combine it with integer linear programming to achieve multiobjective task assignment for multi-UCAV under multiple uncertainties. We first represent the uncertain target information as normal distribution interval numbers so that the values of criteria (operational objectives) concerned can be computed based on the weighted arithmetic averaging operator. Thus, we obtain multiple criteria value matrices for each UCAV. Then, we propose a novel aggregation method to generate the final criteria value matrix based on which the holistic acceptability indices are computed by the extended SMAA-2 method. On this basis, we convert the task assignment model with uncertain parameters into an integer linear programming model without uncertainty so as to implement task assignment using the integer linear programming method. Finally, we conduct a case study and demonstrate the feasibility of the proposed method in solving the multiobjective task assignment problem multi-UCAV under multiple uncertainties.

Description: An increase in users’ online searches, the social concern for an efficient management of resources such as water, and the appearance of more and more digital platforms for sustainable purposes to conduct online searches lead us to reflect more on the users’ behavioral intention with respect to search engines that support sustainable projects like water management projects. Another issue to consider is the factors that determine the adoption of such search engines. In the present study, we aim to identify the factors that determine the intention to adopt a search engine, such as Lilo, that favors sustainable water management. To this end, a model based on the Theory of Planned Behavior (TPB) is proposed. The methodology used is the Structural Equation Modeling (SEM) analysis with the Analysis of Moment Structures (AMOS). The results demonstrate that individuals who intend to use a search engine are influenced by hedonic motivations, which drive their feeling of contentment with the search. Similarly, the success of search engines is found to be closely related to the ability a search engine grants to its users to generate a social or environmental impact, rather than users’ trust in what they do or in their results. However, according to our results, habit is also an important factor that has both a direct and an indirect impact on users’ behavioral intention to adopt different search engines.

Description: The application of information technology in all areas represents a significant facilitation of all business processes and activities. A competitive business system is hardly imaginable without adequate information technology. Therefore, this paper evaluates the conditions for the implementation of barcode technology in a warehouse system of a company for the manufacture of brown paper. SWOT (Strengths, Weaknesses, Opportunities, Threats) matrix was formed with a total of 27 elements based on which the benefits of the implementation of barcode technology in the warehouse system need to be analysed. For this purpose, a new fuzzy PIPRECIA (PIvot Pairwise RElative Criteria Importance Assessment) method has been developed to evaluate all elements in SWOT matrix. In addition, a part of the new developed approach includes new fuzzy scales for criterion assessment that are adapted to the methodology required by the fuzzy PIPRECIA method. To determine the consistency of the method, Spearman and Pearson correlation coefficients are applied. The results obtained in this study show that weaknesses are most noticeable in the current system. By implementing barcode technology, it is possible to create opportunities defined in SWOT matrix, which, in a very efficient way, allow elimination of the current weaknesses of the system.

Description: Sparse-signal recovery in noisy conditions is a problem that can be solved with current compressive-sensing (CS) technology. Although current algorithms based on L 1 regularization can solve this problem, the L 1 regularization mechanism cannot promote signal sparsity under noisy conditions, resulting in low recovery accuracy. Based on this, we propose a regularized reweighted composite trigonometric smoothed L 0 -norm minimization (RRCTSL0) algorithm in this paper. The main contributions of this paper are as follows: (1) a new smoothed symmetric composite trigonometric (CT) function is proposed to fit the L 0 -norm; (2) a new reweighted function is proposed; and (3) a new L 0 regularization objective function framework is constructed based on the idea of T i k h o n o v regularization. In the new objective function framework, Contributions (1) and (2) are combined as sparsity regularization terms, and errors as deviation terms. Furthermore, the conjugate-gradient (CG) method is used to optimize the objective function, so as to achieve accurate recovery of sparse signal and image under noisy conditions. The numerical experiments on both the simulated and real data verify that the proposed algorithm is superior to other state-of-the-art algorithms, and achieves advanced performance under noisy conditions.

Description: In this study, a new α-representation of the inexact T2 fuzzy sets programming model (α-RITF2SP) is proposed for water resources planning under uncertainties. The developed model is a hybrid of inexact type-2 (T2) fuzzy sets (FSs) optimal programming based on α-cuts and α-planes (z-slices) algorithms, and both can be used in problems of water resource management without a loss of generality. Therefore, this novel method represents a complementary method to combine both of these algorithms to make inexact T2FSs methods easier and faster for users under uncertainties. This method provides not only a reduction in computations when computing fuzzy functions, but also a map of the primary variable of T2FSs in the secondary membership function. The α-RITF2SP is applied to a real case study of the operation of water resource systems in the southern Min River basin that involves three cities: Xiamen, Zhangzhou, and Quanzhou. The results of the water allocations and benefits have been analyzed. The symptoms of results indicate the higher profit with a higher wastewater treatment rate. It also represents that this model has enhanced abilities and it is relevant and practical as well as can serve as a guide for the development of this regional economy.

Description: In this paper, the design of MEMS piezoresistive out-of-plane shear and normal stress sensor is described. To improve the sensor sensitivity, a methodology by the incorporation of stress concentration regions, namely surface trenches in the proximity of sensing elements was explored in detail. The finite element (FE) model, verified by a five-layer analytical model was developed as a tool to model the performance of the sensor and guide the geometric optimization of the surface trenches. Optimum location and dimensions of the surface trenches have been obtained through a comprehensive FE analysis. The microfabrication and packing scheme was introduced to prototype the sensor with optimum geometric characteristics of surface trenches. Signal output from the prototyped sensor was tested and compared with those from FE simulation. Good agreement has been achieved between the simulation and experimental results. Moreover, the results suggest the incorporation of surface trenches can help improve the sensor sensitivity. More specifically, the sum of signal output from the sensor chip with surface trenches are 4.52, 5.06 and 5.72 times higher compared to flat sensor chip for center sensing area, edge sensing areas 1 and 2, respectively.

Description: Clean-in-place (CIP) processes are extensively used to clean industrial equipment without the need for disassembly. In food manufacturing, cleaning can account for up to 70% of water use and is also a heavy user of energy and chemicals. Due to a current lack of real-time in-process monitoring, the non-optimal control of the cleaning process parameters and durations result in excessive resource consumption and periods of non-productivity. In this paper, an optical monitoring system is designed and realized to assess the amount of fouling material remaining in process tanks, and to predict the required cleaning time. An experimental campaign of CIP tests was carried out utilizing white chocolate as fouling medium. During the experiments, an image acquisition system endowed with a digital camera and ultraviolet light source was employed to collect digital images from the process tank. Diverse image segmentation techniques were considered to develop an image processing procedure with the aim of assessing the area of surface fouling and the fouling volume throughout the cleaning process. An intelligent decision-making support system utilizing nonlinear autoregressive models with exogenous inputs (NARX) Neural Network was configured, trained and tested to predict the cleaning time based on the image processing results. Results are discussed in terms of prediction accuracy and a comparative study on computation time against different image resolutions is reported. The potential benefits of the system for resource and time efficiency in food manufacturing are highlighted.

Description: Bluetooth Low-Energy (BLE) beacons-based indoor positioning is a promising method for indoor positioning, especially in applications of position-based services (PbS). It has low deployment cost and it is suitable for a wide range of mobile devices. Existing BLE beacon-based positioning methods can be categorized as range-based methods and fingerprinting-based methods. For range-based methods, the positions of the beacons should be known before positioning. For fingerprinting-based methods, a pre-requisite is the reference fingerprinting map (RFM). Many existing methods focus on how to perform the positioning assuming the beacon positions or RFM are known. However, in practical applications, determining the beacon positions or RFM in the indoor environment is normally a difficult task. This paper proposed an efficient and graph optimization-based way for estimating the beacon positions and the RFM, which combines the range-based method and the fingerprinting-based method. The method exists without need for any dedicated surveying instruments. A user equipped with a BLE-enabled mobile device walks in the region collecting inertial readings and BLE received signal strength indication (RSSI) readings. The inertial measurements are processed through the pedestrian dead reckoning (PDR) method to generate the constraints at adjacent poses. In addition, the BLE fingerprints are adopted to generate constraints between poses (with similar fingerprints) and the RSSIs are adopted to generate distance constraints between the poses and the beacon positions (according to a pre-defined path-loss model). The constraints are then adopted to form a cost function with a least square structure. By minimizing the cost function, the optimal user poses at different times and the beacon positions are estimated. In addition, the RFM can be generated through the pose estimations. Experiments are carried out, which validates that the proposed method for estimating the pre-requisites (including beacon positions and the RFM). These estimated pre-requisites are of sufficient quality for both range-based and fingerprinting-based positioning.

Description: After the neutrosophic set (NS) was proposed, NS was used in many uncertainty problems. The single-valued neutrosophic set (SVNS) is a special case of NS that can be used to solve real-word problems. This paper mainly studies multigranulation neutrosophic rough sets (MNRSs) and their applications in multi-attribute group decision-making. Firstly, the existing definition of neutrosophic rough set (we call it type-I neutrosophic rough set (NRSI) in this paper) is analyzed, and then the definition of type-II neutrosophic rough set (NRSII), which is similar to NRSI, is given and its properties are studied. Secondly, a type-III neutrosophic rough set (NRSIII) is proposed and its differences from NRSI and NRSII are provided. Thirdly, single granulation NRSs are extended to multigranulation NRSs, and the type-I multigranulation neutrosophic rough set (MNRSI) is studied. The type-II multigranulation neutrosophic rough set (MNRSII) and type-III multigranulation neutrosophic rough set (MNRSIII) are proposed and their different properties are outlined. We found that the three kinds of MNRSs generate tcorresponding NRSs when all the NRs are the same. Finally, MNRSIII in two universes is proposed and an algorithm for decision-making based on MNRSIII is provided. A car ranking example is studied to explain the application of the proposed model.

Description: Detecting the cognitive profiles of learners is an important step towards personalized and adaptive learning. Electroencephalograms (EEG) have been used to detect the subject’s emotional and cognitive states. In this paper, an approach for detecting two cognitive skills, focused attention and working memory, using EEG signals is proposed. The proposed approach consists of the following main steps: first, subjects undergo a scientifically-validated cognitive assessment test that stimulates and measures their full cognitive profile while putting on a 14-channel wearable EEG headset. Second, the scores of focused attention and working memory are extracted and encoded for a classification problem. Third, the collected EEG data are analyzed and a total of 280 time- and frequency-domain features are extracted. Fourth, several classifiers were trained to correctly classify and predict three levels (low, average, and high) of the two cognitive skills. The classification accuracies that were obtained on 86 subjects were 84% and 81% for the focused attention and working memory, respectively. In comparison with similar approaches, the obtained results indicate the generalizability and suitability of the proposed approach for the detection of these two skills. Thus, the presented approach can be used as a step towards adaptive learning where real-time adaptation is to be done according to the predicted levels of the measured cognitive skills.

Description: GPS trajectories generated by moving objects provide researchers with an excellent resource for revealing patterns of human activities. Relevant research based on GPS trajectories includes the fields of location-based services, transportation science, and urban studies among others. Research relating to how to obtain GPS data (e.g., GPS data acquisition, GPS data processing) is receiving significant attention because of the availability of GPS data collecting platforms. One such problem is the GPS data classification based on transportation mode. The challenge of classifying trajectories by transportation mode has approached detecting different modes of movement through the application of several strategies. From a GPS data acquisition point of view, this paper macroscopically classifies the transportation mode of GPS data into single-mode and mixed-mode. That means GPS trajectories collected based on one type of transportation mode are regarded as single-mode data; otherwise it is considered as mixed-mode data. The one big difference of classification strategy between single-mode and mixed-mode GPS data is whether we need to recognize the transition points or activity episodes first. Based on this, we systematically review existing classification methods for single-mode and mixed-mode GPS data and introduce the contributions of these methods as well as discuss their unresolved issues to provide directions for future studies in this field. Based on this review and the transportation application at hand, researchers can select the most appropriate method and endeavor to improve them.

Description: Personalized emotion recognition provides an individual training model for each target user in order to mitigate the accuracy problem when using general training models collected from multiple users. Existing personalized speech emotion recognition research has a cold-start problem that requires a large amount of emotionally-balanced data samples from the target user when creating the personalized training model. Such research is difficult to apply in real environments due to the difficulty of collecting numerous target user speech data with emotionally-balanced label samples. Therefore, we propose the Robust Personalized Emotion Recognition Framework with the Adaptive Data Boosting Algorithm to solve the cold-start problem. The proposed framework incrementally provides a customized training model for the target user by reinforcing the dataset by combining the acquired target user speech with speech from other users, followed by applying SMOTE (Synthetic Minority Over-sampling Technique)-based data augmentation. The proposed method proved to be adaptive across a small number of target user datasets and emotionally-imbalanced data environments through iterative experiments using the IEMOCAP (Interactive Emotional Dyadic Motion Capture) database.

Description: The influence of temperature, CO2 concentration and relative humidity on the carbonation depth and compressive strength of concrete was investigated. Meanwhile, phase composition, types of hydration products and microstructure characteristics of samples before and after the carbonation were analyzed by XRD and ESEM. Research results demonstrate that temperature, CO2 concentration and relative humidity influence the carbonation depth and compressive strength of concrete significantly. There is a linear relationship between temperature and carbonation depth, as well as the compressive strength of concrete. CO2 concentration and relative humidity present a power function and a polynomial function with carbonation depth of concrete, respectively. The concrete carbonation depth increases with the increase of relative humidity and reaches the maximum value when the relative humidity is 70%. Significant differences of phase composition, hydration products and microstructure are observed before and after the carbonation. Carbonization products of samples are different with changes of temperatures (10 °C, 20 °C and 30 °C). The result of crystal structure analysis indicates that the carbonation products are mainly polyhedral spherical vaterite and aragonite.

Description: In this work, a novel type of diatomite was prepared with a limited content of hindered phenol groups grafted on its hydrophobic surface. The obtained samples were characterized for their surface groups, particle morphology, pore structure, and thermal behaviors. Then, modified diatomite (MDT) was used in preparation of reinforced chlorinated butyl rubber (CIIR) composites by mechanical blending method. The powder of MDT can be uniformly dispersed in CIIR matrices and the compatibility was good. In addition, the MDT showed a positive effect on damping performance of CIIR composites. A blending ratio of CIIR/MDT = 100/10 presented the best damping performance and the damping temperature range (tan δ 〉 0.7) was extended from 60 to 70 °C. The variable temperature FTIR spectra showed the presence of hydrogen bonds between the hydroxyl groups and chloride atoms in the CIIR matrices, and a blue shift exhibited when these hydrogen bonds were dissociated. Hence, these CIIR composites provided good damping behaviors and supplied a novel and promising way for preparation of high damping rubber composites with broad temperature ranges.

Description: Solid oxide electrochemical systems, such as solid oxide fuel cells (SOFC), solid oxide electrolysis cells (SOEC), and oxygen transport membranes (OTM) enable clean and reliable production of energy or fuel for a range of applications, including, but not limited to, residential, commercial, industrial, and grid-support. These systems utilize solid-state ceramic oxides which offer enhanced stability, fuel flexibility, and high energy conversion efficiency throughout operation. However, the nature of system conditions, such as high temperatures, complex redox atmosphere, and presence of volatile reactive species become taxing on solid oxide materials and limit their viability during long-term operation. Ongoing research efforts to identify the material corrosion and degradation phenomena, as well as discover possible mitigation techniques to extend material efficiency and longevity, is the current focus of the research and industrial community. In this review, degradation processes in select solid oxide electrochemical systems, system components, and comprising materials will be discussed. Overall degradation phenomena are presented and certain degradation mechanisms are discussed. State-of-the-art technologies to mitigate or minimize the above-mentioned degradation processes are presented.

Description: We demonstrate that the rectifying field effect transistor, biased to the subthreshold regime, in a large signal regime exhibits a super-linear response to the incident terahertz (THz) power. This phenomenon can be exploited in a variety of experiments which exploit a nonlinear response, such as nonlinear autocorrelation measurements, for direct assessment of intrinsic response time using a pump-probe configuration or for indirect calibration of the oscillating voltage amplitude, which is delivered to the device. For these purposes, we employ a broadband bow-tie antenna coupled Si CMOS field-effect-transistor-based THz detector (TeraFET) in a nonlinear autocorrelation experiment performed with picoseconds-scale pulsed THz radiation. We have found that, in a wide range of gate bias (above the threshold voltage V th = 445 mV), the detected signal follows linearly to the emitted THz power. For gate bias below the threshold voltage (at 350 mV and below), the detected signal increases in a super-linear manner. A combination of these response regimes allows for performing nonlinear autocorrelation measurements with a single device and avoiding cryogenic cooling.

Description: Nucleic acid-based aptamers have emerged as efficient delivery carriers of therapeutics. Thanks to their unique features, they can be, to date, considered one of the best targeting moieties, allowing the specific recognition of diseased cells and avoiding unwanted off-target effects on healthy tissues. In this review, we revise the most recent contributes on bispecific and multifunctional aptamer therapeutic chimeras. We will discuss key examples of aptamer-mediated delivery of nucleic acid and peptide-based therapeutics underlying their great potentiality and versatility. Achieved objectives and challenges will be highlighted as well.

Description: The effect of isothermal multidirectional forging (IMF) on the microstructure evolution of a conventional Al–Mg-based alloy was studied in the strain range of 1.5 to 6.0, and in the temperature range of 200 to 500 °C. A mean grain size in the near-surface layer decreased with increasing cumulative strain after IMF at 400 °C and 500 °C; the grain structure was inhomogeneous, and consisted of coarse and fine recrystallized grains. There was no evidence of recrystallization when the micro-shear bands were observed after IMF at 200 and 300 °C. Thermomechanical treatment, including IMF followed by 50% cold rolling and annealing at 450 °C for 30 min, produced a homogeneous equiaxed grain structure with a mean grain size of 5 µm. As a result, the fine-grained sheets exhibited a yield strength and an elongation to failure 30% higher than that of the sheets processed with simple thermomechanical treatment. The IMF technique can be successfully used to produce fine-grained materials with improved mechanical properties.

Description: Current environmental impact analyses are mainly focused on land, soil, energy, and material consumption, while studies regarding blue water consumption are scarce. Based on the water footprint concept, this study evaluates the impacts of blue water consumption on human health, ecosystem quality, and water resources in China from the production and consumption perspective, respectively. The results indicate that environmental impacts due to blue water consumption in China were 15.82 × 106 DALY (disability-adjusted life years), 96.54 × 109 m2∙year, and 175.20 × 109 MJ, and provinces such as Xinjiang, Shandong, and Hebei could be targets for achieving smaller environmental impacts in the future. More than 80% of environmental impacts were related to the agricultural sector. In terms of agricultural production, about 70% of the environmental impacts were related to product export. Measures such as the shift of the agricultural production pattern from water-intensive crops and animal products toward less water-intensive ones, the increase of agricultural water use efficiency, and the adoption of water-saving technologies could contribute to smaller environmental impacts. In terms of agricultural consumption, more than 95% of the environmental impacts were related to agricultural products produced locally. The focus was on increasing awareness of the importance of saving water and whether products were imported from regions with relatively small environmental impacts.

Description: Crack propagation was quantitatively evaluated to investigate the effect of electropulsing treatment (EPT) on fatigue crack growth of copper specimens. Varying fatigue cycles were obtained under six different load levels. The crack lengths were measured under two load levels to examine the effect of cyclic stress. The microhardness was measured around the vicinity of the crack tip. Furthermore, the fracture surface was observed by scanning electron microscopy. Results show that EPT with electric current density of 150 A/mm2 enhances the high-cycle fatigue life, and the effect tends to increase with the decrease in cyclic stress. Vickers microhardness (HV) near the crack tip decreases to normal levels after treatment, and the approaching cracks on two sides can be observed. Local annealing and recrystallization occur around the fatigue crack tip. Accordingly, crack propagation can be delayed, and fatigue life can be prolonged by EPT.

Description: The prevalence of food allergy (FA) has not been estimated at a population level in Central American countries and, consequently, the magnitude and relevance of the problem in the Central American region remains unknown. Thus, our aim was to evaluate the parent-reported prevalence of FA in a population of schoolchildren from the Central American country El Salvador. A Spanish version of a structured questionnaire was utilized. Five hundred and eight (508) parents returned the questionnaire with valid responses (response rate, 32%). The estimated prevalence rates (95% CI) were: adverse food reactions 15.9 (13.0–19.3), “perceived FA, ever” 11.6 (9.1–14.6), “physician-diagnosed FA, ever” 5.7% (4.0–8.0), “immediate-type FA, ever” 8.8% (6.6–11.6), “immediate-type FA, current” 5.3% (3.6–7.6), and anaphylaxis 2.5% (1.5–4.3). The most common food allergens were milk (1.7%), shrimp (1.3), chili (0.7%), chocolate (0.7%), and nuts (0.3%). Most of the “food-dependent anaphylaxis” cases (60.5%) sought medical attention, but only one case reported the prescription of an epinephrine autoinjector. Mild and severe FA cases are not uncommon among Salvadoran schoolchildren and both the prescription of epinephrine autoinjectors by healthcare personnel and the use of the autoinjectors by anaphylactic individuals should be encouraged.

Description: The soft magnetic properties of Fe-based nanocrystalline alloys are determined by their grain size. In the present article, the (Fe0.4Co0.6)79Nb3B18 nanocrystalline alloys have been successfully prepared by isothermal annealing. The variation of soft magnetic properties as a function of annealing temperature and incubation time is investigated in detail. Two distinct crystallization behaviors were found for the (Fe0.4Co0.6)79Nb3B18 alloys. The initial nanocrystallization products comprise a mixture of α-Fe(Co), Fe2B, and Fe23B6-type crystalline metastable phases, and the final crystallization products are composed of α-Fe(Co), Fe2B, and Fe3B crystalline phases. The grain size decreases first and then increases with the increasing annealing temperature in the range of 764–1151 K, and a fine grain size with mean grain size of 12.7 nm can be achieved for alloys annealed at 880 K. As the annealing temperature increases from 764 K to 1151 K, the saturation magnetization increases first and then decreases without a significant increase of the coercivity. The alloys annealed at 880 K exhibit the optimized soft magnetic properties with high Ms of 145 emu g−1 and low Hc of 0.04 Oe.

Description: This work contributes to the literature in the field of innovation by proposing a quantitative approach for the prediction of the timing and location of patenting activity. In a recent work, it was shown that focusing on couples of technological codes allows for the formation of testable predictions of innovation events, defined as the first time two codes appear together in a patent. In particular, the construction of the vector space of codes and the introduction of the context similarity metric allows for a quantitative analysis of technological progress. Here, we move from that result and we show that, through context similarity, it is possible to assign to countries a score which measures the probability of being the first to patent a potential innovation. In other words, we show that we can not only estimate the likelihood that a potential innovation will be patented in the imminent future, but also forecast where it will be patented.

Description: This study examines the relationship between sustainability managed against downside risk and the cost of equity in the Korean stock market during the 2000–2016 period. We employ downside co-skewness and downside beta as a measure of downside risk, to analyze the cross-sectional relationship between them and average portfolio stock returns. We have also carried out Fama–MacBeth regressions to find the required return for bearing downside risk. The results show that downside co-skewness can be used more effectively than downside beta to explain a cross-section of stock returns or cost of equity. The required premium for bearing downside risk, as measured by downside co-skewness, is approximately 19% per annum in the Korean stock market. This finding suggests that sustainable companies can raise their capital in the form of equity at 19% lower costs, and also implies that increasing sustainability can reduce the cost of capital.