ALBERT

Description: Materials based on biodegradable polyesters, such as poly(butylene terephthalate) (PBT) or poly(butylene terephthalate-co-poly(alkylene glycol) terephthalate) (PBTAT), have potential application as pro-regenerative scaffolds for bone tissue engineering. Herein, the preparation of films composed of PBT or PBTAT and an engineered spider silk protein, (eADF4(C16)), that displays multiple carboxylic acid moieties capable of binding calcium ions and facilitating their biomineralization with calcium carbonate or calcium phosphate is reported. Human mesenchymal stem cells cultured on films mineralized with calcium phosphate show enhanced levels of alkaline phosphatase activity suggesting that such composites have potential use for bone tissue engineering.

Description: The objective of this study was to assess the performance of the simulated start of the photosynthetically active season by a large-scale biosphere model in boreal forests in Finland with remote sensing observations. The start of season for two forest types, evergreen needle- and deciduous broad-leaf, was obtained for the period 2003–2011 from regional JSBACH (Jena Scheme for Biosphere–Atmosphere Hamburg) runs, driven with climate variables from a regional climate model. The satellite-derived start of season was determined from daily Moderate Resolution Imaging Spectrometer (MODIS) time series of Fractional Snow Cover and the Normalized Difference Water Index by applying methods that were targeted to the two forest types. The accuracy of the satellite-derived start of season in deciduous forest was assessed with bud break observations of birch and a root mean square error of seven days was obtained. The evaluation of JSBACH modelled start of season dates with satellite observations revealed high spatial correspondence. The bias was less than five days for both forest types but showed regional differences that need further consideration. The agreement with satellite observations was slightly better for the evergreen than for the deciduous forest. Nonetheless, comparison with gross primary production (GPP) determined from CO2 flux measurements at two eddy covariance sites in evergreen forest revealed that the JSBACH-simulated GPP was higher in early spring and led to too-early simulated start of season dates. Photosynthetic activity recovers differently in evergreen and deciduous forests. While for the deciduous forest calibration of phenology alone could improve the performance of JSBACH, for the evergreen forest, changes such as seasonality of temperature response, would need to be introduced to the photosynthetic capacity to improve the temporal development of gross primary production.

Description: An innovative remote sensing approach that combines land-use change and water quality information is proposed in order to investigate if Artisanal and Small-scale Gold Mining (ASGM) area extension is associated with water siltation in the Tapajós River Basin (Brazil), containing the largest small-scale gold mining district in the world. Taking advantage of a 40-year period of the multi-satellite imagery archive, the objective of this paper is to build a normalized time-series in order to evaluate the influence of temporal mining expansion on the water siltation data (TSS, Total Suspended Solids concentration) derived from previous research. The methodological approach was set to deliver a full characterization of the ASGM expansion from its initial stages in the early 1970s to the present. First, based on IRS/LISSIII images acquired in 2012, the historical Landsat image database (1973–2001) was corrected for radiometric and atmospheric effects using dark vegetation as reference to create a normalized time-series. Next, a complete update of the mining areas distribution in 2012 derived from the TerraClass Project (an official land-use classification for the Brazilian Amazon) was conducted having IRS/LISSIII as the base map with the support of auxiliary data and vector editing. Once the ASGM in 2012 was quantified (261.7 km2) and validated with photos, a reverse classification of ASGM in 2001 (171.7 km2), 1993 (166.3 km2), 1984 (47.5 km2), and 1973 (15.4 km2) with the use of Landsat archives was applied. This procedure relies on the assumption that ASGM changes in the land cover are severe and remain detectable from satellite sensors for decades. The mining expansion area over time was then combined with the (TSS) data retrieved from the same atmospherically corrected satellite imagery based on the literature. In terms of gold mining expansion and water siltation effects, four main periods of ASGM activities were identified in the study area: (i) 1958–1977, first occurrence of mining activities and low water impacts; (ii) 1978–1993, introduction of low-budget mechanization associated with very high gold prices resulting in large mining area expansion and high water siltation levels; (iii) 1994–2003, general recession of ASGM activities and exhaustion of easy-access gold deposits, resulting in decreased TSS; (iv) 2004 to present, intensification of ASGM encouraged by high gold prices, resulting in an increase of TSS.

Description: Current earth observation models do not take into account the influence of water salinity on the evaporation rate, even though the salinity influences the evaporation rate by affecting the density and latent heat of vaporization. In this paper, we adapt the SEBS (Surface Energy Balance System) model for large water bodies and add the effect of water salinity to the evaporation rate. Firstly, SEBS is modified for fresh-water whereby new parameterizations of the water heat flux and sensible heat flux are suggested. This is achieved by adapting the roughness heights for momentum and heat transfer. Secondly, a salinity correction factor is integrated into the adapted model. Eddy covariance measurements over Lake IJsselmeer (The Netherlands) are carried out and used to estimate the roughness heights for momentum (~0.0002 m) and heat transfer (~0.0001 m). Application of these values over the Victoria and Tana lakes (freshwater) in Africa showed that the calculated latent heat fluxes agree well with the measurements. The root mean-square of relative-errors (rRMSE) is about 4.1% for Lake Victoria and 4.7%, for Lake Tana. Verification with ECMWF data showed that the salinity reduced the evaporation at varying levels by up to 27% in the Great Salt Lake and by 1% for open ocean. Our results show the importance of salinity to the evaporation rate and the suitability of the adapted-SEBS model (AquaSEBS) for fresh and saline waters.

Description: Area-based analyses of airborne laser scanning (ALS) data are an established approach to obtain wall-to-wall predictions of forest characteristics for vast areas. The analyses of sparse data in particular are based on the height value distributions, which do not produce optimal information on the horizontal forest structure. We evaluated the complementary potential of features quantifying the textural variation of ALS-based canopy height models (CHMs) for both supervised (linear regression) and unsupervised (k-Means clustering) analyses. Based on a comprehensive literature review, we identified a total of four texture analysis methods that produced rotation-invariant features of different order and scale. The CHMs and the textural features were derived from practical sparse-density, leaf-off ALS data originally acquired for ground elevation modeling. The features were extracted from a circular window of 254 m2 and related with boreal forest characteristics observed from altogether 155 field sample plots. Features based on gray-level histograms, distribution of forest patches, and gray-level co-occurrence matrices were related with plot volume, basal area, and mean diameter with coefficients of determination (R2) of up to 0.63–0.70, whereas features that measured the uniformity of local binary patterns of the CHMs performed poorer. Overall, the textural features compared favorably with benchmark features based on the point data, indicating that the textural features contain additional information useful for the prediction of forest characteristics. Due to the developed processing routines for raster data, the CHM features may potentially be extracted with a lower computational burden, which promotes their use for applications such as pre-stratification or guiding the field plot sampling based solely on ALS data.

Description: There are a great variety of joint types used in nature which can inspire engineering joints. In order to design such biomimetic joints, it is at first important to understand how biological joints work. A comprehensive literature review, considering natural joints from a mechanical point of view, was undertaken. This was used to develop a taxonomy based on the different methods/functions that nature successfully uses to attach dissimilar tissues. One of the key methods that nature uses to join dissimilar materials is a transitional zone of stiffness at the insertion site. This method was used to propose bio-inspired solutions with a transitional zone of stiffness at the joint site for several glass fibre reinforced plastic (GFRP) to steel adhesively bonded joint configurations. The transition zone was used to reduce the material stiffness mismatch of the joint parts. A numerical finite element model was used to identify the optimum variation in material stiffness that minimises potential failure of the joint. The best bio-inspired joints showed a 118% increase of joint strength compared to the standard joints.

Description: The production of activated carbons (ACs) from rapeseed cake and raspberry seed cake using slow pyrolysis followed by physical activation of the obtained solid residues is the topic of this study. The effect of activation temperature (850, 900 and 950 °C), activation time (30, 60, 90 and 120 min) and agent (steam and CO2) on the textural characteristics of the ACs is investigated by N2 adsorption. In general, higher activation temperatures and longer activation times increase the BET specific surface area and the porosity of the ACs, regardless of the activation agent or raw material. Steam is more reactive than CO2 in terms of pore development, especially in the case of raspberry seed cake. The performance of the ACs in liquid adsorption is evaluated by batch phenol adsorption tests. Experimental data are best fitted by the Freundlich isotherm model. Based on total yield, textural characteristics and phenol adsorption, steam activation at 900 °C for 90 min and CO2 activation at 900 °C for 120 min are found as the best activation conditions. Raspberry seed cake turns out to be a better raw material than rapeseed cake. Moreover, AC from raspberry seed cake produced by steam activation at 900 °C for 90 min performs as well as commercial AC (Norit GAC 1240) in phenol adsorption. The adsorption kinetics of the selected ACs are best fitted by the pseudo-second-order model.

Description: Inland saline wetlands are complex systems undergoing continuous changes in moisture and salinity and are especially vulnerable to human pressures. Remote sensing is helpful to identify vegetation change in semi-arid wetlands and to assess wetland degradation. Remote sensing-based monitoring requires identification of the spectral characteristics of soils and vegetation and their correspondence with the vegetation cover and soil conditions. We studied the spectral characteristics of soils and vegetation of saline wetlands in Monegros, NE Spain, through field and satellite images. Radiometric and complementary field measurements in two field surveys in 2007 and 2008 were collected in selected sites deemed as representative of different soil moisture, soil color, type of vegetation, and density. Despite the high local variability, we identified good relationships between field spectral data and Quickbird images. A methodology was established for mapping the fraction of vegetation cover in Monegros and other semi-arid areas. Estimating vegetation cover in arid wetlands is conditioned by the soil background and by the occurrence of dry and senescent vegetation accompanying the green component of perennial salt-tolerant plants. Normalized Difference Vegetation Index (NDVI) was appropriate to map the distribution of the vegetation cover if the green and yellow-green parts of the plants are considered.

Description: Extreme heat weather events have received increasing attention and has become of special importance as they can remarkably affect sectors as diverse as public health, energy consumption, water resources, natural biodiversity and agricultural production. In this regard, summer temperatures have become a parameter of essential interest under a framework of a hypothetical increase in the number of intense-heat conditions. Thus, their forecast is a crucial aspect bearing in mind a mitigation of the effects and impacts that these intense-heat situations could produce. The current work tries to reach a better understanding of these sorts of situations that are really common over the Western Mediterranean coast. An extreme heat episode that took place in the Valencia Region in July 2009 is analysed, based on the simulations performed with the Regional Atmospheric Modeling System (RAMS). This event recorded maximum temperatures exceeding 40 °C amply extended over the region besides reaching minimum temperatures up to 25.92 °C. We examine the role of improved skin and soil temperature (ST) initial conditions in the forecast results by means of different modelling and satellite-derived products. The influence of incorporating the Land Surface Temperature (LST) into RAMS is not found to produce a meaningful impact on the simulation results, independently of the resolution of the dataset used in the initial conditions of the model. In contrast, the introduction of the ST in lower levels, not only the skin temperature, has a more marked decisive effect in the simulation. Additionally, we have evaluated the influence of increasing the number of soil levels to spread deeper underground. This sensitivity experiment has revealed that more soil levels do not produce any meaningful impact on the simulation compared to the original one. In any case, RAMS is able to properly capture the observed patterns in those cases where a Western advection is widely extended over the area of study. This region’s variability in orography and in distances to the sea promotes the development of sea-breeze circulations, thus producing a convergence of two opposite wind flows, a Western synoptic advection and a sea-breeze circulation. As a result, the RAMS skill in those cases where a sea breeze is well developed depends on the proper location of the boundary and convergence lines of these two flows.

Description: Spatially explicit knowledge of aboveground biomass (AGB) in large areas is important for accurate carbon accounting and quantifying the effect of forest disturbance on the terrestrial carbon cycle. We estimated AGB from 1990 to 2011 in northern Guangdong, China, based on a spatially explicit dataset derived from six years of national forest inventory (NFI) plots, Landsat time series imagery (1986–2011) and Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radars (PALSAR) 25 m mosaic data (2007–2010). Four types of variables were derived for modeling and assessment. The random forest approach was used to seek the optimal variables for mapping and validation. The root mean square error (RMSE) of plot-level validation was between 6.44 and 39.49 (t/ha), the normalized root-mean-square error (NRMSE) was between 7.49% and 19.01% and mean absolute error (MAE) was between 5.06 and 23.84 t/ha. The highest coefficient of determination R2 of 0.8 and the lowest NRMSE of 7.49% were reported in 2006. A clear increasing trend of mean AGB from the lowest value of 13.58 t/ha to the highest value of 66.25 t/ha was witnessed between 1988 and 2000, while after 2000 there was a fluctuating ascending change, with a peak mean AGB of 67.13 t/ha in 2004. By integrating AGB change with forest disturbance, the trend in disturbance area closely corresponded with the trend in AGB decrease. To determine the driving forces of these changes, the correlation analysis was adopted and exploratory factor analysis (EFA) method was used to find a factor rotation that maximizes this variance and represents the dominant factors of nine climate elements and nine human activities elements affecting the AGB dynamics. Overall, human activities contributed more to short-term AGB dynamics than climate data. Harvesting and human-induced fire in combination with rock desertification and global warming made a strong contribution to AGB changes. This study provides valuable information for the relationships between forest AGB and climate as well as forest disturbance in subtropical zones.

Description: This study investigated the residual tensile properties of plain woven jute fiber reinforced poly(lactic acid) (PLA) during thermal cycling. Temperature ranges of thermal cycling tests were 35–45 °C and 35–55 °C. The maximum number of cycles was 103 cycles. The quasi-static tensile tests of jute fiber, PLA, and composite were conducted after thermal cycling tests. Thermal mechanical analyses of jute fiber and PLA were conducted after thermal cycling tests. Results led to the following conclusions. For temperatures of 35–45 °C, tensile strength of composite at 103 cycles decreased 10% compared to that of composite at 0 cycles. For temperatures of 35–55 °C, tensile strength and Young’s modulus of composite at 103 cycles decreased 15% and 10%, respectively, compared to that of composite at 0 cycles. Tensile properties and the coefficient of linear expansion of PLA and jute fiber remained almost unchanged after thermal cycling tests. From observation of a fracture surface, the length of fiber pull out in the fracture surface of composite at 103 cycles was longer than that of composite at 0 cycles. Therefore, tensile properties of the composite during thermal cycling were decreased, probably because of the decrease of interfacial adhesion between the fiber and resin.

Description: Merging satellite and rain gauge data by combining accurate quantitative rainfall from stations with spatial continuous information from remote sensing observations provides a practical method of estimating rainfall. However, generating high spatiotemporal rainfall fields for catchment-distributed hydrological modeling is a problem when only a sparse rain gauge network and coarse spatial resolution of satellite data are available. The objective of the study is to present a satellite and rain gauge data-merging framework adapting for coarse resolution and data-sparse designs. In the framework, a statistical spatial downscaling method based on the relationships among precipitation, topographical features, and weather conditions was used to downscale the 0.25° daily rainfall field derived from the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) precipitation product version 7. The nonparametric merging technique of double kernel smoothing, adapting for data-sparse design, was combined with the global optimization method of shuffled complex evolution, to merge the downscaled TRMM and gauged rainfall with minimum cross-validation error. An indicator field representing the presence and absence of rainfall was generated using the indicator kriging technique and applied to the previously merged result to consider the spatial intermittency of daily rainfall. The framework was applied to estimate daily precipitation at a 1 km resolution in the Qinghai Lake Basin, a data-scarce area in the northeast of the Qinghai-Tibet Plateau. The final estimates not only captured the spatial pattern of daily and annual precipitation with a relatively small estimation error, but also performed very well in stream flow simulation when applied to force the geomorphology-based hydrological model (GBHM). The proposed framework thus appears feasible for rainfall estimation at high spatiotemporal resolution in data-scarce areas.

Description: Kernel-based methods and ensemble learning are two important paradigms for the classification of hyperspectral remote sensing images. However, they were developed in parallel with different principles. In this paper, we aim to combine the advantages of kernel and ensemble methods by proposing a kernel supervised ensemble classification method. In particular, the proposed method, namely RoF-KOPLS, combines the merits of ensemble feature learning (i.e., Rotation Forest (RoF)) and kernel supervised learning (i.e., Kernel Orthonormalized Partial Least Square (KOPLS)). In particular, the feature space is randomly split into K disjoint subspace and KOPLS is applied to each subspace to produce the new features set for the training of decision tree classifier. The final classification result is assigned to the corresponding class by the majority voting rule. Experimental results on two hyperspectral airborne images demonstrated that RoF-KOPLS with radial basis function (RBF) kernel yields the best classification accuracies due to the ability of improving the accuracies of base classifiers and the diversity within the ensemble, especially for the very limited training set. Furthermore, our proposed method is insensitive to the number of subsets.

Description: Leaf Area Index (LAI) is a key variable that bridges remote sensing observations to the quantification of agroecosystem processes. In this study, we assessed the universality of the relationships between crop LAI and remotely sensed Vegetation Indices (VIs). We first compiled a global dataset of 1459 in situ quality-controlled crop LAI measurements and collected Landsat satellite images to derive five different VIs including Simple Ratio (SR), Normalized Difference Vegetation Index (NDVI), two versions of the Enhanced Vegetation Index (EVI and EVI2), and Green Chlorophyll Index (CIGreen). Based on this dataset, we developed global LAI-VI relationships for each crop type and VI using symbolic regression and Theil-Sen (TS) robust estimator. Results suggest that the global LAI-VI relationships are statistically significant, crop-specific, and mostly non-linear. These relationships explain more than half of the total variance in ground LAI observations (R2 > 0.5), and provide LAI estimates with RMSE below 1.2 m2/m2. Among the five VIs, EVI/EVI2 are the most effective, and the crop-specific LAI-EVI and LAI-EVI2 relationships constructed by TS, are robust when tested by three independent validation datasets of varied spatial scales. While the heterogeneity of agricultural landscapes leads to a diverse set of local LAI-VI relationships, the relationships provided here represent global universality on an average basis, allowing the generation of large-scale spatial-explicit LAI maps. This study contributes to the operationalization of large-area crop modeling and, by extension, has relevance to both fundamental and applied agroecosystem research.

Description: With its temporal resolution of 10 days (five days with two satellites, and significantly more at high latitudes), its swath width of 290 km, and its 10 m and 20 m spatial resolution bands from the visible to the shortwave infrared, the European Sentinel-2 satellites have significant potential for glacier remote sensing, in particular mapping of glacier outlines and facies, and velocity measurements. Testing Level 1C commissioning and ramp-up phase data for initial sensor quality experiences, we find a high radiometric performance, but with slight striping effects under certain conditions. Through co-registration of repeat Sentinal-2 data we also find lateral offset patterns and noise on the order of a few metres. Neither of these issues will complicate most typical glaciological applications. Absolute geo-location of the data investigated was on the order of one pixel at the time of writing. The most severe geometric problem stems from vertical errors of the DEM used for ortho-rectifying Sentinel-2 data. These errors propagate into locally varying lateral offsets in the images, up to several pixels with respect to other georeferenced data, or between Sentinel-2 data from different orbits. Finally, we characterize the potential and limitations of tracking glacier flow from repeat Sentinel-2 data using a set of typical glaciers in different environments: Aletsch Glacier, Swiss Alps; Fox Glacier, New Zealand; Jakobshavn Isbree, Greenland; Antarctic Peninsula at the Larsen C ice shelf.

Description: Currently there is a lack of quantitative information regarding the driving factors of vegetation dynamics in post-Soviet Central Asia. Insufficient knowledge also exists concerning vegetation variability across sub-humid to arid climatic gradients as well as vegetation response to different land uses, from natural rangelands to intensively irrigated croplands. In this study, we analyzed the environmental drivers of vegetation dynamics in five Central Asian countries by coupling key vegetation parameter “overall greenness” derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI time series data, with its possible factors across various management and climatic gradients. We developed nine generalized least-squares random effect (GLS-RE) models to analyze the relative impact of environmental factors on vegetation dynamics. The obtained results quantitatively indicated the extensive control of climatic factors on managed and unmanaged vegetation cover across Central Asia. The most diverse vegetation dynamics response to climatic variables was observed for “intensively managed irrigated croplands”. Almost no differences in response to these variables were detected for managed non-irrigated vegetation and unmanaged (natural) vegetation across all countries. Natural vegetation and rainfed non-irrigated crop dynamics were principally associated with temperature and precipitation parameters. Variables related to temperature had the greatest relative effect on irrigated croplands and on vegetation cover within the mountainous zone. Further research should focus on incorporating the socio-economic factors discussed here in a similar analysis.

Description: This paper presents a method to estimate steady wind and a maneuvering strategy for loitering under a strong, steady wind. The wind estimation uses Global Positioning System velocity only through a novel filter design without airspeed measurement. The wind estimate is then used to guide the aircraft to crab in a direction perpendicular to the wind, thereby avoiding large changes in flight variables if an orbit-type maneuver is attempted. The proposed method is demonstrated through flight tests.

Description: We propose biased estimators to find the direction of arrival of emitters present in the mainlobe of a spinning antenna-based electronic intelligence system. The proposed estimators were constructed by using Bayesian techniques and by performing a linear transformation and an affine transformation on the maximum likelihood estimator. From a Monte Carlo simulation and experimental results, we demonstrate that the proposed estimators outperform the limit set by the popular performance benchmark, the Cramer-Rao lower bound.

Description: A new method was proposed for chirp signal detection and estimation built on the frame-based fast Fourier transform (FFT). The proposed method uses the peak frequency difference between FFT frames to detect a chirp signal and estimate chirp rate. This approach differs from conventional methods and is easy to implement. It generates more accurate chirp rate estimation especially under a low signal-to-noise ratio. Simulation and experimental data are used to verify the proposed methods.

Description: The quasimaximum likelihood (QML) estimator of polynomial-phase signals (PPSs) is based on the maximization of the short-time Fourier transform and suffers from aliasing when signals are sampled below the Nyquist sampling rate. In this paper, a phase unwrapping procedure has been proposed as an additional step in the QML to estimate parameters of such signals. Statistical study has shown excellent performance of the proposed approach.

Description: This review presents a survey of the literature on recent progress in lithium-ion batteries, with the active sub-micron-sized particles of the positive electrode chosen in the family of lamellar compounds LiMO2, where M stands for a mixture of Ni, Mn, Co elements, and in the family of yLi2MnO3•(1 − y)LiNi½Mn½O2 layered-layered integrated materials. The structural, physical, and chemical properties of these cathode elements are reported and discussed as a function of all the synthesis parameters, which include the choice of the precursors and of the chelating agent, and as a function of the relative concentrations of the M cations and composition y. Their electrochemical properties are also reported and discussed to determine the optimum compositions in order to obtain the best electrochemical performance while maintaining the structural integrity of the electrode lattice during cycling.

Description: Polymer nanocomposites have always attracted the interest of researchers and industry because of their potential combination of properties from both the nanofillers and the hosting matrix. Gathering nanomaterials and 3D printing could offer clear advantages and numerous new opportunities in several application fields. Embedding nanofillers in a polymeric matrix could improve the final material properties but usually the printing process gets more difficult. Considering this drawback, in this paper we propose a method to obtain polymer nanocomposites by in situ generation of nanoparticles after the printing process. 3D structures were fabricated through a Digital Light Processing (DLP) system by disolving metal salts in the starting liquid formulation. The 3D fabrication is followed by a thermal treatment in order to induce in situ generation of metal nanoparticles (NPs) in the polymer matrix. Comprehensive studies were systematically performed on the thermo-mechanical characteristics, morphology and electrical properties of the 3D printed nanocomposites.

Description: A series of substitutional solid solutions—Eu7Cu44−xTxAs23 (T = Fe, Co, Ni)—based on a recently discovered clathrate-like compound (Eu7Cu44As23) were synthesized from the elements at 800 °C. Almost up to 50% of Cu can be substituted by Ni, resulting in a linear decrease of the cubic unit cell parameter from a = 16.6707(1) Å for the ternary compound to a = 16.3719(1) Å for the sample with the nominal composition Eu7Cu24Ni20As23. In contrast, Co and Fe can only substitute less than 20% of Cu. Crystal structures of six samples of different composition were refined from powder diffraction data. Despite very small differences in scattering powers of Cu, Ni, Co, and Fe, we were able to propose a reasonable model of dopant distribution over copper sites based on the trends in interatomic distances as well as on Mössbauer spectra for the iron-substituted compound Eu7Cu36Fe8As23. Ni doping increases the Curie temperature to 25 K with respect to the parent compound, which is ferromagnetically ordered below 17.5 K, whereas Fe doping suppresses the ferromagnetic ordering in the Eu sublattice.

Description: The reactions of enantiomeric glycerol-based 3-armed lactide oligomers (H3DLAO and H3LLAO) and a diethylene glycol-based 2-armed ɛ-caprolactone oligomer (H2CLO) with hexamethylene diisocyanate (HDI) produced polyesterurethane copolymer networks (PEU-3scLAO/2CLOs 100/0, 75/25, 50/50, 25/75 and 0/100) with different feed ratios of stereocomplex (sc) lactide oligomer (H3scLAO = H3DLAO + H3LLAO, H3DLAO/H3LLAO = 1/1) and H2CLO. Thermal and mechanical properties of the copolymer networks were compared with those of a simple homochiral (hc) network (PEU-3DLAO) produced by the reaction of H3DLAO and HDI. X-ray diffraction and differential scanning calorimetric analyses revealed that sc crystallites are formed without any hc crystallization for PEU-3scLAO/2CLOs, and that PEU-3DLAO is amorphous. The melting temperatures of sc crystallites for PEU-3scLAO/2CLOs were much higher than that of hc crystallites of H3DLAO. The polarized optical microscopic analysis revealed that the nucleation efficiency is enhanced with increasing feed of H3scLAO fraction, whereas the spherulite growth rate is accelerated with increasing feed H2CLO fraction over 100/0-50/50 networks. PEU-3scLAO/2CLO 100/0 (i.e., PEU-3scLAO) exhibited a higher tensile strength and modulus than PEU-3DLAO. The elongation at break and tensile toughness for PEU-3scLAO/2CLOs increased with an increasing feed amount of H2CLO.

Description: A novel numerical method at the microscale for studying the mechanical behavior of an aluminum-particle-reinforced polytetrafluoroethylene (Al/PTFE) composite is proposed and validated experimentally in this paper. Two types of 2D representative volume elements (RVEs), real microstructure-based and simulated microstructures, are established by following a series of image processing procedures and on a statistical basis considering the geometry and the distribution of particles and microvoids, respectively. Moreover, 3D finite element modelling based on the same statistical information as the 2D simulated microstructure models is conducted to show the efficiency and effectiveness of the 2D models. The results of all simulations and experiments indicate that real microstructure-based models and simulated microstructure models are efficient methods to predict elastic and plastic constants of particle-reinforced composites.

Description: Plasma polymerized a-C:H thin films have been deposited on Si (100) and aluminum coated glass substrates by a dielectric barrier discharge (DBD) operated at medium pressure using C2Hm/Ar (m = 2, 4, 6) gas mixtures. The deposited films were characterized by Fourier transform infrared reflection absorption spectroscopy (FT-IRRAS), Raman spectroscopy, and ellipsometry. FT-IRRAS revealed the presence of sp3 and sp2 C–H stretching and C–H bending vibrations of bonds in the films. The presence of D and G bands was confirmed by Raman spectroscopy. Thin films obtained from C2H4/Ar and C2H6/Ar gas mixtures have ID/IG ratios of 0.45 and 0.3, respectively. The refractive indices were 2.8 and 3.1 for C2H4/Ar and C2H6/Ar films, respectively, at a photon energy of 2 eV.

Description: There is no standardized procedure for producing geopolymers; therefore, many researchers develop their own procedures for mixing and curing to achieve good workability and strength development. The curing scheme adopted is important in achieving maximum performance of resultant geopolymers. In this study, we evaluated the impact of sealed and unsealed curing on mechanical strength of geopolymers. Fly ash-based geopolymers cured in sealed and unsealed moulds clearly revealed that retention of water during curing resulted in superior strength development. The average compressive strength of sealed-cured geopolymers measured after 1 day of curing was a modest 50 MPa, while after 7 day curing the average compressive strength increased to 120~135 MPa. In the unsealed specimens the average compressive strength of geopolymers was lower; ranging from 60 to 90 MPa with a slight increase as the curing period increased. Microcracking caused by dehydration is postulated to cause the strength decrease in the unsealed cured samples. These results show that water is a crucial component for the evolution of high strength three-dimensional cross-linked networks in geopolymers.

Description: Fretting wear is the material damage of two contact surfaces caused by micro relative displacement. Its characteristic is that debris is trapped on the contact surfaces. Depending on the material properties, the shapes of the debris, and the dominant wear mechanisms, debris can play different roles that either protect or harm interfaces. Due to the micro scale of the debris, it is difficult to obtain instantaneous information and investigate debris behavior in experiments. The Finite Element Method (FEM) has been used to model the process of fretting wear and calculate contact variables, such as contact stress and relative slip during the fretting wear process. In this research, a 2D fretting wear model with a debris layer was developed to investigate the influence of debris on fretting wear. Effects of different factors such as thickness of the debris layer, Young’s modulus of the debris layer, and the time of importing the layer into the FE model were considered in this study. Based on FE results, here we report that: (a) the effect of Young’s modulus of the debris layer on the contact pressure is not significant; (b) the contact pressure between the debris layer and the flat specimen decreases with increasing thickness of the layer and (c) by importing the debris layer in different fretting wear cycles, the debris layer shows different roles in the wear process. At the beginning of the wear cycle, the debris layer protects the contact surfaces of the first bodies (cylindrical pad and flat specimen). However, in the final cycle, the wear volumes of the debris layers exhibit slightly higher damage compared to the model without the debris layer in all considered cases.

Description: Antimicrobial polymers represent a very promising class of therapeutics with unique characteristics for fighting microbial infections. As the classic antibiotics exhibit an increasingly low capacity to effectively act on microorganisms, new solutions must be developed. The importance of this class of materials emerged from the uncontrolled use of antibiotics, which led to the advent of multidrug-resistant microbes, being nowadays one of the most serious public health problems. This review presents a critical discussion of the latest developments involving the use of different classes of antimicrobial polymers. The synthesis pathways used to afford macromolecules with antimicrobial properties, as well as the relationship between the structure and performance of these materials are discussed.

Description: In this paper, we consider retrieving individual wave components in a multi-directional sea wave model. To solve this problem, a currently and commonly used method is three-dimensional discrete Fourier transform (3D DFT) on the radar image sequence. However, the uniform frequency and the uniform wavenumber in a wavenumber frequency domain can not always strictly satisfy the dispersion relation, and the spectral leakage in both temporal and spatial domains exists due to the limited analysis area selected from an image sequence. As a result, the DFT method incurs undesirable error performance in retrieving directional wave components. By deeply investigating the data structure of the multi-directional sea wave model, we obtain a new and decomposable matrix representation for processing the wave components. Then, a novel successive cancellation method is proposed to efficiently and effectively extract individual wave components, whose frequency and wavenumber rigorously satisfy the liner dispersion relation. Thus, it avoids spectral leakage in the spatial domain. The algorithm is evaluated by using linear synthetic wave image sequences. The validity of the proposed novel algorithm is verified by comparing the retrieved parameters of amplitude, phase, and direction of the individual wave components with the simulated parameters as well as those obtained by using the 3D DFT method. In addition, the reconstructed sea field using the retrieved wave components is also compared with the simulated remote sensing images as well as those attained using the inverse 3D DFT method. All the simulation results demonstrate that our proposed algorithm is more effective and has better performance for retrieving individual wave components from the spatio-temporal remote sensing image sequences than the 3D DFT method.

Description: Knowing the current phenological state of an agricultural crop is a powerful tool for precision farming applications. In the past, it has been estimated with remote sensing data by exploiting time series of Normalised Difference Vegetation Index (NDVI), but always at the end of the campaign and only providing results for some key states. In this work, a new dynamical framework is proposed to provide real-time estimates in a continuous range of states, for which NDVI images are combined with a prediction model in an optimal way using a particle filter. The methodology is tested over a set of 8 to 13 rice parcels during 2008–2013, achieving a high determination factor R 2 = 0.93 ( n = 379 ) for the complete phenological range. This method is also used to predict the end of season date, obtaining a high accuracy with an anticipation of around 40–60 days. Among the key advantages of this approach, phenology is estimated each time a new observation is available, hence enabling the potential detection of anomalies in real-time during the cultivation. In addition, the estimation procedure is robust in the case of noisy observations, and it is not limited to a few phenological stages.

Description: Clustering is a fundamental task in data mining. Affinity propagation clustering (APC) is an effective and efficient clustering technique that has been applied in various domains. APC iteratively propagates information between affinity samples, updates the responsibility matrix and availability matrix, and employs these matrices to choose cluster centers (or exemplars) of respective clusters. However, since it mainly uses negative Euclidean distance between exemplars and samples as the similarity between them, it is difficult to identify clusters with complex structure. Therefore, the performance of APC deteriorates on samples distributed with complex structure. To mitigate this problem, we propose an improved APC based on a path-based similarity (APC-PS). APC-PS firstly utilizes negative Euclidean distance to find exemplars of clusters. Then, it employs the path-based similarity to measure the similarity between exemplars and samples, and to explore the underlying structure of clusters. Next, it assigns non-exemplar samples to their respective clusters via that similarity. Our empirical study on synthetic and UCI datasets shows that the proposed APC-PS significantly outperforms original APC and other related approaches.

Description: Big data makes cloud computing more and more popular in various fields. Video resources are very useful and important to education, security monitoring, and so on. However, issues of their huge volumes, complex data types, inefficient processing performance, weak security, and long times for loading pose challenges in video resource management. The Hadoop Distributed File System (HDFS) is an open-source framework, which can provide cloud-based platforms and presents an opportunity for solving these problems. This paper presents video resource management architecture based on HDFS to provide a uniform framework and a five-layer model for standardizing the current various algorithms and applications. The architecture, basic model, and key algorithms are designed for turning video resources into a cloud computing environment. The design was tested by establishing a simulation system prototype.

Description: The high alloying degree of Duplex stainless steels makes them susceptible to the formation of intermetallic phases during their exposure to high temperatures. Precipitation of these phases can lead to a decreasing of the corrosion resistance and sometimes of the toughness. Starting from the advantages of the synergic Metal Active Gas (MAG) pulsed welding process, this paper analyses the structure formation particularities of homogeneous welded joints from Duplex stainless steel. The effect of linear welding energy on the structure morphology of the welded joints was revealed by macro- and micrographic examinations, X-ray energy dispersion analyses, measurements of ferrite proportion and X-ray diffraction analysis. The results obtained showed that the transformation of ferrite into austenite is associated with the chromium, nickel, molybdenum and nitrogen distribution between these two phases and their redistribution degree is closely linked to the overall heat cycle of the welding process. The adequate control of the energy inserted in the welded components provides an optimal balance between the two microstructural constituents (Austenite and Ferrite) and avoids the formation of undesirable intermetallic phases.

Description: Fiber-reinforced composite (FRP) materials have gained an increasing success, mostly for strengthening, retrofitting and repair of existing historic masonry structures and may cause a significant enhancement of the mechanical properties of the reinforced members. This article summarizes the results of previous experimental activities aimed at investigating the effectiveness of GFRP (Glass Fiber Reinforced Polymers) grids embedded into an inorganic mortar to reinforce historic masonry. The paper also presents innovative results on the relationship between the durability and the governing material properties of GFRP grids. Measurements of the tensile strength were made using specimens cut off from GFRP grids before and after ageing in aqueous solution. The tensile strength of a commercially available GFRP grid has been tested after up 450 days of storage in deionized water and NaCl solution. A degradation in tensile strength and Young’s modulus up to 30.2% and 13.2% was recorded, respectively. This degradation indicated that extended storage in a wet environment may cause a decrease in the mechanical properties.

Description: In this article, ultrasonic guided wave propagation and interaction with the rivet hole cracks has been formulated using closed-form analytical solution while the local damage interaction, scattering, and mode conversion have been obtained from finite element analysis. The rivet hole cracks (damage) in the plate structure gives rise to the non-axisymmetric scattering of Lamb wave, as well as shear horizontal (SH) wave, although the incident Lamb wave source (primary source) is axisymmetric. The damage in the plate acts as a non-axisymmetric secondary source of Lamb wave and SH wave. The scattering of Lamb and SH waves are captured using wave damage interaction coefficient (WDIC). The scatter cubes of complex-valued WDIC are formed that can describe the 3D interaction (frequency, incident direction, and azimuth direction) of Lamb waves with the damage. The scatter cubes are fed into the exact analytical framework to produce the time domain signal. This analysis enables us to obtain the optimum design parameters for better detection of the cracks in a multiple-rivet-hole problem. The optimum parameters provide the guideline of the design of the sensor installation to obtain the most noticeable signals that represent the presence of cracks in the rivet hole.

Description: One of the most intriguing renewable energy production methods being explored currently is electrical power generation by microbial fuel cells (MFCs). However, to make MFC technology economically feasible, cost efficient electrode manufacturing processes need to be proposed and demonstrated. In this context, VITO has developed an innovative electrode manufacturing process based on film casting and phase inversion. The screening and selection process of electrode compositions was done based on physicochemical properties of the active layer, which in turn maintained a close relation with their composition A dual hydrophilic-hydrophobic character in the active layer was achieved with values of εhydrophilic up to 10% while εTOTAL remained in the range 65 wt % to 75 wt %. Eventually, selected electrodes were tested as air cathodes for MFC in half cell and full cell modes. Reduction currents, up to −0.14 mA·cm2− at −100 mV (vs. Ag/AgCl) were reached in long term experiments in the cathode half-cell. In full MFC, a maximum power density of 380 mW·m−2 was observed at 100 Ω external load.

Description: Ceramifiable styrene-butadiene (SBR)-based composites containing low-softening-point-temperature glassy frit promoting ceramification, precipitated silica, one of four thermally stable refractory fillers (halloysite, calcined kaolin, mica or wollastonite) and a sulfur-based curing system were prepared. Kinetics of vulcanization and basic mechanical properties were analyzed and added as Supplementary Materials. Combustibility of the composites was measured by means of cone calorimetry. Their thermal properties were analyzed by means of thermogravimetry and specific heat capacity determination. Activation energy of thermal decomposition was calculated using the Flynn-Wall-Ozawa method. Finally, compression strength of the composites after ceramification was measured and their micromorphology was studied by scanning electron microscopy. The addition of a ceramification-facilitating system resulted in the lowering of combustibility and significant improvement of the thermal stability of the composites. Moreover, the compression strength of the mineral structure formed after ceramification is considerably high. The most promising refractory fillers for SBR-based ceramifiable composites are mica and halloysite.

Description: The inverse problem of synthetic aperture imaging radiometers (SAIRs) has been demonstrated to be not well posed. The regularization methods are crucial for providing unique and stable solutions in the reconstruction of radiometric brightness temperature (BT) maps. Different to deterministic ones, a new approach is presented by referring to the rule of Bayesian inference, providing a probability model of regularized constraints to combat the ill-posedness of finite-dimensional discrete inverse problems. In addition, the SAIR inverse problem can be converted into the probability estimation of the reconstructed BT. Furthermore, in application to both uniformly and nonuniformly spaced arrays, our method can obtain the optimal solution adaptively and avoid the dilemma of choosing the optimal regularization parameter. Finally, simulation results illustrating the effectiveness and performance of the proposed method are provided.

Description: A range-cell-focusing algorithm is proposed in order to improve the quality of the target image. In a synthetic aperture radar (SAR) imaging system, the range resolution depends on the frequency bandwidth and determines the ability to distinguish between targets that are very close to each other. In cases where the resolution and the SNR from the environment are not adequate, targets cannot be accurately visualized. In order to successively classify targets that are close, we are combining an enhanced-multiple-signal-classification spectrum as a weighting function to reproduce the raw data. The proposed algorithm improves classification and separation for close targets while suppressing artifacts in the final images. The targets of interest are stationary point scatterers. The results are obtained from both simulated and experimental data to demonstrate that the proposed algorithm provides better performance than a conventional SAR imaging algorithm, the range migration algorithm.

Description: This letter presents a multiscale edge detection method for multilook polarimetric synthetic aperture radar (PolSAR) images based on the nonsubsampled contourlet transform (NSCT). The NSCT can provide flexible multiscale and directional decomposition. In the multiscale decomposition, the coefficients of the nonsubsampled pyramid in the NSCT are calculated via maximizing the polarimetric contrast between the adjacent subband levels, instead of using the difference of the adjacent subbands as used in the additive noise model. By this way, we make the NSCT applicable to PolSAR data and multiband data. Then, the edges are detected in the NSCT domain based on a fusion of the directional subband coefficients at different scales. Experimental results with both simulated and real PolSAR data show that the present approach is robust to noise and the extracted edges are complete and continuous.

Description: A method for defining the spatial resolution of a Global Navigation Satellite System reflectometry delay–Doppler map (DDM) and of any derived geophysical product is proposed. An effective spatial resolution is derived as a function of measurement geometry and delay–Doppler (DD) interval, and as a more appropriate representation of resolution than the geometric resolution previously used in the literature. The definition more accurately accounts for variations in the scattered power across different pixels of the DDM and more accurately includes the power spreading effect caused by the Woodward ambiguity function. The dependence of the effective resolution on incidence angle, receiver altitude, and DD interval is analyzed and compared with the dependence of the geometric resolution with similar parameters.

Description: Laser scanner-captured 3-D point cloud data analysis is becoming more commonly used for remote sensing and plant science applications. Because of nonrigidity and complexity, reconstructing a 3-D model of a plant is extremely challenging. Existing algorithms often fail to find correct correspondences for plantlike thin structures. We address the problem of finding 3-D junction points in plant point cloud data as a first step of this correspondence matching process. Temporarily, we transform the 3-D problem into 2-D by performing appropriate coordinate transformations to the neighborhood of each 3-D point. Our proposed method has two steps. First, a statistical dip test of multimodality is performed to detect the nonlinearity of the local 2D structure. Then, each branch is approximated by sequential random-sample-consensus line fitting and a Euclidean clustering technique. The straight line parameters of each branch are extracted using total-least-squares estimation. Finally, the straight line equations are solved to determine if they intersect in the local neighborhood. Such junction points are good candidates for subsequent correspondence algorithms. Using these detected junction points, we formulate a correspondence algorithm as a subgraph matching problem and show that, without using traditional descriptor similarity-based matching, good correspondences can be obtained by simply considering geodesic distances among graph nodes. Experiments on synthetic and real ( Arabidopsis plant) data show that the proposed method outperforms the state of the art.

Description: Repeat-track analysis is commonly utilized to generate elevation change time series from satellite radar altimetry over ice sheets. It requires surface gradient (SG) correction due primarily to orbital drifts and radar-related empirical corrections caused by radar scatters from ice surface and potential subsurface. In this letter, two approaches, namely, the use of a digital elevation model (DEM) and the modified repeat-track analysis, which uses the accumulated Envisat altimetry profiles, are applied to correct the SG over both Greenland ice sheet (GrIS) and Antarctic ice sheet (AIS). By comparing the root mean square (rms) of elevation change time series after SG correction, the percentage of data (rms< 1 m) obtained by using modified repeat-track analysis is found to be 85% and 88% for the GrIS and AIS, respectively, as opposed to 45% and 44% if the DEM method is used. Furthermore, three cases are studied to assess empirical corrections for elevation retrieved from both ice-1 and ice-2 algorithms over the AIS. We conclude that the modified repeat-track analysis is more effective to remove topographic induced error. For the ice-2 algorithm, waveform shape parameters are needed in addition to applying corrections from changes in backscatter coefficients. The trend of elevation changes from the ice-1 algorithm with only backscatter analysis agrees with that from the ice-2 algorithm with corrections from backscatter coefficient changes and waveform shape parameters. This study could provide a potential data processing recipe for generating improved satellite radar altimetry elevation time series over ice sheets.

Description: Extracting ships from complex backgrounds is the bottleneck of ship detection in high-resolution optical satellite images. In this letter, we propose a nearly closed-form ship rotated bounding box space used for ship detection and design a method to generate a small number of highly potential candidates based on this space. We first analyze the possibility of accurately covering all ships by labeling rotated bounding boxes. Moreover, to reduce search space, we construct a nearly closed-form ship rotated bounding box space. Then, by scoring for each latent candidate in the space using a two-cascaded linear model followed by binary linear programming, we select a small number of highly potential candidates. Moreover, we also propose a fast version of our method. Experiments on our data set validate the effectiveness of our method and the efficiency of its fast version, which achieves a close detection rate in near real time.

Description: In this letter, a two-stage method for airport detection on remote sensing images is proposed. In the first stage, a new algorithm composed of several line-based processing steps is used for extraction of candidate airport regions. In the second stage, the scale-invariant feature transformation and Fisher vector coding are used for efficient representation of the airport and nonairport regions and support vector machines employed for classification. In order to evaluate the performance of the proposed method, extensive experiments are conducted on airports around the world with different layouts. The measures used in the evaluation are accuracy, sensitivity, and specificity. The proposed method achieved an accuracy of 94.6%, which was benchmarked with two previous methods to prove its superiority.

Description: High-resolution wide-swath synthetic aperture radar (SAR) systems are very attractive for the observation of dynamic processes on the Earth's surface, but they require the downlink of a huge volume of data. In order to comply with azimuth ambiguity requirements, in fact, a pulse repetition frequency much higher than the required processed Doppler bandwidth is often desirable. The volume of downlinked data, however, can be drastically reduced by performing Doppler filtering and decimation on board. A finite-impulse-response filter with a relatively small number of taps suffices to suppress the additional ambiguous components and to recover the original impulse response. This strategy is of special relevance for staggered SAR systems, which are typically characterized by a high oversampling factor. The proposed data reduction technique is also baseline for Tandem-L, where onboard Doppler filtering, resampling, and decimation will be jointly implemented.

Description: In this letter, we generate anisotropic bicontinuous media with different vertical and horizontal correlation functions. With the computer-generated bicontinuous medium, we then use numerical solutions of Maxwell equations in 3-dimensions (NMM3D) to calculate the anisotropic effective permittivities and the effective propagation constants of V and H polarizations. The copolarization phase difference (CPD) of VV and HH is then derived. The CPDs have recently been applied to the retrieval of snow water equivalent, snow depth, and anisotropy. The NMM3D simulation results are also compared with the results of the strong permittivity fluctuations in the low frequency limit and compared against the Maxwell–Garnett mixing formula.

Description: The IEEE GRS Society is grateful for the support given by the organizations listed and invites applications for Institutional Listings from other firms interested in the field of geoscience and remote sensing.

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Description: Graph-based semi-supervised classification uses a graph to capture the relationship between samples and exploits label propagation techniques on the graph to predict the labels of unlabeled samples. However, it is difficult to construct a graph that faithfully describes the relationship between high-dimensional samples. Recently, low-rank representation has been introduced to construct a graph, which can preserve the global structure of high-dimensional samples and help to train accurate transductive classifiers. In this paper, we take advantage of low-rank representation for graph construction and propose an inductive semi-supervised classifier called Semi-Supervised Classification based on Low-Rank Representation (SSC-LRR). SSC-LRR first utilizes a linearized alternating direction method with adaptive penalty to compute the coefficient matrix of low-rank representation of samples. Then, the coefficient matrix is adopted to define a graph. Finally, SSC-LRR incorporates this graph into a graph-based semi-supervised linear classifier to classify unlabeled samples. Experiments are conducted on four widely used facial datasets to validate the effectiveness of the proposed SSC-LRR and the results demonstrate that SSC-LRR achieves higher accuracy than other related methods.

Description: This research proposes a two-stage user-based collaborative filtering process using an artificial immune system for the prediction of student grades, along with a filter for professor ratings in the course recommendation for college students. We test for cosine similarity and Karl Pearson (KP) correlation in affinity calculations for clustering and prediction. This research uses student information and professor information datasets of Yuan Ze University from the years 2005–2009 for the purpose of testing and training. The mean average error and confusion matrix analysis form the testing parameters. A minimum professor rating was tested to check the results, and observed that the recommendation systems herein provide highly accurate results for students with higher mean grades.

Description: As a sensitive indicator of climate change, mountain glacier dynamics are of great concern, but the ice motion pattern of an entire glacier surface cannot be accurately and efficiently generated by the use of only phase-based or intensity-based methods with synthetic aperture radar (SAR) imagery. To derive the ice movement of the whole glacier surface with a high accuracy, an integrated approach combining differential interferometric SAR (D-InSAR), multi-aperture interferometry (MAI), and a pixel-tracking (PT) method is proposed, which could fully exploit the phase and intensity information recorded by the SAR sensor. The Chongce Glacier surface flow field is estimated with the proposed integrated approach. Compared with the traditional SAR-based methods, the proposed approach can determine the ice motion over a widely varying range of ice velocities with a relatively high accuracy. Its capability is proved by the detailed ice displacement pattern with the average accuracy of 0.2 m covering the entire Chongce Glacier surface, which shows a maximum ice movement of 4.9 m over 46 days. Furthermore, it is shown that the ice is in a quiescent state in the downstream part of the glacier. Therefore, the integrated approach presented in this paper could present us with a novel way to comprehensively and accurately understand glacier dynamics by overcoming the incoherence phenomenon, and has great potential for glaciology study.

Description: With the upcoming availability of the next generation of high quality orbiting hyperspectral sensors, a major step toward improved regional soil mapping and monitoring and delivery of quantitative soil maps is expected. This study focuses on the determination of the prediction accuracy of spectral models for the mapping of common soil properties based on upcoming EnMAP (Environmental Mapping and Analysis Program) satellite data using semi-operational soil models. Iron oxide (Fed), clay, and soil organic carbon (SOC) content are predicted in test areas in Spain and Luxembourg based on a semi-automatic Partial-Least-Square (PLS) regression approach using airborne hyperspectral, simulated EnMAP, and soil chemical datasets. A variance contribution analysis, accounting for errors in the dependent variables, is used alongside classical error measurements. Results show that EnMAP allows predicting iron oxide, clay, and SOC with an R2 between 0.53 and 0.67 compared to Hyperspectral Mapper (HyMap)/Airborne Hyperspectral System (AHS) imagery with an R2 between 0.64 and 0.74. Although a slight decrease in soil prediction accuracy is observed at the spaceborne scale compared to the airborne scale, the decrease in accuracy is still reasonable. Furthermore, spatial distribution is coherent between the HyMap/AHS mapping and simulated EnMAP mapping as shown with a spatial structure analysis with a systematically lower semivariance at the EnMAP scale.

Description: Carbon nanomaterials like graphene, carbon nanotubes, fullerenes and the various forms of diamond have attracted great attention for their vast potential regarding applications in electrical engineering and as biomaterials. The study of the antibacterial properties of carbon nanomaterials provides fundamental information on the possible toxicity and environmental impact of these materials. Furthermore, as a result of the increasing prevalence of resistant bacteria strains, the development of novel antibacterial materials is of great importance. This article reviews current research efforts on characterizing the antibacterial activity of carbon nanomaterials from the perspective of colloid and interface science. Building on these fundamental findings, recent functionalization strategies for enhancing the antibacterial effect of carbon nanomaterials are described. The review concludes with a comprehensive outlook that summarizes the most important discoveries and trends regarding antibacterial carbon nanomaterials.

Description: For a further understanding of the phase transitions mechanism in type-I silicon clathrates K8Si46, ab initio self-consistent electronic calculations combined with linear-response method have been performed to investigate the vibrational properties of alkali metal K atoms encapsulated type-I silicon-clathrate under pressure within the framework of density functional perturbation theory. Our lattice dynamics simulation results showed that the pressure induced phase transition of K8Si46 was believed to be driven by the phonon instability of the calthrate lattice. Analysis of the evolution of the partial phonon density of state with pressure, a legible dynamic picture for both guest K atoms and host lattice, was given. In addition, based on phonon calculations and combined with quasi-harmonic approximation, the specific heat of K8Si46 was derived, which agreed very well with experimental results. Also, other important thermal properties including the thermal expansion coefficients and Grüneisen parameters of K8Si46 under different temperature and pressure were also predicted.

Description: Recent drastic reductions in the Arctic sea-ice cover have raised an interest in understanding the role of sea ice in the global system as well as pointed out a need to understand the physical processes that lead to such changes. Satellite remote-sensing data provide important information about remote ice areas, and Synthetic Aperture Radar (SAR) data have the advantages of penetration of the omnipresent cloud cover and of high spatial resolution. A challenge addressed in this paper is how to extract information on sea-ice types and sea-ice processes from SAR data. We introduce, validate and apply geostatistical and statistical approaches to automated classification of sea ice from SAR data, to be used as individual tools for mapping sea-ice properties and provinces or in combination. A key concept of the geostatistical classification method is the analysis of spatial surface structures and their anisotropies, more generally, of spatial surface roughness, at variable, intermediate-sized scales. The geostatistical approach utilizes vario parameters extracted from directional vario functions, the parameters can be mapped or combined into feature vectors for classification. The method is flexible with respect to window sizes and parameter types and detects anisotropies. In two applications to RADARSAT and ERS-2 SAR data from the area near Point Barrow, Alaska, it is demonstrated that vario-parameter maps may be utilized to distinguish regions of different sea-ice characteristics in the Beaufort Sea, the Chukchi Sea and in Elson Lagoon. In a third and a fourth case study the analysis is taken further by utilizing multi-parameter feature vectors as inputs for unsupervised and supervised statistical classification. Field measurements and high-resolution aerial observations serve as basis for validation of the geostatistical-statistical classification methods. A combination of supervised classification and vario-parameter mapping yields best results, correctly identifying several sea-ice provinces in the shore-fast ice and the pack ice. Notably, sea ice does not have to be static to be classifiable with respect to spatial structures. In consequence, the geostatistical-statistical classification may be applied to detect changes in ice dynamics, kinematics or environmental changes, such as increased melt ponding, increased snowfall or changes in the equilibrium line.

Description: The rise in cutting temperatures during the machining process can influence the final quality of the machined part. The impact of cutting temperatures is more critical when machining composite-metal stacks and fiber metal laminates due to the stacking nature of those hybrids which subjects the composite to heat from direct contact with metallic part of the stack and the evacuated hot chips. In this paper, the workpiece surface temperature of two grades of fiber metal laminates commercially know as GLARE is investigated. An experimental study was carried out using thermocouples and infrared thermography to determine the emissivity of the upper, lower and side surfaces of GLARE laminates. In addition, infrared thermography was used to determine the maximum temperature of the bottom surface of machined holes during drilling GLARE under dry and minimum quantity lubrication (MQL) cooling conditions under different cutting parameters. The results showed that during the machining process, the workpiece surface temperature increased with the increase in feed rate and fiber orientation influenced the developed temperature in the laminate.

Description: In this study, nano-sized fullerene C60 powder was sufficiently mixed with Cu2SnSe3 powder by ball milling method, and the C60/Cu2SnSe3 composites were prepared by spark plasma sintering technology. The fullerene C60 distributed uniformly in the form of clusters, and the average cluster size was less than 1 μm. With increasing C60 content, the electrical conductivity of C60/Cu2SnSe3 composites decreased, while the Seebeck coefficient was enhanced. The thermal conductivity of composites decreased significantly, which resulted from the phonon scattering by the C60 clusters located on the grain boundaries of the Cu2SnSe3 matrix. The highest figure of merit ZT of 0.38 was achieved at 700 K for 0.8% C60/Cu2SnSe3 composite.

Description: Ti-6Al-4V titanium alloy milling has been frequently used in aviation/aerospace industries. Application environments put forward high requirements to create a desired proportion of the constituent phases and fine grain size for optimum mechanical properties of the machined workpiece. However, quantifying microstructural features of dual-phase (α + β) Ti-6Al-4V titanium alloy is difficult due to its irregular geometry and large dimension span. In this paper, a novel scanning electron microscope (SEM) image processing method was proposed to identify the content of constituent phases of materials. The new approach is based on the fact that the constituent phases of Ti-6Al-4V titanium alloy show different gray levels in digital images. On the basis of the processed image, distribution and average values of grain sizes were calculated directly using Image-Pro Plus software. By the proposed method, sensitivity of microstructural changes to milling parameters is analyzed and the stress-strain behavior for two ductile phase alloys is developed. Main conclusions are drawn that Ti-6Al-4V titanium alloy milling induces a high content of β phase and small grain size on the machined surface. The maximum measured values of change rate of β phase, grain refinement rate at the machined surface, and thickness of the deformation layer are 141.1%, 47.2%, and 12.3 μm, respectively. Thickness of the deformed layer and grain refinement rate decreased distinctly with the increase of cutting speed, but increased with the increase of the feed rate. The parameter of the depth of cut played a positive role in increasing the thickness of the deformed layer, while opposite to the grain refinement rate. For the variation of the change rate of the β phase at the machined surface, depth of cut is the foremost factor among the three studied parameters. Values of yield strength varied from 889–921 MPa with the change of content of the β phase from 30%–45%.

Description: Ambient temperature geopolymerization of paper sludge ashes (PS-ashes) discharged from paper mills was studied by means of scanning electron microscopy (SEM), X-ray diffraction (XRD), induction coupled plasma atomic emission spectrometry (ICP-AES), and X-ray absorption near edge structure (XANES). Two varieties of alkaline liquors were used in the PS-ash based geopolymers, corresponding to aqueous Na-metasilicate and Na-disilicate compositions. PS-ashes were found to be semi-crystalline and to have porous structures that make it possible to absorb much liquor. Flexural strengths of PS-ash-based geopolymers with liquor/filler ratios (L/F) of 1.0–1.5 ranged from 0.82 to 1.51 MPa at 4 weeks age, depending on PS-ashes and liquors used. The reaction process of the constituent minerals of the PS-ash is discussed. Furthermore, we attempted to solidify hazardous water contaminated with radioisotopes. Non-radioactive strontium and cesium nitrates were added as surrogates at a dosage of 1% into the PS-ash-based geopolymers. Generally, high immobilization ratios up to 99.89% and 98.77% were achieved for Sr2+ and Cs+, respectively, depending on the source of PS-ashes, alkaline liquors, and material ages. However, in some cases, poor immobilization ratios were encountered, and we further discussed the causes of the instability of derived geopolymer gels on the basis of XANES spectra.

Description: This paper mainly reports an experimental investigation on the residual mechanical and fracture properties of polystyrene aggregate concrete (PAC) after exposure to high temperatures up to 800 degrees Celsius. The fracture properties namely, the critical stress intensity factor ( K I C S ), the critical crack tip opening displacement (CTODC) for the Two-Parameter Model, and the fracture energy (GF) for the Fictitious Crack Model were examined using the three-point bending notched beam test, according to the RILEM recommendations. The effects of polystyrene aggregate (PA) content and temperature levels on the fracture and mechanical properties of concrete were investigated. The results showed that the mechanical properties of PAC significantly decreased with increase in temperature level and the extent of which depended on the PA content in the mixture. However, at a very high temperature of 800 °C, all samples showed 80 percent reduction in modulus of elasticity compared to room temperature, regardless of the level of PA content. Fracture properties of control concrete (C) and PAC were influenced by temperature in a similar manner. Increasing temperature from 25 °C to 500 °C caused almost 50% reduction of the fracture energy for all samples while 30% increase in fracture energy was occurred when the temperature increased from 500 °C to 800 °C. It was found that adding more PA content in the mixture lead to a more ductile behaviour of concrete.

Description: Ni–Co duplex coatings were cladded onto Cu to improve the antiwear properties of Cu products. Prior to laser cladding, n-Al2O3/Ni layers were introduced as interlayers between laser cladding coatings and Cu substrates to improve the laser absorptivity of these substrates and ensure defect-free laser cladding coatings. The structure and morphology of the coatings were characterized by scanning electron microscopy and optical microscopy, and the phases of the coatings were analyzed by X-ray diffraction. Their hardness was measured using a microhardness tester. Experimental results showed that defect-free composite coatings were obtained and that the coatings were metallurgically bonded to the substrates. The surface of the Ni–Co duplex coatings comprised a Co-based solid solution, Cr7C3, (Fe,Ni)23C6, and other strengthening phases. The microhardness and wear resistance of the duplex coatings were significantly improved compared with the Cu substrates. The average microhardness of the cladded coatings was 845.6 HV, which was approximately 8.2 times greater than that of the Cu substrates (102.6 HV). The volume loss of the Cu substrates was approximately 7.5 times greater than that of the Ni–Co duplex coatings after 60 min of sliding wear testing. The high hardness of and lack of defects in the Ni–Co duplex coatings reduced the plastic deformation and adhesive wear of the Cu substrates, resulting in improved wear properties.

Description: Urban flooding is a serious natural hazard to many cities all over the world, which has dramatic impacts on the urban environment and human life. Urban flooding mapping has practical significance for the prevention and management of urban flood disasters. Remote sensing images with high temporal resolutions are widely used for urban flooding mapping, but have a limitation of relatively low spatial resolutions. In this study, a new method based on a generalized regression neural network (GRNN) is proposed to achieve improved accuracy in super-resolution mapping of urban flooding (SMUF) from remote sensing images. The GRNN-SMUF algorithm was proposed and then assessed using Landsat 5 and Landsat 8 images of Brisbane city in Australia and Wuhan city in China. Compared to three traditional methods, GRNN-SMUF mapped urban flooding more accurately according to both visual and quantitative assessments. The results of this study will improve the accuracy of urban flooding mapping using easily-available remote sensing images with medium-low spatial resolutions and will be propitious to the prevention and management of urban flood disasters.

Description: The availability of a dense time series of satellite observations at moderate (30 m) spatial resolution is enabling unprecedented opportunities for understanding ecosystems around the world. A time series of data from Landsat was used to generate a series of three maps at decadal time step to show how surface water has changed from 1991 to 2011 in the high northern latitudes of North America. Previous attempts to characterize the change in surface water in this region have been limited in either spatial or temporal resolution, or both. This series of maps was generated for the NASA Arctic and Boreal Vulnerability Experiment (ABoVE), which began in fall 2015. These maps show a “nominal” extent of surface water by using multiple observations to make a single map for each time step. This increases the confidence that any detected changes are related to climate or ecosystem changes not simply caused by short duration weather events such as flood or drought. The methods and comparison to other contemporary maps of the region are presented here. Initial verification results indicate 96% producer accuracy and 54% user accuracy when compared to 2-m resolution WorldView-2 data. All water bodies that were omitted were one Landsat pixel or smaller, hence below detection limits of the instrument.

Description: On the example of the Epembe carbonatite-hosted Nb-Ta-LREE deposit, we demonstrate the use of hyperspectral reflectance data and geomorphic indicators for improving the accuracy of remote sensing exploration data of structurally-controlled critical raw material deposits. The results further show how exploration can benefit from a combination of expert knowledge and remotely-sensed relief, as well as imaging data. In the first stage, multi-source remote sensing data were used in lithological mapping based on Kohonen Self-Organizing Maps (SOM). We exemplify that morphological indices, such as Topographic Position Index (TPI), and spatial coordinates are crucial parameters to improve the accuracy of carbonate classification as much as 10%. The resulting lithological map shows the spatial distribution of the ridge forming carbonatite dyke, the fenitization zone, syenite plugs and mafic intrusions. In a second step, the internal zones of the carbonatite complex were identified using the Multi-Range Spectral Feature Fitting (MRSFF) algorithm and a specific decision tree. This approach allowed detecting potential enrichment zones characterized by an abundance of fluorapatite and pyroxene, as well as dolomite-carbonatite (beforsite). Cross-validation of the mineral map with field observations and radiometric data confirms the accuracy of the proposed method.

Description: Landslide monitoring is important for geological disaster prevention, where Synthetic Aperture Radar (SAR) images have been widely used. Compared with the Interferometric SAR (InSAR) technique, intensity-based offset tracking methods (e.g., Normalized Cross-Correlation method) can overcome the limitation of InSAR’s maximum detectable displacement. The normalized cross-correlation (NCC) method, based on single-channel SAR images, estimates azimuth and range displacement by using statistical correlation between the matching windows of two SAR images. However, the matching windows—especially for the boundary area of landslide—always contain pixels with different moving characteristics, affecting the precision of displacement estimation. Based on the advantages of polarimetric scattering properties, this paper proposes a fully polarimetric SAR (PolSAR) offset tracking method for improvement of the precision of landslide displacement estimation. The proposed method uses the normalized inner product (NIP) of the two temporal PolSAR Pauli scattering vectors to evaluate their similarity, then retrieve the surface displacement of the Slumgullion landslide located in southwestern Colorado, USA. A pair of L-band fully polarimetric SAR images acquired by the Jet Propulsion Laboratory’s Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) system are selected for experiment. The results show that the Slumgullion landslide’s moving velocity during the monitoring time ranges between 1.6–10.9 mm/d, with an average velocity of 6.3 mm/d. Compared with the classical NCC method, results of the proposed method present better performance in the sub-pixel estimation. Furthermore, it performs better when estimating displacement in the area around the landslide boundaries.

Description: The savannas of Southern Africa are an important dryland ecosystem as they cover up to 54% of the landscape and support a rich variety of biodiversity. This paper evaluates landscape change in savanna vegetation along Chobe Riverfront within Chobe National Park Botswana, from 1982 to 2011 to understand what change may be occurring in land cover. Classifying land cover in savanna environments is challenging because the vegetation spectral signatures are similar across distinct vegetation covers. With vegetation species and even structural groups having similar signatures in multispectral imagery difficulties exist in making discrete classifications in such landscapes. To address this issue, a Random Forest classification algorithm was applied to predict land-cover classes. Additionally, time series vegetation indices were used to support the findings of the discrete land cover classification. Results indicate that a landscape level vegetation shift has occurred across the Chobe Riverfront, with results highlighting a shift in land cover towards more woody vegetation. This represents a degradation of vegetation cover within this savanna landscape environment, largely due to an increasing number of elephants and other herbivores utilizing the Riverfront. The forested area along roads at a further distance from the River has also had a loss of percent cover. The continuous analysis during 1982–2011, utilizing monthly AVHRR (Advanced Very High Resolution Radiometer) NDVI (Normalized Difference Vegetation Index) values, also verifies this change in amount of vegetation is a continuous and ongoing process in this region. This study provides land use planners and managers with a more reliable, efficient and relatively inexpensive tool for analyzing land-cover change across these highly sensitive regions, and highlights the usefulness of a Random Forest classification in conjunction with time series analysis for monitoring savanna landscapes.

Description: Metal matrix composites reinforced with ceramic particles have become the most attractive material in the research and development of new materials for thermal management applications. In this work, 40–60 vol. % TiCx-TiB2/Al composites were successfully fabricated by the method of combustion synthesis and hot press consolidation in an Al-Ti-B4C system. The effect of the TiCx-TiB2 content on the microstructure and compression properties of the composites was investigated. Moreover, the abrasive wear behavior and thermo-physics properties of the TiCx-TiB2/Al composite were studied and compared with the TiCx/Al composite. The compression properties, abrasive wear behavior and thermo-physics properties of the TiCx-TiB2/Al composite are all better than those of the TiCx/Al composite, which confirms that the TiCx-TiB2/Al composite is more appropriate for application as a heat sink.

Description: The ductile-to-brittle transition (DBT) behavior of two similar Fe-Cr-Al oxide dispersion strengthened (ODS) stainless steels was analyzed following the Cottrell–Petch model. Both alloys were manufactured by mechanical alloying (MA) but by different forming routes. One was manufactured as hot rolled tube, and the other in the form of hot extruded bar. The two hot forming routes considered do not significantly influence the microstructure, but cause differences in the texture and the distribution of oxide particles. These have little influence on tensile properties; however, the DBT temperature and the upper shelf energy (USE) are significantly affected because of delamination orientation with regard to the notch plane. Whereas in hot rolled material the delaminations are parallel to the rolling surface, in the hot extruded material, they are randomly oriented because the material is transversally isotropic.

Description: In this study we report on the sintering behavior, microstructure and electrical properties of Al-doped ZnO ceramics containing 0–0.2 wt. % graphene sheets (AZO-GNSs) and processed using spark plasma sintering (SPS). Our results show that the addition of 〈0.25 wt. % GNSs enhances both the relative density and the electrical resistivity of AZO ceramics. In terms of the microstructure, the GNSs are distributed at grain boundaries. In addition, the GNSs are also present between ZnO and secondary phases (e.g., ZnAl2O4) and likely contribute to the measured enhancement of Hall mobility (up to 105.1 cm2·V−1·s−1) in these AZO ceramics. The minimum resistivity of the AZO-GNS composite ceramics is 3.1 × 10−4 Ω·cm which compares favorably to the value of AZO ceramics which typically have a resistivity of 1.7 × 10−3 Ω·cm.

Description: In order to enhance the compatibilization and interfacial adhesion between epoxy and liquid carboxyl-terminated butadiene acrylonitrile (CTBN) rubber, an initiator was introduced into the mixture and heated to initiate the cross-linking reaction of CTBN. After the addition of curing agents, the CTBN/epoxy blends with a localized interpenetrating network structure were prepared. The mechanical properties and morphologies of pre-crosslinked and non-crosslinked CTBN/epoxy blends were investigated. The results show that the tensile strength, elongation at break and impact strength of pre-crosslinked CTBN/epoxy blends are significantly higher than those of non-crosslinked CTBN/epoxy blends, which is primarily due to the enhanced interfacial strength caused by the chemical bond between the two phases and the localized interpenetrating network structure. Both pre-crosslinked and non-crosslinked CTBN/epoxy blends show a bimodal distribution of micron- and nano-sized rubber particles. However, pre-crosslinked CTBN/epoxy blends have smaller micron-sized rubber particles and larger nano-sized rubber particles than non-crosslinked CTBN/epoxy blends. The dynamic mechanical analysis shows that the storage modulus of pre-crosslinked CTBN/epoxy blends is higher than that of non-crosslinked CTBN/epoxy blends. The glass transition temperature of the CTBN phase in pre-crosslinked CTBN/epoxy blends increases slightly compared with the CTBN/epoxy system. The pre-crosslinking of rubber is a promising method for compatibilization and controlling the morphology of rubber-modified epoxy materials.

Description: In order to investigate the methods to heal fatigue cracks in metals, tubular specimens of 1045 steel with axial and radial fatigue cracks were treated under the eddy current. The optical microscope was employed to examine the change of fatigue cracks of specimens before and after the eddy current treatment. The results show that the fatigue cracks along the axial direction of the specimen could be healed effectively in the fatigue crack initiation zone and the crack tip zone under the eddy current treatment, and the healing could occur within a very short time. The voltage breakdown and the transient thermal compressive stress caused by the detouring of eddy current around the fatigue crack were the main factors contributing to the healing in the fatigue crack initiation zone and the crack tip zone, respectively. Eddy current treatment may be a novel and effective method for crack healing.

Description: In this study microcrystalline cellulose (MCC) was oxidized by 2,2,6,6-tetramethylpiperidine-1-oxyl radical (TEMPO)-mediated oxidation. The treated cellulose slurry was mechanically homogenized to form a transparent dispersion which consisted of individual cellulose nanofibers with uniform widths of 3–4 nm. Bio-nanocomposite films were then prepared from a polyvinyl alcohol (PVA)-chitosan (CS) polymeric blend with different TEMPO-oxidized cellulose nanofiber (TOCN) contents (0, 0.5, 1.0 and 1.5 wt %) via the solution casting method. The characterizations of pure PVA/CS and PVA/CS/TOCN films were performed in terms of field emission scanning electron microscopy (FESEM), tensile tests, thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD). The results from FESEM analysis justified that low loading levels of TOCNs were dispersed uniformly and homogeneously in the PVA-CS blend matrix. The tensile strength and thermal stability of the films were increased with the increased loading levels of TOCNs to a maximum level. The thermal study indicated a slight improvement of the thermal stability upon the reinforcement of TOCNs. As evidenced by the FTIR and XRD, PVA and CS were considered miscible and compatible owing to hydrogen bonding interaction. These analyses also revealed the good dispersion of TOCNs within the PVA/CS polymer matrix. The improved properties due to the reinforcement of TOCNs can be highly beneficial in numerous applications.

Description: Biofouling often occurs in cooling water systems, resulting in the reduction of heat exchange efficiency and corrosion of the cooling pipes, which raises the running costs. Therefore, controlling biofouling is very important. To regulate biofouling, we focus on the formation of biofilm, which is the early step of biofouling. In this study, we investigated whether silver or copper nanoparticles-dispersed silane coatings inhibited biofilm formation in cooling systems. We developed a closed laboratory biofilm reactor as a model of a cooling pipe and used seawater as a model for cooling water. Silver or copper nanoparticles-dispersed silane coating (Ag coating and Cu coating) coupons were soaked in seawater, and the seawater was circulated in the laboratory biofilm reactor for several days to create biofilms. Three-dimensional images of the surface showed that sea-island-like structures were formed on silane coatings and low concentration Cu coating, whereas nothing was formed on high concentration Cu coatings and low concentration Ag coating. The sea-island-like structures were analyzed by Raman spectroscopy to estimate the components of the biofilm. We found that both the Cu coating and Ag coating were effective methods to inhibit biofilm formation in cooling pipes.

Description: Fretting is a phenomenon that occurs at the contacts of surfaces that are subjected to oscillatory relative movement of small amplitudes. Depending on service conditions, fretting may significantly reduce the service life of a component due to fretting fatigue. In this regard, the analysis of stresses at contact is of great importance for predicting the lifetime of components. However, due to the complexity of the fretting phenomenon, analytical solutions are available for very selective situations and finite element (FE) analysis has become an attractive tool to evaluate stresses and to study fretting problems. Recent laboratory studies in fretting fatigue suggested the presence of stress singularities in the stick-slip zone. In this paper, we constructed finite element models, with different element sizes, in order to verify the existence of stress singularity under fretting conditions. Based on our results, we did not find any singularity for the considered loading conditions and coefficients of friction. Since no singularity was found, the present paper also provides some comments regarding the convergence rate. Our analyses showed that the convergence rate in stress components depends on coefficient of friction, implying that this rate also depends on the loading condition. It was also observed that errors can be relatively high for cases with a high coefficient of friction, suggesting the importance of mesh refinement in these situations. Although the accuracy of the FE analysis is very important for satisfactory predictions, most of the studies in the literature rarely provide information regarding the level of error in simulations. Thus, some recommendations of mesh sizes for those who wish to perform FE analysis of fretting problems are provided for different levels of accuracy.

Description: This study is aimed at a better understanding of how upstream runoff formation affected the cropping intensity (CI: number of harvests) in the Aral Sea Basin (ASB) between 2000 and 2012. MODIS 250 m NDVI time series and knowledge-based pixel masking that included settlement layers and topography features enabled to map the irrigated cropland extent (iCE). Random forest models supported the classification of cropland vegetation phenology (CVP: winter/summer crops, double cropping, etc.). CI and the percentage of fallow cropland (PF) were derived from CVP. Spearman’s rho was selected for assessing the statistical relation of CI and PF to runoff formation in the Amu Darya and Syr Darya catchments per hydrological year. Validation in 12 reference sites using multi-annual Landsat-7 ETM+ images revealed an average overall accuracy of 0.85 for the iCE maps. MODIS maps overestimated that based on Landsat by an average factor of ~1.15 (MODIS iCE/Landsat iCE). Exceptional overestimations occurred in case of inaccurate settlement layers. The CVP and CI maps achieved overall accuracies of 0.91 and 0.96, respectively. The Amu Darya catchment disclosed significant positive (negative) relations between upstream runoff with CI (PF) and a high pressure on the river water resources in 2000–2012. Along the Syr Darya, reduced dependencies could be observed, which is potentially linked to the high number of water constructions in that catchment. Intensified double cropping after drought years occurred in Uzbekistan. However, a 10 km × 10 km grid of Spearman’s rho (CI and PF vs. upstream runoff) emphasized locations at different CI levels that are directly affected by runoff fluctuations in both river systems. The resulting maps may thus be supportive on the way to achieve long-term sustainability of crop production and to simultaneously protect the severely threatened environment in the ASB. The gained knowledge can be further used for investigating climatic impacts of irrigation in the region.

Description: The spatial separation of the transmitter and receiver in Bistatic Synthetic Aperture Radar (BiSAR) makes it a promising and useful supplement to a classical Monostatic SAR system (MonoSAR). This paper proposes a novel integrated time and phase synchronization strategy for a multichannel spaceborne-stationary BiSAR system. Firstly, the time synchronization strategy is proposed, which includes Pulse Repetition Frequency (PRF) generation under noisy conditions, multichannel calibration and the alignment of the recorded data with the orbital data. Furthermore, the phase synchronization strategy, which fully considers the deteriorative factors in the BiSAR configuration, is well studied. The contribution of the phase synchronization strategy includes two aspects: it not only compensates the phase error, but also improves the Signal to Noise Ratio (SNR) of the obtained signals. Specifically, all direct signals on different PRF time can be reconstructed with the shift and phase compensation operation using a reference signal. Besides, since the parameters of the reference signal can be estimated only once using the selected practical direct signal and a priori information, the processing complexity is well reduced. Final imaging results with and without compensation for real data are presented to validate the proposed synchronization strategy.

Description: Mangroves are ecologically important ecosystems and globally protected. The purpose of this study was to evaluate the effectiveness of mangrove conservation efforts in two adjacent protected areas in China that were under the management policies of the Ramsar Convention (Mai Po Marshes Nature Reserve (MPMNR), Hong Kong) and China’s National Nature Reserve System (Futian Mangrove National Nature Reserve (FMNNR), Shenzhen). To achieve this goal, eleven Landsat images were chosen and classified, areal extent and landscape metrics were then calculated. The results showed that: from 1973–2015, the areal extent of mangroves in both reserves increased, but the net change for the MPMNR (281.43 hm2) was much higher than those of the FMNNR (101.97 hm2). In general, the area-weighted centroid of the mangroves in FMNNR moved seaward by approximately 120 m, whereas in the MPMNR, the centroid moved seaward even farther (410 m). Although both reserves saw increased integrality and connectivity of the mangrove patches, the patches in the MPMNR always had higher integrality than those in the FMNNR. We concluded that the mangroves in the MPMNR were more effectively protected than those in the FMNNR. This study may provide assistance to the formulation of generally accepted criteria for remote sensing-based evaluation of conservation effectiveness, and may facilitate the development of appropriate mangrove forest conservation and management strategies in other counties.

Description: Monitoring the dynamics of surface water using remotely sensed data generally requires both high spatial and high temporal resolutions. One effective and popular approach for achieving this is image fusion. This study adopts a widely accepted fusion model, the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), for blending the newly available coarse-resolution Suomi NPP-VIIRS data with Landsat data in order to derive water maps at 30 m resolution. The Pan-sharpening technique was applied to preprocessing NPP-VIIRS data to achieve a higher-resolution before blending. The modified Normalized Difference Water Index (mNDWI) was employed for mapping surface water area. Two fusion alternatives, blend-then-index (BI) or index-then-blend (IB), were comparatively analyzed against a Landsat derived water map. A case study of mapping Poyang Lake in China, where water distribution pattern is complex and the water body changes frequently and drastically, was conducted. It has been revealed that the IB method derives more accurate results with less computation time than the BI method. The BI method generally underestimates water distribution, especially when the water area expands radically. The study has demonstrated the feasibility of blending NPP-VIIRS with Landsat for achieving surface water mapping at both high spatial and high temporal resolutions. It suggests that IB is superior to BI for water mapping in terms of efficiency and accuracy. The finding of this study also has important reference values for other blending works, such as image blending for vegetation cover monitoring.

Description: This paper is concerned with the application of computational intelligence techniques to the conceptual design and development of a large-scale floating settlement. The settlement in question is a design for the area of Urla, which is a rural touristic region located on the west coast of Turkey, near the metropolis of Izmir. The problem at hand includes both engineering and architectural aspects that need to be addressed in a comprehensive manner. We thus adapt the view as a multi-objective constrained real-parameter optimization problem. Specifically, we consider three objectives, which are conflicting. The first one aims at maximizing accessibility of urban functions such as housing and public spaces, as well as special functions, such as a marina for yachts and a yacht club. The second one aims at ensuring the wind protection of the general areas of the settlement, by adequately placing them in between neighboring land masses. The third one aims at maximizing visibility of the settlement from external observation points, so as to maximize the exposure of the settlement. To address this complex multi-objective optimization problem and identify lucrative alternative design solutions, a multi-objective harmony search algorithm (MOHS) is developed and applied in this paper. When compared to the Differential Evolution algorithm developed for the problem in the literature, we demonstrate that MOHS achieves competitive or slightly better performance in terms of hyper volume calculation, and gives promising results when the Pareto front approximation is examined.

Description: Membrane-based gas separation has attracted a great deal of attention recently due to the requirement for high purity gasses in industrial applications like fuel cells, and because of environment concerns, such as global warming. The current methods of cryogenic distillation and pressure swing adsorption are energy intensive and costly. Therefore, polymer membranes have emerged as a less energy intensive and cost effective candidate to separate gas mixtures. However, the use of polymeric membranes has a drawback known as the permeability-selectivity tradeoff. Many approaches have been used to overcome this limitation including the use of polymer blends. Polymer blending technology synergistically combines the favorable properties of different polymers like high gas permeability and high selectivity, which are difficult to attain with a single polymer. During polymer mixing, polymers tend to uncontrollably phase separate due to unfavorable thermodynamics, which limits the number of completely miscible polymer combinations for gas separations. Therefore, compatibilizers are used to control the phase separation and to obtain stable membrane morphologies, while improving the mechanical properties. In this review, we focus on immiscible polymer blends and the use of compatibilizers for gas separation applications.

Description: Leaf area index (LAI) is a key parameter used to describe vegetation structures and is widely used in ecosystem biophysical process and vegetation productivity models. Many algorithms have been developed for the estimation of LAI based on remote sensing images. Our goal was to produce accurate and timely predictions of grassland LAI for the meadow steppes of northern China. Here, we compare the predictive power of regression approaches and hybrid geostatistical methods using Chinese Huanjing (HJ) satellite charge coupled device (CCD) data. The regression methods evaluated include partial least squares regression (PLSR), artificial neural networks (ANNs) and random forests (RFs). The two hybrid geostatistical methods were regression kriging (RK) and random forests residuals kriging (RFRK). The predictions were validated for different grassland types and different growing stages, and their performances were also examined by adding several groups of vegetation indices (VIs). The two hybrid geostatistical models (RK and RFRK) yielded the most accurate predictions (root mean squared error (RMSE) = 0.21 m2/m2 and 0.23 m2/m2 for RK and RFRK, respectively), followed by the RF model (RMSE = 0.27 m2/m2), which was the most accurate among the regression models. These three models also exhibited the best temporal performance across the duration of the growing season. The PLSR and ANN models were less accurate (RMSE = 0.33 m2/m2 and 0.35 m2/m2 for ANN and PLSR, respectively), and the PLSR model performed the worst (exhibiting varied temporal performance and unreliable prediction accuracy that was susceptible to ground conditions). By adding VIs to the predictor variables, the predictions of the PLSR and ANN models were obviously improved (RMSE improved from 0.35 m2/m2 to 0.28 m2/m2 for PLSR and from 0.33 m2/m2 to 0.28 m2/m2 for ANN); the RF and RFRK models did not generate more accurate predictions and the performance of the RK model declined (RMSE decreased from 0.21 m2/m2 to 0.32 m2/m2).

Description: We systematically investigated the effects of Al-impurity type on the formation energy, crystal structure, charge density, electronic structure, and optical properties of ZnO by using density functional theory and the Hubbard-U method. Al-related defects, such as those caused by the substitution of Zn and O atoms by Al atoms (Als(Zn) and Als(O), respectively) and the presence of an interstitial Al atom at the center of a tetrahedron (Ali(tet)) or an octahedron (Ali(oct)), and various Al concentrations were evaluated. The calculated formation energy follows the order Ef(Als(Zn)) 〈 Ef(Ali(tet)) 〈 Ef(Ali(oct)) 〈 Ef(Als(O)). Electronic structure analysis showed that the Als(Zn), Als(O), Ali(tet), and Ali(oct) models follow n-type conduction, and the optical band gaps are higher than that of pure ZnO. The calculated carrier concentrations of the Als(O) and Ali(tet)/Ali(oct) models are higher than that of the Als(Zn) model. However, according to the curvature of the band structure, the occurrence of interstitial Al atoms or the substitution of O atoms by Al atoms results in a high effective mass, possibly reducing the carrier mobility. The average transmittance levels in the visible light and ultraviolet (UV) regions of the Als(Zn) model are higher than those of pure ZnO. However, the presence of an interstitial Al atom within the ZnO crystal reduces transmittance in the visible light region; Als(O) substantially reduces the transmittance in the visible light and UV regions. In addition, the properties of ZnO doped with various Als(Zn) concentrations were analyzed.

Description: The problem of optimal multicast routing in Wireless Mess Networks (WMNs) with Quality-of-Service (QoS) provisioning, which is Non-Deterministic Polynomial (NP)-complete, is studied in this paper. The existing algorithms are not very efficient or effective. In order to find an approximation optimal solution for WMNs in feasible time from source to the set of destination nodes, combining the previous deterministic algorithm with the well-known Minimum Path Cost Heuristic (MPH) algorithm, a novel multicast heuristic approximation (NMHA) algorithm with QoS provisioning is proposed in this paper to deal with it. The theoretical validations for the proposed algorithm are presented to show its performance and efficiency. After that, the random static networks with different destination nodes are evaluated. Simulations in these networks show that the proposed algorithm can achieve the approximate optimal solution with the approximation factor of 2(1 + ε)(1 − 1/q) and the time complexity of O(qmn2τK−1).

Description: Cloud storage offers a popular environment for users to store and share content. Yet, content sharing leads to multiple downloads of the same content when users synchronize devices. These downloads contribute to bandwidth waste and increase server workloads. To what extent does this occur? Would network caches alleviate the problem? The authors address these questions by investigating the traffic generated by Dropbox, a popular cloud storage service. Using data collected from four networks, they show that a large fraction (57-70 percent) of downloads generated by Dropbox users is associated with content shared among multiple devices. Moreover, despite optimizations such as the LAN Sync protocol, up to 25 percent of Dropbox download traffic comes from content replicas. The authors then evaluate an alternative synchronization architecture that uses caches to offload storage servers from such downloads. Their experiments show that the approach cost-effectively avoids most repetitive downloads, benefiting service providers, the network, and end users.

Description: Bot detection -- identifying a software program that's using a computer system -- is an increasingly necessary security task. Existing solutions balance proof of human identity with unobtrusiveness in users' workflows. Cognitive modeling and natural interaction might provide stronger security and less intrusiveness.

Description: The IPv6 Internet is an important component of the Internet's continued growth and evolution. By several metrics, IPv6 has grown exponentially and now carries nontrivial amounts of production traffic. Less well-understood, however, is IPv6's topology and the way in which providers are using their IPv6 address allocations. Rather than relying on passive measurements or heuristics, which can bias inferences, here the authors use uniform active probing. They execute Internet Control Message Protocol (ICMP)-Paris traceroute probes to an address in each /48 in all /32's advertised in the global IPv6 routing table (approximately 400 million traces from 26 globally distributed vantage points). At this granularity, they characterize the distribution of IPv6 interface addresses in the wild, and find significant differences among providers and regions. By providing insight into the structure of the current IPv6 Internet router interface addressing method, their hope is to better inform efforts to design future intelligent, active IPv6 topology-mapping algorithms and systems.

Description: This study focused on the development of a crack repair stick as a new repair method along with self-healing materials that can be used to easily repair the cracks in a concrete structure at the construction site. In developing this new repair technique, the self-healing efficiency of various cementitious materials was considered. Likewise, a crack repair stick was developed to apply to concrete structures with 0.3 mm or lower crack widths. The crack repair stick was made with different materials, such as cement, an expansive material (C12A7), a swelling material, and calcium carbonate, to endow it with a self-healing property. To verify the performance of the crack repair stick for concrete structures, two types of procedures (field experiment and field absorption test) were carried out. As a result of such procedures, it was concluded that the developed crack repair stick could be used on concrete structures to reduce repair expenses and for the improved workability, usability, and serviceability of such structures. On the other hand, to evaluate the self-healing performance of the crack repair stick, various tests were conducted, such as the relative dynamic modulus of elasticity test, the water tightness test, the water permeability test, observation via a microscope, and scanning electron microscope (SEM) analysis. From the results, it is found that water leakage can be prevented and that the durability of a concrete structure can be improved through self-healing. Also, it was verified that the cracks were perfectly closed after 28 days due to application of the crack repair stick. These results indicate the usability of the crack repair stick for concrete structures, and its self-healing efficiency.

Description: Dye wastewater severely threatens the environment due to its hazardous and toxic effects. Although many methods are available to degrade dyes, most of them are far from satisfactory. The proposed research provides a green and sustainable approach to degrade an azo dye, methyl orange, by electrically active biofilms (EABs) in the presence of solid and hollow palladium (Pd) nanoparticles. The EABs acted as the electron generator while nanoparticles functioned as the electron carrier agents to enhance degradation rate of the dye by breaking the kinetic barrier. The hollow Pd nanoparticles showed better performance than the solid Pd nanoparticles on the dye degradation, possibly due to high specific surface area and cage effect. The hollow cavities provided by the nanoparticles acted as the reaction centers for the dye degradation.

Description: Along-track multichannel synthetic aperture radar is usually used to achieve ground moving target detection and imaging. Nevertheless, there is a design dilemma between azimuth high resolution and wide swath (HRWS). To solve this problem in HRWS mode, we introduce a virtual multichannel (VMC) scheme. For each virtual channel, the low real pulse repetition frequency (PRF) improves the ability of resolving range ambiguity for wide-swath, and the high virtual PRF improves the capability of resolving Doppler ambiguity for azimuth high resolution. For multiple virtual channels, strong ground clutter is eliminated by the joint VMC processing. Furthermore, a detailed signal model of a moving target in the virtual channel is given, and the special false-peak effect in the azimuthal image is analyzed. Moreover, we propose a novel ground moving target processing method based on the VMC scheme and the clutter suppression interferometry (CSI) technique, which is called VMC-CSI. The integration of detection, location, velocity estimation, and imaging for ground moving targets can be achieved. Accounting for the unresolved main peak and false peak for a moving target, in the VMC-CSI method, we adopt a two-step scheme to estimate the radial velocity and along-track velocity, namely, rough estimation and precise estimation. Meanwhile, considering the same interferometric phases of the main peak and the false peak, we use false peaks first for the robustness of initial azimuth location estimation and remove false peaks afterward. Numerical simulations are provided for testing the effect of the false peak and the effectiveness of VMC-CSI.

Description: This paper presents an open-source canopy height profile (CHP) toolkit designed for processing small-footprint full-waveform LiDAR data to obtain the estimates of effective leaf area index (LAIe) and CHPs. The use of the toolkit is presented with a case study of LAIe estimation in discontinuous-canopy fruit plantations. The experiments are carried out in two study areas, namely, orange and almond plantations, with different percentages of canopy cover (48% and 40%, respectively). For comparison, two commonly used discrete-point LAIe estimation methods are also tested. The LiDAR LAIe values are first computed for each of the sites and each method as a whole, providing “apparent” site-level LAIe, which disregards the discontinuity of the plantations' canopies. Since the toolkit allows for the calculation of the study area LAIe at different spatial scales, between-tree-level clumping can be easily accounted for and is then used to illustrate the impact of the discontinuity of canopy cover on LAIe retrieval. The LiDAR LAIe estimates are therefore computed at smaller scales as a mean of LAIe in various grid-cell sizes, providing estimates of “actual” site-level LAIe. Subsequently, the LiDAR LAIe results are compared with theoretical models of “apparent” LAIe versus “actual” LAIe, based on known percent canopy cover in each site. The comparison of those models to LiDAR LAIe derived from the smallest grid-cell sizes against the estimates of LAIe for the whole site has shown that the LAIe estimates obtained from the CHP toolkit provided values that are closest to those of theoretical models.

Description: Multifrequency and multioffset ground-penetrating radar data acquisition modes are used to maximize the information content and parameter retrieval capabilities. However, they also increase the computational cost dedicated to the inversion procedure. In this paper, the impact of the number of frequencies and the multistatic configurations on the information retrieval capabilities is investigated through the response surface topographies of the objective functions. We resort to a full-wave-inversion procedure and a recently developed electromagnetic model which takes advantage of a closed-form solution of Maxwell's equations to describe the antenna–medium system. We show with numerical and laboratory experiments the possibility of reducing the number of frequencies from several hundreds to one or several tens of components without affecting the information retrieval capabilities. We also show through several scenarios that the presence of a perfect electrical conductor increases the number of frequencies required to ensure an acceptable retrieval of the subsurface properties whereas the conductivity of the first layer and the relative permittivity of the second layer do not affect it. The results highlight that information content analyses are important in order to study and optimize data acquisition and inversion procedures, and thereby the computation time.

Description: This paper addresses some important aspects for the spaceborne/stationary bistatic synthetic aperture radar (SAR) (SS-BiSAR) imaging with the transmitter, TerraSAR-X, operated in staring spotlight (ST) mode. With the large integration time reaching 7.5 s and the azimuth steering span reaching $pm 2.2^{0}$ , several significant effects occur, including troposphere delay, precision phase and time synchronization, the curved orbit effect, azimuth spectrum aliasing problem, and efficient frequency domain focusing algorithm. To circumvent the main effects, corresponding solutions are proposed, including a precise synchronization strategy with troposphere delay correction based on the direct signal from the transmitter and a modified and integrative bistatic polar format algorithm (PFA). This paper covers the theoretical development, implementation, and analysis of the SS-BiSAR PFA based on 2-D fast Gaussian gridding nonuniform fast Fourier transform with wavefront curvature correction. Furthermore, the high-resolution ST-mode SS-BiSAR image processed by the proposed algorithm is acquired, and the differences of scattering behaviors between monostatic and bistatic SAR images are analyzed in detail.

Description: The ground penetrating radar (GPR) is a popular and successful remote sensing modality that has been investigated for landmine detection. GPR offers excellent detection performance, but it is limited by a low rate of advance (ROA) due to its short sensing standoff distance. Standoff distance refers to the distance between the sensing platform and the location in front of the platform where the GPR senses the ground. Large standoff (high ROA) sensing modalities have been investigated as alternatives to the GPR, but they do not yet achieve comparable detection performance. This paper proposes a new sensor management approach, called multistate management (MSM), which combines large and short standoff sensors on the same platform in a way that leverages their respective advantages, yielding a system with better ROA and detection performance. MSM is more difficult to analyze than traditional systems because it allows sensor activity and system velocity to change over time. Therefore, a new probabilistic model based on queuing theory, called Q-MSM, is also proposed for analyzing and designing detection systems operating with MSM. Simulations were conducted using real field-collected data for a system with a large standoff forward-looking infrared camera and a GPR. The system is operated with MSM, and the results show that this leads to better ROA and detection performance than can be attained otherwise. Furthermore, the results show that Q-MSM can accurately predict the behavior of the MSM system, validating its utility for analyzing and designing such systems.

Description: The concept of simultaneous source has recently become of interest in seismic exploration, due to its efficient or economic acquisition or both. The blended data overlapped between shot records are acquired in simultaneous source acquisition. Separating the blended data and recovering the single-shot seismic signals (the recovery) are of great importance in the scenario of current workflows, which can be called seismic simultaneous source separation. In the context of general random time-dithering firing, we propose an alternative method to separate the blended data by combining patchwise dictionary learning with sparse inversion, in which the dictionary is directly learned from the measured blended data. Apart from the sparse coding used for the coefficients, an additional regularization term on the dictionary is particularly designed to remove the severe interference noise. The efficient and flexible alternating direction method of multipliers (ADMM) is used to update the dictionary in the used alternating optimization scheme. The results obtained from the synthetic and real examples reasonably suggest that the separated seismic signals by using dictionary learning are more accurate and robust compared with that using the fixed transform basis, such as the local discrete cosine transform. The learned dictionary tailors for the recovery and is similar to the local seismic waveform, which improves the sparsity of the recovery substantially and is highly advantageous for producing the promised results.

Description: This paper investigates the impact of the soil moisture distribution in the top layer on the accuracy of soil moisture retrieval by microwave remote sensing methods. We modeled soil emission at L-band by coherent and noncoherent models for the different moisture distributions in the top layer. As a result, it is found that, at high moisture gradients, the difference between average moisture within the sensing depth at L-band and the moisture retrievable from remote sensing data can be more than 20% in absolute terms. In addition, high differences between Soil Moisture and Ocean Salinity (SMOS) Level 2 data and the in situ measurements were revealed in cases of high gradients. Such high gradients may be observed during some time in the top layer of the drying soil after rainfall. These differences are significantly more than the accuracy declared by SMOS development team. We proposed a simple method that allows the assessment of the type of soil moisture profile by SMOS and Global Change Observation Mission‐Water “SHIZUKU” (GCOM-W1) satellites data. The procedure for simple processing of data of the two satellites is described. In addition, we compared the type of soil moisture profile retrieved from satellite data and the soil moisture profile found by in situ measurements.

Description: An iterative alternating direction method of multipliers (ADMM) is proposed for inverse finite-element–boundary-integral (FE–BI) problem with total variation (TV) regularization. The inverse FE–BI fits to a wide class of penetrable sensing applications, where this study specifically targets the problem of radio tomography of asteroid interior structure using orbiting spacecraft. The TV regularizer enforces sparsity on the gradient of reconstructed permittivity, which agrees well with the “piecewise constant” reality of “rocks embedded in soil” scenario and, meanwhile, addresses the inherent ill-posedness. For large-scale asteroid problems, the distributed ADMM algorithm is adapted to solve the linear TV inversion at each iteration. The 2-D inversion is validated with the Fresnel Institute measurement data. Simulated cases of asteroid internal imaging are also presented. The proposed iterative ADMM can be also applied to similar penetrable imaging applications.

Description: GNSS Reflectometry, Scatterometry and Radio Occultation aboard ISS is the mission concept under study within the European Space Agency. Its core payload consists of an interferometric GNSS-Reflectometry ocean altimeter/scatterometer which does not need to generate any clean replicas of the GNSS codes for its operation. This paper describes a new interferometric technique by which such payload could also perform radio occultation as an add-on, without requiring any additional hardware resources, like the generation of clean code replicas or a storage of them. Two possibilities are studied. The first one consists of performing the complex autocorrelation function of the received signal transmitted by a rising or setting GNSS satellite. The autocorrelation function is evaluated around time epochs that are multiples of the period of suitable codes found in the modulation of the navigation signals. Satellite discrimination has to be performed spatially, through the antenna pattern. The second possibility consists in acquiring the reference signal separately from the occultation event which, in turn, has two options depending upon the geometry at which the reference is recorded: zenithal and top of the atmosphere. The signal-to-noise ratio, the satellite discrimination, and the impact of clock errors are assessed.