bluuebunny/crossref_metadata_2025 huggingface dataset:
Cell Adhesive Character of Phenylboronic Acid-Modified Insulin and Its Potential as Long-Acting Insulin
Authors: Ohno Yui , Kawakami Momoko , Seki Tomohiro , Miki Ryotaro , Seki Toshinobu , Egawa Yuya
Published: August 2019

Phenylboronic acid (PBA) derivatives have attracted substantial attention owing to their unique character of forming dynamic covalent bonds with polyol compounds. Recent studies have shown interactions between PBA and sugar chains on the cell surface; they have interesting applications for sensors and drug delivery systems. In this study, we prepared phenylboronic acid-modified insulin (PBA-Ins) to evaluate its glucose-lowering activity and cell adhesiveness. In the case of intravenous injection, PBA-Ins showed longer glucose-lowering activity than native insulin. We hypothesized that this prolonged effect was the result of the interaction between the PBA moiety and sugar chains on the cell surface. Red blood cells (RBCs) were used as a cell model, and we confirmed PBA-Ins’s affinity for RBCs, which induced RBC agglutination. Interestingly, using an alternative PBA-Ins administration route markedly changed its glucose-lowering activity. Unlike the intravenous injection of PBA-Ins, the subcutaneous injection showed a small effect on glucose level, which indicated that a small amount of PBA-Ins was absorbed into the bloodstream. This suggested the importance of investigating the interaction between the PBA moiety and many types of cells, such as adipocytes, in subcutaneous tissues.
Selenium Accumulation, Speciation and Localization in Brazil Nuts (Bertholletia excelsa H.B.K.)
Authors: Lima Leonardo W. , Stonehouse Gavin C. , Walters Christina , Mehdawi Ali F. El , Fakra Sirine C. , Pilon-Smits Elizabeth A. H.
Published: August 2019

More than a billion people worldwide may be selenium (Se) deficient, and supplementation with Se-rich Brazil nuts may be a good strategy to prevent deficiency. Since different forms of Se have different nutritional value, and Se is toxic at elevated levels, careful seed characterization is important. Variation in Se concentration and correlations of this element with other nutrients were found in two batches of commercially available nuts. Selenium tissue localization and speciation were further determined. Mean Se levels were between 28 and 49 mg kg−1, with up to 8-fold seed-to-seed variation (n = 13) within batches. Brazil nut Se was mainly in organic form. While present throughout the seed, Se was most concentrated in a ring 1 to 2 mm below the surface. While healthy, Brazil nuts should be consumed in moderation. Consumption of one seed (5 g) from a high-Se area meets its recommended daily allowance; the recommended serving size of 30 g may exceed the allowable daily intake (400 μg) or even its toxicity threshold (1200 μg). Based on these findings, the recommended serving size may be re-evaluated, consumers should be warned not to exceed the serving size and the seed may be sold as part of mixed nuts, to avoid excess Se intake.
Biotechnological Potential of LSD1, EDS1, and PAD4 in the Improvement of Crops and Industrial Plants
Authors: Bernacki Maciej Jerzy , Czarnocka Weronika , Szechyńska-Hebda Magdalena , Mittler Ron , Karpiński Stanisław
Published: August 2019

Lesion Simulating Disease 1 (LSD1), Enhanced Disease Susceptibility (EDS1) and Phytoalexin Deficient 4 (PAD4) were discovered a quarter century ago as regulators of programmed cell death and biotic stress responses in Arabidopsis thaliana. Recent studies have demonstrated that these proteins are also required for acclimation responses to various abiotic stresses, such as high light, UV radiation, drought and cold, and that their function is mediated through secondary messengers, such as salicylic acid (SA), reactive oxygen species (ROS), ethylene (ET) and other signaling molecules. Furthermore, LSD1, EDS1 and PAD4 were recently shown to be involved in the modification of cell walls, and the regulation of seed yield, biomass production and water use efficiency. The function of these proteins was not only demonstrated in model plants, such as Arabidopsis thaliana or Nicotiana benthamiana, but also in the woody plant Populus tremula x tremuloides. In addition, orthologs of LSD1, EDS1, and PAD4 were found in other plant species, including different crop species. In this review, we focus on specific LSD1, EDS1 and PAD4 features that make them potentially important for agricultural and industrial use.
Theoretical Prediction of Mechanical Strength and Desalination Performance of One-Atom-Thick Hydrocarbon Polymer in Pressure-Driven Separation
Authors: Sun Shuangqing , Shan Fei , Lyu Qiang , Li Chunling , Hu Songqing
Published: August 2019

One-atom-thick materials hold promise for the future of membrane-based gas purification and water filtration applications. However, there are a few investigations on the mechanical properties of these materials under pressure-driven condition. Here, by employing molecular simulation techniques and continuum mechanics simulation, we investigate the mechanical strength of two-dimensional hydrocarbon polymers containing sub-nanometer pores with various topologies. We demonstrate that the mechanical strengths of the membranes are correlated with their pore sizes and geometries. In addition, when the pore size of substrates is controlled within a reasonable range, all of the membrane candidates can withstand the practical hydraulic pressure of few megapascal. The studied materials also exhibit better seawater desalination performance as compared to the traditional polymeric reverse osmosis membrane. This work presents a new route to design new separation membrane, and also propose a simulation method to evaluate the mechanical strength and desalination performance.
Dielectric and Thermal Conductivity of Epoxy Resin Impregnated Nano-h-BN Modified Insulating Paper
Authors: Yang Hongda , Chen Qingguo , Wang Xinyu , Chi Minghe , Liu Heqian , Ning Xin
Published: August 2019

Epoxy resin-impregnated insulation paper (RIP) composites are used as the inner insulation of dry condenser bushing in the ultra-high voltage direct current (UHVDC) power transmission system. To improve the dielectric properties and heat conductivity of RIP, hexagonal boron nitride (h-BN) nano-flakes are added to the insulation paper at concentrations of 0–50 wt % before impregnation with pure epoxy resin. X-ray diffraction (XRD), scanning electron microscopy (SEM) observations, thermal conductivity as well as the typical dielectric properties of direct current (DC) volume conductivity. DC breakdown strength and space charge characteristics were obtained. The maximum of nano-h-BN modified heat conductivity reach 0.478 W/(m·K), increased by 139% compared with unmodified RIP. The DC breakdown electric field strength of the nano-h-BN modified RIP does not reduce much. The conductivity of nano-h-BN modified is less sensitive to temperature. As well, the space charge is suppressed when the content is 50 wt %. Therefore, the nano-h-BN modified RIP is potentially useful in practical dry DC bushing application.
Thermal and Mechanical Behavior of Wood Plastic Composites by Addition of Graphene Nanoplatelets
Authors: Zhang Xingli , Zhang Jinglan , Wang Ruihong
Published: August 2019

Wood plastic composites (WPCs) incorporating graphene nano-platelets (GNPs) were fabricated using hot-pressed technology to enhance thermal and mechanical behavior. The influences of thermal filler content and temperature on the thermal performance of the modified WPCs were investigated. The results showed that the thermal conductivity of the composites increased significantly with the increase of GNPs fillers, but decreased with the increase of temperature. Moreover, thermogravimetric analysis demonstrated that coupling GNPs resulted in better thermal stability of the WPCs. The limiting oxygen index test also showed that addition of GNPs caused good fire retardancy in WPCs. Incorporation of GNPs also led to an improvement in mechanical properties as compared to neat WPCs. Through a series of mechanical performance tests, it could be concluded that the flexural and tensile moduli of WPCs were improved with the increase of the content of fillers.
Pyrene-Functionalized Polyacetylenes: Synthesis and Photoluminescence Property
Authors: Shen Tanxiao , Jiang Nan , Zhang Xiao’a , He Lirong , Lang Xian Hua , Sun Jing Zhi , Zhao Hui
Published: August 2019

Four pyrene-functionalized polyacetylenes were designed and prepared through a typical post-polymerization modification route, which is the highly efficient reaction between activated ester and primary anime groups. The chemical structures of the resultant polymers were characterized with multiple spectroscopic techniques and the data indicated the successful functionalization of the polyacetylenes. The introduction of the pyrene moieties into the polymer structure allowed us to investigate the interactions between the polymer backbone and side chains. For the mono-substituted polyacetylenes, both the monomer and excimer emission features of the pyrene groups could be recorded, while for the di-substituted polyacetylenes, the fluorescence from the pyrene excimer vanished and the fluorescence intensity from the pyrene monomer decreased, the fluorescence from the polymer chain predominated the emission features. The concomitant energy transfer from the pyrene monomer and excimer to poly(diphenylacetylene) backbone was associated with the underlying mechanism. In addition to the substitution modes, the linkage between the poly(diphenylacetylene) backbone and the pyrene moiety also played a significant role in the determination of the emission species. A long alkyl spacer was beneficial to the pyrene monomer emission while a short one may be helpful to the formation of the excimer and intramolecular energy transfer.
Improving the Performance of Entities in the Mining Industry by Optimizing Green Business Processes and Emission Inventories
Authors: Oncioiu Ionica , Căpuşneanu Sorinel , Oprea Constantin Dana-Maria , Türkeș Mirela , Topor Dan , Bîlcan Florentina , Petrescu Anca
Published: August 2019

Due to environmental considerations, environmental sustainability has become the main target of contemporary organizations, which has a direct influence on increasing their performance. The purpose of this study was to present the efficiency of green business process optimization for the performances of mining entities. Quantitative research was carried out on a sample of 209 people in an economic entity in the mining industry. The results of the study indicated real possibilities to achieve the objectives set in the research undertaken. Using business process management, the authors examined how green business processes can be optimized in a Romanian mining entity. The main results determined the degree of pollution from suspended and sedimentary dust particles due to coal production from the mining entity that was studied. Moreover, the present research proved that certain key environmental indicators underlie the performance and optimization of green business processes. The practical implications of this study are to respect and continually improve the management of the processes of activities, to reduce the costs of depollution and increase the performances.
Analysis of Thermomechanical Properties of Selected Class of Recycled Thermoplastic Materials Based on Their Applications
Authors: Momanyi Job , Herzog Michael , Muchiri Peter
Published: August 2019

Polypropylene and polystyrene are petroleum-based thermoplastics which are commonly used and disposed of in the environment after their service life, leading to environmental degradation. There is a need to recycle polypropylene and polystyrene, but the effect of recycling on thermo-mechanical properties is not well understood. This study aims to determine thermo-mechanical properties of the recycled polypropylene and recycled polystyrene and compare them with corresponding virgin polypropylene and newly produced polystyrene (general purpose polystyrene 1540 and high impact polystyrene 7240). The study was carried out by preparing bar-shaped samples of recycled polypropylene, recycled polystyrene, general purpose polystyrene 1540, and high impact polystyrene 7240 by compression molding using a hot press and thermally characterizing them to determine glass transition temperature and melting temperature using differential scanning calorimetry. The changes in Young’s modulus, tensile strength, hardness, and toughness due to recycling activities were determined at room temperature (24 °C), 40 °C, 60 °C, and 80 °C. The thermo-mechanical properties of recycled polystyrene (PS) were found to be comparable to those of high impact polystyrene (HIPS) 7240. The study revealed that the hardness and toughness for the recycled polymers were higher than those of corresponding virgin polymers. On the other hand, tensile strength and Young’s modulus for the recycled polymers were lower than those of the virgin polymers. Understanding the thermo-mechanical properties of the recycled polymers will contribute to more industrial applications hence increase the rate of recycling, resulting in a reduction in environmental pollution.
Performance Evaluation of a Sensor Concept for Solving the Direct Kinematics Problem of General Planar 3-RPR Parallel Mechanisms by Using Solely the Linear Actuators’ Orientations
Authors: Schulz Stefan
Published: August 2019

In this paper, we experimentally evaluate the performance of a sensor concept for solving the direct kinematics problem of a general planar 3-RPR parallel mechanism by using solely the linear actuators’ orientations. At first, we review classical methods for solving the direct kinematics problem of parallel mechanisms and discuss their disadvantages on the example of the general planar 3-RPR parallel mechanism, a planar parallel robot with two translational and one rotational degrees of freedom, where P denotes active prismatic joints and R denotes passive revolute joints. In order to avoid these disadvantages, we present a sensor concept together with an analytical formulation for solving the direct kinematics problem of a general planar 3-RPR parallel mechanism where the number of possible assembly modes can be significantly reduced when the linear actuators’ orientations are used instead of their lengths. By measuring the orientations of the linear actuators, provided, for example, by inertial measurement units, only two assembly modes exist. Finally, we investigate the accuracy of our direct kinematics solution under static as well as dynamic conditions by performing experiments on a specially designed prototype. We also investigate the solution formulation’s amplification of measurement noise on the calculated pose and show that the Cramér-Rao lower bound can be used to estimate the lower bound of the expected variances for a specific pose based exclusively on the variances of the linear actuators’ orientations.
An Analysis of Ground-Point Classifiers for Terrestrial LiDAR
Authors: Roberts Kevin , Lindsay John , Berg Aaron
Published: August 2019

Previous literature has compared the performance of existing ground point classification (GPC) techniques on airborne LiDAR (ALS) data (LiDAR—light detection and ranging); however, their performance when applied to terrestrial LiDAR (TLS) data has not yet been addressed. This research tested the classification accuracy of five openly-available GPC algorithms on seven TLS datasets: Zhang et al.’s inverted cloth simulation (CSF), Kraus and Pfeiffer’s hierarchical weighted robust interpolation classifier (HWRI), Axelsson’s progressive TIN densification filter (TIN), Evans and Hudak’s multiscale curvature classification (MCC), and Vosselman’s modified slope-based filter (MSBF). Classification performance was analyzed using the kappa index of agreement (KIA) and rasterized spatial distribution of classification accuracy datasets generated through comparisons with manually classified reference datasets. The results identified a decrease in classification accuracy for the CSF and HWRI classification of low vegetation, for the HWRI and MCC classifications of variably sloped terrain, for the HWRI and TIN classifications of low outlier points, and for the TIN and MSBF classifications of off-terrain (OT) points without any ground points beneath. Additionally, the results show that while no single algorithm was suitable for use on all datasets containing varying terrain characteristics and OT object types, in general, a mathematical-morphology/slope-based method outperformed other methods, reporting a kappa score of 0.902.
Mapping Recent Lava Flows at Mount Etna Using Multispectral Sentinel-2 Images and Machine Learning Techniques
Authors: Corradino Claudia , Ganci Gaetana , Cappello Annalisa , Bilotta Giuseppe , Hérault Alexis , Del Negro Ciro
Published: August 2019

Accurate mapping of recent lava flows can provide significant insight into the development of flow fields that may aid in predicting future flow behavior. The task is challenging, due to both intrinsic properties of the phenomenon (e.g., lava flow resurfacing processes) and technical issues (e.g., the difficulty to survey a spatially extended lava flow with either aerial or ground instruments while avoiding hazardous locations). The huge amount of moderate to high resolution multispectral satellite data currently provides new opportunities for monitoring of extreme thermal events, such as eruptive phenomena. While retrieving boundaries of an active lava flow is relatively straightforward, problems arise when discriminating a recently cooled lava flow from older lava flow fields. Here, we present a new supervised classifier based on machine learning techniques to discriminate recent lava imaged in the MultiSpectral Imager (MSI) onboard Sentinel-2 satellite. Automated classification evaluates each pixel in a scene and then groups the pixels with similar values (e.g., digital number, reflectance, radiance) into a specified number of classes. Bands at the spatial resolution of 10 m (bands 2, 3, 4, 8) are used as input to the classifier. The training phase is performed on a small number of pixels manually labeled as covered by fresh lava, while the testing characterizes the entire lava flow field. Compared with ground-based measurements and actual lava flows of Mount Etna emplaced in 2017 and 2018, our automatic procedure provides excellent results in terms of accuracy, precision, and sensitivity.
Combining ASNARO-2 XSAR HH and Sentinel-1 C-SAR VH/VV Polarization Data for Improved Crop Mapping
Authors: Sonobe Rei
Published: August 2019

The Advanced Satellite with New system ARchitecture for Observation-2 (ASNARO-2), which carries the X-band Synthetic Aperture Radar (XSAR), was launched on 17 January 2018 and is expected to be used to supplement data provided by larger satellites. Land cover classification is one of the most common applications of remote sensing, and the results provide a reliable resource for agricultural field management and estimating potential harvests. This paper describes the results of the first experiments in which ASNARO-2 XSAR data were applied for agricultural crop classification. In previous studies, Sentinel-1 C-SAR data have been widely utilized to identify crop types. Comparisons between ASNARO-2 XSAR and Sentinel-1 C-SAR using data obtained in June and August 2018 were conducted to identify five crop types (beans, beetroot, maize, potato, and winter wheat), and the combination of these data was also tested. To assess the potential for accurate crop classification, some radar vegetation indices were calculated from the backscattering coefficients for two dates. In addition, the potential of each type of SAR data was evaluated using four popular supervised learning models: Support vector machine (SVM), random forest (RF), multilayer feedforward neural network (FNN), and kernel-based extreme learning machine (KELM). The combination of ASNARO-2 XSAR and Sentinel-1 C-SAR data was effective, and overall classification accuracies of 85.4 ± 1.8% were achieved using SVM.
Oceanic Mesoscale Eddy Detection Method Based on Deep Learning
Authors: Duo Zijun , Wang Wenke , Wang Huizan
Published: August 2019

Oceanic mesoscale eddies greatly influence energy and matter transport and acoustic propagation. However, the traditional detection method for oceanic mesoscale eddies relies too much on the threshold value and has significant subjectivity. The existing machine learning methods are not mature or purposeful enough, as their train set lacks authority. In view of the above problems, this paper constructs a mesoscale eddy automatic identification and positioning network—OEDNet—based on an object detection network. Firstly, 2D image processing technology is used to enhance the data of a small number of accurate eddy samples annotated by marine experts to generate the train set. Then, the object detection model with a deep residual network, and a feature pyramid network as the main structure, is designed and optimized for small samples and complex regions in the mesoscale eddies of the ocean. Experimental results show that the model achieves better recognition compared to the traditional detection method and exhibits a good generalization ability in different sea areas.
Global Sensitivity Analysis of Leaf-Canopy-Atmosphere RTMs: Implications for Biophysical Variables Retrieval from Top-of-Atmosphere Radiance Data
Authors: Verrelst Jochem , Vicent Jorge , Rivera-Caicedo Juan Pablo , Lumbierres Maria , Morcillo-Pallarés Pablo , Moreno José
Published: August 2019

Knowledge of key variables driving the top of the atmosphere (TOA) radiance over a vegetated surface is an important step to derive biophysical variables from TOA radiance data, e.g., as observed by an optical satellite. Coupled leaf-canopy-atmosphere Radiative Transfer Models (RTMs) allow linking vegetation variables directly to the at-sensor TOA radiance measured. Global Sensitivity Analysis (GSA) of RTMs enables the computation of the total contribution of each input variable to the output variance. We determined the impacts of the leaf-canopy-atmosphere variables into TOA radiance using the GSA to gain insights into retrievable variables. The leaf and canopy RTM PROSAIL was coupled with the atmospheric RTM MODTRAN5. Because of MODTRAN’s computational burden and GSA’s demand for many simulations, we first developed a surrogate statistical learning model, i.e., an emulator, that allows approximating RTM outputs through a machine learning algorithm with low computation time. A Gaussian process regression (GPR) emulator was used to reproduce lookup tables of TOA radiance as a function of 12 input variables with relative errors of 2.4%. GSA total sensitivity results quantified the driving variables of emulated TOA radiance along the 400–2500 nm spectral range at 15 cm − 1 (between 0.3–9 nm); overall, the vegetation variables play a more dominant role than atmospheric variables. This suggests the possibility to retrieve biophysical variables directly from at-sensor TOA radiance data. Particularly promising are leaf chlorophyll content, leaf water thickness and leaf area index, as these variables are the most important drivers in governing TOA radiance outside the water absorption regions. A software framework was developed to facilitate the development of retrieval models from at-sensor TOA radiance data. As a proof of concept, maps of these biophysical variables have been generated for both TOA (L1C) and bottom-of-atmosphere (L2A) Sentinel-2 data by means of a hybrid retrieval scheme, i.e., training GPR retrieval algorithms using the RTM simulations. Obtained maps from L1C vs L2A data are consistent, suggesting that vegetation properties can be directly retrieved from TOA radiance data given a cloud-free sky, thus without the need of an atmospheric correction.
Evaluation of the Uncertainty in Satellite-Based Crop State Variable Retrievals Due to Site and Growth Stage Specific Factors and Their Potential in Coupling with Crop Growth Models
Authors: Levitan Nathaniel , Kang Yanghui , Özdoğan Mutlu , Magliulo Vincenzo , Castillo Paulo , Moshary Fred , Gross Barry
Published: August 2019

Coupling crop growth models and remote sensing provides the potential to improve our understanding of the genotype x environment x management (G × E × M) variability of crop growth on a global scale. Unfortunately, the uncertainty in the relationship between the satellite measurements and the crop state variables across different sites and growth stages makes it difficult to perform the coupling. In this study, we evaluate the effects of this uncertainty with MODIS data at the Mead, Nebraska Ameriflux sites (US-Ne1, US-Ne2, and US-Ne3) and accurate, collocated Hybrid-Maize (HM) simulations of leaf area index (LAI) and canopy light use efficiency (LUECanopy). The simulations are used to both explore the sensitivity of the satellite-estimated genotype × management (G × M) parameters to the satellite retrieval regression coefficients and to quantify the amount of uncertainty attributable to site and growth stage specific factors. Additional ground-truth datasets of LAI and LUECanopy are used to validate the analysis. The results show that uncertainty in the LAI/satellite measurement regression coefficients lead to large uncertainty in the G × M parameters retrievable from satellites. In addition to traditional leave-one-site-out regression analysis, the regression coefficient uncertainty is assessed by evaluating the retrieval performance of the temporal change in LAI and LUECanopy. The weekly change in LAI is shown to be retrievable with a correlation coefficient absolute value (|r|) of 0.70 and root-mean square error (RMSE) value of 0.4, which is significantly better than the performance expected if the uncertainty was caused by random error rather than secondary effects caused by site and growth stage specific factors (an expected |r| value of 0.36 and RMSE value of 1.46 assuming random error). As a result, this study highlights the importance of accounting for site and growth stage specific factors in remote sensing retrievals for future work developing methods coupling remote sensing with crop growth models.
Influence of Soil Background on Spectral Reflectance of Winter Wheat Crop Canopy
Authors: Prudnikova Elena , Savin Igor , Vindeker Gretelerika , Grubina Praskovia , Shishkonakova Ekaterina , Sharychev David
Published: August 2019

The spectral reflectance of crop canopy is a spectral mixture, which includes soil background as one of the components. However, as soil is characterized by substantial spatial variability and temporal dynamics, its contribution to the spectral reflectance of crops will also vary. The aim of the research was to determine the impact of soil background on spectral reflectance of crop canopy in visible and near-infrared parts of the spectrum at different stages of crop development and how the soil type factor and the dynamics of soil surface affect vegetation indices calculated for crop assessment. The study was conducted on three test plots with winter wheat located in the Tula region of Russia and occupied by three contrasting types of soil. During field trips, information was collected on the spectral reflectance of winter wheat crop canopy, winter wheat leaves, weeds and open soil surface for three phenological phases (tillering, shooting stage, milky ripeness). The assessment of the soil contribution to the spectral reflectance of winter wheat crop canopy was based on a linear spectral mixture model constructed from field data. This showed that the soil background effect is most pronounced in the regions of 350–500 nm and 620–690 nm. In the shooting stage, the contribution of the soil prevails in the 620–690 nm range of the spectrum and the phase of milky ripeness in the region of 350–500 nm. The minimum contribution at all stages of winter wheat development was observed at wavelengths longer than 750 nm. The degree of soil influence varies with soil type. Analysis of variance showed that normalized difference vegetation index (NDVI) was least affected by soil type factor, the influence of which was about 30%–50%, depending on the stage of winter wheat development. The influence of soil type on soil-adjusted vegetation index (SAVI) and enhanced vegetation index (EVI2) was approximately equal and varied from 60% (shooting phase) to 80% (tillering phase). According to the discriminant analysis, the ability of vegetation indices calculated for winter wheat crop canopy to distinguish between winter wheat crops growing on different soil types changed from the classification accuracy of 94.1% (EVI2) in the tillering stage to 75% (EVI2 and SAVI) in the shooting stage to 82.6% in the milky ripeness stage (EVI2, SAVI, NDVI). The range of the sensitivity of the vegetation indices to the soil background depended on soil type. The indices showed the greatest sensitivity on gray forest soil when the wheat was in the phase of milky ripeness, and on leached chernozem when the wheat was in the tillering phase. The observed patterns can be used to develop vegetation indices, invariant to second-type soil variations caused by soil type factor, which can be applied for the remote assessment of the state of winter wheat crops.
Monitoring Tropical Forest Structure Using SAR Tomography at L- and P-Band
Authors: El Moussawi Ibrahim , Ho Tong Minh Dinh , Baghdadi Nicolas , Abdallah Chadi , Jomaah Jalal , Strauss Olivier , Lavalle Marco , Ngo Yen-Nhi
Published: August 2019

Our study aims to provide a comparison of the P- and L-band TomoSAR profiles, Land Vegetation and Ice Sensor (LVIS), and discrete return LiDAR to assess the ability for TomoSAR to monitor and estimate the tropical forest structure parameters for enhanced forest management and to support biomass missions. The comparison relies on the unique UAVSAR Jet propulsion Laboratory (JPL)/NASA L-band data, P-band data acquired by ONERA airborne system (SETHI), Small Footprint LiDAR (SFL), and NASA Land, Vegetation and Ice Sensor (LVIS) LiDAR datasets acquired in 2015 and 2016 in the frame of the AfriSAR campaign. Prior to multi-baseline data processing, a phase residual correction methodology based on phase calibration via phase center double localization has been implemented to improve the phase measurements and compensate for the phase perturbations, and disturbances originated from uncertainties in allocating flight trajectories. First, the vertical structure was estimated from L- and P-band corrected Tomography SAR data measurements, then compared with the canopy height model from SFL data. After that, the SAR and LiDAR three-dimensional (3D) datasets are compared and discussed at a qualitative basis at the region of interest. The L- and P-band’s performance for canopy penetration was assessed to determine the underlying ground locations. Additionally, the 3D records for each configuration were compared with their ability to derive forest vertical structure. Finally, the vertical structure extracted from the 3D radar reflectivity from L- and P-band are compared with SFL data, resulting in a root mean square error of 3.02 m and 3.68 m, where the coefficient of determination shows a value of 0.95 and 0.93 for P- and L-band, respectively. The results demonstrate that TomoSAR holds promise for a scientific basis in forest management activities.
Spatio–Temporal Analysis of Deformation at San Emidio Geothermal Field, Nevada, USA Between 1992 and 2010
Authors: Reinisch Elena C. , Cardiff Michael , Akerley John , Warren Ian , Feigl Kurt L.
Published: August 2019

Although subsidence has been observed at the San Emidio geothermal field in Nevada using interferometric synthetic aperture radar since the early 1990s, the spatial extent and temporal evolution of the subsidence have not heretofore been quantified. Furthermore, the weather conditions and geographic location of San Emidio negatively affect interferometric image quality, causing low correlation amongst pairs. To address this, we introduce a new method for selecting pairs in areas of low correlation and small deformation signal using a minimum spanning tree method with a measure of image quality as the weighting criterion. We validate our pair selection approach by comparing our data products to SqueeSAR TM data products from a previous study at San Emidio. We also develop a deformation model which characterizes the spatial extent of subsidence at San Emidio in terms of volume change of the reservoir. After applying this deformation model to our data set of interferometric pairs, we examine the temporal relationship of the observed deformation with production and injection operations associated with geothermal power production.
An Efficient Three-Dimensional Convolutional Neural Network for Inferring Physical Interaction Force from Video
Authors: Kim Dongyi , Cho Hyeon , Shin Hochul , Lim Soo-Chul , Hwang Wonjun
Published: August 2019

Interaction forces are traditionally predicted by a contact type haptic sensor. In this paper, we propose a novel and practical method for inferring the interaction forces between two objects based only on video data—one of the non-contact type camera sensors—without the use of common haptic sensors. In detail, we could predict the interaction force by observing the texture changes of the target object by an external force. For this purpose, our hypothesis is that a three-dimensional (3D) convolutional neural network (CNN) can be made to predict the physical interaction forces from video images. In this paper, we proposed a bottleneck-based 3D depthwise separable CNN architecture where the video is disentangled into spatial and temporal information. By applying the basic depthwise convolution concept to each video frame, spatial information can be efficiently learned; for temporal information, the 3D pointwise convolution can be used to learn the linear combination among sequential frames. To validate and train the proposed model, we collected large quantities of datasets, which are video clips of the physical interactions between two objects under different conditions (illumination and angle variations) and the corresponding interaction forces measured by the haptic sensor (as the ground truth). Our experimental results confirmed our hypothesis; when compared with previous models, the proposed model was more accurate and efficient, and although its model size was 10 times smaller, the 3D convolutional neural network architecture exhibited better accuracy. The experiments demonstrate that the proposed model remains robust under different conditions and can successfully estimate the interaction force between objects.
Medical Robotics in Bone Fracture Reduction Surgery: A Review
Authors: Bai Long , Yang Jianxing , Chen Xiaohong , Sun Yuanxi , Li Xingyu
Published: August 2019

Since the advantages of precise operation and effective reduction of radiation, robots have become one of the best choices for solving the defects of traditional fracture reduction surgery. This paper focuses on the application of robots in fracture reduction surgery, design of the mechanism, navigation technology, robotic control, interaction technology, and the bone–robot connection technology. Through literature review, the problems in current fracture reduction robot and its future development are discussed.
Trimming of Imperfect Cylindrical Fused Silica Resonators by Chemical Etching
Authors: Tao Yunfeng , Pan Yao , Jin Shilong , Jia Yonglei , Yang Kaiyong , Luo Hui
Published: August 2019

The cylindrical resonator gyroscope (CRG) is a kind of solid-state gyroscope with a wide application market. The cylindrical resonator is the key component of CRG, whose quality factor and symmetry will directly affect the performance of the gyroscope. Due to the material properties and fabrication limitations, the actual resonator always has some defects. Therefore, frequency trimming, i.e., altering the local mass or stiffness distribution by certain methods, is needed to improve the overall symmetry of the resonator. In this paper, we made further derivation based on the chemical trimming theory proposed by Basarab et al. We built up the relation between the frequency split and the balanced mass to determine the mass to be removed. Chemical trimming experiments were conducted on three cylindrical fused silica resonators. The frequency splits of the three resonators were around 0.05 Hz after chemical trimming. The relation between frequency split and balanced mass established from experimental data was consistent with the theoretical calculation. Therefore, frequency split can be reduced to lower than 0.05 Hz under rigorous theoretical calculation and optimized chemical trimming parameters.
Novel S-Bend Resonator Based on a Multi-Mode Waveguide with Mode Discrimination for a Refractive Index Sensor
Authors: Kim Do-Hyun , Jeon Su-Jin , Lee Jae-Sang , Hong Seok-Ho , Choi Young-Wan
Published: August 2019

In this paper, a multi-mode waveguide-based optical resonator is proposed for an integrated optical refractive index sensor. Conventional optical resonators have been studied for single-mode waveguide-based resonators to enhance the performance, but mass production is limited owing to the high fabrication costs of nano-scale structures. To overcome this problem, we designed an S-bend resonator based on a micro-scale multi-mode waveguide. In general, multi-mode waveguides cannot be utilized as optical resonators, because of a performance degradation resulting from modal dispersion and an output transmission with multi-peaks. Therefore, we exploited the mode discrimination phenomenon using the bending loss, and the resulting S-bend resonator yielded an output transmission without multi-peaks. This phenomenon is utilized to remove higher-order modes efficiently using the difference in the effective refractive index between the higher-order and fundamental modes. As a result, the resonator achieved a Q-factor and sensitivity of 2.3 × 103 and 52 nm/RIU, respectively, using the variational finite-difference time-domain method. These results show that the multi-mode waveguide-based S-bend resonator with a wide line width can be utilized as a refractive index sensor.
Active Learning on Dynamic Clustering for Drift Compensation in an Electronic Nose System
Authors: Liu Tao , Li Dongqi , Chen Jianjun , Chen Yanbing , Yang Tao , Cao Jianhua
Published: August 2019

Drift correction is an important concern in Electronic noses (E-nose) for maintaining stable performance during continuous work. A large number of reports have been presented for dealing with E-nose drift through machine-learning approaches in the laboratory. In this study, we aim to counter the drift effect in more challenging situations in which the category information (labels) of the drifted samples is difficult or expensive to obtain. Thus, only a few of the drifted samples can be used for label querying. To solve this problem, we propose an innovative methodology based on Active Learning (AL) that selectively provides sample labels for drift correction. Moreover, we utilize a dynamic clustering process to balance the sample category for label querying. In the experimental section, we set up two E-nose drift scenarios—a long-term and a short-term scenario—to evaluate the performance of the proposed methodology. The results indicate that the proposed methodology is superior to the other state-of-art methods presented. Furthermore, the increasing tendencies of parameter sensitivity and accuracy are analyzed. In addition, the Label Efficiency Index (LEI) is adopted to measure the efficiency and labelling cost of the AL methods. The LEI values indicate that our proposed methodology exhibited better performance than the other presented AL methods in the online drift correction of E-noses.
Physical and Tactical Demands of the Goalkeeper in Football in Different Small-Sided Games
Authors: Jara Daniel , Ortega Enrique , Gómez-Ruano Miguel-Ángel , Weigelt Matthias , Nikolic Brittany , Sainz de Baranda Pilar
Published: August 2019

Background: Several studies have examined the differences between the different small-sided game (SSG) formats. However, only one study has analysed how the different variables that define SSGs can modify the goalkeeper’s behavior. The aim of the present study was to analyze how the modification of the pitch size in SSGs affects the physical demands of the goalkeepers. Methods: Three professional male football goalkeepers participated in this study. Three different SSG were analysed (62 m × 44 m for a large pitch; 50 m × 35 m for a medium pitch and 32 m × 23 m for a small pitch). Positional data of each goalkeeper was gathered using an 18.18 Hz global positioning system. The data gathered was used to compute players’ spatial exploration index, standard ellipse area, prediction ellipse area The distance covered, distance covered in different intensities and accelerations/decelerations were used to assess the players’ physical performance. Results and Conclusions: There were differences between small and large SSGs in relation to the distances covered at different intensities and pitch exploration. Intensities were lower when the pitch size was larger. Besides that, the pitch exploration variables increased along with the increment of the pitch size.
Seasonal Time Series Forecasting by F1-Fuzzy Transform
Authors: Di Martino Ferdinando , Sessa Salvatore
Published: August 2019

We present a new seasonal forecasting method based on F1-transform (fuzzy transform of order 1) applied on weather datasets. The objective of this research is to improve the performances of the fuzzy transform-based prediction method applied to seasonal time series. The time series’ trend is obtained via polynomial fitting: then, the dataset is partitioned in S seasonal subsets and the direct F1-transform components for each seasonal subset are calculated as well. The inverse F1-transforms are used to predict the value of the weather parameter in the future. We test our method on heat index datasets obtained from daily weather data measured from weather stations of the Campania Region (Italy) during the months of July and August from 2003 to 2017. We compare the results obtained with the statistics Autoregressive Integrated Moving Average (ARIMA), Automatic Design of Artificial Neural Networks (ADANN), and the seasonal F-transform methods, showing that the best results are just given by our approach.
A Turning Point as an Opportunity to (Re)Think and Give a Voice to One’s Own Body
Authors: González-Calvo Gustavo , Varea Valeria
Published: August 2019

This article explores the intersectionalities of masculinity, fatherhood, and physical activity in relation to a Physical Education teacher who has been diagnosed with an illness. In so doing, we draw on autobiographical narratives to delve into how embodied subjectivities are constructed to advance knowledge on a new embodied way of being a man and a PE teacher that can be accepted and embraced. The results are organised into three main themes: (1) narratives of continuation: the “before” of chronic illness; (2) narratives of disruption: back pain and temporary physical disability; and (3) restitution narratives: damn it, now that I am a father. The results suggest that narratives such as those presented in this article contribute to the continuously changing process of life projects and that illness can assist in redefining and reconstituting the persona of a PE teacher.
Conservation Payments and Technical Efficiency of farm Households Participating in the Grain for Green Program on the Loess Plateau of China
Authors: Li Li , Tsunekawa Atsushi , Zuo Yangshangyu , Koike Atsushi
Published: August 2019

This study provides an empirical analysis of household technical efficiency and its determinant factors (especially conservation payments) in the context of the Grain for Green program. On the basis of a sample of 225 farm households on the Loess Plateau in 2007, we estimate household technical efficiency using the data envelopment analysis method. In addition to a traditional ordinary least square (OLS) analysis, quantile regression (QR) analysis is also deployed to explore the possible heterogeneous effects of conservation payments and other variables on the technical efficiency across the quantiles. The results suggest that when off-farm activities are taken into account, households have considerable potential for improving their technical efficiency; OLS analysis shows that conservation payments decrease household efficiency, and the QR analysis suggests that the negative impact is significant only for higher performance households; The presence of children, access of households to leased land markets, credit markets, and extension services all show heterogeneous impacts on household efficiency. On the basis of the findings of the study, policies suggestions to improve the program’s effectiveness are provided.
Study of the School–Residence Spatial Relationship and the Characteristics of Travel-to-School Distance in Shenyang
Authors: Mei Dawei , Xiu Chunliang , Feng Xinghua , Wei Ye
Published: August 2019

The school–residence spatial relationship is a key factor in understanding urban spatial structure and travel-to-school behavior of students. Analyzing the change law and the spatial characteristics of travel-to-school distance can provide a basis for improved accessibility of urban educational facilities and enable enrolment of students from the neighborhood. Based on one complete month of mobile phone signaling data for May 2018, the changes in student density with the travel-to-school distance was analyzed using MATLAB and Mann–Kendall Trend Test, and the pattern and the spatial structure of travel-to-school were explored. The results revealed that: (1) With increase in travel-to-school distance, the student density showed a decrease in truncated power law distribution, and it is concentrated within the travel-to-school distance of 5.0 km; (2) According to the sudden change points of the student density growth rate, the threshold distance for travel to kindergartens is 1.30 km, and for primary schools and secondary schools is 1.50 km. The school–residence spatial structure is divided according to the threshold of travel-to-school distance and the scope of attendance; (3) The dominant flow of travel-to-school is generally from urban peripheral and marginal areas to the urban core area, and partly from marginal areas to peripheral areas; (4) The pattern of travel-to-school is polycentric, and the study centers are mainly located in the urban central district north of the Hun River. The urban core area has the strongest attraction of students, while the marginal area has the weakest.
Analysis of Strength and Endurance Values in Schoolchildren Aged 7 to 10 Years in Tolú, Colombia
Authors: Agudelo Velásquez Carlos Alberto , Zagalaz Sánchez María Luisa , Zurita Ortega Félix
Published: August 2019

The objective of this study was to describe the state of strength and endurance in schoolchildren aged 7 to 10 years old from the city of Santiago de Tolú, Colombia, and to relate such values to their weights, heights, and body mass index (BMI) values. This was a descriptive, correlational, cross-sectional research study, whose quantitative statistical analysis was compared with studies conducted in Colombia and other countries. Strength was measured by the summation of the segmental dynamometry of the upper and lower limbs, and endurance was measured with a 5 min continuous run test. This is the first investigation to characterize variables related to physical education and sport in schoolchildren from Tolú. The information collected on the evaluated population may aid in its sustainable human development, since significant differences in height, weight, BMI, strength, and endurance were identified with respect to other national and international populations.