bluuebunny/crossref_metadata_2025 huggingface dataset:
Wheat (Triticum aestivum L.) TaHMW1D Transcript Variants Are Highly Expressed in Response to Heat Stress and in Grains Located in Distal Part of the Spike
Authors: Ko Chan Seop , Kim Jin-Baek , Hong Min Jeong , Seo Yong Weon
Published: April 2021

High-temperature stress during the grain filling stage has a deleterious effect on grain yield and end-use quality. Plants undergo various transcriptional events of protein complexity as defensive responses to various stressors. The “Keumgang” wheat cultivar was subjected to high-temperature stress for 6 and 10 days beginning 9 days after anthesis, then two-dimensional gel electrophoresis (2DE) and peptide analyses were performed. Spots showing decreased contents in stressed plants were shown to have strong similarities with a high-molecular glutenin gene, TraesCS1D02G317301 (TaHMW1D). QRT-PCR results confirmed that TaHMW1D was expressed in its full form and in the form of four different transcript variants. These events always occurred between repetitive regions at specific deletion sites (5′-CAA (Glutamine) GG/TG (Glycine) or (Valine)-3′, 5′-GGG (Glycine) CAA (Glutamine) -3′) in an exonic region. Heat stress led to a significant increase in the expression of the transcript variants. This was most evident in the distal parts of the spike. Considering the importance of high-molecular weight glutenin subunits of seed storage proteins, stressed plants might choose shorter polypeptides while retaining glutenin function, thus maintaining the expression of glutenin motifs and conserved sites.
Anti-Neuroinflammatory Effects and Mechanism of Action of Fructus ligustri lucidi Extract in BV2 Microglia
Authors: Kim Yeon Ju , Park Sung Yun , Koh Young Jun , Lee Ju-Hee
Published: April 2021

For centuries, Fructus ligustri lucidi (FLL; the fruit of Ligustrum lucidum Aiton or Ligustrum japonicum Thunb.) has been commonly used in traditional Chinese medicine for treating hepatitis and aging-related symptoms and in traditional Korean medicine to detoxify kidneys and the liver. Pharmacological research has shown FLL has antioxidant, anti-inflammatory, anticancer, anti-osteoporosis, and hepatoprotective activities. This study was undertaken to investigate the effects of FLL extract (FLLE) on neuroinflammation. After setting a non-toxic concentration using MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-tetrazolium bromide] assay data, we investigated the effects of FLLE using Western blotting, cell migration, enzyme-linked immunosorbent assay, a nitric oxide (NO) assay, and immunofluorescence staining in lipopolysaccharide (LPS)-stimulated murine BV2 microglial cells. FLLE was non-toxic to BV2 cells up to a concentration of 500 μg/mL and concentration-dependently inhibited the production of NO and prostaglandin E2 and the protein levels of inducible nitric oxide synthase and cyclooxygenase-2 under LPS-induced inflammatory conditions. It also inhibited the secretion of the inflammatory cytokines tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6). Furthermore, FLLE pretreatment attenuated LPS-induced increases of CD68 (a marker of microglia activation) and suppressed the activation of mitogen-activated protein kinases (MAPKs) and nuclear factor-kappa B (NF-κB) signaling pathways in LPS-stimulated BV2 cells, and significantly increased heme oxygenase (HO)-1 levels. FLLE also reduced the LPS-induced increase in the migratory ability of BV2 cells and the phosphorylation of vascular endothelial growth factor receptor 1. Collectively, FLLE effectively inhibited inflammatory response by suppressing the MAPK and NF-κB signaling pathways and inducing HO-1 in LPS-stimulated BV2 microglial cells. Our findings provide a scientific basis for further study of FLL as a candidate for preventing or alleviating neuroinflammation.
Preparation of Long Sisal Fiber-Reinforced Polylactic Acid Biocomposites with Highly Improved Mechanical Performance
Authors: Liang Zhifang , Wu Hongwu , Liu Ruipu , Wu Caiquan
Published: April 2021

Green biodegradable plastics have come into focus as an alternative to restricted plastic products. In this paper, continuous long sisal fiber (SF)/polylactic acid (PLA) premixes were prepared by an extrusion-rolling blending process, and then unidirectional continuous long sisal fiber-reinforced PLA composites (LSFCs) were prepared by compression molding to explore the effect of long fiber on the mechanical properties of sisal fiber-reinforced composites. As a comparison, random short sisal fiber-reinforced PLA composites (SSFCs) were prepared by open milling and molding. The experimental results show that continuous long sisal fiber/PLA premixes could be successfully obtained from this pre-blending process. It was found that the presence of long sisal fibers could greatly improve the tensile strength of LSFC material along the fiber extension direction and slightly increase its tensile elongation. Continuous long fibers in LSFCs could greatly participate in supporting the load applied to the composite material. However, when comparing the mechanical properties of the two composite materials, the poor compatibility between the fiber and the matrix made fiber’s reinforcement effect not well reflected in SSFCs. Similarly, the flexural performance and impact performance of LSFCs had been improved considerably versus SSFCs.
A Design for Additive Manufacturing Strategy for Dimensional and Geometrical Quality Improvement of PolyJet-Manufactured Glossy Cylindrical Features
Authors: Beltrán Natalia , Álvarez Braulio J. , Blanco David , Peña Fernando , Fernández Pedro
Published: April 2021

The dimensional and geometrical quality of additively manufactured parts must be increased to match industrial requirements before they can be incorporated to mass production. Such an objective has a great relevance in the case of features of linear size that are affected by dimensional or geometrical tolerances. This work proposes a design for additive manufacturing strategy that uses the re-parameterization of part design to minimize shape deviations from cylindrical geometries. An analysis of shape deviations in the frequency domain is used to define a re-parameterization strategy, imposing a bi-univocal correspondence between verification parameters and design parameters. Then, the significance of variations in the process and design factors upon part quality is analyzed using design of experiments to determine the appropriate extension for modelling form deviation. Finally, local deviations are mapped for design parameters, and a new part design including local compensations is obtained. This strategy has been evaluated upon glossy surfaces manufactured in a Vero™ material by polymer jetting. The results of the proposed example showed a relevant improvement in dimensional quality, as well as a reduction of geometrical deviations, outperforming the results obtained with a conventional scaling compensation.
Fiber Formation and Structural Development of HBA/HNA Thermotropic Liquid Crystalline Polymer in High-Speed Melt Spinning
Authors: Song Bo Seok , Lee Jun Young , Jang Sun Hwa , Hahm Wan-Gyu
Published: April 2021

High-speed melt spinning of thermotropic liquid crystalline polymer (TLCP) resin composed of 4-hydroxybenzoic acid (HBA) and 2-hydroxy-6-napthoic acid (HNA) monomers in a molar ratio of 73/27 was conducted to investigate the characteristic structure development of the fibers under industrial spinning conditions, and the obtained as-spun TLCP fibers were analyzed in detail. The tensile strength and modulus of the fibers increased with shear rate in nozzle hole, draft in spin-line and spinning temperature and exhibited the high values of approximately 1.1 and 63 GPa, respectively, comparable to those of industrial as-spun TLCP fibers, at a shear rate of 70,000 s−1 and a draft of 25. X-ray diffraction demonstrated that the mechanical properties of the fibers increased with the crystalline orientation factor (fc) and the fractions of highly oriented crystalline and non-crystalline anisotropic phases. The results of structure analysis indicated that a characteristic skin-core structure developed at high drafts (i.e., spinning velocity) and low spinning temperatures, which contributed to weakening the mechanical properties of the TLCP fibers. It is supposed that this heterogeneous structure in the cross-section of the fibers was induced by differences in the cooling rates of the skin and core of the fiber in the spin-line.
Electrodeposited Copolymers Based on 9,9′-(5-Bromo-1,3-phenylene)biscarbazole and Dithiophene Derivatives for High-Performance Electrochromic Devices
Authors: Kuo Chung-Wen , Chang Jui-Cheng , Chang Jeng-Kuei , Huang Sheng-Wei , Lee Pei-Ying , Wu Tzi-Yi
Published: April 2021

A 1,3-bis(carbazol-9-yl)benzene derivative (BPBC) was synthesized and its related homopolymer (PBPBC) and copolymers (P(BPBC-co-BT), P(BPBC-co-CDT), and P(BPBC-co-CDTK)) were prepared using electrochemical polymerization. Investigations of polymeric spectra showed that PBPBC film was grey, iron-grey, yellowish-grey, and greyish-green from the neutral to the oxidized state. P(BPBC-co-BT), P(BPBC-co-CDT), and P(BPBC-co-CDTK) films showed multicolor transitions from the reduced to the oxidized state. The transmittance change (ΔT) of PBPBC, P(BPBC-co-BT), P(BPBC-co-CDT), and P(BPBC-co-CDTK) films were 29.6% at 1040 nm, 44.4% at 1030 nm, 22.3% at 1050 nm, and 41.4% at 1070 nm. The coloration efficiency (η) of PBPBC and P(BPBC-co-CDTK) films were evaluated to be 140.3 cm2 C−1 at 1040 nm and 283.7 cm2 C−1 at 1070 nm, respectively. A P(BPBC-co-BT)/PEDOT electrochromic device (ECD) showed a large ΔT (36.2% at 625 nm) and a fast response time (less than 0.5 s), whereas a P(BPBC-co-CDTK)/PEDOT ECD revealed a large η (534.4 cm2 C–1 at 610 nm) and sufficient optical circuit memory.
Best Practice for De-Vulcanization of Waste Passenger Car Tire Rubber Granulate Using 2-2′-dibenzamidodiphenyldisulfide as De-Vulcanization Agent in a Twin-Screw Extruder
Authors: van Hoek Hans , Noordermeer Jacques , Heideman Geert , Blume Anke , Dierkes Wilma
Published: April 2021

De-vulcanization of rubber has been shown to be a viable process to reuse this valuable material. The purpose of the de-vulcanization is to release the crosslinked nature of the highly elastic tire rubber granulate. For present day passenger car tires containing the synthetic rubbers Styrene-Butadiene Rubber (SBR) and Butadiene Rubber (BR) and a high amount of silica as reinforcing filler, producing high quality devulcanizate is a major challenge. In previous research a thermo-chemical mechanical approach was developed, using a twin-screw extruder and diphenyldisulfide (DPDS) as de-vulcanization agent.The screw configuration was designed for low shear in order to protect the polymers from chain scission, or uncontrolled spontaneuous recombination which is the largest problem involved in de-vulcanization of passenger car tire rubber. Because of disadvantages of DPDS for commercial use, 2-2′-dibenzamidodiphenyldisulfide (DBD) was used in the present study. Due to its high melting point of 140 °C the twin-screw extruder process needed to be redesigned. Subsequent milling of the devulcanizate at 60 °C with a narrow gap-width between the mill rolls greatly improved the quality of the devulcanizate in terms of coherence and tensile properties after renewed vulcanization. As the composition of passenger car tire granulate is very complex, the usefulness of the Horikx-Verbruggen analysis as optimization parameter for the de-vulcanization process was limited. Instead, stress-strain properties of re-vulcanized de-vulcanizates were used. The capacity of the twin-screw extruder was limited by the required residence time, implying a low screw speed. A best tensile strength of 8 MPa at a strain at break of 160% of the unblended renewed vulcanizate was found under optimal conditions.
Experiment and Simulation Research on the Fatigue Wear of Aircraft Tire Tread Rubber
Authors: Wu Jian , Chen Long , Chen Da , Wang Youshan , Su Benlong , Cui Zhibo
Published: April 2021

The road surface and the tread pattern structures directly affect the wear performance of aircraft tire, especially for lateral sliding conditions. In this paper, wear tests of tread block with different draft angles and root radiuses, different interfaces, and different slip angles were carried out, and combined with the simulation, the effects of tread groove structure and slip angle on the wear mechanism were analyzed. Results indicated that the influences of draft angle were greater than the root radius; the wear geometry of the tread block decreased when the draft angle increased in the range of 0° to 15°, but for the root radius, the wear geometry of each sample was similar to a strip shape. A considerable material loss occurred at the front edge when the slip angle increased, and the slip angle was larger in the range of 0° to 45°. Combined with the simulation and wear test, fatigue wear and abrasive wear of the slide surface are dominant factors when considering the effects of tread groove structure and slip angle, and both front edges of the tread blocks roll up repeatedly; the coefficient decreases with the increase in load when the cement concrete pavement interface is dry, but for a wet interface, the coefficient decreases softly.
Numerical Analysis of the Spontaneous Combustion Accidents of Oil Storage Tanks Containing Sulfur
Authors: Li Zijun , Cai Rongzi , Xu Yu
Published: April 2021

In order to study various influencing factors of spontaneous combustion accidents of sulfur-containing oil storage tanks, this paper constructed a two-dimensional model of the storage tank wall by COMSOL Multiphysics software. The proposed model takes temperature change trend as an observation index to explore the heat transfer process of the tank wall. By fitting the function curve of heat release with oxidation reaction temperature of sulfur corrosion products and comparing with constant heat sources, it is found that heat source intensity will affect the temperature growth trend of tank spontaneous combustion. In addition, the air convection heat transfer coefficient represents the interference degree of external environment to the spontaneous combustion heating process, and the wall heating rate decreases with the increase of air convection heat transfer coefficient. The different heat release rates in varying oxidation stages will lead to distinct temperature growth trends. The larger the air convection heat transfer coefficient, the greater the temperature difference between the inner and outer walls of the tank, which is not conducive to the detection of the abnormal temperature of the heat source. The difference of thermal insulation and thermal conductivity of tank materials also affects the wall heat transfer, so the material properties should be considered comprehensively in actual production. The research results can provide a research basis and a theoretical basis for monitoring, prevention, and control of spontaneous combustion of sour oil storage tanks.
High Throughput Expression Screening of Arabinofuranosyltransferases from Mycobacteria
Authors: Rodrigues José , Almeida Vanessa T. , Rosário Ana L. , Tan Yong Zi , Kloss Brian , Mancia Filippo , Archer Margarida
Published: April 2021

Studies on membrane proteins can help to develop new drug targets and treatments for a variety of diseases. However, membrane proteins continue to be among the most challenging targets in structural biology. This uphill endeavor can be even harder for membrane proteins from Mycobacterium species, which are notoriously difficult to express in heterologous systems. Arabinofuranosyltransferases are involved in mycobacterial cell wall synthesis and thus potential targets for antituberculosis drugs. A set of 96 mycobacterial genes coding for Arabinofuranosyltransferases was selected, of which 17 were successfully expressed in E. coli and purified by metal-affinity chromatography. We herein present an efficient high-throughput strategy to screen in microplates a large number of targets from Mycobacteria and select the best conditions for large-scale protein production to pursue functional and structural studies. This methodology can be applied to other targets, is cost and time effective and can be implemented in common laboratories.
Critical Tectonic Limits for Geothermal Aquifer Use: Case Study from the East Slovakian Basin Rim
Authors: Jacko Stanislav , Farkašovský Roman , Ďuriška Igor , Ščerbáková Barbora , Bátorová Kristína
Published: April 2021

The Pannonian basin is a major geothermal heat system in Central Europe. Its peripheral basin, the East Slovakian basin, is an example of a geothermal structure with a linear, directed heat flow ranging from 90 to 100 mW/m2 from west to east. However, the use of the geothermal source is limited by several critical tectono-geologic factors: (a) Tectonics, and the associated disintegration of the aquifer block by multiple deformations during the pre-Paleogene, mainly Miocene, period. The main discontinuities of NW-SE and N-S direction negatively affect the permeability of the aquifer environment. For utilization, minor NE-SW dilatation open fractures are important, which have been developed by sinistral transtension on N–S faults and accelerated normal movements to the southeast. (b) Hydrogeologically, the geothermal structure is accommodated by three water types, namely, Na-HCO3 with 10.9 g·L−1 mineralization (in the north), the Ca-Mg-HCO3 with 0.5–4.5 g·L−1 mineralization (in the west), and Na-Cl water type containing 26.8–33.4 g·L−1 mineralization (in the southwest). The chemical composition of the water is influenced by the Middle Triassic dolomite aquifer, as well as by infiltration of saline solutions and meteoric waters along with open fractures/faults. (c) Geothermally anomalous heat flow of 123–129 °C with 170 L/s total flow near the Slanské vchy volcanic chain seems to be the perspective for heat production.
Impact of Income on Life Expectancy: A Challenge for the Pension Policy
Authors: Walczak Damian , Wantoch-Rekowski Jacek , Marczak Robert
Published: April 2021

The aim of this paper is to present life expectancy of both genders depending on their income and to determine the impact of a possible regularity on the state pension policy. The study was based on the income of pensioners in Poland (over 5 million people receiving old-age pension). The results obtained made it possible to formulate several important conclusions: the rich live longer; the impact of income on life expectancy is much stronger among men than women; and with age, income has less and less impact on life expectancy. Consequently, in the capital model that is in force in Poland, the state should take this fact into account in its pension policy when calculating the amount of the benefit.
Interpreting Patterns of Concentric Rings within Small Buoyant River Plumes
Authors: Marmorino George , Evans Thomas
Published: April 2021

High-resolution imagery of small buoyant plumes often reveals an extensive pattern of concentric rings spreading outward from near the discharge point. Recent remote sensing studies of plumes from rivers flowing into the Black Sea propose that such rings are internal waves, which form near a river mouth through an abrupt deceleration of the current, or hydraulic jump. The present study, using numerical simulations, presents an alternative viewpoint in which no hydraulic jump occurs and the rings are not internal waves, but derive instead through shear instability. These two differing dynamical views point to a clear need for additional field studies that combine in-water measurements and time-sequential remote sensing imagery.
Sea Ice Thickness Estimation Based on Regression Neural Networks Using L-Band Microwave Radiometry Data from the FSSCat Mission
Authors: Herbert Christoph , Munoz-Martin Joan Francesc , Llaveria David , Pablos Miriam , Camps Adriano
Published: April 2021

Several methods have been developed to provide polar maps of sea ice thickness (SIT) from L-band brightness temperature (TB) and altimetry data. Current process-based inversion methods to yield SIT fail to address the complex surface characteristics because sea ice is subject to strong seasonal dynamics and ice-physical properties are often non-linearly related. Neural networks can be trained to find hidden links among large datasets and often perform better on convoluted problems for which traditional approaches miss out important relationships between the observations. The FSSCat mission launched on 3 September 2020, carries the Flexible Microwave Payload-2 (FMPL-2), which contains the first Reflected Global Navigation Satellite System (GNSS-R) and L-band radiometer on board a CubeSat—designed to provide TB data on global coverage for soil moisture retrieval, and sea ice applications. This work investigates a predictive regression neural network approach with the goal to infer SIT using FMPL-2 TB and ancillary data (sea ice concentration, surface temperature, and sea ice freeboard). Two models—covering thin ice up to 0.6 m and full-range thickness—were separately trained on Arctic data in a two-month period from mid-October to the beginning of December 2020, while using ground truth data derived from the Soil Moisture and Ocean Salinity (SMOS) and Cryosat-2 missions. The thin ice and the full-range models resulted in a mean absolute error of 6.5 cm and 23 cm, respectively. Both of the models allowed for one to produce weekly composites of Arctic maps, and monthly composites of Antarctic SIT were predicted based on the Arctic full-range model. This work presents the first results of the FSSCat mission over the polar regions. It reveals the benefits of neural networks for sea ice retrievals and demonstrates that moderate-cost CubeSat missions can provide valuable data for applications in Earth observation.
Deep Metric Learning with Online Hard Mining for Hyperspectral Classification
Authors: Dong Yanni , Yang Cong , Zhang Yuxiang
Published: April 2021

Recently, deep learning has developed rapidly, while it has also been quite successfully applied in the field of hyperspectral classification. Generally, training the parameters of a deep neural network to the best is the core step of a deep learning-based method, which usually requires a large number of labeled samples. However, in remote sensing analysis tasks, we only have limited labeled data because of the high cost of their collection. Therefore, in this paper, we propose a deep metric learning with online hard mining (DMLOHM) method for hyperspectral classification, which can maximize the inter-class distance and minimize the intra-class distance, utilizing a convolutional neural network (CNN) as an embedded network. First of all, we utilized the triplet network to learn better representations of raw data so that raw data were capable of having their dimensionality reduced. Afterward, an online hard mining method was used to mine the most valuable information from the limited hyperspectral data. To verify the performance of the proposed DMLOHM, we utilized three well-known hyperspectral datasets: Salinas Scene, Pavia University, and HyRANK for verification. Compared with CNN and DMLTN, the experimental results showed that the proposed method improved the classification accuracy from 0.13% to 4.03% with 85 labeled samples per class.
The Road to Operationalization of Effective Tropical Forest Monitoring Systems
Authors: Portillo-Quintero Carlos , Hernández-Stefanoni Jose L. , Reyes-Palomeque Gabriela , Subedi Mukti R.
Published: April 2021

The urgency to preserve tropical forest remnants has encouraged the development of remote sensing tools and techniques to monitor diverse forest attributes for management and conservation. State-of-the-art methodologies for mapping and tracking these attributes usually achieve accuracies greater than 0.8 for forest cover monitoring; r-square values of ~0.5–0.7 for plant diversity, vegetation structure, and plant functional trait mapping, and overall accuracies of ~0.8 for categorical maps of forest attributes. Nonetheless, existing operational tropical forest monitoring systems only track single attributes at national to global scales. For the design and implementation of effective and integrated tropical forest monitoring systems, we recommend the integration of multiple data sources and techniques for monitoring structural, functional, and compositional attributes. We also recommend its decentralized implementation for adjusting methods to local climatic and ecological characteristics and for proper end-user engagement. The operationalization of the system should be based on all open-source computing platforms, leveraging international support in research and development and ensuring direct and constant user engagement. We recommend continuing the efforts to address these multiple challenges for effective monitoring.
LighterGAN: An Illumination Enhancement Method for Urban UAV Imagery
Authors: Wang Junshu , Yang Yue , Chen Yuan , Han Yuxing
Published: April 2021

In unmanned aerial vehicle based urban observation and monitoring, the performance of computer vision algorithms is inevitably limited by the low illumination and light pollution caused degradation, therefore, the application image enhancement is a considerable prerequisite for the performance of subsequent image processing algorithms. Therefore, we proposed a deep learning and generative adversarial network based model for UAV low illumination image enhancement, named LighterGAN. The design of LighterGAN refers to the CycleGAN model with two improvements—attention mechanism and semantic consistency loss—having been proposed to the original structure. Additionally, an unpaired dataset that was captured by urban UAV aerial photography has been used to train this unsupervised learning model. Furthermore, in order to explore the advantages of the improvements, both the performance in the illumination enhancement task and the generalization ability improvement of LighterGAN were proven in the comparative experiments combining subjective and objective evaluations. In the experiments with five cutting edge image enhancement algorithms, in the test set, LighterGAN achieved the best results in both visual perception and PIQE (perception based image quality evaluator, a MATLAB build-in function, the lower the score, the higher the image quality) score of enhanced images, scores were 4.91 and 11.75 respectively, better than EnlightenGAN the state-of-the-art. In the enhancement of low illumination sub-dataset Y (containing 2000 images), LighterGAN also achieved the lowest PIQE score of 12.37, 2.85 points lower than second place. Moreover, compared with the CycleGAN, the improvement of generalization ability was also demonstrated. In the test set generated images, LighterGAN was 6.66 percent higher than CycleGAN in subjective authenticity assessment and 3.84 lower in PIQE score, meanwhile, in the whole dataset generated images, the PIQE score of LighterGAN is 11.67, 4.86 lower than CycleGAN.
High-Resolution Airborne Hyperspectral Imagery for Assessing Yield, Biomass, Grain N Concentration, and N Output in Spring Wheat
Authors: Raya-Sereno María D. , Ortiz-Monasterio J. Ivan , Alonso-Ayuso María , Rodrigues Francelino A. , Rodríguez Arlet A. , González-Perez Lorena , Quemada Miguel
Published: April 2021

Remote sensing allows fast assessment of crop monitoring over large areas; however, questions regarding uncertainty in crop parameter prediction and application to nitrogen (N) fertilization remain open. The objective of this study was to optimize of remote sensing spectral information for its application to grain yield (GY), biomass, grain N concentration (GNC), and N output assessment, and decision making on spring wheat fertilization. Spring wheat (Triticum turgidum L.) field experiments testing two tillage treatments, two irrigation levels and six N treatments were conducted in Northwest Mexico over four consecutive years. Hyperspectral images were acquired through 27 airborne flight campaigns. At harvest, GY, biomass, GNC and N output were determined. Spectral exploratory analysis was used to identify the best wavelength combinations, the most suitable vegetation indices (VIs) and the best growth stages to assess the agronomic variables. The relationship between the spectral information and the agronomic measurements was evaluated by the coefficient of determination (R2) and the root mean square error (RMSE). The ability of the indices to guide fertilizer recommendation was assessed through an error analysis based on the N sufficiency index. GY was better assessed from the end of flowering to the early milk stage by VIs based on the combination of bands from near infrared radiation/visible and from near infrared radiation/red-edge regions (R2 > 0.6; RMSE < 700 kg ha−1). N output was efficiently assessed by a combination of bands from near infrared radiation/red-edge at booting (R2 > 0.7; RMSE < 9 kg N ha−1). The GNC was better estimated by VIs combining bands in near infrared radiation/red-edge at early milk, but with great variability among the years studied. Some VIs were promising for guiding fertilizer recommendation for increasing GNC, but there was not a single index providing reliable recommendations every year. This study highlights the potential of remote sensing imagery to assess GY and N output in spring wheat, but the identification of GNC responsive sites needs to be improved.
Estimation of Lower-Stratosphere-to-Troposphere Ozone Profile Using Long Short-Term Memory (LSTM)
Authors: Zhang Xinxin , Zhang Ying , Lu Xiaoyan , Bai Lu , Chen Liangfu , Tao Jinhua , Wang Zhibao , Zhu Lili
Published: April 2021

Climate change and air pollution are emerging topics due to their possible enormous implications for health and social perspectives. In recent years, tropospheric ozone has been recognized as an important greenhouse gas and pollutant that is detrimental to human health, agriculture, and natural ecosystems, and has shown a trend of increasing interest. Machine-learning-based approaches have been widely applied to the estimation of tropospheric ozone concentrations, but few studies have included tropospheric ozone profiles. This study aimed to predict the Northern Hemisphere distribution of Lower-Stratosphere-to-Troposphere (LST) ozone at a pressure of 100 hPa to the near surface by employing a deep learning Long Short-Term Memory (LSTM) model. We referred to a history of all the observed parameters (meteorological data of European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5), satellite data, and the ozone profiles of the World Ozone and Ultraviolet Data Center (WOUDC)) between 2014 and 2018 for training the predictive models. Model–measurement comparisons for the monitoring sites of WOUDC for the period 2019–2020 show that the mean correlation coefficients (R2) in the Northern Hemisphere at high latitude (NH), Northern Hemisphere at middle latitude (NM), and Northern Hemisphere at low latitude (NL) are 0.928, 0.885, and 0.590, respectively, indicating reasonable performance for the LSTM forecasting model. To improve the performance of the model, we applied the LSTM migration models to the Civil Aircraft for the Regular Investigation of the Atmosphere Based on an Instrument Container (CARIBIC) flights in the Northern Hemisphere from 2018 to 2019 and three urban agglomerations (the Sichuan Basin (SCB), North China Plain (NCP), and Yangtze River Delta region (YRD)) between 2018 and 2019. The results show that our models performed well on the CARIBIC data set, with a high R2 equal to 0.754. The daily and monthly surface ozone concentrations for 2018–2019 in the three urban agglomerations were estimated from meteorological and ancillary variables. Our results suggest that the LSTM models can accurately estimate the monthly surface ozone concentrations in the three clusters, with relatively high coefficients of 0.815–0.889, root mean square errors (RMSEs) of 7.769–8.729 ppb, and mean absolute errors (MAEs) of 6.111–6.930 ppb. The daily scale performance was not as high as the monthly scale performance, with the accuracy of R2 = 0.636~0.737, RMSE = 14.543–16.916 ppb, MAE = 11.130–12.687 ppb. In general, the trained module based on LSTM is robust and can capture the variation of the atmospheric ozone distribution. Moreover, it also contributes to our understanding of the mechanism of air pollution, especially increasing our comprehension of pollutant areas.
From Microorganism-Based Amperometric Biosensors towards Microbial Fuel Cells
Authors: Andriukonis Eivydas , Celiesiute-Germaniene Raimonda , Ramanavicius Simonas , Viter Roman , Ramanavicius Arunas
Published: April 2021

This review focuses on the overview of microbial amperometric biosensors and microbial biofuel cells (MFC) and shows how very similar principles are applied for the design of both types of these bioelectronics-based devices. Most microorganism-based amperometric biosensors show poor specificity, but this drawback can be exploited in the design of microbial biofuel cells because this enables them to consume wider range of chemical fuels. The efficiency of the charge transfer is among the most challenging and critical issues during the development of any kind of biofuel cell. In most cases, particular redox mediators and nanomaterials are applied for the facilitation of charge transfer from applied biomaterials towards biofuel cell electrodes. Some improvements in charge transfer efficiency can be achieved by the application of conducting polymers (CPs), which can be used for the immobilization of enzymes and in some particular cases even for the facilitation of charge transfer. In this review, charge transfer pathways and mechanisms, which are suitable for the design of biosensors and in biofuel cells, are discussed. Modification methods of the cell-wall/membrane by conducting polymers in order to enhance charge transfer efficiency of microorganisms, which can be potentially applied in the design of microbial biofuel cells, are outlined. The biocompatibility-related aspects of conducting polymers with microorganisms are summarized.
Toward Chalcogenide Platform Infrared Sensor Dedicated to the In Situ Detection of Aromatic Hydrocarbons in Natural Waters via an Attenuated Total Reflection Spectroscopy Study
Authors: Baillieul Marion , Baudet Emeline , Michel Karine , Moreau Jonathan , Němec Petr , Boukerma Kada , Colas Florent , Charrier Joël , Bureau Bruno , Rinnert Emmanuel , Nazabal Virginie
Published: April 2021

The objective of this study is to demonstrate the successful functionalization of the surface of a chalcogenide infrared waveguide with the ultimate goal of developing an infrared micro-sensor device. First, a polyisobutylene coating was selected by testing its physico-chemical compatibility with a Ge-Sb-Se selenide surface. To simulate the chalcogenide platform infrared sensor, the detection of benzene, toluene, and ortho-, meta- and para-xylenes was efficaciously performed using a polyisobutylene layer spin-coated on 1 and 2.5 µm co-sputtered selenide films of Ge28Sb12Se60 composition deposited on a zinc selenide prism used for attenuated total reflection spectroscopy. The thickness of the polymer coating was optimized by attenuated total reflection spectroscopy to achieve the highest possible attenuation of water absorption while maintaining the diffusion rate of the pollutant through the polymer film compatible with the targeted in situ analysis. Then, natural water, i.e., groundwater, wastewater, and seawater, was sampled for detection measurement by means of attenuated total reflection spectroscopy. This study is a valuable contribution concerning the functionalization by a hydrophobic polymer compatible with a chalcogenide optical sensor designed to operate in the mid-infrared spectral range to detect in situ organic molecules in natural water.
Privacy-Preserving IoT Data Aggregation Based on Blockchain and Homomorphic Encryption
Authors: Loukil Faiza , Ghedira-Guegan Chirine , Boukadi Khouloud , Benharkat Aïcha-Nabila
Published: April 2021

Data analytics based on the produced data from the Internet of Things (IoT) devices is expected to improve the individuals’ quality of life. However, ensuring security and privacy in the IoT data aggregation process is a non-trivial task. Generally, the IoT data aggregation process is based on centralized servers. Yet, in the case of distributed approaches, it is difficult to coordinate several untrustworthy parties. Fortunately, the blockchain may provide decentralization while overcoming the trust problem. Consequently, blockchain-based IoT data aggregation may become a reasonable choice for the design of a privacy-preserving system. To this end, we propose PrivDA, a Privacy-preserving IoT Data Aggregation scheme based on the blockchain and homomorphic encryption technologies. In the proposed system, each data consumer can create a smart contract and publish both terms of service and requested IoT data. Thus, the smart contract puts together into one group potential data producers that can answer the consumer’s request and chooses one aggregator, the role of which is to compute the group requested result using homomorphic computations. Therefore, group-level aggregation obfuscates IoT data, which complicates sensitive information inference from a single IoT device. Finally, we deploy the proposal on a private Ethereum blockchain and give the performance evaluation.
Appearance-Based Sequential Robot Localization Using a Patchwise Approximation of a Descriptor Manifold
Authors: Jaenal Alberto , Moreno Francisco-Angel , Gonzalez-Jimenez Javier
Published: April 2021

This paper addresses appearance-based robot localization in 2D with a sparse, lightweight map of the environment composed of descriptor–pose image pairs. Based on previous research in the field, we assume that image descriptors are samples of a low-dimensional Descriptor Manifold that is locally articulated by the camera pose. We propose a piecewise approximation of the geometry of such Descriptor Manifold through a tessellation of so-called Patches of Smooth Appearance Change (PSACs), which defines our appearance map. Upon this map, the presented robot localization method applies both a Gaussian Process Particle Filter (GPPF) to perform camera tracking and a Place Recognition (PR) technique for relocalization within the most likely PSACs according to the observed descriptor. A specific Gaussian Process (GP) is trained for each PSAC to regress a Gaussian distribution over the descriptor for any particle pose lying within that PSAC. The evaluation of the observed descriptor in this distribution gives us a likelihood, which is used as the weight for the particle. Besides, we model the impact of appearance variations on image descriptors as a white noise distribution within the GP formulation, ensuring adequate operation under lighting and scene appearance changes with respect to the conditions in which the map was constructed. A series of experiments with both real and synthetic images show that our method outperforms state-of-the-art appearance-based localization methods in terms of robustness and accuracy, with median errors below 0.3 m and 6°.
Older Drivers’ Motion and Simulator Sickness before and after Automated Vehicle Exposure
Authors: Classen Sherrilene , Hwangbo Seung Woo , Mason Justin , Wersal James , Rogers Jason , Sisiopiku Virginia P.
Published: April 2021

Older drivers desire independence in mobility, and automated vehicles hold plausible opportunities to realize this goal. Motion sickness (automated shuttle exposure) or simulator sickness (automated driving simulator exposure) may affect acceptance of these technologies. This study investigated the onset of motion and simulator sickness in older drivers (mean age = 74.29, SD = 5.96; female = 54%) after exposure to an automated shuttle and automated driving simulator and assessed age and sex as determinants of motion and/or simulator sickness. Using a repeated measures design, 104 older drivers were randomly allocated to the shuttle and simulator. Baseline, as well as post exposures, were measured using the Motion Sickness Assessment Questionnaire (domains: sweatiness, queasiness, dizziness, nauseousness). Older drivers who were exposed to the simulator show a statistically significant increase in simulator sickness symptoms across the four domains compared to the same group being tested in the shuttle. No age and sex differences were detected within the groups and no participants dropped out of the study due to motion or simulator sickness. The automated shuttle and simulator hold plausible opportunities for continued exposure of older drivers to these technologies, as long as motion or driving simulator sickness protocols are used properly.
Between Equality and the Right to Be Different—The Politicization of Concepts in the Fight against Discrimination Due to Sexual Orientation
Authors: Ferreira Costa Bruno
Published: April 2021

The debate around the principle of equality and the theme of discrimination around sexual orientation has been one of the most relevant in the process of ensuring the spread of human rights. After ensuring a set of civil and political rights, several groups and social movements have warned political actors of the need to look at each citizen’s individuality and guarantee through legislation and daily practices, respect for that individuality. This process is being conducted around the dichotomy between the concepts of equality and difference. It is from this analysis of the two concepts that we come across the theme of the rights of the lesbian, gay, bisexual, transvestite, transexual and transgender (LGBTQ+) community. With a qualitative approach, and while referring to the historical path of this theme, we review the central concepts in the promotion of equality and analyze the dichotomy between equality and difference. We ask, in an increasingly globalized world, does it make sense to point out difference as a mechanism for the defense of equality? Using semiotics, we approach the two central concepts and the political effort to normalize this theme to the public, using the Portuguese case (law and Non-Governmental organizations action) to characterize the central debate on equality and difference.
Comparison of Energy Expenditure Observed between Scheduled Activities in Collegiate Team-Sport Female Athletes
Authors: Moon Jessica M. , Zabriskie Hannah A. , Harty Patrick S. , Currier Bradley S. , Blumkaitis Julia C. , Stecker Richard A. , Jagim Andrew , Kerksick Chad M.
Published: April 2021

Energy needs of female team-sport athletes are poorly understood with no evidence highlighting differences present between scheduled activities. The purpose of this study was to examine the difference in energy expenditure between NCAA Division II female basketball (BBALL) and lacrosse (LAX) athletes during different scheduled team activities. Female BBALL (n = 13; 19.8 ± 1.3 yrs; 173.9 ± 13.6 cm; 74.6 ± 9.1kg; 27.1 ± 3.2%fat) and LAX (n = 20; 20.4 ± 1.8yrs; 168.4 ± 6.6cm; 68.8 ± 8.9kg; 27.9 ± 3.1%fat) athletes were outfitted with heart rate and activity monitors during four consecutive days on five different occasions (20 days total) across an entire academic year to assess differences in total daily activity energy expenditure (TDEE), activity energy expenditure (AEE), and physical activity level (PAL). Data were categorized by type of scheduled daily activities: Practice, Game, Conditioning, or Off. Independent of day type, TDEE, AEE, and PAL levels were greater (p < 0.05) in BBALL athletes. For each sport, TDEE, AEE, and PAL were significantly different (p < 0.05) between classified activity days. BBALL and LAX athletes experienced higher values on game days for TDEE, AEE, and PAL, with the lowest values experienced on off days. In conclusion, calculated levels of TDEE, AEE, and PAL in female collegiate BBALL and LAX athletes were determined to be different, irrespective of the scheduled activity.
Investigating Approaches of Integrating BIM, IoT, and Facility Management for Renovating Existing Buildings: A Review
Authors: Altohami Abubaker Basheer Abdalwhab , Haron Nuzul Azam , Ales@Alias Aidi Hizami , Law Teik Hua
Published: April 2021

The importance of building information is highly attached to the ability of conventional storing to provide professional analysis. The Internet of Things (IoT) and smart devices offer a vast amount of live data stored in heterogeneous repositories, and hence the need for smart methodologies to facilitate IoT–BIM integration is very crucial. The first step to better integrating IoT and Building Information Modeling (BIM) can be performed by implementing the Service-Oriented-Architecture (SOA) to combining software and other services by replacing the sematic information that was failed to display elements of indoor conditions. The other development is to create link that able to update static models towards real-time models using SOA approach. The existing approach relies on one-way interaction; however, developing two-way communication to mimic human cognitive has become very crucial. The high-tech approach requires highly involving Cloud computations to better connect IoT devices throughout Internet infrastructure. This approach is based on the integration of Building Information Modeling (BIM) with real-time data from IoT devices aiming at improving construction and operational efficiencies and to provide high-fidelity BIM models for numerous applications. The paper discusses challenges, limitations, and barriers that face BIM–IoT integration and simultaneously solves interoperability issues and Cloud computing. The paper provides a comprehensive review that explores and identifies common emerging areas of application and common design patterns of the traditional BIM-IoT integration followed by devising better methodologies to integrate IoT in BIM.
User Preferences in the Design of Advanced Driver Assistance Systems
Authors: Paiva Sara , Pañeda Xabiel García , Corcoba Victor , García Roberto , Morán Próspero , Pozueco Laura , Valdés Marina , del Camino Covadonga
Published: April 2021

The transport network and mobility aspects are constantly changing, and major changes are expected in the coming years in terms of safety and sustainability purposes. In this paper, we present the main conclusions and analysis of data collected from a survey of drivers in Spain and Portugal regarding user preferences, highlighting the main functionalities and behavior that an advanced driver assistance system must have in order to grant it special importance on the road to prevent accidents and also to enable drivers to have a pleasant journey. Based on the results obtained from the survey, we developed and present a working prototype for an advanced driver assistance system (ADAS), its architecture and rules systems that allowed us to create and test some scenarios in a real environment.