bluuebunny/crossref_metadata_2025 huggingface dataset:
Trends of the Dengue Serotype-4 Circulation with Epidemiological, Phylogenetic, and Entomological Insights in Lao PDR between 2015 and 2019
Authors: Calvez Elodie , Pommelet Virginie , Somlor Somphavanh , Pompon Julien , Viengphouthong Souksakhone , Bounmany Phaithong , Chindavong Thep Aksone , Xaybounsou Thonglakhone , Prasayasith Phoyphaylinh , Keosenhom Sitsana , Brey Paul T. , Telle Olivier , Choisy Marc , Marcombe Sébastien , Grandadam Marc
Published: September 2020

Dengue outbreaks have regularly been recorded in Lao People’s Democratic Republic (PDR) since the first detection of the disease in 1979. In 2012, an integrated arbovirus surveillance network was set up in Lao PDR and an entomological surveillance has been implemented since 2016 in Vientiane Capital. Here, we report a study combining epidemiological, phylogenetic, and entomological analyzes during the largest DENV-4 epidemic ever recorded in Lao PDR (2015–2019). Strikingly, from 2015 to 2019, we reported the DENV-4 emergence and spread at the country level after two large epidemics predominated by DENV-3 and DENV-1, respectively, in 2012–2013 and 2015. Our data revealed a significant difference in the median age of the patient infected by DENV-4 compared to the other serotypes. Phylogenetic analysis demonstrated the circulation of DENV-4 Genotype I at the country level since at least 2013. The entomological surveillance showed a predominance of Aedesaegypti compared to Aedesalbopictus and high abundance of these vectors in dry and rainy seasons between 2016 and 2019, in Vientiane Capital. Overall, these results emphasized the importance of an integrated approach to evaluate factors, which could impact the circulation and the epidemiological profile of dengue viruses, especially in endemic countries like Lao PDR.
Pharmacokinetics of Shikimic Acid Following Intragastric and Intravenous Administrations in Rats
Authors: Noh Keumhan , Back Hyun-Moon , Shin Beom Soo , Kang Wonku
Published: August 2020

Shikimic acid, a critical starting material for the semi-total synthesis of oseltamivir to treat and prevent influenza, exerts many pharmacological effects. However, the optimal bioanalytical method has not been adequately defined. We used liquid chromatography-tandem mass spectrometry to quantitate shikimic acid in rat plasma and studied its pharmacokinetics after intragastric and intravenous administration. Plasma was spiked with an internal standard, and the proteins were precipitated with acetonitrile, followed by solvent evaporation and reconstitution of the mobile phase. Shikimic acid was separated on a hydrophilic reverse-phase column and showed a mass transition ([M-H]−) at m/z 173.4→136.6. Shikimic acid exhibited bi-exponential decay after intravenous dosing, with a rapid distribution (5.57 h−1) up to 1 h followed by slow elimination (0.78 h−1). The steady state distribution and clearance volumes were 5.17 and 1.79 L/h/kg, respectively. After intragastric administration, the shikimic acid level peaked at about 3 h, and the material then disappeared mono-exponentially with a half-life of 1.3 h. A double peak phenomenon was observed. The absolute oral bioavailability was about 10% in rats. We explored the relationship between the pharmacokinetics and pharmacodynamics of shikimic acid.
Expression Fluctuations of Genes Involved in Carbohydrate Metabolism Affected by Alterations of Ethylene Biosynthesis Associated with Ripening in Banana Fruit
Authors: Xia Yan , Chiu Chien-Hsiang , Do Yi-Yin , Huang Pung-Ling
Published: August 2020

The banana is a typical climacteric fruit that undergoes ethylene dependent ripening. During fruit ripening, ethylene production triggers a developmental cascade that results in a series of physiological and biochemical changes. The fruit transcriptomes of untransformated wild-type (WT) and RNAi transgenic banana plants for Mh-ACO1 and Mh-ACO2 have been previously sequenced and analyzed, and most of the differentially expressed genes were enriched in ‘carbon fixation in photosynthetic organism’, ‘cysteine and methionine metabolism’, ‘citrate cycle (tricarboxylic acid cycle, TCA cycle)’, and ‘starch and sucrose metabolism’ based on Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation. In this research, we investigated the expression fluctuations of genes involved in carbohydrate metabolism affected by alterations of ethylene biosynthesis associated with ripening in banana fruits. Expression profiles of sucrose synthase, sucrose phosphate synthase, neutral invertase, and acidic invertase/β-fructofuranosidase, as analyzed by Avadis and Trinity, showed that both analyses were complementary and consistent. The overall gene expression tendency was confirmed by the implementation of quantitative real-time reverse transcription-polymerase chain reaction (RT-PCR) with mRNAs of banana fruits in Mh-ACO1 and Mh-ACO2 RNAi transgenic plants. These results indicated that altered expression of genes associated with ethylene biosynthesis strongly influenced the expression levels of genes related to starch and sucrose metabolism, as well as the glycolysis pathway in ripening banana fruits.
Phylogenetic and Comparative Analyses of Complete Chloroplast Genomes of Chinese Viburnum and Sambucus (Adoxaceae)
Authors: Ran Hang , Liu Yanyan , Wu Cui , Cao Yanan
Published: September 2020

Phylogenetic analyses of complete chloroplast genome sequences have yielded significant improvements in our understanding of relationships in the woody flowering genus Viburnum (Adoxaceae, Dipsacales); however, these relationships were evaluated focusing only on Viburnum species within Central and South America and Southeast Asia. By contrast, despite being a hotspot of Viburnum diversity, phylogenetic relationships of Viburnum species in China are less well known. Here, we characterized the complete chloroplast (cp) genomes of 21 Viburnum species endemic to China, as well as three Sambucus species. These 24 plastomes were highly conserved in genomic structure, gene order and content, also when compared with other Adoxaceae. The identified repeat sequences, simple sequence repeats (SSRs) and highly variable plastid regions will provide potentially valuable genetic resources for further population genetics and phylogeographic studies on Viburnum and Sambucus. Consistent with previous combined phylogenetic analyses of 113 Viburnum species, our phylogenomic analyses based on the complete cp genome sequence dataset confirmed the sister relationship between Viburnum and the Sambucus-Adoxa-Tetradoxa-Sinadoxa group, the monophyly of four recognized sections in Flora of China (i.e., Viburnum sect. Tinus, Viburnum sect. Solenotinus, Viburnum sect. Viburnum and Viburnum sect. Pseudotinus) and the nonmonophyly of Viburnum sect. Odontotinus and Viburnum sect. Megalotinus. Additionally, our study confirmed the sister relationships between the clade Valvatotinus and Viburnum sect. Pseudotinus, as well as between Viburnum sect. Opulus and the Odontotinus-Megalotinus group. Overall, our results clearly document the power of the complete cp genomes in improving phylogenetic resolution, and will contribute to a better understanding of plastome evolution in Chinese Adoxaceae.
Life-Cycle Assessment and Acoustic Simulation of Drywall Building Partitions with Bio-Based Materials
Authors: Quintana-Gallardo Alberto , Alba Jesús , del Rey Romina , Crespo-Amorós José E. , Guillén-Guillamón Ignacio
Published: August 2020

The ecological transition is a process the building industry is bound to undertake. This study aimed to develop new bio-based building partition typologies and to determine if they are suitable ecological alternatives to the conventional non-renewable ones used today. This work started with the development of a bio-based epoxy composite board and a waste-based sheep wool acoustic absorbent. Six different partition typologies combining conventional and bio-based materials were analyzed. A drywall partition composed of gypsum plasterboard and mineral wool was used as the baseline. First, a cradle-to-gate life cycle assessment was performed to compare their environmental impacts. Secondly, a mathematical simulation was performed to evaluate their airborne acoustic insulation. The LCA results show a 50% decrease in the amount of CO2 equivalent emitted when replacing plasterboard with bio-composite boards. The bio-composites lower the overall environmental impact by 40%. In the case of the acoustic absorbents, replacing the mineral wool with cellulose or sheep wool decreases the carbon emissions and the overall environmental impact of the partition from 4% and 6%, respectively. However, while the bio-based acoustic absorbents used offer good acoustic results, the bio-composites have a lower airborne acoustic insulation than conventional gypsum plasterboard.
Leather Waste to Enhance Mechanical Performance of High-Density Polyethylene
Authors: Kiliç Eylem , Tarrés Quim , Delgado-Aguilar Marc , Espinach Xavier , Fullana-i-Palmer Pere , Puig Rita
Published: September 2020

Leather buffing dust (BF) is a waste from tannery which is usually disposed on landfills. The interest in using wastes as fillers or reinforcements for composites has raised recently due to environmental concerns. This study investigates the potential use of BF waste as filler for a high density polyethylene matrix (HDPE). A series of HDPE-BF composites, containing filler concentrations ranging from 20 to 50wt%, were formulated, injection molded and tested. The effect of filler contents on the mechanical properties of the composites were evaluated and discussed. Composites with BF contents up to 30wt% improved the tensile strength and Young’s modulus of the matrix, achieving similar mechanical properties to polypropylene (PP). In the case of flexural strength, it was found to be proportionally enhanced by increasing reinforcement content, maintaining high impact strength. These composites present great opportunities for PP application areas that require higher impact resistance. The materials were submitted to a series of closed-loop recycling cycles in order to assess their recyclability, being able to maintain better tensile strength than virgin HDPE after 5 cycles. The study develops new low-cost and sustainable composites by using a waste as composite filler.
Approaching Spiritual and Existential Care Needs in Health Education: Applying SOPHIE (Self-Exploration through Ontological, Phenomenological, and Humanistic, Ideological, and Existential Expressions), as Practice Methodology
Authors: Ali Gulnar , Lalani Nasreen
Published: September 2020

Addressing existential and spiritual care needs, often remains a challenge in health education. Spirituality is a subjective human experience that shapes how individuals make meaning, construct knowledge, develop their own sense of reality, and bring personal and social transformation. To inspire health and social students at a London based University; learners were engaged into philosophical reasonings associated with the meaning to care. SOPHIE (Self-exploration through Ontological, Phenomenological and Humanistic, Ideological, and Existential expressions)—a reflective practice tool was applied during in-class activities from June 2019–2020. Using SOPHIE as a tool, students were encouraged to explore existential and ontological care aspects by engaging into transformative learning approaches. Participants identified their own existential and spiritual care needs by reflecting on their own meaning making process. SOPHIE enabled resilience and authenticity among learners as a reflexive discourse.
Predicting Channel Conveyance and Characterizing Planform Using River Bathymetry via Satellite Image Compilation (RiBaSIC) Algorithm for DEM-Based Hydrodynamic Modeling
Authors: Bhuyian Md N M , Kalyanapu Alfred
Published: August 2020

Digital Elevation Models (DEMs) are widely used as a proxy for bathymetric data and several studies have attempted to improve DEM accuracy for hydrodynamic (HD) modeling. Most of these studies attempted to quantitatively improve estimates of channel conveyance (assuming a non-braided morphology) rather than accounting for the actual channel planform. Accurate representation of river conveyance and planform in a DEM is critical to HD modeling and can be achieved with a combination of remote sensing (e.g., satellite image) and field data, such as water surface elevation (WSE). Therefore, the objectives of this study are (i) to develop an algorithm for predicting channel conveyance and characterizing planform via satellite images and in situ WSE and (ii) to estimate discharge using the predicted conveyance via an HD model. The algorithm is named River Bathymetry via Satellite Image Compilation (RiBaSIC) and uses Landsat satellite imagery, Shuttle Radar Topography Mission (SRTM) DEM, Multi-Error-Removed Improved-Terrain (MERIT) DEM, and observed WSE. The algorithm is tested on four study areas along the Willamette River, Kushiyara River, Jamuna River, and Solimoes River. Channel slope and predicted hydraulic radius are subsequently estimated for approximating Manning’s roughness factor. Two-dimensional HD models using DEMs modified by the RiBaSIC algorithm and corresponding Manning’s roughness factors are employed for discharge estimation. The proposed algorithm can represent river planform and conveyance in single-channeled, meandering, wandering, and braided river reaches. Additionally, the HD models estimated discharge within 14–19% relative root mean squared error (RRMSE) in simulation of five years period.
Landsat-8 and Sentinel-2 Canopy Water Content Estimation in Croplands through Radiative Transfer Model Inversion
Authors: Boren Erik J. , Boschetti Luigi
Published: August 2020

Despite the potential implications of a cropland canopy water content (CCWC) thematic product, no global remotely sensed CCWC product is currently generated. The successful launch of the Landsat-8 Operational Land Imager (OLI) in 2012, Sentinel-2A Multispectral Instrument (MSI) in 2015, followed by Sentinel-2B in 2017, make possible the opportunity for CCWC estimation at a spatial and temporal scale that can meet the demands of potential operational users. In this study, we designed and tested a novel radiative transfer model (RTM) inversion technique to combine multiple sources of a priori data in a look-up table (LUT) for inverting the NASA Harmonized Landsat Sentinel-2 (HLS) product for CCWC estimation. This study directly builds on previous research for testing the constraint of the leaf parameter (Ns) in PROSPECT, by applying those constraints in PRO4SAIL in an agricultural setting where the variability of canopy parameters are relatively minimal. In total, 225 independent leaf measurements were used to train the LUTs, and 102 field data points were collected over the 2015–2017 growing seasons for validating the inversions. The results confirm increasing a priori information and regularization yielded the best performance for CCWC estimation. Despite the relatively low variable canopy conditions, the inclusion of Ns constraints did not improve the LUT inversion. Finally, the inversion of Sentinel-2 data outperformed the inversion of Landsat-8 in the HLS product. The method demonstrated ability for HLS inversion for CCWC estimation, resulting in the first HLS-based CCWC product generated through RTM inversion.
Motion Parameter Identification and Motion Compensation for Shipborne HFSWR by Using the Reference RF Signal Generated at the Shore
Authors: Zhu Di , Niu Jiong , Li Ming , Zhang Ling , Ji Yonggang , Wu Q. M. Jonathan
Published: August 2020

The shipborne high-frequency surface wave radar (HFSWR) platform produces six degrees of freedom (DOF) motion at sea, which affects the performance of radar target detection and remote sensing of ocean surface dynamics parameters. Motion compensation can mitigate the effect of six-DOF motion, but motion parameters (including amplitude and angular frequency) need to be known. Motion parameters obtained by using high precision sensors are affected by the precision error and time delay, thus affecting the effect of motion compensation. To obtain the motion parameters accurately and in real time, a method of identifying the motion parameters by using an artificially transmitted reference radio frequency (RF) signal generated at the shore is proposed. Based on the results of the parameter identification, the reference RF signal and the first-order radar cross-sections (RCSs) modulated by six-DOF motion of the shipborne HFSWR platform can be compensated. The identification of angular frequency is divided into two steps: (1) Preliminary identification results are obtained by using the reference RF signal; (2) the pattern search method is used to further improve the identification accuracy of angular frequency. The amplitude of translation (including surge and sway) can be identified accurately through the reference RF signal. Due to the small amplitude of rotation (including roll, pitch, and yaw), it needs to be identified by the reference RF signal and pattern search method. After identifying the motion parameters, division in the time domain is used for motion compensation. Through the simulation results, both translation and rotation have good motion compensation effects. In addition, the method of using high precision sensors to obtain motion parameters and compensation is compared with the method in this paper, the simulation results of motion compensation show that the latter is better.
Estimation of Winter Wheat Production Potential Based on Remotely-Sensed Imagery and Process-Based Model Simulations
Authors: Lang Tingting , Yang Yanzhao , Jia Kun , Zhang Chao , You Zhen , Liang Yubin
Published: September 2020

Crop production potential is an index used to evaluate crop productivity capacity in one region. The spatial production potential can help give the maximum value of crop yield and visually clarify the prospects of agricultural development. The DSSAT (Decision Support System for Agrotechnology Transfer) model has been used in crop growth analysis, but spatial simulation and analysis at high resolution have not been widely performed for exact crop planting locations. In this study, the light-temperature production potential of winter wheat was simulated with the DSSAT model in the winter wheat planting area, extracted according to Remote Sensing (RS) image data in the Jing-Jin-Ji (JJJ) region. To obtain the precise study area, a Decision Tree (DT) classification was used to extract the winter wheat planting area. Geographic Information System (GIS) technology was used to process spatial data and provide a map of the spatial distribution of the production potential. The production potential of winter wheat was estimated in batches with the DSSAT model. The results showed that the light-temperature production potential is between 4238 and 10,774 kg/ha in JJJ. The production potential in the central part of the planting area is higher than that in the south and north in JJJ due to the influences of light and temperature. These results can be useful for crop model simulation users and decision makers in JJJ.
Validation and Calibration of Significant Wave Height and Wind Speed Retrievals from HY2B Altimeter Based on Deep Learning
Authors: Wang Jiuke , Aouf Lotfi , Jia Yongjun , Zhang Youguang
Published: September 2020

HY2B is now the latest altimetry mission that provides global nadir significant wave height (SWH) and sea surface wind speed. The validation and calibration of HY2B are carried out against National Data Buoy Center (NDBC) buoy observations from April 2019 to April 2020. In general, the HY2B altimeter measurements agree well with buoy observation, with scatter index of 9.4% for SWH, and 15.1% for wind speed. However, we observed a significant bias of 0.14 m for SWH and −0.42 m/s for wind speed. A deep learning technique is novelly applied for the calibration of HY2B SWH and wind speed. Deep neural network (DNN) is built and trained to correct SWH and wind speed by using input from parameters provided by the altimeter such as sigma0, sigma0 standard deviation (STD). The results based on DNN show a significant reduction of the bias, root mean square error (RMSE), and scatter index (SI) for both SWH and wind speed. Several DNN schemes based on different combination of input parameters have been examined in order to obtain the best model for the calibration. The analysis reveals that sigma0 STD is a key parameter for the calibration of HY2B SWH and wind speed.
Impact of Three Gorges Reservoir Water Impoundment on Vegetation–Climate Response Relationship
Authors: Tian Mengqi , Zhou Jianzhong , Jia Benjun , Lou Sijing , Wu Huiling
Published: September 2020

In recent years, the impact of global climate change and human activities on vegetation has become increasingly prominent. Understanding vegetation change and its response to climate variables and human activities are key tasks in predicting future environmental changes, climate changes and ecosystem evolution. This paper aims to explore the impact of Three Gorges Reservoir (TGR) water impoundment on the vegetation–climate response relationship in the Three Gorges Reservoir Region (TGRR) and its surrounding region. Firstly, based on the SPOT/VEGETATION NDVI and ERA5 reanalysis datasets, the correlation between climatic factors (temperature and precipitation) and NDVI was analyzed by using partial correlation coefficient method. Secondly, nonlinear fitting method was used to fit the mapping relationship between NDVI and climatic factors. Then, the residual analysis was conducted to evaluate the impact of TGR impoundment on vegetation–climate response relationship. Finally, sensitivity index (SI), sensitivity variation index (SVI) and difference index (DI) were defined to quantify the variation of vegetation–climate response relationship before and after water impoundment. The results show that water impoundment might have some impacts on the response of vegetation–climate, which gradually reduced with increasing distance from the channel; comparing with the residual analysis method, the SI and DI index methods are more intuitive, and combining these two methods may provide new ideas for the study of the impact of human activities on vegetation.
Comparative Review of the Algorithms for Removal of Electrocardiographic Interference from Trunk Electromyography
Authors: Xu Lin , Peri Elisabetta , Vullings Rik , Rabotti Chiara , Van Dijk Johannes P. , Mischi Massimo
Published: August 2020

Surface electromyogram (EMG) is a noninvasive measure of muscle electrical activity and has been widely used in a variety of applications. When recorded from the trunk, surface EMG can be contaminated by the cardiac electrical activity, i.e., the electrocardiogram (ECG). ECG may distort the desired EMG signal, complicating the extraction of reliable information from the trunk EMG. Several methods are available for ECG removal from the trunk EMG, but a comparative assessment of the performance of these methods is lacking, limiting the possibility of selecting a suitable method for specific applications. The aim of the present study is therefore to review and compare the performance of different ECG removal methods from the trunk EMG. To this end, a synthetic dataset was generated by combining in vivo EMG signals recorded on the biceps brachii and healthy or dysrhythmia ECG data from the Physionet database with a predefined signal-to-noise ratio. Gating, high-pass filtering, template subtraction, wavelet transform, adaptive filtering, and blind source separation were implemented for ECG removal. A robust measure of Kurtosis, i.e., KR2 and two EMG features, the average rectified value (ARV), and mean frequency (MF), were then calculated from the processed EMG signals and compared with the EMG before mixing. Our results indicate template subtraction to produce the lowest root mean square error in both ARV and MF, providing useful insight for the selection of a suitable ECG removal method.
Efficient Sky Dehazing by Atmospheric Light Fusion
Authors: Hajjami Jaouad , Napoléon Thibault , Alfalou Ayman
Published: August 2020

In this article, we present a new method of dehazing based on the Koschmieder model, which aims to restore an image that has been affected by haze. The difficulty is to improve the estimation of the transmission and the atmospheric light that generally suffer from the nonhomogeneity and the random variability of the environment. The keypoint is to enhance the dehazing of very bright regions of the image in order to improve the treatment of the sky that is often overestimated or underestimated compared to the rest of the scene. The approach proposed in this paper is based on two main contributions: 1. an L0 gradient optimization function weighted by a set of Gaussian filters and based on an iterative algorithm for optimization convergence. Unlike the existing methods using a single value of the atmospheric light for the whole image, our method uses a set of values neighboring an initial estimated value. The fusion is then applied based on Laplacian and Gaussian pyramids to combine all the relevant information from the set of images constructed from atmospheric lights and improves the contrast to recover the colors of the sky without any artifacts. Finally, the results are validated by three criteria: an autocorrelation score (ZNCC), a similarity measure (SSIM) and a visual criterion. The experiments carried out on two datasets show that our approach allows a better dehazing of the images with higher SSIM and ZNCC measurements but also with better visual quality.
Predicting Advanced Balance Ability and Mobility with an Instrumented Timed Up and Go Test
Authors: Bergquist Ronny , Nerz Corinna , Taraldsen Kristin , Mellone Sabato , Ihlen Espen A.F. , Vereijken Beatrix , Helbostad Jorunn L. , Becker Clemens , Mikolaizak A. Stefanie
Published: September 2020

Extensive test batteries are often needed to obtain a comprehensive picture of a person’s functional status. Many test batteries are not suitable for active and healthy adults due to ceiling effects, or require a lot of space, time, and training. The Community Balance and Mobility Scale (CBMS) is considered a gold standard for this population, but the test is complex, as well as time- and resource intensive. There is a strong need for a faster, yet sensitive and robust test of physical function in seniors. We sought to investigate whether an instrumented Timed Up and Go (iTUG) could predict the CBMS score in 60 outpatients and healthy community-dwelling seniors, where features of the iTUG were predictive, and how the prediction of CBMS with the iTUG compared to standard clinical tests. A partial least squares regression analysis was used to identify latent components explaining variation in CBMS total score. The model with iTUG features was able to predict the CBMS total score with an accuracy of 85.2% (84.9–85.5%), while standard clinical tests predicted 82.5% (82.2–82.8%) of the score. These findings suggest that a fast and easily administered iTUG could be used to predict CBMS score, providing a valuable tool for research and clinical care.
Characteristics Research of a High Sensitivity Piezoelectric MOSFET Acceleration Sensor
Authors: Ai Chunpeng , Zhao Xiaofeng , Wen Dianzhong
Published: September 2020

In order to improve the output sensitivity of the piezoelectric acceleration sensor, this paper proposed a high sensitivity acceleration sensor based on a piezoelectric metal oxide semiconductor field effect transistor (MOSFET). It is constituted by a piezoelectric beam and an N-channel depletion MOSFET. A silicon cantilever beam with Pt/ZnO/Pt/Ti multilayer structure is used as a piezoelectric beam. Based on the piezoelectric effect, the piezoelectric beam generates charges when it is subjected to acceleration. Due to the large input impedance of the MOSFET, the charge generated by the piezoelectric beam can be used as a gate control signal to achieve the purpose of converting the output charge of the piezoelectric beam into current. The test results show that when the external excitation acceleration increases from 0.2 g to 1.5 g with an increment of 0.1 g, the peak-to-peak value of the output voltage of the proposed sensors increases from 0.327 V to 2.774 V at a frequency of 1075 Hz. The voltage sensitivity of the piezoelectric beam is 0.85 V/g and that of the proposed acceleration sensor was 2.05 V/g, which is 2.41 times higher than the piezoelectric beam. The proposed sensor can effectively improve the voltage output sensitivity and can be used in the field of structural health monitoring.
Classification Accuracy Improvement for Small-Size Citrus Pests and Diseases Using Bridge Connections in Deep Neural Networks
Authors: Xing Shuli , Lee Malrey
Published: September 2020

Due to the rich vitamin content in citrus fruit, citrus is an important crop around the world. However, the yield of these citrus crops is often reduced due to the damage of various pests and diseases. In order to mitigate these problems, several convolutional neural networks were applied to detect them. It is of note that the performance of these selected models degraded as the size of the target object in the image decreased. To adapt to scale changes, a new feature reuse method named bridge connection was developed. With the help of bridge connections, the accuracy of baseline networks was improved at little additional computation cost. The proposed BridgeNet-19 achieved the highest classification accuracy (95.47%), followed by the pre-trained VGG-19 (95.01%) and VGG-19 with bridge connections (94.73%). The use of bridge connections also strengthens the flexibility of sensors for image acquisition. It is unnecessary to pay more attention to adjusting the distance between a camera and pests and diseases.
Prototype System for Measuring and Analyzing Movements of the Upper Limb for the Detection of Occupational Hazards
Authors: Parras-Burgos Dolores , Gea-Martínez Alfonso , Roca-Nieto Lucas , Fernández-Pacheco Daniel G. , Cañavate Francisco J. F.
Published: September 2020

In the work environment, there are usually different pathologies that are related to Repetitive Efforts and Movements (REM) that tend to predominantly affect the upper limbs. To determine whether a worker is at risk of suffering some type of pathology, observation techniques are usually used by qualified technical personnel. In order to define from quantitative data if there is a risk of suffering a pathology due to movements and repetitive efforts in the upper limb, a prototype of a movement measurement system has been designed and manufactured. This system interferes minimally with the activity studied, maintaining a reduced cost of manufacture and use. The system allows the study of the movements made by the subject in the work environment by determining the origin of the Musculoskeletal Disorder (MSD) from the movements of the elbow and wrist, collecting data on the position and accelerations of the arm, forearm and hand, and taking into account the risk factors established for suffering from an MSD: high repetition of movements, the use of a high force in a repetitive manner, or the adoption of forced positions. The data obtained with this system can be analyzed by qualified personnel from tables, graphs, and 3D animations at the time of execution, or stored for later analysis.
Empirical and Comparative Validation for a Building Energy Model Calibration Methodology
Authors: Gutiérrez González Vicente , Ramos Ruiz Germán , Fernández Bandera Carlos
Published: September 2020

The digital world is spreading to all sectors of the economy, and Industry 4.0, with the digital twin, is a reality in the building sector. Energy reduction and decarbonization in buildings are urgently required. Models are the base for prediction and preparedness for uncertainty. Building energy models have been a growing field for a long time. This paper proposes a novel calibration methodology for a building energy model based on two pillars: simplicity, because there is an important reduction in the number of parameters (four) to be adjusted, and cost-effectiveness, because the methodology minimizes the number of sensors provided to perform the process by 47.5%. The new methodology was validated empirically and comparatively based on a previous work carried out in Annex 58 of the International Energy Agency (IEA). The use of a tested and structured experiment adds value to the results obtained.
Bathymetric Monitoring of Alluvial River Bottom Changes for Purposes of Stability of Water Power Plant Structure with a New Methodology for River Bottom Hazard Mapping (Wloclawek, Poland)
Authors: Popielarczyk Dariusz , Marschalko Marian , Templin Tomasz , Niemiec Dominik , Yilmaz Isik , Matuszková Barbara
Published: September 2020

The aim of this research was to produce a new methodology for a special river bottom hazard mapping for the stability purposes of the biggest Polish water power plant: Włocławek. During the operation period of the water power plant, an engineering-geological issue in the form of pothole formation on the Wisła River bed in the gravel-sand alluvium was observed. This was caused by increased fluvial erosion resulting from a reduced water level behind the power plant, along with frequent changes in the water flow rates and water levels caused by the varying technological and economic operation needs of the power plant. Data for the research were obtained by way of a 4-year geodetic/bathymetric monitoring of the river bed implemented using integrated GNSS (Global Navigation Satellite System), RTS (Robotized Total Station) and SBES (Single Beam Echo Sounder) methods. The result is a customized river bottom hazard map which takes into account a high, medium, and low risk levels of the potholes for the water power plant structure. This map was used to redevelop the river bed by filling. The findings show that high hazard is related to 5% of potholes (capacity of 4308 m3), medium with 38% of potholes (capacity of 36,455 m3), and low hazard with 57% of potholes (capacity of 54,396 m3). Since the construction of the dam, changes due to erosion identified by the monitoring have concerned approximately 405,252 m3 of the bottom, which corresponds to 130 Olympic-size pools. This implies enormous changes, while a possible solution could be the construction of additional cascades on the Wisła River.
A Framework for Human-Robot-Human Physical Interaction Based on N-Player Game Theory
Authors: Zou Rui , Liu Yubin , Zhao Jie , Cai Hegao
Published: September 2020

In order to analyze the complex interactive behaviors between the robot and two humans, this paper presents an adaptive optimal control framework for human-robot-human physical interaction. N-player linear quadratic differential game theory is used to describe the system under study. N-player differential game theory can not be used directly in actual scenerie, since the robot cannot know humans’ control objectives in advance. In order to let the robot know humans’ control objectives, the paper presents an online estimation method to identify unknown humans’ control objectives based on the recursive least squares algorithm. The Nash equilibrium solution of human-robot-human interaction is obtained by solving the coupled Riccati equation. Adaptive optimal control can be achieved during the human-robot-human physical interaction. The effectiveness of the proposed method is demonstrated by rigorous theoretical analysis and simulations. The simulation results show that the proposed controller can achieve adaptive optimal control during the interaction between the robot and two humans. Compared with the LQR controller, the proposed controller has more superior performance.
Mechanical Fault Diagnostic in PMSM from Only One Current Measurement: A Tacholess Order Tracking Approach
Authors: Allouche Abdallah , Etien Erik , Rambault Laurent , Doget Thierry , Cauet Sebastien , Sakout Anas
Published: September 2020

This article presents a mechanical fault diagnosis methodology in synchronous machines using only a single current measurement in variable speed conditions. The proposed methodology uses order tracking in order to sample the analysis signal as a function of the rotor angle. The spectrum of the signal is then independent of speed and it could be employed in frequency analysis. Order tracking is usually applied using rotor position measurement. In this work, the proposed method uses one current measurement to estimate the position as well as the analysis signal (rotation speed). Furthermore, a statistical approach is used to create a complete diagnosis protocol. At variable speed and with only one current measurement the diagnosis is challenging. However, order tracking will allow simpler analysis. The method is proved in simulations and experimental set-up.
A Novel Inspection Technique for Electronic Components Using Thermography (NITECT)
Authors: Liu Haochen , Tinsley Lawrence , Lam Wayne , Addepalli Sri , Liu Xiaochen , Starr Andrew , Zhao Yifan
Published: September 2020

Unverified or counterfeited electronic components pose a big threat globally because they could lead to malfunction of safety-critical systems and reduced reliability of high-hazard assets. The current inspection techniques are either expensive or slow, which becomes the bottleneck of large volume inspection. As a complement of the existing inspection capabilities, a pulsed thermography-based screening technique is proposed in this paper using a digital twin methodology. A FEM-based simulation unit is initially developed to simulate the internal structure of electronic components with deviations of multiple physical properties, informed by X-ray data, along with its thermal behaviour under exposure to instantaneous heat. A dedicated physical inspection unit is then integrated to verify the simulation unit and further improve the simulation by taking account of various uncertainties caused by equipment and samples. Principle component analysis is used for feature extraction, and then a set of machine learning-based classifiers are employed for quantitative classification. Evaluation results of 17 chips from different sources successfully demonstrate the effectiveness of the proposed technique.
Remotely Sensed Data Fusion for Spatiotemporal Geostatistical Analysis of Forest Fire Hazard
Authors: Sakellariou Stavros , Cabral Pedro , Caetano Mário , Pla Filiberto , Painho Marco , Christopoulou Olga , Sfougaris Athanassios , Dalezios Nicolas , Vasilakos Christos
Published: September 2020

Forest fires are a natural phenomenon which might have severe implications on natural and anthropogenic ecosystems. Future projections predict that, under a climate change environment, the fire season would be lengthier with higher levels of droughts, leading to higher fire severity. The main aim of this paper is to perform a spatiotemporal analysis and explore the variability of fire hazard in a small Greek island, Skiathos (a prototype case of fragile environment) where the land uses mixture is very high. First, a comparative assessment of two robust modeling techniques was examined, namely, the Analytical Hierarchy Process (AHP) knowledge-based and the fuzzy logic AHP to estimate the fire hazard in a timeframe of 20 years (1996–2016). The former technique was proven more representative after the comparative assessment with the real fire perimeters recorded on the island (1984–2016). Next, we explored the spatiotemporal dynamics of fire hazard, highlighting the risk changes in space and time through the individual and collective contribution of the most significant factors (topography, vegetation features, anthropogenic influence). The fire hazard changes were not dramatic, however, some changes have been observed in the southwestern and northern part of the island. The geostatistical analysis revealed a significant clustering process of high-risk values in the southwestern and northern part of the study area, whereas some clusters of low-risk values have been located in the northern territory. The degree of spatial autocorrelation tends to be greater for 1996 rather than for 2016, indicating the potential higher transmission of fires at the most susceptible regions in the past. The knowledge of long-term fire hazard dynamics, based on multiple types of remotely sensed data, may provide the fire and land managers with valuable fire prevention and land use planning tools.
“Should I Stay, or Should I Go?”: The Experiences of, and Choices Available to Women of South Asian Heritage Living in the UK When Leaving a Relationship of Choice Following Intimate Partner Violence (IPV)
Authors: Sandhu Kalwinder K. , Barrett Hazel R.
Published: September 2020

Researching South Asian women who have departed social norms and married outside the social conventions of their culture widens our understanding and knowledge on the topic of Intimate Partner Violence (IPV). This paper will investigate how the women participating in the research navigated the socialisation of arranged marriage and expectations on them as women, and how this influenced their decisions to remain in violent and abusive relationships. Often without family support or the “safety net” of an arranged marriage, the women stayed in abusive relationships longer than they would have done if the marriage had been arranged. The findings show that the women’s experiences of leaving the relationship are mediated by the context of forming an intimate relationship. A qualitative research approach using Black Feminist Standpoint Epistemology employed thematic analysis to give voice to South Asian women’s experiences and insights into their experiences of, and responses to, leaving abusive relationships. The analysis shows that women’s agentic act of choosing a partner became the very barrier to leaving the relationship if it turned violent and abusive.
Evidence of Climate Change Engagement Behaviour on a Facebook Fan-Based Page
Authors: Deo Kirtika , Prasad Abhnil Amtesh
Published: August 2020

Climate change has become one of the most debated topics in recent times. The social media platforms have given the general public the power and propensity to share and express concerns about climate change. However, climate change awareness created on social media depends on user engagement with the contents modulated by emotions. Much has been researched in this area using Twitter, but Facebook fan-based pages have not been extensively explored in the past. In this study, we investigate the engagement behaviour of users on a Facebook fan-based page titled “Global Climate Change Awareness” by analysing user insights data for two years starting from April 2018 to April 2020. Results show that the frequency of posts made to the page did not significantly promote engagement but improved visibility of the contents to the users. Overall, fan growth was attributed more to increased post visibility that enhanced post engagement. Hashtags associated with climate change had a significant reach amongst users, but those associated with disasters where the page expressed sadness and informed users about taking precautions had the highest engagement rate. Likewise, users from developing countries, especially from the small islands, were more engaged with climate change awareness. This study did not assess negative responses from users (possible deniers of climate change) and other Facebook fan-based pages due to data privacy and stringent Facebook policy.
A GIS-Based Approach to Inform Agriculture-Water-Energy Nexus Planning in the North Western Sahara Aquifer System (NWSAS)
Authors: Almulla Youssef , Ramirez Camilo , Pegios Konstantinos , Korkovelos Alexandros , Strasser Lucia de , Lipponen Annukka , Howells Mark
Published: August 2020

The North Western Sahara Aquifer System (NWSAS) is a vital groundwater source in a notably water-scarce region. However, impetuous agricultural expansion and poor resource management (e.g., over-irrigation, inefficient techniques) over the past decades have raised a number of challenges. In this exploratory study, we introduce an open access GIS-based model to help answer selected timely questions related to the agriculture, water and energy nexus in the region. First, the model uses spatial and tabular data to identify the location and extent of irrigated cropland. Then, it employs spatially explicit climatic datasets and mathematical formulation to estimate water and electricity requirements for groundwater irrigation in all identified locations. Finally, it evaluates selected supply options to meet the electricity demand and suggests the least-cost configuration in each location. Results indicate that full irrigation in the basin requires ~3.25 billion million m3 per year. This translates to ~730 GWh of electricity. Fossil fuels do provide the least-cost electricity supply option due to lower capital and subsidized operating costs. Hence, to improve the competitiveness of renewable technologies (RT) (i.e., solar), a support scheme to drop the capital cost of RTs is critically needed. Finally, moving towards drip irrigation can lead to ~47% of water abstraction savings in the NWSAS area.
An Adaptive Feed-Forward Phase Locked Loop for Grid Synchronization of Renewable Energy Systems under Wide Frequency Deviations
Authors: Kathiresan Aravind Chellachi , PandiaRajan Jeyaraj , Sivaprakash Asokan , Sudhakar Babu Thanikanti , Islam Md. Rabiul
Published: August 2020

Synchronization is a crucial problem in the grid-connected inverter’s control and operation. A phase-locked loop (PLL) is a typical grid synchronization strategy, which ought to have a high resistance to power system uncertainties since its sensitivity influences the generated reference signal. The traditional PLL catches the phase and frequency of the input signal via the feedback loop filter (LF). In general, to enhance the steady-state capability during distorted grid conditions generally, a filter tuned for nominal frequency is used. This PLL corrects large frequency deviations around the nominal frequency, which increases the PLL’s locking time. Therefore, this paper presents an adaptive feed-forward PLL, where the input signal frequency and phase under large frequency deviations are tracked precisely, which overcomes the above-mentioned limitations. The proposed adaptive PLL consists of a feedback loop that reduces the phase error. The feed-forward loop predicts the frequency and phase error, and the frequency adaptive FIR filter reduces the ripples in output, which is due to input distortions. The adaptive mechanism adjusts the gain of the filter in accordance with the supply frequency. This reduces the phase and frequency error and also decreases the locking time under wide frequency deviations. To verify the effectiveness of the proposed adaptive feed-forward PLL, the system was tested under different grid abnormal conditions. Further, the stability analysis has been carried out via a developed prototype test platform in the laboratory. To bring the proposed simulations into real-time implementations and for control strategies, an Altera Cyclone II field-programmable gate array (FPGA) board has been used. The obtained results of the proposed PLL via simulations and hardware are compared with conventional techniques, and it indicates the superiority of the proposed method. The proposed PLL effectively able to tackle the different grid uncertainties, which can be observed from the results presented in the result section.