bluuebunny/crossref_metadata_2025 huggingface dataset:
Elastomer-Based Visuotactile Sensor for Normality of Robotic Manufacturing Systems
Authors: Zaid Islam Mohamed , Halwani Mohamad , Ayyad Abdulla , Imam Adil , Almaskari Fahad , Hassanin Hany , Zweiri Yahya
Published: November 2022

Modern aircrafts require the assembly of thousands of components with high accuracy and reliability. The normality of drilled holes is a critical geometrical tolerance that is required to be achieved in order to realize an efficient assembly process. Failure to achieve the required tolerance leads to structures prone to fatigue problems and assembly errors. Elastomer-based tactile sensors have been used to support robots in acquiring useful physical interaction information with the environments. However, current tactile sensors have not yet been developed to support robotic machining in achieving the tight tolerances of aerospace structures. In this paper, a novel elastomer-based tactile sensor was developed for cobot machining. Three commercial silicon-based elastomer materials were characterised using mechanical testing in order to select a material with the best deformability. A Finite element model was developed to simulate the deformation of the tactile sensor upon interacting with surfaces with different normalities. Additive manufacturing was employed to fabricate the tactile sensor mould, which was chemically etched to improve the surface quality. The tactile sensor was obtained by directly casting and curing the optimum elastomer material onto the additively manufactured mould. A machine learning approach was used to train the simulated and experimental data obtained from the sensor. The capability of the developed vision tactile sensor was evaluated using real-world experiments with various inclination angles, and achieved a mean perpendicularity tolerance of 0.34°. The developed sensor opens a new perspective on low-cost precision cobot machining.
On Comparison of Heat Treated and Non-Heat-Treated LOM Manufactured Sample for Poly(lactic)acid: Mechanical and Morphological View Point
Authors: Singh I. , Kumar S. , R. Koloor S. S. , Kumar D. , Yahya M. Y. , Mago J.
Published: November 2022

This work reports the comparison of heat-treated and non-heat-treated laminated object-manufactured (LOM) 3D-printed specimens from mechanical and morphological viewpoints. The study suggests that heat treatment of the FDM-printed specimen may have a significant impact on the material characteristics of the polymer. The work has been performed at two stages for the characterization of (a) non-heat-treated samples and (b) heat-treated samples. The results for stage 1 (non-heat-treated samples) suggest that the infill density: 70%, infill pattern: honeycomb, and six number of discs in a single LOM-manufactured sample is the optimized condition with a compression strength of 42.47 MPa. The heat treatment analysis at stage 2 suggests that a high temperature: 65 °C, low time interval: 10 min, works equally well as the low temperature: 55 °C, high time interval: 30 min. The post-heat treatment near Tg (65 °C) for a time interval of 10 min improved the compressive strength by 105.42%.
Preparation and Performance of Water-Active Polyurethane Grouting Material in Engineering: A Review
Authors: Wang Juan , Gao Shuang , Zhang Chao , Deng Yu , Zhang Peng
Published: November 2022

Polyurethane foam materials have broad application prospects in practical engineering as flame retardants, waterproof coatings, and grout repair materials due to advantages such as light weight, quick forming, and good durability. Due to water’s low cost and convenience, water-reactive Polyurethane foam materials are widely used in engineering. The content of the water has a significant effect on the performance of polyurethane foams after molding. Polyurethane foams with anti-seepage and reinforcement effects are used in complex water environments for long durations. This study analyzed the effects of water content on properties and the diffusion mechanism of polyurethane foam materials in water. Additionally, the effect of the water environment on the polyurethane grouting material’s properties was summarized. Finally, this study discussed the future research directions of polyurethane foam materials in a water environment.
Percutaneous Electroosmosis of Berberine-Loaded Ca2+ Crosslinked Gelatin/Alginate Mixed Hydrogel
Authors: Liu Yinyin , Shen Si , Wu Yifang , Wang Mengmeng , Cheng Yongfeng , Xia Hongmei , Jia Ruoyang , Liu Chang , Wang Yu , Xia Ying , Cheng Xiaoman , Yue Yan , Xie Zili
Published: November 2022

Flexible conductive hydrogel has been driven by scientific breakthroughs and offers a wide variety of applications, including sensors, electronic skins, biomedicine, energy storage, etc. Based on the mixed-ion crosslinking method, gelatin and sodium alginate (Gel–Alg) composite hydrogels were successfully prepared using Ca2+ crosslinking. The migration behavior of berberine hydrochloride (BBH) in the matrix network structure of Gel–Alg hydrogel with a certain pore size under an electric field was studied, and the transdermal effect of berberine hydrochloride under an electric field was also studied. The experimental results show that Gel–Alg has good flexibility and conductivity, and electrical stimulation can enhance the transdermal effect of drugs. Gel–Alg composite hydrogel may be a new material with potential application value in future biomedical directions.
Challenges of Urban Artificial Landscape Water Bodies: Treatment Techniques and Restoration Strategies towards Ecosystem Services Enhancement
Authors: Addo-Bankas Olivia , Zhao Yaqian , Gomes Arlindo , Stefanakis Alexandros
Published: November 2022

With the rapid adoption of green infrastructure and nature-based solutions for a low-impact development, much consideration is given to ecosystem services and the ecological enhancement in modern planning of urban spaces. Artificial landscape water bodies have, in recent years, been utilized to enhance the ecological quality of urban environments. As an environmentally friendly measure, the water source of these waters has predominantly been adopting reclaimed water (treated wastewater). As a result, landscape water bodies are often eutrophic, exhibiting poor hydrodynamics, with lengthy water change cycles, creating the ideal environment for algal blooms that negatively impact the aesthetic appeal of these landscape waters. Based on the existing literature, this paper summarizes the treatment techniques and strategies employed in enhancing the quality of urban artificial landscape water bodies and providing integrated design solutions in the urban environment.
A Study of Strong Confinement Regions Using Informational Entropy
Authors: Santos Ademir de J. , Prudente Frederico V. , Guimarães Marcilio N. , Nascimento Wallas S.
Published: November 2022

We present an informational study of a spherically confined hydrogen atom, a hydrogenic ion confined in a strongly coupled plasma, a spherically confined harmonic oscillator, and a particle confined in a cage. For this, we have implemented a numerical procedure to obtain information entropies of these confined quantum systems. The procedure is based on the variational formalism that uses the finite element method (FEM) for the expansion of the wavefunction in terms of local base functions. Such a study is carried out in order to analyze what happens in the rigorous confinement regime. In particular, we have shown that the effects of the interaction potential is no longer important for rigorous confinements and the studied systems start to behave just like an electron confined by a impenetrable spherical cage. When possible, we compared our results with those published in the literature.
Plant Density Estimation Using UAV Imagery and Deep Learning
Authors: Peng Jinbang , Rezaei Ehsan Eyshi , Zhu Wanxue , Wang Dongliang , Li He , Yang Bin , Sun Zhigang
Published: November 2022

Plant density is a significant variable in crop growth. Plant density estimation by combining unmanned aerial vehicles (UAVs) and deep learning algorithms is a well-established procedure. However, flight companies for wheat density estimation are typically executed at early development stages. Further exploration is required to estimate the wheat plant density after the tillering stage, which is crucial to the following growth stages. This study proposed a plant density estimation model, DeNet, for highly accurate wheat plant density estimation after tillering. The validation results presented that (1) the DeNet with global-scale attention is superior in plant density estimation, outperforming the typical deep learning models of SegNet and U-Net; (2) the sigma value at 16 is optimal to generate heatmaps for the plant density estimation model; (3) the normalized inverse distance weighted technique is robust to assembling heatmaps. The model test on field-sampled datasets revealed that the model was feasible to estimate the plant density in the field, wherein a higher density level or lower zenith angle would degrade the model performance. This study demonstrates the potential of deep learning algorithms to capture plant density from high-resolution UAV imageries for wheat plants including tillers.
Quantifying the Spatio-Temporal Variations and Impacts of Factors on Vegetation Water Use Efficiency Using STL Decomposition and Geodetector Method
Authors: Wang Guigang , Li Xuemei , Zhao Kaixin , Li Yikun , Sun Xuwei
Published: November 2022

Water use efficiency of vegetation (WUE), the ratio of carbon gain to water loss, is a valid indicator to describe the photosynthetic carbon–water coupling relationship. Understanding how and why WUE changes are essential for regional ecological conservation. However, the impacts of various factors and their interactions on the spatial variation of WUE remain uncertain in the arid land of Northwest China. Here, we selected the Qilian Mountains (QM) and Hexi Corridor (HC) as the study areas. Supported by the Google Earth Engine, we explored the spatio-temporal variations of WUE in QM and HC for 2002–2021 using STL decomposition (a seasonal-trend decomposition procedure), trend analysis, and the Hurst index. Then, the Geodetector method was applied to quantify impacts of geographical and eco-meteorological factors on the spatial variation of WUE. The WUE in HC was higher than that in QM. Interestingly, the opposite longitude zonality characteristics are shown in the QM and HC. In QM, the WUE showed an upward trend with longitude increasing, while a downward trend with longitude increasing in the oases of HC. The WUE of cropland was the highest (1.15 ± 0.35 gC kg−1 H2O), and that of alpine vegetation was the lowest (0.2 ± 0.15 gC kg−1 H2O). WUE showed a decreasing trend across the study area, almost certainly due to a drop from May to July during 2002–2021. The air temperature is the dominant factor influencing the spatial variation of WUE. In addition, the interaction of any two factors is greater than the independent influence of either factor alone. The Geodetector method proved to be effective for quantifying the impact of complex multi-factors on the spatial variation of WUE. This study provides a new technical scheme to analyze the spatio-temporal pattern and quantify the impact of multi-factors on the spatial variation of WUE. These findings aid in understanding underlying mechanisms of WUE variation and thereby will be beneficial for clarifying the response of vegetation to climate change.
Marine Extended Target Tracking for Scanning Radar Data Using Correlation Filter and Bayes Filter Jointly
Authors: Liu Jiaqi , Wang Zhen , Cheng Di , Chen Weidong , Chen Chang
Published: November 2022

As the radar resolution improves, the extended structure of the targets in radar echoes can make a significant contribution to improving tracking performance, hence specific trackers need to be designed for these targets. However, traditional radar target tracking methods are mainly based on the accumulation of the target’s motion information, and the target’s appearance information is ignored. In this paper, a novel tracking algorithm that exploits both the appearance and motion information of a target is proposed to track a single extended target in maritime surveillance scenarios by incorporating the Bayesian motion state filter and the correlation appearance filter. The proposed algorithm consists of three modules. Firstly, a Bayesian module is utilized to accumulate the motion information of the target. Secondly, a correlation module is performed to capture the appearance features of the target. Finally, a fusion module is proposed to integrate the results of the former two modules according to the Maximum A Posteriori Criterion. In addition, a feedback structure is proposed to transfer the fusion results back to the former two modules to improve their stability. Besides, a scale adaptive strategy is presented to improve the tracker’s ability to cope with targets with varying shapes. In the end, the effectiveness of the proposed method is verified by measured radar data. The experimental results demonstrate that the proposed method achieves superior performance compared with other traditional algorithms, which simply focus on the target’s motion information. Moreover, this method is robust under complicated scenarios, such as clutter interference, target shape changing, and low signal-to-noise ratio (SNR).
A Possibility-Based Method for Urban Land Cover Classification Using Airborne Lidar Data
Authors: Zhao Danjing , Ji Linna , Yang Fengbao , Liu Xiaoxia
Published: November 2022

Airborne light detection and ranging (LiDAR) has been recognized as a reliable and accurate measurement tool in forest volume estimation, urban scene reconstruction and land cover classification, where LiDAR data provide crucial and efficient features such as intensity, elevation and coordinates. Due to the complex urban environment, it is difficult to classify land cover accurately and quickly from remotely sensed data. Methods based on the Dempster–Shafer evidence theory (DS theory) offer a possible solution to this problem. However, the inconsistency in the correspondence between classification features and land cover attributes constrains the improvement of classification accuracy. Under the original DS evidence theory classification framework, we propose a novel method for constructing a basic probability assignment (BPA) function based on possibility distributions and apply it to airborne LiDAR land cover classification. The proposed approach begins with a feature classification subset selected by single-feature classification results. Secondly, the possibility distribution of the four features was established, and the uncertainty relationship between feature values and land cover attributes was obtained. Then, we selected suitable interval cut-off points and constructed a BPA function. Finally, DS evidence theory was used for land cover classification. LiDAR and its co-registration data acquired by Toposys Falcon II were used in the performance tests of the proposed method. The experimental results revealed that it can significantly improve the classification accuracy compared to the basic DS method.
Earthquake-Induced Landslide Susceptibility Assessment Using a Novel Model Based on Gradient Boosting Machine Learning and Class Balancing Methods
Authors: Zhang Shuhao , Wang Yawei , Wu Guang
Published: November 2022

Predicting the susceptibility of a specific part of a landslide (SSPL) involves predicting the likelihood that the part of the landslide (e.g., the entire landslide, the source area, or the scarp) will form in a given area. When predicting SSPL, the landslide samples are far less than the non-landslide samples. This class imbalance makes it difficult to predict the SSPL. This paper proposes an advanced artificial intelligence (AI) model based on the dice-cross entropy (DCE) loss function and XGBoost (XGBDCE) or Light Gradient Boosting Machine (LGBDCE) to ameliorate the class imbalance in the SSPL prediction. We select the earthquake-induced landslides from the 2018 Hokkaido earthquake as a case study to evaluate our proposed method. First, six different datasets with 24 landslide influencing factors and 10,422 samples of a specific part of the landslides are established using remote sensing and geographic information system technologies. Then, based on each of the six datasets, four landslide susceptibility algorithms (XGB, LGB, random-forest (RF) and linear discriminant analysis (LDA)) and four class balancing methods (non-balance (NB), equal-quantity sampling (EQS), inverse landslide-frequency weighting (ILW), and DCE loss) are applied to predict the SSPL. The results show that the non-balanced method underestimates landslide susceptibility, and the ILW or EQS methods overestimate the landslide susceptibility, while the DCE loss method produces more balanced results. The prediction performance of the XGBDCE (average area under the receiver operating characteristic curve (0.970) surpasses that of RF (0.956), LGB (0.962), and LDA (0.921). Our proposed methods produce more unbiased and precise results than the existing models, and have a great potential to produce accurate general (e.g., predicting the entire landslide) and detailed (e.g., combining the prediction of the landslide source area with the landslide run-out modeling) landslide susceptibility assessments, which can be further applied to landslide hazard and risk assessments.
Adsorption of Orange G in Liquid Solution by the Amino Functionalized GO
Authors: Yang Zhiquan , He Chong , Liao Wenning , Zhang Xinyi , Liu Wanhui , Zou Baosheng
Published: November 2022

Dye effluent damaged the water environment and human health with its massive discharge. In order to eliminate dye from the water environment, a variety of adsorbents were used to investigate dye removal. Graphene oxide (GO) attracted extensive attention due to its excellent surface property in the degradation of dye wastewater. Modified GO with multifunctional groups helped to improve adsorption performance. 3-Aminopropyltriethoxysilane modified GO (AS-GO) was fabricated for the removal of Orange G (OG) in this study. The results showed that AS-GO had an excellent adsorption ability of OG. During the reaction process, the maximum adsorptive capacity of OG was up to 576.6 mg/g at T = 313 K and pH = 3 with the initial OG concentration of 100 mg/L and the initial adsorbent dose of 2.5 g/L. The adsorption kinetic process of AS-GO conformed to the pseudo-second-order and Langmuir models. The spontaneous and endothermic adsorption of OG occurred in the adsorption process. The main adsorption mechanisms were electrostatic, π–π and hydrogen bonding interactions in the reaction process. After four cycles of AS-GO, it maintained high removal efficiency owing to its remarkable stability. The scheme of GO modified with AS could hinder the agglomeration of GO and provide more active sites, which would further enhance the adsorption properties and expand its application in water purification.
A Large-Scale Investigation of the Status of Out-Resettlers from the Three Gorges Area Based on the Production–Living–Social Security–Social Integration–Satisfaction Perspective
Authors: Peng Zhou , Xiao Xiaochun , Lv Ye , Guan Xiaoyan , Wang Wei
Published: November 2022

Monitoring the living and production standards of resettlers due to hydraulic engineering is at the core of the evaluation of the effectiveness of resettlement and providing post-relocation support. In the past two decades, 0.196 million individuals were relocated outside of the reservoir area (out-resettlers) because of the construction of Three Gorges Dam. In 2019, large-scale tracking and monitoring of resettlers in 1371 households in 122 villages and 12 provinces was conducted by using the methods of stratified sampling, equidistant random sampling, and simple random sampling. The status of out-resettlers from the Three Gorges Reservoir area was compared with that of local residents in resettlement areas and nearby-resettlers based on the production–living–social security–social integration–satisfaction perspective. The results show that the living and production conditions of out-resettlers have significantly improved, and their income and consumption were positively correlated with the development level of the resettlement area. More than 90% of out-resettlers have adapted to local languages, cultural customs, and living habits. Out-resettlers have the highest satisfaction with infrastructure construction and public service facilities, at more than 90%, and the lowest satisfaction with the availability of arable land, at approximately 80%. This study can provide a reference for follow-up work on the Three Gorges Project.
Adoption of Environmental Information Chatbot Services Based on the Internet of Educational Things in Smart Schools: Structural Equation Modeling Approach
Authors: Rukhiran Meennapa , Phaokla Napasorn , Netinant Paniti
Published: November 2022

The Internet of Educational Things (IoET) equips chatbots with real-time environmental information monitoring to prevent student and instructor absences and safeguard their health. Individual behavioral intention toward a chatbot service is essential for better understanding the user’s experience and acceptance of monitoring environmental elements such as PM2.5, temperature, humidity, and carbon monoxide. This study aims to apply an integration of an extended framework for smart schools developing an environmental information chatbot service (ENICS) and various users’ continued behavioral intentions toward the chatbot system based on the unified theory of acceptance and use of technology model to support health and safety in universities. The proposed framework design can incorporate Internet of Things architecture to develop and utilize the chatbot services. The key results of the partial least square test largely support the validity of the proposed model and the significant effects of IoET, performance expectation, effort expectation, social influence, facilitating conditions, health and safety, behavioral intention, and use behavior on personal environmental information chatbot utilization. This study’s findings deal with a better design for environmental system development and understanding the factors influencing an individual’s intention to continue using a chatbot service for IoET applications with low-cost information facilities in safe environmental sustainability.
Integrable Coupling of Expanded Isospectral and Non-Isospectral Dirac Hierarchy and Its Reduction
Authors: Chen Cheng , Zhou Jian , Zhao Shiyin , Feng Binlu
Published: November 2022

In this paper, we first generalize the Dirac spectral problem to isospectral and non-isospectral problems and use the Tu scheme to derive the hierarchy of some new soliton evolution equations. Then, integrable coupling is obtained by solving the isospectral and non-isospectral zero curvature equations.We find that the obtained hierarchy has the bi-Hamiltonian structure of the combined form. In particular, one of the integrable soliton hierarchies is reduced to be similar to the coupled nonlinear Schördinger system in the AKNS hierarchy. Next, the strict self-adjointness of the reduced equation system is verified, and conservation laws are constructed with the aid of the Ibragimov method. In addition, we apply the extended Kudryashov method to obtain some exact solutions of this reduced equation system.
Modeling Species-Specific Collision Risk of Birds with Wind Turbines: A Behavioral Approach
Authors: Linder Anne Cathrine , Lyhne Henriette , Laubek Bjarke , Bruhn Dan , Pertoldi Cino
Published: November 2022

The increasing number of wind energy sites developed globally, has consequently resulted in a green-on-green predicament, due to an increase in avian mortality caused by collisions with wind turbines. The proportion of collision-related fatalities is not evenly distributed across species, indicating that some species groups are more prone to turbine collision. Such differences between species have been proposed to be affiliated with species-specific foraging and flight behavior. The aim of this study is to investigate how the flight behavioral traits; head position, active flight, track symmetry, and track tortuosity can be used to model collision risk along with other influencing factors i.e., weather variables (temperature, wind speed, and cloud coverage) and temporal variables (time of day and time of year). The study also sought to investigate the species-specificity of the four traits in relation to the phylogenetic relatedness of the study species. This was achieved through a case study at a wind farm on the Swedish island of Gotland in which the behavior of birds from 11 different genera was studied. The flight behavior of these species was assessed using data collected by the IdentiFlight system, e.g., flight trajectories and images of the birds throughout their flight track. The results confirm the species-specificity of the four flight behaviors and indicated that all four traits can be used to predict collision risk along with species as a categorical factor. The framework provided in this study along with the results of the case study can be used to identify risk-prone species based on phylogenetic relatedness and flight behavior.
Glutamine Synthetase Contributes to the Regulation of Growth, Conidiation, Sclerotia Development, and Resistance to Oxidative Stress in the Fungus Aspergillus flavus
Authors: Wang Sen , Lin Ranxun , Tumukunde Elisabeth , Zeng Wanlin , Bao Qian , Wang Shihua , Wang Yu
Published: November 2022

The basic biological function of glutamine synthetase (Gs) is to catalyze the conversion of ammonium and glutamate to glutamine. This synthetase also performs other biological functions. However, the roles of Gs in fungi, especially in filamentous fungi, are not fully understood. Here, we found that conditional disruption of glutamine synthetase (AflGsA) gene expression in Aspergillus flavus by using a xylose promoter leads to a complete glutamine deficiency. Supplementation of glutamine could restore the nutritional deficiency caused by AflGsA expression deficiency. Additionally, by using the xylose promoter for the downregulation of AflgsA expression, we found that AflGsA regulates spore and sclerotic development by regulating the transcriptional levels of sporulation genes abaA and brlA and the sclerotic generation genes nsdC and nsdD, respectively. In addition, AflGsA was found to maintain the balance of reactive oxygen species (ROS) and to aid in resisting oxidative stress. AflGsA is also involved in the regulation of light signals through the production of glutamine. The results also showed that the recombinant AflGsA had glutamine synthetase activity in vitro and required the assistance of metal ions. The inhibitor molecule L-α-aminoadipic acid suppressed the activity of rAflGsA in vitro and disrupted the morphogenesis of spores, sclerotia, and colonies in A. flavus. These results provide a mechanistic link between nutrition metabolism and glutamine synthetase in A. flavus and suggest a strategy for the prevention of fungal infection.
Natural Occurrence of Alternaria Toxins in Agricultural Products and Processed Foods Marketed in South Korea by LC–MS/MS
Authors: Woo So Young , Lee Sang Yoo , Jeong Tae Kyun , Park Su Mi , Auh Joong Hyuck , Shin Han-Seung , Chun Hyang Sook
Published: November 2022

Alternaria mycotoxins including alternariol (AOH), alternariol monomethyl ether (AME), altenuene (ALT), altertoxin-I (ATX-I), tentoxin (TEN), and tenuazonic acid (TeA), are ubiquitous contaminants in agricultural products. A method for the simultaneous determination of these six toxins by ultrahigh performance liquid chromatography–tandem mass spectrometry (LC–MS/MS) with solid phase extraction (SPE) was validated in rice, sesame, tomato, and apple juice matrices. The performance of the method was evaluated in terms of linearity (R2 > 0.999), the limit of detection (0.04–1.67 μg/kg), the limit of quantification (0.12–5.06 μg/kg), recovery (80.0–114.7%), and precision (<17.7%). The validated method was applied to monitor 152 marketed food samples in South Korea, as well as to investigate the co-occurrence and correlation between Alternaria toxins. The mean occurrence levels were 2.77 μg/kg for AOH, 4.36 μg/kg for AME, 0.14 μg/kg for ALT, 0.11 μg/kg for ATX-I, 0.43 μg/kg for TEN, and 104.56 μg/kg for TeA. Mean and extreme (95th percentile) daily dietary exposures of South Koreans to Alternaria toxins were estimated to be 22.93 ng/kg b.w./day and 86.07 ng/kg b.w./day, respectively.
The Potential of Alternaria Toxins Production by A. alternata in Processing Tomatoes
Authors: Qin Qiaomei , Fan Yingying , Jia Qinlan , Duan Shuaishuai , Liu Fengjuan , Jia Binxin , Wang Guangquan , Guo Wanhui , Wang Cheng
Published: November 2022

As a filamentous and spoilage fungus, Alternaria spp. can not only infect processing tomatoes, but also produce a variety of mycotoxins which harm the health of human beings. To explore the production of Alternaria toxins in processing tomatoes during growth and storage, four main Alternaria toxins and four conjugated toxins were detected by ultrahigh-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and ultra-performance liquid chromatography-ion mobility quadrupole time-of-flight mass spectrometry (UPLC-IMS QToF MS) in processing tomatoes on different days after being inoculated with A. alternata. The results show that the content of Alternaria toxins in an in vivo assay is higher than that under field conditions. Tenuazonic acid (TeA) is the predominant toxin detected in the field (205.86~41,389.19 μg/kg) and in vivo (7.64~526,986.37 μg/kg) experiments, and the second-most abundant toxin is alternariol (AOH). In addition, a small quantity of conjugated toxins, AOH-9-glucoside (AOH-9-Glc) and alternariol monomethyl ether-3-glucoside (AME-3-Glc), were screened in the in vivo experiment. This is the first time the potential of Alternaria toxins produced in tomatoes during the harvest period has been studied in order to provide data for the prevention and control of Alternaria toxins.
Evolution of Blood Safety in Switzerland over the Last 25 Years for HIV, HCV, HBV and Treponema pallidum
Authors: Niederhauser Christoph , Tinguely Caroline , Stolz Martin , Vock Michael , El Dusouqui Soraya Amar , Gowland Peter
Published: November 2022

During the last few decades, efforts to increase the safety of blood and blood products have mainly focused on preventing the viral infections HCV, HIV, HBV and Treponema pallidum. The evolution of these approaches and the achieved increase in safety is shown for the last 25 years in Switzerland. In detail, the prevalences and incidences of the infection disease and the theoretical estimated residual risks (RR) of these blood-borne infections are presented. Prevalences, incidences and, in particular, the RR have decreased considerably over the last 25 years. This was achieved primarily by the adoption of strict criteria for the selection of blood donors, refined questionnaires, the introduction of increasingly sensitive serological screening tests and the implementation of nucleic acid testing (NAT) for these blood-borne pathogens. These NAT assays have significantly shortened the window period between infection and the first detection of the infectious agent in the blood of an infected individual. A form of “real life” comparison or confirmation is provided by the reported lookback procedures (LBP) and the haemovigilance data of the Swiss competent authority, Swissmedic. These data are in agreement, and thus support the very low prevalences, incidences and RR.
A Possibility of Vasospastic Angina after mRNA COVID-19 Vaccination
Authors: Awaya Toru , Moroi Masao , Nakamura Fuminori , Toi Satoru , Wakiya Momoko , Enomoto Yoshinari , Kunimasa Taeko , Nakamura Masato
Published: November 2022

We report a case of vasospastic angina (VSA) following COVID-19 mRNA vaccination. Despite the widespread occurrence of myocarditis, there have been few reports of post-vaccinal VSA. A 41-year-old male patient was referred for chest pain at rest following mRNA vaccination; he had never experienced chest pain prior to vaccination. He was diagnosed by an acetylcholine (Ach) provocation test that showed multivessel vasospasm. After the initiation of treatment with a calcium channel blocker and nitrate, no further exacerbation of chest pain was observed. To our knowledge, this constitutes the first reported case of VSA proven by Ach provocation test after COVID-19 vaccination. The vaccination may increase coronary artery spasticity. VSA should be ruled out in post-vaccine new onset resting chest pain.
Integrated Hydrogeochemical Groundwater Flow Path Modelling in an Arid Environment
Authors: Masoud Milad , Rajmohan Natarajan , Basahi Jalal , Schneider Michael , Niyazi Burhan , Alqarawy Abdulaziz
Published: November 2022

In this study, water-rock interaction, salinity sources, evolution, and the mixing of groundwater were modelled. The objectives of this research are to understand the hydrogeochemical factors that govern groundwater composition in a shallow aquifer system, Jazan Province, Saudi Arabia. The study aquifer is called a Quaternary aquifer, which is composed of gravel, sand, sandstone, and intercalated with some shale. In this study, 80 groundwater samples have been collected and analyzed for major ions and 30 representative samples were analyzed for Oxygen-18 (δ18O) and Deuterium (δD). NETPATH and environmental isotopes were integrated and applied to study the overall geochemical processes and to identify the salinity source in the groundwater. Saturation indices calculated for carbonates minerals indicates that 49%, 74%, and 61% of groundwater samples are undersaturated in terms of calcite, aragonite, and dolomite minerals, respectively. The remaining groundwater samples (51%, 39%, and 26%) are close to saturation with calcite, dolomite, and aragonite minerals, respectively. The saturation indices of gypsum, anhydrite, silica, strontionite, and sepiolite minerals show undersaturation in all groundwater samples, which is likely due to the dilution through the groundwater recharge from the surface runoff. In this study, water-rock interaction models were employed with the concentration of major ions of all selected groundwater samples, in addition to reference waters such as rain and sea waters, to evaluate the chemistry of groundwater in the flow path. Mixing calculations suggested that there is a variable contribution of rainwater (5% to 53%) in groundwater samples. The results indicate that evaporation and infiltration have a major impact on water chemistry in the study site. The intrusion of seawater at the coastal zone is well identified in some wells. Stable isotope data (δ18O and δD) support the results and underline the impact of evaporation processes on the groundwater and infiltration of evaporated water.
Chemical-Free Biologically Enhanced Primary Treatment of Raw Wastewater for Improved Capture Carbon
Authors: Azhar Muhammad Rizwan , Nolan Paul , Cadee Keith , Khiadani Mehdi
Published: November 2022

Conventional wastewater treatment processes require extensive energy inputs for their operations. Biologically enhanced primary treatment (BEPT) is a promising technology to capture incoming organics that may be utilized to produce biogas and potentially hydrogen with further downstream processing. This study involved a biologically enhanced primary treatment (BEPT) of raw wastewater at bench and pilot-scale using activated sludge (AS) addition and dissolved air flotation (DAF) using raw wastewater at a municipal wastewater facility in Western Australia with average chemical oxygen demand of ~800 mg/L. The results of pilot-scale testing showed an improved removal performance for total chemical oxygen demand (COD-T), soluble chemical oxygen demand (COD-S), and total suspended solids (TSS) compared to conventional primary treatment (PT). Specifically, average COD-T, COD-S and TSS removals for BEPT were 33.3%, 13.5% and 45%, respectively which was 10%, 100% and 6% higher than PT. Moreover, the sludge produced from BEPT had a high solids content of 4.8 g/L, which might not need further thickening prior to anaerobic digestion. It is important to note that no chemicals were used during BEPT testing, which makes the process very cost-effective.
Les fluctuations économiques de la Guyane au cours du XVIIIe siècle. Un réseau implanté dans le territoire commercial américain
Authors: Losier Catherine
Published: November 2022

En 1971, l’historien Ciro Flammarion Cardoso soulignait avec justesse la faiblesse de l’économie guyanaise. Depuis, son analyse a été citée à maintes reprises dans l’historiographie sans que les données économiques soient réévaluées dans l’objectif de mieux comprendre les causes de cette faiblesse, de même que les fluctuations du réseau commercial associé à la Guyane. La mise en commun des données archéologiques et historiques permet de dresser le portrait du réseau commercial associé à la Guyane au cours du XVIIIe siècle et de suivre ses fluctuations en conjonction avec les différents évènements qui ont ponctué l’histoire de la Guyane au cours de cette période, notamment l’expédition de Kourou. Elles autorisent la mise en perspective du protectionnisme économique de la France face à la colonie et de mesurer l’apport du commerce international, intercolonial et des échanges illicites quant à l’approvisionnement de la Guyane au cours de l’Ancien Régime.
Le réseau dans le réseau. La phalange coloniale ou la collecte de l’information du « parti colonial »
Authors: d'Andurain Julie
Published: November 2022

Analysed formerly in his parliamentary section by Charles Robert Ageron, the colonial lobby is still largely unknown. A cross-analysis of private archives of colonial officers allows us to bring out a military structure, the colonial phalanx. One of its functions was to collect information for the "parti colonial" in order to expand its ability to act on colonial matters.
La construction de l’espace juridique colonial : l’exemple des conflits de maritalité à Pondichéry au tournant du XIXe siècle
Authors: Marquet Julie
Published: November 2022

In Pondicherry at the turn of the nineteenth century, colonial law was a dual law : the procedures and penalties were different for Indian and European subjects. Among conflicts between Indians, the colonial admi nistration picked out those relating to "usages and customs" and delegated their handling to intermediary assemblies. Through these processes of delegation, the different participants in conflict-resolution took part in the construction of a colonial legal space. The study of marital disputes sheds light on this co-construction, as well as the ways in which actors defined a space of opportunities for women.
Matérialisation de l’Atlantique français. Carrières et trajectoires des administrateurs coloniaux (France ¢ Saint-Domingue, XVIIIe siècle)
Authors: Navarro-Andraud Zélie
Published: November 2022

Until now the concept of Atlantic history has been developed and portrayed mainly by Anglo Saxon and Spanish historians as an English and Iberian Atlantic. But, nevertheless the existence of a French Atlantic can not be ruled out. This natural space, driven by the age of discovery, became a socio-economic area as a result of human activity and is thus in perpetual construction. Therefore those involved in this pattern and the paths they have built confirm the Atlantic reality. The colonial administrators are seen as the key protagonists, being both participants and privileged witnesses of the Atlantic scene. Entry into the colony proves to be an important step for careers. The choice, or not choice, of employment placements and the socio-professional outcomes modify the paths, as of the use of the actors make of the area therefore highlighting the reality of a French Atlantic.
Faktor Internal dan Eksternal terhadap Harga Saham dengan Earning Per Share sebagai Variabel Intervening
Authors: Tarmizi M. , Hady Hamdy , Lusiana
Published: November 2022

Penelitian ini bertujuan untuk mengetahui Pengaruh Return on Asset (ROA), Price Book Value (PBV), Nilai Tukar (Kurs) dan Inflasi terhadap pergerakan harga saham dengan Earning per Share (EPS) sebagai variabel intervening pada saham indeks LQ45 yang terdaftar di bursa efek indonesia 2017-2021. Sampel pada penelitian ini diambil dengan metode sampel jenuh (sensus) pada saham indeks LQ45 yang terdaftar di bursa efek indonesia 2017-2021. Jumlah sampel yang digunakan sebanyak 40 perusahaan. Metode analisis dari penelitian ini adalah menggunakan metode analisis regresi linier berganda. Hasil penelitian ini menunjukkan bahwa secara parsial Return On Asset (ROA) berpengaruh signifikan terhadap Earning per Share (EPS), Price Book Value (PBV) berpengaruh signifikan terhadap Earning per Share (EPS), Kurs berpengaruh signifikan terhadap Earning per Share (EPS), Inflasi berpengaruh signifikan terhadap Earning per Share (EPS), Return On Asset (ROA) berpengaruh signifikan terhadap terhadap Harga Saham, Price Book Value (PBV) berpengaruh signifikan terhadap terhadap Harga Saham, Kurs berpengaruh signifikan terhadap Terhadap Harga Saham, Inflasi berpengaruh signifikan terhadap terhadap Harga Saham, Earning per Share (EPS) berpengaruh signifikan terhadap Harga Saham, Return On Asset (ROA) tidak signifikan terhadap harga saham melalui Earning per Share (EPS) sebagai variabel intervening, Price Book Value (PBV) berpengaruh signifikan terhadap harga saham melalui Earning per Share (EPS) sebagai variabel intervening, Kurs berpengaruh signifikan terhadap harga saham melalui Earning per Share (EPS) sebagai variabel intervening dan Inflasi tidak signifikan terhadap harga saham melalui Earning per Share (EPS) terhadap harga saham melalui Earning per Share (EPS) sebagai variabel intervening pada saham indeks LQ45 yang terdaftar di bursa efek indonesia 2017-2021.
Trabajo remoto y satisfacción laboral de los docentes universitarios peruanos durante la pandemia del COVID-19
Authors: López Lourdes , López-Paz Peregrino , López Milton
Published: November 2022

En el Perú, durante la pandemia del COVID-19, se elaboró una normativa especial que permitió la continuidad de la educación superior mediante la enseñanza virtual. En ese contexto, se establecieron los lineamientos del trabajo remoto, cuya aplicación incluyó a los trabajadores públicos y privados. Además, los docentes universitarios han sido un factor importante para asegurar la continuidad de las actividades académicas e influir en el desempeño de las universidades. El objetivo del artículo fue analizar las fuentes documentales sobre la relación entre el trabajo remoto y la satisfacción laboral de los docentes universitarios peruanos antes y durante la pandemia del COVID-19. La metodología utilizada fue la investigación documental. Los resultados muestran que el trabajo remoto no fue una nueva modalidad de empleo y que en el Perú se estableció e implementó sin el marco legal y el soporte tecnológico necesarios. Además, las diferentes modalidades de enseñanza pueden influir en la satisfacción laboral de los docentes universitarios. Finalmente, el trabajo remoto y la pandemia han influido en la satisfacción laboral de los trabajadores, incluyendo a los docentes universitarios. Se concluye que los estudios sobre el trabajo remoto y la satisfacción laboral de los docentes universitarios muestran que existe una relación entre ambas variables; es decir, el trabajo remoto puede influir en el nivel de satisfacción laboral de los docentes universitarios peruanos.
From Scratch to Python : Lego Robots as Motivational Tools for Coding
Authors: Körei Attila , Szilágyi Szilvia
Published: November 2022

Educational Robotics is a specific interdisciplinary field that improves learning experience and develops student skills and competences through robotic-based activities. Constructing of robot models provide hands-on experiences for children while programming the built model teach basic coding knowledge for them. Instead of use text-based programming languages coding can be learned by a Scratch-based language in an age-appropriate way. Educational robots are excellent tools of introducing and teaching programming at all levels of education, though most of them aim at pupils in primary and secondary schools. LEGO Education's products also stand out among the educational robots thanks to their high quality and the very wide range of projects and teaching materials. The recently released Lego robot, SPIKE Prime, can also be programmed in Python, providing a playful way to learn the basics of object-oriented programming even in higher education.
Casassola GM, Schmidt CJ, Affeldt G, Morais DS, Alvarenga LKB, Miller C, Ziegler B Functional status of hospitalized pediatric patients with COVID-19 in southern Brazil: a prospective cohort study
Authors: Morin Casassola1 Giovana , Jacoby Schmidt1 Caroline , Hoff Affeldt2 Guilherme , Sana Morais1 Debora , Krás Borges Alvarenga1 Letícia , Miller1 Cristina , Ziegler1 Bruna
Published: November 2022

Objective: The present study aimed to assess the functional status of children diagnosed with COVID-19 at the time of hospitalization and the associations with clinical features. Methods: This prospective cohort study was carried out with children diagnosed with COVID-19 admitted to a tertiary hospital. The patients' functioning was assessed using the pediatric Functional Status Scale (FSS). Results: A total of 62 children with a median age of 3 years old were included in the study, and 70% had some comorbidity prior to the diagnosis of COVID-19. The median length of stay was nine days, during which period five patients died. The FSS assessment of the sample showed that approximately 55% had some functional alteration. The group of patients with the highest FSS scores presented a lengthier hospital stay (p = 0.016), required more oxygen therapy (p < 0.001), mechanical ventilation (p = 0.001), and intensive care unit admissions (p = 0.019), and had more cardiac (p = 0.007), neurological (p = 0.003), and respiratory (p = 0.013) comorbidities. In the multivariate analysis, there was an association between the dependent variable length of stay and the total FSS score (b = 0.349, p = 0.004) and the presence of comorbidities (b = 0.357, p = 0.004). Conclusions: We observed that more than half of the children hospitalized due to COVID-19 had some level of functional change. Greater alterations in functional status were associated with the presence of previous comorbidities, a greater need for ventilatory support, and longer hospital stays.
Prediction of Customer Churn in Telecom Industry: A Machine Learning Perspective
Authors: Hota Lopamudra , Dash Prasant Kumar
Published: November 2022

The business world is becoming increasingly saturated in today's competitive environment. There is a great deal of competition in the telecommunications industry, especially due to various vibrant service providers. As a result, they have had difficulty retaining their existing customers. As attracting new customers is much more costly than retaining current ones, now is the time to ensure the telecom industry maintains value by retaining customers over acquiring new ones. Numerous machine learning and data mining methods have been proposed in the literature to predict customer churners using heterogeneous customer records over the past decade. This research gives a brief idea on the Customer Churn problem, and explores how various machine learning techniques can be used to predict customer churn via models such as XGBoost, GradientBoost, AdaBoost, ANN, Logistic Regression and Random Forest, and also compare the effectiveness of the models in term of accuracy. Keyword : Machine Learning, Customer Churn, Prediction Model, Random Forest, XGBoost, AdaBoost, GBoost