bluuebunny/crossref_metadata_2025 huggingface dataset:
Improvement of As(V) Adsorption by Reduction of Granular to Micro-Sized Ferric Hydroxide
Authors: Martí Vicenç , Jubany Irene , Fernández-Rojo Lidia , Ribas David , Benito José Antonio , Diéguez Brian , Ginesta Ada
Published: May 2022

The remediation of groundwater containing arsenic is a problem that has been addressed using adsorption processes with granulated materials in columns, but the remediation itself could be improved by using micro-sized adsorbents in stirred systems. In this study, arsenate (As(V)) batch adsorption experiments were performed using granular ferric hydroxide (GFH) and two derived micro-sized materials. Reduced-size adsorbents were produced by energetic ball milling, giving final sizes of 0.1–2 µm (OF-M samples) and ultra-sonication, producing final sizes of 2–50 µm (OF-U samples). Equilibrium isotherm studies showed that the Langmuir model was a good fit for the three sorbents, with the highest maximum adsorption capacity (qmax) for OF-U and the lowest for OF-M. The adsorption of the two groundwater samples occurred according to the obtained equilibrium isotherms and indicated the absence of interfering agents for the three adsorbents. Batch kinetics tests in stirred beakers followed a pseudo second-order model and indicated that the kinetics of the OF-U sorbent was faster than the kinetics of the GFH sorbent. The tests also showed an increase in the qe values for the reduced-size sorbent. The application of ultrasonication to the GFH produced an increase of 23 % in the qmax and b term and an increase of 34-fold for the kinetic constant (k2) in the stirred batch systems tested. These results suggest that this new approach, based on ultra-sonication, has the potential for improving the adsorption of arsenic in groundwater.
Machine Learning Methods to Identify Predictors of Psychological Distress
Authors: Chen Yang , Zhang Xiaomei , Lu Lin , Wang Yinzhi , Liu Jiajia , Qin Lei , Ye Linglong , Zhu Jianping , Shia Ben-Chang , Chen Ming-Chih
Published: May 2022

As people pay ever-increasing attention to the problems caused by psychological stress, research on its influencing factors becomes crucial. This study analyzed the Health Information National Trends Survey (HINTS, Cycle 3 and Cycle 4) data (N = 5484) and assessed the outcomes using descriptive statistics, Chi-squared tests, and t-tests. Four machine learning algorithms were applied for modeling: logistic regression (linear), random forests (RF) (ensemble), the artificial neural network (ANN) (nonlinear), and gradient boosting (GB) (ensemble). The samples were randomly assigned to a 50% training set and a 50% validation set. Twenty-six preselected variables from the databases were used in the study as predictors, and the four models identified twenty predictors of psychological distress. The essence of this paper is a binary classification problem of judging whether an individual has psychological distress based on many different factors. Therefore, accuracy, precision, recall, F1-score, and AUC were used to evaluate the model performance. The logistic regression model selected predictors by forward selection, backward selection, and stepwise regression; variable importance values were used to identify predictors in the other three machine learning methods. Of the four machine learning models, the ANN exhibited the best predictive effect (AUC = 73.90%). A range of predictors of psychological distress was identified by combining the four machine learning models, which would help improve the performance of the existing mental health screening tools.
Possibility to Open Up New Areas by COVID-19 Infection
Authors: Hattori Toshio , Ashino Yugo
Published: May 2022

The rapid increase of COVID-19 cases has brought the number of patients to 513 million [...]
Development and Evaluation of a Real-Time Hourly One-Kilometre Gridded Multisource Fusion Air Temperature Dataset in China Based on Remote Sensing DEM
Authors: Han Shuai , Shi Chunxiang , Sun Shuai , Gu Junxia , Xu Bin , Liao Zhihong , Zhang Yu , Xu Yanqin
Published: May 2022

High-resolution gridded 2 m air temperature datasets are important input data for global and regional climate change studies, agrohydrologic model simulations and numerical weather predictions, etc. In this study, the digital elevation model (DEM) is used to correct temperature forecasts produced by ECMWF. The multi-grid variation formulation method is then used to fuse the data from corrected temperature forecasts and ground automatic station observations. The fused dataset covers the area over (0–60°N, 70–140°S), where different underlying surfaces exist, such as plains, basins, plateaus, and mountains. The spatial and temporal resolutions are 1 km and 1 h, respectively. The comparison of the fusion data with the verification observations, including 2400 weather stations, indicates that the accuracy of the gridded temperature is superior to European Centre for Medium-Range Weather Forecasts (ECMWF) data. This is because a more significant number of stations and high-resolution terrain data are used to generate the fusion data than are utilized in the ECMWF. The obtained dataset can describe the temperature feature of peaks and valleys more precisely. Due to its continuous temporal coverage and consistent quality, the fusion dataset is one of China’s most widely used temperature datasets. However, data uncertainty will increase for areas with sparse observations and high mountains, and we must be cautious when using data from these areas.
Pair-Wise Similarity Knowledge Distillation for RSI Scene Classification
Authors: Zhao Haoran , Sun Xin , Gao Feng , Dong Junyu
Published: May 2022

Remote sensing image (RSI) scene classification aims to identify the semantic categories of remote sensing images based on their contents. Owing to the strong learning capability of deep convolutional neural networks (CNNs), RSI scene classification methods based on CNNs have drawn much attention and achieved remarkable performance. However, such outstanding deep neural networks are usually computationally expensive and time-consuming, making them impossible to apply on resource-constrained edge devices, such as the embedded systems used on drones. To tackle this problem, we introduce a novel pair-wise similarity knowledge distillation method, which could reduce the model complexity while maintaining satisfactory accuracy, to obtain a compact and efficient deep neural network for RSI scene classification. Different from the existing knowledge distillation methods, we design a novel distillation loss to transfer the valuable discriminative information, which could reduce the within-class variations and restrain the between-class similarity, from the cumbersome model to the compact model. This method could obtain the compact student model with higher performance compared with existing knowledge distillation methods in RSI scene classification. To be specific, we distill the probability outputs between sample pairs with the same label and match the probability outputs between the teacher and student models. Experiments on three public benchmark datasets for RSI scene classification, i.e., AID, UCMerced, and NWPU-RESISC datasets, verify that the proposed method could effectively distill the knowledge and result in a higher performance.
Locating an Underwater Target Using Angle-Only Measurements of Heterogeneous Sonobuoys Sensors with Low Accuracy
Authors: Kim Jonghoek
Published: May 2022

This paper considers locating an underwater target, where many sonobuoys are positioned to measure the bearing of the target’s sound. A sonobuoy has very low bearing accuracy, such as 10 degrees. In practice, we can use multiple heterogeneous sonobuoys, such that the variance of a sensor noise may be different from that of another sensor. In addition, the maximum sensing range of a sensor may be different from that of another sensor. The true target must exist within the sensing range of a sensor if the sensor detects the bearing of the target. In order to estimate the target position based on bearings-only measurements with low accuracy, this paper introduces a novel target localization approach based on multiple Virtual Measurement Sets (VMS). Here, each VMS is derived considering the bearing measurement noise of each sonar sensor. As far as we know, this paper is novel in locating a target’s 2D position based on heterogeneous sonobuoy sensors with low accuracy, considering the maximum sensing range of a sensor. The superiority (considering both time efficiency and location accuracy) of the proposed localization is verified by comparing it with other state-of-the-art localization methods using computer simulations.
Real-Time Monitoring Method for Radioactive Substances Using Monolithic Active Pixel Sensors (MAPS)
Authors: Han Yongchao , Xu Shoulong , Huang Youjun
Published: May 2022

This study presents a real-time monitoring technique for radioactive substances that meets safety management needs. We studied the accumulation characteristics of radiation response signals of monolithic active pixel sensors (MAPSs) based on their response and discrimination ability to gamma (γ) photon or neutron radiation. The radiation status of the radioactive substances was determined by monitoring the accumulation data of radiation responses. As per the results, Am-Be and 252Cf radiation response signals are primarily concentrated in the range of 0–70 pixels. Response signals of 60Co and 137Cs γ-ray were concentrated in two regions; there was a peak in the region with a pixel value of less than 50, and a plateau in the region with a pixel value of more than 75. Therefore, the results are able to discriminate between spectra. Furthermore, we designed a radioactivity monitoring system that is able to examine multiple radioactive materials. Its working principle is that a change in the accumulation of radioactivity monitoring data indicates a radiation change during the last accumulation cycle. This study provides vital technical support for the long-term supervision of radioactive substances.
A Predictive Approach for Disassembly Line Balancing Problems
Authors: Paprocka Iwona , Skołud Bożena
Published: May 2022

In selective serial disassembly sequence planning, when the target node (component) is reached, the selective disassembly task is completed and the refurbished component is repaired, reused or remanufactured. Since the efficient utilization of existing resources is necessary, it is crucial to predict disassembly operation times and the condition of joints for recycling, reusing or remanufacturing. The method of estimating the disassembly times of a joint if it is intended for remanufacturing, recycling and reuse is an important and urgent requirement for research development and results. The aim of the paper is to investigate the disassembly system with predicted operation times and the quality of product connections (joints) in order to balance the line smoothness index, to minimize a line time factor, line efficiency and profit and minimize an ex post error. Disassembly times for remanufacturing, recycling and reuse are estimated separately based on the historical data of disassembly times and the quality of joints. The presented estimation method of disassembly operation times increases the reliability and efficiency of elaborated balances of tasks in lines. Underestimated disassembly operation times can be compensated for during the idle points in the successive cycles, provided that the transport operations are performed manually and that travel time determines the cycle time.
Evaluation of Radio Communication Links of 4G Systems
Authors: Ayad Mouloud , Alkanhel Reem , Saoudi Kamel , Benziane Mourad , Medjedoub Smail , Ghoneim Sherif S. M.
Published: May 2022

Radio communication systems are very widely present in our current smart lifestyles. It consists of two ends, which can carry the transmitter’s information to the receptor. Before installing any radio communication system, it is necessary to analyze the link resources. Hence, this analysis allows the determination of the received radio communication strength to prove if it is sufficient for the link to work correctly and assure a high quality of service. For this reason, new services and technologies are integrated. The objective of the present work is to improve the performance of the radio communication link of 4G systems. The study is based on real measurements using the drive test. The data collected by the drive test are analyzed to increase the performance of the radio communication. Based on this data analysis, recommendations and suggestions are issued for improving the radio communication link. The obtained results indicate a significant amelioration in the performance of the radio communication link.
Low-Dimensional Palladium on Graphite-on-Paper Substrate for Hydrogen Sensing
Authors: Wang Boyi , Hashishin Takeshi , Dao Dzung Viet , Zhu Yong
Published: May 2022

To stabilize the detection signal of palladium-based hydrogen sensors on paper substrates, a graphite intermediate layer was painted on the surface of paper. The graphite-on-paper (GOP) substrate offers advantages such as good thermo-electrical conductivity, low cost, and uncomplicated preparation technology. Quasi-1-dimensional palladium (Pd) thin films with 8 nm and 60 nm thicknesses were deposited on the GOP substrates using the vacuum evaporation technique. Thanks to the unique properties of the GOP substrate, a continuous Pd microfiber network structure appeared after deposition of the ultra-thin Pd film. Additionally, the sensing performance of the palladium-based hydrogen sensor was not affected, whether using GOP or paper substrate at 25 °C. Surprisingly, heating-induced loss of sensitivity was restrained due to the increased electrical conductivity of the GOP substrate at 50 °C.
Land Cover and Land Use Changes between 1986 and 2018, and Preliminary Carbon Footprint Implications for Manoka Island (Littoral Region of Cameroon)
Authors: Tatuebu Tagne Claude , Sonwa Denis Jean , Awono Abdon , Mama Moustapha Njayou , Fongnzossie Evariste , Ngala Mbiybe Riddley , Essamba à Rim Lydie Flora , Ntja Rufin Dominique
Published: May 2022

Land and resource use patterns in coastal areas play a key role in the resilience of ecosystems and populations to climate change. Knowing their spatiotemporal dynamics therefore constitutes a strategic tool to help decision-makers. Based on documentary research, geographic information system (GIS), image processing, and field work, this article maps land use on Manoka Island between 1986 and 2018 and identifies the drivers of change and avenues for intervention with a view to strengthening climate change mitigation. The results show a decrease of 4% in forest area on Manoka Island, representing an average of 112 ha of inland forest and 267 ha of mangrove converted between 1986 and 2018. This increases the degraded forest area by 268% (degraded mangrove and degraded inland forest) and exposes some camps to erosion and flooding. Reduction in forest area is mainly linked to the harvesting of fuelwood and the conversion of forests into farmland and residential areas. Settlements have increased in area from 15 ha in 1986 to 90.4 ha in 2018 to the detriment of natural spaces.
A New Decision Support System for Analyzing Factors of Tornado Related Deaths in Bangladesh
Authors: Sufi Fahim , Alam Edris , Alsulami Musleh
Published: May 2022

Tropical cyclones devastate large areas, take numerous lives and damage extensive property in Bangladesh. Research on landfalling tropical cyclones affecting Bangladesh has primarily focused on events occurring since AD1960 with limited work examining earlier historical records. We rectify this gap by developing a new Tornado catalogue that include present and past records of Tornados across Bangladesh maximizing use of available sources. Within this new Tornado database, 119 records were captured starting from 1838 till 2020 causing 8735 deaths and 97,868 injuries leaving more than 102,776 people affected in total. Moreover, using this new Tornado data, we developed an end-to-end system that allows a user to explore and analyze the full range of Tornado data on multiple scenarios. The user of this new system can select a date range or search a particular location, and then, all the Tornado information along with Artificial Intelligence (AI) based insights within that selected scope would be dynamically presented in a range of devices including iOS, Android, and Windows. Using a set of interactive maps, charts, graphs, and visualizations the user would have a comprehensive understanding of the historical records of Tornados, Cyclones and associated landfalls with detailed data distributions and statistics.
The Sustainability of Rock Art: Preservation and Research
Authors: Zerboni Andrea , Villa Federica , Wu Ying-Li , Solomon Tadele , Trentini Andrea , Rizzi Alessandro , Cappitelli Francesca , Gallinaro Marina
Published: May 2022

Rock art is a widespread cultural heritage, representing an immovable element of the material culture created on natural rocky supports. Paintings and petroglyphs can be found within caves and rock shelters or in open-air contexts and for that reason they are not isolated from the processes acting at the Earth surface. Consequently, rock art represents a sort of ecosystem because it is part of the complex and multidirectional interplay between the host rock, pigments, environmental parameters, and microbial communities. Such complexity results in several processes affecting rock art; some of them contribute to its destruction, others to its preservation. To understand the effects of such processes an interdisciplinary scientific approach is needed. In this contribution, we discuss the many processes acting at the rock interface—where rock art is present—and the multifaceted possibilities of scientific investigations—non-invasive or invasive—offered by the STEM disciplines. Finally, we suggest a sustainable approach to investigating rock art allowing to understand its production as well as its preservation and eventually suggest strategies to mitigate the risks threatening its stability.
Review of Intelligent Road Defects Detection Technology
Authors: Zhou Yong , Guo Xinming , Hou Fujin , Wu Jianqing
Published: May 2022

Road defects are important factors affecting traffic safety. In order to improve the identification efficiency of road diseases and the pertinence of maintenance and management, intelligent detection technologies of road diseases have been developed. The problems of high cost and low efficiency of artificial inspection of road diseases are solved efficiently, and the quality of road construction is improved availably. This is not only the guarantee of highway quality but also the guarantee of people’s lives and safety. This study focuses on the intelligent detection of road disease and summarizes the commonly used detection equipment in the intelligent detection technology of road diseases, which include cameras, GPR, LiDAR, and IMU. It systematically describes the evolution and development of road disease detection technology. This study analyzes the common problems existing in road disease detection technology and proposes corresponding improvement suggestions. Finally, the development trend of road detection technology is discussed, which has practical significance for the future development of road detection technology.
Comprehensive Geophysical Measurement in Seismic Safety Evaluation: A Case Study of East Lake High-Tech Development Zone, China
Authors: Wang Wei , Jin Cong , Luo Denggui , Cai Yongjian , Lin Song
Published: May 2022

Wuhan East Lake High-tech Development Zone is a National Innovation Demonstration Zone where several major projects are under construction. For the seismic safety evaluation of the zone, it is urgent to find out basic data such as stratigraphic structure, geometric characteristics of buried faults, and overburden thickness. In this study, seismic reflection and microtremor surveys are adopted in seismic safety evaluation in urban areas for the first time. Combined with borehole data, the overburden thickness and buried faults in the target area are detected and analyzed. The results are as follows: ① The seismic reflection detection is carried out for the possible hidden locations of the Xiangfan-Guangji Fault and Macheng-Tuanfeng Fault in the target area, and the obtained high-resolution seismic reflection profiles can be used to precisely divide the stratigraphic structure and preliminarily find out the geometric characteristics such as the strike, tendency, and the buried depth of the upper breakpoint of the buried faults. ② A microtremor survey is carried out in key regions of the target area, and the obtained velocity structure imaging can provide a perspective window into the urban underground space structure and accurately determine overburden thickness and the depth of strongly and moderately weathered bedrock. Comprehensive geophysical measurements can better realize the acquisition of basic data such as the stratigraphic structure of complex regions and characteristics of urban buried faults, which provides an important basis for seismic fortification. At the same time, the combined application of geophysical methods avoids the detection of the blind area and provides a guarantee for urban safety and sustainable development. Furthermore, the study has reference value for seismic safety evaluation in similar areas of the world. If comprehensive geophysical measurement can be popularized, its economic and scientific value will be immeasurable.
Relationship between Entrepreneurial Orientation and Business Performance among Malay-Owned SMEs in Malaysia: A PLS Analysis
Authors: Alam Syed , Md Salleh Mohd , Masukujjaman Mohammad , Al-Shaikh Mohammed , Makmor Nurkhalida , Makhbul Zafir
Published: May 2022

Entrepreneurship has become a key part of economies, and having an entrepreneurial orientation for SMEs is essential for success. EO and dimensions may differ in different cultures and different countries, thus a cross-cultural validation is suggested by the existing literature, which is lacking Malaysian perspectives. The objective of this study is to examine the relationships between entrepreneurial orientation (EO) and business performances of Malay-based SMEs in Malaysia and used the Partial Least Square (PLS) approach for data analysis. The research model for this study was drawn from the literature on entrepreneurship. This study identified five entrepreneurial orientations and tested hypotheses on which EO has a significant influence on business performance with empirical data from a sample of 407 Malay-based SMEs in Malaysia. The PLS regression analysis shows that risk-taking, proactiveness, innovativeness, and achievement factors are the significant elements of entrepreneurship orientation. Nevertheless, one independent variable, i.e., autonomy does not exhibit any relationship. This study offers a significant contribution to the current literature by empirically analyzing the link between the subcomponent of EO and business performance, specifically in the Malaysian SME sector, which has not been explored comprehensively. The paper’s interesting findings can serve to remind entrepreneurs that they cannot neglect the element of EO in their activities, particularly the success of the business. The research could be useful for policymakers to obtain some ideas and develop policies to help SMEs in Malaysia. Specifically, to enhance the performance in the SMEs sectors, the government should enforce easy to use, consistent, and standardized policies in all SMEs sectors and for all other stakeholders in boosting these sectors.
The Effect of Cash Incentive Projects on the Social Value Performances of Social Enterprises: An Empirical Analysis of SK’s Social Progress Credit in Korea
Authors: Yi Joon-Bum , Chun Se-Hak
Published: May 2022

Social enterprises seek to maximize benefits to society and the environment while obtaining profits. Social enterprises are increasing in number; however, their size and growth rates are very small. In addition, many social enterprises face difficulties in obtaining profits through social activities that generate social value, even though they are supported by government policy. Previous research has focused on the relationship between social performance and financial performance, compensation, and policy making, as well as the effect of incentives on social performance within organizations. To our knowledge, there is lack of empirical research on cash incentives for activities that generate social value. This paper analyzes the behavior of companies with regard to fostering a social enterprise ecosystem and a cash incentive system for social enterprises. In particular, we investigate the relationship between SK’s cash incentive system, which is called social progress credit (SPC), and the activities of social enterprises, and we examine which social value activities are affected by a cash incentive system. Furthermore, through empirical analysis, this paper analyzes how the amount of cash for incentives is determined by specific social activities, such as social service performance, employment performance, environmental performance, and social ecosystem performance, as well as by the size of the social enterprise and its financial performance (i.e., revenue and net profit). The results show that employment performance is the most important factor for incentive payments, reflecting the social atmosphere and government policy in Korea, and that it can be a simpler measurement of performance than other social performance measures. Moreover, the results show that there is a significant positive (+) relationship between incentive payments and financial performance, such as sales and net profit of social enterprises. In addition, it was found that more incentives were paid to small social enterprises with higher sales growth.
The Effects of Teachers’ Error Orientations on Students’ Mathematics Learning: The Role of Teacher Emotions
Authors: Zhao Qian , Han Jiwei , Lin Wenkai , Zhang Siyu , Li Yiran
Published: May 2022

Several attempts have been made to explore the factors influencing teacher emotions, most of which focus on external factors such as student behaviors and classroom teaching. However, research on the links between internal factors and teacher emotions is scant. Based on the control value theory, this article explored the influence of junior secondary mathematics teachers’ error orientations on their emotions, and how teachers’ error orientations and emotions were related to students’ mathematics learning strategies. A sample of 70 junior high school mathematics teachers and their students (N = 2453) in mainland China participated in this study. Confirmatory factor analysis and multilevel structural equation modeling were used to analyze the data. The results showed that teachers’ positive error orientation increased their positive emotions and reduced their negative emotions, whereas teachers’ negative error orientation increased their negative emotions and reduced their positive emotions. Regarding the effects of teacher emotions, teachers’ positive emotions increased students’ positive mathematics achievement emotions and reduced their negative emotions. Meanwhile, students’ negative mathematics achievement emotions significantly reduced their adoption of desirable mathematics learning strategies. The findings highlight the importance of teachers’ positive error orientation and positive emotion for students’ mathematics learning.
Ecolabels as a Tool of Sustainable Development in Tourist Destinations
Authors: Bučar Kristina , Hendija Zvjezdana , Katić Ines
Published: May 2022

The research aimed to explore whether ecolabels could be used as innovation tools to achieve sustainable tourism development (STD) at the level of a tourist destination. The paper used results obtained by a questionnaire survey among destination management organizations (DMOs) in cities and municipalities to investigate how much ecolabels are used at the level of tourist destinations in a case study of the Republic of Croatia (in 2017 and 2021). DMOs were chosen as the subject of research due to their crucial role in the development of tourist destinations. The findings from the linear research indicate that DMOs in Croatia still do not recognize the importance and role of implementation of tourist ecolabels as an innovation tool in achieving sustainable tourism development at the destination level. The paper provides new theoretical insights into the application of ecolabels at the level of cities and municipalities as tourist destinations. Thus, it could induce future research by scholars in this field because an analysis of academic literature indicates that there is a lack of such research. Moreover, the results given by this research could provide a basis for DMOs to start to think in a different way about the application of ecolabels at the level of a tourist destination.
Impact of Policy Instruments in the Implementation of Renewable Sources of Energy in Selected European Countries
Authors: Nasiri Elnaz , Rocha-Meneses Lisandra , Inayat Abrar , Kikas Timo
Published: May 2022

Nowadays, great attention has been paid to alternative sources of energy that can be used as a replacement for fossil fuels and help to reduce their utilization in the overall energy mix. In Europe, the development and implementation of renewable sources of energy is regulated and supported by legal frameworks. This paper investigates the impact of European Directives and its transposition to national policies on the share of renewable sources of energy in electricity, heating and cooling, and transport in Denmark, Ireland, the Netherlands, Estonia, Latvia, and Lithuania. For this, quantitative and qualitative data were utilized. The quantitative data refer to the gross energy consumption, energy consumption for heating and cooling purposes (by category), and energy consumption in the transportation sector, while the qualitative data refer to the main directives and legal frameworks utilized to regulate the utilization and implementation of renewable energy in the selected countries. The results of this study show that the European Directives are not as effective as expected in the promotion and adoption of renewable sources of energy. Although none of the countries investigated in this paper were able to achieve the 10% share of energy produced from renewable sources for the transportation sector, certain goals were still achieved. For instance, in 2018, 6.57% of the energy utilized in the transportation sector in Denmark was from renewable sources, while in Estonia it was 3.29%, in Ireland 7.17%, in Latvia 4.73%, in Lithuania 4.33%, and in the Netherlands 9.59%. These results suggest that the current regulations should be revised and that clear, accountable, and predictable regulations should be put in place to ensure the energetic independence in Europe.
Towards Sustainable Road Safety in Saudi Arabia: Exploring Traffic Accident Causes Associated with Driving Behavior Using a Bayesian Belief Network
Authors: Rahman Muhammad Muhitur , Islam Md Kamrul , Al-Shayeb Ammar , Arifuzzaman Md
Published: May 2022

Understanding the causes and effects of road accidents is critical for developing road and action plans in a country. The causation hypothesis elucidates how accidents occur and may be applied to accident analysis to more precisely anticipate, prevent, and manage road safety programs. Driving behavior is a critical factor to consider when determining the causes of traffic accidents. Inappropriate driving behaviors are a set of acts taken on the roadway that can result in aberrant conditions that may result in road accidents. In this study, using Al-Ahsa city in Saudi Arabia’s Eastern Province as a case study, a Bayesian belief network (BBN) model was established by incorporating an expectation–maximization algorithm. The model examines the relationships between indicator variables with a special focus on driving behavior to measure the uncertainty associated with accident outcomes. The BBN was devised to analyze intentional and unintentional driving behaviors that cause different types of accidents and accident severities. The results showed when considering speeding alone, there is a 26% likelihood that collision will occur; this is a 63% increase over the initial estimate. When brake failure was considered in addition to speeding, the likelihood of a collision jumps from 26% to 33%, more than doubling the chance of a collision when compared to the initial value. These findings demonstrated that the BBN model was capable of efficiently investigating the complex linkages between driver behavior and the accident causes that are inherent in road accidents.
How Nudging Inspires Sustainable Behavior among Event Attendees: A Qualitative Analysis of Selected Music Festivals
Authors: Bär Sören , Korrmann Laura , Kurscheidt Markus
Published: May 2022

This research answers the question of which nudges can be created to subtly influence event attendees in such a way that they contribute to the implementation of a green event. Using the qualitative content analysis according to Mayring, three music festivals were analyzed in detail with regard to their measures for ecological sustainability. All available online resources—in particular, the websites of the music festivals, blog entries, online newspaper articles and, also, observations during several personal visits—were used as sources of the qualitative data. A key result was the development of a model for nudges that can generally be used and implemented for events. The goals, the nudges developed and the possible measures with regard to ecological sustainability are defined in the areas of transport, garbage, electricity, gastronomy, sanitation and compensation of emissions. The more music festival participants already behave in an ecologically sustainable manner, the more others will join them. This can be exploited by using social nudges that consciously inspire group social dynamics. In order to be able to use nudging sensibly, organizers have to internalize that they act as decision-makers, which entails a great ethical and moral responsibility. Even inconspicuous nudges can be very effective.
Opportunities from Unmanned Aerial Vehicles to Identify Differences in Weed Spatial Distribution between Conventional and Conservation Agriculture
Authors: Nikolić Nebojša , Mattivi Pietro , Pappalardo Salvatore Eugenio , Miele Cristiano , De Marchi Massimo , Masin Roberta
Published: May 2022

Weeds are one of the major issues in agricultural production and they are present in most agricultural systems. Due to the heterogeneity of weed distribution, understanding spatial patterns is paramount for precision farming and improving sustainability in crop management. Nevertheless, limited information is currently available about the differences between conventional agricultural (CV) weed spatial patterns and weed spatial patterns in conservation agricultural systems (CA); moreover, opportunities to use unmanned aerial vehicles (UAV) and recognition algorithms to monitor these differences are still being explored and tested. In this work, the opportunity to use UAVs to detect changes in spatial distribution over time between CA and CV fields was assessed for data acquisition. Acquired data were processed using maximum likelihood classification to discriminate between weeds and surrounding elements; then, a similarity assessment was performed using the ‘equal to’ function of the raster calculator. The results show important differences in spatial distribution over time between CA and CV fields. In the CA field 56.18% of the area was infested in both years when the field margin effect was included, and 22.53% when this effect was excluded; on the other hand, in the CV field only 11.50% of the area was infested in both years. The results illustrate that there are important differences in the spatial distribution of weeds between CA and CV fields; such differences can be easily detected using UAVs and identification algorithms combined.
Spin-Dependent Scattering of Scalar and Vector Dark Matter on the Electron
Authors: Wu Ke-Yun , Xiong Zhao-Hua
Published: May 2022

The property of dark matter remains to date unknown. However, a model-independent classification of dark matter candidates can be achieved by using various symmetries, as performed in the standard model. Fermionic dark matter has been extensively researched, and one favored candidate is the neutralino in the Minimal Supersymmetric Standard Model, which is required by fermion–boson symmetry and the preservation of R-parity. Bosonic dark matter has not been sufficiently studied, especially the scenario of dark matter with a mass of sub-GeV. In this paper, we consider the effect of spin-dependent (SD) on scalar and vector dark matter, which are mediated by pseudoscalar and axial-vector, and evaluate the effect on the dark matter–electron scattering cross-section. We list all the interactions and form factor of dark matter–electron SD scattering, and use XENON10/100/1T experiment data to derive the exclusion limit of the SD cross-section. We find that the SD scattering of scalar and vector dark matter can be three orders of magnitude stronger than spin-independent (SI) scattering due to the p-wave scattering.
The Dual Expression of Parallel Equidistant Ruled Surfaces in Euclidean 3-Space
Authors: Gür Mazlum Sümeyye , Şenyurt Süleyman , Grilli Luca
Published: May 2022

In this study, we examine the dual expression of Valeontis’ concept of parallel p-equidistant ruled surfaces well known in Euclidean 3-space, according to the Study mapping. Furthermore, we show that the dual part of the dual angle on the unit dual sphere corresponds to the p-distance. We call these ruled surfaces we obtained “dual parallel equidistant ruled surfaces” and we briefly denote them with “DPERS”. Furthermore, we find the Blaschke vectors, the Blaschke invariants and the striction curves of these DPERS and we give the relationships between these elements. Moreover, we show the relationships between the Darboux screws, the instantaneous screw axes, the instantaneous dual Pfaff vectors and dual Steiner rotation vectors of these surfaces. Finally, we give an example, which we reinforce this article, and we explain all of these features with the figures on the example. Furthermore, we see that the corresponding dual curves on the dual unit sphere to these DPERS are such that one of them is symmetric with respect to the imaginary symmetry axis of the other.
Heat Flow Characteristics of Ferrofluid in Magnetic Field Patterns for Electric Vehicle Power Electronics Cooling
Authors: Hwang Seong-Guk , Garud Kunal Sandip , Seo Jae-Hyeong , Lee Moo-Yeon
Published: May 2022

The ferrofluid is a kind of nanofluid that has magnetization properties in addition to excellent thermophysical properties, which has resulted in an effective performance trend in cooling applications. In the present study, experiments are conducted to investigate the heat flow characteristics of ferrofluid based on thermomagnetic convection under the influence of different magnetic field patterns. The temperature and heat dissipation characteristics are compared for ferrofluid under the influence of no-magnet, I, L, and T magnetic field patterns. The results reveal that the heat gets accumulated within ferrofluid near the heating part in the case of no magnet, whereas the heat flows through ferrofluid under the influence of different magnetic field patterns without any external force. Owing to the thermomagnetic convection characteristic of ferrofluid, the heat dissipates from the heating block and reaches the cooling block by following the path of the I magnetic field pattern. However, in the case of the L and T magnetic field patterns, the thermomagnetic convection characteristic of ferrofluid drives the heat from the heating block to the endpoint location of the pattern instead of the cooling block. The asymmetrical heat dissipation in the case of the L magnetic field pattern and the symmetrical heat dissipation in the case of the T magnetic field pattern are observed following the magnetization path of ferrofluid in the respective cases. The results confirm that the direction of heat flow could be controlled based on the type of magnetic field pattern and its path by utilizing the thermomagnetic behavior of ferrofluid. The proposed lab-scale experimental set-up and results database could be utilized to design an automatic energy transport system for the cooling of power conversion devices in electric vehicles.
Individual and Combined Effects of Paternal Deprivation and Developmental Exposure to Firemaster 550 on Socio-Emotional Behavior in Prairie Voles
Authors: Gillera Sagi Enicole A. , Marinello William P. , Nelson Mason A. , Horman Brian M. , Patisaul Heather B.
Published: May 2022

The prevalence of neurodevelopmental disorders (NDDs) is rapidly rising, suggesting a confluence of environmental factors that are likely contributing, including developmental exposure to environmental contaminants. Unfortunately, chemical exposures and social stressors frequently occur simultaneously in many communities, yet very few studies have sought to establish the combined effects on neurodevelopment or behavior. Social deficits are common to many NDDs, and we and others have shown that exposure to the chemical flame retardant mixture, Firemaster 550 (FM 550), or paternal deprivation impairs social behavior and neural function. Here, we used a spontaneously prosocial animal model, the prairie vole (Microtus ochrogaster), to explore the effects of perinatal chemical (FM 550) exposure alone or in combination with an early life stressor (paternal absence) on prosocial behavior. Dams were exposed to vehicle (sesame oil) or 1000 µg FM 550 orally via food treats from conception through weaning and the paternal absence groups were generated by removing the sires the day after birth. Adult offspring of both sexes were then subjected to open-field, sociability, and a partner preference test. Paternal deprivation (PD)-related effects included increased anxiety, decreased sociability, and impaired pair-bonding in both sexes. FM 550 effects include heightened anxiety and partner preference in females but reduced partner preference in males. The combination of FM 550 exposure and PD did not exacerbate any behaviors in either sex except for distance traveled by females in the partner preference test and, to a lesser extent, time spent with, and the number of visits to the non-social stimulus by males in the sociability test. FM 550 ameliorated the impacts of parental deprivation on partner preference behaviors in both sexes. This study is significant because it provides evidence that chemical and social stressors can have unique behavioral effects that differ by sex but may not produce worse outcomes in combination.
Type I and Type II Interferon Antagonism Strategies Used by Paramyxoviridae: Previous and New Discoveries, in Comparison
Authors: Pisanelli Giuseppe , Pagnini Ugo , Iovane Giuseppe , García-Sastre Adolfo
Published: May 2022

Paramyxoviridae is a viral family within the order of Mononegavirales; they are negative single-strand RNA viruses that can cause significant diseases in both humans and animals. In order to replicate, paramyxoviruses–as any other viruses–have to bypass an important protective mechanism developed by the host’s cells: the defensive line driven by interferon. Once the viruses are recognized, the cells start the production of type I and type III interferons, which leads to the activation of hundreds of genes, many of which encode proteins with the specific function to reduce viral replication. Type II interferon is produced by active immune cells through a different signaling pathway, and activates a diverse range of genes with the same objective to block viral replication. As a result of this selective pressure, viruses have evolved different strategies to avoid the defensive function of interferons. The strategies employed by the different viral species to fight the interferon system include a number of sophisticated mechanisms. Here we analyzed the current status of the various strategies used by paramyxoviruses to subvert type I, II, and III interferon responses.
Advances in Bovine Coronavirus Epidemiology
Authors: Zhu Qinghe , Li Bin , Sun Dongbo
Published: May 2022

Bovine coronavirus (BCoV) is a causative agent of enteric and respiratory disease in cattle. BCoV has also been reported to cause a variety of animal diseases and is closely related to human coronaviruses, which has attracted extensive attention from both cattle farmers and researchers. However, there are few comprehensive epidemiological reviews, and key information regarding the effect of S-gene differences on tissue tendency and potential cross-species transmission remain unclear. In this review, we summarize BCoV epidemiology, including the transmission, infection-associated factors, co-infection, pathogenicity, genetic evolution, and potential cross-species transmission. Furthermore, the potential two-receptor binding motif system for BCoV entry and the association between BCoV and SARS-CoV-2 are also discussed in this review. Our aim is to provide valuable information for the prevention and treatment of BCoV infection throughout the world.
Porcine Intestinal Organoids: Overview of the State of the Art
Authors: Ma Panpan , Fang Puxian , Ren Tianze , Fang Liurong , Xiao Shaobo
Published: May 2022

The intestinal tract is a crucial part of the body for growth and development, and its dysregulation can cause several diseases. The lack of appropriate in vitro models hampers the development of effective preventions and treatments against these intestinal tract diseases. Intestinal organoids are three-dimensional (3D) polarized structures composed of different types of cells capable of self-organization and self-renewal, resembling their organ of origin in architecture and function. Porcine intestinal organoids (PIOs) have been cultured and are used widely in agricultural, veterinary, and biomedical research. Based on the similarity of the genomic sequence, anatomic morphology, and drug metabolism with humans and the difficulty in obtaining healthy human tissue, PIOs are also considered ideal models relative to rodents. In this review, we summarize the current knowledge on PIOs, emphasizing their culturing, establishment and development, and applications in the study of host–microbe interactions, nutritional development, drug discovery, and gene editing potential.
Time to Revise the WHO Categories for Severe Rabies Virus Exposures–Category IV?
Authors: Scholand Stephen J. , Quiambao Beatriz P. , Rupprecht Charles E.
Published: May 2022

Rabies is a devastating disease and affects millions of people globally, yet it is preventable with appropriate and timely postexposure prophylaxis (PEP). The current WHO exposure categories (Categories I, II, and III) need revision, with a special Category IV for severe exposures. Rare cases of PEP failure have occurred in severe bites to the head and neck. Multiple factors, including route, wound severity, depth, contamination, viral dose, proximity to highly innervated areas and the CNS, and the number of lesions, remain unconsidered. Injuries in areas of high neural density are the most significant considering lyssavirus pathophysiology. Current recommendations do not account for these factors. A Category IV designation would acknowledge the severity and the increased risk of progression. Subsequently, patient management would be optimized with wound care and the appropriate administration of rabies-immune globulin/monoclonal antibodies (RIG/MAbs). All Category IV exposures would be infiltrated with the full dose of intact RIG (i.e., human RIG or MAbs) if the patient was previously unvaccinated. More concentrated RIG/MAb formulations would be preferred. As a world rabies community, we cannot tolerate PEP failures. A fourth WHO categorization will improve the care of these high-risk patients and highlight the global health urgency of this neglected disease.