bluuebunny/crossref_metadata_2025 huggingface dataset:
Human Factors Considerations for Quantifiable Human States in Physical Human–Robot Interaction: A Literature Review
Authors: Abdulazeem Nourhan , Hu Yue
Published: August 2023

As the global population rapidly ages with longer life expectancy and declining birth rates, the need for healthcare services and caregivers for older adults is increasing. Current research envisions addressing this shortage by introducing domestic service robots to assist with daily activities. The successful integration of robots as domestic service providers in our lives requires them to possess efficient manipulation capabilities, provide effective physical assistance, and have adaptive control frameworks that enable them to develop social understanding during human–robot interaction. In this context, human factors, especially quantifiable ones, represent a necessary component. The objective of this paper is to conduct an unbiased review encompassing the studies on human factors studied in research involving physical interactions and strong manipulation capabilities. We identified the prevalent human factors in physical human–robot interaction (pHRI), noted the factors typically addressed together, and determined the frequently utilized assessment approaches. Additionally, we gathered and categorized proposed quantification approaches based on the measurable data for each human factor. We also formed a map of the common contexts and applications addressed in pHRI for a comprehensive understanding and easier navigation of the field. We found out that most of the studies in direct pHRI (when there is direct physical contact) focus on social behaviors with belief being the most commonly addressed human factor type. Task collaboration is moderately investigated, while physical assistance is rarely studied. In contrast, indirect pHRI studies (when the physical contact is mediated via a third item) often involve industrial settings, with physical ergonomics being the most frequently investigated human factor. More research is needed on the human factors in direct and indirect physical assistance applications, including studies that combine physical social behaviors with physical assistance tasks. We also found that while the predominant approach in most studies involves the use of questionnaires as the main method of quantification, there is a recent trend that seeks to address the quantification approaches based on measurable data.
PEMFCs Model-Based Fault Diagnosis: A Proposal Based on Virtual and Real Sensors Data Fusion
Authors: Ariza Eduardo , Correcher Antonio , Vargas-Salgado Carlos
Published: August 2023

Proton Exchange Membrane Fuel Cells (PEMFCs) are critical components in renewable hybrid systems, demanding reliable fault diagnosis to ensure optimal performance and prevent costly damages. This study presents a novel model-based fault diagnosis algorithm for commercial hydrogen fuel cells using LabView. Our research focused on power generation and storage using hydrogen fuel cells. The proposed algorithm accurately detects and isolates the most common faults in PEMFCs by combining virtual and real sensor data fusion. The fault diagnosis process began with simulating faults using a validated mathematical model and manipulating selected input signals. A statistical analysis of 12 residues from each fault resulted in a comprehensive fault matrix, capturing the unique fault signatures. The algorithm successfully identified and isolated 14 distinct faults, demonstrating its effectiveness in enhancing reliability and preventing performance deterioration or system shutdown in hydrogen fuel cell-based power generation systems.
Multi-UAV Collaborative Search and Attack Mission Decision-Making in Unknown Environments
Authors: Liang Zibin , Li Qing , Fu Guodong
Published: August 2023

To address the challenge of coordinated combat involving multiple UAVs in reconnaissance and search attacks, we propose the Multi-UAV Distributed Self-Organizing Cooperative Intelligence Surveillance and Combat (CISCS) strategy. This strategy employs distributed control to overcome issues associated with centralized control and communication difficulties. Additionally, it introduces a time-constrained formation controller to address the problem of unstable multi-UAV formations and lengthy formation times. Furthermore, a multi-task allocation algorithm is designed to tackle the issue of allocating multiple tasks to individual UAVs, enabling autonomous decision-making at the local level. The distributed self-organized multi-UAV cooperative reconnaissance and combat strategy consists of three main components. Firstly, a multi-UAV finite time formation controller allows for the rapid formation of a mission-specific formation in a finite period. Secondly, a multi-task goal assignment module generates a task sequence for each UAV, utilizing an improved distributed Ant Colony Optimization (ACO) algorithm based on Q-Learning. This module also incorporates a colony disorientation strategy to expand the search range and a search transition strategy to prevent premature convergence of the algorithm. Lastly, a UAV obstacle avoidance module considers internal collisions and provides real-time obstacle avoidance paths for multiple UAVs. In the first part, we propose a formation algorithm in finite time to enable the quick formation of multiple UAVs in a three-dimensional space. In the second part, an improved distributed ACO algorithm based on Q-Learning is introduced for task allocation and generation of task sequences. This module includes a colony disorientation strategy to expand the search range and a search transition strategy to avoid premature convergence. In the third part, a multi-task target assignment module is presented to generate task sequences for each UAV, considering internal collisions. This module provides real-time obstacle avoidance paths for multiple UAVs, preventing premature convergence of the algorithm. Finally, we verify the practicality and reliability of the strategy through simulations.
Exploration of Biodegradable Substances Using Machine Learning Techniques
Authors: Elsayad Alaa M. , Zeghid Medien , Ahmed Hassan Yousif , Elsayad Khaled A.
Published: August 2023

The concept of being readily biodegradable is crucial in evaluating the potential effects of chemical substances on ecosystems and conducting environmental risk assessments. Substances that readily biodegrade are generally associated with lower environmental persistence and reduced risks to the environment compared to those that do not easily degrade. The accurate development of quantitative structure–activity relationship (QSAR) models for biodegradability prediction plays a critical role in advancing the design and creation of sustainable chemicals. In this paper, we report the results of our investigation into the utilization of classification and regression trees (CARTs) in classifying and selecting features of biodegradable substances based on 2D molecular descriptors. CARTs are a well-known machine learning approach renowned for their simplicity, scalability, and built-in feature selection capabilities, rendering them highly suitable for the analysis of large datasets. Curvature and interaction tests were employed to construct efficient and unbiased trees, while Bayesian optimization (BO) and repeated cross-validation techniques were utilized to improve the generalization and stability of the trees. The main objective was to classify substances as either readily biodegradable (RB) or non-readily biodegradable (NRB). We compared the performance of the proposed CARTs with support vector machine (SVM), K nearest neighbor (kNN), and regulated logistic regression (RLR) models in terms of overall accuracy, sensitivity, specificity, and receiver operating characteristics (ROC) curve. The experimental findings demonstrated that the proposed CART model, which integrated curvature–interaction tests, outperformed other models in classifying the test subset. It achieved accuracy of 85.63%, sensitivity of 87.12%, specificity of 84.94%, and a highly comparable area under the ROC curve of 0.87. In the prediction process, the model identified the top ten most crucial descriptors, with the SpMaxB(m) and SpMin1_Bh(v) descriptors standing out as notably superior to the remaining descriptors.
Study on Groundwater Function Zoning and Sustainable Development and Utilization in Jining City Planning Area
Authors: Chen Hongnian , Tan Xianfeng , Zhang Yan , Hu Bo , Xu Shuming , Dai Zhenfen , Zhang Zhengxuan , Wang Zhiye , Zhang Yawei
Published: August 2023

The sustainable development and utilization of groundwater resources are of paramount importance for the progress of society, the economy, and the environment. This study focuses on the planning area of Jining City and establishes an evaluation index system for groundwater functional zoning by analyzing key factors such as resource supply function, geo-environmental stability function, and ecological environmental protection function. To evaluate the groundwater functions, this study employs the barrel effect AHP. Through the overlay analysis of different groundwater functions, the planning area of Jining City is categorized into distinct zones based on their groundwater functions. These zones include centralized development and utilization areas (5.69%), decentralized development and utilization areas (65.67%), fragile geo-environmental areas (10.44%), ecological protection areas (8.38%), and unsuitable development and utilization areas (9.82%). The comprehensive zoning map of groundwater functions in the planning area of Jining City is generated. Taking into account the challenges posed by human activities, such as groundwater pollution, this study proposes recommendations for the sustainable development of groundwater in the planning area of Jining City. By systematically examining the functional zoning and sustainable management of groundwater, this study provides a scientific foundation for the responsible development and protection of groundwater resources.
Experimental Analysis and Machine Learning of Ground Vibrations Caused by an Elevated High-Speed Railway Based on Random Forest and Bayesian Optimization
Authors: Cao Yanmei , Li Boyang , Xiang Qi , Zhang Yuxian
Published: August 2023

With the aim of predicting the environmental vibrations induced by an elevated high-speed railway, a machine learning method was developed by combining a random forest algorithm and Bayesian optimization, using a dataset from on-site experiments. When it comes to achieving a rapid and effective prediction of environmental vibrations, there is little research on comparisons between and verifications of different algorithms, and none on the parameter tuning and optimization of machine learning algorithms. In this paper, a field experiment is firstly carried out to measure the ground vibrations caused by high-speed trains running on a bridge, and then the environmental vibration characteristics are analyzed in view of ground accelerations and weighted vibration levels. Subsequently, three machine learning algorithms using linear regression, support vector machine, and random forest are developed using an experimental database, and their prediction performance is discussed. Finally, two optimization models for the hyperparameter set of the random forest algorithm are further compared. The results show that the integrated random forest algorithm has a higher accuracy in predicting environmental vibrations than linear regression and the support vector machine; the Bayesian optimization has an excellent performance and a high efficiency in achieving efficient and in-depth optimization of parameters and can be combined with the RF machine learning algorithm to effectively predict the environmental vibrations induced by the high-speed railway.
The Impact of Principal Curriculum Leadership on Students’ Modernity: Moderated Chain Mediation Effect
Authors: Li Yan , Zeng Deyun , Qi Bote , Sun Yuantao
Published: August 2023

Although a principal’s leadership of the curriculum can have a substantial influence on student outcomes and school performance, limited research exists about the impact of a principal curriculum leadership on the development of students’ thoughts, attitudes, values, and behavioral patterns, so that they can participate effectively in modern society. Based on the theory of human development ecology, this study aimed to explore the impact mechanisms of principal curriculum leadership on students’ modernity, examine the chain mediating effects of teacher leadership and class management effectiveness, and examine the moderating effects of class collective effectiveness. The results reveal that principal curriculum leadership was unable to significantly predict students’ modernity; teacher leadership played an independent mediating role, whereas teacher leadership and class management effectiveness played a chain mediating role; and class collective effectiveness significantly positively moderated the effect of teacher leadership on class management effectiveness and the effect of class management effectiveness on students’ modernity. In order to improve principal curriculum leadership and enhance students’ modernity, the former needs to consider students’ sustainable development, and further attention should be paid to the value of “significant others”, such as principals and teachers, in the development of students, as well to the mechanisms by which the school ecosystem influences the sustainable development of students.
Assessment of Gus Expression Induced by Anti-Sense OsPPO Gene Promoter and Antioxidant Enzymatic Assays in Response to Drought and Heavy Metal Stress in Transgenic Arabidopsis thaliana
Authors: Ullah Zakir , Iqbal Javed , Abbasi Banzeer Ahsan , Akhtar Wasim , Kanwal Sobia , Ali Iftikhar , Chalgham Wadie , El-Sheikh Mohamed A. , Mahmood Tariq
Published: August 2023

Abiotic stresses, including drought and heavy metals, are detrimental to plant growth and development and enormously reduce agricultural yields. Plants may quickly change their transcriptome in response to various stressful conditions. Plants develop many defense mechanisms to respond to various stresses that can be classified into morphological, physiological, and biochemical responses. Polyphenol oxidases (PPOs) are one of the self-protective enzymes found in plants except for Arabidopsis. Currently, drought and heavy metals were applied exogenously to transgenic A. thaliana lines (transformed with Oryza sativa PPO promoter fused to the GUS reporter gene). The current study mainly focused on the systematic pathway by which plants respond to stressors. The aim of this study is to investigate the effect/expression of PPO and antioxidant defense system against abiotic stresses. A. thaliana was treated with different concentrations of polyethylene glycols. At 30% PEG, maximum fold induction (1.9) was seen after 12 h. Overall, various concentrations (5%, 20%, and 30%) induced PPO expression after 6, 12, and 24 h. Moreover, three different concentrations of Cu (50 µM, 100 µM, 200 µM) and Ni (50 µM, 100 µM, 200 µM) for 6, 12, and 24 h were also applied. It was observed that the expression profiling of the OsPPO promoter induced GUS gene expression in response to Cu and Ni treatments. The maximum fold induction (15.03) of GUS was observed in 100 µM of Cu after 24 h. In the case of Ni, maximum fold induction of (7.78) was observed at 100 µM after 24 h. So, both Cu and Ni showed a similar pattern of induction at 100 µM after 24 h. In conclusion, the efficiency of the PPOGUS promoter can be operated to assess the response of plants to various abiotic stimuli.
Contemporary Global Coastal Management Strategies and Coastal Infrastructure and Their Application in Ghana: A Systematic Literature Review
Authors: Charuka Blessing , Angnuureng Donatus Bapentire , Agblorti Samuel K. M.
Published: August 2023

Systematic literature reviews provide the foundation for evidence-based research in a particular field of study. In this regard, the systematic review of the relationship between coastal management strategies and coastal infrastructure typologies provides an opportunity to benchmark local coastal adaptation policies against contemporary global practices, technologies, and sustainability. However, systematic reviews of coastal infrastructure in Ghana and West Africa at large are limited. To close this research gap, we conducted a systematic literature review of the global implementation of coastal management strategies and coastal infrastructure and provided a synopsis of coastal management in Ghana. To achieve this, we searched the Scopus Database for literature on coastal management approaches and infrastructure typologies. Forty-eight peer-reviewed publications met the inclusion criteria for full-text analysis. The results indicate a significant global shift from purely grey infrastructure toward integrating green and grey infrastructure. However, despite contemporary global advances, coastal infrastructure in developing contexts—particularly in Ghana—remains mostly static, using reactive, hold the line strategies, and grey infrastructure. As sea-level rise continues to intensify coastal hazards globally, increasing the demand for coastal protection, researching coastal management policies and coastal infrastructure is essential to support the hybridization of grey and green infrastructure and encourage transitions to adaptive coastal management instead of continuous coastal hardening using grey infrastructure.
Post-Disaster Reconstruction of Residential Buildings: Evolution of Structural Vulnerability on Caribbean Island of Saint Martin after Hurricane Irma
Authors: Mehdizadeh Rasool , Deck Olivier , Pottier Nathalie , Péné-Annette Anne
Published: August 2023

This article presents a summary of the results obtained as part of the ANR (French National Research Agency)-RELEV project, which focuses on the long-term recovery and reconstruction of the island of Saint Martin following the passage of Hurricane Irma in 2017. This hurricane was classified as category five on the Saffir-Simpson scale, with an average wind speed of 287 km/h. It caused catastrophic damage along its path and highlighted the significant vulnerability of Caribbean societies to this type of phenomenon. This article focuses on the reconstruction of residential buildings on the French part of the island of Saint Martin. It aims to identify and analyze the factors that have favorably or unfavorably influenced their reconstruction and their structural vulnerability reduction. The research is based mainly on a series of interviews with local actors (construction and insurance companies, architects, territorial services, etc.), an online survey of residents (180 responses), and a field survey involving visits to 104 buildings with interviews of the occupants. The results obtained show that having access to financial resources for the reconstruction of buildings is central. However, different parameters must be considered to understand the disparity of situations and identify the factors that have most favorably contributed to the speed and quality of reconstruction and reduction of vulnerability. Even five years after Irma, a significant number of buildings on the island remain either unrepaired or abandoned. These buildings nevertheless constitute a danger in the case of strong winds (becoming a source of projectiles) and have a negative impact on the reputation and attractiveness of the island. The results reveal that in general, buildings in Saint Martin are slightly more resilient than they were prior to Irma, while presenting a great heterogeneity of situations.
Response of the Anchoring Performance at Betula platyphylla’s Root–Soil Interface to Cyclic Loading
Authors: Yang Shihan , Ji Xiaodong , Zhao Donghui , Liu Shusen
Published: August 2023

In dealing with issues such as soil erosion and slope instability, plant roots enhance the shear strength of the soil mass through their anchoring effect. However, in nature, cyclic loads such as flash floods and blizzards indirectly impose fatigue effects on plant root systems. To explore the impact of cyclic loads on the anchoring capacity of plant roots, this paper selects the roots of Betula platyphylla as the research object and uses a monotonic load and cyclic load as two loading modes. Under different loading amplitudes (25%, 50%, and 75%), root diameters and burial depths (50 mm, 100 mm, and 150 mm), and soil moisture contents (11.85%, 13.85%, and 15.85%), the effects of each factor on the anchoring capacity of the roots under cyclic loading are analyzed. The results showed that the root–soil interface exhibited two failure modes under different cyclic load amplitudes, and the cyclic load significantly reduced the maximum friction of the root–soil interface. As the cyclic load amplitude increased (from 25% to 75%), the hysteretic curve envelope area increased, and the growth rate of cumulative residual slip changed from decreasing to decreasing and then increasing. A good correlation was found between cumulative residual slip and the number of loading cycles, and the three characteristic slips were correlated with loading amplitude but not significantly with diameter. The increase in soil moisture content, root embedment depth, and diameter led to an increase in the ratio of the two maximum friction forces. It was shown that a certain degree of plasticity exists at the root–soil interface to resist environmental stresses in nature. At high fatigue stress levels, the root–soil interface is more nonlinear, and as the load amplitude increases, more energy is dissipated, and bond damage between the root–soil interface becomes more pronounced. The root–soil interface gradually degraded under long-term cyclic loading, whereas the increase in root depth and soil water content could resist the negative effect of cyclic loading on anchorage capacity, and the resistance effect became more and more obvious with the increase in diameter.
Evaluation of the Effectiveness of Trail Repair Works Based on Three-Dimensional Monitoring around Mount Kurodake, Daisetsuzan National Park, Japan
Authors: Kobayashi Yusuke , Watanabe Teiji
Published: August 2023

Many mountainous, protected areas, such as national parks worldwide, face trail erosion; stakeholders have made significant efforts to manage eroded trails. However, their effectiveness has not been evaluated. This study aimed to (1) create digital elevation models of an eroded trail using structure-from-motion and multi-view-stereo photogrammetry in Daisetsuzan National Park, northern Japan; (2) conduct a six-year monitoring of the trails repaired by volunteers to reveal trail surface changes; and (3) discuss the effectiveness of the repair works. Palm-fiber bags were used on the trail section to stop the movement of the eroded soil. The results of the three-dimensional analysis identified a certain effectiveness of the repair work during 2017–2022. However, the effectiveness lasted for only approximately three years and was not permanent. Therefore, regular maintenance is necessary to ensure trail sustainability. In addition, the soil erosion rate calculated using the maximum erosion depth has increased from 0.52 mm y−1 (1923–1990) to 44.4 mm y−1 (2013–2022), suggesting the need for frequent observations. Trail maintenance through a combination of monitoring and repair work is vital, and the role of hikers/trekkers is becoming increasingly important.
Consumer-Perceived Risks and Sustainable Development of China’s Online Gaming Market: Analysis Based on Social Media Comments
Authors: Lin Ling , Shu Tao , Yang Han , Wang Jun , Zhou Jixian , Wang Yuxuan
Published: August 2023

Online gaming constitutes an indispensable facet of China’s digital economy, catalyzing consumer discussions on social media platforms. This study employs a comprehensive natural language processing framework, encompassing topic mining, multi-label classification, and sentiment analysis, to evaluate consumers’ psychological perceptions of the risks associated with online games through social media comments. This study identifies 11 distinct perceived risk topics, including “Excessive Temptation”, “Entry Regulation”, and “Culture Implantation”. Numerous comments encompass multiple topics, each infused with diverse emotional inclinations, thus unveiling disparate consumer perspectives. These findings underscore the critical significance of addressing potential perceived risks and mitigating negative consumer emotions for enterprises operating within online gaming. Such measures are pivotal to maintaining a brand image, business reputation, and enduring growth. Furthermore, this study extends valuable insights to regulatory bodies, contributing to enhancing administrative efficiency, safeguarding consumer rights, and fostering a robust and sustainable trajectory within China’s online gaming market.
Urbanization Reduces the Nest Size of Barn Swallow (Hirundo rustica) in South Korea
Authors: Kim Hyun-Woo , Park Jun-Kyu , Park Woong-Bae , Do Yuno
Published: August 2023

Urbanization affects the natural world, with implications for habitat availability and wildlife behavior, notably in the context of South Korea. This study investigates the effects of urbanization on the nest sizes and materials of barn swallows, a migratory bird species. Utilizing comparative analyses across suburban, exurban, and rural regions, the study found substantial variations in nest volumes. Specifically, rural areas had significantly larger nests than suburban areas, whereas exurban nest sizes fell in between. Although a potential explanation might relate to differences in the availability of nesting materials, this hypothesis necessitates further investigation. The study also found that the soil composition in nests varied by location, with sand, silt, and clay content showing marginal differences, but not statistically significant disparities. However, a clear preference for a specific soil texture was evident, along with the finding that forest cover within a 1 km radius of the nest was correlated with larger nest sizes. Land use was further linked to the external volume of barn swallow nests, pointing to a potential interaction between habitat quality and nest construction. Overall, the findings underscore the complexity of urbanization’s impact on barn swallows, emphasizing the need to conserve natural habitats and devise strategies to mitigate the negative effects on these birds. These results contribute to the growing understanding of urban ecology and the urgent need for thoughtful management of human-altered landscapes.
Diversified Impacts of Enabling a Technology-Intensified Agricultural Supply Chain on the Quality of Life in Hinterland Communities
Authors: Lubag Marian , Bonifacio Joph , Tan Jasper Matthew , Concepcion Ronnie , Mababangloob Giolo Rei , Galang Juan Gabriel , Maniquiz-Redillas Marla
Published: August 2023

The agricultural supply chain (ASC) in the hinterland refers to the entire post-harvest process of processing and distributing agricultural products in rural or secluded areas to be brought to big city markets. This scheme involves various stakeholders (farmers, trading centers, consumers), processes (logistics, storage, monitoring), and infrastructure (traffic and road systems, negative environmental emissions) to ensure the efficient flow of agricultural products from farms to consumers. The quality of life (QoL) in the hinterland can improve with the introduction of disruptive technologies, but no comprehensive studies have explored the QoL of individuals involved in the ASC–socioeconomic system of hinterland communities. This study elucidated and compared the diversified impacts of disruptive technologies brought by the Industrial Revolution 4.0 to the agricultural supply chain and their impacts on food security, sustainability, and climate change mitigation through the analysis of the related literature. This study also mapped out the role of disruptive technologies in the QoL of hinterland communities, particularly with respect to the farmers, trading center workers, and consumers. Points of discussion emerged with respect to precision agriculture, the Artificially Intelligent Internet of Things, big data analytics, blockchain, artificial intelligence, cyber-physical systems, robotics, automation, and e-commerce, and how these enabling technologies enhance fresh food supply and distribution and deliberately affect stakeholders’ life quality indexes through the analysis of situational case studies in India, South America, Malaysia, China, and Europe. The identification of these points of discussion was also achieved purely based on research performed on the related literature. The positive impacts of these technologies, such as the boosting of efficiency and the ensuring of a steady supply of fresh produce, ultimately improve the overall QoL. The technical insights from the studies were synthesized to develop new frameworks for QoL anchored in the agricultural supply chain (AgQoL) in the hinterland, and a six-dimensional network emphasizing the two trifectas of techno-socioenvironmental needs was established. Food-producing communities with a relatively high AgQoL should support food security in the region.
The Development of an Interview Questionnaire and Guide for the Sustainable Use of Assistive Devices among the Disabled in Korea
Authors: Ro Eun-Rae , An Kwang-Ok , Lim Myung-Joon , Lee Sung-Yong , Kim Dong-Ah , Eun Seon-Deok
Published: August 2023

Assistive device use has increased in recent years in Korea following the expansion of disability categories, increase in acquired disabilities, and an aging society. Although assistive devices can improve the quality of life by aiding social participation and removing physical restrictions, some devices are simply not used after users receive them via public distribution projects. Understanding assistive device usage after distribution is crucial to improve their service and supported products by disability type. This study constructed an interview questionnaire and interview guide for investigating the reason for (not) using the assistive device, and the necessity of assistive devices according to time point after disability. The aim was to establish a foundation for accumulating systematic and in-depth data. The interview questionnaire was developed primarily for frequent device users across 15 physical disability types. The terms used in the questionnaire were systematically defined, and interview items were derived based on assistive device-related questionnaires from the extant literature. The final interview questionnaire and guide were then refined after pilot test (N = 4) and expert (N = 2) consultations. The data accumulated by utilizing the interview questionnaire and interview guide developed in this study can improve the service support system for assistive devices by disability type and improvements by assistive devices in the future. This can help improve users’ quality of life by providing a more appropriate and enhanced assistive device.
Assessing the Impact of Farm-Management Practices on Ecosystem Services in European Agricultural Systems: A Rapid Evidence Assessment
Authors: Van Ruymbeke Kato , Ferreira Joana G. , Gkisakis Vasileios D. , Kantelhardt Jochen , Manevska-Tasevska Gordana , Matthews Peter , Niedermayr Andreas , Schaller Lena , Bańkowska Katarzyna , Mertens Kewan , Vranken Liesbet
Published: August 2023

Many farm-management practices focus on maximizing production, while others better reconcile production with the regulation of ecological processes and sociocultural identity through the provisioning of ecosystem services (ESs). Though many studies have evaluated the performance of management practices against ES supply, these studies often focused on only a few practices simultaneously. Here, we incorporate 23 distinct management practices in a rapid evidence assessment to draw more comprehensive conclusions on their supply potential across 14 ESs in European agriculture. The results are visualized using performance indicators that quantify the ES-supply potential of a given management practice. In total, 172 indicators are calculated, among which cover crops are found to have the strongest positive impact on pollination-supply potential, while extensive livestock management is found to have the strongest negative impact for the supply potential for habitat creation/protection. The indicators also provide insight into the state of the peer-reviewed literature. At both the farm and territorial levels, the literature noticeably fails to evaluate cultural services. Further, disparities between the number of indicators composed at the farm and territorial levels indicate a systematic bias in the literature toward the assessment of smaller spatial levels.
Study on the Characteristics of Granite in Different Stress Stages through a Cyclic Loading Experiment
Authors: Liu Handong , Wang Jialiang , Yu Huaichang , Zhang Yiying
Published: August 2023

The deformation and failure process of rocks is a gradual process. The purpose of this study was to examine the characteristics of rocks in different stages through a cyclic loading experiment. The experiment was carried out based on the MTS815 rock mechanics test system combined with acoustic emission monitoring equipment to study the typical characteristics of two kinds of granite in the stages of crack closure, linear elastic deformation, crack initiation and stable crack growth, along with crack damage and unstable crack growth. The results showed that there were significant differences in the characteristics of the strain response, energy evolution, and acoustic emission of the two granites in the different stages. Although the microstructure and mineral elements of the two granites are different, the characteristics of the two granites in the same stage were similar, indicating that the stage characteristics of brittle rocks in the failure process may be widespread and have significant similarities.
The Adoption of a Big Data Approach Using Machine Learning to Predict Bidding Behavior in Procurement Management for a Construction Project
Authors: Kusonkhum Wuttipong , Srinavin Korb , Chaitongrat Tanayut
Published: August 2023

Big data technologies are disruptive technologies that affect every business, including those in the construction industry. The Thai government has also been affected and attempted to use machine learning techniques with the analytics of big data technologies to predict which construction projects have a winning price over the project budget. However, this technology was never developed, and the government did not implement it because they had data obtained via a traditional data collection process. In this study, traditional data were processed to predict the behavior in Thai government construction projects using a machine learning model. The data were collected from the government procurement system in 2019. There were seven input data, including the project owner department, type of construction project, bidding method, project duration, project scale, winning price overestimated price, and winning price over budget. A range of classification techniques, including an artificial neural network (ANN), a decision tree (DC), and a K-nearest neighbor (KNN), were used in this study. According to the results, after hyperparameter tuning, the ANN had the greatest prediction accuracy of 78.9 percent. This study confirms that the data from the Thai government procurement system can be investigated using machine learning techniques from big data technologies.
Seasonal Migrant Workers Perceived Working Conditions and Speculative Opinions on Possible Uptake of Exoskeleton with Respect to Tasks and Environment: A Case Study in Plant Nursery
Authors: Villanueva-Gómez Rebeca , Thamsuwan Ornwipa , Barros-Castro Ricardo A. , Barrero Lope H.
Published: August 2023

Seasonal migrant farmworkers are essential to the success of agriculture in Quebec as they provide the labor needed to produce crops and animals. Notwithstanding, these workers are often at risk of occupational health and safety hazards, while only a few interventions have been implemented to improve the situation. Modern engineering interventions like exoskeleton devices have been introduced to reduce the risk of developing musculoskeletal disorders in other industries, but nothing much has been done in agriculture. This paper employed a mixed-method approach to evaluate the effect of environmental conditions and physical activities on farmworkers’ bodies and sensations and explore their speculative opinions about exoskeletons for their tasks. This study took place in a large plant nursery. Data were collected through field observations, written questionnaires, and semi-structured interviews. The analysis showed heat, humidity, cold, and rain affect farmworkers in feeling sore, worn out, tired, weak, and suffocated. The arms and the back were the body parts most affected by the repetitive bending over and carrying the load. Farmworkers’ exoskeleton perceptions were positive, remarking benefits such as making the task easier, improving posture, reducing fatigue, and protecting the body. The barriers that emerged were concerning the exoskeleton weight, being uncomfortable to wear, causing heat, restricting mobility, not allowing flexibility to change tasks, and not allowing space to work in tight workplaces. The study includes strategies to ensure credibility, reliability, and transferability. Future investigations could test exoskeletons on farmworkers and conduct the cost benefits of exoskeletons in agriculture.
Digital Technology and Green Development in Manufacturing: Evidence from China and 20 Other Asian Countries
Authors: Zhu Lin , Li Xiaoming , Huang Yao , Liu Fangyuan , Yang Chengji , Li Dongyang , Bai Hongpeng
Published: August 2023

The global interest in environmental protection and sustainable development has grown steadily in recent years, sparking widespread concern about green development in the manufacturing industry among governments, enterprises, and scholars around the world. Despite this heightened interest, research on the influence of the digital economy on the manufacturing industry’s green development remains scarce. This article analyzes the impact of the digital economy on the green development of the manufacturing industry and examines the role of human capital and trade competitiveness in this context. Using a two-way fixed-effects model of panel data analysis, we investigated the GTFP (Green Total Factor Productivity) of the Chinese manufacturing industry, as well as that of the overall industry and 20 other Asian countries along the “Belt and Road”. Our findings indicate a positive association between the digital economy and both the overall GTFP and the manufacturing GTFP in China. The countries situated along the Belt and Road experience a U-shaped trend in their GTFP due to the impact of the digital economy. The digital economy displays a delayed impact, and its eco-friendly value is realized, to different extents, after two sequential periods. In addition, human capital and trade competitiveness are threshold variables in the relationship between the digital economy and the green development of the manufacturing industry. When human capital exceeds a certain threshold and trade competitiveness exceeds a certain threshold, the digital economy has a positive effect on GTFP. This study offers unique insights into the impact of the digital economy on the green development of the manufacturing industry. By addressing this research gap, this study gives policymakers the ability to leverage these findings to promote sustainable practices across the industry. Ultimately, the valuable insights provided by this study may contribute to the ongoing efforts to advance the green development of the manufacturing industry.
Relative Influence of Meteorological Variables of Human Thermal Stress in Peninsular Malaysia
Authors: Houmsi Mohamad , Ismail Zulhilmi , Ziarh Ghaith , Hamed Mohammed , Ishak Daeng , Muhammad Mohd , Mokhtar Muhamad , Sa’adi Zulfaqar , Shahid Shamsuddin
Published: August 2023

Climate change has significantly increased human thermal stress, particularly in tropical regions, exacerbating associated risks and consequences, such as heat-related illnesses, decreased workability, and economic losses. Understanding the changes in human thermal stress and its drivers is crucial to identify adaptation measures. This study aims to assess various meteorological variables’ spatial and seasonal impact on Wet Bulb Globe Temperature (WBGT), an indicator of human thermal stress, in Peninsular Malaysia. The Liljegren method is used to estimate WBGT using ERA5 hourly data from 1959 to the present. The trends in WBGT and its influencing factors are evaluated using a modified Mann-Kendall test to determine the region’s primary driver of WBGT change. The results indicate that air temperature influences WBGT the most, accounting for nearly 60% of the variation. Solar radiation contributes between 20% and 30% in different seasons. Relative humidity, zenith, and wind speed have relatively lesser impacts, ranging from −5% to 20%. Air temperature has the highest influence in the northern areas (>60%) and the lowest in the coastal regions (40%). On the other hand, solar radiation has the highest influence in the southern areas (20–40%) and the least in the north. The study also reveals a significant annual increase in temperature across all seasons, ranging from 0.06 to 0.24 °C. This rapid temperature rise in the study area region has led to a substantial increase in WBGT. The higher increase in WBGT occurred in the coastal regions, particularly densely populated western coastal regions, indicating potential implications for public health. These findings provide valuable insights into the factors driving WBGT and emphasize the importance of considering air temperature as a key variable when assessing heat stress.
Quantifying the Nonadiabaticity Strength Constant in Recently Discovered Highly Compressed Superconductors
Authors: Talantsev Evgeny F.
Published: August 2023

Superconductivity in highly pressurized hydrides has become the primary direction for the exploration of the fundamental upper limit of the superconducting transition temperature, Tc, after Drozdov et al. (Nature 2015, 525, 73) discovered a superconducting state with Tc=203 K in highly compressed sulfur hydride. To date, several dozen high-temperature superconducting polyhydrides have been discovered and, in addition, it was recently reported that highly compressed titanium and scandium exhibit record-high Tc (up to 36 K). This exceeded the Tc=9.2 K value of niobium many times over, which was the record-high  Tc ambient pressure metallic superconductor. Here, we analyzed the experimental data for the recently discovered high-pressure superconductors (which exhibit high transition temperatures within their classes): elemental titanium (Zhang et al., Nature Communications 2022; Liu et al., Phys. Rev. B 2022), TaH3 (He et al., Chinese Phys. Lett. 2023), LaBeH8 (Song et al., Phys. Rev. Lett. 2023), black phosphorous (Li et al., Proc. Natl. Acad. Sci. 2018; Jin et al., arXiv 2023), and violet (Wu et al., arXiv 2023) phosphorous to reveal the nonadiabaticity strength constant TθTF (where Tθ is the Debye temperature, and TF the Fermi temperature) in these superconductors. The analysis showed that the δ-phase of titanium and black phosphorous exhibits TθTF scores that are nearly identical to those associated with A15 superconductors, while the studied hydrides and violet phosphorous exhibit constants in the same ballpark as those of H3S and LaH10.
Sérgio Ferreira beyond Pharmacology: His Role as a Science Communicator
Authors: Villarreal Cristiane Flora , Nascimento Paulo Gustavo Barboni Dantas , Ferreira Beatriz Rossetti , Funez Mani Indiana
Published: August 2023

Historically, toxins from animal venoms have contributed significantly to the discovery of new drugs, as illustrated by captopril, the first drug developed from an animal toxin approved for human use [...]
Isolation and Optimization of Aflatoxin B1 Degradation by Uniform Design and Complete Genome Sequencing of Novel Deep-Sea Kocuria rosea Strain 13
Authors: Wang Jingying , Chen Qiqi , Yan Peisheng , Dong Chunming , Shao Zongze
Published: August 2023

Aflatoxin B1 is a natural carcinogenic mycotoxin. The biological detoxification of aflatoxin could result in less environmental pollution, more moderate conditions, and less impact on food and feed, and be more convenient than physical and chemical methods. In this study, strain 13 with aflatoxin B1 degradation activity (67.47 ± 1.44%) was isolated and identified as Kocuria rosea. A uniform design was applied to optimize the degradation activity using a software Data Processing System, and a quadratic polynomial stepwise regression model was selected to investigate the relationships between the degradation rate and five independent variables. Furthermore, the optimal degradation conditions (culture temperature of 30 °C, culture time of 4.2 days, seawater ratio of 100%, pH of 7.11, and inoculation dosage of 0.09%) were verified with a degradation rate of 88 ± 0.03%, which was well matched with the predicted value (92.97%) of the model. Complete genome sequencing of Kocuria rosea, conducted with a combination of Illumina and single-molecule real-time sequencing, was used to analyze the genomic features and functions of the strain, which were predicted by the annotation based on seven databases, and may provide insights into the potential of Kocuria rosea, as well as providing a reference for degradation gene and protein mining. These results indicate that Kocuria rosea strain 13 has the ability to degrade aflatoxin B1 efficiently, and it also has the potential to provide aflatoxin-degrading enzymes.
Evaluation of Statistical Treatment of Left-Censored Contamination Data: Example Involving Deoxynivalenol Occurrence in Pasta and Pasta Substitute Products
Authors: Feraldi Alessandro , De Santis Barbara , Finocchietti Marco , Debegnach Francesca , Mandile Antonio , Alfò Marco
Published: August 2023

The handling of data on food contamination frequently represents a challenge because these are often left-censored, being composed of both positive and non-detected values. The latter observations are not quantified and provide only the information that they are below a laboratory-specific threshold value. Besides deterministic approaches, which simplify the treatment through the substitution of non-detected values with fixed threshold or null values, a growing interest has been shown in the application of stochastic approaches to the treatment of unquantified values. In this study, a multiple imputation procedure was applied in order to analyze contamination data on deoxynivalenol, a mycotoxin that may be present in pasta and pasta substitute products. An application of the proposed technique to censored deoxynivalenol occurrence data is presented. The results were compared to those attained using deterministic techniques (substitution methods). In this context, the stochastic approach seemed to provide a more accurate, unbiased and realistic solution to the problem of left-censored occurrence data. The complete sample of values could then be used to estimate the exposure of the general population to deoxynivalenol based on consumption data.