bluuebunny/crossref_metadata_2025 huggingface dataset:
Predictive Analytics for Sustainable E-Learning: Tracking Student Behaviors
Authors: Mudawi Naif Al , Pervaiz Mahwish , Alabduallah Bayan Ibrahimm , Alazeb Abdulwahab , Alshahrani Abdullah , Alotaibi Saud S. , Jalal Ahmad
Published: October 2023

The COVID-19 pandemic has sped up the acceptance of online education as a substitute for conventional classroom instruction. E-Learning emerged as an instant solution to avoid academic loss for students. As a result, educators and academics are becoming more and more interested in comprehending how students behave in e-learning settings. Behavior analysis of students in an e-learning environment can provide vision and influential factors that can improve learning outcomes and guide the creation of efficient interventions. The main objective of this work is to provide a system that analyzes the behavior and actions of students during e-learning which can help instructors to identify and track student attention levels so that they can design their content accordingly. This study has presented a fresh method for examining student behavior. Viola–Jones was used to recognize the student using the object’s movement factor, and a region-shrinking technique was used to isolate occluded items. Each object has been checked by a human using a template-matching approach, and for each object that has been confirmed, features are computed at the skeleton and silhouette levels. A genetic algorithm was used to categorize the behavior. Using this system, instructors can spot kids who might be failing or uninterested in learning and offer them specific interventions to enhance their learning environment. The average attained accuracy for the MED and Edu-Net datasets are 90.5% and 85.7%, respectively. These results are more accurate when compared to other methods currently in use.
Scoping Potential Routes to UK Civil Unrest via the Food System: Results of a Structured Expert Elicitation
Authors: Jones Aled , Bridle Sarah , Denby Katherine , Bhunnoo Riaz , Morton Daniel , Stanbrough Lucy , Coupe Barnaby , Pilley Vanessa , Benton Tim , Falloon Pete , Matthews Tom K. , Hasnain Saher , Heslop-Harrison John S. , Beard Simon , Pierce Julie , Pretty Jules , Zurek Monika , Johnstone Alexandra , Smith Pete , Gunn Neil , Watson Molly , Pope Edward , Tzachor Asaf , Douglas Caitlin , Reynolds Christian , Ward Neil , Fredenburgh Jez , Pettinger Clare , Quested Tom , Cordero Juan Pablo , Mitchell Clive , Bewick Carrie , Brown Cameron , Brown Christopher , Burgess Paul J. , Challinor Andy , Cottrell Andrew , Crocker Thomas , George Thomas , Godfray Charles J. , Hails Rosie S. , Ingram John , Lang Tim , Lyon Fergus , Lusher Simon , MacMillan Tom , Newton Sue , Pearson Simon , Pritchard Sue , Sanders Dale , Sanderson Bellamy Angelina , Steven Megan , Trickett Alastair , Voysey Andrew , Watson Christine , Whitby Darren , Whiteside Kerry
Published: October 2023

We report the results of a structured expert elicitation to identify the most likely types of potential food system disruption scenarios for the UK, focusing on routes to civil unrest. We take a backcasting approach by defining as an end-point a societal event in which 1 in 2000 people have been injured in the UK, which 40% of experts rated as “Possible (20–50%)”, “More likely than not (50–80%)” or “Very likely (>80%)” over the coming decade. Over a timeframe of 50 years, this increased to 80% of experts. The experts considered two food system scenarios and ranked their plausibility of contributing to the given societal scenario. For a timescale of 10 years, the majority identified a food distribution problem as the most likely. Over a timescale of 50 years, the experts were more evenly split between the two scenarios, but over half thought the most likely route to civil unrest would be a lack of total food in the UK. However, the experts stressed that the various causes of food system disruption are interconnected and can create cascading risks, highlighting the importance of a systems approach. We encourage food system stakeholders to use these results in their risk planning and recommend future work to support prevention, preparedness, response and recovery planning.
Understanding the Impact of Online Communication Strategies on Consumer Purchase Intention for Green Cosmetics
Authors: Teixeira Sara , Oliveira Zaila , Teixeira Sandrina , Teixeira Sara
Published: October 2023

Increased environmental awareness has increased the demand for green products, mainly cosmetics. This fact challenges companies to adapt to changes and consider environmental problems in their communication strategies to offer products that meet current trends in the consumer market. This implies the need to understand the antecedents of purchase intention better. This research was guided by the theory of planned behaviour (TPB) with the aim of understanding the impact of online communication strategies on consumer purchase intention of green cosmetics. Intention to purchase green cosmetics was measured, as were two of the main TPB constructs, specifically attitude and subjective norms. In addition, other variables were added to the study, such as electronic word of mouth (e-WOM), influencer marketing, and brand content. Data collected through an online survey (N = 151) were analysed using statistical techniques based on variance through partial least squares (PLS) using the SmartPLS3 v.3.3.9 software. The results show that the online communication strategies that impact the purchase intention of green cosmetics are e-WOM and brand content. In practice, the results obtained provide valuable information for professionals and academics, benefiting the perception of the factors that motivate the intention to purchase green cosmetics, contributing to the implementation of better online communication strategies.
Enhancing the Efficiency of Bi-Facial Photovoltaic Panels: An Integration Approach
Authors: Abdelsalam Emad , Alnawafah Hamza , Almomani Fares , Mousa Aya , Qandil Hasan
Published: October 2023

This work presents a novel approach to increasing the efficiency of photovoltaic (PV) panels by integrating them with a cooling tower (CT). An infusion of water cools the hot, dry ambient air at the top of the CT. Due to gravity, the cooled air drops toward the base of the CT, where it interacts with a turbine placed at the bottom of the CT to produce electricity. The air then exits the CT base, creating a cooled air jet stream. The PV panels were placed at the base of the CT, right at the stream’s exit. As the cooled air passes underneath the PV panels, it exchanges energy with the PV, reducing the panels’ temperature. The results showed that the maximum annual efficiency improvement (6.831%) was observed using two rows of PV panels. The efficiency declined incrementally from 6.831% to 4.652% when the number of rows of PV panels was increased from two to twelve. The results also showed a significant improvement in the temperature of the PV panels. The best results were obtained at noon (maximum ambient temperature), where the solar panel temperature was lowered to 25 °C from 55 °C. Furthermore, the annual electrical energy generated with two rows of panels was 39,207.4 kWh without the CT, compared to 41,768.2 kWh with the CT. In addition, the results showed that with a 10 m diameter and 200 m height CT, the maximum number of PV rows that can be effectively cooled is 24. Future work will investigate integrating additional techniques to improve the system’s efficiency further.
Perceptions of “Sports for All” Instructor Competence in the Republic of Korea: A Big Data Analysis Approach
Authors: Jang Jusun , So Wi-Young
Published: October 2023

Background: This study examined the perceptions regarding the competency of “sports for all” instructors using big data analysis. Given the increasing number of everyday participants in sports in the Republic of Korea, this study aimed to identify sports for all instructor competency requirements and gaps and thus help to develop and foster such instructors’ competence. Methods: This study employed big data analysis, specifically, text mining, opinion mining, term frequency–inverse document frequency analysis, and degree centrality analysis. Semantic network analysis was also performed using Textom and UCINET 6’s NetDraw program. The data collection period was from 1 January 2016 to 31 December 2020. This five-year study was initiated following the reorganization of the sports for all instructor qualification system in the Republic of Korea in 2015. Results: First, eight groups were formed by extracting 80 words with the highest frequency and conducting a convergence of iteration correlation analysis. Second, categorization based on the results yielded four factors: certification of sports for all instructors, coaching competency, competency education, and emotions. Conclusions: The analysis of perceptions of the competencies of sports for all instructors revealed a great deal of interest in a qualification system that can develop competencies and in education that strengthens them. To become an effective sports for all instructor, corresponding competencies are required and a qualification system to acquire and strengthen these competencies is necessary. The state should focus continuous attention and effort on the qualification system to nurture such competencies.
Current Knowledge, Research Progress, and Future Prospects of Phyto-Synthesized Nanoparticles Interactions with Food Crops under Induced Drought Stress
Authors: Wahab Abdul , Batool Farwa , Muhammad Murad , Zaman Wajid , Mikhlef Rafid Magid , Naeem Muhammad
Published: October 2023

Drought stress threatens global food security and requires creative agricultural solutions. Recently, phyto-synthesized nanoparticles NPs have garnered attention as a way to reduce food crop drought. This extensive research examines how phyto-synthesized NPs improve crop growth and biochemistry in drought-stressed situations. The review begins with an introduction highlighting the urgency of addressing the agricultural challenges posed by drought. It also highlights the significance of nanoparticles synthesized from photosynthesis in this context. Its purpose is to underscore the importance of sustainable farming practices. This approach is contrasted with conventional methods, elucidating the ecological and economic advantages of phyto-synthesized NPs. This review discusses phyto-synthesized nanoparticles, including titanium dioxide, iron oxide, gold, silver, and copper. In addition, we review their ability to enhance crop growth and stress resistance. The primary focus is to elucidate the effects of phyto-synthesized NPs on plant development under drought stress. Noteworthy outcomes encompass improvements in seed germination, seedling growth, water absorption, photosynthesis, chlorophyll content, the activation of antioxidant defense mechanisms, and the modulation of hormonal responses. These results underscore the potential of phyto-synthesized NPs as agents for enhancing growth and mitigating stress. The review assesses the risks and challenges of using phyto-synthesized NPs in agriculture. Considerations include non-target organisms, soil, and environmental impacts. Further research is needed to determine the long-term effects, dangers, and benefits of phyto-synthesized NPs. Nanoparticles offer a targeted and sustainable approach for improving plant drought tolerance, outpacing traditional methods in ethics and ecological balance. Their mechanisms range from nutrient delivery to molecular regulation. However, the long-term environmental impact remains understudied. This review is critical for identifying research gaps and advancing sustainable agricultural practices amid global water scarcity.
Spatio-Temporal Distribution and Trends of Major Agricultural Crops in Romania Using Interactive Geographic Information System Mapping
Authors: Drăguleasa Ionuț-Adrian , Niță Amalia , Mazilu Mirela , Curcan Gheorghe
Published: October 2023

This research study presents the spatio-temporal distribution of the main agricultural crops in Romania using a modern digitalisation technique, namely interactive GIS mapping. Interactive GIS mapping includes various features specific to the development of sustainable Romanian agriculture, including the arable area of Romania, information on the area (hectares) cultivated with corn, wheat, sunflower, and rape during the 1990–2018 period, the degree of mechanisation, the number of tractors, and information regarding the landforms, a natural factor in relation to cultivated surfaces. Agricultural land should be properly used based on its ability to meet the demands of consumers of traditional Romanian products with an ecological label, but also the needs of the local population, and, at the same time, to ensure the sustainability of the natural environment through the practice of ecological agriculture. The purpose of this research is to provide an overview of the current state of the main agricultural crops in Romania. From a theoretical but also practical point of view, this research presents, for the first time, a retrospective analysis of each county in Romania in terms of the geospatial distribution of major agricultural crops using interactive GIS mapping. Geospatial data were processed in ArcGIS Geographic Information System 10.7.2. The results of this study show that the most extensive cereal areas at the county level in Romania are corn and wheat. The largest areas cultivated with corn and wheat in 2018 were recorded in the Western Plain, the Romanian Plain, and the Moldavian Plateau. For wheat, increases were also recorded in the Dobrogea Plateau. The intensification of labour productivity and the promotion of the sustainability of the natural environment in Romania is presented through the main indicator (the number of tractors) of the degree of mechanisation of agriculture. The higher values of this indicator are in the counties of Bihor, Timiș, and Maramureș. Limitations in Romania’s agricultural data present substantial challenges to the sector’s development and sustainability. Addressing these challenges is essential for informed decision making, policy formulation, and effective resource allocation.
Sustainability of the New Energy Automobile Industry: Examining the Relationship among Government Subsidies, R&D Intensity, and Innovation Performance
Authors: Ma Xin , Jiang Hong , Tong Lijuan , Zhang Jingyi , Dong Mengyuan
Published: October 2023

One of the most important factors in fostering the sustainable growth of the world economy is the global green low-carbon transition. With its effective use of resources, its high technological requirements, and its high added value, the new energy vehicle industry exemplifies the potential for sustainability. Its growth satisfies the requirements of China’s transition to an economic growth mode. This study performs an empirical analysis, using panel data from 154 new energy vehicle companies for the years 2015 to 2020. It examines the role of research and development (R&D) intensity in the impact relationship between government subsidies, R&D intensity, and innovation performance. The study’s results reveal that government subsidies have a significant positive influence on the innovation performance of enterprises, with this effect being more pronounced in non-state-owned and large-scale enterprises. Moreover, the mechanism analysis indicates that R&D intensity serves as a mediator between government subsidies and innovation performance. Based on this, this paper proposes that the government should refine the subsidy policy and should scientifically classify the enterprise standards and that enterprises should enhance their R&D capability and should develop innovation mechanisms.
Sensory Profile of Semi-Hard Goat Cheese Preserved in Oil for Different Lengths of Time
Authors: Levak Stefani , Kos Ivica , Kalit Samir , Dolenčić Špehar Iva , Bendelja Ljoljić Darija , Rako Ante , Tudor Kalit Milna
Published: October 2023

The aim of this study was to investigate the sensory profile of semi-hard goat cheese preserved in an oil mixture (extra virgin olive oil from Mljet and refined sunflower oil; 50:50). Five batches of cheese were made, and each batch was divided into three groups: (i) ripening in air (group 1—control group), (ii) ripening in oil after 10 days of ripening in air (group 2), (iii) ripening in oil after 20 days of ripening in air (group 3). After 60 days of ripening, quantitative descriptive analysis (QDA) was performed by six trained experts and texture was analyzed with a texture analyzer. The correlations between the descriptive sensory scores of texture and the texture analyzer results were significantly related. Compared to the control group, the oil-ripened cheeses had significantly (p < 0.05) higher oily odor and taste intensity and greater elasticity and stickiness determined by fingers, but thinner rind, lower cross-sectional color intensity, and lower crumbliness in the mouth. Ripening in oil improved rind thickness, taste, texture, and cross-sectional properties. Group 3 cheeses were preferred in terms of appearance, cross-section, odor, and taste, suggesting that prolonged ripening in air before immersion in oil positively affected the sensory characteristics of the cheese.
RISING Strong: Sustainability through Art, Science, and Collective Community Action
Authors: Hurley Mairéad , Roche Joseph
Published: October 2023

The objective of this research is to offer a qualitative analysis of adult STEAM (science, technology, engineering, the arts and mathematics) learning in a community setting, with a focus on sustainability and climate action. To date, much research on STEAM learning has been directed towards youth and children in formal educational settings. Our qualitative study involving semi-structured interviews with community participants, artists, and scientists over the course of a six-month initiative in Ireland allowed us to develop a rich picture of a multi-faceted STEAM project that held space for both a social change agenda and a learning agenda. In our findings, we identified several contributing factors to transformative learning and changed feelings about climate change, including pride of place, the development of strong interpersonal relationships, and an emerging sense of collective agency through a shared emotional and affective journey. To design for meaningful, community-level climate action, we argue that learning may be supported in, with and through STEAM. Our study also showcases the value of the arts and aesthetic experiences to embrace dissensus when tackling a complex issue like climate change through STEAM education.
Analysis of the Temporal and Spatial Pattern and Convergence Characteristics of High-Quality Sustainable Economic Development of Urban Agglomeration
Authors: Liu Fei , Zhang Genyu , Li Chenghao , Ren Tao , Masi Donato
Published: October 2023

Based on the sample data of 149 cities in ten major urban agglomerations from 2004 to 2019, the entropy method, Dagum Gini coefficient, and three-dimensional kernel density estimation method are used to calculate and describe the spatial pattern of the high-quality, sustainable economic development of these ten major urban agglomerations. We then use the spatial econometric model to estimate the β convergence trend within the urban agglomerations and among the urban agglomerations at different levels. Our main findings include the following: First, the urban agglomeration tends to develop a high-quality economy, but the gap between the urban agglomerations can be large. Second, although the gap within the overall group of urban agglomerations is expanding, the gap between high-quality individuals and the average is constantly shrinking; the gap between groups is still the leading cause of the spatial gap, with a contribution rate of 70.51%. Third, all urban agglomerations have an absolute and conditional β convergence trend, and the convergence speed presents the characteristics of “high level slow, low level fast”. Government intervention, financial development, urbanization, and human capital contribute to the high-quality, sustainable economic development of each urban agglomeration. There is a heterogeneous influence; there is also absolute and conditional β convergence among urban agglomerations at all levels, and the convergence rate presents a gradient characteristic of “third level > second level > first level”, and by balancing the financial relationships between city groups within each level, development differences can promote the dynamic coordination of high-quality, sustainable economic development rates.
A Method for Dividing Rockburst Risk Zones—A Case Study of the Hegang Mining Area in China
Authors: Pang Jiewen , Yang Xiaojie , Yang Shaoqiang , He Yongliang , Xie Jianlin , Han Qiaoyun
Published: October 2023

Rockbursts are serious mine disasters. Through the division of rockburst risk zones, risks can be predicted in advance and measures can be implemented to prevent disasters. In this paper, taking the Hegang mining area as an example, we propose a method for dividing rockburst risk zones based on in-situ stress measurements. First, 24 survey points were established in the Hegang mining area to measure the in-situ stress. Second, based on the in-situ stress measurement data, eight representative prospecting lines were selected to establish a numerical model, and the distribution characteristics of the in-situ stress field at mining elevations of −330 m and −450 m in the Hegang mining area were obtained via the linear differential method. Afterward, division criteria for rockburst risk zones were proposed in accordance with the energy criterion and the minimum energy principle. Finally, the Hegang mining area was divided into rockburst risk zones in accordance with the in-situ microseismic monitoring data and simulation results for the in-situ stress field. Coal seam #3 was chosen as an example to illustrate rockburst risk-zone division in the Hegang mining area considering the division criterion proposed herein, and a rockburst risk zoning map of coal seam #3 in the Hegang mining area was finally obtained. The locations of the five rockbursts that have occurred in coal seam #3 of the Hegang mining area were marked on the risk zoning map and were found to have occurred in the threatened zone. Thus, it was shown that the proposed rockburst risk-zone division method is reasonable. Therefore, the results of this study could serve as a reference for the division of rockburst risk zones.
Industry 4.0 in “Major Emerging Markets”: A Systematic Literature Review of Benefits, Use, Challenges, and Mitigation Strategies in Supply Chain Management
Authors: Alshahrani Saeed Turki
Published: October 2023

The extant literature does not provide consolidated knowledge on the use of Industry 4.0 in supply chains of emerging markets. This systematic literature review investigated the benefits, use, challenges, and mitigation measures related to Industry 4.0 technologies in supply chain management within thirteen “major emerging markets”. Industry 4.0 integrates technologies such as the Internet of Things (IoT), big data analytics, and cloud computing, and it offers tangible benefits for manufacturing and supply chains. However, its adoption faces significant obstacles, particularly in emerging economies. This study used the PSALSAR framework and PRISMA methodology to systematically review 87 peer-reviewed research articles on Industry 4.0 in the supply chain context of thirteen major emerging economies. Findings revealed that while IoT, big data, and artificial intelligence are frequently applied, other technologies such as cloud computing and robotics are underutilized. Key challenges identified include data integration, cyber-security, high upfront investment, weak policy, and business risks. Mitigation strategies proposed include the development of supportive policies, management backing, training, and improved data security. Tangible benefits such as sustainably using resources, reducing power use, enabling collaboration among supply chain partners, incorporating asset traceability, and minimizing meat contamination were evident. This research provides useful insights into the current status of Industry 4.0 adoption in emerging markets, helping stakeholders to navigate towards a more digitized, efficient future.
Constraints Inhibiting Farmers’ Adoption of Cattle Feedlots as a Climate-Smart Practice in Rural Communities of the Eastern Cape, South Africa: An In-Depth Examination
Authors: Slayi Mhlangabezi , Zhou Leocadia , Jaja Ishmael Festus
Published: October 2023

The adoption of climate-smart agricultural practices is crucial for enhancing resilience to climate change in rural communities, particularly in developing regions like the Eastern Cape, South Africa. This study provides an in-depth examination of the factors constraining farmers’ adoption of cattle feedlots as a climate-smart practice in the rural communities of the Eastern Cape. The research aims to identify the barriers and challenges that hinder the widespread adoption of cattle feedlots and understand the underlying factors contributing to the farmers’ decision-making processes. The study employed a mixed-methods approach, including surveys and interviews, to gather data from 250 farmers in rural communities of the Eastern Cape. The data were analyzed using regression analysis and thematic analysis to identify the key constraints inhibiting the adoption of cattle feedlots as a climate-smart strategy. The findings revealed several significant constraints that farmers faced in adopting cattle feedlots. Financial limitations, including limited access to credit and lack of financial resources, emerged as critical barriers. Infrastructure and resource constraints, such as inadequate water supply and electricity, hindered adoption. Knowledge and skills gaps, cultural and social factors, market limitations, and environmental considerations further contributed to the constraints experienced by farmers. To address these constraints, the study proposes interventions to promote the adoption of cattle feedlots as a climate-smart practice. These interventions include improving access to affordable financing options, providing capacity-building programs on feedlot management and climate-smart practices, disseminating information on feedlot benefits and best practices, developing the necessary infrastructure, strengthening market linkages, and creating a supportive policy environment. However, it is important to note the study’s limitations, such as the small sample size and the cross-sectional nature of the data, which may limit the generalizability of the findings. Further research is needed to validate and expand upon these findings in a broader context. Overall, this study provides valuable insights into the factors constraining farmers’ adoption of cattle feedlots as a climate-smart practice in the rural communities of the Eastern Cape, South Africa.
Microbial Fuel Cell Using a Novel Ionic-Liquid-Type Membrane-Cathode Assembly with Heterotrophic Anodic Denitrification for Slurry Treatment
Authors: Hernández-Fernández Adrián , Iniesta-López Eduardo , Garrido Yolanda , Ieropoulos Ioannis A. , Hernández-Fernández Francisco J.
Published: October 2023

In this paper, microbial fuel cell technology with heterotrophic anodic denitrification, based on a new membrane-cathode assembly, was tested for slurry treatment and bioenergy production. Slurry is used due to its high chemical oxygen demand and a high content of nutrient compounds of nitrogen which can contaminate soil and water. The new membrane-cathode assembly systems were based on different ammonium and phosphonium cations combined with chloride, bistriflimide, phosphate, and phosphinate anions and a non-noble catalyst composed of copper and cobalt mixed-valence oxides. The influence of ionic liquids on the catalytic membrane was studied. The best membrane-cathode assembly was based on the ionic liquid catalyst [MTOA+][Cl−]-CoCu which achieved 65% of the energy reached with the Pt-Nafion® system. The [MTOA+][Cl−]-CoCu system improved the water purification parameter, reducing the COD by up to 35%, the concentration of nitrates by up to 26%, and the organic nitrogen by up to 70% during the experiments. This novel membrane-cathode system allows for easier manufacturing, lower costs, and simpler catalysts than conventionally used in microbial fuel cells.
Peppers under Siege: Revealing the Prevalence of Viruses and Discovery of a Novel Potyvirus Species in Venezuela
Authors: Rodríguez-Román Eduardo , León Yrvin , Perez Yearlys , Amaya Paola , Mejías Alexander , Montilla Jose Orlando , Ortega Rafael , Zambrano Karla , Olivares Barlin Orlando , Marys Edgloris
Published: October 2023

Many plant virus outbreaks have been recorded in the last two decades, threatening food security around the world. During pepper production seasons in 2008, 2014, and 2022, virus outbreaks were reported from Lara (western) and Miranda (central) states in Venezuela. Three hundred seventy-three plants exhibiting virus-like symptoms were collected and tested for virus infection through reverse transcription PCR (RT-PCR). The most prevalent viruses during the 2008 surveys conducted in Lara were potato virus Y (PVY, 66.25%), cucumber mosaic virus (CMV, 57.50%), pepper mild mottle virus (PMMoV, 35%), alfalfa mosaic virus (AMV, 23.75%), and tobacco rattle virus (TRV, 17.50%). This survey revealed for the first time that pepper is a natural host of AMV and TRV in Venezuela. A further, divergent potyvirus isolate was also detected in 23.75% of pepper plants from Lara state. In 2014, a follow-up survey after virus outbreaks reported in Lara and Miranda states also detected this divergent potyvirus isolate in 21.68% of pepper plants, with tomato spotted wilt virus (TSWV) and PMMoV dominating the viral landscape (62.65 and 21.68% of tested plants, respectively). By comparison, the surveys revealed significant changes in viral community composition. The complete capsid protein (CP) sequence of the putative potyvirus was obtained from two pepper samples. According to the Potyvirus taxonomic criteria, these results suggest that the isolate represents a distinct virus species, for which we propose the name “pepper severe mottle virus” (PepSMoV). Virus outbreaks could be attributed to agricultural and environmental factors, such as climate change, the use of wastewater, the use of uncertified seeds, misuse of agricultural chemicals, transmission with food trade networks, and the development of new viral strains due to mutations and recombination and pathogen spillover. This study demonstrates the value of knowledge of the prevalence and distribution of viral species to recommend virus-resistant cultivars to replace susceptible ones, especially in virus hotspot areas.
An Adaptive Mesh Refinement–Rotated Lattice Boltzmann Flux Solver for Numerical Simulation of Two and Three-Dimensional Compressible Flows with Complex Shock Structures
Authors: Huang Xiaoyingjie , Chen Jiabao , Zhang Jun , Wang Long , Wang Yan
Published: October 2023

An adaptive mesh refinement–rotated lattice Boltzmann flux solver (AMR-RLBFS) is presented to simulate two and three-dimensional compressible flows with complex shock structures. In the method, the RLBFS, which has a strong shock-capturing capability and can effectively eliminate the shock instability phenomenon, is applied to solve the flow filed by reconstructing the fluxes at each cell interface adaptively with the mesoscopic lattice Boltzmann model. To locally and dynamically improve the resolution of intricate shock structures and optimize the required computational resources, a block-structured adaptive mesh refinement (AMR) technique is introduced. The validity and effectiveness of the proposed method are confirmed through a range of two and three-dimensional numerical cases, including the shock tube problem, the four-wave Riemann problem, explosion within a rectangular box, and the vorticity induced by a shock. The results obtained using the AMR-RLBFS exhibit excellent agreement with published data and demonstrate high accuracy in capturing complex shock structures. The computational efficiency of the AMR-RLBFS can be also improved significantly compared to the RLBFS on uniform grids. Furthermore, the numerical outcomes underscore the capability of the AMR-RLBFS to eliminate shock instability effects while efficiently capturing a broader spectrum of small-scale vertical structures. These findings highlight the ability of AMR-RLBFS to improve the computational efficiency and capture intricate shock structures effectively, making it a valuable tool for studying a wide range of compressible flows from aerodynamics to astrophysics.
On Sharp Bounds of Local Fractional Metric Dimension for Certain Symmetrical Algebraic Structure Graphs
Authors: Alali Amal S. , Ali Shahbaz , Adnan Muhammad , Torres Delfim F. M.
Published: October 2023

The smallest set of vertices needed to differentiate or categorize every other vertex in a graph is referred to as the graph’s metric dimension. Finding the class of graphs for a particular given metric dimension is an NP-hard problem. This concept has applications in many different domains, including graph theory, network architecture, and facility location problems. A graph G with order n is known as a Toeplitz graph over the subset S of consecutive collections of integers from one to n, and two vertices will be adjacent to each other if their absolute difference is a member of S. A graph G(Zn) is called a zero-divisor graph over the zero divisors of a commutative ring Zn, in which two vertices will be adjacent to each other if their product will leave the remainder zero under modulo n. Since the local fractional metric dimension problem is NP-hard, it is computationally difficult to identify an optimal solution or to precisely determine the minimal size of a local resolving set; in the worst case, the process takes exponential time. Different upper bound sequences of local fractional metric dimension are suggested in this article, along with a comparison analysis for certain families of Toeplitz and zero-divisor graphs. Furthermore, we note that the analyzed local fractional metric dimension upper bounds fall into three metric families: constant, limited, and unbounded.
A Symmetrical Approach to Brain Tumor Segmentation in MRI Using Deep Learning and Threefold Attention Mechanism
Authors: Rahman Ziaur , Zhang Ruihong , Bhutto Jameel Ahmed
Published: October 2023

The symmetrical segmentation of brain tumor images is crucial for both clinical diagnosis and computer-aided prognosis. Traditional manual methods are not only asymmetrical in terms of efficiency but also prone to errors and lengthy processing. A significant barrier to the process is the complex interplay between the deep learning network for MRI brain tumor imaging and the harmonious compound of both local and global feature information, which can throw off the balance in segmentation accuracy. Addressing this asymmetry becomes essential for precise diagnosis. In answer to this challenge, we introduce a balanced, end-to-end solution for brain tumor segmentation, incorporating modifications that mirror the U-Net architecture, ensuring a harmonious flow of information. Beginning with symmetric enhancement of the visual quality of MRI brain images, we then apply a symmetrical residual structure. By replacing the convolutional modules in both the encoder and decoder sections with deep residual modules, we establish a balance that counters the vanishing gradient problem commonly faced when the network depth increases. Following this, a symmetrical threefold attention block is integrated. This addition ensures a balanced fusion of local and global image features, fine-tuning the network to symmetrically discern and learn essential image characteristics. This harmonious integration remarkably amplifies the network’s precision in segmenting MRI brain tumors. We further validate the equilibrium achieved by our proposed model using three brain tumor segmentation datasets and four metrics and by juxtaposing our model against 21 traditional and learning-based counterparts. The results confirm that our balanced approach significantly elevates performance in the segmentation of MRI brain tumor images without an asymmetrical increase in computational time.
Elaborating the Occurrence and Distribution of Per- and Polyfluoroalkyl Substances in Rivers and Sediment around a Typical Aging Landfill in China
Authors: Quan Bingxu , Tang Jiawei , Niu Xiameng , Su Peidong , Zhang Zhimin , Yang Yitao
Published: October 2023

Per- and polyfluoroalkyl substances (PFASs) are bioaccumulative and widely distributed persistent organic pollutants (POPs). Understanding the distribution of and ecological risks posed by PFASs is critical, particularly for PFAS emissions and accumulation from a common urban pollution source. The transformation characteristics and ecological risks of PFASs from a typical aging municipal landfill leachate were systematically monitored and assessed over five years in this study. The results showed that the total PFAS concentrations (ΣPFASs) in the rivers were between 26.4 and 464.3 ng/L, whereas in sediment, ΣPFASs ranged from 9.5 to 58.5 ng/g (w/w). The presence of perfluorooctanoic acid (PFOA) was the most prominent PFAS in both water (39.4–152.3 ng/L) and sediment (1.1–56.1 ng/g). In a five-year monitoring study, the concentration of PFASs in the aging landfill decreased by 23.3%, with higher mean concentrations observed during summer (307.6 ng/L) compared to winter (250.4 ng/L). As for the pollution distribution, the suspended particulate matter–water partition coefficient (log Kd) of carboxylic acid (PFCAs) and perfluoroalkane sulfonic acids (PFSAs) ranged from 1.53 to 2.65, and from 1.77 to 2.82, respectively. PFSAs and long-chain PFCAs exhibited a greater propensity for sediment association compared to short-chain PFCAs. An ecological risk assessment of four typical PFASs, PFOA, perfluorooctane sulfonate (PFOS), perfluorobutanoic acid (PFBA), and perfluorobutane sulfonic acid (PFBS), utilizing the hazard quotient method revealed that the rivers surrounding the typical aging landfill exhibited a low contamination risk for PFOA, while no ecological risks were associated with the other three FPASs. This study contributes to an enhanced comprehension of the occurrence, distribution, and risk of PFASs in the rivers in rivers and sediment surrounding a typical aging landfill site in China, thereby providing crucial reference information for ensuring water quality safety.
Technosols Derived from Mining, Urban, and Agro-Industrial Waste for the Remediation of Metal(loid)-Polluted Soils: A Microcosm Assay
Authors: Aguilar-Garrido Antonio , Romero-Freire Ana , Paniagua-López Mario , Martínez-Garzón Francisco Javier , Martín-Peinado Francisco José , Sierra-Aragón Manuel
Published: October 2023

This study evaluated the effectiveness of six Technosols designed for the remediation of polluted soils (PS) by metal(loid)s at physicochemical, biological, and ecotoxicological levels and at a microcosm scale. Technosols T1–T6 were prepared by combining PS with a mix of organic and inorganic wastes from mining, urban, and agro-industrial activities. After two months of surface application of Technosols on polluted soils, we analysed the soil properties, metal(loid) concentration in total, soluble and bioavailable fractions, soil enzymatic activities, and the growth responses of Trifolium campestre and Lactuca sativa in both the Technosols and the underlying polluted soils. All Technosols improved the unfavourable conditions of polluted soils by neutralising acidity, increasing the OC, reducing the mobility of most metal(loid)s, and stimulating both the soil enzymatic activities and growths of T. campestre and L. sativa. The origin of organic waste used in the Technosols strongly conditioned the changes induced in the polluted soils; in this sense, the Technosols composed of pruning and gardening vermicompost (T3 and T6) showed greater reductions in toxicity and plant growth than the other Technosols composed with different organic wastes. Thus, these Technosols constitute a potential solution for the remediation of persistent polluted soils that should be applied in large-scale and long-term interventions to reinforce their feasibility as a cost-effective ecotechnology.
Advancing Mycotoxin Detection: Multivariate Rapid Analysis on Corn Using Surface Enhanced Raman Spectroscopy (SERS)
Authors: Gabbitas Allison , Ahlborn Gene , Allen Kaitlyn , Pang Shintaro
Published: October 2023

Mycotoxin contamination on food and feed can have deleterious effect on human and animal health. Agricultural crops may contain one or more mycotoxin compounds; therefore, a good multiplex detection method is desirable to ensure food safety. In this study, we developed a rapid method using label-free surface-enhanced Raman spectroscopy (SERS) to simultaneously detect three common types of mycotoxins found on corn, namely aflatoxin B1 (AFB1), zearalenone (ZEN), and ochratoxin A (OTA). The intrinsic chemical fingerprint from each mycotoxin was characterized by their unique Raman spectra, enabling clear discrimination between them. The limit of detection (LOD) of AFB1, ZEN, and OTA on corn were 10 ppb (32 nM), 20 ppb (64 nM), and 100 ppb (248 nM), respectively. Multivariate statistical analysis was used to predict concentrations of AFB1, ZEN, and OTA up to 1.5 ppm (4.8 µM) based on the SERS spectra of known concentrations, resulting in a correlation coefficient of 0.74, 0.89, and 0.72, respectively. The sampling time was less than 30 min per sample. The application of label-free SERS and multivariate analysis is a promising method for rapid and simultaneous detection of mycotoxins in corn and may be extended to other types of mycotoxins and crops.
Superluminal Local Operations in Quantum Field Theory: A Ping-Pong Ball Test
Authors: Much Albert , Verch Rainer
Published: October 2023

It is known that, in quantum field theory, localized operations, e.g., given by unitary operators in local observable algebras, may lead to non-causal, or superluminal, state changes within their localization region. In this article, it is shown that, both in quantum field theory as well as in classical relativistic field theory, there are localized operations which correspond to “instantaneous” spatial rotations (leaving the localization region invariant) leading to superluminal effects within the localization region. This shows that “impossible measurement scenarios” which have been investigated in the literature, and which rely on the presence of localized operations that feature superluminal effects within their localization region, do not only occur in quantum field theory, but also in classical field theory.
Novel Epitope Mapping of African Swine Fever Virus pI215L Protein Using Monoclonal Antibodies
Authors: Gao Yanni , Jiang Xiaolin , Yang Xing , Zhang Keshan , Jiang Ping , Bai Juan
Published: October 2023

The African swine fever virus (ASFV) is one of the most important pathogens that causes huge damage to worldwide swine production. The pI215L protein is found within the virion and expressed at a high level in infected porcine alveolar macrophages (PAMs), indicating a possible role of pI215L protein in ASFV detection and surveillance. In the present study, female BALB/c mice (5–6-week-old) were immunized with rpI215L protein, and six hybridomas, 1C1, 2F6, 2F10, 3C8, 5E1 and 5B3, steadily secreted anti-pI215L monoclonal antibodies (mAbs). Among them, 1C4, 5E1, and 5B3 had the IgG1 isotype with a Lambda light chain, 2F10 and 3C8 had the IgG1 isotype with a Kappa light chain, and 2F6 had the IgG2a isotype with a Kappa light chain. Western blot showed a good reactivity of the six mAbs against ASFV. Eight truncated polypeptides were produced for epitope mapping. Two novel B cell epitopes, 67LTFTSEMWHPNIYS80 and 167IEYFKNAASN176, were identified by the mAbs. Further analysis revealed that 2F6 mAb could be widely used in ASFV surveillance and 5B3 mAb might serve as a tool in the distinguishment of different ASFV genotypes. This study provides tools of monoclonal antibodies for further study of I215L function and contributes to the development of serological diagnosis and vaccine research.
Development of a Real-Time PCR Assay for the Detection of the Phlebovirus Fermo Virus
Authors: Calzolari Mattia , Russo Simone , Marzani Katia , Dalmonte Gastone , Ricchi Matteo , Bonilauri Paolo
Published: October 2023

Fermo virus is a Phlebovirus that is increasingly reported in sand flies from northern Italy. The natural cycle is not fully understood, but the virus has been detected by direct methods only in sand flies. Although there is serological evidence that it can infect vertebrates, the virus has not been directly detected in animals or humans. Here, we have developed and reported a specific real-time PCR for Fermo virus. The availability of the described method will be useful to characterize the epidemiology of the FERV, ensuring, compared to previously available protocols, a more sensitive detection in insects and the possible detection in vertebrates to evaluate the presence of reservoirs and the pathogenic potential of the virus in humans or animals.
Recombinant Porcine Interferon-α Decreases Pseudorabies Virus Infection
Authors: Song Bowen , Wei Wenkang , Liu Xueyi , Huang Yaoyao , Zhu Shuaiqi , Yi Lin , Eerdunfu  , Ding Hongxing , Zhao Mingqiu , Chen Jinding
Published: October 2023

Interferon (IFN) is a cell-secreted cytokine possessing biological activities including antiviral functioning, immune regulation, and others. Interferon-alpha (IFN-α) mainly derives from plasmacytoid dendritic cells, which activate natural killer cells and regulate immune responses. IFN-α responds to the primary antiviral mechanism in the innate immune system, which can effectively cure acute infectious diseases. Pseudorabies (PR) is an acute infectious disease caused by pseudorabies virus (PRV). The clinical symptoms of PRV are as follows: reproductive dysfunction among pregnant sows and high mortality rates among piglets. These pose a severe threat to the swine industry. Related studies show that IFN-α has broad applications in preventing and treating viral diseases. Therefore, a PRV mouse model using artificial infection was established in this study to explore the pathogenic effect of IFN-α on PRV. We designed a sequence with IFN-α4 (M28623, Genbank) and cloned it on the lentiviral vector. CHO-K1 cells were infected and identified using WB and RT-PCR; a CHO-K1 cell line with a stable expression of the recombinant protein PoIFN-α was successfully constructed. H&E staining and virus titer detection were used to investigate the recombinant protein PoIFN-α’s effect on PR in BALB/c mice. The results show that the PoIFN-α has a preventive and therapeutic impact on PR. In conclusion, the recombinant protein can alleviate symptoms and reduce the replication of PRV in vivo.