bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of Polycyclic Aromatic Hydrocarbons Using Magnetic Three-Dimensional Graphene Solid-Phase Extraction Coupled with Gas Chromatography–Mass Spectrometry
Authors: Sereshti Hassan , Karimi Mahsa , Karami Sajad , Mahpishanian Shokouh , Esmaeili Bidhendi Mehdi , Rezania Shahabaldin , Mojiri Amin , Kamyab Hesam , Rashidi Nodeh Hamid
Published: November 2023

In this study, a composite material consisting of three-dimensional graphene aerogel and iron oxide nanoparticles (3DG/Fe3O4) was created and utilized for the purpose of magnetic solid-phase extraction (MSPE) of thirteen polycyclic aromatic hydrocarbon (PAH) compounds via gas chromatography–mass spectrometry/selected ion monitoring (GC-MS/SIM) analysis. The synthesized adsorbent underwent a range of characterization techniques, including scanning electron microscopy, vibrating sample magnetometry, Raman spectroscopy, X-ray diffraction, Brunauer–Emmett–Teller, Fourier transform-infrared spectroscopy, and Barrett–Joyner–Halenda techniques, to examine its properties and morphology. The synthesized adsorbent integrates the benefits of superior adsorption capacity from modified graphene oxide (GO) with the magnetic separability of magnetite microparticles, resulting in a high adsorption capacity with easy separation from sample solutions. The efficiency of the proposed method was optimized and modeled using a central composite design (CCD), which considered the primary factors influencing it. The optimal conditions were obtained as the adsorbent dosage of 10 mg, the extraction time of 4 min, and the salt concentration of 3% w/v. The limit of detection for the target PAHs was established to range from 0.016 to 0.2 ng mL−1 in optimal conditions, exhibiting a signal-to-noise ratio of 3. The linear dynamic range spanned from 5 to 100 ng mL−1, with determination coefficients (R2) ranging from 0.9913 to 0.9997. The intra- and inter-day precisions were calculated as relative standard deviations (RSDs) equal to 3.9% and 4.7%, respectively. The proposed method was successfully applied to the determination of PAHs in water samples (tap, river, and rainwater), and recoveries in the range of 71–110% (RSDs < 5.2%, n = 3) were obtained.
Simultaneous Quantification Method of Flavonoids in Jeju Native Citrus from Different Harvest Times Using a High-Performance Liquid Chromatography–Diode Array Detector (HPLC–DAD)
Authors: Hyeon Hyejin , Hyun Ho Bong , Kim Sung Chun , Go Boram , Yoon Seon-A , Jung Yong-Hwan , Ham Young-Min
Published: November 2023

In Jeju-native Citrus, flavonoids are the main contributors to the various types of biological activity, such as antioxidant, antitumor, and anti-inflammatory activity. Thus, we developed simultaneous quantification methods for the analysis of ten bioactive flavonoids in Jeju Citrus fruits (Dangyuja, Gamja, Jigak, Sadugam, and Soyuja) harvested at six different time points using a high-performance liquid chromatography–diode array detector (HPLC-DAD). Separation was performed using a flow rate of 0.8 mL/min, a column temperature of 40 °C, a mobile phase buffer of 0.5% acetic acid, and a detection wavelength of 278 nm. The established analytical method showed good linearity (R2 ≥ 0.9997), precision (inter-day < 0.599%, intra-day < 0.055%), and accuracy (recoveries 92.30–108.80%). The HPLC–DAD method was subsequently applied to analyze flavonoids in Citrus samples. Overall, the quantification results indicated that the compositions and content of flavonoids differed for each Citrus species. The harvesting period also influenced the changes in flavonoid content within each Citrus species. The analytical results with chemometrics revealed that higher flavonoid levels in early-harvested Citrus were derived from the improved fruit size and reduced flavonoid synthesis during maturation. This study provides a practical and reliable method for the analysis of ten flavonoids that can be further utilized in the quality assessment of Jeju Citrus.
“The Only Thing We Have to Fear Is Fear Itself”: Predicting College Students’ Voting Behavior Using the Extended Parallel Process Model
Authors: Roberto Anthony J. , Mattson L. D. , Von Feldt Paige A. , Zhou Xin
Published: November 2023

This longitudinal study examines how well the EPPM predicts and explains college students’ voting behavior. One-hundred-and-seventy-eight undergraduate students filled out a survey at two points in time: (1) four weeks before and (2) one week after the 2022 midterm election. As hypothesized, the EPPM accurately predicted danger control outcomes (i.e., severity, susceptibility, self-efficacy, and response efficacy predicted voting intentions, and voting intentions predicted voting behavior). The EPPM also predicted one fear control outcome (though only the path between severity and fear was significant). More specifically, the EPPM explained 45.7% of the variance in intention, 81.7% of the variance in behavior, 77% of the variance in contesting, and 33.6% of the variance in suppression.
Effects of Vermicompost on Soil and Plant Health and Promoting Sustainable Agriculture
Authors: Oyege Ivan , Balaji Bhaskar Maruthi Sridhar
Published: November 2023

This review highlights the potential of vermicompost and its derived products as sustainable and eco-friendly solutions for enhancing production and pest management in grain crops. It assesses their impact comprehensively on crops such as maize, wheat, barley, rice, and pearl millet. Vermicompost improves soil quality, increases nutrient availability, boosts crop productivity, and enhances pest and disease tolerance. It acts as an organic fertilizer, enriching the soil with essential nutrients, humic acids, growth-regulating hormones, and enzymes, improving plant nutrition, photosynthesis, and overall crop quality. Furthermore, vermicompost shows promise in mitigating soil degradation and sequestering organic carbon while demonstrating the potential for pest management, including effectiveness against pests like fall armyworm (Spodoptera frugiperda). This review emphasizes the importance of integrated nutrient management and proper application strategies to maximize the benefits of vermicompost in grain crops. Factors such as the form and timing of application, efficacy against specific pests, and economic viability for different farming scales are discussed. Understanding these factors is crucial for successfully implementing and adopting vermicompost-based pest management strategies in grain crops. This review also explores the potential of vermicomposting as an eco-friendly and cost-effective solution to remediate organic contaminants, emerging contaminants, personal-care and pharmaceutical products, and microplastics. The review further identifies knowledge gaps and highlights the need for future studies to effectively utilize vermicompost and its derived products in cereal production for sustainable agriculture, contributing to global food security.
Differences in Relaxation and Imagery among NCAA Division I Sport Types
Authors: Warfield Elizabeth , Esposito Philip , Braun-Trocchio Robyn
Published: November 2023

Athletes use psychological skills such as imagery and relaxation to decrease stress, cope with competitive anxiety, and achieve an optimal state of arousal. There is conflicting literature on how team and individual sport athletes use these skills, with some saying that individual sport athletes have better capabilities and others saying team sport athletes use imagery more frequently. The current study analyzed sport type differences in the use of relaxation and performance imagery among NCAA Division I (DI) athletes. This study included 117 NCAA DI athletes, including team sport (n = 72) and individual sport (n = 45). Participants completed a modified version of The Deliberate Relaxation for Sport Survey through Qualtrics. Results indicated there is a statistically significant difference in the type of relaxation technique used based on the individual’s sport type. Team sport athletes used muscle relaxation (p = 0.034), eastern relaxation (p = 0.014), and stretching (p = 0.020) more frequently than individual sport athletes. Additionally, individual sport athletes used performance imagery more often for mental focus than team sport athletes (p = 0.012). There were no differences between sport types in the level of deliberate practice of relaxation and performance imagery. Athletes used a variety of methods to learn both imagery and relaxation skills and have been using these for an average of four years. The majority of participants (n = 67) did not work with a sport psychology professional, but their school has one. This study supports the use of individualized intervention programs to help athletes use relaxation and imagery in the most effective ways for their performances.
Self-Organizing Topological Multilayer Perceptron: A Hybrid Method to Improve the Forecasting of Extreme Pollution Values
Authors: López-Gonzales Javier Linkolk , Gómez Lamus Ana María , Torres Romina , Canas Rodrigues Paulo , Salas Rodrigo
Published: November 2023

Forecasting air pollutant levels is essential in regulatory plans focused on controlling and mitigating air pollutants, such as particulate matter. Focusing the forecast on air pollution peaks is challenging and complex since the pollutant time series behavior is not regular and is affected by several environmental and urban factors. In this study, we propose a new hybrid method based on artificial neural networks to forecast daily extreme events of PM2.5 pollution concentration. The hybrid method combines self-organizing maps to identify temporal patterns of excessive daily pollution found at different monitoring stations, with a set of multilayer perceptron to forecast extreme values of PM2.5 for each cluster. The proposed model was applied to analyze five-year pollution data obtained from nine weather stations in the metropolitan area of Santiago, Chile. Simulation results show that the hybrid method improves performance metrics when forecasting daily extreme values of PM2.5.
A Case Study on Smart Grid Technologies with Renewable Energy for Central Parts of Hamburg
Authors: Bouchard Pierre , Voß Stefan , Heilig Leonard , Shi Xiaoning
Published: November 2023

Globally, efforts are made to balance energy demands and supplies while reducing CO2 emissions. Germany, in its transition to renewable energies, faces challenges in regulating its energy supply. This study investigates the impact of various technologies, including energy storage solutions, peak shaving, and virtual buffers in a smart energy grid on a large scale. Real-time energy supply and demand data are collected from the Port of Hamburg and HafenCity in Germany to analyze the characteristics of different technologies such as load shifting of reefer containers and private electric vehicles’ energy, as well as pumped hydro storage. Through simulations, we assess the usability of renewable energies in a smart grid with versatile energy demands and determine the effects of peak shaving, storage solutions, and virtual buffers on uncertain energy supply. Our case study reveals that integrating smart grid technologies can reduce the overproduction of renewable energies needed to prevent blackouts from 95% to 65% at the HafenCity and the Port of Hamburg. Notably, large, reliable, and predictable energy consumers like the Port of Hamburg play a vital role in managing the uncontrollable nature of renewables, resulting in up to 31% cost savings for new infrastructure.
Healthcare Sustainability: Hospitalization Rate Forecasting with Transfer Learning and Location-Aware News Analysis
Authors: Chen Jing , Creamer Germán G. , Ning Yue , Ben-Zvi Tal
Published: November 2023

Monitoring and forecasting hospitalization rates are of essential significance to public health systems in understanding and managing overall healthcare deliveries and strategizing long-term sustainability. Early-stage prediction of hospitalization rates is crucial to meet the medical needs of numerous patients during emerging epidemic diseases such as COVID-19. Nevertheless, this is a challenging task due to insufficient data and experience. In addition, relevant existing work neglects or fails to exploit the extensive contribution of external factors such as news, policies, and geolocations. In this paper, we demonstrate the significant relationship between hospitalization rates and COVID-19 infection cases. We then adapt a transfer learning architecture with dynamic location-aware sentiment and semantic analysis (TLSS) to a new application scenario: hospitalization rate prediction during COVID-19. This architecture learns and transfers general transmission patterns of existing epidemic diseases to predict hospitalization rates during COVID-19. We combine the learned knowledge with time series features and news sentiment and semantic features in a dynamic propagation process. We conduct extensive experiments to compare the proposed approach with several state-of-the-art machine learning methods with different lead times of ground truth. Our results show that TLSS exhibits outstanding predictive performance for hospitalization rates. Thus, it provides advanced artificial intelligence (AI) techniques for supporting decision-making in healthcare sustainability.
Analysis of the Spatial and Temporal Evolution of China’s Energy Carbon Emissions, Driving Mechanisms, and Decoupling Levels
Authors: Ji Jingyi , Li Chao , Ye Xinyi , Song Yuelin , Lv Jiehua
Published: November 2023

Excessive carbon emissions will cause the greenhouse effect and global warming, which is not conducive to environmental protection and sustainable development. In order to realize the goal of “carbon peak and carbon neutrality” as soon as possible, this paper utilizes the methodology provided by the IPCC to measure the carbon emissions and carbon intensity of China’s energy consumption. The classification method of carbon emission and the kernel density function method are used to explore the spatial and temporal evolution of regional carbon emissions. Based on the Log Mean Divided Index (LMDI) method, the drivers of China’s energy carbon emissions are measured. Based on the Tapio index function and the catch-up decoupling model, the decoupling status of Chinese provinces and the development gap with the benchmark provinces are examined. The results show that (1) China’s total energy carbon emissions show a “rising-declining-rising” trend from 2005 to 2021, and reach the first peak in 2013, totaling 1,484,984.406 million metric tons. China’s Hebei, Shanxi, and Shandong provinces have the highest energy carbon emissions. (2) China’s energy carbon emissions are influenced by multiple factors, and the contribution of each factor to energy carbon emissions is in the following order: economic development effect > energy intensity effect > energy structure effect > population size effect. (3) China’s catch-up provinces develop their economies at the expense of the environment and energy consumption.
Green Supply Chain Management Research Trends and Linkages to UN Sustainable Development Goals
Authors: Raman Raghu , Sreenivasan Aswathy , Ma Suresh , Patwardhan Anand , Nedungadi Prema
Published: November 2023

Growing awareness about environmental responsibility among businesses and policymakers has increased interest in Green Supply Chain Management (GSCM). For the first time, using the SDG mapping algorithms, this article focused on 7009 publications from 2013 to 2022 mapped explicitly to 17 SDGs. This study uses bibliometric and science mapping techniques to create a detailed mapping between GSCM research and SDGs. This study created an SDG citation network to show how specific SDGs are related to GSCM practices. The most mapped SDGs in this study are SDG 9 (Industry, Innovation, and Infrastructure), SDG 12 (Responsible Consumption and Production), and SDG 17 (Partnership for the Goals). Our results showed that GSCM research mainly focuses on three thematic areas: industry 4.0 and sustainable supply chains, GSCM practice coordination, and sustainable environmental policy management. This also includes integrating the circular economy into GSCM, sustainable sourcing, supply chain resilience, digital transformation in GSCM for better environmental performance, and the social impact of GSCM. A shift towards integrating sustainability into supply chain processes has been found. Environmental management, performance monitoring, and new technologies like Industry 4.0 and AI have been used to support the SDGs. International interest and collaboration in GSCM research can be seen from the bibliographic coupling study covering countries like Europe, Western Countries, the Middle East, Southeast Asia, and Eastern Europe. This study shows how GSCM can directly address global challenges identified by the United Nations by mapping GSCM research to specific SDGs.
Risk Assessment of Domestic Wastewater Treatment System Based on Constructed Wetlands
Authors: Pérez Yvelisse , García-Cortes Daniel , Torres-Valle Antonio , Jáuregui-Haza Ulises
Published: November 2023

Risk assessment methods vary and have been applied to areas such as environmental, technological, and occupational safety, adapting to the complexities of the subjects under study. The objective of this work is to conduct a risk analysis of a domestic wastewater treatment system based on constructed wetlands (CW) and to evaluate actions to reduce the operational risk of the studied installation. The approach used is the three-dimensional risk matrix, which is a simplified version of the probabilistic risk evaluation method, making it more accessible and allowing for broader application. To apply the risk matrix method to a wastewater system based on CW, it was necessary to modify a risk model. This modification involved creating a process map and identifying accidental scenarios or sequences within each stage, including their initiating events, defenses, and consequences. The results enabled the identification of the most critical initiating events and defenses. Notably, human factors emerged as the primary contributors to the risk associated with wetland operation. The findings from this study can be used to enhance wetland security, including the prioritization of controls for the most critical defenses identified in this research.
Green Cooperation Strategy of Prefabricated Building Supply Chain Based on Smart Construction Management Platform
Authors: Yu Zhaoqing , Sun Jiakun
Published: November 2023

Green technological innovation in the prefabricated building supply chain (PBSC) is an important way to realize the sustainable development of the construction industry. However, the competitive environment and the green input costs reduce the willingness of PBSC firms to improve the green technology level. This paper constructs a PBSC consisting of a smart construction management platform (SCMP), a contractor, and prefabricated-component manufacturers (PCMs) to explore green cooperation strategies in the PBSC. Stackelberg game models are constructed and the green technology level and PBSC profit under different cooperation strategies are examined. The study shows that the optimal service commission of the SCMP increases with the cost parameter of green technology and the intensity of competition between PCMs. However, the green technology level decreases with the competition. The integration strategy does not necessarily achieve the highest level of green technology. The horizontal cooperation among competing PCMs is not conducive to improving the green technology level, but PCMs always have incentives to form horizontal cooperative alliances to achieve Pareto improvement under certain conditions. For the SCMP, the vertical cooperation strategy with PCMs is the most favorable, but for the PBSC, the system profit under the integration strategy is the most profitable. This study enriches the theoretical foundation of the PBSC and provides theoretical guidance for green cooperation strategies in PBSCs.
Mitigating Greenhouse Gas Emissions from Crop Production and Management Practices, and Livestock: A Review
Authors: Kabange Nkulu Rolly , Kwon Youngho , Lee So-Myeong , Kang Ju-Won , Cha Jin-Kyung , Park Hyeonjin , Dzorkpe Gamenyah Daniel , Shin Dongjin , Oh Ki-Won , Lee Jong-Hee
Published: November 2023

Agriculture is the second most important greenhouse gas (GHG: methane (CH4) and nitrous oxide (N2O) emissions)-emitting sector after the energy sector. Agriculture is also recognized as the source and sink of GHGs. The share of agriculture to the global GHG emission records has been widely investigated, but the impact on our food production systems has been overlooked for decades until the recent climate crisis. Livestock production and feed, nitrogen-rich fertilizers and livestock manure application, crop residue burning, as well as water management in flood-prone cultivation areas are components of agriculture that produce and emit most GHGs. Although agriculture produces 72–89% less GHGs than other sectors, it is believed that reducing GHG emissions in agriculture would considerably lower its share of the global GHG emission records, which may lead to enormous benefits for the environment and food production systems. However, several diverging and controversial views questioning the actual role of plants in the current global GHG budget continue to nourish the debate globally. We must acknowledge that considering the beneficial roles of major GHGs to plants at a certain level of accumulation, implementing GHG mitigation measures from agriculture is indeed a complex task. This work provides a comprehensive review of agriculture-related GHG production and emission mechanisms, as well as GHG mitigation measures regarded as potential solutions available in the literature. This review also discusses in depth the significance and the dynamics of mitigation measures regarded as game changers with a high potential to enhance, in a sustainable manner, the resilience of agricultural systems. Some of the old but essential agricultural practices and livestock feed techniques are revived and discussed. Agricultural GHG mitigation approaches discussed in this work can serve as game changers in the attempt to reduce GHG emissions and alleviate the impact of climate change through sustainable agriculture and informed decision-making.
Lean and Sustainable Supplier Selection in the Furniture Industry
Authors: Ince Melike Nur , Tasdemir Cagatay , Gazo Rado
Published: November 2023

The furniture manufacturing sector faces intricate challenges in pioneering sustainable supply chains, particularly with lean and sustainable supplier selection. This study focused on integrating key performance indicators (KPIs) associated with lean philosophy and sustainability into multi-criteria decision-making (MCDM) methodologies. The study methodically evaluated 18 criteria spanning economic, environmental, and social dimensions to discern supplier suitability in both leanness and sustainability realms. Through the ENTROPY method, weights were systematically assigned to these criteria. Subsequently, Fuzzy ARAS and Fuzzy TOPSIS methods were adeptly employed to comparatively assess supplier options. Noteworthy findings included the paramount importance of the distance to the customer and labor practices in supplier selection. The quality level, however, carried the least weight, mainly due to comparable performance scores among alternatives. Consistently, Fuzzy ARAS and Fuzzy TOPSIS results converged to pinpoint Supplier 2 as the optimal choice, reflecting its superior Ki and CCi metrics. Central to this research was the introduction of a structured and holistic framework for lean and sustainable supplier selection, a significant leap forward that promises to be an invaluable asset for practitioners and scholars in the furniture industry, supply chain management, multi-criteria decision-making, and policymaking.
DFT and MCDS Outcome for a Comparative Analysis of NO, NO2, SO, SO2 and SO3 Gas Adsorption onto a NaMgPO4 (033) Surface
Authors: Attarki Jamal , Khnifira Malika , Boumya Wafaa , Hajjaoui Hind , Mahsoune Anass , Sadiq M’hamed , Achak Mounia , Barka Noureddine , Abdennouri Mohamed
Published: November 2023

The research purpose of this work is to examine the adsorption interaction of gaseous molecules (GMs), such as NO, NO2, SO, SO2, and SO3, with the surface of sodium magnesium phosphate NaMgPO4 (033), in a neutral medium, using two different computational methods: density functional theory (DFT) and Monte Carlo dynamic simulation (MCDS). Various quantum and dynamic descriptors, such as global and local quantum descriptors and the radial distribution function (RDF), are also evaluated and discussed. The data obtained revealed that the NO2 molecule has a small energy gap (0.363 eV) when compared to the other molecules, which means that it is highly reactive and is liable to adsorb, or stick, to the surface of NaMgPO4 (033). Furthermore, this NO2 molecule exhibits good adsorption in aqueous media, returning to the lowest global hardness value (0.1815 eV). MCDS predicted adsorption energies of −874.03, −819.94, −924.81, −876.33, and −977.71 kcal/mol for NO, NO2, SO, SO2, and SO3, respectively. These energies are negative, implying that adsorption occurs spontaneously. Thus, the side views indicated which SO, NO, and SO3 molecules are adsorbed in parallel to NaMgPO4 and the other SO2 and NO2 molecules are adsorbed horizontally. Eventually, the theoretical results reveal that the studied gaseous molecules interact strongly with NaMgPO4. The result obtained by radial distribution function (RDF) analysis for all complexes below 3.5 Å confirm that the adsorption is of the chemi1cal type.
Weight Optimization Decision Algorithm in (p,q)-Rung Probabilistic Hesitant Orthopair Fuzzy Environments
Authors: Bao Jinyan , Kong Xiangzhi
Published: November 2023

Aiming at the fuzzification of a decision environment and the challenge of determining the weights associated with the interaction among decision-makers, this study offers an original method for (p,q)-rung probabilistic hesitant orthopair fuzzy multi-objective group decision-making, which is founded on the weight optimization principle. Firstly, the notion of a probabilistic hesitant fuzzy set is expanded to a (p,q)-rung. Secondly, the determination of subjective and objective weights is accomplished through the utilization of the Analytic Network Process (ANP) and the Entropy Method. According to the degree of deviation and dispersion of each weight, an optimal objective function is constructed, and the neural network is used to iteratively solve for the best scheme of the comprehensive weight. Subsequently, the Elimination Et Choice Translating Reality (ELECTRE) approach was refined and applied to decision-making in the (p,q)-rung probabilistic hesitant orthopair fuzzy environment. Finally, comparative analysis was used to demonstrate the new method’s effectiveness and superiority.
Eigenproblem Basics and Algorithms
Authors: Jäntschi Lorentz
Published: November 2023

Some might say that the eigenproblem is one of the examples people discovered by looking at the sky and wondering. Even though it was formulated to explain the movement of the planets, today it has become the ansatz of solving many linear and nonlinear problems. Formulation in the terms of the eigenproblem is one of the key tools to solve complex problems, especially in the area of molecular geometry. However, the basic concept is difficult without proper preparation. A review paper covering basic concepts and algorithms is very useful. This review covers the basics of the topic. Definitions are provided for defective, Hermitian, Hessenberg, modal, singular, spectral, symmetric, skew-symmetric, skew-Hermitian, triangular, and Wishart matrices. Then, concepts of characteristic polynomial, eigendecomposition, eigenpair, eigenproblem, eigenspace, eigenvalue, and eigenvector are subsequently introduced. Faddeev–LeVerrier, von Mises, Gauss–Jordan, Pohlhausen, Lanczos–Arnoldi, Rayleigh–Ritz, Jacobi–Davidson, and Gauss–Seidel fundamental algorithms are given, while others (Francis–Kublanovskaya, Gram–Schmidt, Householder, Givens, Broyden–Fletcher–Goldfarb–Shanno, Davidon–Fletcher–Powell, and Saad–Schultz) are merely discussed. The eigenproblem has thus found its use in many topics. The applications discussed include solving Bessel’s, Helmholtz’s, Laplace’s, Legendre’s, Poisson’s, and Schrödinger’s equations. The algorithm extracting the first principal component is also provided.
Enhancing Smart IoT Malware Detection: A GhostNet-based Hybrid Approach
Authors: Almazroi Abdulwahab Ali , Ayub Nasir
Published: November 2023

The Internet of Things (IoT) constitutes the foundation of a deeply interconnected society in which objects communicate through the Internet. This innovation, coupled with 5G and artificial intelligence (AI), finds application in diverse sectors like smart cities and advanced manufacturing. With increasing IoT adoption comes heightened vulnerabilities, prompting research into identifying IoT malware. While existing models excel at spotting known malicious code, detecting new and modified malware presents challenges. This paper presents a novel six-step framework. It begins with eight malware attack datasets as input, followed by insights from Exploratory Data Analysis (EDA). Feature engineering includes scaling, One-Hot Encoding, target variable analysis, feature importance using MDI and XGBoost, and clustering with K-Means and PCA. Our GhostNet ensemble, combined with the Gated Recurrent Unit Ensembler (GNGRUE), is trained on these datasets and fine-tuned using the Jaya Algorithm (JA) to identify and categorize malware. The tuned GNGRUE-JA is tested on malware datasets. A comprehensive comparison with existing models encompasses performance, evaluation criteria, time complexity, and statistical analysis. Our proposed model demonstrates superior performance through extensive simulations, outperforming existing methods by around 15% across metrics like AUC, accuracy, recall, and hamming loss, with a 10% reduction in time complexity. These results emphasize the significance of our study’s outcomes, particularly in achieving cost-effective solutions for detecting eight malware strains.
Aluminum Concentrations in Male and Female Football Players during the Season
Authors: Robles-Gil María C. , Toro-Román Víctor , Maynar-Mariño Marcos , Siquier-Coll Jesús , Bartolomé Ignacio , Grijota Francisco J.
Published: November 2023

Aluminum (Al) is one of the most abundant trace mineral elements in the earth’s crust. Al is considered a potent neurotoxicant. Physical exercise could cause modifications in some trace mineral elements. On the other hand, there could be sex differences in the exposure and deposits of toxic mineral elements. The aim of the present study was to compare sex and seasonal differences in extracellular and intracellular Al concentrations in football players. The study involved 22 male and 24 female football players from the fifth and second national category, respectively. Three assessments were carried out during the season (beginning, middle and end). Al concentrations in plasma, urine, erythrocytes and platelets were determined. Male football players ingested more Al (p < 0.05). Higher plasma Al concentrations were reported in male football players (p < 0.01). On the other hand, in both groups, increases and decreases in Al in the plasma and urine were observed in the second and third assessment, respectively (p < 0.01). There were sex differences in platelet Al concentrations (p < 0.05). Plasma and platelet Al concentrations may be different between the sexes. Al concentrations may change over the course of a season in football players.
Physicochemical Characterization and Oxidative Potential of Iron-Containing Particles Emitted from Xuanwei Coal Combustion
Authors: Lu Senlin , Liu Jin , Hou Guoqing , Zhao Jiumei , Liu Xinchun , Xie Tingting , Xiao Kai , Yonemochi Shinichi , Ebere Enyoh Christian , Wang Weiqian , Wang Qingyue
Published: November 2023

Respiratory diseases have been proven to be directly related to air pollutants. Xuanwei, located in South China, has been known to have the highest mortality rate for lung cancer in China because of the air pollutants emitted through local coal combustion. However, the mechanism of lung cancer induced by air pollutants is not clear. Based on the fact that a large number of iron-bearing mineral particles was found in Xuanwei coal combustion particles, the iron-containing particles were hypothesized to play important roles in the pathogenesis of the high incidence rate of lung cancer in this area. In this study, raw coal samples were collected from a coal mine in the Xuanwei area. Size-resolved particles emitted from the raw coal samples were collected using an Anderson high-volume sampler. Mineralogical characterization and an assessment of the oxidative potential of the iron-containing particles were conducted using cutting-edge technologies, and the biological activity of the particles were evaluated via DTT assay. Our data showed that the iron-containing minerals accounted for more than 10% of the measured particles emitted from Xuanwei coal combustion samples. The content analysis of ·OH generated from Xuanwei coal combustion particles showed that ·OH content was dependent on the size of particles in the surrogated lung fluid. The concentration of ·OH increased as the particle size decreased. The DTT assay data further demonstrated that when the mass concentration of dissolved irons increased, the oxidation potential of the particles increased. The highest proportion of divalent iron in the total dissolved iron was found in the submicron particles in low pH solution(pH = 1), which indicated that the oxidative potential induced by submicron particles was stronger than that induced by coarse particles and fine particles. Armed with the above data, the toxicological mechanism of the iron-containing mineral particles can be investigated further.
Endogenous FGF1 Deficiency Aggravates Doxorubicin-Induced Hepatotoxicity
Authors: Gu Chunjie , Liu Zijuan , Li Yingjian , Yi Mei , Wang Simeng , Fan Xia , Sun Da , Zhang Chi , Yan Xiaoqing , Wu Guicheng
Published: November 2023

Doxorubicin (DOX) is a broad-spectrum antineoplastic agent that widely used in clinic. However, its application is largely limited by its toxicity in multiple organs. Fibroblast growth factor 1 (FGF1) showed protective potential in various liver diseases, but the role of endogenous FGF1 in DOX-induced liver damage is currently unknown. Both wild-type (WT) and FGF1 knockout (FGF1-KO) mice were treated with DOX. DOX induced loss of body weight and liver weight and elevation of ALT and AST in WT mice, which were aggravated by FGF1 deletion. FGF1 deletion exacerbated hepatic oxidative stress mirrored by further elevated 3-nitrosative modification of multiple proteins and malondialdehyde content. These were accompanied by blunted compensatively antioxidative responses indicated by impaired upregulation of nuclear factor erythroid 2-related factor 2 and its downstream antioxidant gene expression. The aggravated oxidative stress was coincided with exacerbated cell apoptosis in DOX-treated FGF1-KO mice reflected by further increased TUNEL positive cell staining and BCL-2-associated X expression and caspase 3 cleavage. These detrimental changes in DOX-treated FGF1-KO mice were associated with worsened intestinal fibrosis and increased upregulation fibrotic marker connective tissue growth factor and α-smooth muscle actin expression. However, DOX-induced hepatic inflammatory responses were not further affected by FGF1 deletion. These results demonstrate that endogenous FGF1 deficiency aggravates DOX-induced liver damage and FGF1 is a potential therapeutic target for treatment of DOX-associated hepatoxicity.
Exposure Profile and Characteristics of Parabens and Alkylphenols in Plasma among Rural Adults in Central China
Authors: Gao Qian , Huan Changsheng , Song Yu , Jia Zexin , Cao Qingqing , Wang Chongjian , Mao Zhenxing , Huo Wenqian
Published: November 2023

Parabens and alkylphenols pose serious hazards to human health, yet there are few studies on their exposure profiles and health risks in rural Chinese populations. In this study, 804 participants were selected from the Henan Rural Cohort in mid-eastern China. The plasma levels of parabens (methylparaben, ethylparaben, propylparaben, butylparaben (BuP)) and alkylphenols (4-tert-butylphenol (4-t-BP), 4-tert-octylphenol (4-t-OP)) were analyzed via liquid chromatography–tandem mass spectrometry. Linear regression models were used to investigate factors that may influence pollutant exposure levels. The correlation between contaminants was assessed using Spearman’s correlation. The human contaminant intake was estimated using the estimated daily intake (EDI). The health risk was assessed using the hazard quotient (HQ). The detection frequency of four parabens and two alkylphenols exceeded 75%, with median concentrations of 0.444, 0.067, 0.078, 0.053, 8.810, and 6.401 ng/mL, respectively. Significant correlations were observed between parabens, as well as between 4-t-BP and 4-t-OP. Regarding gender, paraben concentrations were higher in women than in men, except for BuP. The EDI for pollutants except 4-t-OP was lower than their respective tolerable/acceptable daily intake. In total, 85.70% of participants had 4-t-OP HQ > 1. A widespread exposure to parabens and alkylphenols among the rural population was found. The high health risks of alkylphenol exposure indicate that alkylphenols should be used with caution.
Characterization of Fusarium verticillioides Med1 LxxLL Motif Involved in Fumonisin Biosynthesis
Authors: Zhou Zehua , Liu Jie , Zhang Jie , Yan Huijuan , Yi Tuyong , Shim Won Bo
Published: November 2023

The Med1 transcriptional coactivator is a crucial component of the Mediator middle complex, which regulates the expression of specific genes involved in cell development, differentiation, reproduction, and homeostasis. The Med1 LxxLL motif, a five-amino-acid peptide sequence, is essential for Med1-mediated gene expression. Our previous study revealed that the disruption of the Med1 subunit leads to a significant increase in fumonisin B1 (FB1) production in the maize pathogen Fusarium verticillioides. However, our understanding of how Med1 regulates FB1 biosynthesis in F. verticillioides, particularly through the Med1 LxxLL motifs, remains limited. To characterize the role of LxxLL motifs, we generated a series of Med1 LxxLL deletion and amino acid substitution mutants. These mutants exhibited impaired mycelial growth and conidia germination while demonstrating enhanced conidia production and virulence. Similar to the Med1 deletion mutant, Med1 LxxLL motif mutants also exhibited increased FB1 biosynthesis in F. verticillioides. Proteomic profiling revealed that the Med1 LxxLL motif regulated the biosynthesis of several key substances that affected FB1 production, including starch and carotenoid. Subsequent studies demonstrated that the production of amylopectin, which is strongly linked to FB1 biosynthesis, was significantly increased in Med1 LxxLL motif mutants. In addition, the disruption of carotenoid metabolic genes decreased carotenoid content, thus stimulating FB1 biosynthesis in F. verticillioides. Taken together, our results provide valuable insights into how the Med1 LxxLL motif regulates FB1 biosynthesis in the mycotoxigenic fungus F. verticillioides.
Current Knowledge of Individual and Combined Toxicities of Aflatoxin B1 and Fumonisin B1 In Vitro
Authors: Chen Xiangrong , F. Abdallah Mohamed , Chen Xiangfeng , Rajkovic Andreja
Published: November 2023

Mycotoxins are considered the most threating natural contaminants in food. Among these mycotoxins, aflatoxin B1 (AFB1) and fumonisin B1 (FB1) are the most prominent fungal metabolites that represent high food safety risks, due to their widespread co-occurrence in several food commodities, and their profound toxic effects on humans. Considering the ethical and more humane animal research, the 3Rs (replacement, reduction, and refinement) principle has been promoted in the last few years. Therefore, this review aims to summarize the research studies conducted up to date on the toxicological effects that AFB1 and FB1 can induce on human health, through the examination of a selected number of in vitro studies. Although the impact of both toxins, as well as their combination, were investigated in different cell lines, the majority of the work was carried out in hepatic cell lines, especially HepG2, owing to the contaminants’ liver toxicity. In all the reviewed studies, AFB1 and FB1 could invoke, after short-term exposure, cell apoptosis, by inducing several pathways (oxidative stress, the mitochondrial pathway, ER stress, the Fas/FasL signaling pathway, and the TNF-α signal pathway). Among these pathways, mitochondria are the primary target of both toxins. The interaction of AFB1 and FB1, whether additive, synergistic, or antagonistic, depends to great extent on FB1/AFB1 ratio. However, it is generally manifested synergistically, via the induction of oxidative stress and mitochondria dysfunction, through the expression of the Bcl-2 family and p53 proteins. Therefore, AFB1 and FB1 mixture may enhance more in vitro toxic effects, and carry a higher significant risk factor, than the individual presence of each toxin.
Does the Presence or a High Titer of Yellow Fever Virus Antibodies Interfere with Pregnancy Outcomes in Women with Zika Virus Infection?
Authors: Piauilino Isa Cristina Ribeiro , Souza Raillon Keven dos Santos , Lima Maurício Teixeira , Rodrigues Yanka Karolinna Batista , da Silva Luís Felipe Alho , Gouveia Ayrton Sena , Neto Alexandre Vilhena da Silva , Chaves Bárbara Aparecida , Alecrim Maria das Graças Costa , de Menezes Camila Helena Aguiar Bôtto , Castilho Márcia da Costa , Baia-da-Silva Djane Clarys , Espinosa Flor Ernestina Martinez
Published: November 2023

Zika virus (ZIKV) and yellow fever virus (YFV) originated in Africa and expanded to the Americas, where both are co-circulated. It is hypothesized that in areas of high circulation and vaccination coverage against YFV, children of pregnant women have a lower risk of microcephaly. We evaluated the presence and titers of antibodies and outcomes in women who had ZIKV infection during pregnancy. Pregnancy outcomes were classified as severe, moderate, and without any important outcome. An outcome was defined as severe if miscarriage, stillbirth, or microcephaly occurred, and moderate if low birth weight and/or preterm delivery occurred. If none of these events were identified, the pregnancy was defined as having no adverse effects. A sample of 172 pregnant women with an acute ZIKV infection confirmed during pregnancy were collected throughout 2016. About 89% (150 of 169) of them presented immunity against YFV, including 100% (09 of 09) of those who had severe outcomes, 84% (16 of 19) of those who had moderate outcomes, and 89% (125 of 141) of those who had non-outcomes. There was no difference between groups regarding the presence of anti-YFV antibodies (p = 0.65) and YFV titers (p = 0.6). We were unable to demonstrate a protective association between the presence or titers of YFV antibodies and protection against serious adverse outcomes from exposure to ZIKV in utero.
Identification of Host Factors for Rift Valley Fever Phlebovirus
Authors: Balaraman Velmurugan , Indran Sabarish V. , Li Yonghai , Meekins David A. , Jakkula Laxmi U. M. R. , Liu Heidi , Hays Micheal P. , Souza-Neto Jayme A. , Gaudreault Natasha N. , Hardwidge Philip R. , Wilson William C. , Weber Friedemann , Richt Juergen A.
Published: November 2023

Rift Valley fever phlebovirus (RVFV) is a zoonotic pathogen that causes Rift Valley fever (RVF) in livestock and humans. Currently, there is no licensed human vaccine or antiviral drug to control RVF. Although multiple species of animals and humans are vulnerable to RVFV infection, host factors affecting susceptibility are not well understood. To identify the host factors or genes essential for RVFV replication, we conducted CRISPR-Cas9 knockout screening in human A549 cells. We then validated the putative genes using siRNA-mediated knock-downs and CRISPR-Cas9-mediated knock-out studies. The role of a candidate gene in the virus replication cycle was assessed by measuring intracellular viral RNA accumulation, and the virus titers were analyzed using plaque assay or TCID50 assay. We identified approximately 900 genes with potential involvement in RVFV infection and replication. Further evaluation of the effect of six genes on viral replication using siRNA-mediated knock-downs revealed that silencing two genes (WDR7 and LRP1) significantly impaired RVFV replication. For further analysis, we focused on the WDR7 gene since the role of the LRP1 gene in RVFV replication was previously described in detail. WDR7 knockout A549 cell lines were generated and used to dissect the effect of WRD7 on a bunyavirus, RVFV, and an orthobunyavirus, La Crosse encephalitis virus (LACV). We observed significant effects of WDR7 knockout cells on both intracellular RVFV RNA levels and viral titers. At the intracellular RNA level, WRD7 affected RVFV replication at a later phase of its replication cycle (24 h) when compared with the LACV replication, which was affected in an earlier replication phase (12 h). In summary, we identified WDR7 as an essential host factor for the replication of two different viruses, RVFV and LACV, both of which belong to the Bunyavirales order. Future studies will investigate the mechanistic role through which WDR7 facilitates phlebovirus replication.
Comparative Effectiveness of Bivalent (Original/Omicron BA.4/BA.5) COVID-19 Vaccines in Adults
Authors: Kopel Hagit , Nguyen Van Hung , Boileau Catherine , Bogdanov Alina , Winer Isabelle , Ducruet Thierry , Zeng Ni , Bonafede Mac , Esposito Daina B. , Martin David , Rosen Andrew , Van de Velde Nicolas , Vermund Sten H. , Gravenstein Stefan , Mansi James A.
Published: November 2023

The emergence of Omicron variants coincided with declining vaccine-induced protection against SARS-CoV-2. Two bivalent mRNA vaccines, mRNA-1273.222 (Moderna) and BNT162b2 Bivalent (Pfizer-BioNTech), were developed to provide greater protection against the predominate circulating variants by including mRNA that encodes both the ancestral (original) strain and BA.4/BA.5. We estimated their relative vaccine effectiveness (rVE) in preventing COVID-19-related outcomes in the US using a nationwide dataset linking primary care electronic health records and pharmacy/medical claims data. The study population (aged ≥18 years) received either vaccine between 31 August 2022 and 28 February 2023. We used propensity score weighting to adjust for baseline differences between groups. We estimated the rVE against COVID-19-related hospitalizations (primary outcome) and outpatient visits (secondary) for 1,034,538 mRNA-1273.222 and 1,670,666 BNT162b2 Bivalent vaccine recipients, with an adjusted rVE of 9.8% (95% confidence interval: 2.6–16.4%) and 5.1% (95% CI: 3.2–6.9%), respectively, for mRNA-1273.222 versus BNT162b2 Bivalent. The incremental relative effectiveness was greater among adults ≥ 65; the rVE against COVID-19-related hospitalizations and outpatient visits in these patients was 13.5% (95% CI: 5.5–20.8%) and 10.7% (8.2–13.1%), respectively. Overall, we found greater effectiveness of mRNA-1273.222 compared with the BNT162b2 Bivalent vaccine in preventing COVID-19-related hospitalizations and outpatient visits, with increased benefits in older adults.