bluuebunny/crossref_metadata_2025 huggingface dataset:
Advancing Electricity Consumption Forecasts in Arid Climates through Machine Learning and Statistical Approaches
Authors: Alsulaili Abdalrahman , Aboramyah Noor , Alenezi Nasser , Alkhalidi Mohamad
Published: July 2024

This study investigated the impact of meteorological factors on electricity consumption in arid regions, characterized by extreme temperatures and high humidity. Statistical approaches such as multiple linear regression (MLR) and multiplicative time series (MTS), alongside the advanced machine learning method Extreme Gradient Boosting (XGBoost) were utilized to analyze historical consumption data. The models developed were rigorously evaluated using established measures such as the Coefficient of Determination (R2), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE). The performance of the models was highly accurate, with regression-type models consistently achieving an R2 greater than 0.9. Additionally, other metrics such as RMSE and MAPE demonstrated exceptionally low values relative to the overall data scale, reinforcing the models’ precision and reliability. The analysis not only highlights the significant meteorological drivers of electricity consumption but also assesses the models’ effectiveness in managing seasonal and irregular variations. These findings offer crucial insights for improving energy management and promoting sustainability in similar climatic regions.
Traceability of Phreatic Groundwater Contaminants and the Threat to Human Health: A Case Study in the Tabu River Basin, North China
Authors: Zhang Jing , Liao Zilong , Jin Jing , Ni Yanyan , Xu Jian , Wang Mingxin , Wang Zihe , Zhao Yiping , Zhang Yuanzheng
Published: July 2024

Groundwater is the main clean water resource in northern China, and its quality is critical for both human health and social sustainable development. Due to complex anthropogenic and/or geogenic processes, the sources of groundwater contaminants are not easy to determine. The Tabu River Basin, located in northern China, is an agriculture and pasture interlaced area in which phreatic groundwater is the predominant water resource for domestic and agricultural purposes. Groundwater with abnormally high levels of NO3−, F−, and TDS was observed here based on 87 groundwater samples collected from the phreatic aquifer in 2022. In this study, hydrogeochemical and isotopic methods were used to trace groundwater contaminants in the phreatic aquifer, and a risk assessment was conducted to analyze their threat to human health. The results indicated that NO3− in the phreatic groundwater primarily originated from manure, the high concentration of TDS was highly associated with irrigation, and the enrichment of F− was mainly controlled by geogenic factors, including alkaline condition, competitive adsorption, the dissolution of fluorine-bearing minerals, and cation exchange. A principal component analysis (PCA) showed that both anthropogenic (PC1, 50.7%) and geogenic (PC2, 19.9%) factors determined the quality of the phreatic groundwater in the study area. The human health risk assessment demonstrated that 98.9%, 92.0%, and 80.5% of the groundwater samples exceeded the permissible limit of the total noncarcinogenic risk for children, adult females, and adult males, respectively. The monitoring results from 2022 to 2023 suggested that phreatic groundwater contamination could not be mitigated through natural attenuation under the existing external pressures. Measures need to be taken to decrease the contamination of phreatic groundwater and enhance the groundwater sustainability in the Tabu River Basin. The findings of this study can provide a reference for sustainable groundwater development in the Tabu River Basin and other arid and semi-arid regions worldwide.
Composting as a Sustainable Solution for Organic Solid Waste Management: Current Practices and Potential Improvements
Authors: Manea Elena Elisabeta , Bumbac Costel , Dinu Laurentiu Razvan , Bumbac Marius , Nicolescu Cristina Mihaela
Published: July 2024

With increases in global population and urbanization, the production of Municipal Solid Waste (MSW) is growing rapidly, thus contributing to social and environmental concerns for sustainable waste management. This study addresses the research gap in optimizing composting, hypothesizing that integrating best practices and recent innovations can enhance the efficiency of the process. Data were collected through a systematic review of existing literature using Google Scholar and Scopus databases. The review provides an overview of municipal organic waste composting, outlining its processes, benefits, and challenges with the aim of identifying key area of further improvement and possibilities of adopting recent technological innovations. The analysis emphasized that technological advances in composting, as microbial inoculants or in-vessel composting have greatly improved the efficiency and quality of the resulting compost. However, several challenges remain, including managing contaminants such as heavy metals and microplastics, ensuring the compost quality and safety and addressing socioeconomic barriers that prevent widespread adoption. Moreover, process optimization, environmental and economic evaluation, as well as political and public involvement are essential to unlock the whole potential of composting systems.
Towards Integrating Information Systems of Statistical Indicators on Traceability, Quality and Safety of Italian Agrifood Systems for Citizens, Institutions and Policy-Makers
Authors: Betti Gianni , Evangelista Daniela , Gagliardi Francesca , Giordano Emanuele , Riccaboni Angelo
Published: July 2024

This paper arises from an ONRR project on “New technologies and methodologies for traceability, quality, safety, measurements and certifications to enhance the value and protect the typical traits in agrifood chains”. It has a first aim of performing an exhaustive review pertaining to the construction of indicators of the quality and safety of agrifood products, creating information systems dashboards of unidimensional and multidimensional indicators and applying such indicators, in the context of consumer choices and decisions of policy-makers and firms. Since it has been found that the literature offers no single proposal linking all such aspects, a second central and innovative aim is to propose an original step-by-step procedure for integrating information systems of statistical indicators for citizens, institutions and policy-makers with a specific focus on new technologies and methods for traceability, quality and safety of agrifood systems. The final output is a smart and user-friendly online database that is an absolute innovation on the topic.
Determinants of Farmer Participation and Development of Shallot Farming in Search of Effective Farm Management Practices: Evidence Grounded in Structural Equation Modeling Results
Authors: Asriadi Andi Amran , Salam Muslim , Nadja Rahmawaty Andi , Fudjaja Letty , Rukmana Didi , Jamil Muhammad Hatta , Arsyad Muhammad , Rahmadanih  , Maulidiyah Rafiqah
Published: July 2024

The objective of this research was to examine the determinants of farmer participation and shallot-farming development in search of effective farm management practices. The study used structural equation modeling data analysis. The primary data were collected from direct structural interviews with 150 randomly chosen shallot farmers in Bantaeng Regency, Indonesia. It was found that the latent variables of Physical Aspects of Land, System of Economy Peasant Society, and System of Political Peasant Society were fundamental factors that exerted a positive and significant influence on the latent variable of Farmer Participation. Therefore, improvements in the physical aspects of the land, the economic framework, and the political structure of agricultural communities could promote farmer participation. Furthermore, the latent variable of Farmer Participation and System of Political Peasant Society had a positive and significant impact on shallot-farming development. Thus, by increasing the influence of government officials and community leaders, shallot farming can be promoted. The farmers can then enhance their participation in shallot-farming plan formulation and implementation, providing the continued development of shallot farming. The findings of this study contribute significantly to the body of knowledge by validating previous research and proposing different ways to improve effective farm management practices in shallot farming.
Sweet Pepper Farming Strategies in Response to Climate Change: Enhancing Yield and Shelf Life through Planting Time and Cultivar Selection
Authors: Zakir Iqra , Ahmad Shakeel , Haider Sakeena Tul-Ain , Ahmed Talaat , Hussain Sajjad , Saleem Muhammad Shahzad , Khalid Muhammad Fasih
Published: July 2024

Climate change is an important concern worldwide. This huge change is causing a negative impact on crop productivity throughout the whole world and shows some drastic effects on sensitive crops including sweet pepper and other kinds of chilies. These stresses have a negative effect on vegetable growth, fruit quality, and fruit yield. Besides these stresses, accurate planting time is the utmost factor in increasing the crop potential and its productivity. Therefore, this study aimed to evaluate the optimal planting date and best-performing cultivar for sweet pepper to maximize crop productivity, growth, yield, and fruit shelf life under the impacts of climate change. The experiment was conducted in Multan, Pakistan (30° 25 N and 71° 30 E). In this experiment, four planting dates (10 January, 25 January, 10 February, and 25 February) with three cultivars (Ganga, Winner, and Savio) were grown with three replications (each year) during 2020 and 2021. Our findings showed that plant growth, fresh and dry biomass, yield, and yield attributes were statistically higher in earlier plantings, and lower in delayed planting. Regarding the cultivars in both years, ‘Winner’ performed better in all growth and yield parameters as compared to other growing cultivars. Lower weight loss and decay incidence were reported in ‘Winner’ cultivar. Additionally, ‘Winner’ cultivar showed a higher sensory score as compared to the other cultivar in both years. From the results, we conclude that the nursery of sweet pepper plants should be planted on the 25 January to attain higher crop productivity, and the cultivar ‘Winner’ showed promising effects so it should be planted for better yield.
Decarbonization in the Oil and Gas Sector: The Role of Power Purchase Agreements and Renewable Energy Certificates
Authors: Chrysikopoulos Stamatios K. , Chountalas Panos T. , Georgakellos Dimitrios A. , Lagodimos Athanasios G.
Published: July 2024

This study examines the adoption of Power Purchase Agreements (PPAs) and Renewable Energy Certificates (RECs) as strategic tools for decarbonization in the oil and gas sector. Focusing on the 21 largest oil and gas companies across Europe, North America, and South America, the analysis reveals varied adoption rates and strategic emphases between regions. European companies exhibit robust integration of PPAs and RECs to expand renewable energy capacities and reduce emissions, aligning closely with aggressive EU climate policies. In contrast, American companies show a cautious approach, focusing more on emission reduction from existing operations than on renewable expansions. The study’s findings indicate that, while both regions are advancing in their decarbonization efforts, European companies are leading with more defined renewable energy targets and comprehensive low-carbon strategies. This research contributes to understanding how different regulatory environments and market conditions influence corporate strategies towards sustainable energy transitions in traditionally hard-to-abate industries.
An Evaluation of the Physical Characteristics of Seeds of Selected Lilac Species for Seed Sorting Purposes and Sustainable Forest Management
Authors: Kaliniewicz Zdzisław , Konopka Stanisław , Krzysiak Zbigniew , Tylek Paweł
Published: July 2024

The aim of this study was to measure the physical attributes of seeds of selected lilac species and to describe the correlations between these properties and seed mass for seed processing and treatment. Basic physical parameters were measured in the seeds of five lilac species and the results were used to calculate aspect ratios describing seed shape and size. The average values of the measured properties ranged from 3.57 to 5.98 m s−1 for terminal velocity, from 6.20 to 9.61 mm for seed length, from 2.19 to 3.94 mm for seed width, from 0.85 to 1.21 mm for seed thickness, from 5.9 to 19.2 mg for seed mass, and from 32° to 44° for the angle of external friction. Seed mass was bound by the strongest correlations with terminal velocity (Amur lilac, Hungarian lilac, and Pekin lilac), thickness (broadleaf lilac), and width (Japanese tree lilac). Seed thickness followed by terminal velocity were the primary distinguishing features of lilac seeds. Therefore, lilac seeds should be sorted with the use of sieve separators with longitudinal openings or pneumatic separators. These devices effectively sort lilac seeds into fractions with uniform seed mass, which can facilitate the propagation of lilacs in nurseries and the production of high-quality seedlings, thus promoting the sustainable use of natural resources and production materials. In medium-sized and large seed fractions, the coefficient of variation of seed mass can be decreased by up to 50% relative to unsorted seeds.
The Importance of Green Investments in Developed Economies—MCDM Models for Achieving Adequate Green Investments
Authors: Ristanović Vladimir , Primorac Dinko , Dorić Barbara
Published: July 2024

Green investments help to create less harmful alternatives and adequate funds that contribute to economic growth, sustainable development, and social well-being. The paper aims to evaluate decision making on the choice of green investments based on multi-criteria decision making (MCDM). The applied methods are empirical and analytical based on the study of the literature, multi-criteria modeling, the determination of weights, and the ranking of criteria in deciding the green investment mapping of indicators, and mapping the indicators. The research used groups of indicators that reflect the main characteristics of green growth from the OECD database. The idea is to decide on the best green investment based on green growth criteria, which consist of grouped indicators according to the areas of the green economy rather than according to their values. The results of the Analytical Hierarchy Process (AHP method) showed that half of the investments in the green economy come from public sources (0.51) and the other half are private (0.25) and institutional investors (0.24), while the Best/Worst Method (BWM) revealed that the best criterion for the decision to invest in the green economy is the environmental and resource productivity of the economy, and the worst is the base of natural assets. This paper aims to enable decision-makers to use these results as weights for the overall assessment of green investments in ESG and to simplify the decision-making approach in future analyses.
Design, Technical Development, and Evaluation of an Autonomous Compost Turner: An Approach towards Smart Composting
Authors: Cichocki Max , Buchmayer Eva , Theurl Fabian , Schmied Christoph
Published: July 2024

In a sustainable circular economy, the composting of organic waste plays an essential role. This paper presents the design and technical development of a smart and self-driving compost turner. The architecture of the hardware, including the sensor setup, navigation module, and control module, is presented. Furthermore, the methodological development using model-based systems engineering of the architecture of concepts, models, and their subsequent software integration in ROS is discussed. The validation and verification of the overall system are carried out in an industrial environment using three scenarios. The capabilities of the compost turner are demonstrated by requiring it to autonomously follow pre-defined trajectories at the composting plant and perform required composting tasks. The results prove that the autonomous compost turner can perform the required activities. In addition to autonomous driving, the compost turner is capable of intelligent processing of the compost data and of transferring, visualizing, and storing them in a cloud server. The overall system of the intelligent, autonomous compost turner can provide essential leverage for improving sustainability efforts, thus contributing substantially to an environmentally friendly and sustainable future.
Exploring Ring Structures: Multiset Dimension Analysis in Compressed Zero-Divisor Graphs
Authors: Ali Nasir , Siddiqui Hafiz Muhammad Afzal , Qureshi Muhammad Imran , Abdallah Suhad Ali Osman , Almahri Albandary , Asad Jihad , Akgül Ali
Published: July 2024

This paper explores the concept of multiset dimensions (Mdim) of compressed zero-divisor graphs (CZDGs) associated with rings. The authors investigate the interplay between the ring-theoretic properties of a ring R and the associated compressed zero-divisor graph. An undirected graph consisting of a vertex set Z(RE)\{[0]}=RE\{[0],[1]}, where RE={[x] :x∈R} and [x]={y∈R : ann(x)=ann(y)} is called a compressed zero-divisor graph, denoted by ΓER. An edge is formed between two vertices [x] and [y] of Z(RE) if and only if [x][y]=[xy]=[0], that is, iff xy=0. For a ring R, graph G is said to be realizable as ΓER if G is isomorphic to ΓER. We classify the rings based on Mdim of their associated CZDGs and obtain the bounds for the Mdim of the compressed zero-divisor graphs. We also study the Mdim of realizable graphs of rings. Moreover, some examples are provided to support our results. Notably, we discuss the interconnection between Mdim, girth, and diameter of CZDGs, elucidating their symmetrical significance.
An Algorithmic Evaluation of a Family of Logarithmic Integrals and Associated Euler Sums
Authors: Choi Junesang , Batır Necdet
Published: July 2024

Numerous logarithmic integrals have been extensively documented in the literature. This paper presents an algorithmic evaluation of a specific class of these integrals. Our systematic approach, rooted in logarithmic principles, enables us to extend our findings to other cases within this family of integrals. Furthermore, we explore special cases derived from our main results, thereby enhancing the applicability and significance of our work for a wider audience of researchers.
Advanced Multimodal Sentiment Analysis with Enhanced Contextual Fusion and Robustness (AMSA-ECFR): Symmetry in Feature Integration and Data Alignment
Authors: Chen Qing , Dong Shenghong , Wang Pengming
Published: July 2024

Multimodal sentiment analysis, a significant challenge in artificial intelligence, necessitates the integration of various data modalities for accurate human emotion interpretation. This study introduces the Advanced Multimodal Sentiment Analysis with Enhanced Contextual Fusion and Robustness (AMSA-ECFR) framework, addressing the critical challenge of data sparsity in multimodal sentiment analysis. The main components of the proposed approach include a Transformer-based model employing BERT for deep semantic analysis of textual data, coupled with a Long Short-Term Memory (LSTM) network for encoding temporal acoustic features. Innovations in AMSA-ECFR encompass advanced feature encoding for temporal dynamics and an adaptive attention-based model for efficient cross-modal integration, achieving symmetry in the fusion and alignment of asynchronous multimodal data streams. Additionally, the framework employs generative models for intelligent approximation of missing features. It ensures robust alignment of high-level features with multimodal data context, effectively tackling issues of incomplete or noisy inputs. In simulation studies, the AMSA-ECFR model demonstrated superior performance against existing approaches. The symmetrical approach to feature integration and data alignment contributed significantly to the model’s robustness and precision. In simulations, the AMSA-ECFR model demonstrated a 10% higher accuracy and a 15% lower mean absolute error than the current best multimodal sentiment analysis frameworks.
Generating Chaos in Dynamical Systems: Applications, Symmetry Results, and Stimulating Examples
Authors: Kyurkchiev Nikolay , Zaevski Tsvetelin , Iliev Anton , Kyurkchiev Vesselin , Rahnev Asen
Published: July 2024

In this paper, we present a new class of extended oscillators in light of chaos theory. It is based on dynamical complex systems built on the concept of self-describing with a stopping criterion process. We offer an effective studying approach with a specific focus on learning, provoking students’ thinking through the triad of enigmatics–creativity–acmeology. Dynamic processes are the basis of mathematical modeling; thus, we can reach the goal of the above-mentioned triad by the proposed differential systems. The results we derive strongly confirm the presence of symmetry in the outcomes of the proposed models. We suggest a stochastic approach to structuring the proposed dynamical systems by modeling the coefficients that drive them by some discrete probability distribution that exhibits symmetry or asymmetry. We propose specific tools for researching the behavior of these systems.
Refinement of a Lyapunov-Type Inequality for a Fractional Differential Equation
Authors: Xiao Hongying , Li Zhaofeng , Zhang Yuanyuan , Liu Xiaoyou
Published: July 2024

In this paper, we focus on a fractional differential equation  0CDαu(t)+q(t)u(t)=0 with boundary value conditions u(0)=δu(1),u′(0)=γu′(1). The paper begins by pointing out the inadequacies of the study conducted by Ma and Yangin establishing Lyapunov-type inequalities. It then discusses the properties of its Green’s function and investigates extremum problems related to several linear functions. Finally, thorough classification and analysis of various cases for parameters δ and γ are conducted. As a result, a comprehensive solution corresponding to the Lyapunov-type inequality is obtained.
Integrating Genomic, Climatic, and Immunological Factors to Analyze Seasonal Patterns of Influenza Variants
Authors: Bouchnita Anass , Djafari-Rouhani Behzad
Published: July 2024

Influenza, often referred to as the flu, is an extremely contagious respiratory illness caused by influenza viruses, impacting populations globally with significant health consequences annually. A hallmark of influenza is its seasonal patterns, influenced by a mix of geographic, evolutionary, immunological, and environmental factors. Understanding these seasonal trends is crucial for informing public health decisions, including the planning of vaccination campaigns and their formulation. In our study, we introduce a genotype-structured infectious disease model for influenza transmission, immunity, and evolution. In this model, the population of infected individuals is structured according to the virus they harbor. It considers a symmetrical fitness landscape where the influenza A and B variants are considered. The model incorporates the effects of population immunity, climate, and epidemic heterogeneity, which makes it suitable for investigating influenza seasonal dynamics. We parameterize the model to the genomic surveillance data of flu in the US and use numerical simulations to elucidate the scenarios that result in the alternating or consecutive prevalence of flu variants. We show that the speed of virus evolution determines the alternation and co-circulation patterns of seasonal influenza. Our simulations indicate that slow immune waning reduces how often variants change, while cross-immunity regulates the co-circulation of variants. The framework can be used to predict the composition of future influenza outbreaks and guide the development of cocktail vaccines and antivirals that mitigate influenza in both the short and long term.
Dual-Loop μ-Synthesis Direct Thrust Control for Turbofan Engines
Authors: Long Yifu , Wang Xi , Zhao Wenshuai , Liu Jiashuai
Published: July 2024

As the power unit of an aircraft, the engine’s primary task is to provide the demanded thrust, making research on direct thrust control crucial. However, being a complicated multivariable system, effective multivariable direct thrust control methods are currently lacking. The main content of this paper is threefold. First, it presents a dual-loop multivariable μ-synthesis direct thrust control scheme for mixed-exhaust low-bypass turbofan engines, which is a typical rotationally symmetric machine. The scheme adjusts fuel flow for thrust control and nozzle area to control the turbine pressure ratio, ensuring thrust tracking while maintaining the engine’s key parameters within safe limits. Second, a fast, accurate thrust estimation algorithm based on aerodynamic thermodynamics and component characteristics is introduced. At last, considering the model uncertainties between off-design and design points, a weight function frequency shaping μ-synthesis control design method is proposed to address internal loop coupling and external disturbance suppression. Nonlinear simulations within the flight envelope show that μ-synthesis direct thrust control achieves robust servo tracking and disturbance rejection, with a maximum steady-state thrust error of no more than 0.1%, and the key parameters are not over their safety boundaries.
Short-Distance Physics with Rare Kaon Decays
Authors: Neshatpour Siavash
Published: July 2024

In this write-up, we provide an overview of the existing theoretical framework concerning rare kaon decays, with a particular emphasis on flavour-changing neutral current processes. These decays offer crucial indirect pathways for investigating short-distance new physics. Our discussion will encompass standard model predictions for relevant observables, alongside an assessment of their capacity to probe new physics through a comparison with experimental data.
Enhanced Energy Transfer Efficiency for IoT-Enabled Cyber-Physical Systems in 6G Edge Networks with WPT-MIMO-NOMA
Authors: Ezekiel Agbon Ehime , Okafor Kennedy Chinedu , Tersoo Sena Timothy , Alabi Christopher Akinyemi , Abdulsalam Jamiu , Imoize Agbotiname Lucky , Jogunola Olamide , Anoh Kelvin
Published: July 2024

The integration of wireless power transfer (WPT) with massive multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) networks can provide operational capabilities to energy-constrained Internet of Things (IoT) devices in cyber-physical systems such as smart autonomous vehicles. However, during downlink WPT, co-channel interference (CCI) can limit the energy efficiency (EE) gains in such systems. This paper proposes a user equipment (UE)–base station (BS) connection model to assign each UE to a single BS for WPT to mitigate CCI. An energy-efficient resource allocation scheme is developed that integrates the UE–BS connection approach with joint optimization of power control, time allocation, antenna selection, and subcarrier assignment. The proposed scheme improves EE by 24.72% and 33.76% under perfect and imperfect CSI conditions, respectively, compared to a benchmark scheme without UE–BS connections. The scheme requires fewer BS antennas to maximize EE and the distributed algorithm exhibits fast convergence. Furthermore, UE–BS connections’ impact on EE provided significant gains. Dedicated links improve EE by 24.72% (perfect CSI) and 33.76% (imperfect CSI) over standard connections. Imperfect CSI reduces EE, with the proposed scheme outperforming by 6.97% to 12.75% across error rates. More antennas enhance EE, with improvements of up to 123.12% (conventional MIMO) and 38.14% (massive MIMO) over standard setups. Larger convergence parameters improve convergence, achieving EE gains of 7.09% to 11.31% over the baseline with different convergence rates. The findings validate the effectiveness of the proposed techniques in improving WPT efficiency and EE in wireless-powered MIMO–NOMA networks.
Cadmium Minimization in Grains of Maize and Wheat Grown on Smelting-Impacted Land Ameliorated by Limestone
Authors: Sui Fuqing , Yang Yanzheng , Wu Yong , Yan Jiali , Fu Haichao , Li Chang , Qin Shiyu , Wang Long , Zhang Wenwen , Gao Wei , Liu Hongen , Zhao Peng
Published: July 2024

Cadmium (Cd) contamination in agricultural soils has emerged as a significant concern, particularly due to its potential impact on plant-based food. Soil pH reductions can exacerbate Cd mobility, leading to excessive accumulation in crops. While liming has been demonstrated as an effective method to mitigate Cd accumulation in rice grains in acid soils of southern China, its efficacy in remediating acid soils in northern China remains unclear. In this study, a multi-year field experiment was conducted on farmland impacted by zinc ore smelting at coordinates of 33.92° N 112.46° E to investigate the use of limestone for controlling Cd accumulation in wheat and maize grains. The results indicated that applying 7.5 t ha−1 of limestone significantly raised the soil pH from 4.5 to 6.8 as anticipated. Different rates of limestone application (2.25, 4.45, and 7.50 t ha−1) reduced Cd bioavailability in the soil by 20–54%, and Cd accumulation in wheat grains by 5–38% and maize grains by 21–63%, without yield penalty. The remediation effects were sustained for at least 27 months, highlighting limestone as a promising ameliorant for smelting-affected farmland in northern China.
Endocrine-Disrupting Effects of Transplacental and Translactational Exposure to Tembotrione on Hormone Status in Wistar Rat Offspring at Different Developmental Stages: A Pilot Study
Authors: Katić Anja , Brčić Karačonji Irena , Micek Vedran , Želježić Davor
Published: July 2024

Green agronomy promotes the implementation of natural and naturally derived substances in crop protection. In the present study, we evaluated the endocrine-disrupting potential of the allelopathic herbicide tembotrione in Wistar rats by studying the hormone status of offspring from the treated dams. Three doses of tembotrione (0.0004, 0.0007, and 4.0 mg/kg b.w./day) have been administered to dams during gestation and/or lactation. In the serum of newborn, weaning, and pubertal female and male offspring, 17β-estradiol and testosterone were determined using enzyme-linked immunosorbent assay. A decrease in 17β-estradiol and testosterone was observed in female and male weaning and pubertal offspring exposed to all doses of tembotrione during gestation and lactation. In weaning offspring exposed only during lactation, 17β-estradiol dropped significantly after exposure to the two lower doses and testosterone after exposure to the lowest dose of tembotrione. The greatest effect was observed at the lowest dose of tembotrione. In newborns, we observed increased 17β-estradiol after exposure to two lower doses of tembotrione and significantly increased testosterone after exposure to the lowest dose. The highest dose of tembotrione decreased 17β-estradiol significantly in newborn females. The obtained results suggest that tembotrione might be considered a pro-estrogenic or estrogen agonistic compound under the exposure conditions applied in this investigation.
Enhanced Adsorption of Gaseous Naphthalene by Activated Carbon Fibers at Elevated Temperatures
Authors: Lin Chiou-Liang , Huang Chun-Yi , Liu Zhen-Shu
Published: July 2024

This study utilized activated carbon fibers (ACFs) as adsorbents to investigate the removal efficiency of naphthalene and toluene at elevated temperatures and their competitive adsorption behavior. Three types of ACFs, inlet concentrations of naphthalene (343, 457, and 572 mg·Nm−3), and toluene (2055, 2877, and 4110 mg·Nm−3) were investigated to determine the adsorption capacities of naphthalene and toluene. To study the reaction mechanisms of naphthalene and toluene on the ACFs, the BET, SEM, FTIR, and TGA methods were used to examine the physical and chemical characteristics of ACFs. Results showed ACF-A’s superior adsorption capacity for naphthalene that was attributed to its mesoporous structure and hydrophobicity. Adsorption equilibrium studies indicated multilayer adsorption behavior. Competitive adsorption experiments demonstrated the displacement of toluene by naphthalene on ACF-A, highlighting its higher selectivity for naphthalene. Functional group analysis revealed changes in ACF surfaces after naphthalene adsorption, suggesting π-π dispersion and electron donor–acceptor interactions. Overall, this study underscores the importance of pore structure and surface properties in designing ACFs for the efficient adsorption of high-boiling-point organic pollutants.
Using a Knowledge and Awareness Survey to Engage and Inform a Community-Based Tuberculosis Intervention among Nomads in Adamawa State, Nigeria
Authors: John Stephen , Abdulkarim Suraj , Katlholo Thandi , Smyth Caoimhe , Basason Hunpiya , Rahman Md. Toufiq , Creswell Jacob
Published: July 2024

Background: Nomadic populations are frequently isolated and vulnerable to diseases including tuberculosis (TB) and human immunodeficiency virus (HIV) due to limited access to health-related information and services, poverty, and social exclusion. We designed and implemented community-driven and -based outreach for TB and HIV based on the results of a TB knowledge, attitude, and practices (KAP) survey in Adamawa, Nigeria. Methods: We conducted a cross-sectional study on KAP among nomads using an adapted WHO survey. A TB and HIV community-level active case-finding intervention among nomadic populations was planned and delivered based on the KAP survey results. Results: Among 81 respondents, 26 (32.1%) knew what caused TB. More than 60% reported no health facilities in their community. Radio and healthcare workers were primary sources of information on health. Using community input, we developed and broadcasted radio jingles to sensitize people to TB services. Outreach initiatives led to the verbal screening of 61,891 individuals and 306 were diagnosed with TB. Additionally, 4489 people underwent HIV testing, and 69 were HIV-positive, all of whom were linked to treatment. Conclusions: The results of KAP surveys can inform the design of evidence-based TB and HIV community-driven and -based case-finding interventions in rural Nigeria among nomadic populations.
A Study of Spin 1 Unruh–De Witt Detectors
Authors: Guedes F. M. , Guimaraes M. S. , Roditi I. , Sorella S. P.
Published: July 2024

A study of the interaction of spin 1 Unruh–De Witt detectors with a relativistic scalar quantum field is presented here. After tracing out the field modes, the resulting density matrix for a bipartite qutrit system is employed to investigate the violation of the Bell–CHSH inequality. Unlike the case of spin 1/2, for which the effects of the quantum field result in a decrease in the size of violation, in the case of spin 1, both a decrease or an increase in the size of the violation may occur. This effect is ascribed to the fact that Tsirelson’s bound is not saturated in the case of qutrits.
Efficacy and Immunogenicity of a Recombinant Vesicular Stomatitis Virus-Vectored Marburg Vaccine in Cynomolgus Macaques
Authors: Camargos Vidyleison N. , Rossi Shannan L. , Juelich Terry L. , Smith Jennifer K. , Vasilakis Nikos , Freiberg Alexander N. , Nichols Rick , Fusco Joan
Published: July 2024

Filoviruses, like the Marburg (MARV) and Ebola (EBOV) viruses, have caused outbreaks associated with significant hemorrhagic morbidity and high fatality rates. Vaccines offer one of the best countermeasures for fatal infection, but to date only the EBOV vaccine has received FDA licensure. Given the limited cross protection between the EBOV vaccine and Marburg hemorrhagic fever (MHF), we analyzed the protective efficacy of a similar vaccine, rVSV-MARV, in the lethal cynomolgus macaque model. NHPs vaccinated with a single dose (as little as 1.6 × 107 pfu) of rVSV-MARV seroconverted to MARV G-protein prior to challenge on day 42. Vaccinemia was measured in all vaccinated primates, self-resolved by day 14 post vaccination. Importantly, all vaccinated NHPs survived lethal MARV challenge, and showed no significant alterations in key markers of morbid disease, including clinical signs, and certain hematological and clinical chemistry parameters. Further, apart from one primate (from which tissues were not collected and no causal link was established), no pathology associated with Marburg disease was observed in vaccinated animals. Taken together, rVSV-MARV is a safe and efficacious vaccine against MHF in cynomolgus macaques.
The Generation and Characterization of Monoclonal Antibodies against the MPXV A29L Protein
Authors: Zhu Wenlong , Zhang Mengjia , Zhang Mengdi , Jing Ran , Zhou Jiaru , Cao Hua , Liu Changcheng , Zhu Hongmei , Ghonaim Ahmed H. , Rouby Sherin R. , Li Wentao
Published: July 2024

Mpox (formerly known as monkeypox) is a zoonotic disease caused by monkeypox virus (MPXV), a DNA virus belonging to the Orthopoxvirus genus, in the Poxviridae family. The disease constitutes a moderate risk to public health at the global level. The MPXV A29L protein plays a crucial role in coordinating virion assembly and facilitating important virus-host interactions. This study focused on the expression, purification, and recombinant protein synthesis of the A29L protein of MPXV using prokaryotic systems. Using hybridoma technology, we successfully generated the monoclonal antibodies (mAbs) 1E12 and 4B2, which specifically recognize the A29L protein. These mAbs were found to be suitable for use in indirect immunofluorescence assays (IFA), Western blotting, and immunoprecipitation (IP). Our investigation also revealed that mAbs 1E12 and 4B2 could detect the A27L protein, a homologous protein found in the vaccinia virus Western Reserve (VACV WR) strain, using IFA, Western blotting, and immunoprecipitation (IP). Using mAbs 1E12 and 4B2 as primary immunological probes, A27L protein expression was detected as early as 6 h postinfection with VACV WR, with increasing protein levels being observed throughout the infection. This study enhances our understanding of the protein structure and function of MPXV and contributes to the development of specific MPXV detection methods.
CavitOmiX Drug Discovery: Engineering Antivirals with Enhanced Spectrum and Reduced Side Effects for Arboviral Diseases
Authors: Parigger Lena , Krassnigg Andreas , Hetmann Michael , Hofmann Anna , Gruber Karl , Steinkellner Georg , Gruber Christian C.
Published: July 2024

Advancing climate change increases the risk of future infectious disease outbreaks, particularly of zoonotic diseases, by affecting the abundance and spread of viral vectors. Concerningly, there are currently no approved drugs for some relevant diseases, such as the arboviral diseases chikungunya, dengue or zika. The development of novel inhibitors takes 10–15 years to reach the market and faces critical challenges in preclinical and clinical trials, with approximately 30% of trials failing due to side effects. As an early response to emerging infectious diseases, CavitOmiX allows for a rapid computational screening of databases containing 3D point-clouds representing binding sites of approved drugs to identify candidates for off-label use. This process, known as drug repurposing, reduces the time and cost of regulatory approval. Here, we present potential approved drug candidates for off-label use, targeting the ADP-ribose binding site of Alphavirus chikungunya non-structural protein 3. Additionally, we demonstrate a novel in silico drug design approach, considering potential side effects at the earliest stages of drug development. We use a genetic algorithm to iteratively refine potential inhibitors for (i) reduced off-target activity and (ii) improved binding to different viral variants or across related viral species, to provide broad-spectrum and safe antivirals for the future.
Exploring Canine Picornavirus Diversity in the USA Using Wastewater Surveillance: From High-Throughput Genomic Sequencing to Immuno-Informatics and Capsid Structure Modeling
Authors: Faleye Temitope O. C. , Skidmore Peter , Elyaderani Amir , Adhikari Sangeet , Kaiser Nicole , Smith Abriana , Yanez Allan , Perleberg Tyler , Driver Erin M. , Halden Rolf U. , Varsani Arvind , Scotch Matthew
Published: July 2024

The SARS-CoV-2 pandemic resulted in a scale-up of viral genomic surveillance globally. However, the wet lab constraints (economic, infrastructural, and personnel) of translating novel virus variant sequence information to meaningful immunological and structural insights that are valuable for the development of broadly acting countermeasures (especially for emerging and re-emerging viruses) remain a challenge in many resource-limited settings. Here, we describe a workflow that couples wastewater surveillance, high-throughput sequencing, phylogenetics, immuno-informatics, and virus capsid structure modeling for the genotype-to-serotype characterization of uncultivated picornavirus sequences identified in wastewater. Specifically, we analyzed canine picornaviruses (CanPVs), which are uncultivated and yet-to-be-assigned members of the family Picornaviridae that cause systemic infections in canines. We analyzed 118 archived (stored at −20 °C) wastewater (WW) samples representing a population of ~700,000 persons in southwest USA between October 2019 to March 2020 and October 2020 to March 2021. Samples were pooled into 12 two-liter volumes by month, partitioned (into filter-trapped solids [FTSs] and filtrates) using 450 nm membrane filters, and subsequently concentrated to 2 mL (1000×) using 10,000 Da MW cutoff centrifugal filters. The 24 concentrates were subjected to RNA extraction, CanPV complete capsid single-contig RT-PCR, Illumina sequencing, phylogenetics, immuno-informatics, and structure prediction. We detected CanPVs in 58.3% (14/24) of the samples generated 13,824,046 trimmed Illumina reads and 27 CanPV contigs. Phylogenetic and pairwise identity analyses showed eight CanPV genotypes (intragenotype divergence <14%) belonging to four clusters, with intracluster divergence of <20%. Similarity analysis, immuno-informatics, and virus protomer and capsid structure prediction suggested that the four clusters were likely distinct serological types, with predicted cluster-distinguishing B-cell epitopes clustered in the northern and southern rims of the canyon surrounding the 5-fold axis of symmetry. Our approach allows forgenotype-to-serotype characterization of uncultivated picornavirus sequences by coupling phylogenetics, immuno-informatics, and virus capsid structure prediction. This consequently bypasses a major wet lab-associated bottleneck, thereby allowing resource-limited settings to leapfrog from wastewater-sourced genomic data to valuable immunological insights necessary for the development of prophylaxis and other mitigation measures.
FlagT4G Vaccine Prevents Transplacental Transmission of Highly Virulent Classical Swine Fever Virus after Single Vaccination in Pregnant Sows
Authors: Coronado Liani , Muñoz-Aguilera Adriana , Cantero Guillermo , Martínez Patricia , Alberch Mònica , Rosell Rosa , Gladue Douglas P. , Borca Manuel V. , Ganges Llilianne
Published: July 2024

The transplacental transmission of CSFV and the resulting persistent congenital infection in newborn piglets have been abundantly discussed in pregnant sows suffering from virus infection. Importantly, the availability of safe commercial vaccines with proven efficacy to prevent the generation of congenital and postnatal persistent infections in pregnant sows are critical tools for controlling the disease in CSF endemic areas. Here, we demonstrate the high efficacy of a single dose of the recombinant FlagT4G vaccine to provide solid protection in pregnant sows against transplacental transmission of a highly virulent CSFV. Pregnant sows vaccinated with FlagT4G at 44 days of gestation elicited a strong CSFV-specific antibody response, with neutralizing antibody levels above those required for protection against CSFV. Importantly, after the challenge with a highly virulent CSFV, all foetuses from FlagT4G-vaccinated sows lacked CSF macroscopic lesions and showed a complete absence of the challenge virus in their internal organs at day 79 of gestation. Therefore, pregnant sows safely vaccinated with FlagT4G without affecting reproductive efficacy are efficaciously protected, along with their foetuses, against the infection and disease caused by a CSFV virulent field strain.
Simulation and Prediction of Snowmelt Runoff in the Tangwang River Basin Based on the NEX-GDDP-CMIP6 Climate Model
Authors: Zhang Yi-Xin , Liu Geng-Wei , Dai Chang-Lei , Zou Zhen-Wei , Li Qiang
Published: July 2024

In this study, the future snowmelt runoff in the chilly northeast region’s Tangwang River Basin was simulated and predicted using the SWAT model, which was built and used based on the NEX-GDDP-CMIP6 climate model. This study conducted a detailed analysis of the spatial and temporal distribution characteristics of snowmelt runoff using high-resolution DEM, land use, and soil data, along with data from historical and future climatic scenarios. Using box plots and the Bflow digital filtering approach, this study first determined the snowmelt runoff period before precisely defining the snowmelt periods. Sensitivity analysis and parameter rate determination ensured the simulation accuracy of the SWAT model, and the correlation coefficients of the total runoff validation period and rate period were 0.75 and 0.76, with Nashiness coefficients of 0.75 for both. The correlation coefficients of the snowmelt runoff were 0.73 and 0.74, with Nashiness coefficients of 0.7 and 0.68 for both, and the model was in good agreement with the measured data. It was discovered that while temperatures indicate an increasing tendency across all future climate scenarios, precipitation is predicted to increase under the SSP2-4.5 scenario. The SSP2-4.5 scenario predicted a decreasing trend regarding runoff, while the SSP1-2.6 and SSP5-8.5 scenarios showed an increasing trend with little overall change and the SSP5-8.5 scenario even showed a decrease of 6.35%. These differences were evident in the monthly runoff simulation projections. Overall, the findings point to the possibility that, despite future climate change having a negligible effect on the hydrological cycle of the Tangwang River Basin, it may intensify and increase the frequency of extreme weather events, creating difficulties for the management of water resources and the issuing of flood warnings. For the purpose of planning water resources and studying hydrological change in this basin and other basins in cold regions, this study offers a crucial scientific foundation. An in-depth study of snowmelt runoff is of great practical significance for optimizing water resource management, rational planning of water use, spring flood prevention, and disaster mitigation and prevention, and provides valuable data support for future research on snowmelt runoff.