bluuebunny/crossref_metadata_2025 huggingface dataset:
The Status of Collective Action among Rural Households in Underdeveloped Regions of China and Its Livelihood Effects under the Background of Rural Revitalization—Evidence from a Field Survey in Shanxi Province
Authors: He Xuesong , Wu Yawei , Wei Jianzhi
Published: August 2024

Enhancing collective action among rural households is crucial for promoting rural revitalization and improving livelihoods in underdeveloped areas. Taking Shanxi Province, China, as a case study, this paper employed a household survey method to collect 312 questionnaires from rural households. Using the mean value analysis of the measured items in the questionnaire. The participation status of farmers in less developed areas in collective actions, such as farmers’ professional cooperatives, village cadre elections, and cooperative construction of small farmland water conservancy, was examined in four aspects: willingness to participate, frequency of participation, time of participation, and sense of the value of participation. From the perspectives of livelihood risks, livelihood assets, livelihood patterns, and livelihood income, it analyzed the livelihood conditions of rural households in underdeveloped regions. Building upon the empowerment of collective action in rural livelihoods, the study further applied a multiple linear regression model to assess the impact of collective action on livelihoods. The findings indicated (1) a strong willingness and perceived value among rural households to participate in collective action, albeit with a low frequency and limited time commitment; (2) relatively low livelihood levels, characterized by limited livelihood assets, predominant subsistence farming, small-scale non-specialized enterprises, and low livelihood income, yet with notable resilience against livelihood risks; (3) that collective action significantly enhances rural household livelihoods positively. Based on these findings, policy recommendations are proposed, emphasizing the enhancement of collective organization, provision of incentive mechanisms, and improvement of farmers’ skills and qualities to foster greater participation in collective action.
Social Capital and Reflexivity as Conditions of Organisational Morphostasis—Studies of Selected Polish NGOs
Authors: Weryński Piotr , Dolińska-Weryńska Dorota
Published: August 2024

The innovativeness of non-governmental organisations, the basic institutions of civil society, is conditioned, among other things, by the endogenous potential of agency of the entities operating within them. The article attempts to answer two research questions regarding the above-mentioned issues: (1) How individual components of binding and bridging social capital (in the area of trust, norms, and connections) determine innovative activity in a state of morphostasis, i.e., structural and cultural continuity, in selected Silesian NGOs. (2) What type of reflexivity and the related nature of agency of the members of the NGOs surveyed dominate when undertaking innovative activities? At the theoretical level, the study was based on the concept of the three components of social capital by James S. Coleman and the assumptions of Margaret Archer’s morphogenetic theory of structure and agency, in particular, the types of reflexivity as a factor conditioning social agency. Based on them and using qualitative analysis of the FGI and SWOT questionnaires of the surveyed organisations, a diagnosis of intra-organisational barriers to innovation was made. The Atlas.ti computer programme was used. This method allows for the examination of structural elements, cultural features of a given organisation, and the capabilities of individual entities. The dominance of bonding social capital components over bridging social capital components was observed (mainly in the dimension of trust) as the basic bond connecting the members of the NGOs studied. It was accompanied by a communicative type of reflexivity of the respondents, with the aim of maintaining the existing organisational and social status quo. These key sociocultural factors determine the morphostatic nature of the organisations studied, i.e., their focus on maintaining the organisational status quo. Such contexts petrify the existing power structure, but also the level of social tensions and distances, and limit the innovation potential.
LCA Operational Carbon Reduction Based on Energy Strategies Analysis in a Mass Timber Building
Authors: Hemmati Moein , Messadi Tahar , Gu Hongmei , Hemmati Mahboobeh
Published: August 2024

Buildings play a significant role in the rise of energy consumption and carbon emissions. Building operations are responsible for 28% of the world’s carbon emissions. It is crucial, therefore, to evaluate the environmental impact of various buildings’ operational phase in order to implement sustainable strategies for the mitigation of their energy usage and associated carbon footprint. While numerous studies have been conducted to determine the carbon footprint of conventional building operation phases, there are still a lack of actual data on the operational carbon (OC) emissions of mass timber buildings. There is also a lack of research pertaining to the operational carbon of buildings within larger campuses and their inherent energy usage. This study, therefore, aims to quantify empirical data on the carbon footprint of a mass timber building, using, as a case study, the recent Adohi Hall building, situated at the University of Arkansas, Fayetteville. The study also aims to examine and identify the best energy use scenarios for the campus building under consideration. The research team obtained data on Adohi Hall’s energy consumption, fuel input usage, and other utilities (such as water, electricity, chilled water, and natural gas) accounting for the operation of the building from 2021 to 2023, a span of three years. The University of Arkansas Facilities Management (FAMA) provided the data. The study relies on the life cycle assessment (LCA) as its primary approach, with SimaPro 9, Ecoinvent v3.7 database, DataSmart, version 2023.1 and the U.S. Life Cycle Inventory (USLCI) database utilized to model the energy and water consumption of Adohi Hall during the operational phase (B6 & B7). The results indicate 4496 kg CO2 eq emissions associated with the operation per square meter of Adohi Hall over its 50-year lifespan. The study also examines various scenarios of fuel sources leading to carbon emissions and provides insights into reduction strategies during the operational phase of buildings. Among them, the electricity based on a cleaner fuel source diversification, according to realistic expectations and technological advancements projections, results in a 17% reduction in Adohi Hall’s OC. Due to the usage of the combined heat and power (CHP) plant on the campus of the University of Arkansas as a complementary source of electricity and heating for Adohi Hall, the resulting carbon emission is approximately 21% (20.73%) less when compared to similar buildings in the same city but outside the campus. The study, therefore, reveals that CHP plant development is a highly effective strategy for building OC reduction.
Can Innovation Improve Corporate ESG Performance? The Moderating Effect of Internal and External Incentives
Authors: Jia Xiaoxia , Guang Weiyi
Published: August 2024

ESG (Environmental, Social, and Governance) performance is an essential indicator for measuring the sustainability of corporations. It has received increased attention from capital market participants after the proposal of the ‘dual carbon’ goal. Innovation is a necessary skill for corporations to compete in the market. Therefore, this study investigates the impact of innovation on the ESG performance of corporations based on the dual incentive perspective of government subsidies and equity incentives. Using data of China’s A-share main board listed corporations from 2017 to 2022, OLS (Ordinary Least Squares) models are constructed to conduct empirical research. The results show that enhanced innovation can significantly improve corporate ESG performance. This paper also conducts other tests to ensure the robustness of the findings and address potential endogeneity issues. Further analysis shows that both using government subsidies as external incentives and using equity incentives as internal incentives can positively moderate the above findings. Heterogeneity analyses discover that government subsidies granted to asset-advantaged corporations have a more substantial moderating effect than those granted to asset-weakened corporations; equity incentives granted to core technical staff have a more substantial moderating effect than those granted to executives. The concept that innovation with dual incentives can enhance corporate ESG performance can aid in developing programs to improve their ESG performance and generate novel ideas for high-quality, sustainable development.
Optimization Techniques in Municipal Solid Waste Management: A Systematic Review
Authors: Alshaikh Ryan , Abdelfatah Akmal
Published: August 2024

As a consequence of human activity, waste generation is unavoidable, and its volume and complexity escalate with urbanization, economic progress, and the elevation of living standards in cities. Annually, the world produces about 2.01 billion tons of municipal solid waste, which often lacks environmentally safe management. The importance of solid waste management lies in its role in sustainable development, aimed at reducing the environmental harms from waste creation and disposal. With the expansion of urban populations, waste management systems grow increasingly complex, necessitating more sophisticated optimization strategies. This analysis thoroughly examines the optimization techniques used in solid waste management, assessing their application, benefits, and limitations by using PRISMA 2020. This study, reviewing the literature from 2010 to 2023, divides these techniques into three key areas: waste collection and transportation, waste treatment and disposal, and resource recovery, using tools like mathematical modeling, simulation, and artificial intelligence. It evaluates these strategies against criteria such as cost-efficiency, environmental footprint, energy usage, and social acceptability. Significant progress has been noted in optimizing waste collection and transportation through innovations in routing, bin placement, and the scheduling of vehicles. The paper also explores advancements in waste treatment and disposal, like selecting landfill sites and converting waste to energy, alongside newer methods for resource recovery, including sorting and recycling materials. In conclusion, this review identifies research gaps and suggests directions for future optimization efforts in solid waste management, emphasizing the need for cross-disciplinary collaboration, leveraging new technologies, and adopting tailored approaches to tackle the intricate challenges of managing waste. These insights offer valuable guidance for policymakers, waste management professionals, and researchers involved in crafting sustainable waste strategies.
Influence of Catchment Surface Material on Quality of Harvested Rainwater
Authors: Barriga Felipe , Gómez Gloria , Diez M. Cristina , Fernandez Leonardo , Vidal Gladys
Published: August 2024

Rainwater harvesting (RWH) systems offer an opportunity to diversify the water matrix under drought scenario. However, there is not a robust institutional framework for managing this new source of water. The objective of this study was to evaluate the influence of the catchment surface material on the quality of rainwater collected. Three systems were installed in south-central Chile, which collected rainwater from three different surfaces: gravel tile, zinc-polycarbonate sheets, and clay tiles. The RWH system consists of a first flush diverter and then a storage system with chlorination. The rainwater was characterized by its physicochemical and microbiological properties for its possible final use, considering the current regulations for drinking water and agricultural irrigation. The results indicate that the raw rainwater harvested from different surfaces presented a high mean conductivity of 232 ± 146 µS/cm. Meanwhile, fecal coliform values were <1 MPN/100 mL, which indicates good microbiological quality. Regarding the quality for use as drinking water, it was found that of 39 parameters evaluated according to a reference standard, only the pH was above the indicated limit. Meanwhile, the harvested water presents satisfactory quality for irrigation, except for its sodium (35–50% above the standard) and pesticide values (with respect to 0.028 µg Delta-BHC/L at Site 2).
Optimization of Multimodal Paths for Oversize and Heavyweight Cargo under Different Carbon Pricing Policies
Authors: Wu Caiyi , Zhang Yinggui , Xiao Yang , Mo Weiwei , Xiao Yuxie , Wang Juan
Published: August 2024

With the increasing global concern over climate change, reducing greenhouse gas emissions has become a universal goal for governments and enterprises. For oversize and heavyweight cargo (OHC) transportation, multimodal transportation has become widely adopted. However, this mode inevitably generates carbon emissions, making research into effective emission reduction strategies essential for achieving low-carbon economic development. This study investigates the optimization of multimodal transportation paths for OHC (OMTP-OHC), considering various direct carbon pricing policies and develops models for these paths under the ordinary scenario—defined as scenarios without any carbon pricing policies—and two carbon pricing policy scenarios, namely the emission trading scheme (ETS) policy and the carbon tax policy, to identify the most cost-effective solutions. An enhanced genetic algorithm incorporating elite strategy and catastrophe theory is employed to solve the models under the three scenarios. Subsequently, we examine the impact of ETS policy price fluctuations, carbon quota factors, and different carbon tax levels on decision-making through a case study, confirming the feasibility of the proposed model and algorithm. The findings indicate that the proposed algorithm effectively addresses this problem. Moreover, the algorithm demonstrates a small impact of ETS policy price fluctuations on outcomes and a slightly low sensitivity to carbon quota factors. This may be attributed to the relatively low ETS policy prices and the characteristics of OHC, where transportation and modification costs are significantly higher than carbon emission costs. Additionally, a comparative analysis of the two carbon pricing policies demonstrates the varying intensities of emission reductions in multimodal transportation, with the ranking of carbon emission reduction intensity as follows: upper-intermediate level of carbon tax > intermediate level of carbon tax > lower-intermediate level of carbon tax = ETS policy > the ordinary scenario. The emission reduction at the lower-intermediate carbon tax level (USD 8.40/t) matches that of the ETS policy at 30%, with a 49.59% greater reduction at the intermediate level (USD 50.48/t) compared to the ordinary scenario, and a 70.07% reduction at the upper-intermediate level (USD 91.14/t). The model and algorithm proposed in this study can provide scientific and technical support to realize the low-carbonization of the multimodal transportation for OHC. The findings of this study also provide scientific evidence for understanding the situation of multimodal transportation for OHC under China’s ETS policy and its performance under different carbon tax levels in China and other regions. This also contributes to achieving the goal of low-carbon economic development.
Experiential Learning for Applying Green Patents in Sustainable Education
Authors: Yu Ching-Ying
Published: August 2024

The primary objective of this study is to enrich students’ learning experiences by integrating “Experiential Learning Methods” with “Green Patent Strategies”. This study categorizes experiential learning into four distinct modules, each systematically analyzed with the inclusion of four variables. These modules comprise Module 1: Reflective Observation, focusing on the “Corporate Sustainability Policy” variable; Module 2: Abstract Conceptualization, centering on the “Business Model Analysis” variable; Module 3: Active Experimentation, emphasizing the “Patent Strategy Layout” variable; and Module 4: Concrete Experience, delving into the “Case Analysis” variable. Within the “Patent Strategy Layout” module, additional depth is provided through subtopics such as “Green Patents”, “Keywords for Patent Application Writing”, “Zero-Carbon Patent Search Technology”, and “Enterprise Detection and Operation Analysis”, contributing to the thoroughness of the research analysis. The survey results indicate that students have attained a lucid understanding of sustainability-related subjects, including “Business Model Analysis”, “Corporate Sustainability Policy”, and “Patent Strategy Deployment”. Practical exercises have further elevated their comprehension of green patent strategies. The overarching goal of this study is to stimulate inspiration for future curriculum designs that seamlessly integrate sustainability elements, fostering interdisciplinary learning opportunities for students within the framework of sustainable education.
Key Factors Influencing the Adoption of Improved Wheat Production Technologies in the Irrigated, Heat-Prone, Arid Environments of Sudan
Authors: Ibrahim Abdelhamed Mohammed Magboul , Hassan Alawia Osman , Idris Amani Ahmed Mohamed , Gorafi Yasir Serag Alnor , Tsujimoto Hisashi , Tahir Izzat Sidahmed Ali
Published: August 2024

Successful strategies that can contribute to poverty reduction and improve the livelihoods of the poor, particularly in Sub-Saharan Africa (SSA), are critically needed to address the technology adoption constraints. The objectives of this study were to assess the adoption level of improved technologies and management practices and to identify the key factors influencing their adoption in the major wheat-producing areas in the irrigated, arid, and heat-prone environments of Sudan. A farm survey was conducted in 2021 using a structured questionnaire that included almost all recommended technological options for optimum and sustainable wheat production. A total of 300 farmers, 93, 101, and 106 from Northern (NS), Kassala (KS), and Gezira (GS) states, respectively, were selected and interviewed. Besides descriptive statistics, a binary logistic model was used to identify the socioeconomic and production factors affecting farmers’ perceptions of improved and recommended technological options. The study found a wide range of adoption rates depending on the specific technology practice and the area surveyed. The lowest adoption rate was observed for land preparation (6.5%) in NS. Adoption rates ranging from 26–100% were observed for technologies such as the sowing date, the seed rate, seed treatment, the awareness of released varieties, nitrogen and phosphorus fertilizer application, and chemical weed control. The difference in the productivity of technological option adopters was significant (p = 0.015) compared to non-adopters. The binary logistic regression results showed that five out of seven explanatory variables hypothesized to influence wheat farmers’ perceptions on the decision to adopt improved and recommended technologies significantly influenced farmers’ decision to adopt the technologies. In particular, access to quality seeds, financial credit, and extension services were found to be the most critical determinants of adopting improved technologies. Approaches that bring together all stakeholders along the crop value chain, including policymakers, to jointly analyze, identify, and prioritize challenges and develop and apply solutions and work plans using feedback and learning mechanisms are expected to increase farmer awareness and adoption of improved technologies, ultimately leading to sustainable wheat production.
A Hybrid Data Envelopment Analysis–Random Forest Methodology for Evaluating Green Innovation Efficiency in an Asymmetric Environment
Authors: Chen Limei , Xie Xiaohan , Yao Yao , Huang Weidong , Luo Gongzhi
Published: August 2024

The accurate evaluation of green innovation efficiency is a critical prerequisite for enterprises to achieve sustainable development goals and improve environmental performance and economic efficiency. This paper evaluates the green innovation efficiency of 72 new-energy enterprises by using a hybrid method of Data Envelopment Analysis (DEA) and a random forest model. The non-parametric DEA model is combined with the parametric SFA model to analyze the real green innovation efficiency on the basis of removing environmental factors and random factors. Then, the random forest model based on a nonlinear relationship is used to evaluate factors impacting green innovation efficiency. This paper proposes a comprehensive evaluation method designed to assess the green innovation efficiency of new-energy enterprises. By applying this method, companies can gain a comprehensive understanding of the current performance in green innovation, facilitating informed decision-making and accelerating sustainable development.
The OX Optimizer: A Novel Optimization Algorithm and Its Application in Enhancing Support Vector Machine Performance for Attack Detection
Authors: Al Hwaitat Ahmad K. , Fakhouri Hussam N.
Published: August 2024

In this paper, we introduce a novel optimization algorithm called the OX optimizer, inspired by oxen animals, which are characterized by their great strength. The OX optimizer is designed to address the challenges posed by complex, high-dimensional optimization problems. The design of the OX optimizer embodies a fundamental symmetry between global and local search processes. This symmetry ensures a balanced and effective exploration of the solution space, highlighting the algorithm’s innovative contribution to the field of optimization. The OX optimizer has been evaluated on CEC2022 and CEC2017 IEEE competition benchmark functions. The results demonstrate the OX optimizer’s superior performance in terms of convergence speed and solution quality compared to existing state-of-the-art algorithms. The algorithm’s robustness and adaptability to various problem landscapes highlight its potential as a powerful tool for solving diverse optimization tasks. Detailed analysis of convergence curves, search history distributions, and sensitivity heatmaps further support these findings. Furthermore, the OX optimizer has been applied to optimize support vector machines (SVMs), emphasizing parameter selection and feature optimization. We tested it on the NSL-KDD dataset to evaluate its efficacy in an intrusion detection system. The results demonstrate that the OX optimizer significantly enhances SVM performance, facilitating effective exploration of the parameter space.
Mathematical Modeling in Bioinformatics: Application of an Alignment-Free Method Combined with Principal Component Analysis
Authors: Bielińska-Wąż Dorota , Wąż Piotr , Błaczkowska Agata , Mandrysz Jan , Lass Anna , Gładysz Paweł , Karamon Jacek
Published: August 2024

In this paper, an alignment-free bioinformatics technique, termed the 20D-Dynamic Representation of Protein Sequences, is utilized to investigate the similarity/dissimilarity between Baculovirus and Echinococcus multilocularis genome sequences. In this method, amino acid sequences are depicted as 20D-dynamic graphs, comprising sets of “material points” in a 20-dimensional space. The spatial distribution of these material points is indicative of the sequence characteristics and is quantitatively described by sequence descriptors akin to those employed in dynamics, such as coordinates of the center of mass of the 20D-dynamic graph and the tensor of the moment of inertia of the graph (defined as a symmetric matrix). Each descriptor unveils distinct features of similarity and is employed to establish similarity relations among the examined sequences, manifested either as a symmetric distance matrix (“similarity matrix”), a classification map, or a phylogenetic tree. The classification maps are introduced as a new way of visualizing the similarity relations obtained using the 20D-Dynamic Representation of Protein Sequences. Some classification maps are obtained using the Principal Component Analysis (PCA) for the center of mass coordinates and normalized moments of inertia of 20D-dynamic graphs as input data. Although the method operates in a multidimensional space, we also apply some visualization techniques, including the projection of 20D-dynamic graphs onto a 2D plane. Studies on model sequences indicate that the method is of high quality, both graphically and numerically. Despite the high similarity observed among the sequences of E. multilocularis, subtle discrepancies can be discerned on the 2D graphs. Employing this approach has led to the discovery of numerous new similarity relations compared to our prior study conducted at the DNA level, using the 4D-Dynamic Representation of DNA/RNA Sequences, another alignment-free bioinformatics method also introduced by us.
Vitali Theorems for Varying Measures
Authors: Marraffa Valeria , Sambucini Anna Rita
Published: August 2024

The classical Vitali theorem states that, under suitable assumptions, the limit of a sequence of integrals is equal to the integral of the limit functions. Here, we consider a Vitali-type theorem of the following form ∫fndmn→∫fdm for a sequence of pair (fn,mn)n and we study its asymptotic properties. The results are presented for scalar, vector and multivalued sequences of mn-integrable functions fn. The convergences obtained, in the vector and multivalued settings, are in the weak or in the strong sense for Pettis and McShane integrability. A list of known results on this topic is cited and new results are obtained when the ambient space Ω is not compact.
Neutrinoless Double-Beta Decay Investigations of 82Se Using Three Shell Model Hamiltonians
Authors: Neacsu Andrei , Horoi Mihai
Published: August 2024

Neutrinoless double-beta decay is considered one of the most promising processes that would help clarify some of the symmetry-breaking problems in our understanding of the observable universe. Recent studies of neutrinoless double-beta decay matrix elements have employed statistical approaches based on modified shell model effective Hamiltonians for 48Ca (Phys. Rev. C 106, 054302 (2022)) and 136Xe (Phys. Rev. C 107, 045501 (2023)). The analyses rely on inducing perturbations in the starting effective Hamiltonians to observe the behavior of a wide range of observables, besides the 0νββ) NME, that are compared with experimental data. Following a Bayesian model averaging approach, the range of probable values for the neutrinoless double-beta decay matrix elements is presented. In this paper, we present a similar study for 82Se, which is described in the same model space as 76Ge that is under experimental observation. Due to its faster calculation time compared to 76Ge, 82Se can be used as an appropriate substitute in our complex statistical study. Using the calculations performed for the statistical analysis of the neutrinoless double-beta decay matrix elements, we also search for the correlations between the observables that we can compare to experimental data.
The Variation of Constants Formula in Lebesgue Spaces with Variable Exponents
Authors: Bachar Mostafa
Published: August 2024

This study looks closely into the analysis of the variation of constants formula given by Φ(t)=S(t)Φ(0)+∫0tS(t−σ)F(σ,Φ(σ))dσ, for t∈[0,T],T>0, within the context of modular function spaces Lρ. Additionally, this research explores practical applications of the variation of constants formula in variable exponent Lebesgue spaces Lp(·). Specifically, the study examines these spaces under certain conditions applied to the exponent function p(·) and the functions F as well as the semigroup S(t), utilizing the symmetry properties of the algebraic semigroup. This investigation sheds light on the intricate interplay between parameters and functions within these mathematical frameworks, offering valuable insights into their behavior and properties in Lp(·).
A New Hyperbolic Function Approach of Rock Fragmentation Size Distribution Prediction Models
Authors: Safak Suleyman
Published: August 2024

It is well known that the first stage of mine-to-mill optimization is rock fragmentation by blasting. The degree of rock fragmentation can be expressed in terms of average grain (X50) size and size distribution. There are approaches in which exponential functions are used to estimate the size distribution of the pile that will be formed before blasting. The most common of these exponential functions used to estimate the average grain size is the Kuz–Ram and KCO functions. The exponential functions provide a curve from 0% to 100% using the mean grain size (X50), characteristic size (XC), and uniformity index (n) parameters. This distribution curve can make predictions in the range of fine grains and coarse grains outside the acceptable error limits in some cases. In this article, the usability of the hyperbolic tangent function, which is symmetrical at origin, in the estimation of the size distribution as an alternative to the exponential distribution functions used in almost all estimation models is investigated. As with exponential functions, the hyperbolic tangent function can express the aggregated size distribution as a percentage with reference to the variables X50 and XC. It has been shown that the hyperbolic tangent function provides 99% accuracy to the distribution of fine grains and coarse grains of the pile formed as a result of blasting data for the characteristic size (XC) parameter and the uniformity index (n).
Degradation of Three Herbicides and Effect on Bacterial Communities under Combined Pollution
Authors: Mei Liangchi , Xia Xinle , Cao Jian , Zhao Yuzhen , Huang Haiyun , Li Ying , Zhang Zhaoxian
Published: August 2024

Pesticide residues in soil, especially multiple herbicide residues, cause a series of adverse effects on soil properties and microorganisms. In this work, the degradation of three herbicides and the effect on bacterial communities under combined pollution was investigated. The experimental results showed that the half-lives of acetochlor and prometryn significantly altered under combined exposure (5.02–11.17 d) as compared with those of individual exposure (4.70–6.87 d) in soil, suggesting that there was an antagonistic effect between the degradation of acetochlor and prometryn in soil. No remarkable variation in the degradation rate of atrazine with half-lives of 6.21–6.85 d was observed in different treatments, indicating that the degradation of atrazine was stable. 16S rRNA high-throughput sequencing results showed that the antagonistic effect of acetochlor and prometryn on the degradation rate under combined pollution was related to variation of the Sphingomonas and Nocardioide. Furthermore, the potential metabolic pathways of the three herbicides in soil were proposed and a new metabolite of acetochlor was preliminarily identified. The results of this work provide a guideline for the risk evaluation of combined pollution of the three herbicides with respect to their ecological effects in soil.
An ISG15-Based High-Throughput Screening Assay for Identification and Characterization of SARS-CoV-2 Inhibitors Targeting Papain-like Protease
Authors: Samrat Subodh Kumar , Kumar Prashant , Liu Yuchen , Chen Ke , Lee Hyun , Li Zhong , Chen Yin , Li Hongmin
Published: August 2024

Emergence of newer variants of SARS-CoV-2 underscores the need for effective antivirals to complement the vaccination program in managing COVID-19. The multi-functional papain-like protease (PLpro) of SARS-CoV-2 is an essential viral protein that not only regulates the viral replication but also modulates the host immune system, making it a promising therapeutic target. To this end, we developed an in vitro interferon stimulating gene 15 (ISG15)-based Förster resonance energy transfer (FRET) assay and screened the National Cancer Institute (NCI) Diversity Set VI compound library, which comprises 1584 small molecules. Subsequently, we assessed the PLpro enzymatic activity in the presence of screened molecules. We identified three potential PLpro inhibitors, namely, NSC338106, 651084, and 679525, with IC50 values in the range from 3.3 to 6.0 µM. These molecules demonstrated in vitro inhibition of the enzyme activity and exhibited antiviral activity against SARS-CoV-2, with EC50 values ranging from 0.4 to 4.6 µM. The molecular docking of all three small molecules to PLpro suggested their specificity towards the enzyme’s active site. Overall, our study contributes promising prospects for further developing potential antivirals to combat SARS-CoV-2 infection.
Conserved Antagonization of Type I Interferon Signaling by Arterivirus GP5 Proteins
Authors: Ringo Rissar Siringo , Choonnasard Amonrat , Okabayashi Tamaki , Saito Akatsuki
Published: August 2024

Arteriviruses can establish persistent infections in animals such as equids, pigs, nonhuman primates, rodents, and possums. Some Arteriviruses can even cause overt and severe diseases such as Equine Arteritis in horses and Porcine Reproductive and Respiratory Syndrome in pigs, leading to huge economic losses. Arteriviruses have evolved viral proteins to antagonize the host cell’s innate immune responses by inhibiting type I interferon (IFN) signaling, assisting viral evasion and persistent infection. So far, the role of the Arterivirus glycoprotein 5 (GP5) protein in IFN signaling inhibition remains unclear. Here, we investigated the inhibitory activity of 47 Arterivirus GP5 proteins derived from various hosts. We demonstrated that all GP5 proteins showed conserved activity for antagonizing TIR-domain-containing adapter proteins inducing interferon-β (TRIF)-mediated IFN-β signaling through TRIF degradation. In addition, Arterivirus GP5 proteins showed a conserved inhibitory activity against IFN-β signaling, induced by either pig or human TRIF. Furthermore, certain Arterivirus GP5 proteins could inhibit the induction of IFN-stimulated genes. These findings highlight the role of Arterivirus GP5 proteins in supporting persistent infection.
Tixagevimab/Cilgavimab for COVID-19 Pre-Exposure Prophylaxis in Hematologic Patients—A Tailored Approach Based on SARS-CoV-2 Vaccine Response
Authors: Braitsch Krischan , Jeske Samuel D. , Stroh Jacob , Hefter Maike , Platen Louise , Bachmann Quirin , Renders Lutz , Protzer Ulrike , Götze Katharina S. , Herhaus Peter , Verbeek Mareike , Spinner Christoph D. , Bassermann Florian , Högner Marion , Haller Bernhard , Schneider Jochen , Heider Michael
Published: August 2024

Patients with hematologic malignancies still face a significant risk of severe coronavirus disease 2019 (COVID-19). The severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2)-neutralizing monoclonal antibody combination tixagevimab/cilgavimab (TIX/CGB) could be administered to immunocompromised patients for pre-exposure prophylaxis (PrEP) before the emergence of TIX/CGB-resistant COVID-19 Omicron variants. TIX/CGB application could be carried out regardless of the host’s immune response to previous active SARS-CoV-2 vaccinations or infections. Because the efficacy of COVID-19 PrEP remains unclear, especially in SARS-CoV-2-seropositive patients, German national guidelines recommended TIX/CGB PrEP only for SARS-CoV-2-seronegative patients in addition to an intensified active vaccination schedule. Having followed these guidelines, we now report the characteristics and outcomes of 54 recipients of TIX/CGB PrEP in SARS-CoV-2-seronegative patients with hematological disease from a German tertiary medical center and compare them to 125 seropositive patients who did not receive any PrEP. While the number of patients with B-cell lymphomas was significantly higher in the seronegative cohort (33 (61%) vs. 18 (14%) cases, p < 0.01), patients with myeloid diseases were significantly more frequent in the seropositive cohort (51 (41%) vs. 5 (9%) cases, p < 0.01). Strikingly, patients who had undergone allogeneic hematopoietic stem cell transplantation were significantly more likely (forty-nine (39%) vs. six (11%) cases, p < 0.01) to be SARS-CoV-2 seropositive. We observed that prophylactic application of TIX/CGB PrEP to a highly vulnerable group of SARS-CoV-2-seronegative patients resulted in a similar number of COVID-19 breakthrough infections compared to the untreated seropositive control group (16 (32%) vs. 39 (36%), p = 0.62) and comparable COVID-19-related outcomes like hospitalization and oxygen requirement throughout an extended follow-up period of 12 months. In conclusion, our results support the tailored approach of administering TIX/CGB PrEP only to SARS-CoV-2-seronegative patients during the COVID-19 pandemic and might provide a rationale for similar strategies during future outbreaks/diseases, especially in times of initial limited availability and/or financial constraints.
Cost-Effectiveness Analysis of Herpes Zoster Vaccination in a Chinese Population: Recombinant Subunit Vaccine versus Live Attenuated Vaccine
Authors: Wang Jiaqi , Jin Pengfei , Jin Hui , Wang Qiang , Zhu Fengcai , Li Jingxin
Published: August 2024

Background: Currently, the recombinant subunit vaccine and live attenuated vaccine in the prevention of herpes zoster are approved for marketing in China. This study aims to evaluate the cost-effectiveness of the recombinant subunit vaccine and the live attenuated vaccine in the Chinese population. Methods: A decision tree–Markov analysis model was utilized to estimate expected costs and quality-adjusted life years (QALYs), comparing the lifetime cost-effectiveness of vaccination with the recombinant subunit vaccine (London, United Kingdom, Shingrix, GSK) to that of the live attenuated vaccine (Changchun, China, Ganwei, Changchun Bcht) in the Chinese population, with the primary outcome measure being the incremental cost-effectiveness ratio (ICER). Results: In the base-case analysis, the ICERs for the recombinant subunit vaccine ranged by age from USD 3428 to USD 5743 per QALY, while the ICERs for the live attenuated vaccine ranged from USD 4017 to USD 18,254 per QALY, compared with no vaccination. Among all age groups, the category of 60 to 69 years was the optimal age for vaccination. The results were most sensitive to changes in herpes zoster incidence, vaccine efficacy, and discount rate. Even with a two-dose compliance rate of 20% for the recombinant subunit vaccine, vaccination remained cost-effective. ZVL would need to reduce costs by at least 12.2% compared to RZV to have a cost-effectiveness advantage. Conclusions: The recombinant subunit vaccine and the live attenuated vaccine were both cost-effective in the Chinese population, but, relatively, the recombinant subunit vaccine had a greater advantage in disease prevention and cost-effectiveness in all age groups above 50 years.
Recent Advancements in mRNA Vaccines: From Target Selection to Delivery Systems
Authors: Wu Zhongyan , Sun Weilu , Qi Hailong
Published: August 2024

mRNA vaccines are leading a medical revolution. mRNA technologies utilize the host’s own cells as bio-factories to produce proteins that serve as antigens. This revolutionary approach circumvents the complicated processes involved in traditional vaccine production and empowers vaccines with the ability to respond to emerging or mutated infectious diseases rapidly. Additionally, the robust cellular immune response elicited by mRNA vaccines has shown significant promise in cancer treatment. However, the inherent instability of mRNA and the complexity of tumor immunity have limited its broader application. Although the emergence of pseudouridine and ionizable cationic lipid nanoparticles (LNPs) made the clinical application of mRNA possible, there remains substantial potential for further improvement of the immunogenicity of delivered antigens and preventive or therapeutic effects of mRNA technology. Here, we review the latest advancements in mRNA vaccines, including but not limited to target selection and delivery systems. This review offers a multifaceted perspective on this rapidly evolving field.
Tree-Based Machine Learning and Nelder–Mead Optimization for Optimized Cr(VI) Removal with Indian Gooseberry Seed Powder
Authors: Kalabarige Lakshmana Rao , Krishna D. , Potnuru Upendra Kumar , Mishra Manohar , Alharthi Salman S. , Koutavarapu Ravindranadh
Published: August 2024

Wastewater containing a mixture of heavy metals, a byproduct of chemical, petrochemical, and refinery activities driven by urbanization and industrial expansion, poses significant environmental threats. Analyzing such wastewater through adsorbate-adsorbent experiments yields extensive datasets. However, traditional methodologies like the Box–Behnken design (BBD) within the response surface methodology (RSM) struggle with managing large datasets and capturing the complex, nonlinear relationships inherent in such experimental data. To address these challenges, ML techniques have emerged as promising tools for accurately predicting the removal percentage of heavy metals from wastewater. In this study, we utilized tree-based regression models—specifically decision tree regression (DTR), random forest regression (RFR), and extra tree regression (ETR)—to forecast the efficiency of gooseberry seed powder in removing chromium (Cr(VI)) from wastewater. Additionally, we employed an ML-based Nelder–Mead optimization approach to identify the optimal values for key features (initial Cr(VI) concentration, pH, and Indian gooseberry powder dosage) which maximized the Cr(VI) removal percentage. Our experimental results reveal that the ETR model achieved an impressive R2 score of 0.99, demonstrating a low error rate in predicting the Cr(VI) removal percentage. Furthermore, we used DTR-Nelder–Mead, RFR-Nelder–Mead, and ETR-Nelder–Mead optimization approaches on a synthesized dataset of 2000 instances while varying the initial Cr(VI) concentration, pH, and Indian gooseberry powder dosage. The analysis determined that the DTR-Nelder–Mead and RFR-Nelder–Mead approaches yielded the highest Cr(VI) removal percentages of 78.21% and 78.107% at an initial concentration of 95.55 mg/L, respectively, a pH level of four, and an adsorbent dosage of 8 g/L of gooseberry seed powder. Furthermore, the ETR-Nelder–Mead approach obtained the maximum Cr(VI) removal percentage of 85.11% at an initial concentration of 99.25 mg/L, a pH level of 4.97, and an adsorbent dosage of 9.62 g/L of gooseberry seed powder. These results reported an increase in the Cr(VI) removal percentage ranging from 4.66% to 11.56% more than the Cr(VI) removal percentage obtained by experimentation. These findings underscore the efficacy of tree-based regression models and ML-based Nelder–Mead optimization in elucidating chromium removal processes from wastewater, offering valuable insights into effective treatment strategies.
Correlation between Discharge Noise and Flow Field Characteristics of Hydraulic Turbine
Authors: Shi Min , Wang Yu , Lu Xiaochun
Published: August 2024

The water flow within the turbine passage of a hydropower station exhibits high-speed closed-pressure flow. The flow field characteristics will directly affect the turbine’s operational efficiency and safety. To ensure the safe operation of the turbine and accurately monitor its flow state, the relationship between the flow characteristics in the turbine passage and its discharge noise must be established. In this study, the relationship between the flow field and the noise field of the turbine is explored using a combination of a model turbine passage discharge noise test and numerical simulation of flow field characteristics. Results show that the operating parameters are closely related to the discharge noise’s characteristics, in which the operating head and discharge of the unit’s operating parameters greatly influence the discharge noise in the flow passage. Hydrodynamic factors, such as fluctuation pressure and pressure in the flow field, show a strong correlation with the discharge noise characteristics. As the pressure and fluctuation pressure in the inlet area of the spiral case intensify, the sound pressure level (SPL) of the discharge noise increases and the main frequency decreases. A large-scale vortex easily forms in the spiral case and draft tube area, thereby causing low-frequency fluctuation and forming high-decibel noise. Also, the runner area is the main sound source region of the turbine passage. The research results will provide technical and theoretical support for the safe operation and accurate fault diagnosis of hydropower stations.
Developing Macroinvertebrate Biotic Indices in Nigerian Urban-Agricultural River Catchments: Is the Continuous Scoring System More Effective than Discrete Scoring System?
Authors: Edegbene Augustine Ovie , Arimoro Francis Ofurum , Odume Oghenekaro Nelson
Published: August 2024

The evaluation of the ecological consequences of anthropogenic stressors is a critical challenge in the management of the environment. Multimetric indices (MMIs) are one of the biomonitoring tools that have been widely explored to assess the ecological health of riverine systems globally, as MMIs have proven to be extremely effective, owing to their ability to incorporate data and information from both structural and functional assemblages of organisms and the entire ecosystem. Currently, there are very few MMIs developed in Nigeria to assess the ecological health of riverine systems, and none of the MMIs was developed for river stations draining urban and agricultural catchments. In order to close this gap, we developed and validated a macroinvertebrate-based MMI for assessing the ecological health of river systems in the Niger Delta area of Nigeria draining urban and agriculture catchments. Furthermore, we also compared the effectiveness of both continuous scoring and discrete systems for the development of MMI. Physico-chemical variables and macroinvertebrates were collected from 17 well-marked out stations that spread throughout 11 different river systems. The stations were classified into three categories based on the degree of impact: least-impacted stations (LIS), moderately impacted stations (MIS), and heavily impacted stations (HIS). Sixty-seven (67) candidate macroinvertebrate metrics were potentially tested, and only five metrics were deemed significant and ultimately retained for integration into the final Niger Delta urban–agriculture MMI. The following five metrics were chosen to remain in use for the MMI development: Chironomidae/Diptera abundance, %Odonata, Margalef index, Oligochaete richness and logarithmic-transformed relative abundance of sprawler. Notable performance rates of 83.3% for the least-impacted stations and 75% for the moderately impacted stations were found during the index’s validation using a different dataset. However, for the stations that were most affected (i.e., the HIS), a 22.2% performance rate was noted. The Niger Delta urban–agriculture MMI was adjudged to be suitable as a biomonitoring tool for riverine systems subjected to similar combined stressors of urban and agricultural pollution.