bluuebunny/crossref_metadata_2025 huggingface dataset:
Simulation and Application of a New Type of Energy-Saving Steel Claw for Aluminum Electrolysis Cells
Authors: Han Jinfeng , Feng Bing , Chen Zejun , Liang Zhili , Chen Yuran , Liang Xuemin
Published: September 2024

Aluminum electrolysis is a typical industry with high energy consumption, and the energy saving of aluminum electrolysis cells is conducive to the sustainable development of the ecological environment. The current density distribution on the steel claws of conventional aluminum electrolysis cells is uneven, resulting in a large amount of power loss. Therefore, a new type of current-equalized steel claw (CESC) is designed in this paper. The ANSYS simulation study shows that the CESC can achieve a more uniform current density distribution and reduce the voltage drop by about 36 mV compared with the traditional steel claw (TSC). In addition, the use of CESC optimizes the temperature distribution of the steel claws and reduces the risk of cracking and deformation. The results of the industrial application tests are highly consistent with the simulation results, confirming the accuracy of the simulation results. The economic benefit analysis shows that using CESC saves 114.1 kWh of electricity per ton of aluminum produced. If this technology can be promoted throughout China, it is expected to save up to 4.75 billion kWh of electricity annually. The development of CESC is promising and of great significance for improving the overall technical level of the aluminum electrolysis industry.
Robust Load Frequency Control of Interconnected Power Systems with Back Propagation Neural Network-Proportional-Integral-Derivative-Controlled Wind Power Integration
Authors: Ye Fang , Hu Zhijian
Published: September 2024

As the global demand for energy sustainability increases, the scale of wind power integration steadily increases, so the system frequency suffers significant challenges due to the huge fluctuations of the wind power output. To address this issue, this paper proposes a Back Propagation Neural Network-Proportional-Integral-Derivative (BPNN-PID) controller to track the output power of the wind power generation system, which can well alleviate the volatility of the wind power output, resulting in the slighter imbalance with the rated wind power output. Furthermore, at the multi-area power system level, to mitigate the impact of the imbalanced wind power injected into the main grid, the H∞ robust controller was designed to ensure the frequency deviation within the admissible range. Finally, a four-area interconnected power system was employed as the test system, and the results validated the feasibility and effectiveness of both the proposed BPNN-PID controller and the robust controller.
Changes in Tax Strategies Due to Corporate Sustainability: Focusing on the Disclosure of Investment Alert Issues
Authors: Shin Yoojin , Choi Boram
Published: September 2024

Delisting events in the stock market significantly impact capital market participants. In South Korea’s KOSDAQ, an investment alert system signals a firm’s delisting in advance. The system provides warnings to investors in the pre-delisting stage. This paper analyzes whether a firm’s tax avoidance strategy changes depending on investment alert issues, which serves as a measure to identify risks related to corporate sustainability in advance. This study conducted an empirical analysis using an OLS model, with tax avoidance as the dependent variable and the variable related to the investment alert issue as the variable of interest. Analysis of 4964 firm-year data from 2011 to 2020 revealed that firms with investor alert issues exhibited significant increases in tax avoidance behaviors. Additionally, tax avoidance significantly increased when firms were designated as investment alert issues in the designated year. These results provide empirical evidence that such designations may pose a risk to corporate sustainability and intensify a firm’s tax avoidance behavior.
Concentrations of Organochlorine, Organophosphorus, and Pyrethroid Pesticides in Rivers Worldwide (2014–2024): A Review
Authors: López-Benítez Acela , Guevara-Lara Alfredo , Domínguez-Crespo Miguel A. , Andraca-Adame José A. , Torres-Huerta Aidé M.
Published: September 2024

The extensive use of pesticides has led to the contamination of natural resources, sometimes causing significant and irreversible damage to the environment and human health. Even though the use of many pesticides is banned, these compounds are still being found in rivers worldwide. In this review, 205 documents have been selected to provide an overview of pesticide contamination in rivers over the last 10 years (2014–2024). After these documents were examined, information of 47 river systems was organized according to the types of pesticides most frequently detected, including organochloride, organophosphorus, and pyrethroid compounds. A total of 156 compounds were classified, showing that 46% of these rivers contain organochlorine compounds, while 40% exhibit organophosphorus pesticides. Aldrin, hexachlorocyclohexane, and endosulfan were the predominant organochlorine pesticides with concentration values between 0.4 and 37 × 105 ng L−1. Chlorpyrifos, malathion, and diazinon were the main organophosphorus pesticides with concentrations between 1 and 11 × 105 ng L−1. Comparing the pesticide concentrations with standard guidelines, we found that the Ganga River in India (90 ng L−1), the Owan and Okura Rivers in Nigeria (210 and 9 × 103 ng L−1), and the Dong Nai River in Vietnam (68 ng L−1) exceed the permissible levels of aldrin (30 ng L−1).
How Does Digital Transformation Moderate Green Culture, Job Satisfaction, and Competitive Advantage in Sustainable Hotels?
Authors: Degirmen Gul Coskun , Ozbey Derya Ozilhan , Sardagı Emine , Tekin Ilknur Cevik , Koc Durmus , Erdogan Pınar , Koc Feden , Arık Emel
Published: September 2024

Target groups within an organization adopt its culture, reflecting it in all internal and external business processes. Adopting a green organizational culture in hotels with sustainability certificates plays an important role in reshaping business processes by developing sustainability awareness among employees. Digital transformation, which facilitates corporate culture and business processes, plays a role in employee job satisfaction while also supporting environmental, social, and economic sustainability. This research aims to determine the relationship between green organizational culture, job satisfaction, and competitive advantage variables and to examine the moderating role of digital transformation on these relationships. The data-collecting techniques of choice were surveys and semi-structured interviews. While Amos software (Version 24) was used to test the hypothetical model in the analysis of survey data, a Hayes Process macro was used to determine the moderating effect. The interview forms’ data was analyzed using a bag-of-words model. According to the research results, there is a positive relationship between the participation, consistency, and adaptability sub-dimensions of green organizational culture and job satisfaction, while there is no significant relationship between the mission sub-dimension and job satisfaction. Furthermore, the study reveals the moderating role of digital transformation in the effect of job satisfaction on competitive advantage.
Research on the Green Transition Path of Airport Development under the Mechanism of Tripartite Evolutionary Game Model
Authors: Lv Yangyang , Wan Lili , Zhang Naizhong , Wang Zhan , Tian Yong , Ye Wenjing
Published: September 2024

Since existing studies primarily explore green development measures from the static perspective of a single airport stakeholder, this paper constructs an evolutionary game model to analyze the strategic choices of three key stakeholders: airport authorities, third-party organizations, and government departments, based on evolutionary game theory. By solving the stable strategy of the tripartite evolution using the Jacobian matrix, the green transition of airport development can be divided into three stages: “initiation”, “development”, and “maturity”, allowing for the exploration of key factors influencing the green transition of airport development. A simulation analysis is conducted based on real Guangzhou Baiyun International Airport data. The results indicate that the tripartite evolutionary game strategy is stable at E4(0,0,1) and the green transition of Baiyun Airport remains in the development stage. By improving the reward and punishment mechanisms of government departments, the evolutionary game strategy can be stabilized at E8(1,1,1), promoting the green transition of airport development toward the mature stage. By adjusting the game parameters, the dynamic process of green transition in airports at different levels of development and under varying regulatory environments can be effectively captured, supporting the precise formulation of corresponding policies.
Environmental, Social, and Governance Scores and Loan Composition Inside United States Banks
Authors: Bressan Silvia
Published: September 2024

We analyze the loan portfolios of United States banks from 2013 to 2023, showing that high environmental, social, and governance (ESG) banks have larger shares of consumer loans and commercial loans and smaller shares of construction loans and real estate loans. We also find that the governance pillar (G) is more tightly related to the bank loan composition compared to the environmental (E) and social (S) pillars. Furthermore, we show that construction loans and real estate loans decrease more considerably with bank ESG scores inside countries with high gas emissions, i.e., where ESG issues would arguably be more serious. Our interpretation is that sustainable banks are reluctant in lending money for real estate projects, exposing them to potentially high ESG risk. These findings contribute to developing a deeper insight about the relationship between ESG and bank lending, which, in the previous literature, has been treated more frequently in aggregate terms instead of separating loan types. Our outcomes suggest that sustainability is crucial for the availability of funds in the real estate sector, delivering important insights to bank and real estate managers, besides policy makers.
Framework for Rail Transport Inequality Assessment: A Case Study of the Indian Railway Zones with Superfast Express (SE) Trains
Authors: Chandra Shailesh , Mishra Vivek
Published: September 2024

The paper presents a framework for assessing inequality in passenger rail services by examining connectivity and accessibility across two different travelframes: favorable (daytime travel) and unfavorable (nighttime travel). The unfavorable timeframe is often characterized by a lack of adequate first-/last-mile transport availability to train stations, impacting passenger access. The study employs a newly developed inequality-to-investment ratio to classify rail transport entities like stations, routes, or zones as either winners or losers, using a performance persistence analysis. A case study was conducted using data on the superfast express (SE) train schedule and investments from 2016 to 2020 across sixteen zones of the Indian Railway, assessing service inequalities during the hours of favorable (7 a.m. to 9 p.m.) and unfavorable (9 p.m. to 7 a.m.) timeframes. Results revealed inconsistencies in inequalities among zones. Moreover, the research demonstrates that the choice between connectivity and accessibility metrics significantly influences the identification of better or worse performing zones as winners or losers, respectively, throughout the 2016–2020 period and during both timeframes. The study underscores the importance of selecting appropriate measures and suggests re-evaluating or increasing investments in certain zones of Indian Railways based on these insights. The framework proposed in this paper can be used to assess inequalities within any transportation system receiving investments or government funds, contributing to the broader goal of ensuring equitable access to transportation, which is essential for a sustainable transportation system.
Dynamic Multi-Function Lane Management for Connected and Automated Vehicles Considering Bus Priority
Authors: Zhang Zhen , Rong Lingfei , Xie Zhiquan , Yang Xiaoguang
Published: September 2024

Bus lanes are commonly implemented to ensure absolute priority for buses at signalized intersections. However, while prioritizing buses, existing bus lane management strategies often exacerbate traffic demand imbalances among lanes. To address this issue, this paper proposes a dynamic Multi-Function Lane (MFL) management strategy. The proposed strategy transforms traditional bus lanes into Multi-Function Lanes (MFLs) that permit access to Connected and Automated Vehicles (CAVs). By fully utilizing the idle right-of-way of the MFL, the proposed strategy can achieve traffic efficiency improvement. To evaluate the proposed strategy, some experiments are conducted under various demand levels and CAV penetration rates. The results reveal that the proposed strategy (i) improves the traffic intensity balance degree by up to 52.9 under high demand levels; (ii) reduces delay by up to 80.56% and stops by up to 89.35% with the increase in demand level and CAV penetration rate; (iii) guarantees absolute bus priority under various demand levels and CAV penetration rates. The proposed strategy performs well even when CAV penetration is low. This indicates that the proposed strategy has the potential for real-world application.
Modeling of Applying Road Pricing to Airport Highway Using VISUM Software in Jordan
Authors: Assolie Amani Abdallah , Imam Rana , Khliefat Ibrahim , Alobeidyeen Ala
Published: September 2024

Road congestion in Amman City has been increasing yearly, due to the increase in private car ownership and traffic volumes. This study aims to (a) evaluate the toll road’s effects on society and the economy in Amman, Jordan, through a survey questionnaire using statistical software (SPSS), (b) assess the impact of the toll road on reducing congestion and delays using micro-simulation (VISUM), (c) identify the optimal toll price for a selected road using VISUM and (d) validate the simulated models with the optimal revenue. Traffic, geometric, and cost data about the toll technique of two sections on the Airport Highway (from the Ministry of Foreign Affairs to the Madaba Interchange; and from the Madaba Interchange to the Queen Alia International Airport (QAIA) Interchange) were used for simulation purposes. The toll road (across seven different scenarios at different prices) was evaluated for optimal revenue. The survey questionnaire was made based on all scenarios, including the AM peak hour. The operation cost for the toll road was determined based on the Greater Amman Municipality (GAM). The best scenario was determined based on the value of revenue (JOD). The results indicate that higher acceptance is achieved when applying road pricing during the AM peak hour and that users prefer the charging method based on travelled distance (54.02%). Additionally, the total cost of the manual toll collection (MTC) method is 126,935 JOD. Road pricing can reduce traffic delay (or speed up traffic flow) by 4.61 min in the southbound direction and by 9.52 min in the northbound direction. The optimal toll value is 0.25 JOD (34.08%), with revenues of 1089.6 JOD for 2024 and 1122.6 JOD for 2025. Eventually, applying road pricing on the airport road is shown to be effective and economically feasible only when using the manual method.
Spatial Influence of Digital Economy on Carbon Emission Efficiency of the Logistics Industry across 30 Provinces in China
Authors: Guo Yuxia , Wu Xue , Ding Heping , Tian Zhouyu
Published: September 2024

The logistics industry (LI) is a key pillar of the global economy, and its carbon emission efficiency (CEE) is crucial for achieving carbon neutrality. The rapid development of the digital economy (DE) has had a profound impact on the LI, but the spatial impact on its CEE is currently unclear and requires further research. Firstly, based on the collection of relevant data, we use the entropy weight method and linear weighted sum method to measure the level of development of the DE. Secondly, the SBM model is used to measure the CEE level of the LI. Using Moran’s I index model and OLS and GWR models, we analyze the impact and spatial distribution characteristics of the DE on the CEE of the LI and propose development strategies. The article uses statistical data from 30 provinces in China from 2013 to 2022 as an example to demonstrate the implementation process of the method. The results show that the DE has a positive impact on the CEE of the LI, and there are spatial differences. Based on this, this article proposes policy recommendations for the development of green and low-carbon logistics and digital logistics that are tailored to local conditions, providing theoretical and methodological support for low-carbon research in the LI, and providing reference for other countries and regions to explore the path of green and low-carbon transformation.
Charging and Discharging Modeling of Inertial Sensors Based on Ultraviolet Charge Management
Authors: Zhao Zihan , Yu Tao , Wang Shang , Li Huadong , Wang Zhi
Published: September 2024

Inertial sensors act as inertial references in space gravitational wave detection missions, necessitating that their internal test mass (TM) maintains minimal residual acceleration noise. High-energy particles and cosmic rays in space, along with ion pumps in ground-based torsion pendulum experiments, can cause charge accumulation on the TM surface, leading to increased residual acceleration noise. Consequently, a charge management system was introduced to control the TM’s charge. The complex light path propagation within the electrode housing (EH) makes the TM’s charging and discharging process difficult to theoretically calculate and fully simulate. To address this issue, we propose a simulation method for charging and discharging inertial sensors within ultraviolet (UV) charge management systems. This method innovatively considers the impact of photoelectron emission angle and the TM’s position offset from symmetry on performance. The method also simulates charging and discharging rates over time under conditions of symmetry and preliminarily examines factors affecting the TM’s equilibrium potential. Simulation results indicate that this method effectively models the charge management system’s operation, providing a valuable reference for system design.
OGSS: An Ontology-Guided and Scheduled-Sampling Approach for Overlapping Event Extraction
Authors: Zhu Jizhao , Wen Hualong , Pan Xinlong , Li Xiang
Published: September 2024

Event extraction is a complex and challenging task in the field of information extraction. It aims to identify event types, triggers, and argument information from the text. In recent years, overlapping event extraction has attracted the attention of researchers because of its higher challenge and practicability, and some work has carried out in-depth research on overlapping event extraction and achieved remarkable results. But these works (1) ignore the role of ontology knowledge in event extraction; (2) use the same semantic encoding for multi-stage models, lacking consideration for the independent characteristics of extraction tasks such as event types, triggers, and arguments; and (3) face issues in the training process of multi-stage models, such as error cascading and slow convergence. To address the above issues, we propose an ontology-guided and scheduled-sampling approach for overlapping event extraction, termed as OGSS. First, we design a symmetric matrix for event ontology knowledge representation and integrate it into the semantic encoding process, infusing ontology knowledge into event extraction. Second, for extraction targets such as event types, triggers, and arguments, we process the semantic encoding according to the characteristics of each extraction target, obtaining semantic representations tailored for each subtask. Finally, we view multi-stage predictions as sequential outputs of a joint model, using a scheduled sampling strategy between subtasks to effectively mitigate the cascading propagation of errors during training and accelerate model convergence. We conduct extensive experiments on the FewFc event extraction benchmark dataset. The results show that OGSS achieves significant improvements in overlapping event extraction tasks compared to previous methods.
Partial Imaginary Transition State (ITS) Graphs: A Formal Framework for Research and Analysis of Atom-to-Atom Maps of Unbalanced Chemical Reactions and Their Completions
Authors: González Laffitte Marcos E. , Weinbauer Klaus , Phan Tieu-Long , Beier Nora , Domschke Nico , Flamm Christoph , Gatter Thomas , Merkle Daniel , Stadler Peter F.
Published: September 2024

Atom-to-atom maps (AAMs) are bijections that establish the correspondence of reactant and product atoms across chemical reactions. They capture crucial features of the reaction mechanism and thus play a central role in modeling chemistry at the level of graph transformations. AAMs are equivalent to so-called “imaginary transition state” (ITS) graphs, making it possible to reduce tasks such as the computational comparison of AAMs to testing graph isomorphisms. In many application scenarios, nonetheless, only partial information is available, i.e., only partial maps or, equivalently, only subgraphs of the ITS graphs, are known. Here, we investigate whether and how, and to what extent, such partial chemical data can be completed and compared. The focus of this contribution is entirely on the development of a solid mathematical foundation for the analysis of partial AAMs and their associated partial ITS graphs.
Governance of Corporate Greenwashing through ESG Assurance
Authors: Bu Meiwen , Liu Xin , Zhang Bin , Hazaea Saddam A. , Fan Run , Wang Zijian
Published: September 2024

This study utilizes data from Chinese A-share listed companies from 2014 to 2022 to theoretically analyze and empirically test the governance effect of ESG assurance on corporate greenwashing behavior, as well as the role played by the legal environment and management shareholding in this context. The impacts of ownership and the governance mechanism of ESG assurance on corporate greenwashing behavior are also explored. This study employs text mining, OLS, PSM, IV-LIML, treatment effect models, feasible generalized least squares, placebo tests, bootstrap methods, etc., to conduct empirical analysis and conclude the following results: ESG assurance has a significant inhibitory effect on corporate greenwashing behavior, playing a crucial role in resource allocation, particularly in non-state-owned enterprises. The legal environment has a certain substitution effect on ESG assurance in inhibiting corporate greenwashing behavior, meaning that when the legal environment is weak, ESG assurance is more effective in curbing such behavior. Management shareholding also has a certain substitution effect on ESG assurance in inhibiting corporate greenwashing behavior, indicating that when management shareholding is low, ESG assurance is better at curbing such behavior. Further research reveals that corporate ESG performance plays a mediating role between ESG assurance and corporate greenwashing governance. This article provides policy references and empirical evidence for strengthening ESG assurance and enhancing corporate ESG performance and greenwashing governance to promote high-quality corporate development.
The Influence of Machine Learning on Enhancing Rational Decision-Making and Trust Levels in e-Government
Authors: Salem Ayat Mohammad , Eyupoglu Serife Zihni , Ma’aitah Mohammad Khaleel
Published: September 2024

The rapid growth in the use of AI techniques, mainly machine learning (ML), is revolutionizing different industries by significantly enhancing decision-making processes through data-driven insights. This study investigates the influence of using ML, particularly supervised and unsupervised learning, on rational decision-making (RDM) within Jordanian e-government, focusing on the mediating role of trust. By analyzing the experiences of middle-level management within e-government in Jordan, the findings underscore that ML positively impacts the rational decision-making process in e-government. It enables more efficient and effective data gathering, improves the accuracy of data analysis, enhances the speed and accuracy of evaluating decision alternatives, and improves the assessment of potential risks. Additionally, this study reveals that trust plays a critical role in determining the effectiveness of ML adoption for decision-making, acting as a pivotal mediator that can either facilitate or impede the integration of these technologies. This study provides empirical evidence of how trust not only enhances the utilization of ML but also amplifies its positive impact on governance. The findings highlight the necessity of cultivating trust to ensure the successful deployment of ML in public administration, thereby enabling a more effective and sustainable digital transformation. Despite certain limitations, the outcomes of this study offer substantial insights for researchers and government policymakers alike, contributing to the advancement of sustainable practices in the e-government domain.
Tiny but Mighty: Vipera ammodytes meridionalis (Eastern Long-Nosed Viper) Ontogenetic Venom Variations in Procoagulant Potency and the Impact on Antivenom Efficacies
Authors: Qiao Zichen , Jones Lee , Bourke Lachlan A. , Seneci Lorenzo , Chowdhury Abhinandan , Violette Aude , Fourmy Rudy , Soria Raul , Aldridge Matt , Fry Bryan G.
Published: September 2024

The Eastern Long-Nosed Viper (Vipera ammodytes meridionalis) is considered one of the most venomous snakes in Europe. However, it is unknown whether ontogenetic variation in venom effects occurs in this subspecies and how this may impact antivenom efficacy. In this study, we compared the procoagulant activities of V. a. meridionalis venom on human plasma between neonate and adult venom phenotypes. We also examined the efficacy of three antivenoms—Viperfav, ViperaTAb, and Inoserp Europe—across our neonate and adult venom samples. While both neonate and adult V. a. meridionalis venoms produced procoagulant effects, the effects produced by neonate venom were more potent. Consistent with this, neonate venom was a stronger activator of blood-clotting zymogens, converting them into their active forms, with a rank order of Factor X >> Factor VII > Factor XII. Conversely, the less potent adult venom had a rank order of FXII marginally more activated than Factor VII, and both much more so than Factor X. This adds to the growing body of evidence that activation of factors besides FII (prothrombin) and FX are significant variables in reptile venom-induced coagulopathy. Although all three examined antivenoms displayed effective neutralization of both neonate and adult V. a. meridionalis venoms, they generally showed higher efficacy on adult venom than on neonate venom. The ranking of antivenom efficacy against neonate venom, from the most effective to the least effective, were Viperfav, Inoserp Europe, ViperaTAb; for adult venom, the ranking was Inoserp Europe, Viperfav, ViperaTAb. Our data reveal ontogenetic variation in V. a meridionalis, but this difference may not be of clinical concern as antivenom was effective at neutralizing both adult and neonate venom phenotypes. Regardless, our results highlight a previously undocumented ontogenetic shift, likely driven by the documented difference in prey preference observed for this species across age classes
Comparative Effects of Efavirenz and Dolutegravir on Metabolomic and Inflammatory Profiles, and Platelet Activation of People Living with HIV: A Pilot Study
Authors: Roux Crystal G. , Mason Shayne , du Toit Louise D. V. , Nel Jan-Gert , Rossouw Theresa M. , Steel Helen C.
Published: September 2024

Antiretroviral therapy (ART) has reduced the mortality and morbidity associated with HIV. However, irrespective of treatment, people living with HIV remain at a higher risk of developing non-AIDS-associated diseases. In 2019, the World Health Organization recommended the transition from efavirenz (EFV)- to dolutegravir (DTG)-based ART. Data on the impact of this transition are still limited. The current study therefore investigated the metabolic profiles, cytokine inflammatory responses, and platelet activation before and after the treatment transition. Plasma samples from nine virally suppressed adults living with HIV and sixteen healthy, HIV-uninfected individuals residing in Gauteng, South Africa were compared. Metabolite and cytokine profiles, and markers associated with platelet activation, were investigated with untargeted proton magnetic resonance metabolomics, multiplex suspension bead array immunoassays, and sandwich enzyme-linked immunosorbent assays, respectively. In those individuals with normal C-reactive protein levels, the transition to a DTG-based ART regimen resulted in decreased concentrations of acetoacetic acid, creatinine, adenosine monophosphate, 1,7-dimethylxanthine, glycolic acid, 3-hydroxybutyric acid, urea, and lysine. Moreover, increased levels of formic acid, glucose, lactic acid, myo-inositol, valine, glycolic acid, and 3-hydroxybutyric acid were observed. Notably, levels of interleukin-6, platelet-derived growth factor-BB, granulocyte-macrophage colony-stimulating factor, tumor necrosis factor–alpha, soluble cluster of differentiation 40 ligand, as well as regulated on activation, normal T-cell expressed and secreted (RANTES) reached levels close to those observed in the healthy control participants. The elevated concentration of macrophage inflammatory protein-1 alpha was the only marker indicative of elevated levels of inflammation associated with DTG-based treatment. The transition from EFV- to DTG-based regimens therefore appears to be of potential benefit with metabolic and inflammatory markers, as well as those associated with cardiovascular disease and other chronic non-AIDS-related diseases, reaching levels similar to those observed in individuals not living with HIV.
Protection Evaluation of a New Attenuated ASFV by Deletion of the L60L and CD2v Genes against Homologous Challenge
Authors: Yang Jinjin , Zhu Rongnian , Li Nan , Zhang Yanyan , Zhou Xintao , Yue Huixian , Li Qixuan , Wang Yu , Miao Faming , Chen Teng , Zhang Fei , Zhang Shoufeng , Qian Aidong , Hu Rongliang
Published: September 2024

African swine fever (ASF) is an acute infectious disease with a high mortality rate in both domestic and wild boars. Commercial vaccines or antiviral drugs for ASF were not available due to the complex diversity of the structure and genome of its pathogen African swine fever virus (ASFV). In recent years, there have been many reports on candidate strains of attenuated vaccines for ASFV. In this study, we obtained a recombinant virus named SY18ΔL60LΔCD2v by simultaneously deleting the L60L gene and CD2v gene from highly virulent strain SY18. In vitro, SY18ΔL60LΔCD2v displayed a decreased growth kinetic compared to that of parental SY18. In vivo, high doses (105 TCID50) of SY18ΔL60LΔCD2v can protect pigs (5/5) from attacks by the parental SY18 strain (102 TCID50). Low doses (102 TCID50) of SY18ΔL60LΔCD2v only protected 20% of pigs (1/5) from attacks by the parental SY18 strain (102 TCID50). The results indicated that the absence of these two genes in SY18 could induce protection against the homologous parental strain, and there were no obvious clinical symptoms or viremia. These results indicate that the SY18ΔL60LΔCD2v strain can serve as a new live attenuated vaccine candidate for the prevention and control of ASFV infection.
Complete Genome Sequencing and Comparative Phylogenomics of Nine African Swine Fever Virus (ASFV) Isolates of the Virulent East African p72 Genotype IX without Viral Sequence Enrichment
Authors: Domelevo Entfellner Jean-Baka , Okoth Edward Abworo , Onzere Cynthia Kavulani , Upton Chris , Njau Emma Peter , Höper Dirk , Henson Sonal P. , Oyola Samuel O. , Bochere Edwina , Machuka Eunice M. , Bishop Richard P.
Published: September 2024

African swine fever virus (ASFV) is endemic to African wild pigs (Phacochoerus and Potamochoerus), in which viral infection is asymptomatic, and Ornithodoros soft ticks. However, ASFV causes a lethal disease in Eurasian domestic pigs (Sus scrofa). While Sub-Saharan Africa is believed to be the original home of ASFV, publicly available whole-genome ASFV sequences show a strong bias towards p72 Genotypes I and II, which are responsible for domestic pig pandemics outside Africa. To reduce this bias, we hereby describe nine novel East African complete genomes in p72 Genotype IX and present the phylogenetic analysis of all 16 available Genotype IX genomes compared with other ASFV p72 clades. We also document genome-level differences between one specific novel Genotype IX genome sequence (KE/2013/Busia.3) and a wild boar cell-passaged derivative. The Genotype IX genomes clustered with the five available Genotype X genomes. By contrast, Genotype IX and X genomes were strongly phylogenetically differentiated from all other ASFV genomes. The p72 gene region, on which the p72-based virus detection primers are derived, contains consistent SNPs in Genotype IX, potentially resulting in reduced sensitivity of detection. In addition to the abovementioned cell-adapted variant, eight novel ASFV Genotype IX genomes were determined: five from viruses passaged once in primary porcine peripheral blood monocytes and three generated from DNA isolated directly from field-sampled kidney tissues. Based on this methodological simplification, genome sequencing of ASFV field isolates should become increasingly routine and result in a rapid expansion of knowledge pertaining to the diversity of African ASFV at the whole-genome level.
The Synergistic Effect of Baloxavir and Neuraminidase Inhibitors against Influenza Viruses In Vitro
Authors: Guo Xiaojia , Zhao Lei , Li Wei , Cao Ruiyuan , Zhong Wu
Published: September 2024

Influenza viruses remain a major threat to human health. Four classes of drugs have been approved for the prevention and treatment of influenza infections. Oseltamivir, a neuraminidase inhibitor, is a first-line anti-influenza drug, and baloxavir is part of the newest generation of anti-influenza drugs that targets the viral polymerase. The emergence of drug resistance has reduced the efficacy of established antiviral drugs. Combination therapy is one of the options for controlling drug resistance and enhancing therapeutical efficacies. Here, we evaluate the antiviral effects of baloxavir combined with neuraminidase inhibitors (NAIs) against wild-type influenza viruses, as well as influenza viruses with drug-resistance mutations. The combination of baloxavir with NAIs led to significant synergistic effects; however, the combination of baloxavir with laninamivir failed to result in a synergistic effect on influenza B viruses. Considering the rapid emergence of drug resistance to baloxavir, we believe that these results will be beneficial for combined drug use against influenza.
Epithelial Antimicrobial Peptide/Protein and Cytokine Expression Profiles Obtained from Nasopharyngeal Swabs of SARS-CoV-2-Infected and Non-Infected Subjects
Authors: Gambichler Thilo , Goesmann Silke , Skrygan Marina , Susok Laura , Schütte Christian , Hamdani Nahza , Schmidt Wolfgang
Published: September 2024

Immune responses of the epithelia of the upper respiratory tract are likely crucial in early inhibition of the viral replication and finally clearance of SARS-CoV-2. We aimed to compare the expression profiles of antimicrobial peptides/proteins (AMPs) and related cytokines observed in the nasopharynx of SARS-CoV-2-infected patients and non-infected controls and to assess the associations between these parameters and COVID-19 patients’ outcomes. We included 45 subjects who had tested positive for SARS-CoV-2 and 22 control subjects who had tested negative for SARS-CoV-2. Biomaterial for SARS-CoV-2 detection, as well as gene and protein expression studies, was obtained from all subjects using nasopharyngeal swabs which were performed a maximum of 7 days before inclusion in the study. Univariable and multivariable statistics were performed. When compared to the controls, the mRNA expression levels of human β-defensin 1 (hBD-1), LL-37, and trappin-2 were significantly higher in specimens of nasopharyngeal swabs from COVID-19 patients. Protein expression of hBD-1 was also increased in the COVID-19 group. mRNA expression levels of interferon-ɣ (IFN-ɣ), tumor necrosis factor- ɑ (TNF-ɑ), and interleukin-6 (IL-6) measured in SARS-CoV-2-infected patients were significantly higher than those observed in the controls, which could also be confirmed in the protein levels of IFN-ɣ and IL-6. A significant correlation between mRNA and protein levels could be observed only for IL-6. Univariable analysis revealed that low IFN-ɣ mRNA levels were associated with severe/fatal outcomes. The occurrence of COVID-19 pneumonia was significantly associated with lower expression levels of IL-6 mRNA, IFN-ɣ mRNA, and TNF-ɑ mRNA. Concerning the severe/fatal outcomes, the multivariable logistic regression model revealed that none of the aforementioned parameters remained significant in the model. However, the logistic regression model revealed that higher TNF-ɑ mRNA expression was a significant independent predictor of absence of pneumonia [odds ratio: 0.35 (95% CI 0.14 to 0.88, p = 0.024)]. In conclusion, nasopharyngeal expression of AMPs (hBD-1, LL-37, and trappin-2) and cytokines (IL-6, IFN-ɣ, and TNF-ɑ) is upregulated in response to early SARS-CoV-2 infection, indicating that these AMPs and cytokines play a role in the local host defense against the virus. Upregulated nasopharyngeal TNF-ɑ mRNA expression during the early phase of SARS-CoV-2 infection was a significant independent predictor of the absence of COVID-19 pneumonia. Hence, high TNF-ɑ mRNA expression in the nasopharynx appears to be a protective factor for lung complications in COVID-19 patients.
A Serum Multi-Parametric Analysis Identifies an Early Innate Immune Signature Associated to Increased Vaccine-Specific Antibody Production and Seroconversion in Simultaneous COVID-19 mRNA and Cell-Based Quadrivalent Influenza Vaccination
Authors: Severa Martina , Ricci Daniela , Etna Marilena Paola , Facchini Marzia , Puzelli Simona , Fedele Giorgio , Iorio Egidio , Cairo Giada , Castrechini Sara , Ungari Valentina , Iannetta Marco , Leone Pasqualina , Chirico Mattea , Pisanu Maria Elena , Bottazzi Barbara , Benedetti Livia , Sali Michela , Bartolomucci Remo , Balducci Stefano , Garlanda Cecilia , Stefanelli Paola , Spadea Antonietta , Palamara Anna Teresa , Coccia Eliana Marina
Published: September 2024

In this pilot study, a multi-parametric analysis comparing immune responses in sera of adult healthy subjects (HS) or people with type 2 diabetes mellitus (T2D) undergoing the single or simultaneous administration of mRNA-based COVID-19 and cellular quadrivalent inactivated influenza vaccines was conducted. While SARS-CoV-2 antibodies remains comparable, influenza antibody titers and seroconversion were significantly higher upon simultaneous vaccination. Magnitude of anti-influenza humoral response closely correlated with an early innate immune signature, previously described for the COVID-19 vaccine, composed of IL-15, IL-6, TNF-α, IFN-γ, CXCL-10 and here extended also to acute-phase protein Pentraxin 3. People with T2D receiving simultaneous vaccination showed a protective response comparable to HS correlating with the early induction of IFN-γ/CXCL10 and a significant reduction of the circulating glucose level due to increased oxidation of glucose digestion and consumption. These data, although preliminary and in-need of validation in larger cohorts, might be exploited to optimize future vaccination in people with chronic disorders, including diabetes.
Hybrid Immunity against SARS-CoV-2 Variants: A Narrative Review of the Literature
Authors: Tsagkli Panagiota , Geropeppa Maria , Papadatou Ioanna , Spoulou Vana
Published: September 2024

The emergence of SARS-CoV-2 led to a global health crisis and the burden of the disease continues to persist. The rapid development and emergency authorization of various vaccines, including mRNA-based vaccines, played a pivotal role in mitigating severe illness and mortality. However, rapid viral mutations, leading to several variants of concern, challenged vaccine effectiveness, particularly concerning immune evasion. Research on immunity, both from natural infection and vaccination, revealed that while neutralizing antibodies provide protection against infection, their effect is short-lived. The primary defense against severe COVID-19 is derived from the cellular immune response. Hybrid immunity, developed from a combination of natural infection and vaccination, offers enhanced protection, with convalescent vaccinated individuals showing significantly higher levels of neutralizing antibodies. As SARS-CoV-2 continues to evolve, understanding the durability and breadth of hybrid immunity becomes crucial. This narrative review examines the latest data on humoral and cellular immunity from both natural infection and vaccination, discussing how hybrid immunity could inform and optimize future vaccination strategies in the ongoing battle against COVID-19 and in fear of a new pandemic.
Preclinical Development of a Novel Zika Virus-like Particle Vaccine in Combination with Tetravalent Dengue Virus-like Particle Vaccines
Authors: Rothen Dominik A. , Dutta Sudip Kumar , Krenger Pascal S. , Pardini Alessandro , Vogt Anne-Cathrine S. , Josi Romano , Lieknina Ilva , Osterhaus Albert D. M. E. , Mohsen Mona O. , Vogel Monique , Martina Byron , Tars Kaspars , Bachmann Martin F.
Published: September 2024

Declared as a Public Health Emergency in 2016 by the World Health Organization (WHO), the Zika virus (ZIKV) continues to cause outbreaks that are linked to increased neurological complications. Transmitted mainly by Aedes mosquitoes, the virus is spread mostly amongst several tropical regions with the potential of territorial expansion due to environmental and ecological changes. The ZIKV envelope protein’s domain III, crucial for vaccine development due to its role in receptor binding and neutralizing antibody targeting, was integrated into sterically optimized AP205 VLPs to create an EDIII-based VLP vaccine. To increase the potential size of domains that can be accommodated by AP205, two AP205 monomers were fused into a dimer, resulting in 90 rather than 180 N-/C- termini amenable for fusion. EDIII displayed on AP205 VLPs has several immunological advantages, like a repetitive surface, a size of 20–200 nm (another PASP), and packaged bacterial RNA as adjuvants (a natural toll-like receptor 7/8 ligand). In this study, we evaluated a novel vaccine candidate for safety and immunogenicity in mice, demonstrating its ability to induce high-affinity, ZIKV-neutralizing antibodies without significant disease-enhancing properties. Due to the close genetical and structural characteristics, the same mosquito vectors, and the same ecological niche of the dengue virus and Zika virus, a vaccine covering all four Dengue viruses (DENV) serotypes as well as ZIKV would be of significant interest. We co-formulated the ZIKV vaccine with recently developed DENV vaccines based on the same AP205 VLP platform and tested the vaccine mix in a murine model. This combinatory vaccine effectively induced a strong humoral immune response and neutralized all five targeted viruses after two doses, with no significant antibody-dependent enhancement (ADE) observed. Overall, these findings highlight the potential of the AP205 VLP-based combinatory vaccine as a promising approach for providing broad protection against DENV and ZIKV infections. Further investigations and preclinical studies are required to advance this vaccine candidate toward potential use in human populations.
Enhancing Evapotranspiration Estimations through Multi-Source Product Fusion in the Yellow River Basin, China
Authors: Wang Runke , You Xiaoni , Shi Yaya , Wu Chengyong
Published: September 2024

An accurate estimation of evapotranspiration (ET) is critical to understanding the water cycle in watersheds and promoting the sustainable utilization of water resources. Although there are various ET products in the Yellow River Basin, various ET products have many uncertainties due to input data, parameterization schemes, and scale conversion, resulting in significant uncertainties in regional ET data products. To reduce the uncertainty of a single product and obtain more accurate ET data, more accurate ET data can be obtained by fusing different ET data. Addressing this challenge, by calculating the uncertainty of three ET data products, namely global land surface satellite (GLASS) ET, Penman–Monteith–Leuning (PML)-V2 ET, and reliability-affordable averaging (REA) ET, the weight of each product is obtained to drive the Bayesian three-cornered Hat (BTCH) algorithm to obtain higher quality fused ET data, which are then validated at the site and basin scales, and the accuracy has significantly improved compared to a single input product. On a daily scale, the fused data’s root mean square error (RMSE) is 0.78 mm/day and 1.14 mm/day. The mean absolute error (MAE) is 0.53 mm/day and 0.84 mm/day, respectively, which has a lower RMSE and MAE than the model input data; the correlation coefficients (R) are 0.9 and 0.83, respectively. At the basin scale, the RMSE and MAE of the annual average ET of the fused data are 11.77 mm/year and 14.95 mm/year, respectively, and the correlation coefficient is 0.84. The results show that the BTCH ET fusion data are better than single-input product data. An analysis of the fused ET data on a spatiotemporal scale shows that from 2001 to 2017, the ET increased in 85.64% of the area of the Yellow River Basin. Fluctuations in ET were greater in the middle reaches of the Yellow River than in the upstream and downstream regions. The BTCH algorithm has indispensable reference value for regional ET estimation research, and the ET data after BTCH algorithm fusion have higher data quality than the original input data. The fused ET data can inform the development of management strategies for water resources in the YRB and provide a deeper understanding of the regional water supply and demand balance mechanism.
Chemical Fractions and Magnetic Simulation Based on Machine Learning for Trace Metals in a Sedimentary Column of Lake Taihu
Authors: Xiao Hui , Ke Tong , Chen Liming , Li Dehu , Yang Wanru , Qian Xin , Chen Long , Deng Ligang , Li Huiming
Published: September 2024

In this study, the chemical fractions (CFs) of trace metal (TMs) and multiple magnetic parameters were analysed in the sedimentary column from the centre of Lake Taihu. The sedimentary column, measuring 53 cm in length, was dated using 210Pb and 137Cs to be 124 years old. Surface layers of the column were found to contain significantly higher concentrations of Cd, Co, Cu, Pb, Sb, Ti, and Zn than the middle and bottom layers. The sedimentary core contained a substantial amount of ferrimagnetic minerals. Most of the TMs were present in the residual state, except for Mn and Pb. The chemical fractions of Cd exhibited the most significant variation with depth. The pollution load index (PLI) indicated moderate TMs pollution levels in the region, whereas the risk assessment code (RAC) classified Mn as being heavily polluted. Multiple linear regression (MLR) and random forest (RF), support vector machine (SVM), and XGBoost (1.7.7.1) machine learning models were used to simulate the RAC and total concentration of TMs, using physical and chemical indicators and magnetic parameters of the sediments as input variables. The MLR model outperformed RF, SVM, and XGBoost in simulating the CFs and total concentrations of most TMs in the sedimentary column, with R2 up to 0.668 and 0.87. The SHapley Additive exPlanations (SHAP) method reveals that χarm/χ is the dominant factor influencing the RAC of As in the XGBoost models. For the RAC of Co and Cu in RF models, C% and N% exhibit greater contributions.