bluuebunny/crossref_metadata_2025 huggingface dataset:
Spatial Analysis of Air Pollutants in an Industrial City Using GIS-Based Techniques: A Case Study of Pavlodar, Kazakhstan
Authors: Safarov Ruslan , Shomanova Zhanat , Nossenko Yuriy , Kopishev Eldar , Bexeitova Zhuldyz , Kamatov Ruslan
Published: September 2024

The given research employs high-resolution air quality monitoring and contemporary statistical methods to address gaps in understanding the urban air pollution in Pavlodar, a city with a significant industrial presence and promising touristic potential. Using mobile air quality sensors for detailed spatial data collection, the research aims to quantify concentrations of particulate matter (PM2.5, PM10), carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ground-level ozone (O3); assess their distribution; and identify key influencing factors. In this study, we employed Geographic Information Systems (GISs) for spatial analysis, integrating multi-level B-spline interpolation to model spatial variability. Correlation analysis and structural equation modeling were utilized to explore the relationships between variables, while regression analysis was conducted to quantify these relationships. These techniques were crucial for accurately mapping and interpreting spatial patterns and their underlying factors. The study identifies PM2.5 and NO2 as the primary contributors to air pollution in Pavlodar, with NO2 exceeding the 24 h threshold in 87.38% of locations and PM2.5 showing the highest individual air quality index (AQI) in 75.7% of cases. Correlation analysis reveals a positive association between PM2.5 and AQI and a negative correlation between NO2 and AQI, likely due to the dominant influence of PM2.5 in AQI calculations. Structural equation modeling (SEM) further underscores PM2.5 as the most significant impactor on AQI, while NO2 shows no significant direct impact. Humidity is positively correlated with AQI, though this relationship is context-specific to seasonal patterns observed in May. The sectoral analysis of landscape indices reveals weak correlations between the green space ratio (GSR) and air quality, indicating that while vegetation reduces pollutants, its impact is minimal due to urban planting density. The road ratio (RR) lacks sufficient statistical evidence to draw conclusions about its effect on air quality, possibly due to the methodology used. Spatial variability in pollutant concentrations is evident, with increasing PM2.5, PM10, and AQI towards the east-northeast, likely influenced by industrial activities and prevailing wind patterns. In contrast, NO2 pollution does not show a clear geographic pattern, indicating vehicular emissions as its primary source. Spatial interpolation highlights pollution hotspots near industrial zones, posing health risks to vulnerable populations. While the city’s overall AQI is considered “moderate”, the study highlights the necessity of implementing measures to improve air quality in Pavlodar. This will not only enhance the city’s attractiveness to tourists but also support its sustainable development as an industrial center.
Pesticide Use, Regulation, and Policies in Indian Agriculture
Authors: Reddy A. Amarender , Reddy Meghana , Mathur Vartika
Published: September 2024

This research paper presents a comprehensive analysis of pesticide use in global and Indian agriculture, focusing on the mounting food security challenges due to population growth and the increased demand for food and fiber crops. While pesticides are crucial in mitigating losses due to pests, diseases, and weeds, increasing apprehension regarding their adverse effects on human and environment health necessitates a critical examination of their usage patterns. Despite India’s relatively low per-hectare pesticide usage of 0.4 kg compared to China’s 1.83 kg, issues with pesticide residue contamination in the food chain require urgent attention. Additionally, significant regional disparities in pesticide application highlight the need for more uniform and sustainable agricultural practices. Therefore, this study examines the evolving trends in global and Indian pesticide application, providing a comprehensive analysis of the shifting dynamics across various Indian states and crop varieties. Furthermore, it analyzes various pesticide categories and their respective market shares, providing insights into production and export patterns. Our research also explores regulatory frameworks aimed at optimizing pesticide use while minimizing detrimental effects on human health and the environment.
Laboratory and Field Performance Evaluation of NMAS 9.5, 8.0, and 5.6 mm SMA Mixtures for Sustainable Pavement
Authors: Baek Cheolmin , Kwon Ohsun , Lee Jongsub
Published: September 2024

This study evaluates the laboratory and field performance of stone mastic asphalt (SMA) mixtures with nominal maximum aggregate sizes (NMAS) of 9.5, 8.0, and 5.6 mm. Aggregates and fine aggregates of these sizes were produced using an impact crusher and a polyurethane screen. Mix designs for SMA overlays on aged concrete pavement were developed. Laboratory tests assessed rutting performance using full-scale accelerated pavement testing (APT) equipment and reflective cracking resistance using an asphalt mixture performance tester (AMPT). Field evaluations included noise reduction using CPX equipment, skid resistance using SN equipment, and bond strength using field cores. Results showed that for 8.0 mm SMA mixtures to achieve the same rutting performance as 9.5 mm SMA, PG76-22 grade binder was required, whereas 5.6 mm SMA required PG82-22. The 8.0 and 5.6 mm SMA mixtures showed 22.2% and 25% reduced crack progression, respectively, compared with the 9.5 mm SMA mixtures. Field evaluations indicated that 8.0 mm and 5.6 mm SMA pavements reduced tire–pavement noise by 1.7 and 0.8 dB, increased skid resistance by 8.5% and 2.0%, and enhanced shear bond strength by 150%, compared with 9.5 mm SMA. Overall, the 8.0 mm SMA mixture on aged concrete pavement demonstrated superior durability and functionality toward sustainable pavement systems.
Influence of Printing Interval on the Imbibition Behavior of 3D-Printed Foam Concrete for Sustainable and Green Building Applications
Authors: Liu Xiaoshuang , Li Shiming , Duan Yanjun , Du Zhiqin , Zuo Xiaobao , Dong Jianjun , Cheng Helan
Published: September 2024

Foam concrete is highly valued as a sustainable cement-based material, but the development of 3D-printed foam concrete (3DPFC) has remained constrained. This study investigated the influence of printing interval on the microstructure and imbibition behavior of 3DPFC. The results revealed that horizontal interlayers are broader compared to vertical interlayers, leading to more significant imbibition. For X-oriented 3DPFC, the vertical interlayer was rapidly occupied by water after imbibition, forming an elliptical moisture profile. For Y-oriented 3DPFC, the moisture profile appeared more convoluted, mainly surrounding the horizontal interlayers but shifting at intersections with the vertical interlayers. In Z-oriented 3DPFC, where only tight horizontal interlayers were present, interlayer imbibition was almost negligible. Additionally, when the printing interval was less than 15 min, imbibition was primarily restricted to the top filament since the bottom filament was compacted by the filament above. Conversely, with a printing interval longer than 15 min, the bottom filament hardened before the setting of the top filament. This allowed the surface of the bottom filament to be compacted by the top filament, resulting in a dense interlayer that offers better resistance against imbibition compared to the matrix of 3DPFC. This work contributes to the advancement of green building technologies by providing insights into optimizing the 3D printing process for foam concrete, thereby enhancing its structural performance without compromising the designated air content and consistency of the foam concrete, facilitating a more efficient utilization of materials and a reduction in overall material consumption.
Agility and Resilience in Supply Chains: Investigating Their Roles in Enhancing Financial Performance
Authors: Tufan Cenk , Çiğdem Şemsettin , Kılıç Yunus , Sayar Gökçen
Published: September 2024

Business sectors face disruptive challenges such as cash flow problems in finance and material flow problems in supply chain and logistics processes in today’s rapidly evolving and uncertain environment. Given these challenges, effective management of resource and material flows by managers has become increasingly complex. Supply chain management is crucial for businesses to sustain competitive market positioning. This study distinctively explores the interplay between supply chain management and the financial performance of manufacturing companies, highlighting the increasingly dynamic and competitive global markets. It scrutinizes the moderating roles of supply chain agility and flexibility in this relationship, offering diverse analytical perspectives. The research methodology involved surveying white-collar employees within these companies. Factor analysis was employed to affirm the scale’s validity, and the Hayes model 3 method was utilized to test hypotheses. Our research uncovered intricate interactions between supply chain management, agility, and resilience, underscoring their collective impact on financial performance. The thesis that supply chain management has a substantial impact on financial performance was corroborated by the study’s results. The study also emphasizes the moderating impact of supply chain agility in the relationship between financial performance and supply chain management. The results of the study that supply chain resilience moderates the moderating effect of supply chain agility indicate that the interaction between supply chain resilience and supply chain agility may affect the relationship between supply chain management and financial performance if supply chain resilience enhances the resilience of organizations to external challenges. These insights suggest organizations must integrate agility, management, and resilience considerations in their supply chains to optimize performance. This study contributes a novel viewpoint to the literature, providing strategic guidance for managerial decision making.
Travel Time Estimation for Urban Arterials Based on the Multi-Source Data
Authors: Zheng Lingyu , Ma Hao , Wang Zhongyu
Published: September 2024

Accurate traffic information, such as travel time, becomes more important since it could help provide more efficient traffic management strategies. This paper presents a method for estimating the travel time of segments on urban arterials by leveraging multi-source data from loop detectors and probe vehicles. Travel time is defined into three distinct sections based on floating car trajectories, i.e., accelerating, constant speed, and decelerating. Considering the traffic flow characteristics, different methods are developed using various data for each section. The proposed methodology is validated using field data collected in Shanghai, China. The results validated the proposed method with absolute percentage errors (APEs) of approximately 5% in constrained traffic flow conditions and 10–20% in less constrained traffic flow. The results also show that the proposed method has better performance than the method with loop detector data and another data fusion model. It is expected that the proposed method could help improve traffic management efficiency, such as traffic signal control, by providing more accurate travel time information.
Analysis of PM10 Substances via Intuitionistic Fuzzy Decision-Making and Statistical Evaluation
Authors: Güler Ezgi , Yerel Kandemir Süheyla
Published: September 2024

Air pollution is a situation that negatively affects the health of humans and all living things in nature and causes damage to the environment. The most important cause of air pollution is the amount and density of substances called “particulate matter” above guidelines. Particulate matter (PM) are mixed liquid droplets and solid particles with advective diameters less than 2.5 μm (PM2.5—fine particles) and between 2.5 and 10 μm (PM2.5–10—coarse particles). PM10 is defined as one that can remain in the air for a long time and settle in the respiratory tract, damaging the lungs. It is important to identify the underlying causes of air pollution caused by PM10. In this context, these criteria need to be evaluated to minimize the negative effects of PM10. In the study, monthly average PM10 data obtained from the Air Quality Monitoring Station in Kocaeli, Türkiye, between 2017 and 2023 are used. After determining the criteria for PM10, the criteria are prioritized with the Intuitionistic Fuzzy AHP (IF-AHP) method by taking decision-maker opinions. The proposed decision-making model aims to guide obtaining and focusing on the important causes of out-of-limit and dangerous PM10 concentrations in the air. Additionally, PM10 data is analyzed in the context of COVID-19 and a statistical analysis is conducted. One-way Analysis of Variance (ANOVA) is used to evaluate whether there is a significant difference in average monthly data over the years. The Games–Howell test, one of the post-hoc tests, is used for determining differences between groups (years). In addition, monthly PM10 values for the future are estimated using the Expert Modeler tool in the software IBM® SPSS® Statistics 22. The study is important in that it provides a focus on the criteria affecting PM10 with an intuitionistic fuzzy perspective, along with statistical analysis.
Dual Transition of Net Zero Carbon and Digital Transformation: Case Study of UK Transportation Sector
Authors: Manifold Joel , Renukappa Suresh , Suresh Subashini , Georgakis Panagiotis , Perera Gamage Rashini
Published: September 2024

The UK Government’s Building Information Modelling (BIM) mandate has encouraged the utilisation of BIM within the Transportation Sector (TS), with research demonstrating positive effects of BIM. However, BIM processes are incipient to TS project implementation across the UK. This paper is carried out to understand the current BIM usage within the UK’s TS and how BIM practises and workflows contribute towards the government’s NZC approach. We used research questions derived from the population, intervention, comparison and outcome (PICO) system and inclusion and exclusion criteria to screen irrelevant information from a Systematic Literature review with 18 pieces of literature. We identified six key drivers: carbon reduction and BIM, BIM in transportation design, BIM uptake and usage in transportation, BIM in transportation construction and Digital Twins and BIM. It was identified that, with the integration of the Carbon Calculator Tool into Civil 3D, structural and material data can be obtained and areas of Embodied Carbon hotspots can be identified to contribute to reduce overall carbon across a project, which requires further collaboration between software providers and industry leaders for further streamlining the process. A limitation of this research is the requirement for wider study of differing disciplines within the TS, more qualitative research and a lack of information regarding other Carbon Calculator Tools and how compatible they are with Civil 3D.
Assessing Drivers Influencing Net-Zero Emission Adoption in Manufacturing Supply Chain: A Hybrid ANN-Fuzzy ISM Approach
Authors: Yadav Alok , Sachdeva Anish , Garg Rajiv Kumar , Qureshi Karishma M. , Mewada Bhavesh G. , Qureshi Mohamed Rafik Noor Mohamed , Mansour Mohamed
Published: September 2024

Nowadays, there is a constant focus on implementing the net-zero emission (NZE) concept in the manufacturing supply chain (MSC). To reduce emissions and improve organisational efficiency, adopting the net-zero concept is a prevalent trend in today’s highly competitive global business environment. Governments and stakeholders are pressuring the manufacturing sector to use natural resources efficiently and reduce environmental impacts. As a result, the manufacturing industry is focusing on cleaner production using net-zero practices. This study aims to identify and analyse the interaction among the drivers of net-zero adoption in the MSC. Through a systematic literature review (SLR), a list of drivers was recognised. To validate these drivers, we conducted an empirical study with 173 respondents from the Indian manufacturing industry. Further, we employed an artificial neural network (ANN) to weigh the nonlinear effect of drivers. Fuzzy interpretive structural modelling (F-ISM) was used to identify the interaction relationships among the drivers and construct a hierarchical structure among these identified drivers. The fuzzy matrix of cross-impact multiplications applied to the classification (F-MICMAC) method was used to categorise these drivers into driving and dependent categories. The outcomes of ANN show that Environmental predictors (100%) emerged as the most significant drivers, followed by Economic drivers (60.38%) and Technological drivers (59.05%). This study is a valuable resource for academia and industry professionals, providing essential insights into how adopting net zero facilitates the manufacturing industry’s ability to achieve net zero across the supply chain.
Symmetrical Martensite Distribution in Wire Using Cryogenic Cooling
Authors: Volokitina Irina , Volokitin Andrey , Panin Evgeniy , Makhmutov Bolat
Published: September 2024

This article presents the results of research on a new combined process involving multi-cycle wire-drawing and subsequent cryogenic cooling after each deformation stage. For theoretical research, modeling in the Deform software was performed. The analysis of temperature fields and the martensitic component in all models showed that for both considered thicknesses, the most effective option is a low deformation velocity and the conduct of a process without heating. The least effective option is to use an increased thickness of the workpiece at an increased deformation velocity and the conduct of a process without of heating to ambient temperature, which acts as a local cooling of the axial zone of the workpiece with an increase in the workpiece thickness. An analysis of laboratory studies on this combined process revealed that in the absence of intermediate heating of a wire between deformation cycles, 100% martensite is formed in the structure. However, if intermediate heating to 20 °C between deformation cycles is carried out, a gradient distribution of martensite can be obtained. And, since the wire has a circular cross-section, in all cases, martensite is distributed symmetrically about the center of the workpiece.
Random Telegraphic Signals with Fractal-like Probability Transition Rates
Authors: Elaskar Sergio , Bruel Pascal , Gutiérrez Marcantoni Luis
Published: September 2024

Many physical processes feature random telegraph signals, e.g., a time signal c(t) that randomly switches between two values over time. The present study focuses on the class of telegraphic processes for which the transition rates are formulated by using fractal-like expressions. By considering various restrictive hypotheses regarding the statistics of the waiting times, the present analysis provides the corresponding expressions of the unconditional and conditional probabilities, the mean waiting times, the mean phase duration, the autocorrelation function and the associated integral time scale, the spectral density, and the mean switching frequency. To assess the relevance of the various hypotheses, synthetically generated signals were constructed and used as references to evaluate the predictive quality of the theoretically derived expressions. The best predictions were obtained by considering that the waiting times probability density functions were Dirac peaks centered on the corresponding mean values.
Fed-RHLP: Enhancing Federated Learning with Random High-Local Performance Client Selection for Improved Convergence and Accuracy
Authors: Sittijuk Pramote , Tamee Kreangsak
Published: September 2024

We introduce the random high-local performance client selection strategy, termed Fed-RHLP. This approach allows opportunities for higher-performance clients to contribute more significantly by updating and sharing their local models for global aggregation. Nevertheless, it also enables lower-performance clients to participate collaboratively based on their proportional representation determined by the probability of their local performance on the roulette wheel (RW). Improving symmetry in federated learning involves IID Data: symmetry is naturally present, making model updates easier to aggregate and Non-IID Data: asymmetries can impact performance and fairness. Solutions include data balancing, adaptive algorithms, and robust aggregation methods. Fed-RHLP enhances federated learning by allowing lower-performance clients to contribute based on their proportional representation, which is determined by their local performance. This fosters inclusivity and collaboration in both IID and Non-IID scenarios. In this work, through experiments, we demonstrate that Fed-RHLP offers accelerated convergence speed and improved accuracy in aggregating the final global model, effectively mitigating challenges posed by both IID and Non-IID Data distribution scenarios.
Influencing Factors and Mechanisms of Value Co-Creation in Artificial Intelligence-Driven Human Resource Management: A System Dynamics Simulation
Authors: Dong Jun-Jie , Yan Shu-Min , Yang Xiao-Wei
Published: September 2024

In the era of artificial intelligence, human resource management has undergone significant changes compared to traditional approaches regarding value creation methods and influencing factors. This research aims to utilize grounded theory to comprehensively explore the influencing factors of value co-creation in enterprise human resource management within the context of artificial intelligence. Additionally, this research seeks to capture the dynamic relationships, causal links, and evolutionary patterns among the various elements within the system by constructing a system dynamics model. The results indicated that (1) Environmental factors primarily play a regulatory role, organizational factors serve a supportive role, and participant factors act as the driving force in influencing value co-creation in human resource management. (2) In the context of artificial intelligence, both hardware infrastructure and software capabilities can significantly impact value co-creation in human resource management. This research complements current research on the influencing factors of value co-creation in enterprise human resource management. It offers new perspectives and frameworks for the theoretical development and practical application of value co-creation in this area, supporting companies in effectively managing and developing value co-creation in human resource management.
An Evolutionary Game Study of Collaborative Innovation across the Whole Industry Chain of Rural E-Commerce under Digital Empowerment
Authors: Wang Yanling , Xu Junqian , Zhang Guangsheng
Published: September 2024

With the profound integration of digital technology and traditional agriculture, the whole industry chain of rural e-commerce, as an advanced system, is reshaping the production, sales, and management models of agriculture and is emerging as a new catalyst for the advancement of digital agriculture through significant innovation. This paper focuses on the digital empowerment attributes and strategic attributes of the whole industrial chain of rural e-commerce, and evolutionary game models under market mechanisms and regulations are constructed. It examines the influence of various elements, such as the digital technology empowerment coefficient, on collaborative innovation within the whole industry chain of rural e-commerce. Using case simulations, this paper discusses the role of government regulation and intervention when market mechanisms are inadequate. The study reveals that factors such as the digital technology empowerment coefficient, technology absorptive capacity, and the amount of technology and information stored in collaborative innovation positively influence the whole industry chain. Potential risk losses and free-rider gains have negative effects on the evolution of the system toward collaborative innovation. When market mechanisms are inadequate, a combination of operational cost subsidies and incentive measures can yield more effective policy synergy, with the incentive impact of cost subsidies being particularly notable. The strategic application of enterprise-liquidated damage and government penalties will aid in regulating and directing corporate behavior. The findings of this research not only offer a new microlevel explanation for understanding the decision-making mechanism behind collaborative innovation in the whole industrial chain of rural e-commerce but also serve as a reference for government policy formulation to ensure the stability of the whole rural e-commerce industry chain.
Red-Billed Blue Magpie Optimizer for Electrical Characterization of Fuel Cells with Prioritizing Estimated Parameters
Authors: El-Fergany Attia A. , Agwa Ahmed M.
Published: September 2024

The red-billed blue magpie optimizer (RBMO) is employed in this research study to address parameter extraction in polymer exchange membrane fuel cells (PEMFCs), along with three recently implemented optimizers. The sum of squared deviations (SSD) between the simulated and measured stack voltages defines the fitness function of the optimization problem under investigation subject to a set of working constraints. Three distinct PEMFCs stacks models—the Ballard Mark, Temasek 1 kW, and Horizon H-12 units—are used to illustrate the applied RBMO’s feasibility in solving this challenge in comparison to other recent algorithms. The highest percentages of biased voltage per reading for the Ballard Mark V, Temasek 1 kW, and Horizon H-12 are, respectively, +0.65%, +0.20%, and −0.14%, which are negligible errors. The primary characteristics of PEMFC stacks under changing reactant pressures and cell temperatures are used to evaluate the precision of the cropped optimized parameters. In the final phase of this endeavor, the sensitivity of the cropped parameters to the PEMFCs model’s performance is investigated using two machine learning techniques, namely, artificial neural network and Gaussian process regression models. The simulation results demonstrate that the RBMO approach extracts the PEMFCs’ appropriate parameters with high precision.
Identifying Patterns among Tourism-Oriented Online Communities on Facebook
Authors: Zabudská Eva , Pompurová Kristína
Published: September 2024

The proliferation of social media has transformed how people engage in communication and community building, with platforms like Facebook becoming central to connecting individuals with shared interests. Despite the extensive formation of tourism-oriented online communities on these platforms, there is a notable lack of comprehensive studies examining their structural and managerial dynamics. This study addresses this gap by systematically analyzing fifty international tourism-focused Facebook communities to develop a novel typology based on the nature and type of information shared. The research identifies significant variations in community sizes, engagement levels, and management structures, highlighting that only 6% of these communities qualify as large, with membership exceeding one million. Contrary to common assumptions, a direct link between community size and engagement was not found, with qualitative factors like community purpose and content type being more influential. A notable correlation was observed between the number of administrators and moderators and the member count, emphasizing the importance of effective community governance. The study’s findings contribute to a deeper theoretical understanding of online community dynamics and offer practical implications for tourism marketers and community managers aiming to optimize engagement strategies on social media platforms. The research sets a foundation for future exploration of the interplay between virtual community management and tourism-related discourse.
A Comprehensive Review of Lab-Scale Studies on Removing Hexavalent Chromium from Aqueous Solutions by Using Unmodified and Modified Waste Biomass as Adsorbents
Authors: Tripathi Manikant , Pathak Sukriti , Singh Ranjan , Singh Pankaj , Singh Pradeep Kumar , Shukla Awadhesh Kumar , Maurya Sadanand , Kaur Sukhminderjit , Thakur Babita
Published: September 2024

Anthropogenic activities and increasing human population has led to one of the major global problems of heavy metal contamination in ecosystems and to the generation of a huge amount of waste material biomass. Hexavalent chromium [Cr(VI)] is the major contaminant introduced by various industrial effluents and activities into the ecosystem. Cr(VI) is a known mutagen and carcinogen with numerous detrimental effects on the health of humans, plants, and animals, jeopardizing the balance of ecosystems. Therefore, the remediation of such a hazardous toxic metal pollutant from the environment is necessary. Various physical and chemical methods are available for the sequestration of toxic metals. However, adsorption is recognized as a more efficient technology for Cr(VI) remediation. Adsorption by utilizing waste material biomass as adsorbents is a sustainable approach in remediating hazardous pollutants, thus serving the dual purpose of remediating Cr(VI) and exploiting waste material biomass in an eco- friendly manner. Agricultural biomass, industrial residues, forest residues, and food waste are the primary waste material biomass that could be employed, with different strategies, for the efficient sequestration of toxic Cr(VI). This review focuses on the use of diverse waste biomass, such as industrial and agricultural by-products, for the effective remediation of Cr(VI) from aqueous solutions. The review also focuses on the operational conditions that improve Cr(VI) remediation, describes the efficacy of various biomass materials and modifications, and assesses the general sustainability of these approaches to reducing Cr(VI) pollution.
Efficacy of Adjunct Hemoperfusion Compared to Standard Medical Therapy on 28-Day Mortality in Leptospirosis Patients with Renal Failure and Shock: A Single-Center Randomized Controlled Trial
Authors: Leano Danice Romagne , Danguilan Romina , Arakama Mel-Hatra , Apelin Vince , Alamillo Paolo Pinkerton , Chua Eric
Published: September 2024

Hemoperfusion is a novel adjunct therapy that targets the dysregulated inflammatory events in severe sepsis. Previous studies have reported conflicting results on its efficacy and safety. This study was designed to assess the efficacy and safety of hemoperfusion among leptospirosis patients in septic shock and renal failure in terms of improvement in 28-day mortality, SOFA score, level of inflammatory markers, hemodynamics, and renal and pulmonary function. A total of 37 severe leptospirosis patients were enrolled and randomized into either standard medical therapy (SMT) alone, n = 20, or with hemoperfusion (HP), n = 17. Vital signs, urine output, vasopressor dose, PaO2/FiO2 (P/F) ratio, and biochemical parameters of patients from each treatment arm were compared. The hemoperfusion group showed a 36.84% (p = 0.017) risk reduction in 28-day mortality. Levels of procalcitonin, IL6, and lactate significantly decreased from baseline to day 7 in both groups. Statistically significant improvements in serum creatinine (p = 0.04) and PF ratio (p = 0.045) were observed in the hemoperfusion cohort. Intention-to-treat and per-protocol approaches showed that hemoperfusion increased the survival rate and decreased the mortality risk. This benefit for survival persisted even when patients were also receiving extracorporeal membrane oxygenation (ECMO), showing that hemoperfusion’s benefits are independent of ECMO use. Hemoperfusion is a safe and effective adjunct therapy for managing severe sepsis. It promotes earlier renal and pulmonary function recovery and improves the survival of septic shock patients.
Effects of Five Years of Treatment of Onchocerciasis with Ivermectin under Community Guidelines in Resurgent Areas of Burkina Faso: A before-and-after Analysis
Authors: Ouedraogo Micheline O. , Meda Ivlabèhirè Bertrand , Kourouma Karifa , Wienne Fanny Yago , Nare Dieudonné , Bougouma Clarisse , Compaore Justin , Kouanda Seni
Published: September 2024

Background: Almost the entire country of Burkina Faso was endemic to onchocerciasis. Onchocerciasis control efforts thus brought the prevalence of O. volvulus to a level where the disease was no longer a public health problem in 2002. A resurgence of onchocerciasis cases has been observed in two regions (Cascades and the Southwest) located around several river basins in 2010–2011. In accordance with WHO guidelines for the management of resurgent cases, community-directed treatment with ivermectin (CDTI) was implemented in the affected areas. The aim of this study was to determine the effects of this intervention on parasitological indices of onchocerciasis, depending on the distance between villages and rivers. Methodology: We conducted a paired pre-post study using aggregated village-level data from two cross-sectional surveys conducted in each region. A Wilcoxon signed-rank test was used to compare the standardized microfilarodermia prevalence and community microfilarial load (CMFL). Results: A total of 43 villages in 6 health districts, in the Southwest (18) and Cascades (25) regions were included in the study. The key findings were that standardized microfilaria prevalence and CMFL decreased significantly after the implementation of CDTI in both regions (p < 0.0001). The median standardized microfilaria prevalence was 2.8 [interquartile range (IQR): 0.2–6.6] before CDTI and 0.72 [IQR: 0.0–2.17] after CDTI. The results showed also a decline in standardized microfilaria prevalence and CMFL in all villages, regardless of the distance separating the village from the streams. However, the results were not statistically significant for the villages located 5 km or more from streams (p = 0.0816 and 0.0542 for standardized microfilaria prevalence and CMFL, respectively). Conclusion: Our results thus show that the implementation of effective CDTI could stop the transmission of O. volvulus in these two regions. The main challenge for stopping transmission could be the migration of populations to neighboring countries and migration of the vector from one country to another, as Burkina Faso shares some river basins with neighboring countries.
From de Sitter to de Sitter: A Thermal Approach to Running Vacuum Cosmology and the Non-Canonical Scalar Field Description
Authors: Almeida Pedro Eleuterio Mendonça , Santos Rose Clivia , Sales Lima Jose Ademir
Published: September 2024

The entire classical cosmological history between two extreme de Sitter vacuum solutions is discussed based on Einstein’s equations and non-equilibrium thermodynamics. The initial non-singular de Sitter state is characterised by a very high energy scale, which is equal or smaller than the reduced Planck mass. It is structurally unstable, and all of the continuous created matter, energy, and entropy of the material component comes from the irreversible flow powered by the primeval vacuum energy density. The analytical expression describing the running vacuum is obtained from the thermal approach. It opens a new perspective to solve the old puzzles and current observational challenges plaguing the cosmic concordance model driven by a rigid vacuum. Such a scenario is also modelled through a non-canonical scalar field. It is demonstrated that the resulting scalar field model is shown to be a step-by-step a faithful analytical representation of the thermal running vacuum cosmology.
Cytomegalovirus Retinitis: Clinical Manifestations, Diagnosis and Treatment
Authors: Zhang Jing , Kamoi Koju , Zong Yuan , Yang Mingming , Zou Yaru , Miyagaki Miki , Ohno-Matsui Kyoko
Published: September 2024

Cytomegalovirus (CMV) retinitis is the most common eye disease associated with CMV infection in immunocompromised individuals. The CMVR may initially be asymptomatic; however, relatively mild vitreous inflammation at the onset may be an important differential point from other diseases in HIV patients. Fundus photography, CD4 T-cell count, and telemedicine could be used to screen and monitor the high-risk population, particularly in resource-limited regions. Retinitis generally starts in the peripheral retina and advances toward the posterior pole, which could develop to the characteristic “pizza pie” appearance marked by central retinal necrosis and intraretinal hemorrhage. CMVR causes vision loss if left untreated, and early antiviral therapy significantly reduces the risk of vision loss. Alongside traditional antiviral treatments, immunotherapies including CMV-specific adoptive T-cell therapy and CMV immunoglobulin (CMVIG) are emerging as promising treatment options due to their favorable tolerability and reduced mortality. This review comprehensively examines CMV retinitis, encompassing the clinical features, differential diagnosis, laboratory tests, and updated treatment strategies to inform clinical management.
Evaluation of Commercial RNA Extraction Protocols for Avian Influenza Virus Using Nanopore Metagenomic Sequencing
Authors: Chaves Maria , Hashish Amro , Osemeke Onyekachukwu , Sato Yuko , Suarez David L. , El-Gazzar Mohamed
Published: September 2024

Avian influenza virus (AIV) is a significant threat to the poultry industry, necessitating rapid and accurate diagnosis. The current AIV diagnostic process relies on virus identification via real-time reverse transcription–polymerase chain reaction (rRT-PCR). Subsequently, the virus is further characterized using genome sequencing. This two-step diagnostic process takes days to weeks, but it can be expedited by using novel sequencing technologies. We aim to optimize and validate nucleic acid extraction as the first step to establishing Oxford Nanopore Technologies (ONT) as a rapid diagnostic tool for identifying and characterizing AIV from clinical samples. This study compared four commercially available RNA extraction protocols using AIV-known-positive clinical samples. The extracted RNA was evaluated using total RNA concentration, viral copies as measured by rRT-PCR, and purity as measured by a 260/280 absorbance ratio. After NGS testing, the number of total and influenza-specific reads and quality scores of the generated sequences were assessed. The results showed that no protocol outperformed the others on all parameters measured; however, the magnetic particle-based method was the most consistent regarding CT value, purity, total yield, and AIV reads, and it was less error-prone. This study highlights how different RNA extraction protocols influence ONT sequencing performance.
Evaluation of Different Formulations on the Viability of Phages for Use in Agriculture
Authors: León Marcela , Araya Jorge , Nuñez Mauricio , Arce Manuel , Guzmán Fanny , Yáñez Carolina , Besoain Ximena , Bastías Roberto
Published: September 2024

Bacteriophages have been proposed as biological controllers to protect plants against different bacterial pathogens. In this scenario, one of the main challenges is the low viability of phages in plants and under adverse environmental conditions. This work explores the use of 12 compounds and 14 different formulations to increase the viability of a phage mixture that demonstrated biocontrol capacity against Pseudomonas syringae pv. actinidiae (Psa) in kiwi plants. The results showed that the viability of the phage mixture decreases at 44 °C, at a pH lower than 4, and under UV radiation. However, using excipients such as skim milk, casein, and glutamic acid can prevent the viability loss of the phages under these conditions. Likewise, it was demonstrated that the use of these compounds prolongs the presence of phages in kiwi plants from 48 h to at least 96 h. In addition, it was observed that phages remained stable for seven weeks when stored in powder with skim milk, casein, or sucrose after lyophilization and at 4 °C. Finally, the phages with glutamic acid, sucrose, or skim milk maintained their antimicrobial activity against Psa on kiwi leaves and persisted within kiwi plants when added through roots. This study contributes to overcoming the challenges associated with the use of phages as biological controllers in agriculture.
SARS-CoV-2 Variants from Long-Term, Persistently Infected Immunocompromised Patients Have Altered Syncytia Formation, Temperature-Dependent Replication, and Serum Neutralizing Antibody Escape
Authors: Wouters Camille , Sachithanandham Jaiprasath , Akin Elgin , Pieterse Lisa , Fall Amary , Truong Thao T. , Bard Jennifer Dien , Yee Rebecca , Sullivan David J. , Mostafa Heba H. , Pekosz Andrew
Published: September 2024

SARS-CoV-2 infection of immunocompromised individuals often leads to prolonged detection of viral RNA and infectious virus in nasal specimens, presumably due to the lack of induction of an appropriate adaptive immune response. Mutations identified in virus sequences obtained from persistently infected patients bear signatures of immune evasion and have some overlap with sequences present in variants of concern. We characterized virus isolates obtained greater than 100 days after the initial COVID-19 diagnosis from two COVID-19 patients undergoing immunosuppressive cancer therapy, wand compared them to an isolate from the start of the infection. Isolates from an individual who never mounted an antibody response specific to SARS-CoV-2 despite the administration of convalescent plasma showed slight reductions in plaque size and some showed temperature-dependent replication attenuation on human nasal epithelial cell culture compared to the virus that initiated infection. An isolate from another patient—who did mount a SARS-CoV-2 IgM response—showed temperature-dependent changes in plaque size as well as increased syncytia formation and escape from serum-neutralizing antibodies. Our results indicate that not all virus isolates from immunocompromised COVID-19 patients display clear signs of phenotypic change, but increased attention should be paid to monitoring virus evolution in this patient population.
Unveiling the Impact of Human Herpesviruses-Associated on CNS Infections: An Observational Study
Authors: Barrionuevo Caio Cesar L. B. , Baptista Pedro P. A. , da Silva Ewerton F. , da Silva Bernardo M. , Goulart Cássia da L. , de Melo Sabrina A. , da Silva Valderjane A. , de Souza Lara Laycia A. , Monte Rossicleia L. , Almeida-Val Fernando F. , Feitoza Pablo Vinícius S. , Bastos Michele de S.
Published: September 2024

Human Herpesviruses (HHVs) play a significant role in neurological diseases such as encephalitis and meningitis, adding significant morbidity. This study aims to retrospectively analyze the effect of HHVs on patients with neurological symptoms, focusing on the Herpesviridae family’s contributions to central nervous system (CNS) infections. Methods: This retrospective cohort study included 895 patients suspected of viral CNS infections, utilizing molecular diagnosis via qPCR to identify HHVs in cerebrospinal fluid (CSF) samples. This was conducted at a reference tertiary care hospital for infectious diseases in the western Brazilian Amazon from January 2015 to December 2022, focusing on the Herpesviridae family’s clinical repercussions and of Cytomegalovirus in CNS infections. Results: The findings revealed that 7.5% of the analyzed samples tested positive for HHVs, with Human Cytomegalovirus (HCMV) and Epstein–Barr Virus (EBV) being the most prevalent. A significant association was found between HHVs and neurological diseases such as encephalitis and meningitis, especially among people living with HIV/AIDS (PLWHA), highlighting the opportunistic nature of these viruses. The study underscores the critical role of CSF analysis in diagnosing CNS infections and the complexity of managing these infections in HIV patients due to their immunocompromised status. Conclusions: The results emphasize the need for comprehensive diagnostic approaches and tailored treatment strategies for CNS infections in immunocompromised individuals. The study calls for ongoing research and advancements in clinical practice to improve patient outcomes facing CNS infections, particularly those caused by HHVs.
Application of Immobilized Microorganism Gel Beads in Black-Odor Water with High Nitrogen and Phosphorus Removal Performance
Authors: Zhao Fengbin , Liu Shumin , Fang Xin , Yang Ning
Published: September 2024

Black-odor water, which is caused by the excessive accumulation of nitrogen and phosphorus in water, is a significant problem. Immobilized microorganisms are considered to be an effective technical solution, but there are still many key parameters to be determined, such as organic matter dissolution, insufficient stability, and insufficient phosphorus removal capacity, among other problems. In this study, the optimum raw material ratios of immobilized microorganism gel beads were determined by means of a response surface experiment. The optimal ratio of raw materials was 5% polyvinyl alcohol (PVA), 1% sodium alginate (SA), and 6% bacterial powder. In addition, the nitrogen and phosphorus removal performance of the materials was improved by loading inorganic compounds, such as 0.5 wt.% zeolite, 0.5 wt.% iron powder, and 0.2 wt.% activated carbon. Tolerance analysis determined that these gel beads could maintain a good performance in a series of harsh environments, such as during intense agitation, at high temperatures, and at low pH values, etc. The total nitrogen (TN), ammonia nitrogen (NH3-N), and phosphorus (TP) removal efficiencies were 88.9%, 90%, and 95%.
As and Pb Presence within the Meoqui-Delicias Aquifer, Chihuahua, Mexico
Authors: Bencomo-Calderón Marisol , Herrera-Peraza Eduardo Florencio , Villalobos-Aragón Alejandro
Published: September 2024

This study aimed to determine the amount of As and Pb in the water in the Meoqui-Delicias’ aquifer and their spatiotemporal dynamics. Twenty-one water sampling points were selected. Seventeen samples were from wells and four were from surface water; two were used for human consumption and the rest for agricultural use. The samples were taken from May 2019 to January 2020 in four sampling events, one for each climatological season of the year. The studied geochemical anomalies seem to be linked to the nature and mechanism of volcanic emplacement. Several samples exhibited high concentrations of arsenic ranging from 1.20 to 156.54 ppb, unlike lead, with low values being the maximum value of 26.32 ppb. These elements (As and Pb) are in the water in Naica, part of the mining district where tons of Au, Ag, Pb, Cu, and Zn were obtained. From a geographical standpoint, it is impossible to establish that these elements are related, even though these elements (As and Pb) are present in the water in Naica, a mining zone where tons of Au and Ag were historically mined.