bluuebunny/crossref_metadata_2025 huggingface dataset:
Advancing Urban Microclimate Monitoring: The Development of an Environmental Data Measurement Station Using a Low-Tech Approach
Authors: Lefevre Alexandre , Malet-Damour Bruno , Boyer Harry , Rivière Garry
Published: April 2024

Researchers studying urban climates aim to understand phenomena like urban heat islands (UHIs), which describe temperature differences between urban and rural areas. However, studies often lack numerous measurement points and frequently overlook parameters like radiation and air velocity due to the high cost of precision instrumentation. This results in data with a low resolution, particularly in tropical cities where official weather stations are scarce. This research introduces a new, low-tech tool for district-level outdoor thermal comfort assessment and UHI characterization to address these challenges. The automated weather station employs sensors to measure temperature, humidity, wind speed, solar radiation, and globe temperature. The paper details these sensors’ rigorous selection and validation process, followed by a description of the sensor assembly, data acquisition chain, and network operation mechanisms. Calibration outcomes in laboratory and in situ environments highlight the station’s reliability, even in tropical conditions. In conclusion, this weather station offers a cost-effective solution to gathering high-resolution data in urban areas, enabling an improved understanding of the UHI phenomenon and the refinement of urban microclimate numerical models.
A Hybrid Approach Based on Consensus Decision Making for Green Supplier Selection in Automotive Industry
Authors: Bas Sema Akin
Published: April 2024

With increased global commerce, businesses must manage their supply chains while taking into account not only costs but also environmental implications. The decision-making of Green Supplier Selection (GSS) is a strategic priority for companies to survive in challenging market conditions and to effectively and sustainably manage their supply chains in the increasingly polluted and resource-depleted world. Environmental sustainability can be enhanced with the appropriate criteria when choosing green suppliers. Based on these motivations, it is necessary to determine the correct criteria, classify the chosen criteria and employ an effective evaluation method in the GSS process. In particular, evaluating each criterion at its own level is of strategic importance. In this paper, the GSS model, handled by group decision-making, is constructed with multi-sub-criteria to increase the competitive advantage of businesses in challenging market conditions for the purpose of ensuring a sustainable future. A novel hybrid methodology of the Interval Type-2 Fuzzy (IT2F) Analytical Hierarchy Process (AHP) and IT2F Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is presented for the GSS model to deal with uncertainty. This study provides decision-makers with an effective method that performs fuzzy calculations at all steps until a solution is found, especially in areas that may have a complex hierarchical structure, such as the automotive industry. In the proposed method, unlike most studies in the literature, if a criterion has sub-criteria (or multi-sub-criteria) in the hierarchy considered, each criterion is evaluated with other criteria at its own level, without the need for all other criteria to have sub-criteria (or multi-sub-criteria). The effectiveness of the proposed method has been demonstrated by testing it with an application taken from the automotive industry with a complex-structured multi-level hierarchy. Additionally, sensitivity analysis has been conducted to assess the impact of changes in subjective input by means of scenarios.
Selection of a Green Contractor for the Implementation of a Solar Power Plant Project
Authors: Stojanović Ilija
Published: April 2024

This study is focused on the problem of contractor selection for the implementation of a solar power plant project to produce electricity from sustainable sources for the needs of the company Voćar. The goal of this research is to select a construction contractor to install a solar power plant using sustainability criteria. With this power plant, the company Voćar can reduce its electricity costs and contribute to the production of sustainable energy. A total of three main sustainability criteria were used, in which six auxiliary criteria were symmetrically distributed. With these criteria, six suppliers were analyzed, and expert decision making was carried out with the application of the fuzzy–rough approach. To define the weights of the criteria, the SWARA method was utilized in this study. Based on the findings of this method, the most important criteria are the ecological criteria. Using the CRADIS method, the contractors were ranked, and the results show that contractor C6 has the best results and is the first choice for implementing this project. Choosing the best supplier increases the sustainability of project implementation and the realization of the expected effects.
Tsallis Holographic Dark Energy with Power Law Ansatz Approach
Authors: Trivedi Oem , Khlopov Maxim , Timoshkin Alexander V.
Published: April 2024

Holographic principles have proven to be a very interesting approach towards dealing with the issues of the late-time acceleration of the universe, which has resulted in a great amount of work on holographic dark energy models. We consider one such very interesting holographic scenario, namely the Tsallis Holographic dark energy model, and consider an ansatz based approach to such models. We consider three cosmological scenarios in such models, namely those with viscous, non-viscous, and Chaplygin gas scenarios, discussing various crucial aspects related to these models. We discuss various crucial properties of the Tsallis model in such scenarios and see how the phantom divide is crossed in each case, but it is only the Chaplygin gas models which provide a better view on stability issues.The symmetry property of the theory presented in the article is the assumption that space is isotropic. Using bulk viscosity instead of shear viscosity reflects spatial isotropy.
Integration of Decentralized Graph-Based Multi-Agent Reinforcement Learning with Digital Twin for Traffic Signal Optimization
Authors: Kumarasamy Vijayalakshmi K. , Saroj Abhilasha Jairam , Liang Yu , Wu Dalei , Hunter Michael P. , Guin Angshuman , Sartipi Mina
Published: April 2024

Machine learning (ML) methods, particularly Reinforcement Learning (RL), have gained widespread attention for optimizing traffic signal control in intelligent transportation systems. However, existing ML approaches often exhibit limitations in scalability and adaptability, particularly within large traffic networks. This paper introduces an innovative solution by integrating decentralized graph-based multi-agent reinforcement learning (DGMARL) with a Digital Twin to enhance traffic signal optimization, targeting the reduction of traffic congestion and network-wide fuel consumption associated with vehicle stops and stop delays. In this approach, DGMARL agents are employed to learn traffic state patterns and make informed decisions regarding traffic signal control. The integration with a Digital Twin module further facilitates this process by simulating and replicating the real-time asymmetric traffic behaviors of a complex traffic network. The evaluation of this proposed methodology utilized PTV-Vissim, a traffic simulation software, which also serves as the simulation engine for the Digital Twin. The study focused on the Martin Luther King (MLK) Smart Corridor in Chattanooga, Tennessee, USA, by considering symmetric and asymmetric road layouts and traffic conditions. Comparative analysis against an actuated signal control baseline approach revealed significant improvements. Experiment results demonstrate a remarkable 55.38% reduction in Eco_PI, a developed performance measure capturing the cumulative impact of stops and penalized stop delays on fuel consumption, over a 24 h scenario. In a PM-peak-hour scenario, the average reduction in Eco_PI reached 38.94%, indicating the substantial improvement achieved in optimizing traffic flow and reducing fuel consumption during high-demand periods. These findings underscore the effectiveness of the integrated DGMARL and Digital Twin approach in optimizing traffic signals, contributing to a more sustainable and efficient traffic management system.
Topological Photonic Crystal in Microwave Region Based on Coupled Superconducting Resonators
Authors: Zheng Tianning , Chang Xiaoyang , Huang Juntian , Liu Yilun , Wei Jiaqi , Guo Qi
Published: April 2024

Topological photonics has been widely investigated due to its profound physical significance and great number of potential applications. Microwaves have long wavelengths, so it is relatively easy to manufacture large-sized microwave photonic crystals, enabling researchers to observe and measure phenomena such as topological boundary states. Nevertheless, the quality factors (QFs) of most resonators composed of traditional materials in the microwave region are relatively low, leading to topological edge states with high decay rates. In this study, we present a one-dimensional topological photonic crystal in the microwave region based on coupled superconducting resonators. A topological state with a QF as high as 6000 is observed, which proves this to be a new platform for the investigation of topological photonics with low decay rates in the microwave regime.
A Review of Statistical-Based Fault Detection and Diagnosis with Probabilistic Models
Authors: Zhu Yanting , Zhao Shunyi , Zhang Yuxuan , Zhang Chengxi , Wu Jin
Published: April 2024

As industrial processes grow increasingly complex, fault identification becomes challenging, and even minor errors can significantly impact both productivity and system safety. Fault detection and diagnosis (FDD) has emerged as a crucial strategy for maintaining system reliability and safety through condition monitoring and abnormality recovery to manage this challenge. Statistical-based FDD methods that rely on large-scale process data and their features have been developed for detecting faults. This paper overviews recent investigations and developments in statistical-based FDD methods, focusing on probabilistic models. The theoretical background of these models is presented, including Bayesian learning and maximum likelihood. We then discuss various techniques and methodologies, e.g., probabilistic principal component analysis (PPCA), probabilistic partial least squares (PPLS), probabilistic independent component analysis (PICA), probabilistic canonical correlation analysis (PCCA), and probabilistic Fisher discriminant analysis (PFDA). Several test statistics are analyzed to evaluate the discussed methods. In industrial processes, these methods require complex matrix operation and cost computational load. Finally, we discuss the current challenges and future trends in FDD.
System Approach to the Process of Institutional Transformation for Industrial Integrations in the Digital Era
Authors: Tolstykh Tatyana , Shmeleva Nadezhda , Boev Alexey , Guseva Tatiana , Panova Svetlana
Published: April 2024

The digitalization of the high-tech economy is complicated due to several issues. One can mention non-synchrony and imbalance in the development of industrial enterprises and their integrations; changes in the elements and relations between enterprises and the external environment; as well as contradictions between the actors. Therefore, a new institutional system for industrial integrations needs to be formed. This article proposes a concept and scenario of the institutional change needed to bolster industrial integrations in the digital economy. The structural logic and algorithm of the process provides for the gradual progress through seven phases of institutional transformation. The authors have developed an institutional change management platform for strategic transformation, the core of which is a decision-making system. The platform supports the management of digital and material business processes of industrial integrations. The conceptual approach is based on a comparison of the life cycles of enterprises and their markets. The article proposes a methodology for assessing the readiness of industrial integrations to implement institutional change strategies using modified Shewhart control charts. The methodology is based on a two-criterion approach to the analysis of finances, production reserves, human resources, organizational structures, management technologies, corporate institutions, and a personnel motivation system. This approach allows determining the level of compliance of the resources available with the requirements of the transformation strategy implementation plan. The methodology has been tested at 14 enterprises functioning as industrial integration actors. According to the dynamics of the level of readiness to implement the transformation strategy, enterprises within the framework of industrial integrations are divided into three groups: enterprises with consistently high, medium, and low levels of readiness to implement the strategy.
Two-Stage Delivery System for Last Mile Logistics in Rural Areas: Truck–Drone Approach
Authors: Dai Debao , Cai Hanqi , Ye Liang , Shao Wei
Published: April 2024

In rural areas of China, the challenges of efficient and cost-effective distribution are exacerbated by underdeveloped infrastructure and low population density, with last mile logistics distribution posing a significant obstacle. To address the gap in drone application for last mile logistics in rural areas, a truck–drone distribution model was developed based on the specific conditions of rural regions. The improved fuzzy C-means algorithm (FCM) and genetic simulated annealing algorithm (GASA) were employed to tackle real−world cases in rural areas. The focus of the truck–drone system is to optimize the rural logistics distribution process, reduce delivery time, and minimize costs while considering factors such as maximum mileage of trucks and drones as well as customer priority. Compared to traditional methods, this system has demonstrated notable improvements in distribution efficiency and cost reduction, offering valuable insights for practical drone applications in last mile rural logistics.
Concern or Opportunity: Implementation of the TBL Criterion in the Healthcare System
Authors: Milojević Stefan , Slavković Marko , Knežević Snežana , Zdravković Nebojša , Stojić Vladislava , Adamović Miljan , Mirčetić Vuk
Published: April 2024

This study systematically investigated the extent and application of sustainability practices in the healthcare system by thoroughly examining existing research conducted on healthcare-related issues within the framework of sustainability. The review primarily focuses on three key conceptual aspects: the social, economic, and ecological dimensions of sustainability. PLS-SEM (partial least squares structural equation modeling) and MGA (multigroup analysis) for private and state healthcare organizations were applied in the study. The results show that there exists a robust positive relationship between the environmental dimension and the social dimension of health organizations’ outcomes, and the environmental dimension of the sustainability of healthcare organizations achieves a positive relationship with the economic dimension, while this relatedness is absent in the case of private healthcare organizations, for two perspectives: internal processes and learning. Moreover, the social dimension is identified as a factor that strengthens the impact of the environmental dimension on the economic dimension of health organizations’ outcomes. The results can be used in the development of policies and regulations, and for defining the strategies of healthcare organizations.
Dynamic Mechanism of Destination Brand Diffusion: Agent-Based Modeling and Simulation
Authors: Deng Lihui , Tan Jin , He Danyang , Zhao Hong , Wang Zongshui
Published: April 2024

In recent years, social media has emerged as an important channel for the dissemination of destination branding. Despite the fact that the dissemination of information through social media enables a broader audience to become acquainted with destinations, the dissemination process of trending events exhibits variances. Consequently, the precise impact of the underlying mechanisms that govern the spread of information on the efficacy of disseminating destination brand trending events remains ambiguous. In an endeavor to bridge this gap, an improved SEIR model was developed in this research to investigate the dynamic dissemination mechanisms and influencing factors of destination trending events within social media. The model was applied to simulate the diffusion mechanism of destinations’ trending events. The results show that during the dissemination process of destination trending events on social media, the proportion of users affected at different stages influences the ultimate effectiveness of information propagation. In light of these insights, this research proposes a social media trending event dissemination strategy to aid in enhancing the propagation efficiency of destination brands through existing resources.
Parameterization and Performance Analysis of a Scalable, near Real-Time Packet Capturing Platform
Authors: Oliveira Rafael , Pedrosa Tiago , Rufino José , Lopes Rui Pedro
Published: April 2024

The rapid evolution of technology has fostered an exponential rise in the number of individuals and devices interconnected via the Internet. This interconnectedness has prompted companies to expand their computing and communication infrastructures significantly to accommodate the escalating demands. However, this proliferation of connectivity has also opened new avenues for cyber threats, emphasizing the critical need for Intrusion Detection Systems (IDSs) to adapt and operate efficiently in this evolving landscape. In response, companies are increasingly seeking IDSs characterized by horizontal, modular, and elastic attributes, capable of dynamically scaling with the fluctuating volume of network data flows deemed essential for effective monitoring and threat detection. Yet, the task extends beyond mere data capture and storage; robust IDSs must integrate sophisticated components for data analysis and anomaly detection, ideally functioning in real-time or near real-time. While Machine Learning (ML) techniques present promising avenues for detecting and mitigating malicious activities, their efficacy hinges on the availability of high-quality training datasets, which in turn poses a significant challenge. This paper proposes a comprehensive solution in the form of an architecture and reference implementation for (near) real-time capture, storage, and analysis of network data within a 1 Gbps network environment. Performance benchmarks provided offer valuable insights for prototype optimization, demonstrating the capability of the proposed IDS architecture to meet objectives even under realistic operational scenarios.
The Impact of Platform Information Sharing on Manufacturer’s Choice of Online Distribution Mode and Green Investment
Authors: Jiao Leilei , Deng Fumin
Published: April 2024

In this study, we consider a dual-channel supply chain structure where a manufacturer invests in green products and distributes them to green-conscious consumers through an offline retailer and an online platform. The manufacturer has the flexibility to choose sales via either a wholesale mode or an agency selling mode on the online platform channel. The platform can obtain private information and decide whether to share it with the manufacturer. This study investigates the strategic interaction between the green manufacturer’s decision to use an online sales mode and the online platform’s strategy for information sharing. Our analysis reveals that under the wholesale price mode, the platform is willing to share demand information only when the manufacturer exhibits high investment efficiency. In contrast, under the agency selling mode, the platform always shares demand information regardless of the level of investment efficiency. Nevertheless, the manufacturer is discouraged from opting for the agency selling mode due to the higher commission rate. Interestingly, we observe that when the value of information is sufficiently high, the manufacturer still tends to prefer the agency selling mode, despite the added cost of the higher commission fee. Additionally, the offline retailer always benefits from the information sharing conducted by the online platform. Finally, our extended model indicates that the timing of information-sharing decisions has a significant impact on the manufacturer’s choice of mode.
The Effect of Combined Exposure of Fusarium Mycotoxins on Lipid Peroxidation, Antioxidant Defense, Fatty Acid Profile, and Histopathology in Laying Hens’ Liver
Authors: Kulcsár Szabina , Turbók Janka , Kövér György , Balogh Krisztián , Zándoki Erika , Gömbös Patrik , Ali Omeralfaroug , Szabó András , Mézes Miklós
Published: April 2024

Fumonisin B1, T-2 toxin, and deoxynivalenol are frequently detected in feed materials. The mycotoxins induce free radical formation and, thereby, lipid peroxidation. The effects of mycotoxin exposure at the EU recommended limit (T-2/HT-2 toxin: 0.25 mg/kg; DON = 3AcDON/15-AScDON: 5 mg/kg; fumonisin B1: 20 mg/kg) and double dose (T-2/HT-2 toxin: 0.5 mg/kg, DON/3-AcDON/15-AcDON: 10 mg, and FB1: 40 mg/kg feed) were investigated during short-term (3 days) per os exposure in the liver of laying hens. On day 1 higher while on day 3 lower MDA concentrations were found in the low-dose group compared to the control. Fatty acid composition also changed: the proportion of monounsaturated fatty acids increased (p < 0.05) and the proportion of polyunsaturated fatty acids decreased by day 3. These alterations resulted in a decrease in the index of unsaturation and average fatty acid chain length. Histopathological alterations suggested that the incidence and severity of liver lesions were higher in the mycotoxin-treated laying hens, and the symptoms correlated with the fatty acid profile of total phospholipids. Overall, the findings revealed that mycotoxin exposure, even at the EU-recommended limits, induced lipid peroxidation in the liver, which led to changes in fatty acid composition, matched with tissue damage.
The Molecular Architecture and Mode of Action of Clostridium perfringens ε-Toxin
Authors: Titball Richard W.
Published: April 2024

Clostridium perfringens ε-toxin has long been associated with a severe enterotoxaemia of livestock animals, and more recently, was proposed to play a role in the etiology of multiple sclerosis in humans. The remarkable potency of the toxin has intrigued researchers for many decades, who suggested that this indicated an enzymatic mode of action. Recently, there have been major breakthroughs by finding that it is a pore-forming toxin which shows exquisite specificity for cells bearing the myelin and lymphocyte protein (MAL) receptor. This review details the molecular structures of the toxin, the evidence which identifies MAL as the receptor and the possible roles of other cell membrane components in toxin binding. The information on structure and mode of action has allowed the functions of individual amino acids to be investigated and has led to the creation of mutants with reduced toxicity that could serve as vaccines. In spite of this progress, there are still a number of key questions around the mode of action of the toxin which need to be further investigated.
Studying Venom Toxin Variation Using Accurate Masses from Liquid Chromatography–Mass Spectrometry Coupled with Bioinformatic Tools
Authors: Alonso Luis L. , van Thiel Jory , Slagboom Julien , Dunstan Nathan , Modahl Cassandra M. , Jackson Timothy N. W. , Samanipour Saer , Kool Jeroen
Published: April 2024

This study provides a new methodology for the rapid analysis of numerous venom samples in an automated fashion. Here, we use LC-MS (Liquid Chromatography–Mass Spectrometry) for venom separation and toxin analysis at the accurate mass level combined with new in-house written bioinformatic scripts to obtain high-throughput results. This analytical methodology was validated using 31 venoms from all members of a monophyletic clade of Australian elapids: brown snakes (Pseudonaja spp.) and taipans (Oxyuranus spp.). In a previous study, we revealed extensive venom variation within this clade, but the data was manually processed and MS peaks were integrated into a time-consuming and labour-intensive approach. By comparing the manual approach to our new automated approach, we now present a faster and more efficient pipeline for analysing venom variation. Pooled venom separations with post-column toxin fractionations were performed for subsequent high-throughput venomics to obtain toxin IDs correlating to accurate masses for all fractionated toxins. This workflow adds another dimension to the field of venom analysis by providing opportunities to rapidly perform in-depth studies on venom variation. Our pipeline opens new possibilities for studying animal venoms as evolutionary model systems and investigating venom variation to aid in the development of better antivenoms.
Overview of Bacterial Protein Toxins from Pathogenic Bacteria: Mode of Action and Insights into Evolution
Authors: Popoff Michel R.
Published: April 2024

Bacterial protein toxins are secreted by certain bacteria and are responsible for mild to severe diseases in humans and animals. They are among the most potent molecules known, which are active at very low concentrations. Bacterial protein toxins exhibit a wide diversity based on size, structure, and mode of action. Upon recognition of a cell surface receptor (protein, glycoprotein, and glycolipid), they are active either at the cell surface (signal transduction, membrane damage by pore formation, or hydrolysis of membrane compound(s)) or intracellularly. Various bacterial protein toxins have the ability to enter cells, most often using an endocytosis mechanism, and to deliver the effector domain into the cytosol, where it interacts with an intracellular target(s). According to the nature of the intracellular target(s) and type of modification, various cellular effects are induced (cell death, homeostasis modification, cytoskeleton alteration, blockade of exocytosis, etc.). The various modes of action of bacterial protein toxins are illustrated with representative examples. Insights in toxin evolution are discussed.
Serosurvey of Coxiella burnetii in Police Officers and Working Dogs in Brazil: Case Report and One Health Implications
Authors: de França Danilo Alves , da Silva Jéssica Santos , Rodrigues Nássarah Jabur Lot , Duré Ana Íris de Lima , Farinhas João Henrique , Kmetiuk Louise Bach , Langoni Helio , Biondo Alexander Welker
Published: April 2024

Background: Although the Coxiella burnetii infection has been investigated in dogs, its role in human transmission remains to be fully established, particularly in close and daily human–dog contact settings, such as in Police K-9 Units. Methods: Accordingly, this study aimed to assess anti-C. burnetii antibodies in clinically healthy police officers by an in-house indirect immunofluorescence assay (IFA), and working dogs by a commercial IFA Kit, from the State Special Operations Battalion, Paraná, Southern Brazil. Results: Overall, 1/18 (5.5%) police officers and 9/30 (30.0%; CI 95% 16.66–47.88) dogs tested seropositive to anti-C. burnetii IgG antibodies. Conclusions: To date, this is the highest prevalence of Q fever seropositivity among military dogs worldwide. Despite the low sampling rate, a statistically significant association was found between seropositivity and female dogs (p = 0.0492). Further studies with larger sample sizes should be conducted to establish the prevalence of Q Fever in other Brazilian K-9 Units. In summary, this study is the first to conduct a concomitant serosurvey of police officers and working dogs, and its findings should be considered a warning for cross-exposure and transmission of Coxiella burnetii among Police K-9 Units in Brazil and worldwide.
New Timing Results of MSPs from NICER Observations
Authors: Zheng Shijie , Han Dawei , Xu Heng , Lee Kejia , Yuan Jianping , Wang Haoxi , Ge Mingyu , Zhang Liang , Li Yongye , Yin Yitao , Ma Xiang , Chen Yong , Zhang Shuangnan
Published: April 2024

Millisecond pulsars (MSPs) are known for their long-term stability. Using six years of observations from the Neutron Star Interior Composition Explorer (NICER), we have conducted an in-depth analysis of the X-ray timing results for six MSPs: PSRs B1937+21, B1821-24, J0437-4715, J0030+0451, J0218+4232, and J2124-3358. The timing stability parameter σz has been calculated, revealing remarkable timing precision on the order of 10−14 for PSRs B1937+21 and J0437-4715, and 10−13 for PSRs B1821-24, J0218+4232, and J0030+0451 over a timescale of 1000 days. These findings underscore the feasibility of autonomous in-orbit timekeeping using X-ray observations of MSPs. In addition, the consistency of long-term spin-down noise in the X-ray and radio bands has been investigated by comparison with IPTA radio data.
The Susceptibility of Chickens to Zika Virus: A Comprehensive Study on Age-Dependent Infection Dynamics and Host Responses
Authors: Nissly Ruth H. , Lim Levina , Keller Margo R. , Bird Ian M. , Bhushan Gitanjali , Misra Sougat , Chothe Shubhada K. , Sill Miranda C. , Kumar Nagaram Vinod , Sivakumar A. V. N. , Naik B. Rambabu , Jayarao Bhushan M. , Kuchipudi Suresh V.
Published: April 2024

Zika virus (ZIKV) remains a public health concern, with epidemics in endemic regions and sporadic outbreaks in new areas posing significant threats. Several mosquito-borne flaviviruses that can cause human illness, including West Nile, Usutu, and St. Louis encephalitis, have associations with birds. However, the susceptibility of chickens to ZIKV and their role in viral epidemiology is not currently known. We investigated the susceptibility of chickens to experimental ZIKV infection using chickens ranging from 1-day-old chicks to 6-week-old birds. ZIKV caused no clinical signs in chickens of all age groups tested. Viral RNA was detected in the blood and tissues during the first 5 days post-inoculation in 1-day and 4-day-old chicks inoculated with a high viral dose, but ZIKV was undetectable in 6-week-old birds at all timepoints. Minimal antibody responses were observed in 6-week-old birds, and while present in younger chicks, they waned by 28 days post-infection. Innate immune responses varied significantly between age groups. Robust type I interferon and inflammasome responses were measured in older chickens, while limited innate immune activation was observed in younger chicks. Signal transducer and activator of transcription 2 (STAT2) is a major driver of host restriction to ZIKV, and chicken STAT2 is distinct from human STAT2, potentially contributing to the observed resistance to ZIKV infection. The rapid clearance of the virus in older chickens coincided with an effective innate immune response, highlighting age-dependent susceptibility. Our study indicates that chickens are not susceptible to productive ZIKV infection and are unlikely to play a role in the ZIKV epidemiology.
Quantitation of Enterovirus A71 Empty and Full Particles by Sedimentation Velocity Analytical Ultracentrifugation
Authors: Yang Anna , Luo Yun , Yang Jie , Xie Tingbo , Wang Wenhui , Wan Xin , Wang Kaiwen , Pang Deqin , Yang Dongsheng , Dai Hanyu , Wu Jie , Meng Shengli , Guo Jing , Wang Zejun , Shen Shuo
Published: April 2024

The enterovirus A71 (EV71) inactivated vaccine is an effective intervention to control the spread of the virus and prevent EV71-associated hand, foot, and mouth disease (HFMD). It is widely administered to infants and children in China. The empty particles (EPs) and full particles (FPs) generated during production have different antigenic and immunogenic properties. However, the antigen detection methods currently used were established without considering the differences in antigenicity between EPs and FPs. There is also a lack of other effective analytical methods for detecting the different particle forms, which hinders the consistency between batches of products. In this study, we analyzed the application of sedimentation velocity analytical ultracentrifugation (SV-AUC) in characterizing the EPs and FPs of EV71. Our results showed that the proportions of the two forms could be quantified simultaneously by SV-AUC. We also determined the repeatability and accuracy of this method and found that both parameters were satisfactory. We assessed SV-AUC for bulk vaccine quality control, and our findings indicated that SV-AUC can be used effectively to analyze the percentage of EPs and FPs and monitor the consistency of the process to ensure the quality of the vaccine.
Characteristics and Outcomes for Recipients of NVX-CoV2373: A Real-World Retrospective Study in Germany
Authors: Kutikova Lucie , Brash James T. , Helme Kawitha , Brewster Jack , Brand Milou , Adam Atif , Seager Sarah , Kostev Karel , Schelling Jörg
Published: April 2024

Real-world evidence supports SARS-CoV-2 vaccination strategies during the COVID-19 pandemic. This real-world retrospective study utilized the German Disease Analyzer database to characterize recipients of NVX-CoV2373 and explore vaccination outcomes. Recipients (≥12 years) of NVX-CoV2373 as a primary series or booster in Germany were vaccinated between March and December 2022. Outcomes included demographics and clinical characteristics of recipients, tolerability/reactogenicity-related events within 7 and 14 days post-vaccination, and protection from COVID-19. Overall, there were 597 recipients (mean age ~60 years) of NVX-CoV2373; 81% were vaccinated by a general practitioner, and 68% had a Standing Committee on Vaccination (STIKO) high-risk factor. The most common baseline comorbidities were chronic neurological (36%) and chronic intestinal (21%) diseases. Among recipients with metabolic disease (~11%), 65% had diabetes. Tolerability/reactogenicity-related symptoms were recorded in ~1% of recipients. There were no sick-leave notes associated with NVX-CoV2373. After 10 months (median, 7 months) of follow-up, 95% (95% CI, 93–95) of recipients were estimated to be protected from COVID-19. Outcomes were similar across the primary series, booster, and STIKO populations. Tolerability and COVID-19 protection support the use of NVX-CoV2373 as a primary/booster vaccination for all authorized populations, including high-risk.
Innate Responses to the Former COVID-19 Vaccine Candidate CVnCoV and Their Relation to Reactogenicity and Adaptive Immunogenicity
Authors: Wolz Olaf-Oliver , Vahrenhorst Dominik , Quintini Gianluca , Lemberg Christina , Koch Sven D. , Kays Sarah-Katharina , Walz Lisa , Kulkarni Neeraja , Fehlings Michael , Wengenmayer Peter , Heß Jana , Oostvogels Lidia , Lazzaro Sandra , von Eisenhart-Rothe Philipp , Mann Philipp
Published: April 2024

Vaccines are highly effective at preventing severe coronavirus disease (COVID-19). With mRNA vaccines, further research is needed to understand the association between immunogenicity and reactogenicity, which is defined as the physical manifestation of an inflammatory response to a vaccination. This study analyzed the immune response and reactogenicity in humans, post immunization, to the former SARS-CoV-2 mRNA investigational vaccine CVnCoV (CV-NCOV-001 and CV-NCOV-002 clinical trials). Immunogenicity was investigated using whole-blood RNA sequencing, serum cytokine levels, and SARS-CoV-2-specific antibodies. The T cell responses in peripheral blood were assessed using intracellular cytokine staining (ICS) and high-dimensional profiling in conjunction with SARS-CoV-2 antigen-specificity testing via mass cytometry. Reactogenicity was graded after participants’ first and second doses of CVnCoV using vaccine-related solicited adverse events (AEs). Finally, a Spearman correlation was performed between reactogenicity, humoral immunity, and serum cytokine levels to assess the relationship between reactogenicity and immunogenicity post CVnCoV vaccination. Our findings showed that the gene sets related to innate and inflammatory immune responses were upregulated one day post CVnCoV vaccination, while the gene sets related to adaptive immunity were upregulated predominantly one week after the second dose. The serum levels of IFNα, IFNγ, IP-10, CXCL11, IL-10, and MCP-1 increased transiently, peaking one day post vaccination. CD4+ T cells were induced in all vaccinated participants and low frequencies of CD8+ T cells were detected by ex vivo ICS. Using mass cytometry, SARS-CoV-2 spike-specific CD8+ T cells were induced and were characterized as having an activated effector memory phenotype. Overall, the results demonstrated a positive correlation between vaccine-induced systemic cytokines, reactogenicity, and adaptive immunity, highlighting the importance of the balance between the induction of innate immunity to achieve vaccine efficacy and ensuring low reactogenicity.
Different Immune Control of Gram-Positive and Gram-Negative Mammary Infections in Dairy Cows
Authors: Curone Giulio , Filipe Joel , Inglesi Alessia , Bronzo Valerio , Pollera Claudia , Comazzi Stefano , Draghi Susanna , Piccinini Renata , Ferlazzo Gianluca , Quattrone Alda , Vigo Daniele , Amadori Massimo , Riva Federica
Published: April 2024

In the dairy industry, bovine mastitis represents a major concern due to substantial production losses and costs related to therapies and early culling. The mechanisms of susceptibility and effective response to intra-mammary infections are still poorly understood. Therefore, we investigated innate immunity in acellular bovine skim milk through cytofluorimetric analyses of bacterial killing activity against both Gram-positive and Gram-negative pathogens. Freshly cultured E. coli and S. aureus strains were incubated with colostrum and milk samples at different lactation time points from two groups of cows, purportedly representing mastitis-resistant and mastitis-susceptible breeds; bacterial cells were analyzed for vitality by flow cytometry following incorporation of vital dyes. N-acetyl-β-D-glucosaminidase (NAGase) activity was also investigated in milk and colostrum samples. Our findings revealed that colostrum and milk bacterial killing activity was greater against S. aureus compared to E. coli., with this activity correlated with milk NAGase levels. Furthermore, both killing of S. aureus and NAGase activity were negatively correlated to the elapsed time of lactation. Interestingly, samples from the allegedly mastitis-resistant breed displayed higher bacterial killing and NAGase activities. Our study suggests that diverse control mechanisms are exerted against Gram-positive and Gram-negative pathogens in the mammary glands of cows, probably beyond those already described in the literature.
Monitoring of Microplastics in Water and Sediment Samples of Lakes and Rivers of the Akmola Region (Kazakhstan)
Authors: Salikova Natalya S. , Rodrigo-Ilarri Javier , Makeyeva Lyudmila A. , Rodrigo-Clavero María-Elena , Tleuova Zhulduz O. , Makhmutova Anar D.
Published: April 2024

This paper provides a detailed description of the findings and methodology related to the monitoring of microplastics in three lakes and one river of the Akmola Region in Kazakhstan. The concentration of microplastic particles and the analysis of water and sediment quality of the Yesil River and Kopa, Zerendinskoye, and Borovoe lakes have been analyzed. A total of 64 water samples were collected across the spring, summer, and autumn seasons, with subsequent analysis revealing a seasonal increase in microplastic concentrations. The average microplastic content ranged from 1.2 × 10−1 particles/dm3 in spring to 4.5 × 10−1 particles/dm3 in autumn. Lakes exhibited higher concentrations compared to the Yesil River. Correlation analysis highlighted a connection between microplastic content and turbidity, particularly notable during the spring season. Analysis of sediments revealed a decrease in microplastic concentrations from the coastal zone toward open waters sediments. Microplastic fibers were predominant in sediments (69.6%), followed by fragments (19.1%), films (7.4%), and granules (3.9%). Larger particles (>500 µm) were found in beach sediments, constituting an average of 40.5% of the total plastics found. This study contributes valuable insights into the spatial and temporal distribution of microplastics, emphasizing the need for ongoing monitoring and management strategies to address this environmental concern.
Morphometric Analysis Using Geographical Information System and the Relationship with Precipitation Quantiles of Major Dam Basins in South Korea
Authors: Oh Sejeong , Lee Jinwook , Baik Jongjin , Jun Changhyun , Lee Eui Hoon
Published: April 2024

Geographic information system (GIS) and remote sensing (RS) technologies are potent tools for evaluating various aspects of basin hydrology. This study conducted a morphological analysis using GIS tools on seven major dam basins in Korea. Additionally, long-term RS-based precipitation data were obtained, the probability of precipitation was estimated, and their relationship was examined. The findings are summarized as follows. It was observed that most major dam basins in Korea, which were the focus of this study, had a broad radial shape, and due to the mountainous topography, there was a notable presence of numerous river branches. Through the estimation of probability precipitation and its comparison with morphological indices, it was noted that wider basins tend to have higher rainfall amounts and a relatively uniform spatial distribution. Furthermore, it was found that the more uniform the spatial distribution, the simpler the river network. This trend becomes more pronounced in relation to basin size for longer durations, and in spatial dispersion for shorter durations. However, it is crucial to acknowledge that the complexity of these relationships is also affected by other factors such as climate, altitude, and local geographical conditions.
Spatio-Temporal Morphodynamics of a Nourished Sandy Shore Based on LiDAR Measurements
Authors: Harenda Marek , Dudkowska Aleksandra , Szmytkiewicz Piotr
Published: April 2024

Coastal erosion is a pervasive global phenomenon, exemplified by the Hel Peninsula situated in the Gulf of Gdańsk, the southern Baltic Sea. The geological constitution of the Hel Peninsula, characterized by sandy and loosely consolidated material, predisposes its coastal zones to continual morphological changes. The peninsula’s limited width and elevation exacerbate shoreline erosion, particularly during periods of heightened storm activity. This study scrutinizes the effectiveness of coastal nourishment interventions, with a specific focus on segments influenced by the Władysławowo port and the Kuźnica vicinity, over several years. This specific section of the coast serves as a significant case study due to its role as a transit zone for sand transport along the whole peninsula. Protective measures, including shore nourishments and coastal groynes, aim to mitigate erosion impacts. Utilizing Airborne Laser Scanning (ALS) data spanning from 2008 to 2022, erosion dynamics were analyzed. The analysis reveals significant erosion patterns coinciding with the frequency and volume of nourishment material deposition, particularly evident in heavily nourished areas proximate to Władysławowo and Kuźnica. Despite persistent monitoring endeavors, persistent erosive trends pose imminent threats to Kuźnica’s infrastructure, necessitating further research into the efficacy of implemented coastal protection measures.
Water Colour Changes in High-Elevation Alpine Lakes during 2017–2022: A Case Study of the Upper Orco Valley Catchment
Authors: Matta Erica , Bresciani Mariano , Giardino Claudia , Chiarle Marta , Nigrelli Guido
Published: April 2024

The water resource is severely compromised by climate change, and its availability and quality can no longer be taken for granted, even in places considered pristine, such as mountains. In this study, we evaluated the water colour variability of three artificial mountain lakes located in a relatively small basin (Western Italian Alps) at high elevations, and related this variability to the local climate conditions of the hydrological basin to which they belong. We estimated the dominant wavelength (DW) of lake water from Sentinel-2 acquisitions for the period 2017–2022, performing a chromaticity analysis. We correlated DW with climatic parameters recorded by two automated weather stations. Average DW varies from 497 nm of Serrù Lake and Agnel Lake to 512 nm of Lake Ceresole, where DW varies seasonally (variation of 75–100 nm in one year). During April–July, the DW of Lake Ceresole is significative correlated with air temperatures and snow cover (−0.8 and +0.8, respectively). During August–October, the relationship with temperature decreases to −0.5, and a correlation of 0.5 with the amount of rainfall appears. This work shows that mountain lake waters can exhibit variable quality (expressed here by water colour) in response to meteorological and hydrological conditions and events.
The Impact of the Water Tariff on the Economic Feasibility of Rainwater Harvesting for Use in Residential Buildings
Authors: Borgert Aline Eloize , Ghisi Enedir
Published: April 2024

This study aims to analyse the technical viability and economic feasibility of rainwater-harvesting systems for single- and multifamily residential buildings in the city of Florianópolis, Brazil. Simulations were conducted for representative buildings in the city under different water-usage scenarios and system designs, in a total of 36 simulation scenarios. An economic analysis was performed for four scenarios over a twenty-year period. Both initial and operational costs were considered, and the net present value, internal rate of return, and payback were used as feasibility indicators. For houses, between 60.1% and 74.8% of the cases were economically feasible, achieving a discounted payback period ranging from 6.2 to 8.6 years. For flats, between 57.8% and 64.2% of the cases were economically feasible, achieving a discounted payback period ranging from 4.8 to 5.6 years. As the water tariff in the city underwent changes recently, the former and current tariff formats were compared. The current tariff format provides more economic benefits for saving potable water, and leads to a higher net present value and a shorter discounted payback period. This research stands out from previous studies as it examines a new scenario in the use of rainwater-harvesting systems.
On the Use of Weather Generators for the Estimation of Low-Frequency Floods under a Changing Climate
Authors: Beneyto Carles , Aranda José Ángel , Francés Félix
Published: April 2024

The present work presents a methodology based on the use of stochastic weather generators (WGs) for the estimation of high-return-period floods under climate change scenarios. Applying the proposed methodology in a case study, Rambla de la Viuda (Spain), satisfactory results were obtained through the regionalization of the bias-corrected EUROCORDEX climate projections and the integration of this information into the parameterization of the WG. The generated synthetic data series fed a fully distributed hydrological model to obtain the future flood quantiles. The results obtained show a clear increase in the precipitation extreme quantiles for the two analyzed projections. Although slightly reducing the annual amount of precipitation, variations between 4.3% for a return period of 5 years in the mid-term projection and 19.7% for a return period of 100 years in the long-term projection have been observed. In terms of temperatures, the results point to clear increases in the maximum and minimum temperatures for both projections (up to 3.6 °C), these increases being greater for the long-term projection, where the heat waves intensify significantly in both magnitude and frequency. Finally, although rivers may present, in general, with lower flows during the year, flood quantiles experience an increase of 53–58% for high return periods, which reach values of up to 145% when we move to smaller catchments. All this combined translates into substantial shifts in the river flow regimes, increasing the frequency and magnitude of extreme flood events.