bluuebunny/crossref_metadata_2025 huggingface dataset:
Real-Life Clinical Outcomes of Benralizumab Treatment in Patients with Uncontrolled Severe Asthma and Coexisting Chronic Rhinosinusitis with Nasal Polyposis
Authors: Chiner Eusebi , Murcia María , Boira Ignacio , Bernabeu María Ángeles , Esteban Violeta , Martínez-Moragón Eva
Published: July 2024

Background: The objective of this study was to evaluate, the clinical benefit of benralizumab in patients with uncontrolled severe asthma associated with chronic rhinosinusitis with nasal polyposis (CRSwNP).
Methods: The study included patients with uncontrolled severe asthma associated with CRSwNP who started therapy with benralizumab. Pulmonary function, eosinophilia, IgE, comorbidity, changes in the Asthma Control Test (ACT), Asthma Control Questionnaire (ACQ), Visual Analogue Scale (VAS), Quality of Life (AQLQ), VAS (obstruction, drip, anosmia, facial pressure), SNOT-22, decrease or withdrawal of steroids and other medication, hospital admissions and emergency visits were analysed. The FEOS scale and EXACTO were employed in the assessment of response.
Results: We analyzed 58 patients who completed minimal treatment at 12 months. After treatment with benralizumab, exacerbations were reduced by 82% (p
Modeling the Dynamic of Multi-Wave Diseases: The Model of Hand, Foot and Mouth Disease
Authors: Ravel Patrice , Duy Nghia Ngu , Kister Guilhem , Huong Le Thi Song , Dwivedi Ankit , Devaux Christian , Duong Tran Nhu , Hien Nguyen Tran , Gavotte Laurent , Cornillot Emmanuel , Frutos Roger
Published: July 2024

An HFMD outbreak spread over the city of Hải Phòng from Summer 2011 to Autumn 2012. This epidemic was chosen because it was the very first HFMD epidemic in North Vietnam, eliminating thus interferences with previous outbreaks. This epidemic displayed 3 separate waves. A complete dataset was collected for more than 9500 patients during this period, which enabled us to analyze this epidemic at different scales. Access to the healthcare system was crucial during this period, with a reorganization of the system in February-March 2012. An analysis at commune level enables us to track the epidemic along certain communication routes. The three-waves structure reveals a wide disparity at district level. We develop a mathematical model showing high accuracy at the adjustment of data for both the total number of cases and for the number of cases per week. As a consequence, the model was able to accurately determine the dates of beginning and end of each wave and to show that they overlapped. Using mathematical functions associated with this model, it was possible to calculate the probability for a patient to belong to a specific wave.
Usability of Minimal Invasive Surgery for Elbow Dislocation with Coronoid Process Fracture: A Protocol Development Study
Authors: Lin Chun-Cheng , Cheng Ming-Fai , Wang Chien-Shun , Chiang Chao-Ching , Su Yu-Ping
Published: July 2024

Introduction: Treating elbow fracture-dislocation is a challenge, especially in the situation of basal-coronoid trans-ulnar fracture. The study ams to explain whether or not the minimal invasive surgery (MIS) would be feasible in elbow dislocation with coronoid fracture. Materials & Methods: At Taipei Veterans General Hospital, patients who had elbow dislocations with coronoid process fractures underwent single one surgeon’s MIS techniques which included the fluoroscopy-guided ulnar anteromedial (FGUAM) approach in the stage of reducing coronoid process. When there is a proximal ulnar fracture, the posterior incision should be necessary, followed by the incision over the lateral or medial elbow in treating radial fractures or ligament injuries. Results: The Flow Diagram about approach recommendation was established in base of defining MIS as not to do cross-plane dissection. Anteriorly rigid fixation for the coronoid process was also emphasized. Conclusions: MIS can be achieved by multiple limited surgical incisions. However, if there is an unstable ulnar metaphysis or ligament avulsion fracture, the posterior approach has to be extended and the so-called MIS fails to be established.
Performance of Linear and Spiral Hashing
Authors: Kulandai Arockia David Roy , Schwarz Thomas Johannes Emil
Published: July 2024

Linear Hashing is an important algorithm for many key-value stores. Spiral Storage was invented to overcome the poor fringe behavior of Linear Hashing, but after an influential study by Larson, seems to have been discarded. Since almost 50 years have passed, we repeat Larson’s comparison with in-memory implementation of both to see whether his verdict still stands. Our study shows that Spiral Storage has slightly better look-up performance, but slightly poorer insert performance.
LCK Function and Modulation: Immune Cytotoxic Response and Tumor Treatment. More than a Simple Event.
Authors: De Sanctis Juan Bautista , GARMENDIA Jenny Valentina , Duchová Hana , Valentini Viktor , Puskasu Alex , Kubíčková Agata , Hajdúch Marián
Published: July 2024

LCK, a member of the Scr kinase family, is a non-receptor tyrosine kinase involved in immune cell activation, antigen recognition, tumor growth, and cytotoxic response. The enzyme has usually been linked to T lymphocyte activation upon antigen recognition. Lck activation is central to CD4, CD8, and NK activation. However, recently, it has become clearer that activating the enzyme in CD8 cells can be independent of antigen presentation and enhance cytotoxic response. The role of Lck in NK cytotoxic function has been controversial in a similar fashion as the role of the enzyme in CAR T cells. Inhibition of Lck has been mainly to treat hematologic malignancies with a high rate of success. They may be useful in treating other tumor types, and they may be useful to prevent cell exhaustion. New, more selective inhibitors have been documented, and they have shown inter-esting activities not only in tumor growth but in the treatment of autoimmune diseases, asthma, and graft vs host disease. Drug repurposing and bioinformatics can aid in solving several unsolved is-sues on the role of Lck in cancer. In summary, the role of Lck in immune response and tumor growth is not a simple event and requires more research.
Adapting Procurement Practices to Disruptive Events: Lessons from Recent Supply Chain Disruptions
Authors: Cooper Mason
Published: July 2024

This study investigates how organizations adapt their procurement practices in response to supply chain disruptions, aiming to enhance resilience and ensure operational continuity. Through qualitative research involving interviews with procurement professionals and industry experts, the study identifies key adaptive strategies employed by organizations, including supplier diversification, enhanced inventory management, digital transformation, supplier collaboration, and contingency planning. These strategies are explored in depth, highlighting their implementation challenges and the outcomes achieved. Despite facing obstacles such as financial constraints, technological barriers, and supplier resistance, organizations have demonstrated a proactive approach in leveraging these strategies to mitigate risks and improve supply chain resilience. The findings reveal that adaptive procurement strategies have led to significant outcomes, including strengthened supplier relationships, increased operational efficiency, better risk management, and competitive advantage. These outcomes underscore the strategic importance of agility, technological integration, collaborative partnerships, and effective leadership in responding to disruptions and maintaining competitiveness. The study also discusses implications for practice and policy, emphasizing the need for continued investment in technology, collaboration, and resilience-building initiatives across supply chains. Overall, this research contributes to the understanding of how organizations can adapt and innovate in the face of dynamic supply chain challenges, providing insights that can guide future research and inform strategic decision-making in procurement and supply chain management.
From Germ Cells to Implantation: The Role of Extracellular Vesicles
Authors: Fazzio Anna , Caponnetto Angela , Ferrara Carmen , Purrello Michele , Di Pietro Cinzia , Battaglia Rosalia
Published: July 2024

Extracellular vesicles represent a large heterogeneous class of near and long-distance intercellular communication mediators, released by both prokaryotic and eukaryotic cells. Specifically, the scientific community has shown a growing interest in exosomes, which are nano-sized vesicles with an endosomal origin. Not so long ago, the physiological goal of exosome generation was largely unknown and required more investigation; at first, it was hypothesized that exosomes are able to remove excess, rejects and unnecessary constituents from cells to preserve cellular homeostasis. However, thanks to recent studies, the central role of exosomes in regulating cellular dialogue has emerged. Exosomes act as vectors on cell-cell signaling by their cargo, proteins, lipids, and nucleic acids, and influence physiological and pathological processes. The findings on exosomes are widespread in a large spectrum of biomedical applications from diagnosis and prognosis to thera-pies. In this review, we describe exosome biogenesis and the current methods for their isolation and characterization, emphasizing the role of their cargo in female reproductive processes, from gametogenesis to implantation, and the potential involvement in human female disorders.
Distribution of Heavy Metals in Surrounding Mining Region of Kizhnica in Kosovo
Authors: Zeqiri Lavdim , Ukić Šime , Ćurković Lidija , Djokic Jelena , Kerolli Mustafa Mihone
Published: July 2024

In this study the distribution of heavy metal in the agricultural soils in the vicinity of 3 large mine-landfills around Kizhnica mine in Kosovo was investigated. The mining sector is one of the most important sectors of the economic development of Kosovo. The Kizhnica mine is one of the main ore producers in Kosovo. In addition to the positive aspects of production development it has its own side effects such as: industrial waste and the possibility of contamination of sur-rounding areas including the agricultural lands in the surrounding region. Ten sampling sites close to the Kizhnica mining complex were selected. These sampling sites have been characterized and evaluated as the most critical points, due to the anthropogenic influences of the discharge of industrial water from mining flotation and open tailing dumps in the Kizhnica. Concentration of Pb, Zn, Cu, As, Cd, Ni, Mn and Sb in selected samples was carried out by inductively coupled plasma–optical emission spectrometry (ICP–OES). Obtained data were used in order to generate geochemical maps and for calculatation the contamination factor (CF), pollution load index (PLI) and geo-accumulation index (Igeo). The statistical clustering analysis (CA), Pearson correlation coefficient (r) and air spatial distribution patterns using AERMOD View-Gaussian air dispersion model are used to perform evaluation within the area. The results demonstrated higher contents of the heavy metals in the vicinity of the mining area. It may be concluded that the heavy metal contents are impacted by anthropogenic nature of the contamination that confirms a current eco-logical threat of the mining activities in the region. Finally, a paper proposes the potential reas-signment of the deposed waste material into different combinations in construction in order to enhance the waste management and reduce the continued risk to: residents, lands and all living beings in the region.
Marine Delivery Vehicles: Molecular Components and Applications of Bacterial Extracellular Vesicles
Authors: Casillo Angela , D'Amico Raffaele , Lanzetta Rosa , Corsaro Maria Michela
Published: July 2024

In marine ecosystems communication among microorganisms is crucial since the distance is significant if considered on a microbial scale. One of the ways used by microorganism cells to reduce this gap is the production of extracellular vesicles. Marine bacteria release extracellular vesicles (EVs), small membrane-bound structures of 50 to 250 nm diameter, into their surrounding environment. The vesicles contain various cellular compounds, including lipids, proteins, nucleic acids, and glycans. EVs may mediate the communication between microorganisms in aquatic environments thus influencing ecosystem function and determining the structure and composition of microbial populations. This review will focus on marine bacterial EVs analysing their structure, composition, functions, and applications.
Fine Tuning of an Advanced Planner for Cognitive Training of Older Adults
Authors: Gaspari Mauro , Mioni Giovanna , Signorello Dario , Stablum Franca , Zuppiroli Sara
Published: July 2024

Developing effective cognitive training tools for older adults, specifically addressing executive functions such as planning, is a challenging task. It is of paramount importance to ensure the implementation of engaging activities, which must be tailored to the specific needs and expectations of older adults. Furthermore, it is essential to provide the appropriate level of complexity for the planning task. A human-centred approach was employed to address the issues identified in the design of the tool. Two pilot studies were conducted with older adults to fine-tune the training task and optimise its suitability for them. This also led to an enhancement of the underlying planning engine, transitioning from simple fast-forward planner (PDDL4J) to an advanced heuristic search planner (ENHSP). The results show that conducting user studies enabled the development of a cognitive training system that gradually increases the proposed difficulty levels of the planning task while maintaining usability and satisfaction among older adults. This highlights the importance of conducting user studies when implementing cognitive training tools for older adults.
The Contribution of Legionella anisa to Legionella Contamination of Water in the Built Environment
Authors: Crook Brian , Young Charlotte , Ridout Ceri , Smith Duncan
Published: July 2024

Legionella bacteria can proliferate in poorly maintained water systems, posing risks to users. All Legionella species are potentially pathogenic but Legionella pneumophila (L. pneumophila) is usually the primary focus of testing. However, Legionella anisa (L. anisa) also colonises water distribution systems, is frequently found with L. pneumophila and could be a good indicator for increased risk of nosocomial infection. Anonymized data from three commercial Legionella testing laboratories afforded analysis of 565,750 water samples. Data covered July 2019 to August 2021, including the COVID-19 pandemic. Results confirmed L. anisa commonly colonises water distribution systems, being the most frequently identified non-L. pneumophila species. Proportions of L. anisa and L. pneumophila generally remained similar but increases in L. pneumophila during COVID-19 lockdown suggests static water supplies might favour its growth. Disinfection of hospital water systems was effective but re-colonization did occur, appearing to favour L. pneumophila, although L. anisa colony numbers also increased as a proportion of the total. While L. pneumophila remains the main species of concern as a risk to human health, L. anisa’s role should not be under-estimated, either as a potential infection risk or as an indicator of the need to intervene to control Legionella colonization of water supplies.
Research on the Magnetic Field Distribution in Drum-Type Eddy Current Separation
Authors: Jia Youdong , Jiang MingJiang , Liu Jianxiong , Yao Sibo , Wang Lei , Zeng Jiaxing , Wan Xiangming
Published: July 2024

As the number of end-of-life vehicles continues to grow, the field of separation technology for broken copper and aluminium parts of end-of-life vehicles has emerged as a significant area of research. As a key technology for the separation of non-magnetic non-ferrous metals, such as copper and aluminium, eddy current separation can achieve efficient separation of non-magnetic non-ferrous metals according to their differing conductivity and density. Nevertheless, further research is required in the separation of large-scale broken copper and aluminium parts of end-of-life vehicles. This paper presents a novel magnetic roller model comprising circumferential and axial periodic arrangements of permanent magnets. A single permanent magnet was constructed as an equivalent current model, and the magnetic scalar potential equations were solved using simulation tools. This allowed the distribution of the magnetic field outside the magnetic roller to be studied. The results demonstrate that the novel permanent magnet array magnetic roller can enhance the magnetic field intensity and action distance of the external magnetic field, which is more conducive to the separation of large-scale broken copper and aluminium parts of scrap cars. The findings of this research provide a theoretical foundation for the separation of scrap car broken copper and aluminium parts.
Dual-Band Antenna With Pattern and Polarization Diversity
Authors: Mo Jungmin , Sung Youngje
Published: July 2024

In this letter, we propose a pattern-diversity antenna with different radiation patterns at two different frequency bands (f1 and f2) (f1: broadside radiation pattern, f2: conical radiation pattern). The proposed structure consists of a central circular antenna and two annular ring antennas; each of the three antennas has individual ports. Two of the ports exhibit orthogonal broadside radiation patterns; the other two ports exhibit orthogonal conical radiation patterns. Thus, they have polarization diversity characteristics. To improve isolation between ports, the inner part of the annular ring antennas is shorted via array, and the outermost port is positioned orthogonal to the other ports. Using this configuration, the isolation between ports was measured as -26.7 dB and -30.1 dB at the two frequency bands, respectively. Experimental results based on the fabricated prototype show that the proposed antenna achieves -10 dB bandwidths of 240 MHz (5.71~5.95 GHz) and 210 MHz (7.69~7.9 GHz) at f1 and f2, respectively.
Cemented Calcar-Guided Short-Stem Prostheses in Geriatric Patients: Short-Term Results from a Prospective Observational Study
Authors: Regenbrecht Bertram , Yaseen Ahmed , Wagener Gideon , Wild Michael
Published: July 2024

Both cementless and cemented stems have exhibited favorable long-term outcomes in total hip arthroplasty. Nonetheless, in elderly patients, cemented hips offer an advantage because of their reduced risk of periprosthetic fractures.
The present study aimed to assess the initial outcomes of 28 patients who underwent unilateral cemented total hip arthroplasty utilizing the calcar-guided A2 stem (Artiqo GmbH, Lüdinghausen, Germany). Various types of antibiotic-loaded cement were employed. Demographic data, comorbidities, and standardized clinical assessment tools, including the Harris Hip Score, were utilized during the follow-up. Radiographic assessments included preoperative, postoperative, and follow-up imaging to evaluate subsidence, osteolysis, and bone resorption.
The results indicated that among the 28 patients, 5 withdrew consent, and 2 patients passed away from unrelated causes. Additionally, one prosthesis was explanted because of undersizing of the cement stopper, resulting in an inadequate cement mantle. As a result, 20 patients underwent a 1-year follow-up, revealing noteworthy enhancements in clinical scores, with no instances of radiolucent lines or osteolysis.
In summary, our short-term experience with this particular cemented short-stem design yielded promising results, exhibiting excellent functional outcomes and no aseptic loosening attributable to the stem. Further clinical studies and registry data are essential to corroborate these findings.
A Retrospective Cross-Sectional Analysis of Self-Reported Adverse Events Following Immunization with the Shingrix Vaccine  
Authors: Khalid Amna , Wons Michael , Vaghela Avani , Hollar Sabrina , Mack John , Evans Hunter , Snyder Jerold , Brooks Benjamin
Published: July 2024

This paper investigates the safety profile of the Shingrix vaccine, focusing particularly on persistent adverse events post-vaccination. Shingrix, crucial for preventing shingles caused by the varicella-zoster virus, has shown efficacy in clinical trials but is associated with varying degrees of adverse reactions. This retrospective, cross-sectional survey-based study, spanning two years and involving 77 respondents who experienced severe adverse events after vaccination, reveals a spectrum of symptoms ranging from mild to severe, including reports of Guillain-Barré syndrome and neuropathy. These findings underscore the need for ongoing vigilance in vaccine safety monitoring and highlight the importance of personalized care approaches for managing post-vaccination adverse effects. The study aims to contribute to informed decision-making regarding shingles vaccination strategies and calls for continued research into the long-term safety and efficacy of Shingrix.
A Novel Exponential Regression Model for Analyzing Dengue Fever Case Rates in the Federal District of Brazi
Authors: Costa Nicollas Stefan Soares da , Lima Maria do Carmo Soares de , Cordeiro Gauss Moutinho
Published: July 2024

This work offers a new log generalized odd log-logistic exponential regression model for analyzing weekly dengue fever cases in 2022 with a location-systematic component. To achieve this, a data set of 49 observations of dengue fever cases in the Federal District of Brazil is employed. A review of the mathematical properties of the generalized odd log-logistic exponential distribution is provided, the maximum likelihood method is used to estimate the parameters, and, through Monte Carlo simulations, the accuracy of the estimators is investigated. The model's fit is assessed using global influence metrics and residual analysis. For the time scenario studied, the proposed regression identified factors that have an impact on dengue fever cases, which may contribute to improve disease control. Finally, several interpretations are addressed, and a discussion presents results that aid in better understanding the data set and future research on different data.
Agile Procurement in a Changing Marketplace: Examining Adaptability and Responsiveness in Supply Chain Management
Authors: Cooper Mason
Published: July 2024

Agile procurement has emerged as a transformative strategy for organizations striving to maintain competitiveness in a rapidly evolving marketplace. This qualitative research investigates the implementation, benefits, challenges, and outcomes of agile procurement practices in supply chain management. Through semi-structured interviews and case studies across diverse industries, this study explores how agile procurement enhances organizational adaptability and responsiveness. Key findings reveal that agile procurement enables organizations to swiftly adjust strategies in response to market fluctuations and customer demands, fostering increased customer satisfaction and loyalty. The integration of advanced technologies, including AI and blockchain, facilitates real-time data analysis, optimizing procurement processes and enhancing supply chain efficiency. Organizational culture emerges as a critical factor in successful agile procurement, with leadership support and a collaborative environment driving cultural change towards agility and innovation. Despite its benefits, challenges such as resistance to change and the need for significant technology investments are identified, requiring careful change management and strategic alignment. Case studies illustrate the versatility of agile procurement across sectors, showcasing its role in enhancing operational efficiencies, innovation capabilities, and overall supply chain performance. In conclusion, agile procurement offers organizations a strategic framework to navigate complexities and uncertainties effectively, capitalizing on market opportunities while mitigating risks. Embracing agile principles fosters a resilient organizational culture capable of adapting to dynamic market conditions. Future research should focus on further refining agile procurement strategies to address emerging challenges and sustain competitive advantage in the global marketplace.
LLM Intelligent Agent Tutoring in Higher Education Courses using a RAG Approach
Authors: Modran Horia , Bogdan Ioana Corina , Ursuțiu Doru , Samoila Cornel , Modran Paul Livius
Published: July 2024

Conventional tutoring approaches are confronted with limitations such as restricted availability, inconsistent pedagogical quality, and scalability con-straints. Furthermore, the exclusive use of Large Language Models (LLMs) like ChatGPT in education has its shortcomings, including the potential for incorrect responses and the lack of customized guidance aligned with specific course con-tent. This research proposes an innovative intelligent chatbot tutoring system, in-tegrating the Retrieval Augmented Generation (RAG) approach with a custom LLM. The developed system aims to overcome the limitations of traditional tu-toring and general-purpose LLMs by providing accurate, contextually relevant, and personalized assistance, thereby enhancing student understanding and en-gagement. The system, powered by an intelligent agent, retrieves relevant information from curated academic sources, incorporates interactive features for user feedback, and utilizes machine learning algorithms for ongoing performance enhancement, ensuring a robust and effective tutoring experience. The anticipated outcome is an enriched educational experience for university students, advance-ment in personalized learning, and improved student engagement, retention, and academic performance. Through continuous research and refinement, it is expected that the intelligent chatbot tutor will assume an important role in enhancing and supporting the educational journey of students.
Mechanistic Insights into the Mutational Landscape of the Main Protease/3CLPro and Its Impact on Long-Term COVID-19/SARS-CoV-2 Management
Authors: Mushebenge Aganze Gloire-Aimé , Ugbaja Samuel Chima , Magwaza Nonjabulo Ntombikhona , Mbatha Nonkululeko Avril , Muzumbukilwa Tambwe Willy , Kadima Mukanda Gedeon , Tata Fave , Mxumalo Mthokosizi , Manimani Riziki Ghislain , Ndage Ntabaza , Amuri Bakari Salvius , Byanga Kahumba , Nlooto Manimbulu , Khan Rene B. , Kumalo Hezekiel M.
Published: July 2024

The main proteinase (Mpro), or 3CLpro, is a critical enzyme in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lifecycle and is responsible for breaking down and releasing vital functional viral proteins crucial for virus development and transmission. As a catalytically active dimer, its dimerization interface has become an attractive target for antiviral drug development. Recent research has extensively investigated the enzymatic activity of Mpro, focusing on its role in regulating the coronavirus replication complex and its significance in virus maturation and infectivity. Computational investigations have identified four druggable pockets, suggesting potential allosteric sites beyond the substrate-binding region. Empirical validation through site-directed alanine mutagenesis targeted residues in both the active and allosteric regions corroborated these predictions. Structural studies of drug target proteins can inform therapeutic approaches, with metadynamics simulations shedding light on the role of H163 in regulating Mpro function and providing insights into its dynamic equilibrium to the wild-type enzyme. Despite the efficacy of vaccines and drugs in mitigating SARS-CoV-2 spread, ongoing viral evolution, selective pressures, and continued transmission pose challenges, potentially leading to resistance mutations. Phylogenetic analyses indicated the existence of several resistance variations predating drug introduction to the human population, emphasizing the likelihood of drug spread. Hydrogen/deuterium-exchange mass spectrometry reveals the structural influence of the mutation, while clinical trials on 3CLPro inhibitors underscore the clinical significance of reduced enzymatic activity and offer avenues for future therapeutic exploration. Understanding the implications of 3CLPro mutations holds promise for shaping forthcoming therapeutic strategies against COVID-19. This review delves into factors influencing mutation rates and identifies areas warranting further investigation, providing a comprehensive overview of Mpro mutations, their categorization, and terminology. Moreover, we examined their associations with clinical outcomes, illness severity, unresolved issues, and future research prospects, including their impact on vaccine efficacy and potential therapeutic targeting.
Evaluating Atlantic Salmon (Salmo salar) as a Natural or Alternative Host for Piscine Myocarditis Virus (PMCV) Infection
Authors: Nyman Ingvild B. , Wessel Øystein , Bjørgen Håvard , Alarcon Marta , Tengs Torstein , Rimstad Espen
Published: July 2024

Cardiomyopathy syndrome (CMS) caused by piscine myocarditis virus (PMCV) has emerged in aquaculture of Atlantic salmon (Salmo salar). The lack of cell culture has hampered studies of the infection. In this study samples from naturally PMCV infected Atlantic salmon from commercial farms were collected and used.
In situ hybridization revealed intense staining for PMCV RNA in myocard in the spongiform layer of the heart, but almost no staining in the compact layer. In kidneys only sporadic staining was seen. Viral RNA was present in all organs, with the highest loads in the heart, kidney, and spleen.
The high viral PMCV RNA loads in the heart were caused by extensive viral mRNA transcription. The high ratio of viral mRNA to viral genomic dsRNA, indicated active transcription but limited production of new viral particles. This suggests that the histopathological changes of the heart are caused by viral mRNA and corresponding viral proteins.
The production of full-length transcripts is regulated, with a reduction in the relative amount of ORF3-containing transcripts at high transcription rates. Efforts to identify alternative hosts, such as fungi, were inconclusive, as fungal sequences were found inconsistently in salmon tissue samples. The results reinforce the need for further research to fully understand PMCV’s life cycle and potential alternative hosts and its whereabouts when it is not infecting the heart of the At-lantic salmon.
HybridPlantNet23: A Scientific Insight into the Power of Ensemble Modelling using VGG16 and Darknet53 for Plant Disease Classification
Authors: AKINCI Tahir Cetin , Ekici Sami , Kabir Masud , Martinez-Morales Alfredo A.
Published: July 2024

This study evaluates the effectiveness of Darknet53 and VGG16 pretrained models to develop a hybrid ensemble model named HybridPlantNet23 deep learning model for effective plant disease classification, using the publicly available dataset ‘A Dataset of Leaf Images’ from Mendeley webpage. The preprocessing of the dataset involved resizing the images to the respective requirements of the pretrained models to develop a combined datastore which served as the input. All experiments were conducted using MATLAB R2023b deep network designer interface. Model performances were evaluated based on the conventional accuracy, precision, recall, and F1-score. VGG16 achieved the highest accuracy (97.25%), precision (96.30%), recall (96.96%), and F1-score (96.55%), outperforming both Darknet53 and the ensemble HybridPlantNet23 model. Despite the advanced architecture of the ensemble model, its performance (accuracy: 95.37%, precision: 93.56%, recall: 94.20%, F1-score: 93.74%) was not significantly superior, thus highlighting scientific reasons behind this development. Recommendations for future works were provided accordingly.
Relaxing Effect of 8-Methoxycirsilineol Extracted (Larrea tridentata) by Potassium Channels Depend-Voltage Activation on Vascular Smooth Muscle from Guinea Pig
Authors: Algara-Suarez Paola , Navarro-Huerta Martha Patricia , González-Chávez Marco Martín , Ordaz-Ruiz Xochitl , Rodríguez-Menchaca Aldo Azmar , Aréchiga-Figueroa Iván Arael , Brito-Orta María Dolores , Valle-Aguilera Juan Roberto , Espinosa-Tanguma Ricardo
Published: July 2024

Larrea tridentata is an endemic plant from the Mexican highlands used in traditional medicine to treat hypertension and kidney stones, among many ailments. This study evaluated a vasorelaxant compound: 5- Hydroxy-2-(4-hydroxy-3-methoxyphenyl)-6,7,8-trimethoxy-4H-1-benzopyran-4-one (also known as 8-Methoxycirsilineol: 8-M) which we purified from an extract of this plant. Mesenteric artery rings were isolated from male guinea pigs for isometric force measurements. Freshly isolated smooth muscle cells from mesenteric artery were used for ionic current measurement for calcium and potassium. 10 μM 8-M completely relaxed vascular rings contracted with phenylephrine in a dose-dependent fashion with an EC50 = 4.26 ± 1.16 10-6 M and 4.56 ± 1.64 10-6 M for endothelium intact and endothelium-free tissue, respectively. The relaxant effect of 8-M was not affected by maximal doses of nifedipine, verapamil or iberiotoxin. Nevertheless, the relaxant effect was partially abolished by addition of 10 mM Tetraethylammonium (TEA). In accordance to this, calcium currents evoked by depolarization were not affected by 8-M, whereas TEA-sensitive potassium currents, were increased upon its addition. Vasorelaxation due to 8-M is partly due to activation of KV currents in an endothelium independent mode.
New Random Walk Algorithm Based on Different Seed Nodes for Community Detection
Authors: Li Wencong , Cai Jiansheng , Zhang Xiaodong , Wang Jihui
Published: July 2024

The complex network is an abstract modeing of complex systems in the real world, which plays an important role in analyzing the function of complex systems. Community detection is an important tool for analyzing network structure. In this paper, we propose a new community detection algorithm (RWBS) based on different seed nodes aims to understand the community structure of the network, which provides a new idea for the allocation of resources in the network. RWBS provides a new centrality metric ($MC$) to calculate node importance, which calculates the ranking of nodes as seed nodes. Furthermore, two algorithms are proposed for determining seed nodes on networks with and without ground-truth, respectively. We set the number of steps for the random walk to 6 according to the six degrees of separation theory to reduce the running time of the algorithm. Since some traditional community detection algorithms may detect smaller communities, e.g., two nodes become one community, this may make the resource allocation unreasonable. Therefore, modularity ($ Q $) is chosen as the optimization function to combine communities, which can improve the quality of detected communities. Final experimental results on real-world and synthetic networks show that the RWBS algorithm can effectively detect communities.
The Impact of Green Space on PM2.5 Concentration: A Review
Authors: Liu Junyou , Zheng Bohong
Published: July 2024

Fine particulate matter (PM2.5) can enter the lungs and cause premature death in millions of people worldwide every year. More and more international scholars are paying attention to the potential harm of PM2.5 and how to reduce its negative impact. Reducing air pollution and its negative impacts is an important function of green spaces. Many scholars have conducted research on the impact of green spaces on PM2.5. This article attempts to comprehensively review past related research. This is undoubtedly beneficial for people to better understand the impact of green spaces on PM2.5 and optimize green spaces accordingly to reduce PM2.5 concentration. This article first provides a detailed introduction to the impact of plants on PM2.5 pollution from the perspective of the mechanism of action. Then, this article provides a review of the different impacts of green space types and morphological factors on the surrounding environment PM2.5. In addition, this article outlines the range of the impact of green spaces on PM2.5 in the environment. This article categorizes green spaces into different types such as road green spaces, commercial and residential green spaces, and parks and squares, and explores the impact of green spaces on PM2.5 in the environment. This article analyzes the impact of various parts of a single plant on PM2.5 in the environment from a single plant perspective. Finally, this article analyzes which factors in the surrounding environment can affect the impact of green spaces on PM2.5 pollution in the environment. A review of relevant research is also beneficial for people to have a more comprehensive understanding of current research progress and guide future research to better carry out.
The Differential Error Components Models under Treatment Effect Heterogeneity
Authors: Jin Yongtao
Published: July 2024

The fixed and random effects models are popular methods for identifying the causal effects of treatment. First, I introduce the two-way fixed effects model and show a class of the estimators for the random effects models. Misidentification may occur in these models due to the treatment effect heterogeneity. Then, I propose the differential error component models to address such problems while the models exclude the fixed effects of units and time periods and consider the random effects of units and time periods. Meanwhile, I present a simulation of a staggered design and revisit the application in (De Chaisemartin and D'Haultfoeuille, 2020). The results demonstrate that one additional newspaper increases the 0.31% average effect of the presidential turnout and the 1.05% average effect when the newspapers’ changes are non-negative, where the proposed estimators are robust and efficient.
Inner Structure of the Lateral Geniculate Complex of Adult and Newborn Acomys cahirinus
Authors: Merkulyeva Natalia , Mikhalkin Aleksandr , Veshchitskii Aleksandr
Published: July 2024

Acomys cahirinus is a unique Rodentia species with several distinctive physiological traits, such as precocial development and remarkable regenerative abilities. These characteristics render A. cahirinus increasingly valuable for regenerative and developmental physiology studies. Despite this, the structure and postnatal development of the central nervous system in A. cahirinus have been inadequately explored, with only sporadic data available. This study is the first in a series of papers addressing these gaps. Our first objective was to characterize the structure of the main visual thalamic region, the lateral geniculate complex, using several neuronal markers (including Ca2+-binding proteins, glutamic acid decarboxylase enzyme, and non-phosphorylated domains of heavy-chain neurofilaments) to label populations of principal neurons and interneurons in adult and newborn A. cahirinus. As typically found in other rodents, we identified three subdivisions in the geniculate complex: the dorsal and ventral geniculate nuclei (LGNd and LGNv) and the intergeniculate leaflet (IGL). Additionally, we characterized internal diversity in the LGN nuclei. The "shell" and "core" regions of the LGNd were identified using calretinin in adults and newborns. In adults, the inner and outer parts of the LGNv were identified using calbindin, calretinin, parvalbumin, GAD67, and SMI-32, whereas in newborns, calretinin and SMI-32 were employed for this purpose. Our findings revealed more pronounced developmental changes in LGNd compared to LGNv and IGL, suggesting that LGNd is less mature at birth and more influenced by visual experience.
Application of Deep Learning-Based Intrusion Detection System (IDS) in Network Anomaly Traffic Detection
Authors: Zhao Fanyi , Li Hanzhe , Niu Kaiyi , Shi Jiatu , Song Runze
Published: July 2024

This study discusses the application of deep learning technology in network intrusion detection systems (IDS) and focuses on a new model named CNN-Focal. First, through the review of traditional IDS technology, it analyzes its limitations in dealing with complex network traffic. Then, the design principle of the CNN-Focal model is described in detail, which uses threshold convolution and SoftMax multi-class classification technology to effectively improve abnormal traffic detection's accuracy and efficiency. The experimental results show that CNN-Focal performs well on the open data set, demonstrating the potential and advantages of its application in the natural network environment and providing a new perspective and method for further research of deep learning in the field of network security in the future.
Assessing Personality Traits in Women with Gestational Diabetes Compared to Healthy Pregnant Women
Authors: Grinberg Keren , Mekuzas Yael Yisaschar
Published: July 2024

Introduction: Gestational diabetes mellitus (GDM) pregnant women are under more psychological stress than healthy pregnant women. The objectives of the current study were to examine: (1) The differences in anxiety, depression, stress, and somatization levels between women diagnosed with GDM and healthy pregnant women. (2) The differences in anxiety, depression, stress, and somatization levels among women with well-controlled blood sugar levels compared to those who are not well-controlled. Methods: A quantitative cross-sectional study was conducted, involving 103 women who had been pregnant at least once, including 40 women diagnosed with GDM and 63 healthy pregnant women. An online questionnaire was distributed and included three parts: a socio-demographic parameters, the DASS-21 questionnaire assessing anxiety, depression, and stress, and the BSI (Brief Symptom Inventory) questionnaire assessing somatization. Results: Differences in anxiety (t=14.470, <.001), depression (t=8.17, <.001), stress (t=16.354, <.001), and somatization (t=13.679, <.001) levels between women diagnosed with GDM and healthy pregnant women were found. Women diagnosed with GDM reported higher levels of anxiety, depression, stress, and somatization compared to those without GDM. Additionally, Women with better blood sugar control, indicated by lower glycated hemoglobin (HbA1c) levels, reported lower levels of anxiety. (t (38) = -2.04, p<0.05), depression (t(38)= -2.88, p<0.01), stress (t(38)= -1.88, p<0.05), and somatization (t(38)= -1.88, p<0.05) compared to women with poorer blood sugar control. Conclusion: Pregnant women diagnosed with GDM report higher levels of negative personality traits such as anxiety, depression, stress, and somatization compared to healthy pregnant women.
Delineating and Sub-classifying Depressional Wetlands with Gradient Analysis of Littoral Vegetation Using Sentinel-2A Vege-Tation Indices
Authors: Nondlazi Basanda Xhantilomzi , Cho Moses Azong , van Deventer Heidi , Sieben Erwin
Published: July 2024

(1) Background: Depressional wetlands are highly vulnerable to changes in temperature and rainfall, affecting littoral vegetation, thus HydroGeoMorphic (HGM) wetland types. This study aimed to assess the utility of Sentinel-2A vegetation indices in enhancing delineation and sub-classify depressional HGM types. (2) Methods: We sampled 84 pairs of four vegetation indices from 10x10m plots along 14 belt transects in eight depressional wetlands in Mpumalanga, South Africa. We evaluated vegetation index differences between and within wetlands, focusing on lit-toral gradients. (3) Results: Significant differences (Bonferroni p
Deep Learning in Waste Management: A Brief Survey
Authors: Kunwar Suman , Alade Abayomi Simeon
Published: July 2024

The rapid growth of the global population is causing a significant increase in waste production, leading to serious environmental and public health challenges. To address these issues, waste management systems are incorporating advanced technologies. Machine learning and computer vision are used to predict waste patterns, optimize collection schedules, and improve sorting accuracy. Deep learning automates the sorting process, provides predictive analytics, and enhances recycling rates. Robotics, combined with AI and computer vision, improves sorting efficiency, while the Internet of Things (IoT) monitors waste levels and optimizes collection routes. Despite these benefits, challenges such as data scarcity, high computational demands, and the need for substantial infrastructure investments must be addressed. This research explores the integration of advanced technologies into waste management and evaluates their effectiveness using waste datasets. It highlights the potential to tackle environmental challenges and lay the groundwork for more intelligent waste management solutions.
Entrop-Hesitationistic-Fuzz-TOPSIS: A Novel Entropy Based Hesitant Intuitionistic Fuzzy TOPSIS for Web Service Optimization
Authors: Aazagreyir Paul , Ami-Narh James , Brown-Acquaye William Leslie
Published: July 2024

In the fast-evolving landscape of web services, success relies on optimizing efficiency, reliability, and user satisfaction. Decision-making in real-world applications demands a blend of quantitative (numerical values of quality of Service factors) and qualitative data of experts’ ratings of the quality of service factors. This paper proposes an optimization technique that integrates Hesitant and Intuitionistic Fuzzy Linguistic Terms with TOPSIS, leveraging Entropy Objective weights. There is limited research on Hesitant Intuitionistic Fuzzy Linguistic terms and the need to model fuzziness, haste and intuition in data precisely from experts rating. Thus, this article introduces an Entropy-based model tailored for web service optimization. Using the WS-DREAM dataset, quantitative data was extracted and objective weights were determined through the Entropy algorithm and qualitative evaluations from five experts, employing Hesitant Intuitionistic Fuzzy Linguistic Terms, were integrated. The process involved computing criteria weights and experts' assessment of Quality of Service factors for four services (S1, S2, S3, and S4) to form the Fuzzy Decision Matrix using modified Online output software. Applying the proposed technique to a web service optimization problem validated its effectiveness. The results indicated optimal selection of S1 as the best web service, supported by Coefficient Index values (0.785). This study introduces a novel approach, Entrop – Hesitationistic - Fuzz-TOPSIS, for web service optimization, integrating quantitative and qualitative data through an Entropy-based model. The effectiveness of the proposed technique, validated through application on the WS-DREAM dataset, underscores its potential in addressing real-world decision-making challenges. The optimal selection of S1 as the best web service suggests practical utility. The study encourages further exploration of this technique's applicability to diverse Multiple Criteria Decision Making (MCDM) problems, opening avenues for future research and application.
Novel Ionic Liquid Crystal as Electrolytic Ion Charges Carrier for Energy Storage Applications
Authors: Labeeb Ahmad , Nour Hany , El Malah Tamer , Ward Azza , Fikry Mohamed
Published: July 2024

The development of novel ionic liquid crystals for energy storage applications has gained significant attention in recent years due to their potential to develop the field of energy storage. Ionic liquid crystals represent a unique class of materials with high ionic conductivity and thermal stability, making them ideal candidates for use in advanced energy storage devices. This research aims to explore the fundamental properties, structure and liquid crystals performance of these novel materials, with the goal of advancing their practical application in next-generation energy storage technologies. By understanding the structure-function relationship of ionic liquid crystals, researchers can tailor their properties to meet specific energy storage requirements, such as high energy density, fast charging capabilities, and long cycle life. This study seeks to contribute to the growing body of knowledge in the field of energy storage by investigating the potential of novel ionic liquid crystals as efficient and sustainable energy storage solutions. The two ionic liquid crystals show mesomorphic behavior and typical zwitterion characteristics that revealed by the cyclic voltammetry techniques. These materials uploaded with lithium ions for more stability and higher ionic conductivity.