bluuebunny/crossref_metadata_2025 huggingface dataset:
Improving the effectiveness of monolith architecture to microservices migration using existing migration methods
Authors: Kornaha Yaroslav , Hubariev Oleksandr
Published: December 2024

The theme of the transition from monolithic architecture to microservice is one of the key challenges of modern software engineering. This transformation allows for greater flexibility, scalability and adaptability of systems, but requires careful planning and consideration of numerous factors that affect the efficiency of migration. This study aims to improve the algorithm for determining the effectiveness of using methods for migrating monolithic systems to microservice architecture. Migration from monolithic architecture to microservice is a complex process involving significant technical and organizational challenges. Since monolithic systems often have a complex structure and relationships between components, the transition to a microservice architecture requires careful planning and selection of effective migration methods. The lack of a unified approach to assessing the effectiveness of different migration patterns makes the transition process difficult and risky.
The article is aimed at improving the algorithm for determining the efficiency of using migration methods from monolithic architecture to microservices. To do this, we compare existing migration patterns, such as the Strangler Fig Pattern, Branch by Abstraction, Parallel Run, Decorating Collaborator and Change Data Capture, according to the criteria: implementation time, test complexity, error risk, performance degradation and efficiency. The study uses methods of comparative analysis and quantitative evaluation of the effectiveness of migration patterns. For this, criteria are applied to assess the implementation time, testing complexity, possible risks, as well as the impact on system performance. In addition, scenarios are analyzed in which each template is most effective, which allows you to determine the optimal approaches to migration depending on the specifics of the project.
The obtained results allow not only a deeper understanding of the advantages and disadvantages of different approaches to migration, but also to form recommendations for choosing the optimal pattern, depending on the specifics of the system and business needs. The scientific novelty of the study is to create an algorithm that integrates these criteria to increase the efficiency of migration processes. The results of the work can be useful for software engineers, architects and managers planning the transition to microservice architecture, providing a structured methodology for evaluating and selecting migration methods.
Dynamic model of currency exchange based on investor behavior
Authors: Miahkyi Mykhailo
Published: December 2024

In the modern financial environment, cryptocurrencies have gained significant popularity, becoming an important element of the global economy and financial markets. The dynamic development of blockchain technologies and decentralized financial instruments fosters increased interest from both private investors and institutional players. However, the high volatility of cryptocurrencies and the complexity of the mechanisms behind their price formation necessitate a detailed study of these processes.
This paper models cryptocurrency exchange operations, analyzing price formation influenced by buying, selling, and introducing new crypto coins to the market. The system simulates investor behavior with individual parameters: initial balances, risk profiles, and profit-driven trading strategies over a specified period. The model takes into account the psychological aspects of investor behavior, their reaction to changing market conditions, and the impact of external factors such as news and regulatory changes.
Special attention is paid to analyzing the impact of adding additional quantities of coins to the exchange at a reduced price during peak cryptocurrency price values. This creates conditions for activating trading operations, increasing liquidity, and affecting overall market dynamics, particularly volatility and price fluctuation trends. The study shows how such interventions can be used to stabilize the market or stimulate its further growth.
The analysis of the obtained data allows for detailed observation of changes in the cryptocurrency’s value over time, identifying patterns and trends. Using statistical and analytical methods, the impact of different investor strategies on their financial results and the overall market situation was investigated. This enables assessing how investor decisions-timing, trade volume, and market reactions-impact profits and market dynamics.
The research emphasizes the importance of a deep understanding of market mechanisms and trading psychology and can serve as a basis for developing effective trading strategies on cryptocurrency exchanges. The obtained results may be useful for traders, financial analysts, and developers of algorithmic trading systems, contributing to increased efficiency and stability of cryptocurrency markets. Moreover, the findings of the work can be applied to improve regulatory approaches and policies regarding cryptocurrencies.
The algorithm for selecting publications on a given topic considering keyword priorities
Authors: Suprun Olha , Zhurakovska Oksana
Published: December 2024

The article investigates the problems that exist in existing search engines for scientific publications. The search algorithms used in various search engines for scientific publications are described. The aim of the article is to develop a method for selecting publications on a given topic based on assessing the relevance of keyword sets. A review of the literature that was analyzed during the research is presented. Among the publications studied were materials related to the theory of set similarity, namely the use of the Jacquard coefficient and editing distance. A measure for determining the similarity of keyword sets is presented, which is based on the Jacquard coefficient taking into account the weighting coefficients of keywords. An algorithm is presented that can be used to determine the degree of similarity of publications to a user's search query based on keyword sets with weighting coefficients. The algorithm is based on the measure of similarity presented by us and the editing distance presented by us. The algorithm can be used to rank search results in search engines for scientific publications, as well as to compare the efficiency of different search engines, assess the quality of the results they return. The algorithm can also be used in book and film recommendation systems based on user preferences. The article provides the pseudocode of the algorithm. It is demonstrated on a limited data set how the measure calculated by the algorithm changes depending on the distribution of keyword weights in the user's query and the number of keywords.
Effectiveness of Hybrid Quantum-Classical and Quanvolutional Neural Networks for image classification
Authors: Trochun Yevhenii , Gordienko Yuri
Published: December 2024

The article focuses on studying the effectiveness of two different Hybrid Neural Networks (HNNs) architectures for solving real-world image classification problems. The first approach investigated in the research is a hybridization technique that allows creation of HNN based on a classical neural network by replacing a number of hidden layers of the neural network with a variational quantum circuit, which allows to reduce the complexity of the classical part of the neural network and move part of computations to a quantum device. The second approach is a hybridization technique based on utilizing quanvolutional operations for image processing as the first quantum convolutional layer of the hybrid neural network, thus building a Quanvolutional Neural Network (QNN). QNN leverages quantum phenomena to facilitate feature extraction, enabling the model to achieve higher accuracy metrics than its classical counterpart.
The effectiveness of both architectures was tested on several image classification problems. The first one is a classical image classification problem of CIFAR10 images classification, widely used as a benchmark for various imagery-related tasks. Another problem used for the effectiveness study is the problem of geospatial data analysis. The second problem represents a real-world use case where quantum computing utilization can be very fruitful in the future. For studying the effectiveness, several models were assembled: HNN with a quantum device that replaces one of the hidden layers of the neural network, QNN based on quanvolutional operation and utilizes VGG-16 architecture as a classical part of the model, and also an unmodified VGG-16 was used as a reference model. Experiments were conducted to measure the models' key efficiency metrics: maximal accuracy, complexity of a quantum part of the model and complexity of a classical part of the model.
The results of the research indicated the feasibility of both approaches for solving both proposed image classification problems. Results were analyzed to outline the advantages and disadvantages of every approach in terms of selected key metrics. Experiments showed that QNN architectures proved to be a feasible and effective solution for critical practical tasks requiring higher levels of model prediction accuracy and, simultaneously, can tolerate higher processing time and significantly increased costs due to a high number of quantum operations required. Also, the results of the experiments indicated that HNN architectures proved to be a feasible solution for time-critical practical tasks that require higher processing speed and can tolerate slightly decreased accuracy of model predictions.
Assessing Long-term Services and Supports Recipients’ Quality-of-Life and the Impact on Caregivers in Chengdu, China
Authors: Lin Sen , Frick Kevin D , Xiong Yao , Sun Xueying , Li Yu , Dou Xiaolu
Published: December 2024

This study investigates the quality of life (QoL) of long-term services and supports (LTSS) recipients and their caregivers in Chengdu, following the implementation of China's long-term care insurance (LTCI) system. The research utilized three ICEpop CAPability (ICECAP) instruments to evaluate the QoL of both groups and explored the association between the caregivers' QoL and that of the recipients. A total of 464 LTSS recipients and their caregivers were surveyed, yielding a response rate of 92.8%. Key findings indicated that physical and psychological health were the strongest predictors of higher QoL for both male and female LTSS recipients. Female recipients receiving home care experienced lower QoL, while for males, living with family or supporters was a significant predictor of QoL. Caregivers' QoL was associated with higher salary, lower education, and better health status, and it was also found to be positively linked to the QoL of LTSS recipients. The study concludes with recommendations for policymakers to consider gender-specific LTSS delivery and to increase salaries for caregivers as a means to improve QoL.
“Will I get it right?”: reducing test anxiety through resonance frequency breathing
Authors: Boudreau Cameron , Langlais Michael
Published: December 2024

The goal of this study is to test if resonance frequency breathing exercises will minimize test anxiety. This study used an experimental within-person design where participants completed a resonance breathing exercise after completing the first exam in an undergraduate course of their choosing for seven consecutive days before the second exam in the same course. In total, 316 participants completed the pre-test and 279 completed the post-test. Test anxiety decreased and test performance improved as a result of the resonance breathing exercises, even when controlling for the delivery of the exam, the course, and the seating position used for the breathing exercises. Qualitative results revealed that 88.5% of participants reported utility in the resonance breathing activity, with many reporting themes associated with calmness and increased focus. Our results support the physiological benefits of resonance breathing in collegiate settings regarding test anxiety.
On the “Assembly Theory and its Relationship with Computational Complexity”
Authors: Łukaszyk Szymon
Published: December 2024

The study provides an alternative definition of the assembly space as an acyclic, 2-in-regular digraph of strings provided with an edge labeling map that preserves the commutativity of an assembly step but defines the order of concatenation of strings in this step. Remarkably, the uniqueness of each vertex is the sufficient criterion to establish if an assembly step is allowed and to introduce the notion of an assembly pool: unit-length strings cannot be assembled from shorter strings and, hence, are inaccessible, forming the initial assembly pool, and strings present in the assembly space can not be assembled again, possibly using different pathways, as they would not be unique. What is allowed is the evolution of assembly pathways to make them shorter. We also comment on certain results of [10.48550/ARXIV.2406.12176], showing that the Assembly Steps Problem, not the Assembly Index Problem, has been proved in the referenced study to be NP-complete.
Blockchain-Powered Sports Facilities Help Athletes Perform Better. A Comparative Analysis of Team Sports
Authors: Bucea-Manea-Țoniș Rocsana
Published: December 2024

Blockchain technology has the potential to revolutionize the sports industry by enhancing athlete data management, automating smart contracts, improving ticketing security, and fostering fan engagement through innovative loyalty programs. Though more creative uses are starting to emerge, general adoption is still in its early stages, despite its promise. This study explores the impact of blockchain applications on team sports performance in Romania, focusing on their perceived benefits and applicability. A survey, validated by an ethics commission, was conducted among sports professionals to assess these impacts of technology on performance. For data analysis we have done a Structural Equation Modeling (SEM) with Smart PLS and a cluster analysis in SPSS 22.0. Results indicate that blockchain benefits significantly influence the adoption of blockchain applications, which, in turn, positively impact athletes’ performance at national and European levels. This study identifies key factors contributing to the implementation success of blockchain apps in sports and offers insights into the technology's broader potential for fostering transparency, efficiency, and competitive growth in the sports industry. This research validated the hypothesis that in Romania the implementation of Blockchain Apps in sport fosters trust in blockchain benefits and improves the national and European athlete performance.
Investigating Experts’ Science Teachers’ Perspectives on the Integration of STEM Activities into Science Instruction
Authors: Alfarraj Yousef , Alzahrani Roba
Published: December 2024

The ambiguity surrounding the integration of engineering and technology into science and mathematics instruction poses significant challenges for educators, primarily due to varying interpretations of how to efficiently integrate these disciplines within the curriculum. This phenomenological study examines the perspectives of eight expert science educators—selected based on specific criteria—regarding the incorporation of STEM activities into their teaching practices through semi-structured interviews. Findings indicate that these educators emphasize the interdisciplinary nature of STEM education, particularly the integration of technology and engineering within science and mathematics instruction. Participants define technology as the tools and methods used to apply scientific concepts, while engineering is considered the application of these principles to design systems that address real-world challenges through authentic learning. The study emphasizes the importance of aligning STEM activities with established standards to enhance coherence and consistency, revealing benefits such as increased student engagement and the development of critical thinking skills. However, challenges—including resource limitations and insufficient content knowledge among educators—were also recognized. Ultimately, the study advocates for transformative practices to improve the quality of STEM education, emphasizing the need for evidence-based methodologies in curriculum development, such as teacher preparation. In this context, the success of an educational system is shaped by the quality of its teachers.
Adsorption and Recovery Studies of Cadmium and Lead Ions Using Biowaste Adsorbents from Aqueous Solution
Authors: Feng Liang , Wang Enju
Published: December 2024

The use of low-cost biowaste adsorbents for the removal of toxic metal ions from aqueous solutions offers significant environmental benefits and demonstrates strong potential. This research studied the adsorption and recovery of Cd2+ and Pb2+ ions in batch and column modes with luffa peels and chamomile flowers. Metal ion concentrations were determined with ICP-OES. The biosorbents were treated with either acid or base. FTIR characterization indicated that surface carboxylic acid groups played a role in the adsorption process. L-type isotherms were obtained for Pb2+, fitting both the Langmuir and Freundlich models, with maximum adsorption capacities of 34.0 mg/g for luffa peels and 49.5 mg/g for chamomile flowers. Adsorption isotherm for Cd2+fitted better with the Freundlich model with smaller adsorption capacity than Pb2+. Base treated sorbents have higher adsorption capacity. The adsorption kinetic for both ions followed a pseudo-second order chemosorption model. Fixed-bed column dynamic adsorption with luffa peels obtained a Thomas dynamic adsorption capacity of 32.9 mg/g for Pb2+ and 25.8 mg/g for Cd2+. The recovery efficiency remained above 87% over three adsorption-regeneration cycles.
Fault Detection of Permanent Magnet Synchronous Machines: An Overview
Authors: Li Henghui , Zhu Z.Q. , Azar Ziad , Clark Richard , Wu Zhanyuan
Published: December 2024

Nowadays, as the application of permanent magnet synchronous machines (PMSMs) and drive systems becomes popular, the reliability issue of PMSMs gains more and more attention. To improve the reliability of PMSMs, fault detection is one of the practical techniques, which enables early interference and mitigation to the faults, and subsequently reduce the impact of the faults. In this paper, the state-of-art fault detection methods of PMSMs are systematically reviewed. Three typical faults, i.e., the inter-turn short-circuit fault, the PM partial demagnetization fault, and the eccentricity fault are included. The existing methods are firstly classified into signal-, model-, and data-based methods, while the focus of this paper is laid on the signal sources and the signatures utilized in these methods. Based on this perspective, this paper intends to provide a new insight into the inherent commonalities and differences among these detection methods, and thus, inspire further innovation. Furthermore, comparison is conducted between methods based on different signatures. Finally, some issues in existing methods are discussed, and the future work is highlighted.
Response of Healthcare Professionals in the County of Istria to the National Prevention Programme for theb Early Detection of Breast Cancer
Authors: Jovanović Željko , Rojnić Olga
Published: December 2024

INTRODUCTION AND OBJECTIVE OF THE STUDY: National preventive screening programmes, such as mammography for women aged 50-69, are key to detecting malignancies at the earliest stage and increasing the cure rate. Although these programmes have been in place for many years, uptake is still low due to various factors such as lack of information and fear of diagnosis. This research focuses on understanding the response of healthcare professionals to the programmes they promote and the reasons for their possible non-response.
PARTICIPANTS AND METHODS: The quantitative cross-sectional study involved 102 people aged 50 to 72 years employed in public healthcare institutions in Istria County. It was conducted using a 13-question questionnaire that included sociodemographic information and personal history of breast cancer. The questionnaire, which was created using a Google form, was sent by e-mail and took about 10 minutes to complete. Data were processed using Microsoft Excel and Statistics 14.0.0.15, respecting ethical principles and respondent privacy.
RESULTS: The study showed a high response rate of 92.5% of healthcare workers who had received an invitation for mammography screening. The response rate was significantly higher than the average response rate of 60% in the general population of women in Croatia. The main reasons for non-response are practical reasons such as acute illness, lack of information or working hours. Long-term health education and promotion, better information and advertising and more flexible working hours were mentioned as suggestions for increasing the response rate.
CONCLUSION: Healthcare workers in Istria County have a high response rate to the National Breast Cancer Screening Programme, and reasons for non-participation include practical reasons, lack of information and anxiety about screening. These findings can be used to improve the programme's response rate by addressing these issues and providing more information and support to those who are invited to participate.
Analysis of the Beliefs of Psychosocial and Socio-Educational Intervention Professionals in Master's Degree Training About Critical Competence
Authors: Garcia-Moro Francisco Jose , Gomez-Baya Diego
Published: December 2024

Critical thinking is a skill that is of great importance in our current and future society. This value is beyond all theoretical doubt although it does not have its practical realization to the same extent, especially in terms of coordinated and evidence-based approaches. It seems that the principle that life is made by living also applies to critical thinking and this is a problem. But in addition to actions based on evidence, there is another element that also has great relevance, such as the ethical foundation that must permeate the entire critical process, making what to criticize, for what, why, how and when, elements that should not be left to improvisation or what is traditionally done. The objective of this research is to describe the ethical connotations that come together in the critical process. To this end, we focus on a group case study of undergraduate and graduate students of psychosocial and socio-educational studies in Spain, collecting information with instruments built ad hoc. The results show little practical awareness of the weight of ethics in critical decisions, producing a change of orientation when making decisions when the focus is forced on the two dimensions and, above all, on the ethical aspect.
Optimizing Image Watermarking with Dual-Tree Complex Wavelet Transform and Particle Swarm Intelligence for Secure and High-Quality Protection
Authors: Bsoul Abed Al Raoof , Bani Ismail Alaa
Published: December 2024

Watermarking is a technique used to address issues related to the widespread use of the internet, such as copyright protection, tamper localization, and authentication. However, most watermarking approaches negatively affect the quality of the original image. In this research, we propose an optimized image watermarking approach that utilizes the Dual Tree Complex Wavelet Transform and Particle Swarm Optimization Algorithm. Our approach focuses on maintaining the highest possible quality of the watermarked image by minimizing any noticeable changes. During the embedding phase, we break down the original image using a technique called Dual-Tree Complex Wavelet Transform (DTCWT) and then use Particle Swarm Optimization (PSO) to choose specific coefficients. We embed the bits of a binary logo into the least significant bits of these selected coefficients, creating the watermarked image. To extract the watermark, we reverse the embedding process by first decomposing both versions of the input image using DTCWT and extracting the same coefficients to retrieve back those corresponding bits (watermark). In our experiments, we use a common dataset from watermarking research to demonstrate the functionality against various watermarked copies and (PSNR) Peak Signal to Noise Ratio and Normalized Cross Correlation (NCC) metrics. The PSNR is a measure of how well the watermarked image maintains its original quality, and the NCC reflects how accurately the watermark can be extracted. Our method gives a mean PSNR and NCC of 80.50% and 92.51%, respectively.
Machine Learning in the Macromolecular Sciences: From Methods to Applications. A Review
Authors: Kröger Martin
Published: December 2024

Machine learning (ML) and artificial intelligence are revolutionizing macromolecular and polymeric sciences. This review comprehensively explores ML methodologies, including supervised and unsupervised learning strategies, reinforcement and deep learning, generative and coarse-grained models, and their applications in predicting material properties and behaviors, optimizing synthesis, processes, and advancing polymer design and computational strategies. We focus on foundational studies, recent advancements, and future directions.
Third-Order Optical Nonlinearity of Hexagonal Boron Nitride Atomic Layer
Authors: Neupane Tikaram , Poudyal Uma , Tabibi Bagher , Seo Felix Jaetae
Published: December 2024

The third-order optical nonlinearity of hexagonal boron nitride (hBN) nanosheet was characterized by z-scan, I-scan, and spatial self-phase modulation (SSPM). The hBN nanosheets exhibited a positive nonlinear absorption or reverse saturable absorption (RSA) and its coefficient was estimated to be ~ 7.1 x 10-10 m/W via the open z-scan. The I-scan technique further verified the polarity of nonlinear absorption and the prospective application for laser safety (optical limiting) of the optical sensors from high-power lasers. It is found that the given hBN atomic layers could absorb up to ~22 % of incoming laser beam. In addition, the absence of a nonlinear refraction effect was observed using the closed z-scan and SSPM for a given excitation peak intensity. It implies that the free carrier-induced nonlinear absorption that diminishes the NLR signal via free-carrier dispersion. Acknowledgment: This work at HU is supported by ARO W911NF-15-1-0535 and NASA NNX15AQ03A.
Public Opinion Evolution Based on the Two-Dimensional Theory of Emotion and Top2Vec-RoBERTa
Authors: Wang Shaowen , Liu Qingyang , Hu Yanrong , Liu Hongjiu
Published: December 2024

In today’s information age, dominated by social media, online platforms have become crucial venues for information dissemination. While the free flow of information promotes public participation, it also introduces certain challenges. Therefore, analyzing the evolution of public opinion and extracting public sentiment holds significant practical value for managing online public sentiment. This study takes the Zibo Barbecue incident as a case study, utilizing the two-dimensional theory of emotion and Top2Vec for thematic analysis of public opinion comments. By combining sentiment dictionary methods with the RoBERTa model, we conducted a sentiment polarity analysis of public opinion comments. The results show that the RoBERTa model achieved an accuracy of 98.46% on the test set. The proposed method effectively uncovers public sentiment biases and the influencing factors on public emotions during the evolution of public opinion events, providing a more comprehensive understanding of the emotional dynamics throughout the development of public sentiment. This deeper insight aids in addressing issues related to public opinion more effectively.
Generation of a H9N2 Avian Influenza Virus Whose Ha Proteins Fused C3d-P29 and Its Application in Vaccine Development
Authors: Pan Xue , Zhou Fan , Shi Xiaona , Liu Qinfang , Yan Dawei , Teng Qiaoyang , Yuan Chunxiu , Xu Bangfeng , Zhang Zhifei , Yan Minghao , Li Zejun
Published: December 2024

Maternal-derived antibodies (MDAs) interfere with immune responses, leading to the failure of H9N2 avian influenza vaccination in poultry. So far, none of commercial H9N2 avian influenza vaccines used in poultry can overcome MDAs interference. To develop a vaccine overcoming MDAs interference, different copies of minimum-binding domain (P29) of complement protein C3d were inserted between the signal peptide and the head domain of hemagglutinin (HA) of a H9N2 avian influenza virus (A/Chicken/Shanghai/H514/2017, named H514). The HA proteins containing P29 stimulated stronger typeⅠinterfere than pure HA proteins in vitro. The modified viruses with HA containing one copy of P29 (rH514-P29.1) and two copies of P29.2 (rH514-P29.2) were successfully rescued by using reverse genetics. The inactivated H9N2 vaccines developed with rH514-P29.1 or rH514-P29.2 induced higher and faster adaptive immune responses than the vaccine developed with rH514 in chickens without MDAs. Importantly, in the chickens with MDAs, the inactivated rH514-P29.2 vaccine induced significantly higher HI titers than the vaccine without P29, and reduced viral shedding after challenged with H514, which suggests that vaccine antigens fused two copies of P29 can decrease the interference of MDAs to immunity in chickens. Overall, our results provide a new strategy to overcome MDAs interference.
Helminth Seropositivity Inversely Correlated with Th1 and Th17 Cytokines and Severe COVID-19
Authors: Fogang Brice A.N. , Meyer Julia , Debrah Linda B. , Owusu Michael , Agyei George , Adu-Mensah Derrick , Boateng John , Osei-Mensah Jubin , Klarmann-Schulz Ute , Horn Sacha , Kroidl Inge , Debrah Alexander Y , Hoerauf Achim , Adjobimey Tomabu
Published: December 2024

The COVID-19 pandemic has significantly impacted global health. However, Africa has reported relatively low numbers of cases and fatalities. Although the pandemic has largely receded, the reasons for its milder course on the African continent have not yet been fully clarified. This study explored the hypothesis that helminth co-infections may have contributed to these observations. A retrospective cohort study was conducted using 104 archived plasma samples collected during the third wave of the pandemic in the Ashanti Region of Ghana. ELISA and Luminex assays were used to measure SARS-CoV-2-specific IgA and IgG, neutralizing antibodies, and helminth-specific IgG levels. The results indicated that the highest cumulative seroprevalence of helminths (61.5%) was observed in asymptomatic SARS-CoV-2-infected individuals. In comparison, mild and moderate COVID-19 patients had helminth seropositivity rates of 43.8% and 34.5%, respectively, which were 1.4 and 1.8 times lower than those of the asymptomatic group, respectively. Notably, the two severe COVID-19 cases investigated were seronegative for all three helminths tested. Strikingly, co-exposure resulted in lower SARS-CoV-2-specific IgA/IgG expression and reduced neutralization potential. However, in the plasma of individuals co-seropositive for helminths and SARS-CoV-2, a significantly higher expression of Th2 cytokines and IL-10 over Th1 was observed compared to those who were SARS-CoV-2 positive alone. These data suggest that co-exposure to helminths could mitigate severe COVID-19 outcomes by reducing the Th1 and Th17 responses. Our study highlights the potential protective role of helminth co-infection against severe COVID-19, suggesting that helminth-induced immune modulation may improve clinical outcomes. These findings provide valuable insights for public health policies in helminth-endemic regions and underscore the importance of considering helminth co-infections in managing viral infections.
Adaptive Optics for Aberration Control in Einstein Telescope
Authors: Cifaldi Maria , Taranto Claudia , Aiello Lorenzo , Lumaca Diana
Published: December 2024

Optical aberrations represent a critical issue for gravitational wave interferometers, as they impact the stability and controllability of the experiment. In the next generation of detectors, the circulating power in the cavity arms is expected to increase by up to a factor of 20 compared to current ones. This significant increase makes the mitigation of power-dependent optical aberrations extremely challenging. In this paper, we describe the problem of absorption in the optics and its role in generating some of the most important wavefront distortions, along with the present compensation strategy. To meet the new stringent requirements, new technologies must be designed, and existing ones upgraded. We present a review of the strategies and concepts in the field of aberration control in gravitational wave detectors and discuss the challenges for future detectors like the high-power operation of the Einstein Telescope.
Machine Learning Discoveries of HVCN1-X Synergy in ETC-1922159 Treated Colorectal Cancer Cells
Authors: Sinha Shriprakash
Published: December 2024

HVCN1 is the gene that encodes for voltage gated proton channel. It works along with other genes/proteins, however, many of the synergistic combinations are not known. In colorectal cancer (CRC) cells treated with ETC-1922159, HVCN1 was found to be dow regulated along with other genes. A recently developed search engine ranked combinations of hydrogen voltage gated channel HVCN1-X (X, a particular gene/protein) at 2nd order level after drug administration. These rankings reveal which HVCN1-X combinations might be working synergistically in CRC. In this research work, I cover combinations of HVCN1 with NADPH oxidase 1 (NOX1), ecto-NOX disulfide-thiol exchanger 2 (ENOX2), mitogen-activated protein kinase (MAPK), matrix metallopep- tidase (MMP), tumor protein p53 (TP53), marker of proliferation Ki-67 (MKI67), glu- tathione s-transferases (GST) and phospholipase C (PLC) family.
A Comparative Analysis of Multi-Criteria Decision-Making Methods and Normalization Techniques in Holistic Sustainability Assessment for Engineering Applications
Authors: Malefaki Sonia , Markatos Dionysios , Filippatos Angelos , Pantelakis Spiros
Published: December 2024

The sustainability evaluation of engineering processes and structures is a multifaceted challenge, requiring the integration of diverse and often conflicting criteria. A comprehensive Sustainability Index (SI) has been developed to address this complexity, utilizing Multi-Criteria Decision-Making (MCDM), to provide balanced and effective solutions. The SI incorporates key metrics across performance, environmental impact, economic factors, social dimensions, and circular economy principles. Selecting the most appropriate MCDM tool for problems involving multiple criteria is a pivotal challenge in holistic sustainability assessments. Among the numerous methods documented in the literature, the Weighted Sum Method, Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), modified TOPSIS, COPRAS and VIKOR are frequently employed for ranking alternatives. The calculation of SI is based on the normalized data, with the selection of both the MCDM tool and the normalization method playing a crucial role in determining the robustness and reliability of the results. This study investigates the impact of various MCDM tools on the decision-making process and examines how prominent normalization methods, including min-max normalization, vector normalization, z-score normalization, robust normalization and sum normalization, affect the final outcomes. Using a dataset from the aviation sector, a typical aircraft component serves as a case study for a holistic sustainability assessment. A detailed sensitivity analysis investigates the influence of MCDM tools, normalization methods, and weight variations on the holistic SI. This study highlights the importance of selecting appropriate MCDM tools and normalization methods to enhance the interpretability, robustness, reliability, and consistency of sustainability assessments in engineering applications.
Analysis on the Epidemiological Characteristics of Breakthrough Varicella Cases and Incremental Effectiveness of 2-Dose Varicella Vaccine in China
Authors: Lin Ming zhu , Yang Tian , Deng Pengfei , Yang Lai bao , Xue Cao yi
Published: December 2024

The 2-dose varicella vaccination strategy has been implemented in Shanghai, China since 2018. This study aims to analyze the epidemiological characteristics of breakthrough varicella cases and to evaluate the incremental effectiveness of the 2-dose varicella vaccination among Chinese children. We enrolled children born from 2015 to 2019 who experienced varicella breakthrough infections following the administration of the receiving varicella vaccine (VarV) that occurred on or before December 31, 2023 in Pudong New Area, Shanghai. Demographic information and data regarding varicella vaccination were collected by Shanghai Immunization Information System, while information on varicella infections was obtained from China Information System for Disease Control and Prevention. The incremental vaccine effectiveness (VE) for varicella was defined as (1-relative risk (RR)) *100%, where RRs were calculated based on the rate of breakthrough infections. The overall rate of breakthrough varicella infections was found to be 0.25%, corresponding to 1,182 cases. Specifically, the rates of breakthrough varicella infections for individuals who received 1-dose and 2-dose VarV were 0.39% (977 cases) and 0.10% (205 cases), respectively. The average ages of onset for these infections were 2.13±0.99 years and 5.52±1.18 years, respectively. Furthermore, the breakthrough varicella infection rate among individuals born between 2015 and 2019 exhibited a decline, decreasing from 0.52% to 0.26% for those who received 1-dose of VarV, and from 0.23% to 0.01% for those who received 2-dose. The incremental VE for the two-dose regimen was recorded at 56% and 57% for individuals born in 2015 and 2016, respectively, which was significantly lower than the VE of 94% and 95% observed for those born in 2018 and 2019. The incidence of breakthrough varicella among children in Pudong, Shanghai, has shown an upward trend over time following the implementation of Varicella vaccination. Furthermore, the 2-dose VarV vaccination strategy significantly reduced breakthrough incidence, which should be recommended to prevent the varicella disease among children in other provinces of China.
Evolving Landscape of Paediatric Pneumococcal Meningitis in Argentina (2013-2023)
Authors: Zintgraff Jonathan , Gagetti Paula , Sanchez Eluchans Nahuel , Marchetti Paulina , Moscoloni Maria Alicia , Lara Claudia Sara , Corso Alejandra
Published: December 2024

The introduction of pneumococcal conjugate vaccination (PCV) into the Argentinian Childhood National Immunization Program in 2012 marked a significant milestone in public health. Our study aims to assess the impact of this intervention on pneumococcal meningitis cases, serotype distribution, and antimicrobial resistance among paediatric populations from 2013 to 2023.
Specifically, we compared the early post-PCV period (2013–2014) to the late post-PCV period (2022–2023).
A total of 333 pneumococcal isolates were analyzed between 2013 and 2023. Gold standard pneumococcal serotyping was performed to identify the serotypes associated with infection in children < 6 years in Argentina and agar dilution method was carried out to determine their profiles to antimicrobial agent.
Our findings underscore the importance of PCV implementation, revealing notable shifts in pneumococcal epidemiology over the study period: proportion of serotypes 1 (6.7% to 0.0%), 5 (5.6% to 0.0%) and 14 (7.8% to 1.8%) decreased, whereas proportion of serotypes 10A (3.3% to 10.7%), 15B/C (2.2% to 10.7%) and 24B (0.0% to 8.9%) increased The top five rated serotypes in the 2022-2023 period were serogroup 24 (21.4%), 10A (10.7%), 15B/C (10.7%), 23B (7.1%) and 12F (5.4%). Regarding antimicrobial resistance, we found that a total of 115/311 isolates (37%) were non suceptible to penicillin, 2.9% to cefotaxime. Twenty five percent of the isolates were microbial drug resistant, with resistance to penicillin, erythromycin, tetracycline/doxicycline and/or cotrimoxazol. Among PCV13 serotypes, 19A remained the most commonly associated with MDR. Non-PCV13 serotypes, particularly 24F, 24A, and 24B, were prevalent among MDR isolates.
The observed trends advocate for the continued expansion of pneumococcal vaccination policies, including consideration for vaccines offering enhanced indirect protection, thereby extending benefits beyond the paediatric population to encompass adults as well. Such strategies are pivotal in reducing the burden of pneumococcal disease and safeguarding public health.
Conventional and Innovative Drying/Roasting Technologies: Effect on Bioactive and Sensorial Profiles in Nuts and Nut-Based Products
Authors: Pedron Giacomo , Jaouhari Yassine , Bordiga Matteo
Published: December 2024

Nuts are widely recognized for their exceptional nutritional value, being rich in bioactive compounds such as polyphenols, mono- and polyunsaturated fatty acids, dietary fiber, and essential minerals. Roasting, a common processing technique, enhances the sensory attributes of nuts, including flavor, aroma, and texture, while influencing their nutritional and chemical profiles. This review focuses on the effects of roasting technologies specifically on pistachios, hazelnuts, and almonds. The Maillard reaction, triggered during roasting, is pivotal in developing the characteristic flavors of roasted nuts but can also lead to the production of acrylamide under certain conditions. Understanding the balance between enhancing sensory quality and retaining nutritional properties is essential for optimizing roasting conditions. Innovative technologies offer sustainable, efficient alternatives to traditional methods. By emphasizing these three major nut varieties, this review provides valuable insights into the changes occurring before and after roasting, highlighting strategies to balance sensory quality and nutritional preservation. Further research is essential to refine these techniques, enabling the production of high-quality nuts that deliver superior health benefits while meeting consumer expectations.
Real-Life Benefit and Costs of First Line Pembroli-zumab for Advanced NSCLC—A Propensity-Score Matched Case-Control Study
Authors: Pirklbauer Vanessa , Friedrich Lea , Wass Romana , Horner Andreas , Kaiser Bernhard , Lamprecht Bernd , Lang David
Published: December 2024

Background: Immune checkpoint inhibitor (ICI) therapy using Pembrolizumab alone or in combina-tion with chemotherapy (CHT) is a widely used first-line standard for advanced NSCLC without ac-tionable driver mutations. However, a considerable fraction of patients does not respond to ICI, and associated costs are significant. We aimed to investigate the real-life benefit and costs of first line Pembrolizumab as compared to a matched historical cohort treated with first-line CHT in the pre-ICI era. Methods: Ninety-three subsequent patients having received first-line pembrolizumab as mono-therapy (n=17) or together with platinum-based doublet CHT (n=76) between 2017 and 2021 were retrospectively identified. Using propensity-score matching for age, sex, Eastern Co-operative of On-cology Group (ECOG) performance status and histological subtype, the ICI-treated cohort was com-pared to a historical NSCLC cohort treated with first-line platinum-based doublet CHT between 2011 and 2014, whereas patients who had received ICI in later therapy lines were excluded. Progres-sion-free (PFS) and overall survival (OS) were calculated using the Kaplan-Meier method; the log-rank test was used for statistical comparison between the cohorts. Therapy costs were calculated based on the respective average drug prizes between 2017 and 2019 for both treatment groups. Results: Both cohorts did not significantly differ in terms of matching criteria. Among the patients treated with first line pembrolizumab, median PFS was 6 months (M) (95% confidence interval (CI) 4-9) and signifi-cantly longer (p<0.001) than in the historical CHT cohort (4M; 95% CI 3-5). Similarly, median OS was significantly longer in the ICI group (14M (95% CI 8-19) vs. 8M (95% CI 7-10); p=0.01). Total therapy costs were €3,635,572 in the ICI and €867,000 in the CHT cohort, respectively, average costs per pa-tient were €39,092 and €8,179. Incremental cost-effectiveness ratio (ICER) per month of median OS gained was €5,152. Conclusion: Patients with advanced NSCLC treated with first-line pembroli-zumab had significantly longer PFS and OS as compared to historical fist-line CHT patients. Howev-er, this benefit was associated with considerably higher treatment costs.
Exploring Advancements in Bio-Based Composites for Thermal Insulation: A Systematic Review
Authors: Pawłosik Daria , Cebrat Krzysztof , Brzezicki Marcin
Published: December 2024

The increasing urgency to reduce the environmental impact of human activities has underscored the critical role of bio-materials in sustainable architecture and construction. This systematic review consolidates and critically analyzes recent advancements in bio-composite materials, focusing on their thermal insulation capabilities and broader applications within the built environment. Data from studies published since the start of 2024 were meticulously selected using stringent inclusion criteria guided by the PRISMA protocol. A meta-analysis conducted via VOSviewer software (version 1.6.20) illustrates keyword co-occurrence in titles and abstracts, highlighting emerging trends in bio-composite research. This review compiles and categorizes information on 50 bio-composite materials with confirmed properties of biodegradability or recyclability, systematically assessing their morphology, internal structure, and thermal characteristics, which are central to their insulation performance. While the primary focus of this review is on the thermal insulation properties of bio-composite materials, the mechanical properties are also included as supplementary data, reflecting the incidental availability of this information in the reviewed studies. The findings emphasize that thermal insulation applications dominate the usage of these materials (44%), followed by sub-structural roles (40%). A comparative analysis highlights the significant bio-composite thermal conductivity (λ) advancements, po-sitioning them as viable alternatives for standard building materials. A detailed matrix is presented to showcase the roles of polymer and ceramic matrices, further contextualizing their potential in construction, particularly for insulation applications. The study identifies critical challenges, such as scalability and du-rability. It proposes future research directions to enhance bio-materials integration in sustainable building practices, prioritising advancing technologies.
Existence Results and Gap Functions for Nonsmooth Weak Vector Variational-Hemivariational Inequality Problems on Hadamard Manifolds
Authors: Upadhyay Balendu Bhooshan , Sain Shivani , Mishra Priyanka , Stancu-Minasian Ioan
Published: December 2024

In this paper, we consider a class of nonsmooth weak vector variational-hemivariational inequality problems (abbreviated as, WVVHVIP) in the framework of Hadamard manifolds. By employing an analogous to the KKM lemma, we establish the existence of a solution for WVVHVIP without utilizing any monotonicity assumptions. Moreover, a uniqueness result for the solution of WVVHVIP is established by using generalized geodesic strong monotonicity assumptions. We formulate Auslender, regularized, and Moreau-Yosida type regularized gap functions for WVVHVIP to establish necessary and sufficient conditions for the existence of a solution to WVVHVIP. In addition to this, by employing regularized gap functions, we derive the global error bounds for the solution of WVVHVIP under the generalized geodesic strong monotonicity assumptions. Several non-trivial examples are furnished in the Hadamard manifold setting to illustrate the significance of the established results. To the best of our knowledge, this is the first time that the existence results, gap functions, and global error bounds for WVVHVIP have been investigated in the framework of Hadamard manifolds via Clarke subdifferentials.