bluuebunny/crossref_metadata_2025 huggingface dataset:
The Impact of Dealiasing Biases on Bird and Insect Data Products of C-Band Weather Radars and Consequences for Aeroecological Applications
Authors: Weisshaupt Nadja , Harnist Bent , Koistinen Jarmo
Published: January 2025

(1) The aliasing of radial velocities from weather radars is a known challenge in meteorology. It may also occur during bird migration if the unambiguous velocity threshold is below the birds’ ground speed. High variability in birds’ radial velocities and high flight speeds lead to multiple aliasing (folding) and challenge meteorological dealiasing approaches. Unfolded radial velocities are essential for calculating flight directions and speed and derived migration traffic rates for aeroecological applications. (2) We study the occurrence of aliasing in measurements of different pulse repetition frequencies (PRF) in C-band weather radars in bird and insect cases and test the efficiency of a dealiasing algorithm widely used in biological weather radar software. We use dual-PRF measurements as a reference to avoid the folding of radial velocities in quantitative and qualitative bird migration outputs. (3) The dealiasing algorithm performed poorly in single-PRF measurements during bird migration, though not in insect and precipitation cases. In contrast, dual-PRF velocities yielded proper flight speeds, flight directions and migration traffic rates. (4) The study unveils severe biases in aeroecological analyses of C-band weather radars from imperfectly dealiased single-PRF radial velocities. Dual-PRF measurements with appropriate dealiasing postprocessing offer a valid alternative to single PRF and should be preferred whenever available.
Analysis of Metro Users’ Perception Towards Attributes Related to Bicycle–Metro Integration: RIDIT and TOPSIS Model Approach
Authors: Fahim Ashraf Uddin , Minami Masaaki , Yang Daqian , Kawashita Toru
Published: January 2025

This study investigates the viability of incorporating bicycles into the Dhaka Metro system, a groundbreaking urban transit project for Bangladesh. As Dhaka’s inaugural metro rail network, the system signifies a substantial advancement in addressing urban congestion and enhancing transportation alternatives in one of the world’s most densely populated cities. The current design of the metro fails to accommodate bicycles, hindering efficient first- and last-mile connectivity. The investigation utilized data from 382 fully completed questionnaires, obtained through purposive sampling, about metro–cycle integration in Dhaka. The research employed RIDIT and TOPSIS analyses to rank the characteristics deemed most essential for bicycle–metro integration according to user opinions. Research indicates that secure bicycle parking, multi-modal ticketing, route comfort, and safety measures are the foremost objectives for commuters. The high emphasis on secure parking indicates the need for safe and accessible storage options that would make cycling a viable mode for reaching metro stations. A multi-modal ticketing system further enhances convenience, providing seamless transitions between transit modes. Journey comfort and the need to mitigate risks posed by motorized vehicles underscore the importance of safe and user-friendly commuting environments. While features like road and station design were ranked lower in priority, the study emphasizes that a well-integrated bicycle infrastructure is essential to ensure the metro system’s success. With these improvements, Dhaka’s metro system can meet the growing demands for sustainable and inclusive urban mobility, setting a precedent for future infrastructure projects in Bangladesh.
Application of Self-Organizing Maps to Explore the Interactions of Microorganisms with Soil Properties in Fruit Crops Under Different Management and Pedo-Climatic Conditions
Authors: Antonucci Francesca , Violino Simona , Canfora Loredana , Tartanus Małgorzata , Furmanczyk Ewa M. , Turci Sara , Tommasini Maria G. , Cvelbar Weber Nika , Razinger Jaka , Ourry Morgane , Bickel Samuel , Passey Thomas A. J. , Bohr Anne , Maisel Heinrich , Pugliese Massimo , Vitali Francesco , Mocali Stefano , Pallottino Federico , Figorilli Simone , Costa Corrado , Malusà Eligio
Published: January 2025

Background: Self-organizing maps (SOMs) are a class of neural network algorithms able to visually describe a high-dimensional dataset onto a two-dimensional grid. SOMs were explored to classify soils based on an array of physical, chemical, and biological parameters. Methods: The SOM analysis was performed considering soil physical, chemical, and microbial data gathered from an array of apple orchards and strawberry plantations managed by organic or conventional methods and located in different European climatic zones. Results: The SOM analysis considering the “climatic zone” categorical variables was able to discriminate the samples from the three zones for both crops. The zones were associated with different soil textures and chemical characteristics, and for both crops, the Continental zone was associated with microbial parameters—including biodiversity indices derived from the NGS data analysis. However, the SOM analysis based on the “management method” categorical variables was not able to discriminate the soils between organic and integrated management. Conclusions: This study allowed for the discrimination of soils of medium- and long-term fruit crops based on their pedo-climatic characteristics and associating these characteristics to some indicators of the soil biome, pointing to the possibility of better understanding the interactions among diverse variables, which could support unraveling the intricate web of relationships that define soil quality.
Assessment of Reliability Allocation Methods for Electronic Systems: A Systematic and Bibliometric Analysis
Authors: Patil Rajkumar B. , Kyeong San , Pecht Michael , Gujar Rahul A. , Mane Sandip
Published: January 2025

Reliability allocation is the process of assigning reliability targets to sub-systems within a system to meet the overall reliability requirements. However, many traditional reliability allocation methods rely on assumptions that are often unrealistic, leading to misleading, unachievable, and costly outcomes. This paper provides a historical review of reliability allocation methods, focusing on the Weighing Factor Method (WFM), with a detailed analysis of its main findings, assumptions, and limitations. Additionally, the review covers methods for reliability optimization, redundancy optimization, and multi-state system optimization, highlighting their strengths and shortcomings. A case study is presented to demonstrate how the assumption of an exponential distribution impacts the reliability allocation process, showing the limitations it imposes on practical implementations. Furthermore, a bibliometric analysis is conducted to assess publication trends in the field of reliability allocation. Through examples, particularly in the context of electronic systems using commercial off-the-shelf (COTS) components, the challenges are discussed, and recommendations for alternative approaches to improve the reliability allocation process are provided.
A Conceptual Framework for the Upcycling Supply Chain in the Wood Sector
Authors: Mojica Ana , Serrano-Ruiz Julio C. , Andres Beatriz , de la Torre Rocio
Published: January 2025

This paper highlights the importance of sustainable practices in supply chain management, focusing on upcycling as a key approach to transforming discarded materials into valuable products. It proposes a conceptual framework based on state-of-art and action research, which integrates traditional wood upcycling with secondary material recovery, addressing gaps in the existing literature and promoting collaboration among manufacturers, waste managers, and designers. The framework emphasizes circular economy practices in the wood sector, aiming to enhance resource efficiency, reduce waste, foster innovation, and support job creation. Key aspects of the conceptual framework for the upcycling supply chain in the wood sector include supply chain restructuring, valorizing secondary wood, developing digital tools, and aligning global stakeholders to advance sustainability goals.
Improving the Strategic Management of UNESCO Creative Cities of Gastronomy: Integrating Sensitivity Analysis and Tourism Destination Image Based on Analytic Hierarchy Process
Authors: Moreira Pablo Henrique de Oliveira , Fraga Carla , Lavandoski Joice , Cardoso Lucília
Published: January 2025

The globalization of tourism poses complex challenges for destination planning and management, requiring the involvement of various stakeholders and strategic decision-making at various scales. Gastronomic tourism, a key factor in tourist satisfaction and loyalty, has been widely studied for its impact on tourism destination image (TDI). Despite advances in methodologies such as the Analytical Hierarchy Process (AHP), which hierarchies the factors that influence TDI, there are still gaps in the use of sensitivity analysis to improve strategic planning, in particular to leverage TDI as a management tool. Specifically in UNESCO Creative Cities of Gastronomy (UCCG), it is crucial to understand how sensitivity analysis can improve the robustness of AHP models. To address this gap, this study investigates how sensitivity analysis can refine decision-making processes for effective tourism management in Brazil’s UCCG. Using AHP as a decision-making methodology, it integrates sensitivity analysis to assess the reliability of six dimensions in the Analytic Hierarchy Process Image—UNESCO Creative Cities Gastronomy (AHPI-UCCG) model, introducing a dynamic approach to dealing with the complexities of destination planning. The results are valuable for policy-makers and private players in the tourism, creativity, and gastronomy sectors. They offer practical perspectives for improving destination promotion and encouraging coopetition. The study also demonstrates the adaptability of this approach based on sensitivity analysis, suggesting its applicability beyond Brazil to other UCCG networks, contributing to better tourism planning and management at a global level.
Green Growth in Agriculture: Long-Term Evidence from European Union Countries
Authors: Vitunskienė Vlada , Lauraitienė Lina
Published: January 2025

In agriculture, the relationship between economic growth and environmental pressures is complex and difficult to measure and compare between countries. This study had two objectives; the first was to build a new green growth accounting framework for agriculture in relation to natural capital and air pollution, and the second was to assess the long-term green growth of agriculture in EU countries. The data for EU27 from 2005 to 2021 were collected and used in the empirical analysis of green growth in agriculture. The findings showed positive real growth in agriculture from both the economic growth and green growth perspectives in most EU countries in the long term. Slow changes in air pollution (expressed in net GHG emissions from agriculture) and in natural capital (expressed in quality-adjusted agricultural land) did not have a significant impact on green growth in agriculture. The empirical analysis also revealed that most EU countries increasingly rely on technological progress to promote agricultural growth, and half of them rely on investments in produced capital. Labour input only made a positive contribution to agricultural growth in Ireland and Malta. This study will significantly contribute to improving the measure of green growth in agriculture, and the results of the empirical analysis will be used by policymakers and economists.
Towards the Concept of Smart Municipality: Agribusiness Model Integrating Rural and Urban Areas for Organic Food Production: A Review
Authors: Sá Clayton Pereira de , Pagani Regina Negri , Przybysz André Luiz , Souza Fabiane Florencio de , Resende David Nunes , Kovaleski João Luiz
Published: January 2025

Smart cities leverage information and communication technologies to enhance urban life quality, essential in densely populated environments requiring comprehensive planning. A critical area in urban settings is food production and delivery, where effective management becomes vital. New technologies can assist, but require models that support innovative production and commercialization methods. This study proposes an integration model between family farming—producers of organic food—and urban areas—consumers of these products. The model focuses on the management of organic food production and delivery to meet urban demands, serving as a tool in the transformation of these areas into smart municipalities. Additionally, this study suggests an alternative certification method for organic food production within family farming. A systematic literature review was conducted using the Methodi Ordinatio methodology. Content analysis of the selected articles identified strategies cities can adopt to promote organic certification, emphasizing transparent governance, public food procurement policies, and participatory certification systems. The proposed model aims to reduce bureaucracy and improve family farmers’ income, aligning with several Sustainable Development Goals: SDG 2 (Zero Hunger), SDG 8 (Decent Work and Economic Growth), SDG 11 (Sustainable Cities and Communities), SDG 12 (Responsible Consumption and Production), SDG 15 (Life on Land), and SDG 17 (Partnerships for the Goals).
Influence of Ventilation Parameters on Gas Transportation Patterns in Long Highway Tunnels and Sustainable Development of Ventilation Systems
Authors: Suo Liang , Li Shugang , Wu Fengliang
Published: January 2025

In order to study the influence of ventilation parameters on gas movement in large sections of highway tunnels, a mathematical model of gas movement in tunnels is established based on the Yijin Expressway’s Kahaluo No. 1 three-lane tunnel project in Sichuan Province, by using Fluent numerical simulation software to simulate gas tunnel construction. The space–time distribution characteristics of the gas concentration in tunnel construction are obtained, and the influence of ventilation parameters on gas movement is analyzed, the ventilation parameters of the tunnel construction site were optimized. The results show that after ventilation for 20 min, the flow field in the tunnel gradually developed and stabilized, and the gas concentration developing area finally extended to the 45 m position behind the working face, and the gas in the 9 m area behind the face mainly accumulated at the different side of the arched feet of the air duct. Ultimately, the internal flow field structure of the tunnel is mainly composed of a vortex zone (within 10 m in front of the tunnel), a development zone (10–50 m in front of the tunnel), and a stable zone (50–200 m in front of the tunnel). Under the background of the project, the optimal ventilation parameters are as follows: wind velocity 12 m/s, duct diameter 2.0 m, distance from outlet to working face 8 m, and distance from outlet to secondary lining trolley 24 m. According to the optimal ventilation parameter combination, the ventilation system of Cahalo No. 1 tunnel was optimized. It was found that the gas concentration in the tunnel decreased obviously with the increase in ventilation time. The above research further improves the gas tunnel ventilation study, which is of great significance in guiding the site to optimize the ventilation system and guaranteeing the sustainable development of the tunnel ventilation system.
Assessing the Impact of Green Environmental Policy Stringency on Eco-Innovation and Green Finance in Pakistan: A Quantile Autoregressive Distributed Lag (QARDL) Analysis for Sustainability
Authors: Nabi Agha Amad , Ahmed Farhan , Tunio Fayaz Hussain , Hafeez Muhammad , Haluza Daniela
Published: January 2025

Environmental policy stringency, eco-innovation, and green finance play key roles in advancing sustainability, particularly in low- and middle-income countries such as Pakistan. Using annual data from 1990 to 2020, this study employs a quantile autoregressive distributed lag (QARDL) approach to explore the effects across different quantiles. The results reveal a generally negative, quantile-specific relationship between eco-innovation and ecological footprints. At lower quantiles, a 1% increase in green finance is associated with a reduction in ecological footprints ranging from 1% to 4%, demonstrating a beneficial, albeit asymmetric, relationship. As the quantiles increase, the effect of green finance strengthens, with reductions in ecological footprints reaching up to 7% at higher quantiles. Furthermore, stringent environmental policies show a more pronounced impact at higher quantiles, where a 1% increase in policy stringency leads to a reduction in ecological footprints of 5% to 8%. These findings underscore the significance of robust environmental policies, eco-innovation, and green finance as effective mechanisms for reducing ecological impacts and promoting sustainability. This study provides valuable insights for policymakers to strategize on enhancing investments in green financing and implementing stringent environmental regulations, particularly targeting industries and sectors with substantial ecological impacts. Such measures can effectively mitigate environmental degradation by adopting eco-innovation and encouraging sustainable practices, especially in areas provoking acute ecological pressures.
Research on the Contribution of Higher Education to the Sustainable Development of the Economy in China: An Empirical Analysis Based on Provincial Panel Data from 2014 to 2023
Authors: Li Baozhong , Kang Chengxuan
Published: January 2025

In a time of rapid economic development, sustainable development is increasingly becoming the primary concern of governments. Taking the human capital accumulation and spillover model as an analytical tool, we use interprovincial panel data for 2014–2023 to estimate the degree of contribution of higher education to the sustainable development of the economy. Instrumental variables are introduced to alleviate the problem of endogeneity. An urbanization index is also introduced, as well as an interaction term formed by the marketization index and the independent variable to explore the extent of the contribution of higher education to the sustainable development of the regional economy. There are regional differences in the contribution of higher education to sustainable economic development. The study shows that higher education has a significant positive effect on regional economic sustainability. The higher the level of urbanization and the higher the level of marketization, the more significant the positive effect of higher education on economic sustainability. We should continuously increase investment in higher education, optimize the structure and layout of higher education, promote the synergistic development of higher education and urbanization, and deepen the interaction between higher education and market-oriented reform in order to actively promote higher education to serve the sustainable development of regional economies.
Shipping Logistics Network Optimization with Stochastic Demands for Construction Waste Recycling: A Case Study in Shanghai, China
Authors: Wu Ping , Song Yue , Wang Xiangdong
Published: January 2025

In this paper, we introduce a shipping logistics network optimization method for construction waste recycling. In our case, construction waste is transported by a relay mode integrating land transportation, shipping transportation, and land transportation. Under the influence of urban economic life, the quantity (demand) of construction waste is uncertain and stochastic. Considering the randomness of construction waste generation, a two-stage stochastic integer programming model for the design of a shipping logistics network for construction waste recycling is proposed, and an accurate algorithm based on Benders decomposition is presented. Based on an actual case in Shanghai, numerical experiments are carried out to evaluate the efficacy of the proposed model and algorithm. Based on an actual case study in Shanghai, numerical experiments demonstrate that the proposed model can help to reduce transportation costs of construction waste. Sensitivity analysis highlights that factors like the penalty for untransported waste and capacity constraints play a crucial role in network optimization decisions. The findings provide valuable theoretical support for developing more efficient and sustainable logistics networks for construction waste recycling.
Energy Consumption Reduction in Underground Mine Ventilation System: An Integrated Approach Using Mathematical and Machine Learning Models Toward Sustainable Mining
Authors: Saleem Hussein A.
Published: January 2025

This study presents an integrated approach combining the Hardy Cross method and a gradient boosting (GB) optimization model to enhance ventilation systems in underground mines, with a specific application at the Jabal Sayid mine in Saudi Arabia. The Hardy Cross method addresses variations in airflow resistance caused by obstacles within ventilation pathways, enabling accurate predictions of the flow distribution across the network. The GB model complements this by optimizing fan placement, pressure control, and airflow intensity to achieve reduced energy consumption and improved efficiency. The results demonstrate significant improvements in fan efficiency, optimized energy usage, and enhanced ventilation effectiveness, achieving a 31.24% reduction in electricity consumption. This study bridges deterministic and machine learning methodologies, offering a novel framework for the real-time optimization of underground mine ventilation systems. By combining the Hardy Cross method with GB, the proposed approach outperforms traditional techniques in predicting and optimizing airflow distribution under dynamic conditions.
Strain Analysis of Membrane Structures for Photovoltaic Integration in Built Environment
Authors: Milošević Vuk , Marchwiński Janusz , Lucchi Elena
Published: January 2025

The integration of photovoltaic (PV) systems into tensioned membrane structures presents a significant advancement for sustainable applications in the built environment. However, a critical technical challenge remains in the substantial strains induced by external loads, which can compromise both PV efficiency and the structural integrity of the membrane. Current design methodologies prioritize stress, deflection, and ponding analysis of tensioned membranes. Strain behavior of whole structures, a key factor for ensuring long-term performance and compatibility of PV-integrated membranes, has been largely overlooked. This study addresses this gap by examining the whole membrane structure designed for PV integration, with the aim of optimizing the membrane to provide suitable conditions for efficient energy transfer while minimizing membrane strains. For this purpose, it provides a comprehensive strain analysis for full-scale hyperbolic paraboloid (hypar) membrane structures under various design parameters and external loads. Employing the Finite Element Method (FEM) via Sofistik software, the research examines the relationship between load type, geometry, material properties, and patterning direction of membranes to understand their performance under operational conditions. The findings reveal that strain behavior in tensioned membrane structures is strictly influenced by these parameters. Wind loads generate significantly higher strain values compared to snow loads, with positive strains nearly doubling and negative strains tripling in some configurations. Larger structure sizes and increased curvature amplify strain magnitudes, particularly in parallel patterning, whereas diagonal patterning consistently reduces strain levels. High tensile-strength materials and optimized prestress further reduce strains, although edge type has minimal influence. By systematically analyzing these aspects, this study provides practical design guidelines for enhancing the structural and operational efficiency of PV-integrated tensioned membrane structures in the built environment.
Frobenius Norm-Based Global Stability Analysis of Delayed Bidirectional Associative Memory Neural Networks
Authors: Thoiyab N. Mohamed , Shanmugam Saravanan , Vadivel Rajarathinam , Gunasekaran Nallappan
Published: January 2025

The present research investigates the global asymptotic stability of bidirectional associative memory (BAM) neural networks using distinct sufficient conditions. The primary objective of this study is to establish new generalized criteria for the global asymptotic robust stability of time-delayed BAM neural networks at the equilibrium point, utilizing the Frobenius norm and the positive symmetrical approach. The new sufficient conditions are derived with the help of the Lyapunov–Krasovskii functional and the Frobenius norm, which are important in deep learning for a variety of reasons. The derived conditions are not influenced by the system parameter delays of the BAM neural network. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed conclusions regarding network parameters.
Machine Learning-Based Stacking Ensemble Model for Prediction of Heart Disease with Explainable AI and K-Fold Cross-Validation: A Symmetric Approach
Authors: Sultan Sara Qamar , Javaid Nadeem , Alrajeh Nabil , Aslam Muhammad
Published: January 2025

One of the most complex and prevalent diseases is heart disease (HD). It is among the main causes of death around the globe. With changes in lifestyles and the environment, its prevalence is rising rapidly. The prediction of the disease in its early stages is crucial, as delays in diagnosis can cause serious complications and even death. Machine learning (ML) can be effective in this regard. Many researchers have used different techniques for the efficient detection of the disease and to overcome the drawbacks of existing models. Several ensemble models have also been applied. We proposed a stacking ensemble model named NCDG, which uses Naive Bayes, Categorical Boosting, and Decision Tree as base learners, with Gradient Boosting serving as the meta-learner classifier. We performed preprocessing using a factorization method to convert string columns into integers. We employ the Synthetic Minority Oversampling TEchnique (SMOTE) and BorderLineSMOTE balancing techniques to address the issue of data class imbalance. Additionally, we implemented hard and soft voting using voting classifier and compared the results with the proposed stacking model. For the Artificial Intelligence-based eXplainability of our proposed NCDG model, we use the SHapley Additive exPlanations (SHAP) technique. The outcomes show that our suggested stacking model, NCDG, performs better than the benchmark existing techniques. The experimental results of our proposed stacking model achieved the highest accuracy, F1-Score, precision and recall of 0.91, 0.91, 0.91 and 0.91, respectively, and an execution time of 653 s. Moreover, we have also utilized K-Fold Cross-Validation method to validate our predicted results. It is worth mentioning that our prediction results and their validation strongly coincide with each other which proves our approach to be symmetric.
Dual Function Radar and Communication Signal Design with Combined Waveform Selection and Pulse Repetition Interval Agility
Authors: Liu Yu , Li Xiheng , Zou Xing , Yang Zhihang
Published: January 2025

The traditional probe–pass integration system embeds communication information into a radar waveform, which leads to a high level of waveform autocorrelation sidelobes and a poor false symbol rate at low signal-to-noise ratios. This article proposes a three-dimensional indexed modulation-based design method for probe–pass integration waveforms. This method realises communication information modulation and demodulation by simultaneously indexing orthogonal waveform selection, transmitting pulse PRI changes and carrier frequency changes in three dimensions, and applying compressed perception technology to solve the problems of PRI shortcuts and carrier frequency, resulting in a velocity term in the received waveform that cannot be accumulated by phase reference to realise velocity super-resolution. Finally, the radar detection performance and communication performance are simulated and analysed, and the simulation results reveal that the method proposed in this paper can not only satisfy the radar detection performance requirements but also achieve a lower unsigned rate on the basis of an improved communication rate.
A Novel Slot Spiral Symmetric Array Antenna with a Wide Axial Ratio Beamwidth for Microwave-Induced Thermoacoustic Tomography Applications
Authors: Yan An , Zhang Yao , Gao Chengxiang , Ye Jinghua , Zhong Zengpei
Published: January 2025

Conventional circularly polarized antennas have been employed to deliver microwave illumination in microwave-induced thermoacoustic tomography (TAT). However, these antennas exhibit several limitations in TAT systems, including low efficiency, poor axial ratio (AR) roundness, and narrow axial ratio beamwidth (ARBW). These issues lead to uniform radiation only within a relatively confined area, thereby restricting their effectiveness in clinical applications such as breast imaging. To address these issues, we propose a novel planar slot array antenna that offers a wide ARBW and improved axial ratio (AR) roundness, enabling homogeneous illumination over a larger field. We validated this approach both theoretically and experimentally. Tissue-mimicking phantoms were imaged, demonstrating that the antenna generated a circularly polarized electric field as well as a uniformly illuminated area. These advantages make the antenna proposed in this paper more suitable for clinical imaging compared to traditional microwave radiating antennas.
Solvatochromic Analysis of Triton X-100 in Binary Mixtures
Authors: Ambrosi Ecaterina , Zara Alexandru , Dorohoi Dana Ortansa , Dimitriu Dan-Gheorghe
Published: January 2025

Binary solvent mixtures of the non-ionic surfactant Triton X-100 with water, methanol, ethanol, and 1-propanol, respectively, were investigated by solvatochromic studies. The absorption spectral bands of methyl red dye, used as a solvatochromic probe, were recorded in ternary solutions prepared with different mole ratios between Triton X-100 and water/alcohols. The Kamlet–Abboud–Taft model was applied to estimate the contribution of each type of intermolecular interaction to the total shift of the electronic absorption band of the solute. The composition of the solute molecule’s first solvation shell was comparatively estimated by using three models: the statistical cell model of ternary solutions, the Suppan model, and the Bosch–Rosés model. The statistical cell model allows the estimation of the difference between the interaction energies in the solute–solvent pairs of molecules. The Bosch–Rosés model provided important information on the 1:1 complex formed between Triton X-100 and water/alcohol molecules, as well as on the symmetry/asymmetry related to the binary mixtures in the cybotactic region of the solute’s molecule.
Challenges and Ethical Considerations in Implementing Assistive Technologies in Healthcare
Authors: Gkiolnta Eleni , Roy Debopriyo , Fragulis George F.
Published: January 2025

Assistive technologies are becoming an increasingly important aspect of healthcare, particularly for people with physical or cognitive problems. While earlier research has investigated the ethical, legal, and societal implications of AI and assistive technologies, many studies have failed to address real-world obstacles such as data privacy, algorithm bias, and regulatory issues. To further understand these issues, we conducted a thorough analysis of the current literature and analyzed real-world case studies. As AI-powered solutions become more widely used, we discovered that stronger legal frameworks and robust data security standards are required. Furthermore, privacy-preserving procedures and transparent accountability are critical for retaining patient trust and guaranteeing the effective use of these technologies in healthcare. This research provides important insights into the ethical and practical challenges that must be tackled for the successful integration of assistive technologies.
Wide Variation of Aedes albopictus Genotypes First Introduced into Canary Islands Assessed by rDNA Internal Transcribed Spacer Region and mtDNA cox1 Sequencing and Cloning
Authors: De Elías-Escribano Alejandra , Serafín-Pérez Irene , Artigas Patricio , Fernández-Serafín Carolina , Rodríguez-Camacho Sara , Yanes-Manrique Beatriz , González-Alonso Víctor , Mas-Coma Santiago , Lorenzo-Morales Jacob , Bargues María Dolores
Published: January 2025

Aedes albopictus, one of the most rapidly spreading invasive mosquito species, has expanded from Asia to establish populations on every continent except Antarctica, showcasing exceptional adaptability, particularly in island environments. This study provides the first molecular characterization of Ae. albopictus in the Canary Islands, Spain. Genotyping was conducted using rDNA 5.8S-ITS2 and mtDNA cox1 sequencing, with haplotype analysis and phylogenetic network assessment. Among 49 sequences, 28 distinct 5.8S-ITS2 haplotypes were identified, with individual specimens containing 5 to 17 haplotypes (mean, 10.6). Most haplotypes (26/28; 92.85%) were unique to Tenerife, while only two (7.14%) were shared with other regions. H1 was the most frequent haplotype, shared with Valencia and China, while H2, a short-length haplotype, was shared with Mallorca. For cox1, only two haplotypes were detected: cox1-H1, reported in Europe, China, and Brazil, and a novel haplotype, cox1-H28. This genetic diversity suggests the species’ potential capacity to colonize new environments. The findings provide a foundation for further research in the Canary Islands and globally, particularly in regions with high tourism and arbovirus risks, emphasizing the importance of ongoing surveillance and genetic studies to understand the dynamics and public health impacts of invasive mosquito species.
Remdesivir and Obeldesivir Retain Potent Antiviral Activity Against SARS-CoV-2 Omicron Variants
Authors: Rodriguez Lauren , Zamora J. Lizbeth Reyes , Han Dong , Moshiri Jasmine , Peinovich Nadine , Martinez Clarissa , Ho Pui Yan , Li Jiani , Aeschbacher Thomas , Martin Ross , Pekosz Andrew , Bilello John P. , Perry Jason K. , Hedskog Charlotte
Published: January 2025

As new SARS-CoV-2 variants continue to emerge, it is important to evaluate the potency of antiviral drugs to support their continued use. Remdesivir (RDV; VEKLURY®) an approved antiviral treatment for COVID-19, and obeldesivir (ODV) are inhibitors of the SARS-CoV-2 RNA-dependent RNA polymerase Nsp12. Here we show these two compounds retain antiviral activity against the Omicron variants BA.2.86, BF.7, BQ.1, CH.1.1, EG.1.2, EG.5.1, EG.5.1.4, FL.22, HK.3, HV.1, JN.1, JN.1.7, JN.1.18, KP.2, KP.3, LB.1, XBB.1.5, XBB.1.5.72, XBB.1.16, XBB.2.3.2, XBC.1.6, and XBF when compared with reference strains. Genomic analysis identified 29 Nsp12 polymorphisms in these and previous Omicron variants. Phenotypic analysis of these polymorphisms confirmed no impact on the antiviral activity of RDV or ODV and suggests Omicron variants containing these Nsp12 polymorphisms remain susceptible to both compounds. These data support the continued use of RDV in the context of circulating SARS-CoV-2 variants and the development of ODV as an antiviral therapeutic.
The Epidemiology and Clinical Burdens of Human Parainfluenza Virus Infections Amongst Hospitalized Children Under 5 Years of Age in Jordan: A National Multi-Center Cross-Sectional Study
Authors: Abu-Helalah Munir , Abu Lubad Mohammad , Al-Hanaktah Mohammad , Al Tibi Ahmad , Alhousani Maisalreem , Drysdale Simon B.
Published: January 2025

Human parainfluenza virus (HPIV) is a major cause of respiratory illnesses in children under five years, with clinical manifestations ranging from mild upper respiratory tract infections to severe lower respiratory tract diseases. This multi-center, cross-sectional study investigated the burden, clinical features, and predictors of respiratory viral infections in hospitalized children across four sites in Jordan. Nasopharyngeal specimens from 1000 eligible children were analyzed. In this article, we focused on HPIV infections. The overall HPIV positivity rate was 22.6%, with HPIV-3 accounting for 90.3% of cases. Significant geographic variability was observed, with higher positivity rates in the southern region. HPIV-positive cases frequently presented with symptoms like nasal congestion, tachypnea, and poor feeding. Co-infections with respiratory syncytial virus (RSV) or influenza were associated with worse outcomes, including an increased need for invasive ventilation. The logistic regression identified male gender, asthma, and respiratory acidosis as predictors of complications. Geographic differences in HPIV prevalence and severity were notable, emphasizing the influence of environmental and socioeconomic factors. These findings underscore the urgent need for enhanced HPIV surveillance, targeted public health interventions, and vaccine development to mitigate the disease burden. This study provides critical insights that guide healthcare strategies and improve outcomes in young children at risk of severe HPIV infections.
Unraveling the Kaposi Sarcoma-Associated Herpesvirus (KSHV) Lifecycle: An Overview of Latency, Lytic Replication, and KSHV-Associated Diseases
Authors: Losay Victor A. , Damania Blossom
Published: January 2025

Kaposi sarcoma-associated herpesvirus (KSHV) is an oncogenic gammaherpesvirus and the etiological agent of several diseases. These include the malignancies Kaposi sarcoma (KS), primary effusion lymphoma (PEL), and multicentric Castleman disease (MCD), as well as the inflammatory disorder KSHV inflammatory cytokine syndrome (KICS). The KSHV lifecycle is characterized by two phases: a default latent phase and a lytic replication cycle. During latency, the virus persists as an episome within host cells, expressing a limited subset of viral genes to evade immune surveillance while promoting cellular transformation. The lytic phase, triggered by various stimuli, results in the expression of the full viral genome, production of infectious virions, and modulation of the tumor microenvironment. Both phases of the KSHV lifecycle play crucial roles in driving viral pathogenesis, influencing oncogenesis and immune evasion. This review dives into the intricate world of the KSHV lifecycle, focusing on the molecular mechanisms that drive its latent and lytic phases, their roles in disease progression, and current therapeutic strategies.
ILC3 Function as a Double-Edged Sword in EV71 Infection
Authors: Zhang Chang , Bao Linlin , Qi Feifei , Lv Qi , Li Fengdi , Qin Chuan
Published: January 2025

Enterovirus 71 (EV71) is a common pathogen responsible for hand, foot, and mouth disease (HFMD), leading to severe neurological complications and even death. However, the mechanisms underlying severe EV71-induced disease remain unclear, and no effective specific treatments are available. In this study, we successfully infected mice of different ages using a mouse-adapted EV71 strain, resulting in disease and mortality. We compared immune system responses between infected and uninfected mice of different ages to identify key pathogenic targets during EV71 infection. Our findings revealed that the level of Group 3 Innate Lymphoid Cells (ILC3s) in mice negatively correlated with the severity of disease induced by EV71 infection. We conducted anti-ILC3 cytokine injections and cytokine neutralizing antibody experiments on 14-day-old EV71-infected mice. The results showed that the cytokine IL-17 secreted by ILC3 cells had a mild protective effect, while IL-22 promoted inflammatory responses. Our research demonstrates that ILC3 cells play a dual role in EV71 infection. These findings not only clarify key immune factors in the progression of EV71-induced disease but also provide a promising approach for the early diagnosis and treatment of severe EV71 infections.
Revolutionizing Nanovaccines: A New Era of Immunization
Authors: Saleh Mohammed , El-Moghazy Ahmed , Elgohary Adel H. , Saber WesamEldin I. A. , Helmy Yosra A.
Published: January 2025

Infectious diseases continue to pose a significant global health threat. To combat these challenges, innovative vaccine technologies are urgently needed. Nanoparticles (NPs) have unique properties and have emerged as a promising platform for developing next-generation vaccines. Nanoparticles are revolutionizing the field of vaccine development, offering a new era of immunization. They allow the creation of more effective, stable, and easily deliverable vaccines. Various types of NPs, including lipid, polymeric, metal, and virus-like particles, can be employed to encapsulate and deliver vaccine components, such as mRNA or protein antigens. These NPs protect antigens from degradation, target them to specific immune cells, and enhance antigen presentation, leading to robust and durable immune responses. Additionally, NPs can simultaneously deliver multiple vaccine components, including antigens, and adjuvants, in a single formulation, simplifying vaccine production and administration. Nanovaccines offer a promising approach to combat food- and water-borne bacterial diseases, surpassing traditional formulations. Further research is needed to address the global burden of these infections. This review highlights the potential of NPs to revolutionize vaccine platforms. We explore their mechanisms of action, current applications, and emerging trends. The review discusses the limitations of nanovaccines, innovative solutions and the potential role of artificial intelligence in developing more effective and accessible nanovaccines to combat infectious diseases.
Efficacy of LaAg Vaccine Associated with Saponin Against Leishmania amazonensis Infection
Authors: de Mello Mirian França , Machado Patrícia de Almeida , Gomes Pollyanna Stephanie , Oliveira-Silva Gabriel , Carneiro Monique Pacheco Duarte , Ramos Tadeu Diniz , Silveira Pratti Juliana Elena , Peralva Raquel , Firmino-Cruz Luan , Da-Cruz Alda Maria , Covre Luciana , Gomes Daniel Claúdio Oliveira , Rossi-Bergmann Bartira , Pinto Eduardo Fonseca , da Fonseca-Martins Alessandra Marcia , de Matos Guedes Herbert Leonel
Published: January 2025

Background/Objectives: The total lysate of Leishmania amazonensis (LaAg) is one of the most extensively studied vaccine formulations against leishmaniasis. Despite demonstrating safety and immunogenicity when administered intramuscularly, LaAg has failed to show efficacy in clinical trials and, in some cases, has even been associated with an enhanced susceptibility to infection. Adjuvants, which are molecules or compounds added to antigens to enhance the immunogenicity or modulate the immune response, are frequently employed in vaccine studies. This study aimed to evaluate different adjuvants to improve the protective efficacy of LaAg in L.amazonensis infection using a BALB/c mouse model. Methods: BALB/c mice were immunized with LaAg in combination with various adjuvants. The delayed-type hypersensitivity (DTH) test was assessed by measuring the infected paw and was used to evaluate the immunogenicity and to determine the most effective adjuvant. The immune response was analyzed through flow cytometry, focusing on cytokine production, immune cell recruitment and lesion size, alongside the control of parasite load at the infection site. The expression levels of iNOS and TGF-β were quantified using RT-qPCR, while IgG1, IgG2a and IgE antibody levels were determined via ELISA. Results: Among the adjuvants tested, only saponin (SAP) elicited a significant DTH response following LaAg challenge. SAP enhanced the immunogenicity of LaAg, as evidenced by increased IFN-γ-producing CD4+ and CD8+ T cells in the draining lymph nodes at 18 h post-challenge. Additionally, SAP facilitated the recruitment of lymphocytes, macrophages, neutrophils and eosinophils to the infection site. Conclusions: The LaAg + SAP combination conferred partial protection, as demonstrated by a reduction in lesion size and the partial control of parasite load. In conclusion, the addition of SAP as an adjuvant to LaAg effectively modulates the immune response, enhancing the vaccine’s protective efficacy. These findings provide valuable insights into the development of improved vaccines against L.amazonensis infection.
Digital transformation of the state budgetary healthcare Institution of the Samara region «Syzran central city and district hospital» in the period from 2022 to 2024. Achievements and new horizons of healthcare
Authors:   State Budgetary Healthcare Institution of the Samara Region «Syzran Central City and District Hospital», Komarov S. N. , Sentsova M. D. ,   State Budgetary Healthcare Institution of the Samara Region «Syzran Central City and District Hospital»
Published: January 2025

The article covers the issues and cases of digital transformation of the Syzran Central
City and District Hospital, the role and importance of implementing modern technologies and
medical systems. The effects of implementation are considered.
Modern trends in the development of clinical diagnostic laboratory. Innovations and experience of the state budgetary healthcare institution of the Samara region «Syzran central city and district hospital»
Authors:   State Budgetary Healthcare Institution of the Samara Region «Syzran Central City and District Hospital», Fedorchuk V. P. , Syromyatnikova O. M. ,   State Budgetary Healthcare Institution of the Samara Region «Syzran Central City and District Hospital»
Published: January 2025

The article covers the issues of implementation of the complex process of centralization
and optimization of the laboratory service of the State Budgetary Healthcare Institution of the Samara
Region «Syzran Central City and District Hospital» and presents the main goals of this process.
Creation and replication of a new model of a medical organization providing primary medical care within the framework of the implementation of the regional project «Development of the primary medical care system» of the state budgetary healthcare institution «Syzran central city and district hospital» children’s clinic no. 5
Authors:   State Budgetary Healthcare Institution of the Samara Region «Syzran Central City and District Hospital», Susina O. Yu.
Published: January 2025

In the article, the author draws attention to the features of creating a new model of a children’s clinic
providing primary health care within the framework of the implementation of a regional project.
Experience in implementing unified approaches to organizing the work of the procedural room in the state budgetary healthcare institution «Syzran Central City and District Hospital»
Authors:   State Budgetary Healthcare Institution of the Samara Region «Syzran Central City and District Hospital», Syromyatnikova O. M. , Trifonova O. V. ,   State Budgetary Healthcare Institution of the Samara Region «Syzran Central City and District Hospital»
Published: January 2025

The purpose of introducing unified approaches to organizing the work of the procedure room
was to reduce the waiting time for patients to receive a medical service (blood sampling), improve
safety, and improve quality.