bluuebunny/crossref_metadata_2025 huggingface dataset:
Predicting Urban Traffic Congestion with VANET Data
Authors: Chango-Sailema Wilson Chango , Buñay-Guisñan Pamela , Erazo Juan Erazo , Aguilar-Encarnación Pedro Aguilar , Sayago-Heredia Jaime Sayago
Published: January 2025

Recent research has demonstrated a strong correlation between the exponential growth of the transportation sector and the increase in urban phenomena such as traffic accidents and congestion. In this context, accurate congestion prediction has become a primary objective to improve urban mobility and mitigate the negative effects associated with traffic.The study proposes a machine learning-based classification model to predict vehicular congestion. Using a dataset that includes variables such as speed, traffic flow, and weather conditions, various classification algorithms were trained and evaluated. The results obtained indicate that models based on Random Forest offer superior performance in the task of congestion prediction.To evaluate the impact of these predictions on urban mobility, the model was integrated into a vehicular ad-hoc network (VANET) simulation environment. The simulation results demonstrated that providing real-time traffic information based on model predictions allows drivers to make more informed decisions, consequently reducing travel times and emissions.
A Comprehensive Survey of Computational Techniques for Lung Cancer Diagnosis and Prediction
Authors: JAMIL DANISH , Rocha Álvaro , Ferras Carlos
Published: January 2025

Background and Objective: Lung cancer continues to be a major global health issue, with a pressing need for improved diagnostic and prognostic methods to enhance early detection and patient outcomes. The objective of this survey is to review and evaluate the current methods and models used in lung cancer diagnosis and prognosis, focusing on their strengths, limitations, and potential for future advancements. Methods: A systematic review of the literature was conducted across key databases, focusing on studies that utilize deep learning architectures, such as CNN, GoogleNet, VGG-16, U-Net, and machine learning algorithms, including XGBoost, SVM, KNN, ANN, and Random Forest. The review synthesized findings from these studies to assess the effectiveness and limitations of these computational models in the context of lung cancer detection. Results: The review identified several strengths in current models, including high accuracy in controlled environments and potential for early detection. However, significant limitations were also highlighted, such as issues with model interpretability, a lack of real-world validation, and challenges in integrating diverse diagnostic techniques. These gaps indicate the need for further research to enhance the applicability and reliability of AI-driven models in clinical settings. Conclusions: Advanced computational methods, particularly those utilizing deep learning and machine learning, hold transformative potential for lung cancer diagnosis and prognosis. However, to fully realize this potential, future research must address current challenges, such as improving model interpretability and ensuring robust validation in real-world scenarios. By overcoming these obstacles, AI-driven approaches can significantly improve patient care and outcomes in lung cancer treatment.
Bioelectric Membrane Potential and Breast Cancer: Advances in Neuroreceptor Pharmacology for Targeted Therapeutic Strategies
Authors: Mahapatra Chitaranjan , Gawad Jineetkumar , Bonde Chandrakant , Palkar Mahesh B
Published: January 2025

Bioelectric membrane potentials regulate cellular growth, differentiation, and movement. Disruptions in bioelectric signaling are strongly linked to cancer development, particularly in breast cancer, where ion channel dysfunction and neuroreceptor-related pathways play significant roles in the cell cycle, epithelial-mesenchymal transition, angiogenesis, inflammation, the tumor microenvironment, and tumor progression. Neuroreceptors are critical not only in initiating and advancing cancer but also in conferring resistance to treatments. Advances in understanding these biological mechanisms could lead to more cost-effective and less invasive therapeutic strategies to treat tumors. This review explores the expanding evidence connecting bioelectric activity to breast cancer, focusing on neuroreceptor pharmacology as a transformative therapeutic approach. Investigating how neuroreceptor pharmacology-based modulation of bioelectricity affects breast cancer progression and integrating these insights into therapeutic development offers a promising path for addressing treatment challenges and improving precision in managing aggressive cancer subtypes.
Neurological Assessment Scales in Hospitalized Newborns with Congenital Syphilis
Authors: Silva Bruna Vitória Ricardo da , Friedrich Luciana , Biazus Graziela Ferreira , Bueno Renata dos Santos , Almeida Carla Skilhan
Published: January 2025

Background: Congenital syphilis (CS) is a transplacental infection that an lead to many long-term sequelae when not adequately treated; however, knowledge about the motor and neurological signs that newborns (NB) with CS may present is scarce. Objective: To describe the results of neurological assessment scales and general movements in NB with CS in the first days of life. Methods: Cross-sectional study. The Hammersmith Neonatal Neurological Examination (HNNE) and General Movements Assessment (GMA) scales were used to evaluate NB under treatment for CS in a public Brazilian hospital in the first days of life. Results: Sample consisted of 11 NB, with a mean birth weight of 3140.5g, and Apgar score at 5 minutes of 8.3. Among the 11 mothers, 4 (36.4%) had fewer than 6 prenatal visits and 5 (45.5%) did not receive any syphilis treatment. All NB (100%) were asymptomatic, with normal long bone X-rays and cerebrospinal fluid analysis. The mean score on the HNNE was 22 (suboptimal/abnormal). Eight NB (72.7%) showed abnormalities on GMA scale (6 [54.5%] being mildly abnormal and 2 [18%] definitely abnormal. Only 3 NB (27.3%) returned for outpatient follow-up. Conclusions: A high prevalence of abnormalities in neurological and GMA scales was observed in NB with asymptomatic CS in the first days of life. Most mothers did not receive adequate treatment for syphilis during pregnancy, and there were important deficiencies in post-discharge follow-up. Further studies are needed to confirm these findings and investigate whether the observed abnormalities are linked to biological or environmental factors during pregnancy. Keywords: Congenital syphilis; newborns; neurological examination.
The Impact of Blockchain Technology on Customer Loyalty in the Insurance Industry: The Mediating Roles of Transparency, Security, and Efficiency
Authors: Abdollahi Zamharir Mohammad
Published: January 2025

This study investigates the impact of blockchain technology on customer loyalty in the global insurance industry, focusing on the mediating roles of transparency, security, and efficiency. Using data from 2000 customers worldwide, Structural Equation Modeling (SEM) reveals that blockchain technology significantly enhances customer loyalty, mediated by transparency, security, and efficiency. The findings suggest that insurers should prioritize blockchain adoption, enhance transparency, and ensure data security to foster customer loyalty. This study contributes to the literature by addressing the underexplored role of blockchain technology in the insurance sector and provides practical insights for insurance companies aiming to leverage blockchain for improved customer retention. Limitations include reliance on self-reported data and a cross-sectional design. Future research should explore longitudinal effects and cross-industry comparisons.
Metabolic Profiling Reveals Prognostic Biomarkers for SFTS: Insights into Disease Severity and Clinical Outcomes
Authors: Zhu Zhuo-Min , Liu Huan-Yu , An Na , Li Anling , Li Jia , Wang Sai-Jun , Yang Gui , Duan Yongwei , Yang Ying , Zhang Mei , Zhu Quan-Fei , Liu Song-Mei , Feng Yu-Qi
Published: January 2025

Severe fever with thrombocytopenia syndrome (SFTS) is a viral infection primarily found in Asia, with a case fatality rate of about 10%. Despite its increasing prevalence, the underlying pathogenic mechanisms remain poorly understood, limiting the development of effective therapeutic interventions. We employed an untargeted metabolomics approach using liquid chromatography-mass spectrometry (LC-MS) to analyze serum samples from 78 SFTS patients during the acute phase of their illness. Differential metabolic features between survival and fatal cases were identified through multivariate statistical analyses. Furthermore, we constructed a metabolic prognostic model based on these biomarkers to predict disease severity. Significant alterations were observed in four key metabolic pathways: sphingolipid metabolism, biosynthesis of phenylalanine, tyrosine, and tryptophan, primary bile acid biosynthesis, and phenylalanine metabolism. Elevated levels of phenylacetic acid and isocitric acid were strongly associated with adverse outcomes and demonstrated high discriminatory power in distinguishing fatal cases from survivors. The metabolic prognostic model incorporating these biomarkers achieved a sensitivity of 75% and a specificity of 90% in predicting disease severity. Our findings highlight the pivotal role of metabolic dysregulation in the pathogenesis of SFTS and suggest that targeting specific metabolic pathways could open new avenues for therapeutic development. The identification of prognostic biomarkers provides a valuable tool for early risk stratification and timely clinical intervention, potentially improving patient outcomes.
Olympism, Olympic Values and Transgender Athletes: A Difficult Coexistence
Authors: Alessi Longa Francesco
Published: January 2025

The Olympic Games are considered as the ultimate event, the embodiment of excellence, respect and inclusiveness, but the issue of transgender people’s participation in sports has become a subject that threatens the equilibrium between equity, tolerance, and honesty. This paper aims at exploring the philosophical aspects of Olympism and their incorporation, the process and the difficulties in implementing the Olympic values in the contemporary world. It reviews the history of the matter, ethical issues, and the current policies. The aim is to develop a conceptual framework that can help to understand the advantages and disadvantages of the Olympic Movement as an inclusive organization.
Self-MCKD : Enhancing the Effectiveness and Efficiency of Knowledge Transfer in Malware Classification
Authors: Jeong Hyeon-Jin , Lee Han-Jin , Kim Gwang-Nam , Choi Seok-Hwan
Published: January 2025

As malware continues to evolve, AI-based malware classification methods have shown significant promise in improving malware classification performance. However, these methods lead to a substantial increase in computational complexity and the number of parameters, increasing computational cost during the training process. Moreover, the maintenance cost of these methods also increase, as frequent retraining and transfer learning are required to keep pace with evolving malware variants. In this paper, we propose an efficient knowledge distillation technique for AI-based malware classification methods, called Self-MCKD. Self-MCKD transfers output logits that are separated into target class and non-target classes. With the separation of output logits, Self-MCKD enables efficient knowledge transfer by assigning weighted importance to the target class and non-target classes. Also, Self-MCKD utilizes small and shallow AI-based malware classification methods as both the teacher and student models to overcome the need for using large and deep methods as the teacher model. From the experimental results under various malware datasets, we show that Self-MCKD outperforms traditional knowledge distillation techniques in terms of the effectiveness and efficiency of malware classification.
Detection of Coronaviruses and Genomic Characterization of Gammacoronaviruses from Overwintering Black-Headed Gulls (Chroicocephalus ridibundus) in Yunnan Province, China
Authors: Zhao Jun-Ying , Chu Kan-Kan , Han Pei-Yu , Yang Ze , Tang Yi , Kong Wei , Long Yun , Zong Li-Dong , Ge Xing-Yi , Zhang Yun-Zhi
Published: January 2025

Black-headed gulls have been confirmed to be the natural hosts of Deltacoronavirus (δ-CoV) and Gammacoronavirus (γ-CoV). A total of 59 coronaviruses (CoVs) were detected in 509 fecal samples collected from overwintering black-headed gulls in Yunnan Province, China. Among them, the prevalence of black-headed gull Deltacoronavirus (BHG-DCoV) was 3.54% (18/509), and that of black-headed gull Gammacoronaviru (BHG-GCoV) was 8.06% (41/509). The prevalence of BHG-GCoV was higher than that of BHG-DCoV (χ² = 9.518, P < 0.01). It was obtained that two complete genome sequences of BHG-GCoVs with lengths of 27,358 nt and 37,355 nt respectively from the fecal samples of black-headed gulls. The nu-cleotide similarity between the two complete genomes is 98.75%. Phylogenetic analysis based on the whole genome has confirmed that the two stains of BHG-GCoVs clustered into the species Gammacoronavirus anatis. Although BHG-GCoVs belong to the species Gammacoronavirus anatis, they are distantly related to the representative strain Duck_CoV 2714, and have a relatively close genetic relationship with the GCoV from Xenus cinereus (AvXc-GCoV) and the GCoV from Numenius phaeopus (AvNp-GCoV). Based on the similar-ity analysis of the five conserved domains, there is a high amino acid similarity not only with AvXc-GCoV and AvNp-GCoV, but also with the GCoV of the common gull detected in Poland and the GCoV from ruddy turnstone detected in Australia. We also found that the amino acids of the S protein of BHG-GCoVs had a relatively high similarity with GCoV from most of the Charadriiformes except for the common gull, while having a rela-tively low amino acid similarity with that from the Anseriformes. Meanwhile, we also de-tected recombination events in BHG-GCoVs, indicating that recombination events might occur frequently during the viral evolution process.
A Bi-Level Programming Based Method for Service Composition Optimization of Collaborative Manufacturing of Sewing Machine Cases
Authors: Shi Gan , Liu Shanhui , Shi Keqiang , Zhu Langze , Gao Zhenjie , Zhang Jiayue
Published: January 2025

Aiming at the problem of difficult decision-making of manufacturing resource composition optimization in part-level outsourcing of sewing machine case manufacturing, this paper proposes a service composition optimization method based on bi-level programming. We analyze the structure and production process of sewing machine cases, determine the required service composition of manufacturing resources, and establish the evaluation index system of manufacturing service composition in line with the interests of multiple parties; introduce the idea of bi-level programming, and construct the optimization model of manufacturing service composition of sewing machine cases based on bi-level planning; we analyze the characteristics of NSGA-Ⅱ algorithm and the improvement strategy, and complete the solution of the optimization model of manufacturing service composition of sewing machine cases to achieve the combination optimization of the manufacturing services of the machine cases. The combination optimization model of sewing machine case manufacturing services is solved to realize the combination optimization of machine case manufacturing services. The experimental results show the effectiveness and superiority of the combination optimization method and algorithm improvement strategy in solving the combination optimization problem of sewing machine case manufacturing, and the combination optimization of sewing machine case cooperative manufacturing services is realized.
Smart Farming Technologies for Sustainable Agriculture: A Case Study of a Mediterranean Aromatic Farm
Authors: Greco Carlo , Gaglio Raimondo , Settanni Luca , Sciurba Lino , Ciulla Salvatore , Orlando Santo , Mammano Michele Massimo
Published: January 2025

Consumer interest in medicinal and aromatic herbs is on the rise, with buyers increasingly concerned about the microbiological quality of nutraceutical and aromatic plants. The use of Unmanned Aerial Vehicles (UAVs) and sensor technology allows for high-resolution crop monitoring, particularly in the production of rosemary and sage in Grotte (Italy), Agrigento District. The aim of this study is to evaluate the efficacy of UAV-based time series remote sensing data and multimodal data fusion using RGB and multispectral sensors in rosemary and sage harvesting time individuation and the microbiological quality of these nutraceutical and aromatic plants before and after an innovative an sustainable drying process. The multispectral data were acquired with a DJI multispectral camera mounted on the Unmanned Aerial Vehicle (UAV) Phantom 4. The use of drones in the aromatic plants crops can lead to improved efficiency, productivity, and profitability for farmers and businesses. Italian producers follow strict hygiene regulations to reduce bacterial contamination, particularly during the crucial drying process. A rapid drying method at low temperature using a dryer powered by a photovoltaic Renewable Energy Source (RES) helps preserve the quality of the plants. Real-time monitoring of the drying process is enabled through a system based on wireless sensor networks (WSN), providing valuable data on moisture content, drying rates, and microbial stability. Overall, the innovative use of drones, sensor technology, and renewable energy sources in the production of aromatic herbs like rosemary and sage holds great potential for enhancing crop quality, shelf life, and overall sustainability in the chain food industry.
Determinants of Financial Performance in Advertising and Marketing Companies: Evidence from the CEE Countries
Authors: Zavalii Tetiana , Lehenchuk* Serhii , Chyzhevska Lyudmyla , Hrabchuk Iryna
Published: January 2025

The issue of key determinants affecting the financial performance of advertising and marketing companies in Central and Eastern Europe remains understudied, despite the industry's rapid growth and regional specifics. This study investigates financial performance determinants of advertising and marketing companies in four CEE countries (the Czech Republic, Poland, the Slovak Republic, and Ukraine) using panel data from 2021-2023. The study examines three financial performance measures (ROA, ROE, and Operating Profit Margin) using three independent variables (Current Ratio, Debt to Equity, and Total Asset Turnover) and control variables such as Company Size, Leverage, and Company Type. The results show that Total Asset Turnover consistently has a significant positive impact on ROA and ROE across all countries studied, highlighting the crucial role of efficient asset and equity management in the CEE region.
Improving the Transport and Logistics Infrastructure of the City Using the Graph Theory Method: On the Case of Astana, Kazakhstan
Authors: Syzdykbayeva Bakyt , Raimbekov Zhanarys , Baiburiev Ruslan , Dulatbekova Zhanar
Published: January 2025

The development of the city's transport and logistics infrastructure is associated with many problematic issues, such as a decrease in the quality of life of the population, insufficient connectivity of territories, uneven intensity of traffic flows, and ecological impact. The article presents theoretical and practical foundations for improving the city's transport and logistics infrastructure by using graph theory method. The primary results were obtained by dividing the city's territory into meso-districts, determining the poles and vectors of the city's meso-district graph, their territorial placement and connectivity with other districts, considering the availability and provision of industrial, social, institutional and environmental infrastructure. For this purpose, based on expert assessments and sample data from infrastructure facilities, the indices of meso-district congestion by enterprises and institutions were determined. Based on statistical data, the contribution of the studied indicators to the overall polarity of the city's meso-districts was determined. The results allowed us to determine the most problematic meso-districts in the city, to identify the directions of logistics flows in the city. The data obtained allowed us to determine the directions of development of the transport and logistics infrastructure (TLI) in the city. In addition, the polarity of the graph of meso-districts of the city characterizes the state of traffic jams on the roads of meso-districts and the impact on the environment, which makes it possible to adjust when planning the development of the TLI of the city. The proposed methodological approach and the results of the study allow making scientifically based decisions in the formation and development of TLI. The study reveals the practical prospects for using this methodological approach in developing a concept for the development of TLI in any large city. The results provide valuable information for stakeholders, policy makers, local authorities and state bodies to implement specific actions.
Lipid Production in Cultivable Filamentous Fungi Isolated from Antarctic Soils: A Comprehensive Study
Authors: Gallardo Victor , Costa Jéssica , Sepúlveda Marcela , Cayún Yasna , Santander Christian , Ponce Excequel , Bittencourt Juliana , Arriagada César , Soto Javiera , Pedreschi Romina , Vicente Vania , Cornejo Pablo , Santos Cledir
Published: January 2025

Antarctic soil represents an important reservoir of filamentous fungi (FF) species with capability to produce novel bioactive lipids. However, the lipid extraction method is still bottleneck. The objective of the present work was to isolate and identify cultivable FF from Antarctic soils, to assess the most effective methods for fatty acids (FA) extraction, and to characterise the lipids obtained. A total of 18 fungal strains belonging to the genera Botrytis, Cladosporium, Cylindrobasidium, Mortierella, Penicillium, Pseudogymnoascus, Talaromyces, and to the Melanommataceae family were isolated and identified. The Folch, Bligh & Dyer and Lewis extraction methods were assessed, and methyl esters of FA (FAME) were obtained. The Lewis method was the best one in recovering FAME from fungal biomass. A total of 17 FA were identified and their chemical compositions varied depending on fungi species and strains. Oleic, linoleic, stearic and palmitic acids were predominant for all fungal strains in the three methods assessed. From the strains analysed, Cylindrobasidium eucalypti, Penicillium miczynskii, P. virgatum and Pseudogymnoascus pannorum produced high amounts of FA. This suggests that the soils of Antarctica Bay, as well as harbouring known oleaginous fungi, are also an important source of oleaginous filamentous fungi that are still poorly analysed.
Is There a Common Financial Cycle in Systemic Economies?
Authors: Magubane Khwazi
Published: January 2025

Countries such as Advanced Systemic Economies (ASEs) and Systemic Middle-Income Countries (SMICs) considering macroprudential policy coordination must ensure that their financial cycles are sufficiently synchronized. However, differences in the features and significance of financial cycles between ASEs and SMICs pose challenges in determining the extent of their synchronization. Accordingly, this study assesses whether a common financial cycle exists between these economies. The point of departure for this analysis is to examine the characteristics of the common financial cycle. To this end, the study employs data on capital flows, credit, house prices, share prices, and policy rates, utilizing the Markov Switching Dynamic Regression Model and the Dynamic Factor Model to identify and analyze the cycle. The findings reveal strong evidence of a significant financial cycle, which explains 83% of the total variation across countries. This cycle is characterized by longer durations compared to domestic financial cycles and occurs less frequently than domestic cycles. Moreover, it exhibits high persistence in its contractionary and expansionary phases, with greater volatility in the contractionary phase. Based on these findings, it is recommended that ASEs and SMICs consider establishing a supranational prudential authority to coordinate and oversee macroprudential policy on behalf of the majority. Such an entity should play a proactive role, particularly during contractionary phases, to mitigate systemic risks and enhance financial stability across these interconnected economies.
Differential Platelet Spatial Morphodynamics in Response to Local Signaling Environments Within a Jugular Puncture Wound Thrombus
Authors: Ariyarathne Madhavi A. , Pokrovskaya Irina D. , Ball Kelly K. , Zhao Oliver S. , Aronova Maria A. , Leapman Richard D. , Storrie Brian
Published: January 2025

We focused on two microenvironments within a 5-min jugular vein puncture wound thrombus. The goal was to infer from 3D platelet morphodynamics how microenvironments determine platelet activation state. Platelets at the collagen-rich adventitial interface were rod shaped and oriented vertical to flow vectors. The net effect was to maximize their interaction with collagen. At the wound hole interface, soluble signaling should predominant. Here, the typical platelet exhibited what appeared to be a “migratory”, granule-free, leading edge extending toward the wound hole from an organelle rich cell body. Morphologically, this structure resembled the leading edge of a wound associated fibroblast. Platelets were aligned parallel with one another and at ~45 degrees to blood flow. We submit the morphodynamics observed here indicate novel similarities between platelets and wound associated nucleated cells.
Ultra-Lightweight Cryptographic Algorithm for Resource-Constrained Medical IoT Devices to Enhance Healthcare Security
Authors: Rasheed Abdul Muhammed , Kumar R.Mathusoothana S.
Published: January 2025

Difficulty in managing devices, privacy issues, failures of centralized systems, and vulnerabilities to malicious attacks are some of the major challenges that IoT devices face in the healthcare industry. In the medical field, it is important to securely transfer critical data such as medical images and Electronic Health Records (EHRs) between cloud-based services and IoT devices.. The use of IoT in the healthcare sector is very widespread, but many companies are not aware of the security vulnerabilities of these devices, which affects encryption and authentication. In ensuring the secure transmission of data, the security, authentication, and identity management requirements of these devices are often not met by traditional IoT health solutions. To enhance the security of resource-controlled health IoT devices, the study provides a lightweight encryption solution. For effective encryption and decryption, we use the ASCONv 1.2 encryption algorithm. The relevance of ASCONv 1.2's resource limits can be further improved by optimizing the number of keys and other parameters using the Hypercube Optimal Search Algorithm (HOS). By using the Modified Wild Keys (MWG) algorithm, we have improved local and global search capabilities and improved the resource efficiency of medical IoT devices. Compared with conventional encryption methods, experimental analysis shows that this approach increases reliability by 16.859% and reduces processing time by 15.36%. Peak Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE), Bit Error Ratio (BER), and structural similarity index are performance evaluation indicators that guarantee our model operates at its best.
Combined Cognitive and Motor Training Improves Reading, Writing and Motor Capabilities in Dyslexic Children
Authors: Ben Dhia Amal , Bucci Maria-Pia , Naffeti Chokri , Helmi Ben Saad , Hammouda Omar , Driss Tarak
Published: January 2025

Abstract: Background/Objectives: Different strategies were proposed to enhance dyslex-ic children’s performance. This study aimed to investigate the effect of a combined cog-nitive and motor training on reading, writing and motor coordination in dyslexic chil-dren. Methods: Twenty-four children with dyslexia (9.33±0.48 years) were randomly al-located to either a control (CG, 9.25±0.45 years, n=12) or a trained group (TG, 9.42±0.51 years, n=12). The intervention lasted eight weeks with a pre/post measurement (∆) de-sign in each group. It consisted of a combined cognitive and motor program composed of two 45-min sessions per week in TG. Reading and writing capabilities were measured using the letter reading task based on the French battery (BALE), and word dictation task, inspired from ODÉDYS-2 French battery, respectively. The visuospatial orientation and the upper limb coordination parameters were evaluated by judgment of line orienta-tion test and Bruininks-Oseretsky test of motor proficiency, second edition, short form test, respectively. Results: Two-way ANOVA for repeated measures showed no signifi-cant difference between CG and TG in pre-intervention in all tests. Reading (p
Forecasting Wind Speed Using Simulation Models and Climate Variables
Authors: Couto Rafael Araujo , Maçaira Paula , Cyrino Oliveira Fernando Luiz
Published: January 2025

Wind energy in Brazil has been steadily growing, influenced significantly by climate change. To enhance wind energy generation, it is essential to incorporate external climatic variables into wind speed modeling to reduce uncertainties. Periodic Autoregressive Models with Exogenous Variables (PARX), which include the exogenous variable ENSO, are effective for this purpose. This study modeled wind speed series in Rio Grande do Norte, Paraíba, Pernambuco, Alagoas, Sergipe, Rio Grande do Sul, and Santa Catarina, considering the spatial correlation between these states through PARX-Cov modeling. Additionally, the correlation with ENSO indicators was used for out-of-sample prediction of climatic variables, aiding in wind speed scenario simulation. The proposed PARX and PARX-Cov models outperformed the current model used in the Brazilian electric sector for simulating future wind speed series. Specifically, the PARX-Cov model with the Cumulative ONI index is most suitable for Pernambuco, Rio Grande do Sul, and Santa Catarina, while the PARX-Cov with the SOI index is more appropriate for Rio Grande do Norte. For Alagoas and Sergipe, the PARX with the Cumulative ONI index is the best fit, and the PARX with the Cumulative Niño 4 index is most suitable for Paraíba.
Message from the Winners
Authors:   Editorial Office
Published: January 2025

Message from the Winner, Norio Maki

Message from the Winner, T. Sontayasara, S. Jariyapongpaiboon, A. Promjun, N. Seelpipat, K. Saengtabtim, J. Tang, and N. Leelawat

Message from the Winner, Miho Ohara

Message from the Winner, Hisaya Sawano

Message from the Winner, Reo Kimura
Motivations for Voluntary Migration to Hulhumalé in the Context of Climate Change
Authors: Maekawa Miko , Raheem Raheema Abdul , Khalid Adam , Sakamoto Akiko , Nakayama Mikiyasu , Sasaki Daisuke , Okaniwa Hisayo
Published: January 2025

The voluntary migration to Hulhumalé, an artificial island in the Maldives, presents a unique context for studying the impacts of internal migration on life satisfaction. This study aims to identify measures that the Maldivian government could implement to mitigate migration impacts and enhance life satisfaction in Hulhumalé. A recent survey conducted in the four atolls with Maldives National University (MNU) campuses—Kulhudhuffushi, Gan, Hithadhoo, and Thinadhoo—yielded 398 responses, proportionate to their populations. The questionnaire, administered in person by MNU enumerators between December 2023 and January 2024, mirrored the 2022 Hulhumalé survey, focusing on demographics, migration attitudes, and expectations of Hulhumalé. A 2022 survey of Hulhumalé residents revealed disparities in life satisfaction between those who relocated from Malé and those from other atolls. The results from 2024 survey highlight the fact that good facilities, including dining, shopping, sports, and parks, are highly regarded factors driving migration, albeit with the trade-offs of high living expenses, rent, and other housing costs. High-quality primary and higher education, along with access to medical care, were also positively rated. However, aspects related to disaster resilience and safety against sea level rise due to climate change were rated lower.
Climate Change Adaptation Strategies and Economic Challenges in Atoll Nations: A Case Study of the Republic of the Marshall Islands
Authors: Ishiwatari Mikio , Maekawa Miko , Fujikura Ryo
Published: January 2025

Climate change poses an existential threat to small island developing states, particularly atoll nations like the Republic of the Marshall Islands (RMI). This study examines the economic and financial challenges of implementing climate change adaptation measures in these vulnerable countries. Through a comprehensive literature review and a case study of the RMI, the costs and feasibility of various adaptation strategies, including coastal protection, land raising, and migration, were analyzed. Findings reveal that the financial requirements for effective adaptation far exceed the economic capacities of the RMI. Even basic protective measures require investments multiple times the country’s gross domestic product. The benefit-cost ratios of adaptation projects fall below 1 when evaluated solely on disaster risk reduction, highlighting the need for a paradigm shift in assessing adaptation investments in highly vulnerable nations. This study underscores the critical importance of international climate finance and support. While the RMI has received significant climate development finance, the scale of required adaptation measures far surpasses this level of assistance. The key challenges included not only debt sustainability concerns but also traditional land tenure systems, ecological impacts, and the limitations of conventional cost-benefit analyses in the context of national survival. This study offers valuable insights for policymakers, international organizations, and researchers working on climate resilience in vulnerable coastal nations.
Unilateral Biportal Endoscopic Management of Cement Leakage After Cement-Augmented Pedicle Screw Fixation: A Technical Report
Authors: Moon Kihyun , Kim Jung Sug , Kim Won Joong
Published: January 2025

With the growth of the population of older adults, cement-augmented pedicle screws (CAPS) have become more commonly employed. Although CAPS are considered safe, cement leakage can occur, leading to complications. Neurological symptoms resulting from bone cement leakage pose significant challenges in both diagnosis and treatment. Unilateral biportal endoscopy (UBE) offers a minimally invasive solution for these issues. UBE enables a thorough exploration of potential compression sites, allowing precise visualization of the entire nerve roots without necessitating removal of the instrument or compromising spinal stability. Additionally, it facilitates the removal of cement fragments under direct vision. Herein, we present the case of an 84-year-old female patient who underwent endoscopic interbody fusion of L4–5. After surgery, she presented with radiating pain in the right lower extremity. Postoperative magnetic resonance imaging indicated indirect evidence of cement leakage under the right L5 pedicle screw. The patient underwent UBE exploration under spinal anesthesia. During the procedure, the cement fragment was detected and removed without complication. UBE can also be performed under local or regional anesthesia, significantly reducing the anesthetic risk for medically fragile individuals. Using UBE, it is also possible to monitor neurological function while manipulating the neural tissue. UBE is a viable option for both the diagnosis and treatment of cement leakage following CAPS placement.
Unilateral Biportal Endoscopic Discectomy for Upper Thoracic Herniated Discs (T1–2): A Case Report and Technical Notes
Authors: Hahn Bang-Sang , Park Choon Keun , Hwang Jin Sub , Cho Yong-Eun , Jang Jae-Won , Lee Dong-Geun
Published: January 2025

This report presents 2 cases of T1–2 disc herniation managed with unilateral biportal endoscopic (UBE) discectomy. Both patients experienced severe arm pain and neurological impairments due to paracentral disc herniations at the T1–2 level, prompting UBE discectomy. The procedures were completed without complications, leading to substantial pain relief and neurological improvement. No symptom recurrence was observed for up to 27 months postoperatively. These cases highlight that, with appropriate indications and refined techniques, UBE discectomy is a feasible and effective surgical approach for T1–2 disc herniation, offering precise visualization and a secure operative field. Further experience and research may solidify the role of this procedure in treating upper thoracic spine lesions.
Minimally Invasive Strategy for Uniportal Full-Endoscopic Transforaminal Lumbar Interbody Fusion Using a Large Cage Utilized in Oblique Lumbar Interbody Fusion
Authors: Ma Hyun-Jin , Lee Sang Ho , Park Chan Hong
Published: January 2025

A spine endoscope can be used for lumbar interbody fusion, and endoscopic spinal surgery has various advantages over conventional open surgery. With just one small incision, uniportal full-endoscopic surgery can be the most minimally invasive approach. This technique can minimize intraoperative tissue damage, but the working space is very narrow, making it challenging to insert a large cage and posing a dilemma for an additional large skin incision. The anterior approach for lumbar interbody fusion, particularly oblique lumbar interbody fusion (OLIF), has advantages, such as a wider fusion bed and a large supportive cage, potentially increasing the fusion rate and reducing the risk of cage subsidence. Furthermore, OLIF cages can provide robust support to the apophyseal ring of the vertebral body. An elliptical skin incision is performed to expand the usable area for inserting a large cage and pedicle screw. We aimed to introduce a minimally invasive technique for inserting a large OLIF cage during uniportal full-endoscopic transforaminal lumbar interbody fusion through a single small incision measuring 1.8–2 cm, which could facilitate minimal tissue damage and maximal fusion rate by combining the advantages of endoscope and anterior fusion surgery.
Unilateral Biportal Endoscopy-Assisted Thoracic Interbody Cage Insertion for the Treatment of Proximal Junctional Failure
Authors: Kim Hun-Chul , Lee Jin Young , Cho Hyeon Guk , Park Jeong Woo , Han Sang-Ho , Ko Young-Il
Published: January 2025

In the thoracic spine, when disc herniation causes cord compression in the anterior region, it is difficult to access the disc space. When using the unilateral biportal endoscopy (UBE) technique, the disc can be accessed from various angles with minimal damage to normal tissue. We performed cage insertion using UBE when treating a patient with thoracic myelopathy due to proximal junctional failure in the thoracic spine. A 77-year-old woman with prior spinal fusions and recent proximal junctional kyphosis presented with myelopathy. The patient first visited our hospital due to gait instability and decreased muscle strength that had occurred 2 months previously. The imaging findings confirmed cord compression due to disc herniation at the T10–11 level. Interbody fusion was performed at the T10–11 level using the UBE technique, and fusion was performed up to the T8 level. UBE offers a viable alternative to traditional approaches in thoracic spinal surgery, providing improved visualization and reducing pulmonary complications. This technique, combined with open surgery, effectively addresses the challenges of thoracic interbody cage insertion, demonstrating its potential to overcome the limitations of conventional methods.
Investigating molecular mechanisms in ischemic preconditioning-induced resiliency to severe acute global cerebral ischemia using a mouse model of chronic cerebral hypoperfusion
Authors: Kushwaha Roli , Patel Shashikant , KS Yuvaraj , Sharma Pooja , Kumar Arvind , Chakravarty Sumana
Published: January 2025

Cerebral ischemic preconditioning offers a promising strategy to enhance resilience to severe ischemic insults. Unilateral common carotid artery occlusion (UCCAo) is a valuable model to simulate chronic cerebral hypoperfusion (CCH). This study explored UCCAo induced CCH as a preconditioning stimulus to induce ischemic tolerance against transient global cerebral ischemia (tGCI) induced by bilateral common carotid artery occlusion (BCCAo) in both male and female mice. We evaluated the effects of CCH preconditioning on neuroprotection and recovery through behavioral, histopathological, and molecular analyses. Laser Doppler Imaging (LDI) confirmed significant cerebral hypoperfusion post-UCCAo. Preconditioning reduced mortality rates at day 1 and 7 post surgery as compared to BCCAo, suggesting its neuroprotective potential. Neurodeficit scoring demonstrated significant protection in preconditioned animals with recovery aligning closer to sham controls. Behavioral assays revealed improved motor and cognitive outcomes in preconditioned groups, with sex-specific differences evident in recovery dynamics. Molecular analyses indicated reduced reactive astrocyte (GFAP) and microglial (IBA1) activation in preconditioned animals, reflecting controlled glial responses. Sex-dependent variations in markers of hypoxia (Hif1a), autophagy (Becn1) and neurogenesis (Sox2) highlighted neuroadaptive and cellular influences on ischemic resilience. Preconditioning enhanced synaptic plasticity by upregulating PSD-95, synaptophysin and BDNF levels. Additionally, preconditioning increased VEGF expression in blood serum reflecting vascular remodeling and neuroprotective angiogenesis. This study positions UCCAo induced CCH as a reliable model for exploring ischemic tolerance mechanisms to advance therapeutic strategies for mitigating the effects of ischemic stroke.
A Bibliometric Analysis of Online Education Research in India (2014-2024): Trends, Patterns, and Future Directions
Authors: Alrefaee Sara , Khan Mahlaqa , Alrefaee Yasser M. H. Ahmed
Published: January 2025

This study presents a comprehensive bibliometric analysis of online education research in India from 2014 to 2024, examining 1,396 Scopus-indexed publications to map the field's intellectual structure and evolution. Using advanced bibliometric techniques and visualization tools, we analyze publication patterns, institutional contributions, thematic developments, and international collaboration networks. The findings reveal significant growth in research output (11.94% annual growth rate) with a distinctive surge during 2020–2022, demonstrating both crisis response to the COVID-19 pandemic and sustained transformation in research priorities. Medical institutions emerge as unexpected research leaders, with the All India Institute of Medical Sciences contributing the highest number of publications (45). The analysis identifies three major research clusters: core educational technology (25% coverage), stakeholder focus (13%), and emerging technologies (6%). International collaboration patterns show moderate global engagement (15.69% co-authorship rate), with strong ties to Western institutions but limited South-South cooperation. Thematic analysis reveals evolution from basic implementation studies to sophisticated investigations of artificial intelligence and student-centered approaches. Citation analysis demonstrates high impact of pandemic-related research, with papers from 2020–2021 achieving exceptional citation rates. The study also identifies significant research gaps, particularly in rural and resource-constrained educational contexts. These findings provide valuable insights for researchers, policymakers, and practitioners while highlighting opportunities for future research directions in Indian online education.
Exceptional High-temperature Strength in an Additively Manufactured Al-based Superalloy with Stable Nanoscale Eutectic Cellular Network
Authors: Chen Zhe , Ma Siming , Fang Haixing , Ji Gang , Wang Mingliang , Cui Yuchi , Li Yang , Zhong Shengyi , Chen Han , Wu Yi , Zhou Ying , Nie Shixin , Lu Jian
Published: January 2025

Metallic materials typically experience significant strength degradation at elevated temperatures. Traditional strengthening methods, which rely on thermally stable particle dispersion, exhibit limited effectiveness owing to the challenges in suppressing thermally activated dislocation motion. This work introduces a novel strategy for achieving exceptional high-temperature strength through a thermally stable nanoscale eutectic cellular network (ECN) enabled by additive manufacturing. A near-eutectic AlLaScZr alloy is developed for laser powder bed fusion, incorporating an Al-La nanoscale ECN and dense intracellular nanoprecipitates. This alloy demonstrates excellent printability and remarkable high-temperature yield strength above 0.6Tm (~ 250 MPa at 300°C), outperforming conventional aluminium alloys by 2–5 times with minimal degradation after prolonged annealing. Compared with the conventional configuration of particle dispersion, the nanoscale ECN architecture enhances load-bearing capacity and strengthens aluminium by caging dislocation motion within ultrafine cells (~ 200 nm), effectively mitigating intrinsic high-temperature softening. The proposed transformative approach paves the way for designing next-generation heat-resistant alloys, unlocking new possibilities for additive manufacturing in high-temperature applications.
Research on Feature Scheduling Aggregation Clustering Model Based on Convolutional Neural Networks
Authors: Jiao Yu
Published: January 2025

This paper proposes a feature scheduling aggregation clustering model based on Convolutional Neural Networks (CNN), aiming to enhance the performance of clustering tasks using deep learning techniques. The model integrates the automatic feature extraction capability of CNN, the adaptive adjustment of feature scheduling, and the multi-band information integration of feature aggregation, thereby capturing the complex structures and subtle differences in data. Experimental results demonstrate the superiority of the model compared to existing algorithms and show good generalization ability. The model can effectively improve the effectiveness of cluster analysis, providing a new deep learning solution for data analysis.
Prolonged ICU Stay After Coronary Revascularization: Development and Validation of a Predictive Model
Authors: Agámez Diana Marcela Acosta , García Naiby Yulieth Liscano , Quintín María José Nieto , Rodríguez Brenda Yulieth González , Rodríguez Edith Elianna , Lima David Rene Rodriguez
Published: January 2025

Cardiac artery bypass grafting (CABG) is a common cardiac procedure with standardized postoperative intensive care unit (ICU) management. However, prolonged ICU stays increase complications, costs, and reduce service efficiency. We developed a prediction model for prolonged ICU stays in CABG patients based on a retrospective cohort. Prolonged ICU stay was defined as a stay of ≥ 7 days. Demographic data, laboratory results, and complications during the first 48 hours of ICU admission were analyzed. For the prediction model, variables with p < 0.25 in the univariate analysis were selected, followed by backward stepwise selection (significance level = 0.1). Interaction terms and fractional polynomials were evaluated, and bootstrapping was applied for external validation. Model performance was assessed using logistic regression diagnostics, ROC curve analysis (AUC), and calibration. The adjusted model equation was g(x) = age (0.0357) + left ventricular ejection fraction (LVEF) (-0.040) + perfusion time (0.0082) + hypothyroidism (0.754) + postoperative renal failure (1.653) + reoperation due to bleeding (1.885) + postoperative cerebrovascular event (1.287) + postoperative acute myocardial infarction (1.163) and the probability of in-hospital death was p (x) = e g (x)/(1 + e g (x)). The AUC of the ROC curve was 0.7671 (95% CI 0.7161 and 0.8066).