bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimized Machine Learning for Insurance Cost Prediction
Authors: sheza abdul subhan fnu
Published: February 2025

Machine learning (ML) is becoming more common in the insurance industry to predict costs and help set prices. Accurate predictions help insurance companies set fair prices while keeping insurance affordable for customers. However, many ML models are difficult to understand, making it unclear how they make decisions. This study focuses on improving prediction accuracy and making models easier to interpret by using hyperparameter tuning with Optuna and feature importance analysis with SHAP (SHapley Additive Explanations). Three models—Ridge Regression, Random Forest, and XGBoost—were optimized and tested. The results show that XGBoost performed the best, with a median Rsquared of \textbf{0.8655} and RMSE of \textbf{4136.59}. SHAP analysis found that \textbf{smoking status, BMI, and age} were the most important factors affecting insurance costs. These findings show that using both model tuning and explainability tools helps improve ML models for insurance pricing.
Power Frequency Breakdown Properties of LDPE-Doped Inorganic Nanoparticles
Authors: Yujia Yujia , Yu Guang
Published: February 2025

Although polyethylene is widely used in electrical insulation, it does not possess dielectric properties. It is therefore desirable to develop insulation materials with excellent dielectric properties. In this study, low density polyethylene (LDPE) was used as a matrix resin, while MgO, wollastonite, and montmorillonite (MMT) were employed as inorganic nano-additives. Three composites were prepared using the boiling–melt blending approach. Power frequency breakdown tests were performed on the original LDPE and on the prepared nanoparticle/LDPE composites. Upon combination with the Weibull distribution, the breakdown test results revealed that the addition of these nano-additive particles to the LDPE matrix decreased the breakdown field strength of the material. The highest breakdown field strength for the nano-MgO/LDPE composite was obtained using a MgO loading of 0.5%. Notably, the obtained value was 1.8% higher than that of the pure LDPE. In addition, the highest breakdown field strength for the nano-wollastonite/LDPE composite was obtained using a wollastonite loading of 1% (7.48% higher than that of pure LDPE). Similarly, the highest breakdown field strength of the nano-MMT/LDPE composite was obtained using an MMT loading of 3%, giving a value that was 6.67% higher than that of the pure LDPE.
Artificial Intelligence-Enabled Text-to-Music Generation: A Comprehensive Review of Methods, Frameworks, and Future Directions
Authors: Zhao Yujia , Yang Mingzhi , Lin Yujia , Zhang Xiaohong , Shi Feifei , Wang Zongjie , Ding Jianguo , Ning Huansheng
Published: February 2025

Text-to-music generation integrates natural language processing and music generation, enabling artificial intelligence (AI) to compose music from textual descriptions. While AI enabled music generation has advanced, challenges in aligning text with musical structures remain under explored. This paper systematically reviews text-to-music generation across symbolic and audio domains, covering melody composition, polyphony, instrumental synthesis, and singing voice generation. It categorizes existing methods into traditional, hybrid, and LLM-centric frameworks according to the usage of large language model (LLM), highlighting the growing role of LLMs in improving controllability and expressiveness. Despite progress, challenges such as data scarcity, representation limitations, and long-term coherence persist. Future work should enhance multi-modal integration, improve model generalization, and develop more user-controllable frameworks to advance AI-enabled music composition.
Integrating Forest Succession Modeling and a Physics-Based Fire Behavior Model to Support Long-Term Prescribed Fire Management
Authors: Tutland Niko , Cope Zachary , Flanagan Steven , Atchley Adam , Robbins Zachary , Loudermilk E. Louise
Published: February 2025

Background: Fire modeling is a key prescribed fire planning tool, but there are limited operational tools for integrating current models of forest change and fire behavior.AimsWe sought to integrate a widely used forest succession model, LANDIS-II, with a powerful fire behavior model, QUIC-Fire, into a flexible workflow for assessing fire behavior in projected future fuel conditions. MethodsUsing aboveground biomass, we matched LANDIS-II data to cohorts of trees in Forest Inventory and Analysis (FIA) data by predicting tree age across all FIA data using Random Forest modeling. We then voxelized those tree crowns along with surface fuels to create 3D fire model inputs. Key ResultsWe presented L2-QF, a novel crosswalk methodology between cohort-based LANDIS-II successional outputs and individual tree characteristics to create three-dimensional fuel arrays for QUIC-Fire. We demonstrated L2-QF by modeling forest change through time in multiple climate and management scenarios, then used the projected future fuel conditions to model fire behavior and effects.ConclusionsL2-QF can be used by fire practitioners to inform adaptive management, as highlighted by our workflow demonstration. ImplicationsBy integrating long-term ecosystem changes into everyday fire planning, L2-QF allows fire managers to stay proactive in variable future conditions.
Arthropod‐Borne Parasitic Diseases in Africa: Prevalence, Diversity, and the Risk of Re‐Emergence
Authors: Ahmed Ayman , Siddig Emmanuel Edwar , Mohamed Nouh Saad
Published: February 2025

Vector-borne parasitic diseases represent a critical public health challenge in Africa, disproportionately impacting vulnerable populations and linking human, animal, and environmental health through the One Health framework. In this review we explore the epidemiology of these diseases, particularly those that are underreported and highlight the complex transmission dynamics involving domestic and wild animal hosts. Climate change, urbanization, and deforestation exacerbate the emergence and reemergence of arthropod-borne parasitic diseases like malaria, leishmaniasis, and trypanosomiasis, complicating control and disease elimination efforts. Despite progress in managing certain diseases, gaps in surveillance and funding hinder effective responses, allowing many arthropod zoonotic parasitic infections to persist unnoticed. The increased interactions between humans and wildlife, driven by environmental changes, heighten the risk of spillover events. Leveraging comprehensive data on disease prevalence, distribution, and vector ecology, coupled with a One Health approach, is essential for developing adaptive surveillance systems and sustainable control strategies. This review emphasizes the urgent need for interdisciplinary collaboration among medical professionals, veterinarians, ecologists, and policymakers to effectively address the challenges posed by vector-borne parasitic diseases in Africa, ensuring improved health outcomes for both humans and animals.
Cardiac Adverse Events Post Vaccination
Authors: Ricke Darrell
Published: February 2025

Some vaccinees experience cardiac adverse events (AEs) following immunization (AEFI). These AEs include both background events and for some vaccines, vaccine associated AEs. A small subset of AEs experienced by vaccinees are reported to the United States Vaccine Adverse Event Reporting System (VAERS). Herein, VAERS was retrospectively examined to identify cardiac AEFI associations. VAERS data was examined by vaccine type, vaccine source, vaccinee gender, and vaccinee age for infants. Multiple cardiac AEFI association patterns were detected: bradycardia and cardiac arrest for infants age 0, arrhythmia for COVID-19 and HPV vaccines, atrial fibrillation for COVID-19, influenza, and RSV vaccines, myocarditis and pericarditis for anthrax, COVID-19, smallpox, and typhoid vaccines, and chest discomfort, chest pain, palpitations, and tachycardia for multiple vaccines. Gender differences were observed for both myocarditis and palpitation AEFIs. Significant differences in bradycardia and cardiac arrest AEFI normalized frequencies were observed for the same infant vaccines from different manufacturers, suggesting possible manufacturing contaminants (e.g., endotoxins, DNA) as candidate causative components. Conclusions: Infant bradycardia and cardiac arrest AEFIs could be reduced by either delaying specific vaccines until infants are 1 year of age, selecting alternative vaccine options, or reduction or elimination of causative components (e.g., aluminium adjuvant, manufacturing contaminates, etc.). Both male and female myocarditis AEs can be modelled by mathematical age relationships for COVID-19 vaccines that may also apply to additional vaccines, suggesting possible shared etiologies. Multiple vaccines were observed with correlated cardiac AEFIs association signals for chest discomfort, chest pain, palpitations, and tachycardia; elevated histamine levels may contribute to the etiologies of these AEFIs.
Honokiol Mitigates Ionizing Radiation-Induced Injury by Maintaining the Redox Balance of the TrxR/Trx System
Authors: Chen Yaxiong , Shen Ruipeng , Xu Dan , Wu Qingfeng , Zhang Junmin , Fang Jianguo
Published: February 2025

Ionizing radiation like X-rays or heavy ions can induce cellular oxidative stress and damage due to the production of reactive oxygen species. The TrxR/Trx system has a considerable impact on maintaining body redox homeostasis and against cell oxidative damage. In this paper, we described the potential of one natural small molecule, Honokiol (HKL), to repair radiation damage in vivo and in vitro. Pretreatment with HKL significantly protected cell viability and decreased cellular damage, as confirmed by the results of MTT assay, colony formation assay, micronucleus test, and γ-H2AX immunofluorescence analysis. Western blot experiments showed that HKL could mediate the oxidative imbalance of the TrxR/Trx system induced by ionizing radiation. The protective effect of HKL might be associated with regulating the TrxR/Trx system, evidenced by silencing TrxR expression with shRNA. Additional co-culture assays provided evidence that the HKL-precondition might attenuate the ionizing radiation-induced bystander effect. In vivo, studies showed that HKL would improve action against the lung cell tissue of the irradiated mice and prolong mouse survival. The findings indicated that HKL is a potential radioprotective agent that preserves the redox homeostasis of the TrxR/Trx system. Overall, the findings presented here demonstrate that HKL has the potential to be a novel radioprotector capable of cellular protection against radiation-induced injuries. These discoveries hold critical significance for both cancer radiotherapeutics and space radiation protection protocols.
Secure Communications for UAV Relay Networks: A MPC-Based Trajectory Tracking Approach
Authors: Lan Shizhan , Zhong Lei , Tan Bin , Liang Yeyu , Chen Shan , Xie Hanghang
Published: February 2025

Unmanned aerial vehicles (UAVs) have emerged as a promising solution to enhance communication networks, especially in scenarios where traditional infrastructure is impractical or unavailable. However, the reliance on line-of-sight (LoS) channels in UAV-assisted relay networks introduces significant security vulnerabilities. This paper proposes a novel framework that jointly optimizes transmit power and UAV trajectory to achieve secure communications in such networks. To enhance system performance against environmental uncertainties, we employ a model predictive control (MPC)-based approach, which allows for real-time adaptive control of the UAV’s trajectory by considering future states and disturbances. This approach significantly improves the network’s resilience to dynamic environments and potential eavesdropping threats. Simulation results show that the proposed joint optimization of power allocation and trajectory design not only enhances communication security but also demonstrates the effectiveness of the MPC framework in real-time trajectory tracking, ensuring robust performance under varying environmental conditions.
Unraveling The Mystery of Insulin Resistance: From Principle Mechanistic Insights and Consequences to Therapeutic Interventions
Authors: Mir M Muzaffar , Jeelani Mohammed , Alharthi Muffarah Hamid , Rizvi Syeda Fatima , Sohail Shahzada Khalid , Wani Javed Iqbal , Sabah Zia UL , BinAfif Waad Fuad , Nandi Partha A. , Alshahrani Abdullah M. , Alfaifi Jaber , Jehangir Adnan , Mir Rashid
Published: February 2025

Insulin resistance (IR) is a significant factor in the development and progression of metabolic-related diseases like dyslipidemia, T2DM, hypertension, nonalcoholic fatty liver disease, cardiovascular and cerebrovascular disorders and cancer. The pathogenesis of IR depends on multiple factors including age, genetic predisposition, obesity, oxidative stress and other factors. Abnormalities in the insulin signaling cascade lead to IR in the host, including insulin receptor abnormalities, internal environment disturbances, and metabolic alterations in the muscle, liver and cellular organelles. The complex and multifaceted characteristics of insulin signaling and insulin resistance envisage its thorough and comprehensive understanding at the cellular and molecular level. Therapeutic strategies for IR include exercise, dietary interventions and pharmacotherapy. However, there are still gaps to be addressed, and more precise biomarkers for associated chronic diseases and lifestyle interventions are needed. Understanding these pathways is essential for developing effective treatments for IR, reducing healthcare costs and improving quality of patient life.
Energy-Efficient Computing and Circular Design: Paving the Way for Sustainable Digital Innovation
Authors: William Barnty , Mabel Emmanuel
Published: February 2025

This research investigates the role of energy-efficient computing and circular design practices in driving sustainable digital innovation. As the global demand for digital technologies continues to rise, the environmental impact of energy consumption and e-waste has become a pressing concern. This study aims to explore how adopting energy-efficient computing strategies and circular design principles can reduce environmental impact while enhancing economic performance within the technology sector. Using a mixed-methods approach, the study analyzes data from 10 technology companies that have implemented these practices, with a combination of quantitative surveys and qualitative interviews to gather insights on energy usage, e-waste reduction, and cost savings. The key findings reveal that companies adopting energy-efficient computing have achieved an average 28% reduction in energy consumption, while those utilizing circular design principles reduced e-waste by 33%. Furthermore, 70% of the companies reported significant cost savings, reinforcing the financial benefits of sustainability initiatives. The study concludes that energy-efficient computing and circular design are not only essential for reducing environmental impact but also provide significant economic advantages. It recommends that technology companies prioritize these practices to foster innovation, improve sustainability, and increase competitiveness in a rapidly evolving market. Additionally, the research highlights the need for supportive regulatory frameworks to facilitate the widespread adoption of sustainable practices in the digital technology sector.
Uranium Mineral Particles Produced by Weathering in Sierra Peña Blanca, Chihuahua, Mexico: A Synchrotron-Based Study
Authors: Hernández-Herrera Cristina , Canché-Tello Jesús G. , Rodríguez-Guerra Yair , Faudoa-Gómez Fabián G. , Ignatyev Konstantin , Eichert Diane M. , Cabral-Lares Rocío M. , Pérez-Reyes Victoria , Esparza-Ponce Hilda E. , Montero-Cabrera María-Elena
Published: February 2025

Some of the largest uranium deposits in Mexico are located in Chihuahua. The most important is in Sierra Peña Blanca, northwest of the capital, which was explored and partially exploited in the 1980s. After the closure of activities, the mining projects were left exposed to weathering. To characterize the drift of uranium minerals towards the neighboring Laguna del Cuervo, sediment samples were collected in the main streams in the drainage pattern of the largest deposits. The uranium mineral fragments from the fine sand portion were extracted using fluorescence at 365 nm light. These particles' morphology and elemental composition were analyzed by focused ion beam microscopy (FIB) and scanning transmission electron microscopy (STEM). The particle density in samples close to the uranium sources was quantified using gamma spectrometry. The highest density was 2500 part./g, and the lowest was 124 part./g. X-ray absorption spectrometry (XAFS) allowed to establish the speciation of U in the urani-um particles, confirming U(VI) through the XANES spectrum. Theoretical fitting of the EXAFS spectrum confirmed the presence of uranophane. Finally, the Fe, Sr, and U dis-tribution in the particle and its matrix was obtained by X-ray fluorescence microto-mography (CT-µXRF). It was concluded that the particle is composed of uranophane, imbricated with quartz and other oxides.
Epigenetic and Gene Expression Responses in Daphnia magna to Polyethylene and Polystyrene Microplastics
Authors: Im Hyungjoon , Lee Jieun , Oh Jeong-Eun , Song Jinyoung , Jeong Sanghyun
Published: February 2025

Microplastics (MPs), ubiquitous environmental pollutants, pose substantial threats to aquatic ecosystems and organisms, including the model species Daphnia magna. This study examined the effects of polyethylene (PE) and polystyrene (PS) MPs on D. magna, focusing on ingestion, epigenetic alterations, and transcriptional responses. Exposure experiments revealed a concentration-dependent accumulation of MPs, with PS particles showing higher ingestion rates due to their higher density and propensity for aggregation. Epigenetic analyses demonstrated that exposure to PE MPs significantly reduced global DNA methylation (5-mC), suggesting hypomethylation as a potential stress response. Conversely, DNA hydroxymethylation (5-hmC) displayed variability under PS exposure. Transcriptional analysis identified a marked downregulation of Vitellogenin 1 (v1) and upregulation of Ecdysone Receptor B (ecr-b), highlighting stress-related and adaptive molecular responses. These findings enhance our understanding of the molecular and epigenetic effects of MPs on aquatic organisms, offering critical insights for developing effective environmental management and conservation strategies in the face of escalating MP pollution.
The Universe Is a Black Hole Hubble Sphere Carnot Engine Operating at the CMB Temperature Off: T_cmb = Sqrt(Tmax*Tmin) ≈ 2.725K
Authors: Haug Espen  Gaarder
Published: February 2025

Haug has recently suggested that the extremal solution to the Reissner-Nordström metric can be used for black hole cosmology. While the Bekenstein-Hawking entropy is related to the surface area in a Schwarzschild black hole, an extremal black hole has zero net entropy. We will demonstrate how the extremal universe Hubble sphere is likely a Carnot engine and how this helps us derive a formula for the CMB temperature now T_cmb = Sqrt(Tmax*Tmin) ≈ 2.725K. This unlike the Lambda-CDM model, which cannot predict the CMB value at present.
Coherent Manipulation and Magnitude of Optical Force in Chiral Medium
Authors: Hussain Iqbal , Ali Asghar , Alarifi Nassir , R.Abukhadra Mostafa , Choi Jeong Ryeol
Published: February 2025

The study investigate control of the optical force and its modification with variation of the driving field’s strength in the system levels of the chiral medium for left and right circular polarized light. In addition to orbital and magnetic and spin quantum numbers of applied fields, significant vector field arrows of optical force in chiral media are examined using spatial coordinates, detuning , Rabi frequency and decay rates. The parameters of the probe and control fields’ detuning along with their decay rates and phases are provided to determine the optical force in chiral medium both for left and right circularly polarized fields. The optical force is a function of orbital, magnetic and spin quantum numbers. Using phase, detuning, and Rabi frequency of the control fields as variables, the minimum value of optical force measure is 0.003pN for probe detuning and spatial coordinate while the maximum value of optical force for normalized detuning and transverse radial coordinate is measured to be 0.2pN. Potential uses of optical force in fundamental optics, molecular physics, optomechanics, material science, nanoscience, quantum physics, radar, waveguide, antennas and optical tweezers technology are demonstrated by the results.
Wheat Yield Prediction Based on Random Forest Method
Authors: Semahegn Yared
Published: February 2025

Crop yield prediction is crucial for enhancing productivity, managing risks, ensuring food security, and improving the overall sustainability of agriculture. This study evaluated the Random Forest (RF) machine learning method for its ability to predict wheat yield responses to climate and soil related factors, with Multiple Linear Regression (MLR) serving as a benchmark. The results revealed that RF outperformed MLR in predicting wheat yield. Mean absolute error (MAE) and root mean squared error (RMSE) were used as evaluation metrics, with RF achieving an MAE of 135.88 and an RMSE of 163.90. In comparison, MLR produced an MAE of 435.74 and an RMSE of 653.39. These findings demonstrate that RF has superior wheat yield forecasting capabilities compared to MLR.
The Resilience Evaluation and Optimization of Primary Healthcare Facilities in Harbin’s Main Urban Area based on Network Analysis
Authors: Sun Ming , Wang Bingbing
Published: February 2025

The development of primary healthcare facilities facilitates a balanced distribution of medical resources, relieving pressure on large hospitals by enhancing these facilities, thus optimizing resource allocation. Such equitable distribution not only improves the accessibility and fairness of healthcare services, but also supports their sustainable growth. This study introduces a spatial resilience framework that evaluates transmission, diversity, and stability from a spatial resilience perspective. Focusing on Harbin's main urban area's primary healthcare facilities, methods such as Gaussian-Based Two-Step Floating Catchment Area (2SFCA), network analysis-based service radius, walking impedance, and overlap analysis are utilized for spatial distribution analysis. Findings indicate significant variance in facility transmission, with Daoli, Nangang, and Xiangfang Districts showing higher accessibility, Songbei and Daowai Districts exhibiting lower transmission. The road network capacity decreases from the urban center towards the periphery in a diminishing pattern. Local Indicators of Spatial Association (LISA) identifies areas with demand-supply mismatches, primarily in northern Xiangfang District and southern Songbei District, while overall spatial connection remains balanced. Based on these findings, we propose strategic enhancements for medical facilities of corresponding levels, offering insights for similar large cities seeking to refine their primary healthcare spatial layout.
Concerning A Transformative Power in Certain Symbols, Letters and Words}
Authors: Lutalo Joseph
Published: February 2025

This paper is a formal distillation of, presentation of and a rigorous, illustrative defense of a couple of fundamental ideas in the domain of computational mysticism --- a still young discipline, put forward by the author for the first time in this manner. The motivations for this work are several, however, the need to support the exploration of science, and especially computer science with spiritual or at least psychological problems in mind, as well as the fact that 21st Century and beyond, humans can't take for granted the fact that interactions with machines and artificial-abstract constructs such as artificial languages and intelligences do or/shall eventually have a tremendous bearing on the psycho-social manifestations of human life across most if not all levels and classes of society, and that we had better understand and prepare for the inevitable before it is too late.
Professional Forecasters vs. Shallow Neural Network Ensembles: Assessing Inflation Prediction Accuracy
Authors: Binner Jane M. , Kelly Logan J. , Tepper Jonathan A.
Published: February 2025

Accurate inflation forecasting is crucial for effective monetary policy, particularly during turning points that demand policy realignment. This study examines the efficacy of Shallow Neural Network Ensemble Models in predicting U.S. inflation turning points more precisely than traditional methods, including the Survey of Professional Forecasters (SPF). We employ monthly data from January 1970 to May 2024, training these ensemble models on information through December 2022 and testing on out-of-sample observations from January 2023 to May 2024. The models generate forecasts at horizons of up to 16 months, accounting for both short- and medium-term dynamics. Results indicate that Shallow Neural Network Ensemble Models consistently outperform conventional approaches using key performance metrics, notably detecting inflation turning points earlier and projecting a return to target levels by May 2024 - several months ahead of the Survey of Professional Forecasters’ average forecast. These findings underscore the value of such ensembles in capturing complex nonlinear relationships within macroeconomic data, offering a more robust alternative to standard econometric methods. By delivering timely and accurate forecasts, Shallow Neural Network Ensemble Models hold great promise for informing proactive policy measures and guiding decisions under uncertain economic conditions.
Child Opportunity Index Predicts Outcomes in Pediatric Spine Trauma: A Novel Application of Socioeconomic Metrics
Authors: Urreola Gabriel , Ortuno Omar , Juma Michael , Castillo Jose
Published: February 2025

Social factors play a crucial role in health outcomes for pediatric patients, yet in the neurosurgery pediatric literature, these factors are rarely reported. To develop a deeper understanding of pediatric spine trauma outcomes we investigate demographic and social factors measured by the Child Opportunity Index (COI) and Social Deprivation Index (SDI). We hypothesize that socioeconomic factors predict clinical presentation, injury severity, and clinical outcomes. Methods: We conducted a retrospective cohort study of pediatric patients treated for spinal trauma at a Level 1 trauma center in Sacramento, California. We collected patient clinical data such as mechanisms of injury (MOI), length of stay (LOS), treatment type, hospital disposition, polytrauma incidence, and follow-up attendance. Each patient’s socioeconomic environment was characterized using COI and SDI metrics. Statistical comparisons were performed to assess associations between socioeconomic factors and clinical outcomes. Results: Patients with lower socioeconomic status (SES) (lower COI and higher SDI) were more likely to be insured through Medi-Cal, identify as Hispanic, and experience violent MOI. Female patients were more likely to sustain polytrauma and had a higher likelihood of requiring surgical intervention. Additionally, patients from underserved communities demonstrated longer hospital stays and poorer follow-up adherence, with COI and SDI scores significantly correlating with these disparities. Conclusion: Socioeconomic disparities are significantly associated with outcomes in pediatric spine trauma. We found COI and SDI to be valuable clinical metrics, motivating further research to be done at a state and national level. These findings highlight health disparities in pediatric spine trauma.
Artificial Intellihence Tools Used In EducationL A Necessity in Today's Modern World
Authors: Abernathy Peter
Published: February 2025

Artificial intelligence (AI) tools have become an essential part of modern education, transforming traditional learning methods and enhancing student engagement. These tools facilitate personalized learning, automate administrative tasks, and provide educators with valuable insights into student performance. This article review talked about the use of AI tools in the modern world of education. The integration of Artificial Intelligence tools in education is not merely a technological advancement but a necessity in today's modern world. By embracing AI, educational institutions can enhance learning experiences, streamline operations, and prepare students for a future where digital literacy is paramount. To fully harness AI’s potential, collaboration between policymakers, educators, and technology developers is essential. Establishing guidelines for ethical AI use, investing in teacher training programs, and ensuring data security are crucial steps toward responsible AI integration in education. Without proper regulation and oversight, AI may widen educational gaps instead of bridging them.
Communication In Globalization Era: A Fundamental Requirement
Authors: Abernathy Peter
Published: February 2025

In the era of globalization, effective communication has become a fundamental requirement for individuals and organizations operating in an interconnected world. This narrative literature review aimed to establish a relationship between communication and the globalization era. Governments and policymakers should also take an active role in bridging communication gaps by improving access to digital infrastructure and promoting regulations that safeguard online interactions. Strengthening international cooperation on cybersecurity, data protection, and media literacy programs can help mitigate the negative impacts of digital communication. These efforts will contribute to a more equitable and responsible global communication landscape. By fostering digital literacy, intercultural understanding, and regulatory support, societies can harness the full potential of global communication while minimizing its challenges. A collaborative approach involving individuals, businesses, and governments is necessary to ensure that communication remains a force for positive global development.
Polyhedral Embeddings of Triangular Regular Maps of Genus g, 1 < g < 15, and Neighborly Spatial Polyhedra
Authors: Bokowski Jürgen , H. Kevin
Published: February 2025

This article provides a survey about polyhedral embeddings of triangular regular maps of genus g, $2 \leq g \leq 14$, and of neighborly spatial polyhedra. An old conjecture of Gr\"unbaum from 1967, although disproved in 2000, lies behind this investigation. We discuss all duals of these polyhedra as well, whereby we accept, e.g., the Szilassi torus with its non-convex faces to be a dual of the M\"obius torus. A numerical optimization approach of the second author for finding such embeddings, was first applied to finding (unsuccessfully) a dual polyhedron of one of the 59 closed oriented surfaces with the complete graph of 12 vertices as their edge graph. The same method has been successfully applied for finding polyhedral embeddings of triangular regular maps of genus g, $2 \leq g \leq 14$. The effectiveness of the new method has led to ten additional new polyhedral embeddings of triangular regular maps and their duals. There does exist symmetrical polyhedral embeddings of all triangular regular maps with genus g, $2 \leq g \leq 14$, except a single undecided case of genus 13.
microRNAs in Type 1 Diabetes: Roles, Pathological Mechanisms, and Therapeutic Potential
Authors: Cho Hayeong , Ha Se Eun , Singh Rajan , Kim David , Ro Seungil
Published: February 2025

Type 1 diabetes (T1D) is a chronic autoimmune disease characterized by the progressive destruction of pancreatic β-cells, leading to insulin deficiency. The primary drivers of β-cell destruction in T1D involve autoimmune-mediated processes that trigger chronic inflammation and ultimately β-cell loss. Regulatory microRNAs (miRNAs) play a crucial role in modulating these processes by regulating gene expression through post-transcriptional suppression of target mRNAs. Dysregulated miRNAs have been implicated in T1D pathogenesis, serving as both potential diagnostic biomarkers and therapeutic targets. This review explores the role of miRNAs in T1D, highlighting their involvement in disease mechanisms across both rodent models and human patients. While current anti-diabetic therapies manage T1D symptoms, they do not prevent β-cell destruction, leaving patients reliant on lifelong insulin therapy. By summarizing key upregulated and downregulated miRNAs in diabetic models and patients, this review discusses the potential of miRNA-based therapies to restore β-cell function and modify disease progression.
The Effect of Fungal Nutraceutical Supplementation on Postoperative Complications, Inflammatory Factors and Fecal Microbiota in Patients Undergoing Colorectal Cancer Surgery with Curative Intent: A Randomized, Placebo-Controlled, Double-Blind Clinical Trial
Authors: Regueiro Cristina , Díez-Martín Astrid Irene , Pérez Sonia , Daviña-Nuñez Carlos , Zarraquiños Sara , Remedios David , Sánchez-Gómez Cristina Alejandra , Alonso-Lorenzo Sara , Fernández-Poceiro Romina , De-Castro-Parga María Luisa , Hernández-Ramírez Vicent , Rodríguez-Blanco Arturo , Sinde Esteban , Fernández-de Ana Catalina , Cubiella Joaquín
Published: February 2025

Background/Objectives: The combination of different fungal extracts could be beneficial to cancer patients due to their role in gut microbiota modulation and anti-inflammatory activity. The study aimed to evaluate whether fungal extract supplementation reduces postsurgical complications in patients with colorectal cancer undergoing curative surgery. Methods: Patients were randomized to receive the nutraceutical Micodigest 2.0 or a placebo until surgery. Surgical complications were evaluated using the Clavien-Dindo classification. We also assessed the effect of the nutraceutical on gut microbiota composition, inflammatory response, nutritional status, and quality of life. A subanalysis based on surgery type (robotic vs. non-robotic) was performed. Results: We included 46 patients who met the inclusion criteria, with 27 randomized to the intervention group and 19 to the placebo group, receiving treatment for 3 [2–4] weeks. Non-robotic surgery was performed in 35 (76.1%) patients. We found non-significant differences in postoperative complications (Micodigest 2.0: 25.9%, placebo: 26.3%; p = 0.9). In non-robotic surgery, we identified a non-significant reduction in postoperative complications (Micodigest 2.0: 25.0%, placebo: 36.4%; p = 0.7), as well as a significant increase in lymphocyte levels and a reduction in the neutrophil-to-lymphocyte ratio (p = 0.02). Micodigest 2.0 supplementation was also associated with significant changes in gut microbiota composition, as indicated by a decreased relative abundance of the phyla Firmicutes (p = 0.004) and Actinobacteria (p = 0.04). Conclusions: Micodigest 2.0 supplementation was associated with non-significant reductions in postoperative complications and significant modifications in gut microbiota composition. Limitations: The trial did not reach the calculated sample size.
Intrinsic Equations and High-Temperature Heat Distortion Behavior of TA4 Alloy
Authors: Ma Lifeng , Liu Wenshuai , Zhu Yanchun , Qin Ling , Zhou Jingfeng
Published: February 2025

In this study, the high-temperature thermal deformation behavior of TA4 alloy was investigated through thermal compression experiments. The effects of deformation temperature and strain rate on rheological stress were analyzed by examining the variations in stress-strain curves under different conditions and establishing a constitutive equation based on the dynamic material theory model. The prediction accuracy of the developed constitutive model was evaluated, yielding a correlation coefficient of 0.9612 between predicted and experimental values, an average absolute percentage error of 8.7210%, and an average root mean square error of 11.0635 MPa. Thermal processing diagrams were established and plotted to analyze the optimal processing zone and the destabilization zone under different strains. The optimal processing zones at different strains are obtained from the thermal processing diagrams, which are 1040~1133K, 0.01~0.7s-1 at a strain of 0.9, 940~1000K, 0.01~0.04 s-1 at a strain of 0.6, 940~1000K, 0.01~0.08s-1 at a strain of 0.3, 940~1000K, 0.01~0.08s-1 at a strain of 0.3. Additionally, the thermal deformation mechanisms of TA4 alloy under varying deformation parameters were analyzed using EBSD characterization. The results indicate that the primary deformation softening mechanisms include dynamic recovery (DRV) at low temperatures and high strain rates, dynamic recrystallization (DRX) at high temperatures and high strain rates, and DRX at low strain rates.
Study of the Structure and Mechanical Properties of Ti-38Zr-11Nb Alloy
Authors: Sergienko Konstantin V. , Konushkin Sergei V. , Morozova Yaroslava A. , Kaplan Mikhail A. , Gorbenko Artem D. , Rumyantsev Boris A. , Prutskov Mikhail E. , Baranov Evgeny E. , Nasakina Elena O. , Sevostyanova Tatiana M. , Mikhlik Sofia A. , Chizhikov Andrey P. , Shatova Lyudmila A. , Simakin Aleksandr V. , Baimler Ilya V. , Sudarchikova Maria A. , Kheifetz Mikhail L. , Kolmakov Alexey G. , Sevostyanov Mikhail A.
Published: February 2025

Hip joint implants are one of the most common types of medical implants used to replace a damaged joint and restore its functional activity. Hundreds of thousands of surgeries are performed annually to install them, which underscores the importance of developing and improving materials for such implants. Modern materials for implants, including co-balt-chromium alloys, stainless steel, titanium and other titanium alloys, face problems such as the toxicity of certain elements (for example, aluminum, vanadium, nickel) and excessive Young's modulus, which negatively affects biomechanical compatibility. A mismatch between the stiffness of the implant material and the bone tissue, called stress shielding, can lead to bone resorption and loosening of the implant. Recent studies have shifted the focus to β-titanium alloys due to their exceptional biocompatibility, corrosion resistance, and low Young's modulus, which is close to the Young's modulus of bone tis-sue (10-30 GPa). Among them, Ti-38Zr-11Nb alloy is promising for use as an implant material. In this study, the microstructure, mechanical properties, and phase stability of Ti-38Zr-11Nb alloy were studied. Energy dispersion spectrometry confirmed the homo-geneous distribution of Ti, Zr, and Nb in the alloy. Microstructural analysis revealed elongated β-grains after rolling and quenching, and grinding contributed to recrystalliza-tion and the formation of subgrains. X-ray diffraction analysis confirmed the presence of a stable β-phase under any heat treatment conditions, which is explained by the use of Nb as a β-stabilizer and Zr as a neutral element with a weak β-stabilizing effect in the pres-ence of other β-stabilizers. The modulus of elasticity after annealing decreased from 85 GPa to 81 GPa. Mechanical tests showed a significant increase in tensile strength (from 529 MPa to 628 MPa) simultaneously with a 32% decrease in elongation to fracture of the samples. These changes are caused by microstructural transformations such as the for-mation of subgrains and rearrangement of dislocations. Based on the results of the study, it can be concluded that Ti-38Zr-11Nb alloy is a promising material due to its lower low Young's modulus relative to the classical materials used and stable β-phase, which pro-vides the possibility of long-term use of the implant, without the risk of formation of brittle phases.
Research on the Construction Method of Inter-Provincial Spot Trading Network Model Considering Power Grid Congestion
Authors: Cui Hui , Huang Guodong , Zhou Jingyang , Hu Chenxu , Zhang Shuyan , Zhang Shaochong , Zhou Bo
Published: February 2025

To address the issues of the current nodal pricing mechanism, which does not incorporate fixed transmission costs and leads to unfair transmission cost allocation, this paper proposes a full-cost electricity pricing model based on power flow tracing technology. By defining full-cost electricity pricing and integrating generation marginal costs with effective transmission costs, the proposed model adheres to the principle of "costs borne by beneficiaries." The effectiveness of the proposed model is validated through case studies on IEEE 30-bus and IEEE 118-bus systems. The results demonstrate that the proposed method can optimize power grid resource allocation and enhance investment efficiency while considering power grid congestion.
Perspective-based Microblog Summarization
Authors: Li Chih-Yuan , Chun Soon Ae , Geller James
Published: February 2025

Social media allows people to express and share a variety of users’ experiences, opinions, beliefs, interpretations, or viewpoints on a single topic. Summarizing a collection of social media textposts (microblogs) on one topic may be challenging and can result in an incoherent summary due to these multiple perspectives by different users. We introduce an approach of microblog summarization based on user perspectives, called Multiple View Summarization Framework (MVSF), a novel approach designed to efficiently generate multiple summaries from the same social media dataset depending on a chosen perspective, delivering personalized and fine-grained summaries. The MVSF leverages component-of-perspective computing that can recognize the perspectives expressed in microblogs, such as sentiments, critical views, political orientations, or unreliable opinions (fake news), etc. The perspective computing can filter social media data to summarize them according to a specific user-selected perspective. For the summarization methods, our framework implements three extractive summarization methods: Entity-based, Social Signal-based, and Triple-based. We conduct comparative evaluations of MVSF summarizations against state-of-the-art summarization models, including BertSum, SBert, T5, and Bart-Large-CNN, by using a gold standard BBC news dataset and Rouge scores. Furthermore, we utilized a dataset of 18,047 tweets about COVID-19 vaccines to demonstrate the applications of MVSF. Our contributions include the innovative approach of using user perspectives in summarization methods as a unified framework, capable of generating multiple summaries that reflect different perspectives, in contrast to prior approaches of one summary for one dataset. The practical implication of MVSF is that it offers end-users diverse perspectives from social media data. Our prototype web application is also implemented using ChatGPT to show the feasibility of our approach.
Opportunities and Challenges in Antibody-Drug Conjugates for Cancer Therapy: A New Era for Cancer Treatment
Authors: Buyukgolcigezli Idil , Tenekeci Ates Kutay , Sahin Ibrahim Halil
Published: February 2025

The antibody, linker and payload moieties all play a significant role in rendering the ADC its unique therapeutic potential. The antibody subclass employed in ADCs is determined based on relative individual receptor affinities and pharmacokinetics. Meanwhile, the linker used in an ADC can either be cleavable or non-cleavable. ADC therapy comprises antibody-dependent mechanisms in addition to the direct cytotoxic effects of the payload. These include antibody-dependent cellular cytotoxicity, complement-dependent cytotoxicity, and antibody-dependent cellular phagocytosis, as well as the “bystander effect,” which refers to the diffusion of a portion of the cytotoxic molecules out of the target cell, exerting its cytotoxic effect on the adjacent cells. Target antigens of ADCs are expected to be expressed on the membranes of the cancer cells facing the external matrix, although new approaches utilize antigens regarding tumor-associated cells, tumor microenvironment, or tumor vasculature. These target antigens of ADCs not only determine the efficacy of these agents but also impact the off-targets and related adverse effects. The majority of ADC-related toxicities are associated with off-targets. Proposed mechanisms of ADC resistance include disrupted intracellular drug trafficking, dysfunctional lysosomal processing, and the efflux of the cytotoxic molecule via ATP-binding cassette (ABC) transporters. The latter mechanism is especially prominent for multi-drug resistant tumors. An important limitation of ADCs is the penetration of the conjugate into the tumor microenvironment and their delivery to target cancer cells. Cancerous tissues’ vascular profile and the steric “binding site barrier” formed around the peripheral vessels of a tumor stand as potential challenges of ADC therapy for solid tumors. As research efforts focus on reducing toxicities, overcoming resistance, and improving pharmacokinetics, ADC options for cancer therapy are expected to continue to diversify, including standalone approaches and combination therapies.
Language And Society In The Lens Of Young Children: A Review
Authors: Asperis Robert
Published: February 2025

Language is a fundamental component of human society, shaping how individuals communicate, interact, and perceive the world around them. This article review aimed to determine the relationship of language to society through the lens of young children. Language development in young children is an intricate process shaped by social interactions, socioeconomic factors, digital exposure, and cultural influences. By understanding how young children navigate language within society, caregivers and educators can foster environments that promote robust linguistic and cognitive growth. Future research should further explore the long-term effects of early social and linguistic experiences on children's overall academic and social success. Educators should incorporate culturally responsive teaching strategies that recognize and respect the linguistic diversity of their students. Schools should create an inclusive environment where children feel encouraged to use their home language while also developing proficiency in the dominant language of instruction. Additionally, policymakers should invest in early childhood education programs that provide equitable access to language learning resources, particularly for children from disadvantaged backgrounds. By implementing these strategies, society can foster a generation of young learners who are confident communicators and socially aware individuals.
The Impact of Thermal and Electrical Pre-Treatments and Anti-Browning Solution on the Chlorogenic and Dicaffeoylquinic Acids Extraction Yield from Endive Roots
Authors: Diemer Etienne , Chadni Morad , Ioannou Irina , Grimi Nabil
Published: February 2025

Forced endive roots (FER) contain beneficial antioxidant compounds such as chlorogenic acid (5-CQA) and dicaffeoylquinic acids (diCQAs). This study compared the extraction yields of 5-CQA and diCQAs using a biomass pressing method with various pre-treatments, including pulsed electric field (PEF) and microwave (MW), against the solid-liquid extraction method. The results indicated that the MW pre-treatment achieved the highest yields, extracting 28 ± 2% of 5-CQA and 13 ± 1% of diCQAs, surpassing the solid-liquid method. Furthermore, the oxidative degradation of CQAs is studied and it appears that this reaction is enhanced by PEF pretreatment. An anti-browning solution (ABS) is successfully tested to reduce this oxidation and protects CQAs. An extraction process utilizing MW and PEF pre-treatments combined with an ABS solution achieved yields of 65 ± 1% for diCQAs and 80 ± 5% for 5-CQA, significantly outperforming the solid-liquid extraction method.