bluuebunny/crossref_metadata_2025 huggingface dataset:
Ultralight Axion or Axion-Like Particle Dark Matter and 21-cm Absorption Signals in New Physics
Authors: Das Chitta Ranjan
Published: December 2024

A hypothetical particle known as the axion holds the potential to resolve both the cosmic dark matter riddle and particle physics' long-standing, strong CP dilemma. An unusually strong 21-cm absorption feature associated with the initial star formation era, i.e., the dark ages, may be due to ultralight axion dark matter (\( \sim \) 10-22 eV) at this time. The radio wave observation's 21-cm absorption signal can be explained as either anomalous baryon cooling or anomalous cosmic microwave background photon heating. Shortly after the axions or axion-like particles (ALPs) thermalize among themselves and form a Bose-Einstein condensate, the cold dark matter ALPs make thermal contact with baryons, cooling them. ALPs are thought to be the source of some new evidence for dark matter, as the baryon temperature at cosmic dawn was lower than predicted based on presumptions. The detection of baryon acoustic oscillations is found to be consistent with baryon cooling by dark matter ALPs. Simultaneously, under the influence of the primordial black hole and/or intergalactic magnetic fields, the dark radiation composed of ALPs can resonantly transform into photons, significantly heating up the radiation in the frequency range relevant to the 21-cm tests. When examining the 21-cm cosmology at redshifts z between 200 and 20, we see that, when taking into account both heating and cooling options at the same time, heating eliminated the theoretical excess number of neutrino species, \( \Delta \)N_eff, from the cooling effect.
Enhancing Voltage and Power Stability in Distribution System with Photovoltaic from Benefits of Battery Energy Storage
Authors: Rugthaicharoencheep Nattachote , Charlangsut Narate
Published: December 2024

This paper presents enhancing voltage and power stability in distribution system with photovoltaic from benefits of battery energy storage. This objective which is use photovoltaic distributed generation and battery energy storage system in order to reduce electric power loss to minimum loss and generate voltage up to or above 0.95 p.u which is thailand voltage standard. This paper has experiment in MATLAB test in the system for the case study is a IEEE 33 bus distribution system. There are 5 study case in this paper. Case 1 is before installation photovoltaic and battery energy storage system. Case 2 is installation photovoltaic distributed generator in 4 buses. Case 3 is installation photovoltaic distributed generator in only one bus. Case 4 is installation photovoltaic distributed generator in 2 buses that have most voltage drop. Case 5 is installation photovoltaic distributed generator in 4 buses and battery energy storage system in 2 buses. The result show case 5 is the best because none numbers of voltage drop is below 0.95 per unit and the lowest power loss.
Stability of the Implant-Alveolar Bone Complex According to the Peri-Implant Bone Loss and Bone Quality: A Finite Element Analysis Study
Authors: Yoon Youngjae , Kim Jae-Eun , Kim Eunji , Park Soyeon , Kang Inyeong , Kwon Yong-Dae
Published: December 2024

Peri-implant bone loss and bone quality significantly affect the biomechanical stability and long-term success of dental implants. This study used finite element analysis to evaluate the stress distribution and deformation behavior of implants and alveolar bone according to bone loss (0–5 mm) and bone quality (normal and low). A finite element model was implemented based on a three-dimensional mandibular model. The mechanical properties of each component were assigned, and finite element analysis was performed using a static occlusal load. Results showed that progressive bone loss increased von Mises stresses in the implant fixture and surrounding bone, and low quality bone showed a significant vulnerability to stress concentration. The 2 mm bone loss model showed the maximum stress in cortical bone, and from 3 mm onwards, the stress decreased due to extensive loss of cortical bone. This may be because extensive bone loss causes the implant to lose interface with cortical bone and contact only with cancellous bone. This study confirmed that bone loss and the vulnerability of bone quality may potentially affect implant failure. Continued research is needed to suggest customized implants based on the structural vulnerability of alveolar bone.
Anti TNF-a Use in Pediatric Inflammatory Bowel Disease – Reports from a Romanian Center
Authors: Matran Roxana , Diaconu Andra-Mihaela , Iordache Andreea Maria , Dijmărescu Irina , Coroleuca Alexandra , Pacurar Daniela , Becheanu Cristina Adriana
Published: December 2024

Background/Objectives: Treatment armamentarium for inflammatory bowel disease (IBD) has enriched with the advent of anti-tumor necrosis factor (TNF) α molecules, especially infliximab (IFX) and adalimumab (ADA). Besides their incontestable benefits, numerous potential adverse events (AE) are reported to be associated with their use. Our aim was to asses and report the AE for optimal selection and monitoring of patients undergoing these therapies. Methods: A retrospective single-center study was conducted on pediatric IBD patients treated with anti-TNF α at "Grigore Alexandrescu" Emergency Hospital for Children in Bucharest, Romania, from January 2015 to October 2024. AE were classified as: non-infectious complications as acute infusion reactions, anti-drug antibodies formation, dermatological effects such as erythema nodosum (EN) and vasculitis, neurologic effects such as Guillain Barré syndrome and infections. AE were assessed according to the administered molecule and described in detail. Results: Of 40 patients enrolled, 22 (55%) had CD. Median (IQR) age at diagnosis was 14.8 years [10.8-15.9]. IFX was used in 34 (85%) patients while 6 (15%) patients received either ADA or IFX/ADA sequential therapy. Twenty-seven AE were documented in 19 (47.5%) patients, most prevalent being anti-drug antibodies formation, infections and acute infusion reactions. All ADA- treated patients experienced at least one AE, compared to 41.2% in the IFX group, p=.0.01. Conclusions: AE af-fected over half of the patients, with anti-drug antibody formation being most prevalent. ADA treatment was associated with a higher risk of AE compared to IFX. Careful monitoring of patients receiving anti-TNF agents is crucial.
An Analytical Study on Thermal Post-Buckling Behaviors of Geometrically Imperfect FRC Laminated Beams Using a Modified Zig-Zag Beam Model
Authors: Wang Zhoumi , Meng Qingchun
Published: December 2024

An asymptotic analytical method is proposed to study the thermal post-buckling behaviors of fiber-reinforced composite (FRC) laminated beams with geometric imperfections employing a modified zig-zag beam model. The beam model satisfies the discontinuity of the shear deformation at the interlayer interfaces and the stress boundary conditions on upper and lower surfaces. The imperfection is assumed to possess the same shape as the buckling mode and the in-plane boundary conditions supposed immovable. A two-step perturbation method is used to solve the nonlinear governing equations and obtain the equilibrium path. Subsequently, the initial defect sensitivity of the post-buckling behaviors is analyzed and the existence of the equilibrium path of bifurcation type of perfect beams is discussed in depth by plotting the load-deflection curves of beams with different boundary conditions and ply modes. Effects of slenderness ratio, elastic modulus ratio, thermal expansion coefficient ratio, ply modes, supported boundaries on the buckling and post-buckling behaviors are also investigated. Numerical results suggest the necessity to consider the zig-zag displacement fields for buckling instability analysis of general asymmetric FRC laminated beams when the thickness of the beams or the ratio of the two in-plane Young’s moduli is large.
Comparative Evaluation of PID, MPC and Fuzzy Logic Control Strategies for Energy Transfer Stations in District Cooling Networks
Authors: Zafar Mashhood , Ozcelik Selahattin
Published: December 2024

Energy transfer stations (ETS) play a vital role in district cooling networks by facilitating thermal energy transfer between central chilled water plants and connected buildings. Effective control of ETS is crucial to maintain optimal temperature conditions and energy efficiency. However, traditional proportional-integral-derivative (PID) control may not always provide robust performance under changing operating conditions. This study aimed to evaluate and compare the control performances of PID, model predictive control (MPC), and fuzzy logic control (FLC) for an ETS process. A dynamic model of an ETS system incorporating a plate heat exchanger, control valve, temperature sensors and disturbances was developed. PID, MPC and FLC controllers were designed and tuned using the model. Controller performances were assessed through simulation-based experiments under setpoint changes and disturbances. Performance metrics such as rise time, settling time, overshoot, peak time and integral error were analyzed. Results showed that the MPC approach achieved the fastest rise time and lowest overshoot compared to PID and FLC. Meanwhile, FLC offered more robust control with minimal variations in performance metrics under changing conditions. Overall control effort was also lower with MPC and FLC. Proper selection of control strategy based on system requirements could help prevent issues like low delta-T syndrome in district cooling networks.
Stability of Ternary Drug-Drug-Drug Coamorphous Systems Obtained Through Mechanochemistry
Authors: D'Abbrunzo Ilenia , Venier Elisabetta , Selmin Francesca , Škorić Irena , Bernardo Enrico , Procida Giuseppe , Perissutti Beatrice
Published: December 2024

This study explores the successful preparation of coamorphous systems composed entirely of ac-tive pharmaceutical ingredients, namely praziquantel, niclosamide, and mebendazole. Using a mixture design approach, ten different (binary and ternary) mixtures were formulated and pre-pared by neat grinding in a lab-scale vibrational mill. The solvent-free one-step process was re-producible, requiring only 4 hours to generate the coamorphous systems in the whole experi-mental domain. Structural analysis by PXRD and FTIR confirmed the absence of crystalline do-mains and presence of molecular interactions. The glass transition (Tg) temperature was calcu-lated theoretically according to Gordon-Taylor equation for a three-component system and then determined by DSC. In most cases a single Tg was seen, indicating the formation of homogene-ous multicomponent systems. Stability studies on seven systems, stored for six months under different temperature conditions (-30 °C, 5 °C, 25 °C, and 40 °C), demonstrated that all systems were physically stable according to the "Tg – 50 °C" stability rule, with only two exceptions out of seven. Humidity effects were minimal, as shown by DVS data, which revealed only superfi-cial water sorption and no recrystallization. Additionally, the investigation of recrystallization pathways revealed that, depending on the system's interactions, some coamorphous systems separated into their original crystalline phases and others formed new entities such cocrystals.
Influence of Plasticizers on Cross-Linking Process, Morphology and Properties of Lignosulfonate Filled Rubber Compounds
Authors: Kruželák Ján , Džuganová Michaela , Kvasničáková Andrea , Preťo Jozef , Hronkovič Ján , Hudec Ivan
Published: December 2024

Calcium lignosufonate as a biopolymer filler was incorporated into acrylonitrile butadiene rubber in constant amount – 50 phr. Four low molecular organic molecules – 1,4-butanediol, ethylene glycol, and two glycerols with different purity were used as plasticizers. They were applied in rubber formulations in concentration scale ranging from 5 to 30 phr. The influence of plasticizers on curing process, cross-link density, morphology and physical-mechanical properties was investigated. The blooming of plasticizers was also under observation. The results revealed that the application of plasticizers resulted in the deceleration of curing kinetics and reduction in torque increments, pointing out to the decrease of rubber compounds viscosity. This was subsequently confirmed from rheological measurements. The plasticizers soften both the rubber matrix as well as the biopolymer filler. It can be stated the higher the polarity of the plasticizer, the higher the plasticizing effect on lignosulfonate. The plasticizing effect increased in the following order: 1,4-butanediol < ethylene glycol < glycerols. Softened lignosulfonate formed small soft filler like domains well distributed within the rubber matrix. Good adhesion and compatibility between the rubber and the filler on their interface was observed leading to the enhancement in tensile characteristics of vulcanizates plasticized with ethylene glycol and glycerol.
Research on Prediction of Online Training Effect of Newly Recruited PE Teachers in Junior and Senior Middle Schools Based on Machine Learning
Authors: Zhao Feng , Yang Yuelin , Xing Luhan
Published: December 2024

With the continuous development of online education, how to improve the teaching ability of new PE teachers through adaptive and effective online training has become an important research issue. Based on machine learning algorithm, this paper discusses the influence of different characteristics on the adaptability of online training for new physical education teachers, and evaluates the application of various models in predicting the training effect of teachers. The results show that factors such as teachers' professional experience, past training experience, school type and whether to participate in training with colleagues have a significant impact on the adaptability of online training. By comparing Logistic regression model, KNN model, random forest model, XGBoost model and support vector machine model, this paper finds that random forest model is the best in prediction accuracy and generalization ability. This study provides data support and theoretical basis for optimizing the online training of physical education teachers, and can provide reference for educational managers to formulate personalized training programs.
Optimizing Toll Booth Performance with M/M/1 Queueing Models: A Case Study from Indian Highways
Authors: Pandey Satendra , P Vasanthi Kumari
Published: December 2024

In this study, we propose a queuing model for the Toll Plan system, designed to manage vehicle flow through toll booths within the Indian transportation infrastructure. The Toll Plan focuses on optimizing toll booth utilization, reducing driver wait times, and improving overall traffic efficiency. Analyzing queuing behavior at toll booths, we develop a mathematical model to accurately represent vehicle arrival patterns, service times, and queue lengths. The model incorporates key operational factors such as the number of toll booths, traffic volume, and vehicle types. To reflect varying traffic conditions, we examine scenarios for both peak and off-peak hours, capturing fluctuations throughout the day. Using queuing theory principles, we derive critical performance metrics—including average wait times, queue lengths, and service rates—that provide actionable insights into the Toll Plan's efficiency.Additionally, the model is employed for sensitivity analysis and optimization of the Toll Plan's configuration. We investigate strategies such as increasing toll booth capacity, introducing electronic tolling systems and implementing dynamic pricing schemes to evaluate their effects on system performance. These findings offer toll booth operators practical guidance for improving the Toll Plan's design, ensuring smoother traffic flow and enhanced efficiency. Overall, this queuing model serves as a valuable tool for analyzing and enhancing toll booth operations. By leveraging insights from the model, toll authorities can reduce congestion, improve operational efficiency, and significantly enhance the commuting experience for drivers relying on the Toll Plan system.
The Uncertainties of Ground-Level Emission Estimates at Airports, from an Operational and Interdisciplinary-to-Transdisciplinary Standpoint
Authors: D'Amico Francesco
Published: December 2024

Air quality issues are of remarkable interest due to the relevant number of people affected; in the case of ground-level aviation emissions many inventories exist but several degrees of uncertainty, mostly related to the intrinsic variability of aircraft operations and environmental factors, can be highlighted. Via an interdisciplinary-to-transdisciplinary approach accounting for various disciplines, such as Atmospheric Physics, Earth Sciences and Aeronautical procedures, this research paper provides a new insight on the above mentioned uncertainties and calls for more attention be focused on airport air quality measurements and evaluations.
Deep Learning-Empowered RF Sensing in Outdoor Environments: Recent Advances, Challenges, and Future Directions
Authors: Nguyen Duc Minh Quang , Lukito William D. , Liu Xuemeng , Liu Chang
Published: December 2024

Recently, with advancements in Deep Learning (DL) technology, Radio Frequency (RF) sensing has seen substantial improvements, particularly in outdoor applications. Motivated by these developments, this survey presents a comprehensive review of state-of-the-art RF sensing techniques in challenging outdoor scenarios with practical issues such as fading, interference, and environmental dynamics. We first investigate the characteristics of outdoor environments and explore potential wireless technologies. Then, we study the current trends in applying DL to RF-based systems and highlight its advantages in dealing with large-scale and dynamic outdoor environments. Furthermore, this paper provides a detailed comparison between discriminative and generative DL models in support of RF sensing, offering insights into both the theoretical underpinnings and practical applications of these technologies. Finally, we discuss the research challenges and present future directions of leveraging DL in outdoor RF sensing.
Managing Gitelman Syndrome: Socioeconomic Barriers and Clinical Outcomes
Authors: Mohammadi Seyed Omid , Bolds Alexis , Shafiee Amirmohammad , Siripurapu Ravi , Kankanala Suresh
Published: December 2024

Gitelman syndrome (GS) is a rare autosomal recessive renal tubulopathy characterized by hypokalemic metabolic alkalosis, hypomagnesemia, and hypocalciuria due to mutations in the SLC12A3 gene. This case report presents a 54-year-old African American female with near syncope and palpitations. The patient had a history of intermittent palpitations and generalized anxiety disorder and was previously diagnosed with GS. On presentation, the patient exhibited symptoms of severe hypokalemia and hypomagnesemia, attributed to medication non-adherence. Laboratory tests confirmed critically low potassium and magnesium levels, with elevated urine sodium and chloride. Treatment was initiated with oral and intravenous potassium and magnesium, leading to the normalization of electrolyte levels. This case highlights the challenges of managing GS, particularly in patients facing socioeconomic barriers that impede medication adherence and healthcare access. Personalized patient education, combined with comprehensive healthcare resources, is essential to mitigate complications and improve long-term outcomes in such cases.
Prevalence of Listeria monocytogenes in Ewe Milk: A Systematic Review and Meta-Analysis
Authors: Idowu Emmanuel
Published: December 2024

Listeria monocytogenes, a foodborne pathogen of global concern, poses significant health risks through the consumption of contaminated dairy products, including ewe milk. This systematic review and meta-analysis aim to evaluate the prevalence of L. monocytogenes in ewe milk, considering regional, methodological, and seasonal variations, and to identify potential risk factors contributing to contamination.The study systematically reviewed peer-reviewed articles and research papers published from 2000 to 2024. Data were extracted from studies employing standard microbiological and molecular techniques for the detection of L. monocytogenes in raw and processed ewe milk samples. The meta-analysis synthesized prevalence rates across diverse geographical regions, emphasizing differences between developed and developing countries.Results reveal a pooled global prevalence rate of L. monocytogenes in ewe milk, highlighting significant variability based on sampling methods and regional practices. Higher prevalence rates were observed in regions with inadequate hygienic practices during milking and processing, underscoring the importance of improved food safety measures. Seasonality also played a critical role, with increased prevalence during warmer months due to enhanced bacterial growth conditions. Furthermore, molecular characterization of isolates demonstrated considerable genetic diversity, suggesting multiple contamination sources and transmission pathways.The findings emphasize the need for stringent monitoring programs, adherence to hygienic milking practices, and implementation of pasteurization in high-risk regions to mitigate the public health risks associated with L. monocytogenes. Future research should focus on advanced detection techniques and interventions to reduce contamination in the dairy supply chain.
Metabolomics, Genetics, and Environmental Factors: Intersecting Paths in Abdominal Aortic Aneurysm Risk
Authors: Fernandes Silva Lilian , Vangipurapu Jagadish , Oravilahti Anniina , Lusis Aldons Jake , Laakso Markku
Published: December 2024

Abdominal aortic aneurysm (AAA) represents a significant public health concern, particularly in men aged 55 to 64, where it occurs in about 1%. We investigated metabolomics and genetics of AAA by analyzing a cohort consisting of 76 patients diagnosed with AAA and 228 matched controls. Utilizing the Metabolon DiscoveryHD4 platform for non-targeted metabolomics profiling, we identified 11 novel metabolites that significantly increased the risk of AAA. These metabolites were primarily associated with environmental and lifestyle factors, notably smoking and pesticide exposure, which underscores the influence of external factors on the progression of AAA. Additionally, several genetic variants were associated with xenobiotics, highlighting a genetic predisposition that may exacerbate the effects of these environmental exposures. The integration of metabolomic and genetic data provides compelling evidence that lifestyle, environmental, and genetic factors are intricately linked to the etiology of AAA. The results of our study not only deepen the understanding of the complex pathophysiology of AAA but also pave the way for the development of targeted therapeutic strategies.
Physical and Microscopic Characterization of Thermal Treatment Products of Plant Waste for Recycling in Sustainable Construction
Authors: Moromi Isabel , Mendoza Jose , Villegas Carlos , Torre Ana , Reyes Carmen , Shuan Luisa
Published: December 2024

Organic plant waste is a source of pollution, so it is necessary to dispose properly. One way is recycling. Studies show the possibilities of using it in construction. In the present study, some municipal waste has been characterized and evaluated for its application in mortars and concretes. A preliminary evaluation was done with five residues (orange peel, corn cob and husk, pineapple leaf and garden grass). In the compression tests of mortars with various percentages of aggregate replacement, the best results were with grass, with resistances like to the standard sample after 7 days of curing. Therefore, mortar and concrete samples were prepared with 5% and 10% re-placement of sand by volume with grass. The results of the mortar samples, after 7 days of curing, were 88% and 74.6% and the concrete samples were 87% and 85% respectively after 28 days of curing, compared to the standard samples. It is concluded that it is feasible to recycle grass for use as a partial substitute for aggregate in concrete. However, it is necessary to complement the tests carried out, to define the optimal percentage of substitution and in terms of durability, to define the scope of its application in construction.
Assessment of Radioactivity Concentrations and Associated Radiological Health Risk in Natural Spring Mineral Bottled Drinking Water from South Africa
Authors: John Samuel Odumu Ogana , Olukotun Stephen Friday , Mathuthu Manny
Published: December 2024

Naturally occurring radionuclides are ubiquitous at various levels of concentration while exposure to ionizing radiation by humans is of global concern. The assessment of radiological health risk associated with the consumption of natural spring mineral water is critical for ensuring public health and safety. The study aims at investigating the activity concentration levels of natural radionuclides 226Ra, 232Th and 40K and the associated radiological health risk in commercial natural spring bottled water in South Africa. 21 most consumed brands of bottled water collected from the market were analysed using HPGe gamma detector. The results indicate that activity concentrations ranged from 1.060 ± 0.067 to 2.571 ± 0.143 BqL-1, with mean of 1.766± 0.399 BqL-1 for 226Ra; 1.736 ± 0.112 to 7.807 ± 0.099 BqL-1, with mean of 3.688 ± 1.371 BqL-1 for 232Th and 149.000 ± 38.480 to 242.900 ± 59.700 BqL-1 with mean of 220.229 ± 22.297 BqL-1 for 40K. The potential radiological health risks evaluated show mean values for Raeq, DAb, AEID and AGED as 23.976 ± 0.446 BqL-1, 12.232 ± 1.445 nGyh-1, 0.060 ± 0.007 mSvy-1 and 0.090 ± 0.027 mSvy-1, respectively. The radiation dose received by age group is in order of infant (≤ 1 year) > teenagers (12-17 years) > children (1-12 years) > adult (> 17 years). The findings reveal that the activity concentration levels and estimated radiological health risks are within permissible limits set by UNSCEAR guidelines. Therefore, consumption of bottled water is radiologically safe. However, findings also suggests that 12 out of 1000 individuals may suffer cancer fatality while 6 out of 1 million individuals may experience hereditary effects over lifetime, from consumption of bottled water. Regular monitoring and stringent regulatory controls are recommended to ensure the radiological safety of natural spring mineral bottled water in South Africa.
Sequence of Eating at Japanese-Style Set Meals Improves Postprandial Glycemic Elevation in Healthy People
Authors: Kurotobi Yuri , Kuwata Hitoshi , Matsushiro Mari , Omori Yasuhiro , Imura Masahiro , Nakatani Susumu , Matsubara Miho , Haraguchi Takuya , Moyama Shota , Hamamoto Yoshiyuki , Yamada Yuichiro , Seino Yutaka , Yamazaki Yuji
Published: December 2024

Aim: Meal sequencing of macronutrients has been shown to ameliorate postprandial glucose excursion, but its effects in daily meals has not been investigated. We examined the impact on the glucose response to meal sequencing in healthy Japanese adults using Continuous Glucose Monitoring (CGM) during a typical lunch meal.
Method: The test meal was a Japanese set meal or a beef and rice bowl, the contents of which were categorized as "rice" or "non-rice". In the meal experiments, subjects ingested the two categories of food in one of three orders: non-rice before rice, non-rice and rice together, and non-rice after rice. In the beef and rice bowl experiments, the subjects ingested either non-rice 15 minutes before rice or the two foods together. The postprandial glucose level was measured over a 4 h period and the mean level of postprandial glucose was significantly lower than that when eating rice before non-rice or both together.
Results and Conclusion: Consuming non-rice before rice significantly reduced postprandial glycemic excursions in healthy adults in both experiments. Meal-sequencing by “eat carbs last” is a feasible dietary strategy for better prevention and management of diabetes.
Exploring Predictors of Diabetes Within Animal and Plant-Based Dietary Patterns with the XGBoost Machine Learning Classifier: NHANES 2013-2016
Authors: Eckart Adam , Sharma Ghimire Pragya
Published: December 2024

Background/Objectives: Understanding the relationship between dietary patterns, nutrient intake, and chronic disease risk is critical for informing public health strategies. However, confounding from lifestyle and individual factors complicates the assessment of diet-disease associations. Emerging machine learning (ML) techniques offer novel approaches to clarifying the importance of multifactorial predictors. This study investigated the associations between animal-sourced and plant-based dietary patterns and diabetes history, accounting for diet-lifestyle patterns employing the XGBoost algorithm. Methods: Using data from the National Health and Nutrition Examination Survey (NHANES) from 2013-2016, individuals consuming animal-sourced foods (ASF) and plant-based foods (PBF) were matched on key confounders, including age, gender, body composition, energy intake, and activity levels. Predictors of diabetes history were analyzed using the XGBoost classifier, with feature importance derived from Shapley plots. Lifestyle and dietary patterns derived from principal component analysis (PCA) were incorporated as predictors, and high multicollinearity among predictors was examined. Results: The top predictors by importance to diabetes prediction included age, percent body fat, recent BMI changes, and physical activity. Higher protein and fat intake from ASFs and PBFs were associated with lower risk, while unhealthy lifestyle factors exacerbated risk. The XGBoost model achieved an accuracy of 91.4% and an AUROC of 89%. The dietary and serum omega-6 to omega-3 fatty acids ratio emerged as significant dietary predictors. Conclusions: This study underscores the complex interactions between diet, lifestyle, and body composition in diabetes risk. Machine learning techniques like XGBoost provide valuable insights into these multifactorial relationships by mitigating confounding and identifying key predictors. Future research should focus on prospective studies incorporating detailed nutrient analyses and ML approaches to refine prevention strategies and dietary recommendations for type 2 diabetes.
Integrated Analysis of microRNA Targets Reveals New Insights into Transcriptional-Posttranscriptional Regulatory Cross-Talk
Authors: Panni Simona , Pizzolotto Roberto
Published: December 2024

It is becoming increasingly clear that microRNAs are key players in gene regulatory networks, by modulating gene expression at post-transcriptional level. Their involvement in almost all cellular processes has anticipated their role in diseases, with several microRNA-based therapeutics currently undergoing clinical testing. Despite their undeniable relevance and the substantial body of literature demonstrating their role in cancer and other pathologies, the identification of functional interactions is still challenging. Several resources have been developed to address this issue, by gathering information from the literature, following different criteria and reliability scores. In the present study, we have built a network of verified microRNA-mRNA interactions by integrating strong-evidence couples from different resources. We have analysed the resulting network and compared cohorts of co-regulated genes. The results clearly show that hub genes are highly enriched of transcription factors and regulatory proteins, strongly suggesting a cross-talk and a combinatorial effect between transcriptional and post-transcriptional gene control. Data analysis also reveals that several microRNAs control multiple targets involved in the same pathway or biological process, likely contributing in coordinating the levels of the proteins.
Thermal Optimization of Edge Emitting Lasers Arrays
Authors: Sarzała Robert P. , Dąbrówka Dominika , Dems Maciej
Published: December 2024

The paper presents a novel approach to address the issue of uneven temperature distribution in one-dimensional laser arrays, specifically in gallium nitride edge-emitting lasers emitting green light of 540 nm. The results were obtained using heat flow numerical analysis, which included an optimization method specifically developed for this type of array. It was demonstrated that thermal optimization of a one-dimensional edge-emitting laser array can be achieved by adjusting the placement of the emitters within the array and the size of the top gold contact, without changing the overall dimensions of the device. The proposed design alterations ensure an even temperature distribution across the array without the need for a complex and expensive cooling systems. The proposed optimization method can be applied to arrays made from various material systems, including nitrides, arsenides, and phosphides.
A Case Study of Using Numerical Analysis to Assess Slope Stability of National Highways in Northern Taiwan
Authors: Chiu Hao-Wei , Tsai Yi-Hao , Tang Chao-Wei , Chu Chih-Yu , Chen Shong-Long
Published: December 2024

Because of its location at the meeting point of the Eurasian Plate and the Philippine Sea Plate, Taiwan experiences earthquakes frequently. Mountains and hills make up the majority of the landscape, and Taiwan has some of the highest precipitation levels in the world. The stability of slopes in different parts of Taiwan is influenced by all of these factors. The study's instances are the National Freeway 1 and 5 slopes, where several landslide and rockfall incidents have occurred. This study used PLAXIS 2D CE finite element software to simulate and analyze the safety of highway slope protection projects. Displacements induced by normal and high groundwater levels were discussed. Moreover, a pseudo-static study of slope displacements under seismic conditions was performed. According to the results of the numerical study, the force operating on the slope was centered on the sliding surface when the groundwater level was normal, and it extended to the top when the groundwater level was high. By comparison, under seismic conditions, the force acting on the slope extended to the whole slope.
Integrating Sensor Technologies with Conversational AI: En-Hancing Context-Sensitive Interaction Through Real-Time Data Fusion
Authors: Kush Joseph
Published: December 2024

This article examines how sensor technologies (such as environmental sensors, biometric sensors, and IoT devices) intersect with conversational AI models like ChatGPT. In particular, this article explores how data from different sensors in real-time can improve AI models' comprehension of surroundings, user context, and physical conditions. Lastly, the article delves into the scientific principles supporting sensor technologies, data processing methods, and their fusion with gener-ative models such as ChatGPT to develop adaptable, dynamic systems that engage with humans intelligently in real-time. Some of the specific topics that are investigated include the science be-hind sensor networks and acquiring real-time data; how ChatGPT can analyze sensor data to generate dialogue that is sensitive to context; Instances in healthcare (such as using wearable sen-sors along with AI chatbots for patient treatment) and smart homes (interaction with AI assis-tants driven by sensors). These subjects will prove advantageous for researchers in sensor tech-nology as well as AI development, showcasing interdisciplinary progress in smart systems.
Use of AI-Methods over MD Simulations in the Sampling of Conformational Ensembles in IDPs
Authors: Sil Souradeeep , Datta Ishita , Basu Sankar
Published: December 2024

Intrinsically Disordered Proteins (IDPs) challenge traditional structure-function paradigms by existing as dynamic ensembles rather than stable tertiary structures. Capturing these ensembles is critical to understanding their biological roles, yet Molecular Dynamics (MD) simulations, though accurate and widely used, are computationally expensive and struggle to sample rare, transient states. Artificial intelligence (AI) offers a transformative alternative, with deep learning (DL) enabling efficient and scalable conformational sampling. They leverage large-scale datasets to learn complex, non-linear, sequence-to-structure relationships, allowing for the modeling of conformational ensembles in IDPs without the constraints of traditional physics-based approaches. Such DL approaches have been shown to outperform MD in generating diverse ensembles with comparable accuracy. Most models rely primarily on simulated data for training and experimental data serves a critical role in validation, aligning the generated conformational ensembles with observable physical and biochemical properties. However, challenges remain, including dependence on data quality, limited interpretability, and scalability for larger proteins. Hybrid approaches combining AI and MD can bridge the gaps by integrating statistical learning with thermodynamic feasibility. Future directions include incorporating physics-based constraints and learning experimental observables into DL frameworks to refine predictions and enhance applicability. AI-driven methods hold significant promise in IDP research, offering novel insights into protein dynamics and therapeutic targeting while overcoming the limitations of traditional MD simulations.
Forms of Migration of Elements in Natural and Drinking Waters in Village Krasnoshchelye (Lovozero District, the Kola Peninsula) and Human Health Risk Assessment
Authors: Mazukhina Svetlana , Drogobuzhskaya Svetlana , Masloboev Vladimir , Safonov Aleksandr , Shirokaya Anna , Sandimirov Sergey , Rybachenko Vladislav
Published: December 2024

The chemical composition of surface and ground waters of the village Krasnoshchelye (Murmansk region, the Kola Peninsula) have been studied in this work. The quality of surface and ground waters of the village Krasnoshchelye is characterized taking into account the MPC and biologically significant concentration, the forms of migration of elements in the system "solution - crystalline substance" in natural waters and the human body (using the stomach as an example) have been considered. The results of the studies of drinking water in the village Krasnoshchelye indicate that the macro- (Ca, Mg, Na, K) and microelement (Co, Cu, Mn, Ni, V, Zn, Cr) composition have lower concentrations from the standpoint of biological significance for the elemental balance of a person than the recommended level of the lower limit of the BSC, except for the elements U, Th, Y. Their concentration is several times higher than their LLBSC. The forms of migration of elements and newly formed phases depend on both the acidity of the stomach and the amount of gastric juice in the human body, in the "water - gastric juice" system. These are individual characteristics of a person and his age. Well waters can contain up to 50 μg/l of REE, and changes in their migration patterns can lead to accumulation in the human body and cause diseases of the nervous system and other organs.
Chitosan and Its Nanoparticles: A Multifaceted Approach to Antibacterial Applications
Authors: Akdaşçi Emir , Duman Hatice , Eker Furkan , Bechelany Mikhael , Karav Sercan
Published: December 2024

Chitosan, a multifaceted amino polysaccharide biopolymer derived from chitin, has extensive antibacterial efficacy against diverse pathogenic microorganisms, including both Gram-negative and Gram-positive bacteria, in addition to fungus. Over the course of the last several decades, chitosan nanoparticles (NPs), which are polymeric and bio-based, have garnered a great deal of interest as an efficient antibacterial agent. This is mostly due to the fact that they are used in a wide variety of applications, including medical treatments, food, chemicals, and agricultural products. Within the context of the antibacterial mechanism of chitosan and chitosan NPs, we present a review that provides an overview of the synthesis methods, including novel procedures, and compiles the applications that have been developed in the field of biomedicine. These applications include wound healing, drug delivery, dental treatment, water purification, agriculture, and food preservation. In addition to this, we focus on the mechanisms of action and the factors that determine the antibacterial activity of chitosan and its derivatives. In conjunction with this line of inquiry, researchers are strongly urged to concentrate their efforts on developing novel and ground-breaking applications for chitosan NPs.
From Ground to Grid: The Environmental Footprint of Minerals in Renewable Energy Supply Chains
Authors: Sheth Kajal , Patel Dhvanil , Swami Gautam
Published: December 2024

Renewable energy technologies, while often labeled as clean or net-zero alterna-tives to fossil fuels, involve substantial use of critical minerals in products like electric vehicles, solar panels, wind turbines, and battery storage systems. This aspect is frequently underappreciated, yet studies indicate it could be a significant area of environmental impact. For instance, research has shown that a typical electric vehicle needs around six times the mineral resources of a conventional vehicle, while an onshore wind turbine requires nine times the mineral input compared to a gas power plant of similar capacity.
This paper seeks to analyze the environmental effects linked to the critical miner-als required by certain renewable energy technologies. The study begins with an estimation of the future megawatt capacities for each type of renewable technolo-gy. Next, it calculates the specific mineral quantities necessary for each model, followed by an assessment of the environmental repercussions tied to their extrac-tion and processing. The results highlight the unique environmental challenges posed by the rising demand for minerals in solar and wind energy systems, taking into account various adoption scenarios.
Transimpedance Matrix Measurement (TIM) Parameters Evaluation for the Assessment of Cochlear Implant Electrode Placement and Modiolar Proximity in Children
Authors: Radomska Katarzyna , Talar Marcin , Haber Karolina , Mierzwińska - Dolny Paulina , Fishman Andrew J , Mierzwiński Józef
Published: December 2024

Introduction: Transimpedance Matrix Measurement (TIM) is an electrophysiological measurement proto-col of the impedance patterns of electrode contacts within the cochlea. Several studies have reported that TIM is an effective tool for the identification of abnormal electrode array placement. However, the norma-tive values for properly inserted electrodes as well as correlation of the TIM patterns with the electrode po-sition are not completely determined. Objectives: The first aim of this study is to establish normative values of TIM measurements obtained in chil-dren with proper electrode array insertion and tip fold over, with proper inner ear anatomy and in congen-ital anomalies. The second aim of this study is to compare TIM measurements in Slim Modiolar (SM) and in Contour Adavance (CA) electrodes, as they position is different according to the modiolus proximity. Methods: A total of 55 pediatric patients were included in the study and underwent cochlear implantation. 62 intraoperative measurements were conducted in this group – 50 in children with normal inner ear anatomy and 12 in children with inner ear malformations. After each implantation, plain x-ray was ob-tained. Results: There were clear statistically significant differences in TIM patterns in patients where electrode fold-over was confirmed and between SM and CA electrodes. Conclusions: TIM is a promising technique for intraoperative detection of abnormal electrode malinsertion as well as TIM patterns differ and correlate consistently with the different models of array implanted. This study is the first to report TIM patterns observed in children with normal inner ear anatomy and in inner ear malformations.
Comparative Metabolic Analysis of Different Indica Rice Variety Associated with Seed Storability
Authors: Wu Fangxi , Wei Yidong , Zhu Yongsheng , Luo Xi , He Wei , Wang Yingsheng , Cai Qiuhua , Xie Huaan , Zhang Jianfu , Xie Guosheng
Published: December 2024

Background: Seed storability is a crucial agronomic trait indispensable for the safe storage of rice seeds and grains. Nevertheless, metabolite mechanisms of governing rice seed storability under natural condition are still poorly understood. Methods: Therefore, storage tolerance of global rice core germplasm stored for two years under natural aging conditions were identified and compared by UPLC-MS/MS metabolomic analysis. Results: Our results proved that different rice core accessions showed significant variability in storage tolerance, metabolite analysis of two Indica rice pools exhibited different levels of storability. A total of 103 differentially accumulated metabolites (DAMs) between the two pools was obtained, of which 38 were upregulated and 65 were downregulated, respectively. Further analysis disclosed that aging-resistant rice accessions had higher accumulation levels of flavonoid, terpenoid, phenolic acid, organic acid, lignan, and coumarin while exhibiting lower levels of lipid and alkaloid compared to storage-sensitive rice accessions. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis indicated that several biosynthesis pathways were involved in the observed metabolites differences, including alpha-linolenic acid metabolism, butanoat metabolism, and propanoate metabolism. Notably, inhibition of the linolenic acid metabolic pathway could enhance seed storability. Additionally, increased accumulation of organic acids such as succinic acid, D-malic acid, and methylmalonic acid in the butanoate and propanoate metabolisms was identified as a beneficial factor for seed storage. Conclusions: These new findings will deepen our understanding of the underlying mechanisms of governing rice storability and offer a valuable avenue for improving rice storability through breeding program.