bluuebunny/crossref_metadata_2025 huggingface dataset:
Review Article: Diagnostic Paradigm Shift in Spine Surgery
Authors: Levent Aras Efe , Tanaka Masato , Kumawat Chetan , Heng Christian , Nikolaos Salamalikis , Latka Kajetan , Miyamoto Akiyoshi , Komatsubara Tadashi , Arataki Shinya , Oda Yoshiaki , Shinohara Kensuke , Uotani Koji
Published: February 2025

Meticulous clinical examination is essential for spinal disorders to utilize the diagnostic methods and technologies that strongly support physicians and enhance clinical practice. A significant change in the approach to diagnosing spinal disorders has occurred in the last three decades, which has enhanced a more nuanced understanding of spine pathology. Traditional radiographic methods such as conventional and functional X-rays and CT scans are still the first line in the diagnosis of spinal disorders due to their low cost and accessibility. As more advanced imaging technologies become increasingly available worldwide, there is a constantly increasing trend in MRI scans for detecting spinal pathologies and making treatment decisions. Not only do MRI scans have superior diagnostic capabilities, but they also assist surgeons in performing meticulous preoperative planning, making them currently the most widely used diagnostic tool for spinal disorders. Positron Emission Tomography (PET) can help detect inflammatory lesions, infections, and tumors. Other advanced diagnostic tools such as CT/MRI fusion image, Functional Magnetic Resonance Imaging (fMRI), Upright and Kinetic MRI, magnetic resonance spectroscopy (MRS), diffusion-weighted imaging (DWI), and diffusion tensor imaging (DTI) could play an important role when it comes to detecting more special pathologies. However, some technical difficulties in the daily praxis and their high costs act as obstacles to their further spread. Integrating artificial intelligence and advancements in data analytics and virtual reality promises to enhance spinal procedures’ precision, safety, and efficacy. As these technologies continue to develop, they will play a critical role in transforming spinal surgery. This paradigm shift emphasizes the importance of continuous innovation and adaptability in improving the diagnosis and treatment of spinal disorders.
Battery Current Estimation and Prediction During Charging with Ant Colony Optimization Algorithm
Authors: Muslimin Selamat , Prihatini Ekawati , Husni Nyayu Latifah , Dewi Tresna , Wartam Bin Umar Mukhidin , Bela Auvi Crisanta Ana , Handayani Sri Utami , Caesarendra Wahyu
Published: February 2025

This paper presents an application of the Ant Colony Optimization (ACO) algorithm combined with the Logistic Regression (LR) method in the lead acid battery charging process. The ACO algorithm is used to obtain the best current pattern in the battery charging system to produce a smart charging system with a fast and safe charging current for the battery. The best current pattern is conducted gradually and repeatedly to obtain termination in the form of the best current pattern according to the ACO algorithm. The results of the algorithm design produce a current pattern consisting of 10 A, 5 A, 3 A, 2 A, and 0 A. The charging system with this algorithm can charge all types of lead acid batteries. In this research, the capacity of battery 1’s State of Charge (SOC) is 56%, battery 2’s SOC is 62%, and battery 3’s SOC is 80%. When recharging the battery’s full condition to a SOC of 100%, the length of time for charging battery 1 for 12.73 min, battery 2 takes 15.73 min, and battery 3 takes 29.11 min. Smart charging with the ACO can charge the battery safely without current fluctuations compared to charging without an algorithm such that the amount of charging current used is not dangerous for the battery. In addition, data analysis is carried out to determine the value of accuracy in estimating SOC charging using supervised learning linear regression. The results of the data analysis with linear regression show that the battery’s SOC estimation has good accuracy, with an RMSE value of 0.32 and an MAE of 0.27.
Child Enjoyment and Parental Satisfaction with Autistic Children’s Participation in Active and Sedentary Activity Configurations
Authors: Salters Danielle , Sheiknur Samiya , Scharoun Benson Sara M.
Published: February 2025

This research used proxy reports and questionnaire-based data to explore characteristics related to participation among autistic children. The research aimed to explore child enjoyment and parental satisfaction in different activity configurations, including active and sedentary pursuits and activities in which children participate alone or in groups. Parents/guardians (n = 100) of autistic children aged 4–15 years completed questionnaire-based assessments of their autistic child’s motor skills, social skills, and characteristics of participation. Regression analyses were completed to elucidate the factors that may contribute to a child’s enjoyment of and parental satisfaction with the child’s participation in the different activity configurations. A strong positive correlation was found between motor and social skills, and for motor and social skills in concert with the different activity configurations. Regression analyses found that the social skills of autistic children were related to participation in most of the activity configurations for both the child’s enjoyment and parental satisfaction in participation. Other results indicated that lower social skills were more strongly related to child enjoyment and parental satisfaction, and that the highest enjoyment and satisfaction scores were found for the sedentary and individual activities. These results reinforce the impact of social skills on participation in various activities, and the need for early intervention to promote skill development among autistic children.
Age-Related Oral and Para-Oral Tissue Disorders: The Evolving Therapeutic and Diagnostic Potential of Exosomes
Authors: Maria Mohamed Khaled Mohamed , Abdel Moniem Esraa Mohamed , Hanafy Ahmed Khaled , Farag Dina B. E. , Radwan Israa Ahmed , Abbass Marwa M. S. , El Moshy Sara , Rady Dina , Dörfer Christof E. , Fawzy El-Sayed Karim M.
Published: February 2025

This review highlights the key molecular and cellular mechanisms contributing to aging, such as DNA damage, mitochondrial dysfunction, telomere shortening, protein dysfunction, and defective autophagy. These biological mechanisms are involved in various oral health conditions prevalent in the elderly, including periodontal disease, oral cancer, xerostomia, dental caries, and temporomandibular joint disorders. Exosomes generated by mesenchymal stem cells possess substantial therapeutic potential. These exosomes are nanosized extracellular vesicles derived from cells and are involved in essential intercellular communication and tissue homeostasis. The exosome-based therapies proved superior to traditional cell-based approaches, due to lower immunogenicity, ease of storage, and avoidance of complications associated with cell transplantation. Furthermore, the diagnostic potential of exosomes as non-invasive biomarkers for aging processes and age-related oral diseases offers insights into disease diagnosis, staging, and monitoring. Among the challenges and future perspectives of translating exosome research from preclinical studies to clinical applications is the need for standardized procedures to fully harness the therapeutic and diagnostic capabilities of exosomes.
Efficient Post-Shrinkage Estimation Strategies in High-Dimensional Cox’s Proportional Hazards Models
Authors: Ahmed Syed Ejaz , Arabi Belaghi Reza , Hussein Abdulkhadir Ahmed
Published: February 2025

Regularization methods such as LASSO, adaptive LASSO, Elastic-Net, and SCAD are widely employed for variable selection in statistical modeling. However, these methods primarily focus on variables with strong effects while often overlooking weaker signals, potentially leading to biased parameter estimates. To address this limitation, Gao, Ahmed, and Feng (2017) introduced a corrected shrinkage estimator that incorporates both weak and strong signals, though their results were confined to linear models. The applicability of such approaches to survival data remains unclear, despite the prevalence of survival regression involving both strong and weak effects in biomedical research. To bridge this gap, we propose a novel class of post-selection shrinkage estimators tailored to the Cox model framework. We establish the asymptotic properties of the proposed estimators and demonstrate their potential to enhance estimation and prediction accuracy through simulations that explicitly incorporate weak signals. Finally, we validate the practical utility of our approach by applying it to two real-world datasets, showcasing its advantages over existing methods.
The Effect of Affective Exercise Experiences and Environmental Factors on Adherence to Outdoor Exercise Programs
Authors: Marini Sofia , Zinno Raffaele , Belli Guido , Pinelli Erika , Bragonzoni Laura , Toselli Stefania , Ekkekakis Panteleimon , Monguzzi Giovanni Alberto , Belvederi Murri Martino , Folesani Federica , Maietta Latessa Pasqualino
Published: February 2025

Background: This study aimed to investigate the association between Affective Exercise Experiences (AEEs), environmental factors, and adherence to a structured public health exercise initiative. Methods: A prospective experimental design was employed in a primary care setting within green parks in a community in Northern Italy. Community-dwelling individuals who participated in a 15-week outdoor exercise program were recruited. Participants engaged in 43 low-to moderate-intensity outdoor exercise sessions, held three times a week from May to July 2022, with each session lasting 60 min. A total of 68 participants (mean age: 64.6 ± 8.6 years) completed the questionnaires. Results: A causal analysis revealed a small but significant positive effect of AEEs on adherence, with higher AEE scores associated with an increased likelihood of attending exercise sessions. The predictive model identified a combination of AEE scores, environmental temperature, distance from the exercise site, and weekday as significant predictors of adherence. Conclusions: This study highlights the importance of AEEs, as well as environmental and demographic factors, in predicting adherence to structured exercise programs. The findings suggest that fostering positive affective experiences related to exercise could enhance adherence, particularly among older adults.
EQLC-EC: An Efficient Voting Classifier for 1D Mass Spectrometry Data Classification
Authors: Guo Lin , Wang Yinchu , Liu Zilong , Zhang Fengyi , Zhang Wei , Xiong Xingchuang
Published: February 2025

Mass spectrometry (MS) data present challenges for machine learning (ML) classification due to their high dimensionality, complex feature distributions, batch effects, and intensity discrepancies, often hindering model generalization and efficiency. To address these issues, this study introduces the Efficient Quick 1D Lite Convolutional Neural Network (CNN) Ensemble Classifier (EQLC-EC), integrating 1D convolutional networks with reshape layers and dual voting mechanisms for enhanced feature representation and classification performance. Validation was performed on five publicly available MS datasets, each featured in high-impact publications. EQLC-EC underwent comprehensive evaluation against classical machine learning (ML) models (e.g., support vector machine (SVM), random forest) and the leading deep learning methods reported in these studies. EQLC-EC demonstrated dataset-specific improvements, including enhanced classification accuracy (1–5% increase) and reduced standard deviation (1–10% reduction). Performance differences between soft and hard voting mechanisms were negligible (<1% variation in accuracy and standard deviation). EQLC-EC presents a powerful and efficient tool for MS data analysis with potential applications across metabolomics and proteomics.
Efficient Ensemble of Deep Neural Networks for Multimodal Punctuation Restoration and the Spontaneous Informal Speech Dataset
Authors: Beigi Homayoon , Liu Xing Yi
Published: February 2025

Punctuation restoration plays an essential role in the postprocessing procedure of automatic speech recognition, but model efficiency is a key requirement for this task. To that end, we present EfficientPunct, an ensemble method with a multimodal time-delay neural network that outperforms the current best model by 1.0 F1 point while using less than a tenth of its network parameters for inference. This work further streamlines a speech recognizer and a BERT implementation to efficiently output hidden layer acoustic embeddings and text embeddings in the context of punctuation restoration. Here, forced alignment and temporal convolutions are used to eliminate the need for attention-based fusion, greatly increasing computational efficiency and improving performance. EfficientPunct sets a new state of the art with an ensemble that weighs BERT’s purely language-based predictions slightly more than the multimodal network’s predictions. Although EfficientPunct shows great promise, from a different perspective, to date, another important challenge in the field has been the fact that punctuation restoration models have been evaluated almost solely on well-structured, scripted corpora. However, real-world ASR systems and postprocessing pipelines typically apply to spontaneous speech with significant irregularities, stutters, and deviations from perfect grammar. To address this important discrepancy, we also introduce SponSpeech, a punctuation restoration dataset derived from informal speech sources, which includes punctuation and casing information. In addition to publicly releasing the dataset, the authors have contributed by providing a filtering pipeline that can be used to generate more data. This filtering pipeline examines the quality of both the speech audio and the transcription text. A challenging test set is also carefully constructed, aimed at evaluating the models’ ability to leverage audio information to predict, otherwise grammatically ambiguous, punctuation. SponSpeech has been made available to the public, along with all code for dataset building and model runs.
A Real-Time Diagnosis Method of Open-Circuit Faults in Cascaded H-Bridge Rectifiers Based on Voltage Threshold and Current Coefficient of Variation
Authors: Liu Yong , Guo Zhe , Liu Fei , Guo Feiya , Wang Kang , Zhu Yongsheng , Hou Feng , Wang Xiaolei
Published: February 2025

To effectively diagnose open-circuit (OC) faults in the insulated gate bipolar transistor (IGBT) of a cascaded H-bridge rectifier (CHBR) in real-time, this paper uses a single-phase three-cell CHBR as an example. Through mechanism analysis, the variation patterns of the capacitor voltage and grid current due to OC faults are defined. Based on this, the DC capacitor voltage threshold (VT) and the grid current coefficient of variation (CCV) are introduced as fault diagnosis indices, and a real-time OC fault diagnosis method for CHBR is established. The robustness, accuracy, timeliness, and universality of the proposed method are validated through simulations. The results show that the proposed method exhibits strong robustness when the grid voltage fluctuates, either dropping from 3 kV to 2.85 kV or rising from 3 kV to 3.15 kV. Compared to existing diagnostic methods, the proposed approach requires less diagnostic time, with the faulty IGBT being identified in as little as 3.09 ms under optimal conditions. Additionally, the diagnostic performance remains unaffected by changes in control strategies, making it universally applicable for OC fault diagnosis in CHBR under various control strategies (such as dq current decoupling control, PR current control, and transient current control), with comparable diagnosis results and speeds.
The State of the Art of Research on Power Supply Technologies for Moving Targets
Authors: Ruan Man , Wang Xudong , Xu Wanli , Wang Mengyi , Chen Peiqiang , Chen Jinmao
Published: February 2025

With the advancement of power electronics, control systems, and related technologies, devices such as unmanned aerial vehicles (UAVs), airships, and electric vehicles (EVs) have become integral to modern life and industry. However, limited battery capacity, short battery life, attenuated battery performance, environmental sensitivity, and long charging time result in range anxiety in electrically driven devices, which has become an important factor restricting their development. This paper reviews the current status of power supply technologies for moving targets, categorizing them into contact charging, autonomous power supply, and wireless power transfer (WPT) methods. The principles, advantages, disadvantages, and applications of each approach are thoroughly analyzed. Comparative analysis highlights that WPT technology, which eliminates the need for electrical connections between the transmitter and receiver, offers notable advantages, including high flexibility, extended charging distances, and simultaneous power delivery to multiple targets. These features make it particularly well suited for the energy requirements of moving devices. Accordingly, this paper emphasizes the key technologies and future development directions of microwave WPT (MWPT) and laser WPT (LWPT) to facilitate the broader adoption of dynamic wireless power supply systems for moving targets.
Finetuned Deep Learning Models for Fuel Classification: A Transfer Learning-Based Approach
Authors: Shanmugam Hemachandiran , Gnanasekaran Aghila
Published: February 2025

Accurately classifying petrol and diesel fuel using an image processing method is crucial for fuel-related industries such as petrol pumps, refineries, and fuel storage facilities. However, distinguishing between these fuels using traditional methods can be challenging due to their similar visual characteristics. This study aims to enhance the accuracy and robustness of existing fuel classification by utilizing the transfer learning-based finetuned pre-trained deep learning models and ensemble approaches. Specifically, we upgrade pre-trained deep models like ResNet152V2, InceptionResNetV2, and EfficientNetB7 by incorporating additional layers. Through transfer learning, these models are adapted to the specific task of classifying petrol and diesel fuels. To evaluate their performance, the upgraded deep model and an ensemble of these models are tested on a synthetic dataset. The results indicate that the ensemble of upgraded ResNet152V2, InceptionResNetV2, and EfficientNetB7 achieves recall, precision, f-score, and accuracy scores of 99.54%, 99.69%, 99.62%, and 99.67%, respectively. Moreover, a comparative analysis reveals that the upgraded models outperform state-of-the-art baseline models.
A Review of Condition Monitoring of Permanent Magnet Synchronous Machines: Techniques, Challenges and Future Directions
Authors: Sergakis Alexandros , Salinas Marios , Gkiolekas Nikolaos , Gyftakis Konstantinos N.
Published: February 2025

This paper focuses on the latest advancements in diagnosing faults in Permanent Magnet Synchronous Machines (PMSMs), with particular attention paid to demagnetization, inter-turn short circuits (ITSCs), and eccentricity faults. As PMSMs play an important role in electric vehicles, renewable energy systems and aerospace applications, ensuring their reliability is more important than ever. This work examines widely applied methods like Motor Current Signature Analysis (MCSA) and flux monitoring, alongside more recent approaches such as time-frequency analysis, observer-based techniques and machine learning strategies. These methods are discussed in terms of strengths/weaknesses, challenges and suitability for different operating conditions. The review also highlights the importance of experimental validations to connect theoretical research with real-world applications. By exploring potential synergies between these diagnostic methods, the paper outlines ways to improve fault detection accuracy and machine reliability. It concludes by identifying future research directions, such as developing real-time diagnostics, enhancing predictive maintenance and refining sensor and computational technologies, aiming to make PMSMs more robust and fault-tolerant in demanding environments. In addition, the discussion highlights how partial demagnetization or ITSC faults may propagate if not diagnosed promptly, necessitating scalable and efficient multi-physics approaches. Finally, emphasis is placed on bridging theoretical advancements with industrial-scale implementations to ensure seamless integration into existing machine drive systems.
Exploring Performance Degradation of Proton Exchange Membrane Fuel Cells Based on Diffusion Transformer Model
Authors: Lv Lingling , Pei Pucheng , Ren Peng , Wang He , Wang Geng
Published: February 2025

Proton exchange membrane fuel cells (PEMFCs) stand at the forefront of energy conversion technology, efficiently converting the chemical energy of hydrogen and oxygen directly into electricity. Research on predicting the remaining useful life of PEMFCs has long been a focus, as it plays a crucial role in preventing failures and mitigating safety risks. This paper introduces a robust diffusion transformer (DiT) model, which is a novel approach leveraging generative artificial intelligence (GAI) technology to innovate the existing methods for predicting the performance degradation of PEMFCs. This model employs random Gaussian noise to generate stable performance degradation data of PEMFCs under specified conditions. The predictive accuracy is then assessed by benchmarking against a bi-directional long short-term memory recurrent neural network (Bi-LSTM) using two distinct experimental datasets. The evaluation shows that the DiT model achieves higher predictive accuracy than the reference model. Specifically, the mean absolute prediction error is reduced by 72.7% under steady-state conditions and 59.3% under dynamic conditions. Correspondingly, the remaining useful life error (RE) is diminished by 80% and 88%, respectively. These findings indicate that the DiT model has significant potential in PEMFCs performance degradation research.
Exposures of Western Australian Wildland Firefighters: Insights from Real-Time Monitoring
Authors: Padamsey Kiam , Liebenberg Adelle , Wallace Ruth , Oosthuizen Jacques
Published: February 2025

Background: Inhalation of bushfire smoke is a risk to the health of firefighters, particularly across Australia where bushfires are becoming more frequent and intense. This study aimed to use real-time monitoring devices to assess the particle and chemical exposures of Western Australian firefighters during prescribed burns and bushfires. Methods: Participants included volunteer bushfire firefighters and forestry firefighters. Real-time gas and particulate monitors were used across nine unique fire events to evaluate the occupational exposures of firefighters. Findings: Firefighters (n = 40) were exposed to high concentrations of particulate matter (PM), particularly PM10, with concentrations varying widely between individuals and events. Exposures to carbon monoxide (CO) and volatile organic compounds (VOCs) were observed at elevated levels. No significant elevation in internal polycyclic aromatic hydrocarbons (PAHs) was observed. Conclusions: This study highlights the importance of respiratory protective equipment (RPE) and the need for health monitoring programmes for firefighters. Prescribed burns appear reflective of exposures at bushfires and could serve as valuable experimental settings for refining firefighting strategies and protective practises.
Decision Science for Multi-Objective Fuel Management: Integrating Fire Risk Reduction and Biodiversity Conservation
Authors: Cawson Jane G. , Burton Jamie E. , Pickering Bianca J. , Marshall Erica , Elliot-Kerr Shona , Parkins Kate , Penman Trent D.
Published: February 2025

Wildfires threaten human health, economies and the environment. Fuel management is a core activity of land managers to reduce the detrimental impacts of wildfires. Land managers also seek to conserve biodiversity within their fuel management programs. We sought to understand how fuel management could be implemented to achieve fire risk reduction and biodiversity conservation in the same landscape. Specifically, we asked: (1) what vegetation attributes are desirable for wildfire risk reduction and biodiversity conservation, and are they compatible? and (2) what combinations of management actions could achieve both objectives? We used structured decision-making with 23 stakeholders from eight organisations to elicit means objectives and management actions for fire risk reduction and biodiversity conservation in dry eucalypt forests and woodlands. Vegetation attributes identified as desirable to reduce fire risk were often compatible with those desired for biodiversity conservation, suggesting management actions could achieve both objectives in the same landscape. Workshop participants often selected prescribed burning as a management action, and specifically, mixed severity, patchy burns for biodiversity conservation. Predator control, habitat creation and revegetation were coupled with burning and mechanical treatments to improve outcomes for biodiversity. There was uncertainty around the likelihood of success for most management actions, highlighting the need for adaptive management to test and refine management over time. Overall, structured decision-making allowed for integration of a range of stakeholder perspectives into the development of multi-objective fuel management pathways. This approach forms a basis for designing more socially acceptable fuel management programs.
Lactic Acid Bacteria Exopolysaccharides Unveiling Multifaceted Insights from Structure to Application in Foods and Health Promotion
Authors: Liu Wei , Wei Yajun , Xiang Rong , Dong Bo , Yang Xi
Published: February 2025

Lactic acid bacteria (LAB) exopolysaccharides (EPSs) have garnered significant scientific interest due to their multifaceted roles in food technology and health promotion. This comprehensive review systematically examines the structural classification of LAB EPSs, emphasizing distinctions between homo-and heteropolysaccharides, as well as the influence of substituent groups (e. g., acetyl, phosphate) on their physicochemical and bioactive properties. Advanced isolation methodologies, including ethanol precipitation and ultrafiltration, coupled with characterization techniques such as nuclear magnetic resonance (NMR) spectroscopy and atomic force microscopy (AFM), are vital for deciphering their chemical and physical characteristics. The biosynthesis pathway, governed by eps operons and modulated by environmental factors (e.g., carbon sources, Ca2+), are discussed as targets for genetic engineering to enhance yield and functionality. Functionally, LAB EPSs display antioxidant, immunomodulatory, anti-tumor, anti-viral, and anti-biofilm activities, with demonstrated applications as natural additives in the food industry, prebiotics, and drug delivery systems. Despite their potential, challenges such as cost-effective production and regulatory hurdles persist. Future research should prioritize the elucidation of molecular mechanisms, clinical validation of health claims, and sustainable bioprocessing innovations to fully harness the transformative potential of LAB EPSs across food, pharmaceutical, and agricultural industries.
Exploring the Potential of Olive By-Products in Bísaro Pig Feed: Effects on the Chemical Compositions and Fatty Acid Profiles of Three Different Muscles
Authors: Paié-Ribeiro Jessica , Pinheiro Victor , Guedes Cristina , Gomes Maria José , Teixeira José , Leite Ana , Vasconcelos Lia , Teixeira Alfredo , Outor-Monteiro Divanildo
Published: February 2025

The olive oil industry generates large quantities of olive cake (OC), making its use in animal feed an environmentally sustainable alternative. Considering that the ham of Bísaro pigs is traditionally used for the production of cured ham, the analysis of raw meat is essential to understand how diet influences its quality before the maturation process. This study examined the effect of different types of OC in the diets of Bísaro pigs, focusing on the chemical compositions and fatty acid profiles of three fresh ham muscles—biceps femoris (BF), semimembranosus (SM), and semitendinosus (ST). Forty Bísaro pigs were assigned to five diets: control (CD), 10% raw OC (COC), two-phase OC (TPOC), exhausted OC (EOC), and exhausted OC with 1% olive oil (EOC-OO). The diets significantly influenced moisture, protein, collagen, and haem pigments (p < 0.05). TPOC had the highest moisture content, while CD had the lowest. Protein levels were higher in BF and SM for OC-fed pigs. Collagen in ST was highest in CD and lowest in EOC. Haem pigments varied, with EOC highest in BF and ST and EOC-OO highest in SM. Significant MUFA differences were found in BF (p < 0.001), highest in CD and lowest in TPOC. PUFA levels and the PUFA/SFA ratio were highest in TPOC (p < 0.001), while SFA remained unchanged. The results suggest that up to 10% OC can be included in pig diets without compromising meat quality, but factors such as economic viability and nutritional variability must be considered. This study provides new insights into how OC affects muscle composition, contributing to optimizing feeding strategies for better meat quality and sustainability.
Rehydration Beverages Made from Quercus sideroxyla Infusion, Probiotics, and Prebiotics: Antioxidant and Anti-Inflammatory Potential
Authors: Salas-Ramírez Carlos Alonso , Moreno-Jiménez Martha Rocío , Rocha-Guzmán Nuria Elizabeth , Gallegos-Infante José Alberto , González-Laredo Rubén Francisco , González Herrera Silvia Marina , González-Mercado Manuel Efraín , Herrera-Rocha Karen Marlenne , Cháirez-Ramirez Manuel Humberto
Published: February 2025

High rehydration beverage consumption represents a significant opportunity for the integration of biotic products that offer the potential to improve body composition and intestinal health. Quercus sideroxyla (IQS) infusions contain polyphenolic compounds with antioxidant and anti-inflammatory properties, and in combination with probiotic strains and prebiotic materials, they offer a promising alternative for generating designer beverages for physically active people. These beverages were formulated using a combination of IQS, agave fructooligosaccharides (FOS), microencapsulated probiotics of Akkermansia muciniphila and Bifidobacterium longum, electrolytes, and glucose. Stable microencapsulated probiotics were obtained by spray drying, using agave gums (PD > 10) and gum arabic as wall materials. The beverage formulations were generated with different percentages of FOS (A:1.6%, B:1.2%, and C:0.8%). The phenolic profile of the beverages was determined by LC-MS/MS, indicating a difference in the concentration of compounds, highlighting changes associated with the addition of FOS compared with IQS. Sensory analyses indicate a preference for the beverage with the highest FOS concentration. The antioxidant potential of the formulations, determined by ABTS, DPPH, and ORAC, showed no differences between the drinks; however, analyses indicate a positive correlation with quinic acid, t-cinnamic acid, quercetin 3-O-glucoside, and total phenolic content, suggesting a synergistic effect. The drinks with higher FOS content exhibited a higher anti-inflammatory potential (EMA). Therefore, it can be concluded that a rehydrating drink with a higher FOS content offers a prebiotic effect with potential anti-inflammatory activity and, according to the panelists, is a suitable drink for evaluating its effects on body composition and intestinal health in people who have recently started physical activity.
Characterization of Volatile Substances in Pu-erh Tea (Raw Tea) at Different Storage Times
Authors: Liu Yang , Wang Zhixia , Zhang Xinyi , Chen Hongyu , Ruan Dianrong , Bai Silei , Huang Jianan , Liu Zhonghua
Published: February 2025

There is a lack of theoretical evidence regarding the transformation of the aroma of Pu-erh tea (raw tea) during long-term storage. In this study, we comprehensively investigate the aroma characteristics of Pu-erh tea (raw tea) from the same manufacturer, stored for different storage times (7–21 years). Sensory evaluation and qualitative and quantitative analysis of volatile substances were performed on the experimental samples. The results showed that the aroma of Pu-erh tea (raw tea) changed from fruity/floral to smoky and fragrance during the storage process. A total of 290 volatiles were identified by HS-SPME/GC×GC-Q-TOF-MS. The key substances for the fruity/floral aroma are fenchene, (E)-1,2,3-trimethyl-4-propenyl-Naphthalene, (+/−-theaspirane, and decanal, and the key substances for the smoky aroma were 2-ethyl-Furan, camphene, 1-methyl-4-(1-methylethenyl)-Benzene, and cis-β-Ocimene. The key aroma substances for the fragrance aroma are 1-methyl-4-(1-methylethylidene)-Cyclohexene, α-Terpinene, trans-β-Ocimene, (E,E)-2,4-Heptadienal, octanal, 2,5-Dimethoxyethylbenzene, 2,4-Dimethylanisole, 1,2,3-Trimethoxybenzene, and 3,4-Dimethoxytoluene. This study helps us to understand further the aroma changes of Pu-erh tea (raw tea) during long-term storage.
Integrated RNA-Seq and Metabolomics Analyses of Biological Processes and Metabolic Pathways Involved in Seed Development in Arachis hypogaea L.
Authors: Li Long , Wang Yutong , Jin Xiaorui , Meng Qinglin , Zhao Zhihui , Liu Lifeng
Published: February 2025

In peanut cultivation, fertility and seed development are essential for fruit quality and yield, while pod number per plant, seed number per pod, kernel weight, and seed size are indicators of peanut yield. In this study, metabolomic and RNA-seq analyses were conducted on the flowers and aerial pegs (aerpegs) of two peanut cultivars JNH3 (Jinonghei) and SLH (Silihong), respectively. Compared with SLH, JNH3 had 3840 up-regulated flower-specific differentially expressed genes (DEGs) and 5890 up-regulated aerpeg-specific DEGs. Compared with the JNH3 aerpegs, there were 4079 up-regulated variety-specific DEGs and 18 up-regulated differentially accumulated metabolites (DAMs) of JNH3 flowers, while there were 3732 up-regulated variety-specific DEGs and 48 up-regulated DAMs in SLH flowers. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed that the DEGs of JNH3 were associated with pollen germination and phenylalanine metabolism in flower and aerpeg tissues, respectively. In contrast, the DEGs of SLH were associated with protein degradation, amino acid metabolism, and DNA repair. However, there were significant differences in the lipids and lipid-like molecules between JNH3 flowers and SLH flowers. This investigation provides candidate genes and an experimental basis for the further improvement of high-quality and high-yield peanut varieties.
Assessing Future Changes in Mean Radiant Temperature: Considering Climate Change and Urban Development Impacts in Fredericton, New Brunswick, Canada, by 2050
Authors: Amini Hossein , Jabari Shabnam , McGrath Heather
Published: February 2025

Urban development and climate change are two main impacting factors in the thermal environment of cities. This study aims to analyze future changes in Mean Radiant Temperature (MRT), one of the main contributors to human thermal comfort and the concept of Urban Heat Island (UHI), considering climate change and urban development scenarios in the study area, Fredericton, New Brunswick, by 2050. The analysis utilizes the SOLWEIG (Solar and Longwave Environmental Irradiance Geometry) model from the Urban Multi-scale Environmental Predictor (UMEP) platform to calculate MRT values. By integrating these two impacting factors, this research provides insights into the potential future changes in MRT levels and the resulting thermal conditions and geohazards in the study area. The analysis enables the identification of areas susceptible to increased radiant heat exchange due to the proposed changes in land cover, urban morphology, and air temperature. Furthermore, this study contributes to a better understanding of the complex interactions between climate change, urbanization, and urban microclimates. By incorporating MRT assessments and prioritizing thermal comfort, cities can develop strategies to mitigate the negative effects of UHI and create sustainable and livable urban environments for future generations.
An Evaluation of Orthotics on In-Toeing or Out-Toeing Gait
Authors: Bollepalli Harshavardhan , White Carter J. K. , Kodra Jacob Dane , Liu Xue-Cheng
Published: February 2025

Background and Objectives: In-toeing and out-toeing gait are rotational deformities commonly observed in children with neuromuscular conditions. These gait abnormalities often result from internal tibial torsion, increased femoral anteversion, and metatarsus adductus. This study was conducted to create a comprehensive evaluation of the effectiveness of lower extremity orthotics as a non-operative treatment option, given their regular use in clinical settings. The aim of this literature review was to understand the efficacy of various orthotic devices in correcting rotational deformities in the transverse plane, thereby improving ambulation stability and 3D joint motion. Materials and Methods: Literature published after 1 January 1990 was reviewed, utilizing databases such as CENTRAL (Wiley), CINAHL (EBSCO), Medline (OVID), Scopus (Elsevier), and Web of Science (Clarivate). In totality, 13 studies were included, evaluating 365 participants with neuromuscular conditions using various orthotic devices. Results: Among these studies, two were randomized control trials (Level 1), nine were quasi-experimental studies (Level 2), and two were case studies (Level 4). Quality assessment determined that 69% of the included studies had a low risk of bias, while 31% demonstrated a moderate risk. Compression garments and rotational systems showcased the greatest change in proximal lower extremity rotation at 19.73° ± 1.57 and 24.13° ± 8.49, respectively. The most significant difference in foot progression angle is through the use of rotational systems, 19° ± 26.87. Conclusions: In a short-term treatment, children with neuromuscular disorders exhibiting in-toeing or out-toeing gait may benefit from different types of orthoses. Compression garments may aid joint alignment and enhance proprioception, rotational systems correct alignment with precise adjustability, AFOs that achieve effective stabilization can deliver benefits in the transverse plane, and foot orthotics may be appropriate for mild gait abnormality management.
Exploring the Potential Causal Relationship Between Health Insurance Coverage and Child Nutritional Status in Pakistan: Evidence from PDHS-2018
Authors: Shahid Muhammad , Ali Zaiba , Khan Subuhi , Yousaf Muhammad Shahzad , Zhang Zhe , Song Jiayi
Published: February 2025

Objectives: the current study investigates the link between health insurance coverage and child nutritional status in Pakistan. Methods: Using data from the Pakistan Demographic and Health Survey (PDHS) 2017–18, encompassing 4499 children under 5, a binary logistic regression was applied to analyze the relationship between health insurance and child nutritional status. Due to the non-randomized sample, assessing health insurance continuously posed a practical challenge. To mitigate the sample selection bias, the cross-sectional-based propensity score matching (PSM) using the nearest neighbor method was utilized for the causal relationship, based on potential socio-economic covariates. Results: The prevalence rates of stunting, underweight, and wasting among children under five were 38.13%, 23.04%, and 8.05%, respectively. Malnutrition was found in 43.64% of non-insured children compared with 5% in insured children. The findings of PSM supported a causal relationship, given the cross-sectional nature and potential misplaced variables, as the PSM findings revealed that insured children had significantly better nutritional outcomes compared with non-insured children, with a significance level of 1%. The logistic regression outcomes for the covariates of child nutritional outcome indicated that health insurance coverage, higher wealth status, mother’s education, improved water and sanitation facilities, mother’s normal BMI, and urban residence reduced the likelihood of child malnutrition. The logistic regression results for the covariates of child health insurance depicted that factors such as higher birth order, mother’s low BMI, poor water and sanitation facilities, higher wealth status, women’s employment, higher education level, and child illnesses like diarrhea and malnutrition increased the likelihood of obtaining health insurance. The logistic results confirmed that health insurance coverage reduced the likelihood of child malnutrition, and, similarly, child malnutrition and other illnesses increased the chances of obtaining health insurance coverage. Conclusions: The findings underscore the critical need for health insurance, highlighting its role in enhancing child nutritional status. The government should expand health insurance programs, with a special emphasis on child nutrition and health.
From Newton’s Laws to Walras’ Equilibrium: A Historical Perspective on Determinism in Economics and Social Sciences
Authors: Capoani Luigi
Published: February 2025

Focusing on a specific interaction between physics and economics, this study delves into the realm of econophysics and investigates the birth, evolution, and practical applications of this interdisciplinary field. This study explores the influence of Newton’s laws, the concept of gravity, and, more generally, mechanical physics on the development of economic thought. It examines the application of Newtonian principles in interpreting economic dynamics, with a particular focus on the contributions of neoclassical economists and Isard’s gravitational model, offering insights into the intricate dynamics of economic equilibrium in complex systems. Finally, these concepts are situated within the broader debate between determinism and indeterminism in the social sciences.
Thermal Tolerance and Mortality of the Texas Pigtoe (Fusconaia askewi) Under Experimental Conditions
Authors: Rumbelow Sara , Williams Marsha , Williams Lance
Published: February 2025

Systemic habitat destruction over the last 100 years combined with major anthropogenic stressors such as aquatic contaminants, exotic species, and economic endeavors is driving the decline in freshwater unionid species diversity. Global temperatures continue to increase, with January 2024 being the warmest on record according to the latest report by the World Meteorological Organization. Freshwater mussels play a crucial role in aquatic ecosystems, contributing significantly to benthic processes in rivers and streams, yet they remain highly sensitive to environmental changes. This study specifically investigates the thermal tolerance of the Texas pigtoe (Fusconaia askewi) under elevated temperature conditions and explores the implications for developing effective conservation strategies in freshwater ecosystems. Eighty-four individual adult Texas pigtoe mussels were collected from the upper Sabine River near Hawkins, Texas, and taken to the University of Texas at Tyler to evaluate the effects of elevated temperature, a likely factor impacting mussels in East Texas. In the thermal tolerance study presented here, 100% survival occurred at both the control (20 °C) and the 25 °C test points. The 30 °C treatment group had an overall mortality of 14% and the 35 °C treatment group showed a mortality rate of 43% by the end of the trial, suggesting the typical summer temperatures in Texas streams will result in the loss of a portion of an otherwise healthy population.
Feasibility of Retrofitting a Conventional Vessel with Hydrogen Power Systems: A Case Study in Australia
Authors: Khan Muhammad Waris Yaar , Fan Hongjun
Published: February 2025

As the pursuit of greener energy solutions continues, industries worldwide are turning away from fossil fuels and exploring the development of sustainable alternatives to meet their energy requirements. As a signatory to the Paris Agreement, Australia has committed to reducing greenhouse gas emission by 43% by 2030 and reaching net-zero emissions by 2050. Australia’s domestic maritime sector should align with these targets. This paper aims to contribute to ongoing efforts to achieve these goals by examining the technical and commercial considerations involved in retrofitting conventional vessels with hydrogen power. This includes, but is not limited to, an analysis of cost, risk, and performance, and compliance with classification society rules, international codes, and Australian regulations. This study was conducted using a small domestic commercial vessel as a reference to explore the feasibility of implementation of hydrogen-fuelled vessels (HFVs) across Australia. The findings indicate that Australia’s existing hydrogen infrastructure requires significant development for HFVs to meet the cost, risk, and performance benchmarks of conventional vessels. The case study identifies key determining factors for feasible hydrogen retrofitting and provides recommendations for the success criteria.
Assessment of Systemic and Periodontal Conditions in Pregnant Women and Their Impact on Neonatal Birth Weight: A Prospective Cohort Study
Authors: Jesuino Bruno Gualtieri , Foratori Gerson Aparecido , Castilho Ana Virgínia Santana Sampaio , da Silva Pinto Ana Carolina , Meira Gabriela de Figueiredo , Sales-Peres Sílvia Helena de Carvalho
Published: February 2025

The aim of this study was to assess some variables of women in the 27th week of pregnancy and after childbirth, in addition to determining which of these variables were associated with low birth weight during the coronavirus disease (COVID-19) pandemic. The patients were divided into two groups: mothers with normal-weight babies (G1 = 60) and mothers with below-normal-weight babies (G2 = 16). The variables assessed were education, monthly family income, anthropometric parameters, systemic health, periodontal condition, oral hygiene habits, Oral Health Impact Profile–14 results, data from the babies at birth, and a COVID-19 diagnosis during pregnancy. The mothers in G1 showed greater weight gain during pregnancy. There was an increase in tooth plaque percentage, probing pocket depth, and clinical attachment level during the study period for both groups and an increase in periodontitis cases in the patients from G1. The mothers from G1 had longer pregnancy periods and delivered taller babies with a higher body mass index. A one-unit increase in weight during pregnancy decreases the likelihood of having a below-normal-weight baby by 11.3% [confidence interval = 2.4–20.4%]. Weight gain during pregnancy is a protective factor that decreases the likelihood of babies being born with below-normal weights.
Digital Transformation and the Quality of Accounting Information Systems in the Public Sector: Evidence from Developing Countries
Authors: Hamdy Arafat , Diab Ahmed , Eissa Aref M.
Published: February 2025

This study explores how digital transformation affects the accounting and auditing profession and the quality of the accounting information system in governmental units in two developing contexts in the Middle East and North African (MENA) region—Egypt and Saudi Arabia. We collected data by electronically surveying governmental units’ employees in the two countries and analyzed them using linear regression analyses. Interestingly, we found a negative effect of digital transformation on the quality of accounting information systems, which could be interpreted concerning the premature status of digital technologies in emerging markets. However, the negative effect of digital transformation was lower in Egypt compared to Saudi Arabia. This study contributes to the literature by focusing on the governmental sector and investigating a new context—the MENA region—which has rarely been examined in previous studies. Further, it has implications for regulators in the public sector for developing governmental financial reports by supporting the digital transformation process.