bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparison of Computerized Dynamic Posturography and Functional Head Impulse Test Scores Obtained after 30 Minutes of Hatha Yoga Practice and Resistance-Based Aerobic Exercise in Adult Female Yoga Practitioners
Authors: Aras Çağla , Bolat Kübra Binay , Önlü Aysberg Şamil , Aran Mine Baydan , Aras Dicle 
Published: January 2025

Abstract

Objective; The purpose of this study was to investigate the immediate effects of a thirty-minute session of Hatha yoga and a thirty-minute session of resistance-based aerobic exercise on balance and vestibulo-ocular reflex in adult female yoga practitioners. Equipment and Methods; Ten participants underwent balance and vestibulo-ocular reflex assessments at rest, after Hatha yoga, and after resistance-based aerobic exercise. Balance was measured using computerized dynamic posturography, and vestibulo-ocular reflex was evaluated with a functional head impulse test. The Hatha yoga session included twenty-five minutes of yoga poses followed by five minutes of relaxation. The aerobic exercise session was performed at an intensity of seventy to seventy-five percent of heart rate reserve. Results; No significant changes were observed in vestibulo-ocular reflex parameters across conditions. However, balance scores showed significant improvements following resistance-based aerobic exercise compared to both resting and post-yoga conditions. The somatosensory and visual system scores increased significantly after resistance-based aerobic exercise, as did the overall balance score. Lower body weight, lean body mass, and total body water were positively associated with better balance outcomes. Conclusion; While neither Hatha yoga nor resistance-based aerobic exercise acutely influenced vestibulo-ocular reflex, resistance-based aerobic exercise had immediate positive effects on balance and postural stability.
The Role of Triple CFTR Modulator Therapy in Reducing Systemic Inflammation in Cystic Fibrosis
Authors: García Marta Solís , Madrid-Carbajal Claudia Janeth , Laderas Adrián Peláez , Moreno Rosa María Girón , Alonso Esther Ferreira , García Belén Prieto , Punter Rosa Mar Gómez , Bermúdez Julio Ancochea , Bachiller Jose María Eiros , Clemente Marta María García 
Published: January 2025

Abstract

Purpose: Cystic fibrosis (CF) is a genetic disease caused by mutations in the CFTR gene, leading to multisystemic complications, particularly in the lungs. CFTR dysfunction results in altered ion transport, chronic inflammation, and progressive lung damage. The triple therapy elexacaftor/tezacaftor/ivacaftor (ETI) has demonstrated significant improvements in pulmonary function and quality of life. This study aimed to evaluate the anti-inflammatory effects of ETI by analysing systemic cytokine profiles over 12 months.
Methods: A prospective study included 32 CF patients ≥18 years with at least one F508del mutation, undergoing ETI therapy. Clinical stability was ensured prior to therapy initiation. Demographic data, BMI (Body Mass Index), FEV1% (Forced expiratory Volume in the first second), VR/TLC (residual volume/total lung capacity) and sweat chloride concentrations were recorded at baseline, 6 months and 12 months. Inflammatory markers, including fibrinogen, C-reactive protein (CRP), and a panel of 8 cytokines, were measured using multiplex bead-based immunoassays and electrochemiluminescence. Longitudinal changes were analysed using mixed-effects models and statistical tests, with significance set at p < 0.05.
Results: During a 12-month follow-up, the neutrophils number and proinflammatory biomarkers analyzed, fibrinogen, CRP, TNF- α, IFN-gamma, IL-1 alpha, IL-1 beta, IL-6, IL-8, IL-12, IL-17, significantly decreased, while eosinophils remained stable. Mixed-effects models confirmed the significant association of inflammatory biomarkers with FEV1, BMI, sweat chloride levels, and VR/TLC highlighting the role of inflammation in the progression of CF.
Conclusions: ETI demonstrated marked anti-inflammatory effects in CF patients, reducing systemic inflammation and improving clinical parameters.
2-Chloroethanol Induces Hepatic Toxicity by Disrupting Endoplasmic Reticulum Homeostasis Ameliorated by Dimethyl Sulfoxide
Authors: Chou Tzung-Hsin , Hu Min-Hsiu , Hua Kuo-Tai , Fang Cheng-Chung 
Published: January 2025

Abstract

2-Chloroethanol (2CE), a metabolite of ethylene oxide (EO), vinyl chloride (VC), and 1,2-dichloroethene (1,2-DCE), has an unclear toxic mechanism, complicating effective treatment of poisoning. This study examined the impact of acute 2CE exposure on endoplasmic reticulum (ER) homeostasis in liver cells. A single intraperitoneal injection of 130 mg/kg 2CE (approximately LD50) in mice caused severe liver damage and steatosis, along with increased ER stress and activation of the unfolded protein response (UPR) and autophagy. In H4IIEC3 rat hepatocytes, 2CE activated all three UPR pathways—IRE1, PERK, and ATF6—at both the gene and protein levels, and induced lysosomal accumulation, lipid droplet formation, and apoptosis. Among chemical chaperones tested, dimethyl sulfoxide (DMSO, 0.1–0.6%) showed the most potent therapeutic effects, reducing misfolded protein accumulation, alleviating ER stress, and suppressing apoptosis, even when autophagy was inhibited. These findings reveal that 2CE disrupts protein and lipid homeostasis in hepatocytes and highlight DMSO as a promising therapeutic agent for 2CE-induced toxicity.
USFF: A Unified Sales Forecasting Framework with Fourier-Enhanced Decomposed Net
Authors: Li Qianyang , Zhang Xingjun , Wang Shaoxun , Cao Jiawei , Tao Peng 
Published: January 2025

Abstract

With the widespread adoption of big data science, the retail industry has seen an increasing demand for data-driven decision-making. As a critical task within the sector, product sales forecasting faces significant challenges. Traditional statistical methods are limited by their reliance on assumptions of data stationarity, while DL and ML techniques enhance accuracy but struggle to fully address complex features such as temporal dependencies, nonlinear trends, and external influences. No single method proves universally effective across all scenarios. To tackle these challenges, this paper introduces a Unified Sales Forecasting Framework (USFF) for vending machine sales prediction, which integrates statistical methods, machine learning, and deep learning techniques. By classifying data based on statistical features and employing multi-model fusion strategies, the USFF framework effectively captures the complex nature of sales data, significantly improving prediction accuracy by leveraging the strengths of various models. Furthermore, the paper presents a novel deep learning forecasting model, FEDNet (Fourier-Enhanced Decomposed Net), designed to address the dynamic dependencies and seasonal patterns inherent in long time series. FEDNet offers substantial advantages in capturing long-term dependencies and dynamic changes in time series data through the integration of reversible instance normalization, seasonal-trend decomposition, and Fourier decomposition.Experiments conducted on over 30 million real-world data points, along with five public datasets, demonstrate that the proposed framework and deep learning model outperform baseline methods across multiple evaluation metrics, confirming their effectiveness and reliability. The proposed framework and algorithm have been successfully implemented in a retail company in China, providing valuable business decision-making support for operational strategies.
Sentiment Analysis of Imbalanced Dataset through Data Augmentation and Generative Annotation using DistilBERT and Low-Rank Fine-Tuning
Authors: Nasrabadi Hossein Nekkouei , Moattar Mohammad Hossein 
Published: January 2025

Abstract

This paper proposes a novel approach to sentiment analysis of imbalanced datasets, focusing on data augmentation and efficient fine-tuning. We address the challenge of limited minority class representation by leveraging GPT-4 to generate synthetic tweets via paraphrasing and back- translation (using Italian as an intermediary language). Furthermore, the main contribution is that we utilize GPT-4 to annotate tweets with positive reasons, derived by inverting the ten predefined negative categories within the dataset. The augmented dataset trains a DistilBERT model for sentence embeddings, and Low-Rank Adaptation (LoRA) enables efficient fine-tuning. A SoftMax layer provides classification into positive, neutral, and negative sentiments. Experiments on the Twitter US Airline Sentiment dataset demonstrate our approach’s efficacy, achieving 100% accuracy with minimal training time, highlighting the importance of data augmentation and efficient fine-tuning for robust sentiment analysis, particularly with imbalanced datasets.
Association between Digestive Diseases, Nighttime Sleep, and Depressive Symptoms among the Middle-aged and Elderly Adults: A Mediation Analysis
Authors: Cheng Congcong , Guo Dinghui , Cao Xu , Wang Dingmin , Li Wenling , Miao Bei , Fei Sujuan 
Published: January 2025

Abstract

Backgrounds:
As the population ages, the relationship among digestive diseases, nighttime sleep duration, and depressive symptoms in middle-aged and elderly adults, especially sleep's mediating role, remains unclear, thus prompting research.
Aims
To explore how nighttime sleep duration mediates between digestive diseases and depressive symptoms in this group, aiming to guide clinical treatment of related depression.
Methods
Using 2015–2020 China Health and Retirement Longitudinal Study (CHARLS) data, we applied difference, Spearman correlation, and multivariate logistic regression analyses. A mediating effect model was set up and tested via the Bootstrap method.
Results
Digestive diseases had a 23.05% prevalence rate, and depressive symptoms had a 35.90% detection rate. Both digestive diseases (OR = 1.55, 95% CI: 1.38–1.73) and insufficient nighttime sleep (OR = 2.17, 95% CI: 1.97–2.40) significantly affected depressive symptoms. The model showed that insufficient nighttime sleep had a partial mediating effect.
Discussion
Clinically, treating relevant patients requires a holistic approach with an emphasis on sleep. Future research should use objective measures and longitudinal studies to clarify mechanisms and causalities.
Conclusion
Digestive diseases can cause insufficient sleep, promoting depressive symptoms. Clinicians should not overlook sleep quality when treating digestive patients with comorbid depression, as improving sleep may relieve symptoms.
Effect of textures on oxygen reduction electrocatalysis by self-supporting Fe-N-C materials from a universal template synthesis
Authors: Hu Linwei , Ma Hongru , Meng Ziwei , Li Peng , Xiang Kun , Xue Tong , Yan Xiang-Hui 
Published: January 2025

Abstract

Self-supporting Fe-N-C materials with certain ordered mesopores were synthesized through confined carbonization, alkali etching and final anneal by utilizing mesoporous silicas with varied textural properties, polymerized aniline and iron chloride as the hard template, carbon/nitrogen and iron precursors, respectively. These duplicated Fe-N-C materials have orderly mesoporous structure with large pore diameter, pore volume and specific surface area. As a result, all of them showed excellent electrocatalytic activity towards oxygen reduction reaction (ORR) in 0.1 M KOH with 4-electron pathway and half-wave potential (E1/2) > 0.82 V vs. RHE, indicating that the nano-casting method using mesoporous silicas as the hard template is a universal approach for constructing highly active Fe-N-C catalysts. The activity order of PANI-Fe-HT2(MCF) > PANI-Fe-HT2(MCM-48) ≈ PANI-Fe-HT2(KIT-6) > PANI-Fe-HT2(SBA-15) > PANI-Fe-HT2(MCM-41) suggests that the three dimensional (3D) interconnected mesoporous structure of hard templates (MCF, MCM-48 and KIT-6) is generally more favorable for fabricating high-performing Fe-N-C materials. The highest onset potential (Eonset) and E1/2 obtained on the PANI-Fe-HT2(MCF) reached 0.99 and 0.86 V, respectively, which even slightly surpass those of commercial Pt/C catalyst, probably shedding light on the additional contribution of the unique pore structure (large window diameter and spherical chamber) duplicated from the MCF to further enhancement of ORR activity. The PANI-Fe-HT2(MCF)-based zinc-air battery delivered impressing power density (116.26 mW cm-2) and specific capacity (788 mAh gZn-1) as well, completely rivaling the Pt/C-based ZAB. The universal method will hold great promise for exploiting efficient Fe-N-C materials for ORR towards their practical applications to device.
Nano-Fertilizers for Improving Yield in Maize Plants under Calcareous Soil Conditions to Achieve Sustainability
Authors: Sary Dalal H. , El-Aziz Mahmoud E. Abd 
Published: January 2025

Abstract

Agriculture in calcareous soil suffers from many problems such as high calcium carbonate content, low organic matter, and poor availability of elements. In the summer of two seasons 2022 and 2023, the maize crop (Zea mays, L) was planted in the El-Nubaria Agricultural Research Station farm, Egypt, to study the effect of nano-micronutrient fertilizers. The field experiment was done through a randomized completely block design with treatments: Control, Nano-Zn 20 mg/l, Nano-Zn 40 mg/l, Zn-chelate 2 g/l, Nano-Mn 20 mg/l, Nano-Mn 40 mg/l, Mn-chelate 2 g/l, Nano-Mo 20 mg/l, Nano-Mo 40 mg/l and ammonium molybdate 250 mg/l. X-ray diffraction (XRD) and transmission electron microscopy (TEM) were used to analyze the synthesized nano-micronutrient fertilizers. The data showed that 40 mg/l of nano-micronutrient fertilizer was the most effective treatment for most studied traits. Nano-fertilizer (NFs) also demonstrated better preference than traditional fertilizer for each of the growth characteristics, corn productivity, the content of elements in the plant, and their availability in the soil. The application of NFs containing molybdenum to corn grains resulted in a higher positive protein and nitrogen content. The content of zinc, manganese, and molybdenum in corn leaves and grains and their availability in calcareous soil was more stimulated with the treatments of nano-micronutrient and traditional fertilizers containing the same element with all concentrations of doses.
Photoselective isotope fractionation dynamics in cosmo and atmospheric chemistry
Authors: Levine Raphael 
Published: January 2025

Abstract

Photochemical isotope effects have been measured for nearly 50 years with the driving force being the understanding of natural processes. This has ranged from climate and atmospheric chemistry and dynamics, planetary atmospheres such as Mars, Titan and Jupiter, consequences for resolving solar system formation mechanisms, interstellar molecular clouds, solar wind and meteorites. 1,2 The distribution of isotopomers of compounds varies significantly across the solar system and beyond, invalidating the notion of a constant molecular weight.3 Nitrogen, with two stable isotopes, exhibits wide-ranging isotope ratios that arise from different sources across the solar system.4-11 We seek to understand variability by explicitly examining the dynamics of photodissociation. The paper integrates measurements of photodissociation of N2 at the advanced-light-source via scavenging of the nascent N atoms and state of the art dynamics modeling, including preferential light shielding.12-14 We show that the exceptionally high nitrogen isotopic fractionation underscores the essential role of dynamics in interpreting photoselectivity and its dominant non-statistical aspects that we establish. High level quantum chemical computations of the relevant potentials and of their different selective couplings that vary in magnitude are vital input towards our demonstrating photoselective chemistry. Beyond N2, our approach is equally applicable for elucidating the isotope ratio reported for CO.15,16 The findings support planetary exploration models, including NASA's Artemis missions, where nitrogen isotopic studies of the lunar and Martian surfaces are crucial for understanding water sources and volatile chemistry.
Spatial variability of ENSO-based monsoon rainfall in the coastal region of southeastern India
Authors: Kasera Reema , Minocha Vijay K. 
Published: January 2025

ABSTRACT
Climate variability during El Niño and La Niña events is believed to sync with the monsoon fluctuation globally. Studying these phenomena is crucial for predicting meteorological factors like temperature and precipitation. This study investigates the spatial variability of southwest monsoon rainfall (SMR) due to El Niño and La Niña along the southeastern coast of India. Monthly average rainfall data for the coastal districts of Tamil Nadu, Andhra Pradesh, and Odisha from 1970 to 2020 were analyzed. The analysis revealed that the El Niño Southern Oscillation (ENSO) had a distinct impression on these districts. Results showed that during El Niño, Tamil Nadu and Andhra Pradesh received below-normal rainfall with an 82% probability, while above-normal rainfall occurred during La Niña, with probabilities of 65 and 70%, respectively. In Odisha, the probability of below-normal rainfall during El Niño was 41%, and above-normal rainfall during La Niña was 40%. However, the impact on Odisha was insignificant and did not align with conventional ENSO patterns. This study improves understanding of rainfall variability along the southeastern coast of India, highlighting the need for regional climate forecasting. These insights can aid policymakers in developing drought management and flood preparedness strategies, providing a valuable resource for enhancing climate prediction models.
Streamflow projections under climate change framework for the Mahanadi River catchment, India
Authors: Sahu Ramgopal T. , Turkane Sagar D. , Rathnayake Upaka 
Published: January 2025

ABSTRACT
Thirteen GCMs under Coupled Model Intercomparison Project-6 were analysed against IMD grid data using compromise programming (CP) to identify the optimal model. This innovative multi-criteria decision-making approach balances competing performance metrics to enhance model selection. The CP matrix indicated that the MPI-ESM1-2-HR model optimally simulates streamflow using the IMD-calibrated data. This study also examines basin hydrology and development impacts, emphasizing spatiotemporal climate variability. Spatial proximity-based regionalization identified Kurubhata, Bamnidih, and Basantpur as suitable gauged sites for streamflow projections at Kalma using Soil and Water Assessment Tool modelling. Under the SSP245 scenario, streamflow projections for 2019–2050 indicate increases of 44.67%, 27.88%, and 38.10% at Jondhra, Seorinarayan, and Basantpur, respectively. Water yield at Kalma is projected to rise by 96% from a baseline of 396.26 mm, and monsoonal precipitation at the basin outlet is expected to increase by 91.81 mm/year.
Understanding the Bariatric Surgery: Conceptions and Misconceptions in Future Health Care Professionals
Authors: Koodathingal Manasi , Haniya Khadeeja , Kumar Nivedya Anil , Parveen Aabidha , Goud Manjunath , Muthu Priyalatha , Kar Subhranshu Sekhar , Nair Manju Avinash 
Published: January 2025

Introduction:
Medically-complicated obesity, a major public health issue due to the ineffectiveness of traditional treatments, is increasingly managed through
bariatric surgery. This study investigates the knowledge of clinical year students about bariatric surgery at RAKMHSU. It aims to assess their
awareness and understanding of this crucial intervention for severe obesity and its related health risks.

Materials and Methods:
This cross-sectional study was conducted over three months at RAK Medical and Health Sciences University (RAKMHSU) and utilized a survey
to assess perception regarding bariatric surgery among clinical year students from RAK College of Medical Sciences (RAKCOMS) and RAK
College of Nursing (RAKCONS). A pre-validated questionnaire was employed, and participants were randomly selected. Data analysis focused on
the reliability of the tool and the student’s perception.

Results:
The study included 197 participants, comprising 162 medical and 35 nursing students. Significant differences emerged in three areas: nursing
students preferred daily exercise more (Q6), believed in the greater likelihood of weight regain post-surgery (Q9), and were more aware of disease
susceptibility (Q13) compared to medical students. Correlation analysis revealed that students who felt body shape affected self-confidence had
better bariatric surgery knowledge and BMI calculation experience. Notable correlations were found between specific questions, with significant
positive correlations observed among nursing students but not medical students.

Discussion:
Obesity is a global epidemic with rising prevalence, including in the UAE, where 43% of expatriates are overweight and 32.3% obese.
Environmental factors, such as low physical activity due to climate and cultural norms, exacerbate the issue. Our study revealed good knowledge
of BMI among participants, reflecting awareness of obesity's risks. However, concerns about bariatric surgery safety persist, with 32% of
participants wary of complications. Despite this, the most recognized bariatric surgery is a viable option for medical conditions like PCOS.
Educational interventions are essential to address misconceptions, promote informed decisions, and bridge gaps in exercise habits and referral
practices.

Conclusion:
In conclusion, while many medical and nursing students demonstrate a solid understanding of bariatric surgery, hesitations and misconceptions
persist. Continuous education is essential to address these concerns, enhance knowledge, and align perceptions with clinical advancements. By
doing so, future healthcare professionals can make informed decisions and provide better care for patients with severe obesity, ultimately
improving outcomes and fostering greater acceptance of evidence-based surgical interventions.
The Clinical Diagnostic Value of the Super-enhancer-associated Long Noncoding RNA RP11-803D5.4 and AC005592.2 in Colorectal Cancer
Authors: Yang Fengming , Liang Guangshu , Shi Huina , Yan Linping 
Published: January 2025

Background:
Super-enhancer-associated long noncoding RNAs (SE-lncRNAs)
play crucial roles in CRC pathogenesis.

Objective:
RP11-803D5.4 and AC005592.2 were identified as SE-lncRNAs of interest
via microarray analysis, and our study aimed to evaluate their clinical value in CRC diagnosis
and prognosis assessment.

Methods:
Fluorescence quantitative real-time PCR (qRT-PCR) was used to measure the
expression of RP11-803D5.4 and AC005592.2 in the tissues and serum of CRC patients.
Receiver operating characteristic (ROC) curves were generated to determine the predictive
value of the two SE-lncRNAs. Functional assays were applied to assess the ability
of RP11-803D5.4 to promote the proliferation, migration, and invasion of CRC cells.

Results:
The two SE-lncRNAs were significantly upregulated in CRC tissue and serum
samples vs. corresponding controls. ROC curve analysis indicated that RP11-803D5.4
(AUC=0.842) and AC005592.2 (AUC=0.811) had a high diagnostic performance for
CRC. The combination of RP11-803D5.4, AC005592.2, and CEA had an AUC of 0.946
and distinguished CRC patients and healthy controls better than SE-lncRNA alone. The
serum levels of RP11-803D5.4 and AC005592.2 were strongly correlated with their tissue
expression levels. The expression levels of the two SE-lncRNAs were significantly
lower in postoperative samples than in preoperative samples. Furthermore, similar to the
findings of previous studies on AC005592.2, high RP11-803D5.4 expression promoted
the proliferation, invasion, and migration of CRC cells.

Conclusion:
The findings suggested that RP11-803D5.4 and AC005592.2 are upregulated
in CRCact and are crucial promoters of CRC progression. They also suggested that
they might serve as noninvasive biomarkers for diagnosing CRC.