bluuebunny/crossref_metadata_2025_split huggingface dataset:
Short-term passenger flow prediction for urban rail systems: A deep learning approach utilizing multi-source big data
Authors: Cui Hongmeng , Si Bingfeng , Chi Dazhuang , Li Yueqing , Li Ge , Chen Yuanmeng 
Published: July 2024

Abstract

Predicting short-term passenger flow in urban rail transit is crucial for intelligent and real-time management of urban rail systems. This study utilizes deep learning techniques and multi-source big data to develop an enhanced spatial-temporal long short-term memory (ST-LSTM) model for forecasting subway passenger flow. The model includes three key components: (1) a temporal correlation learning module that captures travel patterns across stations, aiding in the selection of effective training data; (2) a spatial correlation learning module that extracts spatial correlations between stations using geographic information and passenger flow variations, providing an interpretable method for quantifying these correlations; and (3) a fusion module that integrates historical spatial-temporal features with real-time data to accurately predict passenger flow. Additionally, we discuss the model's interpretability. The ST-LSTM model is evaluated with two large-scale real-world subway datasets from Nanjing and Beijing. Experimental results show that the ST-LSTM model effectively captures spatial-temporal correlations and significantly outperforms other benchmark methods.
Artemisia annua L. extract regulates bone-fat metabolism on glucocorticoid-induced osteoporosis via regulating PGC-1α/Nrf2-mediated oxidative stress
Authors: Lai Liyong , Xia Tianshuang , Ding Luying , Li Kun , Xu Shengyan , Jiang Yiping , Fan Weiqing , Yue Xiaoqiang , Xin Hailiang 
Published: July 2024

Abstract

Artemisia annua L. is a well-known traditional herb medicine, and possesses antioxidant, antiobesity and antiosteoporosis properties. This paper aimed to explore the role and mechanism of Artemisia annua L. on glucocorticoid-induced osteoporosis (GIOP). Artemisia annua L. extract (AE) improved bone mineral density (BMD) and micro-architectural parameters in GIOP mice femur. Biological indicators showed that AE protected bone formation and inhibited fat formation in GIOP mice, and the potential mechanism was regulating oxidative stress (OS) via promoting the nuclear expression of Nrf2. To further investigate the mechanism of AE on GIOP, MC3T3-E1 cells injured by dexamethasone (DEX) were used for in vitro study. AE promoted proliferation and mineralization, upregulated the expression of Runx2, and downregulated the expression of PPARγ in DEX-injured MC3T3-E1 cells. In addition, AE reduced the level of oxidative factors and promoted the level of antioxidant enzymes in DEX-injured MC3T3-E1 cells. Western blot showed that AE activated the PGC-1α/Nrf2 pathway, which may be the potential mechanism of AE playing antioxidant role. Furthermore, PGC-1α or Nrf2 knockdown by siRNA reversed the antioxidant effect of AE. These results revealed that AE exerts anti-GIOP effects via egulating bone-fat metabolism via regulating PGC-1α/Nrf2-mediated OS.
Examining the Relevance of Gastrointestinal Symptom-Specific Anxiety in Self-Reported IBS and Gluten-Related Conditions: Findings from Two Cross-Sectional Studies
Authors: Bertalan Eszter , Horváth Zsolt , Gajdos Panna , Magyaródi Tímea , Rigó Adrien 
Published: July 2024

Abstract

Background
The present study examines the role of gastrointestinal symptom-specific anxiety in gluten-related conditions (e.g. celiac disease, non-coeliac gluten sensitivity) and in irritable bowel syndrome (IBS). The Visceral Sensitivity Index is widely used instrument for assessing gastrointestinal symptom-specific anxiety, originally used among IBS individuals, but it proved applicable to other health conditions characterized with gastrointestinal symptom presence (e.g., inflammatory bowel disease, eating disorders). The coexistence and symptom overlap between IBS and gluten-related conditions may provide a rationale for investigating gastrointestinal symptom-specific anxiety in the latter population.
Methods
Two cross-sectional studies were conducted; consisting of 304 self-reported IBS individuals (Mage=34.48; SDage=12.18) and 341 individuals with self-reported gluten-related disorders (Mage=36.65; SDage=11.02). Self-reported questionnaire assessed the level of gastrointestinal symptom-specific anxiety, trait anxiety, negative affectivity, perceived gastrointestinal symptoms in IBS and gluten-related conditions, quality of life and well-being.
Results
The confirmatory factor analyses supported a unidimensional structure of the Hungarian version of the Visceral Sensitivity Index with adequate fit and high internal consistency in both samples. Invariance testing revealed variations in item interpretation, suggesting caution in statistical comparisons of Visceral Sensitivity Index scores. Gastrointestinal symptom-specific anxiety demonstrated medium-strong correlations and mediating role between trait anxiety, negative affectivity, perceived gastrointestinal symptom frequency, and quality of life indicators in both samples.
Conclusions
Gastrointestinal symptom-specific anxiety may be relevant not only for IBS, but also for gluten-related conditions, may reflecting mental aspects of quality of life. The Visceral Sensitivity Index proves reliable for measuring gastrointestinal symptom-specific anxiety in IBS and gluten-related disorders, suggesting its assessment in conditions where gastrointestinal symptoms prevail.
A Neural Network-Based Pipeline Parallel Strategy Solver for Heterogeneous Environments
Authors: Ou Jie , Chen Yueming , Tian Wenhong , Zhang Hongjie 
Published: July 2024

Abstract

The escalating interest in language models has accentuated the significance of distributed training approaches, specifically pipeline parallelism. Most investigations primarily employ dynamic programming, these methods face inherent limitations in computational efficiency and do not offer a straightforward end-to-end resolution pathway. Furthermore, their applicability is significantly curtailed in heterogeneous environments. Addressing this challenge, we introduce a novel Neural Network-based Pipeline Parallel strategy solver (NNPiper) tailored for heterogeneous environments. NNPiper can perceive computational and communication costs, the number of stages to be divided, and the number of micro-batches, and it can directly provide the strategy for allocating specific devices to each pipeline stage, without requiring online training based on actual cluster data. Our unique neural network model and training method, the Virtual Contrastive Training Algorithm (VCTA), enables efficient training of NNPiper without collecting large amounts of real data. Compared with the state-of-the-art method, NNPiper can improve the theoretical training speed on average by 17.975%, in the completely heterogeneous environment for the Generative Pre-trained Transformer (GPT) models.
Cervical Cancer Screening Data from the Case-based National Electronic Registry in Bangladesh
Authors: Nessa Ashrafun , Azad Abul Kalam , U Shekh Md. Nizam , Khan Muhammad Abdul Hannan , Zaman Shreshtha , Khan Abdus Salam 
Published: July 2024

Abstract

Introduction: The purpose of this study is to review the cervical cancer surveillance situation of Bangladeshi women based on the data of the national cervical cancer screening, treatment, and follow-up programme which uses longitudinal data tracking through a DHIS2-based electronic registry. Methods: Women aged 30 to 60 were enrolled in the DHIS2 electronic registry in health facilities of all tiers and screened for cervical cancer using the VIA method. The VIA-positive women had their colposcopy in the nearest colposcopy centres. The VIA- and colposcopy-positive women were treated and followed up at certain intervals following the national standard protocol. During each encounter, required data were captured in DHIS2. Data from the DHIS2 covering January 2018 to May 2023 were extracted and analysed for this study. Results: In 6,895 health facilities, 1,562,963 women were enrolled. Among them, 1,557,002 (99.6%) availed VIA tests at 1,094 centres. Primary healthcare facilities performed 74.4% enrolments and 72% VIA tests. 51,913 (3.3%) women were VIA-positive, of which only 20,954 (40.4%) attended for colposcopy. Among the colposcopy-positive women, 6.3% (1,327) and 6.2% (1,302) women had CIN II/III and cervical carcinoma respectively; 81.6% (5,062) of the cervical pre-cancerous women received thermal ablation and 17.6% (1089) received Loop Electrosurgical Excision Procedure (LEEP). Distribution of histopathology reports (n = 3,079) revealed 16.1% (n = 495) squamous cell carcinoma, 4.0% (n = 123) micro-invasive squamous cell carcinoma, 11.7% (n = 36) CIN II and 8.1% (n = 250) CIN III. Conclusions: The sustainable national cervical cancer screening and treatment programme for women in Bangladesh using an effective DHIS2-based electronic case-based tracking system can be a valuable lesson for other countries.
Positive anti-TG antibody is associated with increased breast cancer risk in Turkish peri-postmenopausal women: A retrospective study
Authors: Donmez Bengisu , Serdar Muhittin A. , Uras Cihan , Arıkan Akif Enes , Tokat Fatma , Avdan Selin Naz , Ozpınar Aysel 
Published: July 2024

Abstract

Background:
Breast cancer is one of the most common types of cancer in women worldwide. Thyroid hormones play an important role in regulating metabolism and cell growth, including in breast tissue. Although a potential link between thyroid health and breast cancer risk has been suggested in the literature, highly conflicting results have been obtained, and the relationship between them remains unclear. This study aimed to examine the possible association between breast cancer and thyroid health in Turkish women with breast cancer.
Methods:
For this retrospective study, data from 66587 women aged between 18 and 80 years who had any complaints of thyroid function tests were collected, and the thyroid stimulating hormone (TSH), free thyroxine (fT4), anti-thyroid peroxidase (anti-TPO), and anti-thyroglobulin (anti-TG) levels of 3115 women with breast cancer and peri-postmenopausal women with breast cancer who met the inclusion criteria were analysed. The relationship between thyroid function and breast cancer risk was examined using logistic regression analysis. In addition, this association in peri-postmenopausal women was further investigated with receiver processing characteristic (ROC) curve analysis.
Results:
A total of 3115 Turkish women, including a subgroup of peri-postmenopausal women aged 40 years and older, participated in the study. The fT4, TSH, anti-TPO, and anti-TG levels were assessed in both the overall group and the peri-postmenopausal subgroup. The median anti-TG level was significantly greater in women with breast cancer and peri-postmenopausal breast cancer than in women with anti-TG-negative breast cancer (p < 0.05). No statistically significant differences were found in the median fT4, TSH, or anti-TPO levels between the groups (p > 0.05). A significant positive association was observed between anti-TG antibody levels and breast cancer in Turkish women (OR = 3.325, 95% CI = 1.625–6.803, p = 0.001), with a stronger association in peri-postmenopausal women (OR = 3.57, 95% CI = 1.691–7.540, p = 0.001)
Conclusions:
In conclusion, our study indicated that anti-TG positivity is associated with an increased risk of breast cancer. These findings highlight the importance of routine screening for thyroid antibody levels in women, particularly those in the peri-postmenopausal period. However, further prospectively designed studies are necessary to confirm these results.
Lianas detrimentally affect carbon storage potential and recovery times of tropical secondary forests
Authors: Heijden Geertje van der , Meunier Félicien , Verbeeck Hans , Schnitzer Stefan 
Published: July 2024

Abstract

Tropical secondary forests are important carbon sinks and their carbon sequestration capacity is often greater than that of old-growth forests1–4. Lianas (woody vines) are present in most tropical forests, but areparticularly prevalent in secondary forests5, where they exert strong competitive effects on trees, severely reducing carbon uptake6–8. However, no experimental study has yet examined whether lianas limit the rate of carbon recovery and carbon storage capacity of tropical forests. Here we use a unique combination of 10 years of empirical data from the world’s longest running liana removal study and modelling to simulate the long-term effects of lianas on forest succession. We show, for the first time, that lianas have strong and prolonged negative effects on carbon uptake throughout secondary forest succession. Lianas diminish the carbon storage potential of secondary forests by ~ 25% and delay the carbon recovery time to old-growth carbon standards by approximately a century. Liana proliferation, as observed in multiple forested regions across the globe9–11, may therefore endanger both carbon uptake and carbon storage in tropical forests, with cascading effects on climate change.
A Study on the Prevalence of E. coli in the Urinary Tract Infection and the Risk Factors Associated with It
Authors: GHOSH RAJRUPA , Sarwar Shiblee 
Published: July 2024

Abstract

Millions of people worldwide suffer from infections of the urinary tract (UTIs) brought on by the bacteria Escherichia coli (E. coli), which represents a substantial global health burden. It is essential to comprehend the epidemiology and risk factors that are linked to these illnesses in order to develop appropriate therapy and preventative techniques. The frequency, distribution patterns, and risk factors of UTIs linked to E. coli are examined in this study, with particular attention paid to age, gender, underlying medical problems, and opiate usage. The study intends to improve knowledge of UTI the pathogenesis of clinical symptoms, diagnostic techniques, treatment strategies, and preventive measures by analysis of clinical information, statistical models, and previous research. The results highlight how crucial it is to treat E. coli UTIs holistically, using alternative treatments, and with caution when using antibiotics. The study emphasises the necessity of ongoing efforts to reduce the incidence of UTIs caused by E. coli by means of focused interventions, policy formulation, and public health campaigns. In the end, this dissertation advances knowledge, directs future research paths, and enhances clinical results in the treatment of E. coli-caused UTIs.
Formation mechanism of injured bacteria after disinfection with epigallocatechin gallate (EGCG) as a disinfectant
Authors: Feng Cuimin , Chen Zexin , Guan Sairui , Li Jing , Qu Mengchao , Geng Haochen 
Published: July 2024

ABSTRACT
This study explored the effects of epigallocatechin gallate (EGCG), the main antibacterial component of tea polyphenols, on Escherichia coli in terms of disinfection damage and the underlying mechanisms. The researchers assessed inactivation and injury rates, cell morphology, and antioxidant indicators of E. coli when subjected to different concentrations of EGCG. The results showed that varying EGCG concentrations produced damaged bacteria, with the extent of damage depending on EGCG dosage and treatment duration. The disinfection process involving EGCG resulted in oxidative damage in E. coli, evoking alterations in the antioxidant system of the affected bacteria. During disinfection-induced bacterial injury, E. coli showed the active regulation of metabolism and redox activities in response to EGCG-induced environmental stimuli. Transcriptomic analysis was conducted to investigate the damage mechanism at the gene level. The damaged E. coli countered oxidative stress by adjusting gene expression related to peroxidase and glutathione metabolism processes. In this way, E. coli adjusts its gene expression to alleviate the detrimental effects of EGCG-induced oxidative stress and maintain cellular homeostasis. These findings contribute to our understanding of tea polyphenols' disinfection effects and provide insights into EGCG's mechanisms of damaging bacteria such as E. coli.
Feasibility and sensitivity assessment of various heads for micro-hydropower plant design in the Deluwang watershed, Indonesia
Authors: Widiarti Wiwik Yunarni , Hidayah Entin , Rohman Abdur , Wiyono Retno Utami Agung , Miqdad Muhammad , Halik Gusfan , Supriono Agus , Saifurridzal Saifurridzal , Fawaid Muhammad , Widyawati Indah Kusuma 
Published: July 2024

ABSTRACT
The escalating global demand for electrical energy, including in Indonesia, underscores the need for renewable energy sources like micro-hydropower plants (MHPs). This study examines the financial feasibility and sensitivity of MHP projects in the Deluwang watershed, Situbondo Regency, Indonesia. Three cases with varying head elevations and discharge rates were analyzed, utilizing crossflow turbines. Case 1, with the highest head and discharge, emerged as the most profitable, demonstrating the highest values for Net Present Value (NPV), Benefit–Cost Ratio (BCR), and Internal Rate of Return (IRR). The study found that on-grid systems, despite higher initial costs, offer more stable revenue and faster payback periods compared to off-grid systems. Sensitivity analysis revealed the on-grid method's resilience to fluctuations in interest rates, project lifespan, and river discharge, maintaining feasibility with up to an 80% reduction in discharge over 15 years. This highlights the importance of strategic planning in MHP design, considering head and discharge rates to optimize power generation. The findings provide valuable insights for renewable energy development, contributing to Indonesia's energy needs and local socio-economic benefits. Future research should further explore the socio-economic impacts of MHP installations to enhance their development and sustainability.
Does water rights trading promote the efficiency of water use? Empirical evidence from pilot water rights trading in China
Authors: Xu Tao , Wu Zheng , Tian Guiliang , Shi Ziteng 
Published: July 2024

ABSTRACT

Water rights trading policy is an important economic tool in China's water resource management. Accurately estimating the level of water resource utilization efficiency in experimental areas and impartially assessing the impact of the water rights trading market's operation on water resource utilization efficiency have policy implications for improving water resource governance tools and capabilities. Based on the panel data of 19 provinces (regions) in China from 2010 to 2019, this paper describes the development of a three-stage data envelopment analysis model to measure water use efficiency and the application of the difference-in-differences method based on propensity score matching (PSM-DID) to examine the effect of water rights trading policies on the model. The results indicate that (1) after the introduction of the water rights trading policy, the water use efficiency in the experimental areas improved substantially; (2) the PSM-DID method also confirms this finding, and water rights trading has a positive influence on water use efficiency. The research outcomes of this study can be used to objectively appraise the policy performance of the water rights trading policy and provide a theoretical foundation for its nationwide implementation.
An Ethical Perspective on the Democratization of Mental Health With Generative AI
Authors: Elyoseph Zohar , Gur Tamar , Haber Yuval , Simon Tomer , Angert Tal , Navon Yuval , Tal Amir , Asman Oren 
Published: July 2024

Abstract
Knowledge has become more open and accessible to a large audience with the “democratization of information” facilitated by technology. This paper provides a sociohistorical perspective for the theme issue “Responsible Design, Integration, and Use of Generative AI in Mental Health.” It evaluates ethical considerations in using generative artificial intelligence (GenAI) for the democratization of mental health knowledge and practice. It explores the historical context of democratizing information, transitioning from restricted access to widespread availability due to the internet, open-source movements, and most recently, GenAI technologies such as large language models. The paper highlights why GenAI technologies represent a new phase in the democratization movement, offering unparalleled access to highly advanced technology as well as information. In the realm of mental health, this requires delicate and nuanced ethical deliberation. Including GenAI in mental health may allow, among other things, improved accessibility to mental health care, personalized responses, and conceptual flexibility, and could facilitate a flattening of traditional hierarchies between health care providers and patients. At the same time, it also entails significant risks and challenges that must be carefully addressed. To navigate these complexities, the paper proposes a strategic questionnaire for assessing artificial intelligence–based mental health applications. This tool evaluates both the benefits and the risks, emphasizing the need for a balanced and ethical approach to GenAI integration in mental health. The paper calls for a cautious yet positive approach to GenAI in mental health, advocating for the active engagement of mental health professionals in guiding GenAI development. It emphasizes the importance of ensuring that GenAI advancements are not only technologically sound but also ethically grounded and patient-centered.
Enhancement of the Performance of Large Language Models in Diabetes Education through Retrieval-Augmented Generation: Comparative Study
Authors: Wang Dingqiao , Liang Jiangbo , Ye Jinguo , Li Jingni , Li Jingpeng , Zhang Qikai , Hu Qiuling , Pan Caineng , Wang Dongliang , Liu Zhong , Shi Wen , Shi Danli , Li Fei , Qu Bo , Zheng Yingfeng 
Published: July 2024

Background
Large language models (LLMs) demonstrated advanced performance in processing clinical information. However, commercially available LLMs lack specialized medical knowledge and remain susceptible to generating inaccurate information. Given the need for self-management in diabetes, patients commonly seek information online. We introduce the Retrieval-augmented Information System for Enhancement (RISE) framework and evaluate its performance in enhancing LLMs to provide accurate responses to diabetes-related inquiries.

Objective
This study aimed to evaluate the potential of the RISE framework, an information retrieval and augmentation tool, to improve the LLM’s performance to accurately and safely respond to diabetes-related inquiries.

Methods
The RISE, an innovative retrieval augmentation framework, comprises 4 steps: rewriting query, information retrieval, summarization, and execution. Using a set of 43 common diabetes-related questions, we evaluated 3 base LLMs (GPT-4, Anthropic Claude 2, Google Bard) and their RISE-enhanced versions respectively. Assessments were conducted by clinicians for accuracy and comprehensiveness and by patients for understandability.

Results
The integration of RISE significantly improved the accuracy and comprehensiveness of responses from all 3 base LLMs. On average, the percentage of accurate responses increased by 12% (15/129) with RISE. Specifically, the rates of accurate responses increased by 7% (3/43) for GPT-4, 19% (8/43) for Claude 2, and 9% (4/43) for Google Bard. The framework also enhanced response comprehensiveness, with mean scores improving by 0.44 (SD 0.10). Understandability was also enhanced by 0.19 (SD 0.13) on average. Data collection was conducted from September 30, 2023 to February 5, 2024.

Conclusions
The RISE significantly improves LLMs’ performance in responding to diabetes-related inquiries, enhancing accuracy, comprehensiveness, and understandability. These improvements have crucial implications for RISE’s future role in patient education and chronic illness self-management, which contributes to relieving medical resource pressures and raising public awareness of medical knowledge.