bluuebunny/crossref_metadata_2025_split huggingface dataset:
Shapley Value-based Data Valuation for Machine Learning Data Markets
Authors: Baghcheband Hajar , Soares Carlos , Reis Luis Paulo 
Published: September 2024

Abstract

Data valuation is the act of assigning a monetary value to data based on its estimated usefulness, potential impact, and scarcity. In the current landscape of digital technology, data has emerged as a valuable resource for various entities such as organizations, governments, and individuals. Consequently, data valuation plays an increasingly important role in managing data assets, ultimately facilitating informed decision-making in relation to data acquisition, sharing, analysis, and even monetization. In the context of the Machine Learning Data Market, a platform to exchange data considering its value, data valuation has an important role in putting economic value before trading data. The Shapley Value has assumed a central role in data valuation, due to its equitable value distribution among contributors. This paper focuses on data valuation within the context of the Machine Learning Data Market (MLDM). Our primary objective is to investigate whether data valuation methods based on the Shapley Value can result in improved performance in MLDM. We introduced the Gain Data Shapley Value (GDSV) method. This paper presents an extensive empirical study of its behavior and compares GDSV with performance-based data valuation in MLDM under different configurations and learning algorithms. Our findings confirm that considering the contribution of the data set to performance scores can lead to systematic improvements in learning performance.
Effect of a 16-week Combined Supervised Exercise Program after bariatric surgery on Sarcopenia parameters based on FNIH, EWGSOP2, EASO/ESPEN criteria – The results of the EXPOBAR randomized trial program
Authors: Mendes Cláudia , Carvalho Manuel , Cabo Carolina , Bravo Jorge , Martins Sandra , Raimundo Armando 
Published: September 2024

Abstract

Introduction:
Bariatric surgery is a recognized treatment option for severe obesity, and its effectiveness in reducing weight and controlling obesity-related conditions has been demonstrated. However, it can also lead to decreased skeletal muscle mass and strength, increasing the risk of sarcopenia after surgery. This randomized clinical trial studied the effects of a 16-week supervised combined exercise program on sarcopenia in bariatric surgery patients.
Methods
Thirty-seven surgery candidates participated in the EXPOBAR (EXercise POst BARiatric) program and were randomized into experimental or control groups. The intervention lasted 16 weeks, starting one month after surgery, and included a supervised combined aerobic and resistance exercise intervention. The outcomes, including body composition and physical fitness parameters, were assessed at four time points. All participants underwent gastric bypass surgery (RYGB).
Results
The EXPOBAR trial revealed significant and meaningful effects of the exercise intervention on anthropometric indices, such as weight (p = 0.039) and waist circumference (p = 0.010). The EXPOBAR trial also showed that after bariatric surgery, there was a clear decrease in muscle mass, and this loss continued through the duration of follow-up, despite the exercise protocol. The most substantial improvements were observed in physical function and strength metrics (p = 0.005 and p < 0.001, respectively), along with a reduction in fat mass (p = 0.006), indicating the intervention’s effectiveness in enhancing both physical fitness and body composition.
Discussion
Current findings indicate that following an initial decrease due to bariatric surgery, a combined exercise intervention significantly improves functional physical capacity and strength. The exercise program in this study effectively reversed the surgery-induced loss in function and strength, reducing the number of patients at risk of sarcopenia. Physical and functional capacity are crucial noninvasive indicators for diagnosing muscle quality and sarcopenia.
Conclusion
Long-term management of sarcopenia and sarcopenic obesity in bariatric surgery patients requires frequent monitoring of body composition and muscle function. This approach is essential for tracking progress and optimizing treatment strategies over time. This study highlights the importance of integrating structured exercise programs into after bariatric surgery care to mitigate the risk of sarcopenia. Future options include nutritional protein supplementation and changes in the exercise protocol.
Trial registration
: The trial was registered at Clinicaltrials.gov (NCT03497546).
Environmental role of modified zeolite minerals in mercury removal in water and wastewater : Recoverability with maximum removal of mercury ions
Authors: jahani farahnaz 
Published: September 2024

Abstract

The natural clinoptilolite zeolite was treated with NaOH and heat. The modified zeolite was then investigated by Field-emission Scanning Electron Microscope (FESEM), energy dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), and BET techniques. The modified zeolite managed to remove mercury ions up to 95%; while raw zeolite showed the maximum Hg removal ability of 35%. Also, the modified zeolite was reused seven times with stable adsorption of mercury ions. Based on the kinetic studies, the adsorption of mercury ion by modified zeolite follows the pseudo-second order model. Moreover, the experimental data were better fitted with Langmuir isothermal model than Freundlich. The removal of toxic mercury ions could serve as a useful solution for today's environmental issues.
Direct collaboration between hospitals and NGOs, an essential tool to reinforce linkage to care in People living with HIV
Authors: Aldámiz-Echevarria Teresa , Fanciulli Chiara , Lopez Monica , Perez Leire , Tejerina Francisco , Sanchez David , Lodeiros Blanca , Lopez Juan Carlos , Berenguer Juan , Bellon Jose Maria , Ferris Maria , Blazquez Mario , Calvo Almudena , Domene Mario , Vegas Oswaldo , Rodriguez Carmen , Muñoz Patricia , Gijon Paloma , Montilla Pedro , Bermudez Elena , Valerio Maricela , Alonso Roberto , Padilla Belen , Ventimilla Cristina , Diez Cristina 
Published: September 2024

Abstract

With the aim of improving access and engagement to healthcare in people living with HIV (PLHIV), in 2022 Gregorio Marañón Hospital and the NGO COGAM developed a circuit for recruitment and referral to hospital. Program targeted PLHIV who were neither receiving antiretroviral treatment (ART) nor on medical follow-up (FU); but also, individuals at risk who underwent screening tests at the NGO and, if positive, were referred for confirmation. The result was an increase in annual new PLHIV seen in hospital by reaching a population who were, essentially, young men (94% male, median age 30 years), migrants (95%) with recent diagnosis of HIV (median 5 years) and who were recently arrived in Spain (median 5 months). Most of them hadn´t healthcare coverage (78%). In multivariate analysis, that included all PLHIV seen for the first time in the ID Unit between 2019 and 2022, lack of healthcare coverage was the only independent predictor of lost to FU that reached statistical significance (HR 5.19, CI 2.76–9.47). Furthermore, time from HIV diagnosis to ART initiating was shortened from 14 to 6 days without affecting linkage to care. Our conclusion is that collaboration with NGOs reinforce diagnosis, FU, and adherence to ART for PLHIV.
Enhancing Reproductive Health Among Adolescent Girls in India: Results of An Individualized RCT to study the efficacy of the Go Nisha Go Mobile Game
Authors: Raj Aparna , Shankar Lalita , Dixit Anvita , Saha Ananya , Battala Madhusudana , Khan Nizamuddin , Ayyagari Kavita , Saggurti Niranjan , Howard Susan 
Published: September 2024

Abstract

Background
Adolescent girls in India face significant barriers to accessing sexual and reproductive health (SRH) information and services. Digital interventions, particularly mobile-based ones, promise to deliver SRH education in a fun and engaging manner. These can be offered privately directly to the adolescent, allowing players to ‘experience’ the outcomes of their choices, receive tailored feedback, and the option to ‘try again’.
Methods
This study evaluated the efficacy of "Go Nisha Go®" (GNG), a low-end smartphone-based digital game for adolescent girls in India, using a two-armed, encouragement-led, randomized controlled trial (RCT). The study involved 1,950 participants from Patna, Jaipur, and Delhi NCR. The intervention group received encouragement to play GNG, while the control group did not. Key constructs measured included menstrual health management (MHM), contraception knowledge, and agency. Data were collected at baseline and a ten-week follow-up.
Results
The intervention group showed significant improvements in various MHM parameters, contraception knowledge, and agency outcomes compared to the control group. Overall, 1,697 out of 1,993 participants completed the study after ten weeks (85%). The intervention group's awareness of menstrual hygiene products increased from 33–92%, while comprehensive knowledge of oral contraceptive pills (OCPs) rose from 2–17%. Confidence in negotiating contraception use increased from 60–85%, and the attitude of refusing sex when not ready improved from 61–85%.The subjects in the game group showed high levels of satisfaction with the app, with 74% discussing the game with others and 66% recommending it. The belief in negotiating marriage decisions with parents also improved more in the intervention group than in the control group.
Conclusion
The findings of the first-ever RCT outcome evaluation for a digital mobile game app for enhancing SRH education among adolescent girls in low-resource settings support the efficacy of digital games for health like GNG. The game's engaging and interactive format effectively communicated complex and sensitive SRH information, empowered participants, and encouraged critical health behaviors through informed decision-making. Future studies could explore the long-term sustainability of behavior changes induced by such interventions and their effectiveness across different settings and populations.
Trial Registration: CTRI/2023/03/050447
Registration date: March, 2023
Quality priorities related to the management of type 2 diabetes in primary care: Results from the COMPAS+ quality improvement collaborative
Authors: Gaid Dina , Giasson Guylaine , Gaboury Isabelle , Houle Lise , Layani Géraldine , Menear Matthew , Tilly Véronique Noël , Pomey Marie-Pascale , Vachon Brigitte 
Published: September 2024

Abstract

Structured Abstract
Background: This study aims to describe the main type 2 diabetes mellitus (T2DM) quality improvement (QI) challenges identified by primary care teams in the province of Quebec who participated in the COMPAS+ QI collaborative.
Methods: A qualitative descriptive design was used to analyse the results of 8 COMPAS+ workshops conducted in 4 regions of the province between 2016 to 2020. Deductive content analysis was performed to classify the reported QI priorities under the Consolidated Framework for Implementation Research domains; and proposed change strategies under the Behavior Change Wheel (BCW) intervention functions.
Results: A total of 177 participants attended the T2DM COMPAS+ workshops. Three QI priorities were identified: 1) lack of coordination and integration of T2DM care and services; 2) lack of preventive services for pre-diabetes and T2DM; and 3) lack of integration of the patient-as-partner approach to support T2DM self-management. The proposed QI strategies to address those priorities were classified under the education, training, persuasion, habilitation and restructuring BCW intervention functions.
Conclusion: This study provides insights on how QI collaboratives can support the identification of QI priorities and strategies to improve T2DM management in primary care.
Exploration of the use of machine learning and natural language processing techniques to identify patients who are medically cleared for psychiatric placement among hospitalized patients
Authors: Verma Ritchie , Lipten Samuel D. , Jernigan Michael 
Published: September 2024

Abstract

Purpose
Psychiatric patients who are hospitalized generally require medical clearance before they can be transferred to a psychiatric facility to receive care. Their hospitalization typically ends up being prolonged beyond medical clearance, resulting in significant costs and length of stay burdens on the hospital and delays in receiving psychiatric care. In this study, we explored how different open-source natural language processing (NLP), and machine learning (ML) techniques might assist in identifying patients who are medically cleared to be discharged to inpatient psychiatry wards among hospitalized patients.
Methods
We retrospectively examined patients hospitalized on the medical floors of a 1,063-bed academic medical center during 2020. The Internal Medicine provider notes were classified into “Cleared” vs “Not Cleared” to train a supervised machine learning model. Logistic regression (LR) and support vector machine (SVM) models, among other classifiers, were used. The accuracy results were compared with those of the rule-based approach.
Results
LR and SVM achieved very high accuracy scores on unseen data, with accuracies of 93.6% (95% CI 89–98%) and 91.2% (95% CI 86–96%), respectively. Comparatively, the rule-based approach using regular expression yielded 86.8% (95% CI of 81–93%) accuracy. AUC/ROC score for machine learning approach was 0.96.
Conclusion
Open-source NLP and ML techniques are quite sophisticated in providing high accuracy in text-based classification tasks. These approaches can be replicated to automate the chart review process for both research and clinical decision support, saving countless hours of manpower.
Changes of vertical dimension and alveolar bone remodeling in patients with second molar scissors bite during orthodontic correction
Authors: Guo Feng , Wang Chenxu , Hu Hengyu , Lei Lang 
Published: September 2024

Abstract

The aims of this retrospective study were to assess changes of vertical dimension and alveolar bone remodeling in cases with second molar scissors bite (SB) before and after intermaxillary cross-elastics (ICE) treatment. 36 patients with unilateral SB (SB group) and 36 subjects with normal occlusion (Control group) were included. CBCT records were taken before (SB-T0) and after orthodontic treatment (SB-T1). Alveolar bone height (ABH) and thickness (ABT), tooth and alveolar bone inclination, molar and facial height were measured. No changes on the vertical dimension were observed during treatment. Surrounding alveolar bone displayed synchronous changes in the inclination with molars for both arches. After ICE, the maxillary alveolar bone was found thinner at buccal side (P < 0.05), while no difference was found at the palatal side. The mandibular alveolar bone was found thicker at buccal side and thinner at lingual side (P < 0.05). Nevertheless, no difference in the alveolar bone thickness was observed between SB-T1 group and Control group. ICE is a safe method to correct SB with stability of vertical dimension and safety of periodontal bone. Buccolingual inclination of the alveolar bone changes with the molar tooth movement, showing a bone bending tendency during SB correction.
Concurrent Estimation of Pregabalin and Etoricoxib by New Stability Indicating Rp-uplc Approach- Application in Assay of Commercial Tablets
Authors: Ponnekanti Krishnaphanisri , Godela Ramreddy 
Published: September 2024

Abstract

The present research aims to establish new stability indicating RP-UPLC method for concurrently estimating Pregabalin and Etoricoxib in blended powder and their combined tablet formulation. The effective separation of Pregabalin and Etoricoxib achieved with HSS column C18 (150x2.1mm,1.8µm), 0.1% orthophosphoric acid: acetonitrile in 65:35 v/v) at a flow rate of 0.3mL/min, and isocratic elution at 228nm. The elution of PRB and ETB was noticed at 1.56 and 2.01 minutes, with good resolution and system suitability with the developed approach. PRB and ETB have shown linear responses from 18.75 to 112.5µg/mL and 15 to 90µg/mL, respectively. The range of the % RSD for intraday and inter-day precision was 0.33 to 0.81. The LOD and LOQ of Pregabalin and Etoricoxib were computed to be 0.07 µg/mL, 0.21 µg/mL, and 0.01µg/mL, 0.04 µg/mL, respectively, by standard deviation method. The validation method was carried out using ICH standards. The stability- indicating the feature of the method was confirmed by the forced degradation studies where degradants generated by stress testing were clearly distinguished from the peaks of analytes. The shorter elution period and superior sensitivity of both analytes with this method are appropriate for regular analysis of Pregabalin and Etoricoxib.
A novel electromagnetic forming actuator for curved sheet forming: analytical optimization, simulation, and experimental validation
Authors: Hu Yang , Lai Zhipeng , Li Changxing , Gong Mengyuan , Xu Wei , Zhang Zixuan , Jiang Yuze , Cao Quanliang , Han Xiaotao , Li Liang 
Published: September 2024

Abstract

A newly-designed electromagnetic forming actuator has been proposed to enable curved-geometry sheet metal forming, cannot be efficiently realized by conventional electromagnetic forming. In the pursuit of fast designing the actuator, an analytical model was derived to obtain the relationship between the produced magnetic pressure and the system geometric parameters of the actuator. Based on this analytical formulation, we explored the regulatory behavior and impact mechanism of various parameters of the actuator on the magnetic field, magnetic pressure, and efficiency of the forming system, which has been validated by the results from finite element simulations. A design criterion is proposed for optimization of the actuator. And accordingly, a series of experiments have been performed to validated the feasibility of the proposed actuator for electromagnetic calibration.
The impact of performing arts on mental health, social connection, and creativity in university students: A Randomized Controlled Trial
Authors: Agres Kathleen Rose , Chen Yifan 
Published: September 2024

Abstract

Background: University students often face mental health challenges, exacerbated by stigmas that hinder seeking support and treatment. We introduce a participatory arts programme, Movin' and Groovin' for Wellness (MGW), that features facilitated drumming and dancing sessions. This study aimed to investigate the impact of the MGW programme on students' mental health, social connections, and creativity.
Methods: A 10-week pilot parallel Randomised Controlled Trial (RCT) was conducted with 76 participants randomly assigned into an Experimental (MGW) group (N=38) or a Control group (N=38). Data were collected at baseline, midway, and post-intervention. Mental health was evaluated using the Depression, Anxiety, and Stress Scale-21 (DASS-21), and quality of life via the WHO Quality of Life-BREF (WHOQOL-BREF) scale. The Brief Resilient Coping Scale, Lubben Social Networking scale, Experience of Creation scale, Brief Resilient Coping scale, and Brief Music in Mood Regulation scale (B-MMR) were also administered. Qualitative feedback was gathered through a bespoke survey and focus group discussion (FGD), focusing on participants' subjective experiences of the programme, mood/emotion states, social connections, and creative expression.
Results: The MGW programme led to significant improvements in mental health, quality of life, and creativity, while the Control group experienced significant declines in mental health and quality of life during the term. The Experimental group showed significant reductions in Stress scores (DASS-21) at Week 10, whereas the Control group had significantly worse anxiety, depression, and stress at Week 5, with stress scores remaining elevated at Week 10. Improvements in the Experimental group were also observed in the Psychological (at Week 5) and Physical (at Week 10) domains of the WHOQOL-BREF. In comparison, the Control group showed a significant decrease in WHOQOL-BREF Physical scores at Week 10. The Experimental group also showed enhanced creativity (Experience of Creation scale) at Week 5 and Week 10, although no significant changes were observed in the social networking or resilient coping scales. Qualitative findings highlighted the programme's positive impacts on participants' mental health, social connections, and creativity.
Conclusions: The MGW programme effectively improved mental health, quality of life, social connection and creative expression among university students. These findings suggest that arts-based interventions such as MGW can support student health and well-being in a stigma-free and culturally appropriate manner.
Trial registration: The trial was retrospectively registered at ClinicalTrials.gov under ID: NCT06542003.
Reliability, Availability and Maintainability Analysis of Machining Line at Engine Manufacturing Plant
Authors: Mahajan Tushar , Gargama Heeralal , Sonawane Lokesh 
Published: September 2024

Abstract

In today's competitive manufacturing landscape, operational excellence is vital. Continuous production depends on optimal machine performance to meet high demand. Unplanned downtime threatens revenue. This paper presents a case study of Reliability, Availability, and Maintainability (RAM) analysis of a machining line with 14 machines at an engine manufacturing plant. The analysis aims to address frequent machine failures and improve reliability and availability, enhancing overall plant efficiency. To perform the RAM analysis, comprehensive failure and maintenance time data for all machines were collected over the past year. After data collection, thorough cleaning and analysis techniques were applied to evaluate various statistical parameters of the reliability and maintainability models. Given the non-exponential failure and repair distributions, Semi-Markov Process (SMP) modelling was employed for availability assessment. The analysis computes RAM indices for all machines, offering insights into their current operating status. It includes a comparative study of machine failure frequencies and examines availability, maintainability, and reliability features for different machines in the production facility. It also presents reliability versus time plots for individual machines and the entire machining line. These results guide identifying critical machines, optimizing maintenance practices to minimize downtime, and provide insights for exploring Reliability-Centered Maintenance (RCM) strategies.
Modeling Body Part Interactions for Skeleton-Text Contrastive Learning in Action Recognition
Authors: Liang Shuang , Qian Ruihao , Zhuang Zikun , Xie Chi 
Published: September 2024

Abstract

Skeleton-based action recognition has garnered significant attention due to its efficiency and robustness. Recent advances in skeleton-text contrastive learning show promise but overlook interactions between skeleton parts. This paper proposes a part interaction module that models these interactions to align skeleton features with descriptive texts. Experiments demonstrate that incorporating this module leads to notable improvements, establishing a new state-of-the-art on popular benchmarks. Our work underscores the importance of part interactions for action recognition.Code is released at https://github.com/ReskyQian/Body-Part-Interactions.