bluuebunny/crossref_metadata_2025_split huggingface dataset:
Study on surface roughness and fatigue property of abrasive waterjet peened aluminum alloy
Authors: Lv Zhe , Hou Rongguo , Xue Bing , Xu Jingpei , Sun Haocheng 
Published: July 2024

Abstract

Surface treatment is crucial for the component to function properly in many practical working situations. As an alternative of shot peening, abrasive waterjet peening is an advantageous method to improve various mechanical properties such as hardness, fatigue resistance, corrosion stability, etc. of the component surface. In order to investigate the surface roughness and its effect on fatigue performance in abrasive waterjet peening, simulation and experimental works on aluminum specimens were conducted in this study. Two different surface roughness indices and their dependencies on various processing parameters were analyzed. Fatigue performances of specimens under different processing conditions were also evaluated. The results indicated that shot velocity is the most influential factor on surface roughness under the involved conditions. Higher surface roughness induced by intense shot intensity will negatively affect the fatigue performance of the processed specimen.
Implications of Data Leakage in Machine Learning Preprocessing: A Multi-Domain Investigation
Authors: Bouke Mohamed Aly , Zaid Saleh Ali , Abdullah Azizol 
Published: July 2024

Abstract

Data leakage during machine learning (ML) preprocessing is a critical issue where unintended external information skews the training process, resulting in artificially high-performance metrics and undermining model reliability. This study addresses the insufficient exploration of data leakage across diverse ML domains, highlighting the necessity of comprehensive investigations to ensure robust and dependable ML models in real-world applications. Significant discrepancies in model performance due to data leakage were observed, with notable variations in F1 scores and ROC AUC values for the Breast Cancer dataset. The Tic-Tac-Toe Endgame dataset analysis revealed the varying impact on models like Ridge, SGD, GaussianNB, and MLP, underscoring the profound effect of data leakage. The German Credit Scoring dataset showed slight enhancements in recall and F1 scores for models like DT and GB without data leakage, indicating reduced overfitting. Additionally, models such as PassiveAggressive, Ridge, SGD, GaussianNB, and Nearest Centroid exhibited shifts in performance metrics, highlighting the intricate response to data leakage. The study also revealed raw data leakage rates, such as 6.79% for Spambase and 1.99% for Breast Cancer. These findings emphasize meticulous data management and validation to mitigate leakage effects, which is crucial for developing reliable ML models.
An evaluation of commercialised health interventions to promote physical activity in the workplace in Malaysia.
Authors: Singh Jasveen Kaur Grewachan , Nambiar Prof.Dr.Nisha 
Published: July 2024

Abstract

This evaluation aims to assess the impact of a commercialised health intervention designed to encourage physical activity within the workplace in Malaysia. The intervention was implemented in various organisations across different industries. A mixed-methods approach was utilized, combining quantitative surveys and qualitative interviews to collect data on the intervention's impact on employees' physical activity levels and their perceptions of the program. The results suggest that the commercialised health program had a positive effect by increasing physical activity among employees in the workplace. The intervention included initiatives such as fitness challenges, group exercise sessions, and educational workshops on the importance of physical activity. Participants reported a significant increase in their overall physical activity levels, with a majority engaging in regular exercise both during and outside of working hours. Moreover, participants expressed higher levels of motivation, improved well-being, and increased job satisfaction due to their participation in the intervention. However, some challenges were identified during the implementation process. These included difficulties in sustaining participation over time, limited engagement from certain employee groups, and the need for ongoing support and encouragement from management. In conclusion, the commercialised health intervention demonstrated its potential to effectively promote physical activity in the workplace in Malaysia. It had a positive impact on employees' physical activity levels and was associated with various positive outcomes, including increased motivation and job satisfaction. To ensure the sustainability of such interventions, it is crucial to address the identified challenges and provide ongoing support and encouragement to employees. Further investigations are required to explore the long-term effects and scalability of similar interventions in different workplace settings.
Under the Covert Norm: A Qualitative Study on the Role of Residency Culture on Burnout
Authors: Armas-Neira Mónica , Jaimes-Jiménez Ithandehui , Turnbull Bernardo , Vargas-Lara Alma , López-Covarrubias Adara , Negrete-Meléndez Jatsiri , Mimiaga-Morales Manuel , Oca-Mayagoitia Sandra Montes , Monroy-Ramírez Lilia 
Published: July 2024

Abstract

Purpose: Burnout has become a major concern within healthcare. Medical residents comprise a notorious at-risk population with around half of its population affected. While previous work highlights the role of organizational risk factors as the main contributors to occupational burden, research on culture in medicine as a potential organizational risk factor is limited. The main objective of this qualitative study was to explore the expressions of the cultural norm from the medical residents’ perspective to set the stage for future high-impact interventions.
Methods: Data were gathered from 87 semi-structured interviews with residents in Mexico City and analyzed through a grounded theory lens.
Results: The analysis uncovered harmful customary practices within medical residency culture. A distorted hierarchical system was responsible for promoting abusive power dynamics that fed into a ‘covert norm’ that continually infringed on formal regulations. This system is partly sustainable due to poor reporting mechanisms and self-perpetuating behaviors through normalization and violent enforcement.
Conclusion: The findings suggest that burnout was independently associated with and occurred in the context of covert conventions that defy guidelines. Further studies are needed to assess proper organizational interventions that reject covert sociocultural normative conformity for a more humanistic side of medical culture.
Application of Statistical and Artificial Neural Network(s) on Selected Features of RSRW Data to Nowcast Severe Thunderstorm
Authors: Bhattacharya Sonia , W(Bhattacharyya) Himadri Chakrabarty 
Published: July 2024

Abstract

Severe thunderstorm is one of the extreme natural calamities. In the present study, different weather parameters such as- moisture difference, adiabatic lapse rate and wind shear have been chosen to forecast severe thunderstorm. Here, moisture difference at 5 different geo-potential heights of atmosphere, dry adiabatic lapse rate at 5 different geo-potential heights of atmosphere, and vertical wind shear at 3different geo-potential heights of atmosphere that is, total 13 weather parameters have been chosen for prediction purpose. Here, the Naïve Bayes method, Multi Layer Perceptron, and K-Nearest Neighbor method have been considered. Radial Basis Function Network (RBFN) has been introduced here which produce far better result in comparison with other methodologies. Applying Principal Component Analysis (PCA) on these weather parameters 3variables of adiabatic lapse rates and 3 variables of vertical wind shear have been selected as determinant factor. Again Naïve Bayes method, Multi Layer Perceptron and K-Nearest Neighbor methodologies have been applied on the chosen predicators. This gives better outcome than before, but application of Radial Basis Function Network gives most accurate results among other methodologies. The RBFN gives more than 96% accurate forecast for both squall days and no squall days. Moreover this study has a lead time of 10–12 hours which is very much important to take necessary precaution to save life and property.
Upper Miocene volcanic ash layers from central Italy: looking for the missing eruption.
Authors: Roverato Matteo , Farina Federico , Lupi Matteo , Ovtcharova Maria , Montanari Alessandro , Bonini Marco , Montanari Domenico 
Published: July 2024

Abstract

The Mediterranean region has been characterized by intense explosive volcanism since the Eocene. These eruptions ejected tephra, including fine grained ash, which were thrown into the air and dispersed over wide areas to later be deposited as ash layers, many of which are preserved in some continental and marine sedimentary basins. Their study provides crucial insights into past volcanic activity, yet, for many of such ash layers, the understanding of their sources remains challenging. The presence of many ash layers across central Italy is widely recognized in literature although not uniquely associated with a specific volcanic source. We investigate in detail upper Tortonian (∼7.6 Ma) ash layers sampled from three different localities, from the Tyrrhenian to the Adriatic coast of Italy, comparing our results with others already described in the literature. Electron microprobe geochemical analyses on biotite crystals, U-Pb ID-TIMS and LA-ICP-MS geochronological dating and trace elements / Lu-Hf isotope analyses on zircons permitted us to expand our knowledge of these ancient ash deposits. Several potential volcanic centers were active during the late Tortonian, including the Massif Central (France), the Valencia trough (Spain), the Betics-Rif orogen (Spain-Morocco), and eastern Carpathians (Romania)and Capraia island (Italy). Through detailed radioisotopic dating and geochemical comparisons, we narrow down the possible source to the Upper Miocene Capraia island volcano (Tuscan archipelago), located in the northern Tyrrhenian basin.
Key stakeholders’ perspectives of illicit drug use and associated harms in the Northern Territory of Australia
Authors: Brickley Bryce , Moore Samuel , Tari-Keresztes Noemi , Brand Anthea , Bower Madeleine , Bonson Jason G. , McEntee Alice , Bartram Ashlea J. , Bovopoulos Nataly , McPhie Skye , Martin Craig , Wright Cassandra , Bowden Jacqueline , Smith James A. 
Published: July 2024

Abstract

Background
In the Northern Territory (NT) of Australia, there are significant evidence gaps about illicit drug use and harms, despite having established monitoring and reporting systems. This paper reports on illicit drug use, associated harms, contributing factors, service needs and priorities in the NT from the perspective and experiences of key stakeholders engaged in providing services for, or advocating on behalf of, people who use illicit drugs in the NT.
Methods
Face-to-face and online qualitative interviews were conducted with stakeholders across urban and remote locations in the NT. Key stakeholders were service providers, including acute and primary care clinicians, representatives of Aboriginal community controlled health organisations, lived experience advocates, peak body representatives and public health executives. Qualitative data were analysed thematically.
Results
Four researchers interviewed 21 participants across urban (62%), and remote areas (38%) of the NT. Themes identified were: 1) Illicit drug use and harms are diverse and distinct; 2) Client support needs are complex and influenced by co-morbidities, socio-demographic and cultural factors; 3) Priority population sub-groups need targeted strategies; 4) Local service strengths can be further developed and enhanced; 5) Local services need better resourcing; 6) Invest in progressive legislative and policy reforms; and 7) Improve routine monitoring and evaluation.
Conclusions
Key stakeholders described illicit drug use, harms and contributing factors, which provided insights into the local challenges. Participants emphasised that clients have complex care needs, and further investment into targeted strategies are required to improve service engagement with priority groups. Service needs included greater understanding the role of dual diagnosis and its implementation and enhancing integrated and collaborative care in both primary health and acute care contexts. The voices of people with lived experience captured in this paper must inform local strategy and policy development relating to illicit drug use, in alignment with national strategy.
Dynamics of ionized poly(4-hydroxystyrene)-type resist polymer with tert-butoxycarbonyl-protecting group
Authors: Okamoto Kazumasa , Muroya Yusa , Kozawa Takahiro 
Published: July 2024

Abstract

Resist materials used for micro- and nano-patterning are formed by radiation-induced chemical reactions, with the shortening of wavelengths of the exposure light sources in lithography systems. The most widely used patterning materials in industrial lithography are chemically amplified resists (CAR). Understanding the deprotonation mechanism of ionized polymers (radical cations) is important for acid generation in CARs. In this study, the dynamics of radical cations in poly(4-hydroxystyrene) (PHS)–type resist polymers, partially and totally protected by tert-butoxycarbonyl (t-BOC) groups, are investigated using a combination of electron pulse radiolysis experiments, acid yield measurements, and quantum chemical calculations. The t-BOC(oxy) group exhibits p-electron-donating behavior in the monomer cation but changes to electron-accepting behavior in the polymer cation, owing to the interaction between substituents. The destabilization of radical cations due to decreased intramolecular charge resonance may contribute to the high deprotonation efficiency of t-BOC-capped PHS polymers.
Extraction and Recognition of Robotic Apple Picking Image Features Based on YOLOv5 Detection Models
Authors: Hong Wenqian , Jiang Yirong , Lin Bin 
Published: July 2024

Abstract

As China has emerged as one of the leading exporters of apples globally, the shortage of agricultural labor has posed a significant challenge for the apple industry’s growth. To address the issue of image recognition for robotic apple picking in complex orchard settings, this paper combines computerized image processing and deep learning concepts to propose a detection model based on YOLOv5. By implementing image preprocessing techniques and optimizing the loss function, the study successfully achieves accurate extraction and recognition of apple image features. The experimental findings demonstrate the high performance and accuracy of the proposed method in apple picking tasks, offering valuable support for the advancement of robotic automated picking systems. Future research endeavors will focus on further refining the algorithm to enhance efficiency in real-world production settings.
Measuring neurodevelopment of inhibitory control in children using naturalistic virtual reality
Authors: Dina Larisa-Maria , Pinti Paola , Smith Tim J 
Published: July 2024

Abstract

Inhibitory control develops over time and is linked to fronto-striatal maturation. Traditional computerised assessments often lack ecological validity and are not age appropriate. Here, we developed a naturalistic, age-appropriate paradigm using a cave automatic virtual environment (CAVE) and mobile functional near-infrared spectroscopy (fNIRS) to measure response inhibition. The new task was validated in adults (N=24), toddlers and preschoolers (N=36). Participants completed two Go/No-Go tasks: a standard computer-based version and an adapted CAVE version, while fNIRS recorded brain activity in the bilateral dorsolateral frontal cortices. The aim was to examine the neural and cognitive features of response inhibition. The CAVE task proved feasible and acceptable, with high completion rates and minimal virtual reality-induced symptoms. As expected, we found higher error rates in Go/No-Go blocks compared to Go-only blocks. In children, there were significant associations between performance measures on both tasks, indicating acceptable convergent validity. Notably, specific to the child group, the CAVE task elicited higher activity in the left inferior frontal gyrus, and behavioural task performance was sensitive to age differences. This study shows the brain correlates of response inhibition during a naturalistic task in young children, integrating age-appropriate fNIRS with an immersive CAVE, opening potential new approaches to studying neurodevelopment.
Family member’s help-seeking behaviour for their relative who misuse substances: a cross-sectional national study in Brazil
Authors: Bortolon Cassandra Borges , Canfield Martha , Padin Maria Fatima Rato , Orford Jim , Laranjeira Ronaldo 
Published: July 2024

Abstract

Purpose: Affected family members(AFMs) of relatives who misuse substances (RMS) play an important role in supporting their relatives to enter substance use treatment. This study investigated the help-seeking behaviours for their relatives by AFMs in Brazil including the characteristics of those who sought help and the risk factors for delaying seeking help.
Methods: Secondary analysis from a national cross-sectional study of 3,030 AFMs was performed. Data on socio-demographic characteristics, seeking help behaviours, reasons for delaying help-seeking, demographic and substance use characteristics of the relative, and coping strategies were collected.
Results: Of the 92.7% of the sample that sought help for the relative, 66% delayed seeking help for 37.2 (SD 70.71) months. Help-seeking was associated with higher socioeconomic status and residing in the Southeastern region. Reasons for delaying help-seeking included the relative not accepting help (31.5%) and participants thinking that help/treatment wasn’t needed (20.6%). A longer delay in seeking help was associated with female AFMs, residents in the Centro-West region, non-parents compared to parents, a longer length of time knowing about the substance misuse, older RMS, alcohol as a substance of misuse, having another substance misuse relative in the family, and higher levels of withdrawal coping strategy.
Conclusions: Prominent barriers to motivating families to seek help for their relatives exist at multiple levels including socioeconomic, cultural and regional influences. Public health providers and policymakers should pay more attention to these barriers when developing interventions aimed at promoting substance use treatment entry in individuals with substance misuse problems.
Analysis of changes in protein intake following laparoscopic sleeve gastrectomy and its influencing factors
Authors: Zhao Huiling , Wu Lulu , Zhang Xiaoman , Zhang Xiaojiao , Zhang Dan , Liu Yuping 
Published: July 2024

Abstract

Objective: Little is known about factors associated with protein intake post-laparoscopic sleeve gastrectomy especially in Chinese weight loss patients over six months. This project aimed to identify possible factors to improve protein intake, and investigate protein supplement usage to reduce complications such as malnutrition.
Methods: A prospective observational study was conducted on 120 eligible patients at a tertiary hospital, who completed study measures at baseline, 3 months post-surgery (M3), and 6 months post-surgery (M6). Univariate and multivariate Linear regressions were utilized to analyze factors related to protein intake.
Results:At M6, most patients did not meet the recommended post-LSG protein intake of ≥60 g/day. The three macronutrients for all patients were significant differences in dietary and protein supplement sources between M3 and M6. The EBBS score decreased from M3 to M6, while the chewing cycle and food tolerance scores increased postoperatively. multi-factor linear regression was found that eight independent variables, including gender, age, daily vitamin intake at M6, and total EBBS score at M6, were influencing factors on daily protein intake at M6.
Conclusions: Findings shed new light on factors that may account for deficiency protein intake, which have implications for guiding effective interventions targeting this behavior.
Personalized Federated Learning with Adaptive Information Fusion
Authors: Chai Liming , Yu Wenjun , Zhou Nanrun 
Published: July 2024

Abstract

Data heterogeneity is a key challenge in the field of federated learning. Many existing personalized federated learning approaches focus on the performance of local models, neglecting the generalization capabilities of the global model, which may not be cost-effective. To address this issue, a federated learning algorithm called Personalized Federated Learning with Adaptive Information Fusion (FedIF) is proposed, which fuses two model heads carrying different information to obtain a personalized model fitting the local data better. The personalization steps of the FedIF are carried out after the local training in each round of the FedAvg algorithm, allowing it to be combined with other algorithms that improve upon the FedAvg. Comparative and ablation experiments between FedIF and other state-of-the-art personalized federated learning algorithms were conducted under three public datasets and two medical imaging datasets. The exceptional performance of our algorithm is attested across a wide range of experimental settings.