bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cultural adaptation and evaluation of Namaste Care program for home-dwelling persons with dementia and their caregivers in China: a mixed-methods study protocol
Authors: Jin Meng , Meng Dijuan , Sun Chang , Shen Qinan , Bai Yamei , Xu Guihua , Song Yulei , Wang Shanshan , Chen Hongtu 
Published: July 2024

Abstract

Background: The Namaste Care program is an evidence-based intervention proven effective for individuals with moderate to advanced dementia and their caregivers. To enhance its efficacy, the program will be adapted to align with Chinese culture.
Methods: A multi-stage, mixed-methods design comprising three stages and eleven steps will be implemented, incorporating comprehensive process evaluations. Outcome measures will include the quality of life and self-perceived burden for persons with dementia, as well as the quality of life, caregiving burden, caregiving capacity, attitudes towards caregiving, and positive perceptions of dementia for caregivers. These outcomes will be evaluated through a combination of qualitative feedback and specific quantitative measures collected at baseline (T0), immediately post-intervention(T1), and three-month post-intervention (T2). Linear mixed effects models will be employed to analyze the effects of intervention. Qualitative interviews will explore caregivers’ experiences, and thematic analysis will assess the acceptability of the intervention.
Discussion: A culturally adapted Namaste Care program is essential for implementing practical adjustments that accommodate local communities and cultural contexts.The expected outcomes will enhance the knowledge of non-pharmacological interventions for dementia care within the home setting.
Trial registration: This study was registered on 29 August 2023 at https://www.chictr.org.cn (identifier: ChiCTR2300075195).
LWCNet: A Lightweight and Efficient Algorithm for Household Waste Detection and Classification Based on Deep Learning
Authors: Wang Yue , Wang Jingzhe , Sun Aixi , Zhang Yu 
Published: July 2024

Abstract

The existing waste classification algorithms based on computer vision are hindered by issues such as low classification accuracy, a large number of model parameters, and high computational complexity. Aiming at these problems, a Lightweight Waste Classification Network (LWCNet) based on the basic framework of YOLOv8n is designed and proposed in this paper. Firstly, a detection head based on the self-attention mechanism, SAHead, is proposed to capture a wider range of contextual information. Secondly, the lightweight convolution GSConv is employed to optimize the standard convolution in YOLOv8n. Combined with GELAN, the GRCSPELAN module is designed to reduce the model size without compromising performance. Finally, the AIFI module is introduced to enhance the intra-scale feature interaction ability. The experimental results indicate that LWCNet effectively reduces the model size and enhances detection efficiency, providing reliable theoretical support for the automation of household waste detection and classification.
Can Body Dissatisfaction Worsen Eating Disorders? The Moderating Role of Mindfulness and Body Mass Index among a sample of Lebanese adults
Authors: Khoury-Malhame Myriam El El , Obeid Sahar , Ayoub Mira , Sawma Toni , Hallit Souheil 
Published: July 2024

Abstract

Background.
Body shape dissatisfaction, increasingly common in adults, is a known predictor of mental distress in general and eating disorders in particular. Recently, mindfulness has been introduced as a potential psychological buffer to dampen these disorders. This study investigates the relation between body shape satisfaction and eating disorders and evaluates the potential moderating role of mindfulness and body mass index among a sample of Lebanese adults.
Methods.
A total of 324 adults were recruited via snowball sampling technique and were asked to fill demographic data and standardized questionnaires online. In addition to age, gender, and Body Mass Index (BMI), participants were assessed for body shape dissatisfaction, eating disorders, as well as mindfulness.
Results.
Findings indicate that higher body shape concerns, higher BMI and lower mindfulness were associated with higher eating disorders. We also found that mindfulness and BMI moderated the relationship between body shape concerns and eating disorders. Yet, considered alone, did not dampen the direct relation of body concerns worsening eating disorders.
Conclusion.
Taken together, these results indicate that the impact of perceived body shape concerns over eating disorders could be moderated by mindfulness and actual body mass. Yet, these factors alone are not sufficient to reduce the negative impact of body shape. Therefore, additional studies are warranted to look into the intricate relation between them to further bolster the effect of focused attention and body size on maladaptive eating behaviors worsened by dissatisfaction with ones’ shape.
Pediatric oncology healthcare professionals’ attitudes to and awareness of regulations for minors’ and guardians’ online record access: A mixed-methods study in Sweden
Authors: Hagström Josefin , Blease Charlotte , Harila Arja , Lähteenmäki Päivi , Scandurra Isabella , Hägglund Maria 
Published: July 2024

Abstract

Background: Healthcare providers and policymakers worldwide differ in their provision of access to adolescent patients’ electronic health records (EHR). The regulatory framework in Sweden restricting both guardians’ and adolescents’ online record access (ORA) has during recent years received criticism. The aim was to quantitatively and qualitatively, explore attitudes about ORA and perceptions about ORA regulations among pediatric oncology healthcare professionals (HCPs) in Sweden.
Methods: A convergent mixed-methods design (QUAL, quan) was used, consisting of a survey study (N=95) and semi-structured individual interviews (N=13). Physicians and nurses in pediatric oncology were recruited in clinics face-to-face or via staff e-mail. Descriptive statistics were used to present quantitative survey results. Interviews were recorded, transcribed, and analysed using content analysis.
Results: Participants were critical of the access gap but lacked knowledge about access extensions, with more than 60% unaware of application procedures. Qualitative analysis resulted five themes of benefits (Improving adolescents' and parents' emotional state, Facilitated parental care management, Empowering adolescents, Improving partnership and communication and Enhanced documentation accuracy) and five themes of downsides (Increased emotional distress and confusion, Decreased documentation quality and accuracy, Increased workload, Threatened confidentiality, and Technical portal limitations). HCPs’ views on regulations were categorized into five themes: Uncertainty, Adolescents differ, Balancing parental support and adolescent privacy, “I understand why access is restricted, but…”, and Regulatory changes.
Conclusions: Most pediatric oncology HCPs in this study were critical about ORA restrictions during adolescence, recognizing benefits primarily of parental access. Perceived benefits of enhanced parental support and adolescent empowerment conflicted with perceived risks of confidentiality and emotional distress in adolescents and parents from accessing unexplained results. While ORA has potential to improve partnerships in adolescent healthcare, information, guidance and resources for HCPs are needed to ensure patient safety and quality of documentation.
Trial registration: Not applicable.
Perceptions of integrating cervical cancer screening with HIV and sexual and reproductive health services: results from serial qualitative studies among health workers and women in Zimbabwe
Authors: Ruhode Nancy , Madanhire Claudius , Tumushime Mary K , Gudukeya Stephano , Muhonde Nyaradzo D , Hatzold Karin , Cowan Frances M , Sibanda Euphemia L 
Published: July 2024

Abstract

Background
Cervical cancer screening among Zimbabwean women is suboptimal. Integrating cervical cancer screening with HIV and sexual and reproductive health services can improve uptake. To inform optimisation of integrated models, we explored evolution of women’s and health worker views on integration and cervical cancer screening.
Methods
Over three phases between Nov-2013 and Mar-2016, we collected serial qualitative data from female clinic attendees and health workers at four clinics providing integrated cervical cancer screening and HIV and sexual/reproductive health services. Using program data, we examined trends in uptake of cervical cancer screening.
Results
Between 2013–2016, 38,342 women were screened for cervical cancer at three clinics. Program data showed increasing trends in uptake, capping at clinic capacity. Qualitative studies showed that clinic attendees and health workers viewed integration positively across phases because: i) information on cervical cancer screening was easily disseminated, leading to improved uptake; ii) co-location of services was convenient. As knowledge increased, demand exceeded supply, requiring operation of strict appointment-based systems. Other facilitators to cervical cancer screening included offer of services for free, personal experience of friend/family who suffered cervical cancer, peer encouragement, spousal/partner support, and having suspicious signs/symptoms. Barriers were more pronounced in earlier phases and largely centred around myths that spread in communities or clinic waiting rooms. Lack of training among health workers impeded implementation.
Conclusions
Integrating cervical cancer screening with HIV and sexual/reproductive health services was feasible and acceptable, with less pronounced barriers as programs matured. Addressing individual and program-level barriers can optimise uptake of services.
What proportion of cannabis users in Germany have spoken with their general practitioner about their consumption? A repeated cross-sectional representative population survey
Authors: Borchardt Benjamin , Klosterhalfen Stephanie , Kotz Daniel 
Published: July 2024

Abstract

Introduction:
On 1st of April 2024 a law on cannabis legislation entered into force in Germany. Henceforth, a rise in cannabis consumption rates and consequently cannabis related health impacts is expected. Preventive measures are only possible if harmful use is recognised and addressed at an early stage. We set up to estimate the proportion of cannabis users in Germany that discussed their cannabis consumption with their general practitioner (GP), either on the initiative of the GP or the patient, and how these varied according to person characteristics.
Methods
We used data from the German Study on Tobacco Use (DEBRA). This is a repeated ongoing representative cross-sectional household survey on use of tobacco and alternative nicotine delivery systems in Germany in people aged 14 years and older. During bimonthly study waves we asked all respondents who stated that they had consumed cannabis before whether they had ever spoken with their GP about their cannabis use or received advice about it. We estimated the proportion including 95% confidence intervals and assessed possible associations with person characteristics by using univariate logistic regression models.
Results
Of 2,057 ever users of cannabis, 7.0% [95%CI = 5.9; 8.2%] (n = 139) answered “Yes, I have ever spoken to my general practitioner about my cannabis use or sought advice in this regard”. This response was associated with older age (65+), low educational attainment, low income, and frequent cannabis use. Conversation with a GP was also more common in past-year cannabis users (16.2% [95%CI = 13.5; 19.6%], n = 591).
Conclusions
Around one in fifteen cannabis users has ever spoken with his or her GP, or received advice, about his or her cannabis consumption. In past-year and frequent users, the proportions are highest, between 16 to 26%. The awareness of this topic among GPs needs to be increased. Furthermore, a future re-evaluation on what impact the legislation of cannabis will have on the frequency of consultation about cannabis consumption in primary care is necessary.
Collusion between Retailers and Customers: The Case of Insurance Fraud in Taiwan
Authors: Picard Pierre , Wang Jennifer , Wang Kili 
Published: July 2024

Abstract

We analyze how the insurance distribution channel may affect claim fraud.
Attention is focused on the Taiwan automobile insurance market, with a
database provided by two large insurers. The econometric analysis confirms the
evidence of fraud through claim manipulation, in order to skirt around the
bonus-malus system and to reduce the weight of insurance deductibles. We
highlight the role of car-dealer insurance agencies in this fraud process, and
its change from 2010 to 2018. The theoretical underpinnings of our analysis
are provided by a model of claims fraud with collusion and audit.
Artificial Neural Networks Estimate Evapotranspiration For Miscanthus × Giganteus As Effectively As Empirical Model But With Fewer Inputs
Authors: Sungur Guler (Rojda) Aslan , Moore Caitlin E. , Bernacchi Carl J. , Heaton Emily , Vanloocke Andy 
Published: July 2024

Abstract

Estimating actual evapotranspiration (ET) is particularly crucial for addressing how vegetation affects the water balance of ecosystems. ET estimation can be complex with empirical models due to their many parameters and reliance on aridity. In contrast, artificial neural networks (ANNs) could potentially estimate ET with fewer and more common meteorological parameters. In this study, we trained two ANNs, one using a feed-forward approach (FFN) and the other a nonlinear auto-regressive network (NARX), to predict ET and compared them to the commonly used empirical model Granger and Gray (GG). We trained our models on a nine-year eddy covariance (EC) dataset for Miscanthus × giganteus (M. × giganteus) from Illinois (UIEF), then tested them using out-of-sample data from both UIEF and a different location in Iowa (SABR) to compare the accuracy of FFN, NARX, and GG models in estimating daily ET.
A combination of air temperature (Ta) and solar radiation (Rs) was chosen as inputs due to the highest R2 for FFN (R2= 0.79, 0.81, and 0.79 for training, testing, and validation, respectively) and only Ta for NARX (R2= 0.70 for out-of-sample validation). The predictive power of the FFN model was superior to the NARX and GG models at the UIEF site (R2= 0.84, 0.70, and 0.83 for out-of-sample validation, respectively). Our analysis showed that ANN approaches are as accurate as empirical approaches for estimating ET but use fewer inputs.
Most Potential Neuroprotective compound isolated from Allium sativum Targeting Alpha Synuclein involved in Parkinson’s Disease identified through Molecular Docking and MTT Assay
Authors: Ahmad S Rehan , Zeyaullah Md. , AlShahrani Abdullah M. , Muzammil Khursheed , Khan Mohammad Suhail , Qavi Danish , Husain Izhar , Altijani Abdelrhman Galaleldin , Dawria Adam , Mohieldin Ali , Alam Mohammad Shane 
Published: July 2024

Abstract

Background -Parkinson’s Disease (PD) is the second most common neurodegenerative disorder after Alzheimer’s Disease (AD) which is marked by symptoms like tremors, muscle weakness, etc. Still, levodopa is considered a gold standard drug for PD which just reduces symptoms and there is an urgent need for drugs for permanent cure of PD. In this study, we are investigating nine neuroprotective compounds extracted from Garlic as it has medicinal properties like reducing inflammation. In this study, we are identifying the most promising compound from nine compounds.
Methodology - First molecular docking was performed for all nine compounds using AutoDock 4.2.6 in which we considered Alpha-Synuclein as the target protein. After molecular docking based on binding affinities, we proceed toward the MTT assay.
Result - The binding affinity of the nine compounds lies between −5.1 and −10.8 kcal/mol, In this study allicin and E-ajone show a binding affinity of -10.4 kcal/mol. So, for further in vitro study we took alliin, allicin, ajone, and diallyl disulfide and performed an MTT assay for all four compounds on rotenone-induced neurotoxicity in the SHSY5Y neuroblastoma cell line.
Conclusion - Based on in silico and in vitro findings we reach to the conclusion that allicin is the most promising neuroprotective compound from all nine compounds of Garlic but still depth in vitro and in vivo analysis is needed before we proceed toward clinical trials.
A Multilevel Analysis of Factors Associated with Minimum Acceptable Diets Among Children Aged 6-23 Months in Lesotho: A Study of The Lesotho Multiple Cluster Indicator Study of 2018
Authors: Leseba Nthatisi , Vermaak Kerry , Makatjane Tiisetso 
Published: July 2024

Abstract

Background The World Health Organization’s Infant and Young Children Feeding Guidelines (IYCF) has been adopted as an international acceptable complementary feeding guideline known as the Minimum Acceptable Diet (MAD). MAD is a combination of Minimum Meal Frequency (MMF) and Minimum Dietary Diversity (MDD). MAD is not met in many countries in the world. This study aimed to determine the prevalence and multilevel determinants of a minimum acceptable diet among children aged 6–23 months in Lesotho.Methods We conducted a multilevel logistic regression using data from the Lesotho Multiple Cluster Indicator Study of 2018.Results In Lesotho only 22.7% [CI: 19.6 26.2] of children aged 6–23 months received MAD. At individual level, higher odds of receiving MAD were observed among females (WAR = 1.43; CI: 1.1 1.3) and children aged 9–23 months (WAR = 1.67; CI: 1.3 2.2). At household level, only maternal age of 20–25 and 35–39 were statistically significant to MAD; on the other hand, the odds of receiving MAD were higher for children with maternal age of 30–34 (WAR = 1.15; CI: 0.8 1.7) and 40+ (WAR = 1.13; CI: 0.6 2.0). Moreover, at community level, children in communities with high proportions of poor households had lower odds of receiving MAD (WAR = 0.64; CI: 0.5 0.8) and children in communities with high proportions of maternal media exposure had higher odds of receiving MAD (WAR = 1.53: CI:1.1 2.2).Conclusion At individual level, child sex and age were determinants of MAD. At household level maternal age was a determinant of MAD, maternal age in this case indicates that knowledge and experience in childcare contributed to better dietary intake for children aged 6–23. At community level, lack of care resources, food availability and knowledge acquisition were determinants of MAD. Therefore, strategies and programs to improve MDD nationwide should be done at community level.
Robust-GBDT: Leveraging Robust Loss for Noisy and Imbalanced Classification with GBDT
Authors: Luo Jiaqi , Quan Yuedong , Xu Shixin 
Published: July 2024

Abstract

Dealing with label noise in tabular classification tasks poses a challenge in machine learning. This paper introduces Robust-GBDT, a novel approach to enhance the robustness of Gradient Boosting Decision Trees (GBDT) models against label noise and class imbalance in tabular data classification. We present a theoretical insight demonstrating that nonconvex loss functions, under specific constraints, can be effectively employed in GBDT models. Leveraging this foundation, Robust-GBDT integrates advanced GBDT frameworks with robust loss functions, including a newly proposed Robust Focal Loss designed to address class imbalance. Our method overcomes limitations of existing noise-robust boosting techniques, such as binary classification constraints, inability to handle imbalanced datasets and missing values, and computational inefficiency. Experimental results show that Robust-GBDT outperforms existing bagging and robust boosting methods, delivering more accurate predictions and improved generalization capabilities in scenarios with label noise and class imbalance.
The short-term and accumulated effects of extreme high temperature on depressive symptoms in China: a difference-in-difference analysis
Authors: Liu Linfeng , Yin Bo , Ke Limei , Chen Runsen , Zhang Ying , Liu Jianxiu , Di Qian 
Published: July 2024

Abstract

Background
As global warming continues to worsen, the adverse effects of extreme high temperatures have been extensively studied, including the impact on depression. However, few studies have explored the impact of extreme high temperatures on depressive symptoms at different time scales.
Methods
We conducted a difference-in-difference analysis using data from China Family Panel Studies, which includes 108,099 samples. Depressive symptoms were measured by the Center for Epidemiological Studies Depression Scale. We identified 32 ºC as a threshold and defined the proportion of hours above 32 ºC as the metric of the exposure to extreme high temperatures.
Results
Our results found that extreme high temperatures increased depressive symptoms in both short-term and long-term. Exposure to more than one extreme high temperature hour in a day significantly increased depressive symptoms by 3.21% (95% CI: 2.08%, 4.36%). Our findings also revealed that the effects of extreme high temperature intensified over extended time periods, indicating a cumulative effect. In the subgroup analysis, the elderly (> 60 years) were more vulnerable than the young (< 36 years). Furthermore, we made predictions on the future extreme-high-temperature-induced depressive symptoms in China under different emission scenarios and found that the depressive symptoms in the Chinese population would increase by 22.83% (95% CI: 16.06%, 30.16%) by 2060 even under the most optimistic scenario.
Conclusions
Our study highlighted significant adverse effects of extreme high temperatures on depressive symptoms at different time scales, which warrants effective interventions to protect mental health from a warming climate.
Patch-Wise Self-Supervised Visual Representation Learning: A Fine-Grained Approach
Authors: Javidani Ali , Sadeghi Mohammad Amin , Araabi Babak Nadjar 
Published: July 2024

Abstract

Self-supervised visual representation learning traditionally focuses on image-level instance discrimination. Our study introduces an innovative, fine-grained dimension by integrating patch-level discrimination into these methodologies. This integration allows for the simultaneous analysis of local and global visual features, thereby enriching the quality of the learned representations. Initially, the original images undergo spatial augmentation. Subsequently, we employ a distinctive photometric patch-level augmentation, where each patch is individually augmented, independent from other patches within the same view. This approach generates a diverse training dataset with distinct color variations in each segment. The augmented images are then processed through a self-distillation learning framework, utilizing the Vision Transformer (ViT) as its backbone. The proposed method minimizes the representation distances across both image and patch levels to capture details from macro to micro perspectives. To this end, we present a simple yet effective patch-matching algorithm to find the corresponding patches across the augmented views. Thanks to the efficient structure of the patch-matching algorithm, our method reduces computational complexity compared to similar approaches. Consequently, we achieve an advanced understanding of the model without adding significant computational requirements. We have extensively pretrained our method on datasets of varied scales, such as Cifar10, ImageNet-100, and ImageNet-1K. It demonstrates superior performance over state-of-the-art self-supervised representation learning methods in image classification and downstream tasks, such as copy detection and image retrieval.