bluuebunny/crossref_metadata_2025_split huggingface dataset:
Transfer learning for material parameter extraction from current-voltage characteristics of solar cells
Authors: Lin Zhuoyi , Ragab Mohamed , Ren Zekun , Yoon Ji Wei , Buonassisi Tonio , Chellappan Vijila , Jayavelu Senthilnath 
Published: November 2023

Abstract
Solar cells are a critical component of renewable energy systems and are becoming increasingly important as society moves towards decarbonization. To assess their economic viability and sustainability, developing solar technologies with desired performance levels is an important consideration. Among various material parameters, carrier lifetime is one of the key material properties which influences the performance metrics of solar cells significantly. Measurement of carrier lifetime using experimental methods is a complex and tedious procedure, hence machine learning (ML) methods can be used to accelerate the prediction of carrier lifetime from the Current density-voltage (J-V) characteristics. However, ML methods generally require a large amount of data to achieve accurate predictions. To this end, looking for an efficient solution to learn transferable knowledge for the carrier lifetime prediction of different solar cell materials with less data is of utmost significance. In this paper, we propose a transfer learning (TL) framework to learn common knowledge between Silicon (Si), Gallium arsenide (GaAs), and perovskite solar cells (PSC) for carrier lifetime prediction. Our TL framework uses deep neural network (DNN) architecture with two methods, i) pre-training and fine-tuning entire layers, and ii) pre-training and fine-tuning regressor layer alone. Hence, these methods facilitate data-efficient and parameter-efficient learning. In this way, one can improve the accuracy of carrier lifetime prediction by learning with the source material data and fine-tuning with less data for the material of interest (target material data). The experimental results on simulated data and experimental data indicate that TL has autonomously identiﬁed nontrivial transferability across different materials. This leads to faster convergence and more robustness while training a DNN model and higher accuracy for carrier lifetime prediction.
Research on the influencing factors of chip forming in 304 stainless steel deep hole gun drilling
Authors: Lou Jiacheng , Dong Xiaofei , Cao Maozheng , Jiang Jitao , Zhang Yu , Li Liang 
Published: November 2023

Abstract

In deep hole gun drilling, the relationship between process parameters and chip forming process has always been a difficult point in the research of deep hole machining because of the small hole diameter, long hole depth, and narrow chip removal space.304 stainless steel has good corrosion and heat resistance and is widely used in medical treatment, food processing, and other fields. However, it also has processing difficulties, such as high hardness and poor plasticity. Therefore, this paper takes 304 stainless steel as the research object, with the help of Abaqus simulation software, simulates the chip forming process in the process of deep hole gun drilling and studies the influence of process parameters on chip forming. According to the simulation results, based on the fluid-solid coupling theory, the fluid-solid coupling simulation model is established through Ansys-Fluent simulation software. The influence of coolant pressure on chip forming is studied, and the relationship between coolant pressure and chip curling deformation is expounded in different growth periods of chips. Then, the deep hole gun drilling test was carried out, and the chip morphology was analyzed. Finally, the paper revealed the relationship between chip forming and process parameters in deep-hole gun drilling.
NALA: A Nesterov Accelerated Look-Ahead optimizer for deep neural networks
Authors: Zuo Xuan , Zhang Pu , Gao Shan , Li Hui-Yan , Du Wan-Ru 
Published: November 2023

Abstract

A series of adaptive gradient algorithms, such as Adadelta1, Adam2, AdamW3, Adan4 and AdaXod5, has been successfully used in training deep neural networks (DNN). Previous work reveals that adaptive gradient algorithms mainly borrow the moving average idea of heavy ball acceleration to estimate the first- and second-order moments of gradient for accelerating convergence4. However, Nesterov acceleration which uses the gradient at extrapolation point can achieve a faster convergence speed than heavy ball acceleration in theory. In this paper, a new optimization algorithm which combines adaptive gradient algorithm with Nesterov acceleration by using a look-ahead scheme, called NALA, is proposed for deep learning. NALA iteratively updates two sets of weights, i.e., the ‘fast weights’ in its inner loop and the ‘slow weights’ in its outer loop. Concretely, NALA first updates the fast weights k times using Adam optimizer in the inner loop, and then updates the slow weights once in the direction of Nesterov’s Accelerated Gradient (NAG) in the outer loop. We compare NALA with several popular optimization algorithms on a range of image classification tasks on public datasets. The experimental results show that NALA can achieve faster convergence and higher accuracy than other popular optimization algorithms.
Income-Related Gender Differences in Psychiatric Hospital Admissions Among Children and Adolescents
Authors: Nieminen Veera , Suokas Kimmo , Hakulinen Christian , Pirkola Sami 
Published: November 2023

Abstract
Children from low-income households have more mental disorders, although these connections have rarely been studied in terms of mental health service utilization in population-based data. In this national register-based cohort study all persons born and living in Finland with their families from 1991 to 2017 (n = 1 520 415) were followed until first psychiatric hospital admission, moving away from home, death, emigration, disappearance, or the end of 2017. We calculated age-, gender-, and household income-specific incidence rates (IR) and incidence rate ratios (IRR) for first admissions. In total, 27 691 (13 829 [49.9%] girls) persons were admitted for the first time to psychiatric hospital during the research period. In girls in all income deciles, IRs distinctly peaked at the age of 15 (at age 15 IR = 74.15, 95% CI 71.19–77.21). In boys, IRs started to increase after the age of 5, especially in the lowest income deciles, and there was no rapid peak in adolescence in any income group (at age 5 IR = 3.36, 95% CI 2.93–3.84; at age 10 IR = 26.13, 95% CI 24.70-27.62; at age 15 IR = 27.82, 95% 26.06–29.67). Overall, we observed a negative income gradient in first admissions, which was steeper for boys than for girls. These results highlight household income as an important risk factor for psychiatric hospitalizations in childhood and adolescence. Notably, low income appears to play a more prominent role in boys, whereas adolescence emerges as a critical period for girls, regardless of their household income levels.
Investigation of tazobactam/piperacillin– or meropenem–induced liver injury based on retrospective observational study and the FDA Adverse Event Reporting System
Authors: Shiraishi Chihiro , Kato Hideo , Ogura Toru , Iwamoto Takuya 
Published: November 2023

Abstract

Background
Our objective was to evaluate the association between tazobactam/piperacillin or meropenem and liver injury by performing a retrospective observational study and a study using data from the US Food and Drug Administration Adverse Event Reporting System (FAERS).
Methods
In a retrospective observational study, data of patients hospitalized in Mie University Hospital between 2010 and 2022 who initiated treatment with tazobactam/piperacillin or meropenem in the intensive care unit were extracted. Liver injury was defined as an elevated alanine aminotransferase (ALT) grade based on the Common Terminology Criteria for Adverse Events. The FAERS database between 2013 and 2022 were used.
Results
In the retrospective observational study, multivariate logistic regression analyses indicated that the risk factors for liver injury included administration period (odds ratio [OR] = 1.080, p = 0.005), sequential organ failure assessment score (OR = 1.133, p = 0.004), and ALT (OR = 1.042, p = 0.007). Male, age, the fourth–generation cephalosporin, carbapenem, β–lactam and β–lactamase inhibitor combination, and complication of sepsis were associated with liver injury (p < 0.001).
Conclusion
The periodic monitoring of liver function is strongly recommended in patients receiving tazobactam/piperacillin or meropenem, particularly in those with multiple risk factors for liver injury.
Bayesian Network-based Mendelian Randomization for Variant Prioritization and Phenotypic Causal Inference
Authors: Sun Jianle , Zhou Jie , Gong Yuqiao , Pang Chongchen , Ma Yanran , Zhao Jian , Yu Zhangsheng , Zhang Yue 
Published: November 2023

Abstract
Mendelian randomization is a powerful method for for inferring causal relationships. However, obtaining suitable genetic instrumental variables is often challenging due to gene interaction, linkage, and pleiotropy. We propose Bayesian Network-based Mendelian Randomization (BNMR), a Bayesian causal learning and inference framework using individual-level data. BNMR employs the random graph forest, a series of Bayesian network structural learning processes, to prioritize candidate genetic variants and select appropriate instrumental variables, and then obtains a pleiotropy-robust estimate by incorporating a shrinkage prior in the Bayesian framework. Simulations demonstrate BNMR can efficiently reduce the false positive discoveries in variant selection, and outperforms existing MR methods in terms of accuracy and statistical power in effect estimation. With application to the UK Biobank, BNMR exhibits its capacity in handling modern genomic data, and reveals the causal relationships from hematological traits to blood pressures and psychiatric disorders. Its effectiveness in handling complex genetic structures and modern genomic data highlight the potential to facilitate real-world evidence studies, making it a promising tool for advancing our understanding of causal mechanisms.
Occupational therapy in variant transthyretin amyloidosis in the Iberian Peninsula. A qualitative study
Authors: Gayà-Barroso Aina , González-Moreno Juan , Rodríguez Adrián , Ripoll-Vera Tomás , López Inés Losada , Gili Margarita , Cisneros-Barroso Eugenia , Paneque Milena 
Published: November 2023

Abstract
Occupational therapy is part of integrated care in health services. However, there is little research on how it is applied to rare diseases. The aim of this study was to investigate the occupational therapy situation and services offered to patients diagnosed with variant transthyretin amyloidosis in Portugal and Spain. A structured interview was carried out by an occupational therapist and a genetic counsellor with six Portuguese and four Spanish occupational therapists to collect opinions about the reality of occupational therapy and variant transthyretin amyloidosis. No occupational therapist working with variant transthyretin amyloidosis or other rare diseases was found. Therefore, general aspects of the discipline were discussed in order to study the situation of this profession in general terms. Four interrelated dimensions were considered. The first was a general perspective on psychosocial resources in health care, addressing questions related to the interventions offered to patients; the second and third were professional perspectives, asking questions about the role of occupational therapy in the Portuguese and Spanish psychosocial realities; and the fourth dimension was a social perspective, addressing questions about the role of occupational therapy in the Portuguese and Spanish psychosocial realities. Although this approach is not designed to generalise, it opens up a relevant avenue to explore in this area. The results highlights the importance of further research to develop and implement the discipline of occupational therapy in a multidisciplinary approach after variant transthyretin amyloidosis diagnosis, creating potential strategies to promote its use.
The impact of physical activity and exercise interventions on symptoms for women experiencing menopause: overview of reviews
Authors: Money Annemarie , MacKenzie Aylish , Norman Gill , Eost-Telling Charlotte , Harris Danielle , McDermott Jane , Todd Chris 
Published: November 2023

Abstract

Background
Women experiencing problematic menopausal symptoms report lower health-related quality of life and greater healthcare use than women without symptoms. Not all women want to or are able to take hormone replacement therapy. Strengthening the evidence for menopause symptom-management options, including physical activity, improves agency for women.
Aim
This overview assesses effectiveness of physical activity and exercise interventions targeting women experiencing menopause symptoms.
Methods
Medline, Embase, CINAHL, Scopus, The Cochrane Database of Systematic Reviews and Social Science Citation Index were searched (June 2023) for systematic reviews of physical activity and exercise interventions targeting women experiencing menopause. Reviews were assessed using AMSTAR-2 and a best-evidence approach to synthesis without meta-analysis (SWIM) was adopted. The protocol was registered on PROSPERO (CRD42022298908).
Results
Seventeen reviews included 80 unique relevant primary studies with 8983 participants. There is evidence showing improvement of physical, urogenital, and total symptoms following yoga interventions. Evidence for vasomotor and psychological symptoms was inconclusive. Findings for aerobic exercise were inconclusive although there were some examples of beneficial effects on total and vasomotor symptoms. Evidence was very limited for other types of physical activity and impact on physical, sexual, urogenital symptoms.
Conclusion
There is some evidence that yoga, and to lesser extent, aerobic exercise may be beneficial for some menopause symptoms, but there is insufficient evidence to recommend a particular form of exercise. Current reviews categorise women on menopause status; broadening this to include ethnicity, income status, employment and other factors will allow better understanding of context for successful interventions.
Effect of Dietary Approaches to Stop Hypertension (DASH) and Curcumin on Glycemic parameters in Polycystic ovary syndrome: Randomized controlled Clinical Trial
Authors: Zohrabi Tayebeh , Nadjarzadeh Azadeh , Jambarsang Sara , Sheikhha Mohammad Hasan , Aflatoonian Abbas , Mozaffari-Khosravi Hassan 
Published: November 2023

Abstract
Background
Polycystic ovary syndrome (PCOS) is an endocrine disorder that can lead to major reproductive and metabolic complications, including infertility and insulin resistance. Management of glycemic parameters is an important step to improve the symptoms of PCOS. Lifestyle-based treatments, including interventions with healthy eating patterns and natural bioactive compounds, may be effective. This randomized controlled clinical trial was conducted to evaluate the effects of Dietary Approaches to Stop Hypertension (DASH) diet and curcumin co-administration on glycemic parameters in normal weight and overweight/obese women with PCOS undergoing in vitro fertilization (IVF).
Methods
In this double-blind randomized factorial study, 104 infertile women with PCOS were divided into four intervention groups considering treatment conditions and body mass index (BMI). For 12 weeks, they received 500 mg twice daily of curcumin or placebo along with a DASH or standard diet, based on macronutrient composition (52% carbohydrate, 18% protein, and 30% total fat).
Results
Participants adhered to the intervention protocol (> 80%). Insulin levels in the supplemented group decreased significantly and remained significant even after adjusting for confounding variables (BMI, Energy difference, age and physical activity levels at the baseline) group (ß =34.77, 95% CI (4.93, 64.62), P-Value= 0.023). HOMA-IR also decreased significantly in supplement group (ß =7.616, 95% CI (0.889, 14.34), P-Value= 0.027), after controlling for confounders in the first model and other adjusted models. Changes in fasting blood sugar and insulin sensitivity were not significant in the supplement and diet groups.
Conclusion
The results of the study show that adding curcumin to the DASH diet can have positive effects on reducing insulin levels and improving insulin resistance, and lead to faster recovery of hyperinsulinemia. Therefore, investigating the combined effect of other dietary patterns and bioactive compounds is recommended. Trial Registration Number (TRN): IRCT20200915048731N1, URL: https://www.irct.ir/trial/50970; Date of registration: September 29, 2020.
Examining the Mediation Role of Parental Guilt in the Relationship Between Working Mothers' Smartphone Addiction and Their Children's Problematic Technology Use
Authors: Sarıyıldız Fatma Miray , Erus Seher Merve 
Published: November 2023

Abstract

This study aimed to examine the mediation of parental guilt in the relationship between smartphone addiction in working mothers and problematic technology use among their preschool children. A total of 260 working mothers, aged between 22 and 50, with preschool children, participated in the study. The study utilized the "Personal Information Form," "Smartphone Addiction Scale Short Form," "Parental Guilt Scale," and "Problematic Technology Use Scale for Children." SPSS bootstrapping analysis was applied to investigate the mediation of parental guilt in the relationship between mothers' smartphone addiction and their preschool children's problematic technology use. The analysis revealed that parental delinquency mediated the relationship between mothers' smartphone addiction and their children's problematic technology use. The study's findings were discussed in the context of existing literature, and recommendations were provided.
A new contact and road model for multi-body dynamic simulation of wheeled vehicles on soft-soil terrain
Authors: Koutras Evangelos , Leila Felipe Moretti , Ribaric Adrijan , Natsiavas Sotirios 
Published: November 2023

Abstract
In this paper, a new high-performance and memory-efficient contact and road model is developed. Specifically, the road is modeled as a rectangular structured grid of deformable springs in the vertical direction, thus enabling fast execution. The new road model stands out due to its ability to handle large road scenarios by allocating computer memory dynamically for each spring, resulting in efficient memory utilization. Furthermore, each spring represents a small road patch that entails various information, such as the soil elevation, the soil properties, and the soil compaction, allowing for complicated simulations incorporating spatially varying soil properties as well as phenomena related to the multipass effect. In addition, using the new contact model, complex terrain geometries are handled in a computationally efficient way by approximating locally the irregular road profile with a suitable equivalent plane. For this, two different strategies are proposed. Namely, the Radial Basis Function (RBF) interpolation method and the 3D Enveloping contact model. Finally, the proposed techniques are implemented in Altair MotionSolve, a comprehensive multibody simulation software for complex mechanical systems. In particular, a single-wheel test bed is initially examined, followed by a four-wheeled rover model and the Next-Generation NATO reference mobility model (NG-NRMM). In all cases, the proposed model is validated by using available experimental data. Lastly, a case involving both wheeled and tracked vehicles is also examined by using a shared road model.
Modeling the population health impact of nicotine misperceptions
Authors: Hannel Thad , Wei Lai , Muhammad-Kah Raheema , Largo Edward , Sarkar Mohamadi 
Published: November 2023

Abstract

Background: Scientific evidence clearly demonstrates that inhaling the smoke from the combustion of cigarettes is responsible for most of the harm caused by smoking, and not the nicotine. However, a majority of U.S. adults who smoke (AS) inaccurately believe that nicotine causes cancer which may be a significant barrier, preventing AS from switching to potentially reduced-harm, smoke-free products (SFP) like electronic nicotine delivery systems (ENDS), smokeless tobacco, and snus. We quantify the population health impact associated with nicotine misperceptions.
Methods: Using a previously validated agent-based model to the U.S. population, we analyzed nationally representative data from the Population Assessment of Tobacco and Health (PATH) study to estimate base case rates of sustained (maintained over four waves) cessation and switching to SFP use, by sex. Nicotine perception scenarios used data from Wave 4 of PATH as the baseline wave to analyze levels of nicotine misperceptions. The overall switch rate from smoking in Wave 4 to SFP use in Wave 5 (3.94%) was stratified based on responses to the nicotine perception question “Do you believe nicotine is the chemical that causes most of the cancer caused by smoking cigarettes?”, (Four-item scale from “Definitely not” to “Definitely yes”). The relative percent change between the overall and stratified rates, corresponding to each item, was used to adjust the base case rates of switching to reflect the impact if all AS exhibited switching behaviors based on responses to the nicotine perceptions question. The public health impact of nicotine perceptions was estimated as the difference in all-cause mortality between the base case and the four nicotine perception scenarios.
Results: Switch rates associated with those who responded, “Definitely not” (8.39%) resulted in a net benefit of preventing nearly 800,000 premature deaths over an 85-year period. Conversely switch rates reflective of those who responded, “Definitely yes” (2.59%) resulted in a net harm of nearly 300,000 additional premature deaths over the same period.
Conclusions: Accurate knowledge regarding the role of nicotine is associated with higher switch rates and prevention of premature deaths. Our findings suggest that promoting public education to correct nicotine misperceptions has potential to benefit public health.
GAG-Net: Global Attention-Guided CNN Architecture for Accurate Ship Detection
Authors: Feng Bin , Huang Yuan , Cao Minghua , Lv Zhisheng , Zhang Lingyun , Zhang Yue 
Published: November 2023

Abstract

The YOLOv5 algorithm has gained widespread adoption in maritime target detection due to its impressive speed and accuracy. However, challenges persist in the form of small target leakage and suboptimal multi-target classification performance in complex sea areas during maritime navigation. To address these issues, this paper presents an enhanced convolutional neural network (CNN) named GAG-Net. Specifically, we incorporate a Global Attention Mechanism (GAM) to capture global context information, enabling the model to better discern differences between targets and backgrounds, and thereby significantly improving detection accuracy. Additionally, we introduce the Focal and Efficient IOU (Focal-EIOU) loss for accurate bounding box regression, which focuses more on high-quality samples to improve detection accuracy while accelerating algorithm con-vergence. Finally, we optimize anchor box parameters to better match the shape of vessels and further enhance detection performance. Experimental results demonstrate that our proposal out-performs YOLO series algorithms on the SeaShips dataset in terms of detection accuracy, robustness, and efficiency.