bluuebunny/crossref_metadata_2025_split huggingface dataset:
Preparation of Molybdenum-based carbon nanoparticle for electronic packaging materials
Authors: Xie jiaqiang , chen jin , zhou wenwen , Guo zhifeng 
Published: September 2023

Abstract
This study demonstrated preparation of Mo-Cu-CNTs composites by reflux treatment of carbon nanotubes along with chemical and mechanical activation. We used carbon nanotubes as raw materials and added concentrated sulfuric and nitric acids using the concentrated acid reflux method to activate them. Moreover, we modified the carbon nanotubes by chemical activation method at 100°C. Further, the activated carbon nanotubes and copper molybdenum powder were mechanically activated into mixed powder. Finally, molybdenum-based carbon nanoencapsulation material was prepared by powder metallurgy. Several characterization techniques revealed that the concentrated acid reflux method generated functional groups on the surface, improving the pressing performance and wettability, thereby preventing the occurrence of an interfacial reaction. Furthermore, the composite material of carbon nanotube and molybdenum matrix was realized by the mechanical and chemical activation methods. Thermal conductivity experiments revealed efficient heat transfer of the composite material, and carbon nanotube density variation characteristics showed low density acid treatment after 24 h. The conductivity of the sintered body reached a maximum of 22.4 MS/m, and the thermal conductivity was found to be the highest, reaching 146 Wm− 1K− 1'. The composite material obtained by sintering at 1100°C exhibited the highest Vickers hardness with a value of 214 HV.
Risk factors of retinal hemorrhage among full-term newborns in Anhui Province of China: a retrospective study
Authors: Huang Jin , Wang Lili , Hu Miaomiao , Xu Hong , Li Yingying , Zhang Jinqiu , Mei Zhenzhu , Zhang Rui 
Published: September 2023

Abstract
Background
Neonatal fundus disease lacks typical symptoms, thus early identification and prompt treatment are crucial for preventing visual dysfunction. This study aimed to identify the factors influencing the severity of retinal hemorrhage.
Methods
A total of 507 full-term newborns who underwent fundus disease screening at Suzhou Municipal Hospital from January 2023 to July 2023 were enrolled in this study. All full-term newborns underwent fundus examination using RetCam III shuttle within 7 days of birth, and clinical information on the newborns and their mothers was collected. Univariate and multivariate regression analyses were employed to identify independent risk factors and develop clinical risk nomogram. The risk nomogram was developed using the rms package and evaluated using decision curve analyses.
Results
Among the 507 newborns included in the study, a total of 210 cases exhibited fundus abnormalities. Retinal hemorrhage was identified as the most prevalent fundus abnormality (75.71%), followed by familial exudative vitreoretinopathy (14.76%) and retinopathy of prematurity (3.8%). Univariate and multivariate analysis demonstrated that vaginal delivery (OR = 4.875), binocular hemorrhage (OR = 6.434), and macular involvement (OR = 3.932) as independent risk factors for severe retinal hemorrhage. The C-index of the nomogram model was 0.804, with AUC of the ROC curve at 0.804 (95%CI, 0.733–0.875). The decision curve analysis indicated clinical risk nomogram has application value.
Conclusion
Vaginal delivery, binocular hemorrhage and macular involvement are risk factors for neonatal retinal hemorrhage. The clinical risk model can effectively predict the severity of neonatal retinal hemorrhage.
Identification of the Interaction Domains in the ENO1/Hsp70 Complex, Delve into Novel Potential Therapeutic Target
Authors: Gulotta Maria Rita , Perricone Ugo , Rubino Patrizia , Bonura Angela , Feo Salvatore , Giallongo Agata , Perconti Giovanni 
Published: September 2023

Abstract
Alpha-enolase is a multifunctional protein with oncogenic roles. First described as a glycolytic enzyme the protein performs different functions according to its cellular localization, post-translational modifications, and binding partners. Cell surface-localized alpha-enolase serves as a plasminogen binding receptor and it has been detected in several cell types, including various tumor cells. Plasminogen system plays a crucial role in pathological events such as tumor cell invasion and metastasis. We have previously demonstrated that the interaction of alpha-enolase with the multifunctional chaperone Hsp70 increases its surface localization and the migratory and invasive capacity of breast cancer cells, thus representing a novel potential target to counteract the metastatic potential of tumors. Here we used experimental and computational approaches for the mapping and hot-spot prediction of the interaction domains between alpha-enolase and Hsp70. The molecular definition of this disease-relevant protein-protein interaction will provide the basis for the design of specific inhibitors as potential anti-metastatic agents.
The minimum covariance determinant estimatorfor interval-valued data
Authors: Tian Wan , Qin Zhongfeng 
Published: September 2023

Abstract
Effective estimation of covariance matrices is crucial for statistical analyses andapplications. In this paper, we focus on the robust estimation of the covariancematrix for interval-valued data in low and moderate high dimensions. In the low-dimensional scenario, we extend the Minimum Covariance Determinant (MCD)estimator to interval-valued data. We derive an iterative algorithm for computing this estimator, demonstrate its convergence, and theoretically establish thatit retains the high breakdown-point property of the MCD estimator. Further,we propose a projection-based estimator and a regularization-based estimatorto extend the MCD estimator to moderately high-dimensional settings, respectively. We propose efficient iterative algorithms for solving these two estimatorsand demonstrate their convergence properties. We conduct extensive simulationstudies and real data analysis to validate the finite sample properties of theseproposed estimators.
Mirror Therapy Reduces Pain and Inhibits Reduction of Corticomotor Excitability in Experimental Skeletal Muscle Pain
Authors: Nishi Keita , Okamura Ryohei , Hasegawa Takashi , Matsumoto Shinichi , Xiaoqian Chang , Zongxiang Zhang , Koseki Hironobu , Higashi Toshio , Moriuchi Takefumi 
Published: September 2023

Abstract
Skeletal muscle pain can reduce corticomotor excitability (CE). We examined the effects of mirror therapy (MT), which can increase CE, on skeletal muscle pain. Fifteen healthy adults were injected with hypertonic saline (5.8% NaCl, 0.2 mL) into the first dorsal interosseous muscle (FDI) of the right hand to induce an experimental skeletal muscle pain condition and then divided into pain + MT and pain groups. The pain + MT group observed their left index finger abducting and adducting for 4 min after injection, creating the illusion that they were performing the movement with their right index finger. However, the pain group remained at rest. CE was assessed by measuring motor-evoked potentials (MEPs) of the right FDI through transcranial magnetic stimulation. Pain was assessed using a numerical rating scale (NRS). MEP amplitudes were significantly higher in the pain + MT group; the same trend was observed after MT. NRS scores were significantly lower in the pain + MT group from 60 to 390 s after injection; the time to pain disappearance was also shorter. MT could decrease CE reduction and alleviate skeletal muscle pain. MT may be effective in preventing plastic changes in the neural system associated with skeletal muscle pain and providing early pain relief.
Total Retinal Detachment Combined with a Novel Nonsense Mutation in the COL2A1 Gene: A Case Report
Authors: xu qin , feng Yaling , Xiang Xiaohong , Tang Min , Lv Hongbin 
Published: September 2023

Abstract
Purpose
This study reports a novel nonsense mutation in a family with Stickler syndrome.
Methods
A 20-year-old female patient presented to the Ophthalmology Department of the Affiliated Hospital of Southwest Medical University with a 360° giant retinal tear. In addition to ocular damage (high myopia, cataracts, and retinal detachment), the patient had distinctive facial features, including midface hypoplasia and micrognathia. The patient was diagnosed with Stickler syndrome. Family members were validated using whole-exome and Sanger sequencing.
Results
The family showed autosomal dominant inheritance, with eight members in three generations, six of whom had the disease. The results revealed a nonsense mutation in exon 47 of COL2A1, C.3325C > T, and p.Gln1109Ter. Sanger sequencing confirmed that the mutation at this locus was detected only in patients, and not present in healthy subjects, consistent with family segregation. The patient was subsequently treated with a vitrectomy at our hospital and was discharged after retinal reattachment.
Conclusions
The C.3325C > T locus mutation in COL2A1 is a pathogenic locus mutation in this particular family and is the first such novel nonsense mutation in COL2A1 combined with a 360° giant retinal tear reported in China.
Weight Perception and Its Impact on Health Behaviors among College Students in Hong Kong: A Cross-Sectional Study
Authors: Yeung Joanna Wing Yan , Tsang Mark Cheuk Man , Luk Bronya Hi Kwan , Dang Beatrice Yan Yan 
Published: September 2023

Abstract
Background
Tertiary education is a crucial period during which students develop lifelong habits, including those related to health and wellness. Such students face new stressors and exhibit unhealthy eating behaviors thatmay lead them to become underweight or overweight. Weight misperception is common among young adults but may vary in prevalence by gender and study program. Such misperception may affect a person’s physical and mental health and lead to aggressive weight control behaviors. Therefore, the aim of this study was to examine the factors affecting weight perception and the relationship between weight perception and mental health among college students.
Methods
This cross-sectional study involved 553 students at two higher education institutions in Hong Kong during 2021 and 2022. Students aged 18 or older were eligible for inclusion. The key variables included gender, body mass index (BMI), study program, weight perception, weight control behaviors, and Depression, Anxiety and Stress Scale-21 Items (DASS-21) scores.
Results
The mean age of the participants was 19.6 years; 65.5% of the participants were female; and 53.3% were enrolled in a nursing program. First, stronger agreement between the actual weight and perceived weight was observed in men (Kappa = 0.441) than in women (Kappa = 0.303). Women had a significantly greatertendency to incorrectly perceive themselves as overweight than did men(chi-square test, p < .001). Second, similar levels of agreement were observed in health and non-health students (Kappa = 0.331 and 0.343, respectively),but health students were significantly more likely to perceive themselves as underweight (p = .049). Third, women’s use of weight control behaviors, especially vigorous exercise, walking, and a carbohydrate-based diet, tended to be based on weight perception rather than actual weight, whereas such behaviors were not observed in men. Finally, among students with a normal weight, those who perceived themselves as overweight hadsignificantly higher DASS-21 depression (p =.027), anxiety (p =.001), and stress scores (p =.006) than did their counterparts.
Conclusion
In our sample, an incorrect weight perception was associated with female gender and found to induce unnecessary weight control behaviors and affect mental health among the college students. These findings indicate the need for comprehensive approaches to address weight-related stress and highlight the importance of promoting healthy weight management in future health education programs and policies.
Novel Steganography with Discrete Wavelet Transform for Copyright Protection and Performance Evaluation
Authors: Singh Arun Kumar , Singh Juhi 
Published: September 2023

Abstract

The art and science of hiding information in digital images has become more important in modern times. Currently, a significant amount of one's personal information is openly accessible at a variety of places on the internet in the form of text photographs and video. In this investigation, the data hiding is carried out by altering the coefficients, which is carried out by means of a discrete wavelet transform. Data hiding in frequency domain technique (DFT) offers many advantages as compared to time domain techniques. The scaling factor (SF) is a parameter that influences numerous performance characteristics, such as peak signal-to-noise ratio (PSNR), similarity index, and histogram analysis. The trade-off between SF and PSNR is there and is still relevant in the presence of Gaussian noise, Salt and pepper noise, filtering, and compression.
I/O-signature-based feature analysis and classification of high-performance computing applications
Authors: Park Ju-Won , Huang Xin , Lee Jae-Kook , Hong Taeyoung 
Published: September 2023

Abstract
The demand for high-performance computing (HPC) resources in computing fields such as machine learning has increased significantly in recent years. Computing power has been growing exponentially to keep up with this demand. However, these gains have not been able to translate to performance improvement in real-world applications. One of the biggest reasons for this is performance degradation in terms of input/output (I/O) due to the increased storage latency and complex parallel I/O architecture of accessing data in distributed storage systems. In this study, we analyze application-specific I/O patterns to gain a deeper understanding of I/O throughput and the interaction between applications and the I/O system. Specifically, we analyze the importance of each feature of I/O patterns through feature analysis based on the collected monitoring information. We also investigate the feasibility of identifying the application based on the analyzed key features. To this end, we present the analysis accuracy and confusion matrix of four algorithms, including random forest, which are widely used as classification algorithms in the experimental results. The experiment results confirm that we can distinguish applications with an accuracy of more than 90\% by using application-specific I/O patterns.
Fibrosis quantification using multiphoton excitation imaging of picrosirius red stained cardiac tissue
Authors: Jones Bryce A. , Torrado Belen , Myakala Komuraiah , Wang Xiaoxin X. , Perry Priscilla E. , Rosenberg Avi Z. , Levi Moshe , Ranjit Suman 
Published: September 2023

Abstract

Traditional methodologies for fibrosis quantification involve histological measurements, staining with Masson’s trichrome and picrosirius red (PSR), and label-free imaging using second harmonic generation (SHG). The difficulty of label-free cardiac SHG imaging is that both collagen (i.e., collagen 1 fibrils) and myosin are harmonophores that generate SHG signals, and specific identification of either collagen or myosin is difficult to achieve. Here we present an alternate method of quantifying cardiac fibrosis by using PSR staining followed by multiphoton excitation fluorescence imaging. Our data from the deoxycorticosterone model of cardiac fibrosis shows that this imaging method and downstream analyses, including background correction, are robust and easy to perform. These advantages are due to the high signal-to-noise ratio provided by PSR in areas of collagen fibers. Furthermore, the hyperspectral and fluorescence lifetime information of PSR-stained area of fibrosis shows better quantification can eventually be obtained using more complex instrumentation.
The association between physical activity, self-efficacy, stress self- management and mental health among adolescents
Authors: Zhang Ge , Feng Wanxuan , Zhao Liangyu , Zhao Xiuhan , Li Tuojian 
Published: September 2023

Abstract
This study aimed to explore the interplay between physical activity, self-efficacy, stress self-management and mental health among adolescents. The study gathered data from an online survey conducted among 400 Chinese middle school students (mean age = 13.74 years). The collected data were analyzed using SPSS 27.0 and PROCESS 4.1. The findings indicated a positive and significant relationship between physical activity, self-efficacy, stress self-management, and mental health. Notably, the association between physical activity and mental health was entirely mediated by self-efficacy and stress self-management. Moreover, self-efficacy and stress self-management exhibited a chain mediation effect on the relationship between physical activity and mental health. It is suggested that interventions focusing on physical activity should prioritize strategies for enhancing students' self-efficacy and stress self-management skills as integral components of promoting adolescents' mental health. Future research should delve into identifying specific types of physical activities that have a greater potential to enhance self-efficacy and stress self-management abilities.
Maximum standardized uptake value in 11C-methionine positron emission tomography may predict the prognosis of patients with oral squamous cell carcinoma
Authors: Kuroshima Takeshi , Kitagawa Yoshimasa , Sato Jun , Watanabe Shiro , Asaka Takuya , Abe Takahiro , Harada Hiroyuki , Hirata Kenji , Kuge Yuji 
Published: September 2023

Abstract

Objective: The present study aimed to elucidate the correlation between the uptake of 11C-methionine (MET) by a primary tumor and the survival of patients with oral squamous cell carcinoma (OSCC).
Methods: This study enrolled 31 patients who underwent radical surgery for OSCC. The patients underwent pretreatment MET-positron emission tomography (PET) scanning. We analyzed correlations between the maximum standardized uptake value (SUVmax) of MET-PET in a primary tumor and the clinicopathological features. Further, we compared overall survival (OS), disease-specific survival (DSS), and loco-regional recurrence (LRR) rates between the two groups according to SUVmax of MET-PET.
Results: SUVmax of MET-PET in a primary tumor was higher in patients with advanced T-classification and advanced clinical stage, with significant differences (P = 0.001 and P = 0.016, respectively). The patients with SUVmax of MET-PET ≥4.4 showed significantly lower DSS rates and higher LRR rates than those with SUVmax of <4.4 (P = 0.015 and P = 0.016, respectively). SUVmax of MET-PET and OS rates showed no significant correlation (P = 0.073).
Conclusions: The present study revealed that SUVmax of MET-PET may predict clinical outcomes and prognosis in patients with OSCC who underwent radical surgery.
BAG3 promotes proliferation and migration of arterial smooth muscle cells by regulating STAT3 phosphorylation in diabetic vascular remodeling
Authors: Huang Xinyue , Guo Jiayan , Ning Anqi , Zhang Naijin , Sun Yingxian 
Published: September 2023

Abstract

Diabetic vascular remodeling is the most important pathological basis of diabetic cardiovascular complications. The accumulation of advanced glycation end products (AGEs) caused by elevated blood glucose promotes the proliferation and migration of vascular smooth muscle cells (VSMCs), leading to arterial wall thickening and ultimately vascular remodeling. Therefore, the excessive proliferation and migration of VSMCs is considered as an important therapeutic target for vascular remodeling in diabetes mellitus. However, due to the lack of breakthrough in experiments, there is currently no effective treatment for the excessive proliferation and migration of VSMCs in diabetic patients.
Bcl-2-associated athanogene 3 (BAG3) protein is a multifunctional protein highly expressed in skeletal muscle and myocardium. Previous research has confirmed that BAG3 can not only regulate cell survival and apoptosis, but also affect cell proliferation and migration. Since the excessive proliferation and migration of VSMCs is an important pathogenesis of vascular remodeling in diabetes, the role of BAG3 in the excessive proliferation and migration of VSMCs and its molecular mechanism deserve further investigation.
In this study, BAG3 gene was manipulated in smooth muscle to acquire SM22αCre；BAG3FL/FL mice. Using SM22αCre；BAG3FL/FL mice and human aorta smooth muscle cell line (HASMC), we demonstrated that elevated blood sugar or AGEs could both promote the interaction between BAG3 and STAT3, while BAG3 simultaneously enhanced the interaction between STAT3 and JAK2 and reduced the interaction between STAT3 and ERK1/2, leading to accumulated p-STAT3(705) and decreased p-STAT3(727). Subsequently, the expression of MMP2 is upregulated, thus promoting the migration of VSMCs. In conclusion, our study provides a new orientation for the prevention and treatment of diabetic vascular remodeling.
Analysis of Tightly-Coupled Dipole Phased Array Antennas with Metasurface Superstrate
Authors: Hosseini Seyed Mahdi , Atlasbaf Zahra 
Published: September 2023

Abstract
Tightly coupled dipole arrays, including connected arrays, and capacitively coupled arrays, are one of the best solutions for wideband phased array antenna designs. However, to increase bandwidth and maximum scan angle, we can use a metasurface superstrate. We propose an analytical or semi-analytical model to compute the scan impedance of a tightly coupled dipole array loaded with a metasurface. It is shown that the metasurface superstrate improves the bandwidth and beam scanning angles of the array. Using the proposed general transmission line model, the computation of the scan impedance of tightly coupled dipole arrays is done very fast with minimum error. The semi-analytical model is about 7 times faster than a full-wave simulation.
Data Transformation and Wrapper Impact on Machine Learning Algorithms in Credit Evaluation
Authors: Koc Oguz , Kestel Ayse Sevtap , Ugur Omur 
Published: September 2023

AbstractBanks utilize credit scoring as an important indicator for the financial strength and the eligibility for credit. Scoring models aim to assign statistical odds or probabilities for predicting if there is a risk of nonpayment in relation to many other factors involved. This paper aims to illustrate the beneficial use of the ten machine learning methods (Support Vector Machine, Gaussian Naïve Bayes, Decision Trees, Random Forest, XGBoost, K-Nearest Neighbors, Multi-layer Perceptron Neural Networks, CatBoost, Light Gradient Boosting Machine, and Logistic Regression) in finding the default risk as well as the features contributing to it. An extensive comparison is made in three aspects: (i) which ML models with and without its own wrapper feature selection performs the best; (ii) how appropriate data scaling influences the performance and computational costs; (iii) which of the most successful combination (machine learning method, feature selection and scaling) delivers the best validation indicators such as accuracy rate, sensitivity, and specificity ratio. An open-access credit scoring default risk data sets on German and Australian cases are taken into account for which we determine the best method, scaling and features contributing to default risk. We also illustrate the positive contribution of the feature selection method and scaling on the performance indicators, and a ranking system.