bluuebunny/crossref_metadata_2025_split huggingface dataset:
Automated Enforcement of Vehicle Tail Number Restrictions via SVM and Bayesian Optimization
Authors: Zhu Xuguang , Zou Feifei 
Published: September 2024

Abstract

With urban congestion intensifying, vehicular tail number restriction policies have emerged as an efficacious strategy to mitigate traffic burden. Traditional enforcement, hinging on manual verification, suffers from inefficiencies and vulnerability to human error. Addressing these drawbacks, the present study introduces a Support Vector Machine (SVM)-based license plate recognition technique, augmented by Bayesian optimization, to automate adherence to tail number restrictions. Utilizing the Bayesian optimization algorithm for the fine-tuning of SVM parameters enables the proposed system to identify license plate numbers with heightened precision and swiftness, thus streamlining the enforcement process. Comparative experimental analysis substantiates that our proposed model outperforms existing methods, demonstrating superior recognition efficiency and accuracy. This advancement heralds a significant leap towards the integration of intelligent systems in urban traffic management.
Hybrid PCOS net: A synergistic CNN-LSTM approach for accurate polycysti covary syndrome detection
Authors: Kumar Neha A. Ranjith , Varadarajan Vijayakumar 
Published: September 2024

Abstract

PCOS, a common hormonal disorder in women of reproductive age, manifests with symptoms like irregular periods, ovarian cysts, and hormonal imbalances. Early diagnosis and intervention for PCOS are vital due to its link with metabolic and cardiovascular complications. It is essential for enhancing overall well-being and mitigating risks like infertility and metabolic issues. This paper is centered on the development of two distinct predictive models for PCOS detection, utilizing both image and text datasets. Ensemble learning methods like logistic regression, random forest, and support vector machines are employed to capitalize on the strengths of each dataset. The resultant combined model demonstrates an impressive accuracy of 89% and an area under the curve (AUC) score of 0.83. Additionally, the investigation explores advanced deep learning techniques by integrating Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks to provide features for a Fully Connected Neural Network (FCNN). This innovative approach yields exceptional results, achieving an accuracy of 96.07% with minimal loss.
Landslide hazard assessment of an urban agglomeration in central Guizhou Province based on an information value method and machine learning algorithm
Authors: Junhua Luo , Zulun Zhao , Wei Li , Liang Huang , Weiquan Zhao 
Published: September 2024

Abstract

The urban agglomeration in central Guizhou is located in a crustal deformation area caused by tectonic uplift between the Mesozoic orogenic belt of East Asia and the Alpine-Tethys Cenozoic orogenic belt, with high mountains, steep slopes, fractured rock masses and a fragile ecological environment; this area is the most affected by landslides in Guizhou Province, China. From 2011 to 2023, there were a total of 648 medium and large landslide disasters, resulting in 143 deaths and a direct economic loss of 1.191 billion yuan. Therefore, this study selected 12 indicators from the topography, geological structure, and external inducing factors, and conducted factor collinearity analysis using the variance expansion coefficient to construct a landslide hazard assessment index system. The statistical analysis model was combined with a variety of machine learning models, and the selection of negative sample points was restricted in various ways to improve training data accuracy and enable machine learning model predictions with sufficiently supervised prerequisites. The accuracy of the model was validated by ROC curve analysis. The AUC values of the SVM, DNN, and bagging models were all greater than 0.85, indicating that the results were credible. However, the overall accuracy was SVM > DNN > Bagging; that is, SVM was more suitable for landslide hazard assessment of the urban agglomeration in central Guizhou. Finally, field surveys were used to validate multiple sites with historical landslides in extremely high-hazard areas and analyse their development characteristics. The evaluation results can provide strong guidance for engineering design, construction and disaster prevention decision-making of urban agglomeration in central Guizhou.
Does the Serial Discontinuity Concept apply to microcrustaceans in the presence of a large reservoir along a tropical river?
Authors: Keppe Isabela de Lima , Pralon Bruno Gabriel Nunes , Silva Camila Moreira , Carvalho Vinícius Vilela , Neves Gilmar Perbiche 
Published: September 2024

Abstract

We aimed to assess the impact of damming on the abundance, diversity and dissimilarity of microcrustaceans (Cladocera and Copepoda) along a large tropical river, in the context of the Serial Discontinuity Concept (SDC) and the River Continuum Concept (RCC). Over a two-year period, samples were collected bimonthly at six sites along a 750 km longitudinal gradient, and ten limnological variables were measured to understand their influence on the organisms. The results revealed spatial and temporal variations in limnological variables, as well as differences in microcrustacean abundance between upstream and downstream sites, with an increase observed downstream as in RCC. Some abundant species were oppositely separated according to spatial and seasonal gradients, and the influence of pluviosity, ammonia, temperature, pH, and alkalinity. The presence of a single large reservoir was found to influence the diversity and abundance of microcrustaceans downstream, supporting the SDC's predictions. The findings contribute to a better understanding of the impact of damming on river ecosystems and the downstream transport of organisms, as well as valuable insights for the ecological restoration of dammed rivers.
Hydrogen Diffusion in Magnesium Using Machine Learning Potentials
Authors: Angeletti Andrea , Leoni Luca , Massa Dario , Pasquini Luca , Papanikolaou Stefanos , Franchini Cesare 
Published: September 2024

Abstract

Understanding and accurately predicting hydrogen diffusion in materials is challenging due to the complex interactions between hydrogen defects and the crystal lattice. These interactions span large length and time scales, making them difficult to address with standard ab initio techniques. This work addresses this challenge by employing accelerated machine learning (ML) molecular dynamics simulations through active learning. We conduct a comparative study of different ML-based interatomic potential schemes, including VASP, MACE, and CHGNet, utilizing various training strategies such as on-the-fly learning, pre-trained universal models, and fine-tuning. We obtain an optimal hydrogen diffusion coefficient value of 2.1 x 10-8 m2s-1 at 673 K in MgH0.06, which aligns exceptionally well with experimental results, underlining the efficacy and accuracy of ML-assisted methodologies in the context of diffusive dynamics. Particularly, our procedure significantly reduces the computational effort associated with traditional transition state calculations or ad-hoc designed interatomic potentials. The results highlight the limitations of pre-trained universal solutions for defective materials and how they can be improved by fine-tuning. Specifically, fine-tuning the models on a database produced during on-the-fly training of VASP ML force field allows the retrieving of DFT-level accuracy at a fraction of the computational cost.
Impact of tumor size and peritumoral edema on outcomes and complications in anterior midline skull base meningiomas
Authors: Qasem Lina-Elisabeth , Al-Hilou Ali , Oros Jan , Weber Katharina J. , Jussen Daniel , Prinz Vincent , Seifert Volker , Baumgarten Peter , Marquardt Gerhard , Czabanka Marcus 
Published: September 2024

Abstract

This study aims to describe the impact of tumor size and peritumoral edema in anterior midline skull base meningiomas on clinical outcome. Patients with these meningiomas undergoing resection between 2012 and 2022 were included. Meningiomas were divided into three groups by size and edema. The primary outcome was the Karnofsky Performance Scale (KPS) score at three months post-surgery. Preoperative KPS, KPS at discharge, KPS at last follow-up and complication rates were analyzed. Outcomes for large meningiomas (> 50 mm) were significantly worse at discharge (KPS 50%) compared to medium-sized (30–50 mm; KPS 70%) and small tumors (< 30 mm; KPS 80%; p < 0.0001). KPS at three months showed persisting significant differences: small (KPS 90%), medium-sized (KPS 85%), and large tumors (KPS 80%; p = 0.0209). KPS at discharge in large tumors was significantly dependent on edema: KPS 90% in large tumors without edema, KPS 70% with moderate edema, and KPS 50% with extensive edema (p = 0.0008). Complication rate was 28%, with 14% for small, and 35–37% for medium-sized and large meningiomas (p = 0.0613). Complication rate was higher in tumors with peritumoral edema (35%) compared to tumors without edema (23%; p = 0.2051). The outcome and complication rates suggest higher surgical risk for larger tumors with marked peritumoral edema. Surgical strategies may need to adapt to these risk factors.
Preoperative cardiac abnormalities associated with one-year mortality in elderly patients undergoing hip fracture surgery: The role of focused TTE
Authors: Fan Kaihua , Zhang Jianwei , Gao Ying , Li Weimei 
Published: September 2024

Abstract

Purpose
We sought to identify preoperative cardiac abnormalities associated with postoperative mortality in elderly patients undergoing hip fractures surgery, in order to provide reference for focused transthoracic echocardiography (TTE).
Methods
In this retrospective study, a total of 669 elderly patients (age over 65 years) undergoing hip fractures surgery were included, of which 58(8.7%) died within one-year after discharge. Cox regression analysis models were used to identify the prognostic cardiac abnormalities of postoperative mortality.
Results
Univariate analysis showed that age (HR 1.065, 95%CI 1.030–1.101; P < 0.001), ASA score (III, IV vs. I, II) (HR 1.855, 95%CI 1.098–3.067; P = 0.022), history of chronic obstructive pulmonary disease (COPD)(HR 4.446, 95%CI 1.909–10.355; P = 0.001) and atrial fibrillation (AF)(HR 3.803, 95%CI 1.803–8.024; P < 0.001), presence of left ventricular ejection fraction (LVEF) < 50%(HR 5.009, 95%CI 2.151–11.665; P < 0.001), left ventricular dilatation (HR 3.813, 95%CI 1.730–8.403; P = 0.001), pulmonary arterial systolic pressure (PASP) > 25mmHg(HR 4.388, 95%CI 2.492–7.725; P < 0.001), moderate-severe aortic valve stenosis (AS) (HR 4.702, 95%CI 1.471–15.035; P = 0.009) were the dominant predictors of mortality within one-year. The presence of LVEF < 50%, left ventricular dilatation and elevated PASP were proved to be the independent predictors of one-year mortality in elderly patients in multivariate analysis.
Conclusion
Cardiac abnormalities derived from preoperative TTE, namely LVEF < 50%, AS, left ventricular dilatation and elevated PASP had prognostic value for elderly patients undergoing hip fracture surgery. We consider that these indices would be clinically important regarding the preoperative cardiac risk assessment of elderly hip fracture patients who are treated with surgery, which may be assessed in the focused TTE.
EGF/APOC1/CPT1A Axis: A Novel Pathway in Gastric Cancer Metabolism and Therapeutic Targeting
Authors: Du Feng , Li Peng , Chen Guangyong , Ji Xu , Yang Shuyue , Su Jiayi , Liu Sifan , Zhao Zheng , Zhou Anni , Zhao Guiping , Zhang Zheng , ZHU SHENGTAO , ZHANG Shutian , Wu Jing 
Published: September 2024

Abstract

Gastric cancer (GC) relies heavily on the reprogramming of lipid metabolism for energy, growth, and survival. Apolipoprotein C-I (APOC1) is implicated in the reprogramming of lipid metabolic processes in GC, yet the precise molecular mechanisms underlying this association remain incompletely understood. In this study, we identified APOC1 as a key player in GC metabolism and progression. Our findings show that APOC1 is upregulated in GC tissues and cells compared with controls and is correlated with poor prognosis. Furthermore, the overexpression of APOC1 promoted proliferation and migration, whereas the silencing of APOC1 led to decreased tumor growth and metastasis. Moreover, APOC1 was found to augment fatty acid oxidation (FAO) through its interaction with and regulation of carnitine palmitoyltransferase 1A (CPT1A). Disruption of APOC1 resulted in metabolic dysregulation, leading to mitochondrial oxidative stress. Conversely, the upregulation of APOC1 in GC cells promoted the catabolism of long-chain fatty acids, thereby facilitating tumor growth and migration. Mechanistically, APOC1 was shown to be regulated by epidermal growth factor (EGF), and its expression was directly targeted at the transcriptional level by AP-2α binding to its promoter region. Our research reveals a novel association between APOC1 and lipid metabolism, highlighting the EGF/APOC1/CPT1A axis as crucial factors in the progression of GC and potential targets for therapeutic interventions.
A rare young case of Embryonic rhabdomyosarcoma of the prostate with multiple metastases throughout the body: A case report
Authors: Wang Kai , Ou Yong , Jia Ting-yu , Zheng Zhong , Wang Hua-kang , Chen Ming-xian , Yang Hua , Huang Hua-song , Chen Hou-chuan , Chen Zhi-gang 
Published: September 2024

Abstract

Prostate cancer is the second most commonly diagnosed cancer and the sixth leading cause of cancer death among men worldwide, with an estimated 1 276 000 new cancer cases and 359 000 deaths in 2018[1]. The median age at diagnosis is 66 year, and 69% of deaths occur in men aged 75 yr[2]. As the morbidity and mortality rates rise sharply with age, the burden of prostate cancer will increase with the exponential aging of the population. The pathological type of prostate cancer is mainly adenocarcinoma (98.1%), and other types are relatively rare. Other pathological types of prostate cancer include iprostate duct (endometrioid) ademocarcinoma, small cell carcinoma, smucinous adenocarcinoma, signet ring cell carcinoma, transitional cell carcinoma, Sarcomatoid carcinoma, squamous cell carcinoma, lymphoepithelioid carcinoma, adenoid cystic carcinoma, etc. Rhabdomyosarcoma (RMS) is a soft tissue sarcoma that histologically resembles embryonic skeletal muscle. It can occur anywhere in the body, including tissues devoid of skeletal muscles. The cell of origin of RMS remains unknown, however, recent evidence suggests that RMS can originate from aberrant development of non-myogenic cells [3]. Rhabdomyosarcoma is a common malignant tumor in children. In fact, it accounts for more than 50% of all soft tissue sarcomas in children [4]. However, rhabdomyosarcoma is a rare adult malignant tumor, and it accounts for only 3% of all soft tissue sarcomas [5]. Rhabdomyosarcoma is very rare in prostate tumors.
Trends in levels of organochlorine pesticide residues in breast milk; a case study in Aragatsotn Province, Armenia
Authors: Tadevosyan Natalya S. , Mikulski Marek A. , Tadevosyan Artashes E. 
Published: September 2024

Abstract

The Stockholm Convention on persistent organic pollutants (2001). banned a number of organochlorine pesticides (OCPs) which are persistent and still detected in human milk. Levels of OCPs in breast milk were assessed to understand the trends over time in Armenia. Breast milk samples (N = 627) were collected from randomly selected mothers in Aragatsotn Province of Armenia between 1993 and 2012. OCPs: gamma-hexachlorocyclohexane (γ-HCH), dichlorodiphenyltrichloroethane (DDT), dichlorodiphenyldichloroethylene (DDE) and dichlorodiphenyldichloroethane (DDD) were determined by gas-liquid chromatography with electron capture detector and expressed as µg/L of whole milk. The results were compared for two periods: before the adoption of new legal framework on pesticides management (1993–2002) and after its establishment (2003–2012). Concentrations of individual OCPs and total sums of DDT and OCPs for 1993–2012 decreased over time. In the first period concentrations of DDE were up to 24 times higher than that of γ-HCH, but in the second γ-HCH reached equal or higher levels. In the second period the simultaneous presence of four OCPs increased sharply up to 89%. A significant decrease was observed for DDE, as well as for both total sum of DDT and OCPs in the second period, mainly due to decrease of DDE. At the same time, the mean levels γ-HCH did not differ between the two periods. The detection of OCPs residues indicates their continued circulation in the environment and suggests possible ongoing agricultural use of banned pesticides. Educational campaigns are needed to improve current practice of pesticide application in Armenia.
High expression of transcription factor EGR1 is associated with postoperative muscle atrophy in patients with knee osteoarthritis undergoing total knee arthroplasty
Authors: Liu Xiao-yang , Yu Qiu-ping , Guo Si-qin , Chen Xu-ming , Zeng Wei-Nan , Zhou Zong-ke 
Published: September 2024

Abstract

Background: Muscle atrophy is a typical affliction in patients affected by knee Osteoarthritis (KOA). This study aimed to examine the potential pathogenesis and biomarkers that coalesce to induce muscle atrophy, primarily through the utilization of bioinformatics analysis.
Methods: Two distinct public datasets of osteoarthritis and muscle atrophy (GSE82107 and GSE205431) were subjected to differential gene expression analysis and gene set enrichment analysis (GSEA) to probe for common differentially expressed genes (DEGs) and conduct transcription factor (TF) enrichment analysis from such genes. Venn diagrams were used to identify the target TF, followed by the construction of a protein-protein interaction (PPI) network of the common DEGs governed by the target TF. Hub genes were determined through the CytoHubba plug-in whilst their biological functions were assessed using GSEA analysis in the GTEx database. To validate the study, reverse transcriptase real-time quantitative polymerase chain reaction (qRT-PCR), enzyme-linked immunosorbent assay (ELISA), and Flow Cytometry techniques were employed.
Results: A total of 138 common DEGs of osteoarthritis and muscle atrophy were identified, with 16 TFs exhibiting notable expression patterns in both datasets. Venn diagram analysis identified early growth response gene-1 (EGR1) as the target TF, enriched in critical pathways such as epithelial mesenchymal transition, tumor necrosis factor-alpha signaling NF-κB, and inflammatory response. PPI analysis revealed five hub genes, including EGR1, FOS, FOSB, KLF2, and JUNB. The reliability of EGR1 was confirmed by validation testing, corroborating bioinformatics analysis trends.
Conclusions: EGR1, FOS, FOSB, KLF2, and JUNB are intricately involved in muscle atrophy development. High EGR1 expression directly regulated these hub genes, significantly influencing postoperative muscle atrophy progression in KOA patients.
Visual Image Encryption Based on Logistic-Sine Chaotic Maps
Authors: Sun shiji , Yang Wenzhong , Yin Yabo , Tian Xiaodan , Li Guanghan , Deng Xiangxin 
Published: September 2024

Abstract

The development of 5G technology has produced a huge amount of visual image data, and the protection of visual image data is becoming more and more important. Many researchers use chaotic encryption to encrypt images, but the methods used are too simplistic, and some works only use one single layer of encryption, which may not be able to protect the privacy of the image well. In this paper, we propose a multi-layer encryption method for image encryption protection. Firstly, we extract the R, G, and B channels of the original image. The channels are then transformed in rows and columns. Finally, the chaotic model combining logistic and sine map in this paper is used. The chaotic encryption is performed with the XOR of the image and finally the image is encrypted by the method of cellular automata encryption. The results of several experiments show that the logistic-sine chaotic model has excellent chaotic characteristics. The algorithm shows high security and anti-attack ability.
A Study on the Relationship between Social Support Model and Depression in the Elderly
Authors: Li Ya Lin , Li Lu Yan , Yin Qin 
Published: September 2024

Abstract

Objective
To analyze the relationship between social support patterns and depression in the elderly, and to provide reference for improving the social support system and improving the mental health of the elderly.
Methods
Based on social support theory, the latent category model was used to explore the relationship between social support patterns and depression among Chinese older adults. Results: The social support patterns of the elderly can be categorized into Comprehensive support provided by the offspring, Comprehensive support provided by the spouse, multiple support, and intergenerational emotional detachment; the tendency of depression in the elderly is most closely related to offspring support, and the Chinese traditional concept of "raising children to prevent old age" is no longer sufficient to defend against the tendency of depression in the elderly;Compared with the multiple support model, the elderly who relied on their children’s support in the three aspects of economy, care, and emotion, and the elderly whose children only provided instrumental support but not emotional support had a more significant tendency to be depressed.
Conclusion
The construction of a multiple social support model for the elderly should be realized as soon as possible; the strength of formal support for the elderly should be enhanced in terms of economic support; the main body of life care support for the elderly should be enriched, and the mental harm to the elderly, especially the female elderly, should be guarded against when their children only provide instrumental support instead of emotional support.