bluuebunny/crossref_metadata_2025_split huggingface dataset:
Potential of 20th Century North Anatolian Fault Style Domino Effect of the February 6, 2023, Kahramanmaraş Earthquake on the Centuries Long Dead Sea Fault Seismic Quiescence.
Authors: Altunel Erhan , Kozacı Özgür , Yıldırım Cengiz , Sbeinati Reda , Meghraoui Mustapha 
Published: May 2024

Abstract

Field observations conducted immediately following the February 6, 2023, M 7.8 Kahramanmaraş Earthquake documented the southern surface rupture termination in the Amik Basin. The termination occurred in an en-echelon pattern, stretching across the 3.5 km width of the approximately 10.5-kilometer-wide stepover. This extension reached towards the northern tip of the Hacıpaşa Fault, which constitutes the main northern segment of the Dead Sea Fault Zone (DSFZ). Archaeological and paleoseismologic data show that the approximate 800-kilometre-long DSFZ has been seismically quiet for more than 600 years in the north and 900 years in the south. A similar fault connection geometry at the western end of the 1939 Ms 7.9 Erzincan earthquake in the easternmost part of the North Anatolian Fault Zone and the subsequently triggered successive large magnitude earthquakes migrating westward within a few decades highlights an increased seismic hazard for the entire DSFZ. This heightened seismic hazard potential along the DSFZ, combined with historical population centers experiencing wars and migrations, puts millions of people at an unparalleled risk.
Machine Learning for COVID-19 Patient Management: Predictive Analytics and Decision Support
Authors: Hadi Christopher El , Saliba Rindala , Maalouly Georges , Riachy Moussa , Sleilaty Ghassan 
Published: May 2024

Abstract

Background. The global impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has profoundly affected economies and healthcare systems around the world, including Lebanon. While numerous meta-analyses have explored the systemic manifestations of COVID-19, few have linked them to patient history. Our study aims to fill this gap by using cluster analysis to identify distinct clinical patterns among patients, which could aid prognosis and guide tailored treatments.
Methods.We conducted a retrospective cohort study at Beirut's largest teaching hospital on 556 patients with SARS-CoV-2. We performed cluster analyses using K-prototypes, KAMILA and LCM algorithms based on 26 variables, including laboratory results, demographics and imaging findings. Silhouette scores, concordance index and signature variables helped determine the optimal number of clusters. Subsequent comparisons and regression analyses assessed survival rates and treatment efficacy according to clusters.
Results. Our analysis revealed three distinct clusters: "resilient recoverees" with varying disease severity and low mortality rates, "vulnerable veterans" with severe disease and high mortality rates, and "paradoxical patients" with a late severe presentation but eventual recovery.
Conclusions. These clusters offer insights for prognosis and treatment selection. Future studies should include vaccination data and various COVID-19 strains for a comprehensive understanding of the disease's dynamics.
Esculentin-2CHa (GA30) mitigates copper-induced redox imbalance and behavioural deficit in Drosophila melanogaster
Authors: Udochukwu Onyedika L. , Oyibo Aghogho , Falobi Ayodele A. , Abolaji Amos O. , Ojo Opeolu O. 
Published: May 2024

Abstract

Excess copper ion (Cu2+) has been implicated in various pathological conditions involving oxidative stress and inflammation. This study investigated neuroprotective effects of esculentin-2CHa-(GA30) on copper-induced toxicity in Drosophila melanogaster. Flies were treated with esculentin-2CHa (5.0 and 7.5 µM/kg diet) and/or Cu2+ (1mM) orally for 5 days. Effects of esculetin-2CHa-(GA30) on markers of redox-antioxidant status and neuro-behavioural activities were assessed. Esculetin-2CHa-(GA30) did not affect survival rate but reversed the effect of copper on eclosion rate. Esculetin-2CHa-(GA30) dose-dependently mitigated Cu2+-induced elevation of hydrogen peroxide (15.1–15.8%, P < 0.05), thiobarbituric reactive substance (37.2–55.1%, P < 0.01–0.001) and protein carbonyl (20.7–63.8%, P < 0.05–0.001). Esculetin-2CHa-(GA30) ameliorated Cu2+-induced inhibition of catalase (1.5–1.7-fold, P < 0.01–0.001), glutathione S-transferase activities (1.5–2.1-fold, P < 0.01–0.001) and decline in non-protein thiols levels (13.6–27.7%, P < 0.05). Esculetin-2CHa-(GA30) reduced Cu2+−induced elevation of monoamine oxidase (21.7–39.7%, P < 0.05–0.01) and acetylcholinesterase (40.1–55.9%, P < 0.01–0.001) activities. Copper-induced impaired locomotor activities were dose-dependently improved in esculentin-2CH-(GA30)-treated flies (21.4%, P < 0.05 and 72.1%, P < 0.01). Histological assessments indicated the ability of esculentin-2CHa-(GA30) to sequester Cu2+ in the microglia. In conclusion, esculentin-2CHa-(GA30) exhibited its neuroprotective effects through improved balance of redox status and associated behavioural characteristics. Further studies to delineate molecular mechanisms underlying observed effects would be required.
PPAR agonists in Primary Biliary Cholangitis: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Authors: Faria Hilária Saugo , Sobral Milene Vitória Sampaio , Soares Victor Gonçalves , Cavalheiro Thainá Torres , Nishimoto Beatriz , Pirolla Rafaela Cunha , Sampaio Ana Paula , Gonçalves Ocílio Ribeiro , Costa Daniela Gomez , Souto Eduardo Buzatti 
Published: May 2024

Abstract

Introduction
Agonists of the peroxisome proliferator-activated receptor (PPAR) have attracted attention for their potential to treat primary biliary cholangitis (PBC). However, individual trials lack sufficient power to detect significant differences in clinical and laboratory outcomes.
Objectives
This meta-analysis aims to compare PPAR agonists versus placebo or standard treatment in patients with PBC.
Methods
We systematically searched PubMed, Embase and Cochrane for studies comparing PPAR agonists with placebo or standard-of-care treatment in PBC. The primary outcomes were pruritus, alkaline phosphatase (ALP), gamma-glutamyl transferase (GGT), and total and direct bilirubin levels. We performed statistical analyses using R 4.1.1. Heterogeneity was examined with the Cochran Q test and I2 statistics. We computed risk ratios (RR), mean differences (MD), and Standardized Mean Differences (SMD), with 95% confidence intervals (CI), using a random-effects model.
Results
Thirteen randomized controlled trials were included in this meta-analysis, comprising 1,124 patients, of whom 687 (57%) received PPAR agonists plus UDCA. When compared with control, PPAR analogs were significantly associated with a reduction in pruritus (RR 0.63; 95% CI 0.41 to 0.96; p = 0.031; I²=9%), ALP (MD -130.93; 95% CI -156.44 to -105.42; p < 0.01; I²=84%), GGT (MD -39.83; 95% CI -78.44 to -1.22; p = 0.04; I²=94%) and total bilirubin levels (SMD − 0.03; 95% CI -0.06 to -0.01; p < 0.01; I²=69%).
Conclusion
The use of PPAR agonists reduced the incidence of pruritus and the levels of ALP, GGT, and total bilirubin in patients with PBC.
The WWI and the risk of chronic kidney disease: A national prospective cohort study
Authors: Xie Juan , Dou Haijing , Wang Hongmei , Sun Xuan , Lei Yi , Bai Lin , Liu Jun , Li Hailun , Xu Yong , Li Xiang , Zheng Donghui 
Published: May 2024

Abstract

Objective: The weight-adjusted waist circumference index (WWI) is a more robust indicator of visceral obesity than body mass index (BMI). Cross-sectional studies have demonstrated an association between the WWI and an increased incidence of chronic kidney disease (CKD). However, longitudinal evidence to support this relationship is neither conclusive nor sufficient. This study aimed to prospectively evaluate the relationship between the WWI and CKD.
Methods: This was a prospective cohort study of 10200 community residents aged ≥ 45 years without CKD who were recruited from the Chinese Healthand Longevity Longitudinal Study (CHARLS) and who were followed for up to 8.0 years. Both men and women were categorized into four groups based on the sex-specific quartile of the WWI at the time of inclusion in the trial. CKD was based on self-reported physiciandiagnoses. The relationship between the WWI and CKD occurrence was analyzed through log-rank tests and survival curves before using nonrestricted cubic splines. Finally, we performed a sensitivity analysis to check the robustness of our findings.
Results: In total, 4809 men and 5391 women were included in the trial, with an average age of 67.43 ± 9.55 years. A total of 723 patients were diagnosed with CKD during the 8-year follow-up period. The prevalence of CKD in each group was 5.86%, 4.89%, 6.16%, and 6.83%, respectively, in the female subgroup. After adjusting for covariates, the hazard ratio (HR) (95% CI) in the lowest quartile was 1.56 (1.04 - 2.34), that in the third quartile was 1.59 (1.08 - 2.34), and that in the highest quartile was 1.53 (1.01 - 2.31) compared to that in the second quartile. However, in the male subgroup, the prevalence of CKD in each group was 8.80%, 8.51%, 7.85%, and 8.37%, respectively. After adjusting for various variables, the incidence of CKD did not significantly differ among the groups (P>0.05).
Conclusion: In summary, this study showed that the WWI is significantly linked to the risk of CKD in women, even after adjusting for covariates. This finding underscores the important role of weight management in the prevention and treatment of CKD among the female population. Thus, the adoption of measures to control central obesity among the female population is essential for preventing CKD.
Monitoring and early warning of ovarian cancer using high-dimensional non-parametric EWMA control chart based on sliding window
Authors: Wu Bin , Zhong Wen , Ren Yixing , Zhou Zhongli , Liu Liu 
Published: May 2024

Abstract

Ovarian tumors are one of the common ovarian dysfunctions in women, which to some extent affect women's normal work and life. Although ovarian tumors are usually sensitive to chemotherapy, and typically show initial efficacy with platinum/taxane treatment, the postoperative recurrence rate in advanced patients is very high. There have been a considerable number of researchers working to establish new methods to monitor and warn about the progression and prognosis of this malignant tumor disease. One commonly used approach is to first reduce the dimensionality of the data using methods such as principal component analysis, LASSO, deep learning, etc., to select several features most relevant to malignant tumors. Then, either a one-dimensional control chart is used for multiple monitoring and warning of different indicators, or a multivariate control chart is directly used to monitor and warn about the selected indicators. However, in actual data, different features are not completely independent of each other. Using a one-dimensional control chart for multiple monitoring and warning of different indicators may overlook the interactions between different features. Additionally, reducing the dimensionality of the data may result in the loss of some data information, leading to the omission of details, which may affect the accuracy of the model and result in delayed alarms and poor predictive performance. Therefore, this paper proposes a non-parametric monitoring scheme based on high-dimensional empirical likelihood test and sliding window model of EWMA type, for direct online monitoring and warning of high-dimensional ovarian tumor data. We compared this approach with a multivariate EWMA control chart after dimensionality reduction, and Monte Carlo numerical simulation results showed that the high-dimensional non-parametric EWMA monitoring scheme indeed detects tumor data changes faster and issues alarms more promptly than the dimensionality-reduced multivariate EWMA control chart. Furthermore, we further validated the effectiveness of the high-dimensional non-parametric EWMA monitoring scheme in monitoring and warning using tumor resection data from the Third Affiliated Hospital of Soochow University as an example.
Speaker identification using hybrid subspace, deep learning and machine learning classifiers
Authors: KESER Serkan , GEZER Esra 
Published: May 2024

Abstract

Speaker identification is crucial in many application areas, such as automation, security, and user experience. This study examines the use of traditional classification algorithms and hybrid algorithms, as well as newly developed subspace classifiers, in the field of speaker identification. In the study, six different feature structures were tested for the various classifier algorithms. Stacked Features-Common Vector Approach (SF-CVA) and Hybrid CVA-FLDA (HCF) subspace classifiers are used for the first time in the literature for speaker identification. In addition, CVA is evaluated for the first time for speaker recognition using hybrid deep learning algorithms. This paper is also aimed at increasing accuracy rates with different hybrid algorithms. The study includes Recurrent Neural Network-Long Short-Term Memory (RNN-LSTM), i-vector + PLDA, Time Delayed Neural Network (TDNN), AutoEncoder + Softmax (AE + Softmaxx), K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Common Vector Approach (CVA), SF-CVA, HCF, and Alexnet classifiers for speaker identification. The six different feature extraction approaches consist of Mel Frequency Cepstral Coefficients (MFCC) + Pitch, Gammatone Cepstral Coefficients (GTCC) + Pitch, MFCC + GTCC + Pitch + eight spectral features, spectrograms,i-vectors, and Alexnet feature vectors. For SF-CVA, 100% accuracy was achieved in most tests by combining the training and test feature vectors of the speakers separately. RNN-LSTM, i-vector + KNN, AE + softmax, TDNN, and i-vector + HCF classifiers gave the highest accuracy rates in the tests performed without combining training and test feature vectors.
Ranking Failure Modes with Pythagorean Fuzzy Rough VIKOR: A Case Study in Automatic Washing Machines
Authors: Shahzadi Sundas , Chohan Maryum , Zafar Fariha 
Published: May 2024

Abstract

Failure mode and effects analysis (FMEA) is known for its remarkable and exceptional ability to recognize , evaluate, and remove possible failure modes in various industrial applications. It offers a broad point of view for scrutinizing possible failures, their roots, and their consequences in processes, manufactured articles, and designs. The conventional FMEA method has faced significant criticism due to its difficulties in accurately determining the weight of risk factors, recognizing the priority of failure modes, and handling vagueness during risk assessment. A new linguistic assessment model called Pythagorean fuzzy rough VIKOR is introduced to address these shortcomings. This model utilizes a combination of Pythagorean fuzzy numbers and rough information to improve the accuracy and effectiveness of risk assessment. We also apply the suggested VIKOR method to identify the less or more severe problems. Before applying the VIKOR method, we find criteria weights using the Pythagorean fuzzy rough entropy method. The importance of our proposed method has been discussed in the case study of an automatic washing machine. Different comparison studies show that the Pythagorean fuzzy rough method effectively addresses subjectivity and uncertainty when evaluating failure modes. This paper provides evidence to support using the Pythagorean fuzzy rough VIKOR (PFR-VIKOR) technique for ranking failure modes. This approach has demonstrated exceptional benefits in dealing with subjective and uncertain factors during the evaluation process.
Population genetic structure of Yesso scallop (Mizuhopecten yessoensis) of Russian Far East revealed by mitochondrial and microsatellite genetic markers
Authors: Khamatova Aleksandra , Malyar Vasily , Yagodina Viktoriia , Bondar Evgeniia 
Published: May 2024

Abstract

Yesso scallop (Mizuhopecten yessoensis) is one of the main marine aquaculture species of the Russian Far East. However, the population size of this species is declining due to overfishing and habitat loss. As the population genetic structure of the scallop from Russia is poorly studied, we analyzed polymorphism of the noncoding region mitochondrial DNA (NcR2) and seven microsatellite loci. Genetic diversity and structure of M. yessoensis populations from four geographical areas of the Sea of Japan and the Sea of Okhotsk were revealed. A total of 24 haplotypes with the one main observed in all studded populations were identified. All populations had high genetic diversity with mean expected heterozygosity from 0.612 to 0.687 and haplotype diversity from 0.619 to 0.793, except for the northern sample from the Terpeniya Gulf (h = 0.47). Small but statistically significant genetic differentiation was observed between the southern population from the Posyet Gulf (Sea of Japan) and populations from the Terpeniya Gulf and Busse Lagoon (Sea of Okhotsk). Despite the high genetic variation between populations, low differentiation, and weak geographical separation was observed that suggest Yesso scallop forms the Sea of Japan and the Sea of Okhotsk to be one panmictic population. Our results could provide useful information for resource management and genetic monitoring of the economically and ecologically important species of marine bivalves.
How social support affects depression in college students: a moderated mediating effect
Authors: Zhang Junliang , Wan Chuangang , Zheng Shuang , Shen Ruiqing 
Published: May 2024

Abstract

Objective
To investigate how rumination influences the relationship between depression among college students and social support, and to test the moderating effect of gender differences on this basis.
Methods
A questionnaire survey was conducted using random cluster sampling method to select college students from several colleges and universities in Jiangxi and Zhejiang regions, and SPSS 26.0 was used for regression analysis and PROCESS plug-in for the construction of a moderated mediation model.
Results
Rumination partially mediated the association between social support and depression (indirect impact β = 0.68, P < 0.01);Social support adversely predicted depression in college students (β=-0.40, P < 0.001); and gender moderated the direct pathway of social support on college students' depression.Compared to male college students, female students were more likely to experience depression if they had lower amounts of social support.
Conclusion
Social support influenced college students' depression through the mediation of rumination thinking and the moderation of gender.
A Text Classification Method by Integrating Mobile Inverted Residual Bottleneck Convolution Networks and Capsule Networks with Adaptive Feature Channels
Authors: Jin Tao , Liu Jiaming 
Published: May 2024

Abstract

This study proposes a novel text classification model, MBConv-CapsNet, to address large-scale text data classification issues in the Internet era. Integrating the advantages of Mobile Inverted Bottleneck Convolutional Networks and Capsule Networks, this model comprehensively considers text sequence information, word embeddings, and contextual dependencies to capture both local and global information about the text effectively. It transforms from the original text matrix to a more compact and representative feature representation. A Capsule Network is designed to adaptively adjust the importance of different feature channels, including N-gram convolutional layers, selective kernel network layers, primary capsule layers, convolutional capsule layers, and fully connected capsule layers, aiming to enhance the model’s ability to capture semantic information of text across different feature channels. The use of the sparsemax function instead of the softmax function for dynamic routing within the Capsule Network directs the network’s focus more on capsules contributing significantly to the final output, reducing the impact of noise and redundant information, and further improving the classification performance. Experimental validation on multiple publicly available text classification datasets demonstrates significant performance improvements of the proposed method in binary classification, multi-classification, and multi-label text classification tasks, exhibiting better generalization capability and robustness.
Power Testing of Graphical Methods for identification of Outliers in Poisson Regression Model
Authors: Hussain Zawar , Akbar Atif , Nafisah Ibrahim , Almazah Mohammed M. A. , Alshahrani Mohammed 
Published: May 2024

Abstract

This paper investigates the structure and utility of partial residual (PRES), augmented partial residual (APRES), and conditional expectation and residuals (CERES) plots for visualising influence diagnostics as a function of chosen predictors in the context of generalised linear models (GLMs). Here, predictor transformation is used to analyse Poisson regression as GLM, and PRES, APRES, and CERES plots are created. Due to the behaviour of the response variable and the linked link function with various variables, these plots' effectiveness in creating a strong visual impression may vary. In comparison to other approaches, PRES, CERES (L), and CERES (K) exhibit the highest power for influence diagnostics, according to the power of the tests for various plots.
Natural product Swietenine improve the progression of diabetic nephropathy by inhibiting ferroptosis through activation of the Akt/GSK-3β/Nrf2 signaling pathway
Authors: Lu Mengyuan , Duan Jingyu , Liu Shuang , Deng Wenhao , Pei Feilong , Liu Yaowu , Zhang Chunping 
Published: May 2024

Abstract

Background
Ferroptosis is a newly defined form of iron dependent regulatory cell death distinct from apoptosis, autophagy, and necrosis, characterized by an abnormal increase in intracellular lipid reactive oxygen species. Diabetes nephropathy (DN) is one of the most common complications of diabetes and the most common cause of end-stage renal disease. Recent studies have shown that ferroptosis plays an important role in the occurrence and development of diabetic nephropathy. Swietenine belongs to the limonin class of compounds, which are extracted from the the Swietenia macrophylla King, a plant of the genus Swietenia, family Meliaceae King and have not been artificially synthesized to date. It is a natural product with a variety of pharmacological activities such as anti diabetes, improving inflammation, anti-oxidation, anti-bacterial, anti-tumor, etc. However, it is unclear whether Swietenine can improve diabetes nephropathy by inhibiting the occurrence of ferroptosis in glomerular podocytes (MPC-5) and its potential mechanism.
Objective
This study investigated the natural product Swi through Akt/GSK-3β/Nrf2 signaling pathway inhibits MPC-5 ferroptosis and improves diabetes nephropathy in the process of diabetes.
Method
In vivo, 8-week-old SD rats were induced with STZ/HFD to investigate the effect of Swi on improving DN and resisting ferroptosis. In vitro, the inhibitory effects of Swi on MPC-5 death. By giving verify the activation effect of Akt/GSK-3β/Nrf2 signaling pathway related inhibitors on downstream anti ferroptosis related proteins.
Results
In this study, Swi treatment improved renal injury in DN rats, which was proved by renal function related indexes, histopathological parameters and podocyte damage protein. In addition, Swi inhibited ferroptosis in vivo. Swi improved HG-induced MPC-5 cell viability, inhibited ferroptosis in MPC-5 cells. Swi inhibits ferroptosis by activating the Akt/GSK-3β/Nrf2 signaling pathway, which promotes the expression of downstream anti-ferroptosis related proteins.
Conclusion
Our research findings suggest for the first time that it may be through a new Akt/GSK-3β/Nrf2 dependent ferroptosis regulates the signaling pathway, thereby reducing the level of high glucose induced ferroptosis and improving diabetes nephropathy, which is expected to become a promising candidate drug for the treatment of diabetes