bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Optimized Intelligent Open-Source MLaaS Framework for User-Friendly Clustering and Anomaly Detection
Authors: ElDahshan Kamal A. , Abutaleb Gaber E. , Elemary Berihan R. , Ebeid Ebeid A. , AlHabshy AbdAllah A. 
Published: February 2024

Abstract
In the big data era, businesses are in dire need of intelligent solutions to rapidly extract valuable insights. However, not all companies possess the specialized expertise required to operate machine learning algorithms. To bridge this gap, this paper introduces a cost-effective, user-friendly, dependable, adaptable, and scalable solution for visualizing, analyzing, processing, and extracting valuable insights from data. The proposed solution is an optimized open-source unsupervised machine learning as a service (MLaaS) framework that caters to both experts and non-experts in machine learning. The framework aims to assist companies and organizations in solving problems related to clustering and anomaly detection, even without prior experience or internal infrastructure. With a focus on several clustering and anomaly detection techniques, the proposed framework automates data processing while allowing user intervention. Furthermore, the proposed solution is expandable; it may include additional algorithms. It is versatile and capable of handling diverse datasets by generating separate rapid artificial intelligence (AI) models for each dataset and facilitating their comparison rapidly. The proposed framework provides a solution through a Representational State Transfer (RESTful) Application Programming Interface (API), enabling seamless integration with various systems. Real-world testing of the proposed framework on customer segmentation and fraud detection data demonstrates that it is reliable, efficient, cost-effective, and time-saving. With this innovative MLaaS framework, companies may harness the full potential of business analysis.
Multi-sentence and multi-intent classification using RoBERTa and graph convolutional neural network
Authors: Ravi Kumar , Singh Ajay , Gautam Chandan 
Published: February 2024

Abstract
Citation analysis has garnered significant attention in academia, particularly in the realm of scientometrics analysis. Most studies related to citation analysis focus on quantitative aspects, assigning equal weight to every citation regardless of its placement within the paper. However, understanding the distribution of citation weight across different sections of a research article is crucial for citation analysis and impact assessment. Therefore, the analysis of citation intent becomes a pivotal task in determining the qualitative importance of a citation within a scientific article. In this context, we undertook two essential tasks related to citation analysis: citation length analysis and citation intent analysis. Through citation length analysis, we identified the optimal number of citation sentences to consider around a cited sentence. Simultaneously, citation intent analysis aimed to categorize citations into seven distinct types, namely background, motivation, uses, extends, similarities, differences, and future work. For the latter task, we introduced two novel architectures based on graph neural networks, namely CiteIntentRoBERTaGCN and CiteIntentRoBERTaGAT. The performance of these proposed models was evaluated on five multi-intent datasets curated from 1,200 research papers, considering different context lengths. The results demonstrated that the proposed models achieved state-of-the-art performance.
Combinatorial chemotherapy via poloxamer 188 surface-modified PLGA nanoparticles that traverse the blood-brain-barrier in a glioblastoma model
Authors: Madani Fatemeh , Morovvati Hassan , Webster Thomas J. , Asaadi Sareh Najaf , Rezayat Seyed Mahdi , Hadjighassem Mahmoudreza , Khosravani Masood , Adabi Mahdi 
Published: February 2024

Abstract
The effect of anti-glioblastoma therapies is dwindling due to insufficient delivery across the blood-brain-barrier. It has been stated that poloxamer 188-coated nanoparticles are able to circumvent the blood-brain-barrier. Building off of such success, this study presents the design, preparation, and evaluation of a combination of PLGA nanoparticles loaded with methotrexate (P-MTX NPs) and PLGA nanoparticles loaded with paclitaxel (P-PTX NPs) that were surface-modified by poloxamer188. Cranial tumors were implanted using C6 cells in a rat model and MRI demonstrated that the tumors were indistinguishable in the two rats with P-MTX NPs+P-PTX NPs treated groups. Brain PET scans exhibited a decreased brain-to-background ratio which could be attributed to the diminished metabolic tumor volume. The expression of p53 and Ki-67 as a good and poor prognosis factor, respectively were significantly more and less, in P-MTX NPs+P-PTX NPs than in the control. Furthermore, the biodistribution of PLGA NPs was determined by carbon quantum dots loaded into PLGA NPs (P-CQD NPs), and quantitative analysis of ex-vivo imaging of the dissected organs demonstrated that 17.2 ± 0.6 % of the NPs were concentrated in the brain after 48 h. These results demonstrate the promising combinatorial nano chemotherapy for the treatment of glioblastoma which needs to be urgently investigated in human clinical models.
Pre-operative intra-aortic balloon pump insertion in coronary artery bypass grafting patients reduces in-hospital morbidity
Authors: Sazzad Faizus , Luo Hai Dong , Chang Guohao , Wu Duoduo , Ong Zhi Xian , Kofidis Theo , Kang Giap Swee 
Published: February 2024

Abstract
Background:
The aim of this study was to determine if pre-operative intra-aortic balloon pump (IABP) insertion improves the surgical outcomes of coronary artery bypass grafting (CABG).
Methods:
Patients with EuroSCORE II > 1.2% who underwent CABG from 2009 to 2016 were included in the study. Patients who utilized intra-operative or post-operative IABP were excluded. The analysis included a total of 2907 patients, with 377 patients undergoing pre-operative IABP insertion and 1198 patients receiving no IABP support. Following propensity score matching, 250 patients from each group were eligible for further analysis.
Results:
30-day mortality events occurred in 9 (3.6%) non-IABP users and in 12 (4.8%) IABP users (OR: 1.33 95%CI: 0.52–3.58). Kaplan-Meier survival curve analysis showed no significant differences between the two groups in mortality up to one year after the operation (p = 0.72). On multivariate analysis, IABP usage among the PSM patients was associated with lower 30-day mortality (OR: 0.28, 95%CI: 0.07–0.92, P-value = 0.043), 90-day mortality (OR: 0.26, 95%CI: 0.08–0.78, P-value = 0.022) and reduced risk of developing severe respiratory disorders (OR: 0.10, 95%CI:0.01–0.50, P-value = 0.011).
Conclusion:
Pre-operative IABP use in high-risk patients reduces 30- and 90-day mortality rates, along with a notable decrease in rates of severe respiratory disorders.
Wearable Signal Fusion through Deep Learning: Discriminating Affective States Levels in the Wild among Healthy and Depressed
Authors: Vázquez Cristina Gallego , Eicher Corinne , Huber Reto , Kronenberg Golo , Landolt Hans-Peter , Seifritz Erich , Poian Giulia da 
Published: February 2024

Abstract
The increasing prevalence of depression underscores the critical need for improved monitoring and personalized treatment options. While traditional assessment methods exhibit limitations, smartphone-based ecological momentary assessment has demonstrated validity and reliability in capturing real-time experiences. However, challenges such as time consumption and perceived invasiveness remain. To address these limitations, our research explored the potential of deep learning and wearable sensors to classify self-reported affective symptoms such as valence, arousal, and sleepiness based on objective and continuous passive data. Our study spanned 35 days, incorporating a diverse cohort of 26 participants (14 female, age 29 $\pm$9.0), including sixteen depressed patients and ten healthy controls. We used deep learning techniques to classify high-quality physiological data collected from a wearable patch, combining electrocardiogram signals, raw accelerometer data, and respiration rates into 3-levels of affective states. We identified optimal time windows for prediction — 24 hours for valence and 12 hours for arousal and sleepiness - and showed that combining longitudinal heart rate and heart rate variability metrics with physical activity enhanced the predictive performance for affective states classification compared to individual modalities. Our models achieved notable classification metrics for the 3-level affective states, with a balanced accuracy of 0.65 for valence, 0.56 for arousal and 0.53 for sleepiness, demonstrating competitive performance with previous work. This research contributes to advancing mental health monitoring practices, providing valuable insights into the relationships between affective and physiological states.
Geometric Deep learning Prioritization and validation of cannabis phytochemicals as anti-HCV non- nucleoside direct-acting inhibitors
Authors: Charles Ssemuyiga , Edgar Mulumba Pius 
Published: February 2024

Abstract

Introduction: The rate of acute hepatitis C increased by 7% between 2020 and 2021, after the number of cases doubled between 2014 and 2020. With the current adoption of pan-genotypic HCV therapy, there is a need for improved availability and accessibility of this therapy. However, double and triple DAA-resistant variants have been identified in genotypes 1 and 5 with resistance-associated amino acid substitutions (RAASs) in NS3/4A, NS5A, and NS5B 1. The role of this research was to screen for novel potential NS5B inhibitors from the cannabis compound database (CBD) using Deep Learning.Methods Virtual screening of the CBD compounds was performed using a trained Graph Neural Network (GNN) deep learning model. Re-docking and conventional docking were used to validate the results for these ligands since some had rotatable bonds > 10. 31 of the top 67 hits from virtual screening and docking were selected after ADMET screening. To verify their candidacy, six random hits were obtained for FEP/MD and Molecular Simulation Dynamics.Results The top 200 compounds from the deep learning virtual screening were selected, and the virtual screening results were validated by re-docking and conventional docking. The ADMET profiles were optimal for 31 hits. Simulated complexes indicate that these hits are likely inhibitors with suitable binding affinities and FEP energies. Phytil Diphosphate and glucaric acid were suggested as possible ligands against NS5B.
On Some Extended Energy of Graphs and Their Applications
Authors: Sarkar Prosanta , Kumar Shiv , Pal Anita 
Published: February 2024

Abstract
In this paper, we dealt with extended energy of graphs namely first and second Zagreb energy, Randić energy, reciprocal Randić energy, and the atom-bond connectivity energy. We studied their relationship with some thermodynamic properties of benzenoid hydrocarbons. We have seen that these indices are well correlated to the boiling point (BP), Kovats retention index (RI), entropy (S), enthalpy of formation (ΔHf), octanol-water partition coefficient (logP), and acentric factor (ω) of benzenoid hydrocarbons. Significantly, the correlation coefficients of Randić energy with the boiling point, enthalpy of formation, Kovats retention index, octanol-water partition coefficient, and acentric factor are greater than 0.97.
Rising Sea Levels and the Increase of Shoreline Wave Energy at American Samoa
Authors: Barnes Austin T , Becker Janet M , Tagarino Kelley A , O'Reilly William C , Siegelman Mika , Thompson Philip R , Merrifield Mark A 
Published: February 2024

Abstract
American Samoa is experiencing rapid relative sea level rise due to increases in global sea level and significant post-2009 earthquake land subsidence, endangering homes and critical infrastructure. Wave and water-level observations collected over a fringing reef at Faga‘itua Bay, American Samoa, in 2017 reveal depth-limited shoreline sea-swell wave heights over the range of conditions sampled. Using field data to calibrate a one-dimensional, phase-resolving nonhydrostatic wave model (SWASH), we examine the influence of water level on wave heights over the reef for a range of current and future sea levels. Assuming a fixed reef bathymetry, model results predict rising sea levels will escalate nearshore extreme water levels that are dominated by an increase in nearshore sea-swell wave heights. Model results provide insight into how and at what reef depths rising sea levels reduce reef capacity to dissipate wave energy, compounding shoreline threats. This study aims to bring increased attention to the immediate threats to American Samoa’s way of life, and to demonstrate the utility of SWASH for extrapolating wave transformation to future sea level.
Construction and Validation of a Teachers’ Remotivational Strategies Measure: Ecological Systems and Self-Determination Theories in Perspective
Authors: Alavian Hadis Sadr , Asadollahfam Hassan , Yousefi Mohammad Hossein 
Published: February 2024

Abstract

Given the paramount importance of motivation and the paucity of research into teachers’ remotivational strategies, this study constructed and validated a teachers' remotivational strategies questionnaire. In so doing, the present study built upon an integrative framework encompassing Ecological Systems Theory (EST) and Self-Determination Theory (SDT). The participants comprised 235 EFL teachers within the age range of 21 to 45 (M = 30.63, SD = 5.28) and teaching experience of three months to 23 years (M = 7.30, SD = 3.87). To gather data, semi-structured interviews were conducted. Following that, the interview contents became subject to thematic analysis, and the results along with the existing themes in the extant theoretical and empirical literature were used to develop the questionnaire. The results of thematic data analysis demonstrated that the emerging theme instances were situated within the integrative SDT/EST frame. The results of Exploratory Factor Analysis (EFA) suggested a three-factor structure encompassing relatedness, competence, and autonomy. Moreover, the results of Confirmatory Factor Analysis (CFA) indicated that the three-factor structure fits the Iranian EFL teachers' population. Based on the results, the teachers' remotivational strategies questionnaire can be safely used for developing professional programs aiming at determining and promoting EFL teachers’ understanding and use of remotivational strategies.
Monetary Policy with Heterogeneous Agents in Developing Countries : The Case of CEMAC zone
Authors: Signe Franck Xavier , Poutineau Jean Christophe , Gankou Jean Marie 
Published: February 2024

Abstract
This paper quantitatively assesses the role of farm households heterogeneity in the conduct of monetary policy in developing countries such as CEMAC zone. Using Bayesian estimation techniques via the SSJ (Sequence Space Jacobian) method, we estimate two models, one with heterogeneity of non- farm households (HANK without farmer model) and one with heterogeneity of farm and non- farm households (HANK with farmer model). We find that taking into account the heterogeneity of farm households in the conduct of monetary policy plays an important role in mitigating the transmission of asymmetric shocks. The models also reveal that farm households have an important role to play in the growth process, provided they are supported by monetary and fiscal authorities.
JEL Classification : E21, E31, E40, E50, E52, E61
Phenotypic spectrum of iron-sulfur cluster assembly gene IBA57 mutations: c.286T&gt;C identified as a hotspot mutation in Chinese patients with a stable natural history
Authors: Jiang Huafang , Xu Chaolong , Duan Ruoyu , Liu Zhimei , Ren Xiaotun , Li Jiuwei , Chen Chunhong , Wang Hongmei , Han Tongli , Tian Xiaojuan , Duan Xin , Song Minhan , Li Tongyue , Fang Fang 
Published: February 2024

Abstract
Mutations in IBA57 disrupt iron-sulfur clusters maturation, causing a rare mitochondrial disease. Clinical manifestations vary from neonatal lethality to childhood-onset spastic paraparesis, yet the ethnic heterogeneity and natural history remain unclear, necessitating further exploration. This study aimed to delineate the genotype-phenotype correlation of IBA57 mutations by analyzing diverse clinical presentations. We report 11 Chinese patients and include literature-reported cases, totaling 61 patients enrolled for analysis. Clinical, neuroimaging, genetic and disease progression information were collected. Among these, 46 presented as multiple mitochondrial dysfunctions syndrome 3 (MMDS3), with 58.7% originating from Chinese population. Based on disease course, we propose three clinical subtypes: neonatal, infant and childhood subtypes. Neonatal cases universally displayed hypotonia and respiratory distress at presentation, deceased within three months. Most infancy and childhood cases exhibited developmental regression and impaired motor function. Cavitating leukoencephalopathy was a typical neuroimaging finding in MMDS3 patients. The c.286T > C mutation was reported in 85.2% of Chinese patients. A significantly lower mortality rate was observed compared to the non-Chinese group (P = 0.002), with a survival rate exceeding 90% at 5 years, indicating a relatively stable disease progression. Fifteen cases from three families manifested the spastic paraplegia 74 phenotype, demonstrating normal development before onset, with common clinical manifestations including spastic paraplegia (14/15), visual impairment (10/13), and peripheral neuropathy (9/13).
Conclusion: Despite a diverse phenotypic spectrum, neonatal-onset cases exhibit severe symptoms and a poor prognosis. More than half of the patients were Chinese, and c.286T > C variant was a hotspot mutation in Chinese population, associated with a stable natural history.
Irritable Bowel Syndrome and the Risk of Mouth Ulcers: Insights from a Mendelian Randomization Study
Authors: AO Man , LIU Shu , Ting ZHANG , feng hongchao 
Published: February 2024

Abstract

Background Irritable bowel syndrome (IBS) is a common functional gastrointestinal disorder characterised by chronic abdominal pain and altered bowel habits. However, IBS is often associated with a variety of comorbidities, and the causal relationship between IBS and oral ulcers is currently unclear.Methods A Two-sample Mendelian randomization study was used to investigate the relationship between irritable bowel syndrome and oral ulcers, with Cochran's Q test testing for heterogeneity between instrumental variables (IV). Horizontal pleiotropy was tested by MR-Egger regression intercept analysis and MR-PRESSO analysis.Results MR analysis revealed a significant causal relationship between irritable bowel syndrome and increased risk of developing oral ulcers for IVW (OR = 1.023, 95% CI: 1.007–1.040; p = 0.003). Similar results were observed in the weighted median (OR = 1.022, 95% CI: 1.003–1.042; p = 0.018). Sensitivity analyses and Cochran's Q test did not reveal the presence of pleiotropy and heterogeneity.Conclusions The present study suggests that oral ulcers may be a complication of irritable bowel syndrome and the results have important clinical implications, however, the biological mechanisms of this association need to be further explored.
Chronic constipation and diarrhea are associated with depression in the elderly: Insights from a large cross-sectional study
Authors: 陈 明骏 , Dai Hengheng , Tong ZhanQi 
Published: February 2024

Abstract
Background: This study was to investigate the relationship between chronic constipation, diarrhea, and depression among the elderly, as the extent of their association remains elusive despite the well-established impact of gastrointestinal symptoms on depression.
Methods: Cross-sectional analyses were conducted using data from the 2005-2010 U.S. National Health and Nutrition Examination Surveys (NHANES), focusing on adults aged 60 and above with a sample size of 4878. Depressive symptoms were measured using Patient Health Questionnaire 9 (PHQ-9) scale. Information about chronic diarrhea or constipation was retrieved from the bowel health questionnaire. Multivariable weighted logistic regression analysis models were employed to estimate the relationship between gut health and depression status, adjusting for potential confounders (e.g., age, gender, race, education, marital status, education level, smoking status, drinking habits, and medical history).
Results: Probable depression (PHQ-9≥10) and depressive symptoms (PHQ-9≥5) were more prevalent among elderly individuals with diarrhea or constipation than among those without them (P <0.05). After adjusting for all-cause, the elderly with chronic diarrhea were more likely to have significant increases in their scores for several subtypes of depressive symptoms (P <0.05, six out of nine depressive symptoms). We observed a significantly positive correlation between patients with chronic constipation and the depressive symptoms for low mood/despair, appetite, and lack of concentration (P <0.05).
Conclusion: The elderly with depressive symptoms (PHQ-9 ≥5) may be associated with chronic constipation and diarrhea based on a nationally representative sample of the elderly in the U.S. from 2005 to 2010. These findings suggest that elderly individuals experiencing chronic diarrhea and constipation may have a higher prevalence of psychological depression symptoms.
Association Between Hemoglobin-to-Red Cell Distribution Width Ratio and Bone Mineral Density in the Elderly in the United States: Evidence from NHANES
Authors: Xiao Yongchun , Pan Huawen , Huang Ruihua , Wu Ping , Peng Cheng , Luo Jianxian , Wu Jianxiong , Wang Zhifeng , Zhang Guowei , Yang Hua , Lin Hongsheng , Liang Junze , Ji Zhisheng 
Published: February 2024

Abstract
Background
The Hemoglobin-to-Red Cell Distribution Width Ratio (HRR), a key element of blood cell counts, emerges as a novel biomarker linked to various diseases and adverse health outcomes. However, its correlation with Bone Mineral Density (BMD) and osteoporosis in the elderly remains under-researched.
Methods
This study used NHANES data to examine the link between HRR and Bone Mineral Density (BMD), and osteoporosis in U.S. seniors. It involved 9,128 participants aged 50+, assessing their BMD and blood cell counts. A weighted linear model was used to assess HRR's influence on BMD, while weighted logistic regression examined its connection to osteoporosis, supported by an extensive subgroup analysis.
Results
The study utilized weighted linear regression to reveal a significant positive correlation between higher HRR levels and increased BMD. Additionally, weighted logistic regression indicated an inverse relationship between HRR levels and osteoporosis risk, consistently observed across subgroups and independent of confounders.
Conclusion
HRR may be an important marker for bone density and osteoporosis risk in the elderly, offering new insights for potential preventive and treatment strategies. However, these findings necessitate further validation and research due to study limitations.
Advancing Nonlinear Problem Solutions: Newton-Like Iterative Techniques for Varied Convergence Orders using Homotopy Perturbation
Authors: Raza Muhammad , Toheed Danish , Rehman Najma Abdul 
Published: February 2024

Abstract
In this paper, we develop Newton-like iterative methods of the convergence order three and six to eight. These methods are developed by using homotopy perturbation technique and their order of convergence is verified theoretically. Proposed methods are tested numerically to reveal their effectiveness and superiority over existing approaches in the literature and real world problems.
Math Subject Classifications 2020: 65H20, 90C39.