bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Intelligent-Based System for Detecting Depression on Social Media Platform
Authors: Ojo Oluwafolake , Adewuyi Inioluwa , Oni Oluwadolapo , Oyinloye Olufunke , Gbolade Idris , Ojo Abayomi 
Published: May 2023

Abstract
Purpose: The global quarantine measures implemented in response to the coronavirus outbreak have resulted in a surge of psychiatric issues, including but not limited to depressive symptoms, anxiety, and sleep disturbances, which have placed a significant burden on healthcare systems worldwide. The most efficacious prevention strategy for depression is the identification of its early warning symptoms. In recent times, the healthcare sector has increasingly embraced a technology-oriented strategy. The examination of social media content possesses the capability to significantly reduce the incidence of depression and, consequently, the number of suicides.
Methods: The present study introduces a computational method to detect social media users who exhibit symptoms of depression. The intelligent framework employs machine learning techniques to identify text in social media posts that pertain to depression. In this study, three distinct machine learning models, namely the bidirectional encoder representations from Transformers (BERT), the long short-term memory (LSTM), and the convolutional neural network (CNN) were subjected to 1 Springer Nature 2021 L A T E X template Article Title pre-processing and pre-training using data sets obtained from the Twitter API and the Reddit database. The ultimate goal of this study is to accurately distinguish between depressive and non-depressive content.
Results: According to the empirical analysis, the BERT model demonstrated a 92.4% accuracy rate and achieved the most optimal validation loss during the third epoch. Moreover, in comparison to the CNN and LSTM models, the BERT model exhibited greater efficiency across all performance indicators.
Conclusion: The BERT model performed exceptionally well in both text categorization and feature extraction when compared to the other pre-training models utilized in this investigation. The BERT model has been refined by the identification of these unique characteristics, making it better suited to the task of identifying depressive-related information in digital documents and social media posts.
Long-term impairment of social-related quality of life in COVID-19 pneumonia survivors: a prospective longitudinal study
Authors: Ando Takahiro , Shimada Sho , Sugihara Jun , Takayama Koji , Kobayashi Masayoshi , Miyashita Yoshihiro , Ito Tatsuya , Okayasu Kaori , Tsuyuki Shun , Ohba Takehiko , Doi Masafumi , Saito Hiroaki , Fujie Toshihide , Chiaki Tomoshige , Nakagawa Atsushi , Anzai Tatsuhiko , Takahashi Kunihiko , Shibata Sho , Tateishi Tomoya , Miyazaki Yasunari 
Published: May 2023

Abstract
Long-term sequelae of COVID-19 can affect health-related quality of life (HRQOL). We examined the long-term impact of COVID-19 on HRQOL and elucidated factors associated with low HRQOL. Discharged COVID-19 patients were assessed at 3 and 6 months after disease onset. The patients completed a medical examination and SF-36 questionnaire at the two time points and underwent pulmonary function testing at 6 months. All had undergone computed tomography (CT) imaging upon hospital admission. Of the 74 included patients, 38% reported respiratory symptoms at 3 months and 26% at 6 months. The aggregated SF-36 scores declined in the role/social component summary (RCS), a category related to social activity. Patients with respiratory sequelae or impaired pulmonary function had lower RCS scores. There was a negative linear relation between the RCS score and the CT score, which reflected the extent of COVID-19 pneumonia (3 months, P = 0.0024; 6 months, P = 0.0464). A high CT score (≥ 10 points) predicted a low RCS score at 6 months (P = 0.026). This study highlights the long-term impairment of RCS and its associations with respiratory sequelae. The study also emphasizes the importance of radiological findings in predicting long-term HRQOL outcomes after COVID-19.
Bearing capacity of centrically-vertically loaded strip foundations based on soil parameters: a classical earth pressure analysis problem
Authors: Pantelidis Lysandros 
Published: May 2023

Abstract
The bearing capacity of shallow foundations is one of the major fields of soil mechanics and foundation engineering. Since 1920, when Prandtl suggested the well-known failure mechanism with the three zones and 1943, when Terzaghi, based on this mechanism, suggested his famous equation with the three N-factors, numerous bearing capacity methods for the basic problem of centrically-vertically loaded strip footings have been proposed in the literature, mainly focusing on better defining the Nγ factor. It is mentioned that although Terzaghi considered the vertical balance of forces, he indirectly relied on the theory of earth pressure, calculating three earth pressure coefficients (for the self-weight and cohesion of the soil and for the lateral surcharge), which worked in the vertical direction. The purpose of the present paper is to suggest a completely new approach to the above-mentioned problem. It is shown that the problem in question is a classical earth pressure analysis problem, with a virtual wall dividing the failure mass into an active and a passive Rankine failure zone. Also, it is shown that it is not the Nγ factor which prevents us from having better prediction for the bearing capacity of footings, but the various non-effective depth factors. The solution to the problem demands a unique depth factor to be applied to all three bearing capacity terms. In this paper, this depth factor derives from extensive regression analysis. Moreover, since, as known, the dilatancy of soils affects the bearing capacity value, the proposed method has been calibrated against non-associated finite element models with ψ=0°. Thus, the proposed method is on the safe side.
Evaluation of a digitally enhanced cardiac auscultation learning method: results of a controlled study
Authors: Bediang Georges , Zock Agnès Baran à , Doualla Fred-Cyrille Goethe , Nganou-Gnindjio Chris Nadège 
Published: May 2023

Abstract
Background
Cardiac auscultation is an efficient and effective diagnostic tool, especially in low-income countries where access to modern diagnostic methods remains difficult. This study aimed to evaluate the effect of a digitally enhanced cardiac auscultation learning method on medical students’ performance.
Methods
We conducted a double-arm parallel controlled trial, including newly admitted 4th -year medical students enrolled in two medical schools in Yaoundé, Cameroon and allocated into two groups: the intervention group (benefiting from theoretical lessons, clinical internship and the listening sessions of audio recordings of heart sounds) and the control group (benefiting from theoretical lessons and clinical internship). All the participants were subjected to a pretest before the beginning of the training, evaluating theoretical knowledge and recognition of cardiac sounds, and a post-test at the eighth week of clinical training associated with the evaluation of satisfaction. The endpoints were the progression of knowledge score, skills score, total (knowledge and skills) score and participant satisfaction.
Results
Forty-nine participants (27 in the intervention group and 22 in the control group) completed the study. The knowledge progression (+ 26.7 versus + 7.5 ; p ˂0.01) and the total progression (+ 22.5 versus + 14.6 ; p ˂ 0.01) were higher in the intervention group with a statistically significant difference compared to the control group. There was no significant difference between the two groups in terms of skills progression (+ 25 versus + 17.5 ; p = 0.27). Satisfaction was higher in general in the intervention group (p ˂ 0.01), which recommended this method compared to the control group.
Conclusion
The learning method of cardiac auscultation reinforced by the listening sessions of audio recordings of heart sounds improves the performances (knowledge and global – knowledge and skills) of medical students who find it satisfactory and recommendable.
Trial Registration
This trial has been registered the 29 November 2019 in the Pan African Clinical Trials Registry (http://www.pactr.org) under unique identification number PACTR202001504666847 and the protocol has been published.
Explaining the Gender Gap in Labor Supply of Married Peoplein South Korea
Authors: Kim Anna , Hahn Youjin 
Published: May 2023

Abstract
Despite an increase in female labor force participation over the last decade, the gender gap in labor supply between married men and women has persisted in South Korea. We examine the gender gap in labor supply with a focus on education and spousal earnings in explaining the gap using decomposition analysis. Endowment differences in education between married men and women increase the gender gap. However, its adverse effect has decreased over time with Korean women acquiring either equal or higher access to education. We also highlight spousal earnings as an important explanation for the unchanged gender gap in labor supply. Our result implies that intrahousehold equality in earnings may lead to gender equality in labor supply and vice versa. Consistent with other studies focusing on Asian countries, a large portion of South Korea’s gender gap in labor supply remains unexplained.
JEL classification: J16, J21, J22
Urban Localization using Robust Filtering at Multiple Linearization Points
Authors: Gupta Shubh , Mohanty Adyasha , Gao Grace 
Published: May 2023

Abstract
We propose a robust Bayesian filtering framework for state and multi-modal uncertainty estimation in urban settings by fusing diverse sensor measurements. Our framework addresses multi-modal uncertainty from various error sources by tracking a separate probability distribution for linearization points corresponding to dynamics, measurements, and cost functions. Multiple parallel robust Extended Kalman filters (R-EKF) leverage these linearization points to characterize the state probability distribution. Employing Rao-Blackwellization, we combine the linearization point distribution with the state distribution, resulting in a unified, efficient, and outlier-resistant Bayesian filter that captures multi-modal uncertainty. Furthermore, we introduce a gradient descent-based optimization method to refine the filter parameters using available data. Evaluating our filter on real-world data from a multi-sensor setup comprising camera, Global Navigation Satellite System (GNSS), and Attitude and Heading Reference System (AHRS) demonstrates improved performance in bounding position errors based on uncertainty, while maintaining competitive accuracy and comparable computation to existing methods. Our results suggest that our framework is a promising direction for safe and reliable localization in urban environments.
Surgical resection of the primary tumor improves survival in patients with locoregional stage T1 nasopharyngeal carcinoma: a propensity score-based matched analysis
Authors: Zuo Huifang , Li Min-Min 
Published: May 2023

Abstract
Background Surgery at the primary site of nasopharyngeal carcinoma (NPC) remains controversial. This study aimed to investigate the efficacy of surgery in patients with stage T1N0-3M0 NPC.Methods We reviewed 1803 patients with newly diagnosed stage T1N0-3M0 NPC from the Surveillance, Epidemiology, and End Results (SEER) database for the period 2004–2015. The Kaplan-Meier method and propensity score matching (PSM) analyses were used to compare cancer-specific survival (CSS) and overall survival (OS) between surgery groups and no-surgery groups. Restricted cubic spline regression (RCS) was used to assess the relationship between age and the hazard ratio of mortality. Independent risk factors associated with OS and CSS were identified by Cox ratio hazard regression analysis employing a backward stepwise method, which was used to develop prognostic nomograms for locoregional T1 NPC patients. The correlation index and calibration curves were used to assess the performance of the model. An online dynamic nomogram for CSS was also developed to assist the clinic in better using the predictive model.Results The study examined 1803 patients, of whom 242 received surgery, and the remaining 1561 did not receive surgery. Before PSM, Kaplan-Meier analysis showed that OS and CSS were significantly longer in the surgery group than in the non-surgery group (P < 0.001). After 1:1 matching, similar results as above could be observed, that is, patients in the surgical group had significantly better OS (P < 0.001) and CSS (P = 0.0018) benefits. Subgroup analysis further showed that almost all subgroups undergoing surgery had superior OS and CSS, except for patients with tumor size > 30 mm and primary site located in the anterior wall of the nasopharynx. Finally, COX regression analyses showed that age, sex, marital status, histological type, N stage, tumor size, radiotherapy, and surgery were independent prognostic factors for OS and CSS.Conclusions This study indicated that surgery significantly improved the OS and CSS of patients with stage T1N0-3M0 NPC. The nomograms we established have satisfactory performance and may provide a reference for the clinic. Further prospective large studies are still needed to validate the results.
Experiences and Facilitators of Physical Activity Engagement: The Wearable Activity Technology and Action-Planning (WATAAP) Trial
Authors: Hardcastle Sarah J. , Douglass Emma , Wilson Bree , Maxwell-Smith Chloe 
Published: May 2023

Abstract
Purpose
This study explored cancer survivors' experiences of participation in a wearable intervention and the dimensions that influenced intervention engagement and physical activity behaviour change.
Methods
Semi-structured interviews (n = 23) were conducted with intervention participants (mean age 65.8 (SD ± 7.1) and analysed using thematic analysis.
Results
Four main themes were identified; (i) Commitment, (ii) Accountability and monitoring, (iii) Routine (iv) Fitbit as health coach. Those that assigned a higher priority to PA were more likely to schedule PA and be successful in PA change. Those less successful presented more barriers to change and engaged in more incidental PA. The Fitbit acting as health coach was the active ingredient of the intervention.
Conclusions
Commitment evidenced through prioritising PA was the foundational dimension that influenced PA engagement. Interventions that foster commitment to PA through increasing the value and importance of PA would be worthwhile. Wearables holds great promise in PA promotion and harnessing the technique of discrepancy between behaviour and goals is likely a valuable behaviour change technique.
EasyModel: A User-Friendly Web-Based Interface Based on MODELLER
Authors: Arab Seyed Shahriar , Dantism Alireza 
Published: May 2023

AbstractBackground:Three-dimensional protein structures are invaluable sources of information for the functional annotation of protein molecules. Describing the function of a protein sequence is one of the most common problems in biology. Generally, this problem can be facilitated by studying the tertiary structure of proteins. In the lack of protein structures, comparative modeling often provides a useful three-dimensional model of the protein associated with at least one known protein structure. Comparative modeling predicts the tertiary structure of a certain protein sequence (target) mainly based on its homological sequence to the sequence of one or more proteins with known structures (templates). MODELLER is one of the most widely used tools for homology or comparative modeling of three- dimensional protein structures. However, most users find it challenging to start with MODELLER as it is a command line based and requires knowledge of basic Python scripting to use it efficiently.Results:In this study, a web-based interface has been designed to predict the tertiary structure of proteins based on Modeller, which does the comparative modeling automatically, and uses PHP and Python programming languages. This tool is called “EasyModel” and is available at http://bioinf.modares.ac.ir/software/easymodel/.Conclusion:EasyModel provides a straightforward graphical interface for Modeller that can be used in only one browser.
Should We Consider Sarcopenia in Pediatric Patients with Chronic Kidney Disease? A Preliminary Cross-sectional Analysis
Authors: Barbosa Ana Carolina , Brison Raquel S , Gomes Carolina C , Wilkinson Thomas J , Duarte Marvery P , Gruezo Nádia D , Ribeiro Heitor 
Published: May 2023

Abstract
Objective
We investigated sarcopenia and its traits in children and adolescents with chronic kidney disease.
Methods
Physical function was assessed using handgrip strength (HGS) and the 60-second sit-to-stand (STS-60). Body composition was assessed by bioelectrical impedance and anthropometry through mid-upper arm circumference (MUAC). Probable sarcopenia was considered as low HGS, whereas sarcopenia by adding low MUAC.
Results
Twenty-two patients were evaluated (11 ± 4 years and 59% boys). Sarcopenia prevalence was 50%. Low physical function by HGS and STS-60 was 59% and 100%, respectively, while low MUAC in 77%. HGS was positively associated with all body composition variables in the non-dialysis and peritoneal dialysis groups; on the other hand, the STS-60 was not significantly associated with any of the body composition variables.
Conclusion
Among pediatric patients with CKD, the prevalence of sarcopenia was high. Therefore, strategic interventions to body composition will likely confer positive benefits on HGS, but not on STS-60.
Multiphase CT scans findings for AI training in the differentiation of hepatocellular carcinoma and intrahepatic cholangiocarcinoma based on interobserver agreement of expert abdominal radiologist.
Authors: chiangmai Wittanee Na , Inmutto Nakarin , Chitapanarux Imjai , Pojchamarnwiputh Suwalee , Nimitrungtawee Natthapong , Inkeaw Papangkorn , Sri Patumrat 
Published: May 2023

Abstract
Computed tomography (CT) is the imaging modality used to evaluate liver nodule and differentiate hepatocellular carcinoma (HCC) from intrahepatic cholangiocarcinoma (ICC). The purpose of this study was to find out potential CT features in the differentiation of hepatocellular carcinoma and intrahepatic cholangiocarcinoma. Patients with radiological and pathologically confirmed diagnosis of HCC and ICC between January 2013 and December 2015 were included. Two board certified diagnostic radiologists independently reviewed multiphase CT images. Most of HCC showed arterial hyperenhancement at 95.8%. Arterial enhancement in ICC was less often at 15.4% to 26.9%. Two readers showed a moderate agreement of cirrhosis appearance in both HCC and ICC. Cirrhosis appeared in HCC group more frequently than ICC group. Lymph node enlargement was more common seen in ICC than HCC and agreement between readers was almost perfect. Portal vein invasion in HCC was seen 14.6 % by both readers with a substantial agreement. We believed cirrhosis appearance and lymph node enlargement could be remarkable imaging feature in differentiated HCC and CCA.
Population characteristics of the endangered Barbary sheep in the Amassine nature reserve, Moroccan Western Atlas range
Authors: Bachiri Hakim , Znari Mohammed 
Published: May 2023

Abstract
Population characteristics of Atlas Barbary sheep (Ammotragus lervia) were investigated 17 years following the 1999 introduction of 10 individuals into the fenced nature reserve of Amassine, High Atlas range, Morocco, for promoting wildlife watching and tourism. Population age-sex structure and density were determinate in late winter early spring during four consecutive years (2016–2019) by direct observation before dispersal of the herd. During 2017 the population age-sex structure and density were also investigated and determinate in mid-late spring while the herd is dispersed using the line transect-distance sampling method to have a comparison between the two methods (direct and indirect). Population size increased from 37 to 62 animals during the four-year study period; the maximal population size being 82 individuals recorded in 2006. An estimated population density ranged from 0.25 to 0.41 Barbary sheep/ha. The adult sex ratio varied from 91 to 67 per 100 ewes. The apparent birth rate was of 14 to 73/100 ewes. Juveniles and subadults comprised 27–43% of the population, adult rams 26–31% and, adult ewes 29–45%. The survival rate from birth to 1 year of age approximated 35%. For adult rams was estimated to average 69%/year. The obtained results would be helpful for developing a sustainable population management and habitat restoration plan, and assessing the feasibility of potential reintroduction/restocking in other areas of the Atlas range.
Machine Learning-Based Prediction of Surgical Benefit in Borderline Resectable and Locally Advanced Pancreatic Cancer
Authors: Zhang Leiming , Yu Zehao , Jin Rong , Yang Xuanang , Ying Dongjian 
Published: May 2023

Abstract
Introduction Surgery represents a primary therapeutic approach for borderline resectable and locally advanced pancreatic cancer (BR/LAPC). However, BR/LAPC lesions exhibit high heterogeneity and not all BR/LAPC patients who undergo surgery can derive beneficial outcomes. The present study aims to employ machine learning (ML) algorithms to identify those who would obtain benefits from the primary tumor surgery.Methods We retrieved clinical data of patients with BR/LAPC from the Surveillance, Epidemiology, and End Results (SEER) database and classified them into surgery and non-surgery groups based on primary tumor surgery status. To eliminate confounding factors, propensity score matching (PSM) was employed. We hypothesized that patients who underwent surgery and had a longer median cancer-specific survival (CSS) than those who did not undergo surgery would certainly benefit from surgical intervention. Clinical and pathological features were utilized to construct six ML models, and model effectiveness was compared through measures such as the area under curve (AUC), calibration plots, and decision curve analysis (DCA). We selected the best-performing algorithm (i.e., XGBoost) to predict postoperative benefits. The SHapley Additive exPlanations (SHAP) approach was used to interpret the XGBoost model. Additionally, data from 53 Chinese patients prospectively collected was used for external validation of the model.Results According to the results of the 10-fold cross-validation in the training cohort, the XGBoost model yielded the best performance (AUC = 0.823, 95%CI 0.707–0.938). The internal (74.3% accuracy) and external (84.3% accuracy) validation demonstrated the generalizability of the model. The SHAP analysis provided explanations independent of the model, highlighting important factors related to postoperative survival benefits in BR/LAPC, with age, chemotherapy, and radiation therapy being the top three important factors.Conclusion By integrating of ML algorithms and clinical data, we have established a highly efficient model to facilitate clinical decision-making and assist clinicians in selecting the population that would benefit from surgery.