bluuebunny/crossref_metadata_2025_split huggingface dataset:
Web-based Approach for Detection of Acute Lymphoblastic Leukemia From Microscopic Blood Cell Images Using Convolutional Neural Network
Authors: M Menagadevi , M Nirmala , D Thiyagarajan , R Rajkumar 
Published: March 2023

Abstract

Acute Lymphoblastic Leukemia (ALL) is a blood tumor that affects bone marrow and blood. Leukemia affects young people and adults worldwide. Early diagnosis of leukemia provides a patient with the right treatment option, especially for children. In medical image processing, computational tools play a major role in the field of research. The objective of this paper is to predict the ALL cells using image processing and a Computational Neural Network (CNN). 498 images were collected from the publicly available datasets and the analysis was performed. In the preprocessing stage, noise in the image is eliminated by median and weiner filters and the RGB color leukemia images are converted into lab color images as it enhances segmentation of the nucleus of the image. In this study, the k-means clustering algorithm was applied to segment the nucleus from microscopic blood cell images. Based on the characteristics of the nucleus in the leukemia image, the tumor is detected. CNN takes different features from the input blood sample image and assigns weights to the input image, which helps the network with classification. This model was evaluated with a sensitivity of 98.2%, a specificity of 97%, and an accuracy of 98%. Finally, a flask web page is developed using python to display the output.
Synchronous and Metachronous presentation of Gastrointestinal Stromal Tumors
Authors: Núñez-Rocha Ricardo E. , Panqueva Rocío López , Ortiz-Pereira Mónica , Toscano-Madero María Camila , Pachón María Juliana Miranda , Andrade Rafael , Cadena Manuel , Herrera-Almario Gabriel E. 
Published: March 2023

Abstract
Introduction: Gastrointestinal stromal tumors are uncommon mesenchymal tumors in the gastrointestinal tract. There is evidence reported of associated secondary neoplasms as synchronic and metachronous tumors. We aimed to describe the patients with synchronous and metachronous gastrointestinal stromal tumors in our reference center.
Methods: Review of dataset of a prospectively collected database of 207 patients who underwent surgery for GIST management from 2008 to 2018.
Results: 22 patients were included. Mean overall age was 69 (± 8,92) years. Male patients were 63.6%. Gastric was the most common location (68.1%, n=15), followed by small bowel (13.6%, n=3). Immunohistochemistry showed diffuse +CD117 in 100% of the cases. The synchronous tumors group included 11 cases and the most common type of tumor was gastric adenocarcinoma (n=2). For metachronous tumors, the primary localization was the prostate (45.5%, n=5). The most common type of metachronous tumor was prostatic adenocarcinoma (n=5).
Conclusion: The stomach was the most common location for synchronous tumors and the prostate for metachronous tumors both being adenocarcinomas. The appearance of these tumors is not as uncommon as reported.
Analysis and Prediction of Personality Traits Using a Self-Generated Database of Moroccan Instagram Users: Impact of Gender on Image Content and Quantity on Prediction Accuracy
Authors: BAHY Siham EL , ABOUTABIT Noureddine , HAFIDI Imad 
Published: March 2023

Abstract
Data shared on social networks can reflect numerous information about users, such as personality traits, inclinations, and interests. Consequently, research on predicting user personality from social network data has become increasingly focused. This study focuses on the Instagram application and is the first, to our knowledge, to examine Moroccan Instagram users. To study the effect of personality traits and gender on photo content, we predict and analyze the personalities of female and male Instagram users separately, based on characteristics extracted from the photos they share. This study is the first to predict the personality of both genders separately, given differences in the nature and preferences of genders. Additionally, we examine the effect of the number of images on prediction accuracy. Furthermore, three categories of features have been extracted from the images: visual, emotional, and content. Moreover, the Big Five model is used to represent users' personalities. Additionally, we collected a database of 316 Instagram users; it is the largest compared to previous works and includes users from different regions and social classes, which makes the results more generalizable. A root mean square error (RMSE) related to the [1,5] score scale was used to indicate prediction accuracy. In general, good results were obtained for all traits, with outperforming results in predicting consciousness for females (RMSE=0.59) and openness for males(RMSE=0.59), compared to previous studies.
Non-Enzymatic Glucose Sensors Composed of Nanoflower Shaped CuO/Ag/SiNPs Based Composite Material with High Performance
Authors: Naikoo Gowhar A. , Bano Mustri , BaOmar Fatima , Hassan Israr U. 
Published: March 2023

Abstract
Diabetes management is a challenging task and accurate glucose sensing remains a crucial yet elusive goal. Herein, we demonstrated the capacity of electrochemically-active non-enzymatic glucose sensing of nanoporous CuO/Ag and nanoflower shaped CuO/Ag/SiNPs in an alkaline environment. The crystalline structure and the surface morphology of nanoporous CuO/Ag, and nanoflower shaped CuO/Ag/SiNPs-based composite materials were analyzed using powder X-ray diffraction (P-XRD), energy dispersive X-ray (EDX) spectroscopy, X-ray Photoelectron spectra (XPS), Raman Spectroscopy, scanning electron microscopy (SEM) and transmission electron microscopy (TEM) techniques. The electro-catalytic characteristics of the fabricated electrode materials for glucose electro-oxidation in alkaline circumstances were examined using the cyclic voltammetry (CV) and chronoamperometry methods. The FGGS (Fourth Generation Glucose Sensors) from the composite materials exhibited a remarkable performance for glucose sensing with a wide linear range of 0.001 to 10 mM and 0.1 to 2.5 µM, an ultrahigh sensitivity of 4877.6 μA mM−1 cm−2, and a low detection limit (0.1μM). The designed electrode responded positively to the addition of glucose electro-oxidation and reached steady-state within 0.4 seconds with reproducibility (above 3000 cycles) and the diffusion rate constant for this electrochemical Nanoflower shaped CuO/Ag/SiNPs-based sensor is 0.6 cm/s. The nanoporous composite materials are cost-effective and possess improved sensitivity, selectivity, and response time, thus making them suitable for the fabrication of glucometers. The use of such materials will be beneficial for the diagnosis and treatment of hyperglycemia, as well as for the development of implantable glucose sensors and wearable sensors.
HMGA2 promotes epithelial-mesenchymal transition of clear cell renal cell carcinoma via transforming growth TGF-β/Smad2 signal pathways
Authors: Liu XuJie , Li Tie , Su JiaHao , Fu Qizhong , Chen Qian , Liu Ying 
Published: March 2023

Abstract
Purpose
To investigate the role of high mobility group protein A2 (HMGA2) in the epithelial-mesenchymal transition (EMT) of kidney cancer.
Methods
The renal carcinoma cell line ACHN were transfected using RNA interference technology (siRNA) to develop a cell line with low HMGA2 expression. The expression of E-cadherin, N-cadherin, and zinc finger protein (Snail) was detected using quantitative real-time polymerase chain reaction and Western blot at the mRNA and protein levels.
Results
The results show that the mechanism of HMGA2 action on kidney cancer cells is related to EMT, and this action is achieved by influencing the EMT marker proteins E-cadherin and N-cadherin. The mechanism where HMGA2 exerts its biological function is related to the transforming growth factor-β (TGF-β) signaling pathway, where HMGA2 is able to interact with Smad2 and Smad3. In the TGF-β signaling pathway, HMGA2 can bind and form a complex with Smad2 and Smad3 to induce the expression of the target gene, Snail, promote the production of Snail protein, and induce EMT in kidney cancer cells, thereby promoting the occurrence and development and metastasis of kidney cancer cells.
Conclusion
HMGA2 is closely related to the migration and invasive ability of kidney cancer cells and can promote EMT of kidney cancer cells by activating the intracellular TGF-β signaling pathway. In kidney cancer cells, the intracellular TGF-signaling pathway promotes EMT.
The influence of judging experience on the decision-making of race-walking referees : Evidence from eye tracking
Authors: zhi huijing , Yang Liu 
Published: March 2023

Abstract
This study aims to study the visual search strategy of experienced race-walking referees in the decision-making process. This study selected 20 novices and 13 experienced race-walking referees and divided them into expert and novice groups according to their ruling experience. The eye movement experiment material was a race walking video taken on the spot. The participants were asked to watch the video and respond to the athletes ' fouls or not. Tobbi X3-120 eye tracker recorded the behavioral data and eye movement data. The results show that experienced race-walking referees show superior decision-making performance, high accuracy, and short response time. In addition, we also observed the differences in gaze behavior between the two groups of subjects. The experienced race-walking referees gazed more, longer, and earlier on the knee and ankle regions. The visual images also showed that the expert's gaze trajectory was clear, targeted, and focused on critical areas. In general, experienced race-walking referees have expert advantages in penalty decision-making, manifested in higher behavioral performance and concise, efficient, and goal-oriented visual search features.
The Effects of Processing Conditions on Mechanical Properties of Inconel 718 Super-alloys Manufactured by Electron Beam Melting
Authors: Güler Ebru Saraloğlu , Semiz Mehmet 
Published: March 2023

Abstract
Additive Manufacturing (AM), also known as three-dimensional (3D) printing and rapid prototyping, is the technology of making solid objects by adding material layer by layer based on computer-aided design (CAD). Electron Beam Melting (EBM) technology, which is one of the AM technologies, is based on the principle of melting metal powders by a focused electron beam that provides high energy and temperature and is based on the formation of layers by the repetitive welding technique, which is made by joining one on top of the other. Inconel 718 is the most widely used nickel-based superalloy due to its excellent high temperature strength and good oxidation corrosion resistance up to high temperatures. The main areas of use are discs, shafts, cases, stators, blades, gaskets, supports, pipes and fasteners. The main subject of this thesis study is to investigate the effects of hot isostatic pressing and heat treatment by revealing the mechanical and physical properties of Inconel 718 with experiments to be applied. In this context, tensile test and density values ​​of commercial Inconel 718 samples produced by additive manufacturing, additive manufacturing + heat treatment, additive manufacturing + hot isostatic press + heat treatment were compared.
A Library of High-Entropy-Alloy Nanocrystals with Controlled Surface Atomic Arrangements for Catalysis
Authors: Yang Tung-Han , Hsiao Yueh-Chun , Wu Cheng-Yu , Huang Wen-Yang , Thang Ho Viet , Chi Chong-Chi , Zeng Wen-Jing , Gao Jia-Qi , Lin Chih-Yi , Lin Jui-Tai , Lee Chih-Heng , Mekhemer Islam M. A. , Lu Ming-Yen , Lu Ying-Rui , Chou Ho-Hsiu , Zhou Shan , Chen Hsin-Yi Tiffany , Cowan Alexander , Hung Sung-Fu , Yeh Jien-Wei 
Published: March 2023

Abstract
High-entropy-alloy (HEA) nanocrystals consisting of a minimum of five elements have recently emerged as a versatile family of catalysts due to immense chemical space and tunability1-3. However, there are no effective strategies for synthesizing libraries of HEA nanocrystals with controlled surface atomic structures of exposed facets for boosting catalytic performance4-19. Due to the distinct nucleation and growth kinetics of constituent metals and their distinctive crystal structures, it is incredibly challenging to confine five or more different metal species situated on the nanocrystal surface with a specific arrangement but also in a high-entropy random mixing state. Here we present a straightforward strategy to craft a library of facet-controlled HEA nanocrystals with up to ten dissimilar metallic elements (Pt, Pd, Ir, Ru, Rh, Os, Au, Fe, Co, and Ni) by solution-phase layer-by-layer epitaxial growth, enabling the design of 638 distinct catalysts with 5 to 10 elements in equimolar ratios. The subnanometer-thick solid-solution HEA atomic layers can be deposited epitaxially on nanocrystal seeds with {100} and {111} facets, thus achieving HEA shells with square and hexagonal atomic arrangements, respectively. The hollow HEA nanocages with ultrathin walls along a specific direction can be further fabricated via post-synthetic chemical etching. Three facet-dependent catalytic actives of HEA nanocrystals are discovered in electrocatalysis and photocatalysis, and their catalytic facets with real active sites are also identified by in situ synchrotron X-ray absorption spectroscopy and density-functional theory calculations. Our work enables facet engineering in the multi-elemental space and unveils the critical needs for their future development toward catalysis.
In-silico studies on hydration in EcoRI-cognate DNA complex
Authors: Mandal Sasthi Charan , Chakrabarti Jaydeb 
Published: March 2023

Abstract
Restriction endonucleases (REs) cleave DNA at specific site in presence of Mg2+ ion. Experiments further emphasize the role of hydration in metal ion specificity and sequence specificity of DNA cleavage. However, the relation between hydration and specificity has not been understood till date. This leads us to study via all-atom molecular dynamics (MD) simulations how the hydration around the scissile phosphate group changes in presence of Mg2+ and Ca2+ and depend on the DNA sequence. We observe the least number of hydrogen bonds around the scissile phosphate group in presence of Mg2+ ion. We further find that the hydrogen bonds decrease at the scissile phosphate on mutating one base pair in the cleavage region of the DNA in Mg2+ loaded EcoRI-DNA complex which makes the scissile phosphate group more accessible for the non-hydrogen bonded water molecules. We also perform steered MD simulations and observe that the rate of decrease of hydrogen bonds is slower in the mutated complex than the unmutated complex.
Three-dimensional measurement of the uterus on magnetic resonance images: development and performance analysis of an automated deep learning tool
Authors: Mulliez Daphné , Poncelet Edouard , Ferret Laurie , Hoeffel Christine , Hamet Blandine , Dang Lan Anh , Laurent Nicolas , Ramette Guillaume 
Published: March 2023

Abstract
Background
The aim of our study was to develop, validate, and test a deep learning (DL) tool for fully automated measurement of the three-dimensional size of the uterus on magnetic resonance imaging (MRI) and to compare it to manual reference measurement.
Materials and Methods
In this single-centre retrospective study, 845 cases were included for training and validation. The ground truth was a manual measurement of the uterus on magnetic resonance (MR) images. A deep learning tool using a convolutional neural network (CNN) with VGG-16/VGG-11 architecture was developed. The performance of the model was evaluated using the objective keypoint similarity (OKS), mean difference in millimetres, and coefficient of determination R² on a new set of 100 patients.
Results
The OKS of our artificial intelligence (AI) model was 0.92 (validation) and 0.96 (test). These performances show a strong correspondence of the positioning of the measurement points between the algorithm and radiologists. The average deviation and R² coefficient between the AI measurements and the manual ones were respectively 3.9 mm and 0.93 for two-points length, 3.7 mm and 0.94 for three-points length, 2.6 mm and 0.93 for width, 4.2 mm and 0.75 for thickness. Inter-radiologist variability was 1.4 mm. A three-dimensional automated measurement was obtained in 1.6 s.
Conclusion
Our deep learning model can locate the uterus on MR images and place measurement points on it to obtain its three-dimensional measurement with a very good correlation with manual measurements.
Prevalence and Predictors of Depression among Patients Taking Antiretroviral Drugs in Adama Hospital Medical College, Oromia Regional State, Ethiopia
Authors: Gebru Tessema , Ejara Daba , Yalew Aster , Deyassa Negussie 
Published: March 2023

AbstractBackground:Depression is the most frequently detected and avertible mental illness among people with human immunodeficiency syndrome, with two to four times higher rates than general populations. Currently, depression is measured to disturb 350 million people in the world. Therefore, the purpose of this study was to investigate predictors of depression among patients receiving Antiretroviral drugs.Objective:To assess the prevalence and predictors of depression among people taking Antiretroviral drugs at Adama Hospital Medical College.Methods:Institutional based cross-sectional study was employed from April 01 to September 30, 2021, at Adama Hospital Medical College, Oromia regional state, Ethiopia. A total of 420 individuals were selected via a systematic random sampling technique. Data was collected through a face-to-face interview, observation, and document review, then entered into EPI-info Version 7 and analyzed by SPSS version 21. A binary logistic regression model was used to determine the relationship between independent variables on the outcome variable. The variable with a p-value of less than 0.25 in the bivariate analysis was further entered into the multivariable analysis to control for potential confounders. Adjusted Odds Ratio (AOR) with 95% CI was used to measure association, and the variable with a p-value less than 0.05 was taken as statistically significant.Results: The prevalence of depressive symptoms was 52.4% (95% CI= 47.6-57.1). Employment status [AOR=0.22(95% CI= 0.13-0.36)], the patient’s most recent CD4 count [AOR=6.99 (95% CI=2.81-17.38)], months on ART [AOR=5.05 (95% CI =2.38-10.74)] and chronic non-communicable diseases [AOR=7.90 (95% CI = 4.21-14.85)] were the factors significantly associated with depression among HIV positive patientsConclusion:highest proportion of HIV-positive patients taking ART drugs had depressive symptoms. Employment was found to be preventive while low CD4 count, starting ART therapy recently, and presence of chronic non-communicable diseases were found with increased odds of depression among HIV-positive patients taking ART.
Multi-slice CT features predict pathological risk classification in gastric stromal tumors larger than 2 cm: a retrospective multicenter study
Authors: Wang Sikai , Dai Ping , Si Guangyan , Zeng Mengsu , Wang Mingliang 
Published: March 2023

Abstract
Background
Accurate risk stratification for gastric stromal tumors (GSTs) has become increasingly important. The Armed Forces Institute of Pathology (AFIP) had higher accuracy and reliability in prognostic assessment and treatment strategies for patients with GSTs. This study aimed to investigate the feasibility of multi-slice CT (MSCT) features of GSTs in predicting AFIP risk classification.
Methods
Clinical data and MSCT features of 424 patients with solitary GSTs were retrospectively reviewed. According to pathological AFIP risk criteria, 424 GSTs were divided into low-risk group (n = 282), moderate-risk group (n = 72) and high-risk group (n = 70). Clinical data and MSCT features of GSTs were compared among the three groups.
Results
We found significant differences in tumor location, morphology, necrosis, ulceration, growth pattern, feeding artery, vascular-like enhancement, fat positive sign around GSTs, CT value in venous phase, CT value increment in venous phase, longest diameter, and maximum short diameter (p < 0.05). Two nomogram model were successfully constructed to predict the risk of GSTs. Low- vs high-risk group, the independent risk factors of high-risk GSTs included location, ulceration, longest diameter; The area under the receiver operating characteristic curve (AUC) of prediction model was 0.911 (95% CI: 0.872–0.951 ), the sensitivity and the specificity were 80.0% and 89.0%, respectively. Moderate- vs high-risk group, morphology, necrosis and feeding artery were independent risk factors of high-risk of GSTs, with an AUC value of 0.826 (95% CI: 0.759–0.893), the sensitivity and the specificity were 85.7% and 70.8%, respectively.
Conclusion
MSCT features of GSTs and nomogram model have great practical value in predicting pathological AFIP risk classification between high risk and non-high risk groups before surgery. There is limitations for differentiating the low- and moderate-risk groups.
Enhanced Soil Liquefaction Potential Estimation using Machine Learning and Web-Based Platform
Authors: Vasegh Maleki , Dehghanbanadaki Ali , Motamedi Shervin 
Published: March 2023

Abstract
In this study, a new web-based platform was developed for fast estimation of soil liquefaction potential (SLP). The geotechnical results from 47 boreholes in the north of Iran were collected over three years to create an estimator model. The dataset included information on SPT, soil type, strength parameters, and water content. Python libraries Pycaret and Gradio were used to develop the model for SLP. A set of pipeline codes were applied to base classifiers, including 13 different machine learning models such as the Ada boost classifier (ad), decision tree classifier (dt), gradient boosting classifier (gb), the k-neighbors classifier (knn), light gradient boosting machine (lightgbm) and random forest classifier (rf). The results show that the lightgbm model outperformed the other applied machine learning classifiers with accuracy = 0.946, AUC = 0.982, and F1-score = 0.9. The proposed model was then used as the primary element of the web-based application, providing a helpful tool for geotechnical engineers to determine SLP.