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Predicting Purchasing Behavior on E-Commerce Platforms: A Regression Model Approach for Understanding User Features that Lead to Purchasing

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International Journal of Communications, Network and System Sciences 2024年第6期17卷 81-103页

作者： Abraham Jallah Balyemah Sonkarlay J. Y. Weamie Jiang Bin Karmue Vasco Jarnda felix jwakdak joshua College of Computer Science and Engineering Hunan University Changsha China Department of Health Inspection and Quarantine Xiangya School of Public Health Central South University Changsha China

This research introduces a novel approach to improve and optimize the predictive capacity of consumer purchase behaviors on e-commerce platforms. This study presented an introduction to the fundamental concepts of the logistic regression algorithm. In addition, it analyzed user data obtained from an e-commerce platform. The original data were preprocessed, and a consumer purchase prediction model was developed for the e-commerce platform using the logistic regression method. The comparison study used the classic random forest approach, further enhanced by including the K-fold cross-validation method. Evaluation of the accuracy of the model’s classification was conducted using performance indicators that included the accuracy rate, the precision rate, the recall rate, and the F1 score. A visual examination determined the significance of the findings. The findings suggest that employing the logistic regression algorithm to forecast customer purchase behaviors on e-commerce platforms can improve the efficacy of the approach and yield more accurate predictions. This study serves as a valuable resource for improving the precision of forecasting customers’ purchase behaviors on e-commerce platforms. It has significant practical implications for optimizing the operational efficiency of e-commerce platforms.

关键词： E-Commerce Platform Purchasing Behavior Prediction Logistic Regression Algorithm

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Factors Associated with Sample Rejection for CD4+/CD8+ T Cell Count Analyses at the Kenyatta National Hospital Comprehensive Care Center Laboratory, Kenya

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World Journal of AIDS 2021年第4期11卷 181-188页

作者： Moherai Wilfred felix joshua Nyagol Walter Mwanda Department of Human Pathology Thematic Unit of Immunology University of Nairobi Nairobi Kenya Department of Human Pathology Thematic Unit of Hematology and Blood Transfusion Unit University of Nairobi Nairobi Kenya

Background: The appropriate time to initiate antiretroviral therapy (ART) in HIV/AIDS patients is determined by measurement of CD4+/CD8+ T cell count. The CD4/CD8+ T cell count is also useful, together with viral load, in monitoring disease progression and effectiveness treatment regimens. Several factors may contribute to sample rejection during the CD4+/CD8+ T cells count, resulting in negative effects on patient management. Objective: Evaluate the causes for CD4+CD8+ T cell count sample rejection at the Kenyatta National Hospital Comprehensive Care Center Laboratory. Method: A retrospective cross-sectional study was conducted between 2018 and 2020. Data was obtained from the “rejected samples” for PartecR FlowCyp flow cytometry file. Designed data collection sheet was used for data capture. A total of 3972 samples were submitted for CD4+/CD8+ T cell count during the study period. Causes for sample rejection were numbered 1 to 12, each representing a reason for sample rejection. Number 1 was sub-categorized into clotted, hemolyzed, short-draw and lipemic. Data was analyzed using excel, and presented using tables, graphs and pie charts. Approval to conduct the study was obtained from KNH/UoN ERC. Results: In the study period, 81/3972 (2.0%) samples were rejected. Samples submitted more than 48 hours after collection were mostly rejected. Other factors included improper collection technique, delayed testing, patient identification error and incorrect use of vacutainer. A combination of clotted samples, specimen submission more than 48 hours caused the most frequent sample rejection, followed with combination of specimen submission more than 48 hours, delayed testing and delayed specimen processing. Together, clotted samples, incorrect vacutainer and poor specimen label caused the least sample rejection. Conclusion: Sample re

关键词： Sample Rejection Causes CD4/CD8+ T Cell Count Flow Cytometry

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finDr:A web server for in silico D-peptide ligand identification

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Synthetic and Systems Biotechnology 2021年第4期6卷 402-413页

作者： Helena Engel felix Guischard Fabian Krause Janina Nandy Paulina Kaas Nico Hofflin Maja Kohn Normann Kilb Karsten Voigt Steffen Wolf Tahira Aslan Fabian Baezner Salom´e Hahne Carolin Ruckes joshua Weygant Alisa Zinina Emir Bora Akmeriç Enoch B.Antwi Dennis Dombrovskij Philipp Franke Klara L.Lesch Niklas Vesper Daniel Weis Nicole Gensch Barbara Di Ventura Mehmet Ali Oztürk Signalling Research Centres BIOSS and CIBSS University of FreiburgSchanzlestr.1879104FreiburgGermany Institute of Biology III Faculty of BiologyUniversity of FreiburgSchanzlestr.179104FreiburgGermany Institute of Biology II Faculty of BiologyUniversity of FreiburgSchanzlestr.179104FreiburgGermany AG Roth-Lab for MicroarrayCopying ZBSA-Centre for Biological Systems AnalysisUniversity of FreiburgHabsburgerstrasse 4979104FreiburgGermany Biomolecular Dynamics Institute of PhysicsUniversity of FreiburgHermann-Herder-Strasse 3a79104FreiburgGermany Core Facility Signalling Factory Centre for Biological Signaling Studies(BIOSS)University of FreiburgSchanzlestr.1879104FreiburgGermany Spemann Graduate School of Biology and Medicine(SGBM) University of FreiburgAlbertstraße 19A79104FreiburgGermany Internal Medicine IV Department of MedicineMedical CenterUniversity of FreiburgHugstetter Straße 5579106FreiburgGermany Institute for Biochemistry University of FreiburgAlbertstr.2179104FreiburgGermany

In the rapidly expanding field of peptide therapeutics,the short in vivo half-life of peptides represents a considerable limitation for drug action.D-peptides,consisting entirely of the dextrorotatory enantiomers of naturally occurring levorotatory amino acids(AAs),do not suffer from these shortcomings as they are intrinsically resistant to proteolytic degradation,resulting in a favourable pharmacokinetic *** experimentally identify D-peptide binders to interesting therapeutic targets,so-called mirror-image phage display is typically performed,whereby the target is synthesized in D-form and L-peptide binders are screened as in conventional phage *** technique is extremely powerful,but it requires the synthesis of the target in D-form,which is challenging for large *** we present finDr,a novel web server for the computational identification and optimization of D-peptide ligands to any protein structure(https://***/).finDr performs molecular docking to virtually screen a library of helical 12-mer peptides extracted from the RCSB Protein Data Bank(PDB)for their ability to bind to the *** a separate,heuristic approach to search the chemical space of 12-mer peptides,finDr executes a customizable evolutionary algorithm(EA)for the de novo identification or optimization of D-peptide *** a proof of principle,we demonstrate the validity of our approach to predict optimal binders to the pharmacologically relevant target phenol soluble modulin alpha 3(PSMα3),a toxin of methicillin-resistant Staphylococcus aureus(MRSA).We validate the predictions using in vitro binding assays,supporting the success of this *** to conventional methods,finDr provides a low cost and easy-to-use alternative for the identification of D-peptide ligands against protein targets of choice without size *** believe finDr will facilitate D-peptide discovery with implications in biotechnology and biomedicine.

关键词： D-peptide Web server Evolutionary algorithm Peptide design Molecular docking Mirror-image phage display

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