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science, Engineering and Business for Sustainable Development Goals (SEB-SDG), International Conference on

作者： Damola Gideon Akinola Emmanuel Adetiba Abdultaofeek Abayomi Uche Nnaji Surendra Thakur Sibusiso Moyo Department of Electrical and Information Engineering Covenant Applied Informatics and Communications African Center of Excellence Covenant University Ota Nigeria HRA Institute for Systems Science Durban University of Technology Durban South Africa Department of Information and Communication Technology Mangosuthu University of Technology Durban South Africa Dept. of Computer and Information Science Covenant Applied Informatics and Communications African Center of Excellence Covenant University Ota Nigeria KZN e-Skills CoLab Durban University of Technology Durban South Africa School for Data Science and Computational Thinking and Department of Mathematical Sciences Stellenbosch University Stellenbosch South Africa

ISBN: (数字)9798350358155

ISBN: (纸本)9798350358162

The emergence of cloud computing technology has motivated a very high number of users in different organizations to access its services in running and delivering their various operations and services. However, this surge of cloud users has led to the problem of uneven load sharing among the cloud computing infrastructures. As a result, federated cloud infrastructure was initiated to provide more cloud computing resources to accommodate more cloud users’ requests and also to provide equal requests mapping with the available cloud resources. Nevertheless, the issue of unequal allocation of requests within the datacenter(s) that makes up the federated cloud environment still persists. This research work presents an intra-datacenter load balancing algorithm in a federated cloud environment named; the intra-balancer adapted throttled algorithm to evenly distribute requests in each datacenter that formulate the federated cloud infrastructures. The simulation of the intra-balancer was carried out in CloudAnalyst, the results of the implementation showed that the intra-balancer outperformed the Round-Robin and ESCE with 98.93ms and 2.26ms for the response and processing time respectively. The results assert that the intra-balancer algorithm provides a better load balancing solution in a federated cloud environment.

关键词： Computers Cloud computing Organizations Load management Resource management Time factors Task analysis

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FedMonitor: An Implementation Architecture for Monitoring of Resources and Events'Notifications on Federated Cloud Computing Infrastructures

FedMonitor: An Implementation Architecture for Monitoring of...

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International Conference on Emerging Trends in Networks and Computer Communications (ETNCC)

作者： Emmanuel Adetiba Uche Nnaji John S. Wejin Festus Ojesanmi Matthew B. Akanle Priscilla O. Ajayi Faith O. Sweetwiliams Surendra C. Thakur Ezekiel F. Adebiyi Department of Electrical and Information Engineering and Covenant Applied Informatics & Communication African Center of Excellene(CApIC-ACE) Covenant University Ota Nigeria HRA Institute for Systems Science Durban University of Technology Durban South Africa Department of Computer and Information Science & CApIC-ACE Covenant University Ota Nigeria Department of Electrical and Information Engineering & CApIC-ACE Covenant University Jalingo Nigeria Department of Computer Science Tareba State University Jalingo Nigeria Covenant Applied Informatics & Communication African Center of Excellene(CApIC-ACE) Covenant University Ota Nigeria Department of Electrical and Information Engineering Covenant University & CApIC-ACE Covenant University Ota Nigeria Center for Systems and Information Services & CApIC-ACE Covenant University Ota Nigeria Department of Information Technology and KZN e-Skills Co-Laboratory Durban University of Technology Durban South Africa Covenant University Bioinformatics Research (CUBRe) Covenant University Ota Ogun State Nigeria African Center of Excellence in Bioinformatics & Data Intensive Science Makerere University Kampala Uganda

ISBN: (数字)9798350353266

ISBN: (纸本)9798350353273

In the evolving landscape of cloud computing, federated cloud infrastructures present unique challenges and opportunities for resource and application monitoring. Monitoring the diverse array of cloud resources and applications within a federated cloud environment is crucial for delivering consistent Quality of Service (QoS) and continuous oversight across various cloud applications and infrastructure. Despite the various successes documented in the literature on multi-cloud monitoring, existing frameworks have not fully explored or provided enough insights into centralized monitoring of resources, applications, and network devices in a federated cloud environment. This paper introduces FedMonitor, an implementation architecture designed to enhance the monitoring and notification capabilities in federated cloud environments by building on the theoretical ideals in our earlier work (i.e. FEDARGOS-V1). FedMonitor leverages Prometheus and Grafana to crawl, manage and visualize metrics from diverse software services, hardware resources, and network devices within a federated cloud environment. The results demonstrate hat FedMonitor improves the effectiveness of resource and application monitoring in federated cloud environments.

关键词： Measurement Cloud computing Visualization Computer architecture Quality of service Production Software Real-time systems Stakeholders Monitoring

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Killer cell immunoglobulin receptor diversity and its relevance in the human host’s response to HIV infection in african populations

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Translational Medicine Communications 2023年第1期8卷 1-9页

作者： John Mukisa Marion Amujal Obondo J. Sande Moses L. Joloba David P. Kateete Daudi Jjingo Graeme Mardon Neil Hanchard Mogomotsi Matshaba Jill A. Hollenbach Department of Immunology and Molecular Biology College of Health Sciences Makerere University P.O.BOX 7072 Kampala Uganda College of Computing and Information Sciences Makerere University Kampala Uganda African Center of Excellence in Bioinformatics and Data Science Infectious Diseases Institute (IDI) Makerere University Kampala Uganda Department of Molecular and Human Genetics and Department of Pathology and Immunology Baylor College of Medicine Houston TX USA National Human Genome Research Institute Bethesda MD USA Botswana-Baylor Children’s Clinical Centre of Excellence P/Bag BR 129 Gaborone Botswana Department of Neurology and Department of Epidemiology and Biostatistics University of California San Francisco San Francisco California 94158 USA

Host response to the human immune deficiency virus (HIV) involves both the innate and adaptive immune systems. As part of the innate immune system, the killer cell immunoglobulin-like receptors (KIRs) found on natural killer cells and some T-lymphocytes are genetically diverse and play key functions in the host response against viral pathogens. In the last decade, there has been substantial growth in sequencing technologies and bioinformatics capacity to understand human host genetics, including KIR. However, there is limited literature on how the KIR diversity informs the perspectives on HIV disease states in understudied african settings. A better understanding of the effects of KIRs on the host’s immune response to HIV in african settings is essential to inform strategies to develop more effective therapies and vaccines to improve health among people living with HIV (PLWH). In this paper, we review KIR diversity, the role of KIR immunogenetic variation in the human host response to HIV, discuss current perspectives on the studies to assess the relationship between KIR diversity and the HIV disease continuum, and suggest future research prospects.

关键词： Killer cell immunoglobulin-like receptors ( ) Diversity Human immune deficiency virus (HIV) bioinformatics

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From mechanism to medicine: The progress and potential of epigenetics in osteoarthritis

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Osteoarthritis and Cartilage Open 2025年第3期7卷 100621-100621页

作者： Jack B. Roberts Jason S. Rockel Rick Mulders Terence D. Capellini C. Thomas Appleton Douglas H. Phanstiel Rik Lories Jeroen Geurts Shabana Amanda Ali Nidhi Bhutani Laura Stone Yenisel Cruz-Almeida Igor Jurisica Cindy G. Boer Yolande F.M. Ramos Sarah J. Rice Mohit Kapoor Biosciences Institute Newcastle University Newcastle upon Tyne United Kingdom Division of Orthopedics Osteoarthritis Research Program Schroeder Arthritis Institute University Health Network and Krembil Research Institute University Health Network Toronto ON Canada Department of Biomedical Data Sciences Section Molecular Epidemiology Leiden University Medical Center Leiden The Netherlands Department of Human Evolutionary Biology Harvard University Cambridge MA USA Bone and Joint Institute and Department of Medicine Schulich School of Medicine and Dentistry Western University London Canada Curriculum in Bioinformatics and Computational Biology University of North Carolina Chapel Hill NC USA Laboratory of Tissue Homeostasis and Disease Skeletal Biology and Engineering Research Centre Department of Development and Regeneration KU Leuven Leuven Belgium Division of Rheumatology University Hospitals Leuven Leuven Belgium Rheumatology Department of Musculoskeletal Medicine Lausanne University Hospital and University of Lausanne (CHUV-UNIL) Lausanne Switzerland Bone and Joint Center Henry Ford Health + Michigan State University Health Sciences Detroit MI USA Department of Orthopaedic Surgery Stanford School of Medicine Stanford CA USA Department of Anesthesiology School of Medicine University of Minnesota Minneapolis MN USA Pain Research and Intervention Center of Excellence (PRICE) at the University of Florida Gainesville FL USA Department of Medical Biophysics and Computer Science University of Toronto Toronto ON Canada Department of Internal Medicine Genomics Medicine Center Erasmus MC University Medical Center Rotterdam the Netherlands Department of Laboratory Medicine and Pathobiology University of Toronto Toronto ON Canada Department of Surgery University of Toronto Toronto ON Canada

Objective Osteoarthritis (OA) is a chronic, degenerative disease of the articular joints. The disease presents an enormous clinical and economic burden globally, due in part to the lack of disease modifying therapies. For over a decade, OA researchers have been working to determine epigenetic mechanisms underlying the disease to better understand pathology, identify biomarkers of progression, and pinpoint novel targets for therapeutic intervention. Design This article presents a summary of the 3rd International Workshop on the Epigenetics of Osteoarthritis held in Toronto, Ontario, Canada, in September 2024. The purpose of this meeting was to gather the international community to discuss the status of OA epigenetic research and share expertise on innovative techniques for future. Results Since the two previous meetings, there has been increasing adoption of advanced single-cell and spatial sequencing technologies and bioinfomatic analyses. Furthermore, investigations of multiple joint tissues has highlighted the shifting paradigm from OA as a cartilage centric disease to the consideration of all joint tissues. Conclusions The workshop provided a unique opportunity for early-career researchers to expand their network, and for all participants to discuss new or improved approaches to advance the field, including international consortia and data sharing. The highlights and outcomes from this OA epigenetics workshop are described in this report.

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Trends and determinants of health facility childbirth service utilization among mothers in urban slums of Nairobi, Kenya

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Global Epidemiology 2020年 2卷

作者： Atahigwa, Catherine Kadengye, Damazo T. Iddi, Samuel Abrams, Steven Van Rie, Annelies University of Antwerp Global Health Institute Campus Drie Eiken Universiteitsplein 1 Wilrijk 2610 Belgium African Population and Health Research Center APHRC Campus Manga Close Off Kirawa Road P.O. Box 10787-00100 Nairobi Kenya Center for Statistics Interuniversity Institute for Biostatistics and statistical Bioinformatics Data Science Institute UHasselt Agoralaan Gebouw D Diepenbeek Belgium Department of Statistics and Actuarial Science Accra Ghana

High maternal mortality remains a challenge for the attainment of the third Sustainable Development Goal in Sub-Saharan Africa. In Kenya, maternal mortality ratio remains high at 362 deaths per 100,000 live births. Utilization of health facility childbirth services ensures safe birth and is vital for the reduction of maternal mortality. However, this can be greatly affected by socioeconomic and geographical inequalities. In this study, we assess the trends and determinants of health facility childbirth service utilization among women giving birth in the urban slums of Nairobi, Kenya. data were obtained from the Nairobi Urban Health and Demographic Surveillance System (NUHDSS) comprising 19,469 births observed between 2003 and [19]. A logistic regression model, with parameter estimation using a generalized estimating equations (GEE) approach, was used to assess factors associated with health facility childbirth. About 81% of the births occurred at health facilities while 19% were occurring at home or outside a health facility. The results further indicated that, education, parity, and relationship to head of households were associated with health facility childbirth. Increasing awareness of the mothers about the benefits of health facility childbirth service utilization and the risks of home childbirth should be given extra attention by health practitioners during antenatal care visits. © 2020 The Authors

关键词： Healthcare childbirth Maternal mortality Nairobi NUHDSS Slums

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Author Correction: Single nucleotide polymorphisms are associated with strain-specific virulence differences among clinical isolates of Cryptococcus neoformans

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Nature communications 2025年第1期16卷 2510页

作者： Katrina M Jackson Thomas J Y Kono Jovany J Betancourt Yina Wang Kisakye D Kabbale Minna Ding Perry Kezh Grace Ha J Marina Yoder Sophie R Fulton Liliane Mukaremera Peter Tiffin Asiya Gusa David B Meya R Blake Billmyre Chaoyang Xue Kirsten Nielsen Department of Microbiology and Immunology University of Minnesota Minneapolis MN USA. Pathogen and Microbiome Institute Northern Arizona University Flagstaff AZ USA. Minnesota Supercomputing Institute University of Minnesota Minneapolis MN USA. Institute of Computational Cancer Biology at the University Hospital of Cologne University of Cologne Cologne Germany. Public Health Research Institute and Department of Microbiology Biochemistry and Molecular Genetics New Jersey Medical School Rutgers University Newark NJ USA. Infectious Diseases Institute and School of Medicine College of Health Sciences Makerere University Kampala Uganda. The African Center of Excellence in Bioinformatics and Data Intensive Sciences Kampala Uganda. Center for One Health Research Department of Biomedical Sciences and Pathology Virginia Tech University Blacksburg VA USA. Department of Biosciences Faculty of Health and Life Sciences Medical Research Council Centre for Medical Mycology at the University of Exeter Exeter UK. Department of Plant and Microbial Biology University of Minnesota St. Paul MN USA. Department of Molecular Genetics and Microbiology Duke University Durham NC USA. Division of Infectious Diseases and International Medicine University of Minnesota Minneapolis MN USA. Departments of Pharmaceutical and Biomedical Sciences/Infectious Disease College of Pharmacy/College of Veterinary Medicine University of Georgia Athens GA USA. Department of Microbiology and Immunology University of Minnesota Minneapolis MN USA. kirstennielsen@vt.edu. Center for One Health Research Department of Biomedical Sciences and Pathology Virginia Tech University Blacksburg VA USA. kirstennielsen@vt.edu.

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A universal language for finding mass spectrometry data patterns

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Nature methods 2025年 2025 May 12页

作者： Tito Damiani Alan K Jarmusch Allegra T Aron Daniel Petras Vanessa V Phelan Haoqi Nina Zhao Wout Bittremieux Deepa D Acharya Mohammed M A Ahmed Anelize Bauermeister Matthew J Bertin Paul D Boudreau Ricardo M Borges Benjamin P Bowen Christopher J Brown Fernanda O Chagas Kenneth D Clevenger Mario S P Correia William J Crandall Max Crüsemann Eoin Fahy Oliver Fiehn Neha Garg William H Gerwick Jeffrey R Gilbert Daniel Globisch Paulo Wender P Gomes Steffen Heuckeroth C Andrew James Scott A Jarmusch Sarvar A Kakhkhorov Kyo Bin Kang Nikolas Kessler Roland D Kersten Hyunwoo Kim Riley D Kirk Oliver Kohlbacher Eftychia E Kontou Ken Liu Itzel Lizama-Chamu Gordon T Luu Tal Luzzatto Knaan Helena Mannochio-Russo Michael T Marty Yuki Matsuzawa Andrew C McAvoy Laura-Isobel McCall Osama G Mohamed Omri Nahor Heiko Neuweger Timo H J Niedermeyer Kozo Nishida Trent R Northen Kirsten E Overdahl Johannes Rainer Raphael Reher Elys Rodriguez Timo T Sachsenberg Laura M Sanchez Robin Schmid Cole Stevens Shankar Subramaniam Zhenyu Tian Ashootosh Tripathi Hiroshi Tsugawa Justin J J van der Hooft Andrea Vicini Axel Walter Tilmann Weber Quanbo Xiong Tao Xu Tomáš Pluskal Pieter C Dorrestein Mingxun Wang Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences Prague Czech Republic. Metabolomics Core Facility Immunity Inflammation and Disease Laboratory Division of Intramural Research National Institute of Environmental Health Sciences National Institutes of Health Research Triangle Park NC USA. Department of Chemistry and Biochemistry University of Denver Denver CO USA. Functional Metabolomics Lab CMFI Cluster of Excellence University of Tuebingen Tuebingen Germany. Department of Biochemistry University of California Riverside Riverside CA USA. Department of Pharmaceutical Sciences Skaggs School of Pharmacy and Pharmaceutical Sciences University of Colorado Anschutz Medical Campus Aurora CO USA. Collaborative Mass Spectrometry Innovation Center Skaggs School of Pharmacy and Pharmaceutical Sciences University of California San Diego La Jolla CA USA. Biologicals and Natural Products Discovery Crop Protection R&D Corteva Agrisciences Indianapolis IN USA. BioMolecular Sciences School of Pharmacy University of Mississippi Oxford MS USA. Pharmacognosy Faculty of Pharmacy Al-Azhar University Nasr City Egypt. Department of Fundamental Chemistry Institute of Chemistry University of São Paulo São Paulo Brazil. Department of Chemistry Case Western Reserve University Cleveland OH USA. Walter Mors Institute of Research on Natural Products Federal University of Rio de Janeiro Rio de Janeiro Brazil. Environmental Genomics and Systems Biology Division Lawrence Berkeley National Lab Berkeley CA USA. The Joint Genome Institute Lawrence Berkeley National Lab Berkeley CA USA. Mass Spectrometry Center of Expertise Regulatory and Stewardship Corteva Agrisciences Indianapolis IN USA. Biologicals and Natural Products Crop Protection R&D Corteva Agrisciences Indianapolis IN USA. Department of Chemistry - BMC Science for Life Laboratory Uppsala University Uppsala Sweden. Clinical Biomarkers Laboratory School of Medicine Emory Univers

Despite being information rich, the vast majority of untargeted mass spectrometry data are underutilized; most analytes are not used for downstream interpretation or reanalysis after publication. The inability to dive into these rich raw mass spectrometry datasets is due to the limited flexibility and scalability of existing software tools. Here we introduce a new language, the Mass Spectrometry Query Language (MassQL), and an accompanying software ecosystem that addresses these issues by enabling the community to directly query mass spectrometry data with an expressive set of user-defined mass spectrometry patterns. Illustrated by real-world examples, MassQL provides a data-driven definition of chemical diversity by enabling the reanalysis of all public untargeted metabolomics data, empowering scientists across many disciplines to make new discoveries. MassQL has been widely implemented in multiple open-source and commercial mass spectrometry analysis tools, which enhances the ability, interoperability and reproducibility of mining of mass spectrometry data for the research community.

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How well do experience curves predict technological progress? A method for making distributional forecasts∗

arXiv

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arXiv 2017年

作者： Lafond, François Bailey, Aimee Gotway Bakker, Jan David Rebois, Dylan Zadourian, Rubina McSharry, Patrick Farmer, J. Doyne Institute for New Economic Thinking Oxford Martin School Smith School for Enterprise and the Environment University of Oxford London Institute for Mathematical Sciences U.S. Department of Energy Department of Economics University of Oxford Mathematical Institute University of Oxford Max Planck Institute for the Physics of Complex Systems Germany Carnegie Mellon University Africa Rwanda African Center of Excellence in Data Science University of Rwanda Oxford Man Institute of Quantitative Finance University of Oxford Computer Science Department University of Oxford Santa Fe Institute United States

Experience curves are widely used to predict the cost benefits of increasing the deployment of a technology. But how good are such forecasts? Can one predict their accuracy a priori? In this paper we answer these questions by developing a method to make distributional forecasts for experience curves. We test our method using a dataset with proxies for cost and experience for 51 products and technologies and show that it works reasonably well. The framework that we develop helps clarify why the experience curve method often gives similar results to simply assuming that costs decrease exponentially. To illustrate our method we make a distributional forecast for prices of solar photovoltaic modules. Copyright © 2017, The Authors. All rights reserved.

关键词： Forecasting

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Climate-influenced vector-borne diseases in Africa:a call to empower the next generation of african researchers for sustainable solutions

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Infectious Diseases of Poverty 2024年第2期13卷 83-92页

作者： Judicaël Obame-Nkoghe Adjoavi Esse Agossou Gerald Mboowa Basile Kamgang Cyril Caminade Dawn C.Duke Andrew Karanja Githeko Obed M.Ogega Nestor Engone Elloué Fatou Bintou Sarr DieudonnéNkoghe Pierre Kengne Nicaise T.Ndam Christophe Paupy Moses Bockarie Patricks Voua Otomo Molecular and Cellular Biology Laboratory(LabMC) Biology DepartmentUniversity of Science and Technology of MasukuBP 901FrancevilleGabon Ecology and Health Research Unit Interdisciplinary Center for Medical Research of FrancevilleBP 769FrancevilleGabon Department of Zoology and Entomology Faculty of Natural and Agricultural SciencesUniversity of the Free StatePrivate Bag x13Phuthaditjhaba 9866Republic of South Africa Laboratory of Pharmacology and Improved Traditional Medicines Department of Animal PhysiologyFaculty of Science and TechnologyUniversity of Abomey-CalaviBP 526CotonouBenin The African Center of Excellence in Bioinformatics and Data-Intensive Sciences Infectious Diseases InstituteCollege of Health SciencesMakerere UniversityP.O Box 22418KampalaUganda Africa Centers for Disease Control and Prevention African Union CommissionRoosevelt StreetP.O.Box 3243W21 K19 Addis AbabaEthiopia Centre for Research in Infectious Diseases P.O.Box 13591YaoundéCameroon Earth System Physics Department The Abdus Salam International Centre for Theoretical PhysicsTriesteItaly Africa Research Excellence Fund 99 Charterhouse StreetLondon EC1M 6HRUK Community Health Support Program P.O.Box 872Kisumu 40100Kenya The African Academy of Sciences NairobiKenya Center for Phylosophical Studies and Research(CERP) Omar Bongo University(UOB)BP 13131LibrevilleGabon UMRED Health Training and Research UnitUniversity of Iba Der Thiam of ThièsBP 967ThièsSenegal National Parasitic Diseases Control Program Ministry of HealthLibrevilleGabon MIVEGEC Univ.MontpellierCNRSIRDMontpellierFrance MERIT IRDParis CitéUniversity75006 ParisFrance Department of Parasitology Noguchi Memorial Institute for Medical ResearchUniversity of GhanaLG 54AccraGhana School of Community Health Sciences Njala UniversityBoSierra Leone

We look at the link between climate change and vector-borne diseases in low-and middle-income countries in *** large endemicity and escalating threat of diseases such as malaria and arboviral diseases,intensified by climate change,disproportionately affects vulnerable communities *** highlight the urgency of prioritizing research and development,advocating for robust scientific inquiry to promote adaptation strategies,and the vital role that the next generation of african research leaders will play in addressing these *** significant challenges such as funding shortages within countries,various pan-african-oriented funding bodies such as the african Academy of sciences,the Africa Research excellence Fund,the Wellcome Trust,the *** Institutes of Health,and the Bill and Melinda Gates Foundation as well as initiatives such as the african Research Initiative for Scientific excellence and the Pan-african Mosquito Control Association,have empowered(or are empowering)these researchers by supporting capacity building activities,including continental and global networking,skill development,mentoring,and african-led *** article underscores the urgency of increased national investment in research,proposing the establishment of research government agencies to drive evidence-based *** between governments and scientific communities,sustained by pan-african funding bodies,is *** these efforts,african nations are likely to enhance the resilience and adaptive capacity of their systems and communities by navigating these challenges effectively,fostering scientific excellence and implementing transformative solutions against climate-sensitive vector-borne diseases.

关键词： Climate change Vector-borne diseases Africa Environmental justice Research and development Pan-african funding initiatives

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Lamotrigine therapy for bipolar depression: Analysis of self-reported patient data

arXiv

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arXiv 2020年

作者： Nzeyimana, Antoine Saunders, Kate E.A. Geddes, John R. McSharry, Patrick E. Department of Geography University of Oregon EugeneOR United States Carnegie Mellon University Africa Kigali Rwanda University Department of Psychiatry Warneford Hospital Oxford United Kingdom Oxford Health NHS Foundation Trust Warneford Hospital Oxford United Kingdom African Center of Excellence in Data Science University of Rwanda Kigali Rwanda Oxford-Man Institute of Quantitative Finance University of Oxford Oxford United Kingdom Oxford Internet Institute University of Oxford Oxford United Kingdom Department of Geography University of Oregon 1251 University of Oregon Eugene OR97403-1251 United States

Background: Depression in people with bipolar disorder is a major cause of long-term disability, possibly leading to early mortality and currently, limited safe and effective therapies exist. Although existing monotherapies such as quetiapine have limited proven efficacy and practical tolerability, treatment combinations may lead to improved outcomes. Lamotrigine is an anticonvulsant currently licensed for the prevention of depressive relapses in individuals with bipolar disorder. A double-blinded randomized placebo-controlled trial (comparative evaluation of Quetiapine-Lamotrigine [CEQUEL] study) was conducted to evaluate the efficacy of lamotrigine plus quetiapine versus quetiapine monotherapy in patients with bipolar type I or type II disorders. Objective: Because the original CEQUEL study found significant depressive symptom improvements, the objective of this study was to reanalyze CEQUEL data and determine an unbiased classification accuracy for active lamotrigine versus placebo. We also wanted to establish the time it took for the drug to provide statistically significant outcomes. Methods: Between October 21, 2008 and April 27, 2012, 202 participants from 27 sites in United Kingdom were randomly assigned to two treatments;101: lamotrigine, 101: placebo. The primary variable used for estimating depressive symptoms was based on the Quick Inventory of Depressive Symptomatology—self report version 16 (QIDS-SR16). The original CEQUEL study findings were confirmed by performing t test and linear regression. Multiple features were computed from the QIDS-SR16 time series;different linear and nonlinear binary classifiers were trained to distinguish between the two groups. Various feature-selection techniques were used to select a feature set with the greatest explanatory power;a 10-fold cross-validation was used. Results: From weeks 10 to 14, the mean difference in QIDS-SR16 ratings between the groups was −1.6317 (P=.09;sample size=81, 77;95% CI −0.2403 to 3.5036). F

关键词： Time series

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