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Introduction: Hydrocephalus and myelomeningocele (MMC) place disproportionate burdens of disease on low-income and middle-income countries (LMICs). MMC-associated hydrocephalus and its sequelae result in a spectrum of severely devastating clinical manifestations, for which LMICs are disproportionately unprepared in terms of human, capital and technological resources. This study aims to review and compare the management and outcomes of infant MMC-associated hydrocephalus in LMICs and high-income countries. Methods and analysis: This systematic review and meta-analysis will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines. The following databases will be searched without restrictions on language, publication date or country of origin: EMBASE, MEDLINE, The Cochrane Library, Global Index Medicus, African Journals Online and SciELO. All peer-reviewed studies of primary data reporting management and outcomes of infant MMC-associated hydrocephalus will be included. Where high-quality homogeneous studies exist, meta-analyses will be conducted to compare the management and outcomes of MMC-associated hydrocephalus across socioeconomic and geographical regions of the world. The primary outcome will be treatment failure of the first-line hydrocephalus treatment, which we defined operationally as the performance of a second intervention for the same reason as the first. Secondary outcomes include time to failure, rates of mortality and postoperative complications. Ethics and dissemination: Ethical approval was not applicable because this study does not involve human participants. Dissemination strategies will include publication in a peer-reviewed journal, oral and poster presentations at conferences and an interactive web application to facilitate interaction with the findings and promote the discussion and sharing of findings on social media. PROSPERO registration number: CRD42021285850.

Introduction: Hydrocephalus and myelomeningocele (MMC) place disproportionate burdens of disease on low-income and middle-income countries (LMICs). MMC-associated hydrocephalus and its sequelae result in a spectrum of severely devastating clinical manifestations, for which LMICs are disproportionately unprepared in terms of human, capital and technological resources. This study aims to review and compare the management and outcomes of infant MMC-associated hydrocephalus in LMICs and high-income countries. Methods and analysis: This systematic review and meta-analysis will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines. The following databases will be searched without restrictions on language, publication date or country of origin: EMBASE, MEDLINE, The Cochrane Library, Global Index Medicus, African Journals Online and SciELO. All peer-reviewed studies of primary data reporting management and outcomes of infant MMC-associated hydrocephalus will be included. Where high-quality homogeneous studies exist, meta-analyses will be conducted to compare the management and outcomes of MMC-associated hydrocephalus across socioeconomic and geographical regions of the world. The primary outcome will be treatment failure of the first-line hydrocephalus treatment, which we defined operationally as the performance of a second intervention for the same reason as the first. Secondary outcomes include time to failure, rates of mortality and postoperative complications. Ethics and dissemination: Ethical approval was not applicable because this study does not involve human participants. Dissemination strategies will include publication in a peer-reviewed journal, oral and poster presentations at conferences and an interactive web application to facilitate interaction with the findings and promote the discussion and sharing of findings on social media. PROSPERO registration number: CRD42021285850.

Alison Dillman,1 Michael J Zoratti,2 Jay JH Park,3 Grace Hsu,2 Louis Dron,2 Gerald Smith,2 Ofir Harari,2 Craig R Rayner,4 Noor-E Zannat,2 Alind Gupta,2 Eric Mackay,5 Paul Arora,6 Zelyn Lee,7 Edward J Mills2 1School of Public Health, Faculty of Medicine, Imperial College London, London, England; 2Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada; 3Department of Experimental Medicine, University of British Columbia, Vancouver, British Columbia, Canada; 4Monash Institute of Pharmaceutical Sciences, Monash University, Melbourne, Australia; 5Department of Statistical Sciences, University of Toronto, Toronto, Canada; 6Dalla Lana School of Public Health, University of Toronto, Toronto, Canada; 7Department of Physiology & Department of Neuroscience, University of Toronto, Toronto, CanadaCorrespondence: Jay JH Park Tel +1 604 294-3823Email jayhpark1@alumni.ubc.caPurpose: A multitude of randomized controlled trials (RCTs) have emerged in response to the novel coronavirus disease (COVID-19) pandemic. Understanding the distribution of trials among various settings is important to guide future research priorities and efforts. The purpose of this review was to describe the emerging evidence base of COVID-19 RCTs by stages of disease progression, from pre-exposure to hospitalization.Methods: We collated trial data across international registries: ClinicalTrials.gov; International Standard Randomised Controlled Trial Number Registry; Chinese Clinical Trial Registry; Clinical Research Information Service; EU Clinical Trials Register; Iranian Registry of Clinical Trials; Japan Primary Registries Network; German Clinical Trials Register (up to 7 October 2020). Active COVID-19 RCTs in international registries were eligible for inclusion. We extracted trial status, intervention(s), control, sample size, and clinical context to generate descriptive frequencies, network diagram illustrations, and statistical analyses including odds

Kristian Thorlund,1,2 Louis Dron,2 Jay JH Park,2,3 Edward J Mills1,2 1Department of Health Research Methods, Evidence & Impact (HEI), McMaster University, Hamilton, ON, Canada; 2MTEK Sciences, Vancouver, BC, Canada; 3Department of Medicine, University of British Columbia, Vancouver, BC, CanadaCorrespondence: Kristian ThorlundMTEK Sciences, 802-777 West Broadway, Vancouver, BC V5Z 1J5, CanadaEmail thorluk@mcmaster.caAbstract: There has been a rapid expansion in the use of non-randomized evidence in the regulatory approval of treatments globally. An emerging set of methodologies have been utilized to provide greater insight into external control data used for these purposes, collectively known as synthetic control methods. Through this paper, we provide the reader with a set of key questions to help assess the quality of literature publications utilizing synthetic control methodologies. Common challenges and real-life examples of synthetic controls are provided throughout, alongside a critical appraisal framework with which to assess future publications.Keywords: synthetic control, RCTs, real-world evidence

Deep Neural Network (DNN) models have continuously been growing in size in order to improve the accuracy and quality of the models. Moreover, for training of large DNN models, the use of heterogeneous GPUs is inevitable due to the short release cycle of new GPU architectures. In this paper, we investigate how to enable training of large DNN models on a heterogeneous GPU cluster that possibly includes whimpy GPUs that, as a standalone, could not be used for training. We present a DNN training system, HetPipe (Heterogeneous Pipeline), that integrates pipelined model parallelism (PMP) with data parallelism (DP). In HetPipe, a group of multiple GPUs, called a virtual worker, processes minibatches in a pipelined manner, and multiple such virtual workers employ data parallelism for higher performance. We also propose a novel parameter synchronization model, which we refer to as Wave Synchronous Parallel (WSP) to accommodate both PMP and DP for virtual workers, and provide convergence proof of WSP. Our experimental results on a given heterogeneous setting show that with HetPipe, DNN models converge up to 49% faster compared to the state-of-the-art DP technique.

As Macromolecules celebrates its 50th anniversary, we reflect on the impact of polymer chemistry and engineering on the advancement of synthetic polymer fibers. In this Perspective, we focus on two exemplary cases: (i) high performance fibers and (ii) ultrafine electrospun fibers. High performance in this context refers to fibers like Kevlar and Spectra, which emerged as a consequence of novel chemistry and processing innovations to convert synthetic polymers into fibers with exceptional specific stiffness and strength. More recently, the development of "ultrafine" (i.e., submicrometer diameter) fibers by technologies such as electrospinning has advanced dramatically, resulting in interesting, emergent structures and properties, such as surface and internal morphologies, electrical and mechanical properties, and growth applications like tissue engineering and sensors, which are subjects of current research. In both cases, challenges and opportunities exist in the development of polymer processes to advance the current state of these synthetic polymer fibers.

The Convolutional Neural Network (CNN) model, often used for image classification, requires significant training time to obtain high accuracy. To this end, distributed training is performed with the parameter server (PS) architecture using multiple servers. Unfortunately, scalability has been found to be poor in existing architectures. We find that the PS network is the bottleneck as it communicates a large number of gradients and parameters with the many workers. This is because synchronization with the many workers has to occur at every step of training. Depending on the model, communication can be in the several hundred MBs per synchronization. In this paper, we propose a scheme to reduce network traffic through layer placement that considers the resources that each layer uses. Through analysis of the characteristics of CNN, we find that placement of layers can be done in an effective manner. We then incorporate this observation within the TensorFlow framework such that layers can be automatically placed for more efficient training. Our evaluation making use of this placement scheme show that training time can be significantly reduced without loss of accuracy for many CNN models.

Jay JH Park,1 Kristian Thorlund,2,3 Edward J Mills2,3 1Department of Medicine, University of British Columbia, Vancouver, BC, Canada; 2Department of Health Research Methods, Evidence, and Impact (HEI), McMaster University, Hamilton, ON, Canada; 3The Bill and Melinda Gates Foundation, Seattle, WA, USA Abstract: Adaptive clinical trials are an innovative trial design aimed at reducing resources, decreasing time to completion and number of patients exposed to inferior interventions, and improving the likelihood of detecting treatment effects. The last decade has seen an increasing use of adaptive designs, particularly in drug development. They frequently differ importantly from conventional clinical trials as they allow modifications to key trial design components during the trial, as data is being collected, using preplanned decision rules. Adaptive designs have increased likelihood of complexity and also potential bias, so it is important to understand the common types of adaptive designs. Many clinicians and investigators may be unfamiliar with the design considerations for adaptive designs. Given their complexities, adaptive trials require an understanding of design features and sources of bias. Herein, we introduce some common adaptive design elements and biases and specifically address response adaptive randomization, sample size reassessment, Bayesian methods for adaptive trials, seamless trials, and adaptive enrichment using real examples. Keywords: adaptive designs, response adaptive randomization, sample size reassessment, Bayesian adaptive trials, seamless trials, adaptive enrichment

Stiff, strong and tough ultrafine polyethylene fibers that rival the best high performance fibers, but with diameters less than one micron, are fabricated for the first time by “gel-electrospinning.” In this process, solution concentration and process temperatures are chosen to induce the formation of gel filaments “in flight,” which are subsequently drawn at high rates as a consequence of the whipping instability. The resulting submicron-diameter fibers exhibited Young’s moduli of 73 ± 13 GPa, yield strengths of 3.5 ± 0.6 GPa, and toughnesses of 1.8 ± 0.3 GPa, on average. Among the smallest fibers examined, one with a diameter of 490 ± 50 nm showed a Young’s modulus of 110 ± 16 GPa, ultimate tensile strength of 6.3 ± 0.9 GPa, and toughness of 2.1 ± 0.3 GPa, a combination of mechanical properties that is unparalleled among polymer fibers to date. The correlation of stiffness, strength and toughness with fiber diameter is attributed to high crystallinity and crystallite orientation, combined with fewer defects and enhanced chain slip associated with small diameter and high specific surface area. Gel-electrospinning improves the prospects for production of such fibers at scale., United States. Army. Natick Soldier Research, Development and Engineering Center

This semester, Spring 2018, in CS 4624, Multimedia, Hypertext, and Information Access, our team pursued a project with the Virginia Tech Psychology Department and their Diversity Committee. We were tasked with enhancing the current Diversity and Inclusion webpages that are offered on the Psychology Department’s website. The clients desired for us to create new webpages that would enhance the recruitment of potential students and faculty, bring better awareness to the Department’s Diversity and Inclusion endeavors to current students and faculty, and allow users to easily and conveniently utilize the Department’s resources concerning Diversity and Inclusion. We developed a new website for the Department that included eleven distinct pages with content related to Diversity and Inclusion. The information for the pages was gathered from the InclusiveVT Inclusion and Diversity Strategic Planning Guide [4], provided to us by our clients. We gathered a library of multimedia content for use on the website from the Department. We performed user walkthroughs and distributed a survey to members of the Department in order to gauge user satisfaction and areas requiring improvement. This survey also allowed users to submit additional multimedia content for our use. The Department had also faced the issue of the ease of editing the current webpages that they are hosting. They wanted to be able to edit their webpages in an easier fashion, being able to upload news articles and new events that the Department was holding. They requested that we consider this as we approach the development of the new webpages. We utilized WordPress to allow for a user-friendly environment for editing the webpages in the future. We made all of the clients administrators for the website so that they can make future changes and add other individuals to become administrators. We also created video tutorials that detail the step-by-step instructions to edit each portion of the website. These seven videos w

We report a facile fabrication of porous silicon nanofibers by a simple three-stage procedure. Polymer/silicon precursor composite nanofibers are first fabricated by electrospinning, a water-based spinning dope, which undergoes subsequent heat treatment and then reduction using magnesium to be converted into porous silicon nanofibers. The porous silicon nanofibers are coated with a graphene by using a plasma-enhanced chemical vapor deposition for use as an anode material of lithium ion batteries. The porous silicon nanofibers can be mass-produced by a simple and solvent-free method, which uses an environmental-friendly polymer solution. The graphene-coated silicon nanofibers show an improved cycling performance of a capacity retention than the pure silicon nanofibers due to the suppression of the volume change and the increase of electric conductivity by the graphene., Korea Institute of Energy Technology Evaluation and Planning (Human Resources Development Program Grant 20144030200600)