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ECG heartbeat classification based on an improved ResNet-18 model
No full textBased on a convolutional neural network (CNN) approach, this article proposes an improved ResNet-18 model for heartbeat classification of electrocardiogram (ECG) signals through appropriate model training and parameter adjustment. Due to the unique residual structure of the model, the utilized CNN layered structure can be deepened in order to achieve better classification performance. The results of applying the proposed model to the MIT-BIH arrhythmia database demonstrate that the model achieves higher accuracy (96.50%) compared to other state-of-the-art classification models, while specifically for the ventricular ectopic heartbeat class, its sensitivity is 93.83% and the precision is 97.44%
The Developmental Peacebuilding Model (DPM) of children’s prosocial behaviors in settings of intergroup conflict
No full textThe persistence of intergroup conflicts around the world creates urgency for research on child development in such settings. Complementing the existing knowledge about internalizing and externalizing developmental outcomes, this article shifts the focus to children’s prosocial behaviors, and more specifically, introduces the Developmental Peacebuilding Model (DPM). The DPM makes three main contributions. First, the DPM integrates a developmental intergroup framework and socio-ecological perspective, with a peacebuilding paradigm, to examine the target and type of children’s prosocial behavior in settings of intergroup conflict. Second, DPM outlines how children’s outgroup prosocial behaviors, which promote constructive change at different levels of the social ecology, can be understood as peacebuilding and fostering social cohesion. Third, the article concludes with the DPM’s implications for research and global policy.National Institute of Child Health and Human DevelopmentOffice of First Minister & Deputy First Minister, Government of Northern IrelandSpencer FoundationRichard Benjamin Trust and the British Academy (BA)/LeverhulmeUnited Kingdom Research and Innovation (UKRI) Global Challenges Research Fund (GCRF) Global Impact Acceleration Awards (GIAA)Department for the Economy (DFE) GCRFBritish Psychological Society (BPS) Social Psychology SectionSociety for Research on Child Development Small Grant for Early Career Scholar
Asynchronous distributed clustering algorithms for wireless mesh network
No full textWireless Mesh Networks are becoming increasingly important in many applications.
In many cases, data is acquired by devices that are distributed in space, but
effective actions require a global view of that data across all devices. Transmitting
all data to the centre allows strong data analytics algorithms to be applied,
but consumes battery power for the nodes, and may cause data overload. To
avoid this, distributed methods try to learn within the network, allowing each
agent to learn a global picture and take appropriate actions.
For distributed clustering in particular, existing methods share simple cluster
descriptions until the network stabilises. The approaches tend to require either
synchronous behaviour or many cycles, and omit important information about
the clusters. In this thesis, we develop asynchronous methods that share richer
cluster models, and we show that they are more effective in learning the global
data patterns.
Our underlying method describes the shape and density of each cluster, as well
as its centroid and size. We combine cluster models by re-sampling from received
models, and then re-clustering the new data sets. We then extend the approach,
to allowing clustering methods that do not require the final number of clusters as
input. After that, we consider the cases that there might be sub-groups of agents
that are receiving different patterns of data. Finally, we extend our approaches
to scenarios where each agent has no idea about whether there is a single pattern
or are multiple patterns.
We demonstrate that the approaches can regenerate clusters that are similar to
the distributions that were used to create the test data. When the number of
clusters are not available, the learned number of clusters is close to the ground
truth. The proposed algorithms can learn how data points are clustered even
when there are multiple patterns in the network. When the number of patterns
(single or multiple) is not known in advance, the proposed methods Optimised
KDE and DBSCAN preform well in detecting multiple patterns. Although they
perform worse in detecting the single pattern, they can still learn how data points
are clustered
Putting the system back into training and firm performance research: A review and research agenda
No full textResearch investigating training and firm performance is currently at an inflection point; capable of recognising previous achievements but also having a focus on the future. Based on our review of 207 quantitative papers over a 40‐year period, we find that the field has converged in terms of theory and methods. Important insights have been generated yet there is scope to better understand the complex, interrelated and dynamic nature of the relationship between training and firm performance. We propose that open systems theory (OST) provides the potential to move the field forward and encourage researchers to investigate interactions and linkages between training and performance components, the role of temporal dynamics in inputs and processes, reverse causality and to broaden conceptualisations of firm performance. We consider six principles of OST, highlight productive avenues for future research and identify methodological challenges and implications.2023-03-1
A high-fidelity crystal-plasticity finite element methodology for low-cycle fatigue using automatic electron backscatter diffraction scan conversion: Application to hot-rolled cobalt–chromium alloy
No full textThe common approach to crystal-plasticity finite element modeling for load-bearing prediction of metallic structures involves the simulation of simplified grain morphology and substructure detail. This paper details a methodology for predicting the structure–property effect of as-manufactured microstructure, including true grain morphology and orientation, on cyclic plasticity, and fatigue crack initiation in biomedical-grade CoCr alloy. The methodology generates high-fidelity crystal-plasticity finite element models, by directly converting measured electron backscatter diffraction metal microstructure grain maps into finite element microstructural models, and thus captures essential grain definition for improved microstructure–property analyses. This electron backscatter diffraction-based method for crystal-plasticity finite element model generation is shown to give approximately 10% improved agreement for fatigue life prediction, compared with the more commonly used Voronoi tessellation method. However, the added microstructural detail available in electron backscatter diffraction–crystal-plasticity finite element did not significantly alter the bulk stress–strain response prediction, compared to Voronoi tessellation–crystal-plasticity finite element. The new electron backscatter diffraction-based method within a strain-gradient crystal-plasticity finite element model is also applied to predict measured grain size effects for cyclic plasticity and fatigue crack initiation, and shows the concentration of geometrically necessary dislocations around true grain boundaries, with smaller grain samples exhibiting higher overall geometrically necessary dislocations concentrations. In addition, minimum model sizes for Voronoi tessellation–crystal-plasticity finite element and electron backscatter diffraction–crystal-plasticity finite element models are proposed for cyclic hysteresis and fatigue crack initiation prediction.This publication has emanated from research conducted with the financial support of Science
Foundation Ireland under Grant number 16/RC/3872. For the purpose of Open Access, the author
has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising
from this submission. The authors wish to acknowledge the Irish Centre for High-End Computing
(ICHEC) for the provision of computational facilities and support. The microstructure
668 characterization work is supported by the University of Limerick, which is highly appreciated. The
669 authors would also like to acknowledge Dr P. J. Ashton for the helpful discussion
Study Protocol for DeCOmPRESS: Defining the Disease Course and Immune Profile of COVID-19 in the Immunosuppressed Patient
No full textThe ongoing coronavirus disease 2019 (COVID-19) pandemic is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Current advisory guidelines for high-risk groups—including people with autoimmune disease taking immunosuppressive therapies—are to take increased precautions and avoid any unnecessary contacts. The aim of the DeCOmPRESS study is to define the disease course and immune profile of COVID-19 in immunosuppressed patients. We will clinically phenotype patients with ANCA-associated vasculitis (AAV) who develop COVID-19 using a customized REDCap data collection instrument embedded within the Rare Kidney Disease (RKD) Biobank. This dataset will be interoperable with the rheum-COVID, Global Rheumatology Alliance, and SPRINT-SARI datasets, facilitating international data linkage. Acute and convalescent blood samples will be analysed by flow cytometry and ELISA to define the immunophenotype and cytokine profile. Patients will track COVID-19 and AAV symptoms through a bespoke smartphone app
Linked Data and Cultural Heritage
No full textThe cultural heritage sector has traditionally been concerned with sharing resources and furthering human knowledge, with particular interest to the issues associated with metadata and interoperability, especially when it comes to the use of technology. These goals and interests in the cultural heritage sector are natural alignments with those of linked data; hence. there has been an increasing interest in the application of linked data in this sector. This article studies the implementation of linked data in the cultural heritage sector, through a systematic literature review of case studies of linked data implementation projects in this sector. The results reflect on the parties involved, the level of collaboration, and the motivation behind these projects. The study suggests that universities and national institutions were the main players in implementing such technologies in the cultural heritage sector, suggesting that there may be some barriers preventing smaller GLAM institutions from implementing linked data projects. The results further suggest that many linked data projects in this sector were primarily exploratory projects, and often performed in a collaborative manner. They further indicate that the most common motivating factors behind these projects were research needs, a desire to contribute to linked data as a movement, and other specific user needs. Reflecting on this systematic literature review, this article makes a set of recommendations for future work to increase the use of linked data in the cultural heritage sector and to remove barriers to adoption
Enzyme kinetic and binding studies identify determinants of specificity for the immunomodulatory enzyme ScpA, a C5a inactivating bacterial protease
No full textArticle was replaced as equations missing from Scheme 1, p. 2359 in original published version - 20210524The Streptococcal C5a peptidase (ScpA) specifically inactivates the human complement factor hC5a, a potent anaphylatoxin recently identified as a therapeutic target for treatment of COVID-19 infections. Biologics used to modulate hC5a are predominantly monoclonal antibodies. Here we present data to support an alternative therapeutic approach based on the specific inactivation of hC5a by ScpA in studies using recombinant hC5a (rhC5a). Initial characterization of ScpA confirmed activity in human serum and against rhC5a desArg (rhC5adR), the predominant hC5a form in blood. A new FRET based enzyme assay showed that ScpA cleaved rhC5a at near physiological concentrations (Km 185 nM). Surface Plasmon Resonance (SPR) and Isothermal Titration Calorimetry (ITC) studies established a high affinity ScpA-rhC5a interaction (KD 34 nM, KITC D 30.8 nM). SPR analyses also showed that substrate binding is dominated (88% of DGbind) by interactions with the bulky N-ter cleavage product (PN, ’core’ residues
1–67) with interactions involving the C-ter R74 contributing most of the remaining DGbind.
Furthermore, reduced binding affinity following mutation of a subset of positively charged Arginine residues of PN and in the presence of higher salt concentrations, highlighted the importance of electrostatic interactions. These data provide the first in-depth study of the ScpA-C5a interaction and indicate that ScpA’s ability to efficiently cleave physiological concentrations of C5a is driven by electrostatic interactions between an exosite on the enzyme and the ‘core’ of C5a. The results and methods described herein will facilitate engineering of ScpA to enhance its potential as a therapeutic for excessive immune
response to infectious diseas
Public health practicum: a scoping review of current practice in graduate public health education
No full textThe objectives of this study are to (1) identify Graduate Public Health (GPH) programmes with an integrated practicum, (2) determine current practice for practicum design and (3) use the information to make recommendations to inform the design of Public Health
Graduate programme practicums. Design Scoping review. Data sources Academic Ranking World Universities 2019 was used to identify top 10 institutions in each
geographical hub offering GPH programmes. Each GPH programme website was searched for practicum information Eligibility criteria GPH programmes offering a practice based component as a requirement in their curriculum. Data extraction and synthesis One reviewer screened GPH websites for eligibility and extracted data. Verification of data for accuracy and completeness was done on 10% of the sample by the second author. Data were compiled into an Excel file and were analysed to describe the duration, timing, credit, contact hours, preceptor requirements, prerequisites, objectives, deliverables and
methods of evaluation of the practice-based component
Walking a mile in Viktorija\u27s shoes: Resilience, (Post-) memory and affordances
No full text[No abstract available]Not peer reviewed2021-11-0