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"technical quality control"
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COMP report: CPQR technical quality control guidelines for radiation treatment centers
The Canadian Organization of Medical Physicists (COMP), in close partnership with the Canadian Partnership for Quality Radiotherapy (CPQR) has developed a series of Technical Quality Control (TQC) guidelines for radiation treatment equipment. These guidelines outline the performance objectives that equipment should meet in order to ensure an acceptable level of radiation treatment quality. The TQC guidelines have been rigorously reviewed and field tested in a variety of Canadian radiation treatment facilities. The development process enables rapid review and update to keep the guidelines current with changes in technology. This announcement provides an introduction to the guidelines, describing their scope and how they should be interpreted. Details of recommended tests can be found in separate, equipment specific TQC guidelines published in the JACMP (COMP Reports), or the website of the Canadian Partnership for Quality Radiotherapy (www.cpqr.ca).
Journal Article
The matrix system at work
The 1997 Bank reforms that introduced the matrix management concept aimed to adapt the organization to changing circumstances and address concerns among external stakeholders about the role of aid in development. The reforms were motivated largely by widespread recognition that the Bank's development programs were excessively driven by a culture of lending, with insufficient attention to client needs and the quality of results, which are crucial to development effectiveness. A previous round of reforms in 1987 had strengthened the country focus, but quality remained a concern. Furthermore, access of developing countries to development finance from the private sector had increased significantly, leading to a decreasing share of official development aid, including Bank financing, in total flows to developing countries. This trend has continued after slight interruption by the Asian financial crisis. In 1987, World Bank lending represented 15 percent of all external financing for developing countries. By 2002 Bank lending had declined to 4 percent of external financing (organizational effectiveness task force: final report, 2005). Changes in the external environment indicate that the matrix system is even more relevant today than when it was introduced. Client needs have diversified, with greater differentiation among countries, even within the regions; the growth of global public goods and corporate priorities is creating tensions and has given rise to new challenges which need to be reconciled with the country model; demand for cutting-edge knowledge is growing, both to enhance quality of lending and as a business line for policy and program advice to clients; and new global practices have emerged to meet needs such as information, communication and technology, and disaster management. The Bank's ability to renew itself and function as a truly global Bank is critical to its success.
eBook
Accurate rare variant phasing of whole-genome and whole-exome sequencing data in the UK Biobank
Phasing involves distinguishing the two parentally inherited copies of each chromosome into haplotypes. Here, we introduce SHAPEIT5, a new phasing method that quickly and accurately processes large sequencing datasets and applied it to UK Biobank (UKB) whole-genome and whole-exome sequencing data. We demonstrate that SHAPEIT5 phases rare variants with low switch error rates of below 5% for variants present in just 1 sample out of 100,000. Furthermore, we outline a method for phasing singletons, which, although less precise, constitutes an important step towards future developments. We then demonstrate that the use of UKB as a reference panel improves the accuracy of genotype imputation, which is even more pronounced when phased with SHAPEIT5 compared with other methods. Finally, we screen the UKB data for loss-of-function compound heterozygous events and identify 549 genes where both gene copies are knocked out. These genes complement current knowledge of gene essentiality in the human genome.
SHAPEIT5, a phasing method that accurately processes large sequencing datasets, was applied on the UK Biobank whole-genome and whole-exome sequencing data to generate reference panels of haplotypes that boost imputation accuracy and enable the detection of compound heterozygous loss-of-function events for 549 genes.
Journal Article
Toward an Evidence-Based System for Innovation Support for Implementing Innovations with Quality: Tools, Training, Technical Assistance, and Quality Assurance/Quality Improvement
An individual or organization that sets out to implement an innovation (e.g., a new technology, program, or policy) generally requires support. In the Interactive Systems Framework for Dissemination and Implementation, a
Support System
should work with
Delivery Systems
(national, state and/or local entities such as health and human service organizations, community-based organizations, schools) to enhance their capacity for quality implementation of innovations. The literature on the Support ystem has been under-researched and under-developed. This article begins to conceptualize theory, research, and action for an evidence-based system for innovation support (EBSIS). EBSIS describes key priorities for strengthening the science and practice of support. The major goal of EBSIS is to enhance the research and practice of support in order to build capacity in the Delivery System for implementing innovations with quality, and thereby, help the Delivery System achieve outcomes. EBSIS is guided by a logic model that includes four key support components:
tools, training, technical assistance, and quality assurance/quality improvement
. EBSIS uses the Getting To Outcomes approach to accountability to aid the identification and synthesis of concepts, tools, and evidence for support. We conclude with some discussion of the current status of EBSIS and possible next steps, including the development of collaborative researcher-practitioner-funder-consumer partnerships to accelerate accumulation of knowledge on the Support System.
Journal Article
Deep learning in optical metrology: a review
With the advances in scientific foundations and technological implementations, optical metrology has become versatile problem-solving backbones in manufacturing, fundamental research, and engineering applications, such as quality control, nondestructive testing, experimental mechanics, and biomedicine. In recent years, deep learning, a subfield of machine learning, is emerging as a powerful tool to address problems by learning from data, largely driven by the availability of massive datasets, enhanced computational power, fast data storage, and novel training algorithms for the deep neural network. It is currently promoting increased interests and gaining extensive attention for its utilization in the field of optical metrology. Unlike the traditional “physics-based” approach, deep-learning-enabled optical metrology is a kind of “data-driven” approach, which has already provided numerous alternative solutions to many challenging problems in this field with better performances. In this review, we present an overview of the current status and the latest progress of deep-learning technologies in the field of optical metrology. We first briefly introduce both traditional image-processing algorithms in optical metrology and the basic concepts of deep learning, followed by a comprehensive review of its applications in various optical metrology tasks, such as fringe denoising, phase retrieval, phase unwrapping, subset correlation, and error compensation. The open challenges faced by the current deep-learning approach in optical metrology are then discussed. Finally, the directions for future research are outlined.
Journal Article
Moderating the effect of globalization on financial development, energy consumption, human capital, and carbon emissions: evidence from G20 countries
The policy debate on the financial development and dynamic of carbon dioxide (CO
2
) emission is topical. Globalization can affect this relationship by making financial investments in green energy and environment-friendly technology, as environmental sustainability is the primary concern for modern society. This study proposes a newly formulated conceptual framework to explore globalization’s moderating role on exoplanetary variables (financial development, energy consumption, human capital, and gross domestic product) and CO
2
emission. We employed Fixed Effect Ordinary Least Squares (FE-OLS), Driscoll–Kraay standard error approach (D–K), and Dumitrescu and Hurlin’s (
2012
) panel causality test. Our sample of the study comprised full and subsamples of G20 countries (excluding the European Union) from 1986 to 2018. The results indicated that financial development and human capital decreased carbon emissions, while GDP and energy consumption substantially increased carbon emissions during the study time. Further, globalization moderated the positive impact of financial development and human development on carbon emissions. A sustainable environmental agenda is achieved by a stronger financial system, encouraging green finance, and including technical education that improves production efficiency. However, globalization moderated the negative impact of energy consumption and GDP on carbon emission. Besides, we also reported the bidirectional causal relationship of GDP to energy consumption. Our empirical research provides new insights for policymakers and governments to formulate country-based policies to protect environmental quality while achieving sustainable economic goals.
Journal Article
A rapid review of mental and physical health effects of working at home: how do we optimise health?
Background
The coronavirus (COVID-19) pandemic has resulted in changes to the working arrangements of millions of employees who are now based at home and may continue to work at home, in some capacity, for the foreseeable future. Decisions on how to promote employees’ health whilst working at home (WAH) need to be based on the best available evidence to optimise worker outcomes. The aim of this rapid review was to review the impact of WAH on individual workers’ mental and physical health, and determine any gender difference, to develop recommendations for employers and employees to optimise workers’ health.
Method
A search was undertaken in three databases, PsychInfo, ProQuest, and Web of Science, from 2007 to May 2020. Selection criteria included studies which involved employees who regularly worked at home, and specifically reported on physical or mental health-related outcomes. Two review authors independently screened studies for inclusion, one author extracted data and conducted risk of bias assessments with review by a second author.
Results
Twenty-three papers meet the selection criteria for this review. Ten health outcomes were reported: pain, self-reported health, safety, well-being, stress, depression, fatigue, quality of life, strain and happiness. The impact on health outcomes was strongly influenced by the degree of organisational support available to employees, colleague support, social connectedness (outside of work), and levels of work to family conflict. Overall, women were less likely to experience improved health outcomes when WAH.
Conclusions
This review identified several health outcomes affected by WAH. The health/work relationship is complex and requires consideration of broader system factors to optimise the effects of WAH on workers’ health. It is likely mandated WAH will continue to some degree for the foreseeable future; organisations will need to implement formalised WAH policies that consider work-home boundary management support, role clarity, workload, performance indicators, technical support, facilitation of co-worker networking, and training for managers.
Journal Article
ENIGMA HALFpipe: Interactive, reproducible, and efficient analysis for resting‐state and task‐based fMRI data
The reproducibility crisis in neuroimaging has led to an increased demand for standardized data processing workflows. Within the ENIGMA consortium, we developed HALFpipe (Harmonized Analysis of Functional MRI pipeline), an open‐source, containerized, user‐friendly tool that facilitates reproducible analysis of task‐based and resting‐state fMRI data through uniform application of preprocessing, quality assessment, single‐subject feature extraction, and group‐level statistics. It provides state‐of‐the‐art preprocessing using fMRIPrep without the requirement for input data in Brain Imaging Data Structure (BIDS) format. HALFpipe extends the functionality of fMRIPrep with additional preprocessing steps, which include spatial smoothing, grand mean scaling, temporal filtering, and confound regression. HALFpipe generates an interactive quality assessment (QA) webpage to rate the quality of key preprocessing outputs and raw data in general. HALFpipe features myriad post‐processing functions at the individual subject level, including calculation of task‐based activation, seed‐based connectivity, network‐template (or dual) regression, atlas‐based functional connectivity matrices, regional homogeneity (ReHo), and fractional amplitude of low‐frequency fluctuations (fALFF), offering support to evaluate a combinatorial number of features or preprocessing settings in one run. Finally, flexible factorial models can be defined for mixed‐effects regression analysis at the group level, including multiple comparison correction. Here, we introduce the theoretical framework in which HALFpipe was developed, and present an overview of the main functions of the pipeline. HALFpipe offers the scientific community a major advance toward addressing the reproducibility crisis in neuroimaging, providing a workflow that encompasses preprocessing, post‐processing, and QA of fMRI data, while broadening core principles of data analysis for producing reproducible results. Instructions and code can be found at https://github.com/HALFpipe/HALFpipe. HALFpipe is a user‐friendly software that facilitates reproducible analysis of fMRI data, including preprocessing, single‐subject, and group analysis. It provides state‐of‐the‐art preprocessing using fMRIPrep, but removes the necessity to convert data to the BIDS format. Common resting‐state and task‐based fMRI features can then be calculated on the fly using FSL and Nipype for statistics.
Journal Article