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Evolving Software Architecture Design in Telemedicine: A PRISMA-based Systematic Review
Get PDFObjectives:
This article presents a systematic review of recent advancements in telemedicine architectures for continuous monitoring, providing a comprehensive overview of the evolving software engineering practices underpinning these systems. The review aims to illuminate the critical role of telemedicine in delivering healthcare services, especially during global health crises, and to emphasize the importance of effectiveness, security, interoperability, and scalability in these systems.
Methods:
A systematic review methodology was employed, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework. As the primary research method, the PubMed, IEEE Xplore, and Scopus databases were searched to identify articles relevant to telemedicine architectures for continuous monitoring. Seventeen articles were selected for analysis, and a methodical approach was employed to investigate and synthesize the findings.
Results:
The review identified a notable trend towards the integration of emerging technologies into telemedicine architectures. Key areas of focus include interoperability, security, and scalability. Innovations such as cognitive radio technology, behavior-based control architectures, Health Level Seven International (HL7) Fast Healthcare Interoperability Resources (FHIR) standards, cloud computing, decentralized systems, and blockchain technology are addressing challenges in remote healthcare delivery and continuous monitoring.
Conclusions:
This review highlights major advancements in telemedicine architectures, emphasizing the integration of advanced technologies to improve interoperability, security, and scalability. The findings underscore the successful application of cognitive radio technology, behavior-based control, HL7 FHIR standards, cloud computing, decentralized systems, and blockchain in advancing remote healthcare delivery
Digitising the UK securities market: the case against and proposal to enfranchise indirect investors
Get PDFA taskforce, appointed by HM Treasury, has recently proposed legislation to eliminate certificated (paper) shares and to require the investors currently holding paper shares to hold them indirectly through nominees. It has also suggested that disclosure combined with a common messaging protocol will enable the market to improve the ability of indirect shareholders to exercise their rights. In this paper we make a case against legislation eliminating paper certificates. We argue that the industry does not need the Government to remove paper certificates. If they want paper certificates to disappear, they should develop a model for holding uncertificated shares directly that is affordable for retail investors. The Government should nevertheless intervene. It should encourage the Competition and Markets Authority to investigate the price structure of accounts for holding uncertificated shares directly with CREST, which operates as a monopoly provider for such accounts in the UK. We further explain that the current system for holding shares indirectly disenfranchises investors and argue that this not only affects investors but also deprives issuers of oversight of their governance. We use empirical evidence to explain that disclosure combined with a common messaging protocol is unlikely to cause the market to develop a system that better enfranchises indirect shareholders. Consequently, we propose legislation to give indirect investors better access to shareholder rights.British Academy and the Department for Business, Energy and Industrial Strategy (ref. SRG19\190474)
An algorithm for discontinuing mechanical ventilation in boys with x-linked myotubular myopathy after positive response to gene therapy: the ASPIRO experience
Get PDFData availability: No datasets were generated or analysed during the current study.X-linked myotubular myopathy (XLMTM) is a rare, life-threatening congenital myopathy. Most (80%) children with XLMTM have profound muscle weakness and hypotonia at birth resulting in severe respiratory insufficiency, the inability to sit up, stand or walk, and early mortality. At birth, 85–90% of children with XLMTM require mechanical ventilation, with more than half requiring invasive ventilator support. Historically, ventilator-dependent children with neuromuscular-derived respiratory failure of this degree and nature, static or progressive, are not expected to achieve complete independence from mechanical ventilator support. In the ASPIRO clinical trial (NCT03199469), participants receiving a single intravenous dose of an investigational gene therapy (resamirigene bilparvovec) started showing significant improvements in daily hours of ventilation support compared with controls by 24 weeks post-dosing, and 16 of 24 dosed participants achieved ventilator independence between 14 and 97 weeks after dosing. At the time, there was no precedent or published guidance for weaning chronically ventilated children with congenital neuromuscular diseases off mechanical ventilation. When the first ASPIRO participants started showing dramatically improved respiratory function, the investigators initiated efforts to safely wean them off ventilator support, in parallel with primary protocol respiratory outcome measures. A group of experts in respiratory care and physiology and management of children with XLMTM developed an algorithm to safely wean children in the ASPIRO trial off mechanical ventilation as their respiratory muscle strength increased. The algorithm developed for this trial provides recommendations for assessing weaning readiness, a stepwise approach to weaning, and monitoring of children during and after the weaning process.The ASPIRO trial was sponsored by Astellas Gene Therapies (formerly Audentes Therapeutics) and was the impetus for development of the algorithm for weaning ventilator-dependent children with XLMTM off of ventilator support. Medical writing support from Laurie LaRusso, MS, ELS, of Chestnut Medical Communications was paid for by Astellas Gene Therapies
Optimizing the Patient Journey in Government Hospitals: Strategies for Improving Healthcare Delivery and Outcomes
No full textThis thesis aims to investigate and optimize the patient journey within government hospitals, with the goal of enhancing healthcare delivery and improving patient outcomes. By examining the key factors that influence the patient journey, this study seeks to identify barriers and inefficiencies in current processes. It will propose evidence-based strategies and interventions to optimize the patient journey and enhance healthcare outcomes in government hospitals. The research will utilize qualitative interviews, and a comprehensive literature review. The findings of this study will provide valuable insights for policymakers, healthcare administrators, and practitioners seeking to improve the patient experience and optimize healthcare delivery in government hospitals
Neuronormativity as ignorant design in human resource management: The case of an unsupportive national context
Get PDFData Availability Statement: The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.Supporting Information is available online at: https://onlinelibrary.wiley.com/doi/10.1111/1748-8583.12573#support-information-section .Neurodiversity refers to differences in how people's brains work. Reportedly, human resource functions lag behind scientific developments in offering inclusive design for neurodivergent individuals. Drawing on the sociology of ignorance, we examine mechanisms and forms of ignorant design based on a qualitative study with 20 HR professionals in a country with an unsupportive context for neurodivergence. We expand the literature on an ignorant design by identifying three mechanisms and seven forms of ignorance that shape neuronormative HR policies and practices, revealing that HR practices often marginalise neurodivergent individuals by not recognising their contributions, enforcing neurotypical standards, and maintaining a superficial approach to inclusion. Our findings underscore the need for substantial changes in HR policies and practices, such as involving neurodivergent individuals in policy design, providing comprehensive neurodiversity training for HR professionals, and adopting evidence-based and inclusive HR strategies. Further, a supportive national context is invaluable for neuroinclusion
Evaluate the effect of coarse aggregates on cement hydration heat and concrete temperature modelling using isothermal calorimetry
Get PDFData availability statement: Data will be made available on request.The early-age temperature rise in concrete, induced by cement hydration, poses a significant risk of thermal cracking. Accurate prediction of concrete hydration temperature is essential for thermal cracking prevention. Cement hydration heat obtained from isothermal calorimetry has been applied to concrete temperature modelling by previous studies. Isothermal calorimetry often excludes coarse aggregates due to the calorimeter capacity limitations, assuming mortar hydration heat can represent concrete, which may neglect the hydration delay effect of coarse aggregates. This study uses an isothermal calorimeter capable of accommodating coarse aggregates to measure the hydration heat of concrete and equivalent mortar, evaluating the validity of this assumption. Results show that the 3-day cumulative hydration heat of concrete exceeds that of mortar, especially at elevated curing temperatures. Significant differences were found in the activation energy and hydration parameters between concrete and mortar, indicating that the presence of coarse aggregates affects samples’ temperature sensitivity and hydration heat development. Concrete temperature finite element modelling, validated by semi-adiabatic calorimetry, demonstrates that models based on concrete isothermal calorimetry data provide higher accuracy than those based on mortars. This study demonstrates that the hydration heat development, activation energy, and hydration parameters differ significantly between mortar and concrete. Concrete temperature models based on mortar hydration heat data can result in prediction errors exceeding 5 %. This study recommended employing micro-concrete samples in isothermal calorimetry to replicate actual concrete mixes
Approximate Computing: Concepts, Architectures, Challenges, Applications, and Future Directions
Get PDFThe unprecedented progress in computational technologies led to a substantial proliferation of artificial intelligence applications, notably in the era of big data and IoT devices. In the face of exponential data growth and complex computations, conventional computing encounters substantial obstacles pertaining to energy efficiency, computational speed, and area. Due to the diminishing advantages of technology scaling and increased demands from computing workloads, novel design techniques are required to increase performance and decrease power consumption. Approximate computing, nowadays considered a promising paradigm, achieves considerable improvements in overhead cost reduction (i.e., energy, area, and latency) at the expense of a modest (i.e., still acceptable) deterioration in application accuracy. Therefore, approximate computing at different levels (Data, Circuit, Architecture, and Software) has been attracted by the research and industrial communities. This paper presents a comprehensive review of the major research areas of different levels of approximate computing by exploring their underlying principles, potential benefits, and associated trade-offs. This is a burgeoning field that seeks to balance computational efficiency with acceptable accuracy. The paper highlights opportunities where these techniques can be effectively applied, such as in applications where perfect accuracy is not a strict requirement. This paper presents assessments of applying approximate computing techniques in various applications, especially machine learning algorithms (ML) and IoT. Furthermore, this review underscores the challenges encountered in implementing approximate computing techniques and highlights potential future research avenues. The anticipation is that this survey will stimulate further discourse and underscore the necessity for continued research and development to fully exploit the potential of approximate computing
Blockchain Financial Statements: Innovating Financial Reporting, Accounting, and Liquidity Management
Get PDFData Availability Statement: Data are contained within the article.The complexity and interconnection within the financial ecosystem demand innovative solutions to improve transparency, security, and efficiency in financial reporting and liquidity management, while also reducing accounting fraud. This paper presents Blockchain Financial Statements (BFS), an innovative accounting system designed to address accounting fraud, reduce data manipulation, and misrepresentation of company financial claims, by enhancing availability of the real-time and tamper-proof accounting data, underpinned by a verifiable approach to financial transactions and reporting. The primary goal of this research is to design, develop, and validate a blockchain-based accounting prototype—the BFS system—that can automate transformation of transactional data, generated by traditional business activity into comprehensive financial statements. Incorporating a Design Science Research Methodology with Domain-Driven Design, this study constructs a BFS artefact that harmonises accounting standards with blockchain technology and business orchestration. The resulting Java implementation of the BFS system demonstrates successful integration of blockchain technology into accounting practices, showing potential in real-time validation of transactions, immutable record-keeping, and enhancement of transparency and efficiency of financial reporting. The BFS framework and implementation signify an advancement in the application of blockchain technology in accounting. It offers a functional solution that enhances transparency, accuracy, and efficiency of financial transactions between banks and businesses. This research underlines the necessity for further exploration into blockchain’s potential within accounting systems, suggesting a promising direction for future innovations in tamper-evident financial reporting and liquidity management.This research received no external funding
A two-stage underfrequency load shedding strategy for microgrid groups considering risk avoidance
Get PDFData availability: The data that has been used is confidential.Underfrequency load shedding is the third level protection measure to ensure the safe and stable operation of power systems, which can effectively prevent the rapid decrease in system frequency caused by power system failure. To compensate for the power deficit resulting from faults during the island operation of a microgrid, a two-stage underfrequency load shedding strategy for microgrid groups considering risk avoidance is proposed in this paper. The proposed strategy divides underfrequency load shedding into a fast load shedding stage and a risk avoidance load shedding strategy. The first stage is fast underfrequency load shedding considering the load frequency characteristics and voltage characteristics; the fast underfrequency load shedding in the first stage reduces the fast frequency decrease before the second stage load shedding operation. The second stage of load shedding is risk avoidance under frequent load shedding. The load shedding in this stage accounts for the risk loss caused by the nondeterminacy of the demand side load to the system load shedding while accounting for the load frequency and voltage characteristics. First, the conditional value at risk (CVaR) theory is introduced in this paper to analyze and determine the risk loss caused by load nondeterminacy on load shedding, and the severity of load shedding (SoLS) is adopted as the CVaR value of load shedding. Second, the underfrequency load shedding optimization model is constructed by taking the risk value of the load shedding conditions of the microgrid as the optimization index of load shedding. Finally, the performance of the proposed strategy is verified based on the improved IEEE-37 node system microgrid group model. The results show that the proposed two-stage load shedding strategy can effectively prevent a rapid decrease in system frequency and effectively reduce the risk loss caused by load nondeterminacy during load shedding.Supported in part by the National Natural Science Foundation of China under Grant 52107108, and in part by the Natural Science Foundation of Hubei Province under Grant 2021CFB163
‘The very latest, modom’: The British Commercial Gas Association, the Gas Light and Coke Company and content marketing in interwar Britain
Get PDFContent marketing involves the production of creative content by organisations to engage and develop relations with consumers. It has been practiced since at least the eighteenth century. Despite its longevity, there has been no detailed historical study of content marketing. This article seeks to fill this lacuna by examining the use of content marketing by the British gas industry in the interwar period (1918–1939). During this period, the gas industry faced fierce competition from electricity. It responded with the development of content. This included print, music, films, showrooms, exhibitions, cookery demonstrations and public housing. This paper will provide a historic case study of this content marketing. Through publicity and public relations, this content was consciously and strategically used by the gas sector alongside advertising, distribution, and sales. It was used to influence public opinion, reinforce advertising, and build a brand for the gas industry
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