Actual Implementation Research Articles

Intermediate hepatitis C virus (HCV) endemicity and its genotype distribution in Myanmar: A systematic review and meta-analysis.

Comprehensive details on Hepatitis C virus (HCV) infection in Myanmar are lacking. This study determined the prevalence of HCV antibodies and ribonucleic acid (RNA) and the distribution of HCV genotypes across different populations in Myanmar from 1990 to 2023. A systematic search in PubMed, Web of Science, Scopus, and local journals identified studies reporting on HCV antibodies, RNA, and genotypes, excluding clinical research related to liver disease prognosis. Screening and data extraction was done by two authors and study populations were categorized into low-risk, high-risk, liver disease patients, and refugees outside the country. The pooled prevalence was performed by Dersimonian and Laird method using the R program. The publication bias was shown by funnel plot, the Egger test was used to assess the symmetry of the plot, and the heterogeneity was examined by the Cochran Q test and I2 index. Out of 135 reports screened for eligibility, 35 reports comprising 51 studies were included in which 33 studies provided data on HCV seroprevalence in 685,403 individuals, 8 studies reported HCV RNA prevalence in 25,018 individuals, and 10 studies examined HCV genotypes in 1,845 individuals. The pooled seroprevalence of HCV among low-risk, high-risk, liver disease patients and refugees were 2.18%, 37.07%, 33.84%, and 2.52% respectively. HCV RNA-positive rates in these groups were 1.40%, 5.25%, 24.96%, and 0.84% respectively. Seroprevalence studies showed publication bias (Egger test, p = 0.0001), while RNA studies did not (Egger test, p = 0.8392). HCV genotype 3 was predominant in all sub-groups in Myanmar. Our study shows Myanmar has intermediate HCV endemicity with lowest HCV prevalence of 2.18% in low-risk groups and highest prevalence of 37.07% in high- risk groups. However, the findings highlight the need for further epidemiological studies to understand actual disease burden and implement effective countermeasures to achieve the WHO's goal of HCV elimination by 2030.

A Closed Formalism for Anatomy-Independent Projection and Optimization of Magnetic Stimulation Coils on Arbitrarily Shaped Surfaces.

Transcranial magnetic stimulation (TMS) is a popular method for the noninvasive stimulation of neurons in the brain. It has become a standard instrument in experimental brain research and has been approved for a range of diagnostic and therapeutic applications. These applications require appropriately shaped coils. Various applications have been established or approved for specific coil designs with their corresponding spatial electric field distributions. However, the specific coil implementation may no longer be appropriate from the perspective of available material and manufacturing opportunities or considering the latest understanding of how to achieve induced electric fields in the head most efficiently. Furthermore, in some cases, field measurements of coils with unknown winding or a user-defined field are available and require an actual implementation. Similar applications exist for magnetic resonance imaging coils. This work aims at introducing a complete formalism free from heuristics, iterative optimization, and ad-hoc or manual steps to form practical stimulation coils with individual turns to either equivalently match an existing coil or produce a given field. The target coil can reside on practically any sufficiently large or closed surface adjacent to or around the head. The method derives an equivalent field through vector projection exploiting the well-known Huygens' and Love's equivalence principle. In contrast to other coil design or optimization approaches recently presented, the procedure is an explicit forward Hilbert-space vector projection or basis change. For demonstration, we map a commercial figure-of-eight coil as one of the most widely used devices and a more intricate coil recently approved clinically for addiction treatment (H4) onto a bent surface close to the head for highest efficiency and lowest field energy. The resulting projections are within ≤4% of the target field and reduce the necessary pulse energy by more than 40%.

Target Tracking Two Degrees of Freedom State Feedback Control for Continuous Flow Microfluidic Chips Temperature Controller

Microfluidic chips represent a cutting-edge technology for manipulating fluids within micrometer-scale spaces and are gradually becoming a new favorite platform in life science research. Precise and fast zonal temperature control is essential for accelerating biological experiments. However, current multi-channel temperature controllers typically rely on multiple channel sets to achieve single set-point control, which results in discrepancies between the fluid temperature distribution and sensor temperature due to the distributed temperature field in the fluid channel. To estimate the actual temperature and implement gradient temperature control, this paper introduces an extension of the target tracking (TT) two degrees of freedom (2DOF) state feedback control (SFC) method, followed by a presentation of simulation and experimental results. Through comparisons with an enhanced PID system in both simulation and experimentation, the paper demonstrates an 8.96% reduction in the maximum temperature difference across different regions and a 27.89% decrease in the time taken to reach various temperatures. This solution effectively addresses the existing challenges in temperature control for microfluidic chips, offering a more precise and stable control within the desired temperature range.

Implementing AI in the public sector

ABSTRACT Artificial Intelligence (AI) has advanced as one of the most prominent technological innovations to push the conversation about the digital transformation of the public sector forward. This special issue focuses on actual implementation approaches or challenges that public managers are facing while they fulfil new policy that asks for the implementation of AI in public administrations. In addition to assessing the contributions of papers in this issue, we also provide a research agenda on how future research can fill some of the methodological, theoretical, and application gaps in the public management literature.

MaskCAE: Masked Convolutional AutoEncoder via Sensor Data Reconstruction for Self-Supervised Human Activity Recognition.

Self-supervised Human Activity Recognition (HAR) has been gradually gaining a lot of attention in ubiquitous computing community. Its current focus primarily lies in how to overcome the challenge of manually labeling complicated and intricate sensor data from wearable devices, which is often hard to interpret. However, current self-supervised algorithms encounter three main challenges: performance variability caused by data augmentations in contrastive learning paradigm, limitations imposed by traditional self-supervised models, and the computational load deployed on wearable devices by current mainstream transformer encoders. To comprehensively tackle these challenges, this paper proposes a powerful self-supervised approach for HAR from a novel perspective of denoising autoencoder, the first of its kind to explore how to reconstruct masked sensor data built on a commonly employed, well-designed, and computationally efficient fully convolutional network. Extensive experiments demonstrate that our proposed Masked Convolutional AutoEncoder (MaskCAE) outperforms current state-of-the-art algorithms in self-supervised, fully supervised, and semi-supervised situations without relying on any data augmentations, which fills the gap of masked sensor data modeling in HAR area. Visualization analyses show that our MaskCAE could effectively capture temporal semantics in time series sensor data, indicating its great potential in modeling abstracted sensor data. An actual implementation is evaluated on an embedded platform.

Who Should We Blame for Android App Crashes? An In-Depth Study at Scale and Practical Resolutions

Android system has been widely deployed in energy-constrained IoT devices for many practical applications, such as smart phone, smart home, healthcare, fitness, and beacons. However, Android users oftentimes suffer from app crashes, which directly disrupt user experience and could lead to data loss. Till now, the community have limited understanding of their prevalence, characteristics, and root causes. In this article, we make an in-depth study of the crash events regarding ten very popular apps of different genres, based on fine-grained system-level traces crowd-sourced from 93 million Android devices. We find that app crashes occur prevalently on the various hardware models studied, and better hardware does not seem to essentially relieve the problem. Most importantly, we unravel multi-fold root causes of app crashes, and pinpoint that the most crashes stem from the subtle yet crucial inconsistency between app developers’ supposed memory/process management model and Android’s actual implementations. We design practical approaches to addressing the inconsistency; after large-scale deployment, they reduce 40.4% of the app crashes with negligible system overhead. In addition, we summarize important lessons learned from this study, and have released our measurement code/data to the community.

A Collaborative Compression Scheme for Fast Activity Recognition on Mobile Devices via Global Compression Ratio Decision

Despite strong representation ability, deep convolutional neural networks (CNNs) are largely hindered in practical human activity recognition (HAR) deployment due to high computational cost, which is often unaffordable on resource-limited wearable devices. In this paper, to bridge the gap between on-device HAR and deep learning, we present a collaborative compression scheme to reduce the runtime of HAR with an acceptable performance degradation, which combines channel pruning and tensor decomposition to simultaneously handle sparsity and low-rankness when fully considering mutual interference in one network consisting of efficient 1-dimensional convolutional kernels. Our method includes two main stages. Concretely, given a target compression ratio, a global compression ratio decision optimization is first performed to automatically decide per-layer compression ratio by measuring compression sensitivity, without requiring labor-exhaustive human intervention. Then a multi-step collaborative compression is iteratively implemented to remove the least important compression unit based on an improved importance metric until the per-layer target compression ratio is attained. Extensive experiments on multiple HAR benchmarks show that our approach considerably outperforms previous compression strategies. For example, it can achieve around 50% FLOPs reduction with only an accuracy drop of 0.25% and 0.15% on UCI-HAR and PAMAP2, respectively. Actual implementation is evaluated on an embedded platform.

English teachers’ beliefs and practices in integrating digital literacy in the language classroom

This case study investigates teachers’ beliefs (i.e., behavioral, normative, and control beliefs) and practices in integrating digital literacy in English as foreign language (EFL) classroom. A descriptive study on EFL teachers is used in this research. Four participants were purposively selected to give sufficient information to answer the research questions. Data from the participants were collected by using interviews, observation, and documentation. In terms of the teachers’ beliefs, the finding shows that the behavioral belief was related to the benefits of using digital literacy; normative belief dealt with the expectation in the social context of both superiors and peers; while control belief was about the availability of particular digital technology to be implemented in the classroom and the ability of teachers. With regard to the teachers’ practices, it was found that the teachers used several digital tools for searching for information, communication, collaboration, creativity, critical thinking, cultural understanding, and e-safety. It was evident that teachers’ strong beliefs in integrating digital literacy influence the implementation of digital literacy in the classroom. The findings of this study highlight the importance of cultivating teachers’ beliefs toward the actual implementation of the integration of digital literacy in the EFL classroom.

Unveiling the nexus of climate change, adaptation strategies, and food security: Insights from small-scale farmers in zagros mountains in Iran

In today's world, climate change and its unprecedented impact on food and nutrition security have emerged as a significant and formidable global challenge. This study aimed to investigate the effect of adaptation strategies on the food security of small-scale farmers in Khorramabad city, Iran, using a survey-based analysis. To assess the food security level, the Household Food Security Survey Module (HFSSM) was employed. Additionally, Structural Equation Modeling was utilized to examine the relationship between adaptation dimensions and food security. The findings revealed that households without children exhibited a higher level of food security (48%) compared to households with children (6%). Moreover, the results demonstrated a positive and significant correlation between the food security of households, regardless of whether they had children, and the different adaptation components. Despite a satisfactory level of knowledge regarding climate change adaptation in the study area, the actual implementation of such measures remained low. While weed management, agricultural crop insurance, and access to meteorological information were identified as the top three strategies employed by farmers, the results suggested that sustainable-oriented operations and organic-oriented practices could serve as more effective strategies for both climate change resilience and enhancing food security status.

Recent Progress in Floating Solar Photovoltaic Systems: A Review from Malaysia’s Perspective

Floating solar photovoltaic (FPV) technology has been gaining popularity in various parts of the world to address the growing clean energy demand and land scarcity challenges posed by conventional solar PV installations. This paper presents a comprehensive review of the recent progress in FPV research and actual implementations, highlighting advancements, challenges, and future prospects in this dynamic and promising field in Malaysia.

Film Cooling Modeling in a Turbine Working under the Unsteady Exhaust Flow of Pulsed Detonation Combustion

Pressure gain combustors (PGCs) have demonstrated significant advantages over conventional combustors in gas turbine engines by increasing the thermal efficiency and reducing the pollution emission level. PGCs use shock waves to transfer energy which contributes to the increase in outlet total pressure. One of the major obstacles in the actual implementation of PGCs in the gas turbine cycle is the exploitation of the highly unsteady flow of the combustor outlet with the downstream turbine. Because of the higher outlet temperature from the PGCs, the turbine blade cooling becomes essential. Due to the highly fluctuating unsteady flow of PGCs, 3D CFD simulation of turbines becomes very expensive. In this work, an alternative approach of using a 1D unsteady Euler model for the turbine is proposed. One of the novel aspects of this paper is to implement the turbine blade cooling in the unsteady 1D Euler model. The main parameters required for the turbine blade cooling are the cooling air mass flow rate, temperature, and pressure. Due to the introduction of coolant flow, the blades are no longer adiabatic and the mass flow rate across the turbine is not constant. Comparing the 1D Euler results against zero-dimensional calculation and 3D CFD approach showed a very good match for both steady and unsteady simulations confirming the applicability of the 1D method.

The Impact of Minority Veto in Consociational Democracies

Abstract Developing governance models that are suitable for the effective management of ethnically divided societies arising from conflicts presents a significant challenge for both scholars and peace mediators. The consociational model, founded on power-sharing principles, has emerged as a means of guiding groups which were previously in conflict towards creating institutional frameworks that can help manage divisions and promote peaceful coexistence. In situations where mutual trust is lacking and deep-seated ethnic, religious, or linguistic divisions persist, it is unrealistic to anticipate that minority groups would willingly grant unrestricted decision-making authority to the majority. Consequently, the notion of constraining the majority’s decision-making powers on specific matters, unless it has the consent of minority groups through the implementation of veto rights, has become a fundamental principle for negotiating post-conflict institutional arrangements. This article aims to investigate the practical ramifications of veto rights within consociational systems, focusing on their incorporation into Kosovo’s legal framework post-2008 and their actual implementation in the years that followed. The article seeks to shed light on how veto rights contribute to consensus-based decision-making, the potential for disruption when exploited by irresponsible political leaders, and the possibilities of revisiting these arrangements to address any shortcomings.

WiMAX Network Optimization Using Frame Period with Channel Allocation Techniques

Internet connectivity in WiMAX networks, along with various applications, is increasing rapidly, so the connectivity of internet and data transfer speed are always challenge for effective data transmission in wireless networks. Several factors affect the performance of networks. One important factor is to choose a suitable frame period for effective data transmissions. The performance of different frame period with round-robin and strict priority are evaluated in this work. A frame period in round robin performs better than a strict priority in terms of throughput, but a strict priority performs better in terms of drop rates is observed. This paper also demonstrates that an effective frame period, when combined with a proper bandwidth allocation algorithm, yields better results. This work gives the analysis that round robin performs 83.8847% better while strict priority performs 86.0020% better than the earliest deadline first algorithms for 10 subscriber stations in terms of throughput. This work is helpful to researchers and industrialists for actual implementations in WiMAX networks.

Lean manufacturing in the last decade: insights from published case studies

PurposeLean manufacturing (LM) concepts have been widely adopted in diverse industrial sectors. However, no literature review focusing on case studies describing LM implementation is available. Case studies represent the actual implementation and provide secondary data for further analysis. This study aims to review the same to understand the pathways of LM implementation. In addition, it aims to analyse other related review questions, such as how implementing LM impacts manufacturing capabilities and the maturity level of manufacturing organisations that implemented LM, to name a few.Design/methodology/approachA literature review of case studies that discuss the implementation of LM during the last decade (from 2010 to 2020) is carried out. These studies were synthesised, and content analyses were performed to reveal critical insights.FindingsThe implementation pattern of LM significantly varies across manufacturing organisations. The findings show simultaneous improvement in manufacturing capabilities. Towards the end of the last decade, organisations implemented LM with radio frequency identification, e-kanban, simulation, etc.Originality/valueReviewing the case studies documenting LM implementation to comprehend the various nuances is a novel attempt. Furthermore, potential future research directions are identified for advancing the research in the domain of LM.

Navigating menopause at work: a preliminary study about challenges and support systems.

Women's increasing workforce participation necessitates understanding unique life phases like menopause for enhanced workplace inclusivity. This research investigates the challenges and needs of peri-menopausal women in work settings, using the Job Demands-Resources model as a foundation. A cross-sectional survey was administered to 351 working women aged 40 to 65 years in the United States. Hierarchical multiple regression models were employed to assess the relationship between the severity of menopausal symptoms, emotional exhaustion, work engagement, and turnover intentions. Most of the respondents reported moderate (38.46%) to severe (35.9%) menopausal symptoms. Notably, 54% of the women were caregivers for children or adults. About 77.7% of participants reported work-related challenges due to menopause, with a perceived reduction in productivity (56.8%) being the most common issue. The severity of menopausal symptoms was found to significantly predict more emotional exhaustion ( P < 0.001), less work engagement ( P < 0.001), and greater turnover intentions ( P = 0.03). Concerns about being perceived as less capable in the workplace due to menopausal symptoms were reported by 51.2% of respondents. A striking gap exists between the workplace measures desired by women, such as formal menopause policies and managerial training (65.4%-68%), and their actual implementation (2%-6.3%). This study reveals an exigent need for increased awareness and structural changes to support working women going through menopause. The findings have far-reaching implications for not just promoting gender equity and well-being but are also pivotal for maintaining a diversified, engaged, and effective workforce.

Multifaceted validity analysis of clinical skills test in the educational field setting

Introduction: The importance of clinical skills training in traditional Korean medicine education is increasingly emphasized. Since the clinical skills tests are high-stakes tests that determine success in national licensing exams, it is essential to develop reliable multifaceted analysis methods for clinical skills tests in actual education settings. In this study, we applied the multifaceted validity evaluation methods to the evaluation results of the cardiopulmonary resuscitation module to confirm the applicability and effectiveness of the methods.Methods: In this study, we used internal consistency, factor analysis, generalizability theory G-study and D-study, ANOVA, Kendall's tau, descriptive statistics, and other statistical methods to analyze the multidimensional validity of a cardiopulmonary resuscitation test in clinical education settings over the past three years.Results: The factor analysis and internal consistency analysis showed that the evaluation rubric had an unstable structure and low concordance. The G-study showed that the error of the clinical skills assessment was large due to the evaluator and unexpected errors. The D-study showed that the variance error of the evaluator should be significantly reduced to validate the evaluation. The ANOVA and Kendall's tau confirmed that evaluator heterogeneity was a problem.Discussion and Conclusion: Clinical skills tests should be continuously evaluated and managed for validity in two steps of pre-production and actual implementation. This study has presented specific methods for analyzing the validity of clinical skills training and testing in actual education settings. This study would contribute to the foundation for competency-based evidence-based education in practical clinical training.

Ox-Ethnio: Blockchain E-Voting System

Abstract: In comparison to conventional paper-based systems, electronic voting, or e-voting, offers many benefits, including increased efficiency and fewer mistakes. It has developed into many different forms. However, gaining public approval of these systems remains a constant problem, especially when it comes to making them more resilient to possible weaknesses. With its potential to increase the overall resilience of electronic voting systems, blockchain technology is emerging as a market disruptor. With the use of blockchain technology, this project aims to create an efficient e-voting infrastructure by using its transparency and cryptographic underpinnings. The proposed technique satisfies the essential requirements for electronic voting systems and offers end-to-end variabilities essay delves into the planned e-voting mechanism and its actual implementation on the Multichain platform in great depth. Furthermore, Electronic voting systems, when applied in elections, need to uphold legality, accuracy, security, and convenience. Nevertheless, the potential challenges associated with digital voting methods can impede their widespread adoption. Blockchain technology has emerged as a promising solution to address these concerns, offering decentralized networks for electronic voting. Its main appeal lies in the ability to provide end-to-end verification, making it a preferred choice for developing electronic voting systems.

Public governance in the context of Construction 4.0: a systematic and comprehensive literature review

PurposeBy providing an overview of the existing knowledge on public governance in the context of Construction 4.0, this review serves as a valuable resource for researchers, policymakers and practitioners interested in understanding the current state of public governance in the context of Construction 4.0 and identifying avenues for future research and practical implementation.Design/methodology/approachThis article presents a systematic and comprehensive review of the academic literature on public governance in the context of Construction 4.0. To ensure a systematic and rigorous selection of source material, the study adopts the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.FindingsBy examining a wide range of scholarly works, the review identifies and discusses eight recurring themes that are crucial for understanding the role of public governance in Construction 4.0. These themes include policy and regulation, infrastructure and investment, skill development and education, digital inclusion and access, collaboration and partnerships, data governance and privacy, interactions with environmental and societal goals and the impact of Construction 4.0 on public governance itself. The review highlights a significant disparity between the normative debates on the importance of public governance in Construction 4.0 and the empirical knowledge available regarding its practical implementation. While the literature emphasizes the need for effective governance mechanisms to address the challenges and opportunities presented by Construction 4.0, there is a notable lack of empirical research examining the actual implementation and outcomes of public governance strategies.Originality/valueThis is the first systematic review of academic literature on public governance in the context of Construction 4.0.

Characteristics of water supply network zoning

Relevance. The original studies of water supply network and network exploitation data, as well as international experience, applied in similar conditions, and the data of existing literature, data of works on water supply zoning, which were carried out in the networks of various settlements in the Republic of Armenia, have been improved and are now being implemented effectively through the clear procedure developed by us. In our case, zoning is carried out under the conditions of the existing system, therefore the methods developed during design and reconstruction work consider the features of the existing system.Aim. To develop a technique to enhance the efficiency of water supply systems by implementing network zoning. It involves transforming the network into hydraulically separated zones isolated from each other. Within each zone, water supply can be regulated based on consumption requirements. Objects. The article discusses issues related to design and reconstruction procedures of existing water supply network zones. It defines the priority of zoning implementation for the current stage and proposes a method for assessing the permissible level of losses, taking into account the technical condition of the water supply network. Methods. The calculations for this study were performed using well-known hydraulic principles and laws. Experimental studies were conducted directly on the water supply network under production conditions. Results. The actual implementation of these measures in various urban locations revealed that reduction in water usage in a service zone was only 8–10%. However, analysis of the functioning of the reconstructed zones led to the conclusion that the already constructed zones now offer suitable conditions for productive work on leak detection and elimination. In the given example, during the operation of the study zone, 4300 m (about 25%) of the existing 17400 m pipelines in the reconstruction zone were decommissioned, along with 13 of 22 pumping stations. Over two years of work, the cost of electricity at the existing yard pumping stations was reduced by more than six times, the total cost of electricity in the zone was reduced by more than twelve times, and the amount of water entering the zone was reduced by 44% as a result of the water supply system reconstruction presented in the example.

Attractiveness and gender dynamics in surgical specialties: a comparative analysis of French medical graduates (2017–2022)

BackgroundFrench medical graduates undertake a national examination at the end of their studies with a subsequent national ranking. Specialty is then chosen by each candidate according to their ranking. This study aims to describe the attractiveness of surgical specialties and the evolution of the male-female distribution among French medical graduates (FMG) from 2017 to 2022.MethodsOur database included the candidates’ ranking, sex and choice of specialty from 2017 to 2022. It included all French medical graduates from 2017 to 2022 and all French medical schools. A linear regression was performed to predict future trends. Dependent variables were mean rankings and the percentage of women. The independent variable was year of application. A Pearson correlation was performed to examine any relationship with mean workweek.ResultsA total number of 5270 residents chose a surgical programme between 2017 and 2022. The number of residents who were assigned their desired surgical programme held stable at 878 surgical residents per year. Plastic and reconstructive surgery remained the most frequently chosen surgical programme. Thoracic and cardiovascular surgery was the least frequently chosen surgical programme between 2017 and 2022. The mean ranking for a candidate choosing a surgical programme rose significantly by 9% from 2017 to 2022 (p < 0.01). Neurosurgery exhibited the greatest fall as a surgical specialty as its rankings decreased by 163.6% (p < 0.01). Maxillo-facial surgery was the only specialty with a statistically significant increase in its rankings by 35.9% (p < 0.05). The overall proportion of women was 51.1%. Obstetrics-and-gynecology was the highest represented specialty among female candidates, with a mean of 83.9% of women. Orthopedic surgery was the lowest represented, being composed of a mean of 28.6% of women. The number of female surgical residents increased significantly over the six-year period, by 7.6% (p < 0.01).ConclusionsMore and more medical school graduates decide not to choose surgery for their residency programme. Some specialties continue to be attractive while many are losing their appeal. While there does appear to be progress towards gender equity, further investigation is necessary to assess its actual implementation.