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Digital games are one of the most engaging forms of media. Players can have a first-hand experience and the possibility of feeling immersed within a digital setting where agency is exerted. This paper seeks to understand the role of digital games as new means of communication and their potential to convey messages that may defy gamers to question the moral grand narratives that shape contemporary societies. In a moment when many countries have opted to close or limit the circulation in their borders, it is important to think about the role played by the border as a historic liminal entity for the representation of societies and communities, distinguishing those who belong from those who do not. The representation of the border in digital games have tended to follow one of the main tropes explored in other media: the border as a physical space that set boundaries between different nations and different regions of the world. In order to assert the potential of digital games to offer a more comprehensive representation of the border as a liminal space, the case of Papers, Please! (2013) will be analyzed. Based on a qualitative methodology, having content analysis as primary data collection method, the paper intends to contribute to the discussion on how history may narrativized and, eventually, reinterpreted in digital games. Papers, Please! analysis will be centered on the relationship that is set between player and border, that is presented as a liminal space where the game's action takes places entirely. Moreover, the paper intends to discuss the role that has been played by digital games in the representation of serious topics and how they have evolved as communication tools beyond their role as entertainment products. [ABSTRACT FROM AUTHOR]

Background : The current UK standard for major trauma patients is to record notes in a paper trauma booklet. Through an innovative collaboration between a major trauma centre and a digital transformation industry partner, a TraumaApp was developed. Electronic notes have been shown to have fewer errors, granular data collection and enable time stamped contemporaneous record keeping. Implementation of digital clinical records presents a challenge within the context of trauma multidisciplinary trauma resuscitation. Data can be easily accessible and shared for quality improvement, audit and research purposes. This study compared paper and electronic notes for completeness and for acceptability data following the implementation of the TraumaApp. Methods: Trauma team members who performed scribe function attended training for the newly launched TraumaApp. Two staff members acted as scribe, using either the paper trauma booklet or TraumaApp, and attended major trauma calls. A framework for comparison of paper and electronic notes was created and used for a retrospective review of major trauma patients' notes. Statistical analysis was performed using a two-tailed t-test. Staff using the TraumaApp completed a System Usability Score questionnaire. Results: There was a total of 37 data points for collection per case. The mean numbers collected were paper notes 24.1 of 37 (65.1%) and electronic notes, 25.7 of 37 (69.5%). There was no statistical significance between the completeness of paper and electronic notes. The mean System Usability Score was 68.4. Discussion: Recording accurate patient information during a major trauma call can be challenging and the role of the scribe to accurately record events is critical for immediate and future care. There was no statistically significant difference in completeness of paper and electronic notes, however the mean System Usability Score was 68.4, which is greater than the internationally validated standard of acceptable usability. Conclusion: It is feasible to introduce digital data collection tools enabling accurate record keeping during trauma resuscitation and improve information sharing between clinicians. [ABSTRACT FROM AUTHOR]

mHealth applications (apps) are tools that can enhance research by efficiently collecting and storing large amounts of data. However, data collection alone does not lead to change. Innovation and practice change occur through utilisation of evidence. The volume of data collected raises questions regarding utilisation of data by nurses and midwives, and how data from mHealth apps can be used to improve person-centred practice. There is limited empirical evidence and a lack of direction from global health authorities to guide nurses and midwives in this area. To describe strategies for nurses and midwives that could enhance the effective use of data generated by mHealth apps to inform person-centred practice. The purpose of this paper is to stimulate reflection and generate actions for data utilisation when using mHealth apps in nursing research and practice. This discussion paper has been informed by current evidence, the integrated-Promoting Action on Research Implementation in Health Services (i-PARIHS) framework, and research experience as part of doctoral study. Before engaging in data collection using mHealth apps, nurses and midwives would benefit from considering the nature of the evidence collected, available technological infrastructure, and staff skill levels. When collecting data and interpreting results, use of a team approach supported by engaged leadership and external facilitation is invaluable. This provides support to operate apps, and more importantly use the data collected to inform person-centred practice. This paper addresses the limited available evidence to guide nurses and midwives when using mHealth apps to collect and use data to inform practice change. It highlights the need for appropriate technology, external facilitative support, engaged leadership, and a team approach to collect meaningful evidence using mHealth apps. Clinicians, leaders, and researchers can apply the strategies provided to enhance the use of mHealth apps and ensure translation of evidence into practice. [ABSTRACT FROM AUTHOR]

Background Research theses can have a significant impact on the development of applied sciences, especially when their results are published. Objective This study aims to determine publication rate of papers extracted from the medical residency and master’s degree theses of Guilan University of Medical Sciences (GUMS) during 2008-2018. Methods This is a descriptive cross-sectional study. The data were collected from the medical residency and master’s degree theses of GUMS from 2008 to 2018. Then, they were searched in international and national databases according to the title, keywords, and names of supervisors, advisors, and students. Results Of 774 theses, 449 (58 %) papers had been extracted and published in journals indexed by ISI/ PubMed (41.2%), Scopus (11.8%), BIOSIS, Chemical Abstract, and Embase (0.44%) and others (46.56%). Most of them (98.66%) were original research. Moreover, in 383(85.3%) of the theses, there was no statistician or data advisor. The median time from defending theses to the publication of a paper from them was two years. Conclusion The publication of papers extracted from the theses of GUMS has increased, and more than 50% of them have been published in journals indexed by ISI, PubMed, and Scopus. However, the factors associated with the publication of papers need to be surveyed. [ABSTRACT FROM AUTHOR]

• Remote testing is suitable when performing complex tests requiring careful training. • One-solution test is reliable to assess PROP status in live remote condition. • PROP impregnated paper disks are a valid alternative to solutions in lab setting. • PROP disks can be used out-of-lab if a strict control is provided by the personnel. • Reliable remote testing procedures will promote research in vulnerable populations. Solutions and paper disks are widely used methods for classifying people by their ability to perceive 6-n-propylthiouracil (PROP). Recently, remote sensory testing carried out under the supervision of the panel leader, has been found to be a valid alternative to the traditional lab-setting, offering several practical advantages. This study aimed to validate a protocol for PROP status assessment in remote condition and to compare the results obtained using solutions and paper disks. Individual differences in bitterness responsiveness and the relative classification between two different testing conditions (remote and laboratory) and two stimuli (solutions and disks) were compared. 77 subjects (18–30 years; 60 % women) participated in two sessions (one in laboratory and one in remote setting) and rated the perceived intensity of PROP solutions and disks. Mean PROP ratings did not vary across remote and lab conditions (p = 0.844). PROP phenotype classifications in remote-solution and lab-disk conditions were comparable to lab-solution reference condition (with a misclassification rate of 27 % and 31 % respectively, all occurring within contiguous groups). In contrast, the classification in remote-disk condition was not fully comparable (misclassification in respect to lab-solution of 48 % in contiguous groups, and 1.3 % in non-contiguous groups). One-solution test appears as a reliable procedure for PROP status assessment in live remote testing. Also, impregnated paper disks represent a suitable alternative to solution testing in conventional lab setting for practical reasons. However, paper disks could represent a valid option for data collection outside the lab, but they require rigorous in-person control by the sensory personnel when used. [ABSTRACT FROM AUTHOR]

In this paper, we propose a method of generating the elemental image array (EIA) for the integral imaging (InIm) based light field display (LFD). Firstly, we reveal the intrinsic voxel spatial distributions of the InIm‐based LFD and analyze how the voxel space affects the display performances such as spatial resolution, depth of field, and smoothness of parallax. Then, we present an algorithm to generate an EIA from a pair of RGB and depth (RGBD) images and an optimally selected voxel space. In the experiments, we tested the display performances of the voxels on different depth planes and obtained results consistent with the theoretical analyses. We also experimented with a computer 3D model and a real‐world scene on two InIm‐based LFD prototypes working in different modes, one in real mode and the other in virtual mode, and obtained favorable 3D display effects. The proposed method simplifies the light field data acquisition and image synthesis process, and supports handling both the virtual and the real‐world 3D scenes. We expect the proposed system to help the practical application of the InIm‐based LFD technology. [ABSTRACT FROM AUTHOR]

The global rise of data volume from Zettabyte to Yottabyte raises concerns about effectively managing its use and storage. One concern is dark data, which needs to be tapped and used for critical decision-making and insights generation. This phenomenon is a reality in the data economy that requires a solution through productization. The term data economy refers to the expanding economic activity centered around data collection, analysis, and sale. With the digitization of society and the exponential growth of the internet and social media, individuals, organizations, and society are continuously generating and collecting massive amounts of data. This data can be invaluable for companies and institutions to gain insights into customer behavior, market trends, and the performance of their businesses. Despite the scholarly literature that provides some insights, there remains a need for further exploration and clarification of the intersection between the data economy and productization. This study addresses these unresolved issues by thoroughly analyzing academic and industrial literature. The study contributes to the existing body of knowledge by extending the TTF (Task-Technology Fit) theory to conceptualize the relationship between data economy and productization. The study also proposes a comprehensive framework for countries, organizations, and institutions and offers theoretical and managerial implications. It is important to note that this study has its limitations, and future research should address these limitations and further advance the understanding in this research domain. [ABSTRACT FROM AUTHOR]

This paper proposes diary studies as a methodological choice for addressing crucial questions in qualitative process research. Diary studies unearth within-individual relationships that capture individual experiences and sense-making of these experiences in a processual manner. Therefore, using diary studies not only addresses the need for more dynamic methodological designs in qualitative research, but is advantageous for providing a process view of how the individual engages with the constructs studied. While process-studies, studied longitudinally, are often fraught with challenges of attrition or disengagement, this paper discusses how a methodological choice which is perceived as being beneficial by the participant can sustain engagement and consequently, research rigour. On one hand, a comparison of interview and diary data from the same participants show evidence of memory decay in interviews and reinforce the rigour of diary studies in the study of processual phenomenon. On the other hand, this study also showcases how researcher know-how, unintentionally imparted through reflective and processual questions asked in the study positively impacts the participants, and when reflected on, enhanced learning. This paper therefore demonstrates the ability of a research method to benefit both the research and the researched, and suggests a step-by-step design to implement a rigorous and impactful diary study using user-friendly forms and reflective questioning. [ABSTRACT FROM AUTHOR]

Global science is set to experience different times in the 2020s. China surpasses the USA in terms of the number of scientific papers in 2020 in most scientific databases. This scenario is expected to have implications not only in East Asia but also beyond the region. Against this backdrop, this paper investigates the scientific influence of the US-China competition on six major Muslim-majority science systems. Multiple data sources are used to collect data for the bibliometric analyses, which include the trend analysis of collaboration patterns, discipline-based collaborations, authorship patterns for responsibility in collaborations, and citation premium of collaborations with the USA versus China. All the analyses consistently demonstrate that the USA is losing its scientific influence on the selected Muslim-majority science systems to China. Analysis results indicate an astonishing increase in collaborations with China-based scientists in the last decade. Half of the selected Muslim-majority science systems collaborate more with China-based scientists, whereas the other half collaborate more with the USA in 2021, indicating a fifty-fifty split. The collaborations with China-based authors garner higher citation premiums for the selected Muslim-majority science systems than the collaborations with the USA. [ABSTRACT FROM AUTHOR]

The original article can be found online at https://doi.org/10.1186/s12874-023-01833-8.Correction: BMC Med Res Methodol 23, 10 (2023)https://doi.org/10.1186/s12874-023-01833-8Following publication of the original article [[1]], the authors reported an error in the Fig. 4: the colours in the pie charts in Fig. 4 do not all correspond with the legend. See the Fig. 4 corrected.Graph: Fig. 4 Breakdown of total costs across the surveysThe original article [[1]] has been updated.By Siân Harrison; Fiona Alderdice and Maria A. QuigleyReported by Author; Author; Author [Extracted from the article]

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This paper presents TimelinePTC, a web-based tool developed to improve the collection and analysis of Pathways to Care (PTC) data in first episode psychosis (FEP) research. Accurately measuring the duration of untreated psychosis (DUP) is essential for effective FEP treatment, requiring detailed understanding of the patient's journey to care. However, traditional PTC data collection methods, mainly manual and paper-based, are time-consuming and often fail to capture the full complexity of care pathways. TimelinePTC addresses these limitations by providing a digital platform for collaborative, real-time data entry and visualization, thereby enhancing data accuracy and collection efficiency. Initially created for the Specialized Treatment Early in Psychosis (STEP) program in New Haven, Connecticut, its design allows for straightforward adaptation to other healthcare contexts, facilitated by its open-source codebase. The tool significantly simplifies the data collection process, making it more efficient and user-friendly. It automates the conversion of collected data into a format ready for analysis, reducing manual transcription errors and saving time. By enabling more detailed and consistent data collection, TimelinePTC has the potential to improve healthcare access research, supporting the development of targeted interventions to reduce DUP and improve patient outcomes. [ABSTRACT FROM AUTHOR]

Spatial interaction models with spatial origin-destination (OD) filters are powerful tools to characterize trip flows in space, which is a classic and important problem in regional science. To the authors' knowledge, existing studies adopting OD filters mostly specify the spatial dependence as an autoregressive process, which may not be the full picture of spatial effects. To examine the problem, this paper proposes the hypotheses that 1) spatial OD dependences can take place in both the spatial autoregressive term and the spatial error term in a spatial interaction model. 2) Estimating a spatial autoregressive model with spatial autoregressive disturbances (SARAR) model with OD filters would disentangle where the spatial dependence exists and by how much. 3) The marginal effects obtained from SARAR models would be preferred to analysts when SARAR models outperform spatial autoregressive (SAR) models and spatial error models (SEM) from the statistical point of view. To assess these hypotheses, this paper specifies, estimates, and applies SARAR models with OD filters to investigate trip distributions. By comparing against alternative models, this paper investigates the estimation results in SAR, SEM and SARAR models using an empirical data collected from Hangzhou, China. The contribution of this paper is to be the first in developing an SARAR model with OD filters for trip distribution analyses and examining its performance. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to disclose ontology of DSI as a novel concept in servitization community, explore the research context and themes (i.e. technological and industrial sectors) where DSI emerges, unveil methodological complexities of the research on digital servitization and DSI and provide guidelines for future research avenues regarding DSI. Design/methodology/approach: Bearing in mind the relative novelty of DSI as a concept in servitization literature, the authors adopted a systematic literature review approach to identify 111 peer-reviewed articles published in English language and available in business and management disciplines via scholar databases (Scopus). The analysis of literature discloses descriptive and thematic insights regarding digital servitization and DSI. Findings: The study provides valuable insights from the descriptive and thematic analyses where classification of articles per publication year, citations, methodology/type of the paper, geographical location of data collection, as well as industrial sector and technological contexts are discussed. Moreover, the unique value of this study is observed through its specific focus on the characteristics of DSI-related literature. Originality/value: The study is among the first of its kind to provide extensive descriptive and thematic insights on the available literature dealing with digital servitization and DSI, mapping out prior research across a wide spectrum of publication outlets and illustrating the chronological evolution of research on digital servitization and DSI. [ABSTRACT FROM AUTHOR]

This paper unpacks our efforts as external evaluators to work toward decolonizing our evaluation practice. Undertaking this writing exercise as a form of reflective practice demonstrated that decolonization is much more complex than simply translating materials, organizing locals to collect data, and building participants' capacity around Western modalities. While this complexity is clear in the decolonization literature, practice-based examples that depict barriers and thought processes are rarely presented. Through this paper, we deconstruct our deeply held beliefs around what constitutes good evaluation to assess the effectiveness of our decolonizing approach. Through sharing our critical consciousness-raising dialoguing, this paper reports our progress thus far and provides information and provocations to support others attempting to decolonize their practice. [ABSTRACT FROM AUTHOR]

Aiming at the received signal strength index (RSSI) in wireless positioning system, an improved weighted KNN fingerprint positioning algorithm is proposed in this paper. The algorithm pre-processes fingerprint data in offline stage that including eliminating outliers and Kalman filtering first, in order to improve the accuracy of data acquisition. Secondly, the fingerprint data is partitioned by using RSSI to attenuate obstacles such as walls. Then, points with significant RSSI differences in each region are selected as regional feature points, and the distance between RSSI of test points and feature points in each region is calculated respectively to determine the region in which the test points are located. Geometric method is used to analyse and define the correlation degree, and KNN is re-weighted to achieve accurate positioning in the region. Finally, experiments were carried out in the indoor environment to complete the establishment of the fingerprint database. Compared with the existing NN, KNN and WKNN, the experimental analysis results show that the accumulated error and average error are better than the traditional algorithm with the increase of measurement points, which has reference value for the complex environment positioning technology. [ABSTRACT FROM AUTHOR]

Recently, deep learning (DL) based dynamic security assessment (DSA) methods have been very successful. However, although a DSA model can be trained well for a specific topology, it often does not perform well for other topologies. Since the topology in real‐world power systems is frequently changing, the performance reduction of DL‐based DSA methods is very serious, which is a challenging and urgent problem. This paper proposes a novel DSA method based on a convolutional neural network (CNN) to solve this problem. In the proposed method, a strong yet simple domain adaptation approach named adaptive batch normalization (AdaBN) is used, which significantly enhances the extensibility and generalizability of the DSA model when the topology changes and eliminates the need to train a large number of models. This approach achieves a deep adaptation effect by modulating the statistics from the source domain to the target domain in all batch normalization layers across the model. Unlike other domain adaptation methods, this method is parameter‐free, requires no additional components, and has advanced performance despite its simplicity. In addition, this paper introduces TGAN‐based data augmentation to deal with the difficulty of costly data collection and labelling. This data augmentation makes the proposed model applicable to small databases. The test results of the proposed method on IEEE 39‐bus and IEEE 118‐bus systems show that this method can evaluate system dynamic security during topology changes and in the face of data noise with high accuracy. [ABSTRACT FROM AUTHOR]

This article introduces the concept of load aggregation, which involves a comprehensive analysis of loads to acquire their external characteristics for the purpose of modeling and analyzing power systems. The online identification method is a computer-involved approach for data collection, processing, and system identification, commonly used for adaptive control and prediction. This paper proposes a method for dynamically aggregating large-scale adjustable loads to support high proportions of new energy integration, aiming to study the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction methods. The experiment selected 300 central air conditioners as the research subject and analyzed their regulation characteristics, economic efficiency, and comfort. The experimental results show that as the adjustment time of the air conditioner increases from 5 minutes to 35 minutes, the stable adjustment quantity during the adjustment period decreases from 28.46 to 3.57, indicating that air conditioning loads can be controlled over a long period and have better adjustment effects in the short term. Overall, the experimental results of this paper demonstrate that analyzing the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction algorithms is effective. [ABSTRACT FROM AUTHOR]

Background: Liver disease is an increasing cause of morbidity and mortality in the United Kingdom and can be challenging to live with in the advanced stages. There has been little research exploring the healthcare experiences of UK individuals with decompensated disease when the liver cannot carry out its functions properly. A PhD research project was developed with people who have liver disease to explore care experiences in decompensated advanced liver disease. Public involvement (PI) is an essential aspect of meaningful health research, and this paper reports on the progression of our PI approach in this ongoing study. Objective: To embed PI throughout the research project to ensure that the study is meaningful to individuals with liver disease and the people who support them. Methods: The research adopts a Constructivist Grounded Theory methodology to develop a theory of care experience. Various PI approaches were considered in developing the PI strategy for this qualitative study. Initially, Embedded consultation was the preferred model, which has evolved to include aspects of collaboration and coproduction. A PI group was set up to oversee the project through the national public engagement website VOICE, and reflections on PI from three members of the group are included in this paper to illuminate the PI process. Results: Six individuals with liver disease and three carers from across the United Kingdom are part of an ongoing PI group. Their role includes commenting on the findings of the systematic literature review for this project and contributing to decisions about recruitment, data collection and data analysis. Additionally, they had a direct impact on changing the focus of the research. The PI group will continue involvement until the completion of the project. Conclusion: Successfully embedding PI into doctoral research, as demonstrated in this project, requires commitment, planning and dedication to reciprocal working for the benefit of PI contributors as well as the research. This approach could be adopted by other postgraduate researchers. Patient or Public Contribution: This project is overseen by the PI group, whose contribution is described throughout, including reflections from three PI group members. [ABSTRACT FROM AUTHOR]

Crashes involving large trucks have a significant association with increasing fatalities or serious injuries. Identifying the factors affecting large trucks crashes can be helpful in reducing the number of crashes and corresponded consequences. The purpose of this review was to appraise the published papers on factors affecting large truckinvolved crashes. Data were compiled through searching Google Scholar, Scopus, Science Direct, and Web of Science using keywords included "large truck and accident severity", "large truck and accident", "large truck and crash severity", "large truck and crash", "large truck and fatal accident", "large truck and fatal crash", "large truck and injury", and "large truck and collide". The accomplishment process had two steps: excluding unrelated studies and reviewing related ones to select papers meeting the inclusion criteria. According to data collected, 31 papers achieved the inclusion criteria. The results indicated that speed, driver age, location type, collision type, seat belt wearing, light condition, vehicle technical condition, time, road surface condition, and accident type were common factors in the included papers. From the perspective of our study, speed, location type, and light condition seem to be the most frequent factors in crashes involving large trucks. The present study helps to access the studies on factors affecting the large truck-involved crashes. Thereby, the experts can perform measures to decrease the probability and severity of traffic accidents. [ABSTRACT FROM AUTHOR]

To overcome the issues of the existing properties and the non-configurable supervisory control and data acquisition (SCADA) architecture, this paper proposes an IoT-centered open-source SCADA system for monitoring photovoltaic (PV) systems. The system consists of three voltage sensors and three current sensors for data accumulation from the PV panel, the battery, and the load. As a part of the system design, a relay is used that controls the load remotely. An ESP32-E microcontroller transmits the collected data to a Banana Pi M4 Berry (BPI-M4 Berry) through the Message Queuing Telemetry Transport (MQTT) protocol over a privately established communication channel using Wi-Fi. The ESP32-E is configured as the MQTT publisher and the BPI-M4 Berry serves as the MQTT broker. Locally installed on the BPI-M4 Berry, the Node-RED platform creates highly customizable dashboards as human–machine interfaces (HMIs) to achieve real-time monitoring of the PV system. The proposed system was successfully tested to collect the PV system voltage/current/power data and to control the load in a supervisory way under a laboratory setup. The complete SCADA architecture details and test results for the PV system data during the total eclipse on 8 April 2024 and another day are presented in this paper. [ABSTRACT FROM AUTHOR]

Objectives: Unwarranted clinical variations in radical prostatectomy (RP) procedures are frequently reported, yet less attention is given to the variations in associated costs. This issue can further widen disparities in access to care and provoke questions about the overall value of the procedure. The present paper aimed to delve into the disparities in hospital, medical provider and out-of-pocket costs for RP procedures in Australia, discussing plausible causes and potential policy opportunities. Methods: A retrospective cohort study using Medibank Private claims data for RP procedures conducted in Australian hospitals between 1 January 2015 and 31 December 2020 was undertaken. Results: Considerable variations in both medical provider and out-of-pocket costs were observed across the country, with variations evident between different states or territories. Particularly striking were the discrepancies in the costs charged by medical providers, with a notable contrast between the 10th and 90th percentiles revealing a substantial difference of A$9925. Hospitals in Australia exhibited relatively comparable charges for RP procedures. Conclusions: Initiatives such as enhancing transparency regarding individual medical provider costs and implementing fee regulations with healthcare providers may be useful in curbing the variations in RP procedure costs. What is known about the topic? Unwarranted clinical variations in radical prostatectomy procedures are well documented in the literature; however, variations in cost are less widely reported. What does this paper add? This paper aims to highlight the cost variations in radical prostatectomy procedures in Australia, discussing their plausible causes, implications and proposing potential policy opportunities. What are the implications for practitioners? Excessive fees imposed by medical providers may contribute to inequalities in healthcare access. Enhancing transparency of individual medical provider costs and implementing fee regulations may be useful in controlling unwarranted variations in procedure costs. This article belongs to the Special Issue: Value-based Healthcare. [ABSTRACT FROM AUTHOR]

In order to understand the application of iot Big data information acquisition for heating control systems, a research on iot Big data information acquisition for thermal storage heating control systems is proposed. This paper first analyzes the shortcomings of the traditional heating system, the heating data is scattered and difficult to collect. The IoT technology is applied to the heating platform through data acquisition, data visualization, data mining, data management and other aspects. Secondly, the application of the IoT in heating system data acquisition is studied, including the types of heating data collected, data acquisition process, data acquisition standards, etc. Finally, this paper takes the energy-saving transformation of 26 boilers in a heating enterprise as an example. The research results show that the boiler efficiency obtained in real time by using the online monitoring system of this project is 95.36%, and the reverse balance boiler efficiency in the paper report of the special inspection office is 94.88%, with a deviation of 1.48%. The application of the IoT technology can obtain the boiler indicators in real time and effectively, and can realize the comprehensive analysis of the monitoring data, and realize the evaluation of the energy efficiency operation state of the gas boiler and the fault diagnosis and early warning. The IoT technology is an effective means of fine energy-saving management in heating enterprises. [ABSTRACT FROM AUTHOR]

Purpose--Remittances to North Korea have been examined as an intrinsic part of the North Korean refugee experience. The purpose of this paper is to assess how remittances, social and financial, have impacted the North Korean borderland's marketization and mobility practices, including border-crossing, expectations of life outside of North Korea, and family strategies. Design, Methodology, Approach-A mixed-method approach. Data collection has included reviewing published materials, a survey about remittances with North Korean refugees, and in-depth semi-structured interviews. Findings--Data shows how financial remittances and items sent to the North Korean borderland have piggybacked on the well-established informal trading and smuggling networks, contributing to market supply and demand and the cash in circulation. Social remittances and economic benefits of remittances have supported the emergence of mobility as a family strategy in the northern provinces. Practical Implications--This paper provides evidence about how remittance flows into North Korea impact the receiving household's economy and marketization. It provides insight into how mobility is used as a strategy for the family's benefit. Originality/Value--This study provides evidence that remittances in North Korea extend beyond household support, fueling marketization through informal smuggling, entrepreneurship, and supply-demand dynamics. [ABSTRACT FROM AUTHOR]

Combining online and offline data collection during six months of ethnographic fieldwork in Southern Mozambique in early 2021, this paper explores how media and its everyday use in the Global South are impacting on, and are in turn being transformed by China. It specifically looks into the creative and personalised ways in which Chinese-made garments are sold and promoted in Mozambique via the messenger service WhatsApp. Examining how Mozambican and West African traders use WhatsApp groups and status updates to mediate the fashionability of these Chinese goods, this paper shows that the consequences of Chinese interactions with the Global South on the global media landscape transcend the mere spread of Chinese hardware and software. Going beyond dominant, state-centred narratives of Chinese influence abroad, this paper demonstrates the key role of individuals and their agency in shaping the digital impact of Global China. By doing so, it also highlights the importance of analysing media practices in their specific local contexts. [ABSTRACT FROM AUTHOR]

Purpose: This short paper builds on and critiques work presenting potential non-disasters: disasters that did not seem to happen despite a major hazard. Previous work does not differentiate among different types of potential non-disasters. This short paper uses local information to propose three categories according to reasons for vulnerability being low or absent. These proposed categories are used to critique the construct of "potential non-disasters". Design/methodology/approach: This short paper uses a subjective approach to examples of potential non-disasters in 2022, focusing on local information that describes what happened. This information is applied and analysed for the three proposed categories using examples from Japan, Nepal, the Philippines and Vietnam. Such comparisons are useful for critiquing "potential non-disasters", by understanding better local approaches and information available for reporting on situations that could be disasters. Findings: Potential non-disasters remain relevant for exploring mechanisms, tools and actions for educating about vulnerability causes and vulnerability reduction to avert disasters. Limitations are evident by relying on media reports, even local ones with local authors. A suggestion is to implement a grant programme for collecting data immediately after a major hazard without an evident, major disaster. Additionally, an annual report and critique of each year's potential non-disasters, categorised and analysed, would help to evidence the presence and limits of the "potential non-disaster" construct. Originality/value: This short paper contributes a much deeper theoretical dive into understanding potential non-disasters, both describing them and the drawbacks of the construct. To practitioners, the construct now offers more avenues for actions while illustrating their effectiveness in reducing vulnerabilities. Thus, this paper supports multiple, linked pathways towards more non-disasters. [ABSTRACT FROM AUTHOR]

Background: Hip fractures are a common and debilitating condition posing not only a huge health care but also socioeconomic burden. Surgical management for a neck of femur fracture is typically with arthroplasty in the form of total hip arthroplasty or hip hemiarthroplasty. Serial radiographs are typically performed routinely as part of follow-up to look for complications, although their clinical utility in asymptomatic patients is yet to be validated. Our paper therefore aims to review the utility and necessity of radiographic follow-up following arthroplasty for NOF fractures. Materials and Methods: Patients who underwent operative management for acute fragility neck of femur fractures in the year from 1st January 2018 to 31st December 2018 at the author's institution were identified. All patients who underwent surgery, and had at least one pre and one post-operative plain film radiograph of the affected hip were included in this study. Exclusion criteria included patients who had undergone surgery for chronic fractures, avascular necrosis of the femoral head, mortality within 1 year, peri-prosthetic fractures, pathological fractures from metastases, had concomitant injuries, or had inaccessible or incomplete records. Clinical records were assessed for the number of visits, an abnormal presenting history or clinical examination, as well as changes in management of the patient. The number and type of radiographs were also assessed, and each radiograph analyzed for abnormal findings. Results: A total of 157 patients were included in our study with a mean age of 79.5 at the time of surgery, and a mean follow up of 17.3 months. Data was collected from 626 clinical visits and a total of 973 radiographs. The 3 abnormal radiographic series identified with a corresponding normal consult did not result in a change of management for the patient. A negative change in management was only observed in 1 patient with an abnormal consult and a corresponding normal radiograph. Conclusion: Post-operative complications following arthroplasty for NOF fractures are likely to result in a symptomatic presentation of the patient. Routine radiographic follow-up provides limited utility in asymptomatic patients and should only be performed if clinically indicated. [ABSTRACT FROM AUTHOR]

Background: Collection of detailed dietary data is labor intensive and expensive, harmonization of existing data sets has been proposed as an effective tool for research questions in which individual studies are underpowered. Methods: In this paper, we describe the methodology used to retrospectively harmonize nutritional data from multiple sources, based on the individual participant data of all available studies, which collected nutritional data in Israel between 1963 and 2014. This collaboration was established in order to study the association of red and processed meat with colorectal cancer. Two types of nutritional questionnaires, the Food Frequency Questionnaires (FFQ) and the 24-h dietary recall (24HR recall), and different food composition tables, were used by the participating studies. The main exposure of interest included type of meat (total meat, red meat, and poultry) and level of processing. Results: A total of 29,560 Israeli men and women were enrolled. In studies using FFQ,the weighted mean intakes of total, red, processed meat, and poultry were 95, 27, 37 and 58 gr/day and 92, 25, 10, and 66 gr/day in studies using 24HR recall, respectively.. Despite several methodological challenges, we successfully harmonized nutritional data from the different studies. Conclusions: This paper emphasizes the significance and feasibility of harmonization of previously collected nutritional data, offering an opportunity to examine associations between a range of dietary exposures and the outcome of interest, while minimizing costs and time in epidemiological studies. [ABSTRACT FROM AUTHOR]

Data acquisition systems that receive analog signals, convert them to digital, and perform signal processing are used in a variety of systems that use acoustics, radar, sonar, indoor localization, and navigation. The previous systems, such as NI USRP-RIO, are expensive to build, and the number of signals a single device can receive is limited to between two and four. In order to receive more channels of signals, multi-channel data acquisition systems using ADCs operating at tens of MSPS have been proposed. However, these systems require additional processing time because data acquisition and signal processing are performed on different devices. In this paper, we propose a multi-channel data acquisition system using a 16-channel ADC that can support up to 100 MSPS. In particular, to reduce unnecessary signal transmission time, we propose a one-chip structure where all processes are performed on a single chip. Also, we propose a data acquisition system that applies pipelining techniques to enable real-time processing. To verify the proposed system, we used TI ADS52J90 and a Kintex UltraScale KCU105 evaluation board, and confirmed that it is possible to receive and process all channels simultaneously. Furthermore, it is possible to configure a real-time system by adjusting the speed of the signal-processing operation and the speed of the communication interface. Therefore, the proposed system is expected to reduce the cost of system construction by performing signal reception and processing with a single chip, and to reduce the time required for overall signal processing. [ABSTRACT FROM AUTHOR]

Anomaly detection systems based on artificial intelligence (AI) have demonstrated high performance and efficiency in a wide range of applications such as power plants and smart factories. However, due to the inherent reliance of AI systems on the quality of training data, they still demonstrate poor performance in certain environments. Especially in hazardous facilities with constrained data collection, deploying these systems remains a challenge. In this paper, we propose Generative Anomaly Detection using Prototypical Networks (GAD-PN) designed to detect anomalies using only a limited number of normal samples. GAD-PN is a structure that integrates CycleGAN with Prototypical Networks (PNs), learning from metadata similar to the target environment. This approach enables the collection of data that are difficult to gather in real-world environments by using simulation or demonstration models, thus providing opportunities to learn a variety of environmental parameters under ideal and normal conditions. During the inference phase, PNs can classify normal and leak samples using only a small number of normal data from the target environment by prototypes that represent normal and abnormal features. We also complement the challenge of collecting anomaly data by generating anomaly data from normal data using CycleGAN trained on anomaly features. It can also be adapted to various environments that have similar anomalous scenarios, regardless of differences in environmental parameters. To validate the proposed structure, data were collected specifically targeting pipe leakage scenarios, which are significant problems in environments such as power plants. In addition, acoustic ultrasound signals were collected from the pipe nozzles in three different environments. As a result, the proposed model achieved a leak detection accuracy of over 90% in all environments, even with only a small number of normal data. This performance shows an average improvement of approximately 30% compared with traditional unsupervised learning models trained with a limited dataset. [ABSTRACT FROM AUTHOR]

Objective: To scope how the Australian Bureau of Statistics Socio-Economic Indexes for Areas (SEIFA) has been applied to measure socio-economic status (SES) in peer-reviewed cardiovascular disease (CVD) research. Methods: The Joanna Briggs Institute's scoping review methodology was used. Results: The search retrieved 2788 unique citations, and 49 studies were included. Studies were heterogeneous in their approach to analysis using SEIFA. Not all studies provided information as to what version was used and how SEIFA was applied in analysis. Spatial unit of analysis varied between studies, with participant postcode most frequently applied. Study quality varied. Conclusions: The use of SEIFA in Australian CVD peer-reviewed research is widespread, with variations in the application of SEIFA to measure SES as an exposure. There is a need to improve the reporting of how SEIFA is applied in the methods sections of research papers for greater transparency and to ensure accurate interpretation of CVD research. What is known about the topic? A socio-economic status (SES) gradient is well established for cardiovascular disease (CVD). Research has generally applied two approaches to classifying SES: at an individual level using income, education or occupation data, and at an area level using a range of existing socio-economic information, including the Australian Bureau of Statistics (ABS) Socio-Economic Indexes for Areas (SEIFA). What does this paper add? This review examined how SEIFA has been applied to measure SES in Australian peer-reviewed CVD research and to identify any variations in research practice. What are the implications for practitioners? It is recommended that researchers provide a clear explanation in the methods section of research papers as to which SEIFA version and index was applied, how it was applied, at what spatial unit, and whether the spatial unit was an ABS or non-ABS unit. [ABSTRACT FROM AUTHOR]

Online crowdsourcing platforms have rapidly become a popular source of data collection. Despite the various advantages these platforms offer, there are substantial concerns regarding not only data validity issues, but also the ethical, societal, and global ramifications arising from the prevalent use of online crowdsourcing platforms. This paper seeks to expand the dialogue by examining both the "internal" aspects of crowdsourcing research practices, such as data quality issues, reporting transparency, and fair compensation, and the "external" aspects, in terms of how the widespread use of crowdsourcing data collection shapes the nature of scientific communities and our society in general. Online participants in research studies are informal workers who provide labor in exchange for remuneration. The paper thus highlights the need for researchers to consider the markedly different political, economic, and socio-cultural characteristics of the Global North and the Global South when undertaking crowdsourcing research involving an international sample; such consideration is crucial for both increasing research validity and mitigating societal inequities. We encourage researchers to scrutinize the value systems underlying this popular data collection research method and its associated ethical, societal, and global ramifications, as well as provide a set of recommendations regarding the use of crowdsourcing platforms. [ABSTRACT FROM AUTHOR]

Objective: In this paper we report how the United Kingdom's National Institute for Health and Care Excellence (NICE) search filters for treating and managing COVID-19 were validated for use in MEDLINE (Ovid) and Embase (Ovid). The objective was to achieve at least 98.9% for recall and 64% for precision. Methods: We did two tests of recall to finalize the draft search filters. We updated the data from an earlier peer-reviewed publication for the first recall test. For the second test, we collated a set of systematic reviews from Epistemonikos COVID-19 L.OVE and extracted their primary studies. We calculated precision by screening all the results retrieved by the draft search filters from a targeted sample covering 2020-23. We developed a gold-standard set to validate the search filter by using all articles available from the "Treatment and Management" subject filter in the Cochrane COVID-19 Study Register. Results: In the first recall test, both filters had 99.5% recall. In the second test, recall was 99.7% and 99.8% in MEDLINE and Embase respectively. Precision was 91.1% in a deduplicated sample of records. In validation, we found the MEDLINE filter had recall of 99.86% of the 14,625 records in the gold-standard set. The Embase filter had 99.88% recall of 19,371 records. Conclusion: We have validated search filters to identify records on treating and managing COVID-19. The filters may require subsequent updates, if new SARS-CoV-2 variants of concern or interest are discussed in future literature. [ABSTRACT FROM AUTHOR]

What are the waste management methods' historical places? In order to provide answers from earlier study, the current research work aims to investigate these important questions. The paper employed a desktop approach to provide answers to the research objectives. The work used a descriptive methodology to collect data from peer-reviewed sources, including books, journal articles and reports from environmental organizations. It was found that, waste is to a large extent subjective in meaning as a substance can only be regarded as a waste when the owner labels it as such. This is particularly relevant as different people may view substances differently as a waste, while another may view the same substance as a resource. Nevertheless, it was argued that there is a need to clearly define what constitute wastes as this form the basis for regulation. [ABSTRACT FROM AUTHOR]

This paper revolves around the concept of start-ups in IT Cities of India. Start-ups are mostly created based on creative and innovative ideas and grow to achieve success. Start-up companies are newly established companies which generally strive for existence due to some challenges. The basic purpose of this paper is to put some light on the factors influencing the success of startups in IT Cities of India. factors include Government support, Incubation support and financial support which is again sub divided into various sub factors having an influence on the success of startups in IT Cities of India. An attempt is made to review the literature and based on which primary data were collected from various Start-up Unit, start- up owner, CEO through questionnaire and the total of 309 respondents have been analyzed. Based on data collected all the three factors have been analyzed and proposed some suggestions and strategies. [ABSTRACT FROM AUTHOR]

Harmony of being, a concept that recognized philosophy, values, social science as a unit whole in understanding humanity holistically. This research paper aimed to discuss the relevance of this approach to NU MOA students and faculty members. The essence of studying how it enhanced personal growth and development was therefore explored through this paper. The research methodology used an exploratory and documentary analysis in which primary and secondary sources were used as data collection tools. In conclusion, the results from this study could be used by NU MOA to come up with programs that enhanced harmony among its students and staff. [ABSTRACT FROM AUTHOR]

The Expanded National Nutrition Survey (ENNS), formerly the National Nutrition Survey, is a regularly conducted survey that records the Philippines' overall nutritional status. This is especially important not only for government intervention and policy-making but also for private sector entities that plan for their nutrition and development programs. First deployed during the conduct of the 2013 ENNS, the electronic data collection system (EDCS) is a tool that implemented computer-assisted personal interviewing (CAPI) functionalities. This paper records the improvements made to this system and its division into separate subsystems, various CAPI subsystems with specialized functionalities, and how they interact with each other. Descriptive analysis was used for the users' feedback and recommendations -- specifically, for usability and navigation, system performance and portability, technicality and security, and visual design. The system is able to support interviews during the ENNS and receive positive feedback -- garnering visual design the highest, whereas technicality and security the lowest acceptability rating -- thereby proving this division useful. Overall, the system is capable of supporting the ENNS and will continue its improvement through the continual user feedback received. [ABSTRACT FROM AUTHOR]

Aim: Studies of the effects of COVID‐19, especially post‐acute COVID‐19 syndrome, on psychological health in non‐severe cases are limited. We aimed to evaluate the prevalence and associated risk factors of psychological symptoms, and quality‐of‐life in three groups of outpatients, hospitalized and intensive care patients. Methods: A total 276 patients, previously confirmed with SARS‐CoV‐2 infection, attending the COVID‐19 follow‐up outpatient clinic from December 2020 to July 2021 were interviewed face‐to‐face. In this cross‐sectional, retrospective study, all participants were asked our self‐designed demographic and screening questions to assess their psychological symptoms and administered the WHQOOL‐BREF survey to evaluate quality of life. Results: In screening questions, major depressive disorder symptoms were detected at a rate of 20.3%, generalized anxiety disorder symptoms at a rate of 16.7%, panic attack symptoms at a rate of 10.9%, post‐traumatic stress disorder symptoms at a rate of 28.6% and obsessive‐compulsive disorder symptoms at a rate of 18.1%. The outpatient group with COVID‐19 infection had a higher risk of developing psychological symptoms and decreased quality of life. Conclusion: COVID‐19 infection was found to have a considerable psychological impact on those treated as outpatients despite the less severe course of their illness. Summary statement: What is already known about this topic? Post‐intensive care syndrome affects physical, cognitive and psychological health.It is associated with symptoms such as generalized weakness, memory disturbances, cognitive function impairment, depression, anxiety and post‐traumatic stress disorder.Some physical and psychological symptoms persist for over 12 weeks in some patients and have been classified as 'Post‐acute COVID‐19 Condition or Syndrome' (PCS). What this paper adds? At the post‐acute‐COVID‐19 period, a considerable number of outpatients with COVID‐19 infection were at higher risk for psychological distress symptoms than those who had been treated in the hospital or intensive care unit.Depression, anxiety, panic disorder and PTSD symptoms were found to be higher in outpatients and those with these symptoms were also shown to have a lower quality of life.Our findings highlight the significant psychological impact of COVID‐19 on patients, even after their reported recovery from the acute manifestations of this disease. The implications of this paper: Ongoing psychological symptoms in the post‐COVID period are not associated with the severity of the disease in the acute phase.It is important that healthcare professionals are equally concerned not only with physical condition of post‐COVID‐19 patients but also with their psychological state and the patient's psychology‐related quality of life. [ABSTRACT FROM AUTHOR]

Aims: We aim to analyse the effect of menthol on thirst intensity and thirst comfort in surgical patients. Background: Menthol has achieved good results in quenching thirst in patients in intensive care units, but its safety and reliability in perioperative fasting patients are unknown. Design: A systematic review with meta‐analysis of intervention studies was performed. Data Sources: We used Chinese and English databases from their dates of inception to May 2022. Literature was retrieved from PubMed, Web of Science, Cochrane Library, Embase, CINHAL, SinoMed, CNKI, Wanfang and VIP database. Review Methods: Two reviewers independently examined the records according to the eligibility criteria and extracted the data of each included study. Results: A total of seven studies were identified in this review, which included 537 surgical patients. Overall, menthol reduced thirst intensity in surgical patients and decreased thirst discomfort. Further subgroup analysis revealed that the menthol intervention significantly improved thirst intensity in surgical patients during preoperative and postoperative fasting periods. The Egger's tests showed no significant bias (p = 0.113 and 0.553, thirst intensity and thirst discomfort, respectively). Conclusion: Menthol intervention effectively improved thirst intensity and thirst discomfort during fasting in surgical patients, but more large‐scale, multicentre randomized controlled trials are required to confirm these findings further. Summary statement: What is already known about this topic? Thirst is a common symptom of discomfort during fasting in surgical patients.Thirst in surgical patients is an underappreciated, unmeasured and undertreated symptom. What this paper adds? It is safe and feasible to administer menthol immediately after surgery to patients undergoing surgery.Menthol intervention during fasting in surgical patients can significantly reduce thirst intensity and improve thirst discomfort.More high‐quality trials are essential to explore optimal menthol interventions during fasting in surgical patients. The implications of this paper Menthol provides a safe and effective thirst‐quenching method for perioperative fasting in surgical patients.Menthol reduces thirst intensity and thirst discomfort in surgical patients postoperative fasting periods. [ABSTRACT FROM AUTHOR]

Real-time traffic signal acquisition and network transmission are essential components of intelligent transportation systems, facilitating real-time traffic monitoring, management, and analysis in urban environments. In this paper, we introduce a comprehensive system that incorporates live traffic signal acquisition, real-time data processing, and secure network transmission through a combination of hardware and software modules, called LIDATS. LIDATS stands for Live Intersection Data Acquisition for Traffic Simulators. The design and implementation of our system are detailed, encompassing signal acquisition hardware as well as a software platform that is used specifically for real-time data processing. The performance evaluation of our system was conducted by simulation in the lab, demonstrating its capability to reliably capture and transmit data in real time, and to effectively extract the relevant information from noisy and complex traffic data. Supporting a variety of intelligent transportation applications, such as real-time traffic flow management, intelligent traffic signal control, and predictive traffic analysis, our system enables remote data analysis and decisionmaking, providing valuable insights and enhancing the traffic efficiency while reducing the congestion in urban environments. [ABSTRACT FROM AUTHOR]

With the increasing number of households owning pets, the importance of sensor data for recognizing pet behavior has grown significantly. However, challenges arise due to the costs and reliability issues associated with data collection. This paper proposes a method for classifying pet behavior using cleaned meta pseudo labels to overcome these issues. The data for this study were collected using wearable devices equipped with accelerometers, gyroscopes, and magnetometers, and pet behaviors were classified into five categories. Utilizing this data, we analyzed the impact of the quantity of labeled data on accuracy and further enhanced the learning process by integrating an additional Distance Loss. This method effectively improves the learning process by removing noise from unlabeled data. Experimental results demonstrated that while the conventional supervised learning method achieved an accuracy of 82.9%, the existing meta pseudo labels method showed an accuracy of 86.2%, and the cleaned meta pseudo labels method proposed in this study surpassed these with an accuracy of 88.3%. These results hold significant implications for the development of pet monitoring systems, and the approach of this paper provides an effective solution for recognizing and classifying pet behavior in environments with insufficient labels. [ABSTRACT FROM AUTHOR]

The revolution of the Internet of Things (IoT) and the Web of Things (WoT) has brought new opportunities and challenges for the information retrieval (IR) field. The exponential number of interconnected physical objects and real-time data acquisition requires new approaches and architectures for IR systems. Research and prototypes can be crucial in designing and developing new systems and refining architectures for IR in the WoT. This paper proposes a unified and holistic approach for IR in the WoT, called IR.WoT. The proposed system contemplates the critical indexing, scoring, and presentation stages applied to some smart cities' use cases and scenarios. Overall, this paper describes the research, architecture, and vision for advancing the field of IR in the WoT and addresses some of the remaining challenges and opportunities in this exciting area. The article also describes the design considerations, cloud implementation, and experimentation based on a simulated collection of synthetic XML documents with technical efficiency measures. The experimentation results show promising outcomes, whereas further studies are required to improve IR.WoT effectiveness, considering the WoT dynamic characteristics and, more importantly, the heterogeneity and divergence of WoT modeling proposals in the IR domain. [ABSTRACT FROM AUTHOR]

Charging methods significantly affect the performance and lifespan of lithium-ion batteries. Investigating charging techniques is crucial for optimizing the charging time, charging efficiency, and cycle life of the battery cells. This study introduces a real-time charging monitoring platform based on LabVIEW, enabling observation of battery parameters such as voltage, current, and temperature. The proposed system allows the precise control of charging parameters via a user-friendly interface. Utilizing a programmable DC power supply, it delivers specific charging waveforms, while data acquisition instruments record temperature changes. Key performance metrics, including charging time, efficiency, and temperature rise, are analyzed. Moreover, this paper conducts in-depth research on the constant temperature–constant voltage (CT-CV) charging technique and applies the Taguchi method to identify key parameter configurations that achieve the objectives of the shortest charging time, highest charging efficiency, and lowest average temperature rise. A comprehensive evaluation compares the optimized CT-CV method with conventional constant current–constant voltage (CC-CV) charging. The results demonstrate a 10.7% reduction in charging time compared to the 1C CC-CV method, indicating the efficacy of CT-CV in shortening charging duration while managing temperature rise. [ABSTRACT FROM AUTHOR]

Purpose: Activity sampling is a technique to monitor onsite labourers' time utilisation, which can provide helpful information for the management level to implement suitable labour productivity improvement strategies continuously. However, there needs to be a review paper that compiles research on activity sampling studies to give readers a thorough grasp of the research trend. Hence, this paper aims to investigate the activity sampling techniques applied in earlier research from the angles of activity categories formation, data collection methods and data analysis. Design/methodology/approach: The method used in this paper is a systematic review guided by the PRISMA framework. The search was conducted in Scopus and Web of Science. The inclusion and exclusion criteria were applied, selecting 70 articles published between 2011 and 2022 for data extraction and analysis. The analysis method involved a qualitative synthesis of the findings from the selected articles. Findings: Activity sampling is broadly divided into four stages: targeting trade, determining activity categories, data collection and data analysis. This paper divides the activity categories into three levels and classifies the data collection methods into manual observation, sensor-based activity sampling and computer vision-based activity sampling. The previous studies applied activity sampling for two construction management purposes: labour productivity monitoring and ergonomic safety monitoring. This paper also further discusses the scientific research gaps and future research directions. Originality/value: This review paper contributes to the body of knowledge in construction management by thoroughly understanding current state-of-the-art activity sampling techniques and research gaps. [ABSTRACT FROM AUTHOR]

Background: As a result of the ten years (2012-2022) work under the critical revision of the genera of Reticulariaceae, a set of papers was published. Collection data of hundreds of specimens, used as a material for these studies, were provided as supplements of corresponding papers, but remained unpublished in biodiversity databases. New information: Here, we represent an occurrence dataset "Barcoded Reticulariaceae of the World", published in GBIF. It includes data on 523 myxomycete collections (including 36 types) gathered from five continents and spanning 24 countries. The dataset encompasses 43 distinct species and one subspecies of myxomycetes, including rare, endemic, and recently-described taxa. Species included to the database mainly belong to the genera Alwisia, Lycogala, Reticularia, Siphoptychium, Thecotubifera and Tubifera (Reticulariaceae), but as well Lindbladia and Licaethalium (Cribrariaceae). Nearly all of the research material, with the exception of several old collections, underwent molecular barcoding, primarily involving the 18S rDNA gene, but also the elongation factor 1α gene and mitochondrial cytochrome oxidase subunit I gene. For those sequences that are stored in the NCBI GenBank, accession numbers are provided in the dataset. Newly-described species make up a significant part of the studied herbarium collections; many of them can be characterised as common for their region. A particularly high level of taxonomic novelty is observed in Australia, which may be explained by the endemism of the local myxomycete biota. [ABSTRACT FROM AUTHOR]

With the development of the Internet of Things (IoT), the use of UAV-based data collection systems has become a very popular research topic. This paper focuses on the energy consumption problem of this system. Genetic algorithms and swarm algorithms are effective approaches for solving this problem. However, optimizing UAV energy consumption remains a challenging task due to the inherent characteristics of these algorithms, which make it difficult to achieve the optimum solution. In this paper, a novel particle swarm optimization (PSO) algorithm called Double Self-Limiting PSO (DSLPSO) is proposed to minimize the energy consumption of the unmanned aerial vehicle (UAV). DSLPSO refers to the operational principle of PSO and incorporates two new mechanisms. The first mechanism is to restrict the particle movement, improving the local search capability of the algorithm. The second mechanism dynamically adjusts the search range, which improves the algorithm's global search capability. DSLPSO employs a variable population strategy that treats the entire population as a single mission plan for the UAV and dynamically adjusts the number of stopping points. In addition, the proposed algorithm was also simulated using public and random datasets. The effectiveness of the proposed DSLPSO and the two new mechanisms has been verified through experiments. The DSLPSO algorithm can effectively improve the lifetime of the UAV, and the two newly proposed mechanisms have potential for optimization work. [ABSTRACT FROM AUTHOR]

This paper aims to analyze the regulations related to protecting the architecture of the traditional house in Indonesia and the challenges in related regulations. To achieve these goals, the research uses a normative legal writing method with descriptive-analytical specifications. Firstly, the findings reveal that traditional houses are part of traditional cultural expressions (TCE). Indonesia protects architectural works and TCE in the same intellectual property regime, namely copyright. Therefore, this paper examines the protection of traditional house architecture from the perspective of Copyright law, the Law on the Advancement of Culture, and the TCE Bill. The abovementioned regulations state that the architecture is a protected object unless the TCE Bill is. Second, there are some challenges, such as 1) the priority of the TCE Bill after the change of president; 2) song and music get more benefit from copyright protection rather than the other objects in the copyright regime and no implementing regulation on architecture; and 3) the TCE data collection/inventory is still not optimal yet. Therefore, Indonesia needs to think more seriously about adequate and applicable legal protection for traditional house architecture and other TCEs. The central government should encourage regional governments and related parties to continue data collection and registration of various TCEs in each region to increase the number of registered TCEs. The central government should provide a target number of registered TCEs for the local government. If the target is met, the central government will give a reward so that the local government and related parties will be more enthusiastic about collecting data and registering the TCE with DJKI. [ABSTRACT FROM AUTHOR]

Research on handheld LiDAR data has recently been proliferated due to the emergence of digital twins and indoor mapping. However, most of the existing studies cannot be reproduced in another computational environment. Computational reproducibility requires data, code/software, and computational environment (e.g. versions, settings, etc.) to be openly available. Although there are an increasing number of researches that contribute towards open data, there are still few studies investigating the remaining two aspects. One of the common tasks in digital twin research is the estimation of indoor space areas. This paper contributes to the computational reproducibility of estimating the area of indoor spaces on a handheld LiDAR dataset using the DBSCAN algorithm. The collected dataset -representing the Geomatics Engineering Department of Hacettepe University, code, and the computational environment was made openly available to satisfy the requirements of computational reproducibility. Three different experiments have been carried out: i) identification of the optimal DBSCAN parameter values for a single indoor space, ii) evaluating to what extent these values are applicable to other rooms, and iii) investigating the effect of room enter/exit times on the estimated room sizes. The main finding of this paper is that the simple consideration of an open-door, which reduces data collection time, the uncertainty of a wall's coordinates, and imperfect choice of DBSCAN parameters, may substantially increase the estimated indoor space size ranging between approximately 40% to 300%. Consequently, relying solely on the DBSCAN algorithm for indoor space area estimation should not be considered as a valid approach. [ABSTRACT FROM AUTHOR]

This paper examined good governance as a panacea for the citizens’ well-being. The well-being of the citizens is the essence of government. In other words, government exists to ensure the well-being of the citizens. The well-being of the citizens can only be assured and guaranteed when there is good governance and reverse would be case in the midst of bad governance. Of all the forms of government, democracy has the greatest potential to offer good governance because it is people’s government and as such people have greater opportunity to participate one way or the other in the governance process making it possible for them to influence decisions that would be to their favor. It therefore means that for good governance to be enthroned in a polity; the people have great responsibility to bring it about by not being docile but to be seriously interested in participating in the governance process and system. Secondary method of data collection was adopted in this paper and analysis of data collected was done through the descriptive method. The paper found out that bad governance is responsible for the lack of the citizen’s well-being. The theoretical framework adopted in this paper is structural functionalism. The paper recommended among other things that for the well-being of the citizens to be guaranteed there should be the encouragement of good governance by all and sundry. [ABSTRACT FROM AUTHOR]