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Real‐time and accurate short‐term traffic flow prediction can provide a scientific basis for decision making by travellers and traffic management, and alleviate traffic congestion to a certain extent. The existing traffic flow prediction methods often encounter limitations in real‐time performance and accuracy due to the post‐processing required to rectify anomaly detection results during data pre‐processing. This paper presents a novel traffic flow prediction model, termed the With‐Anomaly Detection Probability (ADP) Attention‐Bidirectional Long‐Short Term Memory (BiLSTM) model. This model takes the probability of anomaly detection into consideration, integrating the anomaly detection outcomes as an inherent parameter into the traffic flow prediction framework. Additionally, the model incorporates an attention mechanism within the long‐short term memory network. Through a comprehensive simulation study utilizing actual measured traffic flow data from the Shanghai‐Chongqing Expressway, the effectiveness of the proposed model is rigorously evaluated. The prediction results show that the model proposed in this paper is a real‐time and accurate short‐time traffic flow prediction model compared with the basic models. [ABSTRACT FROM AUTHOR]

This study determined the validity, reproducibility and usability of a smartphone app – APPetite – for the measure of free-living, subjective appetite. Validity was assessed compared with the criterion tool of pen-and-paper visual analogue scale (VAS) (n 22). Appetite was recorded using APPetite and VAS, one immediately after the other, upon waking and every hour thereafter for 12 h. This was repeated the next day with the order of tool reversed. Agreement between tools was assessed using Bland–Altman analysis. Reproducibility and usability were assessed in a separate experiment (n 22) of two trials (APPetite v. VAS), separated by 7 d. Appetite was recorded in duplicate upon waking and every hour for 12 h using APPetite or VAS. Agreement between duplicate measures was assessed using Bland–Altman analysis and CV was compared between tools. Usability was assessed by comparing compliance and by qualitative evaluation. APPetite demonstrated good criterion validity with trivial bias of 1·65 units/mm·h–1 between APPetite- and VAS-derived AUC appetite scores. Limits of agreement were within a maximum allowed difference of 10 %. However, proportional bias was observed. APPetite demonstrated high reproducibility, with minimal bias (–0·578 units·h–1) and no difference in CV between APPetite and VAS (1·29 ± 1·42 % v. 1·54 ± 2·36 %, P = 0·64). Compliance was high with APPetite (92·7 ± 8·0 %) and VAS (91·6 ± 20·4 %, P = 0·81). Ninety percent of participants preferred APPetite, citing greater accessibility, simplified process and easier/quicker use. While proportional bias precludes using APPetite and VAS interchangeably, APPetite appears a valid, reproducible and highly usable tool for measuring free-living appetite in young-to-middle-aged adults. [ABSTRACT FROM AUTHOR]

Currently, 2D anomaly detection has demonstrated outstanding performance. However, 2D images limit the improvement of anomaly detection accuracy without utilizing depth information. Therefore, this paper proposes a Dual Reconstruction viAInpainting Network for 3D industrial anomaly detection (DRAIN). Firstly, we design a 3D reconstruction network using an encoder-decoder-based U-shaped network for processing RGB images and depth images. Subsequently, accurate anomaly segmentation is implemented through a 3D segmentation network. We introduce a lightweight MLP module to enhance segmentation performance to capture long-range dependencies in the reconstructed images. Furthermore, we propose a dual attention-based information entropy fusion module to expedite feature fusion in the inference process, aiming for enhanced deployment in the industry. Extensive experiments demonstrate that DRAIN achieves a 94.3% AUROC on the 3D anomaly detection dataset MVTec 3D-AD, surpassing other research methods. Overall architecture for 3D industrial anomaly detection via dual reconstruction network [ABSTRACT FROM AUTHOR]

Space non-cooperative target recognition is crucial for on-orbit servicing. Multi-satellite cooperation has great potential for broadening the observation scope and enhancing identification efficiency. However, there is currently a lack of research on recognition methods tailored for multi-satellite cooperative observation. In this paper, we propose a novel space non-cooperative target recognition method to identify satellites and debris in images from multi-satellite observations. Firstly, we design an image-stitching algorithm to generate space-wide-area images. Secondly, we propose a two-stage multi-target detection model, a lighter CNN model with distance merge threshold (LCNN-DMT). Specifically, in the first stage, we propose a novel foreground extraction model based on a minimum bounding rectangle with the threshold for distance merging (MBRT-D) to address redundant detection box extraction for satellite components. Then, in the second stage, we propose an improved SqueezeNet model by introducing separable convolution and attention mechanisms for target classification. Moreover, due to the absence of a public multi-target detection dataset containing satellites and debris, we construct two space datasets by introducing a randomized data augmentation strategy. Further experiments demonstrate that our method can achieve high-precision image stitching and superior recognition performance. Our LCNN-DMT model outperforms mainstream algorithms in target localization accuracy with only 0.928 M parameters and 0.464 GFLOPs, making it ideal for on-orbit deployment. [ABSTRACT FROM AUTHOR]

Background: Festivals play an important role in improving death and grief literacy, enabling members of the public to engage with these often-sensitive topics. Good Grief Weston festival was co-designed and delivered with the community in Weston-super-Mare, a coastal town in South-West England with high levels of socioeconomic disadvantage but rich community assets. It was held in person over 8 days in May 2023. Objectives: To evaluate the reach and impact of Good Grief Weston festival and gather data to inform future festivals. Design: Mixed methods evaluation (survey and focus groups). Methods: Online and paper surveys assessing participants' characteristics and experiences were administrated during and after the festival. Survey participants who indicated their willingness to participate were invited to attend a focus group. Focus groups were recorded, transcribed and analysed using thematic analysis. Data were collected by trained community co-researchers. Results: Approximately 3000 people attended the festival. Of 204 completed surveys, 64.5% were from women, age range ⩽15 to ⩾75 years; 88.2% identified as White; 14.9% deaf, disabled/with a chronic condition; 18.9% neurodivergent; 9.0% gay, bisexual or queer. Festival participants were entertained (70.9%), inspired (68.5%), felt part of a like-minded community (54.3%), talked to someone new (49.2%), learnt about grief/bereavement (34.3%), shared or expressed experiences (30.3%) and found out about local support (19.7%). 71.3% reported that they felt more confident talking about grief after attending. Median experience rating was 5 (IQR 0; possible range 1 = poor to 5 = excellent). In free-text comments, participants expressed appreciation for the festival and described benefits in attending. Two focus groups were conducted (n = 8 participants, all women), lasting c.1.5 h. Focus groups added rich descriptions of the festival's value, and data to inform the next festival. Conclusion: Findings suggest festivals of this nature can play a central role in a public health approach. Plain language summary: What was the impact of Good Grief Weston festival? Why was the study done? Previous studies have shown that many people feel unsupported by their community after the death of a loved one. We designed a festival to improve knowledge and support for bereaved people. We did this study to assess how the festival affected the people who attended. What did the researchers do? The team included researchers and people and organisations from the local community. Together, we designed and ran a festival on the topic of death, grief and bereavement in Weston-super-Mare, a coastal town with areas of high deprivation. The festival took place over an eight-day period in May 2023 and included creative, interactive and educational events. The team collected feedback on attendees' experiences of the festival. We did this using online and paper feedback forms, postcards, and focus groups to collect as many opinions as possible. What did the researchers find? We found that a wide range of people attended the festival. Most people who took part in the research rated the festival as 'excellent'. They told us they learnt about grief and bereavement and found out about local support services. Attendees met new people, shared their experiences, and felt that the festival built community spirit. They also made suggestions to improve any future festivals. What do the findings mean? The findings show that in-person festivals can effectively engage the public on the topic of death, grief and bereavement. They can also help develop connections between people and organisations in communities. These connections and learning opportunities may help communities to support their members through bereavement. [ABSTRACT FROM AUTHOR]

This paper intends to provide the reader with an overview of the main processes that are introducing artificial intelligence (AI) into healthcare services. The first part is organized according to an evolutionary perspective. We first describe the role that digital technologies have had in shaping the current healthcare methodologies and the relevant foundations for new evolutionary scenarios. Subsequently, the various evolutionary paths are illustrated with reference to AI techniques and their research activities, specifying their degree of readiness for actual clinical use. The organization of this paper is based on the interplay three pillars, namely, algorithms, enabling technologies and regulations, and healthcare methodologies. Through this organization we introduce the reader to the main evolutionary aspects of the healthcare ecosystem, to associate clinical needs with appropriate methodologies. We also explore the different aspects related to the Internet of the future that are not typically presented in papers that focus on AI, but that are equally crucial to determine the success of current research and development activities in healthcare. [ABSTRACT FROM AUTHOR]

Aims: To describe a reflexive account of a mental health nurse as researcher undertaking a mixed methods study as part of a doctoral degree, with women in a secure forensic hospital. Design: A discursive paper that draws upon the primary author's experience of dual roles as a mental health nurse and a novice researcher, and relevant literature pertaining to positionality and reflexivity in the context of conducting mixed methods research. Methods: A mixed methods study was conducted within a secure forensic hospital in Australia, to identify factors associated with the frequency and duration of seclusion for women and, to explore their experiences of seclusion. Notes and a reflective diary were used to demonstrate the reflexive approach and strategies used throughout the study design and data collection stages of the research. Results: Women in the secure forensic hospital setting often have complex histories and experiences and are considered a vulnerable group, which can add additional challenges when undertaking research with this population. As a doctoral student with clinical experience in mental health undertaking research in the forensic hospital setting with women, positionality and the connection with reflexivity requires exploration to understand self and the influence on research. This understanding along with identified strategies to enhance reflexivity, supports the management of the dual nurse as researcher roles to enhance all stages of the research process. Conclusion: Doctoral nursing candidates undertaking clinical research in their area of clinical practice and at the location of previous employment, may experience challenges in relation to identity and the dichotomy of roles. Further challenges can be posed when research involves complex populations and/or controversial practices. Support to balance role conflict and maintain reflexivity is critical to understanding the role of self in research and to enhance credibility. Implications for the Profession and/or Clinical Practice: Women are a complex, yet minority population in forensic mental health settings, however the numbers of women being admitted to services is increasing. Future research may consider the use of the strategies explored here to enhance the reflexive process, and support future researchers in this field to conduct research that aims to support an often‐misheard population to better support health outcomes. Patient or Public Involvement: There was no patient or public contribution to this paper, however the study in which this paper is based on, is grounded in the experience of patients (women). [ABSTRACT FROM AUTHOR]

In their process of information seeking, human users tend to selectively ignore information that contradicts their pre-existing beliefs or opinions. These so-called "self-imposed filter bubbles" (SFBs) pose a significant challenge for argumentative conversational agents aiming to facilitate critical, unbiased opinion formation on controversial topics. With the ultimate goal of developing a system that helps users break their self-imposed filter bubbles (SFBs), this paper aims to investigate the role of co-speech gestures, specifically examining how these gestures significantly contribute to achieving this objective. This paper extends current research by examining methods to engage users in cooperative discussions with a virtual human-like agent, encouraging a deep reflection on arguments to disrupt SFBs. Specifically, we investigate the agent's non-verbal behavior in the form of co-speech gestures. We analyze whether co-speech gestures, depending on the conveyed information, enhance motivation, and thus conversational user engagement, thereby encouraging users to consider information that could potentially disrupt their SFBs. The findings of a laboratory study with 56 participants highlight the importance of non-verbal agent behaviors, such as co-speech gestures, in improving users' perceptions of the interaction and the conveyed content. This effect is particularly notable when the content aims to challenge the user's SFB. Therefore, this research offers valuable insights into enhancing user engagement in the design of multimodal interactions with future cooperative argumentative virtual agents. [ABSTRACT FROM AUTHOR]

The fundamentals of the design and operation of self-priming pumps, as indispensable equipment in industry, have been the focus of research in the field of fluid mechanics. This paper begins with a comprehensive background on self-priming pumps and gas-liquid two-phase flow, and it outlines recent advances in the field. Self-priming pumps within the gas-liquid two-phase flow state and the spatial and temporal evolution of the transient characteristics of self-priming pumps determine the self-priming pump self-absorption performance. Through mastery of the self-absorption mechanism, high-performance self-absorption pump products can be formed to provide theoretical support for the development of products. In current research, numerical simulation has become an important tool for analyzing and predicting the behavior of gas-liquid two-phase flow in self-priming pumps. This paper reviews existing numerical models of gas-liquid two-phase flow and categorizes them. Reviewing these models not only provides us with a comprehensive understanding of the existing research but also offers possible directions for future research. The complexity of gas–liquid interactions and their impact on pump performance is analyzed. Through these detailed discussions, we are able to identify the challenges in the simulation process and summarize what has been achieved. In order to further improve the accuracy and reliability of simulations, this paper introduces the latest simulation techniques and research methodologies, which provide new perspectives for a deeper understanding of gas-liquid two-phase flow. In addition, this paper investigates a variety of factors which affect the operating efficiency of self-priming pumps, including the design parameters, fluid properties, and operating conditions. Comprehensive consideration of these factors is crucial for optimizing pump performance. Finally, this paper summarizes the current research results and identifies the main findings and deficiencies. Based on this, the need to improve the accuracy of numerical simulations and to study the design parameters in depth to improve pump performance is emphasized. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to provide a description and evaluation of a graduate-level Health Services Research Methods course offered at the University of Arizona R. Ken Coit College of Pharmacy. This three-credit, round-table discussion-style course introduces students to fundamental concepts in healthcare study design and teaches them how to design and critique example studies for a variety of commonly encountered study designs. The course is assessed through essay-style examinations, development of a research proposal, and low-stakes weekly assignments. Twenty-seven students have completed the course in the past five years. Feedback from student course surveys was almost unanimously positive, with few meaningful suggestions for improvement. The description and evaluation of a graduate-level Health Services Research Methods course at one institution indicates that students had a largely favorable experience with the course. Considerations for future revisions to the course are discussed alongside other lessons learned. [ABSTRACT FROM AUTHOR]

This article is a systematic investigation into the symbolic and sensory metaphors in architectural buildings. It presents definition and differentiation of symbolic (stereotype images) and sensory (architectural experience) metaphors. According to the semiotics model of architecture, they are tested empirically and the results are presented in order to understand their influence in architecture. In this regard, this paper designed a research method and adapted a novel semiotic model to investigate the relationship between sensory metaphors (architectural experience) and symbolic metaphors. The cases included six distinctive buildings and 30 subjects. Results demystified that buildings high in connotative qualities do not always connote positive architectural experience. A building with a high number of symbolic metaphors could create a high number of sensory metaphors but these sensory metaphors may not be necessarily positive feelings and experiences. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to verify the equivalence and effectiveness of the tablet-administered Korean Repeatable Battery for the Assessment of Neuropsychological Status (K-RBANS) for the prevention and early detection of dementia. Methods: Data from 88 psychiatry and neurology patient samples were examined to evaluate the equivalence between tablet and paper administrations of the K-RBANS using a non-randomly equivalent group design. We calculated the prediction scores of the tablet-administered K-RBANS based on demographics and covariate-test scores for focal tests using norm samples and tested format effects. In addition, we compared the receiver operating characteristic curves to confirm the effectiveness of the K-RBANS for preventing and detecting dementia. Results: In the analysis of raw scores, line orientation showed a significant difference (t=-2.94, p<0.001), and subtests showed small to large effect sizes (0.04-0.86) between paper- and tablet-administered K-RBANS. To investigate the format effect, we compared the predicted scaled scores of the tablet sample to the scaled scores of the norm sample. Consequently, a small effect size (d≤0.20) was observed in most of the subtests, except word list and story recall, which showed a medium effect size (d=0.21), while picture naming and subtests of delayed memory showed significant differences in the one-sample t-test. In addition, the area under the curve of the total scale index (TSI) (0.827; 95% confidence interval, 0.738-0.916) was higher than that of the five indices, ranging from 0.688 to 0.820. The sensitivity and specificity of TSI were 80% and 76%, respectively. Conclusion: The overall results of this study suggest that the tablet-administered K-RBANS showed significant equivalence to the norm sample, although some subtests showed format effects, and it may be used as a valid tool for the brief screening of patients with neuropsychological disorders in Korea. [ABSTRACT FROM AUTHOR]

The article presents the discussion on health and social care professionals being critically appraising quantitative research. Topics include considering the main elements of critiquing quantitative methodology focussing on elements of randomised controlled trials (RCTs); and comparing things like the gender, age, and ethnicity splitting between the test and the control group.

Fruit leaf diseases have a significant impact on the later development and maturity of fruits, so rapid and accurate identification of fruit leaf diseases plays an important role in the development of fruit production. In this paper, the leaf disease data set of 6 kinds of fruits is divided into 25 categories according to the species—the type of the disease—the severity, and we propose an improved model based on ResNet101 to identify woody fruit plant leaf diseases, in which a global average pooling layer is used to reduce model training parameters, layer normalization, dropout and L2 regularization are used to prevent model overfitting, SENet attention mechanism is used to improve the model's ability to extract features. At the same time, transfer learning is used to reduce training time and training parameters. Experimental results show that the overall accuracy of woody fruit plant leaf recognition based on this model can reach 85.90%. Compared with the classic ResNet network, the accuracy is increased by 1.20%, and the model parameters are reduced by 98.14%. Therefore, the model proposed in this paper provides a better solution for the identification of leaf diseases of woody fruit plants and has a higher accuracy rate. [ABSTRACT FROM AUTHOR]

Interpretative Phenomenological Analysis (IPA) is an established qualitative methodology widely adopted within health-based research. However, one gap in the literature is that little has been written about IPA's employability within educationally situated research. Our paper aims to demonstrate that IPA is a suitable methodology for education research. This paper has two parts. In the first part, the authors utilise the method of exegesis and theoretical analysis to explicate and provide clarity concerning the often-misunderstood philosophical and theoretical background of IPA. In the second part, we advocate for IPA as a suitable option for qualitative research in educational contexts. To execute this advocacy, the authors present a specific example of qualitative research that successfully employed IPA as its methodological approach and system for analysis. We present the details of a research project that utilised IPA to explore spirituality in early childhood education contexts, and in doing so the authors illustrate how the theories and methods of IPA can be actualised, thus introducing IPA into education contexts in a coherent fashion. The overall aim of the paper is to affirm IPA as a viable qualitative approach for education researchers. [ABSTRACT FROM AUTHOR]

This paper investigates the potential of the Gamified Metaverse as a platform for promoting library services. The study compares the effectiveness of a traditional library program with a Metaverse- based library program in terms of knowledge acquisition and library anxiety. The research also examines students' perceptions of implementing gamification within the context of the Gamified Metaverse platform. A mixed-methods approach was adopted, including pre- and post-test analysis, statistical analysis, and qualitative data collection. The results indicate that both the traditional and Metaverse-based library programs effectively increased the participants' knowledge, with no significant difference between the two approaches. However, the Metaverse-based program was found to be less effective in facilitating interaction with librarians and reducing library anxiety. Additionally, students expressed positive perceptions of implementing gamification in the Gamified Metaverse platform, finding it engaging and motivating. These findings contribute to the understanding of the effect of the Metaverse as a tool for promoting library services and enhancing knowledge acquisition. However, it is not as effective in reducing library anxiety, particularly in terms of interaction with librarians and staff. It should be noted that the platform may have limitations such as high costs and potential side effects of virtual reality, making it more suitable as an additional tool for promoting library services, taking into account its feasibility and potential benefits for specific student populations and larger libraries. [ABSTRACT FROM AUTHOR]

Introduction: The ageing society requires physicians who can deliver integrated care, but it is unclear how they should be prepared for doing so. This scoping review aims to create an overview of educational programmes that prepare (future) physicians to deliver integrated care while addressing components and outcomes of the interventions. Method: We included papers from five databases that contained: (1) integrated care (2) education programme (3) medical students (4) elderly, or synonyms. We divided the WHO definition of integrated care into ten components for the concept of ‘integrated care’. Data were collected with a charting template, and template analysis was used to formulate themes. Results: We found 17 educational programmes in different learning settings. All programmes addressed several components of the WHO definition. The programmes primarily focused on care for individual patients (micro-level), and the outcomes suggested that experiencing the complexity of care is key. Conclusion: This review revealed the limited evidence on educational programmes about integrated care for the elderly. Our findings suggest that educational programmes on integrated care should not be limited to the micro-level, and that students should obtain adaptive expertise by experiencing complexity. Future research should contain an explicit description and definition of integrated care. [ABSTRACT FROM AUTHOR]

A significant paradigm shift is underway in communication research as open science practices (e.g. preregistration, open materials) are becoming more prevalent. The current work identified how much the field has embraced such practices and evaluated their impact on authors (e.g. citation rates). We collected 10,517 papers across 26 journals from 2010 to 2020, observing that 5.1% of papers used or mentioned open science practices. Communication research has seen the rate of nonsignificant p-values (p >.055) increasing with the adoption of open science over time, but p-values just below p <.05 have not reduced with open science adoption. Open science adoption was unrelated to citation rate at the article level; however, it was inversely related to the journals' h-index. Our results suggest communication organizations and scholars have important work ahead to make open science more mainstream. We close with suggestions to increase open science adoption for the field at large. [ABSTRACT FROM AUTHOR]

This article describes the history of the journal published by the UK Market research Society (MRS). The reasons for introducing a journal are discussed, and the competitive context, at that time and onwards. Changes in the format, title and content of the journal over time are described, and its evolution from an in-house production to its current status within the journal portfolio of a leading international academic publishing house. The changing nature of the two main communities with the most interest in the journal, academics and practitioners, are described and the impact on the journal are discussed. Finally, the article summarises some of the many key contributions that the journal has made to the body of knowledge and evidence in the fields of market and social research. [ABSTRACT FROM AUTHOR]

SUMMARY: Interview-based research is growing in prominence in auditing, yet many researchers are self-trained in this method, leading the novice interview researcher to encounter a number of roadblocks along the way. The overarching goal of our study is to add to the methodological resources available on the interview method by providing a compilation of challenges that novice interview researchers have experienced, along with suggested methods to cope with these challenges (i.e., how to overcome these challenges, what to do differently, and advice on navigating the interview method). With this new perspective, our paper serves as a resource to prospective interview-based researchers so they can enter the field better informed about possible roadblocks they might encounter along the way and methods to cope with these challenges. In turn, we hope to contribute to the production of more insightful and efficient interview-based research. [ABSTRACT FROM AUTHOR]

The accuracy of main cable construction in suspension bridges is directly influenced by the sag of the strands during the erection process. Thus, effective methods for controlling strand sag are crucial. However, the current control standards and methods are primarily based on practical engineering experience, lacking quantitative analysis and a sufficient basis. This paper aims to address this gap by summarizing four commonly used strand sag control methods and proposing a quantitative analysis model that considers the influence of random factors. The model quantifies the impact of these methods on the main cable shape and strand tension after cable tightening. To illustrate the practical application, a suspension bridge is utilized as a case study. The results of the study illustrate a linear relationship between the main cable sag and inter-strand distance, with each control method exhibiting a varying linear change rate. Moreover, the discrepancy in strand distance contributes to uneven strand tension after cable tightening. Random errors contribute to the dispersion of the main cable sag and strand tension, which are further exacerbated by cumulative errors between layers of general strands. Based on the study's results, this paper provides valuable references for the erection and control of the main cable in suspension bridges. [ABSTRACT FROM AUTHOR]

The threshing rate is one of the important indexes to evaluate the effect of corn threshing. The weighing method is often used to calculate the depuration rate of maize at present. This method is time-consuming and laborious and can only calculate the overall threshing rate but does not give the threshing rate of individual corn ears. Different parameters of corn ears have complex effects on the threshing rate. By analyzing the threshing rate of each corn ear, we can choose the appropriate ear treatment method, optimize the processing equipment and process flow, and improve the threshing performance. This paper presents a method based on machine vision to detect the threshing rate of corn ears. In this method, machine vision was used to measure the parameters of the corncob and the area of the top of residual kernels. The area of the top of all kernels was restored based on the parameters of the corncob. The threshing rate of corn ears was calculated by the ratio of the area of the top of the missing kernel to the area of the top of all kernels after threshing. A bivariate linear regression area model was established to restore the area of the top of all corn kernels based on corncob parameters. The R2 was more significant than 0.98, and the goodness of fit was good. The machine vision inspection results showed that the maximum relative error of length and midsection radius was 7.46% and 5.55%, and the mean relative error was 2.58% and 2.23%. The maximum relative error of the corn ear threshing rate was 7.08%, and the mean relative error was 2.04%. When the residual kernels were concentrated in the midsection, the inspection result of the corn ear threshing rate was better. The maximum relative error was 3.98%, and the mean relative error was 1.07%. This paper provides a new idea and reference for measuring the threshing rate of corn ears. [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]

Objectives: The objectives of this paper is to conduct a bibliometric analysis to examine the research status and development trend of anterior cruciate ligament injury and reconstruction in children and adolescents over the past 20 years. Design: Descriptive Research. Methods: This study obtained information regarding studies on Anterior Cruciate Ligament Reconstruction in Children and Adolescents from the Web of Science Core Collection database. Visual and bibliometric analysis were conducted using VOSviewer, Origin 2022, Pajek64 5.18and Excel 2019. These analytic tools facilitated the analysis of various aspects, including countries/regions, institutions, authors, journals and keywords related to the research. Results: From 2003 to 2023, a total of 1328 articles were retrieved in WOS, and 637 articles were selected by two authors. The most productive institutions are Childrens Hosp Philadelphia, Kocher, ms. Their articles have the highest number of publications and citations. The American journal of sports medicine is the most frequently cited journal for articles on anterior cruciate ligament reconstruction in children and adolescents. The most common keywords used in these articles were "anterior cruciate ligament reconstruction", "injury, children, adolescent", and "skeletally immature patients". Conclusions: This study provides valuable insights into the research focus of anterior cruciate ligament reconstruction in children and adolescents. In recent years, there has been significant attention paid to areas of "the return to sport, re-repture rate and functional recovery after anterior cruciate ligament reconstruction" in this specific population. These aspects have emerged as key directions for future research in this field. [ABSTRACT FROM AUTHOR]

The development of artificial intelligence (AI) represents one of the greatest discoveries of the current century, being called the fifth industrial revolution. The use of AI-based tools within public sector entities is still at the beginning, but the experience reported to date has identified both advantages and risks. The article aims to analyze the impact of the use of artificial intelligence in the public sector, as well as its evaluation on the activity in this frame. The research methodology is based on the answer to the question "What is the impact of the use of tools based on artificial intelligence on the activity of entities from public sector?" by which the authors aim to evaluate both the advantages and the risks of using such tools. At the same time, the paper addresses the use of tools based on artificial intelligence from the perspective of the public audit carried out by the supreme audit institutions. The main conclusions of the paper refer to the current state of the use of artificial intelligence in the public sector. The authors' recommendations can be the basis of future research in this regard. [ABSTRACT FROM AUTHOR]

Qualitative research methods have treated Western knowledge systems and Indigenous studies as polar opposites with asymmetrical power relations. Studies have documented the hegemonic dominance of Western science over Indigenous knowledge systems. Despite this tension, there is an opportunity to integrate Western science with Indigenous knowledges to bridge these discordant systems. This paper argues that Constructivist Grounded Theory (CGT), a Western-based version of grounded theory can be weaved with Indigenous research. CGT's emphasis on co-construction, relationality, value-free inquiry, and social justice align with Indigenous research principles. Using examples from both CGT and Indigenous scholarship, the paper argues that CGT with its pragmatist and constructivist orientation can exist alongside an Indigenous research agenda. Furthermore, the flexible, emergent, and relativist nature of CGT aligns with some aspects of Indigenous research. The paper demonstrates that both knowledge systems can be treated on an equal par, engender methodological reciprocity and provide mutual benefits to each other. Weaving CGT and Indigenous research might provide new avenues of thinking about doing research with Indigenous communities and other marginalized communities. [ABSTRACT FROM AUTHOR]

Traditional potato grading in China relies mostly on manual sorting, which is labor-intensive, time-consuming, costly, and inefficient. To enhance the operational performance of potato-grading devices, this paper focuses on optimizing the slide rail structure, which is the key component of a self-developed first-generation potato-grading device. A five-factor, three-level orthogonal experiment was designed, with the experimental factors being the height of the horizontal slide rail, angle of the first-stage inclined slide, angle of the second-stage inclined rail, chain horizontal movement speed, and conveyor belt speed. The indoor experiments were conducted using grading accuracy and grading efficiency as the experimental indicators. On the basis of the analysis of the orthogonal experiment results, two relatively optimal solutions were obtained, and validation experiments were conducted. The validation results show that when the height of the horizontal slide rail was 185 mm, the angle of the first-stage inclined rail was 4°, the angle of the second-stage inclined rail was 2.5°, the horizontal movement speed of the chain was 700 mm/s, and the movement speed of the conveyor belt was 275.60 mm/s, the performance of the movable rotating plate (MRP)-type grading device for potatoes reached its optimum. At this point, the grading accuracy was 94.88%, and the grading efficiency was 13.9477 t/h. Compared with the first-generation grading device, the optimized grading device achieved an improvement of 3.84% in grading accuracy and 12.94% in grading efficiency. The research methodology provided in this paper serves as a reference for the performance optimization of potato-grading devices. [ABSTRACT FROM AUTHOR]

There is a growing population of adults aged 50 years or older living with HIV, facing unique challenges in care due to age, minority status, and stigma. Co-design methodologies, aligning with patient-centered care, have potential for informing interventions addressing the complex needs of older adults with HIV. Despite challenges, co-design has shown promise in empowering older individuals to actively participate in shaping their care experiences. The scoping review outlined here aims to identify gaps in existing co-design work with this population, emphasizing the importance of inclusivity based on PROGRESS-Plus characteristics for future patient-oriented research. This scoping review protocol is informed by the Joanna Briggs Institute Manual to explore co-design methods in geriatric HIV care literature. The methodology encompasses six stages: 1) developing research questions, 2) creating a search strategy, 3) screening and selecting evidence, 4) data extraction, 5) data analysis using content analysis, and 6) consultation with key stakeholders, including community partners and individuals with lived experience. The review will involve a comprehensive literature search, including peer-reviewed databases and gray literature, to identify relevant studies conducted in the past 20 years. The inclusive criteria focus on empirical data related to co-design methods in HIV care for individuals aged 50 or older, aiming to inform future research and co-design studies in geriatric HIV care. The study will be limited by the exclusion of papers not published or translated to English. Additionally, the varied terminology used to describe co-design across different research may result in the exclusion of articles using alternative terms. The consultation with key stakeholders will be crucial for translating insights into meaningful co-design solutions for virtual HIV care, aiming to provide a comprehensive synthesis that informs evidence-based strategies and addresses disparities in geriatric HIV care. [ABSTRACT FROM AUTHOR]

In order to reduce the loss of laser point cloud appearance contours by point cloud lightweighting, this paper takes the laser point cloud data of the segment beam of the expressway viaduct as a sample. After comparing the downsampling algorithm from many aspects and angles, the voxel grid method is selected as the basic theory of the research. By combining the characteristics of the normal vector data of the laser point cloud, the top surface point cloud edge data are extracted and the voxel grid method is fused to establish an optimized point cloud lightweighting algorithm. The research in this paper shows that the voxel grid method performs better than the furthest point sampling method and the curvature downsampling method in retaining the top surface data, reducing the calculation time and optimizing the edge contour. Moreover, the average offset of the geometric contour is reduced from 2.235 mm to 0.664 mm by the edge-optimized voxel grid method, which has a higher retention. In summary, the edge-optimized voxel grid method has a better effect than the existing methods in point cloud lightweighting. [ABSTRACT FROM AUTHOR]

In this paper, we introduce the notion of T-conformal transformations and T-conformal maps between Riemannian manifolds. Here, T stands for a smooth (1,1)-tensor field defined on the domain of these maps. We start by defining what it means for a map to be T-conformal and also dwell on some basic properties of such type maps. We next specialize our discussion to the situation when the map T satisfies the condition △T = 0. Accordingly, we prove Liouville's theorem for T-conformal maps between space forms Rn(c) as an application under the condition △T = 0. The proof relies upon properties of T-conformal maps proved earlier. Broadly, the paper seeks to provide a general understanding of conformal mappings in the presence of a tensor field T and show how classical results such as Liouville's theorem apply. [ABSTRACT FROM AUTHOR]

Topic modeling has emerged as a successful approach to uncovering topics from textual data. Various topic modeling techniques have been introduced, ranging from traditional algorithms to those based on neural networks. In this research, we explore advanced topic modeling techniques, including BERT-based approaches, to enhance the analysis of scientific articles. We first investigate a widely used Latent Dirichlet Allocation (LDA) model and then explore the capabilities of BERT, to automatically uncover latent topics within scientific papers. The goal of this study is to identify the optimal hyperparameter setting for BERT-based topic modeling of scientific articles. We conduct experiments across several scenarios involving combinations of word embedding, dimension reduction, and clustering methods. The results were analyzed based on the coherence values, average execution time, number of topics generated, visualization through the inter-topic distance map, and the top-N-words of each topic. Our findings suggest that combination of RoBERTa for word embedding, PCA for dimension reduction, and K-Means for clustering yields superior results among the tested scenarios. Further evaluation of BERT-based topic modeling is necessary to validate these findings and explore its applications in various academic and industrial contexts. The implications of these advanced techniques could significantly streamline the process of staying updated with scientific literature, potentially revolutionizing research methodologies across disciplines. [ABSTRACT FROM AUTHOR]

Introduction: Social Prescribing has an established recognition regarding the benefits provided to the health-related social needs of adults, but little is known about how the intervention addresses young people's needs. There is optimism regarding the central role of two core mechanisms that allows social prescribing to be effective, such as the empathetic role of Link Workers and the connection with community resources. This paper aims to describe the role played by Link Workers working a Social Prescribing intervention targeting young people. Description: This paper adopts a case study methodology to describe the role of Link Workers addressing young people's needs and implementing Social Prescribing scheme in Sheffield (UK). Data were collected through semi-structured interviews with four of the seven link workers of one organisation based in Sheffield. Data were analysed through an inductive approach for emerging themes. Discussion: We provided a description of the profiles and background of Link Workers and described the three models of referral pathways into the intervention. The paper also shows how Link Workers identify young people's needs and how they connect with the community. Conclusion: Based on the insights and the internationally accepted definition of Social Prescribing, we provide a visual representation of the Social Prescribing model and discuss challenges. The paper highlights lessons learned and future directions regarding the role of Link Workers from the case study. [ABSTRACT FROM AUTHOR]

Research on the Leave No One Behind principle of the Sustainable Development Goals (SDGs) within the context of the Agenda 2030 is currently prevalent; however, research on monitoring child poverty at the sub-national (local) level is still limited. This paper addresses this gap by examining indicators developed for monitoring the phenomenon at different territorial levels (global, European, and national) and assessing their territorial transposition locally, using the city of Cadiz, Spain, as a case study. Interviews with local stakeholders reveal that despite the availability and access to related indicators and data, relevant actors must enhance their efforts to utilize such indicators effectively. Based on desktop research and qualitative analysis, the paper delivers recommendations for improving local monitoring of child poverty in Europe and inducing policy changes. This knowledge can inform targeted interventions, policy formulation, and resource allocation to tackle child poverty and promote equitable and inclusive societies. [ABSTRACT FROM AUTHOR]

Replacing traditional manual sweeping with unmanned sweepers in closed parks can not only greatly reduce labor costs, but also improve sweeping efficiency. Efficient path planning is the key technology for unmanned sweepers to complete the sweeping task. Existing unmanned sweepers are often based on fixed path sweeping or completely traversing the sweeping mode, this mode does not have the environmental adaptability, in the actual sweeping is often high energy cost, and sweeping is not complete. In this paper, an environment-adaptive sweeping path planning method is proposed to improve the sweeping intelligence and environmental adaptability of unmanned sweepers, reduce the energy consumption of sweeping and improve the efficiency of sweeping. Specifically, in this paper, we first use YOLOv5 to complete the accurate identification of individual garbage and obstacles in the road, and then work with LIDAR and Gaussian Mixture Model(GMM) to remove redundant targets. We also propose a Permutation Entropy(PE) value-based discrimination method to complete the target distribution posture analysis of each complex garbage pile. Finally, the traditional path planning problem is transformed into a combinatorial optimization problem of garbage areas, and a sweeping path accurate method based on Simulated Annealing(SA) algorithm is proposed. Through comprehensive theoretical analysis and simulation study, the optimality and effectiveness of the proposed method are proved by comparing A star and Coverage Path Planning(CPP) algorithms in a variety of experimental scenarios. [ABSTRACT FROM AUTHOR]

As a characteristic representative of the new generation of vehicles, autonomous driving is expected to improve people's driving experience. The study on traffic accident of autonomous vehicles (AVs) helps provide suggestions for autonomous driving safety from multiple disciplines and perspectives, and provide support for formulating traffic accident treatment schemes. Knowledge mapping, as a cutting-edge research method in bibliometrics, scientifically and objectively displays the relevant research status using visual means. This paper uses CiteSpace 6.1.r3 to analyze 5068 related literature on the Web of Science database from 1991 to 2022 and finds out major thematic clusters, important documents and representative journals according to citation frequency. The results show that research on traffic accidents involving AVs focuses on accident preventing technologies, including how to avoid collisions, track lane-position, and enhance vehicle-toeverything (V2X) communication. This paper extracts the mean research topics and key points involved in the field and illustrates journals related to AVs and traffic accidents, which provides guidance for subsequent researchers to carry out in-depth research and contribute their papers. Popular journals are in disciplines of mathematics, systems, computer, economics, and social science. This paper also suggests scholars to consider the aspects of scene reconstruction, cause analysis, and injury of vulnerable road users, so as to investigate traffic accidents and put forward effective treatment schemes to reduce AV accidents, and ultimately improve road safety. [ABSTRACT FROM AUTHOR]

At present, there are problems such as low fault data, insufficient labeling information, and poor fault diagnosis in the field of ship engine diagnosis. To address the above problems, this paper proposes a fault diagnosis method based on probabilistic similarity and rank-order similarity of multi-head graph attention neural networks (MPGANN) models. Firstly, the ship engine dataset is used to explore the similarity between the data using the probabilistic similarity of T_SNE and the rank order similarity of Spearman's correlation coefficient to define the neighbor relationship between the samples, and then the appropriate weights are selected for the early fusion of the two graph structures to fuse the feature information of the two scales. Finally, the graph attention neural networks (GANN) incorporating the multi-head attention mechanism are utilized to complete the fault diagnosis. In this paper, comparative experiments such as graph construction and algorithm performance are carried out based on the simulated ship engine dataset, and the experimental results show that the MPGANN outperforms the comparative methods in terms of accuracy, F1 score, and total elapsed time, with an accuracy rate of 97.58%. The experimental results show that the model proposed in this paper can still fulfill the ship engine fault diagnosis task well under unfavorable conditions such as small samples and insufficient label information, which is of practical significance in the field of intelligent ship cabins and fault diagnosis. [ABSTRACT FROM AUTHOR]

The last decades have seen an increase in entrepreneurial development based on innovation. Having access to innovation and setting up a business in a country that can serve as an innovation-enabler can increase the degree of attractiveness of that respective country. Governments around the world have adopted innovation-centered views and implemented relevant policies to serve as a driver for reaching high competitiveness and to ensure a more rapid economic and, implicitly, social progress. The aim of the paper is to present the top ten countries in the world in their evolution specific to the Global Innovation Index (GII) for the 2021-2023 period. The research methodology is based on a qualitative method. The paper shows that the top ten ranked countries in the world using this specific index remained the same for the investigated period, also maintaining a fairly constant relative position for the three years subject to analysis, Switzerland being the acknowledged leader. [ABSTRACT FROM AUTHOR]

In recent decades, the increased use of sensor technologies, as well as the increase in digitalisation of aircraft sustainment and operations, have enabled capabilities to detect, diagnose, and predict the health of aircraft structures, systems, and components. Predictive maintenance and closely related concepts, such as prognostics and health management (PHM) have attracted increasing attention from a research perspective, encompassing a growing range of original research papers as well as review papers. When considering the latter, several limitations remain, including a lack of research methodology definition, and a lack of review papers on predictive maintenance which focus on military applications within a defence context. This review paper aims to address these gaps by providing a systematic two-stage review of predictive maintenance focused on a defence domain context, with particular focus on the operations and sustainment of fixed-wing defence aircraft. While defence aircraft share similarities with civil aviation platforms, defence aircraft exhibit significant variation in operations and environment and have different performance objectives and constraints. The review utilises a systematic methodology incorporating bibliometric analysis of the considered domain, as well as text processing and clustering of a set of aligned review papers to position the core topics for subsequent discussion. This discussion highlights state-of-the-art applications and associated success factors in predictive maintenance and decision support, followed by an identification of practical and research challenges. The scope is primarily confined to fixed-wing defence aircraft, including legacy and emerging aircraft platforms. It highlights that challenges in predictive maintenance and PHM for researchers and practitioners alike do not necessarily revolve solely on what can be monitored, but also covers how robust decisions can be made with the quality of data available. [ABSTRACT FROM AUTHOR]

Purpose. As a scientific field, bioinformatics has drawn remarkable attention from various fields, such as information technology, mathematics, and modern biological sciences, in recent years. The topic models originating from the field of natural language processing have become the focus of attention with the rapid accumulation of biological datasets. Thus, this research is aimed at modeling the topic content of the bioinformatics literature presented by Iranian researchers in the Scopus Citation Database. Methodology. This research was a descriptive-exploratory study, and the studied population included 3899 papers indexed in the Scopus database, which had been indexed in this database until March 9, 2022. The topic modeling was then performed on the abstracts and titles of the papers. A combination of LDA and TF-IDF was utilized for topic modeling. Findings. The data analysis with topic modeling resulted in identifying seven main topics "Molecular Modeling," "Gene Expression," "Biomarker," "Coronavirus," "Immunoinformatics," "Cancer Bioinformatics," and "Systems Biology." Moreover, "Systems Biology" and "Coronavirus" had the largest and smallest clusters, respectively. Conclusion. The present investigation demonstrated an acceptable performance for the LDA algorithm in classifying the topics included in this field. The extracted topic clusters indicated excellent consistency and topic connection with each other. [ABSTRACT FROM AUTHOR]

Following trends are not limited to the fashion and beauty industry. Many researchers in papers, master's degree thesis, and PhD dissertations prefer to solve domain questions or problems with research methodologies previously used by others in the field, mainly, case study research in operations management and technology management studies. This paper is about to stress on adding design research methodology (DRM) as a very useful and practical methodology in management studies that can meet the main aim and concern facing researchers in management studies: produce and develop practical domain knowledge which meets the rigor and relevance functions of the research. This study unlocks all the aspects of DRM and represents a methodological perspective, and sheds light on the reasoning behind why and how DRM should be used more as a methodology in management studies in general, and operations and technology management specifically. [ABSTRACT FROM AUTHOR]

Objective. To perform a bibliometric analysis of scientific production related to gut microbiota and Parkinson's disease between 2011 and 2020. Methods. A descriptive, retrospective, cross-sectional, and bibliometric study was carried out. The Scopus database was used as a source to evaluate the worldwide scientific production on intestinal microbiota and its relationship with Parkinson's disease. Data were extracted from Scopus using a formula developed with thesaurus terms MeSH (Medline) and Emtree (Embase). Results. A total of 591 documents were found. The retrieved manuscripts received an average of 41.9 citations per document. Four of the 10 most productive authors were Italian. The University of Helsinki (Finland) was the institution with the highest scientific production (19 papers) and the highest impact (5921 citations). In terms of productivity and impact, Movement Disorders ranked first with 38 papers and 2782 citations, and those papers published in Q1 quartile journals exceeded the sum of the remaining quartiles. Papers with international collaboration were the most cited. Keyword analysis showed that the terms Parkinson Disease, Disease, and Intestine Flora were the most frequent. Conclusion. The number of papers on Parkinson's disease and gut microbiota has been increasing; however, high-quality journals maintain the same high publication rate. International collaboration from high-income countries played an important role in the impact generated by the publications. [ABSTRACT FROM AUTHOR]

Background: Despite increasing support for stakeholder inclusion in research, there is limited evaluative research to guide safe (i.e., youth‐friendly) and meaningful (i.e., non‐tokenistic) partnerships with young people with lived experience of mental ill‐health in research. This paper describes a pilot evaluation and iterative design of a Youth Lived Experience Working Group (LEWG) protocol that was established by the Youth Mental Health and Technology team at The University of Sydney's Brain and Mind Centre, based on the results of two studies. Methods: Study one consisted of a pilot evaluation of the extent to which youth partners felt empowered to contribute, to qualitatively explore how LEWG processes could be improved. Youth partners completed online surveys, and results were shared over two LEWG meetings in 2021 to empower youth partners to collectively identify actions of positive change regarding LEWG processes. These meetings were audio‐recorded and transcripts were subsequently coded using thematic analysis. Study two assessed whether LEWG processes and proposed improvements were acceptable and feasible from the perspective of academic researchers via an online survey in 2022. Results: Quantitative and qualitative data collected from nine youth partners and 42 academic researchers uncovered initial learnings regarding facilitators, motivators, and barriers to partnering with young people with lived experience in research. Implementing clear processes for youth partners and academic researchers on effective partnership strategies, providing training opportunities for youth partners to develop research skills, and providing regular updates on how youth partner contributions led to research outcomes were identified as key facilitators. Conclusions: This pilot study provides insight into a growing international field on how to optimise participatory processes so that researchers and young people with lived experience can be better supported and engaged to make meaningful contributions to mental health research. We argue that more transparency is needed around participatory research processes so that partnerships with young people with lived experience are not merely tokenistic. Consumer Contributions: Our study has also been approved by and reflects the concepts and priorities of our youth lived experience partners and lived experience researchers, all of whom are authors of this paper. [ABSTRACT FROM AUTHOR]

The code-shift keying (CSK) modulation method can achieve higher information transmission rates without changing the spread spectrum signal bandwidth. In order to optimise the spread spectrum modulation and demodulation of GNSS signals, in addition to the signal structure, binary phase-shift keying (BPSK) and CSK signals using time-division multiplexing are proposed. A tracking method based on the BPSK-CSK signals is also proposed, which generates the P-branch local codes by fast Fourier transform to obtain the code-slice spacings for the E-branch and the L-branch local codes. Then, the tracked BPSK signals and tracked CSK signals are compared and analysed. Finally, the bit error rate (BER) and tracking error of each method are compared and analysed by comparing with the tracking of conventional BPSK signals and tracking of CSK signals, in order to verify the convergence process of the I-branch integral value. The BPSK-CSK signal tracking method proposed in this paper combines the high information transmission rate of CSK-modulated signals and the low BER of BPSK signals, and the results provide a solid foundation for high-precision GNSS services. [ABSTRACT FROM AUTHOR]

The aim of this paper is to provide a review of articles reporting on research related to the linguistic landscape as applied to foreign language education, with a focus on the conceptualisation of the linguistic landscape, main themes, and research methods and distribution across years, languages taught and countries of research. The search for relevant articles published between 2003-2023 was conducted in databases: Web of Science, ERIC, MLA, and Scopus. The search yielded a total sample of 20 articles. The presentation of the main results of the review is followed by suggestions of topics for further research and reviews of a broader scope. [ABSTRACT FROM AUTHOR]

Migration to South Africa is motivated by the pursuit of employment, safety, and improved living conditions. However, immigrants encounter significant challenges, such as restricted access to essential services, which were exacerbated by the COVID-19 pandemic. This paper investigates the impact of the COVID-19 pandemic on Malawian immigrants in South Africa, addressing the lack of attention given to this immigrant population by highlighting their vulnerabilities. Using a qualitative exploratory and descriptive approach, in-depth interviews were conducted with 24 Malawi immigrants who were over 18 years old and had established residency in South Africa before the onset of the COVID-19 pandemic. Five key stakeholders were also interviewed for additional perspectives and to ensure triangulation and improve data reliability. The interviews were transcribed verbatim and analyzed using thematic analysis strategies and coding with Nvivo12 software. The study highlighted the exacerbated struggles of Malawian immigrants in South Africa amid the COVID-19 pandemic, uncovering systemic discrimination in healthcare, marked by longer wait times and reluctance from health workers to treat undocumented immigrants. The study also revealed a dire security situation, with immigrants living in high-crime areas and feeling particularly targeted due to their foreign status, a situation worsened by the pandemic's economic effects. Additionally, the economic downturn induced by COVID-19 significantly impacted employment opportunities, with many immigrants facing prolonged unemployment and job losses, especially in sectors where they traditionally found work. The detailed accounts of participants highlight not only the multifaceted challenges imposed by the pandemic but also the critical need for inclusive policies and support systems that ensure healthcare access, safety, and economic resilience for immigrants, particularly during global health emergencies. Future research should focus on effective interventions for socioeconomic integration and well-being, particularly for immigrants from other African countries. [ABSTRACT FROM AUTHOR]

This paper discusses the secrecies of border spirits within 20th century Finnish belief narratives. The aim is to explore how and in which contexts the imaginary aspects of border spirit narratives link to the idea of the "power of storytelling". The following study touches on areas such as the suspension of the fantasy and sociopolitical aspects within the narratives. The folklore materials focus mainly on the Finnish heartland and partly on the national borders. Especially, narrative research methods were used to analyse what is heard and seen of the border spirits and what contexts these narratives involve. Moreover, the results touch on the dynamics of belief narratives without limiting them to the territorial aspects of borders. Hence, the study also explores interpretative bridges between folklore and border studies. [ABSTRACT FROM AUTHOR]

Choosing an appropriate qualitative methodology in nursing research is a researcher's first step before beginning a study. Such a step is critical as the selected qualitative methodology should be congruent with the research questions, study assumptions, data gathering and analysis to promote the utility of such research in enhancing nursing knowledge. In this paper, we compare focused ethnography by Roper and Shapira and interpretive phenomenology by Benner. Though these methodologies are naturalistic and appear similar, both have different methodological underpinnings. The historical, ontological, epistemological, and axiological philosophy guiding each methodology are described. In addition, the methodological underpinnings of both methodologies and a justification for use in nursing research are provided. This paper will assist future researchers who aim to employ these methodologies in nursing research. [ABSTRACT FROM AUTHOR]

The last three census data highlighted that UK Bangladeshi communities have the worst health outcomes. This includes a higher risk of type two diabetes and heart diseases; both are risk factors for developing vascular dementia. However, little is known about Bangladeshi community members' understandings of dementia, including cultural myths. This paper focuses on the cultural myths, superstitions, and stigma surrounding dementia in an English Bangladeshi community from the direct experiences of people living with dementia, their caregivers, and the views of dementia service providers/stakeholders. This qualitative research was undertaken with three distinct participant groups using semistructured interviews (n = 25), who were recruited from community settings. The first and second participant groups explored the experiences of people with dementia (n = 10) and their family caregivers (n = 10). The third group examined stakeholders'/service providers' views (n = 5). Interviews were recorded digitally and transcribed verbatim. Findings were reached using an interpretive approach, emphasising the sense people make in their own lives and experiences and how they frame and understand dementia. The study revealed that participants with dementia and their caregivers have "alternative" knowledge about dementia and do not necessarily understand dementia in a Westernised scientific/biomedical context. Misconceptions about dementia and belief in various myths and superstitions can lead people to go to spiritual healers or practice traditional remedies rather than to their GPs, delaying their dementia diagnosis. This paper concludes that there is a lack of awareness among the Bangladeshi participants and a need for targeted awareness about dementia to help dispel cultural myths and combat the stigma surrounding dementia within the Bangladeshi community. [ABSTRACT FROM AUTHOR]

Background: This paper discusses the stages of health system resilience (HSR) and the factors underlying differences in HSR during the covid-19 pandemic, especially the vaccination challenge. We studied the relationship between vaccination strategies and macro-context backgrounds in 21 Latin American countries. Our objective was to capture the impact of those aspects in the SR and identify potential improvements for future crises and for vaccination programs in general. Methods: The study uses mixed-methods research to provide insights into how the countries' backgrounds and vaccination strategies impact the HSR. Particularly, we used explanatory sequential mixed methods, which entails a quantitative-qualitative two-phase sequence. The quantitative phase was conducted using cluster and variance analysis, in which the HSR was measured using as a proxy the covid-19 vaccination outcomes in three cut-offs of reaching 25%, 50%, and 75% of population coverage. This approach allows us to discriminate covid-19 vaccination progress by stages and contrast it to the qualitative stage, in which we performed a country-case analysis of the background conditions and the changes in vaccination strategies that occurred during the corresponding dates. Results: The paper provides a rich comparative case analysis of countries, classifying them by early, prompt, and delayed performers. The results show that differences in vaccination performance are due to flexibility in adapting strategies, cooperation, and the ability to design multilevel solutions that consider the needs of various actors in the health ecosystem. These differences vary depending on the vaccination stage, which suggests the importance of acknowledging learning, diffusion, and feedback processes at the regional level. Conclusions: We identified the importance of societal well-being as an ideal country antecedent for high and sustained levels of performance in covid-19 vaccination. Whereas in other countries where the set-up and beginning phases were rough, the value of the operational decisions and the learning on the move regarding their own and their peers' trajectories were crucial and were reflected in performance improvement. A contribution of this study is that the above-mentioned analysis was done using vaccination coverage cut-off points that allow a performance view that takes into consideration the stages of the vaccination progress and the learning process that goes with it. As well as framing this into the HSR shock cycles that allow to differentiate the stages of resilience on which countries must act. [ABSTRACT FROM AUTHOR]