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Objective. The aim of this study was to examine the characteristics of scientific production related to the use of filtered water in the field of dentistry. Material and Methods. A quantitative and descriptive observational study was carried out with a scientometric approach. Data were collected from the Web of Science (WOS) database during the period January 1991 to December 2023. A search strategy incorporating a combination of MeSH terms, including terms and thesauri related to "filtered water" and "dentistry", was used. R Studio version 4.3.2 and CiteSpace 6.2.R7 were used for data analysis. Results. Over the 32-year study period, 227 scholarly papers from 134 different sources were reviewed. The literature in this field has shown an annual growth rate of 10.44%. During the year 2010, a steady movement in the number of publications and authors was observed, with considerable collaborative interaction. In the year 2020, a large interaction between publications and their citations was found. The "Citation Burst" graph identified three references that have experienced the largest "burst" of citations in an evaluated period. Lotka's law described the productivity of authors, finding that most authors have published only one paper, while a smaller number of authors have published two papers. Most authors contributed a small number of articles, while a few authors contributed a large amount of the existing literature. Conclusion. A comprehensive overview of the scientific production related to the use of filtered water in dentistry over a span of 32 years is provided. The results highlight the growing interdisciplinarity and international collaboration in this field. Finally, the importance of filtered water in dentistry and its growing relevance in the scientific literature are emphasized. [ABSTRACT FROM AUTHOR]

Three-dimensional plant model visualization (3D-PMV) is based on plant biology and the plant structure construction model for virtual simulation three-dimensional display, reflecting plant structure characteristics and demonstrating the growth process. In this work, we used the method of systematic mapping study (SMS) to screen the relevant literature in order to explore and analyze the methods and goals of virtual plant visualization research and to provide assistance in future literature reviews. To this end, we conducted extensive searches to identify articles related to plant model visualization technology. We searched for papers from July 2010 to November 2020 from four mainstream databases, namely, ACM, IEEE Xplore, EI, and Web of Science, and found more than 2,900 papers on 3D-PMV. Finally, we selected 60 qualified papers. We mainly followed the SMS method to classify papers by answering seven questions, mainly extracting data for analysis on research types, research goals, model construction methods, visual model categories, number of publications, tools, and methods. The results show that solution proposals account for the largest proportion of research types, accounting for 75% of the total number of papers. This shows that the focus is on the improvement of original methods or the proposal of new methods in this field; research goals of research plant phenotypic characteristics account for the total 35%; 28% of the research objectives focus on showing the reflection of plant growth process, indicating that the research objective trends in this research field regard plant phenotypic characteristics and visualization of the growth process; static type model visualization also accounts for 83% of the total, indicating that the related research on visualization in this field is mostly static typing. Therefore, our work not only analyzes the challenges faced by 3D-PVM and the research directions that need more attention in the future but also provides some suggestions for researchers to find suitable research directions in this field. As the future direction of development, researchers need to pay more attention to the study of dynamic visualization methods of plant growth. We believe that for future research, it is indispensable to provide 3D-PMV with research methods, research goals, visualization model types, development, and other tools. This article analyzes the results of the extracted data based on the SMS method and makes an important contribution to the researcher's extensive understanding of the current status of 3D-PMV and the potential future research opportunities in the field. [ABSTRACT FROM AUTHOR]

The plate-like graphene shells (GS) produced by an original methane pyrolysis method and their derivatives graphene oxide (GO) and graphene oxide paper (GO-P) were evaluated with luminescent Escherichia coli biotests and additional bacterial-based assays which together revealed the graphene-family nanomaterials’ toxicity and bioactivity mechanisms. Bioluminescence inhibition assay, fluorescent two-component staining to evaluate cell membrane permeability, and atomic force microscopy data showed GO expressed bioactivity in aqueous suspension, whereas GS suspensions and the GO-P surface were assessed as nontoxic materials. The mechanism of toxicity of GO was shown not to be associated with oxidative stress in the targeted soxS::lux and katG::lux reporter cells; also, GO did not lead to significant mechanical disruption of treated bacteria with the release of intracellular DNA contents into the environment. The well-coordinated time- and dose-dependent surface charge neutralization and transport and energetic disorders in the Escherichia coli cells suggest direct membrane interaction, internalization, and perturbation (i.e., “membrane stress”) as a clue to graphene oxide’s mechanism of toxicity. [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]

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]

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]

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]

Parenting with a physical disability often brings with it a range of challenges. Occupational therapists are well positioned to support parents to address these challenges, yet occupational therapy research and practice around parenting is relatively scarce. This paper addresses the questions: (1) How should occupational therapists support parenting occupations for people with physical disability? (2) How do parents with physical disability experience occupational therapy? An anonymous survey of 62 parents, primarily mothers, with physical disability about their experiences with parenting challenges and occupational therapy was analysed using both quantitative and qualitative techniques. Parents experienced challenges in engaging in a range of parenting tasks with children over a range of age groups. Parents reported that support was often needed and indicated that occupational therapy could assist them directly with specific parenting goals as well as the more usual biomechanical goals that influence parenting. Yet less than half of participants who received occupational therapy services reported that parenting tasks were addressed, and only one‐fifth reported that their goals had been fully met. The data also indicated that the knowledge, skills, and attitudes of occupational therapists with regard to working with parents with disability can be improved. Findings suggest a need to better incorporate parenting occupations in standard occupational therapy training to increase occupational therapists' comfort and competence in working with clients on parenting issues. [ABSTRACT FROM AUTHOR]

The cruising propulsion process of the bionic robotic fish under the swinging tail motion presents a strong periodic dynamic response, and accurate prediction of its performance is the key to the overall design. Taking the two‐jointed bionic robotic dolphin as the research object, five kinds of movement modes were designed, and the coupled analysis model of the propulsion motion of the bionic robotic dolphin was established based on the hydrodynamic and Lagrangian dynamics methods, and the hydrodynamic performance of different movement modes and its linear propulsion dynamic response process were investigated. The results show that the coupled analysis method proposed in the paper can accurately obtain the motion response parameters of the robotic dolphin as well as the forces and moments of each joint, and the speed error with the hydrodynamic simulation is controlled within 5%. The research method and results have good application value to guide the selection design and performance prediction of bionic robotic fish. [ABSTRACT FROM AUTHOR]

Background. Permanent supportive housing (PSH) is an evidence‐based solution to chronic homelessness. There are two common PSH models: place‐based (PB) programs where clients live in one building with services provided onsite and scattered‐site (SS) programs, which use community apartments coupled with mobile case management and support. Understanding the relative strengths and weaknesses of PB and SS is important for PSH planning and service delivery. This paper explores homeless service provider perspectives on these two models after the onset of the COVID‐19 pandemic. Methods. Service providers (N = 37) from across 5 PSH agencies in Los Angeles that provided either PB or SS services during the pandemic participated in focus groups. Discussions were recorded, transcribed, and analyzed using template analysis, grounded theory, and inductive techniques. Results. Providers identified four major differences between PB and SS services: (1) challenges in finding placements; (2) managing relationships with landlords/property managers; (3) frequency of contact; and (4) community integration. Advantages of PB included ease of finding units, ease of managing relationships with landlords/property managers, greater ability to serve clients efficiently, more frequent client contact, and more community among residents. SS was seen to provide tenants with more opportunities to grow, live in healthier environments, and develop independence. During the pandemic, finding units for SS clients became more difficult, while differences between PB and SS related to frequency of contact and community integration became more attenuated. Conclusions. PB can be advantageous for clients with higher levels of acuity, whereas SS could be more appropriate for clients who are more stable and independent. PB programs are seen to have practical and logistical advantages, but some providers prefer SS services. Clients and providers should be matched to PSH configurations that best match their needs and preferences, and providers should be aware that public health emergencies may impact PB and SS settings differently. [ABSTRACT FROM AUTHOR]

Fuel poverty was a significant problem during the cost‐of‐living crisis that started in 2021 as energy prices increased. Local authorities launched warm bank schemes around the United Kingdom to address this problem by providing warm spaces for residents to visit who could not heat their homes. This paper reports on an evaluation of the warm bank scheme launched by South Tyneside Council in winter 2022, locally known as Welcoming Places. Over 70 locations were opened around the borough. The evaluation consisted of two stages. In stage 1, we conducted semistructured interviews (n = 16) with residents who attended Welcoming Places and two focus groups with people running them (n = 9). In stage 2, we discussed the initial findings from stage 1 in a focus group with residents (n = 8). Three major themes are presented: "help and support with the cost‐of‐living crisis," "it's worth its weight in gold," and "capability and strength of Welcoming Places." This is one of the first evaluations of a warm bank scheme in England. We illustrate how the Welcoming Places in South Tyneside were used and experienced by residents. The scheme was valued by residents, provided significant support during the cost‐of‐living crisis, and had a positive impact on self‐reported mental health among participants. Warm bank schemes offer a practical, rapid public health response to the cost‐of‐living crisis for local authorities as well as improving residents' mental health and well‐being; however, holistic approaches must be taken to address the underlying causes of fuel poverty. [ABSTRACT FROM AUTHOR]

Automatic vectorization is an important technique for compilers to improve the parallelism of programs. With the widespread usage of SIMD (Single Instruction Multiple Data) extensions in modern processors, automatic vectorization has become a hot topic in the research of compiler techniques. Accurately evaluating the effectiveness of automatic vectorization in typical compilers is quite valuable for compiler optimization and design. This paper evaluates the effectiveness of automatic vectorization, analyzes the limitation of automatic vectorization and the main causes, and improves the automatic vectorization technology. This paper firstly classifies the programs by two main factors: program characteristics and transformation methods. Then, it evaluates the effectiveness of automatic vectorization in three well-known compilers (GCC, LLVM, and ICC, including their multiple versions in recent 5 years) through TSVC (Test Suite for Vectorizing Compilers) benchmark. Furthermore, this paper analyzes the limitation of automatic vectorization based on source code analysis, and introduces the differences between academic research and engineering practice in automatic vectorization and the main causes, Finally, it gives some suggestions as to how to improve automatic vectorization capability. [ABSTRACT FROM AUTHOR]

Artificial intelligence is part of our future and has allowed the creation of truly advanced devices. Now 3D printing technology can also make full use of AI, and with the development of this technology, it is expected to be used in various fields in the era of the Fourth Industrial Revolution. This technology can be used not only in manufacturing but also in various fields such as architecture and medical care and is recognized as an essential technology for future generations. Educating the students about the use and impact of 3D technology is even more important than it was ever; however, not enough research has been conducted on specific teaching methods for 3D printing technology education. This paper, therefore, studies the future education method using 3D printing technology for children. The research method of this study is a qualitative research method in which interviews and participant observation methods are used. This qualitative research method was developed by James P. Spradley, an American cultural anthropologist. The findings of this study are as follows. Children can make products easily by using 3D programs and can develop creativity through this product design process. Based on these results, this paper aims to present the curriculum and teaching methods of 3D printing that can be practically utilized in public education courses. This education will be a preparatory step for the micro-manufacturing industry in the future. The findings of this study are helpful in developing the courses of future education. [ABSTRACT FROM AUTHOR]

Compressors are one of the three major components of gas turbines, and their characteristic curves are used to analyze off-design performance. How to infer the characteristic curve based on different data is an important research topic. In this paper, PG9351FA gas turbine is taken as the research object. Two methods, artificial neural network and parameter estimation, are used to predict its characteristic curve, and the prediction accuracy and application conditions of the two methods are discussed. This article compares the two methods from the perspectives of known speed characteristic curve regression and unknown speed characteristic curve inference, analyzes the impact of sample size and sample error on their inference results, and quantitatively analyzes the error through statistical methods such as calculating the mean square deviation of the data. The application scope and conditions of different methods are provided. The research results show that the method based on neural network to infer the characteristic curve has high accuracy and is suitable for the prediction of known and unknown speed characteristic curves under sufficient data, but not for the prediction of unknown side curves. The elliptic equation fitting method based on parameter estimation has a slightly lower accuracy in processing the nearly vertical compressor characteristic curve, but it can be used as an effective and reliable method to infer the compressor characteristic curve in the case of a small amount of data. The modulization method based on parameter estimation has high accuracy and is applicable to the estimation of complete characteristic curve from partial data of known characteristic curve. In this paper, the application scope and conditions of these two methods are determined, which can provide reference for engineering practice. [ABSTRACT FROM AUTHOR]

The heart and soul of the Chinese people and the greatest cultural soft power of contemporary China are excellent Chinese healthy cultural environments. Short video platforms and short videos have a chance to develop as the Internet revolution continues to intensify and mobile clients gain popularity. This essay examines the challenges involved in producing brief videos that promote a healthy cultural environment in the new context of internet plus, as well as the means of transmitting such videos and creative methods for doing so. Excellent communication content is created in this paper from two perspectives of visual presentation and in-depth meaning, allowing users to fully understand the connotation of a healthy cultural environment. Through the theme of a healthy cultural environment, topic discussion and characteristic activities will be carried out to encourage users' spontaneous sharing of the interactive behavior of communication and the fission communication of brief videos of a healthy environment. This paper develops a model for intelligent recommendation and short video content analysis based on this. In order to further encourage the creative dissemination and development of short videos about healthy cultural environments, the model is used to choose high-quality videos and accurately recommend them to the appropriate users and to serve as an example of how a quick video can be used to communicate innovation and a healthy cultural environment. [ABSTRACT FROM AUTHOR]

There has been an increasing acknowledgement in the UK of the importance of recognising frailty as a condition that leaves older people vulnerable to dramatic, sudden changes in health triggered by seemingly small events. In policy, the approach to managing frailty is often an emphasis on staying well with limited consideration to frailty as an end-of-life phase. Meanwhile, discharge from hospital continues to be complex. Overstretched acute hospitals are juxtaposed with community and social services that struggle to keep up with the demand of those being discharged and the labelling of older people as "bed blockers" at the centre of delayed discharges. This paper reports a study underpinned by constructivist grounded theory methodology, with the aim of exploring the experiences and perceptions of stakeholders. Semistructured interviews were conducted with 57 participants including patients, their informal carer(s), community hospital staff, community health professionals, and care home managers. The core category of "the drive to discharge conveyor belt" was derived from data analysis. A significant finding of this study was that of the carer, their burden, and their intrinsic role in facilitating discharge, filling in gaps in services, coordinating services, and enabling the patient to stay at home, with little consideration of their choices or autonomy. The "drive to discharge" impacts older people, their informal carers, and health professional. This study suggests how they may be supported, through an ethical lens. [ABSTRACT FROM AUTHOR]

Bolted connections are widely used in assembly structures, and their dynamic characteristics are often affected by stiffness, damping, excitation, and other factors. In order to solve the problems of low computational efficiency of fine modeling and large computational error of linearized equivalent modeling of bolted structures, this paper proposes a dynamic characteristic parameter identification method for bolted structures based on the multiscale method and considering the influence of nonlinear factors. In this method, the bolted connection characteristics are simulated in the form of a combination of shear stiffness, torsional stiffness, nonlinear stiffness, and viscous damping coefficient and identified according to the test measurement frequency and frequency response function. At the same time, by establishing the nonlinear dynamic model of bolted structure, the influence of different bolt preloads and excitation forces on the dynamic characteristics of bolted structure is studied. [ABSTRACT FROM AUTHOR]

Background. Cancer diagnosis is a complex and multifaceted process that can be stressful and anxiety-provoking for patients. Evidence-based tools and information aids that can be used for guiding and supporting patients during cancer investigations and after diagnosis are limited. This paper presents a user-centred codesign project that aims to develop a cancer pathway support tool for patients, carers, and healthcare professionals. Method. A mixed-method codesign approach was used including prototype development (January–March 2022), three online codesign workshops (April–June 2022), one-to-one feedback, and beta testing informed by the standardised Theoretical Framework of Acceptability (TFA) questionnaire (July–October 2022). Nine individuals with lived experience of cancer contributed to the project and are referred to as codesigners. Results. The codesigners valued the potential importance of a tool that can be used by the patients and carers if they want specific information about cancer investigations, diagnosis, and treatment. The ability to select what they need as opposed to long leaflets and generating their own questions for the healthcare providers were highlighted as important aspects of improving patient care. The tool was collectively designed to provide clear definitions of the cancer care pathway and easily accessible links from trusted resources and includes practical information to minimise the burden that can be experienced from preparation for appointments and tests. Beta testing results with a small sample of potential users including patients, carers, and healthcare providers (n = 23) showed high acceptability of the guide (range = 7–35, mean = 28.52, and standard deviation = 3.88) based on the TFA questionnaire. Conclusion. A cancer pathway support tool called "Your Cancer Pathway Support Guide (YCPSG)" was developed as a result of an iterative codesign process aiming to improve patient experience and outcomes for people referred on a suspected cancer pathway or who have been diagnosed with cancer. The tool provides information and support in both digital and PDF formats. Further studies are needed to evaluate the potential impact of "Your Cancer Pathway Support Guide" on patient outcomes and experience and the wider system. [ABSTRACT FROM AUTHOR]

Nurses' turnover intention has increased since the COVID-19 pandemic. Emotional labor is reportedly high among nurses in Korea, and a positive psychological capital can help reduce turnover intention. This cross-sectional study investigated the factors influencing turnover intention in nurses during the COVID-19 pandemic. Survey data were collected from 155 nurses caring for patients with COVID-19 at a university hospital in South Korea in March 2022. Self-reported and paper-based questionnaires on emotional labor, positive psychological capital, and turnover intention were employed. The mean values for emotional labor, positive psychological capital, and turnover intention were 54.52/80, 58.03/90, and 38.92/50, respectively, and 77.8% of nurses reported planning to quit working. Turnover intention correlated with emotional labor (r = 0.17; p = 0.041) and had no significant relationship with positive psychological capital. Sex (β = 0.24; p = 0.003) and emotional labor (β = 0.18; p = 0.019) affected turnover intention, with 9% explanatory power. Female nurses caring for patients with COVID-19 had a higher turnover intention than male nurses. Finally, the higher the emotional labor of nurses caring for patients with COVID-19, the higher the turnover intention. To reduce the turnover intention of nurses, hospitals need to help them enhance their emotional labor and positive psychological capital by establishing measures such as emotional coaching programs or psychological capital interventions. [ABSTRACT FROM AUTHOR]

Social participation is positively related to mental health recovery and wellbeing, yet people with mental health problems are often socially isolated. This article investigates how social participation was incorporated into an Australian-integrated program that aimed to improve the wellbeing of people with chronic mental health needs. The data are from a longitudinal evaluation of the integrated program, including data linkage (5533 participants) and interviews (111). The paper uses concepts from the network perspective of social capital (bonding, bridging, linking, horizontal, and vertical) as lenses to re-examine the evaluation's findings about the consumers' social participation in life areas (social, leisure, and productive) facilitated by the program. This social capital perspective offers a lens to examine the breadth and intensity of participation experienced by the consumers taking part in the support program. The article adds to the literature about how service providers can improve social participation and therefore consumers' opportunities for recovery and wellbeing. The analyses found that the support increased people's social interaction and their capacity in the community. Their social interaction was mostly with other people in the service. Often their interactions in the community were only transactional. Few consumers participated in activities in productive life areas, and few of the activities promoted vertical social capital in social networks outside the service. The implications are that service providers need greater attention on facilitating a variety of social participation activities that can extend mental health consumers' horizontal and vertical social capital and so further contribute to their current and future recovery and wellbeing. [ABSTRACT FROM AUTHOR]

With the continuous updating and advancement of artificial intelligence technology, it gradually begins to shine in various industries, especially playing an increasingly important role in incremental music teaching and assisted therapy systems. This study designs artificial intelligence models from the perspectives of attention mechanism, contextual information guidance, and distant dependencies combined with incremental music teaching for the segmentation of MS (multiple sclerosis) lesions and achieves the automatic and accurate segmentation of MS lesions through the multidimensional analysis of multimodal magnetic resonance imaging data, which provides a basis for physicians to quantitatively analyze MS lesions, thus assisting them in the diagnosis and treatment of MS. To address the highly variable characteristics of MS lesion location, size, number, and shape, this paper firstly designs a 3D context-guided module based on Kronecker convolution to integrate lesion information from different fields of view, starting from lesion contextual information capture. Then, a 3D spatial attention module is introduced to enhance the representation of lesion features in MRI images. The experiments in this paper confirm that the context-guided module, cross-dimensional cross-attention module, and multidimensional feature similarity module designed for the characteristics of MS lesions are effective, and the proposed attentional context U-Net and multidimensional cross-attention U-Net have greater advantages in the objective evaluation index of lesion segmentation, while being combined with the incremental music teaching approach to assist treatment, which provides a new idea for the intelligent assisted treatment approach. In this paper, from algorithm design to experimental validation, both in terms of accuracy, the operational difficulty of the experiment, consumption of arithmetic power, and time cost, the unique superiority of the artificial intelligence attention-based combined with incremental music teaching adjunctive therapy system proposed in this paper can be seen in the MS lesion segmentation task. [ABSTRACT FROM AUTHOR]

In recent years, some scholars have proposed to apply single-stage target detection algorithms such as YOLO (You Only Look Once) to situational element detection, but the traditional YOLO algorithm is to treat the target detection process as a regression problem, which cannot distinguish well between overlapping objects and has defects such as less accurate bounding boxes and hard to distinguish objects from the background, and it is difficult to cope with problems such as the higher overlap of targets to be detected and stronger target camouflage ability in obscured overlapping scenes. In this paper, we propose to add the attention module CBAM to the backbone network of the YOLOv3 model, to construct a SEDNet with high accuracy and good robustness for situational element detection, and to apply it to the situational element detection in occlusion overlapping scenes. We use SEDNet to classify and localize ten elemental targets, respectively. The analysis of experimental results shows that the SEDNet target detection model can complete element detection in complex environments with strong target camouflage, achieve end-to-end detection, and lay the technical foundation for the formation of complete situational awareness. [ABSTRACT FROM AUTHOR]

Background. Missed nursing care adversely affects nurse and patient outcomes in healthcare settings. Comprehensive bibliometric overview of research output in this field is limited, which restricts knowledge of this complex phenomenon in terms of research trends, author's productivity, and thematic focus of scientific publications. This study aims to examine publications on missed nursing care by conducting a comprehensive bibliometric analysis. Methods. A search was performed in the Scopus database to identify 276 published studies on missed nursing care from inception to 20th February 2022. A bibliometric approach was used to comprehensively analyse retrieved publications based on trend, thematic focus, and scientific production. The R based software was used for data analysis. Results. The result from this bibliometric analysis indicates that the first study performed on the concept of missed nursing care was published in 2006. The United States of America (USA) ranked first in number of publications, and the study by Ball et al. published in 2014 was the most cited paper among the documents analysed. The results also identified names of prolific authors such as Kalisch B.J., Ausserhofer D., Willis E., Papastavrou E., Schubert M., Palese A., Simon M., and Aiken L. H. and relevant institutions in this field. Trending keywords identified included "missed nursing care," "unfinished nursing care," "patient safety," and "care left undone." In addition, thematic analysis showed emerging themes such as "neonatal intensive care unit," "patient satisfaction," "health resources," "failure to maintain," and "adverse events." Conclusion. Findings from this study reveal a lack of bibliometric analysis in missed nursing care research. This study provides significant contribution by presenting a comprehensive overview on thematic focus, hotspots studies, and directions for future research in this field. Findings from this study can guide scholars in defining research focus and aspects of research on missed nursing care for future exploration. [ABSTRACT FROM AUTHOR]

With the development of intelligent sports in China and the rapid improvement of the strength of colleges and universities, the reform of traditional football players' header shooting training methods is becoming more and more urgent in order to solve some problems in the development of sports and speed up the intelligent training of Chinese football players. Based on this, this paper studies the biomechanical analysis and training method based on the integration of header strength data of football players. A dynamic header tracking model of football players based on a local search algorithm is designed. The data collection is realized from the aspects of athletes' header shooting training, skill improvement, physical consumption, and trajectory. The biological data of header shooting power is comprehensively analyzed and evaluated by using a local search algorithm. The results show that the training system based on a local search algorithm has the advantages of high feasibility, high data accuracy, and fast response speed. It can effectively conduct accurate guidance and improve the shooting accuracy according to the biological characteristics of header shooting intensity. This paper studies the biological analysis and training method of header strength of football players based on a local search algorithm. This has certain reference significance for accelerating the construction of intelligent training of Chinese football players. [ABSTRACT FROM AUTHOR]

In the new stage of the new century, a new technological revolution is coming quietly. This revolution is represented by "data." The application of "big data (B D A)" technology is causing changes in all walks of life, and the use of "B D A research methods" in the education field will inevitably become a trend. The purpose of this article is an innovative research on the teaching methods of Taekwondo based on the background of B D A in a college elective course. This paper first introduces the core technology of the database by summarizing the basic theory of the database. Based on the current situation of elective Taekwondo teaching in contemporary universities, analyze the current problems and deficiencies and conduct innovative research on college elective Taekwondo teaching methods combined with Beidou technology. This paper systematically expounds the practical connection, method innovation, and implementation path between BDA technology and college elective Taekwondo teaching methods and compares the traditional Taekwondo teaching methods based on BDA technology. Experimental research shows that compared with traditional Taekwondo teaching methods, the performance of university Taekwondo teaching based on data mining (D M I) in the context of B D A is more than 20% higher, which fully reflects its feasibility and the innovation of traditional Taekwondo teaching methods needs to be solved urgently. [ABSTRACT FROM AUTHOR]

Loneliness is considered to be a global public health challenge, impacting a range of physical and mental health conditions. Social prescribing, whereby service users are signposted into community-based activities and social groups by a community link worker, has been suggested as one mechanism to reduce service users' loneliness and social isolation. This paper reflects on service users' experiences of accessing a national social prescribing scheme. Drawing on qualitative findings from interviews with service users who were receiving support through a social prescribing programme between October 2017 and December 2018 (n = 26, with n = 12 interviewed a second time), we reflect on their experiences of the programme. We consider some of the complexities of providing short-term support with a focus on signposting people into local activities, when many service users prefer the companionship of their link worker. Furthermore, we highlight some of the difficulties in ending short-term support. Crucially, we highlight the importance of considering the intersection of the social determinants of health. We suggest that social prescribing schemes may exacerbate inequalities if consideration is not given to the ways in which people are (dis)advantaged in accessing the social capital necessary for their initial and continued involvement. [ABSTRACT FROM AUTHOR]

With the rapid development of computer science, a large number of images and an explosive amount of information make it difficult to filter and effectively extract information. This article focuses on the inability of effective detection and recognition of English text content to conduct research, which is useful for improving the application of intelligent analysis significance. This paper studies how to improve the neural network model to improve the efficiency of image text detection and recognition under complex background. The main research work is as follows: (1) An improved CTPN multidirectional text detection algorithm is proposed, and the algorithm is applied to the multidirectional text detection and recognition system. It uses the multiangle rotation of the image to be detected, then fuses the candidate text boxes detected by the CTPN network, and uses the fusion strategy to find the best area of the text. This algorithm solves the problem that the CTPN network can only detect the text in the approximate horizontal direction. (2) An improved CRNN text recognition algorithm is proposed. The algorithm is based on CRNN and combines traditional text features and depth features at the same time, making it possible to recognize occluded text. The algorithm was tested on the IC13 and SVT data sets. Compared with the CRNN algorithm, the recognition accuracy has been improved, and the detection and recognition accuracy has increased by 0.065. This paper verifies the effectiveness of the improved algorithm model on multiple data sets, which can effectively detect various English texts, and greatly improves the detection and recognition performance of the original algorithm. [ABSTRACT FROM AUTHOR]

Although individual factors play a vital role in determining professional autonomy, their specific impact during the coronavirus disease 2019 (COVID-19) pandemic has not been studied. This study aimed to compare nurses' professional autonomy when caring for patients with COVID-19 and for other patients and explore factors related to autonomy when caring for these patients. A paper-based questionnaire survey was conducted from June to August 2022 among nurses working at a university hospital in Japan. The survey included demographic factors (10 items, including, age, section, years of nursing experience, position, educational background, ladder level, and having certified nurse specialists or certified nurse qualifications) and individual experience factors (4 items: number of COVID-19 patients experienced, frequency and contents of searching for the latest information about COVID-19, frequency of using scientific sources, and frequency of training/study sessions on COVID-19 attended at the hospital). Additionally, basic knowledge of COVID-19 was evaluated. The scale for nurses' professional autonomy was developed based on a previous study. A paired t-test and stepwise multiple linear regression were used for the analyses. Overall, 241 nurses participated in the survey. The average length of nursing experience was 10.3 ± 9.2 years. The total scores for nurses' professional autonomy in all 5 factors 27 items were significantly lower (t = −12.1, p < 0.001) when caring for COVID-19 patients than when caring for other patients. Specifically, Factor 1 (Cognition) exhibited the most decreased scores when caring for COVID-19 patients than when caring for other patients. Factor 4 (Abstract judgment) differed the least between caring for COVID-19 and for other patients, but the average score was the lowest. More years of nursing experience (β = 0.208, p = 0.001) and a higher number of patients with COVID-19 cared for (β = 0.140, p = 0.026) were associated with higher autonomy scores. In conclusion, to enhance professional autonomy during an unprecedented pandemic, nurses must enhance cognition and abstract judgment. In the event of a future pandemic, nurses need to create an environment in which they routinely access and utilize the latest information and scientific evidence to provide high-quality nursing care based on their professional judgment and competence. [ABSTRACT FROM AUTHOR]

To better prevent the occurrence of hidden dangers of coal mine accidents and ensure the safety production of coal mine enterprises. This paper mines and analyses the pattern of historical monthly hidden danger quantity in the coal mine and constructs three models: the traditional backpropagation (BP) neural network model, the BP neural network based on the adaptive moment estimation optimization algorithm (Adam-BP) model, and the BP neural network prediction model with the introduction of monthly moderators (Month-Adam-BP). The experimental results show that the Adam-BP model can improve the prediction accuracy, in which the mean absolute percentage error (MAPE) improves by 8.93%, the root mean square error (RMSE) improves by 8.15%, the postdifference ratio C improves by 0.04, and the small error probability P improves by 0.12; the Month-Adam-BP model with the introduction of the monthly adjustment factor further improves the prediction accuracy, in which MAPE improves by 2.61%, RMSE improves by 5.41%, the postdifference ratio C improves by 0.06, and the small error probability P improves by 0.03. And the Month-Adam-BP model prediction accuracy reaches the level 2 standard with credible prediction effect; it can also be used to predict coal mines with periodic characteristics of hidden hazard data. Our prediction results show that the predicted number of hidden hazards in this coal mine for the next month is 29, which is an increase compared to the number of hidden dangers in the previous month. Thus, the coal mine safety managers need to strengthen the management of hidden hazards further to prevent accidents, which can better serve the standardization of coal mine safety production and ensure the smooth production of the coal mine. [ABSTRACT FROM AUTHOR]

Synchronous chip seal is an advanced road constructing technology, and the gravel coverage rate is an important indicator of the construction quality. The traditional method to measure the gravel coverage rate usually depends on observation by human eyes, which is rough and inefficient. In this paper, a detection method of gravel coverage based on improved wavelet algorithm is proposed. By decomposing the image with two-dimensional discrete wavelet, the high-frequency and low-frequency coefficients are extracted. The noise of the high-frequency coefficients in the image is removed by improving the threshold function, and the contrast of the gravel target in the low-frequency coefficients is improved by the multiscale Retinex algorithm, and then two-dimensional wavelet reconstruction is carried out. Finally, the gravel target is segmented by the block threshold method, and the pixel ratio of the gravel is calculated to complete the detection of the gravel coverage. The experimental results show that the proposed method can effectively segment the gravel target and reduce the influence of environmental factors on the detection accuracy. The detection accuracy error is within ±2%, which can meet the detection requirements. The improved wavelet algorithm improves the signal-to-noise ratio of the denoised image, reduces the mean square error, and achieves a relatively good denoising effect. [ABSTRACT FROM AUTHOR]

Yan'an is one of the "two holy places" of the Chinese nation and the Chinese revolution and is one of the first cities of historical and cultural significance and an outstanding tourist city in China, as announced by the state council. The evaluation of the effectiveness of environmental conservation is one of the very important elements of the conservation of Yan'an's architectural heritage. However, the existing evaluation methods cannot provide new solutions for decision-making, the meaning of the comprehensive evaluation function is unclear, the naming clarity is low, there is less quantitative data and more qualitative components, and the results are not easily convincing. This paper proposes a method for evaluating the practical effects of environmental class measures in the conservation of Yan'an's architectural heritage based on recurrent neural networks. The recurrent neural network makes full use of the memory function in the network, considers the causal relationship of the actual effect, and efficiently evaluates the existing measures. In comparison with factor analysis and hierarchical analysis, this paper has greater applicability in evaluating the practical effects of environmental measures in the conservation of Yan'an's architectural heritage and is basically consistent with the results of the theoretical analysis. It provides a scientific basis for the construction and implementation of environmental measures for the architectural heritage of Yan'an. [ABSTRACT FROM AUTHOR]

The water environment is one of the basic elements that constitute the environment. It is an important place for the survival and development of human society, and it is also the most seriously disturbed and damaged area by humans. The pollution and destruction of water environment has become one of the major environmental problems in the world today. The essence of urban water space landscape design under the concept of integrating people's ecological design is the ecological landscape design of urban water spaces, while the development of ecological landscape design in the field of urban water space landscape design is still in its infancy, and the interpretation of its concept is also different. The ecological design of the landscape reflects a new dream of human beings, a new aesthetics and value: the true cooperative and fraternal relationship between man and nature. At present, the ecological design of urban water space landscape has not put forward a more accurate concept, clear principles and standards, and a complete and systematic theoretical basis, which requires further research, discussion, and continuous practice by this generation of designers to improve it. To this end, this paper proposed a research method on the integration of water environment governance in urban and rural spaces with natural ecological landscape design. This paper mainly talked about the status quo of water environment and its network sensor algorithm research and analyzed its coverage area one by one. Then, the water quality extraction is introduced in detail. And finally, the data analysis of the Beijing river waters, the analyzer rainfall, water quality, and so on are carried out in the experimental part. It could be seen from the experimental results that there were currently 22 reclaimed water plants in six urban areas of Beijing, with a daily water treatment capacity of 4.08 million cubic meters and a sewage treatment rate of 98%. As of 2016, 440 million cubic meters of reclaimed water has been reused. With the commissioning of the new reclaimed water system, the proportion of reclaimed water in the river and lake environment will continue to increase. [ABSTRACT FROM AUTHOR]

This paper constructs an algorithm for youth school violence recognition and an occupational therapy education model for victims through the extraction of action speech features. For the characteristics of violent actions and daily actions, action features in time and frequency domains are extracted and action categories are recognized by BP neural network; for complex actions, it is proposed to decompose complex actions into basic actions to improve the recognition rate; then, LDA dimensionality reduction algorithm is introduced for the problem of the high complexity of algorithm due to high dimensionality of features, and the feature dimensionality is reduced to 8 dimensions by LDA dimensionality reduction algorithm, which reduces the system running time by about 51% and improves the accuracy of violent action recognition by 3.3% while ensuring the overall performance of the system. The LDA dimensionality reduction algorithm reduces the number of features to 8 dimensions, which reduces the running time of the system by 51%, increases the accuracy rate of violent action recognition by 3.3%, and increases the recall rate of violent action recognition by 8.86% while ensuring the overall performance of the system. Based on the classical D-S theory, we proposed an improved D-S evidence fusion algorithm by modifying the original evidence model with a new probability distribution function and constructing new fusion rules, which can solve the fusion conflict problem well. The recall rate for violent actions is increased to 90.0%, thus reducing the missed alarm rate of the system. [ABSTRACT FROM AUTHOR]

This paper constructs a platform framework for extensive data analysis of college students' psychological quality with the help of the thinking mode of big data and related technologies and proposes the construction principles, data sources, data processing methods, data platform construction, and platform application of big data analysis platform for college students' psychological quality assessment. This paper combines the application methods of big data technology, collects the management data related to the psychological quality assessment of college students, saves them into the system database with certain storage logic, and realizes the function of psychological quality assessment through the design of selected psychological quality assessment data, data management and data resource management and other parts based on the data results of extensive data analysis. This study provides some insights into the psychological quality assessment of college students. The strength of association between the variables of psychological quality assessment of college students changes over time, but the overall psychological structure is more stable. This stable psychological structure characteristic is conducive to constructing the policy of constant psychological education in large universities. [ABSTRACT FROM AUTHOR]

The accuracy of the initial ground stress balance determines the accuracy of the finite element analysis of geotechnical problems. The traditional ground stress balance method has a good balance effect for simple geotechnical models but has strong limitations when the structure and soil interact with each other, the geometry of the model is complex, or the constraints are complicated. To deal with such problems, this paper proposes a general ground stress balance method based on geometric tracing by iteratively superimposing the static displacement field of the numerical model with the initial node coordinates of the numerical model. Two commonly used methods as well as the proposed method were tested with a model which contains both soil elements and structural elements and a case study. Test results show that the proposed method is capable of dealing with a complex model in which the commonly used methods fail to. Furthermore, the proposed ground stress balance method was demonstrated to be clear and has rapid convergence and high accuracy for complex stratum-structure geotechnical problems. [ABSTRACT FROM AUTHOR]

Constructing a perfect urban fresh agricultural product supply system is the basic guarantee for the stability of urban life, and it is also the basic condition for supporting urbanization. This paper combines unsupervised learning algorithms to predict and analyze agricultural product consumption behaviors, determines whether to generate new neurons through the cumulative error value of the winning neurons, and gives a network model that can dynamically self-grow. Moreover, this paper constructs an agricultural product consumption behavior prediction model based on unsupervised learning and uses data to verify the performance of the algorithm in this paper. After confirming the performance test of the algorithm, it verifies the prediction effect of this method on the consumption behavior of agricultural products. Through statistical analysis of data, it can be known that the prediction method of agricultural consumption behavior based on unsupervised learning has a certain effect. [ABSTRACT FROM AUTHOR]

Research has historically focussed on participants who are relatively easy to access; those who have resources (time and literacy) to respond to surveys, who can travel, and are socially connected. Failure to meaningfully engage with intended participants and achieve representativeness in participation risks diminishing the applicability and impact of research findings to local contexts. Motivated by goals of social justice and health equity, this scoping review sought to identify strategies to effectively engage and integrate the "authentic voice" of populations that are described as vulnerable or precarious and therefore perceived as "hard-to-reach." A system tic search strategy identified 34 eligible papers. Articles underwent (i) a title and abstract screening by two reviewers, followed by (ii) a full text review of eligible articles by one author. Free-form research problem mind-mapping was applied to facilitate analysis and generate creative associations between ideas. Thematic and content analysis was then applied to generate themes and subthemes. Four high-level themes emerged: key players, trust and rapport, navigating structural precarity, and moving beyond "participation." We identified that substantial shifts in researcher mindsets are required to reframe perceptions of vulnerability and move towards strengths-based approaches. Efforts need to be directed towards establishing deep trust and rapport through early engagement and social reciprocity. Systemic barriers to research participation and partnership must be addressed to overcome issues of structural precarity. We urge researchers and practitioners to embrace "scholar activism" and to actively dismantle the precarity that limits active "participation" and to build deliberate strategies to create forums where the "authentic" voice can be amplified. [ABSTRACT FROM AUTHOR]

Social enterprises, which are businesses with social objectives, have been championed by the UK government as an opportunity to deliver more innovative, socially oriented, and commercially sustainable public services. However, very little is known about them, especially in a social care context. This paper therefore aims to answer the following three questions: (1) What are care social enterprises?, (2) What are their distinctive qualities?, and (3) How can they contribute to the adult social care sector? It presents evidence from a "mapping" of care social enterprises in three English local authorities, and from interviews with 35 stakeholders from across the social care and social enterprise sectors. Drawing on an institutional logics framework, we explore the influence of different norms, goals, and practices on care social enterprises and the extent to which they are aligned with those of the public, private, and not-for-profit sectors. We found that their unique combination of business and social logics, along with an entrepreneurial mindset, may make them more flexible, innovative, and able to diversify their income than public and not-for-profit care organisations. They were also considered more trustworthy than private care services. However, their competing social and business logics can create internal tensions and bring uncertainty about what organisational model they are. These tensions can make it challenging for us to define what a care social enterprise is and in turn for social enterprises to promote themselves and attract funding. [ABSTRACT FROM AUTHOR]

As computer technology advanced, VR has emerged. It is a virtual environment based on high-tech computer technology that can bring people a sense of reality and sensory experience. Through specific devices or equipment, it uses unique means to interact and communicate with the target object in the virtual environment, so that the professor can get a sense of reality and immersive experience. In order to increase students' interest in teaching content, and at the same time to develop the education industry to achieve technology, this article combines virtual reality technology with experimental teaching. The paper discusses the use of VR in animation art experimental teaching and plans to provide thoughts and instructions about the fresh way in animation experimental teaching. This paper proposes the application research methods of VR in animation experiment teaching, including literature research method, expert interview method, questionnaire survey method, VR animation art teaching based on image method, and VR animation teaching evaluation clustering algorithm, which is used for conducting research experiments on the utilization of VR in animation art experimental learning. The experimental results in this article show that 96.25% of students like animation art VR experimental teaching system, which is helpful to the development of the teaching work. [ABSTRACT FROM AUTHOR]

Ligament loss of the ankle joints is common. If it is not handled properly, it is easy to cause repeated sprains of the ankle joints. Usually, medical image examination will be the first choice for the diagnosis of ligament injury. This paper analyzes the ankle ligament injury of hip-hop training based on medical images and studies the hip-hop training skills, to explore the application method of medical images in ankle injury, and can provide some theoretical and practical references for other sports injuries. In this paper, several medical image-related technologies such as texture feature extraction, main visual feature SAR method, and edge detection method are proposed. These technologies are applied to the study of ankle ligament injury, and an effective medical training therapy is determined by setting up the control group and the treatment group to observe the medical image display of each part of the ankle. Through the statistics of the clinical efficacy judgment standard results of patients in the treatment group and patients in the control group after two weeks of injury, it is found that the experimental results show that the cure rate, significant efficiency, and total effective rate of patients in the treatment group after two weeks are higher than those in the control group, and the total effective rate of the treatment group has reached 92.20%. [ABSTRACT FROM AUTHOR]

In order to improve the safety design of roadside areas and reduce the loss of roadside accidents, this paper uses PC-Crash software to perform an accident simulation analysis. By recording the track of the vehicle after entering the roadside, the recommended widths of the roadside clear zone for different operating speeds and horizontal curve radii in straight and curved sections are given. According to our previous research data, the conditions for setting the roadside clear zone are proposed. Finally, based on a cost-benefit ratio analysis, a comprehensive risk index method is adopted to evaluate the social stability risk of the project and conduct research on the design method of the roadside clear zone. The results show that the width of the roadside clear zone has an exponential relation with the departure speed and a power relation with the horizontal curve radius. The research results realize the accurate calculation of the roadside clear zone width and fill in the gaps of the relevant specifications and guidelines in the setting conditions of the roadside clear zone. [ABSTRACT FROM AUTHOR]

This paper studies the behavior of intellectual property pledge loan based on a specific social network and uses the method of experimental research to analyze the impact of factors on the comprehensive trust of intellectual property pledge loan. The results show that if direct cooperation records between enterprises and banks are complete, the larger the scale of cooperation, the higher the trust of intellectual property pledge loans, and the nearer the cooperation record to the present time, the greater the credibility of enterprise cooperation. If there is no direct cooperation record between enterprises and banks, or cooperation record is incomplete, in accordance with the trust evaluation of the recommended members on the intellectual property pledge loan enterprise, the smaller the degree of trust at a certain recommendation node, the lower the credibility of enterprises at this node correspondingly, and the lower the perceived risk tolerance of banks, the lower the cooperation satisfaction in the intellectual property pledge loan enterprises. [ABSTRACT FROM AUTHOR]

The cultivation of strategic emerging industries is strategic to the economic transformation and upgrading in Fujian, a southeastern province of China. It is of great significance to study its selection model. In this paper, according to the characteristics of strategic emerging industries, drawing on the double helix model, this paper sets up an evaluation system for strategic emerging industries. Then, the entropy-VIKOR algorithm was introduced to evaluate and rank the backbone enterprises in Fujian, based on the data on 21 listed enterprises of strategic emerging industries in the province from 2017 to 2019. The empirical research results are consistent with the actual situation of the development of strategic emerging industries in Fujian Province, which proves the feasibility of this research method. Finally, according to the empirical analysis results, this study puts forward some countermeasures for the development of strategic emerging industries in Fujian province. [ABSTRACT FROM AUTHOR]

The clinical research faces numerous challenges, from patient enrollment to data privacy concerns and regulatory requirements to spiraling costs. Blockchain technology has the potential to overcome these challenges, thus making clinical trials transparent and enhancing public trust in a fair and open process with all stakeholders because of its distinct features such as data immutability and transparency. This paper proposes a permissioned blockchain platform to ensure clinical data transparency and provides secure clinical trial-related solutions. We explore the core functionalities of blockchain applied to clinical trials and illustrate its general principle concretely. These clinical trial operations are automated using the smart contract, which ensures traceability, prevents a posteriori reconstruction, and securely automates the clinical trial. A web-based user interface is also implemented to visualize the data from the blockchain and ease the interaction with the blockchain network. A proof of concept is implemented on Hyperledger Fabric in the case study of clinical management for multiple clinical trials to demonstrate the designed approach's feasibility. Lastly, the experiment results demonstrate the efficiency and usability of the proposed platform. [ABSTRACT FROM AUTHOR]

This paper reports findings from a national, qualitative study in England that investigated if young adult carers services are facilitating young people's transitions to adulthood, including considering a future beyond caring. Semi-structured, online interviews were conducted in 2022 with a purposive sample of managers or lead workers of eleven young adult carers services in England. We discuss the consideration given in assessments to young people's caring preferences and the availability of support to facilitate them to relinquish their role, if they so wished. The majority of young adult carers services gave young people the opportunity to express their views on this issue. Although the Care Act 2014 aimed to provide choice over caring in adulthood to young adult carers, this was not matched by the necessary service provision to facilitate their preferences. A new national carers strategy is urgently required to ensure that young people, particularly women, have a credible choice over their future lives. [ABSTRACT FROM AUTHOR]

The test bench was designed to solve the problem of measuring the oil film thickness of the liquid hydrostatic guideway of machine tools. And based on the fast overshoot of the classical PID control, introducing the self-antidisturbance control algorithm, this study established a mathematical model of the test bench electro-hydraulic servo control system. At the same time, this paper also designed a specific structure of the self-turbulence controller, which adopts optimal quadratic control, pole configuration, PID control, and self-turbulence control to study the control methods of the test bench electro-hydraulic servo system, respectively, and uses the SIMULINK module to establish the system simulation model of the above-mentioned four control methods of the test bench. Simulation results of the test bench control system show that the response speed of the self-turbulence control is 0.4 seconds, 0.2 seconds, and 4.4 seconds faster than PID control, pole configuration, and optimal quadratic control, respectively, and the overshoot is significantly reduced. Finally, the test bench was built to complete the experiments, and the experimental results showed that the followability of the loading force and thickness detection accuracy of the test bench were better after adding the self-turbulence control algorithm and the stability of the oil film thickness was significantly improved by the test bench electro-hydraulic servo control system. [ABSTRACT FROM AUTHOR]

The amazing rise of digital currency is not only favored by investors but also attractive to lawbreakers for its anonymity and decentralization. This paper mainly discusses the intelligent digital currency and dynamic coding service system based on Internet of Things technology. In this paper, the RDCAR algorithm is used to realize the routing discovery process of the wireless network. When the intermediate node receives the RREQ message, first of all, to avoid the loop, it checks whether the same RREQ message has been introduced. If it has received it, it will discard it. Otherwise, it will cache the message and attach its own neighbor node list to the signal-to-noise ratio of the channel link, update the RREQ message, and broadcast it. The payment cipher is managed by the bank. When the user opens an account, the bank registers and sends it to the user. The key is generated by the algorithm chip, and the public key is kept in the bank background server. When the bill is delivered to the bank, the bank inputs all the elements on the bill on the counter terminal and transmits it to the verification machine for verification through the bank network. If the verification is correct, it indicates that the bill is indeed issued by the customer, and all bill elements are correct, and payment can be made. The node operation protocol of public chain and alliance chain maintains the operation of the Internet of Things system. The nodes of alliance chain generate new blocks according to the interval of 30 s. When the node fails to complete the block generation within 30 s, it will rotate to the next node. The mkfile command is used to generate 16b, 1 KB, 1 MB, and 1 GB files as input. The peak speed of the encoding service system is about 370 mb/s. The results show that the system designed in this study is robust and suitable for complex trading environment. [ABSTRACT FROM AUTHOR]

This paper provides an in-depth research analysis of occupational therapy strategies and psychological regulation of students' Internet addiction in the existing mobile social media environment. Based on the definition of Internet use peer pressure, a preliminary scale with 2 dimensions of specific behavioral pressure and psychological cognitive pressure was developed. First, a professor of mental health education and a master's degree student in mental health education were invited to rate the scale, while 47 junior high school students were selected to try the scale to ensure that the questions of the scale were clearly expressed. Secondly, 461 subjects were selected to take the initial test of the scale, and item tests and exploratory factor analysis were conducted to ensure that the structure of the scale was as expected and the scale was expressed to psychometric standards. Finally, 810 subjects were selected for the scale retest, and item analysis and validated factor analysis were conducted, and their results met the psychometric criteria. Student peer attachment significantly and positively predicted adolescent Internet addiction; Internet use peer pressure played an incomplete mediating role in the prediction of peer attachment to Internet addiction; loneliness played a moderating role in the pathway of peer attachment to Internet addiction, and loneliness also played a moderating role in the pathway of peer attachment to Internet use peer pressure. The attitude towards online games is entertainment to kill time, a tool to escape the pressure of study and to gain the fun of friends comparing with each other. The main online motivations of adolescents included individual and situational factors, and behaviors were characterized by pan-entertainment and gamification, mainly through mobile social networks to obtain external information and knowledge, maintain interpersonal relationships, and gain a sense of belonging; they were characterized by a fixation on time, space, and online content. The interaction of family members is more of a behavioral habit, and the communication habits and behavior patterns established in the family will influence the construction of children's relationships with others, while parents' head-down behavior will also influence children's attention to various needs of an Internet-dependent behavior problem, which in turn affects children's problem-solving and intimate relationships with family members. [ABSTRACT FROM AUTHOR]

With the rapid development of urbanization, urban land has been expropriated and developed on a large scale. Moreover, people's awareness of the protection of historical buildings is relatively weak, so some historical buildings have been demolished or rebuilt. Historical buildings have played an important role in the spread of national culture, so how to use some methods to protect historical buildings from being destroyed has become an urgent problem to be solved. The protection of historical buildings includes a series of complicated and rigorous procedures, such as on-site drawing and mapping, survey and design, and scheme discussion and construction. The surveying and mapping of traditional historical buildings require people to do it by themselves, so it is inevitably time-consuming and labor-intensive. This paper first discussed and analyzed the significance of historical building protection, and then used digital technology to make up for the shortcomings of traditional manual surveying and mapping and historical building protection methods. Modern technologies such as three-dimensional laser scanning technology and virtual reality technology are used to restore the style and appearance of historical buildings. Among them, in terms of the color of historical buildings, the restoration degree of buildings based on digital protection technology has reached 56.1%; at the same time, the efficiency of information collection and processing, and virtual model construction has also been improved. Thus, the ultimate goal of historical building protection is achieved, and it provides a reference for the digital protection of historical buildings. [ABSTRACT FROM AUTHOR]

In this paper, we develop a detection module with strong training testing to develop a dense convolutional neural network model. The model is designed in such a way that it is trained with necessary features for optimal modelling of the cancer detection. The method involves preprocessing of computerized tomography (CT) images for optimal classification at the testing stages. A 10-fold cross-validation is conducted to test the reliability of the model for cancer detection. The experimental validation is conducted in python to validate the effectiveness of the model. The result shows that the model offers robust detection of cancer instances that novel approaches on large image datasets. The simulation result shows that the proposed method provides analyzes with 94% accuracy than other methods. Also, it helps to reduce the detection errors while classifying the cancer instances than other methods the several existing methods. [ABSTRACT FROM AUTHOR]