Systematic Model Research Articles

Introducing a systematic and sustainable patient safety oversight function in a U.K. arms-length healthcare body

Background The healthcare landscape is experiencing a profound period of change with accelerating developments in medical research, new treatments, care delivery and the use of innovative technology to meet the challenges of delivering care. These changes offer opportunities but as with all innovation, require careful management to reduce the likelihood of harm and error. Objective The National Institute for Health and Care Excellence (NICE) has set out to introduce an adaptable, sustainable and systematic patient safety oversight group to ensure that patient safety is embedded at an organisation level supporting the healthcare system to overcome challenges and deliver high quality care, safely implementing the latest innovations in a timely manner. Method The patient safety oversight group was established through a scoping exercise, led by the senior responsible officer and a small project team. The article sets out the methods used, including extensive internal engagement through structured interviews with senior leadership teams, purposive sampling, data synthesis and reporting. An overview of the group is given and considerations for promoting patient safety information flows and optimising the use of safety signal intelligence are made. Conclusion Through reflection on changing needs within and surrounding the organisation, along with patient safety and complexity literature, NICE has developed an adaptable, systematic and sustainable model for managing patient safety. In addition to generating learning within NICE, the process highlights opportunities for improvement within the patient safety system. Result NICE has developed an adaptable, systematic and sustainable model for managing patient safety.

Transverse energy absorption performance of sandwich tubes with various origami foldcores

Nowadays, composite sandwich tubes are extensively utilized in the civil and aerospace industries due to their superior strength-to-weight mechanical properties. Origami-based core offers a large enhancement of the mechanical properties, yet little study research focuses on the effect of various foldcore configurations on the transverse mechanical properties of sandwich tubes, necessitating the design method for applications. This study introduces an innovative approach by incorporating origami into the composite sandwich core to enhance the transverse energy absorption capacity. The quasi-static transverse mechanical properties of carbon fibre-reinforced polymer (CFRP) sandwich tubes with foldcores are studied under three-point bending-like local compression and transverse structural compression. A systematic geometric design framework and numerical modelling technique are provided. By integrating finite element analysis and experiments, the research investigates the effects of various origami foldcore configurations and geometric parameters on transverse energy absorption capacity. The experiment setup is provided by sandwich tubular specimens with a full-diamond configuration as the foldcore. The cylindrical tubes (foldcore) of the sandwich structures were manufactured using four plies [0°]4 of T700 (T300) woven CFRP with the hot press moulding (vacuum bag using female and male moulds) technique respectively. Then, the parametric study and damage mode analysis of eight different foldcore patterns (axial Miura, circumferential Miura, diamond, Kresling, and their curved-creased counterparts) were studied. The results showed the superior energy absorption performance of the sandwich tube with Miura-pattern foldcore over the origami-pattern counterparts, nested tube, and traditional honeycomb sandwich tube with CFRP or aluminium-made cores. Therefore, the structural parameters optimisation of the Miura pattern tube was carried out by the Response Surface method (RSM) and a design strategy for increasing the energy absorption capacity was found. The findings offer guidance for designing high-specific energy absorption tubular structures for future advanced engineering applications.

Do Heuristic Cues Affect Misinformation Sharing? Evidence From a Meta-Analysis

Information overload in online environments leads individuals to be more likely to rely on heuristic cues to make decisions about (mis)information sharing. Drawing on dual-process models of information processing, namely the heuristic–systematic model and the elaboration likelihood model, we conducted a meta-analysis of 31 individual studies to examine the combined effects of five major heuristic cues on misinformation sharing. The results revealed that the affective heuristic of anxiety exerted the strongest impact on misinformation sharing ( r = .343), followed by three cognitive heuristics: the self-confirmation heuristic ( r = .249), endorsement heuristic ( r = .125), and fact-checking heuristic ( r = -.115)—but not the authority heuristic. The endorsement misinformation receives, consistency between misinformation and individuals’ prior attitudes or beliefs, anxiety people feel, and absence of fact-checking labels all make people more likely to share misinformation. Moderation analyses also highlight the importance of considering contextual and cultural factors in future research.

Leveraging Blockchain Technology for Public Health

This study delves into the metamorphic potential pertaining to blockchain technology public health, concentrating on its aptness towards addressing the critical challenges related to data security, privacy, and it enroute for improving health service outcomes. By incorporating decentralized structures and smart contracts, blockchain intensify data integrity, ensuring consistency and protective access control, which is principally effective for sensitive medical information. The study enlightens on the advantages of blockchain in entrusting patients as well as healthcare providers with control over public health related information, ensuring privacy and reinforcing regulatory compliance. It delves into the process of how blockchain can streamline healthcare processes, upgrading interoperability among healthcare systems, and create more systematic and affordable models for healthcare service delivery. Based on the case studies from different healthcare stakeholders, the paper provides factual and feasible insights for real-world implementations of blockchain in healthcare, exhibiting its potential to transfigure supply chain management, different insurance claims processing and managing electronic health records. Moreover, the study also recognizes the challenges, including technical constraints, ethical reviews, and the complication of integrating blockchain with existing healthcare framework. The study widens it discussion towards the legal and regulatory aspect, emphasizing the need for a comprehensive approach to adoption. Looking forward, the paper covers the emerging trends and offers guidance for healthcare stakeholders considering blockchain implementation, summarizing that blockchain could be a catalyst for remarkable improvements in public healthcare data administration and patient care.

Multi-stage planning of clean resources and energy storage assets with hybrid uncertainty modeling for low-carbon resilient distribution systems

Climate change drives the urgent need for low-carbon and resilient energy system transitions. However, current planning methods ignore the inherent conflicts between carbon emission reduction and resilience enhancement, failing to optimally balance asset allocation for both aspects. They also neglect the long-term dynamic and stochastic nature of transitions, exposing systems to hybrid uncertainties. This paper presents a multi-stage dynamic planning method for clean resources and energy storage assets in power distribution networks. First, to facilitate low-carbon and resilient transitions, adaptive, stage-wise planning decisions are optimally determined under various planning strategies to mitigate risks stemming from hybrid uncertainties. Second, to precisely quantify the impact of hybrid uncertainties on decision-making, a systematic hybrid-uncertainty modeling approach is designed to capture short- and long-term uncertainties arising from both exogenous and endogenous factors. Third, to alleviate computational complexity, a decomposition-based stochastic dynamic dual integer programming method with augmented cut generation is introduced, which decomposes the original problem into stage-wise subproblems coordinated through forward and backward steps. Numerical results show that the proposed method generates cost-effective planning schemes, yielding $60 K in savings and reducing carbon emissions by 3853 tons. The method also demonstrates strong scalability, with a 52% reduction in solution time for large-scale planning problems.

Modeling and analysis of a novel CPSC/CI combined profile for scroll compressors

The scroll profile design has become a research hotspot and plays a decisive role in scroll machines. However, the modeling process is complicated due to different expressions of peripheral and central profiles in most full meshing profile (FMPs). Moreover, systematic modeling and in-depth property investigation of scroll profile are still insufficient. Herein, this study simplifies scroll profile modeling by constructing a novel FMP that combines a cubic power series curve (CPSC) with a circular involute (CI) to improve the properties of scroll compressors. An analytical model of CPSC/CI scroll wraps is proposed using the orthogonal components approach and validated by numerical examples. Geometric models to calculate chamber volume and gas load action length, and gas load models, are established. The effects of the CPSC/CI on the scroll wrap tip, built-in volume ratio and gas load are investigated. The proposed CPSC/CI enhances scroll compressor's properties by providing favorable properties not only with wider range of variation in scroll wrap tip and built-in volume ratio but also smaller gas load vibrations due to its superior flexibility, compared to circular arc/CI. This study provides new possibilities for enhancing scroll compressor performance through the design of scroll wrap profile.

Spatiotemporal Cluster Detection for COVID-19 Outbreak Surveillance: Descriptive Analysis Study.

During the peak of the winter 2020-2021 surge, the number of weekly reported COVID-19 outbreaks in Washington State was 231; the majority occurred in high-priority settings such as workplaces, community settings, and schools. The Washington State Department of Health used automated address matching to identify clusters at health care facilities. No other systematic, statewide outbreak detection methods were in place. This was a gap given the high volume of cases, which delayed investigations and decreased data completeness, potentially leading to undetected outbreaks. We initiated statewide cluster detection using SaTScan, implementing a space-time permutation model to identify COVID-19 clusters for investigation. To improve outbreak detection, the Washington State Department of Health initiated a systematic cluster detection model to identify timely and actionable COVID-19 clusters for local health jurisdiction (LHJ) investigation and resource prioritization. This report details the model's implementation and the assessment of the tool's effectiveness. In total, 6 LHJs participated in a pilot to test model parameters including analysis type, geographic aggregation, cluster radius, and data lag. Parameters were determined through heuristic criteria to detect clusters early when they are smaller, making interventions more feasible. This study reviews all clusters detected after statewide implementation from July 17 to December 17, 2021. The clusters were analyzed by LHJ population and disease incidence. Clusters were compared with reported outbreaks. A weekly, LHJ-specific retrospective space-time permutation model identified 2874 new clusters during this period. While the weekly analysis included case data from the prior 3 weeks, 58.25% (n=1674) of all clusters identified were timely-having occurred within 1 week of the analysis and early enough for intervention to prevent further transmission. There were 2874 reported outbreaks during this same period. Of those, 363 (12.63%) matched to at least one SaTScan cluster. The most frequent settings among reported and matched outbreaks were schools and youth programs (n=825, 28.71% and n=108, 29.8%), workplaces (n=617, 21.46% and n=56, 15%), and long-term care facilities (n=541, 18.82% and n=99, 27.3%). Settings with the highest percentage of clusters that matched outbreaks were community settings (16/72, 22%) and congregate housing (44/212, 20.8%). The model identified approximately one-third (119/363, 32.8%) of matched outbreaks before cases were associated with the outbreak event in our surveillance system. Our goal was to routinely and systematically identify timely and actionable COVID-19 clusters statewide. Regardless of population or incidence, the model identified reasonably sized, timely clusters statewide, meeting the objective. Among some high-priority settings subject to public health interventions throughout the pandemic, such as schools and community settings, the model identified clusters that were matched to reported outbreaks. In workplaces, another high-priority setting, results suggest the model might be able to identify outbreaks sooner than existing outbreak detection methods.

행동기준 평정척도(BARS)를 적용한 대학생 핵심역량 측정도구 개발 및 타당화 연구: D대학의 의사소통역량을 중심으로

Objectives This study attempted to develop the core competency’s measurement tool and secure its validity by focusing on the D University’s communication capabilities and applying the behaviorally anchored rating scale based on experiences or behaviors closely related to students’ university education and life. Methods This study applied appropriate research methods according to a six-step’s systematic research procedure, including core competency analysis and competency modeling, analysis of behavioral characteristics of excellent students through FGI for professors and BEI for students, development of core competency’s measurement tool through expert council, validation through expert delphi survey, pilot test and analysis, and finalizations stage of system, definition, and measurement tool. Results The research results are as follows. First, the core competency’s system and definition with a high consistent were derived through a systematic competency modeling process. Second, the behavioral characteristics of hyperformers(high-performing students) were analyzed through interview with professors and students and reflected in the behaviorally anchored rating scale. Third, the core competency’s measurement tool(draft) with a high consistent were confirmed. Fourth, a core competency measurement tool(revised version) was tentatively derived by verifying its validity through two expert delphi surveys. Fifth, a pilot test was conducted to improve effectiveness of the core competency’s measurement tool, and reliability and validity were secured. Sixth, the finalizations stage was completed, and the system, definition, and measurement tool of core competencies were confirmed. Conclusions By developing a core competency’s measurement tool based on the behaviorally anchored rating scale focusing on D University’s communication capabilities and then revealing the process of securing reliability and validity, It could play a significant role in suggesting alternative methods to objectively measure the core competencies of each university.

Optimal Curve Fitting for Serial Chain in Six-Crease Origami Unit

Abstract Origami-inspired structures have been widely used in aerospace and robotics for three-dimensional (3D) symmetrical configurations using crease-symmetrical origami basic patterns. These patterns offer advantages in repeatable and systematic modeling and mass production. However, few studies have focused on 3D non-symmetrical structures using symmetrical origami basic patterns due to their structure complexity, limiting their application. Therefore, we aim to analyze the folding behavior in 3D non-symmetrical structures using a 6-crease symmetry origami base pattern. To achieve this goal, we first focus on behavior in a two-dimensional (2D) plane. This paper presents a scheme for the behavior of origami units with an optimal curve-fitting algorithm. The curve can be any 2D space curve. The fitting curve, constructed by numerical analysis and an optimal approaching scheme, can satisfy error requirements and retain foldable origami unit features. The paper verifies the feasibility of the curve-fitting scheme by presenting two curve examples, including a quadratic curve and a sin wave function. The results show that the fitting error is reduced by 99% when no boundary conditions are applied. This research provides valuable insights into understanding origami unit kinematic optimization through forward and inverse kinematics. It offers potential applications in the engineering design of foldable structures and precision origami-inspired mechanism, thereby opening avenues for further exploration of complex origami structures and their applications in emerging technologies.

Development of a fuzzy analytic hierarchy process model, sensitivity analysis, and addressing barriers to additive manufacturing implementation in small- and medium-sized enterprises (SMEs)

Additive manufacturing (AM) is gaining popularity worldwide due to its potential to revolutionize manufacturing processes, improve product customization, and reduce waste. Nevertheless, small- and medium-sized enterprises (SMEs) encounter major challenges when implementing AM technologies. The objective of this research is to utilize the fuzzy analytic hierarchy process (FAHP) to identify and prioritize the critical challenges that impede the implementation of AM for SMEs. The study employs a two-stage methodology. First, a thorough literature review and expert discussions identify 15 major barriers to AM adoption. Second, a systematic model is proposed to establish a ranking of these barriers, which is based on the FAHP. The results are validated using sensitivity analysis to ensure the robustness of the findings. Additionally, potential solutions to overcome these barriers are discussed. The research indicates that the two most significant barriers for SMEs are the high costs of equipment and the scarcity of skilled designers. The model that has been presented is a valuable resource for SME managers and practitioners, as it allows them to make strategic and informed decisions that facilitate the efficient implementation of AM. This research is groundbreaking in its comprehensive analysis of the prioritization and ranking of AM implementation barriers, with a particular emphasis on SMEs. It offers essential insights for future research and practical applications.

Research on the classroom teaching design model of enterprise mentors from the perspective of modern apprenticeship

With the advancement of modern apprenticeship, corporate mentors play an increasingly important role in vocational education. However, in the face of new talent training models, corporate mentors face many problems and challenges in classroom teaching design work. This study aims to investigate the problems encountered in the classroom teaching design process for corporate mentors from the perspective of modern apprenticeship. It proposes a classroom teaching design model based on the BOPPPS model that integrates digital technology to solve these problems. This model aims to enhance corporate mentors' teaching design capabilities and classroom instruction quality through digital technology empowerment and optimization of the BOPPPS model. The research results of the paper provide a theoretical, systematic, and scientific classroom teaching design model for enterprise instructors. It provides new perspectives and practical solutions to the classroom instructional design of enterprise instructors under the modern apprenticeship system.

Major clinical relevance and considerations of zygomatic implants in elderly patients: a systematic review

For decades, zygomatic implants (ZI) have been used to rehabilitate atrophic maxillae and reconstruct maxillary defects, demonstrating significant survival rates, and have emerged as an alternative to extensive bone grafting. Despite their efficacy, surgical techniques for ZI placement have consistently been associated with perioperative complications, with additional problems arising later, especially in elderly patients. Objective: The present study developed a systematic review to address the main clinical relevance and considerations of zygomatic implants in elderly patients. Methods: The present study followed a concise systematic review model. The search was carried out in the PubMed, Embase, Ovid, Cochrane Library, Web of Science, and Scopus databases. The quality of the studies was based on the GRADE instrument and the risk of bias was analyzed according to the Cochrane instrument. Results and Conclusion: A total of 220 articles were found. In total, 77 articles were fully evaluated and 57 were included and evaluated in this study, and of the total of 57 articles, only 42 articles were developed in the item results of the systematic review. Of the initial total of articles, 108 articles were excluded because they did not meet the GRADE and AMSTAR-2 classification, and 20 were excluded because they presented a risk of bias that could compromise the credibility of the studies. The symmetric funnel plot does not suggest a risk of bias. According to the GRADE instrument, most studies presented homogeneity in their results, with X2=85.6%>50%. It was concluded the ZI has a high rate of survival accumulated in 12 years, with the majority of failures occurring in the early stages of the postoperative period. The main complication observed related to zygomatic implants in elderly patients was sinusitis, which can appear several years after implantation surgery. The presence of increased maxillary sinus pneumatization with advanced resorption of the posterior alveolus may result in insufficient bone to anchor the implant. Bone augmentation is generally necessary under these conditions to allow the placement of a sufficient number and length of implants. Another more serious condition would be defects of maxillectomy, aplasia of the maxillary sinus, and cleft deformities. Zygomatic implants appear to be a consolidated therapeutic option for a significantly atrophic maxilla in elderly patients, offering a promising alternative to costly heavy bone graft techniques, fewer complications, less time for rehabilitation, less required prosthodontic work, and significantly higher survival rates.

Polygenic risk and rare variant gene clustering enhance cancer risk stratification for breast and prostate cancers

Polygenic risk score (PRS) and rare monogenic variant screening are valuable tools for predicting cancer risk and identifying individuals at high risk. Integrating both common and rare genetic variants is crucial for accurate risk assessment. However, estimating the impacts of rare variants on cancer and combining them with PRS remains challenging. Here, we analyze 454,711 exome sequencing and 487,409 array UK Biobank samples, focusing on breast and prostate cancers. We introduce an expanded PRS (EPRS) approach, yielding a systematic model for more effective risk stratification. By prioritizing and clustering genes with cancer-specific rare variants based on odds ratios and population-attributable fraction, we refine risk stratification by combining both monogenic and polygenic effects. Individuals in high-PRS groups with rare high-impact gene variants show up to 15- and 22-fold higher risk for breast and prostate cancers, respectively, compared to those in the intermediate-PRS groups without rare variants. Combined risk profiles vary across distinct rare variant clusters within the same PRS group for both cancers. Our EPRS approach enhances risk stratification for breast and prostate cancers, offering important insights for future research and potential applications to other cancer types.

An Evaluation of the Sediment Reduction Benefits of Soil and Water Conservation Measures under Extreme Rainfall Conditions in the Loess Plateau in China Based on a Distributed Soil Erosion Model

Since the 1970s, comprehensive control measures on soil erosion in the headwater region of the Loess Plateau have been carried out. Quantitative evaluation of the benefits of soil and water conservation measures during extreme rainstorms is of great significance for the comprehensive management of the catchments. In this study, a systematic modeling methodology for evaluating the effects of soil and water conservation measures on sediment reduction was developed based on a distributed soil erosion model (DSEM). Taking the Chabagou basin in the Loess Plateau as the study area, the tested DSEM was used to simulate soil erosion and sediment yield during an extreme rainstorm under two scenarios, the uncontrolled condition and the controlled condition with soil and water conservation measures implemented. The results showed that DSEM could successfully simulate soil and water losses and evaluate the effects of soil and water conservation measures during extreme storm events. The evaluated results showed that each soil and water conservation measure had the specific function of sediment reduction. And under rainstorm conditions, the effect of engineering measures on sediment reduction was greater than that of forest and grass measures.

Varieties of Number-Line Estimation: Systematic Review, Models, and Data

The psychophysical function that best fits human data from number-line estimation is the subject of a lively, on-going debate with important theoretical and practical implications. We comprehensively reviewed articles which tested competing psychophysical functions and found systematic variablility in task design. To test whether one function could account for data across diverse tasks, we examined 158 children’s and adults’ estimates using two 2 × 2 designs, crossing symbol (symbolic, non-symbolic) and boundedness (bounded, unbounded) on free number-line tasks (Experiment 1) and crossing the same factors on anchored tasks (Experiment 2). This yielded eight varieties of number-line estimation: four old varieties for testing replicability and four new varieties for testing generalizability. Across the eight varieties, 88.84 % of participants provided estimates better fit by a mixed log-linear model than competing models, with weights of the logarithmic component (λ) decreasing with age in each task. Unlike parameters of competing models, λ on any given task significantly predicted λ on the other 7 tasks, as well as predicting arithmetic skills. Results suggest that representations of numerical magnitude play the largest part in number-line estimation, and the “logarithmic-to-linear shift” provides the most accurate and generalizable description of how number-line estimation develops. (196 words)

Artificial Intelligence Powered Pedagogy: Unveiling Higher Educators Acceptance with Extended TAM

There is a growing prevalence of AI tools in the arena of higher education. The willingness and intentions of higher educators play a significant role in successfully incorporating these tools. This investigation extends the Technology Acceptance Model (TAM) to explore the multifaceted interplay among determinants shaping higher educators' intentions for employing AI tools in their professional and pedagogical domains. The data was gathered from 400 respondents, comprising educators holding positions ranging from assistant professors to professors within Indian HEIs. The investigation validated the TAM model's applicability using covariance-based systematic equation modeling (CB-SEM) and supported nine of the fifteen proposed hypotheses. Further, the investigation underscores the significance of fostering higher educators' competency and confidence in AI tools through focused training and support services. Additionally, it highlights the role of their inherent openness to be proficient in such novel technological advancements. This investigation advances the prevailing AI-strengthened pedagogical sphere of education.

National, regional and provincial prevalence of childhood hypertension in China in 2020: a systematic review and modelling study.

Childhood hypertension is a growing health concern in China. Accurate estimation of prevalence is essential but challenging due to the variability of blood pressure and the need for multiple occasions for confirmation. This study aimed to estimate the national, regional, and provincial prevalence of childhood hypertension in China in 2020. For this systematic review and modelling study, we did a comprehensive literature search of epidemiological studies reporting the prevalence of elevated blood pressure (EBP) or hypertension among Chinese children (aged 18 years or younger) that were published between Jan 1, 1990 and June 20, 2024 in PubMed, Embase, MEDLINE, China National Knowledge Infrastructure, Wanfang Data, and Chinese Science and Technology Journal Database. EBP was defined as blood pressure greater than or equal to the 95th percentile on a single occasion, and childhood hypertension as blood pressure greater than or equal to the 95th percentile consistently across three occasions. First, we estimated the prevalence of childhood EBP using a multi-level mixed-effects meta-regression and the pooled odds ratios (ORs) for factors associated with childhood EBP through random-effects meta-analysis. Second, the ratio of childhood EBP to childhood hypertension was calculated via random-effects meta-analysis, based on which the national and regional prevalence of childhood hypertension was imputed. Finally, we derived the provincial prevalence of childhood hypertension using an associated factor-based model. The review protocol was registered in PROSPERO (CRD42024537570). We identified 8872 records, of which 134 articles covering 22 431 861 children were included. In 2020, the overall prevalence of hypertension among Chinese children aged 6-18 years was 3·11% (95% CI 2·35-4·04), equivalent to 6·80 million (5·13-8·83) affected children. The prevalence of childhood hypertension ranged from 2·25% (1·54-2·75) for children aged 6 years to 2·01% (1·36-3·37) for those aged 18 years, peaking at 3·84% (2·97-4·94) for those aged 14 years. The overall prevalence was higher in boys (3·34% [2·53-4·35]) than in girls (2·85% [2·13-3·69]). Associations between four factors (overweight, obesity, salted food intake, and family history of hypertension) and childhood EBP were graded as highly suggestive evidence. This study reveals substantial regional and provincial variations in the prevalence of childhood hypertension in China. Our findings could inform targeted public health initiatives and optimise resource allocation to address this public health concern. This study was supported by the National Natural Science Foundation of China (72104211 and 82273654) and the Chao Kuang Piu High-tech Development Fund (2022RC019). For the Chinese translation of the abstract see Supplementary Materials section.

Analytical and numerical predictions of elastoplastic buckling behaviors of the subsea lined pipelines with ovality defects under hydrostatic pressure

The subsea pipelines may deteriorate and/or be cracked after a long period of service. A cost-effective trenchless rehabilitation technology is to install a thin-walled steel liner inside the pipelines. However, elliptical defects may occur in the liner due to issues such as insufficient inflation, deformation of the host pipelines, and joint misalignment in practical engineering. Thus, this study aims to develop a systematic analytical model and numerical model for the elastic and inelastic buckling behaviors of the thin-walled oval steel liner, respectively. An admissible radial displacement function is introduced to describe the single-lobe deformation of the liner. The governing equations are established to trace the equilibrium paths by applying the theory of thin-walled shells and the principle of minimum potential energy. A two-dimensional finite element model is developed for the elastic and inelastic buckling performance of the liner. The analytical solutions of elastic buckling are in good agreement with other closed-form solutions, numerical results, and respective test results available in the literature. Finally, parametric evaluations are carried out in terms of ovality, non-uniform liner-pipeline gap, internal pressure, and liner yield strength.

“To exercise sustainably” – Patients’ experiences of compulsive exercise in eating disorders and the Compulsive Exercise Activity Therapy (LEAP) as a treatment: a qualitative interview study

BackgroundCompulsive exercise is common in eating disorders (EDs), but a systematic treatment model is lacking. The CompuLsive Exercise Activity TheraPy (LEAP) is a cognitive behavioral therapy treatment for compulsive exercise in EDs, delivered by trained therapists in groups over four consecutive weeks (8 groupsessions and 1 individual session), aiming to promote healthy physical activity. LEAP is currently evaluated in a randomized efficacy trial. In parallel, it is crucial to learn more about how it is perceived by qualitatively investigating participants’ subjective experiences.MethodsNine patients with various EDs participating in the LEAP trial were interviewed about their experiences of taking part in LEAP and about compulsive exercise as an ED symptom using a semi-structured interview guide. The interview transcripts were analyzed according to thematic analysis.ResultsThe informants expressed that compulsive exercise had not been addressed in their standard ED treatment and that LEAP as such provided an important complement, spurring reflection, awareness, and changed feelings and behaviors in relation to compulsive exercise. Initially, increased PA was triggered for some, but this side effect was transitory. A wish for more treatment time, in terms of longer or additional sessions, was expressed.ConclusionsOverall, LEAP seemed to fill an important treatment need and seemed both acceptable and feasible to patients. However, treatment time and the initial increase in PA may need further investigation and attention in order to optimize this treatment.Trial registrationThe trial is registered with the ISRCTN registry (registration date 20200325), trial ID ISRCTN80711391.

Parametric indoor 3D reconstruction based on binary image feature point extraction

Abstract In recent years, with the rapid advancement of laser scanning technology, indoor 3D modeling technology has significantly developed, becoming a research hotspot in the field of 3D reconstruction. Addressing the issues of high complexity in decoding point cloud surfaces in traditional indoor reconstruction, this paper proposes an indoor 3D reconstruction method based on binary image feature point extraction. The method utilizes point cloud data for semantic segmentation of the indoor environment to accurately extract the ceiling area, which is then projected onto the XOY plane and converted into a binary image, thereby transforming the 3D problem into a 2D problem. Subsequently, key feature points are identified through feature point detection technology, and systematic model construction is carried out based on the sequence of these feature points and their associated parameters. This method effectively simplifies the complexity of traditional 3D modeling, achieving accurate and parametric indoor 3D reconstruction.