An Evaluation of Texture‑Modified Diets Compliant with the International Dysphagia Diet Standardization Initiative in Aged‑Care Facilities Using the Consolidated Framework for Implementation Research
Texture-modified diets (TMDs) are commonly prescribed for older adults with swallowing difficulties to improve swallowing safety. The International Dysphagia Diet Standardization Initiative (IDDSI) provides a framework for terminology, definitions and testing of TMDs. This observational mixed-method study used the consolidated framework for implementation research (CFIR) to establish the barriers and enablers to IDDSI adoption in aged-care facilities (ACFs). Five New Zealand ACFs who had adopted IDDSI > 12 months previously were recruited. Evaluation tools were developed based on CFIR constructs, integrating data from (i) mealtime observations; (ii) manager interviews and (iii) staff (nursing, carers and kitchen) selfadministrated surveys. All facility and kitch en managers were IDDSI aware and had access to online resources. Three sites had changed to commercially compliant products post-IDDSI adoption, which had cost implications. Awareness of IDDSI amongst staff ranged from 5 to 79% and < 50% of staff surveyed felt sufficiently trained. Awareness was greater in large sites and where IDDSI was mandated by head office. Managers had not mandated auditing and they felt this had led to reduced perceived importance. Managers felt staff required more training and staff wanted more training, believing it would improve food safety and quality of care. Lack of a dedicated project leader and no speech pathologist on-site were perceived barriers. Collaboration between healthcare assistants, kitchen staff and allied health assisted implementation. ACF staff were aware of IDDSI but staff awareness was low. Using the CFIR, site specific and generic barriers and enablers were identified to improve future implementation effectiveness. Managers and sta ff want access to regular training. Multidisciplinary collaboration and improving communication are essential. ACFs should consider TMD auditing regularly. Successful implementation of IDDSI allows improvement of quality of care and patient safety but requires a systematic, site-specific implementation plan.
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Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning
(1) About 15-20% of couples struggle with the problem of infertility. 30 to 40% of these cases are caused by abnormalities in the structure and motility of sperm. Sometimes the only possibility for such people is to use the procedure of artificial insemination. CASA systems are used to increase the efficiency of this procedure by selecting the appropriate sperm cell. (2) This paper presents an approach to the sperm classification on the basis of its entire structure analysis, including flagella - often poorly visible and therefore ignored in the CASA systems element. The training of the Mask R-CNN architecture was performed on 2 publicly available and one specially created for this purpose sperm database. A 14-element feature vector was also proposed for the classif ication of 4 classes of typical head defects (amorphous, normal, tapered and pyriform) by the Support Vector Machine. (3) The sperm head (mAP 94.28%) and the whole flagellum (mAP 90.29%) were successfully detected. However, the flagella segmentation results were significantly lower (50.88%) than that the head segmentation (88.32%). Classification with SVM scored 82% accuracy. (4) Research has shown that segmentation and the use of a simple SVM classifier allow for quite good results in the classification of sperm defects. However, it is important to develop a larger whole sperm database, to improve the segmentation results.
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: Traffic accidents put tremendous burdens on the psychosocial aspects of communities. Post-traumatic stress disorder (PTSD), after an accident, is one of the most prevalent and incapacitating psychiatric conditions worldwide. In this systematic review, we aimed to investigate the predictors of PTSD in traffic accident victims. Primary search was conducted in November 2021 and updated in 2023. Studies were excluded if they used any analysis except regression for predictors. Cumulatively, primary and update searches retrieved 10,392 articles from databases, and of these, 87 studies were systematically reviewed. The predictors were categorized into sociodemographics, pretrauma, peritrauma, and post-trauma factors. The PTSD assessment time varied between 2 weeks and 3 years. Being a woman, having depression and having a history of road traffic accidents pretraumatically, peritraumatic dissociative experiences, acute stress disorder diagnosis, rumination, higher injury severity, and involvement in litigation or compensation after the trauma were significant predictors of PTSD. Key Words: Stress disorders, post-traumatic, PTSD, crashes, traffic, accidents, traffic (J Nerv Ment Dis 2024;212: 104–116) T here are often long-lasting physical and psychological effects from road accidents. The care process for accident victims involves different specialties. However, little information is available regarding the risk factors for developing psychiatric diseases, such as pos
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The power of the content of the influencers in inducing impulse
Purpose – The present research examines an underlying mechanism outlining how features of the influencers’ content influence the consumers’ urge to buy impulsively through the mediation of trust. Moreover, the moderating role of persuasion knowledge is also investigated in this study. Design/methodology/approach – By employing persuasion theory and social capital theory, this study develops a framework that is tested on 251 social media users. The PLS-SEM modeling technique is employed for data analysis. Findings – Results indicate that vicarious expressions and informational value are the two main characteristics of the influencer’s content, which develop trust in influencers’ posts and instigate an UBI. In addition, trust in influencer posts serves as a mediator between content chara cteristics and UBI. However, no moderating role of persuasion knowledge was found. Originality/value – The present study offers an inclusive understanding of how marketers can strategically use influencers by leveraging the influential power of their content.
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An information fusion approach for increased reliability of condition monitoring With homogeneous and heterogeneous sensor systems
In machinery condition monitoring, it is often vital to consider information from multiple sources due to possible sensor failure or signal distortion, which may result in misclassification of the health status. An issue with multiple sensor data fusion, however, is that the classification can be affected by conflicting results between sensor signals. The proposed method uses a novel three-module approach to information fusion in order to address the problem. Features corresponding to signal integrity are extracted and employed for training a one-class support vector machine to detect unwanted distortions or sensor failures. Different classifiers are trained for the different sensor types available and each signal recorded is used to determine machine health. D ecision-level fusion is conducted through a majority voting system using the integrity scores derived from the OCSVMs and the separate classification results. From this, a dynamically weighted fault diagnosis based on sensor signal quality is obtained. Experimental verification using vibration and acoustic emission signals show that the framework is viable and allows for an increased reliability in machinery health diagnosis. Keywords condition monitoring, information fusion, vibration, acoustic emission, multisensor system, signal integrity Introduction Traditional condition monitoring of rotational machinery typically focuses on a single sensor monitoring approach. Although this has led to great success, existing methods
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Achieving sustainability through the integration of lean, agile, and innovative systems: implications for Indian micro small medium enterprises (MSMEs)
Purpose – The purpose of this study is to learn how the incorporation and use of leanness, agility and innovation in Indian manufacturing micro, small and medium enterprises (MSMEs) affect their bottom lines and how much these factors contribute to the MSMEs’ ability to meet their long-term sustainability goals. Design/methodology/approach – The suggested model was subjected to data validation and additional empirical validation using a sample of 411 Indian manufacturing MSMEs. The analysis of construct measures is conducted through the utilization of confirmatory factor analysis, a statistical technique that is grounded in the theoretical framework of structural equation modeling (SEM). In addition, path model analysis was applied for the purpose to validat e the assumptions that were included in the structural models. Findings – Consistent with the proposed model, the findings of this study demonstrate that leanness, agility and innovation have a substantial favorable impact on the sustainability of a company’s performance. These findings may be helpful in gaining professionals, academics and policymakers to acknowledge the significance of leanness, agility and innovation in enhancing the long-term sustainability of MSMEs and enhancing the overall performance of a particular company. This research excluded the service industriesbased research papers. Research limitations/implications – Many research in the field of manufacturing industries that have adopted leanness, agility, innovativeness and sustainability as individual approaches or as a collective methodology of two or more were considered in the current study. This research excluded the service industries-based research papers. Practical implications – This literatur e review has recognized and analyzed various dimensions and roles of leanness, agility, innovativeness and sustainability that are prevalent in manufacturing industries that include the positive and negative effects on the performance of the industries. The research enlightens the path and shows future directions for research to develop efficient, effective and sustainable manufacturing industries. Social implications – By promoting the concept of focusing on the “human factor”, namely, stakeholder perspectives, the MSME sector is propagating a strategy that moves away from an excessive focus on technology and toward a more humane one. Through the application of the three key concepts of leanness, agility and innovation, this work aims to create a framework for measuring the sustainability performance of micro-, small- and medium-sized enterprises (MSMEs), with the ultimate goal of assisting the country in achieving the Sustainable Development Goals in the fields of industry , innovation and infrastructure by Conflict of interest: None Declaration: None Indian micro small medium enterprises 365 Received 30 May 2023 Revised 14 August 2023 Accepted 16 September 2023 Journal of Science and Technology Policy Management Vol. 16 No. 2, 2025 pp. 365-400 2053-4620 DOI 10.1108/JSTPM-05-2023-0087 The current issue and full text archive of this journal is available on Emerald Insight at: https://www.emerald.com/insight/2053-4620.htm Downloaded from http://www.emerald.com/jstpm/article-pdf/16/2/365/9684924/jstpm-05-2023-0087.pdf by University of Newcastle, kxdigital.bi supporting environmentally friendly and resource-conserving businesses that give back to society and the natural environment. Originality/value – The objective of this research is to assess the importance and effectiveness of integrating various approaches such as leanness, agility, innovativeness and sustainability within the framework of manufacturing micro, small, and medium enterprises (MSMEs) . The authors hope that by going further into these concepts, they will be able to broaden their understanding and get a more comprehensive insight into the role that these concepts play and how they might be successfully used within this environment.
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Early-Excitation Segment Atrophy (EESA) Syndrome: Linking Electrical Dyssynchrony to Regional Myocardial Atrophy
Identifying the underlying cause of cardiac dysfunction is essential for determining the appropriate treatment and prognosis. The current management paradigm for heart failure (HF) and cardiomyopathies predominantly emphasizes structural and ischemic etiologies, often overlooking the substantial role of electrical dyssynchrony in cardiac dysfunction and remodeling. This work introduces a novel conceptual framework that integrates existing evidence illustrating how electrical dyssynchrony induces mechanical dyssynchrony, culminating in regional cardiac impairment and structural remodeling. The myocardial area that activated early lacks proper afterload, impairing its ability to perform work effectively. Consequently, disuse atrophy gradually manifests in the early a ctivation area over time. We propose the concept of early-excitation segment atrophy (EESA) syndrome to address the HF caused by asynchronous conduction. For the left ventricle, whichever part contracts first will become disused and may contribute to or exacerbate HF. The conduction abnormalities known to induce EESA include left bundle branch block (LBBB), right ventricular pacing (RVP), bilateral bundle branch block (BBBB), Wolff–Parkinson–White (WPW) syndrome, and premature ventricular contractions (PVCs). Appropriate diagnosis and treatment will lead to improved left ventricular ejection fraction and reduced mortality. By integrating EESA into clinical practice, we aim to improve the recognition and
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