Search Results (307)

Industry 4.0 (I4.0) promises that technological advances are happening at an accelerating rate, which is pushing all industries to undergo digital transformation to boost competitiveness, productivity, and business efficiency. As industrial companies transition to Industry 4.0, one of the maturity models that helps them identify opportunities is the Smart Industry Readiness Index (SIRI). SIRI is in line with other international manufacturing initiatives and has the potential to become a global standard for the manufacturing sector’s future. To achieve market competitiveness, smart manufacturing requires the end-to-end integration of Industry 4.0 technologies and SIRI. The successful implementation of such a comprehensive integration depends on carefully selecting the I4.0 technologies to conform to industry requirements. The Influences of I4.0 technologies on SIRI are not clearly outlined in any of the earlier research. Thus, employing a dependable Multi-Criteria Decision Making (MCDM) methodology using fuzzy TOPSIS, this article aims to analyze the influence of Industry 4.0 technologies on SIRI from the perspectives of both academic and industry experts. Expert opinions were gathered on the relationship between SIRI and I4.0 technologies. TOPSIS utilizes fuzzy theory to address the ambiguity and uncertainty inherent in human judgment. The findings showed that the best I4.0 technology for SIRI is the cyber-physical system (CPS). Full article

Current systems for exchanging medical records struggle with efficiency and privacy issues. While establishing the Electronic Medical Record Exchange Center (EEC) in 2012 was intended to alleviate these issues, its centralized structure has brought about new attack vectors, such as performance bottlenecks, single points of failure, and an absence of patient consent over their data. Methods: This paper describes a novel EMR Gateway system that uses blockchain technology to exchange electronic medical records electronically, overcome the limitations of current centralized systems for sharing EMR, and leverage decentralization to enhance resilience, data privacy, and patient autonomy. Our proposed system is built on two interconnected blockchains: a Decentralized Identity Blockchain (DID-Chain) based on Ethereum for managing user identities via smart contracts, and an Electronic Medical Record Blockchain (EMR-Chain) implemented on Hyperledger Fabric to handle medical record indexes and fine-grained access control. To address the dual requirements of cross-platform data exchange and patient privacy, the system was developed based on the Fast Healthcare Interoperability Resources (FHIR) standard, incorporating stringent de-identification protocols. Our system is built using the FHIR standard. Think of it as a common language that lets different healthcare systems talk to each other without confusion. Plus, we are very serious about patient privacy and remove all personal details from the data to keep it confidential. When we tested its performance, the system handled things well. It can take in about 40 transactions every second and pull out data faster, at around 49 per second. To give you some perspective, this is far more than what the average hospital in Taiwan dealt with back in 2018. This shows our system is very solid and more than ready to handle even bigger workloads in the future. Full article

Background/Objectives: Childbirth is a natural and joyfully anticipated life event for parents and relatives. Yet, in some cases, it can be a medical emergency requiring immediate intervention, i.e., neonatal resuscitation. The majority of newborns breathe spontaneously; a small number, though, may receive basic life support (assisted transition), and an even smaller but clinically significant number require advanced life support (resuscitation). Within the context of family-centered care, the presence of parents during resuscitation has emerged as a factor with potential implications for emotional adjustment, communication with healthcare providers, and early parent–infant bonding. However, the presence of family members during neonatal resuscitation remains a subject of ongoing debate among healthcare professionals (HCPs). Despite increasing recognition of its potential benefits, HCPs’ views on parental presence during such critical procedures have not been extensively investigated in Greece. This study aims at developing and validating a tool to assess healthcare professionals’ views on parental presence during neonatal resuscitation. Methods: A preliminary questionnaire was developed based on the principles of family-centered care and adapted to the Greek population. The first phase included expert assessment of validity, clarity, and relevance using a modified Delphi method. Item Content Validity Index (I-CVI) and Scale CVI (S-CVI) were calculated. Pilot testing was conducted to assess test–retest reliability. Reliability was assessed using the Intraclass Correlation Coefficient (ICC) and Bland–Altman analyses. The study followed the principles of the Declaration of Helsinki, ensuring anonymity, informed consent, and confidentiality. Results: The questionnaire includes 37–50 items allocated in four sections. It demonstrated excellent content validity (CVI = 1.00) and good test–retest reliability (ICC = 0.86). Qualitative feedback indicated that the tool is user-friendly and comprehensive. Interestingly, participants expressed genuine concerns regarding the implementation of parental presence in neonatal resuscitation. Conclusions: The questionnaire development process led to a comprehensive tool, ready for large-scale testing in order to further establish its validity and internal consistency. Full article

Background: Although evidence-based practice is widely promoted in nursing, direct care nurses remain underrepresented in research activities. This study aimed to assess nurses’ attitudes toward research, their perceptions of the organizational research environment, and their levels of involvement, as well as identify key barriers and facilitators to engagement within a comprehensive healthcare system. This study also explored how racial and ethnic diversity within the nursing workforce may shape research engagement and contribute new perspectives to the field. Methods: A cross-sectional electronic survey was administered to registered nurses across 10 hospitals in a Northeast U.S. health system. The survey instrument assessed research attitudes, environment, involvement (past, present, future), and demographics. Descriptive and inferential statistics, including matched-pairs t-tests, were used to analyze responses. Results: Of 7655 invited nurses, 1094 responses were analyzed. Respondents were predominantly female (88.5%), White (56.8%), and employed full-time (87.1%) as clinical staff nurses (77.3%). While 54.8% had completed a formal research course (mainly within the past 1–3 years), informal research and statistics training were uncommon (17.4% and 5.4%, respectively). Nurses reported highly positive attitudes toward research (composite M = 2.15, SD = 0.51), especially its role in guiding practice, professional growth, and education. However, actual involvement was low. The most common current activities included practice change based on research (20.7%) and participation in committees (18.8%). Anticipated future engagement increased substantially, particularly in collaboration (+21.3%), committee participation (+20.6%), and IRB submission (+18.2%). The research environment was perceived as under-resourced, particularly in terms of protected time, funding, and mentorship. Statistically significant gaps were observed between perceived present and desired future supports (p < 0.01 for all 15 items). The Research Awareness Index revealed high rates of uncertainty about available resources (e.g., 66.1% did not know if internal funding existed). Conclusions: Nurses demonstrate strong positive attitudes and a desire to engage in research, including more advanced roles. Yet structural and informational barriers, particularly a lack of protected time, mentorship, and awareness of existing supports, limit participation. Investments in infrastructure, communication, and accessible development pathways are needed to translate nurses’ readiness into active research engagement. Implications: Institutions should prioritize making research support more visible and navigable while investing in mentorship, protected time, and user-friendly infrastructure. Addressing both facets will empower a highly motivated nursing workforce to engage in and lead practice-relevant research. Full article

This study evaluates the degree to which small and medium sized enterprises (SMEs) are prepared to adopt smart manufacturing in contrast to large enterprises, a transition that depends on the effective use of the Internet of Things, artificial intelligence (AI), and advanced analytics. While many large multinational companies have already integrated such technologies, smaller firms still struggle because of tight budgets, limited technical expertise, and difficulties in scaling new systems. To capture these realities, the investigation refines the Initiative Mittelstand-Digital für Produktionsunternehmen und Logistik-Systeme (IMPULS) Industry 4.0 readiness model, which was initially developed to help German SMEs, so that it aligns with the circumstances faced by smaller manufacturers. A thorough review of published work first surveys existing readiness and maturity frameworks, highlights their limitations, and guides the selection of new, SME-specific indicators. The framework gauges readiness across six dimensions: strategic planning and organizational design, smart factory infrastructure, lean operations, digital products, data-driven services, and workforce capability. Each dimension is operationalized through a questionnaire that offers clear benchmarks and actionable targets suited to the current resources of each enterprise. Weaving strategic vision, skill growth, and cooperative support, the approach offers managers a direct path to sharper competitiveness and lasting innovation within a changing industrial landscape. Additionally, a separate Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis is provided for each dimension based on survey data offering decision-makers concise guidance for future investment. The proposed adaptation of the IMPULS framework, validated through empirical data from 31 SMEs, introduces a novel readiness index, diagnostic gap metrics, and actionable cluster profiles tailored to developing-country industrial ecosystems. Full article

Background: Stroke survivors and their family caregivers face substantial burdens resulting from a complex interplay of clinical, functional, and psychosocial factors. Community-based resources and social networking are critical for alleviating caregiver burden and improving outcomes for both caregivers and stroke survivors. Objectives: To assess the Saudi population’s readiness to use social platforms for stroke survivors’ recovery and caregiver support. Methods: A cross-sectional descriptive design was employed between March and June 2025 to collect data from community-dwelling individuals using sociodemographic and Technology Readiness Index (TRI) questionnaires. Results: A convenience sample of 576 participants was enrolled in this study. Overall, the participants showed a high level of technology readiness, with a total TRI mean score of M = 3.65, SD = 0.86. Optimism had the highest mean score, followed by innovativeness, insecurity, and discomfort. Significant differences in technology readiness were identified based on age, educational level, employment status, familiarity with modern technology, and healthcare provider status. Conclusions: This study demonstrates a high level of technological readiness across the Saudi population, indicating strong potential for integrating social connection platforms into stroke recovery and caregiver support. These findings align with Saudi Arabia’s Vision 2030 goals for digital transformation in the healthcare sector. Future research should focus on conducting feasibility studies to better understand the desirable features of e-health services and digital solutions within the Saudi community. Full article

As a part of sustainable transportation, robotaxis have been rapidly developing around the world because of their advantages in energy saving, improving road safety, and enhancing environmental sustainability, thereby providing consumers with sustainable transportation services. In China, as the number of pilot cities increases, more people are using robotaxi services. This study investigates the factors that affect consumer satisfaction and behavioral intentions after using a robotaxi, aiming to provide data to guide market strategy decisions. To do this, the value-based adoption model was extended and modified by including the technology readiness variable to examine satisfaction, intention to reuse, and electronic word-of-mouth (e-WOM) intentions. Using 425 valid responses, structural equation modeling (SEM) and multi-group analysis were carried out with AMOS 26.0. The results indicate that perceived usefulness, enjoyment, optimism, and innovativeness positively influence service satisfaction, whereas perceived risk and discomfort have negative effects. Consumer satisfaction positively affects both intention to reuse and e-WOM intention. Additionally, uncertainty avoidance shows a moderating effect between satisfaction and intention to reuse. Full article

Spatial heterogeneity in soil deposition poses a significant challenge to accurate geotechnical characterization, which is essential for sustainable infrastructure development. This study presents an advanced geotechnical data-driven mapping framework, based on a monotonized and augmented formulation of Shepard’s inverse distance weighting (IDW) algorithm, implemented through the Google Earth Engine (GEE) platform. The approach is rigorously evaluated through a comparative analysis against the classical IDW and Kriging techniques using standard key performance indices (KPIs). Comprehensive field and laboratory data repositories were developed in accordance with international geotechnical standards (e.g., ASTM). Key geotechnical parameters, i.e., standard penetration test (SPT-N) values, shear wave velocity (Vs), soil classification, and plasticity index (PI), were used to generate high-resolution geospatial models for a previously unmapped region, thereby providing essential baseline data for building infrastructure design. The results indicate that the augmented IDW approach exhibits the best spatial gradient conservation and local anomaly detection performance, in alignment with Tobler’s First Law of Geography, and outperforms Kriging and classical IDW in terms of predictive accuracy and geologic plausibility. Compared to classical IDW and Kriging, the augmented IDW algorithm achieved up to a 44% average reduction in the RMSE and MAE, along with an approximately 30% improvement in NSE and PC. The difference in spatial areal coverage was found to be up to 20%, demonstrating an improved capacity to model spatial subsurface heterogeneity. Thematic design maps of the load intensity (LI), safe bearing capacity (SBC), and optimum foundation depth (OD) were constructed for ready application in practical design. This work not only establishes the inadequacy of conventional geostatistical methods in highly heterogeneous soil environments but also provides a scalable framework for geotechnical mapping with accuracy in data-poor environments. Full article

Driven by the “Dual Carbon” objectives, integrated energy systems face an imperative to achieve synergistic optimization encompassing economic viability, low-carbon performance, and operational flexibility. To facilitate the low-carbon transition of combined heat and power (CHP) units, this study proposes an integrated optimization framework coupling CHP with diversified auxiliary installations. A multi-dimensional comprehensive evaluation is conducted on distinct coupling configurations incorporating electric boilers, heat pumps, thermal energy storage, and carbon capture and storage. Initially, an electro-thermal optimization model integrating multi-component devices—including CHP with carbon capture and storage (CHP-CCS), electric boilers, heat pumps, and thermal energy storage—is developed. A comprehensive evaluation index system is established across four dimensions: economic efficiency, operational flexibility, low-carbon performance, and technology readiness level. Subsequently, the Tanimoto coefficient is introduced to supersede the Euclidean distance in the conventional Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methodology, thereby refining the similarity measurement approach for optimal solution selection. Collectively, the configuration integrating CHP-CCS with electric boilers and heat pumps emerges as the optimal pathway. This configuration ensures reliable electricity and thermal load supply while substantially reducing system-level low-carbon transition costs and carbon emissions, concurrently enhancing renewable energy accommodation capacity. Full article

Background/Objectives: Anterior cruciate ligament reconstruction (ACLR) necessitates evidence-based rehabilitation strategies to optimize return-to-sport (RTS) outcomes, yet persistent re-injury rates and suboptimal performance persist despite standardized protocols. The purpose of this cross-sectional observational study is to examine the relationship between biomechanical, anthropometric, and temporal factors and return-to-sport outcomes. Methods: This cross-sectional study identifies biomechanical, anthropometric, and temporal determinants of RTS readiness in 81 recreational athletes post-ACLR. Outcome measures included anterior (A-SLH), lateral (L-SLH), and medial (M-SLH) single-leg hop for distance, single-leg sit-to-stand (SLSS), single-leg wall-sit hold (SLWS), and ACL-RSI. Statistical analyses employed Spearman’s correlations and multiple linear regression to determine the predictors of ACL-RSI. Results: There were significant correlations between RSI and Limb Symmetry Index (LSI) for L-SLH, M-SLH, SLSS, and SLWS (r = 0.27, r = 0.30, r = 0.44, r = 0.34, and p < 0.01, respectively). Among the functional outcome measures, multiple linear regression revealed that only SLWS significantly predicted ACL-RSI (β = 0.248, p = 0.037). Also, body weight (β = −0.233, p = 0.030) and postoperative duration (β = 0.292, p = 0.006) significantly predicted ACL-RSI. Conclusions: These findings challenge the primacy of limb symmetry indices alone, emphasizing the role of weight management, time-dependent neuromuscular adaptation, and multi-planar closed-chain strength in RTS decision-making. Clinically, rehabilitation frameworks should integrate personalized strategies targeting body composition and dynamic stability to mitigate asymmetric joint loading and enhance functional resilience. Full article

Background/Objectives: Mechanical ventilation is essential in the management of acute respiratory failure (RF); however, prolonged use increases the risk of complications. Accurate predictors are therefore needed to guide timely weaning. The Rapid Shallow Breathing Index (RSBI), the dead space to tidal volume ratio (VD/VT), and the Integrative Weaning Index (IWI) are among the key indices used to assess weaning readiness. This study aimed to examine whether these indices differ between patients with Type 1 (hypoxemic) and Type 2 (hypercapnic) respiratory failure who were successfully extubated in the emergency department, in order to explore their physiologic variability across respiratory failure phenotypes. Methods: This cross-sectional study included 35 adult patients (23 with Type 1 RF, 12 with Type 2 RF) who were successfully weaned from mechanical ventilation in the Emergency Department of a tertiary care hospital between 2022 and 2024. RSBI, VD/VT, IWI, and arterial blood gas parameters were recorded. Descriptive and comparative statistical analyses were performed, with significance set at p < 0.05. Results: There were no significant differences in age, gender, or comorbidities between the groups. Type 2 RF patients had higher FiO₂ requirements (37.5% vs. 30.0%; p = 0.03) and PaCO₂ levels (49.1 ± 9.65 mmHg vs. 40.3 ± 4.49 mmHg; p < 0.001). The PaO₂/FiO₂ ratio was lower in the Type 2 group (169 ± 49.6) compared to the Type 1 group (244 ± 95.6; p = 0.017). VD/VT ratios were significantly higher in Type 2 RF patients (0.37 ± 0.04 vs. 0.29 ± 0.13; p = 0.046). RSBI values were identical between groups (40.0 in both; p = 1.00), and IWI values showed no significant difference (70.8 ± 30.7 vs. 79.3 ± 32.5; p = 0.45). Conclusions: Although RSBI and IWI values were similar across respiratory failure types, patients with Type 2 RF demonstrated higher VD/VT ratios and lower PaO₂/FiO₂, indicating reduced gas exchange and alveolar ventilation efficiency. These findings suggest that VD/VT may be a more useful parameter for assessing weaning readiness in hypercapnic patients. Full article

Background/Objectives: Conventional ketogenic diets, although effective for weight loss, often contain high total and saturated fat intake, which leads to increased low-density lipoprotein cholesterol (LDL-C). Thus, the Healthy Ketogenic Diet (HKD) was developed to address these concerns. It emphasizes calorie restriction, limiting net carbohydrate intake to 50 g per day, prioritizing unsaturated fats, and reducing saturated fat intake. However, adherence to the HKD remains a challenge in urban, time-constrained environments. Therefore, this pilot randomized controlled trial aimed to investigate the effects of Healthy Ketogenic Diet Ready-To-Eat (HKD-RTE) meals (provided for the first month only) versus HKD alone on weight loss and metabolic parameters among overweight adults. Methods: Multi-ethnic Asian adults (n = 50) with a body mass index (BMI) ≥ 27.5 kg/m² were randomized into the HKD-RTE group (n = 24) and the HKD group (n = 26). Both groups followed the HKD for six months, with the HKD-RTE group receiving HKD-RTE meals during the first month. Five in-person workshops and mobile health coaching through the Nutritionist Buddy Keto app helped to facilitate dietary adherence. The primary outcome was the change in body weight at 6 months. Linear regression was performed on the change from baseline for each continuous outcome, adjusting for demographics and relevant covariates. Logistic regression was performed on binary weight loss ≥ 5%, adjusting for demographics and relevant covariates. Results: In the HKD group, participants’ adherence to the 50 g net carbohydrate target was 15 days, while that in the HKD-RTE group was 19 days over a period of 30 days. Participants’ adherence to calorie targets was 21 days in the HKD group and 23 days in the HKD-RTE. The average compliance with the HKD-RTE meals provided in the HKD-RTE group was 55%. The HKD-RTE group experienced a greater percentage weight loss at 1 month (−4.8 ± 3.0% vs. −1.8 ± 6.2%), although this was not statistically significant. This trend continued up to 6 months, with the HKD-RTE group showing a greater percentage weight reduction (−8.6 ± 6.8% vs. −3.9 ± 8.6%; p = 0.092). At 6 months, the HKD-RTE group had a greater reduction in total cholesterol (−0.54 ± 0.76 mmol/L vs. −0.05 ± 0.56 mmol/L; p = 0.283) and LDL-C (−0.43 ± 0.67 mmol/L vs. −0.03 ± 0.52 mmol/L; p = 0.374) compared to the HKD group. Additionally, the HKD-RTE group exhibited greater reductions in systolic blood pressure (−8.3 ± 9.7 mmHg vs. −5.3 ± 11.0 mmHg), diastolic blood pressure (−7.7 ± 8.8 mmHg vs. −2.0 ± 7.0 mmHg), and HbA1c (−0.3 ± 0.5% vs. −0.1 ± 0.4%) than the HKD group (not statistically significant for any). Conclusions: Both HKD-RTE and HKD led to weight loss and improved metabolic profiles. The HKD-RTE group tended to show more favorable outcomes. Short-term HKD-RTE meal provision may enhance initial weight loss, with sustained long-term effects. Full article

Football performance results from the dynamic interaction between physical, tactical, technical, and psychological dimensions—each of which also influences player well-being, recovery, and readiness. However, integrated monitoring approaches remain scarce, particularly in youth and sub-elite contexts. This systematic review screened 341 records from PubMed, Scopus, and Web of Science, with 46 studies meeting the inclusion criteria (n = 1763 players; age range: 13.2–28.7 years). Physical external load was reported in 44 studies using GPS-derived metrics such as total distance and high-speed running, while internal load was examined in 36 studies through session-RPE (rate of perceived exertion × duration), heart rate zones, training impulse (TRIMP), and Player Load (PL). A total of 22 studies included well-being indicators capturing fatigue, sleep quality, stress levels, and muscle soreness, through tools such as the Hooper Index (HI), the Total Quality Recovery (TQR) scale, and various Likert-type or composite wellness scores. Tactical behaviours (n = 15) were derived from positional tracking systems, while technical performance (n = 7) was assessed using metrics like pass accuracy and expected goals, typically obtained from Wyscout^® or TRACAB^® (a multi-camera optical tracking system). Only five studies employed multivariate models to examine interactions between performance domains or to predict well-being outcomes. Most remained observational, relying on descriptive analyses and examining each domain in isolation. These findings reveal a fragmented approach to player monitoring and a lack of conceptual integration between physical, psychological, tactical, and technical indicators. Future research should prioritise multidimensional, standardised monitoring frameworks that combine contextual, psychophysiological, and performance data to improve applied decision-making and support player health, particularly in sub-elite and youth populations. Full article

Background: Brazilian Jiu-Jitsu (BJJ) is a physically demanding sport associated with a notable risk of musculoskeletal injuries. Understanding injury patterns, rehabilitation approaches, and psychological readiness to return to sport (RTS) is essential for prevention and management strategies. This study aimed to investigate injury characteristics among Italian BJJ athletes, assess their rehabilitation processes and psychological recovery, and identify key risk factors such as belt level, body mass index (BMI), and training load. Methods: A cross-sectional survey was conducted among members of the Italian BJJ community, including amateur and competitive athletes. A total of 360 participants completed a 36-item online questionnaire. Data collected included injury history, rehabilitation strategies, RTS timelines, and responses to the Injury-Psychological Readiness to Return to Sport (I-PRRS) scale. A Random Forest machine learning algorithm was used to identify and rank potential injury risk factors. Results: Of the 360 respondents, 331 (92%) reported at least one injury, predominantly occurring during training sessions. The knee was the most frequently injured joint, and the action “attempting to pass guard” was the most reported mechanism. Most athletes (65%) returned to training within one month. BMI and age emerged as the most significant predictors of injury risk. Psychological readiness scores indicated moderate confidence, with the lowest levels associated with playing without pain. Conclusions: Injuries in BJJ are common, particularly affecting the knee. Psychological readiness, especially confidence in training without pain, plays a critical role in RTS outcomes. Machine learning models may aid in identifying individual risk factors and guiding injury prevention strategies. Full article

Background: Selecting enterprise resource planning (ERP) systems for complex port environments is a significant challenge. This study addresses a key research gap by identifying and prioritizing the critical factors for ERP selection within the strategic context of United Arab Emirates (UAE) ports, which function as vital hubs in global trade. Methods: A hybrid methodology was employed, first using the Fuzzy Delphi Method (FDM) to validate thirteen challenges with five industry experts. Subsequently, the Relative Importance Index (RII) was used to rank these challenges based on survey data from 48 UAE port professionals. Results: The analysis revealed “Cybersecurity concerns” as the highest-ranked challenge (RII = 0.896), followed by “Engagement with external stakeholders” (RII = 0.842), and both “Process optimization” and “Technical capabilities” (RII = 0.808). Notably, factors traditionally seen as critical in other sectors, such as “Organizational readiness” (RII = 0.746), were ranked significantly lower. Conclusions: The findings indicate a strategic shift in ERP selection priorities toward digital resilience and external integration rather than internal organizational factors. This research provides a sector-specific decision-support framework and offers actionable insights for port authorities, vendors, and policymakers to enhance ERP implementation in the maritime industry. Full article