Search Results (12,329)

This study suggests a hybrid approach that combines improved feature selection and intelligent diagnosis to increase the operational safety and intelligent diagnosis capabilities of hydropower units. In order to handle the vibration data, complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is used initially. A novel comprehensive index is constructed by combining the Pearson correlation coefficient, mutual information (MI), and Kullback–Leibler divergence (KLD) to select intrinsic mode functions (IMFs). Next, feature extraction is performed on the selected IMFs using Refined Composite Multiscale Fluctuation Dispersion Entropy (RCMFDE). Then, time and frequency domain features are screened by calculating dispersion and combined with IMF features to build a hybrid feature vector. The vector is then fed into a CNN-GRU-Attention model for intelligent diagnosis. The improved slime mold algorithm (ISMA) is employed for the first time to optimize the hyperparameters of the CNN-GRU-Attention model. The experimental results show that the classification accuracy reaches 96.79% for raw signals and 93.33% for noisy signals, significantly outperforming traditional methods. This study incorporates entropy-based feature extraction, combines hyperparameter optimization with the classification model, and addresses the limitations of single feature selection methods for non-stationary and nonlinear signals. The proposed approach provides an excellent solution for intelligent optimized diagnosis of hydropower units. Full article

The development of slicing equipment for Fritillariae Thunbergii Bulbus (FTB) has been constrained by the absence of precise and reliable simulation model parameters, which has hindered the optimization of structural design through simulation techniques. Taking FTB as the research object, this study aims to resolve this issue by conducting the calibration and experimental validation of the discrete element parameters for FTB. Both intrinsic and contact parameters were obtained through physical experiments, on the basis of which a discrete element model for FTB was established by using the Hertz–Mindlin with bonding model. To validate the calibrated bonding parameters of this model, the maximum shear force was selected as the evaluation index. Significant influencing factors were identified and analyzed through a single-factor test, a two-level factorial test, and the steepest ascent method. Response surface methodology was then applied for experimental design and parameter optimization. Finally, shear and compression tests were conducted to verify the accuracy of calibrated parameters. The results show that the mechanical properties of FTB are significantly affected by the normal stiffness per unit area, the tangential stiffness per unit area, and the bonding radius, with optimal values of 1.438 × 10⁸ N·m⁻³, 0.447 × 10⁸ N·m⁻³, and 1.362 mm, respectively. The relative errors in the shear and compression tests were all within 5.18%. The maximum error between the simulated and measured maximum shear force under three different types of blades was less than 5.11%. The percentages of the average shear force of the oblique blade were reduced by 52.23% and 29.55% compared with the flat and arc blades, respectively, while the force variation trends for FTB remained consistent. These findings confirm the reliability of the simulation parameters and establish a theoretical basis for optimizing the structural design of slicing equipment for FTB. Full article

Background/Objectives: Neck pain is defined as an unpleasant sensory and emotional experience associated with actual or potential tissue damage, affecting the cervical region. It represents one of the leading causes of disability, with a prevalence of 30%. Transcranial direct current stimulation (tDCS) is a non-invasive electrotherapy technique that enables direct modulation of cortical excitability. It involves the application of a low-intensity electrical current to the scalp, targeting the central nervous system. The aim of this study was to analyze the effects of tDCS on functionality, pain, mobility, and pressure pain threshold in patients with chronic nonspecific neck pain. Methods: Thirty participants (18–60 years) were selected to receive ten treatment sessions over a four-week period using tDCS (CG = 15) or transcutaneous electrical nerve stimulation (TENS) (CG = 15), with the following various related variables evaluated: functionality (Neck Disability Index), pain intensity (NPRS), cervical range of motion (ROM), and pressure pain threshold (PPT). Assessments were conducted at baseline, post-treatment, one month, and three months after the intervention. Results: The within-group analysis revealed statistically significant improvements for both groups at post-treatment, one-month follow-up, and three-month follow-up. Conclusions: The comparison between groups shows favorable changes in the tDCS group for PPT measurements. Full article

Meat quality is influenced by factors such as age, breed, slaughter weight, and nutrition. This study investigated the growth performance, slaughter performance, and meat quality of ducks across different breeds and ages. Results indicated that at the same age, significant differences in body weight were observed among breeds (p < 0.05), with the weight ranking in descending order as follows: Cherry Valley ducks (C) > Wuqin 10 meat ducks (W) > Mianyang Partridge ducks (M) > Liancheng White ducks (L). A comparison of the same breed across different ages revealed that the pectoral muscle ratio tended to increase with age, whereas the leg muscle ratio showed the opposite trend; however, total meat production gradually rose. At all three growth stages, C ducks exhibited higher body weight and meat yield than the other breeds. W ducks demonstrated excellent meat quality traits and appropriate meat production, with indices such as shear force, water-holding capacity, and fat content all higher than those of the other breeds. L ducks and M ducks had relatively lower body weight and meat production compared to the other breeds, yet their shear force and water-holding capacity were superior to those of C ducks. The analysis of meat quality at different times showed that across all breeds, shear force, meat color, muscle fiber diameter, crude protein content, and fat content increased with age, while drip loss rate and muscle fiber density decreased. A comprehensive multi-index evaluation model for duck meat quality under different breeds was established, along with a four-factor principal component model (Z1, Z2, Z3, Z4). Using the comprehensive ranking equation K, the meat quality performance of different breeds at various ages, in descending order, was as follows: 63-day-old W > 90-day-old M > 63-day-old C > 90-day-old L > 63-day-old M > 90-day-old C > 63-day-old L > 90-day-old W > 42-day-old C > 42-day-old W. This study not only provides a theoretical basis for evaluating meat quality traits in different duck breeds but also offers insights for breed selection and age-related quality optimization. Full article

Introduction: Assessing the quality of patient care within healthcare systems remains a multifaceted challenge due to varying definitions of “quality” and the complexity of care delivery structures worldwide. Patient-centeredness, institutional responsiveness, and contextual adaptability are increasingly recognized as core pillars in quality assessment. Objective: This narrative literature review aims to explore conceptual models and practical frameworks for evaluating healthcare quality, emphasizing tools that integrate technical, functional, and emotional dimensions and proposing a comprehensive model adaptable to diverse health system contexts. Methodology: A systematic literature search was conducted in the PubMed, Scopus, and Cochrane Library databases, covering the years 2000 to 2024. Studies were selected based on relevance to quality assessment models, patient satisfaction, accreditation, and strategic improvement methodologies. The review followed a thematic synthesis approach, integrating structural, process-based, and outcome-driven perspectives. Results: Core frameworks such as Donabedian’s model and balancing measures were reviewed alongside evaluation tools like the Dutch Consumer Quality Index, SERVQUAL, and Importance–Performance Analysis (IPA). These models revealed significant gaps between patient expectations and actual service delivery, especially in functional and emotional quality dimensions. This review also identified limitations related to contextual generalizability and bias. A novel integrative model is proposed, emphasizing the dynamic interaction between institutional structure, clinical processes, and patient experience. Conclusions: High-quality healthcare demands a multidimensional approach. Integrating conceptual frameworks with context-sensitive strategies enables healthcare systems to align technical performance with patient-centered outcomes. The proposed model offers a foundation for future empirical validation, particularly in resource-limited or hybrid settings. Full article

Background/Objectives: Pressure injuries (PIs), a recognized indicator of care quality, have a higher incidence in intensive care units (ICUs). Our objective was to assess whether critically ill patients identified as “unprotected” (COMHON ≥ 11) developed pressure injuries despite additional preventive measures. Methods: A historical cohort study of an adult ICU was carried out. Of the 811 patients admitted in 2022, 400 were selected. All of them were subjected to the ICU’s PI Prevention Protocol, and those with a moving average of the COMHON Index ≥ 11 were given two additional measures: a multilayer dressing on the sacrum, and anti-equinus and heel-pressure-relieving boots. Results: A total of 36 patients presented with PIs (cumulative incidence of 9%). Significant differences were observed in their mean length of stay and in their disease severity score (APACHE-II). Most of the PIs were located on the sacrum, followed by the heel. Prior to the appearance of the PIs, a sacral dressing was applied to 100% of the patients, while anti-equinus and heel-pressure-relieving boots were only applied to 58.3%. Of the 36 patients with PIs, 52.8% had a PI on the sacrum and 22.2% on the heel. Conclusions: Focusing only on those who presented with PIs, we observed that the considered measures were not effective for preventing PIs in all the patients. Not all PIs are preventable, and individual risk factors should be considered. In the future, we will analyze the individual characteristics of these patients and verify whether the Prevention Protocol was followed, in order to determine how they could have been prevented or whether they were so-called unavoidable PIs. Full article

The rising incidence of microplastics (MPs) is a possible health risk to humans. The present study aims to analyze the presence of MPs in intravenous (IV) infusions and compare MP concentrations from multiple brands. The IV solutions of 29 medical devices (IV-MDs) from seven brands commercialized in Ecuador, Spain, and Italy have been selected under specific consideration to carry out the study. The detection of MPs has been quite obvious in almost all of the samples from brands in the mentioned countries. MP concentrations ranged from 9 to 20 MPs/L in glass containers to 166–299 MPs/L in plastic bags, with the majority of fragments (63%) on fibres (37%) and more than 60% of particles less than 100 µm. Nine different types of MPs were identified in this study. High clinical risk was indicated by markings with >200 MPs/L. Nevertheless, the medium polymeric danger index (PHI) was 1.7. According to these outcomes, IV infusion is a direct exposure to MPs that may have harmful medical repercussions. It is imperative that MPs’ limitations be included in pharmacopoeic monographs and in vivo toxicological and epidemiological studies. The present study aims to analyze the presence of MPs in IV-MDs and compare MP concentrations from multiple IV-MD brands. Full article

Non-invasive ventilation (NIV) is a cornerstone in the management of acute and chronic respiratory failure, offering critical support without the risks of intubation. However, successful weaning from NIV remains a complex, high-stakes process. Poorly timed or improperly executed weaning significantly increases morbidity and mortality, yet current clinical practice often relies on subjective judgment rather than evidence-based protocols. This manuscript reviews the current landscape of NIV weaning, emphasizing structured approaches, objective monitoring, and predictors of weaning success or failure. It examines guideline-based indications, monitoring strategies, and various weaning techniques—gradual and abrupt—with evidence of their efficacy across different patient populations. Predictive tools such as the Rapid Shallow Breathing Index, Lung Ultrasound Score, Diaphragm Thickening Fraction, ROX index, and HACOR score are analyzed for their diagnostic value. Additionally, this review underscores the importance of care setting—ICU, step-down unit, or general ward—and how it influences outcomes. Finally, it highlights critical gaps in research, especially around weaning in non-ICU environments. By consolidating current evidence and identifying predictors and pitfalls, this article aims to support clinicians in making safe, timely, and patient-specific NIV weaning decisions. In the current literature, there are gaps regarding patient selection and lack of universal protocolization for initiation and de-escalation of NIV as the data has been scattered. This review aims to consolidate the relevant information to be utilized by clinicians throughout multiple levels of care in all hospital systems. Full article

Background/Objectives: The assessment of platelet kinetics (APK) is recommended for patients with chronic idiopathic thrombocytopenic purpura (chITP). The aim of this study was to examine the importance of APK as a prognostic instrument in the selection of therapy in children with chITP. Methods: Retrospective, observational research, which included chITP children who were treated and subjected to APK in Serbia for 25 years (total number was 152). Results: In the acute phase of the disease, 15% of patients had life-threatening bleeding, 15% were asymptomatic, and there were no cases of fatal bleeding. Mean platelet life was 0.89 ± 0.47 days. A total of 45% of patients had normal platelet production, and 35% had very low production. Among the patients, 55% exhibited splenic platelet sequestration, 35% had mixed sequestration, and 10% showed hepatic platelet sequestration. Platelet lifespan and production indices were less reliable parameters, due to numerous contradictory results, especially when compared with the location of platelet sequestration. Distribution of bleeding and therapy-resistant patients was dominant with mixed sequestration. Good therapy responders had dominant splenic sequestration. In the chronic phase of the disease, initial therapy was sufficient for 40–45% of patients, while another 25% required second-line therapy, regardless of platelet sequestration location. A total of 25% percent of patients had undergone splenectomy, and all of them were in stable remission. The remaining 10%, which represented the most severe cases, required all available therapies, had equally mixed and liver sequestration, and splenectomy showed no effect. Conclusions: APK may be a determining factor for the selection of splenectomy as a therapeutic option in case of predominantly splenic sequestration. Although the platelet production index has been explored in several studies, its clinical relevance remains controversial. In our findings, it did not contribute to therapeutic decision-making and may even lead to misinterpretation. The factors distinguishing the minority of bleeding and therapy-resistant patients with similar laboratory profiles remain unclear. Full article

Landslide susceptibility assessment (LSA) plays a crucial role in disaster prevention and mitigation. Traditional random selection of non-landslide samples (labeled as 0) suffers from poor representativeness and high randomness, which may include potential landslide areas and affect the accuracy of LSA. To address this issue, this study proposes a novel Landslide Susceptibility Index–based Semi-supervised Fuzzy C-Means (LSI-SFCM) sampling strategy combining membership degrees. It utilizes landslide and unlabeled samples to map landslide membership degree via Semi-supervised Fuzzy C-Means (SFCM). Non-landslide samples are selected from low-membership regions and assigned membership values as labels. This study developed three models for LSA—Convolutional Neural Network (CNN), U-Net, and Support Vector Machine (SVM), and compared three negative sample sampling strategies: Random Sampling (RS), SFCM (samples labeled 0), and LSI-SFCM. The results demonstrate that the LSI-SFCM effectively enhances the representativeness and diversity of negative samples, improving the predictive performance and classification reliability. Deep learning models using LSI-SFCM performed with superior predictive capability. The CNN model achieved an area under the receiver operating characteristic curve (AUC) of 95.52% and a prediction rate curve value of 0.859. Furthermore, compared with the traditional unsupervised fuzzy C-means (FCM) clustering, SFCM produced a more reasonable distribution of landslide membership degrees, better reflecting the distinction between landslides and non-landslides. This approach enhances the reliability of LSA and provides a scientific basis for disaster prevention and mitigation authorities. Full article

Urban parks are an important component of public urban spaces, which directly impact the living experiences of residents and the urban image. High-quality urban parks are crucial for enhancing the well-being of residents. This study selected Fukuoka, Japan, as the study site. Five urban parks were chosen to evaluate landscape visual quality by using the Scenic Beauty Estimation (SBE) method. The Semantic Differential (SD) method was used to get sample subjective landscape features. Meanwhile, sample objective landscape features were obtained by using semantic segmentation techniques in deep learning and combined with spatial analysis to understand their distribution. A regression model was established, which used the SBE values as the dependent variable and subjective landscape features as the independent variables to analyze the relationship between urban park landscape visual quality and subjective landscape features. The regression analysis revealed that sense of layering, harmony, interestingness, sense of order, and vitality were the core factors influencing visual quality. All five features had a significant positive impact on landscape visual quality. The sense of order was the most influential factor, which would be the key to enhancing the landscape perception experience. Moreover, the XGBoost model and SHAP value from machine learning were used to reveal the nonlinear relationships and significant threshold effects between urban park visual quality and five objective landscape features: openness, greenness, enclosure, vegetation diversity, and Shannon–Wiener diversity index. This study showed that when openness exceeded 0.27, the positive effect was significant. The optimal threshold for the greenness was 0.38. Vegetation diversity and enclosure had to be below 0.82 and 0.58, respectively, to have a positive impact. Meanwhile, the positive influence of the Shannon–Wiener diversity index reached its maximum at a value of 1.37. This study not only establishes a systematic method for diagnosing landscape problems and evaluating landscape visual quality but also provides both theoretical support and practical guidance for urban park landscape optimization. Full article

Technology-based strategies for the prevention and management of suicidal behavior are widely referenced for identifying vulnerable groups and for supporting clinical reasoning, decision-making, and appropriate referrals. In this study, we estimated the interface and content validity evidence of an interactive mobile application developed for managing suicidal behavior. This methodological study employed psychometric parameters to evaluate the content and interface of the mobile application, following five action phases: analysis, design, development, implementation, and evaluation. A total of 27 healthcare professionals participated, selected by convenience sampling, all working within the Psychosocial Care Network across different regions of Brazil. Data were collected using an electronic form, the Delphi technique for evaluation rounds, and a Likert scale to achieve consensus. The validity analysis was based on a Content Validity Index (CVI) equal to or greater than 0.80. The results showed that GerenciaVida, a technology developed for healthcare workers—regardless of their level of care or professional category—can be used to screen for suicide risk in the general population and indicate preventive alternatives. The app demonstrated satisfactory indicators of content validity (0.974) and interface validity (0.963), reflecting clarity (0.925), objectivity (1.00), adequacy (0.925), coherence (0.962), accuracy (0.962), and clinical relevance (1.00). The development path of this mobile application provided scientific, technological, and operational support, establishing it as an innovative care tool. It consolidates valid evidence that supports the identification, risk classification, and prevention of suicidal behavior in various healthcare contexts. Full article

Drought stress has a significant impact on cotton growth, development, and productivity. This study conducted drought stress treatment and normal water treatment (control group) on 502 cotton accessions and analyzed data on eight phenotypic traits closely related to drought stress tolerance. The results showed that all indicators changed significantly under drought stress conditions compared to the control group, with varying degrees of response among different indicators. To comprehensively evaluate the drought resistance of cotton during the germination period, the values of drought resistance comprehensive evaluation (D-value), weight drought resistance coefficient (WDC-value), and comprehensive drought resistance coefficient (CDC-value) were calculated based on membership function analysis and principal component analysis. Cluster analysis based on the D-value divided the germplasm into five drought-resistant grades, followed by the selection of one extreme material, each from the strongly drought-resistant and strongly drought-sensitive groups. An evaluation model was established using stepwise regression analysis, including the following effective indicators: Relative Fresh Weight (RFW), Relative Hypocotyl Length (RHL), Relative Seeds Water Absorption Rate (RAR), Relative Germination Rate (RGR), Relative Germination Potential (RGP), and Relative Drought Tolerance Index (RDT). The validation of the D-value prediction model based on the Best Linear Unbiased Prediction (BLUP) showed that the results obtained from two independent biological replicates were highly consistent. The comprehensive evaluation system and screening indicators established in this study provide a reliable method for identifying drought tolerance during the germination period. Full article

Fungal infections are recognized as a global health issue, in particular considering the spread of different forms of resistance to the commonly used antifungal drugs and their involvement in the occurrence of co-infections in hospitalized and immunocompromised patients. In this paper, a small series of hybrid compounds were designed and synthesized by linking the privileged chromone and xanthone scaffolds, endowed with recognized antimicrobial potential, to the tert-butylbenzylamino portion of the antifungal drug butenafine, through selected linkers. The results showed for the xanthone-based compound 3 a promising activity towards C. auris, C. tropicalis, and C. neoformans, for which a high degree of resistance is commonly observed, together with a significant antibacterial potency towards Gram-positive bacteria, such as S. aureus. Considering that compound 3 displayed favorable selectivity and therapeutic indexes (9.1 and >16, respectively), it appeared as a valuable prototype, deserving further hit-to-lead optimization. Full article

South Korea is one of the world’s major centers for marine shellfish aquaculture. Since the industry’s rapid expansion began in the 1980s, concerns have grown regarding its environmental impacts on coastal marine ecosystems. Evaluating the benthic ecological quality status (EcoQs) of shellfish farms using benthic indices provides a scientific foundation for the sustainable management of aquaculture areas. In our study, five benthic indices (AZTI’s marine biotic index, BENTIX, benthic opportunistic polychaeta amphipoda index, benthic pollution index, and multivariate AMBI) and one composite index were selected to assess EcoQs of shellfish farms in Gangjin Bay, South Korea. Our results revealed significant differences in macrobenthic community structure and EcoQs between November and December in Gangjin Bay. Spearman correlation analysis and principal coordinates analysis (PCoA) demonstrated that the multivariate AMBI (M-AMBI) exhibited the best overall performance among indices. However, considering the ecological complexity, variability in farming practices, and site-specific conditions typical of shellfish aquaculture environments, the use of five benthic indices and a composite index is recommended to ensure a more comprehensive and robust evaluation of EcoQs in Korean shellfish farms. Full article