Search Results (9,240)

Cardiovascular diseases claim millions of lives each year, yet timely diagnosis remains a significant challenge due to the high number of patients and associated costs. Although various machine learning solutions have been proposed for this problem, most approaches rely on careful data preprocessing and feature engineering workflows that could benefit from more comprehensive documentation in research publications. To address this issue, this paper presents a machine learning framework for predicting heart attack risk online. Our systematic methodology integrates a unified pipeline featuring advanced data preprocessing, optimized feature selection, and an exhaustive hyperparameter search using cross-validated grid evaluation. We employ a metamodel ensemble strategy, testing and combining six traditional supervised models along with six stacking and voting ensemble models. The proposed system achieves accuracies ranging from 90.2% to 98.9% on three independent clinical datasets, outperforming current state-of-the-art methods. Additionally, it powers a deployable, lightweight web application for real-time decision support. By merging cutting-edge AI with clinical usability, this work offers a scalable solution for early intervention in cardiovascular care. Full article

The COVID-19 pandemic has placed a considerable psychological burden on healthcare workers, potentially leading to increased burnout and anxiety. This study aimed to evaluate burnout and anxiety levels among healthcare workers compared to non-healthcare professionals during the pandemic. We initially recruited 438 adults; 351 (217 HCWs and 134 non-HCWs) provided complete responses across all three survey waves and were analyzed. Burnout was assessed using the Maslach Burnout Inventory, and anxiety with the State–Trait Anxiety Inventory. Data were collected through an online self-administered survey at three different time points during the pandemic, and analyzed with non-parametric tests and effect sizes. Healthcare workers exhibited significantly higher levels of emotional exhaustion, depersonalization, overall burnout, and anxiety compared to non-healthcare workers across all three periods (p < 0.05). Of 438 consented individuals, 351 (80.1%) completed all waves, allowing within-population longitudinal comparisons. Within the healthcare worker group, women, individuals living alone, those working night shifts, and those considering a career change had notably higher burnout and anxiety scores. No significant differences were observed in personal accomplishment scores. Healthcare workers experienced greater psychological distress than non-healthcare workers during the COVID-19 pandemic. Identifying vulnerable subgroups and implementing supportive strategies are essential to protect the mental health and well-being of healthcare professionals during pandemics and similar crises. Full article

Background: The digital transition is reshaping healthcare systems through the adoption of telemedicine and electronic health records (EHRs). While these innovations enhance efficiency and access, their implementation unfolds within overstretched organizational settings characterized by workforce shortages, bureaucratic demands, and heightened psychosocial risks. Burnout, impostor syndrome, and the quality of organizational support have thus become pivotal constructs in understanding healthcare professionals’ digital preparedness. Methods: A cross-sectional online survey was conducted among 111 professionals employed at two San Donato Group facilities in Bologna, Italy. The battery included socio-demographic and occupational data, perceptions of digitalization, and validated instruments: the Maslach Burnout Inventory (MBI), the Clance Impostor Phenomenon Scale (CIPS), and the Work Organization Assessment Questionnaire (WOAQ). Descriptive analyses were complemented by Classification and Regression Trees (CART) to identify predictors of perceived digital preparedness. Results: Most respondents (88%) acknowledged the relevance of digitalization, yet 18% felt unprepared, especially women and administrative staff. Burnout levels were high, with 51% reporting emotional exhaustion, most notably among nurses and female participants. Impostor syndrome affected 43% of the sample, with nurses exhibiting the highest prevalence. CART analysis identified emotional exhaustion, impostor syndrome, and age as principal discriminators of digital preparedness. Conclusions: Our findings highlight the role of emotional exhaustion, impostor syndrome, and age in shaping perceived digital preparedness, underscoring the need for tailored training and supportive practices to ensure a sustainable digital transition. Full article

Intestinal bacterial dysbiosis develops in a number of immune-mediated disorders. Fecal microbiota transfer (FMT) is considered a potentially efficient tool for restoration of the patient’s gut microbiota. The aim of our study was to trace the time course of dominant bacterial populations and some Enterobacteria phages in patients with GVHD and Crohn’s disease after FMT procedure. Patients and methods: We observed 12 patients with intestinal graft-versus-host disease (GVHD), and 15 persons with Crohn’s disease after massive anti-infectious treatment. FMT was performed by a standard protocol using oral capsules administered for 2 days. Fecal bacteriome was assessed by 16S rRNA sequencing. Viral sequences were identified by NGS with a customized primer set. Plasma citrulline levels were measured in order to assess enterocyte damage in the patients. Results: Complete clinical response to FMT was observed in 5 of 12 GVHD patients and 10 of 15 Crohn’s disease cases. Before FMT, most anaerobic Bacillota were exhausted in both Crohn’s disease patients and GVHD. Following FMT, Akkermansia ratios tended to decrease within 30 days in Crohn’s disease, along with higher Faecalibacteria, Romboutsia, and Dialister ratios than in GVHD, thus suggesting lesser damage to anaerobic microbiota in Crohn’s disease. Increased contents of facultative anaerobes (Enterococcus and E. coli) was detected in GVHD patients after FMT. Fecal virome changes in Crohn’s disease after FMT included early transient decrease in Caudoviricetes with a rise in Lederbergvirus and Eganvirus ratios at later terms. In GVHD patients, reverse correlations were revealed between E. coli and E. coli-hosted Eganvirus species. Intestinal damage assessed by low plasma citrulline levels was associated with fecal Klebsiella expansion, being more pronounced in GVHD than in Crohn’s disease. Clinical response to FMT in GVHD patients correlated with increased plasma citrulline and lower Eganvirus abundance. Future studies will concern specific relations between fecal bacteriome and virome reconstitution following FMT in gut GVHD and other immune-mediated intestinal disorders. Full article

This study systematically investigates the variation in the ceiling flame tilt angle in an immersed tube tunnel under the combined effect of longitudinal ventilation and sidewall smoke extraction. The experimental program considers different longitudinal velocities, various sidewall smoke exhaust rates and multiple relative distances between the fire source and the sidewall exhaust outlet, aiming to comprehensively reveal the flame tilt angle under multi-factor coupling conditions. Experiments were carried out in a reduced-scale tunnel model (6.64 m long, 0.96 m wide and 0.5 m high). A porous gas burner supplied a steady heat release, with its distance from the sidewall exhaust outlet systematically varied. Results indicate that the flame tilt angle decreases as the distance between the fire source and the sidewall exhaust outlet increases. A theoretical model was developed to predict the flame tilt angle by incorporating both the sidewall smoke exhaust rate and the relative fire source–exhaust distance. The model accounts for mass loss due to smoke extraction, estimated from the local longitudinal velocity distribution. Predictions from the proposed model agree well with the experimental data. Full article

This study investigates T cell subsets in pericardial fluid samples obtained from heart transplantation donors, heart transplantation recipients, and coronary artery bypass graft patients. Using flow cytometry, we characterized regulatory T cells (Tregs), tissue-resident memory T cells (Trm), and exhausted T cells based on specific markers. Our results showed significant alterations in the CD4⁺ and CD8⁺ T cell subsets, migration (CXCR3, CCR5), and exhaustion markers (PD-1, TIM3) across the groups. Notably, Tregs and Trm cells were enriched in recipients, while markers of T cell exhaustion showed a complex regulation. These findings provide novel insights into the local immune regulation in cardiac disease and transplantation. Full article

With the increasing intelligence of modern air-conditioning systems, the difficulty of acquiring data from air-conditioning systems has been significantly reduced. However, analyzing the massive amounts of data collected and obtaining more valuable information still remains challenging, especially considering the internal relationships behind the data. The purpose of this study was to conduct operational experiments on VRF systems under different indoor set temperatures, indoor set air speeds, and terminal load rates. Then, the patterns of various operating parameters and energy consumption of VRF systems during winter operation were analyzed based on unsupervised methods. Three machine learning methods were primarily employed in this study, including correlation analysis, data regression analysis, and association rule analysis. Finally, a regression model was constructed for energy consumption based on eight typical characteristic parameters. The experimental results showed that the system was stable to a certain degree at different wind speeds. Among the characteristic parameters, fixed frequency 1 exhaust temperature, compressor frequency, and other parameters have a significant positive effect on energy consumption, while fixed frequency 1 shell top oil temperature, inlet and outlet pipe temperature difference, and other parameters have a negative effect. The research results provide a reference for air conditioning system data mining and building sustainability. Full article

This study presents a comparative investigation of combustion and emission characteristics in a two-stroke MAN 5S35ME-B9.5 marine diesel engine equipped with a Controllable Pitch Propeller and an Exhaust Gas Recirculation system. Experimental data were obtained from both factory shop tests conducted under the IMO NOx Technical Code 2008 E2 cycle and sea trials performed onboard the T/S Baek-Kyung. Engine performance was evaluated under Tier II-FB, ecoEGR, and Tier III modes, focusing on specific fuel oil consumption, peak cylinder pressure, exhaust gas temperature, and regulated emissions. Results indicate that Tier III achieved the greatest NOx abatement, reducing emissions by up to 76.4% (1464 to 346 ppm), but with penalties of 16.8% higher SFOC and 45.2% higher CO₂ concentration. EcoEGR provided a more favorable compromise, reducing NOx by 52.3% while limiting SFOC increases to ≤15.4% and CO₂ increases to ≤30.9%. Strong correlations were observed between NOx, Pmax, and exhaust gas temperature, reaffirming fundamental trade-offs, while O₂ and CO correlations showed greater variability under sea operation. Despite operational scatter, sea trial results reproduced the key patterns observed in shop tests, confirming robustness across conditions. Overall, this correlation-based analysis provides quantified evidence of performance–emission trade-offs and offers a practical foundation for optimizing CPP-equipped two-stroke engines under varying EGR strategies. Full article

The dairy sector produces considerable amounts of nutrient-rich effluents, which are frequently undervalued as simple by-products or waste. In particular, Second Cheese Whey (SCW), also known as scotta, exhausted whey, or deproteinized whey, represents the liquid fraction from ricotta cheese production. Despite its abundance and high organic and saline content, SCW is often improperly discharged into terrestrial and aquatic ecosystems, causing both environmental impact and resource waste. The available purification methods are expensive for dairy companies, and, at best, SCW is reused as feed or fertilizer. In recent years, increasing awareness of sustainability and circular economy principles has increased interest in the valorization of SCW. Biological treatment of SCW using microalgae represents an attractive strategy, as it simultaneously reduces the organic load and converts waste into algal biomass. This biomass can be further valorized as a source of proteins, pigments, and bioactive compounds with industrial relevance, supporting applications in food, nutraceuticals, biofuels, and cosmetics. This review, starting from analyzing the characteristics, production volumes, and environmental issues associated with SCW, focused on the potential of microalgae application for their valorization. In addition, the broader regulatory and sustainability aspects related to biomass utilization and treated SCW are considered, highlighting both the promises and limitations of microalgae-based strategies by integrating technological prospects with policy considerations. Full article

The paper presents a comprehensive evaluation of certain main parameters and the performance of microjet series models from the same engine manufacturer, AMT Netherlands, under various operating regimes. The study was performed through a percentage-based analysis of a series of actual values extracted from a set of charts, from which a specific database was created. The database comprised data sourced from official specification sheets issued by the manufacturer. The studied engines shared the same technical turbomachinery design, comprising a single shaft, one centrifugal compressor rotor, one axial turbine rotor stage, and a convergent jet nozzle, but differed in thrust class, ranging from 167 to 1569 N. Parameter and performance ratios were calculated to analyze the variation patterns within each engine and across different engines. The study refers to the variation analysis of thrust, fuel flow, exhaust gas temperature, and specific fuel consumption relative to engine speed, from idle to maximum regime. It presents the actual percentage values alongside polynomial functions that characterize the variations in engine parameters through which the analysis can be conducted. Full article

Background: Combined cognitive and physical training develops resilience to mental fatigue, reduces perceived effort, and improves endurance exercise performance when compared to physical training and no training. The isolated contribution of cognitive training toward endurance performance has yet to be determined. Accordingly, we examined the effects of separate cognitive training on endurance exercise performance. Method: Two studies employed a pre-test/training/post-test design, with participants randomly assigned to cognitive training or control groups. At pre-test and post-test, participants completed a rhythmic handgrip task (Study 1) or a graded exercise test on a cycle ergometer (Study 2). In Study 1, the cognitive training group completed 20 sessions (four 20 min sessions per week for five weeks) of cognitive training (incongruent Stroop and 2-back tasks), whereas the control group completed no training. In Study 2, the cognitive training group completed nine sessions (three 10 min sessions per week for three weeks) of cognitive training (incongruent Stroop, stop-signal and typing inhibition tasks), whereas the control group completed nine sessions of sham training (congruent Stroop, sham stop-signal and sham typing inhibition tasks). Endurance exercise performance was measured as force production (Study 1) and time to exhaustion (Study 2). Heart rate, exertion and fatigue were also measured. Results: Endurance performance, indexed by force production (Study 1) and time to exhaustion (Study 2), did not change from pre-test to post-test and did not differ between cognitive training and control groups. Similarly, ratings of perceived exertion and heart rate during the exercise tasks did not differ between cognitive training and control groups (Studies 1 and 2). Conclusions: Since separate cognitive training did not improve exercise endurance performance, combined training should be used to create a synergistic training stimulus for brain adaptation and performance enhancement. Full article

The article presents a method for selecting spray coating systems for furnace walls and heat exchangers, aimed at protecting them and intensifying heat exchange processes. Calculations were made of the effect of the mutual emissivity coefficient between the heating medium (exhaust gases) and the surface of the exchanger—both uncoated and coated—on the heat flux value. Selected coating systems were applied in laboratory conditions by spraying them onto the boiler surfaces and then measuring their heat exchange efficiency with the cooling medium (water) flowing through the piping system. The results of the laboratory tests were verified under industrial conditions in metallurgical installations, confirming the accuracy of the calculations and the validity of using spray coatings to increase thermal efficiency. The use of appropriately selected coating systems increases heat absorption, extends the service life of exchangers, reduces the risk of cooling system failure, and lowers the cost of heating equipment repairs. Full article

Diesel engines power much of the heavy-duty equipment used in underground mines, where exhaust emissions pose acute environmental and occupational health challenges. However, predicting the amount of air required to dilute these emissions is difficult because exhaust mass flow and pollutant concentrations vary nonlinearly with multiple operating parameters. We apply deep learning to predict the total exhaust mass flow and carbon monoxide (CO) concentration of a six-cylinder gas–diesel (dual-fuel) turbocharged KAMAZ 910.12-450 engine under controlled operating conditions. We trained artificial neural networks on the preprocessed experimental dataset to capture nonlinear relationships between engine inputs and exhaust responses. Model interpretation with Shapley additive explanations (SHAP) identifies torque, speed, and boost pressure as dominant drivers of exhaust mass flow, and catalyst pressure, EGR rate, and boost pressure as primary contributors to CO concentration. In addition, symbolic regression yields an interpretable analytical expression for exhaust mass flow, facilitating interpretation and potential integration into control. The results indicate that deep learning enables accurate and interpretable prediction of key exhaust parameters in dual-fuel engines, supporting emission assessment and mitigation strategies relevant to underground mining operations. These findings support future integration with ventilation models and real-time monitoring frameworks. Full article

Selecting an appropriate Multi-Criteria Decision-Making (MCDM) algorithm for optimizing marine diesel engine operation presents a complex challenge due to the diversity in mathematical formulations, normalization schemes, and trade-off resolutions across methods. This study systematically evaluates fourteen MCDM algorithms, which are grouped into five primary methodological categories: Scoring-Based, Distance-Based, Pairwise Comparison, Outranking, and Hybrid/Intelligent System-Based methods. The goal is to identify the most suitable algorithm for real-time performance optimization of two stroke marine diesel engines. Using Diesel-RK software, calibrated for marine diesel applications, simulations were performed on a variant of the MAN-B&W-S60-MC-C8-8 engine. A refined five-dimensional parameter space was constructed by systematically varying five key control variables: Start of Injection (SOI), Dwell Time, Fuel Mass Fraction, Fuel Rail Pressure, and Exhaust Valve Timing. A subset of 4454 high-potential alternatives was systematically evaluated according to three equally important criteria: Specific Fuel Consumption (SFC), Nitrogen Oxides (NO_x), and Particulate Matter (PM). The MCDM algorithms were evaluated based on ranking consistency and stability. Among them, Proximity Indexed Value (PIV), Integrated Simple Weighted Sum Product (WISP), and TriMetric Fusion (TMF) emerged as the most stable and consistently aligned with the overall consensus. These methods reliably identified optimal engine control strategies with minimal sensitivity to normalization, making them the most suitable candidates for integration into automated marine engine decision-support systems. The results underscore the importance of algorithm selection and provide a rigorous basis for establishing MCDM in emission-constrained maritime environments. This study is the first comprehensive, simulation-based evaluation of fourteen MCDM algorithms applied specifically to the optimization of two stroke marine diesel engines using Diesel-RK software. Full article

Acute myeloid leukemia is characterized by the presence of malignant cells and their uncontrolled growth in bone marrow. Recent studies have been focused on the ability of curcumin, a polyphenol derived from the Curcuma longa plant. The role of curcumin is currently under investigation, due to its antitumor properties and action on several pathways, including Nuclear Factor kappa-light-chain-enhancer of activated B cells, Signal Transducer and Activator of Transcription 3, Phosphatidylinositol 3-kinase/protein kinase B, and mitogen-activated protein kinase. The aim of this review is to demonstrate the possible anti-leukemic effect of curcumin, thus its ability to induce apoptosis, inhibit cell proliferation, and modulate angiogenesis. Nowadays, although multiple synergistic effects have been observed and curcumin’s efficacy has been demonstrated through several in vivo and in vitro studies, further broad and exhaustive scientific research is needed to confirm the considerable results. In fact, the low bioavailability of curcumin has limited its clinical applications, a challenge that is currently being addressed through the development of nanoformulations to enhance its stability and absorption within the body. In conclusion, curcumin exhibits antitumor properties with a favorable profile, suggesting its potential as a supportive adjunct in the treatment of patients with acute myeloid leukemia. Full article