Search Results (127)

Background/Objectives: Total arch replacement (TAR) with frozen elephant trunk (FET) using the E-vita Open hybrid prosthesis represents a complex surgical intervention for extensive aortic pathologies in previously operated patients. The comparative safety profile between patients with previous acute Type A dissection repair versus other cardiac surgical histories remains unclear. This pilot study evaluated early and midterm outcomes to determine whether previous aortic dissection carries additional operative risk compared to other previous cardiac operations. Methods: This retrospective single-center pilot cohort study analyzed 27 patients who underwent TAR with E-vita Open hybrid prosthesis between January 2013 and June 2024. Patients were stratified into two groups: Group 1 comprised patients with previous acute Type A dissection repair (n = 15, 55.6%), and Group 2 included patients with other previous cardiac operations (n = 12, 44.4%). Primary endpoints were in-hospital mortality and survival at 1, 2, and 3 years. Secondary endpoints included major neurological complications, spinal cord injury, reoperation for bleeding, and freedom from aortic reinterventions. Results: Baseline characteristics demonstrated comparable risk profiles between groups, with similar EuroSCORE II values (median 4.55 [IQR 3.86–7.28] vs. 5.41 [IQR 3.93–6.74], p = 1.0). Despite Group 1 showing trends toward longer operative times (580.07 ± 126.84 vs. 481.25 ± 119.29 min, p = 0.053), major postoperative outcomes were statistically equivalent. In-hospital mortality was 6.7% in Group 1 versus 0% in Group 2 (p = 1.0). Stroke rates were comparable (20.0% vs. 25.0%, p = 1.0), as were paraplegia rates (13.3% vs. 8.3%, p = 1.0) and dialysis requirements (46.7% vs. 41.7%, p = 0.334). Survival rates at 1, 2, and 3 years were 80.0%, 66.7%, and 60.0% for Group 1 and 75.0%, 66.7%, and 50.0% for Group 2, respectively (all p > 0.05). Conclusions: This pilot study suggests preliminary evidence of comparable early and midterm outcomes between patients with previous Type A dissection repair and those with other previous cardiac operations when undergoing TAR with E-vita Open hybrid prosthesis at an experienced center. However, the small sample size limits definitive conclusions and highlights the need for larger multicenter studies to confirm these findings. Full article

Post-fire soil and vegetation changes can intensify erosion and sediment yield by altering the factors controlling the runoff–infiltration balance. Erosion barriers (EBs) are widely used in hydrological and forest restoration to mitigate erosion, reduce sediment transport, and promote vegetation recovery. However, precise spatial assessments of their effectiveness remain scarce, requiring validation through operational methodologies. This study evaluates the impact of EB on post-fire vegetation recovery at two temporal and spatial scales: (1) Remotely Piloted Aircraft System (RPAS) imagery, acquired at high spatial resolution but limited to a single acquisition date coinciding with the field flight. These data were captured using a MicaSense RedEdge-MX multispectral camera and an RGB optical sensor (SODA), from which NDVI and vegetation height were derived through aerial photogrammetry and digital surface models (DSMs). (2) Sentinel-2 satellite imagery, offering coarser spatial resolution but enabling multi-temporal analysis, through NDVI time series spanning four consecutive years. The study was conducted in the area of the Luna Fire (northern Spain), which burned in July 2015. A paired sampling design compared upstream and downstream areas of burned wood stacks and control sites using NDVI values and vegetation height. Results showed slightly higher NDVI values (0.45) upstream of the EB (p < 0.05), while vegetation height was, on average, ~8 cm lower than in control sites (p > 0.05). Sentinel-2 analysis revealed significant differences in NDVI distributions between treatments (p < 0.05), although mean values were similar (~0.32), both showing positive trends over four years. This study offers indirect insight into the functioning and effectiveness of EB in post-fire recovery. The findings highlight the need for continued monitoring of treated areas to better understand environmental responses over time and to inform more effective land management strategies. Full article

Background: General aviation pilots are, anecdotally, referred to as “weekend warriors” due to their flying infrequency. Considering that flight skills erode with irregular practice/reinforcement, we determined whether private pilots (PPLs) fly/train sufficiently to operate safely in the context of slow flight, a skill critical for safe operations and which rapidly atrophies with <~51 h flight time/8 months per prior research. Method: Slow-flight-related aviation accidents (2008–2019) were per the NTSB Access^R database, and fatal mishap rates were calculated using general aviation fleet times. Eight-month flight histories of airplanes in single PPL ownership were captured retrospectively using FlightAware^R. PPL survey responses were collected between January and March 2025. Statistical tests employed proportion/Independent-Samples Median Tests and a Poisson Distribution. Results: The slow-flight-related fatal accident rate (2017–2019) trended downwards (p = 0.077). In-flight tracking of 90 airplanes revealed an 8-month median flight time of 6 h, which is well below the aforementioned 51 h requisite for safe operations. Of the aircraft flown < 51 h, only 9% engaged in slow-flight practice. In the online survey, only the upper quartile of 126 PPLs achieved the aforementioned time requisite for preserving slow-flight skills, but nevertheless, 89% of respondents attested to being flight-proficient. Conclusions: Persistence in slow-flight-related fatal accidents likely partly reflects PPLs’ deficiency in in-flight time/slow-flight practice. Full article

Background/Objectives: Root canal therapy (RCT) aims to eliminate intracanal infection and promote periapical healing through mechanical instrumentation and chemical disinfection. Conventional irrigants, such as sodium hypochlorite (NaOCl), are effective but may exhibit limited penetration into anatomically complex root canal systems and carry the risks of cytotoxicity if extruded beyond the apical foramen or into surrounding periodontal tissues. In this pilot study, we evaluated the clinical effectiveness and safety of underwater discharge plasma (UDP) as a biocompatible alternative to NaOCl for root canal irrigation. Methods: A prospective, randomized clinical trial was conducted involving 30 patients who required root canal treatment. Patients were randomly allocated to the UDP (n = 15) or NaOCl (n = 15) group. All treatments were performed by a single operator following standardized protocols. Pain was assessed using the visual analog scale (VAS), and periapical healing was evaluated using the Periapical Index (PAI) at baseline, 2 months, and 4 months. Statistical analyses included the Friedman test, Mann–Whitney U test, and Fisher’s exact test. Interobserver agreement for radiographic readings was evaluated using quadratic-weighted Cohen’s kappa coefficient. Results: A total of 28 patients completed the study. VAS scores significantly decreased over time in both groups (p < 0.05), with no significant difference between the groups at any time point (p > 0.05). At 4 months, radiographic healing was observed in 71.4% and 92.9% of patients in the UDP and NaOCl groups, respectively (p > 0.05). PAI score changes and clinical success rates were comparable between groups. No adverse effects or thermal damage was reported when using UDP. Conclusions: UDP demonstrated short-term clinical efficacy and safety comparable to that of NaOCl. Thus, UDP may serve as a biocompatible alternative for root canal disinfection. Further large-scale and long-term studies are warranted to confirm its clinical utility. Full article

Background: Hepato-pancreato-biliary (HPB) surgery involves operations that depend heavily on precise imaging, careful planning, and intraoperative decision-making. The rapid emergence of artificial intelligence (AI) and digital tools has assisted in these domains. Methods: We performed a PRISMA-guided systematic review (searches through June 2025) of AI/digital technologies applied to HPB surgical care, including novel models such as machine learning, deep learning, radiomics, augmented/mixed reality, and computer vision. Our focus was for eligible studies to address imaging interpretation, preoperative planning, intraoperative guidance, or outcome prediction. Results: In total, 38 studies met inclusion criteria. Imaging models constructed with AI showed high diagnostic performance for lesion detection and classification (commonly AUC ~0.80–0.98). Moreover, risk models using machine learning frequently exceeded traditional scores for predicting postoperative complications (e.g., pancreatic fistula). AI-assisted three-dimensional visual reconstructions enhanced anatomical understanding for preoperative planning, while augmented and mixed-reality systems enabled real-time intraoperative navigation in pilot series. Computer-vision systems recognized critical intraoperative landmarks (e.g., critical view of safety) and detected hazards such as bleeding in near real time. Most of the studies included were retrospective, single-center, or feasibility designs, with limited external validation. Conclusions: The usage of AI and digital tools show promising results across the HPB pathway—from preoperative diagnostics to intraoperative safety and guidance. The evidence to date supports technical feasibility and suggests clinical benefit, but routine adoption and further conclusions should await prospective, multicenter validation and consistent reporting. With continued refinement, multidisciplinary collaboration, appropriate cost effectiveness, and attention to ethics and implementation, these technologies could improve the precision, safety, and outcomes of HPB surgery. Full article

Port seaside scheduling, involving berth allocation, quay crane, and tugboat scheduling, is central to intelligent port operations. This survey reviews and statistically analyzes 152 academic publications from 2000 to 2025 that focus on optimization techniques for port seaside scheduling. The reviewed methods span mathematical modeling and exact algorithms, heuristic and simulation-based approaches, and agent-based and learning-driven techniques. Findings show deterministic models remain mainstream (77% of studies), with uncertainty-aware models accounting for 23%. Heuristic and simulation approaches are most commonly used (60.5%), followed by exact algorithms (21.7%) and agent-based methods (12.5%). While berth and quay crane scheduling have historically been the primary focus, there is growing research interest in tugboat operations, pilot assignment, and vessel routing under navigational constraints. The review traces a clear evolution from static, single-resource optimization to dynamic, multi-resource coordination enabled by intelligent modeling. Finally, emerging trends such as the integration of large language models, green scheduling strategies, and human–machine collaboration are discussed, providing insights and directions for future research and practical implementations. Full article

Artificial intelligence (AI) is now the computational core of smart building automation, acting across the entire cyber–physical stack. This review surveys peer-reviewed work on the integration of AI with indoor environmental quality (IEQ) and energy performance, distinguishing itself by presenting a holistic synthesis of the complete technological evolution from IoT sensors to generative AI. We uniquely frame this progression within a human-centric architecture that integrates digital twins of both the building (DT-B) and its occupants (DT-H), providing a forward-looking perspective on occupant comfort and energy management. We find that deep reinforcement learning (DRL) agents, often developed within physics-calibrated digital twins, reduce annual HVAC demand by 10–35% while maintaining an operative temperature within ±0.5 °C and CO₂ below 800 ppm. These comfort and IAQ targets are consistent with ASHRAE Standard 55 (thermal environmental conditions) and ASHRAE Standard 62.1 (ventilation for acceptable indoor air quality); keeping the operative temperature within ±0.5 °C of the setpoint and indoor CO₂ near or below ~800 ppm reflects commonly adopted control tolerances and per-person outdoor air supply objectives. Regarding energy impacts, simulation studies commonly report higher double-digit reductions, whereas real building deployments typically achieve single- to low-double-digit savings; we therefore report simulation and field results separately. Supervised learners, including gradient boosting and various neural networks, achieve 87–97% accuracy for short-term load, comfort, and fault forecasting. Furthermore, unsupervised models successfully mine large-scale telemetry for anomalies and occupancy patterns, enabling adaptive ventilation that can cut sick building complaints by 40%. Despite these gains, deployment is hindered by fragmented datasets, interoperability issues between legacy BAS and modern IoT devices, and the computer energy and privacy–security costs of large models. The key research priorities include (1) open, high-fidelity IEQ benchmarks; (2) energy-aware, on-device learning architectures; (3) privacy-preserving federated frameworks; (4) hybrid, physics-informed models to win operator trust. Addressing these challenges is pivotal for scaling AI from isolated pilots to trustworthy, human-centric building ecosystems. Full article

Large language models (LLMs) now match or exceed human performance on many open-ended language tasks, yet they continue to produce fluent but incorrect statements, which is a failure mode widely referred to as hallucination. In low-stakes settings this may be tolerable; in regulated or safety-critical domains such as financial services, compliance review, and client decision support, it is not. Motivated by these realities, we develop an integrated mitigation framework that layers complementary controls rather than relying on any single technique. The framework combines structured prompt design, retrieval-augmented generation (RAG) with verifiable evidence sources, and targeted fine-tuning aligned with domain truth constraints. Our interest in this problem is practical. Individual mitigation techniques have matured quickly, yet teams deploying LLMs in production routinely report difficulty stitching them together in a coherent, maintainable pipeline. Decisions about when to ground a response in retrieved data, when to escalate uncertainty, how to capture provenance, and how to evaluate fidelity are often made ad hoc. Drawing on experience from financial technology implementations, where even rare hallucinations can carry material cost, regulatory exposure, or loss of customer trust, we aim to provide clearer guidance in the form of an easy-to-follow tutorial. This paper makes four contributions. First, we introduce a three-layer reference architecture that organizes mitigation activities across input governance, evidence-grounded generation, and post-response verification. Second, we describe a lightweight supervisory agent that manages uncertainty signals and triggers escalation (to humans, alternate models, or constrained workflows) when confidence falls below policy thresholds. Third, we analyze common but under-addressed security surfaces relevant to hallucination mitigation, including prompt injection, retrieval poisoning, and policy evasion attacks. Finally, we outline an implementation playbook for production deployment, including evaluation metrics, operational trade-offs, and lessons learned from early financial-services pilots. Full article

Flying cars are an important vehicle for future urban air mobility. Mainstream flying cars predominantly adopt the e-VTOL-like configuration. Unlike traditional aircraft, these flying cars must be operated by a single pilot. The corresponding hybrid ground-flight control scheme remains immature, with only a few reliability analyses focused on flight safety. Based on the single-pilot operation (SPO) concept, this paper designs a hybrid control scheme for e-VTOL-like flying cars and proposes a restricted driving mode for the the take-off and landing stages and an autonomous driving mode for the cruising stage, respectively. Taking the landing phase as an example, a fault mode analysis and fault tree analysis are conducted for the restricted driving mode, focusing on factors that are sensitive to flight safety. A fault probability analysis is performed of the landing control unit in the restricted driving mode. The calculated probability of the top event occurring is 1.98 × 10⁻⁸ per flight, which proves the feasibility of the design meets the safety requirements. This study provides a foundation for a safety assessment of driving modes in future designs of flying cars. Full article

Implementing energy-efficient solutions and developing energy complexes to decentralise power supply are key objectives for enhancing national security in Ukraine and Eastern Europe. This study compares the design, numerical, and experimental parameters of a channel-type jet-reaction turbine. A steam turbogenerator unit and a pilot industrial experimental test bench were developed to conduct full-scale testing of the unit. The article presents experimental data on the operation of a steam turbogenerator unit with a capacity of up to 475 kW, based on a channel-type steam jet-reaction turbine (JRT), and includes the validation of a computational fluid dynamics (CFD) model against the obtained results. For testing, a pilot-scale experimental facility and a turbogenerator were developed. The turbogenerator consists of two parallel-mounted JRTs operating on a single electric generator. During experimental testing, the system achieved an electrical output power of 404 kW at a turbine rotor speed of 25,000 rpm. Numerical modelling of the steam flow in the flow path of the jet-reaction turbine was performed using ANSYS CFX 25 R1 software. The geometry and mesh setup were described, boundary conditions were defined, and computational calculations were performed. The experimental results were compared with those obtained from numerical simulations. In particular, the discrepancy in the determination of the power and torque on the shaft of the jet-reaction turbine between the numerical and full-scale experimental results was 1.6%, and the discrepancy in determining the mass flow rate of steam at the turbine inlet was 1.34%. JRTs show strong potential for the development of energy-efficient, low-power turbogenerators. The research results confirm the feasibility of using such units for decentralised energy supply and recovering secondary energy resources. This contributes to improved energy security, reduces environmental impact, and supports sustainable development goals. Full article

The increasing prevalence of sedentary lifestyles poses significant global health challenges, including obesity, diabetes, musculoskeletal disorders, and cardiovascular issues. This paper presents the design and development of a universal smart chair system aimed at mitigating the adverse effects of prolonged sitting. The proposed solution integrates a pressure sensor, vibration motors, an LED strip, and Bluetooth Low-Energy (BLE) communication into a modular and adaptable design. Powered by an STM32WB55CGU6 microcontroller and a rechargeable lithium-ion battery system, the smart chair monitors sitting duration and the user’s posture, and provides alerts through tactile, visual, and auditory notifications. A complementary mobile application allows users to customize sitting time thresholds, monitor activity, and assess battery status. Designed for universal compatibility, the system can be adapted to various chair types. Technical and functional testing demonstrated reliable performance, with the chair operating for over eight workdays on a single charge. The smart chair offers an innovative, cost-effective approach to improving workplace ergonomics and health outcomes, with potential for further enhancements such as posture monitoring. A pilot study with 83 students at VILNIUS TECH showed that the smart chair detected correct posture with 94.78% accuracy, and 97.59% of users responded to alerts by adjusting their posture within an average of 3.27 s. Full article

The massive heavy oil reserves in the Athabasca region of northern Alberta depend on steam-assisted gravity drainage (SAGD) for their economic exploitation. Even though SAGD has been successful in highly viscous oil recovery, it is still a costly technology because of the large energy input requirement. Large water and natural gas quantities needed for steam generation imply sizable greenhouse gas (GHG) emissions and extensive post-production water treatment. Several methods to make SAGD more energy-efficient and environmentally sustainable have been attempted. Their main goal is to reduce steam consumption whilst maintaining favourable oil production rates and ultimate oil recovery. Oil saturation within the steam chamber plays a critical role in determining both the economic viability and resource efficiency of SAGD operations. However, accurately quantifying the residual oil saturation left behind by SAGD remains a challenge. In this experimental research, sand pack Expanding Solvent SAGD (ES-SAGD) coinjection experiments are reported in which Pentane -C₅H₁₂, and Hexane -C₆H₁₄ were utilised as an additive to steam to produce Long Lake bitumen. Each solvent is assessed at three different constant concentrations through time using experiments simulating SAGD to quantify their impact. The benefits of single-component solvent coinjection gradually diminish as the SAGD process approaches its later stages. ES-SAGD pentane coinjection offers a smaller improvement in recovery factor (RF) (4% approx.) compared to hexane (8% approx.). Between these two single-component solvents, 15 vol% hexane offered the fastest recovery. The obtained data in this research provided compelling evidence that the coinjection of solvent under carefully controlled operating conditions, reduced overall steam requirement, energy consumption, and residual oil saturation allowing proper adjustment of oil and water relative permeability curve endpoints for field pilot reservoir simulations. Full article

This study addresses rising sustainability demands in the agro-industry by examining how data-driven approaches can reduce inefficiencies, waste, and poor resource use in spinach production. It investigates the impact of Total Productive Maintenance (TPM), First-In–First-Out (FIFO), process standardization, and circular economy practices—enhanced through digital transformation—on operational efficiency in a Peruvian agro-industrial firm. An exploratory case study was conducted using pilot implementations, direct observation, and quantitative analysis. Statistical tools, including Holt–Winters forecasting, were applied to assess the effectiveness of the interventions. Digital technologies supported data collection, traceability, and decision-making. An exploratory case study was conducted using pilot implementations, direct observation, and quantitative analysis. The integration of digital tools with lean and circular practices supports sustainable agro-industrial supply chains, contributing to food security and socio-economic resilience. This research offers a holistic, data-driven framework that aligns operational excellence with sustainability and digital innovation. Findings are based on a single case, limiting their generalizability. Broader applications and long-term effects warrant further study. Practitioners should adopt system-thinking approaches integrating digital, lean, and circular strategies. Future research should explore scalability, cost-efficiency, and policy support mechanisms. Full article

Background/Objectives: Hepatocellular carcinoma (HCC) is a major cause of cancer-related mortality and often develops in the context of liver cirrhosis (LC). Its detection remains a clinical challenge, particularly with limited sensitivity of the current serum biomarkers and qualitative imaging tools. The aim of this pilot study is to evaluate the application of a combined model based on the use of Liver to Spleen Volume Ratio (LSVR), a score of regional liver remodeling, and Liver Vein to Cava Attenuation (LVCA), a computed tomography (CT)-based perfusion-related parameter, to diagnose HCC in patients with LC. Methods: In this observational retrospective pilot study, 36 patients with LC, with or without HCC, were enrolled from a single tertiary care center between 2021 and 2024. Demographic, clinical, biochemical, and imaging data were collected. LSVR and LVCA were calculated from contrast-enhanced CT scans. Predictors of HCC were assessed using conditional inference trees and multivariate logistic regression. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC). A p-value < 0.05 was considered statistically significant. Results: LVCA and LSVR levels were significantly higher in the HCC group (p < 0.001). In multivariate analysis, LVCA was significantly associated with HCC onset (Odds Ratio = 2.88, p = 0.0075). The final model incorporating both LVCA and LSVR achieved excellent discrimination (AUC = 0.967), with 91% sensitivity and 88% specificity. The combined model outperformed LSVR alone (p = 0.030), though not LVCA alone. Conclusions: Our pilot study suggests the utility of LVCA and LSVR as potential non-invasive imaging tools for HCC diagnosis. External validation in multicenter cohorts and longitudinal studies assessing the temporal evolution of LSVR and LVCA are necessary to better evaluate their application in clinical practice. Full article

The aberrant DNA methylation of tumour suppressor genes, including CADM1, MAL, and PAX1, is implicated in cervical carcinogenesis. Objectives: This pilot study aimed to evaluate the methylation levels of these genes in HPV-positive women and assess their diagnostic performance for detecting histologic high-grade squamous intraepithelial lesions (HSILs) and carcinoma. Methods: Cervical samples from 73 HPV-positive women were analyzed using droplet digital PCR (ddPCR) to quantify methylation levels of CADM1, MAL, and PAX1. The methylation levels were further compared across cytological and histological classifications. A control group of 26 HPV-negative women with negative cytology was also included. The diagnostic performance was assessed through receiver operating characteristic (ROC) analysis, as well as sensitivity and specificity calculations for individual genes and gene panels. Results: MAL methylation was absent in NILM, LSIL, and HSIL samples but was significantly elevated in carcinoma. PAX1 methylation was observed in both high-grade and some low-grade lesions. CADM1 methylation remained low or undetectable in the NILM, LSIL, and HSIL groups, with a significant increase observed in carcinoma cases. The CADM1/MAL panel demonstrated the highest diagnostic accuracy, with an area under the curve (AUC) of 0.912, 70% sensitivity, and 100% specificity. ddPCR exhibited superior analytical sensitivity compared to real-time PCR. Conclusions: The CADM1/MAL methylation panel, assessed by ddPCR, may serve as a specific biomarker for the triage of HPV-positive women at risk of HSIL and carcinoma. However, this study’s limited sample size and single-centre design necessitate cautious interpretation. Further validation in larger, population-based cohorts is necessary to confirm its clinical utility. Full article