Search Results (55,477)

The interdisciplinary nature of artificial intelligence courses forces non-computer science majors to contend with the simultaneous challenges of terminology comprehension and language cognition. To increase the efficiency of terminology teaching, this project develops and deploys an OpenAI-based AI chatbot teaching system that incorporates the concept of content and language integrated learning (CLIL). The system creates a dual-track “terminology layer-cognition layer” framework that includes term recognition, multi-level explanation (contextual examples and conceptual associations), task-driven dialogues, and conversation memory bank (CMB) modules. It then guides students through natural language interactions to master the core AI terms in context. The system’s effectiveness was confirmed in a controlled experiment with 98 participants (including computer and non-computer majors) separated into two groups: experimental (chatbot teaching) and control (conventional PPT teaching). In terms of terminology mastery, the experimental group’s posttest score (86.0 ± 5.33) was considerably higher than that of the control group (66.98 ± 5.6). Non-computer science major students showed a more significant improvement effect (83.29 ± 4.5 vs. 63.62 ± 4.68 for the control group). Non-computing students evaluated the clarity of systematic terminology explanation (4.33 ± 0.76) and the effectiveness of contextual assistance (4.21 ± 0.88) as the most important aspects of their learning experience. These experimental results show that the fusion AI chatbot teaching system developed in this study can improve teaching efficiency while effectively reducing cognitive load, and that the task-guided and immediate feedback mechanism can significantly increase students’ learning engagement. Full article

The rise in ICU survival rates has introduced new challenges related to the long-term effects of intensive care, known as Post-Intensive Care Syndrome (PICS). Nurses play a key role in these clinics; however, the nature and outcomes of their interventions remain insufficiently understood. Objectives: This review aims to identify nursing interventions for PICS in follow-up clinics. Methods: Using the JBI scoping review methodology, we searched PubMed, Web of Science and CINAHL (via EBSCOhost) in March 2025, and examined grey literature in RCAAP and Open Dissertations (through B-ON). Inclusion criteria, based on JBI’s PCC (Population, Concept, Context), focused on nursing interventions for PICS for patients and families in follow-up. Studies involving children, adolescents, pregnant women, and those receiving end-of-life care were excluded. Results: Encompassing studies from 2005 to 2022 across multiple countries, this review highlights nursing interventions for post-ICU recovery. A total of 394 articles that met our search criteria were found, resulting from searches in the mentioned databases. These were initially exported to Rayyan, and 115 duplicates were removed. The 21 articles that met our inclusion criteria were fully analyzed, and those that effectively answered our questions and met our inclusion criteria were selected. In the end, 9 articles were selected, to which, after an individual analysis of their bibliographic references, 3 more were added, totaling 12 articles submitted to the final analysis. Conclusions: For patients, interventions ranged from debriefing, PICS symptom evaluation, ICU re-visits, health education, cognitive–behavioral therapy and support groups, complemented by home-based physical rehabilitation and virtual reality. Family-focused interventions centered on appointment involvement, educational sessions, patient diary review, and emotional support. These assessments and interventions address the consequences of ICU admission, with the goal of facilitating physical, mental, and emotional rehabilitation of ICU survivors. This review emphasizes the critical role of follow-up consultations in the recovery of both patients and families. A comprehensive assessment using PICS scales and the integration of families into care plans are crucial for optimizing intervention outcomes. Implications for Clinical Practice: The development of evidence-based guidelines for implementation of follow-up clinics for SPICI appointments is necessary. Full article

This article presents the concept of using a functionalised siloxane compound HOL9 with amphiphilic properties as a coating for cement composites to enhance their antifouling properties against algae. The biological properties of the compound were assessed based on its ability to inhibit chlorophyll fluorescence intensity, which is used as an indicator of photosynthetic activity and biofilm development. The greatest decrease in algal photosynthetic activity was observed for a 10% aqueous solution of HOL9 applied by painting. In these conditions, the maximum ^chlFI value decreased by 97.6%. In addition, the impact of the protective coating containing HOL9 on the fundamental physical and mechanical characteristics of the cement composite, along with its resilience to frost cycling, was thoroughly investigated. The coating applied by immersion demonstrated a 50.7% strength loss after 150 freeze–thaw cycles, while the coating applied by painting exhibited a 43.8% loss. In comparison, the control samples experienced a 42.8% strength reduction. It has been demonstrated that the method of application, the modifier concentration, and the type of solvent can have a substantial impact on the protective properties of concrete. The most marked inhibition of algae photosynthetic activity was observed with a 10% aqueous solution applied by painting. Full article

Solution-processed OLEDs represent a low-cost, scalable alternative to vacuum-deposited devices, particularly for flexible and large-scale applications. However, selecting compatible materials for each layer remains a complex task, further complicated by inconsistent documentation, solvent interactions, and limited reproducibility across the literature. This work presents a literature review and critical analysis of materials, solvents, and fabrication methods involved in solution-processed OLEDs, with particular attention to layer formulation, solvent orthogonality, and processing constraints. A Monte Carlo-based optimization framework is introduced as a proof of concept, aiming to formalize stack selection and explore viable combinations based on empirical constraints. The critical analysis highlights recurring issues in the field and advocates for a more structured, reproducibility-oriented approach to OLED design. Full article

K-Means is a well-known algorithm for unsupervised clustering, very often used due to its simplicity and efficiency. Its long-time widespread use has stimulated researchers to investigate its properties further. A critical property concerns K-Means’s strong dependence on the seeding method adopted to initialize centroids. Poor initialization causes K-Means to get stuck in a local sub-optimal solution. This paper proposes DPCCs—Density Peaks of Candidate Centroids—a novel seeding method for K-Means. DPCC rests on genetic concepts and density peaks to define an initialization solution close to the optimal one. First, a population of J elitist candidate solutions, that is, solutions capable of yielding a reduced clustering cost, is built. Although none of these particular solutions can be near the optimal one, candidate centroids, as experimentally confirmed, tend to thicken around ground truth centroids. Therefore, subsequent generations of the population are created by repeating the k-nearest neighbors (kNNs) procedure for different values of the k parameter, and estimating density through the reverse nearest neighbors (RNNs) relationship of each centroid. Centroid density peaks are then exploited to rearrange the population solutions toward extracting a candidate solution, which is finally optimized by K-Means. The paper describes the design and operation of DPCC, which is currently implemented in parallel Java. The clustering effectiveness of DPCC is demonstrated by applications to both benchmark and real-world datasets. Results are compared with those of other competing algorithms. Full article

Background/Objectives: Contemporary food systems face dual imperatives of ensuring nutritional adequacy while minimizing environmental resource consumption, yet conventional dietary assessment methodologies inadequately integrate these competing objectives. This simulation-based proof-of-concept study developed an artificial intelligence-driven computational framework synthesizing nutritional evaluation, environmental footprint quantification, and economic accessibility assessment. Methods: The analytical architecture integrated random forest classification, dimensionality reduction, and scenario-based optimization across a simulated population cohort of 1500 individuals. Food composition data encompassed 55 representative foods across eight categories linked with greenhouse gas emissions, water use, and price parameters. Four dietary patterns (Mediterranean, Western, Plant-based, Mixed) were characterized across nutrient adequacy, greenhouse gas emissions, water consumption, and economic cost. Results: Random forest classification achieved 39.1% accuracy, with cost, greenhouse gas emissions, and water consumption emerging as the most discriminating features. Dietary patterns exhibited convergent macronutrient profiles (protein 108.8–112.8 g per day, 4% variation) despite categorical distinctions, while calcium inadequacy pervaded all patterns (867–927.5 mg per day, 7–13% below requirements). Environmental footprints demonstrated limited differentiation (greenhouse gas 3.73–3.96 kg CO₂e per day, 6% range). Bootstrap resampling (n = 1000) confirmed narrow confidence intervals, with NHANES validation revealing substantial energy intake deviations (38–58% above observed means) attributable to adequacy-prioritized design rather than observed consumption patterns. Scenario modeling identified seasonally flexible dietary configurations maintaining micronutrient and protein adequacy while reducing water use to 87% of baseline at modest cost increases. Conclusions: This framework establishes a validated computational infrastructure for integrated dietary assessment benchmarked against sustainability thresholds and epidemiological reference data, demonstrating the feasibility of AI-driven evaluation of dietary patterns across nutritional, environmental, and economic dimensions. Full article

Background/Objectives: Congenital muscular torticollis (CMT) affects 0.3–3.9% of infants, requiring early physiotherapy to prevent deformities. Vojta and NDT Bobath therapies are widely used, yet comparative evidence remains limited. To compare Vojta versus NDT Bobath efficacy in improving head tilt and cervical rotation in infants with CMT. Methods: Retrospective cohort study (2016–2024) at Polish Mother’s Memorial Hospital included 53 infants under 5 months with ultrasound-confirmed CMT. Non-random allocation based on therapist availability introduced selection bias. Participants received Vojta (n = 29) or NDT Bobath (n = 24) two 30 min sessions weekly for 20 weeks plus home exercises. Blinded physicians measured outcomes. Results: Vojta showed greater angular improvements versus NDT Bobath: head tilt MD = −5.69° (p < 0.001, Hedges’ g = 1.29) and neck rotation MD = −5.89° (p < 0.001, Hedges’ g = 1.21). Early intervention (1–2 months) demonstrated 5-fold (RR = 5.46) and 8-fold (RR = 8.19) higher likelihood of achieving optimal thresholds (70°/90°) versus later intervention (3–4 months) both p < 0.001. No therapy × age interaction was found, indicating consistent between-group differences across age strata. Large effect sizes suggest clinically meaningful angular improvements. Conclusions: Vojta therapy was associated with superior angular outcomes versus NDT Bobath, with early initiation showing better results. However, the retrospective non-randomized design, small sample (n = 53), and absence of functional outcome assessment limit causal inference. Only biomechanical outcomes were measured; functional motor development, complications, and quality of life were not evaluated. Prospective randomized trials with functional assessments and larger samples are essential to confirm these associations and determine clinical significance. Full article

A vibration energy harvester (VEH) based on the principle of variable magnetic reluctance has been developed to enable wireless and maintenance-free power supply for condition monitoring sensors in vibrating machinery. Conventional battery or wired solutions are often impractical due to limited lifetime and high installation costs, motivating the use of vibration-based energy harvesting. The proposed VEH converts mechanical vibrations into electrical energy through the relative motion of a movable ferromagnetic core within a magnetic circuit. Unlike conventional VEH designs, where the magnet is the moving element, this concept utilizes a movable ferromagnetic core in combination with a stationary pole piece for voltage induction. This configuration enables a compact and easily adjustable proof mass, as neither the coil nor the magnet needs to be moved. The VEH is designed to operate effectively under excitation frequencies between $16 \mathrm{H}\mathrm{z}$ and $50 \mathrm{H}\mathrm{z}$ and acceleration levels from $9.81 {\displaystyle \frac{\mathrm{m}}{{\mathrm{s}}^2}}$ (equivalent to $1 \mathrm{g}$) up to $98.1 {\displaystyle \frac{\mathrm{m}}{{\mathrm{s}}^2}}$ (equivalent to $10 \mathrm{g}$). To ensure a reliable power supply, the VEH must deliver a minimum electrical output of $0.1 \mathrm{m}\mathrm{W}$ at the lowest excitation ($1 \mathrm{g}$) while maintaining structural integrity. Additionally, the maximum permissible displacement amplitude of the movable core is limited to $1.15 \mathrm{m}\mathrm{m}$ to avoid mechanical damage and ensure durability over long-term operation. Coupled magnetic-transient and mechanical finite element method (FEM) simulations were conducted to analyze the system’s dynamic behavior and electrical power output across varying excitation frequencies and accelerations. A laboratory prototype was developed and tested under controlled vibration conditions to validate the simulation results. The experimental measurements confirm that the VEH achieves an electrical output of $0.166 \mathrm{m}\mathrm{W}$ at $9.81 {\displaystyle \frac{\mathrm{m}}{{\mathrm{s}}^2}}$ and $16 \mathrm{H}\mathrm{z}$, while maintaining the maximum allowable displacement amplitude of $1.15 \mathrm{m}\mathrm{m}$, even at $98.1 {\displaystyle \frac{\mathrm{m}}{{\mathrm{s}}^2}}$ ($10 \mathrm{g}$) and $50 \mathrm{H}\mathrm{z}$. The strong agreement between simulation and experimental data demonstrates the reliability of the coupled FEM approach. Overall, the proposed VEH design meets the defined performance targets and provides a robust solution for powering wireless sensor systems under a wide range of vibration conditions. Full article

Oncosomes, a distinct subclass of extracellular vesicles released predominantly by tumor cells, have attracted increasing interest as potential carriers for targeted drug delivery in cancer research. Characterized by their large size (1–10 µm) and complex molecular cargo, including oncogenic proteins, nucleic acids, and lipids, oncosomes provide a biologically relevant platform for investigating tumor-associated communication and cargo transport. Preclinical studies suggest that oncosomes may enable tumor-associated delivery of therapeutic agents; however, evidence to date remains largely proof-of-concept and derived from in vitro and animal models. This review summarizes current knowledge on oncosome biogenesis and molecular composition; discusses their roles in cancer progression and metastasis; and critically evaluates existing methodologies for oncosome isolation, characterization, and cargo loading, including incubation, electroporation, sonication, freeze–thaw cycling, and transfection. Potential advantages such as cargo capacity and biological compatibility are discussed alongside key challenges, including vesicle heterogeneity, limited loading efficiency, large-scale manufacturing constraints, safety considerations, and regulatory uncertainty. Future perspectives focus on addressing these technical and translational barriers to support the systematic evaluation of engineered oncosomes as an experimental platform for personalized and precision-oriented cancer research. Full article

Precise control of keratinocyte proliferation and differentiation is critical for oral epithelial regeneration, yet the mechanobiological cues guiding these processes remain incompletely defined. Here, we systematically evaluated how electrospun polycaprolactone (PCL) scaffolds with defined fiber orientations (aligned vs. random) and diameters (600–800 nm, 1.2–1.7 µm, 2.0–2.5 µm) direct gingival keratinocyte fate. Using immortalized human gingival keratinocytes, we assessed cell and nuclear morphology, proliferation dynamics, differentiation marker expression, and the effects of basal keratin (KRT5/KRT14) knockdown. Quantitative morphological analysis revealed scaffold-dependent changes in cell shape: aligned medium-diameter fibers (with fiber diameters of 1.2–1.7 µm) induced pronounced cell and nuclear elongation, whereas random fibers (600–800 nm) promoted larger, more rounded cell and nuclear shapes. Time-resolved EdU assays indicated that aligned scaffolds supported sustained proliferation, whereas random scaffolds elicited a transient proliferative burst followed by a decline. Gene expression analysis (ddPCR) demonstrated that random scaffolds (especially 600–800 nm fibers) upregulated basal keratins (KRT5, KRT14) and early differentiation markers (KRT1, KRT10, KRT4, KRT13) relative to aligned scaffolds. At the protein level, differentiation markers involucrin (IVL) and filaggrin (FLG) were likewise elevated on random scaffolds, corroborating the mRNA findings. Functional KRT5/KRT14 knockdown experiments revealed scaffold-specific dependencies: cells on random scaffolds required these keratins for viability, whereas aligned cultures remained viable upon KRT5/14 loss. Furthermore, KRT5/14 depletion differentially altered downstream differentiation markers (IVL, KRT1) and mechanotransduction markers (LMNB1, YAP1) in a scaffold-dependent manner. Collectively, these findings establish fiber orientation and diameter as key design parameters for controlling keratinocyte fate. As a translational concept, layered scaffolds combining aligned and random fibers may enable spatially controlled proliferation and differentiation in engineered oral epithelia. Full article

Inflammatory and immune-mediated skin diseases are increasingly recognized as disorders in which genetic susceptibility is shaped and sustained by environmentally responsive regulatory programs. Psoriasis, atopic dermatitis (AD), vitiligo, systemic sclerosis (SSc), lupus erythematosus (LE), and lichen planus (LP) are clinically distinct, yet they share chronic or relapsing inflammation, tissue remodeling, and limited durability of many current therapies. Because genetic variation alone cannot fully explain disease onset, flare dynamics, heterogeneity in severity, or lesion recurrence, epigenetic mechanisms have emerged as a plausible link between environmental exposures and stable disease phenotypes in skin. Epigenetic regulation, including DNA methylation, histone modifications, and non-coding RNA networks, controls cell-type-specific transcription without altering the DNA sequence and may contribute to persistent inflammatory states and disease memory despite clinical improvement. The current review synthesizes primary preclinical and translational evidence on epigenetic-targeted therapeutic strategies across these conditions, focusing on interventions that modulate DNA methylation, histone acetylation and deacetylation, histone methylation, chromatin-associated regulatory proteins, and RNA-based approaches. We compare the maturity of therapeutic development across diseases, noting that research and intervention studies are concentrated in psoriasis and AD, whereas evidence for vitiligo, SSc, LE, and LP remains more limited and often derived from systemic or non-cutaneous models. Finally, we outline key gaps that currently restrict clinical translation and discuss why bridging them is essential for determining whether epigenetic modulation can move beyond proof-of-concept toward durable and clinically actionable interventions in inflammatory skin disease. Full article

Nowadays, river systems exhibit significant geomorphic changes that primarily reflect their response to the climate signal, driven by ongoing climate change. In this context, detecting future trends in riverbed dynamics is crucial, especially from a river management perspective. The purpose of the study is to identify long-term trends in riverbed evolution at the Băleni gauging station on the Ialomița River, based on the channel-forming discharge concept, through the end of the 21st century. To achieve this, a comprehensive methodology was developed that primarily focuses on calculating the effective discharge (Qe) as a key driver of riverbed dynamics, using discharges simulated by the E–HYPE hydrological model forced by eight EURO–CORDEX EUR–11 ensemble climate projections under the RCP 4.5 and RCP 8.5 scenarios up to 2100. The results of the study indicate Qe values ranging between 7.49 m³/s and 12.79 m³/s for RCP 4.5, and between 5.66 m³/s and 13.94 m³/s for RCP 8.5. Based on the ensemble mean of Qe, different riverbed evolution trends and are identified: a state of dynamic equilibrium under RCP 4.5, suggesting that the riverbed is probable to maintain its geomorphological state similar to the present; and pronounced variability under RCP 8.5, indicating intense erosion processes until mid-century, followed by a slight aggradation trend that may intensify at the end of the century, with Qe being 23.27% lower than the reference period. Overall, the Qe_8.5 evolution suggests a potential future alteration of the Ialomița riverbed. Beyond its main findings, this study provides a methodological framework for assessing future effective discharge and may support river management and restoration planning in the study area. Full article

As human space exploration advances towards establishing sustainable Martian habitats, achieving autonomous food production is a critical requirement. The potato (Solanum tuberosum L.), with its notable environmental resilience and nutritional efficiency, is a prime candidate crop. This study develops a conceptual framework for Martian potato cultivation by systematically analyzing the profound disparities between Martian conditions and plant physiology. We identify and evaluate seven fundamental challenges: atmospheric composition, extreme temperatures, water scarcity, soil properties, nutrient deficiencies, absent microbiota, and radiation/gravity effects. To address these challenges, we propose a phased, testable roadmap comprising four stages: (I) screening and bio-engineering of multi-stress-tolerant potato genotypes; (II) phased domestication via Earth-based analog experiments to define adaptability thresholds; (III) deployment of a controlled cultivation module within a Martian habitat, integrating targeted technological interventions; and (IV) conceptual exploration of extra-habitat agricultural potential. The primary contribution of this work is a structured set of hypotheses and key performance indicators for each stage, translating visionary goals into a defined research agenda to guide future empirical work in extraterrestrial agronomy. Full article

The present study analyzes the possibilities for diversification in the iGaming sector through the integration of concepts derived from financial derivatives theory. The main idea is the development of a model introducing a mechanism for buying and selling bets between two clients as a means of early position closure—an analog to option trading in capital markets. The model is structured in three phases and four conditions, forming eight scenarios with varying probabilities and expected returns. The analysis demonstrates that, under appropriate parameters, the innovation can be potentially profitable for clients and acceptable for the bookmaker, who may offset potential losses through an increased number of registrations and an enhanced corporate image. The proposed conceptual framework provides a theoretical foundation for the creation of a secondary market in iGaming, which could lead to greater market efficiency, increased liquidity, and the rationalization of player behavior. The results emphasize the significance of an interdisciplinary approach combining game theory, behavioral economics, and financial engineering as a basis for sustainable development and competitive advantage in the dynamically evolving iGaming industry. Full article

The requirements of the upcoming aircraft generation based on hybrid or electric propulsion discourage the use of Ice Protection Systems (IPSs) based on hot-air spilled from engine or demanding a large consumption of electrical power. In line with this need, a low-power IPS based on piezoelectric (PZT) technology is investigated in the current article. Its main objective is to protect an aerodynamic surface by removing ice accretions (de-icing). The idea at the basis of the concept is to drive mechanical waves at the interface between the skin and the ice layer to cause the breaking and the detachment. Moving from an assessed layout and numerical simulations providing the most effective design configuration, dedicated small-scale airfoil demonstrators (NACA 0012 with a chord of 310 mm and a span of 150 mm) were manufactured, with the aim of testing the technology within the representative environment of the IFAM Icing Wind Tunnel (IWT). The test results showed, for power consumption of 4.4 kW/m², ice detachment levels -based on the ice-covered area- between 40 and 50% at −10 °C, about 40% at −20 °C, and a maximum of 15% at −4 °C. The results highlighted the impact of some specific parameters (environmental temperature, skin, and ice thickness) on the effectiveness of the IPS. Full article