Search Results (1,730)

Traditional fermented foods are important reservoirs of wild microorganisms with technological, sensory, protective, and functional potential. However, the performance of these isolates in controlled or compositionally different food matrices remains fragmented across microbial groups and food systems. This systematic review synthesized evidence on using wild microbial isolates from traditional fermented foods and beverages as starters or potential probiotic cultures. The conducted a systematic search exclusively in Scopus, following PRISMA 2020, to include original research articles published between 2021 and 2026, yielding 68 eligible studies. The included studies were analyzed by geographical origin, isolation source, recipient matrix, microbial group, and key physicochemical, technological, sensory, microbiological, nutritional, and functional outcomes. The evidence was organized into wild yeasts and filamentous fungi, lactic acid bacteria (LAB), Bacillus isolates, and defined mixed microbial cultures. Across food matrices, microbial incorporation frequently accelerated acidification, shortened fermentation time, modified volatile compound profiles, and altered texture, color, enzymatic activity, or substrate utilization. Sensory responses improved aroma, flavor, texture, and acceptance, whereas others produced profiles that deviated from the characteristic product and reduced overall liking. Functional effects included increases in phenolic compounds, antioxidant activity, GABA, folate, peptides, and resistant starch, along with reductions in phytates, nitrites, biogenic amines, aflatoxins, and nondigestible oligosaccharides. Researchers also reported antimicrobial, antifungal, protective, and preliminary probiotic properties. Defined mixed microbial cultures often provided complementary metabolic effects, although true synergistic interactions were demonstrated only sporadically. Overall, wild isolates from traditional fermentations represent promising resources for food bioprocessing; however, their performance varies widely across strains, recipient matrices, experimental conditions, and outcomes evaluated. Consequently, their application requires strain–matrix validation, comprehensive sensory assessment, safety characterization, and evaluation under processing and storage conditions relevant to industrial production. Full article

Anode materials play a pivotal role in a wide range of electrochemical applications, including electrolysis, energy storage, corrosion protection, and industrial oxidation processes. This review provides a comprehensive analysis of recent advances in anode materials, with particular emphasis on their structural characteristics and major preparation methods, including thermal decomposition, electrochemical deposition, sol–gel processing, and magnetron sputtering. The degradation behaviour of anodes under electrochemical operating conditions is also critically discussed, together with strategies for improving their durability and overall performance. Particular attention is given to metal oxide-coated anodes, especially those based on ruthenium oxide (RuO₂) and iridium oxide (IrO₂), which remain the most representative systems in dimensionally stable anode (DSA) research and industrial applications. Emerging coating materials, including Co₃O₄- and carbon-based catalysts, are also reviewed as promising alternatives for reducing noble metal usage while maintaining acceptable electrochemical performance. In addition, the role of intermediate layers in titanium-based anodes is examined, with emphasis on their contribution to coating adhesion, conductivity, interfacial stability, and long-term electrode performance. This review further discusses the applications of anode materials in chlorine- and oxygen-related electrochemical industries and evaluates the performance of DSAs in relation to substrate selection, coating composition, and operational requirements. Alternative furnace technologies for anode baking are also reviewed, including conventional furnace heating, laser heating, and microwave heating, together with representative industrial furnace systems such as muffle, continuous, and vacuum furnaces. Overall, this review provides an integrated overview of the current progress in anode material research and development, while highlighting the key challenges and future directions for improving anode efficiency, durability, and sustainability in industrial electrochemical applications. Full article

Fish farming can contribute to sustainable rural tourism when environmental performance and visitor expectations are considered jointly. This study aimed to evaluate fish farming as a strategy for sustainable tourism in Somondoco, Boyacá, Colombia, by integrating an environmental assessment of water quality with visitors’ perceptions of sustainable tourism. A case study was conducted at the “Los Lagos” fish farm, where physicochemical parameters were measured at the water supply and discharge points and the water quality index (WQI) was calculated. In parallel, a survey of 73 visitors was conducted to characterize perceptions of sustainable tourism and willingness to pay for more sustainable services. The WQI decreased from 0.75 (acceptable) at the water supply point to 0.60 (regular) at the discharge point, mainly associated with changes in electrical conductivity and chemical oxygen demand. From the tourism perspective, 93.1% of respondents considered sustainable tourism important, while 54.8% identified responsible management of natural resources as the main aspect to be addressed. In addition, 84.9% expressed willingness to pay an additional 10–20% for a more sustainable offering. The integration of environmental and tourism-perception results, complemented by a SWOT analysis, identified water management, environmental education, technological modernization, and community participation as priority areas for sustainable tourism development. These findings provide a case-based framework for linking aquaculture environmental performance with visitor expectations in the formulation of sustainable tourism strategies. Full article

Artificial intelligence (AI) can be appraised simultaneously as useful, capable, threatening, and demanding. Yet research typically treats attitudes toward AI as a single favorable-unfavorable continuum, obscuring how these evaluations coexist within individuals. Using a three-wave, time-lagged survey of 379 first-year university students in China, we examined configurations of six AI-related appraisal indicators: perceived humanlikeness, adaptability, and quality of AI; AI use anxiety; awareness of smart technology, artificial intelligence, robotics, and algorithms (STARA) as a career threat; and AI creative self-efficacy. Latent profile analysis supported four profiles: Positive Empowerment (19.2%), Anxious Acceptance (37.5%), Low-Perception Detached (37.2%), and High-Perception High-Vigilance (6.1%). R3STEP models showed that learning agility, digital literacy, future work self salience, and perceived university digital support were prospectively associated with profile membership, particularly in distinguishing the Low-Perception Detached profile from the more engaged profiles. BCH comparisons further showed that the Positive Empowerment and High-Perception High-Vigilance profiles reported relatively high levels of both career crafting and self-perceived employability, whereas the Low-Perception Detached profile reported the lowest levels of both outcomes. Notably, the High-Perception High-Vigilance profile combined elevated AI use anxiety and STARA awareness with strong career-development engagement, while the Low-Perception Detached profile combined comparatively low threat perceptions with weak career crafting and employability. These findings demonstrate that higher AI-related threat was not necessarily associated with weaker career preparation and, conversely, that low perceived threat was not necessarily associated with greater adaptive readiness. Overall, the results position students’ responses to AI as configurations of opportunity appraisal, threat, and AI creative self-efficacy rather than as uniformly positive or negative attitudes, thereby highlighting the need for differentiated university career education and AI-readiness interventions. Full article

This study assessed the feasibility of a technology-supported high-intensity interval training (HIIT) program for occupational drivers. A multiphase feasibility study incorporating participant feedback was conducted in Flanders, Belgium, including consultation, pilot, and intervention phases. Occupational drivers were randomized to a HIIT group, an active control group (mindfulness program), or a passive control group (no intervention). The 16-week, equipment-free HIIT program consisted of two 15-min sessions per week, delivered via a technology-supported mobile application, preceded by a 2-week baseline. Primary feasibility outcomes included program completion, session adherence, intervention fidelity, adverse events, and participant experiences, while changes in health-related outcomes were assessed as secondary exploratory outcomes using validated questionnaires. During the consultation (n = 11) and pilot (n = 2) phases, participants reported positive attitudes toward the intervention. Key barriers, including scheduling constraints (n = 5) and bicycle transportation (n = 4), informed refinements such as an equipment-free, technology-supported protocol and flexible scheduling. Of the 23 randomized participants across all groups, 16 participants initiated their assigned study protocol, and 10 completed all assessment points and were included in the final analysis. Of the nine participants allocated to the HIIT group, four initiated the intervention (44.4%), and three completed the program (33.3% of those allocated; 75% of those who initiated). Among the three completers, mean session attendance was 80.2%. Session fidelity was well maintained, but exercise-intensity fidelity could not be objectively confirmed. No exercise-related adverse events were reported. Participant feedback indicated generally positive usability but mixed acceptability of the technology-supported HIIT program among the three participants who completed the intervention. Exploratory individual-level changes in health-related outcomes were heterogeneous, with lower mean scores for depression, anxiety, stress, and fatigue. A technology-supported HIIT program was feasible among the small subgroup of occupational drivers who initiated it, with high session attendance. However, considerable pre-initiation attrition and low retention limit its feasibility for the broader target population. Observed health-related outcomes were heterogeneous and should be interpreted descriptively, warranting evaluation in a fully powered randomized controlled trial. Full article

Background and Objectives: Wearable health technologies have become increasingly important in the remote management of cardiovascular diseases (CVDs); however, their successful implementation depends not only on technical performance but also on patient usability and technology acceptance. This study aimed to evaluate the perceived usability and technology acceptance of a wearable monitoring system among patients with CVDs and to investigate whether demographic and clinical characteristics influenced these outcomes. Materials and Methods: A cross-sectional observational study was conducted among 60 patients with CVDs enrolled in a six-month wearable monitoring program at the Medical Rehabilitation Outpatient Clinic of the Avram Iancu Clinical Hospital, Oradea, Romania. Participants used a Garmin vívosmart^® 5 fitness tracker to continuously monitor physiological and behavioral parameters. At the end of the monitoring period, perceived ease of use (PEU) was assessed using the System Usability Scale (SUS), while technology acceptance was evaluated using a Technology Acceptance Model (TAM)-based questionnaire. Descriptive statistics, reliability analysis, Spearman’s rank correlation, and multiple linear regression analyses were performed. Results: The wearable monitoring system demonstrated high PEU, with a median SUS score of 82.5 (IQR = 23.1) and a mean score of 75.5 ± 17.6. Overall, 75.0% of participants rated the system as having good or excellent usability. The SUS questionnaire demonstrated acceptable internal consistency (Cronbach’s α = 0.730; McDonald’s ω = 0.741). Technology acceptance was generally favorable, with an overall median TAM-based score of 1.33 (IQR = 0.78). Age and comorbidity burden were not associated with PEU, and no participant characteristics independently predicted SUS scores. Although the overall regression model was not statistically significant, age showed a statistically significant association with the overall TAM-based score (β = 0.328, p = 0.037). Significant positive correlations were observed between PU, self-efficacy (SE), and reverse-scored technology anxiety (TA) measure (p < 0.001). Conclusions: Patients with CVDs reported high PEU and favorable acceptance of wearable monitoring technology. While usability appeared independent of demographic and clinical characteristics, technology acceptance showed an exploratory association with age, although the overall regression model was not statistically significant. These findings support the integration of wearable monitoring systems into routine cardiovascular care and highlight the importance of patient-centered implementation strategies to promote long-term engagement. Full article

The global shift toward an aging population presents significant challenges for healthcare systems. This is compounded by rising disability rates, fragmented care models that struggle to meet complex needs, and a digital divide caused by the emergence of smart technologies. This work aims to evaluate how the digital divide affects the adoption, usability, and perceived benefits of smart home technologies designed to support activities of daily living and health monitoring. The influences of socioeconomic status and geographic location (urban versus rural) on the digital divide are considered. Four databases (Web of Science™, Scopus^®, PubMed^®, and IEEE Xplore^®) were searched between 2014 and 2026, resulting in 71 studies that examined older adults, smart home technologies for daily living or health monitoring, and factors related to the digital divide. Findings were synthesized using the Technology Acceptance Model, Van Dijk’s Digital Divide Framework, and Health Behavior Models. Three key barriers were identified—economic, technical, and social—which disproportionately affected vulnerable groups. Smart Home Health Technologies (SH2Techs) present adoption challenges distinct from standalone devices because they require integrated infrastructure and sustained engagement. Limited research addressing the usability of non-clinical SH2Techs has identified the need for co-design, simplified interfaces, targeted training, and policy reforms to support equitable aging in place. Full article

The rapid integration of Artificial Intelligence (AI) into digital commerce and social structures has created a complex perceptual landscape for consumers. While AI is often associated with efficiency and progress, it simultaneously triggers concerns regarding algorithmic opacity and loss of human control. This study investigates the dual role of digital literacy as a predictor of both perceived utility and consumer scepticism, as well as their subsequent impact on the overall perception of AI as an opportunity or a risk. Using secondary data from a nationally representative German survey on artificial intelligence (GESIS, Study No. ZA8719) and employing Structural Equation Modelling (SEM), the research tests a conceptual framework based on the “Privacy Paradox” and technology acceptance theories. The results reveal that digital literacy significantly enhances the perceived utility of AI while concurrently amplifying consumer scepticism. Furthermore, the study identifies a dominant effect of perceived utility on the overall evaluation of AI, whereas the impact of scepticism remains statistically non-significant. These findings suggest a compensatory mechanism where pragmatic benefits outweigh perceived risks in the consumer’s decision-making process. The paper concludes with strategic implications for digital marketing and e-commerce platforms, emphasizing that value creation is the primary driver for overcoming consumer resistance in the digital era. Full article

Background: Wearable sensing and local wireless communication architectures offer significant potential for accessible rehabilitation technologies. The objective of this exploratory study was to design, implement, and describe an interdisciplinary, wireless inertial sensing platform—the Virtual Therapist Platform (VTP)—for real-time postural monitoring and exergame-based rehabilitation in a controlled laboratory setting. Methods: A laboratory proof-of-concept evaluation was conducted across three integrated domains: (1) technical characterisation of the dual-node ESP-NOW architecture (30-min test at 50 packets/s per node via an ESP32-C6 gateway) for real-time trunk tracking; (2) formative usability and acceptability assessment of the VTP interface across two independent cohorts of fourth-year Physiotherapy students ($n=25$ per cohort; 2024 and 2025) using a standardized protocol; and (3) a descriptive mapping of the four-phase interdisciplinary development process integrating Physiotherapy and Mechatronics Engineering inputs. Results: The two-node ESP-NOW test demonstrated high communication performance (99.68% packet delivery ratio (PDR), 8.03 ms mean latency, 1.98 ms jitter, and 99.68 ± 0.52 packets/s throughput). Subjective usability increased from a median score of 85.0 (IQR: 80.0–92.5) in 2024 to 100.0 (IQR: 100.0–100.0) in 2025. Conclusions: The dual-node architecture provided reliable local ESP-NOW packet transmission, while subjective evaluations demonstrated high system usability and acceptability. This interdisciplinary baseline lays the groundwork for future evaluations in clinical environments. Full article

This study protocol presents a pre-specified framework for assessing whether Farm Machinery-as-a-Service (FMaaS) can support inclusive access to Agriculture 4.0 in fragmented agrarian systems. The aim of the protocol is to define the conceptual framework, research questions, hypotheses, target population, sampling strategy, data collection procedures and planned analytical approach for a future empirical study using Poland as a case of a fragmented, family-farm-based agricultural system in which many small and medium-sized farms face difficulties in keeping pace with Agriculture 4.0. The manuscript does not report empirical results or human-subject data. The planned study will use a sequential mixed-methods design in which each component has a specific role. Secondary data analysis will diagnose farm structural conditions, machinery-use patterns, productivity gaps and innovation gaps. Expert and stakeholder interviews will refine the typology of FMaaS arrangements and identify relevant service attributes. A farm survey and a discrete choice experiment will assess farmers’ willingness to use FMaaS, perceived transaction costs, trust, digital readiness and preferences for specific service characteristics. Farm-level economic modeling and Monte Carlo simulation will evaluate the viability of ownership-based and service-based modernization scenarios under uncertainty. Structural equation modeling will examine social-sustainability mechanisms, including adaptive capacity, perceived resilience, perceived inclusion in digital agriculture and the perceived ability to continue farming under technological change. The expected output of the protocol is an integrated analytical framework for evaluating the economic, institutional, resource-use and social conditions under which FMaaS may become a viable and socially acceptable pathway to Agriculture 4.0. By combining transaction-cost theory, market-design reasoning, stated-preference methods, farm-level modeling and social-sustainability assessment, the protocol provides a transparent basis for future empirical research on access-based digital mechanization. Full article

Ambient Assisted Living (AAL) environments aim to enable older people to remain active and lead an autonomous and independent life for as long as possible. Among the technologies that can be incorporated into these settings, socially assistive robots (SAR) seek to establish a more natural and intuitive means of interaction with people, whilst helping them to carry out everyday tasks. One of the main challenges facing the design of these robots is how to enable them to undertake more complex tasks. Recent advances in Large Language Models (LLMs) have opened new avenues for flexible robot deliberation, yet their integration into real-time robotic systems remains challenging due to latency constraints, reasoning reliability, and the complexity of coordinating multi-step tasks. This paper proposes a hierarchical multi-agent architecture for robot deliberation that addresses these challenges by combining LLM-based planning with structured execution mechanisms within the ROS 2 ecosystem. The proposed architecture employs a supervisor agent that decomposes high-level natural language instructions into prioritised subtasks, enabling a priority-driven execution model that dynamically adapts to task relevance, temporal constraints, and environmental feedback. Subtasks are delegated to a set of Single-Purpose Agents (SPAs), orchestrated via LangGraph state machines and coordinated through a priority-aware scheduling mechanism. A key design principle is the use of Behaviour Trees (BTs) as high-level callable tools through the Model Context Protocol (MCP), encapsulating closed-loop control strategies while enabling preemptive and priority-consistent execution. This reduces the number of LLM inference steps required per task and improves robustness under dynamic conditions. A further contribution concerns the deployment of fine-tuned, lightweight LLMs—on the order of 0.6 billion parameters—specifically adapted for both the supervisor and the individual SPA roles through parameter-efficient low-rank adaptation (LoRA). These models are trained on role-specific tool-calling datasets to specialise in constrained reasoning patterns and task-specific decision-making, enabling efficient, low-latency inference directly on edge hardware. The combination of fine-tuning and hierarchical priority control enhances both the determinism and responsiveness of the system while mitigating error propagation across agent interactions. The paper presents the full software architecture, a formal characterisation of the system as a priority-aware hierarchical policy over a graph of agent workflows, and an experimental evaluation in an Ambient Assisted Living scenario assessing task success rate, inference efficiency, responsiveness under competing priorities, and overall user experience. Because SPA execution is decoupled from the supervisor’s own reasoning loop, the architecture is designed to keep accepting, processing, and queuing new user queries while previously dispatched SPAs are still executing their tasks. Full article

Background/Objectives: Liver cirrhosis (LC) is a major cause of morbidity and mortality requiring continuous monitoring and early recognition of clinical deterioration. Home telemonitoring is increasingly considered a supportive strategy for outpatient hepatology care; however, patient acceptance remains insufficiently characterized in Eastern Europe, and no validated instrument currently exists for this population. This study aimed to develop and provide the initial psychometric validation of a Technology Acceptance Model (TAM)-based questionnaire assessing acceptance of home telemonitoring among patients with LC. Methods: In this prospective cross-sectional study, 130 adult patients with LC (Child–Pugh A/B/C) were enrolled. A 25-item questionnaire, including 13 Likert-scale items mapped to Perceived Usefulness (PU), Perceived Ease of Use (PEU), and Intention to Use (ITU), was administered under supervision. Psychometric evaluation included internal consistency, exploratory and confirmatory factor analyses, structural equation modelling (SEM), convergent and discriminant validity, and known-groups validity. Results: Internal consistency was excellent (Cronbach’s α = 0.934; McDonald’s ω = 0.950). EFA identified a 2-factor structure explaining 77.9% of the variance, whereas CFA supported the theoretically driven 3-factor TAM, which showed improved incremental fit (CFI = 0.927; TLI = 0.908) and was retained on theoretical grounds. SEM confirmed the TAM pathway, with PU strongly predicting ITU (β = 0.823, p < 0.001), whereas PEU significantly influenced PU (β = 0.343, p < 0.001) but not ITU directly. The model explained 69.5% of the variance in ITU. Known-groups validity was supported across digital access, IT comfort, education level, and disease severity. Patients with advanced cirrhosis and lower digital confidence showed lower acceptance scores. Conclusions: The proposed 13-item Likert scale demonstrated good initial psychometric performance and may represent a useful tool for assessing telemonitoring acceptance and readiness for digital monitoring among patients with LC. Pending further multicentre validation and assessment of predictive validity, the instrument may support identification of patients requiring additional support for successful telemonitoring adoption. Full article

Industrial Internet of Things (IIoT) systems are increasingly deployed in heavy industrial facilities to support real-time monitoring, automation, and safety-critical operations. Long-range low-power communication technologies such as LoRaWAN are widely used for large-scale sensor connectivity due to their long communication range and energy efficiency. However, dense industrial deployments may experience reduced communication reliability due to network congestion, packet collisions, and challenging propagation conditions caused by metallic infrastructure and electromagnetic interference. To address these limitations, this paper proposes RSrSF-LoRa, an integrated implementation of the reserved spreading factor (rSF) mechanism within the RS-LoRa framework (lightweight scheduling), designed to improve reliability for critical traffic. The study presents a comparative performance evaluation of RSrSF-LoRa and LoRaWAN in a smelter IIoT deployment, assessing packet delivery ratio (PDR), throughput, fairness, energy consumption and scalability under varying node densities and gateway configurations. Single-gateway scenarios with 100, 500, and 1000 nodes, and seven-gateway scenarios with 1000 and 2100 nodes, are evaluated as communication distances increase. The results indicate that while throughput and fairness remain comparable across approaches, RSrSF-LoRa improves alarm message reliability in dense single-gateway deployments, extending the acceptable PDR from 700 m to 900 m. Alarm nodes in RSrSF-LoRa consume slightly more energy due to reserved transmission, but overall energy consumption remains comparable. These findings provide design insights for reliable and energy-aware industrial IoT networks in smelter environments. Full article

The growing demand for clean-label, high-quality, and sustainable meat products has increased interest in non-conventional processing technologies as alternatives to conventional processing methods. Therefore, this review aims to critically evaluate the technological advances, practical benefits, limitations, and industrial implementation potential of cold plasma, high hydrostatic pressure, ultrasound, microwave processing, and ohmic heating in meat and meat products. Studies published between 2016 and 2026 were analyzed, with emphasis on mechanisms of action, effects on physicochemical and microbiological properties, processing performance, and evidence of industrial applicability. Current evidence indicates that these technologies have progressed beyond laboratory-scale investigations in several applications, with HHP showing the highest level of commercial adoption, particularly in ready-to-eat meat products, while ultrasound, cold plasma, microwave processing, and ohmic heating exhibit different degrees of pilot- and industrial-scale development depending on the application. These technologies can enhance microbial safety, improve techno-functional properties, optimize processing efficiency, and contribute to shelf-life extension while reducing reliance on synthetic additives. However, their effectiveness is strongly influenced by processing conditions, product composition, economic feasibility, and technology-specific limitations. Reported challenges include lipid oxidation, color deterioration, texture modifications, heating non-uniformity, high implementation costs, limited process standardization, and regulatory uncertainties. Overall, recent advances demonstrate meaningful progress toward industrial application, but the degree of technological maturity varies substantially among technologies and applications. Further research should prioritize industrial-scale validation, process standardization, techno-economic assessment, regulatory harmonization, and consumer acceptance to facilitate broader commercial adoption. Full article

The application of natural colorants in cheese manufacture is gaining increasing interest as an alternative to synthetic additives. This study investigated the incorporation, stability, and technological effects of blackcurrant (Ribes nigrum L.) anthocyanins on semi-hard Trappist cheese during eight weeks of storage under simulated commercial refrigerated display conditions. Cheese samples were soaked in natural blackcurrant juice for seven days and subsequently evaluated for anthocyanin composition, color characteristics, texture properties, microbiological quality, and sensory acceptance. HPLC analysis confirmed the successful incorporation of blackcurrant anthocyanins into the cheese, with delphinidin-3-rutinoside(D-3-R) being the predominant compound. D-3-R concentration decreased from 20.23 to 5.88 mg/100 g dry matter during storage, corresponding to an approximately 71% reduction, while cyanidin-3-rutinoside content became below the detection limit by week 8. Significant changes were observed in all quantified anthocyanins (p ≤ 0.05), indicating progressive pigment degradation. The maximum image-based color difference reached ΔE = 38.20 under standardized imaging conditions. Interestingly, color development followed a biphasic pattern, characterized by initial pigment redistribution and color intensification despite decreasing anthocyanin concentrations, followed by progressive color fading associated with anthocyanin degradation. Texture analysis revealed significant storage-related changes in the mechanical properties of the rind, suggesting structural reorganization of the cheese matrix. Microbiological analyses demonstrated the persistence of technologically important lactic acid bacteria throughout storage, indicating compatibility of the treatment with the cheese microbiota. Sensory evaluation performed by 60 consumers showed high acceptance of blackcurrant-treated cheese. The results indicate that blackcurrant juice soaking is an effective strategy for producing naturally colored semi-hard cheeses enriched with anthocyanins while maintaining desirable microbiological, textural, and sensory characteristics. The observed degradation kinetics under the storage conditions applied in this study emphasize the importance of optimizing storage conditions for anthocyanin-enriched dairy products. Full article