Search Results (7,371)

Membrane technology is a highly efficient, cost-effective, and chemical-free process, leading to its widespread application across various fields. However, the high capital cost of traditional ceramic benchmarks remains a barrier. This study addresses this challenge by engineering a low-cost, waste-derived geopolymeric membrane functionalized with a silver molybdate (Ag₂MoO₄) catalytic coating for the removal of trimethoprim (TMP), a persistent emerging contaminant. Systematic filtration assays for the removal of TMP (100 mg·L⁻¹, pH 4) revealed the role of the Ag₂MoO₄ layer as a performance intensifier, yielding a 26% increase in initial permeate flux and a 33% improvement in the selectivity compared to the pristine support, while maintaining robust rejection efficiency. Comprehensive characterization attributes these enhancements to synergistic effects between increased surface hydrophilicity and favorable solute–catalyst interfacial interactions. Furthermore, a fouling analysis using Hermia’s models indicated the simultaneous operation of multiple blocking mechanisms, a phenomenon linked to the non-uniform nature of the coating and subsequent formation of preferential flow paths. Overall, the incorporation of the silver molybdate coating effectively improved the membrane’s flux performance and selectivity. These findings demonstrate that integrating catalytic coatings onto waste-based geopolymer frameworks provides a scalable, circular-economy-aligned strategy for advanced wastewater treatment, balancing high-flux performance with the efficient removal of recalcitrant pharmaceuticals. Full article

The growing need for remote patient monitoring, accelerated by the global pandemic and an aging population, necessitates the development of advanced non-contact technologies for measuring vital signs. In this study, an integrated, non-contact system for accurately measuring heart rate (HR) and body temperature (BT) is developed and validated. The proposed system combines a 60 GHz radar sensor and infrared (IR) sensor for HR and BT measurements, respectively, enhanced with advanced signal processing and an AI-based computer vision algorithm. A Window Filter and a Peak Uniformity algorithm were applied to the raw radar signal to mitigate noise and motion artifacts. For Temp measurement, an IR sensor with a narrow five-degree field of view (FOV) was integrated with a YOLO Pose-based tracking system using a camera and servo motors to automatically orient the sensor towards the user’s face. The system was validated with 30 healthy adult participants, benchmarked against a MAX30102 PPG sensor and Braun ThermoScan 7 for BT and BT measurements, respectively. The advanced signal processing reduced the HR Mean Absolute Error from 13.73 BPM to 5.28 BPM (p = 0.002), while the AI-guided IR sensor reduced the BT MAE from 4.10 °C to 1.64 °C (p < 0.001). These findings demonstrate that integrating 60 GHz radar with AI-driven tracking provides a promising approach for home-based trend monitoring. Full article

Background/Objectives: Online sexual violence is an increasingly prevalent form of gender-based harm facilitated by digital technologies, with significant consequences for the health, well-being, and rights of adult women. Despite growing attention to this phenomenon, women’s lived experiences remain underexplored, particularly regarding sexual consent and institutional responses. This study aimed to examine how adult women experience online sexual violence, how consent is negotiated or constrained in digital contexts, and how coping and institutional mechanisms are perceived. Methods: A qualitative study with a hermeneutic phenomenological approach was conducted. Data were collected through three focus groups with 23 women aged 21 to 42 years who were active users of social media. Results: Participants reported diverse forms of online sexual violence, including unsolicited sexual messages and images, persistent harassment, coercion, blackmail, and threats. Sexual consent was often undermined by emotional manipulation, social pressure, and fear, placing women in vulnerable positions. These experiences negatively affected well-being, contributing to anxiety, reduced self-esteem, fear, and difficulties in sexual and emotional relationships. Coping strategies were mainly individual, such as blocking perpetrators or reporting content, while social support was frequently perceived as insufficient. A generalized distrust of institutional responses emerged, with formal mechanisms viewed as ineffective or inaccessible. Conclusions: For the study participants, online sexual violence is increasingly normalized and concealed within digital environments, reinforced by anonymity and impunity. The findings highlight the need for continued research and the development of interventions that include early sexual and emotional education, awareness-raising initiatives, digital regulation, specialized professional training, and the strengthening of victim-centered support networks. Full article

With the increasing consumer demand for high-quality lamb, crossbreeding has become a key technology for improving the production performance and meat quality of sheep. To evaluate the meat quality advantages and characteristics of Suffolk (SFK) and Hu sheep (HH) and their F₁ crossbreds (SH), thirty-six 3-month-old male lambs of SFK (n = 12), HH (n = 12), and SH (n = 12) were selected and raised in individual pens under the same nutritional and management conditions. After standardized feeding until 6 months of age, the Longissimus dorsi muscle was collected to determine meat quality traits, amino acid and fatty acid profiles, and volatile flavor compounds. The results indicated that the L*, a* and b* values of the SH group were significantly lower than those of the parental breeds (p < 0.05), with tenderness being intermediate between the two parent breeds. Notably, drip loss and cooking loss were significantly lower in the SH group (p < 0.05), indicating superior water-holding capacity. In terms of amino acid profiles, the contents of non-essential amino acids (NEAAs) and sweet-tasting amino acids in the SH group were significantly higher than those of the parent breeds (p < 0.05), with the overall profile meeting the FAO/WHO ideal protein pattern. Analysis of fatty acid profiles revealed that the SH group had significantly lower total saturated fatty acids (SFAs) (p < 0.05) and significantly higher levels of functional fatty acids (such as CLA), resulting in a significantly higher UFAs (unsaturated fatty acids)/SFAs (saturated fatty acids) ratio (p < 0.05) and superior nutritional value of fat. Furthermore, 32 volatile flavor compounds were detected in the SH group; among them, key aroma-active compounds such as isoamyl formate, 3-methyl-1-butanol, and acetoin were significantly higher than in the parental breeds (p < 0.05), contributing to a unique flavor profile. Consequently, this study systematically reveals the advantages of Suffolk × Hu F₁ crossbreds in terms of meat quality, nutritional value, and flavor characteristics, providing fundamental data for the optimization of crossbreeding systems, breeding selection, and the quality improvement of sheep meat products. Full article

Based on data from 208 students involved in entrepreneurship studies at Tecnológico de Monterrey, Mexico, this paper examines whether prior experience with AI, expectations, gender, and age reinforce future AI use. To achieve this objective, we applied binary logistic regression with random oversampling to balance the dataset. We complemented it with additional model performance metrics, including the confusion matrix, sensitivity, specificity, and area under the ROC curve. The results show that prior experience with AI, age-related technology use, and positive expectations regarding AI are associated with a higher likelihood of reinforcing future AI use. In terms of gender, the results indicate a gender gap favoring women, who are more likely to use AI when they perceive greater utility and confidence, as well as a stronger desire to succeed. Full article

Digital literacy is widely promoted as enabling later-life inclusion, but its potential to generate trust-related vulnerabilities remains insufficiently examined, particularly in rapidly ageing societies. Using nationally representative data from the 2022 China Family Panel Studies including 1583 adults aged 60 and above, this study examines whether digital literacy is associated with older adults’ trust in strangers, which is interpreted here as a form of trust vulnerability in low-verifiability interactions. In this study, trust vulnerability is operationalised through respondents’ self-reported trust in strangers, while digital literacy is operationalised through behavioural competences spanning information and data literacy, communication and collaboration, content creation, digital transactions, and problem-solving. OLS regression models with Huber–White robust standard errors are employed. The findings indicate that higher levels of digital literacy are positively associated with stronger trust in strangers, suggesting that competence may heighten older adults’ inclination to trust and increase exposure to digital risks. This association is driven primarily by functional competences, with mobile payment use and problem-solving skills showing the largest and most consistent associations. By contrast, subjective well-being and perceived platform security show no significant mediating roles. The study recommends integrating functional training, trust calibration and risk-recognition education, alongside interpretable and verifiable safeguards that make security more visible to older adults. Full article

Generative Artificial Intelligence (GAI) is rapidly transforming higher education by introducing new mechanisms for supporting the development of advanced cognitive processes and research-related capabilities. This study examines how postgraduate students employ GAI to develop their cognitive and research talent, conceptualized here as higher-order academic skills such as analysis, synthesis, and critical reasoning, across six domains: literature review, theoretical development, research design, data analysis, academic writing, ethical use, and challenges encountered—signaled explicitly rather than listed line by line. We administered a validated multidimensional scale to 214 postgraduate students, and the results indicate a moderate overall use of GAI, with notably high involvement in practices that emphasize ethics and responsibility. Students reported clear cognitive benefits in tasks involving information processing, linguistic refinement, and conceptual clarification while showing caution toward delegating higher-order analytical or theoretical reasoning to AI systems. Key challenges included limited institutional training, concerns about data privacy and academic integrity, and difficulties evaluating the originality and reliability of AI-generated content. Inferential analyses indicated significant differences based on gender, academic level, and general technology proficiency, whereas no differences emerged across age groups, departments, or specializations. Overall, this study demonstrates how GAI can contribute to the development of higher-level cognitive skills and research competencies, with “moderate use” operationalized as consistent but selective engagement across domains, while underscoring the need for structured training, clear guidelines, and teaching approaches that foster the responsible and effective incorporation of AI within postgraduate research. The results highlight practical implications for higher education, including the importance of institutional training programs, governance frameworks for responsible AI use, and pedagogical models that foster critical engagement with GAI. Full article

Primary care clinics represent a promising, yet underutilized, setting for delivering health-focused prevention programming targeting adolescent substance use, sexual assault, and sexual risk behaviors; however, little is known about adolescents’ prior exposure to such messaging. Therefore, the present study examined adolescents’ prior prevention exposure, their perceptions of prevention content, and recommendations for future programs. Semi-structured qualitative interviews were conducted with 25 adolescents (ages 14–18; 56% female, 36% male, 8% gender fluid or Two-Spirit) recruited from primary care and community settings in the southeastern United States. Thematic analysis was used to examine youth exposure to and perspectives on prevention programming. Three core themes emerged: (1) prior exposure to prevention content across topics; (2) appraisal of strengths and limitations within previous programming; and (3) recommendations for what adolescents believe their same-aged peers should know. Participants reported a preference for technology-based programs, criticized interventions exclusively promoting abstinence and negative consequences, and emphasized needing additional information on sexual consent. Adolescents in primary care settings report inconsistent exposure to prior prevention, most centering abstinence and negative consequences, rather than inclusive harm-reduction approaches. Findings highlight a structural gap in exposure to comprehensive adolescent prevention programming and position pediatric primary care as a uniquely flexible and developmentally congruent setting for delivering integrated, harm-reduction-oriented prevention interventions. These findings also further support the development of scalable, technology-driven prevention tools that can be implemented within pediatric primary care settings to improve accessibility reach, engagement, and relevance. Full article

Understanding the socio-demographic drivers of residential energy-saving behavior is critical for designing effective energy policies and technologies. This study applies a Multiple Indicators, Multiple Causes (MIMIC) model to examine how individual characteristics are associated with two latent constructs: energy concern and smart-home interest and usage. Using survey data collected from urban residents in Guangdong Province (N = 261), structural equation modeling was employed to assess both measurement and structural components of the model. The results show that income is positively associated with both energy concern and smart-home interest and usage, whereas being a bill payer is negatively related to both. Gender also plays a role, with females reporting higher energy concern. Other factors, such as age, education, and time spent at home, did not show significant effects. The model showed acceptable global fit indices; however, the reliability and convergent validity of the latent constructs were limited. Accordingly, the findings should be interpreted as exploratory associations observed within this sample and may serve as a basis for future research on segmentation in similar urban contexts. Full article

The objective of this paper is to propose a sociological and interdisciplinary framework for analyzing the digitization of emotions in adolescence. This contribution aims to promote theoretical reflection and inform educational and political interventions in the digital age, framing adolescents’ digital experiences as emotionally embodied and socially integrated processes. These aspects are of paramount importance due to the rapid proliferation of digital technologies and artificial intelligence, which have precipitated a profound transformation in the emotional, relational, and educational experiences of adolescents. The role of digital and AI-based environments in mediating communication is expanding beyond the scope of simple facilitation. These environments are increasingly implicated in the production, modulation, and regulation of emotions, thereby influencing developmental trajectories and identity formation processes. This phenomenon is theorized as a socio-technical process, wherein emotions are embodied, narrated, and governed within digital environments. The article introduces the concept of digital emotional embodiment, drawing on the sociology of emotions, theories of embodiment, and critical perspectives on artificial intelligence. Specifically, the concept refers to the manner in which adolescents experience and express emotions through avatars, images, emojis, algorithmic feedback, and AI-mediated interactions. Therefore, it is imperative to underscore the evolution of empathy, which is progressively configured as a virtualized and datafied process, diverging from the tradition established by Hume and characterized by sympathy. In contemporary processes, shaped by the logic of platforms, recommendation systems, and emotionally reactive technologies, conventional emotional concepts have undergone deconstruction, and digital constructs are undergoing a gradual restructuring. In this context, AI systems do not merely reflect adolescents’ emotions but rather actively contribute to the construction of emotional narratives, influencing emotional regulation, social connection, and future orientation. Digital environments have been shown to encourage emotional expressiveness, experimentation, and inclusivity. Conversely, they have the capacity to encourage emotional standardization, dependency, and forms of affective vulnerability, particularly during a sensitive developmental stage such as adolescence. Full article

The rapid spread of misinformation on social media has emerged as a major societal issue. Over 40% of British social media news-sharers admitted they had shared inaccurate or fake news. The extensive distribution of false information causes public trust deterioration while modifying public opinions and potentially destabilizing social and political systems. There are profound challenges due to this hard-to-detect, hard-to-stop reality and the financials and societal implications are remarkable. As an attempt to limit the challenges created from misinformation this paper introduces some preliminary work on detection of fake news and verification of their reliability based on online content. Large language models (LLMs) are being used along with natural language processing (NLP) techniques to evaluate news articles through their linguistic and contextual characteristics. Several models are compared on how they can typically identify typical indicators of misinformation through the analysis of extensive verified datasets to develop an ability to classify content as authentic or fabricated. This work has been through thorough testing to determine its operational effectiveness and dependability after completion. We present a relatively easy-to-use tool which enables a wide range of people also for those without a background in computer science to easily verify news accuracy before sharing or trusting it. This work could help to stop false information from spreading while promoting fact-based discussions and improving digital literacy skills. The research demonstrates how technology fights the fake news crisis to create an informed digital environment which supports public conversation protection and information integrity in the modern digital age. Full article

Promoting resilience, increasing productivity and sustainability, and profit maximization remain key challenges facing farmers globally. These are exacerbated by factors such as climate change, low to no access to technological advancement, financial constraints, poor technical and management skills, inadequate government support, and limited access to resources. However, there are diverse strategies that abound, including on-farm diversification, that farmers could leverage on to address these numerous and complex challenges. This study investigated the determinants of on-farm diversification strategies among smallholders in Mpumalanga Province. The study employed a quantitative approach using closed-ended survey questionnaires to elicit information from a total of 465 farmers who were randomly sampled from a total population of 14,411. The data gathered were analysed using descriptive statistics to determine the on-farm diversification strategies employed by farmers and the factors influencing the use of these strategies. A binary logistic regression model was employed to establish the relationship between on-farm diversification strategies and the determining factors. More than half of the farmers were female (51.8%), with only 48.2% male. The majority (59.1%) of the farmers were between the ages of 36 and 60, with only 20.2% youth participation in farming. Slightly more than half (50.8%) of the farmers practise mixed farming as their on-farm diversification strategy, while only 4.3% of the farmers practise mono-cropping. The study identified significant variables such as level of education (p = 0.001), secondary source of income (p = 0.057), farmland size (p = 0.022), number of farm assistants (p = 0.016), and on-farm diversification awareness as key determinants of on-farm diversification among smallholder farmers in Mpumalanga Province. Therefore, it is recommended that policies within the agricultural sector be revised to encourage on-farm diversification in order to motivate farmers to transition to agripreneurship for poverty alleviation, food security and rural economic development (RED). Full article

In conditions of liquid modernity, marked by accelerated technological change, the virtualization of essential services, and the erosion of stable institutional support, digital participation in later life is less a matter of initial access than of continuously renegotiating engagement within unstable socio-technical environments. While established technology adoption models such as TAM, UTAUT, and STAM have provided robust explanations of cognitive and age-related determinants of adoption, they remain limited in accounting for the relational processes through which technological engagement is learned, stabilized, and sustained over time. This article advances a relational perspective on technology appropriation by foregrounding the role of warm experts—trusted informal supporters who mediate learning, interpretation, and adaptation in everyday contexts. Moving beyond dyadic understandings of assistance, the paper conceptualizes mediation as a distributed ecology of roles embedded within relational networks that both enable and constrain digital inclusion. Building on this perspective, the study proposes the Relational Technology Appropriation Model (RELTAM) as a general multi-level architecture integrating individual determinants, relational mediation processes, and network-level support configurations within a dynamic framework of appropriation. The Relational (Older Adult) Technology Appropriation Model (REL(OA)TAM) is introduced as a context-specific instantiation of this broader framework, calibrated to the distinctive conditions of later life. By incorporating temporal instability and mediation ecologies as structural components, REL(OA)TAM offers a socially grounded account of digital inclusion as an ongoing process of adaptive negotiation within the fluid and uncertain conditions of liquid modernity. Full article

Urbanization fundamentally fractures the natural water cycle, leading to a cascade of interconnected problems including increased flood risk, degraded water quality, stressed groundwater resources, and inefficient distribution networks. Traditional, fragmented management approaches that address these issues in isolation have proven inadequate. This research argues for a paradigm shift towards an Integrated Urban Water Management (IUWM) framework anchored in the concept of the “river-aquifer-pipe network continuum”, treating these components as a single, dynamic hydrological and infrastructural entity. Drawing upon a series of detailed case studies from Eastern Romania, this paper synthesizes the systemic impacts of development across the entire urban water system. Evidence from the Prut, Olt, and Bahlui river basins demonstrate how channelization exacerbates flood peaks and leads to severe biochemical degradation. Hydrogeological modeling of the Gherăești-Bacău wellfield reveals the vulnerabilities of over-extraction, while analysis of the Iași water network highlights the challenge of water losses in the aging infrastructure. In response, a modern, multi-tool approach is consolidated into a practical, three-stage framework for action: Diagnose, Prescribe, and Optimize. This framework advocates for (1) a comprehensive diagnosis using a suite of predictive numerical models (a “digital twin”); (2) the prescription of foundational, nature-based solutions, such as floodplain restoration, to heal core ecological functions; and (3) the continuous optimization of engineered infrastructure using smart, real-time control technologies. The synthesis concludes that an integrated, data-driven, and collaborative approach is the only sustainable path forward. Future research should focus on formally coupling these diagnostic models to create true Digital Twins of urban water systems—an essential step towards building resilient, water-secure cities for the 21st century. Full article

Anterior cruciate ligament (ACL) injuries frequently lead to persistent gait asymmetries, posing challenges for early rehabilitation and functional status. Comprehensive monitoring of pelvic gait symmetry during rehabilitation remains underexplored. This study evaluated post-operative functional status using an integrated monitoring approach combining pelvic-mounted inertial measurement unit (IMU) sensors with standardized clinical assessments in 32 individuals (9 women, 23 men; aged 19–64) following ACL reconstruction with patellar tendon autografts. IMU recordings captured pelvic oscillations in the sagittal, frontal, and transverse planes during standardized 10 m walking tests, providing objective digital biomarkers of gait symmetry. Clinical assessments included knee range of motion, thigh circumference, swelling, and pain using a modified 0–20 visual analogue scale (VAS). Across the early rehabilitation period, VAS scores decreased from 13.6 to 3.0, knee swelling from 2.88 cm to 1.09 cm, knee extension deficit from −9.38° to −2.03°, and knee flexion improved from 61.56° to 98.75°. Thigh hypotrophy increased from 1.13 cm to 2.53 cm. Pelvic oscillations improved in all planes (sagittal: 36.2 to 49.2; frontal: 71.9 to 92.2; transverse: 73.4 to 90.9), reflecting progressive restoration of gait control as patients transitioned from crutch-assisted to independent walking. The integration of wearable sensor data with clinical metrics enabled sensitive tracking of pelvic gait symmetry and functional status, demonstrating the utility of technology-supported monitoring to support individualized clinical assessment and early-phase monitoring following ACL reconstruction. Full article