Search Results (7,735)

The living lab Enrekang, established in 2019 in South Sulawesi, Indonesia, was created to strengthen rural communication and support collaborative innovation across agriculture, livestock, environment, and extension services. Its flagship initiative, the Digital Farmer Field School (DFFS), was co-designed as a digital tool to improve farmers’ access to practical and locally adapted information. The early phase of collaboration generated strong momentum, culminating in a functional prototype tested with farmer groups by 2022. However, progress slowed soon after, revealing a gap between the initiative’s early promise and its subsequent stagnation. This qualitative case study, conducted between December 2024 and June 2025, draws on document reviews, focus group discussions, semi-structured interviews, and participant observations to analyze how the slowdown emerged and how it altered communication, coordination, and relational expectations among participating actors. Applying the governance-of-innovation lifecycle and a social capital lens, the study shows that political transitions, leadership turnover, staff rotation, and the absence of policy and budgetary anchoring disrupted coordination routines and reduced cross-sector interaction, even as motivation among farmers and frontline staff remained high. The case also highlights the novelty and complexity of the living lab approach, which introduced coordination demands and institutional unfamiliarity that local systems were not yet equipped to absorb. This study contributes to ongoing debates on collaborative innovation by illustrating the vulnerability of living labs when governance arrangements do not evolve alongside innovation milestones. Sustaining similar efforts requires formal anchoring, adaptive coordination, and mechanisms that protect collaboration across political and institutional transitions. Full article

Post-stress cognitive impairment (PSCI) is defined as a persistent neuropsychiatric condition characterized by deficits in memory consolidation, executive functioning, and environmental interaction following exposure to violent stress. Despite its high incidence, PSCI remains underdiagnosed and lacks effective therapeutic strategies, posing a substantial societal burden and highlighting a critical gap in neuropsychiatric research. A major constraint in mechanistic studies is the persistent reliance on conventional paradigms, notably the Y-maze and novel object recognition test. Their limited sensitivity and poor translational relevance to human cognitive dysfunction, compounded by slow methodological innovation, significantly impede progress. Furthermore, the specific brain regions or neuronal populations contributing to PSCI pathogenesis are insufficiently explored. To address this, we assessed post-stress cognitive impairment in mice using a triple approach: Skinner box assays, traditional behavioral paradigms, and integrated 3D ethological analysis. This multi-method framework provides novel insights for refining animal models and advancing mechanistic understanding. Using c-Fos-based whole-brain screening, we identified the dentate gyrus (DG) as a key region involved in PSCI. Stress caused by violence markedly increased activity in DG CaMKII-expressing neurons. Chemogenetic inhibition of these neurons effectively alleviated stress-induced mild cognitive impairment phenotypes. In summary, by applying novel behavioral assessment tools, this study demonstrates that DG CaMKII neurons play a critical role in regulating post-stress cognitive impairment. Full article

This study investigates the effectiveness of cold atmospheric plasma (CAP) treatment for improving the microbiological and physicochemical quality of wastewater generated in tourism-affected coastal regions. Experiments were performed on influent and effluent samples from the Ravda Wastewater Treatment Plant (WWTP) collected in April, August, and November 2024, representing different seasonal loading conditions. The plasma pre-treatment of influent aimed to minimize toxic micropollutants that inhibit activated sludge activity, reduce pathogenic and opportunistic microorganisms, and enhance oxidative potential before biological processing. The post-treatment of effluent focused on the elimination of residual pathogens, mainly Enterobacteriaceae, and the oxidative degradation of xenobiotics resistant to conventional treatment. Combined fluorescent (CTC/DAPI) and culture-based analyses were used to assess microbial viability and activity. Plasma exposure (1, 3 and 5 min) caused measurable changes in metabolic potential and bacterial abundance across all sampling periods. The results demonstrate that 1 min CAP treatment does not increase pathogen removal, but enhances oxidation capacity of the influent, while 3 min of CAP treatment ensures the disinfection of the effluent. Both can be combined to improve the effluent safety prior to Black Sea discharge. CAP is showing strong potential as a sustainable technology for wastewater management in tourism-intensive coastal zones. Full article

Background/Objectives: Neuroblastoma (NB) is the most common extracranial solid tumor in children and accounts for 12–15% of pediatric cancer-related deaths. Current multimodal therapies lack specific cellular targets, causing systemic toxicity and drug resistance. The development of innovative tumor-targeted nanoformulations might represent a promising approach to enhance NB diagnosis and antitumor efficacy, while decreasing off targets side effects. Fibronectin extra-domain B (FN-EDB) is upregulated in the tumor microenvironment. Methods: FN-EDB expression was evaluated by immunohistochemical staining in cell line-derived and tumor patient-derived animal models of NB. A gold nanoparticle, decorated with an antibody (Ab) recognizing FN-EDB (L19-AuNP) was developed by the company Nano Flow and its tumor binding was tested by ELISA in vitro and in patient-derived xenograft (PDX) models of NB by photoacoustic imaging in vivo. Results: All animal models of NB used have been shown to express FN-EDB. L19 Ab demonstrated excellent binding specificity to FN-EDB both when used in free form and after conjugation to AuNP. Compared to the non-functionalized (no Ab L19-coupled) AuNP, which showed an increase in PDI and zeta potential over time, making them unsuitable for use in in vivo studies, L19-AuNP demonstrated good stability. In vivo, L19-AuNP specifically homed into PDX models of NB, accumulating better in tumors expressing higher levels of FN-EDB. Negligible distribution to healthy organs occurred. Conclusions: In this preliminary study, L19-AuNP was shown to be a novel diagnostic tool specifically for binding NB expressing FN-EDB, paving the way for the development of theranostic nanoformulations co-encapsulating gold moiety and standard-of-care therapy for NB. Full article

In this research, we assess the feasibility of employing hybrid friction stir channeling (HFSC) to produce composite panels that combined an 8 mm thick AA6082-T6 aluminum alloy and 5 mm thick glass-fiber-reinforced Noryl GFN2. HFSC is an innovative solid-state technology that combines both friction stir joining and channeling characteristics, which enable the generation of integral internal channels while joining different components. A parametric study was outlined to explore the effects of the travel speed, probe length, and tool plunging on the resulting composite panels. The resulting composite panels were subsequently subjected to a comprehensive analysis encompassing exterior ceiling quality, internal channel, and joining interface morphology. Depending on the processing parameters, the geometry of the channels was found to be quasi-rectangular or quasi-trapezoidal, with significant variability on cross-sectional area, resulting in hydraulic diameters ranging from 1.2 to 2.9 mm. The joining interface was characterized by a concavity of aluminum that was extruded downwards into the polymeric molten pool, which was clinched after polymeric re-solidification. The experimental results prove the ability to join metals and polymers while creating an integral channel in a single process step using HFSC. Despite the positive effect of irregular shaped channels on heat exchange, the numerical models evidenced a detrimental effect of 14.3 and 16.3% on ultimate tensile and flexural loads, respectively. This way, this fabrication technology evidenced promising characteristics that are suitable for manufacturing thermal management systems such as conformal cooling for plastic injection molding or battery trays for EVs. Full article

Wine, as a high-value product, is vulnerable to counterfeiting. To tackle increasingly sophisticated fraud, innovative analytical approaches are required. However, they must undergo rigorous validation. Proton nuclear magnetic resonance spectroscopy (¹H-NMR) is intrinsically quantitative, reproducible, and fast, making it a promising tool for official control. This study presents the development and validation of a standardised and fully automated workflow for the quantification of 20 oenologically relevant compounds, including organic acids, sugars, alcohols, esters, phenolics, and an alkaloid. The method combines optimised sample preparation, external quantification standards, spectrometer calibration, and a dedicated R package (RnmrQuant1D) for fully automated spectral processing, enabling high-throughput and operator-independent analysis. Validation was performed under intermediate precision according to OIV metrological standards, evaluating accuracy, precision, robustness, limits of quantification, and measurement uncertainty. The results demonstrated excellent linearity, trueness, and reproducibility, matching the targeted analytical performance. Measurement uncertainties were estimated both by conventional linear modelling and by a dynamic approach better suited to detection limits. The workflow is easy to implement, requires minimal sample consumption, and substantially reduces operator bias. Beyond validating a robust method, this study provides a framework for harmonised, transferable ¹H-NMR workflows that could support large-scale databases, integration with chemometric models, and ultimately, ¹H-NMR’s recognition as a relevant method for wine authentication and quality control. This work fills a crucial gap in wine analysis by uniting practical application and rigorous methods, enabling broader adoption in control laboratories worldwide. Full article

The packaging sector is undergoing a significant transformation driven by increasing environmental challenges and new European regulatory frameworks. The Packaging and Packaging Waste Regulation (PPWR), following the European Green Deal and Circular Economy Action Plan, introduces five strategic priorities: waste prevention, recyclability, recycled content, compostable materials, and reusable systems. This framework aims to systematically review the current state of academic research in relation to these five intervention areas, assessing the extent to which the scientific literature supports the regulation’s circular economy objectives. The PPWR sets guidelines for key aspects such as packaging treatment, recycling targets, Extended Producer Responsibility (EPR) and material optimization. These aspects are strongly linked to market dynamics, driving innovation and new developments in packaging design. This study aims to provide a comprehensive overview of the industry’s evolution, with a focus on the crucial role of the circular economy in addressing the persistent issue of packaging waste. By conducting a systematic literature review using the PRISMA method, the research explores the relationship between the regulation’s structural design and the European Commission’s priority areas. The results reveal that waste prevention and reusability are the most researched areas, particularly concerning environmental assessments and regulatory tools like EPR. Additionally, while recyclability has been studied from technical and environmental perspectives, there is still a lack of research on how it connects with supply chain and material market trends. Strengthening these connections could significantly enhance recycling efficiency and improve the sustainability of packaging systems. Furthermore, financial incentives and policy strategies could play a key role in facilitating the transition to a circular economy. Addressing these gaps will foster a more integrated understanding of sustainable packaging solutions. Full article

Electronic nicotine delivery systems (ENDS) are perceived as safer than conventional smoking, but there is limited knowledge about their risks. This quasi-experimental study aimed to evaluate the perceived usefulness and acceptability of an innovative information strategy concerning the potential harms of e-cigarettes among university students in oral health programs in Mexico and Colombia. The methodology involved implementing a three-phase strategy, utilizing an interactive, self-managed educational game (bowling game) developed on the Genially digital platform and anchored in scientific evidence. Of the 230 invited students, 213 consented to participate in the initial phase. High engagement was demonstrated in the second phase, with 94.8% (n = 203) of students using the game for an average of 5 min and 16 s, and 25.62% answering all embedded knowledge questions correctly on the first attempt. Results from the acceptability phase (n = 36) were highly positive, with 72.2% of IUVA students and 19.4% of BUAP students agreeing the strategy was both entertaining and useful for knowledge improvement. The findings suggest that gamified and interactive digital learning strategies are highly accepted and strengthen academic commitment and knowledge acquisition regarding the public health risks of e-cigarettes. Further longitudinal studies are necessary to evaluate the sustained impact of these digital educational tools. Full article

Two-photon polymerization (2PP) is revolutionizing micro- and nanoscale manufacturing by enabling true 3D fabrication with feature sizes far below the diffraction limit—capabilities that traditional lithography cannot match. By using ultrafast femtosecond laser pulses and nonlinear absorption, 2PP initiates polymerization only at the laser’s focal point, offering unmatched spatial precision. This paper highlights key advancements driving the field forward: the development of new materials engineered for 2PP with improved sensitivity, mechanical strength, and the introduction of high-speed, parallelized fabrication strategies that significantly enhance throughput. These innovations are shifting 2PP from a prototyping tool to a viable method for scalable production. Applications now range from custom biomedical scaffolds to complex photonic and metamaterial structures, demonstrating their growing real-world impact. We also address persistent challenges—including slow writing speeds and limited material options—and explore future directions to overcome these barriers. With continued progress in materials and hardware, 2PP is well positioned to become a cornerstone of next-generation additive manufacturing. Full article

The integration of Building Information Modeling (BIM) and Digital Twin (DT) has emerged as an innovative tool in the architecture, engineering, and construction (AEC) domain. To successfully utilize BIM and DT, it is crucial to update the 3D model in a timely and accurate manner. However, limitations remain when handling massive point clouds to reconstruct complex indoor structures with varying ceiling and floor heights. This study proposes a semi-automatic 3D model reconstruction method. First, point clouds are aligned with 3D Cartesian axes and the spatial extent of the indoor space is measured. Subsequently, the point clouds are projected onto each coordinate plane to hierarchically extract structural elements of a building component, such as boundary lines, rectangles, and cuboids. Boolean operations are then applied to the cuboids to reconstruct a 3D wireframe model. Additionally, wall points are segmented to identify openings like doors and windows. For validation, the method was applied to three typical building components with Manhattan-world structures: an office, a hallway, and a stairway. The reconstructed models were evaluated using reference points, resulting in positional accuracies of 0.033 m, 0.034 m, and 0.030 m, respectively. Finally, the resulting wireframe model served as a reference to build an as-built BIM model. Full article

Oxidative stress (OS) is increasingly recognized as a dynamic disturbance of cellular redox networks rather than a simple imbalance between oxidants and antioxidants. In this context, ferroptosis and cuproptosis—two regulated and metal-dependent forms of cell death—emerge as key mechanisms linking OS to metabolic dysfunction, inflammation, and tissue injury. This review integrates findings from biochemical, lipidomic and metallomic studies to describe how lipid peroxidation (LPO), glutathione (GSH)–Glutathione Peroxidase 4 (GPX4) activity, ferritinophagy, copper-induced mitochondrial protein lipoylation, and altered communication between organelles generate distinct redox signatures across diseases. By examining cutaneous, metabolic, cardiovascular, infectious, neurodegenerative, and oncologic conditions, we outline the shared redox pathways that connect iron- and copper-dependent cell death to systemic inflammation, immune dysregulation, and chronic tissue damage. Common oxidative markers—such as oxidized phospholipids, lipid aldehydes including 4-Hydroxynonenal (4-HNE) and malondialdehyde (MDA), and systemic metal imbalance—are highlighted as potential indicators of disease severity and as emerging therapeutic targets. We also discuss innovative analytical tools, including redox lipidomics, metallomic profiling and artificial-intelligence (AI)-based classification approaches, which improve the characterization of redox vulnerability and may guide the development of precision redox therapies. Overall, ferroptosis and cuproptosis represent unifying mechanisms that connect OS to multisystem disease and provide new opportunities for diagnostic refinement and targeted antioxidant-based interventions. Full article

Background/Objectives: The rapid evolution of digital technologies has significantly transformed prosthodontic workflows, improving clinical precision, communication, and patient satisfaction. However, the extent to which dental professionals perceive, integrate, and evaluate these technologies remains insufficiently standardized. This study aimed to develop and validate a questionnaire for assessing perceptions, attitudes, perceived advantages, barriers, and future intentions regarding the use of digital technologies in prosthodontic practice. Methods: A cross-sectional survey was conducted among 420 dental professionals (305 dentists and 115 dental technicians) from Northeastern Romania. The 27-item questionnaire, structured on five theoretical dimensions, was distributed online via the Survio platform. Internal consistency was assessed using Cronbach’s Alpha, and construct validity was analyzed through Exploratory Factor Analysis (Principal Component Analysis with Varimax rotation). Conclusions: Cronbach’s Alpha coefficients ranged from 0.700 to 0.799 across the five dimensions, indicating acceptable to very good internal reliability. The Kaiser–Meyer–Olkin value (0.646) and Bartlett’s Test of Sphericity (p < 0.001) confirmed data suitability for factor analysis. The validated questionnaire represents a reliable and conceptually coherent tool for evaluating professional perspectives on digitalization in prosthodontics. Its application can inform educational strategies, guide institutional investments, and support a balanced transition toward integrated digital workflows in clinical and laboratory settings. Full article

Mothers’ behavior strongly influences children’s eating habits, with family attitudes and feeding practices playing a key role in dietary development. In accordance with the previous literature, this study examined these aspects, including also mothers’ use of social media to stay informed about nutrition as an innovative element. The main goal was to validate the Italian version of the PSEPAD scale (Parental Self-Efficacy for Promoting Healthy Physical Activity and Dietary Behaviors in Children), which is a valid and reliable tool for assessing parental self-efficacy in encouraging healthy lifestyles in children, through exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). The sample was composed of 217 mothers. Results were interpreted through groups comparisons (chi-square, ANOVA, and t-test). The findings confirmed the central role of mothers in managing children’s diets and using strategies against picky eating behaviors. The study also highlighted the growing use of social media among mothers, especially younger ones, as a source of nutritional information, meal planning, and peer support, despite a generally low level of satisfaction with the content available on pediatric nutrition. Finally, the results showed a positive link between maternal self-efficacy and healthier child behaviors: mothers with higher self-esteem and confidence were more effective in promoting healthy habits. These findings underscore the importance of targeted interventions to strengthen maternal self-efficacy and the development of digital tools to support healthy family lifestyles. Full article

This paper discusses the evolution of convolutional (CNN) and recurrent (RNN) artificial neural networks in applications for Building Information Modeling (BIM). The paper outlines the milestones reached in the last two decades. The article organizes the current state of knowledge and technology in terms of three aspects: (1) computer visualization coupled with BIM models (detection, segmentation, and quality verification in images, videos, and point clouds), (2) sequence and time series modeling (prediction of costs, energy, work progress, risk), and (3) integration of deep learning results with the semantics and topology of Industry Foundation Class (IFC) models. The paper identifies the most used architectures, typical data pipelines (synthetic data from BIM models, transfer learning, mapping results to IFC elements) and practical limitations: lack of standardized benchmarks, high annotation costs, a domain gap between synthetic and real data, and discontinuous interoperability. We indicate directions for development: combining CNN/RNN with graph models and transformers for wider use of synthetic data and semi-/supervised learning, as well as explainability methods that increase trust in AECOO (Architecture, Engineering, Construction, Owners & Operators) processes. A practical case study presents a new application, Bimetria, which uses a hybrid CNN/OCR (Optical Character Recognition) solution to generate 3D models with estimates based on two-dimensional drawings. A deep review shows that although the importance of attention-based and graph-based architectures is growing, CNNs and RNNs remain an important part of the BIM process, especially in engineering tasks, where, in our experience and in the Bimetria case study, mature convolutional architectures offer a good balance between accuracy, stability and low latency. The paper also raises some fundamental questions to which we are still seeking answers. Thus, the article not only presents the innovative new Bimetria tool but also aims to stimulate discussion about the dynamic development of AI (Artificial Intelligence) in BIM. Full article

This study analyzes how sustainability research in the textile and apparel industry is structured and argues that technological innovation—while essential for sustainable transformation—cannot generate meaningful impact when pursued in isolation. Its effectiveness depends on alignment with environmental assessment, ethical and institutional mechanisms, and circular strategies. A review of 133 publications (2020–2024) examining titles, keywords, abstracts, and conclusions identified these four thematic axes as the core framework shaping current research. Findings show that technological innovation is the most extensively addressed dimension, yet its industrial and policy influence remains limited when not connected to standardized assessment tools, governance systems, or consumer use-phase behaviors. When the four dimensions operate collectively, technological advances achieve stronger empirical validation, institutional coherence, and circular-system integration. By addressing a key gap in prior literature—which has typically examined these dimensions separately rather than as an integrated system—this study clarifies how their coordinated interaction conditions sustainability transition pathways. The integrated framework provides a theoretical basis for understanding constraints and mediators within sustainability transitions and suggests that future research and policy should adopt system-level strategies that intentionally strengthen linkages across the four dimensions to accelerate sustainable transformation. Full article