Search Results (676)

Although beer fermentation has traditionally been carried out with Saccharomyces, the boom in craft brewing has led to the use of non-conventional yeast species for beer production. This group also includes non-Saccharomyces starters, which are commonly used in winemaking and which have different technological characteristics compared to standard representatives of the Saccharomyces genus. One of the important characteristics of the non-Saccharomyces group is the richer enzyme profile, which leads to the production of beverages with different taste and aroma profiles. The aim of this study was to investigate sweet and hopped wort fermentation with seven strains of active dry non-conventional yeasts of Lachancea spp., Metschnikowia spp., Torulaspora spp. and a mixed culture of Saccharomyces cerevisiae and Torulaspora delbrueckii. One ale and one lager active dry yeast strain were used as control strains. The extract consumption, ethanol production, degree of fermentation, pH drop, as well as the yeast secondary metabolites formed by the yeast (higher alcohols, esters and aldehydes) in sweet and hopped wort were investigated. The results indicated that all of the studied types of non-conventional yeasts have serious potential for use in beer production in order to obtain new beer styles. For the purposes of this study, statistical methods, principle component analysis (PCA) and correlation analysis were used, thus establishing the difference in the fermentation kinetics of the growth in the studied species in sweet and hopped wort. It was found that hopping had a significant influence on the fermentation kinetics of some of the species, which was probably due to the inhibitory effect of the iso-alpha-acids of hops. Directions for future research with the studied yeast species in beer production are presented. Full article

The growing interest in probiotic bacteria within the food industry is driven by their recognized health benefits for consumers. However, preserving their therapeutic viability and stability during gastrointestinal transit remains a formidable challenge. Hence, this research aimed to enhance the viability of Lactobacillus reuteri through microencapsulation using a binary polysaccharide mixture composed of low acyl gellan gum (LAG), high acyl gellan gum (HAG), and calcium for the microencapsulation of L. reuteri. To achieve this, the Box–Behnken design was applied, targeting the optimization of L. reuteri microencapsulated to withstand simulated gastrointestinal conditions. The microcapsules were crafted using the internal ionic gelation method, and optimization was performed using response surface methodology (RSM) based on the Box–Behnken design. The model demonstrated robust predictive power, with R² values exceeding 95% and a lack of fit greater than p > 0.05. Under optimized conditions—0.88% (w/v) LAG, 0.43% (w/v) HAG, and 24.44 mM Ca—L. reuteri reached a viability of 97.43% following the encapsulation process. After 4 h of exposure to simulated gastric fluid (SGF) and intestinal fluid (SIF), the encapsulated cells maintained a viable count of 8.02 log CFU/mL. These promising results underscore the potential of biopolymer-based microcapsules, such as those containing LAG and HAG, as an innovative approach for safeguarding probiotics during gastrointestinal passage, paving the way for new probiotic-enriched food products. Full article

This study explores the potential of craft-based activities in the context of special education, focusing on a papier mâché sculpting workshop implemented at the Special Kindergarten of Komotini, Greece, as part of the Horizon Europe Craeft project. The initiative aimed to assess how such creative activities could enhance the learning experience of children with intellectual and motor impairments, foster socialization, and develop fine motor skills. With reference to literature in art therapy, craft education, and inclusive pedagogy, the study applied a mixed-methods approach combining observation, visual analysis, and a survey. The findings indicate that, despite varied levels of participation based on individual needs, all students engaged meaningfully with the materials and activities. School professionals observed increased student engagement, emotional comfort, and communication, while also identifying the activity as well adapted and replicable in similar contexts. The results highlight the value of crafts in special education, not only as a sensory and cognitive stimulus but also as a means of fostering inclusion and self-expression. The study concludes with a call for further research into the role of tactile materials and hand gestures in relation to specific impairments. Full article

This study presents a breakthrough in sustainable injection molding by uniquely combining a backpropagation neural network (BPNN) with particle swarm optimization (PSO) to overcome traditional optimization challenges. The BPNN’s exceptional ability to learn complex nonlinear relationships between six key process parameters (including melt temperature and holding pressure) and product quality is amplified by PSO’s intelligent search capability, which efficiently navigates the high-dimensional parameter space. Together, this hybrid approach achieves what neither method could accomplish alone: the BPNN accurately models the intricate process-quality relationships, while PSO rapidly converges on optimal parameter sets that simultaneously meet strict quality targets (66–70 g weight, 3–5 mm thickness) and minimize energy consumption. The significance of this integration is demonstrated through three key outcomes: First, the BPNN-PSO combination reduced optimization time by 40% compared to traditional trial-and-error methods. Second, it achieved remarkable prediction accuracy (RMSE 0.8229 for thickness, 1.5123 for weight) that surpassed standalone BPNN implementations. Third, the method’s efficiency enabled SMEs to achieve CAE-level precision without expensive software, reducing setup costs by approximately 25%. Experimental validation confirmed that the optimized parameters decreased energy use by 28% and material waste by 35% while consistently producing parts within specifications. This research provides manufacturers with a practical, scalable solution that transforms injection molding from an experience-dependent craft to a data-driven science. The BPNN-PSO framework not only delivers superior technical results but does so in a way that is accessible to resource-constrained manufacturers, marking a significant step toward sustainable, intelligent production systems. For SMEs, this framework offers a practical pathway to achieve both economic and environmental sustainability, reducing reliance on resource-intensive CAE tools while cutting production costs by an estimated 22% through waste and energy savings. The study provides a replicable blueprint for implementing data-driven sustainability in injection molding operations without compromising product quality or operational efficiency. Full article

The relationship between ecosystem services (ESs) and human well-being (HWB) is a central issue of sustainable development. However, current research often relies on qualitative frameworks or indicator-based assessments, limiting a comprehensive understanding of the relationship between natural environment and human acquisition, which still needs to be strengthened. As an element transferred in the natural–society coupling system, carbon can assist in characterizing the dynamic interactions within coupled human–natural systems. Carbon, as a fundamental element transferred across ecological and social spheres, offers a powerful lens to characterize these linkages. This study develops and applies a novel analytical framework that integrates carbon flow as a unifying metric to quantitatively assess the spatiotemporal dynamics of the land use and land cover change (LUCC)–ESs–HWB nexus in Guizhou Province, China, from 2000 to 2020. The results show that: (1) Ecosystem services in Guizhou showed distinct trends from 2000 to 2020: supporting and regulating services declined and then recovered, and provisioning services steadily increased, while cultural services remained stable but varied across cities. (2) Human well-being generally improved over time, with health remaining stable and the HSI rising across most cities, although security levels fluctuated and remained low in some areas. (3) The contribution of ecosystem services to human well-being peaked in 2010–2015, followed by declines in central and northern regions, while southern and western areas maintained or improved their levels. (4) Supporting and regulating services were positively correlated with HWB security, while cultural services showed mixed effects, with strong synergies between culture and health in cities like Liupanshui and Qiandongnan. Overall, this study quantified the coupled dynamics between ecosystem services and human well-being through a carbon flow framework, which not only offers a unified metric for cross-dimensional analysis but also reduces subjective bias in evaluation. This integrated approach provides critical insights for crafting spatially explicit land management policies in Guizhou and offers a replicable methodology for exploring sustainable development pathways in other ecologically fragile karst regions worldwide. Compared with conventional ecosystem service frameworks, the carbon flow approach provides a process-based, dynamic mediator that quantifies biogeochemical linkages in LUCC–ESs–HWB systems, which is particularly important in fragile karst regions. However, we acknowledge that further empirical comparison with traditional ESs metrics could strengthen the framework’s generalizability. Full article

This study investigates the effects of key geometric parameters on the hydrodynamic and cavitation characteristics of two-element hydrofoil systems for fully submerged unmanned hydrofoil craft, aiming to solve their active stabilization problems. Using STARCCM+ software, the RANS method, and the SST k-ω turbulence model, the research analyzes the impacts of flap deflection angle (α), main wing-to-flap chord ratio (c1/c2), and spacing (g). Results show that when the spacing is fixed, increasing the chord ratio reduces the lift and drag coefficients. When the chord ratio is fixed, increasing the spacing causes the lift and drag coefficients to first rise and then fall. With increasing flap deflection angle (α), cavitation intensifies, but it can be suppressed by increasing the chord ratio, reaching a minimum at g = 2.4%c1. The optimal configuration is c1/c2 = 1.5 and g = 2.4%c1, which can balance the lift–drag performance and anti-cavitation capability. This study provides a scientific basis for solving the active stabilization problems of fully submerged unmanned hydrofoil craft and insights for enhancing their seakeeping performance. Full article

Virtual reality interaction design and story co-creation design for multiple users is an interdisciplinary research field that merges human–computer interaction, creative design, and virtual reality technologies. Story co-creation design enables multiple users to collectively generate and share narratives, allowing them to contribute to the storyline, modify plot trajectories, and craft characters, thereby facilitating a dynamic storytelling experience. Through advanced virtual reality interaction design, collaboration and social engagement can be further enriched to encourage active participation. This study investigates the facilitation of narrative creation and enhancement of storytelling skills in virtual reality by leveraging existing research on story co-creation design and virtual reality technology. Subsequently, we developed and evaluated the virtual reality card-based collaborative storytelling platform Co-Relay. By analyzing interaction data and user feedback obtained from user testing and experimental trials, we observed substantial enhancements in user engagement, immersion, creativity, and fulfillment of emotional and social needs compared to a conventional web-based storytelling platform. The primary contribution of this study lies in demonstrating how the incorporation of story co-creation can elevate storytelling proficiency, plot development, and social interaction within the virtual reality environment. Our novel methodology offers a fresh outlook on the design of collaborative narrative creation in virtual reality, particularly by integrating participatory multi-user storytelling platforms that blur the traditional boundaries between creators and audiences, as well as between fiction and reality. Full article

The efficient synthetic routes and evaluates cytotoxic profiles of denitroaristolochic acids II–V (DAA-II–V) were demonstrated in this study. Based on retrosynthetic analysis, a modular synthetic strategy was developed through Suzuki–Miyaura coupling, Wittig reaction, and bismuth triflate-catalyzed intramolecular Friedel–Crafts cyclization to efficiently construct the phenanthrene core. Process optimization significantly improved yields: aryl bromide intermediate A reached 50.8% yield via bromination refinement, while arylboronic ester intermediate B overcame selectivity limitations. Combining Darzens condensation with Wittig reaction enhanced throughput, achieving 88.4% yield in the key cyclization. Structures were confirmed by NMR and mass spectra. CCK-8 cytotoxicity assays in human renal proximal tubular epithelial cells revealed distinct toxicological profiles: DAA-III and DAA-IV exhibited IC₅₀ values of 371 μM and 515 μM, respectively, significantly higher than the nitro-containing prototype AA-I (270 μM), indicating that the absence of nitro group attenuates but does not eliminate toxicity, potentially via altered metabolic activation. DAA-II and DAA-V showed no detectable cytotoxicity within assay limits, suggesting reduced toxicological impact. Structure–activity analysis exhibited that the nitro group is not essential for cytotoxicity, with methoxy substituents exerting limited influence on potency. This challenges the conventional DNA adduct-dependent toxicity paradigm, implying alternative mechanisms like oxidative stress or mitochondrial dysfunction may mediate damage in denitro derivatives. These systematic findings provide new perspectives for AA analog research and a foundation for the rational use and safety assessment of Aristolochiaceae plants. Full article

Multi-agent reinforcement learning has demonstrated excellent performance in complex decision-making tasks such as electronic games, power grid management, and autonomous driving. However, its vulnerability to adversarial attacks may impede its widespread application. Currently, research on adversarial attacks in reinforcement learning primarily focuses on single-agent scenarios, while studies in multi-agent settings are relatively limited, especially regarding how to achieve optimized attacks with fewer steps. This paper aims to bridge the gap by proposing a heuristic exploration-based attack method named the Search for Key steps and Key agents Attack (SKKA). Unlike previous studies that train a reinforcement learning model to explore attack strategies, our approach relies on a constructed predictive model and a T-value function to search for the optimal attack strategy. The predictive model predicts the environment and agent states after executing the current attack for a certain period, based on simulated environment feedback. The T-value function is then used to evaluate the effectiveness of the current attack. We select the strategy with the highest attack effectiveness from all possible attacks and execute it in the real environment. Experimental results demonstrate that our attack method ensures maximum attack effectiveness while greatly reducing the number of attack steps, thereby improving attack efficiency. In the StarCraft Multi-Agent Challenge (SMAC) scenario, by attacking 5–15% of the time steps, we can reduce the win rate from 99% to nearly 0%. By attacking approximately 20% of the agents and 24% of the time steps, we can reduce the win rate to around 3%. Full article

With over 180 million tons produced annually and a global market exceeding 500 billion dollars, beer is one of the most widely consumed beverages in the world, thanks to its broad variety of styles, traditions, ingredients, and brewing techniques. However, behind this widespread popularity lies a potentially impactful production chain, whose environmental impacts remain underexplored, particularly within the craft segment. This research evaluates the sustainability of a hemp-based craft beer produced in the Lazio region (Italy) using an integrated approach that combines life cycle assessment with environmental impact monetization. The results indicate that the main impacts in beer production are related to global warming potential (0.916 kg CO₂ eq/L), terrestrial ecotoxicity (0.404 kg 1.4-DCB eq/L), land use (0.841 m²a crop eq/L), and fossil resource scarcity (0.211 kg oil eq/L), primarily due to malt production and hop transportation. Packaging analysis revealed that including environmental costs, aluminum cans may add an additional environmental cost of €0.80–1.60 per unit, while glass bottles, despite their weight, incur a lower additional cost. For a beer priced at €3.50, this would translate to a real cost of €4.30–5.10, reflecting a 22–45% increase. Improving sustainability in the brewing sector requires strategic actions, such as careful supplier selection and appropriate packaging choices. Overall, sustainability in brewing emerges as a balance between production needs, distribution impacts, and systemic decisions. Full article

Background/Objectives: This study aims to develop a standardized weight management intervention program for patients with endometrial cancer (EC) undergoing fertility preservation treatment and to provide a scientific foundation for midwives to implement weight management initiatives in the domains of oncology and reproduction. Methods: The weight management intervention program for patients with EC undergoing fertility preservation treatment was crafted following the directives of the Medical Research Council framework for developing and assessing complex interventions and the World Health Organization handbook for guideline development. The development process encompassed four distinct stages: (1) establishing the intervention development group, (2) identifying a theoretical basis and forming a content framework, (3) gathering and synthesizing evidence, and (4) refining and modeling the practice program. Results: The ultimate weight management program consisted of 6 primary, 18 secondary, and 53 tertiary items. Through two rounds of Delphi consultation, a response rate of 100% was attained, with an expert authority coefficient of 0.83. Conclusions: The developed intervention demonstrates scientific robustness and clinical feasibility, presenting a structured methodology for weight management for EC patients undergoing fertility preservation therapy. Full article

The quality of water in the Red River is a complex interplay between human-induced changes and inherent natural variables. This research utilized the snapshot sampling approach, garnering water quality data from 45 sampling sites in the Red River and crafting 24 environmental indicators related to land use and inherent natural determinants at the catchment scale. Through Spearman rank correlation and redundancy analyses, relationships among land use, natural variables, and water quality were elucidated. Our variance partitioning revealed differentiated impacts of land use and natural factors on water quality. Pivotal findings indicated superior water quality in the Red River, driven mainly by land use dynamics, which showed a distinct geomorphic gradient. Specific land use attributes, like cropland patch density, grassland’s largest patch index, and urban metrics, were pivotal in explaining variations in parameters such as total nitrogen, ammonia, and temperature. Notably, the configuration of land use had a more profound influence on water quality than merely its components. In terms of natural influences, while topography played a dominant role in shaping water quality, other factors like soil and weather had marginal impacts. Elevation was notably linked with metrics like total phosphorus and suspended solids, whereas precipitation and slope significantly determined electrical conductivity and chlorophyll-a models. In sum, incorporating both land use configurations and natural determinants offers a more comprehensive understanding of water quality disparities in the Red River’s ecosystem. For holistic water quality management, the focus should not only be on the major contributors like croplands and urban areas but also on underemphasized areas like grasslands. Tweaking cropland distribution, recognizing the intertwined nature of land use and natural elements, and tailoring land management based on topographical variations are essential strategies moving forward. Full article

Human Activity Recognition (HAR) systems aim to understand human behavior and assign a label to each action, attracting significant attention in computer vision due to their wide range of applications. HAR can leverage various data modalities, such as RGB images and video, skeleton, depth, infrared, point cloud, event stream, audio, acceleration, and radar signals. Each modality provides unique and complementary information suited to different application scenarios. Consequently, numerous studies have investigated diverse approaches for HAR using these modalities. This survey includes only peer-reviewed research papers published in English to ensure linguistic consistency and academic integrity. This paper presents a comprehensive survey of the latest advancements in HAR from 2014 to 2025, focusing on Machine Learning (ML) and Deep Learning (DL) approaches categorized by input data modalities. We review both single-modality and multi-modality techniques, highlighting fusion-based and co-learning frameworks. Additionally, we cover advancements in hand-crafted action features, methods for recognizing human–object interactions, and activity detection. Our survey includes a detailed dataset description for each modality, as well as a summary of the latest HAR systems, accompanied by a mathematical derivation for evaluating the deep learning model for each modality, and it also provides comparative results on benchmark datasets. Finally, we provide insightful observations and propose effective future research directions in HAR. Full article

Machine learning models for personal informatics systems are typically trained offline on records of a specific population of users, resulting in population models. These models may suffer performance degradation in real-world settings due to domain shift, i.e., differences in data distributions across users and contexts. Domain adaptation techniques can address this issue by, e.g., personalizing models with user-specific data. In this paper, we quantify the impact of domain shift on the performance of both population and personalized models in a specific scenario: sleep quality recognition. To this end, we also collect and make available to the research community the new BiheartS dataset. Our analysis shows that domain shift causes the accuracy of population models to decrease by up to 18.54 percentage points, when used on new data. Personalized models, instead, show robust performance across datasets. However, crafting personalized models typically requires using new data or user-provided labels, limiting their applicability in real settings. To mitigate the limitations of both population and personalized models, we propose a novel unsupervised domain adaptation approach: the cluster-based population model (CBPM). CBPM achieves accuracy improvements of up to 13.45 percentage points w.r.t. population model without requiring the use of user-specific records or labels. Full article

This study explores the marketing potential of artisanal agri-food products in Ukraine by examining their structural, regional, and consumer dimensions. Amid growing interest in sustainable and locally rooted food systems, the research addresses how artisanal production can evolve from informal crafts to market-recognized value. This study is based on an analysis of official statistical data and an analysis of registered artisanal food producers in specific areas in Ukraine. It emphasizes the role of household-based agriculture in securing raw materials, the impact of cultural–tourism infrastructure on product visibility, and the benefits of self-sufficiency in raw material sourcing for product differentiation. The findings reveal that regions with stronger household production and cultural engagement demonstrate higher activity in the artisanal food sector. This study concludes that artisanal food production offers a viable pathway for regional development, rural resilience, and the strengthening of local food identity. Full article