Search Results (101)

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

Multi-modal remote sensing image (MRSI) matching suffers from severe nonlinear radiometric distortions and geometric deformations, and conventional feature-based techniques are generally ineffective. This study proposes a novel and robust MRSI matching method using the side window filter (MSWF). First, a novel side window scale space is constructed based on the side window filter (SWF), which can preserve shared image contours and facilitate the extraction of feature points within this newly defined scale space. Second, noise thresholds in phase congruency (PC) computation are adaptively refined with the Weibull distribution; weighted phase features are then exploited to determine the principal orientation of each point, from which a maximum index map (MIM) descriptor is constructed. Third, coarse position, orientation, and scale information obtained through global matching are employed to estimate image-pair geometry, after which descriptors are recalculated for precise correspondence search. MSWF is benchmarked against eight state-of-the-art multi-modal methods—six hand-crafted (PSO-SIFT, LGHD, RIFT, RIFT2, HAPCG, COFSM) and two learning-based (CMM-Net, RedFeat) methods—on three public datasets. Experiments demonstrate that MSWF consistently achieves the highest number of correct matches (NCM) and the highest rate of correct matches (RCM) while delivering the lowest root mean square error (RMSE), confirming its superiority for challenging MRSI registration tasks. Full article

Because neural networks pervade many industrial domains and are increasingly complex and accurate, the trained models themselves have become valuable intellectual properties. Developing highly accurate models demands increasingly higher investments of time, capital, and expertise. Many of these models are commonly deployed in cloud services and on resource-constrained edge devices. Consequently, safeguarding them is critically important. Neural network watermarking offers a practical solution to address this need by embedding a unique signature, either as a hidden bit-string or as a distinctive response to specially crafted “trigger” inputs. This allows owners to subsequently prove model ownership even if an adversary attempts to remove the watermark through attacks. In this manuscript, we adapt three state-of-the-art watermarking methods to “tiny” neural networks deployed on edge platforms by exploiting symmetry-related properties that ensure robustness and efficiency. In the context of machine learning, “tiny” is broadly used as a term referring to artificial intelligence techniques deployed in low-energy systems in the mW range and below, e.g., sensors and microcontrollers. We evaluate the robustness of the selected techniques by simulating attacks aimed at erasing the watermark while preserving the model’s original performances. The results before and after attacks demonstrate the effectiveness of these watermarking schemes in protecting neural network intellectual property without degrading the original accuracy. 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 sustainable preservation of archeological heritage located in rural and coastal regions requires more than technical interventions; it necessitates the awareness and active participation of local communities. However, community involvement in heritage management in such areas remains limited. This study aims to analyze the levels of cultural heritage awareness, conservation tendencies, and tourism-related expectations among local residents and visitors in the Magarsus Archeological Area, located in the Karataş district on the eastern Mediterranean coast of Turkey. The study was conducted in three phases: a literature review, field observations, and a structured survey conducted between June and August 2022 with 510 participants (280 local residents and 230 domestic visitors from surrounding provinces). The data were analyzed using SPSS 25.0 through descriptive statistical methods, complemented by cross-tabulation and chi-square analysis to identify patterns across demographic variables. The survey results not only reflect general perceptions about heritage and tourism but also offer critical insights into how the rural and coastal character of the site shapes conservation attitudes and tourism behavior. The findings reveal nuanced perceptions, including strong symbolic appreciation for heritage and general openness to tourism, alongside concerns about cultural and environmental risks. While the local community prioritizes the potential for economic benefit, many participants also emphasized the importance of safeguarding local traditions, crafts, and culinary heritage. Nevertheless, concerns were expressed regarding the risks posed by uncontrolled tourism, including environmental degradation, erosion of cultural identity, and the commodification of heritage values. Based on these insights, the study introduces a governance approach built upon three interlinked pillars: community-based participation, environmental sustainability, and tourism practices aligned with cultural values. The proposed approach aims to support the inclusive and sustainable management of Magarsus and other rural and coastal archeological landscapes with similar characteristics. Full article

Traditional ethnographic methods have long been employed to study craft practices, yet they often fall short of capturing the full depth of embodied knowledge, material interactions, and procedural workflows inherent in craftsmanship. This paper introduces a digitally enhanced ethnographic framework that integrates Motion Capture, 3D scanning, audiovisual documentation, and semantic knowledge representation to document both the tangible and dynamic aspects of craft processes. By distinguishing between endurant (tools, materials, objects) and perdurant (actions, events, transformations) entities, we propose a structured methodology for analyzing craft gestures, material behaviors, and production workflows. The study applies this proposed framework to eight European craft traditions—including glassblowing, tapestry weaving, woodcarving, porcelain pottery, marble carving, silversmithing, clay pottery, and textile weaving—demonstrating the adaptability of digital ethnographic tools across disciplines. Through a combination of multimodal data acquisition and expert-driven annotation, we present a comprehensive model for craft documentation that enhances the preservation, education, and analysis of artisanal knowledge. This research contributes to the ongoing evolution of ethnographic methods by bridging digital technology with Cultural Heritage studies, offering a robust framework for understanding the mechanics and meanings of craft practices. Full article

This study explores spiritual resilience as a mechanism for sustaining cultural landscapes, focusing on the UNESCO World Heritage Site of the Studenica Monastery (Serbia). By analysing the monastery’s sacred network, which includes monasteries, hermitages, and churches, the study demonstrates how material heritage (architecture, art), intangible practices (monastic life, liturgy, traditional crafts), and the natural environment (UNESCO MaB Golija–Studenica Biosphere Reserve) form a cohesive system of resilience. The concept of spiritual resilience is examined as a dynamic process that links sacred architectural structures and enduring religious practices with authentic land use preserved over centuries. We have utilised a methodological framework combining historical mapping, GIS viewshed analysis in spatial planning, and multidisciplinary data synthesis (historical, architectural, artistic, ecological, ethnographic) with resilience indicators aligned with the UNESCO’s Cultural Landscape approach. The findings reveal that Studenica’s sacred network operates as a coupled socio-ecological system. Spiritual practices, including annual processions and land stewardship rituals, have been identified as key factors in enhancing biodiversity conservation while mitigating land-use conflicts. Historical mapping has been used to highlight the overlap between sacred sites and protected ecological zones, reflecting traditional stewardship practices. By reframing heritage as an adaptive process where spirituality serves as a conduit between tradition and innovation, the study proposes replicable strategies for UNESCO sites worldwide. The concept of sacred landscapes as resilience hubs is furthered by alignment with SDG 11 (Sustainable Cities and Communities). Full article

Embodied Conversational Agents (ECAs) serve as digital twins (DTs), visually and behaviorally mirroring human counterparts in various roles, including healthcare coaching. While existing research primarily focuses on single-coach ECAs, our work explores the benefits of multi-coach virtual health sessions, where users engage with specialized diet, physical, and cognitive coaches simultaneously. ECAs require verbal relational cues—such as empowerment, affirmation, and empathy—to foster user engagement and adherence. Our study integrates Generative AI to automate the embedding of these cues into coaching dialogues, ensuring the advice remains unchanged while enhancing delivery. We employ ChatGPT to generate empathetic and collaborative dialogues, comparing their effectiveness against manually crafted alternatives. Using three participant cohorts, we analyze user perception of the helpfulness of AI-generated versus human-generated relational cues. Additionally, we investigate whether AI-generated dialogues preserve the original advice’s semantics and whether human or automated validation better evaluates their lexical meaning. Our findings contribute to the automation of digital health coaching. Comparing ChatGPT- and human-generated dialogues for helpfulness, users rated human dialogues as more helpful, particularly for working alliance and affirmation cues, whereas AI-generated dialogues were equally effective for empowerment. By refining relational cues in AI-generated dialogues, this research paves the way for automated virtual health coaching solutions. Full article

Sports facilities encompass diverse spaces tailored to various sports disciplines, each characterized by unique shapes and sizes. Skateparks, renowned for their avant-garde designs, are meticulously crafted to exude distinctiveness, featuring an array of constructions, surfaces, and intricate shapes. Traditional measurement methods often struggle to capture the spatial, structural, and architectural diversity of these facilities. Constructing 3D models, particularly with Building Information Modeling (BIM) technology, faces inherent challenges due to the complex and individualistic nature of skateparks. The crux lies in acquiring credible and comprehensive spatial and construction-related information. Geospatial data emerges as a viable solution, effectively addressing the skatepark’s myriad forms while upholding information accuracy and reliability. By gathering, processing, and integrating Terrestrial Laser Scanning and drone-based photogrammetry point cloud data, a precise spatial foundation is established for BIM model generation. Leveraging the integrated point cloud and photographic data aids in identifying elements and construction materials, facilitating the creation of detailed technical documentation and life-like visualizations. This not only supports condition assessment and maintenance planning, but also assists in strategically planning facility expansions, renovations, or component replacements. Moreover, BIM technology streamlines facility information management by preserving vital object-related data in a structured database, enhancing overall efficiency and effectiveness. Full article

Different academic disciplines approach the concept of materials from varying perspectives, and exploring these diverse interpretations can reveal new avenues for creative expression. While scientific analysis offers important insights into the transformation of materials, artistic and humanistic frameworks provide complementary lenses that enrich our understanding. In the context of artistic creation, the intentional and thoughtful use of materials is crucial, often producing unexpected and profound effects that engage audiences on multiple levels. The deep connection between artists and their materials is fundamental for preserving and transmitting cultural values. As the exploration of material transformation within art continues to evolve, it opens up a wealth of creative opportunities. However, significant challenges remain, particularly in evaluating whether transformed artworks truly resonate with audiences and in developing robust criteria for assessing the process of material transformation. This study tackles these challenges by employing a two-phase evaluation framework, focusing on four pairs of paintings reinterpreted as ceramic artworks, with feedback gathered from 389 online participants. The results demonstrate that artworks crafted from diverse materials are accessible to a wide range of viewers, providing valuable insights into the artistic process and broadening perspectives on material usage in art. While artistic creation remains a subjective endeavor, future research should aim to identify consistent patterns in audience reception and further explore the expressive potential of various materials in artistic practice. Full article

Currently, as research on hydrogel beads intensifies, the application scope of chitosan-based hydrogel beads is increasingly expanding. Owing to their unique three-dimensional network structure, chitosan-based hydrogel beads are frequently utilized for encapsulating bioactive substances and adsorbing impurities. The primary material used in the preparation of chitosan-based hydrogel beads is chitosan, which is uniquely a natural polysaccharide possessing a positive charge. Derived from a diverse array of sources, chitosan is non-toxic, exhibits excellent biocompatibility, and possesses certain antibacterial properties. Because of these remarkable attributes, it has found widespread application in tissue engineering, the formulation of drug carriers, and the adsorption of heavy metals and dyes in wastewater. The preparation method for chitosan-based hydrogel beads largely mirrors that of other hydrogel beads. According to existing research, numerous methods exist for crafting hydrogel beads with diverse properties. This paper reviews the preparation methods of chitosan-based hydrogel beads, encompassing both physical and chemical crosslinking techniques. The physical crosslinking method leverages electrostatic interactions between materials to form hydrogel beads, whereas the chemical crosslinking method involves the use of chemical crosslinking agents to facilitate the formation of hydrogel beads through material-based chemical reactions. Given that chitosan carries a positive charge and other polysaccharide materials possess a negative charge, the combination of these materials can yield hydrogel beads with a dense structure, effectively encapsulating bioactive substances. This dense internal structure offers superior protection for the encapsulated bioactive substances. Chitosan-based hydrogel beads typically feature large pore sizes, providing numerous adsorption sites, which makes them well suited for wastewater treatment. Additionally, this paper examines the recent applications of chitosan-based hydrogel beads in food preservation, medicine, and environmental protection. Starting with the materials and methods for preparing chitosan-based hydrogel beads, this paper delves into their applications in food preservation, biomedicine, and environmental protection, offering insights for future developments and applications of chitosan-based hydrogel beads and fostering further innovation and advancement in this field. Full article

Prompt tuning visual-language models (VLMs) for specialized tasks often involves leveraging task-specific textual tokens, which can tailor the pre-existing, broad capabilities of a VLM to more narrowly focused applications. This approach, exemplified by CoOp-based methods, integrates mutable textual tokens with categorical tokens to foster nuanced textual comprehension. Nonetheless, such specialized textual insights often fail to generalize beyond the scope of familiar categories, as they tend to overshadow the versatile, general textual knowledge intrinsic to the model’s wide-ranging applicability. Addressing this base-novel dilemma, we propose the innovative concept of SparseKnowledge-guided Context Optimization (Sparse-KgCoOp). This technique aims to fortify the adaptable prompts’ capacity to generalize to categories yet unencountered. The cornerstone of Sparse-KgCoOp is based on the premise that reducing the differences between adaptive prompt and their hand-crafted counterparts through sparsification operations can mitigate the erosion of fundamental knowledge. Specifically, Sparse-KgCoOp seeks to narrow the gap between the textual embeddings produced by both the dynamic prompts and the manually devised ones, thus preserving the foundational knowledge while maintaining adaptability. Extensive experiments of several benchmarks demonstrate that the proposed Sparse-KgCoOp is an efficient method for prompt tuning. Full article

Intracranial aneurysms (IAs), a significant medical concern due to their prevalence and life-threatening nature, pose challenges regarding diagnosis owing to their diminutive and variable morphology. There are currently challenges surrounding automating the segmentation of IAs, which is essential for diagnostic precision. Existing deep learning methods in IAs segmentation tend to emphasize semantic features at the expense of detailed information, potentially compromising segmentation quality. Our research introduces the innovative Dual-Path Fusion Network (DPF-Net), an advanced deep learning architecture crafted to refine IAs segmentation by adeptly incorporating detailed information. DPF-Net, with its unique resolution-preserving detail branch, ensures minimal loss of detail during feature extraction, while its cross-fusion module effectively promotes the connection of semantic information and finer detail features, enhancing segmentation precision. The network also integrates a detail aggregation module for effective fusion of multi-scale detail features. A view fusion strategy is employed to address spatial disruptions in patch generation, thereby improving feature extraction efficiency. Evaluated on the CADA dataset, DPF-Net achieves a remarkable mean Dice similarity coefficient (DSC) of 0.8967, highlighting its potential in automated IAs diagnosis in clinical settings. Furthermore, DPF-Net’s outstanding performance on the BraTS 2020 MRI dataset for brain tumor segmentation with a mean DSC of 0.8535 further confirms its robustness and generalizability. Full article

This publication highlights the strategic combination of the preservation of heritage and innovation for supporting the sustainability of traditional crafts in Europe. Demonstrating both challenges and opportunities faced by artisans, there is a need to balance cultural authenticity and the pressures of current markets and environmental imperatives. The research has explored interventions at three levels of craft practice, education, and training and recommends practical directions on short- and long-term bases. Key findings include new materials and technologies to revitalize crafts, the integration of digital tools in education, and cross-border collaboration, which are considered vital for enhancing the visibility and viability of traditional crafts. The circular economy principles and eco-certifications emerge as key to aligning traditional crafts with global sustainability goals. The analysis also highlights cultural policies and funding mechanisms as a means of encouraging innovation and promoting the resilience of the craft sector. The publication, by weaving together case studies, policy analysis, and strategic recommendations, provides a comprehensive roadmap for stakeholders—from artisans and educators to policymakers and researchers—to ensure that the legacy and relevance of Europe’s rich craft heritage continue. Full article

As cultural heritage carriers, traditional architectural decorative techniques face substantial adaptation challenges in contemporary society. Chaozhou Inlaid Porcelain, a nationally recognized intangible cultural heritage (ICH) of China, integrates artistic value with functional adaptability. However, its sustainability is undermined by high production costs, limited market demand, and weakening intergenerational transmission. Based on dynamic adaptation theory, this study systematically explores the inheritance and innovative evolution of Inlaid Porcelain. It aims to examine the feasibility of adapting the craft to modern societal needs and provides theoretical and practical references for the sustainable development of ICH. Employing a mixed-method approach, this study integrates SWOT analysis and case studies to delineate the dynamic adaptation pathways of Inlaid Porcelain across technological advancement, functional development, market positioning, education, and dissemination. The results suggest that Inlaid Porcelain possesses strong potential to meet modern aesthetic and functional expectations. This study highlights that ICH crafts can enhance cultural, economic, and social benefits by expanding their functions and adopting market-driven approaches. Yet, limited societal recognition and public engagement constrain its dynamic adaptation. This study proposes a systematic feedback mechanism integrating policy, market, and heritage transmission to enhance adaptive development. Furthermore, by developing a dynamic adaptation model, this research offers a practical framework for safeguarding and revitalizing traditional crafts, ultimately supporting the sustainable integration of cultural, economic, and social development. Full article