Search Results (335)

This study develops a comprehensive competitiveness model for Indonesia’s WealthTech ecosystem by integrating Interpretive Structural Modeling (ISM) and MICMAC analysis. The research identifies and classifies 23 interrelated variables derived from SEM-PLS and NVivo analysis, of which 17 passed expert validation and were subsequently retained in the ISM–MICMAC structural model, including innovation capabilities, regulatory support, digital infrastructure, capital readiness, and customer trust, to evaluate their systemic roles in shaping competitive advantage. Through expert interviews, bibliometric analysis, and a structured modeling process, key independent drivers such as innovation capabilities, geopolitical events, and economic shocks were identified as foundational enablers. Linkage variables including digital transformation, strategic alliances, and cost leadership connect these enablers to dependent outcomes such as customer satisfaction and platform personalization. The resulting hierarchical framework and strategic roadmap offer actionable insights for policymakers, fintech stakeholders, and investors to enhance resilience, regulatory alignment, and ecosystem integration. This research not only fills a critical gap in the digital finance literature but also provides a strategic tool for advancing Indonesia’s WealthTech sector within the global financial landscape. Full article

The proliferation of free-form architecture necessitates efficient detailing methods for complex spatially bending-torsion steel members. Current approaches suffer from low modeling efficiency, inaccurate surface fitting, and limited capabilities for variable-section generation and plate unfolding. This study presents a comprehensive parametric detailing module developed within the Grasshopper (GH) platform to overcome these challenges. The core innovations include (1) a data structure that integrally describes member axes, cross-sections, and unfolding information; (2) an algorithm that automatically generates interpolation points based on curvature variation to ensure axis smoothness; (3) the use of architectural surface normals as member torsion vectors, eliminating manual control point placement; and (4) integrated alignment and unfolding functions for fabrication-ready outputs. In an engineering case study, the module reduced modeling time by approximately 70% compared to conventional methods while achieving a root-mean-square deviation of less than 2 mm between the fitted and target surfaces. The system enables rapid generation of 3D models and 2D fabrication drawings for complex bending-torsion members, significantly enhancing detailing efficiency and precision. Full article

Background/Objectives: Excessive social media usage in the current times and high rates of food advertising can impact the health status of individuals by increasing food cues related to perceived hunger and, thus, dietary behaviour. This study examined the association between social media usage patterns, food-related advertising, and dietary choices among Gen Z individuals. Methods: A cross-sectional study was carried out amongst 314 young adults between the ages of 18 and 25 in Surat city, Gujarat. Data was collected for social media usage, the most used platforms, preferred content, and eating patterns. Anthropometric measurements (height and weight) were also recorded. Perceived hunger responses to 12 social media-based food images were assessed using a ten-point Visual Analogue Scale (VAS). Statistical analyses were performed using SPSS (version 26.0), with the significance level set at p < 0.05. Results: YouTube and Instagram were the most used social media apps. There were no significant differences observed between the BMI of participants using social media for 2 h a day and those using it 3+ hours a day. However, a significant association between the BMI of those who viewed advertisements for ready-to-eat foods (p = 0.004) and the BMI of those who viewed advertisements for food delivery platforms (p = 0.001) was seen. A significant difference between usage of Pinterest (p = 0.02), Instagram (p = 0.047), and BMI was also found. Conclusions: Social media marketing and food content are shaping the dietary choices of young adults, and more studies need to be conducted in Pan India to understand the reasons. Such evidence will be crucial for guiding nutrition policies, digital marketing regulations, and youth-focused awareness programmes. Full article

This paper describes a compact low-cost telemetry system featuring ready-made sensors and an acquisition unit based on the ESP32, which makes use of the LoRa/Wi-Fi wireless standard for communication, and autonomous fallback logging to guarantee data recovery during communication loss. Ensuring safe atmospheric re-entry requires reliable onboard monitoring of capsule conditions during descent. The system is intended for sub-orbital, low-cost educational capsules and experimental atmospheric descent missions rather than full orbital re-entry at hypersonic speeds, where the environmental loads and communication constraints differ significantly. The novelty of this work is the development of a fully self-contained telemetry system that ensures continuous monitoring and fallback logging without external infrastructure, bridging the gap in compact solutions for CubeSat-scale capsules. In contrast to existing approaches built around UAVs or radar, the proposed design is entirely self-contained, lightweight, and tailored to CubeSat-class and academic missions, where costs and infrastructure are limited. Ground test validation consisted of vertical drop tests, wind tunnel runs, and hardware-in-the-loop simulations. In addition, high-temperature thermal cycling tests were performed to assess system reliability under rapid temperature transitions between −20 °C and +110 °C, confirming stable operation and data integrity under thermal stress. Results showed over 95% real-time packet success with full data recovery in blackout events, while acceleration profiling confirmed resilience to peak decelerations of ~9 g. To complement telemetry, the TeleCapsNet dataset was introduced, facilitating a CNN recognition of descent states via 87% mean Average Precision, and an F1-score of 0.82, which attests to feasibility under constrained computational power. The novelty of this work is twofold: having reliable dual-path telemetry in real-time with full post-mission recovery and producing a scalable platform that explicitly addresses the lack of compact, infrastructure-independent proposals found in the existing literature. Results show an independent and cost-effective system for small re-entry capsule experimenters with reliable data integrity (without external infrastructure). Future work will explore AI systems deployment as a means to prolong the onboard autonomy, as well as to broaden the applicability of the presented approach into academic and low-resource re- entry investigations. Full article

The detection of environmental toxicants is transitioning from centralized laboratory methods to decentralized, point-of-care (POC) monitoring. A highly innovative approach in this field is the repurposing of commercially available, low-cost, and portable personal glucose meters (PGMs) as universal biosensing platforms. This strategy leverages the widespread availability and ease of use of PGMs to develop rapid, on-site detection methods for a wide array of non-glucose targets, significantly reducing both cost and development time. This systematic review comprehensively examines the various strategies employed to adapt PGMs for the detection of a wide array of ecotoxicants, including chemical targets (antibiotics, mycotoxins, pesticides, heavy metals, persistent organic pollutants) and biological ones (pathogenic bacteria, and viruses). The systematic review critically evaluates different sensor designs, highlighting that while aptamer-based and non-enzymatic biosensors offer advantages in stability and cost, antibody-based sensors provide high specificity. A significant finding is the persistent trade-off between analytical sensitivity and practical field deployment; many of the most sensitive assays require multi-step procedures, precise temperature control, magnetic separation, centrifugation, and the use of additional equipment, factors that undermine true POC utility. To address this gap, we propose four essential criteria for POC readiness: (i) ambient-temperature operation, (ii) no reliance on magnetic or centrifugal separation, (iii) total assay time, and (iv) robustness in complex environmental matrices. This systematic review confirms the feasibility of this approach across a broad spectrum of targets. However, the key challenge for future research lies in simplifying the assay protocols, eliminating cumbersome sample preparation steps, and enhancing robustness to make these biosensors truly practical for routine, on-site environmental monitoring. Full article

Agricultural and agro-industrial residues are increasingly recognized as sustainable, low-cost feedstocks for high-performance biomedical materials. This review critically examines the translational potential of polysaccharides, proteins, inorganic compounds, and phytochemical-rich extracts derived from agro-waste, highlighting their chemical features, structure–function relationships, and application-specific readiness. Polysaccharides such as nanocellulose, pectin, and chitosan emerge as the most advanced biopolymer platforms, particularly in wound healing, drug delivery, and 3D-printed scaffolds. Protein-derived materials—including collagen, gelatin, keratin, and soy protein—show strong promise in regenerative medicine, though challenges in mechanical stability and batch reproducibility remain. Inorganic phases such as hydroxyapatite and silica obtained from eggshells, rice husk ash, and marine shells demonstrate high bioactivity, with dental and bone applications approaching clinical translation. Finally, fruit-residue phytochemicals provide multifunctional antioxidant and antimicrobial enhancements to composite systems. By integrating material chemistry, processing strategies, and translational considerations, this review outlines the current state, challenges, and future perspectives for advancing agro-waste-derived biomaterials within a circular bioeconomy. Full article

Hydrogen energy, with its high calorific value and zero carbon emissions, serves as a crucial solution for addressing global energy and environmental challenges while achieving carbon neutrality. The ocean offers abundant renewable energy resources including offshore wind, solar, and marine energy, along with vast seawater reserves, making it an ideal platform for green hydrogen production. This review systematically examines recent research progress in several key marine hydrogen production approaches: seawater electrolysis through both desalination-coupled and direct methods, photocatalytic seawater splitting, biological hydrogen production via algae and bacteria, and hybrid renewable energy systems, each demonstrating varying levels of technological development and industrial readiness. Despite significant advancements, challenges remain, such as reduced electrolysis efficiency caused by seawater impurities, high costs of catalysts and corrosion-resistant materials, and the intermittent nature of renewable energy sources. Future improvements require innovations in catalyst design, membrane technology, and system integration to enhance efficiency, durability, and economic feasibility. The review concludes by outlining the technological development directions for marine hydrogen energy, highlighting how hydrogen production from marine renewable energy can facilitate a sustainable blue economy through large-scale renewable energy storage and utilization. Full article

This paper presents an open, modular sensor platform based on wireless energy and data transmission. The platform is powered by the carrier signal of a transceiver and transmits the measured sensor data using backscatter modulation. Through the use of modular ready-to-buy components, the sensor platform can be flexibly adapted to different applications and is therefore suitable for both building automation systems and industrial automation tasks. Energy storage, power management, and modulation are designed so that the overall energy demand of the platform is mainly determined by the sensor in use. The performance of the system was verified with a demonstrator measuring underfloor temperature and humidity. The demonstrator operates at a carrier frequency of 868 MHz, an output power of $27 \mathrm{dBm}$ EIRP at the transceiver antenna, and an antenna gain of 0 dBi at the receiver antenna. A transmission range of more than 3 m has been achieved. The platform provides an input sensitivity of $-15 \mathrm{dBm}$. Its open design enables a straightforward scaling from prototype to small- and medium-volume production. Full article

The present systematic review aims to provide a comprehensive synthesis of evidence and practices regarding sustainable career transitions in elite sport. Following PRISMA guidelines, an extensive literature search was conducted in SPORTDiscus (EBSCOhost), PsycINFO, Scopus, Web of Science, and Google Scholar databases, resulting in 117 manuscripts, published from January 2015 to May 2025, and meeting the defined inclusion criteria. The review focused on mental health, dual-career pathways, transition readiness, and identity-related issues among elite athletes, Olympians, and Paralympians. Methodologies included qualitative, quantitative, and mixed-methods designs, with multisport and mixed-gender samples prevailing. The most commonly used instruments were semi-structured interviews and surveys. The main findings highlighted the centrality of mental health support, the role of dual-career planning, and the importance of proactive identity negotiation. Despite growing research interest, significant gaps persist in access to psychological support, structured transition planning, and dual-career strategies, with notable inconsistencies across countries and sports. The review emphasizes the necessity for integrated, multidimensional guidance, culturally sensitive psychological services, and flexible educational pathways to promote athlete well-being and sustainable post-sport careers. These insights are intended to inform the implementation of the ERASMUS+ funded PORTAL project, supporting evidence-based interventions and the development of resources such as an online platform and Real-Life Transition Officers to enhance the transition experiences of elite athletes. Full article

The rapid digital transformation of the financial sector has driven supervisory authorities to develop new tools for engaging with fintech innovation. Among these, Innovation Hubs have become essential mechanisms for improving regulatory dialogue, interpretive clarity, and institutional learning. This article examines the Romanian Fintech Innovation Hub (FIH), launched by the National Bank of Romania (NBR) as a consultative platform to support fintech and payment service providers operating within complex legal environments. Using a qualitative, single-case methodology (2019–2023), the study draws on internal NBR documentation, anonymized supervisory materials, and interviews with fintech founders, oversight officers, and policy specialists. The analysis evaluates the Hub’s performance across five key dimensions: stakeholder engagement, regulatory learning, policy calibration, innovation barriers, and institutional reflexivity. Findings reveal that while the Hub strengthened supervisory understanding and enhanced trust-based interaction, its influence on rulemaking and market access was limited by structural and procedural constraints, including resource gaps and the absence of a regulatory sandbox function. Nonetheless, the Romanian experience demonstrates how institutional learning can emerge even in bank-dominated markets, generating internal adaptation and improving fintech compliance readiness. Comparative insights from Hungary and Italy highlight the advantages of modular, risk-proportionate engagement models that integrate advisory and testing functions. The study contributes to the theory of adaptive regulation by proposing that innovation hubs function as feedback loop mechanisms linking market experimentation with supervisory evolution, offering a replicable model for small and emerging financial systems seeking to balance innovation facilitation with prudential soundness and legal certainty. As such, it provides generalizable insights for central banks and government policymakers on developing FinTech hubs that balance innovation facilitation with prudential soundness and legal certainty. Full article

Apical hypertrophic cardiomyopathy is a distinctive and often under-recognized variant of hypertrophic cardiomyopathy, characterized by predominant thickening of the apical segments of the left ventricle. Echocardiography and cardiac magnetic resonance imaging represent the two principal modalities for diagnosis and morphological assessment. While transthoracic echocardiography remains the first-line imaging technique, it may underestimate apical involvement, particularly when image foreshortening or poor endocardial/epicardial delineation occurs. Cardiac magnetic resonance has become the reference standard for defining apical morphology, quantifying hypertrophy, and characterizing myocardial tissue and perfusion. Beyond its diagnostic role, magnetic resonance serves as a research platform for the identification of new apical-centric criteria which, after appropriate validation, may be translated into echocardiographic practice. Echocardiography, however, retains unique strengths through its real-time evaluation of cardiac dynamics, ready-to-use approach to diastolic function assessment, and its ability to identify subtle apical or para-apical obstructive gradients that may raise the initial diagnostic suspicion. This review underscores the complementary roles of the two modalities and the multiple domains in which transthoracic echocardiography can derive substantial methodological and conceptual benefit from cardiac magnetic resonance imaging, both in imaging methodology and in the refinement of diagnostic evaluation. Full article

Additive manufacturing (AM), commonly known as 3D printing, is revolutionizing modern dentistry, introducing high-precision, patient-specific, and digital-driven workflows across prosthodontics, orthodontics, implantology, and maxillofacial surgery. Extensive analysis explores the leading platforms in 3D printing such as stereolithography (SLA), fused deposition modeling (FDM), selective laser sintering (SLS), digital light processing (DLP), and PolyJet which all achieve superior performance across multiple areas including resolution capabilities, material compatibility options, clinical application readiness, and cost-effectiveness. Additionally, an extensive overview of common materials, including biocompatible polymers (PLA, PMMA, PEEK), metals (titanium, cobalt-chromium), and ceramics (zirconia, alumina, glass-ceramics), sheds light on the critical role of material selection for patient safety, durability, and functional performance. The review explores new advancements such as 4D printing with shape-adaptive smart biomaterials as well as artificial intelligence-enabled digital processes and prosthesis design for the transformation of regenerative dentistry and intraoral drug delivery operations into new domains and the automation of clinical planning. Equally groundbreaking are 3D printing applications in pediatric dentistry, surgical simulation, and dental education. However, full-scale adoption of AM technology is not without challenges, including material toxicity, regulatory hurdles for approval, high initial investments, and the need for extensive digital expertise training. Sustainability concerns are also being addressed, with recycled materials and circular economy models gaining traction. In conclusion, this article advocates for a future where dentistry is shaped by interdisciplinary collaboration, intelligent automation, and hyper-personalized biocompatible solutions, with 3D printing firmly established as the backbone of next-generation dental care. Full article

CerMapp is a multi-platform and system application designed to address a critical gap in veterinary public health: the lack of a standardized, national-scale geodatabase for wildlife diseases. This gap has long hindered the effective application of GIS and remote sensing in spatial epidemiology. Currently deployed at the prototype level in Aosta Valley, NW Italy, the application’s core innovation is its ability to generate a structured, analysis-ready data repository, which serves as a foundational resource for One Health initiatives. Developed by the National Reference Center for Wildlife Diseases on the ESRI ArcGIS Survey123 platform v.3.24, CerMapp enables veterinarians, foresters, and wildlife professionals to easily collect and georeference field data, including species, health status, and photographic evidence using flexible methods such as Global Navigation Satellite System or manual map entry. Data collected via CerMapp are stored in a centralized geodatabase, facilitating risk analyses and detailed geospatial studies. This data can be integrated with remote sensing information processed on cloud platforms like Google Earth Engine or within traditional GIS software, contributing to a comprehensive and novel wildlife health registry. By promoting the rational and standardized collection of essential geospatial data, CerMapp data may support predictive disease modeling, risk assessment, and habitat suitability mapping for wildlife diseases, zoonoses, and vector-borne pathogens. Its scalable, user-friendly design ensures alignment with existing national systems like the Italian Animal Disease Information System (SIMAN), making advanced geospatial analysis accessible without requiring specialized digital skills from field operators or complex IT maintenance from institutions. Full article

Remote sensing video (RSV) provides continuous, high spatiotemporal earth observations that are increasingly important for environmental monitoring, disaster response, infrastructure inspection and urban management. Despite this potential, operational use of video streams is hindered by very large data volumes, heterogeneous acquisition platforms, inconsistent preprocessing practices, and the absence of standardized formats that deliver data ready for immediate analysis. These shortcomings force repeated low-level computation, complicate semantic extraction, and limit reproducibility and cross-sensor integration. This manuscript presents a principled multi-level analysis-ready data (ARD) model for remote sensing video, named VideoARD, along with VideoCube, a spatiotemporal management and query infrastructure that implements and operationalizes the model. VideoARD formalizes semantic abstraction at scene, object, and event levels and defines minimum and optimal readiness configurations for each level. The proposed pipeline applies stabilization, georeferencing, key frame selection, object detection, trajectory tracking, event inference, and entity materialization. VideoCube places the resulting entities into a five-dimensional structure indexed by spatial, temporal, product, quality, and semantic dimension, and supports earth observation OLAP-style operations to enable efficient slicing, aggregation, and drill down. Benchmark experiments and three application studies, covering vessel speed monitoring, wildfire detection, and near-real-time three-dimensional reconstruction, quantify system performance and operational utility. Results show that the proposed approach achieves multi-gigabyte-per-second ingestion under parallel feeds, sub-second scene retrieval for typical queries, and second-scale trajectory reconstruction for short tracks. Case studies demonstrate faster alert generation, improved detection consistency, and substantial reductions in preprocessing and manual selection work compared with on-demand baselines. The principal trade-off is an upfront cost for materialization and storage that becomes economical when queries are repeated or entities are reused. The contribution of this work lies in extending the analysis-ready data concept from static imagery to continuous video streams and in delivering a practical, scalable architecture that links semantic abstraction to high-performance spatiotemporal management, thereby improving responsiveness, reproducibility, and cross-sensor analysis for Earth observation. Full article

Eosinophilic esophagitis (EoE) is a chronic, immune-mediated disorder characterized by eosinophilic infiltration of the esophageal epithelium, primarily driven by exposure to food and aeroallergens. Although dietary elimination remains the cornerstone of therapy, the identification of specific food triggers still largely relies on empiric methods. This narrative review explores the diagnostic and therapeutic role of component-resolved diagnostics (CRD) and other molecular tools in the personalized management of EoE. Across observational and cohort studies, CRD has shown improved sensitivity in detecting clinically relevant allergen sensitizations compared with conventional tests, allowing for more precise dietary guidance and, in some cases, reducing unnecessary food exclusions. However, remission rates achieved through CRD-guided diets remain comparable or slightly lower than those obtained with empiric elimination, highlighting the need for validation in prospective, controlled studies. Recent advances in omics-based diagnostics, including gene expression profiling and proteomic biomarkers, further underscore the potential of integrating molecular and immunologic endotyping into clinical practice. Overall, current evidence supports CRD as a promising adjunctive tool that enhances the precision of allergen identification but is not yet ready to replace empiric dietary strategies. Future research should focus on validating standardized CRD-guided algorithms, integrating omics-derived biomarkers, and developing non-invasive diagnostic platforms. Incorporating dietitian-led nutritional assessment and biomarker monitoring into CRD- and omics-informed care pathways may help prevent nutrient deficiencies, improve adherence, and translate molecular precision into safer, patient-centered dietary management. Full article