Search Results (3,275)

Healing skin wounds is still difficult in many clinical situations, especially when the wounds are chronic or infected. These wounds often stay inflamed for long periods, and the risk of bacterial invasion is high. Oxidative stress tends to increase as well, while the formation of new blood vessels is often inadequate. Because of these factors, wound repair depends on the proper coordination of several biological events. These include basic antimicrobial activities, the control and resolution of inflammation, protection against oxidative damage, the rebuilding of collagen structures, and the development of new vascular networks. Traditional Chinese Medicine (TCM) provides many active compounds. These compounds work on many targets and through different pathways. They show good potential in wound treatment. But many TCM compounds have poor solubility in water. They are also unstable, have low bioavailability, and do not pass through the skin easily. These problems limit their use in clinical settings. Nanotechnology offers new ways to solve these problems. Nanodelivery systems can improve the solubility and stability of active compounds. They can also help the compounds enter the skin and stay in the wound area. Many types of nanocarriers have been developed, such as liposomes, polymer nanoparticles, nanogels, and inorganic nanomaterials. These systems can also provide controlled release or release that responds to the wound environment. This can make the treatment more accurate. In this review, we summarize how major TCM-derived compounds support wound repair and describe the biological mechanisms behind their effects. We also discuss recent nanodelivery approaches that aim to strengthen these therapeutic actions. These combinations can improve antibacterial performance, shape the immune response, reduce reactive oxygen species, and help the skin close more quickly. We also point out several challenges, such as concerns about material safety, the need for more consistent herbal extraction methods, gaps in mechanistic understanding, and the difficulty of producing these formulations on a large scale. Taken together, these points suggest that nanodelivery approaches using TCM-derived compounds still need more careful study and steady improvement before they can be used more widely in wound care. Full article

Global supply chains face intensifying pressures from disruption, regulatory complexity, and sustainability mandates, requiring a shift toward more resilient and adaptive coordination. While artificial intelligence (AI) and blockchain have been recognised as complementary enablers, their implementation remains largely fragmented, existing as isolated tools linked by manual data exchange rather than integrated, programmable logic. This paper addresses this orchestration gap by proposing the Dynamic Resource Orchestration Framework for AI-Blockchain Integrated Supply Chains (DROF-AIBC). Grounded in Resource Orchestration Theory (ROT) and Dynamic Capabilities Theory (DCT), the framework provides a theoretical foundation for the strategic and autonomous orchestration of digital resources. Unlike classic supply chain orchestration, which focuses on the linear coordination of physical assets and legacy systems, DROF-AIBC conceptualises an “intelligent conductor” as a coordination mechanism combining AI-driven analytics and smart contract-based execution. This mechanism supports the configuration, optimisation, and monitoring of resources in response to changing external signals, effectively closing the loop between analytical insights and verifiable execution. The paper further substantiates how this autonomous capability serves as a foundational roadmap for the Industry 5.0 paradigm, embedding human-centricity through Explainable AI (XAI) to provide a “provenance of logic”, promoting circular economy sustainability, and fostering systemic resilience in turbulent environments. The framework aims to provide both a theoretical foundation and a practical roadmap for orchestrating AI and blockchain to advance resilient, sustainable and adaptive supply chains. Full article

Avocado (Persea americana Mill.) is one of the most widely consumed fruit tree crops worldwide, with cultivation expanding rapidly beyond its Mesoamerican and northwest South America center of origin. In emerging secondary diversity centers such as East Africa, farmers have long propagated seedling naturalized populations that may hold valuable reservoirs of genetic diversity, yet these resources remain underexplored. To help fill this gap, this study developed the first genomic resources for avocados in Tanzania, where avocado has a long history of introduction and diversification dating to the first Arab incursions and Catholic missionary missions. Low-coverage whole-genome resequencing (lcWGS) data were obtained from 95 trees sampled in Tanzania across the low- to mid-altitude Morogoro region (n = 25) and the Southern Highlands—i.e., the Iringa (n = 20), Mbeya (n = 30) and Ruvuma (n = 20) regions. In order to guide racial assignation, sequences were merged with NCBI-available lcWGS data from 205 avocado trees, including 42 commercial varieties, with reported ancestry. Population stratification as inferred via maximum likelihood phylogenetic inference, genetic principal component analysis, and ADMIXTURE unsupervised clustering suggested that the sampled Tanzanian avocado trees were genetically closer to the West Indian race and more distant from the northwest South American Caribbean and Andean groups. Additionally, while the trees from the low- to mid-altitude region of Morogoro were almost exclusively West Indian type, some trees from the Southern Highlands aligned more closely with West Indian × Guatemalan and West Indian × Mexican hybrids. These trends were equally supported by a subset of 10,460 high-coverage (10×) SNP markers. Together these findings clarify the dynamics of avocado diversification in a secondary center in East Africa, spanning recent introductions from a single Mesoamerican race, adaptation to a wide range of locally geographic conditions, and farmer-driven selection matching local tribal preferences. Characterizing these locally adapted resources is key for identifying underrepresented yet promising provenances, developing resilient and sustainable horticultural production systems, and safeguarding the species’ global genetic heritage. Full article

Bitter compounds may function not only as taste substances but also as important active constituents mediating therapeutic effects. Their recognition is primarily mediated by bitter taste receptors (TAS2Rs), which exert pharmacological effects, such as regulating glucose metabolism, anti-inflammatory properties, and immune modulation, aligning closely with the therapeutic effects of bitter Chinese herbal medicine (BCHM). Contemporary pharmacological research has increasingly underscored the therapeutic potential of bitter traditional Chinese medicine (TCM), particularly through their bioactive constituents in the prevention and treatment of diverse pathological conditions. Here, we systematically review the diversity of bitter compounds from TCM and features of TAS2Rs, including their tissue distribution, physiological functions, structural characteristics, signal transduction mechanisms, and single-nucleotide polymorphisms. While numerous bitter phytochemicals have been characterized as agonists of TAS2Rs, the precise physiological functions and underlying molecular mechanisms mediated by TAS2R activation remain incompletely elucidated. This knowledge gap is largely attributable to several methodological and biological challenges, including the widespread tissue distribution of TAS2Rs, the complexity of their downstream signaling cascades, and the structural and functional heterogeneity of bitter compounds. This review outlines theoretical foundations, future perspectives and challenges for the drug development of TAS2R from BCHM. Full article

This study systematically evaluated the taxonomic relationship between Streptococcus taoyuanensis ST2^T and Streptococcus caecimuris CLAAV18^T. Comparative genomic analysis revealed a high 16S rRNA gene sequence similarity of 99.6%, with the two strains clustering closely in the 16S rRNA-based phylogenetic tree. The genetic relatedness was further validated by Multi-Locus Sequence Typing (MLST) analysis: assessments of seven conserved housekeeping genes (atpD, gapA, gyrB, GdhA, recA, dnaK, and sdhA) demonstrated complete concordance in target fragment lengths (ranging from 33 bp to 121 bp). No size polymorphisms, insertions, or deletions were detected, indicating a highly conserved core genome. At the whole-genome level, the Average Amino Acid Identity (AAI), Average Nucleotide Identity (ANI), and digital DNA-DNA hybridization (dDDH) values between the two strains were 96.8%, 95.7%, and 84.6%, respectively. These values significantly exceed the established thresholds for species delineation (AAI: 95.5%; ANI: 95%; dDDH: 70%), providing robust genomic evidence that both strains belong to the same species. Furthermore, phenotypic testing confirmed nearly identical physiological characteristics, with only minor biochemical variations. Based on the integration of phylogenetic, genomic, and phenotypic evidence, we formally propose Streptococcus taoyuanensis as a later heterotypic synonym of Streptococcus caecimuris. Full article

Background: Chronic heart failure (CHF) in older adults requires sustained self-management and close follow-up, yet day-to-day care is often carried out by families with support from primary healthcare nurses. In Saudi Arabia, where family caregiving is culturally normative, collaboration between nurses and patients’ families may be pivotal to effective CHF management, but remains insufficiently understood in primary healthcare contexts. Methods: A qualitative study informed by an interpretive phenomenological approach was conducted. Participants (n = 24; 12 nurses and 12 family caregivers) were recruited using purposive sampling from primary healthcare centers in Riyadh, Saudi Arabia. In-depth, semi-structured interviews were conducted in Arabic or English, audio-recorded, transcribed verbatim, and analyzed using reflexive thematic analysis following Braun and Clarke’s six-phase framework. Strategies to enhance trustworthiness included member checking, peer debriefing, maintenance of an audit trail, and reflexive journaling. Results: Twenty-four participants (12 nurses and 12 family caregivers) were interviewed. Four interrelated themes were generated from both nurses’ and family caregivers’ accounts. (1) “We Are Caring Together”: Collaboration was experienced as shared responsibility for daily CHF management, grounded in trust; (2) Navigating Roles and Boundaries: Participants described unclear expectations, role overlap, and tension between professional authority and family knowledge; (3) Communication as the Engine of Collaboration: Effective partnerships depended on clear information exchange, caregiver-tailored education, and continuity of contact, while communication gaps created uncertainty and delayed support-seeking; and (4) Cultural and System Constraints Shaping Collaboration: Strong family obligation motivated caregiving but also intensified moral pressure and limited help-seeking, while time pressure and fragmented services constrained meaningful engagement and continuity across settings. Conclusions: Nurse–family collaboration in CHF management is relational, shaped by trust, role negotiation, and communication, and constrained by cultural norms and system pressures. This study contributes to the literature by demonstrating how moral obligation, hierarchical professional norms, and system fragmentation distinctively shape collaboration in the Saudi primary care context, extending existing conceptualizations derived primarily from Western individualist settings. Strengthening collaboration requires explicit role clarification, health literacy–informed caregiver education, continuity of contact, and organizational supports. Findings are limited by purposive sampling, single-city context, and exclusion of patient perspectives. Full article

Background/Objectives: Early intervention is associated with improved outcomes for young children with developmental delays, yet many with mild delays are ineligible for services under the Individuals with Disabilities Education Act (IDEA). The Early Discovery (ED) Program addressed this gap by providing short-term, targeted intervention for children ages 0–5 who did not qualify for publicly funded services. This study evaluated program outcomes across intervention types. Methods: During 2024–2025, 342 families completed the ED Program, receiving one of the following: speech-language (68%), general developmental (12%), occupational (14%), or behavioral (6%) intervention across 8–20 sessions. Eligibility required Miami-Dade residency and ineligibility for IDEA-funded services. Standardized pre- and post-intervention assessments were analyzed using descriptive statistics, correlations, and group comparisons. Results: Most households reported incomes <$70,000 (71%), with many experiencing additional risk factors including prematurity (15%), public or no insurance (47%), limited English proficiency (21%), and single-caregiver households (30%). Overall, 85% of children met criteria for improvement. Improvement rates varied by child ethnicity. No statistically significant differences were observed by child age, race, gender, prematurity, insurance status, caregiver demographics, household characteristics, or intervention type. Sensitivity analyses largely confirmed the primary findings, with ethnicity no longer significant and younger age emerging as a significant predictor of improvement. Conclusions: Findings suggest short-term, targeted intervention may support developmental progress among young children with mild delays who would otherwise remain unserved. Community-based programs such as ED may play a critical role in advancing developmental equity by reaching children with developmental and socioeconomic risk factors prior to school entry. Full article

Heterogeneity at the grain scale strongly influences hydraulic fracturing in crystalline rock; however, systematic studies quantifying its impacts on the evolution of injection pressure and crack propagation remain limited. To address this gap, we employ a hydro-mechanical phase-field model incorporating Voronoi-based microstructures to systematically quantify the effects of grain-scale heterogeneity on hydraulic fracturing. Two numerical experimental programs are designed to examine the effects of (i) mean grain size and (ii) mineral distribution under different axial stresses. The simulations reveal a close coupling between injection pressure and crack-length evolution, and both responses are strongly governed by grain-scale heterogeneity. When the fracture enters weak minerals, it advances rapidly and pressure drops; when it encounters on strong minerals, growth slows or arrests and pressure builds until a threshold triggers the next advance. Moreover, peak pressure statistics further indicate that mineral distribution dominates the response scatter, while axial stress plays a secondary role. Specifically, the mean peak pressures at 0 and 10 MPa are similar (about 14.31 and 14.21 MPa), whereas rearranging minerals within the same Voronoi tessellation changes peak pressure by more than 4 MPa. Higher peaks occur when strong minerals lie ahead of the initial crack tip, increasing resistance to initiation and early growth. Finally, the stress state modulates fracture trajectories: under low axial stress, fractures preferentially follow mineral boundaries, whereas higher axial stress strengthens macroscopic stress guidance and shifts the path toward a direction closer to being perpendicular to the maximum principal stress. This trend is consistent with energy minimization, since interface detouring under high axial stress incurs a larger elastic free energy penalty. Full article

Effective Parkinson’s disease (PD) management is hindered by the intermittent nature of clinical snapshots and the discomfort of rigid monitoring hardware. This review critically evaluates the synergy between flexible bioelectronics and artificial intelligence (AI) for continuous remote monitoring. Our analysis reveals that while material innovations have achieved milligram-level sensitivity, a significant ‘translational gap’ persists due to limited validation in real-world environments and small cohort sizes. We conclude that multimodal fusion architectures are essential for accurately mapping digital biomarkers to clinical gold standards such as MDS-UPDRS. By leveraging edge AI for privacy and closed-loop feedback for intervention, this integration facilitates the transition from reactive clinical visits to proactive, personalized digital home-care ecosystems. Full article

Autonomous vegetation management in unstructured forest environments imposes a conflicting requirement: maximizing wide-area coverage while maintaining close-proximity safety around irregular obstacles. Conventional repulsion-based avoidance methods often fail to meet mowing requirements by prematurely steering robots away from target trees, resulting in significant unmowed gaps. To address this limitation, this paper proposes a Hybrid Path Planning (HPP) framework that combines a shared global Boustrophedon coverage scaffold with a local orbital maneuvering strategy inspired by celestial two-body dynamics. Rather than redefining the full environment model, the proposed method treats the currently active tree as the dominant local interaction center and generates orbit-like trunk-proximal motion around it. A variable virtual mass model is introduced so that the local attraction weakens as mowing progresses, thereby supporting transition to a rejoining phase governed by a finite state machine (FSM). MATLAB simulations indicate that the proposed framework can improve the trade-off among near-tree coverage, clearance preservation, and trajectory continuity relative to repulsion-centered local-avoidance baselines under the same global traversal scaffold. Full article

Elevator fault diagnosis heavily relies on high-precision sensing of microscopic physical states. Although Micro-Electro-Mechanical System (MEMS) sensors can capture such subtle features, they are constrained by high-frequency data streams, environmental noise, and the semantic gap between raw sensor data and actionable maintenance decisions. This study proposes a collaborative edge–cloud intelligent diagnosis framework specifically designed for elevator systems. On the edge side, a lightweight temporal Transformer model, ELiTe-Transformer, was designed and deployed on the Jetson platform. This model enhances sensitivity to event-driven MEMS signals through an industrial positional encoding mechanism and by integrating linear attention and INT8 quantization techniques, achieving a real-time inference latency of 21.4 ms. On the cloud side, retrieval-augmented generation (RAG) technology was adopted to integrate physical features extracted at the edge with domain knowledge, generating interpretable diagnostic reports. The experimental results show that the overall accuracy of the system reaches 96.0%. The edge–cloud collaborative framework improves the accuracy of complex fault diagnosis to 92.5%, and the adoption of RAG reduces the report hallucination rate by 71.4%. This work effectively addresses the bottlenecks of MEMS perception in elevator fault diagnosis, forming a closed loop from micro-signal acquisition to high-level decision support. Full article

A large number of existing studies show that fiber-reinforced concrete (FRC) and ultra-high-performance concrete (UHPC) have improved crack resistance relative to conventional concrete, but there is limited research on further advancing the structural performance of FRC and UHPC through prestressing and self-healing. This study addresses this knowledge gap by introducing shape memory alloy (SMA) bars as reinforcement. Existing studies on using SMA bars for prestressing or healing are focused on conventional concrete. Thus, this study experimentally evaluates SMA bars in FRC and UHPC. Small-scale flexural specimens are fabricated for this purpose. Three mix designs are considered, corresponding to mortar, FRC, and UHPC. The prestrained and embedded SMA bars are employed in two different ways. The first method is to activate the SMA to prestress the concrete, thereby delaying cracking. The second is to activate the SMA after cracks develop, thereby closing and “healing” the cracks. Additionally, different heating methods are considered. Heating with electricity is compared to heating by electromagnetic induction to study their efficiency and safety. The experimental results validate the use of SMA for prestressing the different types of concrete. The concept of healing is also validated for all three types of concrete. Reductions in crack width as high as 80%, 90%, and 84% are measured in the mortar, FRC, and UHPC specimens, respectively. Full article

In this study, we examine a length preserving geodesic curvature difference flow for smooth strictly horocyclically convex simple closed curves in the hyperbolic plane ${\mathbb{H}}^2$. Given an initial curve ${\gamma }_1$ and a target curve ${\gamma }_2$ of the same hyperbolic length, we evolve ${\gamma }_1$ by a normal speed given by the difference of the reciprocals of geodesic curvatures evaluated at points with the same outward unit normal, together with a time-dependent scalar term $\mathrm{\Gamma }\left(t\right)$ chosen to preserve the hyperbolic length. Using Leichtweiβ’s hyperbolic support function and Howe’s curvature formula, the flow is reformulated as a quasilinear uniformly parabolic equation on ${\mathbb{S}}^1$ with a nonlocal term $\mathrm{\Gamma }\left(t\right)$. We prove short-time existence, uniqueness, and preservation of strict horocyclic convexity. Linearizing the support function equation at the target support function yields a uniformly elliptic operator whose kernel contains the infinitesimal isometry directions. Under a spectral gap assumption on a normalized slice transverse to the isometry orbit, we prove global existence and exponential convergence for initial data sufficiently close to the target curve. In the last section, this assumption is verified explicitly when the target curve is a geodesic circle. Full article

The European Union aims to cut greenhouse gas emissions by 55% by 2030 and reach climate neutrality by 2050, targets that depend on expanding renewable generation in the European energy system. While photovoltaic (PV) capacity has grown quickly in several member states, others remain far behind. This paper frames that divergence as a systems planning problem: installed MW expands through diffusion-like dynamics, but the conversion of investment into energizable capacity is filtered by grid-integration constraints and institutional throughput. The study develops a macro-level framework for systems-level assessment and decision support to guide PV capacity planning and budget allocation using official 2012–2022 data for 22 EU countries. We combine (i) unsupervised clustering of standardized national deployment trajectories, (ii) bounded logistic fits interpreted as an operational diffusion-with-saturation representation that yield comparable growth parameters and maturity years (80–90% of the estimated ceiling), and (iii) a proportional reallocation scenario for countries below 5 GW in 2022. Three clusters emerge—steady growth, early plateau, and atypical paths—and an analytically tractable maturity indicator integrates capacity, rate, and timing in a single measure. In a 10 GW reallocation scenario, average progress toward the 5 GW benchmark rises from 9.8% to 23.1%, closing about 14.8% of the aggregate shortfall. The allocation experiment reveals a clear asymmetry: systems with an existing installed base convert additional MW into benchmark progress more efficiently than very low-baseline systems, where binding constraints are more likely to sit in permitting, interconnection queues, and hosting capacity rather than in finance alone. Turning these allocations into usable capacity depends on timely interconnection and power-electronics integration and on grid-enablement constraints such as interconnection readiness, inverter compliance, and local hosting capacity in high-penetration areas. The contribution is a transparent, updateable decision-support pipeline that links observed trajectory regimes to a maturity “clock” and an auditable allocation baseline, making the trade-off between closing capacity gaps and respecting feasibility filters explicit in an EU system with heterogeneous national subsystems. The proposed approach links macro-level maturity clusters to operational feasibility signals in the grid integration layer, showing that modeling-based allocation can improve system progress but cannot substitute grid-enablement measures, highlighting the importance of regional coordination in the EU energy system under heterogeneous national trajectories. Full article

Onchocerca flexuosa is a vector-borne filarial nematode infecting red deer (Cervus elaphus) throughout Europe. Despite numerous reports from Central, Northern, and Southern Europe, its occurrence in South-Eastern Europe has remained largely undocumented. This study provides the first molecularly confirmed report and the first systematic epidemiological assessment of O. flexuosa in red deer in Croatia. During the 2024–2025 hunting season, 110 legally harvested red deer from central Croatia were examined for subcutaneous nodules. Nodules were evaluated morphologically, and adult nematodes were identified and confirmed by sequencing of a fragment of the mitochondrial cytochrome c oxidase subunit I (COI) gene. Subcutaneous nodules were detected in 53.6% (59/110) of examined animals. O. flexuosa was confirmed in 52 deer, corresponding to an overall prevalence of 47.3%. Co-infection with Hypoderma diana occurred in 21.2% of infected animals. Sequence similarity ranged from 96.37% to 99.85% compared to published European O. flexuosa isolates. Phylogenetic analysis placed Croatian sequences within the established European lineage, without evidence of regional genetic divergence. The observed prevalence falls within the intermediate range reported across Europe and indicates stable local transmission. These findings close an important geographical knowledge gap and demonstrate that nodular onchocercosis is established in red deer populations in South-Eastern Europe. Full article