Search Results (55,202)

Micro-combustion for micro-thermophotovoltaic (MTPV) and micro-thermoelectric (MTE) systems is gaining renewed interest as a pathway toward compact power generation with high energy density. This review examines how emerging artificial intelligence (AI) methodologies can accelerate the development of such systems by addressing longstanding modeling, optimization, and design challenges. We analyze four major research areas: artificial neural network (ANN)-based design optimization, AI-driven prediction of micro-scale flow variables, Physics-Informed Neural Networks for combustion modeling, and surrogate models that approximate high-fidelity computational fluid dynamics (CFD) and detailed chemistry solvers. These approaches enable faster exploration of geometric and operating spaces, improved prediction of nonlinear flow and reaction dynamics, and efficient reconstructions of thermal and chemical fields. The review outlines a wide range of future research directions motivated by advances in high-fidelity modeling, AI-based optimization, and hybrid data-physics learning approaches, while also highlighting key challenges related to data availability, model robustness, validation, and manufacturability. Overall, the synthesis shows that overcoming these limitations will enable the development of micro-combustors with higher energy efficiency, lower emissions, more stable and controllable flames, and the practical realization of commercially viable MTPV and MTE systems. Full article

Military settlements are an integral part of the military defense system of the Ming Great Wall, and the spatial layout of their constituent elements embodies the wisdom of ancient military geography. However, existing studies have predominantly focused on the macro-scale distribution of military settlements, with insufficient exploration of the spatial differentiation mechanisms of their micro-level constituent elements. Therefore, this study examines 61 military settlements in Miyun District, Beijing. Based on documentary research and field surveys, the types of constituent elements were systematically identified. This study employs kernel density analysis and the Optimal Parameters-based Geographical Detector (OPGD) model to explore their spatial patterns and driving mechanisms. The results show that (1) the constituent elements of military settlements collectively exhibit a spatial pattern of “one belt and three cores”, with pronounced spatial heterogeneity; (2) Fortress level, Military strength, and Distance to the Lu Fort are the core factors influencing the spatial differentiation of elements; and (3) when multiple factors interact, the interaction between Military strength and Distance to the Lu Fort demonstrates a significant nonlinear enhancement effect. This study reveals the spatial organizational logic of the Ming Great Wall military settlements at the micro-element level, providing a scientific basis for the graded protection and adaptive reuse of military settlements in Miyun District. Furthermore, the proposed analytical framework can also offer methodological insights for studies in other regions along the Great Wall. Full article

Procyanidins, a class of substances widely distributed in nature, have attracted the attention of the scientific community due to their bioactive properties, especially with regard to human health. This review is based on an extensive examination of peer-reviewed literature, patents, and clinical trial reports published between 2005 and 2025. From an initial pool of more than 300 documents, 283 studies were selected according to criteria of scientific rigor, methodological clarity, and relevance to the research objectives. A literature search was performed using PubMed, PubChem, Google Scholar, Scopus and ResearchGate employing keywords such as Procyanidins, chemical structure, extraction, and health effects. This article provides a comprehensive overview of current methods for obtaining these compounds, which include both natural sources and synthetic approaches. It provides a concise summary of the molecular structure of procyanidins and emphasizes the importance of understanding their conformational features for predicting biological activity. The challenges of establishing correlations between the structural features of procyanidins and their properties are described. In addition, this article explores the many potential applications of these compounds, spanning both biochemistry and the field of design and synthesis of novel materials. This review provides a comprehensive evaluation of Procyanidins, focusing on their geometrical conformation analysis through advanced NMR spectroscopy techniques including homonuclear correlation (COSY, TOCSY), heteronuclear one-bond (HSQC, HMQC), multiple-bond (HMBC) experiments, and through-space correlation (NOESY) in conjunction with various extraction methodologies. Full article

As critical urban blue–green infrastructure, urban wetland parks serve as vital venues for visitors to obtain restorative experiences. However, existing studies primarily emphasize their ecological and economic benefits, with comparatively limited attention paid to their roles in promoting public mental health and enhancing well-being. Using Yanghu Wetland Park in Changsha as a case study, this research investigates how restorative environmental perception influences visitors’ well-being through two mediating variables: environmental preference and place attachment. A total of 251 valid responses were collected through field surveys and questionnaires. Structural equation modeling (SEM) was employed to empirically examine the relationships among the variables. This study enriches the theoretical framework of environmental psychology and urban landscape behavior research. It also provides evidence-based insights into the planning and design of urban wetland parks, contributing to the enhancement of public well-being and overall life satisfaction. Full article

Wide thermal cracks are a common form of pavement distress affecting primary state and county highways, urban residential streets, and parking lots across the Southwest climatic regions. These cracks are primarily caused by thermal fatigue, driven by diurnal temperature variations despite the lack of extremely cold events. This research aims to identify and analyze the local factors contributing to the initiation and propagation of thermal fatigue cracks. Field cores are collected from 12 sites exhibiting wide thermal cracks in the Phoenix metropolitan area in Arizona to evaluate their volumetric properties and the degree of binder aging. Advanced finite element (FE) models were developed to examine the influence of pavement structures and local climatic conditions on the development of tensile stresses due to thermal fatigue. The FE analysis indicated a high magnitude of thermal stresses due to cyclic temperature variations in Arizona compared to colder regions in the United States. Based on the forensic investigation and analysis performed, the initiation of wide cracks was shown to be primarily due to repeated localized damage from frequent thermal fatigue events on severely aged pavements. This damage is exacerbated by low air voids in mineral aggregate, an insufficient effective binder volume. and excessive binder aging, which compromise the structural integrity of the pavement. Full article

To address the limitations of existing cable damage identification methods in terms of environmental robustness and measurement dependency, this study proposes a novel damage identification approach based on the second-order difference characteristics of main beam deflection. Through theoretical derivation, the intrinsic relationship between cable damage and local deflection field disturbances in the main beam was revealed, leading to the innovative definition of a second-order difference of deflection (DISOD) index for damage localization. By analyzing the second-order deflection differences at the anchorage points of a three-cable group (a central cable and its two adjacent cables), the damage status of the central cable can be directly determined. The research comprehensively employed finite element numerical simulations and scaled model experiments to systematically validate the method’s effectiveness in identifying single-cable and double-cable (both adjacent and non-adjacent) damage scenarios under various noise conditions. This method enables damage localization without direct cable force measurement, demonstrates anti-noise interference capability, achieves rapid and accurate identification, and provides a technically promising solution for the health monitoring of long-span cable-stayed bridges. Full article

The growing use of radiation technologies has increased the need for shielding materials that are lightweight, safe, and adaptable to complex geometries. While lead remains highly effective, its toxicity and weight limit its suitability, driving interest in alternative materials. The process of 3D printing enables the rapid fabrication of customized shielding geometries; however, only limited research has focused on 3D-printed polymer composites formulated specifically for mixed photon–neutron fields. In this study, we developed a series of 3D-printable ABS-based composites incorporating tungsten (W), bismuth oxide (Bi₂O₃), gadolinium oxide (Gd₂O₃), and boron nitride (BN). Composite filaments were produced using a controlled extrusion process, and all materials were 3D printed under identical conditions to enable consistent comparison across formulations. Photon attenuation at 120 kVp and neutron attenuation using a broad-spectrum Pu–Be source (activity 4.5 × 10⁷ n/s), providing a mixed neutron field with a central flux of ~7 × 10⁴ n·cm⁻²·s⁻¹ (predominantly thermal with epithermal and fast components), were evaluated for both individual composite samples and layered (sandwich) configurations. Among single-material prints, the 30 wt% Bi₂O₃ composite achieved a mass attenuation coefficient of 2.30 cm²/g, approximately 68% of that of lead. Layered structures combining high-Z and neutron-absorbing fillers further improved performance, achieving up to ~95% attenuation of diagnostic X-rays and ~40% attenuation of neutrons. The developed materials provided a promising balance between 3D-printability and dual-field shielding effectiveness, highlighting their potential as lightweight, lead-free shielding components for diverse applications. Full article

Seed phenomics is a critical research field for understanding seed germination mechanisms. Metasurfaces, composed of subwavelength nanostructures, offer a promising pathway to achieve both dispersion control and imaging functionalities within an ultra-compact form factor. Recent advances in micro–nano-optics and computational imaging have opened new avenues for high-dimensional, multimodal imaging. However, conventional hyperspectral and light-field systems still face limitations in compactness, depth resolution, and spectral–spatial integration. This review summarizes recent progress in metalens and metasurface lens array-based light-field systems for hyperspectral imaging and 3D reconstruction, with a focus on the underlying principles, design strategies, and reconstruction algorithms that enable single-shot 3D hyperspectral acquisition. We further present a forward-looking roadmap toward the realization of a revolutionized imaging paradigm: a metasurface-based light-field platform that fully integrates 3D and hyperspectral imaging capabilities. In particular, we examine how dispersive metasurfaces serve as core optical elements for precise dispersion control in hyperspectral imaging systems, while metalens arrays enable accurate modulation of spatial–angular distributions in light-field configurations. We systematically review both 3D and spectral reconstruction algorithms, highlighting their roles in decoding complex optical encodings. The application of these integrated systems in seed phenotyping is emphasized, demonstrating their capability to capture 3D spatial–spectral distributions in a single exposure. This approach facilitates high-throughput analysis of morphological traits, germination potential, and internal biochemical composition, offering a comprehensive solution for advanced seed characterization. Finally, we outline a practical roadmap for implementing a metasurface-based light-field platform that integrates hyperspectral imaging and computational 3D reconstruction. This review offers a comprehensive overview of the state of the art in compact 3D light-field systems and multimodal hyperspectral imaging platforms, while providing forward-looking insights aimed at advancing smart seed phenotyping, precision agriculture, and next-generation optical imaging technologies. Full article

Bacterial spores, as one of the most resistant microbial forms, are difficult to completely eliminate through conventional heat treatments such as pasteurization, allowing them to persist in food and pose a significant threat to microbial safety. This study employed a “germination–inactivation” strategy to inactivate Alicyclobacillus acidoterrestris (AAT) spores using a germinant under low-intensity pulsed electric fields (PEFs). Analysis of germination curves identified 40 mM L-valine as the most effective germinant. Results showed that after 4-h incubation with 40 mM L-valine followed by 210 s of 0.18 kV/cm PEF treatment, the synergistic effect of electric field and ohmic heating (OH) reduced AAT spore counts by 1.73 log units. In contrast, the control group treated with the same PEF parameters without a germinant showed only a 0.54 log unit reduction. These findings indicate that germination agents significantly reduce spore resistance. Subsequent experiments confirmed that L-valine-treated AAT spores underwent pronounced structural disruption under the combined effects of the electric field and OH, leading to leakage of intracellular components such as nucleic acids and proteins. This phenomenon was verified via scanning electron microscopy (SEM) and laser confocal microscopy. Additionally, both ROS levels and ATPase activity in spores were substantially reduced, further indicating that the combined electric field and OH synergistically disrupted the spore’s external structure and internal macromolecules, leading to spore death. Thus, low-intensity PEF assisted by spore germination agents offers an energy-efficient and effective inactivation method, opening new avenues for spore inactivation research. Full article

Gas-insulated switchgear (GIS) offers multiple advantages compared to air-insulated switchgear (AIS); primarily, due to its more compact design and reduced maintenance requirements. In recent years, environmentally friendly replacement gases for SF₆ have become an important research topic, not least because EU regulation will ban the use of SF₆ in new equipment for its member states in the coming years. For detecting defects inside equipment, partial discharge (PD) measurements are an important and well-established method, including in acceptance tests (FAT and SAT) and online monitoring. An important question is whether the PD behavior of various defects analyzed in SF₆ differs in potential replacement gases. In this work, standard geometries in form of needle plane arrangements were used to analyze the PD inception behavior of natural origin gases (synthetic air, CO₂ and N_2,) in comparison to SF₆ at various application relevant pressures. PD was measured both by the conventional (IEC 60270 conform) and UHF technique, recording the phase resolved partial discharge patterns (PRPDs), as well as emitted UHF-pulses. The tip radius and the protrusion length of the needle electrode were varied in order to investigate the influence of the electric field distribution on the PD inception behavior. Results show positive pressure dependence, but also deviations from the linear growth of PDIV, intermittent discharge behavior in synthetic air for some conditions and high-current discharges in the N₂ in the setup used. Full article

In an increasingly technologized and automated world, workplace safety and health remain a major global challenge. After decades of regulatory frameworks and substantial technical and organizational advances, the expanding interaction between humans and machines and the growing complexity of work systems are gaining importance. In parallel, the digitalization of Industry 4.0/5.0 is generating unprecedented volumes of safety-relevant data and new opportunities to move from reactive analysis to proactive, data-driven prevention. This review maps how artificial intelligence (AI), with a specific focus on natural language processing (NLP) and large language models (LLMs), is being applied to occupational risk prevention across sectors. A structured search of the Web of Science Core Collection (2013–October 2025), combined OSH-related terms with AI, NLP and LLM terms. After screening and full-text assessment, 123 studies were discussed. Early work relied on text mining and traditional machine learning to classify accident types and causes, extract risk factors and support incident analysis from free-text narratives. More recent contributions use deep learning to predict injury severity, potential serious injuries and fatalities (PSIF) and field risk control program (FRCP) levels and to fuse textual data with process, environmental and sensor information in multi-source risk models. The latest wave of studies deploys LLMs, retrieval-augmented generation and vision–language architectures to generate task-specific safety guidance, support accident investigation, map occupations and job tasks and monitor personal protective equipment (PPE) compliance. Together, these developments show that AI-, NLP- and LLM-based systems can exploit unstructured OSH information to provide more granular, timely and predictive safety insights. However, the field is still constrained by data quality and bias, limited external validation, opacity, hallucinations and emerging regulatory and ethical requirements. In conclusion, this review positions AI and LLMs as tools to support human decision-making in OSH and outlines a research agenda centered on high-quality datasets and rigorous evaluation of fairness, robustness, explainability and governance. Full article

The supply and treatment of water is a highly energy-intensive process and is responsible for large amounts of greenhouse gas emissions and economic costs. There is a worldwide recognition of the requirement for more sustainable water supply systems, and the use of small hydropower turbines within water supply networks offers a viable option for electricity generation in water distribution networks at locations of excessively high flow or pressure without compromising the level of service to consumers. This paper presents a critical review of the current state of the art and knowledge regarding the available energy potential, the hydropower technology options that are under current use and development, existing implementation projects, research activities and economic aspects of this new technological field. The challenges for the improvement of sustainability of water distribution networks through the implementation of small-scale hydropower turbines within water supply networks will be also presented and analysed. Full article

The importance of GIS models to monitor the spread of infectious diseases and support emergency response has been underlined by a large body of literature and strengthened by the COVID-19 pandemic to identify possible solutions able to recognise spatio-temporal clusters and patterns, evaluate the presence of acceleration factors and define specific actions. In the field of applied research on health geography and geography of safety, this work briefly displays the main aims of the project “Integrated revealing GIS models to monitor, understand and foresee the spread of diseases and support emergency response” and shows some illustrative applications. The basic assumption of the project is to test revealing models regarding key objectives of social utility, and one of its main aims is to elaborate GIS applications able to understand the spread of COVID-19, relating the geocalisations of the cases with specific variables. In order to provide targeted evidence able to better highlight local differences, a number of elaborations derived from (Arc)GIS models and based on data regarding COVID-19 according to sex, age and healthcare facilities in the Rome municipality (Italy) are presented and contextualised as examples, also replicable for precision preparedness. Full article

Nitric oxide (NO), a fundamental gaseous signaling molecule, is indispensable for cardiovascular homeostasis. This review synthesizes the expansive field of NO biology within the unifying framework of Nitric Oxide Equilibrium (NOE), i.e., the critical balance between its synthesis, bioavailability, and degradation. In a physiological state, NOE maintains vascular health by regulating blood pressure, preventing thrombosis, suppressing inflammation, and optimizing both cardiac and mitochondrial function. Here, we analyze how NOE disruption, primarily through oxidative stress and enzymatic dysfunction, underlies the pathogenesis of major cardiovascular diseases, including atherosclerosis, heart failure, ischemia–reperfusion injury, and cerebrovascular diseases like stroke. A critical evaluation of therapeutic strategies designed to restore NOE is presented, encompassing classic NO donors and phosphodiesterase-5 inhibitors, alongside next-generation soluble guanylate cyclase modulators and precision nanomedicine approaches. By identifying key knowledge gaps and methodological hurdles, this review charts a course for future research focused on biomarker-guided interventions and personalized medicine. Ultimately, we frame the restoration of NOE as a paramount therapeutic goal, crucial to translating decades of molecular research into effective clinical practice. Full article

Background: Computer-guided static implant surgery (CGSIS) is widely adopted to enhance the precision of dental implant placement. However, significant heterogeneity in reported accuracy values complicates evidence-based clinical decision-making. This variance is likely attributable to a fundamental lack of standardization in the methodologies used to assess dimensional accuracy. Objective: This scoping review aimed to systematically map, synthesize, and analyze the clinical methodologies used to quantify the dimensional accuracy of CGSIS. Methods: The review was conducted in accordance with the PRISMA-ScR guidelines. A systematic search of PubMed/MEDLINE, Scopus, and Embase was performed from inception to October 2025. Clinical studies quantitatively comparing planned versus achieved implant positions in human patients were included. Data were charted on study design, guide support type, data acquisition methods, reference systems for superimposition, measurement software, and accuracy metrics. Results: The analysis of 21 included studies revealed extensive methodological heterogeneity. Key findings included the predominant use of two distinct reference systems: post-operative CBCT (n = 12) and intraoral scanning with scan bodies (n = 6). A variety of proprietary and third-party software packages (e.g., coDiagnostiX, Geomagic, Mimics) were employed for superimposition, utilizing different alignment algorithms. Critically, this heterogeneity in measurement approach directly manifests in widely varying reported values for core accuracy metrics. In addition, the definitions and reporting of core accuracy metrics—specifically global coronal deviation (range of reported means: 0.55–1.70 mm), global apical deviation (0.76–2.50 mm), and angular deviation (2.11–7.14°)—were inconsistent. For example, these metrics were also reported using different statistical summaries (e.g., means with standard deviations or medians with interquartile ranges). Conclusions: The comparability and synthesis of evidence on CGSIS accuracy are significantly limited by non-standardized measurement approaches. The reported ranges of deviation values are a direct consequence of this methodological heterogeneity, not a comparison of implant system performance. Our findings highlight an urgent need for a consensus-based minimum reporting standard for future clinical research in this field to ensure reliable and translatable evidence. Full article