Search Results (985)

Historical and cultural districts are the outcome of cultural sedimentation brought about by urban development, and they embody distinctive urban historical and cultural connotations. Ignoring the protection of the historical and cultural value contained in streetscapes will not only decrease the life quality of residents but will also diminish distinctive local urban features. This study focused on the Fangcheng historical and cultural district in Shenyang. The scenic beauty estimation method was employed to evaluate urban style and features’ visual quality, while the semantic differential method was used to obtain the subjective perceptual features of samples. The study also systematically explored the dynamic relationship between urban style and features’ quality and subjective perception in historical and cultural districts. The results show that color richness, coherence, iconic status, and continuum all exert significant positive predictive effects on visual preferences regarding urban style and features. Color richness was the primary determinant of urban style and features’ visual quality. Continuum interfaces, a unified spatial texture, and coordinated dimensions contributed significantly to improving urban style and features’ visual quality in historic and cultural districts. The distinctiveness and cultural iconic status of historical and cultural districts enhanced the residents’ identity and place memory. Moreover, the coherence and continuum of style between the old and new elements promoted an integrated aesthetic experience. The evaluation results revealed that the overall visual quality of urban style and features of most streets was medium. However, streets with a higher visual quality cluster among historical streets and commercial streets. The residential streets demonstrated a significantly lower visual quality. Establishing a comprehensive evaluation system that integrates urban style and features, subjective perception, and the style of historical and cultural districts can contribute to covering the shortage in the traditional urban style and features’ research and also provide a basis for urban regeneration at the micro scale. Full article

The escalating power density in Active Phased Array Radar has made the thermal management of Transmitter and Receiver (T/R) modules a critical bottleneck for radar performance. To address the thermal resistance of traditional cold plates, this study investigates an innovative embedded cooling strategy utilizing micro-pyramid arrays and advanced nanofluids. Thermal performance was evaluated using maximum temperature, maximum temperature difference and surface temperature standard deviation (ST). Higher pyramid density markedly enhances temperature uniformity, an effect that scales positively with the power load. Under a 100 W condition, the 8-circle micro-pyramids configuration (the densest structure with roughness Ra = 1.3) achieved a 22.58 K reduction in maximum temperature and a 22.5% improvement in temperature uniformity compared to the 2-circle structure, and outperformed the 4-circle structure by 16.98 K and 17.9%, respectively. Furthermore, a comparative analysis of nanofluids (Al₂O₃, CuO, graphene, and h-BN) is conducted and it is found that graphene nanofluid exhibits the best overall heat transfer enhancement because of its high thermal conductivity and moderate reduction in specific heat capacity. The thermal performance of the nanofluid is evaluated by comparing the maximum temperatures of the heat source at the 8-circle structure. The synergistic coupling of graphene nanofluid with the 8-circle array yields a remarkable 35.38% enhancement in temperature uniformity at 100 W. The enhancement mechanisms are mainly attributed to intrinsic thermophysical properties of the nanoparticles and convection caused by denser pyramid array. The aforementioned findings provide important guidance for the thermal management design of antenna and other high-density integrated electronic systems with embedded cold plate design demand. Full article

Autonomous vehicles at level 3 and above must maintain high navigation accuracy, particularly in global navigation satellite system (GNSS)-denied environments. The main innovations of this work are threefold. First, we integrate visual inertial odometry (VIO) and light detection and ranging (LiDAR) inertial odometry (LIO) as external updates to mitigate the rapid drift of micro-electromechanical system (MEMS)-based industrial-grade inertial measurement units (IMUs) during long-term GNSS outages. Second, we adopt a redundant IMU (RIMU) approach that fuses multiple low-cost IMUs to reduce sensor noise and improve reliability. Third, we propose a system calibration methodology using both static and dynamic vehicle motion to estimate extrinsic parameters (boresight angles and lever arms) of the sensors, achieving an overall boresight angle root-mean-square error of 0.04 degrees in the simulation. Experiments were conducted under a 7 min GNSS-denied scenario in an underground parking lot, allowing for comparison of the error characteristics of multi-sensor fusion schemes against a navigation-grade reference. The INS/GNSS/LIO framework achieved a two-dimensional root-mean-square position error of 1.22 m (95% position error within 2.5 m), meeting the lane-level (1.5 m) accuracy requirement under a GNSS outage exceeding 7 min without prior maps. In contrast, the RINS/GNSS/VIO framework yielded a 4.71 m 2D mean position error under the same conditions. This paper provides a quantitative comparison of the baseline error characteristics of VIO-, LIO-, and RIMU-assisted INS/GNSS fusion under a GNSS-denied navigation scenario. Full article

Radiation-responsive promoters represent a functionally distinct class of transcriptional regulatory elements that translate genotoxic stress signals into quantifiable gene expression outputs. These promoters occupy a unique mechanistic position within the broader radiation biomarker landscape: rather than directly measuring molecular damage products, they report the cellular interpretation of radiation-induced stress through coordinated gene regulatory networks. This review provides a systematic analysis of five major classes of radiation-responsive promoters—microRNA (miRNA) promoters, tRNA-derived small RNA (tsRNA) promoters, acute-phase protein gene promoters, DNA repair gene promoters, and long non-coding RNA (lncRNA) promoters—with emphasis on their regulatory logic, dose-response characteristics, and current evidence for clinical deployment. We further describe four complementary screening strategies: homology-based conservation analysis, functional genomics and transcriptomics, epigenetic modification profiling, and synthetic biology promoter engineering. Applications spanning biosensor development, biological dosimetry, treatment response prediction, and radiation-guided gene therapy are evaluated within a two-track framework that distinguishes biomarker-oriented applications (Track A) from tool-oriented reporter gene systems (Track B). Critical appraisal of current limitations—including insufficient clinical-grade validation, absence of standardized dose-response curves, and reproducibility deficits—is integrated throughout. Future priorities include multi-center prospective validation studies, FAIR-compliant data infrastructure, AI-driven multi-omics integration, and point-of-care detection platforms. Radiation-responsive promoter biology holds significant potential for advancing precision radiotherapy and nuclear emergency medical response, contingent upon systematic closure of the current evidence gap relative to established gold-standard cytogenetic methods. 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

Reliable autofocus is a fundamental prerequisite for precise positioning in micro-assembly systems, where complex reflections, scale variations, and narrow depth-of-field often degrade the robustness of traditional sharpness metrics. To address these challenges, we propose an efficient two-stage autofocus method for a dual-camera micro-vision system based on a spatial-frequency image quality assessment (IQA) model. First, we design WaveMamba-IQA for image sharpness estimation, synergistically combining the Discrete Wavelet Transform with Vision Transformers to capture high-frequency details and semantic features, further enhanced by Multi-Linear Transposed Attention and Vision Mamba for global context modeling. Moreover, we implement a coarse-to-fine autofocus workflow, employing the Covariance Matrix Adaptation Evolution Strategy for global optimization on the horizontal camera, followed by geometric prior-based precise adjustment for the oblique camera. Experimental results on a custom microsphere dataset demonstrate that WaveMamba-IQA achieves a Spearman correlation coefficient of 0.9786. Furthermore, the integrated system achieves a 98.33% autofocus success rate across varying lighting conditions. This method significantly improves the robustness and automation level of micro-assembly systems, effectively overcoming the limitations of manual and traditional focusing techniques. Full article

In irrigated areas around the world, the recommendation for the use of subsurface drainage is also associated with controlling salinity problems. Due to the high implementation cost, the search for solutions that make this requirement more flexible is necessary. Among the options to be investigated is the hypothesis that the height and salinity of the water table in plots located at the highest points of a toposequence are lower and do not compromise plant development, even without underground drainage systems. In this context, the present work was developed to monitor and evaluate the variation in water level or mottling over twelve months, as well as to measure and analyze the electrical conductivity and average pH of the water table during this period and its possible impact on plants. For this purpose, three lots in toposequence were selected in the Senador Nilo Coelho Public Irrigation Project, Petrolina—PE, with previously defined characteristics: soil classification (Plinthic Yellow—Ultisol), crop planted (Mangifera indica L.) and irrigation system used (micro-sprinkler). Precipitation, reference evapotranspiration and volume of water applied via irrigation were monitored by an automatic weather station and hydrometers in each lot. In each plot, nine observation wells were installed, distributed in a grid, with the aim of make monthly measurements of the water table level or mottling. The electrical conductivity and pH of the groundwater were also measured to obtain the average monthly value for each lot. Illustrative 3D maps of the water table level in relation to the ground surface were created using the simple kriging method, in the UTM SIRGAS 2000 24S projection system. The absence and presence of groundwater in the upper and lower hillslope lots, respectively, were favored by the toposequence. The decision to install underground drainage or not can be made on a case-by-case basis; this must take into account, among other aspects, changes in physical characteristics along the soil profile, possible occurrence of mottling, the quality of water for irrigation, the irrigation management adopted and the position of the lot in the toposequence. Full article

Permeability is affected by nanopores and pore structure, and anisotropic permeability is the result of shale lamination, orientation, and stratification of minerals. To understand the reasons for permeability anisotropy, the pore networks of over-mature shale has been studied. The mineral compositions, petrophysical properties, and pore structures of the Lower Cambrian Niutitang Formation shales were analyzed using subcritical gas adsorption, field-emission scanning electron microscopic, and X-ray micro-computed tomographic methods. Quartz, clay minerals, and carbonate are the dominant minerals in the shales. The bedding-parallel and bedding-perpendicular permeabilities are 1.25–46.21 × 10⁻² and 1.38–6.62 × 10⁻² mD, respectively. The anisotropy of permeability, which is the ratio between the bedding-parallel and bedding-perpendicular permeability, is 0.21–26.87. The micropore and Barrett–Joyner–Halenda pore volumes are 0.54–3.62 and 0.05–0.69 mL/100 g, respectively. The bedding-parallel permeability is correlated positively with the micropore and Barrett–Joyner–Halenda pore volumes. Thin-section observations indicate the shales exhibit a bedding-parallel alignment of phyllosilicate minerals and planar deformation bands. The scanning electron microscopy shows deformation of the lamination and parallel alignment of the clay minerals due to compaction or differential compaction over coarser-grained quartz grains. The scanning electron microscopy images and subcritical gas adsorption data indicate that the pore fracture system is parallel to bedding and formed after diagenesis. Furthermore, X-ray micro-computed tomographic analysis shows that the micro-fractures are also preferentially oriented, parallel to bedding. Full article

The circular economy (CE) has emerged as a central policy framework for advancing sustainable urban development; however, empirical evidence regarding the role of micro, small, and medium-sized enterprises (MSMEs) in metropolitan CE transitions remains limited, particularly in arid regions. This study examines how private sector firms and MSMEs engage with CE practices within an arid metropolitan context, using the Dammam Metropolitan Area (Saudi Arabia) as an illustrative case study. Adopting a place-based and governance-sensitive analytical perspective grounded in urban studies scholarship, the research employs a structured quantitative survey of 180 firms across key urban–industrial sectors. The analysis investigates levels of CE awareness, adoption patterns, perceived barriers, support needs, and future expectations. The findings indicate that MSMEs primarily engage in resource-based and efficiency-oriented circular practices, while more systemic models, such as supply-chain integration and platform-based circular solutions, remain limited. Moreover, capability-related factors, particularly skills and technological capacity, exert a stronger influence on adoption than awareness alone. Importantly, the study identifies a high level of latent willingness among MSMEs to invest in circular practices under supportive policy and institutional conditions. The discussion reframes CE transitions as governance-mediated urban development processes, emphasizing the importance of metropolitan coordination, institutional capacity-building, and shared spatial infrastructure. By grounding the analysis in the case of the Dammam Metropolitan Area, the study contributes to urban studies and CE scholarship by positioning MSMEs as conditionally willing system-building actors whose engagement is essential for advancing inclusive and place-sensitive circular transitions in arid metropolitan regions. Full article

A support is a machine element that transmits loads to the base or other structures. A simple support is designed to withstand forces acting in the longitudinal direction, and a flexible support is designed to withstand forces in both longitudinal and transverse directions. The possibilities for the use of flexible supports are very wide. In precision mechanics, flexible supports are used in positioning systems, micropositioning systems, vibration damping systems, as well as in fastening applications requiring adjustment and other structural configurations. The main problem of flexible supports is ensuring stability. This work examines the dependence of the stiffness of supports used in mechanical and mechatronic systems on the material and dimensions of the flexible element. A theoretical analysis of the stiffness of flexible supports, finite element method (FEM) modeling, and experimental stiffness research were performed. A special stand was manufactured for experimental research. A research methodology was developed, according to which experimental research was carried out. After theoretical, FEM and experimental research, the results obtained were compared and conclusions were formulated. The obtained data can be practically used in the research and design of new flexible supports that ensure desired stability, as well as in the improvement of existing support structures. Full article

To address the issue of reduced accuracy or even divergence in micro-electro-mechanical inertial navigation systems’/global navigation satellite systems’ (MINSs’/GNSSs’) integrated navigation systems caused by small amplitude fault in GNSS measurement information, this paper proposes a robust extended Kalman filter algorithm based on a sliding window fractional-order grey prediction model (SWFGM(1,1)-REKF). When GNSS signals are disrupted, this algorithm first detects system faults through a weighted index sequential probability ratio test (SPRT) detection. Then, it uses GNSS measurements predicted by a sliding window fractional-order grey prediction model (FGM(1,1)) to replace the faulty GNSS data and integrates them with MINSs. Finally, it combines robust estimation to construct a robust extended Kalman filter to correct the integrated information. Simulation and vehicle experiment results show the advancement of SWFGM(1,1)-REKF. When GNSS measurements experience small amplitude abrupt faults, compared with traditional robust extended Kalman filter algorithm based on a chi-square test, the proposed algorithm improves filtering accuracy of velocity and position. In the vehicle small amplitude mutation fault experiment, the velocity and position accuracy are increased by more than 50% and 80% respectively. Full article

Foreign direct investment (FDI), particularly high-quality FDI, serves as a critical driver in achieving the Sustainable Development Goals (SDGs). However, understanding how to enhance FDI quality remains a pressing challenge for policymakers and researchers alike. As a core determinant of FDI quality, the business environment necessitates a thorough examination of its underlying mechanisms. Drawing on provincial-level data and firm-level data from listed foreign-invested enterprises in China spanning 2011 to 2023, this study constructs an FDI quality evaluation index system aligned with the goal of sustainable development at the micro-enterprise level, empirically examines the impact of the business environment on FDI quality. Our findings reveal a consistent upward trajectory in China’s FDI quality throughout the sample period, with the business environment exerting a significantly positive influence. Dimensional decomposition reveals that the government-legal environment and openness to foreign investment demonstrate particularly pronounced positive effects. These effects operate primarily through three mechanisms: stimulating entrepreneurship, accelerating digital transformation, and optimizing supply chain configurations. Moreover, these effects are more pronounced among wholly foreign-owned enterprises, firms with superior knowledge absorption capacity, and those facing higher perceived economic policy uncertainty. Extended analysis further demonstrates that enhanced FDI quality makes substantial contributions to sustainable development outcomes. This study extends the research on FDI quality from the macro level to the micro level, broadening the research perspective of related fields. The conclusions not only furnish robust theoretical evidence on how business environments foster high-quality FDI, but also provide actionable policy insights for countries seeking to optimize their institutional frameworks to attract quality foreign investment in alignment with the SDGs. Full article

Nanopositioning systems (NPS) are used in various fields of technology, such as micro- and nanoelectronics, optics, and biotechnology, where demands for higher dynamic performance and sub-nanometer accuracy are continuously increasing. Thus, the determination and compensation of stress-induced negative impacts on the systems gain significance to ensure accurate positioning. Major contributors are temperature gradients. Hence, understanding and predicting temperature changes is crucial for improving such systems. This work focuses on a substructure of an NPS drive system consisting of coil assemblies. This substructure serves as a primary heat source due to the occurrence of ohmic losses, leading to an increase in temperature and therefore significantly influencing the thermal deformation. The aim of this paper is to compose a CFD model with reduced submodels of the coil assembly, which, in comparison to experimental validation data, predicts its temperature development with satisfactory accuracy. By simplification of the system through a number of sub-models, computational effort is significantly lowered. The reduced CFD model not only enables efficient thermal analysis of the coil assembly but also provides a practical approach for broader use in system design and optimization, where fast and reliable thermal predictions are essential. Full article

Considering the escalating challenges in ecological environmental protection and the difficulties faced by forest farmers in enhancing livelihood capital in ecologically vulnerable regions, a thorough examination of the impact of capabilities and risk perception on the livelihood resilience of forest farmers can serve as a reference for mitigating pressures on ecological conservation and addressing the enhancement of livelihood capital in similar typical ecologically vulnerable regions. This study utilized micro-level survey data and the Entropy Method to assess the livelihood resilience of forest farmers in an ecologically fragile region. An ordered logit model and a mediating effect model were employed to experimentally examine the influence of capabilities and risk perception on resilience. The results demonstrate that (1) the livelihood resilience of forest farmers exhibits a multi-dimensional, hierarchical condition; (2) capabilities exert a substantial positive influence on livelihood resilience, while risk perception has a considerable negative effect; and (3) capabilities affect the livelihood resilience of forest farmers by mitigating their risk perception. This paper concludes that, for the region under study, internal efforts should be undertaken to enhance forest farmers’ capabilities by increasing their income levels, strengthening their information acquisition skills, and promoting their participation in practical forestry training. The forest product market system must be enhanced externally, and technical thresholds reduced to alleviate perceptions of market volatility and natural disaster risks, ultimately improving livelihood resilience. Full article

Background/Objectives: Alcohol-related liver cirrhosis is a systemic disorder characterized by profound immune, metabolic and gut–liver axis dysregulation. Emerging evidence highlights a bidirectional interaction between the intestinal microbiota and host microRNAs (miRNAs), positioning this axis as a potential regulator of systemic homeostasis. However, human data exploring the impact of microbiota modulation on miRNA expression in advanced liver disease remain limited. Methods: Six patients with alcohol-induced liver cirrhosis underwent fecal microbiota transplantation (FMT). Safety was assessed through clinical and paraclinical monitoring at predefined intervals. Quality of life was evaluated pre- and post-intervention using a validated liver-specific questionnaire. Fecal expression of miR-21-5p, miR-122-5p, miR-125-5p, miR-146-5p and miR-155-5p was analyzed and correlations with clinical domains, demographic variables and hepatic encephalopathy severity were explored. Results: FMT was well tolerated, with no severe adverse events reported. Preliminary improvements were observed in total clinical score (3.22 [3.06–3.57] vs. 4.25 [4.20–4.26], p = 0.001) and in several quality-of-life domains, including abdominal symptoms, fatigue, systemic manifestations, activity and emotional function (p < 0.05), while worry/concern scores remained unchanged. miR-125 and miR-146 demonstrated consistent associations with clinical status both before and after FMT, whereas miR-21 correlated mainly with age and body mass index. Notably, miR-125 and miR-146 were also associated with post-FMT hepatic encephalopathy severity, supporting their potential value as molecular correlates of clinical response in this exploratory study. Conclusions: In this pilot study, FMT appeared safe and was temporally associated with improvements in clinical parameters in alcohol-related cirrhosis, alongside dynamic changes in fecal miRNA expression. These preliminary findings support a potential microbiota–miRNA interaction and warrant validation in larger, controlled longitudinal studies. Full article