Search Results (593)

The Loess Plateau in China is highly susceptible to frequent landslides and other geological disasters, which have led to substantial losses of natural and human resources and are frequently reported in the news media. Yuzhong County, located east of Lanzhou City, is a mountainous region with considerable development potential. On 7 August 2025, this area experienced a large-scale geological disaster characterized by a compound event involving both landslides and debris flows, resulting in nearly several hundred casualties. With the ongoing urban expansion of Yuzhong County in recent years, the prediction and prevention of geological disasters have become increasingly critical. This study employed three machine learning algorithms—Multiple Logistic Regression (LR), Random Forest (RF), and XGBoost (XG)—to assess landslide susceptibility in Yuzhong County. A total of 169 historical landslide points, supplemented by additional sites identified through field investigations, were compiled, along with 200 non-landslide locations. Multiple environmental factors were incorporated into the models to analyze landslide susceptibility across different areas. Because LR can effectively capture the generalized influence of precipitation variability, it was selected as the primary model for the final susceptibility mapping. To more accurately evaluate the impact of precipitation on landslide occurrence, average seasonal precipitation across the four seasons was used as a predictive factor. To refine the risk assessment at the township level, both raster-based and landslide-unit-based evaluation approaches were adopted. Overlay analyses were then performed by integrating urban infrastructure, population distribution, and predicted landslide hazard zones, while also accounting for the potential influence of extreme precipitation events. The results reveal that the mountainous areas in eastern Mapo Township, southern Xiaokangying Township, southern Xiaguanying Town, and the south-central part of Qingshuiyi Township are high-risk zones prone to group-occurrence landslide disasters. Full article

This work provides a structured synthesis of visual cryptography, a secret sharing technique that enables image reconstruction only when a specific number of shares are combined, with decryption performed visually by overlaying the shares. Although conceptually simple and distinctive in its reliance on the human visual system rather than complex computation, this method has been predominantly studied from theoretical and construction-oriented perspectives. The work consolidates fundamental concepts, mathematical foundations, operational principles, and security considerations of selected schemes, providing a common context for analyzing their characteristics. Particular attention is given to known attack vectors, including information leakage from individual shares and integrity violations caused by forged shares, together with corresponding mitigation approaches reported in the literature. In addition to this synthesis, the work presents an experimental investigation of the $\varphi$ correlation coefficient and its behavior for genuine and forged shares. Experiments conducted on a dataset of 100 images show that genuine–genuine share pairs consistently exhibit higher mean $\varphi$ correlation values than genuine–forged pairs, although the observed values depend on the underlying scheme. While these results suggest that $\varphi$ correlation may provide useful information for share authenticity analysis, the experiment used the same forged target image throughout the dataset, limiting the variation of the forged samples and potentially making the observed differences partly dependent on the selected target image. Finally, three Proof-of-Concept application scenarios demonstrate possible integrations of visual cryptography into QR code security, physical document verification, and IoT access control, illustrating its potential use in practical security systems. Full article

The long-term durability of repair systems combining normal concrete (NC) and ultra-high-performance concrete (UHPC) in marine environments depends on the response of the near-interface composite region to sequential carbonation and seawater exposure. However, the effects of seawater immersion following pre-carbonation remain insufficiently understood. This study compared an unexposed reference (REF), specimens carbonated for 28 d (C28), and specimens carbonated for 28 d and then immersed in simplified artificial seawater for 60 d (C28-SW60) using X-ray diffraction, thermogravimetry, backscattered electron imaging with energy-dispersive X-ray spectroscopy, and mercury intrusion porosimetry. Pre-carbonation promoted portlandite consumption, carbonate formation, and pore refinement. Subsequent seawater immersion further enhanced calcite-related diffraction and carbonate decomposition signals, while no typical crystalline salt-attack product was detected as dominant. The initial Ca-rich-to-Si-rich gradient from the NC side through the overlay transition zone to the UHPC side was accompanied by marked Cl accumulation and further S and Mg enrichment and redistribution. After seawater immersion, the measured total intrusion volume increased from 0.026 to 0.043 mL/g, the volume-based median pore-entry diameter increased from 27.49 to 58.42 nm, and the >1000 nm pore-volume fraction reached 39.82%, a change consistent with a shift toward coarser mercury-accessible pore entries. Together, the results link the initial heterogeneity of the NC–Overlay transition zone (OTZ)–UHPC region to a sequence-dependent response in which carbonate enrichment coexisted with multi-ion redistribution and transport-relevant defects, distinguishing carbonate accumulation from sustained near-interface refinement. Full article

Reliable sustainability analysis requires more than the presence of ESG disclosure; it requires information that is specific, traceable and analytically usable. This exploratory study assesses a purposive corpus of 36 organisations in Bulgaria and Moldova (18 per country) using a Data Gap Matrix covering 15 ESG indicators. The revised framework explicitly separates three observed disclosure-quality dimensions—availability, granularity and auditability—from two framework-assigned analytical overlays—LCSA relevance and environmental-risk relevance. Environmental security is retained only as a framework-based interpretive lens for the environmental-risk overlay and is not treated as an observed outcome. The matrix generated 540 organisation–indicator coding units. Medians, interquartile ranges and score frequencies are the primary descriptive summaries; country and sector tests are retained only as secondary, sample-specific checks and are restricted to the three observed dimensions. Auditability is the principal weakness (median = 1.00), with only 7 of 540 coding units receiving the maximum score, while Scope 3 greenhouse gas emissions constitute the weakest observed indicator. No Holm-adjusted country or sector difference is established for the observed disclosure-quality dimensions, consistent with limited statistical power. The findings diagnose limited disaggregation, source traceability and assurance readiness, but do not measure organisational ESG performance, conduct an LCSA, or establish environmental-security outcomes. Interpretation is constrained by purposive sampling, heterogeneous report types, common-indicator applicability and the absence of independent double coding. Full article

Background/Objectives: Performance measurement and management is a key administrative function; however, its application to child and adolescent healthcare services remains poorly mapped in the international literature. This study attempts a systematic bibliometric mapping of the field. To the best of our knowledge, previous bibliometric studies in pediatric and related healthcare fields have primarily focused on specific clinical or service domains, whereas the intersection of performance measurement and management with child and adolescent healthcare services has not been specifically mapped. The novelty of the present study lies in addressing this intersection through an integrated bibliometric assessment of its thematic, temporal, and geographical structure. Methods: A bibliometric analysis was performed on the Scopus database, with a query that combined a proximity operator (W/10) and Boolean logic, yielding 643 documents (1990–2026). After metadata cleaning and application of an occurrence threshold (≥15), 111 keywords were analyzed with VOSviewer (network, overlay, density, targeted analysis, bibliographic coupling of countries). Results: Research production increased strongly since 2010, peaking in 2025. Four thematic clusters emerged—quality of care, clinical outcomes, administrative framework, emergency/operational care—with the term “quality of health care” as the central hub-bridge. The administrative cluster was linked to older publications relative to the clinical/operational clusters. Country-level bibliographic coupling identified distinct geographical patterns in cited-reference similarity, including a predominantly European cluster, a transcontinental cluster dominated by the United States and Canada, and a separate Australian cluster. The term “performance measurement” itself did not meet the inclusion threshold, reflecting the methodological effect of the selected occurrence threshold rather than the absence of the concept from the literature. Conclusions: The retrieved literature was strongly concentrated in clinical and health-related subject areas, while explicitly administrative and managerial perspectives appeared comparatively limited. This pattern indicates a potential research gap that warrants further investigation rather than confirming the absence of managerial performance frameworks in the broader field. Full article

Conventional methods of plant distance and volume measurements are limited by low efficiency, limited spatial coverage, and high measurement error. LiDAR and RGB-D imaging offer cost-effective, precise, and non-destructive techniques for plant distance and volume measurements. This study aimed to measure cabbage height, volume, and distance using LiDAR and RGB-D imaging. The sensors were mounted on a 1.6 kW electric field scouting platform (EFSP) for data collection. Point cloud (PCD) data were collected using LiDAR, whereas data processing, visualization, and measurements were done using commercial software and open-source programming scripts. A total of 20 cabbage plants were analyzed. LiDAR data processing included data frame screening, outlier removal, denoising, voxelization, and generation of 3D PCD density maps. Depth image processing included importing raw data and metadata shaping using intrinsic camera parameters, visualization, extraction of depth points, and pixel-level measurements of distances and volume. RGB image processing involved image conversion, segmentation, normalization, binary masking, mask cleaning, region extraction of cabbages, separation of ROI and preparation of contours, Delaunay triangulation and convex hull preparation, ROI overlay, bounding box preparation, sharing boundary between two boxes, conversion to pixel distances, and for visualization, plant height, volume measurements, and center to center distance measurement for measuring the plant distance. LiDAR demonstrated higher measurement accuracy for cabbage plant height, circumferential volume (geometric canopy volume), and plant distance, followed by RGB-D imaging, while RGB imagery showed comparatively lower performance under the study field conditions. Overall, LiDAR and RGB-D imaging provided reliable and non-destructive approaches for cabbage geometric characterization under field conditions, although accurately capturing complex plant geometry remains challenging. Positive and negative values of bias represent the over- and under-estimated results, respectively. Future studies should include larger and more diverse plant datasets exhibiting diversified size, shape, and geometric structure to further improve the robustness and general applicability of the proposed sensing approaches. Full article

Remote teleoperation interfaces for precision manipulation should support operator awareness and usability while preserving human control, consistent with the human-centred goals of Industry 5.0. This study conducted a within-subject user evaluation with 18 participants using a UR5 arm. Three interface conditions were compared: an enhanced first-person interface with visual overlays (FPV+), a multi-view interface combining first-person and third-person views (PiP), and a multi-view interface with enhanced visual overlays (PiP+). Participants completed a ball task and a pen insertion task in pseudo-randomised order. Binary task success was analysed using generalised linear mixed-effects models, while System Usability Scale scores were analysed using a linear mixed-effects model. Neither adding a third-person view to the enhanced first-person interface nor adding the minimap and tactile-dot overlays to the multi-view interface was significantly associated with task success. A post hoc sensitivity analysis showed that these binary-success comparisons were sensitive only to large effects, so they are interpreted as inconclusive rather than as evidence of absence. Success was significantly lower for the pen task, and its relationship with prior human–robot interaction experience differed from that observed for the ball task. Adding a third-person view was associated with an approximately 16-point higher System Usability Scale score, whereas the minimap and tactile-dot overlays were not significantly associated with usability. These findings illustrate a human-centred evaluation principle relevant to Industry 5.0: an interface feature can improve the operator’s experience of a teleoperation system even when no corresponding change in objective task success is detectable, revealing a benefit that a performance-only evaluation might overlook. Full article

Single-story unreinforced masonry rural houses along the Tanlu Earthquake Belt in Anhui Province are generally constructed without ring beams and tie columns, resulting in poor structural integrity and low seismic performance. This paper proposes a convenient single-sided High-Ductility Concrete Strip (HDCS) retrofitting method. Two 1:2 scaled test specimens, namely the unretrofitted model M1 and HDCS single-side retrofitted model M2, were fabricated for shaking table tests. Systematic analyses were carried out based on white noise sweep tests, failure modes, acceleration responses and inter-story displacement responses. The test results show that HDCS possesses excellent tensile capacity, which forms continuous confinement at wall joints and openings to boost structural stiffness and greatly restrain post-seismic stiffness degradation, as well as achieve more uniform structural deformation distribution. Under strong seismic excitations, the unretrofitted model suffers severe damage, including penetrating diagonal shear cracks and separation between gable walls and lower walls. In contrast, damage of the retrofitted model is concentrated within the HDCS overlay, realizing damage redistribution and preventing brittle failure of the main masonry. HDCS stabilizes the distribution of acceleration amplification factors and restrains wall rocking and stress concentration around openings. Although single-sided strengthening induces slight out-of-plane effects, its adverse influence is acceptable. Full article

Although steel pipelines constitute the primary infrastructure of agricultural irrigation systems, they are highly susceptible to moisture-induced pitting corrosion and severe operational conditions, including internal pressure fluctuations and heavy overburden loads. This study evaluated the structural performance and durability of full-diameter steel pipe specimens (311.5 mm in diameter and 2.0 m long) repaired using CFRP (single-layer) and GFRP (single- and multi-layer) sheet wrapping as well as overlay welding. A 60-mm pinhole defect corresponding to a 6% circumferential damage ratio was introduced to simulate advanced localized corrosion. The repaired pipelines were experimentally assessed under four-point bending, internal hydrostatic pressure, and accelerated salt spray exposure. Under service-level flexural loading, all specimens exhibited similar global load–deflection responses regardless of defect or repair condition. However, localized strain measurements revealed that the unrepaired defect produced tensile strains up to 12 times greater than those of the intact pipe, whereas all repair techniques effectively suppressed the localized strain concentration. The effectiveness of the FRP systems improved with increasing reinforcement thickness. Overlay welding provided the highest structural performance, restoring localized strain behavior to a level comparable to that of the intact pipe. Under an internal pressure of 2.0 MPa, welding and CFRP maintained 100% pressure retention, whereas single-layer GFRP exhibited minor radial bulging, reducing its pressure retention ratio to 73.5%. Increasing the GFRP thickness restored the retention ratio to 93.0%. Accelerated salt spray exposure further demonstrated that GFRP provided effective barrier protection against corrosion by acting as an impermeable dielectric barrier under short-term exposure, whereas welded specimens still exhibited localized corrosion around the heat-affected zone despite epoxy coating. These findings demonstrate that overlay welding offers the greatest immediate structural restoration, whereas adequately dimensioned FRP systems can provide a more balanced solution for multi-hazard durability by simultaneously enhancing structural performance and mitigating electrochemical degradation in aging agricultural steel pipelines. Full article

Drought is a major constraint limiting maize productivity worldwide, highlighting the need for reliable methods to identify drought-tolerant genotypes. This study evaluated the effectiveness of drought tolerance indices and multivariate analyses for discriminating maize genotypes differing in drought adaptation. In total, 20 maize genotypes were assessed under optimal and water-limited conditions using grain yield under non-stress (Yp) and drought stress (Ys) together with 15 drought tolerance indices. Correlation analysis, principal component analysis (PCA), clustering, and overlay analysis were applied to identify informative indices and characterize genotype responses. Productivity-oriented indices (STI, GMP, HM, MSTI, REI, and YI) were strongly associated with grain yield and consistently identified superior genotypes, whereas SSI, TOL, and SSPI mainly reflected drought susceptibility. PCA separated productivity and stress susceptibility into two complementary components and showed that five variables (Yp, Ys, YI, ATI, and MSTI_K1) retained 99.49% of the variation explained by the complete dataset. Cluster and overlay analyses confirmed stable genotype classification and distinct adaptation strategies. These findings demonstrate that a reduced set of complementary variables provides an efficient framework for drought tolerance assessment and supports the identification of maize germplasm, combining high productivity with stable performance under variable water availability. Full article

Agricultural steel pipelines are essential components of pressurized irrigation systems, yet localized corrosion-induced pinholes severely compromise their structural integrity by creating critical stress concentrations. To address the lack of performance-based maintenance guidelines, this study experimentally evaluates three repair techniques—a multi-joint hinge clamp, a GFRP composite sleeve, and overlay welding—applied to steel pipes containing simulated pinhole defects representing 6% and 10% circumferential damage. Four-point bending and uniaxial tensile tests were conducted to simulate transverse overburden and longitudinal axial loading encountered in buried pipelines. Results reveal that repair effectiveness strongly depends on both loading mode and damage severity. At 6% damage, all methods effectively restored bending capacity, with the GFRP sleeve achieving near-complete recovery. Under tensile loading, however, external-confinement methods provided limited ductility improvement because they lack a direct axial load-transfer path. In contrast, overlay welding consistently achieved substantial structural restoration by eliminating stress concentrations and shifting fracture to the parent pipe material. Furthermore, a significant transition in repair performance was observed near the 6% damage level, beyond which confinement-based repairs exhibited reduced efficacy. These findings demonstrate that repair performance cannot be reliably assessed from bending behavior alone and highlight the importance of considering both loading conditions and damage severity in rehabilitation design. The study provides a quantitative framework for load-specific pipeline rehabilitation strategies. Full article

Background: Modern household appliances often present complex interfaces that can be difficult to use, especially for older adults, people with visual impairments, and users with mild cognitive difficulties. In such cases, interacting with appliances may require sustained attention, visuospatial search, working memory, and sequential action planning, while traditional user manuals often provide limited contextual support. Methods: To address this issue, this study presents a proof-of-concept augmented reality (AR) and artificial intelligence (AI)-based system for contextual appliance guidance. The proposed architecture integrates visual sensing, deep learning, and large language models to detect appliance controls, interpret user queries, retrieve relevant information from user manuals, and provide step-by-step guidance directly on the real interface. A YOLOv8 model trained on a custom dataset was used for button detection, YOLO-Seg was employed to enhance visual highlighting through segmentation, and BoT-SORT was used to maintain detection consistency across frames. A Unity-based mobile application displayed real-time AR overlays with customizable visual settings for accessibility needs, such as low vision and color blindness that may be relevant for future accessibility-oriented applications. In addition to its technical pipeline, the system is conceptually relevant as a potential form of external cognitive support because it transforms static manual instructions into situated, sequential, and visually grounded guidance.Results: Experimental results showed promising technical performance for button detection and segmentation, while a preliminary user evaluation in a non-clinical sample suggested good usability, clarity, and acceptability of the interface. Conclusions: These findings support the technical feasibility and preliminary usability of the approach, while cognitive workload, confidence, functional autonomy, and clinical benefit were not directly measured. Targeted validation in older adults, people with visual impairments, and clinical populations is therefore still needed. Future developments will include multimodal feedback, read-aloud guidance, and more specific evaluation of workload, confidence, and functional autonomy. Full article

Following the 2021 Montiferru wildfire, one of the largest wildfire events in modern Italian history, assessing the suitability of olive-growing environments for high-quality extra virgin olive oil (EVOO) production is crucial for supporting sustainable agricultural restoration. This study models the spatial distribution and temporal stability of total polyphenol concentration in EVOO (cv. Bosana) across a complex Mediterranean landscape. Olive samples from georeferenced sites were collected during the 2022 (22 samples) and 2023 (37 samples) harvest seasons and processed using a standardized protocol. Spatial modeling was performed via Empirical Bayesian Kriging Regression Prediction (EBKRP), integrating seven bioclimatic and topographic covariates. Cross-validation demonstrated high predictive accuracy with negligible bias (RMSE = 53.3 and 58.8 mg kg⁻¹ for 2022 and 2023, respectively). While single-predictor correlations were weak, multi-variable analysis highlighted a strong interaction between topography and water balance driving phenolic accumulation. The mean prediction map identified regional hotspots approaching600 mg kg⁻¹ of polyphenols content in the obtained olive oils. Spatial overlay analysis successfully delineated “Stable High-Phenolic Core Areas” (>500 mg kg⁻¹ with interannual variation < 100 mg kg⁻¹), filtering out high-altitude marginal zones. This geostatistical approach provides a valuable territorial decision-making tool to support post-fire agricultural reconversion and the valorization of high-quality monovarietal EVOO terroirs. Full article

Cross-border e-commerce in the European Union remains operationally heterogeneous despite Digital Single Market integration, which complicates first-stage market comparison. This study develops a portfolio-first public-data framework for EU-27 cross-border e-commerce market-entry screening using 2023 as the common reference year. The framework derives PC1_EF, a PCA-derived execution-condition screening axis, from enterprise e-sales penetration, a digital financial participation proxy and the World Bank Logistics Performance Index. Market potential is calculated by multiplying the population aged 16–74 by online-shopping incidence, while cross-border buying openness remains a separate demand-side overlay. The first component explains 67.84% of backbone variance, with all loadings being positive. The portfolio distinguishes country positions across execution conditions, market scale and cross-border openness. Auxiliary rule-based screening bands serve as a compact summary. PC1_EF is positively associated with enterprise-side e-commerce turnover intensity (Spearman ρ = 0.486, p = 0.014, N = 25), providing partial criterion-consistency evidence. GDP_PPS rank differences provide interpretive context. Equal-weight and leave-one-variable-out checks assess the sensitivity of the continuous ordering, while LPI gate-family and no-LPI/no-gate checks assess the sensitivity of the band summaries. The framework provides a transparent and reproducible basis for comparing EU-27 cross-border e-commerce markets. Full article

Although unsupervised anomaly detection has shown promising performance in industrial visual inspection, many architectures still struggle with variable input resolutions, and anomaly scores are often difficult for end users to interpret. This study proposes a multi-stage hybrid workflow for pixel-level defect localization and structured reporting in bolt head images. The proposed SA-PatchCore framework customizes PatchCore by extracting multi-scale representations from a frozen deep feature extractor and supporting resolution-adaptive anomaly-map reconstruction through dynamic feature-map sizing. After anomaly detection, a Qwen3-VL-32B-based reporting module, adapted with GRPO, uses both the original image and the anomaly overlay as visual evidence. It generates structured JSON outputs containing defect presence, a 3 × 3 location label, and a concise textual description. On the industrial bolt dataset, SA-PatchCore achieved 98.69% pixel-level AUROC, 29.73% Pixel-AP, and 39.24% oracle Pixel-F1max. Compared with PatchCore, PaDiM, DRÆM, and CS-Flow, the method delivered strong results, especially in Pixel-AUROC. In the reporting stage, defect presence/absence accuracy improved from 76.63% to 96.41%, while defective-sample recall increased from 74.23% to 96.14% over the baseline Qwen3-VL-32B. Exact location match rose from 28.15% to 53.78%, and mean partial location score improved from 32.29% to 65.34%. Overall, the framework combines accurate anomaly localization with structured reporting, improving interpretability and usability. Full article