Search Results (1,630)

This study presents a four-year (2021–2024) radar-based analysis of warm cloud (non-glaciated) dynamics across northern Thailand, specifically characterizing their properties, kinematics, and occurrence. Utilizing high-resolution S-band dual-polarization weather radar data, a total of 20,493 warm cloud events were tracked and analyzed, with identification based on a maximum reflectivity (≥35 dBZ) and a cloud top height below the seasonal 0 °C isotherm. Occurrence exhibited a profound seasonal disparity, with the rainy season (82.68% of events) dominating due to the influence of the moist Southwest Monsoon (SWM), while the spatial distribution confirmed that convective initiation is exclusively concentrated over mountainous terrain, underscoring orographic lifting as the essential mechanical trigger. Regarding properties, while vertical development and mass are greater in the warm seasons, microphysical intensity and Duration (mean ~26 min) remain highly uniform, suggesting a constrained, efficient warm rain process. In kinematics, clouds move fastest in winter (mean WSPD ~18.38 km/h), yet pervasive directional chaos (SD > 112°) highlights the strong influence of terrain-induced local circulations. In conclusion, while topography dictates where warm clouds form, the monsoon dictates when and how robustly they develop, creating intense, short-lived events that pose significant operational constraints for localized precipitation enhancement strategies. Full article

Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, has had major social and economic consequences worldwide. Whole genome sequencing (WGS) is essential for genomic monitoring, enabling tracking of viral evolution, detection of emerging variants, and identification of introductions and transmission chains to inform timely public health responses. Here, we compile and harmonize SARS-CoV-2 genomic data generated by multiple laboratories across Kazakhstan together with publicly available sequences to provide a national overview of genomic dynamics across successive epidemic waves from 2020 to 2022. We analyzed 4462 genomes deposited in GISAID (including 340 generated in this study), of which 3299 passed Nextclade quality filters, and summarized lineage turnover across major phases (pre-VOC, Alpha, Delta, Omicron BA.1/BA.2, Omicron BA.4/BA.5, and a later recombinant-dominant period). Sequencing intensity varied markedly over time (0.60‰ of confirmed cases during Delta vs. 11.57‰ during the Omicron BA.5 wave), suggesting that lineage diversity and persistence may be underestimated. Pre-VOC circulation included ≥12 Pango lineages with evidence of multiple introductions and sustained local transmission, including a Kazakhstan-restricted B.4.1 lineage that emerged in Nur-Sultan/Astana and disappeared after April 2020. The Tengizchevroil oilfield outbreak comprised B.1.1 viruses with phylogenetic support for ≥three independent introductions. Alpha and Omicron waves were characterized by repeated introductions and heterogeneous origins, whereas Delta was dominated by AY.122 with an additional distinct AY.122 cluster; a notable BF.7 local transmission event was observed during BA.5. We also highlight locally enriched non-lineage-defining mutations. Overall, recurrent importations and variable local amplification shaped SARS-CoV-2 dynamics in Kazakhstan, while interpretation is constrained by strongly time-skewed sequencing. Full article

Accurate clutch-frequency estimates are essential for assessing population abundance and reproductive output in sea turtles. Traditional nighttime beach-monitoring approaches, however, often underestimate clutch frequency by missing nesting events occurring outside patrolled beaches. Here, we integrated long-term beach monitoring (2009–2016) with satellite telemetry to estimate the clutch frequency of loggerhead turtles (Caretta caretta) nesting at Praia do Forte, Bahia, Brazil. A total of 593 females were identified along a 5 km monitored beach segment, and transient individuals represented 42.4% ± 3.9 SD of seasonal records. A 2-year remigration interval was the most frequent. The observed clutch frequency (OCF) averaged 3.1 ± 1.2 SD clutches per female, while the estimated clutch frequency based on beach monitoring alone (ECF_BM) averaged 3.9 ± 1.5 SD. For the subset of satellite-tracked females (n = 12), integration of residency length derived from telemetry increased the estimate to 5.6 ± 0.7 SD clutches per female (ECF_BMST). Statistical comparisons confirmed significant differences among estimation methods. These findings align with previous studies, demonstrating that clutch frequency is substantially underestimated when relying solely on beach monitoring. Incorporating satellite telemetry, therefore, provides a more accurate assessment of reproductive output and has important implications for population modelling and the conservation of loggerhead turtles in Brazil. Full article

Background: Immune checkpoint inhibitors (ICIs) improve cancer outcomes but may cause cardiovascular toxicity, including early subclinical myocardial injury. Conventional echocardiography has limited sensitivity, whereas speckle-tracking echocardiography (STE) allows for early detection of myocardial deformation. Data on short-term ICI-related effects on biventricular mechanics are limited, and atrial function remains poorly characterized. This study evaluated the early impact of ICI therapy on biventricular and biatrial mechanics using STE in patients with advanced cancer. Methods: In this prospective, single-center study, 28 consecutive patients with advanced cancer undergoing ICI therapy were followed for 3 months. Clinical, laboratory, electrocardiographic, and echocardiographic assessments were performed at baseline, 1 month, and 3 months. STE was used to assess left ventricular global longitudinal strain (LV-GLS) and circumferential strain; right ventricular GLS (RV-GLS); and left and right atrial reservoir, conduit, and contractile strain parameters. Subclinical LV dysfunction was defined as a relative LV-GLS reduction >15%. Logistic and Cox regression analyses identified predictors of strain impairment and adverse clinical events. Results: Conventional echocardiographic parameters, including left ventricular ejection fraction, remained stable. In contrast, LV-GLS declined progressively from 20.7 ± 2.1% to 17.6 ± 2.7% at 3 months (p = 0.002), with subclinical LV dysfunction observed in 85.7% of patients. RV-GLS also deteriorated despite preserved TAPSE. Both left and right atrial strain and strain-rate parameters showed an early and marked decline, accompanied by increased left atrial stiffness despite unchanged atrial volumes. Older age and higher neutrophil-to-lymphocyte ratio (NLR) were associated with LV-GLS impairment. Over a mean follow-up of 5.4 ± 3 months, baseline LV-GLS independently predicted adverse clinical events and mortality. Optimal cut-off values were 67 years for age, 4 for NLR, and 19.5% for LV-GLS. Conclusions: Short-term ICI therapy is associated with early, diffuse subclinical myocardial dysfunction involving both ventricles and atria, detectable only by STE. Comprehensive biventricular and biatrial strain assessment may enhance early cardio-oncology surveillance and risk stratification in ICI-treated patients. Full article

This article presents an integrated framework for robust control and cybersecurity of an industrial robot, combining Quantitative Feedback Theory (QFT), digital twin (DT) technology, and a programmable logic controller–based architecture aligned with the requirements of the NIS2 Directive. The study considers a five-axis industrial manipulator modeled as a set of decoupled linear single-input single-output systems subject to parametric uncertainty and external disturbances. For position control of each axis, closed-loop robust systems with QFT-based controllers and prefilters are designed, and the dynamic behavior of the system is evaluated using predefined key performance indicators (KPIs), including tracking errors in joint space and tool space, maximum error, root-mean-square error, and three-dimensional positional deviation. The proposed architecture executes robust control algorithms in the MATLAB/Simulink environment, while a programmable logic controller provides deterministic communication, time synchronization, and secure data exchange. The synchronized digital twin, implemented in the FANUC ROBOGUIDE environment, reproduces the robot’s kinematics and dynamics in real time, enabling realistic hardware-in-the-loop validation with a real programmable logic controller. This work represents one of the first architectures that simultaneously integrates robust control, real programmable logic controller-based execution, a synchronized digital twin, and NIS2-oriented mechanisms for observability and traceability. The conducted simulation and digital twin-based experimental studies under nominal and worst-case dynamic models, as well as scenarios with externally applied single-axis disturbances, demonstrate that the system maintains robustness and tracking accuracy within the prescribed performance criteria. In addition, the study analyzes how the proposed architecture supports the implementation of key NIS2 principles, including command traceability, disturbance resilience, access control, and capabilities for incident analysis and event traceability in robotic manufacturing systems. Full article

This study investigates flooding and erosion impacts and human responses in Aoraki Mount Cook and Westland Tai Poutini national parks in Aotearoa New Zealand. These fast-eroding landscapes provide important test cases and insights for considering the public access dimensions of climate change. Our objectives were to explore and characterise the often-overlooked role of public access as a ubiquitous concern for protected areas and other area-based conservation approaches that facilitate connections between people and nature alongside their protective functions. We employed a mixed-methods approach including volunteered geographic information (VGI) from a park user survey (n = 273) and detailed case studies of change on two iconic mountaineering routes based on geospatial analyses of digital elevation models spanning 1986–2022. VGI data identified 36 adversely affected locations while 21% of respondents also identified beneficial aspects of recent landscape changes. Geophysical changes could be perceived differently by different stakeholders, illustrating the potential for competing demands on management responses. Impacts of rainfall-triggered erosion events were explored in case studies of damaged access infrastructure (e.g., roads, tracks, bridges). Adaptive responses resulted from formal or informal (park user-led) actions including re-routing, rebuilding, or abandonment of pre-existing infrastructure. Three widely transferable dimensions of public access management are identified: providing access that supports the core functions of protected areas; evaluating the impacts of both physical changes and human responses to them; and managing tensions between stakeholder preferences. Improved attention to the role of access is essential for effective climate change adaptation in parks and reserves. Full article

Prolonged +Gz acceleration during high-performance flight exposes pilots to the risk of G-induced loss of consciousness (G-LOC), a dangerous condition that compromises operational safety. To enable early detection without intrusive sensors, we present a vision-based warning system that analyzes facial action units (AUs) as physiological indicators of impending G-LOC. Our approach combines computer vision with physiological modeling to capture subtle facial microexpressions associated with cerebral hypoxia using widely available RGB cameras. We propose a novel Graph Convolution-Augmented Vision Transformer (GC-ViT) network architecture that effectively captures dynamic AU variations in pilots under G-LOC conditions by integrating global context modeling with vision Transformer. The proposed framework integrates a vision–semantics collaborative Transformer for robust AU feature extraction, where EfficientNet-based spatiotemporal modeling is enhanced by Transformer attention mechanisms to maintain recognition accuracy under high-G stress. Building upon this, we develop a graph-based physiological model that dynamically tracks interactions between critical AUs during G-LOC progression by learning the characteristic patterns of AU co-activation during centrifugal training. Experimental validation on centrifuge training datasets demonstrates strong performance, achieving an AUC-ROC of 0.898 and an AP score of 0.96, confirming the system’s ability to reliably identify characteristic patterns of AU co-activation during G-LOC events. Overall, this contact-free system offers an interpretable solution for rapid G-LOC detection, or as a complementary enhancement to existing aeromedical monitoring technologies. The non-invasive design demonstrates significant potential for improving safety in aerospace physiology applications without requiring modifications to current cockpit or centrifuge setups. Full article

Natural disasters occur worldwide and cause significant financial and human losses. Wildfires are among the most important natural disasters, occurring more frequently in recent years due to global warming. Fast and accurate post-disaster damage detection could play an essential role in swift rescue planning and operations. Remote sensing (RS) data is an important source for tracking damage detection. Deep learning (DL) methods, as efficient tools, can extract valuable information from RS data to generate an accurate damage map for future operations. The present study proposes an encoder–decoder architecture composed of pre-trained Yolov11 blocks as the encoder path and Modified UNet (MUNet) blocks as the decoder path. The proposed network includes three main steps: (1) pre-processing, (2) network training, (3) prediction multilabel damage map and accuracy evaluation. To evaluate the network’s performance, the US and Canada datasets were considered. The datasets are satellite images of the 2023 wildfires in the US and Canada. The proposed method reaches the Overall Accuracy (OA) of 97.36, 97.47, and Kappa Coefficient (KC) of 0.96, 0.87 for the US and Canada 2023 wildfire datasets, respectively. Regarding the high OA and KC, an accurate final burnt map can be generated to assist in rescue and recovery efforts after the wildfire. The proposed YOLOv11–MUNet framework introduces an efficient and accurate post-event-only approach for wildfire damage detection. By overcoming the dependency on pre-event imagery and reducing model complexity, this method enhances the applicability of DL in rapid post-disaster assessment and management. Full article

The historic Rockborn strain of the canine distemper virus was widely used as a vaccine, but its use was discontinued due to safety concerns. Yet, Rockborn-like canine distemper virus strains are still used in some vaccine formulations. Genetic analysis of this strain was previously limited to the H gene, leaving its full evolutionary and pathogenic potential unclear. This study aimed to determine the complete genome sequence of the Rockborn strain to reconstruct its origin, understand its evolution, and provide a reference for improving diagnostics and future research on virulence markers. An amplicon-based sequencing protocol using MinION nanopore technology was employed to determine the complete genome of the Rockborn-46th laboratory strain. The genome was assembled, annotated, and analyzed in comparison with 223 genomes. The complete genome of the Rockborn strain was 15,690 nucleotides in length. Phylogenetic analysis revealed that Rockborn forms a unique lineage with field isolates from a masked civet in China and a dog in the United States. Crucially, a significant recombination event was identified, showing that the Rockborn strain acted as a parental strain, contributing its F and H genes to create mosaic viruses. The full-genome characterization of the Rockborn strain confirms that Rockborn-like viruses persist and actively contribute to the evolution of canine distemper virus through recombination. This finding highlights the inadequacy of single-gene analysis for diagnostics and surveillance, and underscores the necessity of whole-genome sequencing to accurately track the virus epidemiology and evolution. Full article

Fluorite, a key accessory mineral associated with rare earth element (REE) deposits, exerts a significant influence on REE migration and precipitation through complexation, adsorption, and lattice substitution within fluorine-bearing fluid systems. It therefore provides a valuable archive for constraining REE enrichment processes. The Weishan alkaline–carbonatite-related REE deposit, the third-largest LREE deposit in China, is formed through a multistage magmatic–hydrothermal evolution of the carbonatite system. However, limited mineralogical constraints on REE enrichment and precipitation have hindered a comprehensive understanding of its metallogenic processes and exploration potential. Here, cathodoluminescence imaging and LA-ICP-MS trace element analyses were conducted on fluorite of multiple generations from the Weishan deposit to constrain the physicochemical conditions of mobility and precipitation mechanisms of this REE deposit. Four generations of fluorite are recognized, recording progressive evolution of the ore-forming fluids. Type I fluorite, which coexists with bastnäsite and calcite, is LREE-enriched and exhibits negative Eu anomalies, indicating precipitation from high-temperature, weakly acidic, and reducing fluids. Type II fluorite occurs as overgrowths on Type I, while Type III fluorite replaces Type II fluorite, with both displaying LREE depletion and MREE-Y enrichment, consistent with cooling during continued hydrothermal evolution. Type IV fluorite, which is interstitial between calcite grains and associated with mica, is formed under low-temperature, oxidizing conditions, reflecting REE exhaustion and the terminal stage of fluorite precipitation. Systematic shifts in REE patterns among the four generations track progressive cooling of the system. The decreasing trend in La/Ho and Tb/La further suggests that these fluorites record dissolution–reprecipitation events and associated element remobilization during fluid evolution. Full article

Interest in the adoption of autonomous vehicles (AVs) continues to grow. It is essential to design new software architectures that meet stringent real-time, safety, and scalability requirements while integrating heterogeneous hardware and software solutions from different vendors and developers. This paper presents a lightweight, modular, and scalable architecture grounded in Service-Oriented Architecture (SOA) principles and implemented in ROS 2 (Robot Operating System 2). The proposed design leverages ROS 2’s Data Distribution System-based Quality-of-Service model to provide reliable communication, structured lifecycle management, and fault containment across distributed compute nodes. The architecture is organized into Perception, Planning, and Control layers with decoupled sensor access paths to satisfy heterogeneous frequency and hardware constraints. The decision-making core follows an event-driven policy that prioritizes fresh updates without enforcing global synchronization, applying zero-order hold where inputs are not refreshed. The architecture was validated on a 1:10-scale autonomous vehicle operating on a city-like track. The test environment covered canonical urban scenarios (lane-keeping, obstacle avoidance, traffic-sign recognition, intersections, overtaking, parking, and pedestrian interaction), with absolute positioning provided by an indoor GPS (Global Positioning System) localization setup. This work shows that the end-to-end Perception–Planning pipeline consistently met worst-case deadlines, yielding deterministic behaviour even under stress. The proposed architecture can be deemed compliant with real-time application standards for our use case on the 1:10 test vehicle, providing a robust foundation for deployment and further refinement. Full article

The adaptive event-triggered fault-tolerant control problem for bidirectional consensus of multi-agent systems (MASs) subject to sensor faults and external disturbances is investigated. A hierarchical algorithm is first introduced to eliminate the dependence on Laplacian matrix information, thereby reducing computational complexity. Subsequently, a disturbance observer (DO) and a compensation signal were constructed to accommodate external disturbances, filtering errors, and approximation errors introduced by the radial basis function neural network (RBFNN). Compared with the absence of a disturbance observer, the tracking performance was improved by $15.2\%$. In addition, a switching event-triggered mechanism is considered, in which the advantages of fixed-time triggering and relative triggering are integrated to balance communication frequency and tracking performance. Finally, the boundedness of all signals under the proposed fault-tolerant control (FTC) scheme is established. It has been clearly demonstrated by the simulation results that the proposed mechanism achieves a $39.8\%$ reduction in triggering frequency relative to the FT scheme, while simultaneously yielding a $5.0\%$ enhancement in tracking performance compared with the RT scheme, thereby highlighting its superior efficiency and effectiveness. Full article

The hard bottom layer in paddy fields significantly impacts the driving stability, operational quality, and efficiency of agricultural machinery. Continuously improving the precision and efficiency of unmanned, precision operations for paddy field machinery is essential for realizing unmanned smart rice farms. Addressing the unclear influence patterns of hard bottom contours on typical scenarios of agricultural machinery motion and posture changes, this paper employs a rice transplanter chassis equipped with GNSS and AHRS. It proposes methods for acquiring motion state information and hard bottom contour data during agricultural operations, establishing motion state expression models for key points on the machinery antenna, bottom of the wheel, and rear axle center. A correlation analysis method between motion state and hard bottom contour parameters was established, revealing the influence mechanisms of typical hard bottom contours on machinery trajectory deviation, attitude response, and wheel trapping. Results indicate that hard bottom contour height and local roughness exert extremely significant effects on agricultural machinery heading deviation and lateral movement. Heading variation positively correlates with ridge height and negatively with wheel diameter. The constructed mathematical model for heading variation based on hard bottom contour height difference and wheel diameter achieves a coefficient of determination R² of 0.92. The roll attitude variation in agricultural machinery is primarily influenced by the terrain characteristics encountered by rear wheels. A theoretical model was developed for the offset displacement of the antenna position relative to the horizontal plane during roll motion. The accuracy of lateral deviation detection using the posture-corrected rear axle center and bottom of the wheel center improved by 40.7% and 39.0%, respectively, compared to direct measurement using the positioning antenna. During typical vehicle-trapping events, a segmented discrimination function for trapping states is developed when the terrain profile steeply declines within 5 s and roughness increases from 0.008 to 0.012. This method for analyzing how hard bottom terrain contours affect the position and attitude changes in agricultural machinery provides theoretical foundations and technical support for designing wheeled agricultural robots, path-tracking control for unmanned precision operations, and vehicle-trapping early warning systems. It holds significant importance for enhancing the intelligence and operational efficiency of paddy field machinery. Full article

Hypoglycaemia in patients with type 1 diabetes mellitus (T1DM) remains a major clinical burden and, beyond its metabolic complications, can cause serious cardiac arrhythmias. Multiple mechanisms lead to different types of arrhythmias during hypoglycaemia. However, existing studies often involve mixed diabetes populations, small cohorts, or limited monitoring during nocturnal periods, leaving a critical gap in understanding the links between glucose fluctuations and arrhythmic events. This review provides an updated combination of experimental and clinical evidence describing how autonomic dysfunction and ionic imbalances lead to electrophysiological instability and structural remodelling of the myocardium during hypoglycaemia. Continuous glucose monitoring (CGM) combined with electrocardiographic or wearable rhythm tracking may enable early detection of glycemic and cardiac disturbances and help identify high-risk individuals. Future prospective studies using combined CGM–ECG monitoring, particularly during sleep, are essential to clarify the relationship between hypoglycaemia and arrhythmic events. Full article

This study presents an integrated, low-cost system for measuring extremely small displacements in Ionic Polymer–Metal Composite (IPMC) actuators operating in aqueous environments. A custom optical setup was developed, combining a glass tank, a tubular microscope with a 10× achromatic objective, a digital USB camera and uniform LED backlighting, enabling side-view imaging of the actuator with high contrast. The microscopy system achieves a spatial sampling of 0.536 μm/pixel on the horizontal axis and 0.518 μm/pixel on the vertical axis, while lens distortion is limited to a maximum edge deviation of +0.015 μm/pixel (≈+2.8%), ensuring consistent geometric magnification across the field of view. On the image-processing side, a predictive grid-based tracking algorithm is introduced to localize the free tip of the IPMC. The method combines edge detection, Harris corners and a constant-length geometric constraint with an adaptive search over selected grid cells. On 1920 × 1080-pixel frames, the proposed algorithm achieves a mean processing time of about 10 ms per frame and a frame-level detection accuracy of approximately 99% (98.3–99.4% depending on the allowed search radius) for actuation frequencies below 2 Hz, enabling real-time monitoring at 30 fps. In parallel, dedicated electronic circuitry for supply and load monitoring provides overvoltage, undervoltage, open-circuit and short-circuit detection in 100 injected fault events, all faults were detected and no spurious triggers over 3 h of nominal operation. The proposed microscopy and tracking framework offer a compact, reproducible and high-resolution alternative to laser-based or Digital Image Correlation techniques for IPMC displacement characterization and can be extended to other micro-displacement sensing applications in submerged or challenging environments. Full article