Search Results (56,506)

This research focuses on enhancing cooperative localization for heterogeneous mobile robots composed of a quadcopter and an unmanned ground vehicle. The study employs sensor fusion techniques, particularly the Extended Kalman Filter, to fuse data from various sensors, including GPSs, IMUs, and cameras. By integrating these sensors and optimizing fusion strategies, the research aims to improve the precision and reliability of cooperative localization in complex and dynamic environments. The primary objective is to develop a practical framework for cooperative localization that addresses the challenges posed by the differences in mobility and sensing capabilities among heterogeneous robots. Sensor fusion is used to compensate for the limitations of individual sensors, providing more accurate and robust localization results. Moreover, a comparative analysis of different sensor combinations and fusion strategies helps to identify the optimal configuration for each robot. This research focuses on the improvement of cooperative localization, path planning, and collaborative tasks for heterogeneous robots. The findings have broad applications in fields such as autonomous transportation, agricultural operation, and disaster response, where the cooperation of diverse robotic platforms is crucial for mission success. Full article

Oncidium has an important market value, with important high-grade cut orchids and potted flowers on the flower market. In the Oncidium cut flowers production industry, there is a common phenomenon that the development of vegetative buds disrupts the normal generation cycle of the inflorescence induction, so-called “bud jumping”. In this study, vegetative bud differentiation and flower bud differentiation were divided into three stages, namely, the initial stage of differentiation, the leaf primordial/flower primordial differentiation stage, and the late stage of leaf bud/flower bud differentiation, as observed by paraffin sectioning. Secondly, we analyzed the differences between the vegetative buds of “bud jumping” plants and the flower buds of normal flowering plants by transcriptome sequencing. The transcriptome analysis results revealed significant differences among plant signaling pathways, particularly in gibberellins, auxins, and cytokinins, which play important roles in this phenomenon’s formation. In conjunction with the transcriptome analysis, the researchers conducted field experiments by applying plant growth regulators on the newborn pseudobulb of young Oncidium plants measuring approximately 49 mm in length. The results showed that the treatment groups of 100 mg/L of gibberellic acid (GA₃) and 100 mg/L GA₃ + 10 mg/L 6-Benziladenine (6-BA) exhibited the highest rate of flower bud differentiation instead of the least “bud jumping” phenomenon, and the “bud jumping” phenomenon was significantly reduced under 25 mg/L, 50 mg/L, and 75 mg/L 3-indoleacetic acid (IAA) treatments. The application of exogenous gibberellins, cytokinins, and auxins can effectively reduce the occurrence of “bud jumping”. Full article

In recent decades, flexible electronics have witnessed remarkable advancements in multiple fields, encompassing wearable electronics, human–machine interfaces (HMI), clinical diagnosis, and treatment, etc. Nevertheless, conventional rigid electronic devices are fundamentally constrained by their inherent non-stretchability and poor conformability, limitations that substantially impede their practical applications. In contrast, conductive hydrogels (CHs) for electronic skin (E-skin) and healthcare monitoring have attracted substantial interest owing to outstanding features, including adjustable mechanical properties, intrinsic flexibility, stretchability, transparency, and diverse functional and structural designs. Considerable efforts focus on developing CHs incorporating various conductive materials to enable multifunctional wearable sensors and flexible electrodes, such as metals, carbon, ionic liquids (ILs), MXene, etc. This review presents a comprehensive summary of the recent advancements in CHs, focusing on their classifications and practical applications. Firstly, CHs are categorized into five groups based on the nature of the conductive materials employed. These categories include polymer-based, carbon-based, metal-based, MXene-based, and ionic CHs. Secondly, the promising applications of CHs for electrophysiological signals and healthcare monitoring are discussed in detail, including electroencephalogram (EEG), electrocardiogram (ECG), electromyogram (EMG), respiratory monitoring, and motion monitoring. Finally, this review concludes with a comprehensive summary of current research progress and prospects regarding CHs in the fields of electronic skin and health monitoring applications. Full article

The investigation of the pore structure and fractal characteristics of coal-bearing shale is critical for unraveling reservoir heterogeneity, storage-seepage capacity, and gas occurrence mechanisms. In this study, 12 representative Upper Paleozoic coal-bearing shale samples from the Yangquan Block of the Qinshui Basin were systematically analyzed through field emission scanning electron microscopy (FE-SEM), high-pressure mercury intrusion, and gas adsorption experiments to characterize pore structures and calculate multi-scale fractal dimensions (D₁–D₅). Key findings reveal that reservoir pores are predominantly composed of macropores generated by brittle fracturing and interlayer pores within clay minerals, with residual organic pores exhibiting low proportions. Macropores dominate the total pore volume, while mesopores primarily contribute to the specific surface area. Fractal dimension D₁ shows a significant positive correlation with clay mineral content, highlighting the role of diagenetic modification in enhancing the complexity of interlayer pores. D₂ is strongly correlated with the quartz content, indicating that brittle fracturing serves as a key driver of macropore network complexity. Fractal dimensions D₃–D₅ further unveil the synergistic control of tectonic activity and dissolution on the spatial distribution of pore-fracture systems. Notably, during the overmature stage, the collapse of organic pores suppresses mesopore complexity, whereas inorganic diagenetic processes (e.g., quartz cementation and tectonic fracturing) significantly amplify the heterogeneity of macropores and fractures. These findings provide multi-scale fractal theoretical insights for evaluating coal-bearing shale gas reservoirs and offer actionable recommendations for optimizing the exploration and development of Upper Paleozoic coal-bearing shale gas resources in the Yangquan Block of the Qinshui Basin. Full article

A novel classification algorithm for precipitation types (CP) was developed to address frequent misclassification issues between shallow convection and intense stratiform precipitation using existing methods and to enhance an understanding of their physical characteristics. Based on three-dimensional radar data and temperature fields, CP integrates three approaches: Storm Labeling in Three Dimensions (SLTD), a feature parameter-based algorithm (FP), and an advanced subcategorization method. The algorithm classifies precipitation into ten types: four non-precipitating, three stratiform, and three convective categories. CP was evaluated against traditional methods (SHY and FP) through both qualitative and quantitative analyses for mid-latitude warm-season systems. The CP method demonstrated improved performance, with higher skill scores (e.g., POD: 0.567–0.571) compared to SHY (0.349–0.364) and FP (0.455–0.470). Additionally, comparative analyses of vertical mean profiles of radar reflectivity, dynamical, and microphysical variables confirmed the enhanced capability of CP in distinguishing detailed precipitation structures. Full article

The demand for large-scale, heavy-duty autonomous pavement-sweeping robots is rising due to urban growth, hygiene needs, and labor shortages. Ensuring their health and safe operation in dynamic outdoor environments is vital, as terrain unevenness and slope gradients can accelerate wear, increase maintenance costs, and pose safety risks. This study introduces an AI-driven condition monitoring (CM) framework designed to detect terrain unevenness and slope gradients in real time, distinguishing between safe and unsafe conditions. As system vibration levels and energy consumption vary with terrain unevenness and slope gradients, vibration and current data are collected for five CM classes identified: safe, moderately safe terrain, moderately safe slope, unsafe terrain, and unsafe slope. A simple-structured one-dimensional convolutional neural network (1D CNN) model is developed for fast and accurate prediction of the safe to unsafe classes for real-time application. An in-house developed large-scale autonomous pavement-sweeping robot, PANTHERA 2.0, is used for data collection and real-time experiments. The training dataset is generated by extracting representative vibration and heterogeneous slope data using three types of interoceptive sensors mounted in different zones of the robot. These sensors complement each other to enable accurate class prediction. The dataset includes angular velocity data from an IMU, vibration acceleration data from three vibration sensors, and current consumption data from three current sensors attached to the key motors. A CM-map framework is developed for real-time monitoring of the robot by fusing the predicted anomalous classes onto a 3D occupancy map of the workspace. The performance of the trained CM framework is evaluated through offline and real-time field trials using statistical measurement metrics, achieving an average class prediction accuracy of 92% and 90.8%, respectively. This demonstrates that the proposed CM framework enables maintenance teams to take timely and appropriate actions, including the adoption of suitable maintenance strategies. Full article

Retinal ischemia is implicated in ocular diseases involving aberrant neovessel proliferation that characterizes proliferative retinopathies. Their therapy still remains confined to the intravitreal administration of anti-vascular endothelial growth factor (VEGF) medication, which is limited by side effects and progressive reduction in efficacy. Mimicking neovascular diseases in rodents, although of great help for translating fundamental mechanistic findings and assessing therapeutic potential in humans, is limited by the rodent’s short life span, which prevents retinal vessel proliferation over time. However, the oxygen-induced retinopathy (OIR) model, which mimics retinopathy of prematurity, seems to meet some criteria that are common to proliferative retinopathies. The present review provides insight into preclinical models and their suitability to mimic proliferative retinopathies. Further considerations will be applied to emerging approaches and advanced methodologies for the management of proliferative retinopathies, leading to the identification of new therapeutic targets, including our contribution in the field. Major emphasis is given to the possibility of using systemic therapies either alone or in combination with intravitreal anti-VEGF administration to maximize clinical benefits by combining drugs with different modes of action. This review is concluded by an in-depth discussion on future advancements and a critical view of preclinical finding translatability. Despite the major effort of preclinical and clinical research to develop novel therapies, the blockade of VEGF activity still remains the only treatment for proliferative retinopathies for more than twenty years since its first therapeutic application. Full article

The accelerating global demand for sustainable materials has brought biodegradable polymers to the forefront of scientific and industrial innovation. These polymers, capable of decomposing through biological processes into environmentally benign byproducts, are increasingly seen as viable alternatives to conventional plastics in sectors such as packaging, agriculture, and biomedicine. However, despite significant advancements, the field remains fragmented due to the diversity of raw materials, synthesis methods, degradation mechanisms, and application requirements. This review aims to provide a comprehensive synthesis of the current state of biodegradable polymer development, including their classifications, sources (natural, synthetic, and microbially derived), degradation pathways, material properties, and commercial applications. It highlights critical scientific and technological challenges—such as optimizing degradation rates, ensuring mechanical performance, and scaling up production from renewable feedstocks. By consolidating recent research findings and regulatory considerations, this review serves as a crucial reference point for researchers, material scientists, and policymakers. It strives to bridge knowledge gaps in order to accelerate the deployment of biodegradable polymers as integral components of a circular and low-impact material economy. Full article

Semantic segmentation is a vast field with many contributions, which can be difficult to organize and comprehend due to the amount of research available. Advancements in technology and processing power over the past decade have led to a significant increase in the number of developed models and architectures. This paper provides a brief perspective on 2D segmentation by summarizing the mechanisms of various neural network models and the tools and datasets used for their training, testing, and evaluation. Additionally, this paper discusses methods for identifying new architectures, such as Neural Architecture Search, and explores the emerging research field of continuous learning, which aims to develop models capable of learning continuously from new data. Full article

When designing, implementing and assessing public policies, and, in particular, those affecting the public management of religious diversity, it is increasingly common to include ethnographic approaches from the field of social anthropology and the broader social sciences. Ethnographic practice can provide more representative and accurate perspectives on the actors, settings, and social phenomena subject to regulation. This article presents the findings of an ethnographic study on two minority religious communities, conducted by a team of anthropologists within the framework of a broader research project on religious freedom in Spain, led by jurists. Based on two case studies—the teaching of Evangelical religion in state schools and Islamic burial practices—our study analyses the implications of the varying degrees of public recognition, as well as how this recognition actually manifests in the everyday practice of religious groups within a context of religious diversity. The study also examines the barriers to the full participation of these communities in public institutions and civil society, as well as the discourses, strategies, and practices they develop to overcome these challenges. Full article

In the era of precision medicine, effective data visualisation plays a pivotal role in supporting clinical decision-making by translating complex, multidimensional datasets into intuitive and actionable insights. This paper explores the foundational principles of visual perception, with a specific focus on pre-attentive attributes such as colour, shape, size, orientation, and spatial position, which are processed automatically by the human visual system. Drawing from cognitive psychology and perceptual science, we demonstrate how these attributes can enhance the clarity and usability of medical visualisations, reducing cognitive load and improving interpretive speed in high-stakes clinical environments. Through detailed case studies and visual examples, particularly within the field of oncology, we highlight best practices and common pitfalls in the design of dashboards, nomograms, and interactive platforms. We further examine the integration of advanced tools—such as genomic heatmaps and temporal timelines—into multidisciplinary workflows to support personalised care. Our findings underscore that visually intelligent design is not merely an aesthetic concern but a critical factor in clinical safety, efficiency, and communication, advocating for user-centred and evidence-based approaches in the development of health data interfaces. Full article

Universities in severely cold regions face the dual challenge of adapting to seasonal climate variations while enhancing outdoor thermal comfort in outdoor leisure plazas. This study takes a university in Hohhot as a case study. Through field investigations conducted in summer and winter, thermal benchmarks were established. Based on this, an orthogonal experimental design was developed considering greenery layout, plant types, and surface albedo. ENVI-met was used to simulate and analyze the seasonal regulatory effects of landscape elements on the microclimate. The results show that: (1) the lower limit of the neutral PET range in Hohhot in winter is −11.3 °C, and the upper limit in summer is 31.3 °C; (2) the seasonal contribution of landscape elements to PET ranks as follows: plant types > greenery layout > surface albedo; and (3) the proposed optimization plan achieved a weighted increase of 6.0% in the proportion of activity area within the neutral PET range in both summer and winter. This study is the first to construct outdoor thermal sensation categories for both summer and winter in Hohhot and to establish a thermal comfort optimization evaluation mechanism that considers both diurnal and seasonal weightings. It systematically reveals the comprehensive regulatory effects of landscape elements on the thermal environment in severely cold regions and provides a nature-based solution for the climate-responsive design of campus plazas in such areas. Full article

Despite the strength and ductility of steel reinforcing bars, their susceptibility to corrosion can limit the long-term durability of reinforced concrete structures. Fiber-reinforced polymer (FRP) reinforcing bars made with a thermosetting matrix offer corrosion resistance but cannot be field-bent, which limits flexibility during construction. FRP reinforcing bars made with fiber-reinforced thermoplastic polymers (FRTP) address this limitation; however, their high processing viscosity presents manufacturing challenges. In this study, the Continuous Forming Machine, a novel pultrusion device that uses pre-consolidated fiber-reinforced thermoplastic tapes as feedstock, is described and used to fabricate 12.7 mm nominal diameter thermoplastic composite rebars. Simple bend tests on FRTP rebar that rely on basic equipment are performed to verify its ability to be field-formed. The manual bending technique demonstrated here is practical and straightforward, although it does result in some fiber misalignment. Subsequently, surface deformations are introduced to the rebar to promote mechanical bonding with concrete, and tensile tests of the bars are conducted to determine their mechanical properties. Finally, flexural tests of simply-supported, 6 meter long beams reinforced with FRTP rebar are performed to assess their strength and stiffness as well as the practicality of using FRTP rebar. The beam tests demonstrated the prototype FRTP rebar’s potential for reinforcing concrete beams, and the beam load–deformation response and capacity agree well with predictions developed using conventional structural analysis principles. Overall, the results of the research reported indicate that thermoplastic rebars manufactured via the Continuous Forming Machine are a promising alternative to both steel and conventional thermoset composite rebar. However, both the beam and tension test results indicate that improvements in material properties, especially elastic modulus, are necessary to meet the requirements of current FRP rebar specifications. Full article

Expansive soils, characterized by the presence of surface and subsurface cracks, over-consolidation, and swell-shrink properties, present significant challenges to slope stability in geotechnical engineering. Despite extensive research, preventing geohazards associated with expansive soils remains unresolved. This study investigates shallow sliding failures in slopes of highly expansive soils induced by rainfall, using model tests to explore deformation and mechanical behavior under cyclic wetting and drying conditions, focusing on the interaction between soil properties and environmental factors. Model tests were conducted in a wedge-shaped box filled with Nanyang expansive clay from Henan, China, which is classified as high-plasticity clay (CH) according to the Unified Soil Classification System (USCS). The soil was compacted in four layers to maintain a 1:2 slope ratio (i.e., 1 vertical to 2 horizontal), which reflects typical expansive soil slope configurations observed in the field. Monitoring devices, including moisture sensors, pressure transducers, and displacement sensors, recorded changes in soil moisture, stress, and deformation. A static treatment phase allowed natural crack development to simulate real-world conditions. Key findings revealed that shear failure propagated along pre-existing cracks and weak structural discontinuities, supporting the progressive failure theory in shallow sliding. Cracks significantly influenced water infiltration, creating localized stress concentrations and deformation. Atmospheric conditions and wet-dry cycles were crucial, as increased moisture content reduced soil suction and weakened the slope’s strength. These results enhance understanding of expansive soil slope failure mechanisms and provide a theoretical foundation for developing improved stabilization techniques. Full article

Teachers’ 21st century technological pedagogical content knowledge affects their performance self-evaluations, and it is considered that their attitudes towards sustainable education disposition and their digital competencies may also have an impact on their performance self-evaluations and thus may significantly affect these relationships. In this study, it was aimed to examine the effect of teachers’ 21st century technological pedagogical content knowledge on their performance self-evaluations, and the moderating role of digital competencies mediated by sustainable educational disposition in the model established for this purpose was examined. The research sample consisted of 478 teachers (305 female (63.8) and 173 (36.2) male teachers) working in various fields in schools in Türkiye. Within the scope of the research, data analyses were carried out in SPSS 21 and PROCESS Macro package programs using Model 4 and Model 58 developed by Hayes (2022). As a result of the analyses, it was seen that sustainable education tendencies had a mediating role in the relationship between teachers’ 21st-century technological pedagogical content knowledge and their performance self-evaluations. In addition to this, it was seen that 21st-century technological pedagogical content knowledge, sustainable educational dispositions and performance self-evaluations depend on the level of digital competencies. Full article