Search Results (17,299)

Gangue backfilling has become an important technique for promoting environmentally friendly and low-carbon coal mining. The long-term creep behavior of cemented backfill plays a critical role in maintaining stope stability and controlling surface subsidence during long-term service. Although considerable research has been conducted on cemented tailings backfill, systematic investigations on the triaxial creep evolution, long-term strength characteristics, confining pressure effects, and the applicability of the classical Burgers model for gangue–gypsum cemented backfill under engineering-relevant confining pressures remain limited. In this study, the experimental scheme was designed based on field monitoring data from practical backfill mining operations, which indicate that the in situ backfill generally remains stable without significant deformation or instability under normal working conditions. Multi-stage loading triaxial creep tests were conducted on gangue–gypsum cemented backfill under confining pressures of 1, 2, 3, and 4 MPa. The creep deformation characteristics were analyzed using Chen’s superposition method, while the long-term strength was computed via inflection point method of isochronous stress–strain curves. The parameters of the Burgers creep model were identified using the Levenberg–Marquardt optimization algorithm, and numerical verification was performed using FLAC3D. Our findings demonstrate that the creep deformation process of the backfill consists of three typical stages: instantaneous deformation, attenuated creep, and steady-state creep, and no accelerated creep was observed within the applied stress range. The absolute creep strain surges nonlinearly with increasing stress level (S_L), whereas higher confining pressure significantly suppresses the creep response of the material. Within the investigated stress range, the backfill exhibits mainly linear viscoelastic behavior, and its critical long-term strength is not less than 0.9 times the failure deviatoric stress (qf). Although confining pressure enhances the long-term strength, the strengthening effect weakens as the confining pressure increases. Model fitting outcomes imply that Burgers model precisely describes the creep behavior of gangue–gypsum cemented backfill under all test conditions, with correlation coefficients (R²) exceeding 0.97. The identified parameters show systematic variation with S_L, reflecting stiffness degradation and viscous evolution during loading. Numerical simulation results agree well with the experimental data, providing theoretical guidance for mixture proportion optimization, long-term stability evaluation, and stope support parameter design in gangue backfill mining engineering. Full article

Modern road infrastructure asset management faces increasing pressure to improve the quality of decision-making processes, also due to limited public resources. The field of road diagnostics is no exception. The aim of the research is to analyze, through a literature review, the possibilities of applying the theoretical concept of information value. The selected point of interest is the tasks associated with the selection of specific sections intended for inspection, monitoring the level of information gain that this inspection can bring. Methodologically, the research is based on a systematic bibliometric analysis of the literature from the Web of Science and SCOPUS databases for the period January 2010 to June 2025. This is supplemented by a non-systematic content review, while the identified publications were processed by the Bibliometrix and VOSviewer tools and subsequently qualitatively interpreted. The result of the research is a synthesis of knowledge from the finally analyzed set of relevant scientific papers. The findings point to a growing interest in linking the process of planning and performing road infrastructure diagnostics with asset management decision-making processes. At the same time, they point to the development of data-oriented and digital approaches, as well as the limited application of the concept of information value in planning inspections before their implementation. The findings indicate that the assessment of expected information benefit represents a promising tool for reducing uncertainty, determining priorities, and allocating resources more efficiently, while its implementation in road infrastructure management requires further methodological research and practical verification. Full article

The extensive cultivation scale of sugar beet seedlings has resulted in the necessity for accurate identification and monitoring of the seedling count, a task which has become crucial and highly challenging in the sugar industry. However, sugar beet seedlings in UAV aerial photography scenarios are mostly small targets with complex backgrounds. Existing general detection models not only have insufficient detection accuracy, but also struggle to balance computational efficiency and resource consumption. To meet the practical needs of field monitoring, this paper proposes the LDH-RTDETR, a sugar beet seedling detection model that balances high accuracy and light weight. This model uses LSNet for feature extraction to reduce size, adds a deformable attention (DAttention) module to capture fine-grained seedling features, and adopts HS-FPN to improve multi-scale feature fusion in the neck network. Experimental results show that the improved model significantly outperforms the original RT-DETR model, with a 3.6% increase in accuracy, a 2.1% increase in mAP50, a recall rate of 86.0%, and a final model size of only 43.3 MB, thus achieving an effective balance between accuracy and model size. This study’s improved model offers an efficient solution for large-area identification and counting of sugar beet seedlings, and is highly significant for advancing the automation of sugar crop field management and agricultural digital transformation. Full article

In order to guarantee sufficient growth, digestive stability, and long-term productivity in dairy heifers, proper nutritional management is crucial both before and after weaning. This case study assesses the impact of dietary modifications on growth performance and digestive parameters in commercial settings and details a field observation of concentrate overload in young Holstein heifers. From 77 to 165 days of age, the body weight (BW), average daily gain (ADG), body condition score (BCS), feed intake, and fecal characteristics of 15 calves were monitored. Infectious and parasitic causes of diarrhea were ruled out by fecal examinations. Ad libitum concentrate feeding resulted in low fecal scores with undigested grain particles and acidic smell, starch intake exceeding requirements, and concentrate intake reaching up to 6 kg as fed head×day. The BCS gradually rose, and ADG peaked at 1.64 kg/day. Forage intake increased, fecal consistency improved, and ADG stabilized after restricting concentrate allowance to 2.5% of BW. These results underline the significance of controlling starch intake and concentrate allowance to avoid excessive growth and digestive disorders in developing dairy heifers, and they support a nutritional basis for the observed digestive imbalance. Full article

Early-age cracking is a common issue in the prefabrication of large-scale box girders, and the application of pre-tensioning techniques to introduce pre-compressive stress is an effective measure to mitigate such cracking. To determine an optimal pre-tensioning scheme for the 60 m large-scale box girder used in the Ningbo–Xiangshan intercity railway, friction coefficient tests and field stress monitoring were conducted. A numerical model simulating the pre-tensioning process of the box girder, accounting for the constraint of the steel formwork, was developed using Abaqus 2021. Based on the validated finite element model, a parametric study was performed to investigate the effects of friction coefficient, internal formwork roof, and prestressing tendon arrangement on the pre-compressive stress. The results indicate that the bond force between cast-in-place concrete and steel formwork is approximately 2.1 times the sliding friction force. As the friction coefficient increases, the pre-compressive stress in the box girder exhibits a notable decreasing trend. For the critical midspan section S40, the inclusion of frictional effects results in a more uniform distribution of pre-compressive stress. Compared to the case without the internal formwork roof, its inclusion leads to a 9.2% to 10.4% reduction in pre-compressive stress at section S40. To mitigate prestress losses transmitted from the ends to the midspan section, it is recommended that the internal formwork be completely removed prior to prestressing tensioning. The pre-compressive stress in the box girder varies considerably with different prestressing combinations. The comparative analysis of different prestressing combinations reveals substantial variations in pre-compressive stress distribution. After evaluating multiple schemes, the optimal pre-tensioning sequence for the 60-m railway box girder is determined as follows: sequentially tensioning tendon groups F1-2, F1-4, F1-5, F1-6, and B2-3, with an anchorage stress controlled at 558 MPa. This scheme ensures that all critical sections of the box girder remain in a pre-compressive state. In particular, the pre-compressive stress at the key midspan section S40 ranges from 1.12 to 1.26 MPa, achieving the desired effect and effectively suppressing early-age cracking in the large-scale box girder concrete. Full article

Frequent flash floods threaten human well-being, hydropower infrastructure, and ecosystems. However, the long-term evolution of flash flood patterns over recent decades remains insufficiently understood, particularly in data-scarce high-altitude regions. Using multi-source remote sensing data integrated with historical disaster records and field investigations, this study examined the spatiotemporal evolution and driving factors of flash floods across the Qinghai–Tibet Plateau (QTP). The results indicate that flash floods have increased exponentially, which may be influenced by disaster management policies, with peaks in July–August and frequent occurrences from April to September. The seasonal trajectory of the center of gravity of flash floods from April to September exhibited a clear directional pattern. Regions with the highest disaster density were concentrated in the headwaters of five major rivers, including the Yarlung Zangbo, Jinsha, Nu, Lancang, and Yellow Rivers. Shapley Additive Explanation (SHAP) and Random Forest analyses reveal that soil moisture, anthropogenic intensity, and seasonal runoff variability are the dominant driving factors. With ongoing socioeconomic development, intensified human activities have become a key contributor to the increasing frequency of flash floods. These findings highlight the value of remote sensing-based assessments for flash flood monitoring and early warning and provide scientific support for risk mitigation, loss reduction, and the advancement of water-related targets under the United Nations’ Sustainable Development Goals. Full article

In recent years, China’s rapid economic development has driven the improvement of infrastructure, with mass concrete widely applied in engineering for its unique structural functions. However, mass concrete is prone to temperature stress and thermal cracks due to its low thermal conductivity, huge volume, complex construction conditions, and frequent environmental changes, which pose potential structural safety risks. The hydration heat of mass concrete can also cause structural deformation, so targeted measures must be taken based on actual engineering conditions to minimize cracks. Real-time temperature monitoring during pouring is of crucial significance to ensure the quality and safety of mass concrete in practical projects. Taking the Phase I Project of Qingdao Metro Line 9 as the research object, this paper explores the temperature variation characteristics of mass concrete during pouring and forming on-site. It analyzes the temperature changes in mass concrete based on field temperature-monitoring data and laboratory test results, plots temperature measurement curves, and identifies the temperature variation trend of mass concrete caused by hydration heat. A numerical model is established via ANSYS to study the effects of ventilation temperature and velocity by simulation. Results show that the temperature of mass concrete pouring blocks rises rapidly to a peak and then decreases to room temperature, which is analyzed from the perspectives of hydration heat reaction mechanism and heat transfer. Laboratory test data are highly consistent with field data, verifying the temperature variation characteristics of concrete pouring. The numerical simulation of heat transfer-influencing factors reveals that the optimal ventilation velocity is 4 m/s for sufficient air circulation in the foundation pit; when the ventilation temperature is below 25 °C, the surface temperature of concrete decreases significantly with an obvious cooling effect. Full article

Winter thermal comfort in university classrooms in China’s Hot Summer and Cold Winter (HSCW) regions remains problematic due to mismatches between institutional heating setpoints and students’ actual thermal preferences. To investigate students’ thermal perceptions and behavioral responses, a post-occupancy evaluation (POE) survey was conducted, followed by field measurements in a typical classroom in Chengdu under three conditions: no-heating condition, heating conditions at 20 °C and 25 °C. Indoor environmental parameters were continuously monitored, and thermal comfort was assessed using the Predicted Mean Vote (PMV) and Predicted Percentage of Dissatisfied (PPD) model. The results show that no-heating conditions were unacceptable, highlighting the necessity of heating. While the 20 °C setpoint provided partial improvement, thermal comfort was not consistently achieved throughout the day. In contrast, the 25 °C setpoint maintained near-neutral conditions during most occupied periods. In addition, a pre-heating duration of approximately 30 min was found to be essential for reducing initial thermal discomfort. Overall, the findings indicate that fixed institutional heating standards may not adequately satisfy students’ thermal needs. Adaptive heating strategies that combine appropriate setpoints with sufficient pre-heating duration are therefore recommended to balance thermal comfort and energy efficiency in university classrooms in the HSCW regions. Full article

Lago Argentino and Lago Viedma are large lakes fed by glaciers in Southern Patagonia, characterized by extraordinarily strong, persistent westerly winds and sharp gradients in regional relief, climate, and gravity field. We present operational models of spatio-temporal lake-level variations that represent instantaneous ellipsoidal lake-surface height as the superposition of three components: (i) a time-averaged lake-level topography derived from geoid modeling and ICESat-2 residuals, (ii) temporally varying water-volume changes in the lake estimated from tide gauge time series corrected for atmospherically driven perturbations, and (iii) a static hydrodynamic response to wind stress and air-pressure forcing. The atmospheric response is parametrized through empirically derived transfer functions obtained by regressing instantaneous lake-level anomalies against ERA5 wind and pressure fields, capturing wind-driven tilting. Standard deviations of ICESat-2 ATL13 elevations amount to 106 cm and 70 cm over Lago Argentino and Lago Viedma, respectively. The subtraction of our models reduces these standard deviations to 8 cm (Argentino) and 14 cm (Viedma). Surface waves incompletely averaged out within ICESat-2’s narrow footprint are identified as a principal source for the residual variability. A standard deviation of ATL13 elevations below 2 cm on calm days demonstrates ICESat-2’s unprecedented capability of monitoring water resources from space in a region of sparse hydrological infrastructure. Full article

Multi-source radar data fusion has become increasingly vital for advancing weather monitoring and forecasting. However, effectively integrating Doppler radar with an X-band phased-array radar remains challenging. Doppler radar offers only low and inconsistent spatial resolution, whereas an X-band phased-array radar provides high resolution but is limited by short detection range, severe signal attenuation, and high deployment costs, constraining its use to localized monitoring. To address the aforementioned challenges, this paper proposes the Multi-source Radar Reflectivity Complementary Enhancement method (MSR-CE). By constructing a paired training dataset, real X-band phased-array radar reflectivity data serve as the starting samples for the forward diffusion process, while paired S-band Doppler radar reflectivity data act as conditional guidance. Leveraging a conditional diffusion model, the method generates high-resolution pseudo X-band phased-array reflectivity fields. Additionally, a Radar-Physics-Aware Loss (RPA Loss) is introduced to enhance spatial detail fidelity and physical consistency. Experiments on multi-source radar observations from Northeast China in 2025 demonstrate that MSR-CE achieves an SSIM of 0.892 and a PSNR of 41.6 dB, outperforming traditional interpolation methods and state-of-the-art generative approaches in radar reflectivity enhancement. Full article

Rapid and real-time monitoring of blood glucose concentration is critical for the diagnosis and management of diabetes, while conventional invasive detection methods suffer from inconvenience and discomfort, making non-invasive detection a research hotspot. In this study, a dual complementary split-ring resonator (DS-CSRR) operating at 3.3 GHz was designed and fabricated for non-invasive glucose concentration detection, aiming to address the problems of low sensitivity and large size of existing microwave glucose sensors. The sensor was fabricated on a low-cost FR4 dielectric substrate with dimensions of 20 × 30 × 0.8 mm³, and two U-shaped slots were incorporated into the traditional DS-CSRR structure to realize cross-polarization excitation. This design not only enhances the interaction between the electric field and glucose solution but also optimizes the quality factor (Q) and electric field distribution of the resonator without changing the overall size. Compared with the traditional DS-CSRR, the Q factor of the modified structure is increased to 130 under no-load conditions. The transmission coefficient Signal Port 2 to Port 1 (S21) of the sensor loaded with glucose solutions of different concentrations was measured using a vector network analyzer (VNA). The experimental results show a good linear frequency shift with the increase in glucose concentration, with a measured sensitivity of 1.95 kHz/(mg·dL⁻¹). In addition, the sensor is characterized by miniaturization, low cost and easy fabrication due to the adoption of standard PCB fabrication processes. This study successfully demonstrates a non-invasive microwave sensor with high sensitivity for glucose concentration detection, which has promising application potential in personal continuous glucose monitoring, and also provides a useful design strategy for the development of miniaturized high-sensitivity microwave biosensors. Full article

Ensuring the safety and effectiveness of first responder teams during critical missions requires real-time health monitoring and responsive intervention systems. This study presents a novel system comprising a multimodal wearable device integrated with a remote command centre, designed to support the physiological monitoring and guidance of first responders in the field. The wearable device includes three main components: a physiological and biochemical signal acquisition unit, an electrotactile stimulation unit and a powerful communication interface. The acquisition unit continuously samples heart rate, body temperature, and biochemical markers from sweat, transmitting this data wirelessly to the remote command centre. The transmitted physiological data could be analyzed at the command centre and, based on the inferred first responder condition, appropriate feedback commands could be issued back to the corresponding wearer. The commands are then executed by the electrotactile stimulation unit on the wearable device. Initial testing in laboratory settings confirmed the system’s ability to generate accurate electrochemical readings and dehydration assessment through changes in bulk ionic conductivity. Electrochemical impedance spectroscopy showed good agreement with a commercial potentiostat. Heart rate and temperature readings demonstrated satisfying accuracy with minor removable artifacts. Field trials with first responders validated continuous signal transmission and electrotactile feedback with over 80% success. These results confirm the system’s robustness and modularity, supporting its application in operational environments. Full article

Numerous studies have demonstrated the potential of Synthetic Aperture Radar (SAR) in monitoring glacier velocity. However, owing to the complex dynamics of glaciers and the variability of their surface features, velocity fields derived from even short-interval SAR image pairs often exhibit missing parts. This study proposes a missing glacier velocity recovery method based on a spatiotemporal hybrid neural network to solve the above problem. Considering the spatiotemporal characteristics of glacier velocity fields, a hybrid network combining an Artificial Neural Network (ANN) and a Denoising Autoencoder (DAE) is developed. The ANN is first employed to capture spatial correlations associated with missing values, after which it is integrated with the DAE to model temporal variations using a time-aware loss function. An iterative weighting strategy adaptively balances spatial and temporal features during training. The method is applied to SAR–derived velocity fields of Petermann Glacier. Experimental results show that the method significantly improves the performance of glacier velocity recovery compared to traditional methods. Additionally, the study compares and analyzes the velocity of Petermann Glacier in different seasons, and the findings indicate that the glacier exhibits more pronounced seasonal differences in the accumulation zone. Full article

Potato is one of the most important food crops worldwide, playing a critical role in global food security and agricultural production. The broken and impurity rates are important indicators for evaluating the harvesting quality of potato combine harvesting operations. To address the difficulty of achieving continuous and online detection using traditional methods, this study investigates an online monitoring approach for potato combine harvesting based on machine vision. Considering the characteristics of large material volume, severe overlap, and similar appearance features under field operating conditions, an online monitoring device suitable for potato combine harvesters was designed, along with a corresponding image acquisition and processing workflow. For the online monitoring device, an improved You Only Look Once version 11 (YOLOv11) detection model, was proposed to meet the requirements of multi-object detection in complex operating scenarios. The model incorporates Multi-Scale Depthwise Convolution (MSDConv), C2PSA_DCA (with Directional Context Attention, DCA), and Directional Selective Attention (DSA) modules, and introduces the Efficient Intersection over Union (EIoU) loss function to enhance recognition capability for broken potatoes and multiple types of impurity targets. While maintaining lightweight characteristics, the improved model demonstrates favorable detection accuracy. Field experiment results show that when the combine harvester operates at a forward speed of 3 km/h, the relative errors for broken and impurity rates are measured as 3.78% and 3.67%, respectively. Under extreme operating conditions with a speed of 4 km/h, the corresponding average relative errors rise to 8.30% and 8.72%, respectively. Overall, the online detection results exhibit satisfactory consistency with manual measurements, providing effective technical support for real-time monitoring of harvesting quality in potato combine harvesting operations. Future research will focus on expanding multi-scenario datasets under diverse soil and illumination conditions, as well as integrating detection results with adaptive control strategies to further enhance intelligent harvesting performance. Full article

Timely identification of canopy decline in commercial strawberry production is challenging because visual scouting often misses subtle or spatially heterogeneous symptoms. We developed a plant-level UAV-based monitoring framework that integrates repeated multispectral imagery, canopy-derived metrics, unsupervised clustering, and Random Survival Forest (RSF) time-to-event modeling. The framework was applied across three commercial strawberry fields in Oxnard, California using nine UAV surveys collected from December 2022 to June 2023, yielding 159,220 plant-level monitoring units. NDRE- and Redness Index-based classifications quantified proportional and absolute canopy dieback within standardized hexagonal units and supported survival-based modeling of canopy decline progression. Across withheld test plants from all survey dates, overall concordance indices ranged from 0.88 to 0.95 across fields, indicating strong ability to rank plants by time-to-decline risk under heterogeneous field conditions. Spatial risk maps revealed localized high-risk clusters that expanded over time in fields with greater canopy deterioration, while fields with minimal visible decline exhibited diffuse but stable risk distributions. Post-hoc comparison with operational fumigation rates (280, 336, and 392 kg Pic-Clor 60/ha) showed no consistent association with predicted canopy decline risk. These results demonstrate that framing repeated UAV observations as a time-to-event process enables fine-scale spatiotemporal modeling of canopy decline dynamics and supports risk stratification for targeted field monitoring in commercial strawberry systems. Full article