Search Results (3,006)

During unmanned drilling operations, the velocity of drill cuttings serves as an important indicator of drilling conditions, which necessitates real-time and accurate measurements. To address challenges such as the small size of cuttings, weak feature representations, and complex motion trajectories, we propose a novel velocity measurement method integrating small-object detection and tracking. Specifically, we enhance the multi-scale feature fusion capability of the YOLOv11 detection head by incorporating a lightweight feature extraction module, Ghost Conv, and a feature-aligned fusion module, FA-Concat, resulting in an improved model named YOLOv11-Dd (drilling debris). Furthermore, considering the robustness of the ByteTrack algorithm in retaining low-confidence targets and handling occlusions, we integrate ByteTrack into the tracking phase to enhance tracking stability. A velocity estimation module is introduced to achieve high-precision measurement by mapping the pixel displacement of detection box centers across consecutive frames to physical space. To facilitate model training and performance evaluation, we establish a drill-cutting splash simulation dataset comprising 3787 images, covering a diverse range of ejection angles, velocities, and material types. The experimental results show that the YOLOv11-Dd model achieves a 4.65% improvement in mAP@80 over YOLOv11, reaching 76.04%. For mAP@75–95, it improves by 0.79%, reaching 41.73%. The proposed velocity estimation method achieves an average accuracy of 92.12% in speed measurement tasks, representing a 0.42% improvement compared to the original YOLOv11. Full article

The soil-borne fungi, Setophoma terrestris and Fusarium spp., are often associated with pink root, although the etiology of the disease remains doubtful. While recognized as the primary inoculum, studies show conflicting views on the formation of chlamydospores and microsclerotia in Setophoma. Therefore, this study aims to clarify the etiology of the pink root of garlic and onion and the formation of chlamydospores and microsclerotia in Setophoma. The isolates were obtained from symptomatic tissues of garlic, leeks, brachiaria, onions, chives, and maize collected from seven different states in Brazil. Representative isolates were selected for pathogenicity tests. Sequence comparison of the tubulin gene showed Setophoma (n = 50) and Fusarium clades (n = 25). Garlic and onion plants inoculated with Setophoma showed pink root symptoms, while plants inoculated with different Fusarium isolates remained asymptomatic. Multigene analysis of pathogenic isolates confirms that only Setophoma terrestris causes pink root in garlic and onion. In addition, brachiaria, chives, and leeks are newly identified hosts of this pathogen in Brazil. To our knowledge, the main sources of primary inoculum of the disease are chlamydospores, pycnidia, colonized roots of garlic, onion, and plant debris of susceptible crops. The new information obtained in this study will be fundamental for researchers in the development of genotypes that are resistant to pink root and will help the efficient management of the disease. Full article

Simulated data created in silico using a previously reported method were sampled by bootstrapping to generate data sets for training multiple copies of an ensemble learner (i.e., a machine learning (ML) method). The posterior probabilities of class membership obtained by applying the ensemble of ML models to previously unseen validation data were fitted to a beta distribution. The shape parameters for the fitted distribution were used to calculate the subjective opinion of sample membership into one of two mutually exclusive classes. The subjective opinion consists of belief, disbelief and uncertainty masses. A subjective opinion for each validation sample allows identification of high-uncertainty predictions. The projected probabilities of the validation opinions were used to calculate log-likelihood ratio scores and generate receiver operating characteristic (ROC) curves from which an opinion-supported decision can be made. Three very different ML models, linear discriminant analysis (LDA), random forest (RF), and support vector machines (SVM) were applied to the two-state classification problem in the analysis of forensic fire debris samples. For each ML method, a set of 100 ML models was trained on data sets bootstrapped from 60,000 in silico samples. The impact of training data set size on opinion uncertainty and ROC area under the curve (AUC) were studied. The median uncertainty for the validation data was smallest for LDA ML and largest for the SVM ML. The median uncertainty continually decreased as the size of the training data set increased for all ML.The AUC for ROC curves based on projected probabilities was largest for the RF model and smallest for the LDA method. The ROC AUC was statistically unchanged for LDA at training data sets exceeding 200 samples; however, the AUC increased with increasing sample size for the RF and SVM methods. The SVM method, the slowest to train, was limited to a maximum of 20,000 training samples. All three ML methods showed increasing performance when the validation data was limited to higher ignitable liquid contributions. An ensemble of 100 RF ML models, each trained on 60,000 in silico samples, performed the best with a median uncertainty of 1.39x${10}^{-2}$ and ROC AUC of 0.849 for all validation samples. Full article

The cigarette butt (CB) recycling process yields several byproducts, including cleaned filters, solid debris (mainly paper and tobacco), and wastewater. This study aimed to assess, for the first time, the long-term suitability of these recycled byproducts for turfgrass cultivation. Under controlled conditions, Paspalum vaginatum Swartz was grown in sand–peat substrate, either unmodified (control) or amended with small pieces of uncleaned CBs or solid byproducts from CB recycling at concentrations of 25% or 50% (v/v). In additional tests, turfgrass grown in unmodified substrate received wastewater instead of tap water once or twice weekly. Over 7 weeks, physiological and biometric parameters were assessed. Plants grown with solid debris showed traits comparable to the control. Those grown with intact CBs or cleaned filters had similar biomass and coverage as the control but accumulated more carotenoids and antioxidants. Wastewater significantly enhanced plant growth when applied once weekly, while becoming toxic when applied twice, reducing biomass and coverage. After scalping, turfgrass recovered well across all treatments, and in some cases biomass improved. Overall, recycled CB byproducts, particularly wastewater used at optimal concentrations, can be a sustainable resource for promoting turfgrass growth. Full article

The Junggar Basin contains a large amount of coal resources and is an important coal production base in China. The coal seam in Zhundong coalfield has a large single-layer thickness and high content of inertinite, but large particle Fe-sulphide minerals are associated with coal seams in some mining areas. A series of economic and environmental problems caused by the combustion of large-grained Fe-sulphide minerals in coal have seriously affected the economic, clean and efficient utilization of coal. In this paper, the ultra-thick coal seam of the Xishanyao formation in the Yihua open-pit mine of the Zhundong coalfield is taken as the research object. Through the analysis of coal quality, X-ray fluorescence spectrometer test of major elements in coal, inductively coupled plasma mass spectrometry test of trace elements, SEM-Raman identification of Fe-sulphide minerals in coal and LA-MC-ICP-MS test of sulfur isotope of marcasite, the coal quality characteristics, main and trace element characteristics, macro and micro occurrence characteristics of Fe-sulphide minerals and sulfur isotope characteristics of marcasite in the ultra-thick coal seam of the Xishanyao formation are tested. On this basis, the occurrence state and genesis of large particle Fe-sulphide minerals in the ultra-thick coal seam of the Xishanyao formation are clarified. The main results and understandings are as follows: (1) the occurrence state of Fe-sulphide minerals in extremely thick coal seams is clarified. The Fe-sulphide minerals in the extremely thick coal seam are mainly marcasite, and concentrated in the YH-2, YH-3, YH-8, YH-9, YH-14, YH-15 and YH-16 horizons. Macroscopically, Fe-sulphide minerals mainly occur in three forms: thin film Fe-sulphide minerals, nodular Fe-sulphide minerals, and disseminated Fe-sulphide minerals. Microscopically, they mainly occur in four forms: flake, block, spearhead, and crack filling. (2) The difference in sulfur isotope of marcasite was discussed, and the formation period of marcasite was preliminarily divided. The overall variation range of the δ³⁴S value of marcasite is wide, and the extreme values are quite different. The polyflake marcasite was formed in the early stage of diagenesis and the δ³⁴S value was negative, while the fissure filling marcasite was formed in the late stage of diagenesis and the δ³⁴S value was positive. (3) The coal quality characteristics of the thick coal seam were analyzed. The organic components in the thick coal seam are mainly inertinite, and the inorganic components are mainly clay minerals and marcasite. (4) The difference between the element content in the thick coal seam of the Zhundong coalfield and the average element content of Chinese coal was compared. The major element oxides in the thick coal seam are mainly CaO and MgO, followed by SiO₂, Al₂O₃, Fe₂O₃ and Na₂O. Li, Ga, Ba, U and Th are enriched in trace elements. (5) The coal-accumulating environment characteristics of the extremely thick coal seam are revealed. The whole thick coal seam is formed in an acidic oxidation environment, and the horizon with Fe-sulphide minerals is in an acidic reduction environment. The acidic reduction environment is conducive to the formation of marcasite and is not conducive to the formation of pyrite. (6) There are many matrix vitrinite, inertinite content, clay content, and terrigenous debris in the extremely thick coal seam. The good supply of peat swamp, suitable reduction environment and pH value, as well as groundwater leaching and infiltration, together cause the occurrence of large-grained Fe-sulphide minerals in the extremely thick coal seam of the Xishanyao formation in the Zhundong coalfield. Full article

The extended operation of high-speed railways has led to an increased incidence of tunnel lining defects, with falling debris posing a significant safety threat. Within tunnels, single-train passage and trains-crossing events constitute the most frequent operational scenarios, both generating extreme aerodynamic environments that alter debris trajectories from free fall. To systematically investigate the aerodynamic differences and underlying mechanisms governing falling debris behavior under these two distinct conditions, a three-dimensional computational fluid dynamics (CFD) model (debris–air–tunnel–train) was developed using an improved delayed detached eddy simulation (IDDES) turbulence model. Comparative analyses focused on the translational and rotational motions as well as the aerodynamic load coefficients of the debris in both single-train and trains-crossing scenarios. The mechanisms driving the changes in debris aerodynamic behavior are elucidated. Findings reveal that under single-train operation, falling debris travels a greater distance compared with trains-crossing conditions. Specifically, at train speeds ranging from 250–350 km/h, the average flight distances of falling debris in the X and Z directions under single-train conditions surpass those under trains crossing conditions by 10.3 and 5.5 times, respectively. At a train speed of 300 km/h, the impulse of C_Fx and C_Fz under single-train conditions is 8.6 and 4.5 times greater than under trains-crossing conditions, consequently leading to the observed reduction in flight distance. Under the conditions of trains crossing, the falling debris is situated between the two trains, and although the wind speed is low, the flow field exhibits instability. This is the primary factor contributing to the reduced flight distance of the falling debris. However, it also leads to more pronounced trajectory deviations and increased speed fluctuations under intersection conditions. The relative velocity (CRV) on the falling debris surface is diminished, resulting in smaller-scale vortex structures that are more numerous. Consequently, the aerodynamic load coefficient is reduced, while the fluctuation range experiences an increase. Full article

The 1980 eruption of Mount St. Helens (WA, USA) presented a unique opportunity to observe primary succession in a post-eruption landscape previously dominated by conifer forests. The eruption scoured soil and biological communities adjacent to the mountain, and species of conifers have generally been slow to colonize the nutrient-poor substrate surrounding the volcano. Further, different species of conifer establish and grow at different rates. The recent advancement of conifers in the post-eruption landscape has highlighted a research gap related to conifer growth patterns. We measured the height, age, and incremental growth of 472 trees representing three common conifers, Pseudotsuga menziesii, Abies procera, and Pinus contorta, on debris avalanche (80 sites) and pyroclastic flow (82 sites) disturbance zones of the 1980 eruption. We paired annual incremental growth with recent climate data. We found that height, age, and growth rates differ among species and sites. All species had higher growth rates on the debris avalanche deposit compared to the pyroclastic flow due to either climate or substrate. Climate influences were mixed, where one species increased growth with temperature, another declined, and another was unrelated. Nevertheless, more than 40 years after the eruption, we find rapid height growth in species with implications for future forests. Full article

This paper presents the design, simulation, and experimental validation of a dual-Circularly Polarized (CP) array antenna to be used as single element for a bistatic radar system, aimed at detecting and tracking objects in Low Earth Orbit (LEO). The antenna operates at 412 MHz in reception mode and consists of an array of 19 slotted-patch radiating elements with a cavity-based metallic superstrate, designed to support dual circular polarization. These elements are arranged in a hexagonal configuration, enabling the array structure to achieve a maximum realized gain of 17 dBi and a Side Lobe Level (SLL) below −17 dB while maintaining high polarization purity. Two identical analog feeding networks enable the precise control of phase and amplitude, allowing the independent reception of Right-Hand and Left-Hand Circularly Polarized (RHCP and LHCP) signals. Full-wave simulations and experimental measurements confirm the high performance and robustness of the system, demonstrating its suitability for integration into large-scale Space Situational Awareness (SSA) sensor networks. Full article

Accurate oil debris analysis and wear monitoring of a gearbox are essential to ensure its stable and reliable operation. Element types of wear debris and their changes in the lubrication oil of the gearbox can be monitored by spectral analysis. However, it is still difficult to identify wear parts of the gearbox due to the complex composition of elements of wear debris. An improved multi-variable grey prediction model by incorporating a multi-objective genetic algorithm (MOGA-GM(1, N)) is proposed to evaluate weight coefficients of element concentrations of wear debris in the lubrication oil of the gearbox. Moreover, a wear growth rate of each element in the lubrication oil is proposed as an index for oil debris analysis to analyze the multi-variable correlation between the common element of iron (Fe) and other related elements of wear parts of the gearbox. Oil debris analysis of the gearbox is conducted on optimal weight coefficients of related elements to the common element Fe using the MOGA-GM(1, N) model. Wear experiment results verify feasibility of the proposed oil debris analysis method. Full article

In this study, dry sliding wear tests were carried out on Er, Zr-microalloyed Al-Zn-Mg alloys with different Zn/Mg ratios under 30–70 N loads. The effects of the Zn/Mg content ratio and Er microalloying on the friction coefficient, wear volume loss, worn surface, and wear debris during the friction process of Al-Zn-Mg alloys were analyzed. At the load of 30 N, abrasive wear, fatigue wear, and adhesive wear were synergistically involved. At a load of 50 N, the abrasive wear dominated, accompanied by fatigue wear and adhesive wear. At a load of 70 N, the primary wear mechanisms transitioned to abrasive wear and fatigue wear, with additional adhesive wear and oxidative wear observed. Reducing the Zn/Mg ratio mitigated wear volume across all tested loads. For the Al4.5Zn1.5Mg alloy, Er microalloying significantly reduced wear volume under moderate-to-low loads (30 N, 50 N). Full article

Plastic debris is a pervasive and persistent threat to marine ecosystems. Microplastics (plastics < 5 mm) are increasing in a variety of marine habitats, including open water systems, shorelines, and benthic sediments. It remains unclear how microplastics distribute and accumulate in marine systems and the extent to which this pollutant is accessible to marine taxa. We examined subtidal benthic sediments and beach sediments in critical nearshore habitats for forage fish species—Pacific sand lance (Ammodytes personatus), Pacific herring (Clupea pallasi), and surf smelt (Hypomesus pretiosus)—to quantify microplastic concentrations in the spawning and deep-water habitats of these fish and better understand how microplastics accumulate and distribute in nearshore systems. In the San Juan Islands, we examined an offshore subtidal bedform in a high-flow channel and beach sites of protected and exposed shorelines. We also examined 12 beach sites proximate to urban areas in Puget Sound. Microplastics were found in all samples and at all sample sites. Microfibers were the most abundant, and flakes were present proximate to major shipyards and marinas. Microplastics were significantly elevated in Puget Sound compared to the San Juan Archipelago. Protected beaches had elevated concentrations relative to exposed beaches and subtidal sediments. Microplastics were in higher concentrations in sand and fine-grain sediments, poorly sorted sediments, and artificial sediments. Microplastics were also elevated at sites confirmed as spawning habitats for forage fish. The model results indicate that both current speed and proximate urban populations influence nearshore microplastic concentrations. Our research provides new insights into how microplastics are distributed, deposited, and retained in marine sediments and shorelines, as well as insight into potential exposure in benthic, demersal, and shoreline habitats. Further analyses are required to examine the relative influence of urban populations and shipping lanes and the effects of physical processes such as wave exposure, tidal currents, and shoreline geometry. Full article

The growing density of space objects in low Earth orbit (LEO), driven by the deployment of large satellite constellations, has elevated the risk of orbital collisions and the need for high-precision conjunction analysis. Traditional methods based on Two-Line Element (TLE) data suffer from limited accuracy and insufficient uncertainty modeling. This study proposes a hybrid collision assessment framework that combines Monte Carlo simulation, spline-based refinement of the time of closest approach (TCA), and a multi-stage deterministic refinement process. The methodology begins with probabilistic sampling of TLE uncertainties, followed by a coarse search for TCA using the SGP4 propagator. A cubic spline interpolation then enhances temporal resolution, and a hierarchical multi-stage refinement computes the final TCA and minimum distance with sub-second and sub-kilometer accuracy. The framework was validated using real-world TLE data from over 2600 debris objects and active satellites. Results demonstrated a reduction in average TCA error to 0.081 s and distance estimation error to 0.688 km. The approach is computationally efficient, with average processing times below one minute per conjunction event using standard hardware. Its compatibility with operational space situational awareness (SSA) systems and scalability for high-volume screening make it suitable for integration into real-time space traffic management workflows. Full article

Plastic (P) and microplastic (MP) pollution in marine and freshwater environments is an increasingly urgent issue that needs to be addressed at many levels. The Seabin (an easily operated and cost-effective floating debris collection device) can help clean up buoyant plastic debris in calm waters while monitoring water pollution. A Seabin was used to conduct a comparative analysis of plastic and microplastic concentrations in northern Lake Garda (Italy) during peak and low tourist seasons. The composition of the litter was further investigated using Fourier-Transform Infrared (FTIR) spectroscopy. The analysis showed a decreased mean amount of plastic from summer (32.5 mg/m³) to autumn (17.6 mg/m³), with an average number of collected microplastics per day of 45 ± 15 and 15 ± 3, respectively. Packaging and foam accounted for 92.2% of the recognized plastic waste products. The material composition of the plastic mass (442 pieces, 103.0 g) was mainly identified as polypropylene (PP, 47.1%) and polyethylene (PE, 21.8%). Moreover, 313 microplastics (approximately 2.0 g) were counted with average weight in the range of 1–16 mg. A case study of selected plastic debris was also conducted. Spectroscopic, microscopic, and thermal analysis of specimens provided insights into how aging affects plastics in this specific environment. The purpose of this study was to establish a baseline for further research on the topic, to provide guidelines for similar analyses from a multidisciplinary perspective, to monitor plastic pollution in Lake Garda, and to inform policy makers, scientists, and the public. Full article

This study evaluated the efficacy of various cleaning protocols on two nickel–titanium (NiTi) file systems—RaCe EVO(RE) and EdgeFile X7(EE)—using scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX). Eighty-four NiTi files (42RE, 42EE) were divided into seven groups (n = 12), including a group with unused, sterilized files and a group of used files without cleaning. The remaining files were subjected to simulated clinical use, followed by different cleaning methods, such as soaking in sodium hypochlorite (NaOCl), ethanol wiping (with or without magnification), enzymatic spray, and enzymatic solution. SEM images were imported into ImageJ to quantify surface changes, while EDX assessed elemental composition. The p-value was set to ≤0.05 for significance. Apart from the unused files, calcium and phosphorus—indicators of dentin debris—were present in all groups, especially those cleaned with enzymatic spray (p ≤ 0.0001). Their percentage in RE files soaked in NaOCl or wiped with ethanol was statistically lower than the positive control (p ≤ 0.0001). Post-use, all files showed significantly higher surface asymmetry in Groups 2 and 6 (p = 0.001). Cleaning efficacy depends on the type of NiTi file. RE files responded well to both wiping and soaking, while EE required soaking for effective debris removal. Enzymatic spray was ineffective. Full article

This study addresses real-world scenarios such as impacts from hailstones, gravel, or external debris, where multiple simultaneous impacts occur on composite structures. The effects of multiple impacts are analyzed in terms of time lag between impacts, energy levels, and the relative positions of the impacts. Quasi-simultaneous impacts with varying energies are performed, and their results are compared in terms of energy dissipation, delaminated area, and material response. It is observed that, beyond a certain distance between impacts, two simultaneous impacts become equivalent to two mono-impacts. Additionally, a specific energy threshold per projectile exists beyond which the effect of multiple impacts becomes negligible. The findings highlight that the parameter time interval between impacts is the most significant factor in multi-impact studies, unlike in mono-impact scenarios where this parameter does not exist. The study underscores the importance of impact energy, the number of simultaneous impacts and their positions in the evolution of delamination and damage in composite materials. This article provides experimental data on simultaneous multi-impacts that researchers could use to validate their models using a high-complexity problem. Full article