Search Results (4,876)

In traditional scallion cultivation, the bare-root transplanting method—which involves direct seeding, seedling raising in the field, and lifting—is commonly adopted to minimize seedling production costs. However, during the mechanized transplanting of bare-root scallion seedlings, practical problems such as severe seedling damage and poor planting uprightness exist. In this paper, the Hertz–Mindlin with Bonding contact model was used to establish the scallion seedling model. Combined with the Plackett–Burman experiment, steepest ascent experiment, and Box–Behnken experiment, the bonding parameters of scallion seedlings were calibrated. Furthermore, the accuracy of the scallion seedling model parameters was verified through the stress–strain characteristics observed during the actual loading and compression process of the scallion seedlings. The results indicate that the scallion seedling normal/tangential contact stiffness, scallion seedling normal/tangential ultimate stress, and scallion Poisson’s ratio significantly influence the mechanical properties of scallion seedlings. Through optimization experiments, the optimal combination of the above parameters was determined to be 4.84 × 10⁹ N/m, 5.64 × 10⁷ Pa, and 0.38. In this paper, the flexible planting components of scallion seedlings were taken as the research object. Flexible protrusions were added to the planting disc to reduce the damage rate of scallion seedlings, and an EDEM-ADAMS coupling interaction model between the planting components and scallion seedlings was established. Based on this model, optimization and verification were carried out on the key components of the planting components. Orthogonal experiments were conducted with the contact area between scallion seedlings and the disc, rotational speed of the flexible disc, furrow depth, and clamping force on scallion seedlings as experimental factors, and with the uprightness and damage status of scallion seedlings as evaluation criteria. The experimental results showed that when the contact area between scallion seedlings and the disc was 255 mm², the angular velocity was 0.278 rad/s, and the furrow depth was 102.15 mm, the performance of the scallion planting mechanism was optimal. At this point, the uprightness of the scallion seedlings was 94.80% and the damage rate was 3%. Field experiments were carried out based on the above parameters. The results indicated that the average uprightness of transplanted scallion seedlings was 93.86% and the damage rate was 2.76%, with an error of less than 2% compared with the simulation prediction values. Therefore, the parameter model constructed in this paper is reliable and effective, and the designed and improved transplanting mechanism can realize the upright and low-damage planting of scallion seedlings, providing a reference for the low-damage and high-uprightness transplanting operation of scallions. Full article

The binary anomaly detection (classification) of ionospheric data related to Very Low Frequency (VLF) signal amplitude in prior research demonstrated the potential for development and further advancement. Further data quality improvement is integral for advancing the development of machine learning (ML)-based ionospheric data (VLF signal amplitude) anomaly detection. This paper presents the transition from binary to multi-class classification of ionospheric signal amplitude datasets. The dataset comprises 19 transmitter–receiver pairs and 383,041 manually labeled amplitude instances. The target variable was reclassified from a binary classification (normal and anomalous data points) to a six-class classification that distinguishes between daytime undisturbed signals, nighttime signals, solar flare effects, instrument errors, instrumental noise, and outlier data points. Furthermore, in addition to the dataset, we developed a freely accessible web-based tool designed to facilitate the conversion of MATLAB data files to TRAINSET-compatible formats, thereby establishing a completely free and open data pipeline from the WALDO world data repository to data labeling software. This novel dataset facilitates further research in ionospheric signal amplitude anomaly detection, concentrating on effective and efficient anomaly detection in ionospheric signal amplitude data. The potential outcomes of employing anomaly detection techniques on ionospheric signal amplitude data may be extended to other space weather parameters in the future, such as ELF/LF datasets and other relevant datasets. Full article

Advancements in remote sensing technology have enabled the acquisition of high spatial and radiometric resolution imagery, offering abundant and reliable data sources for forest fire monitoring. In order to explore the ability of Sustainable Development Science Satellite 1 (SDGSAT-1) in wildfire monitoring, a systematic and comprehensive study was proposed on smoke detection during the wildfire early warning phase, fire point identification during the fire occurrence, and burned area delineation after the wildfire. The smoke detection effect of SDGSAT-1 was analyzed by machine learning and the discriminating potential of SDGSAT-1 burned area was discussed by Mid-Infrared Burn Index (MIRBI) and Normalized Burn Ratio 2 (NBR2). In addition, compared with Sentinel-2, the fixed-threshold method and the two-channel fixed-threshold plus contextual approach are further used to demonstrate the performance of SDGSAT-1 in fire point identification. The results show that the average accuracy of SDGSAT-1 fire burned area recognition is 90.21%, and a clear fire boundary can be obtained. The average smoke detection precision is 81.72%, while the fire point accuracy is 97.40%, and the minimum identified fire area is 0.0009 km², which implies SDGSAT-1 offers significant advantages in the early detection and identification of small-scale fires, which is significant in fire emergency and disposal. The performance of fire point detection is superior to that of Sentinel-2 and Landsat 8. SDGSAT-1 demonstrates great potential in monitoring the entire process of wildfire occurrence, development, and evolution. With its higher-resolution satellite imagery, it has become an important data source for monitoring in the field of remote sensing. Full article

Although significant progress has been made in the global medical level, cardiovascular diseases still pose a serious threat to human life and health. Among many cardiovascular diseases, acute myocardial infarction (AMI) is particularly severe. If not treated in a timely manner, it may lead to serious consequences such as cardiac arrest and sudden death. Early diagnosis of myocardial infarction (MI) is an important means of preventing and controlling the mortality rate of AMI. Creatine kinase isoenzyme (CK-MB) is a key biomarker of MI. It rises rapidly within 2 h after myocardial injury, reaches its peak at 24 h, and returns to normal at 72 h. Furthermore, CK-MB has a high specificity in monitoring secondary MI. Therefore, the early, real-time, and accurate detection of CK-MB is of great significance for the prevention, diagnosis, and prognosis of AMI. Conventional CK-MB detection methods have problems such as false positive elevation, large blood sampling volume, long time consumption, and complex operation, making it difficult to meet the needs of point-of-care testing (POCT). Biosensor technology, with its low cost, high sensitivity, and portability, offers a promising solution for point-of-care CK-MB testing, thereby greatly aiding AMI diagnosis. Full article

Robot energy consumption is a prominent challenge in intelligent manufacturing and construction. Reducing energy consumption during robot trajectory execution is an urgent issue requiring immediate attention. In view of the shortcomings of traditional trajectory optimization methods, this paper proposes a multi-objective trajectory optimization method that combines energy consumption mapping with the NSGA-II, aiming to reduce robots’ trajectory energy consumption and optimize execution efficiency. By establishing a dynamic energy consumption model, energy consumption mapping is employed to constrain energy consumption within the robot’s workspace, thereby providing guidance for the optimization process. Simultaneously, with energy consumption minimization and time consumption as optimization objectives, the NSGA-II is utilized to obtain the Pareto-optimal solution set through non-dominated sorting and congestion distance calculation. Energy consumption mapping serves as a dynamic feedback mechanism during the optimization process, guiding the distribution of trajectory points towards low-energy-consumption regions, accelerating algorithm convergence, and enhancing the quality of the solution set. The experimental results demonstrate that the proposed method can significantly reduce robots’ trajectory energy consumption and achieve an effective balance between energy consumption and time consumption. Compared with the conventional NSGA-II normalized weighted function method in similar task scenarios, the robot can save 14.87% and 10.47% of its energy consumption, respectively. Compared with traditional methods, this method exhibits superior energy-saving performance and adaptability in complex task environments, providing a novel solution for the efficient trajectory planning of robots. Full article

The accuracy of phase unwrapping is a decisive factor in achieving high-precision dimensional measurement using the projected fringe profilometry. However, discontinuities at truncation points inevitably lead to phase jumps, especially when measuring objects with complex hollow features, resulting in significantly increased errors. To address this issue, this paper proposes an adaptive phase correction algorithm based on row and column constraints. First, the algorithm identifies the main normal phase distribution region in each column and interpolates abnormal values deviating from this region, ensuring smooth phase distribution in the column direction. Then, it detects each continuous non-zero segment in every row, locates phase jump positions, and performs local corrections. This approach enhances the overall continuity of the phase map and effectively compensates for phase jump errors. Experimental results demonstrate that the proposed method can effectively suppress phase jumps caused by object edges and hollow regions, achieving an absolute error of less than 0.05 mm in measured step height differences in standard blocks. This provides a reliable phase preprocessing solution for the optical measurement of complex-shaped objects. Full article

Background/Objectives: Developing high-performance artificial intelligence (AI) models for rare diseases like malignant bone tumors is limited by scarce annotated data. This study evaluates same-modality cross-domain transfer learning by comparing an AI model pretrained on chest radiographs with a model trained from scratch for detecting malignant bone tumors on knee radiographs. Methods: Two YOLOv5-based detectors differed only in initialization (transfer vs. scratch). Both were trained/validated on institutional data and tested on an independent external set of 743 radiographs (268 malignant, 475 normal). The primary outcome was AUC; prespecified operating points were high-sensitivity (≥0.90), high-specificity (≥0.90), and Youden-optimal. Secondary analyses included PR/F1, calibration (Brier, slope), and decision curve analysis (DCA). Results: AUC was similar (YOLO-TL 0.954 [95% CI 0.937–0.970] vs. YOLO-SC 0.961 [0.948–0.973]; DeLong p = 0.53). At the high-sensitivity point (both sensitivity = 0.903), YOLO-TL achieved higher specificity (0.903 vs. 0.867; McNemar p = 0.037) and PPV (0.840 vs. 0.793; bootstrap p = 0.030), reducing ~17 false positives among 475 negatives. At the high-specificity point (~0.902–0.903 for both), YOLO-TL showed higher sensitivity (0.798 vs. 0.764; p = 0.0077). At the Youden-optimal point, sensitivity favored YOLO-TL (0.914 vs. 0.892; p = 0.041) with a non-significant specificity difference. Conclusions: Transfer learning may not improve overall AUC but can enhance practical performance at clinically crucial thresholds. By maintaining high detection rates while reducing false positives, the transfer learning model offers superior clinical utility. Same-modality cross-domain transfer learning is an efficient strategy for developing robust AI systems for rare diseases, supporting tools more readily acceptable in real-world screening workflows. Full article

This study examines the efficiency trade-offs of Controllable Pitch Propeller (CPP) systems by comparing Combination and Fixed operation modes using real ship operational data. The analysis focuses on mechanical efficiency (η_mech), propulsive efficiency expressed through the normalized Relative Propulsive Efficiency Index (RPEI_norm), and fuel consumption. Combination mode consistently maintained higher η_mech across all load conditions, with pronounced advantages at low load and low speed (<50% load, <12 knots), where both propulsive efficiency and fuel economy improved. In contrast, Fixed mode outperformed Combination mode at high load and high speed, exceeding approximately 50% load and 12 knots, as propeller performance approached its optimal operating point despite some sacrifice in engine efficiency. To integrate these effects, a proxy overall efficiency index (η_{overall,proxy} = η_mech × RPEI_norm) was introduced, revealing a crossover point at 0.525 load where the efficiency dominance shifted between modes. These findings demonstrate that neither mode is universally superior, but rather their advantages depend on operating conditions. The results provide practical insights for adaptive operational strategies, enabling real-time switching between modes to optimize fuel consumption and overall propulsion performance while supporting compliance with environmental regulations. Full article

Aiming at the problems of feature matching difficulty and limited extension application in the existing pixel offset tracking method for large-gradient landslides, this paper proposes an improved pixel offset tracking method based on corner point variation. Taking the Jinshajiang Baige landslide as the research object, the method’s effectiveness is verified using sentinel data. Through a series of experiments, the results show that (1) the use of VV (Vertical-Vertical) and VH (Vertical-Horizontal) polarisation information combined with the mean value calculation method can improve the accuracy and credibility of the circling of the landslide monitoring range, make up for the limitations of the single polarisation information, and capture the landslide range more comprehensively, which provides essential information for landslide monitoring. (2) The choice of scale factor has an essential influence on the results of corner detection, in which the best corner effect is obtained when the scale factor R is 2, which provides an essential reference basis for practical application. (3) By comparing traditional normalized and adaptive window cross-correlation methods with the proposed approach in calculating landslide offset distances, the proposed method shows superior matching accuracy and sliding direction estimation. (4) Analysis of pixels P1, P2, and P3 confirms the method’s high accuracy and reliability in landslide displacement assessment, demonstrating its advantage in tracking pixel offsets in large-gradient scenarios. Therefore, the proposed method offers an effective solution for large-gradient landslide monitoring, overcoming limitations of feature matching and limited applicability. It is expected to provide more reliable technical support for geological disaster management. Full article

Bus voltage regulation and accurate power sharing constitute two pivotal control objectives in DC microgrids. The conventional droop control method inherently suffers from steady-state voltage deviation. Centralized control introduces vulnerability to single-point failures, with significantly degraded stability under abnormal operating conditions. Distributed control strategies mitigate this vulnerability but require careful balancing between control effectiveness and communication costs. Therefore, this paper proposes a hybrid hierarchical control architecture integrating multiple control strategies to achieve near-zero steady-state deviation voltage regulation and precise power sharing in DC microgrids. Capitalizing on the complementary advantages of different control methods, an operation-condition-adaptive hierarchical control (OCAHC) strategy is proposed. The proposed method improves reliability over centralized control under communication failures, and achieves better performance than distributed control under normal conditions. With a fault-detection logic module, the OCAHC framework enables automatic switching to maintain high control performance across different operating scenarios. For the inherent trade-off between consensus algorithm performance and communication costs, a communication topology optimization model is established with communication cost as the objective, subject to constraints including communication intensity, algorithm convergence under both normal and N-1 conditions, and control performance requirements. An accelerated optimization approach employing node-degree computation and equivalent topology reduction is proposed to enhance computational efficiency. Finally, case studies on a DC microgrid with five DGs verify the effectiveness of the proposed model and methods. Full article

Background: Systemic therapy for soft tissue sarcoma (STS) provides modest survival benefit but carries clinically relevant toxicity. Published trials report adverse events (AEs) of varying quality and extension. Poor toxicity reporting hampers balanced risk–benefit appraisal. Methods: A PRISMA-2020 systematic review was registered in PROSPERO CRD420251087366. PubMed, CENTRAL, and Google Scholar were searched from 16 December 2024 to 16 April 2025 for randomized controlled trials (RCTs) evaluating chemotherapy, kinase inhibitors, or immune checkpoint inhibitors in STS. AE terms were harmonized to CTCAE v5.0; event rates were normalized to patients evaluable for safety. Pooled proportions used DerSimonian–Laird random-effects models; between-group comparisons employed unpaired t-tests. Risk of bias (RoB 2) was assessed with the Cochrane RoB 2 tool. Results: Ten RCTs (1079 treated, 979 control patients; 1994–2024) met the inclusion criteria, although two lacked sufficient presentation of toxicity data and seven failed to report parallel control-arm AEs. Pooled normalized incidences for treated patients were as follows: grade ≥ 3 hematological AEs, 17% (95% CI 14–20); severe gastrointestinal AEs, 9% (8–11); and grade 4 AEs, ≤6%. Anthracycline-based and kinase-inhibitor regimens displayed comparable composite grade ≥ 3 burdens (58% vs. 84%, p = 0.64). Between-study heterogeneity was considerable for gastrointestinal and hematological events (I² > 60%), driven by differing AE scales and denominators. Late-effect toxicities (cardiac, hepatic, neurological, and nephrological) were rarely reported, occurring in <1% of the patients. Across the three RCTs with control-arm data, experimental therapy increased common grade 3 AEs by 4–12 percentage points (p = 0.001). RoB 2 flagged serious concerns in 4/10 trials. Conclusions: Severe AEs in STS systemic therapy are moderately frequent; while the toxicity spectrum differs across drug classes (e.g., hematological for anthracyclines vs. neuropathic or fatigue-related for agents such as eribulin), the aggregate burden of severe AEs has not been lower for newer agents. Confidence in these estimates is limited by incomplete and non-standardized AE reporting. Future sarcoma trials must adopt CTCAE v5.0, specify explicit safety denominators, and publish full AE matrices to enable high-certainty risk–benefit assessment. Full article

The lossof ear tags in breeding pigs can lead to the loss or confusion of individual identity information. Timely and accurate detection, along with continuous tracking of breeding pigs that have lost their ear tags, is crucial for improving the precision of farm management. However, considering the real-time requirements for the detection of ear tag-lost breeding pigs, coupled with tracking challenges such as similar appearances, clustered occlusion, and rapid movements of breeding pigs, this paper proposed a dual-view synergistic method for detecting ear tag-lost breeding pigs and tracking individuals. First, a lightweight ear tag loss detector was developed by combining the Cascade-TagLossDetector with a channel pruning algorithm. Second, a synergistic architecture was designed that integrates a localized top-down view with a panoramic oblique view, where the detection results of ear tag-lost breeding pigs from the localized top-down view were mapped to the panoramic oblique view for precise localization. Finally, an enhanced tracker incorporating Motion Attention was proposed to continuously track the localized ear tag-lost breeding pigs. Experimental results indicated that, during the ear tag loss detection stage for breeding pigs, the pruned detector achieved a mean average precision of 94.03% for bounding box detection and 90.16% for instance segmentation, with a parameter count of 28.04 million and a detection speed of 37.71 fps. Compared to the unpruned model, the parameter count was reduced by 20.93 million, and the detection speed increased by 12.38 fps while maintaining detection accuracy. In the tracking stage, the success rate, normalized precision, and precision of the proposed tracker reached 86.91%, 92.68%, and 89.74%, respectively, representing improvements of 4.39, 3.22, and 4.77 percentage points, respectively, compared to the baseline model. These results validated the advantages of the proposed method in terms of detection timeliness, tracking continuity, and feasibility of deployment on edge devices, providing significant reference value for managing livestock identity in breeding farms. Full article

The integration of a large number of distributed generation (DG) units has altered the grid structure and fault characteristics of distribution networks, posing significant challenges to conventional protection methods. To address this, this paper proposes an adaptive current differential protection method based on comparing the similarity of current waveforms at both ends of a line. After a fault occurs, the current waveforms at both ends of each line are first extracted and normalized. The Fréchet distance algorithm is then introduced to quantify the waveform similarity. Based on the calculated Fréchet distance, the restraint coefficient of the current differential protection is constructed and the protection criterion is improved. Finally, a logic function is derived from the improved criterion. A short-circuit fault within the section is identified when the sum of the logic functions across all sampling points exceeds 50% of the total number of sampling points. A simulation model built in PSCAD/EMTDC is used for validation. Simulation results demonstrate that the proposed method is unaffected by fault type, transition resistance, fault location, or DG grid-connected capacity, has low data synchronization requirements, and exhibits excellent reliability and selectivity. Full article

Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide. However, the spatial and temporal dynamics underlying its development remain poorly characterized. This study employs spatial transcriptomics (ST) to investigate the progression of intestinal tumors in APC ^Min/+ mice across multiple time points. We identified distinct transcriptional profiles between tumor and normal tissues, resolving six major cell types through integrated dimensionality reduction and pathological annotation. Pseudo-time trajectory analysis revealed increased expression of MMP11 and MYL9 in later stages of tumor progression. Analysis of human CRC cohorts from the TCGA database further confirmed that high expression of these genes is associated with advanced clinical stages and promotes tumor proliferation and invasion. Temporal gene expression dynamics indicated enrichment of cancer-related pathways concurrent with suppression of lipid and amino acid metabolism. Notably, genes in the DEFA family were significantly upregulated in normal tissues compared to tumor tissues. Functional validation showed that DEFA3 inhibits colon cancer cell migration and proliferation in vitro. These demonstrate the value of ST in resolving spatiotemporal heterogeneity in CRC and identify both MMP11/MYL9 and DEFA3 as potential biomarkers and therapeutic targets. Full article

Ucuuba (Virola surinamensis) is a fruit of Amazonian origin with anti-inflammatory, nutritional, and phenolic substances. This study aimed to prepare and characterize the ucuuba co-product extract as well as to evaluate its antioxidant and cytotoxic activities, proximate composition, and water activity. For this purpose, the co-product and its extract were analyzed by Fourier-transform infrared (FTIR) spectroscopy, and their thermal behavior was investigated by thermogravimetry (TG). The ucuuba co-product extract was also evaluated for its contents of total polyphenols and flavonoids, antioxidant activity by the DPPH and ABTS assays, and cytotoxicity in normal J774.A1 macrophages by the MTT technique. The co-product proved to have important macronutrient contents from a nutritional point of view, i.e., 11.67 ± 0.731% fiber, 16.67 ± 0.36% lipids, 38.32 ± 0.19% proteins, and 30.56% carbohydrates, as well as low moisture content (6.73 ± 0.05%) and water activity (0.403). FTIR spectra showed characteristic absorption peaks of phenolic compounds. The ucuuba co-product (pressed seeds) and the extract obtained from the ucuuba seed co-product were stable at around 100 °C and showed two mass loss events typical of natural products. The extract contained total polyphenols and flavonoids amounting to 806.45 mg/100 g and 62 mg RE/100 g, respectively, and its antioxidant activity according to the DPPH and ABTS assays was 374.33 and 258.15 µM Trolox/g, respectively. Caffeic acid was identified as an abundant phenolic compound (5.17 µg/mL) by high-performance liquid chromatography (HPLC-DAD), and its quantification method was validated. Furthermore, there was no cytotoxicity in the macrophage cell line at concentrations up to 100 µg/mL. These results indicate that the ucuuba co-product could be reused to develop new functional and nutraceutical foods. Full article