Search Results (657)

High-throughput phenotypic acquisition and analysis allow us to accurately quantify trait expressions, which is essential for developing intelligent breeding strategies. However, there is still much potential to explore in the field of high-throughput phenotyping for edible fungi. In this study, we developed a portable multi-phenotypic acquisition system for Pleurotus eryngii using RGB and RGB-D cameras. We developed an innovative Unet-based semantic segmentation model by integrating the ASPP structure with the VGG16 architecture. This allows for precise segmentation of the cap, gills and stem of the fruiting body. By leveraging depth images from RGB-D cameras, we can effectively collect phenotypic information about Pleurotus eryngii. By combining K-means clustering with Lab color space thresholds, we are able to achieve more precise automatic classification of Pleurotus eryngii cap colors. Moreover, AlexNet is utilized to classify the shapes of the fruiting bodies. The Aspp-VGGUnet network demonstrates remarkable performance with a mean Intersection over Union (mIoU) of 96.47% and a mean pixel accuracy (mPA) of 98.53%. These results reflect respective improvements of 3.03% and 2.23% compared to the standard Unet model, respectively. The average error in size phenotype measurement is just 0.15 ± 0.03 cm. The accuracy for cap color classification reaches 91.04%, while fruiting body shape classification achieves 97.90%. The proposed multi-phenotype acquisition system reduces the measurement time per sample from an average of 76 s (manual method) to about 2 s, substantially increasing data acquisition throughput and providing robust support for scalable phenotyping workflows in breeding research. Full article

To address the low segmentation accuracy and high computational complexity of classical deep learning algorithms—caused by the complex morphology of Northern Corn Leaf Blight (NCLB) and blurred boundaries between diseased and healthy leaf regions—this study proposes an improved lightweight segmentation model (termed MSA-UNet) based on the UNet architecture, specifically tailored for NCLB segmentation. In MSA-UNet, three core modules are integrated synergistically to balance efficiency and accuracy: (1) MobileNetV3 (a mobile-optimized convolutional network) replaces the original UNet encoder to reduce parameters while enhancing fine-grained feature extraction; (2) an Enhanced Atrous Spatial Pyramid Pooling (E-ASPP) module is embedded in the bottleneck layer to capture multi-scale lesion features; and (3) the parameter-free Simple Attention Module (SimAM) is added to skip connections to strengthen focus on blurred lesion boundaries. Compared with the baseline UNet model, the proposed MSA-UNet achieves statistically significant performance improvements: mPA, mIoU, and F1-score increase by 3.59%, 5.32%, and 5.75%, respectively; moreover, it delivers substantial reductions in both computational complexity and parameter scale, with GFLOPs decreased by 394.50 G (an 87% reduction) and parameter count reduced by 16.71 M (a 67% reduction). These experimental results confirm that the proposed model markedly improves NCLB leaf lesion segmentation accuracy while retaining a lightweight architecture—rendering it better suited for practical agricultural applications that demand both efficiency and accuracy. Full article

Accurate soybean mapping is critical for food–oil security and cropping assessment, yet spatiotemporal heterogeneity arising from fragmented parcels and phenological variability reduces class separability and robustness. This study aims to deliver a high-resolution, reusable pipeline and quantify the marginal benefits of feature selection and architecture design. We built a full-season multi-temporal Sentinel-1/2 stack and derived candidate optical/SAR features (raw bands, vegetation indices, textures, and polarimetric terms). Jeffries–Matusita (JM) distance was used for feature–phase joint selection, producing four comparable feature sets. We propose a lightweight APM-UNet: an Attention Sandglass Layer (ASL) in the shallow path to enhance texture/boundary details, and a Parallel Vision Mamba layer (PVML with Mamba-SSM) in the middle/bottleneck to model long-range/global context with near-linear complexity. Under a unified preprocessing and training/evaluation protocol, the four feature sets were paired with U-Net, SegFormer, Vision-Mamba, and APM-UNet, yielding 16 controlled configurations. Results showed consistent gains from JM-guided selection across architectures; given the same features, APM-UNet systematically outperformed all baselines. The best setup (JM-selected composite features + APM-UNet) achieved PA 92.81%, OA 97.95, Kappa 0.9649, Recall 91.42%, IoU 0.7986, and F1 0.9324, improving PA and OA by ~7.5 and 6.2 percentage points over the corresponding full-feature counterpart. These findings demonstrate that JM-guided, phenology-aware features coupled with a lightweight local–global hybrid network effectively mitigate heterogeneity-induced uncertainty, improving boundary fidelity and overall consistency while maintaining efficiency, offering a potentially transferable framework for soybean mapping in complex agricultural landscapes. Full article

The premetastatic niche (PMN) represents a specialized microenvironment established in distant organs before the arrival of metastatic cells. This concept has fundamentally altered our understanding of cancer progression, shifting it from a random event-driven process to an orchestrated one. This review examines the critical role of extracellular proteases in PMN formation, focusing on matrix metalloproteinases (MMPs), serine proteases, and cysteine cathepsins that collectively orchestrate extracellular matrix remodeling, immune modulation, and vascular permeability changes essential for metastatic colonization. Key findings demonstrate that MMP9 and MMP2 facilitate basement membrane degradation and the recruitment of bone marrow-derived cells. At the same time, tissue inhibitor of metalloproteinase-1 (TIMP-1) promotes organ-specific hepatic PMN recruitment through neutrophil recruitment mechanisms. The plasminogen–plasmin system emerges as a master regulator through its broad-spectrum proteolytic activity and ability to activate downstream proteases, with S100A10-mediated plasmin generation providing mechanistic pathways for remote PMN conditioning. Neutrophil elastase and cathepsin G contribute to the degradation of anti-angiogenic proteins, thereby creating pro-metastatic microenvironments. These protease-mediated mechanisms represent the earliest interventional window in metastatic progression, offering therapeutic potential to prevent niche formation rather than treat established metastases. However, significant methodological challenges remain, including the need for organ-specific biomarkers, improved in vivo methods for measuring protease activity, and a better understanding of temporal PMN dynamics across different target organs. Full article

Origanum dubium, mainly grown in the Mediterranean region, is one of the less extensively studied species among the oregano class. Oregano species are recognized for their significant pharmaceutical properties, primarily attributed to carvacrol and other phenolic compounds. The goal of this study was to establish a sustainable method for the extraction of carvacrol, total phenolic, and total flavonoid compounds (TPC and TFC, respectively). Pulse-mode ultrasonic-assisted extraction (UPAE) was employed, using ethanol–water mixtures as green solvents, for the extraction of the bioactive compounds from the plant material. A Box–Behnken design (BBD) coupled with Response Surface Methodology (RSM) was applied to optimize the extraction process with respect to the extraction temperature, extraction time, ethanol-to-water ratio of the solvent and power amplitude of the ultrasonic processor. The responses of carvacrol (determined by HPLC-PDA), TPC, and TFC (determined by spectrometric methods) were evaluated by RSM. The statistical model identified the optimal extraction conditions, which were a combination of increased extraction temperature (70 °C) for 26 min with an intermediate ethanol–water ratio (60%) at the maximum processor’s power amplitude (100%). These conditions led to the optimal response of the three measured parameters. The optimized parameters represent a green and efficient approach to obtain bioactive-enriched extracts from Origanum dubium, suitable for potential applications in functional foods, preservatives, or other applications. Full article

The design of sustainable polymer systems with tunable properties is essential for next-generation functional materials. This study examines the influence of a phenol-free modified rosin resin (Unik Print™ 3340, UP)—a maleic anhydride- and fumaric acid-modified gum rosin—on the structural, thermal, rheological, and mechanical behavior of four poly(lactic acid) (PLA) grades with different molecular weights and crystallinity. Blends containing 3 phr of UP were prepared by melt compounding. Thermogravimetric analysis showed that the incorporation of UP did not alter the thermal degradation of PLA, confirming stability retention. In contrast, differential scanning calorimetry revealed that UP affected thermal transitions, suppressing crystallization and melting in amorphous PLA grades and shifting the crystallization temperature to lower values in semi-crystalline grades. The degree of crystallinity decreased for low-molecular-weight semi-crystalline PLA but slightly increased in higher-molecular-weight samples. Mechanical tests indicated that UP acted as a physical modifier, increasing toughness by over 25% for all PLA grades and up to 60% in the amorphous, low-molecular-weight grade. Rheological measurements revealed moderate viscosity variations, while FESEM analysis confirmed microstructural features consistent with improved ductility. Overall, UP resin enables fine tuning of the structure–property relationships of PLA without compromising stability, offering a sustainable route for developing bio-based polymer systems with enhanced mechanical performance and potential use in future biomimetic material designs. Full article

Background and Objective: Placenta Accreta Spectrum (PAS) encompasses a continuum of abnormal placentation conditions associated with significant maternal and fetal morbidity. Management of PAS requires coordinated cesarean hysterectomy. Associated morbidities include blood transfusion, coagulopathy, and intensive care unit (ICU) admission. Accurate prediction of ICU admission allows for enhanced multidisciplinary management, coordination of care and utilization of resources. Scoring systems exist in other surgical specialties that can predict the likelihood of ICU admission, but these have not been applied to an obstetric population. The SAS is a 10-point scale that has been validated for the prediction of ICU-level care requirements within 72 h post-operatively in numerous surgical specialties. The purpose of this study was to apply the Surgical APGAR Score (SAS, version 9) to patients undergoing management of PAS to determine if it can predict ICU admission in this population. Materials and Methods: This is a case–control study. We retrospectively analyzed 127 cases of pathology-confirmed PAS patients who underwent cesarean hysterectomy in singleton, non-anomalous, viable pregnancies. Our primary outcome was ICU admission. In addition, secondary outcomes included antepartum characteristics, operative time, intraoperative events as well as post-operative complications and total postoperative length of stay. SAS was assigned by extracting estimated blood loss (EBL), and the lowest mean intraoperative heartrate (HR and mean arterial pressure (MAP) from intraoperative documentation. Categorical and continuous factors were summarized using frequencies and percentages or means ± SD or median and range as appropriate. Pearson’s chi-square, Fisher’s exact tests, and Mann–Whitney U and t-tests were applied when appropriate. Logistical regression to assess the impact of SAS on ICU admission was performed. p-values < 0.05 were considered significant for two-tailed analysis. Statistical analysis was performed using Graphpad software (version 9). Results: Fifty-eight patients (45%) were admitted post-operatively to the ICU, while 69 patients (55%) were admitted for routine care to the post-anesthesia care unit. Baseline demographics were similar between groups. Forty-four patients (52%) admitted to the ICU had a SAS score < 4. SAS < 4 was associated with greater blood loss (3000 vs. 2500 mL, p = 0.03) and longer operative time (198 vs. 175 min, p = 0.03). Logistic regression analysis of SAS score and ICU admission revealed a low predictive value (OR 2.28, AUC = 0.599). Conclusions: The SAS system is a poor tool for the prediction of ICU admission in patients with PAS undergoing cesarean hysterectomy. A risk calculator that accounts for the unique physiologic changes in pregnancy and high risk for pregnancy is needed. Full article

Rice lodging is a major agricultural disaster that reduces yield and quality. Accurate lodging detection and causal analysis are essential for disaster mitigation and precision management. To overcome the limited coverage and low automation of conventional approaches, we propose MSR-LodfNet, an enhanced semantic-segmentation model driven by multi-scale remote-sensing imagery, enabling high-precision lodging mapping from regional to field scales. The study selected 13 state-owned farms in Jiansanjiang, Heilongjiang Province, and jointly used PlanetScope satellite images (3 m) and UAV images (0.2 m) to build an integrated workflow of “satellite macro-monitoring, UAV fine verification, and agronomic factor coupling analysis.” The model synergistically optimizes WFNet, DenseASPP multi-scale context enhancement, and Condensed Attention, markedly improving feature extraction and boundary recognition under multi-source imagery. Experimental results show that the model achieves mIoU 84.34% and mPA 93.31% on UAV images and mIoU 81.96% and mPA 90.63% on PlanetScope images, demonstrating excellent cross-scale adaptability and stability. Causal analysis shows that the high-EVI range is significantly positively correlated with lodging probability; its risk is about 6 times that of the low-EVI range, and the lodging probability of direct-seeded rice is about 2.56 times that of transplanted rice, indicating that it may be associated with a higher lodging risk. The results demonstrate that multi-scale remote sensing combined with agronomic parameters can effectively support the mechanism analysis of lodging disasters, providing a quantitative basis and technical reference for precision rice management and lodging-resistant breeding. Full article

The present study aimed to apply ultrasonic probe-assisted extraction (UPAE) using ethanol as a solvent to separate compounds from Stachys byzantina leaves. Experimental tests were carried out to investigate the influence of temperature (T) (30, 45 and 60 °C), ultrasonic amplitude (UA) (30, 60 and 90%) and extraction time (ET) (10, 15 and 20 min) on the extraction yield (EY). The extracts obtained at different extraction times were characterized for compound profile, soluble protein content, and antioxidant potential. The cytotoxic effect of the extract was also evaluated. The greatest mass recovery (19.8 wt%) was verified at the highest levels of the variables. The total phenolic compound content and antioxidant potential increased with the application of extraction times of 5 to 20 min, at 60 °C and UA of 90%. The extracts contained ~25 wt% of soluble protein. The extracts showed a predominance of chlorogenic, protocatechuic, and syringic acids. Nicotinic acid was also detected in the extracts, with levels ranging from 11.91 to 13.86 mg/100 g. The fatty acid profile indicated the presence of lauric, palmitic and linolenic acids in higher concentrations, with quantification of squalene, α-tocopherol and β-sitosterol. The ethanolic extract of Stachys byzantina showed no cytotoxic effect on HaCaT cells at concentrations up to 200 µg/mL, maintaining cell viability above 70% after 48 h of exposure. Full article

Substation equipment operating in harsh environments is highly susceptible to corrosion, yet conventional image segmentation methods often fail to achieve precise delineation of corroded regions. Here, we propose an enhanced TransU-Net-based approach for corrosion segmentation. Deformable convolution is incorporated into the encoder to strengthen the model’s capacity to represent irregular corrosion morphologies. A composite color–texture fusion module is developed to jointly exploit color information from HSV and Lab spaces together with multi-scale texture features. In addition, a Shape-IoU loss function is introduced to refine boundary fitting and improve contour accuracy. Experimental evaluations demonstrate that the proposed method consistently outperforms state-of-the-art models across multiple metrics, achieving an Intersection over Union (IoU) of 75.42% and a Recall (PA) of 83.14%. These results confirm that the model substantially enhances corrosion recognition accuracy and edge integrity under complex background conditions, offering a promising strategy for intelligent maintenance of substation infrastructure. Full article

The Yangtze River Basin, one of China’s most vital watersheds, sustains both ecological balance and human livelihoods through its extensive lake systems. However, since the 1980s, these lakes have experienced significant ecological degradation, particularly in terms of aquatic vegetation decline. To acquire reliable aquatic vegetation data during the peak growing season (July–September), when clear-sky conditions are scarce, we employed Chinese domestic satellite imagery—Gaofen-1/6 (GF-1/6) Wide Field of View (WFV) and Huanjing-2A/B (HJ-2A/B) Charge-Coupled Device (CCD)—with approximately one-day revisit frequency after constellation networking, 16 m spatial resolution, and excellent spectral consistency, in combination with deep learning algorithms, to monitor aquatic vegetation across the basin. Comparative experiments identified the near-infrared, red, and green bands as the most informative input features, with an optimal input size of 256 × 256. Through visual interpretation and dataset augmentation, we generated a total of 5016 labeled image pairs of this size. The U-Net++ model, equipped with an EfficientNet-B5 backbone, achieved robust performance with an mIoU of 90.16% and an mPA of 95.27% on the validation dataset. On independent test data, the model reached an mIoU of 79.10% and an mPA of 86.42%. Field-based assessment yielded an overall accuracy (OA) of 75.25%, confirming the reliability of the model. As a case study, the proposed model was applied to satellite imagery of Lake Taihu captured during the peak growing season of aquatic vegetation (July–September) from 2020 to 2025. Overall, this study introduces an automated classification approach for aquatic vegetation using 16 m resolution Chinese domestic satellite imagery and deep learning, providing a reliable framework for large-scale monitoring of aquatic vegetation across lakes in the Yangtze River Basin during their peak growth period. Full article

This paper addresses the critical challenge of automated lifting ratio detection for crane wire ropes, a key parameter for operational safety traditionally reliant on manual observation or sensor-based methods. We propose a novel SegFormer-based segmentation model enhanced with a decoder-integrated self-attention module, which significantly improves global contextual reasoning and spatial precision in complex industrial environments. Extensive evaluation on a dedicated multi-ratio dataset demonstrates that our method achieves 93.31% mIoU, 96.37% mPA, and 98.84% aAcc, outperforming strong baselines including SegFormer, U-Net, YOLOv11-seg, and RT-DETR. The model further exhibits notable robustness to noise, illumination changes, and occlusion, validating its practical applicability for real-world crane monitoring systems. Full article

This paper presents the design and experimental investigation of a multifunctional friction test bench, aiming to characterize the frictional and transmission efficiency of rope–drum systems in high-altitude wind power generation. The study addresses a critical gap in the experimental validation of key components for this demanding application. The test bench, comprising loading, power, test, and data acquisition modules, was designed to measure the equivalent friction coefficient (a comprehensive macro-parameter, not the traditional material friction coefficient) between an ultra-high-molecular-weight polyethylene (UHMWPE) fiber rope and a drum, as well as the transmission efficiency of pulleys. Key parameters, including contact angle, gasket material (steel vs. polyamide (PA)), groove type (U vs. V), and rotational speed, were systematically tested using tension and speed and torque sensors for data acquisition. Experimental results show that the equivalent friction coefficient initially increased and then decreased with the contact angle, reaching a maximum of approximately 0.15 at 100°. The coefficient was positively correlated with rotational speed, increasing by about 40% for steel and 10% for PA linings as speed rose from 25 to 100 rpm. Steel linings exhibited a significantly higher equivalent friction coefficient (0.14–0.17) than PA linings (0.10–0.13). Similarly, in transmission tests, steel pulleys demonstrated superior efficiency compared to PA pulleys, while V-grooves slightly reduced efficiency compared to U-grooves. Furthermore, pulley misalignment was found to decrease transmission efficiency. This work provides essential experimental data and a robust testing platform, laying a foundation for optimizing the efficiency and reliability of high-altitude wind energy systems. Full article

Background: Spontaneous ventilation with intubation (SVI) during video-assisted thoracoscopic surgery (VATS) has been introduced as a hybrid technique that combines the physiological benefits of spontaneous breathing with the safety of a secured airway. However, its application in patients with chronic obstructive pulmonary disease (COPD) remains controversial due to concerns about hypercapnia, hypoxemia, and dynamic hyperinflation. To date, no study has directly compared COPD and non-COPD patients undergoing VATS lobectomy under SVI using identical anesthetic and surgical protocols. Methods: A prospective observational study was conducted between January 2022 and December 2024 at a single tertiary thoracic surgery center. A total of 36 patients undergoing elective VATS lobectomy with SVI were included and divided into two groups: COPD (n = 17) and non-COPD (n = 19), based on GOLD criteria. All patients were intubated with a double-lumen tube and allowed to maintain spontaneous ventilation during one-lung ventilation (OLV) after recovery from neuromuscular blockade. Arterial blood gas (ABG) samples were collected at four predefined time points (T1–T4), and intraoperative respiratory parameters, hemodynamics, spontaneous ventilation time, and spontaneous ventilation fraction (SpVent%) were recorded. Postoperative outcomes, including ICU stay, complications, and conversion to controlled ventilation, were analyzed. Statistical comparisons were performed using t-test, Mann–Whitney U test, chi-square test, and ANCOVA with adjustment for age, sex, BMI, and FEV₁%. Results: All 36 procedures were successfully completed under SVI without conversion to controlled mechanical ventilation or thoracotomy. Baseline demographics were comparable between COPD and non-COPD patients regarding age (68.4 ± 6.9 vs. 67.8 ± 7.1 years; p = 0.78) and BMI (27.1 ± 4.6 vs. 26.3 ± 4.2 kg/m²; p = 0.56), while pulmonary function was significantly lower in COPD patients (FEV₁/FVC 53.8% (IQR 47.5–59.9) vs. 82.4% (78.5–85.2); p < 0.001). The duration of spontaneous ventilation was significantly longer in the COPD group (82 ± 14 min vs. 58 ± 16 min; p < 0.001), and remained significant after ANCOVA adjustment (β = +23.7 min; p = 0.001). The SpontVent% was higher in COPD patients (80% [70–90] vs. 60% [45–80]), showing a trend toward significance (p = 0.11). Intraoperative permissive hypercapnia was well tolerated: peak PaCO₂ levels at T3 were higher in COPD (52 ± 6 mmHg) than in non-COPD patients (47 ± 5 mmHg; p = 0.06), without pH dropping below 7.25 in either group. No significant differences were observed in mean arterial pressure, oxygen saturation, ICU stay (1.1 ± 0.4 vs. 1.0 ± 0.5 days; p = 0.48), or postoperative complication rates (p = 0.67). All patients were extubated in the operating room. Conclusions: Intubated spontaneous ventilation during VATS lobectomy is feasible and safe in both COPD and non-COPD patients when performed by experienced teams. COPD patients, despite impaired baseline lung function, were able to maintain spontaneous breathing for significantly longer periods without developing severe hypercapnia, acidosis, or hemodynamic instability. These findings suggest that SVI may represent a lung-protective alternative to fully controlled one-lung ventilation, particularly in hypercapnia-adapted COPD patients. Further multicenter studies are warranted to validate these results and define standardized thresholds for CO₂ tolerance, patient selection, and intraoperative monitoring during SVI. Full article

β-Glucosidases, ubiquitous enzymes with significant contribution to several industries were previously identified as diverse in bacterial metagenomes from Vietnamese native goat rumens, wood humus from Cuc Phuong national forest, and termite gut. In this study, we systematically analyzed their sequence diversity, domain architectures, domain arrangements, physicochemical properties, and producers associated with their structures, conserving catalytic domains. A total of 833 β-glucosidase sequences were categorized into three families: GH1, GH16, and GH3, forming 30 distinct domain architectures with variable isoelectric points, alkaline scores, and melting temperatures across ecological niches. GH1 enzymes exhibited the lowest architectural diversity, whereas GH16 enzymes were frequently associated with carbohydrate-binding module 4 (CBM4) and CBM12 domains. Over 90% of GH3 enzymes contained fibronectin type III (FN3) and accessory domains such as PA14, CBM6, Big_2, or ExoP, with some harboring secondary catalytic domains. Most goat rumen β-glucosidases originated from cellulosome-producing bacteria. A recombinant β-glucosidase GH3-31 expressed in E. coli exhibited optimal activity at 40 °C (lower than the predicted Tm of 49.8 °C), pH5.5 (near the predicted pI of 5.61), Km of 1.37 mM ± 0.08 mM, and Vmax of 43.17 ± 0.6 U/mg. Its activity was enhanced by Tween 20, Tween 80, Triton X-100, and CTAB. These findings provide a comprehensive resource for β-glucosidase engineering and application-oriented screening. Full article