Search Results (239)

Dichlorvos (DDVP) has been used in the management of agricultural pests for a long time. DDVP can cause DNA damage in mammals, and its residues in the environment and food have attracted attention. In this study, we reported a DDVP-degrading strain, Stenotrophomonas acidaminiphila G1, which could degrade DDVP to 20 mg/L with a DT₅₀ of 3.81 min at 37 °C, a pH of 7.0, and a concentration of 1.18 × 10¹⁰ colony-forming units (CFUs)/mL. Strain G1’s DDVP degradation products were determined by comparison with standard substances and UPLC-MS/MS analysis. The results showed that dimethyl phosphate (DMPP) was the main metabolite of DDVP, and its toxicity to non-target organisms was significantly lower than that of the parent compound. Furthermore, the key genes for the degradation of DDVP by strain G1 were analyzed using whole-genome sequencing. A methyl parathion hydrolase gene, mpd, was identified, and its activity was verified through prokaryotic expression and enzyme kinetics. The purified enzyme MPD could entirely degrade 20 mg/L DDVP within 1 min. These results not only provide biological resources for the rapid degradation of organophosphorus pesticides but also offer a theoretical basis for the efficient remediation of pesticide residues. Full article

This study addresses the core challenges of precise marigold corollas recognition and efficient continuous path planning under complex natural conditions (strong illumination, occlusion, adhesion) by proposing an integrated lightweight visual recognition and real-time path planning framework. We introduce MPD-YOLO, an optimized model based on YOLOv11n, incorporating (1) a Multi-scale Information Enhancement Module (MSEE) to boost feature extraction; (2) structured pruning for significant model compression (final size: 2.1 MB, 39.6% of original); and (3) knowledge distillation to recover accuracy loss post-pruning. The resulting model achieves high precision (P: 89.8%, mAP@0.5: 95.1%) with reduced computational load (3.2 GFLOPs) while demonstrating enhanced robustness in challenging scenarios—recall significantly increased by 6.8% versus YOLOv11n. Leveraging these recognition outputs, an adaptive ant colony algorithm featuring dynamic parameter adjustment and an improved pheromone strategy reduces average path planning time to 2.2 s—a 68.6% speedup over benchmark methods. This integrated approach significantly enhances perception accuracy and operational efficiency for automated marigold harvesting in unstructured environments, providing robust technical support for continuous automated operations. Full article

Marine plastic pollution has become a critical transboundary environmental issue, particularly affecting coastal regions with insufficient waste management infrastructure. This study applies a modified Lagrangian hydrodynamic model, TrackMPD v.1, to simulate the movement and accumulation of macroplastics in the West Africa Coastal Area. The research investigates three case studies: (1) the Liberia–Gulf of Guinea region, (2) the Mauritania–Gulf of Guinea coastal stretch, (3) the Cape Verde, Mauritania, and Senegal regions. Using both forward and backward simulations, macroplastics’ trajectories were tracked to identify key sources and accumulation hotspots. The findings highlight the cross-border nature of marine litter, with plastic debris transported far from its source due to ocean currents. The Gulf of Guinea emerges as a major accumulation zone, heavily impacted by plastic pollution originating from West African rivers. Interesting connections were found between velocities and directions of the plastic debris and some of the characteristics of the West African Monson climatic system (WAM) that dominates the area. Backward modelling reveals that macroplastics beached in Cape Verde largely originate from the Arguin Basin (Mauritania), an area influenced by fishing activities and offshore oil and gas operations. Results are visualized through point tracking, density, and beaching maps, providing insights into plastic distribution and accumulation patterns. The study underscores the need for regional cooperation and integrated monitoring approaches, including remote sensing and in situ surveys, to enhance mitigation strategies. Future work will explore 3D simulations, incorporating degradation processes, biofouling, and sinking dynamics to improve the representation of plastic behaviour in marine environments. This research is conducted within the Global Development Assistance (GDA) Agile Information Development (AID) Marine Environment and Blue Economy initiative, funded by the European Space Agency (ESA) in collaboration with the Asian. Development Bank and the World Bank. The outcomes provide actionable insights for policymakers, researchers, and environmental managers aiming to combat marine plastic pollution and safeguard marine biodiversity. Full article

Background: Large porous particles (LPPs) offer significant potential in drug delivery due to their porous structure and suitable particle size and shape, which can improve powder dispersibility and control drug release. Methods: In this study, sustained-release large porous microparticles of mannitol, PVA, and diclofenac sodium (MPDs) were developed using a spray drying technique. The influence of PVA co-spray drying and its concentration (0–40%) on the characteristics of the spray-dried particles was investigated. Results: Co-spray drying with PVA enhanced particle morphology, producing MPDs with a spherical shape and smooth surface, which minimized particle adhesion. This improvement correlated with a low Carr’s Index value (17.56%), indicating favorable particle dispersibility and aerosol performance. The large geometric diameter (>5 μm) of the MPDs, coupled with their low bulk density (<0.1 g/cm³), suggested potential for inhalation use. FTIR, XRD, and DSC analyses revealed that PVA altered the polymorphic form of mannitol, with the MPDs exhibiting a mixture of the α and δ forms. In vitro dissolution tests demonstrated that PVA co-spray drying effectively prolonged drug release, with the formulation containing 40% PVA (MPD-4) showing an optimal release profile. The release kinetics followed first-order Higuchi models, suggesting drug release occurred through a matrix diffusion mechanism facilitated by the porous structure. Conclusions: These findings demonstrate the feasibility of engineering large porous microparticles with tailored release characteristics and physicochemical properties suitable for further development in inhalable or other controlled-release dosage forms. Full article

This study investigates the deterioration of skid resistance and surface macrotexture following preventive maintenance using micro-milling techniques. Field data were collected from 31 asphalt pavement sections located across four climatic zones in Texas. The data encompasses a variety of surface types, milling depths, operational speeds, and drum configurations. A standardized data collection protocol was followed, with measurements taken before milling, immediately after treatment, and at 3, 6, 12, and 18 months post-treatment. Skid number and Mean Profile Depth (MPD) were used to evaluate surface friction and texture characteristics. The dataset was reformatted into a time-series structure with 930 observations, including contextual variables such as climatic zone, treatment parameters, and baseline surface condition. A comparative modeling framework was applied to predict the deterioration trends of both skid resistance and macrotexture over time. Eight regression models, including linear, tree-based, and ensemble methods, were evaluated alongside a time series Transformer model. The results show that the Transformer model achieved the highest prediction accuracy for skid resistance (R² = 0.981), while Random Forest performed best for macrotexture prediction (R² = 0.838). The findings indicate that the degradation of surface characteristics after preventive maintenance is non-linear and influenced by a combination of environmental and operational factors. This study demonstrates the effectiveness of data-driven modeling in supporting transportation agencies with pavement performance forecasting and maintenance planning. Full article

Phylogenetic diversity serves as a critical complement to traditional species diversity metrics. However, the performance variations among different computational models in simulating phylogenetic diversity within plant communities in the alpine grasslands of the Qinghai-Xizang Plateau remain insufficiently characterized. Here, we evaluated nine modeling approaches—random forest (RF), generalized boosting regression (GBR), multiple linear regression (MLR), artificial neural network (ANN), generalized linear regression (GLR), conditional inference tree (CIT), extreme gradient boosting (eXGB), support vector machine (SVM), and recursive regression tree (RRT)—for predicting three key phylogenetic diversity metrics [Faith’s phylogenetic diversity (PD), mean pairwise distance (MPD), mean nearest taxon distance (MNTD)] using climate variables and NDVImax. Our comprehensive analysis revealed distinct model performance patterns under grazing vs. fencing regimes. The eXGB algorithm demonstrated superior accuracy for fencing conditions, achieving the lowest relative bias (−0.08%) and RMSE (9.54) for MPD, along with optimal performance for MNTD (bias = 2.95%, RMSE = 44.86). Conversely, RF emerged as the most robust model for grazing scenarios, delivering the lowest bias (−1.63%) and RMSE (16.89) for MPD while maintaining strong predictive capability for MNTD (bias = −1.09%, RMSE = 27.59). Notably, scatterplot analysis revealed that only RF, GBR, and eXGB maintained symmetrical distributions along the 1:1 line, while other models showed problematic one-to-many value mappings or asymmetric patterns. These findings show that machine learning (especially RF and eXGB) enhances phylogenetic diversity predictions by integrating climate and NDVI data, though model performance varies by metric and management context. This study offers a framework for ecological forecasting, emphasizing multi-metric validation in biodiversity modeling. Full article

Background: A dilated main pancreatic duct (MPD) ≥ 5 mm can be observed in main-duct IPMNs (MD-IPMN) and chronic pancreatitis (CP); however, distinguishing between the two differently treated diseases can be difficult. Cell-free (cf) DNA in MPD fluid obtained by EUS-guided FNA might help to distinguish MD-IPMN from CP. Methods: All patients with a dilated MPD ≥ 5 mm on EUS during the period of 1 June 2017 to 30 April 2024 were prospectively analysed in this single-centre study, with EUS-guided MPD fluid aspiration performed for suspected MD-IPMN or CP in patients who were suitable for surgery. Twenty-two known gastrointestinal cancer genes, including GNAS and KRAS, were analysed by deep targeted (dt) NGS. The results were correlated with resected tissue, biopsy, and long-term follow-up. Results: A total of 164 patients with a dilated MPD were identified, of which 30 (18.3%) underwent EUS-guided FNA, with 1 patient having a minor complication (3.3%). Twenty-two patients (mean MPD diameter of 12.4 (7–31) mm) with a definitive, mostly surgically confirmed diagnosis were included in the analysis. Only a fish-mouth papilla, which was present in 3 of 12 (25%) MD-IPMNs, could reliably differentiate between the two diseases, with history, symptoms, diffuse or segmental MPD dilation, presence of calcifications on imaging, cytology, and CEA in the ductal fluid failing to achieve differentiation. However, GNAS mutations were found exclusively in 11 of the 12 (91.6%) patients with MD-IPMN (p < 0.01), whereas KRAS mutations were identified in both diseases. Conclusions: GNAS testing by dtNGS in aspirated fluid from dilated MPD obtained by EUS-guided FNA may help differentiate MD-IPMN from CP for surgical resection. Full article

Mammary Paget disease (MPD) is a rare cutaneous malignancy associated with underlying ductal carcinoma in situ (DCIS) or invasive ductal carcinoma (IDC). Clinically, it appears as eczematous changes in the nipple and areola complex (NAC), which may include itching, redness, crusting, and ulceration; these symptoms can sometimes mimic benign dermatologic conditions such as nipple eczema, making early diagnosis challenging. A 56-year-old woman presented with persistent erythema and scaling of the left nipple, which did not respond to conventional dermatologic treatments: a high degree of suspicion prompted further investigation. Reflectance confocal microscopy (RCM) revealed atypical, enlarged epidermal cells with irregular boundaries, while line-field confocal–optical coherence tomography (LC-OCT) demonstrated thickening of the epidermis, hypo-reflective vacuous spaces and abnormally large round cells (Paget cells). These non-invasive imaging findings were consistent with an aggressive case of Paget disease despite the absence of clear mammographic evidence of underlying carcinoma: in fact, several biopsies were needed, and at the end, massive surgery was necessary. Non-invasive imaging techniques, such as dermoscopy, RCM, and LC-OCT, offer a valuable diagnostic tool in detecting Paget disease, especially in early stages and atypical forms. Full article

Access to clean water is a pressing global concern and membrane technologies play a vital role in addressing this challenge. Thin-film composite membranes prepared via interfacial polymerization (IPol) using meta-phenylenediamine (MPD) and trimesoyl chloride (TMC) exhibit excellent separation performance, but face limitations such as fouling and low hydrophilicity. This study investigated the interaction between MPD and sulfonated zinc phthalocyanine, Zn(SO₂⁻)₄Pc, as a potential strategy for enhancing membrane properties. Using Density Functional Theory (DFT) and Time-Dependent DFT (TD-DFT), we analyzed the optimized geometries, electronic structures, UV–Vis absorption spectra, FT-IR vibrational spectra, and molecular electrostatic potentials of MPD, Zn(SO₂⁻)₄Pc, and their complexes. The results show that MPD/Zn(SO₂⁻)₄Pc exhibits reduced HOMO-LUMO energy gaps and enhanced charge delocalization, particularly in aqueous environments, indicating improved stability and reactivity. Spectroscopic features confirmed strong interactions via hydrogen bonding and π–π stacking, suggesting that Zn(SO₂⁻)₄Pc can act as a co-monomer or additive during IPol to improve polyamide membrane functionality. A conformational analysis of MPD/Zn(SO₂⁻)₄Pc was conducted using density functional theory (DFT) to evaluate the impact of dihedral rotation on molecular stability. The 120° conformation was identified as the most stable, due to favorable π–π interactions and intramolecular hydrogen bonding. These findings offer computational evidence for the design of high-performance membranes with enhanced antifouling, selectivity, and structural integrity for sustainable water treatment applications. Full article

This study investigates measurement methods for and the distribution characteristics of normal stress within tire–road contact areas. A novel measurement method, integrating 3D scanning technology with bearing area curve (BAC) analysis, is proposed. This method quantifies the rubber penetration depth and calculates contact stress based on rubber deformation. The key innovation of this method lies in this integrated methodology for high-precision stress mapping. In the spatial domain, stress distribution is characterized by the percentage of area occupied by different stress intervals, while in the frequency domain, stress levels are analyzed at various frequencies. The results demonstrate that as the Mean Profile Depth (MPD) of the road texture increases, the areas under stress greater than 1.0 MPa increase, while the areas under stress less than 0.8 MPa decrease. However, when the MPD exceeds 0.7 mm, this effect becomes less pronounced. Higher loads and harder rubber reduce the proportion of areas under lower stress and increase the proportion under higher stress. Low-frequency (<800 1/m) stress components increase with an MPD up to 0.7 mm, beyond which they exhibit diminished sensitivity. Stress at the same frequency is not significantly affected by load variation but increases markedly with increasing rubber hardness. This research provides crucial insights into contact stress distribution, establishing a foundation for analyzing road friction and optimizing surface texture design oriented towards high-friction pavements. Full article

Accurate detection of Jinxiu Malus fruits in unstructured orchard environments is hampered by frequent overlap, occlusion, and variable illumination. To address these challenges, we propose YOLOv8-MSP-PD (YOLOv8 with Multi-Scale Pyramid Fusion and Proportional Distance IoU), a lightweight model built on an enhanced YOLOv8 architecture. We replace the backbone with MobileNetV4, incorporating unified inverted bottleneck (UIB) modules and depth-wise separable convolutions for efficient feature extraction. We introduce a spatial pyramid pooling fast cross-stage partial connections (SPPFCSPC) module for multi-scale feature fusion and a modified proportional distance IoU (MPD-IoU) loss to optimize bounding-box regression. Finally, layer-adaptive magnitude pruning (LAMP) combined with knowledge distillation compresses the model while retaining performance. On our custom Jinxiu Malus dataset, YOLOv8-MSP-PD achieves a mean average precision (mAP) of 92.2% (1.6% gain over baseline), reduces floating-point operations (FLOPs) by 59.9%, and shrinks to 2.2 MB. Five-fold cross-validation confirms stability, and comparisons with Faster R-CNN and SSD demonstrate superior accuracy and efficiency. This work offers a practical vision solution for agricultural robots and guidance for lightweight detection in precision agriculture. Full article

Background and Aims: An appropriate surveillance system must be established to efficiently identify cases of intraductal papillary mucinous neoplasm (IPMN)-related malignant transformation. We analyzed the initial clinical background that affects long-term prognosis and narrowed the population for whom continued evaluation is inevitable. Methods: We included 1645 patients with IPMN treated at our hospital since 2010. We examined the types and timing of malignant transformation in terms of the worrisome features (WFs). The chi-squared test, log-rank test, and Cox proportional hazards model were used for the analysis (statistical significance at α = 0.05). Results: In total, 123 (7.5%) and 41 patients (2.5%) had IPMN-derived carcinoma (IPMN-DC) and concomitant pancreatic ductal adenocarcinoma (c-PDAC), respectively. Compared with IPMN-DC, a significantly higher proportion of c-PDAC patients were diagnosed with an advanced disease stage that developed earlier. The factors with significantly shorter time for IPMN-DC development were maximum cyst diameter (MCD) ≥ 30 mm, nonbranched type, main pancreatic duct (MPD) diameter ≥ 5 mm, and septal nodal structure (SNS) for IPMN-DC, and MCD ≥ 30 mm, main duct type, MPD ≥ 5 mm, SNS, cyst enlargement (≥2.5 mm/year), and abnormal CA19-9 levels for c-PDAC. Both groups could be significantly stratified by the number of WFs. A relative risk analysis revealed that SNS, MCD ≥ 30 mm, and MPD ≥ 5 mm were significant factors for IPMN-DC, whereas abnormal CA19-9 and SNS were significant for c-PDAC. Conversely, significantly more patients exhibiting these factors initially later developed IPMN-DC or c-PDAC. Conclusions: Ten percent of IPMN cases will develop IPMN-DC or c-PDAC, thereby requiring careful follow-up, especially in cases with SNS, abnormal CA19-9, and MCD ≥ 30 mm. Full article

Forests harbor most of the world’s terrestrial biodiversity; however, traditional conservation frameworks prioritize species richness over evolutionary diversity. Phylogenetic diversity (PD) reflects the complete evolutionary history contained within a community, offering a more comprehensive understanding of biodiversity. This review examines the theoretical foundations of PD, highlights methodological advancements in its assessment, and discusses its conservation applications in forest ecosystems. We discuss key metrics, including Faith’s PD, mean pairwise distance (MPD), mean nearest taxon distance (MNTD), and indices, including the net relatedness index (NRI) and nearest taxon index (NTI), as well as analytical tools (Picante, Phylocom, Biodiverse) and frameworks like the categorical analysis of neo- and paleo-endemism (CANAPE) and the evolutionarily distinct and globally endangered (EDGE) index, evaluating their effectiveness in identifying evolutionarily significant conservation areas. We examine global and regional forest PD patterns, including elevational and latitudinal gradients, using case studies from the Pan-Himalayan region, Tibetan Plateau, and northern Pakistan, along with the environmental and anthropogenic drivers, e.g., soil pH, precipitation, land-use change, and invasive species, and historical biogeographic forces that shape lineage diversification. We emphasize the need for data standardization, regional research expansion, and the inclusion of PD in national biodiversity strategies and global policy frameworks. This review highlights the transformative potential of shifting from species-centric to evolutionarily informed conservation, and provides a critical framework for enhancing the long-term resilience and adaptive capacity of forest ecosystems. Full article

Background/Objectives: Pancreatic ductal adenocarcinoma (PDAC) prediction in high-risk individuals is essential for early detection and improved outcome. While prior studies have utilized pancreatic radiomics for PDAC prediction, the added value of main pancreatic duct (MPD) features remains unclear. This study aims to assess the additional value of features of the main pancreatic duct (MPD) for predicting PDAC occurrence across different timeframes in advance. Methods: In total, 321 contrast-enhanced CT scans of the MPD and pancreas carried out across control, pre-diagnostic, and diagnostic cohorts were segmented, and radiomics were extracted. A support vector machine (SVM) classifier was used to classify the control and pre-diagnostic cohorts, with model performance assessed using area under the receiver operating characteristic (ROC) curves (AUCs) Results: The MPD diameter and volume significantly increased from the control to the pre-diagnostic and diagnostic CT scans (p < 0.05). The addition of features of the MPD to the pancreas improved the PDAC prediction AUC from 0.83 to 0.96 for subjects 6 months to 3 years in advance, from 0.81 to 0.94 for 3–6 years in advance, and 0.75 to 0.84 for 6–10 years in advance of diagnosis. Additionally, integrating MPD radiomics with diameter and volume significantly improved the AUC from 0.81 to 0.88 for subjects 6 months to 3 years in advance. Conclusions: Radiomic features from abdominal CT scans allow PDAC prediction up to 10 years in advance. Integrating MPD features, including diameter and volume, significantly improves PDAC prediction compared to using radiomics of the pancreas alone. Full article

In this study, the feasibility of using three-dimensional (3D) printing technology to investigate the impact of macrotexture and microtexture on the skid resistance of asphalt pavement was verified. The macrotexture characteristics of the five types of real asphalt mixtures were captured, reconstructed, and printed. The comparison analysis of the skid resistance between the pavement and printed specimens was conducted, and the correlations and contribution proportions of the macrotexture and microtexture on skid resistance were also calculated. Results show that five printed asphalt mixtures present good consistency in the microtexture with a roughness of about 100 nm. The impact of thin water film on the skid resistance is insignificant for real asphalt mixtures, while it is significant for printed mixtures. The printed specimens under dry conditions show a similar British pendulum number (BPN) with the real pavement specimens under wet conditions, while the BPN under wet conditions for printed specimens are much smaller than the real ones but follows a similar variation trend. Mean profile depth (MPD) values of four printed asphalt concrete (AC) mixtures are well linearly correlated with their BPN under dry and wet conditions, especially for wet conditions with the R² of 0.91. The contribution proportion of macrotexture to the skid resistance is nearly 90% for the dry condition and about 50% for the wet condition. Full article