Search Results (3,163)

This study explores the valorization of agro-industrial by-products—riceberry broken rice (RBR) and soybean meal (SBM)—as cost-effective substrates for enhancing exopolysaccharide (EPS) production by Bacillus tequilensis PS21. Eight Bacillus strains were screened, and B. tequilensis PS21 demonstrated the highest EPS yield (2.54 g/100 mL DW). The EPS displayed a strong antioxidant capacity with 65.5% DPPH and 80.5% hydroxyl radical scavenging, and a FRAP value of 6.51 mg Fe²⁺/g DW. Antimicrobial testing showed inhibition zones up to 10.07 mm against Streptococcus agalactiae and 7.83 mm against Staphylococcus aureus. Optimization using central composite design (CCD) and the response surface methodology (RSM) revealed the best production at 5% (w/v) RBR, 3% (w/v) SBM, pH 6.66, and 39.51 °C, yielding 39.82 g/L EPS. This EPS is a moderate-molecular-weight (11,282 Da) homopolysaccharide with glucose monomers. X-ray diffraction (XRD) showed an amorphous pattern, favorable for solubility in biological applications. Thermogravimetric analysis (TGA) demonstrated thermal stability up to ~250 °C, supporting its suitability for high-temperature processing. EPS also exhibited anticancer activity with IC₅₀ values of 226.60 µg/mL (MCF-7) and 224.30 µg/mL (HeLa) at 72 h, reduced colony formation, inhibited cell migration, and demonstrated anti-tyrosinase, anti-collagenase, and anti-elastase effects. This study demonstrates the successful valorization of agro-industrial by-products—RBR and SBM—for the high-yield production of multifunctional EPS with potent antioxidant, antimicrobial, and anticancer properties. The findings highlight the sustainable potential of these low-cost substrates in supporting the development of green and value-added bioproducts, with promising utilizations across the food, pharmaceutical, and cosmetic sectors. Full article

Non-small cell lung cancer (NSCLC) is a predominant form of lung cancer that is often diagnosed at an advanced metastatic stage. The processes of cancer cell migration and invasion involve epithelial-to-mesenchymal transition (EMT), which is crucial for metastasis. Targeting cancer aggressiveness with effective plant compounds has gained attention as a potential adjuvant therapy. Eurycomanone (ECN), a bioactive quassinoid found in the root of Eurycoma longifolia Jack, has demonstrated anti-cancer activity against various carcinoma cell lines, including human NSCLC cells. This study aimed to investigate the in vitro effects of ECN on the migration and invasion of human NSCLC cells and to elucidate the mechanisms by which ECN modulates the EMT in these cells. Non-toxic doses (≤IC20) of ECN were determined using the MTT assay on two human NSCLC cell lines: A549 and Calu-1. The results from wound healing and transwell migration assays indicated that ECN significantly suppressed the migration of both TGF-β1-induced A549 and Calu-1 cells. ECN exhibited a strong anti-invasive effect, as its non-toxic doses significantly suppressed the TGF-β1-induced invasion of NSCLC cells through Matrigel and decreased the secretion of MMP-2 from these cancer cells. Furthermore, ECN could affect the TGF-β1-induced EMT process in various ways in NSCLC cells. In TGF-β1-induced A549 cells, ECN significantly restored the expression of E-cadherin by inhibiting the Akt signaling pathway. Conversely, in Calu-1, ECN reduced the aggressive phenotype by decreasing the expression of the mesenchymal protein N-cadherin and inhibiting the TGF-β1/Smad pathway. In conclusion, this study demonstrated the anti-invasive activity of eurycomanone from E. longifolia Jack in human NSCLC cells and provided insights into its mechanism of action by suppressing the effects of TGF-β1 signaling on the EMT program. These findings offer scientific evidence to support the potential of ECN as an alternative therapy for metastatic NSCLC. Full article

By integrating EarthCARE W-band doppler cloud radar observations with GPM Ku/Ka-band dual-frequency precipitation radar data, this study constructs a novel global “pseudo tripe-frequency” radar coincidence dataset comprising 2886 coincidence events (about one-third of the events detected precipitation), aiming to systematically investigating band-dependent responses to cloud and precipitation structure. Results demonstrate that the W-band is highly sensitive to high-altitude cloud particles and snowfall (reflectivity < 0 dBZ), yet it experiences substantial signal attenuation under heavy precipitation conditions, and with low-altitude reflectivity reductions exceeding 50 dBZ, its probability density distribution is more widespread, with low-altitude peaks increasing first, and then decreasing as precipitation increases. In contrast, the Ku and Ka-band radars maintain relatively stable detection capabilities, with attenuation differences generally within 15 dBZ, but its probability density distribution exhibits multiple peaks. As the precipitation rate increases, the peak value of the dual-frequency ratio (Ka/W) gradually rises from approximately 10 dBZ to 20 dBZ, and can even reach up to 60 dBZ under heavy rainfall conditions. Several cases analyses reveal clear contrasts: In stratiform precipitation regions, W-band radar reflectivity is higher above the melting layer than below, whereas the opposite pattern is observed in the Ku and Ka bands. Doppler velocities exceeding 5 m s⁻¹ and precipitation rates surpassing 30 mm h⁻¹ exhibit strong positive correlations in convection-dominated regimes. Furthermore, the dataset confirms the impact of ice–water cloud phase interactions and terrain-induced precipitation variability, underscoring the complementary strengths of multi-frequency radar observations for capturing diverse precipitation processes. Full article

This article critically considers sample multigenerational oral traditions of Numic-speaking communities known as the Nüümü (Northern Paiute), Nuwu (Southern Paiute), and Newe (Western Shoshone), written down over the last 151 years. Utilizing the GOAT! phenomenological method to compare the onto-epistemologies of Numic peoples with a wide range of data from (G)eology, (O)ral traditions, (A)rchaeology and (A)nthropology, and (T)raditional knowledge, the author analyzed 824 multigenerational ancestral teachings. These descriptions encode multigenerational memories of potential geological, climatic, and ecological observations and interpretations of multiple locations and earth processes throughout the Numic Aboriginal homelands within California and the Great Basin. Through this layered and comparative analysis, the author identified potential convergences of oral traditions, ethnography, ethnohistory, rock art, and geological processes in the regions of California, the Great Basin, and the Colorado Plateau, indicative of large-scale earth changes, cognized by Numic Indigenous communities as earth birthing events, occurring during the Late Pleistocene/Early Holocene to Middle and Late Holocene, including the Late Dry Period, Medieval Climatic Anomaly, and Little Ice Age. Full article

Various data such as power grid sensors and manual observed icing, CMA (China Meteorological Administration) Land Surface Data Assimilation System (CLDAS) products, and the Fifth Generation Atmospheric Reanalysis of the Global Climate from Europe Center of Middle Range Weather Forecast (ERA5) are adopted to diagnose an icing process under a cold surge during 16–23 December 2023 in northeastern Yunnan Province. The results show that: (1) in the early stage of the process, mainly the freezing types, such as GG (temperature > 0 °C, relative humidity ≥ 75%) and DG (temperature < 0 °C, relative humidity ≥ 75%), occur. At the end of the process, an increase in icing type as GD (temperature > 0 °C, relative humidity < 75%) appears. (2) Significant differences exist in the elements during different stages of icing, and the atmospheric thermal, dynamic, and water vapor conditions are conducive to the occurrence of freezing rain during ice accretion. The main impact weather systems of this process include a strong high ridge in the mid to high latitudes of East Asia, transverse troughs in front of the high ridge south to Lake Baikal, low altitude troughs, and ground fronts. The transverse trough in front of the high ridge can cause cold air to accumulate and then move eastward and southward. The southerly flows, surface fronts, and other low-pressure systems can provide powerful thermodynamic and moisture conditions for ice accumulation. Full article

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer characterized by a dense desmoplastic stroma and a highly immunosuppressive tumor microenvironment (TME). The focal adhesion kinase (FAK), a non-receptor tyrosine kinase, is considered a critical regulator of various cellular processes involved in cancer development. FAK inhibitors (FAKi) have proven to be promising therapeutics for cancer treatment including for pancreatic cancer. As monotherapy, however, FAKi showed only a modest effect in clinical studies. In this study, we investigated the cytotoxicity of six FAKi (Defactinib, CEP-37440, VS-4718, VS-6062, Ifebemtinib and GSK2256098) used in clinical trials on five pancreatic tumor cell lines. We further examined whether their anti-tumor activity can be enhanced by combination with the oncolytic coxsackievirus B3 (CVB3) strain PD-H. IC₅₀ analyses identified Defactinib and CEP-37440 as the most potent inhibitors of tumor cell growth. VS-4718, VS-6062, and Ifebemtinib showed slightly lower activity, while GSK2256098 was largely ineffective. The combination of Defactinib, CEP-37440, VS-4718, and VS-6062 with PD-H resulted in varying effects on cytotoxicity, depending on the cell line and the specific FAKi, ranging from no enhancement to a pronounced increase. Using the Chou–Talalay method, we determined combination indices (CI), revealing synergistic, additive, but also antagonistic interactions between the respective FAKi and PD-H. Considering both oncolytic efficacy and the CI, the greatest enhancement in oncolytic activity was achieved when VS-4718 or CEP-37440 was combined with PD-H. These findings indicate that co-treatment with PD-H can potentiate the therapeutic activity of the selected FAKi and may represent a novel strategy to improve treatment outcomes in PDAC. Full article

Underwater explosion ice-breaking technology is critical for Arctic development and ice disaster prevention due to its high efficiency, yet it faces challenges in understanding the coupled dynamics of shock waves, pulsating bubbles, and heterogeneous ice fracture. This review synthesizes theoretical models, experimental studies, and numerical simulations investigating damage mechanisms. Key findings establish that shock waves initiate brittle fracture via stress superposition while bubble pulsation drives crack propagation through pressure oscillation; optimal ice fragmentation depends critically on charge weight, standoff distance, and ice thickness. However, significant limitations persist in modeling sea ice heterogeneity, experimental replication of polar conditions, and computational efficiency. Future advancements require multiscale fluid–structure interaction models integrating brine migration effects, enhanced experimental diagnostics for transient processes, and optimized numerical algorithms to enable reliable predictions for engineering applications. Full article

It is evident that a novel engineering solution is required in order to elevate a greater number of polluting cars into a higher category. There appears to be a paucity of direct interest in upgrading Euro 1, 2, 3, 4, and 5 vehicles to the highest possible level, primarily through software modifications of the parameters determining the performance of the internal combustion engine (ICE). The potential for advancement in this area is evidenced by the presence of systems that enhance environmental efficiency, even in Euro 2 vehicles. These include exhaust gas recirculation, catalytic converter, lambda sensor, electronic control fuel injection, and ignition timing. It is precisely these vehicles that are subject to optimization, a process which would allow the maximum service life of otherwise more reliable but older vehicles to be exploited. Full article

Annona neoinsignis H. Rainer (Annonaceae) is a tree native to the Amazon rainforest. Its fruits are also suitable for human consumption in their natural state or are processed to make desserts. In this work, we characterized the chemical composition of the essential oil (EO) from the leaves of A. neoinsignis and evaluated its anti-liver-cancer potential via in vitro and in vivo approaches. Chemical composition analysis revealed β-elemene, (E)-caryophyllene, germacrene D, and germacrene B as the main constituents. The EO had IC₅₀ values ranging from 12.28 to 37.50 μg/mL for B16-F10 cells and MCF-7 cells, whereas an IC₅₀ value of >50 μg/mL was found for noncancerous MRC-5 cells. DNA fragmentation, YO-PRO-1 staining, and loss of mitochondrial transmembrane potential were detected in EO-treated HepG2 cells, indicating the induction of apoptosis. Significant in vivo growth inhibition of 53.7% was observed in mice bearing HepG2 cell xenografts treated with EO at a dosage of 40 mg/kg. These data suggest that EO from A. neoinsignis leaves is a drug source for liver cancer. Full article

To investigate the slope instability caused by differential frost heaving mechanisms from the slope crest to the toe during frost heave processes, this study takes a typical silty clay slope in Xinjiang, China, as the research object. Through indoor triaxial consolidated undrained shear tests, eight sets of natural and frost-heaved specimens were prepared under confining pressure conditions ranging from 100 to 400 kPa. The geotechnical parameters of the soil in both natural and frost-heaved states were obtained, and a spatiotemporal thermo-hydro-mechanical coupled numerical model was established to reveal the dynamic evolution law of anchor rod axial forces and the frost heave response mechanism between the frame and slope soil. The analytical results indicate that (1) the frost heave process is influenced by slope boundaries, resulting in distinct spatial variations in the temperature field response across the slope surface—namely pronounced responses at the crest and toe but a weaker response in the mid-slope. (2) Under the coupled drive of the water potential gradient and gravitational potential gradient, the ice content in the toe area increases significantly, and the horizontal frost heave force exhibits exponential growth, reaching its peak value of 92 kPa at the toe in February. (3) During soil freezing, the reverse stress field generated by soil arching shows consistent temporal variation trends with the temperature field. Along the height of the soil arch, the intensity of the reverse frost heave force field displays a nonlinear distribution characteristic of initial strengthening followed by attenuation. (4) By analyzing the changes in anchor rod axial forces during frost heaving, it was found that axial forces during the frost heave period are approximately 1.3 times those under natural conditions, confirming the frost heave period as the most critical condition for frame anchor design. Furthermore, through comparative analysis with 12 months of on-site anchor rod axial force monitoring data, the reliability and accuracy of the numerical simulation model were validated. These research outcomes provide a theoretical basis for the design of frame anchor support systems in seasonally frozen regions. Full article

The efficient synthetic routes and evaluates cytotoxic profiles of denitroaristolochic acids II–V (DAA-II–V) were demonstrated in this study. Based on retrosynthetic analysis, a modular synthetic strategy was developed through Suzuki–Miyaura coupling, Wittig reaction, and bismuth triflate-catalyzed intramolecular Friedel–Crafts cyclization to efficiently construct the phenanthrene core. Process optimization significantly improved yields: aryl bromide intermediate A reached 50.8% yield via bromination refinement, while arylboronic ester intermediate B overcame selectivity limitations. Combining Darzens condensation with Wittig reaction enhanced throughput, achieving 88.4% yield in the key cyclization. Structures were confirmed by NMR and mass spectra. CCK-8 cytotoxicity assays in human renal proximal tubular epithelial cells revealed distinct toxicological profiles: DAA-III and DAA-IV exhibited IC₅₀ values of 371 μM and 515 μM, respectively, significantly higher than the nitro-containing prototype AA-I (270 μM), indicating that the absence of nitro group attenuates but does not eliminate toxicity, potentially via altered metabolic activation. DAA-II and DAA-V showed no detectable cytotoxicity within assay limits, suggesting reduced toxicological impact. Structure–activity analysis exhibited that the nitro group is not essential for cytotoxicity, with methoxy substituents exerting limited influence on potency. This challenges the conventional DNA adduct-dependent toxicity paradigm, implying alternative mechanisms like oxidative stress or mitochondrial dysfunction may mediate damage in denitro derivatives. These systematic findings provide new perspectives for AA analog research and a foundation for the rational use and safety assessment of Aristolochiaceae plants. Full article

A methodology for detecting systematic errors in sets of equally accurate, uncorrelated, aggregate measurements is proposed and applied within the automatic real-time dispatch control system of a copper concentrator plant (CCP) to refine the technical and economic performance indicators (EPIs) computed by the system. This work addresses and solves the problem of selecting and obtaining reliable measurement data by exploiting the redundant measurements of process streams together with the balance equations linking those streams. This study formulates an approach for integrating cloud technologies, machine learning methods, and forecasting into information control systems (ICSs) via predictive analytics to optimize CCP production processes. A method for combining the hybrid cloud infrastructure with an LSTM-DNN neural network model has been developed, yielding a marked improvement in TEP for copper concentration operations. The forecasting accuracy for the key process parameters rose from 75% to 95%. Predictive control reduced energy consumption by 10% through more efficient resource use, while the copper losses to tailings fell by 15–20% thanks to optimized reagent dosing and the stabilization of the flotation process. Equipment failure prediction cut the amount of unplanned downtime by 30%. As a result, the control system became adaptive, automatically correcting the parameters in real time and lessening the reliance on operator decisions. The architectural model of an ICS for metallurgical production based on the hybrid cloud and the LSTM-DNN model was devised to enhance forecasting accuracy and optimize the EPIs of the CCP. The proposed model was experimentally evaluated against alternative neural network architectures (DNN, GRU, Transformer, and Hybrid_NN_TD_AIST). The results demonstrated the superiority of the LSTM-DNN in forecasting accuracy (92.4%), noise robustness (0.89), and a minimal root-mean-square error (RMSE = 0.079). The model shows a strong capability to handle multidimensional, non-stationary time series and to perform adaptive measurement correction in real time. Full article

Aircraft wing icing significantly threatens aviation safety, causing substantial losses to the aviation industry each year. High transparency and blurred edges of icing areas in wing images pose challenges to wing icing detection by machine vision. To address these challenges, this study proposes a detection model, Wing Icing Detection DeeplabV3+ (WID-DeeplabV3+), for efficient and precise aircraft wing leading edge icing detection under natural lighting conditions. WID-DeeplabV3+ adopts the lightweight MobileNetV3 as its backbone network to enhance the extraction of edge features in icing areas. Ghost Convolution and Atrous Spatial Pyramid Pooling modules are incorporated to reduce model parameters and computational complexity. The model is optimized using the transfer learning method, where pre-trained weights are utilized to accelerate convergence and enhance performance. Experimental results show WID-DeepLabV3+ segments the icing edge at 1920 × 1080 within 0.03 s. The model achieves the accuracy of 97.15%, an IOU of 94.16%, a precision of 97%, and a recall of 96.96%, representing respective improvements of 1.83%, 3.55%, 1.79%, and 2.04% over DeeplabV3+. The number of parameters and computational complexity are reduced by 92% and 76%, respectively. With high accuracy, superior IOU, and fast inference speed, WID-DeeplabV3+ provides an effective solution for wing-icing detection. Full article

Aircraft icing and snow accumulation are significant threats to flight safety and operational efficiency, necessitating rapid and accurate detection methods. The aim of this study was to develop and comparatively evaluate artificial intelligence (AI) models for the real-time detection of ice and snow on aircraft surfaces using vision systems. A custom dataset of annotated aircraft images under various winter conditions was prepared and augmented to enhance model robustness. Two training approaches were implemented: an automatic process using the YOLOv8 framework on the Roboflow platform and a manual process in the Google Colab environment. Both models were evaluated using standard object detection metrics, including mean Average Precision (mAP) and mAP@50:95. The results demonstrate that both methods achieved comparable detection performance, with final mAP50 values of 0.25–0.3 and mAP50-95 values around 0.15. The manual approach yielded lower training losses and more stable metric progression, suggesting better generalization and a reduced risk of overfitting. The findings highlight the potential of AI-driven vision systems to support intelligent de-icing decision-making in aviation. Future research should focus on refining localization, minimizing false alarms, and adapting detection models to specific aircraft components to further enhance operational safety and reliability. Full article

Mars’ south polar cap hosts dynamic landforms known as Swiss cheese features (SCFs), which form through the sublimation of carbon dioxide (CO₂) ice driven by the planet’s extreme seasonal and diurnal solar insolation cycles. These shallow, rounded depressions—first identified by Mars Global Surveyor in 1999 and later monitored by the Mars Reconnaissance Orbiter (MRO)—have been observed to increase in size over time. However, large-scale analysis of SCF formation and growth has been limited by the slow and labor-intensive nature of manual mapping techniques. This study applies object-based image analysis (OBIA) to automate the detection and measurement of SCFs using High-Resolution Imaging Science Experiment (HiRISE) images spanning five Martian years. Results show that SCFs exhibit a near-linear increase in area, suggesting that summer sublimation consistently outpaces winter CO₂ deposition. Validation against manual digitization shows discrepancies of less than 1%, confirming the reliability of the OBIA method. Regression-based extrapolation of growth trends indicates that the current generation of SCFs likely began forming between Martian years 7 and 16, approximately corresponding to Earth years 1976 to 1998. These findings provide a quantitative assessment of SCF evolution and contribute to our understanding of recent climate-driven surface changes on Mars. HiRISE images were processed using the eCognition software to detect, classify, and measure SCFs, demonstrating that OBIA is a scalable and effective tool for analyzing dynamic planetary landforms. Full article