Search Results (1,890)

The search for sustainable, economically viable, and effective plant protection strategies against pathogenic bacteria, fungi, and viruses is a major challenge in modern agricultural practices. Chitosan (CS) is an abundant cationic natural biopolymer known for its biocompatibility, low toxicity, and antimicrobial properties. Its potential use in agriculture for pathogen control is a promising alternative to traditional chemical fertilisers and pesticides, which raise concerns regarding public health, environmental protection, and pesticide resistance. This study focused on the preparation of chitosan nanoparticles (CS-NPs) through cross-linking with organic molecules, such as tannic acid (TA). Various formulations were explored for the development of stable nanoscale particles having encapsulation capabilities towards low compounds of varying polarity and with potential agricultural applications relevant to plant health and growth. The solution properties of the NPs were assessed using dynamic and electrophoretic light scattering (DLS and ELS); their morphology was observed through atomic force microscopy (AFM), while analytical ultracentrifugation (AUC) measurements provided insights into their molar mass. Their properties proved to be primarily influenced by the concentration of CS, which significantly affected its intrinsic conformation. Additional structural insights were obtained via infrared and UV–Vis spectroscopic measurements, while detailed fluorescence analysis with the use of three different probes, as model cargo molecules, provided information regarding the hydrophobic and hydrophilic microdomains within the particles. Full article

The search for artificial blood substitutes that are suitable for safe transfusion in clinical conditions and in extreme situations has gained increasing interest during recent years. Most of the problems related to donor blood could be overcome with hemoglobin sub-micron particles (HbMPs) that are able to bind and deliver oxygen. On the other hand, the length of the circulation time of HbMPs in the bloodstream strongly depends on their surface properties and can be improved with biopolymer coatings. The redox potential of HbMPs and HbMPs coated with biopolymers using the layer-by-layer technique (LbL-HbMPs) is related to the energy required for electron transfer upon transition from an oxidized to a reduced state. It can be used as a measure of the stability of Hb against oxidation, which is directly connected with its function as an oxygen carrier. The redox potential of Hb, HbMPs, and LbL-HbMPs was determined by a spectroelectrochemical method utilizing the shift of the Soret peak of Hb upon oxidation/reduction of the iron in the heme. The obtained results showed a slight shift in the redox potential of both particle types of about 17 mV towards more negative values compared to the free Hb in the solution. It was demonstrated that the free Hb and the cross-linked Hb in HbMPs and LbL-HbMPs undergo transitions from an oxidized to a reduced state and vice versa several times without Hb destruction. The LbL coating does not affect the redox properties of HbMPs. This ability, as well as the proximity of the obtained redox potentials of Hb, HbMPs, and LbL-HbMPs, indicates that the eventual oxidation of HbMPs in the bloodstream is reversible; thus, HbMPs can be active as artificial oxygen carriers for a longer period of time. Full article

Initially, the effects of sheet combinations for joining two sheets, including 780 MPa steel and A5052 aluminum alloy sheets, on the joined cross-sectional shapes of the sheets in a clinch-bonding process and the tension-shear load of joined sheets were investigated. The effect of an adhesive on the amounts of the interlock and the minimum thickness in the upper sheet was not large, whereas the effect of the sheet combination was observed. Subsequently, for joining the upper 980 MPa ultra-high-strength steel and lower aluminum alloy sheets in the clinch-bonding process, the effects of the die shape, punch velocity, and sheet holding force on the joinability were investigated. As a result, defect-free conditions were narrowly constrained. Finally, a method that involved controlling material flow using an adhesive with fine particles to increase friction between the sheets was introduced. The upper 980 MPa steel and lower aluminum alloy sheets were successfully joined using this approach. Full article

Suspended particulate matter (SPM) plays a pivotal role in marine source-to-sink sedimentary systems. Internal solitary waves (ISWs), a prevalent hydrodynamic phenomenon, significantly influence vertical mixing, cross-shelf material transport, and sediment resuspension. Acting as energetic nonlinear waves, ISWs can disrupt the settling trajectories of suspended particles, enhance lateral transport above the pycnocline, and generate nepheloid layers nearshore. Meanwhile, intense turbulent mixing induced by ISWs accumulates large quantities of SPM at both the leading surface and trailing bottom of the waves, thereby altering the structure and dynamics of the intermediate nepheloid layers. This review synthesizes recent advances in the in situ observational techniques for SPM under the influence of ISWs and highlights the key mechanisms governing their interactions. Particular attention is given to representative field cases in the SCS, where topographic complexity and strong stratification amplify ISWs–sediment coupling. Finally, current limitations in observational and modeling approaches are discussed, with suggestions for future interdisciplinary research directions that better integrate hydrodynamic and sediment transport processes. Full article

Starch extracted from malanga (Colocasia esculenta) is a biopolymer with considerable industrial potential thanks to its high starch content (70–80% on a dry basis) and small granule size, which give it distinctive functional properties. To expand its applications in advanced processes such as encapsulation, it is necessary to modify its structural and physicochemical characteristics. This study evaluated the effects of ultrasound (US) and chemical cross-linking (CL) on the properties of this starch. US was applied at various times and amplitudes, while CL was performed using sodium trimetaphosphate and sodium tripolyphosphate, with sodium sulfate as a catalyst. US treatment reduced particle size and increased amylose content, resulting in lower viscosity and gelatinization temperature, without affecting granule morphology. Meanwhile, CL induced phosphate linkages between starch chains, promoting aggregation and reducing amylose content and enthalpy, but increasing the gelatinization temperature. The modified starches exhibited low syneresis, making them potentially suitable for products such as pastas, baby foods, and jams. Additionally, ultrasound modification enabled the production of fine starch microparticles, which could be applied in the microencapsulation of bioactive compounds in the food and pharmaceutical industries. These findings suggest that modified malanga starch can serve as a functional and sustainable alternative in industrial applications. Full article

Background/Objectives: The resistance mutations EGFR^{L858R/T790M/C797S} in epidermal growth factor receptor (EGFR) are key factors in the reduced efficacy of Osimertinib. Predicting the inhibitory effects of Osimertinib derivatives against these mutations is crucial for the development of more effective inhibitors. This study aims to predict the inhibitory effects of Osimertinib derivatives against EGFR^{L858R/T790M/C797S} mutations. Methods: Six models were established using heuristic method (HM), random forest (RF), gene expression programming (GEP), gradient boosting decision tree (GBDT), polynomial kernel function support vector machine (SVM), and mixed kernel function SVM (MIX-SVM). The descriptors for these models were selected by the heuristic method or XGBoost. Comprehensive learning particle swarm optimizer was adopted to optimize hyperparameters. Additionally, the internal and external validation were performed by leave-one-out cross-validation ($Q_{LOO}^2$), 5-fold cross validation ($Q_{5-fold}^2$) and concordance correlation coefficient (CCC), $Q_{F1}^2$, and $Q_{F2}^2$. The properties of novel EGFR inhibitors were explored through molecular docking analysis. Results: The model established by MIX-SVM whose kernel function is a convex combination of three regular kernel functions is best: $R^2$ and RMSE for training set and test set are 0.9445, 0.1659 and 0.9490, 0.1814, respectively; $Q_{LOO}^2$, $Q_{5-fold}^2$, CCC, $Q_{F1}^2$, and $Q_{F2}^2$ are 0.9107, 0.8621, 0.9835, 0.9689, and 0.9680. Based on these results, the IC₅₀ values of 162 newly designed compounds were predicted using the HM model, and the top four candidates with the most favorable physicochemical properties were subsequently validated through PEA. Conclusions: The MIX-SVM method will provide useful guidance for the design and screening of novel EGFR^{L858R/T790M/C797S} inhibitors. Full article

Cyanotypes, known as photographs and architectural plans made by photo-reproduction from the 19th and 20th centuries, are subjects for conservation. Wet cleaning for conservation treatment has been reported to be unsuitable for cyanotypes because Prussian blue on cyanotypes is thought to move physically with the application of water. The manner in which Prussian blue is fixed onto the paper substrate is important for determining the treatment method. This study is the first step toward clarifying this mechanism. The presence of Prussian blue in cyanotypes was first confirmed using X-ray diffraction analysis (XRD). Then, the location of Prussian blue in the fibre was confirmed using optical microscopy and micro-Raman spectroscopy analysis, by observing the blue colour and by detecting its cyanide bond. With field-emission scanning electron microscopy (FE-SEM), particles approximately 20–100 nm in size were observed on the surface of cyanotype paper fibres, and particles approximately 20–50 nm in size were observed from the cross-section of the paper fibres. The location where the particles were observed agreed with the location where the blue colour was observed and cyanide bond was detected. The fact that the sensitiser solution soaked into the paper fibres and formed Prussian blue within the paper fibres when exposed to light is thought to be important for the blue fixation of cyanotypes. Full article

Calorific value and moisture content are the key indices to evaluate Caragana pellet fuel’s quality and combustion characteristics. Calorific value is the key index to measure the energy released by energy plants during combustion, which determines energy utilization efficiency. But at present, the determination of solid fuel is still carried out in the laboratory by oxygen bomb calorimetry. This has seriously hindered the ability of large-scale, rapid detection of fuel particles in industrial production lines. In response to this technical challenge, this study proposes using hyperspectral imaging technology combined with various chemometric methods to establish quantitative models for determining moisture content and calorific value in Caragana korshinskii fuel. A hyperspectral imaging system was used to capture the spectral data in the 935–1720 nm range of 152 samples from multiple regions in Inner Mongolia Autonomous Region. For water content and calorific value, three quantitative detection models, partial least squares regression (PLSR), random forest regression (RFR), and extreme learning machine (ELM), respectively, were established, and Monte Carlo cross-validation (MCCV) was chosen to remove outliers from the raw spectral data to improve the model accuracy. Four preprocessing methods were used to preprocess the spectral data, with standard normal variate (SNV) preprocessing performing best on the quantitative moisture content detection model and Savitzky–Golay (SG) preprocessing performing best on the calorific value detection method. Meanwhile, to improve the prediction accuracy of the model to reduce the redundant wavelength data, we chose four feature extraction methods, competitive adaptive reweighted sampling (CARS), successive pojections algorithm (SPA), genetic algorithm (GA), iteratively retains informative variables (IRIV), and combined the three models to build a quantitative detection model for the characteristic wavelengths of moisture content and calorific value of Caragana korshinskii fuel. Finally, a comprehensive comparison of the modeling effectiveness of all methods was carried out, and the SNV-IRIV-PLSR modeling combination was the best for water content prediction, with its prediction set determination coefficient $\left(R_P^2\right)$, root mean square error of prediction (RMSEP), and relative percentage deviation (RPD) of 0.9693, 0.2358, and 5.6792, respectively. At the same time, the moisture content distribution map of Caragana fuel particles is established by using this model. The SG-CARS-RFR modeling combination was the best for calorific value prediction, with its $R_P^2$, RMSEP, and RPD of 0.8037, 0.3219, and 2.2864, respectively. This study provides an innovative technical solution for Caragana fuel particles’ value and quality assessment. Full article

Non-Newtonian debris flows represent a critical challenge for hydraulic infrastructure in mountainous regions, often causing significant damage and service disruption. However, current models typically simplify these flows as Newtonian, leading to inaccurate design assumptions. This study addresses this gap by comparing the hydraulic behavior of Newtonian and non-Newtonian flows in an alluvial fan, using the Amoray Gully in Apurímac, Peru, as a case study. This gully intersects the Interoceánica Sur national highway via a low-water crossing (baden), making it a relevant site for evaluating debris flow impacts on critical road infrastructure. The methodology integrates hydrological analysis, rheological characterization, and hydraulic modeling. QGIS 3.16 was used for watershed delineation and extraction of physiographic parameters, while a high-resolution topographic survey was conducted using an RTK drone. Rainfall-runoff modeling was performed in HEC-HMS 4.7 using 25 years of precipitation data, and hydraulic simulations were executed in HEC-RAS 6.6, incorporating rheological parameters and calibrated with the footprint of a historical event (5-year return period). Results show that traditional Newtonian models underestimate flow depth by 17% and overestimate velocity by 54%, primarily due to unaccounted particle-collision effects. Based on these findings, a multi-barrel circular culvert was designed to improve debris flow management. This study provides a replicable modeling framework for debris-prone watersheds and contributes to improving design standards in complex terrain. The proposed methodology and findings offer practical guidance for hydraulic design in mountainous terrain affected by debris flows, especially where infrastructure intersects active alluvial fans. Full article

The spin polarization of current in a conventional ferromagnetic and semiconductor-based Rashba spin–orbit interaction (RSOI) in an infinite two-dimensional system and the electrical properties of the junction are described using the square lattice model. In particular, a suitable approach is devised to compute the particle transport characteristics in the junction, taking into consideration the interface quality. It is found that the spin polarization becomes strongly reliant on the spin-flip scattering potential at applied voltages close to the crossings of the semiconductor-based RSOI band. On the other hand, in the voltage near the middle band, the spin polarization of current is found to remain modest and not influenced by either the spin-flip or non-spin-flip scattering potentials. Full article

To investigate the evolution trend of the extraction zone above the drawbell in block caving, an experimental apparatus incorporating the drawbell structure was designed. Ore drawing experiments were conducted using materials with varying particle size gradations. The results demonstrate that the extraction zones for all three gradations exhibit an ellipsoidal shape in the vertical direction, with elliptical cross-sections. As the draw height increases, both the major and minor axes of the extraction zone’s maximum cross-section continuously enlarge, stabilizing beyond a draw height of 80 cm. The ore fragment size significantly influences the extraction zone dimensions. Gradation I, characterized by the smallest average particle size, yielded the largest extraction zone, whereas Gradation III, with the largest average particle size, resulted in the smallest. Numerical simulations of ore drawing for the different particle sizes were performed using PFC3D. The extent of the extraction zone in the numerical results was determined by reconstructing the initial positions of the drawn particles. The simulations show good agreement with the experimental findings, particularly regarding how the major and minor axes of the extraction zone cross-section vary with increasing draw height. Moreover, the simulations confirm that smaller average particle sizes enhance particle flowability, leading to larger extraction zones, as anticipated. Full article

Traditional data-driven approaches to lithium battery state of health (SOH) estimation face the challenges of difficult feature extraction, insufficient prediction accuracy and weak generalization. To address these issues, this study proposes a novel prediction framework with transfer learning-based linear regression (LR) and a convolutional neural network (CNN) under limited data. In this framework, first, variable inertia weight-based improved particle swarm optimization for variational mode decomposition (VIW-PSO-VMD) is proposed to mitigate the volatility of the “capacity resurgence point” and extract its time-series features. Then, the T-Pearson correlation analysis is introduced to comprehensively analyze the correlations between multivariate features and lithium battery SOH data and accurately extract strongly correlated features to learn the common features of lithium batteries. On this basis, a combination model is proposed, applying LR to extract the trend features and combining them with the multivariate strongly correlated features via a CNN. Transfer learning based on temporal feature analysis is used to improve the cross-domain learning capabilities of the model. We conduct case studies on a NASA dataset and the University of Maryland dataset. The results show that the proposed method is effective in improving the lithium battery SOH estimation accuracy under limited data. Full article

Rock slopes exhibiting anti-inclined interbedded strata have widespread distribution and complex deformation mechanisms. In this study, we used a physical model test with basal friction to replicate the evolution process of the slope deformation. Digital Image Correlation (DIC) and Particle Image Velocimetry (PIV) methods were used to capture the variation in slope velocity and displacement fields. The results show that the slope deformation is conducted by bending of soft rock layers and accumulated overturning of hard blocks along numerous cross joints. As the faces of the rock columns come back into contact, the motion of the slope can progressively stabilize. Destruction of the toe blocks triggers the formation of the landslides within the toppling zone. The toppling fracture zones form by tracing tensile fractures within soft rocks and cross joints within hard rocks, ultimately transforming into a failure surface which is located above the hinge surface of the toppling motion. The evolution of the slope deformation mainly undergoes four stages: the initial shearing, the free rotation, the creep, and the progressive failure stages. Full article

This paper reports on a preliminary experimental study on binder jetting 3D printing of biomass–fungi composite materials. Biomass–fungi composite materials have potential applications in the packaging, furniture, and construction industries. Biomass particles (prepared from agricultural residues) act as the substrate of the composite materials. The filamentous roots of fungi intertwine and bind biomass particles together. In this study, the biomass (hemp hurd) powders used had two distinct average particle sizes. The liquid binder used contained fungi (Trametes versicolor) cells. T-shaped samples were printed using a lab-designed binder jetting setup. Printed samples were kept inside an incubator oven for four days to allow fungi to grow. Afterward, loose biomass powder was removed from the T-shaped samples. The samples were then kept inside the incubator oven for eight more days to allow further fungal growth. The samples were subsequently placed in an oven at 120 °C for four hours to terminate all fungal activity in the samples. SEM micrographs were taken of the cross-sectional surfaces of the samples. The micrographs showed a significant presence of fungi hyphae inside the printed samples, providing evidence of the binding of biomass particles by the hyphae. Full article

In the context of global climate governance and the low-carbon energy transition, virtual power plant (VPP), a key technology for integrating distributed energy resources, is urgently needed to solve the problem of decentralization and lack of synergy in electricity, carbon, and green certificate trading. Existing studies mostly focus on single energy or carbon trading scenarios and lack a multi-market coupling mechanism supported by blockchain technology, resulting in low transaction transparency and a high risk of information tampering. For this reason, this paper proposes a synergistic optimization strategy for electricity/carbon/green certificate virtual power plants based on blockchain cross-chain transactions. First, Latin Hypercubic Sampling (LHS) is used to generate new energy output and load scenarios, and the K-means clustering method with improved particle swarm optimization are combined to cut down the scenarios and improve the prediction accuracy; second, a relay chain cross-chain trading framework integrating quota system is constructed to realize organic synergy and credible data interaction among electricity, carbon, and green certificate markets; lastly, the multi-energy optimization model of the virtual power plant is designed to integrate carbon capture, Finally, a virtual power plant multi-energy optimization model is designed, integrating carbon capture, power-to-gas (P2G) and other technologies to balance the economy and low-carbon goals. The simulation results show that compared with the traditional model, the proposed strategy reduces the carbon emission intensity by 13.3% (1.43 tons/million CNY), increases the rate of new energy consumption to 98.75%, and partially offsets the cost through the carbon trading revenue, which verifies the Pareto improvement of environmental and economic benefits. This study provides theoretical support for the synergistic optimization of multi-energy markets and helps to build a low-carbon power system with a high proportion of renewable energy. Full article