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The effect of colloidal nanoparticles on the phase changes of the amphiphilic AB linear diblock, A1A2B, and A2B heteroarm star copolymers confined between two polymer brush substrates was investigated by using a real-space self-consistent field theory. By changing the concentrations of nanoparticles and polymer brushes, the phase structure of the amphiphilic AB copolymer transforms from lamellar to core-shell hexagonal phase to cylinder phase. The pattern of A2B heteroarm star copolymer changes from core-shell hexagonal phases to lamellar phases and the layer decreases when increasing the density of the polymer brushes. The results showed that the phase behavior of the system is strongly influenced by the polymer brush architecture and the colloidal nanoparticle numbers. The colloidal nanoparticles and the soft confined surface of polymer brushes make amphiphilic AB copolymers easier to form ordered structures. The dispersion of the nanoparticles was also investigated in detail. The soft surfaces of polymer brushes and the conformation of the block copolymers work together to force the nanoparticles to disperse evenly. It will give helpful guidance for making some new functional materials by nano etching technology, nano photoresist, and nanoprinting. [ABSTRACT FROM AUTHOR]

With the increasing complexity and frequency of interactions among a large number of heterogeneous nodes within a combat system of systems (SoS), evaluating the capability of the SoS to withstand external attacks and interferences has become an increasingly challenging and urgent issue. However, the complexity of a combat SoS often brings about difficulties in quantitative analysis. This paper proposes a method to assess the resilience of a combat SoS. Firstly, a network model of a combat SoS is constructed, taking into account multi-functional composite nodes. Secondly, the combat capability model of the combat SoS is built based on the capabilities of the kill chains and kill networks. Lastly, an approach is proposed to calculate the combat capability of the system based on the network's two-terminal connectivity. Moreover, based on the SoS's combat capability, the resilience is analyzed from the dimensions of anti-destruction, survival, and recovery. The simulation experiments show that, compared to other methods, the method in this paper for calculating the combat capability of the combat SoS does not depend on the number of kill chains and aligns with the combat processes and actual patterns. Additionally, the resilience measurement method can effectively analyze its capability to cope with external interferences. [ABSTRACT FROM AUTHOR]

Despite a few attempts to automatically crawl Ewe text from online news portals and magazines, the African Ewe language remains underdeveloped despite its rich morphology and complex "unique" structure. This is due to the poor quality, unbalanced, and religious-based nature of the crawled Ewe texts, thus making it challenging to preprocess and perform any NLP task with current transformer-based language models. In this study, we present a well-preprocessed Ewe dataset for low-resource text classification to the research community. Additionally, we have developed an Ewe-based word embedding to leverage the low-resource semantic representation. Finally, we have fine-tuned seven transformer-based models, namely BERT-based (cased and uncased), DistilBERT-based (cased and uncased), RoBERTa, DistilRoBERTa, and DeBERTa, using the preprocessed Ewe dataset that we have proposed. Extensive experiments indicate that the fine-tuned BERT-base-cased model outperforms all baseline models with an accuracy of 0.972, precision of 0.969, recall of 0.970, loss score of 0.021, and an F1-score of 0.970. This performance demonstrates the model's ability to comprehend the low-resourced Ewe semantic representation compared to all other models, thus setting the fine-tuned BERT-based model as the benchmark for the proposed Ewe dataset. [ABSTRACT FROM AUTHOR]

During the interception of a high-speed gliding vehicle (HGV), the predicted intercept point (PIP) is updated many times, so the interceptor must continuously adjust its trajectory. In this paper, we propose an online guidance correction algorithm for the interceptor, which can effectively meet the position constraints and energy management of the guidance process. Firstly, we simplify the interceptor's maneuvering problem to a two-body orbital transfer problem. The Lambert orbit transfer method is used to enable the interceptor to maneuver towards the target's PIP. Secondly, by comparing the target's high probability existence area (THPEA) with the interceptor-interceptable area (IIA), the engine start threshold is set in stages to avoid frequent redundancy maneuvers caused by frequent engine starting during missile correction. This approach achieves energy management. Simulation results show that our midcourse guidance strategy is effective. [ABSTRACT FROM AUTHOR]

The interactions between starch and protein, the essential components of lotus seed, strongly influence the quality of lotus seed processing by-products. This study investigated the effects of lotus seed starch–protein (LS-LP) interactions on the structural, thermal and gelatinization properties of LS-LP mixtures, using LS/LP ratios of 6:1, 6:2, 6:3, 6:4, 6:5, or 1:1, after heat treatment (95 °C, 30 min). Fourier transform infrared peaks at 1540 cm−1 and 3000–3600 cm−1 revealed the major interactions (electrostatic and hydrogen bonding) between LS and LP. The UV–visible absorption intensities (200–240 nm) of LS-LP mixtures increased with increased protein content. X-ray diffraction and electron microscopy revealed that LS-LP consists of crystalline starch granules encapsulated by protein aggregates. Increasing the addition of protein to the mixtures restricted the swelling of the starch granules, based on their solubility, swelling properties and thermal properties. Viscometric analysis indicated that the formation of LS-LP mixtures improved structural and storage stability. These findings provide a practicable way to control the thermal and gelatinization properties of lotus seed starch–protein mixtures, by changing the proportions of the two components, and provide a theoretical basis for developing novel and functional lotus-seed-based foods. [ABSTRACT FROM AUTHOR]

Psoriasis is a chronic inflammatory skin disorder accompanied by excessive keratinocyte proliferation. Erianin (Eri) is an ideal drug candidate for inhibiting proliferation and inducing apoptosis in the treatment of psoriasis. However, Eri's poor water solubility and low penetration activity across the skin hinder its application in local medicine. In this study, we developed a novel photo-responsive dendritic mesoporous silica nanoparticle-based carrier to deliver erianin, improved its bioavailability, and achieved sustained-release effects. Spiropyran (SP), 3-aminopropyltriethoxysilane (APTES), and perfluorodecyltriethoxysilane (PFDTES) were conjugated to the outer surface, which allowed Eri to be released in response to UV radiation. The physicochemical properties of photo-responsive dendritic mesoporous silica nanoparticles (Eri-DMSN@FSP) were characterized via multiple techniques, such as using a Fourier-transform infrared spectrometer, a high-resolution transmission electron microscope, and nuclear magnetic resonance (NMR) spectroscopy. The anti-proliferative properties and light-triggered release of erianin-loaded photo-responsive dendritic mesoporous silica nanoparticles were assessed via the MTT assay and a drug release study in vitro. Erianin-loaded photo-responsive dendritic mesoporous silica nanoparticles (UV) exhibit a significantly enhanced HaCat cell-inhibiting efficacy compared to other formulations, as demonstrated by their extremely low cell viability of 10.0% (concentration: 500 mg/mL), indicating their capability to release a drug that responds to UV radiation. The cellular uptake of photo-responsive dendritic mesoporous silica nanoparticles (DMSN@FSP) was observed via confocal laser scanning microscopy (CLSM). These experimental results show that Eri-DMSN@FSP could be effectively endocytosed into cells and respond to ultraviolet light to release Eri, achieving a more effective psoriasis treatment. Therefore, this drug delivery system may be a promising strategy for addressing the question of Eri's delivery and psoriasis therapy. [ABSTRACT FROM AUTHOR]

Leveraging global state information to enhance policy optimization is a common approach in multi-agent reinforcement learning (MARL). Even with the supplement of state information, the agents still suffer from insufficient exploration in the training stage. Moreover, training with batch-sampled examples from the replay buffer will induce the policy overfitting problem, i.e., multi-agent proximal policy optimization (MAPPO) may not perform as good as independent PPO (IPPO) even with additional information in the centralized critic. In this paper, we propose a novel noise-injection method to regularize the policies of agents and mitigate the overfitting issue. We analyze the cause of policy overfitting in actor–critic MARL, and design two specific patterns of noise injection applied to the advantage function with random Gaussian noise to stabilize the training and enhance the performance. The experimental results on the Matrix Game and StarCraft II show the higher training efficiency and superior performance of our method, and the ablation studies indicate our method will keep higher entropy of agents' policies during training, which leads to more exploration. [ABSTRACT FROM AUTHOR]

Xanthatin (XT) is a sesquiterpene lactone isolated from the Chinese herb Xanthium, which belongs to the Asteraceae family. In this study, we developed an inflammation model via stimulating macrophage cell line (RAW 264.7 cells) with lipopolysaccharide (LPS), which was applied to assess the anti-inflammatory effect and probable mechanisms of xanthatin. When compared with the only LPS-induced group, cells that were pretreated with xanthatin were found to decrease the amount of nitric oxide (NO), reactive oxygen species (ROS) and associated pro-inflammatory factors (TNF-α, IL-1β and IL-6), and downregulate the mRNA expression of iNOS, COX-2, TNF-α, IL-1β, and IL-6. Interestingly, phosphorylated levels of related proteins (STAT3, ERK1/2, SAPK/JNK, IκBα, p65) were notably increased only with the LPS-activated cells, while the expression of these could be reverted by pre-treatment with xanthatin in a dose-dependent way. Meanwhile, xanthatin was also found to block NF-κB p65 from translocating into the nucleus and activating inflammatory gene transcription. Collectively, these results demonstrated that xanthatin suppresses the inflammatory effects through downregulating the nuclear factor kappa-B (NF-κB), mitogen-activated protein kinase (MAPK) and signal transducer and activator of transcription (STATs) signaling pathways. Taken together, xanthatin possesses the potential to act as a good anti-inflammatory medication candidate. [ABSTRACT FROM AUTHOR]

Dehydrins, also known as Group II late embryogenesis abundant (LEA) proteins, are classic intrinsically disordered proteins, which have high hydrophilicity. A wide range of hostile environmental conditions including low temperature, drought, and high salinity stimulate dehydrin expression. Numerous studies have furnished evidence for the protective role played by dehydrins in plants exposed to abiotic stress. Furthermore, dehydrins play important roles in seed maturation and plant stress tolerance. Hence, dehydrins might also protect plasma membranes and proteins and stabilize DNA conformations. In the present review, we discuss the regulatory networks of dehydrin gene expression including the abscisic acid (ABA), mitogen-activated protein (MAP) kinase cascade, and Ca2+ signaling pathways. Crosstalk among these molecules and pathways may form a complex, diverse regulatory network, which may be implicated in regulating the same dehydrin. [ABSTRACT FROM AUTHOR]

This paper proposes an encryption-based image watermarking scheme using a combination of second-level discrete wavelet transform (2DWT) and discrete cosine transform (DCT) with an auto extraction feature. The 2DWT has been selected based on the analysis of the trade-off between imperceptibility of the watermark and embedding capacity at various levels of decomposition. DCT operation is applied to the selected area to gather the image coefficients into a single vector using a zig-zig operation. We have utilized the same random bit sequence as the watermark and seed for the embedding zone coefficient. The quality of the reconstructed image was measured according to bit correction rate, peak signal-to-noise ratio (PSNR), and similarity index. Experimental results demonstrated that the proposed scheme is highly robust under different types of image-processing attacks. Several image attacks, e.g., JPEG compression, filtering, noise addition, cropping, sharpening, and bit-plane removal, were examined on watermarked images, and the results of our proposed method outstripped existing methods, especially in terms of the bit correction ratio (100%), which is a measure of bit restoration. The results were also highly satisfactory in terms of the quality of the reconstructed image, which demonstrated high imperceptibility in terms of peak signal-to-noise ratio (PSNR ≥ 40 dB) and structural similarity (SSIM ≥ 0.9) under different image attacks. [ABSTRACT FROM AUTHOR]