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The cover image with strong resistance against embedding distortion has promise for improving the holistic security of steganography. However, existing methods use the vulnerability of Convolutional Neural Network (CNN) to construct the enhanced cover which can only deceive the target CNN-based steganalyzer, but is not more suitable for steganography. When resisting steganalysis outside the target steganalyzer, its performance drops significantly. In this paper, we propose an immune-cover construction scheme via Artificial Immune System (AIS). By the association between the steganography and immune theory, we regard the cover as the organism, the distortion introduced by steganography as the pathogenic factor, and the immunoprocessing for optimizing the original cover as the antibody. Based on AIS, the optimal immunoprocessing is dynamically searched and performed on the original cover to construct an immune-cover which is most suitable for steganography. Besides, the proposed method carefully selects the immunoprocessing region to prevent artifacts, and guarantees the visual quality of the immune-cover through the constraint of the immunoprocessing intensity. Extensive experimental results demonstrate that the proposed immune-cover has much stronger resistance against embedding distortion compared with the related methods, thus significantly improving the holistic security of the adaptive steganography evaluated on both traditional and CNN-based steganalyzers.

Fourier phase retrieval (PR) is a severely ill-posed inverse problem that arises in various applications. To guarantee a unique solution and relieve the dependence on the initialization, background information can be exploited as a structural prior. However, the requirement for the background information may be challenging when moving to high-resolution imaging. At the same time, the previously proposed projected gradient descent (PGD) method also demands much background information. In this paper, we present an improved theoretical result about the demand for the background information, along with two Douglas Rachford (DR) based methods. Analytically, we demonstrate that the background information required to ensure a unique solution can be decreased by nearly $1/2$ for the 2-D signals compared to the 1-D signals. By generalizing the results into d-dimension, we show that the length of the background information more than $\left ({{2^{\frac {d+1}{d}}-1}}\right)$ folds of the signal is sufficient to ensure uniqueness. At the same time, we also analyze the stability and robustness of the model when the measurements and background information are corrupted by noise. Furthermore, two methods called Background Douglas Rachford (BDR) and Convex Background Douglas Rachford (CBDR) are proposed. BDR, which is a kind of non-convex method, is proven to have the local R-linear convergence rate under mild assumptions. Instead, the CBDR method uses the techniques of convexification and can be proven to have a global convergence guarantee as long as the background information is sufficient. To support this, a new property called F-RIP is established. We test the performance of the proposed methods through simulations as well as real experimental measurements, and demonstrate that they achieve a higher recovery rate with less background information compared to the PGD method.

Smc5/6 is a member of the eukaryotic structural maintenance of chromosomes (SMC) family of complexes with important roles in genome maintenance and viral restriction. However, limited structural understanding of Smc5/6 hinders the elucidation of its diverse functions. Here, we report cryo-EM structures of the budding yeast Smc5/6 complex in eight-subunit, six-subunit and five-subunit states. Structural maps throughout the entire length of these complexes reveal modularity and key elements in complex assembly. We show that the non-SMC element (Nse)2 subunit supports the overall shape of the complex and uses a wedge motif to aid the stability and function of the complex. The Nse6 subunit features a flexible hook region for attachment to the Smc5 and Smc6 arm regions, contributing to the DNA repair roles of the complex. Our results also suggest a structural basis for the opposite effects of the Nse1–3–4 and Nse5–6 subcomplexes in regulating Smc5/6 ATPase activity. Collectively, our integrated structural and functional data provide a framework for understanding Smc5/6 assembly and function.

We proposed the co-catalysis between the single atom catalyst (SAC) and its B-containing support for boosting the activation and reduction the inert N2molecule to NH3with high efficiency.

The pursuit of increased efficiency of photoelectric energy conversion through optimized semiconductor structures remains highly competitive, with current results yet to align with broad expectations. In this study, we discover a significant enhancement in photocurrent performance of a p-3C-SiC nanothin film on p-Si/n-Si double junction (DJ) heterostructure that integrates p-3C-SiC/p-Si heterojunction and p-Si/n-Si homojunction. The vertical photocurrent (VPC) and vertical photoresponsivity exhibit a substantial enhancement in the DJ heterostructure, surpassing by a maximum of 43-fold compared to the p-3C-SiC/n-Si single junction (SJ) counterpart. The p-3C-SiC layer and n-Si substrate of the two heterostructures have similar material and geometrical properties. More importantly, the fabrication costs for the DJ and SJ heterostructure devices are comparable. Our results demonstrate a significant potential for using DJ devices in energy harvesters, micro/nano electromechanical systems, and sensing applications. This research may also lead to the creation of advanced optoelectronic devices using DJ structures, where employing various semiconductor materials to achieve exceptional performance through the application of the concept and theoretical model described in this work.

The desire to commercialize perovskite solar cells continues to mount, motivating the development of scalable production. Evaluations of the impact of open-air processing have revealed a variety of physical changes in the fabricated devices─with few changes having the capacity to be functionalized. Here, we highlight the beneficial role of ambient oxygen during the open-air thermal processing of metastable γ-CsPbI3-based perovskite thin films and devices. Physiochemical-sensitive probes elucidate oxygen intercalation and the formation of Pb–O bonds in the CsPbI3crystal, entering via iodine vacancies at the surface, creating superoxide (O2–) through electron transfer reactions with molecular oxygen, which drives the formation of a zero-dimensional Cs4PbI6capping layer during annealing (>330 °C). The chemical conversion permanently alters the film structure, helping to shield the subsurface perovskite from moisture and introduces lattice anchoring sites, stabilizing otherwise unstable γ-CsPbI3films. This functional modification is demonstrated in γ-CsPbI2Br perovskite solar cells, boosting the operational stability and photoconversion efficiency of champion devices from 12.7 to 15.4% when annealed in dry air. Such findings prompt a reconsideration of glovebox-based perovskite solar cell research and establish a scenario where device fabrication can in fact greatly benefit from ambient oxygen.

Different from the standard linear quadratic (LQ) problem for stochastic systems, the LQ problem considered in the paper has extra measurability restrictions. The problem also appears in the LQ control problem for stochastic systems with delays, rational expectations problems, asymmetric information control, and so on. The essential difficulty lies in that one has to optimize the input and its conditional expectations simultaneously. The stochastic maximum principle (SMP) and orthogonal decomposition technique are the key tools. Firstly, the authors establish the SMP and convert the original problem into forward and backward stochastic difference equations (FBSDEs) with extra measurability restrictions. Secondly, the authors resolve the FBSDEs by using the orthogonal decomposition technique and obtain the analytical solution to the underlying problem. Thirdly, the authors explore the essential distinction between the problem and the standard stochastic LQ control problem. Finally, numerical examples are given to illustrate the obtained results.

A fully automated online enrichment and separation system for intact glycopeptides, named AutoGP, was developed in this study by integrating three different columns in a nano-LC system. Specifically, the peptide mixture from the enzymatic digestion of a complex biological sample was first loaded on a hydrophilic interaction chromatography (HILIC) column. The nonglycopeptides in the sample were washed off the column, and the glycopeptides retained by the HILIC column were eluted to a C18 trap column to achieve an automated glycopeptide enrichment. The enriched glycopeptides were further eluted to a C18 column for separation, and the separated glycopeptides were eventually analyzed by using an orbitrap mass spectrometer (MS). The optimal operating conditions for AutoGP were systemically studied, and the performance of the fully optimized AutoGP was compared with a conventional manual system used for glycopeptide analysis. The experimental evaluation shows that the total number of glycopeptides identified is at least 1.5-fold higher, and the median coefficient of variation for the analyses is at least 50% lower by using AutoGP, as compared to the results acquired by using the manual system. In addition, AutoGP can perform effective analysis even with a 1-μg sample amount, while a 10-μg sample at least will be needed by the manual system, implying an order of magnitude better sensitivity of AutoGP. All the experimental results have consistently proven that AutoGP can be used for much better characterization of intact glycopeptides.

To clarify the evolution of lamellar phases in the initial microstructure of the Mg-9Gd-0.8Al alloy during the extrusion process and the effect of lamellar phases on the dynamic recrystallization of the extruded Mg alloy, the solid solution treated Mg-9Gd-0.8Al (SS10) alloy, was extruded at different temperatures (380, 400, and 450 °C). With the extrusion temperature increasing, the average size of dynamically recrystallized (DRXed) grains and the second phases decreases firstly and then increases. However, the volume fraction of DRXed grains shows an opposite trend, while the amount of the second phases consistently decreases. The as-extruded SS10 alloy demonstrates superior mechanical properties when extruded at 400 °C, with a yield strength (YS) of 240 MPa, ultimate tensile strength (UTS) of 298 MPa, and elongation (EL) of 19.3%. The alloy achieves enhanced strength through grain boundary strengthening, dislocation strengthening, and Orowan strengthening. Moreover, the presence of DRXed grains with a weak texture plays a significant role in the improvement of the ductility of the alloy.

Owing to the hexagonal close-packed (HCP) crystal structure inherent in Mg alloys, strong basal texture can readily be induced through the processes of rolling or extrusion. The anisotropy of the texture of Mg alloys impacts their stamping and forming capabilities, limiting their use in certain applications. Microalloying and shear deformation are currently the most common methods of weakening the texture of Mg alloys. Many shearing processes have been extensively studied, and given that they require complex equipment and make it difficult to achieve mass production, major attention has turned to studying the design of microalloys. Traditional trial-and-error approaches for developing micro-alloying confront many challenges, including longer test cycles and increasing expenses. The rapid advancement of big data and artificial intelligence opens up a new channel for the efficient advancement of metallic materials, specifically the application of machine learning to aid in the design of Mg alloys. ML modeling can be used to find correlations between features and attributes in data, allowing for the development and design of high-performance Mg alloys. The article provides an extensive overview of machine learning applications in Mg alloys. These include the discovery of high-performance alloys, the selection of coating designs, the design of Mg matrix composites, the prediction of second phases, the microstructure modification, optimization of rolling or extrusion parameters, and the prediction of mechanical and corrosion properties. In conclusion, challenges and prospects for the rational design of alloys with machine learning support were discussed.

Nifedipine is a potent antihypertensive medication classified as a dihydropyridine calcium channel blocker. The objective of this trial was to assess the bioequivalence of a 30‐mg nifedipine controlled‐release tablet and a reference drug in a cohort of healthy Chinese individuals. Two independent open‐label, randomized, single‐dose, crossover studies were conducted, 1 under fasting conditions (N = 44, with 1 participant dropping out midway) and the other under fed conditions (N = 44, with 4 participants dropping out midway). Plasma concentrations of nifedipine were determined using liquid chromatography‐mass spectrometry, and pharmacokinetic (PK) parameters were calculated using noncompartmental analysis with Phoenix WinNonlin 8.0 software. In both fasting and fed studies, reasonable bioequivalence was observed for the PK parameters of both the test product and the reference drug. A good safety profile was demonstrated for both the test product and reference drug, with no serious adverse events reported, and both were similarly well tolerated. An important observation with food coadministration was that systemic exposure to nifedipine (based on area under the curve, AUC0‐∞) was reduced by approximately 12%. The bioequivalence of the test product and reference drug under fasting/fed conditions in healthy subjects in China was demonstrated by the study results.

PARP7 plays a crucial role in cancer immunity. The inhibition of PARP7 has shown potential in boosting the immune response against cancer, making it an attractive target for cancer immunotherapy. Herein, we employed a rigid constraint strategy (reduction in molecular flexibility) to design and synthesize a series of novel indazole-7-carboxamide derivatives based on the structure of RBN-2397. Among these derivatives, (S)-XY-05was identified as the most promising PARP7 inhibitor (IC50: 4.5 nM). Additionally, (S)-XY-05showed enhanced selectivity toward PARP7 and improved pharmacokinetic properties (oral bioavailability: 94.60%) compared with RBN-2397 (oral bioavailability: 25.67%). In the CT26 syngeneic mouse model, monotherapy with (S)-XY-05displayed a strong antitumor effect (TGI: 83%) by activating T-cell-mediated immunity within the tumor microenvironment. Collectively, we confirmed that (S)-XY-05has profound effects on tumor immunity, which paves the way for future studies of PARP7 inhibitors that could be utilized in cancer immunotherapy.

This study proposes a novel detection approach utilising the canny algorithm to address the low accuracy issues in traditional icing thickness detection on overhead transmission lines. Employing an unmanned aerial vehicle equipped with a camera for collecting icing images, noise interference is mitigated via compressive sensing theory. Converting the images into greyscale enables edge detection using the canny algorithm. Utilising random Hough transform for extracting edge lines, which are then fused with edge images for subsequent processing and ice thickness calculation. Experimental results validate the substantial enhancement in detection accuracy and efficiency for icing thickness detection on overhead transmission lines with the application of this method.

The popularity of digital devices and the importance of information which lies in text documents lead to the overflowing of screen-shooting attacks for text documents nowadays. So the robust screen-shooting watermarking for text documents is in great demand. However, the existing watermarking of text documents in traditional channels which is widely researched is not available under the huge distortion from screen-shooting attacks. To tackle this problem, in this letter, watermarking based on text document structures which can persist in both print-camera and screen-shooting processes is developed. Our method has two main advantages: 1) Extensive robustness. We define partial brightness integration accompanied with stroke separation method to embed watermark information on characters. For various documents with different fonts' styles, fonts' sizes and different languages' fonts, it shows great performances. Besides, for different shooting conditions such as different shooting distances and angles, the accuracy is also guaranteed. 2) Great imperceptibility. By introducing special divisional method and adaptive intensity, high visual ability is achieved. Both of these two merits are verified by massive experiments.

In this article, the problem of distributed optimization with nonconvex objective functions is studied by employing a network of agents. Each agent only has access to a noisy estimate on the gradient of its own objective function, and can only communicate with its immediate neighbors via a time-varying directed graph. To handle this problem, a distributed stochastic gradient descent algorithm is adopted. Existing works on distributed algorithms involving stochastic gradients only provide convergence results in expectation. Different from them, we study the convergence of the algorithm in high probability, i.e., the asymptotic convergence rate of the algorithm is characterized by the natural logarithm of the failure probability's inverse. Under mild assumptions on the graph connectivity, we prove that for the general nonconvex objective function, the average of gradients' norm squared converges in high probability. Furthermore, we also consider the case where the objective function satisfies the Polyak–Łojasiewicz condition. In this case, the difference between the objective function and its minimum value converges in high probability, and the convergence rate is faster than that in the general nonconvex case. Finally, simulations are provided to demonstrate the effectiveness of our theoretical results.

This article is concerned with linear quadratic regulation (LQR) and stabilization problems for discrete-time stochastic systems with multiple input channels and input delays. In comparison with single-input-channel problems, a key difficulty, induced by the different delays in different input channels, is that the information sets for multiple controllers are required to be asymmetric and coupled. A novel technique, referred to as orthogonal decomposition–reorganization, is proposed to conquer the coupling between channels. After the technique is used, a new method based on some refined decompositions is provided to solve the delayed forward–backward stochastic difference equations, which overcomes the asymmetry and amounts to finding the solvability condition of the underlying LQR problems. The complete solutions of the finite- and infinite-horizon LQR problems are given by newly developing Riccati-type equations. Also, a necessary and sufficient stabilizing condition is obtained for the system restricted by a performance index. Finally, the effectiveness of the results is evaluated by a numerical example.

This study presents a novel technology in the fabrication of AZ31 Mg alloy sheets using continuous shear extrusion (CSE) with multiple shear platforms at 340 °C. Compared with the conventional extrusion (CE), an asymmetric shear deformation was introduced so that the basal texture deflects towards to extrusion direction. Through finite element simulation, it was found that the differences in flow velocity and strain distributions along the thickness direction can be achieved by introducing the shear strain through CSE technology. Finer grains and more uniform microstructure were obtained in CSEed Mg samples compared to conventional extrusion. The average grain size decreased from 6.33 μm in CE samples to 3.94 μm in CSE samples, and 3.39 μm in CSE-II samples. The continuous asymmetric shear force also led to the basal plane inclining approximately 15° towards the extrusion direction, leading to a weakening of basal texture intensity. In terms of mechanical properties, the CSE Mg plates exhibited higher yield strength (YS), ultimate tensile strength (UTS), and fracture elongation (FE) along the extrusion direction. These improvements in mechanical performance can be attributed to enhanced work hardening ability, texture weakening, finer grains generation, and the dislocation strengthening induced by shear strain.

Under the framework of multiagent systems (MASs), this article is focused on the leaderless consensus of multiple Euler–Lagrange (EL) systems subject to denial-of-service (DoS) attacks. First, a new joint control protocol, which combines the distributed sampled-data (SD) control and adaptive distributed control (DC), is designed. The distributed SD control is equipped with logic processors, which can capture key information of DoS attacks, and the adaptive DC is conducive to relaxing some generally required constraint conditions. Second, a new property of a non-negative differentiable function is proposed, which is very helpful in solving the distributed SD control issue of multiple EL systems. Third, by setting up a $\textbf {W}$ -dependent Lyapunov–Krasovskii functional (LKF) and utilizing the property of the non-negative differentiable function, new leaderless consensus results are derived for multiple EL systems with DoS attacks. The obtained leaderless consensus results are in the shape of linear matrix inequalities (LMIs) and can efficiently counter the influence of the DoS attacks. Ultimately, the effectiveness of the derived results is inspected by an MAS with multiple two-linked robot manipulators.

With the proliferation of smartphones, preserving the confidentiality of digital documents has become increasingly challenging. Document formats, such as PowerPoint (PPT), are particularly susceptible to unauthorized capture and leakage through smartphone cameras. In this letter, we propose a camera shooting resilient watermarking for PowerPoint presentation based on the PPT master layout backdrop, which exhibits two key properties. 1) Imperceptibility. We employ a difference-based embedding method on the PPT master layout backdrop to ensure good visual quality of the watermarked PPT. 2) Robustness. We design a distance-based selection method for embedding coefficients, ensuring the watermark's robustness under various shooting conditions. The experimental results demonstrate the robustness of our scheme against screen and projection shooting of PPT presentation, across diverse shooting distances, angles, and coverage levels of the PPT master layout backdrop.

The combination of immune-checkpoint blockade with chemotherapy for the first-line treatment of advanced triple-negative breast cancer (TNBC) has generated mixed results. TORCHLIGHT is a randomized, double-blinded phase 3 trial evaluating the efficacy and safety of first-line toripalimab and nab-paclitaxel (nab-P) (n= 353; experimental arm) versus placebo and nab-P (n= 178; control arm) for the treatment of women with metastatic or recurrent TNBC. The primary end point was progression-free survival (PFS) assessed by a blinded independent central review in the PD-L1-positive and intention-to-treat populations. The secondary end points included overall survival and safety. Overall, 200 and 100 patients, in the toripalimab and placebo arm respectively had PD-L1-positive TNBC. At the prespecified interim analysis, a statistically significant improvement in PFS assessed by a blinded independent central review was demonstrated in the experimental arm in the PD-L1-positive population (median PFS 8.4 versus 5.6 months; hazard ratio (HR) = 0.65, 95% confidence interval (CI) 0.470–0.906, P= 0.0102). The median overall survival was 32.8 versus 19.5 months (HR = 0.62, 95% CI 0.414–0.914, P= 0.0148). Similar incidences of treatment-emergent adverse events (AEs) (99.2% versus 98.9%), grade ≥3 treatment-emergent AEs (56.4% versus 54.3%) and fatal AEs (0.6% versus 3.4%) occurred in the experimental and control arms. The addition of toripalimab to nab-P provided a significant improvement in PFS for PD-L1-positive patients with metastatic or recurrent TNBC with an acceptable safety profile. ClinicalTrial.gov identifier NCT03777579.

Recent advancements in image steganography demonstrate that reasonable cover enhancement approaches can effectively improve the security performance of steganography. However, the existing proposals based on adversarial steganography against targeted steganalyzers are insufficient in terms of eliminating or reducing anomalous pixels caused by subsequent embedding. This limitation impedes the full potential of cover enhancement schemes for enhancing steganographic security. In this article, we present Immucover, a novel immunized cover image construction method that leverages fuzzy enhancement and an artificial immune system (AIS) to incorporate texture region- and edge-region-adaptive enhancement. Specifically, we first design a parameterized method to adaptively enhance the texture region of the given cover image using a distortion function. Then, Immucover detects and enhances the edge region of the cover image using a fuzzy-parameterized approach based on an optimized smallest univalue segment assimilating nucleus for edge detection. Finally, a powerful AIS module acts as an optimizer to optimize the parameters that affect the texture and edge area, i.e., the area where the secret information is suitably embedded. In this way, a so-called immunized cover image is generated. In addition, we develop a novel affinity metric to assess the antibody quality within the AIS module, which guides the generation of the immunized cover with higher security. Comprehensive experiments conducted on widely used datasets demonstrate that our Immucover provides significantly improved resistance to steganalysis and enhances the security of steganography.

The study in this work fully utilized the computational advantages of various numerical methods and established a SPH-PFM coupling model for the 316 L SLM process. The temperature field, melt pool changes, and microstructure evolution of the 316 L SLM process were simulated and calculated. The correctness of the simulation results was verified through the comparison with experiments, and a calculation platform for melt pool evolution and microstructure simulation of metal material SLM process with independent intellectual property rights was developed. (1) Establish the mathematical model required for the dynamic simulation of the molten pool in the metal material SLM process based on the SPH method. (2) Extract the temperature field data and molten pool shape from the calculation results based on the SPH method, and then substitute them into the phase field model for molten pool modeling. The formation mechanism of the microstructure morphology inside the molten pool and the micro-segregation mechanism of solute elements at different positions during solidification were analyzed and discussed. The article compared the simulation results with the experimental results. The simulation results showed good consistency with the experimental results in terms of primary dendrite spacing, secondary dendrite spacing, and melt pool microstructure morphology, proving the correctness of the model established in this article. At the same time, the SPH-PFM coupling model established in this article can effectively solve the problem of predicting the microstructure of the melt pool in the SLM process, providing a new method for the study of microstructure prediction in the SLM process.

This article considers the decentralized linear–quadratic–Gaussian control problem for discrete-time decentralized system controlled by two players. In this scenario, player 1 shares a unit delayed observations and control inputs with the controller of player 2, whereas due to the limiting capacity, the controller of player 1 cannot obtain the observations and control inputs of player 2, which leads to the asymmetric one-step delay information. It should be emphasized that this structure makes the classical separation principle fail. Under the assumption of linear control strategies, we derive the optimal estimators based on asymmetric information. In virtue of the Pontryagin's maximum principle, the optimal explicit decentralized controllers are obtained by solving the forward and backward stochastic difference equations. It is noted that the control gains are coupled with the estimation gains. Moreover, the estimation gains satisfy the forward Riccati equations and the control gains follow the backward Riccati equations, which cannot be solved simultaneously. To this end, we present iterative solutions to the coupled forward and backward Riccati equations. Finally, a sufficient condition for the stabilization problem is given in terms of the coupled algebraic Riccati equations. Numerical examples are illustrated to show the effectiveness of the proposed algorithm.

In recent years, online video sharing platforms have been widely available on social networks. To protect copyright and track the origins of these shared videos, some video watermarking methods have been proposed. However, their robustness performance is significantly degraded under geometric deformations, which destroy the synchronization between the watermark embedding and extraction. To this end, we propose a novel robust blind video watermarking scheme by embedding the watermark into low-order recursive Zernike moments. To reduce the time complexity, we give an efficient computation method by exploring the characteristics of video and moments. The moment accuracy is greatly improved due to the introduction of a recursive computation method. Furthermore, we design an optimization strategy to enhance visual quality and reduce distortion drift of watermarked videos by analyzing the radial basis function. The robustness of the proposed scheme is verified by different attacks, including geometric deformations, length-width ratio changes, temporal synchronization attacks, and combined attacks. In practical applications, the proposed scheme effectively resists processing from video sharing platforms and screenshots taken with smartphones and PC monitors. The watermark is extracted without the host video. Experimental results show that our proposed scheme outperforms other state-of-the-art schemes in terms of imperceptibility and robustness.

Effects of B4C on the microstructure and properties of Mg94Zn2.5Y2.5Mn1alloy were investigated by means of optical microscope, scanning electron microscope, X-ray diffraction, transmission electron microscope, nano indentation tester and electronic universal testing machine. The results indicated that the as-cast Mg94Zn2.5Y2.5Mn1alloy was mainly composed of α-Mg, fishbone-like W phase, and block 18 R long period stacking ordered (LPSO) phase. The addition of an appropriate amount of B4C could effectively refine grains, promote the formation of the LPSO phase and inhibit the generation of the W phase. The microstructure and mechanical properties of the alloy were both optimal at the addition of 0.5 at.% B4C. The microstructure exhibited a refined grain size from 41.2 μm to 20.7 μm, and the volume fraction of the LPSO phase increased from 8.1 % to 22.5 %. The yield strength increases from 112 MPa to 145 MPa, the tensile strength of the alloy was enhanced from 192 MPa to 256 MPa, and the elongation increased from 4.8 % to 8.6 %.

Due to the hexagonal close-packed (HCP) crystal structure of Mg, the plasticity is poor at low temperatures. In order to solve this problem, the in-depth researches on various deformation modes of Mg are very necessary. However, there are many limitations to study these deformation modes in Mg polycrystals owing to the effect of grain boundaries, etc. It is more reasonable to conduct the researches in Mg single crystals, especially investigating the influence of crystal orientations, and the advantages of Mg single crystals are prominent particularly. On this basis, various investigations in Mg single crystals are carried out thoroughly in recent years, such as the critical resolved shear stress (CRSS) calculation, the slip and twinning modes activation determining, recrystallization behaviors and so on. In order to make clear the research advantages in Mg single crystals, a critical brief summary is conducted in this paper. Besides, various crystal plasticity finite element modeling (CPFEM) and electrochemical corrosion used in Mg single crystals are also reviewed. Finally, the current challenges and possible research directions are proposed.

To explore the effect of the precipitated phase particles and twins on the microstructure evolution and neutral layer evolution during bending, {10–12} tensile twins were introduced along the transverse direction (TD) on AZ80 Mg alloy sheets at room temperature. Then pre-compressed samples were aged to induce more precipitations. The reverse tensile tests were carried out at room temperature, and the three-point bending deformation was carried out at 100 °C. After aging treatment, precipitations increased. The results showed that twin crystals can promote precipitation formation. And the YS (yield strength) values of the pre-twinned aged samples were significantly larger than that before aging. During the bending process on the pre-compressed samples, the outside of the sample was dominated by the detwinning behaviors, while the inside region was dominated mainly by twinning. For pre-compressed bending samples, the k values were smaller than the initial bending sample. The tension and compression asymmetry in its inner and outer regions was weaker than that of the original bending sample. The existence of precipitations hindered the detwinning behaviors in outside the pre-twinning aged bending samples, and the twinning in inner region was restrained as well so that the inner and outer tension asymmetry decreased. The k values were smaller than that of the unaged samples, which was beneficial to weaken the bending springback of Mg alloy sheets.

The need for cancelable biometric techniques has seen a progressive rise due to the rapid deployment of biometric authentication systems. These techniques prevent compromising biometric data by generating and using their corresponding cancelable templates for user authentication. However, the non-invertible distance preserving transformation methods employed in various schemes are often vulnerable to information leakage since matching is performed in the transform domain. This paper proposed a non-invertible distance preserving scheme based on vector permutation and shift-order process. First, the dimension of feature vectors is reduced using kernelized principal component analysis before randomly permuting the extracted vector features. A shift-order process is then applied to the generated features to achieve non-invertibility and combat similarity correlation-based attacks. The generated hash codes are resilient to various security and privacy attacks such as ARM, masquerade, and brute-force preimage. Experimental evaluations conducted on eight fingerprint datasets from FVC2002, FVC2004, and FVC2006 reveal a high matching performance of the proposed method with better recognition accuracy than other existing state-of-the-art. The scheme also fulfills the revocability and unlinkability requirements of cancelable biometrics.

This article focuses on the design of a mode- dependent adaptive event-triggered control (AETC) scheme for the stabilization of Markovian memristor-based reaction–diffusion neural networks (RDNNs). Different from the existing works with completely known transition probabilities, partly unknown transition probabilities (PUTPs) are considered here. The switching conditions and values of memristive connection weights are all correlated with Markovian jumping. A mode-dependent AETC scheme is newly proposed, in which different adaptive event-triggered mechanisms will be applied for different Markovian jumping modes and memristor switching modes. For each given mode, the corresponding event-triggered mechanism can efficiently reduce the number of transmission signals by adaptively adjusting the threshold. Thus, the mode-dependent AETC scheme can effectively save the limited network communication resources for the considered system. Based on the proposed control scheme, a new stabilization criterion is set up for Markovian memristor-based RDNNs with PUTPs. Meanwhile, a memristor-dependent AETC scheme is devised for memristor-based RDNNs. Finally, simulation results are presented to verify the effectiveness and superiority of the analysis results.

Hematite (α-Fe2O3) is an ideal oxide semiconductor candidate for photoelectrochemical (PEC) water splitting. Doping of Fe2O3is known to benefit the PEC water oxidation efficiency, but despite extensive research efforts, the underlying mechanism still remains elusive. In this work, we report a comprehensive study on the relationship between the electronic structure, interfacial reaction kinetics and PEC activity of Ti-doped Fe2O3photoanodes. The results show that the interfacial charge transfer efficiency at the Fe2O3/electrolyte interface is the main factor in the significant increase of the PEC activity of doped Fe2O3. Electrochemical impedance spectroscopy reveals that the interfacial charge transfer efficiency is determined by energy overlap between the water oxidation potential and energy distribution of an intermediate surface state that has been identified as FeIV=O groups on Fe2O3surface generated during PEC process. Interestingly, the potential energy distribution of this intermediate surface state can be modulated by Ti doping, and a shift towards a more positive potential of the intermediate surface state increases the overlap with the water oxidation potential and thus enhances the kinetics of charge transfer for PEC water splitting. The origin of such potential energy modulation is traced to the inductive effect from Ti-doping on the Fe3+/Fe4+redox transition and the Fe-O bond covalency. Our results provide new insight into the mechanism for the doping effect on the PEC water splitting, introducing new strategies to optimize the PEC activity by tuning the redox properties of active metal oxides.

To solve the problem of internal surface cracking problem during equal channel angular pressing (ECAP), this study modified a conventional die. The dies before and after modification were compared and analyzed by using DEFORM-3D software. Finally, a modified ECAP die was manufactured to investigate the effect of different number of pressed passes on the microstructure and mechanical properties of the solution-treated Mg93.5Zn2.5Y2.5Mn1Ti0.5alloy. The results show that the volume fraction of dynamically-recrystallized grains continuously increases while the volume fraction of W phase continuously decreases with the increase of pressed passes. The size of recrystallized grains initially decreases and then increases, reaching the minimum after 6 pressing passes. The basal texture of (0002) initially decreases, then increases and finally decreases, and the basal texture of 6-pass pressed sample displays the strongest texture. The yield strength and tensile strength of the alloy increase initially and then decrease, while the elongation increases continuously. After 6 pressing passes, the alloy exhibits excellent comprehensive mechanical properties, with a yield strength of 251 MPa, a tensile strength of 340 MPa and an elongation of 26.1%.

Forming semiconductor heterojunctions is a promising strategy to boost the efficiency of solar-driven photoelectrochemical (PEC) water splitting by accelerating the separation and transport of photogenerated charge carriers via an interfacial electric field. However, there is limited research considering the influence of electrolytes on the band alignment of the heterojunction under PEC conditions. In this work, we use a single crystal NiCo2O4/SrTiO3(NCO/STO) heterojunction with atomic-precision controlled thickness as a model photoelectrode to study the band structure modulations upon getting in contact with the electrolyte and the correlation with the PEC activity. It is found that the band alignment can be tuned by the control of p–n heterojunction film thickness and regulated by the water redox potential (Eredox). When the Fermi level (EF) of the heterojunction is higher/lower than the Eredox, the band bending at the NCO/STO–electrolyte interface will increase/decrease after contacting with the electrolyte. However, when the band bending width of the NCO layer is thinner than its thickness, the electrolyte will not influence the band alignment at the NCO/STO interface. In addition, PEC characterization results show that the 1 nm NCO/STO heterojunction photoanode exhibits superior water-splitting performance, owing to the optimum band structure of the p–n heterojunction and the shorter charge transfer distance.

This study aimed to prepare collagen glycopeptides by transglutaminase-induced glycosylation and to explore their salt taste-enhancing effects and mechanism. Collagen glycopeptides were obtained by Flavourzyme-catalyzed hydrolysis, followed by transglutaminase-induced glycosylation. The salt taste-enhancing effects of collagen glycopeptides were evaluated by sensory evaluation and an electronic tongue. LC–MS/MS and molecular docking technologies were employed to investigate the underlying mechanism responsible for the salt taste-enhancing effect. The optimal conditions were 5 h for enzymatic hydrolysis, 3 h for enzymatic glycosylation, and 1.0% (E/S, w/w) for transglutaminase. The grafting degree of collagen glycopeptides was 26.9 mg/g, and the salt taste-enhancing rate was 59.0%. LC–MS/MS analysis revealed that Gln was the glycosylation modification site. Molecular docking confirmed that collagen glycopeptides can bind to salt taste receptors epithelial sodium channel protein and transient receptor potential vanilloid 1 through hydrogen bonds and hydrophobic interaction. Overall, collagen glycopeptides have a significant salt taste-enhancing effect, which contributes to the application of collagen glycopeptides for salt reduction without compromising taste in the food industry.

Gas turbine engines must be operated by means of control, and how to achieve multivariable control decoupling with aero-engine control constraints is an open thorny issue attracting increasingly more attention. The paper considers the multivariable decoupling problems of aero-engines by using a compound controller, which originates from the fact that it is impossible to eliminate all the nonlinear dynamics of system to obtain desired constant linear closed-loop system by using full actuated control because of modeling errors and some physical constraints. Two controllers are involved in the compound controller. One is a fully actuated controller and the other is classical feedback controller. In order to use fully actuated control and maintain the accuracy of engine model, a full state scheduling linear parameter-varying (LPV) modeling method is proposed based on fuzzy neural network weights. For a general input matrix of the system, its generalized inverse is applied to design fully actuated controller to result in a pseudolinear system. Combined with a feedback controller and control limiter, the control synthesis is achieved. The simulation shows that the proposed method is possessed of a better decoupling and tracking effect compared with traditional control approach.