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Background: The exact cause of intracranial aneurysms (IA) is still unclear. However, pro‐inflammatory factors are known to contribute to IA progression. The specific changes in the immune microenvironment of IAs remain largely unexplored. Methods: This study analyzed single‐cell sequencing data from a male mouse model of brain aneurysm, focusing on samples before and after elastase‐induced Willis aneurysms. The data helped identify eight distinct cell subpopulations: fibroblasts, macrophages, NK cells, endothelial cells, B cells, granulocytes, and monocytes. The study also involved bulk RNA sequencing of 97 IA samples, utilizing ssGSEA and CIBERSORT algorithms for analysis. Intercellular communication among these cells was inferred to understand the immune dynamics in IA. Results: The study found that fibroblasts and macrophages are predominant in various disease states of IA. Notably, the onset of IA was marked by a significant increase in fibroblasts and a decrease in macrophages. There was a marked increase in cellular interactions, especially involving macrophages, at the onset of the disease. Through enrichment analysis, 12 potential immunogenic biomarkers were identified. Of these, Rgs1 emerged as a critical molecule in IA formation, confirmed through secondary validation in a single‐cell sequencing dataset. Conclusion: This comprehensive analysis of immune cell composition and intercellular communication in IA tissues highlights the significant roles of macrophages and the molecule Rgs1. These findings shed light on the physiological and pathological conditions of IA, offering new insights into its immune microenvironment. [ABSTRACT FROM AUTHOR]

When a laser beam writes on a metallic film, it usually coarsens and deuniformizes grains because of Ostwald ripening, similar to the case of annealing. Here we show an anomalous refinement effect of metal grains: A metallic silver film with large grains melts and breaks into uniform, close-packed, and ultrafine (∼ 10 nm) grains by laser direct writing with a nanoscale laser spot size and nanosecond pulse that causes localized heating and adaptive shock-cooling. This method exhibits high controllability in both grain size and uniformity, which lies in a linear relationship between the film thickness (h) and grain size (D), D ∝ h. The linear relationship is significantly different from the classical spinodal dewetting theory obeying a nonlinear relationship (D ∝ h5/3) in common laser heating. We also demonstrate the application of such a silver film with a grain size of ∼ 10.9 nm as a surface-enhanced Raman scattering chip, exhibiting superhigh spatial-uniformity and low detection limit down to 10−15 M. This anomalous refinement effect is general and can be extended to many other metallic films. [ABSTRACT FROM AUTHOR]

The edaravone and dexborneol concentrated solution for injection (edaravone-dexborneol) is a medication used clinically to treat neurological impairment induced by ischemic stroke. This study was aimed at investigating the preventive effects and the underlying mechanisms of edaravone-dexborneol on cerebral ischemic injury. A rat four-vessel occlusion (4-VO) model was established, and the neuronal injury and consequent neurological impairment of rats was investigated. Brain tissue malondialdehyde (MDA), myeloperoxidase (MPO), and nitric oxide (NO) levels were determined. The levels of proteins in mitogen-activated protein kinases (MAPKs), nuclear factor erythroid 2-related factor 2 (Nrf2), and nuclear factor-κB (NF-κB) signaling pathways were determined by western immunoblotting. The function of mitogen-activated protein kinase phosphatase 1 (MKP-1) was investigated using both western blot and immunofluorescence methods, and the effect of the MKP-1 inhibitor, (2E)-2-benzylidene-3-(cyclohexylamino)-3H-inden-1-one (BCI), was investigated. The results indicated that edaravone-dexborneol alleviated neurological deficiency symptoms and decreased apoptosis and neuron damage in the hippocampal CA1 area of the ischemic rats. Edaravone-dexborneol increased the MKP-1 level; decreased the phosphorylation of extracellular signal-regulated kinase (ERK), c-Jun N-terminal kinase (JNK), and p38 mitogen-activated protein kinase (p38 MAPK); inhibited NF-κB p65 activation; and boosted Nrf2 activation, all of which were partially reversed by the MKP-1 inhibitor, BCI. The above results indicated that the upregulation of MKP-1 contributed to the protective effects of edaravone-dexborneol against ischemic brain injury. Our findings support the hypothesis that edaravone-dexborneol can alleviate cerebral ischemic injury via the upregulation of MKP-1, which inhibits MAPKs and activates Nrf2. [ABSTRACT FROM AUTHOR]

To realize high azimuth resolution for sea-surface targets, this article proposes a superresolution imaging method that relies on the Weibull distribution. The proposed method introduces the generalized Gaussian distribution and Weibull distribution to represent the statistical distribution function of the target prior information and sea clutter, respectively. The corresponding objective function was derived under the maximum a posteriori (MAP) criterion. To address the nonlinearity of the objective function, this article adopts the Newton–Raphson iterative method to resolve it. Simulations and experimental data assessment indicate that the proposed method has superior superresolution imaging performance compared with other traditional superresolution methods for sea-surface target imaging. [ABSTRACT FROM AUTHOR]

Echoes of bistatic forward-looking synthetic aperture radar (BFSAR) disperse to multiple range cells and exist spatial frequency extension as well as Doppler spectrum extension (i.e., namely space–time extension). Furthermore, the characteristics of BFSAR clutter are strongly nonstationary and spatial variants. Because of the abovementioned issues, clutter and moving targets are fully overlapped in the initial 3-D space–time–range raw data domain, and the clutter cannot be suppressed effectively. To solve this problem, a BFSAR multipulse displaced phase center antenna (MP-DPCA) method is proposed in this article. First, keystone transform without Doppler ambiguity is applied to remove the coupling between the space–time and range domains. Hence, the overall complex 3-D processing in the space–time–range domain is reduced to independent 2-D processing in each space–time domain. Subsequently, a spatial-dechirp processing is applied in the space–time domain to eliminate the spatial frequency extension. Meanwhile, Doppler parameters of clutter point scatterers are equalized by nonlinear chirp scaling processing in the frequency and time domains. Accordingly, the Doppler spectrum extension of point scatterers can be eliminated by a uniform azimuth dechirp processing. After aforesaid three steps, the clutter and moving targets are separated in the space–time domain. Finally, based on the linear phase difference of clutter between the channels, a multipulse canceller can be designed to suppress the clutter. Compared with the existing space–time adaptive procession (STAP) and DPCA methods, this method not only overcomes the nonstationary problem in BFSAR but also conquers the strict application conditions of DPCA. Simulation results are given to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Mangiferin is a compound with many pharmacological activities and exists in many natural products. Anhydrous and hydrate of mangiferin have been reported separately in two literatures, but the polymorphism of this compound has not been realized until this paper. In this study, polymorph screening of mangiferin has been carried out and five forms have been obtained including three new forms never reported. Several solid state characterization methods, such as powder X-ray diffraction, differential scanning calorimetry and thermogravimetry, are used to identify and characterize all of mangiferin forms. The comparison of the crystallographic data and hirshfeld surface analysis were first reported for mangiferin anhydrous and hydrate. Furthermore, the studies on stability, transformation and solubility have been undertaken, the results prompt that form V can be used as the dominant polymorph for the development of innovative pharmaceuticals. [ABSTRACT FROM AUTHOR]

Compared with a conventional CMOS-based optoelectronic system, two-dimensional (2D) material-based nonvolatile optoelectronic memory has attracted increasing attention because of its ability to rapidly transform optoelectronic signals, as well as simultaneously store and output signals. However, existing two-dimensional optoelectronic memory cannot meet requirements in performance and cost and so on, and needs urgently to be explored. Here we developed a high-performance nonvolatile MoS2-based optoelectronic memory device based on a MoS2 bilayer grown by a Au catalyst. The device exhibits an excellent performance index of current on/off ratio ∼8 × 104 and retention time ∼2.2 × 104 s. Experimental observations and simulation calculations have revealed that the optoelectronic memory mechanism can be ascribed to defects including S vacancies and disorder of atoms in 2D MoS2 materials. [ABSTRACT FROM AUTHOR]

A bistatic forward-looking synthetic aperture radar (BFSAR) is increasingly in the focus of study, as it breaks through the limitations of imaging on a forward-looking terrain of a moving platform. Fast factorized backprojection (FFBP) is a reliable BFSAR imaging algorithm, with both imaging precision and efficiency being taken into consideration. In FFBP imaging, compensation of the motion errors is important to obtain a well-focused image. To accomplish an accurate motion compensation in image processing, a high-precision navigation system is needed. However, in many cases, because of the accuracy limit of such systems, motion errors are difficult to be compensated correctly, resulting chiefly in resolution decrease in the final images. To deal with such a problem, we propose an FFBP imaging algorithm integrated with motion trajectory estimation for BFSAR. First, a coarse-to-fine residual range cell migration (RCM) correction scheme is applied to ensure the residual RCM within a range resolution. Then, an optimization model with respect to motion trajectory estimation under the criterion of maximum image sharpness is built during FFBP imaging. According to the coarse-to-fine residual RCM correction scheme and the motion trajectory estimation model, a block coordinate descent technique based on steepest descent optimization method integrated with residual RCM correction is proposed to estimate the motion errors in FFBP imaging. We empirically compare the proposed method with several state-of-the-art BFSAR imaging and autofocus algorithms. Simulations on BFSAR data show that the proposed method is more accurate and has similar computational cost. [ABSTRACT FROM AUTHOR]

Geosynchronous (GEO) spaceborne–airborne multistatic synthetic aperture radar (GEO MulSAR) is more flexible and accessible in remote sensing applications because of the high-altitude illuminator and the separation of the receivers and transmitter. In addition, the information obtained by the multiple airborne receivers can be fused to enhance the spatial resolution. However, the fused spatial resolution severely depends on the applied multistatic topology. To achieve the optimal fused spatial resolution by properly adjusting the imaging topology, a topology design method is proposed in this letter. First, the spatial resolution model of GEO MulSAR is given, and the dependence of the spatial resolution on the multistatic topology is analyzed in detail. Then, a topology design method is proposed to obtain the best multistatic topology that simultaneously optimizes the resolution cell area and resolution disequilibrium factor. Finally, the simulation results validate the effectiveness of the proposed method, and some insights into designing the multistatic topology are given. [ABSTRACT FROM AUTHOR]

In general, autofocus methods integrated with frequency-domain imaging algorithms are instrumental to obtain a well-focused bistatic forward-looking synthetic aperture radar (BFSAR) image in the presence of motion errors. Nevertheless, before applying autofocus methods to correct the azimuth phase errors, range cell migration (RCM) should be eliminated by the RCM correction (RCMC) procedure in frequency-domain imaging algorithms. With motion errors being taken into account, there always exists some residual nonsystematic RCM (NsRCM), which refers to the residual migration components after the RCMC procedure. For the conventional side-looking SAR, NsRCM is caused by motion errors. On the other hand, NsRCM of BFSAR is originated from motion errors before RCMC and the NsRCM amplified by the RCMC procedure. In this paper, we analyze the different types of NsRCM in BFSAR imaging and their relationship. Based on the analyses, we propose an autofocus NsRCM correction scheme for BFSAR imagery using frequency-domain imaging algorithms that can eliminate the range-dependent NsRCM. The proposed scheme consists of three steps. First, for the BFSAR data after range compression and RCMC, a division procedure is carried out in the azimuth direction. The subblocks with the highest signal-to-clutter ratio along the range direction are selected after the azimuth segmentation procedure. Second, for the selected subblocks, the total NsRCM is estimated based on the minimum-entropy criterion. Based on the estimation results, different parts of the NsRCM are obtained by solving an ordinary differential equation. Third, a two-step compensation of the NsRCM is executed to reach the spatially variant correction. Simulations and experimental results are provided to demonstrate that our proposed scheme is effective for BFSAR imaging. [ABSTRACT FROM AUTHOR]

Bistatic synthetic aperture radar (SAR) is able to break through the limitation of monostatic SAR on forward-looking area imaging with appropriate geometry configurations. Thanks to such an ability, bistatic forward-looking SAR (BFSAR) has extensive potential practical applications. For the focusing problem of conventional side-looking SAR, $\omega\hbox{--}k$ algorithm is accepted as the ideal solution. In this paper, the $\omega\hbox{--}k$ algorithm will be discussed in BFSAR geometry. As for the bistatic configuration, spatial domain linearization procedure should be carried out to extract a range variable from the point target reference spectrum (PTRS) in the existing $\omega\hbox{--}k$ algorithms. With respect to the BFSAR geometry, nevertheless, the linearization procedure reduces the accuracy of PTRS seriously. To cope with such a problem, a novel $\omega\hbox{--}k$ algorithm for BFSAR is proposed. In the proposed method, the range variable is modeled as a parameterized polynomial, and the corresponding PTRS with respect to two-dimensional frequencies is established. Then, the parameters are estimated by differential evolution to minimize the PTRS errors for each range coordinate and frequency point. Based on the estimated PTRS, the BFSAR data can be focused well by the proposed $\omega\hbox{--}k$ algorithm. Simulation results verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In synthetic aperture radar (SAR) imagery, images of ground moving targets (GMTs) are smeared, distorted, and shifted. Current GMT imaging methods are mostly based on range-Doppler algorithms, which have two main drawbacks: 1) coupling between range cell migration correction (RCMC) and Doppler parameter estimation and 2) cross terms degrade the performance of the nonlinear estimation methods. In this paper, an optimal 2-D spectrum matching method for SAR GMT imaging is proposed. The main innovation or advantage of this method is that the GMT imaging problem is transformed into a constrained optimization problem, and differential evolution is applied to guarantee a high-processing efficiency. As they are associated with the Doppler centroid variation compensation and range shift compensation processing, all GMT point scatterers can be well focused and well located. Compared with the current methods, the improvements exhibited by this method include three main benefits: 1) RCMC and Doppler parameter estimation can be simultaneously accomplished; 2) both along- and cross-track GMT velocities can be simultaneously estimated; and 3) this method can be applied to both monostatic and bistatic SARs. Numerical simulations and experimental data processing have verified the effectiveness and robustness of the proposed method. [ABSTRACT FROM AUTHOR]

Bistatic forward-looking synthetic aperture radar (BFSAR) is a kind of bistatic SAR system that can image forward-looking terrain in the flight direction of a moving platform. In BFSAR, compensation of the flight trajectory errors is of great significance to get a well-focused image. To accomplish an accurate motion compensation in image processing, a high-precision navigation system is needed. However, in many cases, due to the accuracy limit of such systems, flight trajectory errors are hard to be compensated correctly, causing mainly the resolution decrease in final images. In order to cope with such a problem, we propose a rise-dimensional modeling and estimation for flight trajectory error based on raw BFSAR data in this paper. To apply this method, we first carry out a preprocessing named azimuth-slowtime decoupling to deal with the spatially variant flight trajectory error before estimation. Then, an optimization model for flight trajectory estimation under the criterion of maximum image intensity is built. The solution to the optimization model is the accurate flight trajectory. Then, block coordinate descent technique is used to solve this optimization model. The processing of BFSAR data shows that the algorithm can obtain a more accurate estimation results, and generate better focused images compared with the existing trajectory estimation method. [ABSTRACT FROM PUBLISHER]

In bistatic forward-looking synthetic aperture radar (BFSAR), conventional autofocus algorithms cannot estimate the phase errors accurately when the range walk is compensated in the azimuthal time domain. This problem stems from the influence of the azimuth-variant Doppler coefficients after linear range cell migration correction in azimuthal time domain. In principle, nonlinear chirp scaling processing can be carried out to remove the azimuth variance. Nevertheless, Doppler azimuth variations of the Doppler parameters induced by the motion errors are not taken into consideration and serious defocus would emerge in the final image. To cope with such a problem, an estimation–evaluation–equalization scheme is proposed before conventional autofocus for BFSAR. Different from the conventional autofocus method, the azimuth-variant Doppler coefficients are additionally estimated and equalized before autofocus, and as a consequence, phase errors can be precisely estimated. The BFSAR data processing results demonstrate the validity of the proposed method on the improvement of autofocus in BFSAR. [ABSTRACT FROM PUBLISHER]

With appropriate geometry configurations, bistatic synthetic aperture radar (SAR) can break through the limitations of monostatic SAR on forward-looking imaging. Owing to such a capability, bistatic forward-looking SAR (BFSAR) has extensive potential applications. In BFSAR, the compensation of the spatially variant motion errors is of great significance to get a well-focused image. In this paper, first, the spatial-variance properties of motion errors are analyzed analytically and quantitatively. Different from the side-looking monostatic and bistatic SAR, 2-D space-variant motion errors should be taken into consideration in BFSAR. The 2-D spatial variance of the motion errors can be categorized into two parts, range-variant motion errors of the transmitter and azimuth-variant motion errors of the receiver. Moreover, these two parts are independent of each other. Based on this property analysis, second, a motion compensation (MoCo) approach with cubic-order processing is proposed to deal with the spatially variant motion errors in BFSAR. In the cubic-order processing, the first-order MoCo is performed to correct the spatially independent motion errors on the raw data. The second-order MoCo is accomplished on the non-range-cell-migration (RCM) data to deal with the range-variant errors. After the second-order MoCo, since the signal direction of the non-RCM data coincides with the variant direction of the uncompensated phase errors, the azimuth-variant motion errors and slow time signal are coupled together. To cope with such a problem, the slow time signal is transformed into the direction perpendicular to the azimuth by a novel procedure named azimuth–slow time decoupling. At this stage, the coupling between the azimuth-variant motion errors and slow time signal has been eliminated. Azimuth-variant motion errors can be corrected precisely. Simulation and experimental results verify the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]

Synthetic aperture radar (SAR) is an important microwave sensor that is capable of high-resolution imaging. Extracting valuable features from the SAR target imagery is one of crucial issues in SAR automatic target recognition (ATR). In this paper, we propose a new feature extraction method named 2-D principal-component-analysis-based 2-D neighborhood virtual points discriminant embedding (2DPCA-based 2DNVPDE) for SAR ATR. The SAR imagery is projected into the feature space by 2DPCA and 2DNVPDE in this approach. 2DPCA is able to preserve the global spatial structure of the original imagery, while 2DNVPDE establishes the spatial relationships of the neighborhoods to find the classification information from the neighborhoods of the samples. Hence, our method can extract powerful recognition information and represent the original image in low dimensions. Based on the MSTAR dataset, the experimental results show that the proposed method is able to achieve a higher recognition rate with a lower feature dimension over some existing SAR imagery feature extraction methods. Besides, it indicates that our method has a significant advantage in recognition performance and a lower sensitivity in statistical standpoint. [ABSTRACT FROM PUBLISHER]

Background/Aims: Diabetes mellitus (DM) characterized by hyperglycemia contributes to macrovascular and microvascular complications. Salvianolic acid A (SalA) is a polyphenolic compound isolated from the root of Salvia miltiorrhiza Bunge, which is a traditional Chinese medicine widely used to treat cardiovascular diseases. However, little is known about its antidiabetic effect. Our study aimed to investigate the in vivo and in vitro antidiabetic effect of SalA and the underlying mechanisms. Methods: Alloxan-induced type 1 diabetic mice and high-fat diet (HFD) and low-dose streptozotocin (STZ)-induced type 2 diabetic rats received SalA treatment. Blood glucose, oral glucose tolerance test (OGTT), 24-h food and water intake were monitored. In vitro, glucose consumption and uptake were measured in HepG2 cells and L6 myotubes. Mitochondrial function was detected in hepatic and skeletal muscle mitochondria. AMP-activated protein kinase (AMPK) and Akt were analyzed by western blot. Results: In both type 1 and type 2 diabetic animals, SalA lowered fasting blood glucose (FBG) and fed blood glucose in dose-dependent manner, as well as reduced 24-h food and water intake. In vitro, SalA caused dose-dependent increase in glucose consumption and enhanced glucose uptake. SalA significantly increased ATP production from 10 min to 12 h in HepG2 cells and L6 myotubes. Interestingly, SalA decreased mitochondrial membrane potential (MMP) in HepG2 cells. Furthermore, SalA improved hepatic and skeletal muscle mitochondrial function, increased ATP production, and concurrently decreased MMP. In particularly, SalA activated AMPK phosphorylation through Ca2+/calmodulin-dependent protein kinase kinase β (CaMKKβ)/AMPK signaling pathway, independent of liver kinase 1 (LKB1)/AMPK pathway. However, SalA didn't show any effect on insulin secretagogue and activation of PI3K/Akt signaling pathway. Conclusion: SalA exhibits the antidiabetic effects in diabetic animal models through improving mitochondrial function, increasing ATP production, and decreasing MMP via CaMKKβ/AMPK signaling pathway. © 2015 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Type 2 diabetes patients have an increased risk of developing hepatic fibrosis. Salvianolic acid A (SalA) has been reported to be a strong polyphenolic anti-oxidant and free radical scavenger. The aim of the present study was to evaluate the effect of SalA on the pathological progression of hepatic fibrosis in high-fat diet (HFD)-fed and streptozotocin (STZ)-induced diabetic rats and to clarify the underlying mechanisms. Type 2 diabetic animal model with hepatic fibrosis was developed by a high-sucrose, HFD and low-dose STZ injection (i.p.). Diabetic rats were randomly divided into SalA group (0.3 mg/kg/day) and diabetic control groups fed with a HFD. After administration for four months, SalA reversed the hyperlipidemia and reduced hepatic triglyceride (TG). Hematoxylin-Eosin (HE) and Picro acid-Sirius red staining results indicated that SalA significantly alleviated the lesions of hepatic steatosis and fibrosis, with the reduction of type I and III collagens. The expression of α-smooth-muscle-actin (α-SMA) and transforming growth factor β1 (TGF-β1) in the liver were markedly down-regulated by SalA treatment. TUNEL staining showed that SalA reduced apoptosis in hepatocytes. In addition, SalA improved hepatic mitochondrial respiratory function in diabetic rats. Taken together, these findings demonstrated that SalA could prevent the pathological progression of hepatic fibrosis in HFD-fed and STZ-induced diabetic rats. The underlying mechanisms may be involved in reducing oxidative stress, suppressing α-SMA and TGF-β1 expression, as well as exerting anti-apoptotic and mitochondria-protective effects. [ABSTRACT FROM AUTHOR]

With appropriate geometry configurations, bistatic synthetic aperture radar (SAR) can break through the limitations of monostatic SAR on forward-looking imaging. Thanks to such a capability, bistatic forward-looking SAR (BFSAR) has extensive potential applications, such as self-navigation and self-landing. In the mode of BFSAR with a stationary transmitter (ST-BFSAR), the two-dimensional spatial variation makes it difficult to use traditional data focusing algorithms. In this letter, an imaging algorithm based on keystone transform and nonlinear chirp scaling (NLCS) is proposed to deal with this problem. Keystone transform is used to remove the spatial variation of range cell migration. NLCS can eliminate the variation of azimuth reference function. Numerical simulations show that by combining first-order keystone transform and azimuth NLCS operation, the raw data of ST-BFSAR can be well imaged. [ABSTRACT FROM PUBLISHER]

Lentivectors (LVs) have attracted considerable interest for their potential as a vaccine delivery vehicle. In this study, we evaluate in mice a dendritic cell (DC)-directed LV system encoding the Gag protein of human immunodeficiency virus (HIV) (LV-Gag) as a potential vaccine for inducing an anti-HIV immune response. The DC-directed specificity is achieved through pseudotyping the vector with an engineered Sindbis virus glycoprotein capable of selectively binding to the DC-SIGN protein. A single immunization by this vector induces a durable HIV Gag-specific immune response. We investigated the antigen-specific immunity and T-ceIl memory generated by a prime/boost vaccine regimen delivered by either successive LV-Gag injections or a DNA prime/LV-Gag boost protocol. We found that both prime/boost regimens significantly enhance cellular and humoral immune responses. Importantly, a heterologous DNA prime/LV-Gag boost regimen results in superior Gag-specific T-cell responses as compared with a DNA prime/adenovector boost immunization. It induces not only a higher magnitude response, as measured by Gag-specific tetramer analysis and intracellular IFN-7 staining, but also a better quality of response evidenced by a wider mix of cytokines produced by the Gag-specific CD8+ and CD4+ T cells. A boosting immunization with LV-Gag also generates T cells reactive to a broader range of Gag-derived epitopes. These results demonstrate that this DC-directed LV immunization is a potent modality for eliciting anti-HIV immune responses. [ABSTRACT FROM AUTHOR]

Drug combinations have been the hotspot of the pharmaceutical industry, but the promising applications are limited by the unmet solubility and low bioavailability. In this work, novel cocrystals, consisting of two antithrombotic drugs with poor solubility and low bioavailability in vivo, namely, apixaban (Apx) and quercetin (Que), were developed to discover a potential method to improve the poor solubility and internal absorption of the drug combination. Compared with Apx, the dissolution behavior of Apx–Que (1:1) and Apx–Que–2ACN (1:1:2) was enhanced significantly, while the physical mixture of the chemicals failed to exhibit the advantages. The dissolution improvements of Apx–Que–2ACN could be explained by the fact that the solid dispersion-like structure and column-shaped cage of Que accelerated the access of the solvent to the inner layer of Apx. The fracture of the hydrogen bonds of Apx, which was the joint of the adjacent Que chains, facilitated the break-up of the structures. Besides, the bioavailability of Apx–Que was increased compared with the physical mixture and Apx, and Apx–Que remained stable in high temperature and illumination conditions. Therefore, a drug–drug cocrystal of two antithrombotic agents with poor solubility was developed, which exhibited greatly improved solubility, bioavailability and superior stability, indicating a novel method to overcome the shortages of drug combination. [ABSTRACT FROM AUTHOR]

With the recent advances of deep learning, automatic target recognition (ATR) of synthetic aperture radar (SAR) has achieved superior performance. By not being limited to the target category, the SAR ATR system could benefit from the simultaneous extraction of multifarious target attributes. In this paper, we propose a new multi-task learning approach for SAR ATR, which could obtain the accurate category and precise shape of the targets simultaneously. By introducing deep learning theory into multi-task learning, we first propose a novel multi-task deep learning framework with two main structures: encoder and decoder. The encoder is constructed to extract sufficient image features in different scales for the decoder, while the decoder is a tasks-specific structure which employs these extracted features adaptively and optimally to meet the different feature demands of the recognition and segmentation. Therefore, the proposed framework has the ability to achieve superior recognition and segmentation performance. Based on the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset, experimental results show the superiority of the proposed framework in terms of recognition and segmentation. [ABSTRACT FROM AUTHOR]

Correction for 'High-performance optoelectronic memory based on bilayer MoS2 grown by Au catalyst' by Fengyou Yang et al., J. Mater. Chem. C, 2020, 8, 2664–2668. [ABSTRACT FROM AUTHOR]