Recently, deep convolutional neural networks (CNNs) have been demonstrated remarkable progress on single image super-resolution. However, as the depth and width of the networks increase, CNN-based ...super-resolution methods have been faced with the challenges of computational complexity and memory consumption in practice. In order to solve the above questions, we propose a deep but compact convolutional network to directly reconstruct the high resolution image from the original low resolution image. In general, the proposed model consists of three parts, which are feature extraction block, stacked information distillation blocks and reconstruction block respectively. By combining an enhancement unit with a compression unit into a distillation block, the local long and short-path features can be effectively extracted. Specifically, the proposed enhancement unit mixes together two different types of features and the compression unit distills more useful information for the sequential blocks. In addition, the proposed network has the advantage of fast execution due to the comparatively few numbers of filters per layer and the use of group convolution. Experimental results demonstrate that the proposed method is superior to the state-of-the-art methods, especially in terms of time performance. Code is available at https://github.com/Zheng222/IDN-Caffe.
Flexible floating‐gate organic transistor memory (FGOTM) is a potential candidate for emerging memory technologies. Unfortunately, conventional planar FGOTM suffers from weak driving ability and ...insufficient mechanical flexibility, which limits its commercial application. In this work, a novel flexible vertical FGOTM (VFGOTM) is reported. Benefitting from new vertical architecture, VFGOTM provides ultrashort channel length to afford an extremely high current density. Meanwhile, VFGOTM devices exhibit excellent memory performance and outstanding retention property. The memory properties of VFGOTM devices are comparable or even better than traditional planar FGOTM and much better than the reported organic nonvolatile memory with vertical transistor structures. More importantly, organic nonvolatile memory with vertical transistor structures is investigated for the first time on a flexible substrate. The results show that VFGOTM architecture allows vertical current flow across the channel layer to effectively eliminate the effect of mechanical bending during current transport, which significantly improves the mechanical stability of the flexible VFGOTM. Hence, with a combination of excellent driving ability, memory performance, and mechanical stability, VFGOTM devices meet the practical requirements for high performance memory applications, which have great potential for the application in a wide range of flexible and wearable electronics.
A novel vertical‐architecture, floating‐gate organic transistor memory fabricated on a flexible substrate is reported. The unique vertical architecture enables memory devices with ultrashort channel length, which provides a large current density (excellent driving ability), fast operation, and mechanical stability, showing great potential for the application in a wide range of flexible and wearable electronic applications.
► The inhibitive action of 1,8-bis (1-chlorobenzyl-benzimidazolyl)-octane for mild steel in different concentration HCl solution was studied by weight loss, electrochemical methods and SEM. The ...following principle conclusions can be deduced: ► The corrosion of mild steel in HCl medium is effectively reduced by the addition of CBO. ► The compound acts as a mixed-type inhibitor and obeys Langmuir adsorption isotherm. ► Cl
− plays an interconnecting bridge role between steel surface and cationic inhibitor. ► The inhibitor has excellent inhibiting properties in HCl solution.
The influences of a benzimidazole derivative, namely 1,8-bis (1-chlorobenzyl-benzimidazolyl) -octane (CBO) on the corrosion behaviour of mild steel in different concentration HCl solutions were studied by weight loss, potentiodynamic polarization, electrochemical impedance spectroscopy (EIS) measurements and SEM observations. The results showed that CBO acted as an excellent and a mixed-type inhibitor via strongly chemical adsorption onto mild steel surface to suppress simultaneously both anodic and cathodic processes according to the Langmuir adsorption isotherm. Inhibition efficiencies increased with increasing concentration of inhibitor and HCl. An inhibition mechanism was proposed in terms of strongly adsorption of inhibitor molecules on mild steel surface.
No pharmacological treatment is currently available to protect brain from neuronal damage after ischemic stroke. Recent studies found that enkephalin may play an important role in neuron ...regeneration. We assembled a homogeneous size vesicle constituted by transferrin, exosomes, and enkephalin. Immunofluorescence assay showed that transferrin was combined with the exosomes and enkephalin was packaged into the vesicle; thus this complex was called tar-exo-enkephalin. In vitro studies were performed using rat primary hippocampal neurons and the results showed that enkephalin decreased p53 and caspase-3 levels to 47.6% and 67.2%, respectively, compared to neurons treated with glutamate, thus inhibiting neuron apoptosis caused by glutamate. An in vivo experiment in rats was also carried out using a transient middle cerebral artery occlusion (tMCAO)/reperfusion model and tar-exo-enkephalin treatment was performed after tMCAO. The results showed that tar-exo-enkephalin crossed the blood brain barrier (BBB) and decreased the levels of LDH, p53, caspase-3, and NO by 41.9, 52.6, 45.5, and 57.9% compared to the tMCAO rats, respectively. In addition, tar-exo-enkephalin improved brain neuron density and neurological score after tMCAO. These findings suggest that the use of exogenous enkephalin might promote neurological recovery after stroke.
Multimodal hashing, which conducts effective and efficient nearest neighbor search across heterogeneous data on large-scale multimedia databases, has been attracting increasing interest, given the ...explosive growth of multimedia content on the Internet. Recent multimodal hashing research mainly aims at learning the compact binary codes to preserve semantic information given by labels. The overwhelming majority of these methods are similarity preserving approaches which approximate pairwise similarity matrix with Hamming distances between the to-be-learnt binary hash codes. However, these methods ignore the discriminative property in hash learning process, which results in hash codes from different classes undistinguished, and therefore reduces the accuracy and robustness for the nearest neighbor search. To this end, we present a novel multimodal hashing method, named multimodal discriminative binary embedding (MDBE), which focuses on learning discriminative hash codes. First, the proposed method formulates the hash function learning in terms of classification, where the binary codes generated by the learned hash functions are expected to be discriminative. And then, it exploits the label information to discover the shared structures inside heterogeneous data. Finally, the learned structures are preserved for hash codes to produce similar binary codes in the same class. Hence, the proposed MDBE can preserve both discriminability and similarity for hash codes, and will enhance retrieval accuracy. Thorough experiments on benchmark data sets demonstrate that the proposed method achieves excellent accuracy and competitive computational efficiency compared with the state-of-the-art methods for large-scale cross-modal retrieval task.
As is well known, nonnegative matrix factorization (NMF) is a popular nonnegative dimensionality reduction method which has been widely used in computer vision, document clustering, and image ...analysis. However, traditional NMF is an unsupervised learning mode which cannot fully utilize the priori or supervised information. To this end, semi-supervised NMF methods have been proposed by incorporating the given supervised information. Nevertheless, when little supervised information is available, the improved performance will be limited. To effectively utilize the limited supervised information, this paper proposed a novel semi-supervised NMF method (CPSNMF) with pairwise constraints. The method propagates both the must-link and cannot-link constraints from the constrained samples to unconstrained samples, so that we can get the constraint information of the entire data set. Then, this information is reflected to the adjustment of data weight matrix. Finally, the weight matrix is incorporated as a regularization term to the NMF objective function. Therefore, the proposed method can fully utilize the constraint information to keep the geometry of the data distribution. Furthermore, the proposed CPSNMF is explored with two formulations and corresponding update rules are provided to solve the optimization problems. Thorough experiments on standard databases show the superior performance of the proposed method.
Few effective therapeutic options are available for treating severe infections caused by extensively drug-resistant Acinetobacter baumannii (XDR-AB). Using a murine thigh-infection model, we examined ...the in vivo efficacy of colistin in combination with meropenem, tigecycline, fosfomycin, fusidic acid, rifampin, or sulbactam against 12 XDR-AB strains. Colistin, tigecycline, rifampin, and sulbactam monotherapy significantly decreased bacterial counts in murine thigh infections compared with those observed in control mice receiving no treatment. Colistin was the most effective agent tested, displaying bactericidal activity against 91.7% of strains at 48 h post-treatment. With strains showing a relatively low minimum inhibitory concentration (MIC) for meropenem (MIC ≤ 32 mg/L), combination therapy with colistin plus meropenem caused synergistic inhibition at both 24 h and 48 h post-treatment. However, when the meropenem MIC was ≥64 mg/L, meropenem did not significantly alter the efficacy of colistin. The addition of rifampin and fusidic acid significantly improved the efficacy of colistin, showing a synergistic effect in 100% and 58.3% of strains after 24 h of treatment, respectively, while the addition of tigecycline, fosfomycin, or sulbactam did not show obvious synergistic activity. No clear differences in activities were observed between colistin-rifampin and colistin-fusidic acid combination therapy with most strains. Overall, our in vivo study showed that administering colistin in combination with rifampin or fusidic acid is more efficacious in treating XDR-AB infections than other combinations. The colistin-meropenem combination may be another appropriate option if the MIC is ≤32 mg/L. Further clinical studies are urgently needed to confirm the relevance of these findings.
Devices with sensing-memory-computing capability for the detection, recognition and memorization of real time sensory information could simplify data conversion, transmission, storage, and operations ...between different blocks in conventional chips, which are invaluable and sought-after to offer critical benefits of accomplishing diverse functions, simple design, and efficient computing simultaneously in the internet of things (IOT) era. Here, we develop a self-powered vertical tribo-transistor (VTT) based on MXenes for multi-sensing-memory-computing function and multi-task emotion recognition, which integrates triboelectric nanogenerator (TENG) and transistor in a single device with the simple configuration of vertical organic field effect transistor (VOFET). The tribo-potential is found to be able to tune ionic migration in insulating layer and Schottky barrier height at the MXene/semiconductor interface, and thus modulate the conductive channel between MXene and drain electrode. Meanwhile, the sensing sensitivity can be significantly improved by 711 times over the single TENG device, and the VTT exhibits excellent multi-sensing-memory-computing function. Importantly, based on this function, the multi-sensing integration and multi-model emotion recognition are constructed, which improves the emotion recognition accuracy up to 94.05% with reliability. This simple structure and self-powered VTT device exhibits high sensitivity, high efficiency and high accuracy, which provides application prospects in future human-mechanical interaction, IOT and high-level intelligence.
Abstract We investigate the emergence of unconventional corner mode in a two-dimensional (2D) topolectrical circuits induced by asymmetric couplings. The non-Hermitian skin effect of two kinked ...one-dimensional (1D) lattices with multiple asymmetric couplings are explored. Then we extend to the 2D model, derive conditions for the non-Hermitian hybrid skin effect and show how the corner modes are formed by non-reciprocal pumping based on 1D topological modes. We provide explicit electrical circuit setups for realizing our observations via realistic LTspice simulation. Moreover, we show the time varying behaviors of voltage distributions to confirm our results. Our study may help to extend the knowledge on building the topological corner modes in the non-Hermitian presence.
A class of self-assembling peptide nanofiber scaffolds has been shown to be an excellent biological material for 3-dimension cell culture and stimulating cell migration into the scaffold, as well as ...for repairing tissue defects in animals. We report here the development of several peptide nanofiber scaffolds designed specifically for osteoblasts. We designed one of the pure self-assembling peptide scaffolds RADA16-I through direct coupling to short biologically active motifs. The motifs included osteogenic growth peptide ALK (ALKRQGRTLYGF) bone-cell secreted-signal peptide, osteopontin cell adhesion motif DGR (DGRGDSVAYG) and 2-unit RGD binding sequence PGR (PRGDSGYRGDS). We made the new peptide scaffolds by mixing the pure RAD16 and designer-peptide solutions, and we examined the molecular integration of the mixed nanofiber scaffolds using AFM. Compared to pure RAD16 scaffold, we found that these designer peptide scaffolds significantly promoted mouse pre-osteoblast MC3T3-E1 cell proliferation. Moreover, alkaline phosphatase (ALP) activity and osteocalcin secretion, which are early and late markers for osteoblastic differentiation, were also significantly increased. We demonstrated that the designer, self-assembling peptide scaffolds promoted the proliferation and osteogenic differentiation of MC3T3-E1. Under the identical culture medium condition, confocal images unequivocally demonstrated that the designer PRG peptide scaffold stimulated cell migration into the 3-D scaffold. Our results suggest that these designer peptide scaffolds may be very useful for promoting bone tissue regeneration.
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