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A safe, biocompatible, and stimuli-responsive cucurbit[7]uril-mediated supramolecular bactericidal nanoparticle was fabricated by encapsulating a highly bioactive carbazole-decorated imidazolium salt (

Supramolecular chemistry provides huge potentials and opportunities in agricultural pest management. In an attempt to develop highly bioactive, eco-friendly, and biocompatible supramolecular complexes for managing intractable plant bacterial diseases, herein, a type of interesting adamantane-functionalized 1,3,4-oxadiazole was rationally prepared to facilitate the formation of supramolecular complexes via β-cyclodextrin-adamantane host-guest interactions. Initial antibacterial screening revealed that most of these adamantane-decorated 1,3,4-oxadiazoles were obviously bioactive against three typically destructive phytopathogens. The lowest EC

At present, the innovation and entrepreneurship education (referred to as a dual-innovation education) lacks a perfect system, the curriculum content is obsolete, and the teachers are lacking. All these problems hinder the development of our country's innovation and entrepreneurship education. The best way to stimulate students' interest in learning relevant professional knowledge actively, to improve students' professional skills, to exercise students' innovative thinking consciousness and to cultivate students' innovative and entrepreneurial ability is to let students actively participate in innovative and entrepreneurial competitions in universities. This paper briefly analyses the current process of dual-innovation education in universities. Some common problems exist, and put forward the construction of dual-innovation curriculum system based on the innovation and entrepreneurship competition. Based on this system, a set of dual-innovation curriculum content standards is designed, in order to provide some ideas for the future curriculum design of dual-innovation curriculum.

Improvement of subtype selectivity of an inhibitor's binding activity using the conformational restriction approach has become an effective strategy in drug discovery. In this study, we applied this approach to PDE4 inhibitors and designed a series of novel oxazolidinone-fused 1,2,3,4-tetrahydroisoquinoline derivatives as conformationally restricted analogues of rolipram. The bioassay results demonstrated the oxazolidinone-fused tetrahydroisoquinoline derivatives exhibited moderate to good inhibitory activity against PDE4B and high selectivity for PDE4B/PDE4D. Among these derivatives, compound 12 showed both the strongest inhibition activity (IC50=0.60μM) as well as good selectivity against PDE4B and good in vivo activity in animal models of asthma/COPD and sepsis induced by LPS. The primary SAR study showed that restricting the conformation of the catechol moiety in rolipram with the scaffold of oxazolidinone-fused tetrahydroisoquinoline could lead to an increase in selectivity for PDE4B over PDE4D, which was consistent with the observed docking simulation.

Pyrazole constitutes an important heterocyclic family covering a broad range of synthetic as well as natural products that exhibit numerous chemical, biological, agrochemical and pharmacological properties. In order to explore compounds with good fungicidal activity, a series of new pyrazole derivatives containing 5-phenyl-2-furan were designed and synthesized. In vitro and in vivo fungicidal activities were evaluated and the compound ethyl-1-(5-phenylfuran-2-carbonyl)-5-propyl-1H-pyrazole-3-carboxylate (I8) displayed significant fungicidal activity against various fungi, especially against P. infestans. The structures of the novel pyrazole derivatives were confirmed by 1H NMR, 13C NMR, MS, elemental analysis and X-ray single crystal diffraction. Further study showed that compound I8 might act on the synthesis of cell walls from morphological and ultrastructural studies by SEM and TEM. The results also revealed that compound I8 could block the nutritional transportation leading to cells senescence and death. These results suggested that the novel pyrazole derivatives proved to be promising lead compounds.

A series of pyrazole and triazole derivatives containing 5-phenyl-2-furan functionality were designed and synthesized as phosphodiesterase type 4 (PDE4) inhibitors. The bioassay results showed that title compounds exhibited considerable inhibitory activity against PDE4B and blockade of LPS-induced TNFα release. Meanwhile, the activity of compounds containing 1,2,4-triazole (series II) was higher than that of pyrazole-attached derivatives (series I). The primary structure-activity relationship study and docking results showed that the 1,2,4-triazole moiety of compound IIk played a key role to form integral hydrogen bonds and π-π stacking interaction with PDE4B protein while the rest part of the molecule extended into the catalytic domain to block the access of cAMP and formed the foundation for inhibition of PDE4. Compound IIk would be great promise as a hit compound for further study based on the preliminary structure-activity relationship and molecular modeling studies.

A series of 3,5-dimethylpyrazole derivatives containing 5-phenyl-2-furan moiety were designed and synthesized as phosphodiesterase type 4 (PDE4) inhibitors. Bioassay results showed that the title compounds exhibited considerable inhibitory activity against PDE4B and blockade of LPS-induced TNFα release. Among the designed compounds, compound If showed the best inhibitory activity against PDE4B with the IC50 value of 1.7 μM, which also showed good in vivo activity in animal models of asthma/COPD and sepsis induced by LPS. The primary structure–activity relationship (SAR) study and docking results suggested that introduction of the substituent groups to the phenyl ring at the para-position, especially methoxy group, was helpful to enhance inhibitory activity against PDE4B.

In this work, a kernel principle component analysis network (KPCANet) is proposed for classification of the facial expression in unconstrained images, which comprises only the very basic data processing components: cascaded kernel principal component analysis (KPCA), binary hashing, and block-wise histograms. In the proposed model, KPCA is employed to learn multistage filter banks. It is followed by simple binary hashing and block histograms for indexing and pooling. For comparison and better understanding, We have tested these basic networks extensively on many benchmark visual datasets ( such as the JAFFE [13] database, the CMU AMP face expression database, a part of the Extended Cohn-Kanade (CK+) database), The results demonstrate the potential of the KPCANet serving as a simple but highly competitive baseline for facial expression recognition.

In order to classify the objects in nature images, a model with color constancy and principle component analysis network (PCANet) is proposed. The new color constancy model imitates the functional properties of the HVS from the retina to the double-opponent cells in V1. PCANet can be designed and learned extremely, which comprises only the very basic data processing components: cascaded principal component analysis (PCA), binary hashing, and block-wise histograms. At last, a SVM is trained to classify the object in the image. The results of experiments demonstrate the potential of the model for object classification in wild color images.

A deep Neural Network model was trained to classify the facial expression in unconstrained images, which comprises nine layers, including input layer, convolutional layer, pooling layer, fully connected layers and output layer. In order to optimize the model, rectified linear units for the nonlinear transformation, weights sharing for reducing the complexity, “mean” and “max” pooling for subsample, “dropout” for sparsity are applied in the forward processing. With large amounts of hard training faces, the model was trained via back propagation method with stochastic gradient descent. The results of shows the proposed model achieves excellent performance.

In this study, a series of pyrazole derivatives containing 4-phenyl-2-oxazole moiety were designed and synthesized in a concise way, some of which exhibited considerable inhibitory activity against PDE4B and blockade of LPS-induced TNF-α release. Compound 4c displayed the strongest inhibition activity (IC50=1.6±0.4μM) and good selectivity against PDE4B. Meanwhile, compound 4c showed good in vivo activity in animal models of asthma/COPD and sepsis induced by LPS. The primary structure-activity relationship study showed the 3,5-dimethylpyrazole residue was essential for the bioactivity, and the substituted group R1 at the benzene ring also affected the activity. Docking results showed that compound 4c played a key role to form integral hydrogen bonds and a π-π stacking interaction, using hydrazide scaffold (CONN) and pyrazole ring respectively, with PDE4B protein. While the rest part of the molecule extended into the catalytic domain to block the access of cAMP and formed the foundation for inhibition of PDE4B. Compound 4c would be great promise as a lead compound for further study based on the preliminary structure-activity relationship and molecular modeling studies.

A sparse auto-encoder model was trained to extract the code of different facial expression, which comprises four encoder layers and three decode layers, the representation locating in the fourth layer (code layer) is the features expected. With large amounts of patches randomly selected from training faces, the model was trained firstly via backpropagation which minimizes an unsupervised sparse reconstruction error, and then a softmax classifier was learned for supervised classification. The input vector for the classification is the feature of facial image induced by the learned sparse auto-encoder and two key operations (convolving and pooling). Using a small number of hidden units per layer and a relatively small number of training set, the proposed model achieves excellent performance in the experiments.

A multi-feature bio-inspired model for scene image classification (MFBIM) is presented in this work; it extends the hierarchical feedforward model of the visual cortex. Firstly, each of three paths of classification uses each image property (i.e. shape, edge or color based features) independently. Then, BPNN assigns the category of an image based on the previous outputs. Experiments show that the model boosts the classification accuracy over the shape based model. Meanwhile, the proposed approach achieves a high accuracy comparable to other reported methods on publicly available color image dataset.

A series of 2,5-disubstituted-1,3,4-thiadiazoles were synthesized using Lawesson’s reagent by an efficient approach under microwave irradiation in good yields. Their structures were characterized by MS, IR, 1H NMR, 13C NMR and elemental analysis. Their in vitro and in vivo fungicidal activities revealed that the title compounds exhibited considerable activity against five selected fungi, especially to Phytophthora infestans. In order to illustrate the mechanism of title compounds against P. infestans, scanning electron micrographs (SEM) and transmission electron micrographs (TEM) were applied. The morphological and ultrastructural studies demonstrated that compound I18 led to swelling of hyphae, thickening and proliferating multilayer cell walls, excessive septation and accumulation of dense bodies. The bioassay results indicated compound I18 might act on cell wall biosynthesis and blocked the nutrition transportation and led to cells senescence and death. Meanwhile, compound I18 had broad fungicidal activity against other twenty different kinds of fungi. These results suggested that title compounds were eligible to be development candidates and compound I18 as a promising lead compound was worthy to be further discovery, especially against P. infestans.

A pair of chemical isomeric structures of novel N-tert-butylphenyl thenoylhydrazide compounds I and II were designed and synthesized. Their structures were characterized by MS, IR, 1H NMR, elemental analysis and X-ray single crystal diffraction. The regioselectivity of the Meerwein arylation reaction and the electrophilic substitution reaction of N-tert-butyl hydrazine were studied by density functional theory (DFT) quantum chemical method. The larvicidal tests revealed that some compounds I had excellent larvicidal activity against Culex pipiens pallens. As the candidates of insect growth regulators (IGRs), the larval growth inhibition and regulation against Culex pipiens pallens were examined for some compounds, especially I1 and I7. Compounds I1 and I7 were further indicated as an ecdysteroid agonist by reporter gene assay on the Spodoptera frugiperda cell line (Sf9 cells). Finally, a molecular docking study of compound I7 was conducted, which was not only beneficial to understand the structure-activity relationship, but also useful for development of new IGRs for the control of mosquitos.

Single biometric cryptosystems were developed to obtain win-win scenarios for security and privacy. They are seriously threatened by spoof attacks, in which a forged biometric copy or artificially recreated biometric data of a legitimate user may be used to spoof a system. Meanwhile, feature alignment and quantization greatly degrade the accuracy of single biometric cryptosystems. In this paper, by trying to bind multiple biometrics to cryptography, a cryptosystem named multibiometric cryptosystem (MBC), is demonstrated from the theoretical point of view. First, an MBC with two fusion levels: fusion at the biometric level, and fusion at the cryptographic level, is formally defined. Then four models, namely biometric fusion model, MN-split model, nonsplit model, and package model, adopted at those two levels for fusion are presented. Shannon entropy analysis shows that even if the biometric ciphertexts and some biometric traits are disclosed, the new constructions still can achieve consistently data security and biometric privacy. In addition, the achievable accuracy is analyzed in terms of false acceptance rate/false rejection rate at each model. Finally, a comparison on the relative advantages and disadvantages of the proposed models is discussed.

The design, synthesis, and biological evaluation of new phosphodiesterase type 4 (PDE4) inhibitors, which possessed 7-(cyclopentyloxy)-6-methoxy 1,2,3,4-tetrahydroisoquinoline ring, were described. Compound 8 [(7-cyclopentyloxy)-6-methoxy-3,4-dihydroisoquinolin-2(1H)-yl)(4-hydroxy-3-methoxy-phenyl)methanone] showed the best inhibitory activity and good selectivity against PDE4B. The docking results showed that the catechol diether moiety of compound 8 played a key role to form integral hydrogen bonds with PDE4B protein while the rest part of the molecule extended into the catalytic domain to block the access of cAMP and formed the foundation for inhibition of PDE4. Compound 8 would be great promise as a hit compound for further study based on the preliminary structure-activity relationship and molecular modeling studies.

To segment an object from its background image for advanced vision processing, this article presents a novel bio-inspired framework for image segmentation in complex nature scenes, which is a hierarchical system that mimics the organization of layered early visual area in primate visual cortex. The proposed methodology consists of two typical stages: the first stage is a parallel modular structure including three segmenting operators based on color feature, form feature and texture feature, each of which solves the segmentation problem independently for the same input. They implement the similar computing as the parvocellular (P-cell), the magnocellular (M-cell) and koniocellular (K-cell) pathway in lateral geniculate nucleus (LGN) from the retina to the primary visual cortex. Then, a fusion operation, multiple feature fusion segmentation (MFFS), integrates these three feature segmentations together through the backpropagation neuron network (BPNN) in the last stage, which simulates the operation of area following the LGN in primary visual cortex. The proposed approach is applied to several segmentation experiments of many single objects in clustering conditions, the result shows that the approach is capable of competing with state-of-the-art systems.

To locate the object accurately in a scene for further vision processing, a novel approach for figure-ground segmentation is proposed, which combines the normalized-cut method (Ncut) and top-down method inspired by the trickle-up and trickle-down processing in primate visual pathways. Firstly, as the trickle-up stage, the Ncut method groups the pixels into multiple partitions based on the global criterion, which measures both the total dissimilarity between the different groups as well as the total similarity within the groups. The computation of trickle-down includes mainly a covering operator, which covers the result of the trickle-up with the fragments of specific class. As one important computation in the trickle-down stage, the optimal method base on back-propagation neural network is utilized to improve the performance of the model. The proposed approach is applied to several segmentation experiments of clustering conditions. The results demonstrate that the performance of the proposed approach overpasses those achieved by previous top-down or bottom-up schemes on figure-ground segmentation. In addition to its application in computer vision, the success of this approach suggests a plausibility method, which combines the forward and backward processes for solving the visual perceptual grouping problem.