4-Nitro­benzoic acid–2,2′-biimidazole (2/1)

In the title adduct, C7H5NO4·0.5C6H6N4, the complete biimidazole molecule is generated by a crystallographic inversion centre. In the crystal, N—H⋯O and O—H⋯N hydrogen bonds connects the 4-nitro­benzoic acid and 2,2′-biimidazole units, affording multi-dimensional frameworks with graph-set descriptor R 2 2(9)

Almost Sure Asymptotic Stabilization of Differential Equations with Time-Varying Delay by Lévy Noise

This paper aims to determine that the Lévy noise can stabilize the given differential equations with time-varying delay, which has generalized the Brownian motion case. An analysis is developed and sufficient conditions on the stabilization for stochastic differential equations with time-varying delay are presented. Our stabilization criteria is in terms of linear matrix inequalities (LMIs), whence the feedback controls can be designed more easily in practice

Preliminary Functional-Structural Modeling on Poplar (Salicaceae)

Poplar is one of the best fast-growing trees in the world, widely used for windbreak and wood product. Although architecture of poplar has direct impact on its applications, it has not been descried in previous poplar models, probably because of the difficulties raised by measurement, data processing and parameterization. In this paper, the functional-structural model GreenLab is calibrated by using poplar data of 3, 4, 5, 6 years old. The data was acquired by simplifying measurement. The architecture was also simplified by classifying the branches into several types (physiological age) using clustering analysis, which decrease the number of parameters. By multi-fitting the sampled data of each tree, the model parameters were identified and the plant architectures at different tree ages were simulated

On the partial stochastic stability of stochastic differential delay equations with Markovian switching

Abstract: In the paper, we are concerned with the partial asymptotic stochastic stability (stability in probability) of stochastic differential delay equations with Markovian switching(SDDEwMSs), the sufficient conditions for partial asymptotic stability in probability have been given and we have generalized some results of Sharov and Ignatyev to cover a class of much more general SDDEwMSs

Identification of Topping Responsive Proteins in Tobacco Roots

Tobacco plant has many responses to topping, such as the increase in ability of nicotine synthesis and secondary growth of roots. Some topping responsive miRNAs and genes had been identified in our previous work, but it is not enough to elaborate mechanism of tobacco response to topping. Here, topping responsive proteins were screened from tobacco roots with two-dimensional electrophoresis. Of these proteins, calretulin (CRT) and Auxin-responsive protein IAA9 were related to the secondary growth of roots, LRR disease resistance, heat shock protein 70 and farnesyl pyrophosphate synthase 1（FPPS）were involved in wounding stress response, and F-box protein played an important role in promoting the ability of nicotine synthesis after topping. In addition, there were five tobacco bHLH proteins (NtbHLH, NtMYC1a, NtMYC1b, NtMYC2a and NtMYC2b) related to nicotine synthesis. It was suggested that NtMYC2 might be the main positive transcription factor and NtbHLH protein is a negative regulator in the JA-mediating activation of nicotine synthesis after topping. Tobacco topping activates some comprehensive biology processes involving IAA and JA signaling pathway, and the identification of these proteins will be helpful to understand the process of topping response

Growth and development simulation based on functional-structural model GreenLab for poplar (Salicaceae)

International audiencePoplar (salicaceae) is one of the widest planted fast-growing trees in the world. It is not only used for timber, but also used as windbreak and ecological protection of forest widely. The architecture of poplar has direct impact on poplar's growth and applications, but poplar's architecture still has not been discussed deeply in previous poplar models because of the difficulties raised by measurement, data processing and parameterization. This paper aimed to collect the biomass and architecture data of poplars of different ages, and construct the functional-structural model of poplar based on GreenLab. The selected poplar variety was poplar 107 (Populus × euramericana cv. Neva). The biomass and architecture data were collected from four trees with 3, 4, 5 and 6 years old, respectively. The architecture was simplified by classifying the branches into several types (physiological age) according to the length and size. Based on GreenLab model, some parameters were obtained and some strong correlation coefficients were got. The comparison between the measured and simulated results was given for the trunk data of all trees. The topological structures of poplar at different tree ages were reconstructed. This paper was a exploration of poplar growth simulation based on GreenLab model, and was a good reference in the Functional-Structural model construction of complex trees

Weight-dependent Gates for Differentiable Neural Network Pruning

In this paper, we propose a simple and effective network pruning framework, which introduces novel weight-dependent gates to prune filter adaptively. We argue that the pruning decision should depend on the convolutional weights, in other words, it should be a learnable function of filter weights. We thus construct the weight-dependent gates (W-Gates) to learn the information from filter weights and obtain binary filter gates to prune or keep the filters automatically. To prune the network under hardware constraint, we train a Latency Predict Net (LPNet) to estimate the hardware latency of candidate pruned networks. Based on the proposed LPNet, we can optimize W-Gates and the pruning ratio of each layer under latency constraint. The whole framework is differentiable and can be optimized by gradient-based method to achieve a compact network with better trade-off between accuracy and efficiency. We have demonstrated the effectiveness of our method on Resnet34, Resnet50 and MobileNet V2, achieving up to 1.33/1.28/1.1 higher Top-1 accuracy with lower hardware latency on ImageNet. Compared with state-of-the-art pruning methods, our method achieves superior performance.Comment: ECCV worksho

A Potent and Effective Suicidal Listeria Vaccine Platform.

Live-attenuated Listeria monocytogenes has shown encouraging potential as an immunotherapy platform in preclinical and clinical settings. However, additional safety measures will enable application across malignant and infectious diseases. Here, we describe a new vaccine platform, termed Lm-RIID (L. monocytogenes recombinase-induced intracellular death), that induces the deletion of genes required for bacterial viability yet maintains potent T cell responses to encoded antigens. Lm-RIID grows normally in broth but commits suicide inside host cells by inducing Cre recombinase and deleting essential genes flanked by loxP sites, resulting in a self-limiting infection even in immunocompromised mice. Lm-RIID vaccination of mice induces potent CD8+ T cells and protects against virulent challenges, similar to live L. monocytogenes vaccines. When combined with α-PD-1, Lm-RIID is as effective as live-attenuated L. monocytogenes in a therapeutic tumor model. This impressive efficacy, together with the increased clearance rate, makes Lm-RIID ideal for prophylactic immunization against diseases that require T cells for protection