Mitochondrial and Autophagic Regulation of Adult Neurogenesis in the Healthy and Diseased Brain

Adult neurogenesis is a highly regulated process during which new neurons are generated from neural stem cells in two discrete regions of the adult brain: the subventricular zone of the lateral ventricle and the subgranular zone of the dentate gyrus in the hippocampus. Defects of adult hippocampal neurogenesis have been linked to cognitive decline and dysfunction during natural aging and in neurodegenerative diseases, as well as psychological stress-induced mood disorders. Understanding the mechanisms and pathways that regulate adult neurogenesis is crucial to improving preventative measures and therapies for these conditions. Accumulating evidence shows that mitochondria directly regulate various steps and phases of adult neurogenesis. This review summarizes recent findings on how mitochondrial metabolism, dynamics, and reactive oxygen species control several aspects of adult neural stem cell function and their differentiation to newborn neurons. It also discusses the importance of autophagy for adult neurogenesis, and how mitochondrial and autophagic dysfunction may contribute to cognitive defects and stress-induced mood disorders by compromising adult neurogenesis. Finally, I suggest possible ways to target mitochondrial function as a strategy for stem cell-based interventions and treatments for cognitive and mood disorders.     

Novel TiC-based composites with enhanced mechanical properties

Novel TiC-based composites were synthesized by reactive hot-pressing at 1800 °C for 1 h with ZrB₂ addition as a sintering aid for the first time. The effects of ZrB₂ contents on the phase composition, microstructure evolution, and mechanical properties were reported. Based on the reaction and solid solution coupling effects between ZrB₂ and TiC, the product ZrC may be partially or completely dissolved into the TiC matrix, and then phase separation within the miscibility gap is observed to form lamellar nanostructured ZrC-rich (Zr, Ti)C. The TiC-10 mol.% ZrB₂ (starting batch composition) exhibits good comprehensive mechanical properties of hardness 27.7 ± 1.3 GPa, flexural strength 659 ± 48 MPa, and fracture toughness of 6.5 ± 0.6 MPa m^1/2, respectively, which reach or exceed most TiC-based composites using ceramics as sintering aids in the previous reports.     

Grain size effect on microwave dielectric properties of Na2WO4 ceramics prepared by cold sintering process

In this work, cold sintering was adopted to prepare Na₂WO₄ ceramics with different grain sizes ranging from 0.632 μm to 17.825 μm. Their microstructures, complex impedance, and microwave dielectric properties were studied in-depth. It was found that samples with relative densities higher than 92% can be successfully synthesized by cold sintering process at a low temperature of 240 °C. However, their electrical properties have strong dependence on the grain size. Specifically, the resistance of grain boundaries decreases dramatically with the increase of grain sizes, while the quality factor has a positive correlation with the grain sizes of Na₂WO₄ ceramics. Excellent microwave dielectric properties, including permittivity = 5.80, Q × f = 22,000 GHz, and TCF = −70 ppm/°C, are obtained for Na₂WO₄ ceramics with a grain size of 4.477 μm prepared by cold sintering process.     

Controlling Au electrode patterns for simultaneously monitoring electrical actuation and shape recovery in shape memory polymer

This paper presents an effective approach to achieve efficient electrical actuation and monitoring of shape recovery based on patterned Au electrodes on shape memory polymer (SMP). The electrically responsive shape recovery behavior was characterized and monitored by the evolution change in electrical resistance of patterned Au electrode. Both electrical actuation and temperature distribution in the SMP have been improved by optimizing the Au electrode patterns. The electrically actuated shape recovery behavior and temperature evolution during the actuation were monitored and characterized. The resistance changes could be used to detect beginning/finishing points of the shape recovery. Therefore, the Au electrode not only significantly enhances the electrical actuation performance to achieve a fast electrical actuation, but also enables the resistance signal to detect the free recovery process.     

Model checking temporal knowledge and commitments in multi-agent systems using reduction

Though modeling and verifying Multi-Agent Systems (MASs) have long been under study, there are still challenges when many different aspects need to be considered simultaneously. In fact, various frameworks have been carried out for modeling and verifying MASs with respect to knowledge and social commitments independently. However, considering them under the same framework still needs further investigation, particularly from the verification perspective. In this article, we present a new technique for model checking the logic of knowledge and commitments (CTLKC⁺). The proposed technique is fully-automatic and reduction-based in which we transform the problem of model checking CTLKC⁺ into the problem of model checking an existing logic of action called ARCTL. Concretely, we construct a set of transformation rules to formally reduce the CTLKC⁺ model into an ARCTL model and CTLKC⁺ formulae into ARCTL formulae to get benefit from the extended version of NuSMV symbolic model checker of ARCTL. Compared to a recent approach that reduces the problem of model checking CTLKC⁺ to another logic of action called GCTL¹, our technique has better scalability and efficiency. We also analyze the complexity of the proposed model checking technique. The results of this analysis reveal that the complexity of our reduction-based procedure is PSPACE-complete for local concurrent programs with respect to the size of these programs and the length of the formula being checked. From the time perspective, we prove that the complexity of the proposed approach is P-complete with regard to the size of the model and length of the formula, which makes it efficient. Finally, we implement our model checking approach on top of extended NuSMV and report verification results for the verification of the NetBill protocol, taken from business domain, against some desirable properties. The obtained results show the effectiveness of our model checking approach when the system scales up.     

Two-level intelligent modeling method for the rate of penetration in complex geological drilling process

The rate of penetration (ROP) model is of great importance in achieving a high efficiency in the complex geological drilling process. In this paper, a novel two-level intelligent modeling method is proposed for the ROP considering the drilling characteristics of data incompleteness, couplings, and strong nonlinearities. Firstly, a piecewise cubic Hermite interpolation method is introduced to complete the lost drilling data. Then, a formation drillability (FD) fusion submodel is established by using Nadaboost extreme learning machine (Nadaboost-ELM) algorithm, and the mutual information method is used to obtain the parameters, strongly correlated with the ROP. Finally, a ROP submodel is established by a neural network with radial basis function optimized by the improved particle swarm optimization (RBFNN-IPSO). This two-level ROP model is applied to a real drilling process and the proposed method shows the best performance in ROP prediction as compared with conventional methods. The proposed ROP model provides the basis for intelligent optimization and control in the complex geological drilling process.     

一种使用多跳事实的端到端知识库实体描述生成方法

自动化实体描述生成有助于进一步提升知识图谱的应用价值,而流畅度高是实体描述文本的重要质量指标之一。该文提出使用知识库上多跳的事实来进行实体描述生成,从而贴近人工编撰的实体描述的行文风格,提升实体描述的流畅度。该文使用编码器—解码器框架,提出了一个端到端的神经网络模型,可以编码多跳的事实,并在解码器中使用关注机制对多跳事实进行表示。该文的实验结果表明,与基线模型相比,引入多跳事实后模型的BLEU-2和ROUGE-L等自动化指标分别提升约8.9个百分点和7.3个百分点。     

Effects of short carbon fiber on the macro-properties,mechanical performance and microstructure of SiSiC composite fabricated by selective laser sintering

Selective laser sintering was combined with reactive melt infiltration to fabricate SiSiC part, and the effects of carbon fiber (C_f) on the properties of the SLS green body, the carbonized and final SiSiC sample were investigated. Results show that the addition of an appropriate amount of C_f (1.59 wt%~2.97 wt%) can increase the bulk density and geometric precision of the sample at all stages, and improve the mechanical properties of green and carbonized samples. The main phases composed of the SiSiC composite were free Si, a-SiC, β-SiC, plus a very small amount of Al–Si alloy. With 1.59 wt% C_f addition, a relatively comprehensive favorable macro-properties of both the green sample and carbonized sample was achieved, and the homogeneous microstructure of the latter favored the decreased free Si content and increased β-SiC content of the final composite. The evolution mechanism of C_f added to the raw material is inferred to be the mutual diffusion of [C] and [Si] that occurred at the C_f/Si melt boundary leading to the formation of the siliconized C_f with relatively large diameter size (24.3 μm) and high aspect ratio (>30). Amorphous C, which derived from the pyrolysis of epoxy resin E12, undergone a dissolution-precipitation mechanism with the formation of fine-grain β-SiC.     

Stereo matching cost computation based on nonsubsampled contourlet transform

A new matching cost computation method based on nonsubsampled contourlet transform (NSCT) for stereo image matching is proposed in this paper. Firstly, stereo image is decomposed into high frequency sub-band images at different scales and along different directions by NSCT. Secondly, by utilizing coefficients in high frequency domain and grayscales in RGB color space, the computation model of weighted matching cost between two pixels is designed based on the gestalt laws. Lastly, two types of experiments are carried out with standard stereopairs in the Middlebury benchmark. One of the experiments is to confirm optimum values of NSCT scale and direction parameters, and the other is to compare proposed matching cost with nine known matching costs. Experimental results show that the optimum values of scale and direction parameters are respectively 2 and 3, and the matching accuracy of the proposed matching cost is twice higher than that of traditional NCC cost.     

Homogenization with uncertainty in Poisson ratio for polymers with rubber particles

The main aim of this work is dual computer analysis of probabilistic coefficients for the homogenized tensor of the polymer filled with the rubber particles having randomized Poisson ratios of both constituents. The major issue is to verify an influence of a randomness in rubber Poisson ratio close to the compressibility limit on the uncertainty of the effective tensor probabilistic characteristics. Probabilistic analysis presented here is carried out using mainly the stochastic perturbation technique provided by the common application of the traditional FEM commercial code ABAQUS and the symbolic computations package MAPLE. This FEM-based technique employs polynomial response function of the optimum order recovered from the weighted least squares method and following a set of deterministic solutions obtained for various values of the randomized input parameter. Optimization procedure is released entirely into a symbolic environment, where maximization of the correlation factor together with minimization of the fitting variance and approximation error are applied. Homogenization technique consists in equating of deformation energies for the real composite and the artificial one characterized by the effective elasticity tensor with uncertainty.