This paper expatiates the stability and bifurcation for a fractional-order neural network (FONN) with double leakage delays. Firstly, the characteristic equation of the developed FONN is circumspectly researched by employing inequable delays as bifurcation parameters. Simultaneously the bifurcation criteria are correspondingly extrapolated. Then, unequal delays-spurred-bifurcation diagrams are primarily delineated to confirm the precision and correctness for the values of bifurcation points. Furthermore, it lavishly illustrates from the evidence that the stability performance of the proposed FONN can be demolished with the presence of leakage delays in accordance with comparative studies. Eventually, two numerical examples are exploited to underpin the feasibility of the developed theory. The results derived in this paper have perfected the retrievable outcomes on bifurcations of FONNs embodying unique leakage delay, which can nicely serve a benchmark deliberation and provide a comparatively credible guidance for the influence of multiple leakage delays on bifurcations of FONNs.The current state-of-the-art object recognition algorithms, deep convolutional neural networks (DCNNs), are inspired by the architecture of the mammalian visual system, and are capable of human-level performance on many tasks.  https://www.selleckchem.com/products/a-769662.html  As they are trained for object recognition tasks, it has been shown that DCNNs develop hidden representations that resemble those observed in the mammalian visual system (Razavi and Kriegeskorte, 2014; Yamins and Dicarlo, 2016; Gu and van Gerven, 2015; Mcclure and Kriegeskorte, 2016). Moreover, DCNNs trained on object recognition tasks are currently among the best models we have of the mammalian visual system. This led us to hypothesize that teaching DCNNs to achieve even more brain-like representations could improve their performance. To test this, we trained DCNNs on a composite task, wherein networks were trained to (a) classify images of objects; while (b) having intermediate representations that resemble those observed in neural recordings from monkey visual cortex. Compared with Dnal for training DCNNs.The characterization of DOM and its effect on heavy metal solubility in soils have been widely concerned, while few concerns on the phytostabilization of multi-metal contaminated soils. A pot experiment was performed to characterize dissolved organic matter (DOM) in the rhizosphere of the mining ecotype (ME) and non-mining ecotype (NME) of Athyrium wardii (Hook.) when exposed to Cd and Pb simultaneously, and investigate its effect on Cd and Pb solubility in soils. The ME presented more DOM in the rhizosphere when exposed to Cd and Pb simultaneously than that exposed to single Cd or Pb, and also than the NME. The acid fractions (hydrophilic acid, hydrophobic acid) and hydrophilic fractions (hydrophilic acid, hydrophilic neutral, and hydrophilic base) were the dominant parts of DOM in the ME rhizosphere. The ME presented more acid and hydrophilic fractions in the rhizosphere when exposed to Cd and Pb simultaneously. Meanwhile, there were more O-H, C-O, N-H and C-H, assigned to carboxylic groups, phenolic groups, hydroxyl groups, and/or amino groups, present in DOM from the rhizosphere of ME when exposed to Cd and Pb simultaneously. These results highlighted the acid characteristics of DOM in the rhizosphere of ME when exposed to Cd and Pb simultaneously. DOM in the rhizosphere of ME thereby showed greater complexation degree for Cd (68%) and Pb (77%), thus showing greater ability to enhance Cd and Pb solubility in soils when exposed to Cd and Pb simultaneously. This is thereby considered to be one of the key processes for enhancing Cd and Pb uptake by the ME when exposed to Cd and Pb simultaneously.Biodiesel is considered as a valuable and less toxic alternative to diesel. However, cellular and molecular effects of repeated exposure to biodiesel emissions from a recent engine equipped with a diesel particle filter (DPF) remain to be characterized. To gain insights about this point, the lung transcriptional signatures were analyzed for rats (n = 6 per group) exposed to filtered air, 30% rapeseed biodiesel (B30) blend or reference diesel (RF0), upstream and downstream a DPF, for 3 weeks (3 h/day, 5 days/week). Genomic analysis revealed a modest regulation of gene expression level (lower than a 2-fold) by both fuels and a higher number of genes regulated downstream the DPF than upstream, in response to either RF0 or to B30 exhaust emissions. The presence of DPF was found to notably impact the lung gene signature of rats exposed to B30. The number of genes regulated in common by both fuels was low, which is likely due to differences in concentrations of regulated pollutants in exhausts, notably for compound organic volatiles, polycyclic aromatic hydrocarbons, NO or NOx. Nevertheless, we have identified some pathways that were activated for both exhaust emissions, such as integrin-, IGF-1- and Rac-signaling pathways, likely reflecting the effects of gas phase products. By contrast, some canonical pathways relative to "oxidative phosphorylation" and "mitochondrial dysfunction" appear as specific to B30 exhaust emission; the repression of transcripts of mitochondrial respiratory chain in lung of rats exposed to B30 downstream of DPF supports the perturbation of mitochondria function. This study done with a recent diesel engine (compliant with the European IV emission standard) and commercially-available fuels reveals that the diesel blend composition and the presence of an after treatment system may modify lung gene signature of rats repeatedly exposed to exhaust emissions, however in a rather modest manner.A cross-sectional population-based study was conducted in order to evaluate the association of sleep characteristics with anxiety disorders using self-reported questionnaires and taking into account several socio-demographic, lifestyle and health related characteristics. 957 participants between 19 and 86 years old were enrolled in our study. Anxiety symptoms were assessed using the Zung Self-rating Anxiety Scale. Participants self-reported their daily sleep habits and filled in the following scales Epworth Sleepiness Scale, Athens Insomnia Scale, Pittsburgh Sleep Quality Index and Berlin Questionnaire. Overall prevalence of anxiety was 33.6%. Anxiety symptoms were more prominent among minority groups. Subjects with anxiety reported shorter sleep duration and reduced sleep efficiency. After adjusting for all possible confounders, they were five times more likely to exhibit short sleep duration (≤6h) and 0.60 times less likely long sleep duration (>8h). These relations remained significant in both genders, but were more pronounced among men.