Titanium dioxide (TiO2) nanoparticulate films was successfully annealed on a glass substrate via alternative hot air treatment (HAT). Interestingly, HAT not only protects the glass substrate deformation but can also r...
Titanium dioxide (TiO2) nanoparticulate films was successfully annealed on a glass substrate via alternative hot air treatment (HAT). Interestingly, HAT not only protects the glass substrate deformation but can also reduce cost and time in the annealing process. The annealed films using HAT at 500 °C for 10 min can be compared with the annealed films in conventional furnace heat treatment (FHT) at 500 °C for 60 min. The results showed the sizes of ∼7.9 nm are obtained after the films annealed with both annealing techniques. The surface roughness of the as-deposited, the annealed films using FHT and HAT were 17.37, 23.74 and 23.26 nm, respectively. The energy band gap of the as- deposited films, the annealed films using FHT and HAT were 3.24 eV, 3.1 and 3.19 eV, respectively. Moreover, the annealed films using FHT and HAT techniques show superhydrophilic with a water contact angle of 3.42° and 2.81°, while the as-deposited films was 8.93°. After aging time testing, superhydrophilicity of the annealed films using HAT is greater than FHT. The result is in good agreement with Ti wt% of the as-deposited, the annealed films using FHT and HAT left on the substrate to 0.15, 0.73 and 0.65 nm after testing simulation for 20 years.
The experiment was conducted to study strain distribution in circular disk of PMMA by photoelasticity in reflection polariscope. The strain in circular disk was induced by two point load created by hydraulic system (5...
The experiment was conducted to study strain distribution in circular disk of PMMA by photoelasticity in reflection polariscope. The strain in circular disk was induced by two point load created by hydraulic system (535.37-994.63 N) with the step increase of 153.21 N. We added the Babinet compensater in basic reflection polariscope to observe the fractional isochromatic fringe order in the first quadrant of disk and we calculated strain by using stressstrain optic laws. The result showed the relation between absolute of different strain in first quadrant of circular disk and the relation of force with absolute of different strain. It was found that maximum different strain produced at contact area of disk decreased along horizontal and vertical direction. The relation of force with different strain was linear.
The standard genetic code is well known to be optimized for minimizing the phenotypic effects of single nucleotide substitutions, a property that was likely selected for during the emergence of a universal code. Given...
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Feed-forward convolutional neural networks (CNNs) are currently state-of-the-art for object classification tasks such as ImageNet. Further, they are quantitatively accurate models of temporally-averaged responses of n...
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Feed-forward convolutional neural networks (CNNs) are currently state-of-the-art for object classification tasks such as ImageNet. Further, they are quantitatively accurate models of temporally-averaged responses of n...
Feed-forward convolutional neural networks (CNNs) are currently state-of-the-art for object classification tasks such as ImageNet. Further, they are quantitatively accurate models of temporally-averaged responses of neurons in the primate brain's visual system. However, biological visual systems have two ubiquitous architectural features not shared with typical CNNs: local recurrence within cortical areas, and long-range feedback from downstream areas to upstream areas. Here we explored the role of recurrence in improving classification performance. We found that standard forms of recurrence (vanilla RNNs and LSTMs) do not perform well within deep CNNs on the ImageNet task. In contrast, novel cells that incorporated two structural features, bypassing and gating, were able to boost task accuracy substantially. We extended these design principles in an automated search over thousands of model architectures, which identified novel local recurrent cells and long-range feedback connections useful for object recognition. Moreover, these task-optimized ConvRNNs matched the dynamics of neural activity in the primate visual system better than feedforward networks, suggesting a role for the brain's recurrent connections in performing difficult visual behaviors.
Background: Clusters of circulating tumor cells (CTCs), despite being rare, may account for more than 95% of metastases. Cells in these clusters do not undergo a complete epithelial-to-mesenchymal transition (EMT) but...
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Background: Clusters of circulating tumor cells (CTCs), despite being rare, may account for more than 95% of metastases. Cells in these clusters do not undergo a complete epithelial-to-mesenchymal transition (EMT) but retain some epithelial traits as compared to individually disseminating tumor cells. Determinants of single cell dissemination versus collective dissemination remain elusive. Inflammatory breast cancer (IBC), a highly aggressive breast cancer subtype that chiefly metastasizes via CTC clusters, is a promising model for studying mechanisms of collective tumor cell dissemination. Previous studies on breast cancer and adult acute myeloid leukemia, motivated by a theory that suggests physical systems with hierarchical organization tend to be more adaptable, have found that the expression of metastasis associated genes is more hierarchically organized in cases of successful metastases. Methods: We used the cophenetic correlation coefficient (CCC) to quantify the hierarchical organization in the expression networks of two distinct gene sets, collective dissemination associated genes and IBC associated genes, in cancer cell lines and in tumor samples from breast cancer patients. Hypothesizing that a higher CCC for collective dissemination associated genes and for IBC associated genes would be associated with a more evident epithelial phenotype and with worse outcomes in breast cancer patients, we evaluated the correlation of CCC with different phenotypic groups. Results: The CCC of both gene networks, the collective dissemination associated gene network and the IBC associated gene network, was higher in (a) epithelial cell lines as compared to mesenchymal cell lines and (b) tumor samples from IBC patients, as compared to samples from non-IBC breast cancer patients. A higher CCC of both networks was also correlated with a higher rate of metastatic relapse in breast cancer patients. Neither the levels of CDH1 gene expression, nor gene set enrichment analysis cou
A central challenge in sensory neuroscience is to understand neural computations and circuit mechanisms that underlie the encoding of ethologically relevant, natural stimuli. In multilayered neural circuits, nonlinear...
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ISBN:
(纸本)9781510838819
A central challenge in sensory neuroscience is to understand neural computations and circuit mechanisms that underlie the encoding of ethologically relevant, natural stimuli. In multilayered neural circuits, nonlinear processes such as synaptic transmission and spiking dynamics present a significant obstacle to the creation of accurate computational models of responses to natural stimuli. Here we demonstrate that deep convolutional neural networks (CNNs) capture retinal responses to natural scenes nearly to within the variability of a cell's response, and are markedly more accurate than linear-nonlinear (LN) models and Generalized Linear Models (GLMs). Moreover, we find two additional surprising properties of CNNs: they are less susceptible to overfitting than their LN counterparts when trained on small amounts of data, and generalize better when tested on stimuli drawn from a different distribution (e.g. between natural scenes and white noise). An examination of the learned CNNs reveals several properties. First, a richer set of feature maps is necessary for predicting the responses to natural scenes compared to white noise. Second, temporally precise responses to slowly varying inputs originate from feedforward inhibition, similar to known retinal mechanisms. Third, the injection of latent noise sources in intermediate layers enables our model to capture the sub-Poisson spiking variability observed in retinal ganglion cells. Fourth, augmenting our CNNs with recurrent lateral connections enables them to capture contrast adaptation as an emergent property of accurately describing retinal responses to natural scenes. These methods can be readily generalized to other sensory modalities and stimulus ensembles. Overall, this work demonstrates that CNNs not only accurately capture sensory circuit responses to natural scenes, but also can yield information about the circuit's internal structure and function.
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