Fabrication of a new type of organic-inorganic hybrid superlattice films combined with titanium oxide and polydiacetylene

We fabricated a new organic-inorganic hybrid superlattice film using molecular layer deposition [MLD] combined with atomic layer deposition [ALD]. In the molecular layer deposition process, polydiacetylene [PDA] layers were grown by repeated sequential adsorption of titanium tetrachloride and 2,4-hexadiyne-1,6-diol with ultraviolet polymerization under a substrate temperature of 100°C. Titanium oxide [TiO2] inorganic layers were deposited at the same temperatures with alternating surface-saturating reactions of titanium tetrachloride and water. Ellipsometry analysis showed a self-limiting surface reaction process and linear growth of the nanohybrid films. The transmission electron microscopy analysis of the titanium oxide cross-linked polydiacetylene [TiOPDA]-TiO2 thin films confirmed the MLD growth rate and showed that the films are amorphous superlattices. Composition and polymerization of the films were confirmed by infrared spectroscopy. The TiOPDA-TiO2 nanohybrid superlattice films exhibited good thermal and mechanical stabilities

Influence of the waist diameters on transmission characteristics and strain sensitivity of microtapered long-period fiber gratings

Transmission characteristics of microtapered long-period fiber gratings (MTLPGs) and their strain and temperature sensitivities with variations in the waist diameters are investigated theoretically and experimentally. Transmission characteristics of MTLPGs strongly depend on the waist diameter of the tapered optical fiber (TOF) because of the modification of the effective index difference between the core and the cladding modes. Based on the photoelastic effect, the resonant wavelengths of MTLPGs with variations in strain shift to shorter wavelengths. The strain sensitivity of the MTLPG with a waist diameter of 25 μm is improved by a factor of 20 compared with that of a 125 μm long-period fiber grating. The temperature sensitivities of MTLPGs are also enhanced by reducing the waist diameter of the TOF

Round Robin Analyses on Stress Intensity Factors of Inner Surface Cracks in Welded Stainless Steel Pipes

AbstractAustenitic stainless steels (ASSs) are widely used for nuclear pipes as they exhibit a good combination of mechanical properties and corrosion resistance. However, high tensile residual stresses may occur in ASS welds because postweld heat treatment is not generally conducted in order to avoid sensitization, which causes a stress corrosion crack. In this study, round robin analyses on stress intensity factors (SIFs) were carried out to examine the appropriateness of structural integrity assessment methods for ASS pipe welds with two types of circumferential cracks. Typical stress profiles were generated from finite element analyses by considering residual stresses and normal operating conditions. Then, SIFs of cracked ASS pipes were determined by analytical equations represented in fitness-for-service assessment codes as well as reference finite element analyses. The discrepancies of estimated SIFs among round robin participants were confirmed due to different assessment procedures and relevant considerations, as well as the mistakes of participants. The effects of uncertainty factors on SIFs were deducted from sensitivity analyses and, based on the similarity and conservatism compared with detailed finite element analysis results, the R6 code, taking into account the applied internal pressure and combination of stress components, was recommended as the optimum procedure for SIF estimation

‘Evidence of an auxin signal pathway, microRNA167-ARF8-GH3, and its response to exogenous auxin in cultured rice cells’

MicroRNA167 (miR167) was shown to cleave auxin responsive factor 8 (ARF8) mRNA in cultured rice cells. MiR167 level was found to be controlled by the presence of auxin in the growth medium. When cells grew in auxin-free medium, miR167 level decreased, resulting in an increase in the level of ARF8 mRNA. Cells growing in the normal growth medium containing auxin showed a reversed trend. It was also shown that expression of OsGH3-2, an rice IAA-conjugating enzyme, was positively regulated by ARF8. Delivery of synthesized miR167 into cells led to decrease of both ARF8 mRNA and OsGH3-2 mRNA. This study provides an evidence in which the exogeneous auxin signal is transduced to OsGH3-2 through miR167 and ARF8 in sequence. This proposed auxin signal transduction pathway, auxin-miR167-ARF8-OsGH3-2, could be, in conjunction with the other microRNA-mediated auxin signals, an important one for responding to exogeneous auxin and for determining the cellular free auxin level which guides appropriate auxin responses

Pixel-wise Guidance for Utilizing Auxiliary Features in Monte Carlo Denoising

Auxiliary features such as geometric buffers (G-buffers) and path descriptors (P-buffers) have been shown to significantly improve Monte Carlo (MC) denoising. However, recent approaches implicitly learn to exploit auxiliary features for denoising, which could lead to insufficient utilization of each type of auxiliary features. To overcome such an issue, we propose a denoising framework that relies on an explicit pixel-wise guidance for utilizing auxiliary features. First, we train two denoisers, each trained by a different auxiliary feature (i.e., G-buffers or P-buffers). Then we design our ensembling network to obtain per-pixel ensembling weight maps, which represent pixel-wise guidance for which auxiliary feature should be dominant at reconstructing each individual pixel and use them to ensemble the two denoised results of our denosiers. We also propagate our pixel-wise guidance to the denoisers by jointly training the denoisers and the ensembling network, further guiding the denoisers to focus on regions where G-buffers or P-buffers are relatively important for denoising. Our result and show considerable improvement in denoising performance compared to the baseline denoising model using both G-buffers and P-buffers.Comment: 19 page

Endocytic BDNF secretion regulated by Vamp3 in astrocytes

Brain-derived neurotrophic factor (BDNF) regulates diverse brain functions via TrkB receptor signaling. Due to the expression of TrkB receptors, astrocytes can internalize extracellular BDNF proteins via receptor-mediated endocytosis. Endocytosed BDNF can be re-secreted upon stimulation, but the molecular mechanism underlying this phenomenon remains unrecognized. Our study reveals that vesicle-associated membrane protein 3 (Vamp3) selectively regulates the release of endocytic BDNF from astrocytes. By using quantum dot (QD)-conjugated mature BDNF (QD-BDNF) as a proxy for the extracellular BDNF protein, we monitored the uptake, transport, and secretion of BDNF from cultured cortical astrocytes. Our data showed that endocytic QD-BDNF particles were enriched in Vamp3-containing vesicles in astrocytes and that ATP treatment sufficiently triggered either the antero- or retrograde transport and exocytosis of QD-BDNF-containing vesicles. Downregulation of Vamp3 expression disrupted endocytic BDNF secretion from astrocytes but did not affect uptake or transport. Collectively, these results provide evidence of the selective ability of astrocytic Vamp3 to control endocytic BDNF secretion during BDNF recycling. © 2021, The Author(s).1

Prediction model for mechanical properties of lightweight aggregate concrete using artificial neural network

The mechanical properties of lightweight aggregate concrete (LWAC) depend on the mixing ratio of its binders, normal weight aggregate (NWA), and lightweight aggregate (LWA). To characterize the relation between various concrete components and the mechanical characteristics of LWAC, extensive studies have been conducted, proposing empirical equations using regression models based on their experimental results. However, these results obtained from laboratory experiments do not provide consistent prediction accuracy due to the complicated relation between materials and mix proportions, and a general prediction model is needed, considering several mix proportions and concrete constituents. This study adopts the artificial neural network (ANN) for modeling the complex and nonlinear relation between constituents and the resulting compressive strength and elastic modulus of LWAC. To construct a database for the ANN model, a vast amount of detailed and extensive data was collected from the literature including various mix proportions, material properties, and mechanical characteristics of concrete. The optimal ANN architecture is determined to enhance prediction accuracy in terms of the numbers of hidden layers and neurons. Using this database and the optimal ANN model, the performance of the ANN-based prediction model is evaluated in terms of the compressive strength and elastic modulus of LWAC. Furthermore, these prediction accuracies are compared to the results of previous ANN-based analyses, as well as those obtained from the commonly used linear and nonlinear regression models

Anticholinesterase Therapy for Patients with Ophthalmoplegia Following Snake Bites: Report of Two Cases

Although ophthalmoplegia following snake bites is not indicative of a serious neurotoxic complication, symptoms of diplopia, dizziness and ocular discomfort can be emotionally devastating for patients. The authors experienced two cases of ophthalmoplegia following snake bites in Korea. The patients complained of diplopia that had developed several hours after the snake bites. The diplopia did not improve with antivenom treatment, but resolved completely after several injections of neostigmine

A copula method for modeling directional dependence of genes

<p>Abstract</p> <p>Background</p> <p>Genes interact with each other as basic building blocks of life, forming a complicated network. The relationship between groups of genes with different functions can be represented as gene networks. With the deposition of huge microarray data sets in public domains, study on gene networking is now possible. In recent years, there has been an increasing interest in the reconstruction of gene networks from gene expression data. Recent work includes linear models, Boolean network models, and Bayesian networks. Among them, Bayesian networks seem to be the most effective in constructing gene networks. A major problem with the Bayesian network approach is the excessive computational time. This problem is due to the interactive feature of the method that requires large search space. Since fitting a model by using the copulas does not require iterations, elicitation of the priors, and complicated calculations of posterior distributions, the need for reference to extensive search spaces can be eliminated leading to manageable computational affords. Bayesian network approach produces a discretely expression of conditional probabilities. Discreteness of the characteristics is not required in the copula approach which involves use of uniform representation of the continuous random variables. Our method is able to overcome the limitation of Bayesian network method for gene-gene interaction, i.e. information loss due to binary transformation.</p> <p>Results</p> <p>We analyzed the gene interactions for two gene data sets (one group is eight histone genes and the other group is 19 genes which include DNA polymerases, DNA helicase, type B cyclin genes, DNA primases, radiation sensitive genes, repaire related genes, replication protein A encoding gene, DNA replication initiation factor, securin gene, nucleosome assembly factor, and a subunit of the cohesin complex) by adopting a measure of directional dependence based on a copula function. We have compared our results with those from other methods in the literature. Although microarray results show a transcriptional co-regulation pattern and do not imply that the gene products are physically interactive, this tight genetic connection may suggest that each gene product has either direct or indirect connections between the other gene products. Indeed, recent comprehensive analysis of a protein interaction map revealed that those histone genes are physically connected with each other, supporting the results obtained by our method.</p> <p>Conclusion</p> <p>The results illustrate that our method can be an alternative to Bayesian networks in modeling gene interactions. One advantage of our approach is that dependence between genes is not assumed to be linear. Another advantage is that our approach can detect directional dependence. We expect that our study may help to design artificial drug candidates, which can block or activate biologically meaningful pathways. Moreover, our copula approach can be extended to investigate the effects of local environments on protein-protein interactions. The copula mutual information approach will help to propose the new variant of ARACNE (Algorithm for the Reconstruction of Accurate Cellular Networks): an algorithm for the reconstruction of gene regulatory networks.</p