The Post–endodontic Adhesive Interface: Theoretical Perspectives and Potential Flaws

Introduction The aim of this review was to analyze the potential of successful bonds of endodontic posts to radicular dentin as well as the limitations of the post–endodontic adhesive interface. Methods The MEDLINE/PubMed and Web of Science electronic databases were searched. The search was augmented by a manual search of the pertinent bibliographies. Results The post–endodontic adhesive interface finds application in the endodontic cohesive units. Many techniques and materials exist to improve the bond between endodontic posts and resin-based materials as well as between resin-based materials and radicular dentin. Different techniques used for the adhesion of metallic and fiber-reinforced posts are discussed and critically analyzed. Conclusions Although adhesive cementation of endodontic posts is popular, a long-term predictable bond may be compromised because of procedures related to the endodontic treatment and/or the adhesive cementation procedures. Microleakage and degradation phenomena may further jeopardize the post–endodontic adhesive interface

Depth-wise Decomposition for Accelerating Separable Convolutions in Efficient Convolutional Neural Networks

Very deep convolutional neural networks (CNNs) have been firmly established as the primary methods for many computer vision tasks. However, most state-of-the-art CNNs are large, which results in high inference latency. Recently, depth-wise separable convolution has been proposed for image recognition tasks on computationally limited platforms such as robotics and self-driving cars. Though it is much faster than its counterpart, regular convolution, accuracy is sacrificed. In this paper, we propose a novel decomposition approach based on SVD, namely depth-wise decomposition, for expanding regular convolutions into depthwise separable convolutions while maintaining high accuracy. We show our approach can be further generalized to the multi-channel and multi-layer cases, based on Generalized Singular Value Decomposition (GSVD) [59]. We conduct thorough experiments with the latest ShuffleNet V2 model [47] on both random synthesized dataset and a large-scale image recognition dataset: ImageNet [10]. Our approach outperforms channel decomposition [73] on all datasets. More importantly, our approach improves the Top-1 accuracy of ShuffleNet V2 by ~2%.Comment: CVPR 2019 workshop, Efficient Deep Learning for Computer Visio

Investigation of the tetraquark states QqQˉqˉQq\bar{Q} \bar{q} in the improved chromomagnetic interaction model

In the framework of the improved chromomagnetic interaction model, we complete a systematic study of the $S$-wave tetraquark states $Qq\bar{Q}\bar{q}$ ($Q=c,b$, and $q=u,d,s$) with different quantum numbers, $J^{PC}=0^{+(+)}$, $1^{+(\pm)}$, and $2^{+(+)}$. The mass spectra of tetraquark states are predicted and the possible decay channels are analyzed by considering both the angular momentum and $\mathcal{C}$-parity conservation. The recently observed hidden-charm tetraquark states with strangeness, such as $Z_{cs}(3985)^-$, $X(3960)$, and $Z_{cs}(4220)^+$, can be well explained in our model. Besides, based on the wave function of each tetraquark state, we find that the low-lying states of each $Qq\bar{Q}\bar{q}$ configuration have a large overlap to the $Q\bar Q$ and $q\bar q$ meson basis, instead of $Q\bar q$ and $q\bar Q$ meson basis. This indicates one can search these tetraquark states in future experiments via the channel of $Q\bar Q$ and $q\bar q$ mesons.Comment: 11 pages, 9 figures, and 4 tables; accepted for publication in Chinese Physics

Key pathways and genes controlling the development and progression of clear cell renal cell carcinoma (ccRCC) based on gene set enrichment analysis

BACKGROUND: Clear-cell renal cell carcinoma (ccRCC) is one of the most common types of kidney cancer in adults; however, its causes are not completely understood. The study was designed to filter the key pathways and genes associated with the occurrence or development of ccRCC, acquaint its pathogenesis at gene and pathway level, to provide more theory evidence and targeted therapy for ccRCC. METHODS: Gene set enrichment analysis (GSEA) and meta-analysis (Meta) were used to screen the critical pathways and genes which may affect the occurrence and progression of ccRCC on the transcription level. Corresponding pathways of significant genes were obtained with the online website DAVID (http://david.abcc.ncifcrf.gov/). RESULTS: Thirty seven consistent pathways and key genes in these pathways related to ccRCC were obtained with combined GSEA and meta-analysis. These pathways were mainly involved in metabolism, organismal systems, cellular processes and environmental information processing. CONCLUSION: The gene pathways that we identified could provide insight concerning the development of ccRCC. Further studies are needed to determine the biological function for the positive genes

Galactic Phylogenetics

Phylogenetics is a widely used concept in evolutionary biology. It is the reconstruction of evolutionary history by building trees that represent branching patterns and sequences. These trees represent shared history, and it is our intention for this approach to be employed in the analysis of Galactic history. In Galactic archaeology the shared environment is the interstellar medium in which stars form and provides the basis for tree-building as a methodological tool. Using elemental abundances of solar-type stars as a proxy for DNA, we built in Jofre et al 2017 such an evolutionary tree to study the chemical evolution of the solar neighbourhood. In this proceeding we summarise these results and discuss future prospects.Comment: Contribution to IAU Symposium No. 334: Rediscovering our Galax