Bioinspired Multifunctional Anti-icing Hydrogel

The recent anti-icing strategies in the state of the art mainly focused on three aspects: inhibiting ice nucleation, preventing ice propagation, and decreasing ice adhesion strength. However, it is has proved difficult to prevent ice nucleation and propagation while decreasing adhesion simultaneously, due to their highly distinct, even contradictory design principles. In nature, anti-freeze proteins (AFPs) offer a prime example of multifunctional integrated anti-icing materials that excel in all three key aspects of the anti-icing process simultaneously by tuning the structures and dynamics of interfacial water. Here, inspired by biological AFPs, we successfully created a multifunctional anti-icing material based on polydimethylsiloxane-grafted polyelectrolyte hydrogel that can tackle all three aspects of the anti-icing process simultaneously. The simplicity, mechanical durability, and versatility of these smooth hydrogel surfaces make it a promising option for a wide range of anti-icing applications

First Subleading Power Resummation for Event Shapes

We derive and analytically solve renormalization group (RG) equations of gauge invariant non-local Wilson line operators which resum logarithms for event shape observables $\tau$ at subleading power in the $\tau\ll 1$ expansion. These equations involve a class of universal jet and soft functions arising through operator mixing, which we call $\theta$-jet and $\theta$-soft functions. An illustrative example involving these operators is introduced which captures the generic features of subleading power resummation, allowing us to derive the structure of the RG to all orders in $\alpha_s$, and provide field theory definitions of all ingredients. As a simple application, we use this to obtain an analytic leading logarithmic result for the subleading power resummed thrust spectrum for $H\to gg$ in pure glue QCD. This resummation determines the nature of the double logarithmic series at subleading power, which we find is still governed by the cusp anomalous dimension. We check our result by performing an analytic calculation up to ${\cal O}(\alpha_s^3)$. Consistency of the subleading power RG relates subleading power anomalous dimensions, constrains the form of the $\theta$-soft and $\theta$-jet functions, and implies an exponentiation of higher order loop corrections in the subleading power collinear limit. Our results provide a path for carrying out systematic resummation at subleading power for collider observables.Comment: 39 pages + 2 Appendices, 2 figures. v2: journal versio

International clinical practice recommendations on the definition, diagnosis, assessment, intervention, and psychosocial aspects of developmental coordination disorder – Chinese (Mandarin) translation

目的: 本国际临床指南由欧洲残疾儿童学会（the European Academy of Childhood Disability，EACD）牵头制定，旨在解决发育性协调障碍（developmental coordination disorder，DCD）的定义、诊断、评估、干预以及与社会心理方面的临床应用关键问题。 方法: 本指南针对五个领域的关键问题，通过文献综述和专家团队的正式讨论达成共识。为保证指南的循证基础，以“机制”、“评估”和“干预”为检索词, 对2012年更新以来提出的最新建议以及新增的“社会心理问题”和“青少年/成人”为检索词进行检索。根据牛津大学循证医学中心证据等级 (证据水平 [level of evidence, LOE]1–4) 将结果进行分类，最终转化为指南建议。并由国际、多学科专家小组举行了两次会议，5个回合的Delphi 专家问卷调查，制定了高质量临床应用实践 (good clinical practice，GCP) 。 结果: 本指南共制定35条建议。其中8条以文献综述为依据 (3 条涉及“评估”，5条涉及“干预”)； 22 条在 2012 年指南的基础上进行了更新；其他为涉及诊断、评估 (3条GCP) 及社会心理问题 (2 条 GCP) 的新建议。此外，其中有1条(LOE)新建议提出视频游戏可作为以活动和参与为导向的传统干预措施的辅助手段，并针对青少年和成人DCD提出了 2 条新建议 (1 条 GCP，1 条 LOE)。 结论: 本指南是基于当前的研究证据和专家共识对DCD进行全面概述。它反映了不同学科临床和科研人员的最新科技水平。本国际指南可作为各国制定指南的基础

Mining Event-Oriented Topics in Microblog Stream with Unsupervised Multi-View Hierarchical Embedding

This article presents an unsupervised multi-view hierarchical embedding (UMHE) framework to sufficiently reveal the intrinsic topical knowledge in social events. Event-oriented topics are highly related to such events as it can provide explicit descriptions of what have happened in social community. In many real-world cases, however, it is difficult to include all attributes of microblogs, more often, textual aspects only are available. Traditional topic modelling methods have failed to generate event-oriented topics with the textual aspects, since the inherent relations between topics are often overlooked in these methods. Meanwhile, the metrics in original word vocabulary space might not effectively capture semantic distances. Our UMHE framework overcomes the severe information deficiency and poor feature representation. The UMHE first develops a multi-view Bayesian rose tree to preliminarily generate prior knowledge for latent topics and their relations. With such prior knowledge, we design an unsupervised translation-based hierarchical embedding method to make a better representation of these latent topics. By applying self-adaptive spectral clustering on the embedding space and the original space concomitantly, we eventually extract event-oriented topics in word distributions to express social events. Our framework is purely data-driven and unsupervised, without any external knowledge. Experimental results on TREC Tweets2011 dataset and Sina Weibo dataset demonstrate that the UMHE framework can construct hierarchical structure with high fitness, but also yield topic embeddings with salient semantics; therefore, it can derive event-oriented topics with meaningful descriptions

ATG7 Promotes Bladder Cancer Invasion via Autophagy-Mediated Increased ARHGDIB mRNA Stability

Since invasive bladder cancer (BC) can progress to life threatening metastases, understanding the molecular mechanisms underlying BC invasion is crucial for potentially decreasing the mortality of this disease. Herein, it is discovered that autophagy-related gene 7 (ATG7) is remarkably overexpressed in human invasive BC tissues. The knockdown of ATG7 in human BC cells dramatically inhibits cancer cell invasion, revealing that ATG7 is a key player in regulating BC invasion. Mechanistic studies indicate that MIR190A is responsible for ATG7 mRNA stability and protein overexpression by directly binding to ATG7 mRNA 3'-UTR. Furthermore, ATG7-mediated autophagy promotes HNRNPD (ARE/poly(U)-binding/degradation factor 1) protein degradation, and in turn reduces HNRNPD interaction with ARHGDIB mRNA, resulting in the elevation of ARHGDIB mRNA stability, and subsequently leading to BC cell invasion. The identification of the MIR190A/ATG7 autophagic mechanism regulation of HNRNPD/ARHGDIB expression provides an important insight into understanding the nature of BC invasion and suggests that autophagy may represent a potential therapeutic strategy for the treatment of human BC patients

Tensor Regression with Applications in Neuroimaging Data Analysis

Classical regression methods treat covariates as a vector and estimate a corresponding vector of regression coefficients. Modern applications in medical imaging generate covariates of more complex form such as multidimensional arrays (tensors). Traditional statistical and computational methods are proving insufficient for analysis of these high-throughput data due to their ultrahigh dimensionality as well as complex structure. In this article, we propose a new family of tensor regression models that efficiently exploit the special structure of tensor covariates. Under this framework, ultrahigh dimensionality is reduced to a manageable level, resulting in efficient estimation and prediction. A fast and highly scalable estimation algorithm is proposed for maximum likelihood estimation and its associated asymptotic properties are studied. Effectiveness of the new methods is demonstrated on both synthetic and real MRI imaging data.Comment: 27 pages, 4 figure