The Ubiquitin Specific Protease USP34 promotes ubiquitin signaling at DNA double-strand breaks

published_or_final_versio

Revealing microstructural evolutions, mechanical properties and wear performance of wire arc additive manufacturing homogeneous and heterogeneous NiTi alloy

Heterogeneous microstructure designs have attracted a great deal of attention, not only because they have the potential to achieve an ideal combination of two conflicting properties, but also because the processes involved in their fabrication are cost-effective and can be scaled up for industrial production. The process parameters in the preparation process have an important effect on the microstructure and properties of alloy members prepared by wire arc additive manufacturing (WAAM) technology. It was expected that the spatial heterogeneous microstructure with large microstructural heterogeneities in metals can be formed through changing the process parameters. In this work, homogeneous NiTi thin-walled component and heterogeneous NiTi thin-walled component were fabricated using WAAM technology by adjusting the heat input. The effects of deposition height and heat input on the microstructure, mechanical properties and wear properties of WAAM NiTi alloys were investigated. The results show that grains were gradually refined with the increase of deposition height in the homogeneous WAAM NiTi component. The ultimate tensile strength of homogeneous WAAM NiTi component increased from 606.87 MPa to 654.45 MPa and the elongation increased from 12.72% to 15.38%, as the increase of deposition height. Moreover, the homogeneous WAAM NiTi component exhibited excellent wear resistance, the coefficient of friction decreased from 0.760 to 0.715 with the increase of deposition height. Meanwhile, the grains in the heterogeneous WAAM NiTi component shows the finest grains in the central region. The ultimate tensile strength of the lower region, middle region and upper region of heterogeneous WAAM NiTi components were 556.12 MPa, 599.53 MPa and 739.79 MPa, and the elongations were 12.98%, 16.69%, 21.74%, respectively. The coefficient of friction for the lower region, middle region and upper region of heterogeneous WAAM NiTi components were 0.713, 0.720 and 0.710, respectively. The microhardness and cyclic compression properties of the homogeneous components with higher heat input were better than those of the heterogeneous components for the same deposition height. The tensile yield strength, elongation and wear resistance of the heterogeneous components were superior compared to the homogeneous components. These results can be used to optimize the WAAM process parameters to prepare NiTi components with excellent mechanical properties

Primary Care Workforce And Continuous Medical Education In China: Lessons To Learn From A Nationwide Cross-sectional Survey

published_or_final_versio

Human Gyrovirus Apoptin shows a similar subcellular distribution pattern and apoptosis induction as the chicken anaemia virus derived VP3/Apoptin

The chicken anaemia virus-derived protein Apoptin/VP3 (CAV-Apoptin) has the important ability to induce tumour-selective apoptosis in a variety of human cancer cells. Recently the first human Gyrovirus (HGyV) was isolated from a human skin swab. It shows significant structural and organisational resemblance to CAV and encodes a homologue of CAV-Apoptin/VP3. Using overlapping primers we constructed a synthetic human Gyrovirus Apoptin (HGyV-Apoptin) fused to green fluorescent protein in order to compare its apoptotic function in various human cancer cell lines to CAV-Apoptin. HGyV-Apoptin displayed a similar subcellular expression pattern as observed for CAV-Apoptin, marked by translocation to the nucleus of cancer cells, although it is predominantly located in the cytosol of normal human cells. Furthermore, expression of either HGyV-Apoptin or CAV-Apoptin in several cancer cell lines triggered apoptosis at comparable levels. These findings indicate a potential anti-cancer role for HGyV-Apoptin

Anyonic interferometry and protected memories in atomic spin lattices

Strongly correlated quantum systems can exhibit exotic behavior called topological order which is characterized by non-local correlations that depend on the system topology. Such systems can exhibit remarkable phenomena such as quasi-particles with anyonic statistics and have been proposed as candidates for naturally fault-tolerant quantum computation. Despite these remarkable properties, anyons have never been observed in nature directly. Here we describe how to unambiguously detect and characterize such states in recently proposed spin lattice realizations using ultra-cold atoms or molecules trapped in an optical lattice. We propose an experimentally feasible technique to access non-local degrees of freedom by performing global operations on trapped spins mediated by an optical cavity mode. We show how to reliably read and write topologically protected quantum memory using an atomic or photonic qubit. Furthermore, our technique can be used to probe statistics and dynamics of anyonic excitations.Comment: 14 pages, 6 figure

Back reaction, emission spectrum and entropy spectroscopy

Recently, an interesting work, which reformulates the tunneling framework to directly produce the Hawking emission spectrum and entropy spectroscopy in the tunneling picture, has been received a broad attention. However, during the emission process, most related observations have not incorporated the effects of back reaction on the background spacetime, whose derivations are therefore not the desiring results for the real physical process. With this point as a central motivation, in this paper we suitably adapt the \emph{reformulated} tunneling framework so that it can well accommodate the effects of back reaction to produce the Hawking emission spectrum and entropy spectroscopy. Consequently, we interestingly find that, when back reaction is considered, the Parikh-Wilczek's outstanding observations that, an isolated radiating black hole has an unitary-evolving emission spectrum that is \emph{not} precisely thermal, but is related to the change of the Bekenstein-Hawking entropy, can also be reproduced in the reformulated tunneling framework, meanwhile the entropy spectrum has the same form as that without inclusion of back reaction, which demonstrates the entropy quantum is \emph{independent} of the effects of back reaction. As our final analysis, we concentrate on the issues of the black hole information, but \emph{unfortunately} find that, even including the effects of back reaction and higher-order quantum corrections, such tunneling formalism can still not provide a mechanism for preserving the black hole information.Comment: 16 pages, no figure, use JHEP3.cls. to be published in JHE

Quantum corrections and black hole spectroscopy

In the work \cite{BRM,RBE}, black hole spectroscopy has been successfully reproduced in the tunneling picture. As a result, the derived entropy spectrum of black hole in different gravity (including Einstein's gravity, Einstein-Gauss-Bonnet gravity and Ho\v{r}ava-Lifshitz gravity) are all evenly spaced, sharing the same forms as $S_n=n$, where physical process is only confined in the semiclassical framework. However, the real physical picture should go beyond the semiclassical approximation. In this case, the physical quantities would undergo higher-order quantum corrections, whose effect on different gravity shares in different forms. Motivated by these facts, in this paper we aim to observe how quantum corrections affect black hole spectroscopy in different gravity. The result shows that, in the presence of higher-order quantum corrections, black hole spectroscopy in different gravity still shares the same form as $S_n=n$, further confirming the entropy quantum is universal in the sense that it is not only independent of black hole parameters, but also independent of higher-order quantum corrections. This is a desiring result for the forthcoming quantum gravity theory.Comment: 14 pages, no figure, use JHEP3.cls. to be published in JHE

Resolution of the stochastic strategy spatial prisoner's dilemma by means of particle swarm optimization

We study the evolution of cooperation among selfish individuals in the stochastic strategy spatial prisoner's dilemma game. We equip players with the particle swarm optimization technique, and find that it may lead to highly cooperative states even if the temptations to defect are strong. The concept of particle swarm optimization was originally introduced within a simple model of social dynamics that can describe the formation of a swarm, i.e., analogous to a swarm of bees searching for a food source. Essentially, particle swarm optimization foresees changes in the velocity profile of each player, such that the best locations are targeted and eventually occupied. In our case, each player keeps track of the highest payoff attained within a local topological neighborhood and its individual highest payoff. Thus, players make use of their own memory that keeps score of the most profitable strategy in previous actions, as well as use of the knowledge gained by the swarm as a whole, to find the best available strategy for themselves and the society. Following extensive simulations of this setup, we find a significant increase in the level of cooperation for a wide range of parameters, and also a full resolution of the prisoner's dilemma. We also demonstrate extreme efficiency of the optimization algorithm when dealing with environments that strongly favor the proliferation of defection, which in turn suggests that swarming could be an important phenomenon by means of which cooperation can be sustained even under highly unfavorable conditions. We thus present an alternative way of understanding the evolution of cooperative behavior and its ubiquitous presence in nature, and we hope that this study will be inspirational for future efforts aimed in this direction.Comment: 12 pages, 4 figures; accepted for publication in PLoS ON

Orexin receptors exert a neuroprotective effect in Alzheimer's disease (AD) via heterodimerization with GPR103

Orexins are neuropeptides that regulate the sleep-wake cycle and feeding behaviour. QRFP is a newly discovered neuropeptide which exerts similar orexigenic activity, thus playing an important role in energy homeostasis and regulation of appetite. The exact expression and signalling characteristics and physiological actions of QRFP and its receptor GPR103 are poorly understood. Alzheimerâ €™ s disease (AD) patients experience increased nocturnal activity, excessive daytime sleepiness, and weight loss. We hypothesised therefore that orexins and QRFP might be implicated in the pathophysiology of AD. We report that the down-regulation of hippocampal orexin receptors (OXRs) and GPR103 particularly in the cornu ammonis (CA) subfield from AD patients suffering from early onset familial AD (EOFAD) and late onset familial AD (LOAD). Using an in vitro model we demonstrate that this downregulation is due to to Aβ-plaque formation and tau hyper-phosphorylation. Transcriptomics revealed a neuroprotective role for both orexins and QRFP. Finally we provide conclusive evidence using BRET and FRET that OXRs and GPR103 form functional hetero-dimers to exert their effects involving activation of ERK 1/2. Pharmacological intervention directed at the orexigenic system may prove to be an attractive avenue towards the discovery of novel therapeutics for diseases such as AD and improving neuroprotective signalling pathways

Evolutionary Computation, Optimization and Learning Algorithms for Data Science

A large number of engineering, science and computational problems have yet to be solved in a computationally efficient way. One of the emerging challenges is how evolving technologies grow towards autonomy and intelligent decision making. This leads to collection of large amounts of data from various sensing and measurement technologies, e.g., cameras, smart phones, health sensors, smart electricity meters, and environment sensors. Hence, it is imperative to develop efficient algorithms for generation, analysis, classification, and illustration of data. Meanwhile, data is structured purposefully through different representations, such as large-scale networks and graphs. We focus on data science as a crucial area, specifically focusing on a curse of dimensionality (CoD) which is due to the large amount of generated/sensed/collected data. This motivates researchers to think about optimization and to apply nature-inspired algorithms, such as evolutionary algorithms (EAs) to solve optimization problems. Although these algorithms look un-deterministic, they are robust enough to reach an optimal solution. Researchers do not adopt evolutionary algorithms unless they face a problem which is suffering from placement in local optimal solution, rather than global optimal solution. In this chapter, we first develop a clear and formal definition of the CoD problem, next we focus on feature extraction techniques and categories, then we provide a general overview of meta-heuristic algorithms, its terminology, and desirable properties of evolutionary algorithms