Crime victimization and the implications for individual health and wellbeing: A Sheffield case study.

Public health and criminology have developed largely independently of one another at the research and policy levels so that the links between crime victimization and health status are not well understood. Although it is not difficult to support the idea of crime as a threat to the health of individuals and the wider community, the difficulty lies in quantifying the impact of crime on public health, while controlling other variables, including gender and ethnicity. We report the results of a study, the goals of which were to: develop an understanding conceptually of the relationships between different types of crime (violent and non-violent) and health; explore the impact of victimization on quality of life and physical and psychological wellbeing; investigate the role of social and demographic factors in shaping any relationships. The study is based on 840 responses from a postal survey administered to 4,100 households in Sheffield, England, located primarily in deprived areas where overall crime rates were high. Non-violent crimes were more frequently reported than violent crimes and in general, inner city neighbourhoods were associated with higher violent crime rates. Out of 392 victims of crime, 27% of individuals detailed physical injuries resulting directly from a crime event and 31% had taken some medical steps to treat a crime-related injury. 86% experienced at least one psychological or behavioural change, including stress, sleeping difficulties, loss of confidence, and depression. Logistic regression models estimated victimization risk based on various social and demographic variables. Violent crimes were consistently linked with higher odds of seeking medical treatment and a higher likelihood of experiencing psychological ill health effects or behavioural changes. In comparison, victims of non-violent or property crimes were not significantly associated with mental health or behavioural/lifestyle effects.This project was financed by research funds from the Gates Cambridge Trust and the Department of Geography (Philip Lake II Fund), University of Cambridge

An Efficient Algorithm for Deep Stochastic Contextual Bandits

In stochastic contextual bandit (SCB) problems, an agent selects an action based on certain observed context to maximize the cumulative reward over iterations. Recently there have been a few studies using a deep neural network (DNN) to predict the expected reward for an action, and the DNN is trained by a stochastic gradient based method. However, convergence analysis has been greatly ignored to examine whether and where these methods converge. In this work, we formulate the SCB that uses a DNN reward function as a non-convex stochastic optimization problem, and design a stage-wise stochastic gradient descent algorithm to optimize the problem and determine the action policy. We prove that with high probability, the action sequence chosen by this algorithm converges to a greedy action policy respecting a local optimal reward function. Extensive experiments have been performed to demonstrate the effectiveness and efficiency of the proposed algorithm on multiple real-world datasets.Comment: Accepted by AAAI 202

A novel routing optimization strategy based on reinforcement learning in perception layer networks

Wireless sensor networks have become incredibly popular due to the Internet of Things’ (IoT) rapid development. IoT routing is the basis for the efficient operation of the perception-layer network. As a popular type of machine learning, reinforcement learning techniques have gained significant attention due to their successful application in the field of network communication. In the traditional Routing Protocol for low-power and Lossy Networks (RPL) protocol, to solve the fairness of control message transmission between IoT terminals, a fair broadcast suppression mechanism, or Drizzle algorithm, is usually used, but the Drizzle algorithm cannot allocate priority. Moreover, the Drizzle algorithm keeps changing its redundant constant k value but never converges to the optimal value of k. To address this problem, this paper uses a combination based on reinforcement learning (RL) and trickle timer. This paper proposes an RL Intelligent Adaptive Trickle-Timer Algorithm (RLATT) for routing optimization of the IoT awareness layer. RLATT has triple-optimized the trickle timer algorithm. To verify the algorithm’s effectiveness, the simulation is carried out on Contiki operating system and compared with the standard trickling timer and Drizzle algorithm. Experiments show that the proposed algorithm performs better in terms of packet delivery ratio (PDR), power consumption, network convergence time, and total control cost ratio

Infrastructure for mobile sensor network in the Singapore coastal zone

URL to conference page. Scroll down to 2010 conference, click on "Paper and session list," and search the PDF for Patrikalakis.Singapore is an island nation located at southern tip of the Malaysian Peninsula. She is at a strategic location along major shipping routes and therefore has one of the busiest harbors in the world. Having a safe and secure harbor environment is vital to maintain trade and growth in the country and region. To help build and maintain a safe harbor environment, the Center of Environmental Sensing and Modelling (CENSAM) under the Singapore-MIT Alliance for Research and Technology (SMART) is developing a mobile sensor network in the Singapore coastal zone

Identification of Competing Endogenous RNA Regulatory Networks in Vitamin A Deficiency-Induced Congenital Scoliosis by Transcriptome Sequencing Analysis

Background/Aims: Congenital scoliosis (CS) is a result of anomalous development of vertebrae and is frequently associated with somitogenesis malformation. Although noncoding RNAs (ncRNAs) have been recently determined to be involved in the pathogenesis of CS, the competing endogenous RNA (ceRNA) regulatory networks in CS remain largely unknown. Methods: Sequencing was conducted to explore the ncRNA expression profiles in rat embryos (gestation day 9) following vitamin A deficiency (VAD) (n = 9 for the vitamin A deficiency-induced congenital scoliosis (VAD-CS) group and n = 4 for the control group). Real-time reverse transcriptase polymerase chain reaction (RT-PCR) was conducted to verify the expression levels of selected mRNAs, long noncoding RNAs (lncRNAs), circular RNAs (circRNAs), and microRNAs (miRNAs). Bioinformatics analysis was used to discover the possible relationships and functions of the ceRNAs. Results: A total of 749 mRNAs, 56 miRNAs, 685 lncRNAs, and 70 circRNAs were identified to have significantly different expression levels in the two groups. Wnt, PI3K-ATK, FoxO, EGFR, and mTOR were found to be the most significant pathways involved in VAD-CS pathogenesis. The circRNA/miRNA/mRNA and lncRNA/miRNA/mRNA networks of CS were built, and the gene expression mechanisms regulated by ncRNAs were unveiled via the ceRNA regulatory networks. Conclusion: We comprehensively identified ceRNA regulatory networks of embryonic somite development in VAD-CS as well as revealed the contribution of different ncRNA expression profiles. Our data demonstrate the association between mRNAs and ncRNAs in the pathogenic mechanism of CS

Room-temperature quantum interference in single perovskite quantum dot junctions

钙钛矿材料由于其高量子产率、载流子迁移率和独特的光致发光特性而在光电材料领域存在诸多潜在的重要应用。研究钙钛矿材料在纳米尺度下电荷输运的独特尺寸效应对钙钛矿光电器件的设计和开发具有重要的指导意义。洪文晶教授课题组基于机械可控裂结技术自主研发了具有皮米级位移调控灵敏度和飞安级电学测量精度的精密科学仪器，对南开大学李跃龙副教授团队合成的钙钛矿量子点进行了深入表征，研究工作成功将量子干涉的研究体系拓展至在光电领域具有重要应用的钙钛矿材料领域，为未来制备基于量子干涉效应的新型钙钛矿器件提供了一种全新的思路。 这一跨学科国际合作研究工作是在化学化工学院洪文晶教授、英国Lancaster 大学物理系Colin J. Lambert教授以及南开大学电子信息与光电工程学院李跃龙副教授的共同指导下完成的。化工系硕士研究生郑海宁、Lancaster University大学Songjun Hou博士、南开大学硕士研究生辛晨光为论文第一作者。博士后林禄春，博士研究生谭志冰、郑珏婷，硕士研究生蒋枫、张珑漪，本科生何文翔、李庆民等参与了论文的研究工作。刘俊扬特任副研究员、师佳副教授和萨本栋微纳米研究院杨扬副教授也参与了部分指导工作。The studies of quantum interference effects through bulk perovskite materials at the Ångstrom scale still remain as a major challenge. Herein, we provide the observation of roomtemperature quantum interference effects in metal halide perovskite quantum dots (QDs) using the mechanically controllable break junction technique. Single-QD conductance measurements reveal that there are multiple conductance peaks for the CH3NH3PbBr3 and CH3NH3PbBr2.15Cl0.85 QDs, whose displacement distributions match the lattice constant of QDs, suggesting that the gold electrodes slide through different lattice sites of the QD via Auhalogen coupling. We also observe a distinct conductance ‘jump’ at the end of the sliding process, which is further evidence that quantum interference effects dominate charge transport in these single-QD junctions. This conductance ‘jump’ is also confirmed by our theoretical calculations utilizing density functional theory combined with quantum transport theory. Our measurements and theory create a pathway to exploit quantum interference effects in quantum-controlled perovskite materials.This work was supported by the National Key R&D Program of China (2017YFA0204902, 2014DFE60170, 2018YFB1500105), the National Natural Science Foundation of China (Nos. 21673195, 21503179, 21490573, 61674084, 61874167), the Open Fund of the Key Laboratory of Optical Information Science & Technology (Nankai University) of China, the Fundamental Research Funds for the Central Universities of China (63181321, 63191414, 96173224), and the 111 Project (B16027), the Tianjin Natural Science Foundation (17JCYBJC41400), FET Open project 767187—QuIET, the EU project BAC-TO-FUEL and the UK EPSRC projects EP/N017188/1, EP/M014452/1. 该工作得到国家重点研发计划课题（2017YFA0204902）、国家自然科学基金（21673195、21503179、21490573）、厦门大学“人工智能分析引擎”双一流重大专项等项目的资助，也得到了固体表面物理化学国家重点实验室、能源材料化学协同创新中心的支持

Room-temperature quantum interference in single perovskite quantum dot junctions.

The studies of quantum interference effects through bulk perovskite materials at the Ångstrom scale still remain as a major challenge. Herein, we provide the observation of room-temperature quantum interference effects in metal halide perovskite quantum dots (QDs) using the mechanically controllable break junction technique. Single-QD conductance measurements reveal that there are multiple conductance peaks for the CH3NH3PbBr3 and CH3NH3PbBr2.15Cl0.85 QDs, whose displacement distributions match the lattice constant of QDs, suggesting that the gold electrodes slide through different lattice sites of the QD via Au-halogen coupling. We also observe a distinct conductance ’jump’ at the end of the sliding process, which is further evidence that quantum interference effects dominate charge transport in these single-QD junctions. This conductance ’jump’ is also confirmed by our theoretical calculations utilizing density functional theory combined with quantum transport theory. Our measurements and theory create a pathway to exploit quantum interference effects in quantum-controlled perovskite materials

Room-temperature quantum interference in single perovskite quantum dot junctions

The studies of quantum interference effects through bulk perovskite materials at the Ångstrom scale still remain as a major challenge. Herein, we provide the observation of room-temperature quantum interference effects in metal halide perovskite quantum dots (QDs) using the mechanically controllable break junction technique. Single-QD conductance measurements reveal that there are multiple conductance peaks for the CH3NH3PbBr3 and CH3NH3PbBr2.15Cl0.85 QDs, whose displacement distributions match the lattice constant of QDs, suggesting that the gold electrodes slide through different lattice sites of the QD via Au-halogen coupling. We also observe a distinct conductance ‘jump’ at the end of the sliding process, which is further evidence that quantum interference effects dominate charge transport in these single-QD junctions. This conductance ‘jump’ is also confirmed by our theoretical calculations utilizing density functional theory combined with quantum transport theory. Our measurements and theory create a pathway to exploit quantum interference effects in quantum-controlled perovskite materials

Assessing the human immune system through blood transcriptomics

Blood is the pipeline of the immune system. Assessing changes in transcript abundance in blood on a genome-wide scale affords a comprehensive view of the status of the immune system in health and disease. This review summarizes the work that has used this approach to identify therapeutic targets and biomarker signatures in the field of autoimmunity and infectious disease. Recent technological and methodological advances that will carry the blood transcriptome research field forward are also discussed