ESTIMATE THE EFFECT OF POLICE ON CRIME USING ELECTORAL DATA AND UPDATED DATA

It is surprisingly difficult to isolate causal effects of police on crime empirically due to the simultaneous determination of crime and police presence. Instruments are used to address the simultaneity concerns in the previous crime literature. The 2SLS results provide evidence indicating that additional police reduce crime. However, we might suspect whether the same instruments can generate consistent results with previous studies by using datasets of more recent years instead of thirty years ago and considering the change of policies, crime situation, and other factors. This paper use electoral cycles as instrumental variable and updated data of the 1985-2010 period trying to explore the correlation between police and crime using electoral cycles as instruments in different situation. Results show that there are positive elasticities of violent crimes with respect to police as well as negative elasticities for property crimes. Overall, we cannot conclude with strong evidence that increased police reduce crime using electoral cycles as instruments

GaN-Based Schottky Diode

Schottky diode, also known as Schottky barrier diode (SBD), fabricated on GaN and related III-Nitride materials has been researched intensively and extensively for the past two decades. This chapter reviews the property of GaN material, the advantage of GaN-based SBD, and the Schottky contact to GaN including current transporation theory, Schottky material selection, contact quality and thermal stability. The chapter also discusses about the GaN lateral, quasi-vertical and vertical SBDs, and AlGaN/GaN field effect SBDs: the evolution of the epitaxial structure, processing techniques and device structure. The chapter closes with challenges ahead and gives an outlook on the future development of the GaN SBDs

hp-mesh adaptation for 1-D multigroup neutron diffusion problems

In this work, we propose, implement and test two fully automated mesh adaptation methods for 1-D multigroup eigenproblems. The first method is the standard hp-adaptive refinement strategy and the second technique is a goal-oriented hp-adaptive refinement strategy. The hp-strategies deliver optimal guaranteed solutions obtained with exponential convergence rates with respect to the number of unknowns. The goal-oriented method combines the standard hp-adaptation technique with a goal-oriented adaptivity based on the simultaneous solution of an adjoint problem in order to compute quantities of interest, such as reaction rates in a sub-domain or point-wise fluxes or currents. These algorithms are tested for various multigroup 1-D diffusion problems and the numerical results confirm the optimal, exponential convergence rates predicted theoretically

Analysis of Tourism Copywriting for Chinese International Teachers from a Multimodal Perspective

International Chinese language volunteers often need to introduce Chinese tourism culture when teaching abroad. Due to the inability of learners to personally experience China in foreign environments, it can have a significant impact on teaching effectiveness. The multimodal form of combining images and text can more intuitively help overseas Chinese language learners understand and understand China, enrich their Chinese language learning after class, and satisfy their curiosity and longing for China. This article uses Halliday’s multimodal theory to organize and analyze 43 tourism texts edited by international Chinese language volunteers in teaching from four aspects: cultural level, contextual level, meaning level, and formal level. It also summarizes the precautions that Chinese language international teachers should pay attention to when writing tourism texts

Adaptive and Robust Multi-task Learning

We study the multi-task learning problem that aims to simultaneously analyze multiple datasets collected from different sources and learn one model for each of them. We propose a family of adaptive methods that automatically utilize possible similarities among those tasks while carefully handling their differences. We derive sharp statistical guarantees for the methods and prove their robustness against outlier tasks. Numerical experiments on synthetic and real datasets demonstrate the efficacy of our new methods.Comment: 69 pages, 2 figure