Statistical inference of partially linear regression models with heteroscedastic errors

The authors study a heteroscedastic partially linear regression model and develop an inferential procedure for it. This includes a test of heteroscedasticity, a two-step estimator of the heteroscedastic variance function, semiparametric generalized least-squares estimators of the parametric and nonparametric components of the model, and a bootstrap goodness of fit test to see whether the nonparametric component can be parametrized

Quantifying the short-term dynamics of soil organic carbon decomposition using a power function model

Introduction Soil heterotrophic respiration (R h, an indicator of soil organic carbon decomposition) is an important carbon efflux of terrestrial ecosystems. However, the dynamics of soil R h and its empirical relations with climatic factors have not been well understood. Methods We incubated soils of three subtropical forests at five temperatures (10, 17, 24, 31, and 38 °C) and five moistures (20, 40, 60, 80, and 100% water holding capacity (WHC)) over 90 days. R h was measured throughout the course of the incubation. Three types of models (log-linear, exponential, and power model) were fitted to the measurements and evaluated based on the coefficient of determination (r 2) and Akaike Information Criterion (AIC) of the model. Further regression analysis was used to derive the empirical relations between model parameters and the two climatic factors. Results Among the three models, the power function model (R h = R 1 t −k) performed the best in fitting the descending trend of soil R h with incubation time (r 2 \u3e 0.69 for 26 of 30 models). Both R 1 and k generally increased linearly with soil temperature but varied quadratically with soil moisture in the three forest soils. Conclusions This study demonstrated that the power function model was much more accurate than the exponential decay model in describing the decomposition dynamics of soil organic carbon (SOC) in mineral soils of subtropical forests. The empirical relations and parameter values derived from this incubation study may be incorporated into process-based ecosystem models to simulate R h responses to climate changes

Base Station Cooperation for Confidential Broadcasting in Multi-Cell Networks

We design linear precoders that perform confidential broadcasting in multi-cell networks for two different forms of base station (BS) cooperation, namely, multi-cell processing (MCP) and coordinated beamforming (CBf). We consider a twocell network where each cell consists of an N-antenna BS and K single-antenna users. For such a network, we design a linear precoder based on the regularized channel inversion (RCI) for the MCP and a linear precoder based on the generalized RCI for the CBf. For each form of BS cooperation, we derive new channel-independent expressions to approximate the secrecy sum rate achieved by the precoder in the large system regime where K, N → ∞ with a fixed ratio β = K/N. Using these results, we determine the optimal regularization parameters of the RCI and the generalized RCI precoders that maximize the secrecy sum rate for the MCP and the CBf, respectively. We further propose power-reduction strategies that significantly increase the secrecy sum rate at high transmit signal-to-noise ratios when the network load is high. Our numerical results substantiate the derived expressions, verify the optimality of the determined optimal regularization parameters, and demonstrate the performance improvement offered by the proposed power-reduction strategies.ARC Discovery Projects Grant DP15010390

A two-stage approach to semilinear in-slide models

The semilinear in-slide models (SLIMs) have been shown to be effective method for normalizing microarray data (Fan, et al. 2004). Using a backfitting method, Fan, Peng and Huang (2005) proposed a profile least squares (PLS) estimation for the parametric and nonparametric components. The general asymptotic properties for their estimator is not developed. In this paper, we consider a new approach, two-stage estimation, which enables us to establish the asymptotic normalities for both of the parametric and nonparametric component estimators. We further propose a plug-in bandwidth selector using the asymptotic normality of the nonparametric component estimator. The proposed method allow for the modeling of the aggregated SLIMs case where we can explicitly show that taking the aggregated information into account can improve both of the parametric and nonparametric component estimator by the proposed two-stage approach. Some simulation studies are conducted to illustrate the finite sample performance of the proposed procedures

Development of a time-to-digital converter ASIC for the upgrade of the ATLAS Monitored Drift Tube detector

The upgrade of the ATLAS muon spectrometer for high-luminosity LHC requires new trigger and readout electronics for the various elements of the detector. We present the design of a time-to-digital converter (TDC) ASIC prototype for the ATLAS Monitored Drift Tube (MDT) detector. The chip was fabricated in a GlobalFoundries 130 nm CMOS technology. Studies indicate that its timing and power consumption characteristics meet the design specifications, with a timing bin variation of 40 ps for all 48 channels with a power consumption of about 6.5 mW per channel.Comment: 9 pages, 12 figure

Failure to Complete Cross-Border M&As:“To”vs.“From” Emerging Markets

周晨希是厦门大学管理学院2015年引进的海归博士，受聘为“群贤计划”市场学助理教授。他是美国佛罗利达大学商学院营销学专业博士,主要从事企业战略管理、行为经济学等方面的研究。 本研究调查涉及新兴市场跨国并购完成的预测因数如何取决于全球扩张的方向,即向发展中市场的入境投资或来自发达市场的出境投资。【Abstract】While cross-border mergers and acquisitions (M&As) involving emerging markets have been increasing in recent years, a high percentage collapse before completion. This study investigates how the predictors of cross-border M&A completion involving emerging markets depend upon the direction of global expansion, i.e., investment inbound to a developing market or outbound from a developing market. Analysis based on 15 years of data from four emerging economies, Brazil, Russia, India, and China, from 1995 to 2010,reveals fundamental differences in the predictors of inbound vs. outbound M&A completion. Country-level factors reflecting differences in political, trade,and legal environments strongly affect the completion for inbound M&As, but have a much weaker influence on outbound M&As. By contrast, firm-level factors such as past M&A experience have a significantly stronger effect on completion for outbound than for inbound M&As. Most interestingly, two deal-level factors (the percentage of stake sought by the acquirer and whether or not the deal is a cash transaction) increase the likelihood of completion for inbound but decrease it for outbound M&As. These findings have important managerial implications for enhancing the success of global expansions

A Programmable Time Alignment Scheme for Detector Signals from the Upgraded muon Spectrometer at the ATLAS Experiment

We present a programmable time alignment scheme used in an ASIC for the ATLAS forward muon trigger development. The scheme utilizes regenerated clocks with programmable phases to compensate for the timing offsets introduced by different detector trace lengths. Each ASIC used in the design has 104 input channels with delay compensation circuitry providing steps of ~ 3 ns and a full range of 25 ns for each channel. Detailed implementation of the scheme including majority logic to suppress single-event effects is presented. The scheme is flexible and fully synthesizable. The approach is adaptable to other applications with similar phase shifting requirements. In addition, the design is resource efficient and is suitable for cost-effective digital implementation with a large number of channels.Comment: 5 pages, 8 figure