A new noncontact method for the prediction of both internal thermal resistance and junction temperature of white light-emitting diodes

Although critical to the lifetime of LED, the junction temperature of LED cannot be measured easily. Based on the general photoelectrothermal theory for LED systems, the coefficient for the reduction of luminous efficacy with junction temperature is first related to the characteristic temperature of the LED. Then, a noncontact method for estimating the internal junction temperature T j and junction-case thermal resistance R jc of LED from the external power and luminous flux measurements is presented and verified practically. Since these external measurements can be obtained easily, the proposal provides a simple tool for checking T j in new LED system designs without using expensive or sophisticated thermal monitoring equipment for the LED junctions. The proposed method has been checked with measurements on LED devices from three different brands with both constant and nonconstant R jc. The theoretical predictions are found to be highly consistent with practical measurements. © 2011 IEEE.published_or_final_versio

Novel self-configurable current-mirror techniques for reducing current imbalance in parallel Light-Emitting Diode (LED) strings

Traditional current-mirror methods require one fixed current reference for controlling other current source or sources. In this paper, a new self-configurable current-mirror method that can dynamically determine the best current branch as the current reference in order to ensure good balance of all parallel current sources is proposed. The operating principle involves a dynamic and self-configurable transistor-based current-balancing circuit that can be operated in saturation or linear mode. In either operating mode, good current balance or sharing among all parallel-connected current sources can be guaranteed. The novel current-balancing circuit does not require a separate power supply for powering their control circuits. The proposal is a modular one that can be expanded to any number of parallel current sources. Its principle has been successfully applied to current balancing of parallel LED strings. © 2011 IEEE.published_or_final_versio

Towards Atomic Level Simulation of Electron Devices Including the Semiconductor-Oxide Interface

We report a milestone in device modeling whereby a planar MOSFET with extremely thin silicon on insulator channel is simulated at the atomic level, including significant parts of the gate and buried oxides explicitly in the simulation domain, in ab initio fashion, i.e without material or geometrical parameters. We use the density-functional-based tight-binding formalism for constructing the device Hamiltonian, and non-equilibrium Green's functions formalism for calculating electron current. Simulations of Si/SiO2 super-cells agree very well with experimentally observed band-structure phenomena in SiO2-confined sub-6 nm thick Si films. Device simulations of ETSOI MOSFET with 3 nm channel length and sub-nm channel thickness also agree well with reported measurements of the transfer characteristics of a similar transistor.published_or_final_versio

Suspended two-dimensional electron gases in In₀.₇₅Ga₀.₂₅As quantum wells

We demonstrate that In0.75Ga0.25As quantum wells can be freely suspended without losing electrical quality when the epitaxial strain-relieving buffer layer is removed. In applied magnetic fields, non-dissipative behavior is observed in the conductivity, and a current induced breakdown of the quantum Hall effect shows a lower critical current in the suspended layers due to efficient thermal isolation compared to the non-suspended-control device. Beyond the critical current, background impurity scattering in the suspended two-dimensional channel regions dominates with stochastic, resonant-like features in the conductivity. This device fabrication scheme offers the potential for thermally isolated devices containing suspension-asymmetry-induced, high spin–orbit coupling strengths with reduced electron–phonon interaction behavior but without introducing high levels of disorder in the processing. This work was funded by EPSRC Grant Nos. EP/K004077/1 and EP/R029075/1, UK. We thank Professor Chris Ford for useful discussions

A multi-scale modeling of junctionless field-effect transistors

In this work, we simulate a realistic junctionless (JL) field-effect transistor using a multi-scale approach. Our approach features a combination of the first-principles atomistic calculation, semi-classical semiconductor device simulation, compact model generation, and circuit simulation. The transfer characteristics of JL transistors are simulated by a recently developed quantum mechanical/electromagnetics method, and good agreement is obtained compared to experiment. A compact model for JL transistors is then generated for subsequent circuit simulation. We demonstrate a multi-scale modeling framework for quantum mechanical effects in nano-scale devices for next generation electronic design automation. © 2013 AIP Publishing LLC.published_or_final_versio

Empirical likelihood estimation of the spatial quantile regression

The spatial quantile regression model is a useful and flexible model for analysis of empirical problems with spatial dimension. This paper introduces an alternative estimator for this model. The properties of the proposed estimator are discussed in a comparative perspective with regard to the other available estimators. Simulation evidence on the small sample properties of the proposed estimator is provided. The proposed estimator is feasible and preferable when the model contains multiple spatial weighting matrices. Furthermore, a version of the proposed estimator based on the exponentially tilted empirical likelihood could be beneficial if model misspecification is suspect

MicroRNA-21 promotes survival but not functional maturation of human embryonic stem cell-derived cardiomyocytes (hESC-CMs)

published_or_final_versionThe 16th Medical Resarch Conference (MRC), The University of Hong Kong, Hong Kong, China, 22 January 2011. In Hong Kong Medical Journal, 2011, v. 17, suppl. 1, p. 35, abstract no. 5

IFN-gamma is associated with risk of Schistosoma japonicum infection in China.

Before the start of the schistosomiasis transmission season, 129 villagers resident on a Schistosoma japonicum-endemic island in Poyang Lake, Jiangxi Province, 64 of whom were stool-positive for S. japonicum eggs by the Kato method and 65 negative, were treated with praziquantel. Forty-five days later the 93 subjects who presented for follow-up were all stool-negative. Blood samples were collected from all 93 individuals. S. japonicum soluble worm antigen (SWAP) and soluble egg antigen (SEA) stimulated IL-4, IL-5 and IFN-gamma production in whole-blood cultures were measured by ELISA. All the subjects were interviewed nine times during the subsequent transmission season to estimate the intensity of their contact with potentially infective snail habitats, and the subjects were all re-screened for S. japonicum by the Kato method at the end of the transmission season. Fourteen subjects were found to be infected at that time. There was some indication that the risk of infection might be associated with gender (with females being at higher risk) and with the intensity of water contact, and there was evidence that levels of SEA-induced IFN-gamma production were associated with reduced risk of infection

Forecasting Player Behavioral Data and Simulating in-Game Events

Understanding player behavior is fundamental in game data science. Video games evolve as players interact with the game, so being able to foresee player experience would help to ensure a successful game development. In particular, game developers need to evaluate beforehand the impact of in-game events. Simulation optimization of these events is crucial to increase player engagement and maximize monetization. We present an experimental analysis of several methods to forecast game-related variables, with two main aims: to obtain accurate predictions of in-app purchases and playtime in an operational production environment, and to perform simulations of in-game events in order to maximize sales and playtime. Our ultimate purpose is to take a step towards the data-driven development of games. The results suggest that, even though the performance of traditional approaches such as ARIMA is still better, the outcomes of state-of-the-art techniques like deep learning are promising. Deep learning comes up as a well-suited general model that could be used to forecast a variety of time series with different dynamic behaviors

Permittivity of oxidized ultra-thin silicon films from atomistic simulations

We establish the dependence of the permittivity of oxidized ultra-thin silicon films on the film thickness by means of atomistic simulations within the density-functional-based tight-binding theory (DFTB). This is of utmost importance for modeling ultra- and extremely-thin silicon-on-insulator MOSFETs, and for evaluating their scaling potential. We demonstrate that electronic contribution to the dielectric response naturally emerges from the DFTB Hamiltonian when coupled to Poisson equation solved in vacuum, without phenomenological parameters, and obtain good agreement with available experimental data. Comparison to calculations of H-passivated Si films reveals much weaker dependence of permittivity on film thickness for the SiO2-passivated Si, with less than 18% reduction in the case of 0.9 nm silicon-on-insulator.published_or_final_versio