Testing mediators of intervention effects in randomized controlled trials: An evaluation of three depression prevention programs.

Objective: Evaluate a new 5-step method for testing mediators hypothesized to account for the effects of depression prevention programs. Method: In this indicated prevention trial, at-risk teens with elevated depressive symptoms were randomized to a group cognitive–behavioral (CB) intervention, group supportive expressive intervention, CB bibliotherapy, or assessment-only control condition. Results: The group CB intervention reduced depressive symptoms and negative cognitions and increased pleasant activities. Change in these mediators predicted change in depression, and intervention effects became weaker controlling for change in the mediators; yet, change in depression appeared typically to occur before change in the mediators. The supportive expressive intervention reduced depressive symptoms but affected only 1 of 2 mediators (emotional expression but not loneliness). Change in emotional expression did not correlate with change in depression, and change in depression usually occurred before change in the mediators. Bibliotherapy did not significantly affect depressive symptoms or the ostensive mediators (negative cognitions and pleasant activities), and change in depression usually occurred before change in the mediators. Conclusion: Results imply that this procedure provides a sensitive test of mediation but yielded limited support for the hypothesized mediators, suggesting that nonspecific factors may play an important mediational role. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Surface-catalyzed transformations of aqueous endosulfan

We report the effect of suspended solids on the oxidation and hydrolysis of the insecticide endosulfan (alpha and beta isomers) and its degradation products: endosulfan diol, endosulfan sulfate, endosulfan ether, and endosulfan lactone in 0.001 M NaHCO3 buffer (pH 8.15). Suspensions of sea sand, TiO2, alpha-Fe2O3, alpha-FeOOH, Laponite, and SiO2 all catalyzed the hydrolysis of endosulfan to the less toxic endosulfan diol. Suspended creek sediment (Bread and Butter Creek SC, 4% OC) inhibited endosulfan hydrolysis. Heterogeneous and homogeneous rate constants of endosulfan hydrolysis were measured and indicate that beta-endosulfan hydrolyzes faster than alpha-endosulfan. This observation was explained by a more stable transition state for beta-endosulfan that was confirmed with ab initio molecular orbital calculations (STO-6G) on the anionic intermediates of endosulfan hydrolysis. Rates of endosulfan hydrolysis over the different surfaces corresponded to their tritium-exchange site-density and suggest a mechanism involving surface coordination prior to nucleophilic attack. The oxidation of alpha-endosulfan and beta-endosulfan to the persistent pollutant endosulfan sulfate was not observed in this study.     

Testing Web applications by modeling with FSMs

Researchers and practitioners are still trying to find effective ways to model and test Web applications. This paper proposes a system-level testing technique that combines test generation based on finite state machines with constraints. We use a hierarchical approach to model potentially large Web applications. The approach builds hierarchies of Finite State Machines (FSMs) that model subsystems of the Web applications, and then generates test requirements as subsequences of states in the FSMs. These subsequences are then combined and refined to form complete executable tests. The constraints are used to select a reduced set of inputs with the goal of reducing the state space explosion otherwise inherent in using FSMs. The paper illustrates the technique with a running example of a Web-based course student information system and introduces a prototype implementation to support the technique.     

Maximum entropy direct models for speech recognition

Traditional statistical models for speech recognition have mostly been based on a Bayesian framework using generative models such as hidden Markov models (HMMs). This paper focuses on a new framework for speech recognition using maximum entropy direct modeling, where the probability of a state or word sequence given an observation sequence is computed directly from the model. In contrast to HMMs, features can be asynchronous and overlapping. This model therefore allows for the potential combination of many different types of features, which need not be statistically independent of each other. In this paper, a specific kind of direct model, the maximum entropy Markov model (MEMM), is studied. Even with conventional acoustic features, the approach already shows promising results for phone level decoding. The MEMM significantly outperforms traditional HMMs in word error rate when used as stand-alone acoustic models. Preliminary results combining the MEMM scores with HMM and language model scores show modest improvements over the best HMM speech recognizer.     

OWL-Eu: Adding customised datatypes into OWL

Although OWL is rather expressive, it has a very serious limitation on datatypes; i.e., it does not support customised datatypes. It has been pointed out that many potential users will not adopt OWL unless this limitation is overcome, and the W3C Semantic Web Best Practices and Development Working Group has set up a task force to address this issue. This paper makes the following two contributions: (i) it provides a brief summary of OWL-related datatype formalisms, and (ii) it provides a decidable extension of OWL DL, called OWL-Eu, that supports customised datatypes. A detailed proof of the decidability of OWL-Eu is presented.     

Customization of a Commercially Available Prep Scale SFC System to Provide Enhanced Capabilities

Preparative Scale Supercritical Fluid Chromatography is emerging as a powerful alternative to HPLC for the purification and separation of complex chemical reaction mixtures. Advantages include greatly reduced solvent usage (and thus lower cost and environmental impact), higher throughput, and in some cases higher resolution. While there are commercially available prep SFC instruments, none currently offer all the features desired by many medicinal chemists engaged in the drug discovery process. These include: the ability to collect an unlimited number of fractions per sample with high recovery and negligible carryover, fully automated capacity to collect several hundred fractions, and the ability to collect fractions into the same disposable test tubes and racks which are already employed in HPLC. This article describes the customization of a preparatory scale SFC system purchased from Berger Instruments, Inc., Newark, DE. (a subsidiary Mettler-Toledo International, Inc., of Greifensee, Switzerland) in order to provide these capabilities.     

3D Monte Carlo Modeling of Thin SOI MOSFETs Including the Effective Potential and Random Dopant Distribution

We use the effective potential to include quantum mechanical effects in thin SOI MOSFETs simulated with 3D Monte Carlo. We explore the role of discrete dopant distributions on the threshold voltage of the device within the framework of the effective potential by examining the current-voltage behavior as well as the electron distributions within the device. We find that simulations with the effective potential produce a similar shift in current as classical simulations when the dopants are considered to have a random discrete distribution instead of a uniform distribution.     

The Use of Quantum Potentials for Confinement and Tunnelling in Semiconductor Devices

As MOSFETs are scaled to sub 100 nm dimensions, quantum mechanical confinement in the direction normal to the silicon dioxide interface and tunnelling (through the gate oxide, band-to-band and from source-to-drain) start to strongly affect their characteristics. Recently it has been demonstrated that first order quantum corrections can be successfully introduced in self-consistent drift diffusion-type models using Quantum Potentials. In this paper we describe the introduction of such quantum corrections within a full 3D drift diffusion simulation framework. We compare the two most popular quantum potential techniques: density gradient and the effective potential approaches, in terms of their justification, accuracy and computational efficiency. The usefulness of their 3D implementation is demonstrated with examples of statistical simulations of intrinsic fluctuation effects in decanano MOSFETs introduced by discrete random dopants. We also discuss the capability of the density gradient formalism to handle direct source-to-drain tunnelling in sub 10 nm double-gate MOSFETS, illustrated in comparison with Non-Equilibrium Green's Functions simulations.     

On the Electron Transient Response in a 50 nm MOSFET by Ensemble Monte Carlo Simulation in Presence of the Smoothed Potential Algorithm

The inclusion of a smoothed potential algorithm within the Ensemble Monte Carlo method (EMC) to account for quantization effects in the inversion layer of a silicon n-MOSFET has been discussed by several authors. Most of the data reported deal with steady state terminal current, transconductance, and capacitance. Within this approach, the electric field acting on each particle is computed from the smoothed potential, which introduces a potential barrier underneath the gate region that pushes the carriers away from the interface, thus accounting for space quantization effects. However, in the EMC method, the electric field at the interface is also used to compute the displacement charge/current during the transient regime. In the implementation of the smoothed potential algorithm, care must be taken when computing this component of the total gate charge. We distinguish between two differently computed electric fields, one from the smoothed potential used for the charge transport and the other one computed from the real potential, as obtained from the solution of Poisson's equation, and used for the displacement charge. We propose this procedure in order to properly include space quantization effects, and at the same time avoid the inaccuracy introduced by the smoothed potential in the displacement charge.     

The Effective Potential in Device Modeling: The Good, the Bad and the Ugly

We discuss the use of the effective potential to incorporate quantum effects in device models. While threshold shifts and charge set-back are handled well, tunneling is not well handled by this approach, or by any other local potential approach.