Single Particle Transport in Two-dimensional Heterojunction Interlayer Tunneling Field Effect Transistor

The single particle tunneling in a vertical stack consisting of monolayers of two-dimensional semiconductors is studied theoretically and its application to a novel Two-dimensional Heterojunction Interlayer Tunneling Field Effect Transistor (Thin-TFET) is proposed and described. The tunneling current is calculated by using a formalism based on the Bardeen's transfer Hamiltonian, and including a semi-classical treatment of scattering and energy broadening effects. The misalignment between the two 2D materials is also studied and found to influence the magnitude of the tunneling current, but have a modest impact on its gate voltage dependence. Our simulation results suggest that the Thin-TFETs can achieve very steep subthreshold swing, whose lower limit is ultimately set by the band tails in the energy gaps of the 2D materials produced by energy broadening. The Thin-TFET is thus very promising as a low voltage, low energy solid state electronic switch

Multidimensional measurement within adult protective services: design and initial testing of the tool for risk, interventions, and outcomes.

This study describes the development, field utility, reliability, and validity of the multidimensional Tool for Risk, Interventions, and Outcomes (TRIO) for use in Adult Protective Services (APS). The TRIO is designed to facilitate consistent APS practice and collect data related to multiple dimensions of typical interactions with APS clients, including the investigation and assessment of risks, the provision of APS interventions, and associated health and safety outcomes. Initial tests of the TRIO indicated high field utility, social worker "relevance and buy-in," and inter-rater reliability. TRIO concurrent validity was demonstrated via appropriate patterns of TRIO item differentiation based on the type of observed confirmed abuse or neglect; and predictive validity was demonstrated by prediction of the risk of actual APS recurrence. The TRIO is a promising new tool that can help meet the challenges of providing and documenting effective APS practices and identifying those at high risk for future APS recurrence

The effect of the NMDA noncompetitive antagonist ketamine on serial learning in rats

Past research has demonstrated that Nmethyl- D-aspartate (NMDA) receptor antagonists disrupt the acquisition of a variety of spatial and non-spatial tasks. In the present investigation, the effects of the NMDA antagonist, ketamine, were examined in a task with minimal spatial demands. Twenty-six male Long-Evans rats, approximately 5 months of age at the beginning of training, served as the subjects. Before training began, all rats were reduced to 85% of their free feeding weight and maintained with this 15% reduction throughout training. After injections of ketamine or saline, rats were trained to respond in a runway to a nonmonotonic serial pattern consisting of 14-, 0-, 3-, or 7-pellets, respectively. Saline rats were capable of tracking the rewarded and non-rewarded elements of the series while the ketamine rats were markedly impaired. Specifically, analysis of the running times revealed a significant drug group x elements interaction, F(3, 36) = 3.01, p \u3c .05. Examination of the interaction with Tukey a revealed that the saline rats ran significantly faster to the three rewarded elements of the series than the 0-pellet element (p s \u3c .05). Conversely, ketamine-treated rats had similar running times to all elements of the series (ps \u3e .05). The results are discussed in terms of NMDA-receptor involvement in the task acquisition

Nonlinear Geometric Optics for Pulses with Nonlinear Phases

The nonlinear geometric optics approach is used to elucidate the form of pulse solutions to two semilinear hyperbolic PDE problems in which the characteristic phases are nonlinear. The first problem considers a pulse traveling freely through space, and the second considers the collision of two pulses. A key question we sought to address was whether the collision of two pulses produces only two or more than two pulses after collision, given that the phases are nonlinear. We show that one can construct an approximate solution to the collision problem in which there are precisely two pulses in the leading term of the approximate solution after collision. We also construct an approximate solution to the free space problem and prove the approximate solution is close to the exact solution at the rate O(epsilon) as epsilon approaches zero in an appropriate norm. The proof for this statement relies on construction of an exact solution with a uniform time of existence with respect to epsilon using an argument of Guy Metivier in a new context. The proof also relies on the analysis of the error term using some of Metivier's estimates. We anticipate that it can also be proved that the approximate solution to the collision problem is close to the collision problem's exact solution in an analogous way. The results we obtained suggest that the nonlinear geometric optics approach may successfully be applied to study problems involving interaction of pulses with nonlinear phases.Bachelor of Art

(Teff,log g,[Fe/H]) Classification of Low-Resolution Stellar Spectra using Artificial Neural Networks

New generation large-aperture telescopes, multi-object spectrographs, and large format detectors are making it possible to acquire very large samples of stellar spectra rapidly. In this context, traditional star-by-star spectroscopic analysis are no longer practical. New tools are required that are capable of extracting quickly and with reasonable accuracy important basic stellar parameters coded in the spectra. Recent analyses of Artificial Neural Networks (ANNs) applied to the classification of astronomical spectra have demonstrated the ability of this concept to derive estimates of temperature and luminosity. We have adapted the back-propagation ANN technique developed by von Hippel et al. (1994) to predict effective temperatures, gravities and overall metallicities from spectra with resolving power ~ 2000 and low signal-to-noise ratio. We show that ANN techniques are very effective in executing a three-parameter (Teff,log g,[Fe/H]) stellar classification. The preliminary results show that the technique is even capable of identifying outliers from the training sample.Comment: 6 pages, 3 figures (5 files); to appear in the proceedings of the 11th Cambridge Workshop on Cool Stars, Stellar Systems and the Sun, held on Tenerife (Spain), October 1999; also available at http://hebe.as.utexas.ed

Distinguishing artefacts:evaluating the saturation point of convolutional neural networks

Prior work has shown Convolutional Neural Networks (CNNs) trained on surrogate Computer Aided Design (CAD) models are able to detect and classify real-world artefacts from photographs. The applications of which support twinning of digital and physical assets in design, including rapid extraction of part geometry from model repositories, information search \& retrieval and identifying components in the field for maintenance, repair, and recording. The performance of CNNs in classification tasks have been shown dependent on training data set size and number of classes. Where prior works have used relatively small surrogate model data sets ($<100$ models), the question remains as to the ability of a CNN to differentiate between models in increasingly large model repositories. This paper presents a method for generating synthetic image data sets from online CAD model repositories, and further investigates the capacity of an off-the-shelf CNN architecture trained on synthetic data to classify models as class size increases. 1,000 CAD models were curated and processed to generate large scale surrogate data sets, featuring model coverage at steps of 10$^{\circ}$, 30$^{\circ}$, 60$^{\circ}$, and 120$^{\circ}$ degrees. The findings demonstrate the capability of computer vision algorithms to classify artefacts in model repositories of up to 200, beyond this point the CNN's performance is observed to deteriorate significantly, limiting its present ability for automated twinning of physical to digital artefacts. Although, a match is more often found in the top-5 results showing potential for information search and retrieval on large repositories of surrogate models.Comment: 6 Pages, 5 Figures, 2 Tables, Conference, Design Engineering, CNN, Digital Twi

Model-based information navigation for engineering documents

Engineering and the manner in which engineers think is largely visual and functional, and yet engineers are typically provided with search engines that are text-based. While software based on a visual and functional ethos exist (CAD for example), when searching for information engineers are still required to enter a text query into a search box. This process holds potential incompatibilities both with the nature of the data (i.e. 3D models) and with the way in which engineers think and work. Consequentially, the proposition tested in this paper is that a model-based approach to information access, i.e. a representation of an organisations information around a model of an artefact i.e. CAD model, can improve engineering information retrieval. In an A-B test with a traditional text-based search engine, and using study questions derived from real-world information seeking scenarios based on the activities of a world-leading aircraft manufacturer, the results presented in this paper suggest that there is merit to such an approach.Specifically, this paper shows that there is no significant difference in time to complete a search between a model-based and text-based interfaces in spite of the addition of a new stage in the search process (navigating a 3D model); that the system structure of the model-based interface allows for non-text based documents to be indexed, making up for the inherent limitations in traditional text-based search; and that participants enjoy using the model-based interface and find it intuitive, easy and simple to use. Further, this paper also finds that those with more experience/familiar with the product structure and those in managerial positions are more likely to find information using a model-based interface that those who are not, who perform better using a text-based interface

Coordinated induction of cell survival signaling in the inflamed microenvironment of the prostate

PURPOSE: Both prostate cancer and benign prostatic hyperplasia are associated with inflammatory microenvironments. Inflammation is damaging to tissues, but it is unclear how the inflammatory microenvironment protects specialized epithelial cells that function to proliferate and repair the tissue. The objective of this study is to characterize the cell death and cell survival response of the prostatic epithelium in response to inflammation. METHODS: We assessed induction of cell death (TNF, TRAIL, TWEAK, FasL) and cell survival factors (IGFs, hedgehogs, IL-6, FGFs, and TGFs) in inflamed and control mouse prostates by ELISA. Cell death mechanisms were determined by immunoblotting and immunofluorescence for cleavage of caspases and TUNEL. Survival pathway activation was assessed by immunoblotting and immunofluorescence for Mcl-1, Bcl-2, Bcl-XL, and survivin. Autophagy was determined by immunoblotting and immunofluorescence for free and membrane associated light chain 3 (LC-3). RESULTS: Cleavage of all four caspases was significantly increased during the first 2 days of inflammation, and survival protein expression was substantially increased subsequently, maximizing at 3 days. By 5 days of inflammation, 50% of prostatic epithelial cells expressed survivin. Autophagy was also evident during the recovery phase (3 days). Finally, immunofluorescent staining of human specimens indicates strong activation of survival proteins juxtaposed to inflammation in inflamed prostate specimens. CONCLUSIONS: The prostate responds to deleterious inflammation with induction of cell survival mechanisms, most notably survivin and autophagy, demonstrating a coordinated induction of survival factors that protects and expands a specialized set of prostatic epithelial cells as part of the repair and recovery process during inflammation