Exploration of channel width scaling and edge states in transition metal dichalcogenides

We explore the impact of edge states in three types of transition metal dichalcogenides (TMDs), namely metallic Td-phase WTe₂ and semiconducting 2H-phase MoTe₂ and MoS₂, by patterning thin flakes into ribbons with varying channel widths. No obvious charge depletion at the edges is observed for any of these three materials, in contrast to observations made for graphene nanoribbon devices. The semiconducting ribbons are characterized in a three-terminal field-effect transistor (FET) geometry. In addition, two ribbon array designs have been carefully investigated and found to exhibit current levels higher than those observed for conventional one-channel devices. Our results suggest that device structures incorporating a high number of edges can improve the performance of TMD FETs. This improvement is attributed to a higher local electric field, resulting from the edges, increasing the effective number of charge carriers, and the absence of any detrimental edge-related scattering.

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Smoothness maximization along a predefined path accurately predicts the speed profiles of complex arm movements

The speed profiles of arm movements display a number of regularities, including bell-shaped speed profiles in straight reaching movements and an inverse relationship between speed and curvature in extemporaneous drawing movements (described as a 2/3 power law). Here we propose a new model that simultaneously accounts for both regularities by replacing the 2/3 power law with a smoothness constraint. For a given path of the hand in space, our model assumes that the speed profile will be the one that minimizes the third derivative of position (or "jerk"). Analysis of the mathematical relationship between this smoothness constraint and the 2/3 power law revealed that in both two and three dimensions, the power law is equivalent to setting the jerk along the normal to the path to zero; it generates speed predictions that are similar, but clearly distinguishable from the predictions of our model. We have assessed the accuracy of the model on a number of motor tasks in two and three dimensions, involving discrete movements along arbitrary paths, traced with different limb segments. The new model provides a very close fit to the observed speed profiles in all cases. Its performance is uniformly better compared with all existing versions of the 2/3 power law, suggesting that the correlation between speed and curvature may be a consequence of an underlying motor strategy to produce smooth movements. Our results indicate that the relationship between the path and the speed profile of a complex arm movement is stronger than previously thought, especially within a single trial. The accuracy of the model was quite uniform over movements of different shape, size, and average speed. We did not find evidence for segmentation, yet prediction error increased with movement duration, suggesting a continuous fluctuation of the "tempo" of discrete movements. The implications of these findings for motor planning and on-line control are discussed.     

Emission polarization of roughened glass and aluminum surfaces

Ellipsometer measurements of the effective complex refractive index at a wavelength of 10.6 μm are made on a series of glass and aluminum surfaces of increasing surface roughness. The measured values are then used to calculate the degree of emission polarization and are shown to be in agreement with the experimentally determined values when depolarization is small. Comparisons are also made with calculations based on the Kirchhoff scattering theory. Both the theory and the experimental results indicate that it is the local surface slope and not the roughness magnitude that is the prime factor in determining the degree of emission polarization from the samples studied.     

Podcasting in education: Are students as ready and eager as we think they are?

Instructors in higher education are disseminating instructional content via podcasting, as many rally behind the technology’s potential benefits. Others have expressed concern about the risks of deleterious effects that might accompany the adoption of podcasting, such as lower class attendance. Yet, relatively few studies have investigated students’ perceptions of podcasting for educational purposes, especially in relation to different podcasting forms: repetitive and supplemental. The present study explored students’ readiness and attitudes towards these two forms of podcasting to provide fundamental information for future researchers and educators. The results indicated that students may not be as ready or eager to use podcasting for repetitive or supplemental educational purposes as much as we think they are, but they could be persuaded.     

Privacy policies for shared content in social network sites

Social networking is one of the major technological phenomena of the Web 2.0, with hundreds of millions of subscribed users. Social networks enable a form of self-expression for users and help them to socialize and share content with other users. In spite of the fact that content sharing represents one of the prominent features of existing Social network sites, they do not provide any mechanisms for collective management of privacy settings for shared content. In this paper, using game theory, we model the problem of collective enforcement of privacy policies on shared data. In particular, we propose a solution that offers automated ways to share images based on an extended notion of content ownership. Building upon the Clarke-Tax mechanism, we describe a simple mechanism that promotes truthfulness and that rewards users who promote co-ownership. Our approach enables social network users to compose friendship based policies based on distances from an agreed upon central user selected using several social networks metrics. We integrate our design with inference techniques that free the users from the burden of manually selecting privacy preferences for each picture. To the best of our knowledge, this is the first time such a privacy protection mechanism for social networking has been proposed. We also extend our mechanism so as to support collective enforcement across multiple social network sites. In the paper, we also show a proof-of-concept application, which we implemented in the context of Facebook, one of today’s most popular social networks. Through our implementation, we show the feasibility of such approach and show that it can be implemented with a minimal increase in overhead to end-users. We complete our analysis by conducting a user study to investigate users’ understanding of co-ownership, usefulness and understanding of our approach. Users responded favorably to the approach, indicating a general understanding of co-ownership and the auction, and found the approach to be both useful and fair.     

Accelerating Monte Carlo simulations with an NVIDIA graphics processor

Modern graphics cards, commonly used in desktop computers, have evolved beyond a simple interface between processor and display to incorporate sophisticated calculation engines that can be applied to general purpose computing. The Monte Carlo algorithm for modelling photon transport in turbid media has been implemented on an NVIDIA^® 8800gt graphics card using the CUDA toolkit. The Monte Carlo method relies on following the trajectory of millions of photons through the sample, often taking hours or days to complete. The graphics-processor implementation, processing roughly 110 million scattering events per second, was found to run more than 70 times faster than a similar, single-threaded implementation on a 2.67 GHz desktop computer.

Program summary

Program title: Phoogle-C/Phoogle-GCatalogue identifier: AEEB_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEEB_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 51 264No. of bytes in distributed program, including test data, etc.: 2 238 805Distribution format: tar.gzProgramming language: C++Computer: Designed for Intel PCs. Phoogle-G requires a NVIDIA graphics card with support for CUDA 1.1Operating system: Windows XPHas the code been vectorised or parallelized?: Phoogle-G is written for SIMD architecturesRAM: 1 GBClassification: 21.1External routines: Charles Karney Random number library. Microsoft Foundation Class library. NVIDA CUDA library [1].Nature of problem: The Monte Carlo technique is an effective algorithm for exploring the propagation of light in turbid media. However, accurate results require tracing the path of many photons within the media. The independence of photons naturally lends the Monte Carlo technique to implementation on parallel architectures. Generally, parallel computing can be expensive, but recent advances in consumer grade graphics cards have opened the possibility of high-performance desktop parallel-computing.Solution method: In this pair of programmes we have implemented the Monte Carlo algorithm described by Prahl et al. [2] for photon transport in infinite scattering media to compare the performance of two readily accessible architectures: a standard desktop PC and a consumer grade graphics card from NVIDIA.Restrictions: The graphics card implementation uses single precision floating point numbers for all calculations. Only photon transport from an isotropic point-source is supported. The graphics-card version has no user interface. The simulation parameters must be set in the source code. The desktop version has a simple user interface; however some properties can only be accessed through an ActiveX client (such as Matlab).Additional comments: The random number library used has a LGPL (http://www.gnu.org/copyleft/lesser.html) licence.Running time: Runtime can range from minutes to months depending on the number of photons simulated and the optical properties of the medium.References:

[1]

http://www.nvidia.com/object/cuda_home.html.

[2]

S. Prahl, M. Keijzer, Sl. Jacques, A. Welch, SPIE Institute Series 5 (1989) 102.

     

Development of a pit filling algorithm for LiDAR canopy height models

LiDAR canopy height models (CHMs) can exhibit unnatural looking holes or pits, i.e., pixels with a much lower digital number than their immediate neighbors. These artifacts may be caused by a combination of factors, from data acquisition to post-processing, that not only result in a noisy appearance to the CHM but may also limit semi-automated tree-crown delineation and lead to errors in biomass estimates. We present a highly effective semi-automated pit filling algorithm that interactively detects data pits based on a simple user-defined threshold, and then fills them with a value derived from their neighborhood. We briefly describe this algorithm and its graphical user interface, and show its result in a LiDAR CHM populated with data pits. This method can be rapidly applied to any CHM with minimal user interaction. Visualization confirms that our method effectively and quickly removes data pits.