Texas A&M University

About: Texas A&M University is a education organization based out in College Station, Texas, United States. It is known for research contribution in the topics: Population & Finite element method. The organization has 72169 authors who have published 164372 publications receiving 5764236 citations.

Optimal beamforming for two-way multi-antenna relay channel with analogue network coding

Abstract: This paper studies the wireless two-way relay channel (TWRC), where two source nodes, S1 and S2, exchange information through an assisting relay node, R. It is assumed that R receives the sum signal from S1 and S2 in one timeslot, and then amplifies and forwards the received signal to both S1 and S2 in the next time-slot. By applying the principle of analogue network coding (ANC), each of S1 and S2 cancels the so-called "self-interference" in the received signal from R and then decodes the desired message. Assuming that S1 and S2 are each equipped with a single antenna and R with multi-antennas, this paper analyzes the capacity region of the ANC-based TWRC with linear processing (beamforming) at R. The capacity region contains all the achievable bidirectional rate-pairs of S1 and S2 under the given transmit power constraints at S1, S2, and R. We present the optimal relay beamforming structure as well as an efficient algorithm to compute the optimal beamforming matrix based on convex optimization techniques. Low-complexity suboptimal relay beamforming schemes are also presented, and their achievable rates are compared against the capacity with the optimal scheme.

Antifungal Activity of Silver Ions and Nanoparticles on Phytopathogenic Fungi.

Abstract: Silver in ionic or nanoparticle forms has a high antimicrobial activity and is therefore widely used for various sterilization purposes including materials of medical devices and water san...

The Reputational Penalty for Aggressive Accounting: Earnings Restatements and Management Turnover

Abstract: In this paper we investigate the reputational penalties to managers of firms announcing earnings restatements. More specifically, we examine management turnover and the subsequent employment of displaced managers at firms announcing earnings restatements during 1997 or 1998. In contrast to prior research (Beneish 1999; Agrawal et al. 1999), which does not find increased turnover following GAAP violations or revelation of corporate fraud, we find that 60 percent of restating firms experience a turnover of at least one top manager within 24 months of the restatement compared to 35 percent among age‐, size‐, and industry‐matched firms. Moreover, the subsequent employment prospects of the displaced managers of restatement firms are poorer than those of the displaced managers of control firms. Our results hold after controlling for firm performance, bankruptcy, and other determinants of management turnover, and suggest that both corporate boards and the external labor market impose significant penalties on man...

Eight new Milky Way companions discovered in first-year Dark Energy Survey data

Abstract: We report the discovery of eight new Milky Way companions in ~1,800 deg^2 of optical imaging data collected during the first year of the Dark Energy Survey (DES). Each system is identified as a statistically significant over-density of individual stars consistent with the expected isochrone and luminosity function of an old and metal-poor stellar population. The objects span a wide range of absolute magnitudes (M_V from -2.2 mag to -7.4 mag), physical sizes (10 pc to 170 pc), and heliocentric distances (30 kpc to 330 kpc). Based on the low surface brightnesses, large physical sizes, and/or large Galactocentric distances of these objects, several are likely to be new ultra-faint satellite galaxies of the Milky Way and/or Magellanic Clouds. We introduce a likelihood-based algorithm to search for and characterize stellar over-densities, as well as identify stars with high satellite membership probabilities. We also present completeness estimates for detecting ultra-faint galaxies of varying luminosities, sizes, and heliocentric distances in the first-year DES data.

Initial Human and Financial Capital as Predictors of New Venture Performance

Abstract: This research seeks to predict the performance of new ventures based on factors that can be observed at the time of start-up. Indicators of initial human and financial capital are considered to determine how they bear upon the probability of three possible performance outcomes: (1) failure, (2) marginal survival, or (3) high growth. Four categories of initial human and financial capital are examined. General human capital, represented here by the entrepreneur's education, gender, and race, may reflect the extent to which the entrepreneur has had the opportunity to develop relevant skills and contacts. Management know-how, embodied in the entrepreneur or available through advisors or partners, reflects management-specific skills and knowledge, without regard to the kind of business. Industry-specific know-how reflects specific experience in similar businesses. Financial capital is one of the most visible resources; it can create a buffer against random shocks and allow the pursuit of more capital-intensive strategies, which are better protected from imitation. The study utilizes a longitudinal study of 1053 new ventures, representative of all industry sectors and geographical regions. The research departs from most previous studies in considering different measures of performance (marginal survival and growth) and in considering explicitly whether the factors contributing to marginal survival differ from those contributing to high growth. It was found that measures of general human capital influenced both survival and growth (except for gender, with women-owned ventures being less likely to grow, but just as likely to survive). Management know-how variables had more limited impact. Having parents who had owned a business contributed to marginal survival, but not to growth. Number of partners contributed to growth but not to survival. Management level, prior employment in non-profit organizations or not having been in the labor force, and the use of professional advisors did not have significant effects. Industry-specific know-how contributed to both survival and growth. Amount of initial financial capital also contributed to both. The usefulness of the model is enhanced by the fact that the resource variables considered are relatively easy to assess and all can be considered at the time of start-up. Although some of the human capital variables cannot easily be changed, the benefits or risks associated with each can be assessed. In some cases, potential problems can be identified so that plans can be modified to improve prospects. Overall it appears that, using a model based upon the initial human and financial capital of the venture, it is possible to predict the performance of new ventures with some degree of confidence.