On the Capacity of a Class of MIMO Cognitive Radios

Cognitive radios have been studied recently as a means to utilize spectrum in a more efficient manner. This paper focuses on the fundamental limits of operation of a MIMO cognitive radio network with a single licensed user and a single cognitive user. The channel setting is equivalent to an interference channel with degraded message sets (with the cognitive user having access to the licensed user's message). An achievable region and an outer bound is derived for such a network setting. It is shown that under certain conditions, the achievable region is optimal for a portion of the capacity region that includes sum capacity.Comment: 13 pages, 8 figures, Accepted for publication in Journal of Selected Topics in Signal Processing (JSTSP) - Special Issue on Dynamic Spectrum Acces

JOULE HEATING EFFECTS ON ELECTROKINETIC TRANSPORT IN CONSTRICTION MICROCHANNELS

Microfluidic technology involving multidisciplinary studies including MEMS, chemistry, physics, fluids and heat transfer has been developed into a promising research field in the recent decade. If offers many advantages over conventional laboratory techniques like reduced reagent consumption, faster analysis, easy fabrication and low chemical waste. Microfluidic lab-on-a-chip devices have been used to manipulate cells and particles like sorting, separating, trapping, mixing and lysing. Microfluidic manipulation can be achieved through many methods and insulator based dielectrophoresis (iDEP) is one of the highly used method in the recent years. In iDEP, both DC and AC voltages can be applied to the remote electrodes positioned in end-channel reservoirs for transporting and manipulating particles. The electric field gradients are caused by the blockage of electric current due to in-channel hurdles, posts, and ridges. However, iDEP devices suffer from the issue of Joule heating due to locally amplified electric field around the insulators. A parametric study of Joule heating effects on electroosmotic fluid flow in iDEP is studied under various electric fields. It was determined that depending upon the magnitude of DC voltage, a pair of counter rotating vortices fluid circulations can occur at either downstream end or each end of the channel constriction. Moreover, pair at the downstream end appears larger in size than the upstream end due to DC electroosmotic flow. A numerical model is developed to simulate the fluid circulations occurred due to the action of electric field on Joule heating induced fluid inhomogeneities in the constriction region. Focusing particles or cells into a single stream is usually a necessary step prior to counting and separating them in microfluidic devices such as flow cytometers and cell sorters. A systematic study of Joule heating effects on electrokinetic particle transport in constriction microchannels under DC and DC biased AC electric fields is presented in this work. A numerical model is developed to capture the particle trace observed in the experiments. It was determined that particle transport is greatly affected by electrothermal effects where Joule heating is high. At very low DC magnitude where the electrothermal effects dominate the electrokinetic flow, particles in the shallow depth channel are being trapped and particles in deep channels are transported to the downstream reservoir from the constriction in a single streamline. Electrothermal flow circulations should be taken into account in the design and operation of iDEP devices, especially when highly conductive solutions and large electric fields must be employed. They may potentially be harnessed to enhance microfluidic mixing and immunoassay for lab-on-a-chip applications. A numerical study of Joule heating effects on the sample mixing performance in constriction microchannels is presented in this work. It was determined that Joule heating induced electrothermal force enhanced the sample mixing by generating circulations at the ends of the constriction under DC biased AC electric fields. Furthermore, mixing performance was also studied for various parameters like applied electric field, channel structure, channel depth and number of constrictions

Capacity of interference networks : achievable regions and outer bounds

textIn an interference network, multiple transmitters communicate with multiple receivers using the same communication channel. The capacity region of an interference network is defined as the set of data rates that can be simultaneously achieved by the users of the network. One of the most important example of an interference network is the wireless network, where the communication channel is the wireless channel. Wireless interference networks are known to be interference limited rather than noise limited since the interference power level at the receivers (caused by other user's transmissions) is much higher than the noise power level. Most wireless communication systems deployed today employ transmission strategies where the interfering signals are treated in the same manner as thermal noise. Such strategies are known to be suboptimal (in terms of achieving higher data rates), because the interfering signals generated by other transmitters have a structure to them that is very different from that of random thermal noise. Hence, there is a need to design transmission strategies that exploit this structure of the interfering signals to achieve higher data rates. However, determining optimal strategies for mitigating interference has been a long standing open problem. In fact, even for the simplest interference network with just two users, the capacity region is unknown. In this dissertation, we will investigate the capacity region of several models of interference channels. We will derive limits on achievable data rates and design effective transmission strategies that come close to achieving the limits. We will investigate two kinds of networks - "small" (usually characterized by two transmitters and two receivers) and "large" where the number of users is large.Electrical and Computer Engineerin

Mechanical Design and Analysis of a Discrete Variable Transmission System for Transmission-Based Actuators

Over the past few years, replacing the hydraulic servo actuators with their electrical counter parts for robotics and remote handling systems has been an active field of research. These systems are of particular interest for tasks involved with the US Department of Energy, where the level of radiation exposure is high and the tasks are highly repetitive. With the hydraulic servo actuators, one is concerned with the issues like the high complexity, cost of the system and the difficulty of maintenance of the system. For high payload operations, the hydraulic systems provide an order of magnitude increase in the power density, which is almost impossible to achieve using the electrical servo actuators. Hence, for the electrical servo actuators to be used for high payload operations, the fundamental issue concerning the power and torque density must be addressed. Previous research conducted on this front suggested the use of a variable speed transmission system to spread the servomotor’s torque-speed characteristics across a wider output speed range. This has the effect of allowing smaller high power motors to also deliver high torques at low speeds. By using a variable speed transmission, the motor size can be reduced dramatically while increasing the overall actuator power density in the process. This work goes further into the detailed design of the discrete variable transmission system. A three-stage planetary gear transmission system is considered for the analysis and design. With the use of the three-stage planetary gear transmission, there are a complex and varied design issues involved. Selecting a configuration for the transmission is the first question to be answered. With the given configuration, and the ratios required the individual gears have to be sized accordingly. Other design elements involve the design of the shafting, achieving the desired configuration, bearings, housing and the design of a gear shifting mechanism. A detailed kinematic and dynamic analysis of the entire gear system is required for the design of the various components mentioned above. Analytical results are presented along with a computer-aided analysis of the work using the Pro-Engineer design and analysis software. Future work on this will be to turn this into a commercially available system, which comes down to optimizing the current design. Possibilities of optimization for the current design will be identified. A discussion on the prototype evaluation of the transmission system along with a sample test result is presented

Biological Pathways Based Approaches to Model and Control Gene Regulatory Networks

The aim of effective cancer treatment is to prolong the patients’ life while offering a reasonable quality of life during and after treatment. The treatments must carry their actions/effects in a manner such that a very large percentage of tumor cells die or shift into a state where they stop proliferating. The fundamental issue in systems biology is to model gene interaction via gene regulatory networks (GRN) and hence provide an informatics environment to study the effects of gene mutation as well as derive newer and effective intervention (via drugs) strategies to alter the cancerous state of the network, thereby eradicating the tumor. In this dissertation, we present two approaches to model gene regulatory networks. These approach are different, albeit having a common structure to them. We develop the GRN under a Boolean formalism with deterministic and stochastic framework. The knowledge used to model these networks are derived from biological pathways, which are partial and incomplete. This work is an attempt towards understanding the dynamics of a proliferating cell and to control this system. Initial part (deterministic) of this work focuses on formulating a deterministic model by assuming the pathway regulations to be complete and accurate. Using these models algorithms were developed to pin-point faults (mutations) in the network and design personalized combination therapy depending on the expression signature of specific output genes. To introduce stochastic nature onto the model due to incompleteness in the prior biological knowledge, an uncertainty class of models was defined over the biological network. Two such uncertainty class of models are modeled- one over the state transitions and the other over the node transitions in the system. This knowledge is transferred to priors, and the existing Bayesian theory is used to update and converge to a good model. The Bayesian control theory for Markovian processes is applied to the problem of intervention in Markovian gene regulatory networks, while simultaneously updating the model. Via a toy example, it is shown that effective prior knowledge quantification can significantly help in converging on to the actual model with limited information from the system and take advantage of the optimality promised by Bayesian intervention. These control methods however, suffer from computational and memory complexity issues- Curse of Dimensionality, to be useful for any network size of biological relevance. To counter these issues associated with Dynamic Programming, suboptimal approximate algorithm known as Q-learning and its Bayesian variation are used to save on computational and memory complexities. These sub-optimal approximate algorithms perform very close (but inferior) to optimal policy, but the computational saving, both in terms of time and memory are significant to extend them to networks of larger size

BARLERIA MONTANA WIGHT AND NEES–A PROMISING NATURAL ANTI-INFLAMMATORY AGENT AGAINST FORMALIN INDUCED INFLAMMATION

Objective: To evaluate the anti-inflammatory activity of the ethanolic leaf extract of Barleria montana (B. montana) against formalin induced inflammation.Methods: Male albino wistar rats were pretreated with oral doses of 100 mg, 200 mg and 300 mg of the extract for 30 days and the animals received a single dose of sub plantar injection of formalin (0.1 ml/kg body weight (bw.)) Indomethacin (25 mg/kg bw.) was used as the standard drug. The effect of the extract on paw thickness, biochemical and hematological parameters was investigated along with histopathological studies.Results: The results revealed that the extract exhibited an effective dose dependent activity against formalin induced inflammation with a maximum activity at a dosage of 300 mg/kg bw. which was comparable with the standard drug.Conclusion: The results signify promising activity of ethanolic leaf extract of B. montana against formalin induced inflammation in albino rats. The extract was also found to exhibit appreciable antioxidant activity.Â

The Flow-Insensitive Precision of Andersen's Analysis in Practice ; CU-CS-1083-11

Abstract. We present techniques for determining the precision gap between Andersen’s points-to analysis and precise flow-insensitive points-to analysis in practice. While previous work has shown that such a gap may exist, no efficient algorithm for precise flow-insensitive analysis is known, making measurement of the gap on real-world programs difficult. We give an algorithm for precise flow-insensitive analysis of programs with finite memory, based on a novel technique for refining any points-to analysis with a search for flow-insensitive witnesses. We give a compact symbolic encoding of the technique that enables computing the search using a tuned SAT solver. We also present extensions of the algorithm that enable computing lower and upper bounds on the precision gap in the presence of dynamic memory allocation. In our experimental evaluation over a suite of small- to medium-sized C programs, we never observed a precision gap between Andersen’s analysis and the precise analysis. In other words, Andersen’s analysis computed a precise flow-insensitive result for all of our benchmarks. Hence, we conclude that while better algorithms for the precise flow-insensitive analysis are still of theoretical interest, their practical impact for C programs is likely to be negligible.