Transmit signal design for optimal estimation of correlated MIMO channels

We address optimal estimation of correlated multiple-input multiple-output (MIMO) channels using pilot signals, assuming knowledge of the second-order channel statistics at the transmitter. Assuming a block fading channel model and minimum mean square error (MMSE) estimation at the receiver, we design the transmitted signal to optimize two criteria: MMSE and the conditional mutual information between the MIMO channel and the received signal. Our analysis is based on the recently proposed virtual channel representation, which corresponds to beamforming in fixed virtual directions and exposes the structure and the true degrees of freedom in the correlated channel. However, our design framework is applicable to more general channel models, which include known channel models, such as the transmit and receive correlated model, as special cases. We show that optimal signaling is in a block form, where the block length depends on the signal-to-noise ratio (SNR) as well as the channel correlation matrix. The block signal corresponds to transmitting beams in successive symbol intervals along fixed virtual transmit angles, whose powers are determined by (nonidentical) water filling solutions based on the optimization criteria. Our analysis shows that these water filling solutions identify exactly which virtual transmit angles are important for channel estimation. In particular, at low SNR, the block length reduces to one, and all the power is transmitted on the beam corresponding to the strongest transmit angle, whereas at high SNR, the block length has a maximum length equal to the number of active virtual transmit angles, and the power is assigned equally to all active transmit angles. Consequently, from a channel estimation viewpoint, a faster fading rate can be tolerated at low SNRs relative to higher SNRs.     

Gaussian sum particle filtering

We use the Gaussian particle filter to build several types of Gaussian sum particle filters. These filters approximate the filtering and predictive distributions by weighted Gaussian mixtures and are basically banks of Gaussian particle filters. Then, we extend the use of Gaussian particle filters and Gaussian sum particle filters to dynamic state space (DSS) models with non-Gaussian noise. With non-Gaussian noise approximated by Gaussian mixtures, the non-Gaussian noise models are approximated by banks of Gaussian noise models, and Gaussian mixture filters are developed using algorithms developed for Gaussian noise DSS models. As a result, problems involving heavy-tailed densities can be conveniently addressed. Simulations are presented to exhibit the application of the framework developed herein, and the performance of the algorithms is examined.     

The contribution of classical (beta1/2-) and atypical beta-adrenoceptors to the stimulation of human white adipocyte lipolysis and right atrial appendage contraction by novel beta3-adrenoceptor agonists of differing selectivities

The role of beta3- and other putative atypical beta-adrenoceptors in human white adipocytes and right atrial appendage has been investigated using CGP 12177 and novel phenylethanolamine and aryloxypropanolamine beta3-adrenoceptor (beta3AR) agonists with varying intrinsic activities and selectivities for human cloned betaAR subtypes. The ability to demonstrate beta1/2AR antagonist-insensitive (beta3 or other atypical betaAR-mediated) responses to CGP 12177 was critically dependent on the albumin batch used to prepare and incubate the adipocytes. Four aryloxypropanolamine selective beta3AR agonists (SB-226552, SB-229432, SB-236923, SB-246982) consistently elicited beta1/2AR antagonist-insensitive lipolysis. However, a phenylethanolamine (SB-220646) that was a selective full beta3AR agonist elicited full lipolytic and inotropic responses that were sensitive to beta1/2AR antagonism, despite it having very low efficacies at cloned beta1- and beta2ARs. A component of the response to another phenylethanolamine selective beta3AR agonist (SB-215691) was insensitive to beta1/2AR antagonism in some experiments. Because no [corrected] novel aryloxypropanolamine had a beta1/2AR antagonist-insensitive inotropic effect, these results establish more firmly that beta3ARs mediate lipolysis in human white adipocytes, and suggest that putative 'beta4ARs' mediate inotropic responses to CGP 12177. The results also illustrate the difficulty of predicting from studies on cloned betaARs which betaARs will mediate responses to agonists in tissues that have a high number of beta1- and beta2ARs or a low number of beta3ARs.     

Model-based approach to study the impact of biofuels on the sustainability of an ecological system

The importance and complexity of sustainability have been well recognized and a formal study of sustainability based on system theory approaches is imperative as many of the relationships between various components of the ecosystem could be nonlinear, intertwined and non-intuitive. A mathematical model capable of yielding qualitative inferences can serve as an important tool for policy makers as it can be simulated under various important scenarios and also help in evaluating different strategies and technologies. In this article, we consider a simplified ecological food web which comprises a macro-economic system, an industrial production sector, an energy generation sector, and elements of a human society along with a rudimentary legal system. The energy sector is designed to supply energy to the other components of the ecosystem either by using a finite, non-renewable energy source or by a combination of non-renewable source and biomass. Many of the components of the ecosystem depend directly or indirectly on the biomass used for energy production. Subsequently, this model is used to study the impact of using biomass for the production of energy on the sustainability of other components of ecosystem. We have also simulated the model under two commonly foreseen scenarios of population explosion and consumption increase to understand the effect of using biomass for the production of energy on the sustainability of the various components of the system.     

Laser Assisted Uvulopalatoplasty: an objective evaluation of the technique and results

The indications for conservative and surgical management of fractures of the thoracolumbar spine are reviewed, based upon the morphology of the lesions, which is assessed by meticulous analysis of radiographs, CT scan and in some cases MRI. The author advocates using the AO classification, which considers several subtypes of fractures: compression fractures, distraction fractures and fractures with multidirectional displacement. The indication for treatment is based upon morphological analysis of the lesions, while other factors such as the general condition of the patient or the locally available surgical environment must also be taken into consideration. Up to 50% of thoracolumbar fractures can benefit from surgical management, with posterior or anterior stabilisation, the latter performed through thorascoscopy in selected cases.     

Therapeutic Targeting of the Leukaemia Microenvironment

In recent decades, the conduct of uniform prospective clinical trials has led to improved remission rates and survival for patients with acute myeloid leukaemia and acute lymphoblastic leukaemia. However, high-risk patients continue to have inferior outcomes, where chemoresistance and relapse are common due to the survival mechanisms utilised by leukaemic cells. One such mechanism is through hijacking of the bone marrow microenvironment, where healthy haematopoietic machinery is transformed or remodelled into a hiding ground or “sanctuary” where leukaemic cells can escape chemotherapy-induced cytotoxicity. The bone marrow microenvironment, which consists of endosteal and vascular niches, can support leukaemogenesis through intercellular “crosstalk” with niche cells, including mesenchymal stem cells, endothelial cells, osteoblasts, and osteoclasts. Here, we summarise the regulatory mechanisms associated with leukaemia–bone marrow niche interaction and provide a comprehensive review of the key therapeutics that target CXCL12/CXCR4, Notch, Wnt/b-catenin, and hypoxia-related signalling pathways within the leukaemic niches and agents involved in remodelling of niche bone and vasculature. From a therapeutic perspective, targeting these cellular interactions is an exciting novel strategy for enhancing treatment efficacy, and further clinical application has significant potential to improve the outcome of patients with leukaemia.     

Particle filtering

Recent developments have demonstrated that particle filtering is an emerging and powerful methodology, using Monte Carlo methods, for sequential signal processing with a wide range of applications in science and engineering. It has captured the attention of many researchers in various communities, including those of signal processing, statistics and econometrics. Based on the concept of sequential importance sampling and the use of Bayesian theory, particle filtering is particularly useful in dealing with difficult nonlinear and non-Gaussian problems. The underlying principle of the methodology is the approximation of relevant distributions with random measures composed of particles (samples from the space of the unknowns) and their associated weights. First, we present a brief review of particle filtering theory; and then we show how it can be used for resolving many problems in wireless communications. We demonstrate its application to blind equalization, blind detection over flat fading channels, multiuser detection, and estimation and detection of space-time codes in fading channels.     

Efficient optimization strategies with constraint programming

In this article, we propose novel strategies for the efficient determination of multiple solutions for a single objective, as well as globally optimal pareto fronts for multiobjective, optimization problems using Constraint Programming (CP). In particular, we propose strategies to determine, (i) all the multiple (globally) optimal solutions of a single objective optimization problem, (ii) K‐best feasible solutions of a single objective optimization problem, and (iii) globally optimal pareto fronts (including nonconvex pareto fronts) along with their multiple realizations for multiobjective optimization problems. It is shown here that the proposed strategy for determining K‐best feasible solutions can be tuned as per the requirement of the user to determine either K‐best distinct or nondistinct solutions. Similarly, the strategy for determining globally optimal pareto fronts can also be modified as per the requirement of the user to determine either only the distinct set of pareto points or determine the pareto points along with all their multiple realizations. All the proposed techniques involve appropriately modifying the search techniques and are shown to be computationally efficient in terms of not requiring successive re‐solving of the problem to obtain the required solutions. This work therefore convincingly addresses the issue of efficiently determining globally optimal pareto fronts; in addition, it also guarantees the determination of all the possible realizations associated with each pareto point. The uncovering of such solutions can greatly aid the designer in making informed decisions. The proposed approaches are demonstrated via two case studies, which are nonlinear, combinatorial optimization problems, taken from the area of sensor network design. © 2009 American Institute of Chemical Engineers AIChE J, 2010