An Eigen Approach to Transmit Beamforming in Wireless Networks With Single Antenna Receivers

In this paper, we propose an eigen framework for transmit beamforming for single-hop and dual-hop network models with single antenna receivers. In cases where number of receivers is not more than three, the proposed Eigen approach is vastly superior in terms of ease of implementation and computational complexity compared with the existing convex-relaxation-based approaches. The essential premise is that the precoding problems can be posed as equivalent optimization problems of searching for an optimal vector in the joint numerical range of Hermitian matrices. We show that the latter problem has two convex approximations: the first one is a semi-definite program that yields a lower bound on the solution, and the second one is a linear matrix inequality that yields an upper bound on the solution. We study the performance of the proposed and existing techniques using numerical simulations.

Path Sensitive Cache Analysis Using Cache Miss Paths

Cache analysis plays a very important role in obtaining precise Worst Case Execution Time (WCET) estimates of programs for real-time systems. While Abstract Interpretation based approaches are almost universally used for cache analysis, they fail to take advantage of its unique requirement: it is not necessary to find the guaranteed cache behavior that holds across all executions of a program. We only need the cache behavior along one particular program path, which is the path with the maximum execution time. In this work, we introduce the concept of cache miss paths, which allows us to use the worst-case path information to improve the precision of AI-based cache analysis. We use Abstract Interpretation to determine the cache miss paths, and then integrate them in the IPET formulation. An added advantage is that this further allows us to use infeasible path information for cache analysis. Experimentally, our approach gives more precise WCETs as compared to AI-based cache analysis, and we also provide techniques to trade-off analysis time with precision to provide scalability.

Event-triggered sampling using signal extrema for instantaneous amplitude and instantaneous frequency estimation

Event-triggered sampling (ETS) is a new approach towards efficient signal analysis. The goal of ETS need not be only signal reconstruction, but also direct estimation of desired information in the signal by skillful design of event. We show a promise of ETS approach towards better analysis of oscillatory non-stationary signals modeled by a time-varying sinusoid, when compared to existing uniform Nyquist-rate sampling based signal processing. We examine samples drawn using ETS, with events as zero-crossing (ZC), level-crossing (LC), and extrema, for additive in-band noise and jitter in detection instant. We find that extrema samples are robust, and also facilitate instantaneous amplitude (IA), and instantaneous frequency (IF) estimation in a time-varying sinusoid. The estimation is proposed solely using extrema samples, and a local polynomial regression based least-squares fitting approach. The proposed approach shows improvement, for noisy signals, over widely used analytic signal, energy separation, and ZC based approaches (which are based on uniform Nyquist-rate sampling based data-acquisition and processing). Further, extrema based ETS in general gives a sub-sampled representation (relative to Nyquistrate) of a time-varying sinusoid. For the same data-set size captured with extrema based ETS, and uniform sampling, the former gives much better IA and IF estimation. (C) 2015 Elsevier B.V. All rights reserved.

Volume conservation issues in incompressible smoothed particle hydrodynamics

A divergence-free velocity field is usually sought in numerical simulations of incompressible fluids. We show that the particle methods that compute a divergence-free velocity field to achieve incompressibility suffer from a volume conservation issue when a finite time-step position update scheme is used. Further, we propose a deformation gradient based approach to arrive at a velocity field that reduces the volume conservation issues in free surface flows and maintains density uniformity in internal flows while retaining the simplicity of first order time updates. (C) 2015 Elsevier Inc. All rights reserved.

Lead selection and characterization of antitubercular compounds using the Nested Chemical Library

Discovering new drugs to treat tuberculosis more efficiently and to overcome multidrug resistance is a world health priority. To find novel antitubercular agents several approaches have been used in various institutions worldwide, including target-based approaches against several validated mycobacterial enzymes and phenotypic screens. We screened more than 17,000 compounds from Vichem's Nested Chemical Library(TM) using an integrated strategy involving whole cell-based assays with Corynebacterium glutamicum and Mycobacterium tuberculosis, and target-based assays with protein kinases PknA, PknB and PknG as well as other targets such as PimA and bacterial topoisomerases simultaneously. With the help of the target-based approach we have found very potent hits inhibiting the selected target enzymes, but good minimal inhibitory concentrations (MIC) against M. tuberculosis were not achieved. Focussing on the whole cell-based approach several potent hits were found which displayed minimal inhibitory concentrations (MIC) against M. tuberculosis below 10 mu M and were non-mutagenic, non-cytotoxic and the targets of some of the hits were also identified. The most active hits represented various scaffolds. Medicinal chemistry-based lead optimization was performed applying various strategies and, as a consequence, a series of novel potent compounds were synthesized. These efforts resulted in some effective potential antitubercular lead compounds which were confirmed in phenotypic assays. (C) 2015 Elsevier Ltd. All rights reserved.

Recent advances in engineering topography mediated antibacterial surfaces

The tendency of bacterial cells to adhere and colonize a material surface leading to biofilm formation is a fundamental challenge underlying many different applications including microbial infections associated with biomedical devices and products. Although, bacterial attachment to surfaces has been extensively studied in the past, the effect of surface topography on bacteria-material interactions has received little attention until more recently. We review the recent progress in surface topography based approaches for engineering antibacterial surfaces. Biomimicry of antibacterial surfaces in nature is a popular strategy. Whereas earlier endeavors in the field aimed at minimizing cell attachment, more recent efforts have focused on developing bactericidal surfaces. However, not all such topography mediated bactericidal surfaces are necessarily cytocompatible thus underscoring the need for continued efforts for research in this area for developing antibacterial and yet cytocompatible surfaces for use in implantable biomedical applications. This mini-review provides a brief overview of the current strategies and challenges in the emerging field of topography mediated antibacterial surfaces.

Optimal Guidance for Accurate Lunar Soft Landing with Minimum Fuel Consumption using Model Predictive Static Programming

In this paper the soft lunar landing with minimum fuel expenditure is formulated as a nonlinear optimal guidance problem. The realization of pinpoint soft landing with terminal velocity and position constraints is achieved using Model Predictive Static Programming (MPSP). The high accuracy of the terminal conditions is ensured as the formulation of the MPSP inherently poses final conditions as a set of hard constraints. The computational efficiency and fast convergence make the MPSP preferable for fixed final time onboard optimal guidance algorithm. It has also been observed that the minimum fuel requirement strongly depends on the choice of the final time (a critical point that is not given due importance in many literature). Hence, to optimally select the final time, a neural network is used to learn the mapping between various initial conditions in the domain of interest and the corresponding optimal flight time. To generate the training data set, the optimal final time is computed offline using a gradient based optimization technique. The effectiveness of the proposed method is demonstrated with rigorous simulation results.

Molecular/Cluster Statistical Thermodynamics Methods To Simulate Quasi-Static Deformations At Finite Temperature

The rapid evolution of nanotechnology appeals for the understanding of global response of nanoscale systems based on atomic interactions, hence necessitates novel, sophisticated, and physically based approaches to bridge the gaps between various length and time scales. In this paper, we propose a group of statistical thermodynamics methods for the simulations of nanoscale systems under quasi-static loading at finite temperature, that is, molecular statistical thermodynamics (MST) method, cluster statistical thermodynamics (CST) method, and the hybrid molecular/cluster statistical thermodynamics (HMCST) method. These methods, by treating atoms as oscillators and particles simultaneously, as well as clusters, comprise different spatial and temporal scales in a unified framework. One appealing feature of these methods is their "seamlessness" or consistency in the same underlying atomistic model in all regions consisting of atoms and clusters, and hence can avoid the ghost force in the simulation. On the other hand, compared with conventional MD simulations, their high computational efficiency appears very attractive, as manifested by the simulations of uniaxial compression and nanoindenation. (C) 2008 Elsevier Ltd. All rights reserved.

Sequential decision making in general state space models

Many problems in control and signal processing can be formulated as sequential decision problems for general state space models. However, except for some simple models one cannot obtain analytical solutions and has to resort to approximation. In this thesis, we have investigated problems where Sequential Monte Carlo (SMC) methods can be combined with a gradient based search to provide solutions to online optimisation problems. We summarise the main contributions of the thesis as follows. Chapter 4 focuses on solving the sensor scheduling problem when cast as a controlled Hidden Markov Model. We consider the case in which the state, observation and action spaces are continuous. This general case is important as it is the natural framework for many applications. In sensor scheduling, our aim is to minimise the variance of the estimation error of the hidden state with respect to the action sequence. We present a novel SMC method that uses a stochastic gradient algorithm to find optimal actions. This is in contrast to existing works in the literature that only solve approximations to the original problem. In Chapter 5 we presented how an SMC can be used to solve a risk sensitive control problem. We adopt the use of the Feynman-Kac representation of a controlled Markov chain flow and exploit the properties of the logarithmic Lyapunov exponent, which lead to a policy gradient solution for the parameterised problem. The resulting SMC algorithm follows a similar structure with the Recursive Maximum Likelihood(RML) algorithm for online parameter estimation. In Chapters 6, 7 and 8, dynamic Graphical models were combined with with state space models for the purpose of online decentralised inference. We have concentrated more on the distributed parameter estimation problem using two Maximum Likelihood techniques, namely Recursive Maximum Likelihood (RML) and Expectation Maximization (EM). The resulting algorithms can be interpreted as an extension of the Belief Propagation (BP) algorithm to compute likelihood gradients. In order to design an SMC algorithm, in Chapter 8 uses a nonparametric approximations for Belief Propagation. The algorithms were successfully applied to solve the sensor localisation problem for sensor networks of small and medium size.

Fishing capacity management

Excess fishing capacity has been identified as one of the most pernicious problems affecting long-term sustainability and biodiversity of fishery resources and economic viability of fishing operations. Significant economic gains could be achieved by eliminating excess capacity, in addition to attaining objectives of resource sustainability. In this paper, approaches to fishing capacity management are reviewed in the context of Indian fisheries. A rights based regulated access system under a co-management regime based on a strong inclusive cooperative movement of stakeholders with built-in transferable quota system and buy-back or rotational right of entry schemes seems to hold potential for capacity management in the shelf fisheries of Indian states, which need to be implemented in collaboration with the Union Government and the neighboring states with confluent ecosystems and shared fishing grounds. A key advantage of the use of rights based approaches for managing fishing capacity is that they provide a mechanism through which stakeholders can more easily and actively participate in the management process.

Cruise Report: Summer 2008 Ecological Assessment of Stellwagen Bank National Marine Sanctuary NOAA Ship NANCY FOSTER NF-08-09-CCEHBR (June 14-June 21, 2008)

Summary: This cruise report is a summary of a field survey conducted within the Stellwagen Bank National Marine Sanctuary (SBNMS), located between Cape Cod and Cape Ann at the mouth of Massachusetts Bay. The survey was conducted June 14 – June 21, 2008 on NOAA Ship NANCY FOSTER Cruise NF-08-09-CCEHBR. Multiple indicators of ecological condition and human dimensions were sampled synoptically at each of 30 stations throughout SBNMS using a random probabilistic sampling design. Samples were collected for the analysis of benthic community structure and composition; concentrations of chemical contaminants (metals, pesticides, PAHs, PCBs, PBDEs) in sediments and target demersal biota; nutrient and chlorophyll levels in the water column; and other basic habitat characteristics such as depth, salinity, temperature, dissolved oxygen, turbidity, pH, sediment grain size, and organic carbon content. In addition to the fish samples that were collected for analysis of chemical contaminants relative to human-health consumption limits, other human-dimension indicators were sampled as well including presence or absence of fishing gear, vessels, surface trash, marine mammals, and noxious sediment odors. The overall purpose of the survey was to collect data to assess the status of ecosystem condition and potential stressor impacts throughout SBNMS, based on these various indicators and corresponding management thresholds, and to provide this information as a baseline for determining how such conditions may be changing with time. While sample analysis is still ongoing a few preliminary results and observations are reported here. A final report will be completed once all data have been processed. The results are anticipated to be of value in supporting goals of the SBNMS and National Marine Sanctuary Program aimed at the characterization, protection, and management of sanctuary resources (pursuant to the National Marine Sanctuary Reauthorization Act) as well as a new priority of NCCOS and NOAA to apply Ecosystem Based approaches to the Management of coastal resources (EBM) through Integrated Ecosystem Assessments (IEAs) conducted in various coastal regions of the U.S. including the Northeast Atlantic continental shelf. This was a multi-disciplinary partnership effort made possible by scientists from the following organizations:  NOAA, National Ocean Service (NOS), National Centers for Coastal Ocean Science (NCCOS), Center for Coastal Environmental Health and Biomolecular Research (CCEHBR), Charleston, SC.  U.S. Environmental Protection Agency (EPA), National Health and Environmental Effects Research Laboratory (NHEERL), Atlantic Ecology Division (GED), Narragansett, RI.  U.S. Environmental Protection Agency (EPA), National Health and Environmental Effects Research Laboratory (NHEERL), Gulf Ecology Division (GED), Gulf Breeze, FL.  U.S. Geological Survey (USGS), National Wetlands Research Center, Gulf Breeze Project Office, Gulf Breeze, FL.  NOAA, Office of Marine and Aviation Operations (OMAO), NOAA ship Nancy Foster. (31pp) (PDF contains 58 pages)

The South Atlantic Alliance: A southeastern U.S. state Governors initiative to address opportunities and challenges embodied in the region's coastal and ocean domain

The pressures placed on the natural, environmental, economic, and cultural sectors from continued growth, population shifts, weather and climate, and environmental quality are increasing exponentially in the southeastern U.S. region. Our growing understanding of the relationship of humans with the marine environment is leading us to explore new ecosystem-based approaches to coastal management, marine resources planning, and coastal adaptation that engages multiple state jurisdictions. The urgency of the situation calls for coordinated regional actions by the states, in conjunction with supporting partners and leveraging a diversity of resources, to address critical issues in sustaining our coastal and ocean ecosystems and enhancing the quality of life of our citizens. The South Atlantic Alliance (www.southatlanticalliance.org) was formally established on October 19, 2009 to “implement science-based policies and solutions that enhance and protect the value of coastal and ocean resources of the southeastern United States which support the region's culture and economy now and for future generations.” The Alliance, which includes North Carolina, South Carolina, Georgia, and Florida, will provide a regional mechanism for collaborating, coordinating, and sharing information in support of resource sustainability; improved regional alignment; cooperative planning and leveraging of resources; integrated research, observations, and mapping; increased awareness of the challenges facing the South Atlantic region; and inclusiveness and integration at all levels. Although I am preparing and presenting this overview of the South Atlantic Alliance and its current status, there are a host of representatives from agencies within the four states, universities, NGOs, and ongoing southeastern regional ocean and coastal programs that are contributing significant time, expertise, and energy to the success of the Alliance; information presented herein and to be presented in my oral presentation was generated by the collaborative efforts of these professionals. I also wish to acknowledge the wisdom and foresight of the Governors of the four states in establishing this exciting regional ocean partnership. (PDF contains 4 pages)

Analysis and optimization of stress wave propagation in two-dimensional granular crystals with defects

Granular crystals are compact periodic assemblies of elastic particles in Hertzian contact whose dynamic response can be tuned from strongly nonlinear to linear by the addition of a static precompression force. This unique feature allows for a wide range of studies that include the investigation of new fundamental nonlinear phenomena in discrete systems such as solitary waves, shock waves, discrete breathers and other defect modes. In the absence of precompression, a particularly interesting property of these systems is their ability to support the formation and propagation of spatially localized soliton-like waves with highly tunable properties. The wealth of parameters one can modify (particle size, geometry and material properties, periodicity of the crystal, presence of a static force, type of excitation, etc.) makes them ideal candidates for the design of new materials for practical applications. This thesis describes several ways to optimally control and tailor the propagation of stress waves in granular crystals through the use of heterogeneities (interstitial defect particles and material heterogeneities) in otherwise perfectly ordered systems. We focus on uncompressed two-dimensional granular crystals with interstitial spherical intruders and composite hexagonal packings and study their dynamic response using a combination of experimental, numerical and analytical techniques. We first investigate the interaction of defect particles with a solitary wave and utilize this fundamental knowledge in the optimal design of novel composite wave guides, shock or vibration absorbers obtained using gradient-based optimization methods.

Apaf-1 Inhibitors Protect from Unwanted Cell Death in In Vivo Models of Kidney Ischemia and Chemotherapy Induced Ototoxicity

Background: Excessive apoptosis induces unwanted cell death and promotes pathological conditions. Drug discovery efforts aimed at decreasing apoptotic damage initially targeted the inhibition of effector caspases. Although such inhibitors were effective, safety problems led to slow pharmacological development. Therefore, apoptosis inhibition is still considered an unmet medical need. Methodology and Principal Findings: The interaction between Apaf-1 and the inhibitors was confirmed by NMR. Target specificity was evaluated in cellular models by siRNa based approaches. Cell recovery was confirmed by MTT, clonogenicity and flow cytometry assays. The efficiency of the compounds as antiapoptotic agents was tested in cellular and in vivo models of protection upon cisplatin induced ototoxicity in a zebrafish model and from hypoxia and reperfusion kidney damage in a rat model of hot ischemia. Conclusions: Apaf-1 inhibitors decreased Cytc release and apoptosome-mediated activation of procaspase-9 preventing cell and tissue damage in ex vivo experiments and in vivo animal models of apoptotic damage. Our results provide evidence that Apaf-1 pharmacological inhibition has therapeutic potential for the treatment of apoptosis-related diseases.

RESTful Discovery and Eventing for Service Provisioning in Assisted Living Environments

Service provisioning in assisted living environments faces distinct challenges due to the heterogeneity of networks, access technology, and sensing/actuation devices in such an environment. Existing solutions, such as SOAP-based web services, can interconnect heterogeneous devices and services, and can be published, discovered and invoked dynamically. However, it is considered heavier than what is required in the smart environment-like context and hence suffers from performance degradation. Alternatively, REpresentational State Transfer (REST) has gained much attention from the community and is considered as a lighter and cleaner technology compared to the SOAP-based web services. Since it is simple to publish and use a RESTful web service, more and more service providers are moving toward REST-based solutions, which promote a resource-centric conceptualization as opposed to a service-centric conceptualization. Despite such benefits of REST, the dynamic discovery and eventing of RESTful services are yet considered a major hurdle to utilization of the full potential of REST-based approaches. In this paper, we address this issue, by providing a RESTful discovery and eventing specification and demonstrate it in an assisted living healthcare scenario. We envisage that through this approach, the service provisioning in ambient assisted living or other smart environment settings will be more efficient, timely, and less resource-intensive.