Implementations of Sorted-QR Decomposition for MIMO Receivers: Complexity,Reusability and Efficiency Analysis

Matrix decomposition of the channel matrix in the form of QR decomposition (QRD) is needed for advanced multiple input and multiple output (MIMO) demapping algorithms like sphere decoder. Due to the computation-intensive nature of the QRD, its implementation has to be highly efficient. Flexibility in several forms, e.g. support for different algorithms, reusability of wireless implementations, portability, etc. is highly sought in wireless devices. The contradictory nature of flexibility and efficiency requires tradeoffs to be made between them in system development. In this paper, we have analyzed such tradeoffs by implementing two minimum mean squared error-sorted QRD algorithms. The algorithms have been implemented in four different methods with varying degree of reusability and in five different forms of portability. The performance of the implementations is evaluated by using the real-time constraints from the LTE standard. For all the implementations, modular equations for accurately estimating the execution time are derived.     

Correlation between central receiver size and solar field using flat heliostats

In Central Receiver Systems (CRSs), thousands of heliostats track the sunrays and reflect beam radiation on to a receiver surface. The size of the reflected image and the extent of reflection from the heliostats are one of the important criteria that need to be taken into account while designing a receiver, since spillage losses may vary from 2 to 16% of the total losses. The present study aims to determine the size of an external cylindrical receiver, such that the rays reflected from all the heliostats in the field are intercepted. A dimensionless correlation with respect to tower height and receiver size (diameter and height) as a function of heliostat size and its position is discussed in the paper. This correlation could be used as a first-order approximation to estimate the receiver dimensions. When applied to the Ivanpah Solar Electricity Generating Station (ISEGS) plant, the correlation yields satisfactory estimation of receiver dimensions.     

Hydroxyoctadecadienoic Acids Regulate Apoptosis in Human THP‐1 Cells in a PPARγ‐Dependent Manner

Macrophage apoptosis, a key process in atherogenesis, is regulated by oxidation products, including hydroxyoctadecadienoic acids (HODEs). These stable oxidation products of linoleic acid (LA) are abundant in atherosclerotic plaque and activate PPARγ and GPR132. We investigated the mechanisms through which HODEs regulate apoptosis. The effect of HODEs on THP‐1 monocytes and adherent THP‐1 cells were compared with other C18 fatty acids, LA and α‐linolenic acid (ALA). The number of cells was reduced within 24 hours following treatment with 9‐HODE (p < 0.01, 30 μM) and 13 HODE (p < 0.01, 30 μM), and the equivalent cell viability was also decreased (p < 0.001). Both 9‐HODE and 13‐HODE (but not LA or ALA) markedly increased caspase‐3/7 activity (p < 0.001) in both monocytes and adherent THP‐1 cells, with 9‐HODE the more potent. In addition, 9‐HODE and 13‐HODE both increased Annexin‐V labelling of cells (p < 0.001). There was no effect of LA, ALA, or the PPARγ agonist rosiglitazone (1μM), but the effect of HODEs was replicated with apoptosis‐inducer camptothecin (10μM). Only 9‐HODE increased DNA fragmentation. The pro‐apoptotic effect of HODEs was blocked by the caspase inhibitor DEVD‐CHO. The PPARγ antagonist T0070907 further increased apoptosis, suggestive of the PPARγ‐regulated apoptotic effects induced by 9‐HODE. The use of siRNA for GPR132 showed no evidence that the effect of HODEs was mediated through this receptor. 9‐HODE and 13‐HODE are potent—and specific—regulators of apoptosis in THP‐1 cells. Their action is PPARγ‐dependent and independent of GPR132. Further studies to identify the signalling pathways through which HODEs increase apoptosis in macrophages may reveal novel therapeutic targets for atherosclerosis.     

Smart utilization of renewable energy sources in a microgrid system integrated with plug‐in hybrid electric vehicles

Mass roll‐out of plug‐in hybrid electric vehicles (PHEVs) and significant penetration of renewable energy sources in distribution system play a major role in delivering low carbon environment. However, placing and utilizing these units randomly result in overloading, increased power loss, and reduced voltage profile. This paper responds to these technical challenges by using a strategic placement method for locating the distributed generation (DG) and the charging station (CS) of PHEVs in a multi‐zone distribution system. For simultaneously scheduling of these units in each zone, the smart energy management framework is proposed in this paper. Apart from usual energy management constraints, this paper also incorporates the real‐time constraints involving the capacity of PHEV batteries, the mobility pattern, and the power level of the charging infrastructure. The simulation studies are carried out for each hour of a day. To cope with this time constraint execution, particle swarm optimization algorithm‐based approach is used. The proposed framework is tested in IEEE 33 and IEEE 69 bus radial distribution system. The obtained results imply that the presented energy management framework provides maximum profits for the vehicle owner, and meanwhile it fulfills preferences of the user in each zone simultaneously.     

Performance optimization problem in speculative prefetching

Speculative prefetching has been proposed to improve the response time of network access. Previous studies in speculative prefetching focus on building and evaluating access models for the purpose of access prediction. This paper investigates a complementary area which has been largely ignored, that of performance modeling. We analyze the performance of a prefetcher that has uncertain knowledge about future accesses. Our performance metric is the improvement in access time, for which we derive a formula in terms of resource parameters (time available and time required for prefetching) and speculative parameters (probabilities for next access). We develop a prefetch algorithm to maximize the improvement in access time. The algorithm is based on finding the best solution to a stretch knapsack problem, using theoretically proven apparatus to reduce the search space. An integration between speculative prefetching and caching is also investigated     

Quantification of surface damage of tool steels after EDM

The surface transformation and damage in AISI O1, A2, D2 and D6 tool steels after EDM were investigated. The results show that the recast layer is composed of two distinct layers: a topmost layer solidifying inwards from the specimen surface and an intermediate layer solidifying outwards from the base of the molten metal. The depth of surface cracks is found to correlate well with the thickness of the white layer, the latter being a layer of rapidly solidified material which, depending on the tool steel material, may consist either primarily of the topmost recast layer, or both the topmost and a large part of the intermediate recast layer. The density of surface cracks, however, correlates better with the thickness of the overall recast layer.

Attempts were made to quantify the depth of white (or damaged) layer with respect to the process parameters and surface roughness after EDM. It is found that with a fixed dielectric and flushing condition, the damaged layer correlates well with the pulse energy irrespective of thetool steel material. On the other hand, even though the thickness of the white layer increases with the surface roughness, the result shows considerably more scatter. Based on the present findings, ways of estimating the depth of the damaged layer produced by EDM are proposed.     

Generation of an eight node brick element using Papcovitch-Neuber functions

Some conventional finite elements suffer from drawbacks, such as shear locking, membrane locking, etc. To overcome them researchers have developed various techniques, termed as tricks by some and variational crimes by others. Many attempts have been made, but satisfactory explanations for why some of these techniques work have not been obtained, especially in the case of solid elements. This paper attempts a simple non-conforming solid element using assumed displacement fields which satisfy the Navier equation exactly. Its behaviour under simple loadings like bending, torsion and tension is examined and comparisons are made with existing elements.     

An optimal model for representing the kinetics of growth and product formation by Lactobacillus rhamnosus on multiple substrates

A comprehensive model was developed to simulate Lactobacillus rhamnosus growth on a medium containing multiple limiting carbon sources. The strategy of optimizing specific growth rate to predict growth on multiple substrates was demonstrated. The model predictions were based on parameters obtained from L. rhamnosus growth on individual substrates. The model was able to simulate the growth, substrate consumption, product formation and specific growth rate profiles of L. rhamnosus accurately. The model prediction that co-metabolism of glucose and pyruvate enhances growth rate of and flavor production by the bacterium was experimentally verified.     

Pattern identification in dynamical systems via symbolic time series analysis

This paper presents symbolic time series analysis (STSA) of multi-dimensional measurement data for pattern identification in dynamical systems. The proposed methodology is built upon concepts derived from Information Theory and Automata Theory. The objective is not merely to classify the time series patterns but also to identify the variations therein. To achieve this goal, a symbol alphabet is constructed from raw data through partitioning of the data space. The maximum entropy method of partitioning is extended to multi-dimensional space. The resulting symbol sequences, generated from time series data, are used to model the dynamical information as finite state automata and the patterns are represented by the stationary state probability distributions. A novel procedure for determining the structure of the finite state automata, based on entropy rate, is introduced. The diversity among the observed patterns is quantified by a suitable measure. The efficacy of the STSA technique for pattern identification is demonstrated via laboratory experimentation on nonlinear systems.