Using hash tables to manage the time-storage complexity in a point location problem: Application to explicit model predictive control

The online computational burden of linear model predictive control (MPC) can be moved offline by using multi-parametric programming, so-called explicit MPC. The solution to the explicit MPC problem is a piecewise affine (PWA) state feedback function defined over a polyhedral subdivision of the set of feasible states. The online evaluation of such a control law needs to determine the polyhedral region in which the current state lies. This procedure is called point location; its computational complexity is challenging, and determines the minimum possible sampling time of the system. A new flexible algorithm is proposed which enables the designer to trade off between time and storage complexities. Utilizing the concept of hash tables and the associated hash functions, the proposed method solves an aggregated point location problem that overcomes prohibitive complexity growth with the number of polyhedral regions, while the storage–processing trade-off can be optimized via scaling parameters. The flexibility and power of this approach is supported by several numerical examples.     

Analysis of room temperature magnetic regenerative refrigeration

Results of a room temperature magnetic refrigeration test bed and an analysis using a computational model are presented. A detailed demonstration of the four sequential processes in the transient magnetocaloric regeneration process of a magnetic material is presented. The temperature profile during the transient approach to steady state operation was measured in detail. A 5 °C evolution of the difference of temperature between the hot end and the cold end of the magnetocaloric bed due to regeneration is reported. A model is developed for the heat transfer and fluid mechanics of the four sequential processes in each cycle of thermal wave propagation in the regenerative bed combined with the magnetocaloric effect. The basic equations that can be used in simulation of magnetic refrigeration systems are derived and the design parameters are discussed.     

Oxy210, a Semi-Synthetic Oxysterol,Exerts Anti-Inflammatory Effects in Macrophages via Inhibition of Toll-like Receptor (TLR) 4 and TLR2 Signaling and Modulation of Macrophage Polarization

Inflammatory responses by the innate and adaptive immune systems protect against infections and are essential to health and survival. Many diseases including atherosclerosis, osteoarthritis, rheumatoid arthritis, psoriasis, and obesity involve persistent chronic inflammation. Currently available anti-inflammatory agents, including non-steroidal anti-inflammatory drugs, steroids, and biologics, are often unsafe for chronic use due to adverse effects. The development of effective non-toxic anti-inflammatory agents for chronic use remains an important research arena. We previously reported that oral administration of Oxy210, a semi-synthetic oxysterol, ameliorates non-alcoholic steatohepatitis (NASH) induced by a high-fat diet in APOE*3-Leiden.CETP humanized mouse model of NASH and inhibits expression of hepatic and circulating levels of inflammatory cytokines. Here, we show that Oxy210 also inhibits diet-induced white adipose tissue inflammation in APOE*3-Leiden.CETP mice, evidenced by the inhibition of adipose tissue expression of IL-6, MCP-1, and CD68 macrophage marker. Oxy210 and related analogs exhibit anti-inflammatory effects in macrophages treated with lipopolysaccharide in vitro, mediated through inhibition of toll-like receptor 4 (TLR4), TLR2, and AP-1 signaling, independent of cyclooxygenase enzymes or steroid receptors. The anti-inflammatory effects of Oxy210 are correlated with the inhibition of macrophage polarization. We propose that Oxy210 and its structural analogs may be attractive candidates for future therapeutic development for targeting inflammatory diseases.     

A collaborative platform for buyer coalition: Introducing the Awareness-based Buyer Coalition (ABC) system

A variety of buyer coalition schemes already exist in the current e-Commerce literature by which buyers form some sort of coalition in order to enjoy added discounts as a result of purchasing in larger bundles. One major problem in all existing schemes is that none of those schemes explicitly treat the coalition process as a collaborative business process; and as a result, the awareness and knowledge-sharing requirements are not explicitly recognized in the design process of the existing systems. This study proposes a conceptual framework for a buyer coalition system called the Awareness-based Buyer Coalition (ABC) system that allows a buyer to bid on the basis of various levels of awareness that s/he may have about other roles’ actions/intentions. The study is an early attempt for explicitly considering awareness and knowledge-sharing requirements of various roles within the buyer coalition process. The theoretical foundations of the study are rooted in the fields of Game Theory, e-Commerce, and Knowledge Management. The research methodology adopted for the study is design science. Various existing buyer coalition algorithms were reviewed and their strengths and weaknesses identified in terms of addressing the information-sharing needs of collaborating buyers. Furthermore, the existing literature on Knowledge Management was reviewed in order to identify an appropriate process model for the proposed buyer coalition framework with specific emphasis on awareness and knowledge-sharing requirements of its collaborating actors. For validation of the proposed conceptual model simulation software was developed to demonstrate results of a variety of simulations for the proof of the concept.     

Numerical simulation of steady natural convection heat transfer in a 3-dimensional single-ended tube subjected to a nanofluid

In this paper, 3-dimensional numerical simulation of steady natural convective flow and heat transfer are studied in a single-ended tube with non-uniform heat input. Apart from some other applications, it serves as a simplified model of the single-ended evacuated solar tube of a water-in-glass evacuated tube solar water heater. It is assumed that the sealed end of tube to be adiabatic and also the tube opening to be subjected to copper–water nanofluid. Governing equations are derived based on the conceptual model in the cylindrical coordinate system. The governing equations have been then approximated by means of a fully implicit finite volume control method (FVM), using SIMPLE algorithm on the collocated arrangement. The study has been carried out for solid volume fraction 0 ≤ φ ≤ 0.05 and maximum heat flux 100 ≤ q_m ≤ 700. Considering that the driven flow in the tube is influenced by the dimensions and the inclination angle of the solar tube, the flow patterns and temperature distributions are presented on different cross sectional planes and longitudinal sections, when the tube is positioned at different orientations.     

A hybrid discontinuous spectral element method and filtered mass density function solver for turbulent reacting flows

Abstract

We present a novel hybrid scheme for the large eddy simulation (LES) of turbulent reacting flows. The scheme couples the discontinuous spectral element method (DSEM) solver for the unsteady compressible Navier-Stokes equations with a Monte Carlo particle filtered mass density function (FMDF) solver for the transport of reacting species. The method is capable of high-order simulations on unstructured grids. Mean particle estimate construction mimics the DSEM numerical procedure and utilizes variable basis functions. The scheme is tested on non-reacting and reacting Taylor-Green vortex flows. Studies of varying polynomial order, different basis functions for constructing particle estimates, and varying particle quantities are conducted. We demonstrate that a tent kernel, in conjunction with high polynomial order, produces the most accurate results. The chemically reacting simulations validate the hybrid scheme and demonstrate its applicability across a range of reaction regimes. The hybrid scheme's computational cost is 2.1 times the DSEM-LES solver.     

A Distance Based Communication Mode Selection Mechanism for M2M Communications Over Cellular Networks

The implementation of machine-to-machine (M2M) communications in fifth-generation (5G) cellular networks can facilitate with several benefits like enhancement of bandwidth utilization, accommodating large number of users and decreasing traffic load on evolved node B (eNB). Integration of location information of unknown machine in communication mode selection mechanism is the key feature of this research. In this paper, a distance based communication mode selection mechanism using non-orthogonal resource sharing scheme is adopted in the proposed system model. Under the proposed mechanism, the expressions of throughput and RBs utilization policy are derived, which are the key parameters to evaluate the performance in the proposed network. Depending on the mode selection condition, such as threshold distance and threshold SINR between M2M users and regular cellular users, a UE can automatically choose its communication mode in the network. It is supposed that selection of mode before data transfer can improve the system performance. On the other hand, designing of efficient distance assisted proposed resource blocks (RBs) utilization policy reduces the traffic load on the eNB. Extensive simulations are carried out for evaluating the performance of the proposed mechanisms. The system performance is compared with various changeable parameters, such as throughput, mode selection threshold SINR, threshold distance and RBs. Besides, the proposed mechanism provides better network performance as well as reduces the traffic load in the proposed network.

     

A comprehensive review of solar‐driven desalination technologies for off‐grid greenhouses

This paper is motivated by the crisis of freshwater in remote areas around the world and responds to the growing need for sustainable food production in arid lands. It focuses on utilizing solar energy to yield freshwater from the sea or brackish water with less environmental impacts, for greenhouses, which can produce sustainable food all over the year. The integration of various solar‐driven desalinations such as solar still, humidification‐dehumidification, reverse osmosis, electrodialysis, and multieffect and multistage flash with greenhouses are evaluated, for better sustainability towards greenization. The paper first discusses the specifications of solar‐driven desalinations and compares their advantages and limitations. Then, different types of greenhouses are introduced, and their total water requirement is discussed based on their locations, crop type, greenhouse technology, irrigation type, and environmental conditions, as well as their cooling and heating strategies. Later, the existing integration of solar‐driven desalinations with greenhouses are reviewed, and their advantages and limitations are deliberated. Finally, the paper discusses the criteria to be considered when selecting solar‐driven desalinations for greenhouses and presents a detailed comparison between the water production rate and cost as well as the energy consumption of these systems. In the end, the most appropriate combinations of solar‐driven desalinations with greenhouses are recommended based on their water requirement and production cost.