Design of dual‐band microstrip patch antenna with right‐angle triangular aperture slot for energy transfer application

This work focusing on the dual‐band antenna design with rectifying circuit for energy transfer system technology for enhancement gain performance. The air gap technique is applied on this microstrip antenna design work to enhance the antenna gain. The work begins with designing and analyzing the antenna via the CST Microwave Studio software. After validation on acceptable performance in simulation side is obtained, the return loss, S₁₁ of the antenna is measured using vector network analyzer equipment. The rectifier circuit is used to convert the captured signal to DC voltage. This projected dual‐band antenna has successfully accomplished the target on return loss of ?44.707 dB and ?32.163 dB at dual resonant frequencies for 1.8 GHz and 2.4 GHz, respectively. This proposed antenna design benefits in low cost fabrication and has achieved high gain of 6.31 dBi and 7.82 dBi for dual‐band functioning frequencies.     

A multicriteria optimization model for cloud service provider selection in multicloud environments

Multicloud computing is a strategy that helps customers to reduce reliance on any single cloud provider (known as the vendor lock-in problem). The value of such strategy increases with proper selection of qualified service providers. In this paper, a constrained multicriteria multicloud provider selection mathematical model is proposed. Three metaheuristics algorithms (simulated annealing [SA], genetic algorithm [GA], and particle swarm optimization algorithm [PSO]) were implemented to solve the model, and their performance was studied and compared using a hypothetical case study. For the sake of comparison, Taguchi's robust design method was used to select the algorithms' parameters values, an initial feasible solution was generated using analytic hierarchy process (AHP)—as the most used method to solve the cloud provider selection problem in the literature, all three algorithms used that solution and, in order to avoid AHP limitations, another initial solution was generated randomly and used by the three algorithm in a second set of performance experiments. Results showed that SA, GA, PSO improved the AHP solution by 53.75%, 60.41%, and 60.02%, respectively, SA and PSO are robust because of reaching the same best solution in spite of the initial solution.     

Observable Dictionary Learning for High-Dimensional Statistical Inference

This paper introduces a method for efficiently inferring a high-dimensional distributed quantity from a few observations. The quantity of interest (QoI) is approximated in a basis (dictionary) learned from a training set. The coefficients associated with the approximation of the QoI in the basis are determined by minimizing the misfit with the observations. To obtain a probabilistic estimate of the quantity of interest, a Bayesian approach is employed. The QoI is treated as a random field endowed with a hierarchical prior distribution so that closed-form expressions can be obtained for the posterior distribution. The main contribution of the present work lies in the derivation of a representation basis consistent with the observation chain used to infer the associated coefficients. The resulting dictionary is then tailored to be both observable by the sensors and accurate in approximating the posterior mean. An algorithm for deriving such an observable dictionary is presented. The method is illustrated with the estimation of the velocity field of an open cavity flow from a handful of wall-mounted point sensors. Comparison with standard estimation approaches relying on Principal Component Analysis and K-SVD dictionaries is provided and illustrates the superior performance of the present approach.     

Equality test with an anonymous authorization in cloud computing

Wireless Networks - With the rapid popularity and wide adoption of cloud storage, providing privacy-preserving by protecting sensitive information becomes a matter of grave concern. The most...     

Overcoming Microenvironment-Mediated Chemoprotection through Stromal Galectin-3 Inhibition in Acute Lymphoblastic Leukemia

Environmentally-mediated drug resistance in B-cell precursor acute lymphoblastic leukemia (BCP-ALL) significantly contributes to relapse. Stromal cells in the bone marrow environment protect leukemia cells by secretion of chemokines as cues for BCP-ALL migration towards, and adhesion to, stroma. Stromal cells and BCP-ALL cells communicate through stromal galectin-3. Here, we investigated the significance of stromal galectin-3 to BCP-ALL cells. We used CRISPR/Cas9 genome editing to ablate galectin-3 in stromal cells and found that galectin-3 is dispensable for steady-state BCP-ALL proliferation and viability. However, efficient leukemia migration and adhesion to stromal cells are significantly dependent on stromal galectin-3. Importantly, the loss of stromal galectin-3 production sensitized BCP-ALL cells to conventional chemotherapy. We therefore tested novel carbohydrate-based small molecule compounds (Cpd14 and Cpd17) with high specificity for galectin-3. Consistent with results obtained using galectin-3-knockout stromal cells, treatment of stromal-BCP-ALL co-cultures inhibited BCP-ALL migration and adhesion. Moreover, these compounds induced anti-leukemic responses in BCP-ALL cells, including a dose-dependent reduction of viability and proliferation, the induction of apoptosis and, importantly, the inhibition of drug resistance. Collectively, these findings indicate galectin-3 regulates BCP-ALL cell responses to chemotherapy through the interactions between leukemia cells and the stroma, and show that a combination of galectin-3 inhibition with conventional drugs can sensitize the leukemia cells to chemotherapy.     

Symbol error rate calculation and data pre‐distortion for 16‐QAM transmission over nonlinear memoryless satellite channels

This paper presents a simplified mathematical approach to evaluate the performance of any given circular constellation of 16‐level quadrature amplitude modulation (16‐QAM) in terms of symbol error rate (SER). Following this approach, with the aim to work with memoryless nonlinear satellite channels, a model is derived as a generalized form for both linear and nonlinear channels in the presence of down link additive white Gaussian noise (AWGN). The analysis provides means to calculate the optimal ring ratio (RR) and phase difference (PD) for several possible candidates of 16‐QAM circular constellations. The effects of RR and PD on the SER performance are investigated in the analysis. To overcome the nonlinear distortion, data pre‐distortion is taken into account in the study. The paper gives a general procedure for data pre‐distortion implementation for all circular 16‐QAM constellations. The analytical formulation has been extended for total degradation (TD) performance measure as a function of input back‐off (IBO) of the nonlinear amplifier. A SER performance‐comparison between different constellations for 16‐QAM systems has also been presented in this paper. The analytical results are validated by simulation. Copyright © 2006 John Wiley & Sons, Ltd.     

Multi-objective optimization of process cogeneration systems with economic, environmental, and social tradeoffs

Process cogeneration is an effective strategy for exploiting the positive aspects of combined heat and power in the process industry. Traditionally, decisions for process cogeneration have been based mostly on economic criteria. With the growing interest in sustainability issues, there is need to consider economic, environmental, and social aspects of cogeneration. The objective of this article is to develop an optimization framework for the design of process cogeneration systems with economic, environmental, and social aspects. Process integration is used as the coordinating framework for the optimization formulation. First, heat integration is carried out to identify the heating utility requirements. Then, a multi-header steam system is designed and optimized for inlet steam characteristics and their impact on power, fixed and operating costs, greenhouse gas emissions, and jobs. A genetic algorithm is developed to solve the optimization problem. Multi-objective tradeoffs between the economic, environmental, and social aspects are studied through Pareto tradeoffs. A case study is solved to illustrate the applicability of the proposed procedure.     

Application of artificial neural networks for modeling of biohydrogen production

In this study, an artificial neural network (ANN) model was developed to estimate the hydrogen production profile with time in batch studies. A back propagation artificial neural network ANN configuration of 5–6–4–1 layers was developed. The ANN inputs were the initial pH, initial substrate and biomass concentrations, temperature, and time. The model training was done using 313 data points from 26 published experiments. The correlation coefficient between the experimental and estimated hydrogen production was 0.989 for training, validating, and testing the model. Results showed that the trained ANN successfully predicted the hydrogen production profile with time for new data with a correlation coefficient of 0.976.     

Natural Convection around Horizontal Tubes with Smooth,Rough, and Machined Surfaces

This study concerns natural convection around horizontal tubes with smooth, rough, and machined surfaces. The study is motivated by the need for understanding the machining effect or the use of a rough surface layer on the natural convection process. An experimental system is constructed that includes a thick wall metal tube equipped with thermocouples for measuring the surface temperature. A heating element is inserted inside the tube and is coupled with a power supply that can be adjusted to achieve surface temperatures of 60–160°C. The tube surface is machined at various depths of 1–3 mm. Also, four grades of sandpaper are used to cover the tube surface. An analysis of measured data is based on variations in the Nusselt number as a function of the Rayleigh number and surface condition. Results show that the measured data for the smooth tube are consistent with literature results. Although surface machining increases the heat transfer area, it lowers the heat transfer rate because of the low thermal conductivity of air, which replaces the removed metal in the machined grooves. Similarly, covering the tube surface with sandpaper reduces the rate of heat transfer from the tube surface because of contact resistance and the thermal resistance of the sandpaper. Data analysis that takes into consideration the above resistances, where the contact and sandpaper thermal resistances are eliminated, show enhancement of up to 30%. This implies that the direct roughening of a metal surface would enhance the heat transfer rate by 30%.     

UV radiation induces genome-mediated, site-specific cleavage in viral proteins

Much research has been dedicated to understanding the molecular basis of UV damage to biomolecules, yet many questions remain regarding the specific pathways involved. Here we describe a genome-mediated mechanism that causes site-specific virus protein cleavage upon UV irradiation. Bacteriophage MS2 was disinfected with 254 nm UV, and protein damage was characterized with ESI- and MALDI-based FT-ICR, Orbitrap, and TOF mass spectroscopy. Top-down mass spectrometry of the products identified the backbone cleavage site as Cys46-Ser47 in the virus capsid protein, a location of viral genome-protein interaction. The presence of viral RNA was essential to inducing backbone cleavage. The similar bacteriophage GA did not exhibit site-specific protein cleavage. Based on the major protein fragments identified by accurate mass analysis, a cleavage mechanism is proposed by radical formation. The mechanism involves initial oxidation of the Cys46 side chain followed by hydrogen atom abstraction from Ser47 C(α). Computational protein QM/MM studies confirmed the initial steps of the radical mechanism. Collectively, this study describes a rare incidence of genome-induced protein cleavage without the addition of sensitizers.