General Metasurface Synthesis Based on Susceptibility Tensors

A general method, based on susceptibility tensors, is proposed for the synthesis of metasurfaces transforming arbitrary incident waves into arbitrary reflected and transmitted waves. The proposed method exhibits two advantages: 1)it is inherently vectorial, and therefore better suited for full vectorial (beyond paraxial) electromagnetic problems, 2) it provides closed-form solutions, and is therefore extremely fast. Incidentally, the method reveals that a metasurface is fundamentally capable to transform up to four independent wave triplets (incident, reflected and refracted waves). In addition, the paper provides the closed-form expressions relating the synthesized susceptibilities and the scattering parameters simulated within periodic boundary conditions, which allows one to design the scattering particles realizing the desired susceptibilities. The versatility of the method is illustrated by examples of metasurfaces achieving the following transformations: generalized refraction, reciprocal and non-reciprocal polarization rotation, Bessel vortex beam generation, and orbital angular momentum multiplexing

Sparse Spectrum Sensing in Infrastructure-less Cognitive Radio Networks via Binary Consensus Algorithms

Compressive Sensing has been utilized in Cognitive Radio Networks (CRNs) to exploit the sparse nature of the occupation of the primary users. Also, distributed spectrum sensing has been proposed to tackle the wireless channel problems, like node or link failures, rather than the common (centralized approach) for spectrum sensing. In this paper, we propose a distributed spectrum sensing framework based on consensus algorithms where SU nodes exchange their binary decisions to take global decisions without a fusion center to coordinate the sensing process. Each SU will share its decision with its neighbors, and at every new iteration each SU will take a new decision based on its current decision and the decisions it receives from its neighbors; in the next iteration, each SU will share its new decision with its neighbors. We show via simulations that the detection performance can tend to the performance of majority rule Fusion Center based CRNs

Synergetic Effect Of Permethrin And Dmh On Anti-Oxidation And Damage Response Genes

The objective of this study was to evaluate the Synergetic Effect of Permethrin and 1,2-Dimethylhydrazine (DMH) on Anti-oxidation and Damage Response genes. The animal models used for this study were 8 week old C57/blk6 female mice. The mice were fed a Folate Adequate (FA) diet. At 8 weeks, the mice were intraperitoneally injected with pesticides. Three 8-week old female mice were injected intraperitoneally with a mix of cis and trans permethrin (75%:25% respectively) at 30% median lethal dose (96 mg/kg body weight). Permethrin was dissolved in corn oil and injected 24 hours before sacrifice. In three other mice, DMH was also injected intraperitoneally 24 hours before sacrifice at 30 mg/kg body weight per mouse. Three mice were also injected 24 hours before sacrifice with a combination of DMH and permethrin at the same dosage. High levels of ACF formation and inflammation in the colon were seen in the mice injected with the combination of pesticides (combo) when compared to permethrin and DMH alone. To determine synergism of the pesticides, levels of gene expression was measured using cDNA. Anti-oxidation gene expression studied was glutathione peroxidase (GPx), thioredoxin (TRX), thioredoxin reductase (TRXR), and Peroxiredoxin (PRDX). The damage response genes studied were Tumor Protein p53 (p53), Growth Arrest and DNA Damage (GADD45), Mamalian Target of Rapamycin (mTor), and Proliferating cell nuclear antigen (PCNA). As a general trend, anti-oxidation genes had increased expression in mice given the combination of pesticides. An exception was the anti-oxidation gene TRXR which saw no change in expression. Damage response genes had unchanged levels of expression. An exception to this was p53 gene which saw increased expression in mice exposed to combo conditions

Education and Poverty in Morocco: A Computable General Equilibrium Micro-simulation Analysis

The paper uses a micro-simulation computable general equilibrium model (CGE) to analyze the impact on poverty of public spending in higher education in Morocco. The model incorporates 7062 households derived from the 2007 National Survey on Household Living Standards (ENNVM). Two scenarios are simulated: a 100% reduction in the unit cost of higher education supported by households and a 50% reduction in public spending on higher education. In this study, it is assumed that the investment behavior of households is linked to the share of the unit cost financed by the government in higher education. The results show that the policy of exempting households from bearing any unit cost of higher education encourages them to invest massively in education, which leads to increasing their income and consequently improving welfare and reducing poverty and inequalities. On the other hand, the reduction in public investment in higher education affects negatively the behavior of households to invest in education which leads to a decrease in welfare, an increase in poverty and a rise of inequalities