Metasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction ration of »60000 at visible spectral wavelength of 632 nm, could be achieved.
In real conditions of structures, foundations like retaining walls, industrial machines and platforms in offshore areas are commonly subjected to eccentrically inclined loads. This type of loading significantly affects the overall stability of shallow foundations due to exposing the foundation into two components of loads (horizontal and vertical) and consequently reduces the bearing capacity.
Based on a numerical analysis performed using finite element software (Plaxis 3D Foundation), the behavior of model strip foundation rested on dry sand under the effect of eccentric inclined loads with different embedment ratios (D/B) ranging from (0-1) has been explored. The results display that, the bearing capacity of st
... Show MoreBackground: The possibility of converting the organic fraction of municipal solid waste to mature compost using the composting bin method was studied. Nine distinct treatments were created by combining municipal solid waste (MSW) with animal waste (3:1, 2:1), poultry manure (3:1, 2:1), mixed waste (2:1:1), agricultural waste (dry leaves), biocont (Trichoderm hazarium), and humic acid. Weekly monitoring of temperature, pH, EC, organic matter (OM percent), and the C/N ratio was performed, and macronutrients (N, P, K) were measured. Trace elements, including heavy metals (Cd and Pb), were tested in the first and final weeks of maturity. Results: Temperatures in the first days of composting reached the thermophilic phase in MSW compost
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CD-nanosponges were prepared by crosslinking B-CD with diphenylcarbonate (DPC) using ultrasound assisted technique. 5-FU was incorporated with NS by freeze drying, and the phase solubility study, complexation efficiency (CE) entrapment efficiency were performed. Also, the particle morphology was studied using SEM and AFM. The in-vitro release of 5-FU from the prepared nanosponges was carried out in 0.1N HCl.
5-FU nanosponges particle size was in the nano size. The optimum formula showed a particle size of (405.46±30) nm, with a polydispersity index (PDI) (0.328±0.002) and a negative zeta potential (-18.75±1.8). Also the drug entrapment efficiency varied with the CD: DPC molar ratio from 15.6 % to 30%. The SEM an
... Show MoreBackground: The possibility of converting the organic fraction of municipal solid waste to mature compost using the composting bin method was studied. Nine distinct treatments were created by combining municipal solid waste (MSW) with animal waste (3:1, 2:1), poultry manure (3:1, 2:1), mixed waste (2:1:1), agricultural waste (dry leaves), biocont (Trichoderm hazarium), and humic acid. Weekly monitoring of temperature, pH, EC, organic matter (OM percent), and the C/N ratio was performed, and macronutrients (N, P, K) were measured. Trace elements, including heavy metals (Cd and Pb), were tested in the first and final weeks of maturity. Results: Temperatures in the first days of composting reached the thermophilic phase in MSW compost
... Show MoreWireless Multimedia Sensor Networks (WMSNs) are a type of sensor network that contains sensor nodes equipped with cameras, microphones; therefore the WMSNS are able to produce multimedia data such as video and audio streams, still images, and scalar data from the surrounding environment. Most multimedia applications typically produce huge volumes of data, this leads to congestion. To address this challenge, This paper proposes Modify Spike Neural Network control for Traffic Load Parameter with Exponential Weight of Priority Based Rate Control algorithm (MSNTLP with EWBPRC). The Modify Spike Neural Network controller (MSNC) can calculate the appropriate traffi
... Show MoreThe elections of the Council of Representatives in Iraq are one of the manifestations of political participation, which makes it attracts the attention of researchers. Where Iraq witnessed in 2005 important political events in the Iraqi arena, a pluralist parliamentary elections or elections in Iraq by direct free election on January 30, the first almost half a century ago. On November 15 of the same year, Iraq adopted a permanent constitution for the country through a popular referendum.
The present research aimed to study the polymorphisms of the chicken insulin-like growth factor 2 (IGF2) in two commercial broiler breeds (Cobb 500 and Hubbard F-15). In total, 300 avian blood samples were obtained. The genomic DNA was isolated using a fast salt-extraction technique. Moreover, polymerase chain reaction (PCR) was used to amplify 1146 bp fragments of the gene. The amplified fragments were subjected to restriction enzyme digestion using the HinfI endonuclease enzyme, and the digested products were separated on a 2% agarose gel. The findings indicated that there were two alleles, T and C, for the target locus, with frequencies of 73.3% and 26.7%, respectively. Three distinct genotype variations, TT, TC, and CC, were found, with
... Show MoreA mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the
... Show MoreA mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others
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