Effect of ZnO layer thickness upon optoelectrical properties of NiO/ ZnO heterojunction prepared at room temperature

In this work, p-NiO/n-ZnO heterostructures were successfully prepared at room temperature using RF sputtering technique. The influence of ZnO layer thickness on the performance of the heterojunction was investigated. The deposited ZnO layers have a hexagonal Wurtzite structure with preferable growth orientations along (002) and (103) for thinner films. Increasing the thickness results in more crystallographic orientation randomness. The current–voltage measurements of the realized heterojunctions showed a clear rectifying behavior. The measured ideality factor varies from 2.5 to 1.6 according to the thickness of ZnO layer. The series resistance of the device is enlarged with increasing ZnO thickness. The deduced parameters from the I–V characteristics suggest that 200 nm is the optimal thickness of the ZnO layer according to our experimental conditions. We attribute the relatively better performance of this thickness to achieving reasonable compensation between serial resistance and ideality factor. The best heterojunction was tested and successfully used as a UV detector.     

Privacy-preserving iris authentication using fully homomorphic encryption

Multimedia Tools and Applications - Rapid advancement in technology has led to the use of biometric authentication in every field. In particular, from the past few years, iris recognition systems...     

Food recognition using neural network classifier and multiple hypotheses image segmentation

ABSTRACT

This paper proposes the multiple-hypotheses image segmentation and feed-forward neural network classifier for food recognition to improve the performance. Initially, the food or meal image is given as input. Then, the segmentation is applied to identify the regions, where a particular food item is located using salient region detection, multi-scale segmentation, and fast rejection. Then, the features of every food item are extracted by the global feature and local feature extraction. After the features are obtained, the classification is performed for each segmented region using a feed-forward neural network model. Finally, the calorie value is computed with the aid of (i) food volume and (ii) calorie and nutrition measure based on mass value. The experimental results and performance evaluation are validated. The outcome of the proposed method attains 0.947 for Macro Average Accuracy (MAA) and 0.959 for Standard Accuracy (SA), which provides better classification performance.     

Macrophage Immunomodulation Through New Polymers that Recapitulate Functional Effects of Itaconate as a Power House of Innate Immunity

Itaconate (ITA) is an emerging powerhouse of innate immunity with therapeutic potential that is limited in its ability to be administered in a soluble form. A library of polyester materials that incorporate ITA into polymer backbones resulting in materials with inherent immunoregulatory behavior is developed. Harnessing hydrolytic degradation release from polyester backbones, ITA polymers result in the mechanism specific immunoregulatory properties on macrophage polarization in vitro. In a functional assay, the polymer-released ITA inhibits bacterial growth on acetate. Translation to an in vivo model of biomaterial associated inflammation, intraperitoneal injection of ITA polymers demonstrate a rapid resolution of inflammation in comparison to a control polymer silicone, demonstrating the value of sustained biomimetic presentation of ITA.     

Real-time organic aerosol chemical speciation in the indoor environment using extractive electrospray ionization mass spectrometry

Understanding the sources and composition of organic aerosol (OA) in indoor environments requires rapid measurements, since many emissions and processes have short timescales. However, real-time molecular-level OA measurements have not been reported indoors. Here, we present quantitative measurements, at a time resolution of five seconds, of molecular ions corresponding to diverse aerosol-phase species, by applying extractive electrospray ionization mass spectrometry (EESI-MS) to indoor air analysis for the first time, as part of the highly instrumented HOMEChem field study. We demonstrate how the complex spectra of EESI-MS are screened in order to extract chemical information and investigate the possibility of interference from gas-phase semivolatile species. During experiments that simulated the Thanksgiving US holiday meal preparation, EESI-MS quantified multiple species, including fatty acids, carbohydrates, siloxanes, and phthalates. Intercomparisons with Aerosol Mass Spectrometer (AMS) and Scanning Mobility Particle Sizer suggest that EESI-MS quantified a large fraction of OA. Comparisons with FIGAERO-CIMS shows similar signal levels and good correlation, with a range of 100 for the relative sensitivities. Comparisons with SV-TAG for phthalates and with SV-TAG and AMS for total siloxanes also show strong correlation. EESI-MS observations can be used with gas-phase measurements to identify co-emitted gas- and aerosol-phase species, and this is demonstrated using complementary gas-phase PTR-MS observations.     

Shaping the Toroidal Section of End Mills

The shaping of the toroidal cutting section of end mills is considered. Methods are devised for selecting the positional parameters in shaping the helical rake surface on the toroidal section. Relations are established between the geometric parameters of the end mill in the toroidal section.     

Enzyme activity and partial characterization of proteases obtained from Bromelia karatas fruit and compared with Bromelia pinguin proteases

Food Science and Biotechnology - The enzymatic activity and partial characterization of proteases from Bromelia karatas fruits were evaluated and compared with Bromelia pinguin proteases. The...