ZnO(101) films by pulsed reactive crossed-beam laser ablation

We have employed pulsed reactive crossed-beam laser ablation (PRCLA) to deposit a (101) oriented ZnO film. In this method, a supersonic jet of oxygen pulse is made to cross the laser plume from a zinc metal target while being carried to the Si(111) substrate. The obtained deposit was nanocrystalline ZnO as confirmed by a host of characterization techniques. When the substrate was held at varying temperatures, from room temperature to 900°C, the crystallinity of the obtained films increased as expected, but importantly, the crystallographic orientation of the films was varied. High substrate temperatures produced the usual (001) oriented films, while lower substrate temperatures gave rise to increasingly (101) oriented films. The substrate held at room temperature contained only the (101) orientation. The film morphology also varied with the substrate temperature, from being nanoparticulate to rod-like deposits for higher deposition temperatures. Surprisingly, the (101) orientation showed reactivity with acetone forming carbonaceous nanostructures on the surface.     

Influence of CTAB surfactant on structural and optical properties of CuS and CdS nanoparticles by hydrothermal route

Metal sulphide CuS and CdS nanoparticles capped with Cetyltrimethylammonium bromide (CTAB) were synthesized by hydrothermal method. Structural, morphological, chemical composition, optical and luminescent properties were evaluated by different analytical techniques. X-ray diffraction (XRD) analysis of the CTAB capped metal sulfide nanoparticles reveals the formation of hexagonal structure. High-resolution transmission electron microscopy (HRTEM) images show that the morphology of the capped copper sulphide samples consists of hexagonal structure and capped cadmium has spherical shape and also confirms the crystalline nature of the particles with distinct lattice fringes. In FTIR spectroscopy, the composition of the CTAB capped CuS and CdS nanoparticles have been confirmed. The analysis of photoluminescence (PL) and optical transition show a red shift due to the reduction of band gap energy and it is attributed to the low defects and high crystallinity. The optical studies indicate that CuS and CdS nanoparticles with CTAB can be suitable for optoelectronic devices and photovoltaic applications.     

Ontology‐based Grid resource management

Grid resources are typically diverse in nature with respect to their software and hardware configurations, resource usage policies and the kind of application they support. Aggregating and monitoring these resources, and discovering suitable resources for the applications become a challenging issue. This is partially due to the representation of Grid metadata supported by the existing Grid middleware which offers limited scope for matching the job requirements that directly affect scheduling decisions. This paper proposes a semantic component in conventional Grid architecture to support ontology‐based representation of Grid metadata and facilitate context‐based information retrieval that complements Grid schedulers for effective resource management. Web Ontology language is used for creating Grid resource ontology and Algernon inference engine has been used for resource discovery. This semantic component has been integrated with conventional Grid schedulers. Several experiments have also been carried out to investigate the performance overhead that arises while integrating this component with Grid schedulers. Copyright © 2009 John Wiley & Sons, Ltd.     

Electrochemical studies of stainless steel implanted with nitrogen and oxygen by plasma immersion ion implantation

Plasma Immersion Ion Implantation (PIII) of stainless steel with nitrogen at temperatures lower than 400 °C has been reported to increase the hardness of the material by several times. However, expectations that the corrosion resistance will remain unaffected after implantation were not found to be so. In the present study the influence of post-oxygen implantation on the corrosion resistance of nitrogen implanted stainless steel is presented. Stainless steel samples were subjected to oxygen, nitrogen and post-oxygen ion implantation at different temperatures. GIXRD and microRaman studies of the implanted samples showed that oxygen implantation leads to the formation of an oxide layer consisting of corundum and spinel structures. The corrosion properties of the implanted samples were studied by potentiodynamic polarization and electrochemical impedance techniques in 3.5% NaCl solution. After nitrogen implantation the corrosion current increased and the corrosion potential shifted to the less noble side to − 0.486 V as compared to − 0.284 V for the substrate. Oxygen implantation at 400 °C shifted the corrosion potential to the nobler side to − 0.2 V with decrease of corrosion current. For post-oxygen ion implantation at temperatures lower than 400 °C, the corrosion current was higher than the substrate and the corrosion potential was also on the less noble side. However, post-oxygen ion implantation at 400 °C after nitrogen ion implantation resulted in improved corrosion resistance as the corrosion potential shifted to nobler side and the corrosion current was lower than that of substrate.     

An adaptive gravitational search optimization (AGSO)-based convolutional neural network—long short-term memory (CNN-LSTM) approach for face recognition and classification

Face recognition and classification have gained increasing attraction in the recent decades due to their widespread adoption in real time application systems. Most of the conventional research efforts focused on developing face recognition frameworks using enhanced optimization-based classification methods, they are hampered by issues such as computational complexity, increased overhead, limited capacity to handle large datasets, and lengthy processing time. The novel contribution of this paper is to develop a highly competent and precise face recognition methodology through an innovative mechanism. In this framework, the initial step involves face detection from input images using an analytical face parts detection methodology. Subsequently, the tutor face filtering (TFF) technique is applied to preprocess the face image, enhancing its quality and filtering out noise content. Following this preprocessing step, features are extracted from the processed image using the direction-based pattern extraction (DBPE) model. To improve classifier accuracy, a novel adaptive gravitational search optimization (AGSO) technique is employed to select the optimal features during model training. Finally, an integrated deep learning model, referred to as convolutional neural network — long short-term memory (LSTM), is utilized for accurate face image recognition based on the selected optimal features. To assess and compare the system's performance, various metrics are employed in the results analysis to demonstrate the superiority of the proposed approach.     

Cask and plug handling system design in port cell

The ITER maintenance strategy relies partly on the remote transfer of components from vacuum vessel to hot cells. This function will be fulfilled by transfer cask systems.This paper describes the recent design progresses on interfaces in order to increase components handling feasibility by implementing continuous guiding features that avoid cantilevered loads on the in-cask tractor. Also the design has progressed in order to allow generic docking of the casks.When the cask is connected to the port, it becomes part of the machine first confinement boundary, thus it must provide tightness continuity. This high level safety function was one of the main concerns of a finite element analysis study that has been performed to assess the behavior of the whole system. Numerical analysis methodology and results are explained and shown in order to highlight how it has reinforced the knowledge of the system.     

Common vector approach and its combination with GMM for text-independent speaker recognition

In this paper, the common vector approach (CVA) is newly used for text-independent speaker recognition. The performance of CVA is compared with those of Fisher’s linear discriminant analysis (FLDA) and Gaussian mixture models (GMM). The recognition rates obtained for the TIMIT database indicate that CVA and GMM are superior to FLDA. However, while the recognition rates obtained from CVA and GMM are identical, CVA enjoys advantages in terms of processing power and memory requirement. In order to obtain better results than those achieved with GMM, a new method which is a combination of CVA and GMM is proposed in this paper.     

Assessment of crtRB1 Polymorphism Associated with Increased β-Carotene Content in Maize (Zea mays L.) Seeds

Breeding for increasing β-carotene levels in maize (Zea mays L.) kernel aims to address the dietary vitamin A deficiency. Due to 3’TE polymorphism, the crtRB1gene (that encodes β -carotene hydroxylase 1) exists in the three allelic forms, viz., 3’TE allele 1 (termed favorable allele, for it favors higher β-carotene accumulation in kernels), 3’TE allele 2 and 3’TE allele 3 (both termed unfavorable alleles, for they do not favor β-carotene accumulation). Here, we aimed to identify maize lines with favorable allele. First, 3’TE polymorphism assay in 210 inbreds revealed that only “UMI 176” had the favorable allele while the rest had the unfavorable alleles, confirming the previous finding that favorable allele is rare in frequency. Second, β-carotene content analysis in 24 inbreds revealed that it varied from 4.5 to 7.92 (μg/g), 0.23 to 2, and 0.42 to 4.22 for lines with allele 1, 2, and 3 respectively, corroborating the previous findings that the presence of favorable allele correlates with higher β-carotene content. In summary, UMI 176 has the favorable allele and had the highest amount of β-carotene content (7.92 μg/g), indicating that it is a promising donor line that can be utilized in β-carotene biofortification breeding.     

SUPERCRITICAL AND CATALYTIC FLUID EXTRACTIONS OF TEA WASTES

Air dried and ground tea waste was subjected to supercritical and catalytic fluid extraction by using water or acetone as solvent at different temperatures. The most important reactions variables were temperature and ratio of catalyst to the solid sample. The yields of the catalytic fluid reaction have been increased from 70.3 % to 92.4 % as the temperature increased from 230 °C to 340 °C by using water as solvent. The yield of extract was obtained from non catalytic supercritical water extraction was about 50.0 % at380°C.