In this work, p-n junctions were fabricated from highly-pure nanostructured NiO and TiO2 thin films deposited on glass substrates by dc reactive magnetron sputtering technique. The structural characterization showed that the prepared multilayer NiO/TiO2 thin film structures were highly pure as no traces for other compounds than NiO and TiO2 were observed. It was found that the absorption of NiO-on-TiO2 structure is higher than that of the TiO2-on-NiO. Also, the NiO/TiO2 heterojunctions exhibit typical electrical characteristics, higher ideality factor and better spectral responsivity when compared to those fabricated from the same materials by the same technique and with larger particle size and lower structural purity.

            Eight patients (3 male and 5 female) were treated in this study by Endovenous Laser Ablation (EVLA); Mathematical models are proposed to estimate the applied laser power and to assess the recovery period. The estimations of the applied laser power and recovery period in these models will be depended mainly on the diameter of the incompetent vein.  In addition, Excel Program was utilized to find the proposed models.  A 1470 nm diode laser up to 15W continuous power (CW) was used in the treatment of venous ulcers by EVLA procedure. Following up by duplex ultrasound was started in the 1st week after the first session until the vein is completely closed. The present study concluded that the relationship both between

Industrial machining workshops generate substantial quantities of aluminum wire offcuts and filings that cannot be re-entered into bulk metal recycling circuits, posing both a resource management challenge and a potential environmental burden. This study demonstrates a closed-loop valorization route in which this low-grade aluminum waste is converted into nanostructured aluminum oxide (Al2O3) nanoparticles (NPs) by two scalable synthesis pathways (i) chemo-thermal calcination of precipitated Al(OH)₃ at 1000 °C and 1200 °C for 1 and 4 h, and (ii) direct chemical precipitation via AlCl3/Na2CO3 reaction, and then deployed as a functional additive in water-based drilling fluids (WBDFs) used by the oil and gas industry. Comprehensive chara

The aim of the research is to apply fibrewise multi-emisssions of the paramount separation axioms of normally topology namely fibrewise multi-T0. spaces, fibrewise multi-T1 spaces, fibrewise multi-R0 spaces, fibrewise multi-Hausdorff spaces, fibrewise multi-functionally Hausdorff spaces, fibrewise multi-regular spaces, fibrewise multi-completely regular spaces, fibrewise multi-normal spaces and fibrewise multi-functionally normal spaces. Also we give many score regarding it.

We define and study new ideas of fibrewise topological space on D namely fibrewise multi-topological space on D. We also submit the relevance of fibrewise closed and open topological space on D. Also fibrewise multi-locally sliceable and fibrewise multi-locally section able multi-topological space on D. Furthermore, we propose and prove a number of statements about these ideas.

Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an

Cancer is in general not a result of an abnormality of a single gene but a consequence of changes in many genes, it is therefore of great importance to understand the roles of different oncogenic and tumor suppressor pathways in tumorigenesis. In recent years, there have been many computational models developed to study the genetic alterations of different pathways in the evolutionary process of cancer. However, most of the methods are knowledge-based enrichment analyses and inflexible to analyze user-defined pathways or gene sets. In this paper, we develop a nonparametric and data-driven approach to testing for the dynamic changes of pathways over the cancer progression. Our method is based on an expansion and refinement of the pathway bei