Characteristic of silicon doped diamond like carbon thin films on surface properties and human serum albumin adsorption

Diamond-like carbon (DLC) coatings are useful for creating biocompatible surfaces for medical implants. DLC and silicon doped DLC have been synthesised using plasma enhanced chemical vapour deposition (PECVD). The effects of surface morphology on the interaction of human serum albumin (HSA) with doped and undoped DLC films have been investigated using a range of surface analysis techniques using Raman spectroscopy and atomic force microscopy (AFM). Raman spectra of doped DLC show that silicon doped DLC reduces the growth range of the ID/IG ratio, with a significant red-shift of the G peak position. Following exposure to protein, for undoped DLC the peaks at 1664 cm−1 and around 1241 cm−1 can be attributed to amide I and III, respectively, with an increase in the surface morphology of the surfaces giving some indication of the protein structure on the surfaces. Results indicate that HSA exhibit the majority of β-sheet during the adsorption on the surfaces. The results showed that the silicon incorporation DLC tends to increase of surface roughness and the adsorbed level of HSA is higher with higher levels of silicon doping of the DLC. Therefore, doping DLC may provide a method of controlling the adsorption of protein

A Comparison of Strain Deformation Mechanism of Al, Mo, MgO & CaO in Harper-Dorn Creep

Harper-Dorn creep Mechanism is studied for Al, Mo, MgO and CaO. The normalized grain size for each material is compared by using Langdon-Mohamed Type deformation mechanism maps [7]. Al is an F.C.C. metal, Mo is a B.C.C. metal, whereas CaO and MgO are non-metallic oxides, they all have different physical properties and hence this case study has a wide range of spectru

A Case Study of Maintenance Management System for Bread Baking Plant

Maintenance Management System is the back bone of any plant. It helps to arrange Preventive Maintenance, predict for Breakdown Maintenance and hence evaluate the reliability of Maintenance. Bread Plant is selected for the case study but can be modified for any other technology. Important maintenance issues are addressed in this paper. Maintenance Management System will not only reduce maintenance cost but will minimize emergency repairs and downtime, resulting in an increase in overall profitability

Thermoresponsive Switchable Solvents for Enhanced, Simultaneous Microalgae Oil Extraction Reaction for Biodiesel Production

In this study, a thermo-responsive switchable solvent (TSS), with a tunable hydrophobicity by simply changing the temperature (between 25 to 45oC) was used for simultaneous lipids extraction from wet microalgae and biodiesel production. By manipulating the hydrophobicity of the solvent, the cell wall disruption, lipid extraction and transesterification, and product separation steps were all carried out in a single pot, while eliminating the need for the energy intensive and time-consuming drying step. To overcome the problems currently encountered by using conventional alkaline catalysts in the transesterification of lipids, immobilized enzyme has been used. The proposed TSS consisted of an ionic liquid (N,N diethyl-Nmethylammonium methane sulfonate), a polymer poly (propylene) glycol (PPG) and water. The effectiveness of the proposed process was compared to that using conventional organic solvent, n-hexane, and other CO₂ triggered amine based switchable solvents, namely 1,8-diazabicyclo-[5.4.0]-undec-7-ene (DBU)-1-hexanol and DBU-Mono-ethanolamine (MEA). At the same conditions and solvent switching program, using immobilized lipase as a biocatalyst, the biodiesel yields were 45.5 ± 0.38 %, 37.8 ± 1.03 % and 5.9 ± 1.50 %, using TSS, DBU-hexanol, and DBU-MEA respectively. Using n-hexane resulted in insignificant yield of 3.1 ± 0.43 %. Furthermore, a reusability of the TSS-immobilized lipase system was investigated, and it was shown that the reusability biodiesel yield dropped from 50 ± 1.46 % in the first cycle to 20.4 ± 0.60 % in the fourth. A parametric study was performed, using response surface methodology (RSM) to evaluate the effects of cell disruption and extraction/reaction durations in the range of 0-3 h, and methanol amount used in the range of 0.02 – 0.2 mL on the biodiesel production yield from 1 g of wet biomass. The results were used to develop a statistical model to predict the biodiesel yield under different conditions and to optimize the process. The optimum conditions were estimated to 0.5 hr, 3 hr and 0.15 mL for the cell disruption time, extraction-reaction time and methanol amount respectively, at which the yield was predicted to be 78.65 %. The experiment was repeated at the optimum conditions, and the actual yield was found to be 75.11 ± 1.03 %. The successful use of TSS for simultaneous extraction-reaction and product separation from wet biomass has a significant effect on the simplification of microalgae to biodiesel process. By simply changing the temperature, the hydrophobicity of TSS can be manipulated, rendering the overall process easier, as compared to the CO₂ triggered Switchable Solvents. A process similar to the one presented in this work has never been reported before in literature

A study on teacher education in India: Physical education, some policy issues and challenges

This paper deals with some policies, problems and planned suggestions for teacher education and role of teacher in physical education. The goal of this Special Issue was to raise awareness of physical education teacher education (PETE) by expanding the knowledge base and geographical, theoretical, and innovative writing about PETE, physical education teacher educators, and those who shape (policymakers/higher education leadership) and those who experience PETE. The present research paper is based on explorative types of study. This research study is focused on teachers and physical education in India. This present study is basically case types of study, the researcher used secondary sources. The main implication of the study was to the Govt when any policy is introduced, it is the responsibility to checked in ground level, not only in papers

Hydrocarbon quantification using neural networks and deep learning based hyperspectral unmixing

Hydrocarbon (HC) spills are a global issue, which can seriously impact human life and the environment, therefore early identification and remedial measures taken at an early stage are important. Thus, current research efforts aim at remotely quantifying incipient quantities of HC mixed with soils. The increased spectral and spatial resolution of hyperspectral sensors has opened ground-breaking perspectives in many industries including remote inspection of large areas and the environment. The use of subpixel detection algorithms, and in particular the use of the mixture models, has been identified as a future advance that needs to be incorporated in remote sensing. However, there are some challenging tasks since the spectral signatures of the targets of interest may not be immediately available. Moreover, real time processing and analysis is required to support fast decision-making. Progressing in this direction, this thesis pioneers and researches novel methodologies for HC quantification capable of exceeding the limitations of existing systems in terms of reduced cost and processing time with improved accuracy. Therefore the goal of this research is to develop, implement and test different methods for improving HC detection and quantification using spectral unmixing and machine learning. An efficient hybrid switch method employing neural networks and hyperspectral is proposed and investigated. This robust method switches between state of the art hyperspectral unmixing linear and nonlinear models, respectively. This procedure is well suited for the quantification of small quantities of substances within a pixel with high accuracy as the most appropriate model is employed. Central to the proposed approach is a novel method for extracting parameters to characterise the non-linearity of the data. These parameters are fed into a feedforward neural network which decides in a pixel by pixel fashion which model is more suitable. The quantification process is fully automated by applying further classification techniques to the acquired hyperspectral images. A deep learning neural network model is designed for the quantification of HC quantities mixed with soils. A three-term backpropagation algorithm with dropout is proposed to avoid overfitting and reduce the computational complexity of the model. The above methods have been evaluated using classical repository datasets from the literature and a laboratory controlled dataset. For that, an experimental procedure has been designed to produce a labelled dataset. The data was obtained by mixing and homogenizing different soil types with HC substances, respectively and measuring the reflectance with a hyperspectral sensor. Findings from the research study reveal that the two proposed models have high performance, they are suitable for the detection and quantification of HC mixed with soils, and surpass existing methods. Improvements in sensitivity, accuracy, computational time are achieved. Thus, the proposed approaches can be used to detect HC spills at an early stage in order to mitigate significant pollution from the spill areas

Enhancing water use efficiency and grain yield of wheat by optimizing irrigation supply in arid and semi-arid regions of Pakistan

The lack of good irrigation practices and policy reforms in Pakistan triggers major threats to the water and food security of the country. In the future, irrigation will happen under the scarcity of water, as inadequate irrigation water becomes the requirement rather than the exception. The precise application of water with irrigation management is therefore needed. This research evaluated the wheat grain yield and water use efficiency (WUE) under limited irrigation practices in arid and semi-arid regions of Pakistan. DSSAT was used to simulate yield and assess alternative irrigation scheduling based on different levels of irrigation starting from the actual irrigation level up to 65% less irrigation. The findings demonstrated that different levels of irrigation had substantial effects on wheat grain yield and total water consumption. After comparing the different irrigation levels, the high amount of actual irrigation level in semi-arid sites decreased the WUE and wheat grain yield. However, the arid site (Site-1) showed the highest wheat grain yield 2394 kg ha(-1) and WUE 5.9 kg(-3) on actual irrigation (T-1), and with the reduction of water, wheat grain yield decreased continuously. The optimal irrigation level was attained on semiarid (site-2) with 50% (T-11) less water where the wheat grain yield and WUE were 1925 kg ha(-1) and 4.47 kg(-3) respectively. The best irrigation level was acquired with 40% less water (T-9) on semi-arid (site-3), where wheat grain yield and WUE were 1925 kg ha(-1) and 4.57 kg(-3), respectively. The results demonstrated that reducing the irrigation levels could promote the growth of wheat, resulting in an improved WUE. In crux, significant potential for further improving the efficiency of agricultural water usage in the region relies on effective soil moisture management and efficient use of water. (C) 2021 The Authors. Published by Elsevier B.V. on behalf of King Saud University

Stresses in an Isotropic Elastic Plate in the Form of Pascal's Limacon under Concentrated Forces

The problem of a thin elastic plate in the form of Pascal's limacon under concentrated forces at the extremeties of its axis has been solved by using complex variable technique. The solution has been obtained in a closed form. Stress components have been found out. In particular, the solution of an elastic circular plate and that of a plate in the form of a cardioid have been discussed. The variation of stress-intensity factor has been studied

Conflict in the Somali World & How It Is Resolved Through The Use Of Proverb as an Artistic Discourse Strategy

There are many conflicts in the world and especially in Somalia and there are attempts on how to solve them. From the point of view our modern world, solutions to the conflicts are usually sought or left with the United Nations to put in place a peace keeping force or a modern super power state to build coolation of governments to bring a regime change. The study adopts a complete departure and tests a different approach so as to contribute to whatever existing knowledge we have on how to solve conflicts. The study examines the proverb as an artistic discourse strategy in conflict resolution among the Somalis. It explores ways elders use proverbs to hammer points during peace negotiation meetings. To achieve its objectives, the study adopts a composite approach combing Ethno-poetics and Semiotic theories. The study is about the Somali Proverb. The research is based on Northern Region of Kenya where the ethnic Somalis concentrate, however, materials were also collected from inside Somalia, along the Kenyan-Somali border. Thirty two men and twelve women, who are considered opinion leaders, were interviewed. Forty six proverbs were collected through field research and analysed. The researcher actively participated in peace meetings where live performances of the proverb were recorded. The results of the study reveal that he proverb is used to resolve conflicts. In other words, the study tests the role and significance of the Somali proverb in conflict resolution meetings. The study recommends that there is need for a more thorough socio-literacy methodology applied to analyse the functions style and performance of the proverb which include both verbal and non-verbal. Key words: conflict, proverbs, resolution, function