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Compared with traditional battery and super capacitor materials, nanomaterials can significantly improve ion transport and electron conductivity. There are many features to the achievement of nanomaterials in energy storage applications. Nanomaterials development and their related processes can improve the performance based on the energy storage existing system. Current study discuss fruitful approaches and outline a roadmap for using green nanomaterials for advancement in energy storage devise. This review includes the information of the latest research being carried out on green nanomaterials and its sustainability. It also provides an overview of the latest state and proposes the future direction of the use of green nanomaterials for numerous possible applications, which are mainly used in the fields of biotechnology, agriculture, and biomedicine.

Objectives: To determine the frequency of diastolic dysfunction in patients presenting with type II Diabetes Mellitus. Study Design: Cross sectional study. Setting: Sheikh Zayed Hospital, Rahim Yar Khan. Period: From 01-01-2017 to 30-06-2017. Material & Methods: In this study the cases were selected via non probability consecutive sampling of both male and female gender with age more than 40 years having type II DM of at least more than 2 years were included. The cases suffering from type I DM, gestational DM and those with HTN, end stage kidney and liver failure were excluded. Trans thoracic echocardiography was done to label diastolic dysfunction and was labelled as yes when the E/A ratio was

The aim of this study involves establishing a three-dimensional computational fluid dynamic (3D-CFD) model of solar flat plate collector (SFPC) in order to investigate the effect of operating and geometric parameters on thermal efficiency. In this research work, commercial CFD code ANSYS FLUENT®14.0 version was used for the development of a model of solar plate collector. The single circular tube geometry was created using ANSYS DesignModeler®14.0. The general continuity equation along with Navied–Stokes equations was solved for tracking motion of the working fluid. The general k–e turbulence modeling approach was used for solving the turbulence in the flow. Solar ray tracing was activated for calculating solar load in the model. The latitude and longitude of the Hyderabad region were inserted in the solar ray-tracing model for calculating solar intensity as per local conditions. Two fluids i.e., water and air were circulated with different flow rates in the developed model of SFPC. It was observed that water gave higher efficiency due to high density and thermal conductivity. The simulation results gathered revealed that the temperature of water and air was raised by almost 79 °C and 73 °C respectively.

Several investigations on major occupational accidents are demonstrating interest in role of organizational factors. Investigations and evidences manifest that “the root causes involved more than technical or human failures” [1] . Thus, focusing on organizational factors is an important issue in safety as a means of mitigating accident in the workplace. First step for assessing the influence of organizational factors is to identify the relevant organization factors. Out of 22 factors identified from literature review, seven important factors were finalized for Thailand construction industry: communication, culture, management commitment, leadership, organization learning, empowerment, and reward system. At final phase, Bayesian Belief Network was used for handling the complex causality and providing the strategies to enhance the safety work behaviors. According to first alternative, 73.3% of safety work behavior was reached by manipulating management commitment, participation, learning and leadership nodes simultaneously. The second alternative accomplished about 74.6% of safety work behavior when the leadership, management commitment, participation and intention node were assigned to favorable state. For the third alternative, 77.7% of safe work behavior could be obtained by controlling leadership, management commitment, participation and perceived behavioral control node.

Organizational factors and human factors are intimately related and intermingled with each other. Therefore, development of the implications for improving work safety behaviors is difficult due to the complexities of multiple causal relations of those factors within construction safety scenarios. With an aim towards identifying the particular implications for enhancing the desired behaviors or mitigating unfavorable behaviors, Bayesian network was therefore selected as an analytical technique for providing insight into the influence of the relevant contributories by investigating variations in the output of networks. Bayesian Belief Networks have been extensively applied in research because of their capability to capture sophisticated inferences. In addition, researchers are enabled to deliberately investigate the expected consequences of uncertainty prior to establishing an effective intervention. As a result, the present alternatives highlight the useful implications that might lead to the highest probability of safe work behavior. Based on this Bayesian network, an improvement in safe work behavior can be obtained by controlling leadership, management commitment, participation, and the perceived behavioral control node. Accordingly, it is increasingly being acknowledged that management must demonstrate substantive and visible commitment to occupational safety. In addition, managers at all levels must play an important role in establishing a supportive and participative atmosphere to encourage subordinates to work in a safer way. This application and the findings from the empirical evidence of the Bayesian Belief Network can explore the influence of organizational factors and their impact on safe work behavior through manipulating a combination of organizational factors.