Perhaps no other drug in modern medicine rivals the dramatic revitalization of thalidomide. Originally marketed as a sedative, thalidomide gained immense popularity worldwide among pregnant women because of its effective anti-emetic properties in morning sickness. Mounting evidence of human teratogenicity marked a dramatic fall from grace and led to widespread social, legal and economic ramifications. Despite its tragic past thalidomide emerged several decades later as a novel and highly effective agent in the treatment of various inflammatory and malignant diseases. In 2006 thalidomide completed its remarkable renaissance becoming the first new agent in over a decade to gain approval for the treatment of plasma cell myeloma. The catastrophic collapse yet subsequent revival of thalidomide provides important lessons in drug development. Never entirely abandoned by the medical community, thalidomide resurfaced as an important drug once the mechanisms of action were further studied and better understood. Ongoing research and development of related drugs such as lenalidomide now represent a class of irreplaceable drugs in hematological malignancies. Further, the tragedies associated with this agent stimulated the legislation which revamped the FDA regulatory process, expanded patient informed consent procedures and mandated more transparency from drug manufacturers. Finally, we review recent clinical trials summarizing selected medical indications for thalidomide with an emphasis on hematologic malignancies. Herein, we provide a historic perspective regarding the up-and-down development of thalidomide. Using PubMed databases we conducted searches using thalidomide and associated keywords highlighting pharmacology, mechanisms of action, and clinical uses.

Around the world, countries are integrating photovoltaic generating systems to the grid to support climate change initiatives. However, solar power generation is highly uncertain due to variations in solar irradiance level during different hours of the day. Inaccurate modelling of this variability can lead to non-optimal dispatch of system resources. Therefore, accurate characterization of solar irradiance patterns is essential for effective management of renewable energy resources in an electrical power grid. In this paper, the Weibull distribution based probabilistic model is presented for characterization of solar irradiance patterns. Firstly, Weibull distribution is utilized to model inter-temporal variations associated with reference solar irradiance data through moving window averaging technique, and then the proposed model is used for irradiance pattern generation. To achieve continuity of discrete Weibull distribution parameters calculated at different steps of moving window, Generalized Regression Neural Network (GRNN) is employed. Goodness of Fit (GOF) techniques are used to calculate the error between mean and standard deviation of generated and reference patterns. The comparison of GOF results with the literature shows that the proposed model has improved performance. The presented model can be used for power system planning studies where the uncertainty of different resources such as generation, load, network, etc., needs to be considered for their better management.

Conventional fossil-fuel energy resources are being drastically depleted; thus, the current shift towards renewable energy (RE) resources has become imperative. However, there are many impediments to the adoption of renewable power generation. These impediments can be overcome by enacting policies to encourage the acceptance of sustainable energy resources. For instance, the net-metering policy can provide the necessary incentives to promote the development of local distributed energy sources, primarily solar photovoltaic and wind generators. While there has been significant advancement and development in netmetering in Asia with the increased penetration of RE, at present there is a lack of systematic review in this area. This paper aims to present an in-depth review on net-metering advances and challenges, current RE shares, and future RE targets in the Asian region. Additionally, a case study is performed and an economic analysis of net-metering regulations in an Asian country is carried out. In this study, the monetary benefits of net-metering policies for residential consumers are proved. It is envisaged that the information gathered in this paper will be a valuable one-stop source of information for Asian researchers working on this topic. INDEX TERMS Renewable energy shares, renewable energy targets, net-metering policy, net-metering in Asia.

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Net metering is used to incentivize the distributed generation owners. It is introduced in Pakistan with the aim to promote the building integrated local generation. Presently, it is hard to find any study on the economic incentive indicators of the net metering policy for residential customers in Pakistan. This paper presents the economic evaluation of net metering benefits to the individual residential consumers in the presence of Building Integrated PV (BIPV) system under current net metering regulations in Pakistan. The energy demand of the individual apartments and the common area services inside the building is calculated by means of daily energy usage of the residents for a typical day. The aggregate demand of the residential building, comprising of 100 residential units and common area services, is calculated. The estimation of power profiles of the PV generation system is carried out with the help of PVGIS. At the end, the economic analysis of the proposed net metering scheme is presented. The net metering policy is found to be feasible up-to 50 kWp PV capacity when it is applied on the common area services only and the billing is carried out individually. When it is implemented on the aggregate energy demand of the entire residential building, the annual savings are observed for installed PV capacity above 80 kWp

A dense deployment of on-grid small cell base stations (SBSs) in a heterogeneous cellular network (HCN) results in large power consumption which can be reduced by utilizing harvested energy from scavenge sources. Recently, a new layout for HCN with energy harvesting-SBSs (EH-SBSs) has been proposed to reduce inter-cell interference and power consumption; and increase system energy efficiency. In this paper, an energy efficient joint user association and BS on-off scheme for an HCN having diverse energy source(s) is proposed, which aims at utilizing the harvested energy efficiently in order to reduce the on-grid power consumption. The scheme operates in two phases. First, it decides which BS should be in off, sleep or active mode and iteratively updates its transmit power based on energy arrival and consumption, to minimize interference and on-grid power consumption. Secondly, for further reduction in on-grid power consumption, the user discovers and associates itself with the nearest available EH-SBS. The system energy consumption for the proposed scheme is numerically evaluated using Monte Carlo simulations. Simulation results reveal that the proposed scheme shows significantly better results as compared to other schemes in the literature in terms of grid power consumption and energy efficiency.

The uncertainty associated with renewable energy sources, particularly wind, makes them an unpredictable means of power generation. To guarantee continuous and reliable power supply, wind speed variability modeling is considered a vital step for meeting the planning and operational challenges of an electric power grid. In this paper, a novel probabilistic generation model is developed to estimate and generate time-coupled wind speed patterns. A 1 h time step is considered to construct the time-coupled probabilistic wind speed patterns based on a two-parameter Weibull distribution. These parameters of the Weibull distribution are found by considering the variations of reference wind speed patterns at two successive time steps. The probabilistic model is then used to create a number of aggregate wind speed generation scenarios. The validity of our proposed approach is evaluated with the help of goodness-of-fit test indicators such as average mean absolute percentage error and the Kolmogorov–Smirnov test error. The results of goodness of fit tests and comparison of output power determined through the proposed model with the existing model in the literature suggest that the proposed model is appropriate for wind speed uncertainty modeling and can be applied in power system planning studies.

In this paper we describe JClarens; a Java based implementation of the Clarens remote data server. JClarens provides web services for an interactive analysis environment to dynamically access and analyze the tremendous amount of data scattered across various locations. Additionally this research is aimed to develop a service oriented Grid Enabled Portal (GEP) that provides interface and access to several Grid services to give a homogeneous and optimized view of the distributed and heterogeneous environment. Other than showing platform independent behavior provided by Java, the use of XML-RPC based Web Services enabled JClarens to be a language neutral server and demonstrated interoperability with its Python variant. Extreme care has been taken in the usage and manipulation of various Java libraries to cater the needs of high performance computing. The overall exercise has yielded in a prototype with strong emphasis on security and virtual organization management (VOM). This shall provide a common platform to support development of larger, more flexible framework with future aims to integrate it with a loosely coupled, decentralized, and autonomous framework for Grid enabled Analysis Environment (GAE).