The SIMIAN architecture-an object-orientated framework for integrated power system modelling, analysis and control

This paper details the work conducted by the Brunel Institute of Power Systems, UK, into an object orientated framework for power systems modelling, analysis and control. Based around a central OODBMS (object orientated database management system), the architecture provides a framework for the construction of analysis and control applications and the sharing of calculated or real-time data between the applications. Although the paper details the architecture only in so far as its applicability to two applications, the framework is designed such that further applications, either client output (such as control applications) or input(such as SCADA systems) may easily be added to the basic structure. To illustrate the architecture, a load flow simulation application is presented, along with the strategy for incorporating other applications. The mechanism by which these `applications' interact with the OODBMS and core structure of the architecture is illustrate

Preclinical Assessment of HIV Vaccines and Microbicides by Repeated Low-Dose Virus Challenges

BACKGROUND: Trials in macaque models play an essential role in the evaluation of biomedical interventions that aim to prevent HIV infection, such as vaccines, microbicides, and systemic chemoprophylaxis. These trials are usually conducted with very high virus challenge doses that result in infection with certainty. However, these high challenge doses do not realistically reflect the low probability of HIV transmission in humans, and thus may rule out preventive interventions that could protect against “real life” exposures. The belief that experiments involving realistically low challenge doses require large numbers of animals has so far prevented the development of alternatives to using high challenge doses. METHODS AND FINDINGS: Using statistical power analysis, we investigate how many animals would be needed to conduct preclinical trials using low virus challenge doses. We show that experimental designs in which animals are repeatedly challenged with low doses do not require unfeasibly large numbers of animals to assess vaccine or microbicide success. CONCLUSION: Preclinical trials using repeated low-dose challenges represent a promising alternative approach to identify potential preventive interventions

Seeds Buffering for Information Spreading Processes

Seeding strategies for influence maximization in social networks have been studied for more than a decade. They have mainly relied on the activation of all resources (seeds) simultaneously in the beginning; yet, it has been shown that sequential seeding strategies are commonly better. This research focuses on studying sequential seeding with buffering, which is an extension to basic sequential seeding concept. The proposed method avoids choosing nodes that will be activated through the natural diffusion process, which is leading to better use of the budget for activating seed nodes in the social influence process. This approach was compared with sequential seeding without buffering and single stage seeding. The results on both real and artificial social networks confirm that the buffer-based consecutive seeding is a good trade-off between the final coverage and the time to reach it. It performs significantly better than its rivals for a fixed budget. The gain is obtained by dynamic rankings and the ability to detect network areas with nodes that are not yet activated and have high potential of activating their neighbours.Comment: Jankowski, J., Br\'odka, P., Michalski, R., & Kazienko, P. (2017, September). Seeds Buffering for Information Spreading Processes. In International Conference on Social Informatics (pp. 628-641). Springe

A Highly Intensified ART Regimen Induces Long-Term Viral Suppression and Restriction of the Viral Reservoir in a Simian AIDS Model

Stably suppressed viremia during ART is essential for establishing reliable simian models for HIV/AIDS. We tested the efficacy of a multidrug ART (highly intensified ART) in a wide range of viremic conditions (103–107 viral RNA copies/mL) in SIVmac251-infected rhesus macaques, and its impact on the viral reservoir. Eleven macaques in the pre-AIDS stage of the disease were treated with a multidrug combination (highly intensified ART) consisting of two nucleosidic/nucleotidic reverse transcriptase inhibitors (emtricitabine and tenofovir), an integrase inhibitor (raltegravir), a protease inhibitor (ritonavir-boosted darunavir) and the CCR5 blocker maraviroc. All animals stably displayed viral loads below the limit of detection of the assay (i.e. <40 RNA copies/mL) after starting highly intensified ART. By increasing the sensitivity of the assay to 3 RNA copies/mL, viral load was still below the limit of detection in all subjects tested. Importantly, viral DNA resulted below the assay detection limit (<2 copies of DNA/5*105 cells) in PBMCs and rectal biopsies of all animals at the end of the follow-up, and in lymph node biopsies from the majority of the study subjects. Moreover, highly intensified ART decreased central/transitional memory, effector memory and activated (HLA-DR+) effector memory CD4+ T-cells in vivo, in line with the role of these subsets as the main cell subpopulations harbouring the virus. Finally, treatment with highly intensified ART at viral load rebound following suspension of a previous anti-reservoir therapy eventually improved the spontaneous containment of viral load following suspension of the second therapeutic cycle, thus leading to a persistent suppression of viremia in the absence of ART. In conclusion, we show, for the first time, complete suppression of viral load by highly intensified ART and a likely associated restriction of the viral reservoir in the macaque AIDS model, making it a useful platform for testing potential cures for AIDS

Energy Demand Response for High-Performance Computing Systems

The growing computational demand of scientific applications has greatly motivated the development of large-scale high-performance computing (HPC) systems in the past decade. To accommodate the increasing demand of applications, HPC systems have been going through dramatic architectural changes (e.g., introduction of many-core and multi-core systems, rapid growth of complex interconnection network for efficient communication between thousands of nodes), as well as significant increase in size (e.g., modern supercomputers consist of hundreds of thousands of nodes). With such changes in architecture and size, the energy consumption by these systems has increased significantly. With the advent of exascale supercomputers in the next few years, power consumption of the HPC systems will surely increase; some systems may even consume hundreds of megawatts of electricity. Demand response programs are designed to help the energy service providers to stabilize the power system by reducing the energy consumption of participating systems during the time periods of high demand power usage or temporary shortage in power supply. This dissertation focuses on developing energy-efficient demand-response models and algorithms to enable HPC system\u27s demand response participation. In the first part, we present interconnection network models for performance prediction of large-scale HPC applications. They are based on interconnected topologies widely used in HPC systems: dragonfly, torus, and fat-tree. Our interconnect models are fully integrated with an implementation of message-passing interface (MPI) that can mimic most of its functions with packet-level accuracy. Extensive experiments show that our integrated models provide good accuracy for predicting the network behavior, while at the same time allowing for good parallel scaling performance. In the second part, we present an energy-efficient demand-response model to reduce HPC systems\u27 energy consumption during demand response periods. We propose HPC job scheduling and resource provisioning schemes to enable HPC system\u27s emergency demand response participation. In the final part, we propose an economic demand-response model to allow both HPC operator and HPC users to jointly reduce HPC system\u27s energy cost. Our proposed model allows the participation of HPC systems in economic demand-response programs through a contract-based rewarding scheme that can incentivize HPC users to participate in demand response

Cellulose acetate phthalate, a common pharmaceutical excipient, inactivates HIV-1 and blocks the coreceptor binding site on the virus envelope glycoprotein gp120

BACKGROUND: Cellulose acetate phthalate (CAP), a pharmaceutical excipient used for enteric film coating of capsules and tablets, was shown to inhibit infection by the human immunodeficiency virus type 1 (HIV-1) and several herpesviruses. CAP formulations inactivated HIV-1, herpesvirus types 1 (HSV-1) and 2 (HSV-2) and the major nonviral sexually transmitted disease (STD) pathogens and were effective in animal models for vaginal infection by HSV-2 and simian immunodeficiency virus. METHODS: Enzyme-linked immunoassays and flow cytometry were used to demonstrate CAP binding to HIV-1 and to define the binding site on the virus envelope. RESULTS: 1) CAP binds to HIV-1 virus particles and to the envelope glycoprotein gp120; 2) this leads to blockade of the gp120 V3 loop and other gp120 sites resulting in diminished reactivity with HIV-1 coreceptors CXCR4 and CCR5; 3) CAP binding to HIV-1 virions impairs their infectivity; 4) these findings apply to both HIV-1 IIIB, an X4 virus, and HIV-1 BaL, an R5 virus. CONCLUSIONS: These results provide support for consideration of CAP as a topical microbicide of choice for prevention of STDs, including HIV-1 infection