Zinc doped ferrite magnetic resonance imaging contrast agent for atherosclerosis

 This project focuses on the development of zinc doped ferrite nanoparticle based MRI contrast agents with enhanced contrast and site-specific targeting for atherosclerosis diagnosis. The engineered nanocomplexes developed were validated through MRI scans using rat models with potential for multimodal imaging and effective therapy.

Youth Depression Alleviation-Augmentation with an anti-inflammatory agent (YoDA-A): protocol and rationale for a placebo-controlled randomized trial of rosuvastatin and aspirin

AIM: There is growing support for the role of inflammation and oxidative stress in the pathophysiology of major depressive disorder (MDD). This has led to the development of novel strategies targeting inflammation in the treatment of depression. Rosuvastatin and aspirin have well-documented, anti-inflammatory and antioxidant properties. The aim of the Youth Depression Alleviation: Augmentation with an anti-inflammatory agent (YoDA-A) study is to determine whether individuals receiving adjunctive anti-inflammatory agents, aspirin and rosuvastatin experience a reduction in the severity of MDD compared with individuals receiving placebo. METHODS: YoDA-A is a 12-week triple-blind, randomized controlled trial funded by the National Health and Medical Research Council, Australia. Participants aged 15-25, with moderate-to-severe MDD, are allocated to receive either 10 mg/day rosuvastatin, 100 mg/day aspirin, or placebo, in addition to treatment as usual. Participants are assessed at baseline and at weeks 4, 8, 12 and 26. The primary outcome is change in the Montgomery-Åsberg Depression Rating Scale (MADRS) from baseline to week 12. RESULTS: The study is planned to be completed in 2017. At date of publication, 85 participants have been recruited. CONCLUSION: Timely and targeted intervention for youth MDD is crucial. Given the paucity of new agents to treat youth MDD, adjunctive trials are not only pragmatic and 'real-world', but additionally aim to target shortfalls in conventional medications. This study has the potential to first provide two new adjunctive treatment options for youth MDD; aspirin and rosuvastatin. Second, this study will serve as proof of principle of the role of inflammation in MDD.

A decentralised multi-agent approach to enhance the stability of smart microgrids with renewable energy

This paper presents the impact of large penetration of wind power on the transient stability through a dynamic evaluation of the critical clearing times (CCTs) by using intelligent agent-based approach. A decentralised multi-agent-based framework is developed, where agents represent a number of physical device models to form a complex infrastructure for computation and communication. They enable the dynamic flow of information and energy for the interaction between the physical processes and their activities. These agents dynamically adapt online measurements and use the CCT information for relay coordination to improve the transient stability of power systems. Simulations are carried out on a smart microgrid system for faults at increasing wind power penetration levels and the improvement in transient stability using the proposed agent-based framework is demonstrated.

Distributed agent-based control scheme for single-phase parallel inverters in microgrids with photovoltaic systems

In this paper, an agent-based distributed control scheme is presented to control single-phase parallel inverters in solar photovoltaic (PV) systems connected to microgrids. A communication assisted multi-agent framework is developed within microgrids where agents perform their tasks in a distributed manner with an aim of stabilizing load voltage and current under normal and faulted conditions through the asymptotic tracking of the reference current signal. The distributed agent-based control scheme requires information from the neighboring agents through communication network to decide control actions. The proposed control scheme utilizes Ziegler-Nichols (Z-N) tuning approach to design proportional integral (PI) controllers for controlling inverters within the multi-agent system (MAS). A microgrid with parallel inverter-connected solar PV systems is considered for simulations under normal and faulted conditions where results show the excellency of the proposed agent-based scheme in comparison to the conventional scheme without MAS.

Adding a new anticoagulant or antiplatelet agent for patient receiving aspirin after an acute coronary syndrome? - Results from a pairwise and network meta-analysis of randomized-controlled trials

 Objectives: To synthesize the efficacy and safety outcomes from randomized-controlled trials (RCTs) regarding new oral anticoagulant, protease-activated receptor-1 (PAR-1) antagonist, and warfarin adjunctive to aspirin for patients after acute coronary syndrome (ACS) via pair-wise and network meta-analyses.
Methods: A comprehensive literature search was performed in Embase, Medline, Cochrane Library Web of Knowledge, and Scopus. The pair-wise meta-analysis was undertaken respectively to each agent/treatment category via Revmen 5.1. In order to estimate the relative efficacy of each agent/treatment category whilst preserving the randomized comparisons within each trial, a Bayesian network meta-analysis was conducted in WinBUGS using both fixed- and random-effects model. Covariate analysis was performed to explore the effects of length of follow-up and age of subject on the final results.
Results: In total, 23 RCTs were included in the meta-analysis. As shown by the results (OR,95%CI) for the pair-wise meta-analysis, new oral anticoagulants (0.85, [0.78, 0.93] and 3.04, [2.21, 4.19]), PAR-1 antagonists (0.80, [0.52, 1.22] and 1.55, [1.25, 1.93]) and warfarin (0.87, [0.74, 1.02] and 1.77, [1.46, 2.14]) might be able to provide better outcome in the incidences of major adverse events (MAE) but with higher bleeding risk comparing to aspirin treatment alone. Based on the model fit assessment, the random-effects model was adopted. The network meta-analysis (treatment effect comparing to aspirin lone) identified ximelagatran (-0.3044, [-0.8601, 0.2502]), dabigatran (-0.2144, [-0.8666, 0.4525]), rivoroxaban (-0.2179, [-0.5986, 0.1628]) and vorapaxar (-0.2272, [-0.81, 0.1664]) produced better improvements in MAE incidences whereas vorapaxar (0.3764, [-0.4444, 1.124]), warfarin (0.663, [0.3375, 1.037]), ximelagatran (0.7509, [-0.4164, 2.002]) and apixaban (0.8594, [-0.0049, 1.7]) produced less major bleeding events. The indirect comparisons among drug category (difference in incidence comparing to aspirin lone) showed new oral anticoagulants (-0.1974, [-0.284, -0.111]) and PAR-1 antagonists (-0.1239, [-0.215, -0.033]) to besuperior to warfarin (-0.1004, [-0.166, -0.035]) in the occurrences of MAE whereas PAR-1 antagonists (0.4292, [0.2123, 0.6476]) afforded better outcomes in major bleeding events against warfarin (0.5742, [0.3889, 0.7619]) and new oral anticoagulants (1.169, [0.8667, 1.485]).
Conclusion: Based on the study results, we cannot recommend the routine administration of new oral anticoagulant as add-on treatment for patients after ACS. However, for ACS patients comorbid with atrial fibrillation, new oral anticoagulant might be superior to warfarin in both efficacy and safety outcomes.

ANGEL: agent-based scheduling for real-time tasks in virtualized clouds

The success of cloud computing makes an increasing number of real-time applications such as signal processing and weather forecasting run in the cloud. Meanwhile, scheduling for real-time tasks is playing an essential role for a cloud provider to maintain its quality of service and enhance the system's performance. In this paper, we devise a novel agent-based scheduling mechanism in cloud computing environment to allocate real-time tasks and dynamically provision resources. In contrast to traditional contract net protocols, we employ a bidirectional announcement-bidding mechanism and the collaborative process consists of three phases, i.e., basic matching phase, forward announcement-bidding phase and backward announcement-bidding phase. Moreover, the elasticity is sufficiently considered while scheduling by dynamically adding virtual machines to improve schedulability. Furthermore, we design calculation rules of the bidding values in both forward and backward announcement-bidding phases and two heuristics for selecting contractors. On the basis of the bidirectional announcement-bidding mechanism, we propose an agent-based dynamic scheduling algorithm named ANGEL for real-time, independent and aperiodic tasks in clouds. Extensive experiments are conducted on CloudSim platform by injecting random synthetic workloads and the workloads from the last version of the Google cloud tracelogs to evaluate the performance of our ANGEL. The experimental results indicate that ANGEL can efficiently solve the real-time task scheduling problem in virtualized clouds.

Duet: Improvising spatial dialogues with an artificially intelligent agent

This paper presents an experimental framework for a virtual reality artwork, Duet, that employs a combination of live, full body motion capture and Oculus Rift HMD to construct an experience through which a human User can spatially interact with an artificially intelligent Agent. The project explores conceptual notions of embodied knowledge transfer, shared poetics of movement and distortions of the body schema. Within this context, both the User and the Agent become performers, constructing an intimate and spontaneously generated proximal space. The project generates a visualization of the relationship between the User and the Agent without the context of a fixed VR landscape or architecture. The Agent's ability to retain and accumulate movement knowledge in a way that mimics human learning transforms an interactive experience into a collaborative one. The virtual representation of both performers is distorted and amplified in a dynamic manner, enhancing the potential for creative dialogue between the Agent and the User.

Distributed multi-agent scheme to improve dynamic voltage stability of distribution networks

In this paper, a distributed multi-agent scheme is presented for reactive power management with renewable energy sources (RESs). The multi-agent system (MAS) framework is developed for distribution systems to improve the stability which is mostly dominated by voltage and the agents in this framework coordinate among themselves using online information and energy flow. In this paper, the agents basically perform two tasks- reactive power estimation and necessary control actions. The topology of distribution network is used to estimate the required reactive power for maintaining voltage stability where distributed static synchronous compensators (DSTATCOMs) are used to supply this reactive power. The DSTATCOM is controlled by using a linear quadratic regulator (LQR) controller within the agent framework. The proposed scheme is further compared with the conventional approach to validate the simulation results.