Efficient Voltage/Current Spike Reduction by Active Gate Signaling

This paper presents an Active Gate Signaling scheme to reduce voltage/current spikes across insulated gate power switches in hard switching power electronic circuits. Voltage and/or current spikes may cause EMI noise. In addition, they increase voltage/current stress on the switch. Traditionally, a higher gate resistance is chosen to reduce voltage/current spikes. Since the switching loss will increase remarkably, an active gate voltage control scheme is developed to improve efficiency of hard switching circuits while the undesirable voltage and/or current spikes are minimized.

Benign Epilepsy with Centro-temporal Spikes: Spike Triggered fMRI Shows Somato-sensory Cortex Activity

Summary:  Objective: We performed spike triggered functional MRI (fMRI) in a 12 year old girl with Benign Epilepsy with Centro-temporal Spikes (BECTS) and left-sided spikes. Our aim was to demonstrate the cerebral origin of her interictal spikes. Methods: EEG was recorded within the 3 Tesla MRI. Whole brain fMRI images were acquired, beginning 2–3 seconds after spikes. Baseline fMRI images were acquired when there were no spikes for 20 seconds. Image sets were compared with the Student's t-test. Results: Ten spike and 20 baseline brain volumes were analysed. Focal activiation was seen in the inferior left sensorimotor cortex near the face area. The anterior cingulate was more active during baseline than spikes. Conclusions: Left sided epileptiform activity in this patient with BECTS is associated with fMRI activation in the left face region of the somatosensory cortex, which would be consistent with the facial sensorimotor involvement in BECT seizures. The presence of BOLD signal change in other regions raises the possibility that the scalp recorded field of this patient with BECTs may reflect electrical change in more than one brain region.

Demand-side response model to avoid spike of electricity price

The aim of this work is to develop a demand-side-response model, which assists electricity consumers exposed to the market price to independently and proactively manage air-conditioning peak electricity demand. The main contribution of this research is to show how consumers can optimize the energy cost caused by the air conditioning load considering to several cases e.g. normal price, spike price, and the probability of a price spike case. This model also investigated how air-conditioning applies a pre-cooling method when there is a substantial risk of a price spike. The results indicate the potential of the scheme to achieve financial benefits for consumers and target the best economic performance for electrical generation distribution and transmission. The model was tested with Queensland electricity market data from the Australian Energy Market Operator and Brisbane temperature data from the Bureau of Statistics regarding hot days from 2011 to 2012.

Defining expected cost for the air conditioning to avoid a price spike of electricity market under DSR model

This work presents a demand side response model (DSR) which assists small electricity consumers, through an aggregator, exposed to the market price to proactively mitigate price and peak impact on the electrical system. The proposed model allows consumers to manage air-conditioning when as a function of possible price spikes. The main contribution of this research is to demonstrate how consumers can minimise the total expected cost by optimising air-conditioning to account for occurrences of a price spike in the electricity market. This model investigates how pre-cooling method can be used to minimise energy costs when there is a substantial risk of an electricity price spike. The model was tested with Queensland electricity market data from the Australian Energy Market Operator and Brisbane temperature data from the Bureau of Statistics during hot days on weekdays in the period 2011 to 2012.

Identification of pre-spike network in patients with mesial temporal lobe epilepsy

Background: Seizures and interictal spikes in mesial temporal lobe epilepsy (MTLE) affect a network of brain regions rather than a single epileptic focus. Simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) studies have demonstrated a functional network in which hemodynamic changes are time-locked to spikes. However, whether this reflects the propagation of neuronal activity from a focus, or conversely the activation of a network linked to spike generation remains unknown. The functional connectivity (FC) changes prior to spikes may provide information about the connectivity changes that lead to the generation of spikes. We used EEG-fMRI to investigate FC changes immediately prior to the appearance of interictal spikes on EEG in patients with MTLE. Methods/principal findings: Fifteen patients with MTLE underwent continuous EEG-fMRI during rest. Spikes were identified on EEG and three 10 s epochs were defined relative to spike onset: spike (0–10 s), pre-spike (−10 to 0 s), and rest (−20 to −10 s, with no previous spikes in the preceding 45s). Significant spike-related activation in the hippocampus ipsilateral to the seizure focus was found compared to the pre-spike and rest epochs. The peak voxel within the hippocampus ipsilateral to the seizure focus was used as a seed region for FC analysis in the three conditions. A significant change in FC patterns was observed before the appearance of electrographic spikes. Specifically, there was significant loss of coherence between both hippocampi during the pre-spike period compared to spike and rest states. Conclusion/significance: In keeping with previous findings of abnormal inter-hemispheric hippocampal connectivity in MTLE, our findings specifically link reduced connectivity to the period immediately before spikes. This brief decoupling is consistent with a deficit in mutual (inter-hemispheric) hippocampal inhibition that may predispose to spike generation.

AITPM national newsletter President's report May 2010

We’ve had a bit of sticker shock in these parts. Well, apparently. Since my last missive, Brisbane’s Clem Jones Tunnel which was initially free now has a toll, at least partially, at the introductory rate of $2.95 for a one-way car ride between 5a.m. and midnight – free overnight. From 9 May 2010 the toll will be $4.28. Since the introductory toll was introduced, use of the tunnel appears to have declined somewhat – no surprise to transport professionals I suppose. An additional factor may have been that the “novelty value” of driving through the tunnel for free had worn off. This demonstrates to me that much of the community may still see the use of road infrastructure as a rite of passage, with only some actually weighing up the true value of their travel time and vehicle wear and tear against their out of pocket (or onto credit card) cost. Thus, we’re in pioneering times and the role of transport economics in the overall transport infrastructure planning realm is of considerable importance – especially as much of the new big ticket infrastructure is likely to be tolled into the future. The Queensland Premier, Anna Bligh, made poignant commentary about Brisbane City Council’s tunnel use in that such infrastructure is built for future times and not just as a quick fix for current traffic problems. My expectation is that once Airport Link, which is really the northern half of the corridor, opens in 2012, there will be a significant spike in Clem7 usage.

Implementing an employee performance management system in a nonprofit organization

Nonprofit organizations are not exempt from the imperatives of employee attraction, retention, and motivation. As competition for staff, donors, and funding increases, the need to manage employee performance will continue to be a critical human resource management issue. This article outlines a study of the introduction of a performance management system in an Australian nonprofit organization and analyzes its design and implementation. It explores how performance management can be introduced and used effectively within a nonprofit environment to benefit staff and the organization. However, the use of performance management is not without its challenges, and the research also identified initial employee resistance and a resulting initial spike in labor turnover. However, findings indicate that if nonprofit organizations are willing to undertake consultation with staff and ensure that the organization's specific context, values, and mission are reflected in the performance management system, it can be a useful tool for managers and a direct benefit to employees.

Bayesian mixtures for modelling complex medical data : a case study in Parkinson’s disease

Mixture models are a flexible tool for unsupervised clustering that have found popularity in a vast array of research areas. In studies of medicine, the use of mixtures holds the potential to greatly enhance our understanding of patient responses through the identification of clinically meaningful clusters that, given the complexity of many data sources, may otherwise by intangible. Furthermore, when developed in the Bayesian framework, mixture models provide a natural means for capturing and propagating uncertainty in different aspects of a clustering solution, arguably resulting in richer analyses of the population under study. This thesis aims to investigate the use of Bayesian mixture models in analysing varied and detailed sources of patient information collected in the study of complex disease. The first aim of this thesis is to showcase the flexibility of mixture models in modelling markedly different types of data. In particular, we examine three common variants on the mixture model, namely, finite mixtures, Dirichlet Process mixtures and hidden Markov models. Beyond the development and application of these models to different sources of data, this thesis also focuses on modelling different aspects relating to uncertainty in clustering. Examples of clustering uncertainty considered are uncertainty in a patient’s true cluster membership and accounting for uncertainty in the true number of clusters present. Finally, this thesis aims to address and propose solutions to the task of comparing clustering solutions, whether this be comparing patients or observations assigned to different subgroups or comparing clustering solutions over multiple datasets. To address these aims, we consider a case study in Parkinson’s disease (PD), a complex and commonly diagnosed neurodegenerative disorder. In particular, two commonly collected sources of patient information are considered. The first source of data are on symptoms associated with PD, recorded using the Unified Parkinson’s Disease Rating Scale (UPDRS) and constitutes the first half of this thesis. The second half of this thesis is dedicated to the analysis of microelectrode recordings collected during Deep Brain Stimulation (DBS), a popular palliative treatment for advanced PD. Analysis of this second source of data centers on the problems of unsupervised detection and sorting of action potentials or "spikes" in recordings of multiple cell activity, providing valuable information on real time neural activity in the brain.