Optimizing geometric accuracy of four dimensional CT scans acquired using the wall and couch mounted Varian Real-Time Position Management camera systems

Objective:

The aim of this study was to identify sources of anatomical misrepresentation due to the location of camera mounting, tumour motion velocity and image processing artefacts in order to optimise the 4DCT scan protocol and improve geometrical-temporal accuracy.

A phantom with an imaging insert was driven with a sinusoidal superior-inferior motion of varying amplitude and period for 4DCT scanning. The length of a high density cube within the insert was measured using treatment planning software to determine the accuracy of its spatial representation. Scan parameters were varied including the tube rotation period and the cine time between reconstructed images. A CT image quality phantom was used to measure various image quality signatures under the scan parameters tested.

No significant difference in spatial accuracy was found for 4DCT scans carried out using the wall mounted or couch mounted camera for sinusoidal target motion. Greater spatial accuracy was found for 4DCT scans carried out using a tube rotation speed of 0.5s rather than 1.0s. The reduction in image quality when using a faster rotation speed was not enough to require an increase in patient dose.

4DCT accuracy may be increased by optimising scan parameters, including choosing faster tube rotation speeds. Peak misidentification in the recorded breathing trace leads to spatial artefacts and this risk can be reduced by using a couch mounted infrared camera.

This study explicitly shows that 4DCT scan accuracy is improved by scanning with a faster CT tube rotation speed.

An Event Driven Fusion Approach for Enjoyment Recognition in Real-time

Social signals and interpretation of carried information is of high importance in Human Computer Interaction. Often used for affect recognition, the cues within these signals are displayed in various modalities. Fusion of multi-modal signals is a natural and interesting way to improve automatic classification of emotions transported in social signals. Throughout most present studies, uni-modal affect recognition as well as multi-modal fusion, decisions are forced for fixed annotation segments across all modalities. In this paper, we investigate the less prevalent approach of event driven fusion, which indirectly accumulates asynchronous events in all modalities for final predictions. We present a fusion approach, handling short-timed events in a vector space, which is of special interest for real-time applications. We compare results of segmentation based uni-modal classification and fusion schemes to the event driven fusion approach. The evaluation is carried out via detection of enjoyment-episodes within the audiovisual Belfast Story-Telling Corpus.

Identification of Pseudomonas aeruginosa by a duplex real-time polymerase chain reaction assay targeting the ecfX and the gyrB genes

Phenotypic identification of Gram-negative bacteria from respiratory specimens of patients with cystic fibrosis carries a high risk of misidentification. Molecular identification techniques that use single-gene targets are also susceptible to error, including cross-reaction issues with other Gram-negative organisms. In this study, we have designed a Pseudomonas aeruginosa duplex real-time polymerase chain reaction (PCR) (PAduplex) assay targeting the ecfX and the gyrB genes. The PAduplex was evaluated against a panel of 91 clinical and environmental isolates that were presumptively identified as P. aeruginosa. The results were compared with those obtained using a commercial biochemical identification kit and several other P. aeruginosa PCR assays. The results showed that the PAduplex assay is highly suitable for routine identification of P. aeruginosa isolates from clinical or environmental samples. The 2-target format provides simultaneous confirmation of P. aeruginosa identity where both the ecfX and gyrB PCR reactions are positive and may also reduce the potential for false negatives caused by sequence variation in primer or probe targets.

Rapid quantification of microRNAs in plasma using a fast real time PCR system

The ability to rapidly detect circulating small RNAs, in particular microRNAs (miRNAs), would further increase their already established potential as biomarkers in a range of conditions. One rate-limiting factor is the time taken to perform quantitative real time PCR amplification. We therefore evaluated the ability of a novel thermal cycler to perform this step in less than 10 minutes. Quantitative PCR was performed on an xxpress® thermal cycler (BJS Biotechnologies, Perivale, UK), which employs a resistive heating system and forced air cooling to achieve thermal ramp rates of 10 °C/s, and a conventional peltier-controlled LightCycler 480 system (Roche, Basel, Switzerland) ramping at 4.8 °C/s. The threshold cycle (Ct) for detection of 18S rDNA from a standard genomic DNA sample was significantly more variable across the block (F-test, p=2.4x10-25) for the xxpress (20.01±0.47SD) than the LightCycler (19.87±0.04SD). RNA was extracted from human plasma, reverse transcribed and a panel of miRNAs amplified and detected using SYBR green (Kapa Biosystems, Wilmington, Ma, USA). The sensitivity of both systems was broadly comparable and both detected a panel of miRNAs reliably and indicated similar relative abundances. The xxpress thermal cycler facilitates rapid qPCR detection of small RNAs and brings point-of care diagnostics based upon circulating miRNAs a step closer to reality.

Real-time temperature estimation for power MOSFETs considering thermal aging effects

This paper presents a novel real-time power-device temperature estimation method that monitors the power MOSFET's junction temperature shift arising from thermal aging effects and incorporates the updated electrothermal models of power modules into digital controllers. Currently, the real-time estimator is emerging as an important tool for active control of device junction temperature as well as online health monitoring for power electronic systems, but its thermal model fails to address the device's ongoing degradation. Because of a mismatch of coefficients of thermal expansion between layers of power devices, repetitive thermal cycling will cause cracks, voids, and even delamination within the device components, particularly in the solder and thermal grease layers. Consequently, the thermal resistance of power devices will increase, making it possible to use thermal resistance (and junction temperature) as key indicators for condition monitoring and control purposes. In this paper, the predicted device temperature via threshold voltage measurements is compared with the real-time estimated ones, and the difference is attributed to the aging of the device. The thermal models in digital controllers are frequently updated to correct the shift caused by thermal aging effects. Experimental results on three power MOSFETs confirm that the proposed methodologies are effective to incorporate the thermal aging effects in the power-device temperature estimator with good accuracy. The developed adaptive technologies can be applied to other power devices such as IGBTs and SiC MOSFETs, and have significant economic implications. 

Hand-held voltammetric analyser for real-time monitoring of heavy metals in situ

This paper presents a novel hand-held instrument capable of real-time in situ detection and identification of heavy metals. The proposed system provides the facilities found in a traditional lab-based instrument in a hand held a design. In contrast to existing commercial systems, it can stand alone without the need of an associated computer. The electrochemical instrument uses anodic stripping voltammetry which is a precise and sensitive analytical method with excellent limits of detection. The sensors comprise disposable screen-printed (solid working) electrodes rather than the more common hanging mercury drop electrodes. The system is reliable, easy to use, safe, avoids expensive and time-consuming procedures and may be used in a variety of situations to help in the fields of environmental assessment and control.

Melt:for marimba and real-time sound processing

premiered by Mel Puga Iglesias

Game-­theoretic Resource Allocation with Real-­time Probabilistic Surveillance Information

Game-theoretic security resource allocation problems have generated significant interest in the area of designing and developing security systems. These approaches traditionally utilize the Stackelberg game model for security resource scheduling in order to improve the protection of critical assets. The basic assumption in Stackelberg games is that a defender will act first, then an attacker will choose their best response after observing the defender’s strategy commitment (e.g., protecting a specific asset). Thus, it requires an attacker’s full or partial observation of a defender’s strategy. This assumption is unrealistic in real-time threat recognition and prevention. In this paper, we propose a new solution concept (i.e., a method to predict how a game will be played) for deriving the defender’s optimal strategy based on the principle of acceptable costs of minimax regret. Moreover, we demonstrate the advantages of this solution concept by analyzing its properties.

An integrated approach for real-time model-based state-of-charge estimation of lithium-ion batteries

Lithium-ion batteries have been widely adopted in electric vehicles (EVs), and accurate state of charge (SOC) estimation is of paramount importance for the EV battery management system. Though a number of methods have been proposed, the SOC estimation for Lithium-ion batteries, such as LiFePo4 battery, however, faces two key challenges: the flat open circuit voltage (OCV) vs SOC relationship for some SOC ranges and the hysteresis effect. To address these problems, an integrated approach for real-time model-based SOC estimation of Lithium-ion batteries is proposed in this paper. Firstly, an auto-regression model is adopted to reproduce the battery terminal behaviour, combined with a non-linear complementary model to capture the hysteresis effect. The model parameters, including linear parameters and non-linear parameters, are optimized off-line using a hybrid optimization method that combines a meta-heuristic method (i.e., the teaching learning based optimization method) and the least square method. Secondly, using the trained model, two real-time model-based SOC estimation methods are presented, one based on the real-time battery OCV regression model achieved through weighted recursive least square method, and the other based on the state estimation using the extended Kalman filter method (EKF). To tackle the problem caused by the flat OCV-vs-SOC segments when the OCV-based SOC estimation method is adopted, a method combining the coulombic counting and the OCV-based method is proposed. Finally, modelling results and SOC estimation results are presented and analysed using the data collected from LiFePo4 battery cell. The results confirmed the effectiveness of the proposed approach, in particular the joint-EKF method.

Iso-Quality of Service: Fairly Ranking Servers for Real-Time Data Analytics

We present a mathematically rigorous Quality-of-Service (QoS) metric which relates the achievable quality of service metric (QoS) for a real-time analytics service to the server energy cost of offering the service. Using a new iso-QoS evaluation methodology, we scale server resources to meet QoS targets and directly rank the servers in terms of their energy-efficiency and by extension cost of ownership. Our metric and method are platform-independent and enable fair comparison of datacenter compute servers with significant architectural diversity, including micro-servers. We deploy our metric and methodology to compare three servers running financial option pricing workloads on real-life market data. We find that server ranking is sensitive to data inputs and desired QoS level and that although scale-out micro-servers can be up to two times more energy-efficient than conventional heavyweight servers for the same target QoS, they are still six times less energy efficient than high-performance computational accelerators.

Methods and Metrics for Fair Server Assessment under Real-Time Financial Workloads

We present a rigorous methodology and new metrics for fair comparison of server and microserver platforms. Deploying our methodology and metrics, we compare a microserver with ARM cores against two servers with ×86 cores running the same real-time financial analytics workload. We define workload-specific but platform-independent performance metrics for platform comparison, targeting both datacenter operators and end users. Our methodology establishes that a server based on the Xeon Phi co-processor delivers the highest performance and energy efficiency. However, by scaling out energy-efficient microservers, we achieve competitive or better energy efficiency than a power-equivalent server with two Sandy Bridge sockets, despite the microserver's slower cores. Using a new iso-QoS metric, we find that the ARM microserver scales enough to meet market throughput demand, that is, a 100% QoS in terms of timely option pricing, with as little as 55% of the energy consumed by the Sandy Bridge server.

Determining adsorbate configuration on alumina surfaces with 13C nuclear magnetic resonance relaxation time analysis

Relative strengths of surface interaction for individual carbon atoms in acyclic and cyclic hydrocarbons adsorbed on alumina surfaces are determined using chemically resolved 13C nuclear magnetic resonance (NMR) T1 relaxation times. The ratio of relaxation times for the adsorbed atoms T1,ads to the bulk liquid relaxation time T1,bulk provides an indication of the mobility of the atom. Hence a low T1,ads/T1,bulk ratio indicates a stronger surface interaction. The carbon atoms associated with unsaturated bonds in the molecules are seen to exhibit a larger reduction in T1 on adsorption relative to the aliphatic carbons, consistent with adsorption occurring through the carbon-carbon multiple bonds. The relaxation data are interpreted in terms of proximity of individual carbon atoms to the alumina surface and adsorption conformations are inferred. Furthermore, variations of interaction strength and molecular configuration have been explored as a function of adsorbate coverage, temperature, surface pre-treatment, and in the presence of co-adsorbates. This relaxation time analysis is appropriate for studying the behaviour of hydrocarbons adsorbed on a wide range of catalyst support and supported-metal catalyst surfaces, and offers the potential to explore such systems under realistic operating conditions when multiple chemical components are present at the surface.

Characterization of a reference material for BCR-ABL (M-BCR) mRNA quantitation by real-time amplification assays:towards new standards for gene expression measurements

Monitoring of BCR-ABL transcripts has become established practice in the management of chronic myeloid leukemia. However, nucleic acid amplification techniques are prone to variations which limit the reliability of real-time quantitative PCR (RQ-PCR) for clinical decision making, highlighting the need for standardization of assays and reporting of minimal residual disease (MRD) data. We evaluated a lyophilized preparation of a leukemic cell line (K562) as a potential quality control reagent. This was found to be relatively stable, yielding comparable respective levels of ABL, GUS and BCR-ABL transcripts as determined by RQ-PCR before and after accelerated degradation experiments as well as following 5 years storage at -20 degrees C. Vials of freeze-dried cells were sent at ambient temperature to 22 laboratories on four continents, with RQ-PCR analyses detecting BCR-ABL transcripts at levels comparable to those observed in primary patient samples. Our results suggest that freeze-dried cells can be used as quality control reagents with a range of analytical instrumentations and could enable the development of urgently needed international standards simulating clinically relevant levels of MRD.

Geotechnical monitoring using a combination of LIDAR, real-time dGPS, and electrical tomography to assess geotechnical risk of a coastal landslide.

The Antrim Coast Road stretching from the seaport of Larne in the East of Northern Ireland has a well-deserved reputation for being one of the most spectacular roads in Europe (Day, 2006). However the problematic geology; Jurassic Lias Clay and Triassic Mudstone overlain by Cretaceous Limestone and Tertiary Basalt, and environmental variables result in frequent instances of slope instability manifested in both shallow debris flows and occasional massive rotational movements, creating a geotechnical risk to this highway. This paper describes how a variety of techniques are being used to both assess instability and monitor movement of these active slopes near one site at Straidkilly Point, Glenarm. An in-depth understanding of the geology was obtained via boreholes, resistivity surveys and laboratory testing. Environmental variables recorded by an on-site weather station were correlated with measured pore water pressure and soil moisture infiltration data. Terrestrial LiDAR (TLS), with surveys carried out on a bi-monthly basis allowed for the generation of Digital Elevation Models (DEMs) of difference, highlighting areas of recent movement, accumulation and depletion. Morphology parameters were generated from the DEMs and include slope, curvature and multiple measures of roughness. Changes in the structure of the slope coupled with morphological parameters were characterised and linked to progressive failures from the temporal monitoring. In addition to TLS monitoring, Aerial LiDAR datasets were used for the spatio-morphological characterisation of the slope on a macro scale. A Differential Global Positioning System (dGPS) was also deployed on site to provide a real-time warning system for gross movements, which were also correlated with environmental conditions. Frequent electrical resistivity tomography (ERT) surveys were also implemented to provide a better understanding of long-term changes in soil moisture and help to define the complex geology. The paper describes how the data obtained via a diverse range of methods has been combined to facilitate a more informed management regime of geotechnical risk by the Northern Ireland Roads Service.

High Performance Real-time Pre-Processing for Fixed-Complexity Sphere Decoder

Pre-processing (PP) of received symbol vector and channel matrices is an essential pre-requisite operation for Sphere Decoder (SD)-based detection of Multiple-Input Multiple-Output (MIMO) wireless systems. PP is a highly complex operation, but relative to the total SD workload it represents a relatively small fraction of the overall computational cost of detecting an OFDM MIMO frame in standards such as 802.11n. Despite this, real-time PP architectures are highly inefficient, dominating the resource cost of real-time SD architectures. This paper resolves this issue. By reorganising the ordering and QR decomposition sub operations of PP, we describe a Field Programmable Gate Array (FPGA)-based PP architecture for the Fixed Complexity Sphere Decoder (FSD) applied to 4 × 4 802.11n MIMO which reduces resource cost by 50% as compared to state-of-the-art solutions whilst maintaining real-time performance.