Evidence for CRHR1 in multiple sclerosis using supervised machine learning and meta-analysis in 12 566 individuals

The primary genetic risk factor in multiple sclerosis (MS) is the HLA-DRB1*1501 allele; however, much of the remaining genetic contribution to MS has yet to be elucidated. Several lines of evidence support a role for neuroendocrine system involvement in autoimmunity which may, in part, be genetically determined. Here, we comprehensively investigated variation within eight candidate hypothalamic-pituitary-adrenal (HPA) axis genes and susceptibility to MS. A total of 326 SNPs were investigated in a discovery dataset of 1343 MS cases and 1379 healthy controls of European ancestry using a multi-analytical strategy. Random Forests, a supervised machine-learning algorithm, identified eight intronic SNPs within the corticotrophin-releasing hormone receptor 1 or CRHR1 locus on 17q21.31 as important predictors of MS. On the basis of univariate analyses, six CRHR1 variants were associated with decreased risk for disease following a conservative correction for multiple tests. Independent replication was observed for CRHR1 in a large meta-analysis comprising 2624 MS cases and 7220 healthy controls of European ancestry. Results from a combined meta-analysis of all 3967 MS cases and 8599 controls provide strong evidence for the involvement of CRHR1 in MS. The strongest association was observed for rs242936 (OR = 0.82, 95% CI = 0.74-0.90, P = 9.7 × 10-5). Replicated CRHR1 variants appear to exist on a single associated haplotype. Further investigation of mechanisms involved in HPA axis regulation and response to stress in MS pathogenesis is warranted. © The Author 2010. Published by Oxford University Press. All rights reserved.

Load modelling : induction motors

Modelling the power systems load is a challenge since the load level and composition varies with time. An accurate load model is important because there is a substantial component of load dynamics in the frequency range relevant to system stability. The composition of loads need to be charaterised because the time constants of composite loads affect the damping contributions of the loads to power system oscillations, and their effects vary with the time of the day, depending on the mix of motors loads. This chapter has two main objectives: 1) describe the load modelling in small signal using on-line measurements; and 2) present a new approach to develop models that reflect the load response to large disturbances. Small signal load characterisation based on on-line measurements allows predicting the composition of load with improved accuracy compared with post-mortem or classical load models. Rather than a generic dynamic model for small signal modelling of the load, an explicit induction motor is used so the performance for larger disturbances can be more reliably inferred. The relation between power and frequency/voltage can be explicitly formulated and the contribution of induction motors extracted. One of the main features of this work is the induction motor component can be associated to nominal powers or equivalent motors

Topological map induction using neighbourhood information of places

In topological mapping, perceptual aliasing can cause different places to appear indistinguishable to the robot. In case of severely corrupted or non-available odometry information, topological mapping is difficult as the robot is challenged with the loop-closing problem; that is to determine whether it has visited a particular place before. In this article we propose to use neighbourhood information to disambiguate otherwise indistinguishable places. Using neighbourhood information for place disambiguation is an approach that neither depends on a specific choice of sensors nor requires geometric information such as odometry. Local neighbourhood information is extracted from a sequence of observations of visited places. In experiments using either sonar or visual observations from an indoor environment the benefits of using neighbourhood clues for the disambiguation of otherwise identical vertices are demonstrated. Over 90% of the maps we obtain are isomorphic with the ground truth. The choice of the robot’s sensors does not impact the results of the experiments much.

Arc voltage behavior in GMAW-P under different drop transfer modes

Purpose: Experimental measurements have been made to investigate meaning of the change in voltage for the pulse gas metal arc welding (GMAW-P) process operating under different drop transfer modes. Design/methodology/approach: Welding experiments with different values of pulsing parameter and simultaneous recording of high speed camera pictures and welding signals (such as current and voltage) were used to identify different drop transfer modes in GMAW-P. The investigation is based on the synchronization of welding signals and high speed camera to study the behaviour of voltage signal under different drop transfer modes. Findings: The results reveal that the welding arc is significantly affected by the molten droplet detachment. In fact, results indicate that sudden increase and drop in voltage just before and after the drop detachment can be used to characterize the voltage behaviour of different drop transfer mode in GMAW-P. Research limitations/implications: The results show that voltage signal carry rich information about different drop transfer occurring in GMAW-P. Hence it’s possible to detect different drop transfer modes. Future work should concentrate on development of filters for detection of different drop transfer modes. Originality/value: Determination of drop transfer mode with GMAW-P is crucial for the appropriate selection of pulse welding parameters. As change in drop transfer mode results in poor weld quality in GMAW-P, so in order to estimate the working parameters and ensure stable GMAW-P understanding the voltage behaviour of different drop transfer modes in GMAW-P will be useful. However, in case of GMAW-P hardly any attempt is made to analyse the behaviour of voltage signal for different drop transfer modes. This paper analyses the voltage signal behaviour of different drop transfer modes for GMAW-P.

Scheduling Trains with Priorities : a no-wait blocking parallel-machine job-shop scheduling model

The paper investigates train scheduling problems when prioritised trains and non-prioritised trains are simultaneously traversed in a single-line rail network. In this case, no-wait conditions arise because the prioritised trains such as express passenger trains should traverse continuously without any interruption. In comparison, non-prioritised trains such as freight trains are allowed to enter the next section immediately if possible or to remain in a section until the next section on the routing becomes available, which is thought of as a relaxation of no-wait conditions. With thorough analysis of the structural properties of the No-Wait Blocking Parallel-Machine Job-Shop-Scheduling (NWBPMJSS) problem that is originated in this research, an innovative generic constructive algorithm (called NWBPMJSS_Liu-Kozan) is proposed to construct the feasible train timetable in terms of a given order of trains. In particular, the proposed NWBPMJSS_Liu-Kozan constructive algorithm comprises several recursively-used sub-algorithms (i.e. Best-Starting-Time-Determination Procedure, Blocking-Time-Determination Procedure, Conflict-Checking Procedure, Conflict-Eliminating Procedure, Tune-up Procedure and Fine-tune Procedure) to guarantee feasibility by satisfying the blocking, no-wait, deadlock-free and conflict-free constraints. A two-stage hybrid heuristic algorithm (NWBPMJSS_Liu-Kozan-BIH) is developed by combining the NWBPMJSS_Liu-Kozan constructive algorithm and the Best-Insertion-Heuristic (BIH) algorithm to find the preferable train schedule in an efficient and economical way. Extensive computational experiments show that the proposed methodology is promising because it can be applied as a standard and fundamental toolbox for identifying, analysing, modelling and solving real-world scheduling problems.

A hybrid shifting bottleneck procedure algorithm for the parallel-machine job-shop scheduling problem

In practice, parallel-machine job-shop scheduling (PMJSS) is very useful in the development of standard modelling approaches and generic solution techniques for many real-world scheduling problems. In this paper, based on the analysis of structural properties in an extended disjunctive graph model, a hybrid shifting bottleneck procedure (HSBP) algorithm combined with Tabu Search metaheuristic algorithm is developed to deal with the PMJSS problem. The original-version SBP algorithm for the job-shop scheduling (JSS) has been significantly improved to solve the PMJSS problem with four novelties: i) a topological-sequence algorithm is proposed to decompose the PMJSS problem into a set of single-machine scheduling (SMS) and/or parallel-machine scheduling (PMS) subproblems; ii) a modified Carlier algorithm based on the proposed lemmas and the proofs is developed to solve the SMS subproblem; iii) the Jackson rule is extended to solve the PMS subproblem; iv) a Tabu Search metaheuristic algorithm is embedded under the framework of SBP to optimise the JSS and PMJSS cases. The computational experiments show that the proposed HSBP is very efficient in solving the JSS and PMJSS problems.

Mining a data reasoning model for personalized text classification

It is a big challenge to acquire correct user profiles for personalized text classification since users may be unsure in providing their interests. Traditional approaches to user profiling adopt machine learning (ML) to automatically discover classification knowledge from explicit user feedback in describing personal interests. However, the accuracy of ML-based methods cannot be significantly improved in many cases due to the term independence assumption and uncertainties associated with them. This paper presents a novel relevance feedback approach for personalized text classification. It basically applies data mining to discover knowledge from relevant and non-relevant text and constraints specific knowledge by reasoning rules to eliminate some conflicting information. We also developed a Dempster-Shafer (DS) approach as the means to utilise the specific knowledge to build high-quality data models for classification. The experimental results conducted on Reuters Corpus Volume 1 and TREC topics support that the proposed technique achieves encouraging performance in comparing with the state-of-the-art relevance feedback models.

Improvisation in interactive music systems

This project investigates machine listening and improvisation in interactive music systems with the goal of improvising musically appropriate accompaniment to an audio stream in real-time. The input audio may be from a live musical ensemble, or playback of a recording for use by a DJ. I present a collection of robust techniques for machine listening in the context of Western popular dance music genres, and strategies of improvisation to allow for intuitive and musically salient interaction in live performance. The findings are embodied in a computational agent – the Jambot – capable of real-time musical improvisation in an ensemble setting. Conceptually the agent’s functionality is split into three domains: reception, analysis and generation. The project has resulted in novel techniques for addressing a range of issues in each of these domains. In the reception domain I present a novel suite of onset detection algorithms for real-time detection and classification of percussive onsets. This suite achieves reasonable discrimination between the kick, snare and hi-hat attacks of a standard drum-kit, with sufficiently low-latency to allow perceptually simultaneous triggering of accompaniment notes. The onset detection algorithms are designed to operate in the context of complex polyphonic audio. In the analysis domain I present novel beat-tracking and metre-induction algorithms that operate in real-time and are responsive to change in a live setting. I also present a novel analytic model of rhythm, based on musically salient features. This model informs the generation process, affording intuitive parametric control and allowing for the creation of a broad range of interesting rhythms. In the generation domain I present a novel improvisatory architecture drawing on theories of music perception, which provides a mechanism for the real-time generation of complementary accompaniment in an ensemble setting. All of these innovations have been combined into a computational agent – the Jambot, which is capable of producing improvised percussive musical accompaniment to an audio stream in real-time. I situate the architectural philosophy of the Jambot within contemporary debate regarding the nature of cognition and artificial intelligence, and argue for an approach to algorithmic improvisation that privileges the minimisation of cognitive dissonance in human-computer interaction. This thesis contains extensive written discussions of the Jambot and its component algorithms, along with some comparative analyses of aspects of its operation and aesthetic evaluations of its output. The accompanying CD contains the Jambot software, along with video documentation of experiments and performances conducted during the project.

Machine vision toolbox for MATLAB, release 3 [Software]

The Toolbox, combined with MATLAB ® and a modern workstation computer, is a useful and convenient environment for investigation of machine vision algorithms. For modest image sizes the processing rate can be sufficiently ``real-time'' to allow for closed-loop control. Focus of attention methods such as dynamic windowing (not provided) can be used to increase the processing rate. With input from a firewire or web camera (support provided) and output to a robot (not provided) it would be possible to implement a visual servo system entirely in MATLAB. Provides many functions that are useful in machine vision and vision-based control. Useful for photometry, photogrammetry, colorimetry. It includes over 100 functions spanning operations such as image file reading and writing, acquisition, display, filtering, blob, point and line feature extraction, mathematical morphology, homographies, visual Jacobians, camera calibration and color space conversion.

Wikileaks and the challenge of the “Fifth Estate”

The Time magazine ‘Person of theYear’ award is a venerable institution. Established by Time’s founder Henry Luce in 1927 as ‘Man of the Year’, it is an annual award given to ‘a person, couple, group, idea, place, or machine that ‘for better or for worse ... has done the most to influence the events of the year’ (Time 2002, p. 1). In 2010, the award was given to Mark Zuckerberg, the founder and CEO of the social networking site Facebook.There was, however, a strong campaign for the ‘People’s Choice’ award to be given to Julian Assange, the founder and editor-in-chief of Wikileaks, the online whistleblowing site. Earlier in the year Wikileaks had released more than 250 000 US government diplomatic cables through the internet, and the subsequent controver- sies around the actions of Wikileaks and Assange came to be known worldwide as ‘Cablegate’. The focus of this chapter is not on the implications of ‘Cablegate’ for international diplomacy, which continue to have great significance, but rather upon what the emergence of Wikileaks has meant for journalism, and whether it provides insights into the future of journalism. Both Facebook and Wikileaks, as well as social media platforms such as Twitter and YouTube, and independent media practices such as blogging, citizen journalism and crowdsourcing, are manifestations of the rise of social media, or what has also been termed web 2.0.The term ‘web 2.0’ was coined by Tim O’Reilly, and captures the rise of online social media platforms and services, that better realise the collaborative potential of digitally networked media. They do this by moving from the relatively static, top-down notions of interactivity that informed early internet development, towards more open and evolutionary models that better harness collective intelligence by enabling users to become the creators and collaborators in the development of online media content (Musser and O’Reilly 2007; Bruns 2008).

Natural convection in the attic-shaped spaces

Heat transfer through an attic space into or out of buildings is an important issue for attic-shaped houses in both hot and cold climates. One of the important objectives for design and construction of houses is to provide thermal comfort for occupants. In the present energy-conscious society, it is also a requirement for houses to be energy efficient, i.e. the energy consumption for heating or air-conditioning houses must be minimized. Relevant to these objectives, research into heat transfer in attics has been conducted for about three decades. The transient behaviour of an attic space is directly relevant to our daily life. Certain periods of the day or night may be considered as having a constant ambient temperature (e.g. during 11am - 2pm or 11pm - 2am). However, at other times during the day or night the ambient temperature changes with time (e.g. between 5am - 9am or 5pm - 9pm). Therefore, the analysis of steady state solution is not sufficient to describe the fluid flow and heat transfer in the attic space. The discussion of the transient development of the boundary is required. A theoretical understanding of the transient behaviour of the flow in the enclosure is performed through scaling analysis for sudden and ramp heating conditions. A proper identification of the timescales, the velocity and the thickness relevant to the flow that develops inside the cavity makes it possible to predict theoretically the basic flow features that will survive once the thermal flow in the enclosure reaches a steady state. Those scaling predictions have been verified by a series of numerical simulations.

Induction motor load impact on power system eigenvalue sensitivity analysis

Load modelling plays an important role in power system dynamic stability assessment. One of the widely used methods in assessing load model impact on system dynamic response is parametric sensitivity analysis. A composite load model-based load sensitivity analysis framework is proposed. It enables comprehensive investigation into load modelling impacts on system stability considering the dynamic interactions between load and system dynamics. The effect of the location of individual as well as patches of composite loads in the vicinity on the sensitivity of the oscillatory modes is investigated. The impact of load composition on the overall sensitivity of the load is also investigated.

Mixed convection flow of micropolar fluid in an open ended arc-shape cavity

Numerical simulations for mixed convection of micropolar fluid in an open ended arc-shape cavity have been carried out in this study. Computation is performed using the Alternate Direct Implicit (ADI) method together with the Successive Over Relaxation (SOR) technique for the solution of governing partial differential equations. The flow phenomenon is examined for a range of values of Rayleigh number, 102 ≤ Ra ≤ 106, Prandtl number, 7 ≤ Pr ≤ 50, and Reynolds number, 10 ≤ Re ≤ 100. The study is mainly focused on how the micropolar fluid parameters affect the fluid properties in the flow domain. It was found that despite the reduction of flow in the core region, the heat transfer rate increases, whereas the skin friction and microrotation decrease with the increase in the vortex viscosity parameter, Δ.

Speed enforcement in Australia : a changing policy landscape shaped by public opinion

- Speeding and crash involvement in Australia - Speed management in Australia - Jurisdictional differences - National Road Safety Strategy (2011-2020) - Auditor-General reviews of speed camera programs - The role of public opinion/feedback - Implications for speed management

Tracking the magmatic evolution of island arc volcanism : insights from a high-precision Pb isotope record of Montserrat, Lesser Antilles

The volcanic succession on Montserrat provides an opportunity to examine the magmatic evolution of island arc volcanism over a ∼2.5 Ma period, extending from the andesites of the Silver Hills center, to the currently active Soufrière Hills volcano (February 2010). Here we present high-precision double-spike Pb isotope data, combined with trace element and Sr-Nd isotope data throughout this period of Montserrat's volcanic evolution. We demonstrate that each volcanic center; South Soufrière Hills, Soufrière Hills, Centre Hills and Silver Hills, can be clearly discriminated using trace element and isotopic parameters. Variations in these parameters suggest there have been systematic and episodic changes in the subduction input. The SSH center, in particular, has a greater slab fluid signature, as indicated by low Ce/Pb, but less sediment addition than the other volcanic centers, which have higher Th/Ce. Pb isotope data from Montserrat fall along two trends, the Silver Hills, Centre Hills and Soufrière Hills lie on a general trend of the Lesser Antilles volcanics, whereas SSH volcanics define a separate trend. The Soufrière Hills and SSH volcanic centers were erupted at approximately the same time, but retain distinctive isotopic signatures, suggesting that the SSH magmas have a different source to the other volcanic centers. We hypothesize that this rapid magmatic source change is controlled by the regional transtensional regime, which allowed the SSH magma to be extracted from a shallower source. The Pb isotopes indicate an interplay between subduction derived components and a MORB-like mantle wedge influenced by a Galapagos plume-like source.