Simplifying the representation of complex free-energy landscapes using sketch-map

A new scheme, sketch-map, for obtaining a low-dimensional representation of the region of phase space explored during an enhanced dynamics simulation is proposed. We show evidence, from an examination of the distribution of pairwise distances between frames, that some features of the free-energy surface are inherently high-dimensional. This makes dimensionality reduction problematic because the data does not satisfy the assumptions made in conventional manifold learning algorithms We therefore propose that when dimensionality reduction is performed on trajectory data one should think of the resultant embedding as a quickly sketched set of directions rather than a road map. In other words, the embedding tells one about the connectivity between states but does not provide the vectors that correspond to the slow degrees of freedom. This realization informs the development of sketch-map, which endeavors to reproduce the proximity information from the high-dimensionality description in a space of lower dimensionality even when a faithful embedding is not possible.

General, PDB-based collective variables for protein folding

New, automated forms of data-analysis are required in order to understand the high-dimensional trajectories that are obtained from molecular dynamics simulations on proteins. Dimensionality reduction algorithms are particularly appealing in this regard as they allow one to construct unbiased, low-dimensional representations of the trajectory using only the information encoded in the trajectory. The downside of this approach is that different sets of coordinates are required for each different chemical systems under study precisely because the coordinates are constructed using information from the trajectory. In this paper we show how one can resolve this problem by using the sketch-map algorithm that we recently proposed to construct a low-dimensional representation of the structures contained in the protein data bank (PDB). We show that the resulting coordinates are as useful for analysing trajectory data as coordinates constructed using landmark configurations taken from the trajectory and that these coordinates can thus be used for understanding protein folding across a range of systems.

Hierarchical Task Network Planning with Common-Sense Reasoning for Multiple-People Behaviour Analysis

Safety on public transport is a major concern for the relevant authorities. We
address this issue by proposing an automated surveillance platform which combines data from video, infrared and pressure sensors. Data homogenisation and integration is achieved by a distributed architecture based on communication middleware that resolves interconnection issues, thereby enabling data modelling. A common-sense knowledge base models and encodes knowledge about public-transport platforms and the actions and activities of passengers. Trajectory data from passengers is modelled as a time-series of human activities. Common-sense knowledge and rules are then applied to detect inconsistencies or errors in the data interpretation. Lastly, the rationality that characterises human behaviour is also captured here through a bottom-up Hierarchical Task Network planner that, along with common-sense, corrects misinterpretations to explain passenger behaviour. The system is validated using a simulated bus saloon scenario as a case-study. Eighteen video sequences were recorded with up to six passengers. Four metrics were used to evaluate performance. The system, with an accuracy greater than 90% for each of the four metrics, was found to outperform a rule-base system and a system containing planning alone.

The design of a navigation guidance and control system for an unmanned surface vehicle for environmental monitoring

Maintaining the ecosystem is one of the main concerns in this modern age. With the fear of ever-increasing global warming, the UK is one of the key players to participate actively in taking measures to slow down at least its phenomenal rate. As an ingredient to this process, the Springer vehicle was designed and developed for environmental monitoring and pollutant tracking. This special issue paper highlighted the Springer hardware and software architecture including various navigational sensors, a speed controller, and an environmental monitoring unit. In addition, details regarding the modelling of the vessel were outlined based mainly on experimental data. The formulation of a fault tolerant multi-sensor data fusion technique was also presented. Moreover, control strategy based on a linear quadratic Gaussian controller was developed and simulated on the Springer model.
Gaussian controller is developed and simulated on the Springer model.

Timing and trajectory in rhythm production

The Wing-Kristofferson movement timing model (A. M. Wing & A. B. Kristofferson, 1973a, 1973b) distinguishes central timer and motor implementation processes. Previous studies have shown that increases in interresponse interval (IRI) variability with mean IRI are due to central timer processes, not motor implementation. The authors examine whether this is true with IRI duration changes in binary rhythm production. Ten participants provided IRI and movement data in bimanual synchronous tapping under equal (isochronous) and alternating (rhythm) interval conditions. Movement trajectory changes were observed with IRI duration (300, 500, or 833 ms) and for 500-ms IRIs produced in rhythm contexts (300/500 ms, 500/833 ms). However, application of the Wing-Kristofferson model showed that duration and context effects on IRI variability were attributable largely to timer processes with relatively little effect on motor processes.

Impact of weather conditions on electric vehicle performance

Seasonal and day-to-day variations in travel behaviour and performance of private passenger vehicles can be partially explained by changes in weather conditions. Likewise, in the electricity sector, weather affects energy demand. The impact of weather conditions on private passenger vehicle performance, usership statistics and travel behaviour has been studied for conventional, internal combustion engine, vehicles. Similarly, weather-driven variability in electricity demand and generation has been investigated widely. The aim of these analyses in both sectors is to improve energy efficiency, reduce consumption in peak hours and reduce greenhouse gas emissions. However, the potential effects of seasonal weather variations on electric vehicle usage have not yet been investigated. In Ireland the government has set a target requiring 10% of all vehicles in the transport fleet to be powered by electricity by 2020 to meet part of its European Union obligations to reduce greenhouse gas emissions and increase energy efficiency. This paper fills this knowledge gap by compiling some of the published information available for internal combustion engine vehicles and applying the lessons learned and results to electric vehicles with an analysis of historical weather data in Ireland and electricity market data in a number of what-if scenarios. Areas particularly impacted by weather conditions are battery performance, energy consumption and choice of transportation mode by private individuals.

Preliminary analysis of organic Rankine cycles to improve vehicle efficiency

This paper presents the background rationale and key findings for a model-based study of supercritical waste heat recovery organic Rankine cycles. The paper’s objective is to cover the necessary groundwork to facilitate the future operation of a thermodynamic organic Rankine cycle model under realistic thermodynamic boundary conditions for performance optimisation of organic Rankine cycles. This involves determining the type of power cycle for organic Rankine cycles, the circuit configuration and suitable boundary conditions. The study focuses on multiple heat sources from vehicles but the findings are generally applicable, with careful consideration, to any waste heat recovery system. This paper introduces waste heat recovery and discusses the general merits of organic fluids versus water and supercritical operation versus subcritical operation from a theoretical perspective and, where possible, from a practical perspective. The benefits of regeneration are investigated from an efficiency perspective for selected subcritical and supercritical conditions. A simulation model is described with an introduction to some general Rankine cycle boundary conditions. The paper describes the analysis of real hybrid vehicle data from several driving cycles and its manipulation to represent the thermal inertia for model heat input boundary conditions. Basic theory suggests that selecting the operating pressures and temperatures to maximise the Rankine cycle performance is relatively straightforward. However, it was found that this may not be the case for an organic Rankine cycle operating in a vehicle. When operating in a driving cycle, the available heat and its quality can vary with the power output and between heat sources. For example, the available coolant heat does not vary much with the load, whereas the quantity and quality of the exhaust heat varies considerably. The key objective for operation in the vehicle is optimum utilisation of the available heat by delivering the maximum work out. The fluid selection process and the presentation and analysis of the final results of the simulation work on organic Rankine cycles are the subjects of two future publications.

First-order characteristics of the person-to-vehicle channel at 5.8 GHz

In this paper we investigate the first order characteristics of the radio channel between a moving vehicle and a stationary person positioned by the side of a road at 5.8 GHz. The experiments considered a transmitter positioned at different locations on both the body and receivers positioned on the vehicle. The transmitter was alternated between positions on the central chest region, back and the wrist (facing the roadside) of the body, with the receivers placed on the outside roof, the outside rear window and the inside dashboard of the vehicle. The Rice fading model was applied to the measurement data to assess its suitability for characterizing this emerging type of wireless channel. The Ricean K factors calculated from the data suggest that a significant dominant component existed in the majority of the channels considered in this study.

In situ diagnostics and prognostics of solder fatigue in IGBT modules for electric vehicle drives

This paper proposes an in situ diagnostic and prognostic (D&P) technology to monitor the health condition of insulated gate bipolar transistors (IGBTs) used in EVs with a focus on the IGBTs' solder layer fatigue. IGBTs' thermal impedance and the junction temperature can be used as health indicators for through-life condition monitoring (CM) where the terminal characteristics are measured and the devices' internal temperature-sensitive parameters are employed as temperature sensors to estimate the junction temperature. An auxiliary power supply unit, which can be converted from the battery's 12-V dc supply, provides power to the in situ test circuits and CM data can be stored in the on-board data-logger for further offline analysis. The proposed method is experimentally validated on the developed test circuitry and also compared with finite-element thermoelectrical simulation. The test results from thermal cycling are also compared with acoustic microscope and thermal images. The developed circuitry is proved to be effective to detect solder fatigue while each IGBT in the converter can be examined sequentially during red-light stopping or services. The D&P circuitry can utilize existing on-board hardware and be embedded in the IGBT's gate drive unit.

Identification of Road Irregularities via Vehicle Accelerations

A periodic monitoring of the pavement condition facilitates a cost-effective distribution of the resources available for maintenance of the road infrastructure network. The task can be accurately carried out using profilometers, but such an approach is generally expensive. This paper presents a method to collect information on the road profile via accelerometers mounted in a fleet of non-specialist vehicles, such as police cars, that are in use for other purposes. It proposes an optimisation algorithm, based on Cross Entropy theory, to predict road irregularities. The Cross Entropy algorithm estimates the height of the road irregularities from vehicle accelerations at each point in time. To test the algorithm, the crossing of a half-car roll model is simulated over a range of road profiles to obtain accelerations of the vehicle sprung and unsprung masses. Then, the simulated vehicle accelerations are used as input in an iterative procedure that searches for the best solution to the inverse problem of finding road irregularities. In each iteration, a sample of road profiles is generated and an objective function defined as the sum of squares of differences between the ‘measured’ and predicted accelerations is minimized until convergence is reached. The reconstructed profile is classified according to ISO and IRI recommendations and compared to its original class. Results demonstrate that the approach is feasible and that a good estimate of the short-wavelength features of the road profile can be detected, despite the variability between the vehicles used to collect the data.

Detection of Bridge Dynamic Parameters using an Instrumented Vehicle

Highway structures such as bridges are subject to continuous degradation primarily due to ageing and environmental factors. A rational transport policy requires the monitoring of this transport infrastructure to provide adequate maintenance and guarantee the required levels of transport service and safety. In Europe, this is now a legal requirement - a European Directive requires all member states of the European Union to implement a Bridge Management System. However, the process is expensive, requiring the installation of sensing equipment and data acquisition electronics on the bridge. This paper investigates the use of an instrumented vehicle fitted with accelerometers on its axles to monitor the dynamic behaviour of bridges as an indicator of its structural condition. This approach eliminates the need for any on-site installation of measurement equipment. A simplified half-car vehicle-bridge interaction model is used in theoretical simulations to test the possibility of extracting the dynamic parameters of the bridge from the spectra of the vehicle accelerations. The effect of vehicle speed, vehicle mass and bridge span length on the detection of the bridge dynamic parameters are investigated. The algorithm is highly sensitive to the condition of the road profile and simulations are carried out for both smooth and rough profiles

Monitoring Bridge Dynamic Behaviour using an Instrumented Two Axle Vehicle

Highway structures such as bridges are subject to continuous degradation primarily due to ageing, loading and environmental factors. A rational transport policy must monitor and provide adequate maintenance to this infrastructure to guarantee the required levels of transport service and safety. Increasingly in recent years, bridges are being instrumented and monitored on an ongoing basis due to the implementation of Bridge Management Systems. This is very effective and provides a high level of protection to the public and early warning if the bridge becomes unsafe. However, the process can be expensive and time consuming, requiring the installation of sensors and data acquisition electronics on the bridge. This paper investigates the use of an instrumented 2-axle vehicle fitted with accelerometers to monitor the dynamic behaviour of a bridge network in a simple and cost-effective manner. A simplified half car-beam interaction model is used to simulate the passage of a vehicle over a bridge. This investigation involves the frequency domain analysis of the axle accelerations as the vehicle crosses the bridge. The spectrum of the acceleration record contains noise, vehicle, bridge and road frequency components. Therefore, the bridge dynamic behaviour is monitored in simulations for both smooth and rough road surfaces. The vehicle mass and axle spacing are varied in simulations along with bridge structural damping in order to analyse the sensitivity of the vehicle accelerations to a change in bridge properties. These vehicle accelerations can be obtained for different periods of time and serve as a useful tool to monitor the variation of bridge frequency and damping with time.

Predictors of caregiver burden across the home-based palliative care trajectory in Ontario, Canada

Family caregivers of patients enrolled in home-based palliative care programmes provide unpaid care and assistance with daily activities to terminally ill family members. Caregivers often experience caregiver burden, which is an important predictor of anxiety and depression that can extend into bereavement. We conducted a longitudinal, prospective cohort study to comprehensively assess modifiable and non-modifiable patient and caregiver factors that account for caregiver burden over the palliative care trajectory. Caregivers (n = 327) of patients with malignant neoplasm were recruited from two dedicated home-based palliative care programmes in Southern Ontario, Canada from 1 July 2010 to 31 August 2012. Data were obtained from bi-weekly telephone interviews with caregivers from study admission until death, and from palliative care programme and home-care agency databases. Information collected comprised patient and caregiver demographics, utilisation of privately and publicly financed resources, patient clinical status and caregiver burden. The average age of the caregivers was 59.0 years (SD: 13.2), and almost 70% were female. Caregiver burden increased over time in a non-linear fashion from study admission to patient death. Increased monthly unpaid care-giving time costs, monthly public personal support worker costs, emergency department visits and low patient functional status were associated with higher caregiver burden. Greater use of hospice care was associated with lower burden. Female caregivers tended to report more burden compared to men as death approached, and burden was higher when patients were male. Low patient functional status was the strongest predictor of burden. Understanding the influence of modifiable and non-modifiable factors on the experience of burden over the palliative trajectory is essential for the development and targeting of programmes and policies to support family caregivers and reduce burden. Supporting caregivers can have benefits such as improved caregiver health outcomes, and enhancing their ability to meet care-giving demands, thereby potentially allowing for longer patient care in the home setting.