Computer-controlled mechanical simulation of the artificially ventilated human respiratory system

A mechanical lung simulator can be used to simulate specific lung pathologies, to test lung-function equipment, and in instruction. A new approach to mechanical simulation of lung behavior is introduced that uses a computer-controlled active mechatronic system. The main advantage of this approach is that the static and dynamic properties of the simulator can easily be adjusted via the control software. A nonlinear single-compartment mathematical model of the artificially ventilated respiratory system has been derived and incorporated into the simulator control system. This model can capture both the static and dynamic compliance of the respiratory system as well as nonlinear flow-resistance properties. Parameters in this model can be estimated by using data from artificially ventilated patients. It is shown that the simulation model fits patient data well. This mathematical model of the respiratory system was then matched to a model of the available physical equipment (the simulator, actuators, and the interface electronics) in order to obtain the desired lung behavior. A significant time delay in the piston motion control loop has been identified, which can potentially cause oscillations or even instability for high compliance values. Therefore, a feedback controller based on the Smith-predictor scheme was developed to control the piston motion. The control system, implemented on a personal computer, also includes a user-friendly interface to allow easy parameter setting.     

Classification of rheumatoid joint inflammation based on laser imaging

We describe a classification system for a novel imaging method for arthritic finger joints. The basis of this system is a laser imaging technique which is sensitive to the optical characteristics of finger joint tissue. From the laser images acquired at baseline and follow-up, finger joints can automatically be classified according to whether the inflammatory status has improved or worsened. To perform the classification task, various linear and kernel-based systems were implemented and their performances were compared. Based on the results presented in this paper, we conclude that the laser-based imaging permits a reliable classification of pathological finger joints, making it a sensitive method for detecting arthritic changes.     

Ternary Gels of a Polymer Blend and a Recycled Oil: Their Use as Bitumen Modifiers

A blend of random ethylene‐vinyl acetate copolymer (EVA) and triblock styrene‐butadiene‐styrene copolymer (SBS) was dissolved in a recycled engine oil to obtain ternary thermoreversible gels. As the temperature was increased, first a network associated with EVA disappeared, and a second one associated with SBS dominated, maintaining the elastic response of the system. The principal advantage of these ternary systems is that their mechanical properties and thermal stability are better than that of binary gels. These gels, made from waste, can be used as bitumen modifiers to obtain binders of improved properties and good stability, which are useful for road surfacing.

Temperature sweeps of elastic modulus performed at a frequency of 1 Hz.     

Design of phononic materials/structures for surface wave devices using topology optimization

We develop a topology optimization approach to design two- and three-dimensional phononic (elastic) materials, focusing primarily on surface wave filters and waveguides. These utilize propagation modes that transmit elastic waves where the energy is contained near a free surface of a material. The design of surface wave devices is particularly attractive given recent advances in nano- and micromanufacturing processes, such as thin-film deposition, etching, and lithography, which make it possible to precisely place thin film materials on a substrate with submicron feature resolution. We apply our topology optimization approach to a series of three problems where the layout of two materials (silicon and aluminum) is sought to achieve a prescribed objective: (1) a grating to filter bulk waves of a prescribed frequency in two and three dimensions, (2) a surface wave device that uses a patterned thin film to filter waves of a single or range of frequencies, and (3) a fully three-dimensional structure to guide a wave generated by a harmonic input on a free surface to a specified output port on the surface. From the first to the third example, the resulting topologies increase in sophistication. The results demonstrate the power and promise of our computational framework to design sophisticated surface wave devices.     

Training Effective Node Classifiers for Cascade Classification

Cascade classifiers are widely used in real-time object detection. Different from conventional classifiers that are designed for a low overall classification error rate, a classifier in each node of the cascade is required to achieve an extremely high detection rate and moderate false positive rate. Although there are a few reported methods addressing this requirement in the context of object detection, there is no principled feature selection method that explicitly takes into account this asymmetric node learning objective. We provide such an algorithm here. We show that a special case of the biased minimax probability machine has the same formulation as the linear asymmetric classifier (LAC) of Wu et al. (linear asymmetric classifier for cascade detectors, 2005). We then design a new boosting algorithm that directly optimizes the cost function of LAC. The resulting totally-corrective boosting algorithm is implemented by the column generation technique in convex optimization. Experimental results on object detection verify the effectiveness of the proposed boosting algorithm as a node classifier in cascade object detection, and show performance better than that of the current state-of-the-art.     

Computation of the recoverable region and stabilisation problem in the recoverable region for discrete-time systems

This article considers discrete-time linear time-invariant systems subject to input and state constraints. It is shown that in the recoverable region (which is the largest domain of attraction that is theoretically achievable) system can be semi-globally stabilised by nonlinear feedbacks while satisfying the constraints. Moreover, the recoverable region for the given system is constructed by constructing the same, however, for a reduced-order subsystem of the given system. Such a reduction in the order or dimension of the system generally leads to a considerable simplification in the computational effort.     

Impact of a satellite-derived leaf area index monthly climatology in a global numerical weather prediction model

The leaf area index (LAI), defined as the one-sided green leaf area per unit ground area, is used in many numerical weather prediction (NWP) models as an indicator of the vegetation development state, which is of paramount importance to characterize land evaporation, photosynthesis, and carbon-uptake processes. LAI is often simply represented by lookup tables, dependent on the vegetation type and seasons. However, global LAI datasets derived from remote sensing observations have more recently become available. These products are based on sensors such as the Advanced Very High Resolution Radiometer (AVHRR) or the Moderate Resolution Imaging Spectroradiometer (MODIS), onboard polar orbiting satellites that can cover the entire globe within typically 3 days and with a spatial resolution of the order of 1 km.

We examine the meteorological impact of satellite-derived LAI products on near-surface air temperature and humidity, which comes both from the stomatal transpiration of leaves and from the intercepted water on the surface of leaves, re-evaporating into the atmosphere.

Two distinct monthly LAI climatology datasets derived respectively from AVHRR and MODIS sensors are tested. A set of forecasts and data assimilation experiments with the integrated forecasting system of the European Centre for Medium-range Weather Forecasts is performed with the monthly LAI climatology datasets as opposed to a vegetation-dependent constant LAI. The monthly LAI is shown to improve the forecasts of near-surface (screen-level) air temperature and relative humidity through its effect on evapotranspiration, with the largest impact obtained over needleleaf forests, crops, and grassland. At longer time-scales, the introduction of the monthly LAI is shown to have a positive impact on the model climate particularly during the boreal spring, where the LAI climatology has a large seasonal cycle.     

Performance of atmospheric and topographic correction methods on Landsat imagery in mountain areas

An effective removal of atmospheric and topographic effects on remote-sensing imagery is an essential preprocessing step for mapping land cover accurately in mountain areas. Various techniques that remove these effects have been proposed and consist of specific combinations of an atmospheric and a topographic correction (TC) method. However, it is possible to generate a wide range of new combined correction methods by applying alternative combinations of atmospheric and TC methods. At present, a systematic overview of the statistical performance and data input requirement of preprocessing techniques is missing. In order to assess the individual and combined impacts of atmospheric and TC methods, 15 permutations of two atmospheric and/or four TC methods were evaluated statistically and compared to the uncorrected imagery. Furthermore, results of the integrated ATCOR3 method were included. This evaluation was performed in a study area in the Romanian Carpathian mountains. Results showed that the combination of a transmittance-based atmospheric correction (AC), which corrects the effects of Rayleigh scattering and water-vapour absorption, and a pixel-based C or Minnaert TC, which account for diffuse sky irradiance, reduced the image distortions most efficiently. Overall results indicated that TC had a larger impact than AC and there was a trade-off between the statistical performance of preprocessing techniques and their data requirement. However, the normalized difference vegetation index analysis indicated that atmospheric methods resulted in a larger impact on the spectral information in bands 3 and 4.     

On the existence of virtual exosystems for synchronized linear networks

When dealing with heterogeneous networks, where the agents are governed by non-identical models, interesting questions arise regarding the ability of the network to synchronize to a common non-trivial output trajectory, as well as the nature of such a trajectory. On this topic, Wieland, Allgöwer, and Sepulchre have recently derived results showing that for a class of heterogeneous networks of dynamically controlled linear agents, non-trivial output synchronization implies the existence of an observable virtual exosystem for which the regulator equations are solvable for each agent. Moreover, this virtual exosystem defines the output trajectories on the agreement manifold and is contained within each agent as an internal model. In this paper, we shed further light on this topic by showing that, under a more general set of assumptions, non-trivial output synchronization can occur in the absence of such a virtual exosystem. We propose a modified result for this case that specifies the existence of a possibly unobservable virtual exosystem for which the regulator equations are solvable, and for which the observable part defines the output trajectories on the agreement manifold. We also show that a variation of the virtual exosystem is contained within each agent as an internal model.