Dipyridamole technetium-99m Sestamibi imaging in the diagnosis of syndrome X

In a middle-aged woman with anginal chest pain and a normal-appearing angiogram, dypiridamole technetium-99m Sestamibi scintigraphy, a noninvasive method, provided the diagnosis of syndrome X and was used in follow-up to monitor the course of disease.     

Optimal-tuning PID control of adaptive materials for structural efficiency

The objective of this paper was solving the optimization problem of lightweight stiffened structures modelled as a two-dimensional domain in an efficient computational way. The underlying premise was that mass should be distributed in an efficient way, so as to use a minimum amount of material to accomplish the mechanical function. This premise was expressed as a global, multi-objective optimization problem in which stiffness and mass were conflicting objectives. Alternative local evolution rules were implemented to update mass density or Young’s modulus at each step of the iterative procedure. The solution of the structural optimization problem was accomplished by a novel automatic procedure consisting of two consecutive stages of control and optimization. In the first stage of Proportional Integral Derivative (PID) control gains were manually selected whereas in the second stage the finding of optimal values of control gains, target, and cost indices was allowed. In this study a bone-like material was adopted and a thin slab was analysed as a sample problem.     

Persistent ocean monitoring with underwater gliders: Adapting sampling resolution

Ocean processes are dynamic and complex and occur on multiple spatial and temporal scales. To obtain a synoptic view of such processes, ocean scientists collect data over long time periods. Historically, measurements were continually provided by fixed sensors, e.g., moorings, or gathered from ships. Recently, an increase in the utilization of autonomous underwater vehicles has enabled a more dynamic data acquisition approach. However, we still do not utilize the full capabilities of these vehicles. Here we present algorithms that produce persistent monitoring missions for underwater vehicles by balancing path following accuracy and sampling resolution for a given region of interest, which addresses a pressing need among ocean scientists to efficiently and effectively collect high‐value data. More specifically, this paper proposes a path planning algorithm and a speed control algorithm for underwater gliders, which together give informative trajectories for the glider to persistently monitor a patch of ocean. We optimize a cost function that blends two competing factors: maximize the information value along the path while minimizing deviation from the planned path due to ocean currents. Speed is controlled along the planned path by adjusting the pitch angle of the underwater glider, so that higher resolution samples are collected in areas of higher information value. The resulting paths are closed circuits that can be repeatedly traversed to collect long‐term ocean data in dynamic environments. The algorithms were tested during sea trials on an underwater glider operating off the coast of southern California, as well as in Monterey Bay, California. The experimental results show improvements in both data resolution and path reliability compared to previously executed sampling paths used in the respective regions. © 2011 Wiley Periodicals, Inc.     

Sensitivity analysis of the rice model WARM in Europe: Exploring the effects of different locations,climates and methods of analysis on model sensitivity to crop parameters

Sensitivity analysis studies how the variation in model outputs can be due to different sources of variation. This issue is addressed, in this study, as an application of sensitivity analysis techniques to a crop model in the Mediterranean region. In particular, an application of Morris and Sobol' sensitivity analysis methods to the rice model WARM is presented. The output considered is aboveground biomass at maturity, simulated at five rice districts of different countries (France, Greece, Italy, Portugal, and Spain) for years characterized by low, intermediate, and high continentality. The total effect index of Sobol' (that accounts for the total contribution to the output variation due a given parameter) and two Morris indices (mean μ and standard deviation σ of the ratios output changes/parameter variations) were used as sensitivity metrics. Radiation use efficiency (RUE), optimum temperature (T_opt), and leaf area index at emergence (LAI_ini) ranked in most of the combinations site × year as first, second and third most relevant parameters. Exceptions were observed, depending on the sensitivity method (e.g. LAI_ini resulted not relevant by the Morris method), or site-continentality pattern (e.g. with intermediate continentality in Spain, LAI_ini and T_opt were second and third ranked; with low continentality in Portugal, RUE was outranked by T_opt). Low σ values associated with the most relevant parameters indicated limited parameter interactions. The importance of sensitivity analyses by exploring site × climate combinations is discussed as pre-requisite to evaluate either novel crop-modelling approaches or the application of known modelling solutions to conditions not explored previously. The need of developing tools for sensitivity analysis within the modelling environment is also emphasized.     

Water diffusion in polymer nano-films measured with microcantilevers

We present a method to measure the absorption of water molecules from the liquid and the vapour phase into polymer nano-films and the diffusion inside these films. Film thickness can be down to 45 nm. To demonstrate the possibilities of this method we use polymer films that are deposited on the upper side of a silicon cantilever by plasma polymerization of norbornene. When a microdrop of water is deposited onto the initially straight cantilever, the drop causes the cantilever to bend while it evaporates. Evaporation of such small water drops usually takes less than a second. An upwards bending is due to capillary forces and a downwards bending is due to the diffusion of water into the polymer film – and the consequent volume expansion (swelling) of the film. The magnitude of the capillary forces and the extent of swelling continuously change during drop evaporation. When drop evaporation is over the cantilever returns to its initial straight position. We simulate the time dependent bending with a numerical model that qualitatively agrees with the experiment. From the time dependence of cantilever bending we are able to determine the diffusion coefficient of water in the thin polymer film.     

Vanadia doped tungsten-titania SCR catalysts as functional materials for exhaust gas sensor applications

Urea-SCR systems (selective catalytic reduction) are required to meet future NO_x emission standards of heavy-duty and light-duty vehicles. It is a key factor to control the SCR systems and to monitor the catalysts’ functionalities to achieve low emissions. The novel idea of this study is to apply commercially available SCR catalyst materials based on vanadia-doped tungsten-titania as gas sensing films for impedimetric thick-film exhaust gas sensor devices. The dependence of the impedance on the surrounding gas atmosphere, especially on the concentrations of NH₃ and NO₂, is investigated, as well as cross interferences from other components of the exhaust. The sensors provide a good NH₃ sensitivity at 500 °C. The sensor behavior is explained in light of the literature combining the fields of catalysts and semiconducting gas sensors.     

Selective voltammetric determination of electroactive neuromodulating species in biological samples using iron(II) phthalocyanine modified multi-wall carbon nanotubes paste electrode

Iron(II) phthalocyanine (FePc) modified multi-wall carbon nanotubes paste electrodes (MWCNTPEs) were used as voltammetric sensors to selectively detect dopamine (DA) in the presence of serotonin (5-HT). The electrochemical behavior of DA at the new modified electrode was investigated using CV. The enhanced current response of DA indicates that FePc modification of the MWCNTPE surface results in a high catalytic activity for the redox reaction of DA. Differential pulse voltammetry was applied in detection of DA and 5-HT at FePc-MWCNTPE. The method parameters were optimized. Detection limit of 2.05 × 10⁻⁷ M was obtained for DA by using the electrocatalytic oxidation signal corresponding to the Fe^II/Fe^III redox process. The separation between the peak potentials of DA and 5-HT is 170 mV which is large enough for the simultaneously, selective determination of the two chemical species in their mixtures. There was no electrochemical response for ascorbic acid (AA) added in the sample. The monoamine neurotransmitter measuring method has been tested in analyzing deproteinized serum samples.     

Indoor robot gardening: design and implementation

This paper describes the architecture and implementation of a distributed autonomous gardening system with applications in urban/indoor precision agriculture. The garden is a mesh network of robots and plants. The gardening robots are mobile manipulators with an eye-in-hand camera. They are capable of locating plants in the garden, watering them, and locating and grasping fruit. The plants are potted cherry tomatoes enhanced with sensors and computation to monitor their well-being (e.g. soil humidity, state of fruits) and with networking to communicate servicing requests to the robots. By embedding sensing, computation, and communication into the pots, task allocation in the system is de-centrally coordinated, which makes the system scalable and robust against the failure of a centralized agent. We describe the architecture of this system and present experimental results for navigation, object recognition, and manipulation as well as challenges that lie ahead toward autonomous precision agriculture with multi-robot teams.     

Action Recognition Using a Bio-Inspired Feedforward Spiking Network

We propose a bio-inspired feedforward spiking network modeling two brain areas dedicated to motion (V1 and MT), and we show how the spiking output can be exploited in a computer vision application: action recognition. In order to analyze spike trains, we consider two characteristics of the neural code: mean firing rate of each neuron and synchrony between neurons. Interestingly, we show that they carry some relevant information for the action recognition application. We compare our results to Jhuang et al. (Proceedings of the 11th international conference on computer vision, pp. 1–8, 2007) on the Weizmann database. As a conclusion, we are convinced that spiking networks represent a powerful alternative framework for real vision applications that will benefit from recent advances in computational neuroscience.