Composition of <Emphasis Type="Italic">Carlina acanthifolia</Emphasis> Root Essential Oil

The root of Carlina acanthifolia All. (Asteraceae) contained 1.0% of essential oil (expressed in g per 100 g of dried plant material). Using GC and GC/MS, nine components were identified (100% of total oil). The structure of benzyl 2-furylacetylene (carlina oxide), which is the principal component of the oil (91.5%), was spectrometrically identified. __________ Published in Khimiya Prirodnykh Soedinenii, No. 4, pp. 331–332, July–August, 2005.     

Potential Mitigation of Smoke Taint in Wines by Post-Harvest Ozone Treatment of Grapes

When bushfires occur near grape growing regions, vineyards can be exposed to smoke, and depending on the timing and duration of grapevine smoke exposure, fruit can become tainted. Smoke-derived volatile compounds, including volatile phenols, can impart unpleasant smoky, ashy characters to wines made from smoke-affected grapes, leading to substantial revenue losses where wines are perceivably tainted. This study investigated the potential for post-harvest ozone treatment of smoke-affected grapes to mitigate the intensity of smoke taint in wine. Merlot grapevines were exposed to smoke at ~7 days post-veraison and at harvest grapes were treated with 1 or 3 ppm of gaseous ozone (for 24 or 12 h, respectively), prior to winemaking. The concentrations of smoke taint marker compounds (i.e., free and glycosylated volatile phenols) were measured in grapes and wines to determine to what extent ozonation could mitigate the effects of grapevine exposure to smoke. The 24 h 1 ppm ozone treatment not only gave significantly lower volatile phenol and volatile phenol glycoside concentrations but also diminished the sensory perception of smoke taint in wine. Post-harvest smoke and ozone treatment of grapes suggests that ozone works more effectively when smoke-derived volatile phenols are in their free (aglycone) form, rather than glycosylated forms. Nevertheless, the collective results demonstrate the efficacy of post-harvest ozone treatment as a strategy for mitigation of smoke taint in wine.     

Mobility Tracking in Cellular Networks Using Particle Filtering

Mobility tracking based on data from wireless cellular networks is a key challenge that has been recently investigated both from a theoretical and practical point of view. This paper proposes Monte Carlo techniques for mobility tracking in wireless communication networks by means of received signal strength indications. These techniques allow for accurate estimation of mobile station's (MS) position and speed. The command process of the MS is represented by a first-order Markov model which can take values from a finite set of acceleration levels. The wide range of acceleration changes is covered by a set of preliminary determined acceleration values. A particle filter and a Rao-Blackwellised particle filter are proposed and their performance is evaluated both over synthetic and real data. A comparison with an extended Kalman filter (EKF) is performed with respect to accuracy and computational complexity. With a small number of particles the RBPF gives more accurate results than the PF and the EKF. A posterior Cramer Rao lower bound (PCRLB) is calculated and it is compared with the filters' root- mean-square error performance.     

Improvement of visual perceptual capabilities by feedback structures for robotic system FRIEND

The main aim behind the design of rehabilitation robotic systems is to support disabled people in daily life situations as well as in the working environment. This requires the autonomous execution of different tasks. In order to achieve the ability of the robotic system to operate autonomously, the sensor system for the scene observation providing the necessary inputs for the manipulator control is essential. In this paper, the main emphasis is on the development and integration of the closed-loop controls at the visual sensory input level in order to increase the robustness of the vision-based system control. Moreover, the integration of additional sensors in order to support the vision system and to increase the reliability of the whole robotic system is discussed.     

A design of waveguide collimating lenses in the presence ofanisotropic aberrations

Anisotropic aberration correction is discussed on the basis of the extraordinary-ray ray-tracing method. Two closed analytical forms of anisotropic-aberration-free profiles are derived. The two profiles are referred to as pseudoelliptic and pseudohyperbolic, and a comparison is made between the two surfaces. The latter profiles are aberration-free in an isotropic medium. A design limit in the aperture angle is investigated. The relationship between the aperture and the energy reflection coefficient is investigated using the Fresnel formula. The pseudo-hyperbolic surface has a lower energy reflection coefficient in focusing and the pseudo-elliptic surface has a lower energy reflection coefficient in collimating     

A lateral magnetotransistor structure with a linear response to themagnetic field

An experimental study and analytical model of a novel magnetotransistor are presented. This device displays some very promising features. A linear response to the magnetic field is experimentally demonstrated and very high sensitivities are measured, on the order of 3000%/T. Previous comparable magnetotransistors have reported sensitivities on the order of 150%/T. A theoretical explanation of the very high sensitivity is proposed, involving carrier deflection as the dominant operating principle     

Soil stress and compaction effects for four tractor tyres

Compaction effects and soil stresses were examined for four tractor tyres under three inflation pressures: 67, 100 and 150% of the recommended pressure. The four tyres were 18.4 R 38, 520/70 R 38, 600/65 R 38 and 650/60-38 and they carried a wheel load of 2590 kg. The 650/60-38 was a bias-ply tyre while the other three were radial tyres. Increased inflation pressure significantly increased all measured parameters: rut depth, penetration resistance and soil stress at 20 and 40 cm depth. The 18.4 R 38 caused a greater rut depth and penetration resistance than the other tyres, which did not differ significantly from each other. The soil stress was highest for the 18.4 R 38, followed by the 650/60-38. The low-profile tyres decreased compaction compared with the 18.4–38 tyre, mainly by allowing a lower inflation pressure. The use of low-profile tyres did not reduce compaction if not used at a lower inflation pressure. The bias-ply tyre caused a higher stress in the soil than the radial tyres when used with the same inflation pressure, but the compaction effects in terms of rut depth and penetration resistance were not greater for this tyre than for the radial low-profile tyres.     

Bayesian Multi-Object Filtering With Amplitude Feature Likelihood for Unknown Object SNR

In many tracking scenarios, the amplitude of target returns are stronger than those coming from false alarms. This information can be used to improve the multiple-target state estimation by obtaining more accurate target and false-alarm likelihoods. Target amplitude feature is well known to improve data association in conventional tracking filters, such as probabilistic data association and multiple hypothesis tracking, and results in better tracking performance of low signal-to-noise ratio (SNR) targets. The advantage of using the target amplitude approach is that targets can be identified earlier through the enhanced discrimination between target and false alarms. One of the limitations of this approach is that it is usually assumed that the SNR of the target is known. We show that the reliable estimation of the SNR requires a significant number of measurements, and so we propose an alternative approach for situations where the SNR is unknown. We illustrate this approach in the context of multiple targets for different SNRs in the framework of finite set statistics (FISST). Furthermore, we illustrate how this can be incorporated into approximate multiple-object filters derived from FISST, including probability hypothesis density (PHD) and cardinalized PHD (CPHD) filters. We present simulation results for Gaussian mixture implementations of the filters that demonstrate a significant improvement in performance over just using location measurements.