Investigations on the leaf surface ultrastructure in grapevine (Vitis vinifera L.) by scanning microscopy

Several Scanning microscopy techniques were used to investigate the leaf surface ultrastructure in the local “Razegui” grapevine cultivar (Vitis vinifera L.). Conventional scanning electron microscopy performed on glutaraldehyde‐fixed samples allowed observation of well‐preserved epidermal cells with an overlaying waxy layer. At a high magnification, the waxy layer exhibited crystalline projections in the form of horizontal and vertical platelets. Also, to avoid eventual ultrastructural alterations inherent in the use of solvents during sample preparation, fresh leaf blade samples were directly observed by environmental scanning electron microscopy. A classical image of convex living epidermal cells was observed. At 2400× magnification, epicuticular waxes exhibited a granular structure. However, high‐magnification images were not obtained with this device. The atomic force microscopy (AFM) performed on fresh leaf blade samples allowed observation of a textured surface and heterogeneous profiles attributed to epicuticular wax deposits. AFM topography images confirmed further, the presence of irregular crystalloid wax projections as multishaped platelets on the adaxial surface of grapevine leaf. SCANNING 31: 127–131, 2009. © 2009 Wiley Periodicals, Inc.     

Whey protein concentrate hydrogels as bioactive carriers

Two sets of heat‐induced hydrogels were prepared from whey protein concentrate (WPC), one set at a constant concentration [15% (w/v)] and varying pHs (pH 5.1–10.0) and the other set at a constant pH (10.0) and varying concentrations (12%, 15%, and 18%). At a given pH, the higher the protein concentration, the shorter was the gelation time and the larger were the equilibrium storage modulus (G) and failure stress. For a given protein concentration, the gelation kinetics and mechanical properties of WPC hydrogels were strongly pH dependent. The swelling behavior of WPC gels was studied at 37.5°C ± 0.5°C. The equilibrium swelling ratio (SR) was at the minimum when pH of the swelling medium was close to the isoelectric point (pI) of the whey protein, and when the swelling medium pH was far from the pI (from 6.0 to 10.0), the SR increased. In particular, when the pH was higher than the pI, the swelling was highly pH sensitive. The higher the WPC concentration used in preparing the hydrogel, the lower was the SR. The controlled drug release properties of the WPC hydrogels were studied using caffeine as the model drug. Consistent with the swelling behavior of the gels, release was slower when the pH of the medium was lower (pH 1.8) than when it was higher (pH 7.5). The SR and the drug release rate decreased significantly when the gels were surface‐coated with alginate. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci, 2006     

Service level agreement in optical networks

This article proposes a Service Level Agreement applied to the optical domain (O-sla), which is expected to be the near and long term network technology thanks, among other things, to the great bandwidth capacity offered by optical devices. After an exposition of the rationale behind an optical sla, parameters which could enter in thisO-sla, as well as their values for four classes of services, are proposed. Different client (wavelength or sub-wavelength) and services types (from leased wavelength to bandwidth on demand) are distinguished when necessary.     

A Unified Artificial Neural Network Architecture for Active Power Filters

In this paper, an efficient and reliable neural active power filter (APF) to estimate and compensate for harmonic distortions from an AC line is proposed. The proposed filter is completely based on Adaline neural networks which are organized in different independent blocks. We introduce a neural method based on Adalines for the online extraction of the voltage components to recover a balanced and equilibrated voltage system, and three different methods for harmonic filtering. These three methods efficiently separate the fundamental harmonic from the distortion harmonics of the measured currents. According to either the Instantaneous Power Theory or to the Fourier series analysis of the currents, each of these methods are based on a specific decomposition. The original decomposition of the currents or of the powers then allows defining the architecture and the inputs of Adaline neural networks. Different learning schemes are then used to control the inverter to inject elaborated reference currents in the power system. Results obtained by simulation and their real-time validation in experiments are presented to compare the compensation methods. By their learning capabilities, artificial neural networks are able to take into account time-varying parameters, and thus appreciably improve the performance of traditional compensating methods. The effectiveness of the algorithms is demonstrated in their application to harmonics compensation in power systems     

A Classification Approach for an Accurate Analog/RF BIST Evaluation Based on the Process Parameters

Specifications of Radio Frequency (RF) analog integrated circuits have increased strictly as their applications tend to be more complicated and high test cost demanding. This makes them very expensive due to an increased test time and to the use of sophisticated test equipment. Alternative test measures, extracted by means of Built-In Self Test (BIST) techniques, are useful approaches to replace standard specification-based tests. One way to evaluate the efficiency of the CUT measures at the design stage is by estimating the Test Escapes (T _E ) and the Yield Loss (Y _L ) at ppm level. Unfortunately, an important number of Monte Carlo simulations must be run in order to guarantee their accuracy. For certain types of circuits, this requires many months or even years to generate millions of circuits. To overcome this limitation, we present in this paper a new technique where a small number of simulations is sufficient to reach an important precision. This method is based on a classification using machine learning methods, such as SVM and Neural Networks based classifiers to determine pass/fail regions. The proposed approach requires a few number of simulations only to determine the region separating the process parameters generating good and faulty, or pass and fail circuits. Then only this region is needed to estimate the test metrics without running any additional simulation. The proposed methodology is illustrated for the evaluation of a filter BIST technique.     

鱿鱼软骨壳聚糖的制备及其理化特性研究

以鱿鱼软骨为原料，研究碱液浓度、反应温度、反应时间等因素对甲壳素脱乙酰化的影响，得到较好的脱乙酰工艺，制得鱿鱼软骨壳聚糖，并对鱿鱼软骨壳聚糖的理化特性进行研究测定。结果表明：随着反应时间的延长、温度的升高以及NaOH浓度的增大，鱿鱼软骨壳聚糖的脱乙酰度增大；鱿鱼软骨壳聚糖具有较低的灰分含量、较强的黏性以及较高的水分和脂肪结合能力。红外分析表明：鱿鱼软骨壳聚糖为β-壳聚糖。