Application of real-time fluorescent PCR for quantitative assessment of Neospora caninum infections in organotypic slice cultures of rat central nervous system tissue

The previously described Nc5-specific PCR test for the diagnosis of Neospora caninum infections was used to develop a quantitative PCR assay which allows the determination of infection intensities within different experimental and diagnostic sample groups. The quantitative PCR was performed by using a dual fluorescent hybridization probe system and the LightCycler Instrument for online detection of amplified DNA. This assay was successfully applied for demonstrating the parasite proliferation kinetics in organotypic slice cultures of rat brain which were infected in vitro with N. caninum tachyzoites. This PCR-based method of parasite quantitation with organotypic brain tissue samples can be regarded as a novel ex vivo approach for exploring different aspects of cerebral N. caninum infection.

Development of a new real-time polymerase chain reaction assay to detect Duck adenovirus A DNA and application to samples from Swiss poultry flocks.

Between 2008 and 2012, commercial Swiss layer and layer breeder flocks experiencing problems in laying performance were sampled and tested for infection with Duck adenovirus A (DAdV-A; previously known as Egg drop syndrome 1976 virus). Organ samples from birds sent for necropsy as well as blood samples from living animals originating from the same flocks were analyzed. To detect virus-specific DNA, a newly developed quantitative real-time polymerase chain reaction method was applied, and the presence of antibodies against DAdV-A was tested using a commercially available enzyme-linked immunosorbent assay. In 5 out of 7 investigated flocks, viral DNA was detected in tissues. In addition, antibodies against DAdV-A were detected in all of the flocks.

Design of envelope amplifier based on interleaved multiphase buck converter with minimum time control for RF application

In this paper, an interleaved multiphase buck converter with minimum time control strategy for envelope amplifiers in high efficiency RF power amplifiers is proposed. The solution for the envelope amplifier is to combine the proposed converter with a linear regulator in series. High efficiency of envelope amplifier can be obtained through modulating the supply voltage of the linear regulator. Instead of tracking the envelope, the buck converter has discrete output voltage that corresponding to particular duty cycles which achieve total ripple cancellation. The transient model for minimum time control is explained, and the calculation of transient times that are pre-calculated and inserted into a lookup table is presented. The filter design trade-off that limits capability of envelope modulation is also discussed. The experimental results verify the fast voltage transient obtained with a 4-phase buck prototype.

Minimum time control for multiphase buck converter: analysis and application

The combination of minimum time control and multiphase converter is a favorable option for dc-dc converters in applications where output voltage variation is required, such as RF amplifiers and dynamic voltage scaling in microprocessors, due to their advantage of fast dynamic response. In this paper, an improved minimum time control approach for multiphase buck converter that is based on charge balance technique, aiming at fast output voltage transition is presented. Compared with the traditional method, the proposed control takes into account the phase delay and current ripple in each phase. Therefore, by investigating the behavior of multiphase converter during voltage transition, it resolves the problem of current unbalance after the transient, which can lead to long settling time of the output voltage. The restriction of this control is that the output voltage that the converter can provide is related to the number of the phases, because only the duty cycles at which the multiphase converter has total ripple cancellation are used in this approach. The model of the proposed control is introduced, and the design constraints of the buck converters filter for this control are discussed. In order to prove the concept, a four-phase buck converter is implemented and the experimental results that validate the proposed control method are presented. The application of this control to RF envelope tracking is also presented in this paper.

Effects of irrigation and time of application on the yield and quality of cv. Cabernet sauvignon in a warm climate

Mediterranean climate is characterized by hot summer, high evapotranspiration rates, and scarce precipitations (400 mm per year) during grapevine cycle. These extremely dry conditions affect vineyard productivity and sustainability. Supplementary irrigation is a needed practice in order to maintain yield and quality. Almost all Spanish grape growing regions are characterized by these within this context, especially in the center region, where this study was performed. The main objective of this work was to study the influence of irrigation on yield and quality. For this aim, we applied different levels of irrigation (mm of water applied) during different stages of growth and berry maturity. Four experimental treatments were applied considering the amount of water and the moment of the application: T1: Water irrigation (420 mm) applied from bloom to maturity. T2: Corresponded to the traditional irrigation scheduling, from preveraison to maturity (154 mm). T3: Water irrigation from bloom to preveraison, and water deficit from veraison to maturity (312 mm). T4: Irrigation applied from preveraison to maturity (230 mm) Experimental vineyard, cv. Cabernet Sauvignon, was located in a commercial vineyard (Bodegas Licinia S.L.) in the hot region of Morata de Tajuña (Madrid). The trial was performed during 2010 and 2011 seasons. Our results showed that yield increased from 2010 to 2011 in the treatments with a higher amount of water appli ed, T1 and T3 (24 and 10 % of yield increase respectively). This was mainly due to an increase in bud fertility (nº of bunches per shoot). Furthermore, sugar content was higher in T3 (27.3 ºBrix), followed by T2 (27 ºBrix). By contrast, T4 (irrigation from veraison) presented the lowest solid soluble concentration and the highest acidity. These results suggest that grapevine has an intrinsic capacity to adapt to its environment. However, this adaptation capacity should be evaluated considering the sensibility of quality parameters during the maturity period (acidity, pH, aroma, color...) and its impact on yield. Here, we demonstrated that a higher amount of water irrigation applied was no linked to a negative effect on quality.

Real-time Surveillance Application by Multiple Detectors and Compressive Trackers

A real-time surveillance system for IP network cameras is presented. Motion, part-body, and whole-body detectors are efficiently combined to generate robust and fast detections, which feed multiple compressive trackers. The generated trajectories are then improved using a reidentification strategy for long term operation.

Event-based time series data preprocessing: application to traffic flow time series

Traffic flow time series data are usually high dimensional and very complex. Also they are sometimes imprecise and distorted due to data collection sensor malfunction. Additionally, events like congestion caused by traffic accidents add more uncertainty to real-time traffic conditions, making traffic flow forecasting a complicated task. This article presents a new data preprocessing method targeting multidimensional time series with a very high number of dimensions and shows its application to real traffic flow time series from the California Department of Transportation (PEMS web site). The proposed method consists of three main steps. First, based on a language for defining events in multidimensional time series, mTESL, we identify a number of types of events in time series that corresponding to either incorrect data or data with interference. Second, each event type is restored utilizing an original method that combines real observations, local forecasted values and historical data. Third, an exponential smoothing procedure is applied globally to eliminate noise interference and other random errors so as to provide good quality source data for future work.

A Dynamically Adaptable Image Processing Application Trading Off Between High Performance, Consumption and Dependability in Real Time

As embedded systems evolve, problems inherent to technology become important limitations. In less than ten years, chips will exceed the maximum allowed power consumption affecting performance, since, even though the resources available per chip are increasing, frequency of operation has stalled. Besides, as the level of integration is increased, it is difficult to keep defect density under control, so new fault tolerant techniques are required. In this demo work, a new dynamically adaptable virtual architecture (ARTICo3) to allow dynamic and context-aware use of resources is implemented in a high performance Wireless Sensor node (HiReCookie) to perform an image processing application.

Extended theory about the allocation of time: Description and application to the increase in the retirement age policies

This paper revises mainstream economic models which include time use in an explicit and endogenous manner, suggesting a extended theory which escape from the main problem existing in the literature. In order to do it, we start by presenting in section 2 the mainstream time use models in economics, showing their main features. Once this is done, we introduce the reader in the main problems this kind of well established models imply, within section 3, being the most highlighted the problem of joint production. Subsequently, we propose an extended theory which solves the problem of joint production; this is extensively described in section 4. Last, but not least, we apply this model to offer a time use analysis of the effect of a policy which increases the retirement age in a life-cycle perspective for a representative individual.

Real time optimization in chemical process: evaluation of strategies, improvements and industrial application.

The increasing economic competition drives the industry to implement tools that improve their processes efficiencies. The process automation is one of these tools, and the Real Time Optimization (RTO) is an automation methodology that considers economic aspects to update the process control in accordance with market prices and disturbances. Basically, RTO uses a steady-state phenomenological model to predict the process behavior, and then, optimizes an economic objective function subject to this model. Although largely implemented in industry, there is not a general agreement about the benefits of implementing RTO due to some limitations discussed in the present work: structural plant/model mismatch, identifiability issues and low frequency of set points update. Some alternative RTO approaches have been proposed in literature to handle the problem of structural plant/model mismatch. However, there is not a sensible comparison evaluating the scope and limitations of these RTO approaches under different aspects. For this reason, the classical two-step method is compared to more recently derivative-based methods (Modifier Adaptation, Integrated System Optimization and Parameter estimation, and Sufficient Conditions of Feasibility and Optimality) using a Monte Carlo methodology. The results of this comparison show that the classical RTO method is consistent, providing a model flexible enough to represent the process topology, a parameter estimation method appropriate to handle measurement noise characteristics and a method to improve the sample information quality. At each iteration, the RTO methodology updates some key parameter of the model, where it is possible to observe identifiability issues caused by lack of measurements and measurement noise, resulting in bad prediction ability. Therefore, four different parameter estimation approaches (Rotational Discrimination, Automatic Selection and Parameter estimation, Reparametrization via Differential Geometry and classical nonlinear Least Square) are evaluated with respect to their prediction accuracy, robustness and speed. The results show that the Rotational Discrimination method is the most suitable to be implemented in a RTO framework, since it requires less a priori information, it is simple to be implemented and avoid the overfitting caused by the Least Square method. The third RTO drawback discussed in the present thesis is the low frequency of set points update, this problem increases the period in which the process operates at suboptimum conditions. An alternative to handle this problem is proposed in this thesis, by integrating the classic RTO and Self-Optimizing control (SOC) using a new Model Predictive Control strategy. The new approach demonstrates that it is possible to reduce the problem of low frequency of set points updates, improving the economic performance. Finally, the practical aspects of the RTO implementation are carried out in an industrial case study, a Vapor Recompression Distillation (VRD) process located in Paulínea refinery from Petrobras. The conclusions of this study suggest that the model parameters are successfully estimated by the Rotational Discrimination method; the RTO is able to improve the process profit in about 3%, equivalent to 2 million dollars per year; and the integration of SOC and RTO may be an interesting control alternative for the VRD process.

Commercial policy in war time and after; a study of the application of democratic ideas to international commercial relations,

Reprinted in part from various periodicals.