The sample processing time interval as an influential factor in flow cytometry analysis of lymphocyte subsets

The objective of this paper is to propose a protocol to analyze blood samples in yellow fever 17DD vaccinated which developed serious adverse events. We investigated whether or not the time between sample collection and sample processing could interfere in lymphocyte subset percentage, for it is often impossible to analyze blood samples immediately after collection due to transport delay from collection places to the flow cytometry facility. CD4+CD38+ T, CD8+CD38+ T, CD3+ T, CD19+ B lymphocyte subsets were analyzed by flow cytometry in nine healthy volunteers immediately after blood collection and after intervals of 24 and 48 h. The whole blood lysis method and gradient sedimentation by Histopaque were applied to isolate peripheral blood mononuclear cells for flow cytometry analyses. With the lysis method, there was no significant change in lymphocyte subset percentage between the two time intervals (24 and 48 h). In contrast, when blood samples were processed by Histopaque gradient sedimentation, time intervals for sample processing influenced the percentage in T lymphocyte subsets but not in B cells. From the results obtained, we could conclude that the whole blood lysis method is more appropriate than gradient sedimentation by Histopaque for immunophenotyping of blood samples collected after serious adverse events, due to less variation in the lymphocyte subset levels with respect to the time factor.

Nonlinear estimation of neural processing time from BOLD signal with application to decision-making

The extraction of information about neural activity timing from BOLD signal is a challenging task as the shape of the BOLD curve does not directly reflect the temporal characteristics of electrical activity of neurons. In this work, we introduce the concept of neural processing time (NPT) as a parameter of the biophysical model of the hemodynamic response function (HRF). Through this new concept we aim to infer more accurately the duration of neuronal response from the highly nonlinear BOLD effect. The face validity and applicability of the concept of NPT are evaluated through simulations and analysis of experimental time series. The results of both simulation and application were compared with summary measures of HRF shape. The experiment that was analyzed consisted of a decision-making paradigm with simultaneous emotional distracters. We hypothesize that the NPT in primary sensory areas, like the fusiform gyrus, is approximately the stimulus presentation duration. On the other hand, in areas related to processing of an emotional distracter, the NPT should depend on the experimental condition. As predicted, the NPT in fusiform gyrus is close to the stimulus duration and the NPT in dorsal anterior cingulate gyrus depends on the presence of an emotional distracter. Interestingly, the NPT in right but not left dorsal lateral prefrontal cortex depends on the stimulus emotional content. The summary measures of HRF obtained by a standard approach did not detect the variations observed in the NPT. Hum Brain Mapp, 2012. (C) 2010 Wiley Periodicals, Inc.

Sequencing Jobs with Uncertain Processing Times and Minimizing the Weighted Total Flow Time

We consider an uncertain version of the scheduling problem to sequence set of jobs J on a single machine with minimizing the weighted total flow time, provided that processing time of a job can take on any real value from the given closed interval. It is assumed that job processing time is unknown random variable before the actual occurrence of this time, where probability distribution of such a variable between the given lower and upper bounds is unknown before scheduling. We develop the dominance relations on a set of jobs J. The necessary and sufficient conditions for a job domination may be tested in polynomial time of the number n = |J| of jobs. If there is no a domination within some subset of set J, heuristic procedure to minimize the weighted total flow time is used for sequencing the jobs from such a subset. The computational experiments for randomly generated single-machine scheduling problems with n ≤ 700 show that the developed dominance relations are quite helpful in minimizing the weighted total flow time of n jobs with uncertain processing times.

Thermoplastic starch modified during melt processing with organic acids: The effect of molar mass on thermal and mechanical properties

Thermoplastic starch (TPS) was modified with ascorbic acid and citric acid by melt processing of native starch with glycerol as plasticizer in an intensive batch mixer at 160 degrees C. It was found that the molar mass decreases with acid content and processing time causing the reduction in melting temperature (T(m)). As observed by the results of X-ray diffraction and DSC measurements, crystallinity was not changed by the reaction with organic acids. T(m) depression with falling molar mass was interpreted on the basis of the effect of concentration of end-chain units, which act as diluents. FTIR did not show any appreciable change in starch chemical compositions, leading to the conclusion that the main changes observed were produced by the variation in molar mass of the material. We demonstrated that it is possible to decrease melt viscosity without the need for more plasticizer thus avoiding side-effects such as an increase in water affinity or relevant changes in the dynamic mechanical properties. (C) 2010 Elsevier B.V. All rights reserved.

Effect of the processing conditions and the addition of trans-polyoctenylene rubber on the properties of natural rubber/styrene-butadiene rubber blends

In this study, the influence of the processing conditions and the addition of trans-polyoctenylene rubber (TOR) on Mooney viscosity, tensile properties, hardness, tearing resistance, and resilience of natural rubber/styrene-butadiene rubber blends was investigated. The results obtained are explained in light of dynamic mechanical and morphological analyses. Increasing processing time produced a finer blend morphology, which resulted in an improvement in the mechanical properties. The addition of TOR involved an increase in hardness, a decrease in tear resistance, and no effect on the resilience. It resulted in a large decrease in the Mooney viscosity and a slight decrease in the tensile properties if the components of the compounds were not properly mixed. The results indicate that TOR acted more as a plasticizer than a compatibilizer. (c) 2008 Wiley Periodicals, Inc.

Time-domain optimization of amplifiers based on distributed genetic algorithms

Thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Electrical and Computer Engineering

Time diversity solutions to cope with lost packets

A dissertation submitted to Departamento de Engenharia Electrotécnica of Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Engenharia Electrotécnica e de Computadores

UAV - based imagery processing using structure from motion and remote sensing technology

With the recent advances in technology and miniaturization of devices such as GPS or IMU, Unmanned Aerial Vehicles became a feasible platform for a Remote Sensing applications. The use of UAVs compared to the conventional aerial platforms provides a set of advantages such as higher spatial resolution of the derived products. UAV - based imagery obtained by a user grade cameras introduces a set of problems which have to be solved, e. g. rotational or angular differences or unknown or insufficiently precise IO and EO camera parameters. In this work, UAV - based imagery of RGB and CIR type was processed using two different workflows based on PhotoScan and VisualSfM software solutions resulting in the DSM and orthophoto products. Feature detection and matching parameters influence on the result quality as well as a processing time was examined and the optimal parameter setup was presented. Products of the both workflows were compared in terms of a quality and a spatial accuracy. Both workflows were compared by presenting the processing times and quality of the results. Finally, the obtained products were used in order to demonstrate vegetation classification. Contribution of the IHS transformations was examined with respect to the classification accuracy.

Introducing the concept of critical Fo in batch heat processing

The determination of the sterilization value for low acid foods in retorts includes a critical evaluation of the factory's facilities and utilities, validation of the heat processing equipment (by heat distribution assays), and finally heat penetration assays with the product. The intensity of the heat process applied to the food can be expressed by the Fo value (sterilization value, in minutes, at a reference temperature of 121.1 °C, and a thermal index, z, of 10 °C, for Clostridium botulinum spores). For safety reasons, the lowest value for Fo is frequently adopted, being obtained in heat penetration assays as indicative of the minimum process intensity applied. This lowest Fo value should always be higher than the minimum Fo recommended for the food in question. However, the use of the Fo value for the coldest can fail to statistically explain all the practical occurrences in food heat treatment processes. Thus, as a result of intense experimental work, we aimed to develop a new focus to determine the lowest Fo value, which we renamed the critical Fo. The critical Fo is based on a statistical model for the interpretation of the results of heat penetration assays in packages, and it depends not only on the Fo values found at the coldest point of the package and the coldest point of the equipment, but also on the size of the batch of packages processed in the retort, the total processing time in the retort, and the time between CIPs of the retort. In the present study, we tried to explore the results of physical measurements used in the validation of food heat processes. Three examples of calculations were prepared to illustrate the methodology developed and to introduce the concept of critical Fo for the processing of canned food.

Changes in guava (Psidium guajava L. var. Paluma) nectar volatile compounds concentration due to thermal processing and storage

Guava nectars were formulated for approximately 10, 12, or 14 ºBrix, with 40% guava pulp. Sodium benzoate, 500 mg.kg-1 was used as preservative. The Brix value was adjusted with saturated sucrose syrup. The guava nectar was pasteurized (85 ºC/42 seconds) in tubular heat exchanger and then hot filled in 500 mL white glass bottles. The products were stored either at room temperature (25 ± 5 ºC) or refrigerated (5 ± 2 ºC) under fluorescent light exposure and analyzed on the day after processing (time zero) and also 40, 80, and 120 days of storage. Eight compounds were identified and quantified by Gas Chromatography (GC) -Mass Spectrometry (MS): hexanal, (E)-hex-2-enal, 1-hexenol, (Z)-hex-3-enol, (Z)-hex-3-enyl acetate, phenyl-3-propyl acetate, cinnamyl acetate, and acetic acid. There was no significant effect of thermal treatment on the volatile compound concentrations, except for a significant decrease (p = 0.0001) in hexanal and (Z)-hex-3-enyl acetate (p = 0.0029). As for the storage time, there was a much greater decrease in the esters contents, such as (Z)-hex-3-enyl and phenyl-3-propyl acetates. Cinnamyl acetate had the greatest decrease over storage time. Refrigeration was better than room temperature for guava nectar volatile compounds stability over storage time, mainly for esters compounds, which are important for the product aroma and flavor

Development of Time - Frequency Techniques for Sonar Applications

Sonar signal processing comprises of a large number of signal processing algorithms for implementing functions such as Target Detection, Localisation, Classification, Tracking and Parameter estimation. Current implementations of these functions rely on conventional techniques largely based on Fourier Techniques, primarily meant for stationary signals. Interestingly enough, the signals received by the sonar sensors are often non-stationary and hence processing methods capable of handling the non-stationarity will definitely fare better than Fourier transform based methods.Time-frequency methods(TFMs) are known as one of the best DSP tools for nonstationary signal processing, with which one can analyze signals in time and frequency domains simultaneously. But, other than STFT, TFMs have been largely limited to academic research because of the complexity of the algorithms and the limitations of computing power. With the availability of fast processors, many applications of TFMs have been reported in the fields of speech and image processing and biomedical applications, but not many in sonar processing. A structured effort, to fill these lacunae by exploring the potential of TFMs in sonar applications, is the net outcome of this thesis. To this end, four TFMs have been explored in detail viz. Wavelet Transform, Fractional Fourier Transfonn, Wigner Ville Distribution and Ambiguity Function and their potential in implementing five major sonar functions has been demonstrated with very promising results. What has been conclusively brought out in this thesis, is that there is no "one best TFM" for all applications, but there is "one best TFM" for each application. Accordingly, the TFM has to be adapted and tailored in many ways in order to develop specific algorithms for each of the applications.

Scaling up data mining techniques to large datasets using parallel and distributed processing

Advances in hardware and software technology enable us to collect, store and distribute large quantities of data on a very large scale. Automatically discovering and extracting hidden knowledge in the form of patterns from these large data volumes is known as data mining. Data mining technology is not only a part of business intelligence, but is also used in many other application areas such as research, marketing and financial analytics. For example medical scientists can use patterns extracted from historic patient data in order to determine if a new patient is likely to respond positively to a particular treatment or not; marketing analysts can use extracted patterns from customer data for future advertisement campaigns; finance experts have an interest in patterns that forecast the development of certain stock market shares for investment recommendations. However, extracting knowledge in the form of patterns from massive data volumes imposes a number of computational challenges in terms of processing time, memory, bandwidth and power consumption. These challenges have led to the development of parallel and distributed data analysis approaches and the utilisation of Grid and Cloud computing. This chapter gives an overview of parallel and distributed computing approaches and how they can be used to scale up data mining to large datasets.

Real-Time Recognition System for Traffic Signs

The aim of this thesis project is to develop the Traffic Sign Recognition algorithm for real time. Inreal time environment, vehicles move at high speed on roads. For the vehicle intelligent system itbecomes essential to detect, process and recognize the traffic sign which is coming in front ofvehicle with high relative velocity, at the right time, so that the driver would be able to pro-actsimultaneously on instructions given in the Traffic Sign. The system assists drivers about trafficsigns they did not recognize before passing them. With the Traffic Sign Recognition system, thevehicle becomes aware of the traffic environment and reacts according to the situation.The objective of the project is to develop a system which can recognize the traffic signs in real time.The three target parameters are the system’s response time in real-time video streaming, the trafficsign recognition speed in still images and the recognition accuracy. The system consists of threeprocesses; the traffic sign detection, the traffic sign recognition and the traffic sign tracking. Thedetection process uses physical properties of traffic signs based on a priori knowledge to detect roadsigns. It generates the road sign image as the input to the recognition process. The recognitionprocess is implemented using the Pattern Matching algorithm. The system was first tested onstationary images where it showed on average 97% accuracy with the average processing time of0.15 seconds for traffic sign recognition. This procedure was then applied to the real time videostreaming. Finally the tracking of traffic signs was developed using Blob tracking which showed theaverage recognition accuracy to 95% in real time and improved the system’s average response timeto 0.04 seconds. This project has been implemented in C-language using the Open Computer VisionLibrary.

The quiet eye without a target: The primacy of visual information processing

Motor-performance-enhancing effects of long final fixations before movement initiation – a phenomenon called Quiet Eye (QE) – have repeatedly been demonstrated. Drawing on the information-processing framework, it is assumed that the QE supports information processing revealed by the close link between QE duration and task demands concerning, in particular, response selection and movement parameterisation. However, the question remains whether the suggested mechanism also holds for processes referring to stimulus identification. Thus, in a series of two experiments, performance in a targeting task was tested as a function of experimentally manipulated visual processing demands as well as experimentally manipulated QE durations. The results support the suggested link because a performance-enhancing QE effect was found under increased visual processing demands only: Whereas QE duration did not affect performance as long as positional information was preserved (Experiment 1), in the full vs. no target visibility comparison, QE efficiency turned out to depend on information processing time as soon as the interval falls below a certain threshold (Experiment 2). Thus, the results rather contradict alternative, e.g., posture-based explanations of QE effects and support the assumption that the crucial mechanism behind the QE phenomenon is rooted in the cognitive domain.

Enhanced iron gettering by short, optimized low-temperature annealing after phosphorus emitter diffusion for industrial silicon solar cell processing

The introduction of a low-temperature (LT) tail after P emitter diffusion was shown to lead to considerable improvements in electron lifetime and solar cell performance by different researchers. So far, the drawback of the investigated extended gettering treatments has been the lack of knowledge about optimum annealing times and temperatures and the important increase in processing time. In this manuscript, we calculate optimum annealing temperatures of Fe-contaminated Si wafers for different annealing durations. Subsequently, it is shown theoretically and experimentally that a relatively short LT tail of 15 min can lead to a significant reduction of interstitial Fe and an increase in electron lifetime. Finally, we calculate the potential improvement of solar cell efficiency when such a short-tail extended P diffusion gettering is included in an industrial fabrication process.