Yellow fever vaccine induces integrated multilineage and polyfunctional immune responses.

Correlates of immune-mediated protection to most viral and cancer vaccines are still unknown. This impedes the development of novel vaccines to incurable diseases such as HIV and cancer. In this study, we have used functional genomics and polychromatic flow cytometry to define the signature of the immune response to the yellow fever (YF) vaccine 17D (YF17D) in a cohort of 40 volunteers followed for up to 1 yr after vaccination. We show that immunization with YF17D leads to an integrated immune response that includes several effector arms of innate immunity, including complement, the inflammasome, and interferons, as well as adaptive immunity as shown by an early T cell response followed by a brisk and variable B cell response. Development of these responses is preceded, as demonstrated in three independent vaccination trials and in a novel in vitro system of primary immune responses (modular immune in vitro construct [MIMIC] system), by the coordinated up-regulation of transcripts for specific transcription factors, including STAT1, IRF7, and ETS2, which are upstream of the different effector arms of the immune response. These results clearly show that the immune response to a strong vaccine is preceded by coordinated induction of master transcription factors that lead to the development of a broad, polyfunctional, and persistent immune response that integrates all effector cells of the immune system.

Investigating a dynamic modular framework for subjective well-being

According to Diener (1984), the three primary components of subjective well-being (SWB) are high life satisfaction (LS), frequent positive affect (P A), and infrequent negative affect (NA). The present dissertation extends previous research and theorizing on SWB by testing an innovative framework developed by Shmotkin (2005) in which SWB is conceptualized as an agentic process that promotes and maintains positive functioning. Two key components ofShmotkin's framework were explored in a longitudinal study of university students. In Part 1, SWB was examined as an integrated system of components organized within individuals. Using cluster analysis, five distinct configurations of LS, P A, and NA were identified at each wave. Individuals' SWB configurations were moderately stable over time, with the highest and lowest stabilities observed among participants characterized by "high SWB" and "low SWB" configurations, respectively. Changes in SWB configurations in the direction of a high SWB pattern, and stability among participants already characterized by high SWB, coincided with better than expected mental, physical, and interpersonal functioning over time. More positive levels of functioning and improvements in functioning over time discriminated among SWB configurations. However, prospective effects of SWB configurations on subsequent functioning were not observed. In Part 2, subjective temporal perspective "trajectories" were examined based on individuals' ratings of their past, present, and anticipated future LS. Upward subjective LS trajectories were normative at each wave. Cross-sectional analyses revealed consistent associations between upward subjective trajectories and lower levels of LS, as well as less positive mental, physical, and interpersonal functioning. Upward subjective LS trajectories were biased both with respect to underestimation of past LS and overestimation of future LS, demonstrating their illusional nature. Further, whereas more negative retrospective bias was associated with greater current distress and dysfunction, more positive prospective bias was associated with less positive functioning in the future. Prospective relations, however, were not consistently observed. Thus, steep upward subjective LS trajectory appeared to be a form of wishful-thinking, rather than an adaptive form of selfenhancement. Major limitations and important directions for future research are considered. Implications for Shmotkin's (2005) framework, and for research on SWB more generally, also are discussed

Dynamic bandwidth management as part of an integrated network management system based on distributed agents

We present a system for dynamic network resource configuration in environments with bandwidth reservation and path restoration mechanisms. Our focus is on the dynamic bandwidth management results, although the main goal of the system is the integration of the different mechanisms that manage the reserved paths (bandwidth, restoration, and spare capacity planning). The objective is to avoid conflicts between these mechanisms. The system is able to dynamically manage a logical network such as a virtual path network in ATM or a label switch path network in MPLS. This system has been designed to be modular in the sense that in can be activated or deactivated, and it can be applied only in a sub-network. The system design and implementation is based on a multi-agent system (MAS). We also included details of its architecture and implementation

An integrated model of soil-canopy spectral radiances, photosynthesis, fluorescence, temperature and energy balance

This paper presents the model SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes), which is a vertical (1-D) integrated radiative transfer and energy balance model. The model links visible to thermal infrared radiance spectra (0.4 to 50 μm) as observed above the canopy to the fluxes of water, heat and carbon dioxide, as a function of vegetation structure, and the vertical profiles of temperature. Output of the model is the spectrum of outgoing radiation in the viewing direction and the turbulent heat fluxes, photosynthesis and chlorophyll fluorescence. A special routine is dedicated to the calculation of photosynthesis rate and chlorophyll fluorescence at the leaf level as a function of net radiation and leaf temperature. The fluorescence contributions from individual leaves are integrated over the canopy layer to calculate top-of-canopy fluorescence. The calculation of radiative transfer and the energy balance is fully integrated, allowing for feedback between leaf temperatures, leaf chlorophyll fluorescence and radiative fluxes. Leaf temperatures are calculated on the basis of energy balance closure. Model simulations were evaluated against observations reported in the literature and against data collected during field campaigns. These evaluations showed that SCOPE is able to reproduce realistic radiance spectra, directional radiance and energy balance fluxes. The model may be applied for the design of algorithms for the retrieval of evapotranspiration from optical and thermal earth observation data, for validation of existing methods to monitor vegetation functioning, to help interpret canopy fluorescence measurements, and to study the relationships between synoptic observations with diurnally integrated quantities. The model has been implemented in Matlab and has a modular design, thus allowing for great flexibility and scalability.

Dynamic data reconciliation for sequential modular simulators: application to a mixing process

This paper describes a method for dynamic data reconciliation of nonlinear systems that are simulated using the sequential modular approach, and where individual modules are represented by a class of differential algebraic equations. The estimation technique consists of a bank of extended Kalman filters that are integrated with the modules. The paper reports a study based on experimental data obtained from a pilot scale mixing process.

Analysis an development of a prototype based on media wiki and semantic media wiki integrated with a design modeling that allows modeling of organizations based on demo

In a world where organizations are ever more complex the need for the knowledge of the organizational self is a growing necessity. The DEMO methodology sets a goal in achieving the specification of the organizational self capturing the essence of the organization in way independent of its implementation and also coherent, consistent, complete, modular and objective. But having such organization self notion is of little meaning if this notion is not shared by the organization actors. To achieve this goal in a society that has grown attached to technology and where time is of utmost importance, using a tool such as a semantic Wikipedia may be the perfect way of making the information accessible. However, to establish DEMO methodology in such platform there is a need to create bridges between its modeling components and semantic Wikipedia. It’s in that aspect that our thesis focuses, trying to establish and implement, using a study case, the principles of a way of transforming the DEMO methodology diagrams in comprehensive pages on semantic Wikipedia but keeping them as abstract as possible to allow expansibility and generalization to all diagrams without losing any valuable information so that, if that is the wish, those diagrams may be recreated from the semantic pages and make this process a full cycle.

Optimized design of substrate-integrated hollow waveguides for mid-infrared gas analyzers

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Integrated program debugging, verification, and optimization using abstract interpretation (and the Ciao system preprocessor)

The technique of Abstract Interpretation has allowed the development of very sophisticated global program analyses which are at the same time provably correct and practical. We present in a tutorial fashion a novel program development framework which uses abstract interpretation as a fundamental tool. The framework uses modular, incremental abstract interpretation to obtain information about the program. This information is used to validate programs, to detect bugs with respect to partial specifications written using assertions (in the program itself and/or in system libraries), to generate and simplify run-time tests, and to perform high-level program transformations such as multiple abstract specialization, parallelization, and resource usage control, all in a provably correct way. In the case of validation and debugging, the assertions can refer to a variety of program points such as procedure entry, procedure exit, points within procedures, or global computations. The system can reason with much richer information than, for example, traditional types. This includes data structure shape (including pointer sharing), bounds on data structure sizes, and other operational variable instantiation properties, as well as procedure-level properties such as determinacy, termination, nonfailure, and bounds on resource consumption (time or space cost). CiaoPP, the preprocessor of the Ciao multi-paradigm programming system, which implements the described functionality, will be used to illustrate the fundamental ideas.

Experiments in context-sensitive analysis of modular programs

Several models for context-sensitive analysis of modular programs have been proposed, each with different characteristics and representing different trade-offs. The advantage of these context-sensitive analyses is that they provide information which is potentially more accurate than that provided by context-free analyses. Such information can then be applied to validating/debugging the program and/or to specializing the program in order to obtain important performance improvements. Some very preliminary experimental results have also been reported for some of these models which provided initial evidence on their potential. However, further experimentation, which is needed in order to understand the many issues left open and to show that the proposed modes scale and are usable in the context of large, real-life modular programs, was left as future work. The aim of this paper is two-fold. On one hand we provide an empirical comparison of the different models proposed in previous work, as well as experimental data on the different choices left open in those designs. On the other hand we explore the scalability of these models by using larger modular programs as benchmarks. The results have been obtained from a realistic implementation of the models, integrated in a production-quality compiler (CiaoPP/Ciao). Our experimental results shed light on the practical implications of the different design choices and of the models themselves. We also show that contextsensitive analysis of modular programs is indeed feasible in practice, and that in certain critical cases it provides better performance results than those achievable by analyzing the whole program at once, specially in terms of memory consumption and when reanalyzing after making changes to a program, as is often the case during program development.

Night time performance of a storage integrated solar thermophotovoltaic (SISTPV) system

Energy storage at low maintenance cost is one of the key challenges for generating electricity from the solar energy. This paper presents the theoretical analysis (verified by CFD) of the night time performance of a recently proposed conceptual system that integrates thermal storage (via phase change materials) and thermophotovoltaics for power generation. These storage integrated solar thermophotovoltaic (SISTPV) systems are attractive owing to their simple design (no moving parts) and modularity compared to conventional Concentrated Solar Power (CSP) technologies. Importantly, the ability of high temperature operation of these systems allows the use of silicon (melting point of 1680 K) as the phase change material (PCM). Silicon's very high latent heat of fusion of 1800 kJ/kg and low cost ($1.70/kg), makes it an ideal heat storage medium enabling for an extremely high storage energy density and low weight modular systems. In this paper, the night time operation of the SISTPV system optimised for steady state is analysed. The results indicate that for any given PCM length, a combination of small taper ratio and large inlet hole-to-absorber area ratio are essential to increase the operation time and the average power produced during the night time. Additionally, the overall results show that there is a trade-off between running time and the average power produced during the night time. Average night time power densities as high as 30 W/cm(2) are possible if the system is designed with a small PCM length (10 cm) to operate just a few hours after sun-set, but running times longer than 72 h (3 days) are possible for larger lengths (50 cm) at the expense of a lower average power density of about 14 W/cm(2). In both cases the steady state system efficiency has been predicted to be about 30%. This makes SISTPV systems to be a versatile solution that can be adapted for operation in a broad range of locations with different climate conditions, even being used off-grid and in space applications.

Integrated manufacturing systems design in a multi-product company

Using a hydraulic equipment manufacturing plant as the case study, this work explores the problems of systems integration in manufacturing systems design, stressing the behavioural aspects of motivation and participation, and the constraints involved in the proper consideration of the human sub-system. The need for a simple manageable modular organisation structure is illustrated, where it is shown, by reference to systems theory, how a business can be split into semi-autonomous operating units. The theme is the development of a manufacturing system based on an analysis of the business, its market, product, technology and constraints, coupled with a critical survey of modern management literature to develop an integrated systems design to suit a specific company in the current social environment. Society currently moves through a socio-technical revolution with man seeking higher levels of motivation. The transitory environment from an autocratic/paternalistic to a participative operating mode demands systems parameters only found to a limited extent in manufacturing systems today. It is claimed, that modern manufacturing systems design needs to be based on group working, job enrichment, delegation of decision making and reduced job monotony. The analysis shows how negative aspects of cellular manufacture such as lack of flexibility and poor fixed asset utilisation are relatively irrelevant and misleading in the broader context of the need to come to terms with the social stresses imposed on a company operating in the industrial environment of the present and the immediate future.

Applicability of non-modular assessment in construction management and allied undergraduate programmes:perspective of the academics involved

Undergraduate programmes on construction management and other closely related built environment disciplines are currently taught and assessed on a modular basis. This is the case in the UK and in many other countries globally. However, it can be argued that professionally oriented programmes like these are better assessed on a non-modular basis, in order to produce graduates who can apply knowledge on different subject contents in cohesion to solve complex practical scenarios in their work environments. The examples of medical programmes where students are assessed on a non-modular basis can be cited as areas where this is already being done. A preliminary study was undertaken to explore the applicability of non-modular assessment within construction management undergraduate education. A selected sample of university academics was interviewed to gather their perspectives on applicability of non-modular assessment. General acceptance was observed among the academics involved that integrating non-modular assessment is applicable and will be beneficial. All academics stated that at least some form of non-modular assessment as being currently used in their programmes. Examples where cross-modular knowledge is assessed included comprehensive/multi-disciplinary project modules and creating larger modules to amalgamate a number of related subject areas. As opposed to a complete shift from modular to non-modular, an approach where non-modular assessment is integrated and its use further expanded within the current system is therefore suggested. This is due to the potential benefits associated with this form of assessment to professionally aligned built environment programmes

New integrated multilevel converter for switched reluctance motor drives in plug-in hybrid electric vehicles with flexible energy conversion

This paper presents an integrated multilevel converter of switched reluctance motors (SRMs) fed by a modular front-end circuit for plug-in hybrid electric vehicle (PHEV) applications. Several operating modes can be achieved by changing the on-off states of the switches in the front-end circuit. In generator driving mode, the battery bank is employed to elevate the phase voltage for fast excitation and demagnetization. In battery driving mode, the converter is reconfigured as a four-level converter, and the capacitor is used as an additional charge capacitor to produce multilevel voltage outputs, which enhances the torque capability. The operating modes of the proposed drive are explained and the phase current and voltage are analyzed in details. The battery charging is naturally achieved by the demagnetization current in motoring mode and by the regenerative current in braking mode. Moreover, the battery can be charged by the external AC source or generator through the proposed converter when the vehicle is in standstill condition. The SRM-based PHEV can operate at different speeds by coordinating the power flow between the generator and battery. Simulation in MATLAB/Simulink and experiments on a three-phase 12/8 SRM confirm the effectiveness of the proposed converter topology.

Robotic grasping: State of the art and modular real-world implementation

Robotic Grasping is an important research topic in robotics since for robots to attain more general-purpose utility, grasping is a necessary skill, but very challenging to master. In general the robots may use their perception abilities like an image from a camera to identify grasps for a given object usually unknown. A grasp describes how a robotic end-effector need to be positioned to securely grab an object and successfully lift it without lost it, at the moment state of the arts solutions are still far behind humans. In the last 5–10 years, deep learning methods take the scene to overcome classical problem like the arduous and time-consuming approach to form a task-specific algorithm analytically. In this thesis are present the progress and the approaches in the robotic grasping field and the potential of the deep learning methods in robotic grasping. Based on that, an implementation of a Convolutional Neural Network (CNN) as a starting point for generation of a grasp pose from camera view has been implemented inside a ROS environment. The developed technologies have been integrated into a pick-and-place application for a Panda robot from Franka Emika. The application includes various features related to object detection and selection. Additionally, the features have been kept as generic as possible to allow for easy replacement or removal if needed, without losing time for improvement or new testing.