993 resultados para Party identification
Resumo:
The fetal and larval development of many freshwater fish is already relatively well covered. Coverage of the morphology of fish-species' eggs is very sparse. For this reason the authors have attempted to prepare a key on fish eggs which covers the bulk of German Teleostei fish. The key also includes a discussion of problems of categorization and terminology.
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This investigation has resulted in the chemical identification and isolation of the egg-laying hormone from Aplysia californica, Aplysia vaccaria, and Aplysia dactylomela. The hormone, which was originally identified as the Bag Cell-Specific protein (BCS protein) on polyacrylamide gels, is a polypeptide of molecular weight ≈ 6000, which is localized in the neurosecretory bag cells of the parietovisceral ganglion and the surrounding connective tissue sheath which contains the bag cell axons. All three species produce a hormone of similar molecular weight, but varying electrophoretic mobility as determined on polyacrylamide gels. As tested, the hormone is completely cross-reactive among the three species.
Although the bag cells of sexually immature animals contain the active hormone, sexual maturation of the animal results in a 10-fold increase in the BCS protein content of these neurons.
A seasonal variation in the BCS protein content was also observed, with 150 times more hormone contained in the bag cells of Aplysia californica in August than in January. This correlates well with the variation in the animals' ability to lay eggs throughout the year (Strumwasser et al., 1969). There are some indications that the receptivity of the animal to the available hormone also fluctuates during the year, being lower in winter than in swmner. The seasonal rhythm of the other species, Aplysia vaccaria and Aplysia dactylomela, has not been investigated.
A polyacrylamide gel electrophoresis analysis of water-soluble proteins in Aplysia californica revealed several other nerve-specific proteins. One of these is also located in the bag cell somas and stains turquoise with Amido Schwarz. The function of this protein has not been investigated.
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A good understanding of the population dynamics of algal communities is vital in many ecological and pollution studies of freshwater and oceanic systems. Present methods require manual counting and identification of algae and can take up to 90 min to obtain a statistically reliable count on a complex population. Several alternative techniques to accelerate the process have been tried on marine samples but none have been completely successful because insufficient effort has been put into verifying the technique before field trials. The objective of the present study has been to assess the potential of in vivo fluorescence of algal pigments as a means of automatically identifying algae. For this work total fluorescence spectroscopy was chosen as the observation technique.
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This bibliography covers the literature up to the end of 1978. The criteria used in the selection of references were that they should aid identification of invertebrates directly; thus, works solely concerned with the taxonomy of a particular group are in general omitted unless they contain a key. Some check-lists are however included where they give current nomenclature. The references are arranged alphabetically within each group and deal mainly with macro-invertebrates but include available keys to some microscopic invertebrates. Internal parasites and hymenopterous parasitoids are omitted. For insects the life stages to which the key applies are given where this is not clear in the reference. A number of keys to non-aquatic stages have been included in the hope that they may prove useful in certain circumstances. In addition, under a general head, latest check-lists are referred to together with bibliographies of algal keys and a guide for the identification of British water plants.
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The centralized paradigm of a single controller and a single plant upon which modern control theory is built is no longer applicable to modern cyber-physical systems of interest, such as the power-grid, software defined networks or automated highways systems, as these are all large-scale and spatially distributed. Both the scale and the distributed nature of these systems has motivated the decentralization of control schemes into local sub-controllers that measure, exchange and act on locally available subsets of the globally available system information. This decentralization of control logic leads to different decision makers acting on asymmetric information sets, introduces the need for coordination between them, and perhaps not surprisingly makes the resulting optimal control problem much harder to solve. In fact, shortly after such questions were posed, it was realized that seemingly simple decentralized optimal control problems are computationally intractable to solve, with the Wistenhausen counterexample being a famous instance of this phenomenon. Spurred on by this perhaps discouraging result, a concerted 40 year effort to identify tractable classes of distributed optimal control problems culminated in the notion of quadratic invariance, which loosely states that if sub-controllers can exchange information with each other at least as quickly as the effect of their control actions propagates through the plant, then the resulting distributed optimal control problem admits a convex formulation.
The identification of quadratic invariance as an appropriate means of "convexifying" distributed optimal control problems led to a renewed enthusiasm in the controller synthesis community, resulting in a rich set of results over the past decade. The contributions of this thesis can be seen as being a part of this broader family of results, with a particular focus on closing the gap between theory and practice by relaxing or removing assumptions made in the traditional distributed optimal control framework. Our contributions are to the foundational theory of distributed optimal control, and fall under three broad categories, namely controller synthesis, architecture design and system identification.
We begin by providing two novel controller synthesis algorithms. The first is a solution to the distributed H-infinity optimal control problem subject to delay constraints, and provides the only known exact characterization of delay-constrained distributed controllers satisfying an H-infinity norm bound. The second is an explicit dynamic programming solution to a two player LQR state-feedback problem with varying delays. Accommodating varying delays represents an important first step in combining distributed optimal control theory with the area of Networked Control Systems that considers lossy channels in the feedback loop. Our next set of results are concerned with controller architecture design. When designing controllers for large-scale systems, the architectural aspects of the controller such as the placement of actuators, sensors, and the communication links between them can no longer be taken as given -- indeed the task of designing this architecture is now as important as the design of the control laws themselves. To address this task, we formulate the Regularization for Design (RFD) framework, which is a unifying computationally tractable approach, based on the model matching framework and atomic norm regularization, for the simultaneous co-design of a structured optimal controller and the architecture needed to implement it. Our final result is a contribution to distributed system identification. Traditional system identification techniques such as subspace identification are not computationally scalable, and destroy rather than leverage any a priori information about the system's interconnection structure. We argue that in the context of system identification, an essential building block of any scalable algorithm is the ability to estimate local dynamics within a large interconnected system. To that end we propose a promising heuristic for identifying the dynamics of a subsystem that is still connected to a large system. We exploit the fact that the transfer function of the local dynamics is low-order, but full-rank, while the transfer function of the global dynamics is high-order, but low-rank, to formulate this separation task as a nuclear norm minimization problem. Finally, we conclude with a brief discussion of future research directions, with a particular emphasis on how to incorporate the results of this thesis, and those of optimal control theory in general, into a broader theory of dynamics, control and optimization in layered architectures.
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The biomass of the phytoplankton and its composition is one of the most important factors in water quality control. Determination of the phytoplankton assemblage is usually done by microscopic analysis (Utermöhl's method). Quantitative estimations of the biovolume, by cell counting and cell size measurements, are time-consuming and normally are not done in routine water quality control. Several alternatives have been tried: computer-based image analysis, spectral fluorescence signatures, flow cytometry and pigment fingerprinting aided by high performance liquid chromatography (HPLC). The latter method is based on the fact that each major algal group of taxa contains a specific carotenoid which can be used for identification and relative quantification of the taxa in the total assemblage. This article gives a brief comparative introduction to the different techniques available and presents some recent results obtained by HPLC-based pigment fingerprinting, applied to three lakes of different trophic status. The results show that this technique yields reliable results from different lake types and is a powerful tool for studying the distribution pattern of the phytoplankton community in relation to water depth. However, some restrictions should be taken into account for the interpretation of routine data.
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Spurious oscillations are one of the principal issues faced by microwave and RF circuit designers. The rigorous detection of instabilities or the characterization of measured spurious oscillations is still an ongoing challenge. This project aims to create a new stability analysis CAD program that tackles this chal- lenge. Multiple Input Multiple Output (MIMO) pole-zero identification analysis is introduced on the program as a way to create new methods to automate the stability analysis process and to help designers comprehend the obtained results and prevent incorrect interpretations. The MIMO nature of the analysis contributes to eliminate possible controllability and observability losses and helps differentiate mathematical and physical quasi-cancellations, products of overmodeling. The created program reads Single Input Single Output (SISO) or MIMO frequency response data, and determines the corresponding continuous transfer functions with Vector Fitting. Once the transfer function is calculated, the corresponding pole/zero diagram is mapped enabling the designers to analyze the stability of an amplifier. Three data processing methods are introduced, two of which consist of pole/zero elimina- tions and the latter one on determining the critical nodes of an amplifier. The first pole/zero elimination method is based on eliminating non resonant poles, whilst the second method eliminates the poles with small residue by assuming that their effect on the dynamics of a system is small or non-existent. The critical node detection is also based on the residues; the node at which the effect of a pole on the dynamics is highest is defined as the critical node. In order to evaluate and check the efficiency of the created program, it is compared via examples with another existing commercial stability analysis tool (STAN tool). In this report, the newly created tool is proved to be as rigorous as STAN for detecting instabilities. Additionally, it is determined that the MIMO analysis is a very profitable addition to stability analysis, since it helps to eliminate possible problems of loss of controllability, observability and overmodeling.
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Este trabalho se propõe a desvendar os contornos principiológicos e instrumentais daquilo que doravante iremos chamar Justo Processo Coletivo Laboral, ramo especialíssimo do processo dedicado à resolução de lides trabalhistas metaindividuais. O foco de nossas atenções é a tutela que é prestada em favor e não contra a coletividade. A falta de disposições específicas na CLT a respeito da tutela de direitos difusos, coletivos e individuais homogêneos próprios à realidade do trabalho torna imperiosa a inserção do Processo Trabalhista no circuito normativo de tutela coletiva, no chamado microssistema coletivo de tutela, composto, dentre outros diplomas, pelo Código de Defesa do Consumidor e pela Lei da Ação Civil Pública. A acomodação do Processo do Trabalho no ambiente coletivista será feita à luz da constelação de princípios constitucionais do processo e sob influxo do paradigma processual instrumental. A partir da identificação das principais barreiras que repelem o trabalhador do Poder Judiciário, procura-se demonstrar de que modo podem as ações coletivas contribuir para sua superação e assim para alavancar e universalizar o acesso à justiça, meta síntese para a qual convergem todos os esforços da processualística contemporânea. Apresentadas suas nuanças principiológicas, parte-se para a análise de seus principais institutos e do modo como deverá ser operacionalizado no dia-a-dia, isto é, de como irá funcionar. A crise de efetividade do processo de bases individualistas, especialmente para o trabalhador hipossuficiente, acentua a importância do devido processo legal coletivo do trabalho, instrumentalmente vocacionado a tornar justo o embate Capital X Trabalho e a conduzir grupos de trabalhadores de uma só vez à justa ordem jurídico-social.
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In this study we employed a dynamic recurrent neural network (DRNN) in a novel fashion to reveal characteristics of control modules underlying the generation of muscle activations when drawing figures with the outstretched arm. We asked healthy human subjects to perform four different figure-eight movements in each of two workspaces (frontal plane and sagittal plane). We then trained a DRNN to predict the movement of the wrist from information in the EMG signals from seven different muscles. We trained different instances of the same network on a single movement direction, on all four movement directions in a single movement plane, or on all eight possible movement patterns and looked at the ability of the DRNN to generalize and predict movements for trials that were not included in the training set. Within a single movement plane, a DRNN trained on one movement direction was not able to predict movements of the hand for trials in the other three directions, but a DRNN trained simultaneously on all four movement directions could generalize across movement directions within the same plane. Similarly, the DRNN was able to reproduce the kinematics of the hand for both movement planes, but only if it was trained on examples performed in each one. As we will discuss, these results indicate that there are important dynamical constraints on the mapping of EMG to hand movement that depend on both the time sequence of the movement and on the anatomical constraints of the musculoskeletal system. In a second step, we injected EMG signals constructed from different synergies derived by the PCA in order to identify the mechanical significance of each of these components. From these results, one can surmise that discrete-rhythmic movements may be constructed from three different fundamental modules, one regulating the co-activation of all muscles over the time span of the movement and two others elliciting patterns of reciprocal activation operating in orthogonal directions.
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Background: There has been a significant growth in the prevalence of allergy, mainly associated to IgE-mediated disorders such as asthma and rhinitis. The identification of atopy in asthmatic patients through the measurement of specific IgE can help to identify risk factors that cause asthmatic symptoms in patients. The development and use of individualized allergen-based tests by the Component Resolved Diagnosis has been a crucial advance in the accurate diagnosis and control of allergic patients. The objective of this work was to assess the usefulness of molecular diagnosis to identify environmental allergens as possible factors influencing the development and manifestation of asthma in a group of asthmatic patients from Iran. Methods: Studied population: 202 adult asthmatic patients treated at the Loghman Hakim Hospital and Pasteur Institute of Teheran (Iran) from 2011 to 2012. Specific IgE determined by the ImmunoCAP system were used to both evaluate the patients' atopic condition and the molecules involved in the allergic sensitization. SDS-PAGE IgE-immunoblotting associated with mass spectrometry was carried out to study the cockroach IgE-binding sensitizing proteins. Results: Forty-five percent of all patients could be considered atopic individuals. Eighty-two percent of atopic patients were sensitized to pollen allergens. The Salsola kali (Sal k 1) and the Phleum pratense (rPhl p 1 and/or rPhl p 5) major allergens were the most common sensitizers among pollens (71% and 18%, respectively). Thirty-five percent of the atopic population was sensitized to cockroach. Four different allergens, including a previously unknown alpha-amylase, were identified in the cockroach extract. No significant associations could be demonstrated between the severity of asthma and the specific IgE levels in the atopic population. Statistical analysis identified the Sal k 1 as the main protein allergen influencing the development and expression of asthma in the studied population. Conclusions: Pollen and cockroach were the most relevant allergen sources in the asthmatic population. The Salsola kali major allergen was the main cause for sensitization in the atopic patients suffering asthma. Using the Component Resolved Diagnosis, it was possible to identify a new Blattella germanica cockroach allergen (Blattella alpha amylase 53 kDa) that could sensitize a relevant percentage of this population.