Automatic identification and enumeration of algae

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.

A bibliography of works for the identification of freshwater invertebrates in the British Isles

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.

Distributed Optimal Control of Cyber-Physical Systems: Controller Synthesis, Architecture Design and System Identification

The centralized paradigm of a single controller and a single plant upon which modern control theory is built is no longer applicable to modern cyber-physical systems of interest, such as the power-grid, software defined networks or automated highways systems, as these are all large-scale and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.

Recent progress in the identification and determination of freshwater phytoplankton in the natural environment

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.

Stability analysis of RF amplifiers based on MIMO pole-zero identification

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.

Desenvolvimento e validação de sistema multiplex X-STR para identificação humana por DNA

Novas metodologias de análise molecular voltadas para estudos populacionais, clínicos, evolutivos, da biodiversidade e identificação forense foram desenvolvidas com base em marcadores microssátelites ou STR Short Tandem Repeats. Os marcadores STR, que estão amplamente espalhados nos genomas e se caracterizam por apresentar alto grau de polimorfismo, podem ser analisados a partir da amplificação por PCR (Reação em Cadeia da polimerase). A análise foi facilitada a partir do desenvolvimento de sistemas de amplificação simultânea de múltiplos STR (multiplex STR) e com a detecção automatizada dos produtos de amplificação marcados por fluorescência. Recentemente, o uso de marcadores STR do cromossomo X (X-STR) tornou-se significativo na prática forense. Devido ao seu modo de transmissão, os X-STR são úteis em situações particulares de investigação de relações de parentesco, apresentando vantagens sobre o uso de STR autossômicos. Este estudo teve como principal objetivo o desenvolvimento e validação de sistema multiplex, denominado LDD (X-STR) Decaplex, capaz de amplificar dez loci X-STR (DXS7133, DXS7424, DXS8378, DXS6807, DXS7132, DXS10074, DXS7423, DXS8377, GATA172D05 e DXS10101) para aplicação em genética populacional, identificação e análises forenses. Utilizando o LDD (X-STR) Decaplex 170 indivíduos autodenominados afrodescendentes, não aparentados geneticamente, foram genotipados. As freqüências alélicas e genotípicas não apresentaram desvio do equilíbrio de Hardy-Weinberg e estão em concordância com aquelas observadas em outros estudos. Os haplótipos observados foram únicos em indivíduos de amostra masculina. A análise de desequilíbrio de ligação não revelou associação entre os marcadores X-STR. A diversidade genética foi elevada, variando entre 0,6218 para o locus DXS7133 a 0,9327 para o locus DXS8377. Os parâmetros de Probabilidade de Vinculação (PV), Índice de Vinculação (IV), Poder de Exclusão (PE), Poder de Discriminação e Razão de Verossimilhança foram também elevados, demonstraram que os dez X-STRs são altamente polimórficos e discriminativos na população estudada. A concentração mínima de DNA para a amplificação dos loci do LDD (X-STR) Decaplex é de 0,5 ng e verificamos que amplificação por PCR pode ser afetada quando são adicionados mais de 5 ng de DNA nas reações. Os percentuais de bandas stutter foram elevados para os loci DXS7132 e DXS8377. No teste de reprodutibilidade observamos consistência entre as tipagem de diferentes amostras biológicas, incluindo as de restos mortais. No teste de mistura a proporção limite em que observamos a coexistência de duas espécies biológicas foi de 2,5:1ng (feminino-masculino). Os resultados evidenciaram que os loci do LDD (X-STR) Decaplex são altamente informativos, consistindo, em conjunto, uma ferramenta importante em estudos de identificação humana e de relações de parentesco.

Physiological modules for generating discrete and rhythmic movements: action identification by a dynamic recurrent neural network

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.

Identification of the main allergen sensitizers in an Iran asthmatic population by molecular diagnosis

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.