An approach to operational modal analysis using the expectation maximization algorithm

This paper presents the Expectation Maximization algorithm (EM) applied to operational modal analysis of structures. The EM algorithm is a general-purpose method for maximum likelihood estimation (MLE) that in this work is used to estimate state space models. As it is well known, the MLE enjoys some optimal properties from a statistical point of view, which make it very attractive in practice. However, the EM algorithm has two main drawbacks: its slow convergence and the dependence of the solution on the initial values used. This paper proposes two different strategies to choose initial values for the EM algorithm when used for operational modal analysis: to begin with the parameters estimated by Stochastic Subspace Identification method (SSI) and to start using random points. The effectiveness of the proposed identification method has been evaluated through numerical simulation and measured vibration data in the context of a benchmark problem. Modal parameters (natural frequencies, damping ratios and mode shapes) of the benchmark structure have been estimated using SSI and the EM algorithm. On the whole, the results show that the application of the EM algorithm starting from the solution given by SSI is very useful to identify the vibration modes of a structure, discarding the spurious modes that appear in high order models and discovering other hidden modes. Similar results are obtained using random starting values, although this strategy allows us to analyze the solution of several starting points what overcome the dependence on the initial values used.

The Optimal combination: Grammatical Swarm, Particle Swarm Optimization and Neural Networks.

Social behaviour is mainly based on swarm colonies, in which each individual shares its knowledge about the environment with other individuals to get optimal solutions. Such co-operative model differs from competitive models in the way that individuals die and are born by combining information of alive ones. This paper presents the particle swarm optimization with differential evolution algorithm in order to train a neural network instead the classic back propagation algorithm. The performance of a neural network for particular problems is critically dependant on the choice of the processing elements, the net architecture and the learning algorithm. This work is focused in the development of methods for the evolutionary design of artificial neural networks. This paper focuses in optimizing the topology and structure of connectivity for these networks.

Regularized model learning in EDAs for continuous and multi-objective optimization

Probabilistic modeling is the de�ning characteristic of estimation of distribution algorithms (EDAs) which determines their behavior and performance in optimization. Regularization is a well-known statistical technique used for obtaining an improved model by reducing the generalization error of estimation, especially in high-dimensional problems. `1-regularization is a type of this technique with the appealing variable selection property which results in sparse model estimations. In this thesis, we study the use of regularization techniques for model learning in EDAs. Several methods for regularized model estimation in continuous domains based on a Gaussian distribution assumption are presented, and analyzed from di�erent aspects when used for optimization in a high-dimensional setting, where the population size of EDA has a logarithmic scale with respect to the number of variables. The optimization results obtained for a number of continuous problems with an increasing number of variables show that the proposed EDA based on regularized model estimation performs a more robust optimization, and is able to achieve signi�cantly better results for larger dimensions than other Gaussian-based EDAs. We also propose a method for learning a marginally factorized Gaussian Markov random �eld model using regularization techniques and a clustering algorithm. The experimental results show notable optimization performance on continuous additively decomposable problems when using this model estimation method. Our study also covers multi-objective optimization and we propose joint probabilistic modeling of variables and objectives in EDAs based on Bayesian networks, speci�cally models inspired from multi-dimensional Bayesian network classi�ers. It is shown that with this approach to modeling, two new types of relationships are encoded in the estimated models in addition to the variable relationships captured in other EDAs: objectivevariable and objective-objective relationships. An extensive experimental study shows the e�ectiveness of this approach for multi- and many-objective optimization. With the proposed joint variable-objective modeling, in addition to the Pareto set approximation, the algorithm is also able to obtain an estimation of the multi-objective problem structure. Finally, the study of multi-objective optimization based on joint probabilistic modeling is extended to noisy domains, where the noise in objective values is represented by intervals. A new version of the Pareto dominance relation for ordering the solutions in these problems, namely �-degree Pareto dominance, is introduced and its properties are analyzed. We show that the ranking methods based on this dominance relation can result in competitive performance of EDAs with respect to the quality of the approximated Pareto sets. This dominance relation is then used together with a method for joint probabilistic modeling based on `1-regularization for multi-objective feature subset selection in classi�cation, where six di�erent measures of accuracy are considered as objectives with interval values. The individual assessment of the proposed joint probabilistic modeling and solution ranking methods on datasets with small-medium dimensionality, when using two di�erent Bayesian classi�ers, shows that comparable or better Pareto sets of feature subsets are approximated in comparison to standard methods.

Metaheuristic approaches for MWT and MWPT problems

It is known that the Minimum Weight Triangulation problem is NP-hard. Also the complexity of the Minimum Weight Pseudo-Triangulation problem is unknown, yet it is suspected to be also NP-hard. Therefore we focused on the development of approximate algorithms to find high quality triangulations and pseudo-triangulations of minimum weight. In this work we propose two metaheuristics to solve these problems: Ant Colony Optimization (ACO) and Simulated Annealing (SA). For the experimental study we have created a set of instances for MWT and MWPT problems, since no reference to benchmarks for these problems were found in the literature. Through experimental evaluation, we assess the applicability of the ACO and SA metaheuristics for MWT and MWPT problems. These results are compared with those obtained from the application of deterministic algorithms for the same problems (Delaunay Triangulation for MWT and a Greedy algorithm respectively for MWT and MWPT).

A methodology for the implementation and continuous improvement of social responsibility (RS) and financial responsibility

This work sets out an innovative methodology that aims to facilitate the implementation and continuous improvement of Social Responsibility. It is a methodology that takes account of strategic-economic, social and environmental questions and allows measuring the impact of each of these aspects on the stakeholders and on each of the value areas. It can be extrapolated to all kinds of organisations regardless of their size and sector and admits scaleable models. A marked feature that sets it aside from other methodologies is that it eliminates subjectivity from the qualitative aspects and introduces an algorithm to quantify them.

Radio propagation modeling and measurements for ZigBee based indoor wireless sensor networks

The deployment of nodes in Wireless Sensor Networks (WSNs) arises as one of the biggest challenges of this field, which involves in distributing a large number of embedded systems to fulfill a specific application. The connectivity of WSNs is difficult to estimate due to the irregularity of the physical environment and affects the WSN designers? decision on deploying sensor nodes. Therefore, in this paper, a new method is proposed to enhance the efficiency and accuracy on ZigBee propagation simulation in indoor environments. The method consists of two steps: automatic 3D indoor reconstruction and 3D ray-tracing based radio simulation. The automatic 3D indoor reconstruction employs unattended image classification algorithm and image vectorization algorithm to build the environment database accurately, which also significantly reduces time and efforts spent on non-radio propagation issue. The 3D ray tracing is developed by using kd-tree space division algorithm and a modified polar sweep algorithm, which accelerates the searching of rays over the entire space. Signal propagation model is proposed for the ray tracing engine by considering both the materials of obstacles and the impact of positions along the ray path of radio. Three different WSN deployments are realized in the indoor environment of an office and the results are verified to be accurate. Experimental results also indicate that the proposed method is efficient in pre-simulation strategy and 3D ray searching scheme and is suitable for different indoor environments.

Variable threshold algorithm for division of labor analyzed as a dynamical system

Division of labor is a widely studied aspect of colony behavior of social insects. Division of labor models indicate how individuals distribute themselves in order to perform different tasks simultaneously. However, models that study division of labor from a dynamical system point of view cannot be found in the literature. In this paper, we define a division of labor model as a discrete-time dynamical system, in order to study the equilibrium points and their properties related to convergence and stability. By making use of this analytical model, an adaptive algorithm based on division of labor can be designed to satisfy dynamic criteria. In this way, we have designed and tested an algorithm that varies the response thresholds in order to modify the dynamic behavior of the system. This behavior modification allows the system to adapt to specific environmental and collective situations, making the algorithm a good candidate for distributed control applications. The variable threshold algorithm is based on specialization mechanisms. It is able to achieve an asymptotically stable behavior of the system in different environments and independently of the number of individuals. The algorithm has been successfully tested under several initial conditions and number of individuals.

Distributed cognitive radio systems with temperature-interference constraints and overlay scheme

Cognitive radio represents a promising paradigm to further increase transmission rates in wireless networks, as well as to facilitate the deployment of self-organized networks such as femtocells. Within this framework, secondary users (SU) may exploit the channel under the premise to maintain the quality of service (QoS) on primary users (PU) above a certain level. To achieve this goal, we present a noncooperative game where SU maximize their transmission rates, and may act as well as relays of the PU in order to hold their perceived QoS above the given threshold. In the paper, we analyze the properties of the game within the theory of variational inequalities, and provide an algorithm that converges to one Nash Equilibrium of the game. Finally, we present some simulations and compare the algorithm with another method that does not consider SU acting as relays.

Deciduous tree reconstruction algorithm based on cylinder fitting from mobile terrestrial laser scanned point clouds

Vector reconstruction of objects from an unstructured point cloud obtained with a LiDAR-based system (light detection and ranging) is one of the most promising methods to build three dimensional models of orchards. The cylinder fitting method for woody structure reconstruction of leafless trees from point clouds obtained with a mobile terrestrial laser scanner (MTLS) has been analysed. The advantage of this method is that it performs reconstruction in a single step. The most time consuming part of the algorithm is generation of the cylinder direction, which must be recalculated at the inclusion of each point in the cylinder. The tree skeleton is obtained at the same time as the cluster of cylinders is formed. The method does not guarantee a unique convergence and the reconstruction parameter values must be carefully chosen. A balanced processing of clusters has also been defined which has proven to be very efficient in terms of processing time by following the hierarchy of branches, predecessors and successors. The algorithm was applied to simulated MTLS of virtual orchard models and to MTLS data of real orchards. The constraints applied in the method have been reviewed to ensure better convergence and simpler use of parameters. The results obtained show a correct reconstruction of the woody structure of the trees and the algorithm runs in linear logarithmic time

Analysis and optimization of trajectories for Ballistic Missiles Interception

Intercontinental Ballistic Missiles are capable of placing a nuclear warhead at more than 5,000 km away from its launching base. With the lethal power of a nuclear warhead a whole city could be wiped out by a single weapon causing millions of deaths. This means that the threat posed to any country from a single ICBM captured by a terrorist group or launched by a 'rogue' state is huge. This threat is increasing as more countries are achieving nuclear and advanced launcher capabilities. In order to suppress or at least reduce this threat the United States created the National Missile Defense System which involved, among other systems, the development of long-range interceptors whose aim is to destroy incoming ballistic missiles in their midcourse phase. The Ballistic Missile Defense is a high-profile topic that has been the focus of political controversy lately when the U.S. decided to expand the Ballistic Missile system to Europe, with the opposition of Russia. However the technical characteristics of this system are mostly unknown by the general public. The Interception of an ICBM using a long range Interceptor Missile as intended within the Ground-Based Missile Defense System by the American National Missile Defense (NMD) implies a series of problems of incredible complexity: - The incoming missile has to be detected almost immediately after launch. - The incoming missile has to be tracked along its trajectory with a great accuracy. - The Interceptor Missile has to implement a fast and accurate guidance algorithm in order to reach the incoming missile as soon as possible. - The Kinetic Kill Vehicle deployed by the interceptor boost vehicle has to be able to detect the reentry vehicle once it has been deployed by ICBM, when it offers a very low infrared signature, in order to perform a final rendezvous manoeuvre. - The Kinetic Kill Vehicle has to be able to discriminate the reentry vehicle from the surrounding debris and decoys. - The Kinetic Kill Vehicle has to be able to implement an accurate guidance algorithm in order to perform a kinetic interception (direct collision) of the reentry vehicle, at relative speeds of more than 10 km/s. All these problems are being dealt simultaneously by the Ground-Based Missile Defense System that is developing very complex and expensive sensors, communications and control centers and long-range interceptors (Ground-Based Interceptor Missile) including a Kinetic Kill Vehicle. Among all the technical challenges involved in this interception scenario, this thesis focuses on the algorithms required for the guidance of the Interceptor Missile and the Kinetic Kill Vehicle in order to perform the direct collision with the ICBM. The involved guidance algorithms are deeply analysed in this thesis in part III where conventional guidance strategies are reviewed and optimal guidance algorithms are developed for this interception problem. The generation of a realistic simulation of the interception scenario between an ICBM and a Ground Based Interceptor designed to destroy it was considered as necessary in order to be able to compare different guidance strategies with meaningful results. As a consequence, a highly representative simulator for an ICBM and a Kill Vehicle has been implemented, as detailed in part II, and the generation of these simulators has also become one of the purposes of this thesis. In summary, the main purposes of this thesis are: - To develop a highly representative simulator of an interception scenario between an ICBM and a Kill Vehicle launched from a Ground Based Interceptor. -To analyse the main existing guidance algorithms both for the ascent phase and the terminal phase of the missiles. Novel conclusions of these analyses are obtained. - To develop original optimal guidance algorithms for the interception problem. - To compare the results obtained using the different guidance strategies, assess the behaviour of the optimal guidance algorithms, and analyse the feasibility of the Ballistic Missile Defense system in terms of guidance (part IV). As a secondary objective, a general overview of the state of the art in terms of ballistic missiles and anti-ballistic missile defence is provided (part I).

Amelioration of a degraded acid soil from SW Spain by no-tillage and Ca-amendment

En los suelos, el exceso de acidez lleva asociado deficiencias en ciertos nutrientes y una alta disponibilidad de aluminio, tóxico para los cultivos propios del ambiente mediterráneo. Su laboreo, provoca la pérdida de materia orgánica (MO), deteriora su estructura y reduce la actividad biológica, provocando en última instancia una menor calidad del suelo. Es de esperar pues que cuando se labran suelos ácidos, sus problemáticas particulares tiendan a agravarse. En nuestra zona de estudio, la “raña” de Cañamero (Extremadura, España), predominan los suelos muy ácidos y degradados por un laboreo inadecuado. Las rañas constituyen amplias plataformas casi horizontales, con unos suelos muy viejos (Palexerults), que se caracterizan por tener el complejo de cambio dominado por el aluminio, y un pH ácido que decrece en profundidad. Poseen un potente horizonte Bt rico en arcillas caoliníticas, que propicia que en periodos con exceso de lluvia, se generen capas colgadas de agua cercanas a la superficie. En torno a los años 1940’s estos suelos, que previamente sostenían un alcornocal, o su matorral de sustitución, se pusieron en cultivo. El laboreo aceleró la mineralización de la materia orgánica, agravó los problemas derivados del exceso de acidez y condujo al abandono de los campos cultivados por falta de productividad. Para recuperar la calidad de estos suelos degradados y obtener unos rendimientos compatibles con su uso agrícola es necesario, por un lado, aplicar enmiendas que eleven el pH y reduzcan la toxicidad del aluminio y, por otro, favorecer el incremento en el contenido en MO. En 2005 se implantó en esta raña un ensayo de campo para estudiar la influencia del no laboreo y de la utilización de una enmienda cálcica en parámetros relacionados con la calidad del suelo en un cultivo forrajero. El diseño experimental fue en parcelas divididas con cuatro repeticiones donde el factor principal fue el tipo de laboreo, no laboreo (NL) frente a laboreo convencional (LC), y el factor secundario el uso o no de una enmienda cálcica. La enmienda consistió básicamente en una mezcla de espuma de azucarería y yeso rojo y se incorporó al comienzo del ensayo hasta los 7 cm de profundidad. Desde el comienzo del ensayo el NL influyó positivamente en el contenido de carbono orgánico total (COT) y particulado (COP), mientras que la enmienda tuvo una ligera influencia al principio del ensayo en ambos pero su efecto positivo se desvaneció con el paso del tiempo. Los mayores contenidos en COT y POC se observaron cuando se combinó el NL con la enmienda. La enmienda incrementó con rapidez el pH, y el Ca, y disminuyó el contenido en aluminio hasta una profundidad de 50 cm, incluso en NL, y mejoró ligeramente la agregación del suelo. El NL por sí solo, gracias al aumento en POC, TOC y las proteínas del suelo relacionadas con la glomalina (PSRG), que son capaces de formar compuestos estables no tóxicos con el aluminio, también contribuyó a la reducción de la toxicidad de aluminio en la capa más superficial. Cuando en las campañas con exceso de precipitaciones se generaron capas colgadas de agua próximas a la superficie, el NL generó unas condiciones más favorables para la germinación y desarrollo del cultivo, resultando en una producción más alta que el LC. A ello contribuyó la mayor capacidad de almacenamiento de agua y la mayor transmisividad de esta hacia abajo, en la capa más superficial (0-5 cm) que propició una menor saturación por agua que el LC. Respecto a los parámetros relacionados con la agregación, el NL aumentó los macroagregados hasta los 10 cm de profundidad y favoreció la acumulación de CO y N en todas las fracciones de tamaño de agregados. Sin embargo, la recuperación del grado de macroagregación tras el cese del laboreo resulta lenta en comparación con otros suelos, posiblemente debido al bajo contenido en arcilla en el horizonte Ap. En comparación con el NL, la enmienda mostró también un efecto positivo, aunque muy ligero, en la agregación del suelo. En contradicción con otros estudios en suelos ácidos, nuestros resultados indican la existencia de una jerarquía de agregados, y destacan el papel importante de la MO en la mejora de la agregación. Tanto el NL como la enmienda favorecieron por separado varias propiedades químicas, físicas y biológicas del suelo, pero, en general, encontramos los mayores beneficios con su uso combinado. Además, a largo plazo el efecto positivo de NL en las propiedades del suelo fue en aumento, mientras que el efecto beneficioso de la enmienda se limitó básicamente a las propiedades químicas y se desvaneció en pocos años. Destacamos que las condiciones meteorológicas a lo largo del ensayo beneficiaron la producción de biomasa en NL, y en consecuencia las propiedades relacionadas con la materia orgánica, por lo que son un factor a tener en cuenta a la hora de evaluar los efectos de la enmienda y el laboreo sobre las propiedades del suelo, especialmente en zonas donde esas condiciones son muy variables entre una campaña y otra. Los resultados de este estudio han puesto de manifiesto que el NL no ha mermado la eficacia de la enmienda caliza, posiblemente gracias a la alta solubilidad de la enmienda aplicada, es más, el manejo con NL y enmienda es el que ha favorecido en mayor medida ciertos parámetros de calidad del suelo. Por el contrario el LC sí parece anular los beneficios de la enmienda en relación con las propiedades relacionadas con la MO. Por tanto, cabe concluir que la combinación de NL y la enmienda es una práctica adecuada para mejorar las propiedades químicas y físicas de suelos ácidos degradados por el laboreo. ABSTRACT Excessive acidity in soils is associated with deficiencies in certain nutrients and high concentrations of available aluminum, which is toxic for most Mediterranean crops. Tilling these soils results in the loss of soil organic matter (SOM), damages soil structure and reduces biological activity, ultimately degrading soil quality. It is expected, therefore, that when acid soils are tilled, their particular problems will tend to get worse. In our study area, the "Cañamero’s Raña” (Extremadura, Spain), acid soils degraded by an inappropriate tillage prevail. Rañas are large and flat platforms with very old soils (Palexerults), which are characterized by an exchange complex dominated by aluminum and an acid pH which decreases with depth. These soils have a strong Bt horizon rich in kaolinite clays, which encourages the formation of perched water-tables near the soil surface during periods of excessive rain. During the first third of the 20th century, these soils, that previously supported cork oak or its scrub replacement, were cultivated. Tillage accelerated the mineralization of the SOM, aggravating the problems of excessive acidity, which finally led to the abandonment of the land due to low productivity. To recover the quality of these degraded soils and to obtain consistent yields it is necessary, first, to apply amendments to raise the pH and reduce aluminum toxicity, and second to encourage the accumulation of SOM. In 2005 a field trial was established in the Raña to study the influence of no-tillage and the use of a Ca-amendment on soil quality related parameters in a forage crop agrosystem. The experimental design was a split-plot with four replicates where the main factor was tillage type, no-tillage (NT) versus traditional tillage (TT) and the secondary factor was the use or not of a Ca-amendment. The Ca-amendment was a mixture of sugar foam and red gypsum that was incorporated into the top 7 cm of the soil. Since the beginning of the experiment, NT had a positive influence on total and particulate organic carbon (TOC and POC, respectively), while the Ca-amendment had a small positive influence at the beginning of the study but its effect diminished with time. The highest TOC and POC contents were observed when NT and the Ca-amendment were combined. The Ca-amendment, even under NT, rapidly increased pH and Ca, and decreased the aluminum content to a depth of 50 cm, as well as improving soil aggregation slightly. NT, due to the increased POC, TOC and Glomalin-related soil proteins (GRSP), which can form stable non-toxic compounds with aluminum, also contributed to the reduction of aluminum toxicity in the upper layer. When perched water-tables near the soil surface were formed in campaigns with excessive rainfall, NT provided more favorable conditions for germination and crop development, resulting in higher yields compared with TT. This was directly related to the higher water storage capacity and the greater transmissivity of the water downwards from the upper layers, which led to lower water saturation under NT compared with TT. With regards to the aggregation-related parameters, NT increased macroaggregation to a depth of 10 cm and favored the accumulation of OC and N in all aggregate size fractions. However, the degree of recovery of macroaggregation after tillage ceased was slow compared with other soils, possibly due to the low clay content in the Ap horizon. Compared with NT, the Ca-amendment had a slight positive effect on soil aggregation. In contrast to other studies in acid soils, our results indicate the existence of an aggregate hierarchy, and highlight the important role of SOM in improving aggregation. Both NT and the Ca-amendment separately favored various chemical, physical and biological soil properties, but in general we found the greatest benefits when the two treatments were combined. In addition, the positive effect of NT on soil properties increased with time, while the beneficial effect of the Ca-amendment, which was limited to the chemical properties, vanished after a few years. It is important to note that the meteorological conditions throughout the experiment benefited biomass production under NT and, as a consequence, organic matter related properties. This suggests that meteorological conditions are a factor to consider when evaluating the effects of Ca-amendments and tillage on soil properties, especially in areas where such conditions vary significantly from one campaign to another. The results of this study show that NT did not diminish the effectiveness of the Ca-amendment, possibly due to the high solubility of the selected amendment. Moreover, the combination of NT and the Ca-amendment was actually the management that favored certain soil quality parameters the most. By contrast, TT seemed to nullify the benefits of the Ca-amendment with regards to the OM related properties. In conclusion, the combination of NT and the application of a Ca-amendment is an advisable practice for improving the chemical and physical properties of acid soils degraded by tillage.

Nonlinear normal modes in mechanical systems: concept and computation with numerical continuation

The purpose of this Project is, first and foremost, to disclose the topic of nonlinear vibrations and oscillations in mechanical systems and, namely, nonlinear normal modes NNMs to a greater audience of researchers and technicians. To do so, first of all, the dynamical behavior and properties of nonlinear mechanical systems is outlined from the analysis of a pair of exemplary models with the harmonic balanced method. The conclusions drawn are contrasted with the Linear Vibration Theory. Then, it is argued how the nonlinear normal modes could, in spite of their limitations, predict the frequency response of a mechanical system. After discussing those introductory concepts, I present a Matlab package called 'NNMcont' developed by a group of researchers from the University of Liege. This package allows the analysis of nonlinear normal modes of vibration in a range of mechanical systems as extensions of the linear modes. This package relies on numerical methods and a 'continuation algorithm' for the computation of the nonlinear normal modes of a conservative mechanical system. In order to prove its functionality, a two degrees of freedom mechanical system with elastic nonlinearities is analized. This model comprises a mass suspended on a foundation by means of a spring-viscous damper mechanism -analogous to a very simplified model of most suspended structures and machines- that has attached a mass damper as a passive vibration control system. The results of the computation are displayed on frequency energy plots showing the NNMs branches along with modal curves and time-series plots for each normal mode. Finally, a critical analysis of the results obtained is carried out with an eye on devising what they can tell the researcher about the dynamical properties of the system.

The U5 RNA of trypanosomes deviates from the canonical U5 RNA: The Leptomonas collosoma U5 RNA and its coding gene

Fractionation of the abundant small ribonucleoproteins (RNPs) of the trypanosomatid Leptomonas collosoma revealed the existence of a group of unidentified small RNPs that were shown to fractionate differently than the well-characterized trans-spliceosomal RNPs. One of these RNAs, an 80-nt RNA, did not possess a trimethylguanosine (TMG) cap structure but did possess a 5′ phosphate terminus and an invariant consensus U5 snRNA loop 1. The gene coding for the RNA was cloned, and the coding region showed 55% sequence identity to the recently described U5 homologue of Trypanosoma brucei [Dungan, J. D., Watkins, K. P. & Agabian, N. (1996) EMBO J. 15, 4016–4029]. The L. collosoma U5 homologue exists in multiple forms of RNP complexes, a 10S monoparticle, and two subgroups of 18S particles that either contain or lack the U4 and U6 small nuclear RNAs, suggesting the existence of a U4/U6⋅U5 tri-small nuclear RNP complex. In contrast to T. brucei U5 RNA (62 nt), the L. collosoma homologue is longer (80 nt) and possesses a second stem–loop. Like the trypanosome U3, U6, and 7SL RNA genes, a tRNA gene coding for tRNACys was found 98 nt upstream to the U5 gene. A potential for base pair interaction between U5 and SL RNA in the 5′ splice site region (positions −1 and +1) and downstream from it is proposed. The presence of a U5-like RNA in trypanosomes suggests that the most essential small nuclear RNPs are ubiquitous for both cis- and trans-splicing, yet even among the trypanosomatids the U5 RNA is highly divergent.

In vivo restoration of laminin 5 β3 expression and function in junctional epidermolysis bullosa

The blistering disorder, lethal junctional epidermolysis bullosa (JEB), can result from mutations in the LAMB3 gene, which encodes laminin 5 β3 (β3). Appropriate expression of LAMβ3 in JEB skin tissue could potentially ameliorate the symptoms of the underlying disease. To explore the utility of this therapeutic approach, primary keratinocytes from six unrelated JEB patients were transduced with a retroviral vector encoding β3 and used to regenerate human skin on severe combined immunodeficient (SCID) mice. Tissue regenerated from β3-transduced JEB keratinocytes produced phenotypically normal skin characterized by sustained β3 expression and the formation of hemidesmosomes. Additionally, β3 gene transfer corrected the distribution of a number of important basement membrane zone proteins including BPAG2, integrins β4/β1, and laminins α3/γ2. Skin produced from β3-negative (β3[−]) JEB cells mimicked the hallmarks of the disease state and did not exhibit any of the aforementioned traits. Therefore, by effecting therapeutic gene transfer to β3-deficient primary keratinocytes, it is possible to produce healthy, normal skin tissue in vivo. These data support the utility of gene therapy for JEB and highlight the potential for gene delivery in the treatment of human genetic skin disease.

Dynamical hierarchy in transition states: Why and how does a system climb over the mountain?

How a reacting system climbs through a transition state during the course of a reaction has been an intriguing subject for decades. Here we present and quantify a technique to identify and characterize local invariances about the transition state of an N-particle Hamiltonian system, using Lie canonical perturbation theory combined with microcanonical molecular dynamics simulation. We show that at least three distinct energy regimes of dynamical behavior occur in the region of the transition state, distinguished by the extent of their local dynamical invariance and regularity. Isomerization of a six-atom Lennard–Jones cluster illustrates this: up to energies high enough to make the system manifestly chaotic, approximate invariants of motion associated with a reaction coordinate in phase space imply a many-body dividing hypersurface in phase space that is free of recrossings even in a sea of chaos. The method makes it possible to visualize the stable and unstable invariant manifolds leading to and from the transition state, i.e., the reaction path in phase space, and how this regularity turns to chaos with increasing total energy of the system. This, in turn, illuminates a new type of phase space bottleneck in the region of a transition state that emerges as the total energy and mode coupling increase, which keeps a reacting system increasingly trapped in that region.