Truncated robust distance for clinical laboratory safety data monitoring and assessment.

Laboratory safety data are routinely collected in clinical studies for safety monitoring and assessment. We have developed a truncated robust multivariate outlier detection method for identifying subjects with clinically relevant abnormal laboratory measurements. The proposed method can be applied to historical clinical data to establish a multivariate decision boundary that can then be used for future clinical trial laboratory safety data monitoring and assessment. Simulations demonstrate that the proposed method has the ability to detect relevant outliers while automatically excluding irrelevant outliers. Two examples from actual clinical studies are used to illustrate the use of this method for identifying clinically relevant outliers.

Robust control of structures subject to uncertain disturbances and actuator dynamics

The objective the present research is try to find some control design strategies, which must be effective and closed to the real operation conditions. As a novel contribution to structural control strategies, the theories of Interval Modal Arithmetic, Backstepping Control and QFT (Qualitative Feedback Theory) will be studied. The steps to follow are to develop first new controllers based on the above theories and then to implement the proposed control strategies to different kind of structures. The report is organized as follows. The Chapter 2 presents the state-of-the-art on structural control systems. The chapter 3 presents the most important open problems found in field of structural control. The exploratory work made by the author, research proposal and working plan are given in the Chapter 4

How robust are global conservation priorities to climate change?

International conservation organisations have identified priority areas for biodiversity conservation. These global-scale prioritisations affect the distribution of funds for conservation interventions. As each organisation has a different focus, each prioritisation scheme is determined by different decision criteria and the resultant priority areas vary considerably. However, little is known about how the priority areas will respond to the impacts of climate change. In this paper, we examined the robustness of eight global-scale prioritisations to climate change under various climate predictions from seven global circulation models. We developed a novel metric of the climate stability for 803 ecoregions based on a recently introduced method to estimate the overlap of climate envelopes. The relationships between the decision criteria and the robustness of the global prioritisation schemes were statistically examined. We found that decision criteria related to level of endemism and landscape fragmentation were strongly correlated with areas predicted to be robust to a changing climate. Hence, policies that prioritise intact areas due to the likely cost efficiency, and assumptions related to the potential to mitigate the impacts of climate change, require further examination. Our findings will help determine where additional management is required to enable biodiversity to adapt to the impacts of climate change

Optimal robust estimates using the Hellinger distance

Optimal robust M-estimates of a multidimensional parameter are described using Hampel's infinitesimal approach. The optimal estimates are derived by minimizing a measure of efficiency under the model, subject to a bounded measure of infinitesimal robustness. To this purpose we define measures of efficiency and infinitesimal sensitivity based on the Hellinger distance.We show that these two measures coincide with similar ones defined by Yohai using the Kullback-Leibler divergence, and therefore the corresponding optimal estimates coincide too.We also give an example where we fit a negative binomial distribution to a real dataset of "days of stay in hospital" using the optimal robust estimates.

Robust synchronization of coupled circadian and cell cycle oscillators in single mammalian cells.

Circadian cycles and cell cycles are two fundamental periodic processes with a period in the range of 1 day. Consequently, coupling between such cycles can lead to synchronization. Here, we estimated the mutual interactions between the two oscillators by time-lapse imaging of single mammalian NIH3T3 fibroblasts during several days. The analysis of thousands of circadian cycles in dividing cells clearly indicated that both oscillators tick in a 1:1 mode-locked state, with cell divisions occurring tightly 5 h before the peak in circadian Rev-Erbα-YFP reporter expression. In principle, such synchrony may be caused by either unidirectional or bidirectional coupling. While gating of cell division by the circadian cycle has been most studied, our data combined with stochastic modeling unambiguously show that the reverse coupling is predominant in NIH3T3 cells. Moreover, temperature, genetic, and pharmacological perturbations showed that the two interacting cellular oscillators adopt a synchronized state that is highly robust over a wide range of parameters. These findings have implications for circadian function in proliferative tissues, including epidermis, immune cells, and cancer.

Robust fault detection using consistency techniques for uncertainty handling

Often practical performance of analytical redundancy for fault detection and diagnosis is decreased by uncertainties prevailing not only in the system model, but also in the measurements. In this paper, the problem of fault detection is stated as a constraint satisfaction problem over continuous domains with a big number of variables and constraints. This problem can be solved using modal interval analysis and consistency techniques. Consistency techniques are then shown to be particularly efficient to check the consistency of the analytical redundancy relations (ARRs), dealing with uncertain measurements and parameters. Through the work presented in this paper, it can be observed that consistency techniques can be used to increase the performance of a robust fault detection tool, which is based on interval arithmetic. The proposed method is illustrated using a nonlinear dynamic model of a hydraulic system

Developing methodologies to allow the robust prediction dynamic context dominated by perturbations

El principal objectiu del projecte era desenvolupar millores conceptuals i metodològiques que permetessin una millor predicció dels canvis en la distribució de les espècies (a una escala de paisatge) derivats de canvis ambientals en un context dominat per pertorbacions. En un primer estudi, vàrem comparar l'eficàcia de diferents models dinàmics per a predir la distribució de l'hortolà (Emberiza hortulana). Els nostres resultats indiquen que un model híbrid que combini canvis en la qualitat de l'hàbitat, derivats de canvis en el paisatge, amb un model poblacional espacialment explícit és una aproximació adequada per abordar canvis en la distribució d'espècies en contextos de dinàmica ambiental elevada i una capacitat de dispersió limitada de l'espècie objectiu. En un segon estudi abordarem la calibració mitjançant dades de seguiment de models de distribució dinàmics per a 12 espècies amb preferència per hàbitats oberts. Entre les conclusions extretes destaquem: (1) la necessitat de que les dades de seguiment abarquin aquelles àrees on es produeixen els canvis de qualitat; (2) el biaix que es produeix en la estimació dels paràmetres del model d'ocupació quan la hipòtesi de canvi de paisatge o el model de qualitat d'hàbitat són incorrectes. En el darrer treball estudiarem el possible impacte en 67 espècies d’ocells de diferents règims d’incendis, definits a partir de combinacions de nivells de canvi climàtic (portant a un augment esperat de la mida i freqüència d’incendis forestals), i eficiència d’extinció per part dels bombers. Segons els resultats dels nostres models, la combinació de factors antropogènics del regim d’incendis, tals com l’abandonament rural i l’extinció, poden ser més determinants per als canvis de distribució que els efectes derivats del canvi climàtic. Els productes generats inclouen tres publicacions científiques, una pàgina web amb resultats del projecte i una llibreria per a l'entorn estadístic R.

Towards robust network based complex systems : from evolutionary cellular automata to biological models

Abstract Sitting between your past and your future doesn't mean you are in the present. Dakota Skye Complex systems science is an interdisciplinary field grouping under the same umbrella dynamical phenomena from social, natural or mathematical sciences. The emergence of a higher order organization or behavior, transcending that expected of the linear addition of the parts, is a key factor shared by all these systems. Most complex systems can be modeled as networks that represent the interactions amongst the system's components. In addition to the actual nature of the part's interactions, the intrinsic topological structure of underlying network is believed to play a crucial role in the remarkable emergent behaviors exhibited by the systems. Moreover, the topology is also a key a factor to explain the extraordinary flexibility and resilience to perturbations when applied to transmission and diffusion phenomena. In this work, we study the effect of different network structures on the performance and on the fault tolerance of systems in two different contexts. In the first part, we study cellular automata, which are a simple paradigm for distributed computation. Cellular automata are made of basic Boolean computational units, the cells; relying on simple rules and information from- the surrounding cells to perform a global task. The limited visibility of the cells can be modeled as a network, where interactions amongst cells are governed by an underlying structure, usually a regular one. In order to increase the performance of cellular automata, we chose to change its topology. We applied computational principles inspired by Darwinian evolution, called evolutionary algorithms, to alter the system's topological structure starting from either a regular or a random one. The outcome is remarkable, as the resulting topologies find themselves sharing properties of both regular and random network, and display similitudes Watts-Strogtz's small-world network found in social systems. Moreover, the performance and tolerance to probabilistic faults of our small-world like cellular automata surpasses that of regular ones. In the second part, we use the context of biological genetic regulatory networks and, in particular, Kauffman's random Boolean networks model. In some ways, this model is close to cellular automata, although is not expected to perform any task. Instead, it simulates the time-evolution of genetic regulation within living organisms under strict conditions. The original model, though very attractive by it's simplicity, suffered from important shortcomings unveiled by the recent advances in genetics and biology. We propose to use these new discoveries to improve the original model. Firstly, we have used artificial topologies believed to be closer to that of gene regulatory networks. We have also studied actual biological organisms, and used parts of their genetic regulatory networks in our models. Secondly, we have addressed the improbable full synchronicity of the event taking place on. Boolean networks and proposed a more biologically plausible cascading scheme. Finally, we tackled the actual Boolean functions of the model, i.e. the specifics of how genes activate according to the activity of upstream genes, and presented a new update function that takes into account the actual promoting and repressing effects of one gene on another. Our improved models demonstrate the expected, biologically sound, behavior of previous GRN model, yet with superior resistance to perturbations. We believe they are one step closer to the biological reality.

The influence of institutionalization on the perception of autonomy and quality of life in old people

Objective To evaluate the influence exercised by institutionalization on the autonomy and perception of quality of life among the institutionalized elderly. Method The study is quasi-experimental (interrupted time series) and longitudinal. The sample is composed for 104 elderly people who went into a three nursing home in Santander, Spain. To assess the quality of life and dependence two scales were used: the Barthel Index and Lawton Index. Results There was an important relationship between autonomy and independence and their deterioration due to their institutionalisation, such as the physical and social aspects. Conclusion It´s important to point out that the dependence of the elderly is a complex phenomenon, which admits many types of intervention, including the customary ones referring to more classic welfare actions which tend to supplant the absence of autonomy in everyday life by facilitating services and attention to make up for this need, without having to resort to institutionalization.

Virus-like particles induce robust human T-helper cell responses.

Among synthetic vaccines, virus-like particles (VLPs) are used for their ability to induce strong humoral responses. Very little is reported on VLP-based-vaccine-induced CD4(+) T-cell responses, despite the requirement of helper T cells for antibody isotype switching. Further knowledge on helper T cells is also needed for optimization of CD8(+) T-cell vaccination. Here, we analysed human CD4(+) T-cell responses to vaccination with MelQbG10, which is a Qβ-VLP covalently linked to a long peptide derived from the melanoma self-antigen Melan-A. In all analysed patients, we found strong antibody responses of mainly IgG1 and IgG3 isotypes, and concomitant Th1-biased CD4(+) T-cell responses specific for Qβ. Although less strong, comparable B- and CD4(+) T-cell responses were also found specific for the Melan-A cargo peptide. Further optimization is required to shift the response more towards the cargo peptide. Nevertheless, the data demonstrate the high potential of VLPs for inducing humoral and cellular immune responses by mounting powerful CD4(+) T-cell help.

Toward a Statistically Robust Assessment of Social and Solidarity Economy Actors. Conceptual Development and Empirical Validation

Many definitions and debates exist about the core characteristics of social and solidarity economy (SSE) and its actors. Among others, legal forms, profit, geographical scope, and size as criteria for identifying SSE actors often reveal dissents among SSE scholars. Instead of using a dichotomous, either-in-or-out definition of SSE actors, this paper presents an assessment tool that takes into account multiple dimensions to offer a more comprehensive and nuanced view of the field. We first define the core dimensions of the assessment tool by synthesizing the multiple indicators found in the literature. We then empirically test these dimensions and their interrelatedness and seek to identify potential clusters of actors. Finally we discuss the practical implications of our model.

Asymptotic robust inferences in the analysis of mean and covariance structures

Structural equation models are widely used in economic, socialand behavioral studies to analyze linear interrelationships amongvariables, some of which may be unobservable or subject to measurementerror. Alternative estimation methods that exploit different distributionalassumptions are now available. The present paper deals with issues ofasymptotic statistical inferences, such as the evaluation of standarderrors of estimates and chi--square goodness--of--fit statistics,in the general context of mean and covariance structures. The emphasisis on drawing correct statistical inferences regardless of thedistribution of the data and the method of estimation employed. A(distribution--free) consistent estimate of $\Gamma$, the matrix ofasymptotic variances of the vector of sample second--order moments,will be used to compute robust standard errors and a robust chi--squaregoodness--of--fit squares. Simple modifications of the usual estimateof $\Gamma$ will also permit correct inferences in the case of multi--stage complex samples. We will also discuss the conditions under which,regardless of the distribution of the data, one can rely on the usual(non--robust) inferential statistics. Finally, a multivariate regressionmodel with errors--in--variables will be used to illustrate, by meansof simulated data, various theoretical aspects of the paper.

Robust response transformations based on optimal prediction

Nonlinear regression problems can often be reduced to linearity by transforming the response variable (e.g., using the Box-Cox family of transformations). The classic estimates of the parameter defining the transformation as well as of the regression coefficients are based on the maximum likelihood criterion, assuming homoscedastic normal errors for the transformed response. These estimates are nonrobust in the presence of outliers and can be inconsistent when the errors are nonnormal or heteroscedastic. This article proposes new robust estimates that are consistent and asymptotically normal for any unimodal and homoscedastic error distribution. For this purpose, a robust version of conditional expectation is introduced for which the prediction mean squared error is replaced with an M scale. This concept is then used to develop a nonparametric criterion to estimate the transformation parameter as well as the regression coefficients. A finite sample estimate of this criterion based on a robust version of smearing is also proposed. Monte Carlo experiments show that the new estimates compare favorably with respect to the available competitors.

Robust T1-Weighted Structural Brain Imaging and Morphometry at 7T Using MP2RAGE.

PURPOSE: To suppress the noise, by sacrificing some of the signal homogeneity for numerical stability, in uniform T1 weighted (T1w) images obtained with the magnetization prepared 2 rapid gradient echoes sequence (MP2RAGE) and to compare the clinical utility of these robust T1w images against the uniform T1w images. MATERIALS AND METHODS: 8 healthy subjects (29.0±4.1 years; 6 Male), who provided written consent, underwent two scan sessions within a 24 hour period on a 7T head-only scanner. The uniform and robust T1w image volumes were calculated inline on the scanner. Two experienced radiologists qualitatively rated the images for: general image quality; 7T specific artefacts; and, local structure definition. Voxel-based and volume-based morphometry packages were used to compare the segmentation quality between the uniform and robust images. Statistical differences were evaluated by using a positive sided Wilcoxon rank test. RESULTS: The robust image suppresses background noise inside and outside the skull. The inhomogeneity introduced was ranked as mild. The robust image was significantly ranked higher than the uniform image for both observers (observer 1/2, p-value = 0.0006/0.0004). In particular, an improved delineation of the pituitary gland, cerebellar lobes was observed in the robust versus uniform T1w image. The reproducibility of the segmentation results between repeat scans improved (p-value = 0.0004) from an average volumetric difference across structures of ≈6.6% to ≈2.4% for the uniform image and robust T1w image respectively. CONCLUSIONS: The robust T1w image enables MP2RAGE to produce, clinically familiar T1w images, in addition to T1 maps, which can be readily used in uniform morphometry packages.

Health care management autonomy: Evidence from the Catalonian hospital sector in a decentralised Spain

The organisation of inpatient care provision has undergone significant reform in many southern European countries. Overall across Europe, public management is moving towards the introduction of more flexibility and autonomy . In this setting, the promotion of the further decentralisation of health care provision stands out as a key salient policy option in all countries that have hitherto had a traditionally centralised structure. Yet, the success of the underlying incentives that decentralised structures create relies on the institutional design at the organisational level, especially in respect of achieving efficiency and promoting policy innovation without harming the essential principle of equal access for equal need that grounds National Health Systems (NHS). This paper explores some of the specific organisational developments of decentralisation structures drawing from the Spanish experience, and particularly those in the Catalonia. This experience provides some evidence of the extent to which organisation decentralisation structures that expand levels of autonomy and flexibility lead to organisational innovation while promoting activity and efficiency. In addition to this pure managerial decentralisation process, Spain is of particular interest as a result of the specific regional NHS decentralisation that started in the early 1980 s and was completed in 2002 when all seventeen autonomous communities that make up the country had responsibility for health care services.Already there is some evidence to suggest that this process of decentralisation has been accompanied by a degree of policy innovation and informal regional cooperation. Indeed, the Spanish experience is relevant because both institutional changes took place, namely managerial decentralisation leading to higher flexibility and autonomy- alongside an increasing political decentralisation at the regional level. The coincidence of both processes could potentially explain why some organisation and policy innovation resulting from policy experimentation at the regional level might be an additional featureto take into account when examining the benefits of decentralisation.