Adaptive Scattered Data Fitting with Tensor Product Spline-Wavelets

The core of the work we present here is an algorithm that constructs a least squares approximation to a given set of unorganized points. The approximation is expressed as a linear combination of particular B-spline wavelets. It implies a multiresolution setting which constructs a hierarchy of approximations to the data with increasing level of detail, proceeding from coarsest to finest scales. It allows for an efficient selection of the degrees of freedom of the problem and avoids the introduction of an artificial uniform grid. In fact, an analysis of the data can be done at each of the scales of the hierarchy, which can be used to select adaptively a set of wavelets that can represent economically the characteristics of the cloud of points in the next level of detail. The data adaption of our method is twofold, as it takes into account both horizontal distribution and vertical irregularities of data. This strategy can lead to a striking reduction of the problem complexity. Furthermore, among the possible ways to achieve a multiscale formulation, the wavelet approach shows additional advantages, based on good conditioning properties and level-wise orthogonality. We exploit these features to enhance the efficiency of iterative solution methods for the system of normal equations of the problem. The combination of multiresolution adaptivity with the numerical properties of the wavelet basis gives rise to an algorithm well suited to cope with problems requiring fast solution methods. We illustrate this by means of numerical experiments that compare the performance of the method on various data sets working with different multi-resolution bases. Afterwards, we use the equivalence relation between wavelets and Besov spaces to formulate the problem of data fitting with regularization. We find that the multiscale formulation allows for a flexible and efficient treatment of some aspects of this problem. Moreover, we study the problem known as robust fitting, in which the data is assumed to be corrupted by wrong measurements or outliers. We compare classical methods based on re-weighting of residuals to our setting in which the wavelet representation of the data computed by our algorithm is used to locate the outliers. As a final application that couples two of the main applications of wavelets (data analysis and operator equations), we propose the use of this least squares data fitting method to evaluate the non-linear term in the wavelet-Galerkin formulation of non-linear PDE problems. At the end of this thesis we discuss efficient implementation issues, with a special interest in the interplay between solution methods and data structures

Experiencias significativas en torno a la aplicación de estrategias para la enseñanza de procesos químico industriales a estudiantes de secundaria por ciclos

La enseñanza de la química como ciencia básica a nivel de educación media vocacional siempre ha sido independiente de la realidad aplicativa de los productos y procesos industriales que regulan nuestra cotidianidad. Gran cantidad de docentes, profesionales en educación y demás personas preocupadas por la calidad de los contenidos curriculares han cuestionado los acercamientos entre los ejes temáticos y la vida misma1; de hecho los laboratorios y sesiones demostrativas o de observación han buscado acercar al estudiante a la dimensión de las reacciones químicas, fenómenos de transformación de partículas y demás principios de las ciencias en términos prácticos, sin embargo existe aun una brecha considerable entre la relación que establece el estudiante con la química impartida en su aula de clases y las situaciones que considera comunes en su existencia y que por supuesto implican conexión con la ciencia que reciben y que eventualmente ¿aceptan¿. Es menester de los profesionales en química industrial con especial interés en la educación buscar los mecanismos para acercar su área de conocimiento a la comunidad en etapas formativas intelectuales, mas precisamente los estudiantes de secundaria y demostrarles que el conjunto de ecuaciones estériles para su juicio, encuentran una correlación directa y profunda en los productos de uso diario y por que no decir de inminente necesidad en el hogar; por ende es ..

In situ structure determination by subtomogram averaging

Cryo-tomography and subtomogram averaging are increasingly popular techniques for structural determination of macromolecular complexes in situ. They have the potential to achieve high-resolution views of native complexes, together with the details of their location relative to interacting molecules. The subtomogram averaging (StA) pipelines are well-established, with current developments aiming to optimise each step by reducing manual intervention and user decisions, following similar trends in single-particle approaches that have dramatically increased their popularity. Here, we review the main steps of typical StA workflows. We focus on considerations arising from the fact that the objects of study are embedded within unique crowded environments, and we emphasise those steps where careful decisions need to be made by the user. [Abstract copyright: Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.

Automatic plankton quantification using deep features

The study of marine plankton data is vital to monitor the health of the world’s oceans. In recent decades, automatic plankton recognition systems have proved useful to address the vast amount of data collected by specially engineered in situ digital imaging systems. At the beginning, these systems were developed and put into operation using traditional automatic classification techniques, which were fed with handdesigned local image descriptors (such as Fourier features), obtaining quite successful results. In the past few years, there have been many advances in the computer vision community with the rebirth of neural networks. In this paper, we leverage how descriptors computed using Convolutional Neural Networks (CNNs) trained with out-of-domain data are useful to replace hand-designed descriptors in the task of estimating the prevalence of each plankton class in a water sample. To achieve this goal, we have designed a broad set of experiments that show how effective these deep features are when working in combination with state-of-the-art quantification algorithms

Metodología para el acceso a la financiación de proyectos productivos de pequeñas y medianas empresas en el marco del mercado de capitales en Colombia

Las PYMES son una de las principales fuentes de crecimiento de la economía en Colombia, sin embargo, es frecuente encontrar que su periodo de vigencia suele ser inferior a los 3 años. Si bien existen múltiples razones para comprender dicho fenómeno, con base en los estudios que se abordarán en el presente texto, se identifica como principal causa, la falta de recursos o mecanismos de financiación idóneos para este tipo empresarial. Después de abordar algunas de las modalidades de crédito que con frecuencia son consideradas para el desarrollo de los proyectos de las PYMES, se encuentra que existe una importante fuente de financiación no bancaria plenamente regulada en Colombia, que aún no cuenta con suficiente difusión. Ésta se considera como una potencial solución para el acceso a la financiación que éstas requieren. Es el crowdfunding financiero o financiación colaborativa, un mecanismo alternativo de financiación, derivado de la tendencia de las Fintech, fundamentado en las bases del mercado de capitales. Más que un nuevo competidor, el esquema de financiación colaborativa es una solución para un segmento desatendido por el sistema bancario tradicional, al cual se podrá acceder siguiendo la metodología diseñada como resultado del presente trabajo de investigación.SMEs are one of the main sources of Colombian economy growth, however, it is common to find that their term is usually less than 3 years. While there are multiple reasons to understand this phenomenon, based on the studies to be addressed in this text, the lack of adequate resources or financing mechanisms for this type of business is identified as the main cause. After addressing some of the credit modalities that are often considered for the development of SME projects, it is found that, there is an important source of fully regulated non-bank financing in Colombia that is not yet sufficiently widely available. This is seen as a potential solution for access to the funding they require. It is financial crowdfunding or collaborative financing, an alternative financing mechanism derived from the Fintech trend, based on the foundations of the capital market. More than a new competitor, the collaborative financing scheme is a solution for a segment neglected by the traditional banking system, which can be accessed following the methodology designed as a result of this research work

Protocols for Subtomogram Averaging of Membrane Proteins in the Dynamo Software Package

Cryo-electron tomography allows low-resolution three-dimensional (3D) viewing of cellular organelles and macromolecular complexes present as multiple copies within a tomogram. These structures are computationally extracted and averaged in order to obtain high-resolution 3D structures, and provide a map of their spatial distribution and interaction with their biological microenvironment. To do so, we apply the user-friendly Dynamo software package on a tomographic data set. Dynamo acts as a modular toolbox adaptable to different biological scenarios, allowing a custom designed pipeline for subtomogram averaging. Here, we use as a textbook example the mitochondrial docking site of the positive-strand RNA Flock house nodavirus (FHV) to describe how Dynamo coordinates several basic steps in the subtomogram averaging workflow. Our framework covers specific strategies to deal with additional issues in subtomogram averaging as tomographic data management, 3D surface visualization, automatic assignment of asymmetry and inherent loss of Fourier information in presence of preferential views

Radiation dose reduction and image enhancement in biological imaging through equally-sloped tomography

Electron tomography is currently the highest resolution imaging modality available to study the 3D structures of pleomorphic macromolecular assemblies, viruses, organelles and cells. Unfortunately, the resolution is currently limited to 3–5 nm by several factors including the dose tolerance of biological specimens and the inaccessibility of certain tilt angles. Here we report the first experimental demonstration of equally-sloped tomography (EST) to alleviate these problems. As a proof of principle, we applied EST to reconstructing frozen-hydrated keyhole limpet hemocyanin molecules from a tilt-series taken with constant slope increments. In comparison with weighted back-projection (WBP), the algebraic reconstruction technique (ART) and the simultaneous algebraic reconstruction technique (SART), EST reconstructions exhibited higher contrast, less peripheral noise, more easily detectable molecular boundaries and reduced missing wedge effects. More importantly, EST reconstructions including only two-thirds the original images appeared to have the same resolution as full WBP reconstructions, suggesting that EST can either reduce the dose required to reach a given resolution or allow higher resolutions to be achieved with a given dose. EST was also applied to reconstructing a frozen-hydrated bacterial cell from a tilt-series taken with constant angular increments. The results confirmed similar benefits when standard tilts are utilized

Relation between EEG resting-state power and modulation of P300 task-related activity in theta band in schizophrenia

Producción CientíficaThere is some consistency in previous EEG findings that patients with schizophrenia have increased resting-state cortical activity. Furthermore, in previous work, we have provided evidence that there is a deficit in the modulation of bioelectrical activity during the performance of a P300 task in schizophrenia. Our hypothesis here is that a basal hyperactivation would be related with altered ability to change or modulate cortical activity during a cognitive task. However, no study so far, to the best of our knowledge, has studied the association between resting-state activity and task-related modulation. With this aim, we used a dual EEG paradigm (resting state and oddball task for elicitation of the P300 evoked potential) in a sample of patients with schizophrenia (n = 100), which included a subgroup of patients with first episode psychosis (n = 30), as well as a group of healthy controls (n = 93). The study measures were absolute power for resting-state; and spectral entropy (SE) and connectivity strength (CS) for P300-task data, whose modulation had been previously found to be altered in schizophrenia. Following the literature on P300, we focused our study on the theta frequency band. As expected, our results showed an increase in resting state activity and altered task-related modulation. Moreover, we found an inverse relationship between the amount of resting-state activity and modulation of task-related activity. Our results confirm our hypothesis and support the idea that a greater amount of resting theta-band synchrony could hamper the modulation of signal regularity (quantified by SE) and activity density (measured by CS) during the P300 task performance. This association was found in both patients and controls, suggesting the existence of a common mechanism and a possible ceiling effect in schizophrenia patients in relation to a decreased inhibitory function that limits their cortical reactivity to the task

Mutational Profile Enables the Identification of a High-Risk Subgroup in Myelodysplastic Syndromes with Isolated Trisomy 8

Simple Summary Trisomy 8 (+8) is one of the most frequent cytogenetic alterations found in myelodysplastic syndromes (MDS). MDS patients harboring isolated +8 show clinical heterogeneity, and life expectancy varies between several months and several years after diagnosis. We aimed to investigate whether the mutational profile of isolated +8 MDS patients could help to clarify the heterogeneous prognosis of these patients. In fact, we found that mutations in STAG2, SRSF2 and RUNX1 are independent prognostic factors, enough to define the course of the disease in terms of overall survival and leukemic transformation in isolated +8 MDS. Therefore, these findings might help to identify patients at a high risk of evolving disease and open new horizons by changes in the management of a high subset of patients within MDS with isolated +8. Trisomy 8 (+8) is the most frequent trisomy in myelodysplastic syndromes (MDS) and is associated with clinical heterogeneity and intermediate cytogenetic risk when found in isolation. The presence of gene mutations in this group of patients and the prognostic significance has not been extensively analyzed. Targeted deep sequencing was performed in a cohort of 79 MDS patients showing isolated +8. The most frequently mutated genes were: TET2 (38%), STAG2 (34.2%), SRSF2 (29.1%) and RUNX1 (26.6%). The mutational profile identified a high-risk subgroup with mutations in STAG2, SRSF2 and/or RUNX1, resulting in shorter time to acute myeloid leukemia progression (14 months while not reached in patients without these mutations, p < 0.0001) and shorter overall survival (23.7 vs. 46.3 months, p = 0.001). Multivariate analyses revealed the presence of mutations in these genes as an independent prognostic factor in MDS showing +8 isolated (HR: 3.1; p < 0.01). Moreover, 39.5% and 15.4% of patients classified as low/intermediate risk by the IPSS-R and IPSS-M, respectively, were re-stratified as a high-risk subgroup based on the mutational status of STAG2, SRSF2 and RUNX1. Results were validated in an external cohort (n = 2494). In summary, this study validates the prognosis significance of somatic mutations shown in IPSS-M and adds STAG2 as an important mutated gene to consider in this specific subgroup of patients. The mutational profile in isolated +8 MDS patients could, therefore, offer new insights for the correct management of patients with a higher risk of leukemic transformation

A Bayesian approach to single-particle electron cryo-tomography in RELION-4.0

We present a new approach for macromolecular structure determination from multiple particles in electron cryo-tomography (cryo-ET) data sets. Whereas existing subtomogram averaging approaches are based on 3D data models, we propose to optimise a regularised likelihood target that approximates a function of the 2D experimental images. In addition, analogous to Bayesian polishing and contrast transfer function (CTF) refinement in single-particle analysis, we describe the approaches that exploit the increased signal-to-noise ratio in the averaged structure to optimise tilt-series alignments, beam-induced motions of the particles throughout the tilt-series acquisition, defoci of the individual particles, as well as higher-order optical aberrations of the microscope. Implementation of our approaches in the open-source software package RELION aims to facilitate their general use, particularly for those researchers who are already familiar with its single-particle analysis tools. We illustrate for three applications that our approaches allow structure determination from cryo-ET data to resolutions sufficient for de novo atomic modelling.This work was funded by the UK Research and Innovation (UKRI) Medical Research Council (MC_UP_A025_1013 to SHWS; and MC_UP_1201/16 to JAGB), the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (ERC-CoG-2014, grant 648432, MEMBRANEFUSION to JAGB and ERC StG-2019, grant 852915 CRYTOCOP to GZ); the Swiss National Science Foundation (grant 205321_179041/1 to DC-D), the Max Planck Society (to JAGB) and the UKRI Biotechnology and Biological Sciences Research Council (grant BB/T002670/1 to GZ). TAMB is a recipient of a Sir Henry Dale Fellowship, jointly funded by the Wellcome Trust and the Royal Society (202231/Z/16/Z). JZ was partially funded by the European Union’s Horizon 2020 research and innovation program (ERC-ADG-2015, grant 692726, GlobalBioIm to Michael Unser)