Fast Locality-Sensitive Hashing Frameworks for Approximate Near Neighbor Search

The Indyk-Motwani Locality-Sensitive Hashing (LSH) framework (STOC 1998) is a general technique for constructing a data structure to answer approximate near neighbor queries by using a distribution $\mathcal{H}$ over locality-sensitive hash functions that partition space. For a collection of $n$ points, after preprocessing, the query time is dominated by $O(n^{\rho} \log n)$ evaluations of hash functions from $\mathcal{H}$ and $O(n^{\rho})$ hash table lookups and distance computations where $\rho \in (0,1)$ is determined by the locality-sensitivity properties of $\mathcal{H}$. It follows from a recent result by Dahlgaard et al. (FOCS 2017) that the number of locality-sensitive hash functions can be reduced to $O(\log^2 n)$, leaving the query time to be dominated by $O(n^{\rho})$ distance computations and $O(n^{\rho} \log n)$ additional word-RAM operations. We state this result as a general framework and provide a simpler analysis showing that the number of lookups and distance computations closely match the Indyk-Motwani framework, making it a viable replacement in practice. Using ideas from another locality-sensitive hashing framework by Andoni and Indyk (SODA 2006) we are able to reduce the number of additional word-RAM operations to $O(n^\rho)$.Comment: 15 pages, 3 figure

Approximate Near Neighbors for General Symmetric Norms

We show that every symmetric normed space admits an efficient nearest neighbor search data structure with doubly-logarithmic approximation. Specifically, for every $n$, $d = n^{o(1)}$, and every $d$-dimensional symmetric norm $\|\cdot\|$, there exists a data structure for $\mathrm{poly}(\log \log n)$-approximate nearest neighbor search over $\|\cdot\|$ for $n$-point datasets achieving $n^{o(1)}$ query time and $n^{1+o(1)}$ space. The main technical ingredient of the algorithm is a low-distortion embedding of a symmetric norm into a low-dimensional iterated product of top-$k$ norms. We also show that our techniques cannot be extended to general norms.Comment: 27 pages, 1 figur

On the segmentation and classification of hand radiographs

This research is part of a wider project to build predictive models of bone age using hand radiograph images. We examine ways of finding the outline of a hand from an X-ray as the first stage in segmenting the image into constituent bones. We assess a variety of algorithms including contouring, which has not previously been used in this context. We introduce a novel ensemble algorithm for combining outlines using two voting schemes, a likelihood ratio test and dynamic time warping (DTW). Our goal is to minimize the human intervention required, hence we investigate alternative ways of training a classifier to determine whether an outline is in fact correct or not. We evaluate outlining and classification on a set of 1370 images. We conclude that ensembling with DTW improves performance of all outlining algorithms, that the contouring algorithm used with the DTW ensemble performs the best of those assessed, and that the most effective classifier of hand outlines assessed is a random forest applied to outlines transformed into principal components

Off the Beaten Path: Let's Replace Term-Based Retrieval with k-NN Search

Retrieval pipelines commonly rely on a term-based search to obtain candidate records, which are subsequently re-ranked. Some candidates are missed by this approach, e.g., due to a vocabulary mismatch. We address this issue by replacing the term-based search with a generic k-NN retrieval algorithm, where a similarity function can take into account subtle term associations. While an exact brute-force k-NN search using this similarity function is slow, we demonstrate that an approximate algorithm can be nearly two orders of magnitude faster at the expense of only a small loss in accuracy. A retrieval pipeline using an approximate k-NN search can be more effective and efficient than the term-based pipeline. This opens up new possibilities for designing effective retrieval pipelines. Our software (including data-generating code) and derivative data based on the Stack Overflow collection is available online

Distance-Sensitive Hashing

Locality-sensitive hashing (LSH) is an important tool for managing high-dimensional noisy or uncertain data, for example in connection with data cleaning (similarity join) and noise-robust search (similarity search). However, for a number of problems the LSH framework is not known to yield good solutions, and instead ad hoc solutions have been designed for particular similarity and distance measures. For example, this is true for output-sensitive similarity search/join, and for indexes supporting annulus queries that aim to report a point close to a certain given distance from the query point. In this paper we initiate the study of distance-sensitive hashing (DSH), a generalization of LSH that seeks a family of hash functions such that the probability of two points having the same hash value is a given function of the distance between them. More precisely, given a distance space $(X, \text{dist})$ and a "collision probability function" (CPF) $f\colon \mathbb{R}\rightarrow [0,1]$ we seek a distribution over pairs of functions $(h,g)$ such that for every pair of points $x, y \in X$ the collision probability is $\Pr[h(x)=g(y)] = f(\text{dist}(x,y))$. Locality-sensitive hashing is the study of how fast a CPF can decrease as the distance grows. For many spaces, $f$ can be made exponentially decreasing even if we restrict attention to the symmetric case where $g=h$. We show that the asymmetry achieved by having a pair of functions makes it possible to achieve CPFs that are, for example, increasing or unimodal, and show how this leads to principled solutions to problems not addressed by the LSH framework. This includes a novel application to privacy-preserving distance estimation. We believe that the DSH framework will find further applications in high-dimensional data management.Comment: Accepted at PODS'18. Abstract shortened due to character limi

The prevalence of axial spondyloarthritis in the UK: a cross-sectional cohort study

Background: Accurate prevalence data are important when interpreting diagnostic tests and planning for the health needs of a population, yet no such data exist for axial spondyloarthritis (axSpA) in the UK. In this cross-sectional cohort study we aimed to estimate the prevalence of axSpA in a UK primary care population. Methods: A validated self-completed questionnaire was used to screen primary care patients with low back pain for inflammatory back pain (IBP). Patients with a verifiable pre-existing diagnosis of axSpA were included as positive cases. All other patients meeting the Assessment of SpondyloArthritis international Society (ASAS) IBP criteria were invited to undergo further assessment including MRI scanning, allowing classification according to the European Spondyloarthropathy Study Group (ESSG) and ASAS axSpA criteria, and the modified New York (mNY) criteria for ankylosing spondylitis (AS). Results: Of 978 questionnaires sent to potential participants 505 were returned (response rate 51.6 %). Six subjects had a prior diagnosis of axSpA, 4 of whom met mNY criteria. Thirty eight of 75 subjects meeting ASAS IBP criteria attended review (mean age 53.5 years, 37 % male). The number of subjects satisfying classification criteria was 23 for ESSG, 3 for ASAS (2 clinical, 1 radiological) and 1 for mNY criteria. This equates to a prevalence of 5.3 % (95 % CI 4.0, 6.8) using ESSG, 1.3 % (95 % CI 0.8, 2.3) using ASAS, 0.66 % (95 % CI 0.28, 1.3) using mNY criteria in chronic back pain patients, and 1.2 % (95 % CI 0.9, 1.4) using ESSG, 0.3 % (95 % CI 0.13, 0.48) using ASAS, 0.15 % (95 % CI 0.02, 0.27) using mNY criteria in the general adult primary care population. Conclusions: These are the first prevalence estimates for axSpA in the UK, and will be of importance in planning for the future healthcare needs of this population. Trial registration: Current Controlled Trials ISRCTN7687321

Quantization and Compressive Sensing

Quantization is an essential step in digitizing signals, and, therefore, an indispensable component of any modern acquisition system. This book chapter explores the interaction of quantization and compressive sensing and examines practical quantization strategies for compressive acquisition systems. Specifically, we first provide a brief overview of quantization and examine fundamental performance bounds applicable to any quantization approach. Next, we consider several forms of scalar quantizers, namely uniform, non-uniform, and 1-bit. We provide performance bounds and fundamental analysis, as well as practical quantizer designs and reconstruction algorithms that account for quantization. Furthermore, we provide an overview of Sigma-Delta ($\Sigma\Delta$) quantization in the compressed sensing context, and also discuss implementation issues, recovery algorithms and performance bounds. As we demonstrate, proper accounting for quantization and careful quantizer design has significant impact in the performance of a compressive acquisition system.Comment: 35 pages, 20 figures, to appear in Springer book "Compressed Sensing and Its Applications", 201

Spongionella Secondary Metabolites Regulate Store Operated Calcium Entry Modulating Mitochondrial Functioning in SH-SY5Y Neuroblastoma Cells

cknowledgements The research leading to these results has received funding from the following FEDER cofounded-grants. From CDTI and Technological Funds, supported by Ministerio de Economía y Competitividad, AGL2012-40185-CO2-01, AGL2014-58210-R, and Consellería de Cultura, Educación e OrdenaciónUniversitaria, GRC2013-016, and through AxenciaGalega de Innovación, Spain, ITC-20133020 SINTOX. From CDTI under ISIP Programme, Spain, IDI-20130304 APTAFOOD. From the European Union's Seventh Framework Programme managed by REA - Research Executive Agency (FP7/2007-2013) under grant agreement 312184 PHARMASEA. Jon Andoni Sánchez is supported by a fellowship from Plan Galego de Investigación e Crecemento, Xunta de Galicia, Spain.Peer reviewedPublisher PD

Las emociones en la enseñanza de las ciencias

En la primera parte del artículo, se incide en la importancia del estudio de las emociones desde la didáctica de las ciencias, así como en la necesidad de establecer programas de intervención metacognitivos y metaemocionales, tanto en el aprendizaje como en la formación del profesorado, para que alumnos y profesores puedan conocer sus emociones, controlarlas y autorregularlas. En la segunda parte, nos centramos en las emociones en el conocimiento didáctico del contenido del profesorado de ciencias, incluyendo algunos resultados tanto del diagnóstico emocional del profesorado, según distintas variables, como del programa de intervención de la Universidad de Extremadura.The first part of this communication highlights the importance of studying emotions in the context of science teaching. It also examines the need for programs of meta-emotional and metacognitive intervention in learning and teacher education that are aimed at both the future teachers'and their pupils' gaining awareness of, and then controlling and self-regulating, their emotions. The second part focuses on the role emotions play in science teachers' pædagogical content knowledge, with the presentation of some results concerning the University of Extremadura's intervention program and the emotional diagnosis of teachers.En la primera part de l'article, s'incideix en la importància de l'estudi de les emocions des de la didàctica de les ciències, així com en la necessitat d'establir programes d'intervenció metacognitivos i metaemocionales, tant en l'aprenentatge com en la formació del professorat, perquè alumnes i professors puguin conèixer les seves emocions, controlar-les i autorregularlas. En la segona part, ens centrem en les emocions en el coneixement didàctic del contingut del professorat de ciències, incloent alguns resultats tant del diagnòstic emocional del professorat, segons diferents variables, com del programa d'intervenció de la Universitat d'Extremadura

Spongionella Secondary Metabolites, Promising Modulators of Immune Response through CD147 Receptor Modulation

The modulation of the immune system can have multiple applications such as cancer treatment, and a wide type of processes involving inflammation where the potent chemotactic agent cyclophilin A (Cyp A) is implicated. The Porifera phylum, in which Spongionella is encompassed, is the main producer of marine bioactive compounds. Four secondary metabolites obtained from Spongionella (Gracilin H, A, L, and Tetrahydroaplysulphurin-1) were described to hit Cyp A and to block the release of inflammation mediators. Based on these results, some role of Spongionella compounds on other steps of the signaling pathway mediated by this chemotactic agent can be hypothesized. In the present paper, we studied the effect of these four compounds on the surface membrane CD147 receptor expression, on the extracellular levels of Cyp A and on the ability to migrate of concanavalin (Con A)-activated T lymphocytes. Similar to a well-known immunosuppressive agent cyclosporine A (CsA), Gracilin H, A, L, and tetrahydroaplysulphurin-1 were able to reduce the CD147 membrane expression and to block the release of Cyp A to the medium. Besides, by using Cyp A as chemotactic agent, T cell migration was inhibited when cells were previously incubated with Gracilin A and Gracilin L. These positive results lead us to test the in vivo effect of Gracilin H and L in a mouse ear delayed hypersensitive reaction. Thus, both compounds efficiently reduce the ear swelling as well as the inflammatory cell infiltration. These results provide more evidences for their potential therapeutic application in immune-related diseases of Spongionella compound