Constant Approximation for kk-Median and kk-Means with Outliers via Iterative Rounding

In this paper, we present a new iterative rounding framework for many clustering problems. Using this, we obtain an $(\alpha_1 + \epsilon \leq 7.081 + \epsilon)$-approximation algorithm for $k$-median with outliers, greatly improving upon the large implicit constant approximation ratio of Chen [Chen, SODA 2018]. For $k$-means with outliers, we give an $(\alpha_2+\epsilon \leq 53.002 + \epsilon)$-approximation, which is the first $O(1)$-approximation for this problem. The iterative algorithm framework is very versatile; we show how it can be used to give $\alpha_1$- and $(\alpha_1 + \epsilon)$-approximation algorithms for matroid and knapsack median problems respectively, improving upon the previous best approximations ratios of $8$ [Swamy, ACM Trans. Algorithms] and $17.46$ [Byrka et al, ESA 2015]. The natural LP relaxation for the $k$-median/$k$-means with outliers problem has an unbounded integrality gap. In spite of this negative result, our iterative rounding framework shows that we can round an LP solution to an almost-integral solution of small cost, in which we have at most two fractionally open facilities. Thus, the LP integrality gap arises due to the gap between almost-integral and fully-integral solutions. Then, using a pre-processing procedure, we show how to convert an almost-integral solution to a fully-integral solution losing only a constant-factor in the approximation ratio. By further using a sparsification technique, the additive factor loss incurred by the conversion can be reduced to any $\epsilon > 0$

Improving stress echocardiography accuracy for detecting left circumflex artery stenosis: A new echocardiographic sign?

SummaryBackgroundThe accuracy and reproducibility of stress echocardiography (SE) for the detection of coronary artery lesions requires improvement, particularly in the left circumflex artery (LCx).AimsTo evaluate the feasibility and diagnostic value of a new sign: Rise of the Apical lateral wall and/or Horizontal displacement of the Apex toward the septum (“RA-HA”) in apical echocardiographic views.MethodsConsecutive patients with normal left ventricular function at rest, positive SE and an indication for coronary angiography were included. SEs were analysed blindly by three independent cardiologists: two seniors (S1 and S2) and one junior (J).ResultsOf 81 patients, 58 had an exercise SE and 23 had a dobutamine SE. Significant coronary stenosis was found in 59 of 77 patients who underwent coronary angiography (76.6%). Interobserver reproducibility for the presence of RA-HA was very good between S1 and S2 (κ=0.86), and good between S1 and J (0.67) and S2 and J (0.70). The sensitivity, specificity and positive and negative predictive values of RA-HA for the detection of significant coronary artery stenosis were, respectively, 39–41%, 83–89%, 88–92% and 29–31% for S1/S2; and 29%, 83%, 85% and 26% for J. To predict LCx stenosis (single or multivessel): 67–70%, 89%, 80–81% and 80–82% for S1/S2, respectively, and 50%, 89%, 75% and 74% for J.ConclusionWith a short learning curve, RA-HA is easily diagnosed with a very good interobserver reproducibility. It has high specificity and PPV for the detection of a coronary artery stenosis, particularly in the LCx artery, during exercise or dobutamine SE

Event related potentials elicited by violations of auditory regularities in patients with impaired consciousness.

International audienceImproving our ability to detect conscious processing in non communicating patients remains a major goal of clinical cognitive neurosciences. In this perspective, several functional brain imaging tools are currently under development. Bedside cognitive event-related potentials (ERPs) derived from the EEG signal are a good candidate to explore consciousness in these patients because: (1) they have an optimal time resolution within the millisecond range able to monitor the stream of consciousness, (2) they are fully non-invasive and relatively cheap, (3) they can be recorded continuously on dedicated individual systems to monitor consciousness and to communicate with patients, (4) and they can be used to enrich patients' autonomy through brain-computer interfaces. We recently designed an original auditory rule extraction ERP test that evaluates cerebral responses to violations of temporal regularities that are either local in time or global across several seconds. Local violations led to an early response in auditory cortex, independent of attention or the presence of a concurrent visual task, while global violations led to a late and spatially distributed response that was only present when subjects were attentive and aware of the violations. In the present work, we report the results of this test in 65 successive recordings obtained at bedside from 49 non-communicating patients affected with various acute or chronic neurological disorders. At the individual level, we confirm the high specificity of the 'global effect': only conscious patients presented this proposed neural signature of conscious processing. Here, we also describe in details the respective neural responses elicited by violations of local and global auditory regularities, and we report two additional ERP effects related to stimuli expectancy and to task learning, and we discuss their relations to consciousness

The MVGC multivariate Granger causality toolbox: a new approach to Granger-causal inference

Background: Wiener-Granger causality (“G-causality”) is a statistical notion of causality applicable to time series data, whereby cause precedes, and helps predict, effect. It is defined in both time and frequency domains, and allows for the conditioning out of common causal influences. Originally developed in the context of econometric theory, it has since achieved broad application in the neurosciences and beyond. Prediction in the G-causality formalism is based on VAR (Vector AutoRegressive) modelling. New Method: The MVGC Matlab c Toolbox approach to G-causal inference is based on multiple equivalent representations of a VAR model by (i) regression parameters, (ii) the autocovariance sequence and (iii) the cross-power spectral density of the underlying process. It features a variety of algorithms for moving between these representations, enabling selection of the most suitable algorithms with regard to computational efficiency and numerical accuracy. Results: In this paper we explain the theoretical basis, computational strategy and application to empirical G-causal inference of the MVGC Toolbox. We also show via numerical simulations the advantages of our Toolbox over previous methods in terms of computational accuracy and statistical inference. Comparison with Existing Method(s): The standard method of computing G-causality involves estimation of parameters for both a full and a nested (reduced) VAR model. The MVGC approach, by contrast, avoids explicit estimation of the reduced model, thus eliminating a source of estimation error and improving statistical power, and in addition facilitates fast and accurate estimation of the computationally awkward case of conditional G-causality in the frequency domain. Conclusions: The MVGC Toolbox implements a flexible, powerful and efficient approach to G-causal inference. Keywords: Granger causality, vector autoregressive modelling, time series analysi

A Practical Unification of Multi-stage Programming and Macros

Program generation is indispensable. We propose a novel unification of two existing metaprogramming techniques: multi-stage programming and hygienic generative macros. The former supports runtime code generation and execution in a type-safe manner while the latter offers compile-time code generation. In this work we draw upon a long line of research on metaprogramming, starting with Lisp, MetaML and MetaOCaml. We provide direct support for quotes, splices and top-level splices, all regulated uniformly by a level-counting Phase Consistency Principle. Our design enables the construction and combination of code values for both expressions and types. Moreover, code generation can happen either at runtime à la MetaML or at compile time, in a macro fashion, à la MacroML. We provide an implementation of our design in Scala and we present two case studies. The first implements the Hidden Markov Model, Shonan Challenge for HPC. The second implements the staged streaming library Strymonas

A genome-wide scan for common alleles affecting risk for autism

Although autism spectrum disorders (ASDs) have a substantial genetic basis, most of the known genetic risk has been traced to rare variants, principally copy number variants (CNVs). To identify common risk variation, the Autism Genome Project (AGP) Consortium genotyped 1558 rigorously defined ASD families for 1 million single-nucleotide polymorphisms (SNPs) and analyzed these SNP genotypes for association with ASD. In one of four primary association analyses, the association signal for marker rs4141463, located within MACROD2, crossed the genome-wide association significance threshold of P < 5 × 10−8. When a smaller replication sample was analyzed, the risk allele at rs4141463 was again over-transmitted; yet, consistent with the winner's curse, its effect size in the replication sample was much smaller; and, for the combined samples, the association signal barely fell below the P < 5 × 10−8 threshold. Exploratory analyses of phenotypic subtypes yielded no significant associations after correction for multiple testing. They did, however, yield strong signals within several genes, KIAA0564, PLD5, POU6F2, ST8SIA2 and TAF1C

Directedness of Information Flow in Mobile Phone Communication Networks

Without having direct access to the information that is being exchanged, traces of information flow can be obtained by looking at temporal sequences of user interactions. These sequences can be represented as causality trees whose statistics result from a complex interplay between the topology of the underlying (social) network and the time correlations among the communications. Here, we study causality trees in mobile-phone data, which can be represented as a dynamical directed network. This representation of the data reveals the existence of super-spreaders and super-receivers. We show that the tree statistics, respectively the information spreading process, are extremely sensitive to the in-out degree correlation exhibited by the users. We also learn that a given information, e.g., a rumor, would require users to retransmit it for more than 30 hours in order to cover a macroscopic fraction of the system. Our analysis indicates that topological node-node correlations of the underlying social network, while allowing the existence of information loops, they also promote information spreading. Temporal correlations, and therefore causality effects, are only visible as local phenomena and during short time scales. Consequently, the very idea that there is (intentional) information spreading beyond a small vecinity is called into question. These results are obtained through a combination of theory and data analysis techniques

Comisión de Infraestructura Informe 8

Octava dimensión de análisis transversal: Desarrollo, aplicación efectiva de los recursos humanos, organizacionales, técnicos, materiales y financieros.Fil: Álvarez, Teresita. Universidad Nacional de Córdoba. Subsecretaría de Planeamiento Físico; Argentina.Fil: Barrado, Carlos. Universidad Nacional de Córdoba. Subsecretaría de Planeamiento Físico; Argentina.Fil: Baruzzi, Alejandro. Universidad Nacional de Córdoba. Subsecretaría de Planeamiento Físico; Argentina.Fil: Cohen Arazi, Moisés Alejandro. Universidad Nacional de Córdoba. Subsecretaría de Planeamiento Físico; Argentina.Fil: Dutari, Ian. Universidad Nacional de Córdoba. Subsecretaría de Planeamiento Físico; Argentina.Fil: Fernández Saiz, María del Carmen. Universidad Nacional de Córdoba. Subsecretaría de Planeamiento Físico; Argentina.Fil: Fernández, Elvira. Universidad Nacional de Córdoba. Subsecretaría de Planeamiento Físico; Argentina.Fil: Girelli, Inés. Universidad Nacional de Córdoba. Subsecretaría de Planeamiento Físico; Argentina.Fil: Maristany, Arturo. Universidad Nacional de Córdoba. Subsecretaría de Planeamiento Físico; Argentina. Fil: Martínez, Mariela Patricia. Universidad Nacional de Córdoba. Subsecretaría de Planeamiento Físico; Argentina.Fil: Menzaque, Fernando. Universidad Nacional de Córdoba. Subsecretaría de Planeamiento Físico; Argentina.Fil: Moré, Ricardo Rubén. Universidad Nacional de Córdoba. Subsecretaría de Planeamiento Físico; Argentina.Fil: Musso, Nicolás Lionel. Universidad Nacional de Córdoba. Subsecretaría de Planeamiento Físico; Argentina.Fil: Rodríguez, Viviana. Universidad Nacional de Córdoba. Subsecretaría de Planeamiento Físico; Argentina.Fil: Ubino, Mario. Universidad Nacional de Córdoba. Subsecretaría de Planeamiento Físico; Argentina.Fil: Vargas, Laura. Universidad Nacional de Córdoba. Subsecretaría de Planeamiento Físico; Argentina

Converging Intracranial Markers of Conscious Access

We compared conscious and nonconscious processing of briefly flashed words using a visual masking procedure while recording intracranial electroencephalogram (iEEG) in ten patients. Nonconscious processing of masked words was observed in multiple cortical areas, mostly within an early time window (<300 ms), accompanied by induced gamma-band activity, but without coherent long-distance neural activity, suggesting a quickly dissipating feedforward wave. In contrast, conscious processing of unmasked words was characterized by the convergence of four distinct neurophysiological markers: sustained voltage changes, particularly in prefrontal cortex, large increases in spectral power in the gamma band, increases in long-distance phase synchrony in the beta range, and increases in long-range Granger causality. We argue that all of those measures provide distinct windows into the same distributed state of conscious processing. These results have a direct impact on current theoretical discussions concerning the neural correlates of conscious access