Cross-modal Influence on Oral Size Perception

Objective: Evidence suggests people experience an oral size illusion and commonly perceive oral size inaccurately; however, the nature of the illusion remains unclear. The objectives of the present study were to confirm the presence of an oral size illusion, determine the magnitude (amount) and direction (underestimation or overestimation) of the illusion, and determine whether immediately prior crossmodal perceptual experiences affected the magnitude and direction. Design: Participants (N = 27) orally assessed 9 sizes of stainless steel spheres (1/16 in to 1/2 in) categorized as small, medium, or big, and matched them with digital and visual reference sets. Each participant completed 20 matching tasks in 3 assessments. For control assessments, 6 oral spheres were matched with reference sets of same-sized spheres. For primer-control assessments, similar to control, 6 matching tasks were preceded by cross-modal experiences of the same-sized sphere. For experimental assessments, 8 matching tasks were preceded by a cross-modal experience of a differently sized sphere. Results: For control assessments, small and medium spheres were consistently underestimated, and big spheres were consistently overestimated. For experimental assessments, magnitude and direction of the oral size illusion varied according to the size of the sphere used in the cross-modal experience. Conclusion: Results seemed to confirm an oral size illusion, but direction of the illusion depended on the size of the object. Immediately prior cross-modal experiences influenced magnitude and direction of the illusion, suggesting that aspects of oral perceptual experience are dependent upon factors outside of oral perceptual anatomy and the properties of the oral stimulus

Alternative approaches to maximum likelihood estimation of the spatial random effects model

Obtaining spatial predictions by kriging is a common approach in geostatistics. This is usually accomplished by assuming a Gaussian random field (GRF), estimating covariance parameters by maximum likelihood estimation, and using the kriging equation to obtain predictions. For massive data sets, kriging becomes computationally intensive, both in terms of CPU time and memory, and this burden is even more restrictive for multivariate data. Cressie and Johannesson (2008) proposed fixed rank kriging as a solution, with maximum likelihood estimation of the covariance parameters later addressed by Katzfuss and Cressie (2011b). The disadvantage to this method is that accuracy in prediction is bounded by the predetermined fixed components of the model. We propose two methods that utilize the spatial random effects (SRE) model of Cressie and Johannesson (2008), but allow for estimation of the fixed components. In the first method called Reduced Basis Kriging, we use restricted maximum likelihood estimation and sparse matrix methodology to obtain additional gains in computational efficiency without loss of accuracy in prediction. Reduced Basis Kriging does require additional model assumptions, therefore the alternating expectation conditional maximization (AECM) algorithm is suggested as a second method which maintains a very flexible covariance structure and provides estimation of the fixed components. These methods are then extended to handle multivariate data for either a large sample size or a large number of response variables. Unlike previous methods of efficient cokriging, this methodology does not require that observations are recorded at the same locations. Experiments show that our methodology can provide a consistent improvement in accuracy while minimizing the additional computational burden of extra parameter estimation. The methodology is extended to climate data archived by the National Climate Data Center

L'accumulation et l'élimination de cadmium par deux mousses aquatiques, Fontinalis dalecarlica et Platyphypnidium ripariodes : Influence de la concentration de Cd, du temps d'exposition, de la dureté de l'eau et de l'espèce de mousses

Cette étude en laboratoire traite de l'accumulation et de l'élimination du Cd réalisées par deux mousses aquatiques indigènes du Québec, Fontinalis dalecarlica et Platyhypnidium riparioides. Les expositions au Cd étaient de 0 (témoin), 0,8, 2 et 10 µg·L-1, concentrations retrouvées en milieu naturel (non contaminé) et contaminé. Les expériences ont été réalisées à trois niveaux de dureté de l'eau (10 à 15, 40 à 50, 80 à 100 mg·L-1 de CaCO3), à alcalinité constante (80 à 100 mg·L-1 de CaCO3) et à pH stable (7,30) durant une période de 28 jours. Les facteurs d'augmentation des concentrations (FAC) ont démontré une diminution de l'accumulation totale de Cd dans les mousses dans 75% des cas lorsque la dureté de l'eau passe de très douce à dure. Les facteurs de contamination résiduelle (FCR) démontrent la lenteur de l'élimination du Cd par les mousses, et ce, indépendamment de la dureté de l'eau ou de la contamination préalablement subie. Deux équations de régression multiple par étape (Stepwise) ont été établies pour expliquer les facteurs influençant l'accumulation et l'élimination de Cd réalisées par les mousses. Les variables indépendantes incluses dans les équations linéaires de prédiction pour l'accumulation et l'élimination étaient la concentration de Cd dans l'eau, le temps d'exposition, la dureté de l'eau, l'espèce de mousses utilisée et/ou les interactions de ces variables. Les équations linéaires de prédiction pour l'accumulation et l'élimination ont permis d'expliquer respectivement 92% et 71% de la variance observée. Cette identification des principaux facteurs influençant l'accumulation et l'élimination du Cd dans les mousses est d'une grande importance pour la compréhension des processus complexes dirigeant l'absortion des métaux lourds par des organismes vivants. Les équations permettent également de mieux expliquer les interactions engendrées par la variation de divers paramètres sur l'accumulation et l'élimination du Cd par les mousses aquatiques.Aquatic mosses have played a large part in the assessment of toxic elements in water. The advantage of mosses over direct water sampling is that the use of the former lessens spatial and temporal variations, enhances the level of contaminant identification by concentrating toxic elements, and provides information relative to the bioavailable portion. However, the concentration of metals that can be measured in mosses is not a reliable indicator of the concentration of toxic elements in the water, which is why we need to model the bioaccumulation phenomenon.The present laboratory study deals with the accumulation and elimination of Cd by two indigenous Quebec aquatic mosses: Fontinalis dalecarlica and Platyhypnidium riparioides. The previously acclimatized mosses were treated with different concentrations of Cd, three different levels of water hardness, a constant alkalinity and constant pH level for a period of 28 days, in order to establish their bioaccumulative capacity. Cd exposure concentrations were 0 (control), 0.8, 2 and 10 mg·L-1, with a replication at 10 mg·L-1. The experiments were carried out at three levels of water hardness (10 to 15, 40 to 50, 80 to 100 mg·L-1 of CaCO3), with a constant degree of alkalinity (80 to 100 mg·L-1 of CaCO3) and stable pH (7.30). The mosses subsequently went through an elimination period (Cd-free water) of 28 days. The triplicate moss samples were mineralized using nitric acid and all Cd measurements were made by atomic absorption spectrophotometry. The results indicate that the water chemistry conditions remained stable and were properly controlled. The aquatic mosses demonstrated a considerable ability to absorb and adsorb Cd: the measured Cd water concentrations were less than the nominal concentrations. Nonetheless, moss uptake of Cd improves with an increase in Cd contamination and the concentration factors (CF) range from 6 to 122. For the same exposure concentration, the CF drops in some 63% of those instances where water hardness rises from very soft, through soft, to hard. In 75% of the cases there is a drop in CF when water hardness increases directly from very soft to hard. With a stable concentration (e.g. 2 mg·L-1), F. dalecarlica has respective CFs of 26.3, 22.2 and 18, which demonstrates the negative gradation of Cd accumulation as water hardness increases. The residual contamination factors (RCF) bear witness to the slow rate of Cd elimination by the mosses, irrespective of the level of water hardness or of any previous contamination. The elimination factor for RCF is never greater than 2. Mosses take up metals faster than they can eliminate them and have a memory of past contaminations, which is an advantage when it comes to studying ad hoc and/or sporadic contamination phenomena.Two stepwise multiple regression equations have been set up to explain the factors that impact on accumulation and elimination of Cd by mosses. The variables included in the equations were: level of Cd concentration in the water; exposure time; water hardness; the moss species involved, and/or the interactions between these variables. The predictive linear equations for the accumulation and elimination provided explanations for 92% and 71% respectively of the observed variances. The predictive linear equation for accumulation establishes that the length of exposure is the principal parameter responsible for the uptake of Cd by the aquatic mosses. It shows that the accumulation of Cd by the mosses is initially influenced by the level of Cd concentration in the water, but also depends on the length of time over which the bryophytes are exposed to this concentration. Thus, the higher the Cd concentration, the shorter the exposure time for the moss contamination, and vice versa. The second variable is the effect of water hardness taken together with the exposure time. This is a negative variable: the greater the increase in water hardness, the greater the exposure time required to obtain the same degree of moss contamination. This is indicative of the impact of Ca++ and Mg++ on moss uptake. The impact of water hardness is probably the consequence of the availability of or preference of plant-binding sites for Ca++ and Mg++ ions, thus reducing the number of available locations for Cd accumulation. Water hardness and Cd concentration levels are the third variable in this equation and are probably linked to the effect of water hardness on the bioavailability of Cd for the mosses. This variable may also explain why the increase in Cd concentration levels in the water lessens the impact of water hardness on the total accumulation of Cd in the mosses. Finally, the equation identifies a greater level of accumulation in the P. riparoides.Release linear regression shows that the absence of Cd in the water is the major parameter in the elimination of Cd by aquatic mosses. We should remember that the bryophytes are seeking to achieve a steady state condition with their environment, since the Cd is an element that is neither regulated or essential. Its elimination has little to do with water hardness, but is caused by the inversion of a diffusion gradient when the environment is no longer Cd contaminated. During the elimination process, the Ca++ and Mg++ ions have no real impact on the release of Cd by the mosses. The length of prior exposure does affect elimination: the greater it is, the longer the release period required for moss decontamination. Exposure time is less important during elimination than during accumulation. Elimination is a very slow process, and a longer study would probably have shown that this is a major factor in the elimination of moss-accumulated Cd.The present identification of the major factors impacting on the accumulation and elimination of Cd in mosses is extremely important if we are to understand the complex processes that determine the absorption of heavy metals by living organisms. The equations also allow us to better explain the interactions caused by variations in the different parameters with respect to the accumulation and elimination of Cd by aquatic mosses

Estimating basis functions in massive fields under the spatial random effects model

Spatial prediction is commonly achieved under the assumption of a Gaussian random field (GRF) by obtaining maximum likelihood estimates of parameters, and then using the kriging equations to arrive at predicted values. For massive datasets, fixed rank kriging using the Expectation-Maximization (EM) algorithm for estimation has been proposed as an alternative to the usual but computationally prohibitive kriging method. The method reduces computation cost of estimation by redefining the spatial process as a linear combination of basis functions and spatial random effects. A disadvantage of this method is that it imposes constraints on the relationship between the observed locations and the knots. We develop an alternative method that utilizes the Spatial Mixed Effects (SME) model, but allows for additional flexibility by estimating the range of the spatial dependence between the observations and the knots via an Alternating Expectation Conditional Maximization (AECM) algorithm. Experiments show that our methodology improves estimation without sacrificing prediction accuracy while also minimizing the additional computational burden of extra parameter estimation. The methodology is applied to a temperature data set archived by the United States National Climate Data Center, with improved results over previous methodology

Accelerated Computation of a High Dimensional Kolmogorov-Smirnov Distance

Statistical testing is widespread and critical for a variety of scientific disciplines. The advent of machine learning and the increase of computing power has increased the interest in the analysis and statistical testing of multidimensional data. We extend the powerful Kolmogorov-Smirnov two sample test to a high dimensional form in a similar manner to Fasano (Fasano, 1987). We call our result the d-dimensional Kolmogorov-Smirnov test (ddKS) and provide three novel contributions therewith: we develop an analytical equation for the significance of a given ddKS score, we provide an algorithm for computation of ddKS on modern computing hardware that is of constant time complexity for small sample sizes and dimensions, and we provide two approximate calculations of ddKS: one that reduces the time complexity to linear at larger sample sizes, and another that reduces the time complexity to linear with increasing dimension. We perform power analysis of ddKS and its approximations on a corpus of datasets and compare to other common high dimensional two sample tests and distances: Hotelling's T^2 test and Kullback-Leibler divergence. Our ddKS test performs well for all datasets, dimensions, and sizes tested, whereas the other tests and distances fail to reject the null hypothesis on at least one dataset. We therefore conclude that ddKS is a powerful multidimensional two sample test for general use, and can be calculated in a fast and efficient manner using our parallel or approximate methods. Open source implementations of all methods described in this work are located at https://github.com/pnnl/ddks.Comment: Submitted to IEEE Transactions on Pattern Analysis and Machine Intelligenc

Caenorhabditis elegans glp-4 encodes a valyl aminoacyl tRNA synthetase

Germline stem cell proliferation is necessary to populate the germline with sufficient numbers of cells for gametogenesis and for signaling the soma to control organismal properties such as aging. The Caenorhabditis elegans gene glp-4 was identified by the temperature-sensitive allele bn2 where mutants raised at the restrictive temperature produce adults that are essentially germ cell deficient, containing only a small number of stem cells arrested in the mitotic cycle but otherwise have a morphologically normal soma. We determined that glp-4 encodes a valyl aminoacyl transfer RNA synthetase (VARS-2) and that the probable null phenotype is early larval lethality. Phenotypic analysis indicates glp-4(bn2ts) is partial loss of function in the soma. Structural modeling suggests that bn2 Gly296Asp results in partial loss of function by a novel mechanism: aspartate 296 in the editing pocket induces inappropriate deacylation of correctly charged Val-tRNA(val). Intragenic suppressor mutations are predicted to displace aspartate 296 so that it is less able to catalyze inappropriate deacylation. Thus glp-4(bn2ts) likely causes reduced protein translation due to decreased levels of Val-tRNA(val). The germline, as a reproductive preservation mechanism during unfavorable conditions, signals the soma for organismal aging, stress and pathogen resistance. glp-4(bn2ts) mutants are widely used to generate germline deficient mutants for organismal studies, under the assumption that the soma is unaffected. As reduced translation has also been demonstrated to alter organismal properties, it is unclear whether changes in aging, stress resistance, etc. observed in glp-4(bn2ts) mutants are the result of germline deficiency or reduced translation

Reduced Basis Kriging for Big Spatial Fields

In spatial statistics, a common method for prediction over a Gaussian random field (GRF) is maximum likelihood estimation combined with kriging. For massive data sets, kriging is computationally intensive, both in terms of CPU time and memory, and so fixed rank kriging has been proposed as a solution. The method however still involves operations on large matrices, so we develop an alteration to this method by utilizing the approximations made in fixed rank kriging combined with restricted maximum likelihood estimation and sparse matrix methodology. Experiments show that our methodology can provide additional gains in computational efficiency over fixed-rank kriging without loss of accuracy in prediction. The methodology is applied to climate data archived by the United States National Climate Data Center, with very good results

Use of mechanical circulatory support in patients with non-ischaemic cardiogenic shock

Aims Despite its high incidence and mortality risk, there is no evidence-based treatment for non-ischaemic cardiogenic shock (CS). The aim of this study was to evaluate the use of mechanical circulatory support (MCS) for non-ischaemic CS treatment.Methods and results In this multicentre, international, retrospective study, data from 890 patients with non-ischaemic CS, defined as CS due to severe de-novo or acute-on-chronic heart failure with no need for urgent revascularization, treated with or without active MCS, were collected. The association between active MCS use and the primary endpoint of 30-day mortality was assessed in a 1:1 propensity-matched cohort. MCS was used in 386 (43%) patients. Patients treated with MCS presented with more severe CS (37% vs. 23% deteriorating CS, 30% vs. 25% in extremis CS) and had a lower left ventricular ejection fraction at baseline (21% vs. 25%). After matching, 267 patients treated with MCS were compared with 267 patients treated without MCS. In the matched cohort, MCS use was associated with a lower 30-day mortality (hazard ratio 0.76, 95% confidence interval 0.59-0.97). This finding was consistent through all tested subgroups except when CS severity was considered, indicating risk reduction especially in patients with deteriorating CS. However, complications occurred more frequently in patients with MCS; e.g. severe bleeding (16.5% vs. 6.4%) and access-site related ischaemia (6.7% vs. 0%).Conclusion In patients with non-ischaemic CS, MCS use was associated with lower 30-day mortality as compared to medical therapy only, but also with more complications. Randomized trials are needed to validate these findings.[GRAPHICS

Multi-ancestry meta-analysis of tobacco use disorder prioritizes novel candidate risk genes and reveals associations with numerous health outcomes

Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviors, and although strides have been made using genome-wide association studies (GWAS) to identify risk variants, the majority of variants identified have been for nicotine consumption, rather than TUD. We leveraged five biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records, EHR) in 898,680 individuals (739,895 European, 114,420 African American, 44,365 Latin American). We identified 88 independent risk loci; integration with functional genomic tools uncovered 461 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviors in children, and hundreds of medical outcomes, including HIV infection, heart disease, and pain. This work furthers our biological understanding of TUD and establishes EHR as a source of phenotypic information for studying the genetics of TUD