Asymmetric Distributions of Achromatic Bipolar Cells in the Mouse Retina

In the retina, evolutionary changes can be traced in the topography of photoreceptors. The shape of the visual streak depends on the height of the animal and its habitat, namely, woods, prairies, or mountains. Also, the distribution of distinct wavelength-sensitive cones is unique to each animal. For example, UV and green cones reside in the ventral and dorsal regions in the mouse retina, respectively, whereas in the rat retina these cones are homogeneously distributed. In contrast with the abundant investigation on the distribution of photoreceptors and the third-order neurons, the distribution of bipolar cells has not been well understood. We utilized two enhanced green fluorescent protein (EGFP) mouse lines, Lhx4-EGFP (Lhx4) and 6030405A18Rik-EGFP (Rik), to examine the topographic distributions of bipolar cells in the retina. First, we characterized their GFP-expressing cells using type-specific markers. We found that GFP was expressed by type 2, type 3a, and type 6 bipolar cells in the Rik mice and by type 3b, type 4, and type 5 bipolar cells in the Lhx4 mice. All these types are achromatic. Then, we examined the distributions of bipolar cells in the four cardinal directions and three different eccentricities of the retinal tissue. In the Rik mice, GFP-expressing bipolar cells were more highly observed in the nasal region than those in the temporal retina. The number of GFP cells was not different along with the ventral-dorsal axis. In contrast, in the Lhx4 mice, GFP-expressing cells occurred at a higher density in the ventral region than in the dorsal retina. However, no difference was observed along the nasal-temporal axis. Furthermore, we examined which type of bipolar cells contributed to the asymmetric distributions in the Rik mice. We found that type 3a bipolar cells occurred at a higher density in the temporal region, whereas type 6 bipolar cells were denser in the nasal region. The asymmetricity of these bipolar cells shaped the uneven distribution of the GFP cells in the Rik mice. In conclusion, we found that a subset of achromatic bipolar cells is asymmetrically distributed in the mouse retina, suggesting their unique roles in achromatic visual processing.

A unified framework for closed-form nonparametric regression, classification, preference and mixed problems with Skew Gaussian Processes

Skew-Gaussian Processes (SkewGPs) extend the multivariate Unified Skew-Normal distributions over finite dimensional vectors to distribution over functions. SkewGPs are more general and flexible than Gaussian processes, as SkewGPs may also represent asymmetric distributions. In a recent contribution, we showed that SkewGP and probit likelihood are conjugate, which allows us to compute the exact posterior for non-parametric binary classification and preference learning. In this paper, we generalize previous results and we prove that SkewGP is conjugate with both the normal and affine probit likelihood, and more in general, with their product. This allows us to (i) handle classification, preference, numeric and ordinal regression, and mixed problems in a unified framework; (ii) derive closed-form expression for the corresponding posterior distributions. We show empirically that the proposed framework based on SkewGP provides better performance than Gaussian processes in active learning and Bayesian (constrained) optimization. These two tasks are fundamental for design of experiments and in Data Science.

R-estimators in GARCH models; asymptotics and applications

The quasi-maximum likelihood estimation is a commonly-used method for estimating the GARCH parameters. However, such estimators are sensitive to outliers and their asymptotic normality is proved under the finite fourth moment assumption on the underlying error distribution. In this paper, we propose a novel class of estimators of the GARCH parameters based on ranks of the residuals, called R-estimators, with the property that they are asymptotically normal under the existence of a finite 2 + δ moment of the errors and are highly efficient. We propose fast algorithm for computing the R-estimators. Both real data analysis and simulations show the superior performance of the proposed estimators under the heavy-tailed and asymmetric distributions.

USING ASYMMETRIC DISTRIBUTIONS FOR MODELING GENE EXPRESSION DATA

We present a short review of the asymmetric distributions alpha-stable, skew normal, skew Student’s t and skew Laplace. We compare the performance for these distributions, in general, are used to model asymmetric data, using AIC and BIC. These criterias were able to selecting the best model for each data set. We also apply these models to gene expression data and we verify these distributions are qualified to model these observations.

Aluminum Powder Preparation for Additive Manufacturing Using Electrostatic Classification

This work aims to study the possibility of using an electrostatic drum-type separator to prepare a powder with a narrow size distribution curve for usage in additive manufacturing. The size distributions of the uncoated commercial aluminum powders ASP-30, ASP-22, and ASP-5 were analyzed. It was shown that the powders ASP-30 and ASP-22 have similar asymmetric distributions with a SPAN of 1.480 and 1.756, respectively. ASP-5 powder, in turn, has a narrow distribution with a SPAN of 0.869. ASP-30 powder was chosen for further experiment because, traditionally, separators are used to classify large-sized materials with particle size more than 100 μm. The optimal mode of electrostatic classification was proposed for the selected powder. Various classification methods, including centrifugal and electrostatic, were compared. The powders before and after classification were studied by XRD, SEM, TEM, and TG–DSC analyses. The obtained results showed that electrostatic classification does not lead to the formation of coatings on the processed powders. Electrostatic separation effectively narrows the particle size distribution, making it a suitable and valuable method to classify initial powders for additive manufacturing.

Evaluating Asymmetric Approaches to the Estimation of Standard Uncertainties for Emission Factors in the Fuel Sector of Costa Rica

A new environmental challenge for Costa Rica involves the precise and reliable quantification of data from its fossil-fueled transportation sector. In the context of greenhouse gas inventories (measurement), uncertainty assessment, as the best quality parameter of any estimation or measurement, takes on a new relevance by becoming a mandatory requirement on ISO 14064-1:2018. However, a significant limitation has been found by users when quantifying standard (measurement) uncertainties associated with emission factors with asymmetric probability distributions. The present article sought to take advantage of fitting asymmetric distributions to estimate and compare possible standard uncertainties for the official emission factors of Costa Rica, specifically for the fuel sector. Five asymmetric distributions and a “symmetrization” method (symmetric approximation of an asymmetric distribution) were chosen and fitted to the data based on their application and previous use. Standard uncertainties were estimated from each distribution parameters as standard deviations. To evaluate the fit, quantiles of interest were extracted from simulated populations compared with the original data values. A systematically better fit was evidenced for the asymmetric triangular and generalized extreme value distributions, both for CO2 emission factors with less asymmetries and CH4 and N2O emission factors with greater asymmetries. This was not the case for the other distributions, where the log-normal distribution applying the correction factor suggested in the literature showed the worst fit. The use of the former distributions is recommended to estimate the standard uncertainties associated with the emission factors from the official Costa Rican database and other emission factors with similar asymmetries.

Development of margination of platelet-sized particles in red blood cell suspensions flowing through Y-shaped bifurcating microchannels

BACKGROUND: In the blood flow through microvessels, platelets exhibit enhanced concentrations in the layer free of red blood cells (cell-free layer) adjacent to the vessel wall. The motion of platelets in the cell-free layer plays an essential role in their interaction with the vessel wall, and hence it affects their functions of hemostasis and thrombosis. OBJECTIVE: We aimed to estimate the diffusivity of platelet-sized particles in the transverse direction (the direction of vorticity) across the channel width in the cell-free layer by in vitro experiments for the microchannel flow of red blood cell (RBC) suspensions containing platelet-sized particles. METHODS: Fluorescence microscope observations were performed to measure the transverse distribution of spherical particles immersed in RBC suspensions flowing through a Y-shaped bifurcating microchannel. We examined the development of the particle concentration profiles along the flow direction in the daughter channels, starting from asymmetric distributions with low concentrations on the inner side of the bifurcation at the inlet of the daughter channels. RESULTS: In daughter channels of 40 μm width, reconstruction of particle margination revealed that a symmetric concentration profile was attained in ∼30 mm from the bifurcation, independent of flow rate. CONCLUSIONS: We presented experimental evidence of particle margination developing in a bifurcating flow channel where the diffusivity of 2.9-μm diameter particles was estimated to be ∼40 μm2/s at a shear rate of 1000 s−1 and hematocrit of 0.2.

LITHOBIOTOPES OF THE NEMEGT GOBI BASIN

Three distinct but overlapping dinosaur-dominated faunas characterize the Upper Cretaceous Djadokhta, Baruungoyot and Nemegt formations of the Nemegt Basin of Mongolia. Documented faunal differences cannot be explained easily by temporal succession, but can be understood in the light of physical processes controlling life, death, and burial of taxa. The stratigraphy of the Gobi Desert region records tectonically driven geometries, clearly documenting preservational processes different than those acting in most other dinosaur-dominated beds worldwide. Small, asymmetric tectonic grabens were filled with Upper Cretaceous, dinosaur bearing deposits showing asymmetric distributions of facies, here termed Lithobiotopes. The water-lain fluvial and alluvial plain facies of the Nemegt Lithobiotope supported and preserved a fauna dominated by gigantic dinosaurs, but had a preservational bias against smaller animals. The Nemegt passed laterally into interdune facies of the Baruungoyot Lithobiotope, which represented a hostile environment for large species, but preserved smaller animals. This in turn passed laterally into the aeolianite facies of the Djadokhta Lithobiotope, which is characterized by remains of small dinosaurs and a rich fauna of other animals. The Nemegt Gobi Basin can be visualized as an oasis with a central pond supplied with water from ephemeral channels and surrounded by a semi-arid alluvial plain and dune fields.

Organic consumers’ profile beyond the mean

The European organic food market is characterized by very different consumer segments. There are significant differences concerning motivations for organic food consumption, preferences for various attributes, and frequency of purchase among consumers. Although the organic food sector has been studied for about 20 years, little is known about consumer behavior at different levels of consumption. The aim of this study was to investigate the determinants of organic food consumption in various market segments characterized by different purchasing frequencies. The determinants of purchase frequency in Italy and Germany are analyzed not only at the mean regression, by OLS, but also at the median and at the mode. Differing estimates at these measures of central tendency generally occur with asymmetric distributions, and this occurs in the following analysis as well. Moreover, since in Germany the dependent variable presents more than one peak/mode, interpretation of the mode regression becomes problematic and a different tool is implemented, namely the finite mixture model. The latter clusters the observations in homogeneous groups while computing the regression coefficients within each group. Buyers are split into two groups, frequent and rare consumers of organic food, and two different sets of estimated coefficients explain frequency of purchases within each group.