Asymptotic normality of the Parzen-Rosenblatt density estimator for strongly mixing random fields

We prove the asymptotic normality of the kernel density estimator (introduced by Rosenblatt (1956) and Parzen (1962)) in the context of stationary strongly mixing random fields. Our approach is based on the Lindeberg's method rather than on Bernstein's small-block-large-block technique and coupling arguments widely used in previous works on nonparametric estimation for spatial processes. Our method allows us to consider only minimal conditions on the bandwidth parameter and provides a simple criterion on the (non-uniform) strong mixing coefficients which do not depend on the bandwith.Comment: 16 page

Statistical learning techniques applied to epidemiology: a simulated case-control comparison study with logistic regression

<p>Abstract</p> <p>Background</p> <p>When investigating covariate interactions and group associations with standard regression analyses, the relationship between the response variable and exposure may be difficult to characterize. When the relationship is nonlinear, linear modeling techniques do not capture the nonlinear information content. Statistical learning (SL) techniques with kernels are capable of addressing nonlinear problems without making parametric assumptions. However, these techniques do not produce findings relevant for epidemiologic interpretations. A simulated case-control study was used to contrast the information embedding characteristics and separation boundaries produced by a specific SL technique with logistic regression (LR) modeling representing a parametric approach. The SL technique was comprised of a kernel mapping in combination with a perceptron neural network. Because the LR model has an important epidemiologic interpretation, the SL method was modified to produce the analogous interpretation and generate odds ratios for comparison.</p> <p>Results</p> <p>The SL approach is capable of generating odds ratios for main effects and risk factor interactions that better capture nonlinear relationships between exposure variables and outcome in comparison with LR.</p> <p>Conclusions</p> <p>The integration of SL methods in epidemiology may improve both the understanding and interpretation of complex exposure/disease relationships.</p

Spatio-Temporal Transmission Patterns of Black-Band Disease in a Coral Community

Transmission mechanisms of black-band disease (BBD) in coral reefs are poorly understood, although this disease is considered to be one of the most widespread and destructive coral infectious diseases. The major objective of this study was to assess transmission mechanisms of BBD in the field based on the spatio-temporal patterns of the disease

Actomyosin-Dependent Cortical Dynamics Contributes to the Prophase Force-Balance in the Early Drosophila Embryo

embryo mitotic spindle during prophase depends upon a balance of outward forces generated by cortical dynein and inward forces generated by kinesin-14 and nuclear elasticity. Myosin II is known to contribute to the dynamics of the cell cortex but how this influences the prophase force-balance is unclear. mutants displaying abnormally small actin caps but normal prophase spindle length in late prophase, myosin II inhibition produced very short spindles.These results suggest that two complementary outward forces are exerted on the prophase spindle by the overlying cortex. Specifically, dynein localized on the mechanically firm actin caps and the actomyosin-driven contraction of the deformable soft patches of the actin cortex, cooperate to pull astral microtubules outward. Thus, myosin II controls the size and dynamic properties of the actin-based cortex to influence the spacing of the poles of the underlying spindle during prophase

Colorization and Automated Segmentation of Human T2 MR Brain Images for Characterization of Soft Tissues

Characterization of tissues like brain by using magnetic resonance (MR) images and colorization of the gray scale image has been reported in the literature, along with the advantages and drawbacks. Here, we present two independent methods; (i) a novel colorization method to underscore the variability in brain MR images, indicative of the underlying physical density of bio tissue, (ii) a segmentation method (both hard and soft segmentation) to characterize gray brain MR images. The segmented images are then transformed into color using the above-mentioned colorization method, yielding promising results for manual tracing. Our color transformation incorporates the voxel classification by matching the luminance of voxels of the source MR image and provided color image by measuring the distance between them. The segmentation method is based on single-phase clustering for 2D and 3D image segmentation with a new auto centroid selection method, which divides the image into three distinct regions (gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) using prior anatomical knowledge). Results have been successfully validated on human T2-weighted (T2) brain MR images. The proposed method can be potentially applied to gray-scale images from other imaging modalities, in bringing out additional diagnostic tissue information contained in the colorized image processing approach as described

Chitosan Modification of Adenovirus to Modify Transfection Efficiency in Bovine Corneal Epithelial Cells

BACKGROUND: The purpose of this study is to modulate the transfection efficiency of adenovirus (Ad) on the cornea by the covalent attachment of chitosan on adenoviral capsids via a thioether linkage between chitosan modified with 2-iminothiolane and Ad cross-linked with N-[gamma-maleimidobutyryloxy]succinimide ester (GMBS). METHODOLOGY/PRINCIPAL FINDINGS: Modified Ad was obtained by reaction with the heterobifunctional crosslinking reagent, GMBS, producing maleimide-modified Ad (Ad-GMBS). Then, the chitosan-SH was conjugated to Ad-GMBS via a thioether bond at different ratios of Ad to GMBS to chitosan-SH. The sizes and zeta potentials of unmodified Ad and chitosan-modified Ads were measured, and the morphologies of the virus particles were observed under transmission electron microscope. Primary cultures of bovine corneal epithelial cells were transfected with Ads and chitosan-modified Ads in the absence or presence of anti-adenovirus antibodies. Chitosan modification did not significantly change the particle size of Ad, but the surface charge of Ad increased significantly from -24.3 mV to nearly neutral. Furthermore, primary cultures of bovine corneal epithelial cells were transfected with Ad or chitosan-modified Ad in the absence or presence of anti-Ad antibodies. The transfection efficiency was attenuated gradually with increasing amounts of GMBS. However, incorporation of chitosan partly restored transfection activity and rendered the modified antibody resistant to antibody neutralization. CONCLUSIONS/SIGNIFICANCE: Chitosan can provide a platform for chemical modification of Ad, which offers potential for further in vivo applications

Shear wave velocity prediction using seismic attributes and well log data

Formation’s properties can be estimated indirectly using joint analysis of compressional and shear wave velocities. Shear wave data isnot usually acquired during well logging, which is most likely for costsaving purposes. Even if shear data is available, the logging programs provide only sparsely sampled one-dimensional measurements: this informationis inadequate to estimate reservoir rock properties. Thus, if the shear wave data can be obtained using seismic methods, the results can be used across the field to estimate reservoir properties. The aim of this paper is to use seismic attributes for prediction of shear wave velocity in a field located in southern part of Iran. Independent component analysis(ICA) was used to select the most relevant attributes to shear velocity data. Considering the nonlinear relationship between seismic attributes and shear wave velocity, multi-layer feed forward neural network was used for prediction of shear wave velocity and promising results were presented

Leptin Administration Favors Muscle Mass Accretion by Decreasing FoxO3a and Increasing PGC-1α in ob/ob Mice

Absence of leptin has been associated with reduced skeletal muscle mass in leptin-deficient ob/ob mice. The aim of our study was to examine the effect of leptin on the catabolic and anabolic pathways regulating muscle mass. Gastrocnemius, extensor digitorum longus and soleus muscle mass as well as fiber size were significantly lower in ob/ob mice compared to wild type littermates, being significantly increased by leptin administration (P<0.001). This effect was associated with an inactivation of the muscle atrophy-related transcription factor forkhead box class O3 (FoxO3a) (P<0.05), and with a decrease in the protein expression levels of the E3 ubiquitin-ligases muscle atrophy F-box (MAFbx) (P<0.05) and muscle RING finger 1 (MuRF1) (P<0.05). Moreover, leptin increased (P<0.01) protein expression levels of peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α), a regulator of muscle fiber type, and decreased (P<0.05) myostatin protein, a negative regulator of muscle growth. Leptin administration also activated (P<0.01) the regulators of cell cycle progression proliferating cell nuclear antigen (PCNA) and cyclin D1, and increased (P<0.01) myofibrillar protein troponin T. The present study provides evidence that leptin treatment may increase muscle mass of ob/ob mice by inhibiting myofibrillar protein degradation as well as enhancing muscle cell proliferation

Family Businesses and Adaptation: A Dynamic Capabilities Approach

The main objective of this research was to propose a framework centred on the dynamic capabilities approach, and to be applied in the context of family businesses’ adaption to their changing business environment. Data were gathered through interviews with ten FBs operating in Western Australia. Based on the findings, the clusters of activities, sensing, seizing, and transforming emerged as key factors for firms’ adaptation, and were reinforced by firms’ open culture, signature processes, idiosyncratic knowledge, and valuable, rare, inimitable and non-substitutable attributes. Thus, the usefulness of the proposed framework was confirmed. Implications and future research opportunities are presented. © 2018, The Author(s)