Sequence Information Encoded in DNA that May Influence Long-Range Chromatin Structure Correlates with Human Chromosome Functions.

Little is known about the possible function of the bulk of the human genome. We have recently shown that long-range regular oscillation in the motif non-T, A/T, G (VWG) existing at ten-nucleotide multiples influences large-scale nucleosome array formation. In this work, we have determined the locations of all 100 kb regions that are predicted to form distinctive chromatin structures throughout each human chromosome (except Y). Using these data, we found that a significantly greater fraction of 300 kb sequences lacked annotated transcripts in genomic DNA regions ≥300 kb that contained nearly continuous chromatin organizing signals than in control regions. We also found a relationship between the meiotic recombination frequency and the presence of strong VWG chromatin organizing signals. Large (≥300 kb) genomic DNA regions having low average recombination frequency are enriched in chromatin organizing signals. As additional controls, we show using chromosome 1 that the VWG motif signals are not enriched in randomly selected DNA regions having the mean size of the recombination coldspots, and that non-VWG motif sets do not generate signals that are enriched in recombination coldspots. We also show that tandemly repeated alpha satellite DNA contains strong VWG signals for the formation of distinctive nucleosome arrays, consistent with the low recombination activity of centromeres. Our correlations cannot be explained simply by variations in the GC content. Our findings suggest that a specific set of periodic DNA motifs encoded in genomic DNA, which provide signals for chromatin organization, influence human chromosome function

Region- and pixel-based image fusion for disaggregation of actual evapotranspiration

This paper compares a region-based and a pixel-based disaggregation method used to improve obtaining actual evapotranspiration (aET) data from MODIS images. Using these methods and the relationship between different vegetation indices form Landsat-5 and aET from MODIS, a 1 km resolution aET image was disaggregated to 250 and 30 m resolutions in two steps. Disaggregated aET images were compared with aET data obtained from a Landsat-5 TM image. A sensitivity analysis using synthetic data showed the impacts of land-cover homogeneity and registration error of the input images at the three scale levels. Accuracy assessment illustrated that the region-based disaggregation method using the Normalized Difference Vegetation Index (NDVI) has a good agreement with the Landsat-5 aET, having a mean absolute error equal to 0.93 mm. This method can be powerful for improving irrigation management, as it allows to increase the spatial resolution of aET derived from remote sensing images. The study concluded that a region-based method with NDVI data performs best to disaggregate MODIS aET data

Aspects of large-scale chromatin structures in mouse liver nuclei can be predicted from the DNA sequence

The large amount of non-coding DNA present in mammalian genomes suggests that some of it may play a structural or functional role. We provide evidence that it is possible to predict computationally, from the DNA sequence, loci in mouse liver nuclei that possess distinctive nucleosome arrays. We tested the hypothesis that a 100 kb region of DNA possessing a strong, in-phase, dinucleosome period oscillation in the motif period-10 non-T, A/T, G, should generate a nucleosome array with a nucleosome repeat that is one-half of the dinucleosome oscillation period value, as computed by Fourier analysis of the sequence. Ten loci with short repeats, that would be readily distinguishable from the pervasive bulk repeat, were predicted computationally and then tested experimentally. We estimated experimentally that less than 20% of the chromatin in mouse liver nuclei has a nucleosome repeat length that is 15 bp, or more, shorter than the bulk repeat value of 195 ± bp. All 10 computational predictions were confirmed experimentally with high statistical significance. Nucleosome repeats as short as 172 ± 5 bp were observed for the first time in mouse liver chromatin. These findings may be useful for identifying distinctive chromatin structures computationally from the DNA sequence

Recurrent Multiresolution Convolutional Networks for VHR Image Classification

Classification of very high resolution (VHR) satellite images has three major challenges: 1) inherent low intra-class and high inter-class spectral similarities, 2) mismatching resolution of available bands, and 3) the need to regularize noisy classification maps. Conventional methods have addressed these challenges by adopting separate stages of image fusion, feature extraction, and post-classification map regularization. These processing stages, however, are not jointly optimizing the classification task at hand. In this study, we propose a single-stage framework embedding the processing stages in a recurrent multiresolution convolutional network trained in an end-to-end manner. The feedforward version of the network, called FuseNet, aims to match the resolution of the panchromatic and multispectral bands in a VHR image using convolutional layers with corresponding downsampling and upsampling operations. Contextual label information is incorporated into FuseNet by means of a recurrent version called ReuseNet. We compared FuseNet and ReuseNet against the use of separate processing steps for both image fusion, e.g. pansharpening and resampling through interpolation, and map regularization such as conditional random fields. We carried out our experiments on a land cover classification task using a Worldview-03 image of Quezon City, Philippines and the ISPRS 2D semantic labeling benchmark dataset of Vaihingen, Germany. FuseNet and ReuseNet surpass the baseline approaches in both quantitative and qualitative results

New Tools to solve known problems at critical nanoindentation measurements

The nanoindentation measurement process is a widely used in material science. It delivers very useful information about the mechanical properties with high spatial resolution. Nevertheless the knowledge of the exact contact mechanic with its geometrical conditions of indenter tip and sample surface in the contact area is essential for the accuracy of the results. Because the indenter geometry is not free of tolerances as well the sample surface is not in the accurate position to the indenter – so corrections are necessary to solve this incorrectness. The detailed analysis of flat punch force-displacement curves allows to correct the incorrectness of the contact surfaces by aligning the sample surface parallel to the real flat punch surface. Please click Additional Files below to see the full abstract

Modeling spatial-temporal change of Poyang Lake marshland based on an uncertainty theory - random sets

AbstractUncertainty modeling now engages the attention of researchers in spatial temporal change analysis in remote sensing. Some studies proposed to use random sets for modeling the spatial uncertainty of image objects with uncertain boundaries, but none have considered the parameter determination problem for large datasets. In this paper we refined the random set models for monitoring monthly changes in wetland vegetation areas from series of images. Twelve cloud-free HJ-1A/1B images from April 2009 to March 2010 were used for monitoring spatial-temporal changes of Poyang Lake wetlands. We applied random sets to represent spatial uncertainty of wetland vegetation that were extracted from normalized difference vegetation index (NDVI) maps. Time series of random sets reflect the seasonal differences of location and extents of the wetlands, whereas degree of uncertainties indicated by SD and CV indices reflect the gradual change of the wetland vegetation in space. Results show that the uncertain extents of wetland vegetation change through the year, achieving the largest range and uncertainty degree in autumn. This coincides with the highly heterogeneous vegetation status in autumn, since the wetland recovers gradually after flooding and young vegetation emerges at gradually changing densities, thus providing forage in different ecological zones for different types of migratory birds. We conclude that the random set model enriches spatial-temporal modeling of phenomena which are uncertain in space and dynamic in time

Earthquake modelling at the country level using aggregated spatio-temporal point processes

The goal of this paper is to derive a hazard map for earthquake occurrences in Pakistan from a catalogue that contains spatial coordinates of shallow earthquakes of magnitude $4.5$ or larger aggregated over calendar years. We test relative temporal stationarity by the KPSS statistic and use the inhomogeneous J--function to test for inter-point interactions. We then formulate a cluster model, and deconvolve in order to calculate the hazard map, and verify that no particular year has an undue influence on the map. Within the borders of the single country, the KPSS test did not show any deviation from homogeneity in the spatial intensities. The inhomogeneous J-function indicated clustering that could not be attributed to inhomogeneity, and the analysis of aftershocks showed some evidence of two major shocks instead of one during the 2005 Kashmir earthquake disaster. Thus, the spatial point pattern analysis carried out for these data was insightful in various aspects and the hazard map that was obtained may lead to improved measures to protect the population against the disastrous effects of earthquakes