Defective satellite DNA clustering into chromocenters underlies hybrid incompatibility in Drosophila

Although rapid evolution of pericentromeric satellite DNA repeats is theorized to promote hybrid incompatibility (HI), how divergent repeats affect hybrid cells remains poorly understood. Recently, we demonstrated that sequence-specific DNA-binding proteins cluster satellite DNA from multiple chromosomes into chromocenters, thereby bundling chromosomes to maintain the entire genome in a single nucleus. Here we show that ineffective clustering of divergent satellite DNA in the cells of Drosophila hybrids results in chromocenter disruption, associated micronuclei formation and tissue atrophy. We further demonstrate that previously identified HI factors trigger chromocenter disruption and micronuclei in hybrids, linking their function to a conserved cellular process. Together, we propose a unifying framework that explains how the widely observed satellite DNA divergence between closely related species can cause reproductive isolation.

Is diffuse intracluster light a good tracer of the galaxy cluster matter distribution?

ABSTRACT We explore the relation between diffuse intracluster light (central galaxy included) and the galaxy cluster (baryonic and dark) matter distribution using a sample of 528 clusters at 0.2 ≤ z ≤ 0.35 found in the Dark Energy Survey (DES) Year 1 data. The surface brightness of the diffuse light shows an increasing dependence on cluster total mass at larger radius, and appears to be self-similar with a universal radial dependence after scaling by cluster radius. We also compare the diffuse light radial profiles to the cluster (baryonic and dark) matter distribution measured through weak lensing and find them to be comparable. The IllustrisTNG galaxy formation simulation, TNG300, offers further insight into the connection between diffuse stellar mass and cluster matter distributions – the simulation radial profile of the diffuse stellar component does not have a similar slope with the total cluster matter content, although that of the cluster satellite galaxies does. Regardless of the radial trends, the amount of diffuse stellar mass has a low-scatter scaling relation with cluster’s total mass in the simulation, out-performing the total stellar mass of cluster satellite galaxies. We conclude that there is no consistent evidence yet on whether or not diffuse light is a faithful radial tracer of the cluster matter distribution. Nevertheless, both observational and simulation results reveal that diffuse light is an excellent indicator of the cluster’s total mass.

Implementation dbscan algorithm to clustering satellite surface temperature data in indonesia

Forest and land fires are national and international problems. The frequency of fires in one of Indonesia's provinces, Riau, is a significant problem. Knowing where to repair the burn is essential to prevent more massive fires. Fires occur because of a fire triangle, namely fuel, oxygen, and heat. The third factor can be seen through remote sensing. Using the Landsat-8 satellite, named the Enhanced Vegetation Index (EVI) variable, Normalized Burn Area (NBR), Normal Difference Humidity Index (NDMI), Normal Difference Difference Vegetation Index (NDVI), Soil Adapted Vegetation Index (SAVI), and Soil Surface Temperature (LST). DBSCAN, as a grouping algorithm that can group the data into several groups based on data density. This is used because of the density of existing fire data, according to the character of this algorithm. The selected cluster is the best cluster that uses Silhouette Coefficients, eps, and minutes value extracted from each variable, so there is no noise in the resulting cluster. The result is more than 0, and the highest is the best cluster result. There are 5 clusters formed by clustering, each of which has its members. This cluster is formed enough to represent the real conditions, cluster which has a high LST value or has an NBR value. A high LST value indicates an increase in the area's temperature; a high NBR value indicates a fire has occurred in the area. The combination of LST and NBR values indicates the area has experienced forest and land fires. This study shows that DBSCAN clustered fire and surface temperature data following data from the Central Statistics Agency of Riau Province. Proven DBSCAN can cluster satellite imagery data in Riau province into several clusters that have a high incidence of land fires.

The relationship between plasmapause, solar wind and geomagnetic activity between 2007 and 2011

Taking advantage of the Cluster satellite mission and especially the observations made by the instrument WHISPER to deduce the electron number density along the orbit of the satellites, we studied the relationships between the plasmapause positions (LPP) and the following LPP indicators: (a) solar wind coupling functions Bz (Z component of the interplanetary magnetic field vector, B, in GSM system), BV (related to the interplanetary electric field; B is the magnitude of the interplanetary magnetic field vector, V is solar wind velocity), and dΦmp/dt (which combines different physical processes responsible for the magnetospheric activity) and (b) geomagnetic indices Dst, Ap and AE. The analysis is performed separately for three magnetic local time (MLT) sectors (Sector1 – night sector (01:00–07:00 MLT); Sector2 – day sector (07:00–16:00 MLT); Sector3 – evening sector (16:00–01:00 MLT)) and for all MLTs taken together. All LPP indicators suggest the faster plasmapause response in the postmidnight sector. Delays in the plasmapause responses (hereafter time lags) are approximately 2–27 h, always increasing from Sector1 to Sector3. The obtained fits clearly resolve the MLT structures. The variability in the plasmapause is the largest for low values of LPP indicators, especially in Sector2. At low activity levels,LPP exhibits the largest values on the dayside (in Sector2) and the smallest on the postmidnight side (Sector1). Displacements towards larger values on the evening side (Sector3) and towards lower values on the dayside (Sector2) are identified for enhanced magnetic activity. Our results contribute to constraining the physical mechanisms involved in the plasmapause formation and to further study the still not well understood related issues.

Using fuzzy C-means and local autocorrelation to cluster satellite-inferred burn severity classes

Burn severity classifications derived from multitemporal Landsat Thematic Mapper images and the Normalised Burn Ratio (NBR) are commonly used to assess the post-fire ecological effects of wildfires. Ongoing efforts to retrospectively map historical burn severity require defensible, objective methods of classifying continuous differenced Normalised Burn Ratio (dNBR) data where field data are often unavailable. For three fires, we compare three methods of classifying pre- and post-fire Landsat data: (1) dNBR classification using Composite Burn Index (CBI) field data to assign severity classes; (2) fuzzy C-means classification of a dNBR image; (3) local Getis–Ord statistic (Gi*) output applied to a dNBR image, classified using fuzzy C-means clustering. We then use a Kappa statistic to evaluate the agreement of severity classes assigned to a pixel with its corresponding CBI plot. For two of the three fires, the C-means clustering of the dNBR and the Gi* output performed as well or better than dNBR images classified using CBI data, with strong agreement for moderate- and high-severity classes. These results suggest that clustering of dNBR data may be a suitable approach for classifying burn severity data without field data. This method may also be useful as a tool for rapid post-fire assessments (e.g. Burned Area Emergency Response and Burned Area Reflectance Classification maps), where images must often be classified quickly and subjectively. Further analysis using additional field data and across different vegetation types will be necessary to better understand the importance of localised spatial variability in classifying burn severity data or other remote sensing change-detection analyses.

Study of the turbulence in the central plasma sheet during August 24-28 geomagnetic storm using the CLUSTER satellite data

Hemos utilizado la Técnica de medición de intermitencia local (local Intermittency Measure Technique) basada en la técnica de la transformada de wavelet para estudiar las fluctuaciones de velocidad en el plasma, medidas por experimento de espectrómetro de iones de satélite CLUSTER, durante la tormenta geomagnética de 24-28 de agosto de 2005. Los resultados obtenidos mostraron un aumento significativo de nivel de turbulencia intermitente al final de la fase principal. Esto puede estar relacionado con un aumento significativo en la actividad de las subtormentas y estiramiento de las líneas del campo geomagnético observado en la fase principal. Este hecho es importante para la comprensión de la naturaleza de las tormentas geomagnéticas.