Rmi1 stimulates decatenation of double Holliday junctions during dissolution by Sgs1-Top3

double Holliday junction (dHJ) is a central intermediate of homologous recombination that can be processed to yield crossover or non-crossover recombination products. To preserve genomic integrity, cells possess mechanisms to avoid crossing over. We show that Saccharomyces cerevisiae Sgs1 and Top3 proteins are sufficient to migrate and disentangle a dHJ to produce exclusively non-crossover recombination products, in a reaction termed "dissolution." We show that Rmi1 stimulates dHJ dissolution at low Sgs1-Top3 protein concentrations, although it has no effect on the initial rate of Holliday junction (HJ) migration. Rmi1 serves to stimulate DNA decatenation, removing the last linkages between the repaired and template DNA molecules. Dissolution of a dHJ is a highly efficient and concerted alternative to nucleolytic resolution that prevents crossing over of chromosomes during recombinational DNA repair in mitotic cells and thereby contributes to genomic integrity

Magnetooptical Study of Zeeman Effect in Mn modulation-doped InAs/InGaAs/InAlAs Quantum Well Structures

We report on a magneto-photoluminescence (PL) study of Mn modulation-doped InAs/InGaAs/InAlAs quantum wells. Two PL lines corresponding to the radiative recombination of photoelectrons with free and bound-on-Mn holes have been observed. In the presence of a magnetic field applied in the Faraday geometry both lines split into two circularly polarized components. While temperature and magnetic field dependences of the splitting are well described by the Brillouin function, providing an evidence for exchange interaction with spin polarized manganese ions, the value of the splitting exceeds the expected value of the giant Zeeman splitting by two orders of magnitude for a given Mn density. Possible reasons of this striking observation are discussed

Combined InSAR and Terrestrial Structural Monitoring of Bridges

This paper examines advances in InSAR satellite measurement technologies to understand their relevance, utilisation and limitations for bridge monitoring. Waterloo Bridge is presented as a case study to explore how InSAR data sets can be combined with traditional measurement techniques including sensors installed on the bridge and automated total stations. A novel approach to InSAR bridge monitoring was adopted by the installation of physical reflectors at key points of structural interest on the bridge, in order to supplement the bridge’s own reflection characteristics and ensure that the InSAR measurements could be directly compared and combined with insitu measurements. The interpretation and integration of InSAR data sets with civil infrastructure data is more than a trivial task, and a discussion of uncertainty of measurement data is presented. Finally, a strategy for combining and interpreting varied data from multiple sources to provide useful insights into each of these methods is presented, outlining the practical applications of this data analysis to support wider monitoring strategies.Author funding under EPSRC (UK) Award 1636878, co-author funding under Research Council of Norway (RCN Grant no. 237906)

Application of SAR time-series and deep learning for estimating landslide occurence time

The time series of normalized difference vegetation index (NDVI) and interferometric coherence extracted from optical and Synthetic Aperture Radar (SAR) images, respectively, have strong responses to sudden landslide failures in vegetated regions, which is expressed by a sudden increase or decrease in the values of NDVI and coherence. Compared with optical sensors, SAR sensors are not affected by cloud and daylight conditions and can detect the occurrence time of failure in near real-time. The purpose of this paper is to automatically determine the time of failure occurrence using time series coherence values. We propose, based on some existing anomaly detection algorithms, a deep neural network-based anomaly detection strategy that combines supervised and unsupervised learning without a priori knowledge about failure time. Our experiment using July 21, 2020 Shaziba landslide in China shows that in comparison to widely used unsupervised methodology, the use of our algorithm leads to a more accurate detection of the timing of the landslide failure

First measurement of the Head-Tail directional nuclear recoil signature at energies relevant to WIMP dark matter searches

We present first evidence for the so-called Head-Tail asymmetry signature of neutron-induced nuclear recoil tracks at energies down to 1.5 keV/amu using the 1m^3 DRIFT-IIc dark matter detector. This regime is appropriate for recoils induced by Weakly Interacting Massive Particle (WIMPs) but one where the differential ionization is poorly understood. We show that the distribution of recoil energies and directions induced here by Cf-252 neutrons matches well that expected from massive WIMPs. The results open a powerful new means of searching for a galactic signature from WIMPs.Comment: 4 pages, 6 figures, 1 tabl