Techniques for High Contrast Imaging in Multi-Star Systems II: Multi-Star Wavefront Control

Direct imaging of exoplanets represents a challenge for astronomical instrumentation due to the high-contrast ratio and small angular separation between the host star and the faint planet. Multi-star systems pose additional challenges for coronagraphic instruments because of the diffraction and aberration leakage introduced by the additional stars, and as a result are not planned to be on direct imaging target lists. Multi-star wavefront control (MSWC) is a technique that uses a coronagraphic instrument's deformable mirror (DM) to create high-contrast regions in the focal plane in the presence of multiple stars. Our previous paper introduced the Super-Nyquist Wavefront Control (SNWC) technique that uses a diffraction grating to enable the DM to generate high-contrast regions beyond the nominal controllable region. These two techniques can be combined to generate high-contrast regions for multi-star systems at any angular separations. As a case study, a high-contrast wavefront control (WC) simulation that applies these techniques shows that the habitable region of the Alpha Centauri system can be imaged reaching 8 times 10(exp -9) mean contrast in 10 percent broadband light in one-sided dark holes from 1.6-5.5 lambda (wavelength) divided by D (distance)

Exoplanet Terra Incognita

Exoplanet surface imaging, cartography and the search for exolife are the next frontiers of planetology and astrophysics. Here we present an over-view of ideas and techniques to resolve albedo features on exoplanetary surfaces. Albedo maps obtained in various spectral bands (similar to true-colour images) may reveal exoplanet terrains, geological history, life colonies, and even artificial structures of advanced civilizations.Comment: 16 pages, 6 figures, Planetary Cartograph

BiDAl: Big Data Analyzer for Cluster Traces

Modern data centers that provide Internet-scale services are stadium-size structures housing tens of thousands of heterogeneous devices (server clusters, networking equipment, power and cooling infrastructures) that must operate continuously and reliably. As part of their operation, these devices produce large amounts of data in the form of event and error logs that are essential not only for identifying problems but also for improving data center efficiency and management. These activities employ data analytics and often exploit hidden statistical patterns and correlations among different factors present in the data. Uncovering these patterns and correlations is challenging due to the sheer volume of data to be analyzed. This paper presents BiDAl, a prototype “log-data analysis framework” that incorporates various Big Data technologies to simplify the analysis of data traces from large clusters. BiDAl is written in Java with a modular and extensible architecture so that different storage backends (currently, HDFS and SQLite are supported), as well as different analysis languages (current implementation supports SQL, R and Hadoop MapReduce) can be easily selected as appropriate. We present the design of BiDAl and describe our experience using it to analyze several public traces of Google data clusters for building a simulation model capable of reproducing observed behavior

COHESION, CONSENSUS AND EXTREME INFORMATION IN OPINION DYNAMICS

Opinion formation is an important element of social dynamics. It has been widely studied in the last years with tools from physics, mathematics and computer science. Here, a continuous model of opinion dynamics for multiple possible choices is analysed. Its main features are the inclusion of disagreement and possibility of modulating external information/media effects, both from one and multiple sources. The interest is in identifying the effect of the initial cohesion of the population, the interplay between cohesion and media extremism, and the effect of using multiple external sources of information that can influence the system. Final consensus, especially with the external message, depends highly on these factors, as numerical simulations show. When no external input is present, consensus or segregation is determined by the initial cohesion of the population. Interestingly, when only one external source of information is present, consensus can be obtained, in general, only when this is extremely neutral, i.e., there is not a single opinion strongly promoted, or in the special case of a large initial cohesion and low exposure to the external message. On the contrary, when multiple external sources are allowed, consensus can emerge with one of them even when this is not extremely neutral, i.e., it carries a strong message, for a large range of initial conditions

ATAD5 promotes replication restart by regulating RAD51 and PCNA in response to replication stress

Maintaining stability of replication forks is important for genomic integrity. However, it is not clear how replisome proteins contribute to fork stability under replication stress. Here, we report that ATAD5, a PCNA unloader, plays multiple functions at stalled forks including promoting its restart. ATAD5 depletion increases genomic instability upon hydroxyurea treatment in cultured cells and mice. ATAD5 recruits RAD51 to stalled forks in an ATR kinase-dependent manner by hydroxyurea-enhanced protein-protein interactions and timely removes PCNA from stalled forks for RAD51 recruitment. Consistent with the role of RAD51 in fork regression, ATAD5 depletion inhibits slowdown of fork progression and native 5-bromo-2??-deoxyuridine signal induced by hydroxyurea. Single-molecule FRET showed that PCNA itself acts as a mechanical barrier to fork regression. Consequently, DNA breaks required for fork restart are reduced by ATAD5 depletion. Collectively, our results suggest an important role of ATAD5 in maintaining genome integrity during replication stress

A public dataset of 24-H multi-levels psycho-physiological responses in young healthy adults

Wearable devices now make it possible to record large quantities of physiological data, which can be used to obtain a clearer view of a person’s health status and behavior. However, to the best of our knowledge, there are no open datasets in the literature that provide psycho-physiological data. The Multilevel Monitoring of Activity and Sleep in Healthy people (MMASH) dataset presented in this paper provides 24 h of continuous psycho-physiological data, that is, inter-beat intervals data, heart rate data, wrist accelerometry data, sleep quality index, physical activity (i.e., number of steps per second), psychological characteristics (e.g., anxiety status, stressful events, and emotion declaration), and sleep hormone levels for 22 participants. The MMASH dataset will enable the investigation of possible relationships between the physical and psychological characteristics of people in daily life. Data were validated through different analyses that showed their compatibility with the literature

EXD2 governs germ stem cell homeostasis and lifespan by promoting mitoribosome integrity and translation

Mitochondria are subcellular organelles critical for meeting the bioenergetic and biosynthetic needs of the cell. Mitochondrial function relies on genes and RNA species encoded both in the nucleus and mitochondria, as well as their coordinated translation, import and respiratory complex assembly. Here we describe the characterization of exonuclease domain like 2 (EXD2), a nuclear encoded gene that we show is targeted to the mitochondria and prevents the aberrant association of mRNAs with the mitochondrial ribosome. The loss of EXD2 resulted in defective mitochondrial translation, impaired respiration, reduced ATP production, increased reactive oxygen species and widespread metabolic abnormalities. Depletion of EXD2/CG6744 in D.melanogaster caused developmental delays and premature female germline stem cell attrition, reduced fecundity and a dramatic extension of lifespan that could be reversed with an anti-oxidant diet. Our results define a conserved role for EXD2 in mitochondrial translation that influences development and aging