Highly Variable Objects in the Palomar-QUEST Survey: A Blazar Search using Optical Variability

We identify 3,113 highly variable objects in 7,200 square degrees of the Palomar-QUEST Survey, which each varied by more than 0.4 magnitudes simultaneously in two broadband optical filters on timescales from hours to roughly 3.5 years. The primary goal of the selection is to find blazars by their well-known violent optical variability. Because most known blazars have been found in radio and/or X-ray wavelengths, a sample discovered through optical variability may have very different selection effects, elucidating the range of behavior possible in these systems. A set of blazars selected in this unusual manner will improve our understanding of the physics behind this extremely variable and diverse class of AGN. The object positions, variability statistics, and color information are available using the Palomar-QUEST CasJobs server. The time domain is just beginning to be explored over large sky areas; we do not know exactly what a violently variable sample will hold. About 20% of the sample has been classified in the literature; over 70% of those objects are known or likely AGN. The remainder largely consists of a variety of variable stars, including a number of RR Lyrae and cataclysmic variables.Comment: 22 pages (preprint format), 2 figures. Accepted for publication in ApJ. References update

Writing in Britain and Ireland, c. 400 to c. 800

No abstract available

The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

Swarm Learning for decentralized and confidential clinical machine learning

Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine1,2. Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes3. However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation4,5. Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learning—a decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. To illustrate the feasibility of using Swarm Learning to develop disease classifiers using distributed data, we chose four use cases of heterogeneous diseases (COVID-19, tuberculosis, leukaemia and lung pathologies). With more than 16,400 blood transcriptomes derived from 127 clinical studies with non-uniform distributions of cases and controls and substantial study biases, as well as more than 95,000 chest X-ray images, we show that Swarm Learning classifiers outperform those developed at individual sites. In addition, Swarm Learning completely fulfils local confidentiality regulations by design. We believe that this approach will notably accelerate the introduction of precision medicine

Communications Biophysics

Contains reports on four research projects.National Institutes of Health (Grant 5 P01 NS13126-02)National Institutes of Health (Grant 5 K04 NS00113-03)National Institutes of Health (Grant 2 ROI NS11153-02A1)National Science Foundation (Grant BNS77-16861)National Institutes of Health (Grant 5 RO1 NS10916-03)National Institutes of Health (Fellowship 1 F32 NS05327)National Institutes of Health (Grant 5 ROI NS12846-02)National Institutes of Health (Fellowship 1 F32 NS05266)Edith E. Sturgis FoundationNational Institutes of Health (Grant 1 R01 NS11680-01)National Institutes of Health (Grant 2 RO1 NS11080-04)National Institutes of Health (Grant 5 T32 GIM107301-03)National Institutes of Health (Grant 5 TOI GM01555-10

Communications Biophysics

Contains research objectives and summary of research on nine research projects split into four sections.National Institutes of Health (Grant 5 ROI NS11000-03)National Institutes of Health (Grant 1 P01 NS13126-01)National Institutes of Health (Grant 1 RO1 NS11153-01)National Institutes of Health (Grant 2 R01 NS10916-02)Harvard-M.I.T. Rehabilitation Engineering CenterU. S. Department of Health, Education, and Welfare (Grant 23-P-55854)National Institutes of Health (Grant 1 ROl NS11680-01)National Institutes of Health (Grant 5 ROI NS11080-03)M.I.T. Health Sciences Fund (Grant 76-07)National Institutes of Health (Grant 5 T32 GM07301-02)National Institutes of Health (Grant 5 TO1 GM01555-10

Communications Biophysics

Contains reports on nine research projects split into four sections.National Institutes of Health (Grant 5 PO1 NS13126)National Institutes of Health (Grant 5 KO4 NS00113)National Institutes of Health (Training Grant 5 T32 NS07047)National Institutes of Health (Training Grant 1 T32 NS07099)National Science Foundation (Grant BNS77-16861)National Institutes of Health (Grant 5 ROI NS10916)National Institutes of Health (Grant 5 RO1 NS12846)National Science Foundation (Grant BNS77-21751)National Institutes of Health (Grant 1 RO1 NS14092)Edith E. Sturgis FoundationHealth Sciences FundNational Institutes of Health (Grant 2 R01 NS11680)National Institutes of Health (Fellowship 5 F32 NS05327)National Institutes of Health (Grant 2 ROI NS11080)National Institutes of Health (Training Grant 5 T32 GM07301

Communications Biophysics

Contains reports on nine research projects split into four sections.National Institutes of Health (Grant 5 P01 NS13126)National Institutes of Health (Grant 5 K04 NS00113)National Institutes of Health (Training Grant 5 T32 NS07047)National Institutes of Health (Grant 5 ROl NS11153-03)National Institutes of Health (Fellowship 1 T32 NS07099-01)National Science Foundation (Grant BNS77-16861)National Institutes of Health (Grant 5 ROl NS10916)National Institutes of Health (Grant 5 ROl NS12846)National Science Foundation (Grant BNS77-21751)National Institutes of Health (Grant 1 RO1 NS14092)Health Sciences FundNational Institutes of Health (Grant 2 R01 NS11680)National Institutes of Health (Grant 2 RO1 NS11080)National Institutes of Health (Training Grant 5 T32 GM07301

Stranger to Familiar: Wild Strepsirhines Manage Xenophobia by Playing

The power of play in limiting xenophobia is a well-known phenomenon in humans. Yet, the evidence in social animals remains meager. Here, we aim to determine whether play promotes social tolerance toward strangers in one of the most basal group of primates, the strepsirhines. We observed two groups of wild lemurs (Propithecus verreauxi, Verreaux's sifaka) during the mating season. Data were also collected on nine visiting, outgroup males. We compared the distribution of play, grooming, and aggressive interactions across three conditions: OUT (resident/outgroup interactions), IN (resident/resident interactions in presence of outgroups) and BL-IN (baseline of resident/resident interactions in absence of outgroups). Play frequency between males was higher in OUT than in IN and BL-IN conditions; whereas, grooming was more frequent in IN than in OUT and BL-IN conditions. Aggression rates between resident and outgroup males were significantly higher than those between residents. However, aggressions between resident and outgroup males significantly decreased after the first play session and became comparable with resident-resident aggression levels. The presence of strangers in a well-established group implies the onset of novel social circumstances, which sifaka males cope with by two different tactics: grooming with ingroup males and playing with outgroup ones. The grooming peak, concurrently with the visit of outgroups, probably represents a social shield adopted by resident males to make their pre-existing affiliation more evident to the stranger “audience”. Being mostly restricted to unfamiliar males, adult play in sifaka appears to have a role in managing new social situations more than in maintaining old relationships. In particular, our results indicate not only that play is the interface between strangers but also that it has a specific function in reducing xenophobia. In conclusion, play appears to be an ice-breaker mechanism in the critical process that “upgrades” an individual from stranger to familiar