Intrinsic Josephson junctions in the iron-based multi-band superconductor (V2Sr4O6)Fe2As2

In layered superconductors, Josephson junctions may be formed within the unit cell due to sufficiently low interlayer coupling. These intrinsic Josephson junction (iJJ) systems have attracted considerable interest for their application potential in quantum computing as well as efficient sources of THz radiation, closing the famous "THz gap". So far, iJJ have been demonstrated in single-band, copper-based high-Tc superconductors, mainly in Ba-Sr-Ca-Cu-O. Here we report clear experimental evidence for iJJ behavior in the iron-based superconductor (V2Sr4O6)Fe2As2. The intrinsic junctions are identified by periodic oscillations of the flux flow voltage upon increasing a well aligned in-plane magnetic field. The periodicity is well explained by commensurability effects between the Josephson vortex lattice and the crystal structure, which is a hallmark signature of Josephson vortices confined into iJJ stacks. This finding adds (V2Sr4O6)Fe2As2 as the first iron-based, multi-band superconductor to the copper-based iJJ materials of interest for Josephson junction applications, and in particular novel devices based on multi-band Josephson coupling may be realized.Comment: Accepted in Nature Physic

Anyone Can Become a Troll: Causes of Trolling Behavior in Online Discussions

In online communities, antisocial behavior such as trolling disrupts constructive discussion. While prior work suggests that trolling behavior is confined to a vocal and antisocial minority, we demonstrate that ordinary people can engage in such behavior as well. We propose two primary trigger mechanisms: the individual's mood, and the surrounding context of a discussion (e.g., exposure to prior trolling behavior). Through an experiment simulating an online discussion, we find that both negative mood and seeing troll posts by others significantly increases the probability of a user trolling, and together double this probability. To support and extend these results, we study how these same mechanisms play out in the wild via a data-driven, longitudinal analysis of a large online news discussion community. This analysis reveals temporal mood effects, and explores long range patterns of repeated exposure to trolling. A predictive model of trolling behavior shows that mood and discussion context together can explain trolling behavior better than an individual's history of trolling. These results combine to suggest that ordinary people can, under the right circumstances, behave like trolls.Comment: Best Paper Award at CSCW 201

Examining the effects of sleep delay on depressed males and females and healthy controls

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109586/1/jsr12174.pd

Automatically generating adaptive logic to balance non-functional tradeoffs during reconfiguration

Increasingly, high-assurance software systems apply selfreconfiguration in order to satisfy changing functional and non-functional requirements. Most self-reconfiguration approaches identify a target system configuration to provide the desired system behavior, then apply a series of reconfiguration instructions to reach the desired target configuration. Collectively, these reconfiguration instructions define an adaptation path. Although multiple satisfying adaptation paths may exist, most self-reconfiguration approaches select adaptation paths based on a single criterion, such as minimizing reconfiguration cost. However, different adaptation paths may represent tradeoffs between reconfiguration costs and other criteria, such as performance and reliability. This paper introduces an evolutionary computationbased approach to automatically evolve adaptation paths that safely transition an executing system from its current configuration to its desired target configuration, while balancing tradeoffs between functional and non-functional requirements. The proposed approach can be applied both at design time to generate suites of adaptation paths, as well as at run time to evolve safe adaptation paths to handle changing system and environmental conditions. We demonstrate the effectiveness of this approach by applying it to the dynamic reconfiguration of a collection of remote data mirrors, with the goal of minimizing reconfiguration costs while maximizing reconfiguration performance and reliability

The Prevalence of Healthcare Associated Infections Among Adult Inpatients at Nineteen Large Australian Acute-care Public Hospitals: A Point Prevalence Survey

Background Australia does not have a national healthcare associated infection (HAI) surveillance program. Only one HAI point prevalence study has been undertaken in 1984. The objective of this study was to estimate the burden of healthcare associated infection (HAI) in acute adult inpatients in Australia. Methods A cross sectional point prevalence study (PPS) was conducted in a sample of large acute care hospitals. All data were collected by two trained Research Assistants. Surveillance methodology was based on the European Centre for Disease Prevention and Control (ECDC) PPS Protocol with variation in the sampling method in that only acute inpatients ≥ 18 years old were included. ECDC HAI definitions were applied. Results Data was collected between August and November 2018. A total of 2767 patients from 19 hospitals were included in the study. The median age of patients was 67, and 52.9% of the sample were male. Presence of a multi-drug resistant organism was documented for 10.3% of the patients. There were 363 HAIs present in 273 patients. The prevalence of patients with a HAI was 9.9% (95%CI: 8.8–11.0). Hospital prevalence rates ranged from 5.7% (95%CI:2.9–11.0) to 17.0% (95%CI:10.7–26.1). The most common HAIs were surgical site infection, pneumonia and urinary tract infection, comprising 64% of all HAIs identified. Conclusion This is the first HAI PPS to be conducted in Australia in 34 years. The prevalence rate is higher than the previous Australian study and that reported by the ECDC, however differences in methodology limit comparison. Regular, large scale HAI PPS should be undertaken to generate national HAI data to inform and drive national interventions