Recent measures of the latitude and longitude of jupiter's red spot

Latitude and longitude of Jupiter red spot measured from photographic plate

Latitude and longitude measurements of Jovian features in 1967-68

Photographic measurements of latitude and longitude of Jovian feature

Expert-Augmented Machine Learning

Machine Learning is proving invaluable across disciplines. However, its success is often limited by the quality and quantity of available data, while its adoption by the level of trust that models afford users. Human vs. machine performance is commonly compared empirically to decide whether a certain task should be performed by a computer or an expert. In reality, the optimal learning strategy may involve combining the complementary strengths of man and machine. Here we present Expert-Augmented Machine Learning (EAML), an automated method that guides the extraction of expert knowledge and its integration into machine-learned models. We use a large dataset of intensive care patient data to predict mortality and show that we can extract expert knowledge using an online platform, help reveal hidden confounders, improve generalizability on a different population and learn using less data. EAML presents a novel framework for high performance and dependable machine learning in critical applications

Photometric Variability in the Ultracool Dwarf BRI 0021-0214: Possible Evidence for Dust Clouds

We report CCD photometric monitoring of the nonemission ultracool dwarf BRI 0021-0214 (M9.5) obtained during 10 nights in 1995 November and 4 nights in 1996 August, with CCD cameras at 1 m class telescopes on the observatories of the Canary Islands. We present differential photometry of BRI 0021-0214, and we report significant variability in the I-band light curve obtained in 1995. A periodogram analysis finds a strong peak at a period of 0.84 day. This modulation appears to be transient because it is present in the 1995 data but not in the 1996 data. We also find a possible period of 0.20 day, which appears to be present in both the 1995 and 1996 datasets. However, we do not find any periodicity close to the rotation period expected from the spectroscopic rotational broadening (< 0.14 day). BRI 0021-0214 is a very inactive object, with extremely low levels of Halpha and X-ray emission. Thus, it is unlikely that magnetically induced cool spots can account for the photometric variability. The photometric variability of BRI 0021-0214 could be explained by the presence of an active meteorology that leads to inhomogeneous clouds on the surface. The lack of photometric modulation at the expected rotational period suggests that the pattern of surface features may be more complicated than previously anticipated.Comment: Accepted for publication in ApJ. 26 pages, 13 figures include

Relationship Satisfaction Among Mothers of Children With Congenital Heart Defects: A Prospective Case-Cohort Study

Objective To assess the level of partner relationship satisfaction among mothers of children with different severity of congenital heart defects (CHD) compared with mothers in the cohort. Methods Mothers of children with mild, moderate, or severe CHD (n = 182) and a cohort of mothers of children without CHD (n = 46,782) from the Norwegian Mother and Child Cohort Study were assessed at 5 time points from pregnancy to 36 months postpartum. A 5-item version of the Relationship Satisfaction scale was used, and relevant covariates were explored. Results The trajectories of relationship satisfaction among mothers of children with varying CHD severity did not differ from the trajectories in the cohort. All women in the cohort experienced decreasing relationship satisfaction from 18 months after delivery up to 36 months after delivery. Conclusions Having a child with CHD, regardless of severity, does not appear to exacerbate the decline in relationship satisfactio

Exploring quality-aware architectural transformations at run-time: the ENIA case

Adapting software systems at run-time is a key issue, especially when these systems consist of components used as intermediary for human-computer interaction. In this sense, model transformation techniques have a widespread acceptance as a mechanism for adapting and evolving the software architecture of such systems. However, existing model transformations often focus on functional requirements, and quality attributes are only manually considered after the transformations are done. This paper aims to improve the quality of adaptations and evolutions in component-based software systems by taking into account quality attributes within the model transformation process. To this end, we present a quality-aware transformation process using software architecture metrics to select among many alternative model transformations. Such metrics evaluate the quality attributes of an architecture. We validate the presented quality-aware transformation process in ENIA, a geographic information system whose user interfaces are based on coarsegrained components and need to be adapted at run-time

Patient-Centered Outcomes Measurement: Does It Require Information From Patients?

Purpose: Since collecting outcome measure data from patients can be expensive, time-consuming, and subject to memory and nonresponse bias, we sought to learn whether outcomes important to patients can be obtained from data in the electronic health record (EHR) or health insurance claims. Methods: We previously identified 21 outcomes rated important by patients who had advanced imaging tests for back or abdominal pain. Telephone surveys about experiencing those outcomes 1 year after their test from 321 people consenting to use of their medical record and claims data were compared with audits of the participants’ EHR progress notes over the time period between the imaging test and survey completion. We also compared survey data with algorithmically extracted data from claims files for outcomes for which data might be available from that source. Results: Of the 16 outcomes for which patients’ survey responses were considered to be the best information source, only 2 outcomes for back pain and 3 for abdominal pain had kappa scores above a very modest level of ≥ 0.2 for chart audit of EHR data and none for algorithmically obtained EHR/claims data. Of the other 5 outcomes for which claims data were considered to be the best information source, only 2 outcomes from patient surveys and 3 outcomes from chart audits had kappa scores ≥ 0.2. Conclusions: For the types of outcomes studied here, medical record or claims data do not provide an adequate source of information except for a few outcomes where patient reports may be less accurate

Developing autonomous learning in first year university students using perspectives from positive psychology

Autonomous learning is a commonly occurring learning outcome from university study, and it is argued that students require confidence in their own abilities to achieve this. Using approaches from positive psychology, this study aimed to develop confidence in first‐year university students to facilitate autonomous learning. Psychological character strengths were assessed in 214 students on day one at university. Two weeks later their top three strengths were given to them in study skills modules as part of a psycho‐educational intervention designed to increase their self‐efficacy and self‐esteem. The impact of the intervention was assessed against a control group of 40 students who had not received the intervention. The results suggested that students were more confident after the intervention, and that levels of autonomous learning increased significantly compared to the controls. Character strengths were found to be associated with self‐efficacy, self‐esteem and autonomous learning in ways that were theoretically meaningful