The Effect of Dispersed Oil on the Calcification Rate of the Reef-Building Coral Diploria Strigosa

Hermatypic corals represent environmentally and economically important components of the reef ecosystem. Oil spills and clean-up operations in reef areas are potential sources of pollution impact. This paper presents an evaluation of the calcification rate of specimens of the reef-building coral Diploria strigosa in response to 24 hour treatments of chemically dispersed oil at concentrations of 20 ppm. The concentrations and durations were chosen to represent a scenario of a short-term oil spill treated with dispersant passing over a coral reef. Calcification rates were determined by the buoyant weight technique at several day intervals for up to 29 days following treatment. Results from laboratory experiments (Winter and Summer) conducted in a flow-through seawater system indicate that treated corals, both in comparison to untreated controls as well as to their pretreatment rates, experienced no depression in calcification. In contrast, a possible short-term enhancement of calcification for the treated corals was observed

Impaired Competence for Pretense in Children with Autism: Exploring Potential Cognitive Predictors.

Lack of pretense in children with autism has been explained by a number of theoretical explanations, including impaired mentalising, impaired response inhibition, and weak central coherence. This study aimed to empirically test each of these theories. Children with autism (n=60) were significantly impaired relative to controls (n=65) when interpreting pretense, thereby supporting a competence deficit hypothesis. They also showed impaired mentalising and response inhibition, but superior local processing indicating weak central coherence. Regression analyses revealed that mentalising significantly and independently predicted pretense. The results are interpreted as supporting the impaired mentalising theory and evidence against competing theories invoking impaired response inhibition or a local processing bias. The results of this study have important implications for treatment and intervention

Big data, method and the ethics of location : a case study of a hookup app for men who have sex with men

With the rise of geo-social media, location is emerging as a particularly sensitive data point for big data and digital media research. To explore this area, we reflect on our ethics for a study in which we analyze data generated via an app that facilitates public sex among men who have sex with men. The ethical sensitivities around location are further heightened in the context of research into such digital sexual cultures. Public sexual cultures involving men who have sex with men operate both in spaces “meant” for public sex (e.g., gay saunas and dark rooms) and spaces “not meant” for public sex (e.g., shopping centers and public toilets). The app in question facilitates this activity. We developed a web scraper that carefully collected selected data from the app and that data were then analyzed to help identify ethical issues. We used a mixture of content analysis using Python scripts, geovisualisation software and manual qualitative coding techniques. Our findings, which are methodological rather than theoretical in nature, center on the ethics associated with generating, processing, presenting, archiving and deleting big data in a context where harassment, imprisonment, physical harm and even death occur. We find a tension in normal standards of ethical conduct where humans are involved in research. We found that location came to the fore as a key - though not the only - actor requiring attention when considering ethics in a big data context

NASA's Optical Program on Ascension Island: Bringing MCAT to Life as the Eugene Stansbery-Meter Class Autonomous Telescope (ES-MCAT)

In June 2015, the construction of the Meter Class Autonomous Telescope was completed and MCAT saw the light of the stars for the first time. In 2017, MCAT was newly dedicated as the Eugene Stansbery-MCAT telescope by NASA's Orbital Debris Program Office (ODPO), in honor of his inspiration and dedication to this newest optical member of the NASA ODPO. Since that time, MCAT has viewed the skies with one engineering camera and two scientific cameras, and the ODPO optical team has begun the process of vetting the entire system. The full system vetting includes verification and validation of: (1) the hardware comprising the system (e.g. the telescopes and its instruments, the dome, weather systems, all-sky camera, FLIR cloud infrared camera, etc.), (2) the custom-written Observatory Control System (OCS) master software designed to autonomously control this complex system of instruments, each with its own control software, and (3) the custom written Orbital Debris Processing software for post-processing the data. ES-MCAT is now capable of autonomous observing to include Geosynchronous survey, TLE (Two-line element) tracking of individual catalogued debris at all orbital regimes (Low-Earth Orbit all the way to Geosynchronous (GEO) orbit), tracking at specified non-sidereal rates, as well as sidereal rates for proper calibration with standard stars. Ultimately, the data will be used for validation of NASA's Orbital Debris Engineering Model, ORDEM, which aids in engineering designs of spacecraft that require knowledge of the orbital debris environment and long-term risks for collisions with Resident Space Objects (RSOs)

Lemaitre-Tolman-Bondi model and accelerating expansion

I discuss the spherically symmetric but inhomogeneous Lemaitre-Tolman- Bondi (LTB) metric, which provides an exact toy model for an inhomogeneous universe. Since we observe light rays from the past light cone, not the expansion of the universe, spatial variation in matter density and Hubble rate can have the same effect on redshift as acceleration in a perfectly homogeneous universe. As a consequence, a simple spatial variation in the Hubble rate can account for the distant supernova data in a dust universe without any dark energy. I also review various attempts towards a semirealistic description of the universe based on the LTB model.Comment: Invited Review for a special Gen. Rel. Grav. issue on Dark Energy. 17 pages, 3 figure

Mitigating Gender Bias in Machine Learning Data Sets

Artificial Intelligence has the capacity to amplify and perpetuate societal biases and presents profound ethical implications for society. Gender bias has been identified in the context of employment advertising and recruitment tools, due to their reliance on underlying language processing and recommendation algorithms. Attempts to address such issues have involved testing learned associations, integrating concepts of fairness to machine learning and performing more rigorous analysis of training data. Mitigating bias when algorithms are trained on textual data is particularly challenging given the complex way gender ideology is embedded in language. This paper proposes a framework for the identification of gender bias in training data for machine learning.The work draws upon gender theory and sociolinguistics to systematically indicate levels of bias in textual training data and associated neural word embedding models, thus highlighting pathways for both removing bias from training data and critically assessing its impact.Comment: 10 pages, 5 figures, 5 Tables, Presented as Bias2020 workshop (as part of the ECIR Conference) - http://bias.disim.univaq.i

Language and theory of mind in autism spectrum disorder : the relationship between complement syntax and false belief task performance.

This study aimed to test the hypothesis that children with autism spectrum disorder (ASD) use their knowledge of complement syntax as a means of “hacking out” solutions to false belief tasks, despite lacking a representational theory of mind (ToM). Participants completed a “memory for complements” task, a measure of receptive vocabulary, and traditional location change and unexpected contents false belief tasks. Consistent with predictions, the correlation between complement syntax score and location change task performance was significantly stronger within the ASD group than within the comparison group. However, contrary to predictions, complement syntax score was not significantly correlated with unexpected contents task performance within either group. Possible explanations for this pattern of results are considered