Practitioner psychologists' understandings of bondage / discipline, dominance / submission, sadomasochism (BDSM): shared or separate from those who practise it

Research with individuals who practise consensual Bondage, Discipline, Domination, Submission, Sadism, Masochism (BDSM) has revealed a complex and multi-faceted phenomenon which serves various functions for its practitioners. Historical associations of BDSM practice with underlying psychopathology, despite empirical evidence to the contrary, may lead to misunderstanding among practitioner psychologists and potentially biased or culturally insensitive psychological treatment of BDSM-oriented individuals. This Q-methodological study investigated subjective understandings of BDSM among practitioner psychologists and whether these understandings were shared with or separate from those who practise BDSM. Forty practitioner psychologists and 40 BDSM practitioners completed a q-sorting task and brief questionnaire online. Comparable majority understandings of BDSM – as a complex phenomenon concerned mainly with power and pleasure – emerged between the psychologist and BDSM practitioner groups. Psychologists generally did not consider themselves particularly knowledgeable on the subject of BDSM, partly due to having received limited teaching and training. There is a need for raising awareness among practitioner psychologists of BDSM as a non-normative, minority sexuality

A deep learning approach to diabetic blood glucose prediction

We consider the question of 30-minute prediction of blood glucose levels measured by continuous glucose monitoring devices, using clinical data. While most studies of this nature deal with one patient at a time, we take a certain percentage of patients in the data set as training data, and test on the remainder of the patients; i.e., the machine need not re-calibrate on the new patients in the data set. We demonstrate how deep learning can outperform shallow networks in this example. One novelty is to demonstrate how a parsimonious deep representation can be constructed using domain knowledge

A near-infrared study of the star forming region RCW 34

We report the results of a near-infrared imaging study of a $7.8 \times 7.8$ arcmin$^2$ region centered on the 6.7 GHz methanol maser associated with the RCW 34 star forming region using the 1.4m IRSF telescope at Sutherland. A total of 1283 objects were detected simultaneously in J, H, and K for an exposure time of 10800 seconds. The J-H, H-K two-colour diagram revealed a strong concentration of more than 700 objects with colours similar to what is expected of reddened classical T Tauri stars. The distribution of the objects on the K {\it vs} J-K colour-magnitude diagram is also suggestive that a significant fraction of the 1283 objects is lower mass pre-main sequence stars. We also present the luminosity function for the subset of about 700 pre-main sequence stars and show that it suggests ongoing star formation activity for about $10^7$ years. An examination of the spatial distribution of the pre-main sequence stars shows that the fainter (older) part of the population is more dispersed over the observed region and the brighter (younger) subset is more concentrated around the position of the O8.5V star. This suggests that the physical effects of the O8.5V star and the two early B-type stars on the remainder of the cloud out of which they formed, could have played a role in the onset of the more recent episode of star formation in RCW 34.Comment: Accepted for publication in The Astronomical Journa

Ames life science telescience testbed evaluation

Eight surrogate spaceflight mission specialists participated in a real-time evaluation of remote coaching using the Ames Life Science Telescience Testbed facility. This facility consisted of three remotely located nodes: (1) a prototype Space Station glovebox; (2) a ground control station; and (3) a principal investigator's (PI) work area. The major objective of this project was to evaluate the effectiveness of telescience techniques and hardware to support three realistic remote coaching science procedures: plant seed germinator charging, plant sample acquisition and preservation, and remote plant observation with ground coaching. Each scenario was performed by a subject acting as flight mission specialist, interacting with a payload operations manager and a principal investigator expert. All three groups were physically isolated from each other yet linked by duplex audio and color video communication channels and networked computer workstations. Workload ratings were made by the flight and ground crewpersons immediately after completing their assigned tasks. Time to complete each scientific procedural step was recorded automatically. Two expert observers also made performance ratings and various error assessments. The results are presented and discussed

Generating Adversarial Attacks for Sparse Neural Networks

Neural networks provide state-of-the-art accuracy for image classification tasks. However traditional networks are highly susceptible to imperceivable perturbations to their inputs known as adversarial attacks that drastically change the resulting output. The magnitude of these perturbations can be measured as Mean Squared Error (MSE). We use genetic algorithms to produce black-box adversarial attacks and examine MSE on state-of-the-art networks. This method generates an attack that converts 90% confidence on a correct class to 50% confidence of a targeted, incorrect class after 2000 epochs. We will generate and examine attacks and their MSE against several sparse neural networks. We theorize that there exists a sparse architecture used for image classification that reduces input image space and therefore that architecture will cause an increase in the MSE required for a classification change. Our work is relevant for security dependent applications of neural networks, low-power high-performance architectures, and systems architectures