Feasibility of using S-191 infrared spectra for geological studies from space

There are no author-identified significant results in this report

Optical Variability of the Black Hole Candidate GX339-4 (X1659-487, V821 Ara) - Limits on Periodic Modulation

We present results of extensive CCD optical photometry (over 1000 frames representing ~150 hr of integration time) of the optical counterpart of the X-ray source GX339–4 obtained during the high (soft) state. The source was seen to be significantly variable. We do not, however, detect any periodic modulation with semi-amplitude greater than ~0.03 mag for periods less than ~0.5 day or semi-amplitude greater than ~0.07 mag for longer periods. An optical spectrum obtained shortly after GX339–4 made a transition from a ‘low’ to a ‘high’ state is also presented and compared with previous results. The width of the He IIλ4686 emission line in the spectrum implies that GX339–4 does not have an unusually low inclination angle and we therefore conclude that the orbital period of GX339–4 is probably longer than ~0.5 day

The origins of individual differences in how learning is expressed in rats: a general-process perspective

Laboratory rats can exhibit marked, qualitative individual differences in the form of acquired behaviors. For example, when exposed to a signal-reinforcer relationship some rats show marked and consistent changes in sign-tracking (interacting with the signal; e.g., a lever) and others show marked and consistent changes in goal-tracking (interacting with the location of the predicted reinforcer; e.g., the food well). Here, stable individual differences in rats' sign-tracking and goal-tracking emerged over the course of training, but these differences did not generalize across different signal-reinforcer relationships (Experiment 1). This selectivity suggests that individual differences in sign- and goal-tracking reflect differences in the value placed on individual reinforcers. Two findings provide direct support for this interpretation: the palatability of a reinforcer (as measured by an analysis of lick-cluster size) was positively correlated with goal-tracking (and negatively correlated with sign-tracking); and sating rats with a reinforcer affected goal-tracking but not sign-tracking (Experiment 2). These results indicate that the observed individual differences in sign- and goal-tracking behavior arise from the interaction between the palatability or value of the reinforcer and processes of association as opposed to dispositional differences (e.g., in sensory processes, 'temperament,' or response repertoire)

The 14.8-h Orbital Period of GX339-4

We present the results of photometric observations of the black hole candidate GX339-4, obtained while the system was in an \u27off\u27 state. We show that a 14.8-h modulation was present, and provide evidence for a similar periodicity in the \u27high\u27 state from a reanalysis of previously published photometry and spectroscopy. The presence of the same period in both states implies that it is likely to be the orbital period of the system. The spectroscopy analysis provides evidence for an apparent change in the systemic velocity of the system. The amplitude of the observed radial velocity variations, however, permits only crude limits to be placed on the mass of the compact object. Only absorption-line spectroscopy of the secondary in the \u27off\u27 state will provide a convincing mass determination

Teaching introductory undergraduate Physics using commercial video games

Commercial video games are increasingly using sophisticated physics simulations to create a more immersive experience for players. This also makes them a powerful tool for engaging students in learning physics. We provide some examples to show how commercial off-the-shelf games can be used to teach specific topics in introductory undergraduate physics. The examples are selected from a course taught predominantly through the medium of commercial video games.Comment: Accepted to Physics Education, Fig1 does not render properly in this versio

Maximising Social Interactions and Effectiveness within Distance Learning Courses: Cases from Construction

Advanced Internet technologies have revolutionised the delivery of distance learning education. As a result, the physical proximity between learners and the learning providers has become less important. However, whilst the pervasiveness of these technological developments has reached unprecedented levels, critics argue that the student learning experience is still not as effective as conventional face-to-face delivery. In this regard, surveys of distance learning courses reveal that there is often a lack of social interaction attributed to this method of delivery, which tends to leave learners feeling isolated due to a lack of engagement, direction, guidance and support by the tutor. This paper defines and conceptualises this phenomenon by investigating the extent to which distance-learning programmes provide the social interactions of an equivalent traditional classroom setting. In this respect, two distance learning case studies were investigated, covering the UK and Slovenian markets respectively. Research findings identified that delivery success is strongly dependent on the particular context to which the specific distance learning course is designed, structured and augmented. It is therefore recommended that designers of distance learning courses should balance the tensions and nuances associated with commercial viability and pedagogic effectiveness

A novel algorithm for dynamic student profile adaptation based on learning styles

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.E-learning recommendation systems are used to enhance student performance and knowledge by providing tailor- made services based on the students’ preferences and learning styles, which are typically stored in student profiles. For such systems to remain effective, the profiles need to be able to adapt and reflect the students’ changing behaviour. In this paper, we introduce new algorithms that are designed to track student learning behaviour patterns, capture their learning styles, and maintain dynamic student profiles within a recommendation system (RS). This paper also proposes a new method to extract features that characterise student behaviour to identify students’ learning styles with respect to the Felder-Silverman learning style model (FSLSM). In order to test the efficiency of the proposed algorithm, we present a series of experiments that use a dataset of real students to demonstrate how our proposed algorithm can effectively model a dynamic student profile and adapt to different student learning behaviour. The results revealed that the students could effectively increase their learning efficiency and quality for the courses when the learning styles are identified, and proper recommendations are made by using our method