Preserved stratigraphic architecture and evolution of a net-transgressive mixed wave- and tide-influenced coastal system: Cliff House Sandstone, northwestern New Mexico, USA

The Cretaceous Cliff House Sandstone comprises a thick (400 m) net- transgressive succession representing a mixed wave- and tide-influenced shallow-marine system that migrated episodically landwards. This study examines the youngest part (middle Campanian) of the Cliff House Sandstone, exposed in Chaco Cultural Natural Historical Park, northwest New Mexico, U.S. A. Detailed mapping of facies architecture between a three-dimensional network of measured sections has allowed the character, geometry, and distribution of key stratigraphic surfaces and stratal units to be reconstructed. Upward-shallowing facies successions (parasequences) are separated by laterally extensive transgressive erosion (ravinement) surfaces cut by both wave and tide processes. Preservation of facies tracts in each parasequence is controlled by the depth of erosion and migration trajectory of the overlying ravinement surfaces. In most parasequences, there is no preservation of the proximal wave-dominated facies tracts (foreshore, upper-shoreface), resulting in thin (4–7 m) top-truncated packages. Four distinct shallow marine tongues (parasequence sets) have been identified, consisting of ten parasequences with a total stratigraphic thickness of ~ 100 m. Each tongue records an episode of complex shoreline migration history (multiple regressive–transgressive phases) in an overall net-transgressive system. The ravinement surfaces provide a stratigraphic framework in which to understand partitioning of tide- and wave-dominated deposits in a net-transgressive system, and a model is presented to account for the sediment distribution and stratigraphic architecture observed in each parasequence. Despite a complex internal architecture, parasequences exhibit a predictable pattern which can be related to the regressive and transgressive phases of deposition. Preservation of wave-dominated facies tracts is associated with shoreline regression, while tide-dominated facies tracts are interpreted to record sediment accumulation during shoreline transgression that also resulted in significant erosion of the underlying regressive deposits. The interplay between erosion, sediment bypass, and deposition during regression and transgression is shown to ultimately control the preservation and stratigraphic architecture of the larger-scale net-transgressive coastal system. While the Cliff House Sandstone exhibits a facies composition and quantitative stacking patterns (shoreline trajectory) similar to other studied examples, differences in the dip-extent of the wave-dominated sandstone tongue has resulted in a more disconnected architecture between the high-fr equency cycles. Understanding the variety of stratal geometries that ravinement surfaces can generate is therefore crucial to predicting the spatial distribution and facies architecture in transgressive systems

EEuGene: employing electroencephalograph signals in the rating strategy of a hardware-based interactive genetic algorithm

We describe a novel interface and development platform for an interactive Genetic Algorithm (iGA) that uses Electroencephalograph (EEG) signals as an indication of fitness for selection for successive generations. A gaming headset was used to generate EEG readings corresponding to attention and meditation states from a single electrode. These were communicated via Bluetooth to an embedded iGA implemented on the Arduino platform. The readings were taken to measure subjects’ responses to predetermined short sequences of synthesised sound, although the technique could be applied any appropriate problem domain. The prototype provided sufficient evidence to indicate that use of the technology in this context is viable. However, the approach taken was limited by the technical characteristics of the equipment used and only provides proof of concept at this stage. We discuss some of the limitations of using biofeedback systems and suggest possible improvements that might be made with more sophisticated EEG sensors and other biofeedback mechanisms

Effects of laterally wedged insoles on symptoms and disease progression in medial knee osteoarthritis: a protocol for a randomised, double-blind, placebo controlled trial

<p>Abstract</p> <p>Background</p> <p>Whilst laterally wedged insoles, worn inside the shoes, are advocated as a simple, inexpensive, non-toxic self-administered intervention for knee osteoarthritis (OA), there is currently limited evidence to support their use. The aim of this randomised, double-blind controlled trial is to determine whether laterally wedges insoles lead to greater improvements in knee pain, physical function and health-related quality of life, and slower structural disease progression as well as being more cost-effective, than control flat insoles in people with medial knee OA.</p> <p>Methods/Design</p> <p>Two hundred participants with painful radiographic medial knee OA and varus malalignment will be recruited from the community and randomly allocated to lateral wedge or control insole groups using concealed allocation. Participants will be blinded as to which insole is considered therapeutic. Blinded follow up assessment will be conducted at 12 months after randomisation. The outcome measures are valid and reliable measures recommended for OA clinical trials. Questionnaires will assess changes in pain, physical function and health-related quality-of-life. Magnetic resonance imaging will measure changes in tibial cartilage volume. To evaluate cost-effectiveness, participants will record the use of all health-related treatments in a log-book returned to the assessor on a monthly basis. To test the effect of the intervention using an intention-to-treat analysis, linear regression modelling will be applied adjusting for baseline outcome values and other demographic characteristics.</p> <p>Discussion</p> <p>Results from this trial will contribute to the evidence regarding the effectiveness of laterally wedged insoles for the management of medial knee OA.</p> <p>Trial registration</p> <p>ACTR12605000503628; NCT00415259.</p

Empowering Qualitative Research Methods in Education with Artificial Intelligence

Artificial Intelligence is one of the fastest growing disciplines, disrupting many sectors. Originally mainly for computer scientists and engineers, it has been expanding its horizons and empowering many other disciplines contributing to the development of many novel applications in many sectors. These include medicine and health care, business and finance, psychology and neuroscience, physics and biology to mention a few. However, one of the disciplines in which artificial intelligence has not been fully explored and exploited yet is education. In this discipline, many research methods are employed by scholars, lecturers and practitioners to investigate the impact of different instructional approaches on learning and to understand the ways skills and knowledge are acquired by learners. One of these is qualitative research, a scientific method grounded in observations that manipulates and analyses non-numerical data. It focuses on seeking answers to why and how a particular observed phenomenon occurs rather than on its occurrences. This study aims to explore and discuss the impact of artificial intelligence on qualitative research methods. In particular, it focuses on how artificial intelligence have empowered qualitative research methods so far, and how it can be used in education for enhancing teaching and learning