Tidal energy machines: A comparative life cycle assessment

Marine energy in the UK is currently undergoing a period of exponential growth in terms of development and implementation. The current installed tidal energy capacity of around 4MW is expected to rise to provide up to 20% of the UK’s electricity demand by 2050 [5]. With this in mind, there is a huge range of energy devices, all seemingly promoted by their developers as the best method of extracting power from the ocean. Embodied energy is an important aspect of any power producing device or process, and is used to describe the amount of energy required to begin and maintain the process of energy generation. Until a device or process has generated this amount of energy it cannot be said to be a net contributor of energy. This work used Life Cycle Assessment to study four tidal energy devices, representing a cross section of the existing designs, and compares their embodied energy and carbon dioxide emissions. In order to ensure a fair comparison, a hypothetical installation site is used, with conditions typical of those found at potential array installation sites in the UK. The designs studied include a multi-blade turbine, two three blade horizontal axis turbine machines, and an Archimedes’ screw device. These machines were chosen to represent a cross section of device, foundation, installation and operation designs. They have all been developed to prototype stage, meaning that actual manufacturing data is available. Embodied energy is considered over the entire lifetime of each device, beginning with extraction of raw materials. Energy use from fabrication, transport, installation, lifetime maintenance, end-of-life decommissioning and recycling are all calculated, and compared to the energy generation from each device at the test site. Finally, the embodied energy; CO2 intensity; and energy payback periods are compared to those of conventional power generating systems as well as other renewable energy sources. A range of data sources are used. Embodied energy of steel has been provided by the World Steel Association. Of the four devices studied, all were found to achieve CO2 and energy payback within the first 12 years of their lifetime, and exhibited CO2 intensity of between 18 and 35 gCO2/kWh. This compares favourably to many current energy sources, and is likely to fall as technology improves, array size increases and industry experience progresses

Identifying opportunities to integrate digital professionalism into curriculum: a comparison of social media use by health profession students at an Australian university in 2013 and 2016

Social media has become ubiquitous to modern life. Consequently, embedding digitalprofessionalism into undergraduate health profession courses is now imperative and augmentinglearning and teaching with mobile technology and social media on and off campus is a currentcurriculum focus. The aim of this study was to explore whether patterns of social media use forpersonal or informal learning by undergraduate health profession students enrolled at an Australianuniversity across four campuses has changed over time. A previously validated online survey wasadministered in 2013 to a cohort of health profession students as part of an Australian survey. In 2016,the same survey was distributed to a later cohort of health profession students. Three open-endedquestions to elicit descriptive information regarding the use of social media for study purposeswere added to the later survey. A comparative analysis of both cohorts was undertaken and socialmedia acceptance and penetration was shown to increase. Health profession students are nowmore interactive users of Facebook and Twitter, and they have become more familiar with careerdevelopment sites, such as LinkedIn. The maturation of social media platforms within a three-yearperiod has created realistic opportunities to integrate social media for personal and study purposesinto the health profession education curriculum to ensure student understanding of the necessity formaintaining digital professionalism in the workplace

The Wasteland of Random Supergravities

We show that in a general \cal{N} = 1 supergravity with N \gg 1 scalar fields, an exponentially small fraction of the de Sitter critical points are metastable vacua. Taking the superpotential and Kahler potential to be random functions, we construct a random matrix model for the Hessian matrix, which is well-approximated by the sum of a Wigner matrix and two Wishart matrices. We compute the eigenvalue spectrum analytically from the free convolution of the constituent spectra and find that in typical configurations, a significant fraction of the eigenvalues are negative. Building on the Tracy-Widom law governing fluctuations of extreme eigenvalues, we determine the probability P of a large fluctuation in which all the eigenvalues become positive. Strong eigenvalue repulsion makes this extremely unlikely: we find P \propto exp(-c N^p), with c, p being constants. For generic critical points we find p \approx 1.5, while for approximately-supersymmetric critical points, p \approx 1.3. Our results have significant implications for the counting of de Sitter vacua in string theory, but the number of vacua remains vast.Comment: 39 pages, 9 figures; v2: fixed typos, added refs and clarification

A Comprehensive Workflow for General-Purpose Neural Modeling with Highly Configurable Neuromorphic Hardware Systems

In this paper we present a methodological framework that meets novel requirements emerging from upcoming types of accelerated and highly configurable neuromorphic hardware systems. We describe in detail a device with 45 million programmable and dynamic synapses that is currently under development, and we sketch the conceptual challenges that arise from taking this platform into operation. More specifically, we aim at the establishment of this neuromorphic system as a flexible and neuroscientifically valuable modeling tool that can be used by non-hardware-experts. We consider various functional aspects to be crucial for this purpose, and we introduce a consistent workflow with detailed descriptions of all involved modules that implement the suggested steps: The integration of the hardware interface into the simulator-independent model description language PyNN; a fully automated translation between the PyNN domain and appropriate hardware configurations; an executable specification of the future neuromorphic system that can be seamlessly integrated into this biology-to-hardware mapping process as a test bench for all software layers and possible hardware design modifications; an evaluation scheme that deploys models from a dedicated benchmark library, compares the results generated by virtual or prototype hardware devices with reference software simulations and analyzes the differences. The integration of these components into one hardware-software workflow provides an ecosystem for ongoing preparative studies that support the hardware design process and represents the basis for the maturity of the model-to-hardware mapping software. The functionality and flexibility of the latter is proven with a variety of experimental results

The pre-main sequence binary HK Ori : Spectro-astrometry and EXPORT data

In this paper we present multi-epoch observations of the pre-main sequence binary HK Ori. These data have been drawn from the EXPORT database and are complemented by high quality spectro-astrometric data of the system. The spectroscopic data appear to be very well represented by a combination of an A dwarf star spectrum superposed on a (sub-)giant G-type spectrum. The radial velocity of the system is consistent with previous determinations, and does not reveal binary motion, as expected for a wide binary. The spectral, photometric and polarimetric properties and variability of the system indicate that the active object in the system is a T Tauri star with UX Ori characteristics. The spectro-astrometry of HK Ori is sensitive down to milli-arcsecond scales and confirms the speckle interferometric results from Leinert et al. The spectro-astrometry allows with fair certainty the identification of the active star within the binary, which we suggest to be a G-type T Tauri star based on its spectral characteristics.Comment: MNRAS in press 8 pages 7 figure

Predictive Demand Service for Public Transit Using CNN/ Atendimento Preditivo de Demanda do Transporte Público Coletivo Usando CNN

Several cities in Brazil undergo a territorial expansion and inhabitants constantly, this process is called urbanization. An uncontrolled urbanization generates many difficulties, highlighting the mobility of public transport, since many citizens depend on this mobility, we have, for example, public transport in Goiânia, which directly affects the living conditions of passengers. For your foreknowledge, a model capable of mirroring the performance of your demand is essential, providing that the system meets users in an acceptable way. A two-dimensional CNN is a CNN model that has a hidden convolutional layer that operates on a 1D sequence, it is a convenient mechanism to simulate a univariate forecast of time series of the predictive service of Goiânia's public transport. The method is equivalent to an analysis of the focal parts that make up the public transport system and how to represent it in the 1D convolutional neural network. Actual data of the systems and their results were compared to those expected, showing the model's effectiveness. This work manifests a forecast of the demand for public transport in Goiânia, to make it susceptible to users of the system.