Harnessing the power of AI in business

The the first of the two masterclasses delivered to local microcompanies, SMEs and businesses designed to help them learn about digital technologies and AI and strategies helping them to implementing digital tools/ AI into their business. Key themes and objectives: - Introduction to AI in business and AI technologies - Challenges and benefits of AI to business – real-world examples and tips - Adoption challenges and how to overcome them - Responsible and ethical use of AI - Application of AI in your business (marketing, finance, healthcare) Benefits: - Organisations will gain an understanding of digital transformation in small business - Learn practical tips about tools that can be applied in the workplace to support change Who for? Small to medium sized organisations (SMEs) with an appetite for enhancing business capabilities and staying ahead in today’s competitive landscape

Beef Cattle Instance Segmentation Using Fully Convolutional Neural Network

In this paper we present a novel instance segmentation algorithm that extends a fully convolutional network to learn to label objects separately without prediction of regions of interest. We trained the new algorithm on a challenging CCTV recording of beef cattle, as well as benchmark MS COCO and Pascal VOC datasets. Extensive experimentation showed that our approach outperforms the state-of-the-art solutions by up to 8% on our data

A classification of spherically symmetric spacetimes

A complete classification of locally spherically symmetric four-dimensional Lorentzian spacetimes is given in terms of their local conformal symmetries. The general solution is given in terms of canonical metric types and the associated conformal Lie algebras. The analysis is based upon the local conformal decomposition into 2+2 reducible spacetimes and the Petrov type. A variety of physically meaningful example spacetimes are discussed

EFFECTS OF VARIABLE AND FIXED PRACTICE ON THE DEVELOPMENT OF JUMPING ABILITY IN YOUNG CHILDREN

The effects of variable and fixed practice regimes on the development fundamental skills are not fully understood. This study examined the effects of variable and fixed practice in jumping skills in children aged 5 to 6 years. Twenty four children were divided into two groups and each group received fixed or variable practice in jumping skills over a period of six weeks. Jumping skill was evaluated from video records using qualitative analysis procedures. Analysis was carried out before and immediately after the six week intervention and a retention test was conducted one week after the post test. The results indicated that the variable practice group significantly improved their jumping skill compared to pre-test scores but the fixed practice group showed no improvements. The results suggest that variable practice is more effective in improving skill levels in children

Stochastic parameterization: uncertainties from convection

In 2005, the ECMWF held a workshop on stochastic parameterisation, at which the convection was seen as being a key issue. That much is clear from the working group reports and particularly the statement from working group 1 that “it is clear that a stochastic convection scheme is desirable”. The present note aims to consider our current status in comparison with some of the issues raised and hopes expressed in that working group report

The relationship between various live animal scores/measurements and carcass classification for conformation and fatness with meat yield and distribution, and ultimate carcass value

End of project reportAccordingly, the primary objectives of the following study were to: (1) determine the relationship of live animal muscular and skeletal scores, ultrasonically scanned muscle and fat depth measurements of the m. longissimus dorsi, and carcass conformation and fat scores with kill-out proportion, carcass composition and value. (2) Specifically develop and test the accuracy of prediction equations for carcass meat, fat and bone proportions, derived from carcass conformation and fat scores, and develop prediction equations for total carcass composition from hind-quarter composition

The formation heritage of Jupiter Family Comet 10P/Tempel 2 as revealed by infrared spectroscopy

We present spectral and spatial information for major volatile species in Comet 10P/Tempel 2, based on high-dispersion infrared spectra acquired on UT 2010 July 26 (heliocentric distance Rh = 1.44 AU) and September 18 (Rh = 1.62 AU), following the comet's perihelion passage on UT 2010 July 04. The total production rate for water on July 26 was (1.90 +/- 0.12) x 10^28 molecules s-1, and abundances of six trace gases (relative to water) were: CH3OH (1.58% +/- 0.23), C2H6 (0.39% +/- 0.04), NH3 (0.83% +/- 0.20), and HCN (0.13% +/- 0.02). A detailed analysis of intensities for water emission lines provided a rotational temperature of 35 +/- 3 K. The mean OPR is consistent with nuclear spin populations in statistical equilibrium (OPR = 3.01 +/- 0.18), and the (1-sigma) lower bound corresponds to a spin temperature > 38 K. Our measurements were contemporaneous with a jet-like feature observed at optical wavelengths. The spatial profiles of four primary volatiles display strong enhancements in the jet direction, which favors release from a localized vent on the nucleus. The measured IR continuum is much more sharply peaked and is consistent with a dominant contribution from the nucleus itself. The peak intensities for H2O, CH3OH, and C2H6 are offset by ~200 km in the jet direction, suggesting the possible existence of a distributed source, such as the release of icy grains that subsequently sublimed in the coma. On UT September 18, no obvious emission lines were present in our spectra, nevertheless we obtained a 3-sigma upper limit Q(H2O) < 2.86 x 10^27 molecules s-1

Identification of transcription factor contexts in literature using machine learning approaches

Background: Availability of information about transcription factors (TFs) is crucial for genome biology, as TFs play a central role in the regulation of gene expression. While manual literature curation is expensive and labour intensive, the development of semi-automated text mining support is hindered by unavailability of training data. There have been no studies on how existing data sources (e.g. TF-related data from the MeSH thesaurus and GO ontology) or potentially noisy example data (e.g. protein-protein interaction, PPI) could be used to provide training data for identification of TF-contexts in literature. Results: In this paper we describe a text-classification system designed to automatically recognise contexts related to transcription factors in literature. A learning model is based on a set of biological features (e.g. protein and gene names, interaction words, other biological terms) that are deemed relevant for the task. We have exploited background knowledge from existing biological resources (MeSH and GO) to engineer such features. Weak and noisy training datasets have been collected from descriptions of TF-related concepts in MeSH and GO, PPI data and data representing non-protein-function descriptions. Three machine-learning methods are investigated, along with a vote-based merging of individual approaches and/or different training datasets. The system achieved highly encouraging results, with most classifiers achieving an F-measure above 90%. Conclusions: The experimental results have shown that the proposed model can be used for identification of TF-related contexts (i.e. sentences) with high accuracy, with a significantly reduced set of features when compared to traditional bag-of-words approach. The results of considering existing PPI data suggest that there is not as high similarity between TF and PPI contexts as we have expected. We have also shown that existing knowledge sources are useful both for feature engineering and for obtaining noisy positive training data

French responses to the Prague Spring: connections, (mis)perception and appropriation

Looking at the vast literature on the events of 1968 in various European countries, it is striking that the histories of '1968' of the Western and Eastern halves of the continent are largely still written separately.1 Nevertheless, despite the very different political and socio-economic contexts, the protest movements on both sides of the Iron Curtain shared a number of characteristics. The 1968 events in Czechoslovakia and Western Europe were, reduced to the basics, investigations into the possibility of marrying social justice with liberty, and thus reflected a tension within European Marxism. This essay provides an analysis specifically of the responses by the French left—the Communist Party, the student movements and the gauchistes—to the Prague Spring, characterised by misunderstandings and strategic appropriation. The Prague Spring was seen by both the reformist and the radical left in France as a moderate movement. This limited interpretation of the Prague Spring as a liberal democratic project continues to inform our memory of it