Foreword

Early Middle Cambrian bituminous coquinoid limestones from a tectonically isolated outcrop in southwestern Kyrgyzstan yield a remarkably diverse fauna, with stem-group cnidarians, trilobites, rhynchonelliformean brachiopods, and other shelly fossils. The fossil site is in the northern foothills of the Turkestan Range and thus forms part of the westernmost extension of the South Tien Shan. The fauna includes two fairly well known trilobite species, Glabrella ventrosa Lermontova, 1940 and Dorypyge richthofeniformis Lermontova, 1940, that provide confident support for an Amgan age of the rocks. New described taxa include the stem-group cnidarian Cambroctoconus kyrgyzstanicus Peel sp. nov., the trilobite Olenoides sagittatus Geyer sp. nov., and the helcionelloid Manasoconus bifrons Peel gen. et sp. nov. Additional fossils within the samples include the trilobites Olenoides sp. A, Kootenia sp., and Pseudoeteraspis? sp.; the rhynchonelliform brachiopods Narynella cf. ferganensis (Andreeva, 1962), Narynella? sp., Austrohedra? sp. nov., and two species of uncertain generic affinity; the tommotiid Tesella sp.; the hyolithelminth Hyolithellus sp.; and the palaeoscolecid Hadimopanella oezgueli Gedik, 1977. Of particular interest is Cambroctoconus kyrgyzstanicus with an octagonal corallum and a sparsely septate calyx

Designing mobile experiences for collocated interaction

Many of our everyday social interactions involve mobile devices. Yet, these tend to only provide good support for distributed social interactions. Although much HCI and CSCW research has explored how we might support collocated, face-to-face situations using mobile devices, much of this work exists as isolated exemplars of technical systems and / or interaction designs. This paper draws on a range of such exemplars to develop a practical design framework intended for guiding the design of new mobile experiences for collocated interaction as well as analysing existing ones. Our framework provides four relational perspectives for designing the complex interplay between: the social situation in which it takes place; the technology used and the mechanics inscribed; the physical environment; and the temporal elements of design. Moreover, each perspective is features some core properties, which are highly relevant when designing these systems. As part of presenting the framework we also explain the process of its construction along with practical advice on how to read and apply it

Next-to-leading order QCD corrections to top quark spin correlations at hadron colliders: the reactions gg→ttˉ(g)g g \to t {\bar t} (g) and gq(qˉ)→ttˉq(qˉ)g q ({\bar q}) \to t {\bar t} q ({\bar q})

We have computed the cross section for $t\bar t$ production by gluon-gluon fusion at next-to-leading order (NLO) in the QCD coupling, keeping the full dependence on the $t\bar t$ spins. Furthermore we have determined to the same order the spin dependent cross sections for the processes $g + q ({\bar q})\to t {\bar t} + q ({\bar q})$. Together with our previous results for $q + {\bar q} \to t {\bar t} (g)$ these results allow for predictions, at NLO QCD, of the hadronic production of $t\bar t$ pairs in a general spin configuration. As an application we have determined the degree of correlation of the $t$ and $\bar t$ spins at NLO, using various spin quantisation axes.Comment: 10 pages, 8 figure

The Effect of Light Intensity, Sensor Height, and Spectral Pre-Processing Methods When Using NIR Spectroscopy to Identify Different Allergen-Containing Powdered Foods

Food allergens present a significant health risk to the human population, so their presence must be monitored and controlled within food production environments. This is especially important for powdered food, which can contain nearly all known food allergens. Manufacturing is experiencing the fourth industrial revolution (Industry 4.0), which is the use of digital technologies, such as sensors, Internet of Things (IoT), artificial intelligence, and cloud computing, to improve the productivity, efficiency, and safety of manufacturing processes. This work studied the potential of small low-cost sensors and machine learning to identify different powdered foods which naturally contain allergens. The research utilised a near-infrared (NIR) sensor and measurements were performed on over 50 different powdered food materials. This work focussed on several measurement and data processing parameters, which must be determined when using these sensors. These included sensor light intensity, height between sensor and food sample, and the most suitable spectra pre-processing method. It was found that the K-nearest neighbour and linear discriminant analysis machine learning methods had the highest classification prediction accuracy for identifying samples containing allergens of all methods studied. The height between the sensor and the sample had a greater effect than the sensor light intensity and the classification models performed much better when the sensor was positioned closer to the sample with the highest light intensity. The spectra pre-processing methods, which had the largest positive impact on the classification prediction accuracy, were the standard normal variate (SNV) and multiplicative scattering correction (MSC) methods. It was found that with the optimal combination of sensor height, light intensity, and spectra pre-processing, a classification prediction accuracy of 100% could be achieved, making the technique suitable for use within production environments

QCD corrections to top quark spin correlations at hadron colliders

Future hadron collider experiments will allow for a detailed investigation of $t\bar{t}$ spin correlation effects. In this talk, recent progress in the theoretical description of these effects is reported. In particular, next-to-leading order results for the $t\bar t$ spin correlations in $q\bar{q}\to t\bar{t}X$ are presented, using various spin quantization axes.Comment: 5 pages, 5 figures. Talk presented at the conference `QCD 00', Montpellier, 6-13th July 2000, to appear in the proceeding