Supporting local students. An evaluation of the Office for Students Challenge Competition: Industrial strategy and skills support for local students and graduates'

This paper explores the image of the OfS' funding competition for universities and colleges looking for innovative ways to help students find graduate-level employment close to home. Universities, colleges and employers are found to be taking steps to provide students with skills and knowledge to enhance their employability in their local areas, with 89 per cent of student participants positive about their engagement. The evaluation shows that 89 per cent of student or graduate participants were positive about their participation and 87 per cent of employers participating in the programme reported that their participation had brought value to their business. Through the projects, students have gained confidence in their ability to pursue their desired career, developed clarity of career intention, employability technical skills, and an understanding of local labour markets. Employers found that the project improved recruitment processes supporting graduate applicants from diverse backgrounds and improved awareness of the value of employing graduates. The project also improved market insights, particularly relating to young people’s perspectives and interests, and created new skills leading to business improvements, notably technical and digital skills

INVESTIGATION OF CRUSTAL MOTION IN THE TIEN SHAN USING INSAR

The northern Tien Shan of Central Asia is an area of active mid-continent deformation. Although far from a plate boundary, this region has experienced 5 earthquakes larger than magnitude 7 in the past century and includes one event that may as be as large as Mw 8.0. Previous studies based on GPS measurements indicate on the order of 23 mm/yr of shortening across the entire Tien Shan and up to 15 mm/year in the northern Tien Shan (Figure 1). The seismic moment release rate appears comparable with the geodetic measured slip, at least to first order, suggesting that geodetic rates can be considered a proxy for accumulation rates of stress for seismic hazard estimation. Interferometric synthetic aperture radar may provide a means to make detailed spatial measurements and hence in identifying block boundaries and assisting in seismic hazard. Therefore, we hoped to define block boundaries by direct measurement and by identifying and resolving earthquake slip. Due to political instability in Kyrgzystan, the existing seismic network has not performed as well as required to precisely determine earthquake hypocenters in remote areas and hence InSAR is highly useful. In this paper we present the result of three earthquake studies and show that InSAR is useful for refining locations of teleseismically located earthquakes. ALOS PALSAR data is used to investigate crustal motion in the Tien Shan mountains of Central Asia. As part of the work, considerable software development was undertaken to process PALSAR data. This software has been made freely available. Two damaging earthquakes have been imaged in the Tien Shan and the locations provided by ALOS InSAR have helped to refine seismological velocity models. A third earthquake south of Kyrgyzstan was also imaged. The use of InSAR data and especially L band is therefore very useful in providing groundtruth for earthquake locations

HIGH-RESOLUTION SEISMIC VELOCITY AND ATTENUATION MODELS OF THE CAUCASUS-CASPIAN REGION

The southwest edge of Eurasia is a tectonically and structurally complex region that includes the Caspian and Black Sea basins, the Caucasus Mountains, and the high plateaus south of the Caucasus. Crustal and upper mantle velocities show great heterogeneity in this region and regional phases display variations in both amplitudes and travel time. Furthermore, due to a lack of quality data, the region has largely been unexplored in terms of the detailed lithospheric seismic structure. A unified high-resolution 3D velocity and attenuation model of the crust and upper mantle will be developed and calibrated. This model will use new data from 23 new broadband stations in the region analyzed with a comprehensive set of techniques. Velocity models of the crust and upper mantle will be developed using a joint inversion of receiver functions and surface waves. The surface wave modeling will use both event-based methods and ambient noise tomography. Regional phase (Pg, Pn, Sn, and Lg) Q model(s) will be constructed using the new data in combination with existing data sets. The results of the analysis (both attenuation and velocity modeling) will be validated using modeling of regional phases, calibration with selected events, and comparison with previous work. Preliminary analyses of receiver functions show considerable variability across the region. All results will be integrated into the KnowledgeBase

Full moment tensor and source location inversion based on full waveform adjoint inversion: application at the Geysers geothermal field

Abstract not provide

Detecting and monitoring UCG subsidence with InSAR

The use of interferometric synthetic aperture radar (InSAR) to measure surface subsidence caused by Underground Coal Gasification (UCG) is tested. InSAR is a remote sensing technique that uses Synthetic Aperture Radar images to make spatial images of surface deformation and may be deployed from satellite or an airplane. With current commercial satellite data, the technique works best in areas with little vegetation or farming activity. UCG subsidence is generally caused by roof collapse, which adversely affects UCG operations due to gas loss and is therefore important to monitor. Previous studies have demonstrated the usefulness of InSAR in measuring surface subsidence related to coal mining and surface deformation caused by a coal mining roof collapse in Crandall Canyon, Utah is imaged as a proof-of-concept. InSAR data is collected and processed over three known UCG operations including two pilot plants (Majuba, South Africa and Wulanchabu, China) and an operational plant (Angren, Uzbekistan). A clear f eature showing approximately 7 cm of subsidence is observed in the UCG field in Angren. Subsidence is not observed in the other two areas, which produce from deeper coal seams and processed a smaller volume. The results show that in some cases, InSAR is a useful tool to image UCG related subsidence. Data from newer satellites and improved algorithms will improve effectiveness

Machine learning utilising spectral derivative data improves cellular health classification through hyperspectral infra-red spectroscopy

The objective differentiation of facets of cellular metabolism is important for several clinical applications, including accurate definition of tumour boundaries and targeted wound debridement. To this end, spectral biomarkers to differentiate live and necrotic/apoptotic cells have been defined using in vitro methods. The delineation of different cellular states using spectroscopic methods is difficult due to the complex nature of these biological processes. Sophisticated, objective classification methods will therefore be important for such differentiation. In this study, spectral data from healthy/traumatised cell samples using hyperspectral imaging between 2500-3500 nm were collected using a portable prototype device. Machine learning algorithms, in the form of clustering, have been performed on a variety of pre-processing data types including 'raw' unprocessed, smoothed resampling, background subtracted and spectral derivative. The resulting clusters were utilised as a diagnostic tool for the assessment of cellular health and quantified using both sensitivity and specificity to compare the different analysis methods. The raw data exhibited differences for one of the three different trauma types applied, although unable to accurately cluster all the traumatised samples due to signal contamination from the chemical insult. The background subtracted and smoothed data sets reduced the accuracy further, due to the apparent removal of key spectral features which exhibit cellular health. However, the spectral derivative data-types significantly improved the accuracy of clustering compared to other data types, with both sensitivity and specificity for the background subtracted data set being >94% highlighting its utility to account for unknown signal contamination while maintaining important cellular spectral features