1,722,202 research outputs found
Hearts & homes [music] : ballad /
No full textFor voice and piano.; Cover title.; "Solo".; "Companion to the admired ballad 'Speak gently!' by John Blockley"--Caption.; Also available online http://nla.gov.au/nla.mus-vn1975042; Library's N copy lacks t.p
Hearts & homes [music] : ballad /
No full textSolo. For voice and piano.; Cover title.; Date approximated from publishers' imprints: S. Marshall & Sons at 52 Rundle St from 1863 to 1915 [one son of the business died in 1879]; John Blockley at Argyle St, London from 1867 to 1906.; Also available online http://nla.gov.au/nla.mus-vn4927517.Hearts and home
Nearer my God to thee [music] : sacred song /
No full textCover title.; "Inscribed to Lady Dufferin". - p.1.; Sixth edition.; Also available online http://nla.gov.au/nla.mus-vn1689986; MUS: MUSM 114023
Jessie's dream, a story of the 'Relief of Lucknow'. [music] /
No full textCover title.; A. Laby, lith.; Stannard & Dixon, imp.; Also available online http://nla.gov.au/nla.mus-vn1685816; A copy, MUS: MUSM 114023/ ; B copy, MUS N m 780 AA v.37
I remember thy voice, Ballad, / written by The Hon..ble Mrs. Norton, composed by John Blockley.
No full textG major [key]moderato [tempo]Ballad [form/genre]Blockley, John (1800-1882), composer and publisher.Piano forte and voice [instrumentation]Small & Paige, Toronto. [dealer stamp]A select list of new and popular vocal music by John Blockley
Draycott Lane, Blockley, Gloucestershire. Archaeological Evaluation (OASIS ID: cotswold2-300103)
No full textAn archaeological evaluation was undertaken by Cotswold Archaeology in November 2017 on land at Draycott Lane, Blockley, Gloucestershire. Four trenches were excavated. A number of ditches and pits were identified on the site, predominantly dating to the Iron Age and Roman periods and potentially representing an area of agricultural and settlement activity. These remains were heavily truncated by post-Roman ridge and furrow and modern activity
Data acquired to demonstrate model-based Bayesian inference of brain oxygenation using quantitative BOLD
No full textThis dataset will form the basis of a forthcoming publication regarding a model-based Bayesian analysis of streamlined quantitative BOLD data to measure brain oxygenation. In the absence of a reference to this publication the methods used are outlined here. Please reference this dataset if you use it in your work.
Cherukara MT, Stone AJ, Chappell MA, Blockley NP. Data acquired to demonstrate model-based Bayesian inference of brain oxygenation using quantitative BOLD, Oxford University Research Archive 2018. doi: 10.5287/bodleian:6R5px9K0X
*Summary*
Data for Study 1 (7 subjects) of this dataset were acquired as part of a previous study [1] and are also available at via the Oxford University Research Archive [2]. Data for Study 2 (5 subjects) were acquired to demonstrate and validate a model-based Bayesian analysis method of similar data. The aim in this part was to see whether a model-based correction for CSF signal, using an independent CSF partial volume estimate, could be used in place of a FLAIR preparation [3] in order to improve image SNR and reduce total scan time. Images were acquired the streamlined qBOLD protocol [1] both with and without FLAIR preparation, using an Asymmetric Spin Echo (ASE) pulse sequence [4] with Gradient Echo Slice Excitation Profile Imaging (GESEPI) incorporated to minimise the effect of through-slice magnetic field gradients [5].
*MRI data*
Images were acquired using a Siemens Magnetom Verio scanner at 3T. The body coil was used for transmission and the manufacturer's 32-channel head coil was used for reception. For Study 1, GESEPI ASE (GASE) data were acquired with a field of view of 240x240 mm2, a 64x64 matrix, ten 5mm slices, TR/TE=3s/74ms, and an EPI bandwidth of 2004Hz/px. ASE images are acquired with varying amount of R2′ weighting determined by the spin echo displacement time, tau. Twenty four values of tau were acquired for each GASE scan: -28, -24, -20, -16, -12, -8, -4, 0, 4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44, 48, 52, 56, 60, and 64ms. For Study 2, GASE data were acquired with a 220x220 mm2 field of view, a 96x96 matrix, eight 5mm slices, TR/TE=3s/82ms, an EPI bandwidth of 2004Hz/px, and eleven tau values: -16, -8, 0, 8, 16, 24, 32, 40, 48, 56, and 64ms. For all subjects, the GESEPI magnetic field gradient correction technique required each 5mm slice to be encoded into multiple thin partitions each 1.25mm thick. Furthermore, partitions were oversampled by 100% leading to the acquisition of 8 partitions per slice. Oversampled slices were discarded during reconstruction, resulting in 40 slices being acquired for each tau value. To regain signal to noise ratio summing the slices in blocks of four is suggested. This results in the original number of prescribed slices. A FLAIR preparation was used to null the signal from CSF, with an inversion time of 1.21s, based on literature values for T1 and T2 of CSF [3]. In Study 2, GASE data were also acquired with the same protocol but without the FLAIR preparation, as well as a single GASE volume with the same parameters, except with a TE of 250ms, and tau of 0ms, and a set of eight 2D spin echo volumes with the same dimensions as the GASE data were acquired with TE values uniformly spaced from 66 to 248 ms. These were used to generate T2 weighted estimates of CSF partial volume. High resolution T1 weighted anatomical images were acquired for registration and the generation of tissue masks and T1 weighted CSF partial volume estimates. Anatomicals were “defaced” using the shell script in the code directory [6].
*Data curation*
The structure in which this data has been placed is based on the Brain Imaging Data Structure (BIDS) format [7]. However, this format (BIDS version 1.0.0-rc2) does not support ASE data, but we have followed the guiding principles of this specification.
*References*
1. Stone AJ, Blockley NP. A streamlined acquisition for mapping baseline brain oxygenation using quantitative BOLD. NeuroImage 2017:147:79-88.
2. Stone AJ, Blockley NP. Data acquired to demonstrate a streamlined approach to mapping and quantifying brain oxygenation using quantitative BOLD. Oxford University Research Archive 2016. doi: 10.5287/Bodleian:E24JbXQwO.
3. Hajnal JV, Bryant DJ, Kasuboski L, Pattany PM, De Coene B, Lewis PD, Pennock JM, Oatridge A, Young IR, Bydder GM. Use of fluid attenuated inversion recovery (FLAIR) pulse sequences in MRI of the brain. J Comput Assist Tomogr
1992;16:841–844.
4. Wismer GL, Buxton RB, Rosen BR, Fisel CR, Oot RF, Brady TJ, Davis KR. Susceptibility induced MR line broadening: applications to brain iron mapping. J Comput Assist Tomogr 1988;12:259–265.
5. Blockley NP, Stone AJ. Improving the specificity of R2′ to the deoxyhaemoglobin content of brain tissue: Prospective correction of macroscopic magnetic field gradients. Neuroimage 2016, in press. doi: 10.1016/j.neuroimage.2016.04.013
6. https://github.com/hanke/gumpdata/blob/master/scripts/conversion/convert_dicoms_anatomy
7. http://bids.neuroimaging.i
Yesterday [music] /
No full textFor voice and piano.; Caption title.; "Companion to the admired ballads To day, To morrow and For ever" -- Cover.; Also available online http://nla.gov.au/nla.mus-an12823244
Yesterday [music] /
No full textKey of E-flat. For voice and piano.; Caption title.; "Companion to the admired ballads To day, To-morrow and For ever".; Also available online http://nla.gov.au/nla.mus-vn4766989
Data generated by a Monte Carlo based simple vessel simulation of the ASE qBOLD signal
No full textThe data in this archive was generated using a Monte Carlo based numerical simulation of the extravascular blood oxygenation level dependent effect (BOLD) MRI signal. This data will underpin a forthcoming publication investigating systematic error in the asymmetric spin echo (ASE) quantitative BOLD (qBOLD) technique. Please reference this dataset if you use it in your work. Stone AJ, Holland NC, Berman AJL, Blockley NP. Data generated by a Monte Carlo based simple vessel simulation of the ASE qBOLD signal. Oxford University Research Archive 2019. See ORA record for DOI.
The archive consists of multiple data sets, which are saved as MATLAB .mat files. Each folder contains one .mat file for each simulated vessel radius with the format simvessim_resX.mat, where X is the vessel radius in micrometers. Basic physiological parameters are varied for each folder, which can be found in the MATLAB structure p contained within each .mat file
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