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CUBES is a high efficiency spectrograph designed for a Cassegrain focus of the Very Large Telescope and is expected to be in operation in 2028. It is designed to observe point or compact sources in a spectral range from 300 to 405nm. CUBES will provide two spectral resolving powers: R$$\ge$$ ≥ 20,000 for high resolution (HR) and R$$\ge$$ ≥ 5,000 for low resolution (LR). This is achieved by using an image slicer for each resolution mode. The image slicers re-format a rectangular on-sky field of view of either 1.5arcsec by 10arcsec (HR) or 6arcsec by 10arcsec (LR) into six side-by-side slitlets which form the spectrograph slit. The slit dimensions are 0.19mm $$\times$$ × 88mm for HR and 0.77mm $$\times$$ × 88mm for LR. The on-sky and physical widths of the slicer mirrors are 0.25arcsec/0.5mm (HR) and 1arcsec/2mm (LR). The image slicers reduce the spectrograph entrance slit etendue and hence the size of the spectrograph optics without associated slit losses. Each of the proposed image slicers consists of two arrays of six spherical mirrors (slicer mirror and camera mirror arrays) which provide a straight entrance slit to the spectrograph with almost diffraction-limited optical quality. This paper presents the description of the image slicers at the end of the Phase A conceptual design, including their optical design and expected performance.

This thesis addresses a need for further evaluation of existing and new innovation survey indicators, which now provide an important evidence base informing better policy approaches. The research focus is on indicators produced from large scale, economy-wide innovation surveys, which collect firm-level data, and move beyond traditional R&D, patent, and bibliometric approaches by providing a direct, 'subject' approach to measurement. Such surveys are conducted in approximately 80 countries, producing numerous indicators, though many portray counterintuitive results, and are subject to various shortcomings. Consequently, this study seeks to explore how new indicators can improve understanding of innovation. Three indicator categories are assessed, using microdata from two iterations of a large regional innovation survey, the Tasmanian Innovation Census (TIC). Results examine three degrees of innovation novelty, and show that R&D activity and intensity provide good measures of innovation capability. Complex 'mode' indicators reveal the distribution of innovation characteristics at a 'system' level, across sectors, and for firms of different sizes, with linear, chain-link and systems theories all underpinning selected indicators. Using panel data, 'output' mode indicators reveal specific movement of both innovative and non-innovative firms between four innovation modes, providing a dynamic understanding of capability development and erosion over time, and suggesting that innovation capability for the most part develops cumulatively. Innovation based on diffusion is shown as most common in services. Composite indicator results provide a simple, visual picture of sectoral innovation performance, demonstrating usefulness beyond the typical macro-level of analysis. Results and discussion expose issues around theory, policy and practice with implications for related future research, including a need for further work to standardise different indicators for degrees of novelty and capability, and for research to understand the links between innovation modes and economic outcomes.

The importance of accurate structural discrimination of the human grey matter regions has motivated the development of observer-independent reproducible methods that account for inter-individual architectonic variations. We introduce a non-invasive statistical residual analysis framework, employing unique tissue-specific magnetic resonance fingerprinting (MRF) signals after adjusting for the effect of T1 and T2* MR relaxometry parameters (here termed MRF residuals). A 7 T Siemens MR scanner was used to acquire MRF signals, quantitative transmit magnetic field (B1+) maps and T1-weighted anatomical images of eleven cortical areas (5L, 5M, 5Ci, 7A, 7P, 7PC, hIP3, BA2, BA4a, BA4p and BA6) from six female participants. MRF residual signal for each voxel was calculated as the difference between the actual and best matching MRF signal evolutions from a precomputed MRF dictionary covering a range of T1, T2* and B1+ values. To compare MRF residuals between regions of interest, normalised autocorrelation was used as a shape-based statistical signal characterisation method and the Euclidean distance between autocorrelation profiles of residuals was used to measure the interareal dissimilarity. In the eleven cortical areas in both cerebral hemispheres of six participants, the proposed MRF residual analysis consistently showed interareal dissimilarity profiles that concorded with histological studies, indicating that MRF residuals potentially contain tissue microstructural information. MRF residual signals provide additional area-specific information that is complementary to the MR relaxometry-based (T1, T2*) information used previously for distinguishing microstructural differences between human cerebral cortex regions in vivo. The proposed approach led to more accurate identification of structural variations across cortical areas of interest.

PURPOSE: Quantitative susceptibility mapping (QSM) estimates the spatial distribution of tissue magnetic susceptibilities from the phase of a gradient-echo signal. QSM algorithms require a signal mask to delineate regions with reliable phase for subsequent susceptibility estimation. Existing masking techniques used in QSM have limitations that introduce artifacts, exclude anatomical detail, and rely on parameter tuning and anatomical priors that narrow their application. Here, a robust masking and reconstruction procedure is presented to overcome these limitations and enable automated QSM processing. Moreover, this method is integrated within an open-source software framework: QSMxT. METHODS: A robust masking technique that automatically separates reliable from less reliable phase regions was developed and combined with a two-pass reconstruction procedure that operates on the separated sources before combination, extracting more information and suppressing streaking artifacts. RESULTS: Compared with standard masking and reconstruction procedures, the two-pass inversion reduces streaking artifacts caused by unreliable phase and high dynamic ranges of susceptibility sources. It is also robust across a range of acquisitions at 3 T in volunteers and phantoms, at 7 T in tumor patients, and in an in silico head phantom, with significant artifact and error reductions, greater anatomical detail, and minimal parameter tuning. CONCLUSION: The two-pass masking and reconstruction procedure separates reliable from less reliable phase regions, enabling a more accurate QSM reconstruction that mitigates artifacts, operates without anatomical priors, and requires minimal parameter tuning. The technique and its integration within QSMxT makes QSM processing more accessible and robust to streaking artifacts.

Objective: Ultra-high-field B0 ≥ 7 tesla (7T) cardiovascular magnetic resonance (CMR) offers increased resolution. However, electrocardiogram (ECG) gating is impacted by the magneto-hydrodynamic effect distorting the ECG trace. We explored the technical feasibility of a 7T magnetic resonance scanner using an ECG trigger learning algorithm to quantitatively assess cardiac volumes and vascular flow. Methods: 7T scans were performed on 10 healthy volunteers on a whole-body research MRI MR scanner (Siemens Healthineers, Erlangen, Germany) with 8 channel Tx/32 channels Rx cardiac coils (MRI Tools GmbH, Berlin, Germany). Vectorcardiogram ECG was performed using a learning phase outside of the magnetic field, with a trigger algorithm overcoming severe ECG signal distortions. Vectorcardiograms were quantitatively analyzed for false negative and false positive events. Cine CMR was performed after 3rd-order B0 shimming using a high-resolution breath-held ECG-retro-gated segmented spoiled gradient echo, and 2D phase contrast flow imaging. Artefacts were assessed using a semi-quantitative scale. Results: 7T CMR scans were acquired in all patients (100%) using the vectorcardiogram learning method. 3,142 R-waves were quantitatively analyzed, yielding sensitivity of 97.6% and specificity of 98.7%. Mean image quality score was 0.9, sufficient to quantitate both cardiac volumes, ejection fraction, and aortic and pulmonary blood flow. Mean left ventricular ejection fraction was 56.4%, right ventricular ejection fraction was 51.4%. Conclusion: Reliable cardiac ECG triggering is feasible in healthy volunteers at 7T utilizing a state-of-the-art three-lead trigger device despite signal distortion from the magnetohydrodynamic effect. This provides sufficient image quality for quantitative analysis. Other ultra-high-field imaging applications such as human brain functional MRI with physiologic noise correction may benefit from this method of ECG triggering.

We present the results regarding the analysis of the fast X-ray/infrared (IR) variability of the black-hole transient MAXI J1535$-$571. The data studied in this work consist of two strictly simultaneous observations performed with XMM-Newton (X-rays: 0.7$-$10 keV), VLT/HAWK-I ($K_{\rm s}$ band, 2.2 $\mu$m) and VLT/VISIR ($M$ and $PAH2$_$2$ bands, 4.85 and 11.88 $\mu$m respectively). The cross-correlation function between the X-ray and near-IR light curves shows a strong asymmetric anti-correlation dip at positive lags. We detect a near-IR QPO (2.5 $\sigma$) at $2.07\pm0.09$ Hz simultaneously with an X-ray QPO at approximately the same frequency ($f_0=2.25\pm0.05$). From the cross-spectral analysis a lag consistent with zero was measured between the two oscillations. We also measure a significant correlation between the average near-IR and mid-IR fluxes during the second night, but find no correlation on short timescales. We discuss these results in terms of the two main scenarios for fast IR variability (hot inflow and jet powered by internal shocks). In both cases, our preliminary modelling suggests the presence of a misalignment between disk and jet., Comment: 12 pages, 7 figures. Accepted for publication in MNRAS

Local recurrence in glioblastoma (GBM) patients is caused by the ability of tumour cells to develop treatment resistance mechanisms. Hypoxia, which is present in subregions of GBM tumours, is the leading cause of resistance to radiotherapy and is associated with worse clinical outcomes in GBM. Current standard of care treatment does not account for tumour hypoxia. The ability to image tumour hypoxia at various stages of treatment offers opportunities to personalise and improve treatment for GBM patients. Preoperative imaging of tumour hypoxia offers the opportunity for supramarginal resections in surgical planning beyond current neurosurgical standard of care guidelines. Imaging hypoxia prior to radiotherapy enables selective dose escalation strategies to radioresistant tumour regions, increasing the likelihood of local control. Identifying hypoxic tumour regions harbouring progression at follow up is key to intervening at an early stage of tumour recurrence and personalising therapy tailored to the tumour response to treatment. Imaging of tumour hypoxia in routine clinical practice is challenging, as it requires 18FMISO PET, which is not available in most clinical centres. In this clinical imaging study, we aim to investigate the role of oxygen enhanced (OE) and blood-oxygen level dependent (BOLD) MRI as imaging biomarkers of hypoxia in GBM. Aiming to recruit 20 GBM patients, this study involves the addition of OE/BOLD MRI and 18FMISO PET imaging at several timepoints during the course of treatment. The primary objective is to investigate the ability of OE/BOLD MRI to map tumour hypoxia on preoperative scans using 18FMISO PET as the ground truth. Secondary objectives include evaluating the role of hypoxia imaging biomarkers for dose-painting radiotherapy planning and treatment response assessment in GBM. Overall, by validating the role of MRI biomarkers of hypoxia we ought to provide a non-invasive and more accessible means to more effective, personalised treatment to GBM patients.

Purpose The purpose of this study is to demonstrate a method for specific absorption rate (SAR) reduction for 2D T2 -FLAIR MRI sequences at 7 T by predicting the required adiabatic radiofrequency (RF) pulse power and scaling the RF amplitude in a slice-wise fashion. Methods We used a time-resampled frequency-offset corrected inversion (TR-FOCI) adiabatic pulse for spin inversion in a T2 -FLAIR sequence to improve B 1 + homogeneity and calculated the pulse power required for adiabaticity slice-by-slice to minimize the SAR. Drawing on the implicit B 1 + inhomogeneity in a standard localizer scan, we acquired 3D AutoAlign localizers and SA2RAGE B 1 + maps in 28 volunteers. Then, we trained a convolutional neural network (CNN) to estimate the B 1 + profile from the localizers and calculated pulse scale factors for each slice. We assessed the predicted B 1 + profiles and the effect of scaled pulse amplitudes on the FLAIR inversion efficiency in oblique transverse, sagittal, and coronal orientations. Results The predicted B 1 + amplitude maps matched the measured ones with a mean difference of 9.5% across all slices and participants. The slice-by-slice scaling of the TR-FOCI inversion pulse was most effective in oblique transverse orientation and resulted in a 1 min and 30 s reduction in SAR induced delay time while delivering identical image quality. Conclusion We propose a SAR reduction technique based on the estimation of B 1 + profiles from standard localizer scans using a CNN and show that scaling the inversion pulse power slice-by-slice for FLAIR sequences at 7T reduces SAR and scan time without compromising image quality.

Simultaneous [18 F]-fluorodeoxyglucose positron emission tomography and functional magnetic resonance imaging (FDG-PET/fMRI) provides the capability to image two sources of energetic dynamics in the brain – cerebral glucose uptake and the cerebrovascular haemodynamic response. Resting-state fMRI connectivity has been enormously useful for characterising interactions between distributed brain regions in humans. Metabolic connectivity has recently emerged as a complementary measure to investigate brain network dynamics. Functional PET (fPET) is a new approach for measuring FDG uptake with high temporal resolution and has recently shown promise for assessing the dynamics of neural metabolism. Simultaneous fMRI/fPET is a relatively new hybrid imaging modality, with only a few biomedical imaging research facilities able to acquire FDG PET and BOLD fMRI data simultaneously. We present data for n = 27 healthy young adults (18–20 yrs) who underwent a 95-min simultaneous fMRI/fPET scan while resting with their eyes open. This dataset provides significant re-use value to understand the neural dynamics of glucose metabolism and the haemodynamic response, the synchrony, and interaction between these measures, and the development of new single- and multi-modality image preparation and analysis procedures., Measurement(s) glucose import • haemodynamic response • functional brain measurement Technology Type(s) FDG-Positron Emission Tomography • Blood Oxygen Level-Dependent Functional MRI Factor Type(s) resting human brain Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12994508

The MORDOR trial in Niger, Malawi, and Tanzania found that biannual mass distribution of azithromycin to children younger than 5 years led to a 13.5% reduction in all-cause mortality (NCT02048007). To help elucidate the mechanism for mortality reduction, we report IgG responses to 11 malaria, bacterial, and protozoan pathogens using a multiplex bead assay in pre-specified substudy of 30 communities in the rural Niger placebo-controlled trial over a three-year period (n = 5642 blood specimens, n = 3814 children ages 1–59 months). Mass azithromycin reduces Campylobacter spp. force of infection by 29% (hazard ratio = 0.71, 95% CI: 0.56, 0.89; P = 0.004) but serological measures show no significant differences between groups for other pathogens against a backdrop of high transmission. Results align with a recent microbiome study in the communities. Given significant sequelae of Campylobacter infection among preschool aged children, our results support an important mechanism through which biannual mass distribution of azithromycin likely reduces mortality in Niger.

Azithromycin is a promising alternative to amoxicillin in the management of uncomplicated severe acute malnutrition (SAM) as it can be administered as a single dose and has efficacy against several pathogens causing infectious disease and mortality in children under 5. In this pilot trial, we aimed to establish the feasibility of a larger randomized controlled trial and provide preliminary evidence comparing the effect of azithromycin to amoxicillin on weight gain in children with uncomplicated SAM. We enrolled children 6–59 months old with uncomplicated SAM at six healthcare centers in Burkina Faso. Participants were randomized to a single dose of azithromycin or a 7-day course of amoxicillin and followed weekly until nutritional recovery and again at 8 weeks. Apart from antibiotics, participants received standard of care, which includes ready-to-use therapeutic food. Primary feasibility outcomes included enrollment potential, refusals, and loss to follow-up. The primary clinical outcome was weight gain (g/kg/day) over 8 weeks. Outcome assessors were masked. Between June and October 2020, 312 children were screened, 301 were enrolled with zero refusals, and 282 (93.6%) completed the 8-week visit. Average weight gain was 2.5 g/kg/day (standard deviation [SD] 2.0) in the azithromycin group and 2.6 (SD 1.7) in the amoxicillin group (mean difference −0.1, 95% CI −0.5 to 0.3, P = 0.63). Fewer adverse events were reported in the azithromycin group (risk ratio 0.50, 95% CI 0.31–0.82, P = 0.006). With strong enrollment and follow-up, a fully powered trial in this setting is feasible.

KIDSpec, the Kinetic Inductance Detector Spectrograph, is a concept for a highly sensitive, medium-spectral-resolution optical through near-IR spectrograph. It uses the intrinsic-energy-resolving capability of an array of optical/IR-sensitive MKIDs to distinguish multiple orders from a low-resolution grating. By acting as an ‘order resolver,’ the MKID array replaces the cross-disperser in an echelle spectrograph. This greatly simplifies the optical layout of the spectrograph and enables longer slits than are possible with cross-dispersed instruments (to improve sky subtraction). KIDSpec would have similar capabilities to ESO’s highly successful X-shooter instrument. It would provide an R = 4000–10,000 spectrum covering the optical and near-IR spectral range (0.4–1.5 µm). As well as a ‘long-slit’ mode, the IFU would provide a small ($$\sim 50\hbox { spaxel}$$∼50spaxel) field of view for spatially resolved sources. In addition, the photon-counting operation of MKIDs and their photon-energy-resolving ability enable a read-noise-free spectrum with perfect cosmic ray removal. The spectral resolution would be sufficient to remove the bright night-sky lines without the additional pixel noise, making the instrument more sensitive than an equivalent semiconductor-based instrument. KIDSpec would enhance many existing high-profile science cases, including transient (GRB, SNe, etc.) follow-up, redshift determination of faint objects and transit spectroscopy of exoplanets. In addition, it will enable unique science cases, such as dynamical mass estimates of the compact objects in ultra-compact binaries.

PurposeQuantitative Susceptibility Mapping (QSM) is a post-processing technique applied to gradient-echo phase data. QSM algorithms require a signal mask to delineate regions with reliable phase signal for subsequent susceptibility estimation. Existing masking techniques used in QSM have limitations that introduce artefacts, exclude anatomical detail, and rely on parameter tuning and anatomical priors that narrow their application. Here, a robust masking and reconstruction procedure is presented to overcome these limitations and enable automated QSM processing for a wide range of use-cases implemented in an open-source software framework: QSMxT.MethodsA robust masking technique that automatically separates reliable from less reliable phase regions was developed and combined with a two-pass reconstruction procedure that operates on the separated sources before combination, extracting more information while reducing the influence of artefacts.ResultCompared with standard masking and reconstruction procedures, the two-pass inversion reduces streaking artefacts caused by unreliable phase and high dynamic ranges of susceptibility sources. QSMxT is robust across a range of datasets at 3 T in healthy volunteers and phantoms, at 7 T in tumour patients, and in the QSM challenge 2.0 simulated brain dataset, with significant artefact and error reductions, greater anatomical detail, and minimal parameter tuning.ConclusionQSMxT generates masks for QSM that separate reliable from less reliable phase regions, enables a more accurate QSM reconstruction that mitigates artefacts, operates without anatomical priors, and requires minimal parameter tuning. QSMxT makes QSM processing more accessible, reliable and reproducible.

HARMONI is the adaptive optics assisted, near-infrared and visible light integral field spectrograph for the Extremely Large Telescope (ELT). A first light instrument, it provides the work-horse spectroscopic capability for the ELT. As the project approaches its Final Design Review milestone, the design of the instrument is being finalized, and the plans for assembly, integration and testing are being detailed. We present an overview of the instrument's capabilities from a user perspective, provide a summary of the instrument's design, including plans for operations and calibrations, and provide a brief glimpse of the predicted performance for a specific observing scenario. The paper also provides some details of the consortium composition and its evolution since the project commenced in 2015.

This paper presents an analysis of the predicted performance of Microwave Kinetic Inductance Detectors (MKIDS) in interferometric instruments. MKIDS are energy sensitive photon counting detectors which can be designed to operate over a wide range of photon energies, and have excellent timing capabilities. Several Optical and near-IR (OIR) MKID instruments have already been used on-sky, and there are ongoing developments in the US and Europe to improve their capabilities for a wide range of science cases. For interferometric instruments the benefits are clear, with no read out noise or dark current, and time resolution of a microsecond, they can be used for both fringe tracking and science detectors. The inherent energy resolution allows for a range of potential improvements to instruments, from rejection of stray light and cosmic rays, to improved wavelength coverage, to simplified optical designs with few, or no, moving elements.

IntroductionThe majority of blindness worldwide could be prevented or reversed with early diagnosis and treatment, yet identifying at-risk and prevalent cases of eye disease and linking them with care remain important obstacles to addressing this burden. Leading causes of blindness like glaucoma, diabetic retinopathy and age-related macular degeneration have detectable early asymptomatic phases and can cause irreversible vision loss. Mass screening for such diseases could reduce visual impairment at the population level.Methods and analysisThis protocol describes a parallel-group cluster-randomised trial designed to determine whether community-based screening for glaucoma, diabetic retinopathy and age-related macular degeneration reduces population-level visual impairment in Nepal. A door-to-door population census is conducted in all study communities. All adults aged ≥60 years have visual acuity tested at the census visit, and those meeting referral criteria are referred to a local eye care facility for further diagnosis and management. Communities are subsequently randomised to a community-based screening programme or to no additional intervention. The intervention consists of a single round of screening including intraocular pressure and optical coherence tomography assessment of all adults ≥60 years old with enhanced linkage to care for participants meeting referral criteria. Four years after implementation of the intervention, masked outcome assessors conduct a repeat census to collect data on the primary outcome, visual acuity. Individuals with incident visual impairment receive a comprehensive ophthalmological examination to determine the cause of visual impairment. Outcomes are compared by treatment arm according to the originally assigned intervention.Ethics and disseminationThe trial has received ethical approval from the University of California San Francisco Institutional Review Board, Nepal Netra Jyoti Sangh and the Nepal Health Research Council. Results of this trial will be disseminated through publication in peer-reviewed journals and presentation at local and international meetings.Trial registration numberNCT03752840

Optical and near-infrared Microwave Kinetic Inductance Detectors, or MKIDs, are low-temperature detectors with inherent spectral resolution that are able to instantly register individual photons with potentially no false counts or readout noise. These properties make MKIDs transformative for exoplanet direct imaging by enabling photon-statistics-based planet-discrimination techniques as well as performing conventional noise-subtraction techniques on shorter timescales. These detectors are in the process of rapid development, and as such, the full extent of their performance enhancing potential has not yet be quantified. MKID Exoplanet Direct Imaging Simulator, or MEDIS, is a general-purpose end-to-end numerical simulator for high-contrast observations with MKIDs. The simulator exploits current optical propagation libraries and augments them with a new MKIDs simulation module to provide a pragmatic model of many of the degradation effects present during the detection process. We use MEDIS to demonstrate how changes in various MKID properties affect the contrast-separation performance when conventional differential imaging techniques are applied to low-flux, short duration observations. We show that to improve performance at close separations will require increasing the maximum count rate or pixel sampling when there is high residual flux after the coronagraph. We predict that taking pixel yield from the value achieved by current instruments of 80% and increasing it to 100% would result in an improvement in contrast of a factor of $\sim$ 4 at 3$\lambda/D$ and $\sim$ 8 at 6$\lambda/D$. Achieving better contrast performance in this low flux regime would then require exploiting the information encoded in the photon arrival time statistics.

Although having a relatively homogeneous cytoarchitectonic organization, the cerebellar cortex is a heterogeneous region characterized by different amounts of myelin, iron and protein expression profiles. In this study, we used quantitative T1 and T2* mapping at ultra-high field (7T) MRI to investigate the tissue characteristics of the cerebellar gray matter surface and its layers. Detailed subject-specific surfaces were generated at three different cortical depths and averaged across subjects to create averaged T1 and T2* maps on the cerebellar surface. T1 surfaces showed an alternation of lower and higher T1 values when going from the median to the lateral part of the cerebellar hemispheres. In addition, longer T1 values were observed in the more superficial gray matter layers. T2* maps showed a similar longitudinal pattern, but no change related to the cortical depths. These patterns are possibly due to variations in the level of myelination, iron and zebrin protein expression.

Purpose: We present the initial in vivo imaging results of an open architecture eight-channel parallel transmission (pTx) transceive radiofrequency (RF) coil array that was designed and constructed for static and dynamic 7T MRI of the knee and ankle joints. Methods: The pTx coil has a U-shaped dual-row configuration (200 mm overall length longitudinally) that allows static and dynamic imaging of the knee and ankle joints at various postures and during active movements. This coil structure, in combination with B shimming, allows flexible configuration of B transmit profiles, with good homogeneity over 120-mm regions of interest. This coil enabled high-resolution gradient echo (e.g., 3D dual-echo steady state [DESS] and 3D multiecho data image combination [MEDIC]) and turbo spin echo (TSE) imaging (e.g., with proton density weighting [PDw], PDw with fat saturation, and T and T weightings) with local RF energy absorption rates well below regulatory limits. Results: High-resolution 2D and 3D image series (e.g., 0.3 mm in-plane resolution for TSE, 0.47 mm isotropic for DESS and MEDIC) were obtained from the knee and ankle joints with excellent tissue contrast. Dynamic imaging during continuous knee and ankle flexion-extension cycles were successfully acquired. Conclusion: The new open pTx coil array provides versatility for high-quality static and dynamic MRI of the knee and ankle joints at 7T. Magn Reson Med 79:1804–1816, 2018.

Purpose Quantitative susceptibility mapping is a technique to estimate the magnetic property of tissue with particularly high sensitivity at ultra-high field. However, a key challenge at ultra-high field is the combination of phase data acquired using phased array receive coils. Several methods for combining phase data have been proposed, but the influence of coil combination choices on susceptibility quantitation has not been studied systematically. Methods We combined phase data using COMPOSER (COMbining Phase data using a Short Echo-time Reference scan) and a reference-free channel-by-channel method. We investigated the effect of the chosen combination method on susceptibility results in a group of 28 participants at 7 Tesla. Results Our results show that reference scans can bias susceptibility values. Although the proposed reference-free channel-by-channel method cannot remove transmit field phase, it shows comparable results to the COMPOSER method in which a high-resolution ultrashort echo-time reference scan was used. Conclusions We conclude that ultrashort echo-time reference scans reduce quantitation bias and remove the transmit field phase when using COMPOSER to combine phase data, and not combining the phase data before susceptibility processing avoids this bias, resulting in comparable results. Magn Reson Med 79:97–107, 2018. © 2017 InternationalSociety for Magnetic Resonance in Medicine.

Several diffusion-weighted MRI techniques have been developed and validated during the past 2 decades. While offering various neuroanatomical inferences, these techniques differ in their proposed optimal acquisition design, preventing clinicians and researchers benefiting from all potential inference methods, particularly when limited time is available. This study reports an optimal design that enables for a time-efficient diffusion-weighted MRI acquisition scheme at 7 Tesla. The primary audience of this article is the typical end user, interested in diffusion-weighted microstructural imaging at 7 Tesla.We tested b-values in the range of 700 to 3000 s/mmThe suggested design is a protocol with b-values of 1000 and 2500 s/mmWe estimated minimum acquisition requirements that enable diffusion tensor imaging, higher angular resolution diffusion-weighted imaging, neurite orientation dispersion, and density imaging and white matter tract integrity across whole brain with isotropic resolution of 1.8 mm in less than 11 min. Magn Reson Med 78:2170-2184, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

HARMONI (High Angular Resolution MOnolithic Integral field spectrograph) 1 is a planned first-light integral field spectrograph for the Extremely Large Telescope. The spectrograph sub-system is being designed, developed, and built by the University of Oxford. The project has just completed the Preliminary Design Review (PDR), with all major systems having nearly reached a final conceptual design. As part of the overall prototyping and assembly, integration, and testing (AIT) of the HARMONI spectrograph, we will be building a full-scale engineering model of the spectrograph. This will include all of the moving and mechanical systems, but without optics. Its main purpose is to confirm the AIT tasks before the availability of the optics, and the system will be tested at HARMONI cryogenic temperatures. By the time of the construction of the engineering model, all of the individual modules and mechanisms of the spectrograph will have been prototyped and cryogenically tested. The lessons learned from the engineering model will then be fed back into the overall design of the spectrograph modules ahead of their development.

This paper is a report from a recent meeting on "the Future of high-resolution imaging in the visible and infrared", reviewing the astronomical drivers for development and the technological advances that might boost performance. Each of the authors listed contributed a section themselves., 6 pages, 7 figures, 11 contributors, Accepted for publication in Astronomy & Geophysics of the RAS, June 2019 issue

Quantitative susceptibility mapping (QSM) reveals pathological changes in widespread diseases such as Parkinson’s disease, Multiple Sclerosis, or hepatic iron overload. QSM requires multiple processing steps after the acquisition of magnetic resonance imaging (MRI) phase measurements such as unwrapping, background field removal and the solution of an ill-posed field-to-source-inversion. Current techniques utilize iterative optimization procedures to solve the inversion and background field correction, which are computationally expensive and lead to suboptimal or over-regularized solutions requiring a careful choice of parameters that make a clinical application of QSM challenging. We have previously demonstrated that a deep convolutional neural network can invert the magnetic dipole kernel with a very efficient feed forward multiplication not requiring iterative optimization or the choice of regularization parameters. In this work, we extended this approach to remove background fields in QSM. The prototype method, called SHARQnet, was trained on simulated background fields and tested on 3T and 7T brain datasets. We show that SHARQnet outperforms current background field removal procedures and generalizes to a wide range of input data without requiring any parameter adjustments. In summary, we demonstrate that the solution of ill-posed problems in QSM can be achieved by learning the underlying physics causing the artifacts and removing them in an efficient and reliable manner and thereby will help to bring QSM towards clinical applications.