Evaluation of flux expulsion and flux trapping sensitivity of srf cavities fabricated from cold work Nb sheet with successive heat treatment

The main source of RF losses leading to lower quality factor of superconducting radio-frequency cavities is due to the residual magnetic flux trapped during cool-down. The loss due to flux trapping is more pronounced for cavities subjected to impurities doping. The flux trapping and its sensitivity to rf losses are related to several intrinsic and extrinsic phenomena. To elucidate the effect of re-crystallization by high temperature heat treatment on the flux trapping sensitivity, we have fabricated two 1.3 GHz single cell cavities from cold-worked Nb sheets and compared with cavities made from standard fine-grain Nb. Flux expulsion ratio and flux trapping sensitivity were measured after successive high temperature heat treatments. The cavity made from cold worked Nb showed better flux expulsion after 800 C/3h heat treatments and similar behavior when heat treated with additional 900 C/3h and 1000 C/3h. In this contribution, we present the summary of flux expulsion, trapping sensitivity, and RF results.Comment: 21st International Conference on Radio-Frequency Superconductivity (SRF 2023

Quench Detection in a Superconducting Radio Frequency Cavity with Combine Temperature and Magnetic Field Mapping

Local dissipation of RF power in superconducting radio frequency cavities create so called hot spots, primary precursors of cavity quench driven by either thermal or magnetic instability. These hot spots are detected by a temperature mapping system, and a large increase in temperature on the outer surface is detected during cavity quench events. Here, we have used combined magnetic and temperature mapping systems using anisotropic magnetoresistance (AMR) sensors and carbon resisters to locate the hot spots and areas with high trapped flux on a 3.0 GHz single-cell Nb cavity during the RF tests at 2.0 K. The quench location and hot spots were detected near the equator when the residual magnetic field in the Dewar is kept < 1 mG. The hot spots and quench locations moved when the magnetic field is trapped locally, as detected by T-mapping system. No significant dynamics of trapped flux is detected by AMR sensors, however, change in magnetic flux during cavity quench is detected by a flux gate magnetometer, close to the quench location. The result provides the direct evidence of hot spots and quench events due to localized trapped vortices.Comment: 21st International Conference on Radio-Frequency Superconductivity (SRF 2023

Electrodynamics in Friedmann-Robertson-Walker Universe: Maxwell and Dirac fields in Newman-Penrose formalism

Maxwell and Dirac fields in Friedmann-Robertson-Walker spacetime is investigated using the Newman-Penrose method. The variables are all separable, with the angular dependence given by the spin-weighted spherical harmonics. All the radial parts reduce to the barrier penetration problem, with mostly repulsive potentials representing the centrifugal energies. Both the helicity states of the photon field see the same potential, but that of the Dirac field see different ones; one component even sees attractive potential in the open universe. The massless fields have the usual exponential time dependencies; that of the massive Dirac field is coupled to the evolution of the cosmic scale factor $a$. The case of the radiation filled flat universe is solved in terms of the Whittaker function. A formal series solution, valid in any FRW universe, is also presented. The energy density of the Maxwell field is explicitly shown to scale as $a^{-4}$. The co-moving particle number density of the massless Dirac field is found to be conserved, but that of the massive one is not. Particles flow out of certain regions, and into others, creating regions that are depleted of certain linear and angular momenta states, and others with excess. Such current of charged particles would constitute an electric current that could generate a cosmic magnetic field. In contrast, the energy density of these massive particles still scales as $a^{-4}$.Comment: 18 pages including 9 figure

Quantifying the Pressure-dependence of Work of Adhesion in Silicon-Diamond Contacts

Continuum mechanics models for contacting surfaces assume a constant interfacial energy, or work of adhesion, between materials. Recent studies have challenged this assumption, instead demonstrating that stress-dependent chemical reactions across the interface modify the work of adhesion. Here, we perform 77 adhesion tests on diamond-silicon contacts using in situ TEM and atomistic simulations to quantify how the adhesion changes as a function of applied pressure. The results show a 7-fold increase in work of adhesion (from approximately 1 to 7 J/m2) with an increase in mean applied pressure from 0 to 11 GPa, where the most significant increase occurs above 5 GPa. We rule out alternative explanations for the changing work of adhesion, such as electron-beam artifacts, bulk shape change by inelastic deformation, and time-dependent processes such as creep. Therefore, these results confirm the presence of stress-driven chemical reactions in the contact and quantify the resulting change in adhesion of these materials with applied pressure

Confident head circumference measurement from ultrasound with real-time feedback for sonographers

Manual estimation of fetal Head Circumference (HC) from Ultrasound (US) is a key biometric for monitoring the healthy development of fetuses. Unfortunately, such measurements are subject to large inter-observer variability, resulting in low early-detection rates of fetal abnormalities. To address this issue, we propose a novel probabilistic Deep Learning approach for real-time automated estimation of fetal HC. This system feeds back statistics on measurement robustness to inform users how confident a deep neural network is in evaluating suitable views acquired during free-hand ultrasound examination. In real-time scenarios, this approach may be exploited to guide operators to scan planes that are as close as possible to the underlying distribution of training images, for the purpose of improving inter-operator consistency. We train on freehand ultrasound data from over 2000 subjects (2848 training/540 test) and show that our method is able to predict HC measurements within 1.81±1.65 mm deviation from the ground truth, with 50% of the test images fully contained within the predicted confidence margins, and an average of 1.82±1.78 mm deviation from the margin for the remaining cases that are not fully contained

Participatory research approaches rapidly improve household food security in Nepal and identify policy changes required for institutionalisation

The introduction, testing, promotion and release of a rice variety, BG 1442, in Nepal were examined in relation to existing policies governing these procedures and to how more participatory approaches could benefit food security. From 1998 to 2006, participatory varietal selection (PVS) was used to test BG 1442 and other candidate rice varieties in the spring (Chaite) rice-growing season (February to June) and in the main season (June to November). The testing of BG 1442 commenced 11 years after it was first introduced into Nepal in 1987 by the national rice research programme (NRRP). Following its initial acceptance by farmers, it was widely disseminated from 1998 by non-governmental organisations (NGOs) in the low altitude region of Nepal called the terai in projects funded by the Department for International Development (DFID), UK. This dissemination was done using a method termed informal research and development (IRD) where many small packets of seed were distributed without fertiliser or pesticides, the only additional input being a description of varietal characteristics on an enclosed leaflet. From 2001 to 2008, various assessments were made of its extent of adoption and its impact on livelihoods. In a randomised survey of households in 10 districts, BG 1442 increased from not being used at all in 1997 to being grown by about 20% of the surveyed rice farmers by 2008. It was grown both in the Chaite and the main season and was well adapted to the rainfed-upland and medium-land rice ecosystems. The variety was grown from the far west to the far east of low-altitude Nepal by resource-poor farmers. IRD was important in accelerating adoption and improving food security as it was by far the most important external source of seed for farmers. Prior to the adoption of BG 1442, farmers who did not harvest sufficient rice to last their households for 12 months increased rice self sufficiency by over 2 months (25% more). Those households that sold surplus grain and who grew BG 1442 increased grain sales by 600 kg (25% more) in the Chaite season and by 370 kg (24% more) from main season cultivation

Complex-valued Burgers and KdV-Burgers equations

Spatially periodic complex-valued solutions of the Burgers and KdV-Burgers equations are studied in this paper. It is shown that for any sufficiently large time T, there exists an explicit initial data such that its corresponding solution of the Burgers equation blows up at T. In addition, the global convergence and regularity of series solutions is established for initial data satisfying mild conditions

A Method for Quantitative Real-Time Evaluation of Measurement Reliability When Using Atomic Force Microscopy-Based Metrology

In atomic force microscopy (AFM) and metrology, it is known that the radius of the scanning tip affects the accuracy of the measurement. However, most techniques for ascertaining tip radius require interruption of the measurement technique to insert a reference standard or to otherwise image the tip. Here we propose an inline technique based on analysis of the power spectral density (PSD) of the topography that is being collected during measurement. By identifying and quantifying artifacts that are known to arise in the power spectrum due to tip blunting, the PSD itself can be used to determine progressive shifts in the radius of the tip. Specifically, using AFM images of an ultrananocrystalline diamond, various trends in measured PSD are demonstrated. First, using more than 200 different measurements of the same material, the variability in the measured PSD is demonstrated. Second, using progressive scans under the same conditions, a systematic shifting of the mid-to-high-frequency data is visible. Third, using three different PSDs, the changes in radii between them were quantitatively determined and compared to transmission electron microscopy (TEM) images of the tips taken immediately after use. The fractional changes in tip radii were detected; the absolute values of the tip radii could be matched between the two techniques, but only with careful selection of a fitting constant. Further work is required to determine the generalizability of the value of this constant. Overall, the proposed approach represents a step towards quantitative and inline determination of the radius of the scanning tip and thus of the reliability of AFM-based measurements

Standard plane detection in 3D fetal ultrasound using an iterative transformation network

Standard scan plane detection in fetal brain ultrasound (US) forms a crucial step in the assessment of fetal development. In clinical settings, this is done by manually manoeuvring a 2D probe to the desired scan plane. With the advent of 3D US, the entire fetal brain volume containing these standard planes can be easily acquired. However, manual standard plane identification in 3D volume is labour-intensive and requires expert knowledge of fetal anatomy. We propose a new Iterative Transformation Network (ITN) for the automatic detection of standard planes in 3D volumes. ITN uses a convolutional neural network to learn the relationship between a 2D plane image and the transformation parameters required to move that plane towards the location/orientation of the standard plane in the 3D volume. During inference, the current plane image is passed iteratively to the network until it converges to the standard plane location. We explore the effect of using different transformation representations as regression outputs of ITN. Under a multi-task learning framework, we introduce additional classification probability outputs to the network to act as confidence measures for the regressed transformation parameters in order to further improve the localisation accuracy. When evaluated on 72 US volumes of fetal brain, our method achieves an error of 3.83mm/12.7 degrees and 3.80mm/12.6 degrees for the transventricular and transcerebellar planes respectively and takes 0.46s per plane

Fast multiple landmark localisation using a patch-based iterative network

We propose a new Patch-based Iterative Network (PIN) for fast and accurate landmark localisation in 3D medical volumes. PIN utilises a Convolutional Neural Network (CNN) to learn the spatial relationship between an image patch and anatomical landmark positions. During inference, patches are repeatedly passed to the CNN until the estimated landmark position converges to the true landmark location. PIN is computationally efficient since the inference stage only selectively samples a small number of patches in an iterative fashion rather than a dense sampling at every location in the volume. Our approach adopts a multi-task learning framework that combines regression and classification to improve localisation accuracy. We extend PIN to localise multiple landmarks by using principal component analysis, which models the global anatomical relationships between landmarks. We have evaluated PIN using 72 3D ultrasound images from fetal screening examinations. PIN achieves quantitatively an average landmark localisation error of 5.59mm and a runtime of 0.44s to predict 10 landmarks per volume. Qualitatively, anatomical 2D standard scan planes derived from the predicted landmark locations are visually similar to the clinical ground truth