Characterisation and statistical analysis of breakdown data for a corona-stabilised switch in environmentally-friendly gas mixtures

Characterisation of a corona-stabilised switch in the single-shot regime, including triggering range, delay times and jitter is reported, over the pressure range 0-3 bar gauge, as a continuation of work from similar characterisation with this switch filled with SF6 with different gap spacings. When filled with mixtures of HFO-1234ze and N2, the breakdown voltage can be increased by up to ~306% and ~191% under negative and positive polarity, respectively, of that using 100% N2. These results were achieved with gas mixtures consisting of 80% N2 and 20% HFO-1234ze, by pressure. The maximum negative polarity triggering range was 13.6 kV, comparable to that achieved previously using SF6. The measured delay time and calculated jitter was generally found to increase with increasing pressure, and with increasing percentage (from 5% to 20%) of HFO-1234ze in the gas mixtures. Von Laue statistical analysis of time-to-breakdown data showed that both the formative time and statistical time increased with increasing pressure, and with increasing percentage of HFO-1234ze in the gas mixtures. The formative time under negative polarity was significantly longer than that for positive polarity. The results indicate that HFO-1234ze may be considered as a suitable candidate to replace SF6 for switching applications, although there are some operational observations that require further investigation

An analysis of screen-detected invasive cancers by grade in the English breast cancer screening programme: are we failing to detect sufficient small grade 3 cancers?

Abstract: Objective: Randomised controlled trials have shown a reduction in breast cancer mortality from mammography screening and it is the detection of high-grade invasive cancers that is responsible for much of this effect. We determined the detection rates of invasive cancers by grade, size and type of screen and estimated relative sensitivities with emphasis on grade 3 detection. Methods: This observational study analysed data from over 11 million screening episodes (67,681 invasive cancers) from the English NHS breast screening programme over seven screening years 2009/2010 to 2015/2016 for women aged 45–70. Results: At prevalent (first) screens (which are unaffected by screening interval), the detection rate of small (< 15 mm) invasive cancers was 0.95 per 1000 for grade 1, but for grade 3 only 0.30 per 1000. The ratio of small (< 15 mm) to large (≥ 15 mm) cancers was 1.8:1 for grade 1 but reversed to 0.5:1 for grade 3. We estimated that the relative sensitivity for grade 3 invasive cancers was 52% of that for grade 1 and the relative sensitivity for small (< 15 mm) grade 3 only 26% of that for small (< 15 mm) grade 1 invasive cancers. Conclusions: Sensitivity for small grade 3 invasive cancers is poor compared with that for grade 1 and 2 invasive cancers and larger grade 3 malignancies. This observation is likely a limitation of the current technology related to the absence of identifiable mammographic features for small high-grade cancers. Future work should focus on technologies and strategies to improve detection of these clinically most significant cancers. Key Points: • The detection of small high-grade invasive cancers is vital to reduce breast cancer mortality. • We estimate the sensitivity for small grade 3 invasive cancers may be only 26% of that of small grade 1 invasive cancers. This is likely to be associated with the non-specific mammographic features for these cancers. • New technologies and appropriate strategies using current technology are required to maximise the detection of small grade 3 invasive cancers

The Serums Tool-Chain:Ensuring Security and Privacy of Medical Data in Smart Patient-Centric Healthcare Systems

Digital technology is permeating all aspects of human society and life. This leads to humans becoming highly dependent on digital devices, including upon digital: assistance, intelligence, and decisions. A major concern of this digital dependence is the lack of human oversight or intervention in many of the ways humans use this technology. This dependence and reliance on digital technology raises concerns in how humans trust such systems, and how to ensure digital technology behaves appropriately. This works considers recent developments and projects that combine digital technology and artificial intelligence with human society. The focus is on critical scenarios where failure of digital technology can lead to significant harm or even death. We explore how to build trust for users of digital technology in such scenarios and considering many different challenges for digital technology. The approaches applied and proposed here address user trust along many dimensions and aim to build collaborative and empowering use of digital technologies in critical aspects of human society

Statistical analysis of impulsive flashover voltages across solid-air interfaces

Within the pulsed power industry, a key factor determining the achievable output voltage of a HV system is the flashover voltage of the insulating parts. Statistical analysis of the breakdown voltages associated with solid-gas interfaces can reveal useful information to aid system designers in the selection of solid materials. However, it is important to test the applicability of the distribution being applied, to ensure that the fitting parameters obtained are truly representative of the distribution of the data. Normal, lognormal, 2-parameter Weibull and 3-parameter Weibull cumulative distribution functions (CDF) were plotted, to enable extraction of the specific fitting parameters associated with each distribution. The CDF for each statistical method has been plotted alongside the empirical cumulative distribution function (ECDF), found from the flashover voltages recorded during experimental testing. The distribution of best fit was then analysed by using the Kolmogorov-Smirnov (K-S) test, in order to determine the CDF that best represented the ECDF. Maximum values have been compared to the α = 0.05, K-S critical value, in order to reject or accept the null hypothesis based on how the data fits the specified distributions. This will facilitate a comparison between different statistical distributions, applied to experimental data on breakdown/flashover voltages of gas-solid interfaces, generated at a fixed pressure, and different levels of R

The effect of relative humidity on the flashover strength of solid insulation

This paper informs on the flashover strength of 3 materials: Delrin (Polyoxymethylene), HDPE (High Density Polyethylene) and Ultem (Polyetherimide) with 'smooth' and 'knurled' surface finishes, in zero-grade air at -0.5, 0 and 0.5 bar gauge, and at 90% relative humidity (RH). All tests were completed using a 10-stage Marx generator, producing HV impulses with a nominal 100/700 ns waveshape. Each test conformed with the ASTM D3426-97 standard of 'step up' testing, to find the average flashover voltage for each set of conditions. The electrode system with each dielectric material demonstrated a decrease in breakdown voltage as the RH was increased. In high humidity environments, the knurled surface finish was seen to have a positive effect on the flashover strength of Delrin and Ultem samples, compared to a smooth, machined surface. Increasing pressure yielded an increase in the flashover strength also. For samples with a smooth surface finish, a decrease in flashover strength was found as the permittivity of the material increased, irrespective of humidity and pressure. However, a knurled surface finish had a much more erratic effect on flashover strength, with no discernible trend with increasing material permittivit

Effect of surface deviation of solid insulation on impulsive flashover voltages under varying environmental conditions

In pulsed power engineering, the modification of dielectric surfaces is a potential method in order to increase the flashover strength of solid insulation. In this work, dielectric materials are subjected to a knurled finish, where small indentations are machined on to the surface resulting in quick consistent modification. These flashover voltages from the knurled dielectric spacers have been compared to spacers with a ‘smooth’ machined finish. The three materials which have been tested are HDPE (High Density Polyethylene), Delrin (Polyoxymethylene) and Ultem (Polyetherimide). The materials were tested under a 100/700 ns impulse voltage. Cylindrical spacers made of these materials were located in the center of a parallel-plane electrode setup in air, which provided a quasi-uniform field distribution. Breakdown tests published in this work were performed in a sealed container at air pressures of −0.5, 0 and 0.5 bar gauge, with relative humidity levels of 90% RH

CAD in mammography: lesion-level versus case-level analysis of the effects of prompts on human decisions

Object: To understand decision processes in CAD-supported breast screening by analysing how prompts affect readers’ judgements of individual mammographic features (lesions). To this end we analysed hitherto unexamined details of reports completed by mammogram readers in an earlier evaluation of a CAD tool. Material and methods: Assessments of lesions were extracted from 5,839 reports for 59 cancer cases. Statistical analyses of these data focused on what features readers considered when recalling a cancer case and how readers reacted to CAD prompts. Results: About 13.5% of recall decisions were found to be caused by responses to features other than those indicating actual cancer. Effects of CAD: lesions were more likely to be examined if prompted; the presence of a prompt on a cancer increased the probability of both detection and recall especially for less accurate readers in subtler cases; lack of prompts made cancer features less likely to be detected; false prompts made non-cancer features more likely to be classified as cancer. Conclusion: The apparent lack of impact reported for CAD in some studies is plausibly due to CAD systematically affecting readers’ identification of individual features, in a beneficial way for certain combinations of readers and features and a damaging way for others. Mammogram readers do not ignore prompts. Methodologically, assessing CAD by numbers of recalled cancer cases may be misleading

Target Product Profile for a Machine Learning–Automated Retinal Imaging Analysis Software for Use in English Diabetic Eye Screening: Protocol for a Mixed Methods Study

\ua9 2024 JMIR Publications Inc.. All rights reserved.Background: Diabetic eye screening (DES) represents a significant opportunity for the application of machine learning (ML) technologies, which may improve clinical and service outcomes. However, successful integration of ML into DES requires careful product development, evaluation, and implementation. Target product profiles (TPPs) summarize the requirements necessary for successful implementation so these can guide product development and evaluation. Objective: This study aims to produce a TPP for an ML-automated retinal imaging analysis software (ML-ARIAS) system for use in DES in England. Methods: This work will consist of 3 phases. Phase 1 will establish the characteristics to be addressed in the TPP. A list of candidate characteristics will be generated from the following sources: an overview of systematic reviews of diagnostic test TPPs; a systematic review of digital health TPPs; and the National Institute for Health and Care Excellence’s Evidence Standards Framework for Digital Health Technologies. The list of characteristics will be refined and validated by a study advisory group (SAG) made up of representatives from key stakeholders in DES. This includes people with diabetes; health care professionals; health care managers and leaders; and regulators and policy makers. In phase 2, specifications for these characteristics will be drafted following a series of semistructured interviews with participants from these stakeholder groups. Data collected from these interviews will be analyzed using the shortlist of characteristics as a framework, after which specifications will be drafted to create a draft TPP. Following approval by the SAG, in phase 3, the draft will enter an internet-based Delphi consensus study with participants sought from the groups previously identified, as well as ML-ARIAS developers, to ensure feasibility. Participants will be invited to score characteristic and specification pairs on a scale from “definitely exclude” to “definitely include,” and suggest edits. The document will be iterated between rounds based on participants’ feedback. Feedback on the draft document will be sought from a group of ML-ARIAS developers before its final contents are agreed upon in an in-person consensus meeting. At this meeting, representatives from the stakeholder groups previously identified (minus ML-ARIAS developers, to avoid bias) will be presented with the Delphi results and feedback of the user group and asked to agree on the final contents by vote. Results: Phase 1 was completed in November 2023. Phase 2 is underway and expected to finish in March 2024. Phase 3 is expected to be complete in July 2024. Conclusions: The multistakeholder development of a TPP for an ML-ARIAS for use in DES in England will help developers produce tools that serve the needs of patients, health care providers, and their staff. The TPP development process will also provide methods and a template to produce similar documents in other disease areas