152 research outputs found

    Computer vision for understanding catalyst degradation kinetics

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    We report a computer vision strategy for the extraction and colorimetric analysis of catalyst degradation and product formation kinetics from video footage. The degradation of palladium(II) pre-catalyst systems to form 'Pd black' is investigated as a widely relevant case study for catalysis and materials chemistries. Beyond the study of catalysts in isolation, investigation of Pd-catalyzed Miyaura borylation reactions revealed informative correlations between colour parameters (most notably ΔE, a colour-agnostic measure of contrast change) and the concentration of product measured by off-line analysis (NMR and LC-MS). The breakdown of such correlations helped inform conditions under which reaction vessels were compromised by air ingress. These findings present opportunities to expand the toolbox of non-invasive analytical techniques, operationally cheaper and simpler to implement than common spectroscopic methods. The approach introduces the capability of analyzing the macroscopic 'bulk' for the study of reaction kinetics in complex mixtures, in complement to the more common study of microscopic and molecular specifics

    ACL reconstruction with unicondylar replacement in knee with functional instability and osteoarthritis

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    Severe symptomatic osteoarthritis in young and active patients with pre-existing deficiency of the anterior cruciate ligament and severe functionally instability is a difficult subgroup to manage. There is considerable debate regarding management of young patients with isolated unicompartment osteoarthritis and concomitant ACL deficiency. A retrospective analysis of was done in 9 patients with symptomatic osteoarthritis with ACL deficiencies and functional instability that were treated with unicompartment knee arthroplasty and ACL reconstruction between April 2002 and June 2005. The average arc of flexion was 119° (range 85° to 135°) preoperatively and 125° (range 105° to 140°). There were no signs of instability during the follow up of patients. No patients in this group were reoperated. In this small series we have shown that instability can be corrected and pain relieved by this combined procedure

    Radiological Decision Aid to determine suitability for medial unicompartmental knee arthroplasty: development and preliminary validation

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    Aims: An evidence-based radiographic Decision Aid for meniscal-bearing unicompartmental knee arthroplasty (UKA) has been developed and this study investigates its performance at an independent centre. Patients: and Methods Pre-operative radiographs, including stress views, from a consecutive cohort of 550 knees undergoing arthroplasty (UKA or total knee arthroplasty; TKA) by a single-surgeon were assessed. Suitability for UKA was determined using the Decision Aid, with the assessor blinded to treatment received, and compared with actual treatment received, which was determined by an experienced UKA surgeon based on history, examination, radiographic assessment including stress radiographs, and intra-operative assessment in line with the recommended indications as described in the literature. Results: The sensitivity and specificity of the Decision Aid was 92% and 88%, respectively. Excluding knees where a clear pre-operative plan was made to perform TKA, i.e. patient request, the sensitivity was 93% and specificity 96%. The false-positive rate was low (2.4%) with all affected patients readily identifiable during joint inspection at surgery. In patients meeting Decision Aid criteria and receiving UKA, the five-year survival was 99% (95% confidence intervals (CI) 97 to 100). The false negatives (3.5%), who received UKA but did not meet the criteria, had significantly worse functional outcomes (flexion p < 0.001, American Knee Society Score - Functional p < 0.001, University of California Los Angeles score p = 0.04), and lower implant survival of 93.1% (95% CI 77.6 to 100). Conclusion: The radiographic Decision Aid safely and reliably identifies appropriate patients for meniscal-bearing UKA and achieves good results in this population. The widespread use of the Decision Aid should improve the results of UKA

    Ultrafast terahertz-field-driven ionic response in ferroelectric BaTiO3

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    The dynamical processes associated with electric field manipulation of the polarization in a ferroelectric remain largely unknown but fundamentally determine the speed and functionality of ferroelectric materials and devices. Here we apply subpicosecond duration, single-cycle terahertz pulses as an ultrafast electric field bias to prototypical BaTiO[subscript 3] ferroelectric thin films with the atomic-scale response probed by femtosecond x-ray-scattering techniques. We show that electric fields applied perpendicular to the ferroelectric polarization drive large-amplitude displacements of the titanium atoms along the ferroelectric polarization axis, comparable to that of the built-in displacements associated with the intrinsic polarization and incoherent across unit cells. This effect is associated with a dynamic rotation of the ferroelectric polarization switching on and then off on picosecond time scales. These transient polarization modulations are followed by long-lived vibrational heating effects driven by resonant excitation of the ferroelectric soft mode, as reflected in changes in the c-axis tetragonality. The ultrafast structural characterization described here enables a direct comparison with first-principles-based molecular-dynamics simulations, with good agreement obtained

    Dutch women with a low birth weight have an increased risk of myocardial infarction later in life: a case control study

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    BACKGROUND: To investigate whether low birth weight increases the risk of myocardial infarction later in life in women. METHODS: Nationwide population-based case-control study. Patients and controls: 152 patients with a first myocardial infarction before the age of 50 years in the Netherlands. 568 control women who had not had a myocardial infarction stratified for age, calendar year of the index event, and area of residence. RESULTS: Birth weight in the patient group was significantly lower than in control women (3214 vs. 3370 gram, mean difference -156.3 gram (95%CI -9.5 to -303.1). The odds ratio for myocardial infarction, associated with a birth weight lower than 3000 gram (20(th )percentile in controls) compared to higher than 3000 gram was 1.7 (95%CI 1.1–2.7), while the odds ratio for myocardial infarction for children with a low birth weight (< 2000 g) compared to a birth weight ≥ 2000 g was 2.4 (95%CI 1.0 – 5.8). Both figures did not change after adjustment for putative confounders (age, education level, body mass index, waist-hip ratio, hypertension, diabetes, hypercholesterolemia, smoking, and family history of cardiovascular disease). CONCLUSIONS: Low birth weight is associated with an increased risk of myocardial infarction before age of 50 in Dutch women

    Transparency and Trust in Human-AI-Interaction: The Role of Model-Agnostic Explanations in Computer Vision-Based Decision Support

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    Computer Vision, and hence Artificial Intelligence-based extraction of information from images, has increasingly received attention over the last years, for instance in medical diagnostics. While the algorithms' complexity is a reason for their increased performance, it also leads to the "black box" problem, consequently decreasing trust towards AI. In this regard, "Explainable Artificial Intelligence" (XAI) allows to open that black box and to improve the degree of AI transparency. In this paper, we first discuss the theoretical impact of explainability on trust towards AI, followed by showcasing how the usage of XAI in a health-related setting can look like. More specifically, we show how XAI can be applied to understand why Computer Vision, based on deep learning, did or did not detect a disease (malaria) on image data (thin blood smear slide images). Furthermore, we investigate, how XAI can be used to compare the detection strategy of two different deep learning models often used for Computer Vision: Convolutional Neural Network and Multi-Layer Perceptron. Our empirical results show that i) the AI sometimes used questionable or irrelevant data features of an image to detect malaria (even if correctly predicted), and ii) that there may be significant discrepancies in how different deep learning models explain the same prediction. Our theoretical discussion highlights that XAI can support trust in Computer Vision systems, and AI systems in general, especially through an increased understandability and predictability

    Effective control of sars-cov-2 transmission between healthcare workers during a period of diminished community prevalence of covid-19

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    Previously, we showed that 3% (31/1032)of asymptomatic healthcare workers (HCWs) from a large teaching hospital in Cambridge, UK, tested positive for SARS-CoV-2 in April 2020. About 15% (26/169) HCWs with symptoms of coronavirus disease 2019 (COVID-19) also tested positive for SARS-CoV-2 (Rivett et al., 2020). Here, we show that the proportion of both asymptomatic and symptomatic HCWs testing positive for SARS-CoV-2 rapidly declined to nearzero between 25th April and 24th May 2020, corresponding to a decline in patient admissions with COVID-19 during the ongoing UK ‘lockdown’. These data demonstrate how infection prevention and control measures including staff testing may help prevent hospitals from becoming independent ‘hubs’ of SARS-CoV-2 transmission, and illustrate how, with appropriate precautions, organizations in other sectors may be able to resume on-site work safely

    Screening of healthcare workers for SARS-CoV-2 highlights the role of asymptomatic carriage in COVID-19 transmission

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    Significant differences exist in the availability of healthcare worker (HCW) SARS-CoV-2 testing between countries, and existing programmes focus on screening symptomatic rather than asymptomatic staff. Over a 3-week period (April 2020), 1,032 asymptomatic HCWs were screened for SARS-CoV-2 in a large UK teaching hospital. Symptomatic staff and symptomatic household contacts were additionally tested. Real-time RT-PCR was used to detect viral RNA from a throat+nose self-swab. 3% of HCWs in the asymptomatic screening group tested positive for SARS-CoV-2. 17/30 (57%) were truly asymptomatic/pauci-symptomatic. 12/30 (40%) had experienced symptoms compatible with coronavirus disease 2019 (COVID-19) &gt;7 days prior to testing, most self-isolating, returning well. Clusters of HCW infection were discovered on two independent wards. Viral genome sequencing showed that the majority of HCWs had the dominant lineage B·1. Our data demonstrates the utility of comprehensive screening of HCWs with minimal or no symptoms. This approach will be critical for protecting patients and hospital staff

    Longitudinal analysis reveals that delayed bystander CD8+ T cell activation and early immune pathology distinguish severe COVID-19 from mild disease

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    The kinetics of the immune changes in COVID-19 across severity groups have not been rigorously assessed. Using immunophenotyping, RNA sequencing, and serum cytokine analysis, we analyzed serial samples from 207 SARS-CoV2-infected individuals with a range of disease severities over 12 weeks from symptom onset. An early robust bystander CD8+ T cell immune response, without systemic inflammation, characterized asymptomatic or mild disease. Hospitalized individuals had delayed bystander responses and systemic inflammation that was already evident near symptom onset, indicating that immunopathology may be inevitable in some individuals. Viral load did not correlate with this early pathological response but did correlate with subsequent disease severity. Immune recovery is complex, with profound persistent cellular abnormalities in severe disease correlating with altered inflammatory responses, with signatures associated with increased oxidative phosphorylation replacing those driven by cytokines tumor necrosis factor (TNF) and interleukin (IL)-6. These late immunometabolic and immune defects may have clinical implications
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