Charting the low-loss region in Electron Energy Loss Spectroscopy with machine learning

Exploiting the information provided by electron energy-loss spectroscopy (EELS) requires reliable access to the low-loss region where the zero-loss peak (ZLP) often overwhelms the contributions associated to inelastic scatterings off the specimen. Here we deploy machine learning techniques developed in particle physics to realise a model-independent, multidimensional determination of the ZLP with a faithful uncertainty estimate. This novel method is then applied to subtract the ZLP for EEL spectra acquired in flower-like WS$_2$ nanostructures characterised by a 2H/3R mixed polytypism. From the resulting subtracted spectra we determine the nature and value of the bandgap of polytypic WS$_2$, finding $E_{\rm BG} = 1.6_{-0.2}^{+0.3}\,{\rm eV}$ with a clear preference for an indirect bandgap. Further, we demonstrate how this method enables us to robustly identify excitonic transitions down to very small energy losses. Our approach has been implemented and made available in an open source Python package dubbed EELSfitter.Comment: 37 pages, 14 figures. The EELSfitter code is available from https://github.com/LHCfitNikhef/EELSfitte

Charting the low-loss region in Electron Energy Loss Spectroscopy with machine learning

Exploiting the information provided by electron energy-loss spectroscopy (EELS) requires reliable access to the low-loss region where the zero-loss peak (ZLP) often overwhelms the contributions associated to inelastic scatterings off the specimen. Here we deploy machine learning techniques developed in particle physics to realise a model-independent, multidimensional determination of the ZLP with a faithful uncertainty estimate. This novel method is then applied to subtract the ZLP for EEL spectra acquired in flower-like WS$_2$ nanostructures characterised by a 2H/3R mixed polytypism. From the resulting subtracted spectra we determine the nature and value of the bandgap of polytypic WS$_2$, finding $E_{\rm BG} = 1.6_{-0.2}^{+0.3}\,{\rm eV}$ with a clear preference for an indirect bandgap. Further, we demonstrate how this method enables us to robustly identify excitonic transitions down to very small energy losses. Our approach has been implemented and made available in an open source Python package dubbed EELSfitter

The association of kidney function and cognitive decline in older patients at risk of cardiovascular disease: a longitudinal data analysis

Background: Chronic kidney disease (CKD) has been identified as a significant direct marker for cognitive decline, but controversy exists regarding the magnitude of the association of kidney function with cognitive decline across the different CKD stages. Therefore, the aim of this study was to investigate the association of kidney function with cognitive decline in older patients at high risk of cardiovascular disease, using data from the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER). Methods Data of 5796 patients of PROSPER were used. Strata were made according to clinical stages of CKD based on estimated glomerular filtration rate; < 30 ml/min/1.73m2 (stage 4), 30-45 ml/min/1.73m2 (stage 3b), 45-60 ml/min/1.73m2 (stage 3a) and ≥ 60 ml/min/1.73m2 (stage 1–2). Cognitive function and functional status was assessed at six different time points and means were compared at baseline and over time, adjusted for multiple prespecified variables. Stratified analyses for history of vascular disease were executed. Results: Mean age was 75.3 years and 48.3% participants were male. Mean follow-up was 3.2 years. For all cognitive function tests CKD stage 4 compared to the other stages had the worst outcome at baseline and a trend for faster cognitive decline over time. When comparing stage 4 versus stage 1–2 over time the estimates (95% CI) were 2.23 (0.60–3.85; p = 0.009) for the Stroop-Colour-Word test, − 0.33 (− 0.66–0.001; p = 0.051) for the Letter-Digit-Coding test, 0.08 (− 0.06–0.21; p = 0.275) for the Picture-Word-Learning test with immediate recall and − 0.07 (− 0.02–0.05; p = 0.509) for delayed recall. This association was most present in patients with a history of vascular disease. No differences were found in functional status. Conclusion: In older people with vascular burden, only severe kidney disease (CKD stage 4), but not mild to modest kidney disease (CKD stage 3a and b), seem to be associated with cognitive impairment at baseline and cognitive decline over time. The association of severe kidney failure with cognitive impairment and decline over time was more outspoken in patients with a history of vascular disease, possibly due to a higher probability of polyvascular damage, in both kidney and brain, in patients with proven cardiovascular disease

Entropy Generation In The Viscous Layer Of A Turbulent Channel Flow

The local (pointwise) entropy generation rate per unit volume S''' is a key to improving many energy processes and applications. Entropy generation due to friction occurs from viscous dissipation of mean-flow kinetic energy (called "direct dissipation") and dissipation of turbulent kinetic energy into thermal energy ("indirect" or turbulent dissipation). The objective of the present study is to compare two approaches for the prediction of S''' for the viscous layer in near asymptotic (high Reynolds number) turbulent flows. By employing available direct numerical simulations (DNS) it was found that about two-thirds of the entropy generation occurs in this layer. A popular approximate approach does not agree with the result from the more exact evaluation of S''' but its integral falls within about four per cent at the edge of the viscous layer

The evolution of precision oncology:The ongoing impact of the Drug Rediscovery Protocol (DRUP)

Background and purpose: The Drug Rediscovery Protocol (DRUP) is a Dutch, pan-cancer, nonrandomized clinical trial that aims to investigate the efficacy and safety of targeted and immunotherapies outside their registered indication in patients with advanced or metastatic cancer. Patients: Patients with advanced or metastatic cancer are eligible when there are no standard of care treatment options left and the tumor possesses a molecular genomic variant for which commercially available anticancer treatment is accessible off-label in DRUP. Clinical benefit is the study’s primary endpoint, characterized by a confirmed objective response or stable disease after at least 16 weeks of treatment. Results: More than 2,500 patients have undergone evaluation, of which over 1,500 have started treatment in DRUP. The overall clinical benefit rate (CBR) remains 33%. The nivolumab cohort for patients with microsatellite instable metastatic tumors proved highly successful with a CBR of 63%, while palbociclib or ribociclib in patients with tumors harboring CDK4/6 pathway alterations showed limited efficacy, with a CBR of 15%. The formation of two European initiatives (PCM4EU and PRIME-ROSE) strives to accelerate implementation and enhance data collection to broaden equitable access to anticancer treatments and gather more evidence. Conclusion: DRUP persists in improving patients access to off-label targeted or immunotherapy in the Netherlands and beyond. The expansion of DRUP-like clinical trials across Europe provides countless opportunities for broadening the horizon of precision oncology.</p

The evolution of precision oncology:The ongoing impact of the Drug Rediscovery Protocol (DRUP)

Background and purpose: The Drug Rediscovery Protocol (DRUP) is a Dutch, pan-cancer, nonrandomized clinical trial that aims to investigate the efficacy and safety of targeted and immunotherapies outside their registered indication in patients with advanced or metastatic cancer. Patients: Patients with advanced or metastatic cancer are eligible when there are no standard of care treatment options left and the tumor possesses a molecular genomic variant for which commercially available anticancer treatment is accessible off-label in DRUP. Clinical benefit is the study’s primary endpoint, characterized by a confirmed objective response or stable disease after at least 16 weeks of treatment. Results: More than 2,500 patients have undergone evaluation, of which over 1,500 have started treatment in DRUP. The overall clinical benefit rate (CBR) remains 33%. The nivolumab cohort for patients with microsatellite instable metastatic tumors proved highly successful with a CBR of 63%, while palbociclib or ribociclib in patients with tumors harboring CDK4/6 pathway alterations showed limited efficacy, with a CBR of 15%. The formation of two European initiatives (PCM4EU and PRIME-ROSE) strives to accelerate implementation and enhance data collection to broaden equitable access to anticancer treatments and gather more evidence. Conclusion: DRUP persists in improving patients access to off-label targeted or immunotherapy in the Netherlands and beyond. The expansion of DRUP-like clinical trials across Europe provides countless opportunities for broadening the horizon of precision oncology.</p

Alirocumab in Patients With Polyvascular Disease and Recent Acute Coronary Syndrome : ODYSSEY OUTCOMES Trial

Patients with acute coronary syndrome (ACS) and concomitant noncoronary atherosclerosis have a high risk of major adverse cardiovascular events (MACEs) and death. The impact of lipid lowering by proprotein convertase subtilisin-kexin type 9 inhibition in such patients is undetermined.This pre-specified analysis from ODYSSEY OUTCOMES (Evaluation of Cardiovascular Outcomes After an Acute Coronary Syndrome During Treatment With Alirocumab) determined whether polyvascular disease influenced risks of MACEs and death and their modification by alirocumab in patients with recent ACS and dyslipidemia despite intensive statin therapy.Patients were randomized to alirocumab or placebo 1 to 12 months after ACS. The primary MACEs endpoint was the composite of coronary heart disease death, nonfatal myocardial infarction, fatal or nonfatal ischemic stroke, or unstable angina requiring hospitalization. All-cause death was a secondary endpoint.Median follow-up was 2.8 years. Of 18,924 patients, 17,370 had monovascular (coronary) disease, 1,405 had polyvascular disease in 2 beds (coronary and peripheral artery or cerebrovascular), and 149 had polyvascular disease in 3 beds (coronary, peripheral artery, cerebrovascular). With placebo, the incidence of MACEs by respective vascular categories was 10.0%, 22.2%, and 39.7%. With alirocumab, the corresponding absolute risk reduction was 1.4% (95% confidence interval [CI]: 0.6% to 2.3%), 1.9% (95% CI: -2.4% to 6.2%), and 13.0% (95% CI: -2.0% to 28.0%). With placebo, the incidence of death by respective vascular categories was 3.5%, 10.0%, and 21.8%; the absolute risk reduction with alirocumab was 0.4% (95% CI: -0.1% to 1.0%), 1.3% (95% CI: -1.8% to 4.3%), and 16.2% (95% CI: 5.5% to 26.8%).In patients with recent ACS and dyslipidemia despite intensive statin therapy, polyvascular disease is associated with high risks of MACEs and death. The large absolute reductions in those risks with alirocumab are a potential benefit for these patients. (Evaluation of Cardiovascular Outcomes After an Acute Coronary Syndrome During Treatment With Alirocumab [ODYSSEY OUTCOMES]: NCT01663402)

Lessons Learned from Measuring Flood Resilience

The Zurich Flood Resilience Alliance (ZFRA) has identified the measurement of resilience as a valuable ingredient in building community flood resilience. Measuring resilience is particularly challenging because it is an invisible or latent characteristic of a community until a flood occurs. The Flood Resilience Measurement for Communities (FRMC) framework measures “sources of resilience” before a flood happens and looks at the post-flood impacts afterwards. The FRMC is built around the notion of five types of capital (the 5Cs: human, social, physical, natural, and financial capital) and the 4Rs of a resilient system (robustness, redundancy, resourcefulness, and rapidity). The sources of resilience are graded based on Zurich’s Risk Engineering Technical Grading Standard. Results are displayed according to the 5Cs and 4Rs, the disaster risk management (DRM) cycle, themes and context level, to give the approach further flexibility and accessibility. In the first application phase (2013-2018), we measured flood resilience in 118 communities across nine countries, building on responses at household and community levels. Continuing this endeavor in Phase II (2018 – 2023) will allow us to enrich the understanding of community flood resilience and to extend this unique data set. We find that at the community level, the FRMC enables users to track community progress on resilience over time in a standardized way. It thus provides vital information for the decision-making process in terms of prioritizing the resilience-building measures most needed by the community. At community and higher decision-making levels, measuring resilience also provides a basis for improving the design of innovative investment programs to strengthen disaster resilience. By exploring data across multiple communities (facing different flood types and with very different socioeconomic and political contexts), we can generate evidence with respect to which characteristics contribute most to community disaster resilience before an event strikes. This contributes to meeting the challenge of demonstrating that the work we do has the desired impact – that it actually builds resilience. No general measurement framework for disaster resilience has been empirically verified yet , but the FRMC framework has been developed to eventually generate the data needed to demonstrate empirically which ex-ante measures are most effective for communities. Our findings suggest that stronger interactions between community functions induce co-benefits among the five capitals, thus providing evidence for a virtuous cycle type effect where higher resilient capacity in one capital fosters the community’s capacity for resilience in other capitals