Robustness of Generalized Learning Vector Quantization Models against Adversarial Attacks

Adversarial attacks and the development of (deep) neural networks robust against them are currently two widely researched topics. The robustness of Learning Vector Quantization (LVQ) models against adversarial attacks has however not yet been studied to the same extent. We therefore present an extensive evaluation of three LVQ models: Generalized LVQ, Generalized Matrix LVQ and Generalized Tangent LVQ. The evaluation suggests that both Generalized LVQ and Generalized Tangent LVQ have a high base robustness, on par with the current state-of-the-art in robust neural network methods. In contrast to this, Generalized Matrix LVQ shows a high susceptibility to adversarial attacks, scoring consistently behind all other models. Additionally, our numerical evaluation indicates that increasing the number of prototypes per class improves the robustness of the models.Comment: to be published in 13th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualizatio

On the creation and optical microstructure characterisation of additively manufactured foam structures (AMF)

Plastic-based additive manufacturing processes are becoming increasingly popular in the production of structural parts. Based on the idea of lightweight design and the aim of extending the functionality of additive structures, the production of additively manufactured foam structures has emerged as a new field of application. The optical characterisation of these structures is of particular importance for process adjustments and the identification of (unwanted) changes in the foam structure. The degree of foaming and the fineness of a foam structure are of interest at this point. In this context, only the part of a structure dominated by foam pores is considered a foam structure. So far, there are no sophisticated methods for such an optical characterisation. Therefore, in this work, microscope images of manufactured as well as artificially created additively manufactured foam structures were evaluated. On these images, the features porosity, pore size, pore amount and a measure for the textural change were determined in order to obtain information about changes within an additively manufactured foam structure. It is shown that additive structures show changing pore shapes depending on the orientation of the cutting plane, although there are no changes in the foaming behaviour. Therefore, caution is required when identifying changes within the foam structure. It was also found that, owing to the additive process, the total porosity is already set in the slicing process and remains constant even if the degree of foaming of individual tracks is changed. Therefore, the degree of foaming cannot be determined on the basis of the total porosity, but it can be assessed on the basis of the formation of large networks of process-related pores

On the Creation and Optical Microstructure Characterisation of Additively Manufactured Foam Structures (AMF)

Plastic-based additive manufacturing processes are becoming increasingly popular in the production of structural parts. Based on the idea of lightweight design and the aim of extending the functionality of additive structures, the production of additively manufactured foam structures has emerged as a new field of application. The optical characterisation of these structures is of particular importance for process adjustments and the identification of (unwanted) changes in the foam structure. The degree of foaming and the fineness of a foam structure are of interest at this point. In this context, only the part of a structure dominated by foam pores is considered a foam structure. So far, there are no sophisticated methods for such an optical characterisation. Therefore, in this work, microscope images of manufactured as well as artificially created additively manufactured foam structures were evaluated. On these images, the features porosity, pore size, pore amount and a measure for the textural change were determined in order to obtain information about changes within an additively manufactured foam structure. It is shown that additive structures show changing pore shapes depending on the orientation of the cutting plane, although there are no changes in the foaming behaviour. Therefore, caution is required when identifying changes within the foam structure. It was also found that, owing to the additive process, the total porosity is already set in the slicing process and remains constant even if the degree of foaming of individual tracks is changed. Therefore, the degree of foaming cannot be determined on the basis of the total porosity, but it can be assessed on the basis of the formation of large networks of process-related pores

Non-invasive Localization of the Ventricular Excitation Origin Without Patient-specific Geometries Using Deep Learning

Ventricular tachycardia (VT) can be one cause of sudden cardiac death affecting 4.25 million persons per year worldwide. A curative treatment is catheter ablation in order to inactivate the abnormally triggering regions. To facilitate and expedite the localization during the ablation procedure, we present two novel localization techniques based on convolutional neural networks (CNNs). In contrast to existing methods, e.g. using ECG imaging, our approaches were designed to be independent of the patient-specific geometries and directly applicable to surface ECG signals, while also delivering a binary transmural position. One method outputs ranked alternative solutions. Results can be visualized either on a generic or patient geometry. The CNNs were trained on a data set containing only simulated data and evaluated both on simulated and clinical test data. On simulated data, the median test error was below 3mm. The median localization error on the clinical data was as low as 32mm. The transmural position was correctly detected in up to 82% of all clinical cases. Using the ranked alternative solutions, the top-3 median error dropped to 20mm on clinical data. These results demonstrate a proof of principle to utilize CNNs to localize the activation source without the intrinsic need of patient-specific geometrical information. Furthermore, delivering multiple solutions can help the physician to find the real activation source amongst more than one possible locations. With further optimization, these methods have a high potential to speed up clinical interventions. Consequently they could decrease procedural risk and improve VT patients' outcomes.Comment: 14 pages, 9 figures. Abstract was shortened for arXi

Association between convalescent plasma treatment and mortality in COVID-19: a collaborative systematic review and meta-analysis of randomized clinical trials.

Funder: laura and john arnold foundationBACKGROUND: Convalescent plasma has been widely used to treat COVID-19 and is under investigation in numerous randomized clinical trials, but results are publicly available only for a small number of trials. The objective of this study was to assess the benefits of convalescent plasma treatment compared to placebo or no treatment and all-cause mortality in patients with COVID-19, using data from all available randomized clinical trials, including unpublished and ongoing trials (Open Science Framework, https://doi.org/10.17605/OSF.IO/GEHFX ). METHODS: In this collaborative systematic review and meta-analysis, clinical trial registries (ClinicalTrials.gov, WHO International Clinical Trials Registry Platform), the Cochrane COVID-19 register, the LOVE database, and PubMed were searched until April 8, 2021. Investigators of trials registered by March 1, 2021, without published results were contacted via email. Eligible were ongoing, discontinued and completed randomized clinical trials that compared convalescent plasma with placebo or no treatment in COVID-19 patients, regardless of setting or treatment schedule. Aggregated mortality data were extracted from publications or provided by investigators of unpublished trials and combined using the Hartung-Knapp-Sidik-Jonkman random effects model. We investigated the contribution of unpublished trials to the overall evidence. RESULTS: A total of 16,477 patients were included in 33 trials (20 unpublished with 3190 patients, 13 published with 13,287 patients). 32 trials enrolled only hospitalized patients (including 3 with only intensive care unit patients). Risk of bias was low for 29/33 trials. Of 8495 patients who received convalescent plasma, 1997 died (23%), and of 7982 control patients, 1952 died (24%). The combined risk ratio for all-cause mortality was 0.97 (95% confidence interval: 0.92; 1.02) with between-study heterogeneity not beyond chance (I2 = 0%). The RECOVERY trial had 69.8% and the unpublished evidence 25.3% of the weight in the meta-analysis. CONCLUSIONS: Convalescent plasma treatment of patients with COVID-19 did not reduce all-cause mortality. These results provide strong evidence that convalescent plasma treatment for patients with COVID-19 should not be used outside of randomized trials. Evidence synthesis from collaborations among trial investigators can inform both evidence generation and evidence application in patient care

Metal-Assisted Oxo Atom Addition to an Fe(III) Thiolate

Cysteinate oxygenation is intimately tied to the function of both cysteine dioxygenases (CDOs) and nitrile hydratases (NHases), and yet the mechanisms by which sulfurs are oxidized by these enzymes are unknown, in part because intermediates have yet to be observed. Herein, we report a five-coordinate bis-thiolate ligated Fe(III) complex, [FeIII(S2Me2N3(Pr,Pr))]+ (2), that reacts with oxo atom donors (PhIO, IBX-ester, and H2O2) to afford a rare example of a singly oxygenated sulfenate, [FeIII(η2-SMe2O)(SMe2)N3(Pr,Pr)]+ (5), resembling both a proposed intermediate in the CDO catalytic cycle and the essential NHase Fe-S(O)Cys114 proposed to be intimately involved in nitrile hydrolysis. Comparison of the reactivity of 2 with that of a more electron-rich, crystallographically characterized derivative, [FeIIIS2Me2NMeN2amide(Pr,Pr)]- (8), shows that oxo atom donor reactivity correlates with the metal ion's ability to bind exogenous ligands. Density functional theory calculations suggest that the mechanism of S-oxygenation does not proceed via direct attack at the thiolate sulfurs; the average spin-density on the thiolate sulfurs is approximately the same for 2 and 8, and Mulliken charges on the sulfurs of 8 are roughly twice those of 2, implying that 8 should be more susceptible to sulfur oxidation. Carboxamide-ligated 8 is shown to be unreactive towards oxo atom donors, in contrast to imine-ligated 2. Azide (N3-) is shown to inhibit sulfur oxidation with 2, and a green intermediate is observed, which then slowly converts to sulfenate-ligated 5. This suggests that the mechanism of sulfur oxidation involves initial coordination of the oxo atom donor to the metal ion. Whether the green intermediate is an oxo atom donor adduct, Fe-O═I-Ph, or an Fe(V)═O remains to be determined

Metal-Assisted Oxo Atom Addition to an Fe(III) Thiolate

Cysteinate oxygenation is intimately tied to the function of both cysteine dioxygenases (CDOs) and nitrile hydratases (NHases), and yet the mechanisms by which sulfurs are oxidized by these enzymes are unknown, in part because intermediates have yet to be observed. Herein, we report a five-coordinate bis-thiolate ligated Fe­(III) complex, [Fe^III­(S₂^Me2N₃­(Pr,Pr))]⁺ (<b>2</b>), that reacts with oxo atom donors (PhIO, IBX-ester, and H₂O₂) to afford a rare example of a singly oxygenated sulfenate, [Fe^III­(η²‑S^Me2O)­(S^Me2)­N₃­(Pr,Pr)]⁺ (<b>5</b>), resembling both a proposed intermediate in the CDO catalytic cycle and the essential NHase Fe-S­(O)^Cys114 proposed to be intimately involved in nitrile hydrolysis. Comparison of the reactivity of <b>2</b> with that of a more electron-rich, crystallographically characterized derivative, [Fe^IIIS₂^Me2­N^MeN₂^amide­(Pr,Pr)]⁻ (<b>8</b>), shows that oxo atom donor reactivity correlates with the metal ion’s ability to bind exogenous ligands. Density functional theory calculations suggest that the mechanism of S-oxygenation does not proceed via direct attack at the thiolate sulfurs; the average spin-density on the thiolate sulfurs is approximately the same for <b>2</b> and <b>8</b>, and Mulliken charges on the sulfurs of <b>8</b> are roughly twice those of <b>2</b>, implying that <b>8</b> should be more susceptible to sulfur oxidation. Carboxamide-ligated <b>8</b> is shown to be unreactive towards oxo atom donors, in contrast to imine-ligated <b>2</b>. Azide (N₃^–) is shown to inhibit sulfur oxidation with <b>2</b>, and a green intermediate is observed, which then slowly converts to sulfenate-ligated <b>5</b>. This suggests that the mechanism of sulfur oxidation involves initial coordination of the oxo atom donor to the metal ion. Whether the green intermediate is an oxo atom donor adduct, Fe-OI-Ph, or an Fe­(V)O remains to be determined

Report on developing bottom-up Marginal abatement cost curves (MACCS) for representative farm type

Developing efficient policy instruments and incentive schemes to promote the uptake of greenhouse gas mitigation measures requires some kind of prioritisation of the mitigation measures. An important consideration in this process is the estimated cost and costefficiency the measures. The high number of reports done in developed countries show a high variability in the country-level cost-effectiveness estimates, and suggest that approaches providing higher granularity at the spatial and farm type could suit better to the purpose of regional policy development. At the same time, there is still a gap in our understanding of economic mitigation potential of agriculture in developing and newly industrialised countries.[br/] To address these questions this report presents three studies. The first is a literature review of the cost-effectiveness estimates of mitigation measures published in the past 15 years, discussing the variability in these estimates. The second study reports on marginal abatement cost curves for beef cattle production in Brazil. Finally, the last report presents the conceptual basis of a tool to assess the financial implications of the mitigation measures to be used in parallel with the FarmAC model, ultimately providing mitigation measure costeffectiveness estimates specific to individual farms. Additionally, it describes the selection of mitigation measures which have been assessed at the farm level in Component 3 of the AnimalChange project