Deep Learning-based Anomaly Detection on X-ray Images of Fuel Cell Electrodes

Anomaly detection in X-ray images has been an active and lasting research area in the last decades, especially in the domain of medical X-ray images. For this work, we created a real-world labeled anomaly dataset, consisting of 16-bit X-ray image data of fuel cell electrodes coated with a platinum catalyst solution and perform anomaly detection on the dataset using a deep learning approach. The dataset contains a diverse set of anomalies with 11 identified common anomalies where the electrodes contain e.g. scratches, bubbles, smudges etc. We experiment with 16-bit image to 8-bit image conversion methods to utilize pre-trained Convolutional Neural Networks as feature extractors (transfer learning) and find that we achieve the best performance by maximizing the contrasts globally across the dataset during the 16-bit to 8-bit conversion, through histogram equalization. We group the fuel cell electrodes with anomalies into a single class called abnormal and the normal fuel cell electrodes into a class called normal, thereby abstracting the anomaly detection problem into a binary classification problem. We achieve a balanced accuracy of 85.18\%. The anomaly detection is used by the company, Serenergy, for optimizing the time spend on the quality control of the fuel cell electrodesComment: 10 pages, 9 figures, VISAPP202

Risk and Subtypes of Stroke Following New-Onset Postoperative Atrial Fibrillation in Coronary Bypass Surgery:A Population-Based Cohort Study

BACKGROUND: New‐onset postoperative atrial fibrillation (POAF) develops in approximately one‐third of patients undergoing cardiac surgery and is associated with a higher incidence of ischemic stroke and increased mortality. However, it remains unknown to what extent ischemic stroke events in patients with POAF are cardioembolic and whether anticoagulant therapy is indicated. We investigated the long‐term risk and pathogenesis of postoperative stroke in patients undergoing coronary artery bypass grafting experiencing POAF. METHODS AND RESULTS: This was a register‐based cohort study. Data from the WDHR (Western Denmark Heart Registry) were linked with the DNPR (Danish National Patient Register), the Danish National Prescription Register, and the Cause of Death Register. All stroke diagnoses were verified, and ischemic stroke cases were subclassified according to pathogenesis. Furthermore, investigations of all‐cause mortality and the use of anticoagulation medicine for the individual patient were performed. A total of 7813 patients without a preoperative history of atrial fibrillation underwent isolated coronary artery bypass grafting between January 1, 2010, and December 31, 2018, in Western Denmark. POAF was registered in 2049 (26.2%) patients, and a postoperative ischemic stroke was registered in 195 (2.5%) of the patients. After adjustment, there was no difference in the risk of ischemic stroke (hazard ratio [HR], 1.08 [95% CI, 0.74–1.56]) or all‐cause mortality (HR, 1.09 [95% CI, 0.98–1.23]) between patients who developed POAF and non‐POAF patients. Although not statistically significant, patients with POAF had a higher incidence rate (IR; per 1000 patient‐years) of cardioembolic stroke (IR, 1 [95% CI, 0.6–1.6] versus IR, 0.5 [95% CI, 0.3–0.8]), whereas non‐POAF patients had a higher incidence rate of large‐artery occlusion stroke (IR, 1.1 [95% CI, 0.8–1.5] versus IR, 0.7 [95% CI, 0.4–1.4]). Early initiation of anticoagulation medicine was not associated with a lower risk of ischemic stroke. However, patients with POAF were more likely to die of cardiovascular causes than non‐POAF patients (P<0.001). CONCLUSIONS: We found no difference in the adjusted risk of postoperative stroke or all‐cause mortality in POAF versus non‐POAF patients. Patients with POAF after coronary artery bypass grafting presented with a higher, although not significant, proportion of ischemic strokes of the cardioembolic type

Gut Microbiota in Human Adults with Type 2 Diabetes Differs from Non-Diabetic Adults

Recent evidence suggests that there is a link between metabolic diseases and bacterial populations in the gut. The aim of this study was to assess the differences between the composition of the intestinal microbiota in humans with type 2 diabetes and non-diabetic persons as control. was highly enriched in diabetic compared to non-diabetic persons (P = 0.02) and positively correlated with plasma glucose (P = 0.04).The results of this study indicate that type 2 diabetes in humans is associated with compositional changes in intestinal microbiota. The level of glucose tolerance should be considered when linking microbiota with metabolic diseases such as obesity and developing strategies to control metabolic diseases by modifying the gut microbiota

Fatty Acid Composition in Various Types of Cardiac Adipose Tissues and Its Relation to the Fatty Acid Content of Atrial Tissue

Diet, with its content of various types of fatty acids (FAs), is of great importance for cellular function. Adipose tissue (AT) serves as a storage for dietary FAs, but after appropriate activation it may also offer important biological properties, e.g., by releasing adipokines and cytokines to the surrounding milieu. Such effects may depend on the diet and type of FA involved. Similarly, the composition of FAs in the heart is also likely to be important for cardiac function. We investigated samples of epicardial adipose tissue (EAT), pericardial adipose tissue (PAT), subcutaneous adipose tissue (SCAT), and tissue from the right atrial appendage to compare the FA compositions in patients undergoing elective cardiac surgery. Minor differences among AT compartments were found, while the comparison of atrial tissue and EAT showed major differences in saturated fatty acids (SFAs), monounsaturated fatty acids (MUFAs), and n-3 and n-6 polyunsaturated fatty acids (PUFAs). These findings may be of importance for understanding biological availability, dietary effects, and the effects of FAs on the heart

Effects of impurities on pre-doped and post-doped membranes for high temperature PEM fuel cell stacks

In this paper, we experimentally investigated two high temperature polymer electrolyte membrane fuel cell (HT-PEMFC) stacks for their response to the presence of reformate impurities in an anode gas stream. The investigation was aimed at characterizing the effects of reformate impurities at the stack level, including in humidified conditions and identifying fault features for diagnosis purposes. Two HT-PEMFC stacks of 37 cells each with active areas of 165 cm2 were used with one stack containing a pre-doped membrane with a woven gas diffusion layer (GDL) and the other containing a post-doped membrane with non-woven GDL. Polarization curves and galvanostatic electrochemical impedance spectroscopy (EIS) were used for characterization. We found that both N2 dilution and impurities in the anode feed affected mainly the charge transfer losses, especially on the anode side. We also found that humidification alleviated the poisoning effects of the impurities in the stack with pre-doped membrane electrode assemblies (MEA) and woven GDL but had detrimental effects on the stack with post-doped MEAs and non-woven GDL. We demonstrated that pure and dry hydrogen operation at the end of the tests resulted in significant recovery of the performance losses due to impurities for both stacks even after the humidified reformate operation. This implies that there was only limited acid loss during the test period of around 150 h for each stack

Controlling the rheo-electric properties of graphite/carbon black suspensions by 'flow-switching'

The ability to manipulate rheological and electrical properties of colloidal carbon black gels makes them attractive in composites for energy applications such as batteries and fuel cells, where they conduct electricity and prevent sedimentation of `granular' active components. While it is commonly assumed that granular fillers have a simple additive effect on the composite properties, new phenomena can emerge unexpectedly, with some composites exhibiting a unique rheological bi-stability between solid-like and liquid-like states. Here we report such bi-stability in suspensions of non-Brownian graphite and colloidal carbon black in oil, a model system to mimic composite suspensions for energy applications. Steady shear below a critical stress elicits a transition to a persistent mechanically weak and poorly conducting state, which must be `rejuvenated' using high-stress shear to recover a stronger, high-conductivity state. Our findings highlight the highly tunable nature of binary granular/gel composite suspensions, and present new possibilities for optimizing mixing and processing conditions for Li-ion battery slurries. The dataset refers to the upcoming publication 'Controlling the rheo-electric properties of graphite/carbon black suspensions by 'flow-switching' by Thomas Larsen, John R. Royer, Fraser H. J. Laidlaw, Wilson C. K. Poon, Tom Larsen, Søren J. Andreasen, and Jesper de C. Christiansen