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

Continuously non-malleable codes with split-state refresh

Non-malleable codes for the split-state model allow to encode a message into two parts, such that arbitrary independent tampering on each part, and subsequent decoding of the corresponding modified codeword, yields either the same as the original message, or a completely unrelated value. Continuously non-malleable codes further allow to tolerate an unbounded (polynomial) number of tampering attempts, until a decoding error happens. The drawback is that, after an error happens, the system must self-destruct and stop working, otherwise generic attacks become possible. In this paper we propose a solution to this limitation, by leveraging a split-state refreshing procedure. Namely, whenever a decoding error happens, the two parts of an encoding can be locally refreshed (i.e., without any interaction), which allows to avoid the self-destruct mechanism in some applications. Additionally, the refreshing procedure can be exploited in order to obtain security against continual leakage attacks. We give an abstract framework for building refreshable continuously non-malleable codes in the common reference string model, and provide a concrete instantiation based on the external Diffie–Hellman assumption. Finally, we explore applications in which our notion turns out to be essential. The first application is a signature scheme tolerating an arbitrary polynomial number of split-state tampering attempts, without requiring a self-destruct capability, and in a model where refreshing of the memory happens only after an invalid output is produced. This circumvents an impossibility result from a recent work by Fujisaki and Xagawa (Asiacrypt 2016). The second application is a compiler for tamper-resilient read-only RAM programs. In comparison to other tamper-resilient RAM compilers, ours has several advantages, among which the fact that, in some cases, it does not rely on the self-destruct feature

Hornqvæg og Sviin ved den internationale Udstilling i Hamborg.

Hornqvæg og Sviin ved den internationale Udstilling i Hamborg

Om Leveriktens Optræden i Faarebesætningen paa Sjørring Sø.

Om Leveriktens Optræden i Faarebesætningen paa Sjørring Sø

Om Malkekvæget i Danmark. Foredrag ved den 15de danske Landmandsforsamling 1883.

Om Malkekvæget i Danmark. Foredrag ved den 15de danske Landmandsforsamling 1883

The relative timing of trunk muscle activation is retained in response to unanticipated postural-perturbations during acute low back pain

The purpose of this study was to assess the activation of the erector spinae (ES) and external oblique (EO) in response to unanticipated, bi-directional postural perturbations before and after the induction of acute low back pain (LBP) in healthy individuals. An experimental session consisted of a baseline, control, and an acute LBP condition. For the control and acute LBP condition, isotonic or hypertonic saline (HS), respectively, was injected into the right ES muscle. In each condition, participants stood on a moveable platform during which 32 randomized postural perturbations (8 repetitions of 4 perturbation types: 8 cm anterior slides, 8 cm posterior slides, 10° anterior tilts, and 10° posterior tilts) with varying inter-perturbation time intervals were performed over a period of 4–5 min. Bilateral surface electromyography (EMG) was recorded from the ES and EO in addition to subjective pain records. During the acute LBP condition: (1) the onset time of the ES and EO was delayed for the forward and backward sliding perturbations (P < 0.05); (2) EMG amplitude was reduced bilaterally for all perturbations (P < 0.05); (3) the order of activation and interval between the onset times of the ES and EO were unaltered and (4) ES, but not EO, activity was adjusted to account for the directional differences between the perturbations. This study revealed that re-establishment of posture and balance was a result of the individuals’ ability to rapidly modulate ES with respect to EO activity and that the bi-directional postural responses, although shifted in time and amplitude, retained temporal features in the presence of acute LBP

Genomic mapping of social behavior traits in a F2 cross derived from mice selectively bred for high aggression

BACKGROUND: Rapid response to selection was previously observed in mice selected for high levels of inter-male aggression based on number of attacks displayed in a novel social interaction test after isolation housing. Attack levels in this high aggression line (NC900) increased significantly within just four generations of selective breeding, suggesting the presence of a locus with large effect. We conducted an experiment using a small (n ≈ 100) F(2 )cross between the ICR-derived, non-inbred NC900 strain and the low aggression inbred strain C57BL/6J, genotyped for 154 fully informative SNPs, to determine if a locus with large effect controls the high-aggression selection trait. A second goal was to use high density SNP genotyping (n = 549,000) in the parental strains to characterize residual patterns of heterozygosity within NC900, and evaluate regions that are identical by descent (IBD) between NC900 and C57BL/6J, to determine what impacts these may have on accuracy and resolution of quantitative trait locus (QTL) mapping in the F(2 )cross. RESULTS: No evidence for a locus with major effect on aggressive behavior in mice was identified. However, several QTL with genomewide significance were mapped for aggression on chromosomes 7 and 19 and other social behavior traits on chromosomes 4, 7, 14, and 19. High density genotyping revealed that 28% of the genome is still segregating among the six NC900 females used to originate the F(2 )cross, and that segregating regions are present on every chromosome but are of widely different sizes. Regions of IBD between NC900 and C57BL/6J are found on every chromosome but are most prominent on chromosomes 10, 16 and X. No significant differences were found for amounts of heterozygosity or prevalence of IBD in QTL regions relative to global analysis. CONCLUSIONS: While no major gene was identified to explain the rapid selection response in the NC900 line, transgressive variation (i.e. where the allele from the C57BL/6J increased attack levels) and a significant role for dominant gene action were hallmarks of the genetic architecture for aggressive behavior uncovered in this study. The high levels of heterozygosity and the distribution of minor allele frequency observed in the NC900 population suggest that maintenance of heterozygosity may have been under selection in this line

Molecular Drivers of Oncotype DX, Prosigna, EndoPredict, and the Breast Cancer Index: A TransATAC Study.

PURPOSE: The Oncotype DX Recurrence Score (RS), Prosigna Prediction Analysis of Microarray 50 (PAM50) Risk of Recurrence (ROR), EndoPredict (EP), and Breast Cancer Index (BCI) are used clinically for estimating risk of distant recurrence for patients receiving endocrine therapy. Discordances in estimates occur between them. We aimed to identify the molecular features that drive the tests and lead to these differences. PATIENTS AND METHODS: Analyses for RS, ROR, EP, and BCI were conducted by the manufacturers in the TransATAC sample collection that consisted of the tamoxifen or anastrozole arms of the ATAC trial. Estrogen receptor-positive/human epidermal growth factor receptor 2 (HER2)-negative cases without chemotherapy treatment were included in which all four tests were available (n = 785). Clinicopathologic features included in some tests were excluded from the comparisons. Estrogen, proliferation, invasion, and HER2 module scores from RS were used to characterize the respective molecular features. Spearman correlation and analysis of variance tests were applied. RESULTS: There were moderate to strong correlations among the four molecular scores (ρ = 0.63-0.74) except for RS versus ROR (ρ = 0.32) and RS versus BCI (ρ = 0.35). RS had strong negative correlation with its estrogen module (ρ = -0.79) and moderate positive correlation with its proliferation module (ρ = 0.36). RS's proliferation module explained 72.5% of ROR's variance, while the estrogen module explained only 0.6%. Most of EP's and BCI's variation was accounted for by the proliferation module (50.0% and 54.3%, respectively) and much less by the estrogen module (20.2% and 2.7%, respectively). CONCLUSION: In contrast to common understanding, RSs are determined more strongly by estrogen-related features and only weakly by proliferation markers. However, the EP, BCI, and particularly ROR scores are determined largely by proliferative features. These relationships help to explain the differences in the prognostic performance of the tests