Optimal length-constrained segmentation and subject-adaptive learning for real-time arrhythmia detection

© 2018 Association for Computing Machinery. An algorithm of data segmentation with length constraints for each segment is presented and applied in the context of arrhythmia detection. The additivity property of the cost function for each segment yields the induction proof of the exact global optimal solution. The experiments were conducted on the MIT-BIH arrhythmia dataset with the heartbeat categories recommended by the ANSI/AAMI EC57:1998 standard. The heartbeat classification task is enhanced by an adaptive learning scheme. Incremental support vector machine is used to integrate a small number of expert-annotated samples specific to the subject into the existing classifier previously learned from the dataset. The proposed segmentation scheme obtains the sensitivity of 99.89% and the positive predictivity of 99.83%. The classification sensitivities of ventricular and supraventricular detection are significantly boosted from 85.9% and 83.5% (subject-unadaptive) to 97.7% and 93.2% (subject-adaptive), respectively. Similarly the pre-dictivities increase from 94.8% to 99.3% (ventricular), and from 67.7% to 88.0% (supraventricular) when plugging in the adaptive learning method. The signal processing framework is conducted in a simulated real-time model. As compared to the previously reported studies we achieve a competitive performance in terms of all assessment measures

An efficient hardware architecture for a neural network activation function generator

This paper proposes an efficient hardware architecture for a function generator suitable for an artificial neural network (ANN). A spline-based approximation function is designed that provides a good trade-off between accuracy and silicon area, whilst also being inherently scalable and adaptable for numerous activation functions. This has been achieved by using a minimax polynomial and through optimal placement of the approximating polynomials based on the results of a genetic algorithm. The approximation error of the proposed method compares favourably to all related research in this field. Efficient hardware multiplication circuitry is used in the implementation, which reduces the area overhead and increases the throughput

Peripheral blood mitochondrial DNA content in relation to circulating metabolites and inflammatory markers: a population study

Mitochondrial DNA (mtDNA) content might undergo significant changes caused by metabolic derangements, oxidative stress and inflammation that lead to development and progression of cardiovascular diseases. We, therefore, investigated in a general population the association of peripheral blood mtDNA content with circulating metabolites and inflammatory markers. We examined 310 subjects (50.6% women; mean age, 53.3 years) randomly selected from a Flemish population. Relative mtDNA content was measured by quantitative real-time PCR in peripheral blood cells. Peak circulating metabolites were quantified using nuclear magnetic resonance spectroscopy. The level of inflammation was assessed via established inflammatory markers. Using Partial Least Squares analysis, we constructed 3 latent factors from the 44 measured metabolites that explained 62.5% and 8.5% of the variance in the contributing metabolites and the mtDNA content, respectively. With adjustments applied, mtDNA content was positively associated with the first latent factor (P = 0.002). We identified 6 metabolites with a major impact on the construction of this latent factor including HDL3 apolipoproteins, tyrosine, fatty acid with αCH2, creatinine, β-glucose and valine. We summarized them into a single composite metabolite score. We observed a negative association between the composite metabolic score and mtDNA content (P = 0.001). We also found that mtDNA content was inversely associated with inflammatory markers including hs-CRP, hs-IL6, white blood cell and neutrophil counts as well as neutrophil-to-lymphocyte ratio (P≤0.0024). We demonstrated that in a general population relative peripheral blood mtDNA content was associated with circulating metabolites indicative of perturbed lipid metabolism and with inflammatory biomarkers

Security Evaluation of Support Vector Machines in Adversarial Environments

Support Vector Machines (SVMs) are among the most popular classification techniques adopted in security applications like malware detection, intrusion detection, and spam filtering. However, if SVMs are to be incorporated in real-world security systems, they must be able to cope with attack patterns that can either mislead the learning algorithm (poisoning), evade detection (evasion), or gain information about their internal parameters (privacy breaches). The main contributions of this chapter are twofold. First, we introduce a formal general framework for the empirical evaluation of the security of machine-learning systems. Second, according to our framework, we demonstrate the feasibility of evasion, poisoning and privacy attacks against SVMs in real-world security problems. For each attack technique, we evaluate its impact and discuss whether (and how) it can be countered through an adversary-aware design of SVMs. Our experiments are easily reproducible thanks to open-source code that we have made available, together with all the employed datasets, on a public repository.Comment: 47 pages, 9 figures; chapter accepted into book 'Support Vector Machine Applications

Az ENSZ Környezetvédelmi Programjának környezetállapot-értékelési rendszere

The performance of adaptive systems that consist of microscale on-chip elements [microelectromechanical mirror (µ-mirror) arrays and a VLSI stochastic gradient descent microelectronic control system] is analyzed. The µ-mirror arrays with 5 × 5 and 6 × 6 actuators were driven with a control system composed of two mixed-mode VLSI chips implementing model-free beam-quality metric optimization by the stochastic parallel perturbative gradient descent technique. The adaptation rate achieved was near 6000 iterations/s. A secondary (learning) feedback loop was used to control system parameters during the adaptation process, further increasing the adaptation rate

Confession Session: Learning from Others Mistakes

Accepted versio

Sialyltransferase ST3Gal-IV controls CXCR2-mediated firm leukocyte arrest during inflammation

Recent in vitro studies have suggested a role for sialylation in chemokine receptor binding to its ligand (Bannert, N., S. Craig, M. Farzan, D. Sogah, N.V. Santo, H. Choe, and J. Sodroski. 2001. J. Exp. Med. 194:1661–1673). This prompted us to investigate chemokine-induced leukocyte adhesion in inflamed cremaster muscle venules of α2,3 sialyltransferase (ST3Gal-IV)-deficient mice. We found a marked reduction in leukocyte adhesion to inflamed microvessels upon injection of the CXCR2 ligands CXCL1 (keratinocyte-derived chemokine) or CXCL8 (interleukin 8). In addition, extravasation of ST3Gal-IV−/− neutrophils into thioglycollate-pretreated peritoneal cavities was significantly decreased. In vitro assays revealed that CXCL8 binding to isolated ST3Gal-IV−/− neutrophils was markedly impaired. Furthermore, CXCL1-mediated adhesion of ST3Gal-IV−/− leukocytes at physiological flow conditions, as well as transendothelial migration of ST3Gal-IV−/− leukocytes in response to CXCL1, was significantly reduced. In human neutrophils, enzymatic desialylation decreased binding of CXCR2 ligands to the neutrophil surface and diminished neutrophil degranulation in response to these chemokines. In addition, binding of α2,3-linked sialic acid–specific Maackia amurensis lectin II to purified CXCR2 from neuraminidase-treated CXCR2-transfected HEK293 cells was markedly impaired. Collectively, we provide substantial evidence that sialylation by ST3Gal-IV significantly contributes to CXCR2-mediated leukocyte adhesion during inflammation in vivo

Left atrial mechanics and aortic stiffness following high intensity interval training: a randomised controlled study

Purpose: High intensity interval training (HIIT) has been shown to improve important health parameters, including aerobic capacity, blood pressure, cardiac autonomic modulation and left ventricular (LV) mechanics. However, adaptations in left atrial (LA) mechanics and aortic stiffness remain unclear. Methods: Forty-one physically inactive males and females were recruited. Participants were randomised to either a 4-week HIIT intervention (n=21) or 4-week control period (n=20). The HIIT protocol consisted of 3x30-second maximal cycle ergometer sprints with a resistance of 7.5% body weight, interspersed with 2-minutes of active unloaded recovery, 3 times per week. Speckle tracking imaging of the LA and M-Mode tracing of the aorta was performed pre and post HIIT and control period. Results: Following HIIT, there was significant improvement in LA mechanics, including LA reservoir (13.9±13.4%, p=0.033), LA conduit (8.9±11.2%, p=0.023) and LA contractile (5±4.5%, p=0.044) mechanics compared to the control condition. In addition, aortic distensibility (2.1±2.7cm2dyn-1103, p=0.031) and aortic stiffness index (-2.6±4.6, p=0.041) were improved compared to the control condition. In stepwise linear regression analysis, aortic distensibility change was significantly associated with LA stiffness change R2 of 0.613 (p=0.002). Conclusion: A short-term programme of HIIT was associated with a significant improvement in LA mechanics and aortic stiffness. These adaptations may have important health implications and contribute to the improved LV diastolic and systolic mechanics, aerobic capacity and blood pressure previously documented following HIIT

Microparticles from apoptotic platelets promote resident macrophage differentiation

Platelets shed microparticles not only upon activation, but also upon ageing by an apoptosis-like process (apoptosis-induced platelet microparticles, PMap). While the activation-induced microparticles have widely been studied, not much is known about the (patho)physiological consequences of PMap formation. Flow cytometry and scanning electron microscopy demonstrated that PMap display activated integrins and interact to form microparticle aggregates. PMap were chemotactic for monocytic cells, bound to these cells, an furthermore stimulated cell adhesion and spreading on a fibronectin surface. After prolonged incubation, PMap promoted cell differentiation, but inhibited proliferation. Monocyte membrane receptor analysis revealed increased expression levels of CD11b (integrin αMβ2), CD14 and CD31 (platelet endothelial cell adhesion molecule-1), and the chemokine receptors CCR5 and CXCR4, but not of CCR2. This indicated that PMap polarized the cells into resident M2 monocytes. Cells treated with PMap actively consumed oxidized low-density lipoprotein (oxLDL), and released matrix metalloproteinases and hydrogen peroxide. Further confirmation for the differentiation towards resident professional phagocytes came from the finding that PMap stimulated the expression of the (ox)LDL receptors, CD36 and CD68, and the production of proinflammatory and immunomodulating cytokines by monocytes. In conclusion, interaction of PMap with monocytic cells has an immunomodulating potential. The apoptotic microparticles polarize the cells into a resident M2 subset, and induce differentiation to resident professional phagocytes