Numerics of boundary-domain integral and integro-differential equations for BVP with variable coefficient in 3D

This is the post-print version of the article. The official published version can be accessed from the links below - Copyright @ 2013 Springer-VerlagA numerical implementation of the direct boundary-domain integral and integro-differential equations, BDIDEs, for treatment of the Dirichlet problem for a scalar elliptic PDE with variable coefficient in a three-dimensional domain is discussed. The mesh-based discretisation of the BDIEs with tetrahedron domain elements in conjunction with collocation method leads to a system of linear algebraic equations (discretised BDIE). The involved fully populated matrices are approximated by means of the H-Matrix/adaptive cross approximation technique. Convergence of the method is investigated.This study is partially supported by the EPSRC grant EP/H020497/1:"Mathematical Analysis of Localised-Boundary-Domain Integral Equations for Variable-Coefficients Boundary Value Problems"

Understanding the nature of "superhard graphite"

Numerous experiments showed that on cold compression graphite transforms into a new superhard and transparent allotrope. Several structures with different topologies have been proposed for this phase. While experimental data are consistent with these models, the only way to solve this puzzle is to find which structure is kinetically easiest to form. Using state-of-the-art molecular-dynamics transition path sampling simulations, we investigate kinetic pathways of the pressure-induced transformation of graphite to various superhard candidate structures. Unlike hitherto applied methods for elucidating nature of superhard graphite, transition path sampling realistically models nucleation events necessary for physically meaningful transformation kinetics. We demonstrate that nucleation mechanism and kinetics lead to $M$-carbon as the final product. $W$-carbon, initially competitor to $M$-carbon, is ruled out by phase growth. Bct-C$_4$ structure is not expected to be produced by cold compression due to less probable nucleation and higher barrier of formation

Detection and Localization of Myocardial Infarction Based on Multi-Scale ResNet and Attention Mechanism

PURPOSE: Myocardial infarction (MI) is one of the most common cardiovascular diseases, frequently resulting in death. Early and accurate diagnosis is therefore important, and the electrocardiogram (ECG) is a simple and effective method for achieving this. However, it requires assessment by a specialist; so many recent works have focused on the automatic assessment of ECG signals. METHODS: For the detection and localization of MI, deep learning models have been proposed, but the diagnostic accuracy of this approaches still need to be improved. Moreover, with deep learning methods the way in which a given result was achieved lacks interpretability. In this study, ECG data was obtained from the PhysioBank open access database, and was analyzed as follows. Firstly, the 12-lead ECG signal was preprocessed to identify each beat and obtain each heart interval. Secondly, a multi-scale deep learning model combined with a residual network and attention mechanism was proposed, where the input was the 12-lead ECG recording. Through the SENet model and the Grad-CAM algorithm, the weighting of each lead was calculated and visualized. Using existing knowledge of the way in which different types of MI gave characteristic patterns in specific ECG leads, the model was used to provisionally diagnose the type of MI according to the characteristics of each of the 12 ECG leads. RESULTS: Ten types of MI anterior, anterior lateral, anterior septal, inferior, inferior lateral, inferior posterior, inferior posterior lateral, lateral, posterior, and posterior lateral were diagnosed. The average accuracy, sensitivity, and specificity for MI detection of all lesion types was 99.98, 99.94, and 99.98%, respectively; and the average accuracy, sensitivity, and specificity for MI localization was 99.79, 99.88, and 99.98%, respectively. CONCLUSION: When compared to existing models based on traditional machine learning methods, convolutional neural networks and recurrent neural networks, the results showed that the proposed model had better diagnostic performance, being superior in accuracy, sensitivity, and specificity

Comparison of Genome-Wide Association Scans for Quantitative and Observational Measures of Human Hair Curvature.

Previous genetic studies on hair morphology focused on the overall morphology of the hair using data collected by self-report or researcher observation. Here, we present the first genome-wide association study (GWAS) of a micro-level quantitative measure of hair curvature. We compare these results to GWAS results obtained using a macro-level classification of observable hair curvature performed in the same sample of twins and siblings of European descent. Observational data were collected by trained observers, while quantitative data were acquired using an Optical Fibre Diameter Analyser (OFDA). The GWAS for both the observational and quantitative measures of hair curvature resulted in genome-wide significant signals at chromosome 1q21.3 close to the trichohyalin (TCHH) gene, previously shown to harbor variants associated with straight hair morphology in Europeans. All genetic variants reaching genome-wide significance for both GWAS (quantitative measure lead single-nucleotide polymorphism [SNP] rs12130862, p = 9.5 × 10-09; observational measure lead SNP rs11803731, p = 2.1 × 10-17) were in moderate to very high linkage disequilibrium (LD) with each other (minimum r2 = .45), indicating they represent the same genetic locus. Conditional analyses confirmed the presence of only one signal associated with each measure at this locus. Results from the quantitative measures reconfirmed the accuracy of observational measures

Targeting IκB Kinase β in Adipocyte Lineage Cells for Treatment of Obesity and Metabolic Dysfunctions

IκB kinase β (IKKβ), a central coordinator of inflammation through activation of nuclear factor-κB, has been identified as a potential therapeutic target for the treatment of obesity-associated metabolic dysfunctions. In this study, we evaluated an antisense oligonucleotide (ASO) inhibitor of IKKβ and found that IKKβ ASO ameliorated diet-induced metabolic dysfunctions in mice. Interestingly, IKKβ ASO also inhibited adipocyte differentiation and reduced adiposity in high-fat (HF)-fed mice, indicating an important role of IKKβ signaling in the regulation of adipocyte differentiation. Indeed, CRISPR/Cas9-mediated genomic deletion of IKKβ in 3T3-L1 preadipocytes blocked these cells differentiating into adipocytes. To further elucidate the role of adipose progenitor IKKβ signaling in diet-induced obesity, we generated mice that selectively lack IKKβ in the white adipose lineage and confirmed the essential role of IKKβ in mediating adipocyte differentiation in vivo. Deficiency of IKKβ decreased HF-elicited adipogenesis in addition to reducing inflammation and protected mice from diet-induced obesity and insulin resistance. Further, pharmacological inhibition of IKKβ also blocked human adipose stem cell differentiation. Our findings establish IKKβ as a pivotal regulator of adipogenesis and suggest that overnutrition-mediated IKKβ activation serves as an initial signal that triggers adipose progenitor cell differentiation in response to HF feeding. Inhibition of IKKβ with antisense therapy may represent as a novel therapeutic approach to combat obesity and metabolic dysfunctions. Stem Cells 2016;34:1883–1895

IKKβ is Essential for Adipocyte Survival and Adaptive Adipose Remodeling in Obesity

IκB kinase β (IKKβ), a central coordinator of inflammatory responses through activation of nuclear factor-κB (NF-κB), has been implicated as a critical molecular link between inflammation and metabolic disorders; however, the role of adipocyte IKKβ in obesity and related metabolic disorders remains elusive. Here we report an essential role of IKKβ in the regulation of adipose remodeling and adipocyte survival in diet-induced obesity. Targeted deletion of IKKβ in adipocytes does not affect body weight, food intake, and energy expenditure but results in an exaggerated diabetic phenotype when challenged with a high-fat diet (HFD). IKKβ-deficient mice have multiple histopathologies in visceral adipose tissue, including increased adipocyte death, amplified macrophage infiltration, and defective adaptive adipose remodeling. Deficiency of IKKβ also leads to increased adipose lipolysis, elevated plasma free fatty acid (FFA) levels, and impaired insulin signaling. Mechanistic studies demonstrated that IKKβ is a key adipocyte survival factor and that IKKβ protects murine and human adipocytes from HFD- or FFA-elicited cell death through NF-κB-dependent upregulation of antiapoptotic proteins and NF-κB-independent inactivation of proapoptotic BAD protein. Our findings establish IKKβ as critical for adipocyte survival and adaptive adipose remodeling in obesity

A Flexible 2.45-GHz Power Harvesting Wristband with Net System Output from -24.3 dBm of RF Power

This is the final version. Available from IEEE via the DOI in this recordThis paper presents a flexible 2.45-GHz wireless power harvesting wristband that generates a net dc output from a -24.3-dBm RF input. This is the lowest reported system sensitivity for systems comprising a rectenna and impedance-matching power management. A complete system has been implemented comprising: a fabric antenna, a rectifier on rigid substrate, a contactless electrical connection between rigid and flexible subsystems, and power electronics impedance matching. Various fabric and flexible materials are electrically characterized at 2.45 GHz using the two-line and the T-resonator methods. Selected materials are used to design an all-textile antenna, which demonstrates a radiation efficiency above 62% on a phantom irrespective of location, and a stable radiation pattern. The rectifier, designed on a rigid substrate, shows a best-in-class efficiency of 33.6% at -20 dBm. A reliable, efficient, and wideband contactless connection between the fabric antenna and the rectifier is created using broadside-coupled microstrip lines, with an insertion loss below 1 dB from 1.8 to over 10 GHz. A self-powered boost converter with a quiescent current of 150 nA matches the rectenna output with a matching efficiency above 95%. The maximum end-to-end efficiency is 28.7% at -7 dBm. The wristband harvester demonstrates net positive energy harvesting from -24.3 dBm, a 7.3-dB improvement on the state of the art.Engineering and Physical Sciences Research Council (EPSRC

Superconductivity. Quasiparticle mass enhancement approaching optimal doping in a high-T(c) superconductor.

In the quest for superconductors with higher transition temperatures (T(c)), one emerging motif is that electronic interactions favorable for superconductivity can be enhanced by fluctuations of a broken-symmetry phase. Recent experiments have suggested the existence of the requisite broken-symmetry phase in the high-T(c) cuprates, but the impact of such a phase on the ground-state electronic interactions has remained unclear. We used magnetic fields exceeding 90 tesla to access the underlying metallic state of the cuprate YBa2Cu3O(6+δ) over a wide range of doping, and observed magnetic quantum oscillations that reveal a strong enhancement of the quasiparticle effective mass toward optimal doping. This mass enhancement results from increasing electronic interactions approaching optimal doping, and suggests a quantum critical point at a hole doping of p(crit) ≈ 0.18.This work is supported by the US Department of Energy BES \Science at 100 T," the National Science Foundation, the State of Florida, the Natural Science and Engineering Research Council of Canada and the Canadian Institute for Advanced Research. S.E.S. ac- knowledges support from the Royal Society and the European Research Council under the European Union's Seventh Framework Programme (FP7/2007-2013) / ERC Grant Agree- ment no. 337425.This is the accepted manuscript. The final version is available at http://www.sciencemag.org/content/348/6232/317.abstract?sid=a882093c-ded2-481c-b62b-2f79a56b5689

Prognostic value of interleukin-1 receptor antagonist gene polymorphism and cytomegalovirus seroprevalence in patients with coronary artery disease

BACKGROUND: Chronic inflammatory stimuli such as cytomegalovirus (CMV) infection and various genetic polymorphisms determining the inflammatory response are assumed to be important risk factors in atherosclerosis. We investigated whether patients with stable coronary artery disease (CAD) and homozygous for allele 2 of the interleukin 1 receptor antagonist (IL-1RA) gene and seropositive for CMV represent a group particular susceptible for recurrent cardiovascular events. METHODS: In a series of 300 consecutive patients with angiographically defined CAD a prospective follow-up was conducted (mean age 57.9 years, median follow-up time 38.2 months). RESULTS: No statistically significant relationship was found between CMV serostatus and IL-1RN*2 (alone or in combination) and risk for future cardiovascular events (CVE). The hazard ratio (HR) for a CVE given positive CMV-serology and IL-1RN*2 was 1.07 (95% confidence interval (CI) 0.32–3.72) in the fully adjusted model compared to seronegative CMV patients not carrying the IL-1RN*2 allele. In this prospective cohort study involving 300 patients with angiographically defined CAD at baseline, homozygousity for allele 2 of the IL-1 RA and seropositivity to CMV alone and in combination were not associated with an increased risk for cardiovascular events during follow-up; in addition, combination of the CMV-seropositivity and IL-1RN*2 allele were not associated with a proinflammatory response CONCLUSION: Our study suggests that seropositivity to CMV and IL-1RA*2 genotype alone or in combination might not be a strong risk factor for recurrent cardiovascular events in patients with manifest CAD, and is not associated with levels of established inflammatory markers

Whole-genome association analysis of treatment response in obsessive-compulsive disorder.

Up to 30% of patients with obsessive-compulsive disorder (OCD) exhibit an inadequate response to serotonin reuptake inhibitors (SRIs). To date, genetic predictors of OCD treatment response have not been systematically investigated using genome-wide association study (GWAS). To identify specific genetic variations potentially influencing SRI response, we conducted a GWAS study in 804 OCD patients with information on SRI response. SRI response was classified as 'response' (n=514) or 'non-response' (n=290), based on self-report. We used the more powerful Quasi-Likelihood Score Test (the MQLS test) to conduct a genome-wide association test correcting for relatedness, and then used an adjusted logistic model to evaluate the effect size of the variants in probands. The top single-nucleotide polymorphism (SNP) was rs17162912 (P=1.76 × 10(-8)), which is near the DISP1 gene on 1q41-q42, a microdeletion region implicated in neurological development. The other six SNPs showing suggestive evidence of association (P<10(-5)) were rs9303380, rs12437601, rs16988159, rs7676822, rs1911877 and rs723815. Among them, two SNPs in strong linkage disequilibrium, rs7676822 and rs1911877, located near the PCDH10 gene, gave P-values of 2.86 × 10(-6) and 8.41 × 10(-6), respectively. The other 35 variations with signals of potential significance (P<10(-4)) involve multiple genes expressed in the brain, including GRIN2B, PCDH10 and GPC6. Our enrichment analysis indicated suggestive roles of genes in the glutamatergic neurotransmission system (false discovery rate (FDR)=0.0097) and the serotonergic system (FDR=0.0213). Although the results presented may provide new insights into genetic mechanisms underlying treatment response in OCD, studies with larger sample sizes and detailed information on drug dosage and treatment duration are needed