Genetic algorithm based deep learning neural network structure and hyperparameter optimization

Alzheimer’s disease is one of the major challenges of population ageing, and diagnosis and prediction of the disease through various biomarkers is the key. While the application of deep learning as imaging technologies has recently expanded across the medical industry, empirical design of these technologies is very difficult. The main reason for this problem is that the performance of the Convolutional Neural Networks (CNN) differ greatly depending on the statistical distribution of the input dataset. Different hyperparameters also greatly affect the convergence of the CNN models. With this amount of information, selecting appropriate parameters for the network structure has became a large research area. Genetic Algorithm (GA), is a very popular technique to automatically select a high-performance network architecture. In this paper, we show the possibility of optimising the network architecture using GA, where its search space includes both network structure configuration and hyperparameters. To verify the performance of our Algorithm, we used an amyloid brain image dataset that is used for Alzheimer’s disease diagnosis. As a result, our algorithm outperforms Genetic CNN by 11.73% on a given classification task.</jats:p

Chemical ordering in PtNi nanocrystals

We investigated the chemical ordering in PtNi nanocrystals fabricated on sapphire substrate using in-situ synchrotron X-ray scattering. Nanocrystals with composition close to 1:1 were ordered in the tetragonal L1(0) structure at low temperatures. The transition to disordered FCC structure occurred at around 640 degrees C and substantial hysteresis of about 50 K was observed. Nanocrystals of smaller sizes fabricated under the same conditions were Ni rich and ordered into Cu3Au type L1(2) structure. Significantly higher degree of chemical ordering was observed in L1(2) structure than in L1(0) structure. (C) 2016 Elsevier B.V. All rights reserved.1144Ysciescopu

Multidimensional Assessment of Asthma Identifies Clinically Relevant Phenotype Overlap: A Cross-Sectional Study.

BACKGROUND:Asthma is a heterogeneous disease with multiple phenotypes; however, the relevance of phenotype overlap remains largely unexplored. OBJECTIVE:To examine the relationship between phenotype overlap and clinical and inflammatory profiles of asthma. METHODS:In this cross-sectional study, adult participants with stable asthma (n = 522) underwent multidimensional assessments. The 10 most common phenotypes of asthma were defined and then classified into those commonly associated with Type (T) 2 or non-T2 inflammation. Furthermore, phenotype overlap scores (POS), representing the cumulative concomitant phenotypes, were used to analyze its association with clinical and inflammatory asthmatic profiles. RESULTS:Among the 522 participants, 73.4% (n = 383) had phenotype overlap, and mixed T2 and non-T2 inflammation coexisted in 47.5% (n = 248). T2 POS was positively associated with eosinophils, IgE, and fractional exhaled nitric oxide (FeNO), and negatively with Asthma Quality of Life Questionnaire (AQLQ), sputum neutrophils, IL-17A, IL-8, and TNF-α. Non-T2 POS was positively associated with Asthma Control Questionnaire, neutrophils and sputum IL-8, and negatively with AQLQ, forced expiratory volume in 1 s, blood eosinophils, IgE, and FeNO (all P < .05). Patients with phenotypes that are associated with mixed T2 and non-T2 inflammation had elevated T2 inflammation biomarkers but worse asthma control. Both T2 (adjusted β = -0.191, P = .035) and non-T2 (adjusted β = 0.310, P < .001) POS were significantly associated with severe exacerbations. CONCLUSIONS:Phenotype overlap is extremely common in asthmatic patients and significantly associated with clinical and inflammatory profiles. Patients with phenotypes associated with mixed T2 and non-T2 inflammation might be unresponsive to medications owing to increased non-T2 inflammation. Multidimensional asthma assessment identifies clinically relevant phenotype overlap

Experimental Characterization Of Electrical Current Leakage In Poly(Dimethylsiloxane) Microfluidic Devices

Poly(dimethylsiloxane) (PDMS) is usually considered as a dielectric material and the PDMS microchannel wall can be treated as an electrically insulated boundary in an applied electric field. However, in certain layouts of microfluidic networks, electrical leakage through the PDMS microfluidic channel walls may not be negligible, which must be carefully considered in the microfluidic circuit design. In this paper, we report on the experimental characterization of the electrical leakage current through PDMS microfluidic channel walls of different configurations. Our numerical and experimental studies indicate that for tens of microns thick PDMS channel walls, electrical leakage through the PDMS wall could significantly alter the electrical field in the main channel. We further show that we can use the electrical leakage through the PDMS microfluidic channel wall to control the electrolyte flow inside the microfluidic channel and manipulate the particle motion inside the microfluidic channel. More specifically, we can trap individual particles at different locations inside the microfluidic channel by balancing the electroosmotic flow and the electrophoretic migration of the particle

Diseleno[3,2-b:2′,3′-d]selenophene-containing high-mobility conjugated polymer for organic field-effect transistors

KGaA, Weinheim The synthesis of a diseleno[3,2-b:2′,3′-d]selenophene (DSS) composed of three fused selenophenes is reported and it is used as a building block for the preparation of a high hole mobility conjugated polymer (PDSSTV). The polymer demonstrates strong intermolecular interactions even in solution, despite steric repulsion between the large Se atom in DSS and adjacent (C β )–H atoms which leads to a partially twisted confirmation PDSSTV. Nevertheless, 2D grazing incidence X-ray diffraction (2D-GIXD) analysis reveals that the polymer tends to align in a highly ordered edge-on orientation after thermal annealing. The polymer demonstrates promising performance in a field-effect transistor device with saturated hole mobility up to 2 cm 2 V −1 s −1 obtained under relatively low gate voltages of −30 V. The ultilization of a Se-containing fused aromatic system, therefore, appears to be a promising avenue for the development of high-performance conjugated polymers

Crude incidence in two-phase designs in the presence of competing risks.

BackgroundIn many studies, some information might not be available for the whole cohort, some covariates, or even the outcome, might be ascertained in selected subsamples. These studies are part of a broad category termed two-phase studies. Common examples include the nested case-control and the case-cohort designs. For two-phase studies, appropriate weighted survival estimates have been derived; however, no estimator of cumulative incidence accounting for competing events has been proposed. This is relevant in the presence of multiple types of events, where estimation of event type specific quantities are needed for evaluating outcome.MethodsWe develop a non parametric estimator of the cumulative incidence function of events accounting for possible competing events. It handles a general sampling design by weights derived from the sampling probabilities. The variance is derived from the influence function of the subdistribution hazard.ResultsThe proposed method shows good performance in simulations. It is applied to estimate the crude incidence of relapse in childhood acute lymphoblastic leukemia in groups defined by a genotype not available for everyone in a cohort of nearly 2000 patients, where death due to toxicity acted as a competing event. In a second example the aim was to estimate engagement in care of a cohort of HIV patients in resource limited setting, where for some patients the outcome itself was missing due to lost to follow-up. A sampling based approach was used to identify outcome in a subsample of lost patients and to obtain a valid estimate of connection to care.ConclusionsA valid estimator for cumulative incidence of events accounting for competing risks under a general sampling design from an infinite target population is derived

Interactions among mitochondrial proteins altered in glioblastoma

Mitochondrial dysfunction is putatively central to glioblastoma (GBM) pathophysiology but there has been no systematic analysis in GBM of the proteins which are integral to mitochondrial function. Alterations in proteins in mitochondrial enriched fractions from patients with GBM were defined with label-free liquid chromatography mass spectrometry. 256 mitochondrially-associated proteins were identified in mitochondrial enriched fractions and 117 of these mitochondrial proteins were markedly (fold-change &#8805;2) and significantly altered in GBM (p &#8804; 0.05). Proteins associated with oxidative damage (including catalase, superoxide dismutase 2, peroxiredoxin 1 and peroxiredoxin 4) were increased in GBM. Protein–protein interaction analysis highlighted a reduction in multiple proteins coupled to energy metabolism (in particular respiratory chain proteins, including 23 complex-I proteins). Qualitative ultrastructural analysis in GBM with electron microscopy showed a notably higher prevalence of mitochondria with cristolysis in GBM. This study highlights the complex mitochondrial proteomic adjustments which occur in GBM pathophysiology

Vectorial dissipative solitons in vertical-cavity surface-emitting Lasers with delays

We show that the nonlinear polarization dynamics of a vertical-cavity surface-emitting laser placed into an external cavity leads to the formation of temporal vectorial dissipative solitons. These solitons arise as cycles in the polarization orientation, leaving the total intensity constant. When the cavity round-trip is much longer than their duration, several independent solitons as well as bound states (molecules) may be hosted in the cavity. All these solutions coexist together and with the background solution, i.e. the solution with zero soliton. The theoretical proof of localization is given by the analysis of the Floquet exponents. Finally, we reduce the dynamics to a single delayed equation for the polarization orientation allowing interpreting the vectorial solitons as polarization kinks.Comment: quasi final resubmission version, 12 pages, 9 figure

Magnetic Fluffy Dark Matter

We explore extensions of inelastic Dark Matter and Magnetic inelastic Dark Matter where the WIMP can scatter to a tower of heavier states. We assume a WIMP mass $m_\chi \sim \mathcal{O}(1-100)$ GeV and a constant splitting between successive states $\delta \sim\mathcal{O}(1 - 100)$ keV. For the spin-independent scattering scenario we find that the direct experiments CDMS and XENON strongly constrain most of the DAMA/LIBRA preferred parameter space, while for WIMPs that interact with nuclei via their magnetic moment a region of parameter space corresponding to $m_{\chi}\sim 11$ GeV and $\delta < 15$ keV is allowed by all the present direct detection constraints.Comment: 16 pages, 6 figures, added comments about magnetic moment form factor to Sec 3.1.2 and results to Sec 3.2.2, final version to be published in JHE