Development of a Neural Network Simulator for Studying the Constitutive Behavior of Structural Composite Materials

This paper introduces a recent development and application of a noncommercial artificial neural network (ANN) simulator with graphical user interface (GUI) to assist in rapid data modeling and analysis in the engineering diffraction field. The real-time network training/simulation monitoring tool has been customized for the study of constitutive behavior of engineering materials, and it has improved data mining and forecasting capabilities of neural networks. This software has been used to train and simulate the finite element modeling (FEM) data for a fiber composite system, both forward and inverse. The forward neural network simulation precisely reduplicates FEM results several orders of magnitude faster than the slow original FEM. The inverse simulation is more challenging; yet, material parameters can be meaningfully determined with the aid of parameter sensitivity information. The simulator GUI also reveals that output node size for materials parameter and input normalization method for strain data are critical train conditions in inverse network. The successful use of ANN modeling and simulator GUI has been validated through engineering neutron diffraction experimental data by determining constitutive laws of the real fiber composite materials via a mathematically rigorous and physically meaningful parameter search process, once the networks are successfully trained from the FEM database

Prequips—an extensible software platform for integration, visualization and analysis of LC-MS/MS proteomics data

Summary: We describe an integrative software platform, Prequips, for comparative proteomics-based systems biology analysis that: (i) integrates all information generated from mass spectrometry (MS)-based proteomics as well as from basic proteomics data analysis tools, (ii) visualizes such information for various proteomic analyses via graphical interfaces and (iii) links peptide and protein abundances to external tools often used in systems biology studies. Availability: http://prequips.sourceforge.net Contact: [email protected]

Effects of multicomponent exercise on cognitive function in older adults with amnestic mild cognitive impairment: a randomized controlled trial

BACKGROUND: To examine the effects of a multicomponent exercise program on the cognitive function of older adults with amnestic mild cognitive impairment (aMCI). METHODS: Design: Twelve months, randomized controlled trial; Setting: Community center in Japan; Participants: Fifty older adults (27 men) with aMCI ranging in age from 65 to 93 years (mean age, 75 years); Intervention: Subjects were randomized into either a multicomponent exercise (n = 25) or an education control group (n = 25). Subjects in the multicomponent exercise group exercised under the supervision of physiotherapists for 90 min/d, 2 d/wk, for a total of 80 times over 12 months. The exercises included aerobic exercises, muscle strength training, and postural balance retraining, and were conducted using multiple conditions to stimulate cognitive functions. Subjects in the control group attended three education classes regarding health during the 12-month period. Measurements were administered before, after the 6-month, and after the 12-month intervention period; Measurements: The performance measures included the mini-mental state examination, logical memory subtest of the Wechsler memory scale-revised, digit symbol coding test, letter and categorical verbal fluency test, and the Stroop color word test. RESULTS: The mean adherence to the exercise program was 79.2%. Improvements of cognitive function following multicomponent exercise were superior at treatment end (group × time interactions for the mini-mental state examination (P = 0.04), logical memory of immediate recall (P = 0.03), and letter verbal fluency test (P = 0.02)). The logical memory of delayed recall, digit symbol coding, and Stroop color word test showed main effects of time, although there were no group × time interactions. CONCLUSIONS: This study indicates that exercise improves or supports, at least partly, cognitive performance in older adults with aMCI

A Large, Cross-Sectional Observational Study of Serum BDNF, Cognitive Function, and Mild Cognitive Impairment in the Elderly

Objective: The clinical relationship between brain-derived neurotrophic factor (BDNF) and cognitive function or mild cognitive impairment (MCI) is not well understood. The purpose of this study was to identify the relationship between serum BDNF and cognitive function and MCI, and determine whether serum BDNF level might be a useful biomarker for assessing risk for MCI in older people.Materials and Methods: A total of 4463 individuals aged 65 years or older (mean age 72 years) participating in the study. We measured performance in a battery of neuropsychological and cognitive function tests; serum BDNF concentration.Results: Eight hundred twenty-seven participants (18.8%) had MCI. After adjustment for sex, age, education level, diabetes, and current smoking, serum BDNF was associated with poorer performance in the story memory, and digit symbol substitution task scores. Serum BDNF was marginally associated with the presence of MCI (OR, 95% CI: 1.41, 1.00–1.99) when BDNF was 1.5 SD lower than the mean value standardized for sex and age, education level, diabetes, and current smoking.Conclusion: Low serum BDNF was associated with lower cognitive test scores and MCI. Future prospective studies should establish the discriminative value of serum BDNF for the risk of MCI

Azide-Alkyne Huisgen [3+2] Cycloaddition Using CuO Nanoparticles

Recent developments in the synthesis of CuO nanoparticles (NPs) and their application to the [3+2] cycloaddition of azides with terminal alkynes are reviewed. With respect to the importance of click chemistry, CuO hollow NPs, CuO hollow NPs on acetylene black, water-soluble double-hydrophilic block copolymer (DHBC) nanoreactors and ZnO-CuO hybrid NPs were synthesized. Non-conventional energy sources such as microwaves and ultrasound were also applied to these click reactions, and good catalytic activity with high regioselectivity was observed. CuO hollow NPs on acetylene black can be recycled nine times without any loss of activity, and water-soluble DHBC nanoreactors have been developed for an environmentally friendly process.open6

The Distinct Metabolic Phenotype of Lung Squamous Cell Carcinoma Defines Selective Vulnerability to Glycolytic Inhibition

Adenocarcinoma (ADC) and squamous cell carcinoma (SqCC) are the two predominant subtypes of non-small cell lung cancer (NSCLC) and are distinct in their histological, molecular and clinical presentation. However, metabolic signatures specific to individual NSCLC subtypes remain unknown. Here, we perform an integrative analysis of human NSCLC tumour samples, patient-derived xenografts, murine model of NSCLC, NSCLC cell lines and The Cancer Genome Atlas (TCGA) and reveal a markedly elevated expression of the GLUT1 glucose transporter in lung SqCC, which augments glucose uptake and glycolytic flux. We show that a critical reliance on glycolysis renders lung SqCC vulnerable to glycolytic inhibition, while lung ADC exhibits significant glucose independence. Clinically, elevated GLUT1-mediated glycolysis in lung SqCC strongly correlates with high 18F-FDG uptake and poor prognosis. This previously undescribed metabolic heterogeneity of NSCLC subtypes implicates significant potential for the development of diagnostic, prognostic and targeted therapeutic strategies for lung SqCC, a cancer for which existing therapeutic options are clinically insufficient

A systems approach to prion disease

Prions cause transmissible neurodegenerative diseases and replicate by conformational conversion of normal benign forms of prion protein (PrPC) to disease-causing PrPSc isoforms. A systems approach to disease postulates that disease arises from perturbation of biological networks in the relevant organ. We tracked global gene expression in the brains of eight distinct mouse strain–prion strain combinations throughout the progression of the disease to capture the effects of prion strain, host genetics, and PrP concentration on disease incubation time. Subtractive analyses exploiting various aspects of prion biology and infection identified a core of 333 differentially expressed genes (DEGs) that appeared central to prion disease. DEGs were mapped into functional pathways and networks reflecting defined neuropathological events and PrPSc replication and accumulation, enabling the identification of novel modules and modules that may be involved in genetic effects on incubation time and in prion strain specificity. Our systems analysis provides a comprehensive basis for developing models for prion replication and disease, and suggests some possible therapeutic approaches

Robot Manipulator Motion Planning for Fast Path : Shortening and Higher Manipulability

"Sampling-based Motion Planning", "Dynamic Roadmap", "Manipulability", "Shortcut-based Algorithm", "Parallelism"prohibitionⅠ. Introduction 1 II. Manipulability-aware Motion Planning for Robot Manipulator in Dynamic Roadmap 2.1 Introduction 2 2.2 Background 3 2.2.1 Sampling-based Motion Planning 3 2.2.2 Dynamic Roadmap 4 2.2.3 Manipulability Measure 5 2.3 Manipulability-aware DRM 6 2.4 Simulations 8 2.5 Conclusion 11 III. A Parallelization Framework for Real-time Path Shortening of High-DOFs Manipulator 3.1 Introduction 12 3.2 Background 13 3.3 Parallelization Framework for Fast Path Shortening 16 3.3.1 Limitations of APSC Algorithm 16 3.3.2 Parallelization Framework for Fast Path Shortening 18 3.4 Simulations 21 3.4.1 Setup 21 3.4.2 Results 23 3.5 Conclusion 32 IV. Summary 33 References 34 요약문 38MasterdCollectio