Modeling and Prediction of Driving Behaviors Using a Nonparametric Bayesian Method with AR Models

To develop a new generation advanced driver assistance system that avoids a dangerous condition in advance, we need to predict driving behaviors. Since a nonparametric Bayesian method with a two-level structure successfully predicted the symbolized behaviors only, we applied a nonparametric Bayesian method with linear dynamical systems to predicting the driving behavior. The method called the beta process autoregressive hidden Markov model (BP-AR-HMM) segments driving behaviors into states each of which corresponds to an AR model and it predicts future behaviors using the estimated future state sequence and the dynamical systems therein. Here, the segmentation as well as the parameters of the dynamical systems are determined using given training data in an unsupervised way. We carried out experiments with real driving data and found that the BP-AR-HMM predicted driving behaviors better than other methods

CNVs in Three Psychiatric Disorders

BACKGROUND: We aimed to determine the similarities and differences in the roles of genic and regulatory copy number variations (CNVs) in bipolar disorder (BD), schizophrenia (SCZ), and autism spectrum disorder (ASD). METHODS: Based on high-resolution CNV data from 8708 Japanese samples, we performed to our knowledge the largest cross-disorder analysis of genic and regulatory CNVs in BD, SCZ, and ASD. RESULTS: In genic CNVs, we found an increased burden of smaller (500 kb) exonic CNVs in SCZ/ASD. Pathogenic CNVs linked to neurodevelopmental disorders were significantly associated with the risk for each disorder, but BD and SCZ/ASD differed in terms of the effect size (smaller in BD) and subtype distribution of CNVs linked to neurodevelopmental disorders. We identified 3 synaptic genes (DLG2, PCDH15, and ASTN2) as risk factors for BD. Whereas gene set analysis showed that BD-associated pathways were restricted to chromatin biology, SCZ and ASD involved more extensive and similar pathways. Nevertheless, a correlation analysis of gene set results indicated weak but significant pathway similarities between BD and SCZ or ASD (r = 0.25–0.31). In SCZ and ASD, but not BD, CNVs were significantly enriched in enhancers and promoters in brain tissue. CONCLUSIONS: BD and SCZ/ASD differ in terms of CNV burden, characteristics of CNVs linked to neurodevelopmental disorders, and regulatory CNVs. On the other hand, they have shared molecular mechanisms, including chromatin biology. The BD risk genes identified here could provide insight into the pathogenesis of BD

Anisotropic Magnetoresistance of Ni-Co-Fe Alloy Nanowires Electrodeposited into Anodized Aluminium Oxide Membrane Thin Films

To synthesize a novel anisotropic magnetoresistance (AMR) sensor, Ni-Co, Ni-Fe, Co-Ni and Co-Fe alloy nanowires were electrodeposited into nano-channels of anodized aluminium oxide films with the thickness ranging from 20 μm to 200 μm. The growth rate of the nanowires was around 200 nm/sec at the cathode potential of -1.2 V vs. Ag/AgCl. The aspect ratio of the nanowires reached up to ca. 3,000 to 1 and the cylindrical shape was precisely transferred from the nano-channels to the nanowires. Magnetic hysteresis loops of Ni-Co, Ni-Fe, Co-Ni and Co-Fe alloy nanowires with the diameter of 60 nm showed typical perpendicular magnetization behaviour due to the uni-axial shape anisotropy and the coercive force reached up to 1 kOe. 3.2% of AMR was observed in Co-1.5%Ni alloy nanowires with the aspect ratio of 1,000.Magnetic Materials, Processes, and Devices 12 - PRiME 2012; Honolulu, HI; United States; 7 October 2012 ～ 12 October 201

Modeling and Prediction of Driving Behaviors Using a Nonparametric Bayesian Method with AR Models

To develop a new generation advanced driver assistance system that avoids a dangerous condition in advance, we need to predict driving behaviors. Since a nonparametric Bayesian method with a two-level structure successfully predicted the symbolized behaviors only, we applied a nonparametric Bayesian method with linear dynamical systems to predicting the driving behavior. The method called the beta process autoregressive hidden Markov model (BP-AR-HMM) segments driving behaviors into states each of which corresponds to an AR model and it predicts future behaviors using the estimated future state sequence and the dynamical systems therein. Here, the segmentation as well as the parameters of the dynamical systems are determined using given training data in an unsupervised way. We carried out experiments with real driving data and found that the BP-AR-HMM predicted driving behaviors better than other methods

Comparative Analyses of Copy-Number Variation in Autism Spectrum Disorder and Schizophrenia Reveal Etiological Overlap and Biological Insights

Summary: Compelling evidence in Caucasian populations suggests a role for copy-number variations (CNVs) in autism spectrum disorder (ASD) and schizophrenia (SCZ). We analyzed 1,108 ASD cases, 2,458 SCZ cases, and 2,095 controls in a Japanese population and confirmed an increased burden of rare exonic CNVs in both disorders. Clinically significant (or pathogenic) CNVs, including those at 29 loci common to both disorders, were found in about 8% of ASD and SCZ cases, which was significantly higher than in controls. Phenotypic analysis revealed an association between clinically significant CNVs and intellectual disability. Gene set analysis showed significant overlap of biological pathways in both disorders including oxidative stress response, lipid metabolism/modification, and genomic integrity. Finally, based on bioinformatics analysis, we identified multiple disease-relevant genes in eight well-known ASD/SCZ-associated CNV loci (e.g., 22q11.2, 3q29). Our findings suggest an etiological overlap of ASD and SCZ and provide biological insights into these disorders. : Kushima et al. perform comparative analyses of CNVs in ASD and SCZ in a Japanese population. They identify pathogenic CNVs and biological pathways in each disorder with significant overlap. Patients with pathogenic CNVs have a higher prevalence of intellectual disability. Disease-relevant genes are detected in eight well-known ASD/SCZ-associated CNV loci. Keywords: autism spectrum disorder, schizophrenia, copy-number variation, array comparative genomic hybridization, genetic overlap, Japanese population, oxidative stress response, genome integrity, lipid metabolism, gene ontolog

Genome-wide association meta-analysis identifies GP2 gene risk variants for pancreatic cancer

Previous genome-wide association studies have identified risk loci for pancreatic cancer but were centered on individuals of European ancestry. Here the authors identify GP2 gene variants associated with pancreatic cancer susceptibility in populations of East Asian ancestry