Correlations Among Maximum Likelihood and Weighted/Unweighted Least Squares Estimators in Factor Analysis

The asymptotic correlations among maximum likelihood (ML) and various least squares (LS) estimators in factor analysis are derived. The LS estimators include the unweighted (ULS) and weighted estimators for unstandardized variables and the ULS estimators for standardized variables. The derived formulas cover the cases with restrictions on parameters. Numerical examples with simulations are provided to confirm the accuracy of the formulas and the influence of scales on the asymptotic correlations.

     

ATMPKs: a gene family of plant MAP kinases in Arabidopsis thaliana

We previously reported two cDNAs for MAP kinases (cATMPK1 and cATMPK2) from a dicot plant, Arabidopsis thaliana. We describe here the cloning and characterization of five additional cDNAs encoding novel MAP kinases in Arabidopsis, cATMPK3, cATMPK4, cATMPK5, cATMPK6, and cATMPK7. The amino acid residues corresponding to the sites of phosphorylation (Thr-Glu-Tyr) that are involved in the activation of animal MAP kinases are conserved in all the seven putative ATMPK proteins. Genes for MAP kinases in Arabidopsis constitute a family that contains more than seven members. Sequence analysis suggests that there are at least three subfamilies in the family of Arabidopsis genes for MAP kinases.     

Software‐processed edge‐ and level‐adaptive overdrive (SELAO) method for high‐quality motion pictures

Abstract— In this paper, a software‐processed edge‐ and level‐adaptive overdrive (SELAO) method, which is a novel overdrive technique that utilizes not only a temporal change of gray levels but also a spatial edge intensity of motion pictures, is proposed. The SELAO method is a software video‐processing technology to improve motion‐picture quality rendered on LCDs more than is possible with a conventional SLAO method without edge‐adaptive overdrive, and it works in real time on commonly used personal computers (PCs).     

Dynamics and organization of MAP kinase signal pathways

In the budding yeast, Saccharomyces cerevisiae, four separate but structurally related mitogen-activated protein kinase (MAPK) activation pathways are known. The best understood of these regulates mating. Pheromone binding to receptor informs cells of the proximity of a mating partner and induces differentiation to a mating competent state. The MAPK activation cascade mediating this signal is made up of Ste11 (a MEK kinase [MEKK]), Ste7 (a MAPK/ERK kinase [MEK]), and the redundant MAPK-related Fus3 and Kss1 enzymes. Another MAPK activation pathway is important for cell integrity and regulates cell wall construction. This cascade consists of Bck1 (a MEKK), the redundant Mkk1 and Mkk2 enzymes (MEKs), and Mpk1 (a MAPK). We exploited these two pathways to learn about the coordination and signal transmission fidelity of MAPK activation cascades. Two lines of evidence suggest that the activities of the mating and cell integrity pathways are coordinated during mating differentiation. First, cells deficient in Mpk1 are susceptible to lysis when they make a mating projection in response to pheromone. Second, Mpk1 activation during pheromone induction coincides with projection formation. The mechanism underlying this coordination is still unknown to us. Our working model is that projection formation generates a mobile second messenger for activation of the cell integrity pathway. Analysis of a STE7 mutation gave us some unanticipated but important insights into parameters important for fidelity of signal transmission. The Ste7 variant has a serine to proline substitution at position 368. Ste7-P368 has higher basal activity than the wild-type enzyme but still requires Ste11 for its function. Additionally, the proline substitution enables the variant to transmit the signal from mammalian Raf expressed in yeast. This novel activity suggests that Ste7-P368 is inherently more permissive than Ste7 in its interactions with MEKKs. Yet, Ste7-P368 cross function in the cell integrity pathway occurs only when it is highly overproduced or when Ste5 is missing. This behavior suggests that Ste5, which has been proposed to be a tether for the kinases in the mating pathway, contributes to Ste7 specificity and fidelity of signal transmission.     

On the ‘curiosity’ of electrical self‐heating,static charge and electromagnetic shielding effectiveness from carbon black/aluminium flakes reinforced epoxy‐resin composites

This paper shows the wide application range (such as electrical self‐heating and electromagnetic shielding effectiveness) of composites consisting of conductive carbon black/aluminum flakes (CBA) filler and epoxy insulative matrix. The effect of CBA content on the network structure of epoxy matrix was investigated in detail. Static electrical conductivity increases linearly with the increase of filler concentration at the interface in epoxy composites. The large decrease of the conductivity as a function of the temperature is analyzed in terms of the negative temperature coefficient of conductivity (NTCC) effect. The influence of viscosity, surface energy and barrier highest energy on the NTCC behaviour in the composite is also considered. Based on these results, a new interpretation is proposed to explain the NTCC phenomena by computing the swelling force among conductive phases. The correlations of conductivity during the temperature cycling and activation energy were analyzed. The effects of dynamic ageing at various temperatures on the resistivity are reported. Current–voltage–temperature characteristics for epoxy with different contents of CBA were examined in detail. A model based on the law of energy conservation is proposed to calculate the specific heat and amount of heat dissipation. The static charge of the epoxy–CBA composites was estimated. The correlation between electromagnetic wave‐shielding effectiveness (EMS), conductivity and frequency of epoxy composites with different filler contents is also discussed. Furthermore, the effect of annealing on EMS of epoxy composites was examined. © 2002 Society of Chemical Industry     

Stochastic Resonance in Recurrent Neural Network with Hopfield-Type Memory

Stochastic resonance (SR) is known as a phenomenon in which the presence of noise helps a nonlinear system in amplifying a weak (under barrier) signal. In this paper, we investigate how SR behavior can be observed in practical autoassociative neural networks with the Hopfield-type memory under the stochastic dynamics. We focus on SR responses in two systems which consist of three and 156 neurons. These cases are considered as effective double-well and multi-well models. It is demonstrated that the neural network can enhance weak subthreshold signals composed of the stored pattern trains and have higher coherence abilities between stimulus and response.     

Evidence for a Jahn-Teller distortion of Cs2NaHoCl6 at 150 mK observed by X-ray diffractometry

By means of SR X-ray diffractometry, cooperative Jahn-Teller distortion as a structural phase transformation of the first kind is directly confirmed by a splitting of Laue spots. It is understood that the degenerate ground state of a nonmagnetic doublet (₃) of Ho³⁺ in a cubic Ho-elpasolite, Fm3m(O _h ⁵ ), at least above 600 mK, is lifted up by a distortion below 150 mK, which was predicted by a splitting of the NQR spectrum and anomalies in the specific heat and magnetic susceptibility. This structural transformation shows not only the lowest transition temperature up to now, but also the greatest hysteresis specified by a Schottky-type excitation. The magnitude of the relative distortion (1/1) has been roughly estimated to be on the 2.0 · 10^–3 order of magnitude, which is much larger than the predicted value obtained from a point charge approximation. The pecularities of this transition are discussed from the viewpoint that the general theory of a structural transformation, established convincingly at high temperatures could not be easily applied.     

Development of an epileptic seizure prediction algorithm using R–R intervals with self-attentive autoencoder

Epilepsy is a neurological disorder that may affect the autonomic nervous system (ANS) from 15 to 20 min before seizure onset, and disturbances of ANS affect R–R intervals (RRI) on an electrocardiogram (ECG). This study aims to develop a machine learning algorithm for predicting focal epileptic seizures by monitoring R–R interval (RRI) data in real time. The developed algorithm adopts a self-attentive autoencoder (SA-AE), which is a neural network for time-series data. The results of applying the developed seizure prediction algorithm to clinical data demonstrated that it functioned well in most patients; however, false positives (FPs) occurred in specific participants. In a future work, we will investigate the causes of FPs and optimize the developing seizure prediction algorithm to further improve performance using newly added clinical data.

     

Phylogenetic analyses of the matrix and non-structural genes of equine influenza viruses

Matrix (M) and nonstructural (NS) genes of thirteen equine H3N8 and H7N7 influenza viruses were sequenced and analyzed from an evolutionary point of view. The M and NS genes of H3N8 viruses isolated between 1989 and 1993 evolved into two minor branch clusters, including isolates from Europe and the American continent, respectively. It was noteworthy to reveal that the nucleotide sequences of the M and NS genes of an earlier American strain showed highest homology to those of recent European viruses. "Frozen evolution" was observed in the M and NS genes of A/eq/LaPlata/1/88. It was also evident that the NS gene of an H7N7 virus from 1977 was very similar to that of a 1979-H3N8 virus, while the M gene was closest phylogenetically to that of the earliest H7N7 virus isolated in 1956. Furthermore, the M2 protein of A/eq/Newmarket/1/77 virus contained a carboxyl terminal deletion of three amino acids. The evolutionary rates of the M and NS genes of H3N8 equine influenza viruses were estimated to be 5.4 x 10(-4) and 5.1 x 10(-4) substitutions per site per year, respectively, which were slower than those of human viruses.     

Platform design for large-scale artificial market simulation and preliminary evaluation on the K computer

Artificial market simulations have the potential to be a strong tool for studying rapid and large market fluctuations and designing financial regulations. High-frequency traders, that exchange multiple assets simultaneously within a millisecond, are said to be a cause of rapid and large market fluctuations. For such a large-scale problem, this paper proposes a software or computing platform for large-scale and high-frequency artificial market simulations (Plham: /pl\(\Lambda\)m). The computing platform, Plham, enables modeling financial markets composed of various brands of assets and a large number of agents trading on a short timescale. The design feature of Plham is the separation of artificial market models (simulation models) from their execution (execution models). This allows users to define their simulation models without parallel computing expertise and to choose one of the execution models they need. This computing platform provides a prototype execution model for parallel simulations, which exploits the variety in trading frequency among traders, that is, the fact that some traders do not require up-to-date information of markets changing in millisecond order. We evaluated a prototype implementation on the K computer using up to 256 computing nodes.