Mitsubishi Group (Japan)

Bacillus subtilis is the best-characterized member of the Gram-positive bacteria. Its genome of 4,214,810 base pairs comprises 4,100 protein-coding genes. Of these protein-coding genes, 53% are represented once, while a quarter of the genome corresponds to several gene families that have been greatly expanded by gene duplication, the largest family containing 77 putative ATP-binding transport proteins. In addition, a large proportion of the genetic capacity is devoted to the utilization of a variety of carbon sources, including many plant-derived molecules. The identification of five signal peptidase genes, as well as several genes for components of the secretion apparatus, is important given the capacity of Bacillus strains to secrete large amounts of industrially important enzymes. Many of the genes are involved in the synthesis of secondary metabolites, including antibiotics, that are more typically associated with Streptomyces species. The genome contains at least ten prophages or remnants of prophages, indicating that bacteriophage infection has played an important evolutionary role in horizontal gene transfer, in particular in the propagation of bacterial pathogenesis.

We present a methodology for analyzing polyphonic musical passages comprised of notes that exhibit a harmonically fixed spectral profile (such as piano notes). Taking advantage of this unique note structure, we can model the audio content of the musical passage by a linear basis transform and use non-negative matrix decomposition methods to estimate the spectral profile and the temporal information of every note. This approach results in a very simple and compact system that is not knowledge-based, but rather learns notes by observation.

Silver nanoparticles were produced by laser ablation of a metal silver plate in an aqueous solution of sodium dodecyl sulfate, C 12 H 25 OSO 3 Na. The absorption spectrum of the silver nanoparticles is found to be essentially the same as that of silver nanoparticles chemically prepared in a solution. The size distribution of the nanoparticles measured by an electron microscope shifts to a smaller size with increase in the concentration of sodium dodecyl sulfate and with a decrease in the irradiation laser power. These findings are explained by a scheme that the nanoparticles are formed via rapid formation of an embryonic silver particle and a consecutive slow particle growth in competition with termination of the growth due to SDS coating on the particle.

The technology of intelligent agents and multi-agent systems is expected to alter radically the way in which complex, distributed, open systems are conceptualised and implemented. The paper considers the problem of building a multi-agent system as a software engineering enterprise. Three issues are focused on: how agents might be specified; how these specifications might be refined or otherwise transformed into efficient implementations; and how implemented agents and multi-agent systems might subsequently be verified, to show that they are correct with respect to their specifications. These issues are discussed with reference to a number of case studies. The paper concludes by setting out some issues and open problems for future research.

The mushroom body (MB) is an important centre for higher order sensory integration and learning in insects. To analyse the development and organisation of the MB neuropile in Drosophila, we performed cell lineage analysis in the adult brain with a new technique that combines the Flippase (flp)/FRT system and the GAL4/UAS system. We showed that the four mushroom body neuroblasts (MBNbs) give birth exclusively to the neurones and glial cells of the MB, and that each of the four MBNb clones contributes to the entire MB structure. The expression patterns of 19 GAL4 enhancer-trap strains that mark various subsets of MB cells revealed overlapping cell types in all four of the MBNb lineages. Partial ablation of MBNbs using hydroxyurea showed that each of the four neuroblasts autonomously generates the entire repertoire of the known MB substructures.

Knock-in embryonic stem (ES) cells, in which GFP or lacZ was expressed from the endogenous mouse vasa homolog (Mvh), which is specifically expressed in differentiating germ cells, were used to visualize germ cell production during in vitro differentiation. The appearance of MVH-positive germ cells depended on embryoid body formation and was greatly enhanced by the inductive effects of bone morphogenic protein 4-producing cells. The ES-derived MVH-positive cells could participate in spermatogenesis when transplanted into reconstituted testicular tubules, demonstrating that ES cells can produce functional germ cells in vitro. In vitro germ cell differentiation provides a paradigm for studying the molecular basis of germ line establishment, as well as for developing new approaches to reproductive engineering.

The expression of the genes for the major outer membrane proteins OmpF and OmpC are osmoregulated. The ompC locus was found to be transcribed bidirectionally under conditions of high osmolarity and a 174-base transcript encoded upstream of ompC was found to inhibit the OmpF production and to substantially reduce the amount of the ompF mRNA. This RNA [mRNA-interfering complementary RNA (micRNA)] has a long sequence that is complementary to the 5' end region of the ompF mRNA. We propose that the micRNA inhibits the translation of the ompF mRNA by hybridizing with it. This RNA interaction may cause premature termination of the transcription of the ompF gene or destabilization of the ompF mRNA or both.

Throughout this article, we concentrate on the transcoding of block-based video coding schemes that use hybrid discrete cosine transform (DCT) and motion compensation (MC). In such schemes, the frames of the video sequence are divided into macroblocks (MBs), where each MB typically consists of a luminance block (e.g., of size 16 × 16, or alternatively, four 8 × 8 blocks) along with corresponding chrominance blocks (e.g., 8 × 8 Cb and 8 × 8 Cr). This article emphasizes the processing that is done on the luminance components of the video. In general, the chrominance components can be handled similarly and will not be discussed in this article. We first provide an overview of the techniques used for bit-rate reduction and the corresponding architectures that have been proposed. Then, we describe the advances regarding spatial and temporal resolution reduction techniques and architectures. Additionally, an overview of error resilient transcoding is also provided, as well as a discussion of scalable coding techniques and how they relate to video transcoding. Finally, the article ends with concluding remarks, including pointers to other works on video transcoding that have not been covered in this article, as well as some future directions.

The compressive sensing (CS) framework aims to ease the burden on analog-to-digital converters (ADCs) by reducing the sampling rate required to acquire and stably recover sparse signals. Practical ADCs not only sample but also quantize each measurement to a finite number of bits; moreover, there is an inverse relationship between the achievable sampling rate and the bit depth. In this paper, we investigate an alternative CS approach that shifts the emphasis from the sampling rate to the number of bits per measurement. In particular, we explore the extreme case of 1-bit CS measurements, which capture just their sign. Our results come in two flavors. First, we consider ideal reconstruction from noiseless 1-bit measurements and provide a lower bound on the best achievable reconstruction error. We also demonstrate that i.i.d. random Gaussian matrices provide measurement mappings that, with overwhelming probability, achieve nearly optimal error decay. Next, we consider reconstruction robustness to measurement errors and noise and introduce the binary$\epsilon $-stable embedding property, which characterizes the robustness of the measurement process to sign changes. We show that the same class of matrices that provide almost optimal noiseless performance also enable such a robust mapping. On the practical side, we introduce the binary iterative hard thresholding algorithm for signal reconstruction from 1-bit measurements that offers state-of-the-art performance.

The recently introduced theory of compressive sensing enables the recovery of sparse or compressible signals from a small set of nonadaptive, linear measurements. If properly chosen, the number of measurements can be much smaller than the number of Nyquist-rate samples. Interestingly, it has been shown that random projections are a near-optimal measurement scheme. This has inspired the design of hardware systems that directly implement random measurement protocols. However, despite the intense focus of the community on signal recovery, many (if not most) signal processing problems do not require full signal recovery. In this paper, we take some first steps in the direction of solving inference problems-such as detection, classification, or estimation-and filtering problems using only compressive measurements and without ever reconstructing the signals involved. We provide theoretical bounds along with experimental results.

Restricted expression of a mouse Vasa homolog gene (Mvh) expression is first detected in primordial germ cells (PGCs) after colonization of the genital ridges. Subsequently, Mvh is maintained until postmeiotic germ cells are formed. Here, we demonstrate that male mice homozygous for a targeted mutation of Mvh exhibit a reproductive deficiency. Male homozygotes produce no sperm in the testes, where premeiotic germ cells cease differentiation by the zygotene stage and undergo apoptotic death. In addition, the proliferation of PGCs that colonize homozygous male gonads is significantly hampered, and OCT-3/4 expression appears to be reduced. These results indicate that the loss of Mvh function causes a deficiency in the proliferation and differentiation of mouse male germ cells.

Gold nanoparticles were produced by laser ablation of a gold metal plate in an aqueous solution of sodium dodecyl sulfate. The absorption spectrum of the gold nanoparticles was essentially same as that of gold nanoparticles chemically prepared in a solution. The size distribution of the nanoparticles thus produced was measured by an electron microscope and was found to shift to a smaller size with an increase in surfactant concentration. This behavior is explained in terms of the dynamic formation model. Dependence of the nanoparticle abundance on surfactant concentration in the solution shows that stable gold nanoparticles tend to be formed as the surfactant concentration exceeds 10 -5 M. The gold nanoparticles having diameters larger than 5 nm were pulverized into those having diameters of 1−5 nm by a 532-nm laser.

The biochemistry of amyloid proteins has been a fascinating and important area of research because of its contribution to our understanding of protein folding dynamics and assembly and of the pathogenetic mechanisms of human disease. One such disease is AD,2 the most common neurodegenerative disorder of aging. In AD, Aβ (Fig. 1A), which is expressed normally and ubiquitously throughout life as a 40–42-residue peptide, forms fibrils that deposit in the brain as “amyloid plaques.” This pathologic deposition process led researchers to investigate fibril formation as a target for therapeutic intervention.

Nonlinear support vector machines (SVMs) are investigated for appearance-based gender classification with low-resolution "thumbnail" faces processed from 1,755 images from the FERET (FacE REcognition Technology) face database. The performance of SVMs (3.4% error) is shown to be superior to traditional pattern classifiers (linear, quadratic, Fisher linear discriminant, nearest-neighbor) as well as more modern techniques, such as radial basis function (RBF) classifiers and large ensemble-RBF networks. Furthermore, the difference in classification performance with low-resolution "thumbnails" (21/spl times/12 pixels) and the corresponding higher-resolution images (84/spl times/48 pixels) was found to be only 1%, thus demonstrating robustness and stability with respect to scale and the degree of facial detail.

Mushroom bodies are prominent neuropils found in annelids and in all arthropod groups except crustaceans. First explicitly identified in 1850, the mushroom bodies differ in size and complexity between taxa, as well as between different castes of a single species of social insect. These differences led some early biologists to suggest that the mushroom bodies endow an arthropod with intelligence or the ability to execute voluntary actions, as opposed to innate behaviors. Recent physiological studies and mutant analyses have led to divergent interpretations. One interpretation is that the mushroom bodies conditionally relay to higher protocerebral centers information about sensory stimuli and the context in which they occur. Another interpretation is that they play a central role in learning and memory. Anatomical studies suggest that arthropod mushroom bodies are predominately associated with olfactory pathways except in phylogenetically basal insects. The prominent olfactory input to the mushroom body calyces in more recent insect orders is an acquired character. An overview of the history of research on the mushroom bodies, as well as comparative and evolutionary considerations, provides a conceptual framework for discussing the roles of these neuropils.

One of the principal bottlenecks in applying learning techniques to classification problems is the large amount of labeled training data required. Especially for images and video, providing training data is very expensive in terms of human time and effort. In this paper we propose an active learning approach to tackle the problem. Instead of passively accepting random training examples, the active learning algorithm iteratively selects unlabeled examples for the user to label, so that human effort is focused on labeling the most “useful” examples. Our method relies on the idea of uncertainty sampling, in which the algorithm selects unlabeled examples that it finds hardest to classify. Specifically, we propose an uncertainty measure that generalizes margin-based uncertainty to the multi-class case and is easy to compute, so that active learning can handle a large number of classes and large data sizes efficiently. We demonstrate results for letter and digit recognition on datasets from the UCI repository, object recognition results on the Caltech-101 dataset, and scene categorization results on a dataset of 13 natural scene categories. The proposed method gives large reductions in the number of training examples required over random selection to achieve similar classification accuracy, with little computational overhead.

Background and Aims Although the majority of patients with non-alcoholic fatty liver disease (NAFLD) have only steatosis without progression, a sizeable fraction develop non-alcoholic steatohepatitis (NASH), which can lead to cirrhosis and hepatocellular carcinoma (HCC). Many established diet-induced mouse models for NASH require 24–52 weeks, which makes testing for drug response costly and time consuming. Methods We have sought to establish a murine NASH model with rapid progression of extensive fibrosis and HCC by using a western diet (WD), which is high-fat, high-fructose and high-cholesterol, combined with low weekly dose of intraperitoneal carbon tetrachloride (CCl 4 ), which serves as an accelerator. Results C57BL/6J mice were fed a normal chow diet ± CCl 4 or WD ± CCl 4 for 12 and 24 weeks. Addition of CCl 4 exacerbated histological features of NASH, fibrosis, and tumor development induced by WD, which resulted in stage 3 fibrosis at 12 weeks and HCC development at 24 weeks. Furthermore, whole liver transcriptomic analysis indicated that dysregulated molecular pathways in WD/CCl 4 mice and immunologic features were similar to those of human NASH. Conclusions Our mouse NASH model exhibits rapid progression of advanced fibrosis and HCC, and mimics histological, immunological and transcriptomic features of human NASH, suggesting that it will be a useful experimental tool for preclinical drug testing. Lay summary A carefully characterized model has been developed in mice that recapitulates the progressive stages of human fatty liver disease, from simple steatosis, to inflammation, fibrosis and cancer. The functional pathways of gene expression and immune abnormalities in this model closely resemble human disease. The ease and reproducibility of this model make it ideal to study disease pathogenesis and test new treatments.

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) was released to the public in My 2009. The GDEM version 2, currently under development, is reproduced using an updated algorithm and contains new ASTER data observed after September 2008. Validation study of the trial and beta version of GDEM version 2 was carried out to investigate its characteristics such as geolocation error, elevation error and horizontal resolution. The results of the study confirmed that elevation offset and horizontal resolution will be greatly improved in version 2 and the enhanced horizontal resolution will serve to reduce the standard deviation of elevation and geolocation error.

Silver nanoparticles were produced by laser ablation of a metal silver plate in aqueous solutions of surfactants, C n H 2 n +1 SO 4 Na ( n = 8, 10, 12, 16). The nanoparticles thus produced were characterized by electron microscopy and UV−visible absorption spectroscopy. The abundances of the nanoparticles before and after centrifugation were measured as a function of the surfactant concentration. The concentration dependence of the abundance implies that the surfactant coverage and the charge state on the nanoparticle surface are closely related to the stability of the nanoparticles in the solutions. The nanoparticles tend to be aggregated when the coverage is less than unity, while they are very stable when the surface is covered with a double layer of the surfactant molecules.

The solid electrolyte interface (SEI) formation on composite graphite and highly oriented pyrolytic graphite in a vinylene carbonate (VC)-containing electrolyte was analyzed using evolved gas analysis, Fourier transform infrared analysis, two-dimensional nuclear magnetic resonance, X-ray photoelectron spectroscopy, time of flight-secondary-ion mass spectrometry, and scanning electron microscopy. We found that the SEI layers derived from VC-containing electrolytes consist of polymer species such as poly (vinylene carbonate) (poly(VC)), an oligomer of VC, a ring-opening polymer of VC, and polyacetylene. Moreover, lithium vinylene dicarbonate, lithium divinylene dicarbonate, lithium divinylene dialkoxide, and lithium carboxylate, RCOOLi, were formed on graphite as VC reduction products. The presence of VC in the ethylene carbonate (EC)-based electrolyte caused a decrease in the reductive gases of the EC dimethyl carbonate solvent such as and CO. The VC-derived SEI layer was formed at a potential more positive than 1.0 V vs. Effective SEI formation by reduction of VC progresses before that of EC. The thermal decomposition temperature of the SEI layer derived from VC shifted to a higher temperature compared to that derived from the VC-free electrolytes. We concluded that the thermal stability of the VC-derived SEI layer has a close relation to high-temperature storage characteristics at elevated temperatures. © 2004 The Electrochemical Society. All rights reserved.