Learning with a mutualistic teacher

The concept of a “mutualistic teacher” is introduced for unsupervised learning of the mean vectors of the components of a mixture of multivariate normal densities, when the number of classes is also unknown. The unsupervised learning problem is formulated here as a multi-stage quasi-supervised problem incorporating a cluster approach. The mutualistic teacher creates a quasi-supervised environment at each stage by picking out “mutual pairs” of samples and assigning identical (but unknown) labels to the individuals of each mutual pair. The number of classes, if not specified, can be determined at an intermediate stage. The risk in assigning identical labels to the individuals of mutual pairs is estimated. Results of some simulation studies are presented.

Spectral Values

This series of drawings takes a diagrammatically creative approach to understanding the economic theories and personalities at the centre of the Global Financial Crisis. Mimicking the form of US currency, the work removes labels from common economic diagrams and portrays financial titans in repose as a way to express a personal and ambivalent experience of contemporary capitalism.

Beyond Gauss: Image-set matching on the Riemannian manifold of PDFs

State-of-the-art image-set matching techniques typically implicitly model each image-set with a Gaussian distribution. Here, we propose to go beyond these representations and model image-sets as probability distribution functions (PDFs) using kernel density estimators. To compare and match image-sets, we exploit Csiszar´ f-divergences, which bear strong connections to the geodesic distance defined on the space of PDFs, i.e., the statistical manifold. Furthermore, we introduce valid positive definite kernels on the statistical manifold, which let us make use of more powerful classification schemes to match image-sets. Finally, we introduce a supervised dimensionality reduction technique that learns a latent space where f-divergences reflect the class labels of the data. Our experiments on diverse problems, such as video-based face recognition and dynamic texture classification, evidence the benefits of our approach over the state-of-the-art image-set matching methods.

Surface cathepsin B protects cytotoxic lymphocytes from self-destruction after degranulation.

The granule exocytosis cytotoxicity pathway is the major molecular mechanism for cytotoxic T lymphocyte (CTL) and natural killer (NK) cytotoxicity, but the question of how these cytotoxic lymphocytes avoid self-destruction after secreting perforin has remained unresolved. We show that CTL and NK cells die within a few hours if they are triggered to degranulate in the presence of nontoxic thiol cathepsin protease inhibitors. The potent activity of the impermeant, highly cathepsin B-specific membrane inhibitors CA074 and NS-196 strongly implicates extracellular cathepsin B. CTL suicide in the presence of cathepsin inhibitors requires the granule exocytosis cytotoxicity pathway, as it is normal with CTLs from gld mice, but does not occur in CTLs from perforin knockout mice. Flow cytometry shows that CTLs express low to undetectable levels of cathepsin B on their surface before degranulation, with a substantial rapid increase after T cell receptor triggering. Surface cathepsin B eluted from live CTL after degranulation by calcium chelation is the single chain processed form of active cathepsin B. Degranulated CTLs are surface biotinylated by the cathepsin B-specific affinity reagent NS-196, which exclusively labels immunoreactive cathepsin B. These experiments support a model in which granule-derived surface cathepsin B provides self-protection for degranulating cytotoxic lymphocytes.

The supermarket of the future: Directions for Australia

Supermarkets are scrambling to effect change across stores in order to meet the needs of a changing consumer and stay ahead of their competition. If the UK, US and European market is anything to go by, our Australian supermarkets of the future will offer less choice and engagement, but more private labels, greater convenience and solutions.

Sukupolvien ongelma : Tutkielmia sukupolven käsitteestä, sukupolvitietoisuudesta ja suurista ikäluokista

The aims of the thesis are (1) to present a systematic evaluation of generation and its relevance as a sociological concept, (2) to reflect on how generational consciousness, i.e. generation as an object of collective identification that has social significance, can emerge and take shape, (3) to analyze empirically the generational experiences and consciousness of one specific generation, namely Finnish baby boomers (b. 1945 1950). The thesis contributes to the discussion on the social (as distinct from its genealogical) meaning of the concept of generation, launched by Karl Mannheim s classic Das Problem der Generationen (1928), in which the central idea is that a certain group of people is bonded together by a shared experience and that this bonding can result in a distinct self-consciousness. The thesis is comprised of six original articles and an extensive summarizing chapter. In the empirical articles, the baby boomers are studied on the basis of nationally representative survey data (N = 2628) and narrative life-story interviews (N = 38). In the article that discusses the connection of generations and social movements, the analysis is based on the member survey of Attac Finland (N = 1096). Three main themes were clarified in the thesis. (1) In the social sense the concept of generation is a modern, problematic, and ultimately a political concept. It served the interests of the intellectuals who developed the concept in the early 20th century and provided them, as an alternative to the concept of social class, a new way of think about social change and progress. The concept of generation is always coupled with the concept of Zeitgeist or some other controversial way of defining what is essential, i.e. what creates generations, in a given culture. Thus generation is, as a product of definition and classification struggles, a contested concept. The concept also clearly implies elitist connotations; the idea of some kind of vanguard (the elite) that represents an entire generation by proclaiming itself as its spokesman automatically creates a counterpart, namely the others in the peer group who are thought to be represented (the masses). (2) Generational consciousness cannot emerge as a result of any kind of automatic process or endogenously; it must be made. There has to be somebody who represents the generation in order for that generation to exist in people s minds and as an object of identification; generational experiences and their meanings must be articulated. Hence, social generations are, in a fundamental manner, discursively constructed. The articulations of generational experiences (speeches, writings, manifests, labels etc.) can be called as the discursive dimension of social generations, and through this notion, how public discourse shapes people s generational consciousness can be seen. Another important element in the process is collective memory, as generational consciousness often takes form only retrospectively. (3) Finnish baby boomers are not a united or homogeneous generation but are divided into many smaller sections with specific generational experiences and consciousnesses. The content of the generational consciousness of the baby boomers is heavily politically charged. A salient dividing line inside the age group is formed by individual attitudes towards so-called 1960s radicalism. Identification with the 1960s generation functions today as a positive self-definition of a certain small leftist elite group, and the values and characteristics usually connected with the idea of the 1960s generation do not represent the whole age group. On the contrary, among some of the members of the baby boomers, the generational identification is still directed by the experience of how traditional values were disgraced in the 1960s. As objects of identification, the neutral term baby boomers and the charged 1960s generation are totally different things, and therefore they should not be used as synonyms. Although the significance of the group of the 1960s generation is often overestimated, they are however special with respect to generational consciousness because they have presented themselves as the voice of the entire generation. Their generational interpretations have spread through the media with the help of certain iconic images of the generation insomuch that 1960s radicalism has become an indirect generational experience for other parts of the baby boom cohort as well.

Data mining approaches to software fault diagnosis

Automatic identification of software faults has enormous practical significance. This requires characterizing program execution behavior and the use of appropriate data mining techniques on the chosen representation. In this paper, we use the sequence of system calls to characterize program execution. The data mining tasks addressed are learning to map system call streams to fault labels and automatic identification of fault causes. Spectrum kernels and SVM are used for the former while latent semantic analysis is used for the latter The techniques are demonstrated for the intrusion dataset containing system call traces. The results show that kernel techniques are as accurate as the best available results but are faster by orders of magnitude. We also show that latent semantic indexing is capable of revealing fault-specific features.

Fast in-memory XPath search using compressed indexes

A large fraction of an XML document typically consists of text data. The XPath query language allows text search via the equal, contains, and starts-with predicates. Such predicates can be efficiently implemented using a compressed self-index of the document's text nodes. Most queries, however, contain some parts querying the text of the document, plus some parts querying the tree structure. It is therefore a challenge to choose an appropriate evaluation order for a given query, which optimally leverages the execution speeds of the text and tree indexes. Here the SXSI system is introduced. It stores the tree structure of an XML document using a bit array of opening and closing brackets plus a sequence of labels, and stores the text nodes of the document using a global compressed self-index. On top of these indexes sits an XPath query engine that is based on tree automata. The engine uses fast counting queries of the text index in order to dynamically determine whether to evaluate top-down or bottom-up with respect to the tree structure. The resulting system has several advantages over existing systems: (1) on pure tree queries (without text search) such as the XPathMark queries, the SXSI system performs on par or better than the fastest known systems MonetDB and Qizx, (2) on queries that use text search, SXSI outperforms the existing systems by 1-3 orders of magnitude (depending on the size of the result set), and (3) with respect to memory consumption, SXSI outperforms all other systems for counting-only queries.

Phenomenological Ginzburg-Landau-like theory for superconductivity in the cuprates

We propose and develop here a phenomenological Ginzburg-Landau-like theory of cuprate high-temperature superconductivity. The free energy of a cuprate superconductor is expressed as a functional F of the complex spin-singlet pair amplitude psi(ij) equivalent to psi(m) = Delta(m) exp(i phi(m)), where i and j are nearest-neighbor sites of the square planar Cu lattice in which the superconductivity is believed to primarily reside, and m labels the site located at the center of the bond between i and j. The system is modeled as a weakly coupled stack of such planes. We hypothesize a simple form FDelta, phi] = Sigma(m)A Delta(2)(m) + (B/2)Delta(4)(m)] + C Sigma(< mn >) Delta(m) Delta(n) cos(phi(m) - phi(n)) for the functional, where m and n are nearest-neighbor sites on the bond-center lattice. This form is analogous to the original continuum Ginzburg-Landau free-energy functional; the coefficients A, B, and C are determined from comparison with experiments. A combination of analytic approximations, numerical minimization, and Monte Carlo simulations is used to work out a number of consequences of the proposed functional for specific choices of A, B, and C as functions of hole density x and temperature T. There can be a rapid crossover of from small to large values as A changes sign from positive to negative on lowering T; this crossover temperature T-ms(x) is identified with the observed pseudogap temperature T*(x). The thermodynamic superconducting phase-coherence transition occurs at a lower temperature T-c(x), and describes superconductivity with d-wave symmetry for positive C. The calculated T-c(x) curve has the observed parabolic shape. The results for the superfluid density rho(s)(x, T), the local gap magnitude , the specific heat C-v(x, T) (with and without a magnetic field), as well as vortex properties, all obtained using the proposed functional, are compared successfully with experiments. We also obtain the electron spectral density as influenced by the coupling between the electrons and the correlation function of the pair amplitude calculated from the functional, and compare the results successfully with the electronic spectrum measured through angle resolved photoemission spectroscopy (ARPES). For the specific heat, vortex structure, and electron spectral density, only some of the final results are reported here; the details are presented in subsequent papers.

Conformational changes of the chaperone SecB upon binding to a model substrate - bovine pancreatic trypsin inhibitor (BPTI)

SecB is a homotetrameric cytosolic chaperone that forms part of the protein translocation machinery in E. coli. Due to SecB, nascent polypeptides are maintained in an unfolded translocation-competent state devoid of tertiary structure and thus are guided to the translocon. In vitro SecB rapidly binds to a variety of ligands in a non-native state. We have previously investigated the bound state conformation of the model substrate bovine pancreatic trypsin inhibitor (BPTI) as well as the conformation of SecB itself by using proximity relationships based on site-directed spin labeling and pyrene fluorescence methods. It was shown that SecB undergoes a conformational change during the process of substrate binding. Here, we generated SecB mutants containing but a single cysteine per subunit or an exposed highly reactive new cysteine after removal of the nearby intrinsic cysteines. Quantitative spin labeling was achieved with the methanethiosulfonate spin label (MTS) at positions C97 or E90C, respectively. Highfield (W-band) electron paramagnetic resonance (EPR) measurements revealed that with BPTI present the spin labels are exposed to a more polar/hydrophilic environment. Nanoscale distance measurements with double electron-electron resonance (DEER) were in excellent agreement with distances obtained by molecular modeling. Binding of BPTI also led to a slight change in distances between labels at C97 but not at E90C. While the shorter distance in the tetramer increased, the larger diagonal distance decreased. These findings can be explained by a widening of the tetrameric structure upon substrate binding much like the opening of two pairs of scissors.

MAPS: midline analysis and propagation of segmentation

Scenic word images undergo degradations due to motion blur, uneven illumination, shadows and defocussing, which lead to difficulty in segmentation. As a result, the recognition results reported on the scenic word image datasets of ICDAR have been low. We introduce a novel technique, where we choose the middle row of the image as a sub-image and segment it first. Then, the labels from this segmented sub-image are used to propagate labels to other pixels in the image. This approach, which is unique and distinct from the existing methods, results in improved segmentation. Bayesian classification and Max-flow methods have been independently used for label propagation. This midline based approach limits the impact of degradations that happens to the image. The segmented text image is recognized using the trial version of Omnipage OCR. We have tested our method on ICDAR 2003 and ICDAR 2011 datasets. Our word recognition results of 64.5% and 71.6% are better than those of methods in the literature and also methods that competed in the Robust reading competition. Our method makes an implicit assumption that degradation is not present in the middle row.

Effect of signal peptide on stability and folding of escherichia coli thioredoxin

The signal peptide plays a key role in targeting and membrane insertion of secretory and membrane proteins in both prokaryotes and eukaryotes. In E. coli, recombinant proteins can be targeted to the periplasmic space by fusing naturally occurring signal sequences to their N-terminus. The model protein thioredoxin was fused at its N-terminus with malE and pelB signal sequences. While WT and the pelB fusion are soluble when expressed, the malE fusion was targeted to inclusion bodies and was refolded in vitro to yield a monomeric product with identical secondary structure to WT thioredoxin. The purified recombinant proteins were studied with respect to their thermodynamic stability, aggregation propensity and activity, and compared with wild type thioredoxin, without a signal sequence. The presence of signal sequences leads to thermodynamic destabilization, reduces the activity and increases the aggregation propensity, with malE having much larger effects than pelB. These studies show that besides acting as address labels, signal sequences can modulate protein stability and aggregation in a sequence dependent manner.

Maltose Binding Protein Is Partially Structured in Its Molten Globule State

Seven double cysteine mutants of maltose binding protein (MBP) were generated with one each in the active cleft at position 298 and the second cysteine distributed over both domains of the protein. These cysteines were spin labeled and distances between the labels in biradical pairs determined by pulsed double electron-electron resonance (DEER) measurements. The values were compared with theoretical predictions of distances between the labels in biradicals constructed by molecular modeling from the crystal structure of MBP without maltose and were found to be in excellent agreement. MBP is in a molten globule state at pH 3.3 and is known to still bind its substrate maltose. The nitroxide spin label was sufficiently stable under these conditions. In preliminary experiments, DEER measurements were carried out with one of the mutants yielding a broad distance distribution as was to be expected if there is no explicit tertiary structure and the individual helices pointing into all possible directions.

Traffic engineered NoC for streaming applications

Streaming applications demand hard bandwidth and throughput guarantees in a multiprocessor environment amidst resource competing processes. We present a Label Switching based Network-on-Chip (LS-NoC) motivated by throughput guarantees offered by bandwidth reservation. Label switching is a packet relaying technique in which individual packets carry route information in the form of labels. A centralized LS-NoC Management framework engineers traffic into Quality of Service (QoS) guaranteed routes. LS-NoC caters to the requirements of streaming applications where communication channels are fixed over the lifetime of the application. The proposed NoC framework inherently supports heterogeneous and ad hoc system-on-chips. The LS-NoC can be used in conjunction with conventional best effort NoC as a QoS guaranteed communication network or as a replacement to the conventional NoC. A multicast, broadcast capable label switched router for the LS-NoC has been designed. A 5 port, 256 bit data bus, 4 bit label router occupies 0.431 mm(2) in 130 nm and delivers peak bandwidth of 80 Gbits/s per link at 312.5 MHz. Bandwidth and latency guarantees of LS-NoC have been demonstrated on traffic from example streaming applications and on constant and variable bit rate traffic patterns. LS-NoC was found to have a competitive AreaxPower/Throughput figure of merit with state-of-the-art NoCs providing QoS. Circuit switching with link sharing abilities and support for asynchronous operation make LS-NoC a desirable choice for QoS servicing in chip multiprocessors. (C) 2013 Elsevier B.V. All rights reserved.

Extension of TSVM to multi-class and hierarchical text classification problems With general losses

Transductive SVM (TSVM) is a well known semi-supervised large margin learning method for binary text classification. In this paper we extend this method to multi-class and hierarchical classification problems. We point out that the determination of labels of unlabeled examples with fixed classifier weights is a linear programming problem. We devise an efficient technique for solving it. The method is applicable to general loss functions. We demonstrate the value of the new method using large margin loss on a number of multi-class and hierarchical classification datasets. For maxent loss we show empirically that our method is better than expectation regularization/constraint and posterior regularization methods, and competitive with the version of entropy regularization method which uses label constraints.