News and price returns from threshold behaviour and vice-versa: exact solution of a simple agent-based market model

Starting from an exact relationship between news, threshold and price return distributions in the stationary state, I discuss the ability of the Ghoulmie-Cont-Nadal model of traders to produce fat-tailed price returns. Under normal conditions, this model is not able to transform Gaussian news into fat-tailed price returns. When the variance of the news so small that only the players with zero threshold can possibly react to news, this model produces Levy-distributed price returns with a -1 exponent. In the special case of super-linear price impact functions, fat-tailed returns are obtained from well-behaved news.Comment: 4 pages, 3 figures. This is quite possibly the final version. To appear in J. Phys

Mechanisms of Self-Organization and Finite Size Effects in a Minimal Agent Based Model

We present a detailed analysis of the self-organization phenomenon in which the stylized facts originate from finite size effects with respect to the number of agents considered and disappear in the limit of an infinite population. By introducing the possibility that agents can enter or leave the market depending on the behavior of the price, it is possible to show that the system self-organizes in a regime with a finite number of agents which corresponds to the stylized facts. The mechanism to enter or leave the market is based on the idea that a too stable market is unappealing for traders while the presence of price movements attracts agents to enter and speculate on the market. We show that this mechanism is also compatible with the idea that agents are scared by a noisy and risky market at shorter time scales. We also show that the mechanism for self-organization is robust with respect to variations of the exit/entry rules and that the attempt to trigger the system to self-organize in a region without stylized facts leads to an unrealistic dynamics. We study the self-organization in a specific agent based model but we believe that the basic ideas should be of general validity.Comment: 14 pages, 7 figure

Myocarditis and intramural coronary vasculitis in polyarteritis nodosa: an unusual treatable form of heart failure

We describe an uncommon cardiac presentation of polyarteritis nodosa. A 68-year-old woman, with a history of fatigue, weight loss, and myalgia of the lower extremities, was admitted for congestive heart failure. Coronary arteries were normal. Endomyocardial biopsy showed active lymphocytic myocarditis with associated intramural small vessels necrotizing vasculitis. The overexpression of TLR-4 and the negativity for myocardial viruses suggested an immune mediated mechanism of cardiac damage. These histologic findings associated to weight loss >4 kg not due to dieting or other factors, myalgias, and polyneuropathy, were consistent with the diagnosis of polyarteritis nodosa. Immunosuppressive treatment, consisting of cyclophosphamide and prednisolone, led to a significant improvement of cardiac function. Polyarteritis nodosa can be the cause of unexplained heart failure due to myocarditis and intramural vessels vasculitis. Its recognition is crucial to obtain a cardiac recovery with a tailored immunosuppressive treatment

Human immunodeficiency virus type 1, human protein interaction database at NCBI

The ‘Human Immunodeficiency Virus Type 1 (HIV-1), Human Protein Interaction Database’, available through the National Library of Medicine at www.ncbi.nlm.nih.gov/RefSeq/HIVInteractions, was created to catalog all interactions between HIV-1 and human proteins published in the peer-reviewed literature. The database serves the scientific community exploring the discovery of novel HIV vaccine candidates and therapeutic targets. To facilitate this discovery approach, the following information for each HIV-1 human protein interaction is provided and can be retrieved without restriction by web-based downloads and ftp protocols: Reference Sequence (RefSeq) protein accession numbers, Entrez Gene identification numbers, brief descriptions of the interactions, searchable keywords for interactions and PubMed identification numbers (PMIDs) of journal articles describing the interactions. Currently, 2589 unique HIV-1 to human protein interactions and 5135 brief descriptions of the interactions, with a total of 14 312 PMID references to the original articles reporting the interactions, are stored in this growing database. In addition, all protein–protein interactions documented in the database are integrated into Entrez Gene records and listed in the ‘HIV-1 protein interactions’ section of Entrez Gene reports. The database is also tightly linked to other databases through Entrez Gene, enabling users to search for an abundance of information related to HIV pathogenesis and replication

Turnover, account value and diversification of real traders: evidence of collective portfolio optimizing behavior

Despite the availability of very detailed data on financial market, agent-based modeling is hindered by the lack of information about real trader behavior. This makes it impossible to validate agent-based models, which are thus reverse-engineering attempts. This work is a contribution to the building of a set of stylized facts about the traders themselves. Using the client database of Swissquote Bank SA, the largest on-line Swiss broker, we find empirical relationships between turnover, account values and the number of assets in which a trader is invested. A theory based on simple mean-variance portfolio optimization that crucially includes variable transaction costs is able to reproduce faithfully the observed behaviors. We finally argue that our results bring into light the collective ability of a population to construct a mean-variance portfolio that takes into account the structure of transaction costsComment: 26 pages, 9 figures, Fig. 8 fixe

Finding motif pairs in the interactions between heterogeneous proteins via bootstrapping and boosting

<p>Abstract</p> <p>Background</p> <p>Supervised learning and many stochastic methods for predicting protein-protein interactions require both negative and positive interactions in the training data set. Unlike positive interactions, negative interactions cannot be readily obtained from interaction data, so these must be generated. In protein-protein interactions and other molecular interactions as well, taking all non-positive interactions as negative interactions produces too many negative interactions for the positive interactions. Random selection from non-positive interactions is unsuitable, since the selected data may not reflect the original distribution of data.</p> <p>Results</p> <p>We developed a bootstrapping algorithm for generating a negative data set of arbitrary size from protein-protein interaction data. We also developed an efficient boosting algorithm for finding interacting motif pairs in human and virus proteins. The boosting algorithm showed the best performance (84.4% sensitivity and 75.9% specificity) with balanced positive and negative data sets. The boosting algorithm was also used to find potential motif pairs in complexes of human and virus proteins, for which structural data was not used to train the algorithm. Interacting motif pairs common to multiple folds of structural data for the complexes were proven to be statistically significant. The data set for interactions between human and virus proteins was extracted from BOND and is available at <url>http://virus.hpid.org/interactions.aspx</url>. The complexes of human and virus proteins were extracted from PDB and their identifiers are available at <url>http://virus.hpid.org/PDB_IDs.html</url>.</p> <p>Conclusion</p> <p>When the positive and negative training data sets are unbalanced, the result via the prediction model tends to be biased. Bootstrapping is effective for generating a negative data set, for which the size and distribution are easily controlled. Our boosting algorithm could efficiently predict interacting motif pairs from protein interaction and sequence data, which was trained with the balanced data sets generated via the bootstrapping method.</p

Antioxidant capacity of durum wheat large flour particles may be evaluated by QUENCHER_ABTS assay by adopting a proper calculation mode

Assessment of Antioxidant Capacity (AC) of foods is useful to consider cumulative/ synergistic action of all dietary antioxidants, thus providing a more integrated information than the simple sum of measurable antioxidants. Among the different AC assays, the QUENCHERABTS (QUick, Easy, New, CHEap and Reproducible) procedure is based on the direct reaction of ABTS•+ reagent with fine solid food particles without extraction of antioxidants. This assay is able to measure both soluble and insoluble antioxidants, that simultaneously come into contact with ABTS•+ molecules by either liquid–liquid or solid–liquid interactions, respectively. These interactions may change depending on the particle diameter. Usually, particles having 0.1–0.3 mm size are used. Here, AC was evaluated on whole flour (WF), derived from a mix of grains of ten durum wheat varieties, characterized by three different particle sizes: a smaller one, ≤0.2 mm (control, WF0.2), and two larger ones, ≤0.5 mm and ≤1 mm (WF0.5 and WF1, respectively). Moreover, a novel AC calculation procedure based on the slope value of the regression line of ABTS•+ response vs flour amount is presented in detail. The classical QUENCHERABTS procedure provided for WF0.2 an AC value of 42.0±2.7 μmol eq. Trolox/g d.w. A similar result was obtained for WF0.5 (38.3±0.9 μmol eq. Trolox/g d.w.), thus indicating that these large particles may be analyzed by the QUENCHERABTS assay provided that the “slope” calculation procedure is used. On the contrary, WF1 showed about half AC (20.3±0.2 μmol eq. Trolox/g d.w.), thus showing that very large particles cannot be used even adopting the “slope” calculation

Pseudomonas Genome Database: facilitating user-friendly, comprehensive comparisons of microbial genomes

Pseudomonas aeruginosa is a well-studied opportunistic pathogen that is particularly known for its intrinsic antimicrobial resistance, diverse metabolic capacity, and its ability to cause life threatening infections in cystic fibrosis patients. The Pseudomonas Genome Database (http://www.pseudomonas.com) was originally developed as a resource for peer-reviewed, continually updated annotation for the Pseudomonas aeruginosa PAO1 reference strain genome. In order to facilitate cross-strain and cross-species genome comparisons with other Pseudomonas species of importance, we have now expanded the database capabilities to include all Pseudomonas species, and have developed or incorporated methods to facilitate high quality comparative genomics. The database contains robust assessment of orthologs, a novel ortholog clustering method, and incorporates five views of the data at the sequence and annotation levels (Gbrowse, Mauve and custom views) to facilitate genome comparisons. A choice of simple and more flexible user-friendly Boolean search features allows researchers to search and compare annotations or sequences within or between genomes. Other features include more accurate protein subcellular localization predictions and a user-friendly, Boolean searchable log file of updates for the reference strain PAO1. This database aims to continue to provide a high quality, annotated genome resource for the research community and is available under an open source license