Deposit insurance, bank incentives, and the design of regulatory policy

This paper was presented at the conference "Financial services at the crossroads: capital regulation in the twenty-first century" as part of session 6, "The role of capital regulation in bank supervision." The conference, held at the Federal Reserve Bank of New York on February 26-27, 1998, was designed to encourage a consensus between the public and private sectors on an agenda for capital regulation in the new century.Deposit insurance ; Bank investments ; Bank supervision ; Bank capital

Vaccinia virus-regulated acute phase cytokine production in human fibroblasts, U937 cells and endothelium.

The production of acute phase cytokines, interleukin 6 (IL-6), tumour necrosis factor (TNFalpha) and interleukin 1 (IL-1beta), was studied in primary cultures of human skin fibroblasts, human monocytic cell line U937 and primary cultures of human umbilical vein endothelial cells (HUVEC) after in vitro infection with vaccinia virus. Significant increase in IL-6 mRNA followed by enhanced protein secretion into the culture media was found in fibroblasts, U937 cells, and HUVEC. TNFalpha increased production in vaccinia virus infected U937 cells resembled closely the pattern of IL-6 production observed in the infected cells. Transient increase in NF-kappaB binding activity was found in the infected U937 (at 90 min) and endothelial (at 30 min) cells. Vaccinia virus induced cytokine production appeared to be transcriptional

Second-Order Belief Hidden Markov Models

Hidden Markov Models (HMMs) are learning methods for pattern recognition. The probabilistic HMMs have been one of the most used techniques based on the Bayesian model. First-order probabilistic HMMs were adapted to the theory of belief functions such that Bayesian probabilities were replaced with mass functions. In this paper, we present a second-order Hidden Markov Model using belief functions. Previous works in belief HMMs have been focused on the first-order HMMs. We extend them to the second-order model

Bona fide colour: DNA prediction of human eye and hair colour from ancient and contemporary skeletal remains

Background: DNA analysis of ancient skeletal remains is invaluable in evolutionary biology for exploring the history of species, including humans. Contemporary human bones and teeth, however, are relevant in forensic DNA analyses that deal with the identification of perpetrators, missing persons, disaster victims or family relationships. They may also provide useful information towards unravelling controversies that surround famous historical individuals. Retrieving information about a deceased person's externally visible characteristics can be informative in both types of DNA analyses. Recently, we demonstrated that human eye and hair colour can be reliably predicted from DNA using the HIrisPlex system. Here we test the feasibility of the novel HIrisPlex system at establishing eye and hair colour of deceased individuals from skeletal remains of various post-mortem time ranges and storage conditions.Methods: Twenty-one teeth between 1 and approximately 800 years of age and 5 contemporary bones were subjected to DNA extraction using standard organic protocol followed by analysis using the HIrisPlex system.Results: Twenty-three out of 26 bone DNA extracts yielded the full 24 SNP HIrisPlex profile, therefore successfully allowing model-based eye and hair colour prediction. HIrisPlex analysis of a tooth from the Polish general Władysław Sikorski (1881 to 1943) revealed blue eye colour and blond hair colour, which was positively verified from reliable documentation. The partial profiles collected in the remaining three cases (two contemporary samples and a 14th century sample) were sufficient for eye colour prediction.Conclusions: Overall, we demonstrate that the HIrisPlex system is suitable, sufficiently sensitive and robust to successfully predict eye and hair colour from ancient and contemporary skeletal remains. Our findings, therefore, highlight the HIrisPlex system as a promising tool in future routine forensic casework involving skeletal remains, including ancient DNA studies, for the prediction of eye and hair colour of deceased individuals

A compact statistical model of the song syntax in Bengalese finch

Songs of many songbird species consist of variable sequences of a finite number of syllables. A common approach for characterizing the syntax of these complex syllable sequences is to use transition probabilities between the syllables. This is equivalent to the Markov model, in which each syllable is associated with one state, and the transition probabilities between the states do not depend on the state transition history. Here we analyze the song syntax in a Bengalese finch. We show that the Markov model fails to capture the statistical properties of the syllable sequences. Instead, a state transition model that accurately describes the statistics of the syllable sequences includes adaptation of the self-transition probabilities when states are repeatedly revisited, and allows associations of more than one state to the same syllable. Such a model does not increase the model complexity significantly. Mathematically, the model is a partially observable Markov model with adaptation (POMMA). The success of the POMMA supports the branching chain network hypothesis of how syntax is controlled within the premotor song nucleus HVC, and suggests that adaptation and many-to-one mapping from neural substrates to syllables are important features of the neural control of complex song syntax

Networked buffering: a basic mechanism for distributed robustness in complex adaptive systems

A generic mechanism - networked buffering - is proposed for the generation of robust traits in complex systems. It requires two basic conditions to be satisfied: 1) agents are versatile enough to perform more than one single functional role within a system and 2) agents are degenerate, i.e. there exists partial overlap in the functional capabilities of agents. Given these prerequisites, degenerate systems can readily produce a distributed systemic response to local perturbations. Reciprocally, excess resources related to a single function can indirectly support multiple unrelated functions within a degenerate system. In models of genome:proteome mappings for which localized decision-making and modularity of genetic functions are assumed, we verify that such distributed compensatory effects cause enhanced robustness of system traits. The conditions needed for networked buffering to occur are neither demanding nor rare, supporting the conjecture that degeneracy may fundamentally underpin distributed robustness within several biotic and abiotic systems. For instance, networked buffering offers new insights into systems engineering and planning activities that occur under high uncertainty. It may also help explain recent developments in understanding the origins of resilience within complex ecosystems. \ud \u

The Origin of Phenotypic Heterogeneity in a Clonal Cell Population In Vitro

BACKGROUND: The spontaneous emergence of phenotypic heterogeneity in clonal populations of mammalian cells in vitro is a rule rather than an exception. We consider two simple, mutually non-exclusive models that explain the generation of diverse cell types in a homogeneous population. In the first model, the phenotypic switch is the consequence of extrinsic factors. Initially identical cells may become different because they encounter different local environments that induce adaptive responses. According to the second model, the phenotypic switch is intrinsic to the cells that may occur even in homogeneous environments. PRINCIPAL FINDINGS: We have investigated the “extrinsic” and the “intrinsic” mechanisms using computer simulations and experimentation. First, we simulated in silico the emergence of two cell types in a clonal cell population using a multiagent model. Both mechanisms produced stable phenotypic heterogeneity, but the distribution of the cell types was different. The “intrinsic” model predicted an even distribution of the rare phenotype cells, while in the “extrinsic” model these cells formed small clusters. The key predictions of the two models were confronted with the results obtained experimentally using a myogenic cell line. CONCLUSIONS: The observations emphasize the importance of the “ecological” context and suggest that, consistently with the “extrinsic” model, local stochastic interactions between phenotypically identical cells play a key role in the initiation of phenotypic switch. Nevertheless, the “intrinsic” model also shows some other aspects of reality: The phenotypic switch is not triggered exclusively by the local environmental variations, but also depends to some extent on the phenotypic intrinsic robustness of the cells