The dynamics of financial stability in complex networks

We address the problem of banking system resilience by applying off-equilibrium statistical physics to a system of particles, representing the economic agents, modelled according to the theoretical foundation of the current banking regulation, the so called Merton-Vasicek model. Economic agents are attracted to each other to exchange `economic energy', forming a network of trades. When the capital level of one economic agent drops below a minimum, the economic agent becomes insolvent. The insolvency of one single economic agent affects the economic energy of all its neighbours which thus become susceptible to insolvency, being able to trigger a chain of insolvencies (avalanche). We show that the distribution of avalanche sizes follows a power-law whose exponent depends on the minimum capital level. Furthermore, we present evidence that under an increase in the minimum capital level, large crashes will be avoided only if one assumes that agents will accept a drop in business levels, while keeping their trading attitudes and policies unchanged. The alternative assumption, that agents will try to restore their business levels, may lead to the unexpected consequence that large crises occur with higher probability

Crises and collective socio-economic phenomena: simple models and challenges

Financial and economic history is strewn with bubbles and crashes, booms and busts, crises and upheavals of all sorts. Understanding the origin of these events is arguably one of the most important problems in economic theory. In this paper, we review recent efforts to include heterogeneities and interactions in models of decision. We argue that the Random Field Ising model (RFIM) indeed provides a unifying framework to account for many collective socio-economic phenomena that lead to sudden ruptures and crises. We discuss different models that can capture potentially destabilising self-referential feedback loops, induced either by herding, i.e. reference to peers, or trending, i.e. reference to the past, and account for some of the phenomenology missing in the standard models. We discuss some empirically testable predictions of these models, for example robust signatures of RFIM-like herding effects, or the logarithmic decay of spatial correlations of voting patterns. One of the most striking result, inspired by statistical physics methods, is that Adam Smith's invisible hand can badly fail at solving simple coordination problems. We also insist on the issue of time-scales, that can be extremely long in some cases, and prevent socially optimal equilibria to be reached. As a theoretical challenge, the study of so-called "detailed-balance" violating decision rules is needed to decide whether conclusions based on current models (that all assume detailed-balance) are indeed robust and generic.Comment: Review paper accepted for a special issue of J Stat Phys; several minor improvements along reviewers' comment

Image analysis technique as a tool to identify morphological changes in Trametes versicolor pellets according to exopolysaccharide or laccase production

Image analysis technique was applied to identify morphological changes of pellets from white-rot fungus Trametes versicolor on agitated submerged cultures during the production of exopolysaccharide (EPS) or ligninolytic enzymes. Batch tests with four different experimental conditions were carried out. Two different culture media were used, namely yeast medium or Trametes defined medium and the addition of lignolytic inducers as xylidine or pulp and paper industrial effluent were evaluated. Laccase activity, EPS production, and final biomass contents were determined for batch assays and the pellets morphology was assessed by image analysis techniques. The obtained data allowed establishing the choice of the metabolic pathways according to the experimental conditions, either for laccase enzymatic production in the Trametes defined medium, or for EPS production in the rich Yeast Medium experiments. Furthermore, the image processing and analysis methodology allowed for a better comprehension of the physiological phenomena with respect to the corresponding pellets morphological stages.The authors acknowledge Portucel-Empresa de Celulose e Papel, Cacia, Portugal, SA for the pulp and paper Kraft effluent used in this work. This work was funded by FEDER Funds through the Programa Operacional Factores de Competitividade-COMPETE, and national funds through FCT-Fundacao para a Ciencia e a Tecnologia under the projects PEst-C/CTM/LA/0011/2013 and PEst-C/EQB/LA0020/2013. A. P. M. Tavares acknowledge the financial support of (Programme Ciencia 2008) FCT, Portugal

HPLC Analysis of Antipsychotic Asenapine in Alternative Biomatrices: Hair and Nail Clippings

Asenapine is a novel atypical antipsychotic drug for the treatment of schizophrenia and acute mania. Although some analytical methods have been published on the determination of the drug in conventional biological samples, such as blood serum and urine, there is currently no method available for alternative biomatrices, such as hair and nail clippings, which are of utmost importance in forensic and clinical toxicology. A reversed-phase analytical column, Inertsil C8, (250 × 4.0 mm) 5 μm (MZ AnalysenTechnik, Mainz, Germany), was used at ambient temperature, with a mobile phase consisting of an acetate buffer (at pH 4.5), acetonitrile and methanol, (50:40:10%, v/v). Separation was achieved isocratically at a flow rate of 1 mL/min. Quantification was performed at 240 nm. Validation of the method was performed in terms of accuracy and precision: intra-day (n = 5) and inter-day (n = 3 × 5). Recovery rates ranged between 95.0% and 102.5% in hair samples and between 98.8% and 105% in nail samples. In hair the limit of detection was 1.3 ng/mg and the limit of quantitation was 4 ng/mg, whereas in nail clippings the respective values were 2.7 ng/mg and 8 ng/mg. The method was successfully applied to hair and nail clippings, following simple sample pretreatment. © 2015 © Taylor & Francis Group, LLC

On-line SPE sample treatment as a tool for method automatization and detection limits reduction: Quantification of 25-hydroxyvitamin D3/D2

The development and approbation of new, automated UHPLC-DAD method for the quantification of 25-hydroxyvitamin D3/D2 (25OH-D3/D2) metabolites in plasma/serum for the evaluation of patient's vitamin D status are presented. The method was developed on the Ultimate 3000 UHPLC dual gradient system supplied with the on-line SPE-concentration column coupled through six port switching valve to analytical column. This configuration and materials selected enable large volume sample injection (500 μL) and on-line sample preconcentration, clean up and subsequent selective metabolites transfer onto the analytical column. The new method abrogates main conventional time consuming and error source off-line steps of analysis and thus simplifies analysis. The large volume injection increases the sensitivity of instrumental analysis by about ten-fold on-line pre-concentration of metabolites. The instrument response is linear (R > 0.99) in the investigated concentration range 10–100 ng mL−1 which covers all the possible vitamin D status from serious deficiency (<12 ng mL−1) to excess. The method detection limits (S/N = 3) are LOD (25OH-D3) = 0.94 ng mL−1 and LOD (25OH-D2) = 2.4 ng mL−1. The method performance was assessed with the use of certified reference samples and perfect agreement between certified and measured values is demonstrated. The method was applied to human samples previously analyzed for total vitamin D by Competitive Protein-binding assay and findings of the two methods are compared. © 2016 Elsevier B.V