Did Option Traders Predict the Korean Financial Crisis of 1997?

This paper examines KOSPI200 options prices in order to investigate whether implied volatility implicit in options prices foreshadowed the 1997 financial crisis in Korea. A set of call and put implied volatilities are examined for evidence of expectations prior to October 23, 1997 of an impending financial crisis. It is shown that implied volatilities from out-of-the-money calls were relatively higher than those from otherwise identical puts during the period preceding October 23, 1997. Thereafter, however, put implied volatilities became extremely high relative to call implied volatilities. These results indicate no strong fears about the financial crisis during the three months immediately preceding the financial crisis, so KOSPI200 options prices indicate that options traders failed to detect the financial crisis prior to October 23, 1997.Korean financial crisis, options traders

Dynamic Probabilistic Pruning:A General Framework for Hardware-Constrained Pruning at Different Granularities

Unstructured neural network pruning algorithms have achieved impressive compression ratios. However, the resulting, typically irregular sparse matrices hamper efficient hardware implementations, leading to additional memory usage and complex control logic that diminishes the benefits of unstructured pruning. This has spurred structured coarse-grained pruning solutions that prune entire feature maps or even layers, enabling efficient implementation at the expense of reduced flexibility. Here, we propose a flexible new pruning mechanism that facilitates pruning at different granularities (weights, kernels, and feature maps) while retaining efficient memory organization (e.g., pruning exactly k-out-of-n weights for every output neuron or pruning exactly k-out-of-n kernels for every feature map). We refer to this algorithm as dynamic probabilistic pruning (DPP). DPP leverages the Gumbel-softmax relaxation for differentiable k-out-of-n sampling, facilitating end-to-end optimization. We show that DPP achieves competitive compression ratios and classification accuracy when pruning common deep learning models trained on different benchmark datasets for image classification. Relevantly, the dynamic masking of DPP facilitates for joint optimization of pruning and weight quantization in order to even further compress the network, which we show as well. Finally, we propose novel information-theoretic metrics that show the confidence and pruning diversity of pruning masks within a layer.</p

Final results from the EU project AVATAR: aerodynamic modelling of 10 MW wind turbines

This paper presents final results from the EU project AVATAR in which aerodynamic models are improved and validated for wind turbines on a scale of 10 MW and more. Special attention is paid to the improvement of low fidelity engineering (BEM based) models with higher fidelity (CFD) models but also with intermediate fidelity free vortex wake (FVW) models. The latter methods were found to be a good basis for improvement of induction modelling in engineering methods amongst others for the prediction of yawed cases, which in AVATAR was found to be one of the most challenging subjects to model. FVW methods also helped to improve the prediction of tip losses. Aero-elastic calculations with BEM based and FVW based models showed that fatigue loads for normal production cases were over predicted with approximately 15% or even more. It should then be realised that the outcome of BEM based models does not only depend on the choice of engineering add-ons (as is often assumed) but it is also heavily dependent on the way the induced velocities are solved. To this end an annulus and element approach are discussed which are assessed with the aid of FVW methods. For the prediction of fatigue loads the so-called element approach is recommended but the derived yaw models rely on an annulus approach which pleads for a generalised solution method for the induced velocities

Latest results from the EU project AVATAR: aerodynamic modelling of 10 MW wind turbines

This paper presents the most recent results from the EU project AVATAR in which aerodynamic models are improved and validated for wind turbines on a scale of 10 MW and more. Measurements on a DU 00-W-212 airfoil are presented which have been taken in the pressurized DNW-HDG wind tunnel up to a Reynolds number of 15 Million. These measurements are compared with measurements in the LM wind tunnel for Reynolds numbers of 3 and 6 Million and with calculational results. In the analysis of results special attention is paid to high Reynolds numbers effects. CFD calculations on airfoil performance showed an unexpected large scatter which eventually was reduced by paying even more attention to grid independency and domain size in relation to grid topology. Moreover calculations are presented on flow devices (leading and trailing edge flaps and vortex generators). Finally results are shown between results from 3D rotor models where a comparison is made between results from vortex wake methods and BEM methods at yawed conditions

Uptake, accumulation and metabolization of the antidepressant fluoxetine by Mytilus galloprovincialis

Fluoxetine, a selective serotonin re-uptake inhibitor (SSRI) antidepressant, is among the most prescribed pharmaceutical active substances worldwide. This study aimed to assess its accumulation and metabolization in the mussel Mytillus galloprovincialis, considered an excellent sentinel species for traditional and emerging pollutants. Mussels were collected from Ria Formosa Lagoon, Portugal, and exposed to a nominal concentration of fluoxetine (75 ng L-1) for 15 days. Approximately 1 g of whole mussel soft tissues was extracted with acetonitrile:formic acid, loaded into an Oasis MCX cartridge, and fluoxetine analysed by liquid chromatography with tandem mass spectrometry (LC-MSn). After 3 days of exposure, fluoxetine was accumulated in 70% of the samples, with a mean of 2.53 ng g(-1) dry weight (d.w.) and norfluoxetine was only detected in one sample (10%), at 3.06 ng g(-1) d.w. After 7 days of exposure, the accumulation of fluoxetine and norfluoxetine increased up to 80 and 50% respectively, and their mean accumulated levels in mussel tissues were up to 4.43 and 2.85 ng g(-1) d.w., respectively. By the end of the exposure period (15 days), both compounds were detected in 100% of the samples (mean of 9.31 and 11.65 ng g(-1) d.w., respectively). Statistical analysis revealed significant accumulation differences between the 3rd and 15th day of exposure for fluoxetine, and between the 3rd and 7th against the 15th day of exposure for norfluoxetine. These results suggest that the fluoxetine accumulated in mussel tissues is likely to be metabolised into norfluoxetine with the increase of the time of exposure, giving evidence that at these realistic environmental concentrations, toxic effects of fluoxetine in mussel tissues may occur. (C) 2016 Elsevier Ltd. All rights reserved

The Caveolin-1 Connection to Cell Death and Survival

Nunez, S (Nunez, S.)[ 1,4 ] 1. Fac Med, CEMC, Lab Comunicac Celulares, Santiago, Chile. 4. Univ Talca, Fac Hlth Sci, Talca, ChileCaveolins are a family of membrane proteins required for the formation of small plasma membrane invaginations called caveolae that are implicated in cellular trafficking processes. In addition to this structural role, these scaffolding proteins modulate numerous intracellular signaling pathways; often via direct interaction with specific binding partners. Caveolin-1 is particularly well-studied in this respect and has been attributed a large variety of functions. Thus, Caveolin-1 also represents the best-characterized isoform of this family with respect to its participation in cancer. Rather strikingly, available evidence indicates that Caveolin-1 belongs to a select group of proteins that function, depending on the cellular settings, both as tumor suppressor and promoter of cellular traits commonly associated with enhanced malignant behavior, such as metastasis and multi-drug resistance. The mechanisms underlying such ambiguity in Caveolin-1 function constitute an area of great interest. Here, we will focus on discussing how Caveolin-1 modulates cell death and survival pathways and how this may contribute to a better understanding of the ambiguous role this protein plays in cancer