Deterring Holdout Creditors in a Restructuring of PDVSA Bonds and Promissory Notes (¿Cómo disuadir a acreedores \u27holdout\u27 en una restructuración de bonos y pagarés de PDVSA?)

The prospect of the potential mischief that may be caused by holdout creditors in a Venezuelan sovereign debt restructuring is probably the main reason why the Maduro administration has not attempted such an exercise. The next administration in Venezuela — whenever and however it may arrive — will not want for suggestions about how to minimize or neutralize this holdout creditor threat. This short article is another contribution to that growing literature. Were the Republic of Venezuela to acknowledge that there really is only one public sector credit risk in the country, and that the distinction between Republic bonds and PDVSA bonds is an artificial construct, the Republic could offer to exchange PDVSA bonds for new Republic bonds at par. This would be the preliminary to a generalized debt restructuring of some kind affecting all outstanding bonds. The question will be, as it always is, how to discourage PDVSA creditors from declining to participate in such an exchange offer. One method might be for PDVSA to pledge all of its assets to the Republic in consideration for the Republic\u27s assumption of PDVSA\u27s indebtedness under its outstanding bonds and promissory notes. This is a step expressly permitted by PDVSA\u27s bonds and promissory notes. Existing PDVSA creditors would be perfectly free to decline to exchange their exposure for new Republic bonds, but they would face the prospect that a senior lienholder (the Republic) would have a first priority claim over any PDVSA assets that the holdout may attempt to attach to satisfy a judgment against PDVSA. That realization should make them think twice about the wisdom of holding out. Los cálculos sobre el potencial daño que los acreedores “holdout” podrían ocasionar en una restructuración de la deuda soberana de Venezuela son probablemente las razones más importantes por las cuales el gobierno de Maduro no ha intentado aún este ejercicio. Al próximo gobierno venezolano – cuando quiera y como quiera que esto ocurra — no le faltará asesoría sobre las distintas opciones para poder minimizar o neutralizar la amenaza que representan estos acreedores “holdout”. Este breve artículo pretende ser una contribución más a la literatura creciente sobre el tema. En el supuesto que la República de Venezuela reconozca que en el país existe, en realidad, un único riesgo crediticio del sector público y que la distinción entre los bonos de la República y los bonos de PDVSA es una construcción artificial, la República podría ofrecer un intercambio de los bonos existentes de PDVSA por bonos nuevos de la República a valor nominal. Esta oferta de intercambio, de hacerla, sería de alguna manera el preámbulo a una restructuración general de la deuda que incluiría todos los bonos vigentes pendientes. La pregunta será, como siempre, ¿cómo persuadir a los acreedores de PDVSA para que participen en una oferta de intercambio de este tipo? Un método para hacerlo podría ser que PDVSA pignore todos sus activos a favor de la República en contraprestación para que, a su vez, la República se subrogue en la totalidad de las obligaciones de PDVSA documentada en bonos y pagarés. Esta posibilidad está expresamente permitida en la documentación de los bonos y pagarés de PDVSA. Consecuentemente, los actuales acreedores tendrían la plena libertad de declinar intercambiar sus acreencias por bonos nuevos de la República. Sin embargo, de hacerlo, tendrían que asumir la posibilidad que un acreedor prendario preferente -- a saber, la República – sería el acreedor preferente sobre los activos de PDVSA. Así, la República tendría el derecho preferente frente a cualquier acreedor “holdout” que pueda intentar embargar tales activos para satisfacer una sentencia a su favor en contra de PDVSA. Esta posibilidad debería hacer pensar dos veces a cualquier acreedor sobre las ventajas de ser un “holdout”

Convergence in wing coloration between orange underwing moths (Archiearis spp.) and tortoiseshell butterflies (Aglais spp.)

We analysed the wing coloration of the orange underwing moth Archiearis parthenias (Geometridae, Archiearinae) in comparison with the small tortoiseshell butterfly Aglais urticae (Nymphalidae). Both species fly in early spring and occur sympatrically in the northern Palaearctic. Aglais, the more common species, has a longer flight period and uses a broader range of habitats. Both species show a camouflaged colour pattern on surfaces exposed at rest but a bright orange signal in flight. Although the evolution of its coloration is constrained by its geometrid morphology, Archiearis is functionally similar to Aglais both while resting and in flight. Archiearis has presumably evolved from nocturnal geometrid ancestors. Its shift to diurnality has included a change in the predator defence system from one based on ultrasonic hearing, functional against bats, to one presumably functional against birds. Preliminary palatability tests showed that Aglais is distasteful to birds (chicken), while Archiearis seems to be palatable. The function of the convergent coloration is unknown, but several possibilities are discussed

Perceptionsbaserad andra generationens bildkodning med variabel upplösning

In ordinary image coding, the same image quality is obtained in all parts of an image. If it is known that there is only one viewer, and where in the image that viewer is focusing, the quality can be degraded in other parts of the image without incurring any perceptible coding artefacts. This master's thesispresents a coding scheme where an image is segmented into homogeneous regions which are then separately coded, and where knowledge about the user's focus point is used to obtain further data reduction. It is concluded that the coding performance does not quite reach the levels attained when applying focus-based quality degradation to coding schemes not based on segmentation

Advanced MRI Data Processing

Magnetic resonance imaging (MRI) is a very versatile imaging modality which can be used to acquire several different types of images. Some examples include anatomical images, images showing local brain activation and images depicting different types of pathologies. Brain activation is detected by means of functional magnetic resonance imaging (fMRI). This is useful e.g. in planning of neurosurgical procedures and in neurological research. To find the activated regions, a sequence of images of the brain is collected while a patient or subject alters between resting and performing a task. The variations in image intensity over time are then compared to a model of the variations expected to be found in active parts of the brain. Locations with high correlation between the intensity variations and the model are considered to be activated by the task. Since the images are very noisy, spatial filtering is needed before the activation can be detected. If adaptive filtering is used, i.e. if the filter at each location is adapted to the local neighborhood, very good detection performance can be obtained. This thesis presents two methods for adaptive spatial filtering of fMRI data. One of these is a modification of a previously proposed method, which at each position maximizes the similarity between the filter response and the model. A novel feature of the presented method is rotational invariance, i.e. equal sensitivity to activated regions in different orientations. The other method is based on bilateral filtering. At each position, this method averages pixels which are located in the same type of brain tissue and have similar intensity variation over time. A method for robust correlation estimation is also presented. This method automatically detects local bursts of noise in a signal and disregards the corresponding signal segments when the correlation is estimated. Hence, the correlation estimate is not affected by the noise bursts. This method is useful not only in analysis of fMRI data, but also in other applications where correlation is used to determine the similarity between signals. Finally, a method for correcting artifacts in complex MR images is presented. Complex images are used e.g. in the Dixon technique for separate imaging of water and fat. The phase of these images is often affected by artifacts and therefore need correction before the actual water and fat images can be calculated. The presented method for phase correction is based on an image integration technique known as the inverse gradient. The method is shown to provide good results even when applied to images with severe artifacts

Advanced MRI Data Processing

Magnetic resonance imaging (MRI) is a very versatile imaging modality which can be used to acquire several different types of images. Some examples include anatomical images, images showing local brain activation and images depicting different types of pathologies. Brain activation is detected by means of functional magnetic resonance imaging (fMRI). This is useful e.g. in planning of neurosurgical procedures and in neurological research. To find the activated regions, a sequence of images of the brain is collected while a patient or subject alters between resting and performing a task. The variations in image intensity over time are then compared to a model of the variations expected to be found in active parts of the brain. Locations with high correlation between the intensity variations and the model are considered to be activated by the task. Since the images are very noisy, spatial filtering is needed before the activation can be detected. If adaptive filtering is used, i.e. if the filter at each location is adapted to the local neighborhood, very good detection performance can be obtained. This thesis presents two methods for adaptive spatial filtering of fMRI data. One of these is a modification of a previously proposed method, which at each position maximizes the similarity between the filter response and the model. A novel feature of the presented method is rotational invariance, i.e. equal sensitivity to activated regions in different orientations. The other method is based on bilateral filtering. At each position, this method averages pixels which are located in the same type of brain tissue and have similar intensity variation over time. A method for robust correlation estimation is also presented. This method automatically detects local bursts of noise in a signal and disregards the corresponding signal segments when the correlation is estimated. Hence, the correlation estimate is not affected by the noise bursts. This method is useful not only in analysis of fMRI data, but also in other applications where correlation is used to determine the similarity between signals. Finally, a method for correcting artifacts in complex MR images is presented. Complex images are used e.g. in the Dixon technique for separate imaging of water and fat. The phase of these images is often affected by artifacts and therefore need correction before the actual water and fat images can be calculated. The presented method for phase correction is based on an image integration technique known as the inverse gradient. The method is shown to provide good results even when applied to images with severe artifacts

Multisensorsystem för positionering av rökdykare

I det här arbetet presenteras en pågående studie riktad mot positionering och automatisk kartering för rökdykare. Fokus är på metoder för fusion av visuella och termiska kameror samt fotmonterad tröghetsnavigation.QC 20131217</p

Robust Correlation Analysis with an Application to Functional MRI

Correlation is often used to measure the similarity between signals and is an important tool in signal and image processing. In some applications it is common that signals are corrupted by local bursts of noise. This adversely affects the performance of signal recognition algorithms. This paper presents a novel correlation estimator, which is robust to locally corrupted signals. The estimator is generalized to multivariate correlation analysis (general linear model, GLM, and canonical correlation analysis, CCA). Synthetic functional MRI data is used to demonstrate the estimator, and its robustness is shown to increase the performance of signal detection.©2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Joakim Rydell, Magnus Borga and Hans Knutsson, Robust Correlation Analysis with an Application to Functional MRI, 2008, IEEE International Conference on Acoustics, Speech and Signal Processing, 2008, Las Vegas, USA, 453-456. http://dx.doi.org/10.1109/ICASSP.2008.4517644</p