Discrimination in Bankruptcy Situations

In a bankruptcy situation, not all claimants are affected in the same way. In particular, some depositors may enter into a situation of personal bankruptcy if they lose part of their investments. Events of this kind may lead to a social catastrophe. We propose discrimination among the claimants as a possible solution. A fact considered in the American bankruptcy law (among others) that establishes some discrimination on the claimants, or the Santander Bank that in the Madoff’s case reimbursed only the deposits to its particular customers. Moreover, the necessity of discriminating has already been mentioned in different contexts by Young (1988), Bossert (1995), Thomson (2003) and Pulido et al. (2002, 2007), for instance. In this paper, we take a bankruptcy solution as the reference point. Given this initial allocation, we make transfers from richer to poorer with the purpose of distributing not only the personal incurred losses as evenly as possible but also the transfers in a progressive way. The agents are divided into two groups depending on their personal monetary value (wealth, net-income, GDP or any other characteristic). Then, we impose a set of Axioms that bound the maximal transfer that each net-contributor can make and each net-receiver can obtain. Finally, we define a value discriminant solution, and we characterize it by means of the Lorenz criterion. Endogenous convex combinations between solutions are also considered. Keywords: Bankruptcy, Discrimination, Compensation, Rules JEL classification: C71, D63, D71.

Optimal second-degree price discrimination and arbitrage: On the role of asymetric information among buyers

The traditional theory of monopolistic screening tackles individualself-selection but does not address the possibility that buyers couldform a coalition to coordinate their purchases and to reallocate thegoods. In this paper, we design the optimal sale mechanism which takesinto account both individual and coalition incentive compatibilityfocusing on the role of asymmetric information among buyers. We showthat when a coalition of buyers is formed under asymmetric information,the monopolist can do as well as when there is no coalition. Although inthe optimal sale mechanism marginal rates of substitution are notequalized across buyers (hence there exists room for arbitrage), theyfail to realize the gains from arbitrage because of the transaction costsin coalition formation generated by asymmetric information.

Reverse logistics in the editorial sector: An exploratory study

Nowadays, the Reverse Logistics field is becoming very important. On one hand, laws areimposing companies to be responsible for the contamination made by their products. On theother hand, companies have discovered the profits derived from a good Reverse Logisticsprocess. This paper is the result of the work done by a group of companies from the SpanishEditorial sector to understand and improve their Reverse Logistics process. The paperdescribes the characteristics of the Reverse Logistics process in this sector and theimprovements identified by the work group .

Sovereign debt markets in turbulent times: Creditor discrimination and crowding-out effects

In 2007, countries in the Euro periphery were enjoying stable growth, low deficits, and lowspreads. Then the financial crisis erupted and pushed them into deep recessions, raising theirdeficits and debt levels. By 2010, they were facing severe debt problems. Spreads increased and,surprisingly, so did the share of the debt held by domestic creditors. Credit was reallocatedfrom the private to the public sectors, reducing investment and deepening the recessions evenfurther. To account for these facts, we propose a simple model of sovereign risk in which debtcan be traded in secondary markets. The model has two key ingredients: creditor discriminationand crowding-out effects. Creditor discrimination arises because, in turbulent times, sovereigndebt offers a higher expected return to domestic creditors than to foreign ones. This providesincentives for domestic purchases of debt. Crowding-out effects arise because private borrowingis limited by financial frictions. This implies that domestic debt purchases displace productiveinvestment. The model shows that these purchases reduce growth and welfare, and may lead toself-fulfilling crises. It also shows how crowding-out effects can be transmitted to other countriesin the Eurozone, and how they may be addressed by policies at the European level.

EEG windowed statistical wavelet scoring for evaluation and discrimination of muscular artifacts

EEG recordings are usually corrupted by spurious extra-cerebral artifacts, which should be rejected or cleaned up by the practitioner. Since manual screening of human EEGs is inherently error prone and might induce experimental bias, automatic artifact detection is an issue of importance. Automatic artifact detection is the best guarantee for objective and clean results. We present a new approach, based on the time–frequency shape of muscular artifacts, to achieve reliable and automatic scoring. The impact of muscular activity on the signal can be evaluated using this methodology by placing emphasis on the analysis of EEG activity. The method is used to discriminate evoked potentials from several types of recorded muscular artifacts—with a sensitivity of 98.8% and a specificity of 92.2%. Automatic cleaning ofEEGdata are then successfully realized using this method, combined with independent component analysis. The outcome of the automatic cleaning is then compared with the Slepian multitaper spectrum based technique introduced by Delorme et al (2007 Neuroimage 34 1443–9).

Coherency and sharpness measures by using ICA algorithms. An investigation for Alzheimer’s disease discrimination

In this paper, we present a comprehensive study of different Independent Component Analysis (ICA) algorithms for the calculation of coherency and sharpness of electroencephalogram (EEG) signals, in order to investigate the possibility of early detection of Alzheimer’s disease (AD). We found that ICA algorithms can help in the artifact rejection and noise reduction, improving the discriminative property of features in high frequency bands (specially in high alpha and beta ranges). In addition to different ICA algorithms, the optimum number of selected components is investigated, in order to help decision processes for future works.

Investigation of ICA algorithms for feature extraction of EEG signals in discrimination of Alzheimer disease

In this paper we present a quantitative comparisons of different independent component analysis (ICA) algorithms in order to investigate their potential use in preprocessing (such as noise reduction and feature extraction) the electroencephalogram (EEG) data for early detection of Alzhemier disease (AD) or discrimination between AD (or mild cognitive impairment, MCI) and age-match control subjects.

Grain yield, carbon isotope discrimination and mineral content in mature kernels of barley under irrigated and rainfed conditions

The relationship between yield, carbon isotope discrimination and ash content in mature kernels was examined for a set of 13 barley (Hordeum vulgare) cultivars. Plants were grown under rainfed and well-irrigated conditions in a Mediterranean area. Water deficit caused a decrease in both grain yield and carbon isotope discrimination (Δ). The yield was positively related to Δ and negatively related to ash content, across genotypes within each treatment. However, whereas the correlation between yield and Δ was higher for the set of genotypes under well-irrigated (r=0.70, P<0.01) than under rainfed (r=0.42) conditions, the opposite occurred when yield and ash content were related, ie r=-0.38 under well-irrigated and r=-0.73, (P<0.01) under rainfed conditions. Carbon isotope discrimination and ash content together account for almost 60% of the variation in yield, in both conditions. There was no significant relationship (r=-0.15) between carbon isotope discrimination and ash content in well-irrigated plants, whereas in rainfed plants, this relationship, although significant (r=-0.54, P< 0.05), was weakly negative. The concentration of several mineral elements was measured in the same kernels. The mineral that correlated best with ash content, yield and A, was K. For yield and Δ, although the relationship with K followed the same pattern as the relationhip with ash content, the correlation coefficients were lower. Thus, mineral accumulation in mature kernels seems to be independent of transpiration efficiency. In fact, filling of grains takes place through the phloem pathway. The ash content in kernels is proposed as a complementary criterion, in addition to kernel Δ, to assess genotype differences in barley grain yield under rainfed conditions.

Otolith shape analysis as a tool for population discrimination of the white grunt (Haemulon plumieri) stock in the northern coast of the Yucatan Peninsula, Mexico

In this study, the population structure of the white grunt (Haemulon plumieri) from the northern coast of the Yucatan Peninsula was determined through an otolith shape analysis based on the samples collected in three locations: Celestún (N 20°49",W 90°25"), Dzilam (N 21°23", W 88°54") and Cancún (N 21°21",W 86°52"). The otolith outline was based on the elliptic Fourier descriptors, which indicated that the H. plumieri population in the northern coast of the Yucatan Peninsula is composed of three geographically delimited units (Celestún, Dzilam, and Cancún). Significant differences were observed in mean otolith shapes among all samples (PERMANOVA; F2, 99 = 11.20, P = 0.0002), and the subsequent pairwise comparisons showed that all samples were significantly differently from each other. Samples do not belong to a unique white grunt population, and results suggest that they might represent a structured population along the northern coast of the Yucatan Peninsula

Preferred Spatial Frequencies for Human Face Processing Are Associated with Optimal Class Discrimination in the Machine

Psychophysical studies suggest that humans preferentially use a narrow band of low spatial frequencies for face recognition. Here we asked whether artificial face recognition systems have an improved recognition performance at the same spatial frequencies as humans. To this end, we estimated recognition performance over a large database of face images by computing three discriminability measures: Fisher Linear Discriminant Analysis, Non-Parametric Discriminant Analysis, and Mutual Information. In order to address frequency dependence, discriminabilities were measured as a function of (filtered) image size. All three measures revealed a maximum at the same image sizes, where the spatial frequency content corresponds to the psychophysical found frequencies. Our results therefore support the notion that the critical band of spatial frequencies for face recognition in humans and machines follows from inherent properties of face images, and that the use of these frequencies is associated with optimal face recognition performance.

Assessment of the discrimination of animal fat by FT_Raman spectroscopy

In recent years, there has been an increased attention towards the composition of feeding fats. In the aftermath of the BSE crisis all animal by-products utilised in animal nutrition have been subjected to close scrutiny. Regulation requires that the material belongs to the category of animal by-products fit for human consumption. This implies the use of reliable techniques in order to insure the safety of products. The feasibility of using rapid and non-destructive methods, to control the composition of feedstuffs on animal fats has been studied. Fourier Transform Raman spectroscopy has been chosen for its advantage to give detailed structural information. Data were treated using chemometric methods as PCA and PLS-DA which have permitted to separate well the different classes of animal fats. The same methodology was applied on fats from various types of feedstock and production technology processes. PLS-DA model for the discrimination of animal fats from the other categories presents a sensitivity and a specificity of 0.958 and 0.914, respectively. These results encourage the use of FT-Raman spectroscopy to discriminate animal fats.

Generalization transitions in Hidden-Layer neural networks for third-order feature discrimination

Stochastic learning processes for a specific feature detector are studied. This technique is applied to nonsmooth multilayer neural networks requested to perform a discrimination task of order 3 based on the ssT-block¿ssC-block problem. Our system proves to be capable of achieving perfect generalization, after presenting finite numbers of examples, by undergoing a phase transition. The corresponding annealed theory, which involves the Ising model under external field, shows good agreement with Monte Carlo simulations.

The unfathomable secret remains: a reverse engineering study of SEO factors on Google's search engine

The vast majority of users don’t seek results beyond the second page offered by the search engine, so if a site fails to be among the top 20 (second page), it says that this page does not have good SEO and, therefore, is not visible to the user. The overall objective of this project is to conduct a study to discover the factors that determine (or not) the positioning of websites in a search engine.

Phase behavior and rheological analysis of reverse liquid crystals and W/I2, W/H2 gel emulsions using an amphiphilic block copolymer.

This article reports the phase behavior determi- nation of a system forming reverse liquid crystals and the formation of novel disperse systems in the two-phase region. The studied system is formed by water, cyclohexane, and Pluronic L-121, an amphiphilic block copolymer considered of special interest due to its aggregation and structural proper- ties. This system forms reverse cubic (I2) and reverse hexagonal (H2) phases at high polymer concentrations. These reverse phases are of particular interest since in the two-phase region, stable high internal phase reverse emulsions can be formed. The characterization of the I2 and H2 phases and of the derived gel emulsions was performed with small-angle X-ray scattering (SAXS) and rheometry, and the influence of temperature and water content was studied. TheH2 phase experimented a thermal transition to an I2 phase when temperature was increased, which presented an Fd3m structure. All samples showed a strong shear thinning behavior from low shear rates. The elasticmodulus (G0) in the I2 phase was around 1 order of magnitude higher than in theH2 phase. G0 was predominantly higher than the viscousmodulus (G00). In the gel emulsions,G0 was nearly frequency-independent, indicating their gel type nature. Contrarily to water-in-oil (W/O) normal emulsions, in W/I2 and W/H2 gel emulsions, G0, the complex viscosity (|η*|), and the yield stress (τ0) decreased with increasing water content, since the highly viscous microstructure of the con- tinuous phase was responsible for the high viscosity and elastic behavior of the emulsions, instead of the volumefraction of dispersed phase and droplet size. A rheological analysis, in which the cooperative flow theory, the soft glass rheology model, and the slip plane model were analyzed and compared, was performed to obtain one single model that could describe the non-Maxwellian behavior of both reverse phases and highly concentrated emulsions and to characterize their microstructure with the rheological properties.