Subjective well-being, income and relative concerns in the UK

We present an empirical model aimed at testing the relative income hypothesis and the effect of deprivation relative to mean income on subjective well-being. The main concern is to deal with subjective panel data in an ordered response model where error homoskedasticity is not assumed. A heteroskedastic pooled panel ordered probit model with unobserved individual-specific effects is applied to micro-data available in the British Household Panel Survey for 1996-2007. In this framework, absolute income impacts negatively on both completely satisfied and dissatisfied individuals, while relative income affects positively the most satisfied ones. Such an effect is asymmetric, impacting more severely on the relatively poor in the reference group. We argue that our results buttress the validity of the relative income hypothesis as an explanation of the happiness paradox.Subjective Well-being; Relative Income; Absolute Income; Deprivation; Panel Data; Discrete Choice Models.

Reconciling U.S. Banking and Securities Data Preservation Rules with European Mandatory Data Erasure Under GDPR

United States law, which requires financial institutions to retain customer data, conflicts with European Union law, which requires financial institutions to delete customer data on demand. A financial institution operating transnationally cannot comply with both U.S. and EU law. Financial institutions thus face the issue that they cannot possibly delete and retain the same data simultaneously. This Note will clarify the scope and nature of this conflict. First, it will clarify the conflict by examining (1) the relevant laws, which are Europe’s General Data Protection Regulation (GDPR), the U.S. Bank Secrecy Act, and Securities and Exchange Commission (SEC) regulations, (2) GDPR’s application to U.S. financial institutions, and (3) U.S. law’s extraterritorial application to financial institutions operating in Europe, under the U.S. Supreme Court’s Morrison-Kiobel two-step analysis. Second, it will propose a solution by examining international law and U.S. foreign relations law. United States law subjects financial institutions to multiple data retention requirements. Securities regulations require broker-dealers to retain customer account and complaint records. The Bank Secrecy Act of 1970 requires financial institutions to retain customer data for at least five years. Sometimes, banks must permanently retain certain records. GDPR empowers individuals to demand that companies erase their data. Couched in the theory of a right to erasure, GDPR lets customers withdraw their consent for a financial institution to process or retain their data. Violators may face fines of 4 percent of their worldwide revenue. GDPR applies broadly to U.S. data-processors that either (1) are established in the European Union, or (2) monitor or offer to sell goods or services to individuals in the European Union. Establishment is broadly construed by European courts and may be met by “a single representative in the European Union.” In U.S. law, a two-step analysis determines whether and to what extent federal statutes govern conduct abroad. First, courts analyze whether the presumption against extraterritoriality has been rebutted. The presumption derives from the canon that a statute, “unless a contrary intent appears, is meant to apply only within the territorial jurisdiction” of the United States. If the presumption is not rebutted, the court proceeds to the second step, when the court considers the statute’s “focus” and whether the case involves the statute’s domestic application. United States law has domestic application to data stored domestically, and sometimes possibly to data stored internationally; such data operations may also fall under GPDR’s jurisdiction. Then, if a customer asks a financial institution to delete data, the financial institution will face conflicting laws. This Note seeks to resolve the conflict, recommending that courts approach resolution from the framework of the Restatement (Third) of Foreign Relations Law

Storing single photons emitted by a quantum memory on a highly excited Rydberg state

Strong interaction between two single photons is a long standing and important goal in quantum photonics. This would enable a new regime of nonlinear optics and unlock several applications in quantum information science, including photonic quantum gates and deterministic Bell-state measurements. In the context of quantum networks, it would be important to achieve interactions between single photons from independent photon pairs storable in quantum memories. So far, most experiments showing nonlinearities at the single-photon level have used weak classical input light. Here we demonstrate the storage and retrieval of a paired single photon emitted by an ensemble quantum memory in a strongly nonlinear medium based on highly excited Rydberg atoms. We show that nonclassical correlations between the two photons persist after retrieval from the Rydberg ensemble. Our result is an important step towards deterministic photon–photon interactions, and may enable deterministic Bell-state measurements with multimode quantum memories.Peer ReviewedPostprint (published version

Quantification of venous blood signal contribution to BOLD functional activation in the auditory cortex at 3 T

Most modern techniques for functional magnetic resonance imaging (fMRI) rely on blood-oxygen-level-dependent (BOLD) contrast as the basic principle for detecting neuronal activation. However, the measured BOLD effect depends on a transfer function related to neurophysiological changes accompanying electrical neural activation. The spatial accuracy and extension of the region of interest are determined by vascular effect, which introduces incertitude on real neuronal activation maps. Our efforts have been directed towards the development of a new methodology that is capable of combining morphological, vascular and functional information; obtaining new insight regarding foci of activation; and distinguishing the nature of activation on a pixel-by-pixel basis. Six healthy volunteers were studied in a parametric auditory functional experiment at 3 T; activation maps were overlaid on a high-resolution brain venography obtained through a novel technique. The BOLD signal intensities of vascular and nonvascular activated voxels were analyzed and compared: it was shown that nonvascular active voxels have lower values for signal peak (Pb10−7) and area (Pb10−8) with respect to vascular voxels. The analysis showed how venous blood influenced the measured BOLD signals, supplying a technique to filter possible venous artifacts that potentially can lead to misinterpretation of fMRI results. This methodology, although validated in the auditory cortex activation, maintains a general applicability to any cortical fMRI study, as the basic concepts on which it relies on are not limited to this cortical region. The results obtained in this study can represent the basis for new methodologies and tools that are capable of adding further characterization to the BOLD signal properties

Ordinal Welfare Comparisons with Multiple Discrete Indicators: A First Order Dominance Approach and Application to Child Poverty

We develop an ordinal method for making welfare comparisons between populations with multidimensional discrete well-being indicators observed at the micro level. The approach assumes that, for each well-being indicator, the levels can be ranked from worse to better; however, no assumptions are made about relative importance of any dimension nor about complementarity/substitutability relationships between dimensions. The method is based on the concept of multidimensional first order dominance. We introduce a rapid and reliable algorithm for empirically determining whether one population dominates another on the basis of available binary indicators by drawing upon linear programming theory. These approaches are applied to household survey data from Vietnam and Mozambique with a focus on child poverty comparisons over time and between regions.

An Efficient Approach for Preprocessing Data from aLarge-Scale Chemical Sensor Array

In this paper, an artificial olfactory system (Electronic Nose) that mimics the biological olfactory system is introduced. The device consists of a Large-Scale Chemical Sensor Array (16, 384 sensors, made of 24 different kinds of conducting polymer materials) that supplies data to software modules, which perform advanced data processing. In particular, the paper concentrates on the software components consisting, at first, of a crucial step that normalizes the heterogeneous sensor data and reduces their inherent noise. Cleaned data are then supplied as input to a data reduction procedure that extracts the most informative and discriminant directions in order to get an efficient representation in a lower dimensional space where it is possible to more easily find a robust mapping between the observed outputs and the characteristics of the odors in input to the device. Experimental qualitative proofs of the validity of the procedure are given by analyzing data acquired for two different pure analytes and their binary mixtures. Moreover, a classification task is performed in order to explore the possibility of automatically recognizing pure compounds and to predict binary mixture concentrations

Deterministic superresolution with coherent states at the shot noise limit

Interference of light fields plays an important role in various high-precision measurement schemes. It has been shown that super resolving phase measurements beyond the standard coherent state limit can be obtained either by using maximally entangled multi-particle states of light or using complex detection approaches. Here we show that super resolving phase measurements at the shot noise limit can be achieved without resorting to non-classical optical states or to low-efficiency detection processes. Using robust coherent states of light, high-efficiency homodyne detection and a deterministic binarization processing technique, we show a narrowing of the interference fringes that scales with 1/Sqrt{N} where N is the mean number of photons of the coherent state. Experimentally we demonstrate a 12-fold narrowing at the shot noise limit.Comment: 5 pages, 3 figure

Gibrat's Law and quantile regressions : an application to firm growth

The nexus between firm growth, size and age in U.S. manufacturing is examined through the lens of quantile regression models. This methodology allows us to overcome serious shortcomings entailed by linear regression models employed by much of the existing literature, unveiling a number of important properties. Size pushes both low and high performing firms towards the median rate of growth, while age is never advantageous, and more so as firms are relatively small and grow faster. These findings support theoretical generalizations of Gibrat's law that allow size to affect the variance of the growth process, but not its mean (Cordoba, 2008)

OMEGA-3 fatty acids contribute to plaque stability differentially affecting the release of matrix metalloproteinases and tissue inhibitors of metalloproteinases by human monocytes/macrophages in culture

Objectives. High intakes of omega-3 fatty acids has been associated with protection from plaque rupture. The secretion of metalloproteinases (MMPs) by macrophages is believed to play a key role in matrix degradation underlying plaque instability. Conversely, tissue inhibitors of metalloproteinases (TIMPs) would contribute to plaque stability. We therefore studied the effects of omega-3 fatty acids on the release and activity of MMPs and TIMPs in cultured human monocytoid cells. Methods. Human U937 monocytoid cells were differentiated into macrophages by exposure for 24 h to 30 ng/mL phorbol myristate acetate (PMA) and 10 ng/mL tumor necrosis factor(TNF)-α. Both monocytes and macrophages were treated for 48 h with the DHA (22:6 n-3) or EPA (22:6 n-3) (25-100 μmol/L) before stimulation for 24 h with 10 ng/ml TNFα. Cell supernatates were used to test the release of gelatinase A (MMP-2), gelatinase-B (MMP-9), collagenase-1 (MMP-1), TIMP-1 and TIMP-2, by ELISAs, and total gelatinase and anti-gelatinase activities by zymography and retro-zymography techniques, respectively. Results. The long term exposure to 50 μmol/L EPA and DHA, but not to arachidonic acid (20:4 n-6), significantly reduced MMP-9 protein release without affecting the release of MMP-1, MMP-2 and TIMP-1. Conversely, TIMP-2 protein release was significantly increased by EPA and DHA (Table). Zymography for MMP-9 and retro-zymography for TIMP-1 and -2 reproduced the same results. Conclusions. The long term exposure to omega-3 fatty acids significantly reduces MMP-9 release without affecting the release of MMP-1 and -2. This effect, associated with the increase of TIMP-2 protein production and activity, may contribute to explaining the plaque-stabilizing effect by omega-3 fatty acid observed in humans