Relative deprivation as a cause of risky behaviors

ABSTRACT

Combining a standard measure of concern about low relative wealth and a standard measure of relative risk aversion leads to a novel explanation of variation in risk-taking behavior identified and documented by social psychologists and economists. We obtain two results: (1) Holding individual i’s wealth and his rank in the wealth distribution constant, the individual’s relative risk aversion decreases when he becomes more relatively deprived as a result of an increase in the average wealth of the individuals who are wealthier than he is. (2) If relative deprivation enters the individual’s utility function approximately linearly then, holding constant individual i’s wealth and the average wealth of the individuals who are wealthier than he is, the individual’s relative risk aversion decreases when he becomes more relatively deprived as a result of a decline in his rank. Our findings provide a theoretical support for evidence about the propensity of relatively deprived individuals to gamble and resort to other risky behaviors.     

Activity‐Based Probes Developed by Applying a Sequential Dehydroalanine Formation Strategy to Expressed Proteins Reveal a Potential α‐Globin‐Modulating Deubiquitinase

We report a general and novel semisynthetic strategy for the preparation of ubiquitinated protein‐activity‐based probes on the basis of sequential dehydroalanine formation on expressed proteins. We applied this approach to construct a physiologically and therapeutically relevant ubiquitinated α‐globin probe, which was used for the enrichment and proteomic identification of α‐globin‐modulating deubiquitinases. We found USP15 as a potential deubiquitinase for the modulation of α‐globin, an excess of which aggravates β‐thalassemia symptoms. This development opens new opportunities for activity‐based‐probe design to shed light on the important aspects underlying ubiquitination and deubiquitination in health and disease.     

Mode excitation Monte Carlo simulations of mesoscopically large membranes

Solvent-free coarse grained models represent one of the most promising approaches for molecular simulations of mesoscopically large membranes. In these models, the size of the simulated membrane is limited by the slow relaxation time of the longest bending mode. Here, we present a Monte Carlo algorithm with update moves in which all the lipids are simultaneously displaced. These collective moves result in fast excitation and relaxation of the long wavelength thermal fluctuations. We apply the method to simulations of a bilayer membrane with linear size of approximately 50 nm and show reduction in the relaxation time by two orders of magnitudes when compared to conventional Monte Carlo.     

Acyclic Hypergraph Projections

Hypergraphs can be partitioned into two classes: tree (acyclic) hypergraphs and cyclic hypergraphs. This paper analyzes a new class of cyclic hypergraphs called Xrings. HypergraphHis an Xring if the hyperedges ofHcan be circularly ordered so that for every vertex, all hyperedges containing the vertex are consecutive; in addition, the vertices of no hyperedge may be a subset of the vertices of another hyperedge, and no vertex may appear in exactly one hyperedge. LetH₁andH₂be two hypergraphs. A tree projection ofH₁with respect toH₂is an acyclic hypergraphH₃such that the vertices of each hyperedge inH₁appear among the vertices of some hyperedge ofH₃and the vertices of each hyperedge inH₃appear among the vertices of some hyperedge ofH₂. A polynomial time algorithm is presented for deciding, given XringH₁and arbitrary hypergraphH₂, whether there exists a tree projection ofH₂with respect toH₁. It is shown that hypergraphHis an Xring iff a modified adjacency graph ofHis a circular-arc graph. A linear time Xring recognition algorithm, for GYO reduced hypergraphs as inputs, is presented.     

The accuracy of whole brain N-acetylaspartate quantification

A non-localizing pulse sequence to quantify the total amount of N-acetylaspartate (NAA) in the whole brain (WBNAA) was introduced recently [Magn. Reson. Med. 40, 684–689 (1998)]. However, it is known that regional magnetic field inhomogeneities, ΔB₀s, arising from susceptibility differences at tissue interfaces, shift and broaden local resonances to outside the integration window, leading to an underestimation of the true amount of NAA in the entire brain. To quantify the upper limit of this loss, the whole-head proton MR spectrum (¹H-MRS) of the water was integrated over the same frequency width as the NAA. The ratio of this area/total-water-line was 75 ± 5% in 5 volunteers. The procedure was repeated with the brain-only water peak, obtained by summing signals only from voxels within that organ from a three-dimensional chemical-shift-imaging (3D CSI) set. It indicated that <10% of the water signal loss occurred in the brain. Therefore, by analogy, WBNAA accounts for >90% of that metabolite.     

Efficient approximation of product distributions

We describe efficient constructions of small probability spaces that approximate the joint distribution of general random variables. Previous work on efficient constructions concentrate on approximations of the joint distribution for the special case of identical, uniformly distributed random variables. © 1998 John Wiley & Sons, Inc. Random Struct. Alg., 13: 1–16, 1998     

Tiny families of functions with random properties: A quality-size trade-off for hashing

We present three explicit constructions of hash functions, which exhibit a trade-off between the size of the family (and hence the number of random bits needed to generate a member of the family), and the quality (or error parameter) of the pseudorandom property it achieves. Unlike previous constructions, most notably universal hashing, the size of our families is essentially independent of the size of the domain on which the functions operate. The first construction is for the mixing property—mapping a proportional part of any subset of the domain to any other subset. The other two are for the extraction property—mapping any subset of the domain almost uniformly into a range smaller than it. The second and third constructions handle, respectively, the extreme situations when the range is very large or very small. We provide lower bounds showing that our constructions are nearly optimal, and mention some applications of the new constructions. © 1997 John Wiley & Sons, Inc. Random Struct. Alg., 11 , 315–343 (1997)     

Using a virtual skeleton to increase printability of topology optimized design for industry-class applications

This article broadens the scheme previously developed to associate topology optimization with additive manufacturing through the use of a virtual skeleton, consisting in solving the same physical problem with a discrete approach and then with a continuum one. This procedure for 3D designs is applied to various domain geometries, to demonstrate its pertinence on high-resolution industrial cases. An algorithm searching for the best printing direction, exploring the solid angle, is also described and validated; the surface-shaped presentation of the result allows immediate understanding of the influence of the discrete problem parameters, while its running time is much lower than a unique continuum optimization simulation, which proves the attractiveness of the method. In the three examples studied, the procedure outputs exhibit greater printability than the ones produced by traditional methods in each of the printing direction tested, albeit responsibility is left to the final user to choose his best trade-off. Furthermore, the unprintable zones are readily displayed to be either reworked or supported. Explanations about increase of convergence likelihood on discrete structures despite the geometry complexity of an industrial application are also provided and demonstrated.