Annuities and Individual Welfare

This paper advances the theory of annuity demand. First, we derive sufficient conditions under which complete annuitization is optimal, showing that this well-known result holds true in a more general setting than in Yaari (1965). Specifically, when markets are complete, sufficient conditions need not impose exponential discounting, intertemporal separability or the expected utility axioms; nor need annuities be actuarially fair, nor longevity risk be the only source of consumption uncertainty. All that is required is that consumers have no bequest motive and that annuities pay a rate of return for survivors greater than those of otherwise matching conventional assets, net of administrative costs. Second, we show that full annuitization may not be optimal when markets are incomplete. Some annuitization is optimal as long as conventional asset markets are complete. The incompleteness of markets can lead to zero annuitization but the conditions on both annuity and bond markets are stringent. Third, we extend the simulation literature that calculates the utility gains from annuitization by considering consumers whose utility depends both on present consumption and a which they have become accustomed. The value of annuitization hinges critically on the size of the initial standard-of-living relative to wealth.

Paragangliomas and paraganglioma syndromes

Paragangliomas are rare tumors of neural crest origin. They are benign in the majority of cases and are characterized by a strong vascularisation

Peer Review—The Newcomers' Perspective

The World Academy of Young Scientists argue that double blind peer-review will generate a better perception of fairness and equality in global scientific funding and publishin

Nonverbal Problem Solving in Aphasic and Non-Aphasic Patients with Computer Presented and Actual Stimuli

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Neural correlates of colour categories

This study used an electrophysiological marker of visual detection to investigate adults' processing of colour difference. Event-related potentials were collected from the identical colour (green: G0) presented as the frequent or infrequent stimulus within different colour contexts. Critically, we compared differences within the same colour category (G0 vs. green: G1) to differences between colour categories (G0 vs. blue and G0 vs. red). All differences showed a change-related positivity with similar scalp distribution. It was, however, not simply the magnitude of colour difference that reduced the latencies of the change-related positivity. A change in colour category without a magnitude difference also reduced latency of the event-related potential. Thus, for the first time we report an independent neural correlate of a colour category

Gender, migration and the ambiguous enterprise of professionalizing domestic service: the case of vocational training for the unemployed in France

Drawing on ethnographic data concerning migrant male domestic workers, this article examines the gendered dimensions of the process of racialization in Italy and France. First, it shows that specific racialized constructions of masculinity are mobilized by the employers as well as by training and recruitment agencies. These constructions of masculinity are related to different forms of organization of the sector in each country and to different ideologies about the integration of migrants. Second, the data presented reveal the strategies used by migrant male domestic workers to reaffirm their masculinity in a traditionally feminized sector. In doing so, this article intends to explore the connections between international migration and the gendering of occupations, with regard to the construction and management of masculinities in domestic service. Finally, by examining men’s experiences, this article aims to contribute to a more complex definition of the international division of care work

Bayes and health care research.

Bayes’ rule shows how one might rationally change one’s beliefs in the light of evidence. It is the foundation of a statistical method called Bayesianism. In health care research, Bayesianism has its advocates but the dominant statistical method is frequentism. There are at least two important philosophical differences between these methods. First, Bayesianism takes a subjectivist view of probability (i.e. that probability scores are statements of subjective belief, not objective fact) whilst frequentism takes an objectivist view. Second, Bayesianism is explicitly inductive (i.e. it shows how we may induce views about the world based on partial data from it) whereas frequentism is at least compatible with non-inductive views of scientific method, particularly the critical realism of Popper. Popper and others detail significant problems with induction. Frequentism’s apparent ability to avoid these, plus its ability to give a seemingly more scientific and objective take on probability, lies behind its philosophical appeal to health care researchers. However, there are also significant problems with frequentism, particularly its inability to assign probability scores to single events. Popper thus proposed an alternative objectivist view of probability, called propensity theory, which he allies to a theory of corroboration; but this too has significant problems, in particular, it may not successfully avoid induction. If this is so then Bayesianism might be philosophically the strongest of the statistical approaches. The article sets out a number of its philosophical and methodological attractions. Finally, it outlines a way in which critical realism and Bayesianism might work together. </p

RAMESES publication standards: realist syntheses

PMCID: PMC3558331This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Severe renal bleeding caused by a ruptured renal sheath: case report of a rare complication of percutaneous nephrolithotomy

BACKGROUND: Percutaneous nephrolithotomy is a minimally invasive intervention for renal stone disease. Complications, which are rare and usually presented as case reports, are diversified as the utilization of the procedure is expanded. The procedure causes less blood loss and less morbidity when compared to open surgical procedures. Yet, there are some reports involving severe bleeding and relevant morbidity during surgery. These are usually related with the surgical technique or experience of the surgeon. Renal sheaths are designed to cause minimal trauma inside the kidney and, to our knowledge, there are no reports presenting the rupture of a sheath causing severe bleeding during the procedure. CASE REPORT: We present an adult patient who had severe bleeding during percutaneous nephrolithotomy due to parenchymal injury caused by a ruptured renal sheath. During retrieval, due probably to rough handling of the equipment, a piece of stone with serrated edges ruptured the tip of the sheath, and this tip caused damage inside the kidney. The operation was terminated and measures were taken to control bleeding. The patient was transfused with a total of 1600 ml of blood, and the stones were cleared in a second look operation. CONCLUSION: Although considered to be a minimally invasive procedure, some unexpected complications may arise during percutaneous nephrolithotomy. After being fragmanted, stone pieces may damage surgical equipment, causing acute and severe harm to the kidney. Surgeons must manipulate the equipment with fine and careful movements in order to prevent this situation

Optimal network topologies: Expanders, Cages, Ramanujan graphs, Entangled networks and all that

We report on some recent developments in the search for optimal network topologies. First we review some basic concepts on spectral graph theory, including adjacency and Laplacian matrices, and paying special attention to the topological implications of having large spectral gaps. We also introduce related concepts as ``expanders'', Ramanujan, and Cage graphs. Afterwards, we discuss two different dynamical feautures of networks: synchronizability and flow of random walkers and so that they are optimized if the corresponding Laplacian matrix have a large spectral gap. From this, we show, by developing a numerical optimization algorithm that maximum synchronizability and fast random walk spreading are obtained for a particular type of extremely homogeneous regular networks, with long loops and poor modular structure, that we call entangled networks. These turn out to be related to Ramanujan and Cage graphs. We argue also that these graphs are very good finite-size approximations to Bethe lattices, and provide almost or almost optimal solutions to many other problems as, for instance, searchability in the presence of congestion or performance of neural networks. Finally, we study how these results are modified when studying dynamical processes controlled by a normalized (weighted and directed) dynamics; much more heterogeneous graphs are optimal in this case. Finally, a critical discussion of the limitations and possible extensions of this work is presented.Comment: 17 pages. 11 figures. Small corrections and a new reference. Accepted for pub. in JSTA