353 research outputs found

    Section on Prospects for Dark Matter Detection of the White Paper on the Status and Future of Ground-Based TeV Gamma-Ray Astronomy

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    This is a report on the findings of the dark matter science working group for the white paper on the status and future of TeV gamma-ray astronomy. The white paper was commissioned by the American Physical Society, and the full white paper can be found on astro-ph (arXiv:0810.0444). This detailed section discusses the prospects for dark matter detection with future gamma-ray experiments, and the complementarity of gamma-ray measurements with other indirect, direct or accelerator-based searches. We conclude that any comprehensive search for dark matter should include gamma-ray observations, both to identify the dark matter particle (through the charac- teristics of the gamma-ray spectrum) and to measure the distribution of dark matter in galactic halos.Comment: Report from the Dark Matter Science Working group of the APS commissioned White paper on ground-based TeV gamma ray astronomy (19 pages, 9 figures

    From Quantum Systems to L-Functions: Pair Correlation Statistics and Beyond

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    The discovery of connections between the distribution of energy levels of heavy nuclei and spacings between prime numbers has been one of the most surprising and fruitful observations in the twentieth century. The connection between the two areas was first observed through Montgomery's work on the pair correlation of zeros of the Riemann zeta function. As its generalizations and consequences have motivated much of the following work, and to this day remains one of the most important outstanding conjectures in the field, it occupies a central role in our discussion below. We describe some of the many techniques and results from the past sixty years, especially the important roles played by numerical and experimental investigations, that led to the discovery of the connections and progress towards understanding the behaviors. In our survey of these two areas, we describe the common mathematics that explains the remarkable universality. We conclude with some thoughts on what might lie ahead in the pair correlation of zeros of the zeta function, and other similar quantities.Comment: Version 1.1, 50 pages, 6 figures. To appear in "Open Problems in Mathematics", Editors John Nash and Michael Th. Rassias. arXiv admin note: text overlap with arXiv:0909.491

    Revealing heterogeneous nucleation of primary Si and eutectic Si by AlP in hypereutectic Al-Si alloys

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    The heterogeneous nucleation of primary Si and eutectic Si can be attributed to the presence of AlP. Although P, in the form of AlP particles, is usually observed in the centre of primary Si, there is still a lack of detailed investigations on the distribution of P within primary Si and eutectic Si in hypereutectic Al-Si alloys at the atomic scale. Here, we report an atomic-scale experimental investigation on the distribution of P in hypereutectic Al-Si alloys. P, in the form of AlP particles, was observed in the centre of primary Si. However, no significant amount of P was detected within primary Si, eutectic Si and the Al matrix. Instead, P was observed at the interface between the Al matrix and eutectic Si, strongly indicating that P, in the form of AlP particles (or AlP ‘patch’ dependent on the P concentration), may have nucleated on the surface of the Al matrix and thereby enhanced the heterogeneous nucleation of eutectic Si. The present investigation reveals some novel insights into heterogeneous nucleation of primary Si and eutectic Si by AlP in hypereutectic Al-Si alloys and can be used to further develop heterogeneous nucleation mechanisms based on adsorption

    Effect of cadence on locomotor–respiratory coupling during upper-body exercise

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    Introduction: Asynchronous arm-cranking performed at high cadences elicits greater cardiorespiratory responses compared to low cadences. This has been attributed to increased postural demand and locomotor–respiratory coupling (LRC), and yet, this has not been empirically tested. This study aimed to assess the effects of cadence on cardiorespiratory responses and LRC during upper-body exercise. Methods: Eight recreationally-active men performed arm-cranking exercise at moderate and severe intensities that were separated by 10 min of rest. At each intensity, participants exercised for 4 min at each of three cadences (50, 70, and 90 rev min−1) in a random order, with 4 min rest-periods applied in-between cadences. Exercise measures included LRC via whole- and half-integer ratios, cardiorespiratory function, perceptions of effort (RPE and dyspnoea), and diaphragm EMG using an oesophageal catheter. Results: The prevalence of LRC during moderate exercise was highest at 70 vs. 50 rev min−1 (27 ± 10 vs. 13 ± 9%, p = 0.000) and during severe exercise at 90 vs. 50 rev min−1 (24 ± 7 vs. 18 ± 5%, p = 0.034), with a shorter inspiratory time and higher mean inspiratory flow (p < 0.05) at higher cadences. During moderate exercise, (Formula presented.) and fC were higher at 90 rev min−1 (p < 0.05) relative to 70 and 50 rev min−1 ((Formula presented.) 1.19 ± 0.25 vs. 1.05 ± 0.21 vs. 0.97 ± 0.24 L min−1; fC 116 ± 11 vs. 101 ± 13 vs. 101 ± 12 b min−1), with concomitantly elevated dyspnoea. There were no discernible cadence-mediated effects on diaphragm EMG. Conclusion: Participants engage in LRC to a greater extent at moderate-high cadences which, in turn, increase respiratory airflow. Cadence rate should be carefully considered when designing aerobic training programmes involving the upper-limbs

    Algorithms for optimizing drug therapy

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    BACKGROUND: Drug therapy has become increasingly efficient, with more drugs available for treatment of an ever-growing number of conditions. Yet, drug use is reported to be sub optimal in several aspects, such as dosage, patient's adherence and outcome of therapy. The aim of the current study was to investigate the possibility to optimize drug therapy using computer programs, available on the Internet. METHODS: One hundred and ten officially endorsed text documents, published between 1996 and 2004, containing guidelines for drug therapy in 246 disorders, were analyzed with regard to information about patient-, disease- and drug-related factors and relationships between these factors. This information was used to construct algorithms for identifying optimum treatment in each of the studied disorders. These algorithms were categorized in order to define as few models as possible that still could accommodate the identified factors and the relationships between them. The resulting program prototypes were implemented in HTML (user interface) and JavaScript (program logic). RESULTS: Three types of algorithms were sufficient for the intended purpose. The simplest type is a list of factors, each of which implies that the particular patient should or should not receive treatment. This is adequate in situations where only one treatment exists. The second type, a more elaborate model, is required when treatment can by provided using drugs from different pharmacological classes and the selection of drug class is dependent on patient characteristics. An easily implemented set of if-then statements was able to manage the identified information in such instances. The third type was needed in the few situations where the selection and dosage of drugs were depending on the degree to which one or more patient-specific factors were present. In these cases the implementation of an established decision model based on fuzzy sets was required. Computer programs based on one of these three models could be constructed regarding all but one of the studied disorders. The single exception was depression, where reliable relationships between patient characteristics, drug classes and outcome of therapy remain to be defined. CONCLUSION: Algorithms for optimizing drug therapy can, with presumably rare exceptions, be developed for any disorder, using standard Internet programming methods

    The Effect of Partial Retirement on Labor Supply, Public Balances and the Income Distribution: Evidence from a Structural Analysis

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    This paper develops a structural dynamic retirement model to investigate effects and corresponding underlying mechanisms of a partial retirement program on labor supply, fiscal balances, and the pension income distribution. The structural approach allows for disentangling the two counteracting mechanisms that drive the employment effects of partial retirement: 1) the crowding-out from full-time employment, and 2) the movement from early retirement or unemployment to partial retirement. It also allows for investigating the role of financial compensations in a partial retirement program. Based on a unique German administrative dataset, I perform counterfactual policy simulations that analyze the role of partial retirement combined with financial subsidies and an increased normal retirement age. The results show that partial retirement extends working lives but reduces the overall employment volume. The fiscal consequences of partial retirement are negative but substantially less so when wages and pensions in partial retirement remain uncompensated. Partial retirement decreases inequality in pension income and provides a way to smooth consumption especially for retirees in lower income deciles in the context of an increased normal retirement age
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