Some remarks on a new exotic spacetime for time travel by free fall

This work is essentially a review of a new spacetime model with closed causal curves, recently presented in another paper (Class. Quantum Grav. \textbf{35}(16) (2018), 165003). The spacetime at issue is topologically trivial, free of curvature singularities, and even time and space orientable. Besides summarizing previous results on causal geodesics, tidal accelerations and violations of the energy conditions, here redshift/blueshift effects and the Hawking-Ellis classification of the stress-energy tensor are examined.Comment: 17 pages, 9 figures. Submitted as a contribution to the proceedings of "DOMOSCHOOL - International Alpine School of Mathematics and Physics, Domodossola 2018". Possible text overlaps with my previous work arXiv:1803.08214, of which this is essentially a review. Additional results concerning redshift/blueshift effects and the classification of the stress-energy tensor are presented her

PROGRAMMING Intergenerational Exercise Addresses the Public Health Issue of Obesity

ABSTRACT. Health practitioners are increasingly concerned about the rise in obesity and decrease in physical activity in society. This article reports on an intergenerational exercise program involving participants from Jewish Community Housing for the Elderly and four preschool classes in Newton, Massachusetts. The program attempts to address those health issues using an intergenerational approach. Children between ages 3 and 5, and older adults come together weekly during the course of a school year for pre-literacy play, intergenerational stories that raise awareness of aging issues and nutritional snacks. An exercise class is added to this program monthly. The exercise component reflects the physical needs of both groups. The classes enable older adults to recognize their important role as models for lifelong exercise, while simultaneously addressing their own health habits. Children see olde

Addison's disease presenting with idiopathic intracranial hypertension in 24-year-old woman: a case report

<p>Abstract</p> <p>Introduction</p> <p>Idiopathic intracranial hypertension can rarely be associated with an underlying endocrine disorder such as Cushing's syndrome, hyperthyroidism, or with administration of thyroxine or growth hormone. Though cases of idiopathic intracranial hypertension associated with Addison's disease in children have been reported, there is only one documented case report of this association in adults. We describe a case of an acute adrenal insufficiency precipitated by idiopathic intracranial hypertension in a Caucasian female.</p> <p>Case presentation</p> <p>A 24-year-old Caucasian woman was acutely unwell with a background of several months of generalised fatigue and intermittent headaches. She had unremarkable neurological and systemic examination with a normal computerised tomography and magnetic resonance imaging of the brain. Normal cerebrospinal fluid but increased opening pressure at lumbar puncture suggested intracranial hypertension. A flat short synacthen test and raised level of adrenocorticotrophic hormone were consistent with primary adrenal failure.</p> <p>Conclusion</p> <p>Addison's disease can remain unrecognised until precipitated by acute stress. This case suggests that idiopathic intracranial hypertension can rarely be associated with Addison's disease and present as an acute illness. Idiopathic intracranial hypertension is possibly related to an increase in the levels of arginine vasopressin peptide in serum and cerebrospinal fluid secondary to a glucocorticoid deficient state.</p

Islamic Monetary Economics: Insights from the Literature

This chapter reviews critical early literature of Islamic monetary economics. The prohibition of Riba has imposed challenges on Islamic economists to come up with the viable alternatives to achieve Islamic monetary policy goals. Our extensive review of theoretical and empirical literature indicates that equity based profit- and loss-sharing instruments have been proposed for conducting open market operations in an interest-free economy. Theoretically, the central bank can achieve desired goals by controlling money supply and profit-sharing ratios. The findings from empirical literature suggest that money demand tend to be more stable in an interest-free economy. Whether monetary transmission works through Islamic banking channel is controversial, but the literature is growing. These findings are not surprising as majority Muslim countries lack sustainable and equitable economic growth. Moreover, these countries suffer from higher inflation and unemployment with little or no monetary freedom due to fixed exchange rate regime, shallow financial markets and strict capital control

A boosting method for maximizing the partial area under the ROC curve

<p>Abstract</p> <p>Background</p> <p>The receiver operating characteristic (ROC) curve is a fundamental tool to assess the discriminant performance for not only a single marker but also a score function combining multiple markers. The area under the ROC curve (AUC) for a score function measures the intrinsic ability for the score function to discriminate between the controls and cases. Recently, the partial AUC (pAUC) has been paid more attention than the AUC, because a suitable range of the false positive rate can be focused according to various clinical situations. However, existing pAUC-based methods only handle a few markers and do not take nonlinear combination of markers into consideration.</p> <p>Results</p> <p>We have developed a new statistical method that focuses on the pAUC based on a boosting technique. The markers are combined componentially for maximizing the pAUC in the boosting algorithm using natural cubic splines or decision stumps (single-level decision trees), according to the values of markers (continuous or discrete). We show that the resulting score plots are useful for understanding how each marker is associated with the outcome variable. We compare the performance of the proposed boosting method with those of other existing methods, and demonstrate the utility using real data sets. As a result, we have much better discrimination performances in the sense of the pAUC in both simulation studies and real data analysis.</p> <p>Conclusions</p> <p>The proposed method addresses how to combine the markers after a pAUC-based filtering procedure in high dimensional setting. Hence, it provides a consistent way of analyzing data based on the pAUC from maker selection to marker combination for discrimination problems. The method can capture not only linear but also nonlinear association between the outcome variable and the markers, about which the nonlinearity is known to be necessary in general for the maximization of the pAUC. The method also puts importance on the accuracy of classification performance as well as interpretability of the association, by offering simple and smooth resultant score plots for each marker.</p

An archival case study : revisiting the life and political economy of Lauchlin Currie

This paper forms part of a wider project to show the significance of archival material on distinguished economists, in this case Lauchlin Currie (1902-93), who studied and taught at Harvard before entering government service at the US Treasury and Federal Reserve Board as the intellectual leader of Roosevelt's New Deal, 1934-39, as FDR's White House economic adviser in peace and war, 1939-45, and as a post-war development economist. It discusses the uses made of the written and oral material available when the author was writing his intellectual biography of Currie (Duke University Press 1990) while Currie was still alive, and the significance of the material that has come to light after Currie's death

Forecasting Player Behavioral Data and Simulating in-Game Events

Understanding player behavior is fundamental in game data science. Video games evolve as players interact with the game, so being able to foresee player experience would help to ensure a successful game development. In particular, game developers need to evaluate beforehand the impact of in-game events. Simulation optimization of these events is crucial to increase player engagement and maximize monetization. We present an experimental analysis of several methods to forecast game-related variables, with two main aims: to obtain accurate predictions of in-app purchases and playtime in an operational production environment, and to perform simulations of in-game events in order to maximize sales and playtime. Our ultimate purpose is to take a step towards the data-driven development of games. The results suggest that, even though the performance of traditional approaches such as ARIMA is still better, the outcomes of state-of-the-art techniques like deep learning are promising. Deep learning comes up as a well-suited general model that could be used to forecast a variety of time series with different dynamic behaviors