Personality and the happiness of others : a study among 13- to 15-year-old adolescents

This study was designed to assess the level of concern for the happiness of others among a sample of 13- to 15-year-old adolescents in England (N=3,095) and to test the theory that concern for the happiness of others occupies a different psychological space (within Eysenck’s three dimensional model of personality) from the space occupied by personal happiness. The data demonstrated a high level of concern for the happiness of others, with 84% of the adolescents saying that, ‘It is important to me to make other people happy’. While high levels of personal happiness are generally shown to be associated with low neuroticism and high extraversion (stable extraversion), these data demonstrated high levels of concern for the happiness of others tend to be associated with high neuroticism, high extraversion, high social conformity, and low psychoticism

Nanoscale all-oxide-heterostructured bio-inspired optoresponsive nociceptor

Retina nociceptor, as a key sensory receptor, not only enables the transport of warning signals to the human central nervous system upon its exposure to noxious stimuli, but also triggers the motor response that minimizes potential sensitization. In this study, the capability of two-dimensional all-oxide-heterostructured artificial nociceptor as a single device with tunable properties was confirmed. Newly designed nociceptors utilize ultra-thin sub-stoichiometric TiO2-Ga2O3 heterostructures, where the thermally annealed Ga2O3 films play the role of charge transfer controlling component. It is discovered that the phase transformation in Ga2O3 is accompanied by substantial jump in conductivity, induced by thermally assisted internal redox reaction of Ga2O3 nanostructure during annealing. It is also experimentally confirmed that the charge transfer in all-oxide heterostructures can be tuned and controlled by the heterointerfaces manipulation. Results demonstrate that the engineering of heterointerfaces of two-dimensional (2D) films enables the fabrication of either high-sensitive TiO2-Ga2O3 (Ar) or high-threshold TiO2-Ga2O3 (N-2) nociceptors. The hypersensitive nociceptor mimics the functionalities of corneal nociceptors of human eye, whereas the delayed reaction of nociceptor is similar to high-threshold nociceptive characteristics of human sensory system. The long-term stability of 2D nociceptors demonstrates the capability of heterointerfaces engineering for effective control of charge transfer at 2D heterostructured devices

Real-time price discovery in stock, bond and foreign exchange markets

We characterize the response of U.S., German and British stock, bond and foreign exchange markets to real-time U.S. macroeconomic news. Our analysis is based on a unique data set of high-frequency futures returns for each of the markets. We find that news surprises produce conditional mean jumps; hence high-frequency stock, bond and exchange rate dynamics are linked to fundamentals. The details of the linkages are particularly intriguing as regards equity markets. We show that equity markets react differently to the same news depending on the state of the economy, with bad news having a positive impact during expansions and the traditionally-expected negative impact during recessions. We rationalize this by temporal variation in the competing "cash flow" and "discount rate" effects for equity valuation. This finding helps explain the time-varying correlation between stock and bond returns, and the relatively small equity market news effect when averaged across expansions and recessions. Lastly, relying on the pronounced heteroskedasticity in the high-frequency data, we document important contemporaneous linkages across all markets and countries over-and-above the direct news announcement effects. JEL Klassifikation: F3, F4, G1, C

Using machine learning to predict the number of alternative solutions to a minimum cardinality set covering problem

Although the characterization of alternative optimal solutions for linear programming problems is well known, such characterizations for combinatorial optimization problems are essentially non-existent. This is the first article to qualitatively predict the number of alternative optima for a classic NP-hard combinatorial optimization problem, namely, the minimum cardinality (also called unicost) set covering problem (MCSCP). For the MCSCP, a set must be covered by a minimum number of subsets selected from a specified collection of subsets of the given set. The MCSCP has numerous industrial applications that require that a secondary objective is optimized once the size of a minimum cover has been determined. To optimize the secondary objective, the number of MCSCP solutions is optimized. In this article, for the first time, a machine learning methodology is presented to generate categorical regression trees to predict, qualitatively (extra-small, small, medium, large, or extra-large), the number of solutions to an MCSCP. Within the machine learning toolbox of MATLAB®, 600,000 unique random MCSCPs were generated and used to construct regression trees. The prediction quality of these regression trees was tested on 5000 different MCSCPs. For the 5-output model, the average accuracy of being at most one off from the predicted category was 94.2%.Â

A hierarchy of happiness? Mokken scaling analysis of the Oxford Happiness Inventory

The items of the Oxford Happiness Inventory (OHI, a self-report assessment of happiness, are subjected to an analysis for hierarchy among its items. By using Mokken scaling analyses we can assess whether items can reliably be ordered between persons as severity indicators on a latent trait; in this case, a latent trait of Happiness. OHI item-level data from 1024 participants were entered into the Mokken Scaling Procedure (MSP) seeking reliable scales with H > 0.30. 12 OHI items formed a reliable and statistically significant hierarchy. However, the MSP values indicate a 'weak' scale. The 'most difficult' (happiest) item on the scale is 'feeling energetic' and the 'least difficult' (least happy) is 'I have fun'. Items in the scale are consistent with what is already known about both happiness and low mood. The reduction in the OHI's items from 29 to 12 in the Mokken scale may have utility making it more accessible to participants as well as identifying items with reliably different levels of 'difficulty'. (C) 2010 Elsevier Ltd. All rights reserved

Using general-purpose integer programming software to generate bounded solutions for the multiple knapsack problem: a guide for or practitioners

An NP-Hard combinatorial optimization problem that has significant industrial applications is the Multiple Knapsack Problem. If approximate solution approaches are used to solve the Multiple Knapsack Problem there are no guarantees on solution quality and exact solution approaches can be intricate and challenging to implement.  This article demonstrates the iterative use of general-purpose integer programming software (Gurobi) to generate solutions for test problems that are available in the literature. Using the software package Gurobi on a standard PC, we generate in a relatively straightforward manner solutions to these problems in an average of less than a minute that are guaranteed to be within 0.16% of the optimum.  This algorithm, called the Simple Sequential Increasing Tolerance (SSIT) algorithm, iteratively increases tolerances in Gurobi to generate a solution that is guaranteed to be close to the optimum in a short time. This solution strategy generates bounded solutions in a timely manner without requiring the coding of a problem-specific algorithm. This approach is attractive to management for solving industrial problems because it is both cost and time effective and guarantees the quality of the generated solutions.  Finally, comparing SSIT results for 480 large multiple knapsack problem instances to results using published multiple knapsack problem algorithms demonstrates that SSIT outperforms these specialized algorithms

Health behaviors of American pregnant women: a cross-sectional analysis of NHANES 2007-2014.

BackgroundThis study examined engagement in five health behaviors among pregnant women in the USA.MethodsPregnant women who participated in the National Health and Nutrition Examination Survey 2007-2014 were included in this study. Five health behaviors were examined: adequate fruit and vegetable consumption, prenatal multivitamin use, physical activity, sleep and smoking. Multivariable regressions were used to estimate the odds ratio and 95% confidence interval of characteristics associated with health behaviors.ResultsAmong 248 pregnant women, only 10.2% engaged in all five health behaviors and 35.4% consumed adequate fruits and vegetables. For adequate fruit and vegetable consumption, Hispanic and women of 'other' race were more likely to meet the recommendation compared to non-Hispanic white (P = 0.01 and P = 0.03, respectively); high school graduates were less likely to meet the recommendation compared to those with at least some college education or more (P = 0.04).ConclusionsAdequate fruit and vegetable consumption among pregnant women was poor and differed by race/ethnicity and education status. Because of the cross-sectional design, we cannot examine engagement in health behaviors continuously throughout pregnancy. Future research with longitudinal data over the course of pregnancy is needed to confirm these results

CyberGuarder: a virtualization security assurance architecture for green cloud computing

Cloud Computing, Green Computing, Virtualization, Virtual Security Appliance, Security Isolation