Social Networks and the Aggregation on Individual Decisions

This paper analyzes individual decisions to participate in an activity and the aggregation of those decisions when individuals gather information about the outcomes and choices of (a few) others in their social network. In this environment, aggregate participation rates are generally inefficient. Increasing the size of social networks does not necessarily increase efficiency and can lead to less efficient long-run outcomes. Both subsidies for participation and penalties for non-participation can increase participation rates, though not necessarily by the same amount. Punishing non-participation has much greater effects on participation rates than rewarding participation when current rates are very low. A program that provides youth with mentors who have participated themselves can increase participation rates, especially when those rates are low. Finally, communities plagued by the flight of successful participants will experience lower short- and long-run participation rates.

Estimation of the diagnostic accuracy of organ electrodermal diagnostics

Objective. To estimate the diagnostic accuracy and the scope of utilisation of a new bio-electronic method of organ diagnostics. Design. Double-blind comparative study of the diagnostic results obtained using organ electrodermal diagnostics (OED), with clinical diagnosis as the criterion standard. Setting. Department of Surgery, Helen Joseph Hospital, Johannesburg. Patients. Two hundred pre-selected inpatients of mean age 38 years (standard deviation 9 years) with suspected pathology of one (or more) of the following organs: oesophagus, stomach, gallbladder, pancreas, colon, kidneys, urinary bladder and prostate. In total, 714 of the abovementioned internal organs were selected for statistical consideration. Main outcome measures. The degree of rectification of the measuring current once the resistance ‘breakthrough effect' has been induced in the skin, as well as the difference in impedance measured at organ projection areas (OPAs) (skin zones corresponding to particular internal organs). Results. In total, 630 true OED results were obtained from the 714 subjects considered, with a detection rate of 88.2% (95% confidence interval (CI): 85.6 - 90.5%). Established OED sensitivity was 89.5% (CI: 85.2 - 92.8%) and OED specificity equalled 87.5% (CI: 84.0 - 90.4%). The predictive value for positive OED results was 81.7% (CI: 76.9 - 85.9%) and for negative OED results 93.0% (CI 90.1 - 95.2%). Healthy organs usually produced the OED result ‘healthy' or ‘within normal limits', while subacute pathology displayed ‘subcute' and acute pathology ‘acute'. The OED results were not affected by either the type or the aetiology of disease, i.e. OED estimated the actual extent of pathological process activity within particular organs but did not directly explain the cause of pathology. Conclusions. So-called OPAs do exist on the skin surface. Pathology of a particular organ causes a related OPA to rectify electrical currents once the resistance ‘breakthrough effect' has been induced in the skin. Pathology of an internal organ also increases the impedance of the corresponding OPA. The degree of rectification or difference in impedance is proportional to the extent of the pathological process within this organ. OED which utilises the abovementioned electrical phenomena of the skin, is a reliable bio-electronic method of non-invasive medical diagnostics, with high rates of sensitivity, specificity and predictive values. OED may be used to detect diseased organs and estimate the extent of pathological process activity. S Afr Med J 2004; 94: 547-551

Classification of Multiwavelength Transients with Machine Learning

With the advent of powerful telescopes such as the Square Kilometer Array and the Vera C. Rubin Observatory, we are entering an era of multiwavelength transient astronomy that will lead to a dramatic increase in data volume. Machine learning techniques are well suited to address this data challenge and rapidly classify newly detected transients. We present a multiwavelength classification algorithm consisting of three steps: (1) interpolation and augmentation of the data using Gaussian processes; (2) feature extraction using wavelets; and (3) classification with random forests. Augmentation provides improved performance at test time by balancing the classes and adding diversity into the training set. In the first application of machine learning to the classification of real radio transient data, we apply our technique to the Green Bank Interferometer and other radio light curves. We find we are able to accurately classify most of the 11 classes of radio variables and transients after just eight hours of observations, achieving an overall test accuracy of 78 percent. We fully investigate the impact of the small sample size of 82 publicly available light curves and use data augmentation techniques to mitigate the effect. We also show that on a significantly larger simulated representative training set that the algorithm achieves an overall accuracy of 97 percent, illustrating that the method is likely to provide excellent performance on future surveys. Finally, we demonstrate the effectiveness of simultaneous multiwavelength observations by showing how incorporating just one optical data point into the analysis improves the accuracy of the worst performing class by 19 percent.Comment: 16 pages, 12 figure

Price Prediction in a Trading Agent Competition

The 2002 Trading Agent Competition (TAC) presented a challenging market game in the domain of travel shopping. One of the pivotal issues in this domain is uncertainty about hotel prices, which have a significant influence on the relative cost of alternative trip schedules. Thus, virtually all participants employ some method for predicting hotel prices. We survey approaches employed in the tournament, finding that agents apply an interesting diversity of techniques, taking into account differing sources of evidence bearing on prices. Based on data provided by entrants on their agents' actual predictions in the TAC-02 finals and semifinals, we analyze the relative efficacy of these approaches. The results show that taking into account game-specific information about flight prices is a major distinguishing factor. Machine learning methods effectively induce the relationship between flight and hotel prices from game data, and a purely analytical approach based on competitive equilibrium analysis achieves equal accuracy with no historical data. Employing a new measure of prediction quality, we relate absolute accuracy to bottom-line performance in the game

Childhood trauma in adults with social anxiety disorder and panic disorder: a cross-national study

Objectives: The influence of childhood trauma as a specific environmental factor on the development of adult psychopathology is far from being elucidated. As part of a collaborative project between research groups from South Africa (SA) and Sweden focusing on genetic and environmental factors contributing to anxiety disorders, this study specifically investigated rates of childhood trauma in South African and Swedish patients respectively, and whether, in the sample as a whole, different traumatic experiences in childhood are predictive of social anxiety (SAD) or panic disorder (PD) in adulthood. Method: Participants with SAD or PD (85 from SA, 135 from Sweden) completed the Childhood Trauma Questionnaire (CTQ). Logistic regression was performed with data from the two countries separately, and from the sample as a whole, with primary diagnoses as dependent variables, gender, age, and country as covariates, and the CTQ subscale totals as independent variables. The study also investigated the internal consistency (Cronbach alpha) of the CTQ subscales. Results: SA patients showed higher levels of childhood trauma than Swedish patients. When data from both countries were combined, SAD patients reported higher rates of childhood emotional abuse compared to those with PD. Moreover, emotional abuse in childhood was found to play a predictive role in SAD/PD in adulthood in the Swedish and the combined samples, and the same trend was found in the SA sample. The psychometric qualities of the CTQ subscales were adequate, with the exception of the physical neglect subscale. Conclusion: Our findings suggest that anxiety disorder patients may differ across countries in terms of childhood trauma. Certain forms of childhood abuse may contribute specific vulnerability to different types of psychopathology. Longitudinal studies should focus on the potential sequential development of SAD/PD among individuals with childhood emotional abuse.Keywords: Childhood trauma; Social anxiety disorder; Panic disorder; Cross-nationa

Discovery of a new Transient X-ray Pulsar in the Small Magellanic Cloud

Rossi X-Ray Timing Explorer observations of the Small Magellanic Cloud have revealed a previously unknown transient X-ray pulsar with a pulse period of 95s. Provisionally designated XTE SMC95, the pulsar was detected in three Proportional Counter Array observations during an outburst spanning 4 weeks in March/April 1999. The pulse profile is double peaked reaching a pulse fraction \~0.8. The source is proposed as a Be/neutron star system on the basis of its pulsations, transient nature and characteristically hard X-ray spectrum. The 2-10 keV X-ray luminosity implied by our observations is > 2x10^37 erg/s which is consistent with that of normal outbursts seen in Galactic systems. This discovery adds to the emerging picture of the SMC as containing an extremely dense population of transient high mass X-ray binaries.Comment: Accepted by A&A. 7 pages, 6 figure