Compressed television transmission: A market survey

NASA's compressed television transmission technology is described, and its potential market is considered; a market that encompasses teleconferencing, remote medical diagnosis, patient monitoring, transit station surveillance, as well as traffic management and control. In addition, current and potential television transmission systems and their costs and potential manufacturers are considered

The mechanism of double exponential growth in hyper-inflation

Analyzing historical data of price indices we find an extraordinary growth phenomenon in several examples of hyper-inflation in which price changes are approximated nicely by double-exponential functions of time. In order to explain such behavior we introduce the general coarse-graining technique in physics, the Monte Carlo renormalization group method, to the price dynamics. Starting from a microscopic stochastic equation describing dealers' actions in open markets we obtain a macroscopic noiseless equation of price consistent with the observation. The effect of auto-catalytic shortening of characteristic time caused by mob psychology is shown to be responsible for the double-exponential behavior.Comment: 9 pages, 5 figures and 2 tables, submitted to Physica

Correlates of elevational specialisation in Southeast Asian tropical birds

The understanding of elevational selectivity in extremely rich tropical biotas is critical to the study of accelerating human-mediated environmental changes (e.g., deforestation and global climate warming). This paper explores the characteristics of Southeast Asian birds that are altitudinal specialists (i.e., lowland specialists and montane specialists) by assessing the relative importance of various species traits (e.g., breeding phenology and clutch size) in determining the altitudinal specialisation of these tropical birds. After controlling for phylogeny, we found that habitat specificity, breeding phenology, and clutch size were significant correlates of lowland specialisation. The most parsimonious model predicting lowland specialisation included the first of these only. Breeding phenology was the significant phylogeny-independent correlate of montane specialisation. Thus, species were confined to altitudinal niches by different constraints. By analysing the altitudinal distribution of Southeast Asian birds, we provide insights on why altitudinal confinement exists in lowland and montane specialists. Understanding such constraints may be important for the conservation of tropical birds

Evidence and Ideology in Macroeconomics: The Case of Investment Cycles

The paper reports the principal findings of a long term research project on the description and explanation of business cycles. The research strongly confirmed the older view that business cycles have large systematic components that take the form of investment cycles. These quasi-periodic movements can be represented as low order, stochastic, dynamic processes with complex eigenvalues. Specifically, there is a fixed investment cycle of about 8 years and an inventory cycle of about 4 years. Maximum entropy spectral analysis was employed for the description of the cycles and continuous time econometrics for the explanatory models. The central explanatory mechanism is the second order accelerator, which incorporates adjustment costs both in relation to the capital stock and the rate of investment. By means of parametric resonance it was possible to show, both theoretically and empirically how cycles aggregate from the micro to the macro level. The same mathematical tool was also used to explain the international convergence of cycles. I argue that the theory of investment cycles was abandoned for ideological, not for evidential reasons. Methodological issues are also discussed

Money supply, interest rate, liquidity and share prices: A test of their linkage

This paper reports new evidence of a liquidity effect on share prices from money supply changes. Money supply impacts on interest rate and liquidity were first proposed in 1969 and there is evidence that money supply increase leads to interest rate decline. Yet the proposition that money supply increase should lead to liquidity surge – thus to credit expansion – has yet received unanimous empirical support. Using quarterly data over 1968-2011, our results from a two-stage simultaneous solution of a system of equations indicate that money supply changes lead to a positive liquidity effect, as per the theory prediction. By extending the liquidity equation to asset prices, we also show that liquidity change has a significant positive effect on share prices, after controlling the effect of earnings. These findings, obtained after solutions to serious econometric issues of existing studies, appear to provide a clear verification of theory on the money supply effect on liquidity and on asset price

Methods to Develop an Electronic Medical Record Phenotype Algorithm to Compare the Risk of Coronary Artery Disease across 3 Chronic Disease Cohorts

Background Typically, algorithms to classify phenotypes using electronic medical record (EMR) data were developed to perform well in a specific patient population. There is increasing interest in analyses which can allow study of a specific outcome across different diseases. Such a study in the EMR would require an algorithm that can be applied across different patient populations. Our objectives were: (1) to develop an algorithm that would enable the study of coronary artery disease (CAD) across diverse patient populations; (2) to study the impact of adding narrative data extracted using natural language processing (NLP) in the algorithm. Additionally, we demonstrate how to implement CAD algorithm to compare risk across 3 chronic diseases in a preliminary study. Methods and Results We studied 3 established EMR based patient cohorts: diabetes mellitus (DM, n = 65,099), inflammatory bowel disease (IBD, n = 10,974), and rheumatoid arthritis (RA, n = 4,453) from two large academic centers. We developed a CAD algorithm using NLP in addition to structured data (e.g. ICD9 codes) in the RA cohort and validated it in the DM and IBD cohorts. The CAD algorithm using NLP in addition to structured data achieved specificity >95% with a positive predictive value (PPV) 90% in the training (RA) and validation sets (IBD and DM). The addition of NLP data improved the sensitivity for all cohorts, classifying an additional 17% of CAD subjects in IBD and 10% in DM while maintaining PPV of 90%. The algorithm classified 16,488 DM (26.1%), 457 IBD (4.2%), and 245 RA (5.0%) with CAD. In a cross-sectional analysis, CAD risk was 63% lower in RA and 68% lower in IBD compared to DM (p<0.0001) after adjusting for traditional cardiovascular risk factors. Conclusions We developed and validated a CAD algorithm that performed well across diverse patient populations. The addition of NLP into the CAD algorithm improved the sensitivity of the algorithm, particularly in cohorts where the prevalence of CAD was low. Preliminary data suggest that CAD risk was significantly lower in RA and IBD compared to DM.National Institutes of Health (U.S.). Informatics for Integrating Biology and the Bedside Project (U54LM008748