Does money matter in inflation forecasting?.

This paper provides the most fully comprehensive evidence to date on whether or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide range of different definitions of money, including different methods of aggregation and different collections of included monetary assets. In our forecasting experiment we use two non-linear techniques, namely, recurrent neural networks and kernel recursive least squares regression - techniques that are new to macroeconomics. Recurrent neural networks operate with potentially unbounded input memory, while the kernel regression technique is a finite memory predictor. The two methodologies compete to find the best fitting US inflation forecasting models and are then compared to forecasts from a naive random walk model. The best models were non-linear autoregressive models based on kernel methods. Our findings do not provide much support for the usefulness of monetary aggregates in forecasting inflation

Does money matter in inflation forecasting?

This paper provides the most fully comprehensive evidence to date on whether or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide range of different definitions of money, including different methods of aggregation and different collections of included monetary assets. In our forecasting experiment we use two non-linear techniques, namely, recurrent neural networks and kernel recursive least squares regression - techniques that are new to macroeconomics. Recurrent neural networks operate with potentially unbounded input memory, while the kernel regression technique is a finite memory predictor. The two methodologies compete to find the best fitting US inflation forecasting models and are then compared to forecasts from a naive random walk model. The best models were non-linear autoregressive models based on kernel methods. Our findings do not provide much support for the usefulness of monetary aggregates in forecasting inflation.Forecasting ; Inflation (Finance) ; Monetary theory

Remote Control Aircraft

The purpose of the RC aircraft design was not to address a problem that has not been solved, but to redesign an aircraft with the intent to understand the practical applications of the building process. Our approach to completing this project involved two phases; the planning phase and the building phase. In the planning phase, we made selections for the airfoil, wing, fuselage, tail, elevators, and ailerons. These choices were made using aeronautical engineering concepts and theory. For the building phase, we focused on materials selection, fabrication, and testing. During our design process, a lot of time went to choosing the airfoil. While researching, we considered three governing factors: drag coefficient, lift coefficient, and manufacturability. Each airfoil offered a variation of these parameters.The Eppler 423 airfoil was picked for its low drag coefficient. There were issues during fabrication. These issues mainly stemmed from the lack of quality equipment. For example, initial attempts to cut the balsa wood into the airfoil profile caused wood splitting. This happened because the saw was too coarse for that grain of wood. If this project were redone, we would utilize tools that are commonly used within the hobbyist community to optimize fabrication. Our project focused on the application of the engineering design process that we have become familiar with as undergraduate students. In terms of purpose, our project would identify most with the R/C aircraft hobbyist community and FSAE community that also engineer and build aircrafts for personal or competition uses.https://scholarscompass.vcu.edu/capstone/1137/thumbnail.jp

New, nearby bright southern ultracool dwarfs

We report the discovery of twenty-one hitherto unknown bright southern ultracool dwarfs with spectral types in the range M7 to L5.5, together with new observations of a further three late M dwarfs previously confirmed. Three more objects are already identified in the literature as high proper motion stars;we derive their spectral types for the first time. All objects were selected from the 2MASS All Sky and SuperCOSMOS point source databases on the basis of their optical/near-infrared colours, $J$-band magnitudes and proper motions. Low resolution (R $\sim$ 1000) $JH$ spectroscopy with the ESO/NTT SOFI spectrograph has confirmed the ultracool nature of 24 targets, out of a total of 25 candidates observed. Spectral types are derived by direct comparison with template objects and compared to results from H$_2$O and FeH indices. We also report the discovery of one binary, as revealed by SOFI acquisition imaging; spectra were taken for both components. The spectral types of the two components are L2 and L4 and the distance $\sim$ 19 pc. Spectroscopic distances and transverse velocities are derived for the sample. Two $\sim$ L5 objects lie only $\sim$ 10 pc distant. Such nearby objects are excellent targets for further study to derive their parallaxes and to search for fainter, later companions with AO and/or methane imaging.Comment: 11 pages, 10 figures, accepted to MNRA

Evolution, recurrency and kernels in learning to model inflation

This paper provides the most fully comprehensive evidence to date on whether or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide range of different definitions of money, including different methods of aggregation and different collections of included monetary assets. We use non-linear, artificial intelligence techniques, namely, recurrent neural networks, evolution strategies and kernel methods in our forecasting experiment. In the experiment, these three methodologies compete to find the best fitting US inflation forecasting models and are then compared to forecasts from a naive random walk model. The best models were non-linear autoregressive models based on kernel methods. Our findings do not provide much support for the usefulness of monetary aggregates in forecasting inflation. There is evidence in the literature that evolutionary methods can be used to evolve kernels hence our future work should combine the evolutionary and kernel methods to get the benefits of both

Platelet aggregation induced by polystyrene and platinum nanoparticles is dependent on surface area

Nanoparticles are key components underlying recent technological advances in various industrial and medical fields, and thus understanding their mode of interaction with biological systems is essential. However, while several nanoparticle systems have been shown to interact with blood platelets, many questions remain concerning the mechanisms of platelet activation and the role that the physicochemical properties of nanoparticles play in inducing platelet aggregation. Here, using negatively charged polystyrene nanoparticles with sizes of 25, 50, 119, 151, 201 nm and negatively charged platinum nanoparticles with sizes of 7 and 73 nm, we show that it is not the size of the nanoparticles but rather the nanoparticle surface area that is critical in mediating the effects on platelet activation. The nanoparticles stimulate platelet aggregation through passive (agglutination) and activation of integrin αIIbβ3 through a pathway regulated by Src and Syk tyrosine kinase

Liberal arts student learning outcomes: An integrated approach

Researchers completing a study of liberal arts education sought to identify learning outcomes associated with both wisdom and citizenship. They have synthesized these themes into seven outcomes that facilitate effective student learning and development.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/57388/1/222_ftp.pd