Evaluating the Eleventh District's Beige Book

In this study, Nathan Balke and Mine Yucel ask whether the Eleventh Federal Reserve District's Beige Book description contains timely information about economic activity within the District. They examine whether the Beige Book description tracks current Texas real gross state product (GSP) growth and current Texas employment growth. They also study whether the Beige Book has information about growth not present in other regional indicators that would have been available to analysts at the time of the Beige Book's release. They find that both the Beige Book summary and the average across sectors reflect Texas GSP and employment growth very well. These two measures of the Beige Book also have predictive content for one quarter ahead GSP growth. Balke and Yucel also find that the Eleventh District's Beige Book has information content for Texas economic activity over and above other state economic indicators such as Texas employment growth, personal income, or sectoral employment growth. Because the Beige Book is released at least one month earlier than employment data and at least two years before GSP data, its timeliness makes it a good tool for current regional economic analysis.Employment (Economic theory) ; Unemployment ; Economic indicators

Nematic elastomers with aligned carbon nanotubes: new electromechanical actuators

We demonstrate, for the first time, the large electromechanical response in nematic liquid crystalline elastomers filled with a very low (~0.01%) concentration of carbon nanotubes, aligned along the nematic director at preparation. The nanotubes create a very large effective dielectric anisotropy of the composite. Their local field-induced torque is transmitted to the rubber-elastic network and is registered as the exerted uniaxial stress of order ~1kPa in response to a constant field of order ~1MV/m. We investigate the dependence of the effect on field strength, nanotube concentration and reproducibility under multiple field-on and -off cycles. The results indicate the potential of the nanotube-nematic elastomer composites as electrically driven actuators

Oil price shocks and U.S. economic activity: an international perspective

Oil price shocks are thought to have played a prominent role in U.S. economic activity. In this paper, we employ Bayesian methods with a dynamic stochastic general equilibrium model of world economic activity to identify the various sources of oil price shocks and economic fluctuation and to assess their effects on U.S. economic activity. We find that changes in oil prices are best understood as endogenous. Oil price shocks in the 1970s and early 1980s and the 2000s reflect differing mixes of shifts in oil supply and demand, and differing sources of oil price shocks have differing effects on economic activity. We also find that U.S. output fluctuations owe mostly to domestic shocks, with productivity shocks contributing to weakness in the 1970s and 1980s and strength in the 2000s.Petroleum products - Prices ; Petroleum industry and trade ; Economic conditions - United States ; Business cycles

Crude oil and gasoline prices: an asymmetric relationship?

Gasoline is the petroleum product whose price is most visible and, therefore, always under public scrutiny. Many claim there is an asymmetric relationship between gasoline and oil prices - specifically, gasoline price changes follow oil price changes more quickly when oil prices are rising than when they are falling. To explore this issue, Nathan Balke, Stephen Brown and Mine Yucel use several different model specifications to analyze the relationship between oil prices and the spot, wholesale, and retail prices of gasoline. They find asymmetry is sensitive to model specification but is pervasive with the most general model.Petroleum industry and trade ; Prices

Oil price shocks and the U.S. economy: where does the asymmetry originate?

Rising oil prices appear to retard aggregate U.S. economic activity by more than falling oil prices stimulate it. Past research suggests adjustment costs and/or monetary policy may be possible explanations ofthe asymmetric response. This paper uses a quasi-vector autoregressive model of U. S. economy to examine from where the asymmetry might originate. The analysis uses counterfactual impulse response experiments to detennine that monetary policy alone cannot account for the asymmetry. The robustness ofshort-lived asymmetry across the base case and counterfactuals is consistent with the adjustment-cost explanation.Petroleum industry and trade

Oil Price Shocks and U.S. Economic Activity: An International Perspective

Oil price shocks are thought to have played a prominent role in U.S. economic activity. In this paper, we employ Bayesian methods with a dynamic stochastic general equilibrium model of world economic activity to identify the various sources of oil price shocks and economic fluctuation and to assess their effects on U.S. economic activity. We find that changes in oil prices are best understood as endogenous. Oil price shocks in the 1970s and early 1980s and the 2000s reflect differing mixes of shifts in oil supply and demand, and differing sources of oil price shocks have differing effects on economic activity. We also find that U.S. output fluctuations owe mostly to domestic shocks, with productivity shocks contributing to weakness in the 1970s and 1980s and strength in the 2000s.oil price, international business cycles, general equilibrium, Bayesian estimation

An international perspective on oil price shocks and U.S. economic activity

The effect of oil price shocks on U.S. economic activity seems to have changed since the mid-1990s. A variety of explanations have been offered for the seeming change—including better luck, the reduced energy intensity of the U.S. economy, a more flexible economy, more experience with oil price shocks and better monetary policy. These explanations point to a weakening of the relationship between oil prices shocks and economic activity rather than the fundamentally different response that may be evident since the mid-1990s.> ; Using a dynamic stochastic general equilibrium model of world economic activity, we employ Bayesian methods to assess how economic activity responds to oil price shocks arising from supply shocks and demand shocks originating in the United States or elsewhere in the world. We find that both oil supply and oil demand shocks have contributed significantly to oil price fluctuations and that U.S. output fluctuations are derived largely from domestic shocks.Petroleum industry and trade ; Petroleum products - Prices ; International trade ; Economic conditions - United States

Modulating the catalytic activity of enzyme-like nanoparticles through their surface functionalization

The inclusion of transition metal catalysts into nanoparticle scaffolds permits the creation of catalytic nanosystems (nanozymes) able to imitate the behaviour of natural enzymes. Here we report the fabrication of a family of nanozymes comprised of bioorthogonal ruthenium catalysts inserted in the protective monolayer of gold nanoparticles. By introducing simple modifications to the functional groups at the surface of the nanozymes, we have demonstrated control over the kinetic mechanism of our system. Cationic nanozymes with hydrophobic surface functionalities tend to replicate the classical Michaelis Menten model, while those with polar groups display substrate inhibition behaviour, a key mechanism present in 20% of natural enzymes. The structural parameters described herein can be used for creating artificial nanosystems that mimic the complexity observed in cell machinery. © 2018 The Royal Society of Chemistry

Gamma Irradiation on Growth and Development of Amorphophallus Muelleri Blume.

Iles-iles (Amorphophallus muelleri Blume) produces apomictic seeds lead to low genetic variation. In order to induce genetic variation, germinated seeds were exposed to Gamma irradiation (Co-60) at doses of 10 to 100 Gy. Seed irradiation was conducted at Center for the Application of Isotope and Irradiation Technology -National Nuclear Energy Agency (CAIRT), Indonesia. Morphology and yield of M1 generation were observed. Results showed that irradiation at a dose of 10 Gy close to LD50 with survival rate 56%. Gamma irradiation at a dose of 10 Gy delayed seeds germination. Germination rates gradually increased and reached maximum at 4 weeks after planting (WAP) for control plants, and 14 WAP of irradiated plants. At 16 WAP, germination rate of 10 Gy irradiated plants was 56% and 84% for those of control plants. Irradiation induced chimera as indicated by short petiole, variegated and abnornal shape of leaflets. Some irradiated plants entered dormancy at 8-10 weeks later than control ones. Prolong vegetative periode lead the plants to produce heavier corms. This study revealed the possibility to induce variation of A. muelleri by using gamma irradition. Keywords: Amorphophallus muelleri, gamma irradiation (Co-60), morphological variation, mutation breedin

Predicting the Debonding of CAD/CAM Composite Resin Crowns with AI

A preventive measure for debonding has not been established and is highly desirable to improve the survival rate of computer-aided design/computer-aided manufacturing (CAD/CAM) composite resin (CR) crowns. The aim of this study was to assess the usefulness of deep learning with a convolution neural network (CNN) method to predict the debonding probability of CAD/CAM CR crowns from 2-dimensional images captured from 3-dimensional (3D) stereolithography models of a die scanned by a 3D oral scanner. All cases of CAD/CAM CR crowns were manufactured from April 2014 to November 2015 at the Division of Prosthodontics, Osaka University Dental Hospital (Ethical Review Board at Osaka University, approval H27-E11). The data set consisted of a total of 24 cases: 12 trouble-free and 12 debonding as known labels. A total of 8,640 images were randomly divided into 6,480 training and validation images and 2,160 test images. Deep learning with a CNN method was conducted to develop a learning model to predict the debonding probability. The prediction accuracy, precision, recall, F-measure, receiver operating characteristic, and area under the curve of the learning model were assessed for the test images. Also, the mean calculation time was measured during the prediction for the test images. The prediction accuracy, precision, recall, and F-measure values of deep learning with a CNN method for the prediction of the debonding probability were 98.5%, 97.0%, 100%, and 0.985, respectively. The mean calculation time was 2 ms/step for 2,160 test images. The area under the curve was 0.998. Artificial intelligence (AI) technology—that is, the deep learning with a CNN method established in this study—demonstrated considerably good performance in terms of predicting the debonding probability of a CAD/CAM CR crown with 3D stereolithography models of a die scanned from patients.Yamaguchi S., Lee C., Karaer O., et al. Predicting the Debonding of CAD/CAM Composite Resin Crowns with AI. Journal of Dental Research, 98(11), 1234-1238. © 2019 Sage Publications. DOI: 10.1177/0022034519867641