Are disaggregate industrial returns sensitive to economic policy uncertainty

© 2019 Elsevier B.V. This study investigates the impact of economic policy uncertainty on disaggregate US sector based returns. Our work is motivated by the presence of non-linear relationship between US economic policy uncertainty and equity returns of sampled US sectors. The paper uses weekly data from January 1995 to December 2015 for all the return indices and economic policy uncertainty data mainly based on policy issues, provision set for the US federal tax code and disagreement among economic forecasters. Our results indicate that information technology, utilities, industrial and telecommunication sectors remain insensitive to changes in the US economic policy uncertainty. However, financial and the consumer discretionary sectors show significant long run asymmetric relationship with the EPU.Accepted versio

Intelligent Traffic Signal Automation Based on Computer Vision Techniques Using Deep Learning

Traffic congestion in highly populated urban areas is a huge problem these days. A lot of researchers have proposed many systems to monitor traffic flow and handle congestion through different techniques. But the current systems are not reliable enough to perceive traffic signals in real-time. Therefore, we aim to build a system that can efficiently perform real-time environments to solve the traffic congestion problem through signal automation. Since vehicle detection and counting are crucial in any traffic system, we use state-of-the-art deep learning techniques to detect and count vehicles in real-time. We then automate the signal timings by comparing the count of traffic on all sides of a junction. These automated signal timings sufficiently reduce congestion and improve traffic flow. We prepared a dataset of 4500 images and achieved about 91% accuracy by training it on Faster RCNN

Strategic crossing of biomass and harvest index—source and sink—achieves genetic gains in wheat

To accelerate genetic gains in breeding, physiological trait (PT) characterization of candidate parents can help make more strategic crosses, increasing the probability of accumulating favorable alleles compared to crossing relatively uncharacterized lines. In this study, crosses were designed to complement “source” with “sink” traits, where at least one parent was selected for favorable expression of biomass and/or radiation use efficiency—source—and the other for sink-related traits like harvest-index, kernel weight and grains per spike. Female parents were selected from among genetic resources—including landraces and products of wide-crossing (i.e. synthetic wheat)—that had been evaluated in Mexico at high yield potential or under heat stress, while elite lines were used as males. Progeny of crosses were advanced to the F4 generation within Mexico, and F4-derived F5 and F6 generations were yield tested to populate four international nurseries, targeted to high yield environments (2nd and 3rd WYCYT) for yield potential, and heat stressed environments (2nd and 4th SATYN) for climate resilience, respectively. Each nursery was grown as multi-location yield trials. Genetic gains were achieved in both temperate and hot environments, with most new PT-derived lines expressing superior yield and biomass compared to local checks at almost all international sites. Furthermore, the tendency across all four nurseries indicated either the superiority of the best new PT lines compared with the CIMMYT elite checks, or the superiority of all new PT lines as a group compared with all checks, and in some cases, both. Results support—in a realistic breeding context—the hypothesis that yield and radiation use efficiency can be increased by improving source:sink balance, and validate the feasibility of incorporating exotic germplasm into mainstream breeding efforts to accelerate genetic gains for yield potential and climate resilience

Inclusive and multiplicity dependent production of electrons from heavy-flavour hadron decays in pp and p-Pb collisions

Measurements of the production of electrons from heavy-flavour hadron decays in pp collisions at root s = 13 TeV at midrapidity with the ALICE detector are presented down to a transverse momentum (p(T)) of 0.2 GeV/c and up to p(T) = 35 GeV/c, which is the largest momentum range probed for inclusive electron measurements in ALICE. In p-Pb collisions, the production cross section and the nuclear modification factor of electrons from heavy-flavour hadron decays are measured in the p(T) range 0.5 < p(T) < 26 GeV/c at root s(NN) = 8.16 TeV. The nuclear modification factor is found to be consistent with unity within the statistical and systematic uncertainties. In both collision systems, first measurements of the yields of electrons from heavy-flavour hadron decays in different multiplicity intervals normalised to the multiplicity-integrated yield (self-normalised yield) at midrapidity are reported as a function of the self-normalised charged-particle multiplicity estimated at midrapidity. The self-normalised yields in pp and p-Pb collisions grow faster than linear with the self-normalised multiplicity. A strong p(T) dependence is observed in pp collisions, where the yield of high-p(T) electrons increases faster as a function of multiplicity than the one of low-p(T) electrons. The measurement in p-Pb collisions shows no p(T) dependence within uncertainties. The self-normalised yields in pp and p-Pb collisions are compared with measurements of other heavy-flavour, light-flavour, and strange particles, and with Monte Carlo simulations