Dynamic Boundaries in Asymmetric Exclusion Processes

We investigate the dynamics of a one-dimensional asymmetric exclusion process with Langmuir kinetics and a fluctuating wall. At the left boundary, particles are injected onto the lattice; from there, the particles hop to the right. Along the lattice, particles can adsorb or desorb, and the right boundary is defined by a wall particle. The confining wall particle has intrinsic forward and backward hopping, a net leftward drift, and cannot desorb. Performing Monte Carlo simulations and using a moving-frame finite segment approach coupled to mean field theory, we find the parameter regimes in which the wall acquires a steady state position. In other regimes, the wall will either drift to the left and fall off the lattice at the injection site, or drift indefinitely to the right. Our results are discussed in the context of non-equilibrium phases of the system, fluctuating boundary layers, and particle densities in the lab frame versus the frame of the fluctuating wall.Comment: 13 page

Intensive and extensive margins of the peak load: Measuring adaptation with mixed frequency panel data

In this work we investigate the response of daily electricity peak load to daily maximum temperatures across states in Europe and India. We propose a method that decomposes short- from medium/long-run effects, retains the high frequency nature of the load-weather covariation and treats economic growth as a modulating factor. By simultaneously exploiting variation in unexpected daily weather anomalies and decade-long climatic changes in each location we decompose transitory - intensive margin - adjustments from permanent - extensive margin - adjustments. We find that the shocks over the long-run differ substantially from the short-run dynamics. Furthermore, we find evidence that per capita income modulates the adjustments over the short- and long-run. We project that in response to climate change around 2050 the peak load may increase by up to 20%-30% in Southern Europe and in several states in India, depending on the degree of warming and the evolution of socio-economic conditions. Even with a limited scope to two world regions, we identify that the structure of the economy and differences in future income growth matter in shaping the adaptation to climate change. Our decomposition allows to identify how future weather anomalies can further amplify the relative increase associated to the shift in the climate norm. Assuming that the interannual variability of maximum temperatures follows the distribution observed in the past, we find a doubling of the impacts of climate change during the summer in Europe. Uncertainty around the distribution of future weather anomalies may lead to further unexpected peak load amplifications. Our results have important policy implications for power systems’ generation capacity, transmission and storage, as we show that the challenges to accommodate the peak load in days with extreme temperatures may substantially increase already around mid-century

Geographic and socioeconomic variation in the onset of decline of coronary heart disease mortality in white women.

BACKGROUND. Regional, metropolitan, and socioeconomic factors related to the onset of decline of coronary heart disease (CHD) mortality among White women are reported. Such studies are important for planning population-level interventions. METHODS. Mortality data for 1962 to 1978 were used, to estimate the year of onset of decline. Ecological analyses of socioeconomic data from the US census were used to emphasize structural and organizational aspects of changes in disease, rather than as a substitute for an individual-level design. RESULTS. Onset of decline of CHD mortality among White women was estimated to have occurred by 1962 in 53% of 507 state economic areas (SEAs), ranging from 79% in the Northeast to 39% in the South. Metropolitan areas experienced earlier onset of decline than did nonmetropolitan areas. Average income, education, and occupational levels were highest in early onset areas and declined across onset categories. CONCLUSIONS. The results provide additional evidence for previously observed geographic and social patterns of CHD decline. Emphasis on structural economic factors determining the shape of the CHD epidemic curve does not detract from the medical importance of risk factors, but underscores the importance of community development to public health improvements. The results are consistent with the idea that the course of the CHD epidemic in the United States has been strongly influenced by socio-economic development

Air-conditioning adoption and electricity demand highlight climate change mitigation–adaptation tradeoffs

We elucidate mid-century climate change impacts on electricity demand accounting for endogenous adoption of residential air-conditioning (AC) in affluent, cooler countries in Europe, and in poorer, hotter states in India. By 2050, in a high-warming scenario (SSP585) AC prevalence grows twofold in Europe and fourfold in India, reaching around 40% in both regions. We document a mitigation adaptation tradeoff: AC expansion reduces daily heat exposures by 150 million and 3.8 billion person degree-days (PDDs), but increases annual electricity demand by 34 TWh and 168 TWh in Europe and India, respectively (corresponding to 2% and 15% of today's consumption). The increase in adoption and use of AC would result in an additional 130 MMTCO2, of which 120 MMTCO2 in India alone, if the additional electricity generated were produced with today's power mix. The tradeoff varies geographically and across income groups: a one PDD reduction in heat exposure in Europe versus India necessitates five times more electricity (0.53 kWh vs 0.1 kWh) and two times more emissions (0.16 kgCO(2) vs 0.09 kgCO(2)), on average. The decomposition of demand drivers offers important insights on how such tradeoff can be moderated through policies promoting technology-based and behavioral based adaptation strategies

Perturbed Input Ensemble Modeling With the Space Weather Modeling Framework

To assess the effect of uncertainties in solar wind driving on the predictions from the operational configuration of the Space Weather Modeling Framework, we have developed a nonparametric method for generating multiple possible realizations of the solar wind just upstream of the bow shock, based on observations near the first Lagrangian point. We have applied this method to the solar wind inputs at the upstream boundary of Space Weather Modeling Framework and have simulated the geomagnetic storm of 5 April 2010. We ran a 40‐member ensemble for this event and have used this ensemble to quantify the uncertainty in the predicted Sym‐H index and ground magnetic disturbances due to the uncertainty in the upstream boundary conditions. Both the ensemble mean and the unperturbed simulation tend to underpredict the magnitude of Sym‐H in the quiet interval before the storm and overpredict in the storm itself, consistent with previous work. The ensemble mean is a more accurate predictor of Sym‐H, improving the mean absolute error by nearly 2 nT for this interval and displaying a smaller bias. We also examine the uncertainty in predicted maxima in ground magnetic disturbances. The confidence intervals are typically narrow during periods where the predicted dBH/dt is low. The confidence intervals are often much wider where the median prediction is for enhanced dBH/dt. The ensemble also allows us to identify intervals of activity that cannot be explained by uncertainty in the solar wind driver, driving further model improvements. This work demonstrates the feasibility and importance of ensemble modeling for space weather applications.Plain Language SummaryForecasts of space weather usually rely on spacecraft measurements of the solar wind from about a million miles away from Earth. Like water flowing toward a rock in a stream, measurements at a single point upstream may not reflect exactly what will hit the Earth. Forecasts that are driven by these measurements have uncertainty due to the uncertainty in the measurements driving the forecast models. We have developed a technique to estimate the uncertainty on space weather predictions using 7 years of solar wind measurements from two satellites. We have performed computer simulations of the same geomagnetic storm 41 times. In each simulation, the inputs were modified slightly each time to reflect the uncertainty in the measurements. By considering the set of simulations as a whole, we have shown that space weather forecasts can be improved by accounting for the uncertainty in the input data. We have also shown that accounting for uncertainty in the data driving, the model can highlight where incorrect forecasts are due to the uncertainty, as well as where they are due to inadequacies in the model itself. This work shows the importance of ensemble methods and accounting for uncertainties in space weather simulation and forecasting.Key PointsA new nonparametric method for drawing different realizations of solar wind data to drive magnetospheric models is derivedThe new method is used to obtain uncertainties on predicted geophysical indices from the operational Space Weather Modeling FrameworkModel skill can be improved by considering the uncertainty on model inputPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146472/1/swe20747_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146472/2/swe20747.pd

Numerical evidence for the spin-Peierls state in the frustrated quantum antiferromagnet

We study the spin-$1\over2$ Heisenberg antiferromagnet with an antiferromagnetic $J_3$ (third nearest neighbor) interaction on a square lattice. We numerically diagonalize this ``$J_1$-$J_3$'' model on clusters up to 32-sites and search for novel ground state properties as the frustration parameter $J_3/J_1$ changes. For ``larger'' $J_3/J_1$ we find enhancement of incommensurate spin order, in agreement with spin-wave, large-$N$ expansions, and other predictions. But for intermediate $J_3/J_1$, the low lying excitation energy spectrum suggests that this incommensurate order is short-range. In the same region, the first excited state has the symmetries of the columnar dimer (spin-Peierls) state. The columnar dimer order parameter suggests the presence of long-range columnar dimer order. Hence, this spin-Peierls state is the best candidate for the ground state of the $J_1$-$J_3$ model in an intermediate $J_3/J_1$ region.Comment: RevTeX file with five postscript figures uuencode

One-Loop Supergravity Corrections to the Black Hole Entropy and Residual Supersymmetry

We study the one-loop corrections to the effective on-shell action of N=2 supergravity in the background of the Reissner-Nordstrom black hole. In the extreme case the contributions from graviton, gravitino and photon to the one-loop corrections to the entropy are shown to cancel. This gives the first explicit example of the supersymmetric non-renormalization theorem for the on-shell action (entropy) for BPS configurations which admit Killing spinors. We display the residual supersymmetry of the perturbations of a general supersymmetric theory in a bosonic BPS background.Comment: 13 Pages, LaTe

Jets in deep-inelastic scattering at HERA

Jet cross sections in deep-inelastic scattering over a wide region of phase space have been measured at HERA. These cross section measurements provide a thorough test of the implementation of Quantum Chromodynamics in next-to-leading order (NLO) calculations. They also provide the opportunity to test the consistency of the gluon distribution in the proton as extracted from (mainly) inclusive DIS measurements. Comparison of the cross sections with NLO enables accurate extractions of the strong coupling constant, $\alpha_s$, to be made, several of which are reported here.Comment: Talk presented at "New Trends in HERA Physics", Ringberg Workshop, June 2001. 13pages, 12figure