The dynamic electric polarizability of a particle bound by a double delta potential

In this paper we derive an expression for the dynamic electric polarizability of a particle bound by a double delta potential for frequencies below and above the absolute value of the particle's ground state energy. The derived expression will be used to study some of the fundamental features of the system and its representation of real systems. In addition we derive a general expression of the dynamic electric polarizability for a potential of multi-delta functions.Comment: 11 pages, 5 figure

Survey incompleteness and the evolution of the QSO luminosity function

We concentrate on a type of QSO survey which depends on selecting QSO candidates based on combinations of colors. Since QSO's have emission lines and power-law continua, they are expected to yield broadband colors unlike those of stellar photospheres. Previously, the fraction of QSO's expected to be hiding (unselected) within the locus of stellar (U-J, J-F) colors was estimated at about 15 percent. We have now verified that the KK88 survey is at least 11 percent incomplete, but have determined that it may be as much as 34 percent incomplete. The 'missing' QSO's are expected to be predominantly at z less than or = 2.2. We have studied the proper motion and variability properties of all stellar objects with J less than or = 22.5 or F less than or = 21.5 in the SA 57 field which has previously been surveyed with a multicolor QSO search by KK88

Living donor renal transplantation using alemtuzumab induction and tacrolimus monotherapy

Alemtuzumab was used as an induction agent in 205 renal transplant recipients undergoing 207 living donor renal transplants. All donor kidneys were recovered laparoscopically. Postoperatively, patients were treated with tacrolimus monotherapy, and immunosuppression was weaned when possible. Forty-seven recipients of living donor renal transplants prior to the induction era who received conventional triple drug immunosuppression without antibody induction served as historic controls. The mean follow-up was 493 days in the alemtuzumab group and 2101 days in the historic control group. Actuarial 1-year patient and graft survival were 98.6% and 98.1% in the alemtuzumab group, compared to 93.6% and 91.5% in the control group, respectively. The incidence of acute cellular rejection (ACR) at 1 year was 6.8% in the alemtuzumab group and 17.0% (p < 0.05) in the historic control group. Most (81.3%) episodes of ACR in the alemtuzumab group were Banff 1 (a or b) and were sensitive to steroid pulses for the treatment of rejection. There was no cytomegalovirus disease or infection. The incidence of delayed graft function was 0%, and the incidence of posttransplant insulin-dependent diabetes mellitus was 0.5%. This study represents the largest series to date of live donor renal transplant recipients undergoing alemtuzumab induction, and confirms the short-term safety and efficacy of this approach. © 2006 The Authors

Giving ecological meaning to satellite-derived fire severity metrics across North American forests

Satellite-derived spectral indices such as the relativized burn ratio (RBR) allow fire severity maps to be produced in a relatively straightforward manner across multiple fires and broad spatial extents. These indices often have strong relationships with field-based measurements of fire severity, thereby justifying their widespread use in management and science. However, satellite-derived spectral indices have been criticized because their non-standardized units render them difficult to interpret relative to on-the-ground fire effects. In this study, we built a Random Forest model describing a field-based measure of fire severity, the composite burn index (CBI), as a function of multiple spectral indices, a variable representing spatial variability in climate, and latitude. CBI data primarily representing forested vegetation from 263 fires (8075 plots) across the United States and Canada were used to build the model. Overall, the model performed well, with a cross-validated R2 of 0.72, though there was spatial variability in model performance. The model we produced allows for the direct mapping of CBI, which is more interpretable compared to spectral indices. Moreover, because the model and all spectral explanatory variables were produced in Google Earth Engine, predicting and mapping of CBI can realistically be undertaken on hundreds to thousands of fires. We provide all necessary code to execute the model and produce maps of CBI in Earth Engine. This study and its products will be extremely useful to managers and scientists in North America who wish to map fire effects over large landscapes or regions