The Iron K Line Profile of IRAS 18325-5926

IRAS 18325-5926 is an X-ray bright, Compton-thin, type-2 Seyfert galaxy and it was the first Seyfert 2 in which the presence of a broad Fe K-alpha emission line was claimed. However, although the structure of the Fe line appears broad, there is tentative evidence that it may comprise multiple lines. Nevertheless, previous analyses have only consisted of fitting standalone broad components to the Fe K band. Here, we have analyzed all available X-ray CCD data from Suzaku, XMM-Newton and ASCA to fully investigate the nature of the emission complex by testing broad-band physical models and alternative hypotheses. We find that both a model consisting of broad, blurred reflection from an ionized accretion disc and a model consisting of cold, neutral reflection plus narrow emission lines from highly-ionized photoionized gas (log \xi = 3.5) offer statistically comparable fits to the data although the true reality of the Fe line cannot currently be determined with existing data. However, it is hoped that better quality data and improved photon statistics in the Fe K band will allow a more robust distinction between models to be made.Comment: Accepted by MNRAS; 13 pages; 10 figures; 2 table

Space, Settlement, and Environment: Detecting Undocumented Maya Archaeological Sites with Remotely Sensed Data

This study utilizes an integrated remote sensing approach to augment settlement pattern research in the Yalahau Region of northern Quintana Roo, Mexico. The region has a long history of human occupation and an environment ranging from coasts, freshwater wetlands, forests, to fields and towns all above a porous karst geology. By utilizing various sensors (LiDAR, GeoEye and Landsat) and collection methods (satellite, aerial) as well as post-processing (band combinations, component analyses and indices) and cross-referencing the data, it is possible to generate a signature, which strongly correlates with evidence of prehistoric occupation. Field verification of a selection of identified signatures was conducted to assess the presence of human cultural material. The results of this investigation are presented together with other regional settlement pattern data in order to assess the status of a number of methodological and archaeological questions and supplement other regional data already available

The application of macro co-kriging and compound lognormal theory to long range grade forecasts for the carbon leader reef

A project report submitted to the Faculty of Engineering, University of the Witwatersrand, in partial fulfilment of the requirements for the degree of Master of Science in Engineering. Johannesburg, 1997.Due to the extreme costs of establishing new shaft systems in Witwatersrand gold mines it is essential that the resource estimation is optimised, The result of poor Of sub-optimal estimation could be catastrophic even.to the largest of mining companies. This project examines the application of Compound Lognormal Distribution theory and shows the advantages of this distribution model over more traditional models, for the Carbon Leader Reef. The incorporation of information from mined out areas of a deposit in resource estimation is demonstrated. The critical role played by accurate geological modelling is highlighted. The process of Macro Co-Kriging in conjunction with Compound Lognormal Theory is discussed in detail and is shown to be a more accurate estimation technique than traditional techniques using Lognormal theory. Finally the use of the Macro Co-kriged limits are shown to be useful in the classification of Mineral Resources.AC201

Imprints of a high velocity wind on the soft x-ray spectrum of PG 1211+143

An extended XMM-Newton observation of the luminous narrow line Seyfert galaxy PG 1211+143 in 2014 has revealed a more complex high velocity wind, with components distinguished in velocity, ionization level, and column density. Here we report soft x-ray emission and absorption features from the ionized outflow, finding counterparts of both high velocity components, v ~ 0.129c and v ~ 0.066c, recently identified in the highly ionized Fe K absorption spectrum. The lower ionization of the co-moving soft x-ray absorbers imply a distribution of higher density clouds embedded in the main outflow, while much higher column densities for the same flow component in the hard x-ray spectra suggest differing sight lines to the continuum x-ray source.Comment: 8 pages, 5 figures, 4 tables; Accepted for publication in MNRA

Can feedback from the jumbo-CD market improve off-site surveillance of community banks?

We examine the value of feedback from the jumbo-certificate-of-deposit (CD) market in the off-site surveillance of community banks. Using accounting data, we construct proxies for default premiums on jumbo CDs. Then, we produce rank orderings of community banks -- defined as institutions holding less than $500 million in assets (constant 1999 dollars) -- based on these proxies. Next, we use an econometric surveillance model to generate rank orderings based on the probability of encountering financial distress. Finally, we compare these rank orderings as tools for flagging emerging problems. Our comparisons include eight out-of-sample test windows during the 1990s. We find that feedback from the jumbo-CD market would have added little value in community-bank surveillance during our sample period. Specifically, rank orderings based on output from the econometric model significantly outperformed rank orderings based on jumbo-CD default premiums. More important, the jumbo-CD orderings improved little over a random ordering. Other attempts to extract risk signals from the jumbo-CD data yielded similar results. Taken together, our findings validate current surveillance practices. We conclude by arguing that the robust economic environment of the 1990s probably plays a large role in our results.Community banks ; Bank supervision

Can feedback from the jumbo-CD market improve bank surveillance?

We examine the value of jumbo certificate-of-deposit (CD) signals in bank surveillance. To do so, we first construct proxies for default premiums and deposit runoffs and then rank banks based on these risk proxies. Next, we rank banks based on the output of a logit model typical of the econometric models used in off-site surveillance. Finally, we compare jumbo-CD rankings and surveillance-model rankings as tools for predicting financial distress. Our comparisons include eight out-of-sample test windows during the 1990s. We find that rankings obtained from jumbo-CD data would not have improved on rankings obtained from conventional surveillance tools. More importantly, we find that jumbo-CD rankings would not have improved materially over random rankings of the sample banks. These findings validate current surveillance practices and, when viewed with other recent empirical tests, raise questions about the value of market signals in bank surveillance.Finance ; Banks and banking ; Bank supervision

The role of a CAMEL downgrade model in bank surveillance

This article examines the potential contribution to bank supervision of a model designed to predict which banks will have their supervisory ratings downgraded in future periods. Bank supervisors rely on various tools of off-site surveillance to track the condition of banks under their jurisdiction between on-site examinations, including econometric models. One of the models that the Federal Reserve System uses for surveillance was estimated to predict bank failures. Because bank failures have been so rare during the last decade, the coefficients on this model have been "frozen" since 1991. Each quarter the surveillance staff at the Board of Governors provide the supervision staff in the Reserve Banks the probabilities of failure by the banks subject to Fed supervision, based on the coefficients of this bank failure model and the latest call report data for each bank. The number of banks downgraded to problem status in recent years has been substantially larger than the number of bank failures. During a period of few bank failures, the relevance of this bank failure model for surveillance depends to some extent on the accuracy of the model in predicting which banks will have their supervisory ratings downgraded to problem status in future periods. This paper compares the ability of two models to predict downgrades of supervisory ratings to problem status: the Board staff model, which was estimated to predict bank failures, and a model estimated to predict downgrades of supervisory ratings. We find that both models do about as well in predicting downgrades of supervisory ratings for the early 1990s. Over time, however, the ability of the downgrade model to predict downgrades improves relative to that of the model estimated to predict failures. This pattern reflects the value of using a model for surveillance that can be re-estimated frequently. We conclude that the downgrade model may prove to be a useful supplement to the Board's model for estimating failures during periods when most banks are healthy, but that the downgrade model should not be considered a replacement for the current surveillance framework.Bank supervision

Could a CAMELS downgrade model improve off-site surveillance?

The Federal Reserve’s off-site surveillance system includes two econometric models that are collectively known as the System for Estimating Examination Ratings (SEER). One model, the SEER risk rank model, uses the latest financial statements to estimate the probability that each Fed-supervised bank will fail in the next two years. The other component, the SEER rating model, uses the latest financial statements to produce a “shadow” CAMELS rating for each supervised bank. Banks identified as risky by either model receive closer supervisory scrutiny than other state-member banks.> Because many of the banks flagged by the SEER models have already tumbled into poor condition and, hence, would already be receiving considerable supervisory attention, we developed an alternative model to identify safe-and-sound banks that potentially are headed for financial distress. Such a model could help supervisors allocate scarce on- and off-site resources by pointing out banks not currently under scrutiny that need watching.> It is possible, however, that our alternative model improves little over the current SEER framework. All three models—the SEER risk rank model, the SEER rating model, and our downgrade model—produce ordinal rankings based on overall risk. If the financial factors that explain CAMELS downgrades differ little from the financial factors that explain failures or CAMELS ratings, then all three models will produce similar risk ratings and, hence, similar watch lists of one- and two-rated banks.> We find only slight differences in the ability of the three models to spot emerging financial distress among safe-and-sound banks. In out-of-sample tests for 1992 through 1998, the watch lists produced by the downgrade model outperform the watch lists produced by the SEER models by only a small margin. We conclude that, in relatively tranquil banking environments like the 1990s, a downgrade model adds little value in off-site surveillance. We caution, however, that a downgrade model might prove useful in more turbulent banking times.Bank supervision