The New Economy: State Governments and Education

The New Economy: State Governments and EducationBureau of Business Researc

Mathematical Models of Light Transport in Biological Tissues for Quantitative Clinical Diagnostic Applications.

This dissertation focuses on the development and implementation of several novel mathematical models of light transport in biological tissue for use as quantitative diagnostic tools to assess tissue viability and detect diseased tissue. This work includes semi-empirical models of reflectance and fluorescence for pancreatic cancer diagnostics, computational models of inelastic (Raman) scattering in layered tissues for non-invasive bone tissue assessment and breast tumor margin detection during surgery, and computational models of light propagation for tissues with irregular geometries. A novel photon-tissue interaction (PTI) model of reflectance and fluorescence was developed and employed to extract biophysically-relevant tissue parameters (mean size of cell nuclei, percentage contribution of collagen to fluorescence) from measured optical spectra of freshly-excised human pancreatic tissues. The mean cellular nuclear size was statistically significant for distinguishing adenocarcinoma sites from non-cancerous (pancreatitis and normal) sites. The percentage contribution of collagen was statistically significant for distinguishing between all three tissue types included in the study (adenocarcinoma, pancreatitis, normal). When these parameters were included in a statistically-rigorous tissue classification algorithm that accounted for intra-patient correlations in the data, adenocarcinoma was distinguished from the non-cancerous tissues with an area of 0.906 under the receiver operating characteristic (ROC) curve and a sensitivity, specificity, positive predictive value, and negative predictive value of 87.5%, 89.0%, 77.8%, and 94.2%, respectively. A novel Monte Carlo (MC) model of inelastic (Raman) scattering in layered tissues was developed and employed to characterize the effects of tissue and fiber-probe properties on the detected Raman signal. This MC model was employed to assist with two biomedical applications: bone tissue diagnostics and breast tumor margin assessment. For the tumor margin assessment application, it was predicted that the smallest detectable tumor thickness using spatially-offset Raman spectroscopy would be 100 microns under a 0.5 mm margin or 1 mm under a 2 mm margin. The models described in this dissertation provide accurate, versatile, and quantitative analysis of the effects of fiber-optic probe design and biophysical tissue properties on the detected optical signal and can be employed in a wide range of tissue diagnostic applications.Ph.D.Applied PhysicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91513/1/roberthw_1.pd

Development of an Arctic Low Frequency Ambient Noise Model

LONG TERM GOALS: To develop a low frequency Arctic ambient noise model to predict extreme (loud /quiet) noise events due the presence or absence of storms.Award No. N0001497WR3009

Quantifying uncertainty in pest risk maps and assessments : adopting a risk-averse decision maker’s perspective

Pest risk maps are important decision support tools when devising strategies to minimize introductions of invasive organisms and mitigate their impacts. When possible management responses to an invader include costly or socially sensitive activities, decision-makers tend to follow a more certain (i.e., risk-averse) course of action. We presented a new mapping technique that assesses pest invasion risk from the perspective of a risk-averse decision maker. We demonstrated the method by evaluating the likelihood that an invasive forest pest will be transported to one of the U.S. states or Canadian provinces in infested firewood by visitors to U.S. federal campgrounds. We tested the impact of the risk aversion assumption using distributions of plausible pest arrival scenarios generated with a geographically explicit model developed from data documenting camper travel across the study area. Next, we prioritized regions of high and low pest arrival risk via application of two stochastic ordering techniques that employed, respectively, first- and second-degree stochastic dominance rules, the latter of which incorporated the notion of risk aversion. We then identified regions in the study area where the pest risk value changed considerably after incorporating risk aversion. While both methods identified similar areas of highest and lowest risk, they differed in how they demarcated moderate-risk areas. In general, the second-order stochastic dominance method assigned lower risk rankings to moderate-risk areas. Overall, this new method offers a better strategy to deal with the uncertainty typically associated with risk assessments and provides a tractable way to incorporate decisionmaking preferences into final risk estimates, and thus helps to better align these estimates with particular decision-making scenarios about a pest organism of concern. Incorporation of risk aversion also helps prioritize the set of locations to target for inspections and outreach activities, which can be costly. Our results are especially important and useful given the huge number of camping trips that occur each year in the United States and Canada

U.S. Supreme Court Reviews Employers\u27 Responsibilities Regarding Tip Reporting and FICA Taxes

The recent Supreme Court Case, U.S. v. Fior D\u27ltaIia, Inc. (2002), has given the Internal Revenue Service broad new authority to conduct audits of restaurant owners in order to estimate and assess the amount of FICA taxes owed for employee tips and wages. The court approved the use by the IRS of the aggregate method to estimate the amount of tips received by employees in employer tax audits without requiring the prior audits of individual employees. The decision will force restaurant employers to become much more actively involved in obtaining accurate information from their employees as to the precise amount of their tip income in order to avoid the employer first audits. As such, the various alternatives for restaurant owners in deciding how to handle employee tips and FICA taxes are better understood

Quantifying uncertainty in pest risk maps and assessments : adopting a risk-averse decision maker’s perspective

Pest risk maps are important decision support tools when devising strategies to minimize introductions of invasive organisms and mitigate their impacts. When possible management responses to an invader include costly or socially sensitive activities, decision-makers tend to follow a more certain (i.e., risk-averse) course of action. We presented a new mapping technique that assesses pest invasion risk from the perspective of a risk-averse decision maker. We demonstrated the method by evaluating the likelihood that an invasive forest pest will be transported to one of the U.S. states or Canadian provinces in infested firewood by visitors to U.S. federal campgrounds. We tested the impact of the risk aversion assumption using distributions of plausible pest arrival scenarios generated with a geographically explicit model developed from data documenting camper travel across the study area. Next, we prioritized regions of high and low pest arrival risk via application of two stochastic ordering techniques that employed, respectively, first- and second-degree stochastic dominance rules, the latter of which incorporated the notion of risk aversion. We then identified regions in the study area where the pest risk value changed considerably after incorporating risk aversion. While both methods identified similar areas of highest and lowest risk, they differed in how they demarcated moderate-risk areas. In general, the second-order stochastic dominance method assigned lower risk rankings to moderate-risk areas. Overall, this new method offers a better strategy to deal with the uncertainty typically associated with risk assessments and provides a tractable way to incorporate decisionmaking preferences into final risk estimates, and thus helps to better align these estimates with particular decision-making scenarios about a pest organism of concern. Incorporation of risk aversion also helps prioritize the set of locations to target for inspections and outreach activities, which can be costly. Our results are especially important and useful given the huge number of camping trips that occur each year in the United States and Canada

Dissociation of Cerebral Blood Flow and Femoral Artery Blood Pressure Pulsatility After Cardiac Arrest and Resuscitation in a Rodent Model: Implications for Neurological Recovery.

Background Impaired neurological function affects 85% to 90% of cardiac arrest (CA) survivors. Pulsatile blood flow may play an important role in neurological recovery after CA. Cerebral blood flow (CBF) pulsatility immediately, during, and after CA and resuscitation has not been investigated. We characterized the effects of asphyxial CA on short-term (<2 hours after CA) CBF and femoral arterial blood pressure (ABP) pulsatility and studied their relationship to cerebrovascular resistance (CVR) and short-term neuroelectrical recovery. Methods and Results Male rats underwent asphyxial CA followed by cardiopulmonary resuscitation. A multimodal platform combining laser speckle imaging, ABP, and electroencephalography to monitor CBF, peripheral blood pressure, and brain electrophysiology, respectively, was used. CBF and ABP pulsatility and CVR were assessed during baseline, CA, and multiple time points after resuscitation. Neuroelectrical recovery, a surrogate for neurological outcome, was assessed using quantitative electroencephalography 90 minutes after resuscitation. We found that CBF pulsatility differs significantly from baseline at all experimental time points with sustained deficits during the 2 hours of postresuscitation monitoring, whereas ABP pulsatility was relatively unaffected. Alterations in CBF pulsatility were inversely correlated with changes in CVR, but ABP pulsatility had no association to CVR. Interestingly, despite small changes in ABP pulsatility, higher ABP pulsatility was associated with worse neuroelectrical recovery, whereas CBF pulsatility had no association. Conclusions Our results reveal, for the first time, that CBF pulsatility and CVR are significantly altered in the short-term postresuscitation period after CA. Nevertheless, higher ABP pulsatility appears to be inversely associated with neuroelectrical recovery, possibly caused by impaired cerebral autoregulation and/or more severe global cerebral ischemia

One-pot near-ambient temperature syntheses of aryl(difluoroenol) derivatives from trifluoroethanol

Difluoroalkenylzinc reagents prepared from 1-(2’-methoxy-ethoxymethoxy)-2,2,2-trifluoroethane and 1-(N,N-diethylcarbamoyloxy)-2,2,2-trifluoroethane at ice bath temperatures, underwent Negishi coupling with a range of aryl halides in a convenient one pot procedure. While significant differences between the enol acetal and carbamate reagents were revealed, the Negishi protocol compared very favourably with alternative coupling procedures in terms of overall yields from trifluoroethanol

Anticipating Cycle 24 Minimum and Its Consequences

On the basis of the 12-mo moving average of monthly mean sunspot number (R) through November 2006, cycle 23 has persisted for 126 mo, having had a minimum of 8.0 in May 1996, a peak of 120.8 in April 2000, and an ascent duration of 47 mo. In November 2006, the 12-mo moving average of monthly mean sunspot number was 12.7, a value just outside the upper observed envelope of sunspot minimum values for the most recent cycles 16-23 (range 3.4-12.3), but within the 90-percent prediction interval (7.8 +/- 6.7). The first spotless day during the decline of cycle 23 occurred in January 2004, and the first occurrence of 10 or more and 20 or more spotless days was February 2006 and April 2007, respectively, inferring that sunspot minimum for cycle 24 is imminent. Through May 2007, 121 spotless days have accumulated. In terms of the weighted mean latitude (weighed by spot area) (LAT) and the highest observed latitude spot (HLS) in November 2006, 12-mo moving averages of these parameters measured 7.9 and 14.6 deg, respectively, these values being the lowest values yet observed during the decline of cycle 23 and being below corresponding mean values found for cycles 16-23. As yet, no high-latitude new-cycle spots have been seen nor has there been an upturn in LAT and HLS, these conditions having always preceded new cycle minimum by several months for past cycles. Together, these findings suggest that cycle 24 s minimum amplitude still lies well beyond November 2006. This implies that cycle 23 s period either will lie in the period "gap" (127-134 mo), a first for a sunspot cycle, or it will be longer than 134 mo, thus making cycle 23 a long-period cycle (like cycle 20) and indicating that cycle 24 s minimum will occur after July 2007. Should cycle 23 prove to be a cycle of longer period, a consequence might be that the maximum amplitude for cycle 24 may be smaller than previously predicted