Assessment of a prototype sunphotometer for network applications, phase 1

Data taken in Tucson, AZ, for comparing the CE sunphotometer's results against the Univ. of Arizona's no. 3 solar radiometer are in very good agreement. The spectral voltage intercepts obtained on 15 different days taken with the CE instrument during a seven week period are stable and follow the same daily trends as the voltage intercepts for similar wavelengths contained in the Univ. of Arizona's no. 3 radiometer. The spectral optical depths obtained from both instruments are also in very good agreement and follow the same trends. The only problem that exists in the CE instrument does not have a heater to stabilize the detector temperature which is important around 1000 nm. Zenith sky radiance scans are in good agreement, but both instruments are biased by direct solar rays entering the instrument's respective entrance apertures. All diffuse light data shown were, therefore, taken with the instruments shielded from the direct sun. The CE sunphotometer results pertaining to the water vapor wavelength's are also in good agreement with the Univ. of Arizona's no. 3 and should prove useful for water vapor retrieval

A Machine Learning Method of Determining Causal Inference applied to Shifts in Voting Preferences between 2012-2016

This research investigates the application of machine learning techniques to assist in the execution of a synthetic control model. This model was performed to analyze counties within the United States that showed a voter shift from a majority of Democratic voter share to Republican between the 2012 and 2016 election cycles. The following study applies two steps of machine learning analysis. The first, which is the treatment discovery process, leverages a Random Forest to evaluate feature importance. The second step was the execution of the synthetic control model with two predictor variable lists. The first was the parametric method: a hand curated predictor variable list based on domain knowledge. The second was the non-parametric method: all available predictor (descriptive) variables were used. The Random Forest treatment discovery process resulted in two uncommon variables applied as treatment effects: WIC women enrollment and a decrease of vegetable farm acreage. The opportunity to research these atypical treatment variables allows for the potential of surfacing counterfactual arguments for further research. The use of the parametric and non-parametric methods offers a system of comparison for the research in this paper. The result from the decrease in vegetable farm acreage treatment variable was negative for the non-parametric model. However, the parametric model did show strong statistical evidence towards a treatment effect from the decrease in farm acreage. It is likely that the decrease in vegetable farm acreage is a proxy for poverty or a population density metric. These data results suggest that this model was likely suffering from omitted variable bias for representation of one or both of these metrics in the predictor variable list. The WIC women enrollment treatment variable investigation resulted in the synthetic control model having difficulty in forming a synthetic control comparison. These results suggest there is a fundamental difference between those counties used to create the synthetic control and the other counties that saw a treatment effect. Additional research needs to be performed, and it could result in a different application of the data for use in a synthetic control model. The results of this study, while not surfacing causal inference, did open questions for further research. Given the opportunity these joined causal inference and machines learning practices could continue and potential offer assistance to traditional causal modeling methods. Allowing researchers to understand data and relationships between the data more intimately, theoretically allowing for new causal inferences to be discovered

Extinction-to-Backscatter Ratios of Lofted Aerosol Layers Observed During the First Three Months of CALIPSO Measurements

Case studies from the first three months of the Cloud and Aerosol Lidar and Infrared Pathfinder Spaceborne Observations (CALIPSO) measurements of lofted aerosol layers are analyzed using transmittance [Young, 1995] and two-wavelength algorithms [Vaughan et al., 2004] to determine the aerosol extinction-to-backscatter ratios at 532 and 1064 nm. The transmittance method requires clear air below the layer so that the transmittance through the layer can be determined. Suitable scenes are selected from the browse images and clear air below features is identified by low 532 nm backscatter signal and confirmed by low depolarization and color ratios. The transmittance and two-wavelength techniques are applied to a number of lofted layers and the extinction-to-backscatter ratios are compared with values obtained from the CALIPSO aerosol models [Omar et al., 2004]. The results obtained from these studies are used to adjust the aerosol models and develop observations based extinction-to-backscatter ratio look-up tables and phase functions. Values obtained by these techniques are compared to Sa determinations using other independent methods with a goal of developing probability distribution functions of aerosol type-specific extinction to backscatter ratios. In particular, the results are compared to values determined directly by the High Spectral Resolution Lidar (HSRL) during the CALIPSO CloudSat Validation Experiments (CCVEX) and Sa determined by the application of the two-wavelength lidar Constrained Ratio Aerosol Model-fit (CRAM) retrieval approach [Cattrall et al., 2005; Reagan et al., 2004] to the HSRL data. The results are also compared to values derived using the empirical relationship between the multiple-scattering fraction and the linear depolarization ratio by using Monte Carlo simulations of water clouds [Hu et al., 2006]

Pscroph, a parasitic plant EST database enriched for parasite associated transcripts

BACKGROUND: Parasitic plants in the Orobanchaceae develop invasive root haustoria upon contact with host roots or root factors. The development of haustoria can be visually monitored and is rapid, highly synchronous, and strongly dependent on host factor exposure; therefore it provides a tractable system for studying chemical communications between roots of different plants. DESCRIPTION: Triphysaria is a facultative parasitic plant that initiates haustorium development within minutes after contact with host plant roots, root exudates, or purified haustorium-inducing phenolics. In order to identify genes associated with host root identification and early haustorium development, we sequenced suppression subtractive libraries (SSH) enriched for transcripts regulated in Triphysaria roots within five hours of exposure to Arabidopsis roots or the purified haustorium-inducing factor 2,6 dimethoxybenzoquinone. The sequences of over nine thousand ESTs from three SSH libraries and their subsequent assemblies are available at the Pscroph database . The web site also provides BLAST functions and allows keyword searches of functional annotations. CONCLUSION: Libraries prepared from Triphysaria roots treated with host roots or haustorium inducing factors were enriched for transcripts predicted to function in stress responses, electron transport or protein metabolism. In addition to parasitic plant investigations, the Pscroph database provides a useful resource for investigations in rhizosphere interactions, chemical signaling between organisms, and plant development and evolution

Meox2 Haploinsufficiency Accelerates Axonal Degeneration in DBA/2J Glaucoma.

Purpose: Glaucoma is a complex disease with major risk factors including advancing age and increased intraocular pressure (IOP). Dissecting these earliest events will likely identify new avenues for therapeutics. Previously, we performed transcriptional profiling in DBA/2J (D2) mice, a widely used mouse model relevant to glaucoma. Here, we use these data to identify and test regulators of early gene expression changes in DBA/2J glaucoma. Methods: Upstream regulator analysis (URA) in Ingenuity Pathway Analysis was performed to identify potential master regulators of differentially expressed genes. The function of one putative regulator, mesenchyme homeobox 2 (Meox2), was tested using a combination of genetic, biochemical, and immunofluorescence approaches. Results: URA identified Meox2 as a potential regulator of early gene expression changes in the optic nerve head (ONH) of DBA/2J mice. Meox2 haploinsufficiency did not affect the characteristic diseases of the iris or IOP elevation seen in DBA/2J mice but did cause a significant increase in the numbers of eyes with axon damage compared to controls. While young mice appeared normal, aged Meox2 haploinsufficient DBA/2J mice showed a 44% reduction in MEOX2 protein levels. This correlated with modulation of age- and disease-specific vascular and myeloid alterations. Conclusions: Our data support a model whereby Meox2 controls IOP-dependent vascular remodeling and neuroinflammation to promote axon survival. Promoting these earliest responses prior to IOP elevation may be a viable neuroprotective strategy to delay or prevent human glaucoma

What Consensus? Ideology, Politics and Elections Still Matter

This article, which was prepared for an ABA Antitrust Section Panel, discusses the role of ideology and politics in antitrust enforcement and the impact of elections in the last twenty year on enforcement and policy at the federal antitrust agencies. The article explains the differences in antitrust ideologies and their impact on policy preferences. The article then uses a database of civil non-merger complaints by the DOJ and FTC over the last three Presidential administrations to analyze changes in the number, type and other characteristics of antitrust enforcement. It also discusses change in vertical merger enforcement and other antirust policies such as amicus briefs, reports and guidelines. The article concludes that elections do matter and that the impact of elections on the DOJ and FTC has differed significantly

Correlation between Quantitative PCR and Culture-Based Methods for Measuring Enterococcus spp. over Various Temporal Scales at Three California Marine Beaches

ABSTRACT Several studies have examined how fecal indicator bacteria (FIB) measurements compare between quantitative PCR (qPCR) and the culture methods it is intended to replace. Here, we extend those studies by examining the stability of that relationship within a beach, as affected by time of day and seasonal variations in source. Enterococcus spp. were quantified at three southern California beaches in the morning and afternoon using two qPCR assays, membrane filtration, and defined-substrate testing. While qPCR and culture-based measurements were consistently and significantly correlated, strength of the correlation varied both among and within beaches. Correlations were higher in the morning (0.45 < ρ < 0.74 [ P < 0.002]) than in the afternoon (0.18 < ρ < 0.45 [ P < 0.021]) and higher when the fecal contamination was concentrated (0.38 < ρ < 0.83 [ P < 0.001]) than when it was diffuse (0.19 < ρ < 0.34 [ P < 0.003]). The ratios of culture-based and qPCR results (CFU or most probable number [MPN] per calibrator cell equivalents [CCE]) also varied spatially and temporally. Ratios ranged between 0.04 and 0.85 CFU or MPN per CCE and were lowest at the beach affected by diffuse pollution. Patterns in the ratios over the course of the day were dissimilar across beaches, increasing with time at one beach and decreasing at another. The spatial and temporal variability we observed indicate that the empirical relationship between culture-based and qPCR results is not universal, even within a beach