Marketing Percolation

A percolation model is presented, with computer simulations for illustrations, to show how the sales of a new product may penetrate the consumer market. We review the traditional approach in the marketing literature, which is based on differential or difference equations similar to the logistic equation (Bass 1969). This mean field approach is contrasted with the discrete percolation on a lattice, with simulations of "social percolation" (Solomon et al 2000) in two to five dimensions giving power laws instead of exponential growth, and strong fluctuations right at the percolation threshold.Comment: to appear in Physica

Ldcommunity.Com: Helping Educate Students and Postsecondary Instructors About Learning Disabilities

Despite the increase in the number of learning disabled (LD) students attending postsecondary institutions, few of these students decide to disclose their learning disability to postsecondary faculty and staff. Consequently, these students are less likely to receive the necessary support or learning accommodations available to them. This thesis explains how the social constructs of the K-12 educational and familial environments affect the ability of LD students to disclose their learning disability to postsecondary instructors. This thesis proposes that the comfort level between the student and the instructor plays an important role in disclosure. Based on this proposal, this thesis explains the manner in which the Web site www.ldcommunity.com can be employed as an academic reference tool for postsecondary instructors, faculty members, and students as a means of allowing them to communicate about the subject of learning disabilities with a high level of comfort

On the Probabilities of Environmental Extremes

Environmental researchers, as well as epidemiologists, often encounter the problem of determining the probability of exceeding a high threshold of a variable of interest based on observations that are much smaller than the threshold. Moreover, the data available for that task may only be of moderate size. This generic problem is addressed by repeatedly fusing the real data numerous times with synthetic computer-generated samples. The threshold probability of interest is approximated by certain subsequences created by an iterative algorithm that gives precise estimates. The method is illustrated using environmental data including monitoring data of nitrogen dioxide levels in the air

Characterizing Global Ozonesonde Profile Variability from Surface to the UT/LS with a Clustering Technique and MERRA-2 Reanalysis

Our previous studies employing the self-organizing map (SOM) clustering technique to ozonesonde data have found significant links among meteorological and chemical regimes, and the shape of the ozone (O3) profile from the troposphere to the lower stratosphere. These studies, which focused on specific northern hemisphere mid-latitude geographical regions, demonstrated the advantages of SOM clustering by quantifying O3 profile variability and the O3/meteorological correspondence. We expand SOM to a global set of ozonesonde profiles spanning 1980-present from 30 sites to summarize the connections among O3 profiles, meteorology, and chemistry, using the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) reanalysis and other ancillary data. Four clusters of O3 mixing ratio profiles from the surface to the upper troposphere/lower stratosphere (UT/LS) are generated for each site, which show dominant profile shapes and typical seasonality (or lack thereof) that generally correspond to latitude (i.e. Tropical, Subtropical, Mid-Latitude, Polar). Examination of MERRA-2 output reveals a clear relationship among SOM clusters and covarying meteorological fields (geopotential height, potential vorticity, and tropopause height) for Polar and Mid-latitude sites. However, these relationships break down within +/-30 deg latitude. Carbon monoxide satellite data, along with velocity potential, a proxy for convection, calculated from MERRA-2 wind fields assist characterization of the Tropical and Subtropical sites, where biomass burning and convective transport linked to the Madden- Julian Oscillation (MJO) dominate O3 variability. In addition to geophysical characterization of O3 profile variability, these results can be used to evaluate chemical transport model output and satellite measurements of O3

Evaluation of MERRA-2-Based Ozone Profile Simulations with the Global Ozonesonde Network

Chemical transport model (CTM) hindcasts of ozone (O3) are useful for filling in observational gaps and providing context for observed O3 variability and trends. We use global networks of ozonesonde stations to evaluate the O3 profiles in two simulations running versions of the NASA Global Modeling Initiative (GMI) chemical mechanism. Both simulations are tied to the NASA Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) meteorological reanalysis: 1) The GMI CTM, and 2) The MERRA-2 GMI Replay (M2 GMI). Both simulations start in 1980, and are compared against >50,000 ozonesonde profiles from 37 global stations from the tropics to the poles. The comparisons allow us to evaluate how the Replay technique affects modeled O3 distribution, how an updated chemical mechanism in the GMI CTM affects simulated tropospheric O3 amounts, and how observed O3 distributions compare to the full set of model output. In general, M2 GMI O3 is ~10% higher than in the GMI CTM, and shows global near-surface and tropical upper troposphere/lower stratosphere (UT/LS) high biases. The updated chemical mechanism in the GMI CTM reduces these high biases. Both simulations show similar negative biases in tropical free-tropospheric O3, especially during typical biomass burning seasons. The simulations are highly-correlated with ozonesonde measurements, particularly in the UT/LS (r > 0.8), showing the ability of MERRA-2 to capture tropopause height variations. Both simulations show improved correlations with ozonesonde data and smaller O3 biases in recent years. We expect to use the sonde/model comparisons to diagnose causes of disagreement and to gauge the feasibility of calculating multidecadal O3 trends from the model output

Transcriptome-pathology correlation identifies interplay between TDP-43 and the expression of its kinase CK1E in sporadic ALS.

Sporadic amyotrophic lateral sclerosis (sALS) is the most common form of ALS, however, the molecular mechanisms underlying cellular damage and motor neuron degeneration remain elusive. To identify molecular signatures of sALS we performed genome-wide expression profiling in laser capture microdissection-enriched surviving motor neurons (MNs) from lumbar spinal cords of sALS patients with rostral onset and caudal progression. After correcting for immunological background, we discover a highly specific gene expression signature for sALS that is associated with phosphorylated TDP-43 (pTDP-43) pathology. Transcriptome-pathology correlation identified casein kinase 1ε (CSNK1E) mRNA as tightly correlated to levels of pTDP-43 in sALS patients. Enhanced crosslinking and immunoprecipitation in human sALS patient- and healthy control-derived frontal cortex, revealed that TDP-43 binds directly to and regulates the expression of CSNK1E mRNA. Additionally, we were able to show that pTDP-43 itself binds RNA. CK1E, the protein product of CSNK1E, in turn interacts with TDP-43 and promotes cytoplasmic accumulation of pTDP-43 in human stem-cell-derived MNs. Pathological TDP-43 phosphorylation is therefore, reciprocally regulated by CK1E activity and TDP-43 RNA binding. Our framework of transcriptome-pathology correlations identifies candidate genes with relevance to novel mechanisms of neurodegeneration

Ozone Profiles in the Baltimore-Washington Region (2006-2011): Satellite Comparisons and DISCOVER-AQ Observations

Much progress has been made in creating satellite products for tracking the pollutants ozone and NO2 in the troposphere. Yet, in mid-latitude regions where meteorological interactions with pollutants are complex, accuracy can be difficult to achieve, largely due to persistent layering of some constituents. We characterize the layering of ozone soundings and related species measured from aircraft over two ground sites in suburban Washington, DC (Beltsville, MD, 39.05N; 76.9W) and Baltimore (Edgewood, MD, 39.4N; 76.3W) during the July 2011 DISCOVER-AQ (Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality) experiment. First, we compare column-ozone amounts from the Beltsville and Edgewood sondes with data from overpassing satellites. Second, processes influencing ozone profile structure are analyzed using Laminar Identification and tracers: sonde water vapor, aircraft CO and NOy. Third, Beltsville ozone profiles and meteorological influences in July 2011 are compared to those from the summers of 2006-2010. Sonde-satellite offsets in total ozone during July 2011 at Edgewood and Beltsville, compared to the Ozone Monitoring Instrument (OMI), were 3 percent mean absolute error, not statistically significant. The disagreement between an OMIMicrowave Limb Sounder-based tropospheric ozone column and the sonde averaged 10 percent at both sites, with the sonde usually greater than the satellite. Laminar Identification (LID), that distinguishes ozone segments influenced by convective and advective transport, reveals that on days when both stations launched ozonesondes, vertical mixing was stronger at Edgewood. Approximately half the lower free troposphere sonde profiles have very dry laminae, with coincident aircraft spirals displaying low CO (80-110 ppbv), suggesting stratospheric influence. Ozone budgets at Beltsville in July 2011, determined with LID, as well as standard meteorological indicators, resemble those of 4 of the previous 5 summers. The penetration of stratospheric air throughout the troposphere appears to be typical for summer conditions in the Baltimore-Washington region