An investigation of location effect on trip production using artificial neural networks

As traffic congestion exuberates and new roadway construction is severely constrained because of limited availability of land, high cost of land acquisition, and communities' opposition to the building of major roads, new solutions have to be sought to either make roadway use more efficient or reduce travel demand. There is a general agreement that travel demand is affected by land use patterns. However, traditional aggregate four-step models, which are the prevailing modeling approach presently, assume that traffic condition will not affect people's decision on whether to make a trip or not when trip generation is estimated. Existing survey data indicate, however, that differences exist in trip rates for different geographic areas. The reasons for such differences have not been carefully studied, and the success of quantifying the influence of land use on travel demand beyond employment, households, and their characteristics has been limited to be useful to the traditional four-step models. There may be a number of reasons, such as that the representation of influence of land use on travel demand is aggregated and is not explicit and that land use variables such as density and mix and accessibility as measured by travel time and congestion have not been adequately considered. This research employs the artificial neural network technique to investigate the potential effects of land use and accessibility on trip productions. Sixty two variables that may potentially influence trip production are studied. These variables include demographic, socioeconomic, land use and accessibility variables. Different architectures of ANN models are tested. Sensitivity analysis of the models shows that land use does have an effect on trip production, so does traffic condition. The ANN models are compared with linear regression models and cross-classification models using the same data. The results show that ANN models are better than the linear regression models and cross-classification models in terms of RMSE. Future work may focus on finding a representation of traffic condition with existing network data and population data which might be available when the variables are needed to in prediction.

Dioon Lindl. (Zamiaceae): Perspectives from phylogeny and a population genetic study of Dioon edule

Dioon Lindl. (Zamiaceae) is a small genus restricted to Mexico (12 species) and Honduras (one species). Previous systematic studies have been unable to fully resolve species relationships within the genus. Phylogenetic analyses were conducted with data from several sources, including Restriction Fragment Length Polymorphisms from the chloroplast genome, morphology, two introns of the low copy nuclear gene S-adenosyl-L-homocysteine hydrolase (SAHH) and the 5.8S/ITS2 regions of the nuclear ribosomal DNA. The goals of the study were to construct a total evidence species level phylogeny and to explore current biogeographical hypotheses. None of the analyses performed produced a fully resolved topology. Dioon is comprised of two main lineages (the Edule and Spinulosum Clades), which represents an ancient divergence within the genus. The two introns of the nuclear gene SAHH offer additional evidence for the split into two lineages. Intron 2 contains a 18 bp deletion in the Spinulosum Clade, providing a synapomorphy for that group. The 5.8S/ITS2 regions were highly polymorphic and subsequently omitted from the combined analyses. In order to visualize congruence between morphology and molecular data, morphological characters were mapped onto the combined molecular tree. Current biogeographical hypotheses of a general northward pattern of migration and speciation are supported here. However, sister relationships within the Edule Clade are not fully resolved. Seven DNA microsatellite markers were developed to investigate patterns of genetic variation of seven populations of D. edule, a species restricted to Eastern Mexico. We found that most of the genetic variation lies within populations (Ho = 0.2166–0.3657) and that levels of population differentiation are low (Fst = 0.088); this finding is congruent with the breeding system of this species, dioicy. Four of the populations deviate from Hardy Weinberg Equilibrium and have a high number of identical genotypes, we suggest that this unexpected pattern is due to the life-history strategy of the species coupled with the few number of polymorphic loci detected in these populations. Our results are not congruent with earlier evidence from morphology and allozyme markers that suggest that the two northernmost populations represent a distinct entity that is recognized by some taxonomists as D. angustifolium.

Mitochondrial DNA, segments I and II, its applications in population genetics and forensic sciences

The investigations of human mitochondrial DNA (mtDNA) have considerably contributed to human evolution and migration. The Middle East is considered to be an essential geographic area for human migrations out of Africa since it is located at the crossroads of Africa, and the rest of the world. United Arab Emirates (UAE) population inhabits the eastern part of Arabian Peninsula and was investigated in this study. Published data of 18 populations were included in the statistical analysis. The diversity indices showed (1) high genetic distance among African populations and (2) high genetic distance between African populations and non-African populations. Asian populations clustered together in the NJ tree between the African and European populations. MtDNA haplotypes database of the UAE population was generated. By incorporating UAE mtDNA dataset into the existing worldwide mtDNA database, UAE Forensic Laboratories will be able to analyze future mtDNA evidence in a more significant and consistent manner. ^

Population structure of spotted sunfish (Lepomis punctatus) in the Florida Everglades as revealed by DNA microsatellite analysis

Genetic diversity can be used to describe patterns of gene flow within and between local and regional populations. The Florida Everglades experiences seasonal fluctuations in water level that can influence local population extinction and recolonization dynamics. In addition, this expansive wetland has been divided into water management regions by canals and levees. These combined factors can affect genetic diversity and population structure of aquatic organisms in the Everglades. We analyzed allelic variation at six DNA microsatellite loci to examine the population structure of spotted sunfish (Lepomis punctatus) from the Everglades. We tested the hypothesis that recurrent local extinction and recent regional divisions have had an effect on patterns of genetic diversity. No marked differences were observed in comparisons of the heterozygosity values of sites within and among water management units. No evidence of isolation by distance was detected in a gene flow and distance correlation between subpopulations. Confidence intervals for the estimated F-statistic values crossed zero, indicating that there was no significant genetic difference between subpopulations within a region or between regions. Notably, the genetic variation among subpopulations in a water conservation area was greater than variation among regions (Fsp>FPT). These data indicate that the spatial scale of recolonization following local extinction appears to be most important within water management units.

Temporal Population Genetic Structure of Eastern Mosquitofish in a Dynamic Aquatic Landscape

We analyzed the effect of periodic drying in the Florida Everglades on spatiotemporal population genetic structure of eastern mosquitofish (Gambusia holbrooki). Severe periodic drying events force individuals from disparate sources to mix in dry season relatively deep-water refuges. In 1996 (a wet year) and 1999 (a dry year), we sampled mosquitofish at 20 dry-season refuges distributed in 3 water management regions and characterized genetic variation for 10 allozyme and 3 microsatellite loci. In 1996, most of the ecosystem did not dry, whereas in 1999, many of our sampling locations were isolated by expanses of dried marsh surface. In 1996, most spatial genetic variation was attributed to heterogeneity within regions. In 1999, spatial genetic variation within regions was not significant. In both years, a small but significant amount of variation (less than 1% of the total variation) was partitioned among regions. Variance was consistently greater than zero among long-hydroperiod sites within a region, but not among short-hydroperiod sites within a region, where hydroperiod was measured as time since last marsh surface dry-down forcing fishes into local refuges. In 1996, all sites were in Hardy–Weinberg equilibrium. In 1999, we observed fewer heterozygotes than expected for most loci and sites suggesting a Wahlund effect arising from fish leaving areas that dried and mixing in deep-water refuges.

Phylogenetic analysis of within -host serially-sampled viral data

The primary goal of this dissertation is the study of patterns of viral evolution inferred from serially-sampled sequence data, i.e., sequence data obtained from strains isolated at consecutive time points from a single patient or host. RNA viral populations have an extremely high genetic variability, largely due to their astronomical population sizes within host systems, high replication rate, and short generation time. It is this aspect of their evolution that demands special attention and a different approach when studying the evolutionary relationships of serially-sampled sequence data. New methods that analyze serially-sampled data were developed shortly after a groundbreaking HIV-1 study of several patients from which viruses were isolated at recurring intervals over a period of 10 or more years. These methods assume a tree-like evolutionary model, while many RNA viruses have the capacity to exchange genetic material with one another using a process called recombination. ^ A genealogy involving recombination is best described by a network structure. A more general approach was implemented in a new computational tool, Sliding MinPD, one that is mindful of the sampling times of the input sequences and that reconstructs the viral evolutionary relationships in the form of a network structure with implicit representations of recombination events. The underlying network organization reveals unique patterns of viral evolution and could help explain the emergence of disease-associated mutants and drug-resistant strains, with implications for patient prognosis and treatment strategies. In order to comprehensively test the developed methods and to carry out comparison studies with other methods, synthetic data sets are critical. Therefore, appropriate sequence generators were also developed to simulate the evolution of serially-sampled recombinant viruses, new and more through evaluation criteria for recombination detection methods were established, and three major comparison studies were performed. The newly developed tools were also applied to "real" HIV-1 sequence data and it was shown that the results represented within an evolutionary network structure can be interpreted in biologically meaningful ways. ^

On the Existence and Uniqueness of the Maximum Likelihood Estimators of Normal and Lognormal Population Parameters with Grouped Data

Lognormal distribution has abundant applications in various fields. In literature, most inferences on the two parameters of the lognormal distribution are based on Type-I censored sample data. However, exact measurements are not always attainable especially when the observation is below or above the detection limits, and only the numbers of measurements falling into predetermined intervals can be recorded instead. This is the so-called grouped data. In this paper, we will show the existence and uniqueness of the maximum likelihood estimators of the two parameters of the underlying lognormal distribution with Type-I censored data and grouped data. The proof was first established under the case of normal distribution and extended to the lognormal distribution through invariance property. The results are applied to estimate the median and mean of the lognormal population.