Free-classification of American dialects in three conditions: natural, monotonized, and low-pass filtered speech

The dialects of American English have distinct features: these features include vowel shifts – the Northern Cities Chain Shift and the Southern Chain Shift (Labov, Ash, & Boberg 2006; Clopper, Pisoni, & deJong 2005) -- and prosodic variation, including intonation and rhythm (Clopper & Smiljanic 2011, 2015). In the current study, I ran three conditions to test which prosodic cues listeners were using when classifying talkers by regional dialect. American English has six distinct dialects: Northern, Southern, Midland, Mid-Atlantic, Western, and New-England (Labov, Ash, & Boberg 2006). Participants listened to 60 talkers, 10 from each of the six regional American English dialects, and were asked to sort the talkers into groups by dialect using free-classification. All of the talkers read the same sentence, which was manipulated in two of the three conditions. The first condition left the talkers’ voices natural and un-manipulated. The second condition monotonized all of the talkers’ voices. The third condition ran all of the talkers’ voices through a low-pass filter, which removed everything above 400 Hz. Results indicated that all participants, regardless of condition, made about 9 groups of talkers on average. Results also revealed effects of condition and talker dialect on accuracy. For the condition accuracy, the monotonized condition had the most accurate groupings, while the low-pass filtered condition had the least accurate groupings. For the talker dialect accuracy, the Western dialect had the most accurate groupings while the Southern dialect had the least accurate groupings. Multidimensional scaling (MDS) plots visualized the groupings made for each condition. In both the natural and monotonized condition, participants were using dialect and gender to sort talkers. In the low-pass filtered condition, participants were using gender and not dialect to sort talkers, and the MDS plot looked different from the other MDS plots indicating that intonation alone was not effective for dialect classification.This thesis was funded by the Undergraduate Research Scholarship.No embargoAcademic Major: Linguistic

Lysyl-tRNA synthetase as a drug target in malaria and cryptosporidiosis

Malaria and cryptosporidiosis, caused by apicomplexan parasites, remain major drivers of global child mortality. New drugs for the treatment of malaria and cryptosporidiosis, in particular, are of high priority; however, there are few chemically validated targets. The natural product cladosporin is active against blood- and liver-stage; Plasmodium falciparum; and; Cryptosporidium parvum; in cell-culture studies. Target deconvolution in; P. falciparum; has shown that cladosporin inhibits lysyl-tRNA synthetase (; Pf; KRS1). Here, we report the identification of a series of selective inhibitors of apicomplexan KRSs. Following a biochemical screen, a small-molecule hit was identified and then optimized by using a structure-based approach, supported by structures of both; Pf; KRS1 and; C. parvum; KRS (; Cp; KRS). In vivo proof of concept was established in an SCID mouse model of malaria, after oral administration (ED; 90; = 1.5 mg/kg, once a day for 4 d). Furthermore, we successfully identified an opportunity for pathogen hopping based on the structural homology between; Pf; KRS1 and; Cp; KRS. This series of compounds inhibit; Cp; KRS and; C. parvum; and; Cryptosporidium hominis; in culture, and our lead compound shows oral efficacy in two cryptosporidiosis mouse models. X-ray crystallography and molecular dynamics simulations have provided a model to rationalize the selectivity of our compounds for; Pf; KRS1 and; Cp; KRS vs. (human); Hs; KRS. Our work validates apicomplexan KRSs as promising targets for the development of drugs for malaria and cryptosporidiosis

Data from: The effect of cost surface parameterization on landscape resistance estimates

A cost or resistance surface is a representation of a landscape’s permeability to animal movement or gene flow and is a tool for measuring functional connectivity in landscape ecology and genetics studies. Parameterizing cost surfaces by assigning weights to different landscape elements has been challenging however, because true costs are rarely known; thus, expert opinion is often used to derive relative weights. Assigning weights would be made easier if the sensitivity of different landscape resistance estimates to relative costs was known. We carried out a sensitivity analysis of three methods to parameterize a cost surface and two models of landscape permeability: least cost path and effective resistance. We found two qualitatively different responses to varying cost weights: linear and asymptotic changes. The most sensitive models (i.e. those leading to linear change) were accumulated least cost and effective resistance estimates on a surface coded as resistance (i.e. where high-quality elements were held constant at a low-value, and low-quality elements were varied at higher values). All other cost surface scenarios led to asymptotic change. Developing a cost surface that produces a linear response of landscape resistance estimates to cost weight variation will improve the accuracy of functional connectivity estimates, especially when cost weights are selected through statistical model fitting procedures. On the other hand, for studies where cost weights are unknown and model selection is not being used, methods where resistance estimates vary asymptotically with cost weights may be more appropriate, because of their relative insensitivity to parameterization

Forested landscape - conductance grid

Ascii file representing costs to movement for the forested landscape. Values are conductances, where high values represent low cost (high conductance). In Canada Lambert Conformal Conic projection

Data from: Landscape connectivity for wildlife: development and validation of multi-species linkage maps

The ability to identify regions of high functional connectivity for multiple wildlife species is of conservation interest with respect to forest management and corridor planning. We present a method that does not require independent, field-collected data, is insensitive to the placement of source and destination sites (nodes) for modeling connectivity, and does not require the selection of a focal species. In the first step of our approach, we created a cost surface that represented permeability of the landscape to movement for a suite of species. We randomly selected nodes around the perimeter of the buffered study area and used circuit theory to connect pairs of nodes. When the buffer was removed, the resulting current density map represented, for each grid cell, the probability of use by moving animals. We found that using nodes that were randomly located around the perimeter of the buffered study area was less biased by node placement than randomly selecting nodes within the study area. We also found that a buffer of ≥ 20% of the study area width was sufficient to remove the effects of node placement on current density. We tested our method by creating a map of connectivity in the Algonquin to Adirondack region in eastern North America, and we validated the map with independently collected data. We found that amphibians and reptiles were more likely to cross roads in areas of high current density, and fishers (Pekania [Martes] pennanti) used areas with high current density within their home ranges. Our approach provides an efficient and cost-effective method of predicting areas with relatively high functional connectivity

Data from: Landscape connectivity for wildlife: development and validation of multi-species linkage maps

The ability to identify regions of high functional connectivity for multiple wildlife species is of conservation interest with respect to forest management and corridor planning. We present a method that does not require independent, field-collected data, is insensitive to the placement of source and destination sites (nodes) for modeling connectivity, and does not require the selection of a focal species. In the first step of our approach, we created a cost surface that represented permeability of the landscape to movement for a suite of species. We randomly selected nodes around the perimeter of the buffered study area and used circuit theory to connect pairs of nodes. When the buffer was removed, the resulting current density map represented, for each grid cell, the probability of use by moving animals. We found that using nodes that were randomly located around the perimeter of the buffered study area was less biased by node placement than randomly selecting nodes within the study area. We also found that a buffer of ≥ 20% of the study area width was sufficient to remove the effects of node placement on current density. We tested our method by creating a map of connectivity in the Algonquin to Adirondack region in eastern North America, and we validated the map with independently collected data. We found that amphibians and reptiles were more likely to cross roads in areas of high current density, and fishers (Pekania [Martes] pennanti) used areas with high current density within their home ranges. Our approach provides an efficient and cost-effective method of predicting areas with relatively high functional connectivity

settled_landscape_30pts

coordinates of the 30 points for the settled landscape, in North America Lambert Conformal Conic projectio

forested_landscape_30pts

coordinates of the 30 random points for the forested landscape, in North America Lambert Conformal Conic projectio

Settled landscape - conductance grid

Ascii file representing costs to movement for the settled landscape. Values are conductances, where high values represent low cost (high conductance). In Canada Lambert Conformal Conic projection

current_map_raster

A current density map, produced by software Circuitscape. The cost surface was meant to represent permeability of the landscape to movement of forest- and wetland-dwelling species (high cost (1000) to impermeable land (major roads, development, large water bodies); medium cost (100) to semi-permeable land (minor roads, agriculture); and low cost (10) to natural cover (forest, wetland, etc.)). We selected 50 nodes at random locations around the perimeter of the buffered study area and connected them with current using software Circuitscape to produce the current density map