Locative Expressions In Signed Languages: A Cross-Linguistic Comparison

The primary focus of this paper is to examine whether sign languages organize their locative expressions similarly to spoken languages. Paving the way in the study of spatial relations by focusing on the structuring of ON and IN locatives in spoken languages, Bowerman and colleagues (Bowerman 1980; Melissa Bowerman & Eric Pederson 1992a; Bowerman 1993; 1994; 1996a; 1996b; Bowerman & Levinson 2001) found that spoken languages organize the locative phrases representing the relationships of ON and IN in a continuum which is called the ON-IN continuum. This thesis shows that sign languages do not linguistically pattern similarly to spoken languages along the ON-IN continuum. One reason for this could be the vast difference in modality between signed and spoken languages. Essentially, locative constructions in sign languages contain visual representations which resemble real world spatial relationships, while spoken languages tend to use arbitrary locative constructions which do not resemble real world spatial relationships. Locative constructions in sign languages are created by combining representations of ground and figure in various ways. Ground and figure can be represented sequentially or simultaneously by classifiers or lexical items or a combination of the two. In the discourse leading up to a locative construction a noun representing ground is generally introduced first followed by a noun representing the figure. Adpositions can also be used in locative phrases but this was the option least chosen in my data

Monotonicity-Based Regularization for Shape Reconstruction in Linear Elasticity

We deal with the shape reconstruction of inclusions in elastic bodies. For solving this inverse problem in practice, data fitting functionals are used. Those work better than the rigorous monotonicity methods from [5], but have no rigorously proven convergence theory. Therefore we show how the monotonicity methods can be converted into a regularization method for a data-fitting functional without losing the convergence properties of the monotonicity methods. This is a great advantage and a significant improvement over standard regularization techniques. In more detail, we introduce constraints on the minimization problem of the residual based on the monotonicity methods and prove the existence and uniqueness of a minimizer as well as the convergence of the method for noisy data. In addition, we compare numerical reconstructions of inclusions based on the monotonicity-based regularization with a standard approach (one-step linearization with Tikhonov-like regularization), which also shows the robustness of our method regarding noise in practice.Comment: 26 pages, 15 figure

Bayesian experimental design for linear elasticity

This work considers Bayesian experimental design for the inverse boundary value problem of linear elasticity in a two-dimensional setting. The aim is to optimize the positions of compactly supported pressure activations on the boundary of the examined body in order to maximize the value of the resulting boundary deformations as data for the inverse problem of reconstructing the Lam\'e parameters inside the object. We resort to a linearized measurement model and adopt the framework of Bayesian experimental design, under the assumption that the prior and measurement noise distributions are mutually independent Gaussians. This enables the use of the standard Bayesian A-optimality criterion for deducing optimal positions for the pressure activations. The (second) derivatives of the boundary measurements with respect to the Lam\'e parameters and the positions of the boundary pressure activations are deduced to allow minimizing the corresponding objective function, i.e., the trace of the covariance matrix of the posterior distribution, by a gradient-based optimization algorithm. Two-dimensional numerical experiments are performed to demonstrate the functionality of our approach.Comment: 23 pages, 11 figure

Lipschitz stability estimate and reconstruction of Lam\'e parameters in linear elasticity

In this paper, we consider the inverse problem of recovering an isotropic elastic tensor from the Neumann-to-Dirichlet map. To this end, we prove a Lipschitz stability estimate for Lam\'e parameters with certain regularity assumptions. In addition, we assume that the Lam\'e parameters belong to a known finite subspace with a priori known bounds and that they fulfill a monotonicity property. The proof relies on a monotonicity result combined with the techniques of localized potentials. To numerically solve the inverse problem, we propose a Kohn-Vogelius-type cost functional over a class of admissible parameters subject to two boundary value problems. The reformulation of the minimization problem via the Neumann-to-Dirichlet operator allows us to obtain the optimality conditions by using the Fr\'echet differentiability of this operator and its inverse. The reconstruction is then performed by means of an iterative algorithm based on a quasi-Newton method. Finally, we give and discuss several numerical examples.Comment: 23 pages, 17 figure

A Stable Boundary Integral Formulation of an Acoustic Wave Transmission Problem with Mixed Boundary Conditions

In this paper, we consider an acoustic wave transmission problem with mixed boundary conditions of Dirichlet, Neumann, and impedance type. The transmission interfaces may join the domain boundary in a general way independent of the location of the boundary conditions. We will derive a formulation as a \textit{direct}, \textit{space-time retarded boundary integral equation}, where both Cauchy data are kept as unknowns on the impedance part of the boundary. This requires the definition of single-trace spaces which incorporate homogeneous Dirichlet and Neumann conditions on the corresponding parts on the boundary. We prove the continuity and coercivity of the formulation by employing the technique of operational calculus in the Laplace domain.Comment: 15 pages, 1 figur

Do they intend to stay? An empirical study of commercial apprentices’ motivation, satisfaction and intention to remain within the learned occupation

Background: Commercial apprenticeship is the most commonly chosen type of apprenticeship within vocational education training in Switzerland. Both the Swiss economy and the training companies themselves benefit when apprentices remain within the occupation and company after their vocational education and training has ended. However, little is known about commercial apprentices’ intention to remain and its development. The literature discusses learning motivation and (apprenticeship) satisfaction as important factors in the development of the intention to remain from both a theoretical and an empirical perspective. We report the status quo of further educational and working intentions at the end of apprenticeship training and interdependency of the remaining intention’s, learning motivation’s and training satisfaction’s development. To do so, we propose a cross-lagged structural equation model that examines the constructs’ autoregressive paths but also causal effects on each other over time. Methods: We present empirical data gathered in a representative sample of 83 classes (n = 1905) of commercial apprentices of both the E- and M-Profile in German-speaking regions of Switzerland. The apprentices participated in the standardized survey four times in total: at the beginning, at a halfway point during their apprenticeship, half a year before final examinations and two to three months before termination. Hypotheses were tested using descriptive methods as well as latent state models and a cross-lagged structural equation model. Results and conclusions: It was found that a majority of commercial apprentices intend to remain within the learned profession after graduation (57.7%). However, one in five apprentices does not have such intentions, and one in four apprentices is still undecided. Slightly less than 60% of apprentices had a follow-up solution after finishing their training and more than 80% of them planned to remain employed within their training company. Despite their follow-up positions, commercial apprentices tend to continue their education. Only 6% of the apprentices denied having any further educational intention within the next five years. With regard to the intention to remain within the learned occupation, training satisfaction was found to be an important factor. The intention to remain within the occupation also increases training satisfaction. Although learning motivation does not seem to directly affect the intention to remain within the learned occupation, it nevertheless affects training satisfaction positively. For policy-makers, teachers, trainers and educators, it is important to understand the factors that positively contribute to the intention to remain within the learned profession. Therefore, the current study can be considered a starting point. However, more research is needed

Brief Note Difficulties in Determining Factors that Influence Effective Groundwater Recharge in Ohio

Author Institution: COSI Academy, Center of Science and Industry ; US Geological SurveyAS part of a COSI Academy research project, data from a recent statewide analysis of effective groundwater recharge were reexamined by students to further discern relations between recharge and selected environmental characteristics of individual drainage basins: 1) location of the main stem of a river relative to coarse and fine surficial sediments and 2) influence of land use. Lack of sufficiently detailed data was the principal difficulty in most phases of the examination. Other than a potential relation between recharge and the percentages of agricultural and forested land, no relations were found in visual comparisons of mapped and tabulated data

Student Recital

Program listing performers and works performed

Power to Detect Risk Alleles Using Genome-Wide Tag SNP Panels

Advances in high-throughput genotyping and the International HapMap Project have enabled association studies at the whole-genome level. We have constructed whole-genome genotyping panels of over 550,000 (HumanHap550) and 650,000 (HumanHap650Y) SNP loci by choosing tag SNPs from all populations genotyped by the International HapMap Project. These panels also contain additional SNP content in regions that have historically been overrepresented in diseases, such as nonsynonymous sites, the MHC region, copy number variant regions and mitochondrial DNA. We estimate that the tag SNP loci in these panels cover the majority of all common variation in the genome as measured by coverage of both all common HapMap SNPs and an independent set of SNPs derived from complete resequencing of genes obtained from SeattleSNPs. We also estimate that, given a sample size of 1,000 cases and 1,000 controls, these panels have the power to detect single disease loci of moderate risk (λ ∼ 1.8–2.0). Relative risks as low as λ ∼ 1.1–1.3 can be detected using 10,000 cases and 10,000 controls depending on the sample population and disease model. If multiple loci are involved, the power increases significantly to detect at least one locus such that relative risks 20%–35% lower can be detected with 80% power if between two and four independent loci are involved. Although our SNP selection was based on HapMap data, which is a subset of all common SNPs, these panels effectively capture the majority of all common variation and provide high power to detect risk alleles that are not represented in the HapMap data

Differential effects of natural rewards and pain on vesicular glutamate transporter expression in the nucleus accumbens

Background: Pain and natural rewards such as food elicit different behavioral effects. Both pain and rewards, however, have been shown to alter synaptic activities in the nucleus accumbens (NAc), a key component of the brain reward system. Mechanisms by which external stimuli regulate plasticity at NAc synapses are largely unexplored. Medium spiny neurons (MSNs) from the NAc receive excitatory glutamatergic inputs and modulatory dopaminergic and cholinergic inputs from a variety of cortical and subcortical structures. Glutamate inputs to the NAc arise primarily from prefrontal cortex, thalamus, amygdala, and hippocampus, and different glutamate projections provide distinct synaptic and ultimately behavioral functions. The family of vesicular glutamate transporters (VGLUTs 1–3) plays a key role in the uploading of glutamate into synaptic vesicles. VGLUT1-3 isoforms have distinct expression patterns in the brain, but the effects of external stimuli on their expression patterns have not been studied. Results: In this study, we use a sucrose self-administration paradigm for natural rewards, and spared nerve injury (SNI) model for chronic pain. We examine the levels of VGLUTs (1–3) in synaptoneurosomes of the NAc in these two behavioral models. We find that chronic pain leads to a decrease of VGLUT1, likely reflecting decreased projections from the cortex. Pain also decreases VGLUT3 levels, likely representing a decrease in projections from GABAergic, serotonergic, and/or cholinergic interneurons. In contrast, chronic consumption of sucrose increases VGLUT3 in the NAc, possibly reflecting an increase from these interneuron projections. Conclusion: Our study shows that natural rewards and pain have distinct effects on the VGLUT expression pattern in the NAc, indicating that glutamate inputs to the NAc are differentially modulated by rewards and pain