Synthesis and post-functionalization of alternate-linked-meta-para-[2(n). 1(n)]thiacyclophanes

In recent decades, considerable research attention has been devoted to new synthetic procedures for thiacyclophanes. Thiacyclophanes are widely used as host molecules for the molecular recognition of organic compounds as well as metals. Herein, we report the selective and high-yielding synthesis of novel alternate-linked-meta-para-thiacyclophanes. These novel thiacyclophanes are selectively synthesized in high-yielding procedures. Furthermore, post-functionalization of the phenolic moieties was successfully performed. The 3D structure of the alternate-linked-meta-para-[22.12]thiacyclophane was further elucidated via X-ray crystallographic analysis

The Effect of Map Boundary on Estimates of Landscape Resistance to Animal Movement

BACKGROUND: Artificial boundaries on a map occur when the map extent does not cover the entire area of study; edges on the map do not exist on the ground. These artificial boundaries might bias the results of animal dispersal models by creating artificial barriers to movement for model organisms where there are no barriers for real organisms. Here, we characterize the effects of artificial boundaries on calculations of landscape resistance to movement using circuit theory. We then propose and test a solution to artificially inflated resistance values whereby we place a buffer around the artificial boundary as a substitute for the true, but unknown, habitat. METHODOLOGY/PRINCIPAL FINDINGS: We randomly assigned landscape resistance values to map cells in the buffer in proportion to their occurrence in the known map area. We used circuit theory to estimate landscape resistance to organism movement and gene flow, and compared the output across several scenarios: a habitat-quality map with artificial boundaries and no buffer, a map with a buffer composed of randomized habitat quality data, and a map with a buffer composed of the true habitat quality data. We tested the sensitivity of the randomized buffer to the possibility that the composition of the real but unknown buffer is biased toward high or low quality. We found that artificial boundaries result in an overestimate of landscape resistance. CONCLUSIONS/SIGNIFICANCE: Artificial map boundaries overestimate resistance values. We recommend the use of a buffer composed of randomized habitat data as a solution to this problem. We found that resistance estimated using the randomized buffer did not differ from estimates using the real data, even when the composition of the real data was varied. Our results may be relevant to those interested in employing Circuitscape software in landscape connectivity and landscape genetics studies

Predicting Landscape-Genetic Consequences of Habitat Loss, Fragmentation and Mobility for Multiple Species of Woodland Birds

Inference concerning the impact of habitat fragmentation on dispersal and gene flow is a key theme in landscape genetics. Recently, the ability of established approaches to identify reliably the differential effects of landscape structure (e.g. land-cover composition, remnant vegetation configuration and extent) on the mobility of organisms has been questioned. More explicit methods of predicting and testing for such effects must move beyond post hoc explanations for single landscapes and species. Here, we document a process for making a priori predictions, using existing spatial and ecological data and expert opinion, of the effects of landscape structure on genetic structure of multiple species across replicated landscape blocks. We compare the results of two common methods for estimating the influence of landscape structure on effective distance: least-cost path analysis and isolation-by-resistance. We present a series of alternative models of genetic connectivity in the study area, represented by different landscape resistance surfaces for calculating effective distance, and identify appropriate null models. The process is applied to ten species of sympatric woodland-dependant birds. For each species, we rank a priori the expectation of fit of genetic response to the models according to the expected response of birds to loss of structural connectivity and landscape-scale tree-cover. These rankings (our hypotheses) are presented for testing with empirical genetic data in a subsequent contribution. We propose that this replicated landscape, multi-species approach offers a robust method for identifying the likely effects of landscape fragmentation on dispersal

A learning trajectory of quantitative methods : a curriculum based model for overcoming statistics anxiety

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Learning Trajectory of Quantitative Methods – Students' Experience with Curriculum-based Method for Overcoming Statistics Anxiety

Social science students fear and dread statistics; they avoid it whenever possible. This finding sharply contrasts with the importance of quantitative data and the methods applied to it, both in the field, and in society. How then, can we overcome this statistics anxiety, and give students the skills needed for their future careers? Drawing from the constructivist theory of learning and the literature on teaching statistics, it is found that students’ field of interest, the use of progressive steps, active use of these methods are important to achieve long-term retention. Most innovations in this regard targeted methodological courses. We argue that innovation should come from a curriculum perspective, instead of the perspective of individual courses. We suggest the use of a Learning Trajectory of Quantitative Methods, i.e. four hierarchically inclusive stages, which are implemented throughout the curriculum by means of Learning Tasks. These learning tasks, which can consist out of assignments, lectures and discussions, are constructed trough a careful process ensuring support from the responsible lecturer. This paper presents a first assessment of the learning trajectory and the used process of creating learning tasks. Using focus groups with students and interviews with the collaborating professors, we will reflect on the strengths and weaknesses of the suggested approach. This assessment and the detailing of the used process can present a tool other educators can easily use in their courses and more general in other education programmes to integrate statistics in substantive courses.status: publishe

Mad about Methods? Teaching Research Methods in Political Science

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Taking Research Methods out of Isolation. Teachers’ experiences with curriculum-wide integration of research methods in substantive courses

Statistics courses stand rather isolated in most political science curricula. Students do not see the value of statistics to political science, and tend to avoid or at least postpone taking statistics courses. Given the importance of statistics to the field, we educators are left with a baring question. To make students see value in research methods, we need to overcome this isolation of research methods courses in the curriculum, but how can we introduce statistics coherently across the curriculum without intruding lecturers’ ‘academic freedom’? The literature on teaching research methods has shown that using real world contexts and relying on students’ spheres of interest are a necessity to engage students. With this in mind, scholars are looking to integrate research methods in single substantive courses. Curriculum- based strategies, however, are lacking. This paper presents such a curriculum-based approach. Moreover, after narrating the project and the method used to integrate statistics coherently, i.e. the Learning Trajectory of Quantitative Methods, the paper presents lecturers experiences with integrating quantitative methods in their substantive courses. Based on interviews with the involved professors we reveal strengths and weaknesses of this curriculum-based approach. This paper does not only contribute to the literature on teaching research methods, but it also provides educators with a tool to integrate research methods in the curriculum. Although quantitative methods are focused upon in this project, the underlying principles can easily be transferred to other research methods and other educational settings.status: publishe