DEVELOPMENT AND UTILIZATION OF GEODATABASE: PREDICTING BIODIVERSITY IN EQUATORIAL GUINEA, AFRICA

After declaring independence in 1968 and discovering oil reserves in 1995, Equatorial Guinea has arisen as one of the wealthier countries in Africa but unfortunately has become one of the most volatile countries as well, with the numerous military coups and disproportionate distribution of wealth. This nation also houses some of the most diverse wildlife on earth, with several endangered species of mammals, as well as reptilian and bird species that are unique only to Equatorial Guinea. With increased bushmeat demand increasing in the last two decades, illegal hunting activities have increased as well, even in national parks. Because of the threats to the native flora and fauna species in the country, it becomes more important to determine what factors can motivate their movement and development. This way, we can predict the biodiversity in impacted areas and be able to coordinate better enforcement efforts to ensure the continued protection of these species and promote biodiversity throughout both Equatorial Guinea and the continent of Africa itself. The manufactured geodatabase will hopefully provide insight on how to predict biodiversity in the country’s ecoregions and the factors that drive biodiversity. This document will provide formatting instructions on how the Equatorial Guinea geodatabase was created and how to manage and maintain the information stored within it

Human/machine Learning: Becoming Responsible for Learning Cultures of Digital Technologies

This paper centrally asks for the ways in which ubiquitous, ever new digital technologies of 'our' everyday lives transform learning at the digital human-machine interface from the perspective of feminist science and technology studies. How to account for emerging forms of interwoven human and machine learning? Suggesting the term of learning cultures in approaching this question, the paper emphasizes an understanding of learning not as a proficiency of an entity embodying either natural or artificial intelligence, but rather as a culturally situated and materially enacted process. In so doing, the paper brings together recent impulses that suggest a re-conceptualization of learning, e.g. through the notion of "machine learners" (Mackenzie 2017) or that of "posthuman learning (Hasse 2018)". Reading these insights together, I will finally suggest an account of becoming responsible for learning cultures of digital technologies through a reconsidered notion of interwoven human/machine learning

Nancy Treusch to Mr. Meredith (30 September 1962)

https://egrove.olemiss.edu/mercorr_pro/1237/thumbnail.jp

Robotic Knitting

As a reaction to typically dead-end debates on future human and robot collaboration that tend to be either dismissive or overly welcoming towards »cobot« technologies, this book provides a technofeminist intervention. Pat Treusch not only shows how both the fields of technofeminism and robotics can engage in a practical exchange through knitting, but also contributes a tangible example of coboting dynamics. Robotic Knitting re-negotiates the boundaries between formalisation and embodiment, craft and high-tech as well as useful and dysfunctional machines. It re-crafts the nature of collaboration between human and robot. This finally entails an alternative mode of relating - a mode that enables an account of careful coboting

Genetic interactions contribute less than additive effects to quantitative trait variation in yeast.

Genetic mapping studies of quantitative traits typically focus on detecting loci that contribute additively to trait variation. Genetic interactions are often proposed as a contributing factor to trait variation, but the relative contribution of interactions to trait variation is a subject of debate. Here we use a very large cross between two yeast strains to accurately estimate the fraction of phenotypic variance due to pairwise QTL-QTL interactions for 20 quantitative traits. We find that this fraction is 9% on average, substantially less than the contribution of additive QTL (43%). Statistically significant QTL-QTL pairs typically have small individual effect sizes, but collectively explain 40% of the pairwise interaction variance. We show that pairwise interaction variance is largely explained by pairs of loci at least one of which has a significant additive effect. These results refine our understanding of the genetic architecture of quantitative traits and help guide future mapping studies

Rare variants contribute disproportionately to quantitative trait variation in yeast.

How variants with different frequencies contribute to trait variation is a central question in genetics. We use a unique model system to disentangle the contributions of common and rare variants to quantitative traits. We generated ~14,000 progeny from crosses among 16 diverse yeast strains and identified thousands of quantitative trait loci (QTLs) for 38 traits. We combined our results with sequencing data for 1011 yeast isolates to show that rare variants make a disproportionate contribution to trait variation. Evolutionary analyses revealed that this contribution is driven by rare variants that arose recently, and that negative selection has shaped the relationship between variant frequency and effect size. We leveraged the structure of the crosses to resolve hundreds of QTLs to single genes. These results refine our understanding of trait variation at the population level and suggest that studies of rare variants are a fertile ground for discovery of genetic effects

Amyloid Deposits: Protection Against Toxic Protein Species?

Neurodegenerative diseases ranging from Alzheimer’s disease and polyglutamine diseases to transmissible spongiform encephalopathies are associated with the aggregation and accumulation of misfolded proteins. In several cases the intracellular and extracellular protein deposits contain a fibrillar protein species called amyloid. However while amyloid deposits are hallmarks of numerous neurodegenerative diseases, their actual role in disease progression remains unclear. Especially perplexing is the often poor correlation between protein deposits and other markers of neurodegeneration. As a result the question remains whether amyloid deposits are the disease causing species, the consequence of cellular disease pathology or even the result of a protective cellular response to misfolded protein species. Here we highlight studies that suggest that accumulation and sequestration of misfolded protein in amyloid inclusion bodies and plaques can serve a protective function. Furthermore, we discuss how exceeding the cellular capacity for protective deposition of misfolded proteins may contribute to the formation of toxic protein species

Vom Handeln zum Begriff? : Ein Beitrag zur Geschichte missionarischer Jugendarbeit

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