In-situ growth optimization in focused electron-beam induced deposition

We present the application of an evolutionary genetic algorithm for the in-situ optimization of nanostructures prepared by focused electron-beam-induced deposition. It allows us to tune the properties of the deposits towards highest conductivity by using the time gradient of the measured in-situ rate of change of conductance as fitness parameter for the algorithm. The effectiveness of the procedure is presented for the precursor W(CO)6 as well as for post-treatment of Pt-C deposits obtained by dissociation of MeCpPt(Me)3. For W(CO)6-based structures an increase of conductivity by one order of magnitude can be achieved, whereas the effect for MeCpPt(Me)3 is largely suppressed. The presented technique can be applied to all beam-induced deposition processes and has great potential for further optimization or tuning of parameters for nanostrucures prepared by FEBID or related techniques

Comparative Public Health: The Political Economy of Human Misery and Well‐Being

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147083/1/j.0020-8833.2004.00292.x.pd

Artificial Reef Attributes and The Relationship With Natural Reefs: Evidence From The Florida Keys

Natural or coral reefs represent extremely valuable ecosystems supporting an estimated 25 percent of all marine life, yet recent reports suggest that 75 percent of the world’s natural reefs are under threat from both natural and human stressors. In areas such as the Florida Keys that boasts an expansive mix of natural and artificial reefs, recreational diving on the system provides an important economic contribution to the local community but also potentially contributes to the stress of the existing natural reef system. We develop a revealed and stated preference modeling framework of diver behavior and find that deployment of an additional large ship reef increases overall diving activity but does not impact diving behavior on the natural reef system

When Is Domestic Political Unrest Related to International Conflict? Diversionary Theory and Japanese Foreign Policy, 1890–19411

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146888/1/j.1468-2478.2010.00620.x.pd

Enhancing Information Governance with Enterprise Architecture Management: Design Principles Derived from Benefits and Barriers in the GDPR Implementation

Businesses today are increasingly dependent on how they transform information into economic value, while simultaneously being compliant with intensified privacy requirements, resulting from legal acts like the General Data Protection Regulation (GDPR). As a consequence, realizing information governance has become a topic more important than ever to balance the beneficial use and protection of information. This paper argues that enterprise architecture management (EAM) can be a key to GDPR implementation as one important domain of information governance by providing transparency on information integration throughout an organization. Based on 24 interviews with 29 enterprise architects, we identified a multiplicity of benefits and barriers within the interplay of EAM and GDPR implementation and derived seven design principles that should foster EAM to enhance information governance

A Comparison of Survey Methods for Documenting Presence of Myotis leibii (Eastern Small-Footed Bats) at Roosting Areas in Western Virginia

Many aspects of foraging and roosting habitat of Myotis leibii (Eastern Small-Footed Bat), an emergent rock roosting-obligate, are poorly described. Previous comparisons of effectiveness of acoustic sampling and mist-net captures have not included Eastern Small-Footed Bat. Habitat requirements of this species differ from congeners in the region, and it is unclear whether survey protocols developed for other species are applicable. Using data from three overlapping studies at two sampling sites in western Virginia’s central Appalachian Mountains, detection probabilities were examined for three survey methods (acoustic surveys with automated identification of calls, visual searches of rock crevices, and mist-netting) for use in the development of “best practices” for future surveys and monitoring. Observer effects were investigated using an expanded version of visual search data. Results suggested that acoustic surveys with automated call identification are not effective for documenting presence of Eastern Small-Footed Bats on talus slopes (basal detection rate of 0%) even when the species is known to be present. The broadband, high frequency echolocation calls emitted by Eastern Small-Footed Bat may be prone to attenuation by virtue of their high frequencies, and these factors, along with signal reflection, lower echolocation rates or possible misidentification to other bat species over talus slopes may all have contributed to poor acoustic survey success. Visual searches and mist-netting of emergent rock had basal detection probabilities of 91% and 75%, respectively. Success of visual searches varied among observers, but detection probability improved with practice. Additionally, visual searches were considerably more economical than mist-netting

Modelling environmental impacts of agriculture, focusing on oil palm

Cultivation of crops affects the environment via flows of energy and materials. Impacts are felt in the atmosphere, hydrosphere, surrounding terrestrial ecosystems and the field itself. Models are useful tools for improving our understanding of the processes and predicting how they might be affected by changes in management. Current models range from simple indicators of risk or impact, based on empirical relationships, to dynamic process-based models. Increasingly complex and comprehensive models with increasing spatial and temporal resolution and extent are being developed, mostly by coupling diverse sub-models. This chapter reviews the range of models developed for oil palm systems, and discusses how other existing models might be adapted for oil palm

Variability-aware Datalog

Variability-aware computing is the efficient application of programs to different sets of inputs that exhibit some variability. One example is program analyses applied to Software Product Lines (SPLs). In this paper we present the design and development of a variability-aware version of the Souffl\'{e} Datalog engine. The engine can take facts annotated with Presence Conditions (PCs) as input, and compute the PCs of its inferred facts, eliminating facts that do not exist in any valid configuration. We evaluate our variability-aware Souffl\'{e} implementation on several fact sets annotated with PCs to measure the associated overhead in terms of processing time and database size.Comment: PADL'20 pape