Designing a solution to enable agency-academic scientific collaboration for disasters

© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ecology and Society 22 (2017): 18, doi:10.5751/ES-09246-220218.As large-scale environmental disasters become increasingly frequent and more severe globally, people and organizations that prepare for and respond to these crises need efficient and effective ways to integrate sound science into their decision making. Experience has shown that integrating nongovernmental scientific expertise into disaster decision making can improve the quality of the response, and is most effective if the integration occurs before, during, and after a crisis, not just during a crisis. However, collaboration between academic, government, and industry scientists, decision makers, and responders is frequently difficult because of cultural differences, misaligned incentives, time pressures, and legal constraints. Our study addressed this challenge by using the Deep Change Method, a design methodology developed by Stanford ChangeLabs, which combines human-centered design, systems analysis, and behavioral psychology. We investigated underlying needs and motivations of government agency staff and academic scientists, mapped the root causes underlying the relationship failures between these two communities based on their experiences, and identified leverage points for shifting deeply rooted perceptions that impede collaboration. We found that building trust and creating mutual value between multiple stakeholders before crises occur is likely to increase the effectiveness of problem solving. We propose a solution, the Science Action Network, which is designed to address barriers to scientific collaboration by providing new mechanisms to build and improve trust and communication between government administrators and scientists, industry representatives, and academic scientists. The Science Action Network has the potential to ensure cross-disaster preparedness and science-based decision making through novel partnerships and scientific coordination.The authors thank the David and Lucile Packard Foundation for a grant to undertake this project and enable participation of a wide range of participants and interviewees. We thank the Center for Ocean Solutions and ChangeLabs for their oversight and support

Naturally occurring cobalamin (B12) analogs can function as cofactors for human methylmalonyl-CoA mutase

Cobalamin, commonly known as vitamin B12, is an essential micronutrient for humans because of its role as an enzyme cofactor. Cobalamin is one of over a dozen structurally related compounds - cobamides - that are found in certain foods and are produced by microorganisms in the human gut. Very little is known about how different cobamides affect B12-dependent metabolism in human cells. Here, we test in vitro how diverse cobamide cofactors affect the function of methylmalonyl-CoA mutase (MMUT), one of two cobalamin-dependent enzymes in humans. We find that, although cobalamin is the most effective cofactor for MMUT, multiple cobamides support MMUT function with differences in binding affinity (Kd), binding kinetics (kon), and concentration dependence during catalysis (KM, app). Additionally, we find that six disease-associated MMUT variants that cause cobalamin-responsive impairments in enzymatic activity also respond to other cobamides, with the extent of catalytic rescue dependent on the identity of the cobamide. Our studies challenge the exclusive focus on cobalamin in the context of human physiology, indicate that diverse cobamides can support the function of a human enzyme, and suggest future directions that will improve our understanding of the roles of different cobamides in human biology. Keywords: Cobalamin; Cobamide; MMUT; Methylmalonic aciduria; Methylmalonyl-CoA mutase; Vitamin B(12)

Roadmap on electronic structure codes in the exascale era

Electronic structure calculations have been instrumental in providing many important insights into a range of physical and chemical properties of various molecular and solid-state systems. Their importance to various fields, including materials science, chemical sciences, computational chemistry, and device physics, is underscored by the large fraction of available public supercomputing resources devoted to these calculations. As we enter the exascale era, exciting new opportunities to increase simulation numbers, sizes, and accuracies present themselves. In order to realize these promises, the community of electronic structure software developers will however first have to tackle a number of challenges pertaining to the efficient use of new architectures that will rely heavily on massive parallelism and hardware accelerators. This roadmap provides a broad overview of the state-of-the-art in electronic structure calculations and of the various new directions being pursued by the community. It covers 14 electronic structure codes, presenting their current status, their development priorities over the next five years, and their plans towards tackling the challenges and leveraging the opportunities presented by the advent of exascale computing

Roadmap on Electronic Structure Codes in the Exascale Era

Electronic structure calculations have been instrumental in providing many important insights into a range of physical and chemical properties of various molecular and solid-state systems. Their importance to various fields, including materials science, chemical sciences, computational chemistry and device physics, is underscored by the large fraction of available public supercomputing resources devoted to these calculations. As we enter the exascale era, exciting new opportunities to increase simulation numbers, sizes, and accuracies present themselves. In order to realize these promises, the community of electronic structure software developers will however first have to tackle a number of challenges pertaining to the efficient use of new architectures that will rely heavily on massive parallelism and hardware accelerators. This roadmap provides a broad overview of the state-of-the-art in electronic structure calculations and of the various new directions being pursued by the community. It covers 14 electronic structure codes, presenting their current status, their development priorities over the next five years, and their plans towards tackling the challenges and leveraging the opportunities presented by the advent of exascale computing

Roadmap on Electronic Structure Codes in the Exascale Era

Electronic structure calculations have been instrumental in providing many important insights into a range of physical and chemical properties of various molecular and solid-state systems. Their importance to various fields, including materials science, chemical sciences, computational chemistry and device physics, is underscored by the large fraction of available public supercomputing resources devoted to these calculations. As we enter the exascale era, exciting new opportunities to increase simulation numbers, sizes, and accuracies present themselves. In order to realize these promises, the community of electronic structure software developers will however first have to tackle a number of challenges pertaining to the efficient use of new architectures that will rely heavily on massive parallelism and hardware accelerators. This roadmap provides a broad overview of the state-of-the-art in electronic structure calculations and of the various new directions being pursued by the community. It covers 14 electronic structure codes, presenting their current status, their development priorities over the next five years, and their plans towards tackling the challenges and leveraging the opportunities presented by the advent of exascale computing

Roadmap on Electronic Structure Codes in the Exascale Era

Electronic structure calculations have been instrumental in providing many important insights into a range of physical and chemical properties of various molecular and solid-state systems. Their importance to various fields, including materials science, chemical sciences, computational chemistry and device physics, is underscored by the large fraction of available public supercomputing resources devoted to these calculations. As we enter the exascale era, exciting new opportunities to increase simulation numbers, sizes, and accuracies present themselves. In order to realize these promises, the community of electronic structure software developers will however first have to tackle a number of challenges pertaining to the efficient use of new architectures that will rely heavily on massive parallelism and hardware accelerators. This roadmap provides a broad overview of the state-of-the-art in electronic structure calculations and of the various new directions being pursued by the community. It covers 14 electronic structure codes, presenting their current status, their development priorities over the next five years, and their plans towards tackling the challenges and leveraging the opportunities presented by the advent of exascale computing.Comment: Submitted as a roadmap article to Modelling and Simulation in Materials Science and Engineering; Address any correspondence to Vikram Gavini ([email protected]) and Danny Perez ([email protected]

C. PRESL) at the transcriptional level.

This paper investigates differences in gene expression among the two Thlaspi caerulescens ecotypes La Calamine (LC) and Lellingen (LE) that have been shown to differ in metal tolerance and metal uptake. LC originates from a metalliferous soil and tolerates higher metal concentrations than LE which originates from a non-metalliferous soil. The two ecotypes were treated with different levels of zinc in solution culture, and differences in gene expression were assessed through application of a cDNA microarray consisting of 1,700 root and 2,700 shoot cDNAs. Hybridisation of root and shoot cDNA from the two ecotypes revealed a total of 257 differentially expressed genes. The regulation of selected genes was verified by quantitative reverse transcriptase polymerase chain reaction. Comparison of the expression profiles of the two ecotypes suggests that LC has a higher capacity to cope with reactive oxygen species and to avoid the formation of peroxynitrite. Furthermore, increased transcripts for the genes encoding for water channel proteins could explain the higher Zn tolerance of LC compared to LE. The higher Zn tolerance of LC was reflected by a lower expression of the genes involved in disease and defence mechanisms. The results of this study provide a valuable set of data that may help to improve our understanding of the mechanisms employed by plants to tolerate toxic concentrations of metal in the soil

PermaDAQ: a scientific instrument for precision sensing and data recovery in environmental extremes

The PermaSense project has set the ambitious goal of gathering real-time environmental data for high-mountain permafrost in unattended operation over multiple years. This paper discusses the specialized sensing and data recovery architecture tailored to meet the precision, reliability and durability requirements of scientists utilizing the data for model validation. We present a custom sensor interface board including specialized sensors and redundancy features for end-to-end data validation. Aspects of high-quality data acquisition, design for reliability by strict separation of operating phases and analysis of energy efficiency are discussed. The system integration using the Dozer protocol scheme achieves a best-in-class average power consumption of 148μA considerably exceeding the lifetime requirement

System-level performance evaluation of reconfigurable processors

Reconfigurable architectures that tightly integrate a standard CPU core with a field-programmable hardware structure have recently been receiving increased attention. The design of such a hybrid reconfigurable processor involves a multitude of design decisions regarding the field-programmable structure as well as its system integration with the CPU core. Determining the impact of these design decisions on the overall system performance is a challenging task. In this paper, we first present a framework for the cycle-accurate performance evaluation of hybrid reconfigurable processors on the system level. Then, we discuss a reconfigurable processor for data-streaming applications, which attaches a coarse-grained reconfigurable unit to the coprocessor interface of a standard embedded CPU core. By means of a case study we evaluate the system-level impact of certain design features for the reconfigurable unit, such as multiple contexts, register replication, and hardware context scheduling. The results illustrate that a system-level evaluation framework is of paramount importance for studying the architectural trade-offs and optimizing design parameters for reconfigurable processors. q 2004 Elsevier B.V. All rights reserved