34,153 research outputs found
Communication and re-use of chemical information in bioscience.
The current methods of publishing chemical information in bioscience articles are analysed. Using 3 papers as use-cases, it is shown that conventional methods using human procedures, including cut-and-paste are time-consuming and introduce errors. The meaning of chemical terms and the identity of compounds is often ambiguous. valuable experimental data such as spectra and computational results are almost always omitted. We describe an Open XML architecture at proof-of-concept which addresses these concerns. Compounds are identified through explicit connection tables or links to persistent Open resources such as PubChem. It is argued that if publishers adopt these tools and protocols, then the quality and quantity of chemical information available to bioscientists will increase and the authors, publishers and readers will find the process cost-effective.An article submitted to BiomedCentral Bioinformatics, created on request with their Publicon system. The transformed manuscript is archived as PDF. Although it has been through the publishers system this is purely automatic and the contents are those of a pre-refereed preprint. The formatting is provided by the system and tables and figures appear at the end. An accommpanying submission, http://www.dspace.cam.ac.uk/handle/1810/34580, describes the rationale and cultural aspects of publishing , abstracting and aggregating chemical information. BMC is an Open Access publisher and we emphasize that all content is re-usable under Creative Commons Licens
Biosecurity: A 21st Century Challenge
Based on a review of key reports and experts' opinions, summarizes the debate over "dual-use" technologies and the various approaches to controlling biosecurity risk. Outlines proposed preventive measures and steps to build response capacity
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Skills and Knowledge for Data-Intensive Environmental Research.
The scale and magnitude of complex and pressing environmental issues lend urgency to the need for integrative and reproducible analysis and synthesis, facilitated by data-intensive research approaches. However, the recent pace of technological change has been such that appropriate skills to accomplish data-intensive research are lacking among environmental scientists, who more than ever need greater access to training and mentorship in computational skills. Here, we provide a roadmap for raising data competencies of current and next-generation environmental researchers by describing the concepts and skills needed for effectively engaging with the heterogeneous, distributed, and rapidly growing volumes of available data. We articulate five key skills: (1) data management and processing, (2) analysis, (3) software skills for science, (4) visualization, and (5) communication methods for collaboration and dissemination. We provide an overview of the current suite of training initiatives available to environmental scientists and models for closing the skill-transfer gap
A Scientist's Guide to Achieving Broader Impacts through K-12 STEM Collaboration.
The National Science Foundation and other funding agencies are increasingly requiring broader impacts in grant applications to encourage US scientists to contribute to science education and society. Concurrently, national science education standards are using more inquiry-based learning (IBL) to increase students' capacity for abstract, conceptual thinking applicable to real-world problems. Scientists are particularly well suited to engage in broader impacts via science inquiry outreach, because scientific research is inherently an inquiry-based process. We provide a practical guide to help scientists overcome obstacles that inhibit their engagement in K-12 IBL outreach and to attain the accrued benefits. Strategies to overcome these challenges include scaling outreach projects to the time available, building collaborations in which scientists' research overlaps with curriculum, employing backward planning to target specific learning objectives, encouraging scientists to share their passion, as well as their expertise with students, and transforming institutional incentives to support scientists engaging in educational outreach
A Vertical Channel Model of Molecular Communication based on Alcohol Molecules
The study of Molecular Communication(MC) is more and more prevalence, and
channel model of MC plays an important role in the MC System. Since different
propagation environment and modulation techniques produce different channel
model, most of the research about MC are in horizontal direction,but in nature
the communications between nano machines are in short range and some of the
information transportation are in the vertical direction, such as transpiration
of plants, biological pump in ocean, and blood transportation from heart to
brain. Therefore, this paper we propose a vertical channel model which
nano-machines communicate with each other in the vertical direction based on
pure diffusion. We first propose a vertical molecular communication model, we
mainly considered the gravity as the factor, though the channel model is also
affected by other main factors, such as the flow of the medium, the distance
between the transmitter and the receiver, the delay or sensitivity of the
transmitter and the receiver. Secondly, we set up a test-bed for this vertical
channel model, in order to verify the difference between the theory result and
the experiment data. At last, we use the data we get from the experiment and
the non-linear least squares method to get the parameters to make our channel
model more accurate.Comment: 5 pages,7 figures, Accepted for presentation at BICT 2015 Special
Track on Molecular Communication and Networking (MCN). arXiv admin note: text
overlap with arXiv:1311.6208 by other author
Distributed Control of Microscopic Robots in Biomedical Applications
Current developments in molecular electronics, motors and chemical sensors
could enable constructing large numbers of devices able to sense, compute and
act in micron-scale environments. Such microscopic machines, of sizes
comparable to bacteria, could simultaneously monitor entire populations of
cells individually in vivo. This paper reviews plausible capabilities for
microscopic robots and the physical constraints due to operation in fluids at
low Reynolds number, diffusion-limited sensing and thermal noise from Brownian
motion. Simple distributed controls are then presented in the context of
prototypical biomedical tasks, which require control decisions on millisecond
time scales. The resulting behaviors illustrate trade-offs among speed,
accuracy and resource use. A specific example is monitoring for patterns of
chemicals in a flowing fluid released at chemically distinctive sites.
Information collected from a large number of such devices allows estimating
properties of cell-sized chemical sources in a macroscopic volume. The
microscopic devices moving with the fluid flow in small blood vessels can
detect chemicals released by tissues in response to localized injury or
infection. We find the devices can readily discriminate a single cell-sized
chemical source from the background chemical concentration, providing
high-resolution sensing in both time and space. By contrast, such a source
would be difficult to distinguish from background when diluted throughout the
blood volume as obtained with a blood sample
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