927 research outputs found
Machine-learning the phase diagram of a strongly-interacting Fermi gas
We determine the phase diagram of strongly correlated fermions in the
crossover from Bose-Einstein condensates of molecules (BEC) to Cooper pairs of
fermions (BCS) utilizing an artificial neural network. By applying advanced
image recognition techniques to the momentum distribution of the fermions, a
quantity which has been widely considered as featureless for providing
information about the condensed state, we measure the critical temperature and
show that it exhibits a maximum on the bosonic side of the crossover.
Additionally, we back-analyze the trained neural network and demonstrate that
it interprets physically relevant quantities
Globalising assessment: an ethnography of literacy assessment, camels and fast food in the Mongolian Gobi
What happens when standardised literacy assessments travel globally? The paper presents an ethnographic account of adult literacy assessment events in rural Mongolia. It examines the dynamics of literacy assessment in terms of the movement and re-contextualisation of test items as they travel globally and are received locally by Mongolian respondents. The analysis of literacy assessment events is informed by Goodwin’s ‘participation framework’ on language as embodied and situated interactive phenomena and by Actor Network Theory. Actor Network Theory (ANT) is applied to examine literacy assessment events as processes of translation shaped by an ‘assemblage’ of human and non-human actors (including the assessment texts)
Computing exponentially faster: Implementing a nondeterministic universal Turing machine using DNA
The theory of computer science is based around Universal Turing Machines
(UTMs): abstract machines able to execute all possible algorithms. Modern
digital computers are physical embodiments of UTMs. The nondeterministic
polynomial (NP) time complexity class of problems is the most significant in
computer science, and an efficient (i.e. polynomial P) way to solve such
problems would be of profound economic and social importance. By definition
nondeterministic UTMs (NUTMs) solve NP complete problems in P time. However,
NUTMs have previously been believed to be physically impossible to construct.
Thue string rewriting systems are computationally equivalent to UTMs, and are
naturally nondeterministic. Here we describe the physical design for a NUTM
that implements a universal Thue system. The design exploits the ability of DNA
to replicate to execute an exponential number of computational paths in P time.
Each Thue rewriting step is embodied in a DNA edit implemented using a novel
combination of polymerase chain reactions and site-directed mutagenesis. We
demonstrate that this design works using both computational modelling and in
vitro molecular biology experimentation. The current design has limitations,
such as restricted error-correction. However, it opens up the prospect of
engineering NUTM based computers able to outperform all standard computers on
important practical problems
Genome-wide assessment of the carriers involved in the cellular uptake of drugs: a model system in yeast.
BACKGROUND: The uptake of drugs into cells has traditionally been considered to be predominantly via passive diffusion through the bilayer portion of the cell membrane. The recent recognition that drug uptake is mostly carrier-mediated raises the question of which drugs use which carriers. RESULTS: To answer this, we have constructed a chemical genomics platform built upon the yeast gene deletion collection, using competition experiments in batch fermenters and robotic automation of cytotoxicity screens, including protection by 'natural' substrates. Using these, we tested 26 different drugs and identified the carriers required for 18 of the drugs to gain entry into yeast cells. CONCLUSIONS: As well as providing a useful platform technology, these results further substantiate the notion that the cellular uptake of pharmaceutical drugs normally occurs via carrier-mediated transport and indicates that establishing the identity and tissue distribution of such carriers should be a major consideration in the design of safe and effective drugs.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are
Large-scale sequestration of atmospheric carbon via plant roots in natural and agricultural ecosystems: why and how
The soil holds twice as much carbon as does the atmosphere, and most soil carbon is derived from recent photosynthesis that takes carbon into root structures and further into below-ground storage via exudates therefrom. Nonetheless, many natural and most agricultural crops have roots that extend only to about 1 m below ground. What determines the lifetime of below-ground C in various forms is not well understood, and understanding these processes is therefore key to optimising them for enhanced C sequestration. Most soils (and especially subsoils) are very far from being saturated with organic carbon, and calculations show that the amounts of C that might further be sequestered (http://dbkgroup.org/carbonsequestration/rootsystem.html) are actually very great. Breeding crops with desirable below-ground C sequestration traits, and exploiting attendant agronomic practices optimised for individual species in their relevant environments, are therefore important goals. These bring additional benefits related to improvements in soil structure and in the usage of other nutrients and water
Utopia documents: linking scholarly literature with research data
Motivation: In recent years, the gulf between the mass of accumulating-research data and the massive literature describing and analyzing those data has widened. The need for intelligent tools to bridge this gap, to rescue the knowledge being systematically isolated in literature and data silos, is now widely acknowledged
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