239 research outputs found
Giant microwave photoresistance of two-dimensional electron gas
We measure microwave frequency (4-40 GHz) photoresistance at low magnetic
field B, in high mobility 2D electron gas samples, excited by signals applied
to a transmission line fabricated on the sample surface. Oscillatory
photoresistance vs B is observed. For excitation at the cyclotron resonance
frequency, we find an unprecedented, giant relative photoresistance (\Delta
R)/R of up to 250 percent. The photoresistance is apparently proportional to
the square root of applied power, and disappears as the temperature is
increased.Comment: 4 pages, 3 figure
High Magnetic Field Microwave Conductivity of 2D Electrons in an Array of Antidots
We measure the high magnetic field () microwave conductivity,
Re, of a high mobility 2D electron system containing an antidot
array. Re vs frequency () increases strongly in the regime of
the fractional quantum Hall effect series, with Landau filling .
At microwave , Re vs exhibits a broad peak centered around
. On the peak, the 10 GHz Re can exceed its dc-limit
value by a factor of 5. This enhanced microwave conductivity is unobservable
for temperature K, and grows more pronounced as is
decreased. The effect may be due to excitations supported by the antidot edges,
but different from the well-known edge magnetoplasmons.Comment: 4 pages, 3 figures, revtex
Molecular and morphometric variation in European populations of the articulate brachiopod <i>Terebeatulina retusa</i>
Molecular and morphometric variation within and between population samples of the articulate brachiopod <i>Terebratulina</i> spp., collected in 1985-1987 from a Norwegian fjord, sea lochs and costal sites in western Scotland, the southern English Channel (Brittany) and the western Mediterranean, were measured by the analysis of variation in the lengths of mitochondrial DNA (mtDNA) fragments produced by digestion with nine restriction endonucleases and by multivariate statistical analysis of six selected morphometric parameters. Nucleotide difference within each population sample was high. Nucleotide difference between population samples from the Scottish sites, both those that are tidally contiguous and those that appear to be geographically isolated, were not significantly different from zero. Nucleotide differences between the populations samples from Norway, Brittany, Scotland and the western Mediterranean were also very low. Morphometric analysis confirmed the absence of substantial differentiation
Widespread sex differences in gene expression and splicing in the adult human brain
There is strong evidence to show that men and women differ in terms of neurodevelopment, neurochemistry and susceptibility to neurodegenerative and neuropsychiatric disease. The molecular basis of these differences remains unclear. Progress in this field has been hampered by the lack of genome-wide information on sex differences in gene expression and in particular splicing in the human brain. Here we address this issue by using post-mortem adult human brain and spinal cord samples originating from 137 neuropathologically confirmed control individuals to study whole-genome gene expression and splicing in 12 CNS regions. We show that sex differences in gene expression and splicing are widespread in adult human brain, being detectable in all major brain regions and involving 2.5% of all expressed genes. We give examples of genes where sex-biased expression is both disease-relevant and likely to have functional consequences, and provide evidence suggesting that sex biases in expression may reflect sex-biased gene regulatory structures
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Photonic encryption using all optical logic.
With the build-out of large transport networks utilizing optical technologies, more and more capacity is being made available. Innovations in Dense Wave Division Multiplexing (DWDM) and the elimination of optical-electrical-optical conversions have brought on advances in communication speeds as we move into 10 Gigabit Ethernet and above. Of course, there is a need to encrypt data on these optical links as the data traverses public and private network backbones. Unfortunately, as the communications infrastructure becomes increasingly optical, advances in encryption (done electronically) have failed to keep up. This project examines the use of optical logic for implementing encryption in the photonic domain to achieve the requisite encryption rates. In order to realize photonic encryption designs, technology developed for electrical logic circuits must be translated to the photonic regime. This paper examines two classes of all optical logic (SEED, gain competition) and how each discrete logic element can be interconnected and cascaded to form an optical circuit. Because there is no known software that can model these devices at a circuit level, the functionality of the SEED and gain competition devices in an optical circuit were modeled in PSpice. PSpice allows modeling of the macro characteristics of the devices in context of a logic element as opposed to device level computational modeling. By representing light intensity as voltage, 'black box' models are generated that accurately represent the intensity response and logic levels in both technologies. By modeling the behavior at the systems level, one can incorporate systems design tools and a simulation environment to aid in the overall functional design. Each black box model of the SEED or gain competition device takes certain parameters (reflectance, intensity, input response), and models the optical ripple and time delay characteristics. These 'black box' models are interconnected and cascaded in an encrypting/scrambling algorithm based on a study of candidate encryption algorithms. We found that a low gate count, cascadable encryption algorithm is most feasible given device and processing constraints. The modeling and simulation of optical designs using these components is proceeding in parallel with efforts to perfect the physical devices and their interconnect. We have applied these techniques to the development of a 'toy' algorithm that may pave the way for more robust optical algorithms. These design/modeling/simulation techniques are now ready to be applied to larger optical designs in advance of our ability to implement such systems in hardware
Protein Expression in the Nucleus Accumbens of Rats Exposed to Developmental Vitamin D Deficiency
Introduction: Developmental vitamin D (DVD) deficiency is a candidate risk factor for schizophrenia. Animal models have confirmed that DVD deficiency is associated with a range of altered genomic, proteomic, structural and behavioural outcomes in the rat. Because the nucleus accumbens has been implicated in neuropsychiatric disorders, in the current study we examined protein expression in this region in adult rats exposed to DVD deficienc
Predicting RNA secondary structure by the comparative approach: how to select the homologous sequences
<p>Abstract</p> <p>Background</p> <p>The secondary structure of an RNA must be known before the relationship between its structure and function can be determined. One way to predict the secondary structure of an RNA is to identify covarying residues that maintain the pairings (Watson-Crick, Wobble and non-canonical pairings). This "comparative approach" consists of identifying mutations from homologous sequence alignments. The sequences must covary enough for compensatory mutations to be revealed, but comparison is difficult if they are too different. Thus the choice of homologous sequences is critical. While many possible combinations of homologous sequences may be used for prediction, only a few will give good structure predictions. This can be due to poor quality alignment in stems or to the variability of certain sequences. This problem of sequence selection is currently unsolved.</p> <p>Results</p> <p>This paper describes an algorithm, <it>SSCA</it>, which measures the suitability of sequences for the comparative approach. It is based on evolutionary models with structure constraints, particularly those on sequence variations and stem alignment. We propose three models, based on different constraints on sequence alignments. We show the results of the <it>SSCA </it>algorithm for predicting the secondary structure of several RNAs. <it>SSCA </it>enabled us to choose sets of homologous sequences that gave better predictions than arbitrarily chosen sets of homologous sequences.</p> <p>Conclusion</p> <p><it>SSCA </it>is an algorithm for selecting combinations of RNA homologous sequences suitable for secondary structure predictions with the comparative approach.</p
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