185 research outputs found
Self-Organization in Multimode Microwave Phonon Laser (Phaser): Experimental Observation of Spin-Phonon Cooperative Motions
An unusual nonlinear resonance was experimentally observed in a ruby phonon
laser (phaser) operating at 9 GHz with an electromagnetic pumping at 23 GHz.
The resonance is manifested by very slow cooperative self-detunings in the
microwave spectra of stimulated phonon emission when pumping is modulated at a
superlow frequency (less than 10 Hz). During the self-detuning cycle new and
new narrow phonon modes are sequentially ``fired'' on one side of the spectrum
and approximately the same number of modes are ``extinguished'' on the other
side, up to a complete generation breakdown in a certain final portion of the
frequency axis. This is usually followed by a short-time refractority, after
which the generation is fired again in the opposite (starting) portion of the
frequency axis. The entire process of such cooperative spectral motions is
repeated with high degree of regularity. The self-detuning period strongly
depends on difference between the modulation frequency and the resonance
frequency. This period is incommensurable with period of modulation. It
increases to very large values (more than 100 s) when pointed difference is
less than 0.05 Hz. The revealed phenomenon is a kind of global spin-phonon
self- organization. All microwave modes of phonon laser oscillate with the same
period, but with different, strongly determined phase shifts - as in optical
lasers with antiphase motions.Comment: LaTeX2e file (REVTeX4), 5 pages, 5 Postscript figures. Extended and
revised version of journal publication. More convenient terminology is used.
Many new bibliographic references are added, including main early theoretical
and experimental papers on microwave phonon lasers (in English and in
Russian
Mesoscopic description of the annealed Ising model and Multiplicative noise
A new type of Langevin equation exhibiting a non trivial phase transition
associated with the presence of multiplicative noise is introduced. The
equation is derived as a mesoscopic representation of the microscopic annealed
Ising model (AIM) proposed by Thorpe and Beeman, and reproduces perfectly its
basic phenomenology. The AIM exhibits a non-trivial behavior as the temperature
is increased, in particular it presents a disorder-to-order phase transition at
low temperatures, and a order-to-disorder transition at higher temperatures.
This behavior resembles that of some Langevin equations with multiplicative
noise, which exhibit also two analogous phase transitions as the
noise-amplitude is increased. By comparing the standard models for
noise-induced transitions with our new Langevin equation we elucidate that the
mechanisms controlling the disorder-to-order transitions in both of them are
essentially different, even though for both of them the presence of
multiplicative noise is a key ingredient.Comment: Submitted to Phys. Rev.
A comparison of the hypoglycemic effect of insulin with systemic venous and portal venous administration
The hyperglycemic effect of insulin by prolonged intraportal and systemic infusion was measured in unanesthetized dogs with a modified portacaval transposition. There was no significant difference in response with the two routes of administration. The relation of these results to research directed to surgical therapy of diabetes is discussed. © 1963 W. B. Saunders Company
Recent results on multiplicative noise
Recent developments in the analysis of Langevin equations with multiplicative
noise (MN) are reported. In particular, we:
(i) present numerical simulations in three dimensions showing that the MN
equation exhibits, like the Kardar-Parisi-Zhang (KPZ) equation both a weak
coupling fixed point and a strong coupling phase, supporting the proposed
relation between MN and KPZ;
(ii) present dimensional, and mean field analysis of the MN equation to
compute critical exponents;
(iii) show that the phenomenon of the noise induced ordering transition
associated with the MN equation appears only in the Stratonovich representation
and not in the Ito one, and
(iv) report the presence of a new first-order like phase transition at zero
spatial coupling, supporting the fact that this is the minimum model for noise
induced ordering transitions.Comment: Some improvements respect to the first versio
Infant Brain Atlases from Neonates to 1- and 2-Year-Olds
Background: Studies for infants are usually hindered by the insufficient image contrast, especially for neonates. Prior knowledge, in the form of atlas, can provide additional guidance for the data processing such as spatial normalization, label propagation, and tissue segmentation. Although it is highly desired, there is currently no such infant atlas which caters for all these applications. The reason may be largely due to the dramatic early brain development, image processing difficulties, and the need of a large sample size. Methodology: To this end, after several years of subject recruitment and data acquisition, we have collected a unique longitudinal dataset, involving 95 normal infants (56 males and 39 females) with MRI scanned at 3 ages, i.e., neonate, 1-yearold, and 2-year-old. State-of-the-art MR image segmentation and registration techniques were employed, to construct which include the templates (grayscale average images), tissue probability maps (TPMs), and brain parcellation maps (i.e., meaningful anatomical regions of interest) for each age group. In addition, the longitudinal correspondences between agespecific atlases were also obtained. Experiments of typical infant applications validated that the proposed atlas outperformed other atlases and is hence very useful for infant-related studies. Conclusions: We expect that the proposed infant 0–1–2 brain atlases would be significantly conducive to structural and functional studies of the infant brains. These atlases are publicly available in our website
Comprehensive Brain MRI Segmentation in High Risk Preterm Newborns
Most extremely preterm newborns exhibit cerebral atrophy/growth disturbances and white matter signal abnormalities on MRI at term-equivalent age. MRI brain volumes could serve as biomarkers for evaluating the effects of neonatal intensive care and predicting neurodevelopmental outcomes. This requires detailed, accurate, and reliable brain MRI segmentation methods. We describe our efforts to develop such methods in high risk newborns using a combination of manual and automated segmentation tools. After intensive efforts to accurately define structural boundaries, two trained raters independently performed manual segmentation of nine subcortical structures using axial T2-weighted MRI scans from 20 randomly selected extremely preterm infants. All scans were re-segmented by both raters to assess reliability. High intra-rater reliability was achieved, as assessed by repeatability and intra-class correlation coefficients (ICC range: 0.97 to 0.99) for all manually segmented regions. Inter-rater reliability was slightly lower (ICC range: 0.93 to 0.99). A semi-automated segmentation approach was developed that combined the parametric strengths of the Hidden Markov Random Field Expectation Maximization algorithm with non-parametric Parzen window classifier resulting in accurate white matter, gray matter, and CSF segmentation. Final manual correction of misclassification errors improved accuracy (similarity index range: 0.87 to 0.89) and facilitated objective quantification of white matter signal abnormalities. The semi-automated and manual methods were seamlessly integrated to generate full brain segmentation within two hours. This comprehensive approach can facilitate the evaluation of large cohorts to rigorously evaluate the utility of regional brain volumes as biomarkers of neonatal care and surrogate endpoints for neurodevelopmental outcomes
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The genetic basis of a social polymorphism in halictid bees
The emergence of eusociality represents a major evolutionary transition from solitary to group reproduction. The most commonly studied eusocial species, honey bees and ants, represent the behavioral extremes of social evolution but lack close relatives that are non-social. Unlike these species, the halictid bee Lasioglossum albipes produces both solitary and eusocial nests and this intraspecific variation has a genetic basis. Here, we identify genetic variants associated with this polymorphism, including one located in the intron of syntaxin 1a (syx1a), a gene that mediates synaptic vesicle release. We show that this variant can alter gene expression in a pattern consistent with differences between social and solitary bees. Surprisingly, syx1a and several other genes associated with sociality in L. albipes have also been implicated in autism spectrum disorder in humans. Thus, genes underlying behavioral variation in L. albipes may also shape social behaviors across a wide range of taxa, including humans
Price shocks in regional markets: Japan's great Kantō Earthquake of 1923
Japan’s Great Kantō Earthquake of September 1st 1923 devastated the area around Tokyo and the country’s main port of Yokohama. This paper uses the earthquake as a case study to inform our understanding of the economics of disasters and the history of market integration. It seeks to test two main assumptions: firstly, that shifting demand and supply curves consequent on a disaster will have some impact on prices; and secondly, that any local changes in the disaster region are likely to be diffused across a wider geographical area. We make use of a unique monthly wholesale price dataset for a number of cities across Japan, and our analysis suggests three main findings: that price changes in the affected areas immediately following the disaster were in most cases reflected in price changes in Japan’s provincial cities; that cities further away from the devastation witnessed smaller price changes than those nearer to the affected area; and that the observed pattern of price changes reflects the regional heterogeneity identified by scholars who have worked on market integration in Japan
Deconstruction of rheumatoid arthritis synovium defines inflammatory subtypes
Rheumatoid arthritis is a prototypical autoimmune disease that causes joint inflammation and destruction1. There is currently no cure for rheumatoid arthritis, and the effectiveness of treatments varies across patients, suggesting an undefined pathogenic diversity1,2. Here, to deconstruct the cell states and pathways that characterize this pathogenic heterogeneity, we profiled the full spectrum of cells in inflamed synovium from patients with rheumatoid arthritis. We used multi-modal single-cell RNA-sequencing and surface protein data coupled with histology of synovial tissue from 79 donors to build single-cell atlas of rheumatoid arthritis synovial tissue that includes more than 314,000 cells. We stratified tissues into six groups, referred to as cell-type abundance phenotypes (CTAPs), each characterized by selectively enriched cell states. These CTAPs demonstrate the diversity of synovial inflammation in rheumatoid arthritis, ranging from samples enriched for T and B cells to those largely lacking lymphocytes. Disease-relevant cell states, cytokines, risk genes, histology and serology metrics are associated with particular CTAPs. CTAPs are dynamic and can predict treatment response, highlighting the clinical utility of classifying rheumatoid arthritis synovial phenotypes. This comprehensive atlas and molecular, tissue-based stratification of rheumatoid arthritis synovial tissue reveal new insights into rheumatoid arthritis pathology and heterogeneity that could inform novel targeted treatments
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