Tunneling-induced restoration of classical degeneracy in quantum kagome ice

Quantum effect is expected to dictate the behavior of physical systems at low temperature. For quantum magnets with geometrical frustration, quantum fluctuation usually lifts the macroscopic classical degeneracy, and exotic quantum states emerge. However, how different types of quantum processes entangle wave functions in a constrained Hilbert space is not well understood. Here, we study the topological entanglement entropy and the thermal entropy of a quantum ice model on a geometrically frustrated kagome lattice. We find that the system does not show a Z(2) topological order down to extremely low temperature, yet continues to behave like a classical kagome ice with finite residual entropy. Our theoretical analysis indicates an intricate competition of off-diagonal and diagonal quantum processes leading to the quasidegeneracy of states and effectively, the classical degeneracy is restored

Simulating typhoon-induced storm hydrographs in subtropical mountainous watershed: an integrated 3-layer TOPMODEL

International audienceA three-layer TOPMODEL is here constructed by integrating three components, diffusion wave approach into surface flow, soil moisture deficit into interflow and exponential recession curve function into base flow. Sensitivity analysis reveals that D (soil depth), K (hydraulic conductivity), and mi (soil moisture decay) predominate simulated hydrograph shape and total discharge, yet, there are distinct effects on the three flows. A subtropical mountainous watershed, Heng-Chi and eighteen typhoon-induced storms with various rainfall type and wide-ranged total rainfall (81 to 1026 mm) were applied. The global best-fitted combination gives an average efficient coefficient of 75.1% and 76.0% for calibration (14 cases) and validation (4 cases), respectively. Most discharges of validation events fall within the 90% confidence interval derived from calibration events. Those results demonstrate the capability of the 3-layer TOPMODEL in subtropical watershed. Meanwhile, the upper confidence limit is suggested preferably when considering the flood assessment

Influence of Specific Contributing Area algorithms on slope failure prediction in landslide modeling

International audienceThis study anatomized algorithm effects of specific contributing area (SCA) on soil wetness estimation, consequently landslide prediction, in SHALSTAB. A subtropical mountainous catchment during three typhoon invasions is targeted. The peak 2-day rainfall intensity of the three typhoons: Haitang, Mindulle and Herb are 144, 248 and 327 mm/day, respectively. We use modified success rate (MSR) to retrieve the most satisfying mean condition for model parameters in SHALSTAB at three rainfall intensities and respective pre-typhoon NDVI themes. Simulation indicates that algorithm affects the prediction of landslide susceptibility (i.e. FS, Factor of Safety) significantly. Based on fixed NDVI and the mean condition, we simulate by using full scale rainfall intensity from 0 to 1200 mm/day. Simulations show that predicted unstable area coverage increases non-linearly as rainfall intensity increases for all algorithms yet with different increasing trends. Compared to Dinf, D8 always gives lower coverage of predicted unstable area during three typhoons. By contrast, FD8 gives higher coverage areas. The absolute difference (compared to Dinf) in predicted unstable area ranges from ~?3% to +4% (percent watershed area). The relative difference (compared to Dinf) ranges from ?15% to as high as +40%. The maximum absolute and relative differences in unstable area prediction occur around the condition of 100?300 mm/day, which is common in subtropical mountainous region. Theoretical relationship among slope, rainfall intensity, SCA and FS value was derived in which FS values are very sensitive to algorithms in the field of slope from 37 to 52degree. Results imply any comparison among SCA-related landslide models or engineering application of rainfall return period analysis must base on the same algorithm to obtain comparable results. This study clarifies the SCA algorithm effect on FS prediction and deepens our understanding on landslide modeling

Transcription Factor Phox2 Upregulates Expression of Norepinephrine Transporter and Dopamine β-Hydroxylase in Adult Rat Brains

Degeneration of the noradrenergic locus coeruleus (LC) in aging and neurodegenerative diseases is well documented. Slowing or reversing this effect may have therapeutic implications. Phox2a and Phox2b are homeodomain transcriptional factors that function as determinants of the noradrenergic phenotype during embryogenesis. In the present study, recombinant lentiviral eGFP-Phox2a and -Phox2b (vPhox2a and vPhox2b) were constructed to study the effects of Phox2a/2b over-expression on dopamine β-hydroxylase (DBH) and norepinephrine transporter (NET) levels in central noradrenergic neurons. Microinjection of vPhox2 into the LC of adult rats significantly increased Phox2 mRNA levels in the LC region. Over-expression of either Phox2a or Phox2b in the LC was paralleled by significant increases in mRNA and protein levels of DBH and NET in the LC. Similar increases in DBH and NET protein levels were observed in the hippocampus following vPhox2 microinjection. In the frontal cortex, only NET protein levels were significantly increased by vPhox2 microinjection. Over-expression of Phox2 genes resulted in a significant increase in BrdU-positive cells in the hippocampal dentate gyrus. The present study demonstrates an upregulatory effect of Phox2a and Phox2b on the expression of DBH and NET in noradrenergic neurons of rat brains, an effect not previously shown in adult animals. Phox2 genes may play an important role in maintaining the function of the noradrenergic neurons after birth, and regulation of Phox2 gene expression may have therapeutic utility in aging or disorders involving degeneration of noradrenergic neurons

Thermodynamic restrictions on evolutionary optimization of transcription factor proteins

Conformational fluctuations are believed to play an important role in the process by which transcription factor proteins locate and bind their target site on the genome of a bacterium. Using a simple model, we show that the binding time can be minimized, under selective pressure, by adjusting the spectrum of conformational states so that the fraction of time spent in more mobile conformations is matched with the target recognition rate. The associated optimal binding time is then within an order of magnitude of the limiting binding time imposed by thermodynamics, corresponding to an idealized protein with instant target recognition. Numerical estimates suggest that typical bacteria operate in this regime of optimized conformational fluctuations

A DNA vaccine targeting TcdA and TcdB induces protective immunity against Clostridium difficile

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