Universality of Electron Mobility in LaAlO3_3/SrTiO3_3 and bulk SrTiO3_3

Metallic LaAlO$_3$/SrTiO$_3$ (LAO/STO) interfaces attract enormous attention, but the relationship between the electron mobility and the sheet electron density, $n_s$, is poorly understood. Here we derive a simple expression for the three-dimensional electron density near the interface, $n_{3D}$, as a function of $n_s$ and find that the mobility for LAO/STO-based interfaces depends on $n_{3D}$ in the same way as it does for bulk doped STO. It is known that undoped bulk STO is strongly compensated with $N \simeq 5 \times 10^{18}~\rm{cm^{-3}}$ background donors and acceptors. In intentionally doped bulk STO with a concentration of electrons $n_{3D} < N$ background impurities determine the electron scattering. Thus, when $n_{3D} < N$ it is natural to see in LAO/STO the same mobility as in the bulk. On the other hand, in the bulk samples with $n_{3D} > N$ the mobility collapses because scattering happens on $n_{3D}$ intentionally introduced donors. For LAO/STO the polar catastrophe which provides electrons is not supposed to provide equal number of random donors and thus the mobility should be larger. The fact that the mobility is still the same implies that for the LAO/STO the polar catastrophe model should be revisited.Comment: 4 pages and 1 figur

Numerical Evaluation of Subsurface Soil Water Evaporation Derived From Sensible Heat Balance

A recently introduced measurement approach allows in situ determination of subsurface soil water evaporation by means of heat-pulse probes (HPP). The latent heat component of subsurface evaporation is estimated from the residual of the sensible heat balance. This heat balance method requires measurement of vertical soil temperature and estimates of thermal properties for soil water evaporation determination. Our objective was to employ numerically simulated thermal and hydraulic processes using constant or diurnally cycled surface boundary conditions to evaluate and understand this technique. Three observation grid spacings, namely, 6 mm (tri-needle HPP), 3 mm (penta-needle HPP) and 1 mm, along with three soil textures (sand, silt, and silty clay) were used to test the heat balance method. The comparison of heat balance–based evaporation rate estimates with an independent soil profile water balance revealed substantial errors when thermal conductivity was averaged spatially across the evaporation front. Since the conduction component of heat flux is the dominant process at the evaporation front, the estimation of evaporation rate was significantly improved using depth-dependent instead of a space-averaged . A near-surface “undetectable zone” exists, where the heat balance calculation is irreconcilable, resulting in underestimation of total subsurface evaporation. The method performs better for medium- and coarse-textured soils than for fine-textured soils, where portions of the drying front may be maintained longer within the undetectable zone. Using smaller temperature sensor spacing near the soil surface minimized underestimation from the undetectable zone and improved accuracy of total subsurface evaporation rate estimates

Small Polarons in Transition Metal Oxides

The formation of polarons is a pervasive phenomenon in transition metal oxide compounds, with a strong impact on the physical properties and functionalities of the hosting materials. In its original formulation the polaron problem considers a single charge carrier in a polar crystal interacting with its surrounding lattice. Depending on the spatial extension of the polaron quasiparticle, originating from the coupling between the excess charge and the phonon field, one speaks of small or large polarons. This chapter discusses the modeling of small polarons in real materials, with a particular focus on the archetypal polaron material TiO2. After an introductory part, surveying the fundamental theoretical and experimental aspects of the physics of polarons, the chapter examines how to model small polarons using first principles schemes in order to predict, understand and interpret a variety of polaron properties in bulk phases and surfaces. Following the spirit of this handbook, different types of computational procedures and prescriptions are presented with specific instructions on the setup required to model polaron effects.Comment: 36 pages, 12 figure

Predictors of linkage to care following community-based HIV counseling and testing in rural Kenya

Despite innovations in HIV counseling and testing (HCT), important gaps remain in understanding linkage to care. We followed a cohort diagnosed with HIV through a community-based HCT campaign that trained persons living with HIV/AIDS (PLHA) as navigators. Individual, interpersonal, and institutional predictors of linkage were assessed using survival analysis of self-reported time to enrollment. Of 483 persons consenting to follow-up, 305 (63.2%) enrolled in HIV care within 3 months. Proportions linking to care were similar across sexes, barring a sub-sample of men aged 18–25 years who were highly unlikely to enroll. Men were more likely to enroll if they had disclosed to their spouse, and women if they had disclosed to family. Women who anticipated violence or relationship breakup were less likely to link to care. Enrolment rates were significantly higher among participants receiving a PLHA visit, suggesting that a navigator approach may improve linkage from community-based HCT campaigns.Vestergaard Frandse

A Novel Shortwave Infrared Proximal Sensing Approach to Quantify the Water Stability of Soil Aggregates

Soil structure and aggregate stability (AS) are critical soil properties affecting water infiltration, root growth, and resistance to soil and wind erosion. Changes in AS may be early indicators of soil degradation, pointing to low organic matter (OM) content, reduced biological activity, or poor nutrient cycling. Hence, efficient and reliable AS measurement techniques are essential for detection, management, and remediation of degraded soil resources. Here we quantify soil AS by developing a novel proximal sensing technique based on shortwave infrared (SWIR) reflectance measurements. The novel approach is similar to the well-documented high energy moisture characteristic (HEMC) method, which yields a stability ratio (SR) derived from comparison of hydraulic and structural characteristics of slowly- and rapidly-wetted soil samples near-saturation. We rapidly wetted aggregated soil samples (i.e., high energy input) and hypothesized that an AS index can be derived from SWIR surface reflectance spectra due to differences in post-wetting surface roughness that is intimately linked to AS. To test this hypothesis, surface reflectance spectra from a wide range of structured soil textures under both slowly- and rapidly-wetted samples, were measured with a SWIR spectroradiometer (350–2500 nm). The ratio between pre- and post-wetting spectra was determined and compared with the HEMC method’s volume of drainable pore ratio (VDPR). We found a strong correlation (R2 = 0.87) between the VDPR and the SWIR-derived reflectance index (RI) and also between the SR (R2 = 0.90) and the RI for all soils. These results point to the feasibility and appeal of quantifying AS using the newly proposed and more time-efficient proximal sensing method

Determinants of Protein Abundance and Translation Efficiency in S. cerevisiae

The translation efficiency of most Saccharomyces cerevisiae genes remains fairly constant across poor and rich growth media. This observation has led us to revisit the available data and to examine the potential utility of a protein abundance predictor in reinterpreting existing mRNA expression data. Our predictor is based on large-scale data of mRNA levels, the tRNA adaptation index, and the evolutionary rate. It attains a correlation of 0.76 with experimentally determined protein abundance levels on unseen data and successfully cross-predicts protein abundance levels in another yeast species (Schizosaccharomyces pombe). The predicted abundance levels of proteins in known S. cerevisiae complexes, and of interacting proteins, are significantly more coherent than their corresponding mRNA expression levels. Analysis of gene expression measurement experiments using the predicted protein abundance levels yields new insights that are not readily discernable when clustering the corresponding mRNA expression levels. Comparing protein abundance levels across poor and rich media, we find a general trend for homeostatic regulation where transcription and translation change in a reciprocal manner. This phenomenon is more prominent near origins of replications. Our analysis shows that in parallel to the adaptation occurring at the tRNA level via the codon bias, proteins do undergo a complementary adaptation at the amino acid level to further increase their abundance

Advancing NASA’s AirMOSS P-Band Radar Root Zone Soil Moisture Retrieval Algorithm via Incorporation of Richards’ Equation

P-band radar remote sensing applied during the Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) mission has shown great potential for estimation of root zone soil moisture. When retrieving the soil moisture profile (SMP) from P-band radar observations, a mathematical function describing the vertical moisture distribution is required. Because only a limited number of observations are available, the number of free parameters of the mathematical model must not exceed the number of observed data. For this reason, an empirical quadratic function (second order polynomial) is currently applied in the AirMOSS inversion algorithm to retrieve the SMP. The three free parameters of the polynomial are retrieved for each AirMOSS pixel using three backscatter observations (i.e., one frequency at three polarizations of Horizontal-Horizontal, Vertical-Vertical and Horizontal-Vertical). In this paper, a more realistic, physically-based SMP model containing three free parameters is derived, based on a solution to Richards’ equation for unsaturated flow in soils. Evaluation of the new SMP model based on both numerical simulations and measured data revealed that it exhibits greater flexibility for fitting measured and simulated SMPs than the currently applied polynomial. It is also demonstrated that the new SMP model can be reduced to a second order polynomial at the expense of fitting accuracy

Amino Acid Usage Is Asymmetrically Biased in AT- and GC-Rich Microbial Genomes.

INTRODUCTION: Genomic base composition ranges from less than 25% AT to more than 85% AT in prokaryotes. Since only a small fraction of prokaryotic genomes is not protein coding even a minor change in genomic base composition will induce profound protein changes. We examined how amino acid and codon frequencies were distributed in over 2000 microbial genomes and how these distributions were affected by base compositional changes. In addition, we wanted to know how genome-wide amino acid usage was biased in the different genomes and how changes to base composition and mutations affected this bias. To carry this out, we used a Generalized Additive Mixed-effects Model (GAMM) to explore non-linear associations and strong data dependences in closely related microbes; principal component analysis (PCA) was used to examine genomic amino acid- and codon frequencies, while the concept of relative entropy was used to analyze genomic mutation rates. RESULTS: We found that genomic amino acid frequencies carried a stronger phylogenetic signal than codon frequencies, but that this signal was weak compared to that of genomic %AT. Further, in contrast to codon usage bias (CUB), amino acid usage bias (AAUB) was differently distributed in AT- and GC-rich genomes in the sense that AT-rich genomes did not prefer specific amino acids over others to the same extent as GC-rich genomes. AAUB was also associated with relative entropy; genomes with low AAUB contained more random mutations as a consequence of relaxed purifying selection than genomes with higher AAUB. CONCLUSION: Genomic base composition has a substantial effect on both amino acid- and codon frequencies in bacterial genomes. While phylogeny influenced amino acid usage more in GC-rich genomes, AT-content was driving amino acid usage in AT-rich genomes. We found the GAMM model to be an excellent tool to analyze the genomic data used in this study

Multicentre comparison of a diagnostic assay: Aquaporin-4 antibodies in neuromyelitis optica

Objective Antibodies to cell surface central nervous system proteins help to diagnose conditions which often respond to immunotherapies. The assessment of antibody assays needs to reflect their clinical utility. We report the results of a multicentre study of aquaporin (AQP) 4 antibody (AQP4-Ab) assays in neuromyelitis optica spectrum disorders (NMOSD). Methods Coded samples from patients with neuromyelitis optica (NMO) or NMOSD (101) and controls (92) were tested at 15 European diagnostic centres using 21 assays including live (n=3) or fixed cell-based assays (n=10), flow cytometry (n=4), immunohistochemistry (n=3) and ELISA (n=1). Results Results of tests on 92 controls identified 12assays as highly specific (0-1 false-positive results). 32 samples from 50 (64%) NMO sera and 34 from 51 (67%) NMOSD sera were positive on at least two of the 12 highly specific assays, leaving 35 patients with seronegative NMO/spectrum disorder (SD). On the basis of a combination of clinical phenotype and the highly specific assays, 66 AQP4-Ab seropositive samples were used to establish the sensitivities (51.5-100%) of all 21 assays. The specificities (85.8-100%) were based on 92 control samples and 35 seronegative NMO/SD patient samples. Conclusions The cell-based assays were most sensitive and specific overall, but immunohistochemistry or flow cytometry could be equally accurate in specialist centres. Since patients with AQP4-Ab negative NMO/SD require different management, the use of both appropriate control samples and defined seronegative NMOSD samples is essential to evaluate these assays in a clinically meaningful way. The process described here can be applied to the evaluation of other antibody assays in the newly evolving field of autoimmune neurology