First-principles investigation of 180-degree domain walls in BaTiO_3

We present a first-principles study of 180-degree ferroelectric domain walls in tetragonal barium titanate. The theory is based on an effective Hamiltonian that has previously been determined from first-principles ultrasoft-pseudopotential calculations. Statistical properties are investigated using Monte Carlo simulations. We compute the domain-wall energy, free energy, and thickness, analyze the behavior of the ferroelectric order parameter in the interior of the domain wall, and study its spatial fluctuations. An abrupt reversal of the polarization is found, unlike the gradual rotation typical of the ferromagnetic case.Comment: Revtex (preprint style, 13 pages) + 3 postscript figures. A version in two-column article style with embedded figures is available at http://electron.rutgers.edu/~dhv/preprints/index.html#pad_wal

Optimal discrete stopping times for reliability growth tests

Often, the duration of a reliability growth development test is specified in advance and the decision to terminate or continue testing is conducted at discrete time intervals. These features are normally not captured by reliability growth models. This paper adapts a standard reliability growth model to determine the optimal time for which to plan to terminate testing. The underlying stochastic process is developed from an Order Statistic argument with Bayesian inference used to estimate the number of faults within the design and classical inference procedures used to assess the rate of fault detection. Inference procedures within this framework are explored where it is shown the Maximum Likelihood Estimators possess a small bias and converges to the Minimum Variance Unbiased Estimator after few tests for designs with moderate number of faults. It is shown that the Likelihood function can be bimodal when there is conflict between the observed rate of fault detection and the prior distribution describing the number of faults in the design. An illustrative example is provided

A hazard model of the probability of medical school dropout in the United Kingdom

From individual level longitudinal data for two entire cohorts of medical students in UK universities, we use multilevel models to analyse the probability that an individual student will drop out of medical school. We find that academic preparedness—both in terms of previous subjects studied and levels of attainment therein—is the major influence on withdrawal by medical students. Additionally, males and more mature students are more likely to withdraw than females or younger students respectively. We find evidence that the factors influencing the decision to transfer course differ from those affecting the decision to drop out for other reasons

Identification of a bone morphogenetic protein type 2 receptor neutralizing antibody

The bone morphogenetic protein (BMP) signaling pathway comprises the largest subdivision of the transforming growth factor (TGFβ) superfamily. BMP signaling plays essential roles in both embryonic development and postnatal tissue homeostasis. Dysregulated BMP signaling underlies human pathologies ranging from pulmonary arterial hypertension to heterotopic ossification. Thus, understanding the basic mechanisms and regulation of BMP signaling may yield translational opportunities. Unfortunately, limited tools are available to evaluate this pathway, and genetic approaches are frequently confounded by developmental requirements or ability of pathway components to compensate for one another. Specific inhibitors for type 2 receptors are poorly represented. Thus, we sought to identify and validate an antibody that neutralizes the ligand-binding function of BMP receptor type 2 (BMPR2) extracellular domain (ECD)

The effect of zinc on human taste perception

Zinc salts are added as a nutritional or functional ingredient in food and oral care products. The 1st experiment in this study investigated the taste and somatosensory effect of zinc salts (chloride, iodide, sulfate, bromide, acetate). The zinc salts had very little taste (bitter, salty, savory, sour, sweet), and the taste that was present was easily washed away with water rinses. The major oral quality of zinc was astringency, and the astringency lingered beyond expectoration. The 2nd experiment combined zinc salts with prototypical stimuli eliciting basic tastes. Zinc was a potent inhibitor of sweetness and bitterness (&gt;70% reduction in taste) but did not affect salt, savory, or sour taste.<br /

Trends in the Statistical Assessment of Reliability

Changes in technology have had and will continue to have a strong effect on changes in the area of statistical assessment of reliability data. These changes include higher levels of integration in electronics, improvements in measurement technology and the deployment of sensors and smart chips into more products, dramatically improved computing power and storage technology, and the development of new, powerful statistical methods for graphics, inference, and experimental design and reliability test planning. This paper traces some of the history of the development of statistical methods for reliability assessment and makes some predictions about the future

Thermal Diffusion and Quench Propagation in YBCO Pancake Coils Wound with ZnO-and Mylar Insulations

The thermal diffusion properties of several different kinds of YBCO insulations and the quench properties of pancake coils made using these insulations were studied. Insulations investigated include Nomex, Kapton, and Mylar, as well as insulations based on ZnO, Zn2GeO4, and ZnO-Cu. Initially, short stacks of YBCO conductors with interlayer insulation, epoxy, and a central heater strip were made and later measured for thermal conductivity in liquid nitrogen. Subsequently, three different pancake coils were made. The first two were smaller, each using one meter total of YBCO tape present as four turns around a G-10 former. One of these smaller coils used Mylar insulation co-wound with the YBCO tape, the other used YBCO tape onto which ZnO based insulation had been deposited. One larger coil was made which used 12 total meters of ZnO-insulated tape and had 45 turns. The results for all short sample and coil thermal conductivities were ~1-3 Wm-1K-1. Finally, quench propagation velocity measurements were performed on the coils (77 K, self field) by applying a DC current and then using a heater pulse to initiate a quench. Normal zone propagation velocity (NZP) values were obtained for the coils both in the radial direction and in the azimuthal direction. Radial NZP values (0.05-0.7 mm/s) were two orders of magnitude lower than axial values (~14-17 mm/s). Nevertheless, the quenches were generally seen to propagate radially within the coils, in the sense that any given layer in the coil is driven normal by the layer underneath it.Comment: 58 pages, 5 tables, 16 fig

Direct and Absolute Quantification of over 1800 Yeast Proteins via Selected Reaction Monitoring

Defining intracellular protein concentration is critical in molecular systems biology. Although strategies for determining relative protein changes are available, defining robust absolute values in copies per cell has proven significantly more challenging. Here we present a reference data set quantifying over 1800 Saccharomyces cerevisiae proteins by direct means using protein-specific stable-isotope labeled internal standards and selected reaction monitoring (SRM) mass spectrometry, far exceeding any previous study. This was achieved by careful design of over 100 QconCAT recombinant proteins as standards, defining 1167 proteins in terms of copies per cell and upper limits on a further 668, with robust CVs routinely less than 20%. The selected reaction monitoring-derived proteome is compared with existing quantitative data sets, highlighting the disparities between methodologies. Coupled with a quantification of the transcriptome by RNA-seq taken from the same cells, these data support revised estimates of several fundamental molecular parameters: a total protein count of ∼100 million molecules-per-cell, a median of ∼1000 proteins-per-transcript, and a linear model of protein translation explaining 70% of the variance in translation rate. This work contributes a “gold-standard” reference yeast proteome (including 532 values based on high quality, dual peptide quantification) that can be widely used in systems models and for other comparative studies. Reliable and accurate quantification of the proteins present in a cell or tissue remains a major challenge for post-genome scientists. Proteins are the primary functional molecules in biological systems and knowledge of their abundance and dynamics is an important prerequisite to a complete understanding of natural physiological processes, or dysfunction in disease. Accordingly, much effort has been spent in the development of reliable, accurate and sensitive techniques to quantify the cellular proteome, the complement of proteins expressed at a given time under defined conditions (1). Moreover, the ability to model a biological system and thus characterize it in kinetic terms, requires that protein concentrations be defined in absolute numbers (2, 3). Given the high demand for accurate quantitative proteome data sets, there has been a continual drive to develop methodology to accomplish this, typically using mass spectrometry (MS) as the analytical platform. Many recent studies have highlighted the capabilities of MS to provide good coverage of the proteome at high sensitivity often using yeast as a demonstrator system (4⇓⇓⇓⇓⇓–10), suggesting that quantitative proteomics has now “come of age” (1). However, given that MS is not inherently quantitative, most of the approaches produce relative quantitation and do not typically measure the absolute concentrations of individual molecular species by direct means. For the yeast proteome, epitope tagging studies using green fluorescent protein or tandem affinity purification tags provides an alternative to MS. Here, collections of modified strains are generated that incorporate a detectable, and therefore quantifiable, tag that supports immunoblotting or fluorescence techniques (11, 12). However, such strategies for copies per cell (cpc) quantification rely on genetic manipulation of the host organism and hence do not quantify endogenous, unmodified protein. Similarly, the tagging can alter protein levels - in some instances hindering protein expression completely (11). Even so, epitope tagging methods have been of value to the community, yielding high coverage quantitative data sets for the majority of the yeast proteome (11, 12). MS-based methods do not rely on such nonendogenous labels, and can reach genome-wide levels of coverage. Accurate estimation of absolute concentrations i.e. protein copy number per cell, also usually necessitates the use of (one or more) external or internal standards from which to derive absolute abundance (4). Examples include a comprehensive quantification of the Leptospira interrogans proteome that used a 19 protein subset quantified using selected reaction monitoring (SRM)1 to calibrate their label-free data (8, 13). It is worth noting that epitope tagging methods, although also absolute, rely on a very limited set of standards for the quantitative western blots and necessitate incorporation of a suitable immunogenic tag (11). Other recent, innovative approaches exploiting total ion signal and internal scaling to estimate protein cellular abundance (10, 14), avoid the use of internal standards, though they do rely on targeted proteomic data to validate their approach. The use of targeted SRM strategies to derive proteomic calibration standards highlights its advantages in comparison to label-free in terms of accuracy, precision, dynamic range and limit of detection and has gained currency for its reliability and sensitivity (3, 15⇓–17). Indeed, SRM is often referred to as the “gold standard proteomic quantification method,” being particularly well-suited when the proteins to be quantified are known, when appropriate surrogate peptides for protein quantification can be selected a priori, and matched with stable isotope-labeled (SIL) standards (18⇓–20). In combination with SIL peptide standards that can be generated through a variety of means (3, 15), SRM can be used to quantify low copy number proteins, reaching down to ∼50 cpc in yeast (5). However, although SRM methodology has been used extensively for S. cerevisiae protein quantification by us and others (19, 21, 22), it has not been used for large protein cohorts because of the requirement to generate the large numbers of attendant SIL peptide standards; the largest published data set is only for a few tens of proteins. It remains a challenge therefore to robustly quantify an entire eukaryotic proteome in absolute terms by direct means using targeted MS and this is the focus of our present study, the Census Of the Proteome of Yeast (CoPY). We present here direct and absolute quantification of nearly 2000 endogenous proteins from S. cerevisiae grown in steady state in a chemostat culture, using the SRM-based QconCAT approach. Although arguably not quantification of the entire proteome, this represents an accurate and rigorous collection of direct yeast protein quantifications, providing a gold-standard data set of endogenous protein levels for future reference and comparative studies. The highly reproducible SIL-SRM MS data, with robust CVs typically less than 20%, is compared with other extant data sets that were obtained via alternative analytical strategies. We also report a matched high quality transcriptome from the same cells using RNA-seq, which supports additional calculations including a refined estimate of the total protein content in yeast cells, and a simple linear model of translation explaining 70% of the variance between RNA and protein levels in yeast chemostat cultures. These analyses confirm the validity of our data and approach, which we believe represents a state-of-the-art absolute quantification compendium of a significant proportion of a model eukaryotic proteome

Carbon balance of a restored and cutover raised bog: implications for restoration and comparison to global trends

The net ecosystem exchange (NEE) and methane (CH4) flux were measured by chamber measurements for five distinct ecotypes (areas with unique eco-hydrological characteristics) at Abbeyleix Bog in the Irish midlands over a 2-year period. The ecotypes ranged from those with high-quality peat-forming vegetation to communities indicative of degraded, drained conditions. Three of these ecotypes were located in an area where peat was extracted by hand and then abandoned and left to revegetate naturally at least 50 years prior to the start of the study. Two of the ecotypes were located on an adjacent raised bog, which although never mined for peat, was impacted by shallow drainage and then restored (by drain blocking) 6 years prior to the start of the study. Other major aspects of the carbon (C) balance, including dissolved organic carbon (DOC), dissolved inorganic carbon (DIC), and open-water CO2 evasion, were quantified for a catchment area at the study site over the same 2-year period. The ecotype average annual ecotype C balance ranged from a net C sink of -58±60&thinsp;g&thinsp;C&thinsp;m−2&thinsp;yr−1, comparable to studies of intact peatlands, to a substantial C source of +205±80&thinsp;g&thinsp;C m−2&thinsp;yr−1, with NEE being the most variable component of the C balance among the five ecotypes. Ecotype annual CH4 flux ranged from 2.7±1.4&thinsp;g&thinsp;C-CH4&thinsp;m−2&thinsp;yr−1 to 14.2±4.8&thinsp;g&thinsp;C-CH4&thinsp;m−2&thinsp;yr−1. Average annual aquatic C losses were 14.4&thinsp;g&thinsp;C&thinsp;m−2&thinsp;yr−1 with DOC, DIC, and CO2 evasion of 10.4&thinsp;g&thinsp;C&thinsp;m−2&thinsp;yr−1, 1.3&thinsp;g&thinsp;C&thinsp;m−2&thinsp;yr−1, and 2.7&thinsp;g&thinsp;C&thinsp;m−2&thinsp;yr−1, respectively. A statistically significant negative correlation was found between the mean annual water table (MAWT) and the plot-scale NEE but not the global warming potential (GWP). However, a significant negative correlation was observed between the plot-scale percentage of Sphagnum moss cover and the GWP, highlighting the importance of regenerating this keystone genus as a climate change mitigation strategy in peatland restoration. The data from this study were then compared to the rapidly growing number of peatland C balance studies across boreal and temperate regions. The trend in NEE and CH4 flux with respect to MAWT was compared for the five ecotypes in this study and literature data from degraded/restored/recovering peatlands, intact peatlands, and bare peat sites.</p