Families of bianchi modular symbols: critical base-change p-adic L-functions and p-adic Artin formalism

Let $K$ be an imaginary quadratic field. In this article, we study the eigenvariety for $GL(2)/K$, proving an etaleness result for the weight map at non-critical classical points and a smoothness result at base-change classical points. We give three main applications of this. (1) We construct three-variable $p$-adic $L$-functions over the eigenvariety interpolating the (two-variable) $p$-adic $L$-functions of classical Bianchi cusp forms in families. (2) Let $f$ be a $p$-stabilised newform of weight $k$ at least 2 without CM by $K$. We construct a two-variable $p$-adic $L$-function attached to the base-change of $f$ to $K$ under assumptions on $f$ that we conjecture always hold, in particular making no assumption on the slope of $f$. (3) We prove that these base-change $p$-adic $L$-functions satisfy a $p$-adic Artin formalism result, that is, they factorise in the same way as the classical $L$-function under Artin formalism. In an appendix, Carl Wang-Erickson describes a base-change deformation functor and gives a characterisation of its Zariski tangent space

Applying a Bayesian Network methodology to an offshore gas turbine driven power generator to demonstrate the cause and effect relationship of the turbine running over-speed and the associated switchboard failures.

This paper investigates the benefits of applying a Bayesian Network in quantitative risk assessment of the integrity of an offshore gas turbine driven generator. The focus of the research is based on the potential failures and incidents associated with an offshore gas turbine running overspeed and failures within the switchboard. The potential consequences that follow said failures, such as fire, explosion and damage to mechanical equipment are also factored into the analysis. A methodology is outlined in order to construct a coherent BN model. This methodology consists of several steps, starting with identifying variables, to then constructing a qualitative BN model from these variables. The methodology culminates in validation of the BN model. A case study, regarding individual and combined component failures is also applied to demonstrate and validate the methodology. The Bayesian network allows the cause-effect relationships to be modelled through clear graphical representation. Similarly, the model can accommodate for continual updating of failure data. Partial validity of the model is demonstrated against some benchmark axioms. It is vital to maintain that the model must remain practical and close to reality from the perspective of gathering data and generating results

Compressibility of titanosilicate melts

The effect of composition on the relaxed adiabatic bulk modulus (K0) of a range of alkali- and alkaline earth-titanosilicate [X 2 n/n+ TiSiO5 (X=Li, Na, K, Rb, Cs, Ca, Sr, Ba)] melts has been investigated. The relaxed bulk moduli of these melts have been measured using ultrasonic interferometric methods at frequencies of 3, 5 and 7 MHz in the temperature range of 950 to 1600°C (0.02 Pa s < s < 5 Pa s). The bulk moduli of these melts decrease with increasing cation size from Li to Cs and Ca to Ba, and with increasing temperature. The bulk moduli of the Li-, Na-, Ca- and Ba-bearing metasilicate melts decrease with the addition of both TiO2 and SiO2 whereas those of the K-, Rb- and Cs-bearing melts increase. Linear fits to the bulk modulus versus volume fraction of TiO2 do not converge to a common compressibility of the TiO2 component, indicating that the structural role of TiO2 in these melts is dependent on the identity of the cation. This proposition is supported by a number of other property data for these and related melt compositions including heat capacity and density, as well as structural inferences from X-ray absorption spectroscopy (XANES). The compositional dependence of the compressibility of the TiO2 component in these melts explains the difficulty incurred in previous attempts to incorporate TiO2 in calculation schemes for melt compressibility. The empirical relationship KV-4/3 for isostructural materials has been used to evaluate the compressibility-related structural changes occurring in these melts. The alkali metasilicate and disilicate melts are isostructural, independent of the cation. The addition of Ti to the metasilicate composition (i.e. X2TiSiO5), however, results in a series of melts which are not isostructural. The alkaline-earth metasilicate and disilicate compositions are not isostructural, but the addition of Ti to the metasilicate compositions (i.e. XTiSiO5) would appear, on the basis of modulus-volume systematics, to result in the melts becoming isostructural with respect to compressibility

Heterogeneous formic acid production by hydrogenation of CO₂ catalyzed by Ir‐bpy embedded in polyphenylene porous organic polymers

Heterogeneous immobilized molecular catalysis has gained significant attention as a platform for creating more efficient and selective catalysts. A promising type of immobilized molecular catalysts are made from porous organic polymers (POPs) due to their high stability, porosity, and ability to mimic the catalytic activity and selectivity of homogeneous organometallic catalysts. These properties of the POP-based systems make them very attractive as heterogeneous catalysts for hydrogenation of CO2 to formate, where predominately homogeneous systems have been applied. In this study, five POPs were synthesized and assessed in the hydrogenation of CO2 where the active catalysts were made in-situ by mixing IrCl3 and the POPs. One of the Ir/POP catalysts provided a turn-over number (TON) >20,000, which is among the highest for POP-based systems. Thorough characterization (CO2- and N2-physisorption, TGA, CHN-analysis, XRD, XPS, SEM, STEM and TEM) was performed. Notably, the developed Ir/POP system also showed catalytic activity for the decomposition of formic acid into H2 enabling the use of formic acid as a renewable energy carrier

Optimizing genomic medicine in epilepsy through a gene-customized approach to missense variant interpretation

Gene panel and exome sequencing have revealed a high rate of molecular diagnoses among diseases where the genetic architecture has proven suitable for sequencing approaches, with a large number of distinct and highly penetrant causal variants identified among a growing list of disease genes. The challenge is, given the DNA sequence of a new patient, to distinguish disease-causing from benign variants. Large samples of human standing variation data highlight regional variation in the tolerance to missense variation within the protein-coding sequence of genes. This information is not well captured by existing bioinformatic tools, but is effective in improving variant interpretation. To address this limitation in existing tools, we introduce the missense tolerance ratio (MTR), which summarizes available human standing variation data within genes to encapsulate population level genetic variation. We find that patient-ascertained pathogenic variants preferentially cluster in low MTR regions (P < 0.005) of well-informed genes. By evaluating 20 publicly available predictive tools across genes linked to epilepsy, we also highlight the importance of understanding the empirical null distribution of existing prediction tools, as these vary across genes. Subsequently integrating the MTR with the empirically selected bioinformatic tools in a gene-specific approach demonstrates a clear improvement in the ability to predict pathogenic missense variants from background missense variation in disease genes. Among an independent test sample of case and control missense variants, case variants (0.83 median score) consistently achieve higher pathogenicity prediction probabilities than control variants (0.02 median score; Mann-Whitney U test, P < 1 × 10(-16)). We focus on the application to epilepsy genes; however, the framework is applicable to disease genes beyond epilepsy

Numerical investigations of heat transfer enhancement in a latent heat storage exchanger with paraffin/graphite foam

Paper presented to the 10th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, Florida, 14-16 July 2014.The discrepancy between energy supply and demand can be overcome by the implementation of a proper energy storage system. The latent heat thermal energy storage employing a PCM is the most effective way of the thermal energy storage due to its advantages of high energy storage density and its isothermal operating characteristics during solidification and melting processes. Here high conductivity porosity materialgraphite foam is proposed to enhance the phase change materials (PCM), paraffin, in order to solve the problem of its low conductivity in the latent heat storage exchanger (LHSE). The LHSE suggested is like shell-and-tube heat exchanger, which HTF (water) is flowing in the tube while paraffin/graphite foam is in the shell side. And two-dimensional numerical investigations are conducted to predict the heat transfer performance of the PCM/graphite foam for LHSE by CFD software. The results show that graphite foam can improve heat transfer rate effectively, and a series of numerical calculations have been done in order to analyze the influence of several HTF operating conditions on the melting process of the paraffin/ graphite foam in LHSE, which will provide guidelines of thermal performance and design optimization for LHSE.dc201

Shape-induced force fields in optical trapping

Advances in optical tweezers, coupled with the proliferation of two-photon polymerization systems, mean that it is now becoming routine to fabricate and trap non-spherical particles. The shaping of both light beams and particles allows fine control over the flow of momentum from the optical to mechanical regimes. However, understanding and predicting the behaviour of such systems is highly complex in comparison with the traditional optically trapped microsphere. In this Article, we present a conceptually new and simple approach based on the nature of the optical force density. We illustrate the method through the design and fabrication of a shaped particle capable of acting as a passive force clamp, and we demonstrate its use as an optically trapped probe for imaging surface topography. Further applications of the design rules highlighted here may lead to new sensors for probing biomolecule mechanics, as well as to the development of optically actuated micromachines

Learning curves and long-term outcome of simulation-based thoracentesis training for medical students

<p>Abstract</p> <p>Background</p> <p>Simulation-based medical education has been widely used in medical skills training; however, the effectiveness and long-term outcome of simulation-based training in thoracentesis requires further investigation. The purpose of this study was to assess the learning curve of simulation-based thoracentesis training, study skills retention and transfer of knowledge to a clinical setting following simulation-based education intervention in thoracentesis procedures.</p> <p>Methods</p> <p>Fifty-two medical students were enrolled in this study. Each participant performed five supervised trials on the simulator. Participant's performance was assessed by performance score (PS), procedure time (PT), and participant's confidence (PC). Learning curves for each variable were generated. Long-term outcome of the training was measured by the retesting and clinical performance evaluation 6 months and 1 year, respectively, after initial training on the simulator.</p> <p>Results</p> <p>Significant improvements in PS, PT, and PC were noted among the first 3 to 4 test trials (p < 0.05). A plateau for PS, PT, and PC in the learning curves occurred in trial 4. Retesting 6 months after training yielded similar scores to trial 5 (p > 0.05). Clinical competency in thoracentesis was improved in participants who received simulation training relative to that of first year medical residents without such experience (p < 0.05).</p> <p>Conclusions</p> <p>This study demonstrates that simulation-based thoracentesis training can significantly improve an individual's performance. The saturation of learning from the simulator can be achieved after four practice sessions. Simulation-based training can assist in long-term retention of skills and can be partially transferred to clinical practice.</p