The benefit of high-conductivity materials in film cooled turbine nozzles

This study presents an experimental and numerical investigation of the beneficial effect of higher conductivity materials in HP turbine nozzles. Most of the literature studies focus on the maximum temperature that a nozzle can withstand, whereas the effect of thermal gradients is often neglected. However thermal gradients have higher influence on the life of the components and they have to be given careful consideration. In this work it is shown that thermal gradients are reduced by using high conductivity materials and, as a consequence, the nozzles life is appreciably increased. A representative film cooled leading edge with an internal impingement plate was studied experimentally at Texas AM University. Two materials were used, namely polycarbonate and stainless steel, in order to highlight the impact of conduction on coolant effectiveness. Numerically conjugate heat transfer simulations have been carried out with an in house solver to analyse in detail the impact of conduction and internal convection. Both experimental and numerical results show that by increasing the conductivity in the solid region, the thermal gradients are strongly reduced. Numerically it is shown that using inserts of nickel-aluminide alloys in nozzles may reduce the thermal gradients from 3 to 4 times if compared to nowadays design. © 2012 Elsevier Inc

Reduced mechanical efficiency in left-ventricular trabeculae of the spontaneously hypertensive rat.

Long-term systemic arterial hypertension, and its associated compensatory response of left-ventricular hypertrophy, is fatal. This disease leads to cardiac failure and culminates in death. The spontaneously hypertensive rat (SHR) is an excellent animal model for studying this pathology, suffering from ventricular failure beginning at about 18 months of age. In this study, we isolated left-ventricular trabeculae from SHR-F hearts and contrasted their mechanoenergetic performance with those from nonfailing SHR (SHR-NF) and normotensive Wistar rats. Our results show that, whereas the performance of the SHR-F differed little from that of the SHR-NF, both SHR groups performed less stress-length work than that of Wistar trabeculae. Their lower work output arose from reduced ability to produce sufficient force and shortening. Neither their heat production nor their enthalpy output (the sum of work and heat), particularly the energy cost of Ca(2+) cycling, differed from that of the Wistar controls. Consequently, mechanical efficiency (the ratio of work to change of enthalpy) of both SHR groups was lower than that of the Wistar trabeculae. Our data suggest that in hypertension-induced left-ventricular hypertrophy, the mechanical performance of the tissue is compromised such that myocardial efficiency is reduced

A Bayesian LSTM model to evaluate the effects of air pollution control regulations in Beijing, China

© 2020 Elsevier Ltd Rapid socio-economic development and urbanization have resulted in serious deterioration in air-quality in many world cities, including Beijing, China. This study attempts to examine the effectiveness of air pollution control regulations implemented in Beijing during 2008–2019 through a data-driven regulatory intervention analysis. Our proposed Bayesian deep learning model utilizes proxy data including Aerosol Optical Depth (AOD) and meteorology as well as socio-economic data, while accounting for confounding effects via propensity score estimation. Our results show that air pollution control regulatory measures implemented in China and Beijing during 2008–2019 reduced PM2.5 pollution in Beijing by 11 % on average. After the introduction of Action Plan for Clean Air in China and Beijing in late 2013, as compared to the hypothetical PM2.5 concentration (without any regulatory interventions), the estimated PM2.5 reduction increased dramatically from 15 % in 2015 to 44 % in 2018. Our results suggest that Beijing's air quality has improved gradually over the past decade, though the annual PM2.5 pollution still exceeds the WHO threshold. In this regard, the air pollution control regulations introduced in Beijing and China tend to become more effective after 2015, suggesting a 2-year time lag before the stringent air pollution control regulations starting from 2013 takes any strong positive effects. Moreover, as compared to the air pollution control regulations introduced before 2013, newly introduced policy-making governance, which couples the policy-makings of the local jurisdictions with that of the central government, and the new policy measures that tackle the vested interests of the local stakeholders in Beijing and its nearby cities, alongside with the stringent local and national air pollution control regulations and plans, should help reduce air pollution and promote healthy living in Beijing over the longer term.This research is supported in part by the General Research Fund of the Research Grants Council of Hong Kong, under Grant No. 17620920

The QCD sign problem and dynamical simulations of random matrices

At nonzero quark chemical potential dynamical lattice simulations of QCD are hindered by the sign problem caused by the complex fermion determinant. The severity of the sign problem can be assessed by the average phase of the fermion determinant. In an earlier paper we derived a formula for the microscopic limit of the average phase for general topology using chiral random matrix theory. In the current paper we present an alternative derivation of the same quantity, leading to a simpler expression which is also calculable for finite-sized matrices, away from the microscopic limit. We explicitly prove the equivalence of the old and new results in the microscopic limit. The results for finite-sized matrices illustrate the convergence towards the microscopic limit. We compare the analytical results with dynamical random matrix simulations, where various reweighting methods are used to circumvent the sign problem. We discuss the pros and cons of these reweighting methods.Comment: 34 pages, 3 figures, references added, as published in JHE

Determining appropriate approaches for using data in feature selection

Feature selection is increasingly important in data analysis and machine learning in big data era. However, how to use the data in feature selection, i.e. using either ALL or PART of a dataset, has become a serious and tricky issue. Whilst the conventional practice of using all the data in feature selection may lead to selection bias, using part of the data may, on the other hand, lead to underestimating the relevant features under some conditions. This paper investigates these two strategies systematically in terms of reliability and effectiveness, and then determines their suitability for datasets with different characteristics. The reliability is measured by the Average Tanimoto Index and the Inter-method Average Tanimoto Index, and the effectiveness is measured by the mean generalisation accuracy of classification. The computational experiments are carried out on ten real-world benchmark datasets and fourteen synthetic datasets. The synthetic datasets are generated with a pre-set number of relevant features and varied numbers of irrelevant features and instances, and added with different levels of noise. The results indicate that the PART approach is more effective in reducing the bias when the size of a dataset is small but starts to lose its advantage as the dataset size increases

Sol-gel based materials for biomedical applications

Sol-gel chemistry offers a flexible approach to obtaining a diverse range of materials. It allows differing chemistries to be achieved as well as offering the ability to produce a wide range of nano-/micro-structures. The paper commences with a generalized description of the various sol-gel methods available and how these chemistries control the bulk properties of the end products. Following this, a more detailed description of the biomedical areas where sol-gel materials have been explored and found to hold significant potential. One of the interesting fields that has been developed recently relates to hybrid materials that utilize sol-gel chemistry to achieve unusual composite properties. Another intriguing feature of sol-gels is the unusual morphologies that are achievable at the micro- and nano-scale. Subsequently the ability to control pore chemistry at a number of different length scales and geometries has proven to be a fruitful area of exploitation, that provides excellent bioactivity and attracts cellular responses as well as enables the entrapment of biologically active molecules and their controllable release for therapeutic action. The approaches of fine-tuning surface chemistry and the combination with other nanomaterials have also enabled targeting of specific cell and tissue types for drug delivery with imaging capacity

Canonical quantization of non-commutative holonomies in 2+1 loop quantum gravity

In this work we investigate the canonical quantization of 2+1 gravity with cosmological constant $\Lambda>0$ in the canonical framework of loop quantum gravity. The unconstrained phase space of gravity in 2+1 dimensions is coordinatized by an SU(2) connection $A$ and the canonically conjugate triad field $e$. A natural regularization of the constraints of 2+1 gravity can be defined in terms of the holonomies of $A+=A + \sqrt\Lambda e$. As a first step towards the quantization of these constraints we study the canonical quantization of the holonomy of the connection $A_{\lambda}=A+\lambda e$ on the kinematical Hilbert space of loop quantum gravity. The holonomy operator associated to a given path acts non trivially on spin network links that are transversal to the path (a crossing). We provide an explicit construction of the quantum holonomy operator. In particular, we exhibit a close relationship between the action of the quantum holonomy at a crossing and Kauffman's q-deformed crossing identity. The crucial difference is that (being an operator acting on the kinematical Hilbert space of LQG) the result is completely described in terms of standard SU(2) spin network states (in contrast to q-deformed spin networks in Kauffman's identity). We discuss the possible implications of our result.Comment: 19 pages, references added. Published versio

Pioglitazone Prevents Capillary Rarefaction in Streptozotocin-Diabetic Rats Independently of Glucose Control and Vascular Endothelial Growth Factor Expression

Background/Aims: Reduction of capillary network density occurs early in the development of metabolic syndrome and may be relevant for the precipitation of diabetes. Agonists of the peroxisome proliferator-activated receptor (PPAR)-gamma transcription factor are vasculoprotective, but their capacity for structural preservation of the microcirculation is unclear. Methods: Male Wistar rats were rendered diabetic by streptozotocin and treated with pioglitazone in chow for up to 12 weeks. Capillary density was determined in heart and skeletal muscle after platelet endothelial cell adhesion molecule-1 (PECAM-1) immunostaining. Hallmarks of apoptosis and angiogenesis were determined. Results: Capillary density deteriorated progressively in the presence of hyperglycemia (from 971/mm(2) to 475/mm(2) in quadriceps muscle during 13 weeks). Pioglitazone did not influence plasma glucose, left ventricular weight, or body weight but nearly doubled absolute and relative capillary densities compared to untreated controls (1.2 vs. 0.6 capillaries/myocyte in heart and 1.5 vs. 0.9 capillaries/myocyte in quadriceps muscle) after 13 weeks of diabetes. No antiapoptotic or angiogenic influence of pioglitazone was detected while a reduced expression of hypoxia-inducible factor-3 alpha and PPAR coactivator-1 alpha (PGC-1 alpha) mRNA as well as vascular endothelial growth factor (VEGF) protein possibly occurred as a consequence of improved vascularization. Conclusion: Pioglitazone preserves microvascular structure in diabetes independently of improvements in glycemic control and by a mechanism unrelated to VEGF-mediated angiogenesis. Copyright (C) 2012 S. Karger AG, Base

Shotgun Lipidomics Identifies a Paired Rule for the Presence of Isomeric Ether Phospholipid Molecular Species

Ether phospholipids are abundant membrane constituents present in electrically active tissues (e.g., heart and the brain) that play important roles in cellular function. Alterations of ether phospholipid molecular species contents are associated with a number of genetic disorders and human diseases.Herein, the power of shotgun lipidomics, in combination with high mass accuracy/high resolution mass spectrometry, was explored to identify a paired rule for the presence of isomeric ether phospholipid molecular species in cellular lipidomes. The rule predicts that if an ether phospholipid A'-B is present in a lipidome, its isomeric counterpart B'-A is also present (where the ' represents an ether linkage). The biochemical basis of this rule results from the fact that the enzymes which participate in either the sequential oxidation of aliphatic alcohols to fatty acids, or the reduction of long chain fatty acids to aliphatic alcohols (metabolic precursors of ether lipid synthesis), are not entirely selective with respect to acyl chain length or degree of unsaturation. Moreover, the enzymatic selectivity for the incorporation of different aliphatic chains into the obligatory precursor of ether lipids (i.e., 1-O-alkyl-glycero-3-phosphate) is also limited.This intrinsic amplification of the number of lipid molecular species present in biological membranes predicted by this rule and demonstrated in this study greatly expands the number of ether lipid molecular species present in cellular lipidomes. Application of this rule to mass spectrometric analyses provides predictive clues to the presence of specific molecular species and greatly expands the number of identifiable and quantifiable ether lipid species present in biological samples. Through appropriate alterations in the database, use of the paired rule increases the number of identifiable metabolites in metabolic networks, thereby facilitating identification of biomarkers presaging disease states