The bluff body stabilized premixed flame in an acoustically resonating tube: combustion CFD and measured pressure field

The resulting limit cycle amplitude and frequency spectrum of a flame placed in a combustor of rectangular cross section is investigated. The partially premixed flame is stabilized on a bluff body placed in the upstream half of the combustor. The bluff body is an equilateral triangular wedge with one of the edges pointing in upstream direction. Acoustically there is an open downstream end and theer are variable acoustic conditions at the upstream end.\ud In order to assess the properties of the flame in this combustor, steady state flame simulations have been performed of the flame in the enclosure. These provided the fields of the mixing of gases, temperature and the velocity.\ud A test rig was manufactured for this burner at the University of Twente. In a first set of experiments, gas temperature, pressure field and flame chemiluminescence in the combustor were measured as a function of power and acoustic inlet condition. It was observed that the combustor exhibited strong natural pressure oscillations. The measured pressure, temperature and chemiluminescence data are compared to the CFD simulations and to numerical calculations of the acoustics presented in a companion paper by M.Heckl

Subsonic wind tunnel investigation of a twin-engine attack airplane model having nonmetric powered nacelles

A 1/10-scale powered model of a twin-engine attack airplane was investigated in the Langley high-speed 7- by 10-foot tunnel. The study was made at several Mach numbers between 0.225 and 0.75 which correspond to Reynolds numbers, based on the mean aerodynamic chord, of 1.35 million and 3.34 million. Unheated compressed air was used for jet simulation in the nonmetric engine nacelles which were located ahead of and above the horizontal stabilizer

Rough Set Applied to Air Pollution: A New Approach to Manage Pollutions in High Risk Rate Industrial Areas

This study presents a rough set application, using together the ideas of classical rough set approach, based on the indiscernibility relation and the dominance-based rough set approach (DRSA), to air micro-pollution management in an industrial site with a high environmental risk rate, such as the industrial area of Syracuse, located in the South of Italy (Sicily). This new data analysis tool has been applied to different decision problems in various fields with considerable success, since it is able to deal both with quantitative and with qualitative data and the results are expressed in terms of decision rules understandable by the decision-maker. In this chapter, some issue related to multi-attribute sorting (i.e. preference-ordered classification) of air pollution risk is presented, considering some meteorological variables, both qualitative and quantitative as attributes, and criteria describing the different objects (pollution occurrences) to be classified, that is, different levels of sulfur oxides (SOx), nitrogen oxides (NOx), and methane (CH4) as pollution indicators. The most significant results obtained from this particular application are presented and discussed: examples of ‘if, … then’ decision rules, attribute relevance as output of the data analysis also in terms of exchangeable or indispensable attributes/criteria, of qualitative substitution effect and interaction between them

Design, Synthesis and Study of Novel Nucleobase Analogs

This thesis focused on nucleobase modified peptide nucleic acid (PNA) and DNA to expand the repertoire of available nucleobase analogs used in the study of nucleic acids. More specifically, we are interested in modification of the nucleobases such that they retain their ability to undergo Watson-Crick base pairing. Moreover, our goal is to modify the nucleobases in order to engender them with useful photophysical properties such that they may be used as biomolecular tools to investigate nucleic acid structure and dynamics. To that end, a derivative of 5-aminouracil (5-AU) labelled with the amine-reactive chromophore 9-chloroacridine was prepared for the purpose of investigating its potential as a base-discriminating fluorophore. This modified nucleobase was incorporated into PNA by fluorenylmethyloxycarbonyl (Fmoc)-based oligomerization chemistry. During study of its hybridization to complementary DNA (cDNA), the 5-substitution was found to be thermally labile and hydrolyzed to a small degree in neutral aqueous solution, thus liberating the highly fluorescent acridone moiety. Moreover, three novel fluorescent 7-deaza-2´-deoxyadenosine analogs were successfully synthesized via the Sonogashira cross-coupling reaction of 7-iodo-7-deaza-2´-deoxyadenosine with 1-ethynylpyrene, 2-ethynyl-6-methoxynaphthalene, and 9-ethynylphenanthrene. These analogs were photophysically characterized in dioxane, EtOH, and H2O to evaluate their potential for use as environmentally sensitive fluorescent probes. All three analogs displayed high solvatofluorochromicity in H2O, relative to their emission wavelengths in dioxane and EtOH. Moreover, all three analogs exhibited moderate to high fluorescence quantum yields in dioxane and EtOH, and significantly lower fluorescence quantum yields in H2O, indicating that these analogs display microenvironment sensitivity. Furthermore, the synthesis towards a novel tricyclic adenine analog was attempted by extending the substrate scope of the Sonogashira cross-coupling/heteroannulation chemistry developed in the Hudson groupfor cytidine analogs to adenine analogs. However, unlike the cytidine scaffold, the 7-deazaadenine substrate did not cyclize under the Sonogashira cross-coupling/heteroannulation reaction conditions to give the tricyclic adenine and the straight cross-coupled product was obtained in moderate yield. Lastly, an intrinsic nucleobase quencher was synthesized via the azo coupling reaction between 5-diazouracil and N,N-dimethylaniline. Fluorescence quenching experiments were performed between the nucleobase quencher and the fluorophores phenylpyrrolocytidine (pC), and pyrene to determine viable FRET pairs for use in molecular beacon constructs

Asymptotic solutions of the Dirichlet problem for the heat equation with impulses

We propose an algorithm for the construction of asymptotic expansions for solutions of the Dirichlet problem for the heat equation with impulses.Запропоновано алгоритм побудови асимптотичних розвинень для розв'язків задачі Діріхле для рівняння теплопровідності з імпульсною дією

Post-2020 EU Roma Strategy: The Way Forward

The 2011 EU Framework for National Roma Integration Strategies (the EU Roma Framework) set ambitious goals to close the gap between Roma and non-Roma in education, employment, housing, and health, as well as to protect Roma against discrimination. While there have been many achievements since 2011, the EU Roma Framework has failed to reach its goals in all policy areas, including combating discrimination. Its objectives were unrealistic and did not consider crucial missing elements.This report recommends the creation of a fully-fledged strategy on Roma and the EU, not just a framework, and how to make future goals more concrete and achievable

Is Lactate an Oncometabolite? Evidence Supporting a Role for Lactate in the Regulation of Transcriptional Activity of Cancer-Related Genes in MCF7 Breast Cancer Cells.

Lactate is a ubiquitous molecule in cancer. In this exploratory study, our aim was to test the hypothesis that lactate could function as an oncometabolite by evaluating whether lactate exposure modifies the expression of oncogenes, or genes encoding transcription factors, cell division, and cell proliferation in MCF7 cells, a human breast cancer cell line. Gene transcription was compared between MCF7 cells incubated in (a) glucose/glutamine-free media (control), (b) glucose-containing media to stimulate endogenous lactate production (replicating some of the original Warburg studies), and (c) glucose-containing media supplemented with L-lactate (10 and 20 mM). We found that both endogenous, glucose-derived lactate and exogenous, lactate supplementation significantly affected the transcription of key oncogenes (MYC, RAS, and PI3KCA), transcription factors (HIF1A and E2F1), tumor suppressors (BRCA1, BRCA2) as well as cell cycle and proliferation genes involved in breast cancer (AKT1, ATM, CCND1, CDK4, CDKN1A, CDK2B) (0.001 < p < 0.05 for all genes). Our findings support the hypothesis that lactate acts as an oncometabolite in MCF7 cells. Further research is necessary on other cell lines and biopsy cultures to show generality of the findings and reveal the mechanisms by which dysregulated lactate metabolism could act as an oncometabolite in carcinogenesis

A Framework for the Use of Mobile Sensor Networks in System Identification

System identification (SID, also known as structural identification in this context) is the process of extracting a system’s modal properties from sensor measurements. Typically, a mathematical model is chosen for data fitting and the identification of model parameters yields modal property estimates. Historically, SID has relied on measurements from fixed sensors, which remain at specific locations throughout data collection. The ultimate flaw in fixed sensors is they provide restricted spatial information, which can be addressed by mobile sensors. In this dissertation, a framework is developed for extracting structural modal estimates from data collected by mobile sensors. The current state of mobile sensor networks applications in SHM is developing; research has been diverse, however limited. Reduced setup requirements for mobile sensor networks facilitate data collection, thus enable expedited information updates on a structure’s health and improved emergency response times to natural disasters. This research focuses on using mobile sensor data, i.e., data from sensors simultaneously recording in time, while moving in space, for comprehensive system identification of real structural systems. Mobile sensing data is analyzed from two perspectives, each requires different modeling techniques: an incomplete data perspective and a complete data perspective. In Chapter 2, Structural Identification using Expectation Maximization (STRIDE) is introduced, a novel application of the Expectation Maximization (EM) algorithm and approach for output-only modal identification. Chapter 3 revisits STRIDE for consideration of incomplete datasets, i.e., data matrices containing missing entries. Such instances may occur as a result of failed communications or packet losses in a wireless sensor network or as a result of sensing and sampling methods, e.g., mobile sensing. It is demonstrated that sensor network data containing a significant amount of missing observations can be used to achieve a comprehensive modal identification. Moreover, a successful real-world identification with simulated mobile sensors quantifies the preservation of spatial information, establishing benefits of this type of network, and emphasizing an inquiry for future SHM implementations. In Maximum Likelihood (ML) estimation theory, on which STRIDE is based, the precision of ML point estimates can be measured by the curvature of the likelihood function. Chapter 4 presents closed-form partial derivatives, observed information, and variance expressions for discrete-time stochastic state-space model entities. Confidence intervals are constructed for natural frequencies, damping ratios, and mode shapes using the asymptotic normality property of ML estimators. In anticipation of high-resolution scanning, mobile sensor data is also perceived to belong to a general class of data called dynamic sensor networks (DSNs), which inherently contain spatial discontinuities. Chapter 5 introduces state-space approaches for processing data from sensor networks with time-variant configurations for which a novel truncated physical model (TPM) is proposed. In typical state-space frameworks, a spatially dense observation space on the physical structure dictates a large state variable space, i.e., more total sensing nodes require a more complex dynamic model. The result is an overly complex dynamic model for the structural system. As sensor networks evolve and with increased use of novel sensing techniques in practice, it is desirable to decouple the size of the structural dynamic system from spatial sampling resolution during instrumentation. The TPM is presented as a novel technique to reduce physical state sizes and permit a general class of DSN data, with an emphasis on mobile sensing. Also, the role of basis functions in the approximation of mode shape regression is established. Chapter 6 discusses the identification of the TPM using an adjusted STRIDE methodology