562 resultados para Combustion engineering


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Generating discriminative input features is a key requirement for achieving highly accurate classifiers. The process of generating features from raw data is known as feature engineering and it can take significant manual effort. In this paper we propose automated feature engineering to derive a suite of additional features from a given set of basic features with the aim of both improving classifier accuracy through discriminative features, and to assist data scientists through automation. Our implementation is specific to HTTP computer network traffic. To measure the effectiveness of our proposal, we compare the performance of a supervised machine learning classifier built with automated feature engineering versus one using human-guided features. The classifier addresses a problem in computer network security, namely the detection of HTTP tunnels. We use Bro to process network traffic into base features and then apply automated feature engineering to calculate a larger set of derived features. The derived features are calculated without favour to any base feature and include entropy, length and N-grams for all string features, and counts and averages over time for all numeric features. Feature selection is then used to find the most relevant subset of these features. Testing showed that both classifiers achieved a detection rate above 99.93% at a false positive rate below 0.01%. For our datasets, we conclude that automated feature engineering can provide the advantages of increasing classifier development speed and reducing development technical difficulties through the removal of manual feature engineering. These are achieved while also maintaining classification accuracy.

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This chapter presents a brief history of the development of ophthalmic biomaterials. Particularities in the development of ophthalmic biomaterials are discussed and some of their historic priorities within the general field of biomaterials are revealed or emphasized. The chapter then discusses the role and integration of ophthalmic biomaterials in tissue engineering and regenerative medicine applications.

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Modulation of material physical and chemical properties through selective surface engineering is currently one of the most active research fields, aimed at optimizing functional performance for applications. The activity of exposed crystal planes determines the catalytic, sensory, photocatalytic, and electrochemical behavior of a material. In the research on nanomagnets, it opens up new perspectives in the fields of nanoelectronics, spintronics, and quantum computation. Herein, we demonstrate controllable magnetic modulation of α-MnO 2 nanowires, which displayed surface ferromagnetism or antiferromagnetism, depending on the exposed plane. First-principles density functional theory calculations confirm that both Mn- and O-terminated α-MnO2(1 1 0) surfaces exhibit ferromagnetic ordering. The investigation of surface-controlled magnetic particles will lead to significant progress in our fundamental understanding of functional aspects of magnetism on the nanoscale, facilitating rational design of nanomagnets. Moreover, we approved that the facet engineering pave the way on designing semiconductors possessing unique properties for novel energy applications, owing to that the bandgap and the electronic transport of the semiconductor can be tailored via exposed surface modulations.

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The difficult sintering of BaZr0.8Y0.2O 3-δ (BZY20) powders makes the fabrication of anode-supported BZY20 electrolyte films complex. Dense BZY20 membranes were successfully fabricated on anode substrates made of sinteractive NiO-BZY20 powders, prepared by a combustion method. With respect to traditional anode substrates made of powders prepared by mechanical mixing, the anode substrates made of the wet-chemically synthesized composite NiO-BZY20 powders significantly promoted the densification of BZY20 membranes: dense BZY20 films were obtained after co-pressing and co-firing at 1300 °C, a much lower temperature than those usually needed for densifying BZY20 membranes. Improved electrochemical performance was also observed: the supported BZY20 films maintained a high proton conductivity, up to 5.4 × 10-3 S cm-1 at 700 °C. Moreover, an anode-supported fuel cell with a 30 m thick BZY20 electrolyte film fabricated at 1400 °C on the anode made of the wet-chemically synthesized NiO-BZY20 powder showed a peak power density of 172 mW cm-2 at 700 °C, using La0.6Sr0.4Co 0.2Fe0.8O3-δ-BaZr0.7Y 0.2Pr0.1O3-δ as the cathode material, with a remarkable performance for proton-conducting solid oxide fuel cell (SOFC) applications.

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Despite positive testing in animal studies, more than 80% of novel drug candidates fail to proof their efficacy when tested in humans. This is primarily due to the use of preclinical models that are not able to recapitulate the physiological or pathological processes in humans. Hence, one of the key challenges in the field of translational medicine is to “make the model organism mouse more human.” To get answers to questions that would be prognostic of outcomes in human medicine, the mouse's genome can be altered in order to create a more permissive host that allows the engraftment of human cell systems. It has been shown in the past that these strategies can improve our understanding of tumor immunology. However, the translational benefits of these platforms have still to be proven. In the 21st century, several research groups and consortia around the world take up the challenge to improve our understanding of how to humanize the animal's genetic code, its cells and, based on tissue engineering principles, its extracellular microenvironment, its tissues, or entire organs with the ultimate goal to foster the translation of new therapeutic strategies from bench to bedside. This article provides an overview of the state of the art of humanized models of tumor immunology and highlights future developments in the field such as the application of tissue engineering and regenerative medicine strategies to further enhance humanized murine model systems.

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This study investigates the morphology, microstructure and surface composition of Diesel engine exhaust particles. The state of agglomeration, the primary particle size and the fractal dimension of exhaust particles from petroleum Diesel (petrodiesel) and biodiesel blends from microalgae, cotton seed and waste cooking oil were investigated by means of high resolution transmission electron microscopy. With primary particle diameters between 12-19 nm, biodiesel blend primary particles are found to be smaller than petrodiesel ones (21±2 nm). Also it was found that soot agglomerates from biodiesels are more compact and spherical, as their fractal dimensions are higher, e.g. 2.2±0.1 for 50% algae biodiesel compared to 1.7±0.1 for petrodiesel. In addition, analysis of the chemical composition by means of x-ray photoelectron spectroscopy revealed an up to a factor of two increased oxygen content on the primary particle surface for biodiesel. The length, curvature and distance of graphene layers were measured showing a greater structural disorder for biodiesel with shorter fringes of higher tortuosity. This change in carbon chemistry may reflect the higher oxygen content of biofuels. Overall, it seems that the oxygen content in the fuels is the underlying reason for the observed morphological change in the resulting soot particles.

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WO3 nanoplate arrays with (002) oriented facets grown on fluorine doped SnO2 (FTO) glass substrates are tailored by tuning the precursor solution via a facile hydrothermal method. A 2-step hydrothermal method leads to the preferential growth of WO3 film with enriched (002) facets, which exhibits extraordinary photoelectrochemical (PEC) performance with a remarkable photocurrent density of 3.7 mA cm–2 at 1.23 V vs. revisable hydrogen electrode (RHE) under AM 1.5 G illumination without the use of any cocatalyst, corresponding to ~93% of the theoretical photocurrent of WO3. Density functional theory (DFT) calculations together with experimental studies reveal that the enhanced photocatalytic activity and better photo-stability of the WO3 films are attributed to the synergistic effect of highly reactive (002) facet and nanoplate structure which facilitates the photo–induced charge carrier separation and suppresses the formation of peroxo-species. Without the use of oxygen evolution cocatalysts, the excellent PEC performance, demonstrated in this work, by simply tuning crystal facets and nanostructure of pristine WO3 films may open up new opportunities in designing high performance photoanodes for PEC water splitting.