Measurements of the Total and Differential Higgs Boson Production Cross Sections Combining the H→γγ and H→ZZ∗→4ℓ Decay Channels at s√=8 TeV with the ATLAS Detector

Measurements of the total and differential cross sections of Higgs boson production are performed using 20.3 fb−1 of pp collisions produced by the Large Hadron Collider at a center-of-mass energy of s√=8 TeV and recorded by the ATLAS detector. Cross sections are obtained from measured H→γγ and H→ZZ∗→4ℓ event yields, which are combined accounting for detector efficiencies, fiducial acceptances and branching fractions. Differential cross sections are reported as a function of Higgs boson transverse momentum, Higgs boson rapidity, number of jets in the event, and transverse momentum of the leading jet. The total production cross section is determined to be σpp→H=33.0±5.3(stat)±1.6(sys)pb. The measurements are compared to state-of-the-art predictions.

Local non-negative initial data scalar characterization of the Kerr solution

For any vacuum initial data set, we define a local, non-negative scalar quantity which vanishes at every point of the data hypersurface if and only if the data are Kerr initial data. Our scalar quantity only depends on the quantities used to construct the vacuum initial data set which are the Riemannian metric defined on the initial data hypersurface and a symmetric tensor which plays the role of the second fundamental form of the embedded initial data hypersurface. The dependency is algorithmic in the sense that given the initial data one can compute the scalar quantity by algebraic and differential manipulations, being thus suitable for an implementation in a numerical code. The scalar could also be useful in studies of the non-linear stability of the Kerr solution because it serves to measure the deviation of a vacuum initial data set from the Kerr initial data in a local and algorithmic way.

The role of automatic shape and position recognitionin streamlining manufacturing

The main features of most components consist of simple basic functional geometries: planes, cylinders, spheres and cones. Shape and position recognition of these geometries is essential for dimensional characterization of components, and represent an important contribution in the life cycle of the product, concerning in particular the manufacturing and inspection processes of the final product. This work aims to establish an algorithm to automatically recognize such geometries, without operator intervention. Using differential geometry large volumes of data can be treated and the basic functional geometries to be dealt recognized. The original data can be obtained by rapid acquisition methods, such as 3D survey or photography, and then converted into Cartesian coordinates. The satisfaction of intrinsic decision conditions allows different geometries to be fast identified, without operator intervention. Since inspection is generally a time consuming task, this method reduces operator intervention in the process. The algorithm was first tested using geometric data generated in MATLAB and then through a set of data points acquired by measuring with a coordinate measuring machine and a 3D scan on real physical surfaces. Comparison time spent in measuring is presented to show the advantage of the method. The results validated the suitability and potential of the algorithm hereby proposed

Algorithms and computational tools for metabolic flux analysis

PhD thesis in Biomedical Engineering

Lima de Freitas: O simbólico da obra pública – contributos para uma estética educacional

Tese de Doutoramento em Ciências da Educação - Especialidade em Filosofia da Educação

Implementação de sistemas de encriptação AES advanced encryption standard em hardware para segurança

Dissertação de mestrado integrado em Engenharia Electrónica Industrial e Computadores

Enzymatic hydrophobic modification of jute fibers via grafting to reinforce composites

Horseradish peroxidase (HRP)/H2O2 system catalyzes the free-radical polymerization of aromatic compounds such as lignins and gallate esters. In this work, dodecyl gallate (DG) was grafted onto the surfaces of lignin-rich jute fabrics by HRP-mediated oxidative polymerization with an aim to enhance the hydrophobicity of the fibers. The DG-grafted jute fibers and reaction products of their model compounds were characterized by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-TOF MS), attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC). The results clearly indicated the grafting of DG to the jute fiber by HRP. Furthermore, the hydrophobicity of jute fabrics was determined by measuring the wetting time and static contact angle. Compared to the control sample, the wetting time and static contact angle of the grated fabrics changed from ~1 s to 1 h and from ~0° to 123.68°, respectively. This clearly proved that the hydrophobicity of jute fabrics improved considerably. Conditions of the HRP-catalyzed DG-grafting reactions were optimized in terms of the DG content of modified jute fabrics. Moreover, the results of breaking strength and elongation of DG-grafted jute/ polypropylene (PP) composites demonstrated improved reinforcement of the composite due to enzymatic hydrophobic modification of jute fibers.