85 resultados para Quantum Computer


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PURPOSE: To prospectively evaluate the accuracy and reliability of "freehand" posttraumatic orbital wall reconstruction with AO (Arbeitsgemeinschaft Osteosynthese) titanium mesh plates by using computer-aided volumetric measurement of the bony orbits. METHODS: Bony orbital volume was measured in 12 patients from coronal CT scan slices using OsiriX Medical Image software. After defining the volumetric limits of the orbit, the segmentation of the bony orbital region of interest of each single slice was performed. At the end of the segmentation process, all regions of interest were grouped and the volume was computed. The same procedure was performed on both orbits, and thereafter the volume of the contralateral uninjured orbit was used as a control for comparison. RESULTS: In all patients, the volume data of the reconstructed orbit fitted that of the contralateral uninjured orbit with accuracy to within 1.85 cm3 (7%). CONCLUSIONS: This preliminary study has demonstrated that posttraumatic orbital wall reconstruction using "freehand" bending and placement of AO titanium mesh plates results in a high success rate in re-establishing preoperative bony volume, which closely approximates that of the contralateral uninjured orbit.

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There has been a lack of quick, simple and reliable methods for determination of nanoparticle size. An investigation of the size of hydrophobic (CdSe) and hydrophilic (CdSe/ZnS) quantum dots was performed by using the maximum position of the corresponding fluorescence spectrum. It has been found that fluorescence spectroscopy is a simple and reliable methodology to estimate the size of both quantum dot types. For a given solution, the homogeneity of the size of quantum dots is correlated to the relationship between the fluorescence maximum position (FMP) and the quantum dot size. This methodology can be extended to the other fluorescent nanoparticles. The employment of evolving factor analysis and multivariate curve resolution-alternating least squares for decomposition of the series of quantum dots fluorescence spectra recorded by a specific measuring procedure reveals the number of quantum dot fractions having different diameters. The size of the quantum dots in a particular group is defined by the FMP of the corresponding component in the decomposed spectrum. These results show that a combination of the fluorescence and appropriate statistical method for decomposition of the emission spectra of nanoparticles may be a quick and trusted method for the screening of the inhomogeneity of their solution.

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It has been convincingly argued that computer simulation modeling differs from traditional science. If we understand simulation modeling as a new way of doing science, the manner in which scientists learn about the world through models must also be considered differently. This article examines how researchers learn about environmental processes through computer simulation modeling. Suggesting a conceptual framework anchored in a performative philosophical approach, we examine two modeling projects undertaken by research teams in England, both aiming to inform flood risk management. One of the modeling teams operated in the research wing of a consultancy firm, the other were university scientists taking part in an interdisciplinary project experimenting with public engagement. We found that in the first context the use of standardized software was critical to the process of improvisation, the obstacles emerging in the process concerned data and were resolved through exploiting affordances for generating, organizing, and combining scientific information in new ways. In the second context, an environmental competency group, obstacles were related to the computer program and affordances emerged in the combination of experience-based knowledge with the scientists' skill enabling a reconfiguration of the mathematical structure of the model, allowing the group to learn about local flooding.

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In recent years, Business Model Canvas design has evolved from being a paper-based activity to one that involves the use of dedicated computer-aided business model design tools. We propose a set of guidelines to help design more coherent business models. When combined with functionalities offered by CAD tools, they show great potential to improve business model design as an ongoing activity. However, in order to create complex solutions, it is necessary to compare basic business model design tasks, using a CAD system over its paper-based counterpart. To this end, we carried out an experiment to measure user perceptions of both solutions. Performance was evaluated by applying our guidelines to both solutions and then carrying out a comparison of business model designs. Although CAD did not outperform paper-based design, the results are very encouraging for the future of computer-aided business model design.

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We address the challenges of treating polarization and covalent interactions in docking by developing a hybrid quantum mechanical/molecular mechanical (QM/MM) scoring function based on the semiempirical self-consistent charge density functional tight-binding (SCC-DFTB) method and the CHARMM force field. To benchmark this scoring function within the EADock DSS docking algorithm, we created a publicly available dataset of high-quality X-ray structures of zinc metalloproteins ( http://www.molecular-modelling.ch/resources.php ). For zinc-bound ligands (226 complexes), the QM/MM scoring yielded a substantially improved success rate compared to the classical scoring function (77.0% vs 61.5%), while, for allosteric ligands (55 complexes), the success rate remained constant (49.1%). The QM/MM scoring significantly improved the detection of correct zinc-binding geometries and improved the docking success rate by more than 20% for several important drug targets. The performance of both the classical and the QM/MM scoring functions compare favorably to the performance of AutoDock4, AutoDock4Zn, and AutoDock Vina.

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Following their detection and seizure by police and border guard authorities, false identity and travel documents are usually scanned, producing digital images. This research investigates the potential of these images to classify false identity documents, highlight links between documents produced by a same modus operandi or same source, and thus support forensic intelligence efforts. Inspired by previous research work about digital images of Ecstasy tablets, a systematic and complete method has been developed to acquire, collect, process and compare images of false identity documents. This first part of the article highlights the critical steps of the method and the development of a prototype that processes regions of interest extracted from images. Acquisition conditions have been fine-tuned in order to optimise reproducibility and comparability of images. Different filters and comparison metrics have been evaluated and the performance of the method has been assessed using two calibration and validation sets of documents, made up of 101 Italian driving licenses and 96 Portuguese passports seized in Switzerland, among which some were known to come from common sources. Results indicate that the use of Hue and Edge filters or their combination to extract profiles from images, and then the comparison of profiles with a Canberra distance-based metric provides the most accurate classification of documents. The method appears also to be quick, efficient and inexpensive. It can be easily operated from remote locations and shared amongst different organisations, which makes it very convenient for future operational applications. The method could serve as a first fast triage method that may help target more resource-intensive profiling methods (based on a visual, physical or chemical examination of documents for instance). Its contribution to forensic intelligence and its application to several sets of false identity documents seized by police and border guards will be developed in a forthcoming article (part II).

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NlmCategory="UNASSIGNED">A version of cascaded systems analysis was developed specifically with the aim of studying quantum noise propagation in x-ray detectors. Signal and quantum noise propagation was then modelled in four types of x-ray detectors used for digital mammography: four flat panel systems, one computed radiography and one slot-scan silicon wafer based photon counting device. As required inputs to the model, the two dimensional (2D) modulation transfer function (MTF), noise power spectra (NPS) and detective quantum efficiency (DQE) were measured for six mammography systems that utilized these different detectors. A new method to reconstruct anisotropic 2D presampling MTF matrices from 1D radial MTFs measured along different angular directions across the detector is described; an image of a sharp, circular disc was used for this purpose. The effective pixel fill factor for the FP systems was determined from the axial 1D presampling MTFs measured with a square sharp edge along the two orthogonal directions of the pixel lattice. Expectation MTFs were then calculated by averaging the radial MTFs over all possible phases and the 2D EMTF formed with the same reconstruction technique used for the 2D presampling MTF. The quantum NPS was then established by noise decomposition from homogenous images acquired as a function of detector air kerma. This was further decomposed into the correlated and uncorrelated quantum components by fitting the radially averaged quantum NPS with the radially averaged EMTF(2). This whole procedure allowed a detailed analysis of the influence of aliasing, signal and noise decorrelation, x-ray capture efficiency and global secondary gain on NPS and detector DQE. The influence of noise statistics, pixel fill factor and additional electronic and fixed pattern noises on the DQE was also studied. The 2D cascaded model and decompositions performed on the acquired images also enlightened the observed quantum NPS and DQE anisotropy.