45 resultados para design space exploration
Resumo:
OBJECTIVES To evaluate prosthetic parameters in the edentulous anterior maxilla for decision making between fixed and removable implant prosthesis using virtual planning software. MATERIAL AND METHODS CT- or DVT-scans of 43 patients (mean age 62 ± 8 years) with an edentulous maxilla were analyzed with the NobelGuide software. Implants (≥3.5 mm diameter, ≥10 mm length) were virtually placed in the optimal three-dimensional prosthetic position of all maxillary front teeth. Anatomical and prosthetic landmarks, including the cervical crown point (C-Point), the acrylic flange border (F-Point), and the implant-platform buccal-end (I-Point) were defined in each middle section to determine four measuring parameters: (1) acrylic flange height (FLHeight), (2) mucosal coverage (MucCov), (3) crown-Implant distance (CID) and (4) buccal prosthesis profile (ProsthProfile). Based on these parameters, all patients were assigned to one of three classes: (A) MucCov ≤ 0 mm and ProsthProfile≥45(0) allowing for fixed prosthesis, (B) MucCov = 0-5 mm and/or ProsthProfile = 30(0) -45(0) probably allowing for fixed prosthesis, and (C) MucCov ≥ 5 mm and/or ProsthProfile ≤ 30(0) where removable prosthesis is favorable. Statistical analyses included descriptive methods and non-parametric tests. RESULTS Mean values were for FLHeight 10.0 mm, MucCov 5.6 mm, CID 7.4 mm, and ProsthProfile 39.1(0) . Seventy percent of patients fulfilled class C criteria (removable), 21% class B (probably fixed), and 2% class A (fixed), while in 7% (three patients) bone volume was insufficient for implant planning. CONCLUSIONS The proposed classification and virtual planning procedure simplify the decision-making process regarding type of prosthesis and increase predictability of esthetic treatment outcomes. It was demonstrated that in the majority of cases, the space between the prosthetic crown and implant platform had to be filled with prosthetic materials.
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In the context of expensive numerical experiments, a promising solution for alleviating the computational costs consists of using partially converged simulations instead of exact solutions. The gain in computational time is at the price of precision in the response. This work addresses the issue of fitting a Gaussian process model to partially converged simulation data for further use in prediction. The main challenge consists of the adequate approximation of the error due to partial convergence, which is correlated in both design variables and time directions. Here, we propose fitting a Gaussian process in the joint space of design parameters and computational time. The model is constructed by building a nonstationary covariance kernel that reflects accurately the actual structure of the error. Practical solutions are proposed for solving parameter estimation issues associated with the proposed model. The method is applied to a computational fluid dynamics test case and shows significant improvement in prediction compared to a classical kriging model.
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The MQN-mapplet is a Java application giving access to the structure of small molecules in large databases via color-coded maps of their chemical space. These maps are projections from a 42-dimensional property space defined by 42 integer value descriptors called molecular quantum numbers (MQN), which count different categories of atoms, bonds, polar groups, and topological features and categorize molecules by size, rigidity, and polarity. Despite its simplicity, MQN-space is relevant to biological activities. The MQN-mapplet allows localization of any molecule on the color-coded images, visualization of the molecules, and identification of analogs as neighbors on the MQN-map or in the original 42-dimensional MQN-space. No query molecule is necessary to start the exploration, which may be particularly attractive for nonchemists. To our knowledge, this type of interactive exploration tool is unprecedented for very large databases such as PubChem and GDB-13 (almost one billion molecules). The application is freely available for download at www.gdb.unibe.ch.
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The Imager for Low Energetic Neutral Atoms test facility at the University of Bern was developed to investigate, characterize, and quantify physical processes on surfaces that are used to ionize neutral atoms before their analysis in neutral particle-sensing instruments designed for space research. The facility has contributed valuable knowledge of the interaction of ions with surfaces (e.g., fraction of ions scattered from surfaces and angular scattering distribution) and employs a novel measurement principle for the determination of secondary electron emission yields as a function of energy, angle of incidence, particle species, and sample surface for low particle energies. Only because of this test facility it was possible to successfully apply surface-science processes for the new detection technique for low-energetic neutral particles with energies below about 1 keV used in space applications. All successfully flown spectrometers for the detection of low-energetic neutrals based on the particle–surface interaction process use surfaces evaluated, tested, and calibrated in this facility. Many instruments placed on different spacecraft (e.g., Imager for Magnetopause-to-Aurora Global Exploration, Chandrayaan-1, Interstellar Boundary Explorer, etc.) have successfully used this technique.
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The space-qualified design of a miniaturized laser for pulsed operation at a wavelength of 1064 nm and at repetition rates up to 10 Hz is presented. This laser consists of a pair of diode-laser pumped, actively q-switched Nd:YAG rod oscillators hermetically sealed and encapsulated in an environment of dry synthetic air. The system delivers at least 300 million laser pulses with 50 mJ energy and 5 ns pulse width (FWHM). It will be launched in 2017 aboard European Space Agency’s Mercury Planetary Orbiter as part of the BepiColombo Laser Altimeter, which, after a 6-years cruise, will start recording topographic data from orbital altitudes between 400 and 1500 km above Mercury’s surface.
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CMOS-sensors, or in general Active Pixel Sensors (APS), are rapidly replacing CCDs in the consumer camera market. Due to significant technological advances during the past years these devices start to compete with CCDs also for demanding scientific imaging applications, in particular in the astronomy community. CMOS detectors offer a series of inherent advantages compared to CCDs, due to the structure of their basic pixel cells, which each contains their own amplifier and readout electronics. The most prominent advantages for space object observations are the extremely fast and flexible readout capabilities, feasibility for electronic shuttering and precise epoch registration,and the potential to perform image processing operations on-chip and in real-time. Here, the major challenges and design drivers for ground-based and space-based optical observation strategies for objects in Earth orbit have been analyzed. CMOS detector characteristics were critically evaluated and compared with the established CCD technology, especially with respect to the above mentioned observations. Finally, we simulated several observation scenarios for ground- and space-based sensor by assuming different observation and sensor properties. We will introduce the analyzed end-to-end simulations of the ground- and spacebased strategies in order to investigate the orbit determination accuracy and its sensitivity which may result from different values for the frame-rate, pixel scale, astrometric and epoch registration accuracies. Two cases were simulated, a survey assuming a ground-based sensor to observe objects in LEO for surveillance applications, and a statistical survey with a space-based sensor orbiting in LEO observing small-size debris in LEO. The ground-based LEO survey uses a dynamical fence close to the Earth shadow a few hours after sunset. For the space-based scenario a sensor in a sun-synchronous LEO orbit, always pointing in the anti-sun direction to achieve optimum illumination conditions for small LEO debris was simulated.
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Remote sensing observations meet some limitations when used to study the bulk atmospheric composition of the giant planets of our solar system. A remarkable example of the superiority of in situ probe measurements is illustrated by the exploration of Jupiter, where key measurements such as the determination of the noble gases׳ abundances and the precise measurement of the helium mixing ratio have only been made available through in situ measurements by the Galileo probe. This paper describes the main scientific goals to be addressed by the future in situ exploration of Saturn placing the Galileo probe exploration of Jupiter in a broader context and before the future probe exploration of the more remote ice giants. In situ exploration of Saturn׳s atmosphere addresses two broad themes that are discussed throughout this paper: first, the formation history of our solar system and second, the processes at play in planetary atmospheres. In this context, we detail the reasons why measurements of Saturn׳s bulk elemental and isotopic composition would place important constraints on the volatile reservoirs in the protosolar nebula. We also show that the in situ measurement of CO (or any other disequilibrium species that is depleted by reaction with water) in Saturn׳s upper troposphere may help constraining its bulk O/H ratio. We compare predictions of Jupiter and Saturn׳s bulk compositions from different formation scenarios, and highlight the key measurements required to distinguish competing theories to shed light on giant planet formation as a common process in planetary systems with potential applications to most extrasolar systems. In situ measurements of Saturn׳s stratospheric and tropospheric dynamics, chemistry and cloud-forming processes will provide access to phenomena unreachable to remote sensing studies. Different mission architectures are envisaged, which would benefit from strong international collaborations, all based on an entry probe that would descend through Saturn׳s stratosphere and troposphere under parachute down to a minimum of 10 bar of atmospheric pressure. We finally discuss the science payload required on a Saturn probe to match the measurement requirements.
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Three-dimensional oxalate-based {[Ru(bpy)3][Cu2xNi2(1-x)(ox)3]}n (0≤ x ≤ 1, ox = C2O42-, bpy = 2,2‘bipyridine) were synthesized. The structure was determined for x = 1 by X-ray diffraction on single crystal. The compound crystallizes in the cubic space group P4132. It shows a three-dimensional 10-gon 3-connected (10,3) anionic network where copper(II) has an unusual tris(bischelated) environment. X-ray powder diffraction patterns and their Rietveld refinement show that all the compounds along the series are isostructural and single-phased. According to X-ray absorption spectroscopy, copper(II) and nickel(II) have an octahedral environment, respectively elongated and trigonally distorted. As shown by natural circular dichroism, the optically active forms of {[Ru(bpy)3][CuxNi2(1-x)(ox)3]}n are obtained starting from resolved Δ- or Λ-[Ru(bpy)3]2+. The Curie−Weiss temperatures range between −55 (x = 1) and −150 K (x = 0). The antiferromagnetic exchange interaction thus decreases when the copper contents increases in agreement with the crystallographic structure of the compounds and the electronic structure of the metal ions. At low temperature, the compounds exhibit complex long-range ordered magnetic behavior.
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Hope is believed to be beneficial for vocational pursuits, but the question of how and why hope is related to pivotal career development variables remains largely unaddressed. In a series of three studies, we investigated the relationship between hope and career exploration. Study 1 examined at-risk adolescents (N = 228) in Switzerland and showed that hope explains variance in career exploration beyond the significant effects of generalized self-efficacy beliefs and perceived social support. Study 2 found the same result among a group (N = 223) of first-year students at a Swiss university with a measure of state hope. Study 3 applied a one-year cross-lagged design with a diverse group of students (N = 266) at a German university to investigate the mutual effects of dispositional hope and career exploration over time. Although both variables were found to be related within and over time, we could not confirm lagged effects in either direction. The results suggest that hope is significantly correlated with career exploration because both are related to personality and social–contextual variables.
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A bitopic ligand, 4-(3,5-dimethylpyrazol-4-yl)-1,2,4-triazole (Hpz-tr) (1), containing two different heterocyclic moieties was employed for the design of copper(II)–molybdate solids under hydrothermal conditions. In the multicomponent CuII/Hpz-tr/MoVI system, a diverse set of coordination hybrids, [Cu(Hpz-tr)2SO4]·3H2O (2), [Cu(Hpz-tr)Mo3O10] (3), [Cu4(OH)4(Hpz-tr)4Mo8O26]·6H2O (4), [Cu(Hpz-tr)2Mo4O13] (5), and [Mo2O6(Hpz-tr)]·H2O (6), was prepared and characterized. A systematic investigation of these systems in the form of a ternary crystallization diagram approach was utilized to show the influence of the molar ratios of starting reagents, the metal (CuII and MoVI) sources, the temperature, etc., on the reaction products outcome. Complexes 2–4 dominate throughout a wide crystallization range of the composition triangle, while the other two compounds 5 and 6 crystallize as minor phases in a narrow concentration range. In the crystal structures of 2–6, the organic ligand behaves as a short [N–N]-triazole linker between metal centers Cu···Cu in 2–4, Cu···Mo in 5, and Mo···Mo in 6, while the pyrazolyl function remains uncoordinated. This is the reason for the exceptional formation of low-dimensional coordination motifs: 1D for 2, 4, and 6 and 2D for 3 and 5. In all cases, the pyrazolyl group is involved in H bonding (H-donor/H-acceptor) and is responsible for π–π stacking, thus connecting the chain and layer structures in more complicated H-bonding architectures. These compounds possess moderate thermal stability up to 250–300 °C. The magnetic measurements were performed for 2–4, revealing in all three cases antiferromagnetic exchange interactions between neighboring CuII centers and long-range order with a net moment below Tc of 13 K for compound 4.
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Background The RCSB Protein Data Bank (PDB) provides public access to experimentally determined 3D-structures of biological macromolecules (proteins, peptides and nucleic acids). While various tools are available to explore the PDB, options to access the global structural diversity of the entire PDB and to perceive relationships between PDB structures remain very limited. Methods A 136-dimensional atom pair 3D-fingerprint for proteins (3DP) counting categorized atom pairs at increasing through-space distances was designed to represent the molecular shape of PDB-entries. Nearest neighbor searches examples were reported exemplifying the ability of 3DP-similarity to identify closely related biomolecules from small peptides to enzyme and large multiprotein complexes such as virus particles. The principle component analysis was used to obtain the visualization of PDB in 3DP-space. Results The 3DP property space groups proteins and protein assemblies according to their 3D-shape similarity, yet shows exquisite ability to distinguish between closely related structures. An interactive website called PDB-Explorer is presented featuring a color-coded interactive map of PDB in 3DP-space. Each pixel of the map contains one or more PDB-entries which are directly visualized as ribbon diagrams when the pixel is selected. The PDB-Explorer website allows performing 3DP-nearest neighbor searches of any PDB-entry or of any structure uploaded as protein-type PDB file. All functionalities on the website are implemented in JavaScript in a platform-independent manner and draw data from a server that is updated daily with the latest PDB additions, ensuring complete and up-to-date coverage. The essentially instantaneous 3DP-similarity search with the PDB-Explorer provides results comparable to those of much slower 3D-alignment algorithms, and automatically clusters proteins from the same superfamilies in tight groups. Conclusion A chemical space classification of PDB based on molecular shape was obtained using a new atom-pair 3D-fingerprint for proteins and implemented in a web-based database exploration tool comprising an interactive color-coded map of the PDB chemical space and a nearest neighbor search tool. The PDB-Explorer website is freely available at www.cheminfo.org/pdbexplorer and represents an unprecedented opportunity to interactively visualize and explore the structural diversity of the PDB.
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This work deals with parallel optimization of expensive objective functions which are modelled as sample realizations of Gaussian processes. The study is formalized as a Bayesian optimization problem, or continuous multi-armed bandit problem, where a batch of q > 0 arms is pulled in parallel at each iteration. Several algorithms have been developed for choosing batches by trading off exploitation and exploration. As of today, the maximum Expected Improvement (EI) and Upper Confidence Bound (UCB) selection rules appear as the most prominent approaches for batch selection. Here, we build upon recent work on the multipoint Expected Improvement criterion, for which an analytic expansion relying on Tallis’ formula was recently established. The computational burden of this selection rule being still an issue in application, we derive a closed-form expression for the gradient of the multipoint Expected Improvement, which aims at facilitating its maximization using gradient-based ascent algorithms. Substantial computational savings are shown in application. In addition, our algorithms are tested numerically and compared to state-of-the-art UCB-based batchsequential algorithms. Combining starting designs relying on UCB with gradient-based EI local optimization finally appears as a sound option for batch design in distributed Gaussian Process optimization.
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Since the analysis of the lunar rocks and soil samples, brought to Earth by the Apollo missions, it is believed that the Moon has a waterless nature and also other volatile species are strongly depleted. Advancement in analysis techniques helped to identify water and other volatile species in lunar volcanic glasses. Additionally, recent lunar space missions detected water and volatile organic compounds in the region of the lunar poles where permanently shadowed craters are existing. All known lunar soil samples available on Earth come from the lunar near side, close to the equator. To verify the most recent measurement results and to enhance the knowledge of the geological history of the Moon it is of high interest to perform in situ measurements on the lunar poles. For this reason the Russian space agency, Roskosmos, developed aprogram for the scientific exploration of the lunar poles. The Gas Analysis Package (GAP) is part of the selected scientific payload aboard the Luna-Resurs Lander. This instrument uses pyrolytic cells and will apply laser spectroscopy, gas chromatography and mass spectrometry to detect and analyze volatile components trapped in the lunar soil. An existing ion optical design of a compact reflectron type time-of-flight mass spectrometer, originally built for the MEAP/P-BACE balloon mission, was chosen as a part of the GAP instrument. The scope of this thesis is the development of the interface between gas chromatography (GC) and this Neutral Gas Mass Spectrometer (NGMS) to perform coupled GC-MS measurements. In the first part of this thesis the interfacing concept was developed and verified by coupling the NGMS prototype to gas chromatography. The second part of this thesis is devoted to the development of the NGMS flight version.