Boeing (Spain)

A number of multivariate exponential distributions are known, but they have not been obtained by methods that shed light on their applicability. This paper presents some meaningful derivations of a multivariate exponential distribution that serves to indicate conditions under which the distribution is appropriate. Two of these derivations are based on "shock models," and one is based on the requirement that residual life is independent of age. It is significant that the derivations all lead to the same distribution.

We review the working mechanisms, opportunity and challenges of intermediate-temperature and room-temperature sodium–sulfur batteries for low-cost energy storage.

OBJECTIVE: To perform a systematic review and a meta-analysis of accuracy of monoclonal stool antigen test (SAT) for the diagnosis of Helicobacter pylori infection. SELECTION OF STUDIES: assessing the accuracy of monoclonal SAT for the diagnosis of H. pylori infection. SEARCH STRATEGY: electronic and manual bibliographical searches. DATA EXTRACTION: independently done by two reviewers. DATA SYNTHESIS: meta-analyses combining the sensitivities, specificities, and likelihood ratios (LRs) of the individual studies. RESULTS: Twenty-two studies, including 2,499 patients, evaluated the monoclonal SAT before eradication therapy. Pooled sensitivity, specificity, LR+, and LR- were: 0.94 (95% CI 0.93-0.95), 0.97 (0.96-0.98), 24 (15-41), and 0.07 (0.04-0.12). The accuracy of both monoclonal and polyclonal SAT was evaluated together in 13 pretreatment studies, and higher pooled sensitivity was demonstrated with the monoclonal technique (0.95 vs 0.83). Twelve studies, including 957 patients, assessed the monoclonal SAT to confirm eradication after therapy. Pooled sensitivity, specificity, LR+, and LR- were 0.93 (0.89-0.96), 0.96 (0.94-0.97), 17 (12-23), and 0.1 (0.07-0.15). Both tests were evaluated together in eight post-treatment studies and, again, the monoclonal technique showed higher sensitivity (0.91 vs 0.76). Heterogeneity among studies disappeared when a single outlier study was excluded. Subanalysis depending on the reference method, the study population, or the study quality showed similar results. CONCLUSION: Monoclonal SAT is an accurate noninvasive method both for the initial diagnosis of H. pylori infection and for the confirmation of its eradication after treatment. The monoclonal technique has higher sensitivity than the polyclonal one, especially in the post-treatment setting.

deep Raman spectroscopy, emphasizing its potential for liquid biopsy, metabolic phenotyping, and extracellular vesicle diagnostics. The review concludes with a perspective on clinical translation of SERS, addressing commercialization potentials and the challenges in deep tissue in vivo sensing and imaging.

This review provides an extensive summary of the effects of carbohydrate fluorination with regard to changes in physical, chemical and biological properties with respect to regular saccharides. The specific structural, conformational, stability, reactivity and interaction features of fluorinated sugars are described, as well as their applications as probes and in chemical biology.

Lightweight aircraft design has received a considerable attention in recent years as a means for improving cruise efficiency. Reducing aircraft weight results in lower lift requirements which directly translate into lower drag, hence reduced engine thrust requirements during cruise. The use of lightweight materials such as advanced composite materials has been adopted by airframe manufacturers in current and future aircraft. Modern lightweight materials can provide less structural rigidity while maintaining load-carrying capacity. As structural flexibility increases, aeroelastic interactions with aerodynamic forces and moments become an increasingly important consideration in aircraft design and aerodynamic performance. Furthermore, aeroelastic interactions with flight dynamics can result in issues with vehicle stability and control. Abstract This paper describes a recent aeroelastic modeling effort for an elastically shaped aircraft concept (ESAC). The aircraft model is based on the rigid-body generic transport model (GTM) originally developed at NASA Langley Research Center. The ESAC distinguishes itself from the GTM in that it is equipped with highly flexible wing structures as a weight reduction design feature. More significantly, the wings are outfitted with a novel control effector concept called variable camber continuous trailing edge (VCCTE) flap system for active control of wing aeroelastic deflections to optimize the local angle of attack of wing sections for improved aerodynamic efficiency through cruise drag reduction and lift enhancement during take-off and landing. The VCCTE flap is a multi-functional and aerodynamically efficient device capable of achieving high lift-to-drag ratios. The flap system is comprised of three chordwise segments that form the variable camber feature of the flap and multiple spanwise segments that form a piecewise continuous trailing edge. By configuring the flap camber and trailing edge shape, drag reduction could be achieved. Moreover, some parts of the flap system can be made to have a high frequency response for roll control, gust load alleviation, and aeroservoelastic (ASE) modal suppression control. Abstract The aeroelastic model of the ESAC is based on one-dimensional structural dynamic theory that captures the aeroelastic deformation of a wing structure in a combined motion that involves flapwise bending, chordwise bending, and torsion. The model includes the effect of aircraft propulsion due to wing flexibility which causes the propulsive forces and moments to couple with the wing elastic motion. Engine mass is also accounted in the model. A fuel management model is developed to describe the wing mass change due to fuel usage in the main tank and wing tanks during cruise. Abstract The model computes both static and dynamic responses of the wing structures. The static aeroelastic deflections are used to estimate the effect of wing flexibility on induced drag and the potential drag reduction by the VCCTE flap system. A flutter analysis is conducted to estimate the flutter speed boundary. Gust load alleviation via adaptive control has been recently investigated to address flexibility of aircraft structures. A multi-objective flight control approach is presented for drag reduction control. The approach is based on an optimal control framework using a multi-objective cost function. Future studies will demonstrate the potential benefits of the approach.

Click green chemistry as an efficient functionalization and polymerization method of vegetable oils and their derivatives.

A low-cost pre-metallation strategy based on inorganic sacrificial salts that decompose on the first charge.

This paper documents the modeling of harmonic sources with nonlinear voltage-current characteristics such as transformers, iron-core reactors, rotating machines, arc furnaces, energy efficient lightings, and some household electronic appliances. The harmonic generating characteristics of these apparatus are reviewed. Different modeling techniques are summarized and suggestions for the use of different models are also provided whenever possible.

Poly-ether-ketone-ketone (PEKK) is an emerging alternative to poly-ether-ether-ketone (PEEK) as a matrix for high-performance carbon fibre (CF) reinforced composites. Herein, the results of an experimental investigation to examine the influence of matrix properties and fibre–matrix interface behaviour on the mechanical performances of CF/PEKK and CF/PEEK composites are presented. CF/PEKK presents superior strength under longitudinal tension, longitudinal and transverse compression, as well as in-plane shear. It also exhibits better interfacial shear strength (IFSS) than CF/PEEK, which contributes to its superior strength, as damage typically initiates at the fibre–matrix interface under in-plane loading. Predictions of different analytical models adopted from the literature, which assess the influence of fibre–matrix adhesion on the in-plane strength, compare favourably to the experiments. Under cyclic shear tests, CF/PEKK exhibited more gradual stiffness reductions and low shear plasticity until 5% shear strain, indicating a more damage tolerant matrix. Relative to CF/PEEK, CF/PEKK presents superior interlaminar shear strength (ILSS) and mode I fracture toughness (GIC), but similar mode II fracture toughness (GIIC). High GIC is due to a synergistic interaction between its inherently ductile matrix and high IFSS, while ILSS strongly correlates with IFSS. Overall, CF/PEKK offers a better combination of strength and toughness, exceeding CF/PEEK.

G IVEN the high efficiency and environmental advantages that fuel-cell technology could offer, along with the considerable improvements achieved in the automotive sector in the last 5– 10 years, the main airframe manufacturers have started to investigate their potential applications in aviation for both propulsion and onboard auxiliary power generation. In 2008, two important steps toward the implementation of fuel cells in aeronautical applications were met: the flight of the Boeing fuel-cell demonstrator airplane described in this paper and presented in Spain in February 2008 and the demonstration of a fuel-cell system generating auxiliary power for the hydraulic and electric systems of an Airbus 320, presented in France in February 2008 [1]. Although these programs will indubitably facilitate the integration of fuel-cell technology in aeronautical applications, there are still many technical challenges to be overcome before these systems can be integrated onboard commercial airplanes. However, fuel-cell technology could have a shortterm application (for example) in sport aviation or in specific missions of small manned or unmanned aircraft, in which fuel cells could offer improved mission endurances over those attained with current battery technology. The first challenge relates to increasing the specific energy density, a less serious concern for other industrial sectors but crucial in the aeronautical sector. Moreover, it is imperative to determine their reliability and performance in realflight conditions (for example, at high altitude, at different pitch and roll angles, etc.), since there are many requirements that are exclusive of aeronautical applications and for which no experience has been gained in other industrial sectors. Among these are, for example, variable pressure and temperature ranges and stringent safety requirements. Although limited in terms of different applications, there is a relatively long experience in the use of fuel-cell systems in the aerospace sector. Despite the fact that recent developments have centered on the automotive industry and in stationary power generation, in the 1960s, NASA (in collaboration with Pratt and Whitney and General Electric) developed fuel-cell systems for the Gemini and Apollo space missions [2]. Nowadays, considerably improved fuel-cell systems are employed onboard the space shuttles to produce water and electricity. A very innovative program that studied the use of fuel cells in the aeronautical sector was the Helios program, carried out in the United States between 1999 and 2003 [3]. The prototype, developed by AeroVironment, Inc., in collaboration with NASA, was a highaltitude (30,000 m) unmanned air platform with a flying wing configuration powered by electric motors. During the day, the Helios would use the energy provided by the photovoltaic cells for both propulsion and for generating hydrogen (throughwater electrolysis), and during the night, it would be powered by the fuel cell. Unfortunately, although they achieved an extremely impressive altitude record (30,000 m during 17 h) in 2001, the platform broke in flight in June 2003 and never flew with the fuel cells. In Arizona, on 26 May 2005, AeroVironment successfully completed the flight tests of one other unmanned platform with a similar aim to that of the Helios program but without using solar energy. It was a scaled prototype of theGlobalObserver [4]. The fuelcell-powered unmanned aerial vehicle (UAV) had a distributed electrical architecture in which liquid hydrogen fuel cells provided electricity to electric motors driving eight propellers. The Global Observer program continues with the aim of developing a platform able to stay aloft at high altitude (20,000 m) during at least 1 week, while carrying a 450 kg payload, to perform surveillance, reconnaissance, and frontier monitoring missions. NASA continues to be interested in high-altitude long-endurance unmanned platform surveillance missions. The Defense Advanced Research Projects Agency recently launched the Vulture program to develop new UAV concepts able to stay aloft at high altitudes during 5 years without interruptions for intelligence, communications, surveillance, and reconnaissance missions over areas of interest. Currently, the only systems able to cover fixed areas during several years are geosynchronic satellites orbiting at 35,780 km above the earth. The innovative platform would not only need to carry a payload of 454 kg, consuming 5 kW, but it would also need to maintain sufficient speed towithstand thewinds at 18,300–27,500m; that is, it should be able to operate like a satellite but covering larger areas (an almost futuristic challenge). Among other technologies, Received 17 November 2008; revision received 10 April 2009; accepted for publication 9 June 2009. Copyright © 2010 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved. Copies of this paper may be made for personal or internal use, on condition that the copier pay the $10.00 per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923; include the code 0021-8669/10 and $10.00 in correspondence with the CCC. ∗Research and Technology Europe, Environmentally Progressive Air Transport Team C/Canada Real de las Merinas 1-3, Building 4, Third Floor. Data available at http://www.boeing.com/news/releases/2008/q2/ 080403a_nr.html [retrieved April 2008]. Data available at http://www.boeing.com/news/releases/2008/q2/ 080421d_pr.html [retrieved April 2008]. JOURNAL OF AIRCRAFT Vol. 47, No. 6, November–December 2010

Abstract Handling large-scale software variability is still a challenge for many organizations. After decades of research on variability management concepts, many industrial organizations have introduced techniques known from research, but still lament that pure textbook approaches are not applicable or efficient. For instance, software product line engineering—an approach to systematically develop portfolios of products—is difficult to adopt given the high upfront investments; and even when adopted, organizations are challenged by evolving their complex product lines. Consequently, the research community now mainly focuses on re-engineering and evolution techniques for product lines; yet, understanding the current state of adoption and the industrial challenges for organizations is necessary to conceive effective techniques. In this multiple-case study, we analyze the current adoption of variability management techniques in twelve medium- to large-scale industrial cases in domains such as automotive, aerospace or railway systems. We identify the current state of variability management, emphasizing the techniques and concepts they adopted. We elicit the needs and challenges expressed for these cases, triangulated with results from a literature review. We believe our results help to understand the current state of adoption and shed light on gaps to address in industrial practice.

In the winter 2004 issue of AI Magazine, we reported Vulcan Inc.'s first step toward creating a question‐answering system called Digital Aristotle. The goal of that first step was to assess the state of the art in applied knowledge representation and reasoning (KRR) by asking AI experts to represent 70 pages from the advanced placement (AP) chemistry syllabus and to deliver knowledge‐based systems capable of answering questions from that syllabus. This article reports the next step toward realizing a Digital Aristotle: we present the design and evaluation results for a system called AURA, which enables domain experts in physics, chemistry, and biology to author a knowledge base and that then allows a different set of users to ask novel questions against that knowledge base. These results represent a substantial advance over what we reported in 2004, both in the breadth of covered subjects and in the provision of sophisticated technologies in knowledge representation and reasoning, natural language processing, and question answering to domain experts and novice users.

(1964). Generating a Variable from the Tail of the Normal Distribution. Technometrics: Vol. 6, No. 1, pp. 101-102.

A real fluid-stream filament axial-flow-compressor performance method is deduced from theory and statistics. The nonisentropic complete radial equilibrium-momentum equation is combined with the continuity, energy, and flow-process equations to yield a group of equations which is readily adaptable to solution on a digital computer. The real fluid effects, such as subsonic viscous losses and shocks at cascade entry, are deduced from statistics in terms of a blade-loading parameter. A program suitable for rapid calculations on a digital computer is presented in schematic form. A comparison between the deduced and the measured performances of an arbitrary stage is made. The correlation obtained indicates that the performance method is reliable.

In this paper, a formal language called the aircraft intent description language (AIDL) is proposed as a standard, interoperable means of describing and exchanging predicted aircraft trajectories in trajectory-based operations (TBO). The AIDL provides the necessary elements to unambiguously formulate aircraft intent, which, in the context of trajectory prediction, refers to the information that describes how the aircraft is to be operated within a certain time interval. By expressing aircraft intent according to the AIDL, it is ensured that each instance of aircraft intent defines a unique trajectory. It is anticipated that sharing aircraft intent information expressed in a structured and formal manner, e.g. according to the AIDL, can facilitate the synchronization of the predicted aircraft trajectories held by different automation systems in the context of TBO. The AIDL is characterized by an alphabet and a grammar. The definition of the alphabet and the grammar rules are based on a rigorous mathematical analysis of the trajectory computation process at the core of a TP. This analysis relies on a novel approach to modeling the trajectory computation process based on the theory of differential algebraic equations (DAEs). The paper presents the alphabet of the AIDL, which contains a set of instructions that capture the individual commands and guidance modes available to direct the motion of an aircraft in the ATM context. Then, the AIDL grammar rules, which define the possible combinations of the instructions in the alphabet, are defined and mathematically justified. The AIDL seeks to exploit the physical and mathematical foundations underlying the trajectory computation process to allow describing a priori (i.e. before a trajectory is actually computed) any possible motion behavior that can reasonably be elicited from an aircraft in the ATM context. The objective is that the AIDL encompasses all other methods and formats that may be used to describe aircraft intent, i.e. they would be subsets of the AIDL. The AIDL could thus be seen as a metalanguage for aircraft intent description, containing any other language that may be used to describe aircraft intent in the context of TBO.

As the technology of small aircraft systems continues to improve and the number of their possible applications grows, they are likely to be used more frequently in urban environments soon. Such environments are especially dangerous due to their high population and structural density in combination with challenging atmospheric conditions. Particularly the local wind field with its often unknown wind shear and turbulence characteristics endangers manned and unmanned aerial vehicles. Therefore, knowledge of the local turbulent wind is essential to ensure safety for the aircraft and the people onboard as well as on ground and should thus be incorporated in mission planning. This study presents a framework of how atmospheric flow analyses can contribute to safe drone operations in urban environments. High-resolution simulations are carried out, utilizing the large-eddy simulation model PALM, which can resolve turbulent flow and building structures down to the meter scale. Our results highlight the advantages and the necessity of using turbulence-resolving models to reasonably arrange a future drone operation network within cities. Because large-eddy simulations of urban environments are still computationally expensive, a meteorological data base for each urban setup should be established to obtain the relevant wind information for mission planning.

Interfacing artificial devices with the human brain is the central goal of neurotechnology. Yet, our imaginations are often limited by currently available paradigms and technologies. Suggestions for brain-machine interfaces have changed over time, along with the available technology. Mechanical levers and cable winches were used to move parts of the brain during the mechanical age. Sophisticated electronic wiring and remote control have arisen during the electronic age, ultimately leading to plug-and-play computer interfaces. Nonetheless, our brains are so complex that these visions, until recently, largely remained unreachable dreams. The general problem, thus far, is that most of our technology is mechanically and/or electrically engineered, whereas the brain is a living, dynamic entity. As a result, these worlds are difficult to interface with one another. Nanotechnology, which encompasses engineered solid-state objects and integrated circuits, excels at small length scales of single to a few hundred nanometers and, thus, matches the sizes of biomolecules, biomolecular assemblies, and parts of cells. Consequently, we envision nanomaterials and nanotools as opportunities to interface with the brain in alternative ways. Here, we review the existing literature on the use of nanotechnology in brain-machine interfaces and look forward in discussing perspectives and limitations based on the authors' expertise across a range of complementary disciplines─from neuroscience, engineering, physics, and chemistry to biology and medicine, computer science and mathematics, and social science and jurisprudence. We focus on nanotechnology but also include information from related fields when useful and complementary.

Metal nanoclusters (NCs) and their unique properties are increasing in importance and their applications are covering a wide range of areas. Their remarkable fluorescence properties and easy synthesis procedure and the possibility of functionalizing them for the detection of specific targets, such as biomarkers, make them a very interesting biosensing tool. Nowadays the detection of biomarkers related to different diseases is critical. In this context, NCs scaffolded within an appropriate molecule can be used to detect and quantify biomarkers through specific interactions and fluorescence properties of the NCs. These methods include analytical detection and biolocalization using imaging techniques. This review covers a selection of recent strategies to detect biomarkers related to diverse diseases (from infectious, inflammatory, or tumour origin) using fluorescent nanoclusters.

Abstract The results of this paper show that neural networks could be a very promising tool for reliability data analysis. Identifying the underlying distribution of a set of failure data and estimating its distribution parameters are necessary in reliability engineering studies. In general, either a chi‐square or a non‐parametric goodness‐of‐fit test is used in the distribution identification process which includes the pattern interpretation of the failure data histograms. However, those procedures can guarantee neither an accurate distribution identification nor a robust parameter estimation when small data samples are available. Basically, the graphical approach of distribution fitting is a pattern recognition problem and parameter estimation is a classification problem where neural networks have been proved to be a suitable tool. This paper presents an exploratory study of a neural network approach, validated by simulated experiments, for analysing small‐sample reliability data. A counter‐propagation network is used in classifying normal, uniform, exponential and Weibull distributions. A back‐propagation network is used in the parameter estimation of a two‐parameter Weibull distribution.