An investigation of a close-coupled canard as a direct side-force generator on a fighter model at Mach numbers from 0.40 to 0.90

The canard panels had 5 deg of dihedral and were deflected differentially or individually over an incidence range from 10 deg to -10 deg and a model angle-of-attack range from -4 deg to 15 deg. Significant side forces were generated in a transonic tunnel by differential and single canard-panel deflections over the Mach number and angle-of-attack ranges. The yawing moment resulting from the forward location of the generated side force would necessitate a vertical tail/rudder trim force which would augment the forebody side force and be of comparable magnitude. Incremental side forces, yawing moments, lift, and pitching moments due to single canard-panel deflections were additive; that is, their sums were essentially the same as the forces and moments produced by differential canard-panel deflections of the same magnitude. Differential and single canard-panel deflections produced negligible rolling moments over the Mach number and angle-of-attack ranges

A genetic algorithm for the design of a fuzzy controller for active queue management

Active queue management (AQM) policies are those policies of router queue management that allow for the detection of network congestion, the notification of such occurrences to the hosts on the network borders, and the adoption of a suitable control policy. This paper proposes the adoption of a fuzzy proportional integral (FPI) controller as an active queue manager for Internet routers. The analytical design of the proposed FPI controller is carried out in analogy with a proportional integral (PI) controller, which recently has been proposed for AQM. A genetic algorithm is proposed for tuning of the FPI controller parameters with respect to optimal disturbance rejection. In the paper the FPI controller design metodology is described and the results of the comparison with random early detection (RED), tail drop, and PI controller are presented

Distributed XQuery

XQuery is increasingly being used for ad-hoc integration of heterogeneous data sources that are logically mapped to XML. For example, scientists need to query multiple scientific databases, which are distributed over a large geographic area, and it is possible to use XQuery for that. However, the language currently supports only the data shipping query evaluation model (through the document() function): it fetches all data sources to a single server, then runs the query there. This is a major limitation for many applications, especially when some data sources are very large, or when a data source is only a virtual XML view over some other logical data model. We propose here a simple extension to XQuery that allows query shipping to be expressed in the language, in addition to data shipping

Chain Reduction for Binary and Zero-Suppressed Decision Diagrams

Chain reduction enables reduced ordered binary decision diagrams (BDDs) and zero-suppressed binary decision diagrams (ZDDs) to each take advantage of the others' ability to symbolically represent Boolean functions in compact form. For any Boolean function, its chain-reduced ZDD (CZDD) representation will be no larger than its ZDD representation, and at most twice the size of its BDD representation. The chain-reduced BDD (CBDD) of a function will be no larger than its BDD representation, and at most three times the size of its CZDD representation. Extensions to the standard algorithms for operating on BDDs and ZDDs enable them to operate on the chain-reduced versions. Experimental evaluations on representative benchmarks for encoding word lists, solving combinatorial problems, and operating on digital circuits indicate that chain reduction can provide significant benefits in terms of both memory and execution time

How Accurately Can We Measure the Reconnection Rate E M for the MMS Diffusion Region Event of 11 July 2017?

We investigate the accuracy with which the reconnection electric field E M can be determined from in situ plasma data. We study the magnetotail electron diffusion region observed by National Aeronautics and Space Administration's Magnetospheric Multiscale (MMS) on 11 July 2017 at 22:34 UT and focus on the very large errors in E M that result from errors in an L M N boundary normal coordinate system. We determine several L M N coordinates for this MMS event using several different methods. We use these M axes to estimate E M. We find some consensus that the reconnection rate was roughly E M = 3.2 ± 0.6 mV/m, which corresponds to a normalized reconnection rate of 0.18 ± 0.035. Minimum variance analysis of the electron velocity (MVA-v e), MVA of E, minimization of Faraday residue, and an adjusted version of the maximum directional derivative of the magnetic field (MDD-B) technique all produce reasonably similar coordinate axes. We use virtual MMS data from a particle-in-cell simulation of this event to estimate the errors in the coordinate axes and reconnection rate associated with MVA-v e and MDD-B. The L and M directions are most reliably determined by MVA-v e when the spacecraft observes a clear electron jet reversal. When the magnetic field data have errors as small as 0.5% of the background field strength, the M direction obtained by MDD-B technique may be off by as much as 35°. The normal direction is most accurately obtained by MDD-B. Overall, we find that these techniques were able to identify E M from the virtual data within error bars ≥20%

Inactive alleles of cytochrome P450 2C19 may be positively selected in human evolution Genome evolution and evolutionary systems biology

© 2014 Janha et al.; licensee BioMed Central Ltd.Background: Cytochrome P450 CYP2C19 metabolizes a wide range of pharmacologically active substances and a relatively small number of naturally occurring environmental toxins. Poor activity alleles of CYP2C19 are very frequent worldwide, particularly in Asia, raising the possibility that reduced metabolism could be advantageous in some circumstances. The evolutionary selective forces acting on this gene have not previously been investigated. We analyzed CYP2C19 genetic markers from 127 Gambians and on 120 chromosomes from Yoruba, Europeans and Asians (Japanese + Han Chinese) in the Hapmap database. Haplotype breakdown was explored using bifurcation plots and relative extended haplotype homozygosity (REHH). Allele frequency differentiation across populations was estimated using the fixation index (FST) and haplotype diversity with coalescent models. Results: Bifurcation plots suggested conservation of alleles conferring slow metabolism (CYP2C19∗2 and ∗3). REHH was high around CYP2C19∗2 in Yoruba (REHH 8.3, at 133.3 kb from the core) and to a lesser extent in Europeans (3.5, at 37.7 kb) and Asians (2.8, at -29.7 kb). FST at the CYP2C19 locus was low overall (0.098). CYP2C19∗3 was an FST outlier in Asians (0.293), CYP2C19 haplotype diversity ST is low at the CYP2C19 locus, suggesting balancing selection overall. The biological factors responsible for these selective pressures are currently unknown. One possible explanation is that early humans were exposed to a ubiquitous novel toxin activated by CYP2C19. The genetic adaptation took place within the last 10,000 years which coincides with the development of systematic agricultural practices.This work was supported by the Medical Research Council Unit The Gambia and the European and Developing Countries Clinical Trials Partnership [grant number CG_ta_05_40204_018]

A Framework for XML-based Integration of Data, Visualization and Analysis in a Biomedical Domain

Biomedical data are becoming increasingly complex and heterogeneous in nature. The data are stored in distributed information systems, using a variety of data models, and are processed by increasingly more complex tools that analyze and visualize them. We present in this paper our framework for integrating biomedical research data and tools into a unique Web front end. Our framework is applied to the University of Washington’s Human Brain Project. Specifically, we present solutions to four integration tasks: definition of complex mappings from relational sources to XML, distributed XQuery processing, generation of heterogeneous output formats, and the integration of heterogeneous data visualization and analysis tools

Liquid chromatography-tandem mass spectrometry - Application in the clinical laboratory

This review provides a concise survey of liquid chromatography tandem mass spectrometry (LCTMS) as an emerging technology in clinical chemistry. The combination of two mass spectrometers with an interposed collision cell characterizes LCTMS as an analytical technology on its own and not just as a more specific detector for HPLC compared with conventional techniques. In LCTMS, liquid chromatography is rather used for sample preparation but not for complete resolution of compounds of interest. The instrument technology of LCTMS is complex and comparatively expensive; however, in routine use, methods are far more rugged compared to conventional chromatographic techniques and enable highthroughput analyses with very limited manual handling steps. Moreover, compared to both gas chromatographymass spectrometry (GCMS) and conventional HPLC techniques, LCTMS is substantially more versatile with respect to the spectrum of analyzable compounds. For these reasons it is likely that LCTMS will gain far more widespread use in the clinical laboratory than HPLC and GCMS ever did. In this article, the key features of LCTMS are described, method development is explained, typical fields of application are discussed, and personal experiences are related

Zero gravity and cardiovascular homeostasis. The relationship between endogenous hyperprolactinemia and plasma aldosterone

Prolactin, thyrotropin and aldosterone were measured by radioimmunoassay and plasma renin activity by the radioimmunoassay of angiotensin I in normal women before and after the intravenous injection of 200 micrograms of thyrotropin releasing hormone. Prolactin increased at 15 minutes following thyrotropin releasing hormone. Plasma renin activity was not different from control levels during the first hour following the administration of thyrotropin releasing hormone, nor did the plasma aldosterone concentration differ significantly from the control levels during this period. However, with upright posture, an increase in aldosterone and in plasma renin activity was noted, demonstrating a normal capacity to secrete aldosterone. Similarly, no change in aldosterone was seen in 9 patients with primary hypothyroidism given thyrotropin releasing hormone, despite the fact that the increase in prolactin was greater than normal. These data demonstrate that acutely or chronically elevated serum prolactin levels do not result in increased plasma aldosterone levels in humans

Data-Driven Process Mining Framework for Risk Management in Construction Projects

Construction Projects are exposed to numerous risks due to their complex and uncertain nature, threatening the realization of the project objectives. However, Risk Management (RM) is a less efficient realm in the industry than other knowledge areas given the manual and time-consuming nature of its processes and reliance on experience-based subjective judgments. This research proposes a Process Mining-based framework for detecting, monitoring, and analysing risks, improving the RM processes using evidence-based event logs, such as Risk Registers and Change-Logs within previous projects' documents. Process Mining (PM) is a data- driven methodology, well established in other industries, that benefits from Artificial Intelligence(AI) to identify trends and complex patterns among event logs. It performs well while intaking large amounts of data and predicting future outputs based on historical data. Therefore, this research proposes a Bayesian Network (BN)-based Process Mining framework for graphical representation of the RM processes, intaking the conditional dependence structure between Risk variables, and continuous and automated risk identification and management. A systematic literature review on RM, PM, and AI forms the framework theoretical basis and delineates the integration areas for practical implementation. The proposed framework is applied to a small database of 20 projects as the case study, the scope of which can be tailored to the enterprise requirements. It contributes to creating a holistic theoretical foundation and practical workflow applicable to construction projects and filling the knowledge gap in inefficient and discrete conventional RM methods, which ignore the interdependencies between risk variables and assess each risk isolated