4,213 research outputs found
Melarsoprol-Free Drug Combinations for Second-Stage Gambian Sleeping Sickness: The Way to Go.
Dynamic task allocation for a man-machine symbiotic system
This report presents a methodological approach to the dynamic allocation of tasks in a man-machine symbiotic system in the context of dexterous manipulation and teleoperation. This report addresses a symbiotic system containing two symbiotic partners which work toward controlling a single manipulator arm for the execution of a series of sequential manipulation tasks. It is proposed that an automated task allocator use knowledge about the constraints/criteria of the problem, the available resources, the tasks to be performed, and the environment to dynamically allocate task recommendations for the man and the machine. The presentation of the methodology includes discussions concerning the interaction of the knowledge areas, the flow of control, the necessary communication links, and the replanning of the task allocation. Examples of task allocation are presented to illustrate the results of this methodolgy
Paying Positive to Go Negative: Advertisers' Competition and Media Reports
This paper analyzes a two-sided market for news where advertisers may pay a media outlet to conceal negative information about the quality of their own product (paying positive to avoid negative) and/or to disclose negative information about the quality of their competitors' products (paying positive to go negative). We show that whether advertisers have negative consequences on the accuracy of news reports or not ultimately depends on the extent of correlation among advertisers' products. Specifically, the lower the correlation among the qualities of the advertisers' products, the (weakly) higher the accuracy of the media outlet' reports. Moreover, when advertisers' products are correlated, a higher degree of competition in the market of the advertisers' products may decrease the accuracy of the media outlet's reports.
The 3-D world modeling with updating capability based on combinatorial geometry
A 3-D world modeling technique using range data is discribed. Range data quantify the distances from the sensor focal plane to the object surface, i.e., the 3-D coordinates of discrete points on the object surface are known. The approach proposed herein for 3-D world modeling is based on the Combinatorial Geometry (CG) method which is widely used in Monte Carlo particle transport calculations. First, each measured point on the object surface is surrounded by a small sphere with a radius determined by the range to that point. Then, the 3-D shapes of the visible surfaces are obtained by taking the (Boolean) union of all the spheres. The result is an unambiguous representation of the object's boundary surfaces. The pre-learned partial knowledge of the environment can be also represented using the CG Method with a relatively small amount of data. Using the CG type of representation, distances in desired directions to boundary surfaces of various objects are efficiently calculated. This feature is particularly useful for continuously verifying the world model against the data provided by a range finder, and for integrating range data from successive locations of the robot during motion. The efficiency of the proposed approach is illustrated by simulations of a spherical robot in a 3-D room in the presence of moving obstacles and inadequate prelearned partial knowledge of the environment
Fast-convergent fault detection and isolation in a class of nonlinear uncertain systems
The present work proposes a fast-convergent fault detection and isolation (FDI) scheme for linear systems affected by model uncertainties, such as unknown inputs or unbounded nonlinearities. The finite-time convergence is attained by transforming the I/O signals through Volterra operators with suitably designed kernel functions. A novel feature of the proposed approach is the exploitation of a system decomposition that allows removing the effect of intractable uncertainties while recasting the system dynamics in a form applicable for Volterra operators to achieve non-asymptotic estimation. Remarkably, the proposed approach can reconstruct the state variables of the system in an arbitrarily short time and the fault can be diagnosed efficiently by imposing detection and isolation thresholds on transformed signals. The detectability and isolability of the fault are also characterized. The proposed FDI scheme is applied in simulation to a web process system to diagnose the presence of actuator faults. Simulation results confirm the effectiveness of the proposed scheme in two scenarios with nonlinear uncertainties. Furthermore, comparisons are made between the proposed method and a Sliding Mode Control (SMC) method in terms of estimation performance and computational complexity
Eflornithine is Safer Than Melarsoprol for the Treatment of Second-Stage Trypanosoma Brucei Gambiense Human African Trypanosomiasis.
Patients with second-stage human African trypanosomiasis treated with eflornithine (n = 251) in 2003 in Kiri, southern Sudan, had an adjusted relative risk of death of 0.2 and experienced significantly fewer cutaneous and neurological adverse effects than did patients who were treated with melarsoprol in 2001 and 2002 (n = 708)
Extracellular vesicles derived from tumour cells as a trigger of energy crisis in the skeletal muscle
Premier bilan du projet de renforcement du dispositif addictologique de lâOuest vaudois : Ă©valuation de la pĂ©riode 2015-2016
Objectifs et mĂ©thode : A la demande du Service de la santĂ© publique (SSP), un premier Ă©tat des lieux du projet a Ă©tĂ© menĂ© en juin 2016, soit dix-huit mois aprĂšs son dĂ©marrage, afin dâexplorer les activitĂ©s mises en oeuvre, les difficultĂ©s rencontrĂ©es et les lacunes constatĂ©es lors la mise en place de la collaboration et afin de proposer quelques pistes dâajustement du dispositif.
Une Ă©tude de cas descriptive a Ă©tĂ© rĂ©alisĂ©e au moyen dâentretiens semi-dirigĂ©s avec le responsable du PĂŽle addictologique et le directeur dâEdS et dâune analyse de documents relatifs au projet. Lâanalyse des donnĂ©es a portĂ© dâune part sur lâimplantation du projet en termes dâadhĂ©sion au protocole initial, dâexposition et de qualitĂ© et dâautre part sur les dimensions normative (vision globale du projet), fonctionnelle (outils et procĂ©dures rĂ©gissant les rĂŽles et les responsabilitĂ©s) et clinique (outils et procĂ©dures dĂ©finissant la prise en charge et lâaccompagnement des patients) de la collaboration entre EdS et le PĂŽle addictologique
Fast-convergent Fault Detection and Isolation in an Uncertain Scenario
Abstract\u2014In this paper, a fast-convergent fault detection and
isolation architecture is proposed for linear MIMO continuoustime
systems. By exploiting a system decomposition technique
and making use of kernel-based deadbeat estimators, the
state variables can be estimated in a non-asymptotic way.
Estimation residuals are then defined to detect the occurrence
of a fault and identify the occurring fault function after fault
detection. In the noisy scenario, thresholds are defined for the
residual to distinguish the effect of the noise from that of
the fault. Numerical examples are included to characterize the
effectiveness of the proposed FDI architectur
Distributed fault detection and isolation for interconnected systems: a non-asymptotic kernel-based approach
In this paper, a novel framework is proposed for deadbeat distributed Fault Detection and Isolation (FDI) of large-scale continuous-time LTI dynamic systems. The monitored system is composed of several subsystems which are linearly interconnected with unknown parameterization. Each subsystem is monitored by a local diagnoser based on the measured local output, local inputs and the interconnection variables from the neighboring subsystems. The local FDI decision is based on two non-asymptotic state-parameter estimators using Volterra integral operators which eliminate the effect of the unknown initial conditions so that the estimates converge to the true value in a deadbeat manner and therefore the fault diagnosis can be achieved in finite time. Moreover, the unknown interconnection parameters and the unknown fault parameters are simultaneously estimated. Numerical examples are included to show the effectiveness of the proposed FDI architecture
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