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time-optimal control

Ane Odden, Matthew J Denwood, Snorre Stuen, Lucy J Robertson, Antonio Ruiz, Inger Sofie Hamnes, Lisbeth Hektoen, Heidi L Enemark
Ovine Eimeria spp. infections cause reduced welfare, increased mortality, and substantial economic losses, and anticoccidials are crucial for their control. Recent reports of toltrazuril resistance in pigs, and anecdotal reports of reduced anticoccidial efficacy in lambs, necessitate evaluation of anticoccidial efficacy. Due to the substantial lifecycle differences between nematodes and coccidia, current WAAVP methods for assessing anthelmintic efficacy are not suitable for such evaluations. Faecal samples were collected from 8 pairs of twin lambs from 36 Norwegian sheep farms 6-8 days after turnout...
May 16, 2018: International Journal for Parasitology, Drugs and Drug Resistance
Tobey J Betthauser, Karly A Cody, Matthew D Zammit, Dhanabalan Murali, Alexander K Converse, Todd E Barnhart, Charles K Stone, Howard A Rowley, Sterling C Johnson, Bradley T Christian
Tau positron emission tomography (PET) imaging has potential for elucidating changes in the deposition of neuropathological tau aggregates that are occurring during the progression of Alzheimer's disease (AD). This work investigates in vivo kinetics, quantification strategies and imaging characteristics of a novel tau PET radioligand [18 F]MK-6240 in humans. Methods: Fifty-one individuals ranging from cognitively normal young controls to persons with dementia underwent T1-weighted magnetic resonance imaging (MRI), and [11 C]PiB and [18 F]MK-6240 PET imaging...
May 18, 2018: Journal of Nuclear Medicine: Official Publication, Society of Nuclear Medicine
Subrata Dev, Sakuntala Chatterjee
In response to a concentration gradient of chemoattractant, E. coli bacterium modulates the rotational bias of flagellar motors which control its run-and-tumble motion, to migrate towards regions of high chemoattractant concentration. Presence of stochastic noise in the biochemical pathway of the cell has important consequences on the switching mechanism of motor bias, which in turn affects the runs and tumbles of the cell in a significant way. We model the intracellular reaction network in terms of coupled time evolution of three stochastic variables-kinase activity, methylation level, and CheY-P protein level-and study the effect of methylation noise on the chemotactic performance of the cell...
March 2018: Physical Review. E
F M Leupold, M Malinowski, C Zhang, V Negnevitsky, A Cabello, J Alonso, J P Home
We use a single trapped-ion qutrit to demonstrate the quantum-state-independent violation of noncontextuality inequalities using a sequence of randomly chosen quantum nondemolition projective measurements. We concatenate 53×10^{6} sequential measurements of 13 observables, and unambiguously violate an optimal noncontextual bound. We use the same data set to characterize imperfections including signaling and repeatability of the measurements. The experimental sequence was generated in real time with a quantum random number generator integrated into our control system to select the subsequent observable with a latency below 50  μs, which can be used to constrain contextual hidden-variable models that might describe our results...
May 4, 2018: Physical Review Letters
Alexandre Goyon, Yannis Nicolas Francois, Olivier Colas, Alain Beck, Jean Luc Veuthey, Davy Guillarme
The determination of mAb critical quality attributes (CQA) is crucial for their successful application in health diseases. A generic CZE method was developed for the high-resolution separation of various mAb charge variants, which are often recognized as important CQA. A dynamic coating of the capillary was obtained with polyethylene oxide (PEO), whereas Bis-Tris allowed the analysis of mAbs under native conditions at pH 7.0. The effect of PEO and Bis-Tris concentrations, as well as the nature of the acidic counter ion on the method performance were systematically studied...
May 17, 2018: Electrophoresis
Burak Adnan Erkorkmaz, Onur Kırtel, Özlem Ateş Duru, Ebru Toksoy Öner
Levan polysaccharide is an industrially important natural polymer with unique properties and diverse high-value applications. However, current bottlenecks associated with its large-scale production need to be overcome by innovative approaches leading to economically viable processes. Besides many mesophilic levan producers, halophilic Halomonas smyrnensis cultures hold distinctive industrial potential and, for the first time with this study, the advantage of halophilicity is used and conditions for non-sterile levan production were optimized...
May 17, 2018: Bioprocess and Biosystems Engineering
James C Martin, Jennifer A Nichols
Fish, birds, and lizards sometimes perform locomotor activities with maximized muscle power. Whether humans maximize muscular power is unknown because current experimental techniques cannot be applied non-invasively. This study uses simulated muscle work loops to examine whether voluntary maximal cycling is characterized by maximized muscle power. The simulated work loops leverage experimentally measured joint angles, anatomically realistic muscle parameters (muscle-tendon lengths, velocities, and moment arms), and a published muscle model to calculate powers and forces for thirty-eight muscles...
May 17, 2018: Journal of Experimental Biology
Angella Musiimenta, Esther C Atukunda, Wilson Tumuhimbise, Emily E Pisarski, Melanie Tam, Monique A Wyatt, Norma C Ware, Jessica E Haberer
BACKGROUND: Wireless electronic adherence monitors can detect antiretroviral therapy (ART) adherence lapses and trigger interventions in real time, thus potentially avoiding unnecessary HIV viremia. Evidence about the acceptability and feasibility of these monitors and associated interventions, however, is limited. OBJECTIVE: The aim of this study was to assess the acceptability and feasibility of real-time adherence monitoring linked to text messaging (short message service, SMS) reminders and notifications to support adherence among individuals living with HIV who are taking ART in rural southwestern Uganda...
May 17, 2018: JMIR MHealth and UHealth
Adel Taha Abbas, Danil Yurievich Pimenov, Ivan Nikolaevich Erdakov, Mohamed Adel Taha, Mahmoud Sayed Soliman, Magdy Mostafa El Rayes
Magnesium alloys are widely used in aerospace vehicles and modern cars, due to their rapid machinability at high cutting speeds. A novel Edgeworth⁻Pareto optimization of an artificial neural network (ANN) is presented in this paper for surface roughness ( Ra ) prediction of one component in computer numerical control (CNC) turning over minimal machining time ( Tm ) and at prime machining costs ( C ). An ANN is built in the Matlab programming environment, based on a 4-12-3 multi-layer perceptron (MLP), to predict Ra , Tm , and C , in relation to cutting speed, vc , depth of cut, ap , and feed per revolution, fr ...
May 16, 2018: Materials
Weinan Gao, Zhong-Ping Jiang
This paper proposes a novel data-driven control approach to address the problem of adaptive optimal tracking for a class of nonlinear systems taking the strict-feedback form. Adaptive dynamic programming (ADP) and nonlinear output regulation theories are integrated for the first time to compute an adaptive near-optimal tracker without any a priori knowledge of the system dynamics. Fundamentally different from adaptive optimal stabilization problems, the solution to a Hamilton-Jacobi-Bellman (HJB) equation, not necessarily a positive definite function, cannot be approximated through the existing iterative methods...
June 2018: IEEE Transactions on Neural Networks and Learning Systems
Zhanshan Wang, Lei Liu, Yanming Wu, Huaguang Zhang
This paper investigates the problem of optimal fault-tolerant control (FTC) for a class of unknown nonlinear discrete-time systems with actuator fault in the framework of adaptive critic design (ACD). A pivotal highlight is the adaptive auxiliary signal of the actuator fault, which is designed to offset the effect of the fault. The considered systems are in strict-feedback forms and involve unknown nonlinear functions, which will result in the causal problem. To solve this problem, the original nonlinear systems are transformed into a novel system by employing the diffeomorphism theory...
June 2018: IEEE Transactions on Neural Networks and Learning Systems
Tohid Sardarmehni, Ali Heydari
Two approximate solutions for optimal control of switched systems with autonomous subsystems and continuous-time dynamics are presented. The first solution formulates a policy iteration (PI) algorithm for the switched systems with recursive least squares. To reduce the computational burden imposed by the PI algorithm, a second solution, called single loop PI, is presented. Online and concurrent training algorithms are discussed for implementing each solution. At last, effectiveness of the presented algorithms is evaluated through numerical simulations...
June 2018: IEEE Transactions on Neural Networks and Learning Systems
Yongliang Yang, Hamidreza Modares, Donald C Wunsch, Yixin Yin
This paper develops optimal control protocols for the distributed output synchronization problem of leader-follower multiagent systems with an active leader. Agents are assumed to be heterogeneous with different dynamics and dimensions. The desired trajectory is assumed to be preplanned and is generated by the leader. Other follower agents autonomously synchronize to the leader by interacting with each other using a communication network. The leader is assumed to be active in the sense that it has a nonzero control input so that it can act independently and update its control to keep the followers away from possible danger...
June 2018: IEEE Transactions on Neural Networks and Learning Systems
Bo Fan, Qinmin Yang, Xiaoyu Tang, Youxian Sun
In this paper, a novel robust adaptive dynamic programming (RADP)-based control strategy is presented for the optimal control of a class of output-constrained continuous-time unknown nonlinear systems. Our contribution includes a step forward beyond the usual optimal control result to show that the output of the plant is always within user-defined bounds. To achieve the new results, an error transformation technique is first established to generate an equivalent nonlinear system, whose asymptotic stability guarantees both the asymptotic stability and the satisfaction of the output restriction of the original system...
June 2018: IEEE Transactions on Neural Networks and Learning Systems
Bahare Kiumarsi, Kyriakos G Vamvoudakis, Hamidreza Modares, Frank L Lewis
This paper reviews the current state of the art on reinforcement learning (RL)-based feedback control solutions to optimal regulation and tracking of single and multiagent systems. Existing RL solutions to both optimal and control problems, as well as graphical games, will be reviewed. RL methods learn the solution to optimal control and game problems online and using measured data along the system trajectories. We discuss Q-learning and the integral RL algorithm as core algorithms for discrete-time (DT) and continuous-time (CT) systems, respectively...
June 2018: IEEE Transactions on Neural Networks and Learning Systems
Ming Wu, Xinyi Lin, Xionghong Tan, Jiong Li, Zuwu Wei, Da Zhang, Youshi Zheng, Ai-Xian Zheng, Bixing Zhao, Yongyi Zeng, Xiaolong Liu, Jingfeng Liu
Pre-release of RNA molecules than chemotherapeutic drugs with a sufficient interval is a vital prerequisite for RNA/drug co-delivery strategy to overcome multidrug resistance (MDR) of cancer cells, but how to precisely control their release at different time points is still a grand challenge up to now. This study aims to on-demand remotely manipulate RNA and drug release in real time through single delivery system to sequentially play their respective roles for optimizing and enhancing their synergistic antitumor effects...
May 17, 2018: ACS Applied Materials & Interfaces
Chun-Chin Wang, Siân Moorhouse, Chris Stain, Mark Seymour, Ellen Green, Steven Penfield, Julian Moger
Providing sufficient, healthy food for the increasing global population is putting a great deal of pressure on the agrochemical industry to maximise crop yields without sustaining environmental damage. The growth and yield of every plant with sexual reproduction, depends on germination and emergence of sown seeds, which is affected greatly by seed disease. This can be most effectively controlled by treating seeds with pesticides before they are sown. An effective seed coating treatment requires a high surface coverage and adhesion of active ingredients onto the seed surface and the addition of adhesive agents in coating formulations plays a key role in achieving this...
May 17, 2018: Journal of Biophotonics
Alejandro Gómez-Mejia, Gustavo Gámez, Stephanie Hirschmann, Viktor Kluger, Hermann Rath, Sebastian Böhm, Franziska Voss, Niamatullah Kakar, Lothar Petruschka, Uwe Völker, Reinhold Brückner, Ulrike Mäder, Sven Hammerschmidt
Streptococcus pneumoniae two-component regulatory systems (TCS) enable adaptation and ensure its maintenance in host environments. This study deciphers the impact of TCS08 on pneumococcal gene expression and its role in metabolic and pathophysiological processes. Transcriptome analysis and real-time PCR demonstrated a regulatory effect of TCS08 on genes involved mainly in environmental information processing, intermediary metabolism, and colonization by S. pneumoniae D39 and TIGR4. Striking examples are genes for fatty acid biosynthesis, genes of the arginine deiminase system, and the psa operon encoding the manganese ABC transport system...
June 27, 2018: MSphere
Ying Yuan, Ruitao Lin, Daniel Li, Lei Nie, Katherine E Warren
Late-onset toxicity is common for novel molecularly targeted agents and immunotherapy. It causes major logistic difficulty for existing adaptive phase I trial designs, which require the observance of toxicity early enough to apply dose escalation rules for new patients. The same logistic difficulty arises when the accrual is rapid. We propose the time-to-event Bayesian optimal interval (TITE-BOIN) design to accelerate phase I trials by allowing for real-time dose assignment decisions for new patients while some enrolled patients' toxicity data are still pending...
May 16, 2018: Clinical Cancer Research: An Official Journal of the American Association for Cancer Research
Eloise Pariset, Catherine Pudda, François Boizot, Nicolas Verplanck, Frédéric Revol-Cavalier, Jean Berthier, Aurélie Thuaire, Vincent Agache
Particle separation in microfluidic devices is a common problematic for sample preparation in biology. Deterministic lateral displacement (DLD) is efficiently implemented as a size-based fractionation technique to separate two populations of particles around a specific size. However, real biological samples contain components of many different sizes and a single DLD separation step is not sufficient to purify these complex samples. When connecting several DLD modules in series, pressure balancing at the DLD outlets of each step becomes critical to ensure an optimal separation efficiency...
2018: PloS One
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