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https://www.readbyqxmd.com/read/29671385/artificial-neural-network-modeling-for-organic-and-total-nitrogen-removal-of-aerobic-granulation-under-steady-state-condition
#1
H Gong, R Pishgar, J H Tay
Aerobic granulation is a recent technology with high level of complexity and sensitivity to environmental and operational conditions. Artificial neural networks (ANN), computational tools capable of describing complex nonlinear systems, are the best fit to simulate aerobic granular bioreactors. In this study, two feedforward backpropagation ANN models were developed to predict chemical oxygen demand (COD) (Model I) and total nitrogen (TN) removal efficiencies (Model II) of aerobic granulation technology under steady-state condition...
April 19, 2018: Environmental Technology
https://www.readbyqxmd.com/read/29481179/r%C3%A3-nyi-entropies-from-random-quenches-in-atomic-hubbard-and-spin-models
#2
A Elben, B Vermersch, M Dalmonte, J I Cirac, P Zoller
We present a scheme for measuring Rényi entropies in generic atomic Hubbard and spin models using single copies of a quantum state and for partitions in arbitrary spatial dimensions. Our approach is based on the generation of random unitaries from random quenches, implemented using engineered time-dependent disorder potentials, and standard projective measurements, as realized by quantum gas microscopes. By analyzing the properties of the generated unitaries and the role of statistical errors, with respect to the size of the partition, we show that the protocol can be realized in existing quantum simulators and used to measure, for instance, area law scaling of entanglement in two-dimensional spin models or the entanglement growth in many-body localized systems...
February 2, 2018: Physical Review Letters
https://www.readbyqxmd.com/read/29361781/an-inverse-neural-controller-based-on-the-applicability-domain-of-rbf-network-models
#3
Alex Alexandridis, Marios Stogiannos, Nikolaos Papaioannou, Elias Zois, Haralambos Sarimveis
This paper presents a novel methodology of generic nature for controlling nonlinear systems, using inverse radial basis function neural network models, which may combine diverse data originating from various sources. The algorithm starts by applying the particle swarm optimization-based non-symmetric variant of the fuzzy means (PSO-NSFM) algorithm so that an approximation of the inverse system dynamics is obtained. PSO-NSFM offers models of high accuracy combined with small network structures. Next, the applicability domain concept is suitably tailored and embedded into the proposed control structure in order to ensure that extrapolation is avoided in the controller predictions...
January 22, 2018: Sensors
https://www.readbyqxmd.com/read/29341752/tensor-network-simulations-of-the-surface-code-under-realistic-noise
#4
Andrew S Darmawan, David Poulin
The surface code is a many-body quantum system, and simulating it in generic conditions is computationally hard. While the surface code is believed to have a high threshold, the numerical simulations used to establish this threshold are based on simplified noise models. We present a tensor-network algorithm for simulating error correction with the surface code under arbitrary local noise. We use this algorithm to study the threshold and the subthreshold behavior of the amplitude damping and systematic rotation channels...
July 28, 2017: Physical Review Letters
https://www.readbyqxmd.com/read/29122452/estimated-landmark-calibration-of-biomechanical-models-for-inverse-kinematics
#5
Ursula Trinler, Richard Baker
Inverse kinematics is emerging as the optimal method in movement analysis to fit a multi-segment biomechanical model to experimental marker positions. A key part of this process is calibrating the model to the dimensions of the individual being analysed which requires scaling of the model, pose estimation and localisation of tracking markers within the relevant segment coordinate systems. The aim of this study is to propose a generic technique for this process and test a specific application to the OpenSim model Gait2392...
January 2018: Medical Engineering & Physics
https://www.readbyqxmd.com/read/28991730/closed-loop-vagus-nerve-stimulation-based-on-state-transition-models
#6
Hector Manuel Romero Ugalde, Virginie Le Rolle, Jean-Luc Bonnet, Christine Henry, Philippe Mabo, Guy Carrault, Alfredo I Hernandez
OBJECTIVE: Vagus nerve stimulation (VNS) is a potential therapeutic approach in a number of clinical applications. Although VNS is commonly delivered in an open-loop approach, it is now recognized that closed-loop stimulation may be necessary to optimize the therapy. In this paper, we propose an original, generic closed-loop control system which can be readily integrated into an implantable device and allows for the adaptive modulation of multiple VNS parameters. METHODS: The proposed control method consists of a state transition model (STM), in which each state represents a set of VNS parameters, and a state transition algorithm that optimally selects the best STM state, minimizing the error between an observed physiological variable and a given target value...
October 5, 2017: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/28989729/adaptive-recursive-algorithm-for-optimal-weighted-suprathreshold-stochastic-resonance
#7
Liyan Xu, Fabing Duan, Xiao Gao, Derek Abbott, Mark D McDonnell
Suprathreshold stochastic resonance (SSR) is a distinct form of stochastic resonance, which occurs in multilevel parallel threshold arrays with no requirements on signal strength. In the generic SSR model, an optimal weighted decoding scheme shows its superiority in minimizing the mean square error (MSE). In this study, we extend the proposed optimal weighted decoding scheme to more general input characteristics by combining a Kalman filter and a least mean square (LMS) recursive algorithm, wherein the weighted coefficients can be adaptively adjusted so as to minimize the MSE without complete knowledge of input statistics...
September 2017: Royal Society Open Science
https://www.readbyqxmd.com/read/28950188/strengths-and-limitations-of-early-warning-scores-a-systematic-review-and-narrative-synthesis
#8
REVIEW
C L Downey, W Tahir, R Randell, J M Brown, D G Jayne
BACKGROUND: Early warning scores are widely used to identify deteriorating patients. Whilst their ability to predict clinical outcomes has been extensively reviewed, there has been no attempt to summarise the overall strengths and limitations of these scores for patients, staff and systems. This review aims to address this gap in the literature to guide improvements for the optimization of patient safety. METHODS: A systematic review was conducted of MEDLINE® , PubMed, CINAHL and The Cochrane Library in September 2016...
November 2017: International Journal of Nursing Studies
https://www.readbyqxmd.com/read/28891201/predicting-drug-concentration-time-profiles-in-multiple-cns-compartments-using-a-comprehensive-physiologically-based-pharmacokinetic-model
#9
Yumi Yamamoto, Pyry A Välitalo, Dymphy R Huntjens, Johannes H Proost, An Vermeulen, Walter Krauwinkel, Margot W Beukers, Dirk-Jan van den Berg, Robin Hartman, Yin Cheong Wong, Meindert Danhof, John G C van Hasselt, Elizabeth C M de Lange
Drug development targeting the central nervous system (CNS) is challenging due to poor predictability of drug concentrations in various CNS compartments. We developed a generic physiologically based pharmacokinetic (PBPK) model for prediction of drug concentrations in physiologically relevant CNS compartments. System-specific and drug-specific model parameters were derived from literature and in silico predictions. The model was validated using detailed concentration-time profiles from 10 drugs in rat plasma, brain extracellular fluid, 2 cerebrospinal fluid sites, and total brain tissue...
November 2017: CPT: Pharmacometrics & Systems Pharmacology
https://www.readbyqxmd.com/read/28048428/su-f-t-540-comprehensive-fluence-delivery-optimization-with-multileaf-collimation
#10
S Weppler, P McGeachy, J Villarreal-Barajas, R Khan
PURPOSE: Multileaf collimator (MLC) leaf sequencing is performed via commercial black-box implementations, on which a user has limited to no access. We have developed an explicit, generic MLC sequencing model to serve as a tool for future investigations of fluence map optimization, fluence delivery optimization, and rotational collimator delivery methods. METHODS: We have developed a novel, comprehensive model to effectively account for a variety of transmission and penumbra effects previously treated on an ad hoc basis in the literature...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/27991457/real-time-auto-adaptive-margin-generation-for-mlc-tracked-radiotherapy
#11
M Glitzner, M F Fast, B Denis de Senneville, S Nill, U Oelfke, J J W Lagendijk, B W Raaymakers, S P M Crijns
In radiotherapy, abdominal and thoracic sites are candidates for performing motion tracking. With real-time control it is possible to adjust the multileaf collimator (MLC) position to the target position. However, positions are not perfectly matched and position errors arise from system delays and complicated response of the electromechanic MLC system. Although, it is possible to compensate parts of these errors by using predictors, residual errors remain and need to be compensated to retain target coverage...
January 7, 2017: Physics in Medicine and Biology
https://www.readbyqxmd.com/read/27864744/a-generic-multi-compartmental-cns-distribution-model-structure-for-9-drugs-allows-prediction-of-human-brain-target-site-concentrations
#12
Yumi Yamamoto, Pyry A Välitalo, Dirk-Jan van den Berg, Robin Hartman, Willem van den Brink, Yin Cheong Wong, Dymphy R Huntjens, Johannes H Proost, An Vermeulen, Walter Krauwinkel, Suruchi Bakshi, Vincent Aranzana-Climent, Sandrine Marchand, Claire Dahyot-Fizelier, William Couet, Meindert Danhof, Johan G C van Hasselt, Elizabeth C M de Lange
PURPOSE: Predicting target site drug concentration in the brain is of key importance for the successful development of drugs acting on the central nervous system. We propose a generic mathematical model to describe the pharmacokinetics in brain compartments, and apply this model to predict human brain disposition. METHODS: A mathematical model consisting of several physiological brain compartments in the rat was developed using rich concentration-time profiles from nine structurally diverse drugs in plasma, brain extracellular fluid, and two cerebrospinal fluid compartments...
February 2017: Pharmaceutical Research
https://www.readbyqxmd.com/read/27853969/preventable-medical-errors-driven-modeling-of-medical-best-practice-guidance-systems
#13
Andrew Y-Z Ou, Yu Jiang, Po-Liang Wu, Lui Sha, Richard B Berlin
In a medical environment such as Intensive Care Unit, there are many possible reasons to cause errors, and one important reason is the effect of human intellectual tasks. When designing an interactive healthcare system such as medical Cyber-Physical-Human Systems (CPHSystems), it is important to consider whether the system design can mitigate the errors caused by these tasks or not. In this paper, we first introduce five categories of generic intellectual tasks of humans, where tasks among each category may lead to potential medical errors...
January 2017: Journal of Medical Systems
https://www.readbyqxmd.com/read/27828532/investigation-of-solar-noise-impact-on-the-performance-of-underwater-wireless-optical-communication-links
#14
Tasnim Hamza, Mohammad-Ali Khalighi, Salah Bourennane, Pierre Léon, Jan Opderbecke
We investigate the effect of environmental noise, caused by solar radiations under water, on the performance of underwater wireless optical communication (UWOC) systems. Presenting an analytical and generic model for this noise, we examine its impact on the link performance in terms of the bit error rate (BER). This study is conducted for different photo-detector types in the aim of highlighting practical limitations of establishing UWOC links in the presence of subsea solar noise. We show how the solar noise can impact the performance of UWOC links for relatively low operation depths...
October 31, 2016: Optics Express
https://www.readbyqxmd.com/read/27723992/real-time-inverse-kinematics-and-inverse-dynamics-for-lower-limb-applications-using-opensim
#15
C Pizzolato, M Reggiani, L Modenese, D G Lloyd
Real-time estimation of joint angles and moments can be used for rapid evaluation in clinical, sport, and rehabilitation contexts. However, real-time calculation of kinematics and kinetics is currently based on approximate solutions or generic anatomical models. We present a real-time system based on OpenSim solving inverse kinematics and dynamics without simplifications at 2000 frame per seconds with less than 31.5 ms of delay. We describe the software architecture, sensitivity analyses to minimise delays and errors, and compare offline and real-time results...
March 2017: Computer Methods in Biomechanics and Biomedical Engineering
https://www.readbyqxmd.com/read/27633735/a-generalized-method-for-controlling-end-tidal-respiratory-gases-during-nonsteady-physiological-conditions
#16
Shawn M O'Connor, Jeremy D Wong, J Maxwell Donelan
While forcing of end-tidal gases by regulating inspired gas concentrations is a common technique for studying cardiorespiratory physiology, independently controlling end-tidal gases is technically challenging. Feedforward control methods are challenging because end-tidal values vary as a dynamic function of both inspired gases and other nonregulated physiological parameters. Conventional feedback control is limited by delays within the lungs and body tissues and within the end-tidal forcing system itself. Consequently, modern end-tidal forcing studies have generally restricted their analysis to simple time courses of end-tidal gases and to resting steady-state conditions...
December 1, 2016: Journal of Applied Physiology
https://www.readbyqxmd.com/read/27573833/european-neolithic-societies-showed-early-warning-signals-of-population-collapse
#17
Sean S Downey, W Randall Haas, Stephen J Shennan
Ecosystems on the verge of major reorganization-regime shift-may exhibit declining resilience, which can be detected using a collection of generic statistical tests known as early warning signals (EWSs). This study explores whether EWSs anticipated human population collapse during the European Neolithic. It analyzes recent reconstructions of European Neolithic (8-4 kya) population trends that reveal regime shifts from a period of rapid growth following the introduction of agriculture to a period of instability and collapse...
August 30, 2016: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/27410637/detectability-of-active-triangulation-range-finder-a-solar-irradiance-approach
#18
Huizhe Liu, Jason Gao, Viet Phuong Bui, Zhengtong Liu, Kenneth Eng Kian Lee, Li-Shiuan Peh, Ching Eng Png
Active triangulation range finders are widely used in a variety of applications such as robotics and assistive technologies. The power of the laser source should be carefully selected in order to satisfy detectability and still remain eye-safe. In this paper, we present a systematic approach to assess the detectability of an active triangulation range finder in an outdoor environment. For the first time, we accurately quantify the background noise of a laser system due to solar irradiance by coupling the Perez all-weather sky model and ray tracing techniques...
June 27, 2016: Optics Express
https://www.readbyqxmd.com/read/27224739/multipolar-electrostatic-energy-prediction-for-all-20-natural-amino-acids-using-kriging-machine-learning
#19
Timothy L Fletcher, Paul L A Popelier
A machine learning method called kriging is applied to the set of all 20 naturally occurring amino acids. Kriging models are built that predict electrostatic multipole moments for all topological atoms in any amino acid based on molecular geometry only. These models then predict molecular electrostatic interaction energies. On the basis of 200 unseen test geometries for each amino acid, no amino acid shows a mean prediction error above 5.3 kJ mol(-1), while the lowest error observed is 2.8 kJ mol(-1). The mean error across the entire set is only 4...
June 14, 2016: Journal of Chemical Theory and Computation
https://www.readbyqxmd.com/read/26870609/phylopythias-a-self-training-method-for-the-rapid-reconstruction-of-low-ranking-taxonomic-bins-from-metagenomes
#20
Ivan Gregor, Johannes Dröge, Melanie Schirmer, Christopher Quince, Alice C McHardy
Background. Metagenomics is an approach for characterizing environmental microbial communities in situ, it allows their functional and taxonomic characterization and to recover sequences from uncultured taxa. This is often achieved by a combination of sequence assembly and binning, where sequences are grouped into 'bins' representing taxa of the underlying microbial community. Assignment to low-ranking taxonomic bins is an important challenge for binning methods as is scalability to Gb-sized datasets generated with deep sequencing techniques...
2016: PeerJ
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