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Constraint based modeling

Xu Zhao, Lihua Dou, Zhong Su, Ning Liu
A snake robot is a type of highly redundant mobile robot that significantly differs from a tracked robot, wheeled robot and legged robot. To address the issue of a snake robot performing self-localization in the application environment without assistant orientation, an autonomous navigation method is proposed based on the snake robot's motion characteristic constraints. The method realized the autonomous navigation of the snake robot with non-nodes and an external assistant using its own Micro-Electromechanical-Systems (MEMS) Inertial-Measurement-Unit (IMU)...
March 16, 2018: Sensors
Miloslav Pekař
Recently, a method based on non-equilibrium continuum thermodynamics which derives thermodynamically consistent reaction rate models together with thermodynamic constraints on their parameters was analyzed using a triangular reaction scheme. The scheme was kinetically of the first order. Here, the analysis is further developed for several first and second order schemes to gain a deeper insight into the thermodynamic consistency of rate equations and relationships between chemical thermodynamic and kinetics...
2018: Frontiers in Chemistry
E K Yeoh, Martin C S Wong, Eliza L Y Wong, Carrie Yam, C M Poon, Roger Y Chung, Marc Chong, Yuan Fang, Harry H X Wang, Miaoyin Liang, Wilson W L Cheung, Chun Hei Chan, Benny Zee, Andrew J Stewart Coats
BACKGROUND: Chronic Care Model (CCM) has been developed to improve patients' health care by restructuring health systems in a multidimensional manner. This systematic review aims to summarize and analyse programs specifically designed and conducted for the fulfilment of multiple CCM components. We have focused on programs targeting diabetes mellitus, hypertension and cardiovascular disease. METHOD AND RESULTS: This review was based on a comprehensive literature search of articles in the PubMed database that reported clinical outcomes...
May 1, 2018: International Journal of Cardiology
Zhen Tian, Jingqi Yuan, Xiang Zhang, Lei Kong, Jingcheng Wang
The coordinated control system (CCS) serves as an important role in load regulation, efficiency optimization and pollutant reduction for coal-fired power plants. The CCS faces with tough challenges, such as the wide-range load variation, various uncertainties and constraints. This paper aims to improve the load tacking ability and robustness for boiler-turbine units under wide-range operation. To capture the key dynamics of the ultra-supercritical boiler-turbine system, a nonlinear control-oriented model is developed based on mechanism analysis and model reduction techniques, which is validated with the history operation data of a real 1000 MW unit...
March 12, 2018: ISA Transactions
Aida Kamišalić, David Riaño, Tatjana Welzer
BACKGROUND: In medical practice, long term interventions are common and they require timely planning of the involved processes. Unfortunately, evidence-based statements about time are hard to find in Clinical Practice Guidelines (CPGs) and in other sources of medical knowledge. At the same time, health care centers use medical records and information systems to register data about clinical processes and patients, including time information about the encounters, prescriptions, and other clinical actions...
May 2018: Computer Methods and Programs in Biomedicine
Han Liu, Xianchao Zhang, Xiaotong Zhang
Possible world has shown to be effective for handling various types of data uncertainty in uncertain data management. However, few uncertain data clustering and classification algorithms are proposed based on possible world. Moreover, existing possible world based algorithms suffer from the following issues: (1) they deal with each possible world independently and ignore the consistency principle across different possible worlds; (2) they require the extra post-processing procedure to obtain the final result, which causes that the effectiveness highly relies on the post-processing method and the efficiency is also not very good...
February 27, 2018: Neural Networks: the Official Journal of the International Neural Network Society
Mark Hindmarsh
A model for the acoustic production of gravitational waves at a first-order phase transition is presented. The source of gravitational radiation is the sound waves generated by the explosive growth of bubbles of the stable phase. The model assumes that the sound waves are linear and that their power spectrum is determined by the characteristic form of the sound shell around the expanding bubble. The predicted power spectrum has two length scales, the average bubble separation and the sound shell width when the bubbles collide...
February 16, 2018: Physical Review Letters
Antonella Succurro, Oliver Ebenhöh
Understanding microbial ecosystems means unlocking the path toward a deeper knowledge of the fundamental mechanisms of life. Engineered microbial communities are also extremely relevant to tackling some of today's grand societal challenges. Advanced meta-omics experimental techniques provide crucial insights into microbial communities, but have been so far mostly used for descriptive, exploratory approaches to answer the initial 'who is there?' QUESTION: An ecosystem is a complex network of dynamic spatio-temporal interactions among organisms as well as between organisms and the environment...
March 14, 2018: Biochemical Society Transactions
Steven R Dolly, Yang Lou, Mark A Anastasio, Hua Li
It is widely known that the optimization of imaging systems based on objective, task-based measures of image quality via computer-simulation requires the use of a stochastic object model (SOM). However, the development of computationally tractable SOMs that can accurately model the statistical variations in human anatomy within a specified ensemble of patients remains a challenging task. Previously reported numerical anatomic models lack the ability to accurately model inter-patient and inter-organ variations in human anatomy among a broad patient population, mainly because they are established on image data corresponding to a few of patients and individual anatomic organs...
March 14, 2018: Physics in Medicine and Biology
Lokmane Chebouba, Bertrand Miannay, Dalila Boughaci, Carito Guziolowski
BACKGROUND: During the last years, several approaches were applied on biomedical data to detect disease specific proteins and genes in order to better target drugs. It was shown that statistical and machine learning based methods use mainly clinical data and improve later their results by adding omics data. This work proposes a new method to discriminate the response of Acute Myeloid Leukemia (AML) patients to treatment. The proposed approach uses proteomics data and prior regulatory knowledge in the form of networks to predict cancer treatment outcomes by finding out the different Boolean networks specific to each type of response to drugs...
March 8, 2018: BMC Bioinformatics
Samantha Tayne, Christian A Merrill, Rajeev C Saxena, Caitlin King, Karthik Devarajan, Stefan Ianchulev, Jon Chilingerian
Given the rising costs of healthcare delivery and reimbursement constraints, large academic medical centers (AMCs) must improve efficiency while delivering high-quality care. With standardized cases and high volumes, ambulatory surgery is a high-value target for efficiency improvement. Mining a data set of more than 7,500 cases consisting of the three highest-volume ambulatory procedures in orthopedics, otolaryngology-head and neck surgery, and urology, we analyzed process times and wait times involved in patient flow...
March 2018: Journal of Healthcare Management / American College of Healthcare Executives
Isabelle Niedhammer, Thomas Lesuffleur, Géraldine Labarthe, Jean-François Chastang
BACKGROUND: Social inequalities in work injury have been observed but explanations are still missing. The objectives of this study were to evaluate the contribution of working conditions in the explanation of social inequalities in work injury in a national representative sample of employees. METHODS: The study was based on the cross-sectional sample of the national French survey SUMER 2010 including 46,962 employees, 26,883 men and 20,079 women. The number of work injuries within the last 12 months was studied as the outcome...
March 12, 2018: BMC Public Health
Tom Williamson, Scott Everitt, Sunita Chauhan
BACKGROUND: High intensity focused ultrasound (HIFU) represents a non-invasive method for the destruction of cancerous tissue within the body. Heating of targeted tissue by focused ultrasound transducers results in the creation of ellipsoidal lesions at the target site, the locations of which can have a significant impact on treatment outcomes. Towards this end, this work describes a method for the optimization of lesion positions within arbitrary tumors, with specific anatomical constraints...
February 26, 2018: Computers in Biology and Medicine
Jie Wen, Yong Xu, Zuoyong Li, Zhongli Ma, Yuanrong Xu
Least square regression is a very popular supervised classification method. However, two main issues greatly limit its performance. The first one is that it only focuses on fitting the input features to the corresponding output labels while ignoring the correlations among samples. The second one is that the used label matrix, i.e., zero-one label matrix is inappropriate for classification. To solve these problems and improve the performance, this paper presents a novel method, i.e., inter-class sparsity based discriminative least square regression (ICS_DLSR), for multi-class classification...
February 21, 2018: Neural Networks: the Official Journal of the International Neural Network Society
Brett G Olivier, Frank T Bergmann
Constraint-based modeling is a well established modeling methodology used to analyze and study biological networks on both a medium and genome scale. Due to their large size and complexity such steady-state flux models are, typically, analyzed using constraint-based optimization techniques, for example, flux balance analysis (FBA). The Flux balance constraints (FBC) Package extends SBML Level 3 and provides a standardized format for the encoding, exchange and annotation of constraint-based models. It includes support for modeling concepts such as objective functions, flux bounds and model component annotation that facilitates reaction balancing...
March 9, 2018: Journal of Integrative Bioinformatics
Fattaneh Jabbari, Joseph Ramsey, Peter Spirtes, Gregory Cooper
Discovering causal structure from observational data in the presence of latent variables remains an active research area. Constraint-based causal discovery algorithms are relatively efficient at discovering such causal models from data using independence tests. Typically, however, they derive and output only one such model. In contrast, Bayesian methods can generate and probabilistically score multiple models, outputting the most probable one; however, they are often computationally infeasible to apply when modeling latent variables...
September 2017: Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD: Proceedings
Axel H Newton, Frantisek Spoutil, Jan Prochazka, Jay R Black, Kathryn Medlock, Robert N Paddle, Marketa Knitlova, Christy A Hipsley, Andrew J Pask
The Tasmanian tiger or thylacine ( Thylacinus cynocephalus ) was an iconic Australian marsupial predator that was hunted to extinction in the early 1900s. Despite sharing striking similarities with canids, they failed to evolve many of the specialized anatomical features that characterize carnivorous placental mammals. These evolutionary limitations are thought to arise from functional constraints associated with the marsupial mode of reproduction, in which otherwise highly altricial young use their well-developed forelimbs to climb to the pouch and mouth to suckle...
February 2018: Royal Society Open Science
Faizan Ehsan Elahi, Ammar Hasan
Gene regulatory networks (GRNs) are quite large and complex. To better understand and analyse GRNs, mathematical models are being employed. Different types of models, such as logical, continuous and stochastic models, can be used to describe GRNs. In this paper, we present a new approach to identify continuous models, because they are more suitable for large number of genes and quantitative analysis. One of the most promising techniques for identifying continuous models of GRNs is based on Hill functions and the generalized profiling method (GPM)...
February 2018: Royal Society Open Science
Rajeev K Varshney, Mahendar Thudi, Manish K Pandey, Francois Tardieu, Chris Ojiewo, Vincent Vadez, Anthony M Whitbread, Kadambot H M Siddique, Henry T Nguyen, Peter S Carberry, David Bergvinson
Grain legumes form an important component of the human diet, feed for livestock and replenish soil fertility through biological nitrogen fixation. Globally, the demand for food legumes is increasing as they complement cereals in protein requirements and possess a high percentage of digestible protein. Climate change has enhanced the frequency and intensity of drought stress that is posing serious production constraints, especially in rainfed regions where most legumes are produced. Genetic improvement of legumes, like other crops, is mostly based on pedigree and performance-based selection over the last half century...
March 5, 2018: Journal of Experimental Botany
Bonan Jin, Xiaosu Xu, Tao Zhang
Finding the position of a radiative source based on time-difference-of-arrival (TDOA) measurements from spatially separated receivers has been widely applied in sonar, radar, mobile communications and sensor networks. For the nonlinear model in the process of positioning, Taylor series and other novel methods are proposed. The idea of cone constraint provides a new way of solving this problem. However, these approaches do not always perform well and are away from the Cramer-Rao-Lower-Bound (CRLB) in the situations when the source is set at the array edge, the noise in measurement is loud, or the initial position is biased...
March 4, 2018: Sensors
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