1747results about "Computational materials science" patented technology

A method and system for multi-scale anatomical and functional modeling of coronary circulation is disclosed. A patient-specific anatomical model of coronary arteries and the heart is generated from medical image data of a patient. A multi-scale functional model of coronary circulation is generated based on the patient-specific anatomical model. Blood flow is simulated in at least one stenosis region of at least one coronary artery using the multi-scale function model of coronary circulation. Hemodynamic quantities, such as fractional flow reserve (FFR), are computed to determine a functional assessment of the stenosis, and virtual intervention simulations are performed using the multi-scale function model of coronary circulation for decision support and intervention planning.

This invention provides methods for determining drug specificity, therapeutic index and effective doses for individual patients. According to the methods of the invention, graded levels of drug are applied to a biological sample or a patient. A plurality of cellular constituents are measured to determine the activity of the drug on a target pathway and at least one off-target pathway. A drug specificity is determined by comparing the target and off target activities of the drug. A therapeutic concentration (or dose) is defined as a concentration (or dose) of the drug that induces certain response in the target pathway. A toxic concentration (or dose) is defined as a concentration (or dose) of the drug that induces certain response in the off target pathway. Therapeutic index is the ratio of the toxic concentration over therapeutic concentration. Methods are also provided to determine an effective dose of a drug for a patient by measuring the activity of the drug on the particular patient.

A skin incision device has a casing having a bottom surface with a slot formed therein, a cover positioned on the casing and slidable in a direction toward the bottom surface, a blade positioned in the casing adjacent the slot, an actuator cooperatively positioned between the cover and an interior of the casing, and a carriage element. The actuator engages the blade by its horizontal displacement triggered by the slidable movement of the cover toward the bottom surface of the casing. The carriage element guides the movement of the blade between a pre-actuated position and a post-actuated position. The blade moves outwardly through the slot, cuts with a horizontal movement, and returns inwardly through the slot.

A system and method is provided for using a communications network coupling a plurality of computer systems, a database, and a at least one external data source together to facilitate communication therebetween. The plurality of computer systems is configured to extract at least one term from a medical order for the patient, identify at least one medical concept related to an extracted term, and identify at least one medical data element related to an identified medical concept. The plurality of computer system is further configured to query the database for the identified at least one medical data element, query the at least one external data source to retrieve at least one guideline for performing at least one intervention associated with the at least one medical data element, and generate a user interface that displays at least a portion of a result from the queries.

A flexible, multi-product, multi-technology, expandable facility for manufacturing products, such as biologicals, pharmaceuticals, or chemicals, and manufacturing processes using elements of such a facility.

This invention presents an innovative framework for the application of machine learning for identification of alloys or composites with desired properties of interest. For each output property of interest, we identify the corresponding driving (input) factors. These input factors may include the material composition, heat treatment, process, microstructure, temperature, strain rate, environment or testing mode. Our framework assumes selection of optimization technique suitable for the application at hand and data available, starting with simple linear, or quadratic, regression analysis. We present a physics-based model for predicting the ultimate tensile strength, a model that accounts for physical dependencies, and factors in the underlying physics as a priori information. In case an artificial neural network is deemed suitable, we suggest employing custom kernel functions consistent with the underlying physics, for the purpose of attaining tighter coupling, better prediction, and extracting the most out of the—usually limited—input data available.

A method of designing a material by optimising values for design variables includes the steps of: (i) providing one or more property models that produce a prediction for a value of a respective property of the material as a function of the design variables and produce a value for the uncertainty in the prediction, (ii) setting a specification target for a desired value for each property and a probability for that specification target to be met or exceeded, (iii) determining a probabilistic target for a value for each property, the probabilistic target being based on the specification target and the probability, and defining a merit index factor based on the degree to which a given prediction satisfies the probabilistic target, (iv) constructing an overall merit factor from the individual merit index factors of the properties, and (v) determining a set of optimal design variables that optimise the overall merit factor.

An olfaction processor (OLP) (100) that generates RAW data (35) including content data (139d) relating to chemical substances is provided. The OLP (100) includes a generator (130) that generates the RAW data (35). The chemical substances include at least one of compounds, molecules, and elements. The generator (130) includes a conversion unit (131) that converts intensity variations, which show detected chemical substances included in data from at least one sensor that detects an amount that changes due to presence of at least one of the chemical substances, to the content data (139d) by mapping onto a frequency space where a plurality of frequencies have been respectively assigned to a plurality of specified chemical substances.

Methods, systems, and computer program products for computational polymer processing including, without limitation, computational amphiphilic polymer design, conformational energy minimization, generation and refinement of torsional parameters for sub-units of potential polymers, generation of modified force field parameters, and prediction of conformational information for potential polymers. A target polymer backbone or portion thereof is identified. Small model compounds that have structural connectivities that are similar to structural connectivities of the target polymer backbone or portion thereof, are identified, whereby the combination of the small model compounds serve as a model of the target polymer or portion thereof. Gradient-corrected density functional theory (“DFT”) torsional potentials are calculated for the small model compounds, wherein energies are calculated at unconstrained and constrained geometries of the selected small model compounds. New torsional parameters are then obtained from the DFT torsional potentials. The new torsional parameters are combined with other terms to form a modified (or new) force field for the target polymer backbone or portion thereof. Molecular dynamics and configurational-biased Monte Carlo (“MD/MC”) simulations are performed using the modified force field, whereby results of the MD/MC simulations serve as predicted conformation properties of the target polymer backbone. The predicted conformation properties for the multiple target polymer backbones are then used to select one or more of the target polymer backbones as candidate amphiphilic polymer backbones for synthesis.

A particle size distribution creating method includes a particle size range determining step, an integrating step of integrating the frequency of appearance of particles within the particle size range determined in the particle size range determining step, a division point determining step of determining particle sizes that provide division points, using the integral of the frequency of appearance obtained in the integrating step, and a typical point determining step of determining the minimum particle size, maximum particle size and the particle sizes of the division points as typical points. This method is characterized by assuming a particle size distribution which contains particles having the particle sizes of the respective typical points and is plotted such that the frequency of appearance of the particles having the particle size of each of the typical points is equal to the integral over each of the regions defined by the typical points, and obtaining the assumed particle size distribution as a particle size distribution model.

A computer simulation analysis method suitable for describing the mechanical behavior of multiphase composites based on the real microstructure of materials relates to a multidisciplinary field such as computational material science, simulation and high throughput calculation. Through the first-principles calculation under nano scale, the molecular dynamics simulation under micro scale, and the thermodynamic calculation under mesoscopic scale, various physical parameters needed for the finite element simulation under macro scale can be obtained, including the elastic and plastic physical parameters of each phase in the composite at different temperature and different grain sizes. Focused ion beam experiment and image processing are adopted to obtain real material microstructure. Through the parameter coupling and parameter transfer among the calculated results of various scales, combining the microstructure of the material, stress-strain relationship, stress distribution and its evolution law, plastic deformation and other mechanical behaviors of the multiphase composites under complex stress and different temperature can be simulated.

A method for calibrating forecasts involving temperature, precipitation, and other weather related variables is provided. In an embodiment historical ensemble-based forecasts and historical observations are received by an agricultural intelligence computing system. Historical differences are determined between the forecasts and the observations corresponding to the forecasts and stored in the volatile memory of the agricultural intelligence computing system. The agricultural intelligence computing system receives current ensemble-based forecasts and a request for improved forecasts. The agricultural intelligence computing system retrieves the historical differences and uses a combination of the historical differences and the current ensemble-based forecasts to create probability distributions for the weather for each lead day. The agricultural intelligence computing system then samples from the probability distributions to create improved ensemble-based forecasts at the requested location.

The invention discloses a method for evaluating mustard sauce flavor grades by a taste system and an electronic nose, and belongs to the technical field of condiment analysis and identification methods. The method includes the steps of acquiring intelligent sensory data of mustard sauce by an electronic tongue taste system and an electronic nose olfactory system; performing digital processing for traditional sensory evaluation indexes; analyzing relations among the acquired sensory evaluation indexes, stoichiometric indexes and the intelligent sensory data by the aid of a random forest model; evaluating sensory grades of mustard sauce flavor. According to the method, objectivity and accuracy of sensory evaluation of the mustard sauce can be effectively improved, and the method is simple to operate, low in sample consumption and cost and short in consumed time and has high popularization and application values.

The invention provides an automated method for identifying an optimal or near optimal mathematical model to describe observed data including: a) the definition of a candidate model search space, b) methods for searching said candidate model search space to identify the optimal or near optimal model within said candidate model search space. The present invention includes algorithms for writing the computer code needed to implement and evaluate candidate models in the software package NONMEM.

A nano-technology modeling method wherein a group of atoms and an interaction thereof to an open environment are defined by Hamiltonian matrices and overlap matrices, matrix elements of the matrices being obtained by a tight-binding (TB) fitting of system parameters to a first principles atomistic model based on density functional theory (DFT) with non-equilibrium density distribution.

The invention relates to a multi-dimension coupling simulation method for irradiation damage of a nuclear reactor material. According to the method, by combining MD, KMC and CD methods, the respectiveadvantages are achieved, MD is used for simulating a cascade collision process, a simulation result is used as input of KMC, the KMC is used for simulating an annealing process of a cascade defect, asimulation result is used as input of CD, the CD is used for simulating a long-time evolution process of the cascade defect, large-space-time-dimension simulation from defect generation to microcosmic structure representation can be achieved, and accordingly material performance prediction under the service condition is achieved. According to the multi-dimension coupling simulation method, the limit of a single dimension is broken through, long-time and large-scale simulation from atom dimension defect generation of the irradiation damage of the nuclear reactor material to microcosmic structure representation is achieved, the irradiation damage mechanism of the nuclear material can be deeply known, and evolution of a microcosmic structure of an irradiation induction material is predicted.

A system, apparatus, and/or method is disclosed for determining a value of a property of a considered chemical composition. An identity of a sample chemical composition may be received. A sample chemical composition may comprise ingredients. Each of the ingredients may be associated with a value of a chemoinformatic property of chemoinformatic properties of the sample chemical composition. A value of a property of the sample chemical composition and at least one of (1) the identity of the sample chemical composition or (2) the values of the chemoinformatic properties of the ingredients of the sample chemical composition may be input into a model. The value of the property of the considered chemical composition may be determined, via the model, based on at least one of (1) an identity of the considered chemical composition or (2) values of chemoinformatic properties of ingredients of the considered chemical composition.

The invention provides a multi-dimensional predicting method for strength of a braided ceramic base composite material. Firstly a parameterization method is used for establishing a braided ceramic base composite material single-cell model which comprises yarns and a matrix, and then period grid dividing is performed. Afterwards a mesomechanics method is used for simulating the mechanics behavior of the yarn unit. Furthermore a strain conversion matrix is used for converting a yarn element stiffness matrix from a local coordinate system to an integral coordinate system. Finally through applyingan increment type periodic boundary condition, a micro-stress and a strain field of a single cell are calculated. A volume averaging method is used for obtaining a microscopic stress and strain of the braided ceramic base composite material. If a failure unit band which penetrates through the single cell is formed, failure of the braided ceramic base composite material is determined, and the single-cell average stress is the strength of the braided ceramic base composite material. According to the multi-dimensional predicting method, the multidimensional analysis method in which macrography and mesography are combined is utilized. The strength of the braided ceramic base composite material can be accurately predicted without dependence to a large number of experiments with time consumption and high cost.