A method for developing an evolved structure by artificial evolution includes: obtaining one or more properties of a biological structure; computationally evolve the biological structure to obtain an evolved descriptor; inverse-mapping the evolved description to real space to form an evolved structure design; and constructing the evolved structure. The evolved structure comprises stronger performance across the properties than the biological structure. In an example aspect, a method for constructing an evolved structure includes: removing sericin from a cocoon; forming a first solution from the cocoon with removed sericin; forming a silk fibroin powder from the first solution; dissolving the silk fibroin powder to form a second solution; and electro spinning the second solution based on the evolved structure design.

Methods, systems, and software are provided for monitoring a cancer condition of a test subject. The method includes obtaining a liquid biopsy sample from the subject at a second time point, occurring after a first time point, containing cell-free DNA fragments. Low-pass whole genome methylation sequencing of the cell-free DNA fragments is performed to obtain nucleic acid sequences having a methylation pattern for a corresponding cell-free DNA fragment. The nucleic acid sequences are mapped to a location on a reference genome. Methylation metrics are determined based on the methylation patterns and mapped locations of the nucleic acid sequences. A circulating tumor fraction is estimated from the methylation metrics, and the estimate is compared to an estimate of the circulating tumor fraction for the test subject at the first time point.

A method includes grouping, in a first layout, pattern regions which have duplicate layout patterns including weak regions as a group, calculating defect probabilities of the pattern regions, respectively, calculating a defect frequency and a defect rate of the group based on the defect probabilities of the pattern regions, predicting a degree of defects of a second layout of the pattern regions, based on the defect frequency and the defect rate, and performing an extreme ultraviolet (EUV) lithography process on a substrate, based on the second layout. The defect probabilities are calculated by performing an optical proximity correction (OPC) simulation on the pattern region, calculating a stochastic variation of a linewidth of a simulation pattern in the weak region as a Gaussian distribution, and defining a threshold linewidth, which is used as a reference of the random defect, in the Gaussian distribution.

A computer-implemented method is provided for reducing a measure time of a measure process in a multi-shot simulation performed by a quantum computing simulation system. The method includes calculating probabilities from probability amplitudes before the measure process. The method further includes creating, for each node of the quantum computing simulation system, an index of probability by incrementally summing respective different ones of the probabilities into respective sums. The method also includes generating a random number for each of the multi-shots, the random number for sampling a probability distribution of the probabilities. The method additionally includes selecting the index of probability which is larger than the random number by comparing the random number generated for a given one of the multi-shots to the index of probability created for the given one of the multi-shots.

Methods, systems, and computer storage media for providing carbon emissions data analytics recommendations using a carbon emissions data analytics engine in a carbon emissions management system. The recommendation can be associated with simulated carbon emissions optimization results data based on carbon emissions data analytics model of the carbon emissions management system. In operation, using statistical modeling, existing carbon emissions factors of standard activities are retrieved, merged and augmented. Activity data (e.g., activity data of an organization) are automatically mapped to the carbon emissions factors. Input data comprising the activity data mapped to the augmented carbon emissions factors is processed using a carbon emissions data analytics models. Processing the input data can include forecasting, scenario simulation, and scenario optimization. Based on processing the input data, output data associated with a plurality of abatement levers can be generated The output data can be communicated an caused to be displayed with graphical interface elements.

Exemplary embodiments relate to techniques for determining structural color from parameters of an array of nanopartides. The techniques include inputting structural and optical parameters and performing a probabilistic simulation to determine the structural color. An evolutionary optimization may be performed to determine parameters of the array of nanoparticles according to desired properties of structural color. The evolutionary optimization may employ the probabilistic simulation and further adjust one or more parameters of the array to approximate the desired properties of the structural color. Based on applying the probabilistic simulation, the technique may generate an output describing a value, or a range of values, for the one or more parameters of the array of nanoparticles that are selected to approximate the desired properties of the structural color.

A computer representation of a printable product part and a plan for the printable product part to be deposited using an additive manufacturing process are received. The printable product part comprises an accumulation of material deposited by the additive manufacturing process. The plan comprises a tool-path representation of the printable product part and process parameters. A plurality of as-printed shapes of the printable product part are determined after it has been deposited according to the plan. Geometric differences between any of the plurality of as-printed shapes with the computer representation of the product part are determined.

One example described herein involves a system receiving task data and distribution criteria for a state space model from a client device. The task data can indicate a type of sequential Monte Carlo (SMC) task to be implemented. The distribution criteria can include an initial distribution, a transition distribution, and a measurement distribution for the state space model. The system can generate a set of program functions based on the task data and the distribution criteria. The system can then execute an SMC module to generate a distribution and a corresponding summary, where the SMC module is configured to call the set of program functions during execution of an SMC process and apply the results returned from the set of program functions in one or more subsequent steps of the SMC process. The system can then transmit an electronic communication to the client device indicating the distribution and its corresponding summary.

A material failure forecasting system accesses historical failure data to forecasts future failures. The failure data of a material is analyzed using text processing techniques to identify failures and suspensions. The text processing techniques provide for identifying failures when fault words are associated with negations. A fault ontology establishes different failure modes that include primary, secondary and tertiary levels which enable identifying a sequence of failures. The failures thus identified are fitted to a data distribution selected from a plurality of data distributions. The parameters from the data distribution are used for simulating a demand profile for the material which considers interchangeability. Similarly failure data of the materials in an equipment can be analyzed and the reliability of the equipment can be estimated.

Method and systems for generating vehicle motion planning model simulation scenarios are disclosed. The method receives a base simulation scenario with features of a scene through which a vehicle may travel, defines an interaction zone in the scene, generates an augmentation element that includes an object and a behavior for the object, and adds the augmentation element to the base simulation scenario at the interaction zone to yield an augmented simulation scenario. The augmented simulation scenario is applied to a vehicle motion planning model to train the model.