Methods of designing a polynucleotide sequence for expressing a polypeptide-of-interest in a cell are provided. Also provided are artificial transcript sequences generated according to the present teachings. Further provided are methods of estimating the adaptiveness of a transcript sequence encoding a polypeptide-of-interest to a gene expression machinery in a cell.

A cluster system including a plurality of nodes, a plurality of clusters included in each node and a management module managing the cluster system and an arithmetic module, which are included in each of the clusters, wherein, among all the management modules included in the cluster system, one management module is set representative management module, in the individual clusters, one is set as a master management module, and another is set as a standby management module. Each of the management modules includes a failure monitoring unit and a failover control unit. When a failure in the representative management module is detected by any of the failure monitoring units, any of the management modules included in the non-representative management modules, is set as a new representative management module. A recovery unit restores the failure monitoring unit and the failover control unit in the management module in which a failure is detected.

A cluster system including a plurality of nodes, a plurality of clusters included in each node and a management module managing the cluster system and an arithmetic module, which are included in each of the clusters, wherein, among all the management modules included in the cluster system, one management module is set representative management module, in the individual clusters, one is set as a master management module, and another is set as a standby management module. Each of the management modules includes a failure monitoring unit and a failover control unit. When a failure in the representative management module is detected by any of the failure monitoring units, any of the management modules included in the non-representative management modules, is set as a new representative management module. A recovery unit restores the failure monitoring unit and the failover control unit in the management module in which a failure is detected.

The present disclosure provides a system and method for dynamically disabling identified elements in template code transforming into webpage code for rendering. The method comprises: in response to a first request to render a webpage from a template file associated with a service instance, identifying a first code unit in the template file that is associated with a first application that is not included in a set of one or more installed applications registered with the service instance; transforming the template file into a webpage file containing webpage code, wherein the transforming disables the first code unit; and providing the webpage file to an electronic device for rendering the webpage from the webpage file, wherein the first code unit has been disabled.

A non-transitory recording medium records a program that causes a computer to execute a process of causing a display to display, in response to one or more input operations accepted via an input device, one first mathematical expression display area including one first mathematical expression, one first graph display area associated with the one first mathematical expression display area, one first slider display area associated with the one first graph display area, one second mathematical expression display area including one second mathematical expression, one second graph display area which is associated with the one second mathematical expression display area and is an area different from the one first graph display area, and one second slider display area which is associated with the one second graph display area and is an area different from the one first slider display area.

A method for detecting anomalies during operation of an asset to improve performance of the asset includes collecting, via a server, data relating to operation of the asset or a group of assets containing the asset. The data includes normal and abnormal asset behavior of the asset or the group of assets containing the asset. Further, the method includes automatically removing, via an iterative algorithm programmed in the server that utilizes one or more inputs or outputs of an anomaly detection analytic, portions of the data containing the abnormal asset behavior to form a dataset containing only the normal asset behavior. The method also includes training, via a computer-based model programmed in the server, the anomaly detection analytic using, at least, the dataset containing only the normal asset behavior. Moreover, the method includes applying, via the server, the anomaly detection analytic to the asset so as to monitor for anomalies during operation thereof.

A method for detecting anomalies during operation of an asset to improve performance of the asset includes collecting, via a server, data relating to operation of the asset or a group of assets containing the asset. The data includes normal and abnormal asset behavior of the asset or the group of assets containing the asset. Further, the method includes automatically removing, via an iterative algorithm programmed in the server that utilizes one or more inputs or outputs of an anomaly detection analytic, portions of the data containing the abnormal asset behavior to form a dataset containing only the normal asset behavior. The method also includes training, via a computer-based model programmed in the server, the anomaly detection analytic using, at least, the dataset containing only the normal asset behavior. Moreover, the method includes applying, via the server, the anomaly detection analytic to the asset so as to monitor for anomalies during operation thereof.

A processing apparatus includes one or more processors and one or more memories operatively coupled to the one or more processors. The one or more processors are configured to acquire a spectrogram of a sound signal. The one or more processors are also configured to perform a first convolution on the spectrogram at every predetermined width on one of a frequency axis or a time axis. The one or more processors are also configured to combine results of the first convolution to obtain one-dimensional first feature data. The one or more processors are also configured to perform at least one second convolution on the one-dimensional first feature data to obtain one-dimensional second feature data indicating a feature of the spectrogram.

Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.

Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.