Abstract: A cell sorting system that automatically generates a sorting strategy based on examples of target events provided by an operator. The target events can be selected using measurements ranging from traditional flow cytometry measurements to derived measurements that are computationally expensive to complex measurements such as images.

Abstract: In one aspect, a method of sorting cells in a flow cytometry system is disclosed, which includes illuminating a cell with radiation having at least two optical frequencies shifted from one another by a radiofrequency to elicit fluorescent radiation from the cell, detecting the fluorescent radiation to generate temporal fluorescence data, and processing the temporal fluorescence data to arrive at a sorting decision regarding the cell without generating an image (i.e., a pixel-by-pixel image) of the cell based on the fluorescence data. In other words, while the fluorescence data can contain image data that would allow generating a pixel-by-pixel fluorescence intensity map, the method arrives at the sorting decision without generating such a map. In some cases, the sorting decision can be made with a latency less than about 100 microseconds. In some embodiments, the above method of sorting cells can have a sub-cellular resolution, e.g.

Abstract: Aspects of the present disclosure include a method for sorting cells of a sample based on an image of a cell in a flow stream. Methods according to certain embodiments include detecting light from a sample having cells in a flow stream, generating an image mask of a cell from the sample and sorting the cell based on the generated image mask. Systems having a processor with memory operably coupled to the processor having instructions stored thereon, which when executed by the processor, cause the processor to generate an image mask of a cell in a sample in a flow stream and to sort the cell based on the generated image mask are also described. Integrated circuit devices (e.g., field programmable gate arrays) having programming for generating an image mask and for determining one or more features of the cell are also provided.

Abstract: Aspects of the present disclosure include methods for characterizing particles of a sample in a flow stream. Methods according to certain embodiments include generating frequency-encoded fluorescence data from a particle of a sample in a flow stream; and calculating phase-corrected spatial data of the particle by performing a transform of the frequency-encoded fluorescence data with a phase correction component. In certain embodiments, methods include generating an image of the particle in the flow stream based on the phase-corrected spatial data. Systems having a processor with memory operably coupled to the processor having instructions stored thereon, which when executed by the processor, cause the processor to calculate phase-corrected spatial data from frequency-encoded fluorescence data of a particle a flow stream are also described. Integrated circuit devices (e.g., field programmable gate arrays) having programming for practicing the subject methods are also provided.

Abstract: Aspects of the present disclosure include a method for sorting cells of a sample based on an image of a cell in a flow stream. Methods according to certain embodiments include detecting light from a sample having cells in a flow stream, generating an image mask of a cell from the sample and sorting the cell based on the generated image mask. Systems having a processor with memory operably coupled to the processor having instructions stored thereon, which when executed by the processor, cause the processor to generate an image mask of a cell in a sample in a flow stream and to sort the cell based on the generated image mask are also described. Integrated circuit devices (e.g., field programmable gate arrays) having programming for generating an image mask and for determining one or more features of the cell are also provided.

Abstract: Disclosed herein include systems, devices, computer readable media, and methods for subsampling flow cytometric event data. First and second flow cytometric event data can be transformed into a lower-dimensional space, associated with a plurality of bins, and assigned to a first bin and a second bin. Subsampled flow cytometric event data comprising the first flow cytometric event data can be generated. The subsampled flow cytometric event data can comprise the second flow cytometric event data if the first bin and the second bin are different. The subsampled flow cytometric event data may not comprise the second flow cytometric event data if the first bin and the second bin are identical.

Abstract: In one aspect, the present teachings provide a system for performing cytometry that can be operated in three operational modes. In one operational mode, a fluorescence image of a sample is obtained by exciting one or more fluorophore(s) present in the sample by an excitation beam formed as a superposition of a top-hat-shaped beam with a plurality of beams that are radiofrequency shifted relative to one another. In another operational mode, a sample can be illuminated successively over a time interval by a laser beam at a plurality of excitation frequencies in a scanning fashion. The fluorescence emission from the sample can be detected and analyzed, e.g., to generate a fluorescence image of the sample. In yet another operational mode, the system can be operated to illuminate a plurality of locations of a sample concurrently by a single excitation frequency, which can be generated, e.g., by shifting the central frequency of a laser beam by a radiofrequency.

Abstract: Space system TT&C monitoring includes analyzing network traffic comprising of data packets between a front-end processor (FEP) and a cryptographic unit. A JavaScript Object Notation (JSON) object is created when the network traffic containing a vehicle command is detected. The JSON object is transmitted, by way of a data transport mechanism, to either a cyber defense module or a security information and event management (SIEM) module for further ingestions and visualization. The JSON object is analyzed using machine learning (ML) module or a rule-based intrusion detection system (IDS) module to generate an anomaly score for the SIEM module for further ingestions and visualization.

Abstract: Disclosed herein include systems, devices, computer readable media, and methods for subsampling flow cytometric event data. First and second flow cytometric event data can be transformed into a lower-dimensional space, associated with a plurality of bins, and assigned to a first bin and a second bin. Subsampled flow cytometric event data comprising the first flow cytometric event data can be generated. The subsampled flow cytometric event data can comprise the second flow cytometric event data if the first bin and the second bin are different. The subsampled flow cytometric event data may not comprise the second flow cytometric event data if the first bin and the second bin are identical.

Abstract: Non-parametric transforms such as t-distributed stochastic neighbor embedding (tSNE) are used to analyze multi-parametric data such as data derived from flow cytometry or other particle analysis systems and methods. These transforms may be included for dimensionality reduction and identification of subpopulations (e.g., gating). By nature, non-parametric transforms cannot transform new observations without training a new transformation based on the entire dataset including the new observations. The features described parameterize non-parametric transforms using a neural network thereby allowing a small training dataset to be transformed using non-parametric techniques. The training dataset may then be used to generate an accurate parametric model for assessing additional events in a manner consistent with the initial events.

Abstract: A logistics tower includes a vertical storage cell column, a vertical retrieval system and a horizontal shuttle system. The vertical storage cell column includes an elevator shaft extending therethrough and a plurality of storage modules arranged around the elevator shaft. The vertical retrieval system includes a winch and a robotic bin handier. The robotic bin handler is moveably by the winch within the elevator shaft of the vertical storage cell column. The robotic bin handler includes a carnage assembly that extends inwardly and outwardly therefrom to access and retrieve storage bins from the storage modules arranged around the elevator shaft. The carriage assembly includes a gripping assembly that selectively couples and decouples the storage bin to the carriage of the robotic bin handler. The vertical retrieval system lowers the storage bin coupled to the carriage assembly to a. robotic shuttle situated on the horizontal shuttle system.

Abstract: In one aspect, the present teachings provide a system for performing cytometry that can be operated in three operational modes. In one operational mode, a fluorescence image of a sample is obtained by exciting one or more fluorophore(s) present in the sample by an excitation beam formed as a superposition of a top-hat-shaped beam with a plurality of beams that are radiofrequency shifted relative to one another. In another operational mode, a sample can be illuminated successively over a time interval by a laser beam at a plurality of excitation frequencies in a scanning fashion. In yet another operational mode, the system can be operated to illuminate a plurality of locations of a sample concurrently by a single excitation frequency, which can be generated, e.g., by shifting the central frequency of a laser beam by a radiofrequency. The detected fluorescence radiation can be used to analyze the fluorescence content of the sample, e.g., a cell/particle.

Abstract: Aspects of the present disclosure include methods for characterizing particles of a sample in a flow stream. Methods according to certain embodiments include detecting light from a sample having cells in a flow stream, generating an image of an object in the flow stream in an interrogation region and determining whether the object in the flow stream is an aggregate based on the generated image. Systems having a processor with memory operably coupled to the processor having instructions stored thereon, which when executed by the processor, cause the processor to generate an image of an object in a flow stream and to determine whether the object is an aggregate are also described. Integrated circuit devices (e.g., field programmable gate arrays) having programming for practicing the subject methods are also provided.

Abstract: Non-parametric transforms such as t-distributed stochastic neighbor embedding (tSNE) are used to analyze multi-parametric data such as data derived from flow cytometry or other particle analysis systems and methods. These transforms may be included for dimensionality reduction and identification of subpopulations (e.g., gating). By nature, non-parametric transforms cannot transform new observations without training a new transformation based on the entire dataset including the new observations. The features described parameterize non-parametric transforms using a neural network thereby allowing a small training dataset to be transformed using non-parametric techniques. The training dataset may then be used to generate an accurate parametric model for assessing additional events in a manner consistent with the initial events.

Abstract: A cell sorting system that automatically generates a sorting strategy based on examples of target events provided by an operator. The target events can be selected using measurements ranging from traditional flow cytometry measurements to derived measurements that are computationally expensive to complex measurements such as images.

Abstract: Aspects of the present disclosure include methods for characterizing particles of a sample in a flow stream. Methods according to certain embodiments include detecting light from a sample having cells in a flow stream, generating an image of an object in the flow stream in an interrogation region and determining whether the object in the flow stream is an aggregate based on the generated image. Systems having a processor with memory operably coupled to the processor having instructions stored thereon, which when executed by the processor, cause the processor to generate an image of an object in a flow stream and to determine whether the object is an aggregate are also described. Integrated circuit devices (e.g., field programmable gate arrays) having programming for practicing the subject methods are also provided.

Abstract: A cell sorting system that automatically generates a sorting strategy based on examples of target events provided by an operator. The target events can be selected using measurements ranging from traditional flow cytometry measurements to derived measurements that are computationally expensive to complex measurements such as images.

Abstract: In one aspect, a method of sorting cells in a flow cytometry system is disclosed, which includes illuminating a cell with radiation having at least two optical frequencies shifted from one another by a radiofrequency to elicit fluorescent radiation from the cell, detecting the fluorescent radiation to generate temporal fluorescence data, and processing the temporal fluorescence data to arrive at a sorting decision regarding the cell without generating an image (i.e., a pixel-by-pixel image) of the cell based on the fluorescence data.. In other words, while the fluorescence data can contain image data that would allow generating a pixel-by-pixel fluorescence intensity map, the method arrives at the sorting decision without generating such a map. In some cases, the sorting decision can be made with a latency less than about 100 microseconds, In some embodiments, the above method of sorting cells can have a sub-cellular resolution, e.g.

Abstract: Space system TT&C monitoring includes analyzing network traffic comprising of data packets between a front-end processor (FEP) and a cryptographic unit. A JavaScript Object Notation (JSON) object is created when the network traffic containing a vehicle command is detected. The JSON object is transmitted, by way of a data transport mechanism, to either a cyber defense module or a security information and event management (SIEM) module for further ingestions and visualization. The JSON object is analyzed using machine learning (ML) module or a rule-based intrusion detection system (IDS) module to generate an anomaly score for the SIEM module for further ingestions and visualization.

Abstract: In one aspect, a method of sorting cells in a flow cytometry system is disclosed, which includes illuminating a cell with radiation having at least two optical frequencies shifted from one another by a radiofrequency to elicit fluorescent radiation from the cell, detecting the fluorescent radiation to generate temporal fluorescence data, and processing the temporal fluorescence data to arrive at a sorting decision regarding the cell without generating an image (i.e., a pixel-by-pixel image) of the cell based on the fluorescence data. In some cases, the sorting decision can be made with a latency less than about 100 microseconds. In some embodiments, the above method of sorting cells can have a sub-cellular resolution. In some embodiments, a single radiofrequency shift is employed to separate the optical frequencies while in other such embodiments a plurality of different radiofrequency shifts are employed.