Abstract: Sub-micrometer bioparticles are separated by size in a microfluidic channel utilizing a ratchet migration mechanism. A structure within the microfluidic channel includes an array of micro-posts arranged in laterally shifted rows. Reservoirs are disposed at each end of the microfluidic channel. A biased AC potential is applied across the channel via electrodes immersed into fluid in each of the reservoirs to induce a non-uniform electric field through the microfluidic channel. The applied potential comprises a first waveform with a first frequency that induces electro-kinetic flow of sub-micrometer bioparticles in the microfluidic channel, and an intermittent superimposed second waveform with a higher frequency. The second waveform selectively induces a dielectrophoretic trapping force to selectively impart ratchet migration based on particle size for separating the sub-micrometer bioparticles by size in the microfluidic channel.

Abstract: Data reduction services are implemented on one or more nodes of an IIoT data pipeline to intelligently determine an appropriate data reduction strategy based on characteristics of the incoming data. In one or more embodiments, data reduction components on the pipeline node or on an edge device define different data filtering rules or algorithms that are selectively applied to streaming time-series data based on a probability distribution of the data. The data pipeline node performs real-time distribution analysis on the streaming data to determine whether the data has a unimodal distribution, a multimodal distribution, or no mode, and selects one of the data filtering rules based on this determined probability distribution. In this way, the data is intelligently reduced in a manner that retains critical information within the reduced data set while achieving a high level of data reduction.

Abstract: A reactive buffering system for use in IIoT data pipelines dynamically adjusts data accumulation and delivery by a node of a pipeline based on aggregated downstream metrics representing current data processing latencies of downstream nodes. Based on these downstream performance metrics, a reactive node that adjusts the size of the next data batch to be sent to an adjacent downstream node. The nodes of the data pipeline are configured to support a request-response based handshaking protocol whereby the nodes that send data to downstream nodes maintain up-to-date performance level information from adjacent downstream nodes. With this performance information, together with pipeline priorities, the sending node (or reactive node) adjusts the transmission rate and intermediate buffering of data. In this way, the nodes of the pipeline can dynamically regulate interim data storage to avoid overwhelming the pipeline system with too much data during periods of high latency.

Abstract: A reactive buffering system for use in IIoT data pipelines dynamically adjusts data accumulation and delivery by a node of a pipeline based on aggregated downstream metrics representing current data processing latencies of downstream nodes. Based on these downstream performance metrics, a reactive node that adjusts the size of the next data batch to be sent to an adjacent downstream node. The nodes of the data pipeline are configured to support a request-response based handshaking protocol whereby the nodes that send data to downstream nodes maintain up-to-date performance level information from adjacent downstream nodes. With this performance information, together with pipeline priorities, the sending node (or reactive node) adjusts the transmission rate and intermediate buffering of data. In this way, the nodes of the pipeline can dynamically regulate interim data storage to avoid overwhelming the pipeline system with too much data during periods of high latency.

Abstract: Data reduction services are implemented on one or more nodes of an IIoT data pipeline to intelligently determine an appropriate data reduction strategy based on characteristics of the incoming data. In one or more embodiments, data reduction components on the pipeline node or on an edge device define different data filtering rules or algorithms that are selectively applied to streaming time-series data based on a probability distribution of the data. The data pipeline node performs real-time distribution analysis on the streaming data to determine whether the data has a unimodal distribution, a multimodal distribution, or no mode, and selects one of the data filtering rules based on this determined probability distribution. In this way, the data is intelligently reduced in a manner that retains critical information within the reduced data set while achieving a high level of data reduction.

Abstract: Sub-micrometer bioparticles are separated by size in a microfluidic channel utilizing a ratchet migration mechanism. A structure within the microfluidic channel includes an array of micro-posts arranged in laterally shifted rows. Reservoirs are disposed at each end of the microfluidic channel. A biased AC potential is applied across the channel via electrodes immersed into fluid in each of the reservoirs to induce a non-uniform electric field through the microfluidic channel. The applied potential comprises a first waveform with a first frequency that induces electro-kinetic flow of sub-micrometer bioparticles in the microfluidic channel, and an intermittent superimposed second waveform with a higher frequency. The second waveform selectively induces a dielectrophoretic trapping force to selectively impart ratchet migration based on particle size for separating the sub-micrometer bioparticles by size in the microfluidic channel.

Abstract: Sub-micrometer bioparticles are separated by size in a microfluidic channel utilizing a ratchet migration mechanism. A structure within the microfluidic channel includes an array of micro-posts arranged in laterally shifted rows. Reservoirs are disposed at each end of the microfluidic channel. A biased AC potential is applied across the channel via electrodes immersed into fluid in each of the reservoirs to induce a non-uniform electric field through the microfluidic channel. The applied potential comprises a first waveform with a first frequency that induces electro-kinetic flow of sub-micrometer bioparticles in the microfluidic channel, and an intermittent superimposed second waveform with a higher frequency. The second waveform selectively induces a dielectrophoretic trapping force to selectively impart ratchet migration based on particle size for separating the sub-micrometer bioparticles by size in the microfluidic channel.

Abstract: Methods and systems are described for tuning an electrical field gradient for insulator-based di electrophoresis (iDEP). A fluidic layer defines a fluidic channel adjacent to a substrate. A deformable membrane is positioned adjacent to the fluidic channel. An actuator controllably causes the deformable membrane to deflect into the fluidic channel restricting a fluidic flow in the fluidic channel. A control system is configured to tune an electrical field gradient by operating the actuator to adjust a magnitude of the deflection of the deformable membrane into the fluidic channel.

Abstract: Sub-micrometer bioparticles are separated by size in a microfluidic channel utilizing a ratchet migration mechanism. A structure within the microfluidic channel includes an array of micro-posts arranged in laterally shifted rows. Reservoirs are disposed at each end of the microfluidic channel. A biased AC potential is applied across the channel via electrodes immersed into fluid in each of the reservoirs to induce a non-uniform electric field through the microfluidic channel. The applied potential comprises a first waveform with a first frequency that induces electro-kinetic flow of sub-micrometer bioparticles in the microfluidic channel, and an intermittent superimposed second waveform with a higher frequency. The second waveform selectively induces a dielectrophoretic trapping force to selectively impart ratchet migration based on particle size for separating the sub-micrometer bioparticles by size in the microfluidic channel.

Abstract: A technique for monitoring operational parameters of networked components includes storing data within each component descriptive of the component. The data is polled by a monitoring station and provides a basis for monitor views compiled in real time. The monitor views provide a view of current levels of parameters controlled or monitored by each device, such as on virtual meters. Historical levels of operational parameters may be presented in virtual strip chart output. Textual descriptions of the components are provided, along with listings of key settings. More detailed data may be accessed by links between the monitor views and other user viewable representations for the system and the specific components.

Abstract: A technique for monitoring operational parameters of networked components includes storing data within each component descriptive of the component. The data is polled by a monitoring station and provides a basis for monitor views compiled in real time. The monitor views provide a view of current levels of parameters controlled or monitored by each device, such as on virtual meters. Historical levels of operational parameters may be presented in virtual strip chart output. Textual descriptions of the components are provided, along with listings of key settings. More detailed data may be accessed by links between the monitor views and other user viewable representations for the system and the specific components.

Abstract: A technique for monitoring operational parameters of networked components includes storing data within each component descriptive of the component. The data is polled by a monitoring station and provides a basis for monitor views compiled in real time. The monitor views provide a view of current levels of parameters controlled or monitored by each device, such as on virtual meters. Historical levels of operational parameters may be presented in virtual strip chart output. Textual descriptions of the components are provided, along with listings of key settings. More detailed data may be accessed by links between the monitor views and other user viewable representations for the system and the specific components.