Data object classification using feature generation through crowdsourcing
In a computing device that implements a data object classification tool, a method for classifying data may include detecting change in spatial coordinates for each of at least two of a set of data objects within a canvas space. Each of the data objects may be associated with a vector of features. A rule set may be generated based on the vector of features associated with each of the at least two data objects. The rule set may use feature(s) that explain the changed spatial coordinates. The data objects may be selectively rearranged within the canvas space by applying the generated rule set to any remaining data objects among the set of data objects so as to assign spatial coordinates to the remaining objects. For each of the data objects, the spatial coordinates may be stored as new semantic feature(s) within the vector of features for that data object.
Extracting dependencies between network assets using deep learning
A network analysis tool receives network flow information and uses deep learningmachine learning that models high-level abstractions in the network flow informationto identify dependencies between network assets. Based on the identified dependencies, the network analysis tool can discover functional relationships between network assets. For example, a network analysis tool receives network flow information, identifies dependencies between multiple network assets based on evaluation of the network flow information, and outputs results of the identification of the dependencies. When evaluating the network flow information, the network analysis tool can pre-process the network flow information to produce input vectors, use deep learning to extract patterns in the input vectors, and then determine dependencies based on the extracted patterns. The network analysis tool can repeat this process so as to update an assessment of the dependencies between network assets on a near real-time basis.
SYSTEM AND METHOD OF PRECONCENTRATING ANALYTES IN A MICROFLUIDIC DEVICE
Electrokinetic injection is used almost exclusively for microchip electrophoresis. We describe a new approach, based on pneumatic valving, that overcomes the limitations of electrokinetic injection. A detailed description is in the attached file.
SYSTEM AND METHOD OF PRECONCENTRATING ANALYTES IN A MICROFLUIDIC DEVICE
A method and system for preconcentrating analytes at a microvalve in a microfluidic device is disclosed. The system includes a sample channel loaded with a sample solution. The sample channel includes a semi-permeable membrane microvalve. An electric potential is applied at or across the microvalve to preconcentrate the sample solution when the microvalve is closed. The method includes pretreatments of the device or valve for preconcentration of the analytes. For preconcentration of anionic analytes, the device is baked. For preconcentration of the cationic analytes, the surface of the membrane microvalve is coated with a polycationic coating, and the device is baked.
High-Pressure, High-Temperature Magic Angle Spinning Nuclear Magnetic Resonance Devices and Processes for Making and Using Same
Re-usable ceramic magic angle spinning (MAS) NMR rotors constructed of high-mechanic strength ceramics are detailed that include a sample compartment that maintains high pressures up to at least about 200 atmospheres (atm) and high temperatures up to about least about 300° C. during operation. The rotor designs minimize pressure losses stemming from penetration over an extended period of time. The present invention makes possible a variety of in-situ high pressure, high temperature MAS NMR experiments not previously achieved in the prior art.
Search Systems and Computer-Implemented Search Methods
Search systems and computer-implemented search methods are described. In one aspect, a search system includes a communications interface configured to access a plurality of data items of a collection, wherein the data items include a plurality of image objects individually comprising image data utilized to generate an image of the respective data item. The search system may include processing circuitry coupled with the communications interface and configured to process the image data of the data items of the collection to identify a plurality of image content facets which are indicative of image content contained within the images and to associate the image objects with the image content facets and a display coupled with the processing circuitry and configured to depict the image objects associated with the image content facets.
SEALED MAGIC ANGLE SPINNING NUCLEAR MAGNETIC RESONANCE PROBE AND PROCESS FOR SPECTROSCOPY OF HAZARDOUS SAMPLES
This invention is a magic-angle-spinning (MAS) nuclear magnetic resonance (NMR) probe with a unique sealed and filtered sample compartment. The modular two-layer compartment was conceived to ensure secure, efficient containment of hazardous samples while preserving convenience of operation and state-of-the-art NMR performance. High resolution NMR experiments on solid samples typically require the flow of large volumes of gas at high pressures (> 50 psi) to spin rotors containing the sample. Under conditions of high gas flow, dispersal of a hazardous sample can occur through leaks or failure of the rotor. The containment system described here allows high pressure gas to flow into the compartment to spin the sample, while providing a securely filtered exit port to vent the gas. Even in the event of a failure of the rotor, such a compartment will prevent the dispersal of sample outside the containment area. The modular design allows the sample compartment to be separated from the rest of the probe for convenient cleanup, disposal, or contamination checks. In addition to its protective function, the sealed compartment can also be used to maintain a sample in an inert atmosphere during MAS NMR experiments. This is in contrast to standard MAS NMR probes, which are usually well ventilated and open to the atmosphere in order to allow the free flow of gases.