Abstract: Techniques are provided for data discovery and data integration in a data lake. One method comprises obtaining data files from a data lake, wherein each data file comprises multiple records having multiple fields; selecting multiple candidate fields from a data file based on a record type; determining a relevance score for each candidate field from the data file based on multiple features extracted from the data file; and clustering the scored candidate fields into clusters of similar domains using a hashing algorithm, wherein a given cluster comprises candidate fields, wherein multiple data files can be integrated based on a domain of the candidate fields in the given cluster. The relevance score for each candidate field is based on multiple features comprising, for example, features that take into account a morphological or semantic similarity between file name, file metadata and/or file records and features that consider statistics of candidate fields in a data file.

Abstract: Deep brain stimulation (DBS) can be used to treat many neurological conditions beyond traditional movement disorders. When patients do not suffer from traditional movement disorders, medical professionals cannot use traditional observation-based methods to configure the DBS system. A new method for selecting stimulation configurations can include recording internal data and external data as the patient performs (or attempts to perform) a motor task. The internal data is electrophysiology data recorded by a plurality of DBS electrodes, used to identify at least one of the plurality of electrodes closest to a neuronal population involved in control of the at least one motor task. The external data is electroencephalogram (EEG) data recorded by scalp electrodes, which is used to select at least one of the potential stimulation electrodes to deliver the DBS. When the electrode(s) delivering the DBS are selected, optimal parameters for the DBS are then chosen.

Abstract: Techniques are provided for data discovery and data integration in a data lake. One method comprises obtaining data files from a data lake, wherein each data file comprises multiple records having multiple fields; selecting multiple candidate fields from a data file based on a record type; determining a relevance score for each candidate field from the data file based on multiple features extracted from the data file; and clustering the scored candidate fields into clusters of similar domains using a hashing algorithm, wherein a given cluster comprises candidate fields, wherein multiple data files can be integrated based on a domain of the candidate fields in the given cluster. The relevance score for each candidate field is based on multiple features comprising, for example, features that take into account a morphological or semantic similarity between file name, file metadata and/or file records and features that consider statistics of candidate fields in a data file.

Abstract: Techniques are provided for dataflow execution time estimation for distributed processing frameworks. An exemplary method comprises: obtaining an input dataset for a dataflow for execution; determining a substantially minimal data unit for a given operation of the dataflow processed by the given operation; estimating a number of rounds required to execute a number of data units in the input dataset using nodes assigned to execute the given operation; determining an execution time spent by the given operation to process one data unit; estimating the execution time for the given operation based on the execution time spent by the given operation to process one data unit and the number of rounds required to execute the number of data units in the input dataset; and executing the given operation with the input dataset. A persistent cost model is optionally employed to record the execution times of known dataflow operations.

Abstract: A dataflow execution environment is provided with dynamic placement of cache operations. An exemplary method comprises: obtaining a first cache placement plan for a dataflow comprised of multiple operations; executing operations of the dataflow and updating a number of references to the executed operations to reflect remaining executions of the executed operations; determining a current cache gain by updating an estimated reduction in the total execution cost for the dataflow of the first cache placement plan; determining an alternative cache placement plan for the dataflow following the execution; and implementing the alternative cache placement plan based on a predefined threshold criteria. A cost model is optionally updated for the executed operations using an actual execution time of the executed operations. A cached dataset can be removed from memory based on the number of references to the operations that generated the cached datasets.

Abstract: A dataflow execution environment is provided with dynamic placement of cache operations and action execution ordering.

Abstract: A dataflow execution environment is provided with dynamic placement of cache operations and action execution ordering.

Abstract: A system is disclosed for manufacturing a dental workpiece. The system may have a subtractive machine configured to manufacture a base of a dental device from a material blank, and an additive machine configured to manufacture a top of the dental device by adding material onto a surface of the base. The system may also have a controller in communication with the subtractive machine and the additive machine. The controller may be programmed to receive digital data corresponding to a mouth of a particular patient, and to control operation of the subtractive machine to customize the base based on the digital data.

Abstract: Techniques are provided for dataflow execution time estimation for distributed processing frameworks. An exemplary method comprises: obtaining an input dataset for a dataflow for execution; determining a substantially minimal data unit for a given operation of the dataflow processed by the given operation; estimating a number of rounds required to execute a number of data units in the input dataset using nodes assigned to execute the given operation; determining an execution time spent by the given operation to process one data unit; estimating the execution time for the given operation based on the execution time spent by the given operation to process one data unit and the number of rounds required to execute the number of data units in the input dataset; and executing the given operation with the input dataset. A persistent cost model is optionally employed to record the execution times of known dataflow operations.

Abstract: A dataflow execution environment is provided with dynamic placement of cache operations. An exemplary method comprises: obtaining a first cache placement plan for a dataflow comprised of multiple operations; executing operations of the dataflow and updating a number of references to the executed operations to reflect remaining executions of the executed operations; determining a current cache gain by updating an estimated reduction in the total execution cost for the dataflow of the first cache placement plan; determining an alternative cache placement plan for the dataflow following the execution; and implementing the alternative cache placement plan based on a predefined threshold criteria. A cost model is optionally updated for the executed operations using an actual execution time of the executed operations. A cached dataset can be removed from memory based on the number of references to the operations that generated the cached datasets.

Abstract: Techniques are provided for automatic placement of cache operations in a dataflow. An exemplary method obtains a graph representation of a dataflow of operations; determines a number of executions and a computational cost of the operations, and a computational cost of a caching operation to cache a dataset generated by an operation; establishes a dataflow state structure recording values for properties of the dataflow operations for a number of variations of caching various dataflow operations; determines a cache gain factor for dataflow operations as an estimated reduction in the accumulated cost of the dataflow by caching an output dataset of a given operation; determines changes in the dataflow state structure by caching an output dataset of a different operation in the dataflow; and searches the dataflow state structures to determine the output datasets to cache based on a total dataflow execution cost.

Abstract: A cylinder impeller for revolvers, which transmits the trigger pulling movement to a cylinder revolving movement. The impeller includes a cover having inside it a track; a one-piece body having a plate and a slider, said slider being able to slide within and relative to the cover; and a spring arranged between the body slider and the surface of the cover track. Therefore, the cover and the body slide one relative to the other and against the spring action, thus varying the overall length of the impeller and compensating and absorbing possible teeth machining variations of the cylinder extractor.

Abstract: A cylinder impeller for revolvers, which transmits the trigger pulling movement to a cylinder revolving movement. The impeller includes a cover having inside it a track; a one-piece body having a plate and a slider, said slider being able to slide within and relative to the cover; and a spring arranged between the body slider and the surface of the cover track. Therefore, the cover and the body slide one relative to the other and against the spring action, thus varying the overall length of the impeller and compensating and absorbing possible teeth machining variations of the cylinder extractor.

Abstract: A system for treating medical conditions by neuromodulation of one or more target sites in the nervous system. In certain embodiments, at least one of the target sites is the medial thalamic region, including the intralaminar nucleus and the adjacent white and grey matter. In certain embodiments, where there is more than one target site, the other target sites is elsewhere in the nervous system, including the globus pallidus interna, subthalamic nucleus, corpus callosum, cerebellum, cerebral cortex (including the premotor cortex, motor cortex, and sensory cortex), ventral striatum, lateral thalamus, substantia nigra, and pedunculopontine nuclei. The medical conditions include movement disorders or improvement of movement function, stroke, neuropsychiatric or neuropsychologic disorders, neurodevelopmental disorders, and pain. Methods for treating medical conditions by neuromodulation of the intralaminar nuclei either alone or in combination with another target site(s) is also provided.

Abstract: The current request reports an external fixation device to stabilize bone fractures with adaptable configuration during different stages of surgery or during treatment, through the generation of six degrees of freedom among the bone fragments. The device comprises numerous press-connector means, numerous cylindrical bars, numerous osteosynthesis screws and optionally from one to several rigid rings and one or more extension elements that permit generating diverse stable configurations to treat bone fractures.

Abstract: A method is provided for neuromodulation to treat stroke. One step of the method includes recording an input waveform from a first site in the nervous system in a source subject. The first site is healthy or at least partially functioning. Next, an output waveform is applied to a second site in the nervous system of a target subject suffering from the stoke. The second site is diseased due to the stroke.

Abstract: A neurostimulation system can include a memory, a playback system, a stimulation electrode, and a controller. The memory can store data for first and second input waveforms. The playback system can provides first and second output waveforms, based on the first and second input waveforms in the memory, respectively, to form composite patterns of stimulation or waveforms. The first output waveform can be different than the second output waveform. The second output waveform can be periodically superimposed on the first output waveform. The controller can be in communication with the stimulation electrode. The controller can be configured to control application of the composite pattern of stimulation or waveform to a target site in a body of a subject suffering from a medical condition.

Abstract: This disclosure relates to a system and method to evaluate movement disorders. A movement data aggregator can combine data from a plurality of sensors into an aggregate movement data describing multi-dimensional movement of a handheld device. A calculator to compute an indication of a movement disorder based on the movement vector data and user input data, the user input data being generated in response to physical interaction between the handheld device and a human machine interface of a computing device/machine that is separate from the handheld device. In some examples, the handheld device can communicate with computing device via a wireless interface.

Abstract: Neuromodulation assemblies with lead bodies having curvatures that mimic the curvatures of the splenium, trunk, genu, or rostrum of the corpus callosum. Methods of stimulating the corpus callosum and methods of securing an electrical lead in the brain are also provided.

Abstract: The current request reports an external fixation device to stabilize bone fractures with adaptable configuration during different stages of surgery or during treatment, through the generation of six degrees of freedom among the bone fragments. The device comprises numerous press-connector means, numerous cylindrical bars, numerous osteosynthesis screws and optionally from one to several rigid rings and one or more extension elements that permit generating diverse stable configurations to treat bone fractures.