Interface systems for use with surgical instruments

A surgical instrument for use by an operator in a surgical procedure includes an elongate shaft, an end effector extending from the elongate shaft, and a control system. The end effector is articulatable relative to the elongate shaft between a home state position and an articulated position. The control system includes a processor and a memory coupled to the processor to store program instructions. The processor can alert the operator when the end effector reaches the home state position from the articulated position.

Shaft assembly comprising a lockout

An end effector is disclosed comprising a cartridge channel, a staple cartridge positionable in the cartridge channel, and a firing assembly configured to lock itself if the staple cartridge is not positioned in the cartridge channel. Moreover, the firing assembly is configured to lock itself if the staple cartridge has been at least partially spent.

DISTRIBUTED TRANSACTION PROCESSING AND AUTHENTICATION SYSTEM

A method of recording a data transaction comprising, at a device associated with a first entity, determining first seed data, generating a record of a first transaction between the first entity and a second entity, determining second seed data by combining at least the first seed data and the record of the first data transaction, generating a first hash by hashing the second seed data, the first hash comprising a history of data transactions involving the first entity and storing the first hash against the record of the first data transaction in a memory.

METHOD OF FORMING A STRUCTURE INCLUDING SILICON NITRIDE ON TITANIUM NITRIDE AND STRUCTURE FORMED USING THE METHOD

A method of forming a structure including a silicon nitride overlying a titanium nitride layer is disclosed. The method includes forming the titanium nitride layer and the silicon nitride layer in the same reaction chamber—e.g., without a vacuum break—to mitigate oxidation of the titanium nitride layer that might otherwise occur.

System and method for extremely efficient image and pattern recognition and artificial intelligence platform

Specification covers new algorithms, methods, and systems for: Artificial Intelligence; the first application of General-AI. (versus Specific, Vertical, or Narrow-AI) (as humans can do) (which also includes Explainable-AI or XAI); addition of reasoning, inference, and cognitive layers/engines to learning module/engine/layer; soft computing; Information Principle; Stratification; Incremental Enlargement Principle; deep-level/detailed recognition, e.g., image recognition (e.g., for action, gesture, emotion, expression, biometrics, fingerprint, tilted or partial-face, OCR, relationship, position, pattern, and object); Big Data analytics; machine learning; crowd-sourcing; classification; clustering; SVM; similarity measures; Enhanced Boltzmann Machines; Enhanced Convolutional Neural Networks; optimization; search engine; ranking; semantic web; context analysis; question-answering system; soft, fuzzy, or un-sharp boundaries/impreciseness/ambiguities/fuzziness in class or set, e.g., for language analysis; Natural Language Processing (NLP); Computing-with-Words (CWW); parsing; machine translation; music, sound, speech, or speaker recognition; video search and analysis (e.g., “intelligent tracking”, with detailed recognition); image annotation; image or color correction; data reliability; Z-Number; Z-Web; Z-Factor; rules engine; playing games; control system; autonomous vehicles or drones; self-diagnosis and self-repair robots; system diagnosis; medical diagnosis/images; genetics; drug discovery; biomedicine; data mining; event prediction; financial forecasting (e.g., for stocks); economics; risk assessment; fraud detection (e.g., for cryptocurrency); e-mail management; database management; indexing and join operation; memory management; data compression; event-centric social network; social behavior; drone/satellite vision/navigation; smart city/home/appliances/IoT; and Image Ad and Referral Networks, for e-commerce, e.g., 3D shoe recognition, from any view angle.

Locating external interference in a wireless network

A method for determining the location of a source of interference applies data in the vertical dimension to determine the probability of the source being located at various locations, or pixels. The data in the vertical dimension may be used to determine three-dimensional antenna gain for antenna-pixel pairs, and to determine whether a line of sight exists between the antenna-pixel pairs. Probability values are determined for the pixels using one or both of the line of sight information and antenna gain values.

Substrate processing apparatus and substrate transfer method

Examples of a substrate processing apparatus includes a susceptor, a plurality of three or more susceptor pins configured to protrude from an upper surface of the susceptor or be positioned below the upper surface of the susceptor, a transfer arm configured to provide a substrate onto the susceptor or take out a substrate on the susceptor, a plurality of sensors configured to individually detect contact or non-contact of a substrate with the plurality of susceptor pins individually, and a control device configured to monitor a detection result of the plurality of sensors and determine abnormality when an order of variations in a contact state of the substrate with the plurality of susceptor pins is not a predetermined order or when a time difference between the variations in the contact state of the substrate with the plurality of susceptor pins is not within a predetermined time difference range.

Locating external interference in a wireless network

A method for localizing interference uses data available to wireless communication networks to determine probabilities of a source of external interference being located at a plurality of predetermined locations. In a heterogeneous network, data from sites using omnidirectional antennas can be combined with data from multi-sector sites to accurately locate a source of interference.

Ground electrode formed in an electrostatic chuck for a plasma processing chamber

Disclosed herein is a substrate support assembly having a ground electrode mesh disposed therein along a side surface of the substrate support assembly. The substrate support assembly has a body. The body has an outer top surface, an outer side surface and an outer bottom surface enclosing an interior of the body. The body has a ground electrode mesh disposed in the interior of the body and adjacent the outer side surface, wherein the ground electrode does not extend through to the outer top surface or the outer side surface.

Method of compressing tissue within a stapling device and simultaneously displaying of the location of the tissue within the jaws

A surgical system is disclosed including an end effector, a control circuit, a closure member, and a firing member. The end effector includes a first jaw, a second jaw, and an electrode. The first jaw is rotatable relative to the second jaw between an open position and a close position to capture tissue therebetween. The electrode is configured to conduct a sub-therapeutic RF current to the tissue. The control circuit is operably coupled to the electrode. The control circuit is configured to measure impedance of the tissue over time based on the sub-therapeutic RF current. The closure member is configured to move the first jaw towards the second jaw at a closure rate based on the impedance of the tissue. The firing member is configured to move within the end effectors towards a fired position at a firing rate based on the impedance of the tissue.