Abstract: A system for automated, artificial intelligence based oocyte identification and processing includes an imaging system, a set of stations, a set of robotic arms, and an artificial intelligence/machine learning system. The imaging system is positioned in proximity to a biological sample containing a candidate cumulus oocyte complex. The imaging system is configured to identify and locate the candidate cumulus oocyte complex within the biological sample. Each station of the set of stations is configured to receive the biological sample. The set of robotic arms is configured to move the biological sample between one or more stations of the set of stations and denude the candidate cumulus oocyte complex from the biological sample. The artificial intelligence/machine learning system is operatively coupled to at least one of: the imaging system, the set of robotic arms, or the set of stations.

Abstract: Methods, systems, and media for review content traffic are provided. In accordance with some embodiments of the present invention, a method, implemented on a processor, for reviewing advertisement placement on webpages is provided.

Abstract: This document describes wet chemical etching systems designed to apply etching chemistry to a substrate's surface. The system, in some examples, includes a rotor that grips and rotates the substrate, in conjunction with a weir that forms a crest of wet chemistry beneath it. As the substrate rotates, surface tension draws the wet chemistry onto its surface. The system may also include a controller that manages the substrate's movement through different positions.

Abstract: A method for automated ICSI includes receiving at least one droplet containing an egg in a dish placed on a stage. The method includes using an artificial intelligence/machine learning system (AI/ML system) and an imaging system to detect a zona pellucida. The imaging system includes a microscopy system, a camera system, and a lighting system. The method includes holding the egg using a robotic microtool and lowering a robotic pipettor into the droplet. The method includes using the AI/ML system and imaging system to determine an area at which to hold the egg and positioning the robotic microtool to that area. The method includes using the AI/ML system and imaging system to instruct the robotic microtool to apply negative pressure to hold the egg to the robotic pipettor. The method includes using the AI/ML system and imaging system to determine a target location where zona ablation should be performed.

Abstract: Content management systems, methods, and media using an application level firewall are provided.

Abstract: Sulfate salts are removed from a gold sulfite plating solution via supersaturating a sulfate-rich gold sulfite plating solution to form a sulfate-poor saturated gold sulfite plating solution, and un-saturating the sulfate-poor saturated gold sulfite plating solution to form an unsaturated sulfate-poor gold sulfite plating solution. Gold from the unsaturated sulfate-poor gold sulfite plating solution is electrodeposited onto a workpiece.

Abstract: A specimen holder includes a body, a sleeve, and a wireless transponder. The body has distal and proximal portions, the distal portion including a surface that carries a specimen upon engagement of the body with the specimen, and the proximal portion including a first pair of parallel surfaces. The sleeve has distal and proximal portions, a side wall, and an internal cavity at least partially enclosed by the side wall. The distal portion of the sleeve includes a second pair of parallel surfaces. The wireless transponder is sized to be positioned within the internal cavity of the sleeve. The sleeve is attachable to the body by capturing one of the first and second pairs of parallel surfaces between the other of the first and second pairs of parallel surfaces.

Abstract: A method for automated, artificial-intelligence-based denudation includes scanning, robotically, a dish containing a cumulus-oocyte-complex (COC) using an imaging system and an artificial intelligence/machine learning system (AI/ML system) to create an image object. The imaging system includes a microscopy system, a camera system, and a lighting system. The dish includes an enzyme to remove cumulus cells from an oocyte among the COC. The method includes identifying the COC within the image object, and a location, based on comparing the image object to a threshold using the AI/ML system. The threshold is an optical pattern with a probability of corresponding to a COC mass. The method includes instructing a robotic pipettor to collect the COC at the location. The method includes iteratively collecting the COC within the robotic pipettor and expelling the COC to return it to the dish until the AI/ML system confirms sufficient removal of cumulus and corona cells.

Abstract: A biological specimen of a subject is handled and tracked for a procedure involving that specimen. Prior to initiation of the procedure, a first procedure data structure (PDS) is generated. The first PDS binds an identifier corresponding to the subject with an indicator of a procedure to be performed on the specimen and identifiers of a specimen container and a specimen holder that physically contacts the biological specimen, as well as a scheduled time for the procedure. A schedule of a plurality of PDSs including the first PDS, is displayed on a display device of a graphical user interface. Following initiation of the procedure, the first PDS is updated based on user input, and after the procedure, at least a portion of the first PDS, as updated, is stored in a database in conjunction with other PDSs respectively associated with other completed procedures.

Abstract: Content management systems, methods, and media using an application level firewall are provided.

Abstract: A method for automated ICSI includes receiving at least one droplet containing an egg in a dish placed on a stage. The method includes using an artificial intelligence/machine learning system (AI/ML system) and an imaging system to detect a zona pellucida. The imaging system includes a microscopy system, a camera system, and a lighting system. The method includes holding the egg using a robotic microtool and lowering a robotic pipettor into the droplet. The method includes using the AI/ML system and imaging system to determine an area at which to hold the egg and positioning the robotic microtool to that area. The method includes using the AI/ML system and imaging system to instruct the robotic microtool to apply negative pressure to hold the egg to the robotic pipettor. The method includes using the AI/ML system and imaging system to determine a target location where zona ablation should be performed.

Abstract: An electrochemical deposition fountain reactor for processing spinning semiconductor wafers can include a perforated ionic membrane near the wafer surface through which electrolyte flows. This allows high velocity electrolyte jets to impinge the wafer surface at low bulk flow rates, which reduces the boundary layer at the wafer surface and allows for better replenishment of ions at the wafer surface.

Abstract: An electrochemical deposition fountain reactor for processing spinning semiconductor wafers can include a perforated ionic membrane near the wafer surface through which electrolyte flows. This allows high velocity electrolyte jets to impinge the wafer surface at low bulk flow rates, which reduces the boundary layer at the wafer surface and allows for better replenishment of ions at the wafer surface.

Abstract: A method for automated, artificial-intelligence-based COC retrieval includes using an artificial intelligence/machine learning system (AI/ML system) to optically scan a follicular fluid sample to produce an image object using an imaging system that includes a microscopy system, a camera system, and a lighting system. The method includes comparing the image object to a predetermined threshold using an AI/ML system, wherein the predetermined threshold is at least in part an optical pattern with a probability of corresponding to a cumulus-oocyte-complex (COC). The method includes identifying a COC within the follicular fluid sample based at least in part on the image object satisfying the predetermined threshold. The method includes determining a COC location within the follicular fluid sample based at least in part on identifying a region of the image object corresponding to an optical pattern within the image object that satisfies the predetermined threshold.

Abstract: A method for automated, artificial-intelligence-based egg identification using optical coherence tomography (OCT) includes positioning an OCT imaging system head in proximity to a biological sample containing an oocyte, wherein the OCT is operatively coupled to an artificial intelligence/machine learning system (AI/ML system) and an imaging system, wherein the imaging system includes a camera system, and a lighting system. The method includes creating at least one three-dimensional image of the oocyte using the OCT, AI/ML system, and imaging system. The method includes using the AI/ML system to analyze the three-dimensional image, wherein an analysis includes detection of a polar body's presence or absence based at least in part on planar views of the oocyte.

Abstract: Disclosed is a method of artificial intelligence-based robotic pipetting for cell preparation. The method includes training an artificial intelligence/machine learning system (AI/ML system) to classify images of biological specimens. The method includes storing the classified images. The method includes receiving an image object from an imaging system that includes a microscopy system, a camera system configured to receive imaging from the microscopy system, and a lighting system configured to illuminate a biological material. The method includes processing the image object, using the AJ/ML system to determine a presence of a retrievable target cell. The method includes positioning a robotic pipettor at a target physical orientation relative to the retrievable target cell. The method includes confirming the robotic pipettor's location at the target physical orientation, using AI/ML system.

Abstract: A method of artificial-intelligence-based robotic vitrification includes placing at least one oocyte in a buffer or CPA solution. The method includes processing an image object produced by an imaging system, using an AI/ML system, to determine a location of a retrievable target oocyte. The method includes positioning a robotic pipettor at a target physical orientation relative to the retrievable target oocyte. The method includes confirming the robotic pipettor's location at the target physical orientation, using the AI/ML system. The method includes instructing the robotic pipettor to initiate contact with the retrievable target oocyte and apply negative pressure to secure the oocyte to the robotic pipettor. The method includes using a robotic microtool holder to lower a vitrification assembly or cryo-device of any other make into a buffer or CPA solution dish to a position in proximity to the target physical orientation.

Abstract: A method of artificial-intelligence-based robotic pipetting for spermatozoa preparation includes positioning a vessel containing a semen sample on a staging mechanism, wherein the staging mechanism includes at least one motor to position the vessel at a specified orientation, using an artificial intelligence/machine learning (AI/ML system) system. The method includes confirming a position of the vessel, using the AI/ML system. The method includes directing a robotic pipettor to place a pipette tip within the semen sample at a position specified by the AI/ML system. The method includes aspirating and mixing the semen sample using the robotic pipettor. The method includes receiving an image object from an imaging system that includes a microscopy system, a camera system, and a lighting system. The method includes determining a semen liquefaction state of the semen sample based at least in part on the image object, using the AI/ML system.

Abstract: A method for automated, artificial-intelligence-based IVF microtool control includes receiving a command at a controller associated with an artificial intelligence/machine learning system (AI/ML system) and an imaging system used at least in part to operate robotic components of in vitro fertilization (IVF) module. The method includes retrieving at least one IVF microtool assembly (MA) from a tool inventory location using a first robotic mechanism of the robotics system, based at least in part on the command. The method includes retrieving at least one IVF receptacle using a second robotic mechanism of the robotics system based at least in part on the command. The method includes placing the IVF receptacle on a stage within the IVF module based on the command. The method includes positioning the at least one MA in proximity to the IVF receptacle, using the first robotic mechanism, based at least in part on the command.

Abstract: A method for automated, artificial-intelligence-based egg identification using optical coherence tomography (OCT) includes positioning an OCT imaging system head in proximity to a biological sample containing an oocyte, wherein the OCT is operatively coupled to an artificial intelligence/machine learning system (AI/ML system) and an imaging system, wherein the imaging system includes a camera system, and a lighting system. The method includes creating at least one three-dimensional image of the oocyte using the OCT, AI/ML system, and imaging system. The method includes using the AI/ML system to analyze the three-dimensional image, wherein an analysis includes detection of a polar body's presence or absence based at least in part on planar views of the oocyte.