Abstract: The examples of the present disclosure provide a semiconductor device and a manufacturing method thereof, and a memory system. The semiconductor device comprises a first electrode and a first insulating layer. The first electrode extends along a first direction and comprises a first end surface, a second end surface, and a sidewall. The first end surface and the second end surface are oppositely arranged in the first direction, and the sidewall connects the first end surface with the second end surface. The first insulating layer surrounds at least a portion of a sidewall of a first end portion of the first electrode and is located on a side of the first end surface away from the second end surface.

Abstract: The present application discloses an edge-computation-based dynamic optimization control system for an energy storage cluster, and relates to the technical field of energy storage clusters. The edge-computation-based dynamic optimization control system includes: acquiring historical data of the energy storage cluster and local data of edge nodes; predicting a time sequence by using an ARIMA model, recognizing and correcting a non-linear error by using a BP neural network, and outputting a final power prediction value. By means of short-term trend prediction of ARIMA and error correction of the BP neural network, the stable operation of an energy storage system in a grid can be guaranteed; by performing local BP neural network model training on each edge node, distributed computation resources can be sufficiently utilized; and under a synergistic effect of a bi-level optimization model, a final power distribution solution and a transmission path optimization result will be outputted.

Abstract: Systems and methods for predicting that a stock keeping unit (SKU) is likely to be scrapped and performing preventative actions accordingly. The system receives a request to initiate a process related to predicting scrap likelihood associated with a plurality of SKUs, inputs data associated with each SKU into a trained prediction model, outputs, from the trained prediction model, a prediction value for each SKU, measures the trained prediction model by calculating a set of values, and generates a matrix comprising the calculated set of values. Using the matrix, a threshold prediction value is determined, and each SKU prediction value is compared to the threshold prediction value. Based on the comparison, a SKU of the plurality of SKUs is predicted as likely to be scrapped and at least one of a plurality of preventative actions is performed.

Abstract: Provided is a method of providing information related to item scrap, the method including at least one of confirming information on an item scrapped in a fulfillment center, confirming a cause of scrapping the item based on the information on the item including a code life of the item and an average sales amount of the item, and providing information indicating the cause of scrapping the item.

Abstract: Provided is a method of providing information related to an item shortage, the method including confirming information on an item of which a shortage occurs in a fulfillment center, confirming a cause of an item shortage based on the information on the item, and providing information indicating the cause of the item shortage.

Abstract: The present invention provides, among other things, improved therapeutic compositions comprising a C3 fusion protein and methods of making and using the same. In particular, the present invention provides improved methods for the treatment of spinal cord injury and other CNS trauma and/or facilitate axon growth or other tissue repair.

Abstract: Systems and methods for predicting that a stock keeping unit (SKU) is likely to be scrapped and performing preventative actions accordingly. The system receives a request to initiate a process related to predicting scrap likelihood associated with a plurality of SKUs, inputs data associated with each SKU into a trained prediction model, outputs, from the trained prediction model, a prediction value for each SKU, measures the trained prediction model by calculating a set of values, and generates a matrix comprising the calculated set of values. Using the matrix, a threshold prediction value is determined, and each SKU prediction value is compared to the threshold prediction value. Based on the comparison, a SKU of the plurality of SKUs is predicted as likely to be scrapped and at least one of a plurality of preventative actions is performed.

Abstract: The present invention provides, among other things, improved therapeutic compositions comprising a C3 fusion protein and methods of making and using the same. In particular, the present invention provides improved methods for the treatment of spinal cord injury and other CNS trauma and/or facilitate axon growth or other tissue repair.

Abstract: Methods and systems for determining a cause of out of stock condition by running a decision tree against historical information associated with the out of stock item and contacting a supplier of the out of stock item to request items based on the determined cause. The system receives information associated with an out of stock item from a system storing information associated with items in a fulfillment center, the information collected over an extended period, determines a cause of the out of stock condition by running a decision tree against the received information, the decision tree includes a plurality of conditions, and predicts an out of stock condition of the item based on the determined cause. Based on the prediction, the system contacts a supplier of the out of stock item to request more items.

Abstract: The present invention provides, among other things, improved therapeutic compositions comprising a C3 fusion protein and methods of making and using the same. In particular, the present invention provides improved methods for the treatment of spinal cord injury and other CNS trauma and/or facilitate axon growth or other tissue repair.

Abstract: Methods and systems for determining a cause of out of stock condition by running a decision tree against historical information associated with the out of stock item and contacting a supplier of the out of stock item to request items based on the determined cause. The system receives information associated with an out of stock item from a system storing information associated with items in a fulfillment center, the information collected over an extended period, determines a cause of the out of stock condition by running a decision tree against the received information, the decision tree includes a plurality of conditions, and predicts an out of stock condition of the item based on the determined cause. Based on the prediction, the system contacts a supplier of the out of stock item to request more items.

Abstract: A noise cancellation system comprises a first noise cancellation apparatus configured to process an I-channel signal, wherein an I-channel differential mode second-order intermodulation component and an I-channel common mode second-order intermodulation component cancel each other in the first noise cancellation apparatus and a second noise cancellation apparatus configured to process a Q-channel signal, wherein a Q-channel differential mode second-order intermodulation component and a Q-channel common mode second-order intermodulation component cancel each other in the second noise cancellation apparatus.

Abstract: The refractive index of a fiber core of a few mode optical fiber is n1. A cladding layer surrounding the fiber core includes: a downward-concave cladding layer surrounding the fiber core, the refractive index thereof is n2; a first upward-convex cladding layer surrounding the downward-concave cladding layer, the refractive index thereof is n3; a second upward-convex cladding layer surrounding the first upward-convex cladding layer, the refractive index thereof is n4; an outer layer surrounding the second upward-convex cladding layer, the refractive index thereof is n5. The refractive indexes of the fiber core, the downward-concave cladding layer, the first upward-convex cladding layer, the second upward-convex cladding layer, the outer layer satisfy: n1>n3>n4>n5>n2. The fiber is a non-single mode in a direct waveguide state, and equivalent single-mode transmission can be achieved when the optical fiber is bent at a specific bending radius.

Abstract: A low noise amplifier comprising an adjustable gain and a variable impedance controller is provided. The low noise amplifier is configured to sink current and to adjust a shunt resistance substantially simultaneously.

Abstract: The refractive index of a fiber core of a few mode optical fiber is n1. A cladding layer surrounding the fiber core includes: a downward-concave cladding layer surrounding the fiber core, the refractive index thereof is n2; a first upward-convex cladding layer surrounding the downward-concave cladding layer, the refractive index thereof is n3; a second upward-convex cladding layer surrounding the first upward-convex cladding layer, the refractive index thereof is n4; an outer layer surrounding the second upward-convex cladding layer, the refractive index thereof is n5. The refractive indexes of the fiber core, the downward-concave cladding layer, the first upward-convex cladding layer, the second upward-convex cladding layer, the outer layer satisfy: n1>n3>n4>n5>n2. The fiber is a non-single mode in a direct waveguide state, and equivalent single-mode transmission can be achieved when the optical fiber is bent at a specific bending radius.

Abstract: A method is disclosed. The method may include a method for management of an electronic device. The method may include acquiring operation data of an electronic device. The method may include determining, based on the operation data of the electronic device whether to send a data-acquiring command to the electronic device. The method may include sending a data-acquiring command to the electronic device. The method may include receiving, from the electronic device, response data generated by the electronic device in response to the data-acquiring command. An apparatus and program product are also disclosed.

Abstract: A low noise amplifier comprising an adjustable gain and a variable impedance controller is provided. The low noise amplifier is configured to sink current and to adjust a shunt resistance substantially simultaneously.

Abstract: A noise cancellation system comprises a first noise cancellation apparatus configured to process an I-channel signal, wherein an I-channel differential mode second-order intermodulation component and an I-channel common mode second-order intermodulation component cancel each other in the first noise cancellation apparatus and a second noise cancellation apparatus configured to process a Q-channel signal, wherein a Q-channel differential mode second-order intermodulation component and a Q-channel common mode second-order intermodulation component cancel each other in the second noise cancellation apparatus.

Abstract: A mobile device comprising an antenna, a receiver coupled to the antenna, and a transmitter coupled to the antenna, wherein the receiver, the transmitter, or both comprise a low noise amplifier comprising an adjustable gain and a variable impedance controller, and wherein the low noise amplifier is configured to sink current and to adjust a shunt resistance substantially simultaneously. Included is a method comprising receiving an electrical signal, substantially simultaneously adjusting an input impedance and a gain factor, amplifying the electrical signal, thereby producing an amplified signal, and outputting the amplified signal.

Abstract: A noise cancellation system comprises an I-channel mixer configured to receive a radio frequency signal from an antenna and an intermediate frequency signal from a local oscillator, a Q-channel mixer configured to receive the radio frequency signal from the antenna and a phase-shifted intermediate frequency signal from the local oscillator, a first noise cancellation apparatus connected with the I-channel mixer, wherein an I-channel differential mode second-order intermodulation component and an I-channel common mode second-order intermodulation component cancel each other in the first noise cancellation apparatus and a second noise cancellation apparatus connected with the Q-channel mixer, wherein a Q-channel differential mode second-order intermodulation component and a Q-channel common mode second-order intermodulation component cancel each other in the second noise cancellation apparatus.