Abstract: The current disclosure provides alternating current based systems and methods to develop chemical compounds, such as drug molecules using electrochemistry in organic synthesis.

Abstract: Examples described herein include methods, devices, and systems which compensates input data for I/Q imbalance or noise related thereto to generate compensated input data. In doing such the above compensation, during an uplink transmission time interval (TTI), a switch path is activated to provide converted input data to a receiver stage including a recurrent neural network (RNN). The RNN calculates an error representative of the noise based partly on the input signal to be transmitted and a feedback signal to generate filter coefficient data associated with the I/Q imbalance. The feedback signal is provided, after processing through the receiver, to the RNN. During an uplink TTI, the converted input data is transmitted as the RF wireless transmission via an RF antenna. During a downlink TTI, the switch path is deactivated and the receiver stage receives an additional RF wireless transmission to be processed in the receiver stage.

Abstract: Examples described herein include systems and methods which include wireless devices and systems with examples of full duplex compensation with a self interference noise calculator. The self-interference noise calculator may be coupled to antennas of a wireless device and configured to generate adjusted signals that compensate self-interference. The self-interference noise calculator may include a network of processing elements configured to combine transmission signals into sets of intermediate results. Each set of intermediate results may be summed in the self-interference noise calculator to generate a corresponding adjusted signal. The adjusted signal is received by a corresponding wireless receiver to compensate for the self-interference noise generated by a wireless transmitter transmitting on the same frequency band as the wireless receiver is receiving.

Abstract: Examples described herein include methods, devices, and systems which may compensate input data for nonlinear power amplifier noise to generate compensated input data. In compensating the noise, during an uplink transmission time interval (TTI), a switch path is activated to provide amplified input data to a receiver stage including a recurrent neural network (RNN). The RNN may calculate an error representative of the noise based partly on the input signal to be transmitted and a feedback signal to generate filter coefficient data associated with the power amplifier noise. The feedback signal is provided, after processing through the receiver, to the RNN. During an uplink TTI, the amplified input data may also be transmitted as the RF wireless transmission via an RF antenna. During a downlink TTI, the switch path may be deactivated and the receiver stage may receive an additional RF wireless transmission to be processed in the receiver stage.

Abstract: The present invention discloses an asymmetrical PN junction thermoelectric couple structure and its parameter determination method. By changing the structural parameters of p-type semiconductor or n-type semiconductor, the current generated by p-type semiconductor is equal to the current generated by the n-type semiconductor, so that the high-efficiency output of PN junction thermoelectric couple can be realized. Meanwhile, the present invention provides a method for determining the parameters of PN junction based on the numerical solution method. Finally, the optimal size parameters of PN junction are obtained.

Abstract: Examples described herein utilize multi-layer neural networks to decode encoded data (e.g., data encoded using one or more encoding techniques). The neural networks have nonlinear mapping and distributed processing capabilities which are advantageous in many systems employing the neural network decoders. In this manner, neural networks described herein are used to implement error code correction (ECC) decoders.

Abstract: The present application relates to a supercritical fluid injection foaming polylactide foam material and a preparation method therefor. The method includes: first obtaining a surface-modified cellulose nanofiber aqueous solution; then melting and blending the cellulose nanofiber aqueous solution and a polylactide twice; passing same through extrusion, cooling under water, and granulation so as to obtain a polylactide/cellulose nanofiber composite material; then plasticizing and melting the polylactide/cellulose nanofiber composite material in a microporous foaming injection molding machine; uniformly mixing same with a supercritical fluid foaming agent in the injection molding machine; injecting same into a mold cavity; and subjecting the resultant to post-treatment so as to obtain a polylactide foam material.

Abstract: The present disclosure relates to, inter alia, a method of quantitating an amount of an antibody molecule from a mixture comprising two or more antibody molecules, comprising separating each of the two or more antibody molecules from the mixture by hydrophobic interaction chromatography high performance liquid chromatography (HIC-HPLC) and quantitating an amount of each antibody molecule, wherein the molecular weight of each antibody molecule is within 15 kDa of any other antibody molecule in the mixture and either each antibody molecule is different from another antibody molecule in the mixture by more than about 0.25 unit on the Kyte & Doolittle hydropathy scale or each of the antibody molecules when nm alone on HIC-HPLC elutes at distinct run time with little overlap from the other antibody molecules in the mixture, or both.

Abstract: Examples described herein include systems and methods which include wireless devices and systems with examples of full duplex compensation with a self-interference noise calculator. The self-interference noise calculator may be coupled to antennas of a wireless device and configured to generate adjusted signals that compensate self-interference. The self-interference noise calculator may include a network of processing elements configured to combine transmission signals into sets of intermediate results. Each set of intermediate results may be summed in the self-interference noise calculator to generate a corresponding adjusted signal. The adjusted signal is received by a corresponding wireless receiver to compensate for the self-interference noise generated by a wireless transmitter transmitting on the same frequency band as the wireless receiver is receiving.

Abstract: Examples described herein include systems and methods which include an apparatus comprising a memory array including a plurality of memory cells and a memory controller coupled to the memory array. The memory controller comprises a memory mapper configured to configure a memory map on the basis of a memory command associated with a memory access operation. The memory map comprises a specific sequence of memory access instructions to access at least one memory cell of the memory array. For example, the specific sequence of memory access instructions for a diagonal memory command comprises a sequence of memory access instructions that each access a memory cell along a diagonal of the memory array.

Abstract: Examples described herein include systems and methods which include wireless devices and systems with examples of multiple frequency bands transmission with a recurrent neural network that compensates for the self-interference noise generated by power amplifiers at harmonic frequencies of a respective wireless receiver. The recurrent neural network may be coupled to antennas of a wireless device and configured to generate the adjusted signals that compensate self-interference. The recurrent neural network may include a network of processing elements configured to combine transmission signals into sets of intermediate results. Each set of intermediate results may be summed in the recurrent neural network to generate a corresponding adjusted signal. The adjusted signal is receivable by a corresponding wireless receiver to compensate for the self-interference noise generated by a wireless transmitter transmitting on the same or different frequency band as the wireless receiver is receiving.

Abstract: Examples described herein utilize multi-layer neural networks, such as multi-layer recurrent neural networks to estimate an error-reduced version of encoded data based on a retrieved version of encoded data (e.g., data encoded using one or more encoding techniques) from a memory. The neural networks and/or recurrent neural networks may have nonlinear mapping and distributed processing capabilities which may be advantageous in many systems employing a neural network or recurrent neural network to estimate an error-reduced version of encoded data for an error correction coding (ECC) decoder, e.g., to facilitate decoding of the error-reduced version of encoded data at the decoder. In this manner, neural networks or recurrent neural networks described herein may be used to improve or facilitate aspects of decoding at ECC decoders, e.g., by reducing errors present in encoded data due to storage or transmission.

Abstract: Methods and apparatus for performing video processmg matrix operations within a memory fabric. Various embodiments of the present disclosure are directed to converting a memory array into a matrix fabric for discrete cosine transform (DCT) matrix transformations and performing DCT matrix operations therein. Exemplary embodiments described herein perform DCT matrix-matrix multiplication operations within a memory device that includes a matrix fabric and matrix multiplication unit (MMU). In one embodiment, matrix-matrix multiplication operations are obtained using separate matrix-vector products. In one exemplary embodiment, the matrix fabric uses a “crossbar” construction of resistive elements. Each resistive element stores a level of impedance that represents the corresponding matrix coefficient value. The crossbar connectivity can be driven with an electrical signal representing the input vector as an analog voltage.

Abstract: Examples described herein include systems and methods which include wireless devices and systems with examples of full duplex compensation with a self-interference noise calculator that compensates for the self-interference noise generated by power amplifiers at harmonic frequencies of a respective wireless receiver. The self-interference noise calculator may be coupled to antennas of a wireless device and configured to generate the adjusted signals that compensate self-interference. The self-interference noise calculator may include a network of processing elements configured to combine transmission signals into sets of intermediate results. Each set of intermediate results may be summed in the self-interference noise calculator to generate a corresponding adjusted signal.

Abstract: Apparatuses, systems, and methods related to an image processor formed in an array of memory cells are described. An image processor as described herein is configured to reduce complexity and power consumption and/or increase data access bandwidth by performing image processing in the array of memory cells relative to image processing by a host processor external to the memory array. For instance, one apparatus described herein includes sensor circuitry configured to provide an input vector, as a plurality of bits that corresponds to a plurality of color components for an image pixel, and an image processor formed in an array of memory cells. The image processor is coupled to the sensor circuitry to receive the plurality of bits of the input vector. The image processor is configured to perform a color correction operation in the array by performing matrix multiplication on the input vector and a parameter matrix to determine an output vector that is color corrected.

Abstract: Apparatuses, systems, and methods related to memory pooling between selected memory resources are described. A system using a memory pool formed as such may enable performance of functions, including automated functions critical for prevention of damage to a product, personnel safety, and/or reliable operation, based on increased access to data that may improve performance of a mission profile. For instance, one apparatus described herein includes a memory resource, a processing resource coupled to the memory resource, and a transceiver resource coupled to the processing resource. The memory resource, the processing resource, and the transceiver resource are configured to enable formation of a memory pool between the memory resource and another memory resource at another apparatus responsive to a request to access the other memory resource transmitted from the processing resource via the transceiver.

Abstract: Examples described herein include systems and methods which include wireless devices and systems with examples of cross correlation including symbols indicative of radio frequency (RF) energy. An electronic device including a statistic calculator may be configured to calculate a statistic including the cross-correlation of the symbols. The electronic device may include a comparator configured to provide a signal indicative of a presence or absence of a wireless communication signal in the particular portion of the wireless spectrum based on a comparison of the statistic with a threshold. A decoder/precoder may be configured to receive the signal indicative of the presence or absence of the wireless communication signal and to decode the symbols responsive to a signal indicative of the presence of the wireless communication signal. Examples of systems and methods described herein may facilitate the processing of data for wireless communications in a power-efficient and time-efficient manner.

Abstract: Systems, apparatuses and method related to remotely executable instructions are described. A device may be wirelessly coupled to (e.g., physically separated) another device, which may be in a physically separate device. The another device may remotely execute instructions associated with performing various operations, which would have been entirely executed at the device absent the another device. The outputs obtained as a result of the execution may be transmitted, via the transceiver, back to the device via a wireless communication link (e.g., using resources of an ultra high frequency (UHF), super high frequency (SHF), extremely high frequency (EHF), and/or tremendously high frequency (THF) bands). The another device at which the instructions are remotely executable may include memory resources, processing resources, and transceiver resources; they may be configured to use one or several communication protocols over licensed or shared frequency spectrum bands, directly (e.g.

Abstract: Methods, apparatuses, and systems for tensor memory access are described. Multiple data located in different physical addresses of memory may be concurrently read or written by, for example, employing various processing patterns of tensor or matrix related computations. A memory controller, which may comprise a data address generator, may be configured to generate a sequence of memory addresses for a memory access operation based on a starting address and a dimension of a tensor or matrix. At least one dimension of a tensor or matrix may correspond to a row, a column, a diagonal, a determinant, or an Nth dimension of the tensor or matrix. The memory controller may also comprise a buffer configured to read and write the data generated from or according to a sequence of memory of addresses.