Abstract: Disclosed are an integrate-and-fire neuron circuit implemented to enable an integrate-and-fire operation with only a small number of devices by using bistable resistance characteristics of the same two heterojunction NPN devices, unlike a CMOS-based integrate-and-fire neuron circuit having a complex structure, and an operation method thereof. In one or more aspects, an integrate-and-fire neuron circuit and an operation method thereof can increase neuron integration in a system by implementing an integrate-and-fire operation of neurons using only three transistors and two capacitors, or two transistors, one resistor and one capacitor, can improve the efficiency of spiking neural network learning by controlling a fire threshold point of neurons through regulation of a gate voltage of the same two NPN devices, and can expect an increase in energy efficiency of the entire system through inhibition of excessive fire by implementing excitatory and inhibitory post-synaptic potentials.

Abstract: This patent document provides a caged catalyst comprising a catalyst encapsulated in a cage compound of Formula I represented [ZrIV6O4(OI)4(linker)6]). The catalysts demonstrated excellent activities and size selectivity in a model RCM reaction, suggesting successful encapsulation into MOFs. ROMP of cyclopentene mediated by G3@UiO-67 achieved significantly higher molecular weight and lower dispersity than the counterpart mediated by the free catalyst. The ultra-high molecular weight polymers generated by the encapsulated catalysts demonstrated significantly improved mechanical and adhesive properties compared to the low molecular weight counterparts and commercial polymers. The simplicity and generality make this method readily applicable to the ROMP of a wide range of low-strain cyclic olefins.

Abstract: A distributed machine learning based traffic prediction method is provided for predicting traffic of roads. In this case, the distributed machine learning based traffic prediction method includes distributing global multi-task traffic models by a learning server to learning agents to locally train the traffic models, uploading locally trained traffic models by learning agents to the learning server, updating global multi-task traffic models by the learning server using locally trained traffic model parameters acquired from learning agents, generating a time-dependent global traffic map by the learning server using the well trained global multi-task traffic models, distributing the time-dependent global traffic map to vehicles traveling on the roads, and computing an optimal travel route with the least travel time by a vehicle using the time-dependent global traffic map based on a driving plan.

Abstract: A method of additive manufacturing is described wherein powder material is spread in a layer, contacted with a binding polymer and cured with light. Also described is a system for preparing additive manufactured objects such as molds, tools and composites.

Abstract: The disclosure provides a method for manufacturing a cation exchange membrane for a fuel cell, comprising the steps of providing a first hydrocarbon-based polymer having a sulfonic acid group; forming a mixture by mixing the first hydrocarbon-based polymer with 3,4-ethylenedioxythiophene (EDOT); adding an oxidizing agent to the mixture to prepare a cation exchange membrane; and activating the sulfonic acid group of the cation exchange membrane.

Abstract: A method for learning a representation of a sequence of frames includes encoding, via an encoder network, the sequence of frames to obtain a set of feature maps and extracting, a motion-guided slot learning mechanism, mid-level features from the set of feature maps. The method further includes quantizing the mid-level features via a vector quantization process to obtain a set of tokens, and decoding, via a decoder network, the tokens to obtain a reconstructed sequence of frames. The method still further includes optimizing a combination of a reconstruction loss and a motion loss to train the encoder and decoder networks.

Abstract: The present invention relates to functionalized Maleimides and Isomaleimides of general Formula (I) and a process for the preparation thereof, involving [3+2] annulation of ?,?-unsaturated aldehydes with carbamoyl alkylates via an enolate pathway to afford highly functionalized compounds of Formula (I);

Abstract: Described herein are peptides that can be used to treat pain or increase pain sensitivity in subject in need of treatment. Additionally, peptides of the present disclosure can be administered with an analgesic agent and/or anesthetic agent. Peptides of the present disclosure are suitable for use when a subject in need of treatment has an injury, a chronic disease, a chronic inflammation, Morton's neuroma, operative/post-operative pain, or a combination thereof.

Abstract: Methods of transferring nanostructures from a first substrate to another substrate using a copolymer polymerized from one or more non-crosslinking monomers and one or more comonomers bearing crosslinkable groups as a transfer medium are provided. Relative to a poly(methyl methacrylate) homopolymer, the crosslinkable copolymers bond more strongly to the first substrate and, as a result, are able to transfer even very narrow nanostructures between substrates with high transfer yields.

Abstract: Methods that implement image-guided tissue analysis, MRI-based computational modeling, and imaging informatics to analyze the diversity and dynamics of molecularly-distinct subpopulations and the evolving competitive landscapes in human glioblastoma multiforme (“GBM”) are provided. Machine learning models are constructed based on multiparametric MRI data and molecular data (e.g., CNV, exome, gene expression). Models can also be built based on specific biological factors, such as sex and age. Inputting MRI data into the trained predictive models generates maps that depict spatial patterns of molecular markers, which can be used to quantify and co-localize regions molecularly distinct subpopulations in tumors and other regions, such as the non-enhancing parenchyma, or brain around tumor (“BAT”) regions.

Abstract: A filter element for a heating, ventilation, and/or air conditioning (HVAC) system includes a filter media and a support element. The support element includes a first interface member, a second interface member, and a connecting member. The first interface member and the second interface member define opposing lateral ends of the support element and extend parallel to one another. The first interface member and the second interface member are engageable with complementary receiving structures of a rail to support the support element on the rail. The connecting member is coupled to the filter media and extends from the first interface member to the second interface member. The connecting member includes a concave portion extending from the first interface member and a convex portion extending from the second interface member.

Abstract: A ceria nanoparticles preparation method is provided. The method includes preparing a mixed solution containing a cerium precursor and an imidazole derivative and preparing ceria nanoparticles by stirring the mixed solution.

Abstract: Peptides useful as inflammasome inhibitors are disclosed and can comprise an H2 helix of a pyrin domain, wherein at least two non-consecutive amino acids of the H2 helix are covalently linked. Methods of treating a subject with a disease comprising administering to the subject the disclosed peptides are also disclosed. Further, disclosed herein are methods of inhibiting binding between a first polypeptide comprising a pyrin domain and a second polypeptide comprising a pyrin domain, the method comprising contacting either the first polypeptide or the second polypeptide with the disclosed peptides.

Abstract: The disclosure provides a method of using blood or fractions thereof, e.g., serum, obtained from a mammal subjected to liver surgery, for example, obtained following a partial hepatectomy, to increase the engraftment, proliferation and/or functionality of cells on a biocompatible scaffold.

Abstract: Substrates having a textured surface that can maintain or improve droplet mobility in both the Cassie and Wenzel states include a textured surface and a conformal lubricant layer thereover. The textured surface can include a plurality of raised first elements and a plurality of second elements thereon and the conformal lubricant layer over the plurality of raised first elements and covering the plurality of second elements. The plurality of raised first elements can have an average height of between 0.5 ?m and 500 ?m, and the plurality of second elements can have an average height of between 0.01 ?m and 10 ?m. Such substrates can be prepared by texturing a surface of a substrate with a plurality of raised first elements and a plurality of second elements thereon; optionally silanizing the textured surface and applying a lubricant layer over the plurality of raised first elements and between the plurality of second elements.

Abstract: A resource processing method and a resource processing device are provided. The method includes: configuring at least one downlink resource in addition to a cell-specific resource configuration; and/or configuring at least one uplink resource.

Abstract: Provided are a method of growing a two-dimensional transition metal chalcogenide (TMC) film and a method of manufacturing a device including the two-dimensional TMC film. The method of growing a two-dimensional TMC film includes placing a metal layer having a predetermined pattern on a surface of a substrate; separately supplying a chalcogen precursor to a reaction chamber provided with the substrate; supplying a transition metal precursor to the reaction chamber; and evacuating the chalcogen precursor, the transition metal precursor, and by-products generated therefrom from the reaction chamber, wherein an amount of the chalcogen precursor and an amount of the transition metal precursor supplied to the reaction chamber may be controlled.

Abstract: The present disclosure provides a transparent alumina-based plate, and a hot-pressing method to make the transparent alumina-based plate from platelet alumina. Alumina powder with a platelet morphology was hot-pressed to transparency with pre-load pressures of about 0-8 MPa, maximum temperatures of about 1750-1825° C., maximum pressures of about 2.5-80 MPa, and isothermal hold times of 1-7 hours. A novel alumina-based plate has been prepared, wherein the plate has a thickness of 2-5 mm, an in-line transmission of at least 60-75% for a light with a wavelength range of 645-2500 nm, an in-line transmission variance of <15% over the wavelength range of 645-2500 nm, and a relative density of 99.00-99.95%.

Abstract: Systems and methods are provided for synthesizing information from multiple image series of different kernels into a single image series, and also for converting a single baseline image series of a kernel reconstructed by a CT scanner to image series of various other kernels, using deep-learning based methods. For multi-kernel synthesis, a single set of images with desired high spatial resolution and low image noise can be synthesized from multiple image series of different kernels. The synthesized kernel is sufficient for a wide variety of clinical tasks, even in circumstances that would otherwise require many separate image sets. Kernel conversion may be configured to generate images with arbitrary reconstruction kernels from a single baseline kernel. This would reduce the burden on the CT scanner and the archival system, and greatly simplify the clinical workflow.

Abstract: Various examples of methods and systems are provided related to functional deep neural networks (FDNNs), which can be used for high dimensional data analysis. In one example, a FDNN can be trained with a training set of omic data to produce a trained FDNN model. The likelihood of a condition can be determined based upon output indications of the FDNN corresponding to the one or more phenotypes, with the output indications based upon analysis of omic data including a multi-level omic profile from an individual by the trained FDNN. The FDNN model can include a series of basis functions as layers to capture complexity between the omic data with disease phenotypes. A treatment or prevention strategy for the individual can be identified based at least in part upon the likelihood of the condition.