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21.
公开(公告)号:US12109572B2
公开(公告)日:2024-10-08
申请号:US17792592
申请日:2020-05-21
Applicant: Northeastern University
Inventor: Xiating Feng , Feng Lin , Shiping Li , Xiangxin Su , Jiuyu Zhang
CPC classification number: B02C19/186 , B02C23/02
Abstract: Provided is a use method of a gravity double-tube microwave-assisted grinding device capable of controlling ore thickness. The method comprises the following steps: step 1, estimating a metal mineral content of ores; step 2, calculating a penetration depth of the ores, step 3, determining a feeding size; step 4, determining a material thickness; step 5, determining a discharging speed Vp0; step 6, determining whether the gravity double-tube microwave-assisted grinding device capable of controlling ore thickness adopts a single-tube structure or a double-tube structure; and step 7, conveying the ores, performing heating, optimizing material parameters of the ores, and optimizing microwave parameters. By determining the feeding size of the ores and the material thickness, whether the gravity double-tube microwave-assisted grinding device capable of controlling ore thickness adopts the single-tube structure or the double-tube structure is determined, and the assisted grinding efficiency of a microwave equipment on the ores is improved.
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公开(公告)号:US20240319047A1
公开(公告)日:2024-09-26
申请号:US18028352
申请日:2023-02-08
Applicant: Northeastern University
Inventor: Xiating FENG , Xiwei ZHANG , Lei SHI
CPC classification number: G01M99/005 , E21F17/00
Abstract: Provided is an ultra-large physical simulation facility for deep engineering disasters, including a long-time large-load loading system for a geological model, a 3D printing system of a deep oil, gas and water multiphase multi-component complex geological body model, a high-temperature-chemical-multiphase fluid collaborative injection, monitoring and control system, a robot excavation and monitoring system for a complex engineering structure in a model under deep geological environment, an intelligent ventilation system for a deep metal mine complex drilling, mining and transferring network, an intelligent filling system for a deep metal mine ultra-large stope, a deep-well enhanced geothermal safe intelligent mining system, an all-spatial-temporal intelligent high-precision monitoring system for an excavation and fracture process of a large-scale geological model, and an ultra-large multi-task intelligent collaborative main control and digital twin system for physical simulation tests.
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公开(公告)号:US20240310558A1
公开(公告)日:2024-09-19
申请号:US18577919
申请日:2022-07-08
Applicant: Northeastern University
Inventor: Leila Deravi , Patrick Sullivan , Zhuangsheng Lin , Cassandra Leigh Martin , Ivy Wang , Duncan Bower
CPC classification number: G02B1/005 , B82Y20/00 , C09B19/00 , C09B67/0025 , G02B1/118 , G02B2207/101
Abstract: Described herein are photonic crystals comprising a plurality of substantially uniform zein particles. The photonic crystals can be fabricated by assembling the plurality of substantially uniform zein particles into one or more ordered and periodic structures that generate structural color. Also described herein are methods of using the photonic crystals described herein, e.g., as colorants in consumer products, such as food, drugs and/or cosmetics.
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公开(公告)号:US12090209B2
公开(公告)日:2024-09-17
申请号:US17232105
申请日:2021-04-15
Applicant: Northeastern University , Audax Medical, Inc.
Inventor: Thomas J. Webster , Mark A. Johanson
IPC: A61K47/65 , A61K31/155 , A61K31/519 , A61K47/64 , A61P31/14
CPC classification number: A61K47/65 , A61K31/155 , A61K31/519 , A61K47/64 , A61P31/14
Abstract: Functionalized twin base linkers (TBLs) bind to and deactivate viruses by preventing their entry into cells. Functionalization of TBLs allows them to specifically bind to surface proteins of viruses, where they form structures that limit virus entry into cells and prevent viruses from replicating.
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公开(公告)号:US12062249B2
公开(公告)日:2024-08-13
申请号:US17045902
申请日:2019-05-02
Applicant: Northeastern University
CPC classification number: G06V40/165 , G06F18/21 , G06N3/04 , G06T7/50 , G06T7/70 , G06V10/454 , G06V40/171 , G06T2207/20084 , G06T2207/30201
Abstract: A system, neural network, and corresponding method generate 3D landmarks associated with an object in a 2D image. An embodiment is a system comprising a neural network detector configured to produce planar coordinates of landmarks at points of the object in the 2D image and a depth coordinate estimator. The planar coordinates include planar coordinate pairs. The depth coordinate estimator is configured to receive the 2D image and the planar coordinates and to estimate a depth coordinate for each planar coordinate pair of each landmark to generate the 3D landmarks. The system reduces network parameters from MB to KB and has better performance relative to state-of-the-art methods. The system may be configured to apply the 3D landmarks for face alignment, virtual face makeup, face recognition, eye gaze tracking, face synthesis, or other face related application.
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公开(公告)号:US20240249039A1
公开(公告)日:2024-07-25
申请号:US18421910
申请日:2024-01-24
Applicant: Northeastern University
IPC: G06F30/20
CPC classification number: G06F30/20
Abstract: A computer-based system and corresponding computer-implemented method for validating a black-box model are provided. An initial question is transformed into at least one additional question by rephrasing the initial question based on an initial answer from the black-box model to the initial question. A consistency metric is produced based on consistency of the initial answer and respective additional answers received from the black-box model in response to the at least one additional question. The black-box model is validated based on the consistency metric produced.
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27.
公开(公告)号:US20240205095A1
公开(公告)日:2024-06-20
申请号:US17846197
申请日:2022-06-22
Applicant: Northeastern University
Inventor: Lorenzo BERTIZZOLO , Tommaso MELODIA , Salvatore D'ORO , Hai CHENG
IPC: H04L41/122 , H04W84/06
CPC classification number: H04L41/122 , H04W84/06
Abstract: Provided herein are systems for controlling a network of distributed non-terrestrial nodes including a control framework operative to train and control a plurality of the non-terrestrial nodes, the control framework including a control interface in communication with a network operator to receive one or more specified control objectives, and a learning engine operative to train a virtual non-terrestrial network, wherein the control framework is further operative to transfer knowledge gained through the training of the virtual non-terrestrial network to the network of distributed non-terrestrial nodes as data-driven logic unit configurations tailored for the specified control objectives.
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公开(公告)号:US20240201200A1
公开(公告)日:2024-06-20
申请号:US18556655
申请日:2022-04-22
Applicant: Northeastern University , Scienion GmbH
Inventor: Nikolai Slavov , Andrew Leduc , Richard Huffman , Aileen Murphy , Joshua Cantlon-Bruce
CPC classification number: G01N33/6827 , G01N1/34 , G01N33/6848 , G01N2333/976 , G01N2458/15 , G01N2570/00
Abstract: The disclosure provides methods of forming one or more single-cell proteomic samples, such as by: dispensing n droplets of lysis buffer onto a substantially planar solid surface, wherein n>2: dispensing a single cell into each of the n droplets of lysis buffer to produce n droplets with a lysed single cell: dispensing digestion buffer into each of the n droplets to digest proteins from each lysed single cell to produce n droplets comprising peptides: dispensing a chemical tag into at least a subset of the n droplets comprising the peptides to produce labeled peptides, thereby enabling the labeled peptides in a given droplet to be distinguishable from labeled peptides in at least one other droplet: and applying a fluid to merge at least a subset of the droplets into a combined droplet on the substantially planar surface, thereby combining the labeled peptides to form a single-cell proteomic sample.
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公开(公告)号:US20240193809A1
公开(公告)日:2024-06-13
申请号:US18287518
申请日:2022-05-09
Applicant: Northeastern University
Inventor: Sarah OSTADABBAS , Xiaofei HUANG , Nihang FU , Shuangjun LIU
CPC classification number: G06T7/74 , G06T7/75 , G06T15/04 , G06T2207/10016 , G06T2207/10024 , G06T2207/10028 , G06T2207/10048 , G06T2207/20081 , G06T2207/20084 , G06T2207/30196
Abstract: Methods are provided for estimating a pose of an infant using image analysis and artificial intelligence. A classifier is trained using a dataset containing hybrid synthetic and real infant pose data. Multi-stage invariant representation machine learning strategies are employed that transfer knowledge from adjacent domains of adult poses and synthetic infant images into a fine-tuned domain-adapted infant pose estimation model.
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30.
公开(公告)号:US20240173678A1
公开(公告)日:2024-05-30
申请号:US18521460
申请日:2023-11-28
Applicant: Northeastern University
Inventor: Hongli Zhu
CPC classification number: B01D69/12 , B01D67/0009 , B01D71/02 , B01D71/643 , B01D2325/04 , B01D2325/42
Abstract: Disclosed herein is a double-layer ion-selective membrane, method of production, applications of the double-layer ion-selective membrane as a redox flow cell, a fuel cell, and used for wastewater and air purification. The double-layer ion-selective membrane is comprised of a polyetherimide (PEI) layer and an ultrathin layer comprising porous boron nitride (PBN) flakes enmeshed by a NAFION™ resin. The double layer membrane exhibits ion-selectivity and ion-conductivity enabling the membrane to be used in a redox flow cell battery, a fuel cell battery, and to be used in wastewater and air purification applications.
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