Patents Assigned to The Trustee of Princeton University
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Publication number: 20230028572Abstract: Disclosed herein is a simple method for generation of high-throughput aerosols of monodisperse micro-shell particles. To create the aerosol, small nozzles are employed blowing slightly compressed air on a thin liquid film. This allows one to generate bubble aerosols consisting of particles having a thin liquid shell surrounding a gas core, which are suspended in a carrier gas flow or environment. The diameter of the created liquid shells is uniform and scales with the inner diameter of the blowing nozzle, enabling control on the size of the produced monodispersed aerosol and formation of particles between few microns to several hundred of microns in outer diameter. The process throughput is very high, reaching several thousands of particles with liquid micro-shells per second for one blowing nozzle.Type: ApplicationFiled: November 19, 2020Publication date: January 26, 2023Applicant: The Trustees of Princeton UniversityInventors: Maksym MEZHERICHER, Howard A. STONE
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Patent number: 11562411Abstract: Disclosed is a virtual rating device that associate online ratings with differential time costs by endowing the graphical user interface that solicited ratings from the users with “physics,” including an initial (default) slider position and friction. When ratings are associated with differential time cost, scores correlated more strongly with objective service quality. The differential time costs optimize information when proportional to the deviation from the median score. Correlations between subjective rating scores and objective service performance can be further improved by boosting time costs for reporting extreme scores. The disclosed device lowers the sample size (and therefore costs) required for obtaining reliable, averaged crowd estimates. The disclosed device improves information quality in online rating and feedback systems. By endowing a rating widget with virtual friction to increase the time cost for reporting extreme scores, one can obtain a more reliable crowd estimates of quality.Type: GrantFiled: January 4, 2021Date of Patent: January 24, 2023Assignee: THE TRUSTEES OF PRINCETON UNIVERSITYInventors: Dalton Conley, Ofer Tchernichovski
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Patent number: 11554101Abstract: An “inverse” precipitation route to precipitate aqueous soluble species with copolymers as nanoparticles having a hydrophilic, polar core and a less polar shell is described.Type: GrantFiled: January 22, 2019Date of Patent: January 17, 2023Assignee: THE TRUSTEES OF PRINCETON UNIVERSITYInventors: Robert F. Pagels, Robert K. Prud'Homme
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Patent number: 11557034Abstract: Systems and methods are described for the fully automatic, template-free locating and extracting of a plurality of two-dimensional projections of particles in a micrograph image. A set of reference images is automatically assembled from a micrograph image by analyzing the image data in each of a plurality of partially overlapping windows and identifying a subset of windows with image data satisfying at least one statistic criterion compared to other windows. A normalized cross-correlation is then calculated between the image data in each reference image and the image data in each of a plurality of query image windows. Based on this cross-correlation analysis, a plurality of locations in the micrograph is automatically identified as containing a two-dimensional projection of a different instance of the particle of the first type. The two-dimensional projections identified in the micrograph are then used to determine the three-dimensional structure of the particle.Type: GrantFiled: June 13, 2018Date of Patent: January 17, 2023Assignee: The Trustees of Princeton UniversityInventors: Amit Singer, Ayelet Heimowitz, Joakim Anden, Yuehaw Khoo, Joseph Kileel
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Patent number: 11549919Abstract: Systems and methods for prediction of state of charge (SOH), state of health (SOC) and other characteristics of batteries using acoustic signals, includes determining acoustic data at two or more states of charge and determining a reduced acoustic data set representative of the acoustic data at the two or more states of charge. The reduced acoustic data set includes time of flight (TOF) shift, total signal amplitude, or other data points related to the states of charge. Machine learning models use at least the reduced acoustic dataset in conjunction with non-acoustic data such as voltage and temperature for predicting the characteristics of any other independent battery.Type: GrantFiled: March 8, 2019Date of Patent: January 10, 2023Assignee: The Trustees of Princeton UniversityInventors: Daniel Artemis Steingart, Shoham Bhadra, Andrew Gaheem Hsieh, Benjamin Hertzberg, Peter James Gjeltema, Clarence Worth Rowley, III, Alexandre S. R. Goy, Jason Wolf Fleischer
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Publication number: 20220409826Abstract: Systems and methods for automatic intravenous injection in accordance with embodiments of the invention are illustrated. One embodiment includes a method for automatically injecting a needle into a vein. The method includes steps for identifying an injection position using a first set of one or more sensors, positioning an injection mechanism at the identified injection position, and vertically inserting a needle until entry in a vein is detected using a second set of one or more sensors.Type: ApplicationFiled: November 19, 2020Publication date: December 29, 2022Applicants: The Trustees of Princeton University, Invictis Labs, Inc.Inventors: Craig B. Arnold, Miles Cole
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Publication number: 20220403364Abstract: Disclosed is a 3D porous medium and a method of manufacture. The 3D porous medium includes (i) a support structure of transparent hydrogel particles or emulsion droplets, (ii) bacterial nutrient in open volumes between the transparent hydrogel particles, as well as within micropores in the transparent hydrogel particles, and (iii) bacterial cells within the open volumes in the support structure.Type: ApplicationFiled: April 28, 2020Publication date: December 22, 2022Applicant: The Trustees of Princeton UniversityInventors: Sujit Datta, Tapomoy Bhattacharjee
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Publication number: 20220403429Abstract: Microbial consortia exert great influence over the physiology of humans, animals, plants, and ecosystems. However, difficulty in controlling their composition and population dynamics have limited their application in medicine, agriculture, biotechnology, and the environment. The approach disclosed herein provides an effective method to dynamically control population compositions in microbial consortia, which we demonstrate in the context of co-culture fermentations for chemical production. Co-culture fermentations can improve chemical production from complex biosynthetic pathways over monocultures by distributing enzymes across multiple strains, thereby reducing metabolic burden, overcoming endogenous regulatory mechanisms, or exploiting natural traits of different microbial species. However, stabilizing and optimizing microbial sub-populations for maximal chemical production remains a major obstacle in the field.Type: ApplicationFiled: June 21, 2022Publication date: December 22, 2022Applicant: The Trustees of Princeton UniversityInventors: Jose L. Avalos, Makoto A. Lalwani, Mark P. Brynildsen
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Publication number: 20220400375Abstract: According to various embodiments, a cellular architecture for enhanced privacy regarding identity and location of a computing device is disclosed. The architecture includes a next generation core (NGC). The NGC includes an authentication server function (AUSF) configured to determine whether the computing device contains a valid subscriber identity module (SIM) card, and a user plane function (UPF) configured to allow a computing device to connect to the Internet. The architecture further includes a gateway connected to the UPF, the gateway configured to authenticate the computing device while hiding the identity of the computing device by verifying authentication tokens that represent units of access.Type: ApplicationFiled: March 2, 2021Publication date: December 15, 2022Applicant: The Trustees of Princeton UniversityInventor: Paul Schmitt
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Publication number: 20220400024Abstract: A system and method for chat-based studies utilizing a plurality of users may be provided, utilizing at least one chat room processor and a plurality of remote processors. The chat room processors may be configured to receive a chat room template, create a plurality of chat rooms based on the chat room template, assign participants to one chat rooms, provide instructions associated with the chat room when all participants are present, provide questions or prompts at times defined by the chat room template or when conditions defined by the chat room template are met, collect all messages received from each participant, and storing information that includes the message, a time stamp the message was sent and/or received, and at least one unique identification code associated with the participant sending the message.Type: ApplicationFiled: June 14, 2022Publication date: December 15, 2022Applicant: The Trustees of Princeton UniversityInventor: Xiaoxiao Shen
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Patent number: 11521068Abstract: According to various embodiments, a method for generating one or more optimal neural network architectures is disclosed. The method includes providing an initial seed neural network architecture and utilizing sequential phases to synthesize the neural network until a desired neural network architecture is reached. The phases include a gradient-based growth phase and a magnitude-based pruning phase.Type: GrantFiled: October 25, 2018Date of Patent: December 6, 2022Assignee: THE TRUSTEES OF PRINCETON UNIVERSITYInventors: Xiaoliang Dai, Hongxu Yin, Niraj K. Jha
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Publication number: 20220383142Abstract: According to various embodiments, a machine learning based method, system, and non-transitory computer-readable medium for identifying content on social media related to one or more coordinated influence efforts are disclosed. The method includes generating one or more datasets of post-uniform resource locator (URL) pairs produced from one or more known coordinated influence efforts on one or more social media platforms. The method further includes generating one or more datasets of post-URL pairs produced from one or more random users on one or more social media platforms. The method additionally includes extracting a plurality of content-based features from the post-URL pairs from known coordinated influence efforts and random users.Type: ApplicationFiled: August 28, 2020Publication date: December 1, 2022Applicant: The Trustees of Princeton UniversityInventors: Meysam Alizadeh, Jacob Shapiro
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Patent number: 11514925Abstract: Operations of a method include receiving a request to enhance a new source audio. Responsive to the request, the new source audio is input into a prediction model that was previously trained. Training the prediction model includes providing a generative adversarial network including the prediction model and a discriminator. Training data is obtained including tuples of source audios and target audios, each tuple including a source audio and a corresponding target audio. During training, the prediction model generates predicted audios based on the source audios. Training further includes applying a loss function to the predicted audios and the target audios, where the loss function incorporates a combination of a spectrogram loss and an adversarial loss. The prediction model is updated to optimize that loss function. After training, based on the new source audio, the prediction model generates a new predicted audio as an enhanced version of the new source audio.Type: GrantFiled: April 30, 2020Date of Patent: November 29, 2022Assignees: ADOBE INC., THE TRUSTEES OF PRINCETON UNIVERSITYInventors: Zeyu Jin, Jiaqi Su, Adam Finkelstein
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Patent number: 11512071Abstract: Methods described herein enable the production of numerous molecular species through decarboxylative cross-coupling via use of photoredox and transition metal catalysts. For example, methods described herein enable the production of numerous molecular species through decarboxylative cross-coupling via use of photoredox and transition metal catalysts. A method described herein, in some embodiments, comprises providing a reaction mixture including a photoredox catalyst, a transition metal catalyst, a coupling partner and a substrate having a carboxyl group. The reaction mixture is irradiated with a radiation source resulting in cross-coupling of the substrate and coupling partner via a mechanism including decarboxylation, wherein the coupling partner is selected from the group consisting of a substituted aromatic compound and a substituted aliphatic compound.Type: GrantFiled: January 9, 2020Date of Patent: November 29, 2022Assignee: THE TRUSTEES OF PRINCETON UNIVERSITYInventors: David W. C. MacMillan, Zhiwei Zuo
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Publication number: 20220370373Abstract: From diagnostic imaging to drug delivery, nanoparticles have found a tremendous variety of uses across fields. Often, when designing these nanoscale constructs, the two most important criteria are particle size and core loading. For example, small particles below 100 nm can have many advantages for drug delivery—including improved specificity to tumors through the enhanced permeability and retention (EPR) effect. Likewise, higher loading nanoparticles translate very well to more effective drug delivery and cancer imaging—allowing for lower dosage and reduced costs. Traditional formulations of nanoparticles using drug absorption or precipitation methods generally struggle to obtain >50% loading. Disclosed herein is a precipitation process allowing for production of stable particles at very high core loading by taking advantage of different time scales while maintaining biologically relevant sizes.Type: ApplicationFiled: October 14, 2020Publication date: November 24, 2022Applicant: The Trustees of Princeton UniversityInventors: Leon WANG, Kurt RISTROPH, Robert PRUD'HOMME
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Patent number: 11500635Abstract: A heterogeneous microprocessor configured to perform classification on an input signal. The heterogeneous microprocessor includes a die with a central processing unit (CPU) a programmable feature-extraction accelerator (FEA) and a classifier. The FEA is configured to perform feature extraction on the input signal to generate feature data. The classifier is configured to perform classification on the feature data and the CPU is configured to provide processing after classification. The FEA may be configured with a plurality of Gene-Computation (GC) Cores. The FEA may be configured for genetic programing with gene depth constraints, gene number constraints and base function constraints. The classifier may be a support-vector machine accelerator (SVMA). The SVMA may include training data based on error-affected feature data. The heterogeneous microprocessor may also include an automatic-programming & classifier training module.Type: GrantFiled: June 5, 2017Date of Patent: November 15, 2022Assignee: THE TRUSTEES OF PRINCETON UNIVERSITYInventors: Hongyang Jia, Naveen Verma
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Patent number: 11499867Abstract: Disclosed herein is an all-digital phase and timing correction procedure for coherent averaging in dual-comb and multiheterodyne spectroscopy—applicable to any dual-comb spectroscopy setup. It can account for large frequency/phase instabilities of the used sources, yielding a significant reduction of the noise pedestal and an increase in signal-to-noise ratio (SNR) of the radio frequency (RF) beat notes. This technique is computationally efficient and can be conveniently implemented either as a post-processing algorithm or in a real-time data acquisition and processing platform without the necessity of adding any additional optical elements to the dual-comb spectroscopy system. By implementing this technique, the performance of any comb- or comb-like-source-based DCS system with a sufficient degree of mutual coherence between the optical modes can be improved in terms of SNR and number of spectroscopically-usable RF beat notes.Type: GrantFiled: April 26, 2021Date of Patent: November 15, 2022Assignee: THE TRUSTEES OF PRINCETON UNIVERSITYInventors: Lukasz Sterczewski, Jonas Westberg, Gerard Wysocki
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Patent number: 11493428Abstract: Described herein are microfluidic devices and methods that can greatly improve cell quality, streamline workflows, and lower costs. Applications include research and clinical diagnostics in cancer, infectious disease, and inflammatory disease, among other disease areas.Type: GrantFiled: March 14, 2014Date of Patent: November 8, 2022Assignees: GPB SCIENTIFIC, INC., UNIVERSITY OF MARYLAND, BALTIMORE, THE TRUSTEES OF PRINCETON UNIVERSITYInventors: Michael Grisham, Curt I Civin, James C. Sturm, Robert H. Austin, Joseph D'Silva, Yu Chen
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Publication number: 20220348966Abstract: A method for producing metabolites that are heavy alcohols, and particularly branched-chain alcohols is provided, involving contacting a suitable substrate with recombinant microorganisms. The microorganisms contain at least one deletion, disruptions, or mutations from the GLN gene family, VPS gene family, GNP gene family, AVT gene family, GCN gene family, or YDR391C, and combinations thereof, and overproduce the heavy alcohol as compared to a wild-type yeast strain.Type: ApplicationFiled: September 25, 2020Publication date: November 3, 2022Applicants: The Trustees of Princeton University, Massachusetts Institute of Technology, Whitehead Institute for Biomedical Research, Kyoto UniversityInventors: José L. AVALOS, Sarah K. HAMMER, Kouichi KURODA, Gerald R. FINK, Gregory STEPHANOPOULOS
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Publication number: 20220348507Abstract: Ultra-lightweight aerogels and methods for fabricating such aerogels from ammonia borane and a support structure, where the support structure is either two-dimensional nanostructures, or hydrocarbon polymer colloids. The components are mixed, then annealed. The properties of the disclosed aerogels can be tuned by controlling the ratio between the support structure and the ammonia borane, or by infiltrating the aerogels with additives.Type: ApplicationFiled: January 20, 2021Publication date: November 3, 2022Applicants: The Trustees Princeton University, LutaiInventors: Rodney D. PRIESTLEY, Craig B. ARNOLD, Hejun LI, Sehmus OZDEN