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Annual International Symposium on Reliability Physics

作者： M. L. Breeding R. A. Reed K. M. Warren M. L. Alles Interdisciplinary Materials Science and Engineering Program Vanderbilt University Nashville TN USA Electrical Engineering and Computer Science Department Vanderbilt University Nashville TN USA

The complex vertical structures of 2.5D/3D integrated circuits present new challenges for the simulation, experimentation, and analysis of soft errors. Each added layer of circuitry in vertically integrated technologies increases the requirement for interconnect metallization. The proximity of these metal layers to sensitive regions may result in materials-dependent responses to radiation. Monte-Carlo simulations offer flexibility and utility in exploring the impact of geometry and material selection on the resulting radiation response characteristics in 3D IC structures. As the fabrication and experimentation of such technologies at this point follows no universal standard or guidelines, various configuration possibilities are advantageously thus considered in order to minimize cost and waste. Simulations indicate important differences in relative responses to radiation effects; in the discussed parametrizations, copper and cobalt interconnects behave similarly, while tungsten interconnects exhibit better properties than ruthenium.

关键词： Three-dimensional displays Metals Neutrons Radiation effects Integrated circuit interconnections Reliability

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Corrigendum: Moving Next-Generation Phase-Field Models to BMS Applications -A Case Study that Confirms Professor Uzi Landau's Foresight [J. Electrochem. Soc., 171, 063507 (2024)]

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Journal of The Electrochemical Society 2024年第8期171卷 089002-089002页

作者： Tushar K. Telmasre Anthony César Concepción Suryanarayana Kolluri Lubhani Mishra Raghav S. Thiagarajan Aditya Naveen Matam Akshay Subramaniam Taylor R. Garrick Venkat R. Subramanian Materials Science and Engineering Program Texas Materials Institute The University of Texas at Austin Austin TX 78712 United States of America Walker Department of Mechanical Engineering The University of Texas at Austin Austin TX 78712 United States of America Battery Materials and Systems Research General Motors Global Research and Development Center Warren MI 48090 United States of America Chandra Department of Electrical and Computer Engineering The University of Texas at Austin Austin TX 78712 United States of America Energy Storage and Propulsion R&D and Manufacturing Engineering General Motors Technical Center Warren MI 48092 United States of America Affiliate Faculty Oden Institute for Computational Science and Engineering The University of Texas at Austin Austin TX 78712 United States of America

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An artificial neural network for hand movement classification using surface electromyography 12

An artificial neural network for hand movement classificatio...

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12th International Conference on Bio-Inspired Systems and Signal Processing, BIOSIGNALS 2019 - Part of 12th International Joint Conference on Biomedical engineering Systems and Technologies, BIOSTEC 2019

作者： Viana, Paulo L. Fujii, Victoria S. Lima, Larissa M. Ouriques, Gabriel L. Oliveira, Gustavo C. Varoto, Renato Cliquet, Alberto Department of Electrical and Computer Engineering Trabalhador São-Carlense Avenue 400 São Carlos Brazil University of São Paulo Interunits Graduate Program in Bioengineering Trabalhador São-Carlense Avenue 400 São Carlos Brazil Department of Orthopedics and Traumatology University of Campinas Cidade Universitária Zeferino Vaz Campinas Brazil

ISBN: (纸本)9789897583537

In this paper we present the development of an artificial neural network that uses surface EMG data from two forearm muscles to classify hand movements and gestures. We trained our network to classify three different sets of movements, using EMG data from six healthy subjects. We were able to achieve hit rates of above 99% in the training sets and hit rates of above 85% in all three test sets, with a maximum of 88.8% for the second movement set. Advantages of the proposed method include small number of electrodes, reduced complexity, computational cost and response time. Copyright © 2019 by SCITEPRESS - science and Technology Publications, Lda. All rights reserved.

关键词： Neural networks

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Design, Implementation and Validation of a Multipurpose Localization Service for Cooperative Multi-UAV Systems

Design, Implementation and Validation of a Multipurpose Loca...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Edison Pignaton de Freitas Luis Antonio L. F. da Costa Carlos Felipe Emygdio de Melo Maik Basso Marcos Rodrigues Vizzotto Mateus Schein Cavalheiro Corrêa Túlio Dapper e Silva Graduate Program in Computer Science Federal University of Rio Grande do Sul Porto Alegre Brazil Graduate Program in Electrical Engineering Federal University of Rio Grande do Sul Porto Alegre Brazil Department of Electric Automation and Energy Federal University of Rio Grande do Sul Porto Alegre Brazil

ISBN: (数字)9781728142784

ISBN: (纸本)9781728142791

Systems composed of groups of Unmanned Aerial Vehicles (UAVs) are emerging as an extension of the usage of single UAVs in a number of applications. Besides of very desirable, the possibility of using multi-UAV systems requires that each UAV in the group has information about the locations of the others, so that the system as a whole can work smoothly, i.e. keeping configured flight formation, without collisions, evenly distributing the tasks, and even authenticating one another so that no malicious node access the group. To support such multi-UAV systems setup, this work reports the proposal of a multipurpose localization service to disseminate positioning information of the UAVs to the group as well as to estimate the positions that are not received due to communication errors. The proposal consists in a complete methodology to setup, test and perform multi-UAV missions, which are firstly planned, setup and tested in a simulated environment, and then performed in the real-world. Design and implementation details of the proposed infrastructure service are presented, along with a complete validation of the proposal, from simulation to the field experiments. The acquired results provide evidence that the proposed service and methodology are efficient to support fleet of UAVs performing cooperative missions.

关键词： Proposals Unmanned aerial vehicles Estimation Task analysis Planning Global Positioning System Control systems

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SURG-01. DIFFERENTIATION OF GLIOBLASTOMA AND MALIGNANT MENINGIOMA FROM NORMAL BRAIN BY TISSUE STIFFNESS UTILIZING MICROSURGICAL FORCEPS EQUIPPED WITH HAPTICS TECHNOLOGY

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Neuro-Oncology 2023年第SUPPLEMENT_5期25卷 v260–v261页

作者： Ezaki, Taketo Kisima, Kohki Shibao, Shunsuke Matsunaga, Takuya Pareira, Eriel Sandika Kitamura, Yohei Takahara, Kento Iwama, Takashi Sampetrean, Oltea Ohnishi, Kouhei Shimono, Tomoyuki Sasaki, Hikaru Keio University School of Medicine Department of Neurosurgery Shinjuku-ku Tokyo Japan Yokohama National University School of Engineering Science Department of Educational Program for Electrical and Computer Engineering Yokohama-shi Japan Keio University School of Medicine Department of Neurosurgery Shinjuku-ku Japan Kanagawa Institute of Industrial Science and Technology Kawasaki-shi Japan Keio University School of Medicine Department of Microbiology and Immunology Shinjuku-ku Japan Keio University Haptics Research Center Kawasaki-shi Japan Tokyo Dental College Ichikawa General Hospital Department of Neurosurgery Ichikawa-shi Chiba Japan

Stiffness of human cancers strongly correlate with their pathology, and it is reported that stiffness can be used as a biomarker. Furthermore, comprehensive analysis has suggested the usefulness of cancer stiffness in diagnosis and malignancy prediction and its association with molecular expression, as well as its potential for predicting and diagnosing postoperative complications. Neurosurgeons perform tumor resection relying on the sensations that they feel with their own fingertips (tactile sensation), but it takes years of surgical experience to accurately distinguish brain tumor from the surrounding normal brain *** is a new technology regarding touching sensation. Especially, our technology, real haptics, can communicate, record, and reproduce the real sensation. It is also possible to measure and analyze the physical property such as stiffness of the touching object from the obtained haptic *** developed a surgical forceps equipped with haptics technology to distinguish brain tumor tissue from surrounding normal brain tissue. three glioblastoma cell lines (SF126, U87, U251) and a malignant meningioma cell line (IOMM-Lee) were each transplanted intracranially into 5 nude mice. Tumor size was periodically monitored and mice were euthanized at appropriate time points. The stiffness of the tumor and normal brain tissue was measured using a master-slave integrated surgical forceps prototype. The results statistically showed that all four types of brain tumor tissues were stiffer than normal brain tissues. (p = 0.001) In addition, malignant meningioma was statistically stiffer than glioblastomas. (p = 0.025) This result is consistent with actual surgical *** have shown that our surgical forceps has the ability to distinguish pathology of brain tumors as well as to distinguish brain tumor from normal brain tissue. The forceps is also helpful for the neurosurgeons to sense minute change in tissue stiffness.

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Integrative characterization of MYC RNA-binding function

Cell Genomics

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Cell Genomics 2025年 100878页

作者： Li, Sihan Wang, Zehua Wang, Xiaofei Wang, Yifei Pattarayan, Dhamotharan Zhang, Yu Nguyen, Phuong Bhuniya, Avishek Chen, Yuang Huang, Haozhe Huang, Yixian Wang, Luxuan Wang, Junmei Li, Song Zhang, Min Liu, Yang Lee, Nara Yang, Da Center for Pharmacogenetics and Department of Pharmaceutical Sciences University of Pittsburgh Pittsburgh PA United States Department of Medicine University of Pittsburgh Pittsburgh PA United States UPMC Hillman Cancer Center University of Pittsburgh Pittsburgh PA United States Department of Bioengineering Department of Electrical and Computer Engineering Cancer Center at Illinois Beckman Institute for Advanced Science and Technology University of Illinois Urbana-Champaign Urbana IL United States Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center School of Pharmacy University of Pittsburgh Pittsburgh PA United States Department of Microbiology and Molecular Genetics University of Pittsburgh Pittsburgh PA United States Department of Computational and Systems Biology University of Pittsburgh Pittsburgh PA United States

Emerging evidence suggests that MYC interacts with RNAs. Here, we performed an integrative characterization of MYC as an RNA-binding protein in six cell lines. We found that MYC binds to a myriad of RNAs with high affinity for guanosine-rich RNAs. Global and specific depletion of RNAs reduces MYC chromatin occupancy. Mechanistically, two highly conserved sequences, amino acids 355–357 KRR and 364–367 RQRR, within the basic region of MYC are necessary for its RNA binding. Notably, alanine substitution of KRR abolishes MYC's RNA-binding ability both in vitro and in vivo, without affecting its ability to bind E-box DNA as part of the MYC:MAX dimer in vitro. The loss of RNA-binding function decreases MYC chromatin binding in vivo and attenuates its ability to promote gene expression, cell-cycle progression, and proliferation. Our study lays a foundation for future investigation into the role of RNAs in MYC-mediated transcriptional activation and oncogenic functions. © 2025 The Author(s)

关键词： arginine-rich motif CRISPR-Display eCLIP enhancer RNA gene regulation guanosine-rich RNA MYC rChIP RNA-binding protein (RBP) TF RNA binding

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Thermal and electrical properties of hybrid composites with graphene and boron nitride fillers

arXiv

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arXiv 2019年

作者： Lewis, Jacob S. Barani, Zahra Magana, Andres Sanchez Kargar, Fariborz Balandin, Alexander A. Center Department of Electrical and Computer Engineering Materials Science and Engineering Program Bourns College of Engineering University of California RiversideCA92521 United States

We report on the thermal and electrical properties of hybrid epoxy composites with graphene and boron nitride fillers. The thicknesses, lateral dimensions, and aspect ratios of each filler material were intentionally selected for geometric similarity to one another, in contrast to prior studies that utilized dissimilar filler geometries to achieve a "synergistic" effect. We demonstrate that the electrically-conductive graphene and electrically-insulating boron nitride fillers allow one to effectively engineer the thermal and electrical conductivities of their resulting composites. By varying the constituent fraction of boron nitride to graphene in a composite with ~44% total filler loading, one can tune the thermal conductivity enhancement from a factor of ×15 to ×35 and increase the electrical conductivity by many orders of magnitude. The obtained results are important for the development of next-generation thermal interface materials with controllable electrical properties necessary for applications requiring either electrical grounding or insulation. Copyright © 2019, The Authors. All rights reserved.

关键词： Aspect ratio

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Construction and analysis of posterior matching in arbitrary dimensions via optimal transport

arXiv

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arXiv 2019年

作者： Mesa, Diego A. Ma, Rui Gorantla, Siva Coleman, Todd P. Departments of Biomedical Informatics Electrical Engineering and Computer Science Vanderbilt University Dexcomm Inc Google Inc Department of Bioengineering University of California San Diego

The posterior matching scheme, for feedback encoding of a message point lying on the unit interval over memoryless channels, maximizes mutual information for an arbitrary number of channel uses. However, it in general does not always achieve any positive rate;so far, elaborate analyses have been required to show that it achieves any positive rate below capacity. More recent efforts have introduced a random "dither" shared by the encoder and decoder to the problem formulation, to simplify analyses and guarantee that the randomized scheme achieves any rate below capacity. Motivated by applications (e.g. human-computer interfaces) where (a) common randomness shared by the encoder and decoder may not be feasible and (b) the message point lies in a higher dimensional space, we focus here on the original formulation without common randomness, and use optimal transport theory to generalize the scheme for a message point in a higher dimensional space. By defining a stricter, almost sure, notion of message decoding, we use classical probabilistic techniques (e.g. change of measure and martingale convergence) to establish succinct necessary and sufficient conditions on when the message point can be recovered from infinite observations: Birkhoff ergodicity of a random process sequentially generated by the encoder. We also show a surprising "all or nothing" result: the same ergodicity condition is necessary and sufficient to achieve any rate below capacity. We provide applications of this message point framework in human-computer interfaces and multi-antenna communications. Copyright © 2019, The Authors. All rights reserved.

关键词： Signal encoding

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IoT environmental analyzer using sensors and machine learning for migraine occurrence prevention 18

IoT environmental analyzer using sensors and machine learnin...

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18th IEEE International Conference on Machine Learning and Applications, ICMLA 2019

作者： Day, Rosemarie J. Salehi, Hassan Javadi, Mahsa Data Science Program Worcester Polytechnic Institute WorcesterMA United States Department of Electrical and Computer Engineering California State University Chico ChicoCA United States Division of Genetic Research University of Connecticut Health Center FarmingtonCT United States

ISBN: (纸本)9781728145495

Everyday migraines are affecting more than one billion people worldwide. This headache disorder is classified as the sixth most disabling disease in the world. Migraines are just one chronic illness affected by environmental triggers due to changes that occur inside the home. Migraines share this characteristic with sinus headaches and thus are often misdiagnosed. In this research work, an iOS-based environmental analyzer was designed, implemented and evaluated for migraine sufferers with the use of sensors. After the data collection and cleaning, five machine learning model were used to estimate prediction accuracy of migraines in terms of the environment. The data was evaluated against the models using K-Fold cross validation. The algorithm accuracy comparison showed that Linear Discriminant Analysis (LDA) produced highest accuracy for the testing data at a mean of 0.938. Preliminary results demonstrate the feasibility of using machine learning algorithms to perform the automated recognition of migraine trigger areas in the environment. © 2019 IEEE.

关键词： Internet of things

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Terahertz Inverse Spin Hall Effect in Spintronic Nanostructures

SSRN

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SSRN 2023年

作者： Cheng, Jing Komissarov, Ivan Chen, Genyu Adam, Roman Chaktraborty, Debamitra Bürgler, Daniel E. Heidtfeld, Sarah Cao, Derang Büscher, Markus Hardtdegen, Hilde Mikulics, Martin Schneider, Claus Michael Gladczuk, Leszek Przyslupski, Piotr Sobolewski, Roman Materials Science Program University of Rochester RochesterNY14627-1299 United States Laboratory for Laser Energetics University of Rochester RochesterNY14623 United States Department of Electrical and Computer Engineering University of Rochester RochesterNY14627-0231 United States Research Centre Jülich Peter Grünberg Institute Jülich52425 Germany Faculty of Physics University Duisburg-Essen Duisburg47048 Germany College of Physics Center for Marine Observation and Communications National Demonstration Center for Experimental Applied Physics Education Qingdao University Qingdao266071 China Research Centre Jülich Ernst Ruska Centre for Microscopy and Spectroscopy With Electrons Jülich52425 Germany Department of Physics University of California Davis DavisCA95616-5270 United States Institute of Physics Polish Academy of Sciences WarszawaPL-02668 Poland Department of Physics and Astronomy University of Rochester RochesterNY14627-0171 United States

Bilayers of ferromagnetic and heavy metal nanolayers excited with femtosecond laser pulses emit subpicosecond bursts of electromagnetic radiation with spectral frequencies up to several THz. We fabricated such spintronic THz emitters containing various ferromagnetic materials with vastly different magnetic remanence, saturation magnetization, and coercive field. In all cases, the THz amplitude versus magnetic field dependence follows the independently measured magnetization hysteresis loops and the THz polarization direction is perpendicular to the sample’s magnetization M, both consistent with the inverse spin Hall effect as physical origin. The M(T) variation governs the temperature dependence of the THz generation. Emitters with weakly remanent ferromagnets are field-tunable, while moderately and strongly remanent ferromagnets, once magnetized, allow intense THz generation even without an external field, nevertheless exhibiting low susceptibility to magnetic perturbations, if the hysteresis loop is square. Hence, exploiting the magnetic properties of the ferromagnetic layer enables tailoring of weakly temperature-dependent spintronic THz emitters. Finally, we explored the applicability of perovskite oxide materials such as La-Sr-Mn-O (LSMO) for THz transient generation. Although we detected THz emissions from, e.g., LSMO/Au nanobilayers, the signal was attributed to the ultrafast transient demagnetization and not the inverse spin Hall effect. © 2023, The Authors. All rights reserved.

关键词： Nanostructures

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