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Novel diamond shuttle to deliver flexible neural probe with reduced tissue compression

Microsystems & Nanoengineering 2020年第1期6卷 903-915页

作者： Kyounghwan Na Zachariah J.Sperry Jiaao Lu Mihaly Voroslakos Saman S.Parizi Tim M.Bruns Euisik Yoon John P.Seymour Electrical Engineering&Computer Science Department University of MichiganAnn ArborMI 48105USA Biomedical Engineering Department University of MichiganAnn ArborMI 48105USA Biointerfaces Institute University of MichiganAnn ArborMI 48105USA The Neuroscience Institute New York UniversityNew YorkNY 10016USA Center for Nanomedicine Institute for Basic Science(IBS)Seoul 03722Korea Graduate Program of Nano Biomedical Engineering(Nano BME) Yonsei-IBS InstituteYonsei UniversitySeoul 03722Korea Vivian L Smith Department of Neurosurgery University of Texas Health Science CenterHoustonTX 77030USA Department of Electrical and Computer Engineering Rice UniversityHoustonTX 77005USA

The ability to deliver flexible biosensors through the toughest membranes of the central and peripheral nervous system is an important challenge in neuroscience and neural *** devices implanted through dura mater and thick epineurium would ideally create minimal compression and acute damage as they reach the neurons of *** demonstrate that a three-dimensional diamond shuttle can be easily made with a vertical support to deliver ultra-compliant polymer microelectrodes(4.5-µm thick)through dura mater and thick *** diamond shuttle has 54%less cross-sectional area than an equivalently stiff silicon shuttle,which we simulated will result in a 37%reduction in blood vessel *** also discovered that higher frequency oscillation of the shuttle(200Hz)significantly reduced tissue compression regardless of the insertion speed,while slow speeds also independently reduced tissue *** and recording performance are demonstrated in rat and feline models,but the large design space of these tools are suitable for research in a variety of animal models and nervous system targets.

关键词： sectional neural thick

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programming Variational Quantum Circuits with Quantum-Train Agent

Programming Variational Quantum Circuits with Quantum-Train ...

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Quantum Communications, Networking, and Computing (QCNC), International Conference on

作者： Chen-Yu Liu Samuel Yen-Chi Chen Kuan-Cheng Chen Wei-Jia Huang Yen-Jui Chang Graduate Institute of Applied Physics National Taiwan University Taipei Taiwan Hon Hai (Foxconn) Research Institute Taipei Taiwan Wells Fargo New York NY USA Department of Electrical and Electronic Engineering Imperial College London London UK Centre for Quantum Engineering Science and Technology (QuEST) Imperial College London London UK Quantum Information Center Chung Yuan Christian University Taoyuan City Taiwan Master Program in Intelligent Computing and Big Data Chung Yuan Christian University Taoyuan City Taiwan

ISBN: (数字)9798331531591

ISBN: (纸本)9798331531607

This study introduces the Quantum-Train Quantum Fast Weight programmer (QT-QFWP) framework, enabling efficient and scalable programming of variational quantum circuits (VQCs) through quantum-driven parameter updates for the classical slow programmer controlling the fast programmer VQC. By optimizing quantum and classical parameter management, QT-QFWP significantly reduces parameters (by 70–90%) compared to Quantum Long Short-Term Memory (QLSTM) and Quantum Fast Weight programmer (QFWP) while maintaining accuracy. Benchmarking on time-series tasks—including Damped Simple Harmonic Motion (SHM), NARMA5, and Simulated Gravitational Waves (GW)—demonstrates superior efficiency and predictive accuracy. QT-QFWP is particularly advantageous for near-term quantum systems, addressing qubit and gate fidelity constraints, enhancing VQC deployment in time-sensitive applications, and expanding quantum computing’s role in machine learning.

关键词： Quantum system Accuracy computational modeling Qubit Neural networks programming Predictive models Quantum circuit Physics Long short term memory

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Electron mobility of SnO2 from first principles

arXiv

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arXiv 2024年

作者： Wang, Amanda Bushick, Kyle Pant, Nick Lee, Woncheol Zhang, Xiao Leveillee, Joshua Giustino, Feliciano Poncé, Samuel Kioupakis, Emmanouil Department of Materials Science and Engineering University of Michigan Ann ArborMI48109 United States Applied Physics Program University of Michigan Ann ArborMI48109 United States Department of Electrical and Computer Engineering University of Michigan Ann ArborMI48109 United States Oden Institute for Computational Engineering and Sciences The University of Texas at Austin AustinTX78712 United States Department of Physics The University of Texas at Austin AustinTX78712 United States European Theoretical Spectroscopy Facility Institute of Condensed Matter and Nanosciences Université catholique de Louvain Chemin des Étoiles 8 Louvain-la-NeuveB-1348 Belgium WEL Research Institute Avenue Pasteur 6 Wavre1300 Belgium

The transparent conducting oxide SnO2 is a wide bandgap semiconductor that is easily n-type doped and widely used in various electronic and optoelectronic applications. Experimental reports of the electron mobility of this material vary widely depending on the growth conditions and doping concentrations. In this work, we calculate the electron mobility of SnO2 from first principles to examine the temperature- and doping-concentration dependence, and to elucidate the scattering mechanisms that limit transport. We include both electron-phonon scattering and electron-ionized impurity scattering to accurately model scattering in a doped semiconductor. We find a strongly anisotropic mobility that favors transport in the direction parallel to the c-axis. At room temperature and intrinsic carrier concentrations, the low-energy polar-optical phonon modes dominate scattering, while ionized-impurity scattering dominates above 1018 cm-3 Copyright © 2024, The Authors. All rights reserved.

关键词： Electron mobility

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Reduce Fingerprint Construction for Positioning IoT Devices Based on Generative Adversarial Nets 1

Reduce Fingerprint Construction for Positioning IoT Devices ...

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1st International Conference on Pervasive Artificial Intelligence, ICPAI 2020

作者： Tarekegn, Getaneh Berie Juang, Rong-Terng Lin, Hsin-Piao Munaye, Yirga Yayeh Belay Adege, Abebe National Taipei University of Technology Department of International Graduate Program in Electrical Engineering and Computer Science Taipei Taiwan Feng Chia University Department of Electronic Engineering Taichung Taiwan National Taipei University of Technology Department of Electronic Engineering Taipei Taiwan Debre Markos University Department of Information Technology Debre Markos Ethiopia

ISBN: (纸本)9781665404839

Fingerprint-based positioning is popular and applicable for Internet of Things (IoT) applications to offer seamless, intelligent and adaptive location-aware services for IoT devices. However, it takes time and cost to build the radio-map. This paper proposed deep convolutional Generative adversarial nets (DCGANs) to minimize the site survey time and cost, and to mitigate signal fluctuations. The radio-map was designed for receiving radio signals from detectable wireless local area network (WLAN) and cellular networks in scalable environments. The proposed fingerprinting-based positioning is a sequential combination of the hybrid support vector machine and long short-term memory algorithms. The experimental results indicate that the proposed method achieves a promising and reasonable positioning performance for IoT devices in scalable wireless environments. © 2020 IEEE.

关键词： Support vector machines

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Asymptotics of representation learning in finite Bayesian neural networks

arXiv

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arXiv 2021年

作者： Zavatone-Veth, Jacob A. Canatar, Abdulkadir Ruben, Benjamin S. Pehlevan, Cengiz Department of Physics Center for Brain Science Biophysics Graduate Program John A. Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA02138 United States

Recent works have suggested that finite Bayesian neural networks may sometimes outperform their infinite cousins because finite networks can flexibly adapt their internal representations. However, our theoretical understanding of how the learned hidden layer representations of finite networks differ from the fixed representations of infinite networks remains incomplete. Perturbative finite-width corrections to the network prior and posterior have been studied, but the asymptotics of learned features have not been fully characterized. Here, we argue that the leading finite-width corrections to the average feature kernels for any Bayesian network with linear readout and Gaussian likelihood have a largely universal form. We illustrate this explicitly for three tractable network architectures: deep linear fully-connected and convolutional networks, and networks with a single nonlinear hidden layer. Our results begin to elucidate how task-relevant learning signals shape the hidden layer representations of wide Bayesian neural networks. © 2021, CC BY-NC-SA.

关键词： Network architecture

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A new sterol from the Formosan soft coral Lobophytum durum

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Journal of Molecular Structure 2024年第Part2期1296卷

作者： Hung, Chia-Ling Huang, Li-Chieh Shih, Kun-Yauh Lai, Kuei-Hung Peng, Bo-Rong Hwang, Tsong-Long Chien, Su-Ying Li, Chia-Ying Chung, Hsu-Ming Department of Applied Chemistry National Pingtung University Pingtung900391 Taiwan Graduate Institute of Pharmacognosy College of Pharmacy Taipei Medical University Taipei11031 Taiwan PhD Program in Clinical Drug Development of Herbal Medicine College of Pharmacy Taipei Medical University Taipei11031 Taiwan Traditional Herbal Medicine Research Center Taipei Medical University Hospital Taipei11031 Taiwan Graduate Institute of Natural Products College of Medicine Chang Gung University Taoyuan333323 Taiwan Research Center for Chinese Herbal Medicine Graduate Institute of Healthy Industry Technology College of Human Ecology Chang Gung University of Science and Technology Taoyuan333324 Taiwan Department of Chemical Engineering Ming Chi University of Technology New Taipei City243303 Taiwan Department of Anesthesiology Chang Gung Memorial Hospital Taoyuan333423 Taiwan Instrumentation Center National Taiwan University Taipei106319 Taiwan

Chromatographic investigation on the ethyl acetate extract of the soft coral Lobophytum durum collected from the waters of Guishan Island in northeast Taiwan resulted in the isolation of three sterols 1–3, including one new sterol, 3β-hydroxy-25-methylene-5-cholesten-7-one (1), and two previously reported sterols, 7-oxogorgosterol (2), and (24R)-ergostane-3β,5α,6β,25-tetraol 25-monoacetate (3). The structures of sterols 1–3 were determined by extensive spectroscopic data analysis and by comparison with literatures. Additionally, the 24R-configuration of sterol 3 was identified by a single-crystal X-ray diffraction analysis and 13C chemical shifts for first time. The anti-inflammatory activities of sterols 1–3 were evaluated by examining their inhibitory effects on the generation of superoxide anions and the release of elastase against activated human neutrophils. © 2023

关键词： Spectroscopic analysis

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Affordable, high-resolution bioprinting with embedded concentration gradients

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Bioprinting 2021年 21卷

作者： Shen, Edwin M. McCloskey, Kara E. Graduate Program in Biological Engineering and Small-scale Technologies University of California Merced United States Department of Materials Science and Engineering University of California Merced United States

Three-dimensional (3D) bioprinting has brought major innovations to the field in its ability to fabricate cell-laden constructs that closely resemble physiological tissue. Unfortunately, many bioprinters print only one material and at limited resolutions. Improving on the resolutions, functionality, and affordability necessitates attention to both printing techniques and printers. Here, we present our results towards building an affordable, partially open-source bioprinter, ModiPrint, that enables multiple cell-material combination printing with high resolution extrusions (100 μm) of alginate. We also introduce a new technique to improve extrusion resolution in complex geometries. The results show that we were able to maintain viability of human pluripotent stem cells (hiPSCs) after high resolution printing. Lastly, we were able to generate concentration gradients of small molecules or cytokines embedded within hydrogels by combining extrusion and drop-on-demand bioprinting. We expect ModiPrint and the novel techniques in our study will assist other bioprinting researchers. © 2020 The Authors

关键词： Alginate Biomimicry Bioprinting Concentration gradients FRESH Hydrogels ModiPrint Open-source Pluripotent stem cells

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Development and characterization of biodegradable active films based on rice starch with nanocellulose and Amaranthus viridis extract

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International journal of biological macromolecules 2025年 318卷 145243页

作者： Jocilane Pereira de Oliveira Vanderlúcio de Souza Moreira Jéssica Santos de Oliveira Lucas Britto Landim Normane Mirele Chaves da Silva Cristiane Patrícia de Oliveira Graduate Program in Food Engineering and Science State University of Bahia Itapetinga BA 45700-000 Brazil. Electronic address: jocilanepereira20@***. Department of Agribusiness Technology Federal Institute of Education Science and Tecnology of Baiano Guanambi Campus Guanambi 46430-000 Bahia Brazil. Graduate Program in Food Engineering and Science State University of Bahia Itapetinga BA 45700-000 Brazil.

This study investigated the incorporation of Amaranthus viridis (AV) extract into films composed of rice starch (RS) and nanocellulose (CNF) at concentrations of 5 %, 7.5 %, and 10 %, aiming to evaluate the effects on physicochemical, mechanical, and antioxidant properties. The addition of AV increased the films' structural density, especially at 10 %, which showed a compact surface with no visible pores and characteristic specks related to mineral salt crystallization (calcium, iron, magnesium) interacting with oxalates to form insoluble complexes. Fourier-transform infrared spectroscopy (FTIR) analysis confirmed interactions between extract compounds and the polymer matrix. Thermal stability improved with more extract, with degradation peaks reaching 420 °C at 10 % AV. Water solubility increased from 28 % (RS + CNF) to 37 % (10 % AV), while water holding capacity decreased from 42 % to 26 %. Film thickness decreased from 80 μm to 50 μm. Regarding mechanical properties, tensile strength rose to 6.5 MPa at 5 % AV, and elongation at break reached 145 % with 10 % AV, indicating increased flexibility. Antioxidant activity improved with higher AV levels, with the 10 % film presenting the best performance: FRAP (499.10 μg/mL), phosphomolybdenum method (372.42 mg AAE/g), ABTS (26.52 % RSA), and DPPH IC₅₀ (27.42 μg/mL). All formulations exhibited biodegradability, with mass loss above 80 % after 15 days of soil exposure. In conclusion, the incorporation of Amaranthus viridis extract, particularly at 10 %, enhanced the films' structural, mechanical, and antioxidant properties, confirming its potential for use in active and biodegradable packaging.

关键词： Antioxidant activity Caruru Cellulose nanofibrils Food packaging

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Recurrence plots and convolutional neural networks applied to nonintrusive load monitoring

Recurrence plots and convolutional neural networks applied t...

引用

2020 IEEE Power and Energy Society General Meeting, PESGM 2020

作者： Cavalca, Diego L. Fernandes, Ricardo A. S. Federal University of São Carlos Graduate Program in Computer Science São Carlos Brazil Federal University of São Carlos Electrical Engineering Department São Carlos Brazil

ISBN: (纸本)9781728155081

The need to increasingly promote the efficient use of electricity for residential consumers motivated some researches to obtain solutions that allow the identification of loads for use in demand response programs and in the energy consumption disaggregation. Recently, the use of Convolutional Neural Networks for load identification has been common. However, it is necessary to transform the temporal signal into an image. In this sense, the present paper proposes a novel feature engineering stage, based on Recurrence Plots, to obtain the images for Nonintrusive Load Monitoring. In order to prove its effectiveness, the Recurrence Plots were compared to the Gramian Angular Difference Fields, which had already been applied in this context. For this purpose, it was used the REDD dataset, in which only the low frequency data measured in the main distribution panel were considered. Individual load measurements were only used for the labelling of the 90-seconds windows. The Convolutional Neural Network was trained and validated, considering two different strategies (multi-label and binary models), obtaining an F1-score of 66.05% and 72.65%, respectively. © 2020 IEEE.

关键词： Machine learning

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Dynamic programming Algorithm using Furniture Industry 0/1 Knapsack Problem

Dynamic Programming Algorithm using Furniture Industry 0/1 K...

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International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Mietha Anditta Natashya Amartya Laurens Spits Warnars Harco Leslie Hendric Spits Warnars Arief Ramadhan Teddy Siswanto Teddy Mantoro Nurulhuda Noordin Computer Science Departement School of Computer Science Bina Nusantara University Jakarta Indonesia Information Systems Departement School of Information Systems Bina Nusantara University Jakarta Indonesia Computer Science Departement BINUS Graduate Program - Computer Science Bina Nusantara University Jakarta Indonesia PJJ Informatika Telkom University Bandung Indonesia Information Systems Department Trisakti University Jakarta Indonesia Faculty of Engineering and Technology Sampoerna University Jakarta Indonesia School of Computing Sciences College of Computing Informatics and Mathematics Universiti Teknologi MARA Selangor Malaysia

Dynamic programming is a fundamental algorithm that can be found in our daily lives easily. One of the dynamic programming algorithm implementations consists of solving the 0/1 knapsack problem. A 0/1 knapsack problem can be seen from industrial production cost. It is prevalent that a production cost has to be as efficient as possible, but the expectation is to get the proceeds of the products higher. Thus, the dynamic programming algorithm can be implemented to solve the diverse knapsack problem, one of which is the 0/1 knapsack problem, which would be the main focus of this paper. The implementation was implemented using C language. This paper was created as an early implementation algorithm using a Dynamic program algorithm applied to an Automatic Identification System (AIS) dataset.

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