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Gold nanoclusters supported Molybdenum diselenide-porous carbon composite as an efficient electrocatalyst for selective ultrafast probing of chlorpyrifos-pesticide

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Chemical engineering Journal 2023年第1期472卷

作者： Ezhil Vilian, A.T. Mohammadi, Ali Han, Soobin Tiwari, Jitendra N. Kumar, Krishan Senthil Kumar, Annamalai Saravanan, Adhimoorthy Huh, Yun Suk Han, Young-Kyu Department of Energy and Materials Engineering Dongguk University-Seoul Seoul100-715 Korea Republic of Department of Biological Sciences and Bioengineering Incheon402-751 Korea Republic of Nano Bioelectrochemistry Research Laboratory CO2 Research and Green Technologies Centre Vellore Institute of Technology University Vellore632014 India Graduate Institute of Electro-Optical Engineering and Department of Electronic and Computer Engineering National Taiwan University of Science and Technology Taipei106 Taiwan

Chlorpyrifos (CPS) is an organophosphorus pesticide widely utilized in agricultural production. Much like other commonly used highly toxic and hazardous substances, is harmful to humans, plants, and animals. Thus, the development of highly efficient electrocatalysts that can monitor and detect levels of CPS in environmental samples is urgently required. This research describes a simple means of synthesizing Au nanoclusters (AuNCs) incorporated into MoSe2-Porous carbons (PCs) via a single-step hydrothermal reaction followed by chemical reduction. AuNC-MoSe2-PC coated Glassy carbon electrodes (GCEs) exhibited excellent electrocatalytic activity, interfacial charge transfer ability (96 Ω), and cathodic peak intensities at a low reduction wave potential (∼ −0.74 V) for sensing CPS. The developed sensor exhibited a wide linear range from 5 to 185 nM, a rapid amperometric response of −1 cm−2) for CPS at −0.74 V vs. Ag|AgCl than other reported modified electrodes. Furthermore, the sensor had excellent reproducibility, repeatability, reusability, and long-time stability (88 % activity retention after 1 month) with a relative standard deviation (RSD) of © 2023 Elsevier B.V.

关键词： Selenium compounds

Implantable CMOS probes for high resolution Electrical Imaging of Local Field Potentials Across the Rat Barrel Cortex in vivo

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arXiv 2025年

作者： Cecchetto, Claudia Mahmud, Mufti Sorrenti, Vincenzo Maschietto, Marta Chiarello, Enrico Schulz, Mathias Thewes, Roland Vassanelli, Stefano Department of Biomedical Sciences University of Padova via Ugo Bassi 58B Padova35131 Italy Optical Neuroimaging Unit Okinawa Institute of Science and Technology Graduate University OIST Okinawa Japan Padua Neuroscience Center University of Padova via Orus 2/B Padova35131 Italy Nottingham Trent University United Kingdom Department of Pharmaceutical & Pharmacological Sciences University of Padova Padova35131 Italy Faculty of Electrical Engineering & Computer Science TU Berlin Berlin Germany

High-resolution recordings of extracellular potentials are fundamental for the study of neuronal networks, the basis of neuronal coding and transmission. Here we present an innovative method for an in vivo electrical imaging of Local Field Potentials using novel implantable neural interfaces with a high-density array of 256 recording sites and a spatial resolution of 15 µm. Thanks to this technology, we analyze the propagation of whisker-evoked activity in a single barrel-column of the rat somatosensory *** Codes / © 2025, CC BY.

关键词： Rats

Elementary symmetric partitions

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arXiv 2024年

作者： Ballantine, Cristina Beck, George Merca, Mircea Sagan, Bruce E. Department of Mathematics and Computer Science College of the Holy Cross WorcesterMA01610 United States Department of Mathematics and Statistics Dalhousie University HalifaxNSB3H 4R2 Canada Department of Mathematical Methods and Models Fundamental Sciences Applied in Engineering Research Center National University of Science and Technology Politehnica Bucharest BucharestRO-060042 Romania Academy of Romanian Scientists BucharestRO-050044 Romania Department of Mathematics Michigan State University East LansingMI48824 United States

Let ek(x1,..., x) be an elementary symmetric polynomial and let λ = (λ1,..., λ) be an integer partition. Define prek(λ) to be the partition whose parts are the summands in the evaluation ek(λ1,..., λ). The study of such partitions was initiated by Ballantine, Beck, and Merca who showed (among other things) that pre2 is injective as a map on binary partitions of n. In the present work we derive a host of identities involving the sequences which count the number of parts of a given value in the image of pre2. These include generating functions, explicit expressions, and formulas for forward differences. We generalize some of these to d-ary partitions and explore connections with color partitions. Our techniques include the use of generating functions and bijections on rooted partitions. We end with a list of conjectures and a direction for future *** Codes 05A17, 05E05 (Primary) 05A15, 05A19 (Secondary) © 2024, CC BY.

关键词： Integer linear programming

Large-Scale Multidisciplinary Design Optimization of an eVTOL Aircraft Using Comprehensive Analysis

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Large-Scale Multidisciplinary Design Optimization of an eVTO...

AIAA SciTech Forum and Exposition, 2023

作者： Sarojini, Darshan Ruh, Marius L. Sperry, Mark Yan, Jiayao Fletcher, Andrew Joshy, Anugrah Jo Scotzniovsky, Luca Ivanov, Alexander Orndorff, Nicholas Gandarillas, Victor Asher, Isaac Chambers, Jeff Gill, Hyunjune Lee, Seongkyu Cheng, Zeyu Rodriguez, Gabriel Zhao, Shuofeng Mi, Chunting Nascenzi, Thomas Cuatt, Timothy Winter, Tyler Guibert, Alexandre Cronk, Ashley Kim, Alicia Meng, Shirley Hwang, John T. Department of Mechanical and Aerospace Engineering University of California San Diego 9500 Gilman Dr La Jolla CA92093 United States Flight Physics Aurora Flight Sciences A Boeing Company 9950 Wakeman Drive ManassasVA20110 United States Engineering Department Aurora Flight Sciences A Boeing Company 9950 Wakeman Drive ManassasVA20110 United States Department of Mechanical and Aerospace Engineering University of California Davis 1 Shields Avenue DavisCA95616 United States Department of Electrical and Computer Engineering San Diego State University 5500 Campanile Dr San Diego92182 United States Research and Development M4 Engineering Inc 4020 Long Beach Blvd # 2 Long BeachCA90807 United States Structural Engineering Department University of California San Diego 9500 Gilman Dr La Jolla CA92093 United States Materials Science and Engineering Program University of California San Diego 9500 Gilman Dr La Jolla CA92093 United States Department of NanoEngineering University of California San Diego 9500 Gilman Dr La Jolla CA92093 United States

ISBN: (数字)9781624106996

ISBN: (纸本)9781624106996

This paper presents a framework under development for enabling large-scale multi-fidelity modeling and optimization of electric vertical takeoff and landing concepts (eVTOL). The key features of the framework are a geometry-centric approach to multidisciplinary design optimization (MDO), a modular functional-form representation of the disciplines involved in aircraft design, and fully automated derivative computations thereby allowing efficient gradient-based optimization. The framework is first presented in a general manner agnostic to the vehicle concept or the physics-based analyses used. The key disciplines involved in the design of eVTOL aircraft and the couplings between the disciplines are described. The framework is then applied to the design of the NASA lift-plus-cruise concept. Low-fidelity solvers of aerodynamics, propulsion, structural estimation, acoustics, powertrain, and battery are coupled together. The optimization considers 108 design variables and 16 constraints. It is shown that MDO considering geometric variables results in a design with lower gross mass than when the geometric variables are not considered. The optimization turnaround time of 30 minutes on a standard workstation demonstrates the capabilities of fully-coupled large-scale MDO using gradient-based optimization. The framework is under development and an open-source version will be released in the near future. © 2023, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Geometry

A Convolutional Block Attention Module Based Lightweight Convolutional Neural Network Model for Rotating Machinery Fault Diagnosis

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SSRN

SSRN 2023年

作者： Lu, Na Li, Ruiqiang Zhang, Guangtao Cao, Chaofan Chen, Xudong Guo, Jinjun Malik, Om Parkash Yellow River Laboratory Zhengzhou University Zhengzhou45000 China School of Water and Civil Engineering Zhengzhou University Zhengzhou45000 China Rundian Energy Science and Technology Co. Ltd. Zhengzhou450052 China Department of Electrical and Computer Engineering University of Calgary CalgaryABT2N 1N4 Canada

Most deep learning methods have too many parameters for rotating machinery fault diagnosis. As a result, high computer performance is required, which may be difficult to achieve in some circumstances. To address this problem, a Convolutional Block Attention Module based lightweight Convolutional Neural Network (CBAM-LightCNN) model is proposed. To obtain optimal fault diagnosis results, the hyperparameters of this model are optimized by using Neural Network Intelligence (NNI). Besides, a new multi-sensor data fusion (DF) method is designed to fuse the raw multi-sensor data before feeding it into the CBAM-LightCNN. Compared with other traditional CNN models, this method not only reduces the number of parameters but also avoids dependence on user experience for feature extraction and hyperparameter settings. Through the experimental validation of two datasets consisting of the Case Western Reserve University (CWRU) dataset and hydropower unit operation dataset, the proposed method illustrates better diagnostic performance with 100% recognition accuracy in comparison with Artificial Neural Network (ANN), and traditional CNN methods. © 2023, The Authors. All rights reserved.

关键词： Failure analysis

Zero-Shot Audio Captioning Using Soft and Hard Prompts

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arXiv 2024年

作者： Zhang, Yiming Xu, Xuenan Du, Ruoyi Liu, Haohe Dong, Yuan Tan, Zheng-Hua Wang, Wenwu Ma, Zhanyu The Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing100876 China The Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai200240 China The Department of Electronic Systems Aalborg University Aalborg9220 Denmark The Centre for Vision Speech and Signal Processing University of Surrey GuildfordGU2 7XH United Kingdom

In traditional audio captioning methods, a model is usually trained in a fully supervised manner using a human-annotated dataset containing audio-text pairs and then evaluated on the test sets from the same dataset. Such methods have two limitations. First, these methods are often data-hungry and require time-consuming and expensive human annotations to obtain audio-text pairs. Second, these models often suffer from performance degradation in cross-domain scenarios, i.e., when the input audio comes from a different domain than the training set, which, however, has received little attention. We propose an effective audio captioning method based on the contrastive language-audio pre-training (CLAP) model to address these issues. Our proposed method requires only textual data for training, enabling the model to generate text from the textual feature in the cross-modal semantic space. In the inference stage, the model generates the descriptive text for the given audio from the audio feature by leveraging the audio-text alignment from CLAP. We devise two strategies to mitigate the discrepancy between text and audio embeddings: a mixed-augmentation-based soft prompt and a retrieval-based acoustic-aware hard prompt. These approaches are designed to enhance the generalization performance of our proposed model, facilitating the model to generate captions more robustly and accurately. Extensive experiments on AudioCaps and Clotho benchmarks show the effectiveness of our proposed method, which outperforms other zero-shot audio captioning approaches for in-domain scenarios and outperforms the compared methods for cross-domain scenarios, underscoring the generalization ability of our method. © 2024, CC BY.

关键词： Semantics

Compact Silicon Nitride Interferometer

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Compact Silicon Nitride Interferometer

Frontiers in Optics + Laser science 2021, FiO+LS 2021 - Part of Frontiers in Optics, FiO 2021

作者： Armin, Fahimeh Nabki, Frederic Ménard, Michaël Department of Computer Science Université du Québec à Montréal MontréalQCH2X 3Y7 Canada Department of Electrical Engineering Ecole de Technologie Supérieure MontréalQCH3C 1K3 Canada

We demonstrate a silicon nitride interferometer with waveguides having different effective indexes instead of lengths to avoid waveguide bends, reduce losses and footprint. Frontiers in Optics / Laser science © O... 详细信息

ISBN: (纸本)9781557528209

关键词： Silicon nitride

Calorimetric Studies and Thermodynamic Modeling of Ag–Mg–Ti Liquid Alloys

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Materials 2024年第8期17卷 1786页

作者： Gozdur, Weronika Gąsior, Wladyslaw Zrobek, Maciej Budziak, Andrzej Dębski, Roman Gierlotka, Wojciech Pęska, Magda Polański, Marek Dębski, Adam Institute of Metallurgy and Materials Science Polish Academy of Sciences 25 Reymonta Street Kraków30-059 Poland Faculty of Energy and Fuels AGH University of Krakow Al. Mickiewicza 30 Kraków30-059 Poland Institute of Computer Science AGH University of Krakow Al. Mickiewicza 30 Kraków30-059 Poland Department of Materials Science and Engineering National Dong Hwa University Hualien970024 Taiwan Department of Functional Materials and Hydrogen Technology Military University of Technology 2 Kaliskiego St. Warsaw00-908 Poland

Due to the absence of thermodynamic data concerning the Ag–Mg–Ti system in the existing literature, this study aims to fill this gap by offering the outcomes of calorimetric investigations conducted on ternary liquid solutions of these alloys. The measurements were performed using the drop calorimetry method at temperatures of 1294 K and 1297 K for the liquid solutions with the following constant mole fraction ratio: xAg/xMg = 9/1, 7/3, 1/1, 3/7 [(Ag0.9Mg0.1)1−xTix, (Ag0.7Mg0.3)1−xTix, (Ag0.5Mg0.5)1−xTix, (Ag0.3Mg0.7)1−xTix)], and xAg/xTi = 19/1 [(Ag0.95Ti0.05)1−xMgx]. The results show that the mixing enthalpy change is characterized by negative deviations from the ideal solutions and the observed minimal value equals −13.444 kJ/mol for the Ag0.95Ti0.05 alloy and xMg = 0.4182. Next, based on the thermodynamic properties of binary systems described by the Redlich–Kister model and the determined experimental data from the calorimetric measurements, the ternary optimized parameters for the Ag–Mg–Ti liquid phase were calculated by the Muggianu model. Homemade software (TerGexHm 1.0) was used to optimize the calorimetric data using the least squares method. Next, the partial and molar thermodynamic functions were calculated and are presented in the tables and figures. Moreover, this work presents, for comparative purposes, the values of the enthalpy of mixing of liquid Ag–Mg–Ti alloys, which were calculated using Toop’s model. It was found that the best agreement between the modeled and experimental data was observed for the cross-sections xAg/xTi = 19/1 [(Ag0.95Ti0.05)1−xMgx] and xAg/xMg = 9/1 [(Ag0.9Mg0.1)1−xTix]. The results of the experiments presented in this paper are the first step in the investigation and future evaluation of the thermodynamics of phases and the calculation of the phase diagram of the silver–magnesium–titanium system. © 2024 by the authors.

关键词： Calorimetry

How more data can hurt: Instability and regularization in next-generation reservoir computing

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arXiv 2024年

作者： Zhang, Yuanzhao dos Santos, Edmilson Roque Cornelius, Sean P. Santa Fe Institute 1399 Hyde Park Road Santa FeNM87501 United States Department of Electrical and Computer Engineering Clarkson University PotsdamNY13699 United States Clarkson Center for Complex Systems Science Clarkson University PotsdamNY13699 United States Department of Physics Toronto Metropolitan University TorontoONM5B 2K3 Canada

It has been found recently that more data can, counter-intuitively, hurt the performance of deep neural networks. Here, we show that a more extreme version of the phenomenon occurs in data-driven models of dynamical systems. To elucidate the underlying mechanism, we focus on next-generation reservoir computing (NGRC)—a popular framework for learning dynamics from data. We find that, despite learning a better representation of the flow map with more training data, NGRC can adopt an ill-conditioned "integrator" and lose stability. We link this data-induced instability to the auxiliary dimensions created by the delayed states in NGRC. Based on these findings, we propose simple strategies to mitigate the instability, either by increasing regularization strength in tandem with data size, or by carefully introducing noise during training. Our results highlight the importance of proper regularization in data-driven modeling of dynamical systems. Copyright © 2024, The Authors. All rights reserved.

关键词： Spatio-temporal data