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Strong nonreciprocal acoustic extinction and asymmetric audibility from spinning fluid scatterers

Physical Review B 2023年第16期108卷 165129-165129页

作者： Yao-Ting Wang Heedong Goh Sander A. Mann Andrea Alù Photonics Initiative Advanced Science Research Center City University of New York New York New York 10031 USA Department of Photonics National Sun Yat-Sen University Kaohsiung 804201 Taiwan Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 USA Physics Program Graduate Center City University of New York New York New York 10026 USA

Lorentz reciprocity places important constraints on the response of systems to wave excitations, and surpassing these constraints is of both fundamental and applied interest. In the context of scattering, reciprocity requires that the total extinction of an object is identical when excited from opposite directions, regardless of the asymmetry of the scatterer. Here, we demonstrate that, by combining multiple scatterers that break time-reversal symmetry, this extinction symmetry can be largely violated. We consider spinning cylinders, demonstrating that nonreciprocity must be paired with broken parity symmetry to enable large extinction contrast. As a dramatic example, we show a system that strongly scatters when excited from one side, but it is cloaked for the opposite excitation. Our results pave the way for approaches to asymmetric audibility and scattering manipulation, and they may readily translate to other wave domains.

关键词： Acoustic metamaterials Acoustics Non-reciprocal propagation

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Antibacterial activity of functionalized natural zeolites (NZ-AgNPs) and its application in bacteriological water treatment and commercial paints

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Environmental Nanotechnology, Monitoring and Management 2024年 22卷

作者： Ribeiro, Anna Carla de Oliveira, Alessandra Marjorie Beltran, Laiza Bergamasco Diório, Alexandre Magalhães-Ghiotto, Grace Anne Vieira de Abreu Filho, Benício Alves de Almeida Duarte, Elizabeth da Costa Neves Fernandes Bergamasco, Rosângela State University of Maringá Department of Biotechnology Genetics and Cell Biology Paraná Maringá Brazil State University of Maringá Graduate Program in Food Science Paraná Maringá 87020-900 Brazil State University of Maringá Department of Chemical Engineering Paraná Maringá 87020-900 Brazil Linking Landscape Environment Agriculture and Food School of Agriculture – University of Lisbon Lisbon Portugal

Developing advanced materials with efficient antibacterial properties to guarantee human health protection is urgent. This study aimed to evaluate the antibacterial performance of natural zeolite (NZ) functionalized with silver nanoparticles (Ag NPs), obtained from a green reducing method using Moringa oleifera seed extract (NZ-AgNPs), against a Gram-negative bacteria, namely Escherichia coli (E. coli). Moreover, two applications were tested: bacteria adsorption for water treatment, namely Escherichia coli, and its incorporation in commercial paints. The proposed modifications were confirmed by advanced characterization techniques (TEM, SEM, EDX, FTIR, XRD, and ZP). The antibacterial activity assay was conducted using minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC). The results demonstrated the advantages of using an inorganic support for carrying biocidal agents. The required amount of Ag NPs, when it was supported onto NZ (NZ-AgNPs), was four times less to exhibit the bactericidal effect against Escherichia coli than Ag NPs on their own since they had the same MBC value (1.56 mg ml⁻¹). The observed adsorption behavior corroborates such findings and demonstrates that 0.01 g of the proposed composite achieved 100 % of E. coli removal and 9.85 log reduction. Regarding commercial paint experiments, the NZ-AgNPs successfully demonstrated the potential to inhibit bacterial growth with an inhibition zone (IZ) of 41 mm. Using inorganic carriers, as NZ, for controlling the biocidal compound release can bring economic and environmental advantages because zeolite is a natural material and the saved amount of biocidal agent, namely Ag NPs, are desirable features of a new antibacterial additive's generation. © 2024

关键词： Antibacterial agents Clinoptilolite Nanotechnology Paints Water treatment

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Realtime Vehicle Counting Method Using Haar Cascade Classifier Model

Realtime Vehicle Counting Method Using Haar Cascade Classifi...

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International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation (ICAMIMIA)

作者： Prasetyo Mimboro Yaya Heryadi Lukas Wayan Suparta Antoni Wibowo Doctor of Computer Science Graduate Program Faculty of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group (CERG) Atma Jaya University Jakarta Indonesia Computer Science Department Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781665499705

The proliferation of digital camera technology has provided many digital images for object detection and counting in public places. This paper presents an experiment on the realtime vehicle counting method to be implemented in a single board computer. The proposed design's objective is to detect and count vehicles entering and exiting at entrances using haar cascade classifier algorithms and other automatic open and close door systems controlled by a single board computer (SBC). The proposed system was tested using raspberry pi 4 model B with a 4GB RAM platform. The empiric results using 3-minute video as input with a total of 113 passing vehicles the proposed method achieve of 91.2 % of average accuracy.

关键词： Mechatronics Automation computational modeling Digital images Random access memory Object detection Logic gates

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Detection and Quantitation of Adulteration in Flour and Pasta by Reversed-Phase High-Performance Liquid Chromatography Combined with Chemometrics

SSRN

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SSRN 2024年

作者： Unuvar, Aslihan Simsek, Senay Boyaci, Ismail Hakki Ohm, Jae-Bom Manthey, Frank A. Koksel, Hamit Department of Food Engineering Hacettepe University Ankara Turkey Department of Food Science Whistler Center for Carbohydrate Research Purdue University West LafayetteIN47907 United States USDA-ARS Edward T. Schafer Agricultural Research Center Small Grain & Food Crops Quality Research Unit Hard Spring and Durum Wheat Quality Laboratory FargoND58102 United States Cereal Science Graduate Program Department of Plant Sciences North Dakota State University FargoND United States Nutrition and Dietetics Department Istinye University Istanbul Turkey

Reversed-phase high-performance liquid chromatography (RP-HPLC) was utilized to distinguish between durum and common wheat varieties from Turkey (TR) and the United States (U.S.) using partial least squares-discriminant analysis. The root mean squared error values of prediction were 0.172 and 0.040 for TR and U.S. samples. Graphical analysis showed a strong link between wheat origin and clustering. These results indicate that RP-HPLC separates effectively various wheat samples into distinct categories. This study also aimed to detect and quantify common wheat in blended flour and farina in pasta from TR and U.S. using partial least square regression. The coefficients of determination of predicting adulteration were 0.895 and 0.997 for flour samples and were 0.992 and 0.985 for pasta samples of TR and U.S, respectively. These results highlight potential of RP-HPLC with chemometrics, as a robust tool for both differentiating wheat varieties and quantifying adulteration in blended flour and pasta samples. © 2024, The Authors. All rights reserved.

关键词： High performance liquid chromatography

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Optogenetic Neural Probes: Fiberless, High-Density, Artifact-Free Neuromodulation : (Invited)

Optogenetic Neural Probes: Fiberless, High-Density, Artifact...

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International Electron Devices Meeting (IEDM)

作者： Eunah Ko Kanghwan Kim Mihály Vöröslakos Sungjin Oh György Buzsáki Kensall D. Wise Euisk Yoon Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI USA Center for BioMicrosystems Brain Science Institute Korea Institute of Science and Technology Seoul Korea Neuroscience Institute Langone Medical Center New York University New York NY USA Department of Biomedical Engineering University of Michigan Ann Arbor MI USA Center for Nanomedicine Institute for Basic Science (IBS) and Graduate Program of Nano Biomedical Engineering (Nano BME) Advanced Science Institute Yonsei University Seoul Korea

ISBN: (纸本)9781665489607

Evolution of “Michigan Probes” has enabled unraveling the connectivity of neurons at cellular resolution and their dynamic interaction within and across brain areas that underlie behavioral and cognitive functions. Recently, micro-LEDs were monolithically integrated for optogenetic neuromodulation at scale without requiring external optical fiber connection. The ‘hectoSTAR’ micro-LED optoelectrode features 256 recording electrodes and 128 stimulation micro-LEDs in four silicon micro-needle shanks, covering a large volume with 1.3-mm × 0.9-mm cross-sectional area located as deep as 6 mm inside the brain. Technical challenges to overcome in scaling of optogenetic probes will be discussed, followed by future direction.

关键词： Optical fibers Electrodes Brain Optogenetics Silicon Recording Optical fiber devices

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Deep Learning Based Facial Emotion Recognition using Multiple Layers Model

Deep Learning Based Facial Emotion Recognition using Multipl...

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International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation (ICAMIMIA)

作者： Lidia Sandra Yaya Heryadi Lukas Wayan Suparta Antoni Wibowo Psychology Department Krida Wacana Christian University Jakarta Indonesia Computer Science Department BINUS Graduate Program-Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group (CERG) Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781665499705

A Facial Emotion Recognition (FER) system is an important tool to be implemented in any psychology academic field and beyond. This paper aims to show a system of Facial Emotion Recognition that can be done using the multiple layers model of ResN et50 which is an ANN. The dataset is an array that consists of 7 different emotions represented by the numbers 0–6. The emotion included in the dataset is “anger”, “disgust”, “fear”, “happiness”, “sadness”, “shock”, and “neutrality”. This research found that the highest accuracy in the application of the model was recorded at 65% and the test was 60% to recognize facial emotion from a graphical input.

关键词： Deep learning Emotion recognition Mechatronics Automation Face recognition Electric shock Psychology

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Oxygen-producing composite dressing activated by photothermal and piezoelectric effects for accelerated healing of infected wounds

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Chemical engineering Journal 2023年 476卷

作者： Lai, Yen-Han Roy Barman, Snigdha Ganguly, Anindita Pal, Arnab Yu, Jui-Han Chou, Syun-Hong Huang, E-Wen Lin, Zong-Hong Chen, San-Yuan Department of Materials Science and Engineering National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Institute of Biomedical Engineering National Tsing Hua University Hsinchu30013 Taiwan Department of Biomedical Engineering National Taiwan University Taipei10617 Taiwan Graduate Institute of Biomedical Science China Medical University Hospital Taichung40400 Taiwan School of Dentistry College of Dental Medicine Kaohsiung Medical University Kaohsiung80708 Taiwan International Intercollegiate Ph.D. Program National Tsing Hua University Hsinchu30013 Taiwan

The process of wound healing is often obstructed by the prevalence of bacterial infection at the wound site. Hence, innovative strategies to alleviate infection is extremely necessary to realize effective wound recovery in a timely manner. Here, we report a self-activated composite dressing consisting of piezoelectric and photothermal functional layers for combating wound infection and provide the desired treatment. The synergistic dressing is functionalized with piezoelectric Poly-L-lactic acid (PLLA) which under the effect of ultrasound irradiation controllably generates reactive oxygen species (ROS) for antibacterial activity, thus facilitating the dressing to inhibit the growth of bacteria at the wound bed. Further, the dressing is modified with calcium peroxide (CaO2) which can effectively convert the generated ROS into molecular oxygen (O2) in presence of catalase enzyme for treating chronic hypoxia in the infected wounds. The sustained generation of O2 by the wound dressing augmented the cell proliferation, migration and tissue regeneration aiding in wound healing. By combining the inherent photothermal activity of reduced graphene oxide (rGO), the synergistic dressing under NIR irradiation enhanced the wound recovery by upregulating the heat shock protein 90 (Hsp90) secretion owing to the heat generation on the wounds. The results obtained demonstrate that the self-triggered multifunctional wound dressing is a promising candidate for clinical treatment of infected wounds with a user-friendly interface. © 2023 Elsevier B.V.

关键词： Ultrasonics

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GraCo: Granularity-Controllable Interactive Segmentation

GraCo: Granularity-Controllable Interactive Segmentation

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Yian Zhao Kehan Li Zesen Cheng Pengchong Qiao Xiawu Zheng Rongrong Ji Chang Liu Li Yuan Jie Chen School of Electronic and Computer Engineering Peking University Shenzhen China AI for Science (AI4S)-Preferred Program Peking University Shenzhen Graduate School China Peng Cheng Laboratory Shenzhen China Key Laboratory of Multimedia Trusted Perception and Efficient Computing Ministry of Education of China Xiamen University China Department of Automation and BNRist Tsinghua University Beijing China

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

Interactive Segmentation (IS) segments specific objects or parts in the image according to user input. Current IS pipelines fall into two categories: single-granularity out-put and multi-granularity output. The latter aims to allevi-ate the spatial ambiguity present in the former. However, the multi-granularity output pipeline suffers from limited interaction flexibility and produces redundant results. In this work, we introduce Granularity-Controllable Interactive Segmentation (GraCo), a novel approach that allows precise control of prediction granularity by introducing ad-ditional parameters to input. This enhances the customization of the interactive system and eliminates redundancy while resolving ambiguity. Nevertheless, the exorbitant cost of annotating multi-granularity masks and the lack of avail-able datasets with granularity annotations make it difficult for models to acquire the necessary guidance to control out-put granularity. To address this problem, we design an any-granularity mask generator that exploits the semantic property of the pre-trained IS model to automatically gen-erate abundant mask-granularity pairs without requiring additional manual annotation. Based on these pairs, we propose a granularity-controllable learning strategy that efficiently imparts the granularity controllability to the IS model. Extensive experiments on intricate scenarios at ob-ject and part levels demonstrate that our GraCo has signifi-cant advantages over previous methods. This highlights the potential of GraCo to be a flexible annotation tool, capable of adapting to diverse segmentation scenarios. The project page: https://***/GraCo.

关键词： Image segmentation Adaptation models Annotations Interactive systems Pipelines Semantics Redundancy

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Synthesis of a Novel Functionalized Biosorbent from Mango Stone and its Application in the Pharmaceutical's Removal from Water and a Synthetic Mixture

SSRN

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SSRN 2023年

作者： Ribeiro, Anna Carla Januário, Eduarda Freitas Diogo Vidovix, Taynara Basso de Almeida Duarte, Elizabeth da Costa Neves Fernandes Vieira, Angélica Marquetotti Salcedo Bergamasco, Rosângela State University of Maringá Department of Biotechnology Genetics and Cell Biology Paraná Maringá Brazil State University of Maringá Department of Chemical Engineering Paraná Maringá87020-900 Brazil Linking Landscape Environment Agriculture and Food School of Agriculture University of Lisbon Lisbon Portugal State University of Maringá Graduate program in Food Science Paraná Maringá87020-900 Brazil

As the shift towards renewable use of biosorbents of organic origin for water treatment, new approaches for recovery fruits biowastes must be established to a more sustainable waste management strategy. This paper explores the feasibility of functionalize mango stones with iron oxide MNP (MS-Fe3O4) by coprecipitation in batch adsorption processes. The synthesized material was characterized and, sequentially, used in the removal of CQN and SER, present in contaminated waters. The biosorbent was submitted to a regenerative study and treatment using a synthetic mixture of contaminants to evaluate its applicability in real effluents. The surface morphology of the functionalized biosorbent was observed through transmission electron microscopy images (TEM) and scanning electron microscopy (SEM). The chemical elements spectrum shown on material’s surface was analyzed by a dispersion X-ray spectroscopy system (EDX). Functional groups were determined by the infrared spectrum with Fourier transform (FTIR). The surface electrical properties of the material were measured by zeta potential (ZP). The study of the isotherms, in turn, revealed maximum adsorptive capacities of 53.40 and 79.10 mg g-1, respectively for CQN and SER, at 318 K, demonstrating that the increase in temperature is a favorable factor and the Langmuir model better describes the process. The pH strongly influenced the adsorption of drugs on MS-Fe3O4, and the best results were obtained in the range of pH 5 to 6. According to the thermodynamic process’s profile, it is inferred that the reaction is governed essentially by adsorption forces mainly, hydrogen and, π-π bonds, but it is also valid to consider the performance of electrostatic forces in a less significant way, due to CQN and SER molecules ionizing nature. The MS-Fe3O4 biosorbent showed good performance when evaluated in a synthetic mixture of four contaminants, with a global removal efficiency of approximately 86% and the regenerative capacity of three r

关键词： Adsorption

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A weighted multivariate fuzzy time series method for multiple output high-dimensional time series forecasting in IoT applications

A weighted multivariate fuzzy time series method for multipl...

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Latin America Congress on computational Intelligence (LA-CCI)

作者： Hugo Vinicius Bitencourt Patrícia de Oliveira Lucas Omid Orang Petrônio Silva Frederico Gadelha Guimarães Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte MG Brazil Instituto Federal do Norte de Minas Gerais Salinas MG Brazil Department of Computer Science Universidade Federal de Minas Gerais Belo Horizonte MG Brazil Instituto Federal do Norte de Minas Gerais Januária MG Brazil

ISBN: (数字)9798350374575

ISBN: (纸本)9798350374582

In Internet of Things (IoT) applications, data flows are continuous streams of high-dimensional time series that aggregate various data sources. In this context, decision-making processes frequently encompass multiple factors and criteria that demand forecasting these time series. This paper introduces MO-WMVFTS, a novel multiple-input multiple-output (MIMO) fuzzy time series (FTS) method for tackling this complex scenario. MO-WMVFTS is a hybrid forecasting method that fuses weighted multivariate FTS (WMVFTS) with embedding transformations, designed for IoT applications. To assess the performance of the proposed method, it was applied to the prediction of energy consumption in smart homes and air quality in smart cities. Here, three real-world datasets are used to assess the validity of our proposed approach, and the results obtained are highly competitive when compared to other existing methods.

关键词： Smart buildings Smart cities Soft sensors Time series analysis Smart homes Predictive models Internet of Things Forecasting Streams MIMO communication

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