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Harnessing Selectivity and Sensitivity in Ion Sensing via Supramolecular Recognition: A 3D Hybrid Gold Nanoparticle Network Chemiresistor

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advanced FUNCTIONAL MATERIALS 2021年第10期31卷 2008554-2008554页

作者： Montes-Garcia, Veronica de Oliveira, Rafael Furlan Wang, Ye Berezin, Andrey Fanjul-Bolado, Pablo Gonzalez Garcia, Maria Begona Hermans, Thomas M. Bonifazi, Davide Casalini, Stefano Samori, Paolo Univ Strasbourg CNRS UMR 7006 ISIS 8 Allee Gaspard Monge F-67000 Strasbourg France Cardiff Univ Sch Chem Pk Pl Cardiff CF10 3AT Wales Metrohm DropSens SL Vivario Ciencias Salud Calle Oviedo 33010 Spain Univ Strasbourg CNRS UMR 7140 4 Rue Blaise Pascal F-67081 Strasbourg France Univ Vienna Inst Organ Chem A-1090 Vienna Austria Univ Padua Dipartimento Sci Chim Via Marzolo 1 I-35131 Padua Italy

The monitoring of K+ in saliva, blood, urine, or sweat represents a future powerful alternative diagnostic tool to prevent various diseases. However, several K+ sensors are unable to meet the requirements for the development of point-of-care (POC) sensors. To tackle this grand-challenge, the fabrication of chemiresistors (CRs) based on 3D networks of Au nanoparticles covalently bridged by ad-hoc supramolecular receptors for K+, namely dithiomethylene dibenzo-18-crown-6 ether is reported here. A multi-technique characterization allows optimizing a new protocol for fabricating high-performing CRs for real-time monitoring of K+ in complex aqueous environments. The sensor shows exceptional figures of merit: i) linear sensitivity in the 10(-3) to 10(-6) m concentration range;ii) high selectivity to K+ in presence of interfering cations (Na+, Ca2+, and Mg2+);iii) high shelf-life stability (>45 days);iv) reversibility of K+ binding and release;v) successful device integration into microfluidic systems for real-time monitoring;vi) fast response and recovery times (<18 s), and v) K+ detection in artificial saliva. All these characteristics make the supramolecular CRs a potential tool for future applications as POC devices, especially for health monitoring where the determination of K+ in saliva is pivotal for the early diagnosis of diseases.

关键词： chemiresistors metal nanoparticles microfluidics molecular recognition point-of-care sensor

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Energy-Aware Edge Intelligence for Dynamic Intelligent Transportation systems 1

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10th International advanced Computing Conference, IACC 2020

作者： Benedict, Shajulin Indian Institute of Information Technology Kottayam Valavoor Kerala686635 India

ISBN: (数字)9789811604041

ISBN: (纸本)9789811604034

Intelligent Transportation System is propagating its roots among various researchers and smart city experts owing to the emergence of a wide range of applications or services, including connected cars. Next-generation tourism deliberately relies on its upcoming recommendation services that are fueled up with dynamic edge intelligence. This paper proposes an Energy-Aware Edge Intelligence (EAEI) framework for guiding tourists or automated vehicles in selecting air quality-aware tourism locations in an energy-efficient manner. EAEI collects the air quality parameter values through massive sensor networks;opts for an energy optimal prediction service to suggest air quality values;and, guides vehicles or tourists in cities. The proposed framework was evaluated at the IoT Cloud Research Lab and found to save over 90% of energy consumption in edge nodes. Besides, the article highlights the comprehensive need for the framework which inspires tens of thousands of solutions in the near future. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Air quality

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Fluorinated interphase enables reversible aqueous zinc battery chemistries

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NATURE NANOTECHNOLOGY 2021年第8期16卷 902-+页

作者： Cao, Longsheng Li, Dan Pollard, Travis Deng, Tao Zhang, Bao Yang, Chongyin Chen, Long Vatamanu, Jenel Hu, Enyuan Hourwitz, Matt J. Ma, Lin Ding, Michael Li, Qin Hou, Singyuk Gaskell, Karen Fourkas, John T. Yang, Xiao-Qing Xu, Kang Borodin, Oleg Wang, Chunsheng Univ Maryland Dept Chem & Biomol Engn College Pk MD 20742 USA US Army Res Lab Battery Sci Branch Energy Sci Div Sensor & Electron Devices Directorate Adelphi MD 20783 USA Brookhaven Natl Lab Chem Div Upton NY 11973 USA Univ Maryland Dept Chem & Biochem College Pk MD 20742 USA Univ Maryland Inst Phys Sci & Technol College Pk MD 20742 USA

A solid-electrolyte interphase that is permeable to Zn(ii) ions but waterproof is formed using an aqueous electrolyte composition. Cycling performances in an anode-free aqueous pouch cell show promise for intrinsically safe energy storage applications. Metallic zinc is an ideal anode due to its high theoretical capacity (820 mAh g(-1)), low redox potential (-0.762 V versus the standard hydrogen electrode), high abundance and low toxicity. When used in aqueous electrolyte, it also brings intrinsic safety, but suffers from severe irreversibility. This is best exemplified by low coulombic efficiency, dendrite growth and water consumption. This is thought to be due to severe hydrogen evolution during zinc plating and stripping, hitherto making the in-situ formation of a solid-electrolyte interphase (SEI) impossible. Here, we report an aqueous zinc battery in which a dilute and acidic aqueous electrolyte with an alkylammonium salt additive assists the formation of a robust, Zn2+-conducting and waterproof SEI. The presence of this SEI enables excellent performance: dendrite-free zinc plating/stripping at 99.9% coulombic efficiency in a Ti||Zn asymmetric cell for 1,000 cycles;steady charge-discharge in a Zn||Zn symmetric cell for 6,000 cycles (6,000 h);and high energy densities (136 Wh kg(-1) in a Zn||VOPO4 full battery with 88.7% retention for >6,000 cycles, 325 Wh kg(-1) in a Zn||O-2 full battery for >300 cycles and 218 Wh kg(-1) in a Zn||MnO2 full battery with 88.5% retention for 1,000 cycles) using limited zinc. The SEI-forming electrolyte also allows the reversible operation of an anode-free pouch cell of Ti||ZnxVOPO4 at 100% depth of discharge for 100 cycles, thus establishing aqueous zinc batteries as viable cell systems for practical applications.

关键词： Batteries Energy storage

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Part-per-trillion level trace-gas photoacoustic detection with a new racket-shaped cantilever 21

Part-per-trillion level trace-gas photoacoustic detection wi...

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Quantum Sensing and Nano Electronics and Photonics XXI 2025

作者： Pelini, Jacopo Russo, Stefano Dello Siciliani de Cumis, Mario Wang, Zhen Galli, Iacopo Pastor, Pablo Cancio Lopez Garcia, Inaki Canino, Maria Concetta Roncaglia, Alberto Akikusa, Naota Ren, Wei De Natale, Paolo Borri, Simone CNR-INO - Istituto Nazionale di Ottica Largo E. Fermi 6 Firenze50125 Italy LENS via N. Carrara 1 50019 Italy University of Naples"Federico II" Corso Umberto I 40 Napoli80138 Italy ASI Agenzia Spaziale Italiana Centro di Geodesia Spaziale Località Terlecchia Matera75100 Italy Department of Mechanical and Automation Engineering The Chinese University of Hong Kong New Territories Hong Kong Via P. Gobetti 101 Bologna40129 Italy Hamamatsu Photonics K.K. Shizuoka Japan

ISBN: (纸本)9781510685000

Trace-gas sensing at parts-per-trillion level or below, has become a hot research topic impacting daily-life applications such as human health, environmental monitoring, and security control. The scientific effort together with technological progress has enabled the possibility to reach ultra-high sensitivities also with compact and robust photoacoustic-based setups, exploiting their intrinsic high degree of flexibility with the sensitivity enhancement provided by mid-IR semiconductor laser sources and high-finesse optical cavities. In this framework, we present a study of an advanced configuration for photo-acoustic trace-gas sensors, aiming at optimizing all the key components to enable a ppt detection level. Alongside exploiting a mid-infrared continuous-wave Quantum Cascade Laser as the excitation source, a Fabry-Perot optical resonator is implemented for an efficient intracavity power enhancement. For the acoustic-to-voltage transduction an unconventional and highly performing "racket-shaped" silicon-based Micro-Electro-Mechanical System is exploited, whose oscillations are measured via a balanced Michelson interferometric readout. © 2025 SPIE.

关键词： Quantum cascade lasers

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Simulation Experiments for an Approximate Definition of the Macroscopic Fundamental Diagram

Simulation Experiments for an Approximate Definition of the ...

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Workshops of the 34th International Conference on advanced Information Networking and applications, WAINA 2020

作者： Pariota, Luigi Di Costanzo, Luca Spera, Francesco Bifulco, Gennaro Nicola LAERTE-ITS Laboratory for Advanced Experiments on Roads and Traffic Environments - Centre for Advanced Metrology Services University of Naples "Federico II" Naples Italy DICEA Department of Civil Architectural and Environmental Engineering University of Naples "Federico II" Naples Italy

ISBN: (纸本)9783030440374

The paper presents some exploratory experiments for defining a Macroscopic Fundamental Diagram starting from data collected in some specific sensor network layouts, that is by just monitoring the cordon of a study area. Variables defined in the original proposition of the MFD where here re-defined by just considering the number of vehicles estimated to be present in the study area (N) by means of this layout. We found that in some cases a strong correlation among defined variables can be found, and also similar patterns in the depicted MFD are evidenced. Findings of the paper are limited, given the limited amount of simulation performed, and also considering the limited number of factors varied in the simulations;as expected, results seem to be strongly affected by the traffic demand. Apart that, the approach is worth to be investigated, because this kind of layout is becoming very common in some urban contexts (e.g. in Italy). © 2020, Springer Nature Switzerland AG.

关键词： sensor networks

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An Efficient Energy Management Routing and Scalable Topology in Wireless sensor Network Using Virtual Backbone

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WIRELESS COMMUNICATIONS & MOBILE COMPUTING 2022年第0期2022卷 p1-10页

作者： Rayan, Alanazi Taloba, Ahmed, I Hamed, Nadir O. Zahran, Heba Y. Mahmoud, Emad E. Jouf Univ Coll Sci & Arts Qurayyat Dept Comp Sci Sakakah Saudi Arabia Assiut Univ Fac Comp & Informat Informat Syst Dept Assiut Egypt Sudan Technol Univ Elgraif Sharg Technol Coll Comp Studies Dept Khartoum Sudan King Khalid Univ Fac Sci Dept Phys Lab Nanosmart Mat Sci & Technol LNSMST POB 9004 Abha 61413 Saudi Arabia Ain Shams Univ Fac Educ Dept Phys Nanosci Lab Environm & Biomed Applicat NLEBAMet Cairo 11757 Egypt Taif Univ Coll Sci Dept Math & Stat POB 11099 Taif 21944 Saudi Arabia

The wireless sensor network (WSN) approach is one of the fastest growing approaches in the world of communications and engineering. The primary objective of a WSN is to discover the important information about the environment, depending on the nature of the applications under which it is implemented, and to communicate this information to a single base station (BS) so that appropriate measures can be taken. These sensor nodes communicate via a variety of protocols. The difficulty with the traditional system is that while collecting the observed data, each node transmits its felt information directly to a base station, which quickly exhausts its power. This study suggests a Backbone Energy-Efficient Sleeping (BEES) management strategy with two appealing features: (i) the capacity of backbone is scalable by basic parameters, and (ii) the backbone nodes were distributed equally, implying that the backbone on its own is energy efficient during routine activities. Reliable connections are expected to obtain QoS and routing protocols of such backbone nodes in wireless multihop systems. As a result, present localized routing in virtualized backbone schedule cannot ensure energy-efficient paths. An energy-efficient routing scheme for Virtual Back Bone Nodes (VBS) increases life of node and switches off its radio while in sleep state to spend less power. BEES' performance is evaluated by comparing it to two different topology management techniques. The results show that BEES performs better algorithms. It ensures optimal routing with minimal node power consumption but also implements the essential communication range for backbone networks.

关键词： Base stations

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An accurate and dynamic predictive model for a smart M-Health system using machine learning

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INFORMATION SCIENCES 2020年 538卷 486-502页

作者： Qureshi, Kashif Naseer Din, Sadia Jeon, Gwanggil Piccialli, Francesco Bahria Univ Dept Comp Sci Islamabad Pakistan Kyungpook Natl Univ Sch Comp Sci & Engn Daegu South Korea Xidian Univ Sch Elect Engn Xian 710071 Peoples R China Incheon Natl Univ Dept Embedded Syst Engn Incheon 22012 South Korea Univ Naples Federico II Dept Math & Applicat R Caccioppoli Naples Italy

Nowadays, new highly-developed technologies are changing traditional processes related to medical and healthcare systems. Emerging Mobile Health (M-Health) systems are examples of novel technologies based on advanced data communication, deep learning, artificial intelligence, cloud computing, big data, and other machine learning methods. Data are collected from sensor nodes and forwarded to local databases through new technologies that enable cellular networks and then store the information in cloud storage systems. From cloud computing services or medical centres, the data are collected for further analysis. Furthermore, machine learning techniques are being used for accurate prediction of disease analysis and for purposes of classification. This paper presents a detailed overview of M-Health systems, their model and architecture, technologies and applications and also discusses statistical and machine learning approaches. We also propose a secure Androidbased architecture to collect patient data, a reliable cloud-based model for data storage. Finally, a predictive model able to classify cardiovascular diseases according to their seriousness will be discussed. Moreover, the proposed prediction model has been compared with existing models in terms of accuracy, sensitivity, and specificity. The experimental results show encouraging results in terms of the proposed predictive model for an M-Health system. (C) 2020 Elsevier Inc. All rights reserved.

关键词： Machine learning Predictive Models M-Health Classification SVM Decision tree Accuracy

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Water Stable Zn(ii) Metal-Organic Framework as a Selective and Sensitive Luminescent Probe for Fe(iiI) and Chromate Ions

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INORGANIC CHEMISTRY 2020年第13期59卷 8818-8826页

作者： Rath, Bibhuti Bhusan Vittal, Jagadese J. Natl Univ Singapore Dept Chem Singapore 117543 Singapore

Sensing and monitoring toxic contaminants like Fe3+, CrO42-, and Cr2O72- ions in water is very important due to their harmful effects on biological and environmental systems. Enhanced hydrolytic stability, sensitivity, and selectivity, in addition to their excellent luminescence properties, are important attributes of metal-organic framework (MOF)-based sensors for sensing applications. In this work, the water stable Zn-MOF [Zn-2(tpeb)(bpdc)(2)] (where tpeb = 1,3,5-tri-4-pyridyl-1,2-ethenylbenzene and bpdc = biphenyl-4,4'-dicarboxylic acid) was synthesized and characterized. The framework retains its crystallinity and structural integrity in harsh acidic and basic conditions (pH 4-11). Most interestingly, the Zn-MOF demonstrates a strong blue luminescence in water that can be quenched selectively only by contaminants like Fe3+, CrO42-, and Cr2O72- ions. Higher K-sv values and low detection limits in selective luminescence quenching confirm the superior sensing performance, which is comparable to those of contemporary materials. Furthermore, in all cases, quenching efficiency remains unaltered in the presence of interfering ions, even after the compound is used in multiple cycles, which makes this MOF an attractive, reliable, and recyclable luminescent sensor material. The luminescence quenching mechanism is based on the competitive absorption and weak interactions. It is worth noting that most of the reported MOF-based sensors used for the separate sensing of Fe(iiI) and chromate ions are used in organic media due to their poor hydrolytic stabilities. Reports on the dual sensing of Fe(iiI) and chromate ions, which are also in aqueous media, are rare. Based on these results, Zn-MOF can be considered as a suitable candidate for advanced practical applications for the efficient sensing of Fe(iiI) and chromate ions in water.

关键词： Luminescence Anions Ions Metal organic frameworks Quenching

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Few-Shot Human Activity Recognition on Noisy Wearable sensor Data 25th

Few-Shot Human Activity Recognition on Noisy Wearable Sensor...

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25th International Conference on Database systems for advanced applications (DASFAA)

作者： Deng, Shizhuo Hua, Wen Wang, Botao Wang, Guoren Zhou, Xiaofang Northeastern Univ Sch Comp Sci & Engn Shenyang Peoples R China Univ Queensland Sch ITEE Brisbane Qld Australia Beijing Inst Technol Sch Comp Sci & Technol Beijing Peoples R China

ISBN: (纸本)9783030594152;9783030594169

Most existing wearable sensor-based human activity recognition (HAR) models are trained on substantial labeled data. It is difficult for HAR to learn new-class activities unseen during training from a few samples. Very few researches of few-shot learning (FSL) have been done in HAR to address the above problem, though FSL has been widely used in computer vision tasks. Besides, it is impractical to annotate sensor data with accurate activity labels in real-life applications. The noisy labels have great negative effects on FSL due to the limited samples. The weakly supervised few-shot learning in HAR is challenging, significant but rarely researched in existing literature. In this paper, we propose an end-to-end Weakly supervised Prototypical Networks (WPN) to learn more latent information from noisy data with multiple instance learning (MIL). In MIL, the noisy instances (subsequences of segmentation) have different labels from the bag's (segmentation's) label. The prototype is the center of the instances in WPN rather than less discriminative bags, which determines the bag-level classification accuracy. To get the most representative instance-level prototype, we propose two strategies to refine the prototype by selecting high-probability instances same as their bag's label iteratively based on the distance-metric. The model is trained by minimizing the instance-level loss function and infers the final bag-level labels from instance-level labels. In the experiments, our proposals outperform existing approaches and achieve higher average ranks.

关键词： Few-shot learning Weakly supervised models Wearable sensors Human activity recognition

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Data compression mechanisms in an intelligent E-health gateway for medical monitoring applications 17

Data compression mechanisms in an intelligent E-health gatew...

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17th International Conference on Mobile systems and Pervasive Computing, MobiSPC 2020

作者： Hanoune, Mostafa Lysmos, Mezui Eya'a Guy Dept. of Computer Science University Hassan II of Casablanca Faculty of the Sciences Ben M'Sik Av Driss El Harti B.P 7955 Sidi Othmane Casablanca Morocco

In this article, we present data Compression mechanisms in an intelligent E-Health gateway for medical monitoring applications, to improve the collection and processing of data in the context of medical surveillance. These mechanisms, will not only optimize the data storage space required by the gateway, but also to accelerate the processing of the data flow for the fast and lossless transfer of data on the WSN (Wireless sensor Network) and WLAN (Wireless Local Area Network) networks. In addition, all of the modern data compression mechanisms presented in this article are the following: Forecast compression, Sampling compression, Scheduling compression, distributed compression. We apply some formats of lossless data compression algorithms to these mechanisms (LZ4, LZO and Bzip2), to establish a comparative study between mechanisms using metric parameters. The implementation of these mechanisms in the smart gateway highlights an advanced Internet of Things data processing system for health and medical surveillance, based on a comprehensive and efficient study of advanced data compression techniques. © 2020 The Authors.

关键词： Internet of things

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