Use of a multi-sensor approach can provide citizens with holistic insights into the air quality of their immediate surroundings and their personal exposure to urban stressors. Our work, as part of the ICARUS H2020 project, which included over 600 participants from seven European cities, discusses the data fusion and harmonization of a diverse set of multi-sensor data streams to provide a comprehensive and understandable report for participants. Harmonizing the data streams identified issues with the sensor devices and protocols, such as non-uniform timestamps, data gaps, difficult data retrieval from commercial devices, and coarse activity data logging. Our process of data fusion and harmonization allowed us to automate visualizations and reports, and consequently provide each participant with a detailed individualized report. Results showed that a key solution was to streamline the code and speed up the process, which necessitated certain compromises in visualizing the data. A thought-out process of data fusion and harmonization of a diverse set of multi-sensor data streams considerably improved the quality and quantity of distilled data that a research participant received. Though automation considerably accelerated the production of the reports, manual and structured double checks are strongly recommended.

• Klíčová slova
• air quality, data fusion, data treatment, data visualization, exposure assessment, multi-sensor, participant reports,
• MeSH
• lidé MeSH
• ukládání a vyhledávání informací MeSH
• velkoměsta MeSH
• znečištění ovzduší * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Geografické názvy
• velkoměsta MeSH

Wireless Sensor Networks (WSNs) can be defined as a cluster of sensors with a restricted power supply deployed in a specific area to gather environmental data. One of the most challenging areas of research is to design energy-efficient data gathering algorithms in large-scale WSNs, as each sensor node, in general, has limited energy resources. Literature review shows that with regards to energy saving, clustering-based techniques for data gathering are quite effective. Moreover, cluster head (CH) optimization is a non-deterministic polynomial (NP) hard problem. Both the lifespan of the network and its energy efficiency are improved by choosing the optimal path in routing. The technique put forth in this paper is based on multi swarm optimization (MSO) (i.e., multi-PSO) together with Tabu search (TS) techniques. Efficient CHs are chosen by the proposed system, which increases the optimization of routing and life of the network. The obtained results show that the MSO-Tabu approach has a 14%, 5%, 11%, and 4% higher number of clusters and a 20%, 6%, 14%, and 6% lesser average packet loss rate as compared to a genetic algorithm (GA), differential evolution (DE), Tabu, and MSO based clustering, respectively. Moreover, the MSO-Tabu approach has 136%, 36%, 136%, and 38% higher lifetime computation, and 22%, 16%, 51%, and 12% higher average dissipated energy. Thus, the study's outcome shows that the proposed MSO-Tabu is efficient, as it enhances the number of clusters formed, average energy dissipated, lifetime computation, and there is a decrease in mean packet loss and end-to-end delay.

• Klíčová slova
• cluster head (CH), energy consumption, metaheuristics, particle swarm optimization (PSO), wireless energy transfer,
• Publikační typ
• časopisecké články MeSH

Automatic detection of low-magnitude earthquakes has become an increasingly important research topic in recent years due to a sharp increase in induced seismicity around the globe. The detection of low-magnitude seismic events is essential for microseismic monitoring of hydraulic fracturing, carbon capture and storage, and geothermal operations for hazard detection and mitigation. Moreover, the detection of micro-earthquakes is crucial to understanding the underlying mechanisms of larger earthquakes. Various algorithms, including deep learning methods, have been proposed over the years to detect such low-magnitude events. However, there is still a need for improving the robustness of these methods in discriminating between local sources of noise and weak seismic events. In this study, we propose a convolutional neural network (CNN) to detect seismic events from shallow borehole stations in Groningen, the Netherlands. We train a CNN model to detect low-magnitude earthquakes, harnessing the multi-level sensor configuration of the G-network in Groningen. Each G-network station consists of four geophones at depths of 50, 100, 150, and 200 m. Unlike prior deep learning approaches that use 3-component seismic records only at a single sensor level, we use records from the entire borehole as one training example. This allows us to train the CNN model using moveout patterns of the energy traveling across the borehole sensors to discriminate between events originating in the subsurface and local noise arriving from the surface. We compare the prediction accuracy of our trained CNN model to that of the STA/LTA and template matching algorithms on a two-month continuous record. We demonstrate that the CNN model shows significantly better performance than STA/LTA and template matching in detecting new events missing from the catalog and minimizing false detections. Moreover, we find that using the moveout feature allows us to effectively train our CNN model using only a fraction of the data that would be needed otherwise, saving plenty of manual labor in preparing training labels. The proposed approach can be easily applied to other microseismic monitoring networks with multi-level sensors.

• Klíčová slova
• convolutional neural networks, deep learning, induced seismicity, micro-earthquakes,
• MeSH
• algoritmy MeSH
• deep learning * MeSH
• hluk MeSH
• neuronové sítě MeSH
• zemětřesení * MeSH
• Publikační typ
• časopisecké články MeSH

Using low-cost portable air quality (AQ) monitoring devices is a growing trend in personal exposure studies, enabling a higher spatio-temporal resolution and identifying acute exposure to high concentrations. Comprehension of the results by participants is not guaranteed in exposure studies. However, information on personal exposure is multiplex, which calls for participant involvement in information design to maximise communication output and comprehension. This study describes and proposes a model of a user-centred design (UCD) approach for preparing a final report for participants involved in a multi-sensor personal exposure monitoring study performed in seven cities within the EU Horizon 2020 ICARUS project. Using a combination of human-centred design (HCD), human-information interaction (HII) and design thinking approaches, we iteratively included participants in the framing and design of the final report. User needs were mapped using a survey (n = 82), and feedback on the draft report was obtained from a focus group (n = 5). User requirements were assessed and validated using a post-campaign survey (n = 31). The UCD research was conducted amongst participants in Ljubljana, Slovenia, and the results report was distributed among the participating cities across Europe. The feedback made it clear that the final report was well-received and helped participants better understand the influence of individual behaviours on personal exposure to air pollution.

• Klíčová slova
• air pollution exposure campaign, communication, design thinking, focus group, report to participants, user-centred design,
• MeSH
• látky znečišťující vzduch * analýza   MeSH
• lidé MeSH
• monitorování životního prostředí MeSH
• velkoměsta MeSH
• vystavení vlivu životního prostředí analýza   MeSH
• znečištění ovzduší * analýza   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Geografické názvy
• Evropa MeSH
• velkoměsta MeSH
• Názvy látek
• látky znečišťující vzduch * MeSH

A novel π-electron rich fluoranthene embellished with a phenyl spacer and coupled with terpyridine (TS1) was developed through Diels-Alder reaction. Single crystal X-ray structure evidences the variations in dihedral angles between the fluoranthene and the phenyl unit responsible for development of non-coplanar interactions and stabilized by a wave-like molecular packing in the crystal lattice with weak π-π interaction of 4.125 Å. The peripheral terpyridine of TS1 endows an efficient binding with multiple metal ions by colorimetric and fluorometric methods. TS1 exhibits a ratiometric fluorescence response from sky blue to yellow colour upon the addition of Zn2+ ions with a limit of detection (LOD) of 0.05 ppm. The other metal ions such as Cu2+, Co2+ and Fe2+ demonstrate fluorescence quenching behaviour with LODs of 0.1, 0.3 and 0.7 ppm, respectively. The intramolecular charge transfer (ICT) shows the variation in TS1 emission behaviour upon metal ions interaction and quantitatively discriminates the metal ion concentrations. TS1 conferred a visual colorimetric change from colourless to magenta, enabling naked-eye detection of Fe2+ and showing clear discrimination between Fe2+ and Fe3+ ions for the real-time water samples. Furthermore, we have investigated the effect of TS1 in Zebrafish larvae/embryos and cytotoxicity in human urinary tract transitional cell carcinoma cells (UM-UC-3).

• Klíčová slova
• Emission, Fluoranthene, Intramolecular charge transfer (ICT), Multi-metal detection, Quenching, Ratiometric, Zebrafish,
• MeSH
• dánio pruhované * MeSH
• fluoreny toxicita   MeSH
• fluorescenční barviva toxicita   chemie   MeSH
• ionty chemie   MeSH
• kovy * chemie   MeSH
• lidé MeSH
• zvířata MeSH
• Check Tag
• lidé MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• fluoranthene MeSH Prohlížeč
• fluoreny MeSH
• fluorescenční barviva MeSH
• ionty MeSH
• kovy * MeSH

In this paper, we evaluate the secrecy performance of multi-hop cognitive wireless sensor networks (WSNs). In the secondary network, a source transmits its data to a destination via the multi-hop relaying model using the transmit antenna selection (TAS)/selection combining (SC) technique at each hop, in the presence of an eavesdropper who wants to receive the data illegally. The secondary transmitters, including the source and intermediate relays, have to harvest energy from radio-frequency signals of a power beacon for transmitting the source data. Moreover, their transmit power must be adjusted to satisfy the quality of service (QoS) of the primary network. Under the joint impact of hardware imperfection and interference constraint, expressions for the transmit power for the secondary transmitters are derived. We also derive exact and asymptotic expressions of secrecy outage probability (SOP) and probability of non-zero secrecy capacity (PNSC) for the proposed protocol over Rayleigh fading channel. The derivations are then verified by Monte Carlo simulations.

• Klíčová slova
• cognitive radio, energy harvesting, hardware impairments, multi-hop wireless sensor networks, physical-layer security, selection combining, transmit antenna selection,
• Publikační typ
• časopisecké články MeSH

In this work we discuss a new label-free biosensing device based on indium tin oxide (ITO) overlaid section of a multimode optical fiber fused silica core. The sensor has been used to optical measurements also simultaneously interrogated electrochemically (EC). Due to optimized thickness and optical properties of ITO film, a lossy-mode resonance (LMR) could be observed in the optical domain, where electrical properties of the film allowed for application of the sensor as a working electrode in an EC setup. It has been confirmed that the LMR response depends on optical properties of the external medium, as well as potential applied to the electrode during cyclic voltammetry. After the ITO surface functionalization with amine groups and covalently attached biotin, the device has been applied for label-free biosensing of avidin in both the domains simultaneously. On the example of biotin-avidin detection system it was demonstrated that when avidin concentration increases a decrease in current and increase in LMR wavelength shift were recorded in EC and optical domain, respectively. Both optical and EC responses follow the protein interaction process, and thus can be used as cross-verification of the readouts. Moreover, an extended information has been achieved comparing to solely EC interrogation, i.e., the grafting process of biotin and avidin was directly monitored optically displaying individual steps of an incubation procedure.

• Klíčová slova
• Electrochemistry, Indium tin oxide (ITO), Label-free biosensing, Lossy-mode resonance, Multi-domain sensing, Optical fiber sensor, Thin film,
• MeSH
• avidin chemie   izolace a purifikace   MeSH
• biosenzitivní techniky * MeSH
• biotin chemie   izolace a purifikace   MeSH
• elektrochemické techniky * MeSH
• elektrody MeSH
• optika a fotonika MeSH
• sloučeniny cínu chemie   MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• avidin MeSH
• biotin MeSH
• indium tin oxide MeSH Prohlížeč
• sloučeniny cínu MeSH

Surface plasmon resonance (SPR) biosensors are affinity sensing devices exploiting a special mode of electromagnetic field-surface plasmon-polariton-to detect the binding of analyte molecules from a liquid sample to biomolecular recognition elements immobilized on the surface of the sensor. In this paper, we review advances of SPR biosensor technology towards detection systems for the simultaneous detection of multiple analytes (multi-analyte detection). In addition, we report application of a recently developed multichannel SPR sensor based on spectroscopy of surface plasmons and wavelength division multiplexing of sensing channels to multi-analyte detection.

• MeSH
• biosenzitivní techniky metody   MeSH
• povrchová plasmonová rezonance * MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• přehledy MeSH

Underwater wireless sensor networks are currently seeing broad research in various applications for human benefits. Large numbers of sensor nodes are being deployed in rivers and oceans to monitor the underwater environment. In the paper, we propose an energy-efficient clustering multi-hop routing protocol (EECMR) which can balance the energy consumption of these nodes and increase their network lifetime. The network area is divided into layers with regard to the depth level. The data sensed by the nodes are transmitted to a sink via a multi-hop routing path. The cluster head is selected according to the depth of the node and its residual energy. To transmit data from the node to the sink, the cluster head aggregates the data packet of all cluster members and then forwards them to the upper layer of the sink node. The simulation results show that EECMR is effective in terms of network lifetime and the nodes' energy consumption.

• Klíčová slova
• clustering, depth-based routing, energy-efficient, underwater wireless sensor network,
• Publikační typ
• časopisecké články MeSH

The cluster technique involves the creation of clusters and the selection of a cluster head (CH), which connects sensor nodes, known as cluster members (CM), to the CH. The CH receives data from the CM and collects data from sensor nodes, removing unnecessary data to conserve energy. It compresses the data and transmits them to base stations through multi-hop to reduce network load. Since CMs only communicate with their CH and have a limited range, they avoid redundant information. However, the CH's routing, compression, and aggregation functions consume power quickly compared to other protocols, like TPGF, LQEAR, MPRM, and P-LQCLR. To address energy usage in wireless sensor networks (WSNs), heterogeneous high-power nodes (HPN) are used to balance energy consumption. CHs close to the base station require effective algorithms for improvement. The cluster-based glow-worm optimization technique utilizes random clustering, distributed cluster leader selection, and link-based routing. The cluster head routes data to the next group leader, balancing energy utilization in the WSN. This algorithm reduces energy consumption through multi-hop communication, cluster construction, and cluster head election. The glow-worm optimization technique allows for faster convergence and improved multi-parameter selection. By combining these methods, a new routing scheme is proposed to extend the network's lifetime and balance energy in various environments. However, the proposed model consumes more energy than TPGF, and other protocols for packets with 0 or 1 retransmission count in a 260-node network. This is mainly due to the short INFO packets during the neighbor discovery period and the increased hop count of the proposed derived pathways. Herein, simulations are conducted to evaluate the technique's throughput and energy efficiency.

• Klíčová slova
• cluster head, glow-worm, multi-parameters, optimization and heterogeneous, retransmission ratio,
• Publikační typ
• časopisecké články MeSH