The pressure on the radio spectrum increases as more and more IoT devices are deployed, since most of them need to communicate via wireless technology. Spectrum availability and bandwidth are limited, and their shared use poses serious challenges when massive amounts of data need to be transmitted, even after the advent of 5G technology. In search of solutions, there is a growing interest in incorporating cognitive radio technologies into IoT devices [1]. A cognitive radio is a wireless transceiver that can adapt its behavior to the environment, for which the radio automatically selects the best channel in real time. The ultimate goal is the optimal and efficient use of the radio spectrum [2].

The key feature of cognitive radio devices is their spectrum sensing capability: they can detect whether a wireless channel is busy and, if so, recognize the type of modulation used in the channel. This is necessary to detect if a signal from a certain primary user, or even from an interferer, is present in the spectrum. To perform this recognition task, traditionally either matched filters or certain properties of the modulated signals, such as cyclostationarity, have been exploited [3, 4]. Furthermore, deep learning techniques have recently been reported to perform well in the categorization of radio communication signals [5].

However, the above techniques for modulated-signal recognition have high computational complexity and must be tuned or trained ‘off-line’, limiting transceivers to adapt to variations in the environment. In this communication, we will present a new algorithm for spectrum sensing and the categorization of modulated signals that has two main features: (i) it is unsupervised and can handle unforeseen situations in real-time and (ii) it is computationally simple, so that it can operate even with the limited capabilities of common IoT devices. The idea exploits properties of the L1-norm that have been explored in our previous works [6]. Experiments with real and simulated data will demonstrate the effectiveness of the proposed approach.

REFERENCES.

[1] A. Khan, M. Rehmani and A. Rachedi, “Cognitive-radio-based internet of things: Applications, architectures, spectrum related functionalities, and future research directions”, IEEE wireless communications, vol. 24, no. 3, pp. 17-25, 2017.

[2] S. Peyman and S. Haykin, “Fundamentals of cognitive radio”, John Wiley & Sons, 2017.

[3] P. Urriza, E. Rebeiz and D. Cabric, “Multiple antenna cyclostationary spectrum sensing based on the cyclic correlation significance test”, IEEE Journal of Selected Areas in Communications, vol. 31, no. 11, pp. 2185–2195, 2013.

[4] X. Zhang, R. Chai and F. Gao, “Matched filter based spectrum sensing and power level detection for cognitive radio network”, in IEEE Global Conference on Signal and Information Processing (Global SIP), Atlanta, pp. 1267–1270, Dec. 2014.

[5] T. O’Shea, T. Roy and T. Charles Clancy, "Over-the-air deep learning based radio signal classification", IEEE Journal of Selected Topics in Signal Processing, vol. 12, no.1, pp. 168-179, 2018.

[6] J. Camargo, R. Martín-Clemente, S. Hornillo-Mellado and V. Zarzoso, "L1-norm unsupervised Fukunaga-Koontz transform", Signal Processing, vol.182, 2021.

Two of the most relevant gasses correlating to honeybee colony health are likely carbon dioxide and humidity. There are a wide variety of sensors on the market for monitoring these gasses, covering a range of different sizes, prices and accuracy. The most accurate carbon dioxide sensors, at an appropriate physical size for use in honeybee hives, are based on Non-Dispersive Infra-Red (NDIR) detectors. In this work we investigate the use of two of these sensors . As molecular diffusion will severely impact the local equilibrium of any gas measurement, we investigate the most appropriate placement of the sensors by positioning them in the comb of a frame in the brood box, above a modified crown board and in the queen excluder. Both sensors also inherently provide relative humidity and temperature data. Data logging was provided by Teensy 3.5 microcontroller circuits with a current consumption low enough to allow battery deployment if required. With a temporal resolution of less than a minute and several thousands of hours of data for comparison, we present the daily and long-term trends in these important gasses in multiple honeybee colonies.

A series of MOX sensors, having CuO and CoO sensitive thick films were prepared using an eco-friendly technique (sol-gel). The sensor transducers are based on a custom made thick alumina wafer having Au or Pt interdigital electrodes (IDE) printed onto the alumina surface.

The sensing experiment took place inside a custom made ceramic sensing cell, with quartz walls, Teflon seal caps and a metallic plate with dual role: sample holder and sensor heater, due to a special electric heater insertion to insure corresponding working temperature of the sensor.

Sensor response (sensor electrical resistance variations, measured at the IDE contact pads) was recorded at different methane concentrations, using a RLC bridge having a GPIB interface linked with a computer, running custom made Labview based acquisition software.

The sensing experiment took place under lab conditions (dried target and carrier gas from gas cylinders), in a constant gas flow, with target gas concentrations in the 5-2000 ppm domain (calibrated by a mass-flow controller system or MFC) and a direct current (DC) applied to the IDE as sensor operating voltage.

Acknowledgements:

This research was funded by the Romanian National Authority for Scientific Research on Innovation, grant number PN-III-P2-2.1-PED-2019-2073.

Sensors with the electrochemically formed polymeric films as sensitive layer are of high interest in electroanalysis. Various monomers are successfully used for the sensors creation in particular compounds with phenolic moiety. Among them, natural phenolic acids and triphenylmethane dyes forming non-conductive polymeric coverages are of interest. Therefore, carbon nanomaterials are successfully applied as a platform for further electropolymerization of a suitable monomer. Phenolic acids (gallic and ellagic) and triphenylmethane dyes (thymolphthalein and aluminon) have been studied as monomers. Their potentiodynamic electropolymerization conditions (monomer concentration, supporting electrolyte type and pH, potential scan rate and range, number of cycles) on the surface of glassy carbon electrode (GCE) modified with multi- or functionalized single-walled carbon nanotubes and carbon nanofibers have been optimized. The electrode surface has been characterized with SEM, cyclic voltammetry, chronoamperometry and electrochemical impedance spectroscopy (EIS). Polymeric coverages exhibit porous structure with the shape of particles and their aggregates (folded structure with pores and channels in the case of polyaluminon) deposited on the surface of carbon nanomaterials. Modified electrodes have shown increase of the electroactive surface area and statistically significant decrease of the charge transfer resistance in comparison to bare GCE. The electrodes have shown a sensitive and selective response to different classes of the antioxidants (capsaicinoids, flavanones (hesperidin and naringin) and flavonols (rutin and quercetin)). The electrooxidation parameters of the antioxidants have been found. Under conditions of differential pulse voltammetry, the electrodes act as sensitive and selective sensors for capsaicinoids, flavanones and flavonols including possibility of the simultaneous quantification. The analytical characteristics obtained are improved vs. reported earlier for other electrochemical sensors. The practical applicability of the sensors has been demonstrated on food and plant samples. Thus, electropolymerized phenol-containing compound/carbon nanomaterial composites can be considered as a promising sensing platform in the antioxidants electroanalysis.

Essential oils are of high interest in analytical chemistry due to their bioactive properties and wide application area (in aromatherapy, medicine, and food industry). Gas chromatography with mass- spectrometric detection (GC-MS) is the golden standard in their characterization and investigations. On the other hand, the presence of volatile phenolics and terpenoids make it possible to use electrochemical methods for the characterization and screening of essential oils using antioxidant parameters in particular antioxidant capacity. Unfortunately, essential oils are fully out of consideration in modern electroanalysis from this point of view. Voltammetric behavior of essential oils (from 15 types of plant material) at the electrode modified with carboxylated multi-walled carbon nanotubes have been studied for the first time. All samples are electrochemically active in neutral medium under conditions of differential pulse voltammetry. There are well-pronounced signals on the voltammograms in the ranges of 0.0-0.75 and 0.75-1.5 V caused by electrooxidation of phenolic constituents and terpenoids, respectively that is confirmed by oxidation potential of individual standard compounds. Moreover, clear oxidation peaks for 9 essential oils are registered in the range of 0.75-1.5 V only that agrees well with GC-MS data on their major constituents. Two-step chronoamperometric method has been developed for the evaluation of the essential oils antioxidant capacity. Two anodic potentials of 0.80 and 1.4 V have been chosen for these purposes. The electrolysis steady-state is achieved at 75 s of electrolysis. The antioxidant capacity has been expressed as current consumed per 1 mL of essential oil. Screening of 37 samples of essential oils by their antioxidant capacity has been performed. The data obtained are compared to the standard antioxidant parameters (antioxidant activity towards 2,2-diphenyl-1-picrylhydrazyl and total phenolics).

Imidazoles have been explored over the past years as optical chemosensors due to their ability to coordinate with analytes. Heterocyclic molecules, are capable of providing specific binding sites, especially for ions. Consequently, a novel 2,4,5-triheteroarylimidazole was synthetized bearing indole and furyl moieties. The compound was characterized by the usual techniques, and the preliminary chemosensory ability was carried out in acetonitrile and acetonitrile/water (25:75) in the presence of ions with biological, medicinal, and environmental relevance. In aqueous medium, the new compound showed a slight enhancement of fluorescence in the presence of HSO₄^-. As for cations, it exhibited an enhancement of fluorescence with the addition of Fe²⁺, Sn²⁺, Fe³⁺ and Al³⁺ and a more pronounced quenching of fluorescence in the presence of Cu²⁺.

Polarimetric Synthetic Aperture Radar (PolSAR) data has been extensively used in earth observation for scattering-based biophysical and geophysical parameters retrieval in different thematic applications. Several spaceborne SAR satellites have been launched, and many more sensors in different frequency ranges are scheduled and are yet to be launched into space by space agencies. The increased demand for the polarimetric SAR data and the state-of-the-art sensors that are planned in future missions require assurance about the distortion-free data for accurate backscatter information retrieval. Any error in PolSAR-based backscatter information retrieval for thematic applications will give inaccurate modelled output, so the distortion-free data is an essential requirement for accurate output. Polarimetric calibration (PolCal) is essential to minimize distortions from airborne and spaceborne SAR data for scattering-based characterization of the targeted objects. The present study investigates the polarimetric distortions in the L-and S-band airborne dual-frequency SAR data. The L- and S-band airborne SAR (LS-ASAR) is a precursor mission of the spaceborne dual-frequency L- and S-band NASA ISRO Synthetic Aperture Radar (NISAR). The present work utilizes the LS-ASAR data acquired over the Rosamond Corner Reflector Array (RCRA). Five corner reflectors (CRs) of 4.8-meter side-length were oriented to measure the backscatter responses from the CRs in L-and S-band SAR data. To analyze the polarimetric distortions in the SAR data, scatterplots were plotted for co-pol and cross-pol channels of the PolSAR scattering matrix. The correlation between cross-polarimetric combinations (HV and VH) should be very high for a perfectly calibrated monostatic SAR system. A linear trend will be obtained from the scatterplot for the backscatter values of HV and VH channels of polarimetrically calibrated SAR data. The scatterplot between HV and VH channels of LS-ASAR data shows that the backscatter values of HV and VH channels are equal. The scatterplot between the HV and VH channels of the LS-ASAR data shows that the backscatter values ​​of the HV and VH channels are similar. The most efficient way to evaluate polarimetric distortions of SAR data is the analysis of polarimetric signatures of the backscatter responses for field-located corner reflectors that were mounted during SAR data acquisition. The polarimetric signature analysis of co-pol and cross-pol channels shows that the co-pol signature shows perfect behaviour. Still, the polarimetric distortions could be easily seen in the cross-pol signatures.

Piezoelectric transducers have been extensively investigated for the development of non-destructive techniques in structural health monitoring systems. Among the various techniques that have been proposed, the electromechanical impedance technique stands out for its simplicity of installation, where a piezoelectric transducer operates simultaneously as a sensor and an actuator, establishing a relationship between the electrical impedance of the transducer and the integrity of the structure. Although many studies have reported the feasibility of this technique, some practical challenges have hampered its effective application in real structures, where one of the most critical problems has been the temperature variation. In order to mitigate the temperature effects, damage indices and compensation methods have been proposed in recent years and satisfactory results have been obtained. However, these compensation methods are typically tested in laboratories using small structures with uniform temperature variation. On the other hand, large structures in real applications may be subject to irregular temperature variation. Therefore, this study aims to investigate the effects of irregular temperature variation on the impedance signatures of piezoelectric transducers and, consequently, on the feasibility of detecting structural damage. Experimental tests were performed on an aluminum plate with multiple piezoelectric transducers installed under different temperature conditions and the impedance signatures were qualitatively and quantitatively analyzed using damage indices. The results indicate that the irregular temperature variation can make some damage indices and compensation techniques unfeasible in real applications with large structures.

The development of molecular sensors for detection of metal ions is an active research field with great potential for biomedical applications. It is well-known that the exposure to mercury can lead to many health problems, including neurological disorders such as the Minamata’s disease. Furthermore, iron plays a crucial role in physiological processes, however, its abnormal levels in human tissues had been related to diabetes mellitus and neurodegenerative disease, namely, Alzheimer’s disease. Therefore, the efficient detection of these species is a timeless topic in several areas of investigation. 3-Difluoroborodipyrromethene (BODIPY) derivatives have become a cornerstone in the optical sensors field because of their advantageous features: high molar absorptivity, high quantum fluorescence yields, intense and narrow absorption/emission bands in the visible region of the electromagnetic spectrum and good photochemical stability. Moreover, the BODIPY core can be chemically modified to fine tune their optical properties and to attach suitable receptor groups selective to a particular target. Considering the above-mentioned facts as well as our research interest in BODIPY derivatives for several applications, particularly as optical chemosensors, we report herein a BODIPY fluorophore functionalized with a phenyl group at meso position for a selective response towards Fe³⁺. The chemosensing ability of the BODIPY derivative was investigated in acetonitrile in the presence of different ions, showing a selective fluorescence quenching upon Fe³⁺ interaction.

Numerous efforts have been devoted to the design of optical chemosensors for application in several research fields such as biochemistry, biomedical, food and environmental sciences. In particular, the recognition and detection of metal ions is of major interest considering their essential role in biological and environmental systems, as they may become harmful and toxic at concentrations outside of the expected normal range. BODIPY derivatives have emerged as a remarkable class of chemosensors for molecular recognition and biological fluorescent labelling. BODIPYs show notable properties, such as sharp absorption and emission patterns, high molar absorptivity, high fluorescence quantum yield and good photostability under physiological conditions. The versatile chemical modification of the BODIPY core is a notable advantage which enables not only the optimization of its photophysical characteristics but also the introduction of selective recognition sites for a greater target binding affinity. As an extension of the work developed in our research group, we report a BODIPY derivative bearing a phenyl group at meso position and a formyl group at 2-position of the BODIPY core for simultaneous colorimetric and fluorimetric detection of CN^- and F^-. The recognition behavior of the BODIPY derivative was studied in an aprotic solvent (acetonitrile) in the presence of different anions and the UV-vis and fluorescent spectroscopic titrations demonstrated a decrease in the absorption band intensity and a fluorescence quenching upon interaction with CN^- and F^-.