Early Detection of Aphid Infestation and Insect-Plant Interaction Assessment in Wheat Using a Low-Cost Electronic Nose (E-Nose), Near-Infrared Spectroscopy and Machine Learning Modeling.

Advances in early insect detection have been reported using digital technologies through camera systems, sensor networks, and remote sensing coupled with machine learning (ML) modeling. However, up to date, there is no cost-effective system to monitor insect presence accurately and insect-plant interactions. This paper presents results on the implementation of near-infrared spectroscopy (NIR) and a low-cost electronic nose (e-nose) coupled with machine learning. Several artificial neural network (ANN) models were developed based on classification to detect the level of infestation and regression to predict insect numbers for both e-nose and NIR inputs, and plant physiological response based on e-nose to predict photosynthesis rate (A), transpiration (E) and stomatal conductance (gs). Results showed high accuracy for classification models ranging within 96.5-99.3% for NIR and between 94.2-99.2% using e-nose data as inputs. For regression models, high correlation coefficients were obtained for physiological parameters (gs, E and A) using e-nose data from all samples as inputs (R = 0.86) and R = 0.94 considering only control plants (no insect presence). Finally, R = 0.97 for NIR and R = 0.99 for e-nose data as inputs were obtained to predict number of insects. Performances for all models developed showed no signs of overfitting. In this paper, a field-based system using unmanned aerial vehicles with the e-nose as payload was proposed and described for deployment of ML models to aid growers in pest management practices.

Assessment of Smoke Contamination in Grapevine Berries and Taint in Wines Due to Bushfires Using a Low-Cost E-Nose and an Artificial Intelligence Approach.

Bushfires are increasing in number and intensity due to climate change. A newly developed low-cost electronic nose (e-nose) was tested on wines made from grapevines exposed to smoke in field trials. E-nose readings were obtained from wines from five experimental treatments: (i) low-density smoke exposure (LS), (ii) high-density smoke exposure (HS), (iii) high-density smoke exposure with in-canopy misting (HSM), and two controls: (iv) control (C; no smoke treatment) and (v) control with in-canopy misting (CM; no smoke treatment). These e-nose readings were used as inputs for machine learning algorithms to obtain a classification model, with treatments as targets and seven neurons, with 97% accuracy in the classification of 300 samples into treatments as targets (Model 1). Models 2 to 4 used 10 neurons, with 20 glycoconjugates and 10 volatile phenols as targets, measured: in berries one hour after smoke (Model 2; R = 0.98; R2 = 0.95; b = 0.97); in berries at harvest (Model 3; R = 0.99; R2 = 0.97; b = 0.96); in wines (Model 4; R = 0.99; R2 = 0.98; b = 0.98). Model 5 was based on the intensity of 12 wine descriptors determined via a consumer sensory test (Model 5; R = 0.98; R2 = 0.96; b = 0.97). These models could be used by winemakers to assess near real-time smoke contamination levels and to implement amelioration strategies to minimize smoke taint in wines following bushfires.

A multifunctional smart field-programmable radio frequency surface.

Antennas that can operate across multiple communication standards have remained a challenge. To address these limitations, we propose a Field-Programmable Radio Frequency Surface (FPRFS), which is based on manipulating current flow on its surface to achieve desirable RF characteristics. In this work, we demonstrate that substantial enhancements in radiation efficiency can be achieved while preserving the high reconfigurability of antenna structures implemented on the FPRFS. This is accomplished by utilizing an asymmetric excitation, directing the excitation to the low-loss contiguous surface, and dynamically manipulating the imaged return current on a segmented ground plane by switches. This important insight allows for adaptable antenna performance that weakly depends on the number of RF switches or their loss. We experimentally validate that FPRFS antennas can achieve efficiencies comparable to traditionally implemented antenna counterparts. This permits the FPRFS to be effectively utilized as a productive antenna and impedance-matching network with real-time reconfigurability.

Wearable Transmitter Coil Design for Inductive Wireless Power Transfer to Implantable Devices.

Wireless endovascular sensors and stimulators are emerging biomedical technologies for applications such as endovascular pressure monitoring, hyperthermia, and neural stimulations. Recently, coil-shaped stents have been proposed for inductive power transfer to endovascular devices using the stent as a receiver. However, less work has been done on the external transmitter components, so the maximum power transferable remains unknown. In this work, we design and evaluate a wearable transmitter coil that allows 50 mW power transfer in simulation.Clinical Relevance-This allows more accurate measurements and precise control of endovascular devices.

Thermal denaturation of proteins in the muscle fibre and connective tissue from bovine muscles composed of type I (masseter) or type II (cutaneous trunci) fibres: DSC and FTIR microspectroscopy study.

The changes in secondary structure of proteins with heating were characterised and compared for bovine masseter (fibre type I) and cutaneous trunci (fibre type II) muscles by Differential Scanning Calorimetry (DSC) and Fourier Transform InfraRed (FTIR) microspectroscopy. Heating led to a decrease in α- helices, and an increase in aggregated strands, random coils and aromatic side chains in the muscle fibres of both muscles. In the intramuscular connective tissue (IMCT) of both muscles, a decrease in α- helix, turn and unordered structures was complemented with an increase in aggregated strands. At temperatures < 60 °C, the greater thermal denaturation of proteins in cutaneous trunci than in masseter (FTIR), supported by a myosin associated peak at 55.8 °C for cutaneous trunci and no peak for masseter (DSC), indicates that myosin in type II fibres is more sensitive to thermal denaturation than myosin in type I fibres and this should be considered in thermal meat processing.