Staphylococcus aureus dysbiosis and the role of glycative stress

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Adapting International Immersive Education Experiences to Online Education Platforms

International study travel within the tertiary education framework provides students invaluable formative experiences. The current COVID-19 pandemic has put a halt to these excursions, side-lining the valuable learning outcomes that are specific to international immersive study opportunities. This paper explores how the benefits of these trips could be transferred to an online teaching environment. The potential to increase collaborative cultural exchange through media and technology coursework contexts will be discussed. Potential barriers are also considered. The discussion paper draws on the experiences of the authors as lecturers involved in preparing and executing study trips situated in Japan prior to the COVID-19 pandemic.textapplication/pdfdepartmental bulletin pape

High Performance of an In-Material Reservoir Computing Device Achieved by Complex Dynamics in a Nanoparticle Random Network Memristor

An in-material reservoir computing (RC) device with an Ag–Ag2S core–shell nanoparticle (NP) network is proposed. Network-wide nonlinear sine-wave outputs of higher frequencies and varying phases were produced from the different Ag+ ion diffusion rates and filament formation caused by the heterogeneous NP size in the thiol layer. Such emergent dynamics of multiple information regimes enabled the reconstruction of Fourier waves, with a maximum accuracy of 99% achieved only for trained outputs with mixed spatiotemporal complexities. Additionally, the device showed stable retrieval of past information with a two-times-step delay and successfully computed a two-step time-series prediction task with 87% accuracy.journal articl

Performance improvement of in-materio reservoir computing by noise injection

Computation performance of in-materio reservoir device was evaluated by varying intensity of noise injection. Materials for the reservoir device was synthesized using a α-Fe2O3/titanium bismuth oxide composite by using the sol–gel method. The prepared samples were characterized by conducting X-ray diffractmetry, transmission electron microscopy, and energy dispersive X-ray spectroscopy to confirm presence of α-Fe2O3, TiO2, and Bi4Ti3O12 nanoparticles. The I–V and V–t curves show nonlinearity, and phase differences between input and output signals, and the fast Fourier transform of the V–t curve showed high harmonics at the input sine wave with 11 Hz of frequency. In the waveform prediction task, the prediction accuracy was improved only when a small intensity of white noise voltage was superimposed to the input information signal.journal articl

Effect of nonlinearity induced by atomic switch in Ag/Ag2S nanoparticles on performance of in-materio reservoir computing

A random network of Ag/Ag2S nanoparticles (NPs) was used as a physical system in reservoir computing (RC) because the network has nonlinear and dynamical characteristics. Ag/Ag2S NPs were synthesized by the modified Brust–Schiffrin method. Atomic switching among the NPs caused nonlinear dynamical behavior of the random network. The Fourier transform of output signals indicated that the generated harmonics were far higher with a larger amplitude of the input sine wave because the atomic switching occurred only at high bias voltages. Higher accuracy was achieved in the Boolean logic RC task because of the nonlinearity originating from switching. These findings suggest that nonlinearity plays a fundamental role in the design and implementation of RC devices.journal articl

In-materio reservoir working at low frequencies in a Ag2S-island network

A Ag2S-island network is fabricated with surrounding electrodes to enable it to be used as a reservoir for unconventional computing. Local conductance change occurs due to the growth/shrinkage of Ag filaments from/into each Ag2S island in the reservoir. The growth/shrinkage of Ag filaments is caused by the drift of Ag+ cations in each Ag2S island, which results in a unique non-linear response as a reservoir, especially at lower frequencies. The response of the reservoir is shown to depend on the frequency and amplitude of the input signals. So as to evaluate its capability as a reservoir, logical operations were performed using the subject Ag2S-island network, with the results showing an accuracy of greater than 99%.journal articl

Integration of Wireless Power Transfer Technology With Hierarchical Multiwalled Carbon Nanotubes-Polydimethylsiloxane Piezo-Responsive Pressure Sensor for Remote Force Measurement

Integrating sensory devices with wireless power transfer technology for remote sensing (RS) requires the implementation of complex electronic circuitry and communication protocols. To overcome this challenge and remotely monitor mechanical force, we directly integrated piezo-responsive porous multiwalled carbon nanotubes (MWCNTs)/polydimethylsiloxane (PDMS) nanocomposites with a near-field wireless power transfer system. The wireless system transfers power bidirectionally between the transmitter and the sensing receiver at the resonant frequency of 13.56 MHz. The detection principle is based on the mechanical force-induced impedance changes in the receiver circuit. The modulated impedance signal is detected wirelessly at the transmitter circuit via a full-bridge rectifier and a smoothing capacitor. Furthermore, we demonstrate the wireless monitoring of finger bending and applied force using our flexible and disposable sensor without using any energy storage devices. The results suggest a response and recovery time of 400 ± 50 ms, strain sensitivity of 24.73, and pressure sensitivity of 0.98. Our approach adds a new path for disposable haptic-based sensory applications that do not require complex communication protocols in medical, robotics, and other fields.journal articl

Influence of junction resistance on spatiotemporal dynamics and reservoir computing performance arising from an SWNT/POM 3D network formed via a scaffold template technique

For scientists in numerous fields, creating a physical device that can function like the human brain is an aspiration. It is believed that we may achieve brain-like spatiotemporal information processing by fabricating an in materio reservoir computing (RC) device because of a complex random network topology with nonlinear dynamics. One of the significant drawbacks of a two-dimensional physical reservoir system is the difficulty in controlling the network density. This work reports the use of a 3D porous template as a scaffold to fabricate a three-dimensional network of a single-walled carbon nanotube polyoxometalate nanocomposite. Although the three-dimensional system exhibits better nonlinear dynamics and spatiotemporal dynamics, and higher harmonics generation than a two-dimensional system, the results suggest a correlation between a higher number of resistive junctions and reservoir performance. We show that by increasing the spatial dimension of the device, the memory capacity improves, while the scale-free network exponent (γ) remains nearly unchanged. The three-dimensional device also displays improved performance in the well-known RC benchmark task of waveform generation. This study demonstrates the impact of an additional spatial dimension, network distribution and network density on in materio RC device performance and tries to shed some light on the reason behind such behavior.journal articl

In-materio computing in random networks of carbon nanotubes complexed with chemically dynamic molecules: a review

The need for highly energy-efficient information processing has sparked a new age of material-based computational devices. Among these, random networks (RNWs) of carbon nanotubes (CNTs) complexed with other materials have been extensively investigated owing to their extraordinary characteristics. However, the heterogeneity of CNT research has made it quite challenging to comprehend the necessary features of in-materio computing in a RNW of CNTs. Herein, we systematically tackle the topic by reviewing the progress of CNT applications, from the discovery of individual CNT conduction to their recent uses in neuromorphic and unconventional (reservoir) computing. This review catalogues the extraordinary abilities of random CNT networks and their complexes used to conduct nonlinear in-materio computing tasks as well as classification tasks that may replace current energy-inefficient systems.journal articl

Performance of in-materio physical reservoir computing devices based on highly oriented semiconducting polymer thin films

Physical reservoir computing (PRC) harnesses the intrinsic nonlinear dynamics of physical systems for efficient temporal data processing, offering significant advantages in energy-efficient hardware implementation. This study explores the potential of oriented semiconducting polymer (SCP) thin films as reservoirs for PRC, focusing on two types of SCP benzo[c]cinnoline-based conjugated polymer diketopyrrolopyrrole benzo[c]cinnoline p(DPP-BZC) and regioregular poly(3-hexyl thiophene) (RR-P3HT). To enable anisotropic charge transport, uniaxially oriented thin films with edge-on molecular orientation were fabricated using the floating film transfer method. The films were electrically evaluated for anisotropic nonlinear responses, phase-shifting capabilities, and high-dimensional mapping in PRC tasks. Performance metrics, including waveform generation accuracy, were systematically investigated under varying device configurations and molecular structures. The study underscores the critical role of different conjugated polymers and their orientations in PRC performance, paving the way for developing next-generation materials for temporal signal processing and low-power intelligent hardware.journal articl