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Recently graphene and other 2D materials were suggested as nano additives to enhance the performance of nanolubricants and reducing friction and wear-related failures in moving mechanical parts. Nevertheless, to our knowledge there are no previous studies on electrochemical exfoliated nanomaterials as lubricant additives. In this work, engine oil-based nanolubricants were developed via two-steps method using two different 2D nanomaterials a carbon-based nano additive, graphene nanoplatelets (GNP) and a sulphide nanomaterial, molybdenum disulfide (MoS2) nanoplatelets (MSNP). The influence of these nano additives on the thermophysical properties of the nanolubricants, such as viscosity index, density and wettability, was investigated. The unique features of the electrochemical exfoliated GNP and MSNP allow the formulation of nanolubricant with unusual thermophysical properties. Both the viscosity and density of the nanolubricants decreased by increasing the nanoplatelets loading. The effect of the nano additives loading and temperature on the tribological properties of nanolubricants was investigated using two different test configurations reciprocating ball-on-plate and rotational ball-on-three-pins. The tribological specimens were analysed by scanning electron microscopy (SEM) and 3D profiler in order to evaluate the wear. The results showed significant improvement in the antifriction and anti-wear properties, for the 2D-materials-based nanolubricants as compared with the engine oil, using different contact conditions. For the reciprocal friction tests, maximum friction and worn area reductions of 20% and 22% were achieved for the concentrations of 0.10 wt% and 0.20 wt% GNP, respectively. Besides, the best anti-wear performance was found for the nanolubricant containing 0.05 wt% MSNP in rotational configuration test, with reductions of 42% and 60% in the scar width and depth, respectively, with respect to the engine oil.Two-dimensional layered metal chalcogenides (LMCs) are widely used in battery anode materials, energy conversion, and semiconductor devices, because of their high energy storage characteristics, high thermoelectric characteristics, and large electron mobility. SnSe2 as a kind of LMC has strong nonlinear optical characteristics. However, its research on dissipative system dynamics as a saturable absorber has not been studied. In this work, we obtained SnSe2 nanosheets using lithium ion intercalation and we reported a passively mode-locked fiber laser with SnSe2 as a saturable absorber to achieve the dissipative soliton in a dissipative system. Due to the high third-order nonlinearity of SnSe2, the evolution of square wave pulses from 2 to 16 ns was obtained in a fiber ring cavity. Through adjusting the polarization state, the evolution phenomenon of soliton rain, the soliton rain phenomenon with a spectrum of dual-wavelengths, and a bound state harmonic phenomenon with a frequency of 313 MHz were obtained. Therefore, the strong nonlinear fiber laser based on SnSe2 provides a good platform for study the pulsation, explosion, rainfall and other phenomena.

Most deep neural networks (DNNs) used as brain computer interfaces (BCI) classifiers are rarely viable for more than one person and are relatively shallow compared to the state-of-the-art in the wider machine learning literature. The goal of this work is to frame these as a unified challenge and reconsider how transfer learning is used to overcome these difficulties.

We present two variations of a holistic approach to transfer learning with DNNs for BCI that rely on a deeper network called TIDNet. Our approaches use multiple subjects for training in the interest of creating a more universal classifier that is applicable for new (unseen) subjects. The first approach is purely subject-invariant and the second targets specific subjects, without loss of generality. We use five publicly accessible datasets covering a range of tasks and compare our approaches to state-of-the-art alternatives in detail.

We observe that TIDNet in conjunction with our training augmentations is more consistent when compared to sh.

TIDNet in combination with a data alignment-based training augmentation proves to be a consistent classification approach of single raw trials and can be trained even with the inclusion of corrupted trials. Our MDL strategy calls into question the intuition to fine-tune trained classifiers to new subjects, as it proves simpler and more accurate while remaining general. Furthermore, we show evidence that augmented TIDNet training makes better use of additional subjects, showing continued and greater performance improvement over shallower alternatives, indicating promise for a new subject-invariant paradigm rather than a subject-specific one.Gold nanoparticles have demonstrated significant radiosensitization of cancer treatment with x-ray radiotherapy. To understand the mechanisms at the basis of nanoparticle radiosensitization, Monte Carlo simulations are used to investigate the dose enhancement, given a certain nanoparticle concentration and distribution in the biological medium. Earlier studies have ordinarily used condensed history physics models to predict nanoscale dose enhancement with nanoparticles. This study uses Geant4-DNA complemented with novel track structure physics models to accurately describe electron interactions in gold and to calculate the dose surrounding gold nanoparticle structures at nanoscale level. The computed dose in silico due to a clinical kilovoltage beam and the presence of gold nanoparticles was related to in vitro brain cancer cell survival using the local effect model. The comparison of the simulation results with radiobiological experimental measurements shows that Geant4-DNA and local effect model can be used to predict cell survival in silico in the case of x-ray kilovoltage beams.Aquatic organisms jumping for aerial prey require high-performance propulsion, accurate aim, and trajectory control to succeed. Archer fish, capable of jumping up to twice their body length out of the water, address these considerations through multifaceted fin and body kinematics. In this study, we utilized 3D synthetic aperture particle image velocimetry to visualize the wakes of archer fish throughout the jumping process. We found that multiple modes of interaction between the anal and caudal fins occur during jump behaviors. Time-resolved volumetric measurements presented herein illustrate the hydrodynamics of each interaction mode in detail. Additionally, regardless of which fin uses and interactions were exhibited during a jump, we found similar relationships between the cumulative impulse of multiple propulsive vortices in the wake and the instantaneous ballistic momentum of the fish. Our results suggests that fin use may compensate for variations in individual kinematic events and in the aiming posture assumed prior to jumping and highlight how interactions between tailbeats and other fins help the archer fish reach necessary prey heights in a spatially- and visually-constrained environment. In the broader context of bioinspired propulsion, the archer fish exemplifies that multiple beneficial hydrodynamic interactions can be generated in a high-performance scenario using a single set of actuators.Fluorescent nuclear track detectors (FNTDs) are solid-state dosimeters used in a wide range of dosimetric and biomedical applications in research worldwide. FNTDs are a core but currently underutilized dosimetry tool in the field of radiation biology which are inherently capable of visualizing the tracks of ions used in hadron therapy. The ions that traverse the FNTD deposit their energy according to their linear energy transfer and transform colour centres to form trackspots around their trajectory. These trackspots have fluorescent properties which can be visualized by fluorescence microscopy enabling a well-defined dosimetric readout with a spatial component indicating the trajectory of individual ions. The current method used to analyse the FNTDs is laser scanning confocal microscopy (LSM). LSM enables a precise localization of track spots in x, y and z however due to the scanning of the laser spot across the sample, requires a long time for large samples. This body of work conclusively shows for the first time that the readout of the trackspots present after 0.5 Gy carbon ion irradiation in the FNTD can be captured with a widefield microscope (WF). The WF readout of the FNTD is a factor ∼10 faster, for an area 2.97 times the size making the method nearly a factor 19 faster in track acquisition than LSM. The dramatic decrease in image acquisition time in WF presents an alternative to LSM in FNTD workflows which are limited by time, such as biomedical sensors which combine FNTDs with live cell imaging.Anode materials play an important role in the performance of rechargeable batteries and have been attracting much research interest. In this work, we have investigated the electrochemical properties of two-dimensional (2D) Janus MSSe (M = Ti or V) for potential applications as anode materials in alkali metal ion batteries from density functional theory (DFT), following the recent successful synthesis of 2D Janus MoSSe. Our DFT calculations suggest that 2D Janus TiSSe and VSSe are stable in the 1T phase and 1H phase, respectively. It is found that alkali metal atoms X (X = Li, Na or K) can be stably adsorbed on the surfaces of Janus MSSe, and have low diffusion energy barriers. Additionally, small volume changes are observed in Janus MSSe after the adsorption of alkali metal atoms. It is predicted that the MSSe-2X systems have low open circuit voltages and high capacities. Our results suggest that 2D Janus TiSSe and VSSe are potential anode materials for alkali metal ion batteries.

During transcranial electrical stimulation (tES), including transcranial direct current stimulation (tDCS) and transcranial alternating current stimulation (tACS), current density concentration around the electrode edges that is predicted by simplistic skin models does not match experimental observations of erythema, heating, or other adverse events. We hypothesized that enhancing models to include skin anatomical details, would alter predicted current patterns to align with experimental observations.

We develop a high-resolution multi-layer skin model (epidermis, dermis, and fat), with or without additional ultra-structures (hair follicles, sweat glands, and blood vessels). selleck Current flow patterns across each layer and within ultra-structures were predicted using finite element methods considering a broad range of modeled tissue parameters including 78 combinations of skin layer conductivities (S m

) epidermis (standard 1.05 × 10

; range 1.05 × 10

to 0.465); dermis (standard 0.23; range 0.0023 to 23), layers.

Cochleae of long-term cochlear implant users have shown evidence of particulate platinum (Pt) corroded from the surface of Pt electrodes. The pathophysiological effect of Pt within the cochlea has not been extensively investigated. We previously evaluated the effects of Pt corrosion at high charge densities and reported negligible pathophysiological impact. The present study extends this work by examining techniques that may reduce Pt corrosion.

Deafened guinea pigs were continuously stimulated for 28 d using biphasic current pulses at extreme charge densities using (i) electrode shorting; (ii) electrode shorting with capacitive coupling (CC); or (iii) electrode shorting with alternating leading phase (AP). On completion of stimulation, cochleae were examined for corrosion product, tissue response, auditory nerve (AN) survival and trace levels of Pt; and electrodes examined for surface corrosion.

Pt corrosion was evident at ≥200 μC cm

phase

; the amount dependent on charge density (p< 0.01) and charge recovery technique (p < 0.