Comparison of verticality perception and postural sway induced by double temple-mastoidal and bipolar binaural 20 Hz sinusoidal galvanic vestibular stimulation

BACKGROUND: Galvanic vestibular stimulation (GVS) is believed to be one of the most valuable tools for studying the vestibular system. In our opinion, its combined effect on posture and perception needs to be examined more. OBJECTIVE: The present study was conducted to investigate the effect of a 20 Hz sinusoidal Galvanic Vestibular Stimulation (sGVS) on the body sway and subjective visual vertical (SVV) deviation through two sets of electrode montages (bipolar binaural and double temple-mastoidal stimulation) during a three-stage experiment (baseline, threshold, and supra-threshold levels). METHODS: While the individuals (32 normal individuals, 10 males, the mean age of 25.37±3.00 years) were standing on a posturography device and SVV goggles were put on, the parameters of the body sway and SVV deviation were measured simultaneously. Following the baseline stage (measuring without stimulation), the parameters were investigated during the threshold and supra-threshold stages (1 mA above the threshold) for 20 seconds. This was done separately for each electrode montage. Then, the results were compared between the three experimental stages and the two electrode montages. RESULTS: In both electrode montages, “the maximum amplitude” of the mediolateral (ML) and anteroposterior (AP) body sway decreased and increased in the threshold and supra-threshold stages, respectively, compared to the baseline stage. Comparison of the amount of “amplitude change” caused by each electrode montages showed that the double temple-mastoidal stimulation induced a significantly greater amplitude change in body sway during both threshold and supra-threshold stages (relative to the baseline stage). The absolute mean values of the SVV deviation were significantly different between the baseline and supra-threshold levels in both electrode montages. The SVV deviation in double temple-mastoidal stimulation was a bit greater than that in the bipolar binaural stimulation. CONCLUSION: Double temple-mastoidal stimulation has induced greater amount of change in the body sway and SVV deviation. This may be due to the more effective stimulation of the otoliths than semicircular canals.

Microstructural Properties of Human Brain Revealed by Fractional Anisotropy can Predict the After-effect of Intermittent Theta Burst Stimulation

Intermittent theta burst stimulation (iTBS) delivered by transcranial magnetic stimulation (TMS) produces a long term potentiation (LTP)-like after-effect useful for investigations of cortical function and of potential therapeutic value. However, the iTBS-evoked after-effect over the primary motor cortex (M1) as measured by changes in motor evoked potential (MEP) amplitude exhibits a largely unexplained variability across individuals. Here, we present evidence that individual differences in white and grey matter microstructural properties revealed by fractional anisotropy (FA) predict the magnitude of the iTBS-induced after-effect over M1. The MEP amplitude change in the early phase (5–10 min) post-iTBS was associated with FA values in white matter tracts such as right superior longitudinal fasciculus and corpus callosum. In contrast, the MEP amplitude change in the late phase (15–30 min) post-iTBS was associated with FA in grey matter, primarily in right frontal cortex. These results suggest that the microstructural properties of regions connected directly or indirectly to the target region (M1) are crucial determinants of the iTBS after-effect. FA values indicative of these microstructural differences can predict the potential effectiveness of rTMS for both investigational use and clinical application.

The source of uncertainty in projecting the anomalous western North Pacific anticyclone during El Niño–decaying summers

The western North Pacific anomalous anticyclone (WNPAC) is a key bridge that links El Niño and East Asian climate variability. Future projections of ENSO-related WNPAC changes under global warming are highly uncertain across climate models. Based on a 40-member ensemble from the Community Earth System Model Large Ensemble (CESM-LE) project, we investigate the effects of internal variability on the El Niño-related WNPAC projection. Here, we first develop a decomposition method to separate the contributions of El Niño amplitude change and non-amplitude change from the leading uncertainty in the El Niño-related WNPAC projection. Based on the decomposition, approximately 23% of the uncertainty in the El Niño-related WNPAC projection is attributed to the El Niño amplitude change, while the remaining 77% is from the non-amplitude change, which is mainly related to the change in the El Niño decaying pace. A larger (smaller) El Niño amplitude can enhance (weaken) the WNPAC through a stronger (weaker) tropical Indian Ocean (TIO) capacitor effect. For non-amplitude change, a faster (slower) El Niño decaying pace can also enhance (weaken) the WNPAC through descending Rossby waves in response to cold sea surface temperature anomalies (SSTA) over the tropical central-eastern Pacific. The decomposition method can be generalized to investigate the sources of uncertainty related to El Niño properties in climate projections and to help improve the understanding of changes in the interannual variability of East Asian-western Pacific climate under global warming.

Uncertainty of ENSO-amplitude projections in CMIP5 and CMIP6 models

There is a long-standing debate on how the El Niño/Southern Oscillation (ENSO) amplitude may change during the twenty-first century in response to global warming. Here we identify the sources of uncertainty in the ENSO amplitude projections in models participating in the Coupled Model Intercomparison Phase 5 (CMIP5) and Phase 6 (CMIP6), and quantify scenario uncertainty, model uncertainty and uncertainty due to internal variability. The model projections exhibit a large spread, ranging from increasing standard deviation of up to 0.6 °C to diminishing standard deviation of up to − 0.4 °C by the end of the twenty-first century. The ensemble-mean ENSO amplitude change is close to zero. Internal variability is the main contributor to the uncertainty during the first three decades; model uncertainty dominates thereafter, while scenario uncertainty is relatively small throughout the twenty-first century. The total uncertainty increases from CMIP5 to CMIP6: while model uncertainty is reduced, scenario uncertainty is considerably increased. The models with “realistic” ENSO dynamics have been analyzed separately and categorized into models with too small, moderate and too large ENSO amplitude in comparison to instrumental observations. The smallest uncertainties are observed in the sub-ensemble exhibiting realistic ENSO dynamics and moderate ENSO amplitude. However, the global warming signal in ENSO-amplitude change is undetectable in all sub-ensembles. The zonal wind-SST feedback is identified as an important factor determining ENSO amplitude change: global warming signal in ENSO amplitude and zonal wind-SST feedback strength are highly correlated across the CMIP5 and CMIP6 models.

A Novel Method for Sea-Land Clutter Separation Using Regularized Randomized and Kernel Ridge Neural Networks

Classification of clutter, especially in the context of shore based radars, plays a crucial role in several applications. However, the task of distinguishing and classifying the sea clutter from land clutter has been historically performed using clutter models and/or coastal maps. In this paper, we propose two machine learning, particularly neural network, based approaches for sea-land clutter separation, namely the regularized randomized neural network (RRNN) and the kernel ridge regression neural network (KRR). We use a number of features, such as energy variation, discrete signal amplitude change frequency, autocorrelation performance, and other statistical characteristics of the respective clutter distributions, to improve the performance of the classification. Our evaluation based on a unique mixed dataset, which is comprised of partially synthetic clutter data for land and real clutter data from sea, offers improved classification accuracy. More specifically, the RRNN and KRR methods offer 98.50% and 98.75% accuracy, outperforming the conventional support vector machine and extreme learning based solutions.

Fiber Optic Refractive Index Sensors Based on a Ball Resonator and Optical Backscatter Interrogation

In this work, we introduced fabrication and interrogation of simple and highly sensitive fiber-optic refractive index (RI) sensors based on ball resonators built on the tip of single-mode fibers. The probes have been fabricated through a CO2 fiber splicer, with a fast (~600 s) and repeatable method. The ball resonator acted as a weak interferometer with a return loss below −50 dB and was interrogated with an optical backscatter reflectometer measuring the reflection spectrum. The ball resonators behaved as weak interferometers with a shallow fringe and a spectrum that appeared close to a random signal, and RI sensitivity could be measured either through wavelength shift or amplitude change. In this work, we reported four samples having sensitivity ranges 48.9–403.3 nm/RIU and 256.0–566.2 dB/RIU (RIU = refractive index unit). Ball resonators appeared as a sensitive and robust platform for RI sensing in liquid and can be further functionalized for biosensing.

Magnetorheological Elastomer Stress Relaxation Behaviour during Compression: Experiment and Modelling

Materials characterized by magnetorheological properties are non-classic engineering materials. A significant increase in the interest of the scientific community about this group of materials could be observed over the recent years. The results of research presented in this article are oriented on the examination of the said materials’ mechanical properties. Stress relaxation tests were carried out on cylindrical samples of magnetorheological elastomers loaded with compressive stress, for various values of magnetic induction (B1 = 0 mT, B2 = 32 mT, B3 = 48 mT, and B4 = 64 mT) and temperature (T1 = 25 °C, T2 = 30 °C, and T3 = 40 °C). The results of these tests indicate that the stiffness of the examined samples increased along with the increase of magnetic field induction, and decreased along with the increase of temperature. On this basis, it has been determined that: the biggest stress amplitude change, caused by the influence of magnetic field, was σ0ΔB = 12.7%, and the biggest stress amplitude change, caused by the influence of temperature, was σ0ΔT = 11.3%. As a result of applying a mathematical model, it was indicated that the stress relaxation in the examined magnetorheological elastomer, for the adopted time range (t = 3600 s), had a hyperbolic decline nature. The collected test results point to the examined materials being characterized by extensive rheological properties, which leads to the conclusion that it is necessary to conduct further tests in this area.