Oscillator Power Research Articles

Degree of multilingual engagement modulates resting state oscillatory activity across the lifespan

Multilingualism has been demonstrated to lead to a more favorable trajectory of neurocognitive aging, yet our understanding of its effect on neurocognition across the lifespan remains limited. We collected resting state EEG recordings from a sample of multilingual individuals across a wide age range. Additionally, we obtained data on participant multilingual language use patterns alongside other known lifestyle enrichment factors. Language experience was operationalized via a modified multilingual diversity (MLD) score. Generalized additive modeling was employed to examine the effects and interactions of age and MLD on resting state oscillatory power and coherence. The data suggest an independent modulatory effect of individualized multilingual engagement on age-related differences in whole brain resting state power across alpha and theta bands, and an interaction between age and MLD on resting state coherence in alpha, theta, and low beta. These results provide evidence of multilingual engagement as an independent correlational factor related to differences in resting state EEG power, consistent with the claim that multilingualism can serve as a protective factor in neurocognitive aging.

Effects of systemic inflammation on the network oscillation in the anterior cingulate cortex and cognitive behavior.

Network oscillation in the anterior cingulate cortex (ACC) plays a key role in attention, novelty detection and anxiety; however, its involvement in cognitive impairment caused by acute systemic inflammation is unclear. To investigate the acute effects of systemic inflammation on ACC network oscillation and cognitive function, we analyzed cytokine level and cognitive performance as well as network oscillation in the mouse ACC Cg1 region, within 4 hours after lipopolysaccharide (LPS, 30 μg/kg) administration. While the interleukin-6 concentration in the serum was evidently higher in LPS-treated mice, the increases in the cerebral cortex interleukin-6 did not reach statistical significance. The power of kainic acid (KA)-induced network oscillation in the ACC Cg1 region slice preparation increased in LPS-treated mice. Notably, histamine, which was added in vitro, increased the oscillation power in the brain slices from LPS-untreated mice; for the LPS-treated mice, however, the effect of histamine was suppressive. In the open field test, frequency of entries into the center area showed a negative correlation with the power of network oscillation (0.3 μM of KA, theta band (3-8 Hz); 3.0 μM of KA, high-gamma band (50-80 Hz)). These results suggest that LPS-induced systemic inflammation results in increased network oscillation and a drastic change in histamine sensitivity in the ACC, accompanied by the robust production of systemic pro-inflammatory cytokines in the periphery, and that these alterations in the network oscillation and animal behavior as an acute phase reaction relate with each other. We suggest that our experimental setting has a distinct advantage in obtaining mechanistic insights into inflammatory cognitive impairment through comprehensive analyses of hormonal molecules and neuronal functions.

The phase coherence of the neurovascular unit is reduced in Huntington’s disease

Abstract Huntington’s disease is a neurodegenerative disorder in which neuronal death leads to chorea and cognitive decline. Individuals with ≥40 cytosine–adenine–guanine repeats on the interesting transcript 15 gene develop Huntington’s disease due to a mutated huntingtin protein. While the associated structural and molecular changes are well characterized, the alterations in neurovascular function that lead to the symptoms are not yet fully understood. Recently, the neurovascular unit has gained attention as a key player in neurodegenerative diseases. The mutant huntingtin protein is known to be present in the major parts of the neurovascular unit in individuals with Huntington’s disease. However, a non-invasive assessment of neurovascular unit function in Huntington’s disease has not yet been performed. Here, we investigate neurovascular interactions in presymptomatic (N = 13) and symptomatic (N = 15) Huntington’s disease participants compared to healthy controls (N = 36). To assess the dynamics of oxygen transport to the brain, functional near-infrared spectroscopy, ECG and respiration effort were recorded. Simultaneously, neuronal activity was assessed using EEG. The resultant time series were analysed using methods for discerning time-resolved multiscale dynamics, such as wavelet transform power and wavelet phase coherence. Neurovascular phase coherence in the interval around 0.1 Hz is significantly reduced in both Huntington’s disease groups. The presymptomatic Huntington’s disease group has a lower power of oxygenation oscillations compared to controls. The spatial coherence of the oxygenation oscillations is lower in the symptomatic Huntington’s disease group compared to the controls. The EEG phase coherence, especially in the α band, is reduced in both Huntington’s disease groups and, to a significantly greater extent, in the symptomatic group. Our results show a reduced efficiency of the neurovascular unit in Huntington’s disease both in the presymptomatic and symptomatic stages of the disease. The vasculature is already significantly impaired in the presymptomatic stage of the disease, resulting in reduced cerebral blood flow control. The results indicate vascular remodelling, which is most likely a compensatory mechanism. In contrast, the declines in α and γ coherence indicate a gradual deterioration of neuronal activity. The results raise the question of whether functional changes in the vasculature precede the functional changes in neuronal activity, which requires further investigation. The observation of altered dynamics paves the way for a simple method to monitor the progression of Huntington’s disease non-invasively and evaluate the efficacy of treatments.

The cortical neurophysiological signature of amyotrophic lateral sclerosis.

The progressive loss of motor function characteristic of amyotrophic lateral sclerosis is associated with widespread cortical pathology extending beyond primary motor regions. Increasing muscle weakness reflects a dynamic, variably compensated brain network disorder. In the quest for biomarkers to accelerate therapeutic assessment, the high temporal resolution of magnetoencephalography is uniquely able to non-invasively capture micro-magnetic fields generated by neuronal activity across the entire cortex simultaneously. This study examined task-free magnetoencephalography to characterize the cortical oscillatory signature of amyotrophic lateral sclerosis for having potential as a pharmacodynamic biomarker. Eight to ten minutes of magnetoencephalography in the task-free, eyes-open state was recorded in amyotrophic lateral sclerosis (n = 36) and healthy age-matched controls (n = 51), followed by a structural MRI scan for co-registration. Extracted magnetoencephalography metrics from the delta, theta, alpha, beta, low-gamma, high-gamma frequency bands included oscillatory power (regional activity), 1/f exponent (complexity) and amplitude envelope correlation (connectivity). Groups were compared using a permutation-based general linear model with correction for multiple comparisons and confounders. To test whether the extracted metrics could predict disease severity, a random forest regression model was trained and evaluated using nested leave-one-out cross-validation. Amyotrophic lateral sclerosis was characterized by reduced sensorimotor beta band and increased high-gamma band power. Within the premotor cortex, increased disability was associated with a reduced 1/f exponent. Increased disability was more widely associated with increased global connectivity in the delta, theta and high-gamma bands. Intra-hemispherically, increased disability scores were particularly associated with increases in temporal connectivity and inter-hemispherically with increases in frontal and occipital connectivity. The random forest model achieved a coefficient of determination (R2) of 0.24. The combined reduction in cortical sensorimotor beta and rise in gamma power is compatible with the established hypothesis of loss of inhibitory, GABAergic interneuronal circuits in pathogenesis. A lower 1/f exponent potentially reflects a more excitable cortex and a pathology unique to amyotrophic lateral sclerosis when considered with the findings published in other neurodegenerative disorders. Power and complexity changes corroborate with the results from paired-pulse transcranial magnetic stimulation. Increased magnetoencephalography connectivity in worsening disability is thought to represent compensatory responses to a failing motor system. Restoration of cortical beta and gamma band power has significant potential to be tested in an experimental medicine setting. Magnetoencephalography-based measures have potential as sensitive outcome measures of therapeutic benefit in drug trials and may have a wider diagnostic value with further study, including as predictive markers in asymptomatic carriers of disease-causing genetic variants.

Magnon-photon coupling in an opto-electro-magnonic oscillator

The opto-electronic oscillators (OEOs) hosting self-sustained oscillations by a time-delayed mechanism are of particular interest in long-haul signal transmission and processing. On the other hand, owing to their unique tunability and compatibility, magnons—as elementary excitations of spin waves—are advantageous carriers for coherent signal transduction across different platforms. In this work, we integrated an opto-electronic oscillator with a magnonic oscillator consisting of a microwave waveguide and a yttrium iron garnet sphere. We find that, in the presence of the magnetic sphere, the oscillator power spectrum exhibits sidebands flanking the fundamental OEO modes. The measured waveguide transmission reveals anti-crossing gaps, a hallmark of the coupling between the opto-electronic oscillator modes and the Walker modes of the sphere. Experimental results are well reproduced by a coupled-mode theory that accounts for nonlinear magnetostrictive interactions mediated by the magnetic sphere. Leveraging the advanced fiber-optic technologies in opto-electronics, this work lays out a new, hybrid platform for investigating long-distance coupling and nonlinearity in coherent magnonic phenomena.

Neural correlates of retrospective memory confidence during face-name associative learning.

The ability to accurately assess one's own memory performance during learning is essential for adaptive behavior, but the brain mechanisms underlying this metamemory function are not well understood. We investigated the neural correlates of memory accuracy and retrospective memory confidence in a face-name associative learning task using magnetoencephalography in healthy young adults (n = 32). We found that high retrospective confidence was associated with stronger occipital event-related fields during encoding and widespread event-related fields during retrieval compared to low confidence. On the other hand, memory accuracy was linked to medial temporal activities during both encoding and retrieval, but only in low-confidence trials. A decrease in oscillatory power at alpha/beta bands in the parietal regions during retrieval was associated with higher memory confidence. In addition, representational similarity analysis at the single-trial level revealed distributed but differentiable neural activities associated with memory accuracy and confidence during both encoding and retrieval. In summary, our study unveiled distinct neural activity patterns related to memory confidence and accuracy during associative learning and underscored the crucial role of parietal regions in metamemory.

Unraveling the complexity of rapid eye movement microstates: insights from nonlinear EEG analysis.

Although rapid eye movement (REM) sleep is conventionally treated as a unified state, it comprises two distinct microstates: phasic and tonic REM. Recent research emphasizes the importance of understanding the interplay between these microstates, hypothesizing their role in transient shifts between sensory detachment and external awareness. Previous studies primarily employed linear metrics to probe cognitive states, such as oscillatory power, while in this study, we adopt Lempel-Ziv Complexity (LZC), to examine the nonlinear features of electroencephalographic (EEG) data from the REM microstates and to gain complementary insights into neural dynamics during REM sleep. Our findings demonstrate a noteworthy reduction in LZC during phasic REM compared to tonic REM states, signifying diminished EEG complexity in the former. Additionally, we noted a negative correlation between decreased LZC and delta band power, along with a positive correlation with alpha band power. This study highlights the potential of nonlinear EEG metrics, particularly LZC, in elucidating the distinct features of REM microstates. Overall, this research contributes to advancing our understanding of the complex dynamics within REM sleep and opens new avenues for exploring its implications in both clinical and nonclinical contexts.

Coordination of PSS and Multiple FACTS-POD to Improve Stability and Operation Economy of Wind-thermal-bundled Power System

Aims and Background: Focusing on the low-frequency oscillation and system power loss problem in wind-thermal-bundled (WTB) transmission systems and the interaction problem due to different controllers, this study aimed to improve the low-frequency oscillation characteristics of WTB transmission system while ensuring the economy of operation and suppressing the adverse interaction between controllers. Methods: For this purpose, a coordination and optimization strategy for a power system stabilizer (PSS), static synchronous series compensator with additional power oscillation damping controller (SSSC-POD), and static synchronous compensator with additional power oscillation damping controller (STATCOM-POD) is proposed based on multi-objective salp swarm algorithm (MSSA). The controller regulation characteristics are taken into account in the coordination method. Results: Several designed scenarios, including changing the transmission power of the tie line and increasing wind power output, are considered in the IEEE 4-machine 2-area to test the proposed method. The power flow analysis, characteristic root analysis, and time-domain simulation are used to analyze the simulation results. Conclusion: Simulation results demonstrate that the proposed approach can effectively suppress the low-frequency oscillation of the WTB system while reducing its net loss. The application in engineering issues for MSSA is supplemented.

Impact of α enhancement on the asteroseismic age determination of field stars

Aims. We investigated the theoretical biases affecting the asteroseismic grid-based estimates of stellar mass, radius, and age in the presence of a mismatch between the heavy element mixture of observed stars and stellar models. Methods. We performed a controlled simulation adopting a stellar effective temperature, [Fe/H], an average large frequency spacing, and a frequency of maximum oscillation power as observational constraints. Synthetic stars were sampled from grids of stellar models computed with different [α/Fe] values from 0.0 to 0.4. The mass, radius, and age of these objects were then estimated by adopting a grid of models with a fixed [α/Fe] value of 0.0. The experiment was repeated assuming different sets of observational uncertainties. In the reference scenario, we adopted an uncertainty of 1.5% in seismic parameters, 50 K in effective temperature, and 0.05 dex in [Fe/H]. A higher uncertainty in the atmospheric constraints was also adopted in order to explore the impact on the precision of the observations of the estimated stellar parameters. Results. Our Monte Carlo experiment showed that estimated parameters are biased up to 3% in mass, 1.5% in radius, and 4% in age when the reference uncertainty scenario was adopted. These values correspond to 45%, 48%, and 16% of the estimated uncertainty in the stellar parameters. These non-negligible biases in mass and radius disappear when adopting larger observational uncertainties because of the possibility of the fitting algorithm exploring a wider range of possible solutions. However, in this scenario, the age is significantly biased by −8%. Finally, we verified that the stellar mass, radius, and age can be estimated with a high accuracy by adopting a grid with the incorrect value of [α/Fe] if the metallicity [Fe/H] of the target is adjusted to match the Z in the fitting grid. In this scenario, the maximum bias in the age was reduced to 1.5%.

Covert-channels in FPGA-enabled SmartSSDs

Cloud computing providers today offer access to a variety of devices, which users can rent and access remotely in a shared setting. Among these devices are SmartSSDs, which are solid-state disks (SSD) augmented with an FPGA, enabling users to instantiate custom circuits within the FPGA, including potentially malicious circuits for power and temperature measurement. Normally, cloud users have no remote access to power and temperature data, but with SmartSSDs they could abuse the FPGA component to instantiate circuits to learn this information. Additionally, custom power waster circuits can be instantiated within the FPGA. This paper shows for the first time that by leveraging ring oscillator sensors and power wasters, numerous covert-channels in FPGA-enabled SmartSSDs could be used to transmit information. This work presents two channels in single-tenant setting (SmartSSD is used by one user at a time) and two channels in multi-tenant setting (FPGA and SSD inside SmartSSD is shared by different users). The presented covert channels can reach close to 100% accuracy. Meanwhile, bandwidth of the channels can be easily scaled by cloud users renting more SmartSSDs as the bandwidth of the covert channels is proportional to number of SmartSSD used.

Changes in visually and auditory attended audiovisual speech processing in cochlear implant users: A longitudinal ERP study

Limited auditory input, whether caused by hearing loss or by electrical stimulation through a cochlear implant (CI), can be compensated by the remaining senses. Specifically for CI users, previous studies reported not only improved visual skills, but also altered cortical processing of unisensory visual and auditory stimuli. However, in multisensory scenarios, it is still unclear how auditory deprivation (before implantation) and electrical hearing experience (after implantation) affect cortical audiovisual speech processing.Here, we present a prospective longitudinal electroencephalography (EEG) study which systematically examined the deprivation- and CI-induced alterations of cortical processing of audiovisual words by comparing event-related potentials (ERPs) in postlingually deafened CI users before and after implantation (five weeks and six months of CI use). A group of matched normal-hearing (NH) listeners served as controls. The participants performed a word-identification task with congruent and incongruent audiovisual words, focusing their attention on either the visual (lip movement) or the auditory speech signal. This allowed us to study the (top-down) attention effect on the (bottom-up) sensory cortical processing of audiovisual speech.When compared to the NH listeners, the CI candidates (before implantation) and the CI users (after implantation) exhibited enhanced lipreading abilities and an altered cortical response at the N1 latency range (90–150 ms) that was characterized by a decreased theta oscillation power (4–8 Hz) and a smaller amplitude in the auditory cortex. After implantation, however, the auditory-cortex response gradually increased and developed a stronger intra-modal connectivity. Nevertheless, task efficiency and activation in the visual cortex was significantly modulated in both groups by focusing attention on the visual as compared to the auditory speech signal, with the NH listeners additionally showing an attention-dependent decrease in beta oscillation power (13–30 Hz).In sum, these results suggest remarkable deprivation effects on audiovisual speech processing in the auditory cortex, which partially reverse after implantation. Although even experienced CI users still show distinct audiovisual speech processing compared to NH listeners, pronounced effects of (top-down) direction of attention on (bottom-up) audiovisual processing can be observed in both groups. However, NH listeners but not CI users appear to show enhanced allocation of cognitive resources in visually as compared to auditory attended audiovisual speech conditions, which supports our behavioural observations of poorer lipreading abilities and reduced visual influence on audition in NH listeners as compared to CI users.

Potentiation of the depressant effect of alcohol by flunitrazepam in rats: an electrocorticographic, respiratory and electrocardiographic study.

Alcohol, a widely commercialized psychotropic drug, and the benzodiazepine Flunitrazepam, an anxiolytic widely prescribed for patients with anxiety and insomnia problems, are well known drugs and both act on the central nervous system. The misuse and the association of these two drugs are public health concerns in several countries and could cause momentary, long-lasting and even lethal neurophysiological problems due to the potentiation of their adverse effects in synergy. The present study observed the result of the association of these drugs on electrophysiological responses in the brain, heart, and respiratory rate in Wistar rats. 8 experimental groups were determined: control, one alcohol group (20% at a dose of 1ml/100g VO), three Flunitrazepam groups (doses 0.1; 0.2 and 0.3mg/kg) and three alcohol-Flunitrazepam groups (20% at a dose of 1ml/100g VO of alcohol, combined with 0.1; 0.2 and 0.3mg/kg of Flunitrazepam, respectively). The results showed that there was a more pronounced reduction in alpha and theta wave power in the alcohol-Flunitrazepam groups, a decrease in the power of beta oscillations and greater sedation. There was a progressive decrease in respiratory rate linked to the increase of Flunitrazepam dose in the alcohol-Flunitrazepam associated administration. It was observed alteration in heart rate and Q-T interval in high doses of Flunitrazepam. Therefore, we conclude that the association alcohol-Flunitrazepam presented deepening of depressant synergistic effects according to the increase in the dose of the benzodiazepine, and this could cause alterations in low frequency brain oscillations, breathing, and hemodynamics of the patient.

Analysis of deep learning models for estimation of MPP and extraction of maximum power from hybrid PV-TEG: A step towards cleaner energy production

The Hybrid Photovoltaic-Thermoelectric generation system (PV-TEG) exhibits immense potential for effectively harnessing solar energy. However, the overall effectiveness of the hybrid PV-TEG system is hindered by the relatively low efficiency of both PV and thermoelectric generation (TEG). To overcome this limitation, this research investigates the application of an evolutionary Neural Network (NN)-based Maximum Power Point Tracking (MPPT) control technique. This proposed control technique utilizes a Growth Optimizer Algorithm (GO-algorithm) to optimize the weights and biases of a Deep Neural Network (DNN), enabling real-time tracking of the global maximum power point (GMM). Furthermore, to fortify the robustness of the MPPT control, a modified Fractional Order Proportional-Integral-Derivative (FOPID) controller is used whose gains are tuned using the GO-algorithm (GO-FOPID). Experimental evaluations conclusively demonstrate the efficacy of the evolutionary NN-based MPPT control technique in enhancing the generation efficiency of hybrid PV-TEG systems. The effectiveness of the proposed MPPT technique is validated through a comparative analysis with other MPPT techniques. The GO-DNN-based MPPT controller excels in its real-time global maxima tracking capability, exhibiting minimal power oscillations with average efficiency of 99.928% and an exceptionally low tracking time of less than 5ms. This superior performance is verified by comparative, simulation, quantitative, and statistical analyses, thereby highlighting the efficiency, tracking time, stability, and fault detection capabilities of the GO-DNN and GO-FOPID controllers across various practical scenarios.

Finite Set-Model Predictive Control for Modified quasi Switched Z Source Level 3 Off-board Charger for Active Power Oscillations Damping in Weak Grids

Finite Set-Model Predictive Control for Modified quasi Switched Z Source Level 3 Off-board Charger for Active Power Oscillations Damping in Weak Grids

Improving the efficiency of photovoltaic-thermoelectric generator system using novel flying squirrel search optimization algorithm: Hybrid renewable and thermal energy system (RTES) for electricity generation

The world is moving towards cleaner energy to cater to the effects of global warming, the existing renewable energy resources need to be hybridized with other resources for better output using the same input. Photovoltaic-thermoelectric generator (PV-TEG) energy system is one example of a hybrid renewable and thermal energy system (RTES) for electricity generation, the waste heat which if accumulated on the PV Panel causes an efficiency dip, the heat can be converted into useful energy using a TEG module resulting in PV Panel cooling as well as added energy at the output. For the PV-TEG energy system the controllability aspect is crucial as the main problem lies in the optimization and harvesting of energy from these two sources, the non-linear energy generation nature of the PV and TEG energy systems due to changing conditions i.e., partial shading (PS) and dynamic temperature spread (DTS), makes it hard to attain the full potential of PV and TEG systems using classical/analog techniques. To solve this problem, a novel implementation of Flying Squirrel Search Optimization (FSSO) is used for the Maximum Power Point Tracking (MPPT) for the PV-TEG energy system. The proposed FSSO MPPT algorithm is proven effective through a comparison with Particle Swarm Optimization (PSO), Fruit Fly Optimization (FFO), Perturb and Observe (P&O), and Incremental Conductance (InC) algorithms, demonstrating its superiority. The FSSO-based MPPT algorithm exhibits rapid and accurate Global Maxima (GM) tracking in real-time, minimizing power oscillations with a tracking efficiency of 99.56% and a tracking time of under 0.3 s.

Cross-strata co-occurrence of ripples with theta-frequency oscillations in the hippocampus of foraging rats.

Brain rhythms have been postulated to play central roles in animal cognition. A prominently reported dichotomy of hippocampal rhythms links theta-frequency oscillations (4-12Hz) and ripples (120-250Hz) exclusively to preparatory and consummatory behaviours, respectively. However, because of the differential power expression of these two signals across hippocampal strata, such exclusivity requires validation through analyses of simultaneous multi-strata recordings. We assessed co-occurrence of theta-frequency oscillations with ripples in multi-channel recordings of extracellular potentials across hippocampal strata from foraging rats. We detected all ripple events from an identified stratum pyramidale (SP) channel. We then defined theta epochs based on theta oscillations detected from the stratum lacunosum-moleculare (SLM) or the stratum radiatum (SR). We found ∼20% of ripple events (in SP) to co-occur with theta epochs identified from SR/SLM channels, defined here as theta ripples. Strikingly, when theta epochs were instead identified from the SP channel, such co-occurrences were significantly reduced because of a progressive reduction in theta power along the SLM-SR-SP axis. Behaviourally, we found most theta ripples to occur during immobile periods, with comparable theta power during exploratory and immobile theta epochs. Furthermore, the progressive reduction in theta power along the SLM-SR-SP axis was common to exploratory and immobile periods. Finally, we found a strong theta-phase preference of theta ripples within the fourth quadrant [3π/2-2π] of the associated theta oscillation. The prevalence of theta ripples expands the potential roles of ripple-frequency oscillations to span the continuum of encoding, retrieval and consolidation, achieved through interactions with theta oscillations. KEY POINTS: The brain manifests oscillations in recorded electrical potentials, with different frequencies of oscillation associated with distinct behavioural states. A prominently reported dichotomy assigns theta-frequency oscillations (4-12Hz) and ripples (120-250Hz) recorded in the hippocampus to be exclusively associated with preparatory and consummatory behaviours, respectively. Our multi-strata recordings from the rodent hippocampus coupled with cross-strata analyses provide direct quantitative evidence for the occurrence of ripple events nested within theta oscillations. These results highlight the need for an analysis pipeline that explicitly accounts for the specific strata where individual oscillatory power is high, in analysing simultaneously recorded data from multiple strata. Our observations open avenues for investigations involving cross-strata interactions between theta oscillations and ripples across different behavioural states.

Grid-Impedance-Based Transient Current Control for Offshore Wind Turbines under Low-Voltage Fault

In order to enhance the transient stability of offshore wind turbines (OWTs) in marine energy systems, the grid codes stipulate that OWTs should possess the low-voltage ride-through (LVRT) ability of being grid-tied and injecting reactive current during grid fault. However, the grid-side converter (GSC) of OWTs may lose stability under weak grid or severe fault conditions due to inaccurate current references. To address this issue, a novel transient current control method is proposed to improve the transient stability of permanent-magnet-synchronous-generator (PMSG)-based OWTs. The feature of DC-link overvoltage is investigated and is alleviated by utilizing the GSC’s overcurrent capacity and chopper. Additionally, the equivalent circuit of the PMSG-based OWT connected to the onshore grid is derived based on Thevenin’s theorem. The feasible current region (FCR) is then determined, taking into account the GSC capacity, pre-fault power ability, LVRT requirement, and synchronization stability. Furthermore, a grid-impedance-based transient current control method is designed to enhance the fault ride-through performance and mitigate power oscillation of the OWT under various transient grid impedance and fault conditions. Finally, a simulation model is conducted using PSCAD v4.6.3 software to validate the effectiveness of the proposed method.

Single session of intermittent theta burst stimulation alters brain activity of patients in vegetative state.

Non-invasive brain stimulation is considered as a promising technology for treating patients with disorders of consciousness (DOC). Various approaches and protocols have been proposed; however, few of them have shown potential effects on patients with vegetative state (VS). This study aimed to explore the neuro-modulation effects of intermittent theta burst stimulation (iTBS) on the brains of patients with VS and to provide a pilot investigation into its possible role in treating such patients. We conducted a sham-controlled crossover study, a real and a sham session of iTBS were delivered over the left dorsolateral prefrontal cortex of such patients. A measurement of an electroencephalography (EEG) and a behavioral assessment of the Coma Recovery Scale-Revised (CRS-R) were applied to evaluate the modulation effects of iTBS before and after stimulation. No meaningful changes of CRS-R were found. The iTBS altered the spectrum, complexity and functional connectivity of the patients. The real stimulation induced a trend of decreasing of delta power at T1 and T2 in the frontal region, significant increasing of permutation entropy at the T2 in the left frontal region. In addition, brain functional connectivity, particularly inter-hemispheric connectivity, was strengthened between the electrodes of the frontal region. The sham stimulation, however, did not induce any significant changes of the brain activity. One session of iTBS significantly altered the oscillation power, complexity and functional connectivity of brain activity of VS patients. It may be a valuable tool on modulating the brain activities of patients with VS.

Prediction of wind and PV power by fusing the multi-stage feature extraction and a PSO-BiLSTM model

Accurate prediction of wind and photovoltaic (PV) power is essential to ensure the stable operation of power systems. However, the conventional power prediction methods face the challenges in capturing the stochastic fluctuations of wind and PV power. A wind and PV power prediction method fusing the multi-stage feature extraction and a particle swarm optimization (PSO)-bidirectional long and short-term memory (BiLSTM) model is developed. To illustrate the oscillation and instability of wind and PV power, the symplectic geometry model decomposition (SGMD) is presented to decompose the feature data and obtain multiple feature sub-sequences. Due to the excessive feature decomposition using the conventional methods, such as empirical modal decomposition, the kernel principal component analysis is utilized to reduce the dimensionality of the nonlinear sub-sequences of the wind and PV power. Compared to the traditional LSTM that ignores the inverse-time correlation between power and meteorological features and is sensitive to the model hyper-parameters, a power prediction model based on PSO-BiLSTM is developed. Using the power data from a power station in Xinjiang Province, China, as an example, the experimental results show that wind and PV power can be accurately forecasted using the developed method with high prediction accuracies of 97.9 % and 98.5 %, respectively.

Multi-mode stable, high peak power Nd:YAG laser device for laser cleaning

High average power and peak power solid-state lasers are of great interest in the field of laser cleaning. In this research, a high peak power laser with over 400 W average power using a multi-mode stable resonator in a diode-pumped Nd:YAG master oscillator power amplifier has been demonstrated. A maximum peak power over 1.08 MW was achieved at a repetition frequency of 5 kHz. Delivery fiber with a 400 µm core diameter was utilized for flexible laser transmission. A prototype of the laser cleaning system was developed and inspiring application effects for paint and mold cleaning were achieved.