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Type 2 diabetes mellitus (T2DM) increases the risk of neurological diseases, yet how brain oscillations change as age and T2DM interact is not well characterized. To delineate the age and diabetic effect on neurophysiology, we recorded local field potentials with multichannel electrodes spanning the somatosensory cortex and hippocampus (HPC) under urethane anesthesia in diabetic and normoglycemic control mice, at 200 and 400 days of age. We analyzed the signal power of brain oscillations, brain state, sharp wave associate ripples (SPW-Rs), and functional connectivity between the cortex and HPC. We found that while both age and T2DM were correlated with a breakdown in long-range functional connectivity and reduced neurogenesis in the dentate gyrus and subventricular zone, T2DM further slowed brain oscillations and reduced theta-gamma coupling. Age and T2DM also prolonged the duration of SPW-Rs and increased gamma power during SPW-R phase. Our results have identified potential electrophysiological substrates of hippocampal changes associated with T2DM and age. The perturbed brain oscillation features and diminished neurogenesis may underlie T2DM-accelerated cognitive impairment. [ABSTRACT FROM AUTHOR]

A novel scheme for electric field-induced strong terahertz (THz) emission by beating two filamented spatial-Gaussian laser beams (with intensities 10 14 W cm - 2 ) in the pre-existing underdense magnetized plasma is proposed. The coupling between the nonlinear density and nonlinear velocity of the plasma electrons results in the strong nonlinear current which drives the efficient THz radiation in the presence of the D.C. electric and magnetic fields. The contribution of the electron temperature on the THz generation has been investigated. The modulation index also makes a significant contribution to the enhancement of the nonlinear current density and normalized THz amplitude. With the help of a magnetic field, D. C. electric field, D.C. drift speed, and modulation index, one can easily tune the THz radiations for medical and astronomical applications. The normalized amplitude of emitted THz radiation is observed to vary with the externally applied electric field, magnetic field, normalized frequency, drift velocity of electrons, thermal velocity of electrons, temperature of plasma electrons, and modulation index of incident laser beams. The frequency of the emitted THz radiation (corresponding to 25.0 kG ) is found to lie in the frequency range of molecular rotational and vibrational spectra of deoxyribonucleic acid. As a result, emitted THz radiation in the present scheme can play an important role in developing a new technique to distinguish between healthier and non-healthier tissues of human beings. The emitted THz radiation shows sensitive behavior toward water particles. Due to this, emitted THz radiation can also be used to detect water at the surface of the earth as well as on other celestial bodies. [ABSTRACT FROM AUTHOR]

Chan Zhang,1– 3,&ast; Yanhui Wang,1,3,4,&ast; Mengjie Li,1,4 Pengpeng Niu,1,2 Shuo Li,1,2 Zhuopeng Hu,5 Changhe Shi,1,2 Yusheng Li1– 3 1Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, 450000, People’s Republic of China; 2NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, Zhengzhou, Henan, People’s Republic of China; 3Henan Neurological Function Detection and Regulation Center, Zhengzhou, Henan, 450000, People’s Republic of China; 4The Academy of Medical Sciences of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, People’s Republic of China; 5The First Bethune Clinical Medical College of Ji Lin University, Changchun, Jilin, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Yusheng Li, Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, 450000, People’s Republic of China, Tel +86-18236145799, Fax +86-371-66862134, Email fccliyusheng@zzu.edu.cnBackground: Phase-amplitude coupling (PAC) between the phase of low-frequency signals and the amplitude of high-frequency activities plays many physiological roles and is involved in the pathological processed of various neurological disorders. However, how low-frequency and high-frequency neural oscillations or information synchronization activities change under chronic central hypoxia in OSA patients and whether these changes are closely associated with OSA remains largely unexplored. This study arm to elucidate the long-term consequences of OSA-related oxygen deprivation on central nervous system function.Methods: : We screened 521 patients who were clinically suspected of having OSA at our neurology and sleep centers. Through polysomnography (PSG) and other clinical examinations, 103 patients were ultimately included in the study and classified into mild, moderate, and severe OSA groups based on the severity of hypoxia determined by PSG. We utilized the phase-amplitude coupling (PAC) method to analyze the modulation index (MI) trends between different frequency bands during NREM (N1/N2/N3), REM, and wakefulness stages in OSA patients with varying severity levels. We also examined the correlation between the MI index and OSA hypoxia indices.Results: Apart from reduced N2 sleep duration and increased microarousal index, the sleep architecture remained largely unchanged among OSA patients with varying severity levels. Compared to the mild OSA group, patients with moderate and severe OSA exhibited higher MI values of PAC in the low-frequency theta phase and high-frequency beta amplitude in the frontal and occipital regions during N1 sleep and wakefulness. No significant differences in the MI of phase-amplitude coupling were observed during N2/3 and REM sleep. Moreover, the MI of phase-amplitude coupling in theta and beta bands positively correlated with hypoxia-related indices, including the apnea-hypopnea index (AHI) and oxygenation desaturation index (ODI), and the percentage of oxygen saturation below 90% (SaO2< 90%).Conclusion: OSA patients demonstrated increased MI values of theta phase and beta amplitude in the frontal and occipital regions during N1 sleep and wakefulness. This suggests that cortical coupling is prevalent and exhibits sleep-stage-specific patterns in OSA. Theta-beta PAC during N1 and wakefulness was positively correlated with hypoxia-related indices, suggesting a potential relationship between these neural oscillations and OSA severity. The present study provides new insights into the relationship between neural oscillations and respiratory hypoxia in OSA patients.Keywords: phase-amplitude coupling, PAC, modulation index, MI, obstructive sleep apnea, polysomnography, EEG

In this paper, with the development of an intelligent power system idea, sustainable energy sources were increasingly deployed, including transmission and distribution systems networks. As a result, optimal use of cascaded H-bridge inverter topologies (MLIs) and power distribution operations is critical for long-term power generation. Traditionally, selective harmonics reduction models must be performed to achieve the optimal switching frequency of multilevel inverters. This research aims to determine the switching frequency for wind-incorporated multilevel inverters to reduce overall harmonic components used in grid applications. This research adds towards the best possible solution by employing multiple newly established adaptive optimization techniques: MNSGA-II and salp swarm. The well-known genetic algorithm and particle swarm optimization are used for the wind-tied multilevel inverters optimization issue. Seven-level, eleven-level, and fifteen-level MLIs were employed to reduce overall harmonic distortion. The reliability and convergence rate of simulated data with various modulation indices for seven-, eleven-, and fifteen-level MLIs are obtained and compared. Models are developed based on MATLAB Simulink and are used to validate quantitative measurements.

In this paper, with the development of an intelligent power system idea, sustainable energy sources were increasingly deployed, including transmission and distribution systems networks. As a result, optimal use of cascaded H-bridge inverter topologies (MLIs) and power distribution operations is critical for long-term power generation. Traditionally, selective harmonics reduction models must be performed to achieve the optimal switching frequency of multilevel inverters. This research aims to determine the switching frequency for wind-incorporated multilevel inverters to reduce overall harmonic components used in grid applications. This research adds towards the best possible solution by employing multiple newly established adaptive optimization techniques: MNSGA-II and salp swarm. The well-known genetic algorithm and particle swarm optimization are used for the wind-tied multilevel inverters optimization issue. Sevenlevel, eleven-level, and fifteen-level MLIs were employed to reduce overall harmonic distortion. The reliability and convergence rate of simulated data with various modulation indices for seven-, eleven-, and fifteen-level MLIs are obtained and compared. Models are developed based on MATLAB Simulink and are used to validate quantitative measurements. [ABSTRACT FROM AUTHOR]

The objective and automatic detection of the sleep–wake cycle (SWC) stages is essential for the investigation of its physiology and dysfunction. Here, we propose a machine learning model for the classification of SWC stages based on the measurement of synchronization between neural oscillations of different frequencies. Publicly available electrophysiological recordings of mice were analyzed for the computation of phase–amplitude couplings, which were then supplied to a multilayer perceptron (MLP). Firstly, we assessed the performance of several architectures, varying among different input choices and numbers of neurons in the hidden layer. The top performing architecture was then tested using distinct extrapolation strategies that would simulate applications in a real lab setting. Although all the different choices of input data displayed high AUC values (>0.85) for all the stages, the ones using larger input datasets performed significantly better. The top performing architecture displayed high AUC values (>0.95) for all the extrapolation strategies, even in the worst-case scenario in which the training with a single day and single animal was used to classify the rest of the data. Overall, the results using multiple performance metrics indicate that the usage of a basic MLP fed with highly descriptive features such as neural synchronization is enough to efficiently classify SWC stages. [ABSTRACT FROM AUTHOR]

The 5G system generally requires the transmission of significant amount of information in allocated frequency bands. Besides, 5G channel presents two major problems for wireless communications, namely time dispersion, due to the phenomenon of multipath propagation, as well as frequency selectivity. So, improving the reliability of a wireless communication system for 5G requires the use of more suitable modulation techniques and more performance in the wireless context. Among the modulations that can be considered for this kind of application, we find the CPM (continuous phase modulation) scheme. This class of modulations is robust to phase drifts and nonlinear distortions generated by the amplifier when it is pushed to its maximum output power. In this paper, we propose a non-coherent receiver insensitive to fluctuations in the modulation index and capable of offering better performance on 5G channels. A detailed description of CPFSK signal is performed. The blind equalizer was introduced in order to combat inter symbol interference of the 5G channel as well as to make the transceiver insensible to the variation of the modulation index. The obtained results show the robustness, efficiency and low complexity of the proposed system over 5G channel. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Railway Science & Engineering is the property of Journal of Railway Science & Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

It is a crucial basis to improve the performance of neural network by constructing an appropriate activation function. This paper proposes a novel modulation window radial basis function neural network (MW-RBFNN) with an adjustable activation function. In this MW-RBFNN, a raised cosine radial basis function (RC-RBF) is adaptively modulated by an exponential function, and served as a shape-tunable activation function of MW-RBFNN. Compared with the basic RC-RBF neural network, the approximating ability of MW-RBFNN is improved due to its shape-tunable activation function. Besides, the computation of MW-RBFNN is far less than that of Gaussian radial basis function neural network (GRBFNN) because the MW-RBFNN is compactly supported. The training algorithm of MW-RBFNN is provided and its approximating ability is proved. Moreover, the regulation mechanism of the modulation index for the NN's performance is proved and the regulating algorithm of the modulation index in MW-RBFNN is given. The computational complexity of MW-RBFNN is also analyzed. Five typical application cases are presented to illustrate the effectiveness of this proposed MW-RBFNN. [ABSTRACT FROM AUTHOR]

Brain oscillations recorded in the extracellular space are among the most important aspects of neurophysiology data reflecting the activity and function of neurons in a population or a network. The signal strength and patterns of brain oscillations can be powerful biomarkers used for disease detection and prediction of the recovery of function. Electrophysiological signals can also serve as an index for many cutting-edge technologies aiming to interface between the nervous system and neuroprosthetic devices and to monitor the efficacy of boosting neural activity. In this review, we provided an overview of the basic knowledge regarding local field potential, electro- or magneto- encephalography signals, and their biological relevance, followed by a summary of the findings reported in various clinical and experimental stroke studies. We reviewed evidence of stroke-induced changes in hippocampal oscillations and disruption of communication between brain networks as potential mechanisms underlying post-stroke cognitive dysfunction. We also discussed the promise of brain stimulation in promoting post stroke functional recovery via restoring neural activity and enhancing brain plasticity.

This paper proposes a modified structure of reduced switch count H-Bridge Multilevel inverter (MLI) which comes with an advantages of higher voltage level, lower switching loss and lower number of components. This developed topology of MLI can generate 15-level output voltage with only three number of DC voltage sources and ten power devices. In order to generate the higher voltage level in analogy to the conventional Multilevel inverter asymmetrical input voltage sources are used which reduced the number of power devices input voltage sources and driver circuits. To mitigate the voltage and current harmonics from the output of the MLI JAYA algorithm is employed. This algorithm resulted 2.5% total harmonic distortion (THD) for three phase system and 5.2% THD for single phase system by developing suitable switching angles with rapid acceleration and reduces the computational burden. The efficacy of the algorithm has been justified by the comparison study with most popular swarm based algorithms known as particle swarm optimization (PSO) and Genetic algorithm (GA). The performance of the reduced MLI has been studied by developing a prototype for single phase and three phase in both MATLAB Simulink environment and experimental setup.

This paper presents a technique of harmonic minimization from output voltage waveform of a reduced switch Multilevel Inverter (MLI) through an efficient bio inspired metaheuristic algorithm called Black widow optimization (BWO). The proposed reduced switch 13- level MLI scheme uses a single Photovoltaic (PV) source which can be suitable for grid integration. The proposed BWO algorithm minimizes the Total Harmonic Distortion (THD) of output voltage with low operational time compared to other existing nature based algorithms considering large searching area. The weighted THD (WTHD) of the output voltage is also minimized in order to reduce the effect of lower order harmonics from the output voltage in a greater extent. The convergence rate and level of accuracy of BWO algorithm is compared with two different bio inspired algorithms for justification. The MLI operation is carried out with fundamental frequency, minimizing the switching stress while lowering the power loss compared to PWM or Sinusoidal PWM switching schemes. A single PV panel with multi winding flyback converter is used for medium voltage application through reduced switch MLI, serving the purpose of both isolation and reduction of energy sources. Simulation and experimental analysis are carried out with online control technique using a three phase 13-level reduced MLI to validate the proposed concept on a practical system.

This paper introduces a hybrid multilevel inverter (MLI) with reduced switch count, which can generate higher output voltage level with minimum number of DC input sources. The operation of this proposed MLI is carried out with unequal DC sources to achieve the desired output voltage level. The reduced MLI output voltage is set to minimal total harmonic distortion (THD) with the help of modified JAYA (MJAYA) algorithm. A JAYA algorithm with improved steps by adopting an accelerating parameter has been proposed in this research work to obtain a faster convergence of the objective function. The MJAYA algorithm has provided the suitable switching angles for the proposed three-phase 15-level MLI and reduced the output voltage THD to 2.23%, which satisfies the standard set by IEEE-519. To prove the efficiency of this proposed modified algorithm, the comparative analysis is carried out through MATLAB program and Simulink tool using common JAYA and modified particle swarm optimisation algorithms. The performance and productivity of the proposed MLI have been investigated through simulation and experimental setups. [ABSTRACT FROM AUTHOR]

A scheme of generating millimeter‐wave signals with 16 times frequency using a cascaded Mach–Zehnder modulator (MZM) is proposed. Optical delay lines (ODLs) are used to place between cascaded MZMs, two MZMs work at the maximum transmission point. By controlling the modulation index of the MZM and the delay of the ODL, 0‐order, ±8 $\pm 8$‐order, and ±12 $\pm 12$‐order sidebands can be generated. The optical phase shifter and attenuator are adjusted to eliminate the 0‐order sideband, and the photodetector output generates a frequency 16‐tupling millimeter wave (MMW). In the simulation platform, a 160‐GHz MMW signal can be obtained by taking a 10‐GHz radio frequency signal as the driving signal of two MZMs. The optical sideband suppression ratio is 29.92 dB, and the radio frequency sideband suppression ratio is 24.89 dB. Further, the effect of system performance on optical devices under nonideal conditions is also discussed. [ABSTRACT FROM AUTHOR]

With the evolution of an advanced power system concept, green power supplies, comprising transmission and distribution designed networks, were progressively implemented in this research. Consequently, optimum usage of cascaded H-bridge inverter topologies and power distribution activities is crucial for long-term production. Selective harmonics elimination techniques have always been required to attain the appropriate switching frequencies of multilevel inverters. This study aims to estimate the switching frequency for solar-integrated multilevel inverters utilizing boost converters to decrease the total harmonic contents utilized in grid applications. This study contributes to the optimum feasible solution by utilizing a number of recently discovered dynamic controller methods: Type I Fuzzy controller and Interval Type II Fuzzy controller. Seven-level, eleven-level, and fifteen-level MLIs minimize overall harmonic components. The dependability and convergent rates of simulation results with different modulation indices are produced and compared for seven-, eleven-, and fifteen-level MLIs. In addition, as compared to existing control systems, the suggested controller reduces Total Harmonic Distortion and delivers stabilized output power. The suggested IT2-FLC is compared against an T1-FLC and a standard mathematical PI controller. [ABSTRACT FROM AUTHOR]

In this paper, a proficient control approach-based 17-level Quasi Z-source Cascaded Multilevel Inverter (QZS-CMI) topology is proposed to interface photovoltaic (PV) system. The control approach is a combination of GarraRufa Fish Optimization (GRFO) and Random Forest Algorithm (RFA). Hence, it is named as GRFO-RFA technique. The major goal of this paper is to present a 17-level QZS-CMI with fewer semiconductor switches that is ideal in high-power photovoltaic applications with lower total harmonic distortion and higher performance. The interface between the load and PV DC source is performed with QZSI. The design modeling of QZS-CMI is improved and the maximal power of PV power production system is supplied. Initially, the objective function is decided depending on the control restrictions and the parameters. The GRFOA process is utilized to enhance power delivery, voltage profile, and minimal power swing. The enhanced QZS-CMI based on the proposed system controls shoot-through and reduces modulation load and duty ratio. The proposed system is implemented in MATLAB/Simulink and its efficacy is compared to the existing methods. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Signal Processing is the property of Journal of Signal Processing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The objective and automatic detection of the sleep–wake cycle (SWC) stages is essential for the investigation of its physiology and dysfunction. Here, we propose a machine learning model for the classification of SWC stages based on the measurement of synchronization between neural oscillations of different frequencies. Publicly available electrophysiological recordings of mice were analyzed for the computation of phase–amplitude couplings, which were then supplied to a multilayer perceptron (MLP). Firstly, we assessed the performance of several architectures, varying among different input choices and numbers of neurons in the hidden layer. The top performing architecture was then tested using distinct extrapolation strategies that would simulate applications in a real lab setting. Although all the different choices of input data displayed high AUC values (>0.85) for all the stages, the ones using larger input datasets performed significantly better. The top performing architecture displayed high AUC values (>0.95) for all the extrapolation strategies, even in the worst-case scenario in which the training with a single day and single animal was used to classify the rest of the data. Overall, the results using multiple performance metrics indicate that the usage of a basic MLP fed with highly descriptive features such as neural synchronization is enough to efficiently classify SWC stages.

Copyright of International Journal of Engineering Transactions C: Aspects is the property of International Journal of Engineering (IJE) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Researchers have looked for rapidly- and objectively-measurable electrophysiology biomarkers that accurately localize the epileptogenic zone. Promising candidates include interictal high-frequency oscillation and phase-amplitude coupling. Investigators have independently created the toolboxes that compute the high-frequency oscillation rate and the severity of phase-amplitude coupling. This study of 135 patients determined what toolboxes and analytic approaches would optimally classify patients achieving post-operative seizure control. Four different detector toolboxes computed the rate of high-frequency oscillation at ≥80 Hz at intracranial EEG channels. Another toolbox calculated the modulation index reflecting the strength of phase-amplitude coupling between high-frequency oscillation and slow-wave at 3-4 Hz. We defined the completeness of resection of interictally-abnormal regions as the subtraction of high-frequency oscillation rate (or modulation index) averaged across all preserved sites from that averaged across all resected sites. We computed the outcome classification accuracy of the logistic regression-based standard model considering clinical, ictal intracranial EEG and neuroimaging variables alone. We then determined how well the incorporation of high-frequency oscillation/modulation index would improve the standard model mentioned above. To assess the anatomical variability across non-epileptic sites, we generated the normative atlas of detector-specific high-frequency oscillation and modulation index. Each atlas allowed us to compute the statistical deviation of high-frequency oscillation/modulation index from the non-epileptic mean. We determined whether the model accuracy would be improved by incorporating absolute or normalized high-frequency oscillation/modulation index as a biomarker assessing interictally-abnormal regions. We finally determined whether the model accuracy would be improved by selectively incorporating high-frequency oscillation verified to have high-frequency oscillatory components unattributable to a high-pass filtering effect. Ninety-five patients achieved successful seizure control, defined as International League against Epilepsy class 1 outcome. Multivariate logistic regression analysis demonstrated that complete resection of interictally-abnormal regions additively increased the chance of success. The model accuracy was further improved by incorporating z-score normalized high-frequency oscillation/modulation index or selective incorporation of verified high-frequency oscillation. The standard model had a classification accuracy of 0.75. Incorporation of normalized high-frequency oscillation/modulation index or verified high-frequency oscillation improved the classification accuracy up to 0.82. These outcome prediction models survived the cross-validation process and demonstrated an agreement between the model-based likelihood of success and the observed success on an individual basis. Interictal high-frequency oscillation and modulation index had a comparably additive utility in epilepsy presurgical evaluation. Our empirical data support the theoretical notion that the prediction of post-operative seizure outcomes can be optimized with the consideration of both interictal and ictal abnormalities.

• Sevoflurane diffusely augmented intraoperative high-frequency oscillation (HFO) effective connectivity, yet most in the epileptogenic zone. • Intraoperative HFO effective connectivity best classified the epileptogenic sites at sevoflurane 2 MAC. • HFO effective connectivity can be visualized on major white matter pathways, as a function of sevoflurane concentration. To determine how sevoflurane anesthesia modulates intraoperative epilepsy biomarkers on electrocorticography, including high-frequency oscillation (HFO) effective connectivity (EC), and to investigate their relation to epileptogenicity and anatomical white matter. We studied eight pediatric drug-resistant focal epilepsy patients who achieved seizure control after invasive monitoring and resective surgery. We visualized spatial distributions of the electrocorticography biomarkers at an oxygen baseline, three time-points while sevoflurane was increasing, and at a plateau of 2 minimum alveolar concentration (MAC) sevoflurane. HFO EC was combined with diffusion-weighted imaging, in dynamic tractography. Intraoperative HFO EC diffusely increased as a function of sevoflurane concentration, although most in epileptogenic sites (defined as those included in the resection); their ability to classify epileptogenicity was optimized at sevoflurane 2 MAC. HFO EC could be visualized on major white matter tracts, as a function of sevoflurane level. The results strengthened the hypothesis that sevoflurane-activated HFO biomarkers may help intraoperatively localize the epileptogenic zone. Our results help characterize how HFOs at non-epileptogenic and epileptogenic networks respond to sevoflurane. It may be warranted to establish a normative HFO atlas incorporating the modifying effects of sevoflurane and major white matter pathways, as critical reference in epilepsy presurgical evaluation. [ABSTRACT FROM AUTHOR]

ObjectiveTo investigate the diagnostic utility of high frequency oscillations (HFOs) via scalp electroencephalogram (EEG) in infantile spasms.MethodsWe retrospectively analyzed interictal slow-wave sleep EEGs sampled at 2,000 Hz recorded from 30 consecutive patients who were suspected of having infantile spasms. We measured the rate of HFOs (80-500 Hz) and the strength of the cross-frequency coupling between HFOs and slow-wave activity (SWA) at 3-4 Hz and 0.5-1 Hz as quantified with modulation indices (MIs).ResultsTwenty-three patients (77%) exhibited active spasms during the overnight EEG recording. Although the HFOs were detected in all children, increased HFO rate and MIs correlated with the presence of active spasms (p

The functional consequences of ischemic stroke in the remote brain regions are not well characterized. The current study sought to determine changes in hippocampal oscillatory activity that may underlie the cognitive impairment observed following distal middle cerebral artery occlusion (dMCAO) without causing hippocampal structural damage. Local field potentials were recorded from the dorsal hippocampus and cortex in urethane-anesthetized rats with multichannel silicon probes during dMCAO and reperfusion, or mild ischemia induced by bilateral common carotid artery occlusion (CCAO). Bilateral change of brain state was evidenced by reduced theta/delta amplitude ratio and shortened high theta duration following acute dMCAO but not CCAO. An aberrant increase in the occurrence of sharp-wave-associated ripples (150-250 Hz), crucial for memory consolidation, was only detected after dMCAO reperfusion, coinciding with an increased occurrence of high-frequency discharges (250-450 Hz). dMCAO also significantly affected the modulation of gamma amplitude in the cortex coupled to hippocampal theta phase, although both hippocampal theta and gamma power were temporarily decreased during dMCAO. Our results suggest that MCAO may disrupt the balance between excitatory and inhibitory circuits in the hippocampus and alter the function of cortico-hippocampal network, providing a novel insight in how cortical stroke affects function in remote brain regions.

This article proposes a dual space vector PWM control technique for a three-phase to five-phase quasi Z-source direct matrix converter (QZSDMC). The proposed circuit consists of a quasi-impedance source network along with a five-phase traditional matrix converter. With the observation of bidirectional operating capability and the utilization of shoot-through duty ratio, the proposed converter can ensure both buck and boost operations. This converter overcomes the voltage transfer ratio restriction and poor voltage regulation of the traditional matrix converter. Also, this converter ensures continuous input current with an absence of input LC filter components. The proposed direct AC to AC power converter gives an alternate solution to the multiphase drive system instead of the traditional voltage source inverter. The developed dual space vector PWM control technique for three-phase to five-phase voltage conversion is derived from the basic space vector PWM approach. The proposed dual space vector PWM technique utilizes 90 active states and 3 zero vector states among 243 switching states. The QZSDMC has been analysed with a dual space vector PWM approach along with the distribution of shoot-through state in the zero vector. The proposed topology along with the control strategy has been simulated using MATLAB/Simulink environment.

[Display omitted] • Modulation index(MI) Ripples/3–4 Hz and MI Ripples/4–8 Hz in the hippocampus were significantly higher than in other regions at seizure onset. • MI Ripples/3–4 Hz and MI Ripples/4–8 Hz showed chronological changes corresponding to the phase of the seizure. • Continuous measurement of MI Ripples/3–4 Hz and MI Ripples/4–8 Hz during the ictal phase could help identify epileptogenic zones. To analyze chronological changes in phase-amplitude coupling (PAC) and verify whether PAC analysis can diagnose epileptogenic zones during seizures. We analyzed 30 seizures in 10 patients with mesial temporal lobe epilepsy who had ictal discharges with preictal spiking followed by low-voltage fast activity patterns on intracranial electroencephalography. We used the amplitude of two high-frequency bands (ripples: 80–200 Hz, fast ripples: 200–300 Hz) and the phase of three slow wave bands (0.5–1 Hz, 3–4 Hz, and 4–8 Hz) for modulation index (MI) calculation from 2 minutes before seizure onset to seizure termination. We evaluated the accuracy of epileptogenic zone detection by MI, in which a combination of MI was better for diagnosis and analyzed patterns of chronological changes in MI during seizures. MI Ripples/3–4 Hz and MI Ripples/4–8 Hz in the hippocampus were significantly higher than those in the peripheral regions from seizure onset. Corresponding to the phase on intracranial electroencephalography, MI Ripples/3–4 Hz decreased once and subsequently increased again. MI Ripples/4–8 Hz showed continuously high values. Continuous measurement of MI Ripples/3–4 Hz and MI Ripples/4–8 Hz could help identify epileptogenic zones. PAC analysis of ictal epileptic discharges can help epileptogenic zone identification. [ABSTRACT FROM AUTHOR]

This paper investigates the performance of Permanent Magnet Synchronous Motors (PMSM) in terms of torque ripples, a critical aspect affecting their operational efficiency and stability. Torque ripples in AC motors are primarily attributed to the switching action of the inverter Insulated Gate Bipolar Transistors (IGBTs), resulting in current fluctuations that directly influence motor torque. Mitigating these ripples is crucial for enhancing motor performance and reducing mechanical stress. This study focuses on utilizing multilevel inverters to minimize torque ripples by smoothing the motor current through harmonic elimination. Three different types of inverters, namely 2-level, 3-level, and 5-level inverters, are simulated to assess their impact on torque ripple reduction. The torque ripples were obtained from two methods where direct simulation is a method chosen and in second method, the average torque is subtracted from instantaneous torque samples. Stator currents are analyzed in the alpha-beta frame to evaluate the effectiveness of each inverter configuration in producing smoother current profiles and subsequently reducing torque ripples. Additionally, simulations are conducted under varying load torque conditions to assess the robustness and applicability of the proposed methodology across a wide range of operating conditions.

Multilevel inverters (MLI) are aligned with lower harmonics and less commutation losses, which offer high power capacity. MLI is one of the best widespread converters due to its ability to eliminate the harmonic distortion without dropping the converter power output. The cascaded MLI is utilized for a reduced number of switches. In this topology, the switching angles at fundamental frequency are attained by solving the selective harmonic eliminations using sine cosine algorithm. This attains the desired output voltage with the elimination of certain lower order harmonics. In this paper, the analysis of seven-level cascaded MLI is presented with the scheme of carrier-based modulation techniques i.e. Phase-Disposition (PD), Phase-Opposition Disposition (POD) and Alternative Phase-Opposition Disposition (APOD). The Artificial intelligence (AI) is carried out for PD technique. These techniques are capable of defining the required switching angles to eliminate the preferred values of harmonics. The harmonic contents of output voltage in carrier-based modulation are observed with the indices, such as the modulation index with frequency modulation index and amplitude modulation index. The simulation results are obtained for seven-level inverter using MATLAB/SIMULINK. The hardware implementation is carried out using Main Power Management IC TPS65217C Beagle Bone Black Board for seven-level open loop control to justify the achievement of the suggested topology. [ABSTRACT FROM AUTHOR]

Electromagnetic (EM) theory plays a pivotal role in geophysics, offering valuable insights into the subsurface properties of the Earth. In this comprehensive review, we delve into the principles, methods, and advancements in electromagnetic theory for geophysical applications. We explore how EM theory is employed to investigate the Earth's electrical conductivity, map subsurface structures, and detect geological features such as mineral deposits, groundwater reservoirs, and hydrocarbon accumulations. Additionally, we discuss advanced techniques and emerging trends in EM geophysics, including time-domain and frequency-domain methods, inversion algorithms, and multi-physics integration. By gaining a deeper understanding of electromagnetic theory in geophysics, researchers and practitioners can harness its potential to address key challenges in resource exploration, environmental monitoring, and hazard mitigation. [ABSTRACT FROM AUTHOR]

The paper is dedicated to the study of the formation of a high-current stage of a pulsed discharge in cesium vapor from a continuously burning auxiliary plasma channel. The comparison of the electrophysical parameters and the radiation characteristics of a pulsed discharge in the presence and absence of an auxiliary discharge was carried out. Recommendations for choosing the parameters of the auxiliary discharge power supply to ensure the stability of radiation pulses in the pulse-periodic structure of output signals of optoelectronic systems were given. [ABSTRACT FROM AUTHOR]

This article proposes a dual space vector PWM control technique for a three-phase to fivephase quasi Z-source direct matrix converter (QZSDMC). The proposed circuit consists of a quasi-impedance source network along with a five-phase traditional matrix converter. With the observation of bidirectional operating capability and the utilization of shoot-through duty ratio, the proposed converter can ensure both buck and boost operations. This converter overcomes the voltage transfer ratio restriction and poor voltage regulation of the traditional matrix converter. Also, this converter ensures continuous input current with an absence of input LC filter components. The proposed direct AC to AC power converter gives an alternate solution to the multiphase drive system instead of the traditional voltage source inverter. The developed dual space vector PWM control technique for three-phase to five-phase voltage conversion is derived from the basic space vector PWM approach. The proposed dual space vector PWM technique utilizes 90 active states and 3 zero vector states among 243 switching states. The QZSDMC has been analysed with a dual space vector PWM approach along with the distribution of shootthrough state in the zero vector. The proposed topology along with the control strategy has been simulated using MATLAB/Simulink environment. [ABSTRACT FROM AUTHOR]

One of the main problems for flying capacitor multilevel (FCML) inverter is the higher value of total harmonic distortion (THD) with number of capacitors and switching devices. No step has been taken to consider sinusoidal pulse width modulation (SPWM) and third harmonic injection pulse width modulation (THIPWM) techniques with carrier phase disposition (PD) for THD analysis of 13-level FCML inverter. This paper proposes the comparative study of these two PWM techniques with carrier PD to obtain the lowest THD for inverter. The proposed system is simulated and analyzed in MATLAB/SIMULINK environment. The results from this analysis show the optimal value of amplitude and frequency modulation index in which lowest THD is obtained for FCML.

This paper deals with the inverter controller utilizing Sinusoidal Pulse Width Modulation (SPWM) to control the three-phase off-grid system’s modulation index. Particle Swarm Optimization (PSO) algorithm has been used to improve the controller performance by automatically finding its parameters in order to reduce the error in the proportional Integral (PI) controller. The system is included with photovoltaic and battery storage to supply power to a local load of 3 kW. Control was on voltage by measuring load voltage to be feedback to the controller to evaluate the best modulation index value needed for SPWM pulse. Therefore, the inverter is based on load change to adjust the system to be stable at any time because of the proportional and integral controller (PI). The PI Controller provides better results than a system without a controller, especially when applying faults in phase. This shows how the robustness of the controller is. This model is explained in detail. All simulation results show that the modulation index controller acts so that total harmonic distortion (THD) is less after using the optimal PI controller parameters.

Reliability of the multilevel inverters (MLIs) is one of the most important concerns in industrial applications, mainly due to the semiconductor devices. Whenever a fault occurs in one of the switches of the inverter, it leads to abnormal conditions and can also cause serious damage to the equipment connected to the multilevel inverter. In this paper, a recently proposed nine-level Packed-E-Cell (PEC) multilevel inverter topology is investigated for its fault-tolerant capability and improved reliability. The analysis is carried out for a reduced device multilevel inverter topology that, due to a lack of redundant states, cannot tolerate switch failures. The fault-tolerant (FT) topology provides additional redundant states in the switching sequence of the existing topology. The work in this paper presents Packed-E-Cell MLI modified for fault tolerance against single-switch open-circuit faults. The modified FT topology inherently achieves self-voltage balance in the DC-link capacitors. Nearest Level Control(NLC) is used as the modulation strategy for generating the desired switching pulses. Simulation results are obtained in MATLAB/Simulink for the conditions prior to the fault, during the fault and post fault, and results are discussed. Experimental verification of the modified FT topology is also performed, in order to validate its effectiveness. [ABSTRACT FROM AUTHOR]

The given research article represents the voltage-fed quasi Z source direct matrix converter (QZSDMC) for three-phase to K-phase power conversion with the maximum constant boost control-modulation technique. To reduce the switching losses and to achieve high efficiency, a new PWM technique has been proposed. The technique controls both the rectifier side and inverter side of the matrix converter equivalent circuit. Compared with the ZSDMC, the voltage-fed QZSDMC has less effective components, is compact in size, and has higher efficiency and a wide range of controlled buck-boost operations. The proposed modulation technique provides lower harmonic contents in the output, poor switching current stresses, lower switching voltages and maximum voltage gain under the given modulation index. This paper discussed the relationship of the voltage gain to the modulation index and the relationship of the switching voltage stresses to the voltage gain have been analyzed. The proposed modulation technique was verified by simulation using MATLAB and also validated experimentally. [ABSTRACT FROM AUTHOR]

There is currently a growing interest in efficient power generation and transformation without increasing the cost and complexity of a system. One type of transformation is the conversion of energy from a direct current to an alternating current, which is used in various applications, for example, in photovoltaic systems. One of the elementary components of these systems is the inverter. However, there are several drawbacks in the design of these systems, such as the energy balance between their semiconductor devices. Therefore, it is important to study alternatives to balance the energy and thus achieve a positive impact on both the economic and reliability aspects of the system. This article deals with the study, design, and implementation of the modification of a modulation technique with reconstructed modulating signals, which aims to ensure the energy balance in each cell of a multilevel inverter and, at the same time, present better results concerning the different parameters of comparison established, such as harmonic distortion, percentage of unbalance, percentage of use of digital resources, and power transferred to the load. [ABSTRACT FROM AUTHOR]

Recently, single-stage boost inverter topologies like Z-Source Inverter (ZSI), Switched Boost Inverter (SBI) and quasi-Switched Boost Inverter (qSBI) are gaining more attention in Renewable Energy Source (RES) applications. This paper proposes a dual dc source-based qSBI (DqSBI) topology which can be used as a micro-inverter for integrating various RES like solar photovoltaic, fuel cell etc. This study explains the principle of operation, design and steady-state analysis of the DqSBI topology. It also presents a performance comparison with conventional dc-dc boosted inverter and SBI topologies. The proposed inverter topology can achieve high voltage gain with low voltage stress across the switch, capacitor and diode. By using shoot through duty ratio, this topology provides a 110 V (rms) ac from a 324 V dc link voltage. The dc link voltage is obtained from a dc source of 36 V. The THD in the output voltage is 4.13%. Due to the reduced THD, the filter size and cost of the entire system are reduced. A 200-W laboratory prototype is developed to verify the theoretical concepts with an output voltage of 110 V (rms)/50 Hz. The Simple Boost Control (SBC) modulation strategy is used to generate shoot through and non-shoot through pulses. The modulation control algorithm is implemented using Spartan −3E Field Programmable Gate Array (FPGA) processor. [ABSTRACT FROM AUTHOR]

In order to improve the performance of fiber network, not only higher quality factor and minimum bit error rate required but also the role of ER cannot be neglected. Since, only the treatment of linear and nonlinear impairments are not sufficient, there must be a need of degradation of signal leakage through the optical fiber networks related to the extinction ratio. Also, the extinction ratio is the significant parameter to measure the optical signal quality of the transmitter and receiver. Therefore, this research is to investigate that how much the effect of ER on the performance of fiber optic networks based on Optisystem 0.17 designed with EDFA and DWDM technology. [ABSTRACT FROM AUTHOR]

Objective: We assessed the diagnostic utility of the occurrence rate of high-frequency oscillations and modulation index (MI) from intraoperative electrocorticography (ioECoG) in determining the extent of epileptogenicity in mesial temporal lobe epilepsy (TLE) with hippocampal sclerosis (HS).Methods: We enrolled 17 patients who underwent selective amygdalohippocampectomy (SelAH) for TLE due to HS. We analyzed the occurrence rate of ripples (80-200 Hz) and fast ripples (200-300 Hz); and MI between ripples and 3-4 Hz (MIRipples/3-4 Hz) and fast ripples and 3-4 Hz (MIFRs/3-4 Hz) from the amygdala, hippocampus, and lateral temporal lobe (LTL) pre-SelAH and the LTL post-SelAH, and subsequently categorized the patients into good and poor seizure outcome groups. We compared the occurrence rates and MIs over each region of interest between both groups. Receiver operating characteristic analysis was used to identify the most optimal indicator to predict poor surgical outcomes.Results: In the poor seizure outcome group, an increase in the occurrence rate of ripples was seen in the hippocampus and LTL pre-SelAH and the LTL post-SelAH. The MIRipples/3-4 Hz from the LTL pre-SelAH was the most indicative factor of poor outcome.Conclusions: High occurrence rate of ripples and MIRipples/3-4 Hz from the LTL showed wide epileptogenicity in TLE patients with poor seizure outcomes after SelAH. Our data suggest that the analysis of the occurrence rate of HFOs and MIHFOs/3-4 Hz from ioECoG, especially from the LTL, can indicate the distribution of epileptogenicity in TLE with HS. [ABSTRACT FROM AUTHOR]

The parameter analysis of satellite tracking, telemetry, and command signal is necessary for space situational awareness. Unified S-Band (USB) waveforms are widely used in space missions. As a crucial parameter of the USB waveform, the modulation index influences the power distribution and spectrum characteristics of the waveform. This paper proposes two novel blind estimation methods of the modulation index based on spectral analysis. The equations for estimating the modulation index are constructed by the relation between the spectral characteristics and the Fourier transform of signal. The theoretical analysis of the estimation error of the methods is derived. The factors that influence the estimation error are investigated by Monte Carlo simulation, and an actual Geostationary Earth Orbit satellite signal is used to verify the methods. The proposed methods have lower complexity than existing methods, while also providing more than 10 times accuracy improvement at low signal-to-noise ratios. Suggestions for the application of the proposed methods to different scenarios are also provided. [ABSTRACT FROM AUTHOR]