Identification of dominant propagation paths based on sub-synchronous oscillation using branch oscillation energy distribution coefficient

The large-scale integration of wind power into the power grid can cause a new type of sub-synchronous power oscillation, different from traditional thermal power generation. The oscillation energy will spread extensively in the grid, causing power oscillation and even grid-cascading events. To address this issue, this article proposes a method for quantitatively analyzing the propagation characteristics of oscillation energy based on branch oscillation energy. Firstly, analyzing the oscillation energy shared by different branches in the network based on transient energy function. Next, a method is proposed to identify the dominant propagation path of sub-synchronous oscillation by defining the oscillation energy of branches under the dominant oscillation mode and the oscillation energy distribution coefficient of each branch. The oscillation partition set formed by the dominant propagation path can be used to locate the high-risk oscillation area of the system. Finally, the effectiveness of the method proposed in this paper for studying the wide-area propagation characteristics of sub-synchronous oscillations was verified through time-domain simulation analysis

Modified Quasi-Steady State Model of DC System for Transient Stability Simulation under Asymmetric Faults

As using the classical quasi-steady state (QSS) model could not be able to accurately simulate the dynamic characteristics of DC transmission and its controlling systems in electromechanical transient stability simulation, when asymmetric fault occurs in AC system, a modified quasi-steady state model (MQSS) is proposed. The model firstly analyzes the calculation error induced by classical QSS model under asymmetric commutation voltage, which is mainly caused by the commutation voltage zero offset thus making inaccurate calculation of the average DC voltage and the inverter extinction advance angle. The new MQSS model calculates the average DC voltage according to the actual half-cycle voltage waveform on the DC terminal after fault occurrence, and the extinction advance angle is also derived accordingly, so as to avoid the negative effect of the asymmetric commutation voltage. Simulation experiments show that the new MQSS model proposed in this paper has higher simulation precision than the classical QSS model when asymmetric fault occurs in the AC system, by comparing both of them with the results of detailed electromagnetic transient (EMT) model of the DC transmission and its controlling system

Direct arene C-H fluorination with 18F- via organic photoredox catalysis

Positron emission tomography (PET) plays key roles in drug discovery and development, as well as medical imaging. However, there is a dearth of efficient and simple radiolabeling methods for aromatic C-H bonds, which limits advancements in PET radiotracer development. Here, we disclose a mild method for the fluorine-18 (18F)-fluorination of aromatic C-H bonds by an [18F]F- salt via organic photoredox catalysis under blue light illumination. This strategy was applied to the synthesis of a wide range of 18F-labeled arenes and heteroaromatics, including pharmaceutical compounds. These products can serve as diagnostic agents or provide key information about the in vivo fate of the labeled substrates, as showcased in preliminary tracer studies in mice

Multi-contrast atherosclerosis characterization (MATCH) of carotid plaque with a single 5-min scan: technical development and clinical feasibility

BACKGROUND: Multi-contrast weighted imaging is a commonly used cardiovascular magnetic resonance (CMR) protocol for characterization of carotid plaque composition. However, this approach is limited in several aspects including low slice resolution, long scan time, image mis-registration, and complex image interpretation. In this work, a 3D CMR technique, named Multi-contrast Atherosclerosis Characterization (MATCH), was developed to mitigate the above limitations. METHODS: MATCH employs a 3D spoiled segmented fast low angle shot readout to acquire data with three different contrast weightings in an interleaved fashion. The inherently co-registered image sets, hyper T1-weighting, gray blood, and T2-weighting, are used to detect intra-plaque hemorrhage (IPH), calcification (CA), lipid-rich necrotic core (LRNC), and loose-matrix (LM). The MATCH sequence was optimized by computer simulations and testing on four healthy volunteers and then evaluated in a pilot study of six patients with carotid plaque, using the conventional multi-contrast protocol as a reference. RESULTS: On MATCH images, the major plaque components were easy to identify. Spatial co-registration between the three image sets with MATCH was particularly helpful for the reviewer to discern co-existent components in an image and appreciate their spatial relation. Based on Cohen’s kappa tests, moderate to excellent agreement in the image-based or artery-based component detection between the two protocols was obtained for LRNC, IPH, CA, and LM, respectively. Compared with the conventional multi-contrast protocol, the MATCH protocol yield significantly higher signal contrast ratio for IPH (3.1 ± 1.3 vs. 0.4 ± 0.3, p < 0.001) and CA (1.6 ± 1.5 vs. 0.7 ± 0.6, p = 0.012) with respect to the vessel wall. CONCLUSIONS: To the best of our knowledge, the proposed MATCH sequence is the first 3D CMR technique that acquires spatially co-registered multi-contrast image sets in a single scan for characterization of carotid plaque composition. Our pilot clinical study suggests that the MATCH-based protocol may outperform the conventional multi-contrast protocol in several respects. With further technical improvements and large-scale clinical validation, MATCH has the potential to become a CMR method for assessing the risk of plaque disruption in a clinical workup

Escalating morphine dosing in HIV-1 Tat transgenic mice with sustained Tat exposure reveals an allostatic shift in neuroinflammatory regulation accompanied by increased neuroprotective non-endocannabinoid lipid signaling molecules and amino acids

BACKGROUND: Human immunodeficiency virus type-1 (HIV-1) and opiates cause long-term inflammatory insult to the central nervous system (CNS) and worsen disease progression and HIV-1-related neuropathology. The combination of these proinflammatory factors reflects a devastating problem as opioids have high abuse liability and continue to be prescribed for certain patients experiencing HIV-1-related pain. METHODS: Here, we examined the impact of chronic (3-month) HIV-1 transactivator of transcription (Tat) exposure to short-term (8-day), escalating morphine in HIV-1 Tat transgenic mice that express the HIV-1 Tat protein in a GFAP promoter-regulated, doxycycline (DOX)-inducible manner. In addition to assessing morphine-induced tolerance in nociceptive responses organized at spinal (i.e., tail-flick) and supraspinal (i.e., hot-plate) levels, we evaluated neuroinflammation via positron emission tomography (PET) imaging using the [¹⁸F]-PBR111 ligand, immunohistochemistry, and cytokine analyses. Further, we examined endocannabinoid (eCB) levels, related non-eCB lipids, and amino acids via mass spectrometry. RESULTS: Tat-expressing [Tat(+)] transgenic mice displayed antinociceptive tolerance in the tail withdrawal and hot-plate assays compared to control mice lacking Tat [Tat(-)]. This tolerance was accompanied by morphine-dependent increases in Iba-1 +/- 3-nitrotryosine immunoreactive microglia, and alterations in pro- and anti-inflammatory cytokines, and chemokines in the spinal cord and striatum, while increases in neuroinflammation were absent by PET imaging of [¹⁸F]-PBR111 uptake. Tat and morphine exposure differentially affected eCB levels, non-eCB lipids, and specific amino acids in a region-dependent manner. In the striatum, non-eCB lipids were significantly increased by short-term, escalating morphine exposure, including peroxisome proliferator activator receptor alpha (PPAR-alpha) ligands N-oleoyl ethanolamide (OEA) and N-palmitoyl ethanolamide (PEA), as well as the amino acids phenylalanine and proline. In the spinal cord, Tat exposure increased amino acids leucine and valine, while morphine decreased levels of tyrosine and valine but did not affect eCBs or non-eCB lipids. CONCLUSION: Overall results demonstrate that 3 months of Tat exposure increased morphine tolerance and potentially innate immune tolerance evidenced by reductions in specific cytokines (e.g., IL-1alpha, IL-12p40) and microglial reactivity. In contrast, short-term, escalating morphine exposure acted as a secondary stressor revealing an allostatic shift in CNS baseline inflammatory responsiveness from sustained Tat exposure

The stochastic stability and H∞‐fuzzy control of stochastic bifurcation of a doubly‐fed induction generator

Abstract Considering the dynamic behavior of doubly‐fed induction generators (DFIGs) under the influence of random factors, this paper not only analyzes the phenomenon of stochastic instability and bifurcation of a DFIG dynamic variable in its random space when they are affected by environmental noise, but also proposes a method based on the Tkagi–Sugneo (T–S) fuzzy control strategy to control its stochastic bifurcation. First, a four‐dimensional stochastic dynamic DFIG model is established by using multiplicative white noise to simulate the influence of environmental noise on electrical variables, and stochastic central manifold theory is used to reduce the dimensionality of a planar model in the bifurcation neighborhood. Then, the stochastic stability of the model is investigated based on singular boundary theory, while the steady‐state probability density of the stochastic DFIG is determined using the Fokker–Plank–Kolmogorov equation to obtain the location and probability density of its stochastic P‐bifurcation. Finally, the influence of stochastic bifurcation behavior is eliminated by H∞‐fuzzy output feedback control. The numerical simulation results indicate that the location and probability of stochastic bifurcation in a DFIG will vary with the change in noise intensity, and the bifurcation parameter values and stochastic stability domain are obtained. The harm caused by random factors can be solved based on H∞‐fuzzy output feedback, which provides a theoretical basis for the stable operation of the DFIG system

High-Precision Intelligent Identification of Complex Power Quality Disturbances Based on Improved KST and CNNs

With the widespread usage of power electronics and other non-linear loads, the power quality (PQ) issue in the power grid is becoming increasingly prominent, threatening the power system&#x2019;s stability. As a result, accurate identification and categorization of complicated power quality disturbances (PQD) is a necessity and critical to mitigating grid pollution. In this paper, a new approach for high-precision intelligent recognition of complex PQDs based on improved Kaiser window s-transform (IKST) and convolutional neural network (CNN) (KSTCNN) is proposed. Firstly, KST is applied for PQD time-frequency (TF) signal detection, and then the control function is modified to adjust the shape of the KS-window, and its parameters can be automatically optimized according to the maximum energy concentration to satisfy the various TF signal detection requirements. Then, the CNN architecture is improved using a SimAM attention mechanism that assigns higher weights to the neurons conveying useful PQD feature information and suppresses the surrounding neurons with irrelevant information. Then, an improved hierarchical 2D dense network structure is proposed to achieve the feature extraction and high-precision recognition of PQDs. Then, the results of simulation experiments demonstrate that the classification accuracy of the proposed KSTCNN is better than other compared methods under different noise levels. Finally, in the practical hardware platform, the recognition accuracy of PQDs reaches 97.93, and the real-time detection time is 0.11s, which further verifies the practicality of the KSTCNN and meets the requirement of real-time recognition of complex PQDs