Frequency response analysis under faults in weak power systems

The renewable energy sources (RESs) projects are solutions with environmental benefits that are changing the traditional power system operation and concept. Transient stability analysis has opened new research trends to guarantee a secure operation high penetration. Problems such as frequency fluctuations, decoupling between generator angular speed, network frequency fluctuation and kinetic energy storing absence are the main non-conventional RESs penetration in power systems. This paper analyzes short-circuit influence on frequency response, focusing on weak distribution networks and isolated, to demonstrate relevance in frequency stability. A study case considered a generation outage and a load input to analyze frequency response. The paper compares frequency response during a generation outage with a short-circuit occurrence. In addition, modular value and angle generator terminal voltage affectation by electric arc and network ratio R⁄X, failure type influence in power delivered behavior, considering fault location, arc resistance and load. The arc resistance is defined as an added resistance that appears during failure and influences voltage modulus and angle value results showing that intermittent non-conventional RES participation can lead to frequency fluctuations. Results showed that arc resistance, type of failure, location and loadability determine the influence of frequency response factors in weak power systems.

Interannual temperature variability is a principal driver of low-frequency fluctuations in marine fish populations

Marine fish populations commonly exhibit low-frequency fluctuations in biomass that can cause catch volatility and thus endanger the food and economic security of dependent coastal societies. Such variability has been linked to fishing intensity, demographic processes and environmental variability, but our understanding of the underlying drivers remains poor for most fish stocks. Our study departs from previous findings showing that sea surface temperature (SST) is a significant driver of fish somatic growth variability and that life-history characteristics mediate population-level responses to environmental variability. We use autoregressive models to simulate how fish populations integrate SST variability over multiple years depending on fish life span and trophic position. We find that simulated SST-driven population dynamics can explain a significant portion of observed low-frequency variability in independent observations of fisheries landings around the globe. Predictive skill, however, decreases with increasing fishing pressure, likely due to demographic truncation. Using our modelling approach, we also show that increases in the mean and variance of SST could amplify biomass volatility and lessen its predictability in the future. Overall, biological integration of high-frequency SST variability represents a null hypothesis with which to explore the drivers of low-frequency population change across upper-trophic marine species.

Investigation of changes in the activity and function of dry eye-associated brain regions using the amplitude of low frequency fluctuations(ALFF)method

Objective: The local characteristics of spontaneous brain activity in patients with dry eye (DE) and its relationship with clinical characteristics were evaluated using the amplitude of low-frequency fluctuations (ALFF) method. Methods: A total of 27 patients with DE (10 males and 17 females) and 28 healthy controls (HCs) (10 males and 18 females) were recruited, matched according to sex, age, weight, and height, classified into the DE and HC groups, and examined using functional magnetic resonance imaging scans. Spontaneous brain activity changes were recorded using ALFF technology. Data were recorded and plotted on the receiver operating characteristic curve, reflecting changes in activity in different brain areas. Finally, Pearson correlation analysis was used to calculate the potential relationship between spontaneous brain activity abnormalities in multiple brain regions and clinical features in patients with DE. GraphPad Prism 8 (GraphPad Software, Inc.) was used to analyze the linear correlation between the Hospital Anxiety and Depression Scale and ALFF value. Results: Compared with HCs, the ALFF values of patients with DE were decreased in the right middle frontal gyrus/right inferior orbitofrontal cortex, left triangle inferior frontal gyrus, left middle frontal gyrus, and right superior frontal gyrus. In contrast, the ALFF value of patients with DE was increased in the left calcarine. Conclusion: There are significant fluctuations in the ALFF value of specific brain regions in patients with DE versus HCs. This corroborates previous evidence showing that the symptoms of ocular surface damage in patients with DE are related to dysfunction in specific brain areas.

Altered Local Brain Amplitude of Fluctuations in Patients With Myotonic Dystrophy Type 1

This study is aimed at investigating the characteristics of the spontaneous brain activity in patients with myotonic dystrophy type 1 (DM1). A total of 18 patients with DM1 and 18 healthy controls (HCs) were examined by resting-state functional MRI. Combined methods include amplitude of low-frequency fluctuations (ALFFs), the fractional amplitude of low-frequency fluctuations (fALFFs), and Wavelet transform-based ALFFs (Wavelet-ALFFs) with standardization, percent amplitude of fluctuation (PerAF) with/without standardization were applied to evaluate the spontaneous brain activity of patients with DM1. Compared with HCs, patients with DM1 showed decreased ALFFs and Wavelet-ALFFs in the bilateral precuneus (PCUN), angular gyrus (ANG), inferior parietal, but supramarginal and angular gyri (IPL), posterior cingulate gyrus (PCG), superior frontal gyrus, medial (SFGmed), middle occipital gyrus (MOG), which were mainly distributed in the brain regions of default mode network (DMN). Decreased ALFFs and Wavelet-ALFFs were also seen in bilateral middle frontal gyrus (MFG), inferior frontal gyrus, opercular part (IFGoperc), which were the main components of the executive control network (ECN). Patients with DM1 also showed decreased fALFFs in SFGmed.R, the right anterior cingulate and paracingulate gyri (ACGR), bilateral MFG. Reduced PerAF in bilateral PCUN, ANG, PCG, MOG, and IPLL as well as decreased PerAF without standardization in PCUNR and bilateral PCG also existed in patients with DM1. In conclusion, patients with DM1 had decreased activity in DMN and ECN with increased fluctuations in the temporal cortex and cerebellum. Decreased brain activity in DMN was the most repeatable and reliable with PCUN and PCG being the most specific imaging biomarker of brain dysfunction in patients with DM1.

Inward diffusion driven by low frequency fluctuations in self-organizing magnetospheric plasma

The new findings for dynamic process of inward diffusion in the magnetospheric plasma are reported on the RT-1 experiment: (i) The evolution of local density profile in the self-organized process has been analysed by the newly developed tomographic reconstruction applying a deep learning method. (ii) The impact of neutral-gas injection excites low-frequency fluctuations, which continues until the peaked density profile recovers. The fluctuations have magnetic components (suggesting the high-beta effect) which have two different frequencies and propagation directions. The phase velocities are of the order of magnetization drifts, and both the velocities and the intensities increase in proportion to the electron density. The self-regulating mechanism of density profile works most apparently in the naturally made confinement system, magnetosphere, which teaches the basic physics of long-lived structures underlying every stationary confinement scheme.

Improvement of simulated nuclear quadrupole resonance signals from explosive detection via a Red-Pitaya board

In Nuclear quadrupole resonance (NQR), the interaction of the nuclear magnetic moments of quadrupolar nuclei (spin greater than 1/2) with the electric field gradient of the surrounding molecular orbitals produces an energy splitting. Because the resonant frequency is very specific to the molecular structure, the NQR can be used to detect explosive materials very accurately and it is extremely useful for detecting modern bombs whose containers made from plastics and wood instead of metals. However, NQR signals are generally very weak so they are difficult to be detected. Recently, Red-Pitaya boards, a Field Programmable Gate Array (FPGA) on Single Board Computers, have been being utilized in many electronic applications due to their small size and low cost. Since the boards can generate and acquire radio frequency signals, they can be taken as the console of portable bomb detectors. In this work, we study an improvement of the NQR signals of an explosive, ammonium nitrate with a resonant frequency of 423.6 kHz, acquired by using a Red-Pitaya board (STEMlab 125-14). To construct the NQR signals, we simulate free induction decay (FID) signals (exponential decay of sinusoidal functions) and add real measured noises from an input port of the Red-Pitaya board. To mimic real situations, the FID amplitude is varied, frequency fluctuations and phase shifts are added. The results show that averaging of signals from repeat measurements can improve the signals in all cases. To distinguish the signals from the noises, a minimal number of measurements is required. This necessary number of repeat measurements increases with frequency fluctuations and phase shifts but decreases when the FID amplitude grows.