An Novel Six-Segment Modulation Strategy for Three-Phase Isolated PFC Converter

A three-phase isolated rectifier features bidirectional power conversion and galvanic isolation, and is attractive as a high-efficiency energy conversion system. However, when a conventional modulation is applied to this rectifier, the excessive DC-link current ripple will result in increasing switching losses or the size of DC-link inductance, which is not cost-effective. In order to effectively reduce the current ripple, this paper proposes a “six segment” PWM (Pulse Width Modulation) strategy. It can significantly reduce the current ripple compared with the existing “eight segment” PWM strategy. Meanwhile, the current quality of the grid is improved. Finally, the experimental tests were carried out. The experimental results reveal that, compared to the traditional “eight segment” PWM, the dc-side current ripple significantly reduced from 2 A to 0.8 A, the total harmonic distortion significantly reduced from 5.69% to 2.41%, and the power factor increased from 0.87 to 0.99, verifying the effectiveness of the proposed method

A Novel Circulating Current Suppression for Paralleled Current Source Converter Based on Virtual Impedance Concept

The circulating current is one of the important issues for parallel converters. It affects the system stable operation and degrades the power quality. In order to reduce the circulating current of the parallel converter and reduce the harmonic pollution to the power grid, a new circulating current suppression strategy is proposed for the parallel current source converter without any communication line. This strategy is able to realize the current sharing between parallel modules by changing the external characteristics of the parallel modules to thus suppress the circulating current among the parallel current source converters. The proposed control strategy adopts DC-side droop control and AC-side virtual impedance control. The DC-side droop control is used to generate the reference voltage of each parallel module, while the AC-side virtual impedance is used to the circulating current suppression. We performed a time domain test of the parallel converter, and the results show that the proposed control strategy reduced the RMS circulating current of the parallel converter by 50% and effectively reduced the grid-side current THD while ensuring the stable operation of the converter. The effectiveness of the proposed control strategy was, therefore, verified

Optimized Control Strategy for Photovoltaic Hydrogen Generation System with Particle Swarm Algorithm

Distributed generation is a vital component of the national economic sustainable development strategy and environmental protection, and also the inevitable way to optimize energy structure and promote energy diversification. The power generated by renewable energy is unstable, which easily causes voltage and frequency fluctuations and power quality problems. An adaptive online adjustment particle swarm optimization (AOA-PSO) algorithm for system optimization is proposed to solve the technical issues of large-scale wind and light abandonment. Firstly, a linear adjustment factor is introduced into the particle swarm optimization (PSO) algorithm to adaptively adjust the search range of the maximum power point voltage when the environment changes. In addition, the maximum power point tracking method of the photovoltaic generator set with direct duty cycle control is put forward based on the basic PSO algorithm. Secondly, the concept of recognition is introduced. The particles with strong recognition ability directly enter the next iteration, ensuring the search accuracy and speed of the PSO algorithm in the later stage. Finally, the effectiveness of the AOA-PSO algorithm is verified by simulation and compared with the traditional control algorithm. The results demonstrate that the method is effective. The system successfully tracks the maximum power point within 0.89 s, 1.2 s faster than the traditional perturbation and observation method (TPOM), and 0.8 s faster than the incremental admittance method (IAM). The average maximum power point is 274.73 W, which is 98.87 W higher than the TPOM and 109.98 W more elevated than the IAM. Besides, the power oscillation range near the maximum power point is small, and the power loss is slight. The method reported here provides some guidance for the practical development of the system

An open science resource for establishing reliability and reproducibility in functional connectomics

Efforts to identify meaningful functional imaging-based biomarkers are limited by the ability to reliably characterize inter-individual differences in human brain function. Although a growing number of connectomics-based measures are reported to have moderate to high test-retest reliability, the variability in data acquisition, experimental designs, and analytic methods precludes the ability to generalize results. The Consortium for Reliability and Reproducibility (CoRR) is working to address this challenge and establish test-retest reliability as a minimum standard for methods development in functional connectomics. Specifically, CoRR has aggregated 1,629 typical individuals’ resting state fMRI (rfMRI) data (5,093 rfMRI scans) from 18 international sites, and is openly sharing them via the International Data-sharing Neuroimaging Initiative (INDI). To allow researchers to generate various estimates of reliability and reproducibility, a variety of data acquisition procedures and experimental designs are included. Similarly, to enable users to assess the impact of commonly encountered artifacts (for example, motion) on characterizations of inter-individual variation, datasets of varying quality are included

Seamless Switching Control Technology for the Grid-Connected Converter in Micro-Grids

In order to ensure the reliable power supply of the local load in the micro-grid (MG), a seamless switching control technology (SSCT) suitable for grid-connected converter (GCC) is proposed. This technology includes silicon-controlled rectifiers (SCR) forced shutdown control strategy (SCR-FSCS) and three-loop control strategy (TLCS). The SCR-SSCT adjusts the load voltage in real time to form a back voltage at the grid-connected inductor, which greatly reduces the SCR shutdown time and ensures the reliability of local load power supply. The TLCS can easily realize the switching between the current source mode and the voltage source mode of the GCC. An experimental platform is established to carry out the relevant experiments. The experimental results show the rationality and effectiveness of the theoretical analysis and the proposed control technology

Microgrid tie-line power fluctuation mitigation with virtual energy storage

There is a large amount of controllable loads in the microgrid. They can be described as virtual energy storage to participate in microgrid tie-line power fluctuation mitigation. Firstly, in order to meet the grid-connected requirement, the wavelet packet decomposition algorithm is used to smooth the tie-line power fluctuation. Furthermore, in order to prevent overcharge and overdischarge of battery or virtual energy storage, the power allocation between two types of energy storage is implemented equally based on the concept of energy. In addition, the fuzzy control strategy is applied to revise virtual energy storage power based on its SOC (i.e. state-of-charge), so that virtual energy storage can operate within a reasonable work range. Finally, an example is given to verify the effectiveness of the control strategy

Mechanism of intestinal microbiota disturbance promoting the occurrence and development of esophageal squamous cell carcinoma——based on microbiomics and metabolomics

Abstract Esophageal squamous cell carcinoma (ESCC) is a high-risk malignant tumor that has been reported in China. Some studies indicate that gut microbiota disorders can affect the occurrence and development of ESCC, but the underlying mechanism remains unclear. In this study, we aimed to explore the possible underlying mechanisms using microbiomics and metabolomics. Fifty ESCC patients and fifty healthy controls were selected as the study subjects according to sex and age, and fecal samples were collected. 16S rDNA sequencing and LC‒MS were used for microbiomics and nontargeted metabolomics analyses. We found significant differences in the composition of the gut microbiota and metabolites between the ESCC patients and control individuals (P < 0.05). ESCC patients exhibited increased abundances of Fusobacteriaceae and Lactobacillus, increased levels of GibberellinA34 and decreased levels of 12-hydroxydodecanoic acid; these metabolites could be diagnostic and predictive markers of ESCC. An increase in the abundance of Enterobacteriaceae and Lactobacillus significantly reduced the content of L-aspartate and pantothenic acid, which may be involved in the occurrence and development of ESCC by downregulating the expression of proteins in the pantothenate and coenzyme A biosynthesis pathways. An imbalance in the intestinal flora may decrease the number of eosinophils in peripheral blood, resulting in the activation of an inflammatory response and immune dysfunction, leading to ESCC deterioration. We hypothesize that this imbalance in the gut microbiota can cause an imbalance in intestinal metabolites, which can activate carcinogenic metabolic pathways, affect inflammation and immune function, and play a role in the occurrence and development of ESCC

Detecting static and dynamic differences between eyes-closed and eyes-open resting states using ASL and BOLD fMRI.

Resting-state fMRI studies have increasingly focused on multi-contrast techniques, such as BOLD and ASL imaging. However, these techniques may reveal different aspects of brain activity (e.g., static vs. dynamic), and little is known about the similarity or disparity of these techniques in detecting resting-state brain activity. It is therefore important to assess the static and dynamic characteristics of these fMRI techniques to guide future applications. Here we acquired fMRI data while subjects were in eyes-closed (EC) and eyes-open (EO) states, using both ASL and BOLD techniques, at two research centers (NIDA and HNU). Static brain activity was calculated as voxel-wise mean cerebral blood flow (CBF) using ASL, i.e., CBF-mean, while dynamic activity was measured by the amplitude of low frequency fluctuations (ALFF) of BOLD, i.e., BOLD-ALFF, at both NIDA and HNU, and CBF, i.e., CBF-ALFF, at NIDA. We showed that mean CBF was lower under EC than EO in the primary visual cortex, while BOLD-ALFF was higher under EC in the primary somatosensory cortices extending to the primary auditory cortices and lower in the lateral occipital area. Interestingly, mean CBF and BOLD-ALFF results overlapped at the visual cortex to a very small degree. Importantly, these findings were largely replicated by the HNU dataset. State differences found by CBF-ALFF were located in the primary auditory cortices, which were generally a subset of BOLD-ALFF and showed no spatial overlap with CBF-mean. In conclusion, static brain activity measured by mean CBF and dynamic brain activity measured by BOLD- and CBF-ALFF may reflect different aspects of resting-state brain activity and a combination of ASL and BOLD may provide complementary information on the biophysical and physiological processes of the brain

Detecting static and dynamic differences between eyes-closed and eyes-open resting states using ASL and BOLD fMRI.

Resting-state fMRI studies have increasingly focused on multi-contrast techniques, such as BOLD and ASL imaging. However, these techniques may reveal different aspects of brain activity (e.g., static vs. dynamic), and little is known about the similarity or disparity of these techniques in detecting resting-state brain activity. It is therefore important to assess the static and dynamic characteristics of these fMRI techniques to guide future applications. Here we acquired fMRI data while subjects were in eyes-closed (EC) and eyes-open (EO) states, using both ASL and BOLD techniques, at two research centers (NIDA and HNU). Static brain activity was calculated as voxel-wise mean cerebral blood flow (CBF) using ASL, i.e., CBF-mean, while dynamic activity was measured by the amplitude of low frequency fluctuations (ALFF) of BOLD, i.e., BOLD-ALFF, at both NIDA and HNU, and CBF, i.e., CBF-ALFF, at NIDA. We showed that mean CBF was lower under EC than EO in the primary visual cortex, while BOLD-ALFF was higher under EC in the primary somatosensory cortices extending to the primary auditory cortices and lower in the lateral occipital area. Interestingly, mean CBF and BOLD-ALFF results overlapped at the visual cortex to a very small degree. Importantly, these findings were largely replicated by the HNU dataset. State differences found by CBF-ALFF were located in the primary auditory cortices, which were generally a subset of BOLD-ALFF and showed no spatial overlap with CBF-mean. In conclusion, static brain activity measured by mean CBF and dynamic brain activity measured by BOLD- and CBF-ALFF may reflect different aspects of resting-state brain activity and a combination of ASL and BOLD may provide complementary information on the biophysical and physiological processes of the brain