The genus Echinochloa (Poaceae) includes orphan crops and important agricultural weeds. Here, we assembled the complete chloroplast genome of a diploid Echinochloa species (E. haploclada). The ...chloroplast genome is 139,844 bp in length, which includes a large single copy region (81,893 bp), a small single copy region (12,533 bp) and two separated inverted repeat regions (45,418 bp). A total of 119 unique genes were annotated, consisting of 83 protein-coding genes, 32 tRNA genes and 4 rRNA genes. Hexaploid E. crus-galli, one of the most serious weeds worldwide, was derived from a hybrid between tetraploid E. oryzicola and an unknown diploid species. Based on chloroplast genomes of eight Echinochloa species (varieties), the phylogenetic analysis showed that E. crus-galli clustered firstly with diploid E. haploclada rather than tetraploid E. oryzicola, supporting previous assumption that E. oryzicola is the paternal donor of E. crus-galli.
Aiming to improve the performance of human speech emotion recognition (SER), the existing work has made great progress based on the popular mel-scale frequency cepstral coefficient (MFCC). However, ...the existing work rarely pays attention to the low-level emotion related features in MFCC, such as the underlying interactive relations. In this letter, we propose a novel multi-level attention network (MLAnet), which contains a multi-scale low-level feature (MLF) extractor and a multi-unit attention (MUA) module. Within the MLF extractor, we minimize the task-irrelevant information which harms the performance of SER by applying the attention mechanism. Since the features extracted by the MLF extractor contain rich domain-specific emotion information, we further present a MUA module to simultaneously weight the features in terms of time, frequency and channel dimensions. In this way, the discriminative emotion features in different dimensions can be extracted by corresponding weighting blocks. Experimental results on two benchmark datasets demonstrate that the proposed method outperforms other state-of-the-art approaches.
Accident processing is the most important link of the scheduling of daily monitoring. The improvement of intelligent level is of great significance for improving the efficiency of accident processing ...scheduling, shortening the time of accident processing and preventing further deterioration of accidents. According to features of accident processing scheduling, this paper puts forward an integrated framework of aid decision-making of online accident processing based on large power grid, and carries out a study from five aspects, namely integrated information support platform, risk perception in advance, online fault diagnosis, aid decision-making afterwards and visual display, so as to conduct real-time tracking on operating state of power grid, eliminate potential safety hazards of power grid and upgrade power grid from “manual analysis” scheduling to “intelligent analysis” scheduling.
Abstract
Many studies showed that anatomical connectivity supports both anatomical and functional hierarchies that span across the primary and association cortices in the cerebral cortex. Even though ...a structure–function relationship has been indicated to uncouple in the association cortex, it is still unknown whether anatomical connectivity can predict functional activations to the same degree throughout the cortex, and it remains unclear whether a hierarchy of this connectivity–function relationship (CFR) exists across the human cortex. We first addressed whether anatomical connectivity could be used to predict functional activations across different functional domains using multilinear regression models. Then, we characterized the CFR by predicting activity from anatomical connectivity throughout the cortex. We found that there is a hierarchy of CFR between sensory–motor and association cortices. Moreover, this CFR hierarchy was correlated to the functional and anatomical hierarchies, respectively, reflected in functional flexibility and the myelin map. Our results suggest a shared hierarchical mechanism in the cortex, a finding which provides important insights into the anatomical and functional organizations of the human brain.
•A simple but effective spatial filter is proposed to obtain the SLCM.•An enhanced time difference method is proposed to obtain the TLCM.•The STLCM is defined by multiplying the SLCM and TLCM.•An ...enhanced threshold segmentation method is proposed.
Infrared (IR) moving point target detection is an important technique in many onboard applications such as remote sensing, IR searching and tracking (IRST) and early warning system. However, it has been facing great challenges due to the complicated background and the limited processing resources in the onboard system. In this paper, a novel spatial-temporal local contrast method is proposed for moving point target detection in space-based IR imaging system. Firstly, a simple but effective spatial filter based on multi-direction filtering fusion is designed to obtain the spatial local contrast map (SLCM). An enhanced time domain difference method is also proposed to obtain the temporal local contrast map (TLCM). Then, the spatial–temporal local contrast map (STLCM) is obtained by multiplying the newly defined SLCM and TLCM. Finally, an enhanced threshold segmentation method is proposed for target detection and false alarm suppression. To verify the performance of our detection algorithm, we conduct several groups of experiments on four different real IR image sequences with simulated targets. The final experimental results show that our algorithm significantly outperforms other methods in terms of background suppression and target detection.
•Game theory solves the problem of new energy power generation equipment capacity planning.•Electric vehicles connect to hybrid power generation systems as auxiliary equipment to replace energy ...storage batteries.•Establish a representative days selection model based on mixed integer multi-objective linear programming (MIMLP).•Consider the uncertainty of electric vehicle traffic attributes.
In recent years, hybrid power systems (HPSs) with renewable energy sources, such as wind power and photovoltaic (PV) power, have been used as one of the most effective methods to address resource shortages and environmental pollution. In this paper, a model based non-cooperative game theory is developed to optimize the capacity configuration problem with wind power, PV power, and electric vehicles (EVs). The model is integrated with economic factors, such as electricity sales income, investments, and power supply reliability costs. An iterative search algorithm is used to solve the proposed game model, and the particle swarm optimization algorithm was used to optimize the income of each player. Mixed integer multi-objective linear programming (MIMLP) is used to establish the representative days selection model of resources and load demands. To verify the rationality of the model, the grid-connected hybrid power generation system with different game participants and line transmission capacities was studied. Furthermore, the representative days results of the daily load rate and peak valley ratio generated by MIMLP are compared with those obtained using k-means clustering and a scenario reduction method. The results reveal that the proposed model and related strategies can realize a reasonable allocation of resources and effectively improve the operation economy of power systems.
With rapid increases in incidence, diverse subtypes, and complicated etiologies, kidney disease remains a global public health problem. Iron, as an essential trace element, has pleiotropic effects on ...renal function and the progression of kidney diseases. A two-sample Mendelian randomization (MR) analysis was implemented to determine the potential causal effects between systemic iron status on different kidney diseases. Systemic iron status was represented by four iron-related biomarkers: serum iron, ferritin, transferrin saturation (TfSat), and total iron binding capacity (TIBC). For systemic iron status, 163,511, 246,139, 131,471, and 135,430 individuals were included in the genome-wide association study (GWAS) of serum iron, ferritin, TfSat, and TIBC, respectively. For kidney diseases, 653,143 individuals (15,658 cases and 637,485 controls), 657,076 individuals (8160 cases and 648,916 controls), and 659,320 individuals (10,404 cases and 648,916 controls) were included for immunoglobulin A nephropathy (IgAN), acute kidney disease (AKD), and chronic kidney disease (CKD), respectively. Our MR results showed that increased serum iron odds ratio (OR): 1.10; 95% confidence interval (95% CI): 1.04, 1.16; p < 0.0042, ferritin (OR: 1.30; 95% CI: 1.14, 1.48; p < 0.0042), and TfSat (OR: 1.07; 95% CI: 1.04, 1.11; p < 0.0042) and decreased TIBC (OR: 0.92; 95% CI: 0.88, 0.97; p < 0.0042) were associated with elevated IgAN risk. However, no significant associations were found between systemic iron status and AKD or CKD. In our MR study, the genetic evidence supports elevated systemic iron status as a causal effect on IgAN, which suggests a potential protective effect of iron chelation on IgAN patients.
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