Based on the fixed aspect ratio of 650 for carbon fiber (CF) in hybrid‐fiber‐reinforced concrete (HFRC), this study investigated the effect of polypropylene fiber (PPF) and the aramid fiber (AF) aspect ratio on the mechanical properties of HFRC under the early stage. For this purpose, compressive, splitting tensile, and flexural tests were carried out to obtain the optimal hybridization parameters with respect to the aspect ratio of polypropylene fiber (PPF‐AR) and aramid fiber (AF‐AR) in HFRC. Additionally, the microstructure of HFRC was also examined by scanning electron microscope method to investigate the bond properties between fiber and a concrete matrix. It can be found from the results that the failure modes of overall tests are a ductile failure. The enhancement of tensile strength is attributed to PPF‐AR, whereas AF‐AR mainly tends to improve the performance in compressive and flexural strength. Meanwhile, the aspect ratio of fibers has little effect on the tensile‐to‐compressive‐strength ratio (TC‐R) or the flexural‐to‐compressive‐strength ratio (FC‐R) of early‐stage HFRC.

Background Previous studies have revealed that low frequency repeated transcranial magnetic stimulation (rTMS) on the contralesional primary motor cortex (cM1) is less effective in severe stroke patients with poor neural structural reserve than in patients with highly reserved descending motor pathway. This may be attributed to the fact that secondary motor cortex, especially contralesional dorsal premotor cortex (cPMd), might play an important compensatory role in the motor function recovery of severely affected upper extremity. The main purpose of this study is to compare the effectiveness of low frequency rTMS on cM1 and high frequency rTMS on cPMd in subcortical chronic stroke patients with severe hemiplegia. By longitudinal analysis of multimodal neuroimaging data, we hope to elucidate the possible mechanism of brain reorganization following different treatment regimens of rTMS therapy, and to determine the cut-off of stimulation strategy selection based on the degree of neural structural reserve. Methods/design The study will be a single-blinded randomized controlled trial involving a total of 60 subcortical chronic stroke patients with severe upper limb motor impairments. All patients will receive 3 weeks of conventional rehabilitation treatment, while they will be divided into three groups and receive different rTMS treatments: cM1 low frequency rTMS (n = 20), cPMd high frequency rTMS (n = 20), and sham stimulation group (n = 20). Clinical functional assessment, multimodal functional MRI (fMRI) scanning, and electrophysiological measurement will be performed before intervention, 3 weeks after intervention, and 4 weeks after the treatment, respectively. Discussion This will be the first study to compare the effects of low-frequency rTMS of cM1 and high-frequency rTMS of cPMd. The outcome of this study will provide a theoretical basis for clarifying the bimodal balance-recovery model of stroke, and provide a strategy for individualized rTMS treatment for stroke in future studies and clinical practice. Trial registration Chinese Clinical Trial Registry, ChiCTR1900027399. Registered on 12 Nov 2019, http://www.chictr.org.cn/showproj.aspx?proj=43686.

Background Amino acid property-aware phylogenetic analysis (APPA) refers to the phylogenetic analysis method based on amino acid property encoding, which is used for understanding and inferring evolutionary relationships between species from the molecular perspective. Fast Fourier transform (FFT) and Higuchi’s fractal dimension (HFD) have excellent performance in describing sequences’ structural and complexity information for APPA. However, with the exponential growth of protein sequence data, it is very important to develop a reliable APPA method for protein sequence analysis. Results Consequently, we propose a new method named FFP, it joints FFT and HFD. Firstly, FFP is used to encode protein sequences on the basis of the important physicochemical properties of amino acids, the dissociation constant, which determines acidity and basicity of protein molecules. Secondly, FFT and HFD are used to generate the feature vectors of encoded sequences, whereafter, the distance matrix is calculated from the cosine function, which describes the degree of similarity between species. The smaller the distance between them, the more similar they are. Finally, the phylogenetic tree is constructed. When FFP is tested for phylogenetic analysis on four groups of protein sequences, the results are obviously better than other comparisons, with the highest accuracy up to more than 97%. Conclusion FFP has higher accuracy in APPA and multi-sequence alignment. It also can measure the protein sequence similarity effectively. And it is hoped to play a role in APPA’s related research.

text summarization is a classic sequence-to-sequence natural language generation task. In order to improve the quality of unsupervised abstract text summarization in unsupervised mode, we propose two constraints for training text summarization model, embedding space constraint and information ratio constraint. We construct a generative adversarial network with two discriminators based on these two constraints (TC-SUM-GAN). We use unsupervised and supervised methods to train the model in the experiment. Experimental results show that the ROUGE-1 value of the unsupervised TC-SUM-GAN increases by [Formula: see text] points compared with the basic model and at least 1.96 points compared with other comparative models. The ROUGE scores of the supervised TC-SUM-GAN are also improved. TC-SUM-GAN achieves very competitive results for the metrics of ROUGE-1 and ROUGE-2. In addition, the abstracts generated by our model are closer to those generated manually.