Morphology cluster and prediction of growth of human brain pyramidal neurons

Predicting neuron growth is valuable to understand the morphology of neurons, thus it is helpful in the research of neuron classification. This study sought to propose a new method of predicting the growth of human neurons using 1 907 sets of data in human brain pyramidal neurons obtained from the website of NeuroMorpho.Org. First, we analyzed neurons in a morphology field and used an expectation-maximization algorithm to specify the neurons into six clusters. Second, naive Bayes classifier was used to verify the accuracy of the expectation-maximization algorithm. Experiment results proved that the cluster groups here were efficient and feasible. Finally, a new method to rank the six expectation-maximization algorithm clustered classes was used in predicting the growth of human pyramidal neurons.

A Hybrid Signal Processing Method Combining Mathematical Morphology and Walsh Theory for Power Quality Disturbance Detection and Classification

In this paper, a novel signal processing method combining mathematical morphology (MM) and Walsh theory is proposed, which uses Walsh functions to control the structuring element (SE) and MM operators. Based on the Walsh-MM method, a scheme for power quality disturbances detection and classification is developed, which involves three steps: denoising, feature extraction and morphological clustering. First, various evolution rules of Walsh function are used to generate groups of SEs for the multiscale Walsh-ordered morphological operation, so the original signal can be denoised. Next, the fundamental wave of the denoised signal is suppressed by Hadamard matrix;thus, disturbances can be extracted. Finally, the Walsh power spectrum of the waveform extracted in the previous step is calculated, and the parameters of which are taken by morphological clustering to classify the disturbances. Simulation results reveal the proposed scheme can effectively detect and classify disturbances, and the Walsh-MM method is less affected by noise and only involves simple calculation, which has a potential to be implemented in hardware and more suitable for real-time application.

Two new species from Sulawesi and Borneo facilitate phylogeny and taxonomic revision of Engelhardia(Juglandaceae)

Engelhardia,a genus of Juglandaceae(the walnut family),is endemic to tropical and subtropical Asia.The rich Cenozoic fossil records and distinctive morphological characters of the living plants have been used to explore the evolutionary history and geographic distribution of Juglandaceae.However,the taxonomy of this genus has been suffered from a lack of in-depth investigation and good specimens across its distribution ranges.Species delimitation of Engelhardia was defined with seven species in 2020,but detailed information on the circumscription of the species still remains poorly understood.In this study,two new species are described from Sulawesi and Borneo,Engelhardia anminiana and E.borneensis.We also revised and reconstructed the phylogeny within Engelhardia using morphological,molecular(plastid and ribosomal),and distribution data.We sampled 787 individuals in 80 populations,and all the samples were genotyped using plastid regions,trnS-trnG,rps16,trnL-trnF,psbA-trnH,and rpl32-trnL;one ribosomal region,nuclear ribosomal internal transcribed spacer(nrITS).The all datasets were used to reconstruct the phylogenetic relationships.Then,the molecular analyses were combined for 738 sheets of specimens with 15 morphological characteristics to further explore the morphological clusters of Engelhardia.Cluster analysis using morphological data confirmed the delimitation of nine Engelhardia species.Also,phylogenetic analysis based on molecular data(i.e.,plastid and ribosomal)supported the monophyly of Engelhardia and generated phylogenetic trees that included E.fenzelii,E.roxburghiana,E.borneensis,E.hainanensis,E.anminiana,E.serrata,E.villosa,E.apoensis and the varieties of E.spicata(i.e.,E.spicata var.spicata,E.spicata var.rigida,E.spicata var.aceriflora,and E.spicata var.colebrookeana).Our comprehensive taxonomic revision of Engelhardia will provide an insight into understanding the plant diversity in tropical and subtropical Asia.