Spectral‐spatial sequence characteristics‐based convolutional transformer for hyperspectral change detection

Recently,ground coverings change detection(CD)driven by bitemporal hyperspectral images(HSIs)has become a hot topic in the remote sensing community.There are two challenges in the HSI‐CD task:(1)attribute feature representation of pixel pairs and(2)feature extraction of attribute patterns of pixel pairs.To solve the above problems,a novel spectral‐spatial sequence characteristics‐based convolutional transformer(S3C‐CT)method is proposed for the HSI‐CD task.In the designed method,firstly,an eigenvalue extrema‐based band selection strategy is introduced to pick up spectral information with salient attribute patterns.Then,a 3D tensor with spectral‐spatial sequence characteristics is proposed to represent the attribute features of pixel pairs in the bitemporal HSIs.Next,a fusion framework of the convolutional neural network(CNN)and Transformer encoder(TE)is designed to extract high‐order sequence semantic features,taking into account both local context information and global sequence dependencies.Specifically,a spatial‐spectral attention mechanism is employed to prevent information reduction and enhance dimensional interactivity between the CNN and TE.Finally,the binary change map is determined according to the fully‐connected layer.Experimental results on real HSI datasets indicated that the proposed S3C‐CT method outperforms other well‐known and state‐of‐the‐art detection approaches in terms of detection performance.

Modulatory Effect of Pollen Extract on Apoptosis of Lymphocytes in the Elderly

Aim In this study, we investigated the changes of lymphocyte subpopulationand apoptosis process of lymphocytes in the elderly, and the modulatory effect of pollen extract(PE) on apoptosis. Methods Lymphocyte phenotypes were detected using indirect immunofluorescencetechnique. The proliferation responses were determined by MTT method. Flow cytometry and automaticimage analysis were performed to evaluate the apoptosis of lymphocytes. Results The proliferationresponses of lymphocytes in the elderly were lower than that in young adults. Decreased CD_(45) RA^+cells and increased CD_(45) RO^+ cells were found in lymphocyte population of aged people, comparedwith that of young adults. The CD_(45) RO^+ cells were prone to apoptosis. There is an inhibitoryeffect of PE on apoptosis of lymphocytes in the elderly. Conclusion It is implied that thesusceptibility of lymphocyte in the elderly to apoptosis depends on activation, so called,activation-induced cell death. Present results suggest that apoptosis of lymphocytes in aged peopleplay an important role in the pathogenesis of immunosenescence. Thus, a possibility is open fordevelopment of apoptosis-modulating drugs from pollen.

Variation of Electromagnetic Tornogram Before and After Earthquakes

Cross-well electromagnetic tomography has been used to monitor the changes of the abso rption coefficient of electromagnetic waves before and after earthquakes for 5 years at Dahuichang fault since 1992.It has been found that 3 months before the occurrence of moderately strong earthquakes(ML≥4.0,△【210 km),several special changes in tomogram appeared as follows:The mean-value of the absorption coefficient dropped about 10% compared with the annually decreasing tendency; the mean difference of pixels suddenly decreased or increased in different directions; and the entropy of the paragenic matrix in a tomogram decreased and the number of low absorption pixels increased.It is inferred that such changes in electromagnetic tomograms are attributed to the variation of micro-cracks and porosity in rocks.Electromagnetic tomography can be studied as a new technique to detect earthquake precursors.

inMTSCCA:An Integrated Multi-task Sparse Canonical Correlation Analysis for Multi-omic Brain Imaging Genetics

Identifying genetic risk factors for Alzheimer's disease(AD)is an important research topic.To date,different endophenotypes,such as imaging-derived endophenotypes and proteomic expression-derived endophenotypes,have shown the great value in uncovering risk genes compared to case-control studies.Biologically,a co-varying pattern of different omics-derived endophenotypes could result from the shared genetic basis.However,existing methods mainly focus on the effect of endophenotypes alone;the effect of cross-endophenotype(CEP)associations remains largely unexploited.In this study,we used both endophenotypes and their CEP associations of multi-omic data to identify genetic risk factors,and proposed two integrated multi-task sparse canonical correlation analysis(inMTSCCA)methods,i.e.,pairwise endophenotype correlationguided MTSCCA(pcMTSCCA)and high-order endophenotype correlation-guided MTSCCA(hocMTSCCA).pcMTSCCA employed pairwise correlations between magnetic resonance imaging(MRI)-derived,plasma-derived,and cerebrospinal fluid(CSF)-derived endophenotypes as an additional penalty.hocMTSCCA used high-order correlations among these multi-omic data for regularization.To figure out genetic risk factors at individual and group levels,as well as altered endophenotypic markers,we introduced sparsity-inducing penalties for both models.We compared pcMTSCCA and hocMTSCCA with three related methods on both simulation and real(consisting of neuroimaging data,proteomic analytes,and genetic data)datasets.The results showed that our methods obtained better or comparable canonical correlation coefficients(CCCs)and better feature subsets than benchmarks.Most importantly,the identified genetic loci and heterogeneous endophenotypic markers showed high relevance.Therefore,jointly using multi-omic endophenotypes and their CEP associations is promising to reveal genetic risk factors.