Humanoid robots hold significant promise for social interaction and emotional companionship.However,their effectiveness hinges on the ability to convey nuanced and authentic emotions.Here,we presented a universal huma...Humanoid robots hold significant promise for social interaction and emotional companionship.However,their effectiveness hinges on the ability to convey nuanced and authentic emotions.Here,we presented a universal humanoid robot head with a facial kinematics model.Using a reinforcement learning framework guided by symmetry assessment,emotion decoupling,and MLLM authenticity evaluation,our system autonomously learns to generate adaptive facial expressions through dynamic landmark adjustments.By transferring the simulation training results to real-world environments,the robot can perform natural and expressive expressions.Another novel feature is the independent regulation of emotion intensity and expression magnitude across emotional categories,which enhances the ability to achieve culturally adaptive and socially resonant robotic expressions significantly.This research advances adaptive humanoid interaction,offering an easier and more efficient pathway toward culturally resonant and psychologically plausible robotic expressions.展开更多
[Objectives]The present study was conducted to investigate the change rule ofβ-fructofuranosidase gene expression and its enzyme activity in the midgut of 5 th instar silkworm(Bombyx mori),in order to provide a refer...[Objectives]The present study was conducted to investigate the change rule ofβ-fructofuranosidase gene expression and its enzyme activity in the midgut of 5 th instar silkworm(Bombyx mori),in order to provide a reference for illustrating the enzymatic mechanism of usingβ-fructofuranosidase to absorb sucrose nutrition from mulberry leaves.[Methods]Real-time fluorescent quantitative PCR was applied to analyze the expression of BmSuc1 and BmSuc2 in midgut of 5 th-instar silkworm larvae,meanwhile the activities ofβ-fructofuranosidase was determined.[Results]BmSuc1 was expressed in the midgut of 5 th-instar silkworm larvae at different developmental stages.Its expression was upregulated at the beginning of the 5 th instar and during the peak feeding period,whereas BmSuc2 expression remained very low throughout the entire 5 th instar.The activity ofβ-fructofuranosidase was relatively high during the peak feeding period of 5 th-instar larvae,showing a trend of increasing first and then decreasing.[Conclusions]The expression pattern of the BmSuc1 gene and the changes inβ-fructofuranosidase activity were generally consistent with the physiological process of sugar nutrient absorption and utilization from mulberry leaves in 5 th-instar silkworms.It suggests that BmSuc1,as a sucrose hydrolase gene,plays a major role in the digestion and absorption of sucrose nutrients from mulberry leaves in the midgut tissue.展开更多
The pathogenesis-related protein PR10 plays a vital role in plant growth,development,and stress responses.This study systematically identified and analyzed PR10 genes in cultivated peanut(Arachis hypogaea L.),examinin...The pathogenesis-related protein PR10 plays a vital role in plant growth,development,and stress responses.This study systematically identified and analyzed PR10 genes in cultivated peanut(Arachis hypogaea L.),examining their phylogenetic relationships,conserved motifs,gene structures,and syntenic relationships.The analysis identified 54 Ah PR10 genes,which were classified into eight groups based on phylogenetic relationships,supported by gene structure and conserved motif characterization.Analysis of chromosomal distribution and synteny demonstrated that segmental duplications played a crucial role in the expansion of the Ah PR10 gene family.The identified Ah PR10 genes exhibited both constitutive and inducible expression patterns.Significantly,Ah PR10-7,Ah PR10-33,and Ah PR10-41 demonstrated potential importance in peanut resistance to Aspergillus flavus.In vitro fungistatic experiments demonstrated that recombinant Ah PR10-33 effectively inhibited A.flavus mycelial growth.These findings provide valuable insights for future investigations into Ah PR10 functions in protecting peanut from A.flavus infection.展开更多
Due to the unique microstructure and diverse opsin genes of the trinocular compound eye,stomatopoda possess an extraordinary ability to perceive multiple properties of light.They not only can detect natural light(NL)a...Due to the unique microstructure and diverse opsin genes of the trinocular compound eye,stomatopoda possess an extraordinary ability to perceive multiple properties of light.They not only can detect natural light(NL)and linearly polarized light(LPL),but also are the only animals capable of recognizing circularly polarized light(CPL).Here,we integrated single-cell RNA sequencing,previously published Illumina data,and in-situ hybridization(ISH)to quantify and localize functional opsin genes in Oratosquilla oratoria,a common stomatopoda species in the China Sea.A total of high-quality 31777 cells were captured for the first time in the O.oratoria compound eye,which were classified into 25 cell subpopulations,and hypothesized that cluster 22 is a critical cell subpopulation responsible for light(whether NL,LPL,or CPL)response in O.oratoria.Furthermore,we propose that the long-wavelengthsensitive opsin gene(lws)gene family,retinol dehydrogenase(rdh),voltage-gated ion channel(vgic),arrestin(arr),and myosin(myo)collectively mediate the light response in O.oratoria.Considering that very few vision-related opsin genes show differential expression in right-handed CPL(RCPL)-vs.-dark(DL),which provides additional evidence that stomatopoda cannot recognize RCPL.Meanwhile,we believe that UV-stimulated scaffold protein A(uvssa)and red pigment concentrating hormone(rpch)play special contributions in the left-handed CPL(LCPL)environment response.ISH revealing that 16 lws,6 middle-wavelength-sensitive(mws),and 2 ultraviolet(uv)opsin genes were expressed in the photoreceptors of the O.oratoria compound eye.Although the inability to determine the functional types of cell subpopulations limits the resolution of opsin genes,these findings systematically elucidate the specific expression patterns of opsin genes in O.oratoria and represent a significant step toward refining the visual ecological theory of O.oratoria and other stomatopod species.展开更多
Botrytis cinerea is a major necrotrophic pathogen responsible for significant crop losses worldwide.Alternative strategies to control B.cinerea are urgently needed to reduce dependence on chemical fungicides,which are...Botrytis cinerea is a major necrotrophic pathogen responsible for significant crop losses worldwide.Alternative strategies to control B.cinerea are urgently needed to reduce dependence on chemical fungicides,which are increasingly ineffective due to resistance and pose environmental risks.In this study,we identified two immunogenic epitopes derived from the B.cinerea cell death-inducing protein BcCrh1 and used them to engineer disease-resistant plants through a novel,spatially compartmentalized dual-epitope immune activation strategy.The first epitope is derived from a 35-amino acid intracellular peptide that exhibits both immunogenicity and cell death-inducing activity,which was mutated to separate these two properties.The second peptide represents an immunogenic portion of the protein that activates extracellular plant immunity.Transcriptomic and metabolomic analyses revealed that these epitopes trigger complementary defense pathways,and their co-expression integrates these responses into a robust,multilayered immunity,providing significantly enhanced protection compared with individual expression.Although constitutive expression of two epitopes conferred resistance,it also led to growth penalties.In contrast,pathogen-inducible expression of two epitopes preserved normal plant development while maintaining strong resistance to both B.cinerea and Pseudomonas syringae in Arabidopsis and tomato.This inducible strategy offers a major advantage by minimizing fitness costs while maximizing protection,highlighting the potential of spatially and temporally targeted epitope-based immune activation for durable and sustainable crop protection.展开更多
Coconut(Cocos nucifera L.),a major oil and fruit crop of the Arecaceae family,is extensively cultivated across the Asia—Pacific region.Despite its agricultural importance,genome assembly in coconut remains challengin...Coconut(Cocos nucifera L.),a major oil and fruit crop of the Arecaceae family,is extensively cultivated across the Asia—Pacific region.Despite its agricultural importance,genome assembly in coconut remains challenging due to its large genome size and high proportion of repetitive sequences.Allele-specific expression(ASE)plays a key role in regulating plant development and evolution,yet research on ASE in coconut is limited(Shao et al.,2019;Li et al.,2021;Zhang et al.,2021;Hu et al.,2022).Among phenotypic traits,fruit color is especially important as an indicator of maturity,guiding harvest timing and post-harvest processes(Kapoor et al.,2022).While prior studies have explored various coconut traits such as salt tolerance,fiber content,and plant height(Wang et al.,2021;Yang et al.,2021),investigations into ASE and fruit color remain scarce.展开更多
The prognostic and therapeutic roles of biological markers in early-stage breast cancer(eBC)warrant further investigation.Non-Breast Cancer(BRCA)genes,along with moderate-and low-penetrance breast cancer risk variant ...The prognostic and therapeutic roles of biological markers in early-stage breast cancer(eBC)warrant further investigation.Non-Breast Cancer(BRCA)genes,along with moderate-and low-penetrance breast cancer risk variant genes,are crucial formaintaining genome stability,yet their prognostic significance in eBCremains unclear.This study aimed to evaluate the impact of non-BRCA genes on clinical outcomes in eBC patients.Significant correlations were observed between the messenger ribonucleic acid(mRNA)expression levels of the genes Ataxia-telangiectasia mutated(ATM),Bloom helicase gene(BLM),and WRN RecQ Like Helicase(WRN)and patient prognosis.High mRNA expression of ATM was associated with longer metastasis-free survival(MFS).Conversely,lower mRNA expression of BLM correlated with favorable outcomes,particularly in triple-negative tumors.Additionally,high levels of WRN mRNA expression were linked to significantly longer MFS compared to low expression levels.This study highlights the prognostic significance of ATM,BLM,and WRN in predicting survival outcomes in eBC patients.Background:The prognostic significance of various biological and non-BRCA genetic in early-stage breast cancer(eBC)remains unclear and warrants further investigation.This study therefore aimed to evaluate the prognostic impact of these genes on clinical outcomes in breast cancer.Methods:Patients included in this study were subdivided into two groups based on low and high messenger ribonucleic acid(mRNA)expression levels.Statistical analysis,including Kaplan-Meier curves,univariable,andmultivariable Cox regression analyses,was performed to assess metastasis-free survival(MFS)of mRNA expression of non-BRCA genes.Subgroup analyses were also conducted among four different molecular subtypes of eBC.Results:Our analysis revealed significant correlations between mRNA-expression levels of Ataxiatelangiectasia mutated(ATM),Bloom helicase gene(BLM),and WRN RecQ Like Helicase(WRN)and patient prognosis.High mRNA expression of ATM correlated with longer MFS in the entire cohort(p=0.022,Log Rank),and in luminal-B-like tumors(p=0.036).Lower mRNA expression of BLM was associated with favorable outcomes(p=0.011,Log Rank),particularly in triple-negative eBC(p=0.030,Log Rank).Finally,high levels of WRN mRNA expression correlated with significantly longerMFS compared to lowmRNA expression levels(p=0.009,Log Rank).Conclusions:This study underscores the prognostic significance of moderate penetrance breast cancer risk variant genes,such as ATM,BLM,and WRN,for survival outcomes in eBC.展开更多
Micro-expressions(ME)recognition is a complex task that requires advanced techniques to extract informative features fromfacial expressions.Numerous deep neural networks(DNNs)with convolutional structures have been pr...Micro-expressions(ME)recognition is a complex task that requires advanced techniques to extract informative features fromfacial expressions.Numerous deep neural networks(DNNs)with convolutional structures have been proposed.However,unlike DNNs,shallow convolutional neural networks often outperform deeper models in mitigating overfitting,particularly with small datasets.Still,many of these methods rely on a single feature for recognition,resulting in an insufficient ability to extract highly effective features.To address this limitation,in this paper,an Improved Dual-stream Shallow Convolutional Neural Network based on an Extreme Gradient Boosting Algorithm(IDSSCNN-XgBoost)is introduced for ME Recognition.The proposed method utilizes a dual-stream architecture where motion vectors(temporal features)are extracted using Optical Flow TV-L1 and amplify subtle changes(spatial features)via EulerianVideoMagnification(EVM).These features are processed by IDSSCNN,with an attention mechanism applied to refine the extracted effective features.The outputs are then fused,concatenated,and classified using the XgBoost algorithm.This comprehensive approach significantly improves recognition accuracy by leveraging the strengths of both temporal and spatial information,supported by the robust classification power of XgBoost.The proposed method is evaluated on three publicly available ME databases named Chinese Academy of Sciences Micro-expression Database(CASMEII),Spontaneous Micro-Expression Database(SMICHS),and Spontaneous Actions and Micro-Movements(SAMM).Experimental results indicate that the proposed model can achieve outstanding results compared to recent models.The accuracy results are 79.01%,69.22%,and 68.99%on CASMEII,SMIC-HS,and SAMM,and the F1-score are 75.47%,68.91%,and 63.84%,respectively.The proposed method has the advantage of operational efficiency and less computational time.展开更多
Schizophrenia(SZ)stands as a severe psychiatric disorder.This study applied diffusion tensor imaging(DTI)data in conjunction with graph neural networks to distinguish SZ patients from normal controls(NCs)and showcases...Schizophrenia(SZ)stands as a severe psychiatric disorder.This study applied diffusion tensor imaging(DTI)data in conjunction with graph neural networks to distinguish SZ patients from normal controls(NCs)and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features,achieving an accuracy of 73.79%in distinguishing SZ patients from NCs.Beyond mere discrimination,our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis.These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers,providing novel insights into the neuropathological basis of SZ.In summary,our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.展开更多
Facial expression recognition is a hot topic in computer vision, but it remains challenging due to the feature inconsistency caused by person-specific 'characteristics of facial expressions. To address such a chal...Facial expression recognition is a hot topic in computer vision, but it remains challenging due to the feature inconsistency caused by person-specific 'characteristics of facial expressions. To address such a challenge, and inspired by the recent success of deep identity network (DeepID-Net) for face identification, this paper proposes a novel deep learning based framework for recognising human expressions with facial images. Compared to the existing deep learning methods, our proposed framework, which is based on multi-scale global images and local facial patches, can significantly achieve a better performance on facial expression recognition. Finally, we verify the effectiveness of our proposed framework through experiments on the public benchmarking datasets JAFFE and extended Cohn-Kanade (CK+).展开更多
Testis specific protein Y-encoded（TSPY） is a Y-located proto-oncogene predominantly expressed in normal male germ cells and various types of germ cell tumor. Significantly, TSPY is frequently expressed in somatic ca...Testis specific protein Y-encoded（TSPY） is a Y-located proto-oncogene predominantly expressed in normal male germ cells and various types of germ cell tumor. Significantly, TSPY is frequently expressed in somatic cancers including liver cancer but not in adjacent normal tissues, suggesting that ectopic TSPY expression could be associated with oncogenesis in non-germ cell cancers. Various studies demonstrated that TSPY expression promotes growth and proliferation in cancer cells; however, its relationship to other oncogenic events in TSPY-positive cancers remains unknown. The present study seeks to correlate TSPY expression with other molecular features in clinical cancer samples, by analyses of RNA-seq transcriptome and DNA methylation data in the Cancer Genome Atlas（TCGA） database. A total of 53 genes,including oncogenic lineage protein 28 homolog B（LIN28B） gene and RNA-binding motif protein Y-linked（RBMY） gene, are identified to be consistently co-expressed with TSPY, and have been collectively designated as the TSPY co-expression network（TCN）. TCN genes were simultaneously activated in subsets of liver hepatocellular carcinoma（30%） and lung adenocarcinoma（10%） regardless of pathological stage, but only minimally in other cancer types. Further analysis revealed that the DNA methylation level was globally lower in the TCN-active than TCN-silent cancers. The specific expression and methylation patterns of TCN genes suggest that they could be useful as biomarkers for the diagnosis,prognosis and clinical management of cancers, especially those for liver and lung cancers, associated with TSPY co-expression network genes.展开更多
AIM: To identify and understand the relationship between co-expression pattern and clinic traits in uveal melanoma, weighted gene co-expression network analysis(WGCNA) is applied to investigate the gene expression lev...AIM: To identify and understand the relationship between co-expression pattern and clinic traits in uveal melanoma, weighted gene co-expression network analysis(WGCNA) is applied to investigate the gene expression levels and patient clinic features. Uveal melanoma is the most common primary eye tumor in adults. Although many studies have identified some important genes and pathways that were relevant to progress of uveal melanoma, the relationship between co-expression and clinic traits in systems level of uveal melanoma is unclear yet. We employ WGCNA to investigate the relationship underlying molecular and phenotype in this study.METHODS: Gene expression profile of uveal melanoma and patient clinic traits were collected from the Gene Expression Omnibus(GEO) database. The gene co-expression is calculated by WGCNA that is the R package software. The package is used to analyze the correlation between pairs of expression levels of genes.The function of the genes were annotated by gene ontology(GO).RESULTS: In this study, we identified four co-expression modules significantly correlated with clinictraits. Module blue positively correlated with radiotherapy treatment. Module purple positively correlates with tumor location(sclera) and negatively correlates with patient age. Module red positively correlates with sclera and negatively correlates with thickness of tumor. Module black positively correlates with the largest tumor diameter(LTD). Additionally, we identified the hug gene(top connectivity with other genes) in each module. The hub gene RPS15 A, PTGDS, CD53 and MSI2 might play a vital role in progress of uveal melanoma.CONCLUSION: From WGCNA analysis and hub gene calculation, we identified RPS15 A, PTGDS, CD53 and MSI2 might be target or diagnosis for uveal melanoma.展开更多
Maize （Zea mays） is the most widely grown grain crop in the world, playing important roles in agriculture and industry. However, the functions of maize genes remain largely unknown. High-quality genome- wide transcr...Maize （Zea mays） is the most widely grown grain crop in the world, playing important roles in agriculture and industry. However, the functions of maize genes remain largely unknown. High-quality genome- wide transcriptome datasets provide important biological knowledge which has been widely and suc- cessfully used in plants not only by measuring gene expression levels but also by enabling co-expression analysis for predicting gene functions and modules related to agronomic traits. Recently, thousands of maize transcriptomic data are available across different inbred lines, development stages, tissues, and treatments, or even across different tissue sections and cell lines. Here, we integrated 701 transcriptomic and 108 epigenomic data and studied the different conditional networks with multi-dimensional omics levels. We constructed a searchable, integrative, one-stop online platform, the maize conditional co- expression network （MCENet） platform. MCENet provides 10 global/conditional co-expression net- works, 5 network accessional analysis toolkits （i.e., Network Search, Network Remodel, Module Finder, Network Comparison, and Dynamic Expression View） and multiple network functional support toolkits （e.g., motif and module enrichment analysis）. We hope that our database might help plant research communities to identify maize functional genes or modules that regulate important agronomic traits.展开更多
Autophagy plays a vital role in cerebral ischemia and may be a potential target for developing novel therapy for stroke. In this study, we constructed an autophagy-related pathway network by analyzing the genes relate...Autophagy plays a vital role in cerebral ischemia and may be a potential target for developing novel therapy for stroke. In this study, we constructed an autophagy-related pathway network by analyzing the genes related to autophagy and ischemic stroke, and the risk genes were screened. Two autophagy-related modules were significantly up-regulated and clustered to influence cerebral ischemia. Besides, three key modular genes （NFKB1, RELA, and STAT3） were revealed. With 5-fold cross validation, the ROC curves of NFKB1, RELA, and STAT3 were 0.8256, 0.8462, and 0.8923. They formed a complex module and competitively mediated the activation of autophagy in cerebral ischemia. In conclusion, a module containing NFKB1, RELA, and STAT3 mediates autophagy, serving as a potential biomarker for the diagnosis and therapy of ischemic stroke.展开更多
Esophageal cancer is a common malignant tumor, whose pathogenesis and prognosis factors are not fully understood. This study aimed to discover the gene clusters that have similar functions and can be used to predict t...Esophageal cancer is a common malignant tumor, whose pathogenesis and prognosis factors are not fully understood. This study aimed to discover the gene clusters that have similar functions and can be used to predict the prognosis of esophageal cancer. The matched microarray and RNA sequencing data of 185 patients with esophageal cancer were downloaded from The Cancer Genome Atlas(TCGA), and gene co-expression networks were built without distinguishing between squamous carcinoma and adenocarcinoma. The result showed that 12 modules were associated with one or more survival data such as recurrence status, recurrence time, vital status or vital time. Furthermore, survival analysis showed that 5 out of the 12 modules were related to progression-free survival(PFS) or overall survival(OS). As the most important module, the midnight blue module with 82 genes was related to PFS, apart from the patient age, tumor grade, primary treatment success, and duration of smoking and tumor histological type. Gene ontology enrichment analysis revealed that 'glycoprotein binding' was the top enriched function of midnight blue module genes. Additionally, the blue module was the exclusive gene clusters related to OS. Platelet activating factor receptor(PTAFR) and feline Gardner-Rasheed(FGR) were the top hub genes in both modeling datasets and the STRING protein interaction database. In conclusion, our study provides novel insights into the prognosis-associated genes and screens out candidate biomarkers for esophageal cancer.展开更多
Based on the heat flow data published in 1990 and 2001, a study of the factors influencing the terrestrial heat flow distribution in the China continent and its quantitative expression is carried out using the ＂Netli...Based on the heat flow data published in 1990 and 2001, a study of the factors influencing the terrestrial heat flow distribution in the China continent and its quantitative expression is carried out using the ＂Netlike Plastic-Flow＂ continental dynamics model and the methods of statistic analysis and optimum fitting. The result indicates that the factors influencing the heat flow distribution is classified into two groups, i.e. background and tectonic ones, in which the former mainly involves the non- uniform distribution of mantle heat flow, heat production of radioactive dements in the crust, heattransfer media and hydrothermal circulation, while the latter mainly involves plastic-flow networks and relatively-stable blocks. The plastic-flow network is a manifestation of shear localization in the netlike plastic-flow process in the lower lithosphere, which is composed of two sets of plastic-flow belts （PFBs） intersecting each other and, as one of the basic action regimes, controls the intraplate tectonic deformation. Relatively stable blocks （RSBs）, which are the tectonic units with relatively-high viscosities existing in the netlike plastic-flow field, as one of the principal origins, result in the development of large-seale compressional basins. PFB and RSB, as the active and quiet states of tectonic deformation, give rise to the higher and lower heat flow values, respectivdy. The provincial average heat flow in continent can be estimated using the expression qav = q0 ＋ a Pbt-c Pbk, where the three terms of the right side are background heat flow, PFB-positive contribution and RSB-negative contribution, Pbt and Pbk are the PFB- and RSB-coverage ratios, respectively, a is the coefficient of PFB- positive contribution depending mainly on the strain in the lower lithosphere, and c is the coefficient of RSB-negative contribution related mainly to the thickness of the lithosphere, the aseismic-area ratio and the tectonic age. For the major portion of the China continent excluding some of the southeastern region of China, the confidence interval of the provincial average background heat flow is qo=57.25±24.8 mW/m^2 and the PFB-positive- and RSB-negative-contribution coefficients are a=14.8-71.9 mW/m^2 and c=0-25.6 mW/m^2, respectively. The concepts of PFB and RSB effects and the heat flow expression suggested provide a new choice of the approach to the quantitative description of the characteristics of heat flow distribution in continent and their physical mechanisms.展开更多
Facial Expression Recognition(FER)has been an interesting area of research in places where there is human-computer interaction.Human psychol-ogy,emotions and behaviors can be analyzed in FER.Classifiers used in FER hav...Facial Expression Recognition(FER)has been an interesting area of research in places where there is human-computer interaction.Human psychol-ogy,emotions and behaviors can be analyzed in FER.Classifiers used in FER have been perfect on normal faces but have been found to be constrained in occluded faces.Recently,Deep Learning Techniques(DLT)have gained popular-ity in applications of real-world problems including recognition of human emo-tions.The human face reflects emotional states and human intentions.An expression is the most natural and powerful way of communicating non-verbally.Systems which form communications between the two are termed Human Machine Interaction(HMI)systems.FER can improve HMI systems as human expressions convey useful information to an observer.This paper proposes a FER scheme called EECNN(Enhanced Convolution Neural Network with Atten-tion mechanism)to recognize seven types of human emotions with satisfying results in its experiments.Proposed EECNN achieved 89.8%accuracy in classi-fying the images.展开更多
The organoleptic qualities of watermelon fruit are defined by the sugar and organic acid contents,which undergo considerable variations during development and maturation.The molecular mechanisms underlying these varia...The organoleptic qualities of watermelon fruit are defined by the sugar and organic acid contents,which undergo considerable variations during development and maturation.The molecular mechanisms underlying these variations remain unclear.In this study,we used transcriptome profiles to investigate the coexpression patterns of gene networks associated with sugar and organic acid metabolism.We identified 3 gene networks/modules containing 2443 genes highly correlated with sugars and organic acids.Within these modules,based on intramodular significance and Reverse Transcription Quantitative polymerase chain reaction(RT-qPCR),we identified 7 genes involved in the metabolism of sugars and organic acids.Among these genes,Cla97C01G000640,Cla97C05G087120 and Cla97C01G018840(r^(2)=0.83 with glucose content)were identified as sugar transporters(SWEET,EDR6 and STP)and Cla97C03G064990(r^(2)=0.92 with sucrose content)was identified as a sucrose synthase from information available for other crops.Similarly,Cla97C07G128420,Cla97C03G068240 and Cla97C01G008870,having strong correlations with malic(r^(2)=0.75)and citric acid(r^(2)=0.85),were annotated as malate and citrate transporters(ALMT7,CS,and ICDH).The expression profiles of these 7 genes in diverse watermelon genotypes revealed consistent patterns of expression variation in various types of watermelon.These findings add significantly to our existing knowledge of sugar and organic acid metabolism in watermelon.展开更多
This paper investigates epidemic dynamics over dynamic networks via the approach of semi-tensor product of matrices. First, a formal susceptible-infected-susceptible epidemic dynamic model over dynamic networks （SISE...This paper investigates epidemic dynamics over dynamic networks via the approach of semi-tensor product of matrices. First, a formal susceptible-infected-susceptible epidemic dynamic model over dynamic networks （SISED-DN） is given. Second, based on a class of determinate co-evolutionary rule, the matrix expressions are established for the dynamics of individual states and network topologies, respectively. Then, all possible final spreading equilibria are obtained for any given initial epidemic state and network topology by the matrix expression. Third, a sufficient and necessary condition of the existence of state feedback vaccination control is presented to make every individual susceptible. The study of illustrative examples shows the effectiveness of our new results.展开更多
Convolutional neural networks struggle to accurately handle changes in angles and twists in the direction of images,which affects their ability to recognize patterns based on internal feature levels. In contrast, Caps...Convolutional neural networks struggle to accurately handle changes in angles and twists in the direction of images,which affects their ability to recognize patterns based on internal feature levels. In contrast, CapsNet overcomesthese limitations by vectorizing information through increased directionality and magnitude, ensuring that spatialinformation is not overlooked. Therefore, this study proposes a novel expression recognition technique calledCAPSULE-VGG, which combines the strengths of CapsNet and convolutional neural networks. By refining andintegrating features extracted by a convolutional neural network before introducing theminto CapsNet, ourmodelenhances facial recognition capabilities. Compared to traditional neural network models, our approach offersfaster training pace, improved convergence speed, and higher accuracy rates approaching stability. Experimentalresults demonstrate that our method achieves recognition rates of 74.14% for the FER2013 expression dataset and99.85% for the CK+ expression dataset. By contrasting these findings with those obtained using conventionalexpression recognition techniques and incorporating CapsNet’s advantages, we effectively address issues associatedwith convolutional neural networks while increasing expression identification accuracy.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.52405041)the Major Program of the Zhejiang Provincial Natural Science Foundation of China(Grant No.LD25E050001)the Key R&D Program of Zhejiang Province(Grant No.2025C01186)。
文摘Humanoid robots hold significant promise for social interaction and emotional companionship.However,their effectiveness hinges on the ability to convey nuanced and authentic emotions.Here,we presented a universal humanoid robot head with a facial kinematics model.Using a reinforcement learning framework guided by symmetry assessment,emotion decoupling,and MLLM authenticity evaluation,our system autonomously learns to generate adaptive facial expressions through dynamic landmark adjustments.By transferring the simulation training results to real-world environments,the robot can perform natural and expressive expressions.Another novel feature is the independent regulation of emotion intensity and expression magnitude across emotional categories,which enhances the ability to achieve culturally adaptive and socially resonant robotic expressions significantly.This research advances adaptive humanoid interaction,offering an easier and more efficient pathway toward culturally resonant and psychologically plausible robotic expressions.
基金Supported by General Project of Yunnan Provincial Agricultural Basic Research Joint Special Project(202301BD070001-229)Yunnan Provincial Key R&D Program(202403AK140075)+1 种基金Modern Sericulture Industry Technology System of Yunan Province(KJTX-07)Honghe Comprehensive Test Station of National Sericulture Industry Technology System(CARS-18).
文摘[Objectives]The present study was conducted to investigate the change rule ofβ-fructofuranosidase gene expression and its enzyme activity in the midgut of 5 th instar silkworm(Bombyx mori),in order to provide a reference for illustrating the enzymatic mechanism of usingβ-fructofuranosidase to absorb sucrose nutrition from mulberry leaves.[Methods]Real-time fluorescent quantitative PCR was applied to analyze the expression of BmSuc1 and BmSuc2 in midgut of 5 th-instar silkworm larvae,meanwhile the activities ofβ-fructofuranosidase was determined.[Results]BmSuc1 was expressed in the midgut of 5 th-instar silkworm larvae at different developmental stages.Its expression was upregulated at the beginning of the 5 th instar and during the peak feeding period,whereas BmSuc2 expression remained very low throughout the entire 5 th instar.The activity ofβ-fructofuranosidase was relatively high during the peak feeding period of 5 th-instar larvae,showing a trend of increasing first and then decreasing.[Conclusions]The expression pattern of the BmSuc1 gene and the changes inβ-fructofuranosidase activity were generally consistent with the physiological process of sugar nutrient absorption and utilization from mulberry leaves in 5 th-instar silkworms.It suggests that BmSuc1,as a sucrose hydrolase gene,plays a major role in the digestion and absorption of sucrose nutrients from mulberry leaves in the midgut tissue.
基金supported by the National Key R&D Program of China(2022YFD1200400)the National Natural Science Foundation of China(32301851)。
文摘The pathogenesis-related protein PR10 plays a vital role in plant growth,development,and stress responses.This study systematically identified and analyzed PR10 genes in cultivated peanut(Arachis hypogaea L.),examining their phylogenetic relationships,conserved motifs,gene structures,and syntenic relationships.The analysis identified 54 Ah PR10 genes,which were classified into eight groups based on phylogenetic relationships,supported by gene structure and conserved motif characterization.Analysis of chromosomal distribution and synteny demonstrated that segmental duplications played a crucial role in the expansion of the Ah PR10 gene family.The identified Ah PR10 genes exhibited both constitutive and inducible expression patterns.Significantly,Ah PR10-7,Ah PR10-33,and Ah PR10-41 demonstrated potential importance in peanut resistance to Aspergillus flavus.In vitro fungistatic experiments demonstrated that recombinant Ah PR10-33 effectively inhibited A.flavus mycelial growth.These findings provide valuable insights for future investigations into Ah PR10 functions in protecting peanut from A.flavus infection.
基金Supported by the Natural Science Foundation of Shandong Province(No.ZR2021QD110)the National Natural Science Foundation of China(No.42106128)。
文摘Due to the unique microstructure and diverse opsin genes of the trinocular compound eye,stomatopoda possess an extraordinary ability to perceive multiple properties of light.They not only can detect natural light(NL)and linearly polarized light(LPL),but also are the only animals capable of recognizing circularly polarized light(CPL).Here,we integrated single-cell RNA sequencing,previously published Illumina data,and in-situ hybridization(ISH)to quantify and localize functional opsin genes in Oratosquilla oratoria,a common stomatopoda species in the China Sea.A total of high-quality 31777 cells were captured for the first time in the O.oratoria compound eye,which were classified into 25 cell subpopulations,and hypothesized that cluster 22 is a critical cell subpopulation responsible for light(whether NL,LPL,or CPL)response in O.oratoria.Furthermore,we propose that the long-wavelengthsensitive opsin gene(lws)gene family,retinol dehydrogenase(rdh),voltage-gated ion channel(vgic),arrestin(arr),and myosin(myo)collectively mediate the light response in O.oratoria.Considering that very few vision-related opsin genes show differential expression in right-handed CPL(RCPL)-vs.-dark(DL),which provides additional evidence that stomatopoda cannot recognize RCPL.Meanwhile,we believe that UV-stimulated scaffold protein A(uvssa)and red pigment concentrating hormone(rpch)play special contributions in the left-handed CPL(LCPL)environment response.ISH revealing that 16 lws,6 middle-wavelength-sensitive(mws),and 2 ultraviolet(uv)opsin genes were expressed in the photoreceptors of the O.oratoria compound eye.Although the inability to determine the functional types of cell subpopulations limits the resolution of opsin genes,these findings systematically elucidate the specific expression patterns of opsin genes in O.oratoria and represent a significant step toward refining the visual ecological theory of O.oratoria and other stomatopod species.
基金supported by the National Natural Science Foundation of China(grant no.32372514)the Research and Innovation Initiatives of WHPU(grant no.2024J02)+1 种基金Y.L.(202108280009)was funded by the China Scholarship Councilsupported by BARD(grant no.5261-20C)to A.S and T.M.
文摘Botrytis cinerea is a major necrotrophic pathogen responsible for significant crop losses worldwide.Alternative strategies to control B.cinerea are urgently needed to reduce dependence on chemical fungicides,which are increasingly ineffective due to resistance and pose environmental risks.In this study,we identified two immunogenic epitopes derived from the B.cinerea cell death-inducing protein BcCrh1 and used them to engineer disease-resistant plants through a novel,spatially compartmentalized dual-epitope immune activation strategy.The first epitope is derived from a 35-amino acid intracellular peptide that exhibits both immunogenicity and cell death-inducing activity,which was mutated to separate these two properties.The second peptide represents an immunogenic portion of the protein that activates extracellular plant immunity.Transcriptomic and metabolomic analyses revealed that these epitopes trigger complementary defense pathways,and their co-expression integrates these responses into a robust,multilayered immunity,providing significantly enhanced protection compared with individual expression.Although constitutive expression of two epitopes conferred resistance,it also led to growth penalties.In contrast,pathogen-inducible expression of two epitopes preserved normal plant development while maintaining strong resistance to both B.cinerea and Pseudomonas syringae in Arabidopsis and tomato.This inducible strategy offers a major advantage by minimizing fitness costs while maximizing protection,highlighting the potential of spatially and temporally targeted epitope-based immune activation for durable and sustainable crop protection.
基金supported by Central Public-interest Scientific Institution Basal Research Fund(CATAS-Nos.1630152023007,1630152023011,1630152023012,1630152023013)the National Natural Science Foundation of China(Grant No.32071805).
文摘Coconut(Cocos nucifera L.),a major oil and fruit crop of the Arecaceae family,is extensively cultivated across the Asia—Pacific region.Despite its agricultural importance,genome assembly in coconut remains challenging due to its large genome size and high proportion of repetitive sequences.Allele-specific expression(ASE)plays a key role in regulating plant development and evolution,yet research on ASE in coconut is limited(Shao et al.,2019;Li et al.,2021;Zhang et al.,2021;Hu et al.,2022).Among phenotypic traits,fruit color is especially important as an indicator of maturity,guiding harvest timing and post-harvest processes(Kapoor et al.,2022).While prior studies have explored various coconut traits such as salt tolerance,fiber content,and plant height(Wang et al.,2021;Yang et al.,2021),investigations into ASE and fruit color remain scarce.
文摘The prognostic and therapeutic roles of biological markers in early-stage breast cancer(eBC)warrant further investigation.Non-Breast Cancer(BRCA)genes,along with moderate-and low-penetrance breast cancer risk variant genes,are crucial formaintaining genome stability,yet their prognostic significance in eBCremains unclear.This study aimed to evaluate the impact of non-BRCA genes on clinical outcomes in eBC patients.Significant correlations were observed between the messenger ribonucleic acid(mRNA)expression levels of the genes Ataxia-telangiectasia mutated(ATM),Bloom helicase gene(BLM),and WRN RecQ Like Helicase(WRN)and patient prognosis.High mRNA expression of ATM was associated with longer metastasis-free survival(MFS).Conversely,lower mRNA expression of BLM correlated with favorable outcomes,particularly in triple-negative tumors.Additionally,high levels of WRN mRNA expression were linked to significantly longer MFS compared to low expression levels.This study highlights the prognostic significance of ATM,BLM,and WRN in predicting survival outcomes in eBC patients.Background:The prognostic significance of various biological and non-BRCA genetic in early-stage breast cancer(eBC)remains unclear and warrants further investigation.This study therefore aimed to evaluate the prognostic impact of these genes on clinical outcomes in breast cancer.Methods:Patients included in this study were subdivided into two groups based on low and high messenger ribonucleic acid(mRNA)expression levels.Statistical analysis,including Kaplan-Meier curves,univariable,andmultivariable Cox regression analyses,was performed to assess metastasis-free survival(MFS)of mRNA expression of non-BRCA genes.Subgroup analyses were also conducted among four different molecular subtypes of eBC.Results:Our analysis revealed significant correlations between mRNA-expression levels of Ataxiatelangiectasia mutated(ATM),Bloom helicase gene(BLM),and WRN RecQ Like Helicase(WRN)and patient prognosis.High mRNA expression of ATM correlated with longer MFS in the entire cohort(p=0.022,Log Rank),and in luminal-B-like tumors(p=0.036).Lower mRNA expression of BLM was associated with favorable outcomes(p=0.011,Log Rank),particularly in triple-negative eBC(p=0.030,Log Rank).Finally,high levels of WRN mRNA expression correlated with significantly longerMFS compared to lowmRNA expression levels(p=0.009,Log Rank).Conclusions:This study underscores the prognostic significance of moderate penetrance breast cancer risk variant genes,such as ATM,BLM,and WRN,for survival outcomes in eBC.
基金supported by the Key Research and Development Program of Jiangsu Province under Grant BE2022059-3,CTBC Bank through the Industry-Academia Cooperation Project,as well as by the Ministry of Science and Technology of Taiwan through Grants MOST-108-2218-E-002-055,MOST-109-2223-E-009-002-MY3,MOST-109-2218-E-009-025,and MOST431109-2218-E-002-015.
文摘Micro-expressions(ME)recognition is a complex task that requires advanced techniques to extract informative features fromfacial expressions.Numerous deep neural networks(DNNs)with convolutional structures have been proposed.However,unlike DNNs,shallow convolutional neural networks often outperform deeper models in mitigating overfitting,particularly with small datasets.Still,many of these methods rely on a single feature for recognition,resulting in an insufficient ability to extract highly effective features.To address this limitation,in this paper,an Improved Dual-stream Shallow Convolutional Neural Network based on an Extreme Gradient Boosting Algorithm(IDSSCNN-XgBoost)is introduced for ME Recognition.The proposed method utilizes a dual-stream architecture where motion vectors(temporal features)are extracted using Optical Flow TV-L1 and amplify subtle changes(spatial features)via EulerianVideoMagnification(EVM).These features are processed by IDSSCNN,with an attention mechanism applied to refine the extracted effective features.The outputs are then fused,concatenated,and classified using the XgBoost algorithm.This comprehensive approach significantly improves recognition accuracy by leveraging the strengths of both temporal and spatial information,supported by the robust classification power of XgBoost.The proposed method is evaluated on three publicly available ME databases named Chinese Academy of Sciences Micro-expression Database(CASMEII),Spontaneous Micro-Expression Database(SMICHS),and Spontaneous Actions and Micro-Movements(SAMM).Experimental results indicate that the proposed model can achieve outstanding results compared to recent models.The accuracy results are 79.01%,69.22%,and 68.99%on CASMEII,SMIC-HS,and SAMM,and the F1-score are 75.47%,68.91%,and 63.84%,respectively.The proposed method has the advantage of operational efficiency and less computational time.
基金supported by the National Natural Science Foundation of China(62276049,61701078,61872068,and 62006038)the Natural Science Foundation of Sichuan Province(2025ZNSFSC0487)+3 种基金the Science and Technology Innovation 2030-Brain Science and Brain-Inspired Intelligence Project(2021ZD0200200)the National Key R&D Program of China(2023YFE0118600)Sichuan Province Science and Technology Support Program(2019YJ0193,2021YFG0126,2021YFG0366,and 2022YFS0180)Medico-Engineering Cooperation Funds from the University of Electronic Science and Technology of China(ZYGX2021YGLH014).
文摘Schizophrenia(SZ)stands as a severe psychiatric disorder.This study applied diffusion tensor imaging(DTI)data in conjunction with graph neural networks to distinguish SZ patients from normal controls(NCs)and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features,achieving an accuracy of 73.79%in distinguishing SZ patients from NCs.Beyond mere discrimination,our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis.These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers,providing novel insights into the neuropathological basis of SZ.In summary,our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
基金supported by the Academy of Finland(267581)the D2I SHOK Project from Digile Oy as well as Nokia Technologies(Tampere,Finland)
文摘Facial expression recognition is a hot topic in computer vision, but it remains challenging due to the feature inconsistency caused by person-specific 'characteristics of facial expressions. To address such a challenge, and inspired by the recent success of deep identity network (DeepID-Net) for face identification, this paper proposes a novel deep learning based framework for recognising human expressions with facial images. Compared to the existing deep learning methods, our proposed framework, which is based on multi-scale global images and local facial patches, can significantly achieve a better performance on facial expression recognition. Finally, we verify the effectiveness of our proposed framework through experiments on the public benchmarking datasets JAFFE and extended Cohn-Kanade (CK+).
基金partially supported by a Merit-Reviewed grant from the Department of Veterans Affairsa Peer-Reviewed Cancer Research Program grant from the Department of Defense (W81XWH-16-1-0488) to Y-FCL
文摘Testis specific protein Y-encoded（TSPY） is a Y-located proto-oncogene predominantly expressed in normal male germ cells and various types of germ cell tumor. Significantly, TSPY is frequently expressed in somatic cancers including liver cancer but not in adjacent normal tissues, suggesting that ectopic TSPY expression could be associated with oncogenesis in non-germ cell cancers. Various studies demonstrated that TSPY expression promotes growth and proliferation in cancer cells; however, its relationship to other oncogenic events in TSPY-positive cancers remains unknown. The present study seeks to correlate TSPY expression with other molecular features in clinical cancer samples, by analyses of RNA-seq transcriptome and DNA methylation data in the Cancer Genome Atlas（TCGA） database. A total of 53 genes,including oncogenic lineage protein 28 homolog B（LIN28B） gene and RNA-binding motif protein Y-linked（RBMY） gene, are identified to be consistently co-expressed with TSPY, and have been collectively designated as the TSPY co-expression network（TCN）. TCN genes were simultaneously activated in subsets of liver hepatocellular carcinoma（30%） and lung adenocarcinoma（10%） regardless of pathological stage, but only minimally in other cancer types. Further analysis revealed that the DNA methylation level was globally lower in the TCN-active than TCN-silent cancers. The specific expression and methylation patterns of TCN genes suggest that they could be useful as biomarkers for the diagnosis,prognosis and clinical management of cancers, especially those for liver and lung cancers, associated with TSPY co-expression network genes.
基金Supported by the National Natural Science Foundation of China(No.81271019No.61463046)Gansu Province Science Foundation for Youths(No.145RJYA282)
文摘AIM: To identify and understand the relationship between co-expression pattern and clinic traits in uveal melanoma, weighted gene co-expression network analysis(WGCNA) is applied to investigate the gene expression levels and patient clinic features. Uveal melanoma is the most common primary eye tumor in adults. Although many studies have identified some important genes and pathways that were relevant to progress of uveal melanoma, the relationship between co-expression and clinic traits in systems level of uveal melanoma is unclear yet. We employ WGCNA to investigate the relationship underlying molecular and phenotype in this study.METHODS: Gene expression profile of uveal melanoma and patient clinic traits were collected from the Gene Expression Omnibus(GEO) database. The gene co-expression is calculated by WGCNA that is the R package software. The package is used to analyze the correlation between pairs of expression levels of genes.The function of the genes were annotated by gene ontology(GO).RESULTS: In this study, we identified four co-expression modules significantly correlated with clinictraits. Module blue positively correlated with radiotherapy treatment. Module purple positively correlates with tumor location(sclera) and negatively correlates with patient age. Module red positively correlates with sclera and negatively correlates with thickness of tumor. Module black positively correlates with the largest tumor diameter(LTD). Additionally, we identified the hug gene(top connectivity with other genes) in each module. The hub gene RPS15 A, PTGDS, CD53 and MSI2 might play a vital role in progress of uveal melanoma.CONCLUSION: From WGCNA analysis and hub gene calculation, we identified RPS15 A, PTGDS, CD53 and MSI2 might be target or diagnosis for uveal melanoma.
基金supported by the National Natural Science Foundation of China (Nos. 31771467, 31571360 and 31371291)
文摘Maize （Zea mays） is the most widely grown grain crop in the world, playing important roles in agriculture and industry. However, the functions of maize genes remain largely unknown. High-quality genome- wide transcriptome datasets provide important biological knowledge which has been widely and suc- cessfully used in plants not only by measuring gene expression levels but also by enabling co-expression analysis for predicting gene functions and modules related to agronomic traits. Recently, thousands of maize transcriptomic data are available across different inbred lines, development stages, tissues, and treatments, or even across different tissue sections and cell lines. Here, we integrated 701 transcriptomic and 108 epigenomic data and studied the different conditional networks with multi-dimensional omics levels. We constructed a searchable, integrative, one-stop online platform, the maize conditional co- expression network （MCENet） platform. MCENet provides 10 global/conditional co-expression net- works, 5 network accessional analysis toolkits （i.e., Network Search, Network Remodel, Module Finder, Network Comparison, and Dynamic Expression View） and multiple network functional support toolkits （e.g., motif and module enrichment analysis）. We hope that our database might help plant research communities to identify maize functional genes or modules that regulate important agronomic traits.
基金supported by a Shanghai Leading Talents Project (54[2012])a Pudong New Area Leading Talents Project of Health System (PWR12011-02)
文摘Autophagy plays a vital role in cerebral ischemia and may be a potential target for developing novel therapy for stroke. In this study, we constructed an autophagy-related pathway network by analyzing the genes related to autophagy and ischemic stroke, and the risk genes were screened. Two autophagy-related modules were significantly up-regulated and clustered to influence cerebral ischemia. Besides, three key modular genes （NFKB1, RELA, and STAT3） were revealed. With 5-fold cross validation, the ROC curves of NFKB1, RELA, and STAT3 were 0.8256, 0.8462, and 0.8923. They formed a complex module and competitively mediated the activation of autophagy in cerebral ischemia. In conclusion, a module containing NFKB1, RELA, and STAT3 mediates autophagy, serving as a potential biomarker for the diagnosis and therapy of ischemic stroke.
文摘Esophageal cancer is a common malignant tumor, whose pathogenesis and prognosis factors are not fully understood. This study aimed to discover the gene clusters that have similar functions and can be used to predict the prognosis of esophageal cancer. The matched microarray and RNA sequencing data of 185 patients with esophageal cancer were downloaded from The Cancer Genome Atlas(TCGA), and gene co-expression networks were built without distinguishing between squamous carcinoma and adenocarcinoma. The result showed that 12 modules were associated with one or more survival data such as recurrence status, recurrence time, vital status or vital time. Furthermore, survival analysis showed that 5 out of the 12 modules were related to progression-free survival(PFS) or overall survival(OS). As the most important module, the midnight blue module with 82 genes was related to PFS, apart from the patient age, tumor grade, primary treatment success, and duration of smoking and tumor histological type. Gene ontology enrichment analysis revealed that 'glycoprotein binding' was the top enriched function of midnight blue module genes. Additionally, the blue module was the exclusive gene clusters related to OS. Platelet activating factor receptor(PTAFR) and feline Gardner-Rasheed(FGR) were the top hub genes in both modeling datasets and the STRING protein interaction database. In conclusion, our study provides novel insights into the prognosis-associated genes and screens out candidate biomarkers for esophageal cancer.
文摘Based on the heat flow data published in 1990 and 2001, a study of the factors influencing the terrestrial heat flow distribution in the China continent and its quantitative expression is carried out using the ＂Netlike Plastic-Flow＂ continental dynamics model and the methods of statistic analysis and optimum fitting. The result indicates that the factors influencing the heat flow distribution is classified into two groups, i.e. background and tectonic ones, in which the former mainly involves the non- uniform distribution of mantle heat flow, heat production of radioactive dements in the crust, heattransfer media and hydrothermal circulation, while the latter mainly involves plastic-flow networks and relatively-stable blocks. The plastic-flow network is a manifestation of shear localization in the netlike plastic-flow process in the lower lithosphere, which is composed of two sets of plastic-flow belts （PFBs） intersecting each other and, as one of the basic action regimes, controls the intraplate tectonic deformation. Relatively stable blocks （RSBs）, which are the tectonic units with relatively-high viscosities existing in the netlike plastic-flow field, as one of the principal origins, result in the development of large-seale compressional basins. PFB and RSB, as the active and quiet states of tectonic deformation, give rise to the higher and lower heat flow values, respectivdy. The provincial average heat flow in continent can be estimated using the expression qav = q0 ＋ a Pbt-c Pbk, where the three terms of the right side are background heat flow, PFB-positive contribution and RSB-negative contribution, Pbt and Pbk are the PFB- and RSB-coverage ratios, respectively, a is the coefficient of PFB- positive contribution depending mainly on the strain in the lower lithosphere, and c is the coefficient of RSB-negative contribution related mainly to the thickness of the lithosphere, the aseismic-area ratio and the tectonic age. For the major portion of the China continent excluding some of the southeastern region of China, the confidence interval of the provincial average background heat flow is qo=57.25±24.8 mW/m^2 and the PFB-positive- and RSB-negative-contribution coefficients are a=14.8-71.9 mW/m^2 and c=0-25.6 mW/m^2, respectively. The concepts of PFB and RSB effects and the heat flow expression suggested provide a new choice of the approach to the quantitative description of the characteristics of heat flow distribution in continent and their physical mechanisms.
文摘Facial Expression Recognition(FER)has been an interesting area of research in places where there is human-computer interaction.Human psychol-ogy,emotions and behaviors can be analyzed in FER.Classifiers used in FER have been perfect on normal faces but have been found to be constrained in occluded faces.Recently,Deep Learning Techniques(DLT)have gained popular-ity in applications of real-world problems including recognition of human emo-tions.The human face reflects emotional states and human intentions.An expression is the most natural and powerful way of communicating non-verbally.Systems which form communications between the two are termed Human Machine Interaction(HMI)systems.FER can improve HMI systems as human expressions convey useful information to an observer.This paper proposes a FER scheme called EECNN(Enhanced Convolution Neural Network with Atten-tion mechanism)to recognize seven types of human emotions with satisfying results in its experiments.Proposed EECNN achieved 89.8%accuracy in classi-fying the images.
基金supported by the Agricultural Science and Technology Innovation Program(CAAS-ASTIP-2016-ZFRI)National Key R&D Program of China(2018YFD0100704)the China Agriculture Research System(CARS-25-03)+1 种基金National Natural Science Foundation of China[31672178&31471893]Scientific and Technological Project of Henan Province(202102110197).
文摘The organoleptic qualities of watermelon fruit are defined by the sugar and organic acid contents,which undergo considerable variations during development and maturation.The molecular mechanisms underlying these variations remain unclear.In this study,we used transcriptome profiles to investigate the coexpression patterns of gene networks associated with sugar and organic acid metabolism.We identified 3 gene networks/modules containing 2443 genes highly correlated with sugars and organic acids.Within these modules,based on intramodular significance and Reverse Transcription Quantitative polymerase chain reaction(RT-qPCR),we identified 7 genes involved in the metabolism of sugars and organic acids.Among these genes,Cla97C01G000640,Cla97C05G087120 and Cla97C01G018840(r^(2)=0.83 with glucose content)were identified as sugar transporters(SWEET,EDR6 and STP)and Cla97C03G064990(r^(2)=0.92 with sucrose content)was identified as a sucrose synthase from information available for other crops.Similarly,Cla97C07G128420,Cla97C03G068240 and Cla97C01G008870,having strong correlations with malic(r^(2)=0.75)and citric acid(r^(2)=0.85),were annotated as malate and citrate transporters(ALMT7,CS,and ICDH).The expression profiles of these 7 genes in diverse watermelon genotypes revealed consistent patterns of expression variation in various types of watermelon.These findings add significantly to our existing knowledge of sugar and organic acid metabolism in watermelon.
基金This work was supported by the National Natural Science Foundation of China （Nos. 61374065, 61503225）, the Research Fund for the Taishan Scholar Project of Shandong Province, and the Natural Science Foundation of Shandong Province （No. ZR2015FQ003）.
文摘This paper investigates epidemic dynamics over dynamic networks via the approach of semi-tensor product of matrices. First, a formal susceptible-infected-susceptible epidemic dynamic model over dynamic networks （SISED-DN） is given. Second, based on a class of determinate co-evolutionary rule, the matrix expressions are established for the dynamics of individual states and network topologies, respectively. Then, all possible final spreading equilibria are obtained for any given initial epidemic state and network topology by the matrix expression. Third, a sufficient and necessary condition of the existence of state feedback vaccination control is presented to make every individual susceptible. The study of illustrative examples shows the effectiveness of our new results.
基金the following funds:The Key Scientific Research Project of Anhui Provincial Research Preparation Plan in 2023(Nos.2023AH051806,2023AH052097,2023AH052103)Anhui Province Quality Engineering Project(Nos.2022sx099,2022cxtd097)+1 种基金University-Level Teaching and Research Key Projects(Nos.ch21jxyj01,XLZ-202208,XLZ-202106)Special Support Plan for Innovation and Entrepreneurship Leaders in Anhui Province。
文摘Convolutional neural networks struggle to accurately handle changes in angles and twists in the direction of images,which affects their ability to recognize patterns based on internal feature levels. In contrast, CapsNet overcomesthese limitations by vectorizing information through increased directionality and magnitude, ensuring that spatialinformation is not overlooked. Therefore, this study proposes a novel expression recognition technique calledCAPSULE-VGG, which combines the strengths of CapsNet and convolutional neural networks. By refining andintegrating features extracted by a convolutional neural network before introducing theminto CapsNet, ourmodelenhances facial recognition capabilities. Compared to traditional neural network models, our approach offersfaster training pace, improved convergence speed, and higher accuracy rates approaching stability. Experimentalresults demonstrate that our method achieves recognition rates of 74.14% for the FER2013 expression dataset and99.85% for the CK+ expression dataset. By contrasting these findings with those obtained using conventionalexpression recognition techniques and incorporating CapsNet’s advantages, we effectively address issues associatedwith convolutional neural networks while increasing expression identification accuracy.
