22 research outputs found
Electrochemiluminescence Studies of Phosphorescent Dopant and Host Molecules of Polymer Light-emitting Diodes
No full text
Study on Short Text Clustering with Unsupervised SimCSE
No full textTraditional shallow text clustering methods face challenges such as limited context information,irregular use of words,and few words with actual meaning when clustering short texts,resulting in sparse embedding representations of the text and difficulty in extracting key features.To address these issues,a deep clustering model SSKU(SBERT SimCSE Kmeans Umap) incorporating simple data augmentation methods is proposed in the paper.The model uses SBERT to embed short texts and fine-tunes the text embedding model using the unsupervised SimCSE method in conjunction with the deep clustering KMeans algorithm to improve the embedding representation of short texts to make them suitable for clustering.To improve the sparse features of short text and optimize the embedding results,Umap manifold dimension reduction method is used to learn the local manifold structure.Using K-Means algorithm to cluster the dimensionality-reduced embeddings,and the clustering results are obtained.Extensive experiments are carried out on four publicly available short text datasets,such as StackOverFlow and Biomedical, and compared with the latest deep clustering algorithms.The results show that the proposed model exhibits good clustering performance in terms of both accuracy and standard mutual information evaluation metrics
Linear-Time Direct Data Assignment Algorithm for Passive Sensor Measurements
No full textTo solve the problem of passive sensor data association in multi-sensor multi-target tracking, a novel linear-time direct data assignment (DDA) algorithm is proposed in this paper. Different from existing methods which solve the data association problem in the measurement domain, the proposed algorithm solves the problem directly in the target state domain. The number and state of candidate targets are preset in the region of interest, which can avoid the problem of combinational explosion. The time complexity of the proposed algorithm is linear with the number of sensors and targets while that of the existing algorithms are exponential. Computer simulations show that the proposed algorithm can achieve almost the same association accuracy as the existing algorithms, but the time consumption can be significantly reduced
Mapping of QTLs for Rice Grain Size Based on High-density Genetic Map
No full text【Objective】Grain size is one of the main agronomic traits affecting rice yield. A recombinant inbred line population derived from indica rice variety V20B and slender javanica rice variety CPSLO17 was used for QTL mapping of brown rice grain size. It aims to explore the genetically-stable main effect QTLs, providing new genetic resources and scientific basis for developing high-quality and high-yield rice varieties.【Method】Based on the high-density genetic linkage map of V20B/CPSLO17 genetic background, the brown rice grain size phenotype data of 150 recombinant inbred lines under four environments (Guiyang, Guizhou in 2019, Guiyang, Guizhou in 2020, Guiding, Guizhou in 2021, and Sanya, Hainan in 2021) were used for QTL scanning by the ICIM-ADD method of IciMapping 4.0 software.【Result】The grain size of brown rice from parent V20B was significantly larger than that from CPSLO17, and the grain sizes of brown rice from recombinant inbred lines showed significant differences among the four environments, all exhibiting a continuous unimodal distribution. A total of 11 QTLs related to brown rice grain size distributed on 7 chromosomes were found in the four environments, with their LOD values ranging from 3.00 to 14.57. Four QTLs including qRGS5, qRGS7.1, qRGS7.2, and qRGS11.3 had a phenotypic variance explained (PVE) over 10%, of which the qRGS5 was repeatedly detected in all four environments, with its PVE of 29.71%, 28.77%, 17.27% and 12.50%, respectively. The synergistic alleles of three QTLs (qRGS2.1, qRGS2.2 and qRGS12) derived from the parent CPSLO17, while the other eight synergistic alleles (qRGS4.1, qRGS5, qRGS7.1, qRGS7.2, qRGS8, qRGS11.1, qRGS11.2 and qRGS11.3) derived from the parent V20B, and the synergistic alleles of QTL qRGS5 detected in all four environments derived from the parent V20B.【Conclusion】The difference of brown rice grain size between parents V20B and CPSLO17 is extremely significant. The brown rice grain size trait is affected by the environments. The QTL qRGS5 is a genetically-stable main effect QTL that affects grain size in brown rice, which has practical value in new gene discovery for brown rice grain size and molecular breeding for high-yield and high-quality rice
Analysis on Mapping of Rice Grain Thickness QTLs under Multiple Environments
No full text【Objective】Grain thickness is one of the controlling factors affecting rice yield and taste quality of rice. QTL mapping for grain thickness in rice was conducted by using recombinant inbred lines (RIL) with the indica-japonica cross (V20B/CPSLO17) genetic background and major QTLs of grain thickness were obtained, providing a scientific basis for the discovery of new grain thickness genes and the development of functional molecular markers.【Method】Based on the highdensity genetic linkage map and the indica-japonica cross genetic background of RIL populations, combined with the grain thickness phenotype data of RIL populations under three different ecological environments (Guiyang, Guizhou in 2020; Guiding, Guizhou in 2021; Sanya, Hainan in 2021), QTL mapping and genetic effect analysis were performed by the ICIM-ADD method of IciMapping 4.0 software.【Result】The study showed that the grain thickness trait in rice exhibited a continuous unimodal distribution under all three ecological environments and was not affected by planting environmental factors significantly. Five grain thickness QTLs (qGT3-1, qGT5-1, qGT5-2, qGT8-1, and qGT10-1) were detected on chromosomes 3, 5, 8, and 10 in rice under the three different ecological environments. The beneficial alleles of these five QTLs were all from the parent V20B, with LOD values ranging from 3.431 to 14.081 and a range of phenotypic contribution rates from 5.479% to 26.483%. Two QTLs (qGT5-1 and qGT5-2) had a phenotypic contribution rate greater than 10%, with qGT5-2 being the only one repeatedly detected in two planting environments (Guiyang, Guizhou in 2020 and Sanya, Hainan in 2021), explaining 26.483% and 14.933% of the population's phenotypic variance, respectively. The physical distance of QTL qGT5-2 on the chromosome was about 3.9 kb, with only one candidate gene (LOC_Os05g07920); the physical distance of qGT8-1 was about 2.3 kb, with only one candidate gene (LOC_Os08g10360).【Conclusion】Grain thickness in rice is a quantitative genetic trait regulated by multiple genes. qGT5-2 is major QTL with stable heredity and high contribution rate for grain thickness, which has significant application potential in the discovery of grain thickness regulatory genes and the breeding of new high-quality and high-yield rice varieties
Recommended from our members
The automatic identification and prioritisation of criminal networks from police crime data
No full textThe identification of criminal networks is not a routine exploratory process within the current practice of the law enforcement authorities; rather it is triggered by specific evidence of criminal activity being investigated. A network is identified when a criminal comes to notice and any associates who could also be potentially implicated would need to be identified if only to be eliminated from the enquiries as suspects or witnesses as well as to prevent and/or detect crime. However, an identified network may not be the one causing most harm in a given area.. This paper identifies a methodology to identify all of the criminal networks that are present within a Law Enforcement Area, and, prioritises those that are causing most harm to the community. Each crime is allocated a score based on its crime type and how recently the crime was committed; the network score, which can be used as decision support to help prioritise it for law enforcement purposes, is the sum of the individual crime scores
Dielectric Loss and Electrical Conductivity Behaviors of Epoxy Composites Containing Semiconducting ZnO Varistor Particles
No full textPolymer nanodielectrics render a great material platform for exhibiting the intrinsic nature of incorporated particles, particularly semiconducting types, and their interfaces with the polymer matrix. Incorporating the oxide fillers with higher loading percentages (>40 vol%) encounters particular challenges in terms of dispersion, homogeneous distribution, and porosity from the process. This work investigated the dielectric loss and electrical conduction behaviors of composites containing semiconducting ZnO varistor particles of various concentrations using the epoxy impregnation method. The ZnO varistor particles increased the dielectric permittivity, loss, and electrical conductivity of the epoxy composites into three different regimes (0–50 vol%, 50–70 vol%, 70–100 vol%), particularly under an electric bias field or at higher temperatures. For lower loading fractions below 50 vol%, the dielectric responses are dominated by the insulating epoxy matrix. When loading fractions are between 50 and 70 vol%, the dielectric and electric responses are mostly associated with the semiconducting interfaces of ZnO varistor particles and ZnO–epoxy. At above 70 vol%, the apparent increase in the dielectric loss and conductivity is primarily associated with the conducting ZnO core forming the interconnected channels of electric conduction. The foam-agent-assisted ZnO varistor particle framework appears to be a better way of fabricating composites of filler loading above 80 vol%. A physical model using an equivalent capacitor, diode, and resistor in the epoxy composites was proposed to explain the different property behaviors
Hierarchical BiOCl Hollow Microspheres Assembled by Ultrathin Nanosheets with Large Surface Area for the Exceptional Visible Light Photocatalytic Activity
No full textAdministration of <i>Lactobacillus paracasei</i> ameliorates type 2 diabetes in mice
No full text
Lactobacillus paracasei TD062 with high inhibitory activity ameliorated lipid metabolism, oxidative stress, glucose metabolism and the PI3K/Akt pathway in diabetic mice, and the effects were dose-dependent to some extent.</p
