Vehicle Logo Recognition Using Spatial Structure Correlation and YOLO-T.

The vehicle logo contains the vehicle's identity information, so vehicle logo detection (VLD) technology has extremely important significance. Although the VLD field has been studied for many years, the detection task is still difficult due to the small size of the vehicle logo and the background interference problem. To solve these problems, this paper proposes a method of VLD based on the YOLO-T model and the correlation of the vehicle space structure. Aiming at the small size of the vehicle logo, we propose a vehicle logo detection network called YOLO-T. It integrates multiple receptive fields and establishes a multi-scale detection structure suitable for VLD tasks. In addition, we design an effective pre-training strategy to improve the detection accuracy of YOLO-T. Aiming at the background interference, we use the position correlation between the vehicle lights and the vehicle logo to extract the region of interest of the vehicle logo. This measure not only reduces the search area but also weakens the background interference. We have labeled a new vehicle logo dataset named LOGO-17, which contains 17 different categories of vehicle logos. The experimental results show that our proposed method achieves high detection accuracy and outperforms the existing vehicle logo detection methods.

Teasing apart the joint effect of demography and natural selection in the birth of a contact zone.

Vast population movements induced by recurrent climatic cycles have shaped the genetic structure of plant species. During glacial periods species were confined to low-latitude refugia from which they recolonized higher latitudes as the climate improved. This multipronged recolonization led to many lineages that later met and formed large contact zones. We utilize genomic data from 5000 Picea abies trees to test for the presence of natural selection during recolonization and establishment of a contact zone in Scandinavia. Scandinavian P. abies is today made up of a southern genetic cluster originating from the Baltics, and a northern one originating from Northern Russia. The contact zone delineating them closely matches the limit between two major climatic regions. We show that natural selection contributed to its establishment and maintenance. First, an isolation-with-migration model with genome-wide linked selection fits the data better than a purely neutral one. Second, many loci show signatures of selection or are associated with environmental variables. These loci, regrouped in clusters on chromosomes, are often related to phenology. Altogether, our results illustrate how climatic cycles, recolonization and selection can establish strong local adaptation along contact zones and affect the genetic architecture of adaptive traits.

Genetic architecture behind developmental and seasonal control of tree growth and wood properties in Norway spruce.

Genetic control of tree growth and wood formation varies depending on the age of the tree and the time of the year. Single-locus, multi-locus, and multi-trait genome-wide association studies (GWAS) were conducted on 34 growth and wood property traits in 1,303 Norway spruce individuals using exome capture to cover ~130K single-nucleotide polymorphisms (SNPs). GWAS identified associations to the different wood traits in a total of 85 gene models, and several of these were validated in a progenitor population. A multi-locus GWAS model identified more SNPs associated with the studied traits than single-locus or multivariate models. Changes in tree age and annual season influenced the genetic architecture of growth and wood properties in unique ways, manifested by non-overlapping SNP loci. In addition to completely novel candidate genes, SNPs were located in genes previously associated with wood formation, such as cellulose synthases and a NAC transcription factor, but that have not been earlier linked to seasonal or age-dependent regulation of wood properties. Interestingly, SNPs associated with the width of the year rings were identified in homologs of Arabidopsis thaliana BARELY ANY MERISTEM 1 and rice BIG GRAIN 1, which have been previously shown to control cell division and biomass production. The results provide tools for future Norway spruce breeding and functional studies.

The Chinese pine genome and methylome unveil key features of conifer evolution.

Conifers dominate the world's forest ecosystems and are the most widely planted tree species. Their giant and complex genomes present great challenges for assembling a complete reference genome for evolutionary and genomic studies. We present a 25.4-Gb chromosome-level assembly of Chinese pine (Pinus tabuliformis) and revealed that its genome size is mostly attributable to huge intergenic regions and long introns with high transposable element (TE) content. Large genes with long introns exhibited higher expressions levels. Despite a lack of recent whole-genome duplication, 91.2% of genes were duplicated through dispersed duplication, and expanded gene families are mainly related to stress responses, which may underpin conifers' adaptation, particularly in cold and/or arid conditions. The reproductive regulation network is distinct compared with angiosperms. Slow removal of TEs with high-level methylation may have contributed to genomic expansion. This study provides insights into conifer evolution and resources for advancing research on conifer adaptation and development.

Leveraging breeding programs and genomic data in Norway spruce (Picea abies L. Karst) for GWAS analysis.

BACKGROUND: Genome-wide association studies (GWAS) identify loci underlying the variation of complex traits. One of the main limitations of GWAS is the availability of reliable phenotypic data, particularly for long-lived tree species. Although an extensive amount of phenotypic data already exists in breeding programs, accounting for its high heterogeneity is a great challenge. We combine spatial and factor-analytics analyses to standardize the heterogeneous data from 120 field experiments of 483,424 progenies of Norway spruce to implement the largest reported GWAS for trees using 134 605 SNPs from exome sequencing of 5056 parental trees. RESULTS: We identify 55 novel quantitative trait loci (QTLs) that are associated with phenotypic variation. The largest number of QTLs is associated with the budburst stage, followed by diameter at breast height, wood quality, and frost damage. Two QTLs with the largest effect have a pleiotropic effect for budburst stage, frost damage, and diameter and are associated with MAP3K genes. Genotype data called from exome capture, recently developed SNP array and gene expression data indirectly support this discovery. CONCLUSION: Several important QTLs associated with growth and frost damage have been verified in several southern and northern progeny plantations, indicating that these loci can be used in QTL-assisted genomic selection. Our study also demonstrates that existing heterogeneous phenotypic data from breeding programs, collected over several decades, is an important source for GWAS and that such integration into GWAS should be a major area of inquiry in the future.

Genetic control of tracheid properties in Norway spruce wood.

Through the use of genome-wide association studies (GWAS) mapping it is possible to establish the genetic basis of phenotypic trait variation. Our GWAS study presents the first such effort in Norway spruce (Picea abies (L). Karst.) for the traits related to wood tracheid characteristics. The study employed an exome capture genotyping approach that generated 178 101 Single Nucleotide Polymorphisms (SNPs) from 40 018 probes within a population of 517 Norway spruce mother trees. We applied a least absolute shrinkage and selection operator (LASSO) based association mapping method using a functional multi-locus mapping approach, with a stability selection probability method as the hypothesis testing approach to determine significant Quantitative Trait Loci (QTLs). The analysis has provided 30 significant associations, the majority of which show specific expression in wood-forming tissues or high ubiquitous expression, potentially controlling tracheids dimensions, their cell wall thickness and microfibril angle. Among the most promising candidates based on our results and prior information for other species are: Picea abies BIG GRAIN 2 (PabBG2) with a predicted function in auxin transport and sensitivity, and MA_373300g0010 encoding a protein similar to wall-associated receptor kinases, which were both associated with cell wall thickness. The results demonstrate feasibility of GWAS to identify novel candidate genes controlling industrially-relevant tracheid traits in Norway spruce.

Association genetics identifies a specifically regulated Norway spruce laccase gene, PaLAC5, linked to Heterobasidion parviporum resistance.

It is important to improve the understanding of the interactions between the trees and pathogens and integrate this knowledge about disease resistance into tree breeding programs. The conifer Norway spruce (Picea abies) is an important species for the forest industry in Europe. Its major pathogen is Heterobasidion parviporum, causing stem and root rot. In this study, we identified 11 Norway spruce QTLs (Quantitative trait loci) that correlate with variation in resistance to H. parviporum in a population of 466 trees by association genetics. Individual QTLs explained between 2.1 and 5.2% of the phenotypic variance. The expression of candidate genes associated with the QTLs was analysed in silico and in response to H. parviporum hypothesizing that (a) candidate genes linked to control of fungal sapwood growth are more commonly expressed in sapwood, and; (b) candidate genes associated with induced defences are respond to H. parviporum inoculation. The Norway spruce laccase PaLAC5 associated with control of lesion length development is likely to be involved in the induced defences. Expression analyses showed that PaLAC5 responds specifically and strongly in close proximity to the H. parviporum inoculation. Thus, PaLAC5 may be associated with the lignosuberized boundary zone formation in bark adjacent to the inoculation site.

Effect of number of annual rings and tree ages on genomic predictive ability for solid wood properties of Norway spruce.

BACKGROUND: Genomic selection (GS) or genomic prediction is considered as a promising approach to accelerate tree breeding and increase genetic gain by shortening breeding cycle, but the efforts to develop routines for operational breeding are so far limited. We investigated the predictive ability (PA) of GS based on 484 progeny trees from 62 half-sib families in Norway spruce (Picea abies (L.) Karst.) for wood density, modulus of elasticity (MOE) and microfibril angle (MFA) measured with SilviScan, as well as for measurements on standing trees by Pilodyn and Hitman instruments. RESULTS: GS predictive abilities were comparable with those based on pedigree-based prediction. Marker-based PAs were generally 25-30% higher for traits density, MFA and MOE measured with SilviScan than for their respective standing tree-based method which measured with Pilodyn and Hitman. Prediction accuracy (PC) of the standing tree-based methods were similar or even higher than increment core-based method. 78-95% of the maximal PAs of density, MFA and MOE obtained from coring to the pith at high age were reached by using data possible to obtain by drilling 3-5 rings towards the pith at tree age 10-12. CONCLUSIONS: This study indicates standing tree-based measurements is a cost-effective alternative method for GS. PA of GS methods were comparable with those pedigree-based prediction. The highest PAs were reached with at least 80-90% of the dataset used as training set. Selection for trait density could be conducted at an earlier age than for MFA and MOE. Operational breeding can also be optimized by training the model at an earlier age or using 3 to 5 outermost rings at tree age 10 to 12 years, thereby shortening the cycle and reducing the impact on the tree.

Genotypic variation in Norway spruce correlates to fungal communities in vegetative buds.

The taxonomically diverse phyllosphere fungi inhabit leaves of plants. Thus, apart from the fungi's dispersal capacities and environmental factors, the assembly of the phyllosphere community associated with a given host plant depends on factors encoded by the host's genome. The host genetic factors and their influence on the assembly of phyllosphere communities under natural conditions are poorly understood, especially in trees. Recent work indicates that Norway spruce (Picea abies) vegetative buds harbour active fungal communities, but these are hitherto largely uncharacterized. This study combines internal transcribed spacer sequencing of the fungal communities associated with dormant vegetative buds with a genome-wide association study (GWAS) in 478 unrelated Norway spruce trees. The aim was to detect host loci associated with variation in the fungal communities across the population, and to identify loci correlating with the presence of specific, latent, pathogens. The fungal communities were dominated by known Norway spruce phyllosphere endophytes and pathogens. We identified six quantitative trait loci (QTLs) associated with the relative abundance of the dominating taxa (i.e., top 1% most abundant taxa). Three additional QTLs associated with colonization by the spruce needle cast pathogen Lirula macrospora or the cherry spruce rust (Thekopsora areolata) in asymptomatic tissues were detected. The identification of the nine QTLs shows that the genetic variation in Norway spruce influences the fungal community in dormant buds and that mechanisms underlying the assembly of the communities and the colonization of latent pathogens in trees may be uncovered by combining molecular identification of fungi with GWAS.

Vehicle Logo Recognition Based on Enhanced Matching for Small Objects, Constrained Region and SSFPD Network.

Vehicle Logo Recognition (VLR) is an important part of vehicle behavior analysis and can provide supplementary information for vehicle identification, which is an essential research topic in robotic systems. However, the inaccurate extraction of vehicle logo candidate regions will affect the accuracy of logo recognition. Additionally, the existing methods have low recognition rate for most small vehicle logos and poor performance under complicated environments. A VLR method based on enhanced matching, constrained region extraction and SSFPD network is proposed in this paper to solve the aforementioned problems. A constrained region extraction method based on segmentation of the car head and car tail is proposed to accurately extract the candidate region of logo. An enhanced matching method is proposed to improve the detection performance of small objects, which augment each of training images by copy-pasting small objects many times in the unconstrained region. A single deep neural network based on a reduced ResNeXt model and Feature Pyramid Networks is proposed in this paper, which is named as Single Shot Feature Pyramid Detector (SSFPD). The SSFPD uses the reduced ResNeXt to improve classification performance of the network and retain more detailed information for small-sized vehicle logo detection. Additionally, it uses the Feature Pyramid Networks module to bring in more semantic context information to build several high-level semantic feature maps, which effectively improves recognition performance. Extensive evaluations have been made on self-collected and public vehicle logo datasets. The proposed method achieved 93.79% accuracy on the Common Vehicle Logos Dataset and 99.52% accuracy on another public dataset, respectively, outperforming the existing methods.

Genome-wide association study identified novel candidate loci affecting wood formation in Norway spruce.

Norway spruce is a boreal forest tree species of significant ecological and economic importance. Hence there is a strong imperative to dissect the genetics underlying important wood quality traits in the species. We performed a functional genome-wide association study (GWAS) of 17 wood traits in Norway spruce using 178 101 single nucleotide polymorphisms (SNPs) generated from exome genotyping of 517 mother trees. The wood traits were defined using functional modelling of wood properties across annual growth rings. We applied a Least Absolute Shrinkage and Selection Operator (LASSO-based) association mapping method using a functional multilocus mapping approach that utilizes latent traits, with a stability selection probability method as the hypothesis testing approach to determine a significant quantitative trait locus. The analysis provided 52 significant SNPs from 39 candidate genes, including genes previously implicated in wood formation and tree growth in spruce and other species. Our study represents a multilocus GWAS for complex wood traits in Norway spruce. The results advance our understanding of the genetics influencing wood traits and identifies candidate genes for future functional studies.

Systems mapping for hematopoietic progenitor cell heterogeneity.

Cells with the same genotype growing under the same conditions can show different phenotypes, which is known as "population heterogeneity". The heterogeneity of hematopoietic progenitor cells has an effect on their differentiation potential and lineage choices. However, the genetic mechanisms governing population heterogeneity remain unclear. Here, we present a statistical model for mapping the quantitative trait locus (QTL) that affects hematopoietic cell heterogeneity. This strategy, termed systems mapping, integrates a system of differential equations into the framework for systems mapping, allowing hypotheses regarding the interplay between genetic actions and cell heterogeneity to be tested. A simulation approach based on cell heterogeneity dynamics has been designed to test the statistical properties of the model. This model not only considers the traditional QTLs, but also indicates the methylated QTLs that can illustrate non-genetic individual differences. It has significant implications for probing the molecular, genetic and epigenetic mechanisms of hematopoietic progenitor cell heterogeneity.

A model for computing genes governing marital dissolution through sentimental dynamics.

Adverse sentimental relationships that cause marital dissolution may involve a genetic component composed of genes from a couple, which interact with cultural, sociological, psychological and economic factors. However, the identification of these genes is very challenging. Here, we address this challenge by developing a computational model that can identify specific genes that impact on sentimental relationships of couples. The model was derived by implementing the second law of thermodynamics that quantifies sentimental relationships within a dynamic gene identification framework, called systems mapping. The model is equipped with a capacity to characterize and test the pattern of how genes from a couple interact with each other to determine the dynamic behavior of their marital relationships. The testing procedure is based on comparing genotypic differences in mathematical parameters of sentimental dynamics described by a group of ordinary differential equations (ODE). The model allows the test of individual parameters or a combination of parameters, addressing specific details related to martial relationships. The model may find its implications for designing an optimal effort policy and therapy to maintain a harmonic family in light of genetic blueprints of individual couples.

Isolation and mapping of telomeric pentanucleotide (TAACC)n repeats of the Pacific whiteleg shrimp, Penaeus vannamei, using fluorescence in situ hybridization.

To develop genetic and physical maps for shrimp, accurate information on the actual number of chromosomes and a large number of genetic markers is needed. Previous reports have shown two different chromosome numbers for the Pacific whiteleg shrimp, Penaeus vannamei, the most important penaeid shrimp species cultured in the Western hemisphere. Preliminary results obtained by direct sequencing of clones from a Sau3A-digested genomic library of P. vannamei ovary identified a large number of (TAACC/GGTTA)-containing SSRs. The objectives of this study were to (1) examine the frequency of (TAACC)n repeats in 662 P. vannamei genomic clones that were directly sequenced, and perform homology searches of these clones, (2) confirm the number of chromosomes in testis of P. vannamei, and (3) localize the TAACC repeats in P. vannamei chromosome spreads using fluorescence in situ hybridization (FISH). Results for objective 1 showed that 395 out of the 662 clones sequenced contained single or multiple SSRs with three or more repeat motifs, 199 of which contained variable tandem repeats of the pentanucleotide (TAACC/GGTTA)n, with 3 to 14 copies per sequence. The frequency of (TAACC)n repeats in P. vannamei is 4.68 kb for SSRs with five or more repeat motifs. Sequence comparisons using the BLASTN nonredundant and expressed sequence tag (EST) databases indicated that most of the TAACC-containing clones were similar to either the core pentanucleotide repeat in PVPENTREP locus (GenBank accession no. X82619) or portions of 28S rRNA. Transposable elements (transposase for Tn1000 and reverse transcriptase family members), hypothetical or unnamed protein products, and genes of known function such as 18S and 28S rRNAs, heat shock protein 70, and thrombospondin were identified in non-TAACC-containing clones. For objective 2, the meiotic chromosome number of P. vannamei was confirmed as N = 44. For objective 3, four FISH probes (P1 to P4) containing different numbers of TAACC repeats produced positive signals on telomeres of P. vannamei chromosomes. A few chromosomes had positive signals interstitially. Probe signal strength and chromosome coverage differed in the general order of P1>P2>P3>P4, which correlated with the length of TAACC repeats within the probes: 83, 66, 35, and 30 bp, respectively, suggesting that the TAACC repeats, and not the flanking sequences, produced the TAACC signals at chromosome ends and TAACC is likely the telomere sequence for P. vannamei.

Gonad development characteristics and sex ratio in triploid Chinese shrimp ( Fenneropenaeus chinensis).

This paper details for the first time the gonad development characteristics and sex ratio of triploid shrimp ( Fenneropenaeus chinensis). In triploid shrimp the development of gonad is apparently impaired, especially in females. In the ovary of triploids, germ cells mainly remain at oogonia stage during September through December. From January to February of the next year, partial primary oocytes developed in the ovary lobes. Spermatocytes and spermatids could be observed in the testes of triploids, and a few sperm were observed in the vas deferens and spermatophores. The morphology of sperms in triploid shrimp was abnormal. Flow cytometry was used to detect the ploidy of sperm in the vas deferens. The data showed that triploidy could affect the sex ratio in Chinese shrimp. The female-to-male ratio in triploids of about 4:1 will favor triploid shrimp aquaculture.