Iterative Object and Part Transfer for Fine-Grained Recognition

The aim of fine-grained recognition is to identify sub-ordinate categories in images like different species of birds. Existing works have confirmed that, in order to capture the subtle differences across the categories, automatic localization of objects and parts is critical. Most approaches for object and part localization relied on the bottom-up pipeline, where thousands of region proposals are generated and then filtered by pre-trained object/part models. This is computationally expensive and not scalable once the number of objects/parts becomes large. In this paper, we propose a nonparametric data-driven method for object and part localization. Given an unlabeled test image, our approach transfers annotations from a few similar images retrieved in the training set. In particular, we propose an iterative transfer strategy that gradually refine the predicted bounding boxes. Based on the located objects and parts, deep convolutional features are extracted for recognition. We evaluate our approach on the widely-used CUB200-2011 dataset and a new and large dataset called Birdsnap. On both datasets, we achieve better results than many state-of-the-art approaches, including a few using oracle (manually annotated) bounding boxes in the test images.Comment: To appear in ICME 2017 as an oral pape

FPGA-Based On-Board Geometric Calibration for Linear CCD Array Sensors

With increasing demands in real-time or near real-time remotely sensed imagery applications in such as military deployments, quick response to terrorist attacks and disaster rescue, the on-board geometric calibration problem has attracted the attention of many scientists in recent years. This paper presents an on-board geometric calibration method for linear CCD sensor arrays using FPGA chips. The proposed method mainly consists of four modules—Input Data, Coefficient Calculation, Adjustment Computation and Comparison—in which the parallel computations for building the observation equations and least squares adjustment, are implemented using FPGA chips, for which a decomposed matrix inversion method is presented. A Xilinx Virtex-7 FPGA VC707 chip is selected and the MOMS-2P data used for inflight geometric calibration from DLR (Köln, Germany), are employed for validation and analysis. The experimental results demonstrated that: (1) When the widths of floating-point data from 44-bit to 64-bit are adopted, the FPGA resources, including the utilizations of FF, LUT, memory LUT, I/O and DSP48, are consumed at a fast increasing rate; thus, a 50-bit data width is recommended for FPGA-based geometric calibration. (2) Increasing number of ground control points (GCPs) does not significantly consume the FPGA resources, six GCPs is therefore recommended for geometric calibration. (3) The FPGA-based geometric calibration can reach approximately 24 times faster speed than the PC-based one does. (4) The accuracy from the proposed FPGA-based method is almost similar to the one from the inflight calibration if the calibration model and GCPs number are the same

INTERNAL TRANSCRIBED SPACER (ITS), AN IDEAL DNA BARCODE FOR SPECIES DISCRIMINATION IN CRAWFURDIA WALL. (GENTIANACEAE)

Background: DNA barcoding is a technique used to identify species based on species-specific differences in short regions of their DNA. It is widely used in species discrimination of medicinal plants and traditional medicines. Materials and Methods: In the present study, four potential DNA barcodes, namely rbcL, matK, trnH-psbA and ITS (nuclear ribosomal internal transcribed spacer) were adopted for species discrimination in Crawfurdia Wall (Genetiaceae). Discriminatory ability of these DNA barcodes and combinations were evaluated using three classic methods (Distance, Blast and Tree-Building). Results: As a result, ITS, trnH-psbA and rbcL regions showed extremely great universality for a success rate of 100%; whereas matK was disappointing for which only 65% samples gained useful DNA sequences. ITS region performed very well in this study which could clearly and effectively identify the five species in Crawfurdia. On the contrary, trnH-psbA and rbcL were much weaker in discrimination among these species. Conclusion: ITS marker was an ideal DNA barcode in Crawfurdia and it should be incorporated into one of the core barcodes for seed plants

HOW TO CORRECTLY IDENTIFY HERBAL MATERIALS IN MARKET? A CASE STUDY BASED ON DNA BARCODES

Background: Traditional methods for identifying herbal medicines have many shortcomings. In this study, we aim to test discriminating ability of DNA barcodes and explore feasible method on evaluating identification results. Materials and Methods: Materials of whole-plant medicines were sampled from herbal market. 111 samples were used for DNA sequencing of ITS2 and trnH-psbA regions. Assembled sequences were searched against reference database using the BLAST method. Comprehensive evaluation based on pharmacognostic investigation, macroscopic identification and identification of DNA barcodes were performed for authentication of the herbal materials. Results: As a result, ITS2 had better identifying power than trnH-psbA in species-specific level (55.86% & 45.95%), as well as worse success rate of DNA sequencing (74.58% & 94.59%). In total, 89.19% individuals could be identified in genus level at least. Conclusion: It was revealed that DNA barcoding was useful tool in identifying herbal materials. Both ITS2 and trnH-psbA should be incorporated into the standard regions of DNA barcodes for identifying herbal materials

Effective identification of terrain positions from gridded DEM data using multimodal classification integration

Terrain positions are widely used to describe the Earth’s topographic features and play an important role in the studies of landform evolution, soil erosion and hydrological modeling. This work develops a new multimodal classification system with enhanced classification performance by integrating different approaches for terrain position identification. The adopted classification approaches include local terrain attribute (LA)-based and regional terrain attribute (RA)-based, rule-based and supervised, and pixel-based and object-oriented methods. Firstly, a double-level definition scheme is presented for terrain positions. Then, utilizing a hierarchical framework, a multimodal approach is developed by integrating different classification techniques. Finally, an assessment method is established to evaluate the new classification system from different aspects. The experimental results, obtained at a Loess Plateau region in northern China on a 5 m digital elevation model (DEM), show reasonably positional relationship, and larger inter-class and smaller intra-class variances. This indicates that identified terrain positions are consistent with the actual topography from both overall and local perspectives, and have relatively good integrity and rationality. This study demonstrates that the current multimodal classification system, developed by taking advantage of various classification methods, can reflect the geographic meanings and topographic features of terrain positions from different levels

Anchoring Cu 1 species over nanodiamond-graphene for semi-hydrogenation of acetylene

The design of cheap, non-toxic, and earth-abundant transition metal catalysts for selective hydrogenation of alkynes remains a challenge in both industry and academia. Here, we report a new atomically dispersed copper (Cu) catalyst supported on a defective nanodiamondgraphene (ND@G), which exhibits excellent catalytic performance for the selective conversion of acetylene to ethylene, i.e., with high conversion (95%), high selectivity (98%), and good stability (for more than 60 h). The unique structural feature of the Cu atoms anchored over graphene through Cu-C bonds ensures the effective activation of acetylene and easy desorption of ethylene, which is the key for the outstanding activity and selectivity of the catalyst

Data-driven assessment of immune evasion and dynamic Zero-COVID policy on fast-spreading Omicron in Changchun

Due to its immune evasion capability, the SARS-CoV-2 Omicron variant was declared a variant of concern by the World Health Organization. The spread of Omicron in Changchun (i.e., the capital of Jilin province in northeast of China) during the spring of 2022 was successfully curbed under the strategy of a dynamic Zero-COVID policy. To evaluate the impact of immune evasion on vaccination and other measures, and to understand how the dynamic Zero-COVID measure stopped the epidemics in Changchun, we establish a compartmental model over different stages and parameterized the model with actual reported data. The model simulation firstly shows a reasonably good fit between our model prediction and the data. Second, we estimate the testing rate in the early stage of the outbreak to reveal the real infection size. Third, numerical simulations show that the coverage of vaccine immunization in Changchun and the regular nucleic acid testing could not stop the epidemic, while the 'non-pharmaceutical' intervention measures utilized in the dynamic Zero-COVID policy could play significant roles in the containment of Omicron. Based on the parameterized model, numerical analysis demonstrates that if one wants to achieve epidemic control by fully utilizing the effect of 'dynamic Zero-COVID' measures, therefore social activities are restricted to the minimum level, and then the economic development may come to a halt. The insight analysis in this work could provide reference for infectious disease prevention and control measures in the future

Tin Assisted Fully Exposed Platinum Clusters Stabilized on Defect-Rich Graphene for Dehydrogenation Reaction

Tin assisted fully exposed Pt clusters are fabricated on the core-shell nanodiamond@graphene (ND@G) hybrid support (a-PtSn/ND@G). The obtained atomically dispersed Pt clusters, with an average Pt atom number of 3, were anchored over the ND@Gsupport by the assistance of Sn atoms as a partition agent and through the Pt-C bond between Pt clusters and defect-rich graphene nanoshell. The atomically dispersed Pt clusters guaranteed a full metal availability to the reactants, a high thermal stability, and an optimized adsorption/desorption behavior. It inhibits the side reactions and enhances catalytic performance in direct dehydrogenation of n-butane at a low temperature of 450 °C, leading to \u3e98% selectivity toward olefin products, and the turnover frequency (TOF) of a-PtSn/ND@G is approximately 3.9 times higher than that of the traditional Pt3Sn alloy catalyst supported on Al2O3 (Pt3Sn/Al2O3)

QTL Mapping of Fiber-Related Traits Based on a High-Density Genetic Map in Flax (Linum usitatissimum L.)

A genetic map is an important and valuable tool for quantitative trait locus (QTL) mapping, marker-assisted selection (MAS)-based breeding, and reference-assisted chromosome assembly. In this study, 112 F2 plants from a cross between Linum usitatissimum L. “DIANE” and “NY17” and parent plants were subjected to high-throughput sequencing and specific-locus amplified fragment (SLAF) library construction. After preprocessing, 61.64 Gb of raw data containing 253.71 Mb paired-end reads, each 101 bp in length, were obtained. A total of 192,797 SLAFs were identified, of which 23,115 were polymorphic, with a polymorphism rate of 11.99%. Finally, 2,339 SLAFs were organized into a linkage map consisting of 15 linkage groups (LGs). The total length of the genetic map was 1483.25 centimorgans (cM) and the average distance between adjacent markers was 0.63 cM. Combined with flax chromosome-scale pseudomolecules, 12 QTLs associating with 6 flax fiber-related traits were mapped on the chromosomal scaffolds. This high-density genetic map of flax should serve as a foundation for flax fine QTL mapping, draft genome assembly, and MAS-guided breeding. Ultimately, the genomic regions identified in this research could potentially be valuable for improving flax fiber cultivars, as well as for identification of candidate genes involved in flax fiber formation processes.Significance statementA high-density genetic map of flax was constructed, and QTLs were identified on the sequence scaffolds to be interrelated with fiber-related traits. The results of this study will not only provide a platform for gene/QTL fine mapping, map-based gene isolation, and molecular breeding for flax, but also provide a reference to help position sequence scaffolds on the physical map and assist in the process of assembling the flax genome sequence

Microarray-Based Approach Identifies Differentially Expressed MicroRNAs in Porcine Sexually Immature and Mature Testes

MicroRNAs (miRNAs) are short non-coding RNA molecules which are proved to be involved in mammalian spermatogenesis. Their expression and function in the porcine germ cells are not fully understood.We employed a miRNA microarray containing 1260 unique miRNA probes to evaluate the miRNA expression patterns between sexually immature (60-day) and mature (180-day) pig testes. One hundred and twenty nine miRNAs representing 164 reporter miRNAs were expressed differently (p<0.1). Fifty one miRNAs were significantly up-regulated and 78 miRNAs were down-regulated in mature testes. Nine of these differentially expressed miRNAs were validated using quantitative RT-PCR assay. Totally 15,919 putative miRNA-target sites were detected by using RNA22 method to align 445 NCBI pig cDNA sequences with these 129 differentially expressed miRNAs, and seven putative target genes involved in spermatogenesis including DAZL, RNF4 gene were simply confirmed by quantitative RT-PCR.Overall, the results of this study indicated specific miRNAs expression in porcine testes and suggested that miRNAs had a role in regulating spermatogenesis