Progressive edge-sensing dynamic scene deblurring

Deblurring images of dynamic scenes is a challenging task because blurring occurs due to a combination of many factors. In recent years, the use of multi-scale pyramid methods to recover high-resolution sharp images has been extensively studied. We have made improvements to the lack of detail recovery in the cascade structure through a network using progressive integration of data streams. Our new multi-scale structure and edge feature perception design deals with changes in blurring at different spatial scales and enhances the sensitivity of the network to blurred edges. The coarse-to-fine architecture restores the image structure, first performing global adjustments, and then performing local refinement. In this way, not only is global correlation considered, but also residual information is used to significantly improve image restoration and enhance texture details. Experimental results show quantitative and qualitative improvements over existing methods.

The Carboniferous timescale: an introduction

The Carboniferous chronostratigraphic scale consists of two subsystems, six series and seven stages. Precise numerical age control within the Carboniferous is uneven, and a global magnetic polarity timescale for the Carboniferous is far from established. Isotope stratigraphy based on Sr, C and O isotopes is in an early stage but has already identified a few Sr and C isotope events of use to global correlation. Cyclostratigraphy has created a workable astrochronology for part of Pennsylvanian time that needs better calibration. Chronostratigraphic definitions of most of the seven Carboniferous stages remain unfinished. Future research on the Carboniferous timescale should focus on GSSP selection for the remaining, undefined stage bases, definition and characterization of substages, and further development and integration of the Carboniferous chronostratigraphic scale with radioisotopic, magnetostratigraphic, chemostratigraphic and cyclostratigraphic tools for calibration and correlation and the cross correlation of nonmarine and marine chronologies.

Stellar Population and Elemental Abundance Gradients of Early-type Galaxies*

The evolution of galaxies is imprinted on their stellar populations. Several stellar population properties in massive early-type galaxies have been shown to correlate with intrinsic galaxy properties such as the galaxy’s central velocity dispersion, suggesting that stars formed in an initial collapse of gas (z ∼ 2). However, stellar populations change as a function of galaxy radius, and it is not clear how local gradients of individual galaxies are influenced by global galaxy properties and galaxy environment. In this paper, we study the stellar populations of eight early-type galaxies as a function of radius. We use optical spectroscopy (∼4000–8600 Å) and full spectral fitting to measure stellar population age, metallicity, slope of the initial mass function (IMF), and nine elemental abundances (O, Mg, Si, Ca, Ti, C, N, Na, and Fe) out to 1 R e for each galaxy individually. We find a wide range of properties, with ages ranging from 3–13 Gyr. Some galaxies have a radially constant, Salpeter-like IMF, and other galaxies have a super-Salpeter IMF in the center, decreasing to a sub-Salpeter IMF at ∼0.5 R e . We find a global correlation of the central [Z/H] with the central IMF and the radial gradient of the IMF for the eight galaxies, but local correlations of the IMF slope with other stellar population parameters hold only for subsets of the galaxies in our sample. Some elemental abundances also correlate locally with each other within a galaxy, suggesting a common production channel. These local correlations appear only in subsets of our galaxies, indicating variations of the stellar content among different galaxies.

Conditional transcriptional relationships may serve as cancer prognostic markers

Background While most differential coexpression (DC) methods are bound to quantify a single correlation value for a gene pair across multiple samples, a newly devised approach under the name Correlation by Individual Level Product (CILP) revolutionarily projects the summary correlation value to individual product correlation values for separate samples. CILP greatly widened DC analysis opportunities by allowing integration of non-compromised statistical methods. Methods Here, we performed a study to verify our hypothesis that conditional relationships, i.e., gene pairs of remarkable differential coexpression, may be sought as quantitative prognostic markers for human cancers. Alongside the seeking of prognostic gene links in a pan-cancer setting, we also examined whether a trend of global expression correlation loss appeared in a wide panel of cancer types and revisited the controversial subject of mutual relationship between the DE approach and the DC approach. Results By integrating CILP with classical univariate survival analysis, we identified up to 244 conditional gene links as potential prognostic markers in five cancer types. In particular, five prognostic gene links for kidney renal papillary cell carcinoma tended to condense around cancer gene ESPL1, and the transcriptional synchrony between ESPL1 and PTTG1 tended to be elevated in patients of adverse prognosis. In addition, we extended the observation of global trend of correlation loss in more than ten cancer types and empirically proved DC analysis results were independent of gene differential expression in five cancer types. Conclusions Combining the power of CILP and the classical survival analysis, we successfully fetched conditional transcriptional relationships that conferred prognosis power for five cancer types. Despite a general trend of global correlation loss in tumor transcriptomes, most of these prognosis conditional links demonstrated stronger expression correlation in tumors, and their stronger coexpression was associated with poor survival.

End-to-End Joint Multi-Object Detection and Tracking for Intelligent Transportation Systems

Environment perception is one of the most critical technology of intelligent transportation systems (ITS). Motion interaction between multiple vehicles in ITS makes it important to perform multi-object tracking (MOT). However, most existing MOT algorithms follow the tracking-by-detection framework, which separates detection and tracking into two independent segments and limit the global efficiency. Recently, a few algorithms have combined feature extraction into one network; however, the tracking portion continues to rely on data association, and requires complex post-processing for life cycle management. Those methods do not combine detection and tracking efficiently. This paper presents a novel network to realize joint multiobject detection and tracking in an end-to-end manner for ITS, named as global correlation network (GCNet). Unlike most object detection methods, GCNet introduces a global correlation layer for regression of absolute size and coordinates of bounding boxes, instead of offsetting predictions. The pipeline of detection and tracking in GCNet is conceptually simple, and does not require complicated tracking strategies such as non-maximum suppression and data association. GCNet was evaluated on a multi-vehicle tracking dataset, UA-DETRAC, demonstrating promising performance compared to state-of-the-art detectors and trackers.

Ordovician to Silurian graptolite specimen images for global correlation and shale gas exploration

Multi- elemental and -dimensional data are more and more important during the development of data-driven research, as is the case in modern palaeontology, in which visual examination, by experts or someday the artificial intelligence, to every fossil specimen acts a crucial and fundamental role. We here release an integrated image dataset of 113 Ordovician to Silurian graptolite species or subspecies that are significant in global stratigraphy and shale gas exploration. The dataset contains 1550 high-resolution graptolite specimen images and scientific information related to the specimen, e.g., every specimen's taxonomic, geologic, geographic, and related references. We develop a tool, FSIDvis (Fossil Specimen Image Dataset Visualiser), to facilitate the human-interactive exploration of the rich-attribution image dataset. A nonlinear dimension reduction technique, t-SNE (t-Distributed Stochastic Neighbor Embedding), is employed to project the images into the two-dimensional space to visualise and explore the similarities. Our dataset potentially contributes to the analysis of the global biostratigraphic correlations and improves the shale gas exploration efficiency by developing an image-based automated classification model. All images are available from https://doi.org/10.5281/zenodo.5205216 (Xu, 2021).

ELN IMDS Flow Working Group Validation of the Monocyte Assay for Chronic Myelomonocytic Leukemia Diagnosis By Flow Cytometry

Introduction It was proposed that peripheral blood (PB) monocyte subset analysis evaluated by flow cytometry, hereafter referred to as "monocyte assay", could rapidly and efficiently distinguish chronic myelomonocytic leukemia (CMML) from other causes of monocytosis by highlighting an increase in the classical monocyte (cMo) fraction above 94%. However, the robustness of this assay required a large multicenter validation. Methods PB and/or bone marrow (BM) samples from adult patients displaying monocytosis were assessed with the "monocyte assay" by ten ELN iMDS Flow working group centers (6 equipped with BD FACSCanto™ II (BD Biosciences), 3 with Navios™ (Beckman Coulter) and one with BD™ LSRII (BD Biosciences)) with harmonized protocols. The corresponding files were reanalyzed in a blind fashion by a skilled operator and the cMo (CD14 ++CD16 -) percentages obtained by both analyses were compared. Information regarding age, gender, complete blood count, marrow cytomorphology, cytogenetics and molecular analysis was collected. Confirmed diagnoses were collected when available as well as follow-up for CMML patients. Results The comparison between cMo percentages from 267 PB files provided by the 10 centers and the centralized cMo percentages showed a good global significant correlation (r=0.88; p<0.0001; FigA) with no bias (FigB). Confirmed diagnoses were available for 212 files, namely 101 CMML according to the WHO criteria, 99 reactive monocytosis, and 12 MPN with monocytosis. A phenotype in favor of CMML, either classical with accumulation of cMo ≥94% or a bulbous aspect (FigC), was observed respectively in 81 and 14 patients. Hence, a total of 95 out of the 101 CMML patients translated into a sensitivity of 94% (FigD). Assessment of C reactive protein counts were available in seven of the 14 patients with the characteristic bulbous profile and correlated with an inflammatory state, showing a median of 93.0 [7.0-157.4] mg/L. Conversely, a phenotype not in favor of CMML (FigC) was observed in 83 of the 99 patients with reactive monocytosis and in 10 of 12 patients with MPN with monocytosis, leading to a 84% specificity (FigD). We established a Receiver Operator Curve (ROC) and again obtained a 94% cut-off value of cMo with an area under the ROC curve (AUC) of 0.865 (FigE). The second aim of this multicenter study was to assess the feasibility of the monocyte assay on 117 BM samples provided by 7 out of the 10 ELN centers, 43 of which being paired to PB samples. The comparison between cMo percentages provided by the 7 centers and the centralized cMo percentages showed a lower global significant correlation compared to PB samples (r=0.74; p<0.0001; FigF) with a slight underestimation of cMo percentage by the participating centers (FigG). The comparison between PB and BM samples cMo% obtained by centralized reanalysis showed an excellent global correlation (r=0.93; p<0.0001; FigH) with a higher percentage in the marrow (FigI). Seventy-nine files were associated to a confirmed diagnosis, as expected mostly CMML (n=69), only seven reactive monocytosis and three MPN with monocytosis. Thus, we determined a sensitivity of the "monocyte assay" on BM samples of 87% (a phenotype in favor of CMML being observed in 60 out of the 69 CMML with 6 bulbous aspect profiles) and a specificity of 80% (a phenotype not in favor of CMML being observed in 5 of the 7 patients with reactive monocytosis and in 3 of the 3 patients with MPN with monocytosis). Conclusions This ELN multicenter study demonstrates the robustness of the monocyte assay with only limited variability of cMo percentages, validates the 94% cutoff value, confirms its high sensitivity and specificity in PB and finally, also confirms the possibility of its use in BM samples. Figure 1 Figure 1. Disclosures Kern: MLL Munich Leukemia Laboratory: Other: Part ownership.