Learning Implicit Templates for Point-Based Clothed Human Modeling

We present FITE, a First-Implicit-Then-Explicit framework for modeling human avatars in clothing. Our framework first learns implicit surface templates representing the coarse clothing topology, and then employs the templates to guide the generation of point sets which further capture pose-dependent clothing deformations such as wrinkles. Our pipeline incorporates the merits of both implicit and explicit representations, namely, the ability to handle varying topology and the ability to efficiently capture fine details. We also propose diffused skinning to facilitate template training especially for loose clothing, and projection-based pose-encoding to extract pose information from mesh templates without predefined UV map or connectivity. Our code is publicly available at https://github.com/jsnln/fite.Comment: Accepted to ECCV 202

Mantle Dynamics of the North China Craton: New Insights from Mantle Transition Zone Imaging Constrained by P-To-S Receiver Functions

Cratons are generally defined as stable continental blocks with a strong cratonic root that typically is at least ∼200 km thick. Many cratons have undergone little internal tectonism and destruction since their formation, but some of them, such as the eastern part of the North China Craton (NCC), the Dharwar Craton and the Wyoming Craton, have lost their thick cratonic root and become reactivated in recent geological history, leading to widespread Meso-Cenozoic volcanisms. The mechanisms responsible for such decratonization remain debated. To provide new constraints on models leading to decratonization, in this study we stack 612 854 source-normalized P-to-S conversions (receiver functions or RFs) from the 410 and 660 km discontinuities (d410 and d660, respectively) bordering the mantle transition zone (MTZ) recorded at 1986 stations in the NCC. Both the number of RFs and the number of stations are unprecedented in the study area. The average apparent depths of the d410 and d660 and the thickness of the MTZ are 413 ± 6, 669 ± 8 and 255 ± 6 km, respectively. A depression of up to 37 km and mean 11 km of the d660 are clearly observed beneath the eastern NCC, mainly caused by the possible existence of a relatively large amount of water in the MTZ. Our study provides strong observational evidence for geodynamic modelling that suggests water in the MTZ can be driven out into the upper mantle by poloidal mantle flow induced by the subduction and retreat of subducted oceanic slabs. The results are consistent with the weakening of the lithosphere beneath the eastern NCC by the release of water (in the form of structurally bound H/OH) brought down to the MTZ by subduction of the Pacific slab. Continuous slab dehydration and the ascent of fluids would have triggered intraplate volcanism and mantle upwelling in the eastern NCC, as evidenced by the spatial correspondence among the lower-than-normal upper-mantle seismic velocities, unusually large depressions of the d660, Cenozoic basaltic volcanism and thinning of the cratonic lithosphere

A Novel and Robust Approach for Pro-Drop Language Translation

A significant challenge for machine translation (MT) is the phenomena of dropped pronouns (DPs), where certain classes of pronouns are frequently dropped in the source language but should be retained in the target language. In response to this common problem, we propose a semi-supervised approach with a universal framework to recall missing pronouns in translation. Firstly, we build training data for DP generation in which the DPs are automatically labelled according to the alignment information from a parallel corpus. Secondly, we build a deep learning-based DP generator for input sentences in decoding when no corresponding references exist. More specifically, the generation has two phases: (1) DP position detection, which is modeled as a sequential labelling task with recurrent neural networks; and (2) DP prediction, which employs a multilayer perceptron with rich features. Finally, we integrate the above outputs into our statistical MT (SMT) system to recall missing pronouns by both extracting rules from the DP-labelled training data and translating the DP-generated input sentences. To validate the robustness of our approach, we investigate our approach on both Chinese–English and Japanese–English corpora extracted from movie subtitles. Compared with an SMT baseline system, experimental results show that our approach achieves a significant improvement of++1.58 BLEU points in translation performance with 66% F-score for DP generation accuracy for Chinese–English, and nearly++1 BLEU point with 58% F-score for Japanese–English. We believe that this work could help both MT researchers and industries to boost the performance of MT systems between pro-drop and non-pro-drop languages

Chinese–Portuguese machine translation: a study on building parallel corpora from comparable texts

Although there are increasing and significant ties between China and Portuguese-speaking countries, there is not much parallel corpora in the Chinese–Portuguese language pair. Both languages are very populous, with 1.2 billion native Chinese speakers and 279 million native Portuguese speakers, the language pair, however, could be considered as low-resource in terms of available parallel corpora. In this paper, we describe our methods to curate Chinese–Portuguese parallel corpora and evaluate their quality. We extracted bilingual data from Macao government websites and proposed a hierarchical strategy to build a large parallel corpus. Experiments are conducted on existing and our corpora using both Phrased-Based Machine Translation (PBMT) and the state-of-the-art Neural Machine Translation (NMT) models. The results of this work can be used as a benchmark for future Chinese–Portuguese MT systems. The approach we used in this paper also show a good example on how to boost performance of MT systems for low-resource language pairs

CT Image Changes of Severe Acute Pancreatitis Based on Smart Electronic Medical Augmented Reality in Nursing Practice

Severe acute pancreatitis (SAP) is traditionally treated with chemical analysis. Faced with the increasing maturity of CT imaging technology, it is necessary to use more advantageous CT imaging to treat SAP. In this article, 72 SAP patients admitted to the Affiliated Hospital of Southwest Medical University were selected for study, of which 62 were severely ill, 8 were exacerbated, and 2 changed from severe to mild. This article combines the patient’s case records and related CT images during treatment from the perspective of nursing and conducts nursing research on the application of CT image changes in severe acute pancreatitis in nursing practice. CT image processing uses CT imaging system workstation (DICOM). The results of the study showed that, in the care of patients, 21 cases had recurrence after internal drainage, and the cure rate was 91.1%. Internal drainage is an effective way to treat SAP. The higher the incidence of pancreatitis, the more likely it is to relapse after SAP internal drainage, which may be related to repeated episodes of pancreatitis and repeated inflammation of the pancreas and pancreatic duct damage. 4 of the relapsed cases in this article are postchronic pancreatitis SAP, and the relapsed cases account for 50% of the chronic pancreatic cases. This may be due to chronic fibrosis of the branched and main pancreatic ducts, continuous abnormal pancreatic juice drainage. Therefore, it is necessary to further explore the prognosis of different causes of SAP. In terms of complication care, the overall complication rate was 16.6%. One patient died of postoperative hemorrhage. Analysis of the causes of cyst recurrence and complications may be closely related to the mechanism of the occurrence and development of SAP. The initiating factor of SAP is that the pancreatic tissue is damaged due to inflammation, trauma, or microcirculation disorder, and then the pancreatic juice leaks out of the pancreas, wrapping the pancreatic juice; it takes a certain time for the capsule of fibrous knot tissue to form and strengthen

Toroidal Mantle Flow Induced by Slab Subduction and Rollback Beneath the Eastern Himalayan Syntaxis and Adjacent Areas

A total of 431 well-defined and 632 null shear-wave splitting measurements obtained from 115 broadband seismic stations located in the eastern Himalayan syntaxis and adjacent areas is largely inconsistent with predicted fast orientations by absolute plate motion models. Spatial coherency analysis of the splitting parameters suggests that the observed azimuthal anisotropy is mostly located in the upper asthenosphere or the transitional layer between the lithosphere and asthenosphere, and the disagreement between the fast orientations and regional tectonic fabrics suggests an insignificant lithospheric contribution to the observed anisotropy. The observations may be attributed to flow systems that are driven by the westward rollback of the Indian slab beneath the Indo-Burma block and are modulated by a previously revealed gap between the northward and eastward subducting slabs of the Indian plate

Analysis of Water Features in Gas Leakage Area

In a certain frequency range, gas is an effective absorber and scatterer of sound, which changes the compressibility of water, and then changes the speed and frequency of sound. Gas continues rising, deforming, and dissolving. The same bubble of natural gas has different radii at different depths. By analyzing these changes, the resonance frequency of gas bubble, and its impacts on sound wave, characteristics of the influences of gas at different depths on the incident sound wave can be obtained. The main sound features of gas are relevant to the gas size, gas content, velocity, attenuation, resonance frequency, the scattering cross-section, and so forth. Sound models with hydrate and free gas in the water and sediment are established. Through the practical application to actual data, the sound characteristics yielded when the gas (or gas hydrate dissociation) escaped the water of seismic data are very clear

The Integration of Genome-Wide Association Study and Homology Analysis to Explore the Genomic Regions and Candidate Genes for Panicle-Related Traits in Foxtail Millet

Panicle traits are important factors affecting yield, and their improvement has long been a critical goal in foxtail millet breeding. In order to understand the genetic basis of panicle formation, a large-scale genome-wide association study (GWAS) was performed in this study for six panicle-related traits based on 706,646 high-polymorphism SNP loci in 407 accessions. As a result, 87 quantitative trait loci (QTL) regions with a physical distance of less than 100 kb were detected to be associated with these traits in three environments. Among them, 27 core regions were stably detected in at least two environments. Based on rice–foxtail millet homologous comparison, expression, and haplotype analysis, 27 high-confidence candidate genes in the QTL regions, such as Si3g11200 (OsDER1), Si1g27910 (OsMADS6), Si7g27560 (GS5), etc., affected panicle-related traits by involving multiple plant growth regulator pathways, a photoperiod response, as well as panicle and grain development. Most of these genes showed multiple effects on different panicle-related traits, such as Si3g11200 affecting all six traits. In summary, this study clarified a strategy based on the integration of GWAS, a homologous comparison, and haplotype analysis to discover the genomic regions and candidate genes for important traits in foxtail millet. The detected QTL regions and candidate genes could be further used for gene clone and marker-assisted selection in foxtail millet breeding