RayMVSNet++: Learning Ray-based 1D Implicit Fields for Accurate Multi-View Stereo

Learning-based multi-view stereo (MVS) has by far centered around 3D convolution on cost volumes. Due to the high computation and memory consumption of 3D CNN, the resolution of output depth is often considerably limited. Different from most existing works dedicated to adaptive refinement of cost volumes, we opt to directly optimize the depth value along each camera ray, mimicking the range finding of a laser scanner. This reduces the MVS problem to ray-based depth optimization which is much more light-weight than full cost volume optimization. In particular, we propose RayMVSNet which learns sequential prediction of a 1D implicit field along each camera ray with the zero-crossing point indicating scene depth. This sequential modeling, conducted based on transformer features, essentially learns the epipolar line search in traditional multi-view stereo. We devise a multi-task learning for better optimization convergence and depth accuracy. We found the monotonicity property of the SDFs along each ray greatly benefits the depth estimation. Our method ranks top on both the DTU and the Tanks & Temples datasets over all previous learning-based methods, achieving an overall reconstruction score of 0.33mm on DTU and an F-score of 59.48% on Tanks & Temples. It is able to produce high-quality depth estimation and point cloud reconstruction in challenging scenarios such as objects/scenes with non-textured surface, severe occlusion, and highly varying depth range. Further, we propose RayMVSNet++ to enhance contextual feature aggregation for each ray through designing an attentional gating unit to select semantically relevant neighboring rays within the local frustum around that ray. RayMVSNet++ achieves state-of-the-art performance on the ScanNet dataset. In particular, it attains an AbsRel of 0.058m and produces accurate results on the two subsets of textureless regions and large depth variation.Comment: IEEE Transactions on Pattern Analysis and Machine Intelligence. arXiv admin note: substantial text overlap with arXiv:2204.0132

SVDinsTN: An Integrated Method for Tensor Network Representation with Efficient Structure Search

Tensor network (TN) representation is a powerful technique for data analysis and machine learning. It practically involves a challenging TN structure search (TN-SS) problem, which aims to search for the optimal structure to achieve a compact representation. Existing TN-SS methods mainly adopt a bi-level optimization method that leads to excessive computational costs due to repeated structure evaluations. To address this issue, we propose an efficient integrated (single-level) method named SVD-inspired TN decomposition (SVDinsTN), eliminating the need for repeated tedious structure evaluation. By inserting a diagonal factor for each edge of the fully-connected TN, we calculate TN cores and diagonal factors simultaneously, with factor sparsity revealing the most compact TN structure. Experimental results on real-world data demonstrate that SVDinsTN achieves approximately $10^2\sim{}10^3$ times acceleration in runtime compared to the existing TN-SS methods while maintaining a comparable level of representation ability

Combustion reactivity of ilmenite with coal volatiles under steam gasification atmosphere

学位記番号：理工博甲6

Neuropeptide Y-Positive Neurons in the Dorsomedial Hypothalamus Are Involved in the Anorexic Effect of Angptl8

Angiopoietin-like protein 8 (Angptl8), a recently identified member of the angiopoietin-like protein family (ANGPTLs), is a 22-kDa peptide synthesized in the liver. It participates in lipid metabolism by inhibiting lipoprotein lipase (LPL) activity, consequently increasing the triglyceride levels. Despite evidence that Angptl8 is involved in feeding control, the underlying mechanisms are unclear. Central and peripheral injections of Angptl8 significantly decreased food intake. Angptl8 was widely expressed in appetite-related nuclei, including the paraventricular nucleus (PVN), the dorsomedial hypothalamus (DMH), the ventromedial hypothalamus, and the arcuate nucleus (ARC) in the hypothalamus. Peripheral Angptl8 administration decreased c-Fos-positive neurons in the DMH. Central Angptl8 administration decreased c-Fos-positive neurons in the DMH and PVN but increased these neurons in the ARC. Angptl8 inhibited appetite via neuropeptide Y (NPY) neurons in the DMH. Furthermore, the chronic administration of Angptl8 decreased body weight gain and altered adipose tissue deposits. Nevertheless, neither peripheral nor central Angptl8 influenced the brown adipose tissue (BAT) morphology or uncoupling protein 1 (Ucp-1) expression in BAT. Taken together, these data suggested that Angptl8 modulates appetite and energy homeostasis

Open-source genomic analysis of Shiga-toxin–producing E. coli O104:H4

An outbreak caused by Shiga-toxin–producing Escherichia coli O104:H4 occurred in Germany in May and June of 2011, with more than 3000 persons infected. Here, we report a cluster of cases associated with a single family and describe an open-source genomic analysis of an isolate from one member of the family. This analysis involved the use of rapid, bench-top DNA sequencing technology, open-source data release, and prompt crowd-sourced analyses. In less than a week, these studies revealed that the outbreak strain belonged to an enteroaggregative E. coli lineage that had acquired genes for Shiga toxin 2 and for antibiotic resistance

Genomic epidemiology of a densely sampled COVID-19 outbreak in China.

Analysis of genetic sequence data from the SARS-CoV-2 pandemic can provide insights into epidemic origins, worldwide dispersal, and epidemiological history. With few exceptions, genomic epidemiological analysis has focused on geographically distributed data sets with few isolates in any given location. Here, we report an analysis of 20 whole SARS- CoV-2 genomes from a single relatively small and geographically constrained outbreak in Weifang, People's Republic of China. Using Bayesian model-based phylodynamic methods, we estimate a mean basic reproduction number (R 0) of 3.4 (95% highest posterior density interval: 2.1-5.2) in Weifang, and a mean effective reproduction number (Rt) that falls below 1 on 4 February. We further estimate the number of infections through time and compare these estimates to confirmed diagnoses by the Weifang Centers for Disease Control. We find that these estimates are consistent with reported cases and there is unlikely to be a large undiagnosed burden of infection over the period we studied

Huangqi Injection (a Traditional Chinese Patent Medicine) for Chronic Heart Failure: A Systematic Review

Chronic heart failure (CHF) is a global public health problem. Therefore, novel and effective drugs that show few side-effects are needed. Early literature studies indicated that Huangqi injection is one of the most commonly used traditional Chinese patent medicines for CHF in China. As a large number of clinical studies has been carried out and published, it is essential to evaluate the effectiveness and safety of Huangqi injection. Therefore, we carried out this systematic review under the support of the framework of the Joint Sino-Italian Laboratory (JoSIL).To evaluate the efficacy and safety of Huangqi injection for CHF according to the available scientific knowledge.An extensive search including PubMed, EMBASE, CBM, the Cochrane Library and Chinese literature databases was performed up to July 2008. Clinical trials regarding Huangqi injection for the treatment of CHF were searched for, irrespective of languages. The quality of each trial was assessed according to the Cochrane Reviewers' Handbook 5.0, and RevMan 5.0 provided by the Cochrane Collaboration and STATA 9.2 were used for data analysis.After selection of 1,205 articles, 62 RCTs and quasi-RCTs conducted in China and published in Chinese journals were included in the review. The methodological quality of the trials was low. In most trials inclusion and exclusion criteria were not specified. Furthermore, only one study evaluated the outcomes for drug efficacy after an adequate period of time. For these reasons and because of the different baseline characteristics we did not conduct a meta-analysis.Although available studies are not adequate to draw a conclusion on the efficacy and safety of Huangqi injection (a traditional Chinese patent medicine), we hope that our work could provide useful experience on further studies on Huangqi injections. The overall level of TCM clinical research needs to be improved so that the efficacy of TCM can be evaluated by the international community and possibly some TCM can enter into the international market