Search

Instance segmentation on 3D point clouds has been attracting increasing attention due to its wide applications, especially in scene understanding areas. However, most existing methods require training data to be fully annotated. Manually preparing ground-truth labels at point-level is very cumbersome and labor-intensive. To address this issue, we propose a novel weakly supervised method RWSeg that only requires labeling one object with one point. With these sparse weak labels, we introduce a unified framework with two branches to propagate semantic and instance information respectively to unknown regions, using self-attention and random walk. Furthermore, we propose a Cross-graph Competing Random Walks (CGCRW) algorithm which encourages competition among different instance graphs to resolve ambiguities in closely placed objects and improve the performance on instance assignment. RWSeg can generate qualitative instance-level pseudo labels. Experimental results on ScanNet-v2 and S3DIS datasets show that our approach achieves comparable performance with fully-supervised methods and outperforms previous weakly-supervised methods by large margins. This is the first work that bridges the gap between weak and full supervision in the area.

Photoperiod (Ppd) genes play an important role in the adaptation of wheat to the ecological environment. However, the transcriptional regulation mechanism of photoperiodic genes has remained elusive. This study isolated a full-length promoter of Ppd-D1b (2518 bp) from the common wheat genome. Several essential core cis-acting elements and numerous light-responsive cis-acting regulatory elements were identified in Ppd-D1b promoter by the in-silico analysis. Ten 5'-deleted length fragments of the Ppd-D1b promoter fused with GUS were constructed and named D0 ~ D9, then transferred them into Arabidopsis thaliana. GUS gene driven by full-length (D0) in transgenic Arabidopsis thaliana showed the same rhythm with Ppd-D1b in wheat under short-day conditions (SDs, 8-h light/16-h dark). The expression of GUS gene in D0 reached its peak at 3 h after dawn, then decreased to the lowest and remained stable. Analysis of the series of 5'-deleted fragments showed that at 3 h after dawn, GUS gene expression activity decreased significantly in D7a due to removal of CHEBS (CCA1 HIKING EXPEDITION binding site). Moreover, yeast one-hybrid (Y1H) and dual-luciferase (dual-LUC) assays revealed that TaTCP20 could bind to the Ppd-D1b promoter to increase its transcriptional activity. This study revealed a transcription factor, TaTCP20, which activated Ppd-D1b by binding to CHEBS, provided a foundation for the theoretical research on wheat's photoperiodic response mechanism.

3D pose transfer is one of the most challenging 3D generation tasks. It aims to transfer the pose of a source mesh to a target mesh and keep the identity (e.g., body shape) of the target mesh. Some previous works require key point annotations to build reliable correspondence between the source and target meshes, while other methods do not consider any shape correspondence between sources and targets, which leads to limited generation quality. In this work, we propose a correspondence-refinement network to achieve the 3D pose transfer for both human and animal meshes. The correspondence between source and target meshes is first established by solving an optimal transport problem. Then, we warp the source mesh according to the dense correspondence and obtain a coarse warped mesh. The warped mesh will be better refined with our proposed Elastic Instance Normalization, which is a conditional normalization layer and can help to generate high-quality meshes. Extensive experimental results show that the proposed architecture can effectively transfer the poses from source to target meshes and produce better results with satisfied visual performance than state-of-the-art methods.

本稿は、植物バイオマスと抗ウイルス活性の関連を科学的に解明する研究をまとめたものである。ウイルス感染の影響を最小限にすることにより、食の安全、畜産業の保護、人の健康維持につながり、脱石油社会における持続的な生存圏の創成に深く関与する。植物が産生する多彩な有機化合物資源のみならず、バイオマスそのものを人為的に構造変換したものから生理活性物質を見出す領域は未だ十分に確立されておらず、本研究により抗ウイルス活性が見出されれば、抗ウイルス活性物質にとどまらず、広範な生理活性物質を生み出す研究が創成、発展すると期待され、石油資源によらない生存圏の人間生活の質(quality of life)を支えることに資する。

Large Hadron Collider (LHC) has provided direct evidence of Yukawa couplings between the third generation charged fermions and the 125 GeV Higgs boson. Whether the first two generation charged fermions arise from exactly the same mechanism becomes the next interesting question. Therefore, direct measurements of charm or muon Yukawa couplings will be crucial to answering this puzzle. The charm Yukawa measurement at the LHC suffers from severe QCD background and it is extremely difficult to reach the sensitivity. In this paper, we compare the potential of probing charm Yukawa coupling at the two proposed future "Higgs Factory" experiments, the Large Hadron electron Collider (LHeC) and Circular electron positron collider (CEPC). At the LHeC, Higgs bosons will be produced via weak boson fusion and the energetic forward jet may suppress the background significantly. However, due to huge $\gamma-g$ scattering background, the potential of LHeC search is still limited. With $-80\%$ polarized electron beam of 60 GeV, the signal significance can only reach $2\sigma$ for $ \kappa_{c}\simeq 1$ with a 3 ab$^{-1}$ integrated luminosity. In comparison, measurement at the CEPC can then reach $8.0\sigma$ for $\kappa_{c}\simeq 1$ with a 2 ab$^{-1}$ of data., Comment: 28 pages, 9 figures and 11 tables

The search of the light Higgsino {in the Minimal Supersymmetric Standard Model (MSSM)} is a crucial test for the criteria of the naturalness in supersymmetry. On the other hand, the direct production of light Higgsino is also known as one of the most challenging SUSY searches at the current CERN Large Hadron collider (LHC). The lack of visible leptons due to the compressed spectrum and their small production rates limits their discovery potential in both mono-jet plus MET as well as the weak boson fusion (WBF) production. The signal $S/B$ ratio prediction is usually within the background systematic uncertainties at the LHC. Without color exchange between the beams, the $e-p$ colliders are well-known to have the WBF feature. Therefore, we study the search of the light Higgsinos at two future $e-p$ colliders at CERN, LHeC and FCC-eh.~The light Higgsinos will be produced in pair through weak boson fusion with controlled background at these colliders. We find the Higgsino of 95/145~GeV can be reached at 2$\sigma$ level at the future LHeC/FCC-eh with a luminosity $3 ~\text{ab}^{-1}$ respectively., Comment: 18 pages, 7 tables, 5 figures. We updated the results at the LHeC and FCC-eh after detector simulation. The relevant Higgs mass spectrum and cuts criteria are added by new tables. The significance is also updated due to new reducible backgrounds have been considered

地球温暖化などによる環境変動や､グローバル化による人･動物･物の移動が増加したことから､近年ウイルスをはじめとした感染症のリスクが高まっている｡本稿では､再生可能な持続資源として注目を集めている木質バイオマスの中で､木竹酢液の生理活性に着目した研究成果を紹介する｡木竹酢液は､木竹炭を製造する際に副次的に得られ､セルロース､ヘミセルロースおよびリグニンの熱分解生成物などから構成される｡木竹酢液は古くから消毒､殺菌などに使用されており､様々な生理活性を有するバイオマスであるが､ウイルスなどの病原体に対する活性についての検討は十分ではない｡そこで､未利用バイオマスから薬効成分･生理活性物質を生産し､人の健康や安全な生活に貢献するという新しい研究領域を開拓することを目的として著者らが最近行っている､木酢液､竹酢液の抗ウイルス活性についての成果も併せて紹介する｡とりわけ､2010年に宮崎県で発生した家畜伝染病､口蹄疫の原因ウイルスである口蹄疫ウイルスなどに対する消毒薬への応用を視野に入れ､木竹酢液に含まれる抗ウイルス活性物質の探索を行った結果について詳述する｡これまでに､口蹄疫ウイルスと同じピコルナウイルス科に属する脳心筋炎ウイルスを用いて木竹酢液の抗ウイルス活性の検討を行い､木竹酢液は酸性条件下で強い抗ウイルス活性を示すことが明らかになっている｡また､木竹酢液に含まれるphenolと酢酸が相乗的に抗ウイルス活性を示すことを示した｡われわれの実験結果では､ヒノキ由来の木酢液原液が中性条件下においても抗ウイルス活性を示したことから､この画分に含まれる抗ウイルス活性物質の探索を行った｡成分分画と抗ウイルス活性の検討により､精製したフラクションに抗ウイルス活性物質が含まれることを示した｡本稿では､研究課題に関連する今後の展望についても簡単に言及する｡

In this paper, we present our deep attention-based classification (DABC) network for robust single image depth prediction, in the context of the Robust Vision Challenge 2018 (ROB 2018). Unlike conventional depth prediction, our goal is to design a model that can perform well in both indoor and outdoor scenes with a single parameter set. However, robust depth prediction suffers from two challenging problems: a) How to extract more discriminative features for different scenes (compared to a single scene)? b) How to handle the large differences of depth ranges between indoor and outdoor datasets? To address these two problems, we first formulate depth prediction as a multi-class classification task and apply a softmax classifier to classify the depth label of each pixel. We then introduce a global pooling layer and a channel-wise attention mechanism to adaptively select the discriminative channels of features and to update the original features by assigning important channels with higher weights. Further, to reduce the influence of quantization errors, we employ a soft-weighted sum inference strategy for the final prediction. Experimental results on both indoor and outdoor datasets demonstrate the effectiveness of our method. It is worth mentioning that we won the 2-nd place in single image depth prediction entry of ROB 2018, in conjunction with IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018.

The precision measurement of the $WW��$ vertex at the future Large Hadron electron Collider (LHeC) at CERN is discussed in this paper. We propose to measure this vertex in the $e^{-} p\to e^{-}W^{\pm}j$ channel as a complement to the conventional charged current $��_{e}��j$ channel. In addition to the cross section measurement, $��^{2}$ method studies of angular variables provide powerful tools to probe the anomalous structure of triple gauge boson couplings. We study the distribution of the well-known azimuthal angle between the final state forward electron and jet in this vector-boson fusion (VBF) process. On the other hand, full reconstruction of leptonic $W$ decay opens a new opportunity to measure $W$ polarization that is also sensitive to the anomalous triple gauge boson couplings. Taking into consideration the superior determination of parton distribution functions~(PDFs) based on future LHeC data, the constraints of $��_��$ and $����_��$ might reach up to $\mathcal{O}(10^{-3})$ level in the most ideal case with the 2--3~ab$^{-1}$ data set, which shows a potential advantage compared to those from LHC and LEP data., 15 pages, 8 figures