Learning to Predict Charges for Criminal Cases with Legal Basis

The charge prediction task is to determine appropriate charges for a given case, which is helpful for legal assistant systems where the user input is fact description. We argue that relevant law articles play an important role in this task, and therefore propose an attention-based neural network method to jointly model the charge prediction task and the relevant article extraction task in a unified framework. The experimental results show that, besides providing legal basis, the relevant articles can also clearly improve the charge prediction results, and our full model can effectively predict appropriate charges for cases with different expression styles.Comment: 10 pages, accepted by EMNLP 201

The development of new procedures for heterocycle synthesis under metal-free conditions

This thesis mainly describes recent development in the synthesis of N- and O-containing heterocycles, which were conducted under transition-metal-free condition. A series of heterocycles like quinazolinones, quinazolinimines, quinazolinamines, aminoisoquinoline and dibenzoxazepinamines etc. were synthesized under transition-metal-free condition as presented in this thesis, which aims to provide a green, convenient and efficient methodology for the construction of the compounds bearing these units.Diese Arbeit beschreibt vorwiegend die aktuellen Entwicklungen auf dem Gebiet der übergangsmetallfreien Synthese von stickstoff- und sauerstoffhaltigen Heterozyklen. Somit wurden unterschiedliche Heterozyklen wie Quinazolinone, Quinazolinimine, Quinazolinamine, Aminoisoquinoline, Dibenzoxazepinamine und weitere unter übergangsmetall-freien Bedingungen synthetisiert. Die entwickelten Methoden könnten grüne, günstige und effiziente Alternativen für die Herstellung von Substanzen mit diesen genannten Struktureinheiten darstellen

Transposition of Reversed Ac Element Ends Generates Novel Chimeric Genes in Maize

The maize Activator/Dissociation (Ac/Ds) elements are members of the hAT (hobo, Ac, and Tam3) superfamily of type II (DNA) transposons that transpose through a “cut-and-paste” mechanism. Previously, we reported that a pair of Ac ends in reversed orientation is capable of undergoing alternative transposition reactions that can generate large-scale chromosomal rearrangements, including deletions and inversions. We show here that rearrangements induced by reversed Ac ends transposition can join the coding and regulatory sequences of two linked paralogous genes to generate a series of chimeric genes, some of which are functional. To our knowledge, this is the first report demonstrating that alternative transposition reactions can recombine gene segments, leading to the creation of new genes

Surface-SOS:Self-Supervised Object Segmentation via Neural Surface Representation

Self-supervised Object Segmentation (SOS) aims to segment objects without any annotations. Under conditions of multi-camera inputs, the structural, textural and geometrical consistency among each view can be leveraged to achieve fine-grained object segmentation. To make better use of the above information, we propose Surface representation based Self-supervised Object Segmentation (Surface-SOS), a new framework to segment objects for each view by 3D surface representation from multi-view images of a scene. To model high-quality geometry surfaces for complex scenes, we design a novel scene representation scheme, which decomposes the scene into two complementary neural representation modules respectively with a Signed Distance Function (SDF). Moreover, Surface-SOS is able to refine single-view segmentation with multi-view unlabeled images, by introducing coarse segmentation masks as additional input. To the best of our knowledge, Surface-SOS is the first self-supervised approach that leverages neural surface representation to break the dependence on large amounts of annotated data and strong constraints. These constraints typically involve observing target objects against a static background or relying on temporal supervision in videos. Extensive experiments on standard benchmarks including LLFF, CO3D, BlendedMVS, TUM and several real-world scenes show that Surface-SOS always yields finer object masks than its NeRF-based counterparts and surpasses supervised single-view baselines remarkably.</p

CL-MVSNet:Unsupervised Multi-view Stereo with Dual-level Contrastive Learning

Unsupervised Multi-View Stereo (MVS) methods have achieved promising progress recently. However, previous methods primarily depend on the photometric consistency assumption, which may suffer from two limitations: indistinguishable regions and view-dependent effects, e.g., low-textured areas and reflections. To address these issues, in this paper, we propose a new dual-level contrastive learning approach, named CL-MVSNet. Specifically, our model integrates two contrastive branches into an unsupervised MVS framework to construct additional supervisory signals. On the one hand, we present an image-level contrastive branch to guide the model to acquire more context awareness, thus leading to more complete depth estimation in indistinguishable regions. On the other hand, we exploit a scene-level contrastive branch to boost the representation ability, improving robustness to view-dependent effects. Moreover, to recover more accurate 3D geometry, we introduce an ℒ0.5 photometric consistency loss, which encourages the model to focus more on accurate points while mitigating the gradient penalty of undesirable ones. Extensive experiments on DTU and Tanks&amp;Temples benchmarks demonstrate that our approach achieves state-of-the-art performance among all end-to-end unsupervised MVS frameworks and outperforms its supervised counterpart by a considerable margin without fine-tuning

Potential Antitumor Effect of Harmine in the Treatment of Thyroid Cancer

Thyroid cancer is one of the most common types of cancer in endocrine system. In latest studies, harmine has been proved to inhibit the growth of several cancers in vitro and in vivo. In the current study, we evaluated the in vitro and in vivo anticancer efficiency of harmine against thyroid cancer cell line TPC-1. The in vitro cytotoxicity of harmine evaluated by XTT assay indicated that harmine suppressed the proliferation of TPC-1 cells in a dose- and time-dependent manner. Moreover, harmine dose-dependently induced apoptosis of TPC-1 cells through regulating the ratio of Bcl-2/Bax. The colony forming ability of TPC-1 cells was also time-dependently inhibited by harmine. The inhibitory effects of harmine on migration and invasion of TPC-1 cells were studied by wound scratching and Transwell assays. In vivo evaluation showed that harmine effectively inhibited the growth of thyroid cancer in a dose-dependent manner in nude mice. Therefore, harmine might be a promising herbal medicine in the therapy of thyroid cancer and further efforts are needed to explore this therapeutic strategy