Learning "O" Helps for Learning More: Handling the Concealed Entity Problem for Class-incremental NER

As the categories of named entities rapidly increase in real-world applications, class-incremental learning for NER is in demand, which continually learns new entity classes while maintaining the old knowledge. Due to privacy concerns and storage constraints, the model is required to update without any annotations of the old entity classes. However, in each step on streaming data, the "O" class in each step might contain unlabeled entities from the old classes, or potential entities from the incoming classes. In this work, we first carry out an empirical study to investigate the concealed entity problem in class-incremental NER. We find that training with "O" leads to severe confusion of "O" and concealed entity classes, and harms the separability of potential classes. Based on this discovery, we design a rehearsal-based representation learning approach for appropriately learning the "O" class for both old and potential entity classes. Additionally, we provide a more realistic and challenging benchmark for class-incremental NER which introduces multiple categories in each step. Experimental results verify our findings and show the effectiveness of the proposed method on the new benchmark

A hybrid approach for parameter optimization of multiple tuned mass dampers in reducing floor vibrations due to occupant walking : theory and parametric studies

This article presents a hybrid approach for determining optimal parameters of multiple tuned mass dampers to reduce the floor vibration due to human walking. The proposed approach consists of two parts. The first one is a partial mode decomposition algorithm to efficiently calculate dynamic responses of the coupled floor–multiple tuned mass damper system subjected to moving walking loads. The second one is an adaptive genetic simulated annealing method for the optimization of multiple tuned mass damper parameters. To establish optimization, certain variables must be considered. These include the mass, natural frequency, and damping ratio of each tuned mass damper in a multiple tuned mass damper system. The objective is to minimize floor responses and remove unreasonable requirements, such as uniform mass distribution and symmetric distribution of the tuned mass damper frequency. The proposed hybrid approach has successfully been applied to optimize the multiple tuned mass damper system to reduce the vibration of a longspan floor with closely spaced modes. By the hybrid approach, an extensive parametric study has been carried out. The results show that different walking load models and uncertainties in the dynamic properties of the floor and each tuned mass damper itself can affect the overall performance of the multiple tuned mass damper system. The proposed hybrid optimization approach is very effective and the resulting multiple tuned mass damper system is robust in reducing floor vibrations under various conditions

Unravelling charge separation via surface built-in electric fields within single particulate photocatalysts

Kelvin Probe Force Microscopy (KPFM) and spatially resolved surface photovoltage (SRSPV) techniques were employed to reveal built-in electric fields and surface photogenerated charge distribution on single particulate photocatalysts. The photogenerated holes and electrons spread over the whole surface of the particulate photocatalyst are imaged on n-type BiVO4 and p-type Cu2O single particles, respectively. It is demonstrated that the built-in electric field in the surface Space Charge Region (SCR) dictates the charge separation/transfer processes and allows the drift of one kind of the photogenerated carriers to the surface, while holding another kind of the carriers in the bulk. The results emphasize the role of the SCR played in the unidirectional charge transport between the bulk and surface in the particulate photocatalyst, which may be the crucial reason for low solar energy conversion efficiency

Steroids from Ganoderma sinense as new natural inhibitors of cancer-associated mutant IDH1

Isocitrate dehydrogenase (IDH) is one of the key enzymes in the tricarboxylic acid cycle, and IDH mutations have been associated with many cancers, including glioblastoma, sarcoma, acute myeloid leukemia, etc. Three natural steroids 1–3 from Ganoderma sinense, a unique and rare edible-medicinal fungi in China, were found as potential IDH1 inhibitors by virtual ligand screening method. Among the three compounds, 3 showed the highest binding affinity to IDH1 with significant calculated binding free energy. Enzymatic kinetics demonstrated that 3 inhibited mutant enzyme in a noncompetitive manner. The half effective concentration of 3 for reducing the concentration of D-2HG in HT1080 cells was 35.97 μM. The levels of histone H3K9me3 methylation in HT1080 cells were reduced by treating with 3. Furthermore, knockdown of mutant IDH1 in HT1080 cells decreased the anti-proliferative sensitivity to 3. In short, our findings highlight that compound 3 may have clinical potential in tumor therapies as an effective inhibitor of mutant IDH1

Influence of the Electrostatic Interaction between a Molecular Catalyst and Semiconductor on Photocatalytic Hydrogen Evolution Activity in Cobaloxime/CdS Hybrid Systems

The influence of the electrostatic interaction on photocatalytic H-2 evolution activity in cobaloxime/cadmium sulfide (CdS) hybrid systems was studied by measuring the charges of the cobaloximes and the zeta potentials of CdS under different pH conditions (pHs 4-7). Cobaloxime/CdS hybrid systems may have potential as a valid model for the investigation of the electrostatic interaction between a molecular catalyst and semiconductor because the kinetics of methanol oxidation and the driving force of electron transfer from photoirradiated CdS to cobaloxime have little effect on the pH-dependent photocatalytic H-2 evolution activity. Our experimental results suggest that electrostatic repulsion between cobaloxime and CdS disfavors the electron transfer from CdS to cobaloxime and hence lowers the photocatalytic H-2 evolution activity. Whereas, electrostatic attraction favors the electron transfer process and enhances the photocatalytic H-2 evolution activity. However, an electrostatic attraction interaction that is too strong may accelerate both forward and backward electron transfer processes, which would reduce charge separation efficiency and lower photocatalytic H-2 evolution activity

Searching for Optimal Subword Tokenization in Cross-domain NER

Input distribution shift is one of the vital problems in unsupervised domain adaptation (UDA). The most popular UDA approaches focus on domain-invariant representation learning, trying to align the features from different domains into similar feature distributions. However, these approaches ignore the direct alignment of input word distributions between domains, which is a vital factor in word-level classification tasks such as cross-domain NER. In this work, we shed new light on cross-domain NER by introducing a subword-level solution, X-Piece, for input word-level distribution shift in NER. Specifically, we re-tokenize the input words of the source domain to approach the target subword distribution, which is formulated and solved as an optimal transport problem. As this approach focuses on the input level, it can also be combined with previous DIRL methods for further improvement. Experimental results show the effectiveness of the proposed method based on BERT-tagger on four benchmark NER datasets. Also, the proposed method is proved to benefit DIRL methods such as DANN.Comment: IJCAI 202

Surface Assistant Charge Separation in PEC Cu2S-Ni/Cu2O Cathode

Fabrication of a high efficiency photocathode is a challenging issue in photoelectrocatalysis (PEC). In this work, a Cu2S-Ni/Cu2O photocathode was constructed via electrodeposition followed by a two-step overlayer deposition procedure including direct-current magnetron sputtering (DCMS) and ion exchange reaction. We found that the presence of Ni in the inner-layer could not only affect the morphology but also enhance the formation rate of the outerlayer Cu2S. The XPS results indicate that the Ni exist as NiOx instead of Ni-0. The photocurrent of Cu2S-Ni/Cu2O achieved 2 times of it on the pristine Cu2O. The charge dynamic characterizations, including electrochemical impedance spectroscopy (EIS), Tafel slopes, and photoluminescence (PL) spectra, demonstrated that the Ni can promote the hydrogen evolution reaction follow the Heyrovsky reaction, while Cu2S shows a crucial role on the surface charge separation. At last, surface photovoltage microscopy (SPVM) technology was used to reveal the function of each overlayer. It gives direct evidence for the charge transportation pathway in the system and explains the function of each component

Artificial light-driven ion pump for photoelectric energy conversion (vol 10, pg 74, 2019)

The original version of this Article contained errors in Figure 3. In Fig. 3d, the label ‘With light irradiation’ was originally incorrectly given as ‘Without light irradiation’. In Fig. 3f, the label ‘Without light irradiation’ was originally incorrectly given as ‘With light irradiation’. This has been corrected in both the PDF and HTML versions of the Article