Joint RNN Model for Argument Component Boundary Detection

Argument Component Boundary Detection (ACBD) is an important sub-task in argumentation mining; it aims at identifying the word sequences that constitute argument components, and is usually considered as the first sub-task in the argumentation mining pipeline. Existing ACBD methods heavily depend on task-specific knowledge, and require considerable human efforts on feature-engineering. To tackle these problems, in this work, we formulate ACBD as a sequence labeling problem and propose a variety of Recurrent Neural Network (RNN) based methods, which do not use domain specific or handcrafted features beyond the relative position of the sentence in the document. In particular, we propose a novel joint RNN model that can predict whether sentences are argumentative or not, and use the predicted results to more precisely detect the argument component boundaries. We evaluate our techniques on two corpora from two different genres; results suggest that our joint RNN model obtain the state-of-the-art performance on both datasets.Comment: 6 pages, 3 figures, submitted to IEEE SMC 201

Grafted poly-(ethylene glycol) on lipid surfaces inhibits protein adsorption and cell adhesion

AbstractMonolayers of dipalmitoyl-phosphatidylethanolamine (DPPE) mixing with various mole percentages of distearoyl-phosphatidylethanolamine (DSPE)-conjugated poly-(ethylene glycol) (PEG m.w. 750–5000) were deposited on DPPE-coated glass surfaces by the Langmuir-Blodgett method. Increasing percentages of grafted PEG in these supported lipid surfaces increasingly inhibit the adsorption of bovine serum albumin (BSA), laminin, and fibronectin. Increasing percentages of grafted PEG also inhibit the adhesion of erythrocytes, lymphocytes, and macrophages to these supported lipid surfaces. The adsorption of proteins on lipid coated glass surfaces were assayed by the fluorescence of FITC-labelled proteins. Cell adhesion was measured mainly by microscopic counting. The concentration of PEG-grafted lipids required for the inhibition of erythrocyte adhesion decreases with increasing molecular weight of the grafted PEG. The inhibitory effects are strongly dependent on the graft density of PEG at low concentrations, but weakly dependent on graft density at higher concentrations. For DSPE-PEG5000, the change of graft density dependency occurs approximately at the complete coverage of the lipid surface by the grafted polymer in the mushroom conformation (0.7 mol%), and the transition to partial brush conformation. The change-overs become less distinctive for grafted PEG of lower molecular weights, probably due to the failure of strictly mushroom and brush models of the polymer. The relative inhibitory efficiency is protein or cell dependent. The implication on the function of stealth liposomes is discussed

Unitary Constraints on Semiclassical Schwarzschild Black Holes in the Presence of Island

We reconsider $D\geq4$ dimensional asymptotically flat eternal Schwarzschild black hole, and focus on the situation where the inner boundary of the radiation region is chosen to be near the horizon (i.e. $\beta\ll 1$). The tension between the near horizon condition and the short-distance approximation emerges in large dimensions in previous papers. We remove this tension by introducing a more proper near horizon condition, thus the resulting island solution is well-behaved in any $D\geq4$ dimensional spacetime. Interestingly, a novel constraint is obtained in this situation as required by the existence of the island solution, which directly leads to the constraints on the size of the Schwarzschild black hole, the position of the inner boundary for the radiation region, or the value of $c\cdot\tilde{G}_{N}$ in any $D\geq4$ dimension. When considering the large $D$ limit, the constraint on the size of the Schwarzschild black hole obtained in this situation is in agreement with the result given in $[Phys.Rev.D 102 (2020) 2, 026016]$. We interpret these as the unitary constraints implied by the presence of island in semiclassical gravity.Comment: 21 pages, 4 figures; new contents added in Section 3.2 to derive the constraint, also many related modification

Constraints on Ho\v{r}ava-Lifshitz gravity from GRB 170817A

In this work we focus on a toy model: (3+1)-dimensional Ho\v{r}ava-Lifshitz gravity coupling with an anisotropic electromagnetic (EM) field which is generated through a Kaluza-Klein reduction of a (4+1)-dimensional Ho\v{r}ava-Lifshitz gravity. This model exhibits a remarkable feature that it has the same velocity for both gravitational and electromagnetic waves. This feature makes it possible to restrict the parameters of the theory from GRB 170817A. In this work we use this feature to discuss possible constraints on the parameter $\beta$ in the theory, by analyzing the possible Lorentz invariance violation effect of the GRB 170817A. This is achieved by analyzing potential time delay of gamma-ray photons in this event. It turns out that it places a stringent constraint on this parameter. In the most ideal case, it gives $|1-\sqrt{\beta}|<(10^{-19}-10^{-18})$.Comment: 21 pages, 2 tables. Accepted for publication in EPJ

Modeling and performance analysis of marine DTN networks with Nodes-cluster in an ad hoc sub-net

The marine communication environment is complex and changeable, and the sea wireless infrastructure is few. The delay tolerant network is proposed and applied in ocean environment. We use the ships to store, carry and forward the messages, so as to solve the problem that the communication links are broken frequently and the message cannot be transmitted due to the movement of the nodes. Under the environment of MATLAB, the random motion trajectory of a fishing vessel in the South China Sea is modeled and simulated. A mobile Ad hoc network is formed between ship and ship, and the base station of the land mobile communication network is connected with the marine radio transmitting point through optical fiber. Data is generated according to Poisson distribution in a heterogeneous network at sea and the data transmission uses the flooding mechanism. Taking into account the limited capacity of the wireless transmission point of the sea, we introduced a forwarding-time-limited mechanism. The performance of it is analyzed in the delayed network at sea, and the effects of the survival time, the number of fishing vessels and the coverage of the wireless network on data delivery are compared. The simulation results show that increasing the survival time of the data and the coverage of the wireless network can improve the data delivery ratio, reduce the network transmission delay, and improve the performance of the maritime wireless communication network

PD-Flow: A Point Cloud Denoising Framework with Normalizing Flows

Point cloud denoising aims to restore clean point clouds from raw observations corrupted by noise and outliers while preserving the fine-grained details. We present a novel deep learning-based denoising model, that incorporates normalizing flows and noise disentanglement techniques to achieve high denoising accuracy. Unlike existing works that extract features of point clouds for point-wise correction, we formulate the denoising process from the perspective of distribution learning and feature disentanglement. By considering noisy point clouds as a joint distribution of clean points and noise, the denoised results can be derived from disentangling the noise counterpart from latent point representation, and the mapping between Euclidean and latent spaces is modeled by normalizing flows. We evaluate our method on synthesized 3D models and real-world datasets with various noise settings. Qualitative and quantitative results show that our method outperforms previous state-of-the-art deep learning-based approaches

Synthesis and Sensing Properties of ZnO/ZnS Nanocages

Large-scale uniform ZnO dumbbells and ZnO/ZnS hollow nanocages were successfully synthesized via a facile hydrothermal route combined with subsequent etching treatment. The nanocages were formed through preferential dissolution of the twinned (0001) plane of ZnO dumbbells. Due to their special morphology, the hollow nanocages show better sensing properties to ethanol than ZnO dumbbells. The gain in sensitivity is attributed to both the interface between ZnO and ZnS heterostructure and their hollow architecture that promotes analyte diffusion and increases the available active surface area