1,421 research outputs found
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 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. ). 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 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 in any
dimension. When considering the large limit, the constraint on the size of
the Schwarzschild black hole obtained in this situation is in agreement with
the result given in . 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 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 .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
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