Color Filtering Localization for Three-Dimensional Underwater Acoustic Sensor Networks

Accurate localization for mobile nodes has been an important and fundamental problem in underwater acoustic sensor networks (UASNs). The detection information returned from a mobile node is meaningful only if its location is known. In this paper, we propose two localization algorithms based on color filtering technology called PCFL and ACFL. PCFL and ACFL aim at collaboratively accomplishing accurate localization of underwater mobile nodes with minimum energy expenditure. They both adopt the overlapping signal region of task anchors which can communicate with the mobile node directly as the current sampling area. PCFL employs the projected distances between each of the task projections and the mobile node, while ACFL adopts the direct distance between each of the task anchors and the mobile node. Also the proportion factor of distance is proposed to weight the RGB values. By comparing the nearness degrees of the RGB sequences between the samples and the mobile node, samples can be filtered out. And the normalized nearness degrees are considered as the weighted standards to calculate coordinates of the mobile nodes. The simulation results show that the proposed methods have excellent localization performance and can timely localize the mobile node. The average localization error of PCFL can decline by about 30.4% than the AFLA method.Comment: 18 pages, 11 figures, 2 table

First Characterization of Sphingomyeline Phosphodiesterase Expression in the Bumblebee, Bombus lantschouensis

  The bumblebee (Bombus lantschouensis Vogt) is an important pollinator of wild plants. Sphingomyelin phosphodiesterase (SMPD) is a hydrolase that plays a major role in sphingolipid metabolism reactions. We report the preparation and characterization of a polyclonal antibody for bumblebee SMPD. We then use the polyclonal antiserum to detect the SMPD protein at different development stages and in different tissues. Our results showed that a 1228bp fragment homologous with the B. terrestris SMPD gene was successfully amplified. The molecular weight of the fusion protein was about 70 kDa by SDS-PAGE. An effective polyclonal antibody against SMPD was also obtained from mice and found to have a higher specificity for bumblebee SMPD. Western blotting detection showed that SMPD was expressed at a high level in queen ovaries, although expression was lower in the midgut and venom gland. SMPD expression decreased from the egg stage until the pdd stage. We interpret our results as showing that the development of an effective polyclonal antiserum for the SMPD protein of a bumblebee, which provides a tool for exploring the function of the SMPD gene. In addition, the work has confirmed that SMPD should be considered as an important enzyme during bumblebee egg and larval stages

TCBERT: A Technical Report for Chinese Topic Classification BERT

Bidirectional Encoder Representations from Transformers or BERT~\cite{devlin-etal-2019-bert} has been one of the base models for various NLP tasks due to its remarkable performance. Variants customized for different languages and tasks are proposed to further improve the performance. In this work, we investigate supervised continued pre-training~\cite{gururangan-etal-2020-dont} on BERT for Chinese topic classification task. Specifically, we incorporate prompt-based learning and contrastive learning into the pre-training. To adapt to the task of Chinese topic classification, we collect around 2.1M Chinese data spanning various topics. The pre-trained Chinese Topic Classification BERTs (TCBERTs) with different parameter sizes are open-sourced at \url{https://huggingface.co/IDEA-CCNL}

First-principles calculation on the transport properties of molecular wires between Au clusters under equilibrium

Based on the matrix Green's function method combined with hybrid tight-binding / density functional theory, we calculate the conductances of a series of gold-dithiol molecule-gold junctions including benzenedithiol (BDT), benzenedimethanethiol (BDMT), hexanedithiol (HDT), octanedithiol (ODT) and decanedithiol (DDT). An atomically-contacted extended molecule model is used in our calculation. As an important procedure, we determine the position of the Fermi level by the energy reference according to the results from ultraviolet photoelectron spectroscopy (UPS) experiments. After considering the experimental uncertainty in UPS measurement, the calculated results of molecular conductances near the Fermi level qualitatively agree with the experimental values measured by Tao et. al. [{\it Science} 301, 1221 (2003); {\it J. Am. Chem. Soc.} 125, 16164 (2003); {\it Nano. Lett.} 4, 267 (2004).]Comment: 12 pages,8 figure

Opioid-free anesthesia reduces the severity of acute postoperative motion-induced pain and patient-controlled epidural analgesia-related adverse events in lung surgery: randomized clinical trial

BackgroundOpioids have been used as pain relievers for thousands of years. However, they may also cause undesirable side effects. We therefore performed this study to compare the effect of opioid-free anesthesia (OFA) versus opioid-sparing anesthesia (OSA) on postoperative pain and patient-controlled epidural analgesia (PCEA)-related events.MethodsThis is a single center randomized clinical trial that was recruited patients aged from 18 to 70 years who received video-assisted lung surgery between October 2021 and February 2022. Participants were 1:1 randomly assigned to OFA or OSA. Patients in the OFA group received propofol, rocuronium, esmolol, lidocaine, and magnesium sulfate intravenously with epidural ropivacaine. Patients in the OSA group received propofol, rocuronium, remifentanil, and sufentanil intravenously with epidural hydromorphone and ropivacaine.ResultsA total number of 124 patients were randomly allocated to the OFA or OSA group. In the OFA group, the severity of pain during coughs on the first postoperative days (PODs; VAS score 1.88 ± 0.88 vs. 2.16 ± 1.1, p = 0.044) was significantly lower than that in the OSA group. The total ratio of PCEA-related adverse events in the OFA group [11 (19.6%) vs. 26 (47.3%), p = 0.003] was significantly lower than in the OSA group.ConclusionOFA in patients who received video-assisted lung surgery led to lower severity of acute postoperative motion-induced pain and fewer PCEA-related adverse events on the first POD than in the patients in the OSA group.Clinical trial registrationclinicaltrials.gov, identifier (NCT05063396)

Knowledge Graph Link Prediction Fusing Description and Structural Features

Knowledge graph generally has the problem of incomplete knowledge, which makes link prediction an important research content of knowledge graph. Existing models only focus on the embedding representation of triples. On the one hand, in terms of model input, only the embedding representation of entities and relations is randomly initialized, and the description information of entities and relations is not incorporated, which will lack semantic information; on the other hand, in decoding, the influence of the structural features of the triplet itself on the link prediction results is ignored. Aiming at the above problems, this paper proposes a knowledge graph link prediction model BFGAT (graph attention network link prediction based on fusion of description information and structural features) that integrates description information and structural features. The BFGAT model uses the BERT pretraining model to encode the description information of entities and relations, and integrates the description information into the embedding representation of entities and relations to solve the problem of missing semantic information. In the coding process, graph attention mechanism is used to aggregate the information of adjacent nodes to solve the problem that the target node can obtain more information. The embedding representation of triples is spliced into a matrix in the decoding process, using a method based on CNN convolution pooling to solve the problem of triple structural features. The model is subjected to detailed experiments on the public datasets FB15k-237 and WN18RR, and the experiments show that the BFGAT model can effectively improve the effect of knowledge graph link prediction

Modeling seismic wave propagation in the Loess Plateau using a viscoacoustic wave equation with explicitly expressed quality factor

The thick Quaternary loess on the Loess Plateau of China produces strong seismic attenuation, resulting in weak reflections from subsurface exploration targets. Accurately simulating seismic wavefield in the Loess Plateau is important for guiding subsequent data processing and interpretation. We present a 2D/3D wavefield simulation method for the Loess Plateau using a viscoacoustic wave equation with explicitly expressed quality factor. To take into account the effect of irregular surface, we utilize a vertically deformed grid to represent the topography, and solve the viscoacoustic wave equation in a regular computational domain that conforms to topographic surface. Grid deformation introduces the partial derivatives such as ∂vx/∂z and ∂vy/∂z in the wave equation, which is difficult to be accurately computed using traditional staggered-grid finite-difference method. To mitigate this issue, a finite-difference scheme based on a fully staggered-grid is adopted to solve the viscoacoustic wave equation. Numerical experiments for a simple layer model and 2D/3D realistic Loess Plateau models demonstrate the feasibility and adaptability of the proposed method. The 3D modeling results show comparable amplitude and waveform characteristics to the field data acquired from the Chinese Loess Plateau, suggesting a good performance of the proposed modeling method