187 research outputs found
Single Shot Reversible GAN for BCG artifact removal in simultaneous EEG-fMRI
Simultaneous EEG-fMRI acquisition and analysis technology has been widely
used in various research fields of brain science. However, how to remove the
ballistocardiogram (BCG) artifacts in this scenario remains a huge challenge.
Because it is impossible to obtain clean and BCG-contaminated EEG signals at
the same time, BCG artifact removal is a typical unpaired signal-to-signal
problem. To solve this problem, this paper proposed a new GAN training model -
Single Shot Reversible GAN (SSRGAN). The model is allowing bidirectional input
to better combine the characteristics of the two types of signals, instead of
using two independent models for bidirectional conversion as in the past.
Furthermore, the model is decomposed into multiple independent convolutional
blocks with specific functions. Through additional training of the blocks, the
local representation ability of the model is improved, thereby improving the
overall model performance. Experimental results show that, compared with
existing methods, the method proposed in this paper can remove BCG artifacts
more effectively and retain the useful EEG information.Comment: 8 pages, 5 figures, 1 tabl
An effective method for parentage determination of the clam (Meretrix meretrix) based on SSR and COI markers
Three EST-SSR markers associated with QTL for the growth of the clam Meretrix meretrix revealed by selective genotyping
Increased Air Pollution Causing Cancers and Its Rapid Online Monitoring
Pollution of indoor and outdoor air has considerably been taken attention abroad as an important environmental problem, and there is sufficient evidence that exposure to outdoor air pollution causes lung cancer and other cancers. Therefore, the current situation of air pollution will be deeply discussed, and a portable environmental gas monitor integrated by a variety of highly sensitive sensors will be developed for rapidly monitoring air pollution, which is able to provide scientific data for environmental pollution control. By this way, human beings are able to be far away from cancer caused by environmental pollution and its suffering
Extracellular vesicles secreted by Echinococcus multilocularis:Important players inangiogenesis promotion
The involvement of Echinococcus multilocularis, and other parasitic helminths, in regulating host physiology is well recognized, but molecular mechanisms remain unclear. Extracellular vesicles (EVs) released by helminths play important roles in regulating parasite-host interactions by transferring materials to the host. Analysis of protein cargo of EVs from E. multilocularis protoscoleces in the present study revealed a unique composition exclusively associated with vesicle biogenesis. Common proteins in various Echinococcus species were identified, including the classical EVs markers tetraspanins, TSG101 and Alix. Further, unique tegumental antigens were identified which could be exploited as Echinococcus EV markers. Parasite- and host-derived proteins within these EVs are predicted to support important roles in parasite-parasite and parasite-host communication. In addition, the enriched host-derived protein pay loads identified in parasite EVs in the present study suggested that they can beinvolved in focal adhesion and potentially promote angiogenesis. Further, increase dangiogenesis was observed in livers of mice infected with E. multilocularis and the expression of several angiogenesis-regulated molecules, including VEGF, MMP9,MCP-1, SDF-1 and serpin E1 were increased. Significantly, EVs released by the E.multilocularis protoscolex promoted proliferation and tube formation by humanumbilical vein endothelial cells (HUVECs) in vitro. Taken together, we present the first evidence that tapeworm-secreted EVs may promote angiogenesis in Echinococcus-infections, identifying central mechanisms of Echinococcus-host interaction
Who is Gambling? Finding Cryptocurrency Gamblers Using Multi-modal Retrieval Methods
With the popularity of cryptocurrencies and the remarkable development of
blockchain technology, decentralized applications emerged as a revolutionary
force for the Internet. Meanwhile, decentralized applications have also
attracted intense attention from the online gambling community, with more and
more decentralized gambling platforms created through the help of smart
contracts. Compared with conventional gambling platforms, decentralized
gambling have transparent rules and a low participation threshold, attracting a
substantial number of gamblers. In order to discover gambling behaviors and
identify the contracts and addresses involved in gambling, we propose a tool
termed ETHGamDet. The tool is able to automatically detect the smart contracts
and addresses involved in gambling by scrutinizing the smart contract code and
address transaction records. Interestingly, we present a novel LightGBM model
with memory components, which possesses the ability to learn from its own
misclassifications. As a side contribution, we construct and release a
large-scale gambling dataset at
https://github.com/AwesomeHuang/Bitcoin-Gambling-Dataset to facilitate future
research in this field. Empirically, ETHGamDet achieves a F1-score of 0.72 and
0.89 in address classification and contract classification respectively, and
offers novel and interesting insights
Competitive Lotka-Volterra Population Dynamics with Jumps
This paper considers competitive Lotka-Volterra population dynamics with
jumps. The contributions of this paper are as follows. (a) We show stochastic
differential equation (SDE) with jumps associated with the model has a unique
global positive solution; (b) We discuss the uniform boundedness of th
moment with and reveal the sample Lyapunov exponents; (c) Using a
variation-of-constants formula for a class of SDEs with jumps, we provide
explicit solution for 1-dimensional competitive Lotka-Volterra population
dynamics with jumps, and investigate the sample Lyapunov exponent for each
component and the extinction of our -dimensional model.Comment: 25 page
Genome-Wide Identification and Expression Profiles of Myosin Genes in the Pacific White Shrimp, Litopenaeus vannamei
As the main structural protein of muscle fiber, myosin is essential for multiple cellular processes or functions, especially for muscle composition and development. Although the shrimp possess a well-developed muscular system, the knowledge about the myosin family in shrimp is far from understood. In this study, we performed comprehensive analysis on the myosin genes in the genome of the Pacific white shrimp, Litopenaeus vannamei. A total of 29 myosin genes were identified, which were classified into 14 subfamilies. Among them, Myo2 subfamily was significantly expanded in the penaeid shrimp genome. Most of the Myo2 subfamily genes were primarily expressed in abdominal muscle, which suggested that Myo2 subfamily genes might be responsible for the well-developed muscular system of the penaeid shrimp. In situ hybridization detection showed that the slow-type muscle myosin gene was mainly localized in pleopod muscle and superficial ventral muscle of the shrimp. This study provides valuable insights into the evolutionary and functional characterization of myosin genes in shrimps, which provides clues for us to understand the well-developed muscular system of shrimp
Microwave electrometry with Rydberg atoms in a vapor cell using microwave amplitude modulation
We have theoretically and experimentally studied the dispersive signal of the
Rydberg atomic electromagnetically induced transparency (EIT) - Autler-Townes
(AT) splitting spectra obtained using amplitude modulation of the microwave
(MW) field. In addition to the two zero-crossing points, the dispersion signal
has two positive maxima with an interval defined as the shoulder interval of
the dispersion signal . The relationship of MW field
strength and are studied at the MW
frequencies of 31.6 GHz, 22.1 GHz, and 9.2 GHz respectively. The results show
that can be used to character the much weaker
than the interval of two zero-crossing points and the traditional EIT-AT splitting interval , the minimum measured by
is about 30 times smaller than that by . As an example,
the minimum at 9.2 GHz that can be characterized by is 0.056 mV/cm, which is the minimum value characterized by
frequency interval using vapour cell without adding any auxiliary fields. The
proposed method can improve the weak limit and sensitivity of
measured by spectral frequency interval, which is important in the direct
measurement of weak
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