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

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 $p$th moment with $p>0$ 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 $n$-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 $\Delta f_{\text{sho}}$. The relationship of MW field strength $E_{\text{MW}}$ and $\Delta f_{\text{sho}}$ are studied at the MW frequencies of 31.6 GHz, 22.1 GHz, and 9.2 GHz respectively. The results show that $\Delta f_{\text{sho}}$ can be used to character the much weaker $E_{\text{MW}}$ than the interval of two zero-crossing points $\Delta f_{\text{zeros}}$ and the traditional EIT-AT splitting interval $\Delta f_{\text{m}}$, the minimum $E_{\text{MW}}$ measured by $\Delta f_{\text{sho}}$ is about 30 times smaller than that by $\Delta f_{\text{m}}$. As an example, the minimum $E_{\text{MW}}$ at 9.2 GHz that can be characterized by $\Delta f_{\text{sho}}$ 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 $E_{\text{MW}}$ measured by spectral frequency interval, which is important in the direct measurement of weak $E_{\text{MW}}$