An analytical fluid model is proposed for artificially collimating fast electron beams produced in interaction of ultraintense laser pulses with specially engineered sandwich structure targets. The ...theory reveals that in low-density-core structure targets, the magnetic field is generated by the rapid change of the flow velocity of the background electrons in transverse direction (perpendicular to the flow velocity) caused by the density jump. It is found that the spontaneously generated magnetic field reaches as high as 100MG, which is large enough to collimate fast electron transport in overdense plasmas. This theory is also supported by numerical simulations performed using a two-dimensional particle-in-cell code. It is found that the simulation results agree well with the theoretical analysis.
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Twitter has become a target platform for both promoters and spammers to disseminate their messages, which are more harmful than traditional spamming methods, such as email spamming. Recently, large ...amounts of campaigns that contain lots of spam or promotion accounts have emerged in Twitter. The campaigns cooperatively post unwanted information, and thus they can infect more normal users than individual spam or promotion accounts. Organizing or participating in campaigns has become the main technique to spread spam or promotion information in Twitter. Since traditional solutions focus on checking individual accounts or messages, efficient techniques for detecting spam and promotion campaigns in Twitter are urgently needed. In this article, we propose a framework to detect both spam and promotion campaigns. Our framework consists of three steps: the first step links accounts who post URLs for similar purposes; the second step extracts candidate campaigns that may be for spam or promotion purposes; and the third step classifies the candidate campaigns into normal, spam, and promotion groups. The key point of the framework is how to measure the similarity between accounts' purposes of posting URLs. We present two measure methods based on Shannon information theory: the first one uses the URLs posted by the users, and the second one considers both URLs and timestamps. Experimental results demonstrate that the proposed methods can extract the majority of the candidate campaigns correctly, and detect promotion and spam campaigns with high precision and recall.
This study proposes an optimized algorithm for the navigation of the mobile robot in the indoor and dynamic unknown environment based on the decision tree algorithm. Firstly, the error of the yaw ...value outputted from IMU sensor fusion module is analyzed in the indoor environment; then, the adaptive FAST SLAM is proposed to optimize the yaw value from the odometer; in the next, a decision tree algorithm is applied which predicts the correct moving direction of the mobile robot through the outputted yaw value from the IMU sensor fusion module and adaptive FAST SLAM of the odometer data in the indoor and dynamic environment; the following is the navigation algorithm proposed for the mobile robot in the dynamic and unknown environment; finally, a real mobile robot is designed to verify the proposed algorithm.The final result shows the proposed algorithms are valid and effective.
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FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK
Results from the previous experiment have demonstrated bone loss and excess metabolism in Hyperthyroidism-induced rats. Thus, an underlying relationship between metabolism and bone loss was ...speculated. In addition, previous studies have shown the influence of acetylation on metabolism in tissues and diseases. The hypothesis from this case study suggests that excessive metabolism is induced by acetylation of vital metabolism enzymes.
In the case study, a HYP-induced osteoporosis rat model was used and the glucose metabolite was tested through the acetylation of proteins by the mass spectrometer. The results showed that pivotal enzymes of Glycolysis-Tricarboxylic acid cycle-Oxidative phosphorylation were acetylated along with upregulated metabolites. With all acetyly-lysine sites of related enzymes listed, the results in this study showed that bone loss in HYP rats was accompanied by the upregulation of CREB-binding protein (Crebbp, CBP). Furthermore, it is also indicated that CBP has a close relationship with the enhancement of LDHA which promotes glucose metabolism.
Acetylation is highly correlated with excessive energy metabolism in HYP-induced osteoporotic rats, where a representation relationship between CBP and LDHA is demonstrated.
Hyperthyroidism may lead to osteoporosis. Our study found an interesting phenomenon of hyperthyroidism induced-osteoporosis is that osteoporosis is accompanied by excessive glucose metabolism. In this process, some molecular mechanisms are still unclear. This study indicates a high degree of acetylation of metabolic enzymes, which may be closely related to excessive glucose metabolism. The relationship between CBP and LDHA was also investigated in this study, which showed that CBP and LDHA had some extent interaction. Glucose metabolism and acetylation maybe all associated with hyperthyroidism induced-osteoporosis. This data provides new insights into the molecular mechanisms of hyperthyroidism induced-osteoporosis.
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•There were synchronously occurrence of bone loss and excess metabolism in Hyperthyroidism-induced rats.•This study stated that excessive metabolism was highly correlated with acetylated vital metabolism enzymes.•The interaction between CBP and LDHA is obviously evident, and it may play an important role in excessive glucose metabolism in HYP induced OP rats.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
•We propose the GBR algorithm that propagates both trust and distrust.•The propagation of a page’s trust/distrust is decided by its probability of being trust/distrust.•GBR takes advantages from both ...trust and distrust propagation.•GBR outperforms other typical algorithms for both spam demotion and spam detection.
Semi-automatic anti-spam algorithms propagate either trust through links from a set of good seed pages or distrust through inverse-links from a set of bad seed pages to the entire Web. It has been mentioned that a combined usage of both trust and distrust propagations can lead to better results. However, little work has been known to realize this insight successfully. In this paper, we view that each Web page has both a trustworthy side and an untrustworthy side, and propose to assign two scores for each Web page to denote its trustworthy side and untrustworthy side, respectively. We then propose the Good-Bad Rank (GBR) algorithm for propagating trust and distrust simultaneously from both directions. In GBR, the propagation of a page’s trust/distrust is decided by its probability of being trust/distrust. GBR takes advantages from both trust and distrust propagations, thus is more powerful than propagating only trust or distrust. Experimental results show that GBR outperforms other typical link-based anti-spam algorithms that propagates only trust or distrust. GBR achieves comparable performance than another algorithm that propagates both trust and distrust, TDR, but is much more efficient than TDR.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
The exponential growth of computer power in the last 10 years is now creating a great challenge for parallel programming toward achieving realistic performance in the field of scientific computing. ...To improve on the traditional program for numerical simulations of laser fusion in inertial confinement fusion (ICF), the Institute of Applied Physics and Computational Mathematics (IAPCM) initializes a software infrastructure named J Adaptive Structured Meshes applications INfrastructure (JASMIN) in 2004. The main objective of JASMIN is to accelerate the development of parallel programs for large scale simulations of complex applications on parallel computers. Now, JASMIN has released version 1.8 and has achieved its original objectives. Tens of parallel programs have been reconstructed or developed on thousands of processors. JASMIN promotes a new paradigm of parallel programming for scientific computing. In this paper, JASMIN is briefly introduced.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Human facial expressions detection plays a central role in pervasive health care and it is an active research field in computer vision. In this paper, a novel method for facial expression detection ...from dynamic facial images is proposed, which includes two stages of feature extraction and facial expression detection. Firstly, Active Shape Model (ASM) is used to extract the local texture feature, and optical flow technique is determined facial velocity information, which is used to characterize facial expression. Then, fusing the local texture feature and facial velocity information get the hybrid characteristics using Bag of Words. Finally, Multi-Instance Boosting model is used to recognize facial expression from video sequences. In order to be learned quickly and complete the detection, the class label information is used for the learning of the Multi-Instance Boosting model. Experiments were performed on a facial expression dataset built by ourselves and on the JAFFE database to evaluate the proposed method. The proposed method shows substantially higher accuracy at facial expression detection than has been previously achieved and gets a detection accuracy of 95.3%, which validates its effectiveness and meets the requirements of stable, reliable, high precision and anti-interference ability etc.
In this study, a novel method based Multiple Instance Learning is proposed for human action recognition in video image sequences. First of all, HOG and T-HOG model is used for extracting space-time ...interest points feature, optical flow model is used for extracting motion features which are used to characterize human action. Then we combine spatial-temporal points of interest vector with the optical flow vector to form a hybrid feature vector. Final Multiple Instance Learning algorithm is presented which is used to recognize human actions. Experimental results show the effectiveness of the proposed method in comparison with other related works in the literature and the proposed method can enhance the robustness, also tolerate noise and interference conditions.
The massive release of pro-inflammatory cytokines is a crucial step in triggering the inflammatory cascade in sepsis. Exploring the key molecules regulating the expression and release of multiple ...cytokines has important value for revealing the mechanism of the cytokine storm in sepsis. This study aimed to investigate the role of multifunctional nuclear protein non-POU domain containing octamer-binding protein (NONO) in the sepsis cytokine storm and to elucidate the underlying mechanism. We found that NONO expression in tissues and cells of sepsis mice was significantly upregulated. Downregulation of NONO expression inhibited the mRNA expression of multiple cytokines, including IL-6, IL-1β, MCP-1, MIP-1α, and MIP-1β in inflammatory cells from mice and human leukemic monocyte-THP1 cells challenged with lipopolysaccharide (LPS), and significantly decreased the level of these cytokines and TNF-α in the supernatant of THP1 cells challenged by LPS. Nono knockout also reduced the levels of TNF-α, IL-6, MIP-1α, and MIP-1β in serum, alleviated hepatocyte edema, and improved the survival rate of sepsis mice. Reduced NONO expression decreased the phospho-ERK1/2 level in inflammatory cells from sepsis mice or THP1 cells challenged by LPS. Phospho-ERK1/2 inhibitor decreased the mRNA expression and concentration of cytokines in the culture supernatant of LPS-induced THP1 cells, similar to the effect of NONO knockdown. After LPS challenge, the levels of phospho-ERK1/2 and NONO were increased, with obvious colocalization in the nucleus and vesicular-like organelles in macrophages. NONO knockdown decreased nuclear translocation of phospho-ERK1/2 in LPS-challenged THP1 cells. These results suggest that NONO is a potentially critical molecule involved in multiple cytokine production in sepsis. Upregulated NONO in sepsis may promote the expression and release of multiple cytokines to participate in a sepsis cytokine storm by promoting ERK1/2 phosphorylation.
•NONO expression was upregulated in sepsis mice.•Nono knockout inhibited the expression and release of proinflammatory cytokines, and reduced the mortality of sepsis mice.•NONO knockdown inhibited the expression and release of proinflammatory cytokines in lipopolysaccharide-induced THP1 cells.•Reduced NONO expression inhibited the phosphorylation of ERK1/2 in mice and THP1 cells challenged by lipopolysaccharide.•NONO and phospho-ERK1/2 colocalized in macrophages challenged by lipopolysaccharide.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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