Work Function of Single-wall Silicon Carbide Nanotube

Using first-principles calculations, we study the work function of single wall silicon carbide nanotube (SiCNT). The work function is found to be highly dependent on the tube chirality and diameter. It increases with decreasing the tube diameter. The work function of zigzag SiCNT is always larger than that of armchair SiCNT. We reveal that the difference between the work function of zigzag and armchair SiCNT comes from their different intrinsic electronic structures, for which the singly degenerate energy band above the Fermi level of zigzag SiCNT is specifically responsible. Our finding offers potential usages of SiCNT in field-emission devices.Comment: 3 pages, 3 figure

A system for learning statistical motion patterns

Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy k-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction

Web service locating unit in RFID-centric anti-counterfeit system

Abstract-The problem of piracy has disturbed people's daily life for hundreds of years and has not been relieved until now, though many existing anti-counterfeit solutions have been applied. However, due to the emergences of Radio Frequency IDentification (RFID) technologies, there is a more reliable alternative solution to construct authentication system. On the other hand, there arises another issue of how to simplify the deployment of RFID-centric anti-counterfeit system over the Internet. In this article, we propose an approach, Web Service Locating Unit (WSLU), to achieve this goal to manage numbers of RFID-centric authentication services (relied on web services)

A system for learning statistical motion patterns

Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy k-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction

In vitro assessment of the toxicity of lead (Pb2+) to phycocyanin

© 2017 Elsevier Ltd This work reports the influence of lead (Pb2+) on fluorescence characteristics and protein structure of phycocyanin molecules experimentally in vitro. The fluorescence intensity decreases with the increasing concentration of Pb2+ from 0 to 5 × 10−5 mol L−1, showing the fluorescence quenching of phycocyanin by Pb2+. The quenching process is suggested to be static regarding the calculation results and the experimental results of time-resolved fluorescence decay profiles. The synchronous fluorescence spectra show that the effect of Pb2+ on the Tyr residues of phycocyanin is more significant than the Trp residues. The forming of aggregation by the interaction of Pb2+ with phycocyanin molecules is suggested from the results of resonance light scattering spectra. The UV–Vis spectra of the protein skeleton of phycocyanin have a red-shift of about 10 nm with increasing the Pb2+ concentration from 0 to 5 × 10−5 mol L−1, indicating a change in the protein skeleton and its secondary structure. With the increasing Pb2+ concentration, the two negative peaks (209 nm and 218 nm) on circular dichroism spectra become smaller, showing a decrease of the α-helix structure. These results may give people a deeper understanding of that how the heavy metal (Pb2+) can affect the chemo-physical properties of phycocyanin

A new dromaeosaurid (Dinosauria: Theropoda) from the Upper Cretaceous Wulansuhai Formation of Inner Mongolia, China

We describe a new dromaeosaurid theropod from the Upper Cretaceous Wulansuhai Formation of Bayan Mandahu, Inner Mongolia. The new taxon, Linheraptor exquisitus gen. et sp. nov., is based on an exceptionally well-preserved, nearly complete skeleton. This specimen represents the fifth dromaeosaurid taxon recovered from the Upper Cretaceous Djadokhta Formation and its laterally equivalent strata, which include the Wulansuhai Formation, and adds to the known diversity of Late Cretaceous dromaeosaurids. Linheraptor exquisitus closely resembles the recently reported Tsaagan mangas. Uniquely among dromaeosaurids, the two taxa share a large, anteriorly located maxillary fenestra and a contact between the jugal and the squamosal that excludes the postorbital from the infratemporal fenestra. These features suggest a sister-taxon relationship between L. exquisitus and T. mangas, which indicates the presence of a unique dromaeosaurid lineage in the Late Cretaceous of Asia. A number of cranial and dental features seen in L. exquisitus and T. mangas, and particularly some postcranial features of L. exquisitus, suggest that these two taxa are probably intermediate in systematic position between known basal and derived dromaeosaurids. The discovery of Linheraptor exquisitus is thus important for understanding the evolution of some salient features seen in the derived dromaeosaurids

Network intrusion detection based on LDA for payload feature selection

Anomaly Intrusion Detection System (IDS) is a statistical based network IDS which can detect attack variants and novel attacks without a priori knowledge. Current anomaly IDSs are inefficient for real-time detection because of their complex computation. This paper proposes a novel approach to reduce the heavy computational cost of an anomaly IDS. Linear Discriminant Analysis (LDA) and difference distance map are used for selection of significant features. This approach is able to transform high-dimensional feature vectors into a low-dimensional domain. The similarity between new incoming packets and a normal profile is determined using Euclidean distance on the simple, low-dimensional feature domain. The final decision will be made according to a pre-calculated threshold to differentiate normal and abnormal network packets. The proposed approach is evaluated using DARPA 1999 IDS dataset. ©2010 IEEE

ZIKV infection activates the IRE1-XBP1 and ATF6 pathways of unfolded protein response in neural cells.

BACKGROUND: Many viruses depend on the extensive membranous network of the endoplasmic reticulum (ER) for their translation, replication, and packaging. Certain membrane modifications of the ER can be a trigger for ER stress, as well as the accumulation of viral protein in the ER by viral infection. Then, unfolded protein response (UPR) is activated to alleviate the stress. Zika virus (ZIKV) is a mosquito-borne flavivirus and its infection causes microcephaly in newborns and serious neurological complications in adults. Here, we investigated ER stress and the regulating model of UPR in ZIKV-infected neural cells in vitro and in vivo. METHODS: Mice deficient in type I and II IFN receptors were infected with ZIKV via intraperitoneal injection and the nervous tissues of the mice were assayed at 5 days post-infection. The expression of phospho-IRE1, XBP1, and ATF6 which were the key markers of ER stress were analyzed by immunohistochemistry assay in vivo. Additionally, the nuclear localization of XBP1s and ATF6n were analyzed by immunohistofluorescence. Furthermore, two representative neural cells, neuroblastoma cell line (SK-N-SH) and astrocytoma cell line (CCF-STTG1), were selected to verify the ER stress in vitro. The expression of BIP, phospho-elF2α, phospho-IRE1, and ATF6 were analyzed through western blot and the nuclear localization of XBP1s was performed by confocal immunofluorescence microscopy. RT-qPCR was also used to quantify the mRNA level of the UPR downstream genes in vitro and in vivo. RESULTS: ZIKV infection significantly upregulated the expression of ER stress markers in vitro and in vivo. Phospho-IRE1 and XBP1 expression significantly increased in the cerebellum and mesocephalon, while ATF6 expression significantly increased in the mesocephalon. ATF6n and XBP1s were translocated into the cell nucleus. The levels of BIP, ATF6, phospho-elf2α, and spliced xbp1 also significantly increased in vitro. Furthermore, the downstream genes of UPR were detected to investigate the regulating model of the UPR during ZIKV infection in vitro and in vivo. The transcriptional levels of atf4, gadd34, chop, and edem-1 in vivo and that of gadd34 and chop in vitro significantly increased. CONCLUSION: Findings in this study demonstrated that ZIKV infection activates ER stress in neural cells. The results offer clues to further study the mechanism of neuropathogenesis caused by ZIKV infection

A stateful mechanism for the tree-rule firewall

© 2014 IEEE. In this paper, we propose a novel connection tracking mechanism for Tree-rule firewall which essentially organizes firewall rules in a designated Tree structure. A new firewall model based on the proposed connection tracking mechanism is then developed and extended from the basic model of Net filter's Conn Track module, which has been used by many early generation commercial and open source firewalls including IPTABLES, the most popular firewall. To reduce the consumption of memory space and processing time, our proposed model uses one node per connection instead of using two nodes as appeared in Net filter model. This can reduce memory space and processing time. In addition, we introduce an extended hash table with more hashing bits in our firewall model in order to accommodate more concurrent connections. Moreover, our model also applies sophisticated techniques (such as using static information nodes, and avoiding timer objects and memory management tasks) to improve its processing speed. Finally, we implement this model on Linux Cent OS 6.3 and evaluate its speed. The experimental results show that our model performs more efficiently in comparison with the Net filter/IPTABLES