Learning Latent Distribution for Distinguishing Network Traffic in Intrusion Detection System

© 2019 IEEE. We develop a novel deep learning model, Multi-distributed Variational AutoEncoder (MVAE), for the network intrusion detection. To make the traffic more distinguishable, MVAE introduces the label information of data samples into the Kullback-Leibler (KL) term of the loss function of Variational AutoEncoder (VAE). This label information allows MVAEs to force/partition network data samples into different classes with different regions in the latent feature space. As a result, the network traffic samples are more distinguishable in the new representation space (i.e., the latent feature space of MVAE), thereby improving the accuracy in detecting intrusions. To evaluate the efficiency of the proposed solution, we carry out intensive experiments on two popular network intrusion datasets, i.e., NSL-KDD and UNSW-NB15 under four conventional classifiers including Gaussian Naive Bayes (GNB), Support Vector Machine (SVM), Decision Tree (DT), and Random Forest (RF). The experimental results demonstrate that our proposed approach can significantly improve the accuracy of intrusion detection algorithms up to 24.6% compared to the original one (using area under the curve metric)

Time Series Analysis for Encrypted Traffic Classification: A Deep Learning Approach

© 2018 IEEE. We develop a novel time series feature extraction technique to address the encrypted traffic/application classification problem. The proposed method consists of two main steps. First, we propose a feature engineering technique to extract significant attributes of the encrypted network traffic behavior by analyzing the time series of receiving packets. In the second step, we develop a deep learning-based technique to exploit the correlation of time series data samples of the encrypted network applications. To evaluate the efficiency of the proposed solution on the encrypted traffic classification problem, we carry out intensive experiments on a raw network traffic dataset, namely VPN-nonVPN, with three conventional classifier metrics including Precision, Recall, and F1 score. The experimental results demonstrate that our proposed approach can significantly improve the performance in identifying encrypted application traffic in terms of accuracy and computation efficiency

A typology for urban Green Infrastructure, to guide multifunctional planning of nature-based solutions

This is the author accepted manuscript. The final version is available on open access from Elsevier via the DOI in this record Data Availability: No data was used for the research described in the article.Urban Green Infrastructure (GI) provides multiple benefits to city inhabitants and can be an important component in nature-based solutions (NBS), but the ecosystem services that underpin those benefits are inconsistently quantified in the literature. There remain substantial knowledge gaps about the level of service supported by less studied GI types, e.g. cemeteries, or less-studied ecosystem services, e.g. noise mitigation. Decision-makers and planners in cities often face conflicting or incomplete information on the effectiveness of GI, particularly on their ability to provide a suite of co-benefits. Here, we describe a feature-based typology of GI which combines elements of land cover, land use and both ecological and social function. It is consistent with user requirements on mapping, and with the needs of models which can conduct more detailed ecosystem service assessments which can guide NBS design. We provide an evidence synthesis based on published literature, which scores the ability of each GI type to deliver a suite of ecosystem services. In the multivariate analysis of the typology scores, the main axis of variation differentiates between constructed (or hybrid) GI types designed primarily for water flow management (delivering relatively few services) and more natural green GI with trees, or blue GI such as lakes and the sea, which deliver a more multi-functional set of regulating services. The most multi-functional GI on this axis also score highest for biodiversity. The second element of variation separates those GI which support very few cultural services and those which score highly in enabling physical wellbeing and social interaction and, to a lesser extent, restoring capacities. Together the typology and multi-functionality matrix provide a much needed assessment for less studied GI types, and allow planners and decision-makers to make a-priori assessments of the relative ability of different GI as part of NBS to address urban challenges.European CommissionMinistry of Science and Technology of ChinaNatural Environment Research Council (NERC

Ultrahigh-rate supercapacitors based on eletrochemically reduced graphene oxide for ac line-filtering

The recent boom in multifunction portable electronic equipments requires the development of compact and miniaturized electronic circuits with high efficiencies, low costs and long lasting time. For the operation of most line-powered electronics, alternating current (ac) line-filters are used to attenuate the leftover ac ripples on direct current (dc) voltage busses. Today, aluminum electrolytic capacitors (AECs) are widely applied for this purpose. However, they are usually the largest components in electronic circuits. Replacing AECs by more compact capacitors will have an immense impact on future electronic devices. Here, we report a double-layer capacitor based on three-dimensional (3D) interpenetrating graphene electrodes fabricated by electrochemical reduction of graphene oxide (ErGO-DLC). At 120-hertz, the ErGO-DLC exhibited a phase angle of −84 degrees, a specific capacitance of 283 microfaradays per centimeter square and a resistor-capacitor (RC) time constant of 1.35 milliseconds, making it capable of replacing AECs for the application of 120-hertz filtering

Analysis of the functional conservation of ethylene receptors between maize and Arabidopsis

Ethylene, a regulator of plant growth and development, is perceived by specific receptors that act as negative regulators of the ethylene response. Five ethylene receptors, i.e., ETR1, ERS1, EIN4, ETR2, and ERS2, are present in Arabidopsis and dominant negative mutants of each that confer ethylene insensitivity have been reported. In contrast, maize contains just two types of ethylene receptors: ZmERS1, encoded by ZmERS1a and ZmERS1b, and ZmETR2, encoded by ZmETR2a and ZmETR2b. In this study, we introduced a Cys to Tyr mutation in the transmembrane domain of ZmERS1b and ZmETR2b that is present in the etr1-1 dominant negative mutant and expressed each protein in Arabidopsis. Mutant Zmers1b and Zmetr2b receptors conferred ethylene insensitivity and Arabidopsis expressing Zmers1b or Zmetr2b were larger and exhibited a delay in leaf senescence characteristic of ethylene insensitive Arabidopsis mutants. Zmers1b and Zmetr2b were dominant and functioned equally well in a hemizygous or homozygous state. Expression of the Zmers1b N-terminal transmembrane domain was sufficient to exert dominance over endogenous Arabidopsis ethylene receptors whereas the Zmetr2b N-terminal domain failed to do so. Neither Zmers1b nor Zmetr2b functioned in the absence of subfamily 1 ethylene receptors, i.e., ETR1 and ERS1. These results suggest that Cys65 in maize ZmERS1b and ZmETR2b plays the same role that it does in Arabidopsis receptors. Moreover, the results demonstrate that the mutant maize ethylene receptors are functionally dependent on subfamily 1 ethylene receptors in Arabidopsis, indicating substantial functional conservation between maize and Arabidopsis ethylene receptors despite their sequence divergence

A review of elliptical and disc galaxy structure, and modern scaling laws

A century ago, in 1911 and 1913, Plummer and then Reynolds introduced their models to describe the radial distribution of stars in `nebulae'. This article reviews the progress since then, providing both an historical perspective and a contemporary review of the stellar structure of bulges, discs and elliptical galaxies. The quantification of galaxy nuclei, such as central mass deficits and excess nuclear light, plus the structure of dark matter halos and cD galaxy envelopes, are discussed. Issues pertaining to spiral galaxies including dust, bulge-to-disc ratios, bulgeless galaxies, bars and the identification of pseudobulges are also reviewed. An array of modern scaling relations involving sizes, luminosities, surface brightnesses and stellar concentrations are presented, many of which are shown to be curved. These 'redshift zero' relations not only quantify the behavior and nature of galaxies in the Universe today, but are the modern benchmark for evolutionary studies of galaxies, whether based on observations, N-body-simulations or semi-analytical modelling. For example, it is shown that some of the recently discovered compact elliptical galaxies at 1.5 < z < 2.5 may be the bulges of modern disc galaxies.Comment: Condensed version (due to Contract) of an invited review article to appear in "Planets, Stars and Stellar Systems"(www.springer.com/astronomy/book/978-90-481-8818-5). 500+ references incl. many somewhat forgotten, pioneer papers. Original submission to Springer: 07-June-201

TCF7L2 gene polymorphisms do not predict susceptibility to diabetes in tropical calcific pancreatitis but may interact with SPINK1 and CTSB mutations in predicting diabetes

<p>Abstract</p> <p>Background</p> <p>Tropical calcific pancreatitis (TCP) is a type of chronic pancreatitis unique to developing countries in tropical regions and one of its important features is invariable progression to diabetes, a condition called fibro-calculous pancreatic diabetes (FCPD), but the nature of diabetes in TCP is controversial. We analysed the recently reported type 2 diabetes (T2D) associated polymorphisms in the <it>TCF7L2 </it>gene using a case-control approach, under the hypothesis that <it>TCF7L2 </it>variants should show similar association if diabetes in FCPD is similar to T2D. We also investigated the interaction between the <it>TCF7L2 </it>variants and N34S <it>SPINK1 </it>and L26V <it>CTSB </it>mutations, since they are strong predictors of risk for TCP.</p> <p>Methods</p> <p>Two polymorphisms rs7903146 and rs12255372 in the <it>TCF7L2 </it>gene were analyzed by direct sequencing in 478 well-characterized TCP patients and 661 healthy controls of Dravidian and Indo-European ethnicities. Their association with TCP with diabetes (FCPD) and without diabetes was tested in both populations independently using chi-square test. Finally, a meta analysis was performed on all the cases and controls for assessing the overall significance irrespective of ethnicity. We dichotomized the whole cohort based on the presence or absence of N34S <it>SPINK1 </it>and L26V <it>CTSB </it>mutations and further subdivided them into TCP and FCPD patients and compared the distribution of <it>TCF7L2 </it>variants between them.</p> <p>Results</p> <p>The allelic and genotypic frequencies for both <it>TCF7L2 </it>polymorphisms, did not differ significantly between TCP patients and controls belonging to either of the ethnic groups or taken together. No statistically significant association of the SNPs was observed with TCP or FCPD or between carriers and non-carriers of N34S <it>SPINK1 </it>and L26V <it>CTSB </it>mutations. The minor allele frequency for rs7903146 was different between TCP and FCPD patients carrying the N34S <it>SPINK1 </it>variant but did not reach statistical significance (OR = 1.59, 95% CI = 0.93–2.70, P = 0.09), while, <it>TCF7L2</it><it/>variant showed a statistically significant association between TCP and FCPD patients carrying the 26V allele (OR = 1.69, 95% CI = 1.11–2.56, P = 0.013).</p> <p>Conclusion</p> <p>Type 2 diabetes associated <it>TCF7L2 </it>variants are not associated with diabetes in TCP. Since, <it>TCF7L2 </it>is a major susceptibility gene for T2D, it may be hypothesized that the diabetes in TCP patients may not be similar to T2D. Our data also suggests that co-existence of <it>TCF7L2 </it>variants and the <it>SPINK1 </it>and <it>CTSB </it>mutations, that predict susceptibility to exocrine damage, may interact to determine the onset of diabetes in TCP patients.</p

GABA-A Channel Subunit Expression in Human Glioma Correlates with Tumor Histology and Clinical Outcome

GABA (γ-aminobutyric acid) is the main inhibitory neurotransmitter in the CNS and is present in high concentrations in presynaptic terminals of neuronal cells. More recently, GABA has been ascribed a more widespread role in the control of cell proliferation during development where low concentrations of extrasynaptic GABA induce a tonic activation of GABA receptors. The GABA-A receptor consists of a ligand-gated chloride channel, formed by five subunits that are selected from 19 different subunit isoforms. The functional and pharmacological properties of the GABA-A channels are dictated by their subunit composition. Here we used qRT-PCR to compare mRNA levels of all 19 GABA-A channel subunits in samples of human glioma (n = 29) and peri-tumoral tissue (n = 5). All subunits except the ρ1 and ρ3 subunit were consistently detected. Lowest mRNA levels were found in glioblastoma compared to gliomas of lower malignancy, except for the θ subunit. The expression and cellular distribution of the α1, γ1, ρ2 and θ subunit proteins was investigated by immunohistochemistry on tissue microarrays containing 87 gliomas grade II. We found a strong co-expression of ρ2 and θ subunits in both astrocytomas (r = 0.86, p<0.0001) and oligodendroglial tumors (r = 0.66, p<0.0001). Kaplan-Meier analysis and Cox proportional hazards modeling to estimate the impact of GABA-A channel subunit expression on survival identified the ρ2 subunit (p = 0.043) but not the θ subunit (p = 0.64) as an independent predictor of improved survival in astrocytomas, together with established prognostic factors. Our data give support for the presence of distinct GABA-A channel subtypes in gliomas and provide the first link between specific composition of the A-channel and patient survival