Network Proactive Defense Model Based on Immune Danger Theory

Recent investigations into proactive network defense have not produced a systematic methodology and structure; in addition, issues including multi-source information fusion and attacking behavior analysis have not been resolved. Borrowing ideas of danger sensing and immune response from danger theory, a proactive network defense model based on danger theory is proposed. This paper defines the signals and antigens in the network environment as well as attacking behavior analysis algorithm, providing evidence for future proactive defense strategy selection. The results of preliminary simulations demonstrate that this model can sense the onset of varied network attacks and corresponding endangered intensities, which help to understand the attack methods of hackers and assess the security situation of the current network, thus a better proactive defense strategy can be deployed. Moreover, this model possesses good robustness and accuracy

Representations over diagrams of abelian categories I: Global structure and homological objects

Representations over diagrams of abelian categories unify quite a few notions appearing widely in literature such as representations of categories, presheaves of modules over categories, representations of species, etc. In this series of papers we study them systematically, characterizing special homological objects in representation category and constructing various structures (such as model structures and Wandhuasen category strcutres) on it. In the first paper we investigate the Grothendieck structure of the representation category, describe important functors and adjunction relations between them, and characterize special homological objects. These results lay a foundation for our future works.Comment: We reorganize the work in the original version as a series of papers, and this is the first on

Optimal subsampling for large scale Elastic-net regression

Datasets with sheer volume have been generated from fields including computer vision, medical imageology, and astronomy whose large-scale and high-dimensional properties hamper the implementation of classical statistical models. To tackle the computational challenges, one of the efficient approaches is subsampling which draws subsamples from the original large datasets according to a carefully-design task-specific probability distribution to form an informative sketch. The computation cost is reduced by applying the original algorithm to the substantially smaller sketch. Previous studies associated with subsampling focused on non-regularized regression from the computational efficiency and theoretical guarantee perspectives, such as ordinary least square regression and logistic regression. In this article, we introduce a randomized algorithm under the subsampling scheme for the Elastic-net regression which gives novel insights into L1-norm regularized regression problem. To effectively conduct consistency analysis, a smooth approximation technique based on alpha absolute function is firstly employed and theoretically verified. The concentration bounds and asymptotic normality for the proposed randomized algorithm are then established under mild conditions. Moreover, an optimal subsampling probability is constructed according to A-optimality. The effectiveness of the proposed algorithm is demonstrated upon synthetic and real data datasets.Comment: 28 pages, 7 figure

Frequency-aware optical coherence tomography image super-resolution via conditional generative adversarial neural network

Optical coherence tomography (OCT) has stimulated a wide range of medical image-based diagnosis and treatment in fields such as cardiology and ophthalmology. Such applications can be further facilitated by deep learning-based super-resolution technology, which improves the capability of resolving morphological structures. However, existing deep learning-based method only focuses on spatial distribution and disregard frequency fidelity in image reconstruction, leading to a frequency bias. To overcome this limitation, we propose a frequency-aware super-resolution framework that integrates three critical frequency-based modules (i.e., frequency transformation, frequency skip connection, and frequency alignment) and frequency-based loss function into a conditional generative adversarial network (cGAN). We conducted a large-scale quantitative study from an existing coronary OCT dataset to demonstrate the superiority of our proposed framework over existing deep learning frameworks. In addition, we confirmed the generalizability of our framework by applying it to fish corneal images and rat retinal images, demonstrating its capability to super-resolve morphological details in eye imaging.Comment: 13 pages, 7 figures, submitted to Biomedical Optics Express special issu

Synthesis of a Bi2O2CO3/ZnFe2O4 heterojunction with enhanced photocatalytic activity for visible light irradiation-induced NO removal

Although bismuth subcarbonate (Bi2O2CO3), a member of the Aurivillius-phase oxide family, is a promising photocatalyst for the removal of gaseous NO at parts-per-billion level, the large band gap of this material restricts its applications to the UV light region. The above problem can be mitigated by heterojunction fabrication, which not only broadens the light absorbance range, but also inhibits the recombination of photogenerated charge carriers. Herein, we implement this strategy to fabricate a novel Bi2O2CO3/ZnFe2O4 photocatalyst for NO removal under visible light irradiation and authenticate the formation of the above p-n heterojunction using an array of analytical techniques. Notably, the above composite showed activity superior to those of its individual constituents, and the underlying mechanisms of this activity enhancement were probed by density functional theory calculations and photocurrent measurements. Elevated electron/hole separation efficiency caused by the presence of an internal electric field at the Bi2O2CO3/ZnFe2O4 interface was identified as the main reason of the increased photocatalytic activity, with the main active species were determined as center dot O-2(-) and center dot OH by electron spin resonance spectroscopy. Finally, cytotoxicity testing proved the good biocompatibility of Bi2O2CO3/ZnFe2O4. Thus, this work presents deep insights into the preparation and use of a green p-n heterojunction catalyst in various applications

Petrogenesis of granitoids in the eastern section of the Central Qilian Block: Evidence from geochemistry and zircon U-Pb geochronology

The Caledonian-age Qilian Orogenic Belt at the northern margin of the Greater Tibetan Plateau comprises abundant granitoids that record the histories of the orogenesis. We report here our study of these granitoids from two localities. The Qingchengshan (QCS) pluton, which is situated in the eastern section of the Central Qilian Block, is dated at ~430–420 Ma. It has high-K calc-alkaline composition with high SiO2 (> 70 wt%), enrichment in large ion lithophile elements (LILEs), depletion in high field strength elements (HFSEs), and varying degrees of negative Sr and Eu anomalies. The granitoids in the Tongwei (TW) area, 150 km east of the QCS, are complex, the majority of which are dated at ~440 Ma, but there also exist younger, ~230 Ma intrusions genetically associated with the Qinling Orogeny. The Paleozoic TW intrusions also have high SiO2, fractionated REE (rare earth element) patterns, but a negligible Eu anomaly. The whole rock Sr-Nd-Hf isotopic compositions suggest that all these Paleozoic granitoids are consistent with melting-induced mixing of a two-component source, which is best interpreted as the combination of last fragments of subducted/subducting ocean crust with terrigenous sediments. The mantle isotopic signature of these granitoids (87Sr/86Sri: 0.7038 to 0.7100, εNd(t): −4.8 to −1.3, εHf(t): −0.7 to +4.0) reflects significant (~70 %) contribution of the ocean crust derived in no distant past from the mantle at ocean ridges with an inherited mantle isotopic signature. Partial melting of such ocean crust plus terrigenous sediments in response to the ocean closing and continental collision (between the Qilian and Alashan Blocks) under amphibolite facies conditions is responsible for the magmatism. Varying extents of fractional crystallization (±plagioclase, ±amphibole, ±garnet, ±zircon) of the parental magmas produced the observed QCS and TW granitoids. We note that sample HTC12–01 in the TW area shows an A-type or highly fractionated granite signature characterized by elevated abundances and a flat pattern of REEs, weak Nb-Ta anomaly, conspicuous negative Sr and Eu anomalies (Sr/Sr* = 0.09, Eu/Eu* = 0.22), and thus the high 87Sr/86Sr ratio (0.7851), and moderate εNd(t) (−4.9) and εHf(t) (−2.0), pointing to the significant mantle contribution. Compared with the Paleozoic granitoids, the ~230 Ma granitoids in the TW area represented by sample JPC12–02 have higher initial 87Sr/86Sr (0.7073) and lower εNd(t) (−6.2) and εHf(t) (−4.5) values, offering an ideal opportunity for future studies on tectonic effects of juxtaposition of younger orogenesis on an older orogen

Colloidal Ni2- : XCoxP nanocrystals for the hydrogen evolution reaction

A cost-effective and scalable approach was developed to produce monodisperse NiCoP nanocrystals (NCs) with composition tuned over the entire range (0 ≤ x ≤ 2). NiCoP NCs were synthesized using low-cost, stable and low-toxicity triphenyl phosphite (TPP) as a phosphorus source, metal chlorides as metal precursors and hexadecylamine (HDA) as a ligand. The synthesis involved the nucleation of amorphous Ni-P and its posterior crystallization and simultaneous incorporation of Co. The composition, size and morphology of the NiCoP NCs could be controlled simply by varying the ratio of Ni and Co precursors and the amounts of TPP and HDA. Ternary NiCoP-based electrocatalysts exhibited enhanced electrocatalytic activity toward the hydrogen evolution reaction (HER) compared to binary phosphides. In particular, NiCoP electrocatalysts displayed the lowest overpotential of 97 mV at J = 10 mA cm and an excellent long-term stability. DFT calculations of the Gibbs free energy for hydrogen adsorption at the surface of NiCoP NCs showed NiCoP to have the most appropriate composition to optimize this parameter within the whole NiCoP series. However, the hydrogen adsorption energy was demonstrated not to be the only parameter controlling the HER activity in NiCoP

Hybrid core-multishell nanowire forests for electrical connector applications

Electrical connectors based on hybrid core-multishell nanowire forests that require low engagement forces are demonstrated. The physical binding and electrical connectivity of the nanowire electrical connectors arise from the van der Waals interactions between the conductive metallic shells of the engaged nanowire forests. Specifically, the nanofibrillar structure of the connectors causes an amplification of the contact area between the interpenetrating nanowire arrays, resulting in strong adhesion with relatively low interfacial resistance. The nanowire electrical connectors may enable the exploration of a wide range of applications involving reversible assembly of micro- and macroscale components with built-in electrical interfacing.open151