Standard random walks and trapping on the Koch network with scale-free behavior and small-world effect

A vast variety of real-life networks display the ubiquitous presence of scale-free phenomenon and small-world effect, both of which play a significant role in the dynamical processes running on networks. Although various dynamical processes have been investigated in scale-free small-world networks, analytical research about random walks on such networks is much less. In this paper, we will study analytically the scaling of the mean first-passage time (MFPT) for random walks on scale-free small-world networks. To this end, we first map the classical Koch fractal to a network, called Koch network. According to this proposed mapping, we present an iterative algorithm for generating the Koch network, based on which we derive closed-form expressions for the relevant topological features, such as degree distribution, clustering coefficient, average path length, and degree correlations. The obtained solutions show that the Koch network exhibits scale-free behavior and small-world effect. Then, we investigate the standard random walks and trapping issue on the Koch network. Through the recurrence relations derived from the structure of the Koch network, we obtain the exact scaling for the MFPT. We show that in the infinite network order limit, the MFPT grows linearly with the number of all nodes in the network. The obtained analytical results are corroborated by direct extensive numerical calculations. In addition, we also determine the scaling efficiency exponents characterizing random walks on the Koch network.Comment: 12 pages, 8 figures. Definitive version published in Physical Review

Review spam detection via temporal pattern discovery

Online reviews play a crucial role in today’s electronic com-merce. It is desirable for a customer to read reviews of products or stores before making the decision of what or from where to buy. Due to the pervasive spam reviews, customers can be misled to buy low-quality products, while decent stores can be defamed by malicious reviews. We ob-serve that, in reality, a great portion (> 90 % in the data we study) of the reviewers write only one review (singleton re-view). These reviews are so enormous in number that they can almost determine a store’s rating and impression. How-ever, existing methods did not examine this larger part of the reviews. Are most of these singleton reviews truthful ones? If not, how to detect spam reviews in singleton reviews? We call this problem singleton review spam detection. To address this problem, we observe that the normal re-viewers ’ arrival pattern is stable and uncorrelated to their rating pattern temporally. In contrast, spam attacks are usually bursty and either positively or negatively correlated to the rating. Thus, we propose to detect such attacks via unusually correlated temporal patterns. We identify and construct multidimensional time series based on aggregate statistics, in order to depict and mine such correlations. In this way, the singleton review spam detection problem is mapped to a abnormally correlated pattern detection prob-lem. We propose a hierarchical algorithm to robustly detect the time windows where such attacks are likely to have hap-pened. The algorithm also pinpoints such windows in dif-ferent time resolutions to facilitate faster human inspection. Experimental results show that the proposed method is ef-fective in detecting singleton review attacks. We discover that singleton review is a significant source of spam reviews and largely affects the ratings of online stores

C-terminal truncated hepatitis B virus X protein promotes hepatocellular carcinogenesis through induction of cancer and stem cell-like properties

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Heterogenous expression of beta-catenin, p16, e-cadherin, and c-myc in multi-stage colorectal carcinogenesis detected by tissue microarray

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Influencing mechanism analysis of holiday activity-travel patterns on transportation energy consumption and emissions in China

Energy shortage and atmospheric pollution problems are getting more serious in China, and transportation is the main source of energy consumption, pollutants, and carbon emissions. This study combined the activity-based analysis method with emission models, and investigated the influence mechanism of people’s activity travel scheduling on transportation energy consumption and emissions on holidays. Based on the holiday travel behavior survey data, the multinomial logistic regression model was first applied to explore the decision mechanisms of individual travel-mode choices in holidays. Next, the emission model was integrated with an activity-based travel demand model to calculate and compare transportation energy consumption and emissions under different policy scenarios. The results showed that socio-demographic characteristics had significant effects on holiday activity–travel patterns, and combined mode chains had a larger number of activity points than single mode chains. With an increase in the trip time of cars, and decrease of travel distance and the number of activity points, transportation energy consumption and emissions could be reduced greatly with an adjustment of holiday activity–travel patterns. The reduced portion is mainly attracted by slow traffic and public transport. However, the effects of a single policy strategy are very limited, thus portfolio policies need to be considered by policy makers

Oncogenic role of clusterin overexpression in multistage colorectal tumorigenesis and progression

Aim: To investigate the expression pattern of clusterin in colorectal adenoma-carcinoma-metastasis series, and to explore the potential role of clustelin in multistage colorectal tumorigenesis and progression. Methods: A colorectal carcinoma (CRC)-tissue microarray (TMA), which contained 85 advanced CRCs including 43 cases of Dukes B, 21 of Dukes C and 21 of Dukes D tumors, were used for assessing the expression of clusterin (clone 41D) and tumor cell apoptotic index (AI) by immunohistochemistry and TUNEL assay, respectively. Moreover the potential correlation of clusterin expression with the patient's clinical-pathological features were also examined. Results: The positive staining of clusterin in different colorectal tissues was primarily a cytoplasmic pattern. Cytoplasmic overexpression of clusterin was detected in none of the normal colorectal mucosa, 17% of the adenomas, 46% of the primary CRCs, and 57% of the CRC metastatic lesions. In addition, a significant positive correlation between overexpression of clusterin and advanced clinical (Dukes) stage was observed (P<0.01). Overexpression of cytoplasmic clusterin in CRCs was inversely correlated with tumor apoptotic index (P<0.01), indicating the anti-apoptotic function of cytoplasmic clusterin in CRCs. Conclusion: These data suggests that overexpression of cytoplasmic clusterin might be involved in the tumorigenesis and/or progression of CRCs. The anti-apoptotic function of cytoplasmic clusterin may be responsible, at least in part, for the development and biologically aggressive behavior of CRC. © 2005 The WJG Press and Elsevier Inc. All rights reserved.published_or_final_versio

MAVEN-Arg: Completing the Puzzle of All-in-One Event Understanding Dataset with Event Argument Annotation

Understanding events in texts is a core objective of natural language understanding, which requires detecting event occurrences, extracting event arguments, and analyzing inter-event relationships. However, due to the annotation challenges brought by task complexity, a large-scale dataset covering the full process of event understanding has long been absent. In this paper, we introduce MAVEN-Arg, which augments MAVEN datasets with event argument annotations, making the first all-in-one dataset supporting event detection, event argument extraction (EAE), and event relation extraction. As an EAE benchmark, MAVEN-Arg offers three main advantages: (1) a comprehensive schema covering 162 event types and 612 argument roles, all with expert-written definitions and examples; (2) a large data scale, containing 98,591 events and 290,613 arguments obtained with laborious human annotation; (3) the exhaustive annotation supporting all task variants of EAE, which annotates both entity and non-entity event arguments in document level. Experiments indicate that MAVEN-Arg is quite challenging for both fine-tuned EAE models and proprietary large language models (LLMs). Furthermore, to demonstrate the benefits of an all-in-one dataset, we preliminarily explore a potential application, future event prediction, with LLMs. MAVEN-Arg and our code can be obtained from https://github.com/THU-KEG/MAVEN-Argument.Comment: Working in progres

The antimicrobial compound xantholysin defines a new group of Pseudomonas cyclic lipopeptides

The rhizosphere isolate Pseudomonas putida BW11M1 produces a mixture of cyclic lipopeptide congeners, designated xantholysins. Properties of the major compound xantholysin A, shared with several other Pseudomonas lipopeptides, include antifungal activity and toxicity to Gram-positive bacteria, a supportive role in biofilm formation, and facilitation of surface colonization through swarming. Atypical is the lipopeptide’s capacity to inhibit some Gram-negative bacteria, including several xanthomonads. The lipotetradecadepsipeptides are assembled by XtlA, XtlB and XtlC, three co-linearly operating non-ribosomal peptide synthetases (NRPSs) displaying similarity in modular architecture with the entolysin-producing enzymes of the entomopathogenic Pseudomonas entomophila L48. A shifted serine-incorporating unit in the eight-module enzyme XtlB elongating the central peptide moiety not only generates an amino acid sequence differing at several equivalent positions from entolysin, but also directs xantholysin’s macrocyclization into an octacyclic structure, distinct from the pentacyclic closure in entolysin. Relaxed fatty acid specificity during lipoinitiation by XtlA (acylation with 3-hydroxydodec-5-enoate instead of 3-hydroxydecanoate) and for incorporation of the ultimate amino acid by XtlC (valine instead of isoleucine) account for the production of the minor structural variants xantholysin C and B, respectively. Remarkably, the genetic backbones of the xantholysin and entolysin NRPS systems also bear pronounced phylogenetic similarity to those of the P. putida strains PCL1445 and RW10S2, albeit generating the seemingly structurally unrelated cyclic lipopeptides putisolvin (undecapeptide containing a cyclotetrapeptide) and WLIP (nonapeptide containing a cycloheptapeptide), respectively. This similarity includes the linked genes encoding the cognate LuxR-family regulator and tripartite export system components in addition to individual modules of the NRPS enzymes, and probably reflects a common evolutionary origin. Phylogenetic scrutiny of the modules used for selective amino acid activation by these synthetases indicates that bacteria such as pseudomonads recruit and reshuffle individual biosynthetic units and blocks thereof to engineer reorganized or novel NRPS assembly lines for diversified synthesis of lipopeptides

Detection of a superconducting phase in a two-atom layer of hexagonal Ga film grown on semiconducting GaN(0001)

The recent observation of superconducting state at atomic scale has motivated the pursuit of exotic condensed phases in two-dimensional (2D) systems. Here we report on a superconducting phase in two-monolayer crystalline Ga films epitaxially grown on wide band-gap semiconductor GaN(0001). This phase exhibits a hexagonal structure and only 0.552 nm in thickness, nevertheless, brings about a superconducting transition temperature Tc as high as 5.4 K, confirmed by in situ scanning tunneling spectroscopy, and ex situ electrical magneto-transport and magnetization measurements. The anisotropy of critical magnetic field and Berezinski-Kosterlitz-Thouless-like transition are observed, typical for the 2D superconductivity. Our results demonstrate a novel platform for exploring atomic-scale 2D superconductor, with great potential for understanding of the interface superconductivity