A stochastic model for the evolution of the web allowing link deletion

Recently several authors have proposed stochastic evolutionary models for the growth of the web graph and other networks that give rise to power-law distributions. These models are based on the notion of preferential attachment leading to the ``rich get richer'' phenomenon. We present a generalisation of the basic model by allowing deletion of individual links and show that it also gives rise to a power-law distribution. We derive the mean-field equations for this stochastic model and show that by examining a snapshot of the distribution at the steady state of the model, we are able to tell whether any link deletion has taken place and estimate the link deletion probability. Our model enables us to gain some insight into the distribution of inlinks in the web graph, in particular it suggests a power-law exponent of approximately 2.15 rather than the widely published exponent of 2.1

3D buried utility location using a marching-cross-section algorithm for multi-sensor data fusion

We address the problem of accurately locating buried utility segments by fusing data from multiple sensors using a novel Marching-Cross-Section (MCS) algorithm. Five types of sensors are used in this work: Ground Penetrating Radar (GPR), Passive Magnetic Fields (PMF), Magnetic Gradiometer (MG), Low Frequency Electromagnetic Fields (LFEM) and Vibro-Acoustics (VA). As part of the MCS algorithm, a novel formulation of the extended Kalman Filter (EKF) is proposed for marching existing utility tracks from a scan cross-section (scs) to the next one; novel rules for initializing utilities based on hypothesized detections on the first scs and for associating predicted utility tracks with hypothesized detections in the following scss are introduced. Algorithms are proposed for generating virtual scan lines based on given hypothesized detections when different sensors do not share common scan lines, or when only the coordinates of the hypothesized detections are provided without any information of the actual survey scan lines. The performance of the proposed system is evaluated with both synthetic data and real data. The experimental results in this work demonstrate that the proposed MCS algorithm can locate multiple buried utility segments simultaneously, including both straight and curved utilities, and can separate intersecting segments. By using the probabilities of a hypothesized detection being a pipe or a cable together with its 3D coordinates, the MCS algorithm is able to discriminate a pipe and a cable close to each other. The MCS algorithm can be used for both post-and on-site processing. When it is used on site, the detected tracks on the current scs can help to determine the location and direction of the next scan line. The proposed “multi-utility multi-sensor” system has no limit to the number of buried utilities or the number of sensors, and the more sensor data used, the more buried utility segments can be detected with more accurate location and orientation.</p

Empirical analysis of web-based user-object bipartite networks

Understanding the structure and evolution of web-based user-object networks is a significant task since they play a crucial role in e-commerce nowadays. This Letter reports the empirical analysis on two large-scale web sites, audioscrobbler.com and del.icio.us, where users are connected with music groups and bookmarks, respectively. The degree distributions and degree-degree correlations for both users and objects are reported. We propose a new index, named collaborative clustering coefficient, to quantify the clustering behavior based on the collaborative selection. Accordingly, the clustering properties and clustering-degree correlations are investigated. We report some novel phenomena well characterizing the selection mechanism of web users and outline the relevance of these phenomena to the information recommendation problem.Comment: 6 pages, 7 figures and 1 tabl

Effectiveness of Journal Ranking Schemes as a Tool for Locating Information

BACKGROUND: The rise of electronic publishing, preprint archives, blogs, and wikis is raising concerns among publishers, editors, and scientists about the present day relevance of academic journals and traditional peer review. These concerns are especially fuelled by the ability of search engines to automatically identify and sort information. It appears that academic journals can only remain relevant if acceptance of research for publication within a journal allows readers to infer immediate, reliable information on the value of that research. METHODOLOGY/PRINCIPAL FINDINGS: Here, we systematically evaluate the effectiveness of journals, through the work of editors and reviewers, at evaluating unpublished research. We find that the distribution of the number of citations to a paper published in a given journal in a specific year converges to a steady state after a journal-specific transient time, and demonstrate that in the steady state the logarithm of the number of citations has a journal-specific typical value. We then develop a model for the asymptotic number of citations accrued by papers published in a journal that closely matches the data. CONCLUSIONS/SIGNIFICANCE: Our model enables us to quantify both the typical impact and the range of impacts of papers published in a journal. Finally, we propose a journal-ranking scheme that maximizes the efficiency of locating high impact research

Pharmacologic modulation of experimentally induced allergic asthma

Allergic asthma is the most frequent disease of the respiratory tract. The aim of the current experimental and clinical studies was to find new sources of drugs able to control asthmatic inflammation and airway hyperresponsiveness. Our experimental studies were focused on efficiency evaluation of substances able to influence activities of ion channels, phosphodiesterase (PDE) isoforms, substances from the group of polyphenols and NO metabolism modulators during experimentally induced allergic asthma

Genetic Deletion of the Nociceptin/Orphanin FQ Receptor in the Rat Confers Resilience to the Development of Drug Addiction

The nociceptin (NOP) receptor is a G-protein-coupled receptor whose natural ligand is the nociceptin/orphanin FQ (N/OFQ) peptide. Evidence from pharmacological studies suggests that the N/OFQ system is implicated in the regulation of several addiction-related phenomena, such as drug intake, withdrawal and relapse. Here, to further explore the role of NOP system in addiction, we used NOP (-/-) rats to study the motivation for cocaine, heroin and alcohol self-administration in the absence of N/OFQ function. Conditioned place preference (CPP) and saccharin (0.2% w/v) self-administration were also investigated. Results showed that NOP (-/-) rats self-administer less cocaine (0.25, 0.125 or 0.5 mg/infusion) both under a Fixed Ratio 1 and a Progressive Ratio schedule of reinforcement compared to wild type (Wt) controls. Consistently, cocaine (10 mg/kg, i.p.) was able to induce CPP in Wt but not in NOP (-/-). When NOP (-/-) rats were tested for heroin (20 μg/infusion) and ethanol (10% v/v) self-administration, they showeda significantly lower drug intake compared to Wt. Conversely, saccharin self-administration was not affected by NOP deletion, excluding the possibility of nonspecific learning deficits or generalized disruption of reward mechanisms in NOP (-/-) rats. These findings were confirmed with pharmacological experiments using two selective NOP antagonists, SB-612111 and LY2817412. Both drugs attenuated alcohol self-administration in Wt rats but not in NOP (-/-) rats. In conclusion, our results demonstrate that genetic deletion of NOP receptors confers resilience to drug abuse and support a role for NOP receptor antagonism as a potential treatment option for drug addiction.Neuropsychopharmacology accepted article preview online, 26 August 2016. doi:10.1038/npp.2016.171