Efficient Core Maintenance in Large Dynamic Graphs Rong-Hua Li; Yu, Jeffrey Xu; Rui Mao
IEEE transactions on knowledge and data engineering,
2014-Oct., 2014-10-00, 20141001, Letnik:
26, Številka:
10
Journal Article
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The k-core decomposition in a graph is a fundamental problem for social network analysis. The problem of k-core decomposition is to calculate the core number for every node in a graph. Previous ...studies mainly focus on k-core decomposition in a static graph. There exists a linear time algorithm for k-core decomposition in a static graph. However, in many real-world applications such as online social networks and the Internet, the graph typically evolves overtime. In such applications, a key issue is to maintain the core numbers of nodes when the graph changes overtime. A simple implementation is to perform the linear time algorithm to recompute the core number for every node after the graph is updated. Such simple implementation is expensive when the graph is very large. In this paper, we propose a new efficient algorithm to maintain the core number for every node in a dynamic graph. Our main result is that only certain nodes need to update their core numbers when the graph is changed by inserting/deleting an edge. We devise an efficient algorithm to identify and recompute the core numbers of such nodes. The complexity of our algorithm is independent of the graph size. In addition, to further accelerate the algorithm, we develop two pruning strategies by exploiting the lower and upper bounds of the core number. Finally, we conduct extensive experiments over both real-world and synthetic datasets, and the results demonstrate the efficiency of the proposed algorithm.
Community search is a problem of finding densely connected subgraphs that satisfy the query conditions in a network, which has attracted much attention in recent years. However, all the previous ...studies on community search do not consider the influence of a community. In this paper, we introduce a novel community model called
k
-influential community based on the concept of
k
-core, which can capture the influence of a community. Based on the new community model, we propose a linear-time online search algorithm to find the top-
r
k
-influential communities in a network. To further speed up the influential community search algorithm, we devise a linear-space index structure which supports efficient search of the top-
r
k
-influential communities in optimal time. We also propose an efficient algorithm to maintain the index when the network is frequently updated. We conduct extensive experiments on 7 real-world large networks, and the results demonstrate the efficiency and effectiveness of the proposed methods.
Severe COVID-19 disease caused by SARS-CoV-2 is frequently accompanied by dysfunction of the lungs and extrapulmonary organs. However, the organotropism of SARS-CoV-2 and the port of virus entry for ...systemic dissemination remain largely unknown. We profiled 26 COVID-19 autopsy cases from four cohorts in Wuhan, China, and determined the systemic distribution of SARS-CoV-2. SARS-CoV-2 was detected in the lungs and multiple extrapulmonary organs of critically ill COVID-19 patients up to 67 days after symptom onset. Based on organotropism and pathological features of the patients, COVID-19 was divided into viral intrapulmonary and systemic subtypes. In patients with systemic viral distribution, SARS-CoV-2 was detected in monocytes, macrophages, and vascular endothelia at blood-air barrier, blood-testis barrier, and filtration barrier. Critically ill patients with long disease duration showed decreased pulmonary cell proliferation, reduced viral RNA, and marked fibrosis in the lungs. Permanent SARS-CoV-2 presence and tissue injuries in the lungs and extrapulmonary organs suggest direct viral invasion as a mechanism of pathogenicity in critically ill patients. SARS-CoV-2 may hijack monocytes, macrophages, and vascular endothelia at physiological barriers as the ports of entry for systemic dissemination. Our study thus delineates systemic pathological features of SARS-CoV-2 infection, which sheds light on the development of novel COVID-19 treatment.
Influence maximization has recently received significant attention for scheduling online campaigns or advertisements on social network platforms. However, most studies only focus on user influence ...via cyber interactions while ignoring their physical interactions which are also essential to gauge influence propagation. Additionally, targeted campaigns or advertisements have not received sufficient attention. To address these issues, we first devise a novel holistic influence diffusion model that takes into account both cyber and physical user interactions in an effective and practical way. Based on the new diffusion model, we formulate a new problem of holistic influence maximization , denoted as HIM query, for targeted advertisements in a spatial social network. The HIM query problem aims to find a minimum set of users whose holistic influence can cover all target users in the network, which belongs to a set covering problem. Since the HIM query problem is NP-hard, we develop a greedy baseline algorithm and then improve on this algorithm to reduce the computational cost. To deal with large networks, we also design a spatial-social index to maintain the social, spatial and textual information of users, as well as developing an index-based efficient solution. Finally, we conduct extensive experiments using one synthetic and three real-world datasets to validate the efficiency and effectiveness of the proposed holistic influence diffusion model and our developed algorithms.
Dysbiosis, departure of the gut microbiome from a healthy state, has been suggested to be a powerful biomarker of disease incidence and progression
. Diagnostic applications have been proposed for ...inflammatory bowel disease diagnosis and prognosis
, colorectal cancer prescreening
and therapeutic choices in melanoma
. Noninvasive sampling could facilitate large-scale public health applications, including early diagnosis and risk assessment in metabolic
and cardiovascular diseases
. To understand the generalizability of microbiota-based diagnostic models of metabolic disease, we characterized the gut microbiota of 7,009 individuals from 14 districts within 1 province in China. Among phenotypes, host location showed the strongest associations with microbiota variations. Microbiota-based metabolic disease models developed in one location failed when used elsewhere, suggesting that such models cannot be extrapolated. Interpolated models performed much better, especially in diseases with obvious microbiota-related characteristics. Interpolation efficiency decreased as geographic scale increased, indicating a need to build localized baseline and disease models to predict metabolic risks.
Three-dimensional (3D) ultra-tiny Fe
2
O
3
nanoparticles/graphene hydrogels were prepared using a facile and efficient solvothermal reaction, by which the phase of iron oxide, particle size and the ...morphology of hydrogels can be precisely controlled by simply adjusting the solvothermal reaction time. Accordingly, the effect of the microstructures of hydrogels on electrochemical performance was systematically studied. It was found that Fe
2
O
3
/rGO-50 hydrogels (with a solvothermal reaction time of 50 min) possessed a desirable crystallinity, suitable particle size, decent porous structure, large specific surface area and high electrical conductivity, thus exhibiting a superior electrochemical performance as binder-free anode of supercapacitors: a large potential range of 1.15 V, an ultrahigh specific capacitance of 1090 F·g
−1
at a current density of 2 A·g
−1
and excellent rate capability (531 F·g
−1
at 10 A·g
−1
). The rational design and systematic research of electrode materials will provide new lights for the preparation of advanced electrochemical energy storage devices.
This study uses a coupled atmosphere–ocean model with different numerical settings to investigate the mean and eddy momentum transfer processes responsible for Typhoon Muifa′s (2011) early rapid ...intensification (RI). Three experiments are conducted. Two use the coupled model with a horizontal resolution of either 1 km (HRL) or 3 km (LRL). The third (NoTCFB) is the same as LRL but excludes tropical cyclone (TC)‐induced sea‐surface temperature (SST) cooling. HRL reasonably reproduces Muifa′s intensity during its rapid intensification and weakening periods. The azimuthal mean tangential and radial momentum budgets are analysed before the RI rates diverge between HRL and LRL. Results show that the dominant processes responsible for Muifa′s intensification are different in HRL and LRL. For HRL, the net eddy effect intensifies the storm′s circulation and contracts the eyewall during early RI, and it dominates the net mean‐flow effect inside the radius of maximum wind (RMW), except near the surface and between 2 and 5 km close to the RMW. In contrast, the mean and eddy effects in LRL almost cancel inside the RMW, while the mean‐flow effects dominate and intensify tangential winds outside. Without TC‐induced SST cooling, Muifa in NoTCFB reaches a similar storm intensity as in HRL but its rapid weakening rate is substantially underestimated. The dominant mechanisms for tangential wind intensification in NoTCFB are similar to those in LRL, but their magnitudes are larger, implying a misrepresentation of the dominant momentum transfer processes in NoTCFB during RI. For the radial momentum budget analysis, the dominant processes are similar among the three experiments except for some differences in their locations and strengths.
A coupled atmosphere–ocean model with a 1 km resolution is required to reasonably predict Typhoon Muifa′s rapid intensification (RI) and rapid weakening. The mean and eddy momentum transfer processes responsible for Muifa′s circulation intensification during early RI are model‐resolution dependent. Without the TC‐induced SST cooling effect, the storm intensity in a 3 km version of the model can reach the intensity simulated in the coupled 1 km experiment, but the dominant driving processes remain similar to those in the coupled 3 km experiment.
•Fe(VI) degraded algal organic matter into lower molecular weight products.•DOC and org-N were partially adsorbed by in situ formed ferric nanoparticles.•Membrane flux, Rr and Rir were improved after ...Fe(VI) pre-oxidation.•Formation potential of 19 DBPs was controlled by Fe(VI) pre-oxidation.
Effect of ferrate Fe(VI) pre-oxidation on improving FeCl3/ultrafiltration (UF) of algae-laden source water was investigated. Fe(VI) disrupted algae cells and the in situ formed ferric (hydr)oxides aggregated with cell debris. Particle size and zeta potential of algae increased by 20% and 55% on average, respectively, after treatment with 0.02 mM of Fe(VI). These variations facilitated the formation of algae-ferric floc. Fe(VI) degraded algal extracellular organic matter into lower molecular weight products (fulvic-like and humic-like substances). Membrane flux, reversible membrane resistance (Rr) and irreversible membrane resistance (Rir) were improved by 51%, 61%, and 52% in Fe(VI) (0.02 mM)/FeCl3/UF treatment group compared with FeCl3/UF treatment after three filtration cycles. Fe(VI)/FeCl3/UF removed more than 10% ~ 34% of the dissolved organic compounds (DOC) and 6% ~ 17% of the total nitrogen (TN) compared with FeCl3/UF. Due to the enhanced removal of DOC and TN, formation potential of 12 kinds of carbonaceous-disinfection byproducts (C-DBPs) and 7 kinds of nitrogenous-disinfection byproducts (N-DBPs) decreased by 32.5% and 22.5%, respectively. Fe(VI) pre-oxidant was effective for alleviating membrane fouling and reducing formation potential of DBPs in algal laden water treatment.
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The North Pacific Ocean is a significant carbon sink region, but little is known about the dynamics of particulate organic carbon (POC) and the influences of physical and biological processes in this ...region at the basin scale. Here, we analysed high-resolution surface POC data derived from MODIS-Aqua during 2003-2017, together with satellite-derived sea surface chlorophyll and temperature (SST). There are large spatial and temporal variations in surface POC in the North Pacific. Surface POC is much lower in the subtropical region (<50 mg m
) than in the subarctic region (>100 mg m
), primarily resulting from the south-to-north variability in biological production. Our analyses show significant seasonal and interannual variability in surface POC. In particular, there is one peak in winter-spring in the western subtropical region and two peaks in late spring and fall in the western subarctic region. Surface POC is positively correlated with chlorophyll (r = ~1) and negatively correlated with SST (r = ~-0.45, P < 0.001) south of 45°N, indicating the strong influence of physically driven biological activity on the temporal variability of POC in the subtropical region. There is a significantly positive but relatively lower correlation coefficient (0.6-0.8) between POC and chlorophyll and an overall non-significantly positive correlation between POC and SST north of 45°N, reflecting the reduction in the POC standing stock due to the fast sinking of large particles. The climate modes of the Pacific Decadal Oscillation, El Niño-Southern Oscillation and North Pacific Gyre Oscillation have large impacts on POC in various seasons in the subtropical region and weak influences in the subarctic region. Surface POC was anomalously high after 2013 (increased by ~15%) across the basin, which might be the result of complex interactions of physical and biological processes associated with an anomalous warming event (the Blob).
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