Cercopithecins differ from papionins in lacking a M3 hypoconulid. Although this loss may be related to dietary differences, the functional and developmental ramifications of hypoconulid loss are ...currently unclear. The following makes use of dental topographic analysis to quantify shape variation in a sample of cercopithecin M3s, as well as in a sample of Macaca, which has a hypoconulid. To help understand the consequences of hypoconulid loss, Macaca M3s were virtually cropped to remove the hypoconulid and were also subjected to dental topographic analysis. The patterning cascade model and the inhibitory cascade model attempt to explain variation in cusp pattern and molar proportions, respectively. These models have both previously been used to explain patterns of variation in cercopithecines, but have not been examined in the context of hypoconulid loss. For example, previous work suggests that earlier developing cusps impact the development of later developing cusps (i.e., the hypoconulid) and that cercopithecines do not conform to the predictions of the inhibitory cascade model in that the size of the molars is not linear moving distally. Results of the current study suggest that the loss of the hypoconulid is associated with a reduction in dental topography among cercopithecins, which is potentially related to diet, although the connection to diet is not necessarily clear. Results also suggest that the loss of the hypoconulid can be explained by the patterning cascade model, and that hypoconulid loss explains the apparent lack of support for the inhibitory cascade model among cercopithecines. These findings highlight the importance of a holistic approach to studying variation in molar proportions and developmental models.
Selecting influential users in a network is essential to spread information quickly. Identifying influential users is very useful for viral marketing and brand communication. Influence maximization ...(IM) is selecting a few influential users in the network who can maximize the influence spread. Many existing algorithms address IM in single-layer networks. However, the study of IM in multi-layer networks is gaining importance after the advancement and rapid growth in the usage of online social networks. Studying IM in multi-layer networks in the context of viral marketing will be interesting. Motivated by this, this paper investigates the K＋＋ Shell decomposition algorithm to find the k set of influential nodes (seed nodes) in a multi-layer network. The proposed model prunes the nodes based on degree and assign reward points to their neighbors. We conducted a comparative study of various IM algorithms and reported the results. We observed that the K＋＋ Shell decomposition algorithm outperforms other algorithms on various real-time datasets under various settings and environments.
Influence maximization in social networks aims to find a small group of individuals, which have maximal influence cascades. In this study, an optimization model based on a local influence criterion ...is established for the influence maximization problem. The local influence criterion can provide a reliable estimation for the influence propagations in independent and weighted cascade models. A discrete particle swarm optimization algorithm is then proposed to optimize the local influence criterion. The representations and update rules for the particles are redefined in the proposed algorithm. Moreover, a degree based heuristic initialization strategy and a network-specific local search strategy are introduced to speed up the convergence. Experimental results on four real-world social networks demonstrate the effectiveness and efficiency of the proposed algorithm for influence maximization.
Organic topsoil layers are important sources of dissolved organic matter (DOM) transported to deeper soil layers. During passage through the mineral soil, both organic matter (OM) quality and ...quantity change markedly. Whether these alterations are due to sorption processes alone or to additional stepwise exchange processes of OM on mineral surfaces (“cascade model”) is not fully understood. To test the “cascade model”, we conducted a laboratory flow cascade experiment with undisturbed soil columns from three depths of two different soil profiles (Dystric and Eutric Cambisol) using carbon (C) isotope labelling. Each of the connected topsoil and subsoil columns contained a goethite (α-FeOOH) layer either with or without sorbed 13C-labelled OM to assess the importance of OM immobilization/mobilization reactions with reactive soil minerals. By using a multiple method approach including 13C analysis in the solid and solution phases, nanometer scale secondary ion mass spectrometry (NanoSIMS), and quantitative polymerase chain reaction (qPCR), we quantified organic carbon (OC) adsorption and desorption and net OC exchange at goethite surfaces as well as the associated microbial community patterns at every depth step of the column experiment. The gross OC exchange between OM-coated goethite and the soil solution was in the range of 15–32%. This indicates that a considerable proportion of the mineral associated OM was mobilized and replaced by percolating DOM. We showed that specific groups of bacteria play an important role in processing organic carbon compounds in the mineral micro-environment. Whereas bulk soils were dominated by oligotrophic bacteria such as Acidobacteria, the goethite layers were specifically enriched with copiotrophic bacteria such as Betaproteobacteria. This group of microorganisms made use of labile carbon derived either from direct DOM transport or from OM exchange processes at goethite surfaces. Specific microorganisms appear to contribute to the cascade process of OM transport within soils. Our study confirms the validity of the postulated “cascade model”, featuring the stepwise transport of OM within the soil profile.
•Experimental evidence of the “cascade model” of DOM transport is provided.•Mineral-associated OM can be replaced by DOM over the whole soil profile.•Microbial activity at reactive mineral surfaces is involved in downward cycling of DOM.
Over the past 30years, the Eddy Dissipation Concept (EDC) has been widely applied in the industry for the numerical simulations of turbulent combustion problems. The success of the EDC is mainly due ...to its ability to incorporate detailed chemical mechanisms at an affordable computational cost compared to some other models. Detailed kinetic schemes are necessary in order to capture turbulent flames where there is strong coupling between the turbulence and chemical kinetics. Such flames are found in Moderate and Intense Low-oxygen Dilution (MILD) combustion, where chemical time scales are increased compared with conventional combustion, mainly because of slower reactions (due to the dilution of reactants). Recent modelling studies have highlighted limitations of the standard EDC model when applied to the simulation of MILD systems, noticeably a significant overestimation of temperature levels. Modifications of the model coefficients were proposed to account for the specific features of MILD combustion, i.e. an extension of the reaction region and the reduction of maximum temperatures. The purpose of the present paper is to provide functional expressions showing the dependency of the EDC coefficients on dimensionless flow parameters such as the Reynolds and Damköhler numbers, taking into account the specific features of the MILD combustion regime, where the presence of hot diluent and its influence on the flow and mixing fields impacts on the reaction rate and thermal field. The approach is validated using detailed experimental data from flames stabilized on the Adelaide Jet in Hot Co-flow (JHC) burner at different co-flow compositions (3%, 6% and 9% O2 mass fraction) and fuel-jet Reynolds numbers (5000, 10,000 and 20,000). Results show promising improvement with respect to the standard EDC formulation, especially at diluted conditions and medium to low Reynolds numbers.
The assessment of ecosystem services (ES) is covered in a fragmented manner by environmental decision support tools that provide information about the potential environmental impacts of supply chains ...and their products, such as the well-known Life Cycle Assessment (LCA) methodology. Within the flagship project of the Life Cycle Initiative (hosted by UN Environment), aiming at global guidance for life cycle impact assessment (LCIA) indicators, a dedicated subtask force was constituted to consolidate the evaluation of ES in LCA. As one of the outcomes of this subtask force, this paper describes the progress towards consensus building in the LCA domain concerning the assessment of anthropogenic impacts on ecosystems and their associated services for human well-being. To this end, the traditional LCIA structure, which represents the cause-effect chain from stressor to impacts and damages, is re-casted and expanded using the lens of the ES ‘cascade model’. This links changes in ecosystem structure and function to changes in human well-being, while LCIA links the effect of changes on ecosystems due to human impacts (e.g. land use change, eutrophication, freshwater depletion) to the increase or decrease in the quality and/or quantity of supplied ES. The proposed cascade modelling framework complements traditional LCIA with information about the externalities associated with the supply and demand of ES, for which the overall cost-benefit result might be either negative (i.e. detrimental impact on the ES provision) or positive (i.e. increase of ES provision). In so doing, the framework introduces into traditional LCIA the notion of “benefit” (in the form of ES supply flows and ecosystems' capacity to generate services) which balances the quantified environmental intervention flows and related impacts (in the form of ES demands) that are typically considered in LCA. Recommendations are eventually provided to further address current gaps in the analysis of ES within the LCA methodology.
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•Ecosystem services (ES) are not fully encompassed in Life Cycle Assessments (LCAs).•The ES cascade model is investigated and proposed as one solution to address this gap.•This framework addresses externalities associated with the supply and demand of ES.•Through a cascade model, LCA can account for both environmental costs and benefits.
•We formally define the problem of positive influence maximization problem in signed networks under IC model. We also propose a set of propagation rules to model the competitive influence ...spreading.•We present an algorithm to compute the positive activation probability between each node pair using the independent paths.•To avoid the time-consuming process of simulating the influence propagation, we define a propagation function to estimate the influenced range of a seed set.•An algorithm named PIMSN (positive influence maximization in signed networks) is presented for detecting optimal seed set using the propagation function.
With the rapid development of online social networks, the problem of influence maximization (IM) has attracted much attention from researchers and has been applied in many areas such as marketing and finance. Since positive and negative relations may exist between individuals in social networks, the problem of influence maximization in signed networks has a wide range of applications. This paper presents an efficient algorithm for positive influence maximization in signed networks in the independent cascade model. First, we propose an independent path-based algorithm to compute the activation probabilities between the node pairs. Based on the activation probability, we define a propagation increment function to avoid simulating the influence spreading for selecting candidate seed nodes. We present an algorithm to select the seed nodes to obtain the largest positive influence spreading in the signed network. Empirical results in social networks show that our algorithm can have wider positive influence spreading than other methods.
•Review of conceptual frameworks, e.g. the ‘cascade’ in ecosystem service assessments.•The cascade model provided a common reference for a diverse set of place-based studies•Cascade can help organise ...work, re-frame perspectives & design analytical strategies.•Graphical image of the cascade needs to be supported by other types of material.
The aim of this paper is to identify the role of conceptual frameworks in operationalising and mainstreaming the idea of ecosystem services. It builds on some initial discussions from IPBES, which suggested that conceptual frameworks could be used to: ‘simplify thinking’, ‘structure work’, ‘clarify issues’, and ‘provide a common reference point’. The analysis uses the cascade model as a focus and looks at the way it has been used in recent published material and across a set of case studies from the EU-funded OpenNESS Project as a device for conceptual framing. It found that there are examples in the literature that show the cascade model indeed being used as an ‘organising framework’, a tool for ‘re-framing’ perspectives, an ‘analytical template’, and as an ‘application framework’. Although the published materials on the cascade are rich, these accounts lack insights into the process by which the different versions of the model were created, and so we turned to the set of OpenNESS case studies to examine how they read the cascade. We found that the cascade was able to provide a common reference for a diverse set of studies, and that it was sufficiently flexible for it to be developed and elaborated in ways that were meaningful for the different place-based studies. The case studies showed that generalised models like the cascade can have an important ‘awareness-raising’ role. However, we found that using models of this kind it was more difficult for case studies to link their work to broader societal issues such as human well-being, sustainable ecosystem management, governance, and competitiveness, than to their own concerns. We therefore conclude that to be used effectively, conceptual models like the cascade may need to be supported by other materials that help users read it in different, outward looking ways. We also need to find mechanisms for capturing this experience so that it can be shared with others.
•A new fast module extraction method is presented to select important modules.•Optimal module pruning is proposed reduces the search space for IM problem.•A new criterion is defined for calculating ...node’s influence to identify candidate nodes.•A new measure is defined to select final seed set from candidate nodes.•The classic IC model is improved based on real-world information diffusion and different capabilities of nodes.
In this paper, we explore influence maximization, one of the most widely studied problems in social network analysis. However, developing an effective algorithm for influence maximization is still a challenging task given its NP-hard nature. To tackle this issue, we propose the CSP (Combined modules for Seed Processing) algorithm, which aim to identify influential nodes. In CSP, graph modules are initially identified by a combination of criteria such as the clustering coefficient, degree, and common neighbors of nodes. Nodes with the same label are then clustered together into modules using label diffusion. Subsequently, only the most influential modules are selected using a filtering method based on their diffusion capacity. The algorithm then merges neighboring modules into distinct modules and extracts a candidate set of influential nodes using a new metric to quickly select seed sets. The number of selected nodes for the candidate set is restricted by a defined limit measure. Finally, seed nodes are chosen from the candidate set using a novel node scoring measure. We evaluated the proposed algorithm on both real-world and synthetic networks, and our experimental results indicate that the CSP algorithm outperforms other competitive algorithms in terms of solution quality and speedup on tested networks.
The influence maximization problem has gained particular importance in viral marketing for large-scale spreading in social networks. Developing a fast and appropriate algorithm to identify an ...optimized seed set for the diffusion process on social networks is crucial due to the fast growth of networks. Most fast methods only focus on the degree of nodes while ignoring the strategic position of nodes in the networks. These methods do not have the required quality in finding a seed set in most networks. On the other hand, many other methods have acceptable quality, but their computational overhead is significant. To address these issues, the main concentration of this paper is to propose a fast and accurate method for the influence maximization problem, which uses a local traveling for labeling of nodes based on the influence power, called the LMP algorithm. In the proposed LMP algorithm, first, a travel starts from a node with the lowest influence power to assign a ranking-label for this node and its neighbor nodes in each step based on their diffusion capability and strategic position. The LMP algorithm uses node labeling steps to reduce search space significantly. Three ranking-labels are used in the proposed algorithm, and nodes with the highest ranking-label are selected as candidate nodes. This local and fast step strictly reduces the search space. Finally, the LMP algorithm selects seed nodes based on the topology features and the strategic position of the candidate and connector. The performance of the proposed algorithm is benchmarked with the well-known and recently proposed seed selection algorithms. The experimental results are performed on real-world and synthetic networks to validate the efficiency and effectiveness. The experiments exhibit that the proposed algorithm is the fastest in comparison with other state-of-the-art algorithms, and it has linear time complexity. In addition, it can achieve a good tradeoff between the efficiency and time complexity in the influence maximization problem.
•To propose a fast and accurate method for the influence maximization problem.•A local traveling is used to select candidate nodes for node labeling based on their diffusion capability.•The LMP algorithm uses node labeling step to reduce significantly search space.•Seed nodes are selected from the candidate and specially connector nodes based on the topology features and the specific position.•The proposed algorithm has the best stability, accuracy and running time than other well-known and fast algorithms.•The proposed algorithm does not use any adjustable parameters in steps of algorithms.
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