Results 81 to 90 of about 256,683 (274)
Multi-Round Influence Maximization [PDF]
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018 Conference version accepted by KDD ...
Sun, Lichao +3 more
openaire +2 more sources
Greedy Maximization Framework for Graph-based Influence Functions
, 2016 The study of graph-based submodular maximization problems was initiated in a seminal work of Kempe, Kleinberg, and Tardos (2003): An {\em influence} function of subsets of nodes is defined by the graph structure and the aim is to find subsets of seed ...
Cohen, Edith
core +1 more source
Rethinking plastic waste: innovations in enzymatic breakdown of oil‐based polyesters and bioplastics
FEBS Open Bio, EarlyView.Plastic pollution remains a critical environmental challenge, and current mechanical and chemical recycling methods are insufficient to achieve a fully circular economy. This review highlights recent breakthroughs in the enzymatic depolymerization of both oil‐derived polyesters and bioplastics, including high‐throughput protein engineering, de novo ...
Elena Rosini +2 more
wiley +1 more source
Online Influence Maximization in Non-Stationary Social Networks
, 2016 Social networks have been popular platforms for information propagation. An important use case is viral marketing: given a promotion budget, an advertiser can choose some influential users as the seed set and provide them free or discounted sample ...
Bao, Yixin +4 more
core +1 more source
FEBS Open Bio, EarlyView.KHS‐Cnd peptide is able to impair biofilm formation and disaggregate mature biofilms in Acinetobacter baumannii clinical isolates. Differences in extracellular metabolites reflect changes in biofilm metabolism due to KHS‐Cnd treatment. Among the differentially represented extracellular metabolites upon KHS‐Cnd treatment, the significantly altered ...
Fernando Porcelli +9 more
wiley +1 more source
StaticGreedy: solving the scalability-accuracy dilemma in influence maximization
, 2013 Influence maximization, defined as a problem of finding a set of seed nodes to trigger a maximized spread of influence, is crucial to viral marketing on social networks.
Cheng, Suqi +4 more
core +1 more source
Screening and epitope characterization of Nidogen‐2‐specific nanobodies
FEBS Open Bio, EarlyView.Camel immunization and phage display were employed to generate high‐affinity VHH nanobodies against Nidogen‐2. After library construction, biopanning, ELISA screening, sequencing, and recombinant expression, selected nanobodies were purified and characterized, leading to the preliminary exploration of a nanobody‐based sandwich ELISA for specific ...
Jianchuan Wen +9 more
wiley +1 more source
An Efficient Influence Maximization Algorithm Based on Clique in Social Networks
IEEE Access, 2019 Influence Maximization is to find a subset of influential nodes so that they can spread influence to the largest range in a network. The study on influence maximization is of great importance, and many solutions have been developed, including greedy ...
Huan Li +3 more
doaj +1 more source
Scalable Fair Influence Maximization
, 2023 Given a graph $G$, a community structure $\mathcal{C}$, and a budget $k$, the fair influence maximization problem aims to select a seed set $S$ ($|S|\leq k$) that maximizes the influence spread while narrowing the influence gap between different communities.
Rui, Xiaobin +4 more
openaire +2 more sources
Digital twins to accelerate target identification and drug development for immune‐mediated disorders
FEBS Open Bio, EarlyView.Digital twins integrate patient‐derived molecular and clinical data into personalised computational models that simulate disease mechanisms. They enable rapid identification and validation of therapeutic targets, prediction of drug responses, and prioritisation of candidate interventions.
Anna Niarakis, Philippe Moingeon
wiley +1 more source