Domination problems in social networks

The thesis focuses on domination problems in social networks. Domination problems are one of the classical types of problems in computer science. Domination problems are fundamental and widely studied problems in algorithms and complexity theory. They have been extensively studied and adopted in many real-life applications. In general, a set D of vertices of a simple (no loops or multiple edges), undirected graph G = (V,E) is called dominating if each vertex in V −D is adjacent to some vertex in D. The computational problem of computing a dominating set of minimum size is known as “the dominating set problem”. The dominating set problem is NP-hard in general graphs. A social network - the graph of relationships and interactions within a group of individuals - plays a fundamental role as a medium for the spread of information, ideas, and influence among its members. In a social network, people, who have problems such as drinking, smoking and drug use related issues, can have both positive and negative impact on each other and a person can take and move among different roles since they are affected by their peers. As an example, positive impacts of intervention and education programs on a properly selected set of initial individuals can diffuse widely into society via various social contacts: face to face, phone calls, email, social networks and so on. Exploiting the relationships and influences among individuals in social networks might offer considerable benefit to both the economy and society. In order to deal with social problems, the positive influence dominating set (PIDS) is a typical one to help people to alleviate these social problems. However, existing PIDS algorithms are usually greedy and finding approximation solutions that are inefficient for the growing social networks. By now these proposed algorithms can deal with social problems only in undirected social networks with uniform weight value. To overcome the shortcomings of the existing PIDS model, a novel domination model namely weight positive influence dominating set (WPIDS) is presented. A main contribution of the thesis is that the proposed WPIDS model can be applied in weighted directed social networks. It considers the direction and degree of users’ influence in social networks in which the PIDS model does not. The experimental results have revealed that the WPIDS model is more effective than the PIDS model. At the same time, thanks to the publication of Dijkstra’s pioneering paper, a lot of self-stabilizing algorithms for computing minimal dominating sets have been proposed, such as the self-stabilizing algorithms for minimal single dominating sets and minimal k-dominating sets (MKDS). However, for the MKDS problem, so far there is no self-stabilizing algorithm that works in arbitrary graphs. The proposed algorithms for the MKDS either work for tree graphs or find a minimal 2-dominating set. So, in the thesis, for the MKDS problem, two self-stabilizing algorithms are presented that can operate on general graphs. For the weighted dominating set (WDS) problem, most of the proposed algorithms find approximation solutions to a WDS. For the non-uniform WDS problem, there is no self-stabilizing algorithm for the WDS. In the thesis, self-stabilizing algorithms for the minimal weighted dominating set (MWDS) and minimal positive influence dominating set (MPIDS) are presented when operating in any general network. The worst case convergence time of the two algorithms from any arbitrary initial state are also proved. Finally, in order to reduce cost in an education/intervention programme arising from the PIDS problem, two cooperative cost games about PIDS problem are constructed

Mechanical rolling formation of interpenetrated lithium metal/lithium tin alloy foil for ultrahigh-rate battery anode

To achieve good rate capability of lithium metal anodes for high-energy-density batteries, one fundamental challenge is the slow lithium diffusion at the interface. Here we report an interpenetrated, three-dimensional lithium metal/lithium tin alloy nanocomposite foil realized by a simple calendering and folding process of lithium and tin foils, and spontaneous alloying reactions. The strong affinity between the metallic lithium and lithium tin alloy as mixed electronic and ionic conducting networks, and their abundant interfaces enable ultrafast charger diffusion across the entire electrode. We demonstrate that a lithium/lithium tin alloy foil electrode sustains stable lithium stripping/plating under 30mAcm(-2) and 5mAhcm(-2) with a very low overpotential of 20mV for 200 cycles in a commercial carbonate electrolyte. Cycled under 6C (6.6mAcm(-2)), a 1.0mAhcm(-2) LiNi0.6Co0.2Mn0.2O2 electrode maintains a substantial 74% of its capacity by pairing with such anode

Implication of Climate Change Induced Variation in Wind Extremes on Wind Farm in Mountainous Area of Central China—A Case Study of Hengshan

AbstractWind load is critical to the safety of wind turbines. Wind turbines are designed according to the referrence wind speed of 50-year recurrence interval. The climate change induced variation in extremes of wind could impact safety of wind turbines. Meteorological data from Hengshan weather station in central China is investigated. The wind data of 1973–1992 and 1992–2011 are utilized to estimate the extreme wind of 50-year recurrence interval using method of independent storm and generalized pareto distribution model. It is uncovered that although extreme wind of 50-year recurrence interval escalate a little during the two time spans, it will not affect the safety of wind turbines over there notably

Pre-training with Large Language Model-based Document Expansion for Dense Passage Retrieval

In this paper, we systematically study the potential of pre-training with Large Language Model(LLM)-based document expansion for dense passage retrieval. Concretely, we leverage the capabilities of LLMs for document expansion, i.e. query generation, and effectively transfer expanded knowledge to retrievers using pre-training strategies tailored for passage retrieval. These strategies include contrastive learning and bottlenecked query generation. Furthermore, we incorporate a curriculum learning strategy to reduce the reliance on LLM inferences. Experimental results demonstrate that pre-training with LLM-based document expansion significantly boosts the retrieval performance on large-scale web-search tasks. Our work shows strong zero-shot and out-of-domain retrieval abilities, making it more widely applicable for retrieval when initializing with no human-labeled data.Comment: 10 pages, 3 tables, 4 figures, under revie

Diffraction-Free Bloch Surface Waves

In this letter, we demonstrate a novel diffraction-free Bloch surface wave (DF-BSW) sustained on all-dielectric multilayers that does not diffract after being passed through three obstacles or across a single mode fiber. It can propagate in a straight line for distances longer than 110 {\mu}m at a wavelength of 633 nm and could be applied as an in-plane optical virtual probe, both in air and in an aqueous environment. The ability to be used in water, its long diffraction-free distance, and its tolerance to multiple obstacles make this DF-BSW ideal for certain applications in areas such as the biological sciences, where many measurements are made on glass surfaces or for which an aqueous environment is required, and for high-speed interconnections between chips, where low loss is necessary. Specifically, the DF-BSW on the dielectric multilayer can be used to develop novel flow cytometry that is based on the surface wave, but not the free space beam, to detect the surface-bound targets