Routing Protocols for Underwater Acoustic Sensor Networks: A Survey from an Application Perspective

Underwater acoustic communications are different from terrestrial radio communications; acoustic channel is asymmetric and has large and variable end‐to‐end propagation delays, distance‐dependent limited bandwidth, high bit error rates, and multi‐path fading. Besides, nodes’ mobility and limited battery power also cause problems for networking protocol design. Among them, routing in underwater acoustic networks is a challenging task, and many protocols have been proposed. In this chapter, we first classify the routing protocols according to application scenarios, which are classified according to the number of sinks that an underwater acoustic sensor network (UASN) may use, namely single‐sink, multi‐sink, and no‐sink. We review some typical routing strategies proposed for these application scenarios, such as cross‐layer and reinforcement learning as well as opportunistic routing. Finally, some remaining key issues are highlighted

Bring Me a Good One: Seeking High-potential Startups using Heterogeneous Venture Information Networks

Identifying startups with the highest potential for success is a complex task, necessitating the examination of various information sources, including firm demographics, management team composition, and financial performance. The effectiveness of existing methodologies, such as feature-based and network-topological approaches, is limited for predicting high-potential startups. In response, we propose a novel Venture Graph Neural Network (VenGNN) model, leveraging Heterogeneous Information Networks (HIN) and Graph Neural Networks (GNN) techniques to address the prediction problem. Specifically, we construct a Heterogeneous Venture Information Network (HVIN) using raw business data and deem the prediction a node classification task. Our model integrates theory-guided semantic meta-paths, firm demographics, sampling-based self-attention, and centrality encoding to overcome certain constraints of existing GNNs. Our experimental analysis reveals that VenGNN outperforms state-of-the-art models by 15-20% across a wide range of performance metrics. Our study also includes a comprehensive interpretation analysis to provide investors with an essential understanding for better decision-making

Masked Vision-Language Transformers for Scene Text Recognition

Scene text recognition (STR) enables computers to recognize and read the text in various real-world scenes. Recent STR models benefit from taking linguistic information in addition to visual cues into consideration. We propose a novel Masked Vision-Language Transformers (MVLT) to capture both the explicit and the implicit linguistic information. Our encoder is a Vision Transformer, and our decoder is a multi-modal Transformer. MVLT is trained in two stages: in the first stage, we design a STR-tailored pretraining method based on a masking strategy; in the second stage, we fine-tune our model and adopt an iterative correction method to improve the performance. MVLT attains superior results compared to state-of-the-art STR models on several benchmarks. Our code and model are available at https://github.com/onealwj/MVLT.Comment: The paper is accepted by the 33rd British Machine Vision Conference (BMVC 2022

A Network Topology Control and Identity Authentication Protocol with Support for Movable Sensor Nodes

It is expected that in the near future wireless sensor network (WSNs) will be more widely used in the mobile environment, in applications such as Autonomous Underwater Vehicles (AUVs) for marine monitoring and mobile robots for environmental investigation. The sensor nodes’ mobility can easily cause changes to the structure of a network topology, and lead to the decline in the amount of transmitted data, excessive energy consumption, and lack of security. To solve these problems, a kind of efficient Topology Control algorithm for node Mobility (TCM) is proposed. In the topology construction stage, an efficient clustering algorithm is adopted, which supports sensor node movement. It can ensure the balance of clustering, and reduce the energy consumption. In the topology maintenance stage, the digital signature authentication based on Error Correction Code (ECC) and the communication mechanism of soft handover are adopted. After verifying the legal identity of the mobile nodes, secure communications can be established, and this can increase the amount of data transmitted. Compared to some existing schemes, the proposed scheme has significant advantages regarding network topology stability, amounts of data transferred, lifetime and safety performance of the network

Clinical study of Bian-shi therapy to mitigate insomnia symptoms in young and middle-aged patients with chronic insomnia by regulating neurotransmitters

Objective To investigate the therapeutic mechanism of Bian-shi therapy in improving sleep quality in young and middle-aged patients with chronic insomnia. Methods 40 young and middle-aged patients with chronic insomnia were randomly divided into the western medicine group （n = 20） and Bian-shi group （n = 20）. In the western medicine group， patients were orally treated with zopiclone （7.5 mg， oral administration before bedtime）， and those in the Bian-shi group were treated with placebo and Bian-shi therapy （once a week， 40 min a time， 4 times in total）. The changes of Pittsburgh Sleep Quality Index （PSQI）， and serum melatonin， acetylcholine and norepinephrine before and after 30 d treatment were analyzed and compared between two groups. Results After 30 d treatment， PSQI scores were significantly lower compared with those before treatment in two groups （both P < 0.05）. In the Bian-shi group， PSQI scores were more significantly decreased than those in the western medicine group （all P < 0.05）. After 30 d treatment， serum levels of melatonin and acetylcholine were significantly higher， whereas norepinephrine levels were significantly lower than those before treatment in two groups （all P < 0.05）. In the Bian-shi group， serum levels of melatonin and acetylcholine were significantly higher， whereas norepinephrine levels were significantly lower compared with those in the western medicine group （all P < 0.05）. Conclusions Bian-shi therapy can effectively improve the sleep quality of young and middle-aged patients with chronic insomnia， which yields higher clinical efficacy than that of zopiclone tablets. Multiple neurotransmitters may be involved in the mechanism of Bian-shi therapy to mitigate chronic insomnia symptoms

A STUDY ON THE INHIBITORY EFFECT OF MATRINE ON GASTRIC CANCER SGC-7901 CELLS

The objective of this paper was to investigate the antitumour mechanism of action of matrine by studying its inhibitory effect on gastric cancer SGC-7901 cells. SGC-7901 cells were chosen, and cell-killing capacity of matrine on gastric cancer SGC-7901 cells was determined using MTT assay and single PI staining assay. The results showed that matrine had an inhibitory effect on gastric cancer SGC-7901 cells, which was somewhat dose-dependent. The study concluded that matrine has a significant in-vitro inhibitory effect on SGC-7901 tumour cells, influences cell cycle of SGC-7901 cells, and induces their apoptosis