New Travelling Wave Solutions for Sine-Gordon Equation

We propose a method to deal with the general sine-Gordon equation. Several new exact travelling wave solutions with the form of JacobiAmplitude function are derived for the general sine-Gordon equation by using some reasonable transformation. Compared with previous solutions, our solutions are more general than some of the previous

Determinants of price fluctuations in the electricity market: a study with PCA and NARDL models

In the modern electricity markets, negative prices and spike prices coexist as a pair of opposite economic phenomena. This study investigates how these extreme prices play as the determinants to drive price fluctuations in the electricity market. We construct a two-stage analysis including a principal component analysis (PCA) and a nonlinear autoregressive distributed lags model (NARDL). We apply this analytical method to the wholesale Pennsylvania, New Jersey and Maryland (PJM) electricity market. We find that according to PCA, in the individual transmission lines, spike prices are determinants with largest explanatory power to the variation of prices, while according to NARDL, from the standpoint of the overall market, negative prices have a larger potential effect on both the real-time market and the forward market. These results are valuable and contributive to managers and operators in the electricity markets for policy decision making

Internet of Things and Big Data Analytics for Smart and Connected Communities

This paper promotes the concept of smart and connected communities SCC, which is evolving from the concept of smart cities. SCC are envisioned to address synergistically the needs of remembering the past (preservation and revitalization), the needs of living in the present (livability), and the needs of planning for the future (attainability). Therefore, the vision of SCC is to improve livability, preservation, revitalization, and attainability of a community. The goal of building SCC for a community is to live in the present, plan for the future, and remember the past. We argue that Internet of Things (IoT) has the potential to provide a ubiquitous network of connected devices and smart sensors for SCC, and big data analytics has the potential to enable the move from IoT to real-time control desired for SCC. We highlight mobile crowdsensing and cyber-physical cloud computing as two most important IoT technologies in promoting SCC. As a case study, we present TreSight, which integrates IoT and big data analytics for smart tourism and sustainable cultural heritage in the city of Trento, Italy

New Travelling-Wave Solutions for Dodd-Bullough Equation

A new method, which assumes ϕ' with a function form of f(eϕ), is applied to solve the Dodd-Bullough equation ϕuv=eϕ-e-2ϕ through travelling-wave transformation. A new family of explicit travelling wave solutions is derived. The proposed method works efficiently to be applied to solve other forms of Dodd-Bullough equations

A Signature Based Approach Towards Global Channel Charting with Ultra Low Complexity

Channel charting, an unsupervised learning method that learns a low-dimensional representation from channel information to preserve geometrical property of physical space of user equipments (UEs), has drawn many attentions from both academic and industrial communities, because it can facilitate many downstream tasks, such as indoor localization, UE handover, beam management, and so on. However, many previous works mainly focus on charting that only preserves local geometry and use raw channel information to learn the chart, which do not consider the global geometry and are often computationally intensive and very time-consuming. Therefore, in this paper, a novel signature based approach for global channel charting with ultra low complexity is proposed. By using an iterated-integral based method called signature transform, a compact feature map and a novel distance metric are proposed, which enable channel charting with ultra low complexity and preserving both local and global geometry. We demonstrate the efficacy of our method using synthetic and open-source real-field datasets.Comment: accepted by IEEE ICC 2024 Workshop

Electrocatalytic synthesis of C–N coupling compounds from CO2 and nitrogenous species

The authors gratefully acknowledge financial support from the National Natural Science Foundation of China (Nos. 42277485, 21976141, 22272197, 22102184, 22102136, andU22A20392), the Natural Science Foundation of Hubei Province (2022CFB1001 and 2021CFA034), the Department of Education of Hubei Province (Q20221701 and Q20221704), and the Joint Fund of Yulin University and Dalian National Laboratory for Clean Energy (YLU-DNL Fund 2022008).The electrocatalytic synthesis of C–N coupling compounds from CO2 and nitrogenous species not only offers an effective avenue to achieve carbon neutrality and reduce environmental pollution, but also establishes a route to synthesize valuable chemicals, such as urea, amide, and amine. This innovative approach expands the application range and product categories beyond simple carbonaceous species in electrocatalytic CO2 reduction, which is becoming a rapidly advancing field. This review summarizes the research progress in electrocatalytic urea synthesis, using N2, NO2−, and NO3− as nitrogenous species, and explores emerging trends in the electrosynthesis of amide and amine from CO2 and nitrogen species. Additionally, the future opportunities in this field are highlighted, including electrosynthesis of amino acids and other compounds containing C–N bonds, anodic C–N coupling reactions beyond water oxidation, and the catalytic mechanism of corresponding reactions. This critical review also captures the insights aimed at accelerating the development of electrochemical C–N coupling reactions, confirming the superiority of this electrochemical method over the traditional techniques.publishersversionpublishe

The efficacy of upfront craniocerebral radiotherapy and epidermal growth factor receptor-tyrosine kinase inhibitors in patients with epidermal growth factor receptor-positive non-small cell lung cancer with brain metastases

The present study aims to investigate the therapeutic value of third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) combined with cranial radiotherapy (RT) in patients with EGFR-positive non-small cell lung cancer (NSCLC) and brain metastases (BMs).MethodologyThis is a retrospective study that involved 213 patients with EGFR-NSCLC and BMs, with the patients divided into two groups: the upfront cranial RT (ucRT) group (n = 96) and the non-ucRT group (n = 117). All patients were administered with osimertinib, and those in the ucRT group also underwent RT. The overall survival (OS), progression-free survival (PFS) and intracranial PFS (IPFS) of the two groups were compared.ResultsThe ucRT group manifested a markedly higher IPFS than the non-ucRT group (29.65 months vs 21.8 months; P < 0.0001). The subgroup analysis revealed that patients with oligometastases (OLOGO-BMs; 1–3 BMs) demonstrated a notably longer OS (44.5 months vs 37.3 months; P < 0.0001), PFS (32.3 months vs 20.8 months; P = 0.6884) and IPFS (37.8 months vs 22.1 months; P < 0.0001) in the ucRT group than in the non-ucRT group. However, for patients with multiple BMs, there was no significant difference in OS (27.3 months vs 34.4 months; P = 0.0710) and PFS (13.7 months vs 13.2 months; P = 0.0516) between the ucRT group and the non-ucRT group; the ucRT group exhibited a higher IPFS (26.4 months vs 21.35 months; P = 0.0028). Cox’s multivariate analysis of patients with OLOGO-BM indicated that the use of ucRT was linked to a better OS (heart rate [HR] = 0.392; 95% confidence interval [CI]: 0.178–0.863; P = 0.020) and PFS (HR = 0.558; 95% CI: 0.316–0.986; P = 0.044).ConclusionUpfront cerebral cranial stereotactic radiosurgery can improve outcomes in EGFR-positive patients with NSCLC and OLOGO-BM. However, for patients with multiple BMs, the preferable strategy may be pre-treatment with EGFR-TKIs