Aiming at spectrum allocation problem in elastic optical networks, a spectrum allocation method that combines the advantages of genetic algorithm and ant colony algorithm is proposed. This method uses genetic algorithm to generate the initial solution with rapid random population global search ability. Then the initial solution of the genetic algorithm is transformed into the initial distribution of pheromone required by the ant colony algorithm using the cohesion strategy. Finally, the positive feedback and efficient convergence of the ant colony algorithm are used. Features Find the optimal solution and provide a solution for improving network efficiency.
The g abs of the J-type stacking helix assembly induced by DiBTA was an order of magnitude larger than that of the H-type column assembly induced by DiBETA.
Abstract Circularly polarized luminescence (CPL) materials are highly demanded due to their great potential in optoelectronic and chiroptical elements. However, the preparation of CPL films with high luminescence dissymmetry factors (g lum ) remains a formidable task, which impedes their practical application in film‐based devices. Herein, a facile strategy to prepare solid CPL film with a high g lum through exogenous chiral induction and amplification of liquid crystal polymers is proposed. Amplification and reversion of the CPL appear when the films are annealed at the chiral nematic liquid crystalline temperature and the maximal g lum up to 0.30 due to the enhancement of selective reflection. Thermal annealing treatment at different liquid crystalline states facilitates the formation of the chiral liquid phase and adjusts the circularly polarized emission. This work not only provides a straightforward and versatile platform to construct organic films capable of exhibiting strong circularly polarized emission but also is helpful in understanding the exact mechanism for the liquid crystal enhancement of CPL performance.
Circularly polarized luminescence (CPL) film attracted considerable attention in information storage and encryption, three‐dimensional display, and chiral recognition. However, due to the limited molecular mobility within thin film, achieving a high asymmetry factor and non‐contact modulation of CPL remain challenging. In this work, color‐switchable homochiral CPL films with high luminescence asymmetry factor (glum~0.11) were constructed based on the co‐assembly of a liquid crystal block copolymer (poly (ethylene oxide)‐b‐poly (methyl methacrylate) bearing cyanostilbene group) with axial chiral dinaphthalene diamine derivatives (R/S‐DINBPA). Mechanistic investigation revealed that the efficient stacking of R/S‐DINBPA with cyanostilbene groups and the liquid crystal field provide the driving force for chiral transfer and amplification. The dynamic covalent bonds of the cyanostilbene groups endow the film with chiral fixation ability and enable precise modulation of CPL luminescence bands under UV light irradiation, making it suitable for chiral patterned anti‐counterfeit encryption. This facile strategy provides a general platform for designing intelligent chiroptical materials.
Rheumatoid arthritis (RA) has a high prevalence in patients with non-alcoholic fatty liver disease (NAFLD); however, the underlying mechanism is unclear. To address this, our study established a rat model with both NAFLD and RA by feeding a high-fat diet (HFD) and administering intradermal injection of Freund's complete adjuvant (FCA) with bovine type II collagen. Collagen-induced RA (CIA) was confirmed by hind paw swelling and histological examination. The histomorphological characteristics of NAFLD were evaluated by Masson's trichrome and hematoxylin-eosin staining. The development of NAFLD was further evaluated by measuring serum concentrations of triglyceride (TG), total cholesterol (T-CHO), alanine aminotransferase (ALT), aspartate aminotransferase (AST), and lipopolysaccharide (LPS). The results showed that HFD feeding exacerbated secondary inflammation in CIA rats, whereas FCA/bovine type II collagen injection increased serum levels of ALT, AST, TG, T-CHO, and LPS and exacerbated hepatic fibrosis in both normal and NAFLD rats. Interestingly, NAFLD + CIA significantly promoted the expression of PTRF, a caveolae structure protein involved in hepatic lipid metabolism and affecting downstream signaling of Toll-like receptor 4 (TLR4) and PI3K/Akt activation. High resolution confocal microscopy revealed increased PTRF and TLR4 co-localization in hepatic small vessels of NAFLD + CIA rats. AAV9-mediated PTRF knockdown inhibited TLR4 signaling and alleviated hepatic fibrosis in NAFLD + CIA rats. Together, these findings indicate that NAFLD combined with CIA causes synovial injury and enhances non-alcoholic fatty liver fibrosis in rats. PTRF could attenuate the symptoms of NAFLD + CIA likely by affecting TLR4/PTRF co-expression and downstream signaling.
Abstract Many deployed terminal devices require high stability after equipment delivery, and the project cycle is short, the task is many, the time is tight, and the manpower is limited. At present, the test of this kind of equipment is carried out by the combination of manual configuration of test instruments and manual duty, and there are many problems. In order to reduce the test cost and promote the development of the industry, this paper studies the terminal evaluation method and system based on digital twin technology, realizes the simulation test of terminal function integrity, performance compliance, protocol standard compliance, compatibility, security and reliability at the virtual level, and selects the necessary test items. The application of project results can ensure the high scalability of terminal evaluation and reduce the waste of resources caused by unnecessary testing.
With the in-depth development of Internet of things technology, a large number of Internet of things sensing devices are deployed in various environments of power grid. Smart meters can continuously obtain users' power consumption parameters according to a certain frequency, and transmit them to power companies through Internet of things communication technology. In the existing smart grid architecture, the power grid system produces a large amount of related data. Based on these data, more useful information can be mined to improve the accuracy of load forecasting. However, load forecasting is affected by many complex factors, weather, date type, user behavior mode and so on. Most of the existing time series forecasting methods have some limitations when applied to power load forecasting. Aiming at the problem that the structure of traditional ESN reserve pool affects the forecasting performance; this paper adopts the echo state network with double reserve pools. According to the demand of load forecasting, the depth neural network intelligent load forecasting model is constructed by using the historical load data and multi-dimensional information such as environment, and the parameters of the echo state network with double reserve pools are optimized by the bacterial foraging algorithm. The simulation results show that the proposed BFA-DRESN can effectively improve the prediction accuracy.
Traditionally, the voltage and current sampling wiring for the device of low-voltage station area acquisition and monitoring is complex. Furthermore, there are many nodes, and each node is measured by wiring, consequently safety and efficiency have to face great challenges. This paper proposes a new idea of independent voltage and current sampling, using high-precision synchronous time synchronization and high bandwidth wireless transmission technology to promote the miniaturization design of wireless metering devices and smart terminals. It is verified that the synchronous timing accuracy of less than 10us, and the high bandwidth transmission above 1Mbps can be achieved to meet the requirement of 200Kbps. The results show that the ping-pong timing mechanism and broadband wireless technology used in this paper achieve the expected effect. It will improve ubiquitous sensing, data fusion and intelligent application capabilities of distribution equipment at all levels in the future.
With the development of distribution network, the amount of data and computation generated by network edge devices increases dramatically, which brings pressure on data storage, cloud computing and transmission bandwidth. The traditional cloud computing model is difficult to guarantee the real-time performance of data analysis, processing and response, which makes the non-real-time performance of information flow directly affect the stability of energy flow and the reliability of control. According to the requirements of real-time, data security and network bandwidth of active distribution network, this paper proposes a collaborative model of edge computing and cloud computing for active distribution network. Through the analysis of power consumption data, it is verified that the active distribution network based on edge computing can realize the local optimization of storage and processing data of edge nodes, improve the processing efficiency, ensure the real-time data analysis and processing.
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