A dynamic multiobjective evolutionary algorithm based on a dynamic evolutionary environment model

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Traditional dynamic multiobjective evolutionary algorithms usually imitate the evolution of nature, maintaining diversity of population through different strategies and making the population track the Pareto optimal solution set efficiently after the environmental change. However, these algorithms neglect the role of the dynamic environment in evolution, leading to the lacking of active guieded search. In this paper, a dynamic multiobjective evolutionary algorithm based on a dynamic evolutionary environment model is proposed (DEE-DMOEA). When the environment has not changed, this algorithm makes use of the evolutionary environment to record the knowledge and information generated in evolution, and in turn, the knowledge and information guide the search. When a change is detected, the algorithm helps the population adapt to the new environment through building a dynamic evolutionary environment model, which enhances the diversity of the population by the guided method, and makes the environment and population evolve simultaneously. In addition, an implementation of the algorithm about the dynamic evolutionary environment model is introduced in this paper. The environment area and the unit area are employed to express the evolutionary environment. Furthermore, the strategies of constraint, facilitation and guidance for the evolution are proposed. Compared with three other state-of-the-art strategies on a series of test problems with linear or nonlinear correlation between design variables, the algorithm has shown its effectiveness for dealing with the dynamic multiobjective problems

Residual Stress Evaluation with Contour Method for Thick Butt Welded Joint

Thick plate with high tensile strength steel is increasingly employed for offshore structure fabrication, and welding residual stress is essential for assessment of mechanical performance and fatigue toughness. Therefore, it has been becoming the research issue to evaluate the distribution and magnitude of welding residual stress during butt welding of thick plate. With its advantages, contour method (CM) can be used for longitudinal residual stress evaluation by means of measuring sectional shrinkage after cutting the butt welded joint perpendicular to the welding line. Meanwhile, inverse finite element method (IFEM) code is programmed with C++ language to analyze the measured data to reestablish the welding residual stress. And based on the parallel computation of high-performance server, considering the effect of weld remelting and back-gouging during multi-pass welding process, the welding residual stress is predicted by using efficient thermal elastic plastic finite element method (TEP FEM). Results show that longitudinal residual stress turned from tensile stress in welded vicinity into compressive stress in base metal and the maximum tensile stress is 269 MPa. The computed longitudinal residual stress and welding displacement through TEP FEM are identified with the experimental results. In addition, the back-gouging has an insignificant effect on the residual stress but increases the welding displacement of butt welded joint. The proposed TEP FEM can accurately predict the welding residual stress in welded joint and is also an effective method to control welding displacement

Speed, speed variation and crash relationships for urban arterials

Speed and speed variation are closely associated with traffic safety. There is, however, a dearth of research on this subject for the case of urban arterials in general, and in the context of developing nations. In downtown Shanghai, the traffic conditions in each direction are very different by time of day, and speed characteristics during peak hours are also greatly different from those during off-peak hours. Considering that traffic demand changes with time and in different directions, arterials in this study were divided into one-way segments by the direction of flow, and time of day was differentiated and controlled for. In terms of data collection, traditional fixed-based methods have been widely used in previous studies, but they fail to capture the spatio-temporal distributions of speed along a road. A new approach is introduced to estimate speed variation by integrating spatio-temporal speed fluctuation of a single vehicle with speed differences between vehicles using taxi-based high frequency GPS data. With this approach, this paper aims to comprehensively establish a relationship between mean speed, speed variation and traffic crashes for the purpose of formulating effective speed management measures, specifically using an urban dataset. From a total of 234 one-way road segments from eight arterials in Shanghai, mean speed, speed variation, geometric design features, traffic volume, and crash data were collected. Because the safety effects of mean speed and speed variation may vary at different segment lengths, arterials with similar signal spacing density were grouped together. To account for potential correlations among these segments, a hierarchical Poisson log-normal model with random effects was developed. Results show that a 1% increase in mean speed on urban arterials was associated with a 0.7% increase in total crashes, and larger speed variation was also associated with increased crash frequency

Perovskite quantum dot solar cells fabricated from recycled lead-acid battery waste

This document is the Accepted Manuscript version of a Published Work that appeared in final form in ACS Materials Letters, copyright © 2021 American Chemical Societ, after peer review and technical editing by the publisher. To access the final edited and published work see https://doi.org/10.1021/acsmaterialslett.1c00592.A cost-effective and environmentally friendly Pb source is a prerequisite for achieving large-scale, low-cost perovskite photovoltaic devices. Currently, the commonly used method to prepare the lead source is based on a fire smelting process, requiring a high temperature of more than 1000 °C, which results in environmental pollution. Spent car lead acid batteries are an environmentally hazardous waste; however, they can alternatively serve as an abundant and inexpensive Pb source. Due to “self-purification”, quantum dots feature a high tolerance of impurities in the precursor since the impurities tend to be expelled from the small crystalline cores during colloidal nucleation. Herein, PbI2 recycled from spent lead acid batteries via a facile low-temperature solution process is used to synthesize CsPbI3 quantum dots, which simultaneously brings multiple benefits including (1) avoiding pollution originating from the fire smelting process; (2) recycling the Pb waste from batteries; and (3) synthesizing high-quality quantum dots. The resulting CsPbI3 quantum dots have photophysical properties such as PLQY and carrier lifetimes on par with those synthesized from the commercial PbI2 due to expelling of the impurity Na atoms. The resulting solar cells deliver comparable power conversion efficiencies: 14.0% for the cells fabricated using recycled PbI2 and 14.7% for the cells constructed using commercial PbI2. This work paves a new and feasible path to applying recycled Pb sources in perovskite photovoltaics.Peer ReviewedPostprint (author's final draft

Developing Anisotropy In Self-Assembled Block Copolymers: Methods, Properties, and Applications

Block copolymers (BCPs) self-assembly has continually attracted interest as a means to provide bottom-up control over nanostructures. While various methods have been demonstrated for efficiently ordering BCP nanodomains, most of them do not generically afford control of nanostructural orientation. For many applications of BCPs, such as energy storage, microelectronics, and separation membranes, alignment of nanodomains is a key requirement for enabling their practical use or enhancing materials performance. This review focuses on summarizing research progress on the development of anisotropy in BCP systems, covering a variety of topics from established aligning techniques, resultant material properties, and the associated applications. Specifically, the significance of aligning nanostructures and the anisotropic properties of BCPs is discussed and highlighted by demonstrating a few promising applications. Finally, the challenges and outlook are presented to further implement aligned BCPs into practical nanotechnological applications, where exciting opportunities exist

Design of Valve Seating Buffer for Electromagnetic Variable Valve System

An electromagnetic variable valve (EMVV) system can significantly reduce pumping loss and discharge loss of the engine by enabling variable valve timing and variable valve lift. However, the valve seat easily produces a larger impact collision with the engine cylinder head because of fast valve seating velocity, greatly decreasing engine life. Therefore, in this paper, a valve seating buffer (VSB) is designed to solve the problem of large electromagnetic valve seating impact. Firstly, a scheme of an EMVV system with embedded buffer is proposed, the collision model is established to resolve the problem of the soft landing of the valve and the effectiveness of the model is verified by experiment. In addition, the structure, material and dimension parameters of the proposed buffer are designed, and some key parameters of the buffer are optimized by the Nelder–Mead (N–M) algorithm. Finally, a co-simulation model of the actuator and the buffer is built, and the valve seating performance is analyzed. The co-simulation results show that the valve seating velocity and rebound height of the EMVV system with the designed buffer are reduced by 94.8% and 97%, respectively, which verifies the advantages of the designed VSB

An immune and epigenetics-related scoring model and drug candidate prediction for hepatic carcinogenesis via dynamic network biomarker analysis and connectivity mapping

Hepatocellular carcinoma (HCC) is a malignant tumor with high mortality. This study aimed to build a prognostic signature for HCC patients based on immune-related genes (IRGs) and epigenetics-related genes (EPGs). RNA-seq data from Gene Expression Omnibus were used for dynamic network biomarker (DNB) analysis to identify 56 candidate IRG–EPG–DNBs and their first-neighbor genes. These genes were screened using LASSO-Cox regression analysis to finally obtain five candidate genes—RNF2, YBX1, EZH2, CAD, and PSMD1—which constituted the prognostic signature panel. According to this panel, patients in The Cancer Genome Atlas and International Cancer Genome Consortium were divided into high- and low-risk groups. The prognosis, clinicopathological features, and immune cell infiltration significantly differed between the two risk groups. The prognostic ability of the signature panel and expression profiling were further validated using online databases. We used an independent cohort of patients to validate the expression profiles of the five genes using reverse transcription–PCR. CMap and CellMiner predicted four small molecule drug–protein pairs based on the five prognostic genes. Of them, two market drugs approved by the Food and Drug Administration (AT-13387 and KU-55933) have emerged as candidates for HCC study. This new signature panel may serve as a potential prognostic marker, engendering the possibility of novel personalized therapy with classification of HCC patients

‘One-pot’ Synthesis of Dihydrobenzo[4,5][1,3]oxazino[2,3-a] isoquinolines via a Silver(I)-Catalyzed Cascade Approach

An efficient approach for the synthesis of biologically interesting fused tetracyclic isoquinolines in high yields and with a broad substrate scope has been developed. The strategy features an AgNO3 catalyzed ‘one-pot’ cascade process involving formation of two new C–N bonds and one new C–O bond