Improved Multi-Population Differential Evolution for Large-Scale Global Optimization

Differential evolution (DE) is an efficient population-based search algorithm with good robustness, however, it is challenged to deal with high-dimensional problems. In this paper, we propose an improved multi-population differential evolution with best-and-current mutation strategy (mDE-bcM). The population is divided into three subpopulations based on the fitness values, each of subpopulations uses different mutation strategy. After crossover, mutation and selection, all subpopulations are updated based on the new fitness values of their individuals. An improved mutation strategy is proposed, which uses a new approach to generate base vector that is composed of the best individual and current individual. The performance of mDE-bcM is evaluated on a set of 19 large-scale continuous optimization problems, a comparative study is carried out with other state-of-the-art optimization techniques. The results show that mDE-bcM has a competitive performance compared to the contestant algorithms and better efficiency for large-scale optimization problems

Graph Pre-training for AMR Parsing and Generation

Abstract meaning representation (AMR) highlights the core semantic information of text in a graph structure. Recently, pre-trained language models (PLMs) have advanced tasks of AMR parsing and AMR-to-text generation, respectively. However, PLMs are typically pre-trained on textual data, thus are sub-optimal for modeling structural knowledge. To this end, we investigate graph self-supervised training to improve the structure awareness of PLMs over AMR graphs. In particular, we introduce two graph auto-encoding strategies for graph-to-graph pre-training and four tasks to integrate text and graph information during pre-training. We further design a unified framework to bridge the gap between pre-training and fine-tuning tasks. Experiments on both AMR parsing and AMR-to-text generation show the superiority of our model. To our knowledge, we are the first to consider pre-training on semantic graphs.Comment: ACL2022 camera-ready final versio

Constituency Parsing using LLMs

Constituency parsing is a fundamental yet unsolved natural language processing task. In this paper, we explore the potential of recent large language models (LLMs) that have exhibited remarkable performance across various domains and tasks to tackle this task. We employ three linearization strategies to transform output trees into symbol sequences, such that LLMs can solve constituency parsing by generating linearized trees. We conduct experiments using a diverse range of LLMs, including ChatGPT, GPT-4, OPT, LLaMA, and Alpaca, comparing their performance against the state-of-the-art constituency parsers. Our experiments encompass zero-shot, few-shot, and full-training learning settings, and we evaluate the models on one in-domain and five out-of-domain test datasets. Our findings reveal insights into LLMs' performance, generalization abilities, and challenges in constituency parsing

Thermal management performances of PCM/water cooling-plate using for lithium-ion battery module based on non-uniform internal heat source

In order to improve the working performance of the lithium-ion battery, the battery module with Phase change material/water cooling-plate was designed and numerically analyzed based on the energy conservation and fluid dynamics. The non-uniform internal heat source based on 2D electro-thermal model for battery LiFePO4/C was used to simulate the heat generation of each battery. Then factors such as height of water cooling-plate, space between adjacent batteries, inlet mass flow rate, flow direction, thermal conductivity and melting point of PCM were discussed to research their influences on the cooling performance of module. And the 5 continuous charge-discharge cycles was used to research the effect of PCM/water cooling plate on preventing thermal runaway. The results showed that the water cooling plate set close to the near-electrode area of battery removed the majority of heat generated during discharging and decreased the maximum temperature efficiently. The PCM between the adjacent batteries could improve the uniformity of temperature field. In addition, the PCM/water cooling plate could limit the maximum temperature effectively and improve the uniformity of temperature field during the 5 continuous charge-discharge cycles. As a result, it prevented the emergence of thermal runaway and increased the safety of module. (C) 2017 Elsevier Ltd. All rights reserved

Effect of expression levels of multidrug resistance gene related protein 1, P-glycoprotein and topoisomerase II on paclitaxel, gemcitabine and vinorelbine sensitivity in pulmonary cancer

Purpose: To investigate the possible correlation between drug resistance gene expression and development of drug sensitivity, and the possible clinical significance of this relationship. Methods: A total of 100 cancer samples were surgically obtained. MTT assay was employed to determine drug sensitivity. The expression levels of drug resistance genes, multidrug resistance generelated protein 1 (MRP1), P-glycoprotein (P-gp), and topoisomerase II (Topo II) were measured by immunohistochemistry. Results: The expression levels of MRP1, P-gp, and Topo II genes in lung cancer were 70.0, 65.0, and 50.0 %, respectively. No significant statistical differences were observed in the expressions of MRP1, Pgp, and Topo II between human adenocarcinoma and squamous cell carcinoma (p > 0.05), but a significant difference was found in MRP1 and Topo II expressions between human adenocarcinoma or squamous carcinoma cell and small-cell lung cancer (p < 0.05). A significant positive correlation was observed between P-gp expression and resistance cisplatin, gemcitabine, vinorelbine, and paclitaxel (p < 0.05). A significant positive correlation was also found between MRP1 expression and the development of resistance to cisplatin, gemcitabine, and vinorelbine (p < 0.05), but no significant correlation was observed between MRP1 expression and the development of resistance to paclitaxel and ifosfamide (p > 0.05). Conclusion: The up-regulated expression of MRP1 and P-gp, and the down-regulated expression of Topo II may be positively correlated with drug resistance in lung cancer patients. Thus, gene tests are recommended to guide the administration of chemotherap

Investigation of thermal management for lithium-ion pouch battery module based on phase change slurry and mini channel cooling plate

In this paper, the thermal management based on phase change slurry (PCS) and mini channel cooling plate for the lithium-ion pouch battery module was proposed. The three-dimensional thermal model was established and the optimum structure of the cooling plate with mini channel was designed with the orthogonal matrix experimental method to balance the cooling performance and energy consumption. The simulation results showed that the cooling performance of PCS consisting of 20% n-octadecane microcapsules and 80% water was better than that of pure water, glycol solution and mineral oil, when the mass flow rate was less than 3 x 10(-4) kg s(-1). For different concentrations of PCS, if the mass flow rate exceeded the critical value, its cooling performance was worse than that of pure water. When the cooling target for battery maximum temperature was higher than 309 K, the PCS cooling with appropriate microcapsule concentration had the edge over in energy consumption compared with water cooling. At last, the dimensionless empirical formula was obtained to predict the effect of the PCS's physical parameters and flow characteristics on the heat transfer and cooling performance. The simulation results will be useful for the design of PCS based battery thermal management systems. (C) 2018 Elsevier Ltd. All rights reserved

China's low-emission pathways toward climate-neutral livestock production for animal-derived foods

Funding Information: This research was supported by the National Natural Science Foundation of China (Grant No. 31922080 and 31872403 ), China Agriculture Research System of MOF and MARA and the Hunan province science and technology plan (Grant No. 2022NK2021 ).Peer reviewedPublisher PD

Effects of Physical Synergistic Enzymatic Treatment on Structural Characteristics of Highland Barley Starch

In order to study the effect of physical synergistic enzymatic treatment on the structural characteristics of highland barley starch, ultrasonic and pressure heat were combined with pullulanase to treat highland barley starch. The particle morphology, crystal structure, functional group structure and particle size of treated samples were determined. The results showed that the contents of resistant starch and amylose were increased while amylopectin was decreased. The original structure of starch granules of highland barley was seriously damaged by the modification, showing a clumped structure, rough surface, full of wrinkles, cracks and holes, and the polarized cross disappeared. It was also found that the average particles size of highland barley starch and the number of large particles increased. Meanwhile, the crystallinity of highland barley starch changed from A-type crystal to B-, C- and V-type which lead to the crystallinity increased. The modified treatment did not produce new chemical groups and chemical bonds, but changed the internal structure of barley starch rearrangement. In addition, compared to untreated, the order degree (DO) of the modified barley starch increased, and the value of DO treated with pullulanase was the largest. The modification treatment made the starch molecules into smaller particles then formed more denser and larger starch crystals