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Surrogate-assisted evolutionary algorithms have been widely developed to solve complex and computationally expensive multi-objective optimization problems in recent years. However, when dealing with high-dimensional optimization problems, the performance of these surrogate-assisted multi-objective evolutionary algorithms deteriorate drastically. In this work, a novel Classifier-assisted rank-based learning and Local Model based multi-objective Evolutionary Algorithm (CLMEA) is proposed for high-dimensional expensive multi-objective optimization problems. The proposed algorithm consists of three parts: classifier-assisted rank-based learning, hypervolume-based non-dominated search, and local search in the relatively sparse objective space. Specifically, a probabilistic neural network is built as classifier to divide the offspring into a number of ranks. The offspring in different ranks uses rank-based learning strategy to generate more promising and informative candidates for real function evaluations. Then, radial basis function networks are built as surrogates to approximate the objective functions. After searching non-dominated solutions assisted by the surrogate model, the candidates with higher hypervolume improvement are selected for real evaluations. Subsequently, in order to maintain the diversity of solutions, the most uncertain sample point from the non-dominated solutions measured by the crowding distance is selected as the guided parent to further infill in the uncertain region of the front. The experimental results of benchmark problems and a real-world application on geothermal reservoir heat extraction optimization demonstrate that the proposed algorithm shows superior performance compared with the state-of-the-art surrogate-assisted multi-objective evolutionary algorithms. The source code for this work is available at https://github.com/JellyChen7/CLMEA.

Sequential transfer optimization (STO), which aims to improve optimization performance by exploiting knowledge captured from previously-solved optimization tasks stored in a database, has been gaining increasing research attention in recent years. However, despite significant advancements in algorithm design, the test problems in STO are not well designed. Oftentimes, they are either randomly assembled by other benchmark functions that have identical optima or are generated from practical problems that exhibit limited variations. The relationships between the optimal solutions of source and target tasks in these problems are manually configured and thus monotonous, limiting their ability to represent the diverse relationships of real-world problems. Consequently, the promising results achieved by many algorithms on these problems are highly biased and difficult to be generalized to other problems. In light of this, we first introduce a few rudimentary concepts for characterizing STO problems (STOPs) and present an important problem feature overlooked in previous studies, namely similarity distribution, which quantitatively delineates the relationship between the optima of source and target tasks. Then, we propose general design guidelines and a problem generator with superior extendibility. Specifically, the similarity distribution of a problem can be systematically customized by modifying a parameterized density function, enabling a broad spectrum of representation for the diverse similarity relationships of real-world problems. Lastly, a benchmark suite with 12 individual STOPs is developed using the proposed generator, which can serve as an arena for comparing different STO algorithms. The source code of the benchmark suite is available at https://github.com/XmingHsueh/STOP.

OBJECTIVE: To study the effects and mechanism of Shenqihuatan formula (参七化痰方, SQHT) of the transforming growth factor-beta (TGF-β)-stimulated cell processes in airway remodeling. METHODS: The current study examined cell viability using a Cell Counting Kit-8 assay. Furthermore, a Transwell assay was conducted to detect the ability of cell migration, and apoptosis was detected via flowcytometry. Western Blot and quantitative real-time polymerase chain reaction (qRT-PCR) were used to determine the expression levels of apoptosis or inflammation-related factors, such as TGF-β, Interleukin-1β (IL-1β), B cell lymphoma 2 (Bcl-2), Bcl-2-Associated X (Bax), Ras homolog gene family, member A (RhoA), recombinant rho associated coiled coil containing protein kinase 1/2 (ROCK1/2), extracellular regulated protein kinases 1/2 (ERK1/2), Snail, and Slug. Finally, the expression levels of matrix metalloproteinase-9 (MMP-9) and Tissue inhibitor of metalloproteinase (TIMP-1) were admeasured by enzyme-linked immuno sorbent assay. RESULTS: The results demonstrated that SQHT inhibited the viability and migration, as well as the the F-actin formation and cytoskeletal reorganization of airway smooth muscle cells (ASMCs) stimulated by TGF-β. By monitoring the changes of critical regulators in the presence of the formula, it was observed that the expression levels of TGF-β, IL-1β, Bcl-2, RhoA, ROCK1/2, ERK1/2, Snail, and Slug were markedly suppressed, whereas Bax expression exhibited the opposite effect. Compared with a well-characterized RhoA pathway inhibitor, Fasudil, SQHT generated equivalent or even higher inhibitory effects on these processes in ASMCs. CONCLUSION: Collectively, these suggested that SQHT can reduce airway inflammation by inhibiting TGF-β-stimulated signaling pathways in ASMCs. These findings may provide a novel remedy for treating ASMC inflammation, which causes thickening and obstruction of the airway in chronic obstructive pulmonary disease.

The Black Drongo (Dicrurus macrocercus) is an important beneficial bird widespread in China and other Asian countries. In this study, a complete mitochondrial genome of D. macrocercus has been obtained by polymerase chain reaction method for the first time. This circular molecule is 17,017 bp in length with A + T contents of 56.9% and contains 2 rRNA genes, 13 protein-coding genes, and 22 tRNA genes. Phylogenetic analysis shows that D. macrocercus is genetically closest to D. hottentottus.

The wedge-tailed green pigeon (Treron sphenurus) has a protective value in the evolution of the family Columbidae. In this study, the complete mitogenome of T. sphenurus from Baise City, China, which represents the first sequenced species of the genus Treron in Tribe Treronini, is reported. This was accomplished using PCR-based methods and a primer-walking sequencing strategy with genus-specific primers. The mitogenome was found to be 18,919 bp in length comprising 37 genes, including 13 protein-coding genes, two rRNA genes, 22 tRNA genes, and one control region. In terms of structure and composition, many similarities were found between the T. sphenurus and Hemiphaga novaeseelandiae (New Zealand pigeon) mitogenomes. This was further supported by phylogenetic analysis showing that T. sphenurus has a close evolutionary relationship with H. novaeseelandiae. The complete mitogenome of T. sphenurus reported here is expected to provide valuable molecular information for further studies on the phylogeny of the genus Treron and for analyses of the taxonomic status of the family Columbidae.

In this paper, we reported the complete mitogenome of Erythrura gouldiae. E. gouldiae mitogenome is 16,830bp base pairs long. The overall base compositions of complete mitogenomes of E. gouldiae is...

The application of wind power interval prediction for power systems attempts to give more comprehensive support to dispatchers and operators of the grid. Lower upper bound estimation (LUBE) method is widely applied in interval prediction. However, the existing LUBE approaches are trained by meta-heuristic optimization, which is either time-consuming or show poor effect when the LUBE model is complex. In this paper, a deep interval prediction method is designed in the framework of LUBE and an efficient gradient descend (GD) training approach is proposed to train the LUBE model. In this method, the long short-term memory is selected as a representative to show the modelling approach. The architecture of the proposed model consists of three parts, namely the long short-term memory module, the fully connected layers and the rank ordered module. Two loss functions are specially designed for implementing the GD training method based on the root mean square back propagation algorithm. To verify the performance of the proposed model, conventional LUBE models, as well as popular statistic interval prediction models are compared in numerical experiments. The results show that the proposed approach performs best in terms of effectiveness and efficiency with average 45% promotion in quality of prediction interval and 66% reduction of time consumptions compared to traditional LUBE models., Comment: 24 pages

Plant material evidence inspection is Mahonia bealei (Fort.) Carr., Mahonia fortunei (Lindl.) and Mahonia bodinieri Gagnep. are three common medicinal plants commonly found in Mahonia. In this study, gas chromatography-mass spectrometry (GC-MS) was used to compare the chemical constituents of stems and leaves of these three plants. The results showed that 6 of the volatile oils of the three plant species contained the same chemical composition, which was neophytadiene, palmitic acid, n-dodecane, octacosane, erucamide, and vitamin E oil, but the percentage content was difference. The main components of the volatile oils of the three plant stems were different. Erucamide was only detected in Mahonia fortunei (Lindl.) Fedde, oleic acid amide only detected in Mahonia bealei (Fort.) Carr. , and oxidized cyclooctene , and four compounds such as triphenylphosphine oxide was detected in Mahonia bodinieri Gagnep. ..

Through morphological anatomy, viability measurement, seed germination and seedling growth observation, it was found that there was a ring band structure between the brown seed coat and embryo of Cerasusdiscoidea, which was the residual endosperm of Cerasus, and the seeds of Cerasus are composed of seed coat, remaining endosperm and embryo. The remaining endosperm consists of two parts: the endosperm sheath and the endosperm ring. Remaining endosperm is beneficial to the maintenance of seeds viability and the protection of seeds embryo germination and growth.

In this study, 25 flower samples of Parrotia subaequalis individuals were collected in Dalonggou of Yixing, Jiangsu. ISSR markers were used to analyze the genetic diversity of the 25 individuals. Six primers were selected and used for PCR amplification. The result showed that 59 discernible DNA fragments were amplified, among them 47 are polymorphic loci and the percentage of polymorphic loci (PPB) is 79.7%. By analysis with POPGENE32, the effective number of alleles (Ne) is 1.4697, Nei's gene diversity (H) is 0.2792, Shannon's Information index (I) is 0.4195, the Ewens-Watterson Neutral value is between 0.02 to 1, and more than half of the neutral test values are above 0.5. Through cluster analysis with NTSYSpc-2.1, genetic similarity coefficients of 25 samples are between 0.25 and 1 with an average of 0.71. From the results of this study we can get a conclusion that the genetic differences among the wild populations of P. subaequalis in Dalonggou of Yixing, Jiangsu were large and rich in diversity. The aim of this study is to reveal the genetic diversity of wild population of P. subaequalis from molecular level and provide a theoretical basis for the protection of this rare and endangered plant.

Lancang county, Yunnan Province is located in the southwestern border of Yunnan Province, , China and has abundant forest resources. At the same time, there are many cases of illegal logging and deforestation in Lancang county. In the county, the cases of illegal logging and deforestation of Pinus kesiya were mainly carried out by rural personnel, the single-person case was converted into a form of gang, the remoteness of the crime site makes it difficult to find and investigate, especially in most of the rural collective forests, etc. The main reasons for its occurrence are: the general public’s lack of legal awareness and economic poverty. A series of preventive measures and strike strategies, such as perfecting the system of recruiting personnel and intensifying the crackdown on such cases, were proposed to provide theoretical support for the protection and development of Pinus kesiya resources Lancang County.

In this paper, the habitat of Cerasus clarofolia was investigated and analysed, under natural conditions the growth of Cerasus clarofolia is influenced by low temperature of winter. The seeds of Cerasus clarofolia need low-temperature to germination. The seedling with 4 leaves grew well after introduction, the survival rate reached 79.7%. Planting with clear water was found easier to take roots, the roots were come from the lenticels, under diffent environmental conditions, the lenticels formed morphological, physiological differences are the important factors take roots for Cerasus.