An ant colony optimization method for generalized TSP problem

Focused on a variation of the euclidean traveling salesman problem (TSP), namely, the generalized traveling salesman problem (GTSP), this paper extends the ant colony optimization method from TSP to this field. By considering the group influence, an improved method is further improved. To avoid locking into local minima, a mutation process and a local searching technique are also introduced into this method. Numerical results show that the proposed method can deal with the GTSP problems fairly well, and the developed mutation process and local search technique are effective

Multilayer perceptron network optimization for chaotic time series modeling

Chaotic time series are widely present in practice, but due to their characteristics—such as internal randomness, nonlinearity, and long-term unpredictability—it is difficult to achieve high-precision intermediate or long-term predictions. Multi-layer perceptron (MLP) networks are an effective tool for chaotic time series modeling. Focusing on chaotic time series modeling, this paper presents a generalized degree of freedom approximation method of MLP. We then obtain its Akachi information criterion, which is designed as the loss function for training, hence developing an overall framework for chaotic time series analysis, including phase space reconstruction, model training, and model selection. To verify the effectiveness of the proposed method, it is applied to two artificial chaotic time series and two real-world chaotic time series. The numerical results show that the proposed optimized method is effective to obtain the best model from a group of candidates. Moreover, the optimized models perform very well in multi-step prediction tasks.This research was funded in part by the NSFC grant numbers 61972174 and 62272192, the Science-Technology Development Plan Project of Jilin Province grant number 20210201080GX, the Jilin Province Development and Reform Commission grant number 2021C044-1, the Guangdong Universities’ Innovation Team grant number 2021KCXTD015, and Key Disciplines Projects grant number 2021ZDJS138

Relations of stellar mass between electron temperature-based metallicity of star-forming galaxies in a wide mass range

We select 947 star-forming galaxies from SDSS-DR7 with [O~{\sc iii}]$\lambda$4363 emission lines detected at a signal-to-noise {ratio }larger than 5$\sigma$. Their electron temperatures and direct oxygen abundances are {then }determined. {W}e compare the results from different methods. $t_2${, the} electron temperature in {the }low ionization region{,} estimated from $t_3${, that} in {the }high ionization region{,} {is} compared {using} three analysis relations between $t_2-t_3${. These} show obvious differences, which result in some different ionic oxygen abundances. The results of $t_3$, $t_2$, {$\rm O^{++}$/$\rm H^+$} and {$\rm O^{+}$/$\rm H^+$} derived by using methods from IRAF and literature are also compared. The ionic abundances $\rm O^{++}$/$\rm H^+$ {are} higher than $\rm O^{+}$/$\rm H^+$ for most cases. The{ different} oxygen abundances derived from $T_{\rm e}$ and the strong-line ratios show {a }clear discrepancy, which is more obvious following increasing stellar mass and strong-line ratio $R_{23}$. The sample{ of} galaxies from SDSS {with} detected [O~{\sc iii}]$\lambda$4363 have lower metallicites and higher {star formation rates}, {so} they may not be typical representatives of the whole{ population of} galaxies. Adopting data objects from {Andrews \& Martini}, {Liang et al.} and {Lee et al.} data, we derive new relations of stellar mass and metallicity for star-forming galaxies in a much wider stellar mass range: from $10^6\,M_\odot$ to $10^{11}\,M_\odot$.Comment: 16 pages, 11 figures, Accepted by Research in Astronomy and Astrophysic

Pressure-induced melting of magnetic order and emergence of new quantum state in alpha-RuCl3

Here we report the observation of pressure-induced melting of antiferromagnetic (AFM) order and emergence of a new quantum state in the honeycomb-lattice halide alpha-RuCl3, a candidate compound in the proximity of quantum spin liquid state. Our high-pressure heat capacity measurements demonstrate that the AFM order smoothly melts away at a critical pressure (Pc) of 0.7 GPa. Intriguingly, the AFM transition temperature displays an increase upon applying pressure below the Pc, in stark contrast to usual phase diagrams, for example in pressurized parent compounds of unconventional superconductors. Furthermore, in the high-pressure phase an unusual steady of magnetoresistance is observed. These observations suggest that the high-pressure phase is in an exotic gapped quantum state which is robust against pressure up to ~140 GPa.Comment: 20 pages, 4 figure

Link Prediction Based on Extended Local Path Gain in Protein-Protein Interaction Network

Protein–protein interaction (PPI) plays key role in each cellular process of any living cell, however, almost all organisms’ PPIs are still incomplete. In this study, we firstly proposed a computational method Extended Local Path (ELP), which estimated links’ existence likelihood by integrating all their neighbours’ local paths in the network. In addition, on this basis, we extended it to Extended Local Path Gain (ELPG), which estimated gain effect when adding or deleting one potential link to the network. Applying both ELPG and ELP methods and other four recognized outstanding methods on four public PPI data of Yeast, E. coli, Fruit fly and Mouse, we demonstrated that ELPG and ELP obtained better performance under two standard measures: area under curve (AUC) and Precision. Besides, ELP and ELPG were identified as the best features for classifying existing and unknown links by using support vector machine-recursive feature elimination (SVM-RFE) for feature selection

QTL analysis for yield-related traits under different water regimes in maize

Drought is one of the most essential factors influencing maize yield. Improving maize varieties with drought tolerance by using marker-assisted or genomic selection requires more understanding of the genetic basis of yield-related traits under different water regimes. In the present study, 213 F2:3 families of the cross of H082183 (drought-tolerant) × Lv28 (drought susceptible) were phenotyped with five yield-related traits under four well-watered and six drought environments for two years. Quantitative trait loci analysis identified 133 significant QTLs (94 QTLs for ear traits and 39 QTLs for kernel traits) based on single environment analysis. The joint-environment analysis detected 25 QTLs under well-watered environments (eight QTLs for ear length, eight for ear diameter, one for ear weight, two for kernel weight per ear, and six for 100-kernel weight), and nine QTLs under water-stressed environments (two QTLs for ear length, three for ear diameter, one for ear weight, one for kernel weight, and two for 100-kernel weight). Among these joint-environment QTLs, one common QTL (qEL5) was stably identified at both of the water regimes. Meanwhile, two main-effect QTLs were detected in the well-watered environments, i.e. qEL10 for ear length and qHKW2 for 100-kernel weight. Also, qED8, qEW8, and qKW8 were found to be located in the same interval of Chr. 8. Similarly, qEL4s and qKW4s were found to be located in the same interval under water-stressed environments. These genomic regions could be candidate targets for further fine mapping and marker-assisted breeding in maize