A Method of Gene-Function Annotation Based on Variable Precision Rough Sets

It is very important in the field of bioinformatics to apply computer to perform the function annotation for new sequenced bio-sequences. Based on GO database and BLAST program, a novel method for the function annotation of new biological sequences is presented by using the variable-precision rough set theory. The proposed method is applied to the real data in GO database to examine its effectiveness. Numerical results show that the proposed method has better precision, recall-rate and harmonic mean value compared with existing methods.

Clonal Selection Based Memetic Algorithm for Job Shop Scheduling Problems

A clonal selection based memetic algorithm is proposed for solving job shop scheduling problems in this paper. In the proposed algorithm, the clonal selection and the local search mechanism are designed to enhance exploration and exploitation. In the clonal selection mechanism, clonal selection, hypermutation and receptor edit theories are presented to construct an evolutionary searching mechanism which is used for exploration. In the local search mechanism, a simulated annealing local search algorithm based on Nowicki and Smutnicki＇s neighborhood is presented to exploit local optima. The proposed algorithm is examined using some well-known benchmark problems. Numerical results validate the effectiveness of the proposed algorithm.

The local properties of supernova explosions and their host galaxies

We aim to understand the properties at the locations of supernova(SN) explosions in their host galaxies and compare with the global properties of these host galaxies. We use the integral field spectrograph(IFS) of Mapping Nearby Galaxies at Apache Point Observatory(MaNGA) to generate 2 D maps of the parameter properties for 11 SN host galaxies. The sample galaxies are analyzed one by one in detail in terms of their properties of velocity field, star formation rate, oxygen abundance, stellar mass, etc.This sample of SN host galaxies has redshifts around z^0.03, which is higher than those of previous related works. The higher redshift distribution allows us to obtain the properties of more distant SN host galaxies. Metallicity(gas-phase oxygen abundance) estimated from integrated spectra can represent the local metallicity at SN explosion sites with small bias. All the host galaxies in our sample are metal-rich galaxies(12+log(O/H)> 8.5) except for NGC 6387, which means SNe may be more inclined to explode in metallicity-rich galaxies. There is a positive relation between global gas-phase oxygen abundance and the stellar mass of host galaxies. We also try to compare the differences of the host galaxies between SNe Ia and SNe II. In our sample, both SNe Ia and SNe II can explode in normal galaxies, but SNe II can also explode in an interacting or a merging system, in which star formation is occurring in the galaxy.

Automatic determination of stellar atmospheric parameters and construction of stellar spectral templates of the Guoshoujing Telescope (LAMOST)

A number of spectroscopic surveys have been carried out or are planned to study the origin of the Milky Way. Their exploitation requires reliable automated methods and softwares to measure the fundamental parameters of the stars. Adopting the ULySS package, we have tested the effect of different resolutions and signal-to- noise ratios （SNR） on the measurement of the stellar atmospheric parameters （effective temperature Teff, surface gravity log g, and metaUicity [Fe/H]）. We show that ULySS is reliable for determining these parameters with medium-resolution spectra （R ～2000）. Then, we applied the method to measure the parameters of 771 stars selected in the commissioning database of the Guoshoujing Telescope （LAMOST）. The results were compared with the SDSS/SEGUE Stellar Parameter Pipeline （SSPP）, and we derived precisions of 167 K, 0.34dex, and 0.16dex for Teff, logg and [Fe/H] respectively. Furthermore, 120 of these stars are selected to construct the primary stellar spectral template library （Version 1.0） of LAMOST, and will be deployed as basic ingredients for the LAMOST automated parametrization pipeline.

Multiwavelength study of nearly face-on low surface brightness disk galaxies

We study the ages of a large sample （1802） of nearly face-on disk low surface brightness galaxies （LSBGs） using the evolutionary population synthesis （EPS） model PEGASE with an exponentially decreasing star formation rate to fit their mul- tiwavelength spectral energy distributions （SEDs） from far-ultraviolet （FUV） to nearinfrared （NIR）. The derived ages of LSBGs are 1-5 Gyr for most of the sample no matter if constant or varying dust extinction is adopted, which are similar to most of the previous studies on smaller samples. This means that these LSBGs formed the majority of their stars quite recently. However, a small part of the sample （~2%-3%） has larger ages of 5-8 Gyr, meaning their major star forming process may have occurred earlier. At the same time, a large sample （5886） of high surface brightness galaxies （HSBGs） are selected and studied using the same method for comparisons. The de- rived ages are 1-5 Gyr for most of the sample （97%） as well. These results probably mean that these LSBGs have not much different star formation histories from their HSBGs counterparts. However, we should notice that the HSBGs are generally about 0.2 Gyr younger, which could mean that the HSBGs may have undergone more recent star forming activities than the LSBGs.

Stellar Abundance and Galactic Chemical Evolution through LAMOST Spectroscopic Survey

A project of a spectroscopic survey of Galactic structure and evolution with a Large sky Area Multi-Object fiber Spectroscopic Telescope （LAMOST） is presented. The spectroscopic survey consists of two observational modes for various targets in our Galaxy. One is a major survey of the Milky Way aimed at a systematic study of the stellar abundance and Galactic chemical evolution through low resolution （R = 1000 2000） spectroscopy. Another is a follow-up observation with medium resolution （R = 10000） spectrographs aimed at detailed studies of the selected stars with different chemical composition, kinematics and dynamics.

The properties of a large volume-limited sample of face-on low surface brightness disk galaxies

We select a large volume-limited sample of low surface brightness galax- ies （LSBGs, 2021） to investigate in detail their statistical properties and their dif- ferences from high surface brightness galaxies （HSBGs, 3639）. The distributions of stellar masses of LSBGs and HSBGs are nearly the same and they have the same me- dian values. Thus this volume-limited sample has good completeness and is further removed from the effect of stellar masses on their other properties when we compare LSBGs to HSBGs. We found that LSBGs tend to have lower stellar metallicities and lower effective dust attenuations, indicating that they have lower dust than HSBGs. The LSBGs have relatively higher stellar mass-to-light ratios, higher gas fractions, lower star forming rates （SFRs）, and lower specific SFRs than HSBGs. Moreover, with the decreasing surface brightness, gas fraction increases, but the SFRs and spe- cific SFRs decrease rapidly for the sample galaxies. This could mean that the star formation histories between LSBGs and HSBGs are different, and HSBGs may have stronger star forming activities than LSBGs.

Systems biology in the frontier of cancer research: a report of the Second International Workshop of Cancer Systems Biology

The report summarizes the Second International Workshop of Cancer Systems Biology held on July 5-6, 2012 in Changchun, China. The goal of the workshop was to bring together cancer researchers with different backgrounds to share their views about cancer and their experiences in fighting against cancer, and to gain new and systems-level understanding about cancer formation, progression, diagnosis, and treatment through exchanging ideas.

The local and global properties of different types of supernova host galaxies

By using Data Analysis Pipeline(DAP)products of Mapping Nearby Galaxies at Apache Point Observatory(MaNGA),which are publicly available from the SDSS Data Release 15,we analyze the local properties at the SN explosion sites and global properties of different types of SN host galaxies to explore the explosion environments of different types of SNe.In our sample,there are 67 SN host galaxies in the field of view of MaNGA,including 32 Type Ia,29 core collapse SNe(CCSNe),1 superluminous SN(SLSN),1 Type I and 4 unclassified type of SNe,with which we can apply the K-S test for analysis and derive statistically robust results.Due to the limited sample size,we could not remove the mass dependence in this work,which is likely the true driver of the trends for the properties presented in this work.The global star formation rate(SFR)and EW(H)for SN Ia hosts are slightly lower than those for CCSN hosts on average.SN Ia host galaxies are0.3 dex more massive than CCSN hosts,which implies that the number ratio of CCSNe to Type Ia SNe will decrease with increasing stellar mass of host galaxies.The stellar population age of SN Ia host galaxies is older than that of CCSN hosts on average.There is no significant difference between different types of SN hosts for some properties,including local SFR density(SFR),and local and global gas-phase oxygen abundance.For most galaxies in our sample,the global gas-phase oxygen abundance estimated from the integrated spectra of SN hosts can represent the local gas-phase oxygen abundance at the SN explosion sites with small bias.

Abundance analysis of Barium stars

We obtain the chemical abundances of six barium stars and two CH subgiant stars based on the high signal-to-noise ratio and high resolution EcheUe spectra. The neu-Iron capture process elements Y, Zr, Ba, La and Eu show obvious overabundances relative to the Sun, for example, their [Ba/Fe] values are from 0.45 to 1.27. Other elements, including Na, Mg, A1, Si, Ca, Sc, Ti, V, Cr, Mn and Ni, show comparable abundances to the Solar ones, and their [Fe/H] covers a range from -0.40 to 0.21, which means they belong to the Galactic disk. The predictions of the theoretical model of wind accretion for binary systems can explain the observed abundance patterns of the neutron capture process elements in these stars, which means that their overabundant heavy-elements could be caused by accreting the ejecta of AGB stars, the progenitors of present-day white dwarf companions in binary systems.

Feasibility study of emergency intervention for vascular injury outside the hospital

Background: Minimally invasive surgery in the field of traumatic vascular injury diagnosis and treatment has achieved good results. This study was designed to determine whether pre-hospital emergency intervention is feasible for vascular injury in a field intervention cabin under the condition of war or a disaster site.Methods: Different types of animal experiments of vascular injury intervention were performed in a field intervention cabin. Treatment capacity was evaluated by data collection, including duration of surgery, clinical evaluation, image clarity, and equipment handling. Environmental adaptability and mobility were evaluated by maneuverability and long-distance mobility.Results: A total of 56 surgeries(7 types) were performed in the field intervention cabin. Digital subtraction angiography(DSA) had good imaging performance. A total of 4800 km of long-distance mobility was performed, and all the equipment operated normally without any equipment failure. We participated in the medical service maneuver twice. The cabin unfolded and worked properly. There was no equipment damage during the medical service maneuver.Conclusion: Use of a field intervention cabin under the conditions of war or disaster is feasible for pre-hospital emergency intervention of vascular injury.

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

We select 947 star-forming galaxies from SDSS-DR7 with [O III]λ4363emission lines detected at a signal-to-noise ratio larger than 5σ. Their electron temperatures and direct oxygen abundances are then determined. We compare the results from different methods. t2, the electron temperature in the low ionization region, estimated from t3, that in the high ionization region, is compared using three analysis relations between t2- t3. These show obvious differences, which result in some different ionic oxygen abundances. The results of t3, t2, O＋＋/H＋and O＋/H＋derived by using methods from IRAF and literature are also compared. The ionic abundances O＋＋/H＋are higher than O＋/H＋for most cases. The different oxygen abundances derived from Teand the strong-line ratios show a clear discrepancy, which is more obvious following increasing stellar mass and strong-line ratio R23. The sample of galaxies from SDSS with detected [O III]λ4363 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 106 M to 1011 M.

Chemical abundance analysis of 19 barium stars

We aim at deriving accurate atmospheric parameters and chemical abundances of 19 barium（Ba） stars, including both strong and mild Ba stars, based on the high signal-to-noise ratio and high resolution Echelle spectra obtained from the 2.16 m telescope at Xinglong station of National Astronomical Observatories, Chinese Academy of Sciences. The chemical abundances of the sample stars were obtained from an LTE, plane-parallel and line-blanketed atmospheric model by inputting the atmospheric parameters（effective temperatures Teff, surface gravities log g, metallicity [Fe/H] and microturbulence velocity ξt） and equivalent widths of stellar absorption lines. These samples of Ba stars are giants as indicated by atmospheric parameters, metallicities and kinematic analysis about UVW velocity. Chemical abundances of 17 elements were obtained for these Ba stars. Their Na, Al, α- and iron-peak elements（O, Na, Mg, Al, Si, Ca,Sc, Ti, V, Cr, Mn, Ni） are similar to the solar abundances. Our samples of Ba stars show obvious overabundances of neutron-capture（n-capture） process elements relative to the Sun. Their median abundances of[Ba/Fe], [La/Fe] and [Eu/Fe] are 0.54, 0.65 and 0.40, respectively. The Y I and Zr I abundances are lower than Ba, La and Eu, but higher than the α- and iron-peak elements for the strong Ba stars and similar to the iron-peak elements for the mild stars. There exists a positive correlation between Ba intensity and [Ba/Fe].For the n-capture elements（Y, Zr, Ba, La）, there is an anti-correlation between their [X/Fe] and [Fe/H]. We identify nine of our sample stars as strong Ba stars with [Ba/Fe]〉0.6 where seven of them have Ba intensity Ba=2-5, one has Ba=1.5 and another one has Ba=1.0. The remaining ten stars are classified as mild Ba stars with 0.17〈[Ba/Fe]〈0.54.

DeepHBSP:A Deep Learning Framework for Predicting Human Blood-Secretory Proteins Using Transfer Learning

The identification of blood-secretory proteins and the detection of protein biomarkers in the blood have an important clinical application value.Existing methods for predicting blood-secretory proteins are mainly based on traditional machine learning algorithms,and heavily rely on annotated protein features.Unlike traditional machine learning algorithms,deep learning algorithms can automatically learn better feature representations from raw data,and are expected to be more promising to predict blood-secretory proteins.We present a novel deep learning model(DeepHBSP)combined with transfer learning by integrating a binary classification network and a ranking network to identify blood-secretory proteins from the amino acid sequence information alone.The loss function of DeepHBSP in the training step is designed to apply descriptive loss and compactness loss to the binary classification network and the ranking network,respectively.The feature extraction subnetwork of DeepHBSP is composed of a multi-lane capsule network.Additionally,transfer learning is used to train a highly accurate generalized model with small samples of blood-secretory proteins.The main contributions of this study are as follows:1)a novel deep learning architecture by integrating a binary classification network and a ranking network is proposed,superior to existing traditional machine learning algorithms and other state-of-the-art deep learning architectures for biological sequence analysis;2)the proposed model for blood-secretory protein prediction uses only amino acid sequences,overcoming the heavy dependence of existing methods on annotated protein features;3)the blood-secretory proteins predicted by our model are statistically significant compared with existing blood-based biomarkers of cancer.

AN IMPROVED BICLUSTERING ALGORITHM AND ITS APPLICATION TO GENE EXPRESSION SPECTRUM ANALYSIS

Cheng and Church algorithm is an important approach in biclustering algorithms. In this paper, the process of the extended space in the second stage of Cheng and Church algorithm is improved and the selections of two important parameters are discussed. The results of the improved algorithm used in the gene expression spectrum analysis show that, compared with Cheng and Church algorithm, the quality of clustering results is enhanced obviously, the mining expression models are better, and the data possess a strong consistency with fluctuation on the condition while the computational time does not increase significantly.