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The Zhangjiakou-Bohai fault zone (ZBFZ) is an important NW-trending active tectonic zone in North China. The western section of ZBFZ is characterized by frequent moderate and strong earthquakes. This is a typical tectonic area for studying seismic and volcanic activities. The three-dimensional (3D) deep electrical structure of the region was revealed by using 3D electromagnetic inversion of 143 magnetotelluric stations. The results suggest that the deep electrical structure in the western part of the ZBFZ is laterally heterogeneous. To the north of the Shangyi-Chicheng Fault (F4), the upper crust has a high resistivity structure (R), corresponding to the exposed Hanuoba basalts and metamorphic rocks. To the south of F4, high and low resistivity zones alternate, which is attributed to the complex faults and basin-range structures. In the middle crust, the low-resistivity structures (C1 and C2) gradually appear in the northwest and southeast of the study area, showing the characteristics of a high-resistivity structure sandwiched between two low-resistivity structures. In the lower crust, the two low-resistivity structures (C1 and C2) gradually join each other and the whole region becomes characterized by low resistivity. The Shangyi-Chicheng Fault (F4), the northern margin fault of the Huai’an Basin (F7), and the northern margin fault of the Huaizhuo Basin (F11) are definite electrical difference zones, which are connected to a low-resistivity layer in the crust. The results indicate that the focal depth of the 1998 M6.2 Zhangbei earthquake was between 12 km and 15 km and its seismogenic fault was the Dahezhen-Hailiutu Fault (F3), which is concealed beneath the Hanuoba basalt area. It is speculated that owing to the neotectonic activities, the magma originated in the asthenosphere mantle rose and erupted on the surface near Datong, forming the Datong volcanic group. Then the magma continued to migrate and overflow along with the fractures in the NE direction, forming the Hannuoba basalts in the Zhangbei area. The existence of mantle thermal material in this area led to the migration of accompanying fluids to the middle and upper crust, resulting in fault sliding and frequent occurrence of moderate and strong earthquakes in this region.

The study of complex networks is to discover the characteristics of these connections and to discover the nature of the system between them. Link prediction method is a classic in the study of complex networks. It ca not only reflect the relationship between the node similarity. More can be estimated through the edge, which reveals the intrinsic factors of network evolution, namely the network evolution mechanism. Threat information network is the evolution and development of the network. The introduction of such a complex network of interdisciplinary approach is an innovative research perspective to observe that the threat intelligence occurs. The characteristics of the network show, at the same time, also can predict what will happen. The evolution of the network for network security situational awareness of the research provides a new approach.

Additional file 1: Figure S1. In silico analysis of the Phaeodactylum tricornutum Pt2015 gene. (A) Schematic drawing of the Pt2015 gene on chromosome 12, which is annotated as an open reading frame of 444 bp in length corresponding to a predicted protein of 147 amino acids. (B) Analysis of the signal peptide in the Pt2015 protein using SignalP 4.1. The cleavage site of the signal peptide in Pt2015 is between the 17th and 18th amino acid. Figure S2. Transmembrane domain analysis of the Pt2015 protein via the TMHMM Server 2.0. Figure S3. (A) Comparison of the conserved regions in Pt2015 proteins from diatoms, chrysophyta, dinoflagellate, and other red-tide algae using the MEGA 7.0 platform. Conserved motifs are indicated as sequence logos, which are on the top of the sequences. (B) Amino acid sequence alignment of the Pt2015 protein with exosome component 10 in Porphyridium purpureum. The sequences are aligned using BioEdit. Black-boxed and gray-boxed letters represent identical or similar residues, respectively. Figure S4. Chloroplast purification using a discontinuous Percoll gradient (10%, 20%, and 30%) and ultracentrifugation. The chloroplast band is indicated on the right. Figure S5. Blue native-polyacrylamide gel electrophoresis (BN-PAGE) analysis of the thylakoid membrane complex from P. tricornutum wild type (WT). (A) The gel is stained with Coomassie Brilliant Blue. (B) Thylakoid membrane complexes separated by BN-PAGE in A have been further subjected to sodium dodecyl sulfate (SDS)-PAGE, and the proteins are detected with specific antibodies against PsbD, PsaA, and Pt2015, respectively. Figure S6. Effects of salinity and temperature on the Pt2015 overexpression (oeT) strain. Percentage of triradiate abundance (Black square) and fusiform (Red circle) morphotypes of the oeT strain at different salinities and temperatures. (A) 100% sea water and 20 °C; (B) 50% sea water and 20 °C; (C) 30% sea water and 20 °C; and (D) 100% sea water and 10 °C. Data represent the mean ± standard deviation (SD) of four biological replicates. Figure S7. Validation of RNA-Sequencing data using qualitative reverse transcriptase-polymerase chain reaction (qRT–PCR) analysis. The expression of eight genes selected randomly from the list of differently expressed genes (DEGs) is shown, including ID 7,199,712 (A), 7,203,450 (B), 7,195,163 (C), 7,195,518 (D), 7,198,479 (E), 7,204,536 (F), 7,205,131 (G), and 7,198,653 (H). Figure S8. Gene ontology (GO) enrichment analysis (biological processes (A and B) and molecular functions (C and D)) of the wild-type (WT)-vs-Pt2015 knockout strain (2015KO) comparison (A and C) and the WT-vs-Pt2015 overexpression (oeT) strain comparison (B and D) based on RNA-Sequencing data. Figure S9. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of the wild-type (WT)-vs-Pt2015 knockout strain (2015KO) comparison (A) and the WT-vs-Pt2015 overexpression (oeT) strain comparison (B) based on RNA-Sequencing data. Figure S10. Functional profiling analysis [biological process (A) and cellular component (B)] of the pairwise comparison of the wild type (WT), Pt2015 knockout strain (2015KO), and Pt2015 overexpression (oeT) strain based on proteomic data. Figure S11. Functional profiling analysis (molecular function) of the pairwise comparison of the wild type (WT), Pt2015 knockout strain (2015KO), and Pt2015 overexpression (oeT) strains based on proteomic data. Figure S12. Micrographs of the amoebae cultivated with the oeT (A) and WT (B) cells. The spores of amoebae were centrifugated at 3500 × g for 5 min, and then the precipitation was diluted with WT and oeT cells at the same cell density (5 × 106 cells/ml), respectively. The diluent was cultured in culture plates (6 wells) at 25 °C under the dark condition. After 24 h, the cells of the oeT and WT were observed. The scale bar is 5 μm. Figure S13. The metabolic network of Pt2015 and top 30 genes that related closely to Pt2015 indicated that several genes encoding solute carriers or channels (ID: 7,202,857, 7,198,159, 7,197,826) and transporters (ID: 7,201,627, 7,196,383 7,203,428) based on RNA-Sequencing data. The green circle represents the Pt2015 and the purple circles represents the genes related closely to Pt2105. The red lines and blues line represent positive correlation and negative correlation, respectively. Figure S14. The heatmap of genes involving lipid metabolisms in the comparison of WT and oeT based on RNA-Sequencing data. Figure S15. The GO enrichment analysis (the upregulated processes) of the oeT strain-vs-WT based on proteomic data. In the biological process, the GO ID of sphingolipid metabolic process, glycerolipid biosynthetic process, membrane lipid metabolic process, and glycerolipid metabolic process is GO:0,006,665, GO:0,045,017, GO:0,006,643, GO:0,046,486, respectively. Table S1. Sequences of gRNAs targeting the Pt2015 gene in P. tricornutum. The predicted gRNA binding site is the underlined sequence, and the complementary oligonucleotide is also shown in the table. Oligonucleotides are designed with a top strand 5’-TCGA-3’ and bottom strand 3’-CAAA-5’ BsaI restriction cut site overhangs to facilitate cloning into the Cas9 vector. Table S2. Lists of Pt2015 gene and reference gene (RPS) primers.

Background Diatoms are well known for high photosynthetic efficiency and rapid growth rate, which are not only important oceanic primary producer, but also ideal feedstock for microalgae industrialization. Their high success is mainly due to the rapid response of photosynthesis to inorganic carbon fluctuations. Thus, an in-depth understanding of the photosynthetic carbon fixation mechanism of diatoms will be of great help to microalgae-based applications. This work directed toward the analysis of whether C4 photosynthetic pathway functions in the model marine diatom Phaeodactylum tricornutum, which possesses biophysical CO2-concentrating mechanism (CCM) as well as metabolic enzymes potentially involved in C4 photosynthetic pathway. Results For P. tricornutum, differential proteome, enzyme activities and transcript abundance of carbon metabolism-related genes especially biophysical and biochemical CCM-related genes in response to different concentrations of CO2 were tracked in this study. The upregulated protein abundance of a carbonic anhydrases and a bicarbonate transporter suggested biophysical CCM activated under low CO2 (LC). The upregulation of a number of key C4-related enzymes in enzymatic activity, transcript and protein abundance under LC indicated the induction of a mitochondria-mediated CCM in P. tricornutum. Moreover, protein abundance of a number of glycolysis, tricarboxylic acid cycle, photorespiration and ornithine–urea cycle related proteins upregulated under LC, while numbers of proteins involved in the Calvin cycle and pentose phosphate pathway were downregulated. Under high CO2 (HC), protein abundance of most central carbon metabolism and photosynthesis-related proteins were upregulated. Conclusions The proteomic and biochemical responses to different concentrations of CO2 suggested multiple carbon metabolism strategies exist in P. tricornutum. Namely, LC might induce a mitochondrial-mediated C4-like CCM and the improvement of glycolysis, tricarboxylic acid cycle, photorespiration and ornithine–urea cycle activity contribute to the energy supply and carbon and nitrogen recapture in P. tricornutum to cope with the CO2 limitation, while P. tricornutum responds to the HC environment by improving photosynthesis and central carbon metabolism activity. These findings can not only provide evidences for revealing the global picture of biophysical and biochemical CCM in P. tricornutum, but also provide target genes for further microalgal strain modification to improve carbon fixation and biomass yield in algal-based industry.

Internet of things engineering specialty has the characteristics of interdisciplinary, wide range of knowledge and focusing on engineering practice. As a professional basic course of Internet of things engineering, Microcontroller Unit (MCU) course should focus on cultivating students' ability of solving practical engineering problems and application innovation. According to the students' cognitive law, the project tasks based on the working process are jointly developed through school enterprise cooperation. The mainstream 32-bit MCU contents are integrated into 16 teaching tasks, 24 teaching contents and 43 knowledge points by calling library functions. From easy to difficult, from simple to complex, the students are taught in accordance with their aptitude through the online and offline mixed teaching mode, and the ability and thinking of solving practical projects are cultivated In order to meet the needs of students' personalized development, we should promote teaching and learning by competition, stimulate students' interest in learning MCU and build up their confidence in learning the perception layer of Internet of things, and cultivate innovative and applied talents with strong practical ability.

Additional file 1: Figs S1-S7, Table S1. Fig. S1. Identification of ISIP2a knock down strain. (a) Growth analysis of WT, ISIP2a-S1 and ISIP2a-S2 under Fe deplete (-) and Fe replete (+) conditions. (b) relative expression of ISIP2a in WT, ISIP2a-S1 and ISIP2a-S2. Data was shown as mean values �� SD for three independent experiments. Fig. S2. Schematic illustration of the mathematical model for calculating the chlorophyll fluorescence photon flux density (CFPFD) received per cell. (a) Two adjacent cells. (b) Two cells with cellular distance at 10 ��m. (c) Two cells with cellular distance at 100 ��m. Fig. S3. Schematic illustration of the mathematical model for calculating the chlorophyll fluorescence photon flux (CFPF) during diatom blooms in oceans. (a) Evenly distributed cells in real water. The cell in the center can receive chlorophyll fluorescence from the whole space. (b) Percentage of CFPF versus upper limit of the integral. Fig. S4. Relative expression of flavodoxin under different cell density. The cells were adjusted to different cell density (L for low cell density, M for middle cell density and H for high cell density) and cultured at white light (WL), blue light (BL) and dark conditions. Data was shown as mean values �� SD for three independent experiments. Fig. S5. Relative expression of ISIP2a and ISIP1 in the experiments carried out with the following conditions: The cells at mid-exponential growth phase were harvested, resuspended with different sonicated medium of low cell density (L-CE), middle cell density (M-CE), and high cell density (H-CE) and cultured at dark for 24 h. Data was shown as mean values �� SD for three independent experiments. Fig. S6. Prediction of cis-acting element in the iron uptake related genes in P. tricornutum. Fig. S7. Correlations between MetaT expression of ISIPs and iron concentration among various Tara stations. The ISIPs in each Tara stations were expressed as a percentage of the total value of ISIP1, ISIP2a, ISIP2b and ISIP3, and normalized by the total diatom unigene expression, respectively. Pearson correlation coefficients (Pearson r) and their statistical significance (p value) are indicated in graph. Table S1. Primer list

Massive electronic data involve lots of image evidence. The specific classification of geometric curved surfaces on the image set in image recognition algorithm will result in information loss. For this problem, an improved iterative deep learning algorithm (IIDLA) based on convolutional neural network is proposed. The algorithm adopts pooled convolutional layer (PCL) to conduct underlying translation invariant feature learning, applies hierarchical iteration and uses convolutional neural network (CNN) to learn different nonlinear features of input image set. The image library and inquiry examples of the algorithm include face or object image set of different view angle, background, facial expression, resolution and illuminance. The dataset is used to evaluate and compare the proposed algorithm and other algorithms. The results show that the proposed algorithm has the best performance on the evaluation dataset.

In this paper, the wear property of ER8 and SSW-Q3R wheel steel under pure rolling condition was studied by GMP-30 wear tester. The results showed that the wear loss of the ER8 wheel steel was higher than that of the SSW-Q3R wheel steel at the same cycles. The high carbon content of the SSW-Q3R improved the surface hardness during rolling wear. The high hardness increased the wear resistance of the SSW-Q3R wheel steel. During rolling wear, the fatigue wear resistance of ER8 wheel was worse than that of the SSW-Q3R wheel steel due to more proeutectoid ferrite content in ER8 wheel steel. The surface residual stress of ER8 and SSW-Q3R wheel steel increased with the increase in cycles. The axial residual compressive stress on the surface of the sample was greater than the circumferential residual compressive stress. The residual stress at the trough was higher than that at the crest.

The drug resistance of cancer remains a major obstacle to successful chemotherapy. New strategies for improving chemotherapeutic efficacy are urgently required. Recent studies have indicated that LIPC plays a role in promoting the liver metastasis of colorectal cancer. In the present study, we aimed to investigate the effects of LIPC on theproliferation and clone formation of colorectal cancer-derived cells, and chemoresistance in hepatoblastoma-derived HepG2 cells. The activity and expression of LIPC were determined in the cell lines by RT-qPCR and western blot analysis. HepG2 cells in which LIPC was knocked down by LIPC short hairpin RNA (shRNA) and control cells [shRNA control (shCON)] were established and analyzed for cell proliferation and colony formation rates. FACS analysis was used to explore the association between LIPC and the tumor-derived cell biomarker, CD133, and the percentages of CD133-positive cells were assessed by FACS. Additionally, shLIPC- and shCON-transfected cells were treated with various concentrations of doxorubicin and 5-floxuridine (5-FU), and cell viability was determined by MTT assay. mRNA levels in the shLIPC- and shCON-transfected cells were compared by cDNA microarray and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. The results revealed that the HepG2 cells exhibited a relatively higher LIPC activity and expression levels compared to the other colon cancer cell lines. The downregulation of LIPC in the HepG2 cells was associated with the decreased expression of CD133, decreased cell proliferation and colony formation, as well as increased resistance to chemotherapy. KEGG analysis of the cDNA microarray data revealed increased levels in the cell adhesion molecule (CAM) pathway, including CLDN10 and CLDN1, indicating that CAMs may play a role in LIPC-mediated tumor progression. The present findings indicate a potential role of LIPC as a promising therapeutic target in cancer.

A near infrared spectroscopy (NIRS) approach was established for quality control of the alcohol precipitation liquid in the manufacture of Codonopsis Radix. By applying NIRS with multivariate analysis, it was possible to build variation into the calibration sample set, and the Plackett-Burman design, Box-Behnken design, and a concentrating-diluting method were used to obtain the sample set covered with sufficient fluctuation of process parameters and extended concentration information. NIR data were calibrated to predict the four quality indicators using partial least squares regression (PLSR). In the four calibration models, the root mean squares errors of prediction (RMSEPs) were 1.22 μg/ml, 10.5 μg/ml, 1.43 μg/ml, and 0.433% for lobetyolin, total flavonoids, pigments, and total solid contents, respectively. The results indicated that multi-components quantification of the alcohol precipitation liquid of Codonopsis Radix could be achieved with an NIRS-based method, which offers a useful tool for real-time release testing (RTRT) of intermediates in the manufacture of Codonopsis Radix.

A HPLC-UV-ELSD method was established for simultaneous determination of six components in two intermediates of Shenqi Fuzheng injection (SFI) and the feasibility of establishing quantitative analysis of multi-components by single marker (QAMS) methods on different detectors was further explored. Calycosin-7-O-β-D-glucoside and astragloside Ⅳ were selected as internal reference substances for respectively flavonoids and saponins, and relative correlation factors (RCF) of formononetin-7-O-β-D-glucoside, 9, 10-dimethoxypterocarpan-3-O-β-D-glucopyranoside, 2'-dihydroxy-3', 4'-dimethoxyisoflavan-7-O-β-D-glucopyranoside and astragloside Ⅱ were calculated. Eventually, quantitative results of the 14 samples were compared between QAMS and external standard method. The sample concentrations calculated by QAMS were similar with concentrations calculated by external standard method, and the absolute values of relative deviations were generally less than 5% according to the UV detection of flavonoids. On the basis of ELSD detection for saponins, however, the absolute values of relative deviation of the two methods ranged from 0.48% to 23.17%. The QAMS method built on ultraviolet (UV) detectors was stable and can be used as a substitute method to reduce the consumption of standard compounds; meanwhile, the accuracy of QAMS method built on evaporative light scattering detector (ELSD) was inferior to that of external standard method, and the working principle of ELSD and feasible concentration range remain to be further studied.

The annual dynamics of phytoplankton community structure in Lake Caizi has been investigated in 2010.The results indicated that:(1) A total of 285 phytoplankton species from 110 genera of 8 phylum were identified.Phytoplankton species composition in different months showed significant difference.The maximal number of phytoplankton species(173) occurred in March while the minimum(105) in January.The dominant class of phytoplankton changed seasonally.Cyanophyta peaked all the year round;diatoms had an apparent dominance in January,May,September and November;Xanthophyta also played an important role in January,March and May;Chlorophyta dominated in November,Cryptophyta dominated in May while Chrysophyta dominated in January.The cell density and biomass of phytoplankton were higher in summer and autumn than that in winter and spring.The cell density of phytoplankton between different months had significant difference.The maximal density,with the value(66.13±8.58)×105 cells/L occurred in July while the minimal value of(12.78±0.61)×105 cells/L appeared in January.Whereas,the maximal biomass of phytoplankton(2.80±0.17 mg/L) occurred in September and the minimal(0.72±0.03 mg/L) appeared in May,and the biomass in different months was also significant different.(2) Temporal variations of three indices(including Margalef index,Shannon-Wiener index and Pielou evenness index) were obvious.All the indices were higher in winter and spring than those in summer and autumn.The maximal value occurred in March while the minimal one appeared in July.(3) The phytoplankton community structure was influenced by different factors in different months.As a result,the groups of sampling station changed seasonally according to cluster analysis.(4) The obvious variation of phytoplankton community structure was present in 2010 compared with that in 2007.The number of species decreased from 340 in 2007 to 285 in 2010,however,the cell density increased obviously from(5.91±0.90)×105 cells/L in 2007 to(33.81±10.10)×105 cells/L in 2010.At the same time,both the numbers of oligotrophic algae and perphytic algae decreased to the same extent and eutrophic,filamentous and planktonic algae increased.

Although documenting the impact of urbanization on biodiversity has been an important research topic in many developed countries,research on this topic is rare in the developing countries.The aim of this study is to investigate the changes in indigenous plant diversity along an urbanization gradient and the relationship between indigenous plant species and the soil factors in their habitat.In Langfang City,a fast-urbanizing city in northern China,six sites with size of 20 m×20 m each were sampled along central urban,urban,suburban and rural gradient,respectively.In each site,2 plots with size of 2 m×2 m each for shrub species and 3 plots with size of 1 m×1 m each for herbaceous species were selected for plant community survey.Species richness,diversity,and composition of indigenous plants were recorded and analyzed at each site. Our results suggested that urbanization processes have a significant effect on the number,diversity,proportion,and composition of indigenous plant species.A total of 11 species were recorded in the central urban,14 species in urban,46 species in suburban,and 95 species in rural areas.Species diversity reflected by the Shannon-Wiener index increased from central urban to rural areas,with relatively low standard deviations in central urban but relatively high standard deviations in rural area.Evenness increased from urban to rural areas,with high values in central urban spaces.The standard deviation of evenness values was relatively high for all sampling sites,with a significant difference according to the Pearson-test(average 0.91 at P=0.05) along the urbanization gradient.There were six families in central urban areas,ten families were recorded in urban areas(mainly Gramineae),19 families in suburban spaces and 45 families in rural areas.In central urban and urban areas,most indigenous plants belonged to the Gramineae and Chenopodiaceae families,but in the suburban areas species compositions were mixed with members from Gramineae,Compositae,Leguminosae,Chenopodiaceae and Asclepiadaceae.In central urban areas,the main indigenous plant species were Eleusine indica,Digitaria sanguinalis,and Setaria viridis.The urban area communities were dominated by Digitaria sanguinalis,Eleusine indica,Chloris virgata,Setaria viridis and Chenopodium album.Amaranthus retroflexus is present in suburban areas.In rural areas,Amaranthus retroflexus becomes replaced by Kochia scoparia. The similarity index showed that most of the species distributed in the urban area were also found in the suburban,but not in the rural areas.With increase of distance to central urban,the Jaccard index decreased.Most indigenous plant species growing in rural or suburban areas were also likely to grow in central urban than in urban areas.The DCCA analysis showed that total soil nitrogen is the main factor influencing the spatial distribution of indigenous plant species under urbanization.Soil conductivity and total organic matter,and active potassium have a relatively lower effect,and soil pH has the lowest effect on the sample ordination in the DCCA.The plant species surviving in urban areas had high tolerance to tramping,soil compaction and mowing,most of them belong to the Gramineae and Chenopodiaceae families.Thus,urbanization has eliminated most local species and only most common species are left.This result suggests that,in general,urbanization facilitates the homogeneity of plant species distributions worldwide.

The squeezing effect and atomic population of the binomial field interacting with a cascade three level atom are calculated accurately without rotating-wave approximation(without RWA) by using the complete quantum theory.The influences of the binomial state field parameter η on the field squeezing effect and the maximum photon number M of the binomial state field on the atomic population are considered.The results obtained from using the numerical method show that with increase of the binomial state field parameter η,the duration of the squeezing effect increases at first and then decreases.The little indentation oscillation appears in the evolution curves of the field squeezing effect,which is caused by virtual photon without RWA.The period of the revival-collapse increases with the increase of the maximum photon number M,and the atomic population can not collapse completely in the collapse regime,but displays little indentation oscillation.In addition the influence of the without-RWA terms on the quantum properties of the system are discussed.

Register pressure problem has been a known problem for compiler because of the mismatch between the infinite number of pseudo registers and the finite number of hard registers. Too heavy register pressure may results in register spilling and then leads to performance degradation. There are a lot of optimizations, especially loop optimizations suffer from register spilling in compiler. In order to fight register pressure and therefore improve the effectiveness of compiler, this research takes the register pressure into account to improve loop unrolling optimization during the transformation process. In addition, a register pressure aware transformation is able to reduce the performance overhead of some fine-grained randomization transformations which can be used to defend against ROP attacks. Experiments showed a peak improvement of about 3.6% and an average improvement of about 1% for SPEC CPU 2006 benchmarks and a peak improvement of about 3% and an average improvement of about 1% for the LINPACK benchmark.

Objective: To find more effective diagnosis and treatment of NRDS through comparatively analyzing the different gestational neonates with respiratory distress syndrome in risk factors, clinical characteristics, treatment and prognosis. Methods: The clinical data of 232 neonates were retrospectively analyzed who had been admitted into the neonatal intensive care unit and diagnosed with NRDS from January 2008 to December 2010. These cases were divided into three groups according to gestational age, which included full-term group, late preterm and early preterm group. Statistical analysis was used to detect the differences of relative factors among the three groups.Results: For pathogen, the full-term and late preterm infants accounted for more than 50% The majority of full-term infants were less than 39 weeks, taking up 83.7%. As many as 61.1% of the late preterm infants were born at maternal age over 30 years. The incidence of Cesarean section was high among the three groups, especially the full-term (90.7%) and late preterm group (86.1%). For clinical features, full-term infants had late onsets more than 12 h after birth. Air bronchogram could be found commonly in early preterm neonates, influencing 92% of them. However, it was rare in the other two groups. The incidence of lung infection in each group was all about 50%. In addition, Gas leakage and PPHN were more common complications in full-term and late preterm group, while for the early preterm group was the bronchopulmonary dysplasia and intracranial hemorrhage. For treatment, the proportions of full-term infants receiving application of HFOV and NO were 57.0% and 24.4%, and for late preterm infants were 36.1% and 22.2%. The application of HFOV and NO was not as much to early preterm infants as other groups. There was no significant difference in the duration of invasive ventilation between all groups. However, the noninvasive ventilation time after extubation was as long as 10.1±0.5 days in early preterm infants. The proportions of infants receiving application of PS were 53.5%, 83.3% and 81.8%, respectively. OI values improved greatly 2 h after application of PS on early preterm infants. However, the obvious difference was found only after 24 h for full-term and late preterm infants.Conclusion: Besides early preterm infants, full-term and late preterm have the growing trend in the pathogenesis of NRDS. Infants of different gestational age have their own characteristics of the risk factors, which cesarean section impacts greatly on the incidence of term and late preterm infants. The clinical feature, chest X-ray changes and common complications were characteristics between term and premature infants with NRDS. The PS treatment work slower in term and late preterm infants, who needed more HFOV and NO treatment.

Objective: To study the possibility of lower the nosocomial infection rate among the premature infants by prophylactic use of antibiotics. Methods: Retrospectively collect 409 premature infants admitted to the neonatal intensive care unit (NICU) of First Hospital of Jilin University between 1st January in 2009 and 31th December in 2011, who meet inclusion criteria. There were prohylactic group and nonprohylactic group randomly divided and compared the nosocomial infection rates of two groups. Results: The hospital infection rate of the prophylactic group was 62.9%, and the rate of the non-prophylactic group was 47.3%. There was a significant difference between the two groups (P

Spinal cord injury (SCI) is a serious medical problem with high mortality and disability rates. Hyperbaric oxygen (HBO) treatment is beneficial for neurological recovery after SCI, but the underlying mechanisms await characterization. This study examined whether HBO treatment following SCI in rats exerts a neuroprotective effect through activation of the toll-like receptor (TLR) 2/nuclear factor (NF)-κB signaling pathway. The SC of rats was injured via T10 laminectomy. Experimental animals (n = 144) were divided into four groups: sham-operated (SH), SH + HBO, SCI, and SCI + HBO. Each group was subdivided into six subgroups (n = 6 per group) that were examined at 12 h, and 1, 2, 3, 7, and 14 days post-injury. Functional recovery in the hind limb was evaluated using the Basso, Beattie, and Bresnahan (BBB) scoring system. The expression of TLR2 and NF-кB was assessed by real-time polymerase chain reaction and Western blotting, while interleukin-1 (IL)-1β and tumor necrosis factor (TNF)-α levels were measured by enzyme-linked immunosorbent assay. TLR2 and NF-кB levels and histological scores were higher in the SCI than in the SH and SH + HBO groups at various time points. HBO treatment decreased TLR2 and NF-кB expression and histological scores as well as IL-1β and TNF-α levels compared to the SCI group at early post-injury stages. In addition, BBB scores were improved in the SCI + HBO relative to the SCI group at 7 and 14 days. HBO treatment may mitigate secondary injury to the SC by inhibiting inflammatory responses induced by TLR2/NF-кB signaling, thereby promoting functional recovery and improving neurological outcome.

A bionic mode simulating olfactory neural system, KIII model, and its application to face recognition are researched in this paper. The face image features are extracted based on singular value decomposition. Firstly, the whole face image is divided into sub-images with equal size. Then, the maximal singular value is selected as the sub-image feature after the sub-image is decomposed by singular value decomposition. Finally, all sub-image features are combined to construct the whole face image feature vector. According to ORL face database, experimental results show that KIII model has good pattern recognition capability.

Between August 2009 and April 2013, in the Guanyingshan Nature Reserve, Shaanxi Province, we 738 生 物 多 样 性 Biodiversity Science 第 22 卷 collected photo data on six ungulates (Budorcas taxicolor, Naemorhedus griseus, Elaphodus cephalophus, Capricornis milneedwardsii, Muntiacus reevesi and Moschus berezovskii) with 18 infrared cameras. Using the relative abundance index (RAI), we analyzed activity patterns and seasonal differences of these six species. The results show that: (1) their total RAI in the study area reaches 58.71%, the RAI of B. taxicolor was 28.02%, and it was 13.24% for N. griseus, 10.08% for E. cephalophus, 4.21% for C. milneedwardsii, 2.26% for M. reevesi, and 0.90% for M. berezovskii. (2) Monthly RAIs (MRAI) of six ungulates reflected seasonal activity patterns; B. taxicolor, N. griseus, E. cephalophus, C. milneedwardsii, M. reevesi exhibited similar activity patterns. These species were most active in summer, became inactive in autumn and winter, and then gradually increased activity in spring. M. berezovskii, on the other hand, was most active in winter and least active in summer. (3) The time-period relative abundance indices (TRAI) of the six ungulates reflect their daily activity patterns. B. taxicolor and N. griseus have similar daily activity patterns with an active peak at 06:00–20:00.The daily activity pattern of E. cephalophus, M. reevesi and M. berezovskii showed obvious crepuscular habits. C. milneedwardsii also has two peaks but at 02:00–06:00 and 20:00–22:00 implying nocturnal activities. (4) Comparative analyses of daily activity patterns among the four seasons showed that B. taxicolor displayed a different pattern in spring with an activity peak at 16:00–20:00. Compared with other seasons, N. gresius, E. cephalophus and C. milneedwardsii have different patterns in winter with either a delayed or advanced activity peak. In the case of M. reevesi, spring daily activity patterns showed two peaks at 00:00–10:00 and 18:00–20:00. Due to a paucity of captures, M. berezovskii showed different activity patterns in all four seasons. (5) Analysis of the nocturnality showed that C. milneedwardsii was obviously nocturnal with a nighttime relative abundance index (NRAI) of 65.81%. Our results help us to understand the activity patterns of these ungulates in Qinling, to monitor their population dynamics, and provide a theoretical basis and data support for the nature reserves to protect the ungulate animals more efficiently. Key word: activity patterns, camera trap, ungulates, relative abundance index (RAI), seasonal variation 红外相机技术是监测野生动物的有效方法, 可 以24 h无间断运行以收集动物的种类、数量和行为 等相关信息, 在国外应用已有较长的历史, 最早的 报道见于Champion(1927), Gysel等(1956)对其在野 生动物研究上的应用进行了介绍。在20世纪90年代 逐渐发展成熟, 现已广泛用于野生动物资源调查、 活动规律、种群数量与密度的研究,如利用该技术, 马世来和Harris(1996)对云南高黎贡地区的野生动 物资源进行了调查, 卢学理等(2005)对陕西长青自 然保护区大熊猫以及同域分布的野生动物资源调 查 , 余梁哥等 (2013) 对屏边县大围山倭蜂猴 (Nyticebus pygmaeus)、蜂猴(N. bengalensis)及同域分 布兽类资源进行了调查研究; Tape和Gustine(2014) 分析了北美驯鹿 (Rangifer caribou)和雷鸟 (Tetrao urogallus)的季节性迁移习性与纬度之间的关系 ; Karanth(1995)、Wallace等(2003)利用该技术分别对 孟加拉虎(Panthera tigris) 、美洲豹(Panthera onca) 的种群数量和密度进行了研究。这些成果对野生动

To conserve giant panda effectively, it is important to understand the spatial pattern and temporal change of its habitat. Mapping is an effective approach for wildlife habitat evaluation and monitoring. The application of recently developed artificial intelligence tools, including expert systems and neural networks, could integrate qualitative and quantitative information for modeling complex systems, and built the information into a GIS, which could be helpful for giant panda habitat mapping. This study built a mapping approach for giant panda habitat mapping, which integrated expert system and neural network classifiers (ESNNC), and used multi-type data within GIS. The giant panda habitat types and their suitability were mapped by ESNNC. The results showed that the habitat types and their suitability in Foping Nature Reserve were assessed with a higher accuracy (> 80 %) by ESNNC, compared with non-integrated classifiers, i. e., expert system, neural network, and maximum likelihood. Z-statistic test showed that ESNNC was significantly better than the other three non-integrated classifiers. It was recommended that the integrated approach could be widely applied into wildlife habitat assessment

In 2014, Wiley and the Zoological Society of London launched Remote Sensing in Ecology and Conservation, an open-access journal that aims to support communication and collaboration among experts in remote sensing, ecology and conservation science. Remote sensing was from the start understood as the acquisition of information about an object or phenomenon through a device that is not in physical contact with the object, thus including camera traps, field spectrometry, terrestrial and aquatic acoustic sensors, aerial and satellite monitoring as well as ship-borne automatic identification systems. The primary goals of this new journal were, and still are, to maximize the understanding and uptake of remote sensing-based techniques and products by the ecological and conservation communities, prioritizing findings that advance the scientific basis of, and applied outcomes from, ecology and conservation science; and to identify ecological challenges that might direct development of future remote sensors and data products. In October 2015, the first issue of the journal was published, with four other issues produced in 2016 and four to be published in 2017. As Remote Sensing in Ecology and Conservation is about to complete its second full year of publication and is working towards a first impact factor score in early 2019, the time has come to reflect on how the journal has done to date, what impact it has had, which niches it has successfully filled and where the journal is yet to meet its full potential. By sharing our successes and experiences so far with our contributors and readers, we hope to demonstrate how Remote Sensing in Ecology and Conservation has swiftly gained significant visibility and status among scientists and practitioners interested in natural resource management. Fil: Pettorelli, Nathalie. The Zoological Society Of London; Reino Unido Fil: Nagendra, Harini. Azim Premji University; India Fil: Rocchini, Duccio. Università Degli Studi Di Trento; Italia Fil: Rowcliffe, Marcus. The Zoological Society Of London; Reino Unido Fil: Williams, Rob. Oceans Initiative; Estados Unidos Fil: Ahumada, Jorge. Conservation International; Estados Unidos Fil: de Angelo, Carlos Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; Argentina Fil: Atzberger, Clement. Universitat Fur Bodenkultur Wien; Austria Fil: Boyd, Doreen. Science and Technology Facilities Council of Nottingham. Rutherford Appleton Laboratory; Reino Unido. University of Nottingham; Estados Unidos Fil: Buchanan, Graeme. Royal Society For The Protection Of Birds; Reino Unido Fil: Chauvenet, Alienor. University of Queensland; Australia Fil: Disney, Mathias. Colegio Universitario de Londres; Reino Unido Fil: Duncan, Clare. Deakin University; Australia Fil: Fatoyinbo, Temilola. NASA Goddard Space Flight Center; Estados Unidos Fil: Fernandez, Nestor. Consejo Superior de Investigaciones Científicas. Estación Biológica de Doñana; España Fil: Haklay, Muki. Colegio Universitario de Londres; Reino Unido Fil: He, Kate. Murray State University Murray; Estados Unidos Fil: Horning, Ned. American Museum of Natural History; Estados Unidos Fil: Kelly, Natalie. Australian Antarctic Division; Australia Fil: de Klerk, Helen. Stellenbosch University; Sudáfrica Fil: Liu, Xuehua. Tsinghua University; China Fil: Merchant, Nathan. Centre for Environment, Fisheries and Aquaculture Science; Reino Unido Fil: Paruelo, José. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Roy, Helen. NERC Centre for Ecology & Hydrology; Reino Unido Fil: Roy, Shovonlal. University of Reading; Reino Unido Fil: Ryan, Sadie. University of Florida; Estados Unidos Fil: Sollmann, Rahel. University of California at Davis; Estados Unidos Fil: Swenson, Jennifer. University of Duke; Estados Unidos Fil: Wegmann, Martin. Universität Würzburg; Alemania