[Spectra Classification Based on Local Mean-Based K-Nearest Centroid Neighbor Method].

In the present paper, a local mean-based K-nearest centroid neighbor (LMKNCN) technique is used for the classification of stars, galaxies and quasars (QSOS). The main idea of LMKNCN is that it depends on the principle of the nearest centroid neighborhood(NCN), and selects K centroid neighbors of each class as training samples and then classifies a query pattern into the class with the distance of the local centroid mean vector to the samples . In this paper, KNN, KNCN and LMKNCN were experimentally compared with these three different kinds of spectra data which are from the United States SDSS-DR8. Among these three methods, the rate of correct classification of the LMKNCN algorithm is higher than the other two algorithms or comparable and the average rate of correct classification is higher than the other two algorithms, especially for the identification of quasars. Experiment shows that the results in this work have important significance for studying galaxies, stars and quasars spectra classification.

[SKLOF: a new algorithm to reduce the range of supernova candidates].

Supernova (SN) is called the "standard candles" in the cosmology, the probability of outbreak in the galaxy is very low and is a kind of special, rare astronomical objects. Only in a large number of galaxies, we have a chance to find the supernova. The supernova which is in the midst of explosion will illuminate the entire galaxy, so the spectra of galaxies we obtained have obvious features of supernova. But the number of supernova have been found is very small relative to the large number of astronomical objects. The time computation that search the supernova be the key to weather the follow-up observations, therefore it needs to look for an efficient method. The time complexity of the density-based outlier detecting algorithm (LOF) is not ideal, which effects its application in large datasets. Through the improvement of LOF algorithm, a new algorithm that reduces the searching range of supernova candidates in a flood of spectra of galaxies is introduced and named SKLOF. Firstly, the spectra datasets are pruned and we can get rid of most objects are impossible to be the outliers. Secondly, we use the improved LOF algorithm to calculate the local outlier factors (LOF) of the spectra datasets remained and all LOFs are arranged in descending order. Finally, we can get the smaller searching range of the supernova candidates for the subsequent identification. The experimental results show that the algorithm is very effective, not only improved in accuracy, but also reduce the operation time compared with LOF algorithm with the guarantee of the accuracy of detection.

[Automatic Measurement of the Stellar Atmospheric Parameters Based Mass Estimation].

We have collected massive stellar spectral data in recent years, which leads to the research on the automatic measurement of stellar atmospheric physical parameters (effective temperature Teff, surface gravity log g and metallic abundance [Fe/ H]) become an important issue. To study the automatic measurement of these three parameters has important significance for some scientific problems, such as the evolution of the universe and so on. But the research of this problem is not very widely, some of the current methods are not able to estimate the values of the stellar atmospheric physical parameters completely and accurately. So in this paper, an automatic method to predict stellar atmospheric parameters based on mass estimation was presented, which can achieve the prediction of stellar effective temperature Teff, surface gravity log g and metallic abundance [Fe/H]. This method has small amount of computation and fast training speed. The main idea of this method is that firstly it need us to build some mass distributions, secondly the original spectral data was mapped into the mass space and then to predict the stellar parameter with the support vector regression (SVR) in the mass space. we choose the stellar spectral data from the United States SDSS-DR8 for the training and testing. We also compared the predicted results of this method with the SSPP and achieve higher accuracy. The predicted results are more stable and the experimental results show that the method is feasible and can predict the stellar atmospheric physical parameters effectively.

Effect of the intraoperative wake-up test in sevoflurane-sufentanil combined anesthesia during adolescent idiopathic scoliosis surgery: a randomized study.

STUDY OBJECTIVE: To investigate the effect of the intraoperative wake-up test on sevoflurane-sufentanil anesthesia for adolescent idiopathic scoliosis (AIS) surgery. DESIGN: Randomized, double-blind, parallel trial. SETTING: Operating room. PATIENTS: 30 ASA physical status 1 patients, aged 13 to 20 years, scheduled for AIS surgery. INTERVENTIONS: Patients were randomized to two groups: Group W patients received sevoflurane-sufentanil combined anesthesia and underwent the intraoperative wake-up test; Group NW received sevoflurane-sufentanil combined anesthesia without the wake-up test. Anesthesia was induced with an intravenous (IV) injection of midazolam, propofol, and sufentanil and maintained with sevoflurane inhalation, a target-controlled infusion (TCI) of sufentanil, and IV infusion of cisatracurium besylate. MEASUREMENTS: The primary outcome was postoperative delirium. Secondary outcomes were duration of surgery, duration of anesthesia, intraoperative blood loss and transfusion, exposure of drugs administered, time to eye opening, extubation, and consciousness. MAIN RESULTS: Postoperative delirium occurred in one patient from each group (P > 0.05). There were no significant differences between the two groups in duration of surgery (322 ± 65 min vs 336 ± 72 min), duration of anesthesia (356 ± 76 min vs 368 ± 81 min), intraoperative blood loss (1847 ± 423 mL vs 1901 ± 451 mL) and transfusion (1663 ± 398 mL vs 1649 ± 382 mL), average exposure of drugs (72 ± 13 mg vs 75 ± 15 mg for propofol, 116 ± 28 µg vs 109 ± 25 µg for sufentanil, and 22 ± 5 vs 23 ± 4 mg for cisatracurium), time to eye opening (4.7 ± 1.5 min vs 4.8 ± 1.4 min), extubation (7.5 ± 2.0 min vs 7.3 ± 2.2 min), and consciousness (8.9 ± 1.8 min vs 9.1 ± 2.1 min) (all P > 0.05). CONCLUSIONS: Sevoflurane-sufentanil combined anesthesia provides hemodynamic stability and rapid recovery from AIS surgery. There is no correlation between the intraoperative wake-up test and postoperative delirium after sevoflurane-sufentanil combined anesthesia.

[Effect of resuscitation strategy based on the early goal directed therapy on the prognosis of patients with shock].

OBJECTIVE: To evaluate the effects of fluid management strategies in early goal directed therapy (EGDT) on the prognosis of patients with shock. METHODS: Clinical data of 79 patients with septic shock or hemorrhagic shock admitted to emergency intensive care unit (EICU) of the First People's Hospital of Yunnan Province were retrospectively analyzed. Patients were divided into continual fluid administrating group (n=41) in accordance with protocol calculating approximating fluid volume and adjust the infusion speed based on blood pressure, heart rate, pulse saturation of blood oxygen (SpO(2)) and urine output with the end of fluid resuscitation was set to restore spontaneous circulation function and wean off vasoactive drugs, and the conservative fluid resuscitation group (n=38) by means of using vasoactive agents to maintenance blood pressure after infusing amount (20 ml/kg) of liquid early, respectively. The 28-day mortality and the time of using pressure agents were compared between two groups. According to the 28-day mortality, patients were further divided into the survival group (n=37) and death group (n=42), and acute physiology and chronic health evaluation II (APACHEII) score was compared between two groups. Logistic regression analysis of prognostic factors was conducted to identify and describe the relationship between the prognosis and fluid resuscitation methods and strategies. RESULTS: The 28-day mortality of continual fluid administrating group was significantly lower than that of the conservative fluid resuscitation group (14.63% vs. 94.74%, P<0.01), total drugs supporting time (hours) was significantly shorter than that in conservative fluid resuscitation group (33.24±17.56 vs. 58.29±34.78, P<0.05). Thirty-six cases of 42 death patients received conservative fluid resuscitation (85.7%), but 35 cases of 37 survival patients received continual fluid administration (94.6%). Logistic regression analysis showed that odds ratio (OR) of brain natriuretic peptide before death or shifted out ICU was 0.9136, 95% confidence interval (95%CI) was 0.8125 to 0.9986, regression coefficient was -0.0931, P=0.0478, OR of procalcitonin before death or shifted out ICU was 0.9095, 95%CI was 0.8294 to 0.9973, regression coefficient was -0.0949, P=0.0436, and OR of blood lactate level before death or shifted out ICU was 0.5023, 95%CI was 0.2833 to 0.8905, regression coefficient was -0.6885, P=0.0184. CONCLUSIONS: Ongoing fluid resuscitation early in accordance with method to theoretically calculate fluid volume and to adjust infusion speed based on blood pressure, heart rate, SpO(2) and urine, withdrawal of vasoactive drugs, the mortality of patients with shock was significantly reduced.