A Genetic Algorithm-based BP Neural Network Method for Operational Performance Assessment of ATC Sector

To assess operational performance of air traffic control sector, a multivariate detection index system consisting of 5 variables and 17 indicators is presented, which includes operational trafficability, operational complexity, operational safety, operational efficiency, and air traffic controller workload. An improved comprehensive evaluation method, is designed for the assessment by optimizing initial weights and thresholds of back propagation (BP) neural network using genetic algorithm. By empirical study conducted in one air traffic control sector, 400 sets of sample data are selected and divided into 350 sets for network training and 50 sets for network testing, and the architecture of genetic algorithm-based back propagation (GABP) neural network is established as a three-layer network with 17 nodes in input layer, 5 nodes in hidden layers, and 1 node in output layer. Further testing with both GABP and traditional BP neural network reveals that GABP neural network performs betterthan BP neural work in terms of mean error, mean square error and error probability, indicating that GABP neural network can assess operational performance of air traffic control sector with high accuracy and stable generalization ability. The multivariate detection index system and GABP neural network method in this paper can provide comprehensive, accurate, reliable and practical operational performance assessment of air traffic control sector, which enable the frontline of air traffic service provider to detect and evaluate operational performance of air traffic control sector in real time, and trigger an alarm when necessary.</p

Identification of a Disulfide Bridge in Sodium-Coupled Neutral Amino Acid Transporter 2(SNAT2) by Chemical Modification

Sodium-coupled neutral amino acid transporter 2 (SNAT2) belongs to solute carrier 38 (SLC38) family of transporters, which is ubiquitously expressed in mammalian tissues and mediates transport of small, neutral amino acids, exemplified by alanine(Ala, A). Yet structural data on SNAT2, including the relevance of intrinsic cysteine residues on structure and function, is scarce, in spite of its essential roles in many tissues. To better define the potential of intrinsic cysteines to form disulfide bonds in SNAT2, mutagenesis experiments and thiol-specific chemical modifications by N-ethylmaleimide (NEM) and methoxy-polyethylene glycol maleimide (mPEG-Mal, MW 5000) were performed, with or without the reducing regent dithiothreitol (DTT) treatment. Seven single mutant transporters with various cysteine (Cys, C) to alanine (Ala, A) substitutions, and a C245,279A double mutant were introduced to SNAT2 with a hemagglutinin (HA) tag at the C-terminus. The results showed that the cells expressing C245A or C279A were labeled by one equivalent of mPEG-Mal in the presence of DTT, while wild-type or all the other single Cys to Ala mutants were modified by two equivalents of mPEG-Mal. Furthermore, the molecular weight of C245,279A was not changed in the presence or absence of DTT treatment. The results suggest a disulfide bond between Cys245 and Cys279 in SNAT2 which has no effect on cell surface trafficking, as well as transporter function. The proposed disulfide bond may be important to delineate proximity in the extracellular domain of SNAT2 and related proteins

Analysis of prognostic factors of metastatic endometrial cancer based on surveillance, epidemiology, and end results database

ObjectiveTo explore the risk factors for survival and prognosis of patients with metastatic endometrial cancer and to build and verify a reliable prediction model.MethodsWe retrospectively analyzed patients diagnosed with metastatic endometrial cancer in the US Surveillance, Epidemiology, and End Results (SEER) database between January 2010 and December 2015. Univariate and multivariate Cox regression analyses were used to assess clinical variables impact on survival and to construct nomograms. The results of the consistency index (C-index), subject operating characteristic (ROC) curve, and calibration curve were used to evaluate the predictive ability of the nomogram.ResultsThis study included 3,878 patients with metastatic endometrial cancer. In the univariate analysis, variables associated with overall survival (OS) and cancer-specific survival (CSS) included age, race, marital status, pathological type, pathological grade, T-stage, N-stage, surgery, radiotherapy, chemotherapy, bone metastasis, brain metastasis, liver metastasis, and lung metastasis. In the multivariate analysis, age, race, pathological type, pathological grade, T-stage, N-stage, surgery, radiotherapy, chemotherapy, brain metastasis, liver metastasis, and lung metastasis were independent risk factors for OS and CSS (all P &lt; 0.05). Combined with the results of the multiple factors, the 1-, 3-, 5-, and 8-year nomograms were constructed. For OS and CSS, T-stage had the greatest impact on the adverse prognosis of patients with metastatic endometrial cancer. The C-indexes of the OS and CSS nomograms in the training cohort were 0.749 (95% CI, 0.739–0.760) and 0.746 (95% CI, 0.736–0.756), respectively. The C-indices of OS and CSS in the validation cohort were 0.730 (95% CI, 0.714–0.746) and 0.728 (95% CI, 0.712–0.744), respectively. The ROC curve revealed our model's good prediction accuracy and clinical practicability. The calibration curve also confirmed the consistency between the model and actual existence. The Kaplan-Meier curves revealed statistically significant differences between the risk subgroups (P &lt; 0.05).ConclusionOur SEER-based nomograms for predicting survival in patients with metastatic endometrial cancer were helpful for the clinical evaluation of patient prognosis

An evaluation of EQ-5D-3L health utility scores using five country-specific tariffs in a rural population aged 45-69 years in Hua county, Henan province, China.

BACKGROUND: This study aims to compare the performance of the recently developed Chinese (city) tariff of the EQ-5D-3L against the UK, US, Japanese and Korean tariffs in a general rural population in China. METHODS: From November 2015 to September 2016, 12,085 permanent residents aged 45-69 from 257 villages randomly selected from Hua County, Henan Province, China, were interviewed using EQ-5D-3L, and a one-on-one questionnaire investigation was used to collect data on factors associated with HRQOL. The health utility scores were calculated using the UK, US, Japanese, Korean and Chinese (city) tariffs. The agreement, known-groups validity and sensitivity of these five tariffs were evaluated. Transition scores for pairs of observed EQ-5D-3L health states were calculated and compared. RESULTS: The Korean tariff yielded the highest mean health utility score (0.963), followed by the Chinese (city) (0.948), US (0.943), UK (0.930) and Japanese (0.921) tariffs, but the differences in the scores of any two tariffs did not exceed the MCID. The Chinese (city) tariff showed higher ICC values (ICCs> 0.89, 95% CI:0.755-0.964) and narrower limits of agreement (0.099-0.167) than the Korean tariff [(ICCs> 0.71, 95% CI:0.451-0.955); (0.146-0.253)]. The Chinese (city) tariff had a higher relative efficiency and effect size statistics in 10 out of 11 variables as compared to the UK, US and Japanese tariffs. The Chinese (city) tariff (0.215) was associated with moderate mean absolute transition scores compared with the UK (0.342), US (0.230), Japanese (0.149) and Korean (0.189) tariffs for 1485 observed pairs of the EQ-5D-3L health states. CONCLUSIONS: Health utility scores derived from the five tariffs differed. The Chinese (city) tariff was the most suitable of these tariffs and was without obvious weakness. We recommend adopting the Chinese (city) tariff when applying EQ-5D-3L to assess quality of life among the elderly in China's agricultural region with socio-economic status similar to Hua County. Results of this study had provided a crucial basis for health surveys, health promotion projects, health intervention trials, and health economic evaluation taking HRQOL as a target in rural areas of China

Oral microbiome and risk of malignant esophageal lesions in a high-risk area of China: A nested case-control study.

OBJECTIVE: We aimed to prospectively evaluate the association of oral microbiome with malignant esophageal lesions and its predictive potential as a biomarker of risk. METHODS: We conducted a case-control study nested within a population-based cohort with up to 8 visits of oral swab collection for each subject over an 11-year period in a high-risk area for esophageal cancer in China. The oral microbiome was evaluated with 16S ribosomal RNA (rRNA) gene sequencing in 428 pre-diagnostic oral specimens from 84 cases with esophageal lesions of severe squamous dysplasia and above (SDA) and 168 matched healthy controls. DESeq analysis was performed to identify taxa of differential abundance. Differential oral species together with subject characteristics were evaluated for their potential in predicting SDA risk by constructing conditional logistic regression models. RESULTS: A total of 125 taxa including 37 named species showed significantly different abundance between SDA cases and controls (all P0.84. CONCLUSIONS: The oral microbiome may play an etiological and predictive role in esophageal cancer, and it holds promise as a non-invasive early warning biomarker for risk stratification for esophageal cancer screening programs

Enhancement of anomalous boundary current by high temperature

Recently it is found that Weyl anomaly leads to novel anomalous currents in the spacetime with a boundary. However, the anomalous current is suppressed by the mass of charge carriers and the distance to the boundary, which makes it difficult to be measured. In this paper, we explore the possible mechanisms for the enhancement of anomalous currents. Interestingly, we find that the anomalous current can be significantly enhanced by the high temperature, which makes easier the experimental detection. For free theories, the anomalous current is proportional to the temperature in the high temperature limit. Note that the currents can be enhanced by thermal effects only at high temperatures. In general, this is not the case at low temperatures. For general temperatures, the absolute value of the current of Neumann boundary condition first decreases and then increases with the temperature, while the current of Dirichlet boundary condition always increases with the temperature. It should be mentioned that the enhancement does not have an anomalous nature. In fact, the so-called anomalous current in this paper is not always related to Weyl anomaly. Instead, it is an anomalous effect due to the boundary

Calibration of the thermo-hydro-mechanical parameters of the Callovo-Oxfordian claystone and the modelling of the ALC experiment

Andra performs a wide range of in-situ experiments at its Meuse/Haute-Marne Underground Research Laboratory (MHM URL). The purpose of these experiments is to study the feasibility of a radioactive waste repository in the Callovo-Oxfordian claystone formation (COx). An important research program has been conducted by Andra since 2005 to investigate THM response of the COx to a thermal load through laboratory and in situ experimentations. A step-by-step approach is followed, which starts with small scale heating boreholes (TED experiment) and extends to full-scale (ALC experiment). Modelling and interpretation of the TED and ALC experiments are conducted in the context of the Task E within the DECOVALEX-2019 framework. DECOVALEX-2019 is a multidisciplinary, co-operative international research effort focused on modelling coupled Thermal-Hydraulic-Mechanical-Chemical (THMC) processes. Based on the TED experiment measurements, the THM parameters of the COx are calibrated through a fully-coupled THM model using COMSOL. Then, the ALC experiment is successfully blind predicted and interpretatively modelled using the calibrated THM parameters of the COx and the proposed coupled THM model

Face verification using sparse representations

We propose a face verification framework using sparse representations that integrates two ways of employing spar-sity. Given an image pair (A,B) and a dictionary D, for image A(B), we generate two sparse codes, one by using the original dictionary and the other by adding B(A) into D as an augmented dictionary. Then the correlation of the sparse codes of A and B, both under the original dictio-naryD, measuring how similar the pair is, is referred to as the similarity score. The dissimilarity of the sparse codes of A(B), respectively under D and D+B(A), is referred to as the dissimilarity score. We exploit multiple feature trans-forms to obtain several scores using these two measures and fuse them by simple averaging for the situation where no training set is available or by an SVM when a training set is given. We evaluate our algorithm on the LFW dataset, where it is shown to outperform state-of-the-art methods in the unsupervised setting by a large margin and delivers very comparable performance to methods in the image restricted setting despite its simplicity. 1