A hybrid model for human factor analysis in process accidents: FBN-HFACS

Human factors are the largest contributing factors to unsafe operation of the chemical process systems. Conventional methods of human factor assessment are often static, unable to deal with data and model uncertainty, and to consider independencies among failure modes. To overcome the above limitations, this paper presents a hybrid dynamic human factor model considering Human Factor Analysis and Classification System (HFACS), intuitionistic fuzzy set theory, and Bayesian network. The model is tested on accident scenarios which have occurred in a hot tapping operation of a natural gas pipeline. The results demonstrate that poor occupational safety training, failure to implement risk management principles, and ignoring reporting unsafe conditions were the factors that contributed most failures causing accident. The potential risk-based safety measures for preventing similar accidents are discussed. The application of the model confirms its robustness in estimating impact rate (degree) of human factor induced failures, consideration of the conditional dependency, and a dynamic and flexible modelling structure.     

颗粒物分界层Mie散射激光雷达识别的sigmoid算法

基于成都市2013年6月~2015年5月期间由Mie散射激光雷达探测的大气消光系数廓线资料,发现混合层以上在颗粒物消光和分子消光之间一致存在一个S型的过渡区,利用sigmoid函数对此分布形态进行模拟,通过计算该函数上下曲率最大点所在的高度,据此提出了颗粒物分界层Mie散射激光雷达识别的sigmoid算法.针对该算法模拟效果的分析表明,颗粒物分界层过渡区附近大气消光系数理论廓线和实测廓线保持了高度的相关性,二者在春夏秋冬四季的相关系数（R）分别为0.9971±0.0052、0.9935±0.0167、0.9979±0.0038和0.9990±0.0021（均通过α=0.05的显著性检验）.基于sigmoid算法计算的颗粒物分界层过渡区与成都市温江站探空资料得到的逆温层之间存在很好的对应关系.     

Peri- and paracentric inversions in chromosome 12: Prenatal diagnosis and family study

Three different types of chromosome 12 inversion were seen in 15 individuals out of 44 individuals examined in one 8 generation family. Type 1: a pericentric inversion inv(12) (p112; q131) was found in 7 individuals and twice at prenatal diagnosis. Type 2: a paracentric inversion inv(12) (p123; p131) was seen in two individuals. Two individuals carried both inversion chromosomes, namely type 1 and type 2. The two inversion chromosomes were transmitted from each of the parents. Type 3: a double pericentric and paracentric inversion (type 3) inv(12) (p123; p131) (p112; q131) was observed in the daughter of one of the carriers of type 1 and 2 inversions and again at prenatal diagnosis in her son. The double inversion most likely arose through crossing-over in between the two inversion loops. A balanced translocation t(7; 13) and the inversion type 1 was observed in one individual, who transmitted the translocation only to an offspring. The frequency of inversions in amniotic fluid cells observed in our laboratory was 1·9 per cent. The clinical implications of these findings are discussed.     

Sex‐specific and dose‐response relationships of urinary cobalt and molybdenum levels with glucose levels and insulin resistance in U.S. adults

Growing studies have linked metal exposure to diabetes risk. However, these studies had inconsistent results. We used a multiple linear regression model to investigate the sex-specific and dose-response associations between urinary metals (cobalt (Co) and molybdenum (Mo)) and diabetes-related indicators (fasting plasma glucose (FPG), hemoglobin A1c (HbA1c), homeostasis model assessment for insulin resistance (HOMA-IR), and insulin) in a cross-sectional study based on the United States National Health and Nutrition Examination Survey. The urinary metal concentrations of 1423 eligible individuals were stratified on the basis of the quartile distribution. Our results showed that the urinary Co level in males at the fourth quartile (Q4) was strongly correlated with increased FPG (β = 0.61, 95% CI: 0.17–1.04), HbA1c (β = 0.31, 95% CI: 0.09–0.54), insulin (β = 8.18, 95% CI: 2.84–13.52), and HOMA–IR (β = 3.42, 95% CI: 1.40–5.44) when compared with first quartile (Q1). High urinary Mo levels (Q4 vs. Q1) were associated with elevated FPG (β = 0.46, 95% CI: 0.17–0.75) and HbA1c (β = 0.27, 95% CI: 0.11–0.42) in the overall population. Positive linear dose-response associations were observed between urinary Co and insulin (P_nonlinear = 0.513) and HOMA–IR (P_nonlinear = 0.736) in males, as well as a positive linear dose-response relationship between urinary Mo and FPG (P_nonlinear = 0.826) and HbA1c (P_nonlinear = 0.376) in the overall population. Significant sex-specific and dose-response relationships were observed between urinary metals (Co and Mo) and diabetes-related indicators, and the potential mechanisms should be further investigated.     

Antenatal diagnosis of a de novo paracentric inversion of chromosome 11

A de novo paracentric inversion of chromosome 11 identified through antenatal diagnosis is described along with long-term follow-up information on the child and discussion of reported experiences with de novo inversions.     

逆温天气与鄂尔多斯高原中小城镇大气污染

本文根据鄂尔多斯高原逆温天气的形成，讨论了高原地区中小城镇大气污染的时空分布及控制污染的可行性途径。     

Application of Bayesian regularized BP neural network model for analysis of aquatic ecological data-A case study of chlorophyll-a prediction in Nanzui water area of Dongting Lake

Bayesian regularized BP neural network（BRBPNN） technique was applied in the chlorophyll-α prediction of Nanzui water area in Dongting Lake. Through BP network interpolation method, the input and output samples of the network were obtained. After the selection of input variables using stepwise/multiple linear regression method in SPSS i1.0 software, the BRBPNN model was established between chlorophyll-α and environmental parameters, biological parameters. The achieved optimal network structure was 3-11-1 with the correlation coefficients and the mean square errors for the training set and the test set as 0.999 and 0.000？8426, 0.981 and 0.0216 respectively. The sum of square weights between each input neuron and the hidden layer of optimal BRBPNN models of different structures indicated that the effect of individual input parameter on chlorophyll- α declined in the order of alga amount 〉 secchi disc depth（SD） 〉 electrical conductivity （EC）. Additionally, it also demonstrated that the contributions of these three factors were the maximal for the change of chlorophyll-α concentration, total phosphorus（TP） and total nitrogen（TN） were the minimal. All the results showed that BRBPNN model was capable of automated regularization parameter selection and thus it may ensure the excellent generation ability and robustness. Thus, this study laid the foundation for the application of BRBPNN model in the analysis of aquatic ecological data（chlorophyll-α prediction） and the explanation about the effective eutrophication treatment measures for Nanzui water area in Dongting Lake.     

TEMPORAL CHANGES IN THE YADKIN RIVER FLOW VERSUS SUSPENDED SEDIMENT CONCENTRATION RELATIONSHIP1

ABSTRACT: Dynamic linear models (DLM) and seasonal trend decomposition (STL) using local regression, or LOESS, were used to analyze the 50‐year time series of suspended sediment concentrations for the Yadkin River, measured at the U.S. Geological Survey station at Yadkin College, North Carolina. A DLM with constant trend, seasonality, and a log₁₀ streamflow regressor provided the best model to predict monthly mean log₁₀ suspended sediment concentrations, based on the forecast log likelihood. Using DLM, there was evidence (odds approximately 69:1) that the log₁₀ streamflow versus log₁₀ suspended sediment concentration relationship has changed, with an approximate 20 percent increase in the log₁₀ streamflow coefficient over the period 1981 to 1996. However, sediment concentrations in the Yadkin River have decreased during the decade of the 1990s, which has been accompanied by a concomitant increase in streamflow variability. Although STL has been shown to be a versatile trend analysis technique, DLM is shown to be more suitable for discovery and inference of structural changes (trends) in the model coefficient describing the relationship between flow and sediment concentration.     

Using long-term data for a reintroduced population to empirically estimate future consequences of inbreeding

Inbreeding depression is an important long-term threat to reintroduced populations. However, the strength of inbreeding depression is difficult to estimate in wild populations because pedigree data are inevitably incomplete and because good data are needed on survival and reproduction. Predicting future population consequences is especially difficult because this also requires projecting future inbreeding levels and their impacts on long-term population dynamics, which are subject to many uncertainties. We illustrate how such projections can be derived through Bayesian state-space modeling methods based on a 26-year data set for North Island Robins (Petroica longipes) reintroduced to Tiritiri Matangi Island in 1992. We used pedigree data to model increases in the average inbreeding level (F ) over time based on kinship of possible breeding pairs and to estimate empirically N_e/N (effective/census population size). We used multiple imputation to model the unknown components of inbreeding coefficients, which allowed us to estimate effects of inbreeding on survival for all 1458 birds in the data set while modeling density dependence and environmental stochasticity. This modeling indicated that inbreeding reduced juvenile survival (1.83 lethal equivalents [SE 0.81]) and may have reduced subsequent adult survival (0.44 lethal equivalents [0.81]) but had no apparent effect on numbers of fledglings produced. Average inbreeding level increased to 0.10 (SE 0.001) as the population grew from 33 (0.3) to 160 (6) individuals over the 25 years, giving a ratio of 0.56 (0.01). Based on a model that also incorporated habitat regeneration, the population was projected to reach a maximum of 331–1144 birds (median 726) in 2130, then to begin a slow decline. Without inbreeding, the population would be expected stabilize at 887–1465 birds (median 1131). Such analysis, therefore, makes it possible to empirically derive the information needed for rational decisions about inbreeding management while accounting for multiple sources of uncertainty.     

Tracking a half century of media reporting on gray wolves

Natural resource and wildlife managers must balance the disparate priorities of a diversity of stakeholders. To manage these priorities, a firm understanding of topics salient to the public is needed. The media often report on issues of importance to the public; therefore, these reports may be a useful measure of public interest. However, efficient methods for distinguishing diverse topics related to a wildlife management issue reported in the media and changes in the salience of those topics have been lacking. We used latent Dirichlet allocation, a Bayesian mixture model, to quantitatively assess the salience of topics surrounding the gray wolf (Canis lupus), which was reintroduced to Idaho (U.S.A.) in 1995. We analyzed articles published from 1960 to 2015 in an Idaho newspaper. We identified 6 distinct topics associated with gray wolves: policy, hunting, biological status, implementation of management, recovery, and human-wolf conflict. The salience of topics pre- and postreintroduction of wolves (1995) and pre- and postdelisting of wolves from the U.S. Endangered Species Act (2009) differed significantly, underscoring that these events were turning points in how issues were being publicly discussed and framed. Articles written by the local reporters were more likely to report on topics regarding conflict between humans and wolves, whereas articles sourced from a national outlet reported more on topics pertaining to wolf policy and biological status. In the context of managing a contentious, far-ranging, and long-lived wildlife species, our methods can help guide the location and timing of a suite of management strategies (e.g., media relation plans and stakeholder engagement) that promote human-wildlife coexistence across different landscapes.