Analysis and Assessment of Essential Toxic Heavy Metals, PH and EC in Ishaqi River and Adjacent Soil

This research was conducted to determine content levels of heavy metal pollution.  Samples taken from Ishaqi River bank and adjacent agricultural soils area, in ten sites, distributed along 48 km of the Ishaqi River, north Baghdad. The evaluated metals were Zinc, Copper, Manganese, Iron, Cobalt, Nickel, Chromium, Cadmium, Vanadium and Lead. PH and Electric Conductivity (EC) were measured to evaluate the acidity and (EC). Results showed that most site were contaminated with metals evaluated. Among these metals, Zn, Mn, Fe and Ni were consistently higher in all the samples (both river bank and adjacent soil) followed by PB, CU, V, Cd, Co and Cr. The level concentrations of river bank were almost higher than that of adjacent soil. As will be reported later, the concentrations of Nickel, Zinc, Manganese and Iron in river bank and agricultural adjacent soil were over the permissible levels. The average mean levels were (Ni 66.36 mg/kg, Zn 42.59 mg/kg, Mn 26.78 mg/kg, Fe 25.15 mg/kg) in river bank and (Ni 46.31 mg/kg, Zn 33.06 mg/kg, Mn 20.78 mg/kg Fe 16.28 mg/kg) in agricultural adjacent soil. Overall, Nickel had the highest concentrations in the ecosystem. Keywords: heavy metals, environmental pollution, river bank, adjacent soil, AAS

Lead, Nickel, Copper, Cadmium and Zinc concentrations in airborne particulates and Lead in Blood, in Al- Tarmiayh city, north Baghdad-Iraq

The concentrations of lead, nickel, copper, cadmium and zinc in airborne particulates and lead in blood, have been measured in the area of Tarmiya, during a period of one year 2011.The air pollution levels caused by these elements are still in somehow comparatively medium or low. Concerning the Pb concentrations in blood from different groups of individuals, the levels do not exceed the safe limits. And we distinguish the groups of elements and stations by using multidimensional scaling (MDS)

Tracing and Analysis of Manganese, Nickel, Cadmium ,Copper, zinc , Lead And Aluminum Concentration and PH Values In Iraqi Chewing Gums

Evaluation of trace elements in Iraqi chewing gums are unavailable, particularly pollution of toxic elements, materials which change the values of PH in the Oral. Atomic Absorption Spectroscopy (AAS) were successfully employed to determine the concentration of 7 trace elements (essentially toxic and nonessential) and the PH, in thirteen different brands of chewing gum generally consumed in Iraq. Combined wet and dry digestion procedures were applied. Two types of heated graphite tubes were used, coated and uncoated tubes treated with tungsten solution. Result showed that Cu, Al and Zn were at very high levels in almost all brands whereas Mn was found to be high in brands A and O only. Keywords: Trace metals – heavy elements, Chewing gums - AAS-  Baghdad – Iraq

Bayes Estimators for the Parameter of the Inverted Exponential Distribution under Symmetric and Asymmetric Loss Functions

This paper is devoted to discuss Bayes method to estimate the unknown scale parameter of the inverted exponential distribution along with the maximum likelihood method. Bayes estimators are obtained under symmetric "squared error" and asymmetric "precautionary" loss functions corresponding to informative "inverted gamma and Gumbel type II" and non-informative "Jeffrey and extension of Jeffrey" priors. The obtained Bayes estimators along with the maximum likelihood estimator are compared empirically for different cases and sample sizes using Monte-Carlo simulation method in terms of two statistical criteria which are mean squared error (MSE) and mean absolute percentage error (MAPE). Among the set of conclusions that have been reached, it is observed that, conjugate inverted gamma prior with hyper-parameters  and  record full appearance as best prior depending on the value of the parameter of inverted exponential distribution. Keywords: Inverted exponential distribution; maximum likelihood estimator; Bayes estimator; informative prior; non-informative prior; squared error loss function; precautionary loss function; mean squared error; mean absolute percentage error

Non-Bayes, Bayes and Empirical Bayes Estimators for the Shape Parameter of Lomax Distribution

Point estimation is one of the core topics in mathematical statistics. In this paper we consider the most common methods of point estimation: non-Bayes, Bayes and empirical Bayes methods to estimate the shape parameter of Lomax distribution based on complete data. The maximum likelihood, moment and uniformly minimum variance unbiased estimators are obtained as non-Bayes estimators. Bayes and empirical Bayes estimators are obtained corresponding to three informative priors "gamma, chi-square and inverted Levy" based on symmetric "squared error" and asymmetric "LINEX and general entropy" loss functions. The estimates of the shape parameter were compared empirically via Monte Carlo simulation study based upon the mean squared error. Among the set of conclusions that have been reached, it is observed that, for all sample sizes and different cases, the performance of uniformly minimum variance unbiased estimator is better than other non-Bayes estimators. Further that, Monte Carlo simulation results indicate that the performance of Bayes and empirical Bayes estimator in some cases are better than non-Bayes for some appropriate of prior distribution, loss function, values of parameters and sample size. Keywords: Lomax distribution; maximum likelihood estimator; moment estimator; uniformly minimum variance unbiased estimator; Bayes estimator; empirical Bayes estimator; informative prior; squared error loss function; LINEX  loss  function;  general  entropy  loss  function;  mean  squared  error

Model of Robust Regression with Parametric and Nonparametric Methods

In the present work, we evaluate the performance of the classical parametric estimation method "ordinary least squares" with the classical nonparametric estimation methods, some robust estimation methods and two suggested methods for conditions in which varying degrees and directions of outliers are presented in the observed data. The study addresses the problem via computer simulation methods. In order to cover the effects of various situations of outliers on the simple linear regression model, samples were classified into four cases (no outliers, outliers in the X-direction, outliers in the Y-direction and outliers in the XY-direction) and the percentages of outliers are varied between 10%, 20% and 30%. The performances of estimators are evaluated in respect to their mean squares error and relative mean squares error. Keywords: Simple Linear Regression model; Ordinary Least Squares Method; Nonparametric Regression; Robust Regression; Least Absolute Deviations Regression; M-Estimation Regression; Trimmed Least Squares Regression

Some Estimation Methods for the Shape Parameter and Reliability Function of Burr Type XII Distribution / Comparison Study

Burr type XII distribution plays an important role in reliability modeling, risk analyzing and process capability estimation. The choice of the best estimation method is one of the goals in estimating parameters of the distribution. The main aim of this paper is to obtain and compare the classical "maximum likelihood and uniformly minimum variance unbiased" estimators and the Bayesian estimators of the shape parameter, ???? and reliability function based on a complete sample when the other shape parameter, ? known. The Bayes estimators are obtained under non-informative priors "Jeffrey’s prior, modified and extension of Jeffrey’s prior" as well as under informative gamma prior based on different symmetric and asymmetric loss functions "squared error, quadratic, LINEX, precautionary and entropy". The Monte Carlo experiment was performed under a wide range of cases and sample size. The estimates of the unknown shape parameter were compared by employing the mean square errors and the estimates of reliability function were compared by employing the integrated mean squared error.   Keywords: Burr type XII distribution; Maximum likelihood estimator; Uniformly Minimum Variance Unbiased estimator; Bayes estimators; non-informative Prior; informative Prior; Squared error loss function; quadratic loss function; LINEX loss function; Precautionary loss function; Entropy Loss function; Mean squared error; integrated mean squared error

Robust regression type estimators to determine the population mean under simple and two-stage random sampling techniques

For the estimation of population mean, there are several ratio and regression type estimators available in literature. However, they can be misleadingto contain the desired results when data are contaminated by outliers. Inrecent past, Zaman and Bulut (2019a) provided the solution of this issueby utilizing some robust regression tools and develop a class of ratio typeestimators under simple random sampling scheme. To extending their work,Zaman (2019) has suggested another class of estimators but this time usingratio technique. In this paper, we proposed a new class of robust regression type estimators with utilizing LAD, LMS, LTS, Huber-M, Hampel-M,Tukey-M, Huber-MM as robust regression tools. The desired class is subsequently extended for two stage sampling, where mean of the study variableis not available at first stage. Also, we have developed some reviewed andproposed estimators under above mentioned sampling technique. Further,we have divided our supposition into two cases as: (i)- when drawn a second stage sample depends upon first stage sample and, (ii)- when drawn asecond stage sample is independent of first stage sample. The mean squareexpressions of the proposed estimators have been determined through Taylor series expansion. A real life application and the simulation study are alsoprovided to assess existing and proposed estimators. In the light of numericalillustration, we see that our proposed estimators give more efficient resultsthan the reviewed ones

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London