Hair mercury levels in pregnant women in Mahshahr, Iran: Fish consumption as a determinant of exposure

MeHg is a well-documented neurotoxicant even at low levels of exposure. Developing brain, in particular, is vulnerable to that. Through bioaccumulating to differing degrees in various fish species, it can have serious adverse effects on the development and functioning of the human central nervous system, especially during prenatal exposure. Therefore, the purpose of this study was to investigate mercury concentration in hair samples of pregnant women living in Mahshahr located in Khuzestan province, Iran. It assessed the association between fish consumption and specific characteristics that can influence exposure. From April to June 2008, 149 pregnant women were invited to participate in this study. An interview administered questionnaire was used to collect information about age, body weight, height, fish (fresh, canned and shrimp) consumption, pregnancy stage, residence duration, education level, family income and number of dental amalgam fillings. The obtained results showed that the geometric mean and range for hair total Hg concentration was 3.52 μg/g (0.44-53.56 μg/g). About 5.4% of mothers had hair total Hg levels in excess of 10 μg/g. Maternal hair mercury level was less than threshold level of WHO (5 μg/g). As expected, there was a clear increase in hair Hg with reported fresh marine fish consumption (p = 0.04). The highest mean for hair mercury level in a group who consumed fish several times per week, was 4.93 μg/g. Moreover, a significant effect of age and residential time on Hg concentration in the hair of the women was found. Pregnant women in Mahshahr consumed large amounts of fish; consequently, most of their offspring were prenatally exposed to moderately high levels of mercury. The results found suggest that pregnant women should decrease their fish consumption.     

Intermittent swelling and shrinkage of a highly expansive soil treated with polyacrylamide

This laboratory study examines the potential use of an anionic polyacrylamide(PAM)-based material as an environmentally sustainable additive for the stabilization of an expansive soil from South Australia.The experimental program consisted of consistency limits,sediment volume,compaction and oedometer cyclic swell-shrink tests,performed using distilled water and four different PAM-to-water solutions of P_D=0.1 g/L,0.2 g/L,0.4 g/L and 0.6 g/L as the mixing liquids.Overall,the relative swelling and shrinkage strains were found to decrease with increasing number of applied swell-shrink cycles,with an‘elastic equilibrium’condition achieved on the conclusion of four cycles.The propensity for swelling/shrinkage potential reduction(for any given cycle)was found to be in favor of increasing the PAM dosage up to P_D=0.2 g/L,beyond which the excess PAM molecules self-associate as aggregates,thereby functioning as a lubricant instead of a flocculant;this critical dosage was termed‘maximum flocculation dosage’(MFD).The MFD assertion was discussed and validated using the consistency limits and sediment volume properties,both exhibiting only marginal variations beyond the identified MFD of P_D=0.2 g/L.The accumulated axial strain progressively transitioned from‘expansive’for the unamended soil to an ideal‘neutral’state at the MFD,while higher dosages demonstrated undesirable‘contractive’states.     

Value of information-based experimental design: Application to process damping in milling

This paper describes a value of information-based experimental design method that uses Bayesian inference for belief updating. The application is process damping coefficient identification in milling. An analytical process damping algorithm is used to model the prior distribution of the stability boundary (between stable and unstable cutting conditions). The prior distribution is updated using experimental results via Bayesian inference. The updated distribution of the stability boundary is used to determine the posterior process damping coefficient value. A value of information approach for experimental test point selection is then demonstrated which minimizes the number of experiments required to determine the process damping coefficient. Subsequent experimental parameters are selected such that the percent reduction in the standard deviation of the process damping coefficient is maximized. The method is validated by comparing the process damping posterior values to residual sum of squares results using a grid-based experimental design approach. Results show a significant reduction in the number of experiments required for process damping coefficient parameter determination. The advantages of using the value of information approach over the traditional design of experimental methods are discussed.     

Optimum creep feed grinding process conditions for Rene 80 supper alloy using neural network

Creep feed grinding is widely used in manufacturing supperalloy materials. These materials are usually used in aircrafts, gas turbines, rocket engines, petrochemical equipments and other high temperature applications. The objective of this paper is to model and predict the grinding forces of the creep feed grinding of these materials using the neural network. This model is then used to select the working conditions (such as depth of cut, the wheel speed and workpiece speeds) to prevent the surface burning and to maximize the material removal rate. The results show that the combined neural network and an optimization system are capable of generating optimal process parameters. The outcomes of the paper are now used to apply the optimal working conditions for grinding the turbine blades.     

Identifying the mean step change of UBM chart

The traditional control charts are developed based on the assumption that the successive observations are independent and identically distributed. In some processes, the independence assumption is violated when there is autocorrelation between observations. To solve this problem, two methods, classified as model-based and model-free, could be applied. When a control chart alarms an assignable cause, it is essential to detect the process change point in order to remove the root cause. In the presence of autocorrelated data, different methods for change-point identification have been applied only for model-based methods. Hence, this is considered as the research gap and an attempt is made to fill this gap by applying maximum likelihood function in unweighted batch mean control chart, one of the most applied model-free methods. In this article, an estimator is presented to determine the change point for the first-order autoregressive process, AR(1). When a real change occurs, the performance of proposed estimator is evaluated through simulation.     

Microscopic characterization of petiole anatomy of Asteraceous taxa of Western Himalaya-Pakistan

Petiole anatomy of 15 species of family Asteraceae was examined which aimed to investigate petiolar anatomical structures for species level identification. Shandon Microtome was used for petiole histological preparations. Both qualitative and quantitative features were studied under microscope which showed significant variation in petiole, collenchyma, parenchyma shape/size, vascular bundles arrangement/size, and vessel elements quantity. Artemisia japonica Thunb., Cirsium vulgare (Savi) Ten., Myriactis nepalensis Less., Seriphidium brevifolium Ling & Y.R.Ling, Taraxacum officinale (L.) Weber ex F.H.Wigg., and Xanthium strumarium L. showed winged petioles. Maximum length and width of upper and lower epidermis was found in Tagetes erecta L. which is 23.05 ± 0.89 μm, 24.9 ± 1.257 μm length and 21.75 ± 1.38067 μm, 22.75 ± 0.467 μm width, respectively. Petioles of Parthenium hysterophorus L. was longest one with 9.85 ± 10.45 μm while A. japonica Thunb. showed highest number of vessel elements. Maximum size of vascular bundles was found in T. erecta L. with 5.05 ± 14.25 μm. Artemisia annua L., C. vulgare (Savi) Ten, Cyanthillium cinereum (L.) H.Rob., Helianthus annus L., M. nepalensis Less., P. hysterophorus L., Senecio chrysanthemoides DC. have trichomes while Tussilago farfara L. has highest number of vascular bundles. All species have angular collenchyma type except M. nepalensis Less., P. hysterophorus L., S. brevifolium Ling & Y.R.Ling, Tagetes minuta L., T. officinale L., S. chrysanthemoides DC., and T. farfara L. Cluster analysis implemented that distinct plant species in cluster. Petiolar anatomical structures and taxonomic key will helpful for distinguishing Asteraceous taxa at genus and species level. This taxonomic significant investigation will also provide baseline to taxonomists for other Asteraceae studies and phylogenetic research.     

Multifunctional leather surface embedded with zinc oxide nanoparticles by pulsed laser ablation method

A simple procedure was used to generate and decorate leather structures with different amounts from zinc oxide (ZnO) nanoparticles to produce multifunctional leather structure by pulsed laser ablation method in liquid media based on changing the ablation time in just one-pot method. The impact of varying concentrations of ZnO nanoparticles embedded on the surface of leather on water resistance, water vapor permeability, mechanical characteristics, and UV-shielding efficiency was examined by different characterization techniques like X-ray diffraction, surface area, UV–visible spectroscopy, scanning electron microscope (SEM), energy-dispersive X-ray spectroscopy, and thermogravimetric analysis. The results showed that the combination between the external functional groups of leather with ZnO nanoparticles was discovered. ZnO nanoparticles effectively coated the surface of leather tissue, as seen by SEM images, and their form a spherical morphology. Leather with ZnO nanoparticles added had the highest capacity to kill Escherichia coli bacteria, exceeding leather without modification and ZnO nanoparticles alone in 50-hr incubation. In addition, the incubation period had a substantial impact on the suppression of Staphylococcus aureus bacteria growth by leather samples.     

Evaluating measurement and process capabilities by GR&R with four quality measures

This paper proposes a procedure for assessing a measurement system and manufacturing process capabilities using Gage Repeatability and Reproducibility (GR&R) designed experiments with four quality measures. In this procedure, a GR&R study is conducted to obtain replicate measurements on units by several different operators. The gage and part variance components are then estimated by conducting analysis of variance (ANOVA) on the GR&R measurement observations. Finally, the acceptance and rejection criteria of the precision-to-tolerance ratio (PTR), signal-to-noise ratio (SNR), discrimination ratio (DR), and process capability index (C_p or C_pk), are employed to assess the measurement and process capabilities. Three previously studied case studies are provided for illustration; in all of which the procedure provided efficient capability assessments at minimal computational and statistical efforts. In conclusion, the procedure proposed in this research using GR&R designed experiments provides valuable procedure and helpful guidelines to quality and production managers in assessing the capabilities of a measurement system and manufacturing process, and deciding the needed actions for improving performance.     

Investigation of membrane preparation condition effect on the PSD and porosity of the membranes using a novel image processing technique

A totally computerized image processing program package is developed to analyze the SEM images of membrane surface and cross‐section. Pore size distribution and porosity of the fabricated membranes are determined using the proposed image processing procedure. Furthermore, effect of coagulation bath temperature on the morphology and mechanical properties (such as tensile strength, strain break, tensile energy absorbent, and tensile stiffness) of Polysulfone (PSf) membranes are investigated. The results reveal that the mechanical properties are higher when N‐methyl‐2‐pyrrolidone (NMP) is used as solvent. Also, an increase in the coagulation bath temperature caused a monotonous increase in the mean pore size value of Dimethylformamide (DMF)‐based membranes. However, mean pore size curve has a maximum when NMP is used as solvent. Also, porosity of the fabricated membranes increased when coagulation bath temperature increased. For the NMP‐base membranes, pore's diameter was in the range of 0–5 μm. However, DMF‐based membranes have pore size value of smaller than 1 μm when the precipitation medium is kept at 8°C. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 39899.     

Plasmodium life cycle stage classification based quantification of malaria parasitaemia in thin blood smears

Visual inspection for the quantification of malaria parasitaemiain (MP) and classification of life cycle stage are hard and time taking. Even though, automated techniques for the quantification of MP and their classification are reported in the literature. However, either reported techniques are imperfect or cannot deal with special issues such as anemia and hemoglobinopathies due to clumps of red blood cells (RBCs). The focus of the current work is to examine the thin blood smear microscopic images stained with Giemsa by digital image processing techniques, grading MP on independent factors (RBCs morphology) and classification of its life cycle stage. For the classification of the life cycle of malaria parasite the k‐nearest neighbor, Naïve Bayes and multi‐class support vector machine are employed for classification based on histograms of oriented gradients and local binary pattern features. The proposed methodology is based on inductive technique, segment malaria parasites through the adaptive machine learning techniques. The quantification accuracy of RBCs is enhanced; RBCs clumps are split by analysis of concavity regions for focal points. Further, classification of infected and non‐infected RBCs has been made to grade MP precisely. The training and testing of the proposed approach on benchmark dataset with respect to ground truth data, yield 96.75% MP sensitivity and 94.59% specificity. Additionally, the proposed approach addresses the process with independent factors (RBCs morphology). Finally, it is an economical solution for MP grading in immense testing .