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Phthalates are widely used in industry, personal care products, and medications. Recent studies have suggested that phthalate exposure alters thyroid hormones. However, longitudinal studies concerning the association between phthalate exposure and thyroid function in children are scant. Therefore, we examined the association between pre- and postnatal phthalate exposure and thyroid function in children born in 2000-2001.We studied 181 mother-child pairs in central Taiwan and followed-up the children from 2000 to 2009 at 2, 5, and 8 years old. We measured serum levels of thyroxine (T4), free T4, triiodothyronine (T3), and thyroid-stimulating hormone in children by using radioimmunoassay. We quantified seven phthalate metabolites, representing the five most commonly used phthalates, in maternal and child urine samples by using liquid chromatography-tandem mass spectrometry. The metabolites were monoethylhexyl phthalate (MEHP), mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP) derived from di(2-ethylhexyl) phthalate (DEHP), monomethyl phthalate (MMP), monoethyl phthalate (MEP), monobutyl phthalate (MBP), and monobenzyl phthalate (MBzP). We constructed a linear mixed model to examine these associations after adjustments for covariates.The T4 levels were inversely associated with maternal urinary MEHHP (β = -0.028 [95% confidence interval (CI) = -0.051, -0.006]) and MEOHP (β = -0.027 [-0.050, -0.003]), with similar T3 levels being observed in boys, even when the children exposure levels were considered spontaneously. In the girls, the free T4 levels were inversely associated with levels of maternal urinary MEP (β = -0.042), maternal urinary MBzP (β = -0.050), and children's urinary MEHP (β = -0.027).Early life phthalate exposure was associated with decreased thyroid hormone levels in young children.

Foundry FAB manufactures a variety of semiconductor products with adverse mixture of process flows. For process control, it is a challenge to define some critical dimension measurement items target of each unique product characteristic before new tape out (NTO). After some wafers pilot run completed, a proper measurement target was defined. The engineers have to waste valuable resources for measurement retargeting and expense extra process time to validate these changes satisfied.As we know, the mask layout pattern density (PD) has highly correlated with measurement target. However, traditional regression model results can not satisfy advanced processes requirements. In this study, we proposed new factors, including local pattern density, line density and traditional global pattern density (GPD) into model. Furthermore, the regression model was refined with machine learning, k-NN (k-th Near Neighbor), to enhance the prediction accuracy for NTO measurement target. The simulation result showed average prediction accuracy come up to 85% above, compared with previous 61% only. Even some layers accuracy achieved 95% above.

A sequence of jackknife estimators is developed to estimate the number of shared species in two communities. The estimators have simple and explicit formulae. A sequential testing criterion is also developed to determine a proper order for these jackknife estimators. The performance of the estimators is evaluated using empirical data on two forests from Malaysia, where 209 shared species present in both forests, and using simulated data. Results for the empirical data and simulated scenarios (for sampling fraction ranging from 0.5 to 20 %) show that the jackknife estimator, compared with other existing estimators, has a smaller bias and provides more reliable interval estimation in most cases. Additionally, two avian datasets from Taiwan and Hong Kong are used to demonstrate the proposed method. To extend the proposed method to three communities, we also list the first six orders of the jackknife estimators explicitly.

Background Phthalate diesters are commonly used and have been well established as environmental endocrine disruptors. However, few studies have examined their effects on sex steroid hormones in children. We followed children over time to examine the association between pre- and post-natal phthalate exposure and sex steroid hormone levels at 2, 5, 8, and 11 years of age. Methods We recruited 430 pregnant women from central Taiwan from 2000 to 2001 and assessed their children at birth, 2, 5, 8, and 11 years of age. We studies children with at least one measurement for both phthalate and hormone levels during each any of the follow-up time point (n = 193). Estradiol, free testosterone, testosterone, and progesterone were measured from venous blood. Three monoesters of di-2-ethylhexyl phthalate (DEHP), mono-benzyl phthalate, mono-n-butyl phthalate, mono-ethyl phthalate, and mono-methyl phthalate were measured in maternal urine collected during the 3rd trimester and child urine collected at each follow-up point. The sum of mono-2-ethylhexyl phthalate (∑MEHP) was calculated by summing the concentrations of the three DEHP monoesters. Generalized estimating equation regression analysis with repeated measures was used to estimate associations between phthalate metabolites and hormone levels. Results After adjustment for potential confounders, maternal ∑MEHP level was associated with decreased levels of progesterone in girls (β = −0.309 p = 0.001). The child ∑MEHP concentration was associated with decreased levels of progesterone for girls (β = −0.194, p = 0.003) and with decreased levels of free testosterone for boys (β = −0.124, p = 0.004). Conclusions Early-life DEHP exposure may alter sex steroid hormones of children over time, which may pose potential reproductive health risks., Highlights • Prenatal phthalate exposure was associated with decreased PG levels in girls. • Postnatal DEHP exposure was related to decreased free TT in boys and PG in girls. • Use of phthalate-containing products in developing children should be limited.

Background: Epidemiological studies concerning the relations of exposure to phthalates, thyroid function and cognitive function among children could be limited. Objectives: We conducted the longitu...

We aim to use 12 channel filter array spectrum sensor for monitor's CIE tristimulus color sensing. Although low-cost RGB color sensors are available for monitor's color sensing, however their spectral response functions are usually different from the CIE XYZ color matching functions, and hence cannot deliver an accurate color sensing. Alternatively, our proposed filter array spectrum sensor using plasmonic filter technology can supply a low-cost and highly accurate solution. In this work, partial least squares (PLS) and nonlinear iterative partial least squares (NIPLS) are adopted to associate 12 sensor outputs to the CIE XYZ values. Preliminary experimental results show Δxy = 0.0023 has been achieved by this proposed approach.