The relationship between exposure to polycyclic aromatic hydrocarbons and adult atopic dermatitis.

Background: Polycyclic aromatic hydrocarbons are one of the major pathogenic components in air pollution. Previous studies have demonstrated an association between air pollution and atopic dermatitis.

Objective: We sought to explore the relationship between polycyclic aromatic hydrocarbons exposure and adult atopic dermatitis.

The NCA-1 and NCA-2 Ion Channels Function Downstream of G and Rho To Regulate Locomotion in .

The heterotrimeric G protein G positively regulates neuronal activity and synaptic transmission. Previously, the Rho guanine nucleotide exchange factor Trio was identified as a direct effector of G that acts in parallel to the canonical G effector phospholipase C. Here, we examine how Trio and Rho act to stimulate neuronal activity downstream of G in the nematode Through two forward genetic screens, we identify the cation channels NCA-1 and NCA-2, orthologs of mammalian NALCN, as downstream targets of the G-Rho pathway.

Estimating spatio-temporal dynamics of stream total phosphate concentration by soft computing techniques.

This study attempts to model the spatio-temporal dynamics of total phosphate (TP) concentrations along a river for effective hydro-environmental management. We propose a systematical modeling scheme (SMS), which is an ingenious modeling process equipped with a dynamic neural network and three refined statistical methods, for reliably predicting the TP concentrations along a river simultaneously. Two different types of artificial neural network (BPNN-static neural network; NARX network-dynamic neural network) are constructed in modeling the dynamic system.

Modeling water quality in an urban river using hydrological factors--data driven approaches.

Contrasting seasonal variations occur in river flow and water quality as a result of short duration, severe intensity storms and typhoons in Taiwan. Sudden changes in river flow caused by impending extreme events may impose serious degradation on river water quality and fateful impacts on ecosystems. Water quality is measured in a monthly/quarterly scale, and therefore an estimation of water quality in a daily scale would be of good help for timely river pollution management.

Assessment of arsenic concentration in stream water using neuro fuzzy networks with factor analysis.

We propose a systematical approach to assessing arsenic concentration in a river through: important factor extraction by a nonlinear factor analysis; arsenic concentration estimation by the neuro-fuzzy network; and impact assessment of important factors on arsenic concentration by the membership degrees of the constructed neuro-fuzzy network. The arsenic-contaminated Huang Gang Creek in northern Taiwan is used as a study case. Results indicate that rainfall, nitrite nitrogen and temperature are important factors and the proposed estimation model (ANFIS(GT)) is superior to the two comparative models, in which 50% and 52% improvements in RMSE are made over ANFIS(CC) and ANFIS(all), respectively.

Reinforced two-step-ahead weight adjustment technique for online training of recurrent neural networks.

A reliable forecast of future events possesses great value. The main purpose of this paper is to propose an innovative learning technique for reinforcing the accuracy of two-step-ahead (2SA) forecasts. The real-time recurrent learning (RTRL) algorithm for recurrent neural networks (RNNs) can effectively model the dynamics of complex processes and has been used successfully in one-step-ahead forecasts for various time series.

Dictyostelium gnt15 encodes a protein with similarity to LARGE and plays an essential role in development.

LARGE is a putative glycosyltransferase found to be mutated in mice with myodystrophy or patients with congenital muscular dystrophy. By homology searches, we identified in the Dictyostelium discoideum genome four open reading frames, i.e.