Gas bubbles investigation in contaminated water using optical tomography based on independent component analysis method

This paper presents the results of concentration profiles for gas bubble flow in a vertical pipeline containing contaminated water using an optical tomography system. The concentration profiles for the bubble flow quantities are investigated under five different flows conditions, a single bubble, double bubbles, 25% of air opening, 50% of air opening, and 100% of air opening flow rates where a valve is used to control the gas flow in the vertical pipeline. The system is aided by the independent component analysis (ICA) algorithm to reconstruct the concentration profiles of the liquid-gas flow. The behaviour of the gas bubbles was investigated in contaminated water in which the water sample was prepared by adding 25 mL of colour ingredients to 3 liters of pure water. The result shows that the application of ICA has enabled the system to detect the presence of gas bubbles in contaminated water. This information provides vital information on the flow inside the pipe and hence could be very significant in increasing the efficiency of the process industries

Estimation of turbidity in water treatment plant using hammerstein-wiener and neural network technique

Turbidity is a measure of water quality. Excessive turbidity poses a threat to health and causes pollution. Most of the available mathematical models of water treatment plants do not capture turbidity. A reliable model is essential for effective removal of turbidity in the water treatment plant. This paper presents a comparison of Hammerstein Wiener and neural network technique for estimating of turbidity in water treatment plant. The models were validated using an experimental data from Tamburawa water treatment plant in Kano, Nigeria. Simulation results demonstrated that the neural network model outperformed the Hammerstein-Wiener model in estimating the turbidity. The neural network model may serve as a valuable tool for predicting the turbidity in the plant

Forecasting of global solar radiation using anfis and armax techniques

Procurement of measuring device, maintenance cost coupled with calibration of the instrument contributed to the difficulty in forecasting of global solar radiation in underdeveloped countries. Most of the available regressional and mathematical models do not capture well the behavior of the global solar radiation. This paper presents the comparison of Adaptive Neuro Fuzzy Inference System (ANFIS) and Autoregressive Moving Average with eXogenous term (ARMAX) in forecasting global solar radiation. Full-Scale (experimental) data of Nigerian metrological agency, Sultan Abubakar III international airport Sokoto was used to validate the models. The simulation results demonstrated that the ANFIS model having achieved MAPE of 5.34% outperformed the ARMAX model. The ANFIS could be a valuable tool for forecasting the global solar radiation

Risdiplam in Type 1 Spinal Muscular Atrophy

BACKGROUND: Type 1 spinal muscular atrophy is a rare, progressive neuromuscular disease that is caused by low levels of functional survival of motor neuron (SMN) protein. Risdiplam is an orally administered, small molecule that modifies SMN2 pre-messenger RNA splicing and increases levels of functional SMN protein. METHODS: We report the results of part 1 of a two-part, phase 2-3, open-label study of risdiplam in infants 1 to 7 months of age who had type 1 spinal muscular atrophy, which is characterized by the infant not attaining the ability to sit without support. Primary outcomes were safety, pharmacokinetics, pharmacodynamics (including the blood SMN protein concentration), and the selection of the risdiplam dose for part 2 of the study. Exploratory outcomes included the ability to sit without support for at least 5 seconds. RESULTS: A total of 21 infants were enrolled. Four infants were in a low-dose cohort and were treated with a final dose at month 12 of 0.08 mg of risdiplam per kilogram of body weight per day, and 17 were in a high-dose cohort and were treated with a final dose at month 12 of 0.2 mg per kilogram per day. The baseline median SMN protein concentrations in blood were 1.31 ng per milliliter in the low-dose cohort and 2.54 ng per milliliter in the high-dose cohort; at 12 months, the median values increased to 3.05 ng per milliliter and 5.66 ng per milliliter, respectively, which represented a median of 3.0 times and 1.9 times the baseline values in the low-dose and high-dose cohorts, respectively. Serious adverse events included pneumonia, respiratory tract infection, and acute respiratory failure. At the time of this publication, 4 infants had died of respiratory complications. Seven infants in the high-dose cohort and no infants in the low-dose cohort were able to sit without support for at least 5 seconds. The higher dose of risdiplam (0.2 mg per kilogram per day) was selected for part 2 of the study. CONCLUSIONS: In infants with type 1 spinal muscular atrophy, treatment with oral risdiplam led to an increased expression of functional SMN protein in the blood. (Funded by F. Hoffmann-La Roche; ClinicalTrials.gov number, NCT02913482.)

Growth factor concentrations and their placental mRNA expression are modulated in gestational diabetes mellitus: possible interactions with macrosomia

<p>Abstract</p> <p>Background</p> <p>Gestational diabetes mellitus (GDM) is a form of diabetes that occurs during pregnancy. GDM is a well known risk factor for foetal overgrowth, termed macrosomia which is influenced by maternal hypergycemia and endocrine status through placental circulation. The study was undertaken to investigate the implication of growth factors and their receptors in GDM and macrosomia, and to discuss the role of the materno-foeto-placental axis in the <it>in-utero </it>regulation of foetal growth.</p> <p>Methods</p> <p>30 women with GDM and their 30 macrosomic babies (4.75 ± 0.15 kg), and 30 healthy age-matched pregnant women and their 30 newborns (3.50 ± 0.10 kg) were recruited in the present study. Serum concentrations of GH and growth factors, <it>i.e</it>., IGF-I, IGF-BP3, FGF-2, EGF and PDGF-B were determined by ELISA. The expression of mRNA encoding for GH, IGF-I, IGF-BP3, FGF-2, PDGF-B and EGF, and their receptors, <it>i.e</it>., GHR, IGF-IR, FGF-2R, EGFR and PDGFR-β were quantified by using RT-qPCR.</p> <p>Results</p> <p>The serum concentrations of IGF-I, IGF-BP3, EGF, FGF-2 and PDGF-B were higher in GDM women and their macrosomic babies as compared to their respective controls. The placental mRNA expression of the growth factors was either upregulated (FGF-2 or PDGF-B) or remained unaltered (IGF-I and EGF) in the placenta of GDM women. The mRNA expression of three growth factor receptors, <it>i.e</it>., IGF-IR, EGFR and PDGFR-β, was upregulated in the placenta of GDM women. Interestingly, serum concentrations of GH were downregulated in the GDM women and their macrosomic offspring. Besides, the expression of mRNAs encoding for GHR was higher, but that encoding for GH was lower, in the placenta of GDM women than control women.</p> <p>Conclusions</p> <p>Our results demonstrate that growth factors might be implicated in GDM and, in part, in the pathology of macrosomia via materno-foeto-placental axis.</p