Statistical assessment for performance of Al-Mussaib drinking water treatment plant at the year 2020

Assessment of water quality is a major step in the water industry to ensure the suitability of water for human use. In this study, statistically evaluate the quality of raw and treated drinking water of the Al-Mussaib drinking water treatment plant, Babylon city, Iraq, from January to December 2020. Additionally, the water quality of treated water was assessed according to World Health Organization (WHO) and Iraqi standards for drinking water. The results showed the plant has a good efficiency in removing the studied parameters, such as alkaline, calcium and hardness. It is noteworthy to mention that although the measured concentrations/levels met the WHO and Iraqi standards, they were higher than the favourable limits. For example, the measured sulphate concentration in the produced water was 248 mg/L which is higher than the favourable concentration (200 mg/L) (WHO). The statistical analysis indicated significant differences between the quality of raw and treated water (p-value 0.05) in terms of alkalinity, pH, calcium and sulphates concentrations. The results of this work could be useful for water authorities and decision-makers in Iraq and national and international environmental agencies

Hybridised Artificial Neural Network model with Slime Mould Algorithm: A novel methodology for prediction urban stochastic water demand

Urban water demand prediction based on climate change is always challenging for water utilities because of the uncertainty which results from a sudden rise in water demand due to stochastic patterns of climatic factors. For this purpose, a novel combined methodology including, firstly, data pre-processing techniques were employed to decompose the time series of water and climatic factors by using Empirical Mode Decomposition and identifying the best model input via tolerance to avoid multi-collinearity. Second, the Artificial Neural Network (ANN) model was optimised by an up-to-date Slime Mould Algorithm (SMA-ANN) to predict the medium term of the stochastic signal of monthly urban water demand. Ten climatic factors over 16 years were used to simulate the stochastic signal of water demand. The results reveal that SMA outperforms Multi-Verse Optimiser and Backtracking Search Algorithm based on error scale. The performance of the hybrid model SMA-ANN is better than ANN (stand-alone) based on the range of statistical criteria. Generally, this methodology yields accurate results with a coefficient of determination of 0.9 and a mean absolute relative error of 0.001. This study can assist local water managers to efficiently manage the present water system and plan extensions to accommodate the increasing water demand

Assessing the Potential of Hybrid-Based Metaheuristic Algorithms Integrated with ANNs for Accurate Reference Evapotranspiration Forecasting

Evapotranspiration (ETo) is one of the most important processes in the hydrologic cycle, with specific application to sustainable water resource management. As such, this study aims to evaluate the predictive ability of a novel method for monthly ETo estimation, using a hybrid model comprising data pre-processing and an artificial neural network (ANN), integrated with the hybrid particle swarm optimisation–grey wolf optimiser algorithm (PSOGWO). Monthly data from Al-Kut City, Iraq, over the period 1990 to 2020, were used for model training, testing, and validation. The predictive accuracy of the proposed model was compared with other cutting-edge algorithms, including the slime mould algorithm (SMA), the marine predators algorithm (MPA), and the constriction coefficient-based particle swarm optimisation and chaotic gravitational search algorithm (CPSOCGSA). A number of graphical methods and statistical criteria were used to evaluate the models, including root mean squared error (RMSE), Nash–Sutcliffe model efficiency (NSE), coefficient of determination (R2), maximum absolute error (MAE), and normalised mean standard error (NMSE). The results revealed that all the models are efficient, with high simulation levels. The PSOGWO–ANN model is slightly better than the other approaches, with an R2 = 0.977, MAE = 0.1445, and RMSE = 0.078. Due to its high predictive accuracy and low error, the proposed hybrid model can be considered a promising technique

Assessing the Benefits of Nature-Inspired Algorithms for the Parameterisation of ANN in the Prediction of Water Demand

Accurate forecasting techniques for a stochastic pattern of water demand are essential for any city that faces high variability in climate factors and a shortage of water resources. This is the first research that assesses the impact of climatic factors on urban water demand in Iraq, which is one of the hottest countries in the world. We present a novel forecasting methodology that includes data preprocessing and an artificial neural network (ANN) model, which is integrated by a recently nature-inspired metaheuristic algorithm (marine predators algorithm (MPA)). The MPA-ANN algorithm will be compared with four different nature-inspired metaheuristic algorithms. Nine climatic factors were examined with different scenarios to simulate the monthly stochastic urban water demand over eleven years for Baghdad City, Iraq. The results reveal that: 1) precipitation, solar radiation, and dew point temperature are the most relevant factors to develop the models. 2) The ANN model becomes more accurate when it is used in combination with the MPA. 3) This methodology can accurately forecast the water demand considering the variability in climatic factors. These findings are of considerable significance to water utilities to plan, review, and compare the availability of freshwater resources and increase water requests (i.e., adaptation variability of climatic factors)

The 5-HTTLPR polymorphism of the serotonin transporter gene and short term behavioral response to methylphenidate in children with ADHD

<p>Abstract</p> <p>Background</p> <p>Animal models of ADHD suggest that the paradoxical calming effect of methylphenidate on motor activity could be mediated through its action on serotonin transmission. In this study, we have investigated the relationship between the 5-HTTLPR polymorphism in the serotonin transporter gene (<it>SLC6A4</it>) and the response of ADHD relevant behaviors with methylphenidate treatment.</p> <p>Methods</p> <p>Patients between ages 6-12 (n = 157) were assessed with regard to their behavioral response to methylphenidate (0.5 mg/kg/day) using a 2-week prospective within-subject, placebo-controlled (crossover) trial. The children were then genotyped with regard to the triallelic 5-HTTLPR polymorphism in the <it>SLC6A4 </it>gene. Main outcome measure: Conners' Global Index for parents (CGI-Parents) and teachers (CGI-Teachers) at baseline and at the end of each week of treatment with placebo and methylphenidate. For both outcome measurements, we used a mixed model analysis of variance to determine gene, treatment and gene × treatment interaction effects.</p> <p>Results</p> <p>Mixed model analysis of variance revealed a gene × treatment interaction for CGI-Parents but not for CGI-Teachers. Children homozygous for the lower expressing alleles (<it>s+l_G= s'</it>) responded well to placebo and did not derive additional improvement with methylphenidate compared to children carrying a higher expressing allele (<it>l_A</it>). No genotype main effects on either CGI-Parents or CGI-teachers were observed.</p> <p>Conclusions</p> <p>A double blind placebo-controlled design was used to assess the behavioral effects of methylphenidate in relation to the triallelic 5-HTTLPR polymorphism of the <it>SLC6A4 </it>gene in children with ADHD. This polymorphism appears to modulate the behavioral response to methylphenidate in children with ADHD as assessed in the home environment by parents. Further investigation is needed to assess the clinical implications of this finding.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov NCT00483106</p

Catechol-O-Methyltransferase (COMT) Val(108/158 )Met polymorphism does not modulate executive function in children with ADHD

BACKGROUND: An association has been observed between the catechol-O-methyltransferase (COMT) gene, the predominant means of catecholamine catabolism within the prefrontal cortex (PFC), and neuropsychological task performance in healthy and schizophrenic adults. Since several of the cognitive functions typically deficient in children with Attention Deficit Hyperactivity Disorder (ADHD) are mediated by prefrontal dopamine (DA) mechanisms, we investigated the relationship between a functional polymorphism of the COMT gene and neuropsychological task performance in these children. METHODS: The Val(108/158 )Met polymorphism of the COMT gene was genotyped in 118 children with ADHD (DSM-IV). The Wisconsin Card Sorting Test (WCST), Tower of London (TOL), and Self-Ordered Pointing Task (SOPT) were employed to evaluate executive functions. Neuropsychological task performance was compared across genotype groups using analysis of variance. RESULTS: ADHD children with the Val/Val, Val/Met and Met/Met genotypes were similar with regard to demographic and clinical characteristics. No genotype effects were observed for WCST standardized perseverative error scores [F(2,97 )= 0.67; p > 0.05], TOL standardized scores [F(2,99 )= 0.97; p > 0.05], and SOPT error scores [F(2,108 )= 0.62; p > 0.05]. CONCLUSIONS: Contrary to the observed association between WCST performance and the Val(108/158 )Met polymorphism of the COMT gene in both healthy and schizophrenic adults, this polymorphism does not appear to modulate executive functions in children with ADHD

Automated template-based hippocampal segmentations from MRI: the effects of 1.5T or 3T field strength on accuracy.

Hippocampal volumetric measures may be useful for Alzheimer's disease (AD) diagnosis and disease tracking; however, manual segmentation of the hippocampus is labour-intensive. Therefore, automated techniques are necessary for large studies and to make hippocampal measures feasible for clinical use. As large studies and clinical centres are moving from using 1.5 Tesla (T) scanners to higher field strengths it is important to assess whether specific image processing techniques can be used at these field strengths. This study investigated whether an automated hippocampal segmentation technique (HMAPS: hippocampal multi-atlas propagation and segmentation) and volume change measures (BSI: boundary shift integral) were as accurate at 3T as at 1.5T. Eighteen Alzheimer's disease patients and 18 controls with 1.5T and 3T scans at baseline and 12-month follow-up were used from the Alzheimer's Disease Neuroimaging Initiative cohort. Baseline scans were segmented manually and using HMAPS and their similarity was measured by the Jaccard index. BSIs were calculated for serial image pairs. We calculated pair-wise differences between manual and HMAPS rates at 1.5T and 3T and compared the SD of these differences at each field strength. The difference in mean Jaccards (manual and HMAPS) between 1.5T and 3T was small with narrow confidence intervals (CIs) and did not appear to be segmentor dependent. The SDs of the difference between volumes from manual and automated segmentations were similar at 1.5T and 3T, with a relatively narrow CI for their ratios. The SDs of the difference between BSIs from manual and automated segmentations were also similar at 1.5T and 3T but with a wider CI for their ratios. This study supports the use of our automated hippocampal voluming methods, developed using 1.5T images, with 3T images

Vessel geometry and microvascular hand-sewn end-to-end anastomoses using Alexis Carrell’s technique: is the intuition of the Nobel Prize still valuable?

Background We review here our substantial experience in using Alexis Carrel’s technique with a geometrical optimization for microsurgical end-to-end anastomoses. Methods The technique used for microsurgical end-to-end anastomoses is described. We performed a retrospective analysis of head and neck free flaps where we used the described microsurgical anastomoses technique at Bufalini Hospital in Cesena, Italy. Patients’ demographic data, intraoperative findings, and postoperative progress, including complications, were accurately re- corded. We also recorded the cases where vessel size discrepancy was observed intraoperatively, either arterial or venous. Results The described technique has been used in 300 consecutive flaps in the last 18 years, with an average of 16 free flaps per year. No significant problems were encountered using this simple technique. Comprehensive flap survival was 98%. We had 5 free flap failures, and in all cases, the main problem was not related to the microvascular anastomoses. Vessel size discrepancy was recorded in 25% of the total. Conclusions Alexis Carrel’s technique for microvascular end-to-end anastomoses is still a very efficient end safe technique. Our geometrical optimization of it is a useful trick to keep in mind for the microvascular surgeon, especially in hospitals with a small volume of microsurgical procedures per year