Comparison of Artificial Neural Networks and Autoregressive Model to Forecast Inflows to Roseires Reservoir for better Prediction of Irrigation Water Supply in the Sudan

The Blue Nile River is utilized in Sudan as the main source of irrigation water. However, the river has a long, dry, low-flow season (October–May), which necessitates the use of regulations and rules to manage its water use during this period. This depends on the use of accurate lead time forecasts of inflows to the reservoirs built along the river. Thus a reliable and tested forecasting tool is needed to provide inflow forecast, with sufficient lead time. In the present study, artificial neural network (ANN) is used to model the recession curve of the flow hydrograph at El-Deim gauging station, which subsequently is used as inflows to the Roseires Reservoir on the Blue Nile River. Different scenarios of ANN have been tested to forecast 23 10-day mean discharges during the recession period and their performances were assessed. Results from the optimal ANN model were compared to those simulated with an autoregressive (AR1) model to check their accuracy. Modelling results showed that the ANN model developed is capable of accurately forecasting the inflows to the Roseires Reservoir and outperforms the AR1 model. It has then proposed for use in operation of the reservoir for purposes of predicting irrigation water supply

Improved chemotaxis differential evolution optimization algorithm

The social foraging behavior of Escherichia coli has recently received great attention and it has been employed to solve complex search optimization problems.This paper presents a modified bacterial foraging optimization BFO algorithm, ICDEOA (Improved Chemotaxis Differential Evolution Optimization Algorithm), to cope with premature convergence of reproduction operator.In ICDEOA, reproduction operator of BFOA is replaced with probabilistic reposition operator to enhance the intensification and the diversification of the search space.ICDEOA was compared with state-of-the-art DE and non-DE variants on 7 numerical functions of the 2014 Congress on Evolutionary Computation (CEC 2014). Simulation results of CEC 2014 benchmark functions reveal that ICDEOA performs better than that of competitors in terms of the quality of the final solution for high dimensional problems

Data mining techniques for the assessment of factors contributing to the damage of residential houses in Australia

This paper reports on the preparation and management processes of inconsistent data on damage on residential houses in Victoria, Australia. There are no existing specific and fully relevant databases readily available except for the incomplete paper-based and electronic-based reports. Therefore, the extracting of information from the reports is complicated and time consuming in order to extract and include all the necessary information needed for analysis of damage on residential houses founded on expansive soils. Data mining is adopted to develop a database. Statistical methods and Artificial Intelligence methods are used to quantify the quality of data. The paper concludes that the development of such database could enable BHC to evaluate the usefulness of the reports prepared on the reported damage properties for further analysis

Selection of important input parameters using neural network trained with genetic algorithm for damage to light structures

Abstract not available

Modelling and Simulation of Dissolution/Reprecipitation Technique for Low-Density Polyethene Using Solvent/Non-Solvent System

The global production and consumption of plastics have continued to increase. Plastics degrade slowly, causing persistent environmental pollution Developed waste plastic recycling methods are discussed in this report, with a focus on the dissolution/reprecipitation technique to restore low-density polyethene (LDPE) wastes. Aspen HYSYS is used to simulate the recycling of waste LDPE. Turpentine/petroleum ether (TURP/PetE) is chosen as solvent/non-solvent with fractions proved efficient through laboratory experiments. PetE is selected to be the non-solvent used for the precipitation of pure LDPE. The feedstock is assumed to be LDPE products containing additives such as dye. The simulation model developed estimated a pure LDPE precipitate recovery with a composition of 99% LDPE with a flowrate of 1024 tonnes per year. In addition, Aspen HYSYS could approximate a rough cost estimate that includes utility cost, installation cost and other factors. Technical challenges were eliminated, and several assumptions were taken into consideration to be able to simulate the process

Vancomycin-resistant enterococci colonization in patients with hematological malignancies: screening and its cost-effectiveness

Background and objective: We evaluated the rates of vancomycin-resistant enterococci (VRE) colonization and VRE related bacteremia in patients with hematological malignancies in terms of routine screening culture and its cost-effectiveness.Materials and Methods: All patients of the hematology department who were older than 14 years of age and who developed at least one febrile neutropenia episode during chemotherapy for hematological cancers between November 2010 and November 2012 were evaluated retrospectively.Results: We retrospectively analyzed 282 febrile episodes in 126 neutropenic patients during a two-year study period. The study included 65 cases in the first study-year and 78 cases in the second study-year. The numbers of colonization days and colonized patient were 748 days of colonization in 29 patients (44%) in the first study-year and 547 colonization days in 21 patients (26%) in the second study-year, respectively. Routine screening culture for VRE cost $4516,4 (427 cultures) in the first study-year,$5082,7 (504 cultures) in the second study-year depending on the number of patients and their length of stay.Conclusion: In line with our study results, routine screening of hematological patients for VRE colonization is not costeffective. Routine surveillance culture for VRE should be considered with respect to the conditions of health care setting.Keywords: Hematological patients, febrile neutropenia, vancomycin-resistant enterococci, vancomycin-sensitive enterococci, bacteremia, colonization

ENHANCEMENT OF DISSOLUTION RATE OF HYDROCHLOROTHIAZIDE

Objective: The aim of this study was to enhance the dissolution rate of hydrochlorothiazide (HCTZ).Methods: Binary solid dispersions (SDs) of HCTZ with increasing weight ratios of poloxamer 407, polyethylene glycol 6000 (PEG 6000) or gelucire 50/13 were prepared by solvent evaporation technique. The solid dispersions were deposited on the surface of aerosil 200 to produce a dry product with large surface area. The SDs were characterized with respect to drug dissolution. The mechanism of dissolution enhancement was researched using Fourier transform infrared spectroscopy (FTIR) and differential scanning calorimetry (DSC).Results: The unprocessed drug showed erratic, slow dissolution which can be explained on the basis of its hydrophobic nature. Preparation of SDs with hydrophilic carriers resulted in a significant increase in the dissolution rate with most of the drug being liberated in the first 5 min. The dissolution pattern of the drug from the prepared SDs depends mainly on the type of polymer used, and the best dissolution pattern was observed in the SD prepared using 1:1 ratio of the drug to gelucire 50/13 in the presence of aerosil 200 as a carrier. FTIR studies revealed no interaction between the drug and polymers. DSC showed a change in the crystalline structure of the drug after SDs formation. This change can explain the recorded dissolution enhancement.Conclusion: The study presented a system capable of increasing the dissolution rate of HCTZ using polymers which can increase the intestinal permeability as well.Keywords: Hydrochlorothiazide, Poloxamer 407, PEG 6000, Gelucire 50/13, Solid dispersion, Dissolutio

One-Year Results of Simultaneous Topography-Guided Photorefractive Keratectomy and Corneal Collagen Cross-Linking in Keratoconus Utilizing a Modern Ablation Software

Purpose. To evaluate effectiveness of simultaneous topography-guided photorefractive keratectomy and corneal collagen cross-linking in mild and moderate keratoconus. Methods. Prospective nonrandomized interventional study including 20 eyes of 14 patients with grade 1-2 keratoconus that underwent topography-guided PRK using a Custom Ablation Transition Zone (CATz) profile with 0.02% MMC application immediately followed by standard 3 mw/cm2 UVA collagen cross-linking. Maximum ablation depth did not exceed 58 μm. Follow-up period: 12 months. Results. Progressive statistically significant improvement of UCVA from 0.83±0.37 logMAR preoperative, reaching 0.25±0.26 logMAR at 12 months (P<0.001). Preoperative BCVA (0.27±0.31 logMAR) showed a progressive improvement reaching 0.08±0.12 logMAR at 12 months (P=0.02). Mean Kmax reduced from 48.9±2.8 to 45.4±3.1 D at 12 months (P<0.001), mean Kmin reduced from 45.9±2.8 D to 44.1±3.2 D at 12 months (P<0.003), mean keratometric asymmetry reduced from 3.01±2.03 D to 1.25±1.2 D at 12 months (P<0.001). The safety index was 1.39 at 12 months and efficacy index 0.97 at 12 months. Conclusion. Combined topography-guided PRK and corneal collagen cross-linking are a safe and effective option in the management of mild and moderate keratoconus. Precis. To our knowledge, this is the first published study on the use of the CATz ablation system on the Nidek Quest excimer laser platform combined with conventional cross-linking in the management of mild keratoconus

Passengers' destinations from China: low risk of Novel Coronavirus (2019-nCoV) transmission into Africa and South America

Novel Coronavirus (2019-nCoV [SARS-COV-2]) was detected in humans during the last week of December 2019 at Wuhan city in China, and caused 24 554 cases in 27 countries and territories as of 5 February 2020. The objective of this study was to estimate the risk of transmission of 2019-nCoV through human passenger air flight from four major cities of China (Wuhan, Beijing, Shanghai and Guangzhou) to the passengers' destination countries. We extracted the weekly simulated passengers' end destination data for the period of 1–31 January 2020 from FLIRT, an online air travel dataset that uses information from 800 airlines to show the direct flight and passengers' end destination. We estimated a risk index of 2019-nCoV transmission based on the number of travellers to destination countries, weighted by the number of confirmed cases of the departed city reported by the World Health Organization (WHO). We ranked each country based on the risk index in four quantiles (4th quantile being the highest risk and 1st quantile being the lowest risk). During the period, 388 287 passengers were destined for 1297 airports in 168 countries or territories across the world. The risk index of 2019-nCoV among the countries had a very high correlation with the WHO-reported confirmed cases (0.97). According to our risk score classification, of the countries that reported at least one Coronavirus-infected pneumonia (COVID-19) case as of 5 February 2020, 24 countries were in the 4th quantile of the risk index, two in the 3rd quantile, one in the 2nd quantile and none in the 1st quantile. Outside China, countries with a higher risk of 2019-nCoV transmission are Thailand, Cambodia, Malaysia, Canada and the USA, all of which reported at least one case. In pan-Europe, UK, France, Russia, Germany and Italy; in North America, USA and Canada; in Oceania, Australia had high risk, all of them reported at least one case. In Africa and South America, the risk of transmission is very low with Ethiopia, South Africa, Egypt, Mauritius and Brazil showing a similar risk of transmission compared to the risk of any of the countries where at least one case is detected. The risk of transmission on 31 January 2020 was very high in neighbouring Asian countries, followed by Europe (UK, France, Russia and Germany), Oceania (Australia) and North America (USA and Canada). Increased public health response including early case recognition, isolation of identified case, contract tracing and targeted airport screening, public awareness and vigilance of health workers will help mitigate the force of further spread to naïve countries

Application of neural networks in modelling serviceability deterioration of concrete stormwater pipes

Stormwater pipe systems in Australia are designed to convey water from rainfall and surface runoff only and do not transport sewage. Any blockage can cause flooding events with the probability of subsequent property damage. Proactive maintenance plans that can enhance their serviceability need to be developed based on a sound deterioration model. This paper uses a neural network (NN) approach to model deterioration in serviceability of concrete stormwater pipes, which make up the bulk of the stormwater network in Australia. System condition data was collected using CCTV images. The outcomes of model are the identification of the significant factors influencing the serviceability deterioration and the forecasting of the change of serviceability condition over time for individual pipes based on the pipe attributes. The proposed method is validated and compared with multiple discriminant analysis, a traditionally statistical method. The results show that the NN model can be applied to forecasting serviceability deterioration. However, further improvements in data collection and condition grading schemes should be carried out to increase the prediction accuracy of the NN model.<br /