Hydrodynamics and phosphorus loading in an urbanized river channel influences response to future managed change: Insights from advection-dispersion modelling.

There is a need to understand what makes certain targeted measures for in-river phosphorus load reduction more effective than others. Therefore, this paper investigates multiple development scenarios in a small lowland polluted river draining an urban area (The Cut, Bracknell, UK), using an advection-dispersion model (ADModel-P). A comparative analysis is presented whereby changes in concentrations and fluxes of soluble reactive phosphorus (SRP) and organic phosphorus (OP) have been attributed to specific transformations (mineralization, sedimentation, resuspension, adsorption-desorption, and algal uptake) and correlated to controlling factors.

Optimization Method of the Solvothermal Parameters Using Box-Behnken Experimental Design-The Case Study of ZnO Structural and Catalytic Tailoring.

ZnO photocatalysts were synthesized via solvothermal method and a reduced experimental design (Box-Behnken) was applied to investigate the influence of four parameters (temperature, duration, composition of the reaction mixture) upon the photocatalytic activity and the crystal structure of ZnO. The four parameters were correlated with photocatalytic degradation of methyl orange and the ratio of two crystallographic facets ((002) and (100)) using a quadratic model. The quadratic model shows good fit for both responses.

Dairy wastewater processing and automatic control for waste recovery at the municipal wastewater treatment plant based on modelling investigations.

Based on the calibrated model for an Anaerobic-Anoxic-Oxic (AO) municipal wastewater treatment plant (WWTP), this research investigated and proposed feasible solutions, control system configurations and optimal operating conditions for the dairy wastewater processing. The steady state study on adding different daily amounts of dairy wastewater in the WWTP water line revealed the most efficient amount to be treated by finding a minimum of the total nitrogen concentration in the water effluent. The dynamic investigations on adding different daily amounts of diary wastewater demonstrated the incentives of the proposed cascade control system configurations, based on the ammonia or nitrates concentration control in the aerated reactors, associated to nitrates and nitrites concentration control in the anoxic reactor.

Reducing energy costs of the wastewater treatment plant by improved scheduling of the periodic influent load.

The wastewater treatment plant (WWTP) is a major actor of the water-energy nexus. This study proposes to partially store in available WWTP tank infrastructure the wastewater received during the day-time and schedule the purification of the stored wastewater at night-time. The intended operational approach aims to shift part of the WWTP electrical energy consumption from day-time into the night-time period when the energy has lower prices, also contributing to the balance of the electrical power generation system.

Serum tests, liver stiffness and artificial neural networks for diagnosing cirrhosis and portal hypertension.

Background: The diagnostic performance of biochemical scores and artificial neural network models for portal hypertension and cirrhosis is not well established.

Aims: To assess diagnostic accuracy of six serum scores, artificial neural networks and liver stiffness measured by transient elastography, for diagnosing cirrhosis, clinically significant portal hypertension and oesophageal varices.

Methods: 202 consecutive compensated patients requiring liver biopsy and hepatic venous pressure gradient measurement were included.

Analysis of total phenolic, flavonoids, anthocyanins and tannins content in Romanian red wines: prediction of antioxidant activities and classification of wines using artificial neural networks.

Wine is one of the most consumed beverages over the world containing large quantities of polyphenolic compounds. These compounds are responsible for quality of red wines, influencing the antioxidant activity, astringency, bitterness and colour, their composition in wine being influenced by the varieties, the vintage and the wineries. The aim of the present work is to build software instruments intended to work as data-mining tools for predicting valuable properties of wine and for revealing different wine classes.

Counteracting the accidental pollutant propagation in a section of the River Someş by automatic control.

Real-time response to accidental pollution in rivers is a challenging mission that requires efficient on-line monitoring and rapid mitigating systems and calls for automatic control for diminishing or eliminating the pollutant effect. Remediation measures are addressed for cases in which the pollutant concentration can be measured and a neutralising agent can be identified and added to react with the pollutant and transform it by a chemical reaction into less harmful or non-harmful products. Pollution in a section of the River Someş is presented as a case study.

Antioxidant activity prediction and classification of some teas using artificial neural networks.

In order to characterise and to classify some teas a simple, rapid and economical method based on composition, antioxidant activity and artificial neural networks (ANNs) is proposed. For these purpose two types of ANN based applications have been developed: one for predicting the antioxidant activity and a second one for establishing the class of the teas. The complex relationship between the total antioxidant activity (AA) depending on the total flavonoids content (F), total catechins content (C) and total methyl-xanthines content (MX) of commercial teas was revealed by the first designed feed-forward ANN.