CFD-based process optimization of a dissolved air flotation system for drinking water production

Dissolved air flotation (DAF) has received more attention recently as a separation technique in both drinking water as well as wastewater treatment. However, the process as well as the preceding flocculation step is complex and not completely understood. Given the multiphase nature of the process, fluid dynamics studies are important to understand and optimize the DAF system in terms of operation and design. The present study is intended towards a comprehensive computational analysis for design optimization of the treatment plant in Kluizen, Belgium. Setting up the modelling framework involving the multiphase flow problem is briefly discussed. 3D numerical simulations on a scaled down model of the DAF design were analysed. The flow features give better confidence, but the flocs escape through the outlet still prevails which is averse to the system performance. In order to improve the performance and ease of maintenance, design modifications have been proposed by using a perforated tube for water extraction and are found to be satisfactory. The discussion is further reinforced through validating the numerical model against the experimental findings for stratified flow conditions

On the Hierarchical Preconditioning of the PMCHWT Integral Equation on Simply and Multiply Connected Geometries

We present a hierarchical basis preconditioning strategy for the Poggio-Miller-Chang-Harrington-Wu-Tsai (PMCHWT) integral equation considering both simply and multiply connected geometries.To this end, we first consider the direct application of hierarchical basis preconditioners, developed for the Electric Field Integral Equation (EFIE), to the PMCHWT. It is notably found that, whereas for the EFIE a diagonal preconditioner can be used for obtaining the hierarchical basis scaling factors, this strategy is catastrophic in the case of the PMCHWT since it leads to a severly ill-conditioned PMCHWT system in the case of multiply connected geometries. We then proceed to a theoretical analysis of the effect of hierarchical bases on the PMCHWT operator for which we obtain the correct scaling factors and a provably effective preconditioner for both low frequencies and mesh refinements. Numerical results will corroborate the theory and show the effectiveness of our approach

Constraints on the evolution of azole resistance in plant pathogenic fungi

The durability of azole fungicides in controlling agriculturally important pathogenic fungi is unique amongst modern single site fungicides. Today, azoles are still relied on to control pathogens of many crops including cereals, fruits and vegetables, canola and soybeans. Significantly, this widespread use continues despite many reports of azole-resistant fungal strains. In this review, recent reports of azole resistance and the mechanisms associated with resistant phenotypes are discussed. The example of the complex evolution of the azole target sterol 14-demethylase (CYP51) enzyme in modern European populations of the wheat pathogen Mycosphaerella graminicola is used to describe the quantitative and epistatic effects on fungicide sensitivity and enzyme function of target site mutations, and to explore the hypothesis that constraints on CYP51 evolution have ensured the longevity of azoles. In addition, the threats posed by alternative resistance mechanisms causing cross-resistance to all azoles or even unrelated fungicides are discussed, and postulations are made on how using new genomic technologies to gain a greater understanding of azole resistance evolution should enhance the ability to control azole-resistant strains of plant pathogenic fungi in the future

Preoperative Exercise Training to Prevent Postoperative Pulmonary Complications in Adults Undergoing Major Surgery. A Systematic Review and Meta-analysis with Trial Sequential Analysis.

Rationale: Poor preoperative physical fitness and respiratory muscle weakness are associated with postoperative pulmonary complications (PPCs) that result in prolonged hospital length of stay and increased mortality.Objectives: To examine the effect of preoperative exercise training on the risk of PPCs across different surgical settings.Methods: We searched MEDLINE, Web of Science, Embase, the Physiotherapy Evidence Database, and the Cochrane Central Register, without language restrictions, for studies from inception to July 2020. We included randomized controlled trials that compared patients receiving exercise training with those receiving usual care or sham training before cardiac, lung, esophageal, or abdominal surgery. PPCs were the main outcome; secondary outcomes were preoperative functional changes and postoperative mortality, cardiovascular complications, and hospital length of stay. The study was registered with PROSPERO (International Prospective Register of Systematic Reviews).Results: From 29 studies, 2,070 patients were pooled for meta-analysis. Compared with the control condition, preoperative exercise training was associated with a lower incidence of PPCs (23 studies, 1,864 patients; relative risk, 0.52; 95% confidence interval [CI], 0.41 to 0.66; grading of evidence, moderate); Trial Sequential Analysis confirmed effectiveness, and there was no evidence of difference of effect across surgeries, type of training (respiratory muscles, endurance or combined), or preoperative duration of training. At the end of the preoperative period, exercise training resulted in increased peak oxygen uptake (weighted mean difference [WMD], +2 ml/kg/min; 99% CI, 0.3 to 3.7) and higher maximal inspiratory pressure (WMD, +12.2 cm H <sub>2</sub> O; 99% CI, 6.3 to 18.2). Hospital length of stay was shortened (WMD, -2.3 d; 99% CI, -3.82 to -0.75) in the intervention group, whereas no difference was found in postoperative mortality.Conclusions: Preoperative exercise training improves physical fitness and reduces the risk of developing PPCs while minimizing hospital resources use, regardless of the type of intervention and surgery performed.Systematic review registered with https://www.crd.york.ac.uk/prospero/ (CRD 42018096956)

Traffic flow on realistic road networks with adaptive traffic lights

We present a model of traffic flow on generic urban road networks based on cellular automata. We apply this model to an existing road network in the Australian city of Melbourne, using empirical data as input. For comparison, we also apply this model to a square-grid network using hypothetical input data. On both networks we compare the effects of non-adaptive vs adaptive traffic lights, in which instantaneous traffic state information feeds back into the traffic signal schedule. We observe that not only do adaptive traffic lights result in better averages of network observables, they also lead to significantly smaller fluctuations in these observables. We furthermore compare two different systems of adaptive traffic signals, one which is informed by the traffic state on both upstream and downstream links, and one which is informed by upstream links only. We find that, in general, both the mean and the fluctuation of the travel time are smallest when using the joint upstream-downstream control strategy.Comment: 41 pages, pdflate

Dopamine precursor depletion improves punishment prediction during reversal learning in healthy females but not males

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