Industrial Process Water Treatment and Reuse: A Framework for Synthesis and Design

Mathematical optimization has shown the potential to contribute to industrial water management, through the development of the solution methods needed for optimization-based design of wastewater treatment and reuse networks (also called water networks). Nevertheless, the application of this approach is still limited to motivating examples lacking the ability to handle problems with complexity of industrial relevance. To address this challenge, in this contribution, we focus on the integration of wastewater engineering concepts and models, together with optimization methods and solution algorithms. To this end, we propose a computer-aided framework for the design of water treatment and reuse networks. In the framework, optimization methods, problem analysis tools and wastewater engineering knowledge are integrated in a computer-aided environment, in order to facilitate the formulation and solution of the design problems with fair complexity representative of industrial applications. The framework is demonstrated through the solution of a case study dealing with the treatment and reuse of water effluent produced by an oil refinery. The problem is solved, and a win–win solution is identified, allowing a reduced water footprint, and the treatment costs are identified

Age-standardized all-cause mortality in Italy from 1901 to 2008 as related to gender and age classes.

<p>Age-standardized all-cause mortality in Italy from 1901 to 2008 as related to gender and age classes.</p

Age-adjusted mortality rates (per 100,000, world standard), for all causes and specific causes, and Annual Percent Changes (APC) between Join Points (JP) in Italian males (A) and females (B) aged 0–49 years during the period 1901–2008.

<p>*<i>P</i><0.05; #Period 1951–2008.</p><p>Age-adjusted mortality rates (per 100,000, world standard), for all causes and specific causes, and Annual Percent Changes (APC) between Join Points (JP) in Italian males (A) and females (B) aged 0–49 years during the period 1901–2008.</p

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Age-standardized mortality data for the 10 main causes of death in Italy from 1901 to 2008 as related to gender and age classes.

<p>Age-standardized mortality data for the 10 main causes of death in Italy from 1901 to 2008 as related to gender and age classes.</p

The microRNA Expression Profile in Donation after Cardiac Death (DCD) Livers and Its Ability to Identify Primary Non Function

<div><p>Donation after cardiac death (DCD) livers are marginal organs for transplant and their use is associated with a higher risk of primary non function (PNF) or early graft dysfunction (EGD). The aim was to determine if microRNA (miRNA) was able to discriminate between DCD livers of varying clinical outcome. DCD groups were categorized as PNF retransplanted within a week (n=7), good functional outcome (n=7) peak aspartate transaminase (AST) ≤ 1000 IU/L and EGD (n=9) peak AST ≥ 2500 IU/L. miRNA was extracted from archival formalin fixed post-perfusion tru-cut liver biopsies. High throughput expression analysis was performed using miRNA arrays. Bioinformatics for expression data analysis was performed and validated with real time quantitative PCR (RT-qPCR). The function of miRNA of interest was investigated using computational biology prediction algorithms. From the array analysis 16 miRNAs were identified as significantly different (p<0.05). On RT-qPCR miR-155 and miR-940 had the highest expression across all three DCD clinical groups. Only one miRNA, miR-22, was validated with marginal significance, to have differential expression between the three groups (p=0.049). From computational biology miR-22 was predicted to affect signalling pathways that impact protein turnover, metabolism and apoptosis/cell cycle. In conclusion, microRNA expression patterns have a low diagnostic potential clinically in discriminating DCD liver quality and outcome.</p></div

Real time quantitative PCR of individual microRNA.

<p>From the microRNA (miRNA) array analysis 16 miRNAs were identified as having significant differential expression (p<0.05) and selected for further validation with real time quantitative PCR (RT-qPCR). Threshold cycle (Ct) values were normalised using the average Ct of small nucleolar RNAs (snoRNAs) and to determine miRNA relative expression 2ΔΔCT was used and calculated as follows ΔCT (miRNA Ct—averaged endogenous control Ct) and fold-change to reference sample of normal liver (a non steatotic donation after brain stem death liver). Due to the range and magnitude of relative miRNA expression, data was log transformed and presented as mean +/- SE. The relative expression for a given miRNA in the three donation after cardiac death (DCD) liver groups of primary non function (PNF) retransplanted within a week (n = 7), good functional outcome (n = 7) peak aspartate transaminase (AST) ≤ 1000 IU/L and early graft dysfunction (EGD) (n = 9) peak AST ≥ 2500 IU/L is represented graphically. The observed differences in the relative expression of a given miRNA species on RT-qPCR between the three DCD liver groups was only found to be significant for miR-22 (p = 0.049).</p

Real time quantitative PCR profile in donation after cardiac death liver.

<p>From the microRNA (miRNA) array analysis 16 miRNAs were identified as having significant differential expression (p<0.05) and selected for validation with real time quantitative PCR (RT-qPCR). Threshold cycle (Ct) values were normalised using the average Ct of small nucleolar RNAs (snoRNAs) and to determine miRNA relative expression 2ΔΔCT was used and calculated as follows ΔCT (miRNA Ct—averaged endogenous control Ct) and fold-change to reference sample of normal liver (a non steatotic donation after brain stem death liver). Across the three donation after cardiac death (DCD) liver groups of primary non function (PNF) retransplanted within a week (n = 7), good functional outcome (n = 7) peak aspartate transaminase (AST) ≤ 1000 IU/L and early graft dysfunction (EGD) (n = 9) peak AST ≥ 2500 IU/L, miR-155 and miR-940 had the highest relative expression.</p

Heatmap of microRNA from the donation after cardiac death liver groups.

<p>microRNA (miRNA) was extracted from archival formalin fixed post-perfusion tru-cut donor liver biopsies taken from donation after cardiac death (DCD) livers of varying clinical outcome. DCD groups were categorized as primary non function (PNF) retransplanted within a week (n = 7), good functional outcome (n = 7) peak aspartate transaminase (AST) ≤ 1000 IU/L and early graft dysfunction (EGD) (n = 9) peak AST ≥ 2500 IU/L. The heatmap demonstrates miRNA differential expression between the three DCD liver groups of primary PNF, EGD and good (p<0.05). Columns of the heatmap represent the different individual DCD liver biopsies and the horizontal cladogram at the top of the heatmap demonstrates clustering of samples according to DCD group of PNF, EGD and good. Key in top corner illustrates color labelling of DCD groups in the horizontal cladogram. The rows of the heatmap represent different miRNAs and the vertical cladogram shows clustering of miRNA species within each DCD group. The vertical graded scale shows that white within the heatmap represents increased expression and black decreased expression of a given miRNA. As no microRNA species was strongly associated with a given DCD clinical group, there is no clear heatmap pattern to be seen.</p

Principal Component Analysis (unsupervised hierarchial cluster analysis) of microRNA (miRNA) array data.

<p>miRNA was extracted from archival formalin fixed post-perfusion tru-cut donor liver biopsies taken from donation after cardiac death (DCD) livers of varying clinical outcome. DCD groups were categorized as primary non function (PNF) retransplanted within a week (n = 7), good functional outcome (n = 7) peak aspartate transaminase (AST) ≤ 1000 IU/L and early graft dysfunction (EGD) (n = 9) peak AST ≥ 2500 IU/L. The principal component analysis shows clustering of samples according to DCD liver group of PNF, EGD and good (p = 0.05, q = 0.95).</p