Titrimetric monitoring of chemical equilibrium and pH dynamics in a pilot-scale water resource recovery facility using PHREEQC and buffer capacity modelling

L’augmentation considérable de l’eutrophisation des eaux de surface dans les dernières décennies a mené à la création de stations de récupération des ressources de l’eau (StaRRE) de plus en plus instrumentées pouvant procéder à l’élimination des nutriments. Pour assurer l’efficacité des procédés de récupération, plusieurs paramètres de qualité des eaux doivent être surveillés. Des méthodes en ligne et hors-ligne existent pour réaliser cette surveillance. Cependant, certains paramètres sont difficilement mesurés en ligne, alors des analyses en laboratoire sont toujours de mise. La titrimétrie est une méthode hors-ligne permettant la surveillance de la qualité des eaux en laboratoire. Un appareil Titrino a été installé afin de procéder à l’analyse titrimétrique des eaux usées de l’usine pilEAUte, une StaRRE de traitement expérimentale de 12 m3 située sur le campus de l’Université Laval. L’eau usée de cette station provient d’une résidence étudiante du campus et de ses environs. L’eau pompée vers la station est stockée dans un bassin de 5 m3 avant d’être acheminée à un décanteur primaire. L’effluent du décanteur est alors envoyé vers deux chaînes de traitement biologique composées de cinq bioréacteurs chacune. Enfin, l’eau est acheminée vers deux décanteurs secondaires. Dans le cadre de ce projet, des campagnes de mesure ont été réalisées afin de comparer les données provenant de capteurs en ligne avec l’information extraite d’expériences de titrimétrie pour la mesure de la qualité des eaux usées de la station. Ces campagnes de mesure ont été réalisées en lien avec de projets menés avec des partenaires industriels. L’objectif de cette étude est d’évaluer l’efficacité des analyses de titrimétrie pour la mesure de la qualité de l’eau à l’affluent et à l’effluent d’une StaRRE. Les données extraites de la titrimétrie sont analysées de deux façons différentes: la modélisation de la capacité tampon de l’eau et la modélisation de l’équilibre chimique via le logiciel PHREEQC. Ces méthodes ont été mises en place, puis comparées sur la base de leur efficacité pour mesurer la concentration de certaines substances tampon présentes dans les eaux usées. Pour améliorer les estimations des modèles, des améliorations au protocole d’utilisation du Titrino ont été développées. Il a été déterminé que l’utilisation d’une couverture d’azote gazeux et le stripage du CO2 dissout dans les échantillons sont nécessaires à la réalisation de titrations fiables, et sont donc aussi nécessaires à la mesure de substances tampon autre que l’alcalinité, soit l’ammoniaque et les acides gras volatils (AGV). Afin de valider les résultats obtenus à l’aide du modèle de capacité tampon et afin d’obtenir une description complète de l’équilibre chimique des solutions analysées, un modèle de simulation de la procédure de titration a été développé avec le logiciel PHREEQC et l’interface PHREEQXCEL. Cet environnement de simulation a été supplémenté du solveur OpenSolver, un complément Excel à licence libre capable de réaliser les estimations de paramètres requises pour estimer la concentration de chaque espèce chimique présente dans les échantillons. De plus, la base de données de réactions chimiques de PHREEQC a été modifiée afin d’inclure toute l’information chimique nécessaire à la modélisation des spéciations se produisant dans les eaux usées. Après avoir proposé ces améliorations et avoir comparé les résultats des analyses de titration à des analyses chimiques conventionnelles, il a été déterminé que la titrimétrie est une alternative fiable pour la surveillance de la performance des procédés de récupération des nutriments des eaux usées.The considerable rise of eutrophication in water bodies has led to highly instrumented water resource recovery facilities (WRRFs) that can perform nutrient removal processes. To ensure the efficiency of these processes, several parameters that influence the performance of WRRFs need to be well thought out. The latter requires monitoring strategies composed of on-line and off-line methods. Lately, on-line measurements have contributed significantly to monitor and characterize the quality of water and wastewater. However, on-line measurements are not applicable or not implemented yet for some specific areas. For this, off-line laboratory methods are welcome alternatives. Titrimetry is one of the examples of a low-cost off-line method that allows characterizing aquatic streams. Concerning titrimetric monitoring of wastewater, a Titrino device was installed in the laboratory of the 12 m3 pilEAUte WRRF located at Université Laval. The wastewater feeding the plant is coming from a student residence building on campus. The water pumped to the station is feeding a storage tank with a volume of 5 m3 , from which it is then pumped to a primary clarifier. The influent stream is then split into two similar treatment lines, composed of several bioreactors. These two lanes are followed by two secondary settling tanks. In this work, sampling campaigns were performed to compare the sensor data and the off-line titrimetric measurements in a framework of research projects in which industrial partners are involved. The goal of this study was to investigate the efficiency of using titrimetry to analyze and characterize influent and effluent samples of a WRRF. Two data interpretation methods, buffer capacity and PHREEQC, were tested and their performances in estimating the concentration of the concerned buffers were evaluated. For better model estimation, first, some of the lab procedures were improved. It was found out that nitrogen blanketing and CO2 stripping are necessary to perform reliable titration, and thus, to measure other concerned buffers besides alkalinity, such as ammonia and volatile fatty acids (VFA). Moreover, to validate the results of the buffer capacity model and to have a complete description of the equilibrium reactions of the chemical system under study, a titration simulation model was successfully built in PHREEQC with the PHREEQXCEL interface. This titration lab simulation was extended with the OpenSolver, an open-source Excel add-in, which allows to reliably perform the parameter estimation needed to find the concentration of the different species in the sample. In addition, PHREEQC’s database was modified to include all the model components and their essential chemical information for the speciation calculations.After introducing the mentioned lab and modelling improvements, the reliability of the titrimetric measurements for monitoring the performance of nutrient removal was enhanced

Lipid measures for prediction of incident cardiovascular disease in diabetic and non-diabetic adults: results of the 8.6 years follow-up of a population based cohort study

<p>Abstract</p> <p>Background</p> <p>Diabetes is a strong risk factor for cardiovascular disease (CVD).The relative role of various lipid measures in determining CVD risk in diabetic patients is still a subject of debate. We aimed to compare performance of different lipid measures as predictors of CVD using discrimination and fitting characteristics in individuals with and without diabetes mellitus from a Middle East Caucasian population.</p> <p>Methods</p> <p>The study population consisted of 1021 diabetic (men = 413, women = 608) and 5310 non-diabetic (men = 2317, women = 2993) subjects, aged ≥ 30 years, free of CVD at baseline. The adjusted hazard ratios (HRs) for CVD were calculated for a 1 standard deviation (SD) change in total cholesterol (TC), log-transformed triglyceride (TG), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), non-HDL-C, TC/HDL-C and log-transformed TG/HDL-C using Cox proportional regression analysis. Incident CVD was ascertained over a median of 8.6 years of follow-up.</p> <p>Results</p> <p>A total of 189 (men = 91, women = 98) and 263(men = 169, women = 94) CVD events occurred, in diabetic and non-diabetic population, respectively. The risk factor adjusted HRs to predict CVD, except for HDL-C, TG and TG/HDL-C, were significant for all lipid measures in diabetic males and were 1.39, 1.45, 1.36 and 1.16 for TC, LDL-C, non- HDL-C and TC/HDL-C respectively. In diabetic women, using multivariate analysis, only TC/HDL-C had significant risk [adjusted HR1.31(1.10-1.57)].Among non-diabetic men, all lipid measures, except for TG, were independent predictors for CVD however; a 1 SD increase in HDL-C significantly decreased the risk of CVD [adjusted HR 0.83(0.70-0.97)].In non-diabetic women, TC, LDL-C, non-HDL-C and TG were independent predictors.</p> <p>There was no difference in the discriminatory power of different lipid measures to predict incident CVD in the risk factor adjusted models, in either sex of diabetic and non-diabetic population.</p> <p>Conclusion</p> <p>Our data according to important test performance characteristics provided evidence based support for WHO recommendation that along with other CVD risk factors serum TC vs. LDL-C, non-HDL-C and TC/HDL-C is a reasonable lipid measure to predict incident CVD among diabetic men. Importantly, HDL-C did not have a protective effect for incident CVD among diabetic population; given that the HDL-C had a protective effect only among non- diabetic men.</p

Residual Information of Previous Decision Affects Evidence Accumulation in Current Decision

Bias in perceptual decisions can be generally defined as an effect which is controlled by factors other than the decision-relevant information (e.g., perceptual information in a perceptual task, when trials are independent). The literature on decision-making suggests two main hypotheses to account for this kind of bias: internal bias signals are derived from (a) the residual of motor signals generated to report a decision in the past, and (b) the residual of sensory information extracted from the stimulus in the past. Beside these hypotheses, this study suggests that making a decision in the past per se may bias the next decision. We demonstrate the validity of this assumption, first, by performing behavioral experiments based on the two-alternative forced-choice (TAFC) discrimination of motion direction paradigms and, then, we modified the pure drift-diffusion model (DDM) based on the accumulation-to-bound mechanism to account for the sequential effect. In both cases, the trace of the previous trial influences the current decision. Results indicate that the probability of being correct in the current decision increases if it is in line with the previously made decision even in the presence of feedback. Moreover, a modified model that keeps the previous decision information in the starting point of evidence accumulation provides a better fit to the behavioral data. Our findings suggest that the accumulated evidence in the decision-making process after crossing the bound in the previous decision can affect the parameters of information accumulation for the current decision in consecutive trials

The relationship between personality characteristics and the quality of life in patients with epilepsy

Introduction: Identification of effective factors in the quality of life (QOL) of patients with epilepsy is important in improving their quality of life. Regarding this, the present study aimed to investigate the relationship between personality characteristics and QOL in patients with epilepsy. Material and methods: This cross-sectional study was conducted on 100 epileptic patients referred to Neurology Clinic of Ali-ibn Abi Talib Hospital in Zahedan, Iran in 2015. The NEO Personality Inventory (NEO-PI) and Short Form Health Survey (SF-12) questionnaires were used to determine the personality characteristics and QOL scores, respectively. Results: The mean of QOL score was 28.94±4.58. Age, gender, marital status, education level, and duration of epilepsy had no significant correlation with the QOL. The QOL showed a negative correlation with openness to experience and neuroticism. However, this variable had a direct correlation with conscientiousness, agreeableness, and extraversion. There was a significant relationship between the predictor variables (extraversion and neuroticism) and the criterion variable (QOL). Therefore, extraversion and neuroticism can be considered as the predictors of the QOL. Conclusions: The extraversion and neuroticism seem to be two predictors of the QOL in the epileptic patients. Accordingly, whereas the patients with high levels of neuroticism had low QOL, this value was higher in those with high levels of extraversion.Introduction: Identification of effective factors in the quality of life (QOL) of patients with epilepsy is important inimproving their quality of life. Regarding this, the present study aimed to investigate the relationship between personalitycharacteristics and QOL in patients with epilepsy.Material and methods: This cross-sectional study was conducted on 100 epileptic patients referred to NeurologyClinic of Ali-ibn Abi Talib Hospital in Zahedan, Iran in 2015. The NEO Personality Inventory (NEO-PI) and Short FormHealth Survey (SF-12) questionnaires were used to determine the personality characteristics and QOL scores, respectively.Results: The mean of QOL score was 28.94±4.58. Age, gender, marital status, education level, and duration of epilepsyhad no significant correlation with the QOL. The QOL showed a negative correlation with openness to experience andneuroticism. However, this variable had a direct correlation with conscientiousness, agreeableness, and extraversion.There was a significant relationship between the predictor variables (extraversion and neuroticism) and the criterionvariable (QOL). Therefore, extraversion and neuroticism can be considered as the predictors of the QOL.Conclusions: The extraversion and neuroticism seem to be two predictors of the QOL in the epileptic patients. Accordingly,whereas the patients with high levels of neuroticism had low QOL, this value was higher in those with highlevels of extraversion

The prevalence of polycystic ovary syndrome in a community sample of Iranian population: Iranian PCOS prevalence study

<p>Abstract</p> <p>Background</p> <p>Despite the heavy burden and impact of the polycystic ovary syndrome (PCOS) in reproduction and public health, estimates regarding its prevalence at community levels are limited. We aimed to ascertain prevalence of PCOS in a community based sample using the National Institute of Health (NIH), the Rotterdam consensus (Rott.) and the Androgen Excess Society (AES) criteria.</p> <p>Methods</p> <p>Using the stratified, multistage probability cluster sampling method, 1126 women were randomly selected from among reproductive aged women of different geographic regions of Iran. PCOS were diagnosed using universal assessment of ultrasonographic parameters, hormonal profiles and clinical histories.</p> <p>Results</p> <p>The mean +/- SD of age of study population was 34.4 +/- 7.6 years. Estimated prevalence of idiopathic hirsutism was 10.9% (95% CI: 8.9-12.9%); 8.3% of women had only oligo/anovulation and 8.0% had only polycystic ovaries. The prevalence of PCOS was 7.1% (95% CI: 5.4-8.8%) using the NIH definition, 11.7% (95% CI: 9.5-13.7%) by AES criteria and 14.6% (95% CI: 12.3-16.9%) using the Rott definition.</p> <p>Conclusions</p> <p>At community level, widespread screening of Rotterdam criteria will increase the estimated prevalence of PCOS over twofold. Establishing an explicit and contemporaneous method for definition and screening of each PCOS criteria has important investigational implications and increase the comparability of published research.</p

Lipid ratios and appropriate cut off values for prediction of diabetes: a cohort of Iranian men and women

<p>Abstract</p> <p>Background</p> <p>Dyslipidemia is a risk factor for incident type 2 diabetes; however, no study has specifically assessed the lipid ratios (i.e. total cholesterol (TC)/high density lipoprotein cholesterol (HDL-C) and triglyceride (TG)/HDL-C) as predictors of diabetes. We aimed to compare the independent association between the different lipid measures with incident diabetes over a median follow up of 6.4 years in Iranian men and women.</p> <p>Method</p> <p>The study population consisted of 5201 non diabetic (men = 2173, women = 3028) subjects, aged ≥20 years. The risk factor adjusted odds ratios (ORs) for diabetes were calculated for every 1 standard deviation (SD) change in TC, log-transformed TG, HDL-C, non-HDL-C, TC/HDL-C and log-transformed TG/HDL-C using multivariate logistic regression analysis. Receiver operator characteristic (ROC) curve analysis was used to define the points of the maximum sum of sensitivity and specificity (MAXss) of each lipid measure as a predictor of diabetes.</p> <p>Result</p> <p>We found 366 (146 men and 220 women) new diabetes cases during follow-up. The risk-factor-adjusted ORs for a 1 SD increase in TG, TC/HDL-C and TG/HDL-C were 1.23, 1.27 and 1.25 in men; the corresponding risks in females were 1.36, 1.14, 1.39 respectively (all p < 0.05, except TC/HDL-C in females which was marginally significant, p = 0.07). A 1 SD increase of HDL-C only in women decreased the risk of diabetes by 25% [0.75(0.64-0.89)]. In both genders, there was no difference in the discriminatory power of different lipid measures to predict incident diabetes in the risk factor adjusted models (ROC ≈ 82%). TG cutoff values of 1.98 and 1.66 mmol/l; TG/HDL-C cutoff values of 4.7 and 3.7, in men and women, respectively, TC/HDL-C cutoff value of 5.3 in both genders and HDL-C cutoff value of 1.18 mmol/l in women yielded the MAXss for defining the incidence of diabetes.</p> <p>Conclusion</p> <p>TC/HDL-C and TG/HDL-C showed similar performance for diabetes prediction in men population however; among women TG/HDL-C highlighted higher risk than did TC/HDL-C, although there was no difference in discriminatory power. Importantly, HDL-C had a protective effect for incident diabetes only among women.</p

Effect of phlebotomy versus oral contraceptives containing cyproterone acetate on the clinical and biochemical parameters in women with polycystic ovary syndrome : a randomized controlled trial

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Does the Anti-Mullerian Hormone Decline Rate Improve the Prediction of Age at Menopause?

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Maxillofacial fracture epidemiology and treatment plans in the Northeast of Iran: A retrospective study

Background: The epidemiology of facial injuries varies based on lifestyle, cultural background and socioeconomic status in different countries and geographic zones. This study evaluated the epidemiology of maxillofacial fractures and treatment plans in hospitalized patients in Northeast of Iran (2015-2016). Material and Methods: In this retrospective study, the medical records of 502 hospitalized patients were evaluated in the Department of Maxillofacial Surgery in Kamyab Hospital in Mashhad, Iran. The type and cause of fractures and treatment plans were recorded in a checklist. Data were analyzed with Mann–Whitney test, chi-squared test and Fisher’s exact test, using SPSS 21. Results: The majority of patients were male (80.3%). Most subjects were in 20-30-year age range (43.2%). The fractures were mostly caused by accidents, particularly motorcycle accidents (MCAs), and the most common site of involvement was the body of the mandible. There was a significant association between the type of treatment and age. In fact, the age range of 16-59 years underwent open reduction internal fixation (ORIF) more than other age ranges (P=0.001). Also, there was a significant association between gender and fractures (P=0.002). Conclusions: It was concluded that patient age and gender and trauma significantly affected the prevalence of maxillofacial traumas, fracture types and treatment plans. This information would be useful for making better health policy strategies. Key words:Epidemiology, treatment, facial injuries, maxillofacial fractures, trauma