Evaluating Filter Materials for E. Coli Removal from Stormwater

Stormwater runoff from agricultural and urban areas carries a wide range of pollutants and pathogens that can negatively affect surface water bodies and cause significant risks to the ecosystem and public health. Bacteria is one of the pollutants carried by stormwater, and Escherichia coli (E. coli) is commonly used as a microbial pollution indicator of surface water. The aim of this research was to investigate the removal of E. coli from stormwater using low-cost filter materials. Two industrial byproducts (steel slag and steel chips) and two natural minerals (zeolite and limestone) with three different sizes (0.5-1 mm, 1-2 mm, and 2-4 mm) were chosen to investigate the potential of these materials as filter media for E. coli removal from stormwater. Batch experiments were conducted to investigate the impact of initial E. coli concentration, temperature, pH, particles size and mass, salt, natural organic matter (NOM), and contact time on the removal of E. coli. Column adsorption experiments were also performed to obtain the E. coli adsorption characteristics of steel chips, steel slag, limestone, and zeolite under continuous flow conditions. In addition, the E. coli release potential of these materials were determined. Using a desorption test, the batch adsorption results demonstrated that the maximum E. coli removal efficiencies of 100%, 99.5%, 86.5%, and 80.2% were achieved using steel byproducts, steel slag, limestone, and zeolite, respectively, using E.coli concentrations of 107 MPN/mL for steel chips and 104 MPN/mL for steel slag, limestone, and zeolite, in the synthetic stormwater. Increasing pH from 5 to 9 resulted in a reduction in E. coli adsorption by 33.5% and 19.0% for steel chips and steel slag, respectively. As temperature increased steel chips and steel slag adsorption capacities increased. The effect of the addition of NOM on E. coli removal efficiencies was determined. The results indicated that E. coli removal efficiency were reduced by 19.77% and 41.77% for steel chips and 6.86% and 11.56% for steel slag in the presence of 20 and 50 mg/L of NOM. Moreover, E. coli release from steel chips was negligible in comparison with other absorbents. Finally, adding high salt concentrations in E. coli solution showed a significant impact in natural minerals adsorption capacities. As the salinity increased the E. coli adsorption capacity of limestone and zeolite were improved by 23.5%, and 35.5%, respectively

Chemometrics Methods Applied to Non-Selective Signals in Order to Address Mainly Food, Industrial and Environmental Problems

Chemometrics is a chemical discipline that uses mathematical and statistical methods in order to extract useful information from multivariate chemical data. Moreover, chemometrics is applied to correlate quality parameters or physical properties to analytical instrument data such as calculating pH from a measurement of hydrogen ion activity or a Fourier transform interpolation of a spectrum. Aim of this thesis project is to develop chemometrical strategies for the elaboration and the interpretation of non-selective complex data in order to solve real problems in food, industry and environmental fields

Gamma Ray Spectroscopy for Logging While Drilling in Mineral Exploration

Natural gamma ray spectroscopy has changed little in 30 years. Simulations, laboratory scale models, and field experiments all demonstrate that the natural gamma ray spectrum recorded during borehole drilling can be used to track changes in heavy element concentrations with the Heavy Mineral Index, and it correlates well with iron-rich zones. This research creates a basis for a new generation of safe logging-while-drilling tools plus changes the analysis of airborne radiometrics in the future

Prevalence of Psychiatric Disorders among Children and Adolescents: A Study from Khuzestan

  Objective This cross-sectional study aimed to study the prevalence rate of psychiatric disorders in children and adolescents in Khuzestan province. Materials & Methods A community sample consisting of 1028 (51.6% female) children and adolescents aged 6-18 years was selected using a multistage cluster sampling method. Data were gathered using the Kiddie-SADSPresent and Lifetime Version (K-SADS-PL) and a demographic questionnaire (i.e., gender, age, level of education, place of residence, parent’s education, and parent’s Job) Results Nearly 22.6% (22.3% of boys and 23% of girls) of all participants suffered from at least one psychiatric disorder. There was no significant difference in the prevalence of psychiatric disorders based on gender, age, father’s education, mother’s education, mother’s job, and father’s job (all p>0.05). Psychiatric disorders were significantlymore prevalent among children and adolescents in urban areas compared to rural places (2.9% vs. 8.1; p<0.001). The most prevalent category was anxiety disorders (15%). Also, the most common disorders were specific phobia (7%), separation anxiety disorder (6.3%), and enuresis (5.2%). The most common comorbid disorders were mood disorders and anxiety disorders (56.3%), followed by anxiety disorders and elimination disorders (32.1%). ConclusionPsychiatric conditions are prevalent in children and adolescents living in Khuzestanian. The study’s findings have important implications for providing effective psychiatric services.   &nbsp

Performance of various training algorithms on scene illumination classification

The increasing number of training algorithms along with their convincing results will make this question that which algorithm will be more efficient. This study aims to perform some widespread tests on some well-known training algorithms (Levenberg-Marquardt, Resilient back propagation and Scaled conjugate gradient) to evaluate their performance for scene illumination classification. The results presented by this research can provide a reliable guide line for choosing the most appropriate training algorithm depends on the problem specification. The results of this study select the LM training method with the accuracy of 94.41% as the most accurate and RP as the most quick method with response time of 0.426 s

The effect of extraction methodology on the recovery and distribution of naphthenic acids of oilfield produced water

Comprehensive chemical characterization of naphthenic acids (NAs) in oilfield produced water is a challenging task due to sample complexity. The recovery of NAs from produced water, and the corresponding distribution of detectable NAs are strongly influenced by sample extraction methodologies. In this study, we evaluated the effect of the extraction method on chemical space (i.e. the total number of chemicals present in a sample), relative recovery, and the distribution of NAs in a produced water sample. Three generic and pre-established extraction methods (i.e. liquid-liquid extraction (Lq), and solid phase extraction using HLB cartridges (HLB), and the combination of ENV+ and C8 (ENV) cartridges) were employed for our evaluation. The ENV method produced the largest number of detected NAs (134 out of 181) whereas the HLB and Lq methods produced 108 and 91 positive detections, respectively, in the tested produced water sample. For the relative recoveries, the ENV performed better than the other two methods. The uni-variate and multi-variate statistical analysis of our results indicated that the ENV and Lq methods explained most of the variance observed in our data. When looking at the distribution of NAs in our sample the ENV method appeared to provide a more complete picture of the chemical diversity of NAs in that sample. Finally, the results are further discussed

Combining excitation-emission matrix fluorescence spectroscopy, parallel factor analysis, cyclodextrin-modified micellar electrokinetic chromatography and partial least squares class-modelling for green tea characterization

In this study, an alternative analytical approach for analyzing and characterizing green tea (GT) samples is proposed, based on the combination of excitation–emission matrix (EEM) fluorescence spectroscopy and multivariate chemometric techniques. The three-dimensional spectra of 63 GT samples were recorded using a Perkin–Elmer LS55 luminescence spectrometer; emission spectra were recorded between 295 and 800 nm at excitation wavelength ranging from 200 to 290 nm, with excitation and emission slits both set at 10 nm. The excitation and emission profiles of two factors were obtained using Parallel Factor Analysis (PARAFAC) as a 3-way decomposition method. In this way, for the first time, the spectra of two main fluorophores in green teas have been found. Moreover, a cyclodextrin-modified micellar electrokinetic chromatography method was employed to quantify the most represented catechins and methylxanthines in a subset of 24 GT samples in order to obtain complementary information on the geographical origin of tea. The discrimination ability between the two types of tea has been shown by a Partial Least Squares Class-Modelling performed on the electrokinetic chromatography data, being the sensitivity and specificity of the class model built for the Japanese GT samples 98.70% and 98.68%, respectively. This comprehensive work demonstrates the capability of the combination of EEM fluorescence spectroscopy and PARAFAC model for characterizing, differentiating and analyzing GT samples

Prevalence and correlates of psychiatric disorders in a national survey of Iranian children and adolescents

Objective: Considering the impact of rapid sociocultural, political, and economical changes on societies and families, population-based surveys of mental disorders in different communities are needed to describe the magnitude of mental health problems and their disabling effects at the individual, familial, and societal levels. Method: A population-based cross sectional survey (IRCAP project) of 30 532 children and adolescents between 6 and 18 years was conducted in all provinces of Iran using a multistage cluster sampling method. Data were collected by 250 clinical psychologists trained to use the validated Persian version of the semi-structured diagnostic interview Kiddie-Schedule for Affective Disorders and Schizophrenia-PL (K-SADS-PL). Results: In this national epidemiological survey, 6209 out of 30 532 (22.31%) were diagnosed with at least one psychiatric disorder. The anxiety disorders (14.13%) and behavioral disorders (8.3%) had the highest prevalence, while eating disorders (0.13%) and psychotic symptoms (0.26%) had the lowest. The prevalence of psychiatric disorders was significantly lower in girls (OR = 0.85; 95% CI: 0.80-0.90), in those living in the rural area (OR = 0.80; 95% CI: 0.73-0.87), in those aged 15-18 years (OR = 0.92; 95% CI: 0.86-0.99), as well as that was significantly higher in those who had a parent suffering from mental disorders (OR = 1.96; 95% CI: 1.63-2.36 for mother and OR = 1.33; 95% CI: 1.07-1.66 for father) or physical illness (OR = 1.26; 95% CI: 1.17-1.35 for mother and OR = 1.19; 95% CI: 1.10-1.28 for father). Conclusion: About one fifth of Iranian children and adolescents suffer from at least one psychiatric disorder. Therefore, we should give a greater priority to promoting mental health and public health, provide more accessible services and trainings, and reduce barriers to accessing existing services. © 2019 Tehran University of Medical Scienc

Prevalence and Correlates of Psychiatric Disorders in a National Survey of Iranian Children and Adolescents

Objective: Considering the impact of rapid sociocultural, political, and economical changes on societies and families, population-based surveys of mental disorders in different communities are needed to describe the magnitude of mental health problems and their disabling effects at the individual, familial, and societal levels. Method: A population-based cross sectional survey (IRCAP project) of 30 532 children and adolescents between 6 and 18 years was conducted in all provinces of Iran using a multistage cluster sampling method. Data were collected by 250 clinical psychologists trained to use the validated Persian version of the semi-structured diagnostic interview Kiddie-Schedule for Affective Disorders and Schizophrenia-PL (K-SADS-PL). Results: In this national epidemiological survey, 6209 out of 30 532 (22.31%) were diagnosed with at least one psychiatric disorder. The anxiety disorders (14.13%) and behavioral disorders (8.3%) had the highest prevalence, while eating disorders (0.13%) and psychotic symptoms (0.26%) had the lowest. The prevalence of psychiatric disorders was significantly lower in girls (OR = 0.85; 95% CI: 0.80-0.90), in those living in the rural area (OR = 0.80; 95% CI: 0.73-0.87), in those aged 15-18 years (OR = 0.92; 95% CI: 0.86-0.99), as well as that was significantly higher in those who had a parent suffering from mental disorders (OR = 1.96; 95% CI: 1.63-2.36 for mother and OR = 1.33; 95% CI: 1.07-1.66 for father) or physical illness (OR = 1.26; 95% CI: 1.17-1.35 for mother and OR = 1.19; 95% CI: 1.10-1.28 for father). Conclusion: About one fifth of Iranian children and adolescents suffer from at least one psychiatric disorder. Therefore, we should give a greater priority to promoting mental health and public health, provide more accessible services and trainings, and reduce barriers to accessing existing services

Estimation of Validation and Reliability of Screening Test of Tobacco, Alcohol and Addictive Drugs in Iran

Objective: the aim of the present study was the estimation of validation and reliability test of ASSIST instrument in Iran. Method: our research populations were Iranian alcohol and drugs users and abusers in the year 1390 that had referred to rehabilitation camps and addiction treatment centers for self-improving. Sample sizes of 2600, average age 36/5, were selected by cluster random sampling in eight provinces. The ASSIST and demographic form exercised for all of sample group. Also in order to validity estimation, 300 number of main sample we interviewed by ASI, SDS, DAST and DSM-IV criteria. Findings: ASSIST reliability estimated by Cronbach’s alpha for all of domains was between %79 to %95. Data analyses showed fair criteria, construct, discriminate and multi dimension validity. These types of validity for other domains were Discriminative validity of the ASSIST was investigated by comparison of ASSIST scores as groupes of dependence, abuser and user. There were significant confirmation between this scores and DSM-IV scores. Construct validity of the ASSIST was investigated by statistical comparison with health scores. ASSIST's cut off points classify clients in 3 categories in term of intensity of addiction. Conclusion: we surely recommend researchers to use this instrument in research and screening purposes or other situations in Iran