Designing Efficient and Sustainable Predictions of Water Quality Indexes at the Regional Scale Using Machine Learning Algorithms

Water quality and scarcity are key topics considered by the Sustainable Development Goals (SDGs), institutions, policymakers and stakeholders to guarantee human safety, but also vital to protect natural ecosystems. However, conventional approaches to deciding the suitability of water for drinking purposes are often costly because multiple characteristics are required, notably in low-income countries. As a result, building right and trustworthy models is mandatory to correctly manage available groundwater resources. In this research, we propose to check multiple classification techniques such as Decision Trees (DT), K-Nearest Neighbors (KNN), Discriminants Analysis (DA), Support Vector Machine (SVM), and Ensemble Trees (ET) to design the best strategy allowing the forecast a Water Quality Index (WQI). To achieve this goal, an extended dataset characterized by water samples collected in a total of twelve municipalities of the Wilaya of Naâma in Algeria was considered. Among them, 151 samples were examined as training samples, and 18 were used to test and confirm the prediction model. Later, data samples were classified based on the WQI into four states: excellent water quality, good water quality, poor water quality, and very poor or unsafe water. The main results revealed that the SVM classifier obtained the highest forecast accuracy, with 95.4% of prediction accuracy when the data are standardized and 88.9% for the accuracy of the test samples. The results confirmed that the use of machine learning models are powerful tools for forecasting drinking water as larger scales to promote the design of efficient and sustainable water quality control and support decision-plans.This work is part of PRFU project N° E04N01CU450120220001. The authors gratefully acknowledge the support of the General Directorate of Scientific Research and Technological Development (DGRSDT) and to Taif University Researchers Supporting Project TURSP 2020/34, Taif University, Taif, Saudi Arabia

Effects of Steel Fibers (SF) and Ground Granulated Blast Furnace Slag (GGBS) on Recycled Aggregate Concrete

[EN] Recycled aggregate is a good option to be used in concrete production as a coarse aggregate that results in environmental benefits as well as sustainable development. However, recycled aggregate causes a reduction in the mechanical and durability performance of concrete. On the other hand, the removal of industrial waste would be considerably decreased if it could be incorporated into concrete production. One of these possibilities is the substitution of the cement by slag, which enhances the concrete poor properties of recycled aggregate concrete as well as provides a decrease in cement consumption, reducing carbon dioxide production, while resolving a waste management challenge. Furthermore, steel fiber was also added to enhance the tensile capacity of recycled aggregate concrete. The main goal of this study was to investigate the characteristics of concrete using ground granulated blast-furnace slag (GGBS) as a binding material on recycled aggregate fibers reinforced concrete (RAFRC). Mechanical performance was assessed through compressive strength and split tensile strength, while durability aspects were studied through water absorption, acid resistance, and dry shrinkage. The results detected from the different experiments depict that, at an optimum dose (40% RCA, 20%GGBS, and 2.0%), compressive and split tensile strength were 39% and 120% more than the reference concrete, respectively. Furthermore, acid resistance at the optimum dose was 36% more than the reference concrete. Furthermore, decreased water absorption and dry shrinkage cracks were observed with the substitution of GGBS into RAFRC.SIThe authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through a group research program under grant number RGP. 2/129/42 and Taif University Researchers Supporting Project grant number [TURSP-2020/324]

Determination of the tensile properties and biodegradability of cornstarch-based biopolymers plasticized with sorbitol and glycerol

In this study, the effects of various quantities of sorbitol and glycerol plasticizers (0%, 30%, 45%, and 60%) on cornstarch-based film were examined to develop a novel polymer for usage with biodegradable materials. The film was prepared using the casting process. According to the test findings, the application of the plasticizer concentrations affected the thickness, moisture content, and water absorption of the film. When plasticizer concentrations were increased to 60%, the tensile stress and Young’s modulus of plasticized films dropped regardless of plasticizer type. However, the thin film with addition of 30% sorbitol plasticizer demonstrated a steady value of Young’s modulus (60.17 MPa) with an increase in tensile strength (13.61 MPa) of 46%, while the lowest combination of tensile strength and Young’s modulus is the film that was plasticized with 60% glycerol, with 2.33 MPa and 16.23 MPa, respectively. In summary, the properties and performance of cornstarch-based film were greatly influenced by plasticizer types and concentrations. The finest set of features in this research appeared in the film plasticized with 30% sorbitol, which achieved the best mechanical properties for food packaging applications

The potential of chalcone-capped gold nanoparticles for the management of diabetes mellitus

Searching for new natural bioactive capping agents represent an urgent priority in the green synthesis of metal nanoparticles. Additionaly, the biosaftey of metal nanparticles is a major concern especially in medical applications. Recently, the use of pharmacollogicaly active natural products as capping agents has been deployed to avoid toxic effects during the nanoparticles preparation and to enhance their drugability compared with convential drugs. Helichrysum foetidum is a South African medicinal plant used in folk medicine for the treatment of different human pathologies, and it is known to contain a variety of bioactive compounds. Herein, the total extract and two pure chalcones, helichrysetin and helichrysin, isolated from the same plant were successfully used to synthesize quasi-monodispersed gold nanoparticles in the size range of 2–12 nm. The bio-evaluation of samples indicated that the AuNP/capping agent conjugates are biostable, and have different biological profiles from the total extract/pure compounds. The enzymatic inhibition assays showed significant inhibition by the total extract, helichrysetin and their gold nanoparticles. Interestingly, a similar activity was observed for glucose uptake in HEK293 treated cells. On the other hand, all the tested samples relatively demonstrated no cytotoxicity when tested against the HaCaT keratinocytes. In conclusion, the study demonstrated potential enhancement of glucose uptake in mammalian kidney cells, and inhibition of carbohydrate-hydrolysing enzymes by green synthesized gold nanoparticles of H. foetidum. It also provides a therapeutic appraisal of AuNPs/chalcones conjugate towards the development of antidiabetes drugs derived from H. foetidum and its gold nanoparticles

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

Prediction of the pollutants movements from the polluted industrial zone in 10th of Ramadan city to the Quaternary aquifer

Abstract There are some sources of pollution of the groundwater such as the industrial, agriculture, domestic activities and the oxidation ponds that are considered collection points for waste disposal plants. The motivations to do this work were: (1) investigating the concentrations of pollutants in the oxidation ponds and well surrounding the 10th Ramadan city and (2) predicting the groundwater flow and the pollutant transport to the groundwater from the pollution source using a numerical simulation (MODFLOW-2000 with MT3D code). The samples of groundwater were collected from the wells that spread around the studied area as well as many samples were collected from the oxidation ponds to investigate the concentrations of pollutants in these samples and predict the pollutant transport to the groundwater over 30 years. The results illustrated that the ion concentration of most samples from the oxidation ponds resources contained Al3+, Fe2+, Sr2+, Ni2+, and Cr2+ which were exceeding the acceptable limit of WHO (International standards for drinking water, WHO, Geneva, 1996) standards. The results also demonstrated that most of the analyzed groundwater samples are polluted with strontium (Sr2+), aluminum (Al3+), and iron (Fe2+). The simulation predicted that the pollutants movements toward the northeast of the study zone over a long-term period (30 years)

Heavy Metal Removal from the Water of the River Nile Using Riverbank Filtration

Riverbank filtration (RBF) is considered as a natural treatment process. During this process, a group of chemical, physical, and biological processes occur when water moves through the soil along the bank of the River Nile, which can act as a conventional treatment process. RBF is one of the most effective solutions that the Egyptian government and responsible parties should embrace. Egypt has started to use the RBF technique widely in many sites through the path of the River Nile. This study provides a detailed analysis of the RBF technique; it represents the outlet quality of the water in a study performed on the River Nile. The effect of RBF on water quality can be measured using the software designed for this study. The study&rsquo;s main aim is to improve the water quality of the River Nile by removing heavy metals from the water by using an effective and fast method of treatment, which is riverbank filtration. The results of the research&rsquo;s experimental study show the average percentage of metal removal for iron, cobalt, lead, zinc, and copper are 74.04%, 74.44%, 70.72%, 75.1%, and 70.8%, respectively. These results have proved that RBF acts as a substantial barrier versus heavy metals

Structural Identification of a 90 m High Minaret of a Landmark Structure under Ambient Vibrations

This paper presents the operational modal analysis of a 90-m-high RC minaret of an iconic mosque considered as a landmark of the city. The minaret was monitored for three days with 11 tri-axial MEMS accelerometers. The purpose of the study was to observe the behavior, develop a representative finite element (FE) model, and establish baseline data for health monitoring studies. The modal properties were extracted using three operational modal analysis techniques (OMA): Enhanced Frequency Domain Decomposition (EFDD), Stochastic Subspace Identification (SSI), and Natural Excitation Technique with Eigensystem Realization Algorithm (NExT-ERA). The first 10 identified modes were below 7 Hz. Eight modes out of the ten were bending-dominant, while the remaining two were torsion-dominant. A FE model was also developed in ETABS to ascertain and compare the response of the structure with the identified results. From the FE model, the modes corresponding to the first ten identified modes were considered for comparison with the identified frequencies from ambient monitoring. The maximum 7.71% error was observed between the experimental and numerical frequencies. The error was minimized by using the manual updating the material properties and adding the weight of nonstructural elements. The variation of identified modal frequencies with ambient temperature was observed to be linearly dependent to a reasonable degree. A general trend of decreasing identified frequencies was observed with the rise in temperature

Influence of Temperature in Degradation of Organic Pollution Using Corona Discharge Plasma

Dye solution temperature influences the elimination efficiency of water-soluble and anionic acid dye. Acid Blue 25 dye, using a gas–liquid electrical discharge system, was successfully investigated. The results showed an increase in the percentage of dye decolorization from 91.16% to 96.12% when the dye solution temperature was increased from 278 K to 308 K. However, the initial dye decolorization percentage was decreased with the further increase in dye solution temperature from 318 K to 358 K. The 2D simulation model was introduced to consider the influence of temperature and the electric field generated by corona discharge plasma in air and water. Results also showed a great match between the experimental and the simulation results. The reaction rates of dye degradation were analyzed using the Arrhenius equation. Furthermore, pseudo-zero-, pseudo-first-, and pseudo-second-order models were used to determine the reaction kinetics. The best fit for the experimental data would follow the pseudo-first-order model. Finally, electrical energy per order, energy yield, and experimental degradation data were calculated to investigate the cost analysis