Treatment of oily wastewater by electrocoagulation technology: A general review (2018-2022)

A huge amount of oily wastewater is discharged annually from several industries like petroleum and petrochemical factories. Scientists and researchers are permanently concentrated on creating conventional technologies or identifying novel treatment options for oily wastewaters, since they need to be treated before being discharged into the soil and aquatic ecosystems. Electroc­oagu­lation technology (ECT) is an electrochemical method employed to remove numerous pollutants from domestic and industrial wastewaters. This paper aims to review the recently published articles from 2018 to 2022 concerned with ECT for oily wastewater remediation. Based on the present review, it is obvious that ECT is strongly dependent on the value of electric current or voltage applied to provide the required amounts of electro-coagulants for efficient remediation, reaction time duration for the generation of electro-coagulants and pollutants elimination, and electrode configuration such as shape, type of metal, and distance between electrodes. Other operating parameters include solution pH (since some pollutants are removed based on their cationic or anionic nature), type of electrolyte which affects the electric conductivity and ohmic drop and stirring speed that may influence the contact among numerous ions throughout the EC reactor. The core findings show that the ECT is highly effective, eco-friendly, and cost-effective in eliminating organic and inorganic pollutants from oily wastewater

A system-theoretic approach to global and local regulation in neuron morphologies

Synaptic plasticity is a crucial neuronal mechanism for learning and memory. It allows synapses to change their strength over time. This dissertation focuses on a particular form of synaptic plasticity called synaptic scaling, a homeostatic mechanism that preserves relative synaptic strengths in an activity-dependent manner. Synaptic scaling is fundamental for neuronal stability, regulating other plasticity mechanisms like Hebbian plasticity or long-term potentiation (LTP). The aims of this dissertation are to explore the implications of synaptic scaling (and other forms of plasticity, such as structural plasticity) on the overall behavior of neurons. This is done using system-theoretic tools and feedback control. We first formulate a biophysical closed loop model of synaptic scaling. We then study how synaptic scaling affect neurons’ behavior in both abstract and reconstructed morphologies. This study reveals important tradeoffs between robustness, convergence rate, and accuracy of scaling. We first look at synaptic scaling as a “global control action” whose main role is to guarantee a steady level of neural activity. We then consider activity-dependent degradation as a “local control action” whose role is to assist the neuron in fine-tuning different desirable spatial concentration profiles. We show that, in extreme scenarios, it can promote a level of competition between synapses that has a destabilizing effect on the overall behavior. At the methodological level, we use compartmental modeling and we focus on the in- teraction between feedback and transport, in linear and nonlinear settings. Using classical system-theoretic tools like Bode and Nyquist analysis and singular perturbation arguments, and more recent tools like contraction and dominance theory, we derive parameter ranges under which synaptic scaling is stable and well-behaved (slow regulation), stable and oscilla- tory (aggressive regulation), and unstable (pathological regulation). We also study the system robustness against static and dynamics uncertainties. Finally, to understand how different plasticity mechanisms simultaneously affect the neuron behavior, we study synaptic scaling in the presence of activity-dependent growth (mimicking a structural plasticity mechanism). This is a third layer of control action shaping the neuron morphology. We find that activity-dependent growth improves the neuron’s performance when synaptic scaling is insufficient

Designing prenatal m-Health interventions through transmigrants reflection on their pregnancy ecology

This dissertation presents the findings from three participatory focus group and co-design sessions with Caribbean transmigrant women in the United States. Informed by their focus group discussions regarding their pregnancy experiences in the United States, the participants produced design ideas that reflected on physical, emotional, informational and social gap themes. The purpose of this study was to understand the challenges affecting the women’s prenatal wellbeing practices, and to conceive a set of recommendations and opportunities for mHealth technology design to assist with prenatal preventative care and management. The study uses the theoretical concept of pregnancy ecology to identify gaps in prenatal health management, and understand participants’ reflection on these gaps through design. Then, the study identifies opportunities for mHealth and HCI research to consider designing tailored interventions to the realities of the expecting immigrant mother, including the role of transnational social support, and embracing the role of entertainment in mental health during pregnancy

ASSESSING THE IMPACT OF ALFALFA (MEDICAGO SATIVA) CROP ON GROUNDWATER RESOURCES IN THE EMIRATE of ABU DHABI USING GEOSPATIAL TECHNIQUES

Groundwater is a major source of fresh water in the world, especially in arid and semi-arid countries like the United Arab Emirates (UAE), where rainfall is not evenly distributed through the four seasons of the year. Therefore, it is necessary to pay serious attention to the importance of preserving groundwater resources. The agriculture sector poses a real threat to groundwater. Irrigated crop cultivation practices change groundwater levels as a result of cultivating crops or farming plants that consume large amounts of water. Alfalfa is an example of a high-water consuming crop, being a widely cultivated crop in the UAE. This research has been conducted with the objective of studying the impact of the alfalfa-cultivated areas on groundwater. It is based on calculating the groundwater level (GWL) in wells located near or inside a number of farms, with the end goal of generating a map that shows the areas planted with alfalfa in the same area for three different years using images provided by the Landsat satellite. The study assessed in a detailed manner, the expansion of alfalfa-cultivated areas in the Emirate of Abu Dhabi. A total of five vegetation indices (VIs) were calculated and stacked with visible and near infrared bands (VNIR), producing a composite image. The image was then classified applying unsupervised ISODATA algorithm. Furthermore, GWL was calculated using two parameters: the height above mean sea level and the depth of groundwater in the wells. The data were provided by the National Water and Energy Center (NWEC). The aim was to study the effect of the cultivation alfalfa crop on groundwater storage. As a result, we detected an ongoing increase in the area occupied by alfalfa in the last two decades, which increased from 102.32 km2 to 430.59 km2 between 2002 and 2020. The output was cross validated with field samples, and the overall accuracy of the method was around 81.7%. The well measurements, which were located near or inside the farms accessed and used in this study, showed that there was a significant decrease in the average groundwater amount in the Emirate of Abu Dhabi from 2005 to 2013 and that the mean groundwater level (MGWL) has decreased from 41.4 m to 5.11 m between the years 2005 and 2017, despite the fact that the amount of precipitation had not significantly changed during the mentioned period. In conclusion, the study indicates that the more the area is planted with Alfalfa, the lower the groundwater levels are

Pre-Service Elementary School Teachers’ learning styles and their Ability to Solve Mathematical Problems according to Polya's Strategy

The purpose of this study is to determine the learning styles of pre-service elementary school teachers at the University of Petra, and to assess their ability to solve mathematical problems according to Polya's strategy. This research was administered to 85 students who had completed a course on basic concepts in mathematics during the second semester of 2013-2014 academic years. To collect the data, the researcher employed two types of instruments: the Learning Style Inventory (LSQ), which was prepared by Honey & Mumford (1992), and the Mathematical Problems Solving Test (MPST) according to Polya's strategy, which was prepared by the researcher. The study concluded that students lack the ability to solve mathematical problems and that the level of students' ability to solve mathematical problems varies depending on the school year. In addition, the study concluded that students' ability to solve mathematical problems varies depending on their learning style. The most frequently preferred learning style was Activist-Reflector style, which showed better performance in solving math problems than other styles. Keywords: Learning styles, math problem solving, G. Poly

Removal of nickel from Ni(II)-NH3-SO2-CO2-H2O system by electrocoagulation, sedimentation and filtration processes

The nickel removal by electrocoagulation of Ni(II)-NH3-CO2-SO2-H2O system was studied in a batch reactor of 50 L useful volume, with stirring and two pairs of aluminum electrodes. The operating parameters were nickel concentration between 255 and 342 mg L-1, current density of 11.0 and 16.6 mA cm-2, pH 8.34±0.06, mean temperature 58.4±3.9 °C and retention time of 50 min. The maximum nickel removal was 99.7 % at 11.0 mA cm-2, specific energy consumption 16.86 kWh kg-1 of Al3+, 2.438 kWh kg-1 of Ni and the adsorption capacity 5819 mg Ni g-1 of Al3+. The precipitate contained a nickel content of 37.2 % and a true density of 2720 kg m-3, hydro­talcite-like structure layered double hydroxides. The unit area of sedimentation was between 0.25 and 1.96 m2 t-1 day, at a density from 971 to 1019 kg m-1 and 53±4 °C. A model for pre­dicting the specific cake resis­tance was estimated as a function of pressure drop and sus­pension concentration at 44.45 kPa and 59.52 kg m-3, resulting in the value of 6.47±107 m kg-1. The average cake humidity was 88 % base humid

The Relationship between the University Students’ Level of Metacognitive Thinking and their Ability to Solve Mathematical and Scientific Problems

The purpose of this study is to investigate the relationship between the university students’ metacognition thinking and their ability to solve mathematical and scientific problems. 172 university students were involved in this study. The researchers employed two types of instruments: metacognition awareness inventory, and a mathematical & scientific problem solving test; which was constructed by the researchers. After the collection of data, the researchers ran a suitable statistical analysis. The study has concluded that Petra University students have a medium level of metacognitive thinking, and that the variables of sex, faculty, high school stream, and the current year in the university had no effect on their level of metacognitive thinking. The study has also shown that these students suffer from a lack of ability in solving mathematical and scientific problems; no significance correlation between the level of metacognitive thinking in the overall scale and the ability to solve mathematical and scientific problems. However, there was a significant correlation between a few factors of metacognitive thinking and the ability to solve mathematical problems, and these are: Procedural Knowledge, Evaluation, Fault Picking, and Managing Knowledge; as well as a significant correlation between Fault Picking and the ability to solve both mathematical and scientific problems. Keywords: metacognitive thinking, problem solving

The most effective techniques of industrial purification processes: a technical review

This paper reviews various separation techniques used in purification processes to remove pollutants like carbon dioxide and hydrogen sulfide from petroleum products. The most effective techniques include absorption, adsorption, cryogenic distillation, chemical looping combustion, and membrane separation. The study reviews over 100 published studies to assess their characteristics, benefits, and drawbacks. The choice of separation technology depends on ideal conditions, cost, efficiency, and energy required in the regeneration phase