The extraction of pesticides is a critical and urgent issue in the preparation for and determination of pesticide residues. The lack of a quick, easy, and successful extraction process is the most critical and challenging problem, even if diagnostic tools have improved and pesticide residues have been better understood. This study contrasted the QuEChERS method, which uses gas chromatography with a flame ionization detector, with the LLE method, which uses liquid-liquid extraction, in order to extract pyridaben from cucumbers and spiromesifen from tomatoes. The GC-FID device was employed to ascertain the spiromesifen LOD and LOQ, which were 0.002 μg mL-1 and 0.006 g mL-1, respectively, according to the findings from the QuEChERS technique (95.6% recovery, RSD 0.28%-1.95%) and the LLE method (85.4% recovery, RSD 0.25%-6.9%). When testing the cucumber sample for pyridaben, the LLE method yielded an RSD of 0.12-0.21 percent, while the QuEChERS method yielded 95.22 percent. Pyridaben has limits of detection (LOD) of 0.001 μg mL-1 and quantification (LOQ) of 0.003 μg mL-1. A higher recovery level in both samples suggests that the QuEChERS method may be preferable to the LLE for extracting spiromesifen from tomatoes and pyridaben from cucumbers, according to the data. This was followed by a comparison of the two sets of results using a paired t-test with a 95% confidence level. Thus, the two methods are statistically distinct at the 95% confidence level. Among the most environmentally safe and sustainable solutions in this field, the QuEChERS method stands out for its quick sample preparation, affordability, ease of use, effectiveness, and absence of toxic chemicals and solvents.
Business organizations strive to reach organizational excellence, in instruction to maintain their position in the market, so the research started from the problem of the weakness of the senior leaders in the two companies investigated in the management and sustainability of work, as well as their inability to face challenges that could affect the work of the two companies in the future, especially the lack of organizational of the future and the prediction of those events, so the two companies seek to explore and invest opportunities to achieve organizational excellence. The research aims to know the role of Ambidexterity leadership behaviors in organizational excellence in my company .and create ideas that will achieve organizati
... Show MoreThe world faces, in the last years of the last century and the beginning
of the current century i.e. the 21st century, a great expansion and a large
openness on new worlds in studies differ in their development, detection of
thinking methods and practice of mental processes.
The recent studies have proved an increase in the scientific
achievement among students through the presence of new techniques one of
which is Landa Organizing and Exploring Model concerning Physiology that
deals with various body organs.
This research aims at identifying the effectiveness of Landa Model on
the achievement of the Technical Medicine Institute students in Physiology so
as to be sure of the following nil hypothesis: there i
Radiological assessment for the East Baghdad oilfield-southern part was conducted in the current study. 10 samples (scale, soil, sludge, water, and oil) from the different stages of oil production were collected. 232Th, 226Ra, and 40K in the samples were analyzed with 40% efficiency for Gamma spectrometry. system based on HPGe. The findings indicated that the examined sites exhibit comparatively lower levels of NORM contamination, in contrast to other global oilfields. Nevertheless, certain areas, particularly those within separation stages, demonstrate relatively elevated NORM concentrations exceeding the global average in soil and sludge. The maximum value of 226Ra, 232Th, was found in sludge sample the findings indicated that ove
... Show MoreParticulate matter (PM) emitted from diesel engine exhaust have been measured in terms of mass, using
99.98 % pure ethanol blended directly, without additives, with conventional diesel fuel (gas – oil),to
get 10 % , 15 %, 20 % ethanol emulsions . The resulting PM collected has been compared with those
from straight diesel. The engine used is a stationary single cylinder, variable compression ratio Ricardo
E6/US. This engine is fully instrumented and could run as a compression or spark ignition.
Observations showed that particulate matter (PM) emissions decrease with increasing oxygenate
content in the fuel, with some increase of fuel consumption, which is due to the lower heating value of
ethanol. The reduction in
Zinc oxide (ZnO) nanostructures were synthesized through the hydrothermal method at various conditions growth times (6,7 and 8 hrs.) and a growth temperature (70, 90, and 100 ºC). The prepared ZnO nanostructure samples were described using scanning electron microscopy (SEM) and X-ray diffractometer to distinguish their surface morphologies and crystal structures. The ZnO samples were confirmed to have the same crystal type, with different densities and dimensions (diameter and length). The obtained ZnO nanostructures were used to manufacture gas sensors for NO2 gas detection. Sensing characteristics for the fabricated sensor to NO2 gas were examined at different operating temperatures (180, 200, 220, and 240) ºC with a low gas concentrati
... Show MoreThe impact of decorating Fe, Ru, Rh, and Ir metals upon the sensing capability of a gallium nitride nanotube (GaNNT) in detecting chlorine trifluoride (CT) was scrutinized using the density functionals B3LYP and B97D. The interaction of the pristine GaNNT with CT was a physical adsorption with the sensing response (SR) of approximately 6.9. After decorating the above-mentioned metals on the GaNNT, adsorption energy of CT changed from −5.8 to −18.6, −18.9, −19.4, and −20.1 kcal/mol by decorating the Fe, Ru, Rh, and Ir metals into the GaNNT surface, respectively. Also, the corresponding SR dramatically increased to 39.6, 52.3, 63.8, and 106.6. This shows that the sensitivity of the metal-decorated GaNNT (metal@GaNNT) increased by in
... Show MoreParasitological examination of gills of three species of sparid fishes in the territorial waters of Iraq was performed, two diplectanid monogenoids were isolated and described; Lamellodiscus indicus Tripathi, 1959 from both Haffara seabream Rhabdosargus haffara (Forsskål, 1775) and Goldline seabream R. sarba (Forsskål, 1775) and Protolamellodiscus senilobatus Kritsky, Jiménez-Ruiz and Sey, 2000 from King soldierbream Argyrops spinifer (Forsskål, 1775). The record of the parasites is considered new to the parasite fauna of Iraq. The redescription of L. indicus for the first time which is collected from a new distribution area (Arabian Gulf). R. haffara is considered a new host record .
The present study develops an artificial neural network (ANN) to model an analysis and a simulation of the correlation between the average corrosion rate carbon steel and the effective parameter Reynolds number (Re), water concentration (Wc) % temperature (T o) with constant of PH 7 . The water, produced fom oil in Kirkuk oil field in Iraq from well no. k184-Depth2200ft., has been used as a corrosive media and specimen area (400 mm2) for the materials that were used as low carbon steel pipe. The pipes are supplied by Doura Refinery . The used flow system is all made of Q.V.F glass, and the circulation of the two –phase (liquid – liquid ) is affected using a Q.V.F pump .The input parameters of the model consists of Reynolds number , w
... Show MoreA new efficient Two Derivative Runge-Kutta method (TDRK) of order five is developed for the numerical solution of the special first order ordinary differential equations (ODEs). The new method is derived using the property of First Same As Last (FSAL). We analyzed the stability of our method. The numerical results are presented to illustrate the efficiency of the new method in comparison with some well-known RK methods.
Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables
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