A study conducted a laboratory experiment to measure the release of potassium and the dissolution of feldspar minerals in soils from different locations in Karbala Province (Ain Al-tamur, Qasr Al-Akhyar, Fadak Farm). The study involved the addition of organic acids (fulvic and humic) and mineral acids (sulfuric and phosphoric) at concentrations of 5% and 10% to sand-separated soil samples obtained through wet sieving. Feldspar minerals were identified using a polarized light microscope, and the percentage of each type of feldspar mineral was calculated. The results demonstrated that organic acids outperformed mineral acids in releasing potassium at both concentrations. Among the organic acids, fulvic acid released more potassium than humic acid, with the highest amounts recorded at the Qasr Al-Akhyar site (198.65 and 246.67 mg kg−1 for 5% and 10% concentrations, respectively). In comparison, the values for humic acid at the same site were 142.75 and 194.60 mg kg−1 for 5% and 10% concentrations, respectively. For mineral acids, sulfuric acid released the highest amount of potassium, reaching 100.88 mg kg−1 at a 10% concentration at the Qasr Al-Akhyar site, while the lowest value was recorded with phosphoric acid at a 5% concentration, measuring 69.23 mg kg−1 at the Ain Al-tamur.site. Feldspar minerals were identified in both plagioclase and potassium feldspar forms. Plagioclase feldspars accounted for 9.14%, 13.12%, and 9.12% at the Ain Al-tamur., Qasr Al-Akhyar, and Fadak Farm sites, respectively. potassium feldspars constituted 11.65%, 22.80%, and 13.25% in the sand-separated samples from the three sites.
In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A
... Show MorePolymer blended electrolytes of various concentrations of undoped PAN/PMMA (80/20, 75/25, 70/30, 65/35 and 60/40 wt%) and doped with lithium salts (LiCl, Li2SO4H2O, LiNO3, Li2CO3) at 20% wt have been prepared by the solution casting method using dimethylformamide as a solvent. The electrical conductivity has been carried out using an LCR meter. The results showed that the highest ionic conductivity was 2.80x10-7 (Ω.cm)-1 and 1.05x10-1 (Ω.cm)-1 at 100 kHz frequency at room temperature for undoped (60% PAN + 40% PMMA) and (80% PAN + 20% PMMA) doped with 20%wt Li2CO3 composite blends, respect
... Show MoreThe paper generates a geological model of a giant Middle East oil reservoir, the model constructed based on the field data of 161 wells. The main aim of the paper was to recognize the value of the reservoir to investigate the feasibility of working on the reservoir modeling prior to the final decision of the investment for further development of this oilfield. Well log, deviation survey, 2D/3D interpreted seismic structural maps, facies, and core test were utilized to construct the developed geological model based on comprehensive interpretation and correlation processes using the PETREL platform. The geological model mainly aims to estimate stock-tank oil initially in place of the reservoir. In addition, three scenarios were applie
... Show MoreNanofluids, liquid suspensions of nanoparticles (Np), are an effective agent to alter the wettability of oil-wet reservoirs to water-wet thus promoting hydrocarbon recovery. It can also have an application to more efficient carbon storage. We present a series of contact angle (θ) investigations on initially oil-wet calcite surfaces to quantify the performance of hydrophilic silica nanoparticles for wettability alteration. These tests are conducted at typical in-situ high pressure (CO2), temperature and salinity conditions. A high pressure–temperature (P/T) optical cell with a regulated tilted surface was used to measure the advancing and receding contact angles at the desired conditions. The results showed that silica nanofluids can alte
... Show MoreAlginate is one of the natural biopolymers that is widely used for drug formulations, combination of alginate with other polymers, such as gum acacia, pectin, and carrageenan can increase mechanical strength, therefore, can reduce leakage of the encapsulated active pharmaceutical ingredient from the polymer matrix. Interaction of alginate and these polymers can occur via intermolecular hydrogen bonds causing synergism, which is determined from the viscosity of polymer mixture.
Alginate was combined with gum acacia/pectin/carrageenan in different blending ratios (100:0, 75:25, 50:50, 25:75, and 0:100) with and without addition of CaCl2. The synergism effect is obtained from the design of experimental (DoE), and calculati
... Show MorePolymer additives binder system provides many properties useful in thermal energy storage (TES) then developed the efficient energy storage materials and green strength bodies system.
This paper studies the thermal energy storage property for polyvinyl alcohol (PVOH) / paraffin wax (WPw) blends. To enhance paraffin wax thermal conductivity, PVOH as a material which high conductivity was employed. A fixed weight of Paraffin wax was dispersed with PVOH heterogeneously at different additive weights ratios of PVOH/Pw (50/50, 67/33, 75/25, and 80/20) wt. ratio respectively. The composite material was prepared using wetted pressing method.
Both base materials (polyvinyl alcohol and paraffin wax) were scanned using differential
... Show MoreThe massive growth of the automotive industry and the development of vehicles use lead to produce a huge amount of waste tire rubber. Rubber tires are non-biodegradable, resulting in environmental problems such as fire risks. In this search, the flexural behavior of steel fiber reinforced self-compacting concrete (SFRSCC) beams containing different percentages and sizes of waste tire rubbers were studied and compared them with the flexural behavior of SCC and SFRSCC. Micro steel fiber (straight type) with aspect ratio 65 was used in mixes. The replacement of coarse and fine aggregate was 20% and 10% with chip and crumb rubber. Also, the replacement of limestone dust and silica fume was 50%, 25%, and 12% with ground rubbe
... Show MoreDeep Learning Techniques For Skull Stripping of Brain MR Images
A progression of Polyaniline (PANI) and Titanium dioxide (TiO2) nanoparticles (NPs) were prepared by an in-situ polymerization strategy within the sight of TiO2 NPs. The subsequent nanocomposites were analyzed using Fourier-transform infrared spectra (FTIR), X-ray diffraction (XRD), Scanning Electron Microscopy (SEM), and Energy Dispersive X-Ray Analysis (EDX) taken for the prepared samples. PANI/TiO2 nanocomposites were prepared by various compound materials (with H2SO4 0.3 M and without it, to compare the outcome of it) by the compound oxidation technique using ammonium persulfate (APS) as oxidant within the sight of ultrafine grade powder of TiO2 cooled in an ice bath.
... Show MoreSamples of gasoline engine oil (SAE 5W20) that had been exposed to various oxidation times were inspected with a UV-Visible (UV-Vis) spectrophotometer to select the best wavelengths and wavelength ranges for distinguishing oxidation times. Engine oil samples were subjected to different thermal oxidation periods of 0, 24, 48, 72, 96, 120, and 144 hours, resulting in a range of total base number (TBN) levels. Each wavelength (190.5 – 849.5 nm) and selected wavelength ranges were evaluated to determine the wavelength or wavelength ranges that could best distinguish among all oxidation times. The best wavelengths and wavelength ranges were analyzed with linear regression to determine the best wavelength or range to predict oxidation t
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