Fuel Economy at the Heat Treatment Furnaces of Steel Cast Pieces

The paper presents a study made at the annealing furnaces for homogenization of cast pieces regarding the replacement of marsh gas with blast furnace gas, in a proportion of 100%. In this way an important economy of marsh gas is achieved, representing a special interest because its international deficit and its putting up the price

Monitoring Techniques for Inorganic and Organic Pollutants in Soils Around an Integrated Iron and Steel Plant

In this paper the analytical techniques of X-Ray Fluorescence (XRF) and Gas Chromatography with Electron Capture Detection (GC-ECD) and coupled with Mass Spectrometry (GC-MS) are used in order to assess the level of industrial and agricultural pollution of soils. The soil samples were collected from Galati County, near an industrial plant and near cultivated areas. In this study, it is investigated the way in which the anthropic activities influence the quality of the environment, due to the contribution of inorganic and organic elements enrichments

Geotechnical aspects of alluvial soils at different depths under sodium chloride action in Najran region, Saudi Arabia: Field supported by laboratory tests

The current research study is aimed at studying the impact of sodium chloride on the performance of semi-arid soils in the Najran area of Saudi Arabia. Experimental work has been undertaken to investigate how adding salt to the semi-arid soil collected in the Najran area affects the boundaries of Atterberg, compaction characteristics, California bearing ratio, and shear strength. All testing was conducted on soil samples from different zones of the Najran area at varying depths of 1.5, 3, and 4.5 m along the soil profiles. The soil samples were analyzed individually and then compared with the same soil samples mixed with NaCl at different percentages of 5, 10, and 20% by weight of the dry soil. Using advanced techniques, such as the scanning electron microscope, energy dispersive x-ray analysis, and X-ray diffraction analysis, the stabilization process was examined. The findings revealed that NaCl significantly impacts the geotechnical characteristics of semi-arid soils. The maximum dry density increased from 1.995, 1.93, and 1.96 to 2.02, 1.99, and 2.03 g/cm3, and the optimal water content decreased from 9.47, 13.7, and 11.29 to 7.01, 9.58%, and 8.09% with 20% NaCl added at various depths, respectively. Shear resistance parameters were improved by adding 20% NaCl, where the soil cohesion increased from 0.1333, 0.0872, and 0.0533 to 0.1843, 0.1034, and 0.0372 kg/cm2, and the angle of internal friction increased from 24°, 25.5°, and 29° to 27.8°, 30°, and 33°, respectively. The liquid and plastic limits and, in turn, the plasticity index reduced as the added percentage of NaCl increased. Furthermore, the California bearing ratio percentages significantly increased and reached more than 50%. As a result, it is established that NaCl is an excellent stabilizer, especially at 20% concentration, and might be used as a sub-base substance in highway construction

Utilization of artificial intelligence approach for prediction of DLP values for abdominal CT scans: A high accuracy estimation for risk assessment

PurposeThis study aimed to evaluate Artificial Neural Network (ANN) modeling to estimate the significant dose length product (DLP) value during the abdominal CT examinations for quality assurance in a retrospective, cross-sectional study.MethodsThe structure of the ANN model was designed considering various input parameters, namely patient weight, patient size, body mass index, mean CTDI volume, scanning length, kVp, mAs, exposure time per rotation, and pitch factor. The aforementioned examination details of 551 abdominal CT scans were used as retrospective data. Different types of learning algorithms such as Levenberg-Marquardt, Bayesian and Scaled-Conjugate Gradient were checked in terms of the accuracy of the training data.ResultsThe R-value representing the correlation coefficient for the real system and system output is given as 0.925, 0.785, and 0.854 for the Levenberg-Marquardt, Bayesian, and Scaled-Conjugate Gradient algorithms, respectively. The findings showed that the Levenberg-Marquardt algorithm comprehensively detects DLP values for abdominal CT examinations. It can be a helpful approach to simplify CT quality assurance.ConclusionIt can be concluded that outcomes of this novel artificial intelligence method can be used for high accuracy DLP estimations before the abdominal CT examinations, where the radiation-related risk factors are high or risk evaluation of multiple CT scans is needed for patients in terms of ALARA. Likewise, it can be concluded that artificial learning methods are powerful tools and can be used for different types of radiation-related risk assessments for quality assurance in diagnostic radiology

Notable changes in geochemical and mineralogical characteristics of different phases of episyenitization: insights on the radioactive and shielding of the late phase

Kab Amiri granites are submitted to post-magmatic hydrothermal solutions through fracture and faults, causing several alteration processes. The most common processes are episyenitization, saussuritization, hematitization, sericitization, kaolinization, albitization, chloritization, silicification, and muscovitization. Kab Amiri granites are vuggy, with the vugs partially to completely refilled with new constituents. The least episyenitized granites have elevated amounts of Fe, P, Zr, Ni, U, Th, Ba, Y, Hf, Nb, and As, which are correlated with their mobilization from biotite, k-feldspar, plagioclase and metamict zircon. These elemental changes are related the partial albitization, muscovitization, desilicification and chloritizatiom, which lead to the mobilization of these elements and forming of specific mineral association in the least altered granites such as autonite, tripiolite, columbite, Zircon and galena. On the second stage, granites were subjected to intense alteration processes by mineralizing fluids, causing wholly muscovitization of biotite and feldspar, albitization of plagioclase, carbonitization and apatitization. Many elements were mobilized from these altered minerals, including Ti, Al, Mn, Mg, Ca, Na, K, Mo, Cu, Pb, Zn, Ag, Co, Sr, V, Cr, Sn, Rb, Ta, Li, Sc, W, S, In, and Tl, leading to definite mineralization as kaslite, monazite, xenotime, polycrase and apatite. The mineralizing fluids in the least and highly episyenitized granites are incorporated in some ore minerals like uranophane, fergusonite, bazzite and garnet. Notably, the presence of elements such as U, Th, and other heavy metals in Kab Amiri granites highlights the potential for these rocks in radiation shielding applications. The unique combination of elements and minerals resulting from the alteration processes can be leveraged for developing new materials or enhancing existing materials used in radiation shielding

Hormonal and inflammatory modulatory effects of hesperidin in hyperthyroidism-modeled rats

The goal of the current study was to investigate the hormonal modulatory efficiency of hesperidin, through its regulatory potential of immunological, inflammatory, and/or antioxidant changes in on hyperthyroidism modeled adult female albino rats. Both normal and hyperthyroidism modeled rats (140-160g) were randomly divided into four groups (10 animals each) as follows: 1) healthy animals were daily ingested with saline for six weeks, and served as control group, 2) healthy animals were intraperitoneally injected with hesperidin (50 mg/kg/day) for a similar period, 3) hyperthyroidism-modeled animals without any treatment acted as positive control, and 4) hyperthyroidism-modeled animals were treated intraperitoneally with hesperidin for a similar period. The findings showed that hesperidin significantly modulated hyperthyroidism deteriorations, this was evidenced by a remarkable decline in serum T4, FT4, T3, FT3, TNF-α, IL1β-, IL4-, IL-6, and IL-10 levels, with a minor increase in TSH and significant raise in CD4+ level. Similarly, valuable improvement was observed in the oxidative status; serum SOD, GPx, CAT, and GSH levels were dramatically enhanced, associated with remarkable drop in MDA and NO levels. Also, hesperidin demonstrated nephro-hepatoprotective and anti-atherogenic potential, this was achieved from the notable reduction in ALAT and ASAT activities as well as urea, creatinine, cholesterol, and triglyceride close to the corresponding values of healthy group. These findings were supported by histological and immunohistochemical ones that showed a notable decrease in the expression of the calcitonin antibody. In conclusion, hesperidin possesses anti-hyperthyroidism, immunoinflammatory regulatory, and antioxidant activities that evidenced from the improvement of physio-architecture of the thyroid gland, reduction of inflammation and restoration of the impaired oxidative stress. This effect might be mechanized through immunological, inflammatory, apoptotic, and/or antioxidant modulatory pathways

Modelling spatial patterns of correlations between concentrations of heavy metals in mosses and atmospheric deposition in 2010 across Europe

Background: This paper aims to investigate the correlations between the concentrations of nine heavy metals in moss and atmospheric deposition within ecological land classes covering Europe. Additionally, it is examined to what extent the statistical relations are affected by the land use around the moss sampling sites. Based on moss data collected in 2010/2011 throughout Europe and data on total atmospheric deposition modelled by two chemical transport models (EMEP MSC-E, LOTOS-EUROS), correlation coefficients between concentrations of heavy metals in moss and in modelled atmospheric deposition were specified for spatial subsamples defined by ecological land classes of Europe (ELCE) as a spatial reference system. Linear discriminant analysis (LDA) and logistic regression (LR) were then used to separate moss sampling sites regarding their contribution to the strength of correlation considering the areal percentage of urban, agricultural and forestry land use around the sampling location. After verification LDA models by LR, LDA models were used to transform spatial information on the land use to maps of potential correlation levels, applicable for future network planning in the European Moss Survey. Results: Correlations between concentrations of heavy metals in moss and in modelled atmospheric deposition were found to be specific for elements and ELCE units. Land use around the sampling sites mainly influences the correlation level. Small radiuses around the sampling sites examined (5 km) are more relevant for Cd, Cu, Ni, and Zn, while the areal percentage of urban and agricultural land use within large radiuses (75–100 km) is more relevant for As, Cr, Hg, Pb, and V. Most valid LDA models pattern with error rates of < 40% were found for As, Cr, Cu, Hg, Pb, and V. Land use-dependent predictions of spatial patterns split up Europe into investigation areas revealing potentially high (= above-average) or low (= below-average) correlation coefficients. Conclusions: LDA is an eligible method identifying and ranking boundary conditions of correlations between atmospheric deposition and respective concentrations of heavy metals in moss and related mapping considering the influence of the land use around moss sampling sites

Modelling spatial patterns of correlations between concentrations of heavy metals in mosses and atmospheric deposition in 2010 across Europe

BackgroundThis paper aims to investigate the correlations between the concentrations of nine heavy metals in moss and atmospheric deposition within ecological land classes covering Europe. Additionally, it is examined to what extent the statistical relations are affected by the land use around the moss sampling sites. Based on moss data collected in 2010/2011 throughout Europe and data on total atmospheric deposition modelled by two chemical transport models (EMEP MSC-E, LOTOS-EUROS), correlation coefficients between concentrations of heavy metals in moss and in modelled atmospheric deposition were specified for spatial subsamples defined by ecological land classes of Europe (ELCE) as a spatial reference system. Linear discriminant analysis (LDA) and logistic regression (LR) were then used to separate moss sampling sites regarding their contribution to the strength of correlation considering the areal percentage of urban, agricultural and forestry land use around the sampling location. After verification LDA models by LR, LDA models were used to transform spatial information on the land use to maps of potential correlation levels, applicable for future network planning in the European Moss Survey.ResultsCorrelations between concentrations of heavy metals in moss and in modelled atmospheric deposition were found to be specific for elements and ELCE units. Land use around the sampling sites mainly influences the correlation level. Small radiuses around the sampling sites examined (5km) are more relevant for Cd, Cu, Ni, and Zn, while the areal percentage of urban and agricultural land use within large radiuses (75-100km) is more relevant for As, Cr, Hg, Pb, and V. Most valid LDA models pattern with error rates of <40% were found for As, Cr, Cu, Hg, Pb, and V. Land use-dependent predictions of spatial patterns split up Europe into investigation areas revealing potentially high (=above-average) or low (=below-average) correlation coefficients.ConclusionsLDA is an eligible method identifying and ranking boundary conditions of correlations between atmospheric deposition and respective concentrations of heavy metals in moss and related mapping considering the influence of the land use around moss sampling sites

Evaluation of Greenhouse Gas Emissions from Reservoirs: A Review

In order to evaluate the greenhouse gas (GHG) emissions from a reservoir or from several reservoirs in a country or a climatic zone, simpler or more complex models based on measurements and analyses of emissions presented in the literature were developed, which take into account one or more reservoir-specific parameters. The application of the models in the assessment of GHG emissions from a multipurpose reservoir gave values that are more or less close to the average values reported in the literature for the temperate zone reservoirs. This is explained by the fact that some models only consider emissions caused by impoundment and not degassing, spillway emissions, and downstream emissions, or those that use different calculation periods. The only model that calculates GHG emissions over the life cycle that occur pre-impoundment, post-impoundment, from unrelated anthropogenic sources and due to the reservoir construction is the model used by the G-res tool. In addition, this tool is best suited for multipurpose reservoirs because it allocates GHG emissions for each use, thus facilitating the correct reporting of emissions. The G-res tool used to calculate GHG emissions from the Stânca-Costești Multipurpose Reservoir shows that this is a sink of GHG with a net emission of −5 g CO2eq/m2/yr (without taking into account the emissions due to dam construction)

An Investigative Study on the Progress of Nanoclay-Reinforced Polymers: Preparation, Properties, and Applications: A Review

Nanoclay-reinforced polymers have attracted considerable universal attention in academic and industrial research due to their outstanding properties and their ever-expanding utilization in diversified applications. In that regard, in the present review, the structure of layered silicate clay, as well as procedures for clay material modification, are outlined. We also discuss the general characterization techniques, synthesis methods, and various properties of polymer–clay nanocomposites (PCNs), and some examples likewise are depicted from the scientific literature. The study’s primary goal is to provide an up-to-date survey of polymer–clay nanocomposites and their specific applications in industries such as automotive, flame-retardant, and biomedical applications, coating, and packaging