This research sought to present a concept of cross-sectional data models, A crucial double data to take the impact of the change in time and obtained from the measured phenomenon of repeated observations in different time periods, Where the models of the panel data were defined by different types of fixed , random and mixed, and Comparing them by studying and analyzing the mathematical relationship between the influence of time with a set of basic variables Which are the main axes on which the research is based and is represented by the monthly revenue of the working individual and the profits it generates, which represents the variable response And its relationship to a set of explanatory variables represented by the years of service of the working individual and the academic achievement of him and the classifier starting with (graduates of the intermediate school or below, graduates of the preparatory school, graduates of institutes, graduates of colleges and universities) Finally sex was divided into two categories: male and female The sample of the research is a group of individuals (100) individuals working in private sector companies with different commercial agencies in Baghdad with financial, administrative, technical, sales and services sectors, namely, the research community And then to extract the estimates of the parameters of the models and the Variations of errors as well as their testing and analysis where it was observed how to control the heterogeneity of variance and increase in degrees of freedom and less multicollinearity among the variables, which illustrates the efficiency and importance and accuracy of this type of models and their importance in making sound decisions and reliable results The results also showed the importance of the years of service on the performance of the working individual and the increase in productivity and efficiency, adding to the practical experience of utmost importance, as well as distinguished individuals working in the achievement of university degree on the rest of the other educational collections.
The catalytic cracking of three feeds of extract lubricating oil, that produced as a by-product from the process of furfural extraction of lubricating oil base stock in AL-Dura refinery at different operating condition, were carried out at a fixed bed laboratory reactor. The initial boiling point for these feeds was 140 ºC for sample (1), 86 ºC for sample (2) and 80 ºC for sample (3). The catalytic cracking processes were carried out at temperature range 325-400 ºC and initially at atmospheric pressure after 30 minutes over 9.88 % HY-zeolite catalyst load. The comparison between the conversion at different operating conditions of catalytic cracking processes indicates that a high yield was obtained at 375°C, according to gasoline pr
... Show MoreThe dynamic behavior of laced reinforced concrete (LRC) T‐beams could give high‐energy absorption capabilities without significantly affecting the cost, which was offered through a combination of high strength and ductile response. In this paper, LRC T‐beams, composed of inclined continuous reinforcement on each side of the beam, were investigated to maintain high deformations as predicted in blast resistance. The beams were tested under four‐point loading to create pure bending zones and obtain the ultimate flexural capacities. Transverse reinforcement using lacing reinforcement and conventional vertical stirrups were compared in terms of deformation, strain, and toughness changes of the tes
Decolorization of red azo dye (Cibacron Red FN-R) from synthetic wastewater has been investigated as a function of solar advanced oxidation process. The photocatalytic activity using ZnO as a photocatalysis has been estimated. Different parameters affected the removal efficiency, including pH of the solution, initial dye concentration and H2O2 concentration were evaluated to find out the optimum value of these parameters. The results proved that the optimal pH value was 8 and the most efficient H2O2 concentration was 100mg/L. Toxicity reduction percent for effluent solution was also monitored to assess the degradation process. This treatment method was able to strongly reduce the color and toxicity of reactive red dye-238 to about (99 an
... Show MoreThis paper investigates the experimental response of composite reinforced concrete with GFRP and steel I-sections under limited cycles of repeated load. The practical work included testing four beams. A reference beam, two composite beams with pultruded GFRP I-sections, and a composite beam with a steel I-beam were subjected to repeated loading. The repeated loading test started by loading gradually up to a maximum of 75% of the ultimate static failure load for five loading and unloading cycles. After that, the specimens were reloaded gradually until failure. All test specimens were tested under a three-point load. Experimental results showed that the ductility index increased for the composite beams relative to the refe
... Show MoreCancer disease has a complicated pathophysiology and is one of the major causes of death and morbidity. Classical cancer therapies include chemotherapy, radiation therapy, and immunotherapy. A typical treatment is chemotherapy, which delivers cytotoxic medications to patients to suppress the uncontrolled growth of cancerous cells. Conventional oral medication has a number of drawbacks, including a lack of selectivity, cytotoxicity, and multi-drug resistance, all of which offer significant obstacles to effective cancer treatment. Multidrug resistance (MDR) remains a major challenge for effective cancer chemotherapeutic interventions. The advent of nanotechnology approach has developed the field of tumor diagnosis and treatment. Cancer nanote
... Show MoreThis paper proposes a neuro-fuzzy system to model β-glucosidase activity based on the reaction’s pH level and temperature. The developed fuzzy inference system includes two input variables (pH level and temperature) and one output (enzyme activity). The multi-input fuzzy inference system was developed in two stages: first, developing a single input-single output fuzzy inference system for each input variable (pH, temperature) separately, using the robust adaptive network-based fuzzy inference system (ANFIS) approach. The neural network learning techniques were used to tune the membership functions based on previously published experimental data for β-glucosidase. Second, each input’s optimized membership functions from the ANF
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