Reactivity of O-Drug Bond in some Suggested Voltarine Carriers: Semiempirical and ab Initio Methods

 تمت مناقشة إمكانية استخدام مادة حاملة مقترحة جديدة (D) لعقار ديكلوفيناك (فولتارين) باستخدام حسابات ميكانيكا الكم. تم استخدام طرق الحساب (PM3) و (DFT) لتحديد مسار التفاعل لطاقات كسر الرابطة (O-Drug). تم استخدام مجموعات مختلفة الأدوية كحاملات لعقاقير أولية من ديكلوفيناك (في الفراغ كوسط تفاعل) عند الشكل الهندسي التوازني. تضمنت الحسابات التركيب الهندسي وبعض الخواص الفيزيائية، بالإضافة إلى السمية والنشاط البيولوجي وخصائص NLO للدواء مع حوامله، والتي درست باستخدام طريقة HF. تم إجراء العمليات الحسابية بواسطة برنامج .Gaussian 09 تم إجراء المقارنة بين الطاقات الكلية للمواد المتفاعلة وطاقات التنشيط والحالات الانتقالية إلى الحالة النهائية. تهدف العقاقير الأولية المقترحة إلى تحسين خصائص حوامل الديكلوفيناك والحصول على بدائل جديدة للناقلات المعتمدة نظريا.In this work, the possibility to use new suggested carriers (D= Aspirin, Ibuprofen, Paracetamol, Tramal) is discussed for diclofenac drug (voltarine) by using quantum mechanics calculations. The calculation methods (PM3) and (DFT) have been used for determination the reaction path of (O-D) bond rupture energies. Different groups of drugs as a carrier for diclofenac prodrugs (in a vacuum) have been used; at their optimized geometries. The calculations included the geometrical structure and some of the physical properties, in addition to the toxicity, biological activity, and NLO properties of the prodrugs, investigated using HF method. The calculations were done by Gaussian 09 program. The comparison was made for total energies of reactants, activation energies, and transition states to final products. The suggested prodrugs aim to improve the diclofenac carrier's properties and obtain new alternatives for the approved carriers theoretically

Seismic behavior of a strengthened full scale reinforced concrete building using the finite element modelling approach

In Iraq, the increase in earthquake activity was observed, but most of the existing buildings can still suffer from severe injury or destruction, and therefore can cause major issues. In this paper, we performed numerically analyses by experimental modeling to demonstrate efficiency using final element analysis (FEA) in the development of modern solutions (FEA) in the development of modern solutions to maintain existing structures from the risk of earthquakes. Using ABAQUS software that supports dynamic analysis, and uses this model to use models for several ways to enhance the earthquake center. This model was a large-scale 4 building tested using a doctor dynamic test (PSD). Experimental models were performed by extending RC walls with various connectivity details in existing buildings to comply with gravity design only for this building. The goal of this study was to determine the impact of adding an above RC wall as a way of modernization, including the design of Dowels and their contribution to the new mouse wall's connection to the existing RC buildings. These enhancements are performed by converting the selected compartment to the new inlet wall RC [2]. The result of analysis modeling is 4.11% of the proportion of differences in the X direction in the upper layer displacement of Abaqus software and the experimental test of Elsa results, and 2.15% of the negative direction X is 4.11%. an accurate similarity and exact building modeling. After verification process, three earthquake enhancement methods are used Next analysis

Thermo-hydrodynamic Analysis of Misaligned Journal Bearing Considering Surface Roughness and Non-Newtonian Effects

This paper presents a numerical simulation for the combined effect of surface roughness and non-Newtonian behavior of the lubricant on the performance of misaligned journal bearing. The modified Reynolds equation to include the effect of non-Newtonian lubricant and bearing surface roughness has been formulated. The model accounts for the lubricant viscosity dependence on temperature and shear rate. In order to make a complete thermo-hydrodynamic analysis (THD) of rough surface misaligned journal bearing lubricated with non-Newtonian lubricant, the modified Reynolds equation coupled with the energy, heat conduction equations, the equation related the viscosity and temperature with appropriate boundary conditions have been solved simultaneously. The performance characteristics of the bearing were presented with different roughness parameter for the pressure, temperature, load carrying capacity, misalignment moment and friction force. The computer program prepared to solve the governing equations of the problem has been verified by comparing the results obtained through this work with that published by different workers. It has been found that the results are in a good agreement .The results obtained in the present work showed that the surface roughness characteristics of opposing surfaces and its orientation play an important role in affecting the performance parameters of the bearing. It has been shown that the load in rough aligned journal bearing is higher than that in rough misaligned journal bearing for all surface roughness patterns (γ). An increase in load has been calculated and found to be 29.5% for the bearing with moving roughness while it becomes 32% for the bearing with stationary roughness

Diagnosis of Autism Spectrum Disorder Based on Symptoms and Face Recognition

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that has various effects on language, speech, and communication of individuals. When ASD is detected in the earlier stages of life, especially in childhood, there would be many identifiers that would aid in the strategizing of the right therapeutic plan at the right time period. Human faces have important markers that would aid in the identification of ASD through the analyzation of facial features and eye contact. There are other Artificial Intelligence-aided means of detection of ASD through the studying of various symptoms and finding patterns. In this research, we developed two systems that would aid in the diagnosis of Autism Spectrum Disorder in children, one of which uses a transfer-learning-based face detection framework. And the other system uses a decision-tree-based system to identify Autism in chlidren based on symptoms. Various machine learning and deep learning techniques were applied

Novel triazine-functionalized tetra-imidazolium hexafluorophosphate salt : synthesis, crystal structure and DFT study

Please read abstract in the article.Research data for this article available at: CCDC Cambridge Crystallographic Data Center Crystallographic data (https://www.ccdc.cam.ac.uk/structures/search?id=doi:10.5517/ccdc.csd.ccz83y8&sid=DataCite)Universiti Sains Malaysia (USMhttp://www.elsevier.com/ locate/molstruc2020-12-15hj2020Chemistr

A Deep Learning Algorithm for Lung Cancer Detection Using EfficientNet-B3

Lung carcinoma is one of the main causes of deaths over the whole world, causing a global burden of morbidity and mortality. Detecting lung tumors at their early stages can help reducing the risk of having lung cancer. This paper proposes a deep learning algorithm using EfficientNet B3 for lung cancer detection. The purpose is to improve detection accuracy highlighting potential to revolutionize the field of medical imaging and improve patient care. The proposed approach is build based on EfficientNet B3 model to classify four different types of lung cancer. The approach used CT scan images labeled into Normal, Squamous.cell.carcinoma, Large.cell.carcinoma, and Adenocarcinoma for the purpose of lung cancer detection. The results showed that the proposed model provided an improvement rate of 2.13% compared with the best-trained classifier with accuracy of 96%. This model can be generalized to improve lung cancer detection. The finding of deep neural networks, particularly EfficientNet B3, in supporting the diagnosis and detection of the lung disease, particularly in its early times

Correlation with renin-angiotensin-aldosterone and glomerular filtration rate in chronic renal failure patients

Background: One of the more significant hormonal systems, the renin-angiotensin-aldosterone system, controls the kidney function, adrenal gland through its effect on the balance of sodium and potassium, blood pressure, fluid volume, and also manages the functions of cardiovascular. Objective: To clarify the interrelationship between renal dysfunction and renin-angiotensin-aldosterone system. Patients and Methods: One hundred samples were collected from December 1, 2022, to February 18, 2023, from Al Shams Medical Laboratories (56 male, and 44) female, age range (of 45-60 years), all of them were volunteers suffering from chronic renal failure in the third stage the average glomerular filtration rate was 35. 70 ± 0.37 125 mL/min/1.73m2. and under conservative treatment. Kidney function test, active renin, angiotensin II, and aldosterone were assessed in the serum of all subjects. The p - value of differences less than 0.05 is measured significant, and uses the statistical package for the social sciences (23) software to calculate the correlation coefficient between various parameters. Results: The result shows relationship between the changes in GFR with creatinine, urea and active renin, the mean GFR showed significant negative correlated with mean creatinine (R = -0.76, p < 0.01. As well as the mean GFR with mean urea (R = -0.64, p < 0.01). The mean GFR also showed significant negative correlated with mean active renin in (R = -0.41, p < 0.01). Also, the mean serum active renin level was significantly positive correlated with mean aldosterone (R =0.33, p < 0.05). Conclusion: Renin enzyme is inversely related to renal dysfunction, so when the glomerular filtration rate decrease, the higher the renin increased, and as a result, the increase in blood pressure in chronic renal failure patients

A review on material analysis of food safety based on fluorescence spectrum combined with artificial neural network technology

Aiming at the problem that it is difficult to achieve rapid and accurate detection of pesticide residues, the artificial neural network method is used to separate the mixed fluorescence spectra in the measurement of acetamiprid pesticide residues, and a fluorescence spectrum that can quickly detect the pesticide residues of acetamiprid on solid surfaces is designed. According to the back-propagation algorithm, the three-layer artificial neural network principle is used to detect the acetamiprid residue in the mixed system of acetamiprid and filter paper with severely overlapping fluorescence spectra. In the range of 340nm~400nm, using the fluorescence intensity values ​​at 20 characteristic wavelengths as the characteristic network parameters, after network training and testing, the recovery rates of acetamiprid concentrations of 40mg/kg and 90mg/kg are 102% and 97%, respectively. The relative standard deviations of the determination results were 1.4% and 1.9%, respectively. The experimental results show that the BP neural network-assisted fluorescence spectroscopy method for the determination of acetamiprid pesticide residues on filter paper has the characteristics of fast network training, short detection period, and high measurement accuracy

Modelling of inactivation of microorganisms in the process of sterilization using high pressure supercritical fluids

Abstract High hydrostatic pressure technology is a relatively new method for the food industry and is considered more as an alternative to traditional storage methods such as thermal processes. Inactivation of spores, models, yeasts, and viruses has been demonstrated by this method. Although issues related to the safety and longevity of food, as well as their legal permits, require extensive case studies, the available experimental findings can be useful in expanding the potential applications of high pressure in the food industry. In this paper, CO2 is used as a fluid. Increasing the pressure in Weibull and log-logistic models from 2.5 MPa to 10 MPa has reduced the processing time from 700 minutes to 70 and 60 minutes, respectively. The log-logistic model in predicting the process of inactivation of microbes compared to the Weibull model has been the lowest, and also the log-logistic model has a suitable ability to predict the shoulder of the chart if the Weibull model does not have this ability and its error is almost high. Increasing the increase in pressure has increased the level of inactivation of Salmonella typhimurium and Listeria monocytogenes, except Listeria monocytogenes at a pressure of 6.05 MPa, which reduced inactivation

One Parameter Composite Semigroups of Linear Bounded Operators in Strong Operator Topology of Schatten Class Cp

For semigroups of linear bounded operators on Hilbert spaces, the problem of being in Cp , 0 Keyword