Objective: To determine the ability of uVDBP to discern SRNS from steroid-sensitive nephrotic syndrome (SSNS) in Iraqi children. Materials and Methods: This cross-sectional study enrolled children with SRNS (n=31) and SSNS (n=32) from the pediatric nephrology clinic of Babylon Hospital for Maternity and Pediatrics over three months. Patients' characteristics in terms of demographics, clinical data, and urinary investigations were collected. Quantitative analysis of uVDBP levels was undertaken via a commercially available ELISA kit. Results: The median uVDBP values were significantly higher (p-value<0.001) in the SRNS group (median=10.26, IQR=5.91 μg/mL) than in the SSNS group (median=0.953, IQR=4.12 μg/mL). A negative correlation was noted between uVDBP levels and estimated glomerular filtration rate (eGFR) (Spearman's rho coefficient= − 0.494, p=0.001). Nevertheless, the rise in uVDBP concentrations was still considerable in children with SRNS whose eGFR measurements were above 60 mL/min/1.73 m2. The study revealed a good discriminatory power for uVDBP as a predicting parameter to distinguish SRNS from SSNS (AUC= 0.909, p<0.0001. The optimal uVDBP cut-off value of 5.781 μg/mL was associated with a sensitivity of 0.839 and specificity of 0.844 to differentiate SRNS from SSNS. Conclusion: Considering its significant discriminatory strength, uVDBP can be considered as a potential marker to noninvasively distinguish children with SRNS from those with SSNS.
In real conditions of structures, foundations like retaining walls, industrial machines and platforms in offshore areas are commonly subjected to eccentrically inclined loads. This type of loading significantly affects the overall stability of shallow foundations due to exposing the foundation into two components of loads (horizontal and vertical) and consequently reduces the bearing capacity.
Based on a numerical analysis performed using finite element software (Plaxis 3D Foundation), the behavior of model strip foundation rested on dry sand under the effect of eccentric inclined loads with different embedment ratios (D/B) ranging from (0-1) has been explored. The results display that, the bearing capacity of st
... Show Moreهدفت الدراسة الحالية الى التعرف ما اذا كان هناك تقبل اجتماعي للتلاميذ بطيئي من قبل اقرانهم العاديين؟ وكذلك معرفة ما اذا كان هناك فروق ذات دلالة في التقبل الاجتماعي بين افراد عينة الدراسة على وفق المتغيرات الاتية:
أ- العمر (9-13)
ب- الجنس (ذكور –اناث)
ج- المرحلة الدراسية
د- الحالة الاقتصادية (جيدة –متوسطة –جيدة جدا)
ولغرض تحقيق اه
... Show MoreThe aim of this research is to adopt a close range photogrammetric approach to evaluate the pavement surface condition, and compare the results with visual measurements. This research is carried out on the road of Baghdad University campus in AL-Jaderiyiah for evaluating the scaling, surface texture for Portland cement concrete and rutting, surface texture for asphalt concrete pavement. Eighty five stereo images of pavement distresses were captured perpendicular to the surface using a DSLR camera. Photogrammetric process was carried out by using ERDAS IMAGINE V.8.4. The results were modeled by using a relationship between the photogrammetric and visual techniques and selected the highest coefficient of determinatio
... Show MoreThis study aims to demonstrate the role of artificial intelligence and metaverse techniques, mainly logistical Regression, in reducing earnings management in Iraqi private banks. Synthetic intelligence approaches have shown the capability to detect irregularities in financial statements and mitigate the practice of earnings management. In contrast, many privately owned banks in Iraq historically relied on manual processes involving pen and paper for recording and posting financial information in their accounting records. However, the banking sector in Iraq has undergone technological advancements, leading to the Automation of most banking operations. Conventional audit techniques have become outdated due to factors such as the accuracy of d
... Show MoreThe research seeks to find the relationship between psychological flow and futuristic thinking among postgraduate students. To this end, the researchers have made up two scales: one scale to measure the psychological flow which consisted of (32) items and the other to measure the futuristic thinking included (39) items which were distributed into three domains. As to collect the required data, the two scales had applied on a sample comprised (200) postgraduate students. The findings revealed that there is a correlation between psychological flow and futuristic thinking. The researcher recommended the coming studies take the relationship between psychological flow and psychological happiness.
The research aims to identify the correlation between self-reliance and human relationship of kindergartens’ teachers. Total of (120) kindergarten teachers at Baghdad city. To collect needed data, two scales were administered to the research sample consisted of (25) items of each scale with (five) alternatives. The results revealed that teachers have good level of self-reliance and human relationship. There is a positive correlation between self-reliance and human relationship.
Elzaki Transform Adomian decomposition technique (ETADM), which an elegant combine, has been employed in this work to solve non-linear Riccati matrix differential equations. Solutions are presented to demonstrate the relevance of the current approach. With the use of figures, the results of the proposed strategy are displayed and evaluated. It is demonstrated that the suggested approach is effective, dependable, and simple to apply to a range of related scientific and technical problems.
Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le
... Show MoreArtificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le
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