Groupwise non-rigid image alignment is a difficult non-linear optimization problem involving many parameters and often large datasets. Previous methods have explored various metrics and optimization strategies. Good results have been previously achieved with simple metrics, requiring complex optimization, often with many unintuitive parameters that require careful tuning for each dataset. In this chapter, the problem is restructured to use a simpler, iterative optimization algorithm, with very few free parameters. The warps are refined using an iterative Levenberg-Marquardt minimization to the mean, based on updating the locations of a small number of points and incorporating a stiffness constraint. This optimization approach is efficient, has very few free parameters to tune, and the authors show how to tune the few remaining parameters. Results show that the method reliably aligns various datasets including two facial datasets and two medical datasets of prostate and brain MRI images and demonstrates efficiency in terms of performance and a reduction of the computational cost.
It highlights the importance of research through its focus on the assessment of tax for settling accounts Mmakhr medicines and annual statement controls and its role in determining the taxable income of the real tax Mmakhr drugs and achieve tax equity through tax settling accounts. The tax authority relies annual controls laid down by the tax settling accounts for Mmakhr medicines despite their inclusion bookkeeping business No. 2 system for the year 1985 average .ually this basis formulated hypothesis (that the adoption of the tax authority on annual controls in the tax settling accounts for Mmakhr medicine does not contribute in determining income taxable real tax for this Almmakr). the resulting search for a number of conclusions and
... Show MoreObjective: To suggest a weighted measure to diagnose the reasons for the low student success ratios in mathematics concerning the third grade of intermediate schools in light of components educational system represented by: [Students, Teachers, Curriculum, and Environmental reasons (others reasons)] assuming differentiated and interrelated components, Also the effectiveness forming of these components according to the gender variable. Methods: Data collection tools were prepared by constructing two questionnaires for each of (Students and Teachers), which included a number of items that involved some domains for studied components of educational system, which demonstrated a high level of validity and reliability in the pilot study, in addi
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Aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor and 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) is a potent ligand for AhR and a known carcinogen. While AhR activation by TCDD leads to significant immunosuppression, how this translates into carcinogenic signal is unclear. Recently, we demonstrated that activation of AhR by TCDD in naïve C57BL6 mice leads to massive induction of myeloid derived-suppressor cells (MDSCs). In the current study, we investigated the role of the gut microbiota in TCDD-mediated MDSC induction. TCDD caused significant alterations in the gut microbiome, such as increases in Prevotella and Lactobacillus, while decreasing Sutterella and Bacteroides. Fecal transplants from TCDD-treated
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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 correlati
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This study investigates the impact of spatial resolution enhancement on supervised classification accuracy using Landsat 9 satellite imagery, achieved through pan-sharpening techniques leveraging Sentinel-2 data. Various methods were employed to synthesize a panchromatic (PAN) band from Sentinel-2 data, including dimension reduction algorithms and weighted averages based on correlation coefficients and standard deviation. Three pan-sharpening algorithms (Gram-Schmidt, Principal Components Analysis, Nearest Neighbour Diffusion) were employed, and their efficacy was assessed using seven fidelity criteria. Classification tasks were performed utilizing Support Vector Machine and Maximum Likelihood algorithms. Results reveal that specifi
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This research is seeks to state the role of Green Human Resources Management Practices and their dimensions (Green Employment and Selection, Green Performance Assessment, Green Training & Development and Green Compensation and Stimulation Systems) in strengthening the Strategic Positioning in the Nongovernmental Hospitals in Erbil city, and aims to analyze the relationship between Green Human Resources Management Practices and Strategic Positioning and to show the impact of Green Human Resources Management Practices in determining the Strategic Position.
It is depended on a questionnaire as key tools for achieving data, as designed on
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