BEHAVIOUR OF HIGH STRENGTH CONCRETE COMPOSITE SLABS WITH DIFFERENT END ANCHORAGES

This study is performed to investigate experimentally the behaviour of steel deck composite slabs with different end anchorages. End anchorage as a type of shear connection for composite slabs plays an important role to prevent relative slip between concrete and steel deck. The presented composite slab specimens are made of high strength concrete and loaded at a specific shear span. Objectives of this study is to evaluate experimentally load carrying capacity, end slip, mode of failure, shear bond capacity, and the end anchorage contribution to the whole composite slab behaviour. Research also presents a comparison between the experimental results and the theoretical results derived according to m-k and partial shear connection methods included in these standards (BS 5950-4:1994, CSSBI S3-2003, and EC4 EN 1994-1-1:2004)

Acridine Orange and Flow Cytometry: Which Is Better to Measure the Effect of Varicocele on Sperm DNA Integrity?

We evaluated the effect of varicocelectomy on semen parameters and levels of sperm DNA damage in infertile men. A total of 75 infertile men with varicocele and 40 fertile men (controls) were included in this study. Semen analysis and sperm DNA damage expressed as the DNA fragmentation index using acridine orange staining and chromatin condensation test by flow cytometry were assessed before and 6 months after varicocelectomy. The patients were also followed up for 1 year for pregnancy outcome. Semen parameters were significantly lower in varicocele patients compared to controls (P<0.05). Mean percentages of sperm DNA fragmentation and sperm DNA chromatin condensation in patients were significantly higher than those in controls (P<0.05). After varicocelectomy, sperm DNA fragmentation improved significantly, whereas sperm chromatin condensation was not significantly changed. In 15 out of 75 varicocele patients, clinical pregnancy was diagnosed; those with positive pregnancy outcome had significant improvement in sperm count, progressive sperm motility, and sperm DNA fragmentation, but there was no significant difference in sperm DNA condensation compared to negative pregnancy outcome patients. We concluded from this study that acridine orange stain is more reliable method than flow cytometry in the evaluation of sperm DNA integrity after varicocelectomy

Substantial Effect of Fenugreek Seeds Aqueous Extract on Serum Estradiol Level in Ovarian Hyperstimulation Syndrome Rat Model

Objectives: Estradiol (E2) plays an important role in the pathophysiology of ovarian hyperstimulation syndrome (OHSS). This study aimed to evaluate the effect of fenugreek seed aqueous (FSA) extract on serum E2 levels in a rat model of OHSS. Methods: A total of 34 female Sprague Dawley rats, aged 18 days old, weighing 40 to 45 g, were randomly divided into negative control, positive control, and treatment groups. A daily dose of 1500 mg/kg per body weight of FSA extract was administrated orally to rats in the treatment group for 13 days. On day eight of the study, OHSS was induced in both positive control and treated groups by subcutaneous injection of pregnant mare’s serum gonadotropin 50 IU for four consecutive days, followed by human chorionic gonadotropin 25 IU on the fifth day. The effect of FSA extract was evaluated by measuring the concentration of serum E2 using the enzyme-linked immunosorbent assay. Results: FSA extract reduced serum E2 level significantly in the treated OHSS model (p-value < 0.050) compared to the positive control group. Conclusions: The finding has important implications on the development of female infertility adjuvant drugs for safe assisted reproduction technology cycles in terms of OHSS prevention

Comparative Analysis of the Performance of Popular Sorting Algorithms on Datasets of Different Sizes and Characteristics

Abstract: The efficiency and performance of sorting algorithms play a crucial role in various applications and industries. In this research paper, we present a comprehensive comparative analysis of popular sorting algorithms on datasets of different sizes and characteristics. The aim is to evaluate the algorithms' performance and identify their strengths and weaknesses under varying scenarios. We consider six commonly used sorting algorithms: QuickSort, TimSort, MergeSort, HeapSort, RadixSort, and ShellSort. These algorithms represent a range of approaches and techniques, including divide-and-conquer, hybrid sorting, and simple comparison-based methods. To assess their performance, we employ a diverse set of datasets, including the Iris dataset (1K), student dataset (5.8K), Wine dataset (6.5K), Uniform (10K), Normal (10K), Exponential (10K), Bimodal (10K), Yelp dataset (10K), MNIST dataset (42K), Uniform (100K), Normal (100K), Exponential (100K), Bimodal (100K), Uniform (500K), Normal (500K), Exponential (500K), Bimodal (500K), Uniform (1M), Normal (1M), Exponential (1M), and Bimodal (1M). These datasets cover a wide range of sizes and characteristics, allowing us to analyze the algorithms' performance across different dimensions. We measure and compare several key metrics, including execution time, memory usage, algorithmic complexity and stability. By analyzing these metrics, we gain insights into the efficiency and suitability of each algorithm for different dataset sizes and characteristics. We also discuss the implications of the findings in practical applications. Our results reveal important trade-offs among the sorting algorithms. While some algorithms excel in certain scenarios, others demonstrate better scalability or memory efficiency. We identify the best-performing algorithms for specific dataset characteristics and highlight their strengths and limitations. This research can assist developers and practitioners in selecting appropriate sorting algorithms based on their specific requirements and dataset characteristics. In conclusion, this comparative analysis provides a valuable contribution to the understanding of sorting algorithm performance. The findings contribute insights into the efficiency and suitability of popular sorting algorithms across datasets of different sizes and characteristics. By evaluating key metrics and discussing the implications, we offer guidance for selecting the most appropriate sorting algorithm in various practical scenarios