This study aimed to elucidate the genetic architecture and selection signatures in two prominent Iraqi fat‐tailed sheep breeds, Awassi and Hamdani. One hundred forty animals were genotyped using the Illumina Ovine SNP50K BeadChip, providing genome‐wide coverage with approximately 53,714 SNP markers. To uncover candidate genomic regions under selection, we employed three complementary approaches: integrated haplotype score (iHS), runs of homozygosity (ROH) and Tajima's D analyses. The iHS analysis identified 69 candidate genes in Awassi sheep and 286 in Hamdani sheep, whereas ROH analysis revealed 190 and 277 candidate genes in the respective breeds. Tajima's D corroborated these findings with one gene in Awassi and four in Hamdani sheep. Population structure was rigorously assessed using ADMIXTURE, principal component analysis (PCA) and neighbour‐joining phylogenetic tree reconstruction, collectively demonstrating a distinct genetic separation of the Awassi breed and a more admixed genetic profile for the Hamdani breed. Functional enrichment analysis of candidate genes implicated several biological processes and pathways, including immune response, hormone regulation and cellular signalling, underscoring their potential roles in adaptation and disease resistance. Overall, our findings provide novel insights into the genetic differentiation and adaptive evolution of Iraqi fat‐tailed sheep, offering a valuable resource for future breeding and conservation programmes.

Bu çalışma Akdeniz iklim kuşağında yetiştirilen Siyah Alaca sığırlarda somatik hücre sayısına (SHS) mevsim, laktasyon sayısı ve tip puanı faktörlerinin etkisini belirlemek amacı ile yapılmıştır. Toplam 128 baş sığırdan elde edilen 1368 adet süt örneği somatik hücre sayısı tespiti için analiz edilmiştir. Mevsim, laktasyon sayısı ve tip özelliklerinin somatik hücre sayısına etkili faktörler olduğu tespit edilmiştir. Sonuçlar yaz aylarında ineklerin bakım ve ahır temizliğine riayet edilmesi gerekliliğini ve seleksiyon programlarında tip özelliklerine önem verilmesinin somatik hücre sayısını düşürmekte etkili olabileceğini işaret etmektedir.

This study examines the effectiveness of thyme oil and argan oil as potential treatments for leg edema in horses. Swollen legs, often a result of infections, injuries, allergies, and underlying health conditions can significantly affect a horse's mobility and overall health. Traditional treatments may include antibiotics, anti-inflammatories, cold therapy, compression bandaging, and rest, but there is growing interest in natural remedies. For this purpose, argan and thyme oil were applied to 22 horses of various ages and different breeds at different times at Mersin Doğa Horse Farm. As a result of the study, some observations before and after the application of thyme and argan oil are listed. In addition, there was a significant association between oils and side effect from rash, itchiness, temperature increase, drinking too much, excessive urination (p

This study aimed to predict the albumen index value in Tinted Coral chicken eggs. Researchers collected 60 eggs from a flock at 82 weeks of age and measured egg weight, egg width, egg length, and shell weight. They also calculated the shape index, Haugh unit, shell thickness and albumen index.Multiple linear regression (MLR) analysis showed that the model was statistically significant (F=65.65;

Cooperatives play a significant role within organizational models by providing essential services such as technical support, advocacy, information, knowledge, and guidance, which contribute to the production of high-quality animal products in a safe, efficient, and responsible manner. Furthermore, cooperatives aim to enhance the livelihoods of marginalized populations and address consumer needs. In this context, a study focusing on the status of women’s cooperatives in the Eastern Mediterranean offers valuable insights into women’s participation in economic and social life, as well as their challenges and expectations. This research aims to evaluate the status, perspectives, participation, activities, and expectations of women’s cooperatives in Lebanon and Turkey. The findings indicate that 90% of respondents in Lebanon and 45.5% in Turkey expressed satisfaction with their respective cooperatives. Additionally, 90% of Lebanese respondents and 59.1% of Turkish respondents would recommend that women establish their own cooperatives. The most common motivation for forming cooperatives in both countries was the belief that women are stronger when they collaborate. Furthermore, 75% of respondents in Lebanon and 45.4% in Turkey believe that cooperatives are suitable for conducting business, while those who disagreed emphasized the need for specialized traders to address specific business requirements. Respondents who expressed dissatisfaction with cooperative collaboration often mentioned difficulties in making joint decisions and challenges in group cohesion. These findings underline the importance of cooperatives in enhancing women’s roles in economic activities and the challenges they face in both Lebanon and Turkey. Despite these challenges, women’s cooperatives continue to be perceived as a valuable means of empowerment and a key strategy for fostering collaboration and economic growth.

In data mining, in order to calculate descriptive statistics and other statistical model parameters correctly, outliers should be identified and excluded from the data set before starting data analysis. This paper studied and compared the performance of model-based, density-based, clustering-based, angle-based, and isolation-based outlier detection methods used in data mining. ROC and AUC curves were used to compare the performances of outlier detection methods. A data set with a standard normal distribution and fit a logistic regression was simulated. To compare the methods, the data was modified by randomly adding 30 outliers to the data set. The iForest algorithm was found to have higher predictive power than Mahalanobis, LOF, k-means, and ABOD. In addition, outliers were found in a real data set with the iForest algorithm and deleted from the data set. Then, the data sets with outliers and without outliers were compared. The results showed that the model without outliers has a higher predictive ability.