The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi

       Canonical correlation analysis is one of the common methods for analyzing data and know the relationship between two sets of variables under study, as it depends on the process of analyzing the variance matrix or the correlation matrix. Researchers resort to the use of many methods to estimate canonical correlation (CC); some are biased for outliers, and others are resistant to those values; in addition, there are standards that check the efficiency of estimation methods.

In our research, we dealt with robust estimation methods that depend on the correlation matrix in the analysis process to obtain a robust canonical correlation coefficient, which is the method of Biwe

Interleukin-38 (IL-38), an inflammatory cytokine discovered in recent years, has been implicated in the pathogenesis of systemic lupus erythematosus (SLE). IL-38 is encoded by the IL1F10 (interleukin 1 family member 10) gene. Genetic variants of this gene have been associated with susceptibility to a number of autoimmune and inflammatory diseases, while their association with SLE risk has not been explored. In this case–control study, two novel variants of the 5 prime untranslated region (5′UTR) of the IL1F10 gene, rs3811050 C/T and rs3811051 T/G, were investigated

The study aimes to investigate the effects of leaves & fruits ethanolic extract of Duranta repens L. on biological performance for all stages of life cycle of the mosquito Culex pipiens piepiens L., For this purpose the mosquitoes were reared in the laboratory till the fourth generation .Different concentrations of leaves (800,1000,1200,1400ppm) and fruits (800,1000,1200ppm) were tested on (eggs,larval stages,pupal stages and the adult stages). The results revealed that the extracts gave highest mortality rate for the eggs at(100%) compared with control,fruits extract shown highest mortality rate of the four larval instars (100%)at 1200ppm compared with leave extract at(80,50,33.33,20%).Also the extract caused a high mortality rate for pupa