This research includes a detailed morphological description of the Pollenia mesopotamica sp. nov. in Iraq. Locality, host plant and data of collection were given.

Fluidization process is widely used by a great assortment of industries worldwide and represents a trillion dollar industry [6]. They are currently used in separation, classification, drying and mixing of particles, chemical reactions and regeneration processes; one of these processes is the mass transfer from an immersed surface to a gas fluidized bed

This paper proposes a neuro-fuzzy system to model β-glucosidase activity based on the reaction’s pH level and temperature. The developed fuzzy inference system includes two input variables (pH level and temperature) and one output (enzyme activity). The multi-input fuzzy inference system was developed in two stages: first, developing a single input-single output fuzzy inference system for each input variable (pH, temperature) separately, using the robust adaptive network-based fuzzy inference system (ANFIS) approach. The neural network learning techniques were used to tune the membership functions based on previously published experimental data for β-glucosidase. Second, each input’s optimized membership functions from the ANF

Despite the global economic downturn, online e-commerce, especially the sale of counterfeit goods, continues to witness a rise in sales, and one of the important players in e-commerce is the owners of e-commerce auction sites. Although they do not have a direct role in trademark infringement, they still consider them indirectly responsible (secondary liability) for infringing on their trademarks. Thus, many cases have been filed by the owners of the original trademarks (which have been infringed by persons who have sold some of the goods and products that are imitating their marks through some electronic auctions) against the owners of those auctions. In view of the international character of the Internet, in different countries, and despit

This study aims at examining and confirming the patterns of phenetic relationships and the levels of variations within and among the species of Lotus L., 1753 in Egypt by using morphometric analysis techniques. We have evaluated 24 morphological characters from about 300 herbarium specimens representing 19 species of Lotus that are currently recognized. Based on numerical analyses of macromorphological characters (cluster analysis, principal coordinate analysis and principal component analysis), 19 species of Lotus were recognized from Egypt. These species were clustered in six species-specific groups: (I) Lotus halophilus Boiss. & Spruner, L. angustissimus L., L. glinoides Delile and L. schimperi Steud. ex Boiss., (II) Lotus glaber

In the recent years the research on the activated carbon preparation from agro-waste and byproducts have been increased due to their potency for agro-waste elimination. This paper presents a literature review on the synthesis of activated carbon from agro-waste using microwave irradiation method for heating. The applicable approach is highlighted, as well as the effects of activation conditions including carbonization temperature, retention period, and impregnation ratio. The review reveals that the agricultural wastes heated using a chemical process and microwave energy can produce activated carbon with a surface area that is significantly higher than that using the conventional heating method.

The present study introduces description of new species of leafhopper Cicadella latreilla nov. External morphological characters particularly female genitalia were discussed and illustrated, shape of male abdominal apodeme, chaetotaxy of genital style and genital plate of male genitalia, shape of Aedeagus and connective . The external morphological characters were: spotting patterns of vertex, face, pronotum of prothorax, and metothorax, and of lower and upper valves of ovipositors,shape of female seventh abdominasternum.

Face recognition and identity verification are now critical components of current security and verification technology. The main objective of this review is to identify the most important deep learning techniques that have contributed to the improvement in the accuracy and reliability of facial recognition systems, as well as highlighting existing problems and potential future research areas. An extensive literature review was conducted with the assistance of leading scientific databases such as IEEE Xplore, ScienceDirect, and SpringerLink and covered studies from the period 2015 to 2024. The studies of interest were related to the application of deep neural networks, i.e., CNN, Siamese, and Transformer-based models, in face recogni