This research aims to clarify the principles governing the exploration and utilization of outer space, emphasizing the role of international law, particularly international criminal law, in addressing crimes committed beyond Earth whether aboard spacecraft, the International Space Station, or in outer space generally. It examines relevant international treaties governing outer space activities, evaluates their strengths and ambiguities, and highlights deficiencies in their provisions. Furthermore, the study analyzes traditional principles of state criminal jurisdiction territoriality, nationality, universality, and protection and assesses their applicability to offenses committed in outer space.

Abstract

Biosimilars are non-innovative copy versions of biologic medicines which are proven to be clinically equivalent to, as effective and as safe as their reference biologics. Biosimilars creates opportunities for cost savings for payers, governments, and patients compared with the reference products. Pharmacist plays an essential role in developing biosimilar medicines from manufacturing to post-marketing pharmacovigilance monitoring. The aim of the current study was to explore  the level of  knowledge, behaviors and practices of  a sample of Iraqi pharmacists towards biosimilar medicines.  The current study was a cross sectional, carried out during May 2020. A total of 2

The current study aims to identify agreeableness and orientation towards voluntary work of officials in public facilities, as well as to identify the nature of the correlation between agreeableness and orientation towards voluntary work of officials in public facilities. To achieve the aims of the research, the researchers designed the agreeableness scale, which consists of (28) items in its final form. The researchers also built a scale of orientation towards voluntary work, which consists of (29) items in its final form. Psychometric properties of validity and reliability of the two scales were extracted in various ways. The researcher applied the two scales on a sample of (400) officials, the results indicated that the

The paper deals with a study of peculiarities of gluttonic text structures in the Arabic-Russian language pair at the sociolinguistic, system structural, functional-stylistic and lexico-semantic aspects from the standpoint of view at functional approach to the phenomena of language systems and the gluttonic discourse as a special type of ver bal and social discourse. Profound attention is paid to the consideration of lexical and grammatical means of explication of glutton discourse on the examples of identi cal Arabic and Russian literary texts as well as language situations in Arab countries and Russia, features of which are due to the characteristics of gluttonic discourses that reflect the features of the two different ethnolingual cu

Raghad Fattah RADHI

Thethesis of theresearch is to deal with relations between Russia and Yemen after 2011.That relationwas significant in different fields, historic, economic, strategic and cultural ones. There are mutual interestsbetweenRussia and Yemen, especially with the economic development and growth in Russia as an important partner to Yemen.Their has to an a great deal of progress in different types of relations, where as they were only partner in military relations. The studywasclassifiedintoto three sections: the first section dealt with strategic importance of Yemen to Russia. And second section dealt withthe military factor between Russia and Yemen. While the third section dealt with the economic factor between Russia and Yemen. In addi

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c