European Journal of Molecular & Clinical Medicine

The aim of the present study was to assess the ability of dynamic contrast-enhanced MRI (DCE–MRI), and Diffusion-weighted image (DWI) to describe uncertain ovarian masses.
Methods: The present study was conducted in department of radiology and we did transabdominal ultrasound and transvaginal ultrasound for all cases. We investigated 50 patients with 50 adnexal lesions.
Results: The patient’s age ranged from 20 to 78 years old (mean 43.56 years). The main complaint was abdominal pain and/or abdominal distension; other cases came with different symptoms as subfertility or irregular vaginal bleeding. The histopathology of the assessed masses were 21 benign, 4 borderline, and 25 malignant. The age range for patients with benign tumors was 20 - 65 years (mean 39 ± 13 years) while those with malignant tumors, their age range was 21- 78 years (mean 46 ± 16.953 years). Benign masses included seven serous cystadenoma, six mucinous cysadenoma, three mature cystic teratoma, two ovarian fibroma, and fibrothecoma, and one tubo-ovarian abscess. There were four Borderline tumors (two serous and two mucinous). There were 25 invasive malignant masses (Nine Serous cyst-adenocarcinoma, six Mucinous cyst-adenocarcinoma, three Metastatic krukenburg, three Immature teratoma, two fibrosarcoma, and two clear cell carcinoma).
Conclusion: DCE-MRI and DWI have accepted ability to distinguish between benign and malignant ovarian mass.

The Animal Coats are unique for each species in the sense that they differ in texture, colour, pattern etc. Major factors such as habitat, lifestyle, camouflaging etc. influence the formation of the animal coat. Melanin is the major pigment in the body of the organism responsible for the pigmentation on surface of the skin and other appendages. Melanin is produced by specialised cells in the basal layer of the epidermis called ‘Melanocytes’ whose distribution determines the pattern and overall colour concentration of the pigmentation. The distribution of Melanocytes is specific in each organism determined by chemical signals called ‘Morphogens.’ A number of authors have put forth theories regarding Melanogenesis and its subsequent distribution to form patterns. Turing and Murray have been considered the pioneer in the work of using differentiation to form a reaction diffusion model to explain the movement of melanocytes and the melanin pigment through a concentration gradient by Morphogens. According to them, body surface area and its uniformity throughout the organism plays an important role in dispersion of Melanocytes. Various patterns like strips, spots, colour variations and other criteria can be explained on the basis of such mathematical theorems and models. In this article, we have made an attempt to study a biological concept that is animal coat pattern formation, in a mathematical way. Ordinary differential equations and Partial differential equations are being used for determining the colours and patterns occurring in Animal coats. 

Investigation of the features of the transition of self-oscillations of current from one type to another in highly compensated silicon doped with impurity atoms of manganese, zinc and sulfur is of great interest from the point of view of studying both the mechanisms of self-sustained oscillations of the current and the physics of nonequilibrium processes. Based on the results obtained and the analysis performed, it has been established that the observed self-oscillations of the current in strongly compensated silicon are associated with nanoclusters of primus atoms. A model of a strongly compensated semiconductor is proposed to explain the mechanism of self-oscillations of the current in strongly compensated silicon, taking into account the multi-charge character of nano-clusters of atoms.
It was found that the proposed model is in satisfactory agreement with the experimental results.

The article explores the topic of "Capillary phenomena" in agrophysics, which is taught to students of agronomy on the basis of innovative technologies, ie the specific features of future agronomists, the content of its components, the study of innovative technologies in agrophysics, the information model of agrophysical processes