Aim: To evaluate the side effects of Tamsulosin hydrochloride in fertility of experimental rats. Materials and methods: three groups of mice were used. First and second groups were injected [intraperitoneal (I.P.)] daily for 42 with 8 and 16 µg /kg mouse body weight (kg.b.wt) of Tamsulosin hydrochloride, respectively. Third group was injected with PBS (control). Several biological and histopathological studies were conducted on rat groups. Results: Significant decrease in number, motility and viability of epididymal sperm post injection with 16 µg /kg.b.wt, while injection with 8 µg /kg.b.wt reduced significantly, percentage of viability of sperm as compared with the control group. High percentage of abnormal sperm was observed in mice t

Hierarchical temporal memory (HTM) is a biomimetic sequence memory algorithm that holds promise for invariant representations of spatial and spatio-temporal inputs. This article presents a comprehensive neuromemristive crossbar architecture for the spatial pooler (SP) and the sparse distributed representation classifier, which are fundamental to the algorithm. There are several unique features in the proposed architecture that tightly link with the HTM algorithm. A memristor that is suitable for emulating the HTM synapses is identified and a new Z-window function is proposed. The architecture exploits the concept of synthetic synapses to enable potential synapses in the HTM. The crossbar for the SP avoids dark spots caused by unutil

Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in