Publications by authors named "A M Zakir"

Background: Typical pneumonia is a pressing issue in the treatment of human immunodeficiency virus (HIV) patients, especially in Sub-Saharan Africa, where it remains a significant menace. Addressing this problem is crucial in improving health outcomes and the reduction of the burden of diseases in this vulnerable category of patients.

Objective: To determine the prevalence of community-acquired typical pneumonia among HIV patients in Public Hospitals in southern Ethiopia.

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Hybrid supercapacitors can produce extraordinary advances in specific power and energy to display better electrochemical performance and better cyclic stability. Amalgamating metal oxides with metal-organic frameworks endows the prepared composites with unique properties and advantageous possibilities for enhancing the electrochemical capabilities. The present study focused on the synergistic effects of the CuCo(5-NIPA)-NdO composite.

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In the recent era, 2D human pose estimation (HPE) has become an integral part of advanced computer vision (CV) applications, particularly in understanding human behaviors. Despite challenges such as occlusion, unfavorable lighting, and motion blur, advancements in deep learning have significantly enhanced the performance of 2D HPE by enabling automatic feature learning from data and improving model generalization. Given the crucial role of 2D HPE in accurately identifying and classifying human body joints, optimization is imperative.

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The development of electrode materials with extraordinary energy densities or high power densities has experienced a spectacular upsurge because of significant advances in energy storage technology. In recent years, the family of metal-organic frameworks (MOFs) has become an essential contender for electrode materials. Herein, two cobalt-based MOFs are synthesized with distinct linkers named 1,2,4,5-benzene-tetra-carboxylic acid (BTCA) and 1,2,3,4-cyclopentane-tetracarboxylic acid (CPTC).

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In the field of computer vision, hand pose estimation (HPE) has attracted significant attention from researchers, especially in the fields of human-computer interaction (HCI) and virtual reality (VR). Despite advancements in 2D HPE, challenges persist due to hand dynamics and occlusions. Accurate extraction of hand features, such as edges, textures, and unique patterns, is crucial for enhancing HPE.

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