Acute pulmonary oedema is a significant cause of morbidity and mortality in pregnant and postpartum women. We present an unusual case of near-fatal acute pulmonary oedema in a pregnant woman, which was attributed to the acute onset of neurogenic pulmonary oedema secondary to epileptic seizure activity. The patient required supportive management in the intensive care setting for a short period and subsequently made complete recovery with regular neurological follow-up arranged for the management of her epilepsy.

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To assess the knowledge and awareness of osteoporosis and its risk factors among female university students in Mirpur Azad Kashmir. A cross-sectional study was carried out in female university students in Mirpur Azad Kashmir using a self-administered questionnaire. Knowledge and awareness of osteoporosis was assessed using OKAT (Osteoporosis Knowledge Assessment Tool) and descriptive analysis by using SPSS (version 25). Pearson Chi-Square test (p < 0.05) was used to assess significance.Mean age of the participants was 22.45 + 1.279 years. Mean total score was 11.86 + 3.3. The overall score of knowledge was moderate (68.8%). There was a significantly high difference about risk factors, complications, and preventive measures of osteoporosis between the two groups (p = 0.000). Discipline and family history of disease were significantly associated with overall knowledge score. This study concluded that overall knowledge of osteoporosis among female students was moderate. A well-structured education programs must be added to curriculum to prevent osteoporosis in later stages.

In applications like autonomous vehicle driving or robot maneuverability, Precise depth estimation from images is vital for understanding the scene and its reconstruction. Traditional depth estimation techniques are based on component correspondences of several viewpoints. Monocular depth estimation from a single image is a challenging task due to the inherent ambiguity in the scene's geometry. Deep neural networks have shown great promise in addressing this problem by capturing complex features from the image and providing accurate depth maps. In this paper, we review the recent advances in monocular depth estimation based on deep learning techniques. We explore the various network frameworks and training methods used to improve the accuracy of depth estimation. We also examine the limitations of current methods and discuss open challenges in this field. Our goal is to provide a comprehensive overview of the current stateof-the-art in monocular depth estimation based on deep learning and to inspire further research in this area. The paper examines a variety of learning strategies, as well as datasets for Monocular depth estimates and challenges.

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