Background: Ectopic pregnancy is a life threatening emergency leading to maternal death. Incidence of ectopic pregnancies has been increasing in last two to three decades with reduction in mortality. The presenting symptoms include abdominal pain, amenorrhoea and/or irregular vaginal bleeding. The present study was undertaken to study the clinical features of ectopic pregnancies in a tertiary care hospital.Methods: The present study on ectopic pregnancies was carried out in Department of Pathology, Krishna Institute of Medical Sciences, Karad, Maharashtra, India from January 2010 to June 2014. All the cases of ectopic pregnancy managed surgically were included in the study.Results: Total 102 cases of ectopic pregnancy were studied. Proportion of ectopic pregnancy in the present study is 1 in 205 deliveries. Majority of the cases (37) (36.27%) were noted between 21 to 25 years of age group followed by the age group 26 to 30 years. Ectopic pregnancy was most commonly noted in nulliparous women (44/102) (43.14%). Majority of the cases (50/102) (49.02%) had no risk factors. Abortion was the most common risk factor identified, alone as well as in conjunction with other factors. Ampulla was the most common site for ectopic pregnancy. 55% of the cases were on the right side where as 45% on the left side. We had 2 cases of heterotropic pregnancy with tubal ectopic in both the cases. The typical triad of amenorrhoea, pain in abdomen and bleeding was observed in 21.57% cases.Conclusions: The incidence of ectopic pregnancies is on rise as evident in this study. In order to reduce the morbidity and mortality due to ectopic pregnancies, there is need for early diagnosis especially in high risk cases.
Renal primitive neuroectodermal tumor (PNET) is a rare entity. It should be differentiated from other primary renal malignancies. The differentiation of the malignant small round cell tumors may be challenging; however, it is essential for better management of the patient. We report a 45-year-old male having complaints of pain in the abdomen, hematuria, and mass in the abdomen for 6 months. Abdominal and pelvic sonography finding showed cystic-solid, right renal mass suggestive of malignancy. On histopathology diagnosed as malignant small round blue cell tumor suggestive of primitive neuroectodermal tumor. On immunohistochemistry, CD99 positivity confirmed the diagnosis of primary PNET of the kidney. We are presenting this case for its rarity, clinical presentation, and pathological findings.
Wireless Sensor Networks (WSNs) have gained an emerging importance in different application domains especially in event tracking and monitoring. The sensor nodes in WSNs are observed to have shorter lifetime due to the continuous sensing and processing operations that result in quicker energy depletion. Small, inexpensive, low-power, multipurpose nodes that are connected to one another form the basis of WSNs. Efficiently gather & communicate data to a washbasin. Cluster Heads (CHs) are used in cluster-based approaches to effectively arrange WSNs for data collection and energy conservation. A CH collects data from cluster nodes and aggregates/compresses it before sending it to a sink. The node's greater responsibility does, however, result in a higher energy drain, which leads to uneven network deterioration. This is made up for by LEACH (Low Energy Adaptive Clustering Hierarchy), which probabilistically alternates CH roles among nodes with energy over a set threshold. CH selection in WSN is NP-Hard because optimal data aggregation with effective energy savings cannot be done in polynomial time. To improve system performance, the synchronous firefly approach, a modified firefly heuristic, is introduced in this paper. A thorough simulation shows that the suggested method performs better than LEACH and energy-efficient hierarchical clustering. In today's world of intelligent networks, the internet of things (IoT) and industrial IoT (IIoT) are extremely important, and they fundamentally use a wireless sensor network (WSN) as a perception layer to collect the necessary data. The difficulty here is the usage of minimal energy for processing and communication. This data is processed as information and sent to cloud servers through a base station. The lifespan of WSNs is increased by the dynamic generation of cluster heads and energy-conscious clustering strategies.
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