Successful live birth after heterotopic ruptured cornual pregnancy with twin intrauterine gestation in an in vitro fertilization conception

Heterotopic pregnancies, especially in the cornual region which were a rarity till recent times, have become a more common occurrence due to increasing practice of assisted reproduction. Optimal management of such cases is imperative to manage the risk of hypotension and shock in case of rupture and to judiciously preserve the intrauterine pregnancy. Here we are reporting a case of IVF conception of twin intrauterine pregnancy with a cornual heterotopic pregnancy. Patient presented to the emergency department with features of acute abdomen, haemoperitoneum and shock. Ultrasound findings were suggestive of rupture of cornual heterotopic pregnancy, 1500 ml haemoperitoneum with live twin intrauterine gestation. Patient was resuscitated with iv fluids blood transfusion. Immediate laparotomy was done and cornual site repaired and covered with an omental patch while preserving the intrauterine gestations. Thereafter, pregnancy was carefully monitored with a high index of suspicion for rupture of site of cornual repair with advancing gestational age. Patient was readmitted at 24 weeks with pain abdomen and cornual site was found to be 4mm in thickness. She was managed conservatively till 27 weeks when she had preterm rupture of membranes and emergency LSCS was done. She delivered healthy twin male babies, 780 gmb and 795 gm respectively. This case demonstrates that cornual heterotopic pregnancy is a diagnosis which may be easily missed and can present as a life-threatening complication if it ruptures and significant intraperitoneal bleeding occurs. However, it is possible to successfully manage these cases with timely intervention, proper uterine reconstruction and monitoring of intrauterine gestation

Functional Knowledge Transfer with Self-supervised Representation Learning

This work investigates the unexplored usability of self-supervised representation learning in the direction of functional knowledge transfer. In this work, functional knowledge transfer is achieved by joint optimization of self-supervised learning pseudo task and supervised learning task, improving supervised learning task performance. Recent progress in self-supervised learning uses a large volume of data, which becomes a constraint for its applications on small-scale datasets. This work shares a simple yet effective joint training framework that reinforces human-supervised task learning by learning self-supervised representations just-in-time and vice versa. Experiments on three public datasets from different visual domains, Intel Image, CIFAR, and APTOS, reveal a consistent track of performance improvements on classification tasks during joint optimization. Qualitative analysis also supports the robustness of learnt representations. Source code and trained models are available on GitHub.Comment: Accepted at IEEE International Conference on Image Processing (ICIP 2023

Analysis & prognosis of sustainable development goals using big data-based approach during COVID-19 pandemic

The world has changed considerably in the previous two decades. Today, people are facing extreme poverty, global warming, and unwanted climate changes. The economic gap between countries is continuously growing. Moreover, with the expanding influence of technology, governance is getting more difficult. To address these issues, the UN announced Sustainable Development Goals (SDGs), also called Global Goals, in 2015. These goals fill in as an overall source of inspiration to annihilate poverty, protect the environment, and guarantee that all individuals live in harmony and thrive by 2030. The 17 SDGs are interconnected in that they recognize that activities in a single region sway result in others and that improvement should adjust to social, monetary, and natural sustainability. The SDGs intend to kill poverty, hunger, AIDS, and gender discrimination against women and girls. The COVID-19 epidemic, on the other hand, has hampered attempts to accomplish the 2030 Agenda for Sustainable Development. As a result, the impact of these SDGs must be thoroughly studied and analyzed. As a result, the purpose of this research is to examine the SDG before and after Covid-19, as well as how they have influenced various national and international markets. The research also assesses the 17 SDGs in each of India's 29 states in depth. Since SDGs have a larger scope, this paper predicts the SDG-9 scores of few countries like UAE, New Zealand, Japan, India, Germany, China, Bhutan, and USA