INTRODUCTIONWorld Health Organisation (WHO) defines Birth asphyxia as failure to initiate and sustain breath-ing in a newborn at birth. 1 It is a temporary interruption of oxygen availability that implies a risky metabolic challenge, even when the insult does not lead to a fatal outcome. Asphyxia results in hypoxemia (lack of oxygen) and hypercapnia (accumulation of carbon diox-ide).The combination of the decrease in oxygen supply (hypoxia) and blood supply (ischemia) re-sults in a ABSTRACT Background: Birth asphyxia is a serious clinical problem worldwide and contributes greatly to neonatal mortality and morbidity. Perinatal asphyxia is the fifth largest cause of under-5 deaths (8.5%) after pneumonia, diarrhea, neonatal infections and complications of preterm birth. Risk factors of birth asphyxia have been divided into antepartum, intrapartum and fetal. Risk factors include increasing or decreasing ma-ternal age, prolonged rupture of membranes, meconium stained fluid, multiple births, non-attendance for antenatal care, low birth weight infants, malpresentation, augmentation of labour with oxytocin, antepartum haemorrhage, severe eclampsia and preeclampsia, ante partum and intrapartum anemia. The objective of this study was to study the risk factors in children with birth asphyxia. Methods: Observational prospective study was conducted on babies delivered in our hospital and requiring resuscitation (basic and/or advanced). Their clinical course was observed and studied in NICU till time of discharge or death. Detailed maternal history was taken for risk factors. Results: The mean age of mothers was 24.28 years which ranged from 20 years to 29 years. Most of the population was from the lower middle and upper lower socioeconomic status as per the Modified Kuppuswamy scale. 51% neonates were born to primiparous mothers. Anemia was widely prevalent in the moth-ers of neonates requiring resuscitation. The maternal risk factors for newborns requiring resuscita-tion were PIH (23.7%) , oligohydramnios (15%),multiple gestation (3.75 %), PROM (2.5%), diabetes mellitus (2.5%) and UTI (2.5%).One third of neonates requiring resuscitation were born to unbooked mothers.In the neonates requiring resuscitation, the male to female ratio was 1:1. The fetal factors associated with resuscitation of newborns were IUGR (33.75%), fetal distress (31.25%), prematurity (26.25%), MAS (12.5%) and malpresentations (5%). Conclusions:The most common maternal risk factors for newborns requiring resuscitation was PIH followed by oligohydramnios, multiple gestation, PROM, diabetes mellitus and UTI.IUGR was the most com-mon fetal risk factor followed by fetal distress, prematurity, MAS and malpresentations. One third of neonates requiring resuscitation were born to unbooked mothers. In There was no gender predomi-nance found in this study.

Due to large number of entities in biomedical knowledge bases, only a small fraction of entities have corresponding labelled training data. This necessitates entity linking models which are able to link mentions of unseen entities using learned representations of entities. Previous approaches link each mention independently, ignoring the relationships within and across documents between the entity mentions. These relations can be very useful for linking mentions in biomedical text where linking decisions are often difficult due mentions having a generic or a highly specialized form. In this paper, we introduce a model in which linking decisions can be made not merely by linking to a knowledge base entity but also by grouping multiple mentions together via clustering and jointly making linking predictions. In experiments we improve the state-of-the-art entity linking accuracy on two biomedical entity linking datasets including on the largest publicly available dataset.

Natural hazards including floods can trigger catastrophic failures in interdependent urban transport network-of-networks (nons). population growth has enhanced transportation demand while urbanization and climate change have intensified urban floods. However, despite the clear need to develop actionable insights for improving the resilience of critical urban lifelines, the theory and methods remain underdeveloped. furthermore, as infrastructure systems become more intelligent, security experts point to the growing threat of targeted cyber-physical attacks during natural hazards. Here we develop a hypothesis-driven resilience framework for urban transport nons, which we demonstrate on the London Rail Network (LRN). We find that topological attributes designed for maximizing efficiency rather than robustness render the network more vulnerable to compound natural-targeted disruptions including cascading failures. our results suggest that an organizing principle for post-disruption recovery may be developed with network science principles. Our findings and frameworks can generalize to urban lifelines and more generally to real-world spatial networks. According to the World Economic Forum's Global Risks Report 2019 1 , extreme weather events are the global risks of highest concern. Heavy precipitation, along with associated flooding in urban megaregions, has been on the rise both in intensity and frequency under the dual forcings of climate change and rapid urbanization. Consequently, critical urban lifeline infrastructure systems (CULIS) across the globe are under stress, with multimodal urban transport systems (MUTS) among the worst affected by urban flooding. Moreover, transportation networks are functionally interdependent with each other and on other infrastructure systems such as the power grid and communication networks. Thus, even a limited disruption in one system can spiral out of control leading to severe loss of lifeline functions. Further, as MUTS are becoming increasingly connected and autonomous, security experts have pointed to the growing threat of opportunistically targeted cyber-attacks designed to take advantage of natural hazard events 2. Numerous definitions of resilience have been proposed in the literature 3 , although here we adopt the most widely cited provided by the US National Academy of Sciences: "the ability to prepare and plan for, absorb, recover from and more successfully adapt to adverse events" 4. The growing threat of natural, targeted and compound disruptions on MUTS calls for an urgent need to analyze and build resilience at a system level. Compound disruptions here refer to disruptions which may occur simultaneously or sequentially where the network has not fully recovered from the initial disruption. For example, a targeted cyber-physical attack in conjunction with a natural hazard in order to exploit the already weakened network capacity. Furthermore, the multiscale and interconnected nature of MUTS, combined with the inherent unpredictability of extreme weather events, make t...