Simulation-based flood fragility and vulnerability analysis for expanding cities

Accurately quantifying flood-induced impacts on buildings and other infrastructure systems is essential for risk-sensitive planning and decision-making in expanding urban regions. Flood-induced impacts are directly related to the physical components of assets damaged due to contact with water. Such components include building contents (e.g., appliances, furniture) and other non-structural components whose damage/unavailability can severely impact the buildingsﾒ functionality. Conventional fragility analysis approaches for flooding do not account for the physical damage to the individual components, mostly relying on empirical methods based on historical data. However, recent studies proposed simulation-based, assembly-based fragility models that account for the damage to the building components. Such fragility models require developing detailed inventories of vulnerable components of households and identifying building archetypes to be considered in a building portfolio for the region of interest. Content inventories and building portfolios have so far been obtained for specific socio-economic contexts such as the United States of America. However, building types and their content can significantly differ between countries, making the available fragility models and computational frameworks unsuitable for flood vulnerability analysis in rapidly expanding cities characterised by extensive informal settlements, such as low- and middle-income countries. This paper details how to adapt the available methodologies for flood vulnerability assessment to the context of formal and informal settlements of expanding cities in the global south. It also details the development of content inventories for households in these cities using field surveys. The proposed survey is deployed in various areas vulnerable to floods in Kathmandu, Nepal. Based on the survey results, each component within the household is associated with a corresponding flood capacity (resistance) distribution (in terms of water height and flood duration). These distributions are then employed in a simulation-based probabilistic framework to obtain fragility relationship and consequence models. The relevant differences between the results obtained in this study and those from previous studies are then investigated for a case-study building type. In addition, the influence of socio-economic factors (e.g., household income) and past flood experience (possibly resulting in various flood-risk mitigation strategies at a household level) on the resulting flood impacts is also included in the model

A low-cost hierarchical nanostructured beta-titanium alloy with high strength

Lightweighting of automobiles by use of novel low-cost, high strength-to-weight ratio structural materials can reduce the consumption of fossil fuels and in turn CO(2) emission. Working towards this goal we achieved high strength in a low cost β-titanium alloy, Ti–1Al–8V–5Fe (Ti185), by hierarchical nanostructure consisting of homogenous distribution of micron-scale and nanoscale α-phase precipitates within the β-phase matrix. The sequence of phase transformation leading to this hierarchical nanostructure is explored using electron microscopy and atom probe tomography. Our results suggest that the high number density of nanoscale α-phase precipitates in the β-phase matrix is due to ω assisted nucleation of α resulting in high tensile strength, greater than any current commercial titanium alloy. Thus hierarchical nanostructured Ti185 serves as an excellent candidate for replacing costlier titanium alloys and other structural alloys for cost-effective lightweighting applications

Closing the Gaps: From Science to Action in Maternal, Newborn, and Child Health in Africa

As part of a series on maternal, neonatal, and child health in sub-Saharan Africa, Sara Bennett and Freddie Ssengooba discuss the challenges of getting science into policy in Africa

Pontine stroke presenting as isolated facial nerve palsy mimicking Bell's palsy: a case report

<p>Abstract</p> <p>Introduction</p> <p>Isolated facial nerve palsy usually manifests as Bell's palsy. Lacunar infarct involving the lower pons is a rare cause of solitary infranuclear facial paralysis. The present unusual case is one in which the patient appeared to have Bell's palsy but turned out to have a pontine infarct.</p> <p>Case presentation</p> <p>A 47-year-old Asian Indian man with a medical history of hypertension presented to our institution with nausea, vomiting, generalized weakness, facial droop, and slurred speech of 14 hours' duration. His physical examination revealed that he was conscious, lethargic, and had mildly slurred speech. His blood pressure was 216/142 mmHg. His neurologic examination showed that he had loss of left-sided forehead creases, inability to close his left eye, left facial muscle weakness, rightward deviation of the angle of the mouth on smiling, and loss of the left nasolabial fold. Afferent corneal reflexes were present bilaterally. MRI of the head was initially read as negative for acute stroke. Bell's palsy appeared less likely because of the acuity of his presentation, encephalopathy-like imaging, and hypertension. The MRI was re-evaluated with a neurologist's assistance, which revealed a tiny 4 mm infarct involving the left dorsal aspect of the pons. The final diagnosis was isolated facial nerve palsy due to lacunar infarct of dorsal pons and hypertensive encephalopathy.</p> <p>Conclusion</p> <p>The facial nerve has a predominant motor component which supplies all muscles concerned with unilateral facial expression. Anatomic knowledge is crucial for clinical localization. Bell's palsy accounts for around 72% of facial palsies. Other causes such as tumors and pontine infarcts can also present as facial palsy. Isolated dorsal infarct presenting as isolated facial palsy is very rare. Our case emphasizes that isolated facial palsy should not always be attributed to Bell's palsy. It can be a presentation of a rare dorsal pontine infarct as observed in our patient.</p

Gender, health and the 2030 agenda for sustainable development

Gender refers to the social relationships between males and females in terms of their roles, behaviours, activities, attributes and opportunities, and which are based on different levels of power. Gender interacts with, but is distinct from, the binary categories of biological sex. In this paper we consider how gender interacts with the 2030 agenda for sustainable development, including sustainable development goal (SDG) 3 and its targets for health and well-being, and the impact on health equity. We propose a conceptual framework for understanding the interactions between gender (SDG 5) and health (SDG 3) and 13 other SDGs, which influence health outcomes. We explore the empirical evidence for these interactions in relation to three domains of gender and health: gender as a social determinant of health; gender as a driver of health behaviours; and the gendered response of health systems. The paper highlights the complex relationship between health and gender, and how these domains interact with the broad 2030 agenda. Across all three domains (social determinants, health behaviours and health system), we find evidence of the links between gender, health and other SDGs. For example, education (SDG 4) has a measurable impact on health outcomes of women and children, while decent work (SDG 8) affects the rates of occupationrelated morbidity and mortality, for both men and women. We propose concerted and collaborative actions across the interlinked SDGs to deliver health equity, health and well-being for all, as well as to enhance gender equality and women’s empowerment. These proposals are summarized in an agenda for action

A Prediction Model for Neonatal Mortality in Low- and Middle-income Countries: An Analysis of Data from Population Surveillance Sites in India, Nepal and Bangladesh

Background: In poor settings, where many births and neonatal deaths occur at home, prediction models of neonatal mortality in the general population can aid public-health policy-making. No such models are available in the international literature. We developed and validated a prediction model for neonatal mortality in the general population in India, Nepal and Bangladesh. Methods: Using data (49 632 live births, 1742 neonatal deaths) from rural and urban surveillance sites in South Asia, we developed regression models to predict the risk of neonatal death with characteristics known at (i) the start of pregnancy, (ii) start of delivery and (iii) 5 minutes post partum. We assessed the models’ discriminative ability by the area under the receiver operating characteristic curve (AUC), using cross-validation between sites. Results: At the start of pregnancy, predictive ability was moderate {AUC 0.59 [95% confidence interval (CI) 0.58–0.61]} and predictors of neonatal death were low maternal education and economic status, short birth interval, primigravida, and young and advanced maternal age. At the start of delivery, predictive ability was considerably better [AUC 0.73 (95% CI 0.70–0.76)] and prematurity and multiple pregnancy were strong predictors of death. At 5 minutes post partum, predictive ability was good [AUC: 0.85 (95% CI 0.80–0.89)]; very strong predictors were multiple birth, prematurity and a poor condition of the infant at 5 minutes. Conclusions: We developed good performing prediction models for neonatal mortality. Neonatal deaths are highly concentrated in a small group of high-risk infants, even in poor settings in South Asia. Risk assessment, as supported by our models, can be used as a basis for improving community- and facility-based newborn care and prevention strategies in poor settings

The effectiveness of emergency obstetric referral interventions in developing country settings : a systematic review

Peer reviewedPublisher PD

Women's health groups to improve perinatal care in rural Nepal

BACKGROUND: Neonatal mortality rates are high in rural Nepal where more than 90% of deliveries are in the home. Evidence suggests that death rates can be reduced by interventions at community level. We describe an intervention which aimed to harness the power of community planning and decision making to improve maternal and newborn care in rural Nepal. METHODS: The development of 111 women's groups in a population of 86 704 in Makwanpur district, Nepal is described. The groups, facilitated by local women, were the intervention component of a randomized controlled trial to reduce perinatal and neonatal mortality rates. Through participant observation and analysis of reports, we describe the implementation of this intervention: the community entry process, the facilitation of monthly meetings through a participatory action cycle of problem identification, community planning, and implementation and evaluation of strategies to tackle the identified problems. RESULTS: In response to the needs of the group, participatory health education was added to the intervention and the women's groups developed varied strategies to tackle problems of maternal and newborn care: establishing mother and child health funds, producing clean home delivery kits and operating stretcher schemes. Close linkages with community leaders and community health workers improved strategy implementation. There were also indications of positive effects on group members and health services, and most groups remained active after 30 months. CONCLUSION: A large scale and potentially sustainable participatory intervention with women's groups, which focused on pregnancy, childbirth and the newborn period, resulted in innovative strategies identified by local communities to tackle perinatal care problems

NEREL: A Russian Dataset with Nested Named Entities, Relations and Events

In this paper, we present NEREL, a Russian dataset for named entity recognition and relation extraction. NEREL is significantly larger than existing Russian datasets: to date it contains 56K annotated named entities and 39K annotated relations. Its important difference from previous datasets is annotation of nested named entities, as well as relations within nested entities and at the discourse level. NEREL can facilitate development of novel models that can extract relations between nested named entities, as well as relations on both sentence and document levels. NEREL also contains the annotation of events involving named entities and their roles in the events. The NEREL collection is available via https://github.com/nerel-ds/NEREL. © 2021 Incoma Ltd. All rights reserved.The project is supported by the Russian Science Foundation, grant # 20-11-20166. The experiments were partially carried out on computational resources of HPC facilities at HSE University. We are grateful to Alexey Yandutov and Igor Rozhkov for providing results of their experiments in named entity recognition and relation extraction

Single lesion multibacillary leprosy, a treatment enigma: a case report

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens