Applying air pollution modelling within a multi-criteria decision analysis framework to evaluate UK air quality policies

A decision support system for evaluating UK air quality policies is presented. It combines the output from a chemistry transport model, a health impact model and other impact models within a multi-criteria decision analysis (MCDA) framework. As a proof-of-concept, the MCDA framework is used to evaluate and compare idealized emission reduction policies in four sectors (combustion in energy and transformation industries, non-industrial combustion plants, road transport and agriculture) and across six outcomes or criteria (mortality, health inequality, greenhouse gas emissions, biodiversity, crop yield and air quality legal compliance). To illustrate a realistic use of the MCDA framework, the relative importance of the criteria were elicited from a number of stakeholders acting as proxy policy makers. In the prototype decision problem, we show that reducing emissions from industrial combustion (followed very closely by road transport and agriculture) is more advantageous than equivalent reductions from the other sectors when all the criteria are taken into account. Extensions of the MCDA framework to support policy makers in practice are discussed

ENSO-driven extreme oscillations in mean sea level destabilise critical shoreline mangroves—An emerging threat

Recent ENSO-related, extreme low oscillations in mean sea level, referred to as ‘Taimasa’ in Samoa, have destabilised shoreline mangroves of tropical northern Australia, and possibly elsewhere. In 1982 and 2015, two catastrophic Taimasa each resulted in widespread mass dieback of ~76 km2 of shoreline mangroves along 2,000 km of Australia’s Gulf of Carpentaria. For the 2015 event, we determined that a temporary drop in sea level of ~0.4 metres for up to six months duration caused upper zone shoreline mangroves across the region to die from severe moisture deficit and desiccation. The two dramatic collapse events revealed a previously unrecognised vulnerability of semi-arid tidal wetland habitats to more extreme ENSO influences on sea level. In addition, we also observed a relationship between annual sea level oscillations and mangrove forest productivity where seasonal oscillations in mean sea level were co-incident with regular annual mangrove leaf growth during months of higher sea levels (March-May), and leaf shedding during lower sea levels (September-November). The combination of these periodic fluctuations in sea level defined a mangrove ‘Goldilocks’ zone of seasonal productivity during median-scale oscillations, bracketed by critical threshold events when sea levels became unusually low, or high. On the two occasions reported here when sea levels were extremely low, upper zone mangrove vegetation died en masse in synchrony across northern Australia. Such extreme pulse impacts combined with localised stressors profoundly threaten the longer-term survival of mangrove ecosystems and their benefits, like minimisation of shoreline erosion with rising sea levels. These new insights into such critical influences of climate and sea level on mangrove forests offer further affirmation of the urgency for implementing well-considered mitigation efforts for the protection of shoreline mangroves at risk, especially given predictions of future re-occurrences of extreme events affecting sea levels, combined with on-going pressure of rapidly rising sea levels

Using and communicating uncertainty for the effective control of invasive non-native species

Estimates of quantities needed to plan invasive species control, such as population size, are always uncertain; this is an issue that can become a problem when mishandled in ecological science and its communication. The complexities of incorporating uncertainty into sophisticated decision‐support tools may be a barrier to their use by decision makers, leading to decisions being made without due regard to uncertainty and risking misplaced certainty of predicted outcomes. We summarise ways in which uncertainty has been incorporated into and used to advise decisions on the management of invasive non‐native species and other problem species, and offer a simple conceptual model for accommodating and using uncertainty at the planning stage. We also demonstrate how frequently uncertainty has been misused and miscommunicated in the wildlife management literature. We contend that uncertainty in estimates of natural quantities must be acknowledged, can inform decisions and can be made to derive decisions, and should not be ignored if invasive species policy is to be delivered effectively. Uncertainty must be communicated thoroughly and correctly by scientists if decision makers are to understand its consequences for planning and resourcing control programmes

Learning with Weak Supervision for Email Intent Detection

Email remains one of the most frequently used means of online communication. People spend a significant amount of time every day on emails to exchange information, manage tasks and schedule events. Previous work has studied different ways for improving email productivity by prioritizing emails, suggesting automatic replies or identifying intents to recommend appropriate actions. The problem has been mostly posed as a supervised learning problem where models of different complexities were proposed to classify an email message into a predefined taxonomy of intents or classes. The need for labeled data has always been one of the largest bottlenecks in training supervised models. This is especially the case for many real-world tasks, such as email intent classification, where large scale annotated examples are either hard to acquire or unavailable due to privacy or data access constraints. Email users often take actions in response to intents expressed in an email (e.g., setting up a meeting in response to an email with a scheduling request). Such actions can be inferred from user interaction logs. In this paper, we propose to leverage user actions as a source of weak supervision, in addition to a limited set of annotated examples, to detect intents in emails. We develop an end-to-end robust deep neural network model for email intent identification that leverages both clean annotated data and noisy weak supervision along with a self-paced learning mechanism. Extensive experiments on three different intent detection tasks show that our approach can effectively leverage the weakly supervised data to improve intent detection in emails.Comment: 10 pages, 3 figure

Reciprocity as a foundation of financial economics

This paper argues that the subsistence of the fundamental theorem of contemporary financial mathematics is the ethical concept ‘reciprocity’. The argument is based on identifying an equivalence between the contemporary, and ostensibly ‘value neutral’, Fundamental Theory of Asset Pricing with theories of mathematical probability that emerged in the seventeenth century in the context of the ethical assessment of commercial contracts in a framework of Aristotelian ethics. This observation, the main claim of the paper, is justified on the basis of results from the Ultimatum Game and is analysed within a framework of Pragmatic philosophy. The analysis leads to the explanatory hypothesis that markets are centres of communicative action with reciprocity as a rule of discourse. The purpose of the paper is to reorientate financial economics to emphasise the objectives of cooperation and social cohesion and to this end, we offer specific policy advice

Treatment of Verrucous Carcinoma of the Lower Lip with Topical Imiquimod (Aldara®) and Debulking Therapy

Verrucous carcinoma is an unusual, non-metastasizing, distinct variant of squamous cell carcinoma composed of four subtypes according to the site of occurrence: oral type, anogenital type, plantar type, and other cutaneous sites. Oral type verrucous carcinoma usually shows slow progression with a low incidence of metastases. Treatment of verrcous carcinoma is challenging; multiple medical and surgical therapies are often attempted, with limited success. We reported on 2 cases of verrucous carcinoma of the lip treated with topical imiquimod and debulking therapy

Clonal Differences between Non-Typhoidal Salmonella (NTS) Recovered from Children and Animals Living in Close Contact in The Gambia

Salmonellosis is a neglected tropical disease causing serious dysentery and septicaemia particularly in young infants, elderly and immunocompromised individuals such as HIV patients and associated with substantial mortality in developing countries. Salmonellosis also constitutes a major public health problem as it is considered the most widespread bacterial zoonosis of food origin throughout the world. Many epidemiological data exist from developed countries concerning transmission of Non-Typhoidal Salmonella (NTS) but few are available from developing countries. In addition few studies in sub-Saharan Africa have considered the interface between humans and their environment in relation to animals present in the household and food hygiene. This study describes the prevalence of NTS among fourteen Gambian children and 210 domestic animals living in close proximity (household) to the children in a rural setting in The Gambia. We found that the domestic animals living in the same household as patients carried different NTS serovar and genotypes; indicating that zoonotic transmission does not occur in our setting. This study provides baseline data for future studies of transmission of NTS in rural Africa

Prescriptive variability of drugs by general practitioners

<div><p>Prescription drug spending is growing faster than any other sector of healthcare. However, very little is known about patterns of prescribing and cost of prescribing between general practices. In this study, we examined variation in prescription rates and prescription costs through time for 55 GP surgeries in Northern Ireland Western Health and Social Care Trust. Temporal changes in variability of prescribing rates and costs were assessed using the Mann–Kendall test. Outlier practices contributing to between practice variation in prescribing rates were identified with the interquartile range outlier detection method. The relationship between rates and cost of prescribing was explored with Spearman's statistics. The differences in variability and mean number of prescribing rates associated with the practice setting and socioeconomic deprivation were tested using t-test and <i>F</i>-test respectively. The largest between-practice difference in prescribing rates was observed for Apr-Jun 2015, with the number of prescriptions ranging from 3.34 to 8.36 per patient. We showed that practices with outlier prescribing rates greatly contributed to between-practice variability. The largest difference in prescribing costs was reported for Apr-Jun 2014, with the prescription cost per patient ranging from £26.4 to £64.5. In addition, the temporal changes in variability of prescribing rates and costs were shown to undergo an upward trend. We demonstrated that practice setting and socio-economic deprivation accounted for some of the between-practice variation in prescribing. Rural practices had higher between practice variability than urban practices at all time points. Practices situated in more deprived areas had higher prescribing rates but lower variability than those located in less deprived areas. Further analysis is recommended to assess if variation in prescribing can be explained by demographic characteristics of patient population and practice features. Identification of other factors contributing to prescribing variability can help us better address potential inappropriateness of prescribing.</p></div

Narrative and Cognitive Modeling: Insights From Beckett Exploring Mind's Complexity

Complex systems exacerbate a common problem for scientific enquiry: the difficulty of creating models able to discriminate fundamental elements or patterns from random behaviours or corollary components in the event or process at issue. This chapter argues that a similar tension between order and randomness has been a chief modelling problem of Samuel Beckett’s narratives, tied to his interest in a specific kind of complex system (the mind) and its emergent properties (consciousness and the narrative sense of self). Bulding on narratology, complex system frameworks, cognitive theories of emergence and of scientific modelling, this chapter introduces the idea of “fictional cognitive modelling”. Through this concept, the chapter analyses Beckett’s treatment of narrative devices as formal tools for the creation of “exploratory models” able to atomise the emerging unity of conscious experience and of a narrative sense of self into its core components (defined as the “narrative dynamic core”). It concludes by suggesting that Beckett’s narrative method shows how literature can occupy a proper position in the investigation and exploration of complex systems