Random walk forecast of urban water in Iran under uncertainty

There are two significant reasons for the uncertainties of water demand. On one hand, an evolving technological world is plagued with accelerated change in lifestyles and consumption patterns; and on the other hand, intensifying climate change. Therefore, with an uncertain future, what enables policymakers to define the state of water resources, which are affected by withdrawals and demands? Through a case study based on thirteen years of observation data in the Zayandeh Rud River basin in Isfahan province located in Iran, this paper forecasts a wide range of urban water demand possibilities in order to create a portfolio of plans which could be utilized by different water managers. A comparison and contrast of two existing methods are discussed, demonstrating the Random Walk Methodology, which will be referred to as the â On uncertainty pathâ , because it takes the uncertainties into account and can be recommended to managers. This On Uncertainty Path is composed of both dynamic forecasting method and system simulation. The outcomes show the advantage of such methods particularly for places that climate change will aggravate their water scarcity, such as Iran

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Crypto Art: A Decentralized View

Crypto art is limited-edition digital art, cryptographically registered with a token on a blockchain. Tokens represent a transparent, auditable origin and provenance for a piece of digital art. Blockchain technologies allow tokens to be held and securely traded without the involvement of third parties. Crypto art draws its origins from conceptual art: sharing the immaterial and distributive nature of artworks, the tight blending of artworks with currency, and the rejection of conventional art markets and institutions. The authors propose a collection of viewpoints on crypto art from different actors of the system: artists, collectors, galleries, art historians and data scientists. A set of emerging themes and open challenges surfaces

Perspectives on ‘the lens of risk’ interview series: interviews with Tom Horlick-Jones, Paul Slovic and Andy Alaszewski

This article is the fourth and final of an interview series with a selection of significant contributors to the social science of risk. It provides quasi-verbatim interviews with Tom Horlick-Jones, Paul Slovic and Andy Alaszewski. Tom Horlick-Jones contributed to Chapter 6 of the Royal Society Risk monograph, on risk management. He offers further insights into the debates which underlay its production to those given by Nick Pidgeon in the first article of this series. Paul Slovic provides a North American perspective on risk social science. Andy Alaszewski, in the last of the eight interviews, discusses his views about risk in relation to the evolution of his journal, Health, Risk & Society

Autonomy: Risk Assessment

Oceanography and ocean observation in general is ever trending toward both automated in situ observation and working in extreme environments. These goals can only be met by de?risking the technology and deployment practices to acceptable levels of risks. A number of industries have standardised risk management processes to support the design and development of their systems. The lack of formal risk assessment of autonomous ocean vehicles has hindered the potential for true autonomy, which is required for exploring unstructured and unexplored environments. When discussing risks different stakeholders may have different consequences foremost in mind. For example the vehicle owner may be interested in risk of loss, whereas the user is interested in risk of vehicle unavailability. Other risks, such as legal risks and risk of collision, affect all stakeholders. This chapter presents a risk management process using several methods tailored to autonomous oceanvehicles in which risk assessment is a key component