Analytical Optimization Model to Locate and Design Runway-Taxiway Junctions

Aims: Air traffic and airport operations are expected to experience significant growth worldwide in the upcoming years. One of the possible approaches to adapt to this demand-led growth in the sector, while guaranteeing optimal levels of airport services and operations safety, is to maximize the capacities of busy airport infrastructures (in particular runways) by evacuating them in the shortest time possible to be ready for hosting next operations. Background: The main research areas in this field range from statistical risk analyses based on the registered accidents databases to simulation analyses modelling the behaviour of the aircraft during landing operations. Objective: The main objective of this study is to determine precisely the optimal distances of runway-taxiway junctions from the runway’s threshold, according to numerous impact parameters such as airport climate pattern, operating aircraft categories, infrastructure type, and capacity, route connections, operating costs, and associated risks. Methods: The authors developed a mathematical model with the goal of simulating the dynamic behaviour of the aircraft during landing and possible consequences introduced by the presence of contaminants over the pavement surface, by calculating their braking distances, and finally to optimize the use of existing infrastructures, specially runway-taxiway junctions, of a commercial airport. In this regard, the interactions between landing gear, pavement, and fluid were carefully analysed. The dynamic pavement skid resistance values in wet pavement conditions were evaluated for optimizing the required landing distances, which are setting the base for optimizing the location of the taxiway junctions. An Italian international airport was selected as the case study to be simulated by the developed model in order to optimize its runway capacity and maximize its rate of operations. Results: In the process, two different scenarios are simulated with the developed model; a modified design of an existing runway and an alternative design solution for constructing a new runway. The developed model offers improvements for both scenarios with respect to the current runway configurations in terms of reduction in mean rolling distances. The simulation of the selected case study shows that the taxiway modification scenario achieves a reduction of 23% in the mean rolling distance for wet and 25% for dry pavement conditions. While, for designing a new runway, greater reductions of 27% for wet and 39% for dry pavement conditions are obtained due to the higher flexibilities and degrees of freedom in designing a runway from the beginning. Conclusion: The developed model can precisely propose new configurations of the runway-taxiway junctions with lower mean rolling distances, which lower the operation costs and fuel consumption, decrease the runway evacuation times and increase the capacity of the airfield. The main advantage of this model is its ability to cover a wider spectrum of boundary conditions with respect to the existing models and its applicability for designing new runways, plus to optimize the configuration of existing infrastructures in order to satisfy the evolution of the industry.

Protection of a Stationary Object from the Massive Impact of Mobile Objects under Conditions of von Neumann's Mixed Game

The method of statistical simulation modeling (SSM) has been used to analyze the operating conditions and the efficiency of the physical protection system of a stationary object from the massive impact of unmanned aerial vehicles (drones). It is shown that the conditions of the problem correspond to the reflexive version of a two-sided von Neumann's mixed game. statistical risk-oriented characteristics for two variants of the object protection system implementation using force mechanical and electromagnetic effects on the "drones cloud" are determined. The possibilities and the prospects for using the results obtained using the SSM method are presented.

Other Statistical Lives

While recent scholarship has considered how algorithmic risk assessment is both shaped by and impacts social inequity, public health has not adequately considered the ways that statistical risk functions in the social world. Drawing on ethnographic and interview data collected in interpersonal violence prevention programs, this manuscript theorizes three “other lives” of statistically produced risk factors: the past lives of risk factors as quantifiable lived experience, the professional lives of risk as a practical vocabulary shaping social interactions, and the missing lives of risk as a meaningful social category for those marked as at risk. The manuscript considers how understanding these other lives of statistical risk can help public health scholars better understand barriers to social equity.

Acquired autoimmune Haemophilia following SARS-CoV-2 vaccines: Dual drug effects on blood coagulation and the Scylla and Charybdis phenomenon

Vaccination against the SARS-CoV-2 may lead to immunologic reactions activating the haemostatic system and resulting in both venous and arterial thromboembolism. Aquired autoimmune Haemophilia following SARS-CoV-2 vaccines were now reported 15 to 19 days (or later) after vaccination and resolution of symptoms by adequate treatment of the immunologic reaction. From patients’ point of view, anticoagulants and SARS-CoV-2 vaccines share their capacity to induce thrombosis as well as bleeding and clinicians are subjected to Scylla and Charybdis when they treat patients not only with anticoagulants but also with SARS-CoV-2 vaccines. Careful analysis of coincidence and causality requires attention when reporting on acquired coagulation inhibitors regarding severity, treatments, duration and statistical risk.

Grading Investment Diversification Options in Presence of Non-Historical Financial Information

Modern portfolio theory deals with the problem of selecting a portfolio of financial assets such that the expected return is maximized for a given level of risk. The forecast of the expected individual assets’ returns and risk is usually based on their historical returns. In this work, we consider a situation in which the investor has non-historical additional information that is used for the forecast of the expected returns. This implies that there is no obvious statistical risk measure any more, and it poses the problem of selecting an adequate set of diversification constraints to mitigate the risk of the selected portfolio without losing the value of the non-statistical information owned by the investor. To address this problem, we introduce an indicator, the historical reduction index, measuring the expected reduction of the expected return due to a given set of diversification constraints. We show that it can be used to grade the impact of each possible set of diversification constraints. Hence, the investor can choose from this gradation, the set better fitting his subjective risk-aversion level.

Statistical risk warnings in gambling

Gambling is considered a public health issue by many researchers, similarly to alcohol or obesity. Statistical risk warnings on gambling products can be considered a public health intervention that encourages safer gambling while preserving freedom of consumer choice. Statistical risk warnings may be useful to gamblers, given that net gambling losses are the primary driver of harm and that gambling products vary greatly in the degree to which they facilitate losses. However, there is some doubt as to whether statistical risk warnings are, in their current form, effective at reducing gambling harm. Here, we consider current applications and evidence, discuss product-specific issues around a range of gambling products and suggest future directions. Our primary recommendation is that current statistical risk warnings can be improved and also applied to a wider range of gambling products. Such an approach should help consumers to make more informed judgements and potentially encourage gambling operators to compete more directly on the relative ‘price’ of gambling products.

Calculating Race

Calculating Race: Racial Discrimination in Risk Assessment presents the historical relationship between statistical risk assessment and race in the United States. It illustrates how, through a reliance on the variable of race, actuarial science transformed the nature of racism and, in turn, helped usher racial disparities in wealth, incarceration, and housing from the nineteenth century into the twentieth. The monograph begins by investigating the development of statistical risk assessment explicitly based on race in the late-nineteenth-century life insurance industry. It then traces how such risk assessment migrated from industry to government, becoming a guiding force in parole decisions and in federal housing policy. Finally, it concludes with an analysis of “proxies” for race—statistical variables that correlate significantly with race—in order to demonstrate the persistent presence of race in risk assessment even after the anti-discrimination regulations won by the Civil Rights Movement. Offering readers a new perspective on the historical importance of actuarial science in structural racism, Calculating Race is a particularly timely contribution as Big Data and algorithmic decision-making increasingly pervade American life.