An Exploratory Investigation of Public Perceptions Towards Key Benefits and Concerns from the Future Use of Flying Cars

The imminent introduction of flying cars in the traffic fleet is anticipated to modify the mobility patterns of urban commuters. Flying cars' hybrid operation on the ground and in the air, in conjunction with their (semi-) automated capabilities, may lead to more appealing trip considerations, such as travel time, fuel consumption, or environmental emissions, as well as to the emergence of new sources of concerns for the potential users. In this context, the future adoption of flying cars is directly associated with individuals' perceptions of the benefits and concerns arising from the use of flying cars. This paper aims to identify the perceptual patterns of individuals towards travel time, cost and environmental benefits, as well as towards challenges arising from key flying cars operational characteristics. To that end, grouped random parameters bivariate probit models of individuals' perceptions are estimated using data collected from an online survey of 692 individuals. The statistical analysis shows that a number of socio-demographic, behavioral, and attitudinal characteristics affect respondents' expectations and concerns towards the adoption and implementation of flying cars. Even though individuals' perceptions are anticipated to undergo substantial changes until the introduction of flying cars in the traffic fleet, the findings of this work may shed more light on perceptual nuances with critical effect on public interest about the adoption of flying cars

An exploratory empirical analysis of willingness to hire and pay for flying taxis and shared flying car services

A new transportation mode that can simultaneously operate on land and in the air, namely the flying cars, is anticipated to penetrate the automobile fleet between 2020 and 2025. Due to their flexible mobility patterns and automated operational characteristics, flying taxi and shared flying car services are expected to expand the existing shared mobility services (such as Uber, Lyft, and similar services) of the urban transportation network. Despite their forthcoming introduction in the shared mobility market, public perceptions and expectations about these services have not been investigated in travel demand literature. This study aims to provide an exploratory analysis of public willingness to hire and pay for flying taxis and shared flying car services, and to identify the determinants of the willingness to hire and pay for such services. Using data collected from an online survey, individuals’ willingness to hire and to pay for flying taxi and shared flying car services are statistically modeled within a correlated grouped random parameters bivariate probit framework. The analysis shows that various socio-demographic characteristics and individuals’ opinions towards the perceived benefits and challenges of flying cars affect public willingness to hire and pay for flying taxi and shared flying car services. Even though the awareness about the operation of flying taxis and shared flying car services is possibly limited in the public sphere, the findings of this study can provide insights into the challenges that policymakers, manufacturing companies, and shared mobility providers will face with the introduction of such flying car services in the transportation networks

Analysis of Safety Benefits and Security Concerns from the Use of Autonomous Vehicles: A Grouped Random Parameters Bivariate Probit Approach with Heterogeneity in Means

This paper investigates public perceptions towards potential safety benefits, and safety- and security-related concerns from the future use of autonomous vehicles by utilizing data collected from an online survey. The survey includes responses from 584 individuals from the United States, who responded to a varying range of questions related to autonomous vehicles and their usage. The subsequent exploratory statistical analysis is conducted by employing a novel method, namely the grouped random parameters bivariate probit model with heterogeneity in means. The proposed method accounts for the challenges stemming from the presence of multiple layers of unobserved heterogeneity in the data, and simultaneously offers more insightful results. From the analysis, several socio-demographic characteristics, and driving attitude related characteristics and opinions were found to affect the perceptions towards the safety and security related aspects of autonomous vehicles. The heterogeneity in means approach revealed distinct individual-specific characteristics that affect the peak of the distribution of the parameter density function of the random parameters, adding further clarity to the understanding of the factors affecting individuals’ perceptions towards autonomous vehicles. The findings from this study suggest the ongoing evaluation of public perceptions, and reinforce the requirement of analyzing temporal variations in public perceptions. This can, in turn, aid regulatory and governance entities and autonomous vehicle manufacturers to adapt their strategies and implementation plans accordingly

Regularizing Portfolio Optimization

The optimization of large portfolios displays an inherent instability to estimation error. This poses a fundamental problem, because solutions that are not stable under sample fluctuations may look optimal for a given sample, but are, in effect, very far from optimal with respect to the average risk. In this paper, we approach the problem from the point of view of statistical learning theory. The occurrence of the instability is intimately related to over-fitting which can be avoided using known regularization methods. We show how regularized portfolio optimization with the expected shortfall as a risk measure is related to support vector regression. The budget constraint dictates a modification. We present the resulting optimization problem and discuss the solution. The L2 norm of the weight vector is used as a regularizer, which corresponds to a diversification "pressure". This means that diversification, besides counteracting downward fluctuations in some assets by upward fluctuations in others, is also crucial because it improves the stability of the solution. The approach we provide here allows for the simultaneous treatment of optimization and diversification in one framework that enables the investor to trade-off between the two, depending on the size of the available data set

Second law, entropy production, and reversibility in thermodynamics of information

We present a pedagogical review of the fundamental concepts in thermodynamics of information, by focusing on the second law of thermodynamics and the entropy production. Especially, we discuss the relationship among thermodynamic reversibility, logical reversibility, and heat emission in the context of the Landauer principle and clarify that these three concepts are fundamentally distinct to each other. We also discuss thermodynamics of measurement and feedback control by Maxwell's demon. We clarify that the demon and the second law are indeed consistent in the measurement and the feedback processes individually, by including the mutual information to the entropy production.Comment: 43 pages, 10 figures. As a chapter of: G. Snider et al. (eds.), "Energy Limits in Computation: A Review of Landauer's Principle, Theory and Experiments

The history of attention deficit hyperactivity disorder

The contemporary concept of attention deficit hyperactivity disorder (ADHD) as defined in the DSM-IV-TR (American Psychiatric Association 2000) is relatively new. Excessive hyperactive, inattentive, and impulsive children have been described in the literature since the nineteenth century. Some of the early depictions and etiological theories of hyperactivity were similar to current descriptions of ADHD. Detailed studies of the behavior of hyperactive children and increasing knowledge of brain function have changed the concepts of the fundamental behavioral and neuropathological deficits underlying the disorder. This article presents an overview of the conceptual history of modern-day ADHD

Environmental risk factors for dementia: a systematic review

Background - Dementia risk reduction is a major and growing public health priority. While certain modifiable risk factors for dementia have been identified, there remains a substantial proportion of unexplained risk. There is evidence that environmental risk factors may explain some of this risk. Thus, we present the first comprehensive systematic review of environmental risk factors for dementia. Methods - We searched the PubMed and Web of Science databases from their inception to January 2016, bibliographies of review articles, and articles related to publically available environmental data. Articles were included if they examined the association between an environmental risk factor and dementia. Studies with another outcome (for example, cognition), a physiological measure of the exposure, case studies, animal studies, and studies of nutrition were excluded. Data were extracted from individual studies which were, in turn, appraised for methodological quality. The strength and consistency of the overall evidence for each risk factor identified was assessed. Results - We screened 4784 studies and included 60 in the review. Risk factors were considered in six categories: air quality, toxic heavy metals, other metals, other trace elements, occupational-related exposures, and miscellaneous environmental factors. Few studies took a life course approach. There is at least moderate evidence implicating the following risk factors: air pollution; aluminium; silicon; selenium; pesticides; vitamin D deficiency; and electric and magnetic fields. Conclusions - Studies varied widely in size and quality and therefore we must be circumspect in our conclusions. Nevertheless, this extensive review suggests that future research could focus on a short list of environmental risk factors for dementia. Furthermore, further robust, longitudinal studies with repeated measures of environmental exposures are required to confirm these associations

In Vivo Assessment of Cold Adaptation in Insect Larvae by Magnetic Resonance Imaging and Magnetic Resonance Spectroscopy

Background Temperatures below the freezing point of water and the ensuing ice crystal formation pose serious challenges to cell structure and function. Consequently, species living in seasonally cold environments have evolved a multitude of strategies to reorganize their cellular architecture and metabolism, and the underlying mechanisms are crucial to our understanding of life. In multicellular organisms, and poikilotherm animals in particular, our knowledge about these processes is almost exclusively due to invasive studies, thereby limiting the range of conclusions that can be drawn about intact living systems. Methodology Given that non-destructive techniques like 1H Magnetic Resonance (MR) imaging and spectroscopy have proven useful for in vivo investigations of a wide range of biological systems, we aimed at evaluating their potential to observe cold adaptations in living insect larvae. Specifically, we chose two cold-hardy insect species that frequently serve as cryobiological model systems–the freeze-avoiding gall moth Epiblema scudderiana and the freeze-tolerant gall fly Eurosta solidaginis. Results In vivo MR images were acquired from autumn-collected larvae at temperatures between 0°C and about -70°C and at spatial resolutions down to 27 µm. These images revealed three-dimensional (3D) larval anatomy at a level of detail currently not in reach of other in vivo techniques. Furthermore, they allowed visualization of the 3D distribution of the remaining liquid water and of the endogenous cryoprotectants at subzero temperatures, and temperature-weighted images of these distributions could be derived. Finally, individual fat body cells and their nuclei could be identified in intact frozen Eurosta larvae. Conclusions These findings suggest that high resolution MR techniques provide for interesting methodological options in comparative cryobiological investigations, especially in vivo

Lawson criterion for ignition exceeded in an inertial fusion experiment

For more than half a century, researchers around the world have been engaged in attempts to achieve fusion ignition as a proof of principle of various fusion concepts. Following the Lawson criterion, an ignited plasma is one where the fusion heating power is high enough to overcome all the physical processes that cool the fusion plasma, creating a positive thermodynamic feedback loop with rapidly increasing temperature. In inertially confined fusion, ignition is a state where the fusion plasma can begin "burn propagation" into surrounding cold fuel, enabling the possibility of high energy gain. While "scientific breakeven" (i.e., unity target gain) has not yet been achieved (here target gain is 0.72, 1.37 MJ of fusion for 1.92 MJ of laser energy), this Letter reports the first controlled fusion experiment, using laser indirect drive, on the National Ignition Facility to produce capsule gain (here 5.8) and reach ignition by nine different formulations of the Lawson criterion