The influential pure embedding methodology of embedding domainspecific languages (DSLs) as libraries into a general-purpose host language forces the DSL designer to commit to a single semantics. This precludes the subsequent addition of compilation, optimization or domain-specific analyses. We propose polymorphic embedding of DSLs, where many different interpretations of a DSL can be provided as reusable components, and show how polymorphic embedding can be realized in the programming language Scala. With polymorphic embedding, the static type-safety, modularity, composability and rapid prototyping of pure embedding are reconciled with the flexibility attainable by external toolchains.

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Self-representation -the ability to represent programs in their own language -has important applications in reflective languages and many other domains of programming language design. Although approaches to designing typed program representations for sublanguages of some base language have become quite popular recently, the question whether a fully metacircular typed selfrepresentation is possible is still open. This paper makes a big step towards this aim by defining the F * ω calculus, an extension of the higher-order polymorphic lambda calculus Fω that allows typed self-representations. While the usability of these representations for metaprogramming is still limited, we believe that our approach makes a significant step towards a new generation of reflective languages that are both safe and efficient.

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Our current labour market is affected by massive changes like digitalization, automation and globalization, which gives rise to completely new forms of generating income. One such innovative idea is crowdworking, where many people (a so-called crowd) work on individual tasks for a firm in a way similar to a self-employed freelancer. This form of occupation is a recent development but gains acceptance, esteem and relevance quite rapidly. The risk potential for wage dumping and (self-) exploitation is still unknown. A crucial, but often neglected fact about crowdworking is that it exists in many variants which have completely different properties. We investigate how much these distinct versions of crowdworking differ by using an agent-based computer simulation. Wages, job security, workforce composition and other relevant indicators are calculated by simulating the micro scale to gain aggregated information on the macro-scale. We find that there is a significant difference between the versions of crowdworking. Our main finding is that especially variants where the crowdworkers are able to set their own wages are susceptible to wage dumping. Simulations suggest that this phenomenon is independent of the specifics of the labour market but rather a fundamental property of those variants of crowdworking.

BackgroundUnderstanding traffic is an important challenge in different scientific fields. While there are many approaches to constructing traffic models, most of them rely on origin–destination data and have difficulties when phenomena should be investigated that have an effect on the origin–destination matrix.MethodsA macroscopic traffic model is introduced that is novel in the sense that no origin–destination data are required as an input. This information is generated from mobility behavior data using a hybrid approach between agent-based modeling to find the origin and destination points of each vehicle and network techniques to find efficiently the routes most likely used to connect those points. The simulated road utilization and resulting congestion is compared to traffic data to quantitatively evaluate the results. Traffic jam avoidance behavior is included in the model in several variants, which are then all evaluated quantitatively.ResultsThe described model is applied to the City of Graz, a typical European city with about 320,000 inhabitants. Calculated results correspond well with reality.ConclusionsThe introduced traffic model, which uses mobility data instead of origin–destination data as input, was successfully applied and offers unique advantages compared to traditional models: Mobility behavior data are valid for different systems, while origin–destination data are very specific to the region in question and more difficult to obtain. In addition, different scenarios (increased population, more use of public transport, etc.) can be evaluated and compared quickly.

Critical transitions of complex systems can often be predicted by so-called early-warning signals (EWS). In some cases, however, such signals cannot be detected although a critical transition is imminent. Observing a relation of EWS-detectability and the network topology in which the system is implemented, we simulate and investigate scale-free networks and identify which networks show, and which do not show EWS in the framework of a two state system that exhibits critical transitions. Additionally, we adapt our approach by examining the effective state of the system, rather than its natural state, and conclude that this transformation can reveal hidden EWS in networks where those signals are otherwise obscured by a complex topology.

Motorized transport is one of the main contributors to anthropogenic CO 2 emissions, which cause global warming. Other emissions, like nitrogen oxides or carbon monoxide, are detrimental to human health. A prominent way to understand and thus be able to minimize emissions is by using traffic simulations to evaluate different scenarios. In that way, one can find out which policies, technical innovations, or behavioral changes can lead to a decrease in emissions. Since the effect of CO 2 is on a global scale, a macroscopic model is often enough to find reasonable results. However, NO x emissions can also have a direct, local effect. Therefore, it is interesting to investigate these emissions on a mesoscopic scale, to gain insight into the local distribution of this pollutant. In this study, we used a traffic model that, contrary to most other state-of-the-art traffic simulations, does not require an origin-destination matrix as an input, but calculates it from mobility behavior extracted from a survey. We then generated agents with realistic mobility behavior that perform their daily trips and calculate key features like congestion and emissions for every edge of the road network. Our approach has the additional advantage of allowing to investigate technical, juridical, as well as behavioral changes, all within the same framework. It is then possible to identify strategies that minimize NO x emissions caused by private motorized transport. Evaluation showed good agreement with reality in terms of local and temporal resolution. Especially when looking at the sum of emissions, the main feature for evaluating policies, and deviations between our simulation and available statistics were negligible. We found that, from all scenarios we investigated, the ban of old diesel cars is the most promising policy: By replacing all diesel cars built in 2005 or earlier with petrol cars of the same age, NO x emissions could drop by roughly a third.the city of Lyon [6] found that traffic was the main contributor, responsible for over 50% of total NO x emissions. When considering citizen exposure to NO 2 in urban areas, the relative contribution of the road sector is even bigger [5]. This extent of emissions is not only caused by the higher population density of an urban environment, but also by high congestion. Congested roads lead to an increase in traffic emissions and thus health risks for people in these areas [4]. In order to quantify those health risks, emission inventories created by coupled traffic and emissions models are then fed into meteorological and atmospheric chemistry transport models to yield their effect on air quality [7]. Subsequently, human exposure models link the concentration of pollutants with human factors [8].There is not necessarily a linear relation of the concentration to health effects. Thus, together with data on other adverse substances, the health hazard can finally be modeled [9].In order to combat the negative effects of traffic-related emissions, infrastructural and policy changes in a city's ro...