String-String triality for d=4, Z_2 orbifolds

We investigate the perturbative and non-perturbative correspondence of a class of four dimensional dual string constructions with N=4 and N=2 supersymmetry, obtained as Z_2 or Z_2 x Z_2 orbifolds of the type II, heterotic and type I string. In particular, we discuss the heterotic and type I dual of all the symmetric Z_2 x Z_2 orbifolds of the type II string, classified in hep-th/9901123. .Comment: latex, 50 pages, figures, final published versio

Scaling of Magneto-Quantum-Radiative Hydrodynamic Equations: From Laser-produced Plasmas to Astrophysics

We introduce here the equations of magneto-quantum-radiative hydrodynamics. By rewriting them in a dimensionless form, we obtain a set of parameters that describe scale-dependent ratios of all the characteristic hydrodynamic quantities. We discuss how these dimensionless parameters relate to the scaling between astrophysical observations and laboratory experiments.Comment: 12 page

Reconsidering the analysis of longitudinal happiness data - with an application to the effect of unemployment

The paper reconsiders existing estimators for the panel data fixed effects ordered logit model, including one that has not been used in econometric studies before, and studies the small sample properties of these estimators in a series of Monte Carlo simulations. There are two main findings. First, we show that some of the estimators used in the literature are inconsistent. Second, the new estimator seems to be more immune to small sample bias than other consistent estimators and is easy to implement. The empirical relevance is illustrated in an application to the effect of unemployment on happiness. Choosing the right estimator avoids a bias of up to 30 percent in key parameters.Ordered response, panel data, correlated heterogeneity, incidental parameters

R^2 Corrections and Non-perturbative Dualities of N=4 String ground states

We compute and analyse a variety of four-derivative gravitational terms in the effective action of six- and four-dimensional type II string ground states with N=4 supersymmetry. In six dimensions, we compute the relevant perturbative corrections for the type II string compactified on K3. In four dimensions we do analogous computations for several models with (4,0) and (2,2) supersymmetry. Such ground states are related by heterotic-type II duality or type II-type II U-duality. Perturbative computations in one member of a dual pair give a non-perturbative result in the other member. In particular, the exact CP-even R^2 coupling on the (2,2) side reproduces the tree-level term plus NS 5-brane instanton contributions on the (4,0) side. On the other hand, the exact CP-odd coupling yields the one-loop axionic interaction a.R\wedge R together with a similar instanton sum. In a subset of models, the expected breaking of the SL(2,Z)_S S-duality symmetry to a \Gamma(2)_S subgroup is observed on the non-perturbative thresholds. Moreover, we present a duality chain that provides evidence for the existence of heterotic N=4 models in which N=8 supersymmetry appears at strong coupling.Comment: Latex2e, 51 pages, 1 figur

Dispatcher3 D4.2 - Prototype package (first release) - User manual

This deliverable along with deliverable D4.1. Technical documentation first release consists of the release of the first prototype of Dispatcher3. The release consists of the binaries and Docker version of the prototype (sent to the Topic Manager). The first release prototype package consists of a set on individual machine learning models which can be executed using Jupyter notebooks. It also includes the integration of the outcome of some of these individual models into a visualisation which would be part of the advice generator to provide high-level information to the end users. All models described in the Deliverable D4.1 will be available and executable in this release. Data required to run the models (with some examples) are also provided. If data are public raw sample values are provided, otherwise pre-computed features are delivered so that the models can be run on individual flight examples. The prototypes can be run using local data (provided in the release) or with data stored in cloud storage (Amazon Web Services (AWS)). This deliverable serves as a manual for the execution of the first release prototype software

Modelling passengers in air-rail multimodality

Air-rail mobility has the potential to play a significant role in addressing European mobility challenges such as emissions reduction and capacity shortages. Rail can complement the air network in different ways: enlarging airport catchment areas, supporting operations in case of disruption or replacing air links to obtain environmental benefits. There is, however, still a need to better understand the potential role of rail when substituting current air links both from a strategic and a tactical mobility perspective, particularly when passenger connections are considered. This was initially assessed, considering passengers' door-to-door itineraries, as part of the Modus project (H2020 - SESAR 2020) with an innovative approach towards data driven, integrated air-rail modelling. Further considerations, such as the evaluation of strategic and tactical multimodal solutions, will be explored in the MultiModX project (Horizon Europe - SESAR 3). This discussion paper presents the modelling challenges addressed in Modus and the approach defined for MultiModX to evaluate and model multimodal door-to-door solutions

Dispatcher3 – Machine learning to support flight planning processes

This poster will present the final results of the Clean Sky 2 project Dispatcher3. Dispatcher3 focuses on the use of machine learning techniques to support flight operations prior departure with holding predictions, runway at arrival estimation and fuel deviations pre-departure to support the flight crew, and ATFM and reactionary delays on D-1 to support the duty manage

Dispatcher3 – Machine learning for efficient flight planning - Approach and challenges for data-driven prototypes in air transport

Machine learning techniques to support decision making processes are in trend. These are particularly relevant in the context of flight management where large datasets of planned and realised operations are available. Current operations experience discrepancies between planned and executed flight plan, these might be due to external factors (e.g. weather, congestion) and might lead to sub-optimal decisions (e.g. recovering delay (burning extra fuel) when no holding is expected at arrival and therefore it was no needed). Dispatcher3 produces a set of machine learning models to support flight crew pre-departure, with estimations on expected holding at arrival, runway in use and fuel usage, and the airline’s duty manager on pre-tactical actions, with models trained with a larger look ahead time for ATFM and reactionary delay estimations. This paper describes the prototype architecture and approach of Dispatcher3 with particular focus on the challenges faced by this type of data-driven machine learning models in the field of air transport ranging: from technical aspects such as data leakage to operational requirements such as the consideration and estimation of uncertainty. These considerations should be relevant for projects which try to use machine learning in the field of aviation in general

An experimental study of steel fiber-reinforced high-strength concrete slender columns under cyclic loading

Structural engineers usually limit the use of HSC columns to seismic active zones because of their britle behavior in comparison with NSC, even though it presents advantages both in terms of mechanics and durability. A possible solution to improve the ductile behavior of HSC columns is the use of transverse reinforcement and steel fibers simultaneously. In addition, the use of HSC makes the design of more slender columns possible, with the consequent increase of second-order effects. However, there are few experimental tests on columns of medium slenderness (between 5 and 10) subjected to cyclic loads including or excluding steel fibers. This article presents experimental research work on the behavior of slender columns subjected to combined constant compression and cyclic lateral loads. Fifteen tests were carried out in order to study the behavior of such elements. The following variables were studied: concrete strength, slenderness, axial load level, transverse reinforcement ratio, and volumetric steel-fiber ratio. The maximum load and deformation capacity of the columns were analyzed. The fact that the inclusion of steel fibers into the concrete mixture increases the deformation capacity was verified. Moreover, a minimum transverse reinforcement is required in order to improve the effectiveness of the steel fibers with no significant decrease in the carrying capacity under cyclic loading. The inclusion of steel fibers in HSC can ensure similar ductility values to those of NSC. It was shown that slenderness influences the deformation capacity.Structural engineers usually limit the use of HSC columns to seismic active zones because of their britle behavior in comparison with NSC, even though it presents advantages both in terms of mechanics and durability. A possible solution to improve the ductile behavior of HSC columns is the use of transverse reinforcement and steel fibers simultaneously. In addition, the use of HSC makes the design of more slender columns possible, with the consequent increase of second-order effects. However, there are few experimental tests on columns of medium slenderness (between 5 and 10) subjected to cyclic loads including or excluding steel fibers. This article presents experimental research work on the behavior of slender columns subjected to combined constant compression and cyclic lateral loads. Fifteen tests were carried out in order to study the behavior of such elements. The following variables were studied: concrete strength, slenderness, axial load level, transverse reinforcement ratio, and volumetric steel-fiber ratio. The maximum load and deformation capacity of the columns were analyzed. The fact that the inclusion of steel fibers into the concrete mixture increases the deformation capacity was verified. Moreover, a minimum transverse reinforcement is required in order to improve the effectiveness of the steel fibers with no significant decrease in the carrying capacity under cyclic loading. The inclusion of steel fibers in HSC can ensure similar ductility values to those of NSC. It was shown that slenderness influences the deformation capacity