Heterotic free fermionic and symmetric toroidal orbifold models

Free fermionic models and symmetric heterotic toroidal orbifolds both constitute exact backgrounds that can be used effectively for phenomenological explorations within string theory. Even though it is widely believed that for Z2xZ2 orbifolds the two descriptions should be equivalent, a detailed dictionary between both formulations is still lacking. This paper aims to fill this gap: We give a detailed account of how the input data of both descriptions can be related to each other. In particular, we show that the generalized GSO phases of the free fermionic model correspond to generalized torsion phases used in orbifold model building. We illustrate our translation methods by providing free fermionic realizations for all Z2xZ2 orbifold geometries in six dimensions.Comment: 1+49 pages latex, minor revisions and references adde

Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions

We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We consider model selection criteria which have data-dependent penalties for a lack of parsimony, as well as the traditional ones. We suggest a new procedure which is a hybrid of traditional criteria with data-dependant penalties. In order to compute the fit of each model, we propose an iterative procedure to compute the maximum likelihood estimates of parameters of a VAR model with short-run and long-run restrictions. Our Monte Carlo simulations measure the improvements in forecasting accuracy that can arise from the joint determination of lag-length and rank, relative to the commonly used procedure of selecting the lag-length only and then testing for cointegration.Reduced rank models, model selection criteria, forecasting accuracy

Topography Effects in the Athens 1999 Earthquake: The Case of Hotel Dekelia

The effects of surface topography on the seismic ground response of the site of Hotel DEKELIA, which partially collapsed in the Athens 1999 earthquake, is studied by the finite element method. The hotel site is located at the crest of a 40m high bank of a stream crossing the area. 2-D and I-D analyses of seismic ground response were conducted using five accelerograms recorded in past earthquakes (including the Athens 1999 earthquake) as input motion. Geotechnical data for the site were obtained from the results of a geotechnical investigation conducted at the hotel site whereas a VSO vs. depth profile was estimated by using the SASW method. The ground response analyses were conducted by assuming both equivalent-linear and truly non-linear soil behavior. The results indicate that surface topography has the potential of amplifying the peak horizontal accelerations and the maximum spectral accelerations (for period values ranging from 0.35sec to 0.50 sec) at the hotel site by up to 35% and loo%, respectively. It was also found that the local soil conditions at the site may have amplified significantly the input motion. It is concluded that the combined effects of surface topography and local soil conditions may have contributed to the partial collapse of the hotel

Response of the chiral soliton lattice to spin polarized currents

Spin polarized currents originate a spin-transfer torque that enables the manipulation of magnetic textures. Here we theoretically study the effect of a spin-polarized current on the magnetic texture corresponding to a chiral soliton lattice in a monoaxial helimagnet under a transverse magnetic field. At sufficiently small current density the chiral soliton lattice reaches a steady motion state with a velocity proportional to the intensity of the applied current, the mobility being independent of the density of solitons and the magnetic field. This motion is accompanied with a small conical distortion of the chiral soliton lattice. At large current density the spin-transfer torque destabilizes the chiral soliton lattice, driving the system to a ferromagnetic state parallel to the magnetic field. We analyze how the deformation of the chiral soliton lattice depends on the applied current density. The destruction of the chiral soliton lattice under current could serve as a possible erasure mechanisms for spintronic applications.Comment: 13 pages, 8 figure

A wearable motion capture suit and machine learning predict disease progression in Friedreich's ataxia.

Friedreich's ataxia (FA) is caused by a variant of the Frataxin (FXN) gene, leading to its downregulation and progressively impaired cardiac and neurological function. Current gold-standard clinical scales use simplistic behavioral assessments, which require 18- to 24-month-long trials to determine if therapies are beneficial. Here we captured full-body movement kinematics from patients with wearable sensors, enabling us to define digital behavioral features based on the data from nine FA patients (six females and three males) and nine age- and sex-matched controls, who performed the 8-m walk (8-MW) test and 9-hole peg test (9 HPT). We used machine learning to combine these features to longitudinally predict the clinical scores of the FA patients, and compared these with two standard clinical assessments, Spinocerebellar Ataxia Functional Index (SCAFI) and Scale for the Assessment and Rating of Ataxia (SARA). The digital behavioral features enabled longitudinal predictions of personal SARA and SCAFI scores 9 months into the future and were 1.7 and 4 times more precise than longitudinal predictions using only SARA and SCAFI scores, respectively. Unlike the two clinical scales, the digital behavioral features accurately predicted FXN gene expression levels for each FA patient in a cross-sectional manner. Our work demonstrates how data-derived wearable biomarkers can track personal disease trajectories and indicates the potential of such biomarkers for substantially reducing the duration or size of clinical trials testing disease-modifying therapies and for enabling behavioral transcriptomics

Cohesion-Driven Decomposition of Service Interfaces without Access to Source Code

International audience—Software cohesion concerns the degree to which the elements of a module belong together. Cohesive software is easier to understand, test and maintain. In the context of service-oriented development, cohesion refers to the degree to which the operations of a service interface belong together. In the state of the art, software cohesion is improved based on refactoring methods that rely on information, extracted from the software implementation. This is a main limitation towards using these methods in the case of Web services: Web services do not expose their implementation; instead all that they export is the Web service interface specification. To deal with this problem, we propose an approach that enables the cohesion-driven decomposition of service interfaces, without information on how the services are implemented. Our approach progressive decomposes a given service interface into more cohesive interfaces; the backbone of the approach is a suite of cohesion metrics that rely on information, extracted solely from the specification of the service interface. We validate the approach in 22 real-world services, provided by Amazon and Yahoo. We assess the effectiveness of the proposed approach, concerning the cohesion improvement, and the number of interfaces that result from the decomposition of the examined interfaces. Moreover, we show the usefulness of the approach in a user study, where developers assessed the quality of the produced interfaces