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Communication technologies, from printing to social media, affect our historical records by changing the way ideas are spread and recorded. Yet, finding statistical instruments to address the endogeneity of this relationship has been problematic. Here we use a city's distance to Mainz as an instrument for the introduction of the printing press in European cities, together with data on nearly 50 thousand biographies, to show that cities that adopted printing earlier were more likely to be the birthplace of a famous scientist or artist in the years after the introduction of printing. At the global scale, we find that the introduction of printing is associated with a significant and discontinuous increase in the number of biographies available from people born after the introduction of printing. We bring these findings to more recent communication technologies by showing that the number of radios and televisions in a country correlates with the number of performing artists and sports players from that country that reached global fame, even after controlling for GDP, population, and including country and year fixed effects. These findings support the hypothesis that the introduction of communication technologies shift historical records in the direction of the content that is best suited for each technology.

Reconstruction of images from noisy linear measurements is a core problem in image processing, for which convex optimization methods based on total variation (TV) minimization have been the long-standing state-of-the-art. We present an alternative probabilistic reconstruction procedure based on approximate message-passing, Scampi, which operates in the compressive regime, where the inverse imaging problem is underdetermined. While the proposed method is related to the recently proposed GrAMPA algorithm of Borgerding, Schniter, and Rangan, we further develop the probabilistic approach to compressive imaging by introducing an expectation-maximizaiton learning of model parameters, making the Scampi robust to model uncertainties. Additionally, our numerical experiments indicate that Scampi can provide reconstruction performance superior to both GrAMPA as well as convex approaches to TV reconstruction. Finally, through exhaustive best-case experiments, we show that in many cases the maximal performance of both Scampi and convex TV can be quite close, even though the approaches are a prori distinct. The theoretical reasons for this correspondence remain an open question. Nevertheless, the proposed algorithm remains more practical, as it requires far less parameter tuning to perform optimally. Comment: Presented at the 2015 International Meeting on High-Dimensional Data Driven Science, Kyoto, Japan

International audience; Our aim is to derive the symmetries of the space-time, i.e. the Lorentz transformations, from discrete symmetries of the interactions between the most fundamental constituents of matter, in particular quarks and leptons. The role of Pauli’s exclusion principle in the derivation of the SL(2,C), symmetry is put forward as the source of the macroscopically observed Lorentz symmetry. Then Pauli’s principle is generalized for the case of the Z 3 grading replacing the usual Z 2 grading, leading to ternary commutation relations for quantum operator algebras. In the case of lowest dimension, with two generators only, it is shown how the cubic combinations Z 3-graded elements behave like Lorentz spinors, and the binary product of elements of this algebra with an element of the conjugate algebra behave like Lorentz vectors.

Mathematical representation of complex data knowledge is one of the most important problems in Classification and Data Mining. In this contribution we present an original and very general formalization of various types of knowledge. The specific data are endowed with biological descriptions of phlebotomine sandfly species. Relative to a descriptive categorical variable, subsets of categories values have to be distinguished. On the other hand, hierarchical dependencies between the descriptive variables, associated with the mother → daughter relation, have to be taken into account. Additionally, an ordinal similarity function on the modality set of each categorical variable. The knowledge description is formalized by means of a new type of descriptor that we call “Taxonomic preordonance variable with multiple choice”. Probabilistic similarity index between concepts described by such variables can be built.

We implement a 3D spectral-element method for multistage excavation problems. To simulate excavation in elastoplastic soils, we employ a Mohr-Coulomb yield criterion using an initial strain method. We parallelize the software based on non-overlapping domain decomposition using MPI. We verify the uniqueness principle for multistage excavation in linear elastic materials. We validate our serial and parallel programs, and illustrate several examples of multistage excavation in elastoplastic materials. Finally, we apply our software to a model of the Pyhasalmi ore mine in Finland. Strong-scaling performance tests involving multistage excavation show that the parallel program performs reasonably well for large-scale problems.

ObjectivesThis review investigates characteristics of implemented adaptive design clinical trials and provides examples of regulatory experience with such trials.DesignReview of adaptive design clinical trials in EMBASE, PubMed, Cochrane Registry of Controlled Clinical Trials, Web of Science and ClinicalTrials.gov. Phase I and seamless Phase I/II trials were excluded. Variables extracted from trials included basic study characteristics, adaptive design features, size and use of independent data monitoring committees (DMCs) and blinded interim analyses. We also examined use of the adaptive trials in new drug submissions to the Food and Drug Administration (FDA) and European Medicines Agency (EMA) and recorded regulators’ experiences with adaptive designs.Results142 studies met inclusion criteria. There has been a recent growth in publicly reported use of adaptive designs among researchers around the world. The most frequently appearing types of adaptations were seamless Phase II/III (57%), group sequential (21%), biomarker adaptive (20%), and adaptive dose-finding designs (16%). About one-third (32%) of trials reported an independent DMC, while 6% reported blinded interim analysis. We found that 9% of adaptive trials were used for FDA product approval consideration, and 12% were used for EMA product approval consideration. International regulators had mixed experiences with adaptive trials. Many product applications with adaptive trials had extensive correspondence between drug sponsors and regulators regarding the adaptive designs, in some cases with regulators requiring revisions or alterations to research designs.ConclusionsWider use of adaptive designs will necessitate new drug application sponsors to engage with regulatory scientists during planning and conduct of the trials. Investigators need to more consistently report protections intended to preserve confidentiality and minimise potential operational bias during interim analysis.

The present work investigates the memory accessibility of linguistically focused elements and the representation of the alternatives for these elements (i.e., their possible replacements) in Working Memory (WM) and in delayed recognition memory in the case of the Hungarian pre-verbal focus construction (preVf). In two probe recognition experiments we presented preVf and corresponding focusless neutral sentences embedded in five-sentence stories. Stories were followed by the presentation of sentence probes in one of three conditions: (i) the probe was identical to the original sentence in the story, (ii) the focused word (i.e., target) was replaced by a semantically related word and (iii) the target word was replaced by a semantically unrelated but contextually suitable word. In Experiment 1, probes were presented immediately after the stories measuring WM performance, while in Experiment 2, blocks of six stories were presented and sentences were probed with a 2-minute delay measuring delayed recognition memory performance. Results revealed an advantage of the focused element in immediate but not in delayed retrieval. We found no effect of sentence type on the recognition of the two different probe types in WM performance. However, results pertaining to the memory accessibility of focus alternatives in delayed retrieval showed an interference effect resulting in a lower memory performance. We conclude that this effect is indirect evidence for the enhanced activation of focus alternatives. The present work is novel in two respects. First, no study has been conducted on the memory representation of focused elements and their alternatives in the case of the structurally marked Hungarian pre-verbal focus construction. Second, to our knowledge, this is the first study that investigates the focus representation accounts for WM and delayed recognition memory using the same stimuli and same measured variables. Since both experiments used exactly the same stimulus set, and they only differed in terms of the timing of recognition probes, the principle of ceteris paribus fully applied with respect to how we addressed our research question regarding the two different memory systems.

The manual reading of all the product reviews to find a satisfying item is not only labor-intensive, but also tedious for the consumers. In this paper, we propose a feature-opinion mining approach to automatically summarize the reviews, which is based on dependency parsing. Specifically, in our approach we first utilize a regression model to generate sentiment word, including phrase and its sentiment weight, and then we extract the feature based on the dependency relationship between feature word and sentiment word, finally we assign a score to the feature according to the dependency relationship. The experimental results demonstrate that our approach can effectively mine the feature-opinion from reviews.

Abstract We present a polling strategy to predict and analyze runoff elections using the 2017 French presidential race as an empirical case. This strategy employs rejective probability sampling to identify a small sample of polling stations that is balanced with respect to past election results. We then survey the voters’ candidate evaluations in first-round exit polls. We poststratify the voter sample to first-round election returns to account for nonresponse and coverage issues, and impute missing candidate evaluations to emulate campaign learning. Next, the votes for eliminated competitors are redistributed according to their supporters’ lower-order preferences. Finally, the predictions are validated against official results and other polls. We end with a discussion of the advantages and limitations of this approach.