Pulse shaper assisted short laser pulse characterization

We demonstrate that a pulse shaper is able to simultaneously act as an optical waveform generator and a short pulse characterization device when combined with an appropriate nonlinear element. We present autocorrelation measurements and their frequency resolved counterparts. We show that control over the carrier envelope phase allows continuous tuning between an intensity-like and an interferometric autocorrelation. By changing the transfer function other measurement techniques, for example STRUT, are easily realized without any modification of the optical setu

Ptychographic reconstruction of attosecond pulses

We demonstrate a new attosecond pulse reconstruction modality which uses an algorithm that is derived from ptychography. In contrast to other methods, energy and delay sampling are not correlated, and as a result, the number of electron spectra to record is considerably smaller. Together with the robust algorithm, this leads to a more precise and fast convergence of the reconstruction.Comment: 12 pages, 7 figures, the MATLAB code for the method described in this paper is freely available at http://figshare.com/articles/attosecond_Extended_Ptychographyc_Iterative_Engine_ePIE_/160187

Land as a Commodity Affected with a Public Interest

It is our purpose to suggest that a land use policy which is socially equitable and environmentally sensitive is not resolved simply by labelling land as a resource rather than a commodity. Instead, we propose to examine the special status land has enjoyed for many centuries, and which distinguishes it from other commodities, and to suggest that land transactions and land use should at last be scrutinized in a manner not unlike the treatment extended to a multitude of other commodities no more affected with a public interest than is land

Configurational theory and practices of firms employing multiple pricing policies: assessing effective and ineffective pricing recipes in multiple firm contexts

This study examines the presence and impact of complex alternative organizational configurations of pricing on firm performance. The dataset is from a survey of company owners and company CEOs, of which a subsample was used previously and analyzed with multiple regression analysis. Analyzing an enlarged dataset that includes new data using fuzzy-set qualitative comparative analysis (fsQCA) supports the perspective that multiple price policy paths are identifiable for indicating high performance for different firm operational contexts. By applying the perspective of complex interdependences of specific pricing activities and specific organizational configurations related to pricing, this study offers a nuanced contribution to marketing theory. To practicing managers, this study offers guidance for adopting specific configurations of pricing policies in specific contexts for achieving high firm performance as well as guidance on which configurations indicate negative firm performance outcomes

Pig fecal and tonsil contamination of Yersinia enterocolita in one French slaughterhouse

Pig is considered to be the main animal reservoir of human pathogenic Yersinia enterocolitica strains which is frequently isolated from tonsils, but can also be found in the feces and onto carcasses. In France, while the main pathogenic biotypes are known for humans, few data are available regarding their prevalence in the pork chain production, and generally focus on tonsils contamination

Very-high-resolution mapping of river-immersed topography by remote sensing

Remote sensing has been used to map river bathymetry for several decades. Non-contact methods are necessary in several cases: inaccessible rivers, large-scale depth mapping, very shallow rivers. The remote sensing techniques used for river bathymetry are reviewed. Frequently, these techniques have been developed for marine environment and have then been transposed to riverine environments. These techniques can be divided into two types: active remote sensing, such as ground penetrating radar and bathymetric lidar; or passive remote sensing, such as through-water photogrammetry and radiometric models. This last technique which consists of finding a logarithmic relationship between river depth and image values appears to be the most used. Fewer references exist for the other techniques, but lidar is an emerging technique. For each depth measurement method, we detail the physical principles and then a review of the results obtained in the field. This review shows a lack of data for very shallow rivers, where a very high spatial resolution is needed. Moreover, the cost related to aerial image acquisition is often huge. Hence we propose an application of two techniques, radiometric models and through-water photogrammetry, with very high-resolution passive optical imagery, light platforms, and off-the-shelf cameras. We show that, in the case of the radiometric models, measurement is possible with a spatial filtering of about 1 m and a homogeneous river bottom. In contrast, with through-water photogrammetry, fine ground resolution and bottom textures are necessary

Hyperparameter Importance Across Datasets

With the advent of automated machine learning, automated hyperparameter optimization methods are by now routinely used in data mining. However, this progress is not yet matched by equal progress on automatic analyses that yield information beyond performance-optimizing hyperparameter settings. In this work, we aim to answer the following two questions: Given an algorithm, what are generally its most important hyperparameters, and what are typically good values for these? We present methodology and a framework to answer these questions based on meta-learning across many datasets. We apply this methodology using the experimental meta-data available on OpenML to determine the most important hyperparameters of support vector machines, random forests and Adaboost, and to infer priors for all their hyperparameters. The results, obtained fully automatically, provide a quantitative basis to focus efforts in both manual algorithm design and in automated hyperparameter optimization. The conducted experiments confirm that the hyperparameters selected by the proposed method are indeed the most important ones and that the obtained priors also lead to statistically significant improvements in hyperparameter optimization.Comment: \c{opyright} 2018. Copyright is held by the owner/author(s). Publication rights licensed to ACM. This is the author's version of the work. It is posted here for your personal use, not for redistribution. The definitive Version of Record was published in Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Minin