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This data article describes the original data, the sample selection process and the variables used in Andreoli and Fusco (Andreoli and Fusco, 2019) to estimate gap curves for a sample of European countries. Raw data are from 2011 roaster of EU-SILC, cross-sectional sample of module “intergenerational transmission of disadvantage”. This article reports descriptive statistics of the using sample. It also discusses the algorithm adopted to estimate the main effects and details the content of additional Stata files stored on the online repository. These additional files contain raw estimates from bootstrapped samples, which form the basis for estimating gap curves and their variance-covariance matrices. The data article also reports representations of gap curves for all 16 selected countries. Keywords: Inequality, Survey data, Intergenerational, Cohort, Earnings, Gap curves, Europe

If used appropriately, panel data in transportation allow for better decision making for mobility of passengers and supply chain services for freight. Research on transport is constrained by the availability of data. While the trend is to examine questions at a more disaggregate level, often building to the aggregate level through the summation of a multitude of individual data observations (big data), this chapter offers examples of how constraints in data availability can still provide useful and robust analysis.

Generalized regression neural networks (GRNN) may act as crowdsourcing cognitive agents to screen small, dense and complex datasets. The concurrent screening and optimization of several complex physical and sensory traits of bread is developed using a structured Taguchi-type micro-mining technique. A novel product outlook is offered to industrial operations to cover separate aspects of smart product design, engineering and marketing. Four controlling factors were selected to be modulated directly on a modern production line: 1) the dough weight, 2) the proofing time, 3) the baking time, and 4) the oven zone temperatures. Concentrated experimental recipes were programmed using the Taguchi-type L9(34) OA-sampler to detect potentially non-linear multi-response tendencies. The fused behavior of the master-ranked bread characteristics behavior was smart sampled with GRNN-crowdsourcing and robust analysis. It was found that the combination of the oven zone temperatures to play a highly influential role in all investigated scenarios. Moreover, the oven zone temperatures and the dough weight appeared to be instrumental when attempting to synchronously adjusting all four physical characteristics. The optimal oven-zone temperature setting for concurrent screening-and-optimization was found to be 270–240 °C. The optimized (median) responses for loaf weight, moisture, height, width, color, flavor, crumb structure, softness, and elasticity are: 782 g, 34.8 %, 9.36 cm, 10.41 cm, 6.6, 7.2, 7.6, 7.3, and 7.0, respectively.

Rendezvous orbital dynamics and control (RODC) is a key technology for operating space rendezvous and docking missions. This paper surveys the studies on RODC. Firstly, the basic relative dynamics equation set is introduced and its improved versions are evaluated. Secondly, studies on rendezvous trajectory optimization are commented from three aspects: the linear rendezvous, the nonlinear two-body rendezvous, and the perturbed and constrained rendezvous. Thirdly, studies on relative navigation are briefly reviewed, and then close-range control methods including automated control, manual control, and telecontrol are analyzed. Fourthly, advances in rendezvous trajectory safety and robust analysis are surveyed, and their applications in trajectory optimization are discussed. Finally, conclusions are drawn and prospects of studies on RODC are presented.

The characteristics of solar-irradiance datasets used to forecast the performance of solar electrical systems and to estimate the ability of the electricality generated to meet scheduled loan repayments are discussed in this chapter. Examples are given of datasets currently available, and their strengths and weaknesses are illustrated. Measured datasets, ground-based measurement models, and satellite-derived models are evaluated. Steps needed to create a sound, bankable solar-radiation database are described. A discussion of the use of such datasets to generate P50, P90, and P99 probabilities of exceedance is presented along with a description of the bootstrap method used to generate a larger dataset for a more robust analysis of these probabilities.

Single molecule imaging techniques overcome the averaging effects inherent in ensemble measurements and enable characterization of the enormous heterogeneity that exists in biomolecular systems. Though long the domain of a few highly specialized labs, optical imaging of single molecules in living cells is becoming a widely accessible technique. The development of commercially available microscopes, robust analysis tools, and sensitive, low-noise detectors has contributed to this dissemination, as has the ever-growing array of fluorescent proteins. The relative ease with which genetically-tagged proteins can be created and introduced into a cell has largely eliminated more cumbersome and less precise means of particle labeling. A number of special considerations apply when using genetically encoded fluorophores for single molecule experiments, however. We discuss the means by which fluorescent proteins can be transfected into living cells to obtain the low particle densities required for single molecule imaging, and consider the limitations that are placed on single molecule analysis by the fluorophore's photophysical properties. We also discuss the types of morphology and subcellular localization that make certain preparations more amenable to single particle imaging than others. Last, we discuss some common pitfalls involved in analyzing single molecule datasets, and consider some of the unique information that can be obtained using these techniques.

Publisher Summary Antibiotics were designed for therapeutic purposes such as human bacterial infection treatment and for animal disease prevention. In addition to therapeutic uses, antibiotics are also applied for nontherapeutic reasons such as growth promotion in animals. This chapter discusses a developed analytical method for quantifying antibiotics released into the environment in solid matrices including soil, sediment, and animal waste. The chapter reviews the past and current trends in the development of analytical methods for quantification of antibiotics in solid matrices. A general review of occurrence, transport, and fate of released antibiotics in solid matrices is provided for an understanding of antibiotics in the environment. Extraction of antibiotics from solid matrices is more challenging as compared to aqueous media due to the complexity of solid matrices. The antibiotic extraction in solid matrices can be done by liquid– solid extraction (LSE) method and accelerated solvent extraction (ASE) method. After the residuals of target antibiotics are extracted from the solid into the liquid phase, further sample cleanup processes are necessary to provide a robust analysis. The occurrence of antibiotics in environment including surface water, groundwater, and various solid matrices has been detected with the use of liquid chromatography (LC) combined with several ionization sources and mass analyzers.

Publisher Summary This chapter discusses the principal technique used to derive the deep subsurface distribution of electrical resistivity—namely, the magnetotelluric (MT) method. MT exploration of the Earth is evolved to the status of a mature science during the past two decades with the advent of digital instrumentation, real-time processing, and sophisticated, robust analysis techniques showing increasing promise for interpreting complex, three-dimensional (3-D) electrical structures in the Earth. Magnetellurics is the recording and study of naturally occurring electric and magnetic fields at the Earth's surface. There are several electromagnetic geophysical techniques that use transmitted energy from man-made sources. The chapter deals with the physics of these consequences and how they are used in practice to apply the MT method. Basic MT principles are applied both to synthetic and to actual continental rift data to illustrate the value and limitations of the method.