Father, Mother, Child? Eight Trends in Family Life for Policymakers to Keep in Mind. Summary

The family is the first context for a child’s development, and the most important. This is where children begin to develop their own identities and first experience a sense of closeness, community and security. Family is a domain where learning takes place – for all generations. In their daily interactions, children, mothers and fathers learn from and with one another. They develop empathy and a sense of responsibility, and learn to deal with conflict. Values, beliefs and norms, passed on from parents to children, evolve in the course of everyday life. Thus parents exert an enormous influence on their children’s educational opportunities and overall life chances – as research in Germany and other countries has clearly shown

Integrating Autonomous Busses as Door-to-Door and First-/Last-Mile Service into Public Transport: Findings from a Stated Choice Experiment

Autonomous busses and on-demand (OD) services have the potential to improve the public transport system. However, research on potential traffic impacts is still ongoing, mainly because of a lack of existing use cases of autonomous driving as part of public transport. The availability of revealed preference data for mode choice decisions is thus very limited. Therefore, we conducted a stated choice experiment to assess mode choice preferences with regard to use cases as the main mode of transport and as the solution for the first and last mile. We also distinguished between OD and schedule-based (sched.) services. The target population of the survey is the population of Baden-Württemberg, a state in southwestern Germany. The responses of 1,434 people were analyzed using a nested logit approach. On this basis, we established exemplary utility functions and descriptively derived recommendations for efficient forms of deploying autonomous busses in addition to already existing well-developed public transport systems. It was found that, under the given conditions, public transport pass owners without a car in their household would be the most interested in using autonomous busses. Car owners without a smartphone see less benefit. It was also shown that the recruiting method of the respondents is crucial. Those reached via social media were significantly more positive than those contacted via an online panel. Further evaluations show that autonomous busses are rated similarly to existing public transport and consequently have particularly high potential on medium distances, especially if their deployment leads to shorter access routes

The effects of spatial characteristics on car ownership and its impacts on agent-based travel demand models

The objective of this study is to investigate the role of spatial characteristics on car ownership and availability respectively in agent-based travel demand models and its affection on the model’s results. Based on Open Data we generate an automated workflow to evaluate spatial characteristics such as land use, points of interest, private vehicle network, and public transport quality. We estimate two multinomial logit models for car ownership: one considering socio-demographic characteristics only, and one considering both, socio-demographic and spatial characteristics. The models’ results are spatially evaluated and compared with statistical data. Moreover, we analyze the sensitivity of public transport quality measures on car ownership. The application of both car ownership models in the agent-based travel demand model mobiTopp to the city of Hamburg, Germany shows that integrating spatial characteristics significantly improves the model’s goodness of fit as well as its overall prediction power. Moreover, the application demonstrates that a detailed consideration of spatial characteristics in car ownership models contributes to a more realistic spatial distribution of cars. Furthermore, the study shows that i.e., public transport quality measures in car ownership models are relevant to reflect secondary mode choice effects (i.e., different mode choice sets due to change in car stock) in travel demand models

Using OpenStreetMap as a Data Source for Attractiveness in Travel Demand Models

We present a methodology to extract points of interest (POIs) data from OpenStreetMap (OSM) for application in travel demand models. We use custom taglists to identify and assign POI elements to typical activities used in travel demand models. We then compare the extracted OSM data with official sources and point out that the OSM data quality depends on the type of POI and that it generally matches the quality of official sources. It can therefore be used in travel demand models. However, we recommend that plausibility checks should be done to ensure a certain quality. Further, we present a methodology for calculating attractiveness measures for typical activities from single POIs and national trip generation guidelines. We show that the quality of these calculated measures is good enough for them to be used in travel demand models. Using our approach, therefore, allows the quick, automated, and flexible generation of attractiveness measures for travel demand models

Quality Assessment of OpenStreetMap’s Points of Interest with Large-Scale Real Data

OpenStreetMap (OSM) data are geographical data that are easy and open to access and therefore used for a large set of applications including travel demand modeling. However, often there is a limited awareness about the shortcomings of volunteered geographic information data, such as OSM. One important issue for the application in travel demand modeling is the completeness of OSM elements, particularly points of interest (POI), since it directly influences the predictions of trip distributions. This might cause unreliable model sensitivities and end up in wrong predictions leading to expensive misinterpretations of the effects of policy measures. Because of a lack of large-scale real-world data, a detailed assessment of the quality of POI from OSM has not been done yet. Therefore, in this work, we assess the quality of POI from OSM for use within travel demand models using surveyed real-world data from 49 areas in Germany. We perform a descriptive and a model-based analysis using spatial, demographic, and intrinsic indicators for two common trip purpose categories used in travel demand modeling. We show that the completeness of POI data in OSM depends on the category of POI. We further show that intrinsic indicators and indicators calculated based on data from other sources (e.g., land use or census data) are able to detect quality deficiencies of OSM data

Spectral analysis of the Forel-Ule ocean colour comparator scale

François Alphonse Forel (1890) and Willi Ule (1892) composed a colour comparator scale, with tints varying from indigo-blue to coca-cola brown, to quantify the colour of natural waters, like seas, lakes and rivers. For each measurement, the observer compares the colour of the water above a submersed white disc (Secchi disc) with the hand-held scale of pre-defined colours. The scale can be well reproduced from a simple recipe for twenty-one coloured chemical solutions and because the ease of its use, the Forel-Ule (FU) scale has been applied globally and intensively by oceanographers and limnologists from the year 1890. Indeed, the archived FU data belong to the oldest oceanographic data sets and do contain information on the changes in geobiophysical properties of natural waters during the last century. In this article we describe the optical properties of the FU-scale and its ability to cover the colours of natural waters, as observed by the human eye. The recipe of the scale and its reproduction is described. The spectral transmission of the tubes, with belonging chromaticity coordinates, is presented. The FU scale, in all its simplicity, is found to be an adequate ocean colour comparator scale. The scale is well characterized, is stable and observations are reproducible. This supports the idea that the large historic data base of FU measurements is coherent and well calibrated. Moreover, the scale can be coupled to contemporary multi-spectral observations with hand-held and satellite-based spectrometers

Ocean colour changes in the North Pacific since 1930

In this paper we present an analysis of historical ocean colour data from the North Pacific Ocean. This colour is described by the Forel-Ule colour index, a sea colour comparator scale that is composed of 21 tube colours that is routinely measured since the year 1890. The main objective of this research is to characterise colour changes of the North Pacific Ocean at a timescale of decades. Next to the seasonal colour changes, due to the yearly cycle of biological activity, this time series between 1930 and 1999 might contain information on global changes in climate conditions. From seasonal independent analyses of the long-term variations it was found that the greenest values, with mean Forel-Ule scale ((FU) ̅) of 4.1 were reached during the period of 1950-1954, with a second high ((FU) ̅ = 3) in the period 1980-1984. The bluest ocean was encountered during the years 1990-1994. The data indicate that after 1955 a remarkable long bluing took place till 1980

Schmeils botanische Wandtafeln [Material gráfico]

Contenido parcial: 1. [Tulpe] ; 11. Hunsrose (Rosa canina) 20. Häufige essbare, ungeniessbare und gftige pilze I / nach originalen von Professor E. DoerftlingSegún DNB (Deutsche National Bibliothek), 16/05/2008 se editaron en 1913-1914En la lám. 11 consta Graphisches Institut Julius Klinkhard

Disentangling the effects of evolutionary, demographic, and environmental factors influencing genetic structure of natural populations: Atlantic herring as a case study

The spatial structuring of intraspecific genetic diversity is the result of random genetic drift, natural selection, migration, mutation, and their interaction with historical processes. The contribution of each has been typically difficult to estimate, but recent advances in statistical genetics have provided valuable new investigative tools to tackle such complexity. Using a combination of such methods, we examined the roles of environment (i.e., natural selection), random genetic processes (i.e., drift), and demography and life histories (e. g., feeding migrations) on population structure of a widely distributed and abundant marine pelagic fish of economic importance, Atlantic herring (Clupea harengus). Individuals were collected during peak spawning time from 19 spawning locations spanning the region from the western North Sea to the eastern Baltic Sea (N = 1859, eight microsatellite loci). We carried out separate analyses of neutral and selected genetic variation, which allowed us to establish that the two most important factors affecting population structure were selection due to salinity at spawning sites and feeding migrations. The genetic signal left by the demographic history of herring, on the other hand, seems to have been largely eroded, which is not surprising given the large reproductive potential and presumed enormous local effective population sizes of pelagic fish that constrain the effect of stochastic processes. The approach we used can in principle be applied to any abundant and widely distributed aquatic or terrestrial species.</p