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Job satisfaction is a major driver of an individual’s subjective well-being and thus affects public health, societal prosperity, and organisations, as dissatisfied employees are less productive and more likely to change jobs. However, changing jobs does not necessarily lead to higher job satisfaction in the long run. Previous studies have shown, instead, that changing jobs only increases job satisfaction for a short period of time before it gradually falls back to similar levels as before. This phenomenon is known as the ’honeymoon–hangover’ pattern. In our study, we identify an important new moderator of the relation between job change and job satisfaction: the job–education match of job changes. Based on relative deprivation theory, we argue that job changes from being overeducated in a job lowers the likelihood of negative comparisons and thus increases the honeymoon period, lessens the hangover period, and increases long-term job satisfaction. We use data from the Socio-Economic Panel ranging from 1994–2018 and focus specifically on individual periods of employees before and after job changes (n = 134,404). Our results confirm that a change to a job that requires a matched education has a stronger and longer-lasting effect on job satisfaction, and that this effect is slightly lower for respondents born abroad.
Statistical distributions of flood peak discharge often show heavy tail behavior, that is, extreme floods are more likely to occur than would be predicted by commonly used distributions that have exponential asymptotic behavior.
This heavy tail behavior may surprise flood managers and citizens, as human intuition tends to expect light tail behavior, and the heaviness of the tails is very difficult to predict, which may lead to unnecessarily high flood damage.
Despite its high importance, the literature on the heavy tail behavior of flood distributions is rather fragmented.
In this review, we provide a coherent overview of the processes causing heavy flood tails and the implications for science and practice.
Specifically, we propose nine hypotheses on the mechanisms causing heavy tails in flood peak distributions related to processes in the atmosphere, the catchment, and the river system.
We then discuss to which extent the current knowledge supports or contradicts these hypotheses.
We also discuss the statistical conditions for the emergence of heavy tail behavior based on derived distribution theory and relate them to the hypotheses and flood generation mechanisms.
We review the degree to which the heaviness of the tails can be predicted from process knowledge and data. Finally, we recommend further research toward testing the hypotheses and improving the prediction of heavy tails.
Continuous pollen and chironomid records from Lake Emanda (65 degrees 17'N, 135 degrees 45'E) provide new insights into the Late Quaternary environmental history of the Yana Highlands (Yakutia). Larch forest with shrubs (alders, pines, birches) dominated during the deposition of the lowermost sediments suggesting its Early Weichselian [Marine Isotope Stage (MIS) 5] age. Pollen- and chironomid-based climate reconstructions suggest July temperatures (T-July) slightly lower than modern. Gradually increasing amounts of herb pollen and cold stenotherm chironomid head capsules reflect cooler and drier environments, probably during the termination of MIS 5. T-July dropped to 8 degrees C. Mostly treeless vegetation is reconstructed during MIS 3. Tundra and steppe communities dominated during MIS 2. Shrubs became common after similar to 14.5 ka BP but herb-dominated habitats remained until the onset of the Holocene. Larch forests with shrub alder and dwarf birch dominated after the Holocene onset, ca. 11.7 ka BP. Decreasing amounts of shrub pollen during the Lateglacial are assigned to the Older Dryas and Younger Dryas with T-July similar to 7.5 degrees C. T-July increased up to 13 degrees C. Shrub stone pine was present after similar to 7.5 ka BP. The vegetation has been similar to modern since ca. 5.8 ka BP. Chironomid diversity and concentration in the sediments increased towards the present day, indicating the development of richer hydrobiological communities in response to the Holocene thermal maximum.
Die Mehrheit aktueller Studien schätzt das Transformationspotenzial digitaler Technologien für Organisationen hoch ein. In Auseinandersetzung mit dieser Einschätzung entwickelt der Artikel eine konzeptionelle organisationssoziologische Perspektive auf das Verhältnis von Organisation und digitalen Technologien. Wir nutzen diese Perspektive, um den Fall des Predictive Policing in Deutschland zu betrachten und die Entscheidung zur Adaption der Technologie, ihre organisationale Situierung sowie die Rolle des Organisationstyps zu diskutieren. Unsere Perspektive führt zu einem zurückhaltenden Urteil über das Transformationspotenzial dieser digitalen Technologie, die wir daher als Reform unter anderen Reformen begreifen. Insgesamt argumentieren wir dafür, Digitalisierung stärker als bisher als heterogenen Prozess zu verstehen.
Climate change projections predict that Mediterranean-type ecosystems (MTEs) are becoming hotter and drier and that fires will become more frequent and severe.
While most plant species in these important biodiversity hotspots are adapted to hot, dry summers and recurrent fire, the Interval Squeeze framework suggests that reduced seed production (demographic shift), reduced seedling establishment after fire (post fire recruitment shift), and reduction in the time between successive fires (fire interval shift) will threaten fire killed species under climate change.
One additional potential driver of accelerated species decline, however, has not been considered so far: the decrease in pollination success observed in many ecosystems worldwide has the potential to further reduce seed accumulation and thus population persistence also in these already threatened systems.
Using the well-studied fire-killed and serotinous shrub species Banksia hookeriana as an example, we apply a new spatially implicit population simulation model to explore population dynamics under past (1988-2002) and current (2003-2017) climate conditions, deterministic and stochastic fire regimes, and alternative scenarios of pollination decline.
Overall, model results suggest that while B. hookeriana populations were stable under past climate conditions, they will not continue to persist under current (and prospective future) climate.
Negative effects of climatic changes and more frequent fires are reinforced by the measured decline in seed set leading to further reduction in the mean persistence time by 12-17%.
These findings clearly indicate that declining pollination rates can be a critical factor that increases further the pressure on the persistence of fire-killed plants.
Future research needs to investigate whether other fire-killed species are similarly threatened, and if local population extinction may be compensated by recolonization events, facilitating persistence in spatially structured meta-communities.
The radiation-sensitive field-effect transistors (RADFETs) with an oxide thickness of 400 nm are irradiated with gate voltages of 2, 4 and 6 V, and without gate voltage.
A detailed analysis of the mechanisms responsible for the creation of traps during irradiation is performed.
The creation of the traps in the oxide, near and at the silicon/silicon-dioxide (Si/SiO2) interface during irradiation is modelled very well. This modelling can also be used for other MOS transistors containing SiO2.
The behaviour of radiation traps during postirradiation annealing is analysed, and the corresponding functions for their modelling are obtained. The switching traps (STs) do not have significant influence on threshold voltage shift, and two radiation-induced trap types fit the fixed traps (FTs) very well. The fading does not depend on the positive gate voltage applied during irradiation, but it is twice lower in case there is no gate voltage.
A new dosimetric parameter, called the Golden Ratio (GR), is proposed, which represents the ratio between the threshold voltage shift after irradiation and fading after spontaneous annealing. This parameter can be useful for comparing MOS dosimeters.
Monitoring agricultural systems becomes increasingly important in the context of global challenges like climate change, biodiversity loss, population growth, and the rising demand for agricultural products. High-resolution, national-scale maps of agricultural land are needed to develop strategies for future sustainable agriculture.
However, the characterization of agricultural land cover over large areas and for multiple years remains challenging due to the locally diverse and temporally variable characteristics of cultivated land.
We here propose a workflow for generating national agricultural land cover maps on a yearly basis that accounts for varying environmental conditions. We tested the approach by mapping 24 agricultural land cover classes in Germany for the three years 2017, 2018, and 2019, in which the meteorological conditions strongly differed.
We used a random forest classifier and dense time series data from Sentinel-2 and Landsat 8 in combination with monthly Sentinel-1 composites and environmental data and evaluated the relative importance of optical, radar, and environmental data.
Our results show high overall accuracy and plausible class accuracies for the most dominant crop types across different years despite the strong inter-annual meteorological variability and the presence of drought and nondrought years. The maps show high spatial consistency and good delineation of field parcels.
Combining optical, SAR, and environmental data increased overall accuracies by 6% to 10% compared to single sensor approaches, in which optical data outperformed SAR. Overall accuracy ranged between 78% and 80%, and the mapped areas aligned well with agricultural statistics at the regional and national level.
Based on the multi-year dataset we mapped major crop sequences of cereals and leaf crops. Most crop sequences were dominated by winter cereals followed by summer cereals.
Monocultures of summer cereals were mainly revealed in the Northwest of Germany. We showcased that high spatial and thematic detail in combination with annual mapping will stimulate research on crop cycles and studies to assess the impact of environmental policies on management decisions.
Our results demonstrate the capabilities of integrated optical time series and SAR data in combination with variables describing local and seasonal environmental conditions for annual large-area crop type mapping.
Only a fast and global transformation towards decarbonization and sustainability can keep the Earth in a civilization-friendly state. As hotspots for (green) innovation and experimentation, cities could play an important role in this transition. They are also known to profit from each other's ideas, with policy and technology innovations spreading to other cities. In this way, cities can be conceptualized as nodes in a globe-spanning learning network. The dynamics of this process are important for society's response to climate change and other challenges, but remain poorly understood on a macroscopic level. In this contribution, we develop an approach to identify whether network-based complex contagion effects are a feature of sustainability policy adoption by cities, based on dose-response contagion and surrogate data models. We apply this methodology to an exemplary data set, comprising empirical data on the spreading of a public transport innovation (Bus Rapid Transit Systems) and a global inter-city connection network based on scheduled flight routes. Although our approach is not able to identify detailed mechanisms, our results point towards a contagious spreading process, and cannot be explained by either the network structure or the increase in global adoption rate alone. Further research on the role of a city's abstract "global neighborhood" regarding its policy and innovation decisions is thus both needed and promising, and may connect with research on social tipping processes. The methodology is generic, and can be used to compare the predictive power for innovation spreading of different kinds of inter-city network connections, e.g. via transport links, trade, or co-membership in political networks.
For many years scholars and politicians discuss the economic importance of the middle income class. Our article contributes to broaden the present state of research by not only examining the structure of the middle class whilst focusing on individual attributes, but by especially taking the role of gender-specific occupational characteristics and country-specific conditions into account. Based on the EU-SILC data 2020 for 17 countries, we analyze which factors affect the structure of the middle income class on the individual, on the occupational and country level. Our findings show that occupational attributes (e.g. part-time rate) prove to be highly relevant in this realm. Moreover, significant gender differences can be observed: women who work in an occupation which is mainly performed by women bear a higher risk of belonging to the lower income class as compared to men.
Ultrafast X-ray diffraction is used to quantify the transport of energy in laser-excited nanoscale gold-nickel (Au-Ni) bilayers.
Electron transport and efficient electron-phonon coupling in Ni convert the laser-deposited energy in the conduction electrons within a few picoseconds into a strong non-equilibrium between hot Ni and cold Au phonons at the bilayer interface.
Modeling of the subsequent equilibration dynamics within various two-temperature models confirms that for ultrathin Au films, the thermal transport is dominated by phonons instead of conduction electrons because of the weak electron-phonon coupling in Au.