Grandparents’ involvement in their adult children’s everyday family life seems to have increased, especially in relation to care arrangements around grandchildren (Arber & Timonen 2012; May et al., 2012; Cantillon et al., 2021). This is the case also in Sweden, despite extensive public welfare provision of childcare (Hank & Buber, 2009; Björnberg & Ekbrand, 2008). This “new army of pro

The CO2 Human Emissions project has generated realistic high-resolution 9 km global simulations for atmospheric carbon tracers referred to as nature runs to foster carbon-cycle research applications with current and planned satellite missions, as well as the surge of in situ observations. Realistic atmospheric CO2, CH4 and CO fields can provide a reference for assessing the impact of proposed desi

During the summer of 2018, a widespread drought developed over Northern and Central Europe. The increase in temperature and the reduction of soil moisture have influenced carbon dioxide (CO 2) exchange between the atmosphere and terrestrial ecosystems in various ways, such as a reduction of photosynthesis, changes in ecosystem respiration, or allowing more frequent fires. In this study, we charact

Metrics of temporal light artefacts (TLAs) are tools meant to quantify the magnitude of the impact of temporal modulated light generated by light sources. However, as lighting systems are becoming more and more complex, just assigning a TLA metrics to a light source is not necessarily an easy task. For example, a luminaire containing two drivers operating on slightly different frequencies could ge

Combining neo-institutionalism, actor network theory, and Gabriel Tarde’s sociology, Czarniawska considers the key driver of organizational change to be imitation but an imitation that rests on translation. Organizations emulate one another by translating fashionable ideas according to their understanding, traditions, needs, and means. As translation in this tradition always entails a transformati

Adjectives that are used to describe sensory experiences are often used to express more than one modality. The adjective sweet, for instance, may primarily be associated with taste (i.e., taste is the dominant modality of sweet), but it can also be used for smell, sound or sight, and possibly even for touch. It has also been shown that some sensory modalities combine more easily than others. Many

Motivated by the random covering problem and the study of Dirichlet uniform approximable numbers, we investigate the uniform random covering problem. Precisely, consider an i.i.d. sequence ω = (ωn)n≥1 uniformly distributed on the unit circle &x1D54B; and a sequence (rn)n≥1 of positive real numbers with limit 0. We investigate the size of the random set U(ω) := {y ∈ &x1D54B;: ∀N ≫ 1, ∃n ≤ N

I detta paper behandlas temporalitet utifrån begreppets historiekulturella innebörder. Skolans historieämne rymmer ett spänningsfält av olika typer av temporalitet. Historiestuderande förväntas lära sig om den kronologiska, framåtsyftande historien som indirekt förklarar vår egen tid. Samtidigt återspeglar skolans kursplaner sin samtids behov av minne och orientering. Historia fyller med andra ord

Methods to promote professionals’ self-knowledge and affinity for therapeutic alliances may be valuable to facilitate clients’ journeys towards recovery. This article illuminates how the use of creative art diaries can support the development of generic professional competencies in therapeutic work with clients. The methods entailed the construction of a telling case. This case was based on an aut

The statistical sparse jump model, a recently developed, robust and interpretable regime-switching model, is used to analyze the factors driving the return dynamics of the largest cryptocurrencies. This method simultaneously incorporates feature selection, parameter estimation, and state classification. We consider a wide range of candidate features, including cryptocurrency, sentiment, and financThe statistical sparse jump model, a recently developed, robust and interpretable regime-switching model, is used to analyze the factors driving the return dynamics of the largest cryptocurrencies. This method simultaneously incorporates feature selection, parameter estimation, and state classification. A wide range of candidate features is considered, including cryptocurrency, sentiment, and fina

We consider the statistical sparse jump model, a recently developed, robust and interpretable regime switching model, to identify features that drive the return dynamics of the largest cryptocurrencies. The approach simultaneously performs feature selection, parameter estimation, and state classification. Our large number of candidate features comprises cryptocurrency, sentiment, and financial mar