Human Capital Investments in Children: A Comparative Analysis of the Role of Parent-Child Shared Time in Selected Countries

Parents invest in their children's human capital in several ways. We investigate the extent to which the levels and composition of parent-child time varies across countries with different welfare regimes: Finland, Germany and the United States. We test the hypothesis of parent-child time as a form of human capital investment in children using a propensity score treatment effects approach that accounts for the possible endogenous nature of time use and human capital investment. Result: There is considerable evidence of welfare regime effects on parent-child shared time. Our results provide mixed support for the hypothesis that non-care related parent-child time is human capital enriching. The strongest support is found in the case of leisure time and eating time.parent-child time, comparative research, welfare regimes, Finland, Germany, USA, treatment effects, propensity score matching

Cu nuclear magnetic resonance study of charge and spin stripe order in La1.875_{1.875}Ba0.125_{0.125}CuO4_4

We present a Cu nuclear magnetic/quadrupole resonance study of the charge stripe ordered phase of LBCO, with detection of previously unobserved ('wiped-out') signal. We show that spin-spin and spin-lattice relaxation rates are strongly enhanced in the charge ordered phase, explaining the apparent signal decrease in earlier investigations. The enhancement is caused by magnetic, rather than charge fluctuations, conclusively confirming the long-suspected assumption that spin fluctuations are responsible for the wipeout effect. Observation of the full Cu signal enables insight into the spin and charge dynamics of the stripe-ordered phase, and measurements in external magnetic fields provide information on the nature and suppression of spin fluctuations associated with charge order. We find glassy spin dynamics, in agreement with previous work, and incommensurate static charge order with charge modulation amplitude similar to other cuprate compounds, suggesting that the amplitude of charge stripes is universal in the cuprates.Comment: 7 pages, 5 figure

Heat pumping with optically driven excitons

We present a theoretical study showing that an optically driven excitonic two-level system in a solid state environment acts as a heat pump by means of repeated phonon emission or absorption events. We derive a master equation for the combined phonon bath and two-level system dynamics and analyze the direction and rate of energy transfer as a function of the externally accessible driving parameters. We discover that if the driving laser is detuned from the exciton transition, cooling the phonon environment becomes possible

Prospective cognitions in anxiety and depression: Replication and methodological extension

The present study presents a replication and methodological extension of MacLeod, Tata, Kentish, and Jacobsen (1997) with a nonclinical sample, using future-directed imagery to assess prospective cognitions. Results showed that only anxiety (but not depression) was related to enhanced imagery for future negative events. Both anxiety and depression showed significant zero-order correlations with reduced imagery for future positive events. However, when the overlap between anxiety and depression was controlled for, only depression (but not anxiety) showed a unique association with reduced imagery for positive events. Implications of these findings for cognitive models of anxiety and depression are discussed

Learning Dictionaries with Bounded Self-Coherence

Sparse coding in learned dictionaries has been established as a successful approach for signal denoising, source separation and solving inverse problems in general. A dictionary learning method adapts an initial dictionary to a particular signal class by iteratively computing an approximate factorization of a training data matrix into a dictionary and a sparse coding matrix. The learned dictionary is characterized by two properties: the coherence of the dictionary to observations of the signal class, and the self-coherence of the dictionary atoms. A high coherence to the signal class enables the sparse coding of signal observations with a small approximation error, while a low self-coherence of the atoms guarantees atom recovery and a more rapid residual error decay rate for the sparse coding algorithm. The two goals of high signal coherence and low self-coherence are typically in conflict, therefore one seeks a trade-off between them, depending on the application. We present a dictionary learning method with an effective control over the self-coherence of the trained dictionary, enabling a trade-off between maximizing the sparsity of codings and approximating an equiangular tight frame.Comment: 4 pages, 2 figures; IEEE Signal Processing Letters, vol. 19, no. 12, 201

Data Structures for Halfplane Proximity Queries and Incremental Voronoi Diagrams

We consider preprocessing a set $S$ of $n$ points in convex position in the plane into a data structure supporting queries of the following form: given a point $q$ and a directed line $\ell$ in the plane, report the point of $S$ that is farthest from (or, alternatively, nearest to) the point $q$ among all points to the left of line $\ell$. We present two data structures for this problem. The first data structure uses $O(n^{1+\varepsilon})$ space and preprocessing time, and answers queries in $O(2^{1/\varepsilon} \log n)$ time, for any $0 < \varepsilon < 1$. The second data structure uses $O(n \log^3 n)$ space and polynomial preprocessing time, and answers queries in $O(\log n)$ time. These are the first solutions to the problem with $O(\log n)$ query time and $o(n^2)$ space. The second data structure uses a new representation of nearest- and farthest-point Voronoi diagrams of points in convex position. This representation supports the insertion of new points in clockwise order using only $O(\log n)$ amortized pointer changes, in addition to $O(\log n)$-time point-location queries, even though every such update may make $\Theta(n)$ combinatorial changes to the Voronoi diagram. This data structure is the first demonstration that deterministically and incrementally constructed Voronoi diagrams can be maintained in $o(n)$ amortized pointer changes per operation while keeping $O(\log n)$-time point-location queries.Comment: 17 pages, 6 figures. Various small improvements. To appear in Algorithmic