Temperamental Constellations and School Readiness: A MultiVariate Approach

This study uses canonical correlation analyses to explore the relationship between mul- tiple predictors of school readiness (i.e., academic readiness, social readiness, and teacher-child relationship) and multiple temperamental traits using data from the second wave (age 54 months, n = 1226) of the longitudinal Study of Early Child Care and Youth Development (SECCYD; NICHD ECCRN 1993). This longitudinal study collected data on a large cohort of children and their families from birth through age 15. For academic readiness, only one temperamental constellation emerged, representing the construct of effortful control (i.e., high attentional focusing, high inhibitory con- trol). For peer interactions, two significant constellations emerged: “dysregulated” (low inhibitory control, low shyness, and high activity), and “withdrawn” (high shyness, low inhibitory control, low attentional focusing). Finally, the analyses exploring child-teacher relationships revealed two significant constellations: “highly surgent” (high activity, low inhibitory control, low shyness) and “emotionally controlled” (low anger/frustration and high inhibitory control). Results of this study form a more nuanced exploration of relationships between temperamental traits and indicators of school readiness than can be found in the extant literature, and will provide the groundwork for future research to test specific hypotheses related to the effect temperamental constellations have on children’s school readiness

Landscape characterization and biodiversity research

Rapid deforestation often produces landscape-level changes in forest characteristics and structure, including area, distribution, and forest habitat types. Changes in landscape pattern through fragmentation or aggregation of natural habitats can alter patterns of abundance for single species and entire communities. Examples of single-species effects include increased predation along the forest edge, the decline in the number of species with poor dispersal mechanisms, and the spread of exotic species that have deleterious effects (e.g., gypsy moth). A decrease in the size and number of natural habitat patches increases the probability of local extirpation and loss of diversity of native species, whereas a decline in connectivity between habitat patches can negatively affect species persistence. Thus, there is empirical justification for managing entire landscapes, not just individual habitat types, in order to insure that native plant and animal diversity is maintained. A landscape is defined as an area composed of a mosaic of interacting ecosystems, or patches, with the heterogeneity among the patches significantly affecting biotic and abiotic processes in the landscape. Patches comprising a landscape are usually composed of discrete areas of relatively homogeneous environmental conditions and must be defined in terms of the organisms of interest. A large body of theoretical work in landscape ecology has provided a wealth of methods for quantifying spatial characteristics of landscapes. Recent advances in remote sensing and geographic information systems allow these methods to be applied over large areas. The objectives of this paper are to present a brief overview of common measures of landscape characteristics, to explore the new technology available for their calculation, to provide examples of their application, and to call attention to the need for collection of spatially-explicit field data

New Criticality of 1D Fermions

One-dimensional massive quantum particles (or 1+1-dimensional random walks) with short-ranged multi-particle interactions are studied by exact renormalization group methods. With repulsive pair forces, such particles are known to scale as free fermions. With finite $m$-body forces (m = 3,4,...), a critical instability is found, indicating the transition to a fermionic bound state. These unbinding transitions represent new universality classes of interacting fermions relevant to polymer and membrane systems. Implications for massless fermions, e.g. in the Hubbard model, are also noted. (to appear in Phys. Rev. Lett.)Comment: 10 pages (latex), with 2 figures (not included

Proving termination of programs automatically with AProVE

AProVE is a system for automatic termination and complexity proofs of Java, C, Haskell, Prolog, and term rewrite systems (TRSs). To analyze programs in high-level languages, AProVE automatically converts them to TRSs. Then, a wide range of techniques is employed to prove termination and to infer complexity bounds for the resulting TRSs. The generated proofs can be exported to check their correctness using automatic certifiers. For use in software construction, we present an AProVE plug-in for the popular Eclipse software development environment

Vicinal Surfaces and the Calogero-Sutherland Model

A miscut (vicinal) crystal surface can be regarded as an array of meandering but non-crossing steps. Interactions between the steps are shown to induce a faceting transition of the surface between a homogeneous Luttinger liquid state and a low-temperature regime consisting of local step clusters in coexistence with ideal facets. This morphological transition is governed by a hitherto neglected critical line of the well-known Calogero-Sutherland model. Its exact solution yields expressions for measurable quantities that compare favorably with recent experiments on Si surfaces.Comment: 4 pages, revtex, 2 figures (.eps

Low agreement between cardiologists diagnosing left ventricular hypertrophy in children with end-stage renal disease

Background: Monitoring of the appearance of left ventricular hypertrophy (LVH) by echocardiography is currently recommended for in the management of children with End-stage renal disease (ESRD). In order to investigate the validity of this method in ESRD children, we assessed the intra- and inter-observer reproducibility of the diagnosis LVH. Methods. Echocardiographic measurements in 92 children (0-18 years) with ESRD, made by original analysists, were reassessed offline, twice, by 3 independent observers. Smallest detectable changes (SDC) were calculated for continuous measurements of diastolic interventricular septum (IVSd), Left ventricle posterior wall thickness (LVPWd), Left ventricle end-diastolic diameter (LVEDd), and Left ventricle mass index (LVMI). Cohen's kappa was calculated to assess the reproducibility of LVH defined in two different ways. LVHWT was defined as Z-value of IVSd and/or LVPWd>2 and LVHMI was defined as LVMI> 103 g/m 2 for boys and >84 g/m2 for girls. Results: The intra-observer SDCs ranged from 1.6 to 1.7 mm, 2.0 to 2.6 mm and 17.7 to 30.5 g/m2 for IVSd, LVPWd and LVMI, respectively. The inter-observer SDCs were 2.6 mm, 2.9 mm and 24.6 g/m2 for IVSd, LVPWd and LVMI, respectively. Depending on the observer, the prevalence of LVHWT and LVHMI ranged from 2 to 30% and from 8 to 25%, respectively. Kappas ranged from 0.4 to 1.0 and from 0.1 to 0.5, for intra-and inter- observer reproducibility, respectively. Conclusions: Changes in diastolic wall thickness of less than 1.6 mm or LVMI less than 17.7 g/m2 cannot be distinguished from measurement error in individual children, even when measured by the same observer. This limits the use of echocardiography to detect changes in wall thickness in children with ESRD in routine practice

Automatically proving termination and memory safety for programs with pointer arithmetic

While automated verification of imperative programs has been studied intensively, proving termination of programs with explicit pointer arithmetic fully automatically was still an open problem. To close this gap, we introduce a novel abstract domain that can track allocated memory in detail. We use it to automatically construct a symbolic execution graph that over-approximates all possible runs of a program and that can be used to prove memory safety. This graph is then transformed into an integer transition system, whose termination can be proved by standard techniques. We implemented this approach in the automated termination prover AProVE and demonstrate its capability of analyzing C programs with pointer arithmetic that existing tools cannot handle

Europe-wide air pollution modeling from 2000 to 2019 using geographically weighted regression

Previous European land-use regression (LUR) models assumed fixed linear relationships between air pollution concentrations and predictors such as traffic and land use. We evaluated whether including spatially-varying relationships could improve European LUR models by using geographically weighted regression (GWR) and random forest (RF). We built separate LUR models for each year from 2000 to 2019 for NO2, O3, PM2.5 and PM10 using annual average monitoring observations across Europe. Potential predictors included satellite retrievals, chemical transport model estimates and land-use variables. Supervised linear regression (SLR) was used to select predictors, and then GWR estimated the potentially spatially-varying coefficients. We developed multi-year models using geographically and temporally weighted regression (GTWR). Five-fold cross-validation per year showed that GWR and GTWR explained similar spatial variations in annual average concentrations (average R(2) = NO2: 0.66; O3: 0.58; PM10: 0.62; PM2.5: 0.77), which are better than SLR (average R(2) = NO2: 0.61; O3: 0.46; PM10: 0.51; PM2.5: 0.75) and RF (average R(2) = NO2: 0.64; O3: 0.53; PM10: 0.56; PM2.5: 0.67). The GTWR predictions and a previously-used method of back-extrapolating 2010 model predictions using CTM were overall highly correlated (R(2) > 0.8) for all pollutants. Including spatially-varying relationships using GWR modestly improved European air pollution annual LUR models, allowing time-varying exposure-health risk models

Anisotropic susceptibility of ferromagnetic ultrathin Co films on vicinal Cu

We measure the magnetic susceptibility of ultrathin Co films with an in-plane uniaxial magnetic anisotropy grown on a vicinal Cu substrate. Above the Curie temperature the influence of the magnetic anisotropy can be investigated by means of the parallel and transverse susceptibilities along the easy and hard axes. By comparison with a theoretical analysis of the susceptibilities we determine the isotropic exchange interaction and the magnetic anisotropy. These calculations are performed in the framework of a Heisenberg model by means of a many-body Green's function method, since collective magnetic excitations are very important in two-dimensional magnets.Comment: 7 pages, 3 figure