A Comparison of a Traditional Physical Educcation Program to a Movement Exploration Program Involving Junior High School Socially Maladjusted and Emotionally Disturbed Students

Educators have a responsibility to provide a physical education program for the socially maladjusted and emotionally disturbed. Some authorities recognize the problems and special handicaps of the socially maladjusted and emotionally disturbed students and recommend experimental variations in teaching methods from traditional methodology. The purpose of this study was to determine whether or not a planned program of movement exploration would show an efficient way of improving the physical fitness and motor abilities of an experimental group of junior high school socially maladjusted and emotionally disturbed students. The experimental movement program was compared to a traditional program of physical education with a second group of socially maladjusted and emotionally disturbed junior high school students as a control

Traps of multi-level governance. Lessons from the implementation of the Water Framework Directive in Italy

During recent decades, different patterns of multi-level governance (MLG) have spread across Europe as a consequence of Europeanisation of public policies, which have increasingly adopted decentralized and participatory procedures conceived as a tool of more effective and accountable policy-making. It appears, however, that the implementation of operational designs based on MLG may be rather problematic and it does not necessarily bring to the expected performance improvements. Referring to the case of the EU Water Framework Directive (2000/60/EC), which conceives the creation of new multi-level institutional settings as a key tool for enacting a new holistic approach to water management and protection, this article explores the difficulties that the implementation of such settings has brought in Italy, despite some favorable pre-conditions existing in the country. Evidence is provided that along with institutional and agency variables, the implementation effectiveness of MLG arrangements promoted by the EU can be challenged by their inherent characteristics

A new ghost cell/level set method for moving boundary problems:application to tumor growth

In this paper, we present a ghost cell/level set method for the evolution of interfaces whose normal velocity depend upon the solutions of linear and nonlinear quasi-steady reaction-diffusion equations with curvature-dependent boundary conditions. Our technique includes a ghost cell method that accurately discretizes normal derivative jump boundary conditions without smearing jumps in the tangential derivative; a new iterative method for solving linear and nonlinear quasi-steady reaction-diffusion equations; an adaptive discretization to compute the curvature and normal vectors; and a new discrete approximation to the Heaviside function. We present numerical examples that demonstrate better than 1.5-order convergence for problems where traditional ghost cell methods either fail to converge or attain at best sub-linear accuracy. We apply our techniques to a model of tumor growth in complex, heterogeneous tissues that consists of a nonlinear nutrient equation and a pressure equation with geometry-dependent jump boundary conditions. We simulate the growth of glioblastoma (an aggressive brain tumor) into a large, 1 cm square of brain tissue that includes heterogeneous nutrient delivery and varied biomechanical characteristics (white matter, gray matter, cerebrospinal fluid, and bone), and we observe growth morphologies that are highly dependent upon the variations of the tissue characteristics—an effect observed in real tumor growth

Occurrence and mechanisms of formation of a dramatic thin layer of marine snow in a shallow Pacific fjord

Huge accumulations of diatom-dominated marine snow (aggregates \u3e0.5 mm in diameter) were observed in a layer approximately 50 cm thick persisting over a 24 h period in a shallow fjord in the San Juan Islands, Washington, USA. The layer was associated with the 22.4 σt density surface. A second thin layer of elevated phytoplankton concentration located at a density discontinuity 1.5 to 2 m above the marine snow layer occurred within a dense diatom bloom near the surface. At the end of the study period, isopycnals shoaled and the 2 layers merged. More than 80% of the diatom bloom consisted of Thalassiosira spp. (50 to 59%), Odontella longicruris (5 to 14%), Asterionellopsis glacialis, and Thalassionema nitzschioides. A much higher proportion of O. longicruris occurred in marine snow (about 53%) than among suspended cells suggesting that this species differentially aggregated. Most zooplankton avoided the mucus-rich aggregate layer. The layer of marine snow was formed when sinking aggregated diatoms reached neutral buoyancy at the 22.4 isopycnal, probably due to the presence of low salinity mucus resistant to salt exchange in the interstices of the aggregates. Rates of turbulent kinetic energy dissipation throughout the water column rarely exceeded 10-8 m2 s-3 and aggregates below the thin layer were largely detrital in composition indicating that small-scale shears due to turbulence did not erode the layer of marine snow. The accumulation of marine snow and phytoplankton in persistent, discrete layers at density discontinuities results in habitat partitioning of the pelagic zone, impacts the distribution and interactions of planktonic organisms as well as the intensity and location of biological processes in the water column, and helps maintain species diversity

Biodiversity-productivity relationships are key to nature-based climate solutions

The global impacts of biodiversity loss and climate change are interlinked, but the feedbacks between them are rarely assessed. Areas with greater tree diversity tend to be more productive, providing a greater carbon sink, and biodiversity loss could reduce these natural carbon sinks. Here, we quantify how tree and shrub species richness could affect biomass production on biome, national and regional scales. We find that GHG mitigation could help maintain tree diversity and thereby avoid a 9–39% reduction in terrestrial primary productivity across different biomes, which could otherwise occur over the next 50 years. Countries that will incur the greatest economic damages from climate change stand to benefit the most from conservation of tree diversity and primary productivity, which contribute to climate change mitigation. Our results emphasize an opportunity for a triple win for climate, biodiversity and society, and highlight that these co-benefits should be the focus of reforestation programmes

Evaluation of pediatric rheumatology telehealth satisfaction during the COVID-19 pandemic

Background: During the Coronavirus disease 2019 pandemic, ambulatory pediatric rheumatology healthcare rapidly transformed to a mainly telehealth model. However, pediatric patient and caregiver satisfaction with broadly deployed telehealth programs remains largely unknown. This study aimed to evaluate patient/caregiver satisfaction with telehealth and identify the factors associated with satisfaction in a generalizable sample of pediatric rheumatology patients. Methods: Patients with an initial telehealth video visit with a rheumatology provider between April and June 2020 were eligible. All patients/caregivers were sent a post-visit survey to assess a modified version of the Telehealth Usability Questionnaire (TUQ) and demographic and clinical characteristics. TUQ total and sub-scale (usefulness, ease of use, effectiveness, satisfaction) scores were calculated and classified as positive based on responses of agree or strongly agree on a 5-point Likert scale. Results were analyzed using standard descriptive statistics and Wilcoxon signed rank testing. The association between demographic and clinical characteristics with TUQ scores was assessed using univariate linear regression. Results: 597 patients/caregivers met inclusion criteria, and the survey response rate was 42% (n = 248). Juvenile idiopathic arthritis was the most common diagnosis (33.5%). The majority of patients were diagnosed greater than 6 months previously (72.6%) and were prescribed chronic medications (59.7%). The median total TUQ score was 4 (IQR: 4-5) with positive responses in 81% of items. Of the subscales, usefulness scores were lowest (median: 4, p \u3c 0.001). Telehealth saves time traveling was the highest median item score (median = 5, IQR: 4-5). Within subscales, items that scored significantly lower included convenience, providing for needs, seeing rheumatologist as well as in person, and being an acceptable way to receive rheumatology services (all p \u3c 0.001). There were no significant demographic or clinical features associated with TUQ scores. Conclusions: Our results suggest telehealth is a promising mode of healthcare delivery for pediatric rheumatic diseases but also identifies opportunities for improvement. Innovation and research are needed to design a telehealth system that delivers high quality and safe care that improves healthcare outcomes. Since telehealth is a rapidly emerging form of pediatric rheumatology care, improved engagement and training of patients, caregivers, and providers may help improve the patient experience in the future

Enhancement and suppression effects resulting from information structuring in sentences

Information structuring through the use of cleft sentences increases the processing efficiency of references to elements within the scope of focus. Furthermore, there is evidence that putting certain types of emphasis on individual words not only enhances their subsequent processing, but also protects these words from becoming suppressed in the wake of subsequent information, suggesting mechanisms of enhancement and suppression. In Experiment 1, we showed that clefted constructions facilitate the integration of subsequent sentences that make reference to elements within the scope of focus, and that they decrease the efficiency with reference to elements outside of the scope of focus. In Experiment 2, using an auditory text-change-detection paradigm, we showed that focus has similar effects on the strength of memory representations. These results add to the evidence for enhancement and suppression as mechanisms of sentence processing and clarify that the effects occur within sentences having a marked focus structure

Inferring signalling networks from longitudinal data using sampling based approaches in the R-package 'ddepn'

<p>Abstract</p> <p>Background</p> <p>Network inference from high-throughput data has become an important means of current analysis of biological systems. For instance, in cancer research, the functional relationships of cancer related proteins, summarised into signalling networks are of central interest for the identification of pathways that influence tumour development. Cancer cell lines can be used as model systems to study the cellular response to drug treatments in a time-resolved way. Based on these kind of data, modelling approaches for the signalling relationships are needed, that allow to generate hypotheses on potential interference points in the networks.</p> <p>Results</p> <p>We present the R-package 'ddepn' that implements our recent approach on network reconstruction from longitudinal data generated after external perturbation of network components. We extend our approach by two novel methods: a Markov Chain Monte Carlo method for sampling network structures with two edge types (activation and inhibition) and an extension of a prior model that penalises deviances from a given reference network while incorporating these two types of edges. Further, as alternative prior we include a model that learns signalling networks with the scale-free property.</p> <p>Conclusions</p> <p>The package 'ddepn' is freely available on R-Forge and CRAN <url>http://ddepn.r-forge.r-project.org</url>, <url>http://cran.r-project.org</url>. It allows to conveniently perform network inference from longitudinal high-throughput data using two different sampling based network structure search algorithms.</p

Using Markov chain Monte Carlo methods for estimating parameters with gravitational radiation data

We present a Bayesian approach to the problem of determining parameters for coalescing binary systems observed with laser interferometric detectors. By applying a Markov Chain Monte Carlo (MCMC) algorithm, specifically the Gibbs sampler, we demonstrate the potential that MCMC techniques may hold for the computation of posterior distributions of parameters of the binary system that created the gravity radiation signal. We describe the use of the Gibbs sampler method, and present examples whereby signals are detected and analyzed from within noisy data.Comment: 21 pages, 10 figure