A Qualitative Study of the Assistive Technology Decision-Making Process in Four Pennsylvania School Districts

The purpose of this study was to gain an understanding of the Assistive Technology decision making process at four regional school districts in Pennsylvania. A qualitative case study research method involving the triangulation of data sources was implemented to collect and analyze data. Through an analysis of the data, three major topics emerged that will be addressed in the body of this paper: (a) the procedure for determining assistive technology needs and the dynamics of the decision-making process, b) the cohesiveness of Special Education and General Education programs, and c) major concerns that impact the delivery of assistive technology services.

Robust trends of landscape dynamics in the Arctic Lena Delta with temporally dense Landsat time-series stacks, with links to GeoTIFFs

Arctic permafrost landscapes are among the most vulnerable and dynamic landscapes globally, but due to their extent and remoteness most of the landscape changes remain unnoticed. In order to detect disturbances in these areas we developed an automated processing chain for the calculation and analysis of robust trends of key land surface indicators based on the full record of available Landsat TM, ETM +, and OLI data. The methodology was applied to the ~ 29,000 km**2 Lena Delta in Northeast Siberia, where robust trend parameters (slope, confidence intervals of the slope, and intercept) were calculated for Tasseled Cap Greenness, Wetness and Brightness, NDVI, and NDWI, and NDMI based on 204 Landsat scenes for the observation period between 1999 and 2014. The resulting datasets revealed regional greening trends within the Lena Delta with several localized hot-spots of change, particularly in the vicinity of the main river channels. With a 30-m spatial resolution various permafrost-thaw related processes and disturbances, such as thermokarst lake expansion and drainage, fluvial erosion, and coastal changes were detected within the Lena Delta region, many of which have not been noticed or described before. Such hotspots of permafrost change exhibit significantly different trend parameters compared to non-disturbed areas. The processed dataset, which is made freely available through the data archive PANGAEA, will be a useful resource for further process specific analysis by researchers and land managers. With the high level of automation and the use of the freely available Landsat archive data, the workflow is scalable and transferrable to other regions, which should enable the comparison of land surface changes in different permafrost affected regions and help to understand and quantify permafrost landscape dynamics.

PEECE II mesocosm experiment: Dynamics of extracellular enzyme activities in seawater under changed atmospheric pCO2, 2011

As part of the PeECE II mesocosm project, we investigated the effects of pCO2 levels on the initial step of heterotrophic carbon cycling in the surface ocean. The activities of microbial extracellular enzymes hydrolyzing 4 polysaccharides were measured during the development of a natural phytoplankton bloom under pCO2 conditions representing glacial (190 µatm) and future (750 µatm) atmospheric pCO2. We observed that (1) chondroitin hydrolysis was variable throughout the pre-, early- and late-bloom phases, (2) fucoidanase activity was measurable only in the glacial mesocosm as the bloom developed, (3) laminarinase activity was low and constant, and (4) xylanase activity declined as the bloom progressed. Concurrent measurements of microbial community composition, using denaturing-gradient gel electrophoresis (DGGE), showed that the 2 mesocosms diverged temporally, and from one another, especially in the late-bloom phase. Enzyme activities correlated with bloom phase and pCO2, suggesting functional as well as compositional changes in microbial communities in the different pCO2 environments. These changes, however, may be a response to temporal changes in the development of phytoplankton communities that differed with the pCO2 environment. We hypothesize that the phytoplankton communities produced dissolved organic carbon (DOC) differing in composition, a hypothesis supported by changing amino acid composition of the DOC, and that enzyme activities responded to changes in substrates. Enzyme activities observed under different pCO2 conditions likely reflect both genetic and population-level responses to changes occurring among multiple components of the microbial loop.

Effects of ocean acidification on population dynamics and community structure of crustose coralline algae

Calcification and growth of crustose coralline algae (CCA) are affected by elevated seawater pCO2 and associated changes in carbonate chemistry. However, the effects of ocean acidification (OA) on population and community-level responses of CCA have barely been investigated. We explored changes in community structure and population dynamics (size structure and reproduction) of CCA in response to OA. Recruited from an experimental flow-through system, CCA settled onto the walls of plastic aquaria and developed under exposure to one of three pCO2 treatments (control [present day, 389±6 ppm CO2], medium [753±11 ppm], and high [1267±19 ppm]). Elevated pCO2 reduced total CCA abundance and affected community structure, in particular the density of the dominant species Pneophyllum sp. and Porolithon onkodes. Meanwhile, the relative abundance of P. onkodes declined from 24% under control CO2 to 8.3% in high CO2 (65% change), while the relative abundance of Pneophyllum sp. remained constant. Population size structure of P. onkodes differed significantly across treatments, with fewer larger individuals under high CO2. In contrast, the population size structure and number of reproductive structures (conceptacles) per crust of Pneophyllum sp. was similar across treatments. The difference in the magnitude of the response of species abundance and population size structure between species may have the potential to induce species composition changes in the future. These results demonstrate that the impacts of OA on key coral reef builders go beyond declines in calcification and growth, and suggest important changes to aspects of population dynamics and community ecology.

Long-term dynamics of adaptive evolution in a globally important coccolithophore to ocean acidification

Recent evolution experiments have revealed that marine phytoplankton may adapt to global change, for example to ocean warming or acidification. Long-term adaptation to novel environments is a dynamic process and phenotypic change can take place thousands of generations after exposure to novel conditions. Using the longest evolution experiment performed in any marine species to date (4 yrs, = 2100 generations), we show that in the coccolithophore Emiliania huxleyi, long-term adaptation to ocean acidification is complex and initial phenotypic responses may revert for important traits. While fitness increased continuously, calcification was restored within the first 500 generations but later reduced in response to selection, enhancing physiological declines of calcification in response to ocean acidification. Interestingly, calcification was not constitutively reduced but revealed rates similar to control treatments when transferred back to present-day CO2 conditions. Growth rate increased with time in controls and adaptation treatments, although the effect size of adaptation assessed through reciprocal assay experiments varied. Several trait changes were associated with selection for higher cell division rates under laboratory conditions, such as reduced cell size and lower particulate organic carbon content per cell. Our results show that phytoplankton may evolve phenotypic plasticity that can affect biogeochemically important traits, such as calcification, in an unforeseen way under future ocean conditions.

From foot-draggers to strategic counter-partners : the dynamics of U.S. and Chinese policies for tackling climate change

As can been seen from the U.S.'s non-ratification of the Kyoto Protocol, together with the negotiations toward the post-Kyoto Protocol framework, the U.S. and China have been quarrelling over their responsibilities and have contradicted one another over the introduction of compulsory domestic greenhouse gases emission reduction targets. Therefore, for a long time, it has been argued that the controversy between the two countries has hindered the process of forging an international agreement to deal with climate change. On the other hand, Sino-U.S. bilateral cooperation on climate change has significantly increased in recent years in summit talks and their Strategic & Economic Dialogue (S&ED), especially after the 15th Conference of Parties (COP) of the United Nations Framework Convention on Climate Change (UNFCCC) in Copenhagen, one of whose aims was to facilitate positive negotiations for the post-Kyoto Protocol agreement. Analyzing this in the light of recent developments, we find that the U.S. and China have tended to address climate change and related issues from a pluralistic viewpoint and approach, by regarding the achievement of bilateral cooperation and global agreements as their common strategic objective.

Interactive Graphic Simulation: An Advanced Methodology to Improve the Teaching-Learning Process in Nuclear Engineering Education and Training

Nowadays, computer simulators are becoming basic tools for education and training in many engineering fields. In the nuclear industry, the role of simulation for training of operators of nuclear power plants is also recognized of the utmost relevance. As an example, the International Atomic Energy Agency sponsors the development of nuclear reactor simulators for education, and arranges the supply of such simulation programs. Aware of this, in 2008 Gas Natural Fenosa, a Spanish gas and electric utility that owns and operate nuclear power plants and promotes university education in the nuclear technology field, provided the Department of Nuclear Engineering of Universidad Politécnica de Madrid with the Interactive Graphic Simulator (IGS) of “José Cabrera” (Zorita) nuclear power plant, an industrial facility whose commercial operation ceased definitively in April 2006. It is a state-of-the-art full-scope real-time simulator that was used for training and qualification of the operators of the plant control room, as well as to understand and analyses the plant dynamics, and to develop, qualify and validate its emergency operating procedures.

Influence of local wind speed and direction on wind power dynamics - Application to offshore very short-term forecasting

Wind power time series usually show complex dynamics mainly due to non-linearities related to the wind physics and the power transformation process in wind farms. This article provides an approach to the incorporation of observed local variables (wind speed and direction) to model some of these effects by means of statistical models. To this end, a benchmarking between two different families of varying-coefficient models (regime-switching and conditional parametric models) is carried out. The case of the offshore wind farm of Horns Rev in Denmark has been considered. The analysis is focused on one-step ahead forecasting and a time series resolution of 10 min. It has been found that the local wind direction contributes to model some features of the prevailing winds, such as the impact of the wind direction on the wind variability, whereas the non-linearities related to the power transformation process can be introduced by considering the local wind speed. In both cases, conditional parametric models showed a better performance than the one achieved by the regime-switching strategy. The results attained reinforce the idea that each explanatory variable allows the modelling of different underlying effects in the dynamics of wind power time series.

Brain dynamics of mild cognitive impairment during face encoding

Brain oscillations are closely correlated with human information processing and fundamental aspects of cognition. Previous literature shows that due to the relation between brain oscillations and memory processes, spectral dynamics during such tasks are good candidates to study and characterize memory related pathologies. Mild cognitive impairment (MCI), defined as a clinical condition characterized by memory impairment and/ or deterioration of additional cognitive domains, is considered a preliminary stage in the dementia process. In consequence, the study of its brain patterns could help to achieve an early diagnosis of Alzheimer Disease.

Dynamics of thermal ignition of spray flames in mixing layers

Conditions are identified under which analyses of laminar mixing layers can shed light on aspects of turbulent spray combustion. With this in mind, laminar spray-combustion models are formulated for both non-premixed and partially premixed systems. The laminar mixing layer separating a hot-air stream from a monodisperse spray carried by either an inert gas or air is investigated numerically and analytically in an effort to increase understanding of the ignition process leading to stabilization of high-speed spray combustion. The problem is formulated in an Eulerian framework, with the conservation equations written in the boundary-layer approximation and with a one-step Arrhenius model adopted for the chemistry description. The numerical integrations unveil two different types of ignition behaviour depending on the fuel availability in the reaction kernel, which in turn depends on the rates of droplet vaporization and fuel-vapour diffusion. When sufficient fuel is available near the hot boundary, as occurs when the thermochemical properties of heptane are employed for the fuel in the integrations, combustion is established through a precipitous temperature increase at a well-defined thermal-runaway location, a phenomenon that is amenable to a theoretical analysis based on activation-energy asymptotics, presented here, following earlier ideas developed in describing unsteady gaseous ignition in mixing layers. By way of contrast, when the amount of fuel vapour reaching the hot boundary is small, as is observed in the computations employing the thermochemical properties of methanol, the incipient chemical reaction gives rise to a slowly developing lean deflagration that consumes the available fuel as it propagates across the mixing layer towards the spray. The flame structure that develops downstream from the ignition point depends on the fuel considered and also on the spray carrier gas, with fuel sprays carried by air displaying either a lean deflagration bounding a region of distributed reaction or a distinct double-flame structure with a rich premixed flame on the spray side and a diffusion flame on the air side. Results are calculated for the distributions of mixture fraction and scalar dissipation rate across the mixing layer that reveal complexities that serve to identify differences between spray-flamelet and gaseous-flamelet problems.

Mapping Dynamics into Graphs. The Visibility Algorithm

Si no tenemos en cuenta posibles procesos subyacentes con significado físico, químico, económico, etc., podemos considerar una serie temporal como un mero conjunto ordenado de valores y jugar con él algún inocente juego matemático como transformar dicho conjunto en otro objeto con la ayuda de una operación matemática para ver qué sucede: qué propiedades del conjunto original se conservan, cuáles se transforman y cómo, qué podemos decir de alguna de las dos representaciones matemáticas del objeto con sólo atender a la otra... Este ejercicio sería de cierto interés matemático por sí solo. Ocurre, además, que las series temporales son un método universal de extraer información de sistemas dinámicos en cualquier campo de la ciencia. Esto hace ganar un inesperado interés práctico al juego matemático anteriormente descrito, ya que abre la posibilidad de analizar las series temporales (vistas ahora como evolución temporal de procesos dinámicos) desde una nueva perspectiva. Hemos para esto de asumir la hipótesis de que la información codificada en la serie original se conserva de algún modo en la transformación (al menos una parte de ella). El interés resulta completo cuando la nueva representación del objeto pertencece a un campo de la matemáticas relativamente maduro, en el cual la información codificada en dicha representación puede ser descodificada y procesada de manera efectiva. ABSTRACT Disregarding any underlying process (and therefore any physical, chemical, economical or whichever meaning of its mere numeric values), we can consider a time series just as an ordered set of values and play the naive mathematical game of turning this set into a different mathematical object with the aids of an abstract mapping, and see what happens: which properties of the original set are conserved, which are transformed and how, what can we say about one of the mathematical representations just by looking at the other... This exercise is of mathematical interest by itself. In addition, it turns out that time series or signals is a universal method of extracting information from dynamical systems in any field of science. Therefore, the preceding mathematical game gains some unexpected practical interest as it opens the possibility of analyzing a time series (i.e. the outcome of a dynamical process) from an alternative angle. Of course, the information stored in the original time series should be somehow conserved in the mapping. The motivation is completed when the new representation belongs to a relatively mature mathematical field, where information encoded in such a representation can be effectively disentangled and processed. This is, in a nutshell, a first motivation to map time series into networks.

The dynamics of axisymmetric slender liquid bridges between unequal disks

n this paper the influence of an axial microgravity on the dynamic stability of axisymmetric slender liquid bridges between unequal disks is numerically studied by using a one-dimensional theory. The breaking of such liquid configurations is analyzed and the dependence of some overall characteristics of the breaking process on the value of axial microgravity, the geometry and the volume of the liquid bridge, as well as stability limits are obtained.

Numerical and experimental study of the dynamics of axisymmetric slender liquid bridges

A one-dimensional inviscid slice model has been used to study numerically the influence of axial microgravity on the breaking of liquid bridges having a volume close to that of gravitationless minimum volume stability limit. Equilibrium shapes and stability limits have been obtained as well as the dependence of the volume of the two drops formed after breaking on both the length and the volume of the liquid bridge. The breaking process has also been studied experimentally. Good agreement has been found between theory and experiment for neutrally buoyant systems

A Special Perturbation Method in Orbital Dynamics

Bead models are used in dynamical simulation of tethers. These models discretize a cable using beads distributed along its length. The time evolution is obtained nu- merically. Typically the number of particles ranges between 5 and 50, depending on the required accuracy. Sometimes the simulation is extended over long periods (several years). The complex interactions between the cable and its spatial environment require to optimize the propagators —both in runtime and precisión that constitute the central core of the process. The special perturbation method treated on this article conjugates simpleness of computer implementation, speediness and precision, and is capable to propagate the orbit of whichever material particle. The paper describes the evolution of some orbital elements, which are constants in a non-perturbed problem, but which evolve in the time scale imposed by the perturbation. It can be used with any kind of orbit and it is free of sin- gularities related to small inclination and/or small eccentricity. The use of Euler parameters makes it robust.

Modeling GHG emissions, N and C dynamics in Spanish agricultural soils.

To date, only few initiatives have been carried out in Spain in order to use mathematical models (e.g. DNDC, DayCent, FASSET y SIMSNIC) to estimate nitrogen (N) and carbon (C) dynamics as well as greenhouse gases (GHG) in Spanish agrosystems. Modeling at this level may allow to gain insight on both the complex relationships between biological and physicochemical processes, controlling the processes leading to GHG production and consumption in soils (e.g. nitrification, denitrification, decomposing, etc.), and the interactions between C and N cycles within the different components of the continuum plant-soil-environment. Additionally, these models can simulate the processes behind production, consumition and transport of GHG (e.g. nitrous oxide, N2O, and carbon dioxide, CO2) in the short and medium term and at different scales. Other sources of potential pollution from soils can be identified and quantified using these process-based models (e.g. NO3 y NH3).