¿Barreras invisibles? Actitudes de los estudiantes universitarios ante sus compañeros con discapacidad

El presente trabajo analiza los conocimientos, opiniones y actitudes de los estudiantes universitarios sobre sus compañeros con discapacidad. La integración educativa y social de estos estudiantes es objeto de preocupación y estudio en todo el sistema educativo español, incluida la enseñanza superior en la que 21.942 universitarios con discapacidad se encontraban matriculados en el curso 2013-2014. El estudio se realiza en el marco de dos Proyectos de Innovación Educativa[1] de la Universidad de Málaga en los que se examinaron las actitudes del personal docente e investigador, el alumnado en general y el alumnado con discapacidad de esta institución. En este artículo se recogen las perspectivas de los estudiantes sin discapacidad, necesarias para medir el grado de aceptación dentro de las aulas universitarias. Se empleó una encuesta suministrada mediante correo electrónico a la totalidad de la población de estudiantes de la Universidad de Málaga (N= 32.464). El tamaño de la muestra fue de 620 estudiantes, por lo que trabajamos con un margen de error del 3,9% para la estimación de los porcentajes con un nivel de confianza del 95%. Los datos, analizados mediante análisis estadístico, visibilizan la importancia de un elevado grado de información y conocimiento así como de una experiencia directa con la discapacidad. Ambas circunstancias se traducen en actitudes más positivas y favorables. Tan solo el 20% de los alumnos manifestó haber recibido en alguna ocasión cualquier tipo de información sobre este asunto por parte de la Universidad; no obstante, la mayoría valora positivamente la presencia de alumnos con discapacidad en la Universidad, la posibilidad de contar ellos como compañeros de clase y el enriquecimiento que supone esta convivencia dentro del aula. Se discuten posibles acciones para mejorar las actitudes hacia los estudiantes con discapacidad. Además, se plantea incluir una perspectiva que promueva el empoderamiento de estos estudiantes. [1] PIE 10-135 y PIE 13-103.

Modeling energy consumption in error-prone IEEE 802.11-based wireless ad-hoc networks

In the IEEE 802.11 MAC layer protocol, there are different trade-off points between the number of nodes competing for the medium and the network capacity provided to them. There is also a trade-off between the wireless channel condition during the transmission period and the energy consumption of the nodes. Current approaches at modeling energy consumption in 802.11 based networks do not consider the influence of the channel condition on all types of frames (control and data) in the WLAN. Nor do they consider the effect on the different MAC and PHY schemes that can occur in 802.11 networks. In this paper, we investigate energy consumption corresponding to the number of competing nodes in IEEE 802.11's MAC and PHY layers in error-prone wireless channel conditions, and present a new energy consumption model. Analysis of the power consumed by each type of MAC and PHY over different bit error rates shows that the parameters in these layers play a critical role in determining the overall energy consumption of the ad-hoc network. The goal of this research is not only to compare the energy consumption using exact formulae in saturated IEEE 802.11-based DCF networks under varying numbers of competing nodes, but also, as the results show, to demonstrate that channel errors have a significant impact on the energy consumption.

Prediction- and simulation-error based perceptron training: Solution space analysis and a novel combined training scheme

Previous papers have noted the difficulty in obtaining neural models which are stable under simulation when trained using prediction-error-based methods. Here the differences between series-parallel and parallel identification structures for training neural models are investigated. The effect of the error surface shape on training convergence and simulation performance is analysed using a standard algorithm operating in both training modes. A combined series-parallel/parallel training scheme is proposed, aiming to provide a more effective means of obtaining accurate neural simulation models. Simulation examples show the combined scheme is advantageous in circumstances where the solution space is known or suspected to be complex. (c) 2006 Elsevier B.V. All rights reserved.

Rapid, quantitative analysis of ppm/ppb nicotine using surface-enhanced Raman scattering from polymer-encapsulated Ag nanoparticles (gel-colls)

Rapid, quantitative SERS analysis of nicotine at ppm/ppb levels has been carried out using stable and inexpensive polymer-encapsulated Ag nanoparticles (gel-colls). The strongest nicotine band (1030 cm(-1)) was measured against d(5)-pyridine internal standard (974 cm(-1)) which was introduced during preparation of the stock gel-colls. Calibration plots of I-nic/I-pyr against the concentration of nicotine were non-linear but plotting I-nic/I-pyr against [nicotine](x) (x = 0.6-0.75, depending on the exact experimental conditions) gave linear calibrations over the range (0.1-10 ppm) with R-2 typically ca. 0.998. The RMS prediction error was found to be 0.10 ppm when the gel-colls were used for quantitative determination of unknown nicotine samples in 1-5 ppm level. The main advantages of the method are that the gel-colls constitute a highly stable and reproducible SERS medium that allows high throughput (50 sample h(-1)) measurements.

Non-stationary variogram models for geostatistical sampling optimisation: An empirical investigation using elevation data

A problem with use of the geostatistical Kriging error for optimal sampling design is that the design does not adapt locally to the character of spatial variation. This is because a stationary variogram or covariance function is a parameter of the geostatistical model. The objective of this paper was to investigate the utility of non-stationary geostatistics for optimal sampling design. First, a contour data set of Wiltshire was split into 25 equal sub-regions and a local variogram was predicted for each. These variograms were fitted with models and the coefficients used in Kriging to select optimal sample spacings for each sub-region. Large differences existed between the designs for the whole region (based on the global variogram) and for the sub-regions (based on the local variograms). Second, a segmentation approach was used to divide a digital terrain model into separate segments. Segment-based variograms were predicted and fitted with models. Optimal sample spacings were then determined for the whole region and for the sub-regions. It was demonstrated that the global design was inadequate, grossly over-sampling some segments while under-sampling others.

Complex PTSD, interpersonal trauma and relational consequences: Findings from a treatment-receiving Northern Irish sample

Background:
The relationship between PTSD and complex PTSD remains unclear. As well as further addressing this issue, the current study aimed to assess the degree to which DESNOS (complex PTSD) was related to interpersonal trauma and had relational consequences.

Methods:
Eighty one treatment-receiving participants with a history of exposure to the ‘Troubles’ in Northern Ireland, were assessed on various forms of interpersonal trauma, including exposure to the Troubles, and measures of interpersonal and community connectedness.

Results:
DESNOS symptom severity was related to childhood sexual abuse and perceived psychological impact of Troubles-related exposure. A lifetime diagnosis of DESNOS was related to childhood Troubles-related experiences, while a current diagnosis of DESNOS was associated with childhood emotional neglect. PTSD avoidance predicted current DESNOS diagnosis and severity. Feeling emotionally disconnected from family and friends (i.e., interpersonal disconnectedness) was related to all three indices of DESNOS (i.e., lifetime diagnosis, current diagnosis and current symptom severity).

Limitations:
Sample characteristics (i.e., treatment-receiving) and size may limit the generalizability of findings.

Conclusions:
Complex PTSD is associated with PTSD but when present should be considered a superordinate diagnosis.