Memorability as a measure of processing: a unit analysis of prose and list learning.

The percentage of subjects recalling each unit in a list or prose passage is considered as a dependent measure. When the same units are recalled in different tasks, processing is assumed to be the same; when different units are recalled, processing is assumed to be different. Two collections of memory tasks are presented, one for lists and one for prose. The relations found in these two collections are supported by an extensive reanalysis of the existing prose memory literature. The same set of words were learned by 13 different groups of subjects under 13 different conditions. Included were intentional free-recall tasks, incidental free recall following lexical decision, and incidental free recall following ratings of orthographic distinctiveness and emotionality. Although the nine free-recall tasks varied widely with regard to the amount of recall, the relative probability of recall for the words was very similar among the tasks. Imagery encoding and recognition produced relative probabilities of recall that were different from each other and from the free-recall tasks. Similar results were obtained with a prose passage. A story was learned by 13 different groups of subjects under 13 different conditions. Eight free-recall tasks, which varied with respect to incidental or intentional learning, retention interval, and the age of the subjects, produced similar relative probabilities of recall, whereas recognition and prompted recall produced relative probabilities of recall that were different from each other and from the free-recall tasks. A review of the prose literature was undertaken to test the generality of these results. Analysis of variance is the most common statistical procedure in this literature. If the relative probability of recall of units varied across conditions, a units by condition interaction would be expected. For the 12 studies that manipulated retention interval, an average of 21% of the variance was accounted for by the main effect of retention interval, 17% by the main effect of units, and only 2% by the retention interval by units interaction. Similarly, for the 12 studies that varied the age of the subjects, 6% of the variance was accounted for by the main effect of age, 32% by the main effect of units, and only 1% by the interaction of age by units.(ABSTRACT TRUNCATED AT 400 WORDS)

Impact of tumor board recommendations on treatment outcome for locally advanced head and neck cancer

Background/Aims: To identify physician selection factors in the treatment of locally advanced head and neck cancer and how treatment outcome is affected by Tumor Board recommendations. Methods: A retrospective analysis of 213 patients treated for locally advanced head and neck cancer in a single institution was performed. All treatments followed Tumor Board recommendations: 115 patients had chemotherapy and radiation, and 98 patients received postoperative radiation. Patient characteristics, treatment toxicity, locoregional control and survival between these two treat- ment groups were compared. Patient survival was compared with survival data reported in randomized studies of locally advanced head and neck cancer. Results: There were no differences in comorbidity factors, and T or N stages between the two groups. A statistically significant number of patients with oropharyngeal and oral cavity tumors had chemoradiation and postoperative radiation, respectively (p < 0.0001). Grade 3-4 toxicities during treatment were 48 and 87% for the postoperative radiation and chemoradiation groups, respectively (p = 0.0001). There were no differences in survival, locoregional recurrences and distant metastases between the two groups. Patient survival was comparable to survival rates reported by randomized studies of locally advanced head and neck cancer. Conclusion: Disease sites remained the key determining factor for treatment selection. Multidisciplinary approaches provided optimal treatment outcome for locally advanced head and neck cancer, with overall survival in these patients being comparable to that reported in randomized clinical trials. Copyright © 2008 S. Karger AG.

Environmental impacts of tropospheric volcanic gas plumes

info:eu-repo/semantics/published

Comportamiento agronómico de lupino (Lupinus albus L.) en el sur de la provincia de Santa Fe

p.213-218

Crecimiento y partición de materia seca en Senecio madagascariensis Poiret (Compositae)

p.213-225

Variaciones del proceso de desertificación en la cuenca del río Santa María, Catamarca

p.213-221

Caracteres de la descendencia afectados por la vitriosidad de la semilla en algunas especies del género Triticum

p.213-221

Tres enfoques económicos de los problemas ambientales

p.213-223

Efectividad de la evaluación de polen en el campo para determinar androesterilidad en maíz (Zea mays ssp. mays)

p.213-220

Eficiencia de la capacitancia y altura de canopeo comprimido (con disco) para estimar biomasa forrajera

p.213-219

Acrinatrín 15 CE nuevo acaricida - insecticida en frutales de pepita : desarrollo a campo

p.203-213

Nace un problema

Con base en el enfoque de resolución de problemas, se describe una experiencia vivida por un grupo de maestros en la que se parte de un problema que es resuelto sin mayor dificultad, pero que, al realizar la mirada retrospectiva, da lugar a un nuevo problema que invita a los participantes a un viaje.

Proyectos de aprendizaje en la enseñanza de la estadística

Para que el aprendizaje ocurra, es necesario que los estudiantes se unen momentos de exploración, al realizar experimentos contextualizados en el mundo físico, con momentos de reflexión. En este sentido, el objetivo de este taller es presentar proyectos de aprendizaje como una alternativa pedagógica para promover la construcción del conocimiento estadístico de los estudiantes. En primer lugar, vamos a abordar la forma de desarrollar proyectos de aprendizaje en la enseñanza de estadística. Para orientar las acciones futuras de los participantes, se presentarán las estrategias metodológicas que ya se aplican en la conducción del desarrollo de proyectos de aprendizaje en la enseñanza de la estadística en los cursos de licenciatura en diversas áreas del conocimiento en Brasil.

A knowledge-based system to represent spatial reasoning for fire modelling

This paper describes the architecture of the knowledge based system (KBS) component of Smartfire, a fire field modelling tool for use by members of the fire safety engineering community who are not expert in modelling techniques. The KBS captures the qualitative reasoning of an experienced modeller in the assessment of room geometries, so as to set up the important initial parameters of the problem. Fire modelling expertise is an example of geometric and spatial reasoning, which raises representational problems. The approach taken in this project is a qualitative representation of geometric room information based on Forbus’ concept of a metric diagram. This takes the form of a coarse grid, partitioning the domain in each of the three spatial dimensions. Inference over the representation is performed using a case-based reasoning (CBR) component. The CBR component stores example partitions with key set-up parameters; this paper concentrates on the key parameter of grid cell distribution.

Representing the dividing instant

The so-called dividing instant (DI) problem is an ancient historical puzzle encountered when attempting to represent what happens at the boundary instant which divides two successive states. The specification of such a problem requires a thorough exploration of the primitives of the temporal ontology and the corresponding time structure, as well as the conditions that the resulting temporal models must satisfy. The problem is closely related to the question of how to characterize the relationship between time periods with positive duration and time instants with no duration. It involves the characterization of the ‘closed’ and ‘open’ nature of time intervals, i.e. whether time intervals include their ending points or not. In the domain of artificial intelligence, the DI problem may be treated as an issue of how to represent different assumptions (or hypotheses) about the DI in a consistent way. In this paper, we shall examine various temporal models including those based solely on points, those based solely on intervals and those based on both points and intervals, and point out the corresponding DI problem with regard to each of these temporal models. We shall propose a classification of assumptions about the DI and provide a solution to the corresponding problem.