KAM: Automatic Planning and Interpretation of Numerical Experiments Using Geometrical Methods

KAM is a computer program that can automatically plan, monitor, and interpret numerical experiments with Hamiltonian systems with two degrees of freedom. The program has recently helped solve an open problem in hydrodynamics. Unlike other approaches to qualitative reasoning about physical system dynamics, KAM embodies a significant amount of knowledge about nonlinear dynamics. KAM's ability to control numerical experiments arises from the fact that it not only produces pictures for us to see, but also looks at (sic---in its mind's eye) the pictures it draws to guide its own actions. KAM is organized in three semantic levels: orbit recognition, phase space searching, and parameter space searching. Within each level spatial properties and relationships that are not explicitly represented in the initial representation are extracted by applying three operations ---(1) aggregation, (2) partition, and (3) classification--- iteratively.

Categorization in IT and PFC: Model and Experiments

In a recent experiment, Freedman et al. recorded from inferotemporal (IT) and prefrontal cortices (PFC) of monkeys performing a "cat/dog" categorization task (Freedman 2001 and Freedman, Riesenhuber, Poggio, Miller 2001). In this paper we analyze the tuning properties of view-tuned units in our HMAX model of object recognition in cortex (Riesenhuber 1999) using the same paradigm and stimuli as in the experiment. We then compare the simulation results to the monkey inferotemporal neuron population data. We find that view-tuned model IT units that were trained without any explicit category information can show category-related tuning as observed in the experiment. This suggests that the tuning properties of experimental IT neurons might primarily be shaped by bottom-up stimulus-space statistics, with little influence of top-down task-specific information. The population of experimental PFC neurons, on the other hand, shows tuning properties that cannot be explained just by stimulus tuning. These analyses are compatible with a model of object recognition in cortex (Riesenhuber 2000) in which a population of shape-tuned neurons provides a general basis for neurons tuned to different recognition tasks.

Relative Contributions of Internal and External Features to Face Recognition

The central challenge in face recognition lies in understanding the role different facial features play in our judgments of identity. Notable in this regard are the relative contributions of the internal (eyes, nose and mouth) and external (hair and jaw-line) features. Past studies that have investigated this issue have typically used high-resolution images or good-quality line drawings as facial stimuli. The results obtained are therefore most relevant for understanding the identification of faces at close range. However, given that real-world viewing conditions are rarely optimal, it is also important to know how image degradations, such as loss of resolution caused by large viewing distances, influence our ability to use internal and external features. Here, we report experiments designed to address this issue. Our data characterize how the relative contributions of internal and external features change as a function of image resolution. While we replicated results of previous studies that have shown internal features of familiar faces to be more useful for recognition than external features at high resolution, we found that the two feature sets reverse in importance as resolution decreases. These results suggest that the visual system uses a highly non-linear cue-fusion strategy in combining internal and external features along the dimension of image resolution and that the configural cues that relate the two feature sets play an important role in judgments of facial identity.

Protein Microarray: "Theory" to "Real Practice"

Fueled by ever-growing genomic information and rapid developments of proteomics–the large scale analysis of proteins and mapping its functional role has become one of the most important disciplines for characterizing complex cell function. For building functional linkages between the biomolecules, and for providing insight into the mechanisms of biological processes, last decade witnessed the exploration of combinatorial and chip technology for the detection of bimolecules in a high throughput and spatially addressable fashion. Among the various techniques developed, the protein chip technology has been rapid. Recently we demonstrated a new platform called “Spacially addressable protein array” (SAPA) to profile the ligand receptor interactions. To optimize the platform, the present study investigated various parameters such as the surface chemistry and role of additives for achieving high density and high-throughput detection with minimal nonspecific protein adsorption. In summary the present poster will address some of the critical challenges in protein micro array technology and the process of fine tuning to achieve the optimum system for solving real biological problems.

Replicated nil associations of digit ratio (2D:4D) and absolute finger lengths with implicit and explicit measures of aggression. 'Replicaci??n de asociaciones nulas del ratio del segundo y cuarto dedo (2D:4D) y la longitud absoluta de los dedos con medidas de agresi??n impl??citas y expl??citas'

Resumen tomado de la publicaci??n

A distributed environment for virtual and/or real experiments for underwater robots

This paper presents the distributed environment for virtual and/or real experiments for underwater robots (DEVRE). This environment is composed of a set of processes running on a local area network composed of three sites: 1) the onboard AUV computer; 2) a surface computer used as human-machine interface (HMI); and 3) a computer used for simulating the vehicle dynamics and representing the virtual world. The HMI can be transparently linked to the real sensors and actuators dealing with a real mission. It can also be linked with virtual sensors and virtual actuators, dealing with a virtual mission. The aim of DEVRE is to assist engineers during the software development and testing in the lab prior to real experiments

Nou racó d'experiments al cicle inicial. 'Nuevo rincón de experimentos al ciclo inicial'.

Resumen de la autora en catalán

El laboratori de física Mentora Alsina : sorprendre's amb experiments científics. 'El laboratorio de física Mentora Alsina : sorprenderse con experimentos científicos'.

Se describe el taller que se realizaba en el gabinete de física experimental Mentora Alsina y que están en exposición en el mNATEC de Terrassa.

Experiments on myself.

Con diferentes tipos de texto y letra se presenta la información sobre el cuerpo humano y los experimentos que deben realizarse para comprobar, entre otras cosas, la talla, relación entre el olfato y el gusto, cómo se mueven los músculos. Adecuado para la lectura compartida o independiente, puede utilizarse de manera multidisciplinar.

Science experiments with water.

Estudia las propiedades del agua a través de experimentos, utilizando materiales que se pueden conseguir fácilmente en casa o en la escuela. Desarrolla los conocimientos y las habilidades científicas claves para la experimentación y la observación. Las instrucciones están acompañadas de fotografías en color para animar a los lectores a que lleguen a sus propias conclusiones. Tiene glosario.

101 great science experiments.

Recurso para hacer ciencia divertida con ciento uno experimentos explicados paso a paso para que sean seguros y fáciles de hacer en casa. Muestra cómo se puede utilizar objetos cotidianos para descubrir los principios básicos de la ciencia y comprender cómo estos se aplican al mundo que nos rodea. Introduce a muchas áreas de la ciencia: la electricidad, el sonido y la música, el movimiento y las máquinas.