A Dim Light
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Dark Revelation - The Role Playing Game - Player's Guide
The Hodgepocalypse takes North America and the d20 system and makes it a diverse world filed with magical rites, modern technology and bizarre cultures.
Photosynthesis Under Fluctuating Light
Photosynthesis is a fundamental process that drives almost all life on Earth, and is the motor of agriculture and food production. For several decades, its basic functioning has been investigated mainly at steady-state, under constant illumination. This approach was necessary to understand the basic mechanisms underlying the light reactions and carbon assimilation. However, this condition does not reflect the natural environment, where plants experience changes in both the intensity and spectrum of irradiance in a wide range of time scales, spanning from seconds to several hours. In recent years, it has become clear that the processes allowing the photosynthetic apparatus to adapt to changes in irradiance are of paramount importance to plant fitness and productivity. Therefore, increased research effort has been directed towards studying the regulation of photosynthetic activity under fluctuating light, i.e. upon the variation of light intensity or light spectrum. This is important for understanding how photosynthetic organisms cope with natural environmental conditions. Fluctuating light itself constitutes a potentially stressful condition, because, depending on the scale of the fluctuation, it can transiently generate extreme redox and transthylakoid potentials, and forces the photosynthetic machinery to be re-adjusted. Not surprisingly, plants have evolved several mechanisms allowing a prompt response to these normal environmental events. In natural environments, photosynthetic organisms often have to cope with fluctuating light while experiencing other kinds of stress, such as heat, nutrient deficiency, drought, and pathogen attacks. Therefore, the study of combined stresses is essential for understanding the acclimation to realistic environmental conditions.
Pattern Recognition by Self-organizing Neural Networks
Pattern Recognition by Self-Organizing Neural Networks presentsthe most recent advances in an area of research that is becoming vitally important in the fields ofcognitive science, neuroscience, artificial intelligence, and neural networks in general. The 19articles take up developments in competitive learning and computational maps, adaptive resonancetheory, and specialized architectures and biological connections. Introductorysurvey articles provide a framework for understanding the many models involved in various approachesto studying neural networks. These are followed in Part 2 by articles that form the foundation formodels of competitive learning and computational mapping, and recent articles by Kohonen, applyingthem to problems in speech recognition, and by Hecht-Nielsen, applying them to problems in designingadaptive lookup tables. Articles in Part 3 focus on adaptive resonance theory (ART) networks,selforganizing pattern recognition systems whose top-down template feedback signals guarantee theirstable learning in response to arbitrary sequences of input patterns. In Part 4, articles describeembedding ART modules into larger architectures and provide experimental evidence fromneurophysiology, event-related potentials, and psychology that support the prediction that ARTmechanisms exist in the brain. Contributors: J.-P. Banquet, G.A. Carpenter, S.Grossberg, R. Hecht-Nielsen, T. Kohonen, B. Kosko, T.W. Ryan, N.A. Schmajuk, W. Singer, D. Stork, C.von der Malsburg, C.L. Winter.