Thermal Adaptation and Diversity in Tropical Ecosystems: Evidence from Cicadas (Hemiptera, Cicadidae)

The latitudinal gradient in species diversity is a central problem in ecology. Expeditions covering approximately 16°54′ of longitude and 21°4′ of latitude and eight Argentine phytogeographic regions provided thermal adaptation data for 64 species of cicadas. We test whether species diversity relates to the diversity of thermal environments within a habitat. There are general patterns of the thermal response values decreasing in cooler floristic provinces and decreasing maximum potential temperature within a habitat except in tropical forest ecosystems. Vertical stratification of the plant communities leads to stratification in species using specific layers of the habitat. There is a decrease in thermal tolerances in species from the understory communities in comparison to middle level or canopy fauna. The understory Herrera umbraphila Sanborn & Heath is the first diurnally active cicada identified as a thermoconforming species. The body temperature for activity in H. umbraphila is less than and significantly different from active body temperatures of all other studied species regardless of habitat affiliation. These data suggest that variability in thermal niches within the heterogeneous plant community of the tropical forest environments permits species diversification as species adapt their physiology to function more efficiently at temperatures different from their potential competitors

Spin- and energy relaxation of hot electrons at GaAs surfaces

The mechanisms for spin relaxation in semiconductors are reviewed, and the mechanism prevalent in p-doped semiconductors, namely spin relaxation due to the electron-hole exchange interaction, is presented in some depth. It is shown that the solution of Boltzmann-type kinetic equations allows one to obtain quantitative results for spin relaxation in semiconductors that go beyond the original Bir-Aronov-Pikus relaxation-rate approximation. Experimental results using surface sensitive two-photon photoemission techniques show that the spin relaxation-time of electrons in p-doped GaAs at a semiconductor/metal surface is several times longer than the corresponding bulk spin relaxation-times. A theoretical explanation of these results in terms of the reduced density of holes in the band-bending region at the surface is presented.Comment: 33 pages, 12 figures; earlier submission replaced by corrected and expanded version; eps figures now included in the tex

Charles Bonnet Syndrome:Evidence for a Generative Model in the Cortex?

Several theories propose that the cortex implements an internal model to explain, predict, and learn about sensory data, but the nature of this model is unclear. One condition that could be highly informative here is Charles Bonnet syndrome (CBS), where loss of vision leads to complex, vivid visual hallucinations of objects, people, and whole scenes. CBS could be taken as indication that there is a generative model in the brain, specifically one that can synthesise rich, consistent visual representations even in the absence of actual visual input. The processes that lead to CBS are poorly understood. Here, we argue that a model recently introduced in machine learning, the deep Boltzmann machine (DBM), could capture the relevant aspects of (hypothetical) generative processing in the cortex. The DBM carries both the semantics of a probabilistic generative model and of a neural network. The latter allows us to model a concrete neural mechanism that could underlie CBS, namely, homeostatic regulation of neuronal activity. We show that homeostatic plasticity could serve to make the learnt internal model robust against e.g. degradation of sensory input, but overcompensate in the case of CBS, leading to hallucinations. We demonstrate how a wide range of features of CBS can be explained in the model and suggest a potential role for the neuromodulator acetylcholine. This work constitutes the first concrete computational model of CBS and the first application of the DBM as a model in computational neuroscience. Our results lend further credence to the hypothesis of a generative model in the brain

Environmental factors and human puberty

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