Sparse visual models for biologically inspired sensorimotor control

Given the importance of using resources efficiently in the competition for survival, it is reasonable to think that natural evolution has discovered efficient cortical coding strategies for representing natural visual information. Sparse representations have intrinsic advantages in terms of fault-tolerance and low-power consumption potential, and can therefore be attractive for robot sensorimotor control with powerful dispositions for decision-making. Inspired by the mammalian brain and its visual ventral pathway, we present in this paper a hierarchical sparse coding network architecture that extracts visual features for use in sensorimotor control. Testing with natural images demonstrates that this sparse coding facilitates processing and learning in subsequent layers. Previous studies have shown how the responses of complex cells could be sparsely represented by a higher-order neural layer. Here we extend sparse coding in each network layer, showing that detailed modeling of earlier stages in the visual pathway enhances the characteristics of the receptive fields developed in subsequent stages. The yield network is more dynamic with richer and more biologically plausible input and output representation

Time-dependent opportunities in energy business : a comparative study of locally available renewable and conventional fuels

This work investigates and compares energy-related, private business strategies, potentially interesting for investors willing to exploit either local biomass sources or strategic conventional fuels. Two distinct fuels and related power-production technologies are compared as a case study, in terms of economic efficiency: the biomass of cotton stalks and the natural gas. The carbon capture and storage option are also investigated for power plants based on both fuel types. The model used in this study investigates important economic aspects using a "real options" method instead of traditional Discounted Cash Flow techniques, as it might handle in a more effective way the problems arising from the stochastic nature of significant cash flow contributors' evolution like electricity, fuel and CO(2) allowance prices. The capital costs have also a functional relationship with time, thus providing an additional reason for implementing, "real options" as well as the learning-curves technique. The methodology as well as the results presented in this work, may lead to interesting conclusions and affect potential private investment strategies and future decision making. This study indicates that both technologies lead to positive investment yields, with the natural gas being more profitable for the case study examined, while the carbon capture and storage does not seem to be cost efficient with the current CO(2) allowance prices. Furthermore, low interest rates might encourage potential investors to wait before actualising their business plans while higher interest rates favor immediate investment decisions. (C) 2009 Elsevier Ltd. All rights reserved

Enzymatic functionalization of carbon-hydrogen bonds

The development of new catalytic methods to functionalize carbon–hydrogen (C–H) bonds continues to progress at a rapid pace due to the significant economic and environmental benefits of these transformations over traditional synthetic methods. In nature, enzymes catalyze regio- and stereoselective C–H bond functionalization using transformations ranging from hydroxylation to hydroalkylation under ambient reaction conditions. The efficiency of these enzymes relative to analogous chemical processes has led to their increased use as biocatalysts in preparative and industrial applications. Furthermore, unlike small molecule catalysts, enzymes can be systematically optimized via directed evolution for a particular application and can be expressed in vivo to augment the biosynthetic capability of living organisms. While a variety of technical challenges must still be overcome for practical application of many enzymes for C–H bond functionalization, continued research on natural enzymes and on novel artificial metalloenzymes will lead to improved synthetic processes for efficient synthesis of complex molecules. In this critical review, we discuss the most prevalent mechanistic strategies used by enzymes to functionalize non-acidic C–H bonds, the application and evolution of these enzymes for chemical synthesis, and a number of potential biosynthetic capabilities uniquely enabled by these powerful catalysts (110 references)

Efficient Wasserstein Natural Gradients for Reinforcement Learning

A novel optimization approach is proposed for application to policy gradient methods and evolution strategies for reinforcement learning (RL). The procedure uses a computationally efficient Wasserstein natural gradient (WNG) descent that takes advantage of the geometry induced by a Wasserstein penalty to speed optimization. This method follows the recent theme in RL of including a divergence penalty in the objective to establish a trust region. Experiments on challenging tasks demonstrate improvements in both computational cost and performance over advanced baseline

Natural Evolution Strategies as a Black Box Estimator for Stochastic Variational Inference

Stochastic variational inference and its derivatives in the form of variational autoencoders enjoy the ability to perform Bayesian inference on large datasets in an efficient manner. However, performing inference with a VAE requires a certain design choice (i.e. reparameterization trick) to allow unbiased and low variance gradient estimation, restricting the types of models that can be created. To overcome this challenge, an alternative estimator based on natural evolution strategies is proposed. This estimator does not make assumptions about the kind of distributions used, allowing for the creation of models that would otherwise not have been possible under the VAE framework

Directed evolution of an enantioselective Bacillus subtilis lipase

Chiral compounds are of steadily increasing importance to the chemical industry, in particular for the production of pharmaceuticals. Where do these compounds come from? Apart from natural resources, two synthetic strategies are available: asymmetric chemical catalysis using transition metal catalysts and biocatalysis using enzymes. In the latter case, screening programs have identified a number of enzymes. However, their enantioselectivity is often not high enough for a desired reaction. This problem can be solved by applying directed evolution to create enantioselective enzymes as shown here for a lipase from Bacillus subtilis. The reaction studied was the asymmetric hydrolysis of meso-1,4-diacetoxy-2-cyclopentene with the formation of chiral alcohols which were detected by electrospray ionization mass spectrometry. Iterative cycles of random mutagenesis and screening allowed the identification of several variants with improved enantioselectivities. In parallel, we have started to use X-ray structural data to simulate the Bacillus subtilis lipase A-catalyzed substrate hydrolysis by using quantum mechanical and molecular mechanical calculations. This combined approach should finally enable us to devise more efficient strategies for the directed evolution of enantioselective enzymes

Geothermal systems simulation: A case study

Geothermal reservoir simulation is a key step for developing sustainable and efficient strategies for the exploitation of geothermal resources. It is applied in the assessment of several areas of reservoir engineering, such as reservoir performance and re-injection programs, pressure decline in depletion, phase transition conditions, and natural evolution of hydrothermal convection systems. Fluid flow and heat transfer in rock masses, fluid-rock chemical interaction and rock mass deformation are some of the processes addressed in reservoir modelling. The case study of the Las Tres Virgenes (LTV) geothermal field (10 MWe), Baja California Sur, Mexico is presented. Three dimensional (3D) natural state simulations were carried out from emplacement and cooling of two spherical magma chambers using a conductive approach. A conceptual model of the volcanic system was developed on a lithostratigraphic and geochronological basis. Magma chamber volumes were established from eruptive volumes estimations. The thermophysical properties of the medium were assumed to correspond to the dominant rock in each lithological unit as an initial value, and further calibration was made considering histograms of experimentally obtained thermophysical properties of rocks. As the boundaries of the model lie far from the thermal anomaly, we assumed specified temperature boundaries. A Finite Volume (FV) numerical scheme was implemented in a Fortran 90 code to solve the heat equation. Static formation temperatures from well logs were used for validation of the numerical results. Good agreement was observed in those geothermal wells dominated by conductive heat transfer. For other wells, however, it is clear that conduction alone cannot explain observed behaviour, three-dimensional convective models are being implemented for future multiphysics simulations

Nature versus Technology - Performance building skins inspired by nature

p. 598-610The research will demonstrate new strategies and concepts for building envelopes based on natural systems. Smart structures and adaptive systems are standard in nature and could be the key to the next step in the evolution of intelligent building skins for architecture. The translation of abstracted nature in mathematical terms and the application of prerequisite architectural considerations are the fundamental concepts of bio-inspired structures, materials and systems in engineering. Nature typically uses not additive, but highly integrated systems, which optimize several necessary features in one component. Energy acquired by photosynthesis or heterotrophic processes has to be diverted between growth and reproduction, and protective measures. Bionic skins are highly integrated and multifunctional and based on the compulsion to generation, self-optimize and selfadjustment. The basis for a transfer of biological systems into technical systems requires detailed studies in combination with the crucial functional aspects within the ecological context. Thereby, the efficient use of energy is critical for survival. This present an attractive design pool for advanced technical applications. The paper will be demonstrated new strategies and concepts for building envelopes based on natural systems. Smart structures and adaptive systems are standard in nature and could be the key to the next step in the evolution of intelligent building skins for architecture. Natural structures and skins offer an abundance of observational material for optimization, but direct derivations in the sense of a literal imitation are not possible. The fundamental differences.Stach, E. (2010). Nature versus Technology - Performance building skins inspired by nature. Editorial Universitat Politècnica de València. http://hdl.handle.net/10251/684