Investigations Pertaining to Texas Beekeeping.

59 pgEXPERIMENTS IN ARTIFICIAL DIVISION AND SWARM-CONTROL THE LIFE HISTORY AND CONTROL OF THE BEE-MOTH OR WAX-WORM A STATISTICAL STUDY OF TEXAS BEEKEEPIN

Development of Models to Simulate Tracer Tests for Characterization of Enhanced Geothermal Systems

A recent report found that power and heat produced from enhanced (or engineered) geothermal systems (EGSs) could have a major impact on the U.S energy production capability while having a minimal impact on the environment. EGS resources differ from high-grade hydrothermal resources in that they lack sufficient temperature distribution, permeability/porosity, fluid saturation, or recharge of reservoir fluids. Therefore, quantitative characterization of temperature distributions and the surface area available for heat transfer in EGS is necessary for the design and commercial development of the geothermal energy of a potential EGS site. The goal of this project is to provide integrated tracer and tracer interpretation tools to facilitate this characterization. This project was initially focused on tracer development with the application of perfluorinated tracer (PFT) compounds, non-reactive tracers used in numerous applications from atmospheric transport to underground leak detection, to geothermal systems, and evaluation of encapsulated PFTs that would release tracers at targeted reservoir temperatures. After the 2011 midyear review and subsequent discussions with the U.S. Department of Energy Geothermal Technology Program (GTP), emphasis was shifted to interpretive tool development, testing, and validation. Subsurface modeling capabilities are an important component of this project for both the design of suitable tracers and the interpretation of data from in situ tracer tests, be they single- or multi-well tests. The purpose of this report is to describe the results of the tracer and model development for simulating and conducting tracer tests for characterizing EGS parameters

Representation recovers information

Early agreement within cognitive science on the topic of representation has now given way to a combination of positions. Some question the significance of representation in cognition. Others continue to argue in favor, but the case has not been demonstrated in any formal way. The present paper sets out a framework in which the value of representation-use can be mathematically measured, albeit in a broadly sensory context rather than a specifically cognitive one. Key to the approach is the use of Bayesian networks for modeling the distal dimension of sensory processes. More relevant to cognitive science is the theoretical result obtained, which is that a certain type of representational architecture is *necessary* for achievement of sensory efficiency. While exhibiting few of the characteristics of traditional, symbolic encoding, this architecture corresponds quite closely to the forms of embedded representation now being explored in some embedded/embodied approaches. It becomes meaningful to view that type of representation-use as a form of information recovery. A formal basis then exists for viewing representation not so much as the substrate of reasoning and thought, but rather as a general medium for efficient, interpretive processing

Amplitude equations for a system with thermohaline convection

The multiple scale expansion method is used to derive amplitude equations for a system with thermohaline convection in the neighborhood of Hopf and Taylor bifurcation points and at the double zero point of the dispersion relation. A complex Ginzburg-Landau equation, a Newell-Whitehead-type equation, and an equation of the $\phi^4$ type, respectively, were obtained. Analytic expressions for the coefficients of these equations and their various asymptotic forms are presented. In the case of Hopf bifurcation for low and high frequencies, the amplitude equation reduces to a perturbed nonlinear Schr\"odinger equation. In the high-frequency limit, structures of the type of "dark" solitons are characteristic of the examined physical system.Comment: 21 pages, 8 figure

Microscopic Polarization in Bilayer Graphene

Bilayer graphene has drawn significant attention due to the opening of a band gap in its low energy electronic spectrum, which offers a promising route to electronic applications. The gap can be either tunable through an external electric field or spontaneously formed through an interaction-induced symmetry breaking. Our scanning tunneling measurements reveal the microscopic nature of the bilayer gap to be very different from what is observed in previous macroscopic measurements or expected from current theoretical models. The potential difference between the layers, which is proportional to charge imbalance and determines the gap value, shows strong dependence on the disorder potential, varying spatially in both magnitude and sign on a microscopic level. Furthermore, the gap does not vanish at small charge densities. Additional interaction-induced effects are observed in a magnetic field with the opening of a subgap when the zero orbital Landau level is placed at the Fermi energy

Binding of lac repressor-GFP fusion protein to lac operator sites inserted in the tobacco chloroplast genome examined by chromatin immunoprecipitation

Chromatin immunoprecipitation (ChIP) has been used to detect binding of DNA-binding proteins to sites in nuclear and mitochondrial genomes. Here, we describe a method for detecting protein-binding sites on chloroplast DNA, using modifications to the nuclear ChIP procedures. The method was developed using the lac operator (lacO)/lac repressor (LacI) system from Escherichia coli. The lacO sequences were integrated into a single site between the rbcL and accD genes in tobacco plastid DNA and homoplasmic transplastomic plants were crossed with transgenic tobacco plants expressing a nuclear-encoded plastid-targeted GFP-LacI fusion protein. In the progeny, the GFP-LacI fusion protein could be visualized in living tissues using confocal microscopy, and was found to co-localize with plastid nucleoids. Isolated chloroplasts from the lacO/GFP-LacI plants were lysed, treated with micrococcal nuclease to digest the DNA to fragments of ∼600 bp and incubated with antibodies to GFP and protein A-Sepharose. PCR analysis on DNA extracted from the immunoprecipitate demonstrated IPTG (isopropylthiogalactoside)-sensitive binding of GFP-LacI to lacO. Binding of GFP-LacI to endogenous sites in plastid DNA showing sequence similarity to lacO was also detected, but required reversible cross-linking with formaldehyde. This may provide a general method for the detection of binding sites on plastid DNA for specific proteins

A synthesis of automated planning and reinforcement learning for efficient, robust decision-making

Automated planning and reinforcement learning are characterized by complementary views on decision making: the former relies on previous knowledge and computation, while the latter on interaction with the world, and experience. Planning allows robots to carry out different tasks in the same domain, without the need to acquire knowledge about each one of them, but relies strongly on the accuracy of the model. Reinforcement learning, on the other hand, does not require previous knowledge, and allows robots to robustly adapt to the environment, but often necessitates an infeasible amount of experience. We present Domain Approximation for Reinforcement LearnING (DARLING), a method that takes advantage of planning to constrain the behavior of the agent to reasonable choices, and of reinforcement learning to adapt to the environment, and increase the reliability of the decision making process. We demonstrate the effectiveness of the proposed method on a service robot, carrying out a variety of tasks in an office building. We find that when the robot makes decisions by planning alone on a given model it often fails, and when it makes decisions by reinforcement learning alone it often cannot complete its tasks in a reasonable amount of time. When employing DARLING, even when seeded with the same model that was used for planning alone, however, the robot can quickly learn a behavior to carry out all the tasks, improves over time, and adapts to the environment as it changes

Lower trunk motion and speed-dependence during walking

Abstract Background There is a limited understanding about how gait speed influences the control of upper body motion during walking. Therefore, the primary purpose of this study was to examine how gait speed influences healthy individual's lower trunk motion during overground walking. The secondary purpose was to assess if Principal Component Analysis (PCA) can be used to gain further insight into postural responses that occur at different walking speeds. Methods Thirteen healthy subjects (23 ± 3 years) performed 5 straight-line walking trials at self selected slow, preferred, and fast walking speeds. Accelerations of the lower trunk were measured in the anterior-posterior (AP), vertical (VT), and mediolateral (ML) directions using a triaxial accelerometer. Stride-to-stride acceleration amplitude, regularity and repeatability were examined with RMS acceleration, Approximate Entropy and Coefficient of Multiple determination respectively. Coupling between acceleration directions were calculated using Cross Approximate Entropy. PCA was used to reveal the dimensionality of trunk accelerations during walking at slow and preferred speeds, and preferred and fast speeds. Results RMS acceleration amplitude increased with gait speed in all directions. ML and VT trunk accelerations had less signal regularity and repeatability during the slow compared to preferred speed. However, stride-to-stride acceleration regularity and repeatability did not differ between the preferred and fast walking speed conditions, partly due to an increase in coupling between frontal plane accelerations. The percentage of variance accounted for by each trunk acceleration Principal Component (PC) did not differ between grouped slow and preferred, and preferred and fast walking speed acceleration data. Conclusion The main finding of this study was that walking at speeds slower than preferred primarily alters lower trunk accelerations in the frontal plane. Despite greater amplitudes of trunk acceleration at fast speeds, the lack of regularity and repeatability differences between preferred and fast speeds suggest that features of trunk motion are preserved between the same conditions. While PCA indicated that features of trunk motion are preserved between slow and preferred, and preferred and fast speeds, the discriminatory ability of PCA to detect speed-dependent differences in walking patterns is limited compared to measures of signal regularity, repeatability, and coupling.</p