Evaluating evolution as a learning algorithm

We interpret the Moran model of natural selection and drift as an algorithm for learning features of a simplified fitness landscape, specifically genotype superiority. This algorithm's efficiency in extracting these characteristics is evaluated by comparing it to a novel Bayesian learning algorithm developed using information-theoretic tools. This algorithm makes use of a communication channel analogy between an environment and an evolving population. We use the associated channel-rate to determine an informative population-sampling procedure. We find that the algorithm can identify genotype superiority faster than the Moran model but at the cost of larger fluctuations in uncertainty

Securing tropical forest carbon: the contribution of protected areas to REDD

Forest loss and degradation in the tropics contribute 6-17% of all greenhouse gas emissions. Protected areas cover 217.2 million ha (19.6%) of the world's humid tropical forests and contain c. 70.3 petagrams of carbon (Pg C) in biomass and soil to 1 m depth. Between 2000 and 2005, we estimate that 1.75 million ha of forest were lost from protected areas in humid tropical forests, causing the emission of 0.25-0.33 Pg C. Protected areas lost about half as much carbon as the same area of unprotected forest. We estimate that the reduction of these carbon emissions from ongoing deforestation in protected sites in humid tropical forests could be valued at USD 6,200-7,400 million depending on the land use after clearance. This is >1.5 times the estimated spending on protected area management in these regions. Improving management of protected areas to retain forest cover better may be an important, although certainly not sufficient, component of an overall strategy for reducing emissions from deforestation and forest degradation (REDD

Using Geological Facies to Estimate Chromate Sorption to Soils

Quantifying the extent to which contaminant metals bind to subsurface soils is important for risk assessment, the tendency for a contaminant to migrate, and developing environmental remediation strategies. Unfortunately, subsurface soils vary widely in their composition, which in turn affect their tendency to bind metals. The hypothesis of this study was predicated on how a better understanding of geological facies would reduce uncertainty associated with predicting contaminant metal sorption. Facies are layers of sediment deposited in the subsurface due to similar depositional conditions, including energy of an overlying waterway. As such, facies are expected to have similar assemblages of minerals, particle size distributions, origins of organic matter, and similar microbial population structures. These are all important factors affecting contaminant metal sorption. The approach of this study was to collect 42 composite soil samples from a 5 m by 1.5 m grid outcrop in Graniteville, South Carolina and five end-member facies samples. The fraction of each of the five facies comprising the 42 composite soil samples were estimated. Particle size distribution (gravel, sand, silt, and clay fractions), pH, organic matter (OM), iron coating content, and microbial colony forming units were determined for each composite soil and the five end-member facies soils. Because hexavalent chromium (Cr) is the most common contaminant metal in the U.S. to exceed drinking water limits, this highly toxic and soluble metal was used as a model contaminant to provide a measure of contaminant sorption. Chromium distribution coefficients (Kd = Crsoil/Crwater) were measured. Significant correlations were identified between several soil chemical and microbial properties. A significant correlation (r = 0.423; p ≤ 0.05, d.f. = 47) was also determined between measured Kd values and Kd values calculated based on knowledge of facies Kd values. Importantly, the calculated values were characterized by large amount of inherent error. Additional work is needed to determine the applicability of this approach for remediation of contaminated sites and how best to identify appropriate facies for this novel application

Deep mining of oxysterols and cholestenoic acids in human plasma and cerebrospinal fluid: Quantification using isotope dilution mass spectrometry

Both plasma and cerebrospinal fluid (CSF) are rich in cholesterol and its metabolites. Here we describe in detail a methodology for the identification and quantification of multiple sterols including oxysterols and sterol-acids found in these fluids. The method is translatable to any laboratory with access to liquid chromatography – tandem mass spectrometry. The method exploits isotope-dilution mass spectrometry for absolute quantification of target metabolites. The method is applicable for semi-quantification of other sterols for which isotope labelled surrogates are not available and approximate quantification of partially identified sterols. Values are reported for non-esterified sterols in the absence of saponification and total sterols following saponification. In this way absolute quantification data is reported for 17 sterols in the NIST SRM 1950 plasma along with semi-quantitative data for 8 additional sterols and approximate quantification for one further sterol. In a pooled (CSF) sample used for internal quality control, absolute quantification was performed on 10 sterols, semi-quantification on 9 sterols and approximate quantification on a further three partially identified sterols. The value of the method is illustrated by confirming the sterol phenotype of a patient suffering from ACOX2 deficiency, a rare disorder of bile acid biosynthesis, and in a plasma sample from a patient suffering from cerebrotendinous xanthomatosis, where cholesterol 27-hydroxylase is deficient

Temporal fluctuations in seawater pCO<inf>2</inf> may be as important as mean differences when determining physiological sensitivity in natural systems

Most studies assessing the impactsofocean acidification (OA) onbenthic marine invertebrates have used stable mean pH/pCO2 levelsto highlight variation in the physiological sensitivities in a range of taxa. However, many marine environments experience natural fluctuations in carbonate chemistry, and to date little attempt has been made to understand the effect of naturally fluctuating seawater pCO2 (pCO2sw) on the physiological capacity of organisms to maintain acid-base homeostasis. Here, for the first time, we exposed two species of sea urchin with different acid-base tolerances, Paracentrotus lividus and Arbacia lixula, to naturally fluctuating pCO2sw conditions at shallow water CO2 seep systems (Vulcano, Italy) and assessed their acid-base responses. Both sea urchin species experienced fluctuations in extracellular coelomic fluid pH, pCO2, and [HCO-3] (pHe, pCO2e, and [HCO-3]e, respectively) in line with fluctuations in pCO2sw. The less tolerant species, P. lividus, had the greatest capacity for [HCO-3]e buffering in response to acute pCO2sw fluctuations, but it also experienced greater extracellular hypercapnia and acidification and was thus unabletofully compensate for acid-basedisturbances. Conversely, themore tolerant A.lixula reliedonnon-bicarbonate protein buffering and greater respiratory control. In the light of these findings, we discuss the possible energetic consequences of increased reliance on bicarbonate buffering activity in P. lividus compared with A. lixula and how these differing physiological responses to acute fluctuations in pCO2sw may be as important as chronic responses to mean changes in pCO2sw when considering how CO2 emissions will affect survival and success of marine organisms within naturally assembled systems

Q^2 Dependence of the S_{11}(1535) Photocoupling and Evidence for a P-wave resonance in eta electroproduction

New cross sections for the reaction $ep \to e'\eta p$ are reported for total center of mass energy $W$=1.5--2.3 GeV and invariant squared momentum transfer $Q^2$=0.13--3.3 GeV$^2$. This large kinematic range allows extraction of new information about response functions, photocouplings, and $\eta N$ coupling strengths of baryon resonances. A sharp structure is seen at $W\sim$ 1.7 GeV. The shape of the differential cross section is indicative of the presence of a $P$-wave resonance that persists to high $Q^2$. Improved values are derived for the photon coupling amplitude for the $S_{11}$(1535) resonance. The new data greatly expands the $Q^2$ range covered and an interpretation of all data with a consistent parameterization is provided.Comment: 31 pages, 9 figure

Technological collaboration : bridging the innovation gap between small and large firms

This paper analyzes how technological collaboration acts as an input to the innovation process and allows small and medium-sized entetprises to bridge the innovation gap with their bigger counterparts. Based on a large longitudinal sample of Spanish manufacturing firms, the results show that though technological collaboration is a useful mechanism for firms of all sizes to improve innovativeness, it is a critical factor for the smallest firms. The impact on this collaboration varies depending on innovation output and type of partner. Specifically, the impact of collaboration in small and medium-sized firms is more significant for product than process innovations. Regarding type of partner, vertical collaboration-with suppliers and clients-has the greatest impact on firm innovativeness, though (his effect is clearer lor medium-sized entetprises than for the smallest firmsThis study has been finaneially supported by projeets SEC]2007-67582-C02-02/ECON and CCG08-UC3M/HUM-4152Publicad

Mode shifting between storage and recall based on novelty detection in oscillating hippocampal circuits.

ABSTRACT: It has been suggested that hippocampal mode shifting between a storage and a retrieval state might be under the control of acetylcholine (ACh) levels, as set by an autoregulatory hippocampo-septohippocampal loop. The present study investigates how such a mechanism might operate in a large-scale connectionist model of this circuitry that takes into account the major hippocampal subdivisions, oscillatory population dynamics and the time scale on which ACh exerts its effects in the hippocampus. The model assumes that hippocampal mode shifting is regulated by a novelty signal generated in the hippocampus. The simulations suggest that this signal originates in the dentate. Novel patterns presented to this structure lead to brief periods of depressed firing in the hippocampal circuitry. During these periods, an inhibitory influence of the hippocampus on the septum is lifted, leading to increased firing of cholinergic neurons. The resulting increase in ACh release in the hippocampus produces network dynamics that favor learning over retrieval. Resumption of activity in the hippocampus leads to the reinstatement of inhibition. Despite theta-locked rhythmic firing of ACh neurons in the septum, ACh modulation in the model fluctuates smoothly on a time scale of seconds. It is shown that this is compatible with the time scale on which memory processes take place. A number of strong predictions regarding memory function are derived from the model. © 2004 Wiley-Liss, Inc. KEY WORDS: acetylcholine; computational modeling; hippocampus; medial septum; memor