Microsatellite Analysis of Trophy Largemouth Bass from Arkansas Reservoirs

The Arkansas Game and Fish Commission (AGFC) has introduced Florida largemouth bass (FLMB; Micropterus salmoides floridanus) to water bodies historically containing the northern largemouth bass (NLMB; Micropterus salmoides salmoides) subspecies since the late 1970s in an attempt to produce a trophy LMB fishery. Since 2006, the AGFC has been biannually sampling reservoirs stocked with FLMB to determine levels of admixture. Here, total sampling efforts between 2006 and 2011 have been combined, and LMB heavier than 2,268 g (5 lb) were analyzed in an effort to investigate distribution of bass by their genetic composition designated as trophy LMB by the AGFC. Of the 148 trophy LMB sampled, 123 possessed FLMB alleles (83.1%). Thirty-two of the heaviest 50 (64.0%) LMB sampled, including a potential state record that was nullified, were genetically confirmed to be FLMB. Distributions of trophy bass within reservoirs were preferentially represented by Fx-FLMB and FLMB

Deep learning methods for modeling bitcoin price

A precise prediction of Bitcoin price is an important aspect of digital financial markets because it improves the valuation of an asset belonging to a decentralized control market. Numerous studies have studied the accuracy of models from a set of factors. Hence, previous literature shows how models for the prediction of Bitcoin suffer from poor performance capacity and, therefore, more progress is needed on predictive models, and they do not select the most significant variables. This paper presents a comparison of deep learning methodologies for forecasting Bitcoin price and, therefore, a new prediction model with the ability to estimate accurately. A sample of 29 initial factors was used, which has made possible the application of explanatory factors of different aspects related to the formation of the price of Bitcoin. To the sample under study, different methods have been applied to achieve a robust model, namely, deep recurrent convolutional neural networks, which have shown the importance of transaction costs and difficulty in Bitcoin price, among others. Our results have a great potential impact on the adequacy of asset pricing against the uncertainties derived from digital currencies, providing tools that help to achieve stability in cryptocurrency markets. Our models offer high and stable success results for a future prediction horizon, something useful for asset valuation of cryptocurrencies like BitcoinThis research was funded by Cátedra de Economía y Finanzas Sostenibles, University of Malaga, Spai

Identifying explanatory factors of bitcoin price with artificial neural networks

This study aims to develop a new model that allows determining with high precision the factors that explain the price of bitcoin. To do this, an extensive database of variables related to bitcoin and artificial neural network techniques has been used. The results obtained have made it possible to identify that aspects related to the number of forum posts, the volume of transactions on the blockchain, and the hash rate provide an excellent strategy for predicting the price of bitcoi

Evaluating functional diversity conservation for freshwater fishes resulting from terrestrial protected areas

Protected areas are one of the hammers in conservation toolkits, yet few protected areas exist that were designed to protect freshwater ecosystems. This is problematic as freshwater ecosystems are among the most threatened systems on earth. Nonetheless, terrestrial protected areas (TPAs) may afford spill‐over benefits to freshwater ecosystems included within their boundaries, but evaluations of these potential benefits for the protection of freshwater fish diversity are lacking.Using fish community data from 175 lakes inside, outside, or bordering TPAs in Ontario, Canada, we sought to determine if TPAs preserve fish functional diversity. We focused on functional diversity because previous work indicated no taxonomic differences between these lakes, but a difference in normalised‐length size‐spectra slopes inside versus outside TPAs (indicator of unique predator–prey ratios and trophic energy transfer). We expected that communities inside TPAs would show greater functional diversity (i.e. functional dispersion and functional richness) and have more extreme trait combinations (i.e. functional divergence) than communities outside or bordering TPAs. We also tested for differences in the rarity of species‐specific functional traits between fish communities inside, outside, or bordering TPAs, between thermal guilds, and across average body size and overall prevalence of the species.Our results indicated no significant differences in functional diversity among lake fish communities inside, outside, or bordering TPAs. However, fish communities inside TPAs had more extreme trait combinations than outside TPAs because abundant species in lake communities outside TPAs had more ubiquitous trait combinations than abundant fishes inside TPAs.Small‐bodied species showed greater functional rarity than large‐bodied species, indicating that small‐bodied fishes fill functionally unique roles while the most prevalent, large‐bodied species possess a more generalist set of traits.Overall, the similarity of functional diversity metrics for lake fish communities inside, outside, or bordering TPAs in Ontario suggests that TPAs capture the functional diversity of Ontario’s lake fish communities. However, we encourage similar evaluations in regions where environmental conditions and stressors are more distinct across TPA boundaries than they are in Ontario, as these types of evaluations will inform guidelines for the design of freshwater protected areas and monitoring of their effectiveness in the future.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151997/1/fwb13395.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151997/2/fwb13395_am.pd

Dependencia financiera y crecimiento económico: evidencia en PYME

This paper is intended to contribute to the debate on the consequences of the external financing needs of Small and Medium Enterprises (SMEs) for their economic growth. This paper differs from previous research in that it uses investment flows that cannot be financed with generated cash flows as a proxy of external financing. The results obtained show that financial dependence explains the economic growth of SMEs but there are also other important explanatory variables such as financial development.En este trabajo contribuimos al debate de los efectos de las necesidades financieras externas de las empresas sobre el crecimiento económico. Nuestra investigación se distingue por utilizar como proxy de dependencia financiera externa de pequeñas y medianas empresas (PYME) los flujos de inversiones que no pueden ser financiados con cash flows generados. Los resultados obtenidos indican que la dependencia financiera explica el nivel de crecimiento económico de las PYME, y que también son significativas otras variables de control como las de desarrollo financiero