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

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

Identifying influencing factors on cryptocurrency price: Evidence for bitcoin and ethereum

El presente estudio tiene como objetivo el desarrollo de nuevos modelos para determinar con alta precisión los factores que explican el precio de las principales criptomonedas. Para ello, se ha utilizado una amplia base de datos de variables relacionadas con el bitcoin y el ethereum, y se han aplicado técnicas de redes neuronales artificiales. Los resultados obtenidos han permitido identificar que los aspectos relacionados con el número de publicaciones en foros, el volumen de transacciones en blockchain y la tasa de hash proporcionan una excelente estrategia para predecir el precio del bitcoin. También, que el volumen de transacciones, el tamaño de los bloques, las comisiones de mineros y los precios del petróleo son los mejores predictores del valor de mercado del ethereu

Enhancing genetic mapping of complex genomes through the design of highly-multiplexed SNP arrays: application to the large and unsequenced genomes of white spruce and black spruce

<p>Abstract</p> <p>Background</p> <p>To explore the potential value of high-throughput genotyping assays in the analysis of large and complex genomes, we designed two highly multiplexed Illumina bead arrays using the GoldenGate SNP assay for gene mapping in white spruce (<it>Picea glauca </it>[Moench] Voss) and black spruce (<it>Picea mariana </it>[Mill.] B.S.P.).</p> <p>Results</p> <p>Each array included 768 SNPs, identified by resequencing genomic DNA from parents of each mapping population. For white spruce and black spruce, respectively, 69.2% and 77.1% of genotyped SNPs had valid GoldenGate assay scores and segregated in the mapping populations. For each of these successful SNPs, on average, valid genotyping scores were obtained for over 99% of progeny. SNP data were integrated to pre-existing ALFP, ESTP, and SSR markers to construct two individual linkage maps and a composite map for white spruce and black spruce genomes. The white spruce composite map contained 821 markers including 348 gene loci. Also, 835 markers including 328 gene loci were positioned on the black spruce composite map. In total, 215 anchor markers (mostly gene markers) were shared between the two species. Considering lineage divergence at least 10 Myr ago between the two spruces, interspecific comparison of homoeologous linkage groups revealed remarkable synteny and marker colinearity.</p> <p>Conclusion</p> <p>The design of customized highly multiplexed Illumina SNP arrays appears as an efficient procedure to enhance the mapping of expressed genes and make linkage maps more informative and powerful in such species with poorly known genomes. This genotyping approach will open new avenues for co-localizing candidate genes and QTLs, partial genome sequencing, and comparative mapping across conifers.</p

COMPARING GC×GC-TOFMS-BASED METABOLOMIC PROFILING AND WOOD ANATOMY FOR FORENSIC IDENTIFICATION OF FIVE MELIACEAE (MAHOGANY) SPECIES

Illegal logging and associated trade have increased worldwide. Such environmental crimes represent a major threat to forest ecosystems and society, causing distortions in market prices, economic instability, ecological deterioration, and poverty. To prevent illegal imports of forest products, there is a need to develop wood identification methods for identifying tree species regulated by the Convention on International Trade in Species of Wild Fauna andFlora in Trade (CITES) and other look-alike species. In this exploratory study, we applied metabolomic profiling of five species (Swietenia mahagoni, Swietenia macrophylla, Cedrela odorata, Khaya ivorensis, and Toona ciliata) using two-dimensional gas chromatog- raphy combined with time-of-flight mass spectrometry (GC3GC-TOFMS). We also performed qualitative, quantitative (based on the measurement of vessel area, tangential vessel lumina diameter,vessel element length, ray height, and ray width), and machine-vision aided (XyloTron) wood anatomy on a subsample of wood specimens to explore thepotential and limits of each approach. Fifty dried xylaria wood specimens were ground, extracted with methanol, and subsequently analyzed by GC3GC-TOFMS. In this study, the four genera could easily be identified using qualitative wood anatomy and chemical profiling. At the spe- cies level, Swietenia macrophylla and Swietenia mahagoni specimens were found to share many major metabolites and could only be differentiated after feature selection guided by cluster resolution (FS-CR) and visualization using Principal Component Analysis (PCA). Expectedly, specimens from the two Swiete- nia spp. could not be distinguished based on qualitative wood anatomy. However, significant differences in quantitative anatomical features were obtained for these two species. Excluding T. ciliata that was not included in the reference database of end grain images at the time of testing (2021), the XyloTron could successfully identify the majority of the specimens to the right genus and 50% of the specimens to the right species. The machine-vision tool was particularly successful at identifying Cedrela odorata samples, where all samples were correctly identified. Despite the limited number of specimens available for thisstudy, our preliminary results indicate that GC3GC-TOFMS-based metabolomic profiles could be used as comple- mentary method to differentiate CITES-regulated wood specimens at the genus and species levels.

Valoración agrometeorológica de empresas pecuarias con ganado carnicero en Cuba

Background: Climate change is a reality and agricultural development strategies must know the agrometeorological characteristics of the corresponding areas. Objective. To characterize nine genetic companies in the country that have beef breeds through some climatic variables. Methods: Monthly information on climatic variables was available: minimum environmental temperature (0C) (Tmin), average (0C) (Tmed), maximum (0C) (Tmax), relative humidity (RH) (%), estimating also the temperature humidity index (ITH), of 9 companies in the three regions of the country, from 1980-2018, with 3 374 records. Analysis of variance was carried out for the five climatic variables, including company, year and month and interactions as sources of variation. Results: The general means were: 21,91 ± 1,46 oC; 27,29 ± 1,52 oC; 30,57 ± 1,68 oC; 76,19 ± 4,18% y 77,78 ± 3,45 for Tmin, Tmed, Tmax, RH and ITH, respectively. The company, year and month and the interactions were highly significant (P≤ 0.001), excepted the interactions of third order and season x year. R2 in models were in the range from 51,25% for RH to 76,02% for ITH. The Turiguanó company was the one with the worst climatic indicators. Conclusions: It is concluded that the climatic variables allow characterizing the companies, which facilitates the selection of the races and/or genotypes appropriate to the environmental conditions. Keywords: cattle, beef breeds, climatic variables (Source: DeCS)Antecedentes: El cambio climático es una realidad y las estrategias de desarrollo agropecuario deben conocer las características agrometeorológicas de las áreas correspondientes. Caracterizar empresas genéticas del país que tienen razas carniceras a través de variables climáticas. Métodos: Se dispuso de la información mensual de las variables climáticas: temperatura ambiental mínima (0C) (Tmin), media (0C) (Tmed), máxima (0C) (Tmax), la humedad relativa (HR) (%), estimándose además la índice temperatura humedad (ITH), de empresas en las tres regiones del país, desde 1980-2018, con 3 374 registros. Se hicieron análisis de varianza para las cinco variables climáticas incluyendo como fuentes de variación empresa, quinquenio, cuatrimestre y las interacciones. Resultados: Las medias generales fueron: 21,91 ± 1,46 oC; 27,29 ± 1,52 oC; 30,57 ± 1,68 oC; 76,19 ± 4,18% y 77,78 ± 3,45 para Tmin, Tmed, Tmax, HR e ITH, respectivamente. La empresa, cuatrimestre y quinquenio de inicio de las pruebas de comportamiento y las interacciones entre ellos fueron significativas (P≤ 0.001), excepto las interacciones triples y cuatrimestre x quinquenio. Los R2 de los modelos variaron desde 51,25% para HR hasta 76,02% para ITH. La empresa Turiguanó resultó la de peores indicadores climáticos. Conclusiones: Se concluye que las variables climáticas permiten caracterizar las empresas lo que facilita la selección de las razas y/o genotipos adecuados a las condiciones ambientales. Palabras clave: ganado bovino, razas de carne, variables climáticas (Fuente: DeCS

Caracterización climática de la EPG “Manuel Fajardo” y su relación con las pruebas de comportamiento en ganado Criollo cubano

Background: The strategies for cattle production development should rely on information of agro-meteorological characteristics, which determines production processes. The aim was to analyze the climatic conditions at the Genetic Livestock Company, home to the largest herd of Cuban Creole cattle, and its possible relation to the outcome of performance tests. Methods: The information available about 1 375 animals tested during the 1982-2015 period was used. The final weight was adjusted to 540 days (AFW). The mean daily gain (MDG) and weight by age (WBA) were included. The monthly records of minimum temperatures (Tmin), medium temperatures (Tmid), relative humidity (RH) % were also available for the study. The temperature-humidity index (THI) was generated as well. Monthly and yearly analysis of variance and regression equations were performed to analyze the behavior of the climatic variables per year and month, the behavior of AFW, MDG, and WBA throughout time, and their relations with the climatic variables. Results: The general means were, 19.19 ± 0.87 0C; 24.51 ± 0.63 0C; 78.64 ± 2.66 %; 74.23 ± 0.99 for Tmin, Tmid, RH, and THI, respectively. All the variables were influenced (P≤0.001) by start month and year of PT, and the means for the tests. 334.43 ± 39.59 kg; 494.21 ± 107.81 g/day; 610.90 ± 77.25 g/day for AFW, MDG, and WBA, respectively. All the variables were affected (P≤0.001) by the start month and year, and the HTI. The most accurate regression equations with R2 &gt; 94% were observed between AFW-HTI and WBA-HTI. Conclusions: A clear trend was observed toward a worsening of climatic conditions and the PT indicators throughout time. They are developed under conditions of climatic alert, and were favorable only when they were initiated in the first quarter of the year, and December. Keywords: Cuban Creole, performance tests, climatic variables (Source: DeCS)Antecedentes: Las estrategias de desarrollo agropecuario deben estar respaldadas por el conocimiento de las características agrometeorológicas que es un factor determinante en los procesos productivos. Objetivo. Analizar las condiciones climáticas en la Empresa Pecuaria Genética que tiene el principal rebaño de ganado Criollo cubano y su posible relación con el desenvolvimiento en pruebas de comportamiento. Métodos: Se dispuso de la información de 1 375 animales que realizaron su prueba durante el periodo 1982-2015 después que la base fue depurada. El peso final se ajustó a 540 días (PFA) y se dispuso también de la ganancia media diaria (GMD) y el peso por edad (PPE). Se contó con los registros mensuales de la temperatura mínima (Tmin), media (Tmed) en 0C, humedad relativa (HR) en % y se generó el índice temperatura-humedad (ITH). Mediante análisis de varianza y ecuaciones de regresión se analizó el comportamiento de las variables climáticas por mes y año, el comportamiento del PFA, GMD y PPE a través del tiempo y sus relaciones con las variables climáticas. Resultados: Las medias generales y las desviaciones estándar fueron: 19,19 ± 0,87 0C; 24,51 ± 0,63 0C; 78,64 ± 2,66 %; 74,23 ± 0,99 para Tmin, Tmed, HR e ITH, respectivamente. Todas las variables estuvieron influidas (P≤0,001) por el mes y año de inicio de las PC y las medias para la prueba: 334,43 ± 39,59 kg; 494,21 ± 107,81 g/día; 610,90 ± 77,25 g/día para PFA, GMD y PPE, respectivamente. Todas las variables fueron afectadas (P≤0,001) por el mes, año de inicio y el ITH. Las ecuaciones de regresión más precisas con R2 &gt; 94% fueron entre PFA-ITH y PPE-ITH. Conclusiones: Hay una tendencia clara a un empeoramiento de las condiciones climáticas a través del tiempo, así como los indicadores de las PC. Estas se desarrollan bajo condiciones de alerta climática resultando solo favorables cuando se iniciaron en el primer trimestre del año y diciembre. Palabras clave: Criollo cubano, pruebas de comportamiento, variables climáticas (Fuente: DeCS

Combining QTL mapping and transcriptomics to decipher the genetic architecture of phenolic compounds metabolism in the conifer white spruce

Conifer forests worldwide are becoming increasingly vulnerable to the effects of climate change. Although the production of phenolic compounds (PCs) has been shown to be modulated by biotic and abiotic stresses, the genetic basis underlying the variation in their constitutive production level remains poorly documented in conifers. We used QTL mapping and RNA-Seq to explore the complex polygenic network underlying the constitutive production of PCs in a white spruce (Picea glauca) full-sib family for 2 years. QTL detection was performed for nine PCs and differentially expressed genes (DEGs) were identified between individuals with high and low PC contents for five PCs exhibiting stable QTLs across time. A total of 17 QTLs were detected for eightmetabolites, including one major QTL explaining up to 91.3% of the neolignan-2 variance. The RNA-Seq analysis highlighted 50 DEGs associated with phenylpropanoid biosynthesis, several key transcription factors, and a subset of 137 genes showing opposite expression patterns in individuals with high levels of the flavonoids gallocatechin and taxifolin glucoside. A total of 19 DEGs co-localized with QTLs. Our findings represent a significant step toward resolving the genomic architecture of PC production in spruce and facilitate the functional characterization of genes and transcriptional networks responsible for differences in constitutive production of PCs in conifers.National Sciences and Engineering Research Council of Canada, the Spruce-Up LSARP project with funding from Genome Canada and Genome Quebec and Genomics Research and Development Initiative of Canada.http://www.frontiersin.org/Plant_Scienceam2022Forestry and Agricultural Biotechnology Institute (FABI)Zoology and Entomolog

Symmetries and asymmetries associated with non-random segregation of sister DNA strands in Escherichia coli

AbstractThe successful inheritance of genetic information across generations is a complex process requiring replication of the genome and its faithful segregation into two daughter cells. At each replication cycle there is a risk that new DNA strands incorporate genetic changes caused by miscopying of parental information. By contrast the parental strands retain the original information. This raises the intriguing possibility that specific cell lineages might inherit “immortal” parental DNA strands via non-random segregation. If so, this requires an understanding of the mechanisms of non-random segregation. Here, we review several aspects of asymmetry in the very symmetrical cell, Escherichia coli, in the interest of exploring the potential basis for non-random segregation of leading- and lagging-strand replicated chromosome arms. These considerations lead us to propose a model for DNA replication that integrates chromosome segregation and genomic localisation with non-random strand segregation