3,402 research outputs found
Phylogenetics of the Tiger-flower Group (Tigridieae: Iridaceae): Molecular and Morphological Evidence
The phylogenetic relationships among 23 species of the tribe Tigridieae (lridaceae) were inferred using morphological data and nucleotide sequences from nuclear ITS and three intergenic spacers of the cpDNA: psbA-trnH, trnT-trnL, and trnL-trnF. Although all data sets supported a monophyletic Mexican-Guatemalan Tigridiinae including two taxa usually placed in Cipurinae (Cardiostigma longispatha and Nemastylis convoluta), neither morphology, cpDNA, nor ITS resolved phylogenetic relationships within this lineage. A graphical tree of trees analysis showed the cladograms derived from morphology to be the most topologically distinct within the set of all trees examined and to be the set with most divergent trees. Finally, cladistic analysis of the combined data sets supported the recurrent dispersal of Cipurinae from South to North America and a South American origin of the Mexican-Guatemalan subtribe Tigridiinae
Why federal intervention in Portland shouldn’t be a shock
For several months, protests have been ongoing in Portland, Oregon, following the police killings of Breonna Taylor and George Floyd. Aaron Roussell and Gisela Rodriguez Fernandez examine the intentional misconceptions which have developed to delegitimize the protests in Portland and elsewhere, writing that despite sentiments that such tactics are ‘not American’, the use of police violence and federal agents against protests in US cities is nothing new
Is there any genetic variation among native mexican and argentinian populations of Dalbulus maidis (Hemiptera: Cicadellidae)?.
The corn leafhopper Dalbulus maidis (Delong & Wolcott) (Hemiptera: Cicadellidae) originated in Mexico, but is found from southeastern and southwestern USA to Argentina. Differences in reproductive and phenotypic traits between Mexican (native) and Argentinian (adventive) populations have been previously reported, but information on their genetic variation is currently unavailable. The objective was to investigate possible genetic variability among D. maidis populations collected in Mexico on maize and maize relatives (annual and perennial teosintes) and on maize in Argentina. A region of the mitochondrial gene coding for the cytochrome oxidase subunit I (mtCOI) and the ribosomal internal transcribed spacer (ITS2) were sequenced and analyzed. We developed the forward and reverse primers for the DNA amplification of COI in D. maidis (dalCOI). Twenty two and 17 sequences for dalCOI and ITS2, respectively, were generated and analyzed. No genetic variation among Mexican and Argentinian populations was found in the ribosomal region and low genetic variation was found in the mitochondrial region. These results could be explained by the short evolutionary time scale, since both maize and the corn leafhopper moved throughout the Americas only in the most recent millenia, or in part to the limited host range, and thus a limited change in the corn leafhopper associated bacteria.Fil: Palomera, Veronica. Universidad de Guadalajara; MéxicoFil: Bertin, Sabrina. Universidad de Torino ; ItaliaFil: Rodriguez, Aaron. Universidad de Guadalajara; MéxicoFil: Bosco, Domenico. Universidad de Torino; ItaliaFil: Virla, Eduardo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Planta Piloto de Procesos Industriales Microbiológicos; ArgentinaFil: Moya-Raygoza, Gustavo. Universidad de Guadalajara; Méxic
Programa con fundamento personalista para formar actitudes ante el sufrimiento como medio de perfeccionamiento, en estudiantes de una universidad de Chiclayo-2021
El sufrimiento es una realidad propia de la limitación del ser humano, de la que nadie puede escapar; pero la persona, por su excelsa grandeza, es capaz de asumir actitudes positivas que conviertan al sufrimiento en un triunfo, en cuanto que pueden descubrir el sentido del sufrimiento, como una invitación al crecimiento. Por esa razón se ha realizado la presente investigación, con el propósito de diseñar un programa personalista para mejorar las actitudes ante el sufrimiento como medio de perfeccionamiento en estudiantes de educación del décimo ciclo de la USAT- Chiclayo, en el año 2021. Se trata de una investigación cuantitativa, de nivel descriptivo, porque se recogieron datos que fueron procesados estadísticamente para identificar la problemática y necesidades en relación a la variable de estudio. En ese sentido, en los resultados, además del diagnóstico realizado, se argumentó teóricamente la necesidad de formar sus actitudes ante el sufrimiento humano como medio de perfeccionamiento; y así se pudo justificar la elaboración de un programa con fundamento personalista para mejorar sus actitudes ante esta realidad inherente al ser humano. Finalmente, se elaboró el programa formativo
implementado con sesiones de aprendizaje centrados en la persona humana, teniendo en cuenta
su dignidad y singularidad
Cryptocurrency Price Predictions Using High Performance Computing
Digital currency has recently gained popularity as it has become increasingly dependent on computers and the Internet. New forms of currency have been constantly evolving over the past few years, namely cryptocurrency. Virtual forms of currency have open new doors within the software industry in finance, data storage, and data collection. Cryptocurrency (crypto) is very volatile in terms of market value, which carries a host of unknowns that make it difficult to predict and analyze the future prices of crypto. However, cryptocurrency behaves similarly to stocks, which allows for the use of linear regression models to make predictions about price levels. With the ability to predict crypto prices, one can make a prediction for crypto stocks since the popular coin, Bitcoin, affects stock prices. This paper will discuss the use of two types of linear regression models, least squares and auto regression, as well as predictors such as social media and economic data to calculate the volatility of a given cryptocurrency and its prices. Using high performance computing techniques will allow regression models to predict relatively accurate crypto prices and past available cryptocurrency price data will be used to verify our results
El desenlace de un viaje. La expansión de las ciudades distópicas
This document is a journey through imaginary
cities, cities that are or were, through pollution,
decadence, and the inevitable end of today's
society if no action is taken. Starting from Ítalo
Calvino's The imaginary Cities, a series of
watercolor illustrations are made representing
different social and environmental problems.
These problems are described and specified,
together with the process of making the plastic
works.Este documento es un viaje por ciudades
imaginadas, urbes que son o que fueron, a través
de la contaminación, la decadencia, y el inevitable
fin de la sociedad actual si no se actúa al respecto.
Partiendo de Las ciudades imaginarias de Ítalo
Calvino, se realizan una serie de dibujos en
acuarela que representan diferentes problemas
sociales y medioambientales.
Estos problemas son descritos y especificados,
junto con el proceso de realización de las obras
plásticas
Recharge Uncertainty Analysis of Major Aquifers in Texas
While the reduction of the groundwater available volume in the state of Texas of urban, agricultural, and industrial use has been dealt with in different ways, the first step is to assess the current and future behavior of the aquifers that supply it. For this the Texas Water Development Board created the Groundwater Availability models. This paper studies the recharge data used to build them and how the sensitivity to changes in recharge of each aquifer can affect the available groundwater statewide to point to interest aquifers that need a more in-depth recharge analysis. The reported recharge in the models was variated from 50% to 150% to determine changes in head, stored volume, and overall baseflow. The normalized variations where then compared to select the most and least recharge sensitive aquifers to perform a recharge surge reflecting that of hurricane Harvey (1000% normal recharge) in the Gulf Coast Center (Houston, Texas) to determine the behavior when subjected to atypical recharge events. Given the great geohydrological variability, not only inside the aquifers, but between the analyzed aquifers, the changes in head, volume, and baseflow do not only follow the greatest increase in recharge. The Hueco Mesilla Bolson aquifer experienced the least absolute change in mean head (0.0003% of normal head), paired with the lowest absolute change in recharge (0.004m1 y -1). However, the Edwards Balcones Fault Zone Springs (near San Antonio, Texas) experiences the largest absolute change in recharge (0.370m-1 y -1), but the Gulf Coast North experienced the largest absolute change in mean head (42% of normal head). While the differences in composition and size of the aquifers make a complete comparison difficult, the most sensitive aquifers, determined by the linear model to which head and stored volume were subjected to, were determined to be the Trinity North and the Edwards Trinity Plateau for respectively. These two can be the focus of subsequent and more localized studies to determine the feasibility of the recharge driven strategies to increase the groundwater availability of Texas
An Energy-aware, Fault-tolerant, and Robust Deep Reinforcement Learning based approach for Multi-agent Patrolling Problems
Autonomous vehicles are suited for continuous area patrolling problems.
However, finding an optimal patrolling strategy can be challenging for many
reasons. Firstly, patrolling environments are often complex and can include
unknown environmental factors. Secondly, autonomous vehicles can have failures
or hardware constraints, such as limited battery life. Importantly, patrolling
large areas often requires multiple agents that need to collectively coordinate
their actions. In this work, we consider these limitations and propose an
approach based on model-free, deep multi-agent reinforcement learning. In this
approach, the agents are trained to automatically recharge themselves when
required, to support continuous collective patrolling. A distributed
homogeneous multi-agent architecture is proposed, where all patrolling agents
execute identical policies locally based on their local observations and shared
information. This architecture provides a fault-tolerant and robust patrolling
system that can tolerate agent failures and allow supplementary agents to be
added to replace failed agents or to increase the overall patrol performance.
The solution is validated through simulation experiments from multiple
perspectives, including the overall patrol performance, the efficiency of
battery recharging strategies, and the overall fault tolerance and robustness
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