De retibus socialibus et legibus momenti

Online Social Networks (OSNs) are a cutting edge topic. Almost everybody --users, marketers, brands, companies, and researchers-- is approaching OSNs to better understand them and take advantage of their benefits. Maybe one of the key concepts underlying OSNs is that of influence which is highly related, although not entirely identical, to those of popularity and centrality. Influence is, according to Merriam-Webster, "the capacity of causing an effect in indirect or intangible ways". Hence, in the context of OSNs, it has been proposed to analyze the clicks received by promoted URLs in order to check for any positive correlation between the number of visits and different "influence" scores. Such an evaluation methodology is used in this paper to compare a number of those techniques with a new method firstly described here. That new method is a simple and rather elegant solution which tackles with influence in OSNs by applying a physical metaphor.Comment: Changes made for third revision: Brief description of the dataset employed added to Introduction. Minor changes to the description of preparation of the bit.ly datasets. Minor changes to the captions of Tables 1 and 3. Brief addition in the Conclusions section (future line of work added). Added references 16 and 18. Some typos and grammar polishe

Macrosintaxis y enunciación. Análisis pragmalingüístico de «digo», «digo yo», «ya digo» y «ya te digo»

The verb decir has two characteristics that increase the interest of its study: it reflects the enunciation process and it is one of the most productive bases for the creation of discursive markers. This work addresses to the pragmalinguistic analysis of four of them: digo, digo yo, ya digo and ya te digo. All of them are conjugated in the first person singular of the present indicative. However, there are some variations that cause them to belong to different categories (markers or operators) and also work in different macrostructures (enunciation, modality, assertion, informative structuring). The analysis carried out identifies the above divergences, indicating to which grammatical category they belong (operators or connectors), and describing their operation in the different levels of discourse. The ultimate goal is to contribute to the macrosyntactic description of the current Spanish language.El verbo decir, como reflejo del proceso de enunciación, es una de las bases más productivas para la creación de marcadores discursivos. Este trabajo aborda el análisis pragmalingüístico de cuatro de ellos: digo, digo yo, ya digo y ya te digo. Todos ellos presentan dicho verbo metalingüístico conjugado en primera persona del singular del presente de indicativo. Sin embargo, existen variaciones que causan que pertenezcan a categorías distintas (marcadores u operadores) y funcionen también en macroestructuras diferentes (enunciación, modalidad, aserción, estructuración informativa). El análisis realizado identifica tales divergencias, indicando a qué categoría gramatical pertenecen (operadores o conectores), y describiendo su funcionamiento en los distintos planos del discurso. La meta última es contribuir a la descripción macrosintáctica del español actual

Picture Power? The Contribution of Visuals and Text to Partisan Selective Exposure

Today’s high-choice media environment allows citizens to select news in line with their political preferences and avoid content counter to their priors. So far, however, selective exposure research has exclusively studied news selection based on textual cues, ignoring the recent proliferation of visual media. This study aimed to identify the contribution of visuals alongside text in selective exposure to pro-attitudinal, counter-attitudinal and balanced content. Using two experiments, we created a social media-style newsfeed with news items comprising matching and non-matching images and headlines about the contested issues of immigration and gun control in the U.S. By comparing selection behavior of participants with opposing prior attitudes on these topics, we pulled apart the contribution of images and headlines to selective exposure. Findings show that headlines play a far greater role in guiding selection, with the influence of images being minimal. The additional influence of partisan source cues is also considered

A Change in Perspective: Agriculturally -Based Study Abroad Experience for Nicaraguan Students

Study abroad experiences serve to enrich students’ educational experiences, granted these programs must be evaluated to assess educational effectiveness. The purpose of this qualitative study was toexamine Nicaraguan students’ perceptions of agriculture and future aspirations, before and after engaging in a four-day agricultural-based program. Graphic elicitation and arts-based projective techniques served as metrics to assess students’ perceptions.Four major themes, with six sub-themes emerged from the data: a) perceptions of agriculture (i.e., previous agriculture); b) strength through unity (i.e., unity; and ripple effect); c) aspirations (i.e., importance of education); d) value of experience (i.e., learning new things; and thankfulness). Overall, the Nicaraguan students indicated the study abroad experience broadened their perspective of agriculture, having a direct impact on their career aspirations

Una explicación para el desamargado natural de aceitunas Hurma durante su maduración en el árbol

Harvested olives require further processing to make them edible due to their content in the bitter substance oleuropein. However, some olives of the Erkence cultivar naturally de-bitter on the tree giving rise to the so-called Hurma olives. In this study, the evolution of the chemical characteristics of Erkence and Hurma olives harvested from the northeast and southwest area of trees located in the Karaburun Peninsula was assayed. It was confirmed that the oleuropein content in Hurma olives was much lower (< 2000 mg/kg fresh weight) than Erkence, which reached 35.000 mg/kg fresh weight at the beginning of the season. In addition, no free or polymerized anthocyanins were found in Hurma fruit in contrast to ripened Erkence fruit. The concentration of glucose was also lower in Hurma than Erkence olives. These results suggest that the enzymatic oxidation of oleuropein could be responsible for the natural de-bittering of Hurma olives during their ripening on the tree.Las aceitunas recién cogidas del árbol necesitan ser procesadas para hacerlas comestibles, debido a su contenido en el compuesto amargo oleuropeína. Sin embargo, algunas aceitunas de la variedad Erkence desamargan de forma natural en el árbol dando lugar a las aceitunas conocidas como Hurma. En este trabajo se han analizado las características químicas de aceitunas Erkence y Hurma recolectadas de la zona noreste y suroeste de árboles situados en la provincia de Karaburun. Se ha confirmado que el contenido en oleuropeína de aceitunas Hurma es muy inferior (< 2000 mg/kg) que Erkence, las cuales alcanzaron una concentración en dicha sustancia hasta de 35.000 mg/kg al principio del periodo de maduración. Además, no se encontraron en aceitunas Hurma antocianinas ni libres ni polimerizadas, a diferencia de Erkence. Estos resultados indican que la oxidación enzimática de la oleuropeína podría ser la responsable de la eliminación del amargor de forma natural en aceitunas Hurma durante su maduración en el árbol

INDIGO : better geomagnetic observatories where we need them

The INDIGO project aims to improve the global coverage of digital observatories by deploying digital magnetometer systems in: i) Observatories where existing analog recording equipment is in need of upgrading. ii) Newly established digital observatories. iii) Existing digital observatories for the purpose of quality control and redundancy. In implementing the project and selecting suitable sites, special attention is paid to parts of the Earth devoid of magnetic observatories, increasing the reliability and long-term operation of existing observatories and cost-effective use of local resources. The Poster reviews the current status of the project. We examine the different steps and initiatives taken since the initiation of INDIGO in 2004 and assess their effectiveness in achieving progress towards our aims of improving global coverage and enhanced data quality

About identification of features that affect the estimation of citrus harvest

Accurate models for early harvest estimation in citrus production generally involve expensive variables. The goal of this research work was to develop a model to provide early and accurate estimations of harvest using low-cost features. Given the original data may derive from tree measurements, meteorological stations, or satellites, they have varied costs. The studied orchards included tangerines (Citrus reticulata x C. sinensis) and sweet oranges (C. sinensis) located in northeastern Argentina. Machine learning methods combined with different datasets were tested to obtain the most accurate harvest estimation. The final model is based on support vector machines with low-cost variables like species, age, irrigation, red and near-infrared reflectance in February and December, NDVI in December, rain during ripening, and humidity during fruit growth. Highlights: Red and near-infrared reflectance in February and December are helpful values to predict orange harvest. SVM is an efficient method to predict harvest. A ranking method to A ranking-based method has been developed to identify the variables that best predict orange production.  Accurate models for early harvest estimation in citrus production generally involve expensive variables. The goal of this research work was to develop a model to provide early and accurate estimations of harvest using low-cost features. Given the original data may derive from tree measurements, meteorological stations, or satellites, they have varied costs. The studied orchards included tangerines (Citrus reticulata x C. sinensis) and sweet oranges (C. sinensis) located in northeastern Argentina. Machine learning methods combined with different datasets were tested to obtain the most accurate harvest estimation. The final model is based on support vector machines with low-cost variables like species, age, irrigation, red and near-infrared reflectance in February and December, NDVI in December, rain during ripening, and humidity during fruit growth. Highlights: Red and near-infrared reflectance in February and December are helpful values to predict orange harvest. SVM is an efficient method to predict harvest. A ranking method to A ranking-based method has been developed to identify the variables that best predict orange production

Insights on Hydrothermal‐Magmatic Interactions and Eruptive Processes at Poás Volcano (Costa Rica) From High‐Frequency Gas Monitoring and Drone Measurements

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