Weather impacts expressed sentiment

We conduct the largest ever investigation into the relationship between meteorological conditions and the sentiment of human expressions. To do this, we employ over three and a half billion social media posts from tens of millions of individuals from both Facebook and Twitter between 2009 and 2016. We find that cold temperatures, hot temperatures, precipitation, narrower daily temperature ranges, humidity, and cloud cover are all associated with worsened expressions of sentiment, even when excluding weather-related posts. We compare the magnitude of our estimates with the effect sizes associated with notable historical events occurring within our data.This work was supported by Ministerio de Economía y Competitividad: FIS2013-47532-C3-3-P, FIS2016-78904-C3-3-P (http://www.mineco.gob.es/); and National Science Foundation DGE0707423, TG-SES130013, 0903551 (https://www.nsf.gov/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Oprimización y paralelización de un algoritmo de sincronización mediante el uso de GPUs y la tecnología CUDA

En el presente documento se hablará acerca del desarrollo de un proyecto para la mejora de un programa de análisis de señales; con ese fin, se hará uso de técnicas de optimización del software y de tecnologías de aceleración, mediante el aprovechamiento del paralelismo del programa. Además se hará un análisis de acerca del uso de dos tecnologías basadas en diferentes paradigmas de programación paralela; una mediante múltiples hilos con memoria compartida y la otra mediante el uso de GPUs como dispositivos de coprocesamiento. This paper will talk about the development of a Project to improve a program that does signals analysis; to that end, it will make use of software optimization techniques and acceleration technologies by exploiting parallelism in the program. In Addition will be done an analysis on the use of two technologies based on two different paradigms; one using multiple threads with shared memory and the other using GPU as co-processing devices

Rapid assessment of disaster damage using social media activity

Could social media data aid in disaster response and damage assessment? Countries face both an increasing frequency and an increasing intensity of natural disasters resulting from climate change. During such events, citizens turn to social media platforms for disaster-related communication and information. Social media improves situational awareness, facilitates dissemination of emergency information, enables early warning systems, and helps coordinate relief efforts. In addition, the spatiotemporal distribution of disaster-related messages helps with the real-time monitoring and assessment of the disaster itself. We present a multiscale analysis of Twitter activity before, during, and after Hurricane Sandy. We examine the online response of 50 metropolitan areas of the United States and find a strong relationship between proximity to Sandy's path and hurricane-related social media activity. We show that real and perceived threats, together with physical disaster effects, are directly observable through the intensity and composition of Twitter's message stream. We demonstrate that per-capita Twitter activity strongly correlates with the per-capita economic damage inflicted by the hurricane. We verify our findings for a wide range of disasters and suggest that massive online social networks can be used for rapid assessment of damage caused by a large-scale disaster.Publicad

Optimizing humanitarian aids : formulating influencer advertisement in social networks

In order to solve problems encountered during natural disasters, in addition to NGOs and relief teams, various individuals intend to help the injured. Although the cooperation of people has remarkable advantages, the disparity between the needs of the injured and the people’s donations can cause problems such as trouble for relief teams and wasting the substantial resources. In generic, the influencer selection in the marketing endeavors is mainly aimed to maximize people’s awareness and attention, but this research proposes a method for influencer selection, using Social Network Analysis (SNA) and optimization techniques, by which it is possible to establish an adaptation between the public attention and the type of injured necessities. The proposed method is applied to a real sample network of Facebook friends, to evaluate the efficiency and validity of the formulated method

Отбор информативных геометрических признаков ядер клеток на люминесцентных изображениях раковых клеток

The methods of geometric informative features selection of nuclei on fluorescent images of cancer cells are considered. During the survey, a review of existing geometric features was carried out, including both the signs of rotation resisted shape and displacement of the image, as well as signs of location in space. For the selection of characteristics, the methods were used: median, correlation with calculation of the Pearson correlation coefficient, correlation with calculation of the Spearman correlation coefficient, logistic regression model, random forest with CART trees and Gini criterion, random forest with CART trees and error minimization criterion. As a result of the investigation 11 characteristics were selected from 59 features, the quality of classification and time costs were calculated depending on the number of features for describing the objects. The use of 11 features is sufficient for the accuracy of classification as it allows to reduce time costs in 2,3 times.Рассмотрены методы отбора информативных признаков для выделения геометрических признаков при описании ядер на люминесцентных изображениях раковых клеток. Выполнен обзор существующих геометрических признаков, который включает в себя как признаки формы, устойчивые к повороту и перемещению изображения, так и признаки расположения в пространстве. Для отбора наиболее информативных признаков использованы шесть методов: медианный, корреляционный с расчетом коэффициента корреляции по Пирсону, корреляционный с расчетом коэффициента корреляции по Спирмену, метод логистической регрессии, случайного леса с CART-деревьями и критерием Gini, случайного леса с CART-деревьями и критерием минимизации ошибки. В результате исследования из 59 признаков отобраны 11 наиболее информативных, выполнен анализ качества классификации с помощью метода случайного леса и рассчитаны временные затраты в зависимости от количества признаков для описания объектов. Для метода случайного леса использование 11 признаков является достаточным по точности классификации и позволяет снизить временные затраты в 2,3 раза

ЗОЛЬ-ГЕЛЬ СИНТЕЗ И ЛЮМИНЕСЦЕНЦИЯ ПЛЕНОЧНЫХ СТРУКТУР, СОДЕРЖАЩИХ ИТТРИЙ-АЛЮМИНИЕВЫЙ ГРАНАТ, ЛЕГИРОВАННЫЙ ТЕРБИЕМ

The results of synthesis and analysis of the film structures fabricated from suspensions based on titanium dioxide sol and terbium-doped yttrium aluminum composite powder are presented. The film structures comprising titania with terbium-doped yttrium aluminum garnet grains were fabricated by sol-gel method on the textured aluminum foil. The synthesized samples reveal strong room temperature terbium photoluminescence with the most intensive band at 543 nm.Приведены результаты синтеза и анализа пленочных структур, изготовленных из суспензии на основе золя диоксида титана и легированного тербием порошка иттрий-алюминиевого граната, полученного золь-гель методом, на подложке из текстурированной алюминиевой фольги. Синтезированные образцы демонстрируют интенсивную фотолюминесценцию тербия с наиболее интенсивной полосой с максимумом 543 нм

Crowdsourcing Methods for Data Collection in Geophysics: State of the Art, Issues, and Future Directions

Data are essential in all areas of geophysics. They are used to better understand and manage systems, either directly or via models. Given the complexity and spatiotemporal variability of geophysical systems (e.g., precipitation), a lack of sufficient data is a perennial problem, which is exacerbated by various drivers, such as climate change and urbanization. In recent years, crowdsourcing has become increasingly prominent as a means of supplementing data obtained from more traditional sources, particularly due to its relatively low implementation cost and ability to increase the spatial and/or temporal resolution of data significantly. Given the proliferation of different crowdsourcing methods in geophysics and the promise they have shown, it is timely to assess the state‐of‐the‐art in this field, to identify potential issues and map out a way forward. In this paper, crowdsourcing‐based data acquisition methods that have been used in seven domains of geophysics, including weather, precipitation, air pollution, geography, ecology, surface water and natural hazard management are discussed based on a review of 162 papers. In addition, a novel framework for categorizing these methods is introduced and applied to the methods used in the seven domains of geophysics considered in this review. This paper also features a review of 93 papers dealing with issues that are common to data acquisition methods in different domains of geophysics, including the management of crowdsourcing projects, data quality, data processing and data privacy. In each of these areas, the current status is discussed and challenges and future directions are outlined