Spatio-temporal variations in the urban rhythm: the travelling waves of crime

This is the final version. Available from EDP Sciences via the DOI in this record.In the last decades, the notion that cities are in a state of equilibrium with a centralised organisation has given place to the viewpoint of cities in disequilibrium and organised from bottom to up. In this perspective, cities are evolving systems that exhibit emergent phenomena built from local decisions. While urban evolution promotes the emergence of positive social phenomena such as the formation of innovation hubs and the increase in cultural diversity, it also yields negative phenomena such as increases in criminal activity. Yet, we are still far from understanding the driving mechanisms of these phenomena. In particular, approaches to analyse urban phenomena are limited in scope by neglecting both temporal non-stationarity and spatial heterogeneity. In the case of criminal activity, we know for more than one century that crime peaks during specific times of the year, but the literature still fails to characterise the mobility of crime. Here we develop an approach to describe the spatial, temporal, and periodic variations in urban quantities. With crime data from 12 cities, we characterise how the periodicity of crime varies spatially across the city over time. We confirm one-year criminal cycles and show that this periodicity occurs unevenly across the city. These ‘waves of crime’ keep travelling across the city: while cities have a stable number of regions with a circannual period, the regions exhibit non-stationary series. Our findings support the concept of cities in a constant change, influencing urban phenomena—in agreement with the notion of cities not in equilibrium.Leibniz AssociationArmy Research OfficeScience Without Borders program (CAPES, Brazil

Ácido indolbutírico, estiolamento de ramos e ferimento na base, no enraizamento de estacas lenhosas de caramboleira.

Este trabalho foi desenvolvido com o objetivo de verificar a influência do estiolamento, técnica de incisão na base da estaca e aplicação do ácido indolbutírico (AIB) no enraizamento de estacas lenhosas de caramboleira.Suplemento. Edição dos Resumos do XI Congresso Brasileiro de Fisiologia Vegetal, Gramado, set. 2007

Spatial and temporal dynamics of the abundance of crustose calcareous algae on the southernmost coral reefs of the western Atlantic (Abrolhos Bank, Brazil)

Crustose calcareous algae (CCA) constitute one of the main reef builders on the Abrolhos Bank, Brazil. Once CCA taxonomy is locally understood, differences in growth-forms may be useful for the delimitation of taxa using characteristics such as the presence or absence of surface protuberances. Here, growth-forms were used to identify and quantify the most common CCA taxa on the shallow reefs (3-10 m) of the Abrolhos Bank to determine possible changes in the CCA community over a period of 10 years, and the ecological significance of CCA to local reefs was interpreted. The CCA assemblages were surveyed from 2006-2015 by using fixed photoquadrats at four sites in the inner (10-20 km from the mainland) and mid-shelf reefs (40-75 km from the mainland). The five most common CCA taxa were Pneophyllum conicum, the Lithophyllum kaiserii / Lithophyllum sp. complex, Melyvonnea erubescens, the Hydrolithon boergesenii / Porolithon onkodes complex and Peyssonelia sp. The overall mean CCA cover on the reefs was 20%. A comparison with a previous monitoring study in the same region indicated that the CCA cover nearly doubled from 2003-2008 to 2006-2015. This study reveals that the coral-killing species P. conicum dominated CCA flora on the shallow Abrolhos reefs in the last decade, and the local specific abundance of CCA slightly fluctuated over time and was species-and site-specific. The information obtained in this study contributes to the understanding of the ecology of the key calcifying components of the Abrolhos reefs and provides a useful baseline for exploring the responses of CCA to future environmental changes.PELDMudancas Climaticas scientific programmes of the Brazilian National Science Agency (CNPq)Brazilian IODP Program (CAPES/MEC)P&D Program ANP/BrasoilFAPERJDiretoria Pesquisa Cient, Inst Pesquisas, Jardim Bot Rio De Janeiro, Rua Pacheco Leao 915, BR-22460030 Rio De Janeiro, RJ, BrazilUniv Fed Rio de Janeiro, Inst Biol, BR-21941599 Rio De Janeiro, RJ, BrazilUniv Fed Espirito Santo, Dept Oceanog, Ave Fernando Ferrari 514, BR-29090600 Vitoria, ES, BrazilUniv Fed Sao Paulo, Inst Mar, Campus Baixada Santista, BR-11030400 Santos, SP, BrazilUniv Fed Paraiba, Ctr Ciencias Aplicadas & Educ, Campus 4 Litoral Norte, BR-58297000 Rio Tinto, PB, BrazilUniv Fed Sao Paulo, Inst Mar, Campus Baixada Santista, BR-11030400 Santos, SP, BrazilANP/Brasoil: 48610.011015/2014-55Web of Scienc

Uncovering the social interaction network in swarm intelligence algorithms

This is the final version. Available from the publisher via the DOI in this record.Swarm intelligence is the collective behavior emerging in systems with locally interacting components. Because of their self-organization capabilities, swarm-based systems show essential properties for handling real-world problems, such as robustness, scalability, and flexibility. Yet, we fail to understand why swarm-based algorithms work well, and neither can we compare the various approaches in the literature. The absence of a common framework capable of characterizing these several swarm-based algorithms, transcending their particularities, has led to a stream of publications inspired by different aspects of nature without a systematic comparison over existing approaches. Here we address this gap by introducing a network-based framework—the swarm interaction network—to examine computational swarm-based systems via the optics of the social dynamics. We investigate the structure of social interaction in four swarm-based algorithms, showing that our approach enables researchers to study distinct algorithms from a common viewpoint. We also provide an in-depth case study of the Particle Swarm Optimization, revealing that different communication schemes tune the social interaction in the swarm, controlling the swarm search mode. With the swarm interaction network, researchers can study swarm algorithms as systems, removing the algorithm particularities from the analyses while focusing on the structure of the swarm social interaction

Human-machine interfaces based on EMG and EEG applied to robotic systems

<p>Abstract</p> <p>Background</p> <p>Two different Human-Machine Interfaces (HMIs) were developed, both based on electro-biological signals. One is based on the EMG signal and the other is based on the EEG signal. Two major features of such interfaces are their relatively simple data acquisition and processing systems, which need just a few hardware and software resources, so that they are, computationally and financially speaking, low cost solutions. Both interfaces were applied to robotic systems, and their performances are analyzed here. The EMG-based HMI was tested in a mobile robot, while the EEG-based HMI was tested in a mobile robot and a robotic manipulator as well.</p> <p>Results</p> <p>Experiments using the EMG-based HMI were carried out by eight individuals, who were asked to accomplish ten eye blinks with each eye, in order to test the eye blink detection algorithm. An average rightness rate of about 95% reached by individuals with the ability to blink both eyes allowed to conclude that the system could be used to command devices. Experiments with EEG consisted of inviting 25 people (some of them had suffered cases of meningitis and epilepsy) to test the system. All of them managed to deal with the HMI in only one training session. Most of them learnt how to use such HMI in less than 15 minutes. The minimum and maximum training times observed were 3 and 50 minutes, respectively.</p> <p>Conclusion</p> <p>Such works are the initial parts of a system to help people with neuromotor diseases, including those with severe dysfunctions. The next steps are to convert a commercial wheelchair in an autonomous mobile vehicle; to implement the HMI onboard the autonomous wheelchair thus obtained to assist people with motor diseases, and to explore the potentiality of EEG signals, making the EEG-based HMI more robust and faster, aiming at using it to help individuals with severe motor dysfunctions.</p

Estiolamento, incisão na base da estaca e uso do ácido indolbutírico na propagação da caramboleira por estacas lenhosas.

Objetivou-se, neste trabalho, avaliar o efeito do estiolamento, da incisão na base da estaca e do tratamento com ácidoindolbutírico (AIB) no enraizamento de estacas lenhosas de caramboleira. As estacas foram padronizadas com um par de folhasinteiras e 12 cm de comprimento

Predicting Thermoelectric Power Plants Diesel/Heavy Fuel Oil Engine Fuel Consumption Using Univariate Forecasting and XGBoost Machine Learning Models

Monitoring and controlling thermoelectric power plants (TPPs) operational parameters have become essential to ensure system reliability, especially in emergencies. Due to system complexity, operating parameters control is often performed based on technical know-how and simplified analytical models that can result in limited observations. An alternative to this task is using time series forecasting methods that seek to generalize system characteristics based on past information. However, the analysis of these techniques on large diesel/HFO engines used in Brazilian power plants under the dispatch regime has not yet been well-explored. Therefore, given the complex characteristics of engine fuel consumption during power generation, this work aimed to investigate patterns generalization abilities when linear and nonlinear univariate forecasting models are used on a representative database related to an engine-driven generator used in a TPP located in Pernambuco, Brazil. Fuel consumption predictions based on artificial neural networks were directly compared to XGBoost regressor adaptation to perform this task as an alternative with lower computational cost. AR and ARIMA linear models were applied as a benchmark, and the PSO optimizer was used as an alternative during model adjustment. In summary, it was possible to observe that AR and ARIMA-PSO had similar performances in operations and lower error distributions during full-load power output with normal error frequency distribution of −0.03 ± 3.55 and 0.03 ± 3.78 kg/h, respectively. Despite their similarities, ARIMA-PSO achieved better adherence in capturing load adjustment periods. On the other hand, the nonlinear approaches NAR and XGBoost showed significantly better performance, achieving mean absolute error reductions of 42.37% and 30.30%, respectively, when compared with the best linear model. XGBoost modeling was 8.7 times computationally faster than NAR during training. The nonlinear models were better at capturing disturbances related to fuel consumption ramp, shut-down, and sudden fluctuations steps, despite being inferior in forecasting at full-load, especially XGBoost due to its high sensitivity with slight fuel consumption variations

The scaling of crime concentration in cities

All crime data are official open data sets that are available as described in the Supporting Information file available at https://doi.org/10.1371/journal.pone.0183110.s001Crime is a major threat to society’s well-being but lacks a statistical characterization that could lead to uncovering some of its underlying mechanisms. Evidence of nonlinear scaling of urban indicators in cities, such as wages and serious crime, has motivated the understanding of cities as complex systems - a perspective that offers insights into resources limits and sustainability, but that usually neglects details of the indicators themselves. Notably, since the nineteenth century, criminal activities have been known to occur unevenly within a city; crime concentrates in such way that most of the offenses take place in few regions of the city. Though confirmed by different studies, this concentration lacks broad analyses on its characteristics, which hinders not only the comprehension of crime dynamics but also the proposal of sounding counter-measures. Here, we developed a framework to characterize crime concentration which divides cities into regions with the same population size. We used disaggregated criminal data from 25 locations in the U.S. and the U.K., spanning from 2 to 15 years of longitudinal data. Our results confirmed that crime concentrates regardless of city and revealed that the level of concentration does not scale with city size. We found that the distribution of crime in a city can be approximated by a power-law distribution with exponent α that depends on the type of crime. In particular, our results showed that thefts tend to concentrate more than robberies, and robberies more than burglaries. Though criminal activities present regularities of concentration, we found that criminal ranks have the tendency to change continuously over time - features that support the perspective of crime as a complex system and demand analyses and evolving urban policies covering the city as a whole.CAPES FoundationArmy Research Offic