Discutindo a educação ambiental no cotidiano escolar: desenvolvimento de projetos na escola formação inicial e continuada de professores

A presente pesquisa buscou discutir como a Educação Ambiental (EA) vem sendo trabalhada, no Ensino Fundamental e como os docentes desta escola compreendem e vem inserindo a EA no cotidiano escolar., em uma escola estadual do município de Tangará da Serra/MT, Brasil. Para tanto, realizou-se entrevistas com os professores que fazem parte de um projeto interdisciplinar de EA na escola pesquisada. Verificou-se que o projeto da escola não vem conseguindo alcançar os objetivos propostos por: desconhecimento do mesmo, pelos professores; formação deficiente dos professores, não entendimento da EA como processo de ensino-aprendizagem, falta de recursos didáticos, planejamento inadequado das atividades. A partir dessa constatação, procurou-se debater a impossibilidade de tratar do tema fora do trabalho interdisciplinar, bem como, e principalmente, a importância de um estudo mais aprofundado de EA, vinculando teoria e prática, tanto na formação docente, como em projetos escolares, a fim de fugir do tradicional vínculo “EA e ecologia, lixo e horta”.Facultad de Humanidades y Ciencias de la Educació

A line follower robot implementation using Lego's Mindstorms Kit and Q-Learning

Un problema común al trabajar con robots móviles es que la fase de programación puede ser un proceso largo, costoso y difícil para los programadores. Los Algoritmos de Aprendizaje por Refuerzo ofrecen uno de los marcos de trabajo más generales en el ámbito de aprendizaje de máquina. Este trabajo presenta un enfoque usando el algoritmo de Q-Learning en un robot Lego para que aprenda "por sí mismo" a seguir una línea negra dibujada en una superficie blanca. El entorno de programación utilizado en este trabajo es Matlab.<br>A common problem working with mobile robots is that programming phase could be a long, expensive and heavy process for programmers. The reinforcement learning algorithms offer one of the most general frameworks in learning subjects. This work presents an approach using the Q-Learning algorithm on a Lego robot in order for it to learn by itself how to follow a blackline drawn down on a white surface, using Matlab [5] as programming environment

Full Model Selection Problem and Pipelines for Time-Series Databases: Contrasting Population-Based and Single-point Search Metaheuristics

The increasing production of temporal data, especially time series, has motivated valuable knowledge to understand phenomena or for decision-making. As the availability of algorithms to process data increases, the problem of choosing the most suitable one becomes more prevalent. This problem is known as the Full Model Selection (FMS), which consists of finding an appropriate set of methods and hyperparameter optimization to perform a set of structured tasks as a pipeline. Multiple approaches (based on metaheuristics) have been proposed to address this problem, in which automated pipelines are built for multitasking without much dependence on user knowledge. Most of these approaches propose pipelines to process non-temporal data. Motivated by this, this paper proposes an architecture for finding optimized pipelines for time-series tasks. A micro-differential evolution algorithm (µ-DE, population-based metaheuristic) with different variants and continuous encoding is compared against a local search (LS, single-point search) with binary and mixed encoding. Multiple experiments are carried out to analyze the performance of each approach in ten time-series databases. The final results suggest that the µ-DE approach with rand/1/bin variant is useful to find competitive pipelines without sacrificing performance, whereas a local search with binary encoding achieves the lowest misclassification error rates but has the highest computational cost during the training stage.La creciente producción de datos temporales, especialmente de series de tiempo, ha motivado la extracción analítica de conocimiento valioso para comprender fenómenos o para la toma de decisiones. A medida que aumenta la disponibilidad de algoritmos para procesar datos, el problema de elegir el más adecuado se vuelve más frecuente. Este problema se conoce como la Selección del Modelo Completo (SMC), que consiste en encontrar un conjunto apropiado de métodos y la optimización de hiperparámetros para realizar un conjunto de tareas estructuradas como una tubería. Se han propuesto múltiples enfoques (basados en metaheurísticas) para abordar este problema, en los que se construyen tuberías automatizadas para realizar múltiples tareas sin mucha dependencia del conocimiento del usuario. La mayoría de estos enfoques proponen tuberías para procesar datos no temporales. Motivado por esto, este artículo propone una arquitectura para encontrar tuberías optimizadas para tareas de series de tiempo. El algoritmo de micro-Evolución Diferencial (µ-ED, metaheurística basada en población) con diferentes variantes y codificación continua, es comparado contra una búsqueda local (BL, búsqueda de un solo punto) con codificación binaria y mixta. Se realizan múltiples experimentos para analizar el rendimiento de cada enfoque en diez bases de datos de series de tiempo. Los resultados finales sugieren que el enfoque de µ-ED con la variante rand/1/bin es útil para encontrar tuberías competitivas sin sacrificar el rendimiento, mientras que la BL con codificación binaria logra las tasas de error de clasificación incorrecta más bajas, pero tiene el costo computacional más alto durante la etapa de entrenamiento

Análisis bayesiano de la compra de alimentos en espacios de distribución de Ciudad Guzmán, Jalisco, México

To identify and classify the distribution places where people in Ciudad Guzman buy food and why they do it, to describe how food buying practices are, it was developed, validated a questionnaire applied to 366 people between 25 and 64 years of age in the southern and Lagoon regions of Jalisco, analyzed through probabilistic statistics with a bayesian network model. The results indicate that it is purchased more frequently (38.26%) in grocery stores and in the supermarket more food groups are purchased (22.62%). The reasons for choosing an establishment and buying food were significantly (p <0.05) related to gender, the administration of the domestic economy, social aspects. Food purchases are diversified, going to traditional distribution spaces (91.09%) and modern distribution (8.91%) due to the need to eat, which goes against the trends registered in large cities.Con el fin de identificar y clasificar los lugares de distribución donde las personas de Ciudad Guzmán compran alimentos y por qué lo hacen, para describir cómo son las prácticas de compra de alimento, se elaboró y validó un cuestionario aplicado a 366 personas entre 25 y 64 años de las regiones sur y Lagunas de Jalisco, analizados con estadística-probabilística con un modelo de redes bayesianas. Los resultados indican que se compra con mayor frecuencia (38.26%) en tiendas de abarrotes y en el supermercado se compran más grupos de alimentos (22.62%). Las razones para elegir un establecimiento y comprar alimentos se relacionaron significativamente (p<0.05) con el género, la administración de la economía doméstica, aspectos sociales. Las compras de alimentos son diversificadas, se acude a espacios de distribución tradicional (91.09%) y distribución moderna (8.91%) ante la necesidad de alimentarse, lo cual va en contra de las tendencias registradas en grandes ciudades

Enhanced deuteron coalescence probability in jets

The transverse-momentum (pT) spectra and coalescence parameters B2 of (anti)deuterons are measured in pp collisions at s√=13 TeV for the first time in and out of jets. In this measurement, the direction of the leading particle with the highest pT in the event (pleadT>5 GeV/c) is used as an approximation for the jet axis. The event is consequently divided into three azimuthal regions and the jet signal is obtained as the difference between the Toward region, that contains jet fragmentation products in addition to the underlying event (UE), and the Transverse region, which is dominated by the UE. The coalescence parameter in the jet is found to be approximately a factor of 10 larger than that in the underlying event. This experimental observation is consistent with the coalescence picture and can be attributed to the smaller average phase-space distance between nucleons inside the jet cone as compared to the underlying event. The results presented in this Letter are compared to predictions from a simple nucleon coalescence model, where the phase space distributions of nucleons are generated using PYTHIA 8 with the Monash 2013 tuning, and to predictions from a deuteron production model based on ordinary nuclear reactions with parametrized energy-dependent cross sections tuned on data. The latter model is implemented in PYTHIA 8.3. Both models reproduce the observed large difference between in-jet and out-of-jet coalescence parameters, although the almost flat trend of the BJet2 is not reproduced by the models, which instead give a decreasing trend

Measurement of the radius dependence of charged-particle jet suppression in Pb–Pb collisions at √sNN = 5.02 TeV

The ALICE Collaboration reports a differential measurement of inclusive jet suppression using pp and Pb−Pb collision data at a center-of-mass energy per nucleon-nucleon collision sNN−−−√=5.02 TeV. Charged-particle jets are reconstructed using the anti-kT algorithm with resolution parameters R= 0.2, 0.3, 0.4, 0.5, and 0.6 in pp collisions and R= 0.2, 0.4, 0.6 in central (0−10%), semi-central (30−50%), and peripheral (60−80%) Pb−Pb collisions. A novel approach based on machine learning is employed to mitigate the influence of jet background. This enables measurements of inclusive jet suppression in new regions of phase space, including down to the lowest jet pT≥40 GeV/c at R=0.6 in central Pb−Pb collisions. This is an important step for discriminating different models of jet quenching in the quark-gluon plasma. The transverse momentum spectra, nuclear modification factors, derived cross section, and nuclear modification factor ratios for different jet resolution parameters of charged-particle jets are presented and compared to model predictions. A mild dependence of the nuclear modification factor ratios on collision centrality and resolution parameter is observed. The results are compared to a variety of jet-quenching models with varying levels of agreement

First measurement of prompt and non-prompt D⁎+ vector meson spin alignment in pp collisions at <math altimg="si1.svg"><msqrt><mrow><mi>s</mi></mrow></msqrt><mo linebreak="goodbreak" linebreakstyle="after">=</mo><mn>13</mn></math> TeV

International audienceThis letter reports the first measurement of spin alignment, with respect to the helicity axis, for D⁎+ vector mesons and their charge conjugates from charm-quark hadronisation (prompt) and from beauty-meson decays (non-prompt) in hadron collisions. The measurements were performed at midrapidity (|y|&lt;0.8) as a function of transverse momentum (pT) in proton–proton (pp) collisions collected by ALICE at the centre-of-mass energy s=13TeV. The diagonal spin density matrix element ρ00 of D⁎+ mesons was measured from the angular distribution of the D⁎+→D0(→K−π+)π+ decay products, in the D⁎+ rest frame, with respect to the D⁎+ momentum direction in the pp centre of mass frame. The ρ00 value for prompt D⁎+ mesons is consistent with 1/3, which implies no spin alignment. However, for non-prompt D⁎+ mesons an evidence of ρ00 larger than 1/3 is found. The measured value of the spin density element is ρ00=0.455±0.022(stat.)±0.035(syst.) in the 5&lt;pT&lt;20GeV/c interval, which is consistent with a Pythia 8 Monte Carlo simulation coupled with the EvtGen package, which implements the helicity conservation in the decay of D⁎+ meson from beauty mesons. In non-central heavy-ion collisions, the spin of the D⁎+ mesons may be globally aligned with the direction of the initial angular momentum and magnetic field. Based on the results for pp collisions reported in this letter it is shown that alignment of non-prompt D⁎+ mesons due to the helicity conservation coupled to the collective anisotropic expansion may mimic the signal of global spin alignment in heavy-ion collisions

Measurement of the radius dependence of charged-particle jet suppression in Pb–Pb collisions at <math altimg="si1.svg"><msqrt><mrow><msub><mrow><mi>s</mi></mrow><mrow><mi mathvariant="normal">NN</mi></mrow></msub></mrow></msqrt><mo linebreak="goodbreak" linebreakstyle="after">=</mo><mn>5.02</mn><mspace width="0.25em"/><mtext>TeV</mtext></math>

International audienceThe ALICE Collaboration reports a differential measurement of inclusive jet suppression using pp and Pb–Pb collision data at a center-of-mass energy per nucleon–nucleon collision sNN=5.02 TeV. Charged-particle jets are reconstructed using the anti-kT algorithm with resolution parameters R=0.2, 0.3, 0.4, 0.5, and 0.6 in pp collisions and R=0.2, 0.4, 0.6 in central (0–10%), semi-central (30–50%), and peripheral (60–80%) Pb–Pb collisions. A novel approach based on machine learning is employed to mitigate the influence of jet background. This enables measurements of inclusive jet suppression in new regions of phase space, including down to the lowest jet pT≥40 GeV/c at R=0.6 in central Pb–Pb collisions. This is an important step for discriminating different models of jet quenching in the quark–gluon plasma. The transverse momentum spectra, nuclear modification factors, derived cross section, and nuclear modification factor ratios for different jet resolution parameters of charged-particle jets are presented and compared to model predictions. A mild dependence of the nuclear modification factor ratios on collision centrality and resolution parameter is observed. The results are compared to a variety of jet-quenching models with varying levels of agreement

Enhanced deuteron coalescence probability in jets

The transverse-momentum ($p_{\rm T}$) spectra and coalescence parameters $B_2$ of (anti)deuterons are measured in pp collisions at $\sqrt{s} = 13$ TeV in and out of jets. In this measurement, the direction of the leading particle with the highest $p_{\rm T}$ in the event ($p_{\rm T}^{\rm{ lead}} > 5$ GeV/$c$) is used as an approximation for the jet axis. The event is consequently divided into three azimuthal regions and the jet signal is obtained as the difference between the Toward region, that contains jet fragmentation products in addition to the underlying event (UE), and the Transverse region, which is dominated by the UE. The coalescence parameter in the jet is found to be approximately a factor of 10 larger than that in the underlying event. This experimental observation is consistent with the coalescence picture and can be attributed to the smaller average phase-space distance between nucleons inside the jet cone as compared to the underlying event. The results presented in this Letter are compared to predictions from a simple nucleon coalescence model, where the phase space distributions of nucleons are generated using PYTHIA 8 with the Monash 2013 tuning, and to predictions from a deuteron production model based on ordinary nuclear reactions with parametrized energy-dependent cross sections tuned on data. The latter model is implemented in PYTHIA 8.3. Both models reproduce the observed large difference between in-jet and out-of-jet coalescence parametersThe transverse-momentum (pT) spectra and coalescence parameters B2 of (anti)deuterons are measured in p-p collisions at s=13  TeV for the first time in and out of jets. In this measurement, the direction of the leading particle with the highest pT in the event (pTlead&gt;5  GeV/c) is used as an approximation for the jet axis. The event is consequently divided into three azimuthal regions, and the jet signal is obtained as the difference between the toward region, that contains jet fragmentation products in addition to the underlying event (UE), and the transverse region, which is dominated by the UE. The coalescence parameter in the jet is found to be approximately a factor of 10 larger than that in the underlying event. This experimental observation is consistent with the coalescence picture and can be attributed to the smaller average phase-space distance between nucleons in the jet cone as compared with the underlying event. The results presented in this Letter are compared to predictions from a simple nucleon coalescence model, where the phase-space distributions of nucleons are generated using pythia8 with the Monash 2013 tuning, and to predictions from a deuteron production model based on ordinary nuclear reactions with parametrized energy-dependent cross sections tuned on data. The latter model is implemented in pythia8.3. Both models reproduce the observed large difference between in-jet and out-of-jet coalescence parameters, although the almost flat trend of the B2Jet is not reproduced by the models, which instead give a decreasing trend.The transverse-momentum ($p_{\rm T}$) spectra and coalescence parameters $B_2$ of (anti)deuterons are measured in pp collisions at $\sqrt{s} = 13$ TeV for the first time in and out of jets. In this measurement, the direction of the leading particle with the highest $p_{\rm T}$ in the event ($p_{\rm T}^{\rm{ lead}} > 5$ GeV/$c$) is used as an approximation for the jet axis. The event is consequently divided into three azimuthal regions and the jet signal is obtained as the difference between the Toward region, that contains jet fragmentation products in addition to the underlying event (UE), and the Transverse region, which is dominated by the UE. The coalescence parameter in the jet is found to be approximately a factor of 10 larger than that in the underlying event. This experimental observation is consistent with the coalescence picture and can be attributed to the smaller average phase-space distance between nucleons inside the jet cone as compared to the underlying event. The results presented in this Letter are compared to predictions from a simple nucleon coalescence model, where the phase space distributions of nucleons are generated using PYTHIA 8 with the Monash 2013 tuning, and to predictions from a deuteron production model based on ordinary nuclear reactions with parametrized energy-dependent cross sections tuned on data. The latter model is implemented in PYTHIA 8.3. Both models reproduce the observed large difference between in-jet and out-of-jet coalescence parameters, although the almost flat trend of the $B^{\rm Jet}_2$ is not reproduced by the models, which instead give a decreasing trend