The Applicability of the Eclectic Method on the Development of the Oral Production

Developing our students\u27 English oral expression in Public Institutions is a process that needs to be carefully analyzed by teachers. It is more than selected a method, it is more than following step by step what a theory says. It is going beyond our students\u27 needs. It is a deeply study of what a student really can do and needs to learn. Based on a post-method pedagogy which provides teachers the ability to break down barriers to the imposition of a specific method and make the teaching process more effective, this paper proposes the application of the eclectic method for the development of the oral expression of public high school students encouraging teachers to see the teaching process from a different and modern perspective. By analyzing the principles and features of this method, this paper describes the research made on a Public Institution with students in third year. With the goal of improving each one of the principal components of the English oral expression: range, accuracy, fluency, pronunciation and coherence, there were used selected methods, techniques and strategies based upon the students\u27 learning styles and needs. The observation and Interview techniques were used on data collection and the parameters of Inferential and descriptive statistic were applied in order to analyze the results achieved. They showed that even though not all of the group of the students could achieve the B1 level in reference to the Common European Framework and required by the Ministry of Education, a large number of them were able to increase their English oral expression. According to this data, this paper concludes that the selection of objectives, the modern teacher‘s and student\u27s role, the use of different but selected methods, the linguistic input activation and the contextualization had a significant impact on learners´ learning

Assembly of Matted Panels with Guadua Cane (Angustifolia Kunth), for Construction of Houses in Manabi Province

In some regions of Ecuador, mainly in the rural areas, the bamboo cane (Angustifolia Kunth), is presented as a renewable natural resource par excellence, which has ecological importance, the wood obtained from this plant is used since very ancient times in the construction of Housing, its technology has not changed in several years. Its industrialization is restricted, due to different factors, mainly because the natural characteristics of the material are unknown, such as age, moisture content, soil nutrients, and treatment after cutting, among others. Knowing these elements can be implemented technologies for the cutting and sterilization of the wood obtained from these plantations and develops a national technology for the construction of housing for social use, thereby achieving an impact on society by having more comfortable, safe and economic facilities

ERP and Economic Influence on the Development of Business

The use of software in business has become very significant, thanks to this business have access to a progressive technological development, as a result you get great benefits in optimizing processes and information. This research work emphasizes on the ERP and its economic influence in business, an unknown subject for many people. The realization of this research will help understand how it has contributed ERP largely to the development of enterprises, through the creation of systems that are responsible for optimizing most processes within companies to obtain a gradual enterprise-level development. Through documentary research it has been able to gather information from scientific papers, journals, academic papers, among others, which will help to better understand the problem to find a solution. Of enterprises or industries. The result of this research shows that ERP applied in companies have largely improved the process optimization and cost reduction and improved management practices efficiency, therefore a constant business development is produced

THERMODYNAMIC PROPERTIES CALCULATION USING A MULTIOBJECTIVE APPROACH IN ESTIMATING THE PARAMETERS OF THE GEOS3C EQUATION OF STATE

Since van der Waals' first publication, a lot of equations of state have been proposed to represent the PVT behavior of pure compounds, as is the case with GEOS3C, which is a new form of generalized cubic equation of state that uses a temperature function dependent on three adjustable empirical parameters. In order to obtain the parameters that lead to the lowest errors of vapor pressure and saturated liquid volume predictions, it is possible to turn this problem into a multiobjective optimization problem. In this context, a modified MOPSO algorithm was employed. This method has the main advantage to provide a set of solutions that show the existing conflict in the attempt to minimize the properties of interest. Substances from different chemical families were used to evaluate the methodology proposed in this work and comparisons against experimental data were made. Results showed that the values obtained through multiobjective optimization for GEOS3C adjustable parameters provide better or equivalent predictions for all calculated thermodynamic properties. In addition, it was possible to observe a correlation between the parameters in the viable regions of the Pareto fronts: C1 assuming a constant value, whereas C2 and C3 are linearly dependent on each othe

Prediction of the shear strength of reinforced masonry walls using a large experimental database and artificial neural networks

This paper analyses the accuracy of a selection of expressions currently available to estimate the in-plane shear strength of reinforced masonry (RM) walls, including those presented in some international masonry codes. For this purpose, predictions of such expressions are compared with a set of xperimental results reported in the literature. The experimental database includes specimens built with ceramic bricks and concrete blocks tested in partially and fully grouted conditions, which typically present a shear failure mode. Based on the experimental data collected and using artificial neural networks (ANN), this paper presents alternative expressions to the different existing methods to predict the in-plane shear strength of RM walls. The wall aspect ratio, the axial pre-compression level on the wall, the compressive strength of masonry, as well as the amount and spacing of vertical and horizontal reinforcement throughout the wall are taken into consideration as the input parameters for the proposed expressions. The results obtained show that ANN-based proposals give good predictions and in general fit the experimental results better than other calculation methods.This work was supported by the Fondo Nacional de Ciencia y Tecnologia de Chile, (Fondecyt de Iniciacion) [grant number 11121161].Aguilar, V.; Sandoval, C.; Adam Martínez, JM.; Garzón-Roca, J.; Valdebenito, G. (2016). Prediction of the shear strength of reinforced masonry walls using a large experimental database and artificial neural networks. Structure and Infrastructure Engineering. 12(12):1661-1674. https://doi.org/10.1080/15732479.2016.1157824S16611674121

Wild dogs at stake: deforestation threatens the only Amazon endemic canid, the short-eared dog (Atelocynus microtis)

The persistent high deforestation rate and fragmentation of the Amazon forests are the main threats to their biodiversity. To anticipate and mitigate these threats, it is important to understand and predict how species respond to the rapidly changing landscape. The short-eared dog Atelocynus microtis is the only Amazon-endemic canid and one of the most understudied wild dogs worldwide. We investigated short-eared dog habitat associations on two spatial scales. First, we used the largest record database ever compiled for short-eared dogs in combination with species distribution models to map species habitat suitability, estimate its distribution range and predict shifts in species distribution in response to predicted deforestation across the entire Amazon (regional scale). Second, we used systematic camera trap surveys and occupancy models to investigate how forest cover and forest fragmentation affect the space use of this species in the Southern Brazilian Amazon (local scale). Species distribution models suggested that the short-eared dog potentially occurs over an extensive and continuous area, through most of the Amazon region south of the Amazon River. However, approximately 30% of the short-eared dog's current distribution is expected to be lost or suffer sharp declines in habitat suitability by 2027 (within three generations) due to forest loss. This proportion might reach 40% of the species distribution in unprotected areas and exceed 60% in some interfluves (i.e. portions of land separated by large rivers) of the Amazon basin. Our local-scale analysis indicated that the presence of forest positively affected short-eared dog space use, while the density of forest edges had a negative effect. Beyond shedding light on the ecology of the short-eared dog and refining its distribution range, our results stress that forest loss poses a serious threat to the conservation of the species in a short time frame. Hence, we propose a re-assessment of the short-eared dog's current IUCN Red List status (Near Threatened) based on findings presented here. Our study exemplifies how data can be integrated across sources and modelling procedures to improve our knowledge of relatively understudied species

POTENTIAL OF MULTISPECTRAL IMAGES TAKEN BY SENSORS EMBEDDED IN UAVS FOR MONITORING THE COFFEE CROP IRRIGATION

Leaf Water Potential (LWP) is an indicator widely used to understand water relations in a coffee tree. Monitoring water potential is a challenge for remote sensing using low-cost multispectral cameras, with images taken by remotely piloted aircraft. The objective of this work was to evaluate the potential of a low-cost camera to discriminate different water treatments in the coffee tree. In addition, the accuracy of models to estimate LWP in the coffee crop was evaluated. The results showed that the NDVI (Normalized Difference Vegetation Index) vegetation index was able to discriminate 61.6 % more plots in a drought regime than the Near-InfraRed (NIR) band in the rainfall regime. For LWP, the architecture that presented the best performance in the detection of water stress was for the first flight (SMOreg algorithm using as predictor variables all bands, Red, Green, and NIR, and the NDVI vegetation index) with RMSE value of 0.1880 and RMSE% of 34.18. For the second flight (Random Tree algorithm, using as predictor variables all bands and NDVI) with RMSE (0.0520) and RMSE% (32.00) values

Global and regional ecological boundaries explain abrupt spatial discontinuities in avian frugivory interactions

Species interactions can propagate disturbances across space via direct and indirect effects, potentially connecting species at a global scale. However, ecological and biogeographic boundaries may mitigate this spread by demarcating the limits of ecological networks. We tested whether large-scale ecological boundaries (ecoregions and biomes) and human disturbance gradients increase dissimilarity among plant-frugivore networks, while accounting for background spatial and elevational gradients and differences in network sampling. We assessed network dissimilarity patterns over a broad spatial scale, using 196 quantitative avian frugivory networks (encompassing 1496 plant and 1004 bird species) distributed across 67 ecoregions, 11 biomes, and 6 continents. We show that dissimilarities in species and interaction composition, but not network structure, are greater across ecoregion and biome boundaries and along different levels of human disturbance. Our findings indicate that biogeographic boundaries delineate the world’s biodiversity of interactions and likely contribute to mitigating the propagation of disturbances at large spatial scales.The authors acknowledge the following funding: University of Canterbury Doctoral Scholarship (L.P.M.); The Marsden Fund grant UOC1705 (J.M.T., L.P.M.); The São Paulo Research Foundation - FAPESP 2014/01986-0 (M.G., C.E.), 2015/15172-7 and 2016/18355-8 (C.E.), 2004/00810-3 and 2008/10154-7 (C.I.D., M.G., M.A.P.); Earthwatch Institute and Conservation International for financial support (C.I.D., M.G., M.A.P.); Carlos Chagas Filho Foundation for Supporting Research in the Rio de Janeiro State – FAPERJ grant E-26/200.610/2022 (C.E.); Brazilian Research Council grants 540481/01-7 and 304742/2019-8 (M.A.P.) and 300970/2015-3 (M.G.); Rufford Small Grants for Nature Conservation No. 22426–1 (J.C.M., I.M.), No. 9163-1 (G.B.J.) and No. 11042-1 (MCM); Universidade Estadual de Santa Cruz (Propp-UESC; No. 00220.1100.1644/10-2018) (J.C.M., I.M.); Fundação de Amparo à Pesquisa do Estado da Bahia - FAPESB (No. 0525/2016) (J.C.M., I.M.); European Research Council under the European Union’s Horizon 2020 research and innovation program (grant 787638) and The Swiss National Science Foundation (grant 173342), both awarded to C. Graham (D.M.D.); ARC SRIEAS grant SR200100005 Securing Antarctica’s Environmental Future (D.M.D.); German Science Foundation—Deutsche Forschungsgemeinschaft PAK 825/1 and FOR 2730 (K.B.G., E.L.N., M.Q., V.S., M.S.), FOR 1246 (K.B.G., M.S., M.G.R.V.) and HE2041/20-1 (F.S., M.S.); Portuguese Foundation for Science and Technology - FCT/MCTES contract CEECIND/00135/2017 and grant UID/BIA/04004/2020 (S.T.) and contract CEECIND/02064/2017 (L.P.S.); National Scientific and Technical Research Council, PIP 592 (P.G.B.); Instituto Venezolano de Investigaciones Científicas - Project 898 (V.S.D.)