The Poetry of Travel in Mario Campana: A Theoretical Approach

Mario Campana’s poetry is one of the most representative of contemporary Ecuador. This document aims to carry out a conceptual review based on different authors that exposes the importance of the work mentioned in the context of national letters. In the aforementioned context, a reflection on poetry is proposed, with a continuous line throughout its journey through successive books by the author. This article intends from a descriptive-exploratory nature, to present a rereading of the work through analysts who account for its connection with the trip. Keywords: Ecuadorian poetry, Mario Campana, trip Resumen: La poesía de Mario Campaña es una de las más representativas del Ecuador contemporáneo. El objetivo del presente documento es efectuar una revisión conceptual a base de distintos autores, que expone la importancia de la obra mencionada en el contexto de las letras nacionales. En el contexto mencionado, se plantea una reflexión sobre la poesía y un línea continua a lo largo de su recorrido a través de sucesivos libros del autor. El presente artículo pretende, desde un carácter descriptivo-exploratorio, presentar una relectura de la obra a través de analistas que dan cuenta de su vinculación con el viaje. Palabras Clave: poesia ecuatoriana, Mario Campana, viaj

SME food suppliers versus large retailers: perspectives in the international supply chains

none3noThe market share of international retail chains substantially increased from the beginning of the nineties. The supplier’s market has been adapted to the evolutions of retailers’ market in terms of modified purchasing processes. The concentration of large food retailers has been much faster than the same process among manufacturers. Due to these changes, the requirements towards food industry suppliers grew in number and quality. Thus it is generally true that the nature of the buyer-supplier relationship in retailing has been undergoing dramatic changes. Important literature has described these emerging relationships as "partnerships" or "strategic alliances," as opposed to the traditional "arm's length" type of associations. But these conditions are likely to change especially in the relationships between small and medium suppliers and large retailers. The paper shows how the relationships between suppliers and retailers are experiencing several important changes, above all at international level. In particular, the analysis is focused on the Italian food SME suppliers related with international large retailers. Considering the focus of this paper, in-depth interviews to 28 Italian food SME suppliers have been conducted in early 2007. Results have been analyzed and compared to the retailers’ point of view, resulting from public reports (such as Annual report, CSR report, etc.) to understand retail companies’ approach to SME suppliers. Considering the main topics of such relations and the selection criteria used by retailers, one of the main results of the analysis is that the unbalance of power in the relation is not necessarily a negative condition, as the growth of SME suppliers is stimulated by an improving attitude to operate with large retailers. Retailers reserve a wide space on their shelves to SME references because they contribute to increase the variety of merchandising and ensure a more tight control on the supply chain (traceability). At the same time, the strong pressure on price and the required organizational qualifications lead to a selection process, in which smaller manufacturers seem to be the more vulnerable actors.openC. Pepe; F. Musso; M. RissoC., Pepe; Musso, Fabio; M., Riss

Étude comparée des communautés benthiques et ripicoles endogées d'un réseau méditerranéen perturbé : l'Arc (Bouches-du-Rhône, France)

L'utilisation des méthodes biologiques et plus particulièrement l'étude des communautés benthiques pour l'appréciation de la qualité des eaux est actuellement d'un usage général. L'impact des perturbations des milieux peut être déduit de la composition et de la structure des peuplements qu'ils hébergent. En est-il de même pour les peuplements d'invertébrés ripicoles endogés humides, soumis moins directement à t'influence du milieu aquatique? Pour répondre à cette question une étude comparée (par analyse factorielle des correspondances) a été entreprise sur le réseau hydrographique d'une rivière de la région méditerranéenne, l'Arc, présentant des situations hydrochimiques variées.L'A.F.C., à partir de l'axe I, sépare les prélèvements d'invertébrés benthiques des prélèvements d'invertébrés ripicoles. Sur l'axe II les couples, prélèvement benthique - prélèvement ripicole de chaque station, possèdent sensiblement la même valeur sur l'axe et s'ordonnent selon un gradient de trophie croissant de l'amont vers l'aval. Les communautés ripicoles endogées humides peuvent donc être considérées comme des bio-indicateurs de la chimie de l'eau de la même manière que les communautés benthiques. Par contre le facteur temporarité (axe III) a une influence plus importante sur les communautés benthiques que sur les communautés ripicoles.L'examen de la répartition des taxons sur les axes factoriels a permis de déterminer un certain nombre d'espèces qui, tout en étant représentées dans les 2 milieux, sont caractéristiques de l'habitat rivulaire endogé humide. La prise en compte des peuplements ripicoles, malgré des difficultés d'ordre taxonomique, pourrait être envisagée lors de la détermination de la qualité des eaux.Utilization of biological methods and particularly through the study of benthic communities in order to estimate the quality of the water is for the present time very common. The impact of the disturbances of the medium may be deducted from the composition and the structure of the populations living there. But is it altogether the same for endogenous riparian wet invertebrate populations less directly submitted to the influence of the aquatic medium?To answer to this question, a comparative study (Factorial Analysis of Correspondences) has been carried out on the hydrographic network of the Arc River (Mediterranean region) which exhibits diversified hydrochemical situations. From and after axis I, the F.A.C. separates the benthic invertebrate samples from the riparian invertebrate ones. On axis II, the couples "benthic samples-riparian samples" of each station appreciably posses the same value on the axis and are arranged according to a trophic gradient ascending from upstream to downstream. The wet endogenous riparian communities can therefore be considered as bioindicators of the chemistry of the water in the same way as benthic communities. In contrast, the temporality factor (axis III) has a more important influence on the benthic communities than on the riparian ones.Examination of the distribution of the taxons on the factorial axis leads to identify a certain number of species which, although present in both mediums are characteristic of the wet endogenous riverside habitat. Taking into account of the riparian populations, in spite of taxonomic difficulties, should be considered as a valuable method for the determination of the quality of the waters

Role of COVID-19 and motionless communication on expected trends of mobility: Evidence from Italian and Turin data

The 2020-2021 pandemic has changed everyday mobility for part of the world. One of the main elements of change is the consolidation of distance working, which further prompted communications without mobility. The emergency-induced reduction of systematic travel demand has been counterbalanced by the increased volume of web traffic. As a result, communications which formerly required mobility have been regularly performed virtually during the lockdowns. This paper quantifies this phenomenon, with a focus on the Italian city of Turin, in Italy, which was one of the first countries hit by COVID-19, soon after China. Local mobility data trends before and during the lockdown are presented and compared. Implications for the "new normal" ahead are discussed. The paper provides directions for further transport policies, with the aim of advancing knowledge of this transportation topic

Predicting general academic performance and identifying the differential contribution of participating variables using artificial neural networks

oai:flr.journals.publicknowledgeproject.org:article/13Many studies have explored the contribution of different factors from diverse theoretical perspectives to the explanation of academic performance. These factors have been identified as having important implications not only for the study of learning processes, but also as tools for improving curriculum designs, tutorial systems, and students’ outcomes. Some authors have suggested that traditional statistical methods do not always yield accurate predictions and/or classifications (Everson, 1995; Garson, 1998). This paper explores a relatively new methodological approach for the field of learning and education, but which is widely used in other areas, such as computational sciences, engineering and economics. This study uses cognitive and non-cognitive measures of students, together with background information, in order to design predictive models of student performance using artificial neural networks (ANN). These predictions of performance constitute a true predictive classification of academic performance over time, a year in advance of the actual observed measure of academic performance. A total sample of 864 university students of both genders, ages ranging between 18 and 25 was used. Three neural network models were developed. Two of the models (identifying the top 33% and the lowest 33% groups, respectively) were able to reach 100% correct identification of all students in each of the two groups. The third model (identifying low, mid and high performance levels) reached precisions from 87% to 100% for the three groups. Analyses also explored the predicted outcomes at an individual level, and their correlations with the observed results, as a continuous variable for the whole group of students. Results demonstrate the greater accuracy of the ANN compared to traditional methods such as discriminant analyses.  In addition, the ANN provided information on those predictors that best explained the different levels of expected performance. Thus, results have allowed the identification of the specific influence of each pattern of variables on different levels of academic performance, providing a better understanding of the variables with the greatest impact on individual learning processes, and of those factors that best explain these processes for different academic levels

Assessment of the structural representativeness of sample data sets for the mechanical characterization of deep formations.

Accurate characterization of the mechanical behavior of geomaterials at depth is a fundamental need for geologic and engineering purposes. Laboratory tests on samples from well cores provide the material characterization in terms of mechanical response and other relevant properties. Representativeness of a sample data set with respect to the in situ conditions at depth is a key issue, which needs to be addressed to extrapolate the laboratory response to the whole rock mass. We have developed a procedure aimed at quantitatively evaluating the representativeness of laboratory samples. The methodology is based on joint processing of laboratory ultrasonic tests and wellbore sonic logs. A structural index is used to quantify the difference between the average structure of the laboratory sample and the structure of the formation at the wellbore scale. This index could be used to identify different causes of discrepancies between the behavior of the cored samples and the behavior of the rock formation as documented by well logs. Then, it could also be used to integrate laboratory data for the construction of a reliable geomechanical model with reference to the real in situ state. The methodology was applied to three different experimental data sets, showing the effectiveness of the method

Predicting key educational outcomes in academic trajectories: a machine-learning approach

Predicting and understanding different key outcomes in a student's academic trajectory such as grade point average, academic retention, and degree completion would allow targeted intervention programs in higher education. Most of the predictive models developed for those key outcomes have been based on traditional methodological approaches. However, these models assume linear relationships between variables and do not always yield accurate predictive classifications. On the other hand, the use of machine-learning approaches such as artificial neural networks has been very effective in the classification of various educational outcomes, overcoming the limitations of traditional methodological approaches. In this study, multilayer perceptron artificial neural network models, with a backpropagation algorithm, were developed to classify levels of grade point average, academic retention, and degree completion outcomes in a sample of 655 students from a private university. Findings showed a high level of accuracy for all the classifications. Among the predictors, learning strategies had the greatest contribution for the prediction of grade point average. Coping strategies were the best predictors for degree completion, and background information had the largest predictive weight for the identification of students who will drop out or not from the university programs.Fil: Musso, Mariel Fernanda. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Saavedra 15. Centro Interdisciplinario de Investigaciones en Psicología Matemática y Experimental "Dr. Horacio J. A. Rimoldi". Grupo Vinculado CIIPME - Entre Ríos - Centro Interdisciplinario de Investigaciones en Psicología Matemática y Experimental "Dr. Horacio J. A. Rimoldi"; ArgentinaFil: Rodríguez Hernández, Carlos Felipe. Katholikie Universiteit Leuven; BélgicaFil: Cascallar, Eduardo C.. Katholikie Universiteit Leuven; Bélgic