LEVERAGING SANDBOX IMMERSIVE 3D VIRTUAL WORLDS TO DEVELOP DO-IT- YOURSELF TEACHING GAMES: IMPLEMENTATION TO MARKETING CASE STUDY TEACHING IN SECOND LIFE

Games are powerful and engaging. On average, one billion people spend at least 1 hour a day playing computer and videogames. This is even more true with the younger generations. Our students have become the < digital natives >, the < gamers >, the < virtual generation >. Research shows that those who are most at risk for failure in the traditional classroom setting, also spend more time than their counterparts, using video games. They might strive, given a different learning environment. Educators have the responsibility to align their teaching style to these younger generation learning styles. However, many academics resist the use of computer-assisted learning that has been "created elsewhere". This can be extrapolated to game-based teaching: even if educational games were more widely authored, their adoption would still be limited to the educators who feel a match between the authored games and their own beliefs and practices. Consequently, game-based teaching would be much more widespread if teachers could develop their own games, or at least customize them. Yet, the development and customization of teaching games are complex and costly. This research uses a design science methodology, leveraging gamification techniques, active and cooperative learning theories, as well as immersive sandbox 3D virtual worlds, to develop a method which allows management instructors to transform any off-the-shelf case study into an engaging collaborative gamified experience. This method is applied to marketing case studies, and uses the sandbox virtual world of Second Life. -- Les jeux sont puissants et motivants, En moyenne, un milliard de personnes passent au moins 1 heure par jour jouer à des jeux vidéo sur ordinateur. Ceci se vérifie encore plus avec les jeunes générations, Nos étudiants sont nés à l'ère du numérique, certains les appellent des < gamers >, d'autres la < génération virtuelle >. Les études montrent que les élèves qui se trouvent en échec scolaire dans les salles de classes traditionnelles, passent aussi plus de temps que leurs homologues à jouer à des jeux vidéo. lls pourraient potentiellement briller, si on leur proposait un autre environnement d'apprentissage. Les enseignants ont la responsabilité d'adapter leur style d'enseignement aux styles d'apprentissage de ces jeunes générations. Toutefois, de nombreux professeurs résistent lorsqu'il s'agit d'utiliser des contenus d'apprentissage assisté par ordinateur, développés par d'autres. Ceci peut être extrapolé à l'enseignement par les jeux : même si un plus grand nombre de jeux éducatifs était créé, leur adoption se limiterait tout de même aux éducateurs qui perçoivent une bonne adéquation entre ces jeux et leurs propres convictions et pratiques. Par conséquent, I'enseignement par les jeux serait bien plus répandu si les enseignants pouvaient développer leurs propres jeux, ou au moins les customiser. Mais le développement de jeux pédagogiques est complexe et coûteux. Cette recherche utilise une méthodologie Design Science pour développer, en s'appuyant sur des techniques de ludification, sur les théories de pédagogie active et d'apprentissage coopératif, ainsi que sur les mondes virtuels immersifs < bac à sable > en 3D, une méthode qui permet aux enseignants et formateurs de management, de transformer n'importe quelle étude de cas, provenant par exemple d'une centrale de cas, en une expérience ludique, collaborative et motivante. Cette méthode est appliquée aux études de cas Marketing dans le monde virtuel de Second Life.

Year-round poultry litter decomposition and N, P, K and Ca release

Poultry litter is an important nutrient source in agriculture, although little information is available regarding its decomposition rate and nutrient release. To evaluate these processes, poultry litter (PL) was applied to the soil to supply 100, 200 and 300 kg ha-1 N contained in 4,953, 9,907 and 14,860 kg ha-1 PL, respectively. The litter bag technique was used to monitor the process of decomposition and nutrient release from the litter. These bags were left on the soil surface and collected periodically (after 15, 30, 60, 90, 120, 150, 180, 210, 240, 270, 300, 330, and 365 days). The dry matter (DM) loss was highest (35 %) after the first 30 days of field incubation. The highest nutrient release occurred in the first 60 days on the field, when 40, 34, 91, and 39 %, respectively, of N, P, K, and Ca of the initial PL dry matter (4,860 kg ha-1) was already released to the soil. In absolute terms, these percentages represent 40, 23, 134, and 69 kg ha-1 of N, P, K, and Ca and these values doubled and tripled as the PL fertilization rates increased to 9,907 and 14,860 kg ha-1, respectively. After one year of field incubation, the residual contents in the litter were 27, 15, 18 and 30 % of the initial DM , and N, P and Ca, respectively. The release rate of K was the fastest and 91 % of the K had been released from the PL after 30 days of field incubation.

Particulate soil organic carbon and stratification ratio increases in response to crop residue decomposition under no-till

In soils under no-tillage (NT), the continuous crop residue input to the surface layer leads to carbon (C) accumulation. This study evaluated a soil under NT in Ponta Grossa (State of Paraná, Brazil) for: 1) the decomposition of black oat (Avena strigosa Schreb.) residues, 2) relation of the biomass decomposition effect with the soil organic carbon (SOC) content, the particulate organic carbon (POC) content, and the soil carbon stratification ratio (SR) of an Inceptisol. The assessments were based on seven samplings (t0 to t6) in a period of 160 days of three transects with six sampling points each. The oat dry biomass was 5.02 Mg ha-1 at t0, however, after 160 days, only 17.8 % of the initial dry biomass was left on the soil surface. The SOC in the 0-5 cm layer varied from 27.56 (t0) to 30.07 g dm-3 (t6). The SR increased from 1.33 to 1.43 in 160 days. There was also an increase in the POC pool in this period, from 8.1 to 10.7 Mg ha-1. The increase in SOC in the 0-5 cm layer in the 160 days was mainly due to the increase of POC derived from oat residue decomposition. The linear relationship between SOC and POC showed that 21 % of SOC was due to the more labile fraction. The results indicated that the continuous input of residues could be intensified to increase the C pool and sequestration in soils under NT.

Model-Free Reconstruction of Excitatory Neuronal Connectivity from Calcium Imaging Signals

A systematic assessment of global neural network connectivity through direct electrophysiological assays has remained technically infeasible, even in simpler systems like dissociated neuronal cultures. We introduce an improved algorithmic approach based on Transfer Entropy to reconstruct structural connectivity from network activity monitored through calcium imaging. We focus in this study on the inference of excitatory synaptic links. Based on information theory, our method requires no prior assumptions on the statistics of neuronal firing and neuronal connections. The performance of our algorithm is benchmarked on surrogate time series of calcium fluorescence generated by the simulated dynamics of a network with known ground-truth topology. We find that the functional network topology revealed by Transfer Entropy depends qualitatively on the time-dependent dynamic state of the network (bursting or non-bursting). Thus by conditioning with respect to the global mean activity, we improve the performance of our method. This allows us to focus the analysis to specific dynamical regimes of the network in which the inferred functional connectivity is shaped by monosynaptic excitatory connections, rather than by collective synchrony. Our method can discriminate between actual causal influences between neurons and spurious non-causal correlations due to light scattering artifacts, which inherently affect the quality of fluorescence imaging. Compared to other reconstruction strategies such as cross-correlation or Granger Causality methods, our method based on improved Transfer Entropy is remarkably more accurate. In particular, it provides a good estimation of the excitatory network clustering coefficient, allowing for discrimination between weakly and strongly clustered topologies. Finally, we demonstrate the applicability of our method to analyses of real recordings of in vitro disinhibited cortical cultures where we suggest that excitatory connections are characterized by an elevated level of clustering compared to a random graph (although not extreme) and can be markedly non-local.

DNA topology: feeling the pulse of a topoisomerase.

The action of individual type II DNA topoisomerases has been followed in real time by observing the elastic response of single DNA molecules to sequential strand passage events. Micromanipulation methods provide a complementary approach to biochemical studies for investigating the mechanism of DNA topoisomerases.

Invariant decomposition of the retarded electromagnetic field.

The integral representation of the electromagnetic two-form, defined on Minkowski space-time, is studied from a new point of view. The aim of the paper is to obtain an invariant criteria in order to define the radiative field. This criteria generalizes the well-known structureless charge case. We begin with the curvature two-form, because its field equations incorporate the motion of the sources. The gauge theory methods (connection one-forms) are not suited because their field equations do not incorporate the motion of the sources. We obtain an integral solution of the Maxwell equations in the case of a flow of charges in irrotational motion. This solution induces us to propose a new method of solving the problem of the nature of the retarded radiative field. This method is based on a projection tensor operator which, being local, is suited to being implemented on general relativity. We propose the field equations for the pair {electromagnetic field, projection tensor J. These field equations are an algebraic differential first-order system of oneforms, which verifies automatically the integrability conditions.

Mode decomposition and renormalization in semiclassical gravity

We compute the influence action for a system perturbatively coupled to a linear scalar field acting as the environment. Subtleties related to divergences that appear when summing over all the modes are made explicit and clarified. Being closely connected with models used in the literature, we show how to completely reconcile the results obtained in the context of stochastic semiclassical gravity when using mode decomposition with those obtained by other standard functional techniques.

Biomass decomposition and nutrient release from black oat and hairy vetch residues deposited in a vineyard

A significant quantity of nutrients in vineyards may return to the soil each year through decomposition of residues from cover plants. This study aimed to evaluate biomass decomposition and nutrient release from residues of black oats and hairy vetch deposited in the vines rows, with and without plastic shelter, and in the between-row areas throughout the vegetative and productive cycle of the plants. The study was conducted in a commercial vineyard in Bento Gonçalves, RS, Brazil, from October 2008 to February 2009. Black oat (Avena strigosa) and hairy vetch (Vicia villosa) residues were collected, subjected to chemical (C, N, P, K, Ca, and Mg) and biochemical (cellulose - Cel, hemicellulose - Hem, and lignin - Lig content) analyses, and placed in litter bags, which were deposited in vines rows without plastic shelter (VPRWS), in vines rows with plastic shelter (VPRS), and in the between-row areas (BR). We collected the residues at 0, 33, 58, 76, and 110 days after deposition of the litter bags, prepared the material, and subjected it to analysis of total N, P, K, Ca, and Mg content. The VPRS contained the largest quantities and percentages of dry matter and residual nutrients (except for Ca) in black oat residues from October to February, which coincides with the period from flowering up to grape harvest. This practice led to greater protection of the soil surface, avoiding surface runoff of the solution derived from between the rows, but it retarded nutrient cycling. The rate of biomass decomposition and nutrient release from hairy vetch residues from October to February was not affected by the position of deposition of the residues in the vineyard, which may especially be attributed to the lower values of the C/N and Lig/N ratios. Regardless of the type of residue, black oat or hairy vetch, the greatest decomposition and nutrient release mainly occurred up to 33 days after deposition of the residues on the soil surface, which coincided with the flowering of the grapevines, which is one of the phenological stages of greatest demand for nutrients.

Synchronization, diversity, and topology of networks of integrate and fire oscillators

We study synchronization dynamics of a population of pulse-coupled oscillators. In particular, we focus our attention on the interplay between topological disorder and synchronization features of networks. First, we analyze synchronization time T in random networks, and find a scaling law which relates T to network connectivity. Then, we compare synchronization time for several other topological configurations, characterized by a different degree of randomness. The analysis shows that regular lattices perform better than a disordered network. This fact can be understood by considering the variability in the number of links between two adjacent neighbors. This phenomenon is equivalent to having a nonrandom topology with a distribution of interactions and it can be removed by an adequate local normalization of the couplings.

Topology of the world trade web

Economy, and consequently trade, is a fundamental part of human social organization which, until now, has not been studied within the network modeling framework. Here we present the first, to the best of our knowledge, empirical characterization of the world trade web, that is, the network built upon the trade relationships between different countries in the world. This network displays the typical properties of complex networks, namely, scale-free degree distribution, the small-world property, a high clustering coefficient, and, in addition, degree-degree correlation between different vertices. All these properties make the world trade web a complex network, which is far from being well described through a classical random network description.

Analysis of linear networks with inconsistent initial conditions

This paper presents a new method to analyze timeinvariant linear networks allowing the existence of inconsistent initial conditions. This method is based on the use of distributions and state equations. Any time-invariant linear network can be analyzed. The network can involve any kind of pure or controlled sources. Also, the transferences of energy that occur at t=O are determined, and the concept of connection energy is introduced. The algorithms are easily implemented in a computer program.

Comparative performance of supertree algorithms in large data sets using the soapberry family (Sapindaceae) as a case study.

For the last 2 decades, supertree reconstruction has been an active field of research and has seen the development of a large number of major algorithms. Because of the growing popularity of the supertree methods, it has become necessary to evaluate the performance of these algorithms to determine which are the best options (especially with regard to the supermatrix approach that is widely used). In this study, seven of the most commonly used supertree methods are investigated by using a large empirical data set (in terms of number of taxa and molecular markers) from the worldwide flowering plant family Sapindaceae. Supertree methods were evaluated using several criteria: similarity of the supertrees with the input trees, similarity between the supertrees and the total evidence tree, level of resolution of the supertree and computational time required by the algorithm. Additional analyses were also conducted on a reduced data set to test if the performance levels were affected by the heuristic searches rather than the algorithms themselves. Based on our results, two main groups of supertree methods were identified: on one hand, the matrix representation with parsimony (MRP), MinFlip, and MinCut methods performed well according to our criteria, whereas the average consensus, split fit, and most similar supertree methods showed a poorer performance or at least did not behave the same way as the total evidence tree. Results for the super distance matrix, that is, the most recent approach tested here, were promising with at least one derived method performing as well as MRP, MinFlip, and MinCut. The output of each method was only slightly improved when applied to the reduced data set, suggesting a correct behavior of the heuristic searches and a relatively low sensitivity of the algorithms to data set sizes and missing data. Results also showed that the MRP analyses could reach a high level of quality even when using a simple heuristic search strategy, with the exception of MRP with Purvis coding scheme and reversible parsimony. The future of supertrees lies in the implementation of a standardized heuristic search for all methods and the increase in computing power to handle large data sets. The latter would prove to be particularly useful for promising approaches such as the maximum quartet fit method that yet requires substantial computing power.

Extreme prematurity and intra uterine growth restriction effects in brain network topology at school age

Higher risk for long-term behavioral and emotional sequelae, with attentional problems (with or without hyperactivity) is now becoming one of the hallmarks of extreme premature (EP) birth and birth after pregancy conditions leading to poor intra uterine growth restriction (IUGR) [1,2]. However, little is know so far about the neurostructural basis of these complexe brain functional abnormalities that seem to have their origins in early critical periods of brain development. The development of cortical axonal pathways happens in a series of sequential events. The preterm phase (24-36 post conecptional weeks PCW) is known for being crucial for growth of the thalamocortical fiber bundles as well as for the development of long projectional, commisural and projectional fibers [3]. Is it logical to expect, thus, that being exposed to altered intrauterine environment (altered nutrition) or to extrauterine environment earlier that expected, lead to alterations in the structural organization and, consequently, alter the underlying white matter (WM) structure. Understanding rate and variability of normal brain development, and detect differences from typical development may offer insight into the neurodevelopmental anomalies that can be imaged at later stages. Due to its unique ability to non-invasively visualize and quantify in vivo white matter tracts in the brain, in this study we used diffusion MRI (dMRI) tractography to derive brain graphs [4,5,6]. This relatively simple way of modeling the brain enable us to use graph theory to study topological properties of brain graphs in order to study the effects of EP and IUGR on childrens brain connectivity at age 6 years old.

Socio-economic inequalities in reported depression in Spain : a decomposition approach

Recent evidence questions some conventional view on the existence of income-related inequalities in depression suggesting in turn that other determinants might be in place, such as activity status and educational attainment. Evidence of socio-economic inequalities is especially relevant in countries such as Spain that have a limited coverage of mental health care and are regionally heterogeneous. This paper aims at measuring and explaining the degree of socio-economic inequality in reported depression in Spain. We employ linear probability models to estimate the concentration index and its decomposition drawing from 2003 edition of the Spanish National Health Survey, the most recent representative health survey in Spain. Our findings point towards the existence of avoidable inequalities in the prevalence of reported depression. However, besides ¿pure income effects¿ explaining 37% of inequality, economic activity status (28%), education (15%) and demographics (15%) play also a key encompassing role. Although high income implies higher resources to invest and cure (mental) illness, environmental factors influencing in peoples perceived social status act as indirect path as explaining the prevalence of depression. Finally, we find evidence of a gender effect, gender social-economic inequality in income is mainly avoidable.