The influence of work context on demand for master's studies: a comparative analysisi between Brasil and Spain

The communication presents the results of an investigation of exploratory and comparative character which objective is to analyze the influence of the actual labour situation into the demand of official master studies in the field of education. The study has been developed in two countries with a very different labour situation: Brasil, country of economic expansion and Spain, in recession due to the actual economic crisis. In that sense, the study provides data for deep thinking about the influence of the constriction or expansion of employment on the behaviour and demand of the students who access master studies and on how the previous formative and labour trajectory affects their expectations, demands and future projects. The working methodology is qualitative and the strategy for data collection the “focus group”. As a first approach, two groups of discussion have been formed with master students. A first one with students from Universidad de Barcelona- España and another one with members of Universidade do Vale do Itajaí- Brasil. Then, we constituted a mixed group of discussion in order to analyze differences and similarities.

The Demand for Social Insurance: Does Culture Matter?

Does culture shape the demand for social insurance against risks to health and work? We study this issue across language groups in Switzerland where a language border sharply separates social groups at identical actual levels of publicly provided social insurance. We find substantially stronger support for expansions of social insurance among residents of French, Italian or Romansh-speaking language border municipalities compared with their German-speaking neighbours in adjacent municipalities. Informal insurance does not vary enough to explain stark differences in social insurance but differences in ideology and segmented media markets potentially contribute to the discrepancy in demand for social insurance.

Linking supply to demand: the neuronal monocarboxylate transporter MCT2 and the alpha-amino-3-hydroxyl-5-methyl-4-isoxazole-propionic acid receptor GluR2/3 subunit are associated in a common trafficking process.

MCT2 is the major neuronal monocarboxylate transporter (MCT) that allows the supply of alternative energy substrates such as lactate to neurons. Recent evidence obtained by electron microscopy has demonstrated that MCT2, like alpha-amino-3-hydroxyl-5-methyl-4-isoxazole-propionic acid (AMPA) receptors, is localized in dendritic spines of glutamatergic synapses. Using immunofluorescence, we show in this study that MCT2 colocalizes extensively with GluR2/3 subunits of AMPA receptors in neurons from various mouse brain regions as well as in cultured neurons. It also colocalizes with GluR2/3-interacting proteins, such as C-kinase-interacting protein 1, glutamate receptor-interacting protein 1 and clathrin adaptor protein. Coimmunoprecipitation of MCT2 with GluR2/3 and C-kinase-interacting protein 1 suggests their close interaction within spines. Parallel changes in the localization of both MCT2 and GluR2/3 subunits at and beneath the plasma membrane upon various stimulation paradigms were unraveled using an original immunocytochemical and transfection approach combined with three-dimensional image reconstruction. Cell culture incubation with AMPA or insulin triggered a marked intracellular accumulation of both MCT2 and GluR2/3, whereas both tumor necrosis factor alpha and glycine (with glutamate) increased their cell surface immunolabeling. Similar results were obtained using Western blots performed on membrane or cytoplasm-enriched cell fractions. Finally, an enhanced lactate flux into neurons was demonstrated after MCT2 translocation on the cell surface. These observations provide unequivocal evidence that MCT2 is linked to AMPA receptor GluR2/3 subunits and undergoes a similar translocation process in neurons upon activation. MCT2 emerges as a novel component of the synaptic machinery putatively linking neuroenergetics to synaptic transmission.

An allele-specific, stochastic gene expression process controls the expression of multiple Ly49 family genes and generates a diverse, MHC-specific NK cell receptor repertoire.

Mouse NK cells express MHC class I-specific inhibitory Ly49 receptors. Since these receptors display distinct ligand specificities and are clonally distributed, their expression generates a diverse NK cell receptor repertoire specific for MHC class I molecules. We have previously found that the Dd (or Dk)-specific Ly49A receptor is usually expressed from a single allele. However, a small fraction of short-term NK cell clones expressed both Ly49A alleles, suggesting that the two Ly49A alleles are independently and randomly expressed. Here we show that the genes for two additional Ly49 receptors (Ly49C and Ly49G2) are also expressed in a (predominantly) mono-allelic fashion. Since single NK cells can co-express multiple Ly49 receptors, we also investigated whether mono-allelic expression from within the tightly linked Ly49 gene cluster is coordinate or independent. Our clonal analysis suggests that the expression of alleles of distinct Ly49 genes is not coordinate. Thus Ly49 alleles are apparently independently and randomly chosen for stable expression, a process that directly restricts the number of Ly49 receptors expressed per single NK cell. We propose that the Ly49 receptor repertoire specific for MHC class I is generated by an allele-specific, stochastic gene expression process that acts on the entire Ly49 gene cluster.

Stochastic resonance in a dipole

We show that the dipole, a system usually proposed to model relaxation phenomena, exhibits a maximum in the signal-to-noise ratio at a nonzero noise level, thus indicating the appearance of stochastic resonance. The phenomenon occurs in two different situations, i.e., when the minimum of the potential of the dipole remains fixed in time and when it switches periodically between two equilibrium points. We have also found that the signal-to-noise ratio has a maximum for a certain value of the amplitude of the oscillating field.

Stochastic inversion of tracer test and electrical geophysical data to estimate hydraulic conductivities.

Quantifying the spatial configuration of hydraulic conductivity (K) in heterogeneous geological environments is essential for accurate predictions of contaminant transport, but is difficult because of the inherent limitations in resolution and coverage associated with traditional hydrological measurements. To address this issue, we consider crosshole and surface-based electrical resistivity geophysical measurements, collected in time during a saline tracer experiment. We use a Bayesian Markov-chain-Monte-Carlo (McMC) methodology to jointly invert the dynamic resistivity data, together with borehole tracer concentration data, to generate multiple posterior realizations of K that are consistent with all available information. We do this within a coupled inversion framework, whereby the geophysical and hydrological forward models are linked through an uncertain relationship between electrical resistivity and concentration. To minimize computational expense, a facies-based subsurface parameterization is developed. The Bayesian-McMC methodology allows us to explore the potential benefits of including the geophysical data into the inverse problem by examining their effect on our ability to identify fast flowpaths in the subsurface, and their impact on hydrological prediction uncertainty. Using a complex, geostatistically generated, two-dimensional numerical example representative of a fluvial environment, we demonstrate that flow model calibration is improved and prediction error is decreased when the electrical resistivity data are included. The worth of the geophysical data is found to be greatest for long spatial correlation lengths of subsurface heterogeneity with respect to wellbore separation, where flow and transport are largely controlled by highly connected flowpaths.

Entropic stochastic resonance

We present a novel scheme for the appearance of stochastic resonance when the dynamics of a Brownian particle takes place in a confined medium. The presence of uneven boundaries, giving rise to an entropic contribution to the potential, may upon application of a periodic driving force result in an increase of the spectral amplification at an optimum value of the ambient noise level. The entropic stochastic resonance, characteristic of small-scale systems, may constitute a useful mechanism for the manipulation and control of single molecules and nanodevices.

A hybrid algorithm combining metaheuristic with Monte Carlo simulation for solving the Stochastic Flow Shop problem

In this paper, a hybrid simulation-based algorithm is proposed for the StochasticFlow Shop Problem. The main idea of the methodology is to transform the stochastic problem into a deterministic problem and then apply simulation to the latter. In order to achieve this goal, we rely on Monte Carlo Simulation and an adapted version of a deterministic heuristic. This approach aims to provide flexibility and simplicity due to the fact that it is not constrained by any previous assumption and relies in well-tested heuristics.

A hybrid algorithm combining metaheuristic with Monte Carlo simulation for solving the Stochastic Flow Shop problem

In this paper, a hybrid simulation-based algorithm is proposed for the StochasticFlow Shop Problem. The main idea of the methodology is to transform the stochastic problem into a deterministic problem and then apply simulation to the latter. In order to achieve this goal, we rely on Monte Carlo Simulation and an adapted version of a deterministic heuristic. This approach aims to provide flexibility and simplicity due to the fact that it is not constrained by any previous assumption and relies in well-tested heuristics.

Asymmetric stochastic switching driven by intrinsic molecular noise

Low-copy-number molecules are involved in many functions in cells. The intrinsic fluctuations of these numbers can enable stochastic switching between multiple steady states, inducing phenotypic variability. Herein we present a theoretical and computational study based on Master Equations and Fokker-Planck and Langevin descriptions of stochastic switching for a genetic circuit of autoactivation. We show that in this circuit the intrinsic fluctuations arising from low-copy numbers, which are inherently state-dependent, drive asymmetric switching. These theoretical results are consistent with experimental data that have been reported for the bistable system of the gallactose signaling network in yeast. Our study unravels that intrinsic fluctuations, while not required to describe bistability, are fundamental to understand stochastic switching and the dynamical relative stability of multiple states.

Demand-based structural change and balanced economic growth

[eng] We analyze the equilibrium of a multi-sector exogenous growth model where the introduction of minimum consumption requirements drives structural change. We show that equilibrium dynamics simultaneously exhibt structural change and balanced growth of aggregate variables as is observed in US when the initial intensity of minimum consumption requirements is sufficiently small. This intensity is measured by the ratio between the aggregate value of the minimum consumption requirements and GDP and, therefore, it is inversely related with the level of economic development. Initially rich economies benefit from an initially low intensity of the minimum consumption requirements and, as a consequence, these economies end up exhibiting balanced growth of aggregate variables, while there is structural change. In contrast, initially poor economies suffer from an initially large intensity of the minimum consumption requirements, which makes the growth of the aggregate variables unbalanced during a very large period. These economies may never exhibit simultaneously balanced growth of aggregate variables and structural change.

Cost Analysis of Long-Term Treatment of Patients with Symptomatic Gastroesophageal Reflux Disease (GERD) with Esomeprazole On-Demand Treatment or Esomeprazole Continuous Treatment: An Open, Randomized, Multicenter Study in Switzerland.

Objectives: To assess the difference in direct medical costs between on-demand (OD) treatment with esomeprazole (E) 20 mg and continuous (C) treatment with E 20 mg q.d. from a clinical practice view in patients with gastroesophageal reflux disease (GERD) symptoms. Methods: This open, randomized study (ONE: on-demand Nexium evaluation) compared two long-term management options with E 20 mg in endoscopically uninvestigated patients seeking primary care for GERD symptoms who demonstrated complete relief of symptoms after an initial treatment of 4 weeks with E 40 mg. Data on consumed quantities of all cost items were collected in the study, while data on prices during the time of study were collected separately. The analysis was done from a societal perspective. Results: Forty-nine percent (484 of 991) of patients randomized to the OD regimen and 46% (420 of 913) of the patients in the C group had at least one contact with the investigator that would have occurred nonprotocol-driven. The difference of the adjusted mean direct medical costs between the treatment groups was CHF 88.72 (95% confidence interval: CHF 41.34-153.95) in favor of the OD treatment strategy (Wilcoxon rank-sum test: P < 0.0001). Adjusted direct nonmedical costs and productivity loss were similar in both groups. Conclusions: The adjusted direct medical costs of a 6-month OD treatment with esomeprazole 20 mg in uninvestigated patients with symptoms of GERD were significantly lower compared with a continuous treatment with E 20 mg once a day. The OD therapy represents a cost-saving alternative to the continuous treatment strategy with E.

Modeling and mitigation of supply-demand mismatches

In this thesis, I develop analytical models to price the value of supply chain investments under demand uncer¬tainty. This thesis includes three self-contained papers. In the first paper, we investigate the value of lead-time reduction under the risk of sudden and abnormal changes in demand forecasts. We first consider the risk of a complete and permanent loss of demand. We then provide a more general jump-diffusion model, where we add a compound Poisson process to a constant-volatility demand process to explore the impact of sudden changes in demand forecasts on the value of lead-time reduction. We use an Edgeworth series expansion to divide the lead-time cost into that arising from constant instantaneous volatility, and that arising from the risk of jumps. We show that the value of lead-time reduction increases substantially in the intensity and/or the magnitude of jumps. In the second paper, we analyze the value of quantity flexibility in the presence of supply-chain dis- intermediation problems. We use the multiplicative martingale model and the "contracts as reference points" theory to capture both positive and negative effects of quantity flexibility for the downstream level in a supply chain. We show that lead-time reduction reduces both supply-chain disintermediation problems and supply- demand mismatches. We furthermore analyze the impact of the supplier's cost structure on the profitability of quantity-flexibility contracts. When the supplier's initial investment cost is relatively low, supply-chain disin¬termediation risk becomes less important, and hence the contract becomes more profitable for the retailer. We also find that the supply-chain efficiency increases substantially with the supplier's ability to disintermediate the chain when the initial investment cost is relatively high. In the third paper, we investigate the value of dual sourcing for the products with heavy-tailed demand distributions. We apply extreme-value theory and analyze the effects of tail heaviness of demand distribution on the optimal dual-sourcing strategy. We find that the effects of tail heaviness depend on the characteristics of demand and profit parameters. When both the profit margin of the product and the cost differential between the suppliers are relatively high, it is optimal to buffer the mismatch risk by increasing both the inventory level and the responsive capacity as demand uncertainty increases. In that case, however, both the optimal inventory level and the optimal responsive capacity decrease as the tail of demand becomes heavier. When the profit margin of the product is relatively high, and the cost differential between the suppliers is relatively low, it is optimal to buffer the mismatch risk by increasing the responsive capacity and reducing the inventory level as the demand uncertainty increases. In that case, how¬ever, it is optimal to buffer with more inventory and less capacity as the tail of demand becomes heavier. We also show that the optimal responsive capacity is higher for the products with heavier tails when the fill rate is extremely high.