Wellposedness of a nonlinear, logarithmic Schrödinger equation of Doebner-Goldin type modeling quantum dissipation

This paper is concerned with the modeling and analysis of quantum dissipation phenomena in the Schrödinger picture. More precisely, we do investigate in detail a dissipative, nonlinear Schrödinger equation somehow accounting for quantum Fokker–Planck effects, and how it is drastically reduced to a simpler logarithmic equation via a nonlinear gauge transformation in such a way that the physics underlying both problems keeps unaltered. From a mathematical viewpoint, this allows for a more achievable analysis regarding the local wellposedness of the initial–boundary value problem. This simplification requires the performance of the polar (modulus–argument) decomposition of the wavefunction, which is rigorously attained (for the first time to the best of our knowledge) under quite reasonable assumptions.

Uncertainties regarding dengue modeling in Rio de Janeiro, Brazil

Dengue fever is currently the most important arthropod-borne viral disease in Brazil. Mathematical modeling of disease dynamics is a very useful tool for the evaluation of control measures. To be used in decision-making, however, a mathematical model must be carefully parameterized and validated with epidemiological and entomological data. In this work, we developed a simple dengue model to answer three questions: (i) which parameters are worth pursuing in the field in order to develop a dengue transmission model for Brazilian cities; (ii) how vector density spatial heterogeneity influences control efforts; (iii) with a degree of uncertainty, what is the invasion potential of dengue virus type 4 (DEN-4) in Rio de Janeiro city. Our model consists of an expression for the basic reproductive number (R0) that incorporates vector density spatial heterogeneity. To deal with the uncertainty regarding parameter values, we parameterized the model using a priori probability density functions covering a range of plausible values for each parameter. Using the Latin Hypercube Sampling procedure, values for the parameters were generated. We conclude that, even in the presence of vector spatial heterogeneity, the two most important entomological parameters to be estimated in the field are the mortality rate and the extrinsic incubation period. The spatial heterogeneity of the vector population increases the risk of epidemics and makes the control strategies more complex. At last, we conclude that Rio de Janeiro is at risk of a DEN-4 invasion. Finally, we stress the point that epidemiologists, mathematicians, and entomologists need to interact more to find better approaches to the measuring and interpretation of the transmission dynamics of arthropod-borne diseases.

COMMIT: Convex Optimization Modeling for Microstructure Informed Tractography.

Tractography is a class of algorithms aiming at in vivo mapping the major neuronal pathways in the white matter from diffusion magnetic resonance imaging (MRI) data. These techniques offer a powerful tool to noninvasively investigate at the macroscopic scale the architecture of the neuronal connections of the brain. However, unfortunately, the reconstructions recovered with existing tractography algorithms are not really quantitative even though diffusion MRI is a quantitative modality by nature. As a matter of fact, several techniques have been proposed in recent years to estimate, at the voxel level, intrinsic microstructural features of the tissue, such as axonal density and diameter, by using multicompartment models. In this paper, we present a novel framework to reestablish the link between tractography and tissue microstructure. Starting from an input set of candidate fiber-tracts, which are estimated from the data using standard fiber-tracking techniques, we model the diffusion MRI signal in each voxel of the image as a linear combination of the restricted and hindered contributions generated in every location of the brain by these candidate tracts. Then, we seek for the global weight of each of them, i.e., the effective contribution or volume, such that they globally fit the measured signal at best. We demonstrate that these weights can be easily recovered by solving a global convex optimization problem and using efficient algorithms. The effectiveness of our approach has been evaluated both on a realistic phantom with known ground-truth and in vivo brain data. Results clearly demonstrate the benefits of the proposed formulation, opening new perspectives for a more quantitative and biologically plausible assessment of the structural connectivity of the brain.

An introductory review on gravitational-deformation induced structures, fabrics and modeling

Recent studies have pointed out a similarity between tectonics and slope tectonic-induced structures. Numerous studies have demonstrated that structures and fabrics previously interpreted as of purely geodynamical origin are instead the result of large slope deformation, and this led in the past to erroneous interpretations. Nevertheless, their limit seems not clearly defined, but it is somehow transitional. Some studies point out continuity between failures developing at surface with upper crust movements. In this contribution, the main studies which examine the link between rock structures and slope movements are reviewed. The aspects regarding model and scale of observation are discussed together with the role of pre-existing weaknesses in the rock mass. As slope failures can develop through progressive failure, structures and their changes in time and space can be recognized. Furthermore, recognition of the origin of these structures can help in avoiding misinterpretations of regional geology. This also suggests the importance of integrating different slope movement classifications based on distribution and pattern of deformation and the application of structural geology techniques. A structural geology approach in the landslide community is a tool that can greatly support the hazard quantification and related risks, because most of the physical parameters, which are used for landslide modeling, are derived from geotechnical tests or the emerging geophysical approaches.

Quantitative genetic modeling and inference in the presence of nonignorable missing data.

Natural selection is typically exerted at some specific life stages. If natural selection takes place before a trait can be measured, using conventional models can cause wrong inference about population parameters. When the missing data process relates to the trait of interest, a valid inference requires explicit modeling of the missing process. We propose a joint modeling approach, a shared parameter model, to account for nonrandom missing data. It consists of an animal model for the phenotypic data and a logistic model for the missing process, linked by the additive genetic effects. A Bayesian approach is taken and inference is made using integrated nested Laplace approximations. From a simulation study we find that wrongly assuming that missing data are missing at random can result in severely biased estimates of additive genetic variance. Using real data from a wild population of Swiss barn owls Tyto alba, our model indicates that the missing individuals would display large black spots; and we conclude that genes affecting this trait are already under selection before it is expressed. Our model is a tool to correctly estimate the magnitude of both natural selection and additive genetic variance.

Learning collaboration in General Internal Medicine: a pilot project for undergraduate students in nursing, physiotherapy and medicine

Background: A form of education called Interprofessional Education (IPE) occurs when two or more professions learn with, from and about each other. The purpose of IPE is to improve collaboration and the quality of care. Today, IPE is considered as a key educational approach for students in the health professions. IPE is highly effective when delivered in active patient care, such as in clinical placements. General internal medicine (GIM) is a core discipline where hospital-based clinical placements are mandatory for students in many health professions. However, few interprofessional (IP) clinical placements in GIM have been implemented. We designed such a placement. Placement design: The placement took place in the Department of Internal Medicine at the CHUV. It involved students from nursing, physiotherapy and medicine. The students were in their last year before graduation. Students formed teams consisting of one student from each profession. Each team worked in the same unit and had to take care of the same patient. The placement lasted three weeks. It included formal IP sessions, the most important being facilitated discussions or "briefings" (3x/w) during which the students discussed patient care and management. Four teams of students eventually took part in this project. Method: We performed a type of evaluation research called formative evaluation. This aimed at (1) understanding the educational experience and (2) assessing the impact of the placement on student learning. We collected quantitative data with pre-post clerkship questionnaires. We also collected qualitative data with two Focus Groups (FG) discussions at the end of the placement. The FG were audiotaped and transcribed. A thematic analysis was then performed. Results: We focused on the qualitative data, since the quantitative data lacked of statistical power due to the small numbers of students (N = 11). Five themes emerged from the FG analysis: (1) Learning of others' roles, (2) Learning collaborative competences, (3) Striking a balance between acquiring one's own professional competences and interprofessional competences, (4) Barriers to apply learnt IP competences in the future and (5) Advantages and disadvantages of IP briefings. Conclusions: Our IP clinical placement in GIM appeared to help students learn other professionals' roles and collaborative skills. Some challenges (e.g. finding the same patient for each team) were identified and will require adjustments.

Schistosoma mansoni major egg antigen Smp40: molecular modeling and potential immunoreactivity for anti-pathology vaccine development

The pathogenesis of Schistosoma mansoni infection is largely determined by host T-cell mediated immune responses such as the granulomatous response to tissue deposited eggs and subsequent fibrosis. The major egg antigens have a valuable role in desensitizing the CD4+ Th cells that mediate granuloma formation, which may prevent or ameliorate clinical signs of schistosomiasis.S. mansoni major egg antigen Smp40 was expressed and completely purified. It was found that the expressed Smp40 reacts specifically with anti-Smp40 monoclonal antibody in Western blotting. Three-dimensional structure was elucidated based on the similarity of Smp40 with the small heat shock protein coded in the protein database as 1SHS as a template in the molecular modeling. It was figured out that the C-terminal of the Smp40 protein (residues 130 onward) contains two alpha crystallin domains. The fold consists of eight beta strands sandwiched in two sheets forming Greek key. The purified Smp40 was used for in vitro stimulation of peripheral blood mononuclear cells from patients infected with S. mansoni using phytohemagglutinin mitogen as a positive control. The obtained results showed that there is no statistical difference in interferon-g, interleukin (IL)-4 and IL-13 levels obtained with Smp40 stimulation compared with the control group (P > 0.05 for each). On the other hand, there were significant differences after Smp40 stimulation in IL-5 (P = 0.006) and IL-10 levels (P < 0.001) compared with the control group. Gaining the knowledge by reviewing the literature, it was found that the overall pattern of cytokine profile obtained with Smp40 stimulation is reported to be associated with reduced collagen deposition, decreased fibrosis, and granuloma formation inhibition. This may reflect its future prospect as a leading anti-pathology schistosomal vaccine candidate.

Travailler sur les articulations interprofessionnelles en périnatalité: un objectif obstétrical [Interprofessional collaboration in perinatality: an obstetrical goal]

In the field of perinatality, development of prenatal diagnosis and neonatal management have been impressive. But these were also associated with the emergence of the increasingly important emotional dimension for parents and professionals. Obstetricians dealing with the difficult breaking of bad news, the uncertainties of prenatal diagnosis and the complex somatic, psychological and social follow-up have to work in a multidisciplinary approach. The securing role of a coherent teamwork is recognised by parents as well as health care providers This article discusses interprofessional relationship as an obstetrical goal and give some landmarks in order to improve the management and the collaboration with parents.

Statistical modeling on (α, +∞)

Observations in daily practice are sometimes registered as positive values larger then a given threshold α. The sample space is in this case the interval (α,+∞), α & 0, which can be structured as a real Euclidean space in different ways. This fact opens the door to alternative statistical models depending not only on the assumed distribution function, but also on the metric which is considered as appropriate, i.e. the way differences are measured, and thus variability