Group Analysis of the Novikov Equation

We find the Lie point symmetries of the Novikov equation and demonstrate that it is strictly self-adjoint. Using the self-adjointness and the recent technique for constructing conserved vectors associated with symmetries of differential equations, we find the conservation law corresponding to the dilations symmetry and show that other symmetries do not provide nontrivial conservation laws. Then we investigat the invariant solutions

Phase computation for the finite-genus solutions to the focusing nonlinear Schrödinger equation using convolutional neural networks

We develop a method for retrieving a set of parameters of a quasi-periodic finite-genus (finite-gap) solution to the focusing nonlinear Schrödinger (NLS) equation, given the solution evaluated on a finite spatial interval for a fixed time. These parameters (named “phases”) enter the jump matrices in the Riemann-Hilbert (RH) problem representation of finite-genus solutions. First, we detail the existing theory for retrieving the phases for periodic finite-genus solutions. Then, we introduce our method applicable to the quasi-periodic solutions. The method is based on utilizing convolutional neural networks optimized by means of the Bayesian optimization technique to identify the best set of network hyperparameters. To train the neural network, we use the discrete datasets obtained in an inverse manner: for a fixed main spectrum (the endpoints of arcs constituting the contour for the associated RH problem) and a random set of modal phases, we generate the corresponding discretized profile in space via the solution of the RH problem, and these resulting pairs – the phase set and the corresponding discretized solution in a finite interval of space domain – are then employed in training. The method's functionality is then verified on an independent dataset, demonstrating our method's satisfactory performance and generalization ability

Collaborative research between clinicians and researchers: a multiple case study of implementation

<p>Abstract</p> <p>Background</p> <p>Bottom-up, clinician-conceived and directed clinical intervention research, coupled with collaboration from researcher experts, is conceptually endorsed by the participatory research movement. This report presents the findings of an evaluation of a program in the Veterans Health Administration meant to encourage clinician-driven research by providing resources believed to be critical. The evaluation focused on the extent to which funded projects: maintained integrity to their original proposals; were methodologically rigorous; were characterized by collaboration between partners; and resulted in sustained clinical impact.</p> <p>Methods</p> <p>Researchers used quantitative (survey and archival) and qualitative (focus group) data to evaluate the implementation, evaluation, and sustainability of four clinical demonstration projects at four sites. Fourteen research center mentors and seventeen clinician researchers evaluated the level of collaboration using a six-dimensional model of participatory research.</p> <p>Results</p> <p>Results yielded mixed findings. Qualitative and quantitative data suggested that although the process was collaborative, clinicians' prior research experience was critical to the quality of the projects. Several challenges were common across sites, including subject recruitment, administrative support and logistics, and subsequent dissemination. Only one intervention achieved lasting clinical effect beyond the active project period. Qualitative analyses identified barriers and facilitators and suggested areas to improve sustainability.</p> <p>Conclusions</p> <p>Evaluation results suggest that this participatory research venture was successful in achieving clinician-directed collaboration, but did not produce sustainable interventions due to such implementation problems as lack of resources and administrative support.</p

Acceptability and feasibility of magnetic femoral nerve stimulation in older, functionally impaired patients

Abstract Objective Magnetic femoral nerve stimulation to test muscle function has been largely unexplored in older people. We assessed acceptability, feasibility, along with reproducibility and correlation with other physical function measures. Results Study 1 recruited older people with sarcopenia. Stimulation was performed at baseline and 2 weeks along with six minute walk (6MW), maximum voluntary quadriceps contraction, short physical performance battery and grip strength. Acceptability was measured using visual analog scales. Study 2 used baseline data from a trial of older people. We correlated stimulation results with 6MW, maximal voluntary contraction and muscle mass. Maximum quadriceps twitch tension was measured in both studies, evoked using biphasic magnetic stimulation of the femoral nerve. In study 1 (n = 12), magnetic stimulation was well tolerated with mean discomfort rating of 9% (range 0–40%) on a visual analog scale. Reproducibility was poor (intraclass correlation coefficient 0.06; p = 0.44). Study 2 (n = 64) showed only weak to moderate correlations for maximum quadriceps twitch tension with other measures of physical function (6 minute walk test r = 0.24, p = 0.06; maximal voluntary contraction r = 0.26; p = 0.04). We conclude that magnetic femoral nerve stimulation is acceptable and feasible but poorly reproducible in older, functionally impaired people

Optimization of Time-Course Experiments for Kinetic Model Discrimination

Systems biology relies heavily on the construction of quantitative models of biochemical networks. These models must have predictive power to help unveiling the underlying molecular mechanisms of cellular physiology, but it is also paramount that they are consistent with the data resulting from key experiments. Often, it is possible to find several models that describe the data equally well, but provide significantly different quantitative predictions regarding particular variables of the network. In those cases, one is faced with a problem of model discrimination, the procedure of rejecting inappropriate models from a set of candidates in order to elect one as the best model to use for prediction

The Challenges of the External Vote

UID/CPO/04627/2019Over the last few decades, emigrants all over the world have gained expanded voting rights. Despite the normative debates about this issue, there are few empirical studies on why states decide to implement external voting and how electoral systems perform. This chapter seeks to fill this gap by looking at the Portuguese case. Our study suggests that a combination of political and socio-economic factors explains the implementa tion of external voting. On the other hand, the interests of political parties and the low level of civil society engagement are key factors in the failure of both electoral reforms and attempts to overcome the shortcomings of external voting.publishersversionpublishe