Traveling dark-bright solitons in a reduced spin-orbit coupled system: application to Bose-Einstein condensates

In the present work, we explore the potential of spin-orbit (SO) coupled Bose-Einstein condensates to support multi-component solitonic states in the form of dark-bright (DB) solitons. In the case where Raman linear coupling between components is absent, we use a multiscale expansion method to reduce the model to the integrable Mel'nikov system. The soliton solutions of the latter allow us to reconstruct approximate traveling DB solitons for the reduced SO coupled system. For small values of the formal perturbation parameter, the resulting waveforms propagate undistorted, while for large values thereof, they shed some dispersive radiation, and subsequently distill into a robust propagating structure. After quantifying the relevant radiation effect, we also study the dynamics of DB solitons in a parabolic trap, exploring how their oscillation frequency varies as a function of the bright component mass and the Raman laser wavenumber

Is There a Relationship between Abdominal Aortic Aneurysms and Alpha1-antitrypsin Deficiency (PiZ)?

AbstractObjective:to determine if the frequency of α1AT deficiency (PiZ) is increased in patients with abdominal aortic aneurysm (AAA), and, to investigate whether aneurysmal stiffness and other clinical characteristics differ in AAA patients with and without α1AT deficiency.Methods:we identified α1AT-deficient individuals by a monoclonal-antibody ELISA technique, in 102 consecutive patients with AAA. Positive ELISA samples were further phenotyped by isoelectric focusing to differentiate between the heterozygosity (PiZ) and homozygosity (PiZZ) state. Aneurysmal diameter and stiffness was measured using echotracking sonography and blood pressure measurements.Results:the frequency of heterozygous α1AT deficiency (PiZ) in patients with AAA was similar to that in the general population (6.8% and 4.7%, respectively,p>0.3). The frequency of popliteal and femoral aneurysm was similar in male PiZ-carriers and non-carriers with AAA, as were age at diagnosis of AAA, aneurysmal diameter, aneurysmal stiffness, and presence of factors that may be associated with AAA (i.e. smoking, hypertension, diabetes mellitus, and family history of AAA). Occurrence of ischaemic heart disease was more frequent in male non-PiZ-carriers than in male PiZ-carriers with AAA (p=0.03).Conclusions:the frequency of α1AT deficiency (PiZ) was not increased in our series of patients with AAA and patients in whom the two disorders coexisted did not appear to have different clinical characteristics except for the lower occurrence of ischaemic heart disease among the PiZ-carriers

Influence on Plasma β-N-Acetyl-D-glucosaminidase of Reticuloendothelial Stimulation and Depression: An Experimental Study in Rats

Peer Reviewe

Artificial Intelligence Meets IS Researchers: Can It Replace Us?

Given we live in an era with accelerating digitization and rapid advances in artificial intelligence (AI), AI may eventually automate more job tasks. However, researchers have scarcely if at all critically analyzed how AI will automate such tasks and what professions it will automate more than others. Some studies suggest that AI cannot conduct highly creative and knowledge-intensive tasks. Yet, AI algorithms have generated creative art pieces that even art critics could not distinguish from human-drawn paintings. As IS (and most other) researchers, we pride ourselves on our work’s scarcity, novelty, and creativity. In this context, we report on a panel at the 40th International Conference for Information Systems that debated whether AI can and will replace our major activity, IS research, or even IS researchers themselves

RNA sequencing-based single sample predictors of molecular subtype and risk of recurrence for clinical assessment of early-stage breast cancer

BackgroundMultigene expression assays for molecular subtypes and biomarkers can aid clinical management of early invasive breast cancer. Based on RNA-sequencing we aimed to develop single-sample predictor (SSP) models for conventional clinical markers, molecular intrinsic subtype and risk of recurrence (ROR).MethodsA uniformly accrued breast cancer cohort of 7743 patients with RNA-sequencing data from fresh tissue was divided into a training set and a reserved test set. We trained SSPs for PAM50 molecular subtypes and ROR assigned by nearest-centroid (NC) and SSPs for conventional clinical markers from histopathology data. Additionally, SSP classifications were compared with Prosigna® in two external cohorts. Prognostic value was assessed using distant recurrence-free interval.ResultsIn the test set, agreement between SSP and NC classifications for PAM50 (five subtypes) and Subtype (four subtypes) was high (85%, Kappa=0.78) and very high (90%, Kappa=0.84) respectively. Accuracy for ROR risk category was high (84%, Kappa=0.75, weighted Kappa=0.90). The prognostic value for SSP and NC was assessed as equivalent. Agreement for SSP and histopathology was very high or high for receptor status, while moderate and poor for Ki67 status and Nottingham histological grade, respectively. SSP concordance with Prosigna® was high for subtype and moderate and high for ROR risk category. In pooled analysis, concordance between SSP and Prosigna® for emulated treatment recommendation for chemotherapy (yes vs. no) was high (85%, Kappa=0.66). In postmenopausal ER+/HER2-/N0 patients SSP application suggested changed treatment recommendations for up to 17% of patients, with nearly balanced escalation and de-escalation of chemotherapy.ConclusionsSSP models for histopathological variables, PAM50, and ROR classifications can be derived from RNA-sequencing that closely matches clinical tests. Agreement and outcome analyses suggest that NC and SSP models are interchangeable on a group-level and nearly so on a patient level. Retrospective evaluation in postmenopausal ER+/HER2-/N0 patients suggested that molecular testing could lead to a changed therapy recommendation for almost one-fifth of patients

An integral method for solving nonlinear eigenvalue problems

We propose a numerical method for computing all eigenvalues (and the corresponding eigenvectors) of a nonlinear holomorphic eigenvalue problem that lie within a given contour in the complex plane. The method uses complex integrals of the resolvent operator, applied to at least $k$ column vectors, where $k$ is the number of eigenvalues inside the contour. The theorem of Keldysh is employed to show that the original nonlinear eigenvalue problem reduces to a linear eigenvalue problem of dimension $k$. No initial approximations of eigenvalues and eigenvectors are needed. The method is particularly suitable for moderately large eigenvalue problems where $k$ is much smaller than the matrix dimension. We also give an extension of the method to the case where $k$ is larger than the matrix dimension. The quadrature errors caused by the trapezoid sum are discussed for the case of analytic closed contours. Using well known techniques it is shown that the error decays exponentially with an exponent given by the product of the number of quadrature points and the minimal distance of the eigenvalues to the contour