Jet Dynamics in Black Hole Fields: A Collimation Mechanism

We study the axial collimation of the vortical geodesics in the field of a rotating black hole. This effect manifests itself when the energy and angular momenta of the particles that move on those geodesics vary slowly in dynamical time. In this paper we deduce the constraints that ensure collimation and show how the latter arises when the orbital parameters are perturbed by a given electromagnetic field or by pressure gradients

Adjuvant radiation therapy in stage I seminoma: 20 years of oncologic results

Aim: To report long term oncologic outcomes after adjuvant radiotherapy (RT) for stage I seminoma. Method: We reviewed the complete data set for all patients treated at our institute between 1988 and 2005 for stage I seminoma with adjuvant RT after radical orchiectomy. Results: A total of 85 patients were included. The median follow-3up was 15 years. The 20-3year overall survival (OS) and relapse free survival (RFS) were 92% and 96.3%, respectively. No severe acute and late complications were recorded. Overall 5.9% of patients had a second unrelated malignancy. Conclusion: Adjuvant RT is an efficacious and safe treatment in stage I seminom

Unifying Einstein and Palatini gravities

We consider a novel class of $f(\R)$ gravity theories where the connection is related to the conformally scaled metric $\hat g_{\mu\nu}=C(\R)g_{\mu\nu}$ with a scaling that depends on the scalar curvature $\R$ only. We call them C-theories and show that the Einstein and Palatini gravities can be obtained as special limits. In addition, C-theories include completely new physically distinct gravity theories even when $f(\R)=\R$. With nonlinear $f(\R)$, C-theories interpolate and extrapolate the Einstein and Palatini cases and may avoid some of their conceptual and observational problems. We further show that C-theories have a scalar-tensor formulation, which in some special cases reduces to simple Brans-Dicke-type gravity. If matter fields couple to the connection, the conservation laws in C-theories are modified. The stability of perturbations about flat space is determined by a simple condition on the lagrangian.Comment: 17 pages, no figure

Purification and partial characterization of bacillocin 490, a novel bacteriocin produced by a thermophilic strain of Bacillus licheniformis

BACKGROUND: Applications of bacteriocins as food preservatives have been so far limited, principally because of their low antimicrobial activity in foods. Nisin is the only bacteriocin of significant use, but applications are restricted principally because of its very low activity at neutral or alkaline pH. Thus the isolation of new bacteriocins active in foods is desirable. RESULTS: We isolated a Bacillus licheniformis thermophilic strain producing a bacteriocin with some novel features, named here bacillocin 490. This bacteriocin was inactivated by pronase E and proteinase K and was active against closely related Bacillus spp. both in aerobic and in anaerobic conditions. Bactericidal activity was kept during storage at 4°C and was remarkably stable in a wide pH range. The bacteriocin was partially purified by elution after adhesion to cells of the food-isolated strain Bacillus smithii and had a rather low mass (2 KDa). Antimicrobial activity against B. smithii was observed also when this organism was grown in water buffalo milk. CONCLUSIONS: Bacillocin 490 is a novel candidate as a food anti-microbial agent since it displays its activity in milk, is stable to heat treatment and during storage, is active in a wide pH range and has bactericidal activity also at high temperature. These features may allow the use of bacillocin 490 during processes performed at high temperature and as a complementary antimicrobial agent of nisin against some Bacillus spp. in non-acidic foods. The small size suggests its use on solid foods

Graph Drawing via Gradient Descent, (GD)2(GD)^2

Readability criteria, such as distance or neighborhood preservation, are often used to optimize node-link representations of graphs to enable the comprehension of the underlying data. With few exceptions, graph drawing algorithms typically optimize one such criterion, usually at the expense of others. We propose a layout approach, Graph Drawing via Gradient Descent, $(GD)^2$, that can handle multiple readability criteria. $(GD)^2$ can optimize any criterion that can be described by a smooth function. If the criterion cannot be captured by a smooth function, a non-smooth function for the criterion is combined with another smooth function, or auto-differentiation tools are used for the optimization. Our approach is flexible and can be used to optimize several criteria that have already been considered earlier (e.g., obtaining ideal edge lengths, stress, neighborhood preservation) as well as other criteria which have not yet been explicitly optimized in such fashion (e.g., vertex resolution, angular resolution, aspect ratio). We provide quantitative and qualitative evidence of the effectiveness of $(GD)^2$ with experimental data and a functional prototype: \url{http://hdc.cs.arizona.edu/~mwli/graph-drawing/}.Comment: Appears in the Proceedings of the 28th International Symposium on Graph Drawing and Network Visualization (GD 2020

Survival analysis using the Covid-death mean-imputation (CoDMI) algorithm: a first clinical application in radiation oncology

Background/Aim: To report long-term survival results after trimodal approach for locally advanced rectal cancer (LARC) in the Covid-19 era. We herein illustrate a clinical application of Covid-death mean-imputation (CoDMI) algorithm in LARC patients with Covid-19 infection. Patients and Methods: We analyzed 94 patients treated for primary LARC. Overall survival was calculated in months from diagnosis to first event (last follow-up/death). Because Covid-19 death events potentially bias survival estimation, to eliminate skewed data due to Covid-19 death events, the observed lifetime of Covid-19 cases was replaced by its corresponding expected lifetime in absence of the Covid-19 event using the CoDMI algorithm. Patients who died of Covid-19 (DoC) are mean-imputed by the Kaplan-Meier estimator. Under this approach, the observed lifetime of each DoC patient is considered as an "incomplete data" and is extended by an additional expected lifetime computed using the classical Kaplan-Meier model. Results: Sixteen patients were dead of disease (DoD), 1 patient was DoC and 77 cases were censored (Cen). The DoC patient died of Covid-19 52 months after diagnosis. The CoDMI algorithm computed the expected future lifetime provided by the Kaplan-Meier estimator applied to the no-DoC observations as well as to the DoC data itself. Given the DoC event at 52 months, the CoDMI algorithm estimated that this patient would have died after 79.5 months of follow-up. Conclusion: The CoDMI algorithm leads to "unbiased" probability of overall survival in LARC patients with Covid-19 infection, compared to that provided by a naive application of Kaplan-Meier approach. This allows for a proper interpretation/use of Covid-19 events in survival analysis. A user-friendly version of CoDMI is freely available at https://github.com/alef-innovation/codmi