Nonlinear Dirac Equations

We construct nonlinear extensions of Dirac's relativistic electron equation that preserve its other desirable properties such as locality, separability, conservation of probability and Poincar\'e invariance. We determine the constraints that the nonlinear term must obey and classify the resultant non-polynomial nonlinearities in a double expansion in the degree of nonlinearity and number of derivatives. We give explicit examples of such nonlinear equations, studying their discrete symmetries and other properties. Motivated by some previously suggested applications we then consider nonlinear terms that simultaneously violate Lorentz covariance and again study various explicit examples. We contrast our equations and construction procedure with others in the literature and also show that our equations are not gauge equivalent to the linear Dirac equation. Finally we outline various physical applications for these equations

Information and Particle Physics

Information measures for relativistic quantum spinors are constructed to satisfy various postulated properties such as normalisation invariance and positivity. Those measures are then used to motivate generalised Lagrangians meant to probe shorter distance physics within the maximum uncertainty framework. The modified evolution equations that follow are necessarily nonlinear and simultaneously violate Lorentz invariance, supporting previous heuristic arguments linking quantum nonlinearity with Lorentz violation. The nonlinear equations also break discrete symmetries. We discuss the implications of our results for physics in the neutrino sector and cosmology

Integrable Hierarchies and Information Measures

In this paper we investigate integrable models from the perspective of information theory, exhibiting various connections. We begin by showing that compressible hydrodynamics for a one-dimesional isentropic fluid, with an appropriately motivated information theoretic extension, is described by a general nonlinear Schrodinger (NLS) equation. Depending on the choice of the enthalpy function, one obtains the cubic NLS or other modified NLS equations that have applications in various fields. Next, by considering the integrable hierarchy associated with the NLS model, we propose higher order information measures which include the Fisher measure as their first member. The lowest members of the hiearchy are shown to be included in the expansion of a regularized Kullback-Leibler measure while, on the other hand, a suitable combination of the NLS hierarchy leads to a Wootters type measure related to a NLS equation with a relativistic dispersion relation. Finally, through our approach, we are led to construct an integrable semi-relativistic NLS equation.Comment: 11 page

2-Chloro­quinoline-3-carbaldehyde

The quinolinyl fused ring system of the title compound, C10H6ClNO, is planar (r.m.s. deviation = 0.018 Å); the formyl group is slightly bent out of the plane of the fused ring system [C—C—C—O torsion angle = 8.2 (3)°]

Cochlear implant programming: a global survey on the state of the art

The programming of CIs is essential for good performance. However, no Good Clinical Practice guidelines exist. This paper reports on the results of an inventory of the current practice worldwide. A questionnaire was distributed to 47 CI centers. They follow 47600 recipients in 17 countries and 5 continents. The results were discussed during a debate. Sixty-two percent of the results were verified through individual interviews during the following months. Most centers (72%) participated in a cross-sectional study logging 5 consecutive fitting sessions in 5 different recipients. Data indicate that general practice starts with a single switch-on session, followed by three monthly sessions, three quarterly sessions, and then annual sessions, all containing one hour of programming and testing. The main focus lies on setting maximum and, to a lesser extent, minimum current levels per electrode. These levels are often determined on a few electrodes and then extrapolated. They are mainly based on subjective loudness perception by the CI user and, to a lesser extent, on pure tone and speech audiometry. Objective measures play a small role as indication of the global MAP profile. Other MAP parameters are rarely modified. Measurable targets are only defined for pure tone audiometry. Huge variation exists between centers on all aspects of the fitting practice

Human wharton’s jelly-derived mesenchymal stem cells minimally improve the growth kinetics and cardiomyocyte differentiation of aged murine cardiac c-kit cells in in vitro without rejuvenating effect

Cardiac c-kit cells show promise in regenerating an injured heart. While heart disease commonly affects elderly patients, it is unclear if autologous cardiac c-kit cells are functionally competent and applicable to these patients. This study characterised cardiac c-kit cells (CCs) from aged mice and studied the effects of human Wharton’s Jelly-derived mesenchymal stem cells (MSCs) on the growth kinetics and cardiac differentiation of aged CCs in vitro. CCs were isolated from 4-week- and 18-month-old C57/BL6N mice and were directly co-cultured with MSCs or separated by transwell insert. Clonogenically expanded aged CCs showed comparable telomere length to young CCs. However, these cells showed lower Gata4, Nkx2.5, and Sox2 gene expressions, with changes of 2.4, 3767.0, and 4.9 folds, respectively. Direct co-culture of both cells increased aged CC migration, which repopulated 54.6 ± 4.4% of the gap area as compared to aged CCs with MSCs in transwell (42.9 ± 2.6%) and CCs without MSCs (44.7 ± 2.5%). Both direct and transwell co-culture improved proliferation in aged CCs by 15.0% and 16.4%, respectively, as traced using carboxyfluorescein succinimidyl ester (CFSE) for three days. These data suggest that MSCs can improve the growth kinetics of aged CCs. CCs retaining intact telomere are present in old hearts and could be obtained based on their self-renewing capability. Although these aged CCs with reduced growth kinetics are improved by MSCs via cell–cell contact, the effect is minimal

Denture Induced Submandibular Hematoma in a Patient on Warfarin

A 79-year-old lady, who was taking warfarin, presented to the Emergency Department with a painless anterior neck swelling, which was associated with hoarseness of voice, odynophagia, and shortness of breath. She first noticed the swelling after she removed her dentures in the evening. On examination, she had an increased respiratory rate. There was a large submandibular swelling at the anterior side of her neck. Upon mouth opening, there was a hematoma at the base of her tongue, which extended to both sides of the tonsillar pillars. The patient was intubated with a video laryngoscope due to her worsening respiratory distress. Intravenous vitamin K and fresh frozen plasma were given immediately. the patient was admitted to the ICU for ventilation and observation. the hematoma subsided after 2 days and she was discharged well

Anomaly Detection Using Agglomerative Hierarchical Clustering Algorithm

Intrusion detection is becoming a hot topic of research for the information security people. There are mainly two classes of intrusion detection techniques available till today namely anomaly detection techniques and signature recognition techniques. Anomaly detection techniques are becoming area of interest for the researchers and new techniques are developing every day. However, no techniques have been found to be absolutely perfect. Clustering is an important data mining techniques used to find patterns and data distribution in the datasets. It is mainly used to identify the dense regions and sparse regions in the datasets. The sparse regions were often considered as outliers. There are several clustering algorithms developed till today for the discovery outliers in the datasets. K-means algorithm. K-medoids algorithm, CLARA, CLARANS, DBSCAN, ROCK, BIRCH, CACTUS etc. are some of the popular algorithms dealing with numeric datasets, categorical datasets, spatial datasets or hybrid datasets. Clustering techniques have been successfully used in detection anomaly in dataset. The techniques were found to be useful in the design of a couple of anomaly based Intrusion Detection Systems (IDS). But most of clustering techniques used for these purpose have taken partitioning approach. In this article, we propose a different clustering algorithm for the anomaly detection on network datasets. Our algorithm is an agglomerative hierarchical clustering algorithm which tries to find clusters on the dataset consisting of both numeric and categorical datasets i.e. hybrid datasets. For this purpose, we define a suitable similarity measure on both numeric and categorical attributes available on any network datasets