Lepto-hadronic model for the broadband emission of Cygnus X-1

Cygnus X-1 is a well observed microquasar. Broadband observations at all wavelengths have been collected over the years. The origin of the MeV tail observed with COMPTEL and INTEGRAL is still under debate and it has mostly been attributed to the corona, although its high degree of polarization suggests it is synchrotron radiation from a jet. The origin of the transient emission above $\sim 100$ GeV is also unclear. We aim to disentangle the origin of the broadband spectral energy distribution (SED) of Cygnus X-1, focusing particularly on the gamma-ray emission, and to gain information on the physical conditions inside the jets. We develop and apply a lepto-hadronic, inhomogeneous jet model to the non-thermal SED of Cygnus X-1. We calculate the contributions to the SED of both protons and electrons accelerated in an extended region of the jet. We also estimate the radiation of charged secondaries produced in hadronic interactions, through several radiative processes. Absorption effects are considered. We produce synthetic maps of the jets at radio wavelengths. We find two sets of model parameters that lead to good fits of the SED. One of the models fits all the observations, including the MeV tail. This model also predicts hadronic gamma-ray emission slightly below the current upper limits. The flux predicted at 8.4 GHz is in agreement with the observations available in the literature, although the synthetic source is more compact than the imaged radio jet. Our results show that the MeV emission in Cygnus X-1 may be jet synchrotron radiation. This depends mainly on the strength of the jet magnetic field and the location of the injection region of the relativistic particles. Our calculations show that there must be energetic electrons in the jets quite far from the black hole.Comment: Accepted for publication in A&

Partial AUC Estimation and Regression

Accurate disease diagnosis is critical for health care. New diagnostic and screening tests must be evaluated for their abilities to discriminate disease from non-diseased states. The partial area under the ROC curve (partial AUC) is a measure of diagnostic test accuracy. We present an interpretation of the partial AUC that gives rise to a new non-parametric estimator. This estimator is more robust than existing estimators, which make parametric assumptions. We show that the robustness is gained with only a moderate loss in efficiency. We describe a regression modelling framework for making inference about covariate effects on the partial AUC. Such models can help refine an understanding of test accuracy. Model parameters can be estimated using binary regression methods. We use the regression framework to compare two Prostate-Specific Antigen biomarkers and to evaluate the dependence of biomarker accuracy on the time prior to clinical diagnosis of prostate cancer

Concepción heroica Homérica en The Lord of the rings

Fil: Pepe de Suárez, Luz E. A.

Semi-parametric Regression for the Area Under the Receiver Operating Characteristic Curve

Medical advances continue to provide new and potentially better means for detecting disease. Such is true in cancer, for example, where biomarkers are sought for early detection and where improvements in imaging methods may pick up the initial functional and molecular changes associated with cancer development. In other binary classification tasks, computational algorithms such as Neural Networks, Support Vector Machines and Evolutionary Algorithms have been applied to areas as diverse as credit scoring, object recognition, and peptide-binding prediction. Before a classifier becomes an accepted technology, it must undergo rigorous evaluation to determine its ability to discriminate between states. Characterization of factors influencing classier performance is an important step in this process. Analysis of covariates may reveal sub-populations in which classifier performance is greatest or identify features of the classifier that improve accuracy. We develop regression methods for the non-parametric area under the ROC curve, a well-accepted summary measure of classifier accuracy. The estimating function generalizes standard approaches, and, interestingly, is related to the two-sample Mann-Whitney U-statistic. Implementation is straightforward as it is an adaptation of binary regression methods. Asymptotic theory is non-standard because the regressor variables are cross-correlated. Nevertheless, simulation studies show the method produces estimates with small bias and reasonable coverage probability. Application of the method to evaluate the covariate effects on a new device for diagnosing hearing impairment reveals that the device performs better in the more severely impaired subjects and that certain test parameters, which are adjustable by the device operator, are key to test performance

Study of M2 polarization in mouse brain

Microglia are the resident immunocompetent cells of the central nervous system (CNS), which immediately react to any neurological insult to remove the damaging stimulus and restore tissue homeostasis. Similarly to peripheral macrophages, infective stimuli induce these cells to undergo a classical proinflammatory response (M1 activation), characterized by the production of inflammatory mediators, while in response to IL-4/IL-13 an \u201calternative\u201d activation state is induced (M2 polarization), which is associated with the expression of anti-inflammatory molecules that lead to tissue repair and reconstruction. Several studies suggest the existence of heterogeneous populations of microglia in different areas of the brain, with differences reported in cell density and morphology, proliferation rate, expression of immunoregolatory proteins and in response to TNF-\u3b1. The region-specific difference in microglial phenotypes has been ascribed to microenvoirmental signals and is suggestive of specific microglial functions. Since several CNS diseases involve specific brain regions, the region-specific reactivity of microglia could play a key role in preventing or potentiating disease progression. The aim of this study was thus to evaluate whether microglia show a region-specific M2 response. We induced M2 polarization in vivo by injecting IL-4 in the cerebroventricular space (icv), using different IL-4 concentrations and length of treatments. Through realtime-PCR, Western blot and immunohistochemistry analyses we evaluated the expression of M2 markers, such as Arg1, Fizz-1 and YM-1 in different brain areas. Our preliminary results show that our icv IL-4 model provides a novel and reliable manner to study M2 activation in brain; more importantly, our data show that the expression profile of M2 markers in glial cells might be region-specific. These results suggest that glial populations residing in different cerebral areas undergo specific M2 responses, with interesting consequences on the role of microglia in neurodegenerative diseases

Feedback Volterra control of integro-differential equations

This paper describes a general physical background that originates integro-differential problems with specific reference to aero-elastic coupling, and offers two techniques of control for this class of problems. The central result of the paper is that integro-differential equations with kernel exponential series admit an optimal solution described, in turn, by a Volterra integral equation in terms of the control. Numerical simulations show how controls prevent the flutter instability of a two-dimensional wing and a wind turbine blade

Retention, retention, retention: targeting the young in CPR skills training!

The usefulness of basic cardiopulmonary resuscitation (CPR) training in school systems has been questioned, considering that young students may not have the physical or cognitive skills required to perform complex tasks correctly. In the study conducted by Fleishhackl and coworkers, students as young as 9 years were able to successfully and effectively learn basic CPR skills, including automated external defibrillator deployment, correct recovery position, and emergency calling. As in adults, physical strength may limit the depth of chest compressions and ventilation volumes given by younger individuals with low body mass index; however, skill retention is good. Training all persons across an entire community in CPR may have a logarithmic improvement in survival rates for out-of-hospital cardiac arrest because bystanders, usually family members, are more likely to know CPR and can perform it immediately, when it is physiologically most effective. Training captured audiences of trainees, such as the entire work-force of the community or the local school system, are excellent mechanisms to help achieve that goal. In addition to better retention with new half hour training kits, a multiplier effect can be achieved through school children. In addition, early training not only sets the stage for subsequent training and better retention, but it also reinforces the concept of a social obligation to help others

TW Hydrae: evidence of stellar spots instead of a Hot Jupiter

TW Hydrae shows significant radial-velocity variations in the optical regime. They have been attributed to a 10 Jupiter Mass planet orbiting the star at 0.04 AU. In this work, we have tested whether the observed RV variations can be caused by stellar spots. We have also analyzed new optical and infrared data to confirm the signal of the planet companion. We fitted the RV variations of TW Hya using a cool spot model. Our model shows that a cold spot covering 7% of the stellar surface and located at a latitude of 54 deg can reproduce the reported RV variations. The model also predicts a bisector semi-amplitude variation <10 m/s, which is less than the errors of the RV measurements discussed in an earlier publication. The analysis of new optical RV data, with typical errors of 10 m/s, shows a larger RV amplitude that varies depending on the correlation mask used. A slight correlation between the RV variation and the bisector is also observed, although not at a very significant level. The infrared H-band RV curve is almost flat, showing a small variation (<35 m/s) that is not consistent with the optical orbit. All these results support the spot scenario rather than the presence of a hot Jupiter around TW Hya.Comment: accepted for publication in A&

Detection of activity and position of speakers by using deep neural networks and acoustic data augmentation

The task of Speaker LOCalization (SLOC) has been the focus of numerous works in the research field, where SLOC is performed on pure speech data, requiring the presence of an Oracle Voice Activity Detection (VAD) algorithm. Nevertheless, this perfect working condition is not satisfied in a real world scenario, where employed VADs do commit errors. This work addresses this issue with an extensive analysis focusing on the relationship between several data-driven VAD and SLOC models, finally proposing a reliable framework for VAD and SLOC. The effectiveness of the approach here discussed is assessed against a multi-room scenario, which is close to a real-world environment. Furthermore, up to the authors’ best knowledge, only one contribution proposes a unique framework for VAD and SLOC acting in this addressed scenario; however, this solution does not rely on data-driven approaches. This work comes as an extension of the authors’ previous research addressing the VAD and SLOC tasks, by proposing numerous advancements to the original neural network architectures. In details, four different models based on convolutional neural networks (CNNs) are here tested, in order to easily highlight the advantages of the introduced novelties. In addition, two different CNN models go under study for SLOC. Furthermore, training of data-driven models is here improved through a specific data augmentation technique. During this procedure, the room impulse responses (RIRs) of two virtual rooms are generated from the knowledge of the room size, reverberation time and microphones and sources placement. Finally, the only other framework for simultaneous detection and localization in a multi-room scenario is here taken into account to fairly compare the proposed method. As result, the proposed method is more accurate than the baseline framework, and remarkable improvements are specially observed when the data augmentation techniques are applied for both the VAD and SLOC tasks