Globular Cluster Streams as Galactic High-Precision Scales - The Poster Child Palomar 5

Using the example of the tidal stream of the Milky Way globular cluster Palomar 5 (Pal 5), we demonstrate how observational data on streams can be efficiently reduced in dimensionality and modeled in a Bayesian framework. Our approach combines detection of stream overdensities by a Difference-of-Gaussians process with fast streakline models, a continuous likelihood function built from these models, and inference with MCMC. By generating $\approx10^7$ model streams, we show that the geometry of the Pal 5 debris yields powerful constraints on the solar position and motion, the Milky Way and Pal 5 itself. All 10 model parameters were allowed to vary over large ranges without additional prior information. Using only SDSS data and a few radial velocities from the literature, we find that the distance of the Sun from the Galactic Center is $8.30\pm0.25$ kpc, and the transverse velocity is $253\pm16$ km/s. Both estimates are in excellent agreement with independent measurements of these quantities. Assuming a standard disk and bulge model, we determine the Galactic mass within Pal 5's apogalactic radius of 19 kpc to be $(2.1\pm0.4)\times10^{11}$ M$_\odot$. Moreover, we find the potential of the dark halo with a flattening of $q_z = 0.95^{+0.16}_{-0.12}$ to be essentially spherical within the radial range that is effectively probed by Pal 5. We also determine Pal 5's mass, distance and proper motion independently from other methods, which enables us to perform vital cross-checks. We conclude that with more observational data and by using additional prior information, the precision of this method can be significantly increased.Comment: 28 pages, 14 figures, submitted to ApJ (revised version), comments welcom

The leading Ruelle resonances of chaotic maps

The leading Ruelle resonances of typical chaotic maps, the perturbed cat map and the standard map, are calculated by variation. It is found that, excluding the resonance associated with the invariant density, the next subleading resonances are, approximately, the roots of the equation $z^4=\gamma$, where $\gamma$ is a positive number which characterizes the amount of stochasticity of the map. The results are verified by numerical computations, and the implications to the form factor of the corresponding quantum maps are discussed.Comment: 5 pages, 4 figures included. To appear in Phys. Rev.

Renormalization of Quantum Anosov Maps: Reduction to Fixed Boundary Conditions

A renormalization scheme is introduced to study quantum Anosov maps (QAMs) on a torus for general boundary conditions (BCs), whose number ($k$) is always finite. It is shown that the quasienergy eigenvalue problem of a QAM for {\em all} $k$ BCs is exactly equivalent to that of the renormalized QAM (with Planck's constant $\hbar ^{\prime}=\hbar /k$) at some {\em fixed} BCs that can be of four types. The quantum cat maps are, up to time reversal, fixed points of the renormalization transformation. Several results at fixed BCs, in particular the existence of a complete basis of ``crystalline'' eigenstates in a classical limit, can then be derived and understood in a simple and transparent way in the general-BCs framework.Comment: REVTEX, 12 pages, 1 table. To appear in Physical Review Letter

Reversible Nanoparticle–Micelle Transformation of Ionic Liquid–Sulfonatocalix[6]arene Aggregates

The effect of temperature and NaCl concentration variations on the self-assembly of 1-methyl-3- tetradecylimidazolium (C14mim+) and 4-sulfonatocalix[6]- arene (SCX6) was studied by dynamic light scattering and isothermal calorimetric methods at pH 7. Inclusion complex formation promoted the self-assembly to spherical nanoparticles (NP), which transformed to supramolecular micelles (SM) in the presence of NaCl. Highly reversible, temperature-responsive behavior was observed, and the conditions of the NP−SM transition could be tuned by the alteration of C14mim+:SCX6 mixing ratio and NaCl concentration. The association to SM was always exothermic with enthalpy independent of the amount of NaCl. In contrast, NPs were produced in endothermic process at low temperature, and the enthalpy change became less favorable upon increase in NaCl concentration. The NP formation was accompanied by negative molar heat capacity change, which further diminished when NaCl concentration was raised

On the Experimental Analysis of Integral Sliding Modes for Yaw Rate and Sideslip Control of an Electric Vehicle with Multiple Motors

With the advent of electric vehicles with multiple motors, the steady-state and transient cornering responses can be designed and implemented through the continuous torque control of the individual wheels, i.e., torque-vectoring or direct yaw moment control. The literature includes several papers on sliding mode control theory for torque-vectoring, but the experimental investigation is so far limited. More importantly, to the knowledge of the authors, the experimental comparison of direct yaw moment control based on sliding modes and typical controllers used for stability control in production vehicles is missing. This paper aims to reduce this gap by presenting and analyzing an integral sliding mode controller for concurrent yaw rate and sideslip control. A new driving mode, the Enhanced Sport mode, is proposed, inducing sustained high values of sideslip angle, which can be limited to a specified threshold. The system is experimentally assessed on a four-wheel-drive electric vehicle. The performance of the integral sliding mode controller is compared with that of a linear quadratic regulator during step steer tests. The results show that the integral sliding mode controller significantly enhances the tracking performance and yaw damping compared to the more conventional linear quadratic regulator based on an augmented singletrack vehicle model formulation. © 2018, The Korean Society of Automotive Engineers and Springer-Verlag GmbH Germany, part of Springer Natur

Fast relational learning using bottom clause propositionalization with artificial neural networks

Relational learning can be described as the task of learning first-order logic rules from examples. It has enabled a number of new machine learning applications, e.g. graph mining and link analysis. Inductive Logic Programming (ILP) performs relational learning either directly by manipulating first-order rules or through propositionalization, which translates the relational task into an attribute-value learning task by representing subsets of relations as features. In this paper, we introduce a fast method and system for relational learning based on a novel propositionalization called Bottom Clause Propositionalization (BCP). Bottom clauses are boundaries in the hypothesis search space used by ILP systems Progol and Aleph. Bottom clauses carry semantic meaning and can be mapped directly onto numerical vectors, simplifying the feature extraction process. We have integrated BCP with a well-known neural-symbolic system, C-IL2P, to perform learning from numerical vectors. C-IL2P uses background knowledge in the form of propositional logic programs to build a neural network. The integrated system, which we call CILP++, handles first-order logic knowledge and is available for download from Sourceforge. We have evaluated CILP++ on seven ILP datasets, comparing results with Aleph and a well-known propositionalization method, RSD. The results show that CILP++ can achieve accuracy comparable to Aleph, while being generally faster, BCP achieved statistically significant improvement in accuracy in comparison with RSD when running with a neural network, but BCP and RSD perform similarly when running with C4.5. We have also extended CILP++ to include a statistical feature selection method, mRMR, with preliminary results indicating that a reduction of more than 90 % of features can be achieved with a small loss of accuracy

Knowledge about and attitude towards COVID-19 vaccination of rural residents in Zambales, Philippines

Vaccines are among the most effective preventive measures developed to minimize the risks of COVID-19. This cross-sectional study employs an online survey to determine the knowledge and attitude toward COVID-19 vaccination among the general population in rural Zambales, Philippines. A total of 690 residents responded to the knowledge and attitude towards COVID-19 vaccination survey questionnaire (KAC19V-SQ) regarding the residents' knowledge about and attitude towards COVID-19 vaccination. Television, Facebook and YouTube are the residents' primary sources of COVID-19 vaccine information. Almost all of them (98.0%) know about the COVID-19 vaccine, but only 81.3% of the residents know about its effectiveness. Most (69.7%) indicated they want to get vaccinated. Zambales residents' knowledge about COVID-19 vaccination was low. Despite having a low level of knowledge, respondents showed a favorable attitude (mean±SD:2.76±0.47) toward COVID-19 vaccination. Women had a less favorable attitude than men. Furthermore, a moderately positive correlation (r=0.511, p<0.01) was noted between knowledge and attitude towards COVID-19 vaccination. It is imperative that the government works in tandem with public health experts, local government officials, and academic institutions to develop and implement initiatives geared towards enhancing public awareness and fostering a positive outlook towards COVID-19 vaccination

Cause of Death and Predictors of All-Cause Mortality in Anticoagulated Patients With Nonvalvular Atrial Fibrillation : Data From ROCKET AF

M. Kaste on työryhmän ROCKET AF Steering Comm jäsen.Background-Atrial fibrillation is associated with higher mortality. Identification of causes of death and contemporary risk factors for all-cause mortality may guide interventions. Methods and Results-In the Rivaroxaban Once Daily Oral Direct Factor Xa Inhibition Compared with Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation (ROCKET AF) study, patients with nonvalvular atrial fibrillation were randomized to rivaroxaban or dose-adjusted warfarin. Cox proportional hazards regression with backward elimination identified factors at randomization that were independently associated with all-cause mortality in the 14 171 participants in the intention-to-treat population. The median age was 73 years, and the mean CHADS(2) score was 3.5. Over 1.9 years of median follow-up, 1214 (8.6%) patients died. Kaplan-Meier mortality rates were 4.2% at 1 year and 8.9% at 2 years. The majority of classified deaths (1081) were cardiovascular (72%), whereas only 6% were nonhemorrhagic stroke or systemic embolism. No significant difference in all-cause mortality was observed between the rivaroxaban and warfarin arms (P=0.15). Heart failure (hazard ratio 1.51, 95% CI 1.33-1.70, P= 75 years (hazard ratio 1.69, 95% CI 1.51-1.90, P Conclusions-In a large population of patients anticoagulated for nonvalvular atrial fibrillation, approximate to 7 in 10 deaths were cardiovascular, whereasPeer reviewe

Modeling of leishmaniasis infection dynamics: novel application to the design of effective therapies

<p>Abstract</p> <p>Background</p> <p>The WHO considers leishmaniasis as one of the six most important tropical diseases worldwide. It is caused by parasites of the genus <it>Leishmania </it>that are passed on to humans and animals by the phlebotomine sandfly. Despite all of the research, there is still a lack of understanding on the metabolism of the parasite and the progression of the disease. In this study, a mathematical model of disease progression was developed based on experimental data of clinical symptoms, immunological responses, and parasite load for <it>Leishmania amazonensis </it>in <it>BALB/c </it>mice.</p> <p>Results</p> <p>Four biologically significant variables were chosen to develop a differential equation model based on the GMA power-law formalism. Parameters were determined to minimize error in the model dynamics and time series experimental data. Subsequently, the model robustness was tested and the model predictions were verified by comparing them with experimental observations made in different experimental conditions. The model obtained helps to quantify relationships between the selected variables, leads to a better understanding of disease progression, and aids in the identification of crucial points for introducing therapeutic methods.</p> <p>Conclusions</p> <p>Our model can be used to identify the biological factors that must be changed to minimize parasite load in the host body, and contributes to the design of effective therapies.</p

ENGAGING LEARNERS IN MATHEMATICS 2 ACTIVITIES THROUGH MARIS-PARES TECHNIQUE

This study was conducted to increase pupils’ level of engagement in Mathematics II. Due to the limited classroom interaction in the new normal set-up, learners have developed passive behavior in participating in different classroom activities. One of the subjects where pupils show poor engagement is Mathematics. Hence, we designed an intervention to improve the passive behavior of Grade 2 learners and increase their level of engagement in Mathematics. The data were obtained from the twelve (12) identified passive Grade 2 learners. Purposive sampling was employed in identifying the subjects of the study. Pre-observation was conducted to determine the level of engagement of the respondents, which was followed by the post-observation after the Maris-Pares Technique was implemented. Mean and t-test were used to treat the gathered data. Before the implementation of the intervention, the respondents were slightly engaged in Mathematics. The findings revealed that the Maris-Pares Technique contributes to the improvement of the Mathematics engagement of the respondents. Hence, the more the respondents are exposed to the Maris-Pares Technique, the higher the chance of their engagement in Mathematics activities.  Article visualizations