A Dynamic Era-Based Time-Symmetric Block Time-Step Algorithm with Parallel Implementations

The time-symmetric block time--step (TSBTS) algorithm is a newly developed efficient scheme for $N$--body integrations. It is constructed on an era-based iteration. In this work, we re-designed the TSBTS integration scheme with dynamically changing era size. A number of numerical tests were performed to show the importance of choosing the size of the era, especially for long time integrations. Our second aim was to show that the TSBTS scheme is as suitable as previously known schemes for developing parallel $N$--body codes. In this work, we relied on a parallel scheme using the copy algorithm for the time-symmetric scheme. We implemented a hybrid of data and task parallelization for force calculation to handle load balancing problems that can appear in practice. Using the Plummer model initial conditions for different numbers of particles, we obtained the expected efficiency and speedup for a small number of particles. Although parallelization of the direct $N$--body codes is negatively affected by the communication/calculation ratios, we obtained good load balance results. Moreover, we were able to conserve the advantages of the algorithm (e.g., energy conservation for long--term simulations).Comment: 18 pages, 11 figures, accepted for publication in PAS

Price Setting Behavior in Turkish Industries: Evidence From Survey Data

This study investigates the price setting behavior of Turkish industries based on the results of a survey that was conducted by the Central Bank of the Republic of Turkey. The results show that under normal conditions, the majority of the firms follow time-dependent pricing rule but when significant events occur substantial fraction of them alter their behavior to state dependent reviewing. The median Turkish firm reviews its prices every month, but changes its prices four times a year. Price reviews and changes are affected by: the market share, price discrimination, customer type, firm size and the existence of regulated prices.price-setting, price-rigidity, survey

Projections for Neutral Di-Boson and Di-Higgs Interactions at FCC-he Collider

As a high energy e-p collider, FCC-he, has been recently proposed with sufficient energy options to investigate Higgs couplings. To analyse the sensitivity on the Higgs boson couplings, we focus spesifically on the CP-even and CP-odd Wilson coefficients with $hhZZ\:$and $hh\gamma\gamma\:$ four-point interactions of Higgs boson with Effective Lagrangian Model through the process $e^{-}p\to hhje^{-}$ . We simulate the related processes in FCC-he, with 60 GeV and 120 GeV $e^{-}$ beams and 50 TeV proton beam collisions. We present the exclusion limits on these couplings both for 68% and 95% C.L. in terms of integrated luminosities.Comment: 18 pages, 20 figures, 3 table

Probing Charged Higgs Boson Couplings at the FCC-hh Collider

Many of the new physics models predicts a light Higgs boson similar to the Higgs boson of the Standard Model (SM) and also extra scalar bosons. Beyond the search channels for a SM Higgs boson, the future collider experiments will explore additional channels that are specific to extended Higgs sectors. We study the charged Higgs boson production within the framework of two Higgs doublet models (THDM) in the proton-proton collisions at the FCC-hh collider. With an integrated luminosity of 500 fb$^{-1}$ at very high energy frontier, we obtain a significant coverage of the parameter space and distinguish the charged Higgs-top-bottom interaction within the THDM or other new physics models with charged Higgs boson mass up to 1 TeV.Comment: 22 pages, 26 figures, 6 table

Using multiple visual tandem streams in audio-visual speech recognition

The method which is called the "tandem approach" in speech recognition has been shown to increase performance by using classifier posterior probabilities as observations in a hidden Markov model. We study the effect of using visual tandem features in audio-visual speech recognition using a novel setup which uses multiple classifiers to obtain multiple visual tandem features. We adopt the approach of multi-stream hidden Markov models where visual tandem features from two different classifiers are considered as additional streams in the model. It is shown in our experiments that using multiple visual tandem features improve the recognition accuracy in various noise conditions. In addition, in order to handle asynchrony between audio and visual observations, we employ coupled hidden Markov models and obtain improved performance as compared to the synchronous model

Do Girls Really Outperform Boys in Educational Outcomes?

The reversing gender gap observed in many countries led to a heated debate to explain the persistent gap in academia and other top fields despite the reversal. This paper aims at analyzing the gender gap in education outcomes from different evaluation and exam techniques and gender gap in outcomes of college applications using Turkish administrative data. In Turkey, university applications are centralized based on a standardized test. Assignments of applicants depend on an assignment score which is calculated as a weighted sum of standardized test score and high school GPA with a little contribution from the latter. I find considerable gender gap in favor of females in high school GPAs which is a long term evaluation of students based on every written exam during high school while the female outperformance is not as obvious in standardized test scores which comes from a stressful 3 hours multiple choice test. I also analyze the gender gap in college application outcomes and show that females are less likely to be assigned to a top major conditional on test scores. These findings contribute to the discussion of gender gap in performance in education suggesting that evaluation systems might have gender biased impacts on students and underrepresentation of females in top fields and/or universities can not be explained only by mean differences in test scores and test score distributions

Gender Differences in College Applications: Evidence from the Centralized System in Turkey

In Turkey, as in many other countries, female students perform better in high school and have higher test scores than males. Nevertheless, men still predominate at highly selective programs that lead to high-paying careers. The gender gap at elite schools is particularly puzzling because college admissions are based entirely on nationwide exam scores. Using detailed administrative data from the centralized college entrance system, I study the impact of gender differences in preferences for programs and schools on the allocation of students to colleges. Controlling for test score and high school attended, I find that females are more likely to apply to lower-ranking schools, whereas males set a higher bar, revealing a higher option value for re-taking the test and applying again next year. I also find that females and males value program attributes differently, with females placing more weight on the distance from home to college, and males placing more weight on program attributes that are likely to lead to better job placements. Together, these differences in willingness to be unassigned and in relative preferences for school attributes can explain much of the gender gap at the most elite programs

EEG theta and Mu oscillations during perception of human and robot actions.

The perception of others' actions supports important skills such as communication, intention understanding, and empathy. Are mechanisms of action processing in the human brain specifically tuned to process biological agents? Humanoid robots can perform recognizable actions, but can look and move differently from humans, and as such, can be used in experiments to address such questions. Here, we recorded EEG as participants viewed actions performed by three agents. In the Human condition, the agent had biological appearance and motion. The other two conditions featured a state-of-the-art robot in two different appearances: Android, which had biological appearance but mechanical motion, and Robot, which had mechanical appearance and motion. We explored whether sensorimotor mu (8-13 Hz) and frontal theta (4-8 Hz) activity exhibited selectivity for biological entities, in particular for whether the visual appearance and/or the motion of the observed agent was biological. Sensorimotor mu suppression has been linked to the motor simulation aspect of action processing (and the human mirror neuron system, MNS), and frontal theta to semantic and memory-related aspects. For all three agents, action observation induced significant attenuation in the power of mu oscillations, with no difference between agents. Thus, mu suppression, considered an index of MNS activity, does not appear to be selective for biological agents. Observation of the Robot resulted in greater frontal theta activity compared to the Android and the Human, whereas the latter two did not differ from each other. Frontal theta thus appears to be sensitive to visual appearance, suggesting agents that are not sufficiently biological in appearance may result in greater memory processing demands for the observer. Studies combining robotics and neuroscience such as this one can allow us to explore neural basis of action processing on the one hand, and inform the design of social robots on the other