THE TALENT VERSUS LUCK MODEL AS AN ENSEMBLE OF ONE-DIMENSIONAL RANDOM WALKS

The role of luck on individual success is hard to be investigated empirically. Simplified mathematical models are often used to shed light on the subtle relations between success and luck. Recently, a simple model called “Talent versus Luck” showed that the most successful individual in a population can be just an average talented individual that is subjected to a very fortunate sequence of events. Here, we modify the framework of the TvL model such that in our model the individuals’ success is modelled as an ensemble of one-dimensional random walks. Our model reproduces the original TvL results and, due to the mathematical simplicity, it shows clearly that the original conclusions of the TvL model are the consequence of two factors: first, the normal distribution of talents with low standard deviation, which creates a large number of average talented individuals; second, the low number of steps considered, which allows the observation of large fluctuations. We also show that the results strongly depend on the relative frequency of good and bad luck events, which defines a critical value for the talent: in the long run, the individuals with high talent end up very successful and those with low talent end up ruined. Last, we considered two variations to illustrate applications of the ensemble of random walks model.

Forecasting of Natural Gas Consumption in Poland Based on ARIMA-LSTM Hybrid Model

Natural gas is one of the main energy sources in Poland and accounts for about 15% of the primary energy consumed in the country. Poland covers only 1/5 of its demand from domestic deposits. The rest is imported from Russia, Germany, Norway, the Czech Republic, Ukraine, and Central Asia. An important issue concerning the market of energy resources is the question of the direct impact of the prices of energy resources on the income of exporting and importing countries. It should also be remembered that unexpected and large fluctuations are detrimental to both exporters and importers of primary fuels. The article analyzes natural gas deposits in Poland, raw material trade and proposes a model for forecasting the volume of its consumption, which takes into account historical consumption, prices of energy resources and assumptions of Poland’s energy policy until 2040. A hybrid model was built by combining ARIMA with LSTM artificial neural networks. The validity of the constructed model was assessed using ME, MAE, RMSE and MSE. The average percentage error is 2%, which means that the model largely represents the real gas consumption course. The obtained forecasts indicate an increase in consumption by 2040.

Regulation of Serotonin 1A Receptor SUMOylation by SENP2 and PIASxα

Serotonin 1A receptors (5-HT1ARs) are implicated in the control of mood, cognition, and memory and in various neuropsychiatric disorders such as depression and anxiety. As such, understanding the regulation of 5-HT1ARs will inform the development of better treatment approaches. We previously demonstrated 5-HT1ARs are SUMOylated by SUMO1 in the rat brain. Agonist stimulation increased SUMOylation and was further enhanced when combined with 17β-estradiol-3-benzoate (EB), which are treatments that cause the transient and prolonged desensitization of 5-HT1AR signaling, respectively. In the current study, we identified the protein inhibitor of activated STAT (PIAS)xα as the enzyme that facilitates SUMOylation, and SENP2 as the protein that catalyzes the deSUMOylation of 5-HT1ARs. We demonstrated that PIASxα significantly increased in the membrane fraction of rats co-treated with EB and an agonist, compared to either the EB-treated or vehicle-treated groups. The acute treatment with an agonist alone shifted the location of SENP2 from the membrane to the cytoplasmic fraction, but it has little effect on PIASxα. Hence, two separate mechanisms regulate SUMOylation and the activity of 5-HT1ARs by an agonist and EB. The effects of EB on 5-HT1AR SUMOylation and signaling may be related to the higher incidence of mood disorders in women during times with large fluctuations in estrogens. Targeting the SUMOylation of 5-HT1ARs could have important clinical relevance for the therapy for several neuropsychiatric disorders in which 5-HT1ARs are implicated.

Gravity waves and primordial black holes in scalar warm little inflation

In warm inflation, dissipation due to the interactions of the inflaton field to other light degrees of freedom leads naturally to the enhancement of the primordial spectrum during the last 10-20 efolds of inflation. We study this effect in a variant of the Warm Little Inflaton model, where the inflaton couples to light scalars, with a quartic chaotic potential. These large fluctuations on re-entry will form light, evaporating Primordial Black Holes, with masses lighter than 106 g. But at the same time they will act as a source for the tensors at second order. The enhancement is maximal near the end of inflation, which result in a spectral density of Gravitational Waves (GW) peaked at frequencies f ∼ O(105-106) Hz today, and with an amplitude ΩGW ∼ 10-9. Although the frequency range is outside the reach of present and planned GW detectors, it might be reached in future high-frequency gravitational waves detectors, designed to search for cosmological stochastic GW backgrounds above MHz frequencies.

Constraints on the End of Reionization from the Density Fields Surrounding Two Highly Opaque Quasar Sightlines

The observed large-scale scatter in Lyα opacity of the intergalactic medium at z < 6 implies large fluctuations in the neutral hydrogen fraction that are unexpected long after reionization has ended. A number of models have emerged to explain these fluctuations that make testable predictions for the relationship between Lyα opacity and density. We present selections of z = 5.7 Lyα-emitting galaxies (LAEs) in the fields surrounding two highly opaque quasar sightlines with long Lyα troughs. The fields lie toward the z = 6.0 quasar ULAS J0148+0600, for which we reanalyze previously published results using improved photometric selection, and toward the z = 6.15 quasar SDSS J1250+3130, for which results are presented here for the first time. In both fields, we report a deficit of LAEs within 20 h −1 Mpc of the quasar. The association of highly opaque sightlines with galaxy underdensities in these two fields is consistent with models in which the scatter in Lyα opacity is driven by large-scale fluctuations in the ionizing UV background or by an ultra-late reionization that has not yet concluded at z = 5.7.

Model for the catalytic reduction of no on a surface with species desorption and impurities that cannot desorb

The dynamical behavior of a modified Yaldram–Khan model for the catalytic reduction of NO on a surface is studied by Kinetic Monte Carlo simulations. In this modified model, temperature effects are incorporated as desorption rates of the N and CO species. How the presence of contaminants in the gas phase affects the catalytic process is also analyzed by including impurities that can be adsorbed on the lattice and once there remain inert. When N desorption is included, a reactive window appears that is not present in the original YK model on a square lattice. When CO desorption is added large fluctuations appear in the coverages, the system can take a long time to stabilize, during this period, a long lasting reactive state exists that disappears when the stability is reached. When nondesorbing impurities are added, the discontinuous transition to a CO poisoned phase that presents the original YK model disappears, the coverages become continuous, and a nonreactive steady-state is rapidly reached.

Direct Measurements of Cosmic Rays (TeV and beyond) Using an Ultrathin Calorimeter: Lessening Fluctuation Method

In this paper, we propose a method that makes it possible to use an ultrathin calorimeter for direct measurements of cosmic rays with energies of TeV and higher. The problems of determining the primary energy with a thin calorimeter, due to large fluctuations in shower development, the low statistics of analyzed events and the large size required for the calorimeter, are considered in detail. A solution to these problems is proposed on the basis of a lessening fluctuation method. This method is based on the assumption of the universality of the development of cascades initiated by particles of the same energy and mass. For energy reconstruction, so-called correlation curves are used. The main analyzed quantities are the size of the cascade and the rate of its development. The method was tested using the calorimeter of the PAMELA collaboration. Based on simulations, it is shown that the primary energy can be determined on the ascending branch of the cascade curve. This fact solves the problems associated with the need to increase the calorimeter thickness with an increase in primary energy and with the limitation of the analyzed events. The proposed technique is universal for different energies and different nuclei.

Artificial Neural Network for analyzing the chaotic time series motion: The case of the Lebanese GDP

In this paper, we propose to analyze the motion of the Lebanese GDP over the period 1950-2019. This macroeconomic aggregate reveals large fluctuations notably during the civil war period (1975-1990). By estimating the Lyapunov exponents with the Artificial Neural Network (ANN) procedure, we show that this series exhibits a strange attractor generated by a chaotic dynamic and we use the embedding procedure to shed in light the bizarre structure of such a series. Thus, the ANN method gives better results regarding prediction than other linear regression models and allows to fit with accuracy the chaotic motion followed by the Lebanese GDP in the phase space.

The Cross-Correlations between Foreign Flows in Chinese A-Share Markets and Uncertainties in Home Markets

This paper investigates the cross-correlations between the foreign flows in A-share market and the uncertainties of market, economy, and policy in home markets, namely, the VIX index and the US EPU index. By employing the cross-correlation statistics and MF-DCCA method, we find the existence of the cross-correlations between the foreign flows and the VIX index, the foreign flows, and the US EPU index from qualitative and quantitative perspectives, respectively. For the cross-correlation between the foreign flows and VIX, small fluctuations are persistent, while large fluctuations are antipersistent. In contrast, the cross-correlation between the foreign flows and US EPU is antipersistent and steady. These results are robust by dividing the foreign flows into two parts in Shenzhen and Shanghai stock exchanges, respectively, and by shortening the periods to after the implementation of Shenzhen-Hong Kong Stock Connect.

Subcritical dynamo and hysteresis in a Babcock-Leighton type kinematic dynamo model

In the Sun and Sun-like stars, it is believed that cycles of the large-scale magnetic field are produced due to the existence of differential rotation and helicity in the plasma flows in their convection zones (CZs). Hence, it is expected that for each star, there is a critical dynamo number for the operation of a large-scale dynamo. As a star slows down, it is expected that the large-scale dynamo ceases to operate above a critical rotation period. In our study, we explore the possibility of the operation of the dynamo in the subcritical region using the Babcock–Leighton type kinematic dynamo model. In some parameter regimes, we find that the dynamo shows hysteresis behavior, i.e., two dynamo solutions are possible depending on the initial parameters—decaying solution if starting with weak field and strong oscillatory solution (subcritical dynamo) when starting with a strong field. However, under large fluctuations in the dynamo parameter, the subcritical dynamo mode is unstable in some parameter regimes. Therefore, our study supports the possible existence of subcritical dynamo in some stars which was previously demonstrated in a mean-field dynamo model with distributed α and MHD turbulent dynamo simulations.