Questioning the relationship between the χ\chi4 susceptibility and the dynamical correlation length in a glass former

Clusters of fast and slow correlated particles, identified as dynamical heterogeneities (DHs), con-stitute a central aspect of glassy dynamics. A key ingredient of the glass transition scenario is asignificant increase of the cluster size $\xi$4 as the transition is approached. In need of easy-to-computetools to measure $\xi$4 , the dynamical susceptibility $\chi$4 was introduced recently, and used in various ex-perimental works to probe DHs. Here, we investigate DHs in dense microgel suspensions using imagecorrelation analysis, and compute both $\chi$4 and the four-point correlation function G4 . The spatialdecrease of G4 provides a direct access to $\xi$4 , which is found to grow significantly with increasingvolume fraction. However, this increase is not captured by $\chi$4 . We show that the assumptions thatvalidate the connection between $\chi$4 and $\xi$4 are not fulfilled in our experiments.Comment: The present version was accepted for publication in Soft Matter (http://pubs.rsc.org/en/journals/journalissues/sm

Spatially heterogeneous dynamics in a thermosensitive soft suspension before and after the glass transition

The microscopic dynamics and aging of a soft thermosensitive suspension was investigated by looking at the thermal fluctuations of tracers in the suspension. Below and above the glass transition, the dense microgel particles suspension was found to develop an heterogeneous dynamics, featured by a non Gaussian Probability Distribution Function (PDF) of the probes' displacements, with an exponential tail. We show that non Gaussian shapes are a characteristic of the ensemble-averaged PDF, while local PDF remain Gaussian. This shows that the scenario behind the non Gaussian van Hove functions is a spatially heterogeneous dynamics, characterized by a spatial distribution of locally homogeneous dynamical environments through the sample, on the considered time scales. We characterize these statistical distributions of dynamical environments, in the liquid, supercooled, and glass states, and show that it can explain the observed exponential tail of the van Hove functions observed in the concentrated states. The intensity of spatial heterogeneities was found to amplify with increasing volume fraction. In the aging regime, it tends to increase as the glass gets more arrested.Comment: 19 pages, 10 figures, Soft Matter accepte

Helical Packings and Phase Transformations of Soft Spheres in Cylinders

The phase behavior of helical packings of thermoresponsive microspheres inside glass capillaries is studied as a function of volume fraction. Stable packings with long-range orientational order appear to evolve abruptly to disordered states as particle volume fraction is reduced, consistent with recent hard sphere simulations. We quantify this transition using correlations and susceptibilities of the orientational order parameter psi_6. The emergence of coexisting metastable packings, as well as coexisting ordered and disordered states, is also observed. These findings support the notion of phase transition-like behavior in quasi-1D systems.Comment: 5 pages, with additional 4 pages of supplemental material, accepted to Physical Review E: Rapid Communication

Time’s Bang Theory

Pre Big Bang phase remains a key to get perfect time’s origin and to determine its creative role, so the aim of this study is to confide time’s mechanism in the universes evolves processes. Calculations based on Quran data – fourteen centuries ago – of universes evolves phases are the access to have a due theory: Pre Big Bang evolves period = 91,736,492,148,000 m/s Big Bang evolves period = 122,315,322,864,000 m/s. Time occurs in two types; compact at pre Big Bang phase where it begins and multitude at Big Bang phase. Its six fold body structure and its motions mechanism evince universes evolve bifurcation conjunct with time’s develop before and after Bing Bang. Time’s expansion process in the consequent of clockwise and anti-clock wise of its two body circles motions found to be dominant in whole universes evolve motions. This time’s mechanism which begins in pre Big Bang phase is the essential inducement of Big Bang processes. Universe Light-Darkness mechanism’s percentage and ratios; which formulate here in a law emphasize time’s building role in addition to its indicating function. The gravity presents here as time’s duty, gives a full idea of universes dynamic pillars, and it is managing universes inner and outer equilibrium; subjectively and aggregatively. Modeling of a single time’s motion which communized in whole universes actions gives a new   evolves theory; it is Time’s Bang Theory. Keywords: Time’s begins, phase’s durations, time’s body structure, time’s mechanism, expansion, and evolves specification, universe L-D mechanism, and time’s gravity.

Regional economic convergence in federation contexts: a comparative analysis of Brazil and the European Union

This article examines regional economic convergence in two federal contexts: Brazil and the European Union. Despite many differences, in the last decades these two economies have shown irregular economic growth and been facing economic inequalities, launching public policies to reduce them. We analyse the tendencies of regional convergence within these economies between 2002 and 2019, focusing on σ-convergence, absolute convergence, convergence clubs and the transitional behaviour of club members. The results show that in both cases convergence occurs, but at a slow rhythm, especially in the European Union

Association between coronavirus cases and seasonal climatic variables in Mediterranean European Region, evidence by panel data regression

The coronavirus pandemic is one of the most fast-spreading diseases in the history, and the transmission of this virus has crossed rapidly over the whole world. In this study, we intend to detect the effect of temperature, precipitation, and wind speed on the Coronavirus infected cases throughout climate seasons for the whole year of epidemic starting from February 20, 2020 to February 19, 2021 with considering data patterns of each season separately; winter, spring, summer, autumn, in Mediterranean European regions, whereas those are located at the similar temperature zone in southern Europe. We apply the panel data approach by considering the developed robust estimation of clustered standard error which leads to achieving high forecasting accuracy. The main finding supports that temperature and wind speed have significant influence in reducing the Coronavirus cases at the beginning of this epidemic particularly in the first-winter, spring, and early summer, but they have very weak effects in the autumn and second-winter. Therefore, it is important to take into account the changes throughout seasons, and to consider other indirect factors which influence the virus transmission. This finding could lead to significant contributions to policymakers in European Union and European Commission Environment to limit the Coronavirus transmissions. As the Mediterranean region becomes more crowded for tourism purposes particularly in the summer season

Biological Conversion Process of Methane into Methanol Using Mixed Culture Methanotrophic Bacteria Enriched from Activated Sludge System

Wastewater treatment plants contribute to the global warming phenomena not only by GHG emissions, but also, by consuming enormous amount of fossil fuel based energy. Therefore, methane bio-hydroxylation has attracted the attention as methanol is an efficient substitute for methane (GHG) due to its transportability and higher energy yield. This work is destined to investigate and optimize the factors affecting the microbial activity within methane bio-hydroxylation system using type I methanotrophs enriched from activated sludge system. The optimization resulted in a notable enhancement of the growth kinetics. The attained maximum specific growth rate (max) (0.358 hr-1) and maximum specific methane biodegradation rate (qmax) (0.605 g-CH4,Total/g-DCW/hr-1) were the highest reported in mixed cultures. Furthermore, the maximum methanol productivity achieved is comparable with pure cultures and equal to 211581 mg/L/day. Whereas, methanol concentration of 48521 mg/L was attained which is two times higher than the reported using mixed culture

Turkish Stock Market from Pandemic to Russian Invasion, Evidence from Developed Machine Learning Algorithm

In recent time, the two significant events; Coronavirus epidemic and Russian invasion are effecting all over the world in various aspects; healthily, economically, environmentally, and socially, etc. The first event has brought uncertainties to the economic situation in most countries based on the epidemic transmission. In addition to that, on 24th February 2022 the Russian invasion of Ukraine affected negatively almost all stock markets all over the world, but the effects are heterogeneous across countries according to their economic-political relationship or neighbourhood, etc. Due to that, the stock market price in Turkey has been affected dramatically over that period. This empirical study is the first attempts to explore the impact of Coronavirus epidemic and Russian invasion on the stock market index XU100 in Turkey by applying the developed statistical method namely elastic-net regression based on empirical mode decomposition which can precisely tackle the nonstationary and nonlinearity data. Then we performed the robustness check by applying a nonlinear techniques Markov switching regression. The data are collected from the beginning of the epidemic in Turkey from March 11, 2020 until May 31, 2022. The finding reveals that there is significant effect of the Coronavirus spreading on the Turkish stock market index, particularly during the first wave. Then after the Russian Invasion the XU100 index is effected more negatively. As the credit default swap and TL reference interest rate have a negative impact but the foreigner exchange rate has a positive significant impact on the XU100 index, and it varies according to the period of short term and long term. Moreover, the results obtained by using the robustness check shows a robust and consistent finding. In conclusion, understanding the impact of Coronavirus pandemic and Russian invasion on the Turkish stock market can provide important implications for investors, financial sectors, and policymakers

Enhancing Model Selection by Obtaining Optimal Tuning Parameters in Elastic-Net Quantile Regression, Application to Crude Oil Prices

Recently, there has been an increased focus on enhancing the accuracy of machine learning techniques. However, there is the possibility to improve it by selecting the optimal tuning parameters, especially when data heterogeneity and multicollinearity exist. Therefore, this study proposed a statistical model to study the importance of changing the crude oil prices in the European Union, in which it should meet state-of-the-art developments on economic, political, environmental, and social challenges. The proposed model is Elastic-net quantile regression, which provides more accurate estimations to tackle multicollinearity, heavy-tailed distributions, heterogeneity, and selecting the most significant variables. The performance has been verified by several statistical criteria. The main findings of numerical simulation and real data application confirm the superiority of the proposed Elastic-net quantile regression at the optimal tuning parameters, as it provided significant information in detecting changes in oil prices. Accordingly, based on the significant selected variables; the exchange rate has the highest influence on oil price changes at high frequencies, followed by retail trade, interest rates, and the consumer price index. The importance of this research is that policymakers take advantage of the vital importance of developing energy policies and decisions in their planning