A physics-informed AI method for calculating melting points with uncertainty control and optimal sampling

We present an artificial intelligence (AI) method for automatically computing the melting point based on coexistence simulations in the NPT ensemble. Given the interatomic interaction model, the method makes decisions regarding the number of atoms and temperature at which to conduct simulations, and based on the collected data predicts the melting point along with the uncertainty, which can be systematically improved with more data. We demonstrate how incorporating physical models of the solid-liquid coexistence evolution enhances the AI method's accuracy and enables optimal decision-making to effectively reduce predictive uncertainty. To validate our approach, we compare our results with approximately 20 melting point calculations from the literature. Remarkably, we observe significant deviations in about one-third of the cases, underscoring the need for accurate and reliable AI-based algorithms for materials property calculations.Comment: 9 figure

The Relationship Between Measures of Impulsivity and Clinical Characteristics of Patients With Alcohol Use Disorder

The current article presents findings on the interaction between impulsivity features and clinical characteristics of patients with alcohol use disorders (AUD). Patients (n = 88), who were completing detoxification program for the symptoms of AUD, were recruited for the study. They completed biographical questionnaire, Penn CravingScale (PACS), self-report screening measure of the symptoms of adult ADHD (ASRS v.1.1) and underwent a series of experimental tasks (Delay Discounting Task (DDT), Stroop Task, Continuous Performance Test-Identical Pairs (CPT-IP), Tower of London (ToL)). Two distinct groups of impulsivity features were identified using clusteranalysis. One group, which was comprised of DDT and ToL measures, described the level of impulsivity during the decision-making process. The second group included Stroop task and CPT-IP measures and expressed the level of response inhibition and interference control. In addition, the model of interaction between measuresof impulsivity and clinical characteristics of patients was developed. The self-report measure of inattention and hyperactivity had significant effect on the level of craving and the duration of remission. No significant relationships were observed between DDT clinical characteristics. Keywords: impulsivity, alcohol use disorder, delay discounting, stroop task, Tower of London, CPT-IP, craving, ASR

CJEU and Qualification Directive

The aim of the paper is to analyse how and in what situations the Court of Justice of the European Union applies and interprets international law and what margin of appreciation it leaves for national courts when applying the Qualification Directive. The main focus is on the exploration of the strategies of the Court towards Convention and Qualification Directive in asylum cases related to terrorism and public security

Bayesian inference of composition-dependent phase diagrams

Phase diagrams serve as a highly informative tool for materials design, encapsulating information about the phases that a material can manifest under specific conditions. In this work, we develop a method in which Bayesian inference is employed to combine thermodynamic data from molecular dynamics (MD), melting point simulations, and phonon calculations, process these data, and yield a temperature-concentration phase diagram. The employed Bayesian framework yields us not only the free energies of different phases as functions of temperature and concentration but also the uncertainties of these free energies originating from statistical errors inherent to finite-length MD trajectories. Furthermore, it extrapolates the results of the finite-atom calculations to the infinite-atom limit and facilitates the choice of temperature, chemical potentials, and the number of atoms conducting the next simulation with which will be the most efficient in reducing the uncertainty of the phase diagram. The developed algorithm was successfully tested on two binary systems, Ge-Si and K-Na, in the full range of concentrations and temperatures

Pragmalinguistic and Functional Parameters of Written Instruction in Classroom Discourse

In the present paper pragmalinguistic and functional aspects of classroom discourse are analyzed in terms of speech act theory. The system of language means organizing written instruction is worked out and the factors determining linguistic variation within the analyzed text genre are specified

Estimating the influence of social capital on entrepreneurial activity in the Russian regions

Objective to assess the impact of social capital on economic growth welfare and entrepreneurial activity of the Russian regions. Methods abstractlogical method descriptive method econometric modeling. Results when preparing the literature review on the subject of the study a consensus view was revealed that social capital is a multifactorial phenomenon with many elements forms of manifestation and channels of influence on the development of socioeconomic systems. The direction of the social capital impact significantly depends on its context. The paper shows that at different times different elements of social capital influence differently on the indicators of entrepreneurial activity in the Russian regions. In particular two of the three main elements of social capital ndash trust capital and social media capital ndash calculated according to the ldquoGeoRating 2007rdquo poll by ldquoPublic Opinionrdquo foundation and the ldquoSocial Capital alternative source of energyrdquo report 2015 account for 14 to 18 of the differences between the Russian regions in the share of revenues of small enterprises in their gross regional product GRP. It is significant that in the above two periods of observation the nature of this effect changed qualitatively. In particular in 2015 the capital of trust became more significant and began to have a negative impact on the GRP. The capital of social networks retained its positive influence on the dependent variable but its importance in the model was somewhat reduced. Scientific novelty the study proved the moderate influence of one of the elements of social capital ndash the capital ofnbsp social networks ndash on the gross regional product of the Russian regions its elasticity for this indicator is estimated at 0.1. The positive impact of capital norms and values on the level of welfare in the regions of Russia is also confirmed. It is concluded that the impact of open social capital has a positive influence on business activity expressed in the number of small businesses per 10000 people in the region of the Russian Federation. It is also shown that the capital of values and norms affected the dynamics of entrepreneurial activity in the period 2010ndash2015 it had a positive effect on the growth of the average number of employees of small enterprises and revenues from the sale of goods works services of small enterprises in the regions of the Russian Federation. Practical significance the results of the study can be used in the practical activities of the authorities forming the regional policy of entrepreneurship development in Russia

Classification of multidimensional element types in automatic regulation systems

This study examines the possibility of applying the A.A. Krasovsky method of complex coordinates and complex transfer functions for multidimensional element types modeling. As it is demonstrated, the method can be taken as the basis for multidimensional regulation system design along with the extended version of classification suggested by A.A. Krasovsky