Analytical and Computational Study of Economic Dynamical Processes by Methods of Wave Dynamics

By methods of wave dynamics nonlinear equations for economic dynamical processes are derived. They deal both with the transition probabilities of Markov diffusion processes and the ones of random functions values. By using the mean curves of variations of random functions values with respect to time the nonlinear equations coefficients are ob-tained. Analytic and numerical solutions for several economic problems, such as the Black-Sholes precise bonds dynam-ics problem and others are foundMarkov diffusion processes; Black-Scholes model

Study of different heterocycles showing significant anti-severe acute respiratory syndrome 2 activity in vitro and in vivo

Background and Aim: With the emergence of severe acute respiratory syndrome-related coronavirus (SARS-CoV-2), antiviral drug development has gained increased significance due to the high incidence and potentially severe complications of the resulting coronavirus infection. Heterocycle compounds, acting as antimetabolites of DNA and RNA monomers, rank among the most effective antiviral drugs. These compounds’ antiviral effects on various SARS-CoV-2 isolates, as found in existing data collections, form the basis for further research. The aim of this study was to examine the possible antiviral effect of some originally synthesized heterocyclic compounds. Materials and Methods: The main methods were cell culturing, cytotoxicity assay, qRT-PCR assay, tissue and blood cells analysis, and micro-computed tomography (micro-CT) imaging. Results: In both in vitro and in vivo conditions, the elimination of SARS-Cov-2 occurred significantly earlier after administration of the compounds compared to the control group. In hamsters, the primary symptoms of coronavirus disease disappeared following administration of heterocycle compounds. Conclusion: Using delta and omicron strains of the SARS-CoV-2 virus, newly created heterocycle compound analogs dramatically reduced SARS-CoV-2 multiplication, resulting in a drop in viral RNA load in the supernatant under in vitro conditions. Improvements in pathological manifestations in the blood, bone marrow, and internal organs of hamsters demonstrated that heterocycle compounds inhibited SARS-CoV-2 replication both in vitro and in vivo

Measuring the predictability of life outcomes with a scientific mass collaboration.

How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences

Relationship between the Implicit Association Test and intergroup behavior: A meta-analysis

Supplementary materials for Kurdi, B., Seitchik, A. E., Axt, J. R., Carroll, T. J., Karapetyan, A., Kaushik, N., Tomezsko, D., Greenwald, A. G., & Banaji, M. R. (2018). Relationship between the Implicit Association Test and intergroup behavior: A meta-analysis. American Psychologist

Predicting intergroup discrimination using the Implicit Association Test: Meta-analysis and recommendations for future research

A meta-analysis found significant correlations between Implicit Association Tests and a wide range of intergroup behaviors and identified crucial areas for improvement, including ensuring adequate statistical power, considering the influence of methodological variables on effect sizes, adopting a structural equation modeling approach to data analysis, and using repeated measurement designs

Relationship between the Implicit Association Test and intergroup behavior: A meta-analysis

Using data from 217 research reports (N = 36,071, compared to 3,471 and 5,433 in previous meta-analyses), this meta-analysis investigated the conceptual and methodological conditions under which Implicit Association Tests (IATs) measuring attitudes, stereotypes, and identity correlate with criterion measures of intergroup behavior. We found significant implicit–criterion correlations (ICCs) and explicit–criterion correlations (ECCs), with unique contributions of implicit (β = .14) and explicit measures (β = .11) revealed by structural equation modeling. ICCs were found to be highly heterogeneous, making moderator analyses necessary. Basic study features or conceptual variables did not account for any heterogeneity: Unlike explicit measures, implicit measures predicted for all target groups and types of behavior, and implicit, but not explicit, measures were equally associated with behaviors varying in controllability and conscious awareness. However, ICCs differed greatly by methodological features: Studies with a declared focus on ICCs, standard IATs rather than variants, high-polarity attributes, behaviors measured in a relative (two categories present) rather than absolute manner (single category present), and high implicit–criterion correspondence (k = 13) produced a mean ICC of r = .37. Studies scoring low on these variables (k = 6) produced an ICC of r = .02. Examination of methodological properties—a novelty of this meta-analysis—revealed that most studies were vastly underpowered and analytic strategies regularly ignored measurement error. Recommendations, along with online applications for calculating statistical power and internal consistency (http://www.benedekkurdi.com/#iat), are provided to improve future studies on the implicit–criterion relationship. Open materials are available under https://osf.io/47xw8/

Measuring the predictability of life outcomes with a scientific mass collaboration.

How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences