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Grit, a non-cognitive skill that indicates perseverance and passion for long-term goals, has been shown to predict academic achievement. This paper provides evidence that grit also predicts student outcomes during the challenging period of the Covid-19 pandemic. We use a unique dataset from a digital learning platform in the United Arab Emirates to construct a behavioral measure of grit. We find that controlling for baseline achievement, students who were grittier according to this measure before the pandemic, register lower declines in math and science scores during the coronavirus period. Using machine learning, behavioral data obtained from the platform prior to the pandemic can explain 77% of the variance in academic resilience. A survey measure of grit coming from the same students, on the other hand, does not have significant predictive power over performance changes. Our findings have implications for interventions on non-cognitive skills, as well as how data from digital learning platforms can be used to predict student behavior and outcomes, which we expect will be increasingly relevant as AI-based learning technologies become more common. [ABSTRACT FROM AUTHOR]

We define a Bessel type equation in multiplicative calculus by some algebraic structures. Eigenfunctions of constructed problem are obtained by power series solution technique. While making these solutions, multiplicative Bessel functions are used strongly. We get a generator for that problem and construct integration representations for multiplicative Bessel functions. Finally, some basic spectral properties of multiplicative Bessel problem are examined in detail. [ABSTRACT FROM AUTHOR]

The study aims to examine the effects of social media activities on stock prices of the energy sector. In this respect, the sample covers the monthly period from 2015m6 to 2020m5 has been observed. Energy stocks as S&P 500 index (SP), stock market volatility index (VIX), trade-weighted USD index (USD), and Brent oil prices (OIL) have been used as independent variables. Accordingly, three different models have been created to analyze the link between returns, volatility and trading volume and Twitter sentiments by using Augmented Mean Group. As a result, we found that Twitter sentiment values have no significant impact on the returns and volatility of the companies. Tweets, on the other hand, appear to have a favorable impact on company trading volume values. [ABSTRACT FROM AUTHOR]

In this study, we deal with an inverse problem for Bessel operator on a finite interval. We present some results of the associated with Ambarzumyan's theorem by using spectrum and nodal points (zeros of eigenfunction). [ABSTRACT FROM AUTHOR]

We study the conformable fractional (CF) Dirac system with separated boundary conditions on an arbitrary time scale $\mathbb{T}$ . Then we extend some basic spectral properties of the classical Dirac system to the CF case. Eventually, some asymptotic estimates for the eigenfunction of the CF Dirac eigenvalue problem are obtained on $\mathbb{T} $ . So, we provide a constructive procedure for the solution of this problem. These results are important steps to consolidate the link between fractional calculus and time scale calculus in spectral theory. [ABSTRACT FROM AUTHOR]

In this study, we consider reconstruction and stability issues of an inverse nodal problem for a p-Laplacian Schrödinger equation with energy dependent potential. We solve Lipschitz stability of the inverse nodal problem for this p-Laplacian operator. Furthermore, we show that the space of all potential functions q is homeomorphic to the partition set of all asymptotically equivalent nodal sequences induced by an equivalence relation. [ABSTRACT FROM AUTHOR]