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In recent years, Large Language Models (LLMs) have emerged as a transformative development in artificial intelligence (AI), drawing significant attention from industry and academia. Trained on vast datasets, these sophisticated AI systems exhibit impressive natural language processing and content generation capabilities. This paper explores the potential of LLMs to address key challenges in personal finance, focusing on the United States. We evaluate several leading LLMs, including OpenAI's ChatGPT, Google's Gemini, Anthropic's Claude, and Meta's Llama, to assess their effectiveness in providing accurate financial advice on topics such as mortgages, taxes, loans, and investments. Our findings show that while these models achieve an average accuracy rate of approximately 70%, they also display notable limitations in certain areas. Specifically, LLMs struggle to provide accurate responses for complex financial queries, with performance varying significantly across different topics. Despite these limitations, the analysis reveals notable improvements in newer versions of these models, highlighting their growing utility for individuals and financial advisors. As these AI systems continue to evolve, their potential for advancing AI-driven applications in personal finance becomes increasingly promising.

The prevailing educational methods predominantly rely on traditional classroom instruction or online delivery, often limiting the teachers' ability to engage effectively with all the students simultaneously. A more intrinsic method of evaluating student attentiveness during lectures can enable the educators to tailor the course materials and their teaching styles in order to better meet the students' needs. The aim of this paper is to enhance teaching quality in real time, thereby fostering a higher student engagement in the classroom activities. By monitoring the students' electroencephalography (EEG) signals and employing machine learning algorithms, this study proposes a comprehensive solution for addressing this challenge. Machine learning has emerged as a powerful tool for simplifying the analysis of complex variables, enabling the effective assessment of the students' concentration levels based on specific parameters. However, the real-time impact of machine learning models necessitates a careful consideration as their deployment is concerned. This study proposes a machine learning-based approach for predicting the level of students' comprehension with regard to a certain topic. A browser interface was introduced that accesses the values of the system's parameters to determine a student's level of concentration on a chosen topic. The deployment of the proposed system made it necessary to address the real-time challenges faced by the students, consider the system's cost, and establish trust in its efficacy. This paper presents the efforts made for approaching this pertinent issue through the implementation of innovative technologies and provides a framework for addressing key considerations for future research directions., Comment: Published in Romanian Journal of Information Technology and Automatic Control

The Zirconium (Z = 40) isotopic chain has attracted interest for more than four decades. The abrupt lowering of the energy of the first $2^+$ state and the increase in the transition strength B(E2; $2_1^\rightarrow 0_1^+$ going from $^{98}$Zr to $^{100}$Zr has been the first example of "quantum phase transition" in nuclear shapes, which has few equivalents in the nuclear chart. Although a multitude of experiments have been performed to measure nuclear properties related to nuclear shapes and collectivity in the region, none of the measured lifetimes were obtained using the Recoil Distance Doppler Shift method in the $\gamma\gamma$-coincidence mode where a gate on the direct feeding transition of the state of interest allows a strict control of systematical errors. This work reports the results of lifetime measurements for the first yrast excited states in $^{98-104}$Zr carried out to extract reduced transition probabilities. The new lifetime values in $\gamma\gamma$-coincidence and $\gamma$-single mode are compared with the results of former experiments. Recent predictions of the Interacting Boson Model with Configuration Mixing, the Symmetry Conserving Configuration Mixing model based on the Hartree-Fock-Bogoliubov approach and the Monte Carlo Shell Model are presented and compared with the experimental data.

Systematic study of theoretical estimation of nuclear cross section of charged particle induced reactions on rare earth nuclei has been carried out. The production cross section of the $^{150,149,148,146,144,143,141}$Pm and $^{149,147}$Nd nuclei were calculated theoretically via proton induced reaction on neodymium using TALYS (version 1.96) code in the default mode, with different combination of nuclear models as well as using adjusted nuclear model parameters from reaction threshold to the proton energy upto 65 MeV. The theoretically computed results were compared with the experimental results taken from EXFOR database and literature, reported by various research groups. Moreover, the effect of the various Level Density Models (LDMs), Preequilibrium Models (PEs), Optical Model Potentials (OMPs), gamma Strength Functions ($\gamma$SFs) in the cross section calculation were taken into consideration. The present theoretical analysis will help to understand the theory of nuclear reaction models and improve the evaluated nuclear data libraries., Comment: 15 pages, 13 figures, to be published in Chinese Physics C

In this work, we have studied various mixed state information theoretic quantities for an excited state of Lifshitz spacetime in $3+1$-dimensions. This geometry is the gravity dual to a class of $2+1$-dimensional quantum field theories having Lifshitz symmetry. We have holographically calculated mutual information, entanglement wedge cross section, entanglement negativity and mutual complexity for strip like subsystems at the boundary. For this we have used the results of holographic entanglement entropy and complexity present in the literature. We first calculate all of these mentioned quantities for the pure state of Lifshitz spacetime. Then we have moved on to calculate all these quantities for excited state of the Lifshitz spacetime. The gravity dual of excited state of Lifshitz systems in field theory can be obtained by applying constant perturbations along the boundary direction. Further, we would like to mention that for the simplicity of calculation we are only considering results up to the first order in perturbation. The change in the obtained holographic information theoretic quantities are then related to entanglement entropy, entanglement pressure, entanglement chemical potential and charge using the stress tensor complex. These relations are analogous to the first law of entanglement thermodynamics given earlier in the literature. All the calculations are carried out for both values of dynamical scaling exponent ($z$) present in the Lifshitz field theory., Comment: v1: 51 pages LaTex, multiple figures, v2: matches with the published version

The current work reports a study on bounce cosmology with a highly generalized holographic dark fluid inspired by S. Nojiri and S. D. Odintsov, 2017, European Physical Journal C, 77, pp.1-8. The holographic dark fluid that is mostly used for late-time acceleration has been implemented to reconstruct towards realisation of cosmological bounce. We first used the most generalized Nojiri-Odintsov(NO) cutoff to implement the holographic dark fluid. Accordingly, we have reconstructed this dark fluid via some solutions of scale factors. With those solutions, we have explored the evolution of different cosmological parameters. We have examined the effects of each reconstructed parameter in the context of the realization of the cosmic bounce. Next, we use the analytical inferences of the scalar spectral index, tensor-to-scalar ratio, and slow-roll characteristics of the model to study a bounce inflationary scenario. Since inflation is usually associated with the existence of scalar fields, we looked at a possible relationship between NO generalized holographic dark energy and scalar field models. Plotting the evolution of the potential that results from the scalar fields against time. Finally, we investigated the GSL of thermodynamics in the pre-and post-bounce scenarios., Comment: 31 pages, 16 figures

We report a comprehensive study of Sperrylite (PtAs2), the main platinum source in natural minerals, as a function of applied pressures up to 150 GPa. While no structural phase transition was detected from pressure-dependent X-ray measurements, the unit cell volume shrinks monotonically with pressure following the third-order Birch-Murnaghan equation of state. The mildly semiconducting behavior found in pure synthesized crystals at ambient pressures becomes more insulating upon increasing applied pressure before metalizing at higher pressures, giving way to the appearance of an abrupt decrease in resistance near 3 K at pressures above 92 GPa consistent with the onset of a superconducing phase. The pressure evolution of the calculated electronic band structure reveals the same physical trend as our transport measurements, with a non-monotonic evolution explained by a hole band that is pushed below the Fermi energy and an electron band that approaches it as a function of pressure, both reaching a touching point suggestive of an excitonic state. A topological Lifshitz transition of the electronic structure and an increase in the density of states may naturally explain the onset of superconductivity in this material, Comment: 7 pages, 7 figures

We study percolation transition of run and tumble particles (RTPs) on a two dimensional square lattice. RTPs in these models run to the nearest neighbour along their internal orientation with unit rate, and to other nearest neighbours with rates $p$. In addition, they tumble to change their internal orientation with rate $\omega$. We show that for small tumble rates, RTP-clusters created by joining occupied nearest neighbours irrespective of their orientation form a phase separated state when the rate of positional diffusion $p$ crosses a threshold; with further increase of $p$ the clusters disintegrate and another transition to a mixed phase occurs. The critical exponents of this re-entrant site-percolation transition of RTPs vary continuously along the critical line in the $\omega$-$p$ plane, but a scaling function remains invariant. This function is identical to the corresponding universal scaling function of percolation transition observed in the Ising model. We also show that the critical exponents of the underlying motility induced phase separation transition are related to corresponding percolation-critical-exponents by constant multiplicative factors known from the correspondence of magnetic and percolation critical exponents of the Ising model., Comment: 8 pages, 8 figures, Supp. Material (5 pages with 9 figures)