The public attitude towards ChatGPT on reddit: A study based on unsupervised learning from sentiment analysis and topic modeling.

ChatGPT has demonstrated impressive abilities and impacted various aspects of human society since its creation, gaining widespread attention from different social spheres. This study aims to comprehensively assess public perception of ChatGPT on Reddit. The dataset was collected via Reddit, a social media platform, and includes 23,733 posts and comments related to ChatGPT. Firstly, to examine public attitudes, this study conducts content analysis utilizing topic modeling with the Latent Dirichlet Allocation (LDA) algorithm to extract pertinent topics. Furthermore, sentiment analysis categorizes user posts and comments as positive, negative, or neutral using Textblob and Vader in natural language processing. The result of topic modeling shows that seven topics regarding ChatGPT are identified, which can be grouped into three themes: user perception, technical methods, and impacts on society. Results from the sentiment analysis show that 61.6% of the posts and comments hold favorable opinions on ChatGPT. They emphasize ChatGPT's ability to prompt and engage in natural conversations with users, without relying on complex natural language processing. It provides suggestions for ChatGPT developers to enhance its usability design and functionality. Meanwhile, stakeholders, including users, should comprehend the advantages and disadvantages of ChatGPT in human society to promote ethical and regulated implementation of the system.

Nitrogen sources and conversion processes in shallow groundwater around a plain lake (Northwest China): Evidenced by multiple isotopes and water chemistry.

The groundwater quality is severely impacted by Nitrate (NO3--N) pollution worldwide. Effective lake quality management depends on understanding the origin and fate of nitrogen (N) in the groundwater around lakes. This study combined data for multiple stable isotopes (δ2H-H2O and δ18O-H2O, δ15N-NO3 and δ18O-NO3) and hydrochemistry with the hydrodynamic monitoring profile and a Bayesian isotope mixing (MixSIAR) model to clarify the sources and transformation of N within shallow groundwater around Shahu Lake in the arid area plain of Northwest China. In May 2022, multiple water samples were collected from aquifers (n = 33), drainage water (n = 1), channel water (n = 1), and lake water (n = 7). The results showed that 57% of groundwater samples had high NO3--N concentrations exceeding the World Health Organisation threshold for drinking water (10 mg/L). The high variation in δ15N-NO3 (from -9.21‰ to +27.57‰) and δ18O-NO3 (from -8.32‰ to +19.04‰) revealed multiple N sources and conversion processes. According to nitrate isotopes and the MixSIAR model, N fertilizer, soil organic N and manure, and sewage are the main sources of nitrogen in groundwater and lake water, which account for 40.61%, 35.86%, and 21.55% of groundwater NO3--N, respectively, and 35.07%, 34.43%, and 27.49% of lake water NO3--N. Hydrodynamic monitoring combined with water isotopes showed that upper groundwater (5-10 m) within 1.22 km of the adjacent lake shore strongly interacted with the lake. In groundwater, nitrification predominated, while local denitrification remained a possibility. In conclusion, this research offers a comprehensive approach to determining the sources and conversion of N in contaminated groundwater.

Insights into the Effect of Precursors on the FeP-Catalyzed Hydrogen Evolution Reaction.

Iron phosphide nanoparticles (NPs) are promising noble metal-free electrocatalysts for the hydrogen evolution reaction (HER), but they usually show inferior activity due to the limited surface area and oxidative passivation. We reported a facile synthetic method to prepare FeP hollow NPs (HNPs) with various precursors. It was proven that the structural parameters (i.e., size, phosphating temperature, phase, and surfactant) of oxide precursors were correlated to the electrochemically active surface area (ECSA), phase purity, surface oxidation, and hollow morphology of FeP HER catalysts, thus affecting the HER activity. Among the three FeP HNPs, the 9 nm FeP HNPs prepared using the Fe3O4 precursor exhibited the highest overall activity with the lowest overpotential of 76 mV to drive a cathodic current density of 10 mA·cm-2 due to the highest ECSA, while 25 nm FeP prepared using the Fe2O3 precursor showed the highest turnover frequency because of the high phase purity and low surface oxidation degree.