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  1. Removal of humic and tannic acids by adsorption-coagulation combined systems with activated biochar
    Jung C, Phal N, Oh J, Chu KH, Jang M, Yoon Y
    J Hazard Mater, 2015 Dec 30;300:808-814.
    PMID: 26340547 DOI: 10.1016/j.jhazmat.2015.08.025
    Despite recent interest in transforming biomass into bio-oil and syngas, there is inadequate information on the compatibility of byproducts (e.g., biochar) with agriculture and water purification infrastructures. A pyrolysis at 300°C yields efficient production of biochar, and its physicochemical properties can be improved by chemical activation, resulting in a suitable adsorbent for the removal of natural organic matter (NOM), including hydrophobic and hydrophilic substances, such as humic acids (HA) and tannic acids (TA), respectively. In this study, the adsorption affinities of different HA and TA combinations in NOM solutions were evaluated, and higher adsorption affinity of TA onto activated biochar (AB) produced in the laboratory was observed due to its superior chemisorption tendencies and size-exclusion effects compared with that of HA, whereas hydrophobic interactions between adsorbent and adsorbate were deficient. Assessment of the AB role in an adsorption-coagulation hybrid system as nuclei for coagulation in the presence of aluminum sulfate (alum) showed a synergistic effect in a HA-dominated NOM solution. An AB-alum hybrid system with a high proportion of HA in the NOM solution may be applicable as an end-of-pipe solution.
  2. Fulltext The Potential of Chatbots for Emotional Support and Promoting Mental Well-Being in Different Cultures: Mixed Methods Study
    Chin H, Song H, Baek G, Shin M, Jung C, Cha M, et al.
    J Med Internet Res, 2023 Oct 20;25:e51712.
    PMID: 37862063 DOI: 10.2196/51712
    BACKGROUND: Artificial intelligence chatbot research has focused on technical advances in natural language processing and validating the effectiveness of human-machine conversations in specific settings. However, real-world chat data remain proprietary and unexplored despite their growing popularity, and new analyses of chatbot uses and their effects on mitigating negative moods are urgently needed.

    OBJECTIVE: In this study, we investigated whether and how artificial intelligence chatbots facilitate the expression of user emotions, specifically sadness and depression. We also examined cultural differences in the expression of depressive moods among users in Western and Eastern countries.

    METHODS: This study used SimSimi, a global open-domain social chatbot, to analyze 152,783 conversation utterances containing the terms "depress" and "sad" in 3 Western countries (Canada, the United Kingdom, and the United States) and 5 Eastern countries (Indonesia, India, Malaysia, the Philippines, and Thailand). Study 1 reports new findings on the cultural differences in how people talk about depression and sadness to chatbots based on Linguistic Inquiry and Word Count and n-gram analyses. In study 2, we classified chat conversations into predefined topics using semisupervised classification techniques to better understand the types of depressive moods prevalent in chats. We then identified the distinguishing features of chat-based depressive discourse data and the disparity between Eastern and Western users.

    RESULTS: Our data revealed intriguing cultural differences. Chatbot users in Eastern countries indicated stronger emotions about depression than users in Western countries (positive: P

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