Yi-Cheng Wang

Purpose: Text- and voice-based conversational agents (CAs) provide interactivity beyond the messages public health agencies traditionally use to share information and correct misperceptions. Yet, little research has compared how interactivity and modality influence misperception correction and behavior change. This study examines how modality and information quantity shape cognitive load, misperception change, and behavioral intention. Design/methodology/approach: A 3 (modality: non-interactive message vs. text-based CA vs. voice-based CA) × 2 (information quantity: short vs. long) between-subjects experiment was conducted with 1,157 U.S. adults. Findings: Both CA modalities were associated with lower post-intervention misperceptions than non-interactive messages. Relative to text-based CAs, voice delivery was linked to higher cognitive load, which in turn was associated with greater post-intervention misperceptions and lower intention to adopt healthy behavior. Nevertheless, when information quantity, cognitive load, preexisting and post-intervention misperceptions, and preexisting behavioral intention were controlled for, voice-based CAs were directly associated with the intention to adopt recommended behaviors. Information quantity did not moderate the relationship between modality and cognitive load. Originality/value: To our knowledge, this study is the first controlled experiment to compare text-based CAs, voice-based CAs, and social media messages used to correct health misinformation, while clarifying the mechanisms through which they shape behavior change. The results show that neither CA modality is consistently more effective than the other across all outcomes. As such, practitioners should adopt a “fit-for-purpose” strategy, i.e. use text-based CAs when demands for comprehension are high and voice-based CAs when the main goal is to motivate behavior change.

This study evaluated far-UVC light exposure on the visual quality of deli turkey and ham during a 5-day retail display period. Deli turkey and ham were sliced and treated with 222 nm far-UVC. Turkey received treatments: no far-UVC light (Control), low-dose 337 mJ/cm² (L-UVC; Low-UVC), and high-dose 786.3 mJ/cm² (H-UVC; high-UVC), while ham received Control and H-UVC treatments. Display slices were stored refrigerated and evaluated daily for color and purchase intent, with lipid oxidation measured on days 1 and 5. Data were analyzed using repeated-measure models. On day 5, H-UVC turkey slices demonstrated reduced purchase intent scores (p < 0.05) and a 23.7% greater total color change (ΔE; p < 0.01) compared with Control and L-UVC turkey. In ham, Control slices had a 9.5% greater ΔE from day 1 to 5 than H-UVC (p = 0.03). No differences in lipid oxidation were observed between treatments. Four hours after H-UVC treatment, deli turkey slice yellowness remained elevated compared to pre-treatment levels (p < 0.01). Far-UVC doses evaluated in the present study would not negatively impact the ham visual quality over a 5-day display. However, increased yellowness observed in turkey suggests that far-UVC light may be more appropriate for post-packaging surface sanitation applications than for the direct treatment of deli turkey.

Woody biomass is an abundant renewable resource. In this study, aerogels for versatile triboelectric devices are fabricated from poplar biomass via a dissolution‐and‐regeneration method with concentrated lithium bromide solution as the solvent. To improve the aerogels' structural homogeneity, two treatments—ball‐milling the raw poplar woody biomass before its dissolution, and, separately, ultrasonication following its dissolution—were applied. These treatments altered the porous structures and mechanical properties of the resulting aerogels, leading to a marked increase in their triboelectric performance. Removing the majority of the lignin from the aerogels was also explored, and resulted in triboelectric output ≈5 times greater than that of pristine woody biomass aerogel (i.e., without ball milling, ultrasonication, or lignin reduction). The underlying mechanisms of such increases were found to be both chemical and physical. Next, triboelectric devices were fabricated using the optimal (i.e., low‐lignin) aerogel for energy harvesting and biomechanical monitoring. These devices were able to: 1) respond sensitively to force, likely due to the aerogel's porous structures; 2) capture mechanical energy, charge capacitors, and power small portable electronics; and 3) monitor biomechanical movements including respiration, joint motions, and gait‐pattern changes.

Food waste is an enormous challenge, with implications for the environment, society, and economy. Every year around the world, 1.3 billion tons of food are wasted or lost, and food waste-associated costs are around $2.6 trillion. Waste upcycling has been shown to mitigate these negative impacts. This study's optimized pomelo-peel biomass-derived porous material-based triboelectric nanogenerator (PP-TENG) had an open circuit voltage of 58 V and a peak power density of 254.8 mW/m². As porous structures enable such triboelectric devices to respond sensitively to external mechanical stimuli, we tested our optimized PP-TENG's ability to serve as a self-powered sensor of biomechanical motions. As well as successfully harvesting sufficient mechanical energy to power light-emitting diodes and portable electronics, our PP-TENGs successfully monitored joint motions, neck movements, and gait patterns, suggesting their strong potential for use in healthcare monitoring and physical rehabilitation, among other applications. As such, the present work opens up various new possibilities for transforming a prolific type of food waste into value-added products and thus could enhance long-term sustainability while reducing such waste.

Antimicrobial-resistant (AMR) bacteria pose a significant global health threat, and bacteria that produce New Delhi metallo-β-lactamase (NDM) are particularly concerning due to their resistance to most β-lactam antibiotics, including carbapenems. The emergence and spread of NDM-producing genes in food-producing animals highlight the need for a fast and accurate method for detecting AMR bacteria. We therefore propose a PCR-coupled CRISPR/Cas12a-based fluorescence assay that can detect NDM-producing genes (bla_NDM) in bacteria. Thanks to its designed gRNA, this CRISPR/Cas12a system was able to simultaneously cleave PCR amplicons and ssDNA-FQ reporters, generating fluorescence signals. Our method was found to be highly specific when tested against other foodborne pathogens that do not carry bla_NDM and also demonstrated an excellent capability to distinguish single-nucleotide polymorphism. In the case of bla_NDM-₁ carrying E. coli, the assay performed exceptionally well, with a detection limit of 2.7 × 10⁰ CFU/mL: 100 times better than conventional PCR with gel electrophoresis. Moreover, the developed assay detected AMR bacteria in food samples and exhibited enhanced performance compared to previously published real-time PCR assays. Thus, this novel PCR-coupled CRISPR/Cas12a-based fluorescence assay has considerable potential to improve current approaches to AMR gene detection and thereby contribute to mitigating the global threat of AMR.

Textual social media data have become indispensable to researchers’ understanding of message strategies and other marketing practices. In a new departure for the field of brand communication, this study adopts and extends a semi-supervised machine-learning approach, guided latent Dirichlet allocation (LDA), which incorporates human insights into the discovery and classification of topics. We used it to analyze tweets from businesses involved with an emerging food technology, cultured meat, and delineated four key message strategies used by these brands: providing functional, educational, corporate social responsibility, and relational content. We further ascertained the relationships between brands and the key topics embedded in their Twitter data. A comparison of model performance suggests that guided LDA can be an advantageous alternative to traditional LDA, which is characterized by high efficiency and immense popularity among researchers, but—because of its unsupervised nature—yields findings that can be difficult to interpret. The present study therefore has critical theoretical and methodological implications for communication and marketing scholars.