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[This corrects the article DOI: 10.1371/journal.pone.0303858.].

ObjectiveThe study aims to explore the driving forces behind physical activity engagement among patients with chronic obstructive pulmonary disease, focusing on motivation, opportunity, and capability.DesignA phenomenological qualitative study applied the motivation, opportunity, and capability model, conducted in two respiratory units of a Chinese university hospital.MethodsParticipants, selected by age, gender, and illness duration, included inpatients during the interview sessions and those recently discharged within six months. One-on-one semi-structured interviews were recorded, transcribed, and analyzed by the Colaizzi seven-step method.ResultsSeventeen participants diagnosed with chronic obstructive pulmonary disease for over one year aged between 66 (range: 42-96) participated. Three major themes were identified: Inspiring participation motivation-transitioning from recognizing significance to habit formation; Offering participation opportunities-reiterating demand for personalized strategies and ideal environmental settings; Enhancing participation capability-addressing strategies for overcoming fears, setting goals, ensuring safety, and adjusting activity levels.ConclusionsThis research underscores the vital role of inspiring participation motivation, offering opportunities, and enhancing the capability for participation in effective engagement. Advocating increased attention from healthcare departments, fostering interdisciplinary collaboration, improving activity guidance and counseling effectiveness, and considering individual preferences can significantly benefit those patients with chronic obstructive pulmonary disease who hesitate or are unable to participate in physical activities, thereby increasing the dose of non-leisure time physical activity.

An optical multiple-image authentication is suggested using computational ghost imaging and total-variation minimization. Differing from encrypting multiple images into a noise-like ciphertext directly, as described in most conventional authentication methods, the related encoded information is embedded into a cover image to avoid the attention of eavesdroppers. First, multiple images are encoded to form real-valued sequences composed of corresponding bucket values obtained by the aid of computational ghost imaging, and four sub-images are obtained by decomposing the cover image using wavelet transform. Second, measured sequences are embedded into one of the sub-images, and embedding positions are randomly selected using corresponding binary masks. To enhance the security level, a chaotic sequence is produced using logistic map and used to scramble measured intensities. Most importantly, original images with high quality can be directly recovered using total-variation minimization. The validity and robustness of the proposed approach are verified with optical experiments.