This study investigated the effects of icon familiarity on visual search performance. An equal number of familiar and unfamiliar icons were selected as background icons. These background icons were randomly arranged, and a visual search experiment was conducted to locate the target icon. The results showed no significant difference in the time required to find the target icon, regardless of whether the target icon was familiar or unfamiliar. This finding contrasts with previous studies that have suggested a positive effect of target icon familiarity on visual search performance, indicating that the influence of target icon familiarity may not always be consistent and could depend on the characteristics of the background icons. However, when background icons were grouped based on their familiarity, the time taken to locate the target icon was significantly reduced compared to when the icons were randomly arranged. To understand the underlying mechanism of this effect, participants' gaze fixation times were observed. The results revealed that participants spent more time fixating on areas where the target icon was located, rather than on areas without the target icon, suggesting a more efficient visual search process. Moreover, the shorter the visual search time, the higher the proportion of time spent fixating on the area containing the target icon. Additionally, this study examined the contrast ratio between the color of the background space and the dominant color of the target icon, comparing it with the visual search time. The findings indicated that as the contrast ratio increased, the visual search time decreased.

This study examines the feasibility of using event-related potentials (ERPs) obtained from electroencephalographic (EEG) recordings as biomarkers for long-term memory item classification. Previous studies have identified old/new effects in memory paradigms associated with explicit long-term memory and familiarity. Recent advancements in convolutional neural networks (CNNs) have enabled the classification of ERP trials under different conditions and identification of features related to neural processes at the single-trial level. We employed this approach to compare three CNN models with distinct architectures using experimental data. Participants (N = 25) performed an association memory task while recording ERPs that were used for training and validation of the CNN models. The EEGNET-based model achieved the most reliable performance in terms of precision, recall, and specificity compared with the shallow and deep convolutional approaches. The classification accuracy of this model reached 70% for known items and 62% for unknown items. Good overall accuracy requires a trade-off between recall and specificity and depends on the architecture of the model and the dataset size. These results suggest the possibility of integrating ERP and CNN into online learning tools and identifying the underlying processes related to long-term memorization.

As governments in various countries and regions issue tourism-friendly policies in the post-pandemic period, the voices for tourism consumption recovery and innovative transformation have attracted great attention. Many scholars, experts and industry professionals in the field of festivals are actively exploring efficient solutions for festival marketing and sustainability. It is worth rethinking tourists’ consumption psychology and perceived image toward exiting festival products as well as the antecedents that affect festival loyalty. The Qingdao International Beer Festival, as one of the most influential festivals in China, was selected as the research case for this study. The main goal of this study was to investigate festival consumption promotion mechanism by proposing a conceptual framework in which the associations from destination familiarity and product familiarity to loyal intentions (re-patronage and recommendation) were examined, with mediators of overall festival image, perceived value and overall satisfaction. Furthermore, the moderating role of visitor involvement in the proposed framework was also adequately demonstrated. The research findings are expected to provide a significant reference for the recovery and competitiveness improvement of the entire festival industry.

Background: Hashimoto’s thyroiditis (HT) is an autoimmune disease that progressively leads to thyroid gland destruction and hypothyroidism. Patients produce antibodies against two thyroid-specific antigens: thyroglobulin and thyroid peroxidase. As a result of the abnormal amount of thyroid hormone produced and its autoimmune etiology, patients with HT display a higher frequency of either autoimmune or non-autoimmune dermatological disorders. On ultrasound examination, HT can be detected by observing an enlarged thyroid gland with hypoechoic parenchymal regions or by observing a small gland indicating atrophy and diffusely heterogeneous parenchyma. Changes in the parenchymal vascularity can be observed as decreased or increased levels of vascularization. Objective: This study aimed to analyze the role of clinical data and ultrasound evaluation of patients with HT in suggesting an association with dermatological disorders. Patients and methods: Complete dermatological and endocrinological assessments as well as ultrasonography of the thyroid and lymphnodes were performed in HT patients. Results: The data obtained showed that a family history of thyroid disease, increased diameter of the inferior thyroid artery, and the presence of cervical lymphadenopathy were more frequent in the group of patients with dermatological diseases. Taken together, our results suggest the usefulness of ultrasound in determining a possible association between HT and dermatological disorders.

Efficient use of the operating room (OR) is crucial for any hospital. One of the major inefficiencies in the OR is surgical cases not starting or finishing on time as scheduled. When a case is delayed, it affects all subsequent cases in that OR. This study uses discrete choice analysis to determine the significant factors, including team familiarity, that influence OR case on-time start and finish. A case is considered on-time if the documented procedure start and finish times are no more than 10 minutes after the scheduled start and finish times. The analysis uses surgical case data from a large tertiary referral hospital and academic center in Greenville, South Carolina. The case data includes all surgical cases (15,091) performed during regular workdays in 2013. Two binary logit models are developed: one for case on-time start and one for case on-time finish. Results indicate that higher team familiarity between surgeon and anesthesiologist, surgeon and circulating nurse, surgeon and scrub nurse, and surgeon and CRNA improve the likelihood of an OR case on-time start and on-time finish. This finding indicates that the OR scheduling staff in the study hospital make a concerted effort to schedule the surgical teams with members who have worked well together in the past.

Our brain continuously interacts with the body as we engage with the world. Although we are mostly unaware of internal bodily processes, such as our heartbeats, they may be influenced by and in turn influence our perception and emotional feelings. While there is a recent focus on understanding cardiac interoceptive activity and interaction with brain activity during emotion processing, the investigation of cardiac-brain interactions with more ecologically valid naturalistic emotional stimuli is still very limited. We also do not understand how an essential aspect of emotions like context familiarity influences affective feelings and is linked to cardiac-brain interactions. Hence to answer these questions, we designed an exploratory study by recording ECG and EEG signals for the emotional events while participants were watching emotional movie clips. Participants also rated their familiarity with the stimulus on the familiarity scale. Linear mixed effect modelling was performed in which the ECG power and familiarity were considered as predictors of EEG power. We focused on three brain regions, including prefrontal (PF), frontocentral (FC) and parietooccipital (PO). The analyses showed that cardiac-brain interaction is dependent on familiarity such that the interaction is stronger with high familiarity. In addition, the results indicate that arousal is predicted by cardiac-brain interaction, which also depends on familiarity. The results support emotional theories that emphasize context dependency and interoception. Multimodal studies with more realistic stimuli would further enable us to understand and predict different aspects of emotional experience.