Realizing quantum computation with semiconductor spin qubits requires large-scale integration of quantum dots (QDs). In large-scale gate-defined QD arrays, adjusting the physical parameters such as electrochemical potentials and tunnel couplings becomes increasingly complicated due to crosstalk arising from capacitive couplings between the gate electrodes and QDs. To compensate for this crosstalk, virtual gates were developed to enable independent control of QD-array parameters. Constructing virtual gates requires determining and frequently updating the cross-capacitance matrix that maps the gate voltage effects on physical parameters. However, as the number of QDs increases, manual extraction of cross-capacitance matrix becomes increasingly time-consuming, posing a significant scalability challenge. To address this challenge, we introduce a convolutional neural network (CNN)-assisted framework that automates the construction of virtual gates. Using a double QD as a testbed, our automated framework accurately extracts the cross-capacitance matrix and constructs virtual gates, providing a key step toward scalable virtual-gate control of large QD arrays.
As demonstrated, heart rate variability (HRV) biofeedback (HRVB) is effective in managing chronic conditions. However, reviews specifically addressing HRVB effects on cardiac autonomic dysfunction in patients with cardiovascular diseases (CVDs) are lacking. We evaluated HRVB effects on autonomic, hemodynamic, and psychological outcomes in such patients. This systematic review and meta-analysis of randomized controlled trials (RCTs) searched MEDLINE, CINAHL, Web of Science, Cochrane Central Register of Controlled Trials, and Igaku Chuo Zasshi from inception to April 2025. We included RCTs on HRVB in CVD populations and excluded those without HRV, clinical, or psychological outcomes. Two reviewers independently screened, extracted data, and assessed risk of bias using Cochrane RoB 2 tool. Random-effects models were applied to HRV indices, blood pressure, respiratory rate, and psychological outcomes. From 2402 records, 13 RCTs (965 participants; 795 analyzed) were included. HRVB significantly improved the standard deviation of NN interval; low-frequency (LF) and logLF increased, high-frequency (HF) and logHF showed no significant changes. Both systolic (mean difference [MD] = − 3.08, 95
Background: Recent studies have focused on oral frailty and hypofunction, and their relationship with swallowing function and dysphagia. These play especially important roles in patients with dysphagia in medical-dental cooperation at acute hospitals. Objective: This study aimed to assess oral frailty, in terms of nutritional intake by evaluating oral and swallowing functions simultaneously, in patients consulting at an acute hospital. Methods: This cross-sectional study was conducted at the Center for Dysphagia of Tohoku University Hospital and involved a comprehensive survey of 183 patients. Their oral function and oral status were evaluated, which included factors such as poor oral hygiene, oral dryness, tongue-lip motor function, tongue pressure, and masticatory performance. Additionally, swallowing status was evaluated using various methods, including a questionnaire related to swallowing, Hyodo-Komagane score, modified water-swallowing, and repetitive saliva swallowing tests. This thorough approach ensured the validity and reliability of our findings.Results Approximately 60% of patients had head and neck tumours, degenerative diseases, and muscular diseases. Therefore, a high prevalence of oral hypofunction was observed. Furthermore, since 41.5% of patients had limited tongue movement, a characteristic correlation existed between the oral diadochokinesis and Hyodo-Komagane score. Conclusion: These results suggest that oral dryness score, oral diadochokinesis, and tongue pressure are associated with oral hypofunction and dysphagia. Additionally, patients with hypofunction and decreased tongue pressure may have hypopharyngeal residuals. The medical-dental cooperation in an acute hospital allows for the simultaneous assessment of oral and swallowing functions. This suggests a potential to contribute to the practice of safe oral intake and appropriate rehabilitation.
This study examines how visible engagement cues on RED influence purchase intention in beauty-related user-generated content (UGC). Drawing on the Stimulus–Organism–Response (S-O-R) framework, the study treats likes, saves, comment counts, and hashtags as stimulus variables, sentiment score, comment length, and lexical density as comment-level processing variables, and purchase intention expressed in comments as the response. The data were collected from 500 publicly available RED posts identified through five beauty-related Chinese search terms, with an initial sample of 4,590 comments and a final analytical sample of 4,371 valid comments after preprocessing. Descriptive statistics, correlation analysis, logistic regression, linear regression, and bootstrap mediation analysis with 5,000 resamples were employed. The results show that visible engagement cues do not operate uniformly. Saves were positively associated with purchase intention, whereas likes and comment counts showed negative associations, and hashtags were not significant. At the comment level, comment length was positively associated with purchase intention, while lexical density was negatively associated; sentiment score was not significant. The mediation analysis further indicates that comment length and lexical density serve as meaningful pathways linking visible engagement to purchase intention, whereas sentiment does not. These findings suggest that comment-based processing indicators provide more useful insight than sentiment alone in explaining purchase intention on RED.
