Background: Few studies have investigated traditional Chinese medicine (TCM) utilization patterns for irritable bowel syndrome (IBS), despite the potential benefits of exploring TCM utilization patterns in optimizing TCM management. This study aimed to evaluate TCM utilization patterns and clinical features for IBS patterns in Taiwan. Methods: This was a population-based cross-sectional study using claim data from the National Health Insurance Research Database between 2012 and 2018. Patients newly diagnosed with IBS and aged over 20 years were included. The TCM utilization patterns and characteristics, including Chinese herbal medicine (CHM) treatment types and prescription patterns, were evaluated. Results: A total of 73,306 patients newly diagnosed with IBS used TCM for IBS at least once. Females used TCM for IBS more than males (female-to-male ratio = 1.89: 1). The age distribution showed a peak at 30-39 years (27.29%), followed by 40-49 years (20.74%) and 20-29 years (20.71%). Patients who received Western medications for IBS had a lower tendency to seek TCM. CHM was the most commonly used TCM modality (98.22%), with Jia-wei-xiao-yao-san being the most commonly prescribed Chinese herbal formula and Bai-zhu being the most frequently prescribed single Chinese herb. Conclusion: This study enhances our understanding of TCM usage patterns for IBS, particularly CHM prescriptions. Further research is needed to investigate commonly used TCM formulas and individual herbs.
Facial Expression Recognition (FER) is a hot research topic currently, many efforts have been made on improving the recognition accuracy on certain datasets. Nevertheless, most of the existing works on FER are focused on verifying their algorithms on testing set, ignoring the practicability of their model in the real world. In this paper, more attention is addressed on improving the FER performance in the wild and the application of the FER model on robots. Firstly, a FER dataset is collected for training the model of facial expression recognition in the wild (FERW). Furthermore, a real-time positive emotion incentive system (PEIS) is developed for improving user experience of the robot. The proposed PEIS, which can recognize, record, analysis the emotion status of the users and give humanized feedback, consists of emotion recognition, emotion analysis and emotion feedback. Emotion recognition, the first as well as the most important part of this system, is realized by FERW based on deep learning and voting method. The PEIS is evaluated in two scenario, one is the accuracy of FERW in natural scene, and the other is the user experience of the robot employs the PEIS. Finally, experiments show that our FERW model can recognize facial expressions in real-life with an accuracy of 79%, which is practicable in the real world. Our robot XiaoBao, equipped with the PEIS, is able to enhance user experience.
In this paper, we aimed to study the energy consumption problem in a collaborative activity monitoring system (CAMS) that consists of a companion robot and a wearable device. First, we tested the energy consumption in different operation modes of the system. Based on that, we analyzed the effect of bandwidth on the time cost and energy consumption which allowed us to combine WiFi and Bluetooth together for data transmission to improve the performance of the system. Second, we preprocessed the image data on the wearable device to reduce the size of images before sending them to the robot, and analyzed the time and energy consumption cost by local computing and data transmission. Third, based on the bandwidth of WiFi and Bluetooth, the requirement of time and energy consumption, we proposed an optimization problem on image sizes in which the wearable device decides how to send the data to the robot to reduce the energy and time cost. The results showed that the relations between the bandwidth, time cost, image resolutions and energy consumption could be used to improve the performance of CAMS.
Traditionally the leader or follower role of the robot in a human-robot collaborative task has to be predetermined. However, humans performing collaborative tasks can switch between or share the leader-follower roles effortlessly even in the absence of audio-visual cues. This is because humans are capable of developing a mutual understanding while performing the collaborative task. This paper proposes a framework to endow robots with a similar capability. Behavior of the robot is controlled by two types of controllers such as reactive and proactive controllers each giving the robot follower and leader characteristics respectively. Proactive actions are based on human motion prediction. We propose that the role of the robot can be governed by the confidence of prediction. Hence, the robot can determine its role during the task autonomously and dynamically. The framework is demonstrated and evaluated through a table-lifting task. Experimental results confirm that the proposed system improves the overall task performance.
OBJECTIVE To investigate the therapeutic effect of verapamil for patients with left ventricular diastolic heart failure (DHF).METHODS Eighty-four patients with DHF were randomLy divided into group A (n=42) who were given standard treatment including ACEI and diuretic and group B (n=42) who were administrated verapamil and standard treatment,for 30 weeks.Before and after treatment the 6-minute walk test and plasma brain natriuretic peptide (BNP) concentrations were measured in order to evaluate the effect of verapamil on left ventricular diastolic heart failure.RESULTS Compared with group A,distance of 6 minute walk remarkably improved (P0.05)and BNP concentration in plasma significantly decreased in group B (P0.05) after 30 weeks.CONCLUSION Verapamil combined with ACEI and diuretic can definitely improve the left ventricular diastolic function of DHF.
Brain parenchyma schwannoma is a rare intracranial tumor, and especially rare in cerebellar hemisphere.In this report, a case of cerebellar schwannoma in a 52-year-old woman, was studied by computed tomography (CT), magnetic resonance image (MRI) and PET-CT.This tumor was totally removed by surgery.The histological diagnosis of schwannoma was confirmed by histological, HE and immunohistological staining examination (positivity for the S-100 protein and vimentin, and partly positivity for P53 (70 %+), and negative for GFAP).The patient has been followed-up for more than one year, and she lives in good condition and brain MRI shows no recurrence.Surgery is the most effective treatment for cerebellar schwannoma. KeywOrds:
Breakthrough infection of SARS-CoV-2 is a serious challenge, as increased infections were documented in fully-vaccinated individuals. Recipients with poor antibody response are highly vulnerable to reinfection, whereas those with strong antibody responses achieve sterilizing immunity. Thus far, biomarkers associated with levels of vaccine-elicited antibody response are still lacking. Here, we studied the antibody response of age- and gender-controlled healthy cohort, who received inactivated SARS-CoV-2 vaccines and profiled the B cell receptor repertoires in longitudinally consecutive samples. Upon vaccination, all vaccinated individuals displayed a convergent antibody response with shared common antibody clones and public neutralizing antibodies. Strikingly, poor vaccine-responders are distinguishable from strong vaccine-responders by a biased V-usage before vaccination and IgG to IgM mRNA ratio. These findings reveal molecular signatures associated with the different levels of vaccine-induced antibody response, which could be further developed into biomarkers for the design of vaccination strategies.
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