Understanding the Impact Mechanism of User Behavior Pattern toward Real Estate APP Platforms in the Post-COVID Era: A Quantitative Analysis

While technology factors are the main driver of the booming real estate APP platforms with important implications for user behavior pattern during and post-pandemic contexts, there is a lack of adequate research. In response, this study explores the user behavior pattern of real estate APP platforms to promote user mental health by taking the real estate APP platforms users as the participants based on theory of technology readiness and acceptance model. Data collected from offline surveys are analyzed using PLS-SEM. The results reveal the technology readiness index positively affects individuals' perceived usefulness and satisfaction, ultimately positively affects individuals' continuance intention with real estate APP platforms;satisfaction with real estate APP platforms mediated the relationship between technology readiness index, perceived ease of use, perceived usefulness, and individuals' continuance intention with real estate APP platforms. However, the group comparison finds no significant difference in user behavior patterns by gender. The contribution of this study is to reveal the influence mechanisms of digital technology on users' behavioral patterns toward real estate APP platforms, which can help guide the sustainable development of real estate APP platforms and promote user mental health and wellbeing in the post-COVID era.

The Association between Perceived Teacher Support, Students' ICT Self-Efficacy, and Online English Academic Engagement in the Blended Learning Context

The present study intended to examine the relationship between perceived teacher support, students' ICT self-efficacy, and online English academic engagement in the blended learning setting, especially in mobile-assisted foreign language instruction contexts. A sample of 960 Chinese undergraduate and postgraduate students was recruited to participate in the online questionnaire. SPSS version 24.0 was used for descriptive, correlation, independent samples t-test, and mediation analysis of the three variables. The results showed that: (1) there is a significant correlation between perceived teacher support, students' ICT self-efficacy, and online English academic engagement;(2) students' ICT self-efficacy partially mediates the relationship between perceived teacher support and student online English academic engagement;(3) students' ICT self-efficacies differed by sex and level of education, but not by major;(4) students' sense of self-competence in ICT self-efficacy has a significant positive influence on engagement with online English learning. The findings reveal that students' ICT self-efficacy positively impacts students' online English learning, and perceived teacher support also affects students' learning engagement. School administrators should encourage teachers to focus on students' online self-efficacy, especially the sense of environmental control. Implications and further directions for future research are presented at the end.

Investigating sleep quality and sleep hygiene awareness among Chinese adults: an association and network analysis study.

PURPOSE: The relationships between sleep quality and sleep hygiene awareness in the Chinese population were unclear. We aimed to investigate the associations and related factors between sleep quality and sleep hygiene awareness in adults and to identify the most central domain for sleep quality using network analysis. METHODS: A cross-sectional survey was conducted from April 22 to May 5, 2020. Adults (18 years old or above) who had access to smartphones were invited to participate in this survey. The Pittsburg Sleep Quality Index (PSQI) and the Sleep Hygiene Awareness and Practice Scale (SHAPS) were used to evaluate the sleep quality and sleep hygiene awareness of the participants. Propensity score matching (PSM) was used as sensitivity analysis to reduce the confounding effects. Multiple logistic regression was performed to evaluate the associations. The R packages "bootnet" and "qgraph" were used to estimate the connection and calculate the network centrality indices between good and poor sleepers. RESULTS: In total, 939 respondents were included in the analysis. Of them, 48.8% (95% CI: 45.6-52.0%) were identified as poor sleepers. Participants with nervous system diseases, psychiatric diseases, and psychological problems were more likely to have poor sleep quality. The notion that using sleep medication regularly was beneficial to sleep was associated with poor sleep quality. Similarly, the notion that waking up at the same time each day disrupted sleep was also associated with poor sleep quality. The findings were consistent before and after PSM. Subjective sleep quality was the most central domain for sleep quality in good and poor sleepers. CONCLUSION: Poor sleep quality was positively associated with certain sleep hygiene notions in Chinese adults. Effective measures such as self-relief, sleep hygiene education, and cognitive behavioral treatment may have been needed to improve sleep quality, especially during the COVID-19 outbreak.

Ensemble learning with speaker embeddings in multiple speech task stimuli for depression detection.

Introduction: As a biomarker of depression, speech signal has attracted the interest of many researchers due to its characteristics of easy collection and non-invasive. However, subjects' speech variation under different scenes and emotional stimuli, the insufficient amount of depression speech data for deep learning, and the variable length of speech frame-level features have an impact on the recognition performance. Methods: The above problems, this study proposes a multi-task ensemble learning method based on speaker embeddings for depression classification. First, we extract the Mel Frequency Cepstral Coefficients (MFCC), the Perceptual Linear Predictive Coefficients (PLP), and the Filter Bank (FBANK) from the out-domain dataset (CN-Celeb) and train the Resnet x-vector extractor, Time delay neural network (TDNN) x-vector extractor, and i-vector extractor. Then, we extract the corresponding speaker embeddings of fixed length from the depression speech database of the Gansu Provincial Key Laboratory of Wearable Computing. Support Vector Machine (SVM) and Random Forest (RF) are used to obtain the classification results of speaker embeddings in nine speech tasks. To make full use of the information of speech tasks with different scenes and emotions, we aggregate the classification results of nine tasks into new features and then obtain the final classification results by using Multilayer Perceptron (MLP). In order to take advantage of the complementary effects of different features, Resnet x-vectors based on different acoustic features are fused in the ensemble learning method. Results: Experimental results demonstrate that (1) MFCC-based Resnet x-vectors perform best among the nine speaker embeddings for depression detection; (2) interview speech is better than picture descriptions speech, and neutral stimulus is the best among the three emotional valences in the depression recognition task; (3) our multi-task ensemble learning method with MFCC-based Resnet x-vectors can effectively identify depressed patients; (4) in all cases, the combination of MFCC-based Resnet x-vectors and PLP-based Resnet x-vectors in our ensemble learning method achieves the best results, outperforming other literature studies using the depression speech database. Discussion: Our multi-task ensemble learning method with MFCC-based Resnet x-vectors can fuse the depression related information of different stimuli effectively, which provides a new approach for depression detection. The limitation of this method is that speaker embeddings extractors were pre-trained on the out-domain dataset. We will consider using the augmented in-domain dataset for pre-training to improve the depression recognition performance further.

Association between COVID-19 and Postoperative Neurological Complications and Antipsychotic Medication Use after Cancer Surgery: A Retrospective Study.

INTRODUCTION: Millions of Americans infected with the severe acute respiratory syndrome-associated coronavirus-19 (COVID-19) need oncologic surgery. Patients with acute or resolved COVID-19 illness complain of neuropsychiatric symptoms. How surgery affects postoperative neuropsychiatric outcomes such as delirium is unknown. We hypothesize that patients with a history of COVID-19 could have an exaggerated risk of developing postoperative delirium after undergoing major elective oncologic surgery. METHODS: We conducted a retrospective study to determine the association between COVID-19 status and antipsychotic drugs during postsurgical hospitalization as a surrogate of delirium. Secondary outcomes included 30 days of postoperative complications, length of stay, and mortality. Patients were grouped into pre-pandemic non-COVID-19 and COVID-19-positive groups. A 1:2 propensity score matching was used to minimize bias. A multivariable logistic regression model estimated the effects of important covariates on the use of postoperative psychotic medication. RESULTS: A total of 6003 patients were included in the study. Pre- and post-propensity score matching demonstrated that a history of preoperative COVID-19 did not increase the risk of antipsychotic medications postoperatively. However, respiratory and overall 30-day complications were higher in COVID-19 individuals than in pre-pandemic non-COVID-19 patients. The multivariate analysis showed that the odds of using postoperative antipsychotic medication use for the patients who had COVID-19 compared to those who did not have the infection were not significantly different. CONCLUSION: A preoperative diagnosis of COVID-19 did not increase the risk of postoperative antipsychotic medication use or neurological complications. More studies are needed to reproduce our results due to the increased concern of neurological events post-COVID-19 infection.

Immunogenicity and reactogenicity of heterologous immunization schedules with COVID-19 vaccines: a systematic review and network meta-analysis.

BACKGROUND: Data on the immunogenicity and safety of heterologous immunization schedules are inconsistent. This study aimed to evaluate the immunogenicity and safety of homologous and heterologous immunization schedules. METHODS: Multiple databases with relevant studies were searched with an end date of October 31, 2021, and a website including a series of Coronavirus disease 2019 studies was examined for studies before March 31, 2022. Randomized controlled trials (RCTs) that compared different heterologous and homologous regimens among adults that reported immunogenicity and safety outcomes were reviewed. Primary outcomes included neutralizing antibodies against the original strain and serious adverse events (SAEs). A network meta-analysis (NMA) was conducted using a random-effects model. RESULTS: In all, 11 RCTs were included in the systematic review, and nine were ultimately included in the NMA. Among participants who received two doses of CoronaVac, another dose of mRNA or a non-replicating viral vector vaccine resulted in a significantly higher level of neutralizing antibody than a third CoronaVac 600 sino unit (SU); a dose of BNT162b2 induced the highest geometric mean ratio (GMR) of 15.24, 95% confidence interval [CI]: 9.53-24.39. Following one dose of BNT162b2 vaccination, a dose of mRNA-1273 generated a significantly higher level of neutralizing antibody than BNT162b2 alone (GMR = 1.32; 95% CI: 1.06-1.64), NVX-CoV2373 (GMR = 1.60; 95% CI: 1.16-2.21), or ChAdOx1 (GMR = 1.80; 95% CI: 1.25-2.59). Following one dose of ChAdOx1, a dose of mRNA-1273 was also more effective for improving antibody levels than ChAdOx1 (GMR = 11.09; 95% CI: 8.36-14.71) or NVX-CoV2373 (GMR = 2.87; 95% CI: 1.08-3.91). No significant difference in the risk for SAEs was found in any comparisons. CONCLUSIONS: Relative to vaccination with two doses of CoronaVac, a dose of BNT162b2 as a booster substantially enhances immunogenicity reactions and has a relatively acceptable risk for SAEs relative to other vaccines. For primary vaccination, schedules including mRNA vaccines induce a greater immune response. However, the comparatively higher risk for local and systemic adverse events introduced by mRNA vaccines should be noted. REGISTRATION: PROSPERO; https://www.crd.york.ac.uk/PROSPERO/ ; No. CRD42021278149.

UGTs-mediated metabolic interactions contribute to enhanced anti-inflammation activity of Jinhongtang.

ETHNOPHARMACOLOGICAL RELEVANCE: Jinhongtang, a traditional Chinese medicine (TCM) formula consisting of dry stems of Rheum palmatum L. (Polygonaceae) and Sargentodoxa cuneata (Oliv.) Rehder & E.H.Wilson (Lardizabalaceae) and whole plant of Taraxacum mongolicum Hand.-Mazz. (Asteraceae), is widely used for the treatment of infection diseases including severe sepsis and COVID-19. AIM OF THE STUDY: The present study aimed to explore the compatibility mechanism in the prescription of Jinhongtang based on the pharmacokinetic interaction. MATERIALS AND METHODS: CLP-induced sepsis mice and LPS-induced RAW264.7 cells were used to explore the anti-inflammatory effect of Jinhongtang and herbs in this clinical prescription. Pharmacokinetics of active components in Jinhongtang (Rhein, Emodin and Aloe emodin) was studied in rats. In vitro analysis of metabolic pathways and interactions mediated by metabolic enzymes were conducted using human liver microsomes (HLMs) and recombinant UGT isoforms. RESULTS: Jinhongtang exhibited much more potent anti-inflammatory effect than its single herbs on CLP-induced sepsis mice and LPS-induced RAW264.7 cells. Next, the bioavailability of active ingredients (Rhein, Emodin and Aloe emodin) in R. palmatum was significantly improved through reduced metabolic clearance when co-administered with S. cuneata and T. mongolicum as Jinhongtang during the in vivo pharmacokinetic study, which presented the rational herbal compatibility mechanism. In detailed, the components in S. cuneata and T. mongolicum including Sargentodoxoside A, Chanitracin Ia, Quercetin and Luteolin inhibited the UGT1A9-mediated glucuronidation of active ingredients in R. palmatum, with Ki values of 2.72 µM, 1.25 µM, 2.84 µM and 0.83 µM, respectively. CONCLUSION: T. mongolicum and S. cuneata, the adjuvant herbs of Jinhongtang, could reduce the metabolic clearance of key active components of R. palmatum, prolong their action time and further enhance their anti-inflammatory activity via inhibition of UGTs. Our findings provided deep insight for the rational compatibility of TCMs and useful guidance for the development of TCM formula.

Analysis on mosquito control effect in quarantine hotels for COVID-19 medical observation in Pudong District in 2020

Objective To analyze the mosquito density and larvae breeding of quarantine hotels for COVID-19 medical observation in Pudong District of Shanghai in 2020, assess mosquito control effect in outdoor environment of the hotels, and provide suggestions for the prevention and control of mosquito-borne diseases in these hotels. Methods CO2 traps were used for the investigation of mosquito density outside the quarantine hotels in the middle of every month from May to November in 2020, Breteau index and mosq-ovitrap method were adopted to monitor Aedes albopictus laval density in the middle of every month from May to October. Those investigation were also carried out in residential areas around the quarantine hotels. Mosquito control was conducted once a month in the town where the quarantine hotels located from May to November. Results The peak of mosquito density, Breteau index and mosq-ovitrap index in quarantine hotels for medical observation all appeared in June, being 1.85, 10.49 and 7.99 insects per trap per hour, respectively. The peak of mosquito density, Breteau index and mosq-ovitrap index in residential areas appeared in different month, being 2.00, 9.08 and 12.40 insects per trap per hour, respectively. The peaks of mosquito density and mosq-ovitrap index in quarantine hotels were earlier than those in residential areas. Statistical analysis showed that there was significant difference in the positive rate of mosq-ovitrap between quarantine hotels and residential areas (P < 0.001). The mosquito density in quarantine hotels reached the control standard, but the control effect of Aedes albopictus breeding sites was poor. Conclusion There was a risk of mosquito-borne diseases in quarantine hotels, so attention should be paid to mosquito control in such places and the construction of anti-mosquito facilities.

Investigation on the risk factors of blood infection in patients with lymphoma

Objectives: To investigate the risk factors for a blood infection in patients with lymphoma in order to guide the clinical prevention and control Of infection. Method: Clinical data were collected from 434 patients with lymphoma in 2019. including 231 males and 203 females. Blood samples were collected for culture, and the pathogens were identified by a VITEK-32 automated microbial identification system. PCR was used to detect Virulence genes of Klebsiella pneumoniae. Data were collected, such as patients' age, disease status, clinical stage, and pathological type. and risk factors affecting the incidence of infection in patients were analyzed using a Chi-square test.

Customized protective visors enabled by closed loop controlled 4D printing.

The COVID-19 pandemic makes protective visors important for protecting people in close contacts. However, the production of visors cannot be increased greatly in a short time, especially at the beginning of the pandemic. The 3D printing community contributed largely in fabricating the visor frames using the rapid and adaptive manufacturing ability. While there are many open source designs of face visors for affordable 3D printers, all these designs fabricate mono-sized frames without considering diverse users' dimensions. Here, a new method of visor post-processing technology enabled by closed loop controlled 4D printing is proposed. The new process can further deform the printed visor to any customized size for a more comfortable user experience. FEM analysis of the customized visor also shows consistent wearing experience in different circumstances compared with the old visor design. The fabrication precision and time cost of the method is studied experimentally. A case study regarding the reducing, reusing and recycling (3R) of customized visors in classrooms is proposed to enable the customized visors manufactured in a more sustainable way.

Mental health status of rural residents in Southwest Anhui province during prevention and control of coronavirus disease 2019

Objective: To explore the mental health status of rural residents in Southwest Anhui province and its influencing factors during the coronavirus disease 2019 (COVID-19) epidemic.

Investigation of the Cognitive Attitudes and Behaviors of Medical Post-graduates in Clinical Practice During the COVID-19 Pandemic in China.

The cognitive attitudes and behaviors of medical post-graduates may be influenced by the coronavirus disease 2019 (COVID-19) pandemic. A cross-sectional study was used from a questionnaire survey in hospitals affiliated with the Zhejiang University School of Medicine. Questionnaire was distributed online including demographic information, cognitive attitudes, and personal protective behaviors. Moreover, personal protective behaviors such as wearing protective equipment were compared between different academic major and gender, respectively. A total of 176 valid questionnaires were obtained. Of the medical post-graduates in this study, (1) 89.67% believed that the COVID-19 pandemic had an impact on their clinical internships, and 40.34% expressed concerns about their infection on inadequate personal protection; (2) 91.48% took personal protection in hospital and 86.36% enhanced personal hygiene; (3) There were no statistically differences in the personal protection by academic major and gender (p > 0.05). This study suggests that the COVID-19 pandemic had an impact on the medical post-graduates' clinical practice, and affected their cognitive attitudes and behaviors. As such, universities and hospitals should increase pandemic prevention training and investment, provide more psychological counseling to their medical post-graduates to reduce their psychological burden, and take measures to reduce the influence of the COVID-19 pandemic on their medical post-graduates' clinical practice.

The evolution of chest CT findings from admission to follow-up in 30 moderate to severe adult patients with COVID-19 pneumonia.

OBJECTIVE: To analyze the evolution of chest computed tomography (CT) findings from admission to follow-up in moderate to severe patients with coronavirus disease-19 (COVID-19) pneumonia. METHODS: During December 2019-April 2020, the sequential CT images of 30 patients with COVID-19 pneumonia were retrospectively analyzed from admission to follow-up. The qualitative evolution tendency of lung abnormalities and semi-quantitative CT scores were analyzed for temporal change. RESULTS: The mean hospitalized period was 24.5 ± 9.6 days (range 6-49 days). The average time from the first, second, third, fourth and follow-up CT examination to the initial symptom onset were 4.2 ± 3.1 days, 10.7 ± 4.4 days, 17.1 ± 3.9 days, 24.6 ± 7.5 days, and 42.4 ± 15.6 days, respectively. During illness day 0-5, groundglass opacity (GGO) was the main pattern. The following illness day 6-11, the main CT pattern was consolidation and reticular pattern. The consolidation and reticular pattern gradually dissipate during illness day 12-23, and the reticular pattern and light GGO increased. When illness day was ≥ 24 days, the reticular pattern and light GGO gradually decrease until complete dissipation. The highest CT score was at illness day 6-11. Pearson correlation analysis showed that the mean and maximum CT score were not correlated with the length of fever (r = 0.018, p = 0.923 and r = 0.086, p = 0.652) and hospitalization (r = 0.192, p = 0.31 and r = 0.273, p = 0.144). CONCLUSIONS: The dynamic evolution of CT manifestation in moderate to severe COVID-19 pneumonia patients followed a specific pattern over time. During illness day 6-11, the extent of lung abnormalities on chest CT was the most severe. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s42058-021-00058-2.

Role of anti-Müllerian hormone and testosterone in follicular growth: a cross-sectional study

BACKGROUND: Anti-Müllerian hormone (AMH) is now considered the best serum biomarker of ovarian reserve, while basal sex hormones are classic markers used for assessing ovarian reserve. The interaction between AMH and sex hormones are complicated and not sufficiently addressed. In this study, we took diminished ovarian reserve (DOR) and polycystic ovarian syndrome (PCOS) as two extremes of ovarian reserve (deficient and excessive respectively) to investigate the role of AMH and sex hormones in follicular growth. METHODS: A retrospective cross-sectional survey was performed. The patients assessed AMH and basal sex hormones in the Second Hospital of Zhejiang University from April 2016 to March 2019 were involved in this study. Serum AMH and sex hormone concentrations were tested with electrochemiluminescence method. Stepwise linear regression and binary logistic regression was used to determine the predictors of AMH level and to explore the involved factors determining DOR and PCOS. RESULTS: In the present study, we found that age and follicle-stimulating hormone (FSH) were main negative correlation factors, and luteinizing hormone (LH) and testosterone (T) were main positive factors of AMH. In DOR group, age, FSH and estradiol (E2) increased and T decreased, while in PCOS group, LH and T increased. Binary logistic regression found that age, weight, FSH, E2, and T were the significant factors which independently predicted the likelihood of DOR, and that age, body mass index (BMI), AMH, LH, and T predicted the likelihood of PCOS. CONCLUSIONS: Our study demonstrated that age, FSH, and T were factors that most closely correlated with AMH level, and T was involved in both DOR and PCOS. Since DOR and PCOS are manifested with insufficient AMH and excessive AMH respectively, it is suggested that total testosterone correlated with AMH closely and plays an important role in follicular growth. More attention should be given to testosterone level during controlled ovarian hyperstimulation (COH) process.