Life changes and mental health among Chinese children and adolescents during the pandemic: a combination of cross-sectional, longitudinal and clustering studies (preprint)

The measures to prevent COVID-19 pandemic had caused significant life changes, which could be distressing for mental health among children and adolescents. We aimed to evaluate the short- and long-term effects of life changes on children’s mental health in a large Chinese cohort. Survey-based life changes during COVID-19 lockdown were measured among 7,829 Chinese students at Grade 1–9, including social contacts, lifestyles and family financial status. Clustering analysis was applied to identify potential patterns of these changes. Depressive and anxiety symptoms were measured using the Center for Epidemiologic Studies Depression Scale and Screen for Child Anxiety Related Emotional Disorders. Logistic regression models were used to investigate the associations between these changes, their patterns and the presence of depression/anxiety symptoms using both cross-sectional and longitudinal designs. We found that the prevalence of depression and anxiety symptoms decreased during pandemic (34.6–32.6%). However, during and shortly after lockdown, students who reported negative impacts on their study, social and outside activities and diet, and decreased electronic time and sugar-sweetened consumption, as well as family income decline and unemployment had increased risks of depressive/anxiety symptoms, and students with changed sleep time had increased depressive symptoms. These associations attenuated or disappeared one year later. Similar patterns were observed in clustering analysis, while only the group with severe impact on family financial status showed a sustained increase in depression symptoms. In summary, restrictive measures that changed children and adolescents’ daily life during COVID-19 lockdown showed negative effects on their mental health, with some commonalities and distinctions patterns in the manifestation of depression and anxiety symptoms.

COVID-19 Caused by the Omicron Variant in Lung Transplant Recipients: A Single Center Case Series (preprint)

Background: Limited data from the Chinese experience are available regarding the infection status, clinical characteristics, treatments and early outcomes of lung transplant recipients (LTRs) afflicted with coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 Omicron Variant. Methods: We conducted a study on LTRs with COVID-19 caused by the Omicron Variant from November 17, 2022, to May 1, 2023. Clinical information was gathered through electronic medical records, questionnaires, or follow-up telephone calls. To identify potential risk factors for severe disease progression, a multivariate logistic analysis was performed. Results: 178 LTRs with COVID-19 were included, with 50% (89/178) requiring hospitalization for an average stay of 16 days (IQR: 9.5-25.5 days). The most common symptoms were fever (79.8%), dry cough (75.3%) and fatigue (61.8%). Ultimately, 17 recipients succumbed to COVID-19-related respiratory failure or secondary multiple organ dysfunction, resulting in an overall mortality rate of 9.6%. Of the 89 hospitalized patients, 41.6% (37/89) eventually progressed to severe or critical disease, forming the Severe/Critical Group (S/C group), while the remaining 58.4% (52/89) had mild to moderate disease (M/M group). In comparison to the M/M group, the S/C group had higher CRP (59.6 vs. 16.8 mg/L, P＜0.01), ESR (45.5 vs. 22.5mm/h, P＜0.01) and D-dimer (1.09 vs. 0.65 mg/L, P＜0.05), but lower CD3+ T lymphocytes (577 vs. 962 cells/ul, P＜0.01) and CD4+ T lymphocytes (217 vs. 427 cells/ul, P＜0.01). The S/C group had significantly higher rates of combined pulmonary bacterial infection (67.6% vs. 38.5%, P＜0.01) and pulmonary fungal infection (73.0% vs. 38.5%, P＜0.01) during the course of COVID-19, nearly double that of the M/M group. In a multivariate logistic analysis, elevated CRP (>41.8mg/L), combined pulmonary fungal infection, and interstitial lung disease(ILD) as primary disease emerged as high-risk factors for developing the severe disease phenotype following Omicron variant infection in LTRs, with respective OR values of 4.23 (95% CI: 1.68-11.23), 4.76 (95% CI: 1.59-15.64), and 5.13 (95% CI: 1.19-29.17). Conclusions: LTRs displayed an increased vulnerability to combined lung bacterial or fungal infections following Omicron infection. CRP> 41.8mg/L, ILD as primary disease, and combined pulmonary fungal infection are high-risk factors for developing severe disease.

Carbon Monitor Europe near-real-time daily CO2 emissions for 27 EU countries and the United Kingdom.

With the urgent need to implement the EU countries pledges and to monitor the effectiveness of Green Deal plan, Monitoring Reporting and Verification tools are needed to track how emissions are changing for all the sectors. Current official inventories only provide annual estimates of national CO2 emissions with a lag of 1+ year which do not capture the variations of emissions due to recent shocks including COVID lockdowns and economic rebounds, war in Ukraine. Here we present a near-real-time country-level dataset of daily fossil fuel and cement emissions from January 2019 through December 2021 for 27 EU countries and UK, which called Carbon Monitor Europe. The data are calculated separately for six sectors: power, industry, ground transportation, domestic aviation, international aviation and residential. Daily CO2 emissions are estimated from a large set of activity data compiled from different sources. The goal of this dataset is to improve the timeliness and temporal resolution of emissions for European countries, to inform the public and decision makers about current emissions changes in Europe.

Large-scale, national, family-based epidemiological study on Helicobacter pylori infection in China: the time to change practice for related disease prevention.

BACKGROUND AND AIMS: Current practice on Helicobacter pylori infection mostly focuses on individual-based care in the community, but family-based H. pylori management has recently been suggested as a better strategy for infection control. However, the family-based H. pylori infection status, risk factors and transmission pattern remain to be elucidated. METHODS: From September 2021 to December 2021, 10 735 families (31 098 individuals) were enrolled from 29 of 31 provinces in mainland China to examine family-based H. pylori infection, related factors and transmission pattern. All family members were required to answer questionnaires and test for H. pylori infection. RESULTS: Among all participants, the average individual-based H. pylori infection rate was 40.66%, with 43.45% for adults and 20.55% for children and adolescents. Family-based infection rates ranged from 50.27% to 85.06% among the 29 provinces, with an average rate of 71.21%. In 28.87% (3099/10 735) of enrolled families, there were no infections; the remaining 71.13% (7636/10 735) of families had 1-7 infected members, and in 19.70% (1504/7636), all members were infected. Among 7961 enrolled couples, 33.21% had no infection, but in 22.99%, both were infected. Childhood infection was significantly associated with parental infection. Independent risk factors for household infection were infected family members (eg, five infected members: OR 2.72, 95% CI 1.86 to 4.00), living in highly infected areas (eg, northwest China: OR 1.83, 95% CI 1.57 to 2.13), and large families in a household (eg, family of three: OR 1.97, 95% CI 1.76 to 2.21). However, family members with higher education and income levels (OR 0.85, 95% CI 0.79 to 0.91), using serving spoons or chopsticks, more generations in a household (eg, three generations: OR 0.79, 95% CI 0.68 to 0.92), and who were younger (OR 0.57, 95% CI 0.46 to 0.70) had lower infection rates (p<0.05). CONCLUSION: Familial H. pylori infection rate is high in general household in China. Exposure to infected family members is likely the major source of its spread. These results provide supporting evidence for the strategic changes from H. pylori individual-based treatment to family-based management, and the notion has important clinical and public health implications for infection control and related disease prevention.

A novel capsule endoscopy for upper and mid-GI tract: the UMGI capsule.

BACKGROUNDS AND AIMS: Complete and consecutive observation of the gastrointestinal (GI) tract continues to present challenges for current endoscopy systems. We developed a novel upper and mid gastrointestinal (UMGI) capsule endoscopy using the modified detachable string magnetically controlled capsule endoscopy (DS-MCE) and inspection method and aimed to assess the clinical application. METHODS: Patients were recruited to undergo UMGI capsule endoscopy followed by esophagogastroduodenoscopy. All capsule procedures in the upper gastrointestinal (UGI) tract were conducted under the control of magnet and string. The main outcome was technical success, and the secondary outcomes included visualization of the UMGI tract, examination time, diagnostic yield, compliance, and safety evaluation. RESULTS: Thirty patients were enrolled and all UMGI capsule procedures realized repeated observation of the esophagus and duodenum with detection rates of 100.0%, 80.0%, and 86.7% of Z-line, duodenal papilla, and reverse side of pylorus, respectively. String detachment was succeeded in 29 patients (96.7%) and the complete examination rate of UMGI tract was 95.45% (21/22). All UMGI capsule procedures were well tolerated with low discomfort score, and had a good diagnostic yield with per-lesion sensitivity of 96.2% in UGI diseases. No adverse events occurred. CONCLUSIONS: This new capsule endoscopy system provides an alternative screening modality for the UMGI tract, and might be indicated in cases of suspected upper and small bowel GI bleeding. Trial registration DS-MCE-UGI and SB, NCT04329468. Registered 27 March 2020, https://clinicaltrials.gov/ct2/results?cond=&term=NCT04329468 .

Risk Perception of COVID-19 as a Cause of Minority Ethnic Community Tourism Practitioners' Willingness to Change Livelihood Strategies: A Case Study in Gansu Based on Cognitive-Experiential Self-Theory.

This study based on the cognitive-experiential self-theory, with risk attitude as the mediator and livelihood capacity as the moderator, explores the mechanism of the effect of risk perception of COVID-19 on minority ethnic community tourism practitioners' willingness to change livelihood strategies. Taking 423 tourism practitioners from five minority ethnic tourism communities as the objects of investigation in Gansu Province, China. This paper empirically tests the theoretical model by using Amos and SPSS. The results indicated the following: Risk perception of COVID-19 has a significant positive impact on the willingness of minority ethnic community tourism practitioners to change their livelihood strategies. Risk attitude partially mediated the relationship between risk perception of COVID-19 and willingness to change livelihood strategies. Livelihood capacity negatively moderated the relationship between risk perception of COVID-19 and willingness of minority ethnic community tourism practitioners to change their livelihood strategies. Livelihood capacity also negatively moderated the mediation effect of the relationship between risk perception of COVID-19 and willingness to change livelihood strategies. Based on the research conclusions, it provides theoretical guidance and practical enlightenment for minority ethnic community tourism practitioners on how to improve the stability and sustainability of their livelihoods through the adjustment and transformation of livelihood strategies in the post-epidemic era.

Impact of COVID-19 outbreak risk perception on willingness to consume products from restaurants: mediation effect of risk attitude

The COVID-19 outbreak caused huge losses for the catering industry. The outbreak's influence on consumers' risk perception and risk attitude was an important factor for these heavy losses. The aim of this study was to investigate the change in epidemic risk perception, risk attitude, and the consumers' willingness to consume products from restaurants during the spread of the COVID-19 epidemic. The study collected 502 questionnaires at the end of 2021, and structural analysis was conducted using SPSS 26.0 and AMOS 20.0 statistical programs. The results showed that consumers' awareness of the coronavirus pandemic (consumers' epidemic risk perception) had a significant positive effect on their decision-making behavior under uncertain conditions (risk attitude);consumers' decision-making behavior under uncertain conditions (risk attitude) had a significant negative effect on their willingness to purchase from restaurants;consumers' awareness of the coronavirus pandemic (consumers' epidemic risk perception) had a significant negative effect on their willingness to consume products from restaurants;and risk attitude played a mediating role in the influence of consumers' epidemic risk perception on their willingness to consume products from restaurants. This study can provide guidance and reference for restaurants on how to deal with the epidemic situation, help them undertake risk prevention work and reduce losses, and promote the healthy and sustainable development of the restaurant.

Pretreatment Methods for Human Nasopharyngeal Swabs to Increase the Signal to Noise Ratio of High Sensitivity Immunoassays.

Mucous samples collected through nasopharyngeal (NP) swabs are considered gold standard specimens for the detection of respiratory pathogens. Matrices of these highly viscous samples often cause significant background noises in immunoassays, especially immunoassays with high sensitivity. We demonstrated such nonspecific background signals in both a chemiluminescence enzyme-linked immunosorbent assay (ELISA) and a novel highly sensitive immunoassay called Microbubbling SARS-CoV-2 Antigen Assay (MSAA). We developed and demonstrated the effectiveness of two quick sample pretreatment methods, filtration and preadsorption, to decrease nonspecific signals and increase the signal-to-noise ratio (SNR). Using these pretreatment methods, the SNR (at 3.6 × 104 copies/mL of inactivated SARS-CoV-2) was increased by 42.4-fold (95% CI 41.0-43.8) and 67.1-fold (95% CI 57.9-76.3) in the MSAA, and 1.3-fold (95% CI 0.9-1.7) and 1.8-fold (95% CI 1.6-2.0) in the chemiluminescence ELISA assay. Sample pretreatment methods developed in this study are broadly adaptable for the development of immunoassays for highly viscous samples.

Reciprocal Effect between Depressive Symptoms and Adolescent Non-suicidal self-injury before and after COVID-19: A Longitudinal Study (preprint)

Background Non-suicidal   self-injury (NSSI) is a common psychological and behavioral problem among   adolescents and has now become a major public health problem for adolescents.   Since the COVID-19 outbreak in 2019, it has caused various mental health   problems, such as anxiety, depression, and mental burnout, contributing to a   severe mental health crisis globally. Thus far, a few studies recorded the   temporal change in adolescents’ psychological status during the COVID-19   pandemic as well as that with the implementation of large-scale public health   intervention methods, and this study adds to the evidence. Methods Based on   the Chengdu Positive Child Development (CPCD) survey, the baseline dataset   was collected in December 2019, and the first follow-up of the CPCD was conducted   in July 2020. A total of 6,023 adolescents aged 10-19 were recruited from   five primary and middle schools. Two independent autoregressive cross-lagged   models were used to test the bidirectional relationship between NSSI and   depressive symptoms in adolescents; logistic regression analysis was used to   explore the predictors of NSSI implementation in adolescents with depressive   symptoms, which could provide an entry point for behavioral interventions to   NSSI. Results The   prevalence of depressive symptoms among our participants was 32.69% at   baseline, and 34.27% at follow-up. The occurrence rate of NSSI in adolescents   who may have depressive symptoms was 44.34%%, and that during the pandemic   was 53.44%. The difference was statistically significant (P <   0.05). The results of the binary logistic analysis showed that among   adolescents, gender, duration of the online class, depression mood, place of   residence, and self-perception of relationship with caregivers were the risk   factors for NSSI (or > 1, β> 0), and daily sleep hours positive mood   was the protective factor (or < 1, β< 0).  The lag effect of adolescent depression on   their NSSI behavior is significant, which means that based on controlling the   adolescent baseline NSSI, the deeper the adolescent depression degree, the   more frequent their NSSI behavior (β=0.26, P<0.01). At the same time,   adolescents' NSSI behavior also had a lagging effect on depressive symptoms,   and adolescents with self-injury behavior were more likely to be depressed (β=0.02, P<0.01). Depression and   NSSI are mutual(β=0.77,   P<0.05；β=0.27,   P<0.01). Conclusions The   increased depressive symptoms among adolescents exacerbated their NSSI   behaviors and hurt their mental health during COVID-19. Screening for   depression should be carried out early to serve as a warning sign in   preventing and reducing NSSI in adolescents.

Parameters Sensitivity Analysis of COVID-19 Based on the SCEIR Prediction Model

At the end of 2019, COVID-19 outbreaks occurred one after another in countries worldwide. Managing the outbreak efficiently and stably is an essential public health issue facing countries worldwide. In this paper, based on the SEIR model, we propose a SCEIR model that incorporates close contacts (C) and self-protectors (P). Firstly, the epidemic data of China, the USA, and Italy are predicted and compared with the actual data. Secondly, sensitivity analysis of each parameter in the SCEIR model was conducted using Anylogic. The study shows that the SCEIR model established in this paper has a certain validity. The infection rate in contact with E (𝛽) etc., has positive effects on the basic regeneration number (R0);the self-isolation rate (phi) etc., has a negative effect on the basic regeneration number (R0). Emergency management measures are proposed according to the influencing factors corresponding to the model parameters. These can provide theoretical guidance for developing effective epidemic prevention and control measures in areas where the epidemic has not yet been controlled. It also provides some reference for formulating prevention and control policies for similar epidemics that may occur in the future.

Variational deep embedding-based active learning for the diagnosis of pneumonia.

Machine learning works similar to the way humans train their brains. In general, previous experiences prepared the brain by firing specific nerve cells in the brain and increasing the weight of the links between them. Machine learning also completes the classification task by constantly changing the weights in the model through training on the training set. It can conduct a much more significant amount of training and achieve higher recognition accuracy in specific fields than the human brain. In this paper, we proposed an active learning framework called variational deep embedding-based active learning (VaDEAL) as a human-centric computing method to improve the accuracy of diagnosing pneumonia. Because active learning (AL) realizes label-efficient learning by labeling the most valuable queries, we propose a new AL strategy that incorporates clustering to improve the sampling quality. Our framework consists of a VaDE module, a task learner, and a sampling calculator. First, the VaDE performs unsupervised reduction and clustering of dimension over the entire data set. The end-to-end task learner obtains the embedding representations of the VaDE-processed sample while training the target classifier of the model. The sampling calculator will calculate the representativeness of the samples by VaDE, the uncertainty of the samples through task learning, and ensure the overall diversity of the samples by calculating the similarity constraints between the current and previous samples. With our novel design, the combination of uncertainty, representativeness, and diversity scores allows us to select the most informative samples for labeling, thus improving overall performance. With extensive experiments and evaluations performed on a large dataset, we demonstrate that our proposed method is superior to the state-of-the-art methods and has the highest accuracy in the diagnosis of pneumonia.

Ångstrom-scale silver particles potently combat SARS-CoV-2 infection by suppressing the ACE2 expression and inflammatory responses.

The SARS-CoV-2 pandemic has become a severe global public health event, and the development of protective and therapeutic strategies is urgently needed. Downregulation of angiotensin converting enzyme 2 (ACE2; one of the important SARS-CoV-2 entry receptors) and aberrant inflammatory responses (cytokine storm) are the main targets to inhibit and control COVID-19 invasion. Silver nanomaterials have well-known pharmaceutical properties, including antiviral, antibacterial, and anticancer properties. Here, based on a self-established metal evaporation-condensation-size graded collection system, smaller silver particles reaching the Ångstrom scale (AgÅPs) were fabricated and coated with fructose to obtain a stabilized AgÅP solution (F-AgÅPs). F-AgÅPs potently inactivated SARS-CoV-2 and prevented viral infection. Considering the application of anti-SARS-CoV-2, a sterilized F-AgÅP solution was produced via spray formulation. In our model, the F-AgÅP spray downregulated ACE2 expression and attenuated proinflammatory factors. Moreover, F-AgÅPs were found to be rapidly eliminated to avoid respiratory and systemic toxicity in this study as well as our previous studies. This work presents a safe and potent anti-SARS-CoV-2 agent using an F-AgÅP spray.

Boosting the Photothermal Conversion Efficiency of MXene Film by Porous Wood for Light-driven Soft Actuators

Ti3C2Tx (a typical MXene) has been widely used in light-driven actuators due to its outstanding photothermal conversion capability. However, the response speed of these actuators is always slow because the effective irradiated area is limited to their surface. Herein, we propose a wood-based composite material which is made by coating Ti3C2Tx on delignified wood (DW). The high porosity of DW leads to high loading of Ti3C2Tx and provides large irradiated areas, thus enhancing photothermal conversion efficiency. The delignification on wood can expose cellulose with highly hydrophilic surface for rapid diffusion of Ti3C2Tx suspension, and the hydroxy in cellulose can act as binding sites to form stable combination with Ti3C2Tx. Taking advantage of the good compressibility of DW, a simple densification is conducted on TDW (Ti3C2Tx/DW) to greatly shorten the distance between adjacent oxygen-enriched Ti3C2Tx nanosheets, enhancing the conjugation among nanosheets, thus endowing TDW with good flexibility and high heat transfer efficiency. Moreover, we manufacture a light-driven bilayer actuator comprised of TDW as the passive layer and low-density polyethylene (LDPE) as the active layer. Our light-driven actuator exhibits a tremendous angle variation of 160° at a light intensity of 120 mW/cm2. A series of devices based on the TDW/LDPE actuator are demonstrated, including simulated gestures, a four-finger soft gripper, and a bionic flower. Moreover, we propose a light-controlled smart switch which can be used on non-contact (COVID-19) or dangerous (blasting) occasions. Additionally, we present a finite element simulation to predict the bending deformation, which guides the accurate control of the devices.

A Comprehensive Review of Artificial Intelligence in Prevention and Treatment of COVID-19 Pandemic.

The unprecedented outbreak of the Corona Virus Disease 2019 (COVID-19) pandemic has seriously affected numerous countries in the world from various aspects such as education, economy, social security, public health, etc. Most governments have made great efforts to control the spread of COVID-19, e.g., locking down hard-hit cities and advocating masks for the population. However, some countries and regions have relatively poor medical conditions in terms of insufficient medical equipment, hospital capacity overload, personnel shortage, and other problems, resulting in the large-scale spread of the epidemic. With the unique advantages of Artificial Intelligence (AI), it plays an extremely important role in medical imaging, clinical data, drug development, epidemic prediction, and telemedicine. Therefore, AI is a powerful tool that can help humans solve complex problems, especially in the fight against COVID-19. This study aims to analyze past research results and interpret the role of Artificial Intelligence in the prevention and treatment of COVID-19 from five aspects. In this paper, we also discuss the future development directions in different fields and prove the validity of the models through experiments, which will help researchers develop more efficient models to control the spread of COVID-19.

The initial attempt at home hemodialysis in mainland China (preprint)

Background Observational studies showed home hemodialysis (HHD) to be associated with better survival than facility hemodialysis (HD) and peritoneal dialysis (PD). Patients on HHD have reported higher quality of life and independence. HHD is considered to be an economical way to manage end-stage kidney disease (ESKD). The coronavirus disease 2019 pandemic has had a significant impact on patients with ESKD. Patients on HHD may have an advantage over in-center HHD patients because of a lower risk of exposure to infection.Participants and Methods: We enrolled hemodialysis patients from our dialysis center. We estabilished HHD training center at first. The training center was approved by Chinese government. Doctors, nurses and engineers train and assess patients separately. There are three forms of patient monitoring: home visit, internet remote monitoring, and out-patient service. Demographic and medical data included age, gender, blood pressure, dialysis related data. Laboratory tests were conducted in our central testing laboratory including hemoglobin (Hgb), serum creatinine (Cr), urea nitrogen (BUN), uric acid (UA), albumin (Alb), calcium (Ca), phosphorus (P), parathyroid hormone (PTH), brain natriuretic peptide (BNP).Results Six patients who underwent regular dialysis in the hemodialysis center of our hospital were selected for HHD training. We enrolled 6 patients, including 4 males and 2 females. The mean age of the patients was 47.5 (34.7–55.7) years, the mean dialysis age was 33.5 (11.2–41.5) months. After an average of 16.0 (11.2–25.5) months of training, Alb, P and BNP were improved compared with baseline values. After training, three patients returned home to begin independent hemodialysis. During the follow-up, there are no serious adverse events leading to hospitalization or death, but there are several adverse events. They have been solved quickly by extra home visits of the technicians or online by remote monitoring. During the time, laboratory indicators of all the patients including Hgb, Alb, Ca, P, PTH, BNP, β2-MG remained stable before and after HHD treatment.Conclusion HHD is feasible and safe for ESRD in China, but larger-scale and longer-term studies are needed to further confirm.

Effects of temperature, humidity, and air saturation state on the transmission risk prediction of COVID-19 in typical scenarios (preprint)

Environmental parameters have a significant impact on the spread of respiratory viral diseases. Temperature and relative humidity are correlated with viral inactivation in the air, whereas supersaturated air can promote viral deposition in the respiratory tract. This study introduces a new concept, the dynamic virus deposition ratio (α), that reflects the dynamic changes in particle size and viral deposition under varying ambient environments. Moreover, a non-steady-state modified Wells-Riley model is established to predict the infection risk of shared air space under varying environmental parameters, including temperature, relative humidity, and air saturation state. The quanta emission rate of an asymptomatic infector during different respiratory activities (breath, voice, and cough) are explored, and the differences in the infection risk under saturated and unsaturated air conditions are also compared. Finally, six typical exposure scenarios from daily life are also explored, highlighting scenarios of higher risk. The results show that the highest infection risk (R max =5.2%) and the longest risk duration (T terminal =6.8h) are both reached in cold and damp conditions. This study quantitatively reflects how environmental parameters are linked to viral inactivation and particle deposition, affecting transmission risk.

Digital Technology, Knowledge Level, and Food Safety Governance: Implications for National Healthcare System.

Exploring the intrinsic relationship between digital technology and the efficiency of food safety supervision contributes to a better understanding of the role of digital technology in food safety supervision and how to maximize its influence. This study employed sample data from 31 regions in China between 2015 and 2017 for an empirical analysis of the correlation between the two and to examine the moderating effects of the knowledge levels of food producers and consumers. The results show that the development of digital technology contributes to enhancing the efficiency of food safety supervision. In this process, the higher the knowledge level of consumers, the greater the positive promotional effect of digital technology. On the contrary, when the knowledge level of producers is higher, it is not conducive to enhancing the effect of digital technology on the efficiency of food safety supervision. The author holds the view that this is related to the fact that employees in the food production and manufacturing industry have insufficient moral and legal knowledge. This not only limits the effect of digital technology on enhancing the efficiency of food safety supervision, but also opens the door to illegal production for some unprincipled producers. The policy implications are that digital technology should be used to improve food safety supervision, the moral and legal knowledge of food producers should be improved, and consumers should be encouraged to use digital technology more in the pursuit of food safety. Implications for national healthcare system would be also discussed in our paper.

The influencing factors of psychological carrying capacity of tourists in outdoor scenic areas in the context of COVID-19 - empirical study based on a visual behavior experiment

As COVID-19 mainly transmits through close contact, people tend to avoid crowded places when travelling. The psychological carrying capacity from tourists' perspective in outdoor scenic areas changes accordingly. However, tourism carrying capacity has been refined overtime to fit the changing situations in the context of COVID-19 without considering the psychological dimension. The Chinese government has required social distancing and mask wearing in crowded areas to control COVID-19 transmission at the individual level, which may change the psychological carrying capacity from tourists' perspective. Moreover, tourism risk perception and tourism motivation under the pandemic also leads to the change of psychological carrying capacity. What is the impact of self-protections, tourism risk perception and tourism motivation on the psychological carrying capacity in outdoor scenic areas? Therefore, based on the normative theory, with crowding norms as the indicator of psychological carrying capacity, this study focuses on the influence of social distance, mask wearing, tourism risk perception and tourism motivation on psychological carrying capacity of tourists in outdoor scenic areas. Since the visual method has been widely used to measure psychological carrying capacity with pictures as the substitutes of real scenes, the study takes the simulation pictures of outdoor scenic spots as the visual materials and carry out a visual behavior experiment. The experiment adopts a 6(in-group: social distance of 0 m/0.5 m-1 m/1 m-1.2 m/1.5 m-2 m/3 m-4.5 m/5 m-10 m)..2(between group: wearing/without a mask) two-factor mixed design. The results show that:(1) social distance and mask wearing both have significant main effect and interaction effect on crowding norms.(2) When wearing a mask, the psychological carrying capacity is the"safe distance"of 1 m-1.2 m, consistent with the current space carrying capacity of outdoor scenic areas and the safe social distance standard. When without a mask, the psychological carrying capacity is the"medium distance"of 1.5 m-2 m, which is significantly lower than the current space carrying capacity of outdoor scenic areas.(3) EFA discovers tourism risk perception includes three factors, namely "risk of infection", "individual realistic pressure", and "tourism environment pressure", and tourism motivation includes "released from the pandemic", "regaining sense of autonomy", and "enjoying life". Regression analysis finds that "risk of infection" has a significant negative impact on crowding norms, and"released from the pandemic"has a significant positive impact on crowding norms. The study integrated the COVID-19 prevention standards about self-protections closely related to outdoor activities with the psychological carrying capacity of outdoor scenic areas, and analyzed the influence mechanism of psychological carrying capacity, thus providing a theoretical basis for tourism carrying capacity management practices in the context of COVID-19.

Erratum: Noncontact magnetically controlled capsule endoscopy for infection-free gastric examination during the COVID-19 pandemic: a pilot, open-label, randomized trial.

[This corrects the article DOI: 10.1055/a-1648-2238.].

All-in-One Metal-Oxide Heterojunction Artificial Synapses for Visual Sensory and Neuromorphic Computing Systems

An all-in-one artificial synapse integrating central nervous and sensory nervous functions utilizing low-dimensional metal-oxide heterojunction is demonstrated in this work. With an ion-electrolyte gate, synaptic emulations modulated by electrical and photonic stimulus have been integrated into one high-performance three-terminal artificial synapse. Various long-term and short-term synaptic plasticity functions have been achieved by altering the electrolyte-gate stimulus amplitude/width/frequency/number. The linear potentiation behavior and maintained states enable artificial synapses for neuromorphic computing. Simulated artificial neural network based on the artificial synapses achieved Covid-19 chest image recognition (>85%). The photo-sensing metal-oxide heterojunction enables the synaptic functions mimicking the biological visual sensory functions responding to optical and UV stimulus. Photonic synaptic plasticity modulations responding to photonic stimulus wavelength/power/width/number are investigated, and short-term/long-term synaptic plasticity transition was achieved. Dual-mode modulation combining photonic stimulus and gate stimulus was examined, along with a ‘AND Gate’ demonstration with electrical and photonic inputs. Finally, an artificial neural network was demonstrated based on the synapses with dual-mode synaptic weight modulation, indicating the potential of the artificial synapse for compact artificial intelligence systems combing neuromorphic computing and visual sensory nervous functions.