Tea Culture Tourism Perception: A Study on the Harmony of Importance and Performance

Tea culture tourism is a product of the combination of agricultural tourism and ecotourism. After the COVID-19 period, this product is more and more popular. Tourism performance is an important index for measuring the development level of tourist destinations, and research on the influencing factors of tourism performance is an important way to promote the high-quality development of tea culture tourism. Using the tea tourism town of Wushan as a case study, 452 valid questionnaires were used as research data, and exploratory factor analysis, paired sample t-test and IPA analysis were applied. The results indicate that: (1) tourism performance is mainly divided into 5 dimensions and 22 specific indicators, including service quality, resource environment, tourism transportation, tourism-supporting facilities and tea tourism products;(2) there is a significant difference between the degree of importance and performance of visitors to each indicator, and the overall tourism performance of the case sites at an average level;(3) convenient service, professional service, business management, park traffic, parking conditions, environmental design, shopping environment, tea quality, and tea culture characteristics are potential advantageous factors, and 'service with a smile', accessibility, trail layout, overall image, air quality, natural scenery, landscape vignettes, network communication, public toilets, sanitation facilities, tourist service centers, tea travel activities, and tourism souvenirs are areas in need of improvement.

A simple in-host model for COVID-19 with treatments: model prediction and calibration.

In this paper, we provide a simple ODEs model with a generic nonlinear incidence rate function and incorporate two treatments, blocking the virus binding and inhibiting the virus replication to investigate the impact of calibration on model predictions for the SARS-CoV-2 infection dynamics. We derive conditions of the infection eradication for the long-term dynamics using the basic reproduction number, and complement the characterization of the dynamics at short-time using the resilience and reactivity of the virus-free equilibrium are considered to inform on the average time of recovery and sensitivity to perturbations in the initial virus free stage. Then, we calibrate the treatment model to clinical datasets for viral load in mild and severe cases and immune cells in severe cases. Based on the analysis, the model calibrated to these different datasets predicts distinct scenarios: eradication with a non reactive virus-free equilibrium, eradication with a reactive virus-free equilibrium, and failure of infection eradication. Moreover, severe cases generate richer dynamics and different outcomes with the same treatment. Calibration to different datasets can lead to diverse model predictions, but combining long- and short-term dynamics indicators allows the categorization of model predictions and determination of infection severity.

Heat inactivation decreases the qualitative real-time RT-PCR detection rates of clinical samples with high cycle threshold values in COVID-19.

SARS-CoV-2 has caused COVID-19 pandemic globally in the beginning of 2020, and qualitative real-time RT-PCR has become the gold standard in diagnosis. As SARSCoV-2 with strong transmissibility and pathogenicity, it has become a professional consensus that clinical samples from suspected patients should be heat inactivated at 56°C for 30 min before further processing. However, previous studies on the effect of inactivation on qualitative real-time RT-PCR were conducted with diluted samples rather than clinical samples. The aim of this study was to investigate whether heat inactivation on clinical samples before detection will affect the accuracy of qualitative real-time RT-PCR detection. All 46 throat swab samples from 46 confirmed inpatients were detected by qualitative real-time RT-PCR directly, as well as after heat inactivation. Heat-Inactivation has significantly influenced the qualitative detection results on clinical samples, especially weakly positive samples. The results indicate the urgency to establish a more suitable protocol for COVID-19 clinical sample's inactivation.