Time to transform the way we travel?: A conceptual framework for slow tourism and travel research

Slow food movement gave rise to subsequent movements including Cittáslow and slow tourism. This emphasises a steady state mindful approach to travel and consumption patterns. With consideration for pressing issues like overtourism, mass tourism and the onslaught of the COVID-19 pandemic, it is pertinent to discuss viable alternatives to a fast-paced life and travel that we consider normal. One such alternative is slow tourism that accentuates sustainable tourism practices as well as tourism at a reduced pace. It endorses mindfulness in travelling and discovering destinations in a responsible manner. Furthermore, slow travel aims to promote tourists' consumption-oriented enjoyment of experience through slow-paced and low carbon emission travel patterns. An in-depth scientometric review coupled with a critical qualitative review highlights the state-of-the-art of slow tourism and travel research, offers an integrative multilevel and multistage framework, and proposes future research avenues drawing on the gaps within the slow tourism and travel research. © 2023 The Authors

The personalized recommendation for OTA flight cancellation and change services during the pandemic

The COVID-19 pandemic has had a dramatic impact on people’s travels. Due to the recurrent pandemic and regionally different policies in China, travelers must pay a lot for flight cancellations and changes. To accommodate this, online travel agencies (OTA) can provide a more flexible ancillary as a supplement to the airline company's services. Here, we introduced the upgraded all-in-one (AIO) service package, which offers compensation for flight delays, changes, or refund. We also designed a dynamic recommendation engine (DRE), which can make real-time personalized recommendations. Backed by AB testing, the machine learning-based DRE not only raises the package attach rate without interrupting the flight ordering process, but also helps the customers cut cost when making flight cancellations or changes.

An Improved Fireworks Algorithm for Integrated Flight Timetable and Crew Schedule Recovery Problem

Abnormal flights, which deviate from their scheduled plans, incurred huge costs for airlines and serious inconvenience for passengers. This phenomenon occurs frequently, especially under the influence of COVID-19 and requires high-quality solution within short time limits. To mitigate these negative effects, first, an integrated flight timetable and crew schedule recovery model with the aim of minimizing total cost is constructed in this paper. Second, an improved fireworks algorithm is proposed to effectively solve the model. Finally, an unscheduled temporary aircraft maintenance scenario is obtained to illustrate the superiority of the proposed algorithm in terms of computing time and solution quality. © 2022, Springer Nature Switzerland AG.

Clinical Course and Factors Associated with Viral RNA Shedding and Radiologic Resolution in Patients with COVID-19: a Retrospective Study

Background: The outbreak of SARS-CoV-2 lead to a worldwide pandemic which poses substantial challenges to public health. Methods: We enrolled 102 consecutive recovered patients with laboratory-confirmed SARS-CoV-2 infection. Epidemiological and demographic characteristics, temporal dynamic profiles of laboratory tests and findings on chest CT radiography, and clinical outcomes were collected and analyzed. Results: Independent risk factors for prolonged fever, viral RNA shedding or radiologic recovery included age of more than 44 years, female gender, having symptoms of cough and fever, a delay from the symptom onset to hospitalization of more than 3 days, a lower CD4 count of less than 500/mu L on admission, and severe or critical illness in hospitalization. The estimated median time from symptom onset was 6.4 (5.5 -7.4) days to peak viral load, 9.1 (7.9 -10.4) days to afebrile, 8 (6.7 -9.4) days to worst radiologic finding, 12.7 (11.2 -14.3) days to viral RNA negativity, and 26.7 (23.8 -29.9) days to radiologic resolution. This study included the entire cross-section of patients seen in our clinical practice and reflected the real-world situation. Conclusions: These findings provide the rationale for strategies of active symptom monitoring, timing of quarantine and antiviral interventions, and duration of radiologic follow-up in patients with COVID-19.

Particle Aerosolization during Tracheostomy Procedure as Modeled by Computational Fluid Dynamics

Introduction SARS-CoV-2 has created a hazardous environment for healthcare workers, with some of the riskiest procedures being those that generate aerosolized particles, such as tracheostomy surgery. Tracheostomy is both particle aerosolizing and extremely common, particularly for patients in respiratory distress. We utilized computational fluid dynamics (CFD) to model aerosolized particle spread during tracheostomy to deduce the viral loading risks posed to surgeons and anesthesiologists by aerosolized viruses. Additionally, we studied how these risks change with varying tracheal incision sizes. MethodsAn intubated subject's CT scan was virtually modified to replicate the tracheostomy procedure. An anatomically accurate trachea, thorax, incision, and operating room were created. Airflow simulations were performed to reproduce the exhalation occurring with removal of the intubation tube and opening of the airway to room pressure. Particles were released into the trachea from the primary bronchi, which then escaped into open air via the tracheal incision. Three tracheal incision sizes were modeled. Four particle sizes were released (0.2μ m-20μ m). Airflow was modeled for 20 seconds. ResultsFor small, medium, and large incisions, 68.7%, 68.4%, and 68.5% of particles by mass remained in the trachea, respectively (68.5% average of the three) (Figure1). Average size of escaped particles was 5.31μ m, 5.27μ m, and 5.29μ m for the small, medium, and large incisions respectively, while average particle size remaining in the trachea was 14.0μ m, 14.66μ m, 14.29μ m.From 4 to 8 seconds after initial particle release, the average particle size falling to the level of the patient's forehead increased from 11.6μ m to 18.4μ m. Large particles (10μ -20μ m) fell quickly, while smaller particles (0.2μ m to 2μ m) were more likely to remain suspended in air after 20 seconds. ConclusionsCFD particle aerosolization modeling of tracheostomy procedures can predict the viral loads healthcare workers are exposed to for the purpose of implementing proper safety precautions. These results highlight the extended residence times of aerosols in the absence of room ventilation which should ordinarily clear suspended particles, as well as the importance of considering smaller particles when designing personal protective equipment (PPE) for hospital staff. Large particles fall due to gravity relatively quickly, meaning the largest viral loads are airborne immediately after exhalation. Tracheal incision size was insignificant to the amount of aerosol generated during tracheostomy. In the absence of proper room ventilation, particles remained suspended in highest concentration directly above the patient's forehead, not directly above the tracheal incision. This implies physicians in this relative danger zone, such as anesthesiologists, need additional safety precautions.

"Five-early" model: The magic weapon against covid-19

Background: COVID-19(2019 novel coronavirus disease)has brought tremendous pressure to the prevention and control of the national epidemic due to its concealed onset, strong infectivity and fast transmission speed. Methods: In this retrospective study, 226 patients diagnosed with 2019 novel coronavirus pneumonia (NCP) in the Chongqing University Three Gorges Hospital were included. The patients' clinical data, including general information, initial symptoms at the onset, time of disease diagnosis, time to treatment in hospital, time of nucleic acid conversion to negative, disease classification, total time of hospitalization were collected. The clinical data of the mild and severe patients were compared. Results: Fever, cough, sore throat, poor appetite andfatigue were the main symptoms of the diagnosed patients. The time of diagnosis was significantly shorter in the mild patients (4.96 ± 4.10 days) than severe patients (7.63 ± 9.17 days) (P=0.004). Mild patients had shorter time to treatment in hospital (6.09 ± 4.47 vs. 8.71 ± 9.04 days) and less time of nucleic acid conversion to negative (7.58 ± 2.51 vs. 11.6 ± 4.67 days) compared to the severe patients. Conclusion: The above results can be used as a quantitative basis for the “five-early"(early detection, early screening, early diagnosis, early isolation treatment, and early recovery) model. The government, the masses, and the hospitals' joint prevention and optimization of the "five-early" model will provide important scientific reference for further prevention and control of the epidemics. © 2020, Iranian Journal of Public Health. All rights reserved.