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Objective: The current study aimed to describe the clinical characteristics of mild SARS-CoV-2 infected pregnant women with abnormal liver function (ALF), explore the association between ALF with maternal and fetal outcomes. Method(s): This retrospective analysis included 87 pregnant patients with mild SARS-CoV-2 infection admitted and treated from December 1, 2022, to 31, 2022 in the department of Obestircs at Beijing Obstetrics and Gynecology Hospital. We evaluated patients for demographic and clinical features, laboratory parameters and pregnancy complications. Result(s): 27 Patients in this cohort had clinical presentations of ALF. Compared with the control group, the peripheral blood platelet (PLT), D-dimer quantitative determination (D-Dimer), lactate dehydrogenase (LDH), total protein (TP), albumin (ALB), indirect bilirubin (DBIL), gamma- glutamyltranspeptidase (GGT) and total bile acid (TBA) showed significantly differences (p<0.05). 12 cases (44.44%) complicated with pregnancy induced hypertension (PIH), 14 cases (51.85%) complicated with intrahepatic cholestasis of pregnancy (ICP), 2 cases (7.4%) complicated with acute fatty liver during pregnancy (AFLP) and 5 cases (14.81%) complicated with postpartum hemorrhage in patients with abnormal LFT were significantly higher than those in the control group (p<0.05). Compared with the control group, the incidence of premature delivery (22.22%) and fetal distress (37.04%) in the experiment group were significantly higher (p<0.05), and the incidence of neonatal asphyxia was not significantly different (p>0.05). Conclusion(s): Pregnant women are generally susceptible to mild SARS-CoV-2 and may induce ALF. ALF is associated with increased risk of mother and infant. The maternal and infant outcomes of those who terminated pregnancy in time are acceptable. Therefore, pregnant women with COVID-19 who received antiviral treatment should be closely monitored for evaluating liver function and relevant indicators. The long-term outcomes in the future are worth to further study.Copyright © 2023
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In 2021, the airline industry was affected by COVID-19, and many airlines suffered losses. The main reason for the loss were the decline in revenue and the surge in costs. Therefore, in terms of creating the competitive advantage of airlines, "price war" is no longer applicable, and improving service quality has become an effective means. Customer satisfaction is the most effective indicator to measure service quality. In this study, a satisfaction evaluation system is established based on structural equation model and customer satisfaction importance matrix. Then, a questionnaire is designed to analyze the influence of different factors on customer satisfaction. The research finds that brand image and perceived quality have a great impact on customer satisfaction. In addition, some suggestions for airlines to improve customer satisfaction are given. © 2023 SPIE.
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Inclusive digital financial services should welcome older populations and make them beneficiaries of the digital and financial revolution. To understand older adults' experience of using digital financial tools, we conducted an online survey of 268 older internet users aged 60 or above from urban areas of 14 Chinese provinces after China's nationwide COVID-19 lockdown in 2021. Our results revealed that older internet surfers were active in digital financial activities and engaged most with activities that were highly compatible with their lifestyles. Active users significantly differed from inactive users in sociodemographics, confirming that a digital divide related to social stratification exists among older internet users. Digital finance active users were also distinguished from inactive users' attitudes and perceptions toward digital finance. Logistic regression results indicated that perceived usefulness, access to proper devices for digital finance, risk perceptions, and perceived exclusion if not using technology were associated with their adoption of these advanced tools. Older adults reported the perceived inconvenience of in-person financial services during the lockdown. They also expressed a willingness to participate in relevant training if provided. The findings of this study could help aging-related practitioners to understand older adults' engagement in digital finance and guide policy and project design in the area of financial inclusion of the aging population.
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Due to the COVID-19 pandemic, the international shipping market has been highly volatile, posing a serious threat to the survival and development of many maritime start-ups. With the development of the digital economy, digital transformation is affecting the evolution and upgrading of many traditional enterprises, including maritime enterprises. In the post-COVID-19 era, start-up small and medium-sized enterprises will need to consider the importance of enterprise risk management to achieve transformation and upgrading. The purpose of this study is to provide guidance for the establishment and upgrading of risk management systems for start-ups based on the identification of risk management strategies of maritime enterprises and the evaluation of their performance. The fuzzy analytic hierarchy process and importance-performance analysis methods were used to rank the operational risk, financial risk, market risk, innovation risk, and disaster risk according to sub-items and screen out the risk management schemes for priority improvements. Through empirical research, it was found that the financial risk and market risk response schemes have the lowest performance and need to be prioritised for improvement. This study argues that start-ups can appropriately challenge their risk management strategies to meet potential risk management needs based on their own circumstances.
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Using climate-optimized flight trajectories is one essential measure to reduce aviation's climate impact. Detailed knowledge of temporal and spatial climate sensitivity for aviation emissions in the atmosphere is required to realize such a climate mitigation measure. The algorithmic Climate Change Functions (aCCFs) represent the basis for such purposes. This paper presents the first version of the Algorithmic Climate Change Function submodel (ACCF 1.0) within the European Centre HAMburg general circulation model (ECHAM) and Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) model framework. In the ACCF 1.0, we implement a set of aCCFs (version 1.0) to estimate the average temperature response over 20 years (ATR20) resulting from aviation CO2 emissions and non-CO2 impacts, such as NOx emissions (via ozone production and methane destruction), water vapour emissions, and contrail cirrus. While the aCCF concept has been introduced in previous research, here, we publish a consistent set of aCCF formulas in terms of fuel scenario, metric, and efficacy for the first time. In particular, this paper elaborates on contrail aCCF development, which has not been published before. ACCF 1.0 uses the simulated atmospheric conditions at the emission location as input to calculate the ATR20 per unit of fuel burned, per NOx emitted, or per flown kilometre.In this research, we perform quality checks of the ACCF 1.0 outputs in two aspects. Firstly, we compare climatological values calculated by ACCF 1.0 to previous studies. The comparison confirms that in the Northern Hemisphere between 150–300 hPa altitude (flight corridor), the vertical and latitudinal structure of NOx-induced ozone and H2O effects are well represented by the ACCF model output. The NOx-induced methane effects increase towards lower altitudes and higher latitudes, which behaves differently from the existing literature. For contrail cirrus, the climatological pattern of the ACCF model output corresponds with the literature, except that contrail-cirrus aCCF generates values at low altitudes near polar regions, which is caused by the conditions set up for contrail formation. Secondly, we evaluate the reduction of NOx-induced ozone effects through trajectory optimization, employing the tagging chemistry approach (contribution approach to tag species according to their emission categories and to inherit these tags to other species during the subsequent chemical reactions). The simulation results show that climate-optimized trajectories reduce the radiative forcing contribution from aviation NOx-induced ozone compared to cost-optimized trajectories. Finally, we couple the ACCF 1.0 to the air traffic simulation submodel AirTraf version 2.0 and demonstrate the variability of the flight trajectories when the efficacy of individual effects is considered. Based on the 1 d simulation results of a subset of European flights, the total ATR20 of the climate-optimized flights is significantly lower (roughly 50 % less) than that of the cost-optimized flights, with the most considerable contribution from contrail cirrus. The CO2 contribution observed in this study is low compared with the non-CO2 effects, which requires further diagnosis.
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Delivery of self-amplifying mRNA (SAM) has high potential for infectious disease vaccination due to its self-adjuvanting and dose-sparing properties. Yet a challenge is the susceptibility of SAM to degradation and the need for SAM to reach the cytosol fully intact to enable self-amplification. Lipid nanoparticles are successfully deployed at incredible speed for mRNA vaccination, but aspects such as cold storage, manufacturing, efficiency of delivery, and the therapeutic window can benefit from further improvement. To investigate alternatives to lipid nanoparticles, a class of >200 biodegradable end-capped lipophilic poly(beta-amino ester)s (PBAEs) that enable efficient delivery of SAM in vitro and in vivo as assessed by measuring expression of SAM encoding reporter proteins is developed. The ability of these polymers to deliver SAM intramuscularly in mice is evaluated, and a polymer-based formulation that yields up to 37-fold higher intramuscular (IM) expression of SAM compared to injected naked SAM is identified. Using the same nanoparticle formulation to deliver a SAM encoding rabies virus glycoprotein, the vaccine elicits superior immunogenicity compared to naked SAM delivery, leading to seroconversion in mice at low RNA injection doses. These biodegradable nanomaterials may be useful in the development of next-generation RNA vaccines for infectious diseases.Copyright © 2023 The Authors. Advanced Therapeutics published by Wiley-VCH GmbH.
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Objective: Semaglutide is the first glucagon-like peptide- 1 receptor agonist with oral and subcutaneous formulations. We studied patient adherence and clinical response following their prescription in a primary care setting. Method(s): We searched for patients starting semaglutide between October 2020 to November 2021 in primary care registries in Dudley, West Midlands. We tracked their collection of medications for up to six months, changes in HbA1C and weight if these data were available at 26 weeks (range 22-52 weeks), with significance tested using a t-test. Patients prescribed both formulations were excluded. Result(s): Clinical data were available in 180 of the 443 patients. Baseline HbA1c was 79.0 +/- 18.6mmol/mol (Ozempic) and 81.9 +/- 19.3mmol/mol (Rybelsus) and pre-treatment weight was 108.4 +/- 10.5 kg (Ozempic) and 104.3 +/- 26.7 kg (Rybelsus). 62.8% of patients were of non-white ethnicity and 82.8% were on >= two anti-diabetic drugs. In patients with six-month follow-up data, mean reduction in HbA1c and weight was 17.1 +/- 20.8mmol/ mol and 3.9 +/- 6.2 kg (Ozempic n = 53, p < 0.01) and 18.2 +/- 14.5mmol/mol and 5.9 +/- 4.2 kg (Rybelsus n = 5, p < 0.05). Drug continuation rates were measured in 324 patients. 3.2% and 19.0% of patients for Ozempic and Rybelsus respectively did not obtain further prescriptions after their initial script. At six months, 87.2% continued with Ozempic and 57.2% with Rybelsus. Conclusion(s): This study demonstrates similarly significant reductions in HbA1c and weight with Ozempic and Rybelsus, despite the complexity of follow-up during Covid-19 restrictions. The lower adherence to Rybelsus warrants further study.
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The COVID-19 pandemic has heightened the visibility of economic inequality and the inadequacy of current minimum wage laws in the United States. Changes in the minimum wage, a living wage, or just employment practices may be compelled by law or voluntarily enacted by employers. A literature search failed to yield a concise and practical tool to comprehensively assess existing just employment policies or practices in higher education institutions. This article describes the development of a concise and practical assessment based on the "Model Just Employment Policy" from the Kalmanovitz Initiative for Labor and the Working Poor at Georgetown University. The resulting Just Employment Policy Assessment is used to evaluate the publicly available policies of four disparate higher education institutions in the United States. The article concludes with a discussion of implications for future research and administrative practice.
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Container ports operate in more challenging and volatile environments at present times. Events such as US-China trade tensions and the COVID-19 pandemic severely affect numerous container ports at various levels. Strategies pursued by container ports are key to port development and management amidst these challenges. Drawing on configuration theory, this research employs Fuzzy-set Qualitative Comparative Analysis to investigate the relation between port strategies and container throughput. The research contributes to the literature by proposing an approach to account for complexity of the port sector and offers insights into strategies adopted by major container ports. The research further identifies 10 port strategies and proposed indicators that can represent the essence of these strategies. Being able to represent strategies in a quantitative format is important for strategy analysis and performance evaluation. Results reveal that major container ports employ a combination of strategies which address both the supply and demand-side aspects of the port business. Growing digitalization and digitization coupled with advancements in information capture, diagnostics capabilities and predictive abilities means a greater role for data analytics to influence container port strategy and performance. Implications for port managers, policy makers and researchers from the perspective of port policy and management are proposed.
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Background It is a challenge for pharmacy courses worldwide to combine theoretical knowledge with practical skills to equip students for their future practice. Computer-based simulation offers a way of building a bridge between theory and practice. In recent years, digital simulation has expanded rapidly as a new technique of virtual learning. The digital platform ''Pharmacy Simulator'' proposes computer-based encounters with virtual patients to train clinical and communication skills in a community pharmacy setting. However, during the COVID-19 pandemic, while students were digitally resilient and endured the endless challenges of online lectures, many were dealing with Zoom and screen fatigue. Purpose To investigate pharmacy students' acceptance of Pharmacy Simulator before and during a pandemic situation. This focuses on students' self-assessment and confidence in counselling after playing the scenarios on Pharmacy Simulator. Method Two cohorts of Master of Pharmacy students at The University of Western Australia played two scenarios on Pharmacy Simulator in 2019 (anaphylaxis and salbutamol) and 2021 (anaphylaxis and vaccination). A mixed-method analysis was performed with data from (i) qualitative semi-structured interviews carried out in 2019 pertaining to participants' acceptance of Pharmacy Simulator and in 2021 (ii) a questionnaire with 25 items derived from the interviews. The interviews were transcribed verbatim into electronic format with the data management assistance MAXQDA and analyzed inductively using the Framework Method. Questionnaire responses were analyzed in Microsoft Excel using descriptive statistics. Openended questions were evaluated inductively. Findings Data were collected from 20 interviews and 31 answered questionnaires. In 2019, participants reported that Pharmacy Simulator was a fun, engaging, and straightforward learning tool and, therefore, user-friendly. They reported the feedback at the end of the session to be most valuable. The platform was perceived to fill the gap between the theory from lectures and community pharmacy practice. In 2021, participants ''agreed'' (median: 4, on a 5-point Likert scale) with seven statements about Pharmacy Simulator's usability, such as it being a helpful tool for acquiring new knowledge. Participants' confidence in counselling regarding the scenario topics improved. One participant stated, ''It taught me more through trial and error''. Conclusion Pharmacy students reported similar acceptance levels of Pharmacy Simulator before and during the COVID-19 pandemic. The use of simulation during virtual patient encounters seems to facilitate the transfer from theory to practice, independently of learning conditions that were predominantly screen-based.
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Objective To investigate the impact of dynamic adaptive teaching model on surgical education. Methods Due to the COVID-19 pandemic in 2020, we adopted dynamic adaptive teaching model in the Department of Breast Surgery, Peking Union Medical College Hospital, which divided the whole curriculum into several individual modules and recombined different modules to accommodate to student's levels and schedules. Meanwhile, adaptive strategy also increased the proportion of online teaching and fully utilized electronic medical resources. The present study included quantitative teaching score (QTS) recorded from January 2020 to June 2020, and used the corresponding data from 2019 as control. The main endpoint was to explore the impact of dynamic adaptive teaching model on overall QTS and its interaction effect with trainer's experience and student category. Results Totally, 20 trainers and 181 trainees were enrolled in the present study. With implementation of dynamic adaptive strategy, the overall QTS decreased dramatically (1.76+/-0.84 vs. 4.91+/-1.15, t=4.85, P=0.005). The impact was consistent irrespective of trainers' experience (high experience trainers: 0.85+/-0.40 vs. 2.12+/-0.44, t=4.98, P=0.004;medium experience trainers: 0.85+/-0.29 vs. 2.06+/-0.53, t=4.51, P=0.006;and low experience trainers: 0.10+/-0.16 vs. 0.44+/-0.22, t=2.62, P=0.047). For resident (including graduate) and undergraduate student teaching, both QTS was lower with dynamic strategy (residents: 0.18+/-0.34 vs. 0.97+/-0.14, t=4.35, P=0.007;undergraduate students 1.57+/-0.55 vs. 3.77+/-1.24, t=3.62, P=0.015), but dynamic strategy was effective for post-doc student subgroup and reached comparable QTS as traditional model (0.00+/-0.00 vs. 0.17+/-0.41, t=1.00, P=0.363). Conclusions Dynamic adaptive teaching strategy could be a useful alternative to traditional teaching model for post-doc students. It could be a novel effective solution for saving teaching resources and providing individualized surgical teaching modality.Copyright © 2023, Peking Union Medical College Hospital. All rights reserved.
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This paper presents a control system for indoor safety measures using a Faster R-CNN (Region-based Convolutional Neural Network) architecture. The proposed system aims to ensure the safety of occupants in indoor environments by detecting and recognizing potential safety hazards in real time, such as capacity control, social distancing, or mask use. Using deep learning techniques, the system detects these situations to be controlled, notifying the person in charge of the company if any of these are violated. The proposed system was tested in a real teaching environment at Rey Juan Carlos University, using Raspberry Pi 4 as a hardware platform together with an Intel Neural Stick board and a pair of PiCamera RGB (Red Green Blue) cameras to capture images of the environment and a Faster R-CNN architecture to detect and classify objects within the images. To evaluate the performance of the system, a dataset of indoor images was collected and annotated for object detection and classification. The system was trained using this dataset, and its performance was evaluated based on precision, recall, and F1 score. The results show that the proposed system achieved a high level of accuracy in detecting and classifying potential safety hazards in indoor environments. The proposed system includes an efficiently implemented software infrastructure to be launched on a low-cost hardware platform, which is affordable for any company, regardless of size or revenue, and it has the potential to be integrated into existing safety systems in indoor environments such as hospitals, warehouses, and factories, to provide real-time monitoring and alerts for safety hazards. Future work will focus on enhancing the system's robustness and scalability to larger indoor environments with more complex safety hazards.
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Clerkship on primary care and family medicine is multi-elemental and was very challenging during the COVID-19 pandemic. Some medical students postponed their graduation because the clerkship at the health center could not be carried out in a pandemic situation. This article aims to describe the community medicine clerkship (CMC) module and its implementation amidst the COVID-19 pandemic. This module was delivered by online and offline activities from 10th August to 13th September 2020. A total of forty students, twelve faculty mentors, and fifteen Primary Health Care (PHC) preceptors from ten PHCs in the Tangerang District, Indonesia were involved. Students could carry out activities and fulfil assignments given in the midst of a pandemic with a re-designing of the CMC module. The one-sample t-tests were employed to compare the difference between the study values and the values before the COVID-19 pandemic. The study showed that the scores of students participating in CMC module during the COVID-19 pandemic were significantly different from the scores before the pandemic in terms of both individual and group scores. The findings of the study clearly indicated that all clinical clerkship modules must be redesigned to suit the current conditions. Modifications and variations of various learning methods, guidance techniques, monitoring and coordination are all factors that must be considered in implementing changes to these modules. © 2023 Dwi Tyastuti, Risahmawati Risahmawati, Marita Fadhillah, Fika Ekayanti, Sity Kunarisasia & Ahmad A. Habibi.
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Education officials have long hoped that the statewide academic assessments most students take each year could be used not only for accountability but also to guide instruction. Congress established the Innovative Assessment Demonstration Authority (IADA) program in 2015 to help address this goal, offering up to seven states temporary flexibility from federal testing requirements so that they may more easily make progress toward replacing their current assessments with more innovative ones. The key incentive to participate in IADA is that students trying out the innovative assessment are not required to also take the state's current assessment. However, states approved for IADA must still show that their innovative assessments meet most requirements for federal accountability, and they are expected to implement the new assessments statewide within 5 years. This report describes the progress of the first five assessment systems approved under IADA in order to help policymakers consider expanding the program to more states. The report is primarily based on an analysis of states' IADA applications and performance reports to the U.S. Department of Education through the 2020-2021 school year and is part of a broader evaluation of IADA required by Congress. [For the Appendix, see ED627873. For the Study Highlights, see ED627880.]
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Objectives: Acne is a leading skin problem in adolescents. After the end of COVID-19 pandemic, with the gradual transition to the routine life, we started to encounter more severe forms of acne in the last 6-month than we had seen before in the 10 year period of our Paediatric Dermatology outpatient clinic. Method(s): We evaluated the demographic and clinical characteristics, COVID infection and vaccination status, and treatment of patients who were treated at our Paediatric Dermatology outpatient clinic in the last 6 months due to severe acne. Result(s): One of our patients had acne fulminans, and four patients had acne conglobata. The common features of these patients presenting with severe acne were that they were young boys aged 15- 16 years, medium height, normal weight, and skin type 3-4. All patients had a family history of acne in their parents. They had no known comorbidities, additional treatment, history of nutritional supplement use, or accompanying arthralgia or arthritis. Four patients were initially treated with isotretinoin for severe acne, developed acne conglobata, and one developed acne fulminans during the follow-up period. Dapsone therapy was initiated in all patients according to the severity of the lesions, and adalimumab was administered to acne fulminans. Discussion(s): The frequent occurrence of severe forms of acne after the pandemic raises the question of whether COVID-19 infection or vaccination may play a role in its aetiology. Cases of mask-related acne exacerbation during COVID-19 have been well-described in the literature. However, there are no data on the effects of COVID-19 vaccination or infection on the development of severe acne. In this report, we present cases of adolescent patients with severe acne to investigate the possible reasons for the increasing number of severe acne cases presenting to our outpatient clinic during the postpandemic period.
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Purpose: The aim of this study was to evaluate how prevalent asymptomatic SARS-CoV-2 virus infection (COVID-19) is among patients undergoing ophthalmic surgery at two tertiary referral hospitals. Material(s) and Method(s): This retrospective study included patients without COVID-19 symptoms who underwent preoperative screening using reverse transcription-polymerase chain reaction (RT-PCR) before ophthalmic surgery at the Kocaeli University and Gaziantep University departments of ophthalmology [between September 1, 2020, and December 15, 2020 (group 1);between March 1, 2021, and May 30, 2021 (group 2)]. Patients scheduled for surgery and followed up in the retina, glaucoma, pediatric ophthalmology and strabismus, cataract and refractive surgery, and cornea departments were examined. Result(s): RT-PCR was positive for SARS-CoV-2 in 12 (1.4%) of 840 patients in group 1 and 7 (1.1%) out of 600 patients in group 2. None of the patients were symptomatic of COVID-19. The majority of the patients were scheduled for retina or cataract and refractive surgery in both groups (group 1;retina: 29.2%, cataract and refractive: 57.0%, group-2;retina: 31.3%, cataract and refractive: 54.5%). SARS-CoV-2 RT-PCR testing was positive for seven patients in group 1 (7/245, 2.9%) and five patients in group 2 (5/188, 2.6%) who were scheduled for retinal surgery. Conclusion(s): The necessity, availability, and practicality of COVID-19 RT-PCR testing prior to ophthalmic surgeries varies depending on the protocols of each institution. COVID-19 RT-PCR testing is suggested especially before vitreoretinal surgeries and general anesthesia procedures, because of the difficulty in managing postoperative complications.Copyright © 2023 Gazi Eye Foundation. All rights reserved.
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In this work we investigate the effectiveness of two train-the-trainer workshops on intelligent industrial robotics. The two workshops, which took place in summer 2021 in Tennessee and Alabama, were the first of a series of six workshops. A total of 32 persons applied to the two summer workshops from 10 states, of whom 15 attended and successfully completed the workshops. Evaluation results show that the participants' knowledge on industrial robotics significantly improved after the workshops, and the vast majority indicated that the training will be used in their home institutions. The major challenge faced during the workshops was the spread of the delta variant of CoVid-19 at the time the workshops were scheduled to take place, and the wide diversity of the educational background of participants. © 2023 IEEE.
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The outbreak of COVID-19 makes people feel distant from each other, and masks have become one of the indispensable articles in People's Daily life. At present, there are many brands of masks with various types and uneven quality. In order to understand the current market of masks and the sales of different brands, users can choose masks with perfect quality. This paper uses Python web crawler technology, based on the input of the word "mask", crawl JD website sales data, through data visualization technology drawing histogram, pie chart, the word cloud, etc., for goods compared with the relationship between price, average price of all brands, brands, average distribution of analysis and evaluation of user information, In this way, the sales situation, price distribution and quality evaluation of each store of the product can be visually displayed. At the same time, it also provides some reference for other users who need to buy the product. © The Authors. Published under a Creative Commons Attribution CC-BY 3.0 License.
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Background/Objectives: Chemosensory dysfunction is a hallmark of SARS-CoV-2 infection;nevertheless, the genetic factors predisposing to long-term smell and taste loss are still unknown. This study aims to identify candidate genes possibly involved in persistent smell/taste loss through Whole Genome Sequencing (WGS) analysis of a large cohort of 130 fully characterised Italian individuals, previously diagnosed with COVID-19. Method(s): DNA of all analysed patients was used to perform WGS analysis, and a detailed personal anamnesis was collected. Moreover, orthonasal function was assessed through the extended Sniffin' Sticks test, retronasal function was tested with 20 powdered tasteless aromas, and taste was determined with validated Taste Strips. Self-reported smell and taste alterations were assessed via Visual Analog Scales plus questionnaires. Result(s): The clinical evaluation allowed to classify the patients in two groups: 88 cases affected by persistent smell dysfunction (median age, 49) and 42 controls (median age, 51). Among cases, 26.1% (n = 23) were functionally anosmic and 73.9% (n = 65) were hyposmic. Within cases, 77 underwent the taste strip test: 53.2% (n = 41) presented hypogeusia and 46.8% (n = 36) were normogeusic. Preliminary WGS results on a first subset of 76 samples confirmed the important role of UGT2A1 gene, previously described as involved in smell loss. Interestingly, we identified a nonsense variant (rs111696697, MAF 0.046) significantly associated with anosmia in males (p-value: 0.0183). Conclusion(s): Here, for the first time a large cohort of patients, fully characterised through a comprehensive psychophysical evaluation of smell and taste, have been analysed to better define the genetic bases of COVID-19-related persistent chemosensory dysfunction.