Study on Dynamic Change of Land Usage in Hongta District Based on Sentinel-2

This work utilizes Sentinel-2A L1C remote sensing photographs from the years 2018, 2020, and 2022 to identify the different land use categories in the study area using the support vector machine (SVM) technique. The accuracy of categorization is greater than 90%. This research explores four factors of the dynamic change in land use in Hongta District from 2018 to 2022: the proportion of various types of land;the extent of something like the changing land usage;land use transfer;and the dynamic degree of the change in land use. According to the study's results, the proportion of cultivated and grassland land grew, while the quantity of barren and construction land fell by 1.90 percent, 0.03 percent, and 0.69 percent, respectively. The water system land portion of total area increased by 2.58 percent and 0.13 percent, respectively. After comparing the two research periods, the entire dynamic degree of the second stage is determined to be 3.5 percent lower than that of the first stage, and the pace of land use change is quite sluggish, which may be associated with the worldwide COVID-19 outbreak in 2020. The outcomes of the research may give the natural resources department the knowledge it needs to manage land resources properly. © 2023 SPIE.

Encountering pandas and their valleys in precarious times: A tourism assemblage perspective

This paper analyses the precarity of tourism in viral pandemic times through an analysis of animal-human relations in China's panda and valley tourism at Dajiuzhai. Drawing on a tour to Dajiuzhai to see giant pandas and the valleys of Jiuzhai, which was disrupted midway by increased viral infections, we trace ethnographically how disruptions in tourism emerge in the micro-setting of a single viral-hit tour and highlight the roles of natural agents, pandas, valleys and virus play, alongside humans in tourism's fluid assemblages. Desire/wish to encounter pandas motivated the formation of a fluid constellation of tourism objects, species and humans, which was aligned towards the goal of a stable tourism experience but persistently disturbed. Animal-human relation-based tourism assemblage at Dajiuzhai was found to be a fluid spatiality that coped with Covid-19 disruptions through responses at attractions involving health checks and declarations but remained precarious despite its transformational potentialities. © The Author(s) 2023.

Dynamic change detection in topics based on rolling LDAs

Topic modeling methods such as e.g. Latent Dirichlet Allocation (LDA) are popular techniques to analyze large text corpora. With huge amounts of textual data that are collected over time in various fields of applied research, it becomes also relevant to be able to automatically monitor the evolution of topics identified from some sort of dynamic topic modeling approach. For this purpose, we propose a dynamic change detection method that relies on a rolling version of the classical LDA that allows for coherently modeled topics over time that are able to adapt to changing vocabulary. The changes are detected by assessing the intensity of word change in the LDA's topics over time in comparison to the expected intensity of word change under stable conditions using resampling techniques. We apply our method to topics obtained by applying the RollingLDA to Covid-19 related news data from CNN and illustrate that the detected changes in these topics are well interpretable. © 2021 Copyright for this paper by its authors

Mining intrinsic information of convalescent patients after suffering coronavirus disease 2019 in Wuhan.

OBJECTIVE: To summarize the potential characteristics of convalescent patients with coronavirus disease 2019 (COVID-19) in China based on emerging clinical tongue data and guide the treatment and recovery of COVID-19 patients from the perspective of Traditional Chinese Medicine tongue diagnosis. METHODS: In this study, we developed and validated radiomics-based and lab-based methods as a novel approach to provide individualized pretreatment evaluation by analyzing different features to mine the orderliness behind tongue data of convalescent patients. In addition, this study analyzed the tongue features of convalescent patients from clinical tongue qualitative values, including thick and thin, fur, peeling, fat and lean, tooth marks and cracked, and greasy and putrid fur. RESULTS: We included 2164 tongue images in total (34% from day 0, 35.4% from day 14 and 30.6% from day 28) from convalescent patients. The significance results are shown as follows. Firstly, as the recovery time prolongs, the L average values of tongue and coat decrease from 60.21 to 57.18 and from 60.06 to 57.03 respectively. Secondly, the decrease of abnormality rate of tongue coat, included greasy tongue fur, putrid fur, teeth-mark, thick-thin fur, are of significant statistical difference ( < 0.05). Thirdly, the average value of gray-level co-occurrence matrices increases from 0.173 to 0.194, the average value of entropy increases from 0.606 to 0.665, the average value of inverse difference normalized decrease from 0.981 to 0.979, and the average value of dissimilarity decrease from 0.1576 to 0.1828. The details of other radiomics features are describe in results section. CONCLUSIONS: Our experiment shows that patients in different recovery periods have a relationship with quantitative values of tongue images, including L color space of the tongue and coat radiomics features analysis. This relationship can help clinical doctors master the recovery and health of patients as soon as possible and improve their understanding of the potential mechanisms underlying the dynamic changes and mechanisms underlying COVID-19.

Clinical characteristics of COVID-19 patients with complications: implications for management.

BACKGROUND: A novel coronavirus disease 2019 (COVID-19) has caused outbreaks worldwide, and the number of cases is rapidly increasing through human-to-human transmission. Because of the greater transmission capacity and possible subsequent multi-organ damage caused by the virus, it is crucial to understand precisely and manage COVID-19 patients. However, the underlying differences in the clinical features of COVID-19 with and without comorbidities are not fully understood. AIM: The objective of this study was to identify the clinical features of COVID-19 patients with and without complications to guide treatment and predict the prognosis. METHOD: We collected the clinical characteristics of COVID-19 patients with and without different complications, including hypertension, cardiovascular disease and diabetes. Next, we performed a baseline comparison of each index and traced the dynamic changes in these factors during hospitalization to explore the potential associations. RESULT: A clinical index of differential expression was used for the regression to select top-ranking factors. The top-ranking clinical characteristics varied in each subgroup, such as indices of liver function, renal function and inflammatory markers. Among them, the indices of renal function were highly ranked in all subgroups and displayed significant differences during hospitalization. CONCLUSION: Organ functions of COVID-19 patients, particularly renal function, should be cautiously taken care of during management and might be a crucial factor for a poor prognosis of these patients with complications.

Dynamic Changes in the Immune Response Correlate with Disease Severity and Outcomes During Infection with SARS-CoV-2.

INTRODUCTION: The coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has rapidly spread throughout China and worldwide. Little is known about the dynamic changes in the patient immune responses to SARS-CoV-2 and how different responses are correlated with disease severity and outcomes. METHODS: Seventy-four patients with confirmed COVID-19 were enrolled in this prospective research. The demographic information, medical history, symptoms, signs and laboratory results were analyzed and compared between severe and non-severe patients. The leukocytes, lymphocyte subsets and inflammatory cytokines were longitudinally collected. RESULTS: Of the 74 patients included, 17 suffered from severe disease. The severe patients tended be older (65.29 ± 12.33 years vs. 45.37 ± 18.66 years) and had a greater degree of underlying disease (41.18% vs. 24.56%), lower baseline lymphocyte counts [0.64 (0.46-0.95) × 109 vs. 1.27 (0.95-1.70) × 109], higher neutrophil-lymphocyte ratios [NLRs; 3.76 (3.15-5.51) vs. 2.07 (1.48-2.93)] and lower baseline eosinophil counts [0 (0-0.01) × 109 vs. 0.03 (0.01-0.06) × 109] than those in non-severe patients. The baseline helper T (Th) cells (335.47 vs. 666.46/µl), suppressor T(Ts) cells (158 vs. 334/µl), B cells (95 vs. 210/µl) and natural killer (NK) cells (52 vs. 122/µl) were significantly decreased in severe cases compared to that in non-severe cases. In addition, the baseline neutrophils were positively correlated with the severity of COVID-19, and the baseline lymphocytes were negatively correlated with the severity of COVID-19. The dynamic change of T cells, Th cells and IFN-γ in the severe cases were parallel to the amelioration of the disease. CONCLUSIONS: Collectively, our study provides novel information on the kinetics of the immune responses in a cohort of COVID-19 patients with different disease severities. Furthermore, our study indicates that both innate and adaptive immune responses correlate with better clinical outcomes.

CT findings and dynamic imaging changes of COVID-19 in 2908 patients: a systematic review and meta-analysis.

Quick screening patients with COVID-19 is the most important way of controlling transmission by isolation and medical treatment. Chest computed tomography (CT) has been widely used during the initial screening process, including pneumonia diagnosis, severity assessment, and differential diagnosis of COVID-19. The course of COVID-19 changes rapidly. Serial CT imaging could observe the distribution, density, and range of lesions dynamically, monitor the changes, and then guide towards appropriate treatment. The aim of the review was to explore the chest CT findings and dynamic CT changes of COVID-19 using systematic evaluation methods, instructing the clinical imaging diagnosis. A systematic literature search was performed. The quality of included literature was evaluated with a quality assessment tool, followed by data extraction and meta-analysis. Homogeneity and publishing bias were analyzed. A total of 109 articles were included, involving 2908 adults with COVID-19. The lesions often occurred in bilateral lungs (74%) and were multifocal (77%) with subpleural distribution (81%). Lesions often showed ground-glass opacity (GGO) (68%), followed by GGO with consolidation (48%). The thickening of small vessels (70%) and thickening of intralobular septum (53%) were also common. The dynamic changes of chest CT manifestations showed that lesions were absorbed and improved gradually after reaching the peak (80%), had progressive deterioration (55%), were absorbed and improved gradually (46%), fluctuated (22%), or remained stable (26%). The review showed the common and key CT features and the dynamic imaging change patterns of COVID-19, helping with timely management during COVID-19 pandemic.

The Utility of Specific Antibodies Against SARS-CoV-2 in Laboratory Diagnosis.

The Coronavirus Disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has now become a global pandemic due to its high transmissibility. The unavoidable shortcomings of traditional diagnostic assay, including nucleic acid testing, diverse serological assays characterized by high-throughput and less workload, are playing a more and more crucial role to supplement the nucleic acid test. In this review, we summarize the dynamic change of the specific IgM, IgG, and IgA antibodies against SARS-CoV-2 as well as neutralizing antibodies and discuss the clinical utility and limitations of the different serological assays. SARS-CoV-2, a newly discovered virus, shows some unique pathogenetic and epidemiological characteristics that have not been completely understood so far. Currently, studies about the antibody responses against SARS-CoV-2 and the clinical utility of serological testing are increasing. It's well suggested that the combination of serological tests and nucleic acid tests can cohesively improve the testing efficiency for identifying COVID-19 suspected patients.

Lymphocyte subsets with the lowest decline at baseline and the slow lowest rise during recovery in COVID-19 critical illness patients with diabetes mellitus.

BACKGROUND: Host dysregulation of immune response was highly involved in the pathological process of Coronavirus disease 2019 (COVID-19), especially COVID-19 severe cases with DM. AIM: In this study we aimed at the dynamic change of peripheral lymphocyte and subsets during COVID-19 covery. METHODS: The peripheral lymphocyte and subsets of 95 confirmed cases with COVID-19 from baseline to four weeks were compared between critical illness and non-critical illness cases with or without DM. RESULTS: The dynamic characteristics of lymphocyte and subsets in COVID-19 patients was that it reduced significantly at one week, rapidly elevated to the peak at two weeks after onset, then gradually declined during recovery. The COVID-19 critical illness patients with DM had the lowest decline at one week and the slow lowest rise at two weeks after onset, while COVID-19 non-critical illness patients with DM had the rapid highest rise at two weeks after onset, both of them had similar lymphocyte and subsets at five weeks after onset and lower than those patients without DM. CONCLUSIONS: These findings provide a reference for clinicians that for COVID-19 patients with DM and the lowest decline of lymphocyte and subsets, immunomodulatory therapy as soon as possible might avoid or slow down disease progression; moreover for COVID-19 critical illness patients with or without DM and non-critical illness patients with DM, continuous immunomodulatory therapy in later stages of disease might speed up virus clearance, shorten hospital stay, improve disease prognosis in COVID-19 critical illness patients with DM.

Dynamic changes in clinical and CT characteristics of COVID-19 cases with different exposure histories: a retrospective study.

BACKGROUND: To assess the dynamic changes in clinical and CT characteristics of COVID-19 patients with different epidemiology histories. METHODS: Fifty-three discharged COVID-19 patients were enrolled at Beijing YouAn Hospital, Capital Medical University, between January 21 and March 10, 2020. Spearman correlation analysis was performed between CT scores and laboratory indicators. Patients were divided into the Wuhan group (lived in or with travel to Wuhan, numbering 30 cases) and non-Wuhan group (close contacts or unknown exposure, totaling 23 cases). The CT and laboratory findings were compared between and within groups during the clinical process. RESULTS: Fever (88.7%), cough (64.2%), fatigue (34%), and abnormal laboratory indicators, including lymphopenia, reduced albumin, albumin/globulin (A/G), and elevated C-reactive protein (CRP), were mainly observed. Subpleural ground-glass opacities (86.8%) were usually detected at admission. The CT scores were highly correlated with lymphocytes, CRP, albumin, and A/G at initial and follow-ups (all p < 0.05). Four days after admission, most patients (66.7% Wuhan, 47.8% non-Wuhan) showed progression, and the CT scores of Wuhan significantly increased (p = 0.015). Eight days after admission, the vast majority of patients (69.2% Wuhan, 100% non-Wuhan, p = 0.006) presented improvement, and the CT scores of non-Wuhan were significantly lower than Wuhan (p = 0.006). Pneumonia was completely absorbed in most patients 2-4 weeks after discharge. CONCLUSIONS: CT plays a crucial role in the early diagnosis and monitoring of changes in COVID-19. Lymphocytes, CRP, albumin, and A/G are expected to predict disease severity and prognosis. Viral pathogenicity in non-endemic areas may be weaker than core-infected areas. In most patients, lung lesions can disappear around 4 weeks after discharge.

Pattern of liver injury in adult patients with COVID-19: a retrospective analysis of 105 patients.

BACKGROUND: Recent studies reported that patients with coronavirus disease-2019 (COVID-19) might have liver injury. However, few data on the combined analysis and change patterns of alanine aminotransferase (ALT), aspartate aminotransferase (AST) and total bilirubin (TBil) have been shown. METHODS: This is a single-center retrospective study. A total of 105 adult patients hospitalized for confirmed COVID-19 in Beijing Ditan Hospital between January 12, and March 17, 2020 were included, and divided into mild group (n = 79) and severe group(n = 26). We compared liver functional test results between the two groups. Category of ALT change during the disease course was also examined. RESULTS: 56.2% (59/105) of the patients had unnormal ALT, AST, or total TBil throughout the course of the disease, but in 91.4% (96/105) cases the level of ALT, AST or TBil ≤3 fold of the upper limit of normal reference range (ULN). The overall distribution of ALT, AST, and TBil were all significantly difference between mild and severe group (P <  0.05). The percentage of the patients with elevated both ALT and AST was 12.7% (10/79) in mild cases vs. 46.2% (12/26) in severe cases (P = 0.001). 34.6% (9/26) severe group patients started to have abnormal ALT after admission, and 73.3% (77/105) of all patients had normal ALT before discharge. CONCLUSIONS: Elevated liver function index is very common in patients with COVID-19 infection, and the level were less than 3 × ULN, but most are reversible. The abnormality of 2 or more indexes is low in the patients with COVID-19, but it is more likely to occur in the severe group.

[Chest CT findings and their dynamic changes in patients with COVID-19].

ObjectiveTo define chest CT findings and their dynamic changes in patients with coronavirus disease 2019 (COVID-19) from disease onset to the cure.MethodWe analyzed the clinical and chest CT data of 6 patients with RT-PCR-confirmed COVID-19. According to the time from the disease onset to the cure or from the onset to each CT scan, the total of 30 chest CT scans were divided into 4 stages, namely stage 1 (0-4 days), stage 2 (5-9 days), stage 3 (10-14 days), and stage 4 (over 14 days). A semi-quantitative scoring system was used to quantitatively assess the pulmonary involvement on the basis of the involved area. The differences in chest CT signs and the lung injury scores based on CT findings were compared among the 4 stages.ResultsIn stage 1, ground-glass opacities (GGO) was found frequently in the subpleura, and the CT score was the lowest at 4.00±0.40. Stage 2 was characterized by an increased and mixed density (crazy-paving pattern) with mild consolidation of the lungs, and the CT score reached its peak level of 7.38±3.34 (P < 0.05). In stage 3, an expanded range of consolidation and linear lesions were found in the lungs, and the total CT score averaged 6.86±2.91. In stage 4, a gradual resolution of the consolidation occurred with more linear lesions in the lungs, and the total CT score was 6.21±1.56. The CT scores of the lower lobes were significantly higher compared with those of the middle/upper lobes (P < 0.05) in stage 3 and stage 4.ConclusionChest CT scans allows dynamic monitoring of the changes in the distribution, density and extent of the pulmonary lesions in the 4 stages, which are closely correlated with the evolution of the disease course of COVID-19.