ANALYSIS OF TWITTER USER COVID-19 VACCINE HESITANCY: CAUSE AND SOLUTIONS

Reducing vaccine hesitancy is an essential public health & safety challenge worldwide, especially during the COVID - 19 pandemic. Governments and health safety agencies have noticed that social media can significantly influence people\u27s sentiments and opinions about vaccinations. There is a lack of studies on the impact of social norms, herding effects, and social media influencers on people\u27s sentiments and opinions about vaccinations. This culminating experience project extracted and analyzed Twitter data (2021 to 2022) using Twitter API and the RStudio AcdemicTwitterR package to study the impact of social norms, herding effects, and social media influencers on people\u27s sentiments, emotions, and opinions about COVID - 19 vaccinations. Methods used to fulfil the data analysis are natural language processing algorithm - sentiment analysis, and social network analysis algorithms. The top three main questions for this study are (1) What caused Twitter COVID-19 vaccine-related keywords trends and sentiment to change over time, (2) How do social media influencers on Twitter impact other users’ sentiment on COVID-19 vaccine-related topics, and (3) Do herding behaviors exist and how does it affect media users’ sentiments and opinions about the COVID-19 vaccine. The results for the main questions showed that (1) Twitter keyword trends change and fluctuate with COVID-19 vaccine-related news and events; (2) Social media influencers use their unique influence and the information dissemination pattern of the topic community to influence other users on vaccine-related opinions; (3) The python subjectivity test shows herding behaviors exist in negative polarity topic communities and significantly change COVID-19 vaccine sentiment.egative polarity topic communities and significantly change other users’ COVID-19 vaccine emotion. Social media platform like Twitter is a double-edged sword. It could cause more vaccine hesitancy if public health agencies do not pay enough attention. However, if public health agencies could utilize Twitter properly, it would be a potent weapon that can significantly reduce vaccine hesitancy. It is recommended that public health agencies (1) utilize social media influencers to promote reliable information sources and official information to users, (2) use social norms-based messages to warn users, and (3) invite health professionals to social media to help dispel misinformation with their influence. Areas for further study include factors that caused vaccine hesitancy, such as political, cultural, ethnicity, and social aspects by state, county, and city

Linear hypothesis testing for high dimensional generalized linear models

This paper is concerned with testing linear hypotheses in high dimensional generalized linear models. To deal with linear hypotheses, we first propose the constrained partial regularization method and study its statistical properties. We further introduce an algorithm for solving regularization problems with folded-concave penalty functions and linear constraints. To test linear hypotheses, we propose a partial penalized likelihood ratio test, a partial penalized score test and a partial penalized Wald test. We show that the limiting null distributions of these three test statistics are χ2 distribution with the same degrees of freedom, and under local alternatives, they asymptotically follow noncentral χ2 distributions with the same degrees of freedom and noncentral parameter, provided the number of parameters involved in the test hypothesis grows to ∞ at a certain rate. Simulation studies are conducted to examine the finite sample performance of the proposed tests. Empirical analysis of a real data example is used to illustrate the proposed testing procedures

An Experimental Study on the Establishment of Pulmonary Hypertension Model in Rats induced by Monocrotaline

Pulmonary hypertension is called PH for short. It is caused by the pulmonary artery vascular disease leading to pulmonary vascular resistance, and the increase right lung compartment load, which resulting in weakening or even collapse of the right ventricular function. The establishment of rat PH model under the action of monocrotaline is a repeatable, simple and accessible operation technique, which has been widely used in the treatment of pulmonary hypertension. This paper discusses the principle and properties of the PH model on rats under the monocrotaline action

Comparison of variations detection between whole-genome amplification methods used in single-cell resequencing

Background: Single-cell resequencing (SCRS) provides many biomedical advances in variations detection at the single-cell level, but it currently relies on whole genome amplification (WGA). Three methods are commonly used for WGA: multiple displacement amplification (MDA), degenerate-oligonucleotide-primed PCR (DOP-PCR) and multiple annealing and looping-based amplification cycles (MALBAC). However, a comprehensive comparison of variations detection performance between these WGA methods has not yet been performed. Results: We systematically compared the advantages and disadvantages of different WGA methods, focusing particularly on variations detection. Low-coverage whole-genome sequencing revealed that DOP-PCR had the highest duplication ratio, but an even read distribution and the best reproducibility and accuracy for detection of copy-number variations (CNVs). However, MDA had significantly higher genome recovery sensitivity (~84 %) than DOP-PCR (~6 %) and MALBAC (~52 %) at high sequencing depth. MALBAC and MDA had comparable single-nucleotide variations detection efficiency, false-positive ratio, and allele drop-out ratio. We further demonstrated that SCRS data amplified by either MDA or MALBAC from a gastric cancer cell line could accurately detect gastric cancer CNVs with comparable sensitivity and specificity, including amplifications of 12p11.22 (KRAS) and 9p24.1 (JAK2, CD274, and PDCD1LG2). Conclusions: Our findings provide a comprehensive comparison of variations detection performance using SCRS amplified by different WGA methods. It will guide researchers to determine which WGA method is best suited to individual experimental needs at single-cell level

Clinical factors and major pathological response after neoadjuvant chemoimmunotherapy in potentially resectable lung squamous cell carcinoma

ObjectiveMajor pathological response (MPR) helps evaluate the prognosis of patients with lung squamous cell carcinoma (LUSC). However, the clinical factors that affect the achievement of MPR after neoadjuvant chemoimmunotherapy (NCIO) in patients with LUSC remain unclear. This study aimed to explore the clinical factors affecting the MPR after NCIO in patients with potentially resectable LUSC.MethodsThis retrospective study included patients with stage IIB-IIIC LUSC who underwent surgical resection after receiving NCIO at a center between March 2020 and November 2022. In addition to the postoperative pathological remission rate, sex, age, body mass index (BMI), smoking history, TNM stage, hematological and imaging test results, and other indicators were examined before NCIO. According to the pathological response rate of the surgically removed tumor tissue, the patients were split into MPR and non-MPR groups.ResultsIn total, 91 LUSC patients who met the study’s eligibility criteria were enrolled: 32 (35%) patients in the non-MPR group and 59 (65%) in the MPR group, which included 43 cases of pathological complete remission (pCR). Pre-treatment lymphocyte level (LY) (odds ratio [OR] =5.997), tumor burden (OR=0.958), N classification (OR=15.915), radiographic response (OR=11.590), pulmonary atelectasis (OR=5.413), and PD-L1 expression (OR=1.028) were independently associated with MPR (all P < 0.05). Based on these six independent predictors, we developed a nomogram model of prediction having an area under the curve (AUC) of 0.914 that is simple to apply clinically to predict the MPR. The MPR group showed greater disease-free survival (DFS) than the non-MPR group, according to the survival analysis (P < 0.001).ConclusionThe MPR rate of NCIO for potentially resectable LUSC was 65%. LY, tumor burden, N classification, radiographic response, pulmonary atelectasis, and PD-L1 expression in patients with LUSC before NCIO were the independent and ideal predictors of MPR. The developed nomogram demonstrated a good degree of accuracy and resilience in predicting the MPR following NCIO, indicating that it is a useful tool for assuring customized therapy for patients with possibly resectable LUSC

Phycocyanin: Anti-inflammatory effect and mechanism

As the host defense response to various injuries and pathogens in the body, inflammation can remove damaged cells and pathogens in the host organism and protect the body. However, excessive inflammation may cause damage to normal tissue cells while removing pathogens, which in turn cause numerous inflammatory diseases and adversely affect the human health. Phycocyanin is an active substance extracted from algae; it has outstanding antioxidant and anti-inflammatory activities, and can effectively inhibit various diseases caused by inflammation. This review systematically summarizes recent applications of phycocyanin against various inflammatory diseases in lung, liver, cardiovascular, and cerebrovascular systems. In addition, possible antiinflammatory action pathways of phycocyanin are reviewed to canvass the anti-inflammatory mechanism. At last, based on the existing research, phycocyanobilin in phycocyanin is proposed as a bilirubin analog by inducing heme oxygenase 1 in vivo to suppress inflammation

Heterogeneous cellular automata subway station personnel evacuation model based on cooperative behavior

In order to study the influence of cooperative behavior in the evacuation process of subway station personnel, and considering the heterogeneity of evacuees, the heterogeneous cellular automata method is adopted to establish a human evacuation model of subway station under cooperative behavior based on the floor field model. In the research process, the evacuated persons are divided into two types, which are seeking cooperation and accepting cooperation. Then, the effects of different cooperative behavior probability ratios of seeking cooperative personnel on evacuation efficiency, evacuation process, and evacuation bottleneck are analyzed through simulation. The result shows that cooperative behavior can effectively improve evacuation efficiency of the subway station, but it is limited by cooperative probability and the proportion of people seeking cooperation; Cooperative behavior plays a role in the whole evacuation process, which is mainly reflected in the later stage of evacuation and will promote the gathering of evacuees. The higher the probability of cooperation, the shorter the evacuation bottleneck formation time, the duration, and overall evacuation time, which will help improve the emergency safety of subway stations

Analysis of the Influence of Foggy Weather Environment on the Detection Effect of Machine Vision Obstacles

This study is to analyze the influence of visibility in a foggy weather environment on the accuracy of machine vision obstacle detection in assisted driving. We present a foggy day imaging model and analyze the image characteristics, then we set up the faster region convolutional neural network (Faster R-CNN) as the basic network for target detection in the simulation experiment and use Karlsruhe Institute of Technology and Toyota Technological Institute (KITTI) data for network detection and classification training. PreScan software is used to build weather and traffic scenes based on a foggy imaging model, and we study object detection of machine vision in four types of weather condition—clear (no fog), light fog, medium fog, and heavy fog—by simulation experiment. The experimental results show that the detection recall is 91.55%, 85.21%, 72.54~64.79%, and 57.75% respectively in no fog, light fog, medium fog, and heavy fog environments. Then we used real scenes in medium fog and heavy fog environment to verify the simulation experiment. Through this study, we can determine the influence of bad weather on the detection results of machine vision, and hence we can improve the safety of assisted driving through further research

Heterogeneous cellular automata subway station personnel evacuation model based on cooperative behavior

In order to study the influence of cooperative behavior in the evacuation process of subway station personnel, and considering the heterogeneity of evacuees, the heterogeneous cellular automata method is adopted to establish a human evacuation model of subway station under cooperative behavior based on the floor field model. In the research process, the evacuated persons are divided into two types, which are seeking cooperation and accepting cooperation. Then, the effects of different cooperative behavior probability ratios of seeking cooperative personnel on evacuation efficiency, evacuation process, and evacuation bottleneck are analyzed through simulation. The result shows that cooperative behavior can effectively improve evacuation efficiency of the subway station, but it is limited by cooperative probability and the proportion of people seeking cooperation; Cooperative behavior plays a role in the whole evacuation process, which is mainly reflected in the later stage of evacuation and will promote the gathering of evacuees. The higher the probability of cooperation, the shorter the evacuation bottleneck formation time, the duration, and overall evacuation time, which will help improve the emergency safety of subway stations