In this paper, compositions of nanodomains in a commercial high-impact polypropylene (HIPP) were investigated by an atomic force microscopy-infrared (AFM-IR) technique. An AFM-IR quantitative ...analysis method was established for the first time, which was then employed to analyze the polyethylene content in the nanoscopic domains of the rubber particles dispersed in the polypropylene matrix. It was found that the polyethylene content in the matrix was close to zero and was high in the rubbery intermediate layers, both as expected. However, the major component of the rigid cores of the rubber particles was found to be polypropylene rather than polyethylene, contrary to what was previously believed. The finding provides new insight into the complicated structure of HIPPs, and the AFM-IR quantitative method reported here offers a useful tool for assessing compositions of nanoscopic domains in complex polymeric systems.
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IJS, KILJ, NUK, PNG, UL, UM
The influence of molecular weight on the polymorphic behavior of polybutene-1 (PB-1) in cold crystallization from PB-1/iPP (isotactic polypropylene) blend has been investigated. Twelve PB-1/iPP blend ...samples of 90/10 (w/w) composition were prepared from three PB-1s and four iPPs with molecular weight of 77–711 kg/mol and 12–580 kg/mol, respectively, and their cold crystallization was studied by Fourier transform infrared spectroscopy, wide-angle X-ray diffraction and differential scanning calorimetry. The relatively small amount of iPP in the blend can facilitate form I′ crystallization and suppress form II formation of the PB-1, and it was found that by decreasing the molecular weight of either PB-1 or iPP, especially the latter, the content of form I′ crystals can be increased significantly. In PB-1 blends with iPP of the lowest molecular weight of 12 kg/mol, 90–95% of the crystalline PB-1 obtained was form I′. The observed molecular weight effects on the PB-1 polymorphism in the cold crystallization are attributed to miscibility between the PB-1 and iPP components in the molten state, and a size-constrained nucleation mechanism is discussed.
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•Effects of molecular weight on PB-1 cold crystallization from PB-1/iPP blends are investigated.•Lower molecular weights of PB-1 and iPP favor form I′ formation.•The molecular weight effects are attributed to miscibility of the two components.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
In this work, an anti-icing coating based on superhydrophilic polyzwitterion brushes is reported. Poly(sulfobetaine methacrylate) (PSBMA) brushes were synthesized by surface-initiated ...atom-transferred radical polymerization to create superhydrophilic films on silicon wafers. The thickness of the PSBMA brushes film increased linearly with the polymerization time, and the film remained superhydrophilic in a nonassociated state when the thickness was less than ∼100 nm. DSC and FTIR analyses revealed that PSBMA contains more nonfreezable bound water than typical polyelectrolytes such as poly(sodium styrenesulfonate) and poly(2-(methacryloyloxy)ethyltrimethylammonium chloride), leading to lower ice adhesion strength than the latter two. At −20 °C, the PSBMA brushes coating demonstrated low ice adhesion strength of 60 kPa, showing a significant reduction in ice adhesion by up to ∼75% compared to uncoated silicon wafer. The optimum PSBMA layer thickness for low ice adhesion was ∼100 nm. These findings suggest that polyzwitterions are excellent candidates for anti-icing coating application.
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During global pandemics, such as coronavirus disease 2019 (COVID-19), crisis communication is indispensable in dispelling fears, uncertainty, and unifying individuals worldwide in a collective fight ...against health threats. Inadequate crisis communication can bring dire personal and economic consequences. Mounting research shows that seemingly endless newsfeeds related to COVID-19 infection and death rates could considerably increase the risk of mental health problems. Unfortunately, media reports that include infodemics regarding the influence of COVID-19 on mental health may be a source of the adverse psychological effects on individuals. Owing partially to insufficient crisis communication practices, media and news organizations across the globe have played minimal roles in battling COVID-19 infodemics. Common refrains include raging QAnon conspiracies, a false and misleading "Chinese virus" narrative, and the use of disinfectants to "cure" COVID-19. With the potential to deteriorate mental health, infodemics fueled by a kaleidoscopic range of misinformation can be dangerous. Unfortunately, there is a shortage of research on how to improve crisis communication across media and news organization channels. This paper identifies ways that legacy media reports on COVID-19 and how social media-based infodemics can result in mental health concerns. This paper discusses possible crisis communication solutions that media and news organizations can adopt to mitigate the negative influences of COVID-19 related news on mental health. Emphasizing the need for global media entities to forge a fact-based, person-centered, and collaborative response to COVID-19 reporting, this paper encourages media resources to focus on the core issue of how to slow or stop COVID-19 transmission effectively.
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Network analysis is an effective approach for examining complex relationships between psychiatric symptoms. This study was designed to examine item-level relationships between depressive and anxiety ...symptoms using network analysis in an adolescent sample and identified the most central symptoms within the depressive-anxiety symptoms network model. Depressive and anxiety symptoms were assessed using the Patient Health Questionire-9 (PHQ-9) and Generalized Anxiety Disorder Screener (GAD-7), respectively. The structure of depressive and anxiety symptoms was characterized using "Strength" and "Bridge Strength" as centrality indices in the symptom network. Network stability was tested using a case-dropping bootstrap procedure. Finally, a Network Comparison Test (NCT) was conducted to examine whether network characteristics differed on the basis of gender, school grade and residence. Network analysis revealed that nodes PHQ2 ("Sad mood"), GAD6 ("Irritability"), GAD3 ("Worry too much"), and PHQ6 ("Guilty") were central symptoms in the network model of adolescents. Additionally, bridge symptoms linking anxiety and depressive symptoms in this sample were nodes PHQ6 ("Guilty"), PHQ2 ("Sad mood"), and PHQ9 ("Suicide ideation"). Gender, school grade and residence did not significantly affect the network structure. Central symptoms (e.g., Sad mood, Irritability, Worry too much, and Guilty) and key bridge symptoms (e.g., Guilty, Sad mood, and Suicide ideation) in the depressive and anxiety symptoms network may be useful as potential targets for intervention among adolescents who are at risk for or suffer from depressive and anxiety symptoms.
Mind the "Vaccine Fatigue" Su, Zhaohui; Cheshmehzangi, Ali; McDonnell, Dean ...
Frontiers in immunology,
03/2022, Volume:
13
Journal Article
Peer reviewed
Open access
Omicron scares and speculations are gaining momentum. Amid the nonstop debates and discussions about COVID-19 vaccines, the "vaccine fatigue" phenomenon may become more prevalent. However, to date, ...no research has systematically examined factors that shape people's vaccine fatigue. To bridge the research gap, this study aims to investigate the antecedents that cause or catalyze people's vaccine fatigue.
A narrative literature review was conducted in PubMed, Scopus, and PsycINFO to identify factors that shape people's vaccine fatigue. The search was completed on December 6, 2021, with a focus on scholarly literature published in English.
A total of 37 articles were reviewed and analyzed. Vaccine fatigue was most frequently discussed in the context of infectious diseases in general at the pre-vaccination stage. Vaccine fatigue has been identified in the general public, the parents, and the doctors. Overall, a wide range of antecedents to vaccine fatigue has been identified, ranging from the frequency of immunization demands, vaccine side effects, misconceptions about the severity of the diseases and the need for vaccination, to lack of trust in the government and the media.
Vaccine fatigue is people's inertia or inaction towards vaccine information or instruction due to perceived burden and burnout. Our study found that while some contributors to vaccine fatigue are rooted in limitations of vaccine sciences and therefore can hardly be avoided, effective and empathetic vaccine communications hold great promise in eliminating preventable vaccine fatigue across sectors in society.
In addition to worry, the accumulated unknowns and uncertainties about COVID-19 may also result in “worry fatigue” that could harm the public’s vigilance towards the pandemic and their adherence to ...preventive measures. Worry could be understood as future-oriented concerns and challenges that could result in negative outcomes, whereas worry fatigue is the feeling of extreme burden and burnout associated with too much worry unsolved. As the world embraces its second COVID-19 winter, along with the pandemic-compromised holiday season, the Omicron variant has been declared a variant of concern by the World Health Organization. However, the fluid and unpredictable nature of COVID-19 variants dictates that, instead of definitive answers that could ease people’s worry about Omicron, dividing debates and distracting discussions that could further exacerbate people’s worry fatigue might be the norm in the coming months. This means that, amid the ever-changing public health guidance, the forever-breaking news reports, and the always-debatable media analyses, government and health officials need to be more invested in addressing people’s potential worry and worry fatigue about the pandemic, to ensure the public’s rigorous cooperation and compliance with safety measures.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Abstract
Background
Pulmonary arterial hypertension (PAH) is a severe complication of systemic lupus erythematosus (SLE). This study aims to explore the clinical characteristics and prognosis in ...SLE-PAH based on consensus clustering and risk prediction model.
Methods
A total of 205 PAH (including 163 SLE-PAH and 42 idiopathic PAH) patients were enrolled retrospectively based on medical records at the First Affiliated Hospital of Zhengzhou University from July 2014 to June 2021. Unsupervised consensus clustering was used to identify SLE-PAH subtypes that best represent the data pattern. The Kaplan–Meier survival was analyzed in different subtypes. Besides, the least absolute shrinkage and selection operator combined with Cox proportional hazards regression model were performed to construct the SLE-PAH risk prediction model.
Results
Clustering analysis defined two subtypes, cluster 1 (
n
= 134) and cluster 2 (
n
= 29). Compared with cluster 1, SLE-PAH patients in cluster 2 had less favorable levels of poor cardiac, kidney, and coagulation function markers, with higher SLE disease activity, less frequency of PAH medications, and lower survival rate within 2 years (86.2% vs. 92.8%) (
P
< 0.05). The risk prediction model was also constructed, including older age at diagnosis (≥ 38 years), anti-dsDNA antibody, neuropsychiatric lupus, and platelet distribution width (PDW).
Conclusions
Consensus clustering identified two distinct SLE-PAH subtypes which were associated with survival outcomes. Four prognostic factors for death were discovered to construct the SLE-PAH risk prediction model.
With evidence-based measures, COVID-19 can be effectively controlled by advanced data analysis and prediction. However, while valuable insights are available, there is a shortage of robust and ...rigorous research on what factors shape COVID-19 transmissions at the city cluster level. Therefore, to bridge the research gap, we adopted a data-driven hierarchical modeling approach to identify the most influential factors in shaping COVID-19 transmissions across different Chinese cities and clusters. The data used in this study are from Chinese officials, and hierarchical modeling conclusions drawn from the analysis are systematic, multifaceted, and comprehensive. To further improve research rigor, the study utilizes SPSS, Python and RStudio to conduct multiple linear regression and polynomial best subset regression (PBSR) analysis for the hierarchical modeling. The regression model utilizes the magnitude of various relative factors in nine Chinese city clusters, including 45 cities at a different level of clusters, to examine these aspects from the city cluster scale, exploring the correlation between various factors of the cities. These initial 12 factors are comprised of 'Urban population ratio', 'Retail sales of consumer goods', 'Number of tourists', 'Tourism Income', 'Ratio of the elderly population (> 60 year old) in this city', 'population density', 'Mobility scale (move in/inbound) during the spring festival', 'Ratio of Population and Health facilities', 'Jobless rate (%)', 'The straight-line distance from original epicenter Wuhan to this city', 'urban per capita GDP', and 'the prevalence of the COVID-19'. The study's results provide rigorously-tested and evidence-based insights on most instrumental factors that shape COVID-19 transmissions across cities and regions in China. Overall, the study findings found that per capita GDP and population mobility rates were the most affected factors in the prevalence of COVID-19 in a city, which could inform health experts and government officials to design and develop evidence-based and effective public health policies that could curb the spread of the COVID-19 pandemic.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
In network theory depression is conceptualized as a complex network of individual symptoms that influence each other, and central symptoms in the network have the greatest impact on other symptoms. ...Clinical features of depression are largely determined by sociocultural context. No previous study examined the network structure of depressive symptoms in Hong Kong residents. The aim of this study was to characterize the depressive symptom network structure in a community adult sample in Hong Kong during the COVID-19 pandemic. A total of 11,072 participants were recruited between 24 March and 20 April 2020. Depressive symptoms were measured using the Patient Health Questionnaire-9. The network structure of depressive symptoms was characterized, and indices of "strength", "betweenness", and "closeness" were used to identify symptoms central to the network. Network stability was examined using a case-dropping bootstrap procedure. Guilt, Sad Mood, and Energy symptoms had the highest centrality values. In contrast, Concentration, Suicide, and Sleep had lower centrality values. There were no significant differences in network global strength (p = 0.259), distribution of edge weights (p = 0.73) and individual edge weights (all p values > 0.05 after Holm-Bonferroni corrections) between males and females. Guilt, Sad Mood, and Energy symptoms were central in the depressive symptom network. These central symptoms may be targets for focused treatments and future psychological and neurobiological research to gain novel insight into depression.
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