Browsing by Subject "cluster"

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  • Lu, Yiqun; Liu, Ling; Ning, An; Yang, Gan; Liu, Yiliang; Kurten, Theo; Vehkamäki, Hanna; Zhang, Xiuhui; Wang, Lin (2020)
    Sulfuric acid (SA)-dimethylamine (DMA)-H2O cluster formation has been proven to be responsible for a significant part of new particle formation (NPF) in a Chinese megacity. However, the possible involvement of common atmospheric acids in the subsequent growth of SA-DMA clusters remains elusive. We simulated formation and growth of clusters using atmospheric relevant concentrations of SA, DMA, and trifluoroacetic acid (TFA), a commonly observed atmospheric perfluorocarboxylic acid, using Density Functional Theory combined with Atmospheric Cluster Dynamics Code. The presence of TFA leads to complex cluster formation routes and an enhancement of NPF rates by up to 2.3 ([TFA] = 5.0 x 10(6) molecules cm(-3), [SA] = 1.0 x 10(6) molecules cm(-3), and [DMA] = 1.5 x 10(9) molecules cm(-3)). The agreement of (SA)(1)center dot(DMA)(1-2)center dot(TFA)(1) concentrations between simulations and ambient measurements during NPF events validates model predictions and implies that perfluorocarboxylic acids could potentially boost atmospheric SA-DMA NPF rates.
  • Gao, Jing; Li, Jing; Han, Xia; Yuan, Yuan; Li, Chuan-Xing; Zhang, Dong-Quan (2021)
    Background: Increased stress among medical personnel had been reported in previous virus outbreaks. The novel coronavirus disease (COVID-19) emerged in December 2019, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). No qualitative assessment has yet described the physical and mental health conditions of frontline medical personnel in the COVID-19 outbreaks. Methods: Here, 251 frontline medical personnel involved in COVID-19 missions completed electronic questionnaires, consisting of 31 categorical variables related to their physical and mental health status, medical history and environmental conditions. We constructed a correlation amongst these variables through pairwise Kendall rank correlation coefficient test. Then, clusters of highly correlated variables were identified using the leading eigenvector. Finally, we used the network and clusters to clarify the correlations amongst variables. Results: This qualitative study identified the six clusters. Cluster 1 was characterized by skin allergy. Cluster 2 was predominantly associated with anxiety. Cluster 3 consisted mostly of respiratory symptoms. The participants in cluster 4 had medical history. Cluster 5 and cluster 6 were characterized by disinfection and demography, respectively. Finally, we revealed three major findings. First, more than 80% of medical personnel worry about COVID-19-related infection and experience newly appearing anxiety (56.2%), airway or heart symptoms (34.3%) and skin allergies (20.3%). Second, COVID-19- related worry significantly associates with all variables in the anxiety and respiratory symptom clusters. Third, new-onset skin allergies did not associate with either disinfection or anxiety, but did associate with a previous history of allergies. Conclusions: COVID-19-related worry leads to physical and mental health problems amongst medical personnel. Effective responses and interventions could relieve a series of new-onset physical and mental health problems.
  • Pesonen, Anu-Katriina; Lipsanen, Jari; Halonen, Risto; Elovainio, Marko; Sandman, Nils; Makelä, Juha-Matti; Antila, Minea; Bechard, Deni; Ollila, Hanna M.; Kuula, Liisa (2020)
    We used crowdsourcing (CS) to examine how COVID-19 lockdown affects the content of dreams and nightmares. The CS took place on the sixth week of the lockdown. Over the course of 1 week, 4,275 respondents (mean age 43, SD = 14 years) assessed their sleep, and 811 reported their dream content. Overall, respondents slept substantially more (54.2%) but reported an average increase of awakenings (28.6%) and nightmares (26%) from the pre-pandemic situation. We transcribed the content of the dreams into word lists and performed unsupervised computational network and cluster analysis of word associations, which suggested 33 dream clusters including 20 bad dream clusters, of which 55% were pandemic-specific (e.g., Disease Management, Disregard of Distancing, Elderly in Trouble). The dream-association networks were more accentuated for those who reported an increase in perceived stress. This CS survey on dream-association networks and pandemic stress introduces novel, collectively shared COVID-19 bad dream contents
  • Horcea-Milcu, Andra-Ioana; Martin-Lopez, Berta; Lam, David P. M.; Lang, Daniel J. (2020)
    Although sustainability science and social-ecological systems research pursue very similar goals, i.e., generate problem- and solution-oriented knowledge to foster sustainability transformation, they partly apply different research approaches and use different key concepts. Our aim is to identify archetypes of sustainability transformation research derived for sustainability science and social-ecological systems research that make knowledge from the two research pathways more accessible to each other in order to foster transformation. To reach this goal, we applied a mixed method approach toward an archetype analysis, based on semantic networks and clusters. Our findings point out that the fields of sustainability science and social-ecological systems research are rather coherent and not so distinct as may be expected, especially in terms of normative goals and addressed topics. Our analysis inductively reveals four archetypes of sustainability transformation research, with thematic structures clustered around (1) environmental change and ecosystem services; (2) resilience and vulnerability; (3) knowledge production for sustainability; and (4) governance for sustainability. We describe how these archetypes interact and facilitate dialogue between the fields. When considering the two transformation research pathways from the perspective of the research mode of transdisciplinary research, their discourses appear more disconnected. To fill this gap, we uncover key concepts that can strengthen the connection of the two fields to inform and foster sustainability transformations. These concepts involve engaging with nonacademic actors and seeking impact in policy.
  • Osmani, Lirim; Toor, Salman; Komu, Miika; Kortelainen, Matti J.; Linden, Tomas; White, John; Khan, Rasib; Eerola, Paula; Tarkoma, Sasu (2018)
    Cloud computing improves utilization and flexibility in allocating computing resources while reducing the infrastructural costs. However, in many cases cloud technology is still proprietary and tainted by security issues rooted in the multi-user and hybrid cloud environment. A lack of secure connectivity in a hybrid cloud environment hinders the adaptation of clouds by scientific communities that require scaling-out of the local infrastructure using publicly available resources for large-scale experiments. In this article, we present a case study of the DII-HEP secure cloud infrastructure and propose an approach to securely scale-out a private cloud deployment to public clouds in order to support hybrid cloud scenarios. A challenge in such scenarios is that cloud vendors may offer varying and possibly incompatible ways to isolate and interconnect virtual machines located in different cloud networks. Our approach is tenant driven in the sense that the tenant provides its connectivity mechanism. We provide a qualitative and quantitative analysis of a number of alternatives to solve this problem. We have chosen one of the standardized alternatives, Host Identity Protocol, for further experimentation in a production system because it supports legacy applications in a topologically-independent and secure way.