89 research outputs found
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Search for baryon resonances up to 10 GeV mass produced in p+p->+mm with a resolution of +- 25 MeV
A simple magnet-less missiong-mass experiment is proposed to investigate the mass-spectrum of non-strange baryons of isospins 1/2 and 3/2 in the mass-range from 4 to 10GeV with a resolution of {+-}25 MeV or better. The spacing between baryons expected from the empirical interval rule {Delta}M{sup 2} = 1 BeV{sup 2} is 125 and 50 MeV for masses of 4 and 10 GeV respectively; if the rule holds, one expects 10{sup 2}-4{sup 2} = 84 resonances in this range. They plan to use the reaction p + p - p + MM and to detect the recoil protons in the region of the Jacobian peak. The protons of momenta from 400 to 850 MeV/c are selected by means of time-of-flight, range, and pulse height and are recorded in a pulse height analyzer. Since no magnets, wire planes, computers or any other major facilities are needed, the experiment can be done as soon as the beam, either full extracted (Option 1) or secondary diffracted (Option 2) or interla (Option 3) is available
National identity predicts public health support during a global pandemic
Changing collective behaviour and supporting non-pharmaceutical interventions is an important component in mitigating virus transmission during a pandemic. In a large international collaboration (Study 1, N = 49,968 across 67 countries), we investigated self-reported factors associated with public health behaviours (e.g., spatial distancing and stricter hygiene) and endorsed public policy interventions (e.g., closing bars and restaurants) during the early stage of the COVID-19 pandemic (April-May 2020). Respondents who reported identifying more strongly with their nation consistently reported greater engagement in public health behaviours and support for public health policies. Results were similar for representative and non-representative national samples. Study 2 (N = 42 countries) conceptually replicated the central finding using aggregate indices of national identity (obtained using the World Values Survey) and a measure of actual behaviour change during the pandemic (obtained from Google mobility reports). Higher levels of national identification prior to the pandemic predicted lower mobility during the early stage of the pandemic (r = −0.40). We discuss the potential implications of links between national identity, leadership, and public health for managing COVID-19 and future pandemics.publishedVersio
Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning
At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution-individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic.Published versio
National identity predicts public health support during a global pandemic
Understanding collective behaviour is an important aspect of managing the pandemic response. Here the authors show in a large global study that participants that reported identifying more strongly with their nation reported greater engagement in public health behaviours and support for public health policies in the context of the pandemic.Changing collective behaviour and supporting non-pharmaceutical interventions is an important component in mitigating virus transmission during a pandemic. In a large international collaboration (Study 1, N = 49,968 across 67 countries), we investigated self-reported factors associated with public health behaviours (e.g., spatial distancing and stricter hygiene) and endorsed public policy interventions (e.g., closing bars and restaurants) during the early stage of the COVID-19 pandemic (April-May 2020). Respondents who reported identifying more strongly with their nation consistently reported greater engagement in public health behaviours and support for public health policies. Results were similar for representative and non-representative national samples. Study 2 (N = 42 countries) conceptually replicated the central finding using aggregate indices of national identity (obtained using the World Values Survey) and a measure of actual behaviour change during the pandemic (obtained from Google mobility reports). Higher levels of national identification prior to the pandemic predicted lower mobility during the early stage of the pandemic (r = -0.40). We discuss the potential implications of links between national identity, leadership, and public health for managing COVID-19 and future pandemics
Comprehensive molecular characterization of the hippo signaling pathway in cancer
Hippo signaling has been recognized as a key tumor suppressor pathway. Here, we perform a comprehensive molecular characterization of 19 Hippo core genes in 9,125 tumor samples across 33 cancer types using multidimensional “omic” data from The Cancer Genome Atlas. We identify somatic drivers among Hippo genes and the related microRNA (miRNA) regulators, and using functional genomic approaches, we experimentally characterize YAP and TAZ mutation effects and miR-590 and miR-200a regulation for TAZ. Hippo pathway activity is best characterized by a YAP/TAZ transcriptional target signature of 22 genes, which shows robust prognostic power across cancer types. Our elastic-net integrated modeling further reveals cancer-type-specific pathway regulators and associated cancer drivers. Our results highlight the importance of Hippo signaling in squamous cell cancers, characterized by frequent amplification of YAP/TAZ, high expression heterogeneity, and significant prognostic patterns. This study represents a systems-biology approach to characterizing key cancer signaling pathways in the post-genomic era
Prospective pion-electron colliding beam experiments using /c-shell of heavy atom as electron «storage ring»
MoloVol: an easy-to-use program to calculate various volumes and surface areas of chemical structures and identify cavities
Cavities are a ubiquitous feature of chemical structures encountered in various fields ranging from supramolecular chemistry to molecular biology. They are involved in the encapsulation, transport, and transformation of guest molecules, thus necessitating a precise and accessible tool for estimating and visualizing their size and shape. MoloVol, a free, user-parametrizable, open-source software, developed for calculating a range of geometric features for both unit cell and isolated structures is presented here. MoloVol utilizes up to two spherical probes to define cavities, surfaces, and volumes. The program was optimized by combining an octree data structure with voxel-partitioned space allowing for even high-resolution protein structure calculations at reasonable timescales. MoloVol comes with a user-friendly graphic interface along with a command line interface for high throughput calculations. It was written in C++ and is available on Windows, macOS, and Linux distributions
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