Models of contagion arise broadly in both the biological and the social sciences, with applications ranging from the transmission of infectious diseases to the spread of cultural fads. In this ...Letter, we introduce a general model of contagion which, by explicitly incorporating memory of past exposures to, for example, an infectious agent, rumor, or new product, includes the main features of existing contagion models and interpolates between them. We obtain exact solutions for a simple version of the model, finding that under general conditions only three classes of collective dynamics exist. Furthermore, we find that, for a given length of memory, the class into which a particular system falls is determined by only two parameters. Our model suggests novel measures for assessing the susceptibility of a population to large contagion events, and also a possible strategy for inhibiting or facilitating them.
Collecting personally identifiable information (PII) on data subjects has become big business. Data brokers and data processors are part of a multi-billion-dollar industry that profits from ...collecting, buying, and selling consumer data. Yet there is little transparency in the data collection industry which makes it difficult to understand what types of data are being collected, used, and sold, and thus the risk to individual data subjects. In this study, we examine a large textual dataset of privacy policies from 1997-2019 in order to investigate the data collection activities of data brokers and data processors. We also develop an original lexicon of PII-related terms representing PII data types curated from legislative texts. This mesoscale analysis looks at privacy policies over time on the word, topic, and network levels to understand the stability, complexity, and sensitivity of privacy policies over time. We find that (1) privacy legislation may be correlated with changes in stability and turbulence of PII data types in privacy policies; (2) the complexity of privacy policies decreases over time and becomes more regularized; (3) sensitivity rises over time and shows spikes that appear to be correlated with events when new privacy legislation is introduced.
Collecting personally identifiable information (PII) on data subjects has become big business. Data brokers and data processors are part of a multi-billion-dollar industry that profits from ...collecting, buying, and selling consumer data. Yet there is little transparency in the data collection industry which makes it difficult to understand what types of data are being collected, used, and sold, and thus the risk to individual data subjects. In this study, we examine a large textual dataset of privacy policies from 1997-2019 in order to investigate the data collection activities of data brokers and data processors. We also develop an original lexicon of PII-related terms representing PII data types curated from legislative texts. This mesoscale analysis looks at privacy policies overtime on the word, topic, and network levels to understand the stability, complexity, and sensitivity of privacy policies over time. We find that (1) privacy legislation correlates with changes in stability and turbulence of PII data types in privacy policies; (2) the complexity of privacy policies decreases over time and becomes more regularized; (3) sensitivity rises over time and shows spikes that are correlated with events when new privacy legislation is introduced.
Data scientists across disciplines are increasingly in need of exploratory analysis tools for data sets with a high volume of features of mixed data type (quantitative continuous and discrete ...categorical). We introduce Sirius, a novel visualization package for researchers to explore feature relationships among mixed data types using mutual information. The visualization of feature relationships aids data scientists in finding meaningful dependence among features prior to the development of predictive modeling pipelines, which can inform downstream analysis such as feature selection, feature extraction, and early detection of potential proxy variables. Using an information theoretic approach, Sirius supports network visualization of heterogeneous data sets (consisting of continuous and discrete data types), and provides a user interface for exploring feature pairs with locally significant mutual information scores. Mutual information algorithm and bivariate chart types are assigned on a data type pairing basis (continuous-continuous, discrete-discrete, and discrete-continuous). We show how this tool can be used for tasks such as hypothesis confirmation, identification of predictive features, suggestions for feature extraction, or early warning of data abnormalities. The accompanying website for this paper can be accessed at https://sirius.universalities.com/. All code and supplemental materials can be accessed at https://osf.io/pdm9r/.
Plants are engaged in a continuous co-evolutionary struggle for dominance with their pathogens. The outcomes of these interactions are of particular importance to human activities, as they can have ...dramatic effects on agricultural systems. The recent convergence of molecular studies of plant immunity and pathogen infection strategies is revealing an integrated picture of the plant-pathogen interaction from the perspective of both organisms. Plants have an amazing capacity to recognize pathogens through strategies involving both conserved and variable pathogen elicitors, and pathogens manipulate the defence response through secretion of virulence effector molecules. These insights suggest novel biotechnological approaches to crop protection.
Apoplastic effectors, in particular, often contain several disulfide bonds 17 and predicted secretomes of pathogenic fungi contain proteins with elevated levels of cysteines compared to all ...proteins (Fig 1A). ...the criteria of small and cysteine-rich can be used to mine predicted secretomes for apoplastic effectors and reduce the number of candidates 18,19. ...an increase in the number of identified fungal effectors might enable machine learning approaches for unbiased prediction, which could lead to the discovery of protein properties common to fungal effectors.
...new variants of Asian soybean rust (Phakopsora pachyrhizi) detected in Brazil and the United States pose a major constraint to soybean cultivation 2. Since genetic resistance can provide effective ...and chemical-free disease control, many efforts are directed towards isolating rust-resistance genes in crop plants and understanding how to best deploy them for durable resistance 3. ...the stripe rust-resistance gene Yr36 encodes a chloroplast-localised protein with kinase and steroidogenic acute regulatory protein-related transfer (START) lipid-binding domains and is proposed to reduce the detoxification of reactive oxygen species by phosphorylation of a thylakoid-associated ascorbate peroxidase, resulting in enhanced defense responses 18. Transgenic expression of the wheat Lr34 or Lr67 genes in other cereal species, such as durum wheat, barley, rice, and maize, confers resistance to multiple adapted pathogens of these crops, suggesting that the roles of these genes in infection are conserved across a wide taxonomic range 22. ...these genes have the potential to be used as new sources of basal/background resistance in other species, although it remains to be determined whether they can function in eudicots. Basal immunity would be relatively more important in interactions where the nonhost species is distantly related to the normal host, and NLR immunity more important in interactions involving a more closely related nonhost species. ...it is not surprising that many responses associated with NHR overlap those activated during host resistance 4, 27, 28, 29.
PDF
