Spatio-Temporal Gaussianization Flows for Extreme Event Detection

2021 ◽  
Author(s):  
Miguel-Ángel Fernández-Torres ◽  
J. Emmanuel Johnson ◽  
María Piles ◽  
Gustau Camps-Valls
Keyword(s):  
Event Detection ◽  
Land Surface ◽  
Extreme Event ◽  
Learning Approaches ◽  
Proposed Model ◽  
Individual Contributions ◽  
Current Context ◽  
Spatio Temporal ◽  
The Individual ◽  
Anomaly Score

<p>Automatic anticipation and detection of extreme events constitute a major challenge in the current context of climate change. Machine learning approaches have excelled in detection of extremes and anomalies in Earth data cubes recently, but are typically both computationally costly and supervised, which hamper their wide adoption. We alternatively present here an unsupervised, efficient, generative approach for extreme event detection, whose performance is illustrated for drought detection in Europe during the severe Russian heat wave in 2010. The core architecture of the model is generic and could naturally be extended to the detection of other kinds of anomalies. First, it computes hierarchical appearance (spatial) and motion (temporal) representations of several informative Essential Climate Variables (ECVs), including soil moisture, land surface temperature, as well as features describing vegetation health. Then, these representations are combined using Gaussianization Flows that yield a spatio-temporal anomaly score. This allows the proposed model not only to detect droughts areas, but also to explain why they were produced, monitoring the individual contributions of each of the ECVs to the indicator at its output.</p>

Mol2vec: Unsupervised Machine Learning Approach with Chemical Intuition

2017 ◽  
Author(s):  
Sabrina Jaeger ◽  
Simone Fulle ◽  
Samo Turk
Keyword(s):  
Machine Learning ◽  
Language Processing ◽  
Supervised Machine Learning ◽  
Learning Approach ◽  
Learning Approaches ◽  
Unsupervised Machine Learning ◽  
Feature Representations ◽  
Machine Learning Approach ◽  
The Individual ◽  
Vector Representations

Inspired by natural language processing techniques we here introduce Mol2vec which is an unsupervised machine learning approach to learn vector representations of molecular substructures. Similarly, to the Word2vec models where vectors of closely related words are in close proximity in the vector space, Mol2vec learns vector representations of molecular substructures that are pointing in similar directions for chemically related substructures. Compounds can finally be encoded as vectors by summing up vectors of the individual substructures and, for instance, feed into supervised machine learning approaches to predict compound properties. The underlying substructure vector embeddings are obtained by training an unsupervised machine learning approach on a so-called corpus of compounds that consists of all available chemical matter. The resulting Mol2vec model is pre-trained once, yields dense vector representations and overcomes drawbacks of common compound feature representations such as sparseness and bit collisions. The prediction capabilities are demonstrated on several compound property and bioactivity data sets and compared with results obtained for Morgan fingerprints as reference compound representation. Mol2vec can be easily combined with ProtVec, which employs the same Word2vec concept on protein sequences, resulting in a proteochemometric approach that is alignment independent and can be thus also easily used for proteins with low sequence similarities.

A Handbook to Eddic Poetry: Myths and Legends of Early Scandinavia, ed. Carolyne Larrington, Judy Quinn, and Brittany Schorn. Cambridge: Cambridge University Press, 2016, xii, 413 pp., 12 b/w ill.

Mediaevistik ◽  
2018 ◽  
Vol 31 (1) ◽  
pp. 366-366
Author(s):  
Albrecht Classen
Keyword(s):  
Old Norse ◽  
Entire Volume ◽  
Cambridge University ◽  
Critical Studies ◽  
Individual Contributions ◽  
The Many ◽  
The Individual ◽  
Made In ◽  
Scandinavian Literature

Eddic poetry constitutes one of the most important genres in Old Norse or Scandinavian literature and has been studied since the earliest time of modern-day philology. The progress we have made in that field is impressive, considering the many excellent editions and translations, not to mention the countless critical studies in monographs and articles. Nevertheless, there is always a great need to revisit, to summarize, to review, and to digest the knowledge gained so far. The present handbook intends to address all those goals and does so, to spell it out right away, exceedingly well. But in contrast to traditional concepts, the individual contributions constitute fully developed critical article, each with a specialized topic elucidating it as comprehensively as possible, and concluding with a section of notes. Those are kept very brief, but the volume rounds it all off with an inclusive, comprehensive bibliography. And there is also a very useful index at the end. At the beginning, we find, following the table of contents, a list of the contributors, unfortunately without emails, a list of translations and abbreviations of the titles of Eddic poems in the Codex Regius and then elsewhere, and a very insightful and pleasant introduction by Carolyne Larrington. She briefly introduces the genre and then summarizes the essential points made by the individual authors. The entire volume is based on the Eddic Network established by the three editors in 2012, and on two workshops held at St. John’s College, Oxford in 2013 and 2014.

Employee Surveys and Sensing

2020 ◽  
Keyword(s):  
Organizational Performance ◽  
Employee Engagement ◽  
Computational Linguistics ◽  
Full Range ◽  
Organization Culture ◽  
Employee Survey ◽  
Passive Data ◽  
Individual Contributions ◽  
Action Taking ◽  
The Individual

This volume comprises 27 chapters focused on the design and execution of employee survey programs. These chapters reflect the latest advances in technology and analytics and a pervasive emphasis on driving organizational performance and effectiveness. The individual chapters represent the full range of survey-related topics, including design, administration, analysis, feedback, and action-taking. The latest methodological trends and capabilities are discussed including computational linguistics, applications of artificial intelligence, and the use of qualitative methods such as focus groups. Extending beyond traditional employee surveys, contributions include the role of passive data collection as an alternative or supplement in a comprehensive employee listening system. Unique contextual factors are discussed including the use of surveys in a unionized environment. Individual contributions also reflect increasing stakeholder concerns for the protection of privacy among other ethical considerations. Finally, significant clarifications to the literature are provided on the use of surveys for measuring organization culture, strategic climate, and employee engagement.

Knowledge First

2017 ◽  
Author(s):  
J. Adam Carter ◽  
Emma C. Gordon ◽  
Benjamin W. Jarvis
Keyword(s):  
Philosophy Of Mind ◽  
Theoretical Background ◽  
Contemporary Research ◽  
Timothy Williamson ◽  
Research Themes ◽  
New Directions ◽  
Individual Contributions ◽  
The Individual

In this introductory chapter, the volume’s editors provide a theoretical background to the volume’s topic and a brief overview of the papers included. The chapter is divided into five parts: Section 1 explains the main contours of the knowledge-first approach, as it was initially advanced by Timothy Williamson in Knowledge and its Limits. In Sections 2–3, some of the key philosophical motivations for the knowledge-first approach are reviewed, and several key contemporary research themes associated with this approach in epistemology, the philosophy of mind and elsewhere are outlined and briefly discussed. The volume’s papers are divided into two broad categories: foundational issues and applications and new directions. Section 4 discusses briefly the scope and aim of the volume as the editors have conceived it, and Section 5 offers an overview of each of the individual contributions in the volume.

scholarly journals Real-time spatio-temporal event detection on geotagged social media

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Yasmeen George ◽  
Shanika Karunasekera ◽  
Aaron Harwood ◽  
Kwan Hui Lim
Keyword(s):  
New York ◽  
Social Media ◽  
Event Detection ◽  
Detection System ◽  
Time And Space ◽  
Social Media Data ◽  
Event Time ◽  
Spatio Temporal ◽  
Geographical Space ◽  
Media Data

AbstractA key challenge in mining social media data streams is to identify events which are actively discussed by a group of people in a specific local or global area. Such events are useful for early warning for accident, protest, election or breaking news. However, neither the list of events nor the resolution of both event time and space is fixed or known beforehand. In this work, we propose an online spatio-temporal event detection system using social media that is able to detect events at different time and space resolutions. First, to address the challenge related to the unknown spatial resolution of events, a quad-tree method is exploited in order to split the geographical space into multiscale regions based on the density of social media data. Then, a statistical unsupervised approach is performed that involves Poisson distribution and a smoothing method for highlighting regions with unexpected density of social posts. Further, event duration is precisely estimated by merging events happening in the same region at consecutive time intervals. A post processing stage is introduced to filter out events that are spam, fake or wrong. Finally, we incorporate simple semantics by using social media entities to assess the integrity, and accuracy of detected events. The proposed method is evaluated using different social media datasets: Twitter and Flickr for different cities: Melbourne, London, Paris and New York. To verify the effectiveness of the proposed method, we compare our results with two baseline algorithms based on fixed split of geographical space and clustering method. For performance evaluation, we manually compute recall and precision. We also propose a new quality measure named strength index, which automatically measures how accurate the reported event is.

scholarly journals Of Visions and Visionaries: Information and Communication Technologies (ICT) in China

2021 ◽  
Vol 50 (1) ◽  
pp. 3-11
Author(s):  
Barbara Schulte ◽  
Marina Svensson
Keyword(s):  
Information And Communication Technologies ◽  
Communication Technologies ◽  
Special Issue ◽  
Empirical Reality ◽  
Information And Communication ◽  
Individual Contributions ◽  
State Governance ◽  
Different Dimensions ◽  
Chinese State ◽  
The Individual

This special issue approaches information and communication technologies (ICT) visions and their realisation/implementation at various levels, among different actors and from various perspectives. Conceptually, we distinguish three different dimensions, even though those overlap in the individual contributions as well as in empirical reality – namely ideational, instrumental, and relational. The different contributions address both visions formulated by the Chinese state and by individual actors such as entrepreneurs. Even though the conditions for the use of ICT in China are deeply affected by state governance, this governance is in no way tantamount to one single government. As this issue’s contributions show, state attempts at building a stable cyber-governance are in need of allies and, depending on the allies’ visions and other, competitive visions, the outcomes of these dynamics are seldom truthful realisations of one original grand masterplan.

scholarly journals Shared Partisanship, Household Norms and Turnout: Testing a Relational Theory of Electoral Participation

2016 ◽  
Vol 48 (3) ◽  
pp. 807-823 ◽  
Author(s):  
Edward Fieldhouse ◽  
David Cutts
Keyword(s):  
Party Identification ◽  
Household Survey ◽  
Relational Theory ◽  
Civic Duty ◽  
Proposed Model ◽  
The Social ◽  
Empirical Tests ◽  
Partisan Identification ◽  
Consumption Benefits ◽  
The Individual

Previous research shows that the household context is a crucial source of influence on turnout. This article sets out a relational theory of voting in which turnout is dependent on the existence of relational selective consumption benefits. The study provides empirical tests of key elements of the proposed model using household survey data from Great Britain. First, building on expressive theories of voting, it examines the extent to which shared partisan identification enhances turnout. Secondly, extending theories of voting as a social norm, it tests whether the civic norms of citizens’ families or households affect turnout over and above the social norms of the individual. In accordance with expectations of expressive theories of voting, it finds that having a shared party identification with other members of the household increases turnout. It also finds that the civic duty of other household members is important in explaining turnout, even when allowing for respondent’s civic duty.

scholarly journals Postprenylation CAAX Processing Is Required for Proper Localization of Ras but Not Rho GTPases

2005 ◽  
Vol 16 (4) ◽  
pp. 1606-1616 ◽  
Author(s):  
David Michaelson ◽  
Wasif Ali ◽  
Vi K. Chiu ◽  
Martin Bergo ◽  
Joseph Silletti ◽  
...  
Keyword(s):  
Posttranslational Modifications ◽  
Protein Trafficking ◽  
Rho Gtpases ◽  
Ras Proteins ◽  
Rho Proteins ◽  
Carboxyl Methylation ◽  
C Terminus ◽  
Individual Contributions ◽  
The Individual ◽  
And Function

The CAAX motif at the C terminus of most monomeric GTPases is required for membrane targeting because it signals for a series of three posttranslational modifications that include isoprenylation, endoproteolytic release of the C-terminal– AAX amino acids, and carboxyl methylation of the newly exposed isoprenylcysteine. The individual contributions of these modifications to protein trafficking and function are unknown. To address this issue, we performed a series of experiments with mouse embryonic fibroblasts (MEFs) lacking Rce1 (responsible for removal of the –AAX sequence) or Icmt (responsible for carboxyl methylation of the isoprenylcysteine). In MEFs lacking Rce1 or Icmt, farnesylated Ras proteins were mislocalized. In contrast, the intracellular localizations of geranylgeranylated Rho GTPases were not perturbed. Consistent with the latter finding, RhoGDI binding and actin remodeling were normal in Rce1- and Icmt-deficient cells. Swapping geranylgeranylation for farnesylation on Ras proteins or vice versa on Rho proteins reversed the differential sensitivities to Rce1 and Icmt deficiency. These results suggest that postprenylation CAAX processing is required for proper localization of farnesylated Ras but not geranygeranylated Rho proteins.

scholarly journals Holocene changes in African vegetation: tradeoff between climate and water availability

2014 ◽  
Vol 10 (2) ◽  
pp. 681-686 ◽  
Author(s):  
C. Hély ◽  
A.-M. Lézine ◽  
APD contributors
Keyword(s):  
West Africa ◽  
Water Availability ◽  
Regional Scale ◽  
Plant Distribution ◽  
Climate Conditions ◽  
Tropical Plants ◽  
Plant Migration ◽  
Spatio Temporal ◽  
The Individual ◽  
Instrumental Records

Abstract. Although past climate change is well documented in West Africa through instrumental records, modeling activities, and paleo-data, little is known about regional-scale ecosystem vulnerability and long-term impacts of climate on plant distribution and biodiversity. Here we use paleohydrological and paleobotanical data to discuss the relation between available surface water, monsoon rainfall and vegetation distribution in West Africa during the Holocene. The individual patterns of plant migration or community shifts in latitude are explained by differences among tolerance limits of species to rainfall amount and seasonality. Using the probability density function methodology, we show here that the widespread development of lakes, wetlands and rivers at the time of the "Green Sahara" played an additional role in forming a network of topographically defined water availability, allowing for tropical plants to migrate north from 15 to 24° N (reached ca. 9 cal ka BP). The analysis of the spatio–temporal changes in biodiversity, through both pollen occurrence and richness, shows that the core of the tropical rainbelt associated with the Intertropical Convergence Zone was centered at 15–20° N during the early Holocene wet period, with comparatively drier/more seasonal climate conditions south of 15° N.

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