1,720,993 research outputs found
Detecting fingerprints of landslide drivers: A MaxEnt model
No full textLandslides are important geomorphic events that sculpt river basins by eroding hillslopes and providing sediments to coastal areas. However, landslides are also hazardous events for socio-ecological systems in river basins causing enormous biodiversity, economic, and social impacts. We propose a probabilistic spatially explicit model for the prediction of landslide patterns based on a maximum entropy principle model (MAXENT). The model inputs are the centers of mass of historical landslides and environmental variables at the basin scale. The model has only three parameters requiring calibration: the threshold for the network extraction, the trade-off factor between model complexity and accuracy, and the threshold of landslide susceptibility. The calibration on a subset of observations detects the environmental drivers and their relative importance for landslides. We employ the model in the Arno basin, Italy, selected because of its widespread landslide dynamics and the large availability of landslide observations. The model reproduces the size distribution and location of over 27,500 historical landslides for the Arno basin with an accuracy of 86% obtained from the variable-landslide inference on about 37% of observed landslides. Future landslide patterns are predicted for 17 A1B and A2 rainfall scenarios and for a multimodel ensemble from 2000 to 2100. We show that potential landslide hazard is strongly correlated with variation in the 12 and 48 h rainfall with a return time of 10 years. As the climate gets wetter, the average probability of landslides gets higher which is shown by the landslide size distribution. Hence, the landslide size distribution is a fingerprint of the geomorphic effectiveness of rainfall as a function of climate change. MAXENT is proposed as a parsimonious model for the prediction of landslide patterns with respect to more complex models. The need for very accurately sampled and delineated landslides is lower than for other prediction models. Moreover, the model informs about the drivers of landslides and their relative importance without assumptions on the main triggering factors. This is important to inform monitoring of environmental variables. Our modeling approach can enhance the planning of socio-ecological systems in river basins by improving the accuracy of landslide prediction in space and time. ©2013. American Geophysical Union. All Rights Reserved
Information-theoretic portfolio decision model for optimal flood management
No full textThe increasing impact of flooding urges more effective flood management strategies to guarantee sustainable ecosystem development. Recent catastrophes underline the importance of avoiding local flood management, but characterizing large scale basin wide approaches for systemic flood risk management. Here we introduce an information-theoretic Portfolio Decision Model (iPDM) for the optimization of a systemic ecosystem value at the basin scale by evaluating all potential flood risk mitigation plans. iPDM calculates the ecosystem value predicted by all feasible combinations of flood control structures (FCS) considering environmental, social and economical asset criteria. A multi-criteria decision analytical model evaluates the benefits of all FCS portfolios at the basin scale weighted by stakeholder preferences for assets’ criteria as ecosystem services. The risk model is based on a maximum entropy model (MaxEnt) that predicts the flood susceptibility, the risk of floods based on the exceedance probability distribution, and its most important drivers. Information theoretic global sensitivity and uncertainty analysis is used to select the simplest and most accurate model based on a flood return period. A stochastic optimization algorithm optimizes the ecosystem value constrained to the budget available and provides Pareto frontiers of optimal FCS plans for any budget level. Pareto optimal solutions maximize FCS diversity and minimize the criticality of floods manifested by the scaling exponent of the Pareto distribution of flood size that links management and hydrogeomorphological patterns. The proposed model is tested on the 17,000 km2 Tiber river basin in Italy. iPDM allows stakeholders to identify optimal FCS plans in river basins for a comprehensive evaluation of flood effects under future ecosystem trajectories
9,10-Anthraquinone hinders beta-aggregation: how does a small molecule interfere with Abeta-peptide amyloid fibrillation?
No full textAmyloid aggregation is linked to a number of neurodegenerative syndromes, the most prevalent one being Alzheimer's disease. In this pathology, the beta-amyloid peptides (Abeta) aggregate into oligomers, protofibrils, and fibrils and eventually into plaques, which constitute the characteristic hallmark of Alzheimer's disease. Several low-molecular-weight compounds able to impair the Abeta aggregation process have been recently discovered; yet, a detailed description of their interactions with oligomers and fibrils is hitherto missing. Here, molecular dynamics simulations are used to investigate the influence of two relatively similar tricyclic, planar compounds, that is, 9, 10-anthraquinone (AQ) and anthracene (AC), on the early phase of the aggregation of the Abeta heptapeptide segment H(14)QKLVFF(20), the hydrophobic stretch that promotes the Abeta self-assembly. The simulations show that AQ interferes with beta-sheet formation more than AC. In particular, AQ intercalates into the beta-sheet because polar interactions between the compound and the peptide backbone destabilize the interstrand hydrogen bonds, thereby favoring disorder. The thioflavin T-binding assay indicates that AQ, but not AC, sensibly reduces the amount of aggregated Abeta(1-40) peptide. Taken together, the in silico and in vitro results provide evidence that structural perturbations by AQ can remarkably affect ordered oligomerization. Moreover, the simulations shed light at the atomic level on the interactions between AQ and Abeta oligomers, providing useful insights for the design of small-molecule inhibitors of aggregation with therapeutic potential in Alzheimer's disease
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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