Overview of Design of Structures to Extreme Hazards

2019 ◽  
Author(s):  
Shalva Marjanishvili
Keyword(s):  
Large Scale ◽  
Extreme Event ◽  
Topological Analysis ◽  
Quantitative Measure ◽  
Engineering Practice ◽  
Loss Assessment ◽  
Intensity Measures ◽  
Underlying Assumption ◽  
Functional Relationships ◽  
Generalized Variables

<p>Common engineering practice in multi-hazard design is to consider each natural hazard independently. The underlying assumption is that it is highly unlikely that one disaster will be closely followed by another. This approach dominated large part of the 20th century. The engineering community has made large strides in designing structures to withstand known hazards, leading to improved reliability and safety of infrastructure. This in turn has supported population growth and increased prosperity. As witness to our success, it is common in developed nations to consider it unacceptable for a disaster to cause large scale devastation. However, the nature of the disasters has proved otherwise.</p><p>It is unlikely that one extreme event will have catastrophic consequences on communities, because we know how to prepare for a single event. Instead, as experience shows, disasters are more typically comprised by one event followed by one or more other events, exposing the vulnerability of our design assumptions. The examples of multiple disasters are Indonesia (i.e., earthquake followed by tsunami followed by volcano), Haiti (i.e., earthquake followed by cholera outbreak) and Japan (i.e., earthquake followed by tsunami followed by nuclear meltdown). The obvious solution is to focus on understanding on the resilience of the system as an its ability to rapidly recover from the event.</p><p>This paper proposes a framework for quantitative measure and mathematically reproducible definitions of structural resilience as it pertains to a building’s ability to minimize the potential for undesirable consequences. The resilience assessment and design process follow logical progression of steps, starting with the characterization of hazards, continuing through analysis simulations, damage modelling, and loss assessment by finding and subsequently balancing functional relationships between design and analysis and consequences. The outcomes of each process are articulated through a series of generalized variables, termed as topology, geometry, damage and hazard intensity measures. Topological analysis methods are developed to map the effects of blast and extreme fire exposure so that the corresponding intensity measures can be addressed simultaneously during design</p>

Epigenetic Target Prediction with Accurate Machine Learning Models

2021 ◽  
Author(s):  
Norberto Sánchez-Cruz ◽  
Jose L. Medina-Franco
Keyword(s):  
Machine Learning ◽  
Small Molecules ◽  
Predictive Models ◽  
Large Scale ◽  
Target Prediction ◽  
Quantitative Measure ◽  
Learning Models ◽  
Discovery Research ◽  
Drug Discovery Research ◽  
Machine Learning Models

<p>Epigenetic targets are a significant focus for drug discovery research, as demonstrated by the eight approved epigenetic drugs for treatment of cancer and the increasing availability of chemogenomic data related to epigenetics. This data represents a large amount of structure-activity relationships that has not been exploited thus far for the development of predictive models to support medicinal chemistry efforts. Herein, we report the first large-scale study of 26318 compounds with a quantitative measure of biological activity for 55 protein targets with epigenetic activity. Through a systematic comparison of machine learning models trained on molecular fingerprints of different design, we built predictive models with high accuracy for the epigenetic target profiling of small molecules. The models were thoroughly validated showing mean precisions up to 0.952 for the epigenetic target prediction task. Our results indicate that the herein reported models have considerable potential to identify small molecules with epigenetic activity. Therefore, our results were implemented as freely accessible and easy-to-use web application.</p>

scholarly journals Spatial impact and triggering conditions of the exceptional hydro-geomorphological event of December 1909 in Iberia

2016 ◽  
Vol 16 (2) ◽  
pp. 371-390 ◽  
Author(s):  
S. Pereira ◽  
A. M. Ramos ◽  
J. L. Zêzere ◽  
R. M. Trigo ◽  
J. M. Vaquero
Keyword(s):  
Spatial Distribution ◽  
Iberian Peninsula ◽  
Large Scale ◽  
Extreme Event ◽  
Social Impacts ◽  
Meteorological Conditions ◽  
Pressure System ◽  
Data Set ◽  
Upper Level ◽  
Disaster Event

Abstract. According to the DISASTER database the 20–28 December 1909 event was the hydro-geomorphologic event with the highest number of flood and landslide cases that occurred in Portugal in the period 1865–2010 (Zêzere et al., 2014). This event also caused important social impacts over the Spanish territory, especially in the Douro Basin, having triggered the highest floods in more than 100 years at the river's mouth in the city of Oporto. This work has a dual purpose: (i) to characterize the spatial distribution and social impacts of the December 1909 hydro-geomorphologic DISASTER event over Portugal and Spain; (ii) to analyse the meteorological conditions that triggered the event and the spatial distribution of the precipitation anomalies. Social impacts that occurred in Portugal were obtained from the Disaster database (Zêzere et al., 2014) whereas the data collection for Spain was supported by the systematic analysis of Spanish daily newspapers. In addition, the meteorological conditions that triggered the event are analysed using the 20th Century Reanalysis data set from NOAA and precipitation data from Iberian meteorological stations. The Iberian Peninsula was spatially affected during this event along the SW-NE direction spanning from Lisbon, Santarém, Oporto, and Guarda (in Portugal), to Salamanca, Valladolid, Zamora, Orense, León, and Palencia (in Spain). In Iberia, 134 DISASTER cases were recorded (130 flood cases; 4 landslides cases) having caused 89 casualties (57 due to floods and 32 due to landslides) and a further total of 3876 affected people, including fatalities, injured, missing, evacuated, and homeless people. This event was associated with outstanding precipitation registered at Guarda (Portugal) on 22 December 1909 and unusual meteorological conditions characterized by the presence of a deep low-pressure system located over the NW Iberian Peninsula with a stationary frontal system striking the western Iberian Peninsula. The presence of an upper-level jet (250 hPa) and low-level jet (900 hPa) located SW–NE oriented towards Iberia along with upper-level divergence and lower-level convergence favoured large-scale precipitation. Finally, associated with these features it is possible to state that this extreme event was clearly associated with the presence of an elongated Atmospheric River, crossing the entire northern Atlantic Basin and providing a continuous supply of moisture that contributed to enhance precipitation. This work contributes to a comprehensive and systematic synoptic evaluation of the second most deadly hydro-geomorphologic DISASTER event that has occurred in Portugal since 1865 and will help to better understand the meteorological system that was responsible for triggering the event.

scholarly journals Methodical approach to determining permissible time limits of intermittent carbon monoxide exposure in rescuers

2021 ◽  
pp. 82-88
Author(s):  
D. V. Myasnikov ◽  
P. V. Avitisov ◽  
A. V. Zolotukhin ◽  
M. F. Barinov
Keyword(s):  
Carbon Monoxide ◽  
Large Scale ◽  
Operation Time ◽  
Theoretical Data ◽  
Combustion Products ◽  
Research Area ◽  
Time Limits ◽  
Emergency Rescue ◽  
Functional Relationships ◽  
Methodical Approach

Relevance. Current operation time limits under hazardous chemical conditions (“emergency regulations”) have been developed mainly for a limited number of emergency situations occurring in spacecraft, submarines or other specific objects. At the same time, many emergencies accompanied by large-scale releases of toxic combustion products from various materials and compounds into the environment are not limited to these facilities. Therefore, risks associated with toxic effects of chemicals should be predicted, since permissible time limits with adequate performance of personnel under certain chemical exposures are used for individual protection (time-based protection).Intention: On the basis of physiological aspects, the peculiarities of the work performed by rescuers and the requirements for organizing and conducting emergency rescue operations, to propose a methodical approach to determining the permissible time for rescuers in conditions of intermittent carbon monoxide release.Methodology. The scientific works and results of experiments in the research area were analyzed. Systematization and generalization of empirical and theoretical data, traditional analysis of documents and publications were used with the least squares approximation.Results and Discussion. Specific effects of various carbon monoxide concentrations are shown for different exposure times. Critical concentrations and exposure times are revealed, functional relationships between permissible time of operation and carbon monoxide concentrations are determined. Carboxyhemoglobin formation and effects were taken into account.Conclusion. The data given in the article are an important basis for organizing and conducting emergency rescue operations at increased concentrations of carbon monoxide.

scholarly journals ComplexBrowser: a tool for identification and quantification of protein complexes in large scale proteomics datasets

2019 ◽  
Author(s):  
Wojciech Michalak ◽  
Vasileios Tsiamis ◽  
Veit Schwämmle ◽  
Adelina Rogowska-Wrzesińska
Keyword(s):  
T Cell Activation ◽  
Protein Complex ◽  
Quantitative Proteomics ◽  
Large Scale ◽  
Protein Complexes ◽  
Quantitative Measure ◽  
Exploratory Analysis ◽  
List Type ◽  
Link Type ◽  
Complex Components

AbstractWe have developed ComplexBrowser, an open source, online platform for supervised analysis of quantitative proteomics data that focuses on protein complexes. The software uses information from CORUM and Complex Portal databases to identify protein complex components. Based on the expression changes of individual complex subunits across the proteomics experiment it calculates Complex Fold Change (CFC) factor that characterises the overall protein complex expression trend and the level of subunit co-regulation. Thus up- and down-regulated complexes can be identified. It provides interactive visualisation of protein complexes composition and expression for exploratory analysis. It also incorporates a quality control step that includes normalisation and statistical analysis based on Limma test. ComplexBrowser performance was tested on two previously published proteomics studies identifying changes in protein expression in human adenocarcinoma tissue and during activation of mouse T-cells. The analysis revealed 1519 and 332 protein complexes, of which 233 and 41 were found co-ordinately regulated in the respective studies. The adopted approach provided evidence for a shift to glucose-based metabolism and high proliferation in adenocarcinoma tissues and identification of chromatin remodelling complexes involved in mouse T-cell activation. The results correlate with the original interpretation of the experiments and also provide novel biological details about protein complexes affected. ComplexBrowser is, to our knowledge, the first tool to automate quantitative protein complex analysis for high-throughput studies, providing insights into protein complex regulation within minutes of analysis.A fully functional demo version of ComplexBrowser v1.0 is available online via http://computproteomics.bmb.sdu.dk/Apps/ComplexBrowser/The source code can be downloaded from: https://bitbucket.org/michalakw/complexbrowserHighlightsAutomated analysis of protein complexes in proteomics experimentsQuantitative measure of the coordinated changes in protein complex componentsInteractive visualisations for exploratory analysis of proteomics resultsIn briefComplexBrowser is capable of identifying protein complexes in datasets obtained from large scale quantitative proteomics experiments. It provides, in the form of the CFC factor, a quantitative measure of the coordinated changes in complex components. This facilitates assessing the overall trends in the processes governed by the identified protein complexes providing a new and complementary way of interpreting proteomics experiments.

scholarly journals Local memory boosts label propagation for community detection

2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Antonio Maria Fiscarelli ◽  
Matthias R. Brust ◽  
Grégoire Danoy ◽  
Pascal Bouvry
Keyword(s):  
Community Detection ◽  
Large Scale ◽  
Linear Time ◽  
Topological Analysis ◽  
Detection Algorithm ◽  
Label Propagation ◽  
Performance Study ◽  
Global Knowledge ◽  
Local Optima ◽  
Propagation Algorithm

Abstract The objective of a community detection algorithm is to group similar nodes that are more connected to each other than with the rest of the network. Several methods have been proposed but many are of high complexity and require global knowledge of the network, which makes them less suitable for large-scale networks. The Label Propagation Algorithm initially assigns a distinct label to each node that iteratively updates its label with the one of the majority of its neighbors, until consensus is reached among all nodes in the network. Nodes sharing the same label are then grouped into communities. It runs in near linear time and is decentralized, but it gets easily stuck in local optima and often returns a single giant community. To overcome these problems we propose MemLPA, a variation of the classical Label Propagation Algorithm where each node implements a memory mechanism that allows them to “remember” about past states of the network and uses a decision rule that takes this information into account. We demonstrate through extensive experiments, on the Lancichinetti-Fortunato-Radicchi benchmark and a set of real-world networks, that MemLPA outperforms other existing label propagation algorithms that implement memory and some of the well-known community detection algorithms. We also perform a topological analysis to extend the performance study and compare the topological properties of the communities found to the ground-truth community structure.

Relative Efficiency of Ancillary and Small Scale Units

1978 ◽  
Vol 3 (4) ◽  
pp. 279-284
Author(s):  
K.R. Shaligram
Keyword(s):  
Small Firms ◽  
Large Scale ◽  
Small Scale ◽  
Underlying Assumption ◽  
Significant Difference ◽  
End Products ◽  
Policy Measures ◽  
The Mean ◽  
Small Manufacturers ◽  
Better Than

Ancillary units are small firms manufacturing and supplying intermediate goods, typically to large firms. Several policy measures are under consideration to raise the output of the ancillary industry to the level of 15 per cent of the value of output of the large scale industry by 1985. The underlying assumption appears to be that the ancillary status enhances the prospect for the viability of the small firm. This paper examines whether ancillary units perform better than small scale units (small manufacturers of end products) under the conditions prevailing in India. The findings reveal no significant difference in the mean performance of the two classes of small firms. It also draws implications for policymakers and management from the findings.

scholarly journals The Dynamics of an Extreme Precipitation Event in Northeastern Vietnam in 2015 and Its Predictability in the ECMWF Ensemble Prediction System

2017 ◽  
Vol 32 (3) ◽  
pp. 1041-1056 ◽  
Author(s):  
Roderick van der Linden ◽  
Andreas H. Fink ◽  
Joaquim G. Pinto ◽  
Tan Phan-Van
Keyword(s):  
Large Scale ◽  
Extreme Event ◽  
Coastal Region ◽  
Economic Loss ◽  
Precipitation Event ◽  
Ensemble Prediction ◽  
Ensemble Forecasts ◽  
Ensemble Prediction System ◽  
Upper Level ◽  
Quang Ninh

Abstract A record-breaking rainfall event occurred in northeastern Vietnam in late July–early August 2015. The coastal region in Quang Ninh Province was hit severely, with station rainfall sums in the range of 1000–1500 mm. The heavy rainfall led to flooding and landslides, which resulted in an estimated economic loss of $108 million (U.S. dollars) and 32 fatalities. Using a multitude of data sources and ECMWF ensemble forecasts, the synoptic–dynamic development and practical predictability of the event is investigated in detail for the 4-day period from 1200 UTC 25 July to 1200 UTC 29 July 2015, during which the major portion of the rainfall was observed. A slowly moving upper-level subtropical trough and the associated surface low in the northern Gulf of Tonkin promoted sustained moisture convergence and convection over northeastern Vietnam. The humidity was advected in a moisture transport band lying across the Indochina Peninsula and emanating from a tropical storm over the Bay of Bengal. Analyses of the ECMWF ensemble forecasts clearly showed a sudden emergence of the predictability of the extreme event at lead times of 3 days that was associated with the correct forecasts of the intensity and location of the subtropical trough in the 51 ensemble members. Thus, the Quang Ninh event is a good example in which the predictability of tropical convection arises from large-scale synoptic forcing; in the present case it was due to a tropical–extratropical interaction that has not been documented before for the region and season.

scholarly journals A Product Feature Inference Model for Mining Implicit Customer Preferences Within Large Scale Social Media Networks

2015 ◽  
Author(s):  
Suppawong Tuarob ◽  
Conrad S. Tucker
Keyword(s):  
Social Media ◽  
Large Scale ◽  
Ground Truth ◽  
Inference Model ◽  
Underlying Assumption ◽  
Ground Truth Data ◽  
Social Media Networks ◽  
Customer Preferences ◽  
Product Features ◽  
Online Sources

The acquisition and mining of product feature data from online sources such as customer review websites and large scale social media networks is an emerging area of research. In many existing design methodologies that acquire product feature preferences form online sources, the underlying assumption is that product features expressed by customers are explicitly stated and readily observable to be mined using product feature extraction tools. In many scenarios however, product feature preferences expressed by customers are implicit in nature and do not directly map to engineering design targets. For example, a customer may implicitly state “wow I have to squint to read this on the screen”, when the explicit product feature may be a larger screen. The authors of this work propose an inference model that automatically assigns the most probable explicit product feature desired by a customer, given an implicit preference expressed. The algorithm iteratively refines its inference model by presenting a hypothesis and using ground truth data, determining its statistical validity. A case study involving smartphone product features expressed through Twitter networks is presented to demonstrate the effectiveness of the proposed methodology.

scholarly journals The 23–26 September 2012 U.K. Floods: Using PV Surgery to Quantify Sensitivity to Upper-Level Forcing

2017 ◽  
Vol 145 (10) ◽  
pp. 4055-4079 ◽  
Author(s):  
Sam Hardy ◽  
David M. Schultz ◽  
Geraint Vaughan
Keyword(s):  
United Kingdom ◽  
Large Scale ◽  
Extreme Event ◽  
Initial Conditions ◽  
Initial Position ◽  
River Flooding ◽  
The United Kingdom ◽  
Accumulated Rainfall ◽  
Upper Level ◽  
The Impact

Major river flooding affected the United Kingdom in late September 2012 as a slow-moving extratropical cyclone brought over 150 mm of rain to parts of northern England and north Wales. The cyclone deepened over the United Kingdom on 24–26 September as a potential vorticity (PV) anomaly approached from the northwest, elongated into a PV streamer, and wrapped around the cyclone. The strength and position of the PV anomaly is modified in the initial conditions of Weather Research and Forecasting Model simulations, using PV surgery, to examine whether different upper-level forcing, or different phasing between the PV anomaly and cyclone, could have produced an even more extreme event. These simulations reveal that quasigeostrophic (QG) forcing for ascent ahead of the anomaly contributed to the persistence of the rainfall over the United Kingdom. Moreover, weakening the anomaly resulted in lower rainfall accumulations across the United Kingdom, suggesting that the impact of the event might be proportional to the strength of the upper-level QG forcing. However, when the anomaly was strengthened, it rotated cyclonically around a large-scale trough over Iceland rather than moving eastward as in the verifying analysis, with strongly reduced accumulated rainfall across the United Kingdom. A similar evolution developed when the anomaly was moved farther away from the cyclone. Conversely, moving the anomaly nearer to the cyclone produced a similar solution to the verifying analysis, with slightly increased rainfall totals. These counterintuitive results suggest that the verifying analysis represented almost the highest-impact scenario possible for this flooding event when accounting for sensitivity to the initial position and strength of the PV anomaly.

Sign in / Sign up

Export Citation Format

Share Document