scholarly journals The impact of modelling method selection on predicted extent and distribution of deep-sea benthic assemblages

2014 ◽  
Vol 105 (4) ◽  
pp. 251-261 ◽  
Author(s):  
Nils Piechaud ◽  
Anna Downie ◽  
Heather A. Stewart ◽  
Kerry L. Howell
Keyword(s):  
Deep Sea ◽  
Performance Metrics ◽  
Predictive Modelling ◽  
Lophelia Pertusa ◽  
Benthic Assemblages ◽  
Modelling Method ◽  
Input Variables ◽  
The Impact ◽  
Modelling Methods ◽  
Political Decisions

ABSTRACTPredictive modelling of deep-sea species and assemblages with multibeam acoustic datasets as input variables is now a key tool in the provision of maps upon which spatial planning and management of the marine environment can be based. However, with a multitude of methods available, advice is needed on the best methods for the task at hand. In this study, we predictively modelled the distribution and extent of three vulnerable marine ecosystems (VMEs) at the assemblage level (‘Lophelia pertusa reef frameworks’; ‘Stylasterids and lobose sponges’; and ‘Xenophyophore fields’) on the eastern flank of Rockall Bank, using three modelling methods: MaxEnt; RandomForests classification with multiple assemblages (gRF); and RandomForests classification with the presence/absence of a single VME (saRF). Performance metrics indicated that MaxEnt performed the best, but all models were considered valid. All three methods broadly agreed with regard to broad patterns in distribution. However, predicted extent presented a variation of up to 35 % between the different methods, and clear differences in predicted distribution were observed. We conclude that the choice of method is likely to influence the results of predicted maps, potentially impacting political decisions about deep-sea VME conservation.

Predictive modelling of hospital readmission: Evaluation of different preprocessing techniques on machine learning classifiers

2021 ◽  
Vol 25 (5) ◽  
pp. 1073-1098
Author(s):  
Nor Hamizah Miswan ◽  
Chee Seng Chan ◽  
Chong Guan Ng
Keyword(s):  
Machine Learning ◽  
Hospital Readmission ◽  
Performance Metrics ◽  
Predictive Performance ◽  
Predictive Modelling ◽  
Machine Learning Classifiers ◽  
Learning Classifiers ◽  
Set Up ◽  
The Right ◽  
The Impact

Hospital readmission is a major cost for healthcare systems worldwide. If patients with a higher potential of readmission could be identified at the start, existing resources could be used more efficiently, and appropriate plans could be implemented to reduce the risk of readmission. Therefore, it is important to predict the right target patients. Medical data is usually noisy, incomplete, and inconsistent. Hence, before developing a prediction model, it is crucial to efficiently set up the predictive model so that improved predictive performance is achieved. The current study aims to analyse the impact of different preprocessing methods on the performance of different machine learning classifiers. The preprocessing applied by previous hospital readmission studies were compared, and the most common approaches highlighted such as missing value imputation, feature selection, data balancing, and feature scaling. The hyperparameters were selected using Bayesian optimisation. The different preprocessing pipelines were assessed using various performance metrics and computational costs. The results indicated that the preprocessing approaches helped improve the model’s prediction of hospital readmission.

Effect of Flexible Joint Modelling Method on Deep Water Catenary Riser Hang-Off Fatigue Response

2019 ◽  
Author(s):  
Guanyu Hu ◽  
Chaojun Huang ◽  
Fengjie Yin ◽  
Mark Cerkovnik ◽  
Guangqiang Yang
Keyword(s):  
Deep Water ◽  
Joint Stiffness ◽  
Fatigue Performance ◽  
Fatigue Load ◽  
Flexible Joint ◽  
Cyclic Bending ◽  
Modelling Method ◽  
The Impact ◽  
Nonlinear Curve ◽  
Modelling Methods

Abstract The Flexible joint is one of the most widely used hang-off systems for deep water catenary riser for its large rotation and load bearing capacity. The fatigue performance of riser hang-off region and fatigue load on the flexible joint highly depend on the rotational stiffness of the flexible joint. Thus, modelling the flexible joint stiffness to accurately simulate the behavior under cyclic bending cycles is critical in global riser fatigue analysis. The load-displacement relationship of a flexible joint typically follows a nonlinear curve, and it shows hysteresis behavior when subject to cyclic bending cycles. However, in current industry practice, the flexible joint stiffness is modelled either as a nonlinear curve or simplified as a fixed value. These simplified methods sometimes can lead to unconservative or over conservative results in riser design. Modelling the flexible joint stiffness in an accurate approach becomes more important especially when the riser fatigue is critical at the hang-off region. In addition, the design of flexible joint will also be impacted by the fatigue load extracted from global fatigue analysis, which is also largely affected by the flexible joint stiffness modelling method. Thus, modelling a flexible joint by accounting for the nonlinear hysteretic stiffness is recommended. This paper compares the different modelling methodologies of the flexible joint for catenary riser hang-off and presents the impact on fatigue performance considering hysteretic behavior. This study considers the effects of wave amplitude and hosting vessel offset. A case study is also presented on the application of all the modelling methods on fatigue performance of an SCR in the Gulf of Mexico. The fatigue behavior is compared for the different modelling methods considering long term wave motion and platform offsets. The impact on the results from different types of hosting platform is also discussed.

Recifes de Coral de Profundidade: Corais Construtores e sua Distribuição no Brasil

2016 ◽  
Vol 19 (3) ◽  
Author(s):  
Débora De Oliveira Pires
Keyword(s):  
Coral Reefs ◽  
Deep Sea ◽  
Decision Makers ◽  
Advanced Technology ◽  
Marine Biodiversity ◽  
Brazilian Coast ◽  
Lophelia Pertusa ◽  
Deep Waters ◽  
The World ◽  
The Impact

Deep-sea coral reefs and coral habitats are hotspots of biodiversity and provide numerous resources for fishing, bioprospecting and science. The deep-water coral reefs and coral aggregates were first discovered in locations off the coast of Norway, in 1865. The increase of commercial operations in deep waters, and the use of advanced technology in offshore areas have revealed the true scale of deep-sea coral ecosystems of Europe, until then virtually unknown. From the 1990’s, there was a considerable increase in the number of important scientific contributions on deep-sea coral habitats. So, today is known that the occurrence of coral reefs is not restricted to shallow waters of tropical and subtropical regions and that there are deep-sea coral reefs spread out of the world, including Brazil. The goal of this study was to indicate the existence of potential areas of deep-sea coral reefs/habitats along the Brazilian coast, from records of occurrence of coral reef builders species (Lophelia pertusa, Madrepora oculata, Solenosmilia variabilis, Dendrophyllia alternata and Enallopsammia rostrata). The examination of the records/specimens demonstrated an extensive and almost continuous latitudinal distribution of the coral species along the Brazilian coast. Fishing is the main cause of impact to deep-sea coral reefs in several regions of the world. For more than a decade the deep demersal fishing has been held in Brazil and the extent of the impact caused by fishing nets, used by the boats close to the reefs, is unknown. The data presented here provide a contribution not only to the scientific community, but also to the decision makers regarding the uses of areas of the Brazilian shelf and slope, which represent reservoirs of rich marine biodiversity.

scholarly journals Recommendations for best practice in deep-sea habitat classification: Bullimore et al. as a case study

2013 ◽  
Vol 71 (4) ◽  
pp. 895-898 ◽  
Author(s):  
Lea-Anne Henry ◽  
J. Murray Roberts
Keyword(s):  
Deep Sea ◽  
Best Practice ◽  
Cold Water ◽  
Future Climate Change ◽  
Cold Seeps ◽  
Climate Change Scenarios ◽  
Lophelia Pertusa ◽  
Benthic Assemblages ◽  
Habitat Classification

Abstract We assert that the reef framework-forming coral, Solenosmilia variabilis Duncan, 1873, is sometimes incorrectly recorded as another coral, Lophelia pertusa (Linnaeus, 1758) in surveys of deep-sea habitat (e.g. Bullimore, R., Foster, N., and Howell, K. 2013. Coral-characterized benthic assemblages of the deep Northeast Atlantic: defining “Coral Gardens” to support future habitat mapping efforts. ICES Journal of Marine Science, 70: 511–522). Accurate species lists are critical for developing robust deep-sea habitat classification schemes that allow us to map the distribution of different vulnerable marine ecosystems (VMEs) and predict their occurrences under future climate change scenarios, both of which help prioritize areas for marine protected areas. We recommend that the survey reported by Bullimore et al. (2013), as well as analogous surveys, consider the likelihood of Solenosmilia having been misidentified, and revise their data if necessary. We also make two further recommendations for best practice in deep-sea habitat classification using Bullimore et al. (2013) as a case study. Preferably, physical specimens should be obtained during deep-sea surveys. However, in the absence of identifications confirmed with specimens, image-based analyses of deep-sea communities can be achieved with high confidence when (i) independent validation is provided by senior taxonomic specialists in taxa that are indicators of VMEs, such as cold-water coral reefs, coral gardens, sponge grounds, cold seeps and xenophyophore fields; and (ii) stronger consideration is given to methods in classical taxonomy, the chemical oceanographic setting and community ecology.

scholarly journals Time-to-event analysis in economic evaluations: a comparison of modelling methods to assess the cost-effectiveness of transplanting a marginal quality kidney

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sameera Senanayake ◽  
Nicholas Graves ◽  
Helen Healy ◽  
Keshwar Baboolal ◽  
Adrian Barnett ◽  
...  
Keyword(s):  
Cost Effectiveness ◽  
Time Horizon ◽  
Transition Probabilities ◽  
Discrete Event ◽  
Economic Evaluations ◽  
Event Analysis ◽  
Time To Event ◽  
Modelling Method ◽  
Cycle Lengths ◽  
Modelling Methods

Abstract Background Economic-evaluations using decision analytic models such as Markov-models (MM), and discrete-event-simulations (DES) are high value adds in allocating resources. The choice of modelling method is critical because an inappropriate model yields results that could lead to flawed decision making. The aim of this study was to compare cost-effectiveness when MM and DES were used to model results of transplanting a lower-quality kidney versus remaining waitlisted for a kidney. Methods Cost-effectiveness was assessed using MM and DES. We used parametric survival models to estimate the time-dependent transition probabilities of MM and distribution of time-to-event in DES. MMs were simulated in 12 and 6 monthly cycles, out to five and 20-year time horizon. Results DES model output had a close fit to the actual data. Irrespective of the modelling method, the cycle length of MM or the time horizon, transplanting a low-quality kidney as compared to remaining waitlisted was the dominant strategy. However, there were discrepancies in costs, effectiveness and net monetary benefit (NMB) among different modelling methods. The incremental NMB of the MM in the 6-months cycle lengths was a closer fit to the incremental NMB of the DES. The gap in the fit of the two cycle lengths to DES output reduced as the time horizon increased. Conclusion Different modelling methods were unlikely to influence the decision to accept a lower quality kidney transplant or remain waitlisted on dialysis. Both models produced similar results when time-dependant transition probabilities are used, most notable with shorter cycle lengths and longer time-horizons.

scholarly journals Mining Google and Apple mobility data: temporal anatomy for COVID-19 social distancing

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Corentin Cot ◽  
Giacomo Cacciapaglia ◽  
Francesco Sannino
Keyword(s):  
Infection Rate ◽  
The United States ◽  
Strong Decrease ◽  
Social Distancing ◽  
Mobility Data ◽  
Actual Measure ◽  
The Us ◽  
The Impact ◽  
Political Decisions ◽  
Mobility Reduction

AbstractWe employ the Google and Apple mobility data to identify, quantify and classify different degrees of social distancing and characterise their imprint on the first wave of the COVID-19 pandemic in Europe and in the United States. We identify the period of enacted social distancing via Google and Apple data, independently from the political decisions. Our analysis allows us to classify different shades of social distancing measures for the first wave of the pandemic. We observe a strong decrease in the infection rate occurring two to five weeks after the onset of mobility reduction. A universal time scale emerges, after which social distancing shows its impact. We further provide an actual measure of the impact of social distancing for each region, showing that the effect amounts to a reduction by 20–40% in the infection rate in Europe and 30–70% in the US.

scholarly journals The Impact of Probability Density Functions Assessment on Model Performance for Slope Stability Analysis

Geosciences ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 322
Author(s):  
Evelina Volpe ◽  
Luca Ciabatta ◽  
Diana Salciarini ◽  
Stefania Camici ◽  
Elisabetta Cattoni ◽  
...  
Keyword(s):  
Probability Density ◽  
Central Italy ◽  
Model Performance ◽  
Probability Density Functions ◽  
Slope Instability ◽  
Complex Nature ◽  
Density Functions ◽  
Umbria Region ◽  
Input Variables ◽  
The Impact

The development of forecasting models for the evaluation of potential slope instability after rainfall events represents an important issue for the scientific community. This topic has received considerable impetus due to the climate change effect on territories, as several studies demonstrate that an increase in global warming can significantly influence the landslide activity and stability conditions of natural and artificial slopes. A consolidated approach in evaluating rainfall-induced landslide hazard is based on the integration of rainfall forecasts and physically based (PB) predictive models through deterministic laws. However, considering the complex nature of the processes and the high variability of the random quantities involved, probabilistic approaches are recommended in order to obtain reliable predictions. A crucial aspect of the stochastic approach is represented by the definition of appropriate probability density functions (pdfs) to model the uncertainty of the input variables as this may have an important effect on the evaluation of the probability of failure (PoF). The role of the pdf definition on reliability analysis is discussed through a comparison of PoF maps generated using Monte Carlo (MC) simulations performed over a study area located in the Umbria region of central Italy. The study revealed that the use of uniform pdfs for the random input variables, often considered when a detailed geotechnical characterization for the soil is not available, could be inappropriate.

scholarly journals People exposed to traffic noise in european agglomerations from noise maps. A critical review

Noise Mapping ◽  
2014 ◽  
Vol 1 (1) ◽  
Author(s):  
Miguel Arana ◽  
Ricardo San Martin ◽  
Juan C. Salinas
Keyword(s):  
Road Traffic ◽  
Noise Source ◽  
Traffic Noise ◽  
Noise Pollution ◽  
Environmental Noise ◽  
Action Plans ◽  
Implementation Phase ◽  
Pollution Levels ◽  
Input Variables ◽  
The Impact

AbstractTwo of the main objectives of the European Directive on environmental noise are, firstly, to unify acoustic indices for assessing environmental noise and, secondly, to standardize assessment methodologies. The ultimate goal is to objectively and comparably manage the impact and evolution of environmental noise caused both by urban agglomerations and by traffic infrastructures (roads, rails and airports). The use of common indices and methodologies (together with five-year plan assessment required by the authorities in charge) should show how noise pollution levels are evolving plus the effectiveness of corrective measures implemented in the action plans. In this paper, available results fromnumerous European agglomerations (with particular emphasis on Spanish agglomerations) are compared and analysed. The impact and its evolution are based on the percentage of people exposed to noise. More specifically, it demonstrates the impact caused by road traffic, which proves to be the main noise source in all agglomerations. In many cases, the results are extremely remarkable. In some case, the results are illogical. For such cases, it can be concluded that either assessment methodologies have been signifi- cantly amended or the input variables to the calculation programs have been remarkably changed. The uncertainty associated with the results is such that, in our opinion, no conclusions can be drawn concerning the effectiveness of remedial measures designed within the action plans after the Directive’s first implementation Phase.

scholarly journals Virus-mediated archaeal hecatomb in the deep seafloor

2016 ◽  
Vol 2 (10) ◽  
pp. e1600492 ◽  
Author(s):  
Roberto Danovaro ◽  
Antonio Dell’Anno ◽  
Cinzia Corinaldesi ◽  
Eugenio Rastelli ◽  
Ricardo Cavicchioli ◽  
...  
Keyword(s):  
Viral Infection ◽  
Deep Sea ◽  
Viral Infections ◽  
Biogeochemical Cycles ◽  
Global Scale ◽  
Viral Lysis ◽  
Group I ◽  
Global Biogeochemical Cycles ◽  
Bacterial Genes ◽  
The Impact

Viruses are the most abundant biological entities in the world’s oceans, and they play a crucial role in global biogeochemical cycles. In deep-sea ecosystems, archaea and bacteria drive major nutrient cycles, and viruses are largely responsible for their mortality, thereby exerting important controls on microbial dynamics. However, the relative impact of viruses on archaea compared to bacteria is unknown, limiting our understanding of the factors controlling the functioning of marine systems at a global scale. We evaluate the selectivity of viral infections by using several independent approaches, including an innovative molecular method based on the quantification of archaeal versus bacterial genes released by viral lysis. We provide evidence that, in all oceanic surface sediments (from 1000- to 10,000-m water depth), the impact of viral infection is higher on archaea than on bacteria. We also found that, within deep-sea benthic archaea, the impact of viruses was mainly directed at members of specific clades of Marine Group I Thaumarchaeota. Although archaea represent, on average, ~12% of the total cell abundance in the top 50 cm of sediment, virus-induced lysis of archaea accounts for up to one-third of the total microbial biomass killed, resulting in the release of ~0.3 to 0.5 gigatons of carbon per year globally. Our results indicate that viral infection represents a key mechanism controlling the turnover of archaea in surface deep-sea sediments. We conclude that interactions between archaea and their viruses might play a profound, previously underestimated role in the functioning of deep-sea ecosystems and in global biogeochemical cycles.

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