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  1. Article: Short-term forecasting of saltwater occurrence at La Comté River (French Guiana) using a kernel-based support vector machine

    Rohmer, J / N. Brisset

    Environmental earth sciences. 2017 Mar., v. 76, no. 6

    2017  

    Abstract: Saltwater intrusion into rivers is a major concern for freshwater exploitation and management in French Guiana (South America). To detect and analyse saltwater occurrence, a permanent station was installed on La Comté River to measure the electrical ... ...

    Abstract Saltwater intrusion into rivers is a major concern for freshwater exploitation and management in French Guiana (South America). To detect and analyse saltwater occurrence, a permanent station was installed on La Comté River to measure the electrical conductivity C. The objective of the present study was twofold. First, the temporal link between C, sea water level SWL and river discharge Q was explored during the dry seasons from 2009 to 2012 (total measurement duration of ~6 months). A lag of 3 h between C and SWL was evidenced (i.e. the C peaks are delayed by 3 h with high water conditions), as well as the co-occurrence of sea water intrusion with the low Q period. Second, a data-driven approach was set up through a kernel-based support vector machine SVM technique to forecast two events: (1) the forthcoming maximum value of C (for the next 3 h) exceeds 500 µS/cm; (2) C exceeds 500 µS/cm during more than 2 h. One potential drawback of such a data-driven approach is to fail to predict outside the range of calibration: this issue was thoroughly explored by means of an intensive bootstrap-based test exercise. It was showed that SVM has very high degree of predictive capability with accuracy and area under receiver operator curve above 90% in average. We additionally analyse the practical implementation of the SVM model with comparison to alternative popular classification techniques (logistic regression, random forest, linear and quadratic discriminant analysis): the SVM strength is to provide the nonlinear decision boundary without making a priori restrictive assumptions on its shape (like linear or quadratic methods) and without being too sensitive to noisy observations/outliers. Yet this strength can turn to be a weakness unless a careful examination of the shape is done from a physical perspective.
    Keywords discriminant analysis ; dry season ; electrical conductivity ; freshwater ; models ; regression analysis ; rivers ; saline water ; saltwater intrusion ; seawater ; stream flow ; support vector machines ; French Guiana
    Language English
    Dates of publication 2017-03
    Size p. 246.
    Publishing place Springer Berlin Heidelberg
    Document type Article
    ZDB-ID 2493699-6
    ISSN 1866-6299 ; 1866-6280
    ISSN (online) 1866-6299
    ISSN 1866-6280
    DOI 10.1007/s12665-017-6553-5
    Database NAL-Catalogue (AGRICOLA)

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  2. Article ; Online: High levels of TNFα in patients with COVID-19 refractory to tocilizumab.

    Danlos, F X / Ackermann, F / Rohmer, J / Roumier, M / Marabelle, A / Michot, J M

    European journal of cancer (Oxford, England : 1990)

    2021  Volume 149, Page(s) 102–104

    MeSH term(s) Antibodies, Monoclonal, Humanized ; COVID-19/drug therapy ; Humans ; SARS-CoV-2 ; Tumor Necrosis Factor-alpha
    Chemical Substances Antibodies, Monoclonal, Humanized ; Tumor Necrosis Factor-alpha ; tocilizumab (I031V2H011)
    Language English
    Publishing date 2021-03-20
    Publishing country England
    Document type Letter ; Comment
    ZDB-ID 82061-1
    ISSN 1879-0852 ; 0277-5379 ; 0959-8049 ; 0964-1947
    ISSN (online) 1879-0852
    ISSN 0277-5379 ; 0959-8049 ; 0964-1947
    DOI 10.1016/j.ejca.2021.01.056
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 456: Show issues Location:
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    Zs.MO 583: Show issues

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  3. Book ; Online: Analysing the spatial patterns of erosion scars using point process theory at the coastal chalk cliff of Mesnil-Val, Normandy, northern France

    Rohmer, J. / Dewez, T.

    eISSN: 1684-9981

    2018  

    Abstract: Over the last decade, many cliff erosion studies have focused on frequency-size statistics using inventories of sea cliff retreat sizes. By comparison, only a few paid attention to quantifying the spatial and temporal organisation of erosion scars over a ...

    Abstract Over the last decade, many cliff erosion studies have focused on frequency-size statistics using inventories of sea cliff retreat sizes. By comparison, only a few paid attention to quantifying the spatial and temporal organisation of erosion scars over a cliff face. Yet, this spatial organisation carries essential information about the external processes and the environmental conditions that promote or initiate sea-cliff instabilities. In this article, we use summary statistics of spatial point process theory as a tool to examine the spatial and temporal pattern of a rockfall inventory recorded with repeated terrestrial laser scanning surveys at the chalk coastal cliff site of Mesnil-Val (Normandy, France). Results show that: (1) the spatial density of erosion scars is specifically conditioned alongshore by the distance to an engineered concrete groyne, with an exponential-like decreasing trend, and vertically focused both at wave breaker height and on strong lithological contrasts; (2) small erosion scars (10 −3 to 10 −2 m 3 ) aggregate in clusters within a radius of 5 to 10 m, which suggests some sort of attraction or focused causative process, and disperse above this critical distance; (3) on the contrary, larger erosion scars (10 −2 to 10 1 m 3 ) tend to disperse above a radius of 1 to 5 m, possibly due to the spreading of successive failures across the cliff face; (4) large scars significantly occur albeit moderately, where previous large rockfalls have occurred during preceding winter; (5) this temporal trend is not apparent for small events. In conclusion, this study shows, with a worked example, how spatial point process summary statistics are a tool to test and quantify the significance of geomorphological observation organisation.
    Subject code 333
    Language English
    Publishing date 2018-09-27
    Publishing country de
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article: Revealing the interlevel dependence structure of categorical inputs in numerical environmental simulations with kernel model selection

    Rohmer, Jeremy / Roustant, Olivier / Lecacheux, Sophie / Manceau, Jean-Charles

    Environmental modelling & software. 2022 Mar. 10,

    2022  

    Abstract: Model uncertainties are generally integrated in environmental long-running numerical simulators via a categorical variable. By focusing on Gaussian process (GP) models, we show how different categorical kernel models (exchangeable, ordinal, group, etc.) ... ...

    Abstract Model uncertainties are generally integrated in environmental long-running numerical simulators via a categorical variable. By focusing on Gaussian process (GP) models, we show how different categorical kernel models (exchangeable, ordinal, group, etc.) can bring valuable insights into the correlation of the simulator output values computed for different levels of the categorical variable, i.e., the interlevel dependence structure. Supported by two real case applications (cyclone-induced waves and reservoir modeling), we have proposed a cross-validation approach to select the most appropriate kernel by finding a trade-off between predictability, explainability, and stability of the covariance coefficients. This approach can be used effectively to support some physical assumptions regarding the categorical variable. Through comparison to tree-based techniques, we show that GP models can be considered a satisfactory compromise when only a few model runs (∼100) are available by presenting a high predictability and a concise and graphical way to map the interlevel dependence structure.
    Keywords computer software ; covariance ; normal distribution
    Language English
    Dates of publication 2022-0310
    Publishing place Elsevier Ltd
    Document type Article
    Note Pre-press version
    ISSN 1364-8152
    DOI 10.1016/j.envsoft.2022.105380
    Database NAL-Catalogue (AGRICOLA)

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  5. Article ; Online: Extensive DVT and Pulmonary Embolism Leading to the Diagnosis of Coronavirus Disease 2019 in the Absence of Severe Acute Respiratory Syndrome Coronavirus 2 Pneumonia.

    Delcros, Quentin / Rohmer, Julien / Tcherakian, Colas / Groh, Matthieu

    Chest

    2020  Volume 158, Issue 6, Page(s) e269–e271

    Abstract: There is growing evidence that coronavirus disease 2019 (COVID-19) is associated with a hypercoagulable state. To date, all patients reported with venous thromboembolic disease and COVID-19 have shown evidence of viral pneumonia. Here, we report the case ...

    Abstract There is growing evidence that coronavirus disease 2019 (COVID-19) is associated with a hypercoagulable state. To date, all patients reported with venous thromboembolic disease and COVID-19 have shown evidence of viral pneumonia. Here, we report the case of a 31-year-old patient with unexplained extensive DVT and bilateral pulmonary embolism in the absence of COVID-19 pneumonia, leading to the diagnosis of otherwise asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. In the context of the COVID-19 pandemic, given the high rates of otherwise asymptomatic patients, testing for SARS-CoV-2 should be performed in all patients with unexplained VTE occurring in COVID-19-endemic areas, even in the absence of other disease manifestations suggestive of SARS-CoV-2 infection.
    MeSH term(s) Adult ; COVID-19/complications ; COVID-19/diagnosis ; COVID-19/therapy ; Humans ; Pulmonary Embolism/diagnosis ; Pulmonary Embolism/therapy ; Pulmonary Embolism/virology ; SARS-CoV-2 ; Venous Thrombosis/diagnosis ; Venous Thrombosis/therapy ; Venous Thrombosis/virology
    Language English
    Publishing date 2020-12-21
    Publishing country United States
    Document type Case Reports ; Journal Article
    ZDB-ID 1032552-9
    ISSN 1931-3543 ; 0012-3692
    ISSN (online) 1931-3543
    ISSN 0012-3692
    DOI 10.1016/j.chest.2020.06.024
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.MO 349: Show issues

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  6. Article: A nuanced quantile random forest approach for fast prediction of a stochastic marine flooding simulator applied to a macrotidal coastal site

    Rohmer, Jeremy / Idier, Deborah / Pedreros, Rodrigo

    Stochastic environmental research and risk assessment. 2020 June, v. 34, no. 6

    2020  

    Abstract: Integrating full-process high resolution hydrodynamic simulations within early warning system (EWS) for marine flooding is hindered by the large computation time cost of such numerical models. This problem can be alleviated through the statistical ... ...

    Abstract Integrating full-process high resolution hydrodynamic simulations within early warning system (EWS) for marine flooding is hindered by the large computation time cost of such numerical models. This problem can be alleviated through the statistical analysis of pre-calculated simulation results to build a fast (low computation time cost) statistical predictive model (named metamodel). Despite the success of this approach, a direct application of such techniques for EWS is not straightforward in all settings, more particularly in environments where the stochastic character of waves has a significant effect on the induced flood, i.e., where overtopping is on a duration smaller than 500 times the offshore wave period. In such environments, the numerical simulator is not deterministic and provides statistical quantities of the flooding indicators. By focusing on the estimates of quantiles, the objective of the present study is to explore the applicability of random forest (RF) models for marine flooding prediction by providing two levels of information: (1) the quantile of interest via a quantile random forest regression model (qRF); (2) the flooding probability via a classification random forest (cRF). We use the macrotidal site of Gâvres (French Atlantic coast) as an application case for which ~ 2000 numerical simulations were performed (i.e. stochastic simulations given 100 different extreme-but-realistic offshore meteo-oceanic input conditions were repeated 20 times) to compute local and global flooding indicators (respectively the maximum water depth at the coast and the total volume of water entering the territory). Through an extensive repeated cross-validation procedure, we tune the qRF parameters leading to high coefficient of determination of ~ 90% for the quantiles at 25–50–75%, and we show that the qRF models outperform the commonly used Tobit regression model. The comparison with the numerical results on historical events shows very satisfactory prediction for events both leading to major flooding and to absence of impact. For low quantile level and minor-to-moderate flooding events, the second level provided by the cRF-derived flooding probability shows its added value by enabling the EWS user to nuance the qRF prediction and to tag some situations where the prediction remains unsure.
    Keywords algorithms ; coasts ; early warning systems ; hydrodynamics ; mathematical models ; prediction ; probability ; regression analysis
    Language English
    Dates of publication 2020-06
    Size p. 867-890.
    Publishing place Springer Berlin Heidelberg
    Document type Article
    ZDB-ID 1481263-0
    ISSN 1436-3259 ; 1435-151X ; 1436-3240 ; 0931-1955
    ISSN (online) 1436-3259 ; 1435-151X
    ISSN 1436-3240 ; 0931-1955
    DOI 10.1007/s00477-020-01803-2
    Database NAL-Catalogue (AGRICOLA)

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  7. Book ; Online: Multioutput Gaussian Processes with Functional Data

    López-Lopera, A. F. / Idier, D. / Rohmer, J. / Bachoc, F.

    A Study on Coastal Flood Hazard Assessment

    2020  

    Abstract: Surrogate models are often used to replace costly-to-evaluate complex coastal codes to achieve substantial computational savings. In many of those models, the hydrometeorological forcing conditions (inputs) or flood events (outputs) are conveniently ... ...

    Abstract Surrogate models are often used to replace costly-to-evaluate complex coastal codes to achieve substantial computational savings. In many of those models, the hydrometeorological forcing conditions (inputs) or flood events (outputs) are conveniently parameterized by scalar representations, neglecting that the inputs are actually time series and that floods propagate spatially inland. Both facts are crucial in flood prediction for complex coastal systems. Our aim is to establish a surrogate model that accounts for time-varying inputs and provides information on spatially varying inland flooding. We introduce a multioutput Gaussian process model based on a separable kernel that correlates both functional inputs and spatial locations. Efficient implementations consider tensor-structured computations or sparse-variational approximations. In several experiments, we demonstrate the versatility of the model for both learning maps and inferring unobserved maps, numerically showing the convergence of predictions as the number of learning maps increases. We assess our framework in a coastal flood prediction application. Predictions are obtained with small error values within computation time highly compatible with short-term forecast requirements (on the order of minutes compared to the days required by hydrodynamic simulators). We conclude that our framework is a promising approach for forecast and early-warning systems.
    Keywords Statistics - Machine Learning ; Computer Science - Machine Learning ; Statistics - Applications
    Subject code 006
    Publishing date 2020-07-28
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Conference proceedings ; Online: Evidence for remotely triggered microearthquakes during salt cavern collapse

    Jousset, P. / Rohmer, J.

    Geophysical Research Abstracts

    2016  

    Publishing country de
    Document type Conference proceedings ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article: Mechano-chemical interactions in sedimentary rocks in the context of CO2 storage: Weak acid, weak effects?

    Rohmer, J / A. Pluymakers / F. Renard

    Earth-science reviews. 2016 June, v. 157

    2016  

    Abstract: Due to the corrosive nature of dissolved CO2, the potential short or long term alteration of rock properties, represents a major issue in several sites where natural CO2 circulation is observed, as well as in reservoirs targeted for storage of ... ...

    Abstract Due to the corrosive nature of dissolved CO2, the potential short or long term alteration of rock properties, represents a major issue in several sites where natural CO2 circulation is observed, as well as in reservoirs targeted for storage of anthropogenic CO2. To date, this has been primarily studied from a transport-chemical perspective, with laboratory evidence of microstructural modifications together with the consequences for flow properties. Compared to the transport-chemical aspects, the mechanical-chemical aspects have been less investigated, though it is to be expected that mechanical properties (e.g. elastic properties, failure parameters, and time-dependent mechanical behaviour) could potentially be affected in a similar manner to hydraulic parameters. Yet, since CO2 is a weak acid, the pH drop is expected to be moderate with a likely lower limit close to 4.0. The buffering of pH by calcite minerals present in most reservoirs targeted for storage may further limit the pH drop, as well as confining it to a localized rock volume around the injection well. This leads to the question of the magnitude and time/spatial scales of chemically-mediated mechanical processes during CO2 sequestration. The authors propose to address this issue by reviewing recent laboratory-based studies restricted to sedimentary rocks, namely: reservoir rocks (carbonate or sandstone), intact or fractured caprocks and fault rocks. Key findings include the following: 1. the short-term impact on the elastic and inelastic behaviour of intact caprocks remains limited; 2. shear strength weakening is likely to be respectively low and low-to-moderate for shale/clay-rich and anhydrite-rich faults, but without modifying slip stability in either case; 3. the largest impact is located within carbonate reservoirs, but with a broad range of reported responses depending on hydrodynamic conditions (closed or open) and on dissolution regime (uniform or channelling); and 4. creep experiments confirm that CO2-induced dissolution may enhance long-term compaction of carbonate reservoirs, but the magnitude of acceleration (varying from non-significant to 50 times) depends to a large extent on site-specific conditions (grain size, pH, temperature, effective stress state, etc.), which renders any direct extrapolation from laboratory to reservoir scale difficult. Finally, some directions for future research studies are discussed.
    Keywords calcite ; carbon dioxide ; carbon sequestration ; dissolved carbon dioxide ; hydrodynamics ; pH ; sandstone ; shear strength ; temperature
    Language English
    Dates of publication 2016-06
    Size p. 86-110.
    Publishing place Elsevier B.V.
    Document type Article
    ZDB-ID 1792-9
    ISSN 0012-8252
    ISSN 0012-8252
    DOI 10.1016/j.earscirev.2016.03.009
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    In stock of ZB MED Bonn / Germany

    Z 69/92: Show issues

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  10. Article: Source characterisation by mixing long-running tsunami wave numerical simulations and historical observations within a metamodel-aided ABC setting

    Rohmer, J / M. Rousseau / A. Lemoine / R. Pedreros / J. Lambert / A. Benki

    Stochastic environmental research and risk assessment. 2018 Apr., v. 32, no. 4

    2018  

    Abstract: Uncertainty related to the source parameters of earthquake can largely impact the tsunami-induced wave characteristics, especially in the case of near-field tsunami source. The combination of numerical simulations and historical eyewitness accounts can ... ...

    Abstract Uncertainty related to the source parameters of earthquake can largely impact the tsunami-induced wave characteristics, especially in the case of near-field tsunami source. The combination of numerical simulations and historical eyewitness accounts can be used to better constrain those uncertainties. In the present study, we propose a Bayesian procedure to infer (i.e. learn) the probability distribution of the source parameters of the earthquake. The strategy is based on the combination of: (1) kriging-based metamodelling techniques to overcome the high computation time cost of the numerical simulator; and (2) Approximate Bayesian Computation (ABC) procedure to perform the Bayesian inference. The procedure is applied to the Ligurian (North West of Italy) 1887 tsunami case, for which tsunami-induced sea surface elevations at the coast have been reported at four locations, namely Marseille, Imperia, Diano-Marina and Genoa. The kriging metamodels are trained using only 300 long-running numerical simulations that were performed using the FUNWAVE-TVD code. Contrary to recent inversion exercises that can benefit from current modern observation networks (like tide gauges, sea bottom pressure gauges, GPS-mounted buoys), the case of historical tsunami like Liguria is complicated by the imprecision and scarcity of the observations: this is accounted for by conducting the combined ABC-kriging procedure a large number of times (i.e. 1000); each time a new set of observations being randomly generated to account for this observational error. The combined analysis of the inference results and of the observation uncertainty reveals that: (1) the coseismic slip is the most important source parameter with a very peaky density distribution around low values ranging from 0.3 to 0.6 m; (2) The fault width has a peaky density distribution around low values ranging from 10 to 12 km; (3) The rake and azimuth distribution only slightly deviate from the uniform prior, hence indicating a low influence of those parameters; (4) The bi-modal distribution of the dip is also evidenced.
    Keywords Bayesian theory ; coasts ; earthquakes ; kriging ; mathematical models ; mixing ; pressure gauges ; probability distribution ; tsunamis ; uncertainty ; Italy
    Language English
    Dates of publication 2018-04
    Size p. 967-984.
    Publishing place Springer Berlin Heidelberg
    Document type Article
    ZDB-ID 1481263-0
    ISSN 1436-3259 ; 1436-3240 ; 0931-1955
    ISSN (online) 1436-3259
    ISSN 1436-3240 ; 0931-1955
    DOI 10.1007/s00477-017-1423-y
    Database NAL-Catalogue (AGRICOLA)

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