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- Jakosky, B. M., et al.
(författare)
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MAVEN observations of the response of Mars to an interplanetary coronal mass ejection
- 2015
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Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 350:6261
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Tidskriftsartikel (refereegranskat)abstract
- Coupling between the lower and upper atmosphere, combined with loss of gas from the upper atmosphere to space, likely contributed to the thin, cold, dry atmosphere of modern Mars. To help understand ongoing ion loss to space, the Mars Atmosphere and Volatile Evolution (MAVEN) spacecraft made comprehensive measurements of the Mars upper atmosphere, ionosphere, and interactions with the Sun and solar wind during an interplanetary coronal mass ejection impact in March 2015. Responses include changes in the bow shock and magnetosheath, formation of widespread diffuse aurora, and enhancement of pick-up ions. Observations and models both show an enhancement in escape rate of ions to space during the event. Ion loss during solar events early in Mars history may have been a major contributor to the long-term evolution of the Mars atmosphere.
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- Ketzer, João Marcelo, et al.
(författare)
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Gravity complexes as a focus of seafloor fluid seepage : the Rio Grande Cone, SE Brazil
- 2023
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Ingår i: Scientific Reports. - : Nature Publishing Group. - 2045-2322. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- Seafloor methane emissions can affect Earth’s climate and ocean chemistry. Vast quantities of methane formed by microbial decomposition of organic matter are locked within gas hydrate and free gas on continental slopes, particularly in large areas with high sediment accumulations such as deep-sea fans. The release of methane in slope environments has frequently been associated with dissociation of gas hydrates near the edge of the gas hydrate stability zone on the upper slope, with discharges in greater water depths less understood. Here we show, using data from the Rio Grande Cone (western South Atlantic), that the intrinsic, gravity-induced downslope collapse of thick slope sediment accumulations creates structures that serve as pathways for gas migration, unlocking methane and causing seafloor emissions via giant gas flares in the water column. The observed emissions in the study region (up to 310 Mg year−1) are three times greater than estimates for the entire US North Atlantic margin and reveal the importance of collapsing sediment accumulations for ocean carbon cycling. Similar outgassing systems on the Amazon and Niger fans suggest that gravity tectonics on passive margins is a common yet overlooked mechanism driving massive seafloor methane emissions in sediment-laden continental slopes. © 2023, The Author(s).
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| 6. |
- Sheykhifard, Z., et al.
(författare)
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Magnetic graphene/Ni-nano-crystal hybrid for small field magnetoresistive effect synthesized via electrochemical exfoliation/deposition technique
- 2018
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Ingår i: Journal of Materials Science-Materials in Electronics. - : Springer Science and Business Media LLC. - 0957-4522 .- 1573-482X. ; 29:5, s. 4171-4178
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Tidskriftsartikel (refereegranskat)abstract
- Two-dimensional heterostructures of graphene (Gr) and metal/semiconducting elements convey new direction in electronic devices. They can be useful for spintronics because of small spin orbit interaction of Gr as a non-magnetic metal host with promising electrochemical stability. In this paper, we demonstrate one-step fabrication of magnetic Ni-particles entrapped within Gr-flakes based on simultaneous electrochemical exfoliation/deposition procedure by two-electrode system using platinum as the cathode electrode and a graphite foil as the anode electrode. The final product is an air stable hybrid element including Gr flakes hosting magnetic Ni-nano-crystals showing superparamagnetic-like response and room temperature giant magnetoresistance (GMR) effect at small magnetic field range. The GMR effect is originated from spin scattering through ferromagnetic/non-magnetic nature of Ni/Gr heterostructure and interpreted based on a phenomenological spin transport model. Our work benefits from XRD, XPS, Raman, TEM, FTIR and VSM measurements We addressed that how our results can be used for rapid manufacturing of magnetic Gr for low field magneto resistive elements and potential printed spintronic devices.
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| 7. |
- Ketzer, João Marcelo, et al.
(författare)
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Gas hydrate dissociation linked to contemporary ocean warming in the southern hemisphere
- 2020
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Ingår i: Nature Communications. - : Nature Publishing Group. - 2041-1723. ; 11:1, s. 1-9
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Tidskriftsartikel (refereegranskat)abstract
- Ocean warming related to climate change has been proposed to cause the dissociation of gas hydrate deposits and methane leakage on the seafloor. This process occurs in places where the edge of the gas hydrate stability zone in sediments meets the overlying warmer oceans in upper slope settings. Here we present new evidence based on the analysis of a large multi-disciplinary and multi-scale dataset from such a location in the western South Atlantic, which records massive gas release to the ocean. The results provide a unique opportunity to examine ocean-hydrate interactions over millennial and decadal scales, and the first evidence from the southern hemisphere for the effects of contemporary ocean warming on gas hydrate stability. Widespread hydrate dissociation results in a highly focused advective methane flux that is not fully accessible to anaerobic oxidation, challenging the assumption that it is mostly consumed by sulfate reduction before reaching the seafloor.
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- Rahmati, O., et al.
(författare)
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Development of novel hybridized models for urban flood susceptibility mapping
- 2020
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Ingår i: Scientific Reports. - : Nature Research. - 2045-2322. ; 10:1
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Tidskriftsartikel (refereegranskat)abstract
- Floods in urban environments often result in loss of life and destruction of property, with many negative socio-economic effects. However, the application of most flood prediction models still remains challenging due to data scarcity. This creates a need to develop novel hybridized models based on historical urban flood events, using, e.g., metaheuristic optimization algorithms and wavelet analysis. The hybridized models examined in this study (Wavelet-SVR-Bat and Wavelet-SVR-GWO), designed as intelligent systems, consist of a support vector regression (SVR), integrated with a combination of wavelet transform and metaheuristic optimization algorithms, including the grey wolf optimizer (GWO), and the bat optimizer (Bat). The efficiency of the novel hybridized and standalone SVR models for spatial modeling of urban flood inundation was evaluated using different cutoff-dependent and cutoff-independent evaluation criteria, including area under the receiver operating characteristic curve (AUC), Accuracy (A), Matthews Correlation Coefficient (MCC), Misclassification Rate (MR), and F-score. The results demonstrated that both hybridized models had very high performance (Wavelet-SVR-GWO: AUC = 0.981, A = 0.92, MCC = 0.86, MR = 0.07; Wavelet-SVR-Bat: AUC = 0.972, A = 0.88, MCC = 0.76, MR = 0.11) compared with the standalone SVR (AUC = 0.917, A = 0.85, MCC = 0.7, MR = 0.15). Therefore, these hybridized models are a promising, cost-effective method for spatial modeling of urban flood susceptibility and for providing in-depth insights to guide flood preparedness and emergency response services.
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| 9. |
- Darabi, H., et al.
(författare)
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Development of a novel hybrid multi-boosting neural network model for spatial prediction of urban flood
- 2021
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Ingår i: Geocarto International. - : Taylor and Francis Ltd.. - 1010-6049 .- 1752-0762.
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Tidskriftsartikel (refereegranskat)abstract
- In this study, a new hybridized machine learning algorithm for urban flood susceptibility mapping, named MultiB-MLPNN, was developed using a multi-boosting technique and MLPNN. The model was tested in Amol City, Iran, a data-scarce city in an ungauged area which is prone to severe flood inundation events and currently lacks flood prevention infrastructure. Performance of the hybridized model was compared with that of a standalone MLPNN model, random forest and boosted regression trees. Area under the curve, efficiency, true skill statistic, Matthews correlation coefficient, misclassification rate, sensitivity and specificity were used to evaluate model performance. In validation, the MultiB-MLPNN model showed the best predictive performance. The hybridized MultiB-MLPNN model is thus useful for generating realistic flood susceptibility maps for data-scarce urban areas. The maps can be used to develop risk-reduction measures to protect urban areas from devastating floods, particularly where available data are insufficient to support physically based hydrological or hydraulic models.
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| 10. |
- Haghighi, Mona, et al.
(författare)
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A Comparison of Rule-based Analysis with Regression Methods in Understanding the Risk Factors for Study Withdrawal in a Pediatric Study
- 2016
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 6
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Tidskriftsartikel (refereegranskat)abstract
- Regression models are extensively used in many epidemiological studies to understand the linkage between specific outcomes of interest and their risk factors. However, regression models in general examine the average effects of the risk factors and ignore subgroups with different risk profiles. As a result, interventions are often geared towards the average member of the population, without consideration of the special health needs of different subgroups within the population. This paper demonstrates the value of using rule-based analysis methods that can identify subgroups with heterogeneous risk profiles in a population without imposing assumptions on the subgroups or method. The rules define the risk pattern of subsets of individuals by not only considering the interactions between the risk factors but also their ranges. We compared the rule-based analysis results with the results from a logistic regression model in The Environmental Determinants of Diabetes in the Young (TEDDY) study. Both methods detected a similar suite of risk factors, but the rule-based analysis was superior at detecting multiple interactions between the risk factors that characterize the subgroups. A further investigation of the particular characteristics of each subgroup may detect the special health needs of the subgroup and lead to tailored interventions.
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