Soil organic carbon mobility in equatorial podzols: soil column experiments

Transfer of organic carbon from topsoil horizons to deeper horizons and to the water table is still little documented, in particular in equatorial environments, despite the high primary productivity of the evergreen forest. Due to its complexing capacity, organic carbon also plays a key role in the transfer of metals in the soil profile and, therefore, in pedogenesis and for metal mobility. Here we focus on equatorial podzols, which are known to play an important role in carbon cycling. We carried out soil column experiments using soil material and percolating solution sampled in an Amazonian podzol area in order to better constrain the conditions of the transfer of organic carbon at depth. The dissolved organic matter (DOM) produced in the topsoil was not able to percolate through the clayey, kaolinitic material from the deep horizons and was retained in it. When it previously percolated through the Bh material, there was production of fulvic-like, protein-like compounds and small carboxylic acids able to percolate through the clayey material and increase the mobility of Al, Fe and Si. Podzolic processes in the Bh can, therefore, produce a DOM likely to be transferred to the deep water table, playing a role in the carbon balances at the profile scale and, owing to its complexing capacity, playing a role in deep horizon pedogenesis and weathering. The order of magnitude of carbon concentration in the solution percolating at depth was around 1.5–2.5 mg L−1. Our findings reveal a fundamental mechanism that favors the formation of very thick kaolinitic saprolites.

Soil organic carbon mobility in equatorial podzols: soil column experiments

Transfer of organic carbon from topsoil horizons to deeper horizons and to water table is still little documented, in particular in equatorial environments despite the high primary productivity of the evergreen forest. Due to its complexing capacity, organic carbon also plays a key role in the transfer of metals in the soil profile and therefore in pedogenesis and for metal mobility. We were interested in equatorial podzols, which are known to play a significant role in carbon cycling. We carried out soil column experiments using soil material and percolating solution sampled in an Amazonian podzol area. The dissolved organic matter (DOM) produced in the topsoil was not able to percolate through the clayey, kaolinitic material from the deep horizons and was retained in it. When it previously percolated through the Bh material, there was production of fulvic-like, protein-like compounds and small carboxylic acids able to percolate through the clayey material and increasing the mobility of Al, Fe and Si. Podzolic processes in the Bh can therefore produce a DOM likely to be transferred to the deep water table, playing a role in the carbon balances at the profile scale, and owing to its complexing capacity, playing a role in deep horizon pedogenesis and weathering. The order of magnitude of carbon concentration in the solution percolating in depth was around 1.5–2.5 mg L−1.

Deep Horizon: A machine learning network that recovers accreting black hole parameters

Context. The Event Horizon Telescope recently observed the first shadow of a black hole. Images like this can potentially be used to test or constrain theories of gravity and deepen the understanding in plasma physics at event horizon scales, which requires accurate parameter estimations. Aims. In this work, we present Deep Horizon, two convolutional deep neural networks that recover the physical parameters from images of black hole shadows. We investigate the effects of a limited telescope resolution and observations at higher frequencies. Methods. We trained two convolutional deep neural networks on a large image library of simulated mock data. The first network is a Bayesian deep neural regression network and is used to recover the viewing angle i, and position angle, mass accretion rate Ṁ, electron heating prescription Rhigh and the black hole mass MBH. The second network is a classification network that recovers the black hole spin a. Results. We find that with the current resolution of the Event Horizon Telescope, it is only possible to accurately recover a limited number of parameters of a static image, namely the mass and mass accretion rate. Since potential future space-based observing missions will operate at frequencies above 230 GHz, we also investigated the applicability of our network at a frequency of 690 GHz. The expected resolution of space-based missions is higher than the current resolution of the Event Horizon Telescope, and we show that Deep Horizon can accurately recover the parameters of simulated observations with a comparable resolution to such missions.

Organic Carbon and Nitrogen stocks in two soil types of Northwestern Tunisia: Temporal and spatial variation

<p>Soil organic matter has generated international interest in carbon and nitrogen sequestration. In reality, small fluctuations of soil organic stock could have large impacts on global warming. Therefore, quantification of Soil Organic Carbon (SOCs) and Total Nitrogen (TNs) stocks in surface and deep horizons are important to control the release of greenhouse gases. The present research was undertaken in order to determine SOCs and TNs evolution over 50 years. For this aim, we selected two soils (P1 and P2) developed under contrasted pedogenetic conditions in North-West of Tunisia (Beja governorate). P1 is a Luvisol located in a forest region. However, P2 is a Cambisol situated in an agriculture zone. Soil samples were gathered from surface (0-30 cm) and deep (50-100 cm) horizons in 1971, 2005, 2012 and 2019. SOCs declined in surface and deep horizons during the experimental period in both studied soils. In the case of Luvisol, the values declined from 91.01 t/ha to 75.54 t/ha and from 53.00 t/ha to 24.51 t/ha, respectively in surface horizons and deep horizons. Likewise, the SOCs values decreased from 84.24 t/ha to 25.52 t/ha in surface horizons and from 24.45 t/ha to 14.20 t/ha in deep horizons of the Cambisol. The TNs recorded lower values than SOCs. Nevertheless, they showed the same behavior. Our results showed that the highest values of SOCs and TNs were recorded in the Luvisol. This soil exhibited the greatest amount of organic matter since it was developed under forest vegetation. In addition, the results showed an enrichment in SOCs and TNs of superficial horizons to the detriment of the deep horizons. Nevertheless, this decrease in organic stocks with depth occurred following different patterns according to soil type. In fact, the Cambisol reported an important depletion of soil organic stocks as compared to the Luvisol. The loss of SOCs and TNs were estimated to be 69.71% and 54.17% in surface horizon, and 41.94 % and 28.28 % in deep horizon, respectively. Indeed, the land-use change increases the decomposition of soil organic matter principal source of SOCs and TNs. Such a reduction has wider implications on global warming and soil fertility.  </p>

St. Elijah and the Fairies. Understanding a Charm Through Legends

The images, characters, and events featured in a charm enter into mutual, organic relations with other images, characters, and events that are not explicitly included in the given text but contribute implicitly to the overall significance of the charm. The aim of the current article is to reveal the unspoken components of St. Elijah narrative file embedded in the deep horizon of beliefs and knowledge implied by a given charm. Following the charm step by step, I point out items that imply the unvoiced – but still present – level of images and beliefs taken from the non-charming narrative corpus.

LARGE OIL SPILL CLASSIFICATION USING SAR IMAGES BASED ON SPATIAL HISTOGRAM

Among the different types of marine pollution, oil spill is a major threat to the sea ecosystems. Remote sensing is used in oil spill response. Synthetic Aperture Radar (SAR) is an active microwave sensor that operates under all weather conditions and provides information about the surface roughness and covers large areas at a high spatial resolution. SAR is widely used to identify and track pollutants in the sea, which may be due to a secondary effect of a large natural disaster or by a man-made one . The detection of oil spill in SAR imagery relies on the decrease of the backscattering from the sea surface, due to the increased viscosity, resulting in a dark formation that contrasts with the brightness of the surrounding area. <br><br> Most of the use of SAR images for oil spill detection is done by visual interpretation. Trained interpreters scan the image, and mark areas of low backscatter and where shape is a-symmetrical. It is very difficult to apply this method for a wide area. In contrast to visual interpretation, automatic detection algorithms were suggested and are mainly based on scanning dark formations, extracting features, and applying big data analysis. <br><br> We propose a new algorithm that applies a nonlinear spatial filter that detects dark formations and is not susceptible to noises, such as internal or speckle. The advantages of this algorithm are both in run time and the results retrieved. The algorithm was tested in genesimulations as well as on COSMO-SkyMed images, detecting the Deep Horizon oil spill in the Gulf of Mexico (occurred on 20/4/2010). The simulation results show that even in a noisy environment, oil spill is detected. Applying the algorithm to the Deep Horizon oil spill, the algorithm classified the oil spill better than focusing on dark formation algorithm. Furthermore, the results were validated by the National Oceanic and Atmospheric Administration (NOAA) data.

LARGE OIL SPILL CLASSIFICATION USING SAR IMAGES BASED ON SPATIAL HISTOGRAM

Among the different types of marine pollution, oil spill is a major threat to the sea ecosystems. Remote sensing is used in oil spill response. Synthetic Aperture Radar (SAR) is an active microwave sensor that operates under all weather conditions and provides information about the surface roughness and covers large areas at a high spatial resolution. SAR is widely used to identify and track pollutants in the sea, which may be due to a secondary effect of a large natural disaster or by a man-made one . The detection of oil spill in SAR imagery relies on the decrease of the backscattering from the sea surface, due to the increased viscosity, resulting in a dark formation that contrasts with the brightness of the surrounding area. <br><br> Most of the use of SAR images for oil spill detection is done by visual interpretation. Trained interpreters scan the image, and mark areas of low backscatter and where shape is a-symmetrical. It is very difficult to apply this method for a wide area. In contrast to visual interpretation, automatic detection algorithms were suggested and are mainly based on scanning dark formations, extracting features, and applying big data analysis. <br><br> We propose a new algorithm that applies a nonlinear spatial filter that detects dark formations and is not susceptible to noises, such as internal or speckle. The advantages of this algorithm are both in run time and the results retrieved. The algorithm was tested in genesimulations as well as on COSMO-SkyMed images, detecting the Deep Horizon oil spill in the Gulf of Mexico (occurred on 20/4/2010). The simulation results show that even in a noisy environment, oil spill is detected. Applying the algorithm to the Deep Horizon oil spill, the algorithm classified the oil spill better than focusing on dark formation algorithm. Furthermore, the results were validated by the National Oceanic and Atmospheric Administration (NOAA) data.

Chemical Process of Carex meyeriana Mire Wetland in Wuyiling in Yichun in Northeast China

The content of total and soluble elements in different soil profiles of Carex meyeriana mire wetland changed in different seasons, and moved in deep horizon of soil. The correlation among each element in soil profiles was different. As far as the element content of Carex meyeriana fraction is concerned, nitrogen in laminae, phosphorus and kalium in vagina were the highest content, respectively. The accumulated quantity of elements in laminae was the highest in May and account for 22%, that of August was the lowest with 1%; the content of total kalium in May was the lowest and account for 15%, the lowest occurred in September with a percent of 5%; the content of total phosphorus in August was the highest accounting for 31%, and that of September was lowest with 2%.

Research of Seabed Rescue Method of Uncontrolled Blowout in Offshore Drilling

Presently, rescue equipment and method for uncontrolled blowout in offshore drilling are very rare, of which the consequences were very serious. With analysis of mechanics of materials based on shut-in water hammer pressure and wellhead pressure while rescuing, and fluid mechanics of uncontrolled blowout based CFD, a rescue equipment for uncontrolled blowout in offshore drilling has been invented, and proposing a rescue method. There are several emergency scenarios have been made. Take the “deep horizon oil rig” in the gulf of Mexico for example, the flow field properties around this equipment could be calculated by software to prove the reliability of it. The equipment is a conceptual invention which could be designed in different types according to the size and strength of original wellhead. This equipment could prevent well blowout and collect leaped oil.