Multi-Conjugate Adaptive Optics with laser guide stars: performance in the infrared and visible

The assumption of the Gaussianity of primordial perturbations plays an important role in modern cosmology. The most direct test of this hypothesis consists of testing the Gaussianity of cosmic microwave background (CMB) maps. Counting the pixels with the temperatures in given ranges and thus estimating the one-point probability function of the field is the simplest of all the tests. Other usually more complex tests of Gaussianity generally use a great deal of the information already contained in the probability function. However, the most interesting outcome of such a test would be the signal of non-Gaussianity independent of the probability function. It is shown that the independent information has purely morphological character i.e. it depends on the geometry and topology of the level contours only. As an example we discuss in detail the quadratic model   v = u + α ( u ²-1)  ( u is a Gaussian field with   u¯ =0  and  〈 u ²〉=1  , α is a parameter) that may arise in slow-roll or two-field inflation models. We show that in the limit of small amplitude α the full information about the non-Gaussianity is contained in the probability function. If other tests are performed on this model they simply recycle the same information. A simple procedure allowing us to assess the sensitivity of any statistics to the morphological information is suggested. We provide an analytic estimate of the statistical limit for detecting the quadratic non-Gaussianity α _c as a function of the map size in the ideal situation when the scale of the field is resolved. This estimate is in a good agreement with the results of the Monte Carlo simulations of 256² and 1024² maps. The effect of resolution on the detection quadratic non-Gaussianity is also briefly discussed.     

An example of health hazard: People killed by gas during a phreatic eruption: Diëng plateau (Java,Indonesia), February 20th 1979

On February 20th, 1979, 142 inhabitants of Dieng Plateau (Indonesia) were asphyxiated by poisonous gases during a mild phreatic eruption. From later fields gas collection and analysis, the casualties are considered to be due to CO₂ rich volcanic gases.     

Biogenic carbon flows through the planktonic food web of the Amundsen Gulf (Arctic Ocean): A synthesis of field measurements and inverse modeling analyses

Major pathways of biogenic carbon (C) flow are resolved for the planktonic food web of the flaw lead polynya system of the Amundsen Gulf (southeast Beaufort Sea, Arctic Ocean) in spring-summer 2008. This period was relevant to study the effect of climate change on Arctic marine ecosystems as it was characterized by unusually low ice cover and warm sea surface temperature. Our synthesis relied on a mass balance estimate of gross primary production (GPP) of 52.5 ± 12.5 g C m⁻² calculated using the drawdown of nitrate and dissolved inorganic C, and a seasonal f-ratio of 0.64. Based on chlorophyll a biomass, we estimated that GPP was dominated by phytoplankton (93.6%) over ice algae (6.4%) and by large cells (>5 μm, 67.6%) over small cells (<5 μm, 32.4%). Ancillary in situ data on bacterial production, zooplankton biomass and respiration, herbivory, bacterivory, vertical particle fluxes, pools of particulate and dissolved organic carbon (POC, DOC), net community production (NCP), as well as selected variables from the literature were used to evaluate the fate of size-fractionated GPP in the ecosystem. The structure and functioning of the planktonic food web was elucidated through inverse analysis using the mean GPP and the 95% confidence limits of every other field measurement as lower and upper constraints. The model computed a net primary production of 49.2 g C m⁻², which was directly channeled toward dominant calanoid copepods (i.e. Calanus hyperboreus 20%, Calanus glacialis 10%, and Metridia longa 10%), other mesozooplankton (12%), microzooplankton (14%), detrital POC (18%), and DOC (16%). Bacteria required 29.9 g C m⁻², a demand met entirely by the DOC derived from local biological activities. The ultimate C outflow comprised respiration fluxes (82% of the initial GPP), a small sedimentation (3%), and a modest residual C flow (15%) resulting from NCP, dilution and accumulation. The sinking C flux at the model limit depth (395 m) supplied 60% of the estimated benthic C demand (2.8 g C m⁻²), suggesting that the benthos relied partly on other C sources within the bottom boundary layer to fuel its activity. In summary, our results illustrate that the ongoing decline in Arctic sea ice promotes the growth of pelagic communities in the Amundsen Gulf, which benefited from a ∼80% increase in GPP in spring-summer 2008 when compared to 2004 – a year of average ice conditions and relatively low GPP. However, 53% of the secondary production was generated within the microbial food web, the net ecological efficiency of zooplankton populations was not particularly high (13.4%), and the quantity of biogenic C available for trophic export remained low (6.6 g C m⁻²). Hence it is unlikely that the increase in lower food web productivity, such as the one observed in our study, could support new harvestable fishery resources in the offshore Beaufort Sea domain.     

基于脉冲小电流的经颅磁刺激电路设计

为改进传统磁刺激治疗仪需要使用脉冲大电流产生磁场,以及在临界阻尼震荡条件下电路的RLC参数匹配难度大等缺点,根据感应电场产生的原理,提出一种基于低电压,脉冲小电流,用RL电路代替RLC电路的设计。该电路在产生磁场的回路中用+5V低电压电源代替电容器,通过加快电流的变化速率产生与脉冲大电流同样的刺激效果,具有安全,易调控的优点,也推进了磁刺激治疗仪面向小型、便携、低功耗等方向的发展。     

Graphical tools based on Turc-Budyko plots to detect changes in catchment behaviour

Abstract

This paper aims at revisiting the use of non-dimensional representations for catchment change and model robustness analysis. As well as being helpful for catchment classification according to hydroclimatic conditions, the Turc-Budyko representation enables visualization of temporal changes in these conditions and/or modification of the hydrological behaviour of the catchment. This brings a new perspective to hydrological analysis, different from the classical time series plots, which helps when interpreting catchment functioning with respect to hydroclimatic constraints. These tools do not require statistical analyses of observed series and are therefore very simple to implement. Four case studies are considered here to illustrate the use of the Q/P = f(P/E_p) graph. When combined with the inter-annual Turc-Mezentsev formula, this visual framework enables anticipation of potential difficulties for models based on the same hypotheses, solely using the analysis of observed data.     

The information system of the French Peatland Observation Service: Service National d'Observation Tourbières – A valuable tool to assess the impact of global changes on the hydrology and biogeochemistry of temperate peatlands through long term monitoring

Mitigating and adapting to global changes requires a better understanding of the response of the Biosphere to these environmental variations. Human disturbances and their effects act in the long term (decades to centuries) and consequently, a similar time frame is needed to fully understand the hydrological and biogeochemical functioning of a natural system. To this end, the ‘Centre National de la Recherche Scientifique’ (CNRS) promotes and certifies long-term monitoring tools called national observation services or ‘Service National d'Observation’ (SNO) in a large range of hydrological and biogeochemical systems (e.g., cryosphere, catchments, aquifers). The SNO investigating peatlands, the SNO ‘Tourbières’, was certified in 2011 ( https://www.sno-tourbieres.cnrs.fr/ ). Peatlands are mostly found in the high latitudes of the northern hemisphere and French peatlands are located in the southern part of this area. Thus, they are located in environmental conditions that will occur in northern peatlands in coming decades or centuries and can be considered as sentinels. The SNO Tourbières is composed of four peatlands: La Guette (lowland central France), Landemarais (lowland oceanic western France), Frasne (upland continental eastern France) and Bernadouze (upland southern France). Thirty target variables are monitored to study the hydrological and biogeochemical functioning of the sites. They are grouped into four datasets: hydrology, fluvial export of organic matter, greenhouse gas fluxes and meteorology/soil physics. The data from all sites follow a common processing chain from the sensors to the public repository. The raw data are stored on an FTP server. After operator or automatic processing, data are stored in a database, from which a web application extracts the data to make them available ( https://data-snot.cnrs.fr/data-access/ ). Each year at least, an archive of each dataset is stored in Zenodo, with a digital object identifier (DOI) attribution ( https://zenodo.org/communities/sno_tourbieres_data/ ).     

X-ray flares raising upon magnetar plateau as an implication of a surrounding disk of newborn magnetized neutron star

The X-ray flares have usually been ascribed to long-lasting activities of the central engine of gamma-ray bursts(GRBs),e.g.,fallback accretion.The GRB X-ray pla...     

Mental maps and travel behaviour: meanings and models

In this paper, the “mental map” concept is positioned with regard to individual travel behaviour to start with. Based on Ogden and Richards’ triangle of meaning (The meaning of meaning: a study of the influence of language upon thought and of the science of symbolism. International library of psychology, philosophy and scientific method. Routledge and Kegan Paul, London, 1966) distinct thoughts, referents and symbols originating from different scientific disciplines are identified and explained in order to clear up the notion’s fuzziness. Next, the use of this concept in two major areas of research relevant to travel demand modelling is indicated and discussed in detail: spatial cognition and decision-making. The relevance of these constructs to understand and model individual travel behaviour is explained and current research efforts to implement these concepts in travel demand models are addressed. Furthermore, these mental map notions are specified in two types of computational models, i.e. a Bayesian Inference Network (BIN) and a Fuzzy Cognitive Map (FCM). Both models are explained, and a numerical and a real-life example are provided. Both approaches yield a detailed quantitative representation of the mental map of decision-making problems in travel behaviour.     

A robust debris-flow and GLOF risk management strategy for a data-scarce catchment in Santa Teresa,Peru

The town of Santa Teresa (Cusco Region, Peru) has been affected by several large debris-flow events in the recent past, which destroyed parts of the town and resulted in a resettlement of the municipality. Here, we present a risk analysis and a risk management strategy for debris-flows and glacier lake outbursts in the Sacsara catchment. Data scarcity and limited understanding of both physical and social processes impede a full quantitative risk assessment. Therefore, a bottom-up approach is chosen in order to establish an integrated risk management strategy that is robust against uncertainties in the risk analysis. With the Rapid Mass Movement Simulation (RAMMS) model, a reconstruction of a major event from 1998 in the Sacsara catchment is calculated, including a sensitivity analysis for various model parameters. Based on the simulation results, potential future debris-flows scenarios of different magnitudes, including outbursts of two glacier lakes, are modeled for assessing the hazard. For the local communities in the catchment, the hazard assessment is complemented by the analysis of high-resolution satellite imagery and fieldwork. Physical, social, economic, and institutional vulnerability are considered for the vulnerability assessment, and risk is eventually evaluated by crossing the local hazard maps with the vulnerability. Based on this risk analysis, a risk management strategy is developed, consisting of three complementing elements: (i) standardized risk sheets for the communities; (ii) activities with the local population and authorities to increase social and institutional preparedness; and (iii) a simple Early Warning System. By combining scientific, technical, and social aspects, this work is an example of a framework for an integrated risk management strategy in a data scarce, remote mountain catchment in a developing country.     

基于光谱—空间特征的ASTER影像岩性分类研究——以甘肃北山白峡尼山地区为例

遥感岩性制图是地质填图中的重要工作,基于光谱特征的岩性分类易受到色调、纹理等因素影响导致精度不佳。前人进行岩性自动分类研究多关注影像的光谱特征,而忽略空间特征,笔者等基于甘肃北山白峡尼山地区ASTER影像,将支持向量机、极限学习机两种机器学习分类方法与基于空间特征的快速漂移算法相结合进行岩性分类。结果表明支持向量机分类总体精度为89.17%;极限学习机不但具有需调节参数少的优势,且分类精度和速度均优于支持向量机,分类总体精度达96.70%;利用快速漂移算法提取的影像空间特征可有效减少错分区,提升岩性分类效果。研究证实将基于光谱特征的极限学习机和基于空间特征的快速漂移算法结合的岩性分类方法具有客观、高效、高精度等优势,可为后续地质填图和找矿勘查工作提供可靠数据支撑,在遥感岩性分类领域具有较高的推广价值。