HIRFL—CSR循环冷却水温度远程测量系统设计；A Design of Remote Temperature-measuring System for HIFRL-CSR Recyclable Cooling Water System

介绍了一种基于一线总线数字温度传感器的HIFRL-CSR循环冷却水温度远程测量系统,阐述了以DT400模块为核心的温度测量的硬件模块和软件设计。该系统具有测温精度高、易扩展性、低成本、低功耗、可靠性高、抗干扰能力强等特点,根据不同需要可应用于多种温度测量系统中。

Ultrahigh compression of water using intense heavy ion beams: laboratory planetary physics

Intense heavy ion beams offer a unique tool for generating samples of high energy density matter with extreme conditions of density and pressure that are believed to exist in the interiors of giant planets. An international accelerator facility named FAIR (Facility for Antiprotons and Ion Research) is being constructed at Darmstadt, which will be completed around the year 2015. It is expected that this accelerator facility will deliver a bunched uranium beam with an intensity of 5x10(11) ions per spill with a bunch length of 50-100 ns. An experiment named LAPLAS (Laboratory Planetary Sciences) has been proposed to achieve a low-entropy compression of a sample material like hydrogen or water (which are believed to be abundant in giant planets) that is imploded in a multi-layered target by the ion beam. Detailed numerical simulations have shown that using parameters of the heavy ion beam that will be available at FAIR, one can generate physical conditions that have been predicted to exist in the interior of giant planets. In the present paper, we report simulations of compression of water that show that one can generate a plasma phase as well as a superionic phase of water in the LAPLAS experiments.

Application of Dempster-Shafer evidence theory to unsupervised classification in multisource remote sensing

The aim of this paper is to show that Dempster-Shafer evidence theory may be successfully applied to unsupervised classification in multisource remote sensing. Dempster-Shafer formulation allows for consideration of unions of classes, and to represent both imprecision and uncertainty, through the definition of belief and plausibility functions. These two functions, derived from mass function, are generally chosen in a supervised way. In this paper, the authors describe an unsupervised method, based on the comparison of monosource classification results, to select the classes necessary for Dempster-Shafer evidence combination and to define their mass functions. Data fusion is then performed, discarding invalid clusters (e.g. corresponding to conflicting information) thank to an iterative process. Unsupervised multisource classification algorithm is applied to MAC-Europe'91 multisensor airborne campaign data collected over the Orgeval French site. Classification results using different combinations of sensors (TMS and AirSAR) or wavelengths (L- and C-bands) are compared. Performance of data fusion is evaluated in terms of identification of land cover types. The best results are obtained when all three data sets are used. Furthermore, some other combinations of data are tried, and their ability to discriminate between the different land cover types is quantified

Surface pigments,algal biomass profiles,and potential production of the euphotic layer:Relationships reinvestigated in view of remote-sensing applications

Maps of surface chlorophyllous pigment (Chl a + Pheo a) are currently produced from ocean color sensors. Transforming such maps into maps of primary production can be reliably done only by using light-production models in conjuction with additional information about the column-integrated pigment content and its vertical distribution. As a preliminary effort in this direction. $\ticksim 4,000$ vertical profiles pigment (Chl a + Pheo a) determined only in oceanic Case 1 waters have been statistically analyzed. They were scaled according to dimensionless depths (actual depth divided by the depth of the euphotic layer, $Z_e$) and expressed as dimensionless concentrations (actual concentration divided by the mean concentration within the euphotic layer). The depth $Z_e$ generally unknown, was computed with a previously develop bio-optical model. Highly sifnificant relationships were found allowing $\langle C \rangle_tot$, the pigment content of the euphotic layer, to be inferred from the surface concentration, $\bar C_pd$, observed within the layer of one penetration depth. According to their $\bar C_pd$ values (ranging from $0.01 to > 10 mg m^-3$), we categorized the profiles into seven trophic situations and computed a mean vertical profile for each. Between a quasi-uniform profile in eutrophic waters and a profile with a strong deep maximum in oligotrophic waters, the shape evolves rather regularly. The wellmixed cold waters, essentially in the Antarctic zone, have been separately examined. On average, their profiles are featureless, without deep maxima, whatever their trophic state. Averaged values their profiles are featureless, without deep maxima, whatever their trophic state. Averaged values their profiles are featureless, without deep maxima, whatever their trophic state. Averaged values of $ρ$, the ratio of Chl a tp (Chl a + Pheo a), have also been obtained for each trophic category. The energy stored by photosynthesizing algae, once normalized with respect to the integrated chlorophyll biomass $\langle C \rangle _tot $ is proportional to the available photosythetic energy at the surface via a parameter $ψ∗$ which is the cross-section for photosynthesis per unit of areal chlorophyll. By tanking advantage of the relative stability of $ψ∗.$ we can compute primary production from ocean color data acquired from space. For such a computation, inputs are the irradiance field at the ocean surface, the "surface" pigment from which $\langle C \rangle _tot$ can be derived, the mean $ρ value pertinent to the trophic situation as depicted by the $\bar C_pd or $\langle C \rangle _tot$ values, and the cross-section $ψ∗$. Instead of a contant $ψ∗.$ value, the mean profiles can be used; they allow the climatological field of the $ψ∗.$ parameter to be adjusted through the parallel use of a spectral light-production model.

remote attestation for custom-built software

Huazhong Univ Sci & Technol, Natl Tech Univ Ukraine, Huazhong Normal Univ, Harbin Inst Technol, IEEE Ukraine Sect, I& M/CI Joint Chapter

A data-model fusion approach for upscaling gross ecosystem productivity to the landscape scale based on remote sensing and flux footprint modelling

Chinese Academy of Sciences ; National Science Foundation of China [41071059]; National Key Technology R&D Program of China [2008BAK50B06-02]; National Basic Research Program of China [2010CB950900, 2010CB950704]; Natural Sciences and Engineering Research Council of Canada

Research on extracting method of micro-scale remote sensing information combination and application in coastal zone

973 Project of China [2006CB701305]; "863" Project of China [2009AA12Z148]; National Natural Science Foundation of China [40971224]

Effects of soil type on leaching and runoff transport of rare earth elements and phosphorous in laboratory experiments

Through leaching experiments and simulated rainfall experiments, characteristics of vertical leaching of exogenous rare earth elements (REEs) and phosphorus (P) and their losses with surface runoff during simulated rainfall in different types of soils (terra nera soil, cinnamon soil, red soil, loess soil, and purple soil) were investigated. Results of the leaching experiments showed that vertical transports of REEs and P were relatively low, with transport depths less than 6 cm. The vertical leaching rates of REEs and P in the different soils followed the order of purple soil > terra nera soil > red soil > cinnamon soil > loess soil. Results of the simulated rainfall experiments (83 mm h(-1)) revealed that more than 92% of REEs and P transported with soil particles in runoff. The loss rates of REEs and P in surface runoff in the different soil types were in the order of loess soil > terra nera soil > cinnamon soil > red soil > purple soil. The total amounts of losses of REEs and P in runoff were significantly correlated.

Validating MODIS-derived land surface evapotranspiration with in situ measurements at two AmeriFlux sites in a semiarid region

Reducing uncertainties in the estimation of land surface evapotranspiration (ET) from remote-sensing data is essential to better understand earth-atmosphere interactions. This paper demonstrates the applicability of temperature-vegetation index triangle (T-s-VI) method in estimating regional ET and evaporative fraction (EF, defined as the ratio of latent heat flux to surface available energy) from MODIS/Terra and MODIS/Aqua products in a semiarid region. We have compared the satellite-based estimates of ET and EF with eddy covariance measurements made over 4 years at two semiarid grassland sites: Audubon Ranch (AR) and Kendall Grassland (KG). The lack of closure in the eddy covariance measured surface energy components is shown to be more serious at MODIS/Aqua overpass time than that at MODIS/Terra overpass time for both AR and KG sites. The T-s-VI-derived EF could reproduce in situ EF reasonably well with BIAS and root-mean-square difference (RMSD) of less than 0.07 and 0.13, respectively. Surface net radiation has been shown to be systematically overestimated by as large as about 60 W/m(2). Satisfactory validation results of the T-s-VI-derived sensible and latent heat fluxes have been obtained with RMSD within 54 W/m(2). The simplicity and yet easy use of the T-s-VI triangle method show a great potential in estimating regional ET with highly acceptable accuracy that is of critical significance in better understanding water and energy budgets on the Earth. Nevertheless, more validation work should be carried out over various climatic regions and under other different land use/land cover conditions in the future.