A Low Density Lattice Decoder via Non-Parametric Belief Propagation

The recent work of Sommer, Feder and Shalvi presented a new family of codes called low density lattice codes (LDLC) that can be decoded efficiently and approach the capacity of the AWGN channel. A linear time iterative decoding scheme which is based on a message-passing formulation on a factor graph is given. In the current work we report our theoretical findings regarding the relation between the LDLC decoder and belief propagation. We show that the LDLC decoder is an instance of non-parametric belief propagation and further connect it to the Gaussian belief propagation algorithm. Our new results enable borrowing knowledge from the non-parametric and Gaussian belief propagation domains into the LDLC domain. Specifically, we give more general convergence conditions for convergence of the LDLC decoder (under the same assumptions of the original LDLC convergence analysis). We discuss how to extend the LDLC decoder from Latin square to full rank, non-square matrices. We propose an efficient construction of sparse generator matrix and its matching decoder. We report preliminary experimental results which show our decoder has comparable symbol to error rate compared to the original LDLC decoder.%Comment: Submitted for publicatio

Comparison of three land-surface schemes with the Fourier amplitude sensitivity test (FAST)

This paper explores which are the land-surface parameters playing a key role in three surface schemes, namely the land-atmosphere interactive dynamics (LAID), the interaction soil-biosphere-atmosphere (ISBA) and the biosphere-atmosphere transfer scheme (BATS). The Fourier amplitude sensitivity test (FAST) was used for that purpose. This test estimates the relative contribution of model input parameters to the variance of surface heat fluxes. This analysis demonstrates that, for the three considered schemes, four parameters can explain most of the variance of surface heat fluxes under a broad range of environmental conditions. Soil wetness plays a predominant roˆ le for the heat fluxes. Roughness length is the most important parameter for the momentum flux. Leaf area index, in vegetated land, and texture, mainly in bare land, also have a significant impact on the fluxes. Roughness length is usually more important for sensible heat flux than for latent heat flux, and is mostly important under stable atmospheric conditions. Soil wetness and vegetation parameters are the dominant parameters under buoyant conditions

Effective parameters for surface heat fluxes in heterogeneous terrain

The relations between most land-surface characteristics and surface heat fluxes are typicallynon-linear. Because the ground surface is heterogeneous at all scales, it is important to accountfor these non-linear relations. EVective parameters are often applied for that purpose. Steady-state simulations were used in this paper to thoroughly analyse the eVective parameters impactunder a broad range of atmospheric conditions. The eVect of diVerent types of aggregatingfunctions on the accuracy of various eVective parameters is also examined. The authors foundthat linear averaging of leaf area index and soil water content gives higher latent and lowersensible heat fluxes than the corresponding flux averaging over all surface types existing in onesquare grid. Linear averaging of roughness length under unstable conditions provides higherlatent and lower sensible heat fluxes than flux averaging, whereas under stable conditions giveshigher sensible and lower latent heat fluxes. Non-linear functions result to be more useful thanlinear functions to compute the eVective value of those parameters which aVect the surface heatfluxes independently of the atmospheric stability (e.g., leaf area index and soil water content,and unlike roughness length)

Regulation of Phytochrome Gene Expression

In etiolated oat seedlings exposure to red light results in a decrease in the transcription of the phytochrome genes, the abundance of phytochrome mRNA, and the level of phytochrome protein. Phytochrome itself serves as the photoreceptor for the response of decreased mRNA and transcription levels. The decrease in phytochrome mRNA is sensitive to low levels of Pfr. Even green safelight is capable of inducing a decrease in phytochrome mRNA abundance. Barley phytochrome mRNA abundance is also dramatically down-regulated in response to red light but other plant species vary in their ability to decrease phytochrome mRNA abundance after red light treatment. Kinetic analysis and protein synthesis inhibitor data indicate that the abundance of phytochrome mRNA in oat seedlings may be regulated in part at the post-transcriptional level. Phytochrome mRNA may provide a useful model system for the investigation of posttranscriptional regulation of plant gene expression

Use of Sensor Imagery Data for Surface Boundary Conditions in Regional Climate Modeling

Mesoscale climate and hydrology modeling studies have increased in sophistication and are being run at increasingly higher resolutions. Data resolution sufficiently finer than that of the computational model is required not only to support sophisticated linkages and process interactions at small scales but to assess their cumulative impact at larger scales. The global distributions at fine spatial and temporal scales can be described by means of various senor imagery data collected through remote sensing techniques, sensor image and photo programs, scanning and digitizing skills for existing maps, etc. The availability of global sensor imagery maps facilitates assimilation in land surface models to account for terrestrial dynamics. This study focuses on the use of global imagery data for development and construction of surface boundary conditions (SBCs) specifically designed for mesoscale regional climate model (RCM) applications. The several SBCs are currently presented in a RCM domain for the continent of Asia at 30-km spacing by using sensor imagery data. Geographic Information System (GIS) software application tools are mainly used to convert data information from various raw data onto RCM-specific grids. The raw data sources and processing procedures are elaborated in detail, by which the SBCs can be readily constructed for any specific RCM domain anywhere in the world