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

Optimization of canopy conductance models from concurrent measurements of sap flow and stem water potential on Drooping Sheoak in South Australia

This project is supported by National Centre for Groundwater Research and Training (NCGRT, Australia). The first author is supported by China Scholarship Council and NCGRT for his PhD study at Flinders University of South Australia. Xiang Xu and Yunhui Guo provided assistance in the field. Constructive comments and suggestion from three anonymous reviewers significantly improve the manuscript. This article also appears in: Patterns in Soil-Vegetation-Atmosphere Systems: Monitoring, Modelling and Data Assimilation.Peer reviewedPublisher PD

Assessing 20th century climate-vegetation feedbacks of land-use change and natural vegetation dynamics in a fully coupled vegetation-climate model

This study describes the coupling of the dynamic global vegetation model (DGVM), Lund–Potsdam–Jena Model for managed land (LPJmL), with the general circulation model (GCM), Simplified Parameterizations primitivE Equation DYnamics model (SPEEDY), to study the feedbacks between land-use change and natural vegetation dynamics and climate during the 20th century. We show that anthropogenic land-use change had a stronger effect on climate than the natural vegetation's response to climate change (e.g. boreal greening). Changes in surface albedo are an important driver of the climate's response; but, especially in the (sub)tropics, changes in evapotranspiration and the corresponding changes in latent heat flux and cloud formation can be of equal importance in the opposite direction. Our study emphasizes that implementing dynamic vegetation into climate models is essential, especially at regional scales: the dynamic response of natural vegetation significantly alters the climate change that is driven by increased atmospheric greenhouse gas concentrations and anthropogenic land-use chang

Inside and/or Outside? Working Sensitively with Political Material in Psychotherapy

This article focuses on one particular dimension of psychopolitics: that which manifests itself in the personal contents or materials clients bring into psychotherapy. It seems that many psychotherapists find themselves struggling when faced with political issues which come up in psychotherapy, both overtly and covertly. Many psychotherapists find value in clarifying political aspects of clients' lives and psychotherapy itself, but are hesitant to touch upon this loaded issue or do not know how to approach it. The present article seeks to formulate a theoretical basis for politically-conscious therapy, as well guiding principles that help to implement this position

Protecting climate with forests

Policies for climate mitigation on land rarely acknowledge biophysical factors, such as reflectivity, evaporation, and surface roughness. Yet such factors can alter temperatures much more than carbon sequestration does, and often in a conflicting way. We outline a framework for examining biophysical factors in mitigation policies and provide some best-practice recommendations based on that framework. Tropical projects-avoided deforestation, forest restoration, and afforestation-provide the greatest climate value, because carbon storage and biophysics align to cool the Earth. In contrast, the climate benefits of carbon storage are often counteracted in boreal and other snow-covered regions, where darker trees trap more heat than snow does. Managers can increase the climate benefit of some forest projects by using more reflective and deciduous species and through urban forestry projects that reduce energy use. Ignoring biophysical interactions could result in millions of dollars being invested in some mitigation projects that provide little climate benefit or, worse, are counter-productive

Modeling elucidates how refractory period can provide profound nonlinear gain control to graded potential neurons

Refractory period (RP) plays a central role in neural signaling. Because it limits an excitable membrane's recovery time from a previous excitation, it can restrict information transmission. Classically, RP means the recovery time from an action potential (spike), and its impact to encoding has been mostly studied in spiking neurons. However, many sensory neurons do not communicate with spikes but convey information by graded potential changes. In these systems, RP can arise as an intrinsic property of their quantal micro/nanodomain sampling events, as recently revealed for quantum bumps (single photon responses) in microvillar photoreceptors. Whilst RP is directly unobservable and hard to measure, masked by the graded macroscopic response that integrates numerous quantal events, modeling can uncover its role in encoding. Here, we investigate computationally how RP can affect encoding of graded neural responses. Simulations in a simple stochastic process model for a fly photoreceptor elucidate how RP can profoundly contribute to nonlinear gain control to achieve a large dynamic range. [Abstract copyright: © 2017 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of The Physiological Society and the American Physiological Society.

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)

“This Is Not What I Normally Do” : An Insignificant Step in the Downfall of the Humanities

This video essay, a product of the “Videographic Methods and Practices: Embodying the Video Essay” workshop (Bowdoin College, July 2023), is comprised of two sections, exploring constraint-based approaches to videographic scholarship. Part 1, “The Incredible Machine,” documents an attempt at recreating a 1990s Rube Goldberg-inspired computer game interface through the handling of various film clips arranged on a computer desktop. The deliberate avoidance of digital shortcuts highlights the value of playful experimentation within scholarly and artistic practices. Part 2, “The Five Obstructions,” presents five interviews conducted under randomly-assigned constraints, fostering unforeseen responses and creative insights. These ludic experiments demonstrate the potential of constraints to stimulate creativity and to provoke unconventional outputs. Emphasizing process over outcome, the video showcases the laborious yet rewarding nature of scholarly experimentation, echoing a broader shift towards embracing the creative-academic journey in videographic scholarship

Regionally coupled atmosphere-ocean-sea ice-marine biogeochemistry model ROM: 1. Description and validation

The general circulation models used to simulate global climate typically feature resolution too coarse to reproduce many smaller-scale processes, which are crucial to determining the regional responses to climate change. A novel approach to downscale climate change scenarios is presented which includes the interactions between the North Atlantic Ocean and the European shelves as well as their impact on the North Atlantic and European climate. The goal of this paper is to introduce the global ocean-regional atmosphere coupling concept and to show the potential benefits of this model system to simulate present-day climate. A global ocean-sea ice-marine biogeochemistry model (MPIOM/HAMOCC) with regionally high horizontal resolution is coupled to an atmospheric regional model (REMO) and global terrestrial hydrology model (HD) via the OASIS coupler. Moreover, results obtained with ROM using NCEP/NCAR reanalysis and ECHAM5/MPIOM CMIP3 historical simulations as boundary conditions are presented and discussed for the North Atlantic and North European region. The validation of all the model components, i.e., ocean, atmosphere, terrestrial hydrology, and ocean biogeochemistry is performed and discussed. The careful and detailed validation of ROM provides evidence that the proposed model system improves the simulation of many aspects of the regional climate, remarkably the ocean, even though some biases persist in other model components, thus leaving potential for future improvement. We conclude that ROM is a powerful tool to estimate possible impacts of climate change on the regional scale

An Amazonian rainforest and its fragments as a laboratory of global change

We synthesize findings from one of the world’s largest and longest-running experimental investigations, the Biological Dynamics of Forest Fragments Project (BDFFP). Spanning an area of ~1,000 km2 in central Amazonia, the BDFFP was initially designed to evaluate the effects of fragment area on rainforest biodiversity and ecological processes. However, over its 38-year history to date the project has far transcended its original mission, and now focuses more broadly on landscape dynamics, forest regeneration, regional- and global-change phenomena, and their potential interactions and implications for Amazonian forest conservation. The project has yielded a wealth of insights into the ecological and environmental changes in fragmented forests. For instance, many rainforest species are naturally rare and hence are either missing entirely from many fragments or so sparsely represented as to have little chance of long-term survival. Additionally, edge effects are a prominent driver of fragment dynamics, strongly affecting forest microclimate, tree mortality, carbon storage and a diversity of fauna. Even within our controlled study area, the landscape has been highly dynamic: for example, the matrix of vegetation surrounding fragments has changed markedly over time, succeeding from large cattle pastures or forest clearcuts to secondary regrowth forest. This, in turn, has influenced the dynamics of plant and animal communities and their trajectories of change over time. In general, fauna and flora have responded differently to fragmentation: the most locally extinction-prone animal species are those that have both large area requirements and low tolerance of the modified habitats surrounding fragments, whereas the most vulnerable plants are those that respond poorly to edge effects or chronic forest disturbances, and that rely on vulnerable animals for seed dispersal or pollination. Relative to intact forests, most fragments are hyperdynamic, with unstable or fluctuating populations of species in response to a variety of external vicissitudes. Rare weather events such as droughts, windstorms and floods have had strong impacts on fragments and left lasting legacies of change. Both forest fragments and the intact forests in our study area appear to be influenced by larger-scale environmental drivers operating at regional or global scales. These drivers are apparently increasing forest productivity and have led to concerted, widespread increases in forest dynamics and plant growth, shifts in tree-community composition, and increases in liana (woody vine) abundance. Such large-scale drivers are likely to interact synergistically with habitat fragmentation, exacerbating its effects for some species and ecological phenomena. Hence, the impacts of fragmentation on Amazonian biodiversity and ecosystem processes appear to be a consequence not only of local site features but also of broader changes occurring at landscape, regional and even global scales