Developing the untapped wealth of Britain's ?Celtic Fringe? : Water engineering and the Welsh landscape, 1870 ? 1960

Roberts, O. (2006). Developing the untapped wealth of Britain's ?Celtic fringe?: water engineering and the Welsh landscape, 1870-1960. Landscape Research. 31(2), pp.121-133. RAE2008

Appreciating ecological complexity: Habitat contours as a conceptual landscape model

Joern Fischer, David B. Lindermayer, and Ioan Fazey (2004). Appreciating Ecological Complexity: Habitat Contours as a Conceptual Landscape Model. Conservation Biology, 18 (5)pp.1245-1253 RAE2008

Protein Docking by the Underestimation of Free Energy Funnels in the Space of Encounter Complexes

Similarly to protein folding, the association of two proteins is driven by a free energy funnel, determined by favorable interactions in some neighborhood of the native state. We describe a docking method based on stochastic global minimization of funnel-shaped energy functions in the space of rigid body motions (SE(3)) while accounting for flexibility of the interface side chains. The method, called semi-definite programming-based underestimation (SDU), employs a general quadratic function to underestimate a set of local energy minima and uses the resulting underestimator to bias further sampling. While SDU effectively minimizes functions with funnel-shaped basins, its application to docking in the rotational and translational space SE(3) is not straightforward due to the geometry of that space. We introduce a strategy that uses separate independent variables for side-chain optimization, center-to-center distance of the two proteins, and five angular descriptors of the relative orientations of the molecules. The removal of the center-to-center distance turns out to vastly improve the efficiency of the search, because the five-dimensional space now exhibits a well-behaved energy surface suitable for underestimation. This algorithm explores the free energy surface spanned by encounter complexes that correspond to local free energy minima and shows similarity to the model of macromolecular association that proceeds through a series of collisions. Results for standard protein docking benchmarks establish that in this space the free energy landscape is a funnel in a reasonably broad neighborhood of the native state and that the SDU strategy can generate docking predictions with less than 5 � ligand interface Ca root-mean-square deviation while achieving an approximately 20-fold efficiency gain compared to Monte Carlo methods.

Dutch influence in the urban landscape of Cork City pre-1800: Fact or myth?

The early years of the eighteenth century Irish port town, Cork saw an expansion of its city limits, an era of reconstruction both within and beyond the walls of its Medieval townscape and a reclamation of its marshlands to the east and west. New people, new ideas and the beginnings of new wealth infused the post Elizabethan character of the recently siege battered city. It also brought a desire for something different, something new, an opportunity to redefine the ambience and visual perception of the urban landscape and thereby make a statement about its intended cultural and social orientations. It brought an opportunity to re-imagine and model a new, continental style of place and surrounding environment.

Hidden land and changing landscape: Narratives about Mount Khangchendzonga among the Lepcha and the Lhopo

This article explores contemporary ‘hidden land’ narrative constructs of Máyel Lyáng and Beyul Dremojong in Sikkim, India, as conceived by the Lepcha and the Lhopo, two ‘scheduled tribes’. Lepcha and Lhopo narratives about these hidden lands in Mount Khangchendzonga inform us about their contemporary and historical, indigenous and Buddhist contexts and the interactions between these contexts. Lhopo perspectives on the hidden Beyul Dremojong echo classical Tibetan Buddhist ‘revealed treasure’ guidebooks and exist within the complex and reciprocal relationship between the Lhopo and the land they inhabit; development initiatives are understood to have caused illness and death in the Lhopo community of Tashiding, often referred to as the geographical ‘center’ of Beyul Dremojong. Contemporary Lepcha comprehensions of Máyel Lyáng, described in oral narratives within an ethnic community whose cosmology is intimately connected with Mount Khangchendzonga, today show some influence of Lhopo interpretations of Beyul Dremojong and the treasure texts; they also reflect Lepcha fears about cultural dispersion. Present-day narratives about both hidden lands reference notable political events in modern Sikkimese history (encounters with the British; the Chinese occupation of Tibet).

Discharge competence and pattern formation in peatlands: a meta-ecosystem model of the Everglades ridge-slough landscape.

Regular landscape patterning arises from spatially-dependent feedbacks, and can undergo catastrophic loss in response to changing landscape drivers. The central Everglades (Florida, USA) historically exhibited regular, linear, flow-parallel orientation of high-elevation sawgrass ridges and low-elevation sloughs that has degraded due to hydrologic modification. In this study, we use a meta-ecosystem approach to model a mechanism for the establishment, persistence, and loss of this landscape. The discharge competence (or self-organizing canal) hypothesis assumes non-linear relationships between peat accretion and water depth, and describes flow-dependent feedbacks of microtopography on water depth. Closed-form model solutions demonstrate that 1) this mechanism can produce spontaneous divergence of local elevation; 2) divergent and homogenous states can exhibit global bi-stability; and 3) feedbacks that produce divergence act anisotropically. Thus, discharge competence and non-linear peat accretion dynamics may explain the establishment, persistence, and loss of landscape pattern, even in the absence of other spatial feedbacks. Our model provides specific, testable predictions that may allow discrimination between the self-organizing canal hypotheses and competing explanations. The potential for global bi-stability suggested by our model suggests that hydrologic restoration may not re-initiate spontaneous pattern establishment, particularly where distinct soil elevation modes have been lost. As a result, we recommend that management efforts should prioritize maintenance of historic hydroperiods in areas of conserved pattern over restoration of hydrologic regimes in degraded regions. This study illustrates the value of simple meta-ecosystem models for investigation of spatial processes.

Computational Inference of Genome-Wide Protein-DNA Interactions Using High-Throughput Genomic Data

Transcriptional regulation has been studied intensively in recent decades. One important aspect of this regulation is the interaction between regulatory proteins, such as transcription factors (TF) and nucleosomes, and the genome. Different high-throughput techniques have been invented to map these interactions genome-wide, including ChIP-based methods (ChIP-chip, ChIP-seq, etc.), nuclease digestion methods (DNase-seq, MNase-seq, etc.), and others. However, a single experimental technique often only provides partial and noisy information about the whole picture of protein-DNA interactions. Therefore, the overarching goal of this dissertation is to provide computational developments for jointly modeling different experimental datasets to achieve a holistic inference on the protein-DNA interaction landscape.

We first present a computational framework that can incorporate the protein binding information in MNase-seq data into a thermodynamic model of protein-DNA interaction. We use a correlation-based objective function to model the MNase-seq data and a Markov chain Monte Carlo method to maximize the function. Our results show that the inferred protein-DNA interaction landscape is concordant with the MNase-seq data and provides a mechanistic explanation for the experimentally collected MNase-seq fragments. Our framework is flexible and can easily incorporate other data sources. To demonstrate this flexibility, we use prior distributions to integrate experimentally measured protein concentrations.

We also study the ability of DNase-seq data to position nucleosomes. Traditionally, DNase-seq has only been widely used to identify DNase hypersensitive sites, which tend to be open chromatin regulatory regions devoid of nucleosomes. We reveal for the first time that DNase-seq datasets also contain substantial information about nucleosome translational positioning, and that existing DNase-seq data can be used to infer nucleosome positions with high accuracy. We develop a Bayes-factor-based nucleosome scoring method to position nucleosomes using DNase-seq data. Our approach utilizes several effective strategies to extract nucleosome positioning signals from the noisy DNase-seq data, including jointly modeling data points across the nucleosome body and explicitly modeling the quadratic and oscillatory DNase I digestion pattern on nucleosomes. We show that our DNase-seq-based nucleosome map is highly consistent with previous high-resolution maps. We also show that the oscillatory DNase I digestion pattern is useful in revealing the nucleosome rotational context around TF binding sites.

Finally, we present a state-space model (SSM) for jointly modeling different kinds of genomic data to provide an accurate view of the protein-DNA interaction landscape. We also provide an efficient expectation-maximization algorithm to learn model parameters from data. We first show in simulation studies that the SSM can effectively recover underlying true protein binding configurations. We then apply the SSM to model real genomic data (both DNase-seq and MNase-seq data). Through incrementally increasing the types of genomic data in the SSM, we show that different data types can contribute complementary information for the inference of protein binding landscape and that the most accurate inference comes from modeling all available datasets.

This dissertation provides a foundation for future research by taking a step toward the genome-wide inference of protein-DNA interaction landscape through data integration.

The FUELCON meta-architecture, in the landscape of intelligent technologies for refuelling

The conception of the FUELCON architecture, of a composite tool for the generation and validation of patterns for assigning fuel assemblies to the positions in the grid of a reactor core section, has undergone an evolution throughout the history of the project. Different options for various subtask were possible, envisioned, or actually explored or adopted. We project these successive, or even concomitant configurations of the architecture, into a meta-architecture, which quite not by chance happens to reflect basic choices in the field's history over the last decade.

The Medway Valley: a Kent landscape transformed

In 1750 the lower Medway Valley, the area between the towns of Maidstone and Rochester, was firmly part of Kent's 'Garden of England'. A century later, this tranquil, agrarian landscape had been transformed into a hive of industry and commerce, through the emergence of papermaking, cement manufacture, brickmaking, brewing, ship and barge building, seed crushing and engineering. The lower Medway Valley became synonymous with the production of Portland cement, stock bricks and the steam engines of Aveling and Porter, yet, by the end of the Second World War, much of this industry was gone. "The Medway Valley: A Kent Landscape Transformed", the first Victoria County History publication in Kent for over 75 years, charts this cyclical story of landscape change. It explores how the quiet, rural landscape of a collection of eight riverside parishes around Rochester was dramatically transformed during industrialization, before returning to its formal rural state. This volume traces the impact of industrial development and decline on the valley and its people. It details changing patterns of work and society, the creation of new settlements and the pivotal role of the river in all aspects of village life reflecting two centuries of change and upheaval.