text:
@article{ ISI:000470947700052,
Author = {Porter, Kenneth D. H. and Quilliam, Richard S. and Reaney, Sim M. and
   Oliver, David M.},
Title = {{High resolution characterisation of E. coli proliferation profiles in
   livestock faeces}},
Journal = {{WASTE MANAGEMENT}},
Year = {{2019}},
Volume = {{87}},
Pages = {{537-545}},
Month = {{MAR 15}},
Abstract = {{Agricultural intensification can lead to high volumes of livestock
   faeces being applied to land, either as solid or liquid manures or via
   direct defecation, and can result in reservoirs of faecal indicator
   organisms (FIOs) persisting within farmland. Understanding the survival
   of FIOs, e.g. E. coli, in agricultural environments, and in particular
   within different livestock faeces, is key to developing catchment
   management practices for the protection of ecosystem services provided
   by clean water. Frequently, controlled laboratory studies, under
   constant temperature regimes, are used to determine the impact of
   environmental factors on E. coli persistence in livestock faeces;
   however, such studies oversimplify the diurnal variations and
   interactions of real world conditions. The aim of this study was to
   investigate the survival of E. coli using a controlled environment
   facility, which simulated diurnal variation of temperatures typically
   experienced during a British spring and summer. The approach provided a
   comparison of E. coli persistence profiles within faeces of sheep, beef
   cattle and dairy cattle to allow novel interpretations of E. coli
   regrowth patterns in contrasting livestock faeces in the period
   immediately post-defecation. Thus, the coupling of a tightly controlled
   environment facility with high resolution monitoring enabled the
   development of a new non-linear, asymptotic description of E. coli
   proliferation in livestock faeces, with increased potential for E. coli
   growth observed during warmer temperatures for all livestock types.
   While this study focused on temperatures typical of the UK, the
   occurrence of a phase of E. coli regrowth has implications for microbial
   water quality management worldwide. (C) 2019 The Authors. Published by
   Elsevier Ltd.}},
DOI = {{10.1016/j.wasman.2019.02.037}},
ISSN = {{0956-053X}},
Times-Cited = {{0}},
Unique-ID = {{ISI:000470947700052}},
}

@article{ ISI:000459984600016,
Author = {Snell, M. A. and Barker, P. A. and Surridge, B. W. J. and Benskin, C.
   McW H. and Barber, N. and Reaney, S. M. and Tych, W. and Mindham, D. and
   Large, A. R. G. and Burke, S. and Haygarth, P. M.},
Title = {{Strong and recurring seasonality revealed within stream diatom
   assemblages}},
Journal = {{SCIENTIFIC REPORTS}},
Year = {{2019}},
Volume = {{9}},
Month = {{MAR 1}},
Abstract = {{Improving stream water quality in agricultural landscapes is an
   ecological priority and a legislative duty for many governments.
   Ecosystem health can be effectively characterised by organisms sensitive
   to water quality changes such as diatoms, single-celled algae that are a
   ubiquitous component of stream benthos. Diatoms respond within daily
   timescales to variables including light, temperature, nutrient
   availability and flow conditions that result from weather and land use
   characteristics. However, little consideration has been given to the
   ecological dynamics of diatoms through repeated seasonal cycles when
   assessing trajectories of stream function, even in catchments actively
   managed to reduce human pressures. Here, six years of monthly diatom
   samples from three independent streams, each receiving differing levels
   of diffuse agricultural pollution, reveal robust and repeated seasonal
   variation. Predicted seasonal changes in climate-related variables and
   anticipated ecological impacts must be fully captured in future
   ecological and water quality assessments, if the apparent resistance of
   stream ecosystems to pollution mitigation measures is to be better
   understood.}},
DOI = {{10.1038/s41598-018-37831-w}},
Article-Number = {{3313}},
ISSN = {{2045-2322}},
ResearcherID-Numbers = {{Reaney, Sim M/H-2951-2013
   Tych, Wlodzimierz/K-6510-2012
   }},
ORCID-Numbers = {{Reaney, Sim M/0000-0003-3063-2044
   Tych, Wlodzimierz/0000-0003-1655-844X
   Barker, Philip/0000-0002-5334-9201
   Haygarth, Philip/0000-0002-1672-6290}},
Times-Cited = {{0}},
Unique-ID = {{ISI:000459984600016}},
}

@article{ ISI:000448821900119,
Author = {Adams, Russell and Quinn, Paul and Barber, Nick and Reaney, Sim},
Title = {{The Role of Attenuation and Land Management in Small Catchments to
   Remove Sediment and Phosphorus: A Modelling Study of Mitigation Options
   and Impacts}},
Journal = {{WATER}},
Year = {{2018}},
Volume = {{10}},
Number = {{9}},
Month = {{SEP}},
Abstract = {{It is well known that soil, hillslopes, and watercourses in small
   catchments possess a degree of natural attenuation that affects both the
   shape of the outlet hydrograph and the transport of nutrients and
   sediments. The widespread adoption of Natural Based Solutions (NBS)
   practices in the headwaters of these catchments is expected to add
   additional attenuation primarily through increasing the amount of new
   storage available to accommodate flood flows. The actual type of NBS
   features used to add storage could include swales, ditches, and small
   ponds (acting as sediment traps). Here, recent data collected from
   monitored features (from the Demonstration Test Catchments project in
   the Newby Beck catchment (Eden) in northwest England) were used to
   provide first estimates of the percentages of the suspended sediment
   (SS) and total phosphorus (TP) loads that could be trapped by additional
   features. The Catchment Runoff Attenuation Flux Tool (CRAFT) was then
   used to model this catchment (Newby Beck) to investigate whether adding
   additional attenuation, along with the ability to trap and retain SS
   (and attached P), will have any effect on the flood peak and associated
   peak concentrations of SS and TP. The modelling tested the hypothesis
   that increasing the amount of new storage (thus adding attenuation
   capacity) in the catchment will have a beneficial effect. The model
   results implied that a small decrease of the order of 5-10\% in the peak
   concentrations of SS and TP was observable after adding 2000 m(3) to
   8000 m(3) of additional storage to the catchment.}},
DOI = {{10.3390/w10091227}},
Article-Number = {{1227}},
ISSN = {{2073-4441}},
ResearcherID-Numbers = {{Reaney, Sim M/H-2951-2013}},
ORCID-Numbers = {{Reaney, Sim M/0000-0003-3063-2044}},
Times-Cited = {{0}},
Unique-ID = {{ISI:000448821900119}},
}

@article{ ISI:000424121800069,
Author = {Oliver, David M. and Bartie, Phil J. and Heathwaite, A. Louise and
   Reaney, Sim M. and Parnell, Jared A. Q. and Quilliam, Richard S.},
Title = {{A catchment-scale model to predict spatial and temporal burden of E.
   coli on pasture from grazing livestock}},
Journal = {{SCIENCE OF THE TOTAL ENVIRONMENT}},
Year = {{2018}},
Volume = {{616}},
Pages = {{678-687}},
Month = {{MAR}},
Abstract = {{Effective management of diffuse microbial water pollution from
   agriculture requires a fundamental understanding of how spatial patterns
   of microbial pollutants, e.g. E. coli, vary over time at the landscape
   scale. The aim of this study was to apply the Visualising Pathogen \&
   Environmental Risk (ViPER) model, developed to predict E. coli burden on
   agricultural land, in a spatially distributed manner to two contrasting
   catchments in order to map and understand changes in E. coli burden
   contributed to land from grazing livestock. The model was applied to the
   River Ayr and Lunan Water catchments, with significant correlations
   observed between area of improved grassland and the maximum total E.
   coli per 1 km(2) grid cell (Ayr: r = 0.57; p < 0.001, Lunan: r = 0.32; p
   < 0.001). There was a significant difference in the predicted maximum E.
   coli burden between seasons in both catchments, with summer and autumn
   predicted to accrue higher E. coli contributions relative to spring and
   winter (P < 0.001), driven largely by livestock presence. The ViPER
   model thus describes, at the landscape scale, spatial nuances in the
   vulnerability of E. coli loading to land as driven by stocking density
   and livestock grazing regimes. Resulting risk maps therefore provide the
   underpinning evidence to inform spatially-targeted decision-making with
   respect to managing sources of E. coli in agricultural environments. (c)
   2017 The Author(s). Published by Elsevier B.V.}},
DOI = {{10.1016/j.scitotenv.2017.10.263}},
ISSN = {{0048-9697}},
EISSN = {{1879-1026}},
ResearcherID-Numbers = {{Reaney, Sim M/H-2951-2013
   Heathwaite, Ann Louise/F-7002-2014
   }},
ORCID-Numbers = {{Reaney, Sim M/0000-0003-3063-2044
   Heathwaite, Ann Louise/0000-0001-8791-0039
   Oliver, David/0000-0002-6200-562X}},
Times-Cited = {{0}},
Unique-ID = {{ISI:000424121800069}},
}

@article{ ISI:000410352900050,
Author = {Porter, Kenneth D. H. and Reaney, Sim M. and Quilliam, Richard S. and
   Burgess, Chris and Oliver, David M.},
Title = {{Predicting diffuse microbial pollution risk across catchments: The
   performance of SCIMAP and recommendations for future development}},
Journal = {{SCIENCE OF THE TOTAL ENVIRONMENT}},
Year = {{2017}},
Volume = {{609}},
Pages = {{456-465}},
Month = {{DEC 31}},
Abstract = {{Microbial pollution of surface waters in agricultural catchments can be
   a consequence of poor farm management practices, such as excessive
   stocking of livestock on vulnerable land or inappropriate handling of
   manures and slurries. Catchment interventions such as fencing of
   watercourses, streamside buffer strips and constructed wetlands have the
   potential to reduce faecal pollution of watercourses. However these
   interventions are expensive and occupy valuable productive land. There
   is, therefore, a requirement for tools to assist in the spatial
   targeting of such interventions to areas where they will have the
   biggest impact on water quality improvements whist occupying the minimal
   amount of productive land. SCIMAP is a risk-based model that has been
   developed for this purpose but with a focus on diffuse sediment and
   nutrient pollution. In this study we investigated the performance of
   SCIMAP in predicting microbial pollution of watercourses and assessed
   modelled outputs of E. coli, a common faecal indicator organism (FIO),
   against observed water quality information. SCIMAP was applied to two
   river catchments in the UK. SCIMAP uses land cover riskweightings, which
   are routed through the landscape based on hydrological connectivity to
   generate catchment scale maps of relative in-stream pollution risk.
   Assessment of the model's performance and derivation of optimum land
   cover risk weightings was achieved using a Monte-Carlo sampling
   approach. Performance of the SCIMAP framework for informing on FIO risk
   was variable with better performance in the Yealm catchment (r(s) =
   0.88; p < 0.01) than the Wyre (r(s) = -0.36; p > 0.05). Across both
   catchments much uncertainty was associated with the application of
   optimum risk weightings attributed to different land use classes.
   Overall, SCIMAP showed potential as a useful tool in the spatial
   targeting of FIO diffuse pollution management strategies; however,
   improvements are required to transition the existing SCIMAP framework to
   a robust FIO risk-mapping tool. (C) 2017 The Authors. Published by
   Elsevier B.V.}},
DOI = {{10.1016/j.scitotenv.2017.07.186}},
ISSN = {{0048-9697}},
EISSN = {{1879-1026}},
ResearcherID-Numbers = {{Reaney, Sim M/H-2951-2013
   }},
ORCID-Numbers = {{Reaney, Sim M/0000-0003-3063-2044
   Oliver, David/0000-0002-6200-562X}},
Times-Cited = {{4}},
Unique-ID = {{ISI:000410352900050}},
}

@article{ ISI:000409294000013,
Author = {Perks, M. T. and Warburton, J. and Bracken, L. J. and Reaney, S. M. and
   Emery, S. B. and Hirst, S.},
Title = {{Use of spatially distributed time-integrated sediment sampling networks
   and distributed fine sediment modelling to inform catchment management}},
Journal = {{JOURNAL OF ENVIRONMENTAL MANAGEMENT}},
Year = {{2017}},
Volume = {{202}},
Number = {{2, SI}},
Pages = {{469-478}},
Month = {{NOV 1}},
Abstract = {{Under the EU Water Framework Directive, suspended sediment is omitted
   from environmental quality standards and compliance targets. This
   omission is partly explained by difficulties in assessing the complex
   dose-response of ecological communities. But equally, it is hindered by
   a lack of spatially distributed estimates of suspended sediment
   variability across catchments. In this paper, we demonstrate the
   inability of traditional, discrete sampling campaigns for assessing
   exposure to fine sediment. Sampling frequencies based on Environmental
   Quality Standard protocols, whilst reflecting typical manual sampling
   constraints, are unable to determine the magnitude of sediment exposure
   with an acceptable level of precision. Deviations from actual
   concentrations range between -35 and +20\% based on the interquartile
   range of simulations. As an alternative, we assess the value of
   low-cost,, suspended sediment sampling networks for quantifying
   suspended sediment transfer (SST). In this study of the 362 km(2) upland
   Esk catchment we observe that spatial patterns of sediment flux are
   consistent over the two year monitoring period across a network of 17
   monitoring sites. This enables the key contributing sub-catchments of
   Butter Beck (SST: 1141 t km(2) yr(-1)) and Glaisdale Beck (SST: 841 t
   km(2) yr(-1)) to be identified. The time -integrated samplers offer a
   feasible alternative to traditional infrequent and discrete sampling
   approaches for assessing spatio-temporal changes in contamination. In
   conjunction with a spatially distributed diffuse pollution model
   (SCIMAP), time-integrated sediment sampling is an effective means of
   identifying critical sediment source areas in the catchment, which can
   better inform sediment management strategies for pollution prevention
   and control. (C) 2017 Elsevier Ltd. All rights reserved.}},
DOI = {{10.1016/j.jenvman.2017.01.045}},
ISSN = {{0301-4797}},
EISSN = {{1095-8630}},
ResearcherID-Numbers = {{Reaney, Sim M/H-2951-2013
   Emery, Steven/L-9926-2015
   Bracken, Louise/L-8198-2018
   }},
ORCID-Numbers = {{Reaney, Sim M/0000-0003-3063-2044
   Bracken, Louise/0000-0002-1268-5516
   Perks, Matthew/0000-0002-6960-5484}},
Times-Cited = {{6}},
Unique-ID = {{ISI:000409294000013}},
}

@article{ ISI:000370246000034,
Author = {Ockenden, M. C. and Deasy, C. E. and Benskin, C. McW. H. and Beven, K.
   J. and Burke, S. and Collins, A. L. and Evans, R. and Falloon, P. D. and
   Forber, K. J. and Hiscock, K. M. and Hollaway, M. J. and Kahana, R. and
   Macleod, C. J. A. and Reaney, S. M. and Snell, M. A. and Villamizar, M.
   L. and Wearing, C. and Withers, P. J. A. and Zhou, J. G. and Haygarth,
   P. M.},
Title = {{Changing climate and nutrient transfers: Evidence from high temporal
   resolution concentration-flow dynamics in headwater catchments}},
Journal = {{SCIENCE OF THE TOTAL ENVIRONMENT}},
Year = {{2016}},
Volume = {{548}},
Pages = {{325-339}},
Month = {{APR 1}},
Abstract = {{We hypothesise that climate change, together with intensive agricultural
   systems, will increase the transfer of pollutants from land to water and
   impact on stream health. This study builds, for the first time, an
   integrated assessment of nutrient transfers, bringing together a)
   high-frequency data from the outlets of two surface water dominated,
   headwater (similar to 10 km(2)) agricultural catchments, b)
   event-by-event analysis of nutrient transfers, c) concentration duration
   curves for comparison with EU Water Framework Directive water quality
   targets, d) event analysis of location-specific, sub-daily rainfall
   projections (UKCP, 2009), and e) a linear model relating storm rainfall
   to phosphorus load. These components, in combination, bring innovation
   and new insight into the estimation of future phosphorus transfers,
   which was not available from individual components. The data
   demonstrated two features of particular concern for climate change
   impacts. Firstly, the bulk of the suspended sediment and total
   phosphorus (TP) load (greater than 90\% and 80\% respectively) was
   transferred during the highest discharge events. The linear model of
   rainfall-driven TP transfers estimated that, with the projected increase
   in winter rainfall (+ 8\% to + 17\% in the catchments by 2050s), annual
   event loads might increase by around 9\% on average, if agricultural
   practices remain unchanged. Secondly, events following dry periods of
   several weeks, particularly in summer, were responsible for high
   concentrations of phosphorus, but relatively low loads. The high
   concentrations, associated with low flow, could become more frequent or
   last longer in the future, with a corresponding increase in the length
   of time that threshold concentrations (e.g. for water quality status)
   are exceeded. The results suggest that in order to build resilience in
   stream health and help mitigate potential increases in diffuse
   agricultural water pollution due to climate change, land management
   practices should target controllable risk factors, such as soil nutrient
   status, soil condition and crop cover. (C) 2016 Elsevier B.V. All rights
   reserved.}},
DOI = {{10.1016/j.scitotenv.2015.12.086}},
ISSN = {{0048-9697}},
EISSN = {{1879-1026}},
ResearcherID-Numbers = {{Beven, Keith J/F-8707-2011
   Reaney, Sim M/H-2951-2013
   Collins, Adrian/V-5938-2018
   }},
ORCID-Numbers = {{Reaney, Sim M/0000-0003-3063-2044
   Collins, Adrian/0000-0001-8790-8473
   Hollaway, Michael/0000-0003-0386-2696
   Haygarth, Philip/0000-0002-1672-6290
   Forber, Kirsty Jessica/0000-0001-7182-9586
   Benskin, Clare/0000-0002-8058-6886
   Zhou, Jian Guo/0000-0002-4262-1898}},
Times-Cited = {{43}},
Unique-ID = {{ISI:000370246000034}},
}

@article{ ISI:000369491500006,
Author = {Oliver, David M. and Porter, Kenneth D. H. and Pachepsky, Yakov A. and
   Muirhead, Richard W. and Reaney, Sim M. and Coffey, Rory and Kay, David
   and Milledge, David G. and Hong, Eunmi and Anthony, Steven G. and Page,
   Trevor and Bloodworth, Jack W. and Mellander, Per-Erik and Carbonneau,
   Patrice E. and McGrane, Scott J. and Quilliam, Richard S.},
Title = {{Predicting microbial water quality with models: Over-arching questions
   for managing risk in agricultural catchments}},
Journal = {{SCIENCE OF THE TOTAL ENVIRONMENT}},
Year = {{2016}},
Volume = {{544}},
Pages = {{39-47}},
Month = {{FEB 15}},
Abstract = {{The application of models to predict concentrations of faecal indicator
   organisms (FIOs) in environmental systems plays an important role for
   guiding decision-making associated with the management of microbial
   water quality. In recent years there has been an increasing demand by
   policy-makers for models to help inform FIO dynamics in order to
   prioritise efforts for environmental and human-health protection.
   However, given the limited evidence-base on which FIO models are built
   relative to other agricultural pollutants (e.g. nutrients) it is
   imperative that the end-user expectations of FIO models are
   appropriately managed. In response, this commentary highlights four
   over-arching questions associated with: (i) model purpose; (ii)
   modelling approach; (iii) data availability; and (iv) model application,
   that must be considered as part of good practice prior to the deployment
   of any modelling approach to predict FIO behaviour in catchment systems.
   A series of short and longer-term research priorities are proposed in
   response to these questions in order to promote better model deployment
   in the field of catchment microbial dynamics. (C) 2015 The Authors.
   Published by Elsevier B.V.}},
DOI = {{10.1016/j.scitotenv.2015.11.086}},
ISSN = {{0048-9697}},
EISSN = {{1879-1026}},
ResearcherID-Numbers = {{Pachepsky, Yakov/H-7236-2019
   Coffey, Rory P/G-4542-2014
   Reaney, Sim M/H-2951-2013
   Quilliam, Richard/E-6920-2011
   }},
ORCID-Numbers = {{Pachepsky, Yakov/0000-0003-0232-6090
   Coffey, Rory P/0000-0001-5941-0205
   Reaney, Sim M/0000-0003-3063-2044
   Quilliam, Richard/0000-0001-7020-4410
   Oliver, David/0000-0002-6200-562X
   McGrane, Scott/0000-0002-5277-1347
   Milledge, David/0000-0003-4077-4898
   Muirhead, Richard/0000-0002-0913-561X}},
Times-Cited = {{24}},
Unique-ID = {{ISI:000369491500006}},
}

@article{ ISI:000353910900019,
Author = {Perks, M. T. and Owen, G. J. and Benskin, C. McW. H. and Jonczyk, J. and
   Deasy, C. and Burke, S. and Reaney, S. M. and Haygarth, P. M.},
Title = {{Dominant mechanisms for the delivery of fine sediment and phosphorus to
   fluvial networks draining grassland dominated headwater catchments}},
Journal = {{SCIENCE OF THE TOTAL ENVIRONMENT}},
Year = {{2015}},
Volume = {{523}},
Pages = {{178-190}},
Month = {{AUG 1}},
Abstract = {{Recent advances in monitoring technology have enabled high frequency,
   in-situ measurements of total phosphorus and total reactive phosphorus
   to be undertaken with high precision, whilst turbidity can provide an
   excellent surrogate for suspended sediment. Despite these measurements
   being fundamental to understanding the mechanisms and flow paths that
   deliver these constituents to river networks, there is a paucity of such
   data for headwater agricultural catchments. The aim of this paper is to
   deduce the dominant mechanisms for the delivery of fine sediment and
   phosphorus to an upland river network in the UK through characterisation
   of the temporal variability of hydrological fluxes, and associated
   soluble and particulate concentrations for the period spanning March
   2012-February 2013. An assessment of the factors producing constituent
   hysteresis is undertaken following factor analysis (FA) on a suite of
   measured environmental variables representing the fluvial and wider
   catchment conditions prior to, and during catchment-wide hydrological
   events. Analysis indicates that suspended sediment is delivered to the
   fluvial system predominantly via rapidly responding pathways driven by
   event hydrology. However, evidence of complex, figure-of-eight
   hysteresis is observed following periods of hydrological quiescence,
   highlighting the importance of preparatory processes. Sediment delivery
   via a slow moving, probably sub-surface pathway does occur, albeit
   infrequently and during low magnitude events at the catchment outlet.
   Phosphorus is revealed to have a distinct hysteretic response to that of
   suspended sediment, with sub-surface pathways dominating. However, high
   magnitude events were observed to exhibit threshold-like behaviour,
   whereby activation and connection of usually disconnected depositional
   zones to the fluvial networks results in the movement of vast phosphorus
   fluxes. Multiple pathways are observed for particulate and soluble
   constituents, highlighting the challenges faced in mitigating the
   delivery of contaminant fluxes to headwater river systems. Crown
   Copyright (C) 2015 Published by Elsevier B.V. All rights reserved.}},
DOI = {{10.1016/j.scitotenv.2015.03.008}},
ISSN = {{0048-9697}},
EISSN = {{1879-1026}},
ResearcherID-Numbers = {{Reaney, Sim M/H-2951-2013
   }},
ORCID-Numbers = {{Reaney, Sim M/0000-0003-3063-2044
   Benskin, Clare/0000-0002-8058-6886
   Perks, Matthew/0000-0002-6960-5484
   Haygarth, Philip/0000-0002-1672-6290}},
Times-Cited = {{26}},
Unique-ID = {{ISI:000353910900019}},
}

@article{ ISI:000353073700018,
Author = {Greene, S. and Johnes, P. J. and Bloomfield, J. P. and Reaney, S. M. and
   Lawley, R. and Elkhatib, Y. and Freer, J. and Odoni, N. and Macleod, C.
   J. A. and Percy, B.},
Title = {{A geospatial framework to support integrated biogeochemical modelling in
   the United Kingdom}},
Journal = {{ENVIRONMENTAL MODELLING \& SOFTWARE}},
Year = {{2015}},
Volume = {{68}},
Pages = {{219-232}},
Month = {{JUN}},
Abstract = {{Anthropogenic impacts on the aquatic environment, especially in the
   context of nutrients, provide a major challenge for water resource
   management. The heterogeneous nature of policy relevant management units
   (e.g. catchments), in terms of environmental controls on nutrient source
   and transport, leads to the need for holistic management. However,
   current strategies are limited by current understanding and knowledge
   that is transferable between spatial scales and landscape typologies.
   This study presents a spatially-explicit framework to support the
   modelling of nutrients from land to water, encompassing environmental
   and spatial complexities. The framework recognises nine homogeneous
   landscape units, distinct in terms of sensitivity of nutrient losses to
   waterbodies. The functionality of the framework is demonstrated by
   supporting an exemplar nutrient model, applied within the Environmental
   Virtual Observatory pilot (EVOp) cloud cyber-infrastructure. We
   demonstrate scope for the use of the framework as a management decision
   support tool and for further development of integrated biogeochemical
   modelling. (C) 2015 The Authors. Published by Elsevier Ltd.}},
DOI = {{10.1016/j.envsoft.2015.02.012}},
ISSN = {{1364-8152}},
EISSN = {{1873-6726}},
ResearcherID-Numbers = {{Johnes, Penny J/D-1381-2009
   Freer, Jim/C-7335-2009
   Reaney, Sim M/H-2951-2013
   Elkhatib, Yehia/G-9800-2013
   }},
ORCID-Numbers = {{Johnes, Penny J/0000-0003-1605-6896
   Freer, Jim/0000-0001-6388-7890
   Reaney, Sim M/0000-0003-3063-2044
   Elkhatib, Yehia/0000-0003-4639-436X
   Bloomfield, John/0000-0002-5730-1723}},
Times-Cited = {{12}},
Unique-ID = {{ISI:000353073700018}},
}

@article{ ISI:000342632000005,
Author = {Pattison, Ian and Lane, Stuart N. and Hardy, Richard J. and Reaney, Sim
   M.},
Title = {{The role of tributary relative timing and sequencing in controlling
   large floods}},
Journal = {{WATER RESOURCES RESEARCH}},
Year = {{2014}},
Volume = {{50}},
Number = {{7}},
Pages = {{5444-5458}},
Month = {{JUL}},
Abstract = {{Hydrograph convolution is a product of tributary inputs from across the
   watershed. The time-space distribution of precipitation, the biophysical
   processes that control the conversion of precipitation to runoff and
   channel flow conveyance processes, are heterogeneous and different areas
   respond to rainfall in different ways. We take a subwatershed approach
   to this and account for tributary flow magnitude, relative timing, and
   sequencing. We hypothesize that as the scale of the watershed increases
   so we may start to see systematic differences in subwatershed
   hydrological response. We test this hypothesis for a large flood (T >
   100 years) in a large watershed in northern England. We undertake a
   sensitivity analysis of the effects of changing subwatershed
   hydrological response using a hydraulic model. Delaying upstream
   tributary peak flow timing to make them asynchronous from downstream
   subwatersheds reduced flood magnitude. However, significant hydrograph
   adjustment in any one subwatershed was needed for meaningful reductions
   in stage downstream, although smaller adjustments in multiple
   tributaries resulted in comparable impacts. For larger hydrograph
   adjustments, the effect of changing the timing of two tributaries
   together was lower than the effect of changing each one separately. For
   smaller adjustments synergy between two subwatersheds meant the effect
   of changing them together could be greater than the sum of the parts.
   Thus, this work shows that while the effects of modifying biophysical
   catchment properties diminishes with scale due to dilution effects,
   their impact on relative timing of tributaries may, if applied in the
   right locations, be an important element of flood management.}},
DOI = {{10.1002/2013WR014067}},
ISSN = {{0043-1397}},
EISSN = {{1944-7973}},
ResearcherID-Numbers = {{Reaney, Sim M/H-2951-2013}},
ORCID-Numbers = {{Reaney, Sim M/0000-0003-3063-2044}},
Times-Cited = {{11}},
Unique-ID = {{ISI:000342632000005}},
}

@article{ ISI:000330743000045,
Author = {Reaney, S. M. and Bracken, L. J. and Kirkby, M. J.},
Title = {{The importance of surface controls on overland flow connectivity in
   semi-arid environments: results from a numerical experimental approach}},
Journal = {{HYDROLOGICAL PROCESSES}},
Year = {{2014}},
Volume = {{28}},
Number = {{4}},
Pages = {{2116-2128}},
Month = {{FEB 15}},
Abstract = {{In semi-arid environments, the characteristics of the land surface
   determine how rainfall is transformed into surface runoff and influences
   how this runoff moves from the hillslopes into river channels. Whether
   or not water reaches the river channel is determined by the hydrological
   connectivity. This paper uses a numerical experiment-based approach to
   systematically assess the effects of slope length, gradient, flow path
   convergence, infiltration rates and vegetation patterns on the
   generation and connectivity of runoff. The experiments were performed
   with the Connectivity of Runoff Model, 2D version distributed,
   physically based, hydrological model. The experiments presented are set
   within a semi-arid environment, characteristic of south-eastern Spain,
   which is subject to low frequency high rainfall intensity storm events.
   As a result, the dominant hydrological processes are infiltration excess
   runoff generation and surface flow dynamics. The results from the
   modelling experiments demonstrate that three surface factors are
   important in determining the form of the discharge hydrograph: the slope
   length, the slope gradient and the infiltration characteristics at the
   hillslope-channel connection. These factors are all related to the time
   required for generated runoff to reach an efficient flow channel,
   because once in this channel, the transmission losses significantly
   decrease. Because these factors are distributed across the landscape,
   they have a fundamental role in controlling the landscape hydrological
   response to storm events. Copyright (c) 2013 John Wiley \& Sons, Ltd.}},
DOI = {{10.1002/hyp.9769}},
ISSN = {{0885-6087}},
EISSN = {{1099-1085}},
ResearcherID-Numbers = {{Reaney, Sim M/H-2951-2013
   Bracken, Louise/L-8198-2018}},
ORCID-Numbers = {{Reaney, Sim M/0000-0003-3063-2044
   Bracken, Louise/0000-0002-1268-5516}},
Times-Cited = {{38}},
Unique-ID = {{ISI:000330743000045}},
}

@article{ ISI:000338637700010,
Author = {Snell, M. A. and Barker, P. A. and Surridge, B. W. J. and Large, A. R.
   G. and Jonczyk, J. and Benskin, C. Mcw. H. and Reaney, S. and Perks, M.
   T. and Owen, G. J. and Cleasby, W. and Deasy, C. and Burke, S. and
   Haygarth, P. M.},
Title = {{High frequency variability of environmental drivers determining benthic
   community dynamics in headwater streams}},
Journal = {{ENVIRONMENTAL SCIENCE-PROCESSES \& IMPACTS}},
Year = {{2014}},
Volume = {{16}},
Number = {{7}},
Pages = {{1629-1636}},
Abstract = {{Headwater streams are an important feature of the landscape, with their
   diversity in structure and associated ecological function providing a
   potential natural buffer against downstream nutrient export.
   Phytobenthic communities, dominated in many headwaters by diatoms, must
   respond to physical and chemical parameters that can vary in magnitude
   within hours, whereas the ecological regeneration times are much longer.
   How diatom communities develop in the fluctuating, dynamic environments
   characteristic of headwaters is poorly understood. Deployment of near-
   continuous monitoring technology in sub-catchments of the River Eden, NW
   England, provides the opportunity for measurement of temporal
   variability in stream discharge and nutrient resource supply to benthic
   communities, as represented by monthly diatom samples collected over two
   years. Our data suggest that the diatom communities and the derived
   Trophic Diatom Index, best reflect stream discharge conditions over the
   preceding 18-21 days and Total Phosphorus concentrations over a wider
   antecedent window of 7-21 days. This is one of the first quantitative
   assessments of long-term diatom community development in response to
   continuously-measured stream nutrient concentration and discharge
   fluctuations. The data reveal the sensitivity of these headwater
   communities to mean conditions prior to sampling, with flow as the
   dominant variable. With sufficient understanding of the role of
   antecedent conditions, these methods can be used to inform
   interpretation of monitoring data, including those collected under the
   European Water Framework Directive and related mitigation efforts.}},
DOI = {{10.1039/c3em00680h}},
ISSN = {{2050-7887}},
EISSN = {{2050-7895}},
ResearcherID-Numbers = {{Barker, Philip/J-5938-2012
   Reaney, Sim M/H-2951-2013
   }},
ORCID-Numbers = {{Reaney, Sim M/0000-0003-3063-2044
   Barker, Philip/0000-0002-5334-9201
   Haygarth, Philip/0000-0002-1672-6290
   Benskin, Clare/0000-0002-8058-6886
   Perks, Matthew/0000-0002-6960-5484}},
Times-Cited = {{6}},
Unique-ID = {{ISI:000338637700010}},
}

@article{ ISI:000317554000002,
Author = {Bracken, L. J. and Wainwright, J. and Ali, G. A. and Tetzlaff, D. and
   Smith, M. W. and Reaney, S. M. and Roy, A. G.},
Title = {{Concepts of hydrological connectivity: Research approaches, pathways and
   future agendas}},
Journal = {{EARTH-SCIENCE REVIEWS}},
Year = {{2013}},
Volume = {{119}},
Pages = {{17-34}},
Month = {{APR}},
Abstract = {{For effective catchment management and intervention in hydrological
   systems a process-based understanding of hydrological connectivity is
   required so that: i) conceptual rather than solely empirical
   understanding drives how systems are interpreted; and ii) there is an
   understanding of how continuous flow fields develop under different sets
   of environmental conditions to enable managers to know when, where and
   how to intervene in catchment processes successfully. In order to direct
   future research into process-based hydrological connectivity this paper:
   i) evaluates the extent to which different concepts of hydrological
   connectivity have emerged from different approaches to measure and
   predict flow in different environments; ii) discusses the extent to
   which these different concepts are mutually compatible; and iii)
   assesses further research to contribute to a unified understanding of
   hydrological processes. Existing research is categorised into five
   different approaches to investigating hydrological connectivity: i)
   evaluating soil moisture patterns (soil moisture connectivity); ii)
   understanding runoff patterns and processes on hillslopes (flow-process
   connectivity); iii) investigating topographic controls
   (terrain-connectivity) including the impact of road networks on
   hydrological connectivity and catchment runoff; iv) developing models to
   explore and predict hydrological connectivity; and v) developing indices
   of hydrological connectivity. Analysis of published research suggests a
   relationship between research group, approach, geographic setting and
   the interpretation of hydrological connectivity. For further
   understanding of hydrological connectivity our knowledge needs to be
   developed using a range of techniques and approaches, there should be
   common understandings between researchers approaching the concept from
   different perspectives, and these meanings need to be communicated
   effectively with those responsible for land management. Crown Copyright
   (C) 2013 Published by Elsevier B.V. All rights reserved.}},
DOI = {{10.1016/j.earscirev.2013.02.001}},
ISSN = {{0012-8252}},
ResearcherID-Numbers = {{Reaney, Sim M/H-2951-2013
   Tetzlaff, Doerthe/N-5228-2019
   Bracken, Louise/L-8198-2018
   Ali, Genevieve/E-3162-2013
   }},
ORCID-Numbers = {{Reaney, Sim M/0000-0003-3063-2044
   Tetzlaff, Doerthe/0000-0002-7183-8674
   Bracken, Louise/0000-0002-1268-5516
   Ali, Genevieve/0000-0001-8219-1346
   Ali, Genevieve/0000-0001-5144-8188
   Smith, Mark/0000-0003-4361-9527}},
Times-Cited = {{187}},
Unique-ID = {{ISI:000317554000002}},
}

@article{ ISI:000313593500016,
Author = {Ali, Genevieve and Oswald, Claire J. and Spence, Christopher and
   Cammeraat, Erik L. H. and McGuire, Kevin J. and Meixner, Thomas and
   Reaney, Sim M.},
Title = {{Towards a unified threshold-based hydrological theory: necessary
   components and recurring challenges}},
Journal = {{HYDROLOGICAL PROCESSES}},
Year = {{2013}},
Volume = {{27}},
Number = {{2}},
Pages = {{313-318}},
Month = {{JAN 15}},
DOI = {{10.1002/hyp.9560}},
Abstract = {{ }},
ISSN = {{1099-1085}},
ResearcherID-Numbers = {{Ali, Genevieve/E-3162-2013
   Reaney, Sim M/H-2951-2013
   McGuire, Kevin/E-7770-2010
   Cammeraat, Erik/G-2863-2010
   }},
ORCID-Numbers = {{Ali, Genevieve/0000-0001-8219-1346
   Reaney, Sim M/0000-0003-3063-2044
   McGuire, Kevin/0000-0001-5751-3956
   Cammeraat, Erik/0000-0003-4398-206X
   Ali, Genevieve/0000-0001-5144-8188}},
Times-Cited = {{31}},
Unique-ID = {{ISI:000313593500016}},
}

@article{ ISI:000312517200002,
Author = {Laniak, Gerard F. and Olchin, Gabriel and Goodall, Jonathan and Voinov,
   Alexey and Hill, Mary and Glynn, Pierre and Whelan, Gene and Geller,
   Gary and Quinn, Nigel and Blind, Michiel and Peckham, Scott and Reaney,
   Sim and Gaber, Noha and Kennedy, Robert and Hughes, Andrew},
Title = {{Integrated environmental modeling: A vision and roadmap for the future}},
Journal = {{ENVIRONMENTAL MODELLING \& SOFTWARE}},
Year = {{2013}},
Volume = {{39}},
Number = {{SI}},
Pages = {{3-23}},
Month = {{JAN}},
Abstract = {{Integrated environmental modeling (IEM) is inspired by modern
   environmental problems, decisions, and policies and enabled by
   transdisciplinary science and computer capabilities that allow the
   environment to be considered in a holistic way. The problems are
   characterized by the extent of the environmental system involved,
   dynamic and interdependent nature of stressors and their impacts,
   diversity of stakeholders, and integration of social, economic, and
   environmental considerations. IEM provides a science-based structure to
   develop and organize relevant knowledge and information and apply it to
   explain, explore, and predict the behavior of environmental systems in
   response to human and natural sources of stress. During the past several
   years a number of workshops were held that brought IEM practitioners
   together to share experiences and discuss future needs and directions.
   In this paper we organize and present the results of these discussions.
   IEM is presented as a landscape containing four interdependent elements:
   applications, science, technology, and community. The elements are
   described from the perspective of their role in the landscape, current
   practices, and challenges that must be addressed. Workshop participants
   envision a global scale IEM community that leverages modern technologies
   to streamline the movement of science-based knowledge from its sources
   in research, through its organization into databases and models, to its
   integration and application for problem solving purposes. Achieving this
   vision will require that the global community of IEM stakeholders
   transcend social, and organizational boundaries and pursue greater
   levels of collaboration. Among the highest priorities for community
   action are the development of standards for publishing IEM data and
   models in forms suitable for automated discovery, access, and
   integration: education of the next generation of environmental
   stakeholders, with a focus on transdisciplinary research, development,
   and decision making: and providing a web-based platform for community
   interactions (e.g., continuous virtual workshops). Published by Elsevier
   Ltd.}},
DOI = {{10.1016/j.envsoft.2012.09.006}},
ISSN = {{1364-8152}},
EISSN = {{1873-6726}},
ResearcherID-Numbers = {{Goodall, Jonathan/B-3663-2009
   Reaney, Sim M/H-2951-2013
   , Nigel/G-2407-2015
   Voinov, Alexey/F-7397-2010
   }},
ORCID-Numbers = {{Goodall, Jonathan/0000-0002-1112-4522
   Reaney, Sim M/0000-0003-3063-2044
   , Nigel/0000-0003-3333-4763
   Voinov, Alexey/0000-0002-2985-4574
   PECKHAM, SCOTT/0000-0002-1373-2396
   Geller, Gary/0000-0002-4490-6002}},
Times-Cited = {{239}},
Unique-ID = {{ISI:000312517200002}},
}

@article{ ISI:000308787500047,
Author = {Milledge, David G. and Lane, Stuart N. and Heathwaite, A. Louise and
   Reaney, Sim M.},
Title = {{A Monte Carlo approach to the inverse problem of diffuse pollution risk
   in agricultural catchments}},
Journal = {{SCIENCE OF THE TOTAL ENVIRONMENT}},
Year = {{2012}},
Volume = {{433}},
Pages = {{434-449}},
Month = {{SEP 1}},
Abstract = {{The hydrological and biogeochemical processes that operate in catchments
   influence the ecological quality of freshwater systems through delivery
   of fine sediment, nutrients and organic matter. Most models that seek to
   characterise the delivery of diffuse pollutants from land to water are
   reductionist. The multitude of processes that are parameterised in such
   models to ensure generic applicability make them complex and difficult
   to test on available data. Here, we outline an alternative - data-driven
   - inverse approach. We apply SCIMAP, a parsimonious risk based model
   that has an explicit treatment of hydrological connectivity. we take a
   Bayesian approach to the inverse problem of determining the risk that
   must be assigned to different land uses in a catchment in order to
   explain the spatial patterns of measured in-stream nutrient
   concentrations. We apply the model to identify the key sources of
   nitrogen (N) and phosphorus (P) diffuse pollution risk in eleven UK
   catchments covering a range of landscapes. The model results show that:
   1) some land use generates a consistently high or low risk of diffuse
   nutrient pollution; but 2) the risks associated with different land uses
   vary both between catchments and between nutrients; and 3) that the
   dominant sources of P and N risk in the catchment are often a function
   of the spatial configuration of land uses. Taken on a case-by-case
   basis, this type of inverse approach may be used to help prioritise the
   focus of interventions to reduce diffuse pollution risk for freshwater
   ecosystems. (C) 2012 Elsevier B.V. All rights reserved.}},
DOI = {{10.1016/j.scitotenv.2012.06.047}},
ISSN = {{0048-9697}},
EISSN = {{1879-1026}},
ResearcherID-Numbers = {{Reaney, Sim M/H-2951-2013
   Lane, Stuart/M-7934-2014
   Heathwaite, Ann Louise/F-7002-2014}},
ORCID-Numbers = {{Reaney, Sim M/0000-0003-3063-2044
   Lane, Stuart/0000-0002-6077-6076
   Milledge, David/0000-0003-4077-4898
   Heathwaite, Ann Louise/0000-0001-8791-0039}},
Times-Cited = {{14}},
Unique-ID = {{ISI:000308787500047}},
}

@article{ ISI:000298778000003,
Author = {Oven, K. J. and Curtis, S. E. and Reaney, S. and Riva, M. and Stewart,
   M. G. and Ohlemueller, R. and Dunn, C. E. and Nodwell, S. and Dominelli,
   L. and Holden, R.},
Title = {{Climate change and health and social care: Defining future hazard,
   vulnerability and risk for infrastructure systems supporting older
   people's health care in England}},
Journal = {{APPLIED GEOGRAPHY}},
Year = {{2012}},
Volume = {{33}},
Number = {{1, SI}},
Pages = {{16-24}},
Month = {{APR}},
Abstract = {{Health and social care systems (including the care needs of the
   population and infrastructures providing health and social care) are
   likely to be influenced by climate change, in particular by the
   increasing frequency and severity of weather-related hazards such as
   floods and heatwaves. Coldwaves will also continue to be challenging in
   the foreseeable future. Protecting people's health and wellbeing from
   the impacts of climate change is especially important for older people,
   as they are particularly vulnerable to climate-related hazards. In
   addition, the proportion of people aged 65 and over is projected to
   increase significantly. This paper addresses these issues through a
   discussion of our work to map variations across England in future
   hazards, vulnerability and risk. We explain how this mapping has been
   used to identify areas of the country where the built infrastructure
   serving the older age group might be most severely impacted by
   climate-related events over the next 20-30 years and where planning for
   adaptation and resilience is most urgently required.
   Based on a review of research on the links between extreme weather
   events and their impacts on older people's health and the care services
   on which they depend, we developed operational definitions of extreme
   weather-related hazards likely to place particular pressure on health
   and social care systems that are essential for older people's health and
   wellbeing. We consider ways to relate these to the latest climate
   projections for the 2030s from the UK Climate Impacts Programme
   (UKCP09); river and coastal flooding projections for the 2050s from the
   2004 UK Government's Foresight Flood and Coastal Defence Project
   (Environment Agency, 2004); and demographic projections for 2031
   produced by the Office for National Statistics, UK. The research
   highlights the complexity of undertaking future hazard and vulnerability
   assessments. Key challenges include: how to define future hazards
   associated with climate change; how to predict and interpret future
   socio-demographic conditions contributing to vulnerability; and how
   geographical variability in hazards and vulnerabilities may combine to
   produce risks at the local level. In contrast to a number of more local
   studies which have focused on the vulnerability of urban populations to
   the impact of climate change (particularly heatwaves), the findings
   highlight the potential vulnerability of older populations in more rural
   regions (often in coastal areas) to a range of extreme weather-related
   hazards in both the North and South of England. (C) 2011 Elsevier Ltd.
   All rights reserved.}},
DOI = {{10.1016/j.apgeog.2011.05.012}},
ISSN = {{0143-6228}},
EISSN = {{1873-7730}},
ResearcherID-Numbers = {{Reaney, Sim M/H-2951-2013
   Brooks, Katya/J-4975-2014}},
ORCID-Numbers = {{Reaney, Sim M/0000-0003-3063-2044
   }},
Times-Cited = {{46}},
Unique-ID = {{ISI:000298778000003}},
}

@article{ ISI:000293485400008,
Author = {Wall, D. and Jordan, P. and Melland, A. R. and Mellander, P. -E. and
   Buckley, C. and Reaney, S. M. and Shortie, G.},
Title = {{Using the nutrient transfer continuum concept to evaluate the European
   Union Nitrates Directive National Action Programme}},
Journal = {{ENVIRONMENTAL SCIENCE \& POLICY}},
Year = {{2011}},
Volume = {{14}},
Number = {{6}},
Pages = {{664-674}},
Month = {{OCT}},
Abstract = {{Agricultural catchments are where farm and landscape management interact
   with policy and science; especially with regard to the implementation
   and evaluation of agri-environmental regulation. The Nitrates Directive
   constrains nitrogen and phosphorus use and management on agricultural
   land across all EU member states and is one of the programmes of
   measures to mitigate eutrophication of water resources under the Water
   Framework Directive. All policies require a robust evaluation tool and
   for the potential diffuse transfer of nutrients from land to water, the
   nutrient transfer continuum concept is applied here as an example
   framework in small (6-30 km(2)) catchments. The experimental design,
   methods and some early results are presented: auditing nutrient sources
   to established levels of compliance is the first stage and considers
   nutrient use and soil status. Studying pathways provides an
   understanding of linkages between the land sources and delivery in
   catchment rivers. This delivery is generally associated with episodic,
   high magnitude transfers and may not necessarily be the only or even
   primary ecological impact in rivers. Critiquing existing delivery/impact
   metrics and defining appropriate standards for identifying trajectories
   associated with diffuse nutrient transfer will be important in ensuring
   that agri-environmental policies are given a fair and thorough
   evaluation over a suitable time period. (C) 2011 Elsevier Ltd. All
   rights reserved.}},
DOI = {{10.1016/j.envsci.2011.05.003}},
ISSN = {{1462-9011}},
ResearcherID-Numbers = {{Wall, david/F-5146-2018
   Reaney, Sim M/H-2951-2013
   }},
ORCID-Numbers = {{Wall, david/0000-0002-2365-0335
   Reaney, Sim M/0000-0003-3063-2044
   Jordan, Philip/0000-0002-0893-4591}},
Times-Cited = {{72}},
Unique-ID = {{ISI:000293485400008}},
}

@article{ ISI:000287291000011,
Author = {Reaney, Sim M. and Lane, Stuart N. and Heathwaite, A. Louise and
   Dugdale, Lucy J.},
Title = {{Risk-based modelling of diffuse land use impacts from rural landscapes
   upon salmonid fry abundance}},
Journal = {{ECOLOGICAL MODELLING}},
Year = {{2011}},
Volume = {{222}},
Number = {{4}},
Pages = {{1016-1029}},
Month = {{FEB 24}},
Abstract = {{Research has demonstrated that landscape or watershed scale processes
   can influence instream aquatic ecosystems, in terms of the impacts of
   delivery of fine sediment, solutes and organic matter. Testing such
   impacts upon populations of organisms (i.e. at the catchment scale) has
   not proven straightforward and differences have emerged in the
   conclusions reached. This is: (1) partly because different studies have
   focused upon different scales of enquiry; but also (2) because the
   emphasis upon upstream land cover has rarely addressed the extent to
   which such land covers are hydrologically connected, and hence able to
   deliver diffuse pollution, to the drainage network However, there is a
   third issue. In order to develop suitable hydrological models, we need
   to conceptualise the process cascade. To do this, we need to know what
   matters to the organism being impacted by the hydrological system, such
   that we can identify which processes need to be modelled. Acquiring such
   knowledge is not easy, especially for organisms like fish that might
   occupy very different locations in the river over relatively short
   periods of time. However, and inevitably, hydrological modellers have
   started by building up piecemeal the aspects of the problem that we
   think matter to fish. Herein, we report two developments: (a) for the
   case of sediment associated diffuse pollution from agriculture, a
   risk-based modelling framework, SCIMAP, has been developed, which is
   distinct because it has an explicit focus upon hydrological
   connectivity; and (b) we use spatially distributed ecological data to
   infer the processes and the associated process parameters that matter to
   salmonid fry. We apply the model to spatially distributed salmon and fry
   data from the River Eden, Cumbria, England. The analysis shows, quite
   surprisingly, that arable land covers are relatively unimportant as
   drivers of fry abundance. What matters most is intensive pasture, a land
   cover that could be associated with a number of stressors on salmonid
   fry (e.g. pesticides, fine sediment) and which allows us to identify a
   series of risky field locations, where this land cover is readily
   connected to the river system by overland flow. (C) 2010 Elsevier B.V.
   All rights reserved.}},
DOI = {{10.1016/j.ecolmodel.2010.08.022}},
ISSN = {{0304-3800}},
ResearcherID-Numbers = {{Lane, Stuart/M-7934-2014
   Reaney, Sim M/H-2951-2013
   Heathwaite, Ann Louise/F-7002-2014}},
ORCID-Numbers = {{Lane, Stuart/0000-0002-6077-6076
   Reaney, Sim M/0000-0003-3063-2044
   Heathwaite, Ann Louise/0000-0001-8791-0039}},
Times-Cited = {{33}},
Unique-ID = {{ISI:000287291000011}},
}

@article{ ISI:000269037900002,
Author = {Lane, S. N. and Reaney, S. M. and Heathwaite, A. L.},
Title = {{Representation of landscape hydrological connectivity using a
   topographically driven surface flow index}},
Journal = {{WATER RESOURCES RESEARCH}},
Year = {{2009}},
Volume = {{45}},
Month = {{AUG 15}},
Abstract = {{This paper assesses the extent to which a topographically defined
   description of the spatial arrangement of catchment wetness can be used
   to represent landscape hydrological connectivity in temperate river
   catchments. A physically based distributed hydrological model is used to
   characterize the space-time patterns of surface overland flow connection
   to the drainage network. These characterizations are compared with a
   static descriptor of the spatial structure of topographically controlled
   local wetness, called here the Network Index. Theoretically, if
   topography is the primary control upon hydrological response, the level
   of catchment wetness required to maintain connectivity along a flow path
   should be greater for flow paths that have a lower value of the
   topographically controlled local wetness. We find that our static
   descriptor can be used to generalize a significant proportion of the
   time-averaged spatial variability in connectivity, in terms of both the
   propensity to and duration of connection. Although the extent to which
   this finding holds will vary with the extent of topographic control of
   hydrological response, in catchments with relatively shallow soils and
   impervious geology our index could improve significantly the estimation
   of the transfer of sediment and dissolved materials to the drainage
   network and so assist with both diffuse pollution and climate change
   impact studies. The work also provides a second reason for the concept
   that there are Critical Source Areas in river catchments: these arise
   from the extent to which that material can be delivered to the drainage
   network, as well as the generation of risky material itself.}},
DOI = {{10.1029/2008WR007336}},
Article-Number = {{W08423}},
ISSN = {{0043-1397}},
ResearcherID-Numbers = {{Lane, Stuart/M-7934-2014
   Reaney, Sim M/H-2951-2013
   Heathwaite, Ann Louise/F-7002-2014}},
ORCID-Numbers = {{Lane, Stuart/0000-0002-6077-6076
   Reaney, Sim M/0000-0003-3063-2044
   Heathwaite, Ann Louise/0000-0001-8791-0039}},
Times-Cited = {{82}},
Unique-ID = {{ISI:000269037900002}},
}

@article{ ISI:000253695100011,
Author = {Reaney, S. M.},
Title = {{The use of agent based modelling techniques in hydrology: determining
   the spatial and temporal origin of channel flow in semi-arid catchments}},
Journal = {{EARTH SURFACE PROCESSES AND LANDFORMS}},
Year = {{2008}},
Volume = {{33}},
Number = {{2}},
Pages = {{317-327}},
Month = {{FEB}},
Abstract = {{Information on the spatial and temporal origin of runoff entering the
   channel during a storm event would be valuable in understanding the
   physical dynamics of catchment hydrology; this knowledge could be used
   to help design flood defences and diffuse pollution mitigation
   strategies. The majority of distributed hydrological models give
   information on the amount of flow leaving a catchment and the pattern of
   fluxes within the catchment. However, these models do not give any
   precise information on the origin of runoff within the catchment. The
   spatial and temporal distribution of runoff sources is particularly
   intricate in semi-arid catchments, where there are complex interactions
   between runoff generation, transmission and re-infiltration over short
   temporal scales.
   Agents are software components that are capable of moving through and
   responding to their local environment. In this application, the agents
   trace the path taken by water through the catchment. They have
   information on their local environment and on the basis of this
   information make decisions on where to move. Within a given model
   iteration, the agents are able to stay in the current cell, infiltrate
   into the soil or flow into a neighbouring cell. The information on the
   current state of the hydrological environment is provided by the
   environment generator. In this application, the Connectivity of Runoff
   Model (CRUM) has been used to generate the environment. CRUM is a
   physically based, distributed, dynamic hydrology model, which considers
   the hydrological processes relevant for a semi-arid environment at the
   temporal scale of a single storm event. During the storm event, agents
   are introduced into the model across the catchment; they trace the flows
   of water and store information on the flow pathways. Therefore, this
   modelling approach is capable of giving a novel picture of the temporal
   and spatial dynamics of flow generation and transmission during a storm
   event. This is possible by extracting the pathways taken by the agents
   at different time slices during the storm.
   The agent based modelling approach has been applied to two small
   catchments in South East Spain. The modelling approach showed that the
   two catchments responded differently to the same rainfall event due to
   the differences in the runoff generation and overland flow connectivity
   between the two catchments. The model also showed that the time of
   travel to the nearest flow concentration is extremely important for
   determining the connectivity of a point in the landscape with the
   catchment outflow. Copyright (C) 2007 John Wiley \& Sons, Ltd.}},
DOI = {{10.1002/esp.1540}},
ISSN = {{0197-9337}},
ResearcherID-Numbers = {{Reaney, Sim M/H-2951-2013}},
ORCID-Numbers = {{Reaney, Sim M/0000-0003-3063-2044}},
Times-Cited = {{22}},
Unique-ID = {{ISI:000253695100011}},
}

@article{ ISI:000245595000005,
Author = {Reaney, S. M. and Bracken, L. J. and Kirkby, M. J.},
Title = {{Use of the Connectivity of Runoff Model (CRUM) to investigate the
   influence of storm characteristics on runoff generation and connectivity
   in semi-arid areas}},
Journal = {{HYDROLOGICAL PROCESSES}},
Year = {{2007}},
Volume = {{21}},
Number = {{7}},
Pages = {{894-906}},
Month = {{MAR 30}},
Abstract = {{Much attention has been given to the surface controls on the generation
   and transmission of runoff in semi-arid areas. However, the surface
   controls form only one part of the system; hence, it is important to
   consider the effect that the characteristics of the storm event have on
   the generation of runoff and the transmission of flow across the slope.
   The impact of storm characteristics has been investigated using the
   Connectivity of Runoff Model (CRUM). This is a distributed, dynamic
   hydrology model that considers the hydrological processes relevant to
   semi-arid environments at the temporal scale of a single storm event.
   The key storm characteristics that have been investigated are the storm
   duration, rainfall intensity, rainfall variability and temporal
   structure. This has been achieved through the use of a series of defined
   storm hydrographs and stochastic rainfall. Results show that the
   temporal fragmentation of high-intensity rainfall is important for
   determining the travel distances of overland flow and, hence, the amount
   of runoff that leaves the slope as discharge. If the high-intensity
   rainfall is fragmented, then the runoff infiltrates a short distance
   downslope. Longer periods of high-intensity rainfall allow the runoff to
   travel further and, hence, become discharge. Therefore, storms with
   similar amounts of high-intensity rainfall can produce very different
   amounts of discharge depending on the storm characteristics. The
   response of the hydrological system to changes in the rainfall
   characteristics can be explained using a four-stage model of the runoff
   generation process. These stages are: (1) all water infiltrating, (2)
   the surface depression store filling or emptying without runoff
   occurring, (3) the generation and transmission of runoff and (4) the
   transmission of runoff without new runoff being generated. The storm
   event will move the system between the four stages and the nature of the
   rainfall required to move between the stages is determined by the
   surface characteristics. This research shows the importance of the
   variable-intensity rainfall when modelling semi-arid runoff generation.
   The amount of discharge may be greater or less than the amount that
   would have been produced if constant rainfall intensity is used in the
   model. Copyright (c) 2006 John Wiley \& Sons, Ltd.}},
DOI = {{10.1002/hyp.6281}},
ISSN = {{0885-6087}},
ResearcherID-Numbers = {{Bracken, Louise/L-8198-2018
   Reaney, Sim M/H-2951-2013}},
ORCID-Numbers = {{Bracken, Louise/0000-0002-1268-5516
   Reaney, Sim M/0000-0003-3063-2044}},
Times-Cited = {{65}},
Unique-ID = {{ISI:000245595000005}},
}

@article{ ISI:000238396200007,
Author = {Lane, SN and Brookes, CJ and Heathwaite, AL and Reaney, S},
Title = {{Surveillant science: Challenges for the management of rural environments
   emerging from the new generation diffuse pollution models}},
Journal = {{JOURNAL OF AGRICULTURAL ECONOMICS}},
Year = {{2006}},
Volume = {{57}},
Number = {{2}},
Pages = {{239-257}},
Month = {{JUL}},
Abstract = {{Current models of diffuse pollution are characterised by a progressive
   engagement with remotely-sensed data coupled with more elegant modelling
   approaches. Central to these new models is the concept of connectivity,
   which leads to the identification and prioritisation of those landscape
   units (e.g., fields) where the consequences of land management
   activities are most readily transmitted to watercourses. The practice of
   diffuse pollution modelling using such models encounters certain
   problems. Following Brewer we argue that interdisciplinarity offers the
   opportunity to overcome these problems through: (1) its explicit
   recognition of the framing implicit in model development; (2) an
   emphasis on context in problem-solving; (3) methodological pluralism;
   and (4) following from these other factors, the possibility of a
   different sort of engagement between land managers and modellers. Hence,
   the case for developing interdisciplinary approaches goes beyond the
   conventional dictates of problem-led research and points to very
   different ways of conducting diffuse pollution research, taking on board
   the full dimensions of interdisciplinarity, with its emphasis on
   reflexivity, contextuality, substance and engagement.}},
DOI = {{10.1111/j.1477-9552.2006.00050.x}},
ISSN = {{0021-857X}},
ResearcherID-Numbers = {{Reaney, Sim M/H-2951-2013
   Lane, Stuart/M-7934-2014
   Heathwaite, Ann Louise/F-7002-2014}},
ORCID-Numbers = {{Reaney, Sim M/0000-0003-3063-2044
   Lane, Stuart/0000-0002-6077-6076
   Heathwaite, Ann Louise/0000-0001-8791-0039}},
Times-Cited = {{40}},
Unique-ID = {{ISI:000238396200007}},
}

@article{ ISI:000180181600009,
Author = {Kirkby, M and Bracken, L and Reaney, S},
Title = {{The influence of land use, soils and topography on the delivery of
   hillslope runoff to channels in SE Spain}},
Journal = {{EARTH SURFACE PROCESSES AND LANDFORMS}},
Year = {{2002}},
Volume = {{27}},
Number = {{13}},
Pages = {{1459-1473}},
Month = {{DEC}},
Note = {{Meeting on the Linkage of Hillslope Erosion to Sediment Transport and
   Storage in River and Floodplain Systems, ALMERIA, SPAIN, SEP 08-10, 2000}},
Abstract = {{It is generally accepted that within particular physiographic and
   climatic regions catchments exhibit differences in their hydrological
   response. These differences result from the interaction of spatial
   variability in catchment characteristics, variability of rainfall inputs
   and surface and subsurface hydrological processes. These interactions
   are complex and difficult to unravel. Hydrologically similar surfaces
   (HYSS) have been used to identify catchment areas that have a similar
   response to rainfall and have been identified at a number of scales.
   HYSS have been identified at the subcatchment scale for the Rambla de
   Nogalte in SE Spain. Areas with similar at-a-point hydrological storages
   were distinguished by using a combination of geology, land use and
   topography. This mapping was compared with discharge estimates made
   throughout the catchment following a seven-year return interval flood in
   September 1997. From this significant flood source areas were identified
   from reaches showing rapidly increasing channel discharge, and
   associated with HYSS that combined suitable internal characteristics
   with good connectivity to the main channel. This paper presents a
   simulation model that has been developed to investigate the way in which
   the hydrological response of areas within a HYSS respond to changes in
   source area, gradient, connectivity to the channel, storm size and
   intensity profile. This is one of the first studies using a hillslope
   model to investigate spatial patterns of runoff-response in semi-arid
   areas and results have implications for scaling up hydrological
   response, and on how the dynamics of runoff producing areas vary both
   underchanging storm conditions and over time. It is implicit in our
   results that the nature of stream-slope coupling differs substantively
   between semi-arid and humid areas. Copyright (C) 2002 John Wiley Sons,
   Ltd.}},
DOI = {{10.1002/esp.441}},
ISSN = {{0197-9337}},
ResearcherID-Numbers = {{Bracken, Louise/L-8198-2018
   Reaney, Sim M/H-2951-2013}},
ORCID-Numbers = {{Bracken, Louise/0000-0002-1268-5516
   Reaney, Sim M/0000-0003-3063-2044}},
Times-Cited = {{85}},
Unique-ID = {{ISI:000180181600009}},
}


text:
@article{2016Galax...4...46W,
 adsnote = {Provided by the SAO/NASA Astrophysics Data System},
 adsurl = {https://ui.adsabs.harvard.edu/abs/2016Galax...4...46W},
 archiveprefix = {arXiv},
 author = {Walker, R.~C. and Hardee, P.~E. and Davies, F. and Ly, C. and
Junor, W. and Mertens, F. and Lobanov, A.},
 doi = {10.3390/galaxies4040046},
 eprint = {1610.08600},
 journal = {Galaxies},
 month = {October},
 pages = {46},
 primaryclass = {astro-ph.HE},
 title = {Observations of the Structure and Dynamics of the Inner M87 Jet},
 volume = {4},
 year = {2016}
}

license: MIT

repository: astrochun/academic-kickstart

license_type: permissive

repo_name: astrochun/academic-kickstart

branch_name: refs/heads/master

gha_license_id: MIT

extension: bib


text:
package pkg

import (
	"fmt"
	"io/ioutil"
	"net/http"
	"os"
	"time"
)

// Notify returns socialblade search results for modesttim
func Notify(w http.ResponseWriter, r *http.Request) {
	url := "https://api.notify.me/secret/channel/username/tim"

	req, err := http.NewRequest("GET", url, nil)
	if err != nil {
		fmt.Println(err.Error())
	}

	req.Header.Set("Origin", "https://notify.me")
	req.Header.Set("Authorization", os.Getenv("NOTIFY_KEY"))
	req.Header.Set("User-Agent", "timcole.me homepage")

	res, err := (&http.Client{
		Timeout: 30 * time.Second,
	}).Do(req)
	if err != nil {
		fmt.Println(err.Error())
	}
	defer res.Body.Close()

	body, err := ioutil.ReadAll(res.Body)
	if err != nil {
		fmt.Println(err.Error())
	}

	w.Header().Set("Content-Type", "application/json")
	w.WriteHeader(200)
	w.Write(body)
}

extension: go


text:
package pool

import (
	"context"
	"errors"
	"time"
)

// ErrClosed 连接池已经关闭Error
var ErrClosed = errors.New("pool is closed")

// Pool 基本方法
type Pool interface {
	Get() (interface{}, error)

	GetContext(context.Context) (interface{}, error)

	RegisterChecker(interval time.Duration, check func(interface{}) bool)

	Put(interface{}) error

	Close(interface{}) error

	Connect() (interface{}, error)

	Release()

	Len() int
}

repository: DavidLiRemini/go-pool

repo_name: DavidLiRemini/go-pool

gha_language: Go


text:
package pacs

import (
	"encoding/xml"

	"github.com/thought-machine/finance-messaging/iso20022"
)

type Document00800105 struct {
	XMLName xml.Name                         `xml:"urn:iso:std:iso:20022:tech:xsd:pacs.008.001.05 Document"`
	Message *FIToFICustomerCreditTransferV05 `xml:"FIToFICstmrCdtTrf"`
}

func (d *Document00800105) AddMessage() *FIToFICustomerCreditTransferV05 {
	d.Message = new(FIToFICustomerCreditTransferV05)
	return d.Message
}

// Scope
// The FinancialInstitutionToFinancialInstitutionCustomerCreditTransfer message is sent by the debtor agent to the creditor agent, directly or through other agents and/or a payment clearing and settlement system. It is used to move funds from a debtor account to a creditor.
// Usage
// The FIToFICustomerCreditTransfer message is exchanged between agents and can contain one or more customer credit transfer instructions.
// The FIToFICustomerCreditTransfer message does not allow for grouping: a CreditTransferTransactionInformation block must be present for each credit transfer transaction.
// The FIToFICustomerCreditTransfer message can be used in different ways:
// - If the instructing agent and the instructed agent wish to use their direct account relationship in the currency of the transfer then the message contains both the funds for the customer transfer(s) as well as the payment details;
// - If the instructing agent and the instructed agent have no direct account relationship in the currency of the transfer, or do not wish to use their account relationship, then other (reimbursement) agents will be involved to cover for the customer transfer(s). The FIToFICustomerCreditTransfer contains only the payment details and the instructing agent must cover the customer transfer by sending a FinancialInstitutionCreditTransfer to a reimbursement agent. This payment method is called the Cover method;
// - If more than two financial institutions are involved in the payment chain and if the FIToFICustomerCreditTransfer is sent from one financial institution to the next financial institution in the payment chain, then the payment method is called the Serial method.
// The FIToFICustomerCreditTransfer message can be used in domestic and cross-border scenarios.
type FIToFICustomerCreditTransferV05 struct {

	// Set of characteristics shared by all individual transactions included in the message.
	GroupHeader *iso20022.GroupHeader49 `xml:"GrpHdr"`

	// Set of elements providing information specific to the individual credit transfer(s).
	CreditTransferTransactionInformation []*iso20022.CreditTransferTransaction19 `xml:"CdtTrfTxInf"`

	// Additional information that cannot be captured in the structured elements and/or any other specific block.
	SupplementaryData []*iso20022.SupplementaryData1 `xml:"SplmtryData,omitempty"`
}

func (f *FIToFICustomerCreditTransferV05) AddGroupHeader() *iso20022.GroupHeader49 {
	f.GroupHeader = new(iso20022.GroupHeader49)
	return f.GroupHeader
}

func (f *FIToFICustomerCreditTransferV05) AddCreditTransferTransactionInformation() *iso20022.CreditTransferTransaction19 {
	newValue := new(iso20022.CreditTransferTransaction19)
	f.CreditTransferTransactionInformation = append(f.CreditTransferTransactionInformation, newValue)
	return newValue
}

func (f *FIToFICustomerCreditTransferV05) AddSupplementaryData() *iso20022.SupplementaryData1 {
	newValue := new(iso20022.SupplementaryData1)
	f.SupplementaryData = append(f.SupplementaryData, newValue)
	return newValue
}

repository: thought-machine/finance-messaging

repo_name: thought-machine/finance-messaging


text:
% Encoding: ISO-8859-1

@Article{Archie1942,
  author  = {Archie, G.E.},
  title   = {{The Electrical Resistivity Log as an Aid in Determining Some Reservoir Characteristics}},
  journal = {Transactions of the AIME},
  year    = {1942},
  volume  = {146},
  pages   = {54--62},
  month   = dec,
  issn    = {0081-1696},
  doi     = {10.2118/942054-G},
}

@Article{Ruecker2017,
  author    = {Carsten R\"ucker and Thomas G\"unther and Florian M. Wagner},
  title     = {{pyGIMLi: A}n open-source library for modelling and inversion in geophysics},
  journal   = {Computers {\&} Geosciences},
  year      = {2017},
  volume    = {109},
  pages     = {106--123},
  doi       = {10.1016/j.cageo.2017.07.011},
  owner     = {fwagner},
  timestamp = {2018.09.22},
}

@Comment{jabref-meta: databaseType:bibtex;}

repository: tuhinmallick/thesis-tex-template

repo_name: tuhinmallick/thesis-tex-template


text:
# Copyright (C) 2020 Khem Raj <raj.khem@gmail.com>
# Released under the MIT license (see COPYING.MIT for the terms)

SUMMARY = "Kronosnet, often referred to as knet, is a network abstraction layer \
           designed for High Availability use cases, where redundancy, security, \
           fault tolerance and fast fail-over are the core requirements of your application."
HOMEPAGE = "https://kronosnet.org/"
LICENSE = "GPL-2.0-or-later & LGPL-2.1-only"
LIC_FILES_CHKSUM = "file://COPYING.applications;md5=751419260aa954499f7abaabaa882bbe \
                    file://COPYING.libraries;md5=2d5025d4aa3495befef8f17206a5b0a1"
SECTION = "libs"
DEPENDS = "doxygen-native libqb-native libxml2-native bzip2 libqb libxml2 libnl lksctp-tools lz4 lzo openssl nss xz zlib zstd"

SRCREV = "f8f80fd7f9b85f2626d2c6452612962ad8efca9e"
SRC_URI = "git://github.com/kronosnet/kronosnet;protocol=https;branch=stable1 \
           file://0001-links.c-Fix-build-with-gcc-12.patch \
           "

UPSTREAM_CHECK_URI = "https://github.com/kronosnet/kronosnet/releases"

inherit autotools pkgconfig

S = "${WORKDIR}/git"

# libknet/transport_udp.c:326:48: error: comparison of integers of different signs: 'unsigned long' and 'int' [-Werror,-Wsign-compare]
# for (cmsg = CMSG_FIRSTHDR(&msg);cmsg; cmsg = CMSG_NXTHDR(&msg, cmsg)) {
#                                                             ^~~~~~~~~~~~~~~~~~~~~~~
CFLAGS:append:toolchain-clang = " -Wno-sign-compare"

PACKAGECONFIG[man] = "enable_man="yes", --disable-man, "

PACKAGECONFIG:remove = "man"

repository: openembedded/meta-openembedded

repo_name: openembedded/meta-openembedded

gha_language: BitBake

extension: bb


text:
package discovery

import (
	"bytes"
	"context"
	"encoding/json"
	"github.com/flipkart-incubator/dkv/internal/hlc"
	"github.com/flipkart-incubator/dkv/internal/opts"
	"github.com/flipkart-incubator/dkv/pkg/ctl"
	"github.com/flipkart-incubator/dkv/pkg/serverpb"
	"go.uber.org/zap"
	"io"
)

type discoverService struct {
	dkvCli serverpb.DKVClient
	logger *zap.Logger
	config *opts.DiscoveryServerConfig
}

// Create the dkv lookup key from region info
// Since granularity of an update is at a region per node, the same is used for creating a key
// As lookups will be mostly on database and possibly on vBucket (within a database) the same order is used for key
// This enables faster scans for database/vBucket
func createKeyToInsert(info *serverpb.RegionInfo) []byte {
	return []byte(info.GetDatabase() + ":" + info.GetVBucket() + ":" + info.GetNodeAddress())
}

// Create lookup key based on input request
// Using the sorted nature of keys, lookup by either database or by database and vBucket or all keys
func createKeyToGet(request *serverpb.GetClusterInfoRequest) []byte {
	if request.GetDatabase() != "" {
		if request.GetVBucket() != "" {
			return []byte(request.GetDatabase() + ":" + request.GetVBucket() + ":")
		} else {
			return []byte(request.GetDatabase() + ":")
		}
	} else {
		return []byte{}
	}
}

func (d *discoverService) UpdateStatus(ctx context.Context, request *serverpb.UpdateStatusRequest) (*serverpb.Status, error) {
	// Store the serialised form of the request
	val, err := json.Marshal(request)

	if err != nil {
		d.logger.Error("Unable to marshal status request", zap.Error(err))
		return newErrorStatus(err), err
	}

	putRequest := serverpb.PutRequest{Key: createKeyToInsert(request.GetRegionInfo()), Value: val, ExpireTS: hlc.GetUnixTimeFromNow(uint64(d.config.StatusTTl))}
	if _, err = d.dkvCli.Put(ctx, &putRequest); err != nil {
		return newErrorStatus(err), err
	} else {
		return &serverpb.Status{Code: 0, Message: ""}, nil
	}
}

func (d *discoverService) GetClusterInfo(ctx context.Context, request *serverpb.GetClusterInfoRequest) (*serverpb.GetClusterInfoResponse, error) {
	iterReq := &serverpb.IterateRequest{KeyPrefix: createKeyToGet(request)}
	kvStrm, err := d.dkvCli.Iterate(ctx, iterReq)
	if err != nil {
		d.logger.Error("Unable to get cluster info", zap.Error(err))
		return nil, err
	}
	var clusterInfo []serverpb.KVPair
	for {
		itRes, err := kvStrm.Recv()
		if err == io.EOF {
			break
		} else if err != nil {
			// Better to return error rather than partial results as incomplete results could cause client misbehaviour
			d.logger.Error("Partial failure in getting cluster info", zap.Error(err))
			return nil, err
		} else if bytes.Contains(itRes.Key, []byte("dkv_meta")) {
			continue
		} else {
			clusterInfo = append(clusterInfo, serverpb.KVPair{
				Key:   itRes.Key,
				Value: itRes.Value,
			})
		}
	}

	var regionsInfo []*serverpb.RegionInfo
	for _, serializedStatusUpdate := range clusterInfo {
		statusUpdate := serverpb.UpdateStatusRequest{}
		if err = json.Unmarshal(serializedStatusUpdate.Value, &statusUpdate); err != nil {
			d.logger.Error("Unable to unmarshal status request", zap.Error(err), zap.String("json", string(serializedStatusUpdate.Value)))
			continue
		}
		// Filter regions outside the requested DC (if provided)
		if request.GetDcID() != "" && request.GetDcID() != statusUpdate.GetRegionInfo().GetDcID() {
			continue
		}
		// Filter inactive regions and regions whose status was updated long time back and hence considered inactive
		// This simplifies logic on consumers of this API (envoy, slaves) which don't need to filter by status
		if hlc.GetTimeAgo(statusUpdate.GetTimestamp()) < uint64(d.config.HeartbeatTimeout) && statusUpdate.GetRegionInfo().GetStatus() != serverpb.RegionStatus_INACTIVE {
			regionsInfo = append(regionsInfo, statusUpdate.GetRegionInfo())
		}
		// TODO : Filter such that only 1 master is returned per region
	}
	return &serverpb.GetClusterInfoResponse{RegionInfos: regionsInfo}, nil
}

func NewDiscoveryService(dkvService serverpb.DKVServer, logger *zap.Logger, config *opts.DiscoveryServerConfig) (serverpb.DKVDiscoveryServer, error) {
	dkvClient, err := ctl.CreateInProcessDKVClient(dkvService).GRPCClient()
	if err != nil {
		return nil, err
	}
	return &discoverService{dkvCli: dkvClient, logger: logger, config: config}, nil
}

func newErrorStatus(err error) *serverpb.Status {
	return &serverpb.Status{Code: -1, Message: err.Error()}
}

repository: flipkart-incubator/dkv

repo_name: flipkart-incubator/dkv


text:
package main

import (
	"fmt"
	"github.com/gocraft/web"
	"net/http"
	"strings"
)

type User struct {
	nickname string
	login    int
}

type Context struct {
	HelloCount int
	User       *User
}

// Pretend like this is defined. It reads a session cookie and returns a *User or nil.
func userFromSession(r *web.Request) *User {
	return &User{"kk", 20}
}

func (c *Context) UserRequired(rw web.ResponseWriter, r *web.Request, next web.NextMiddlewareFunc) {
	user := userFromSession(r)
	if user != nil {
		c.User = user
		next(rw, r)
	} else {
		rw.Header().Set("Location", "/")
		rw.WriteHeader(http.StatusMovedPermanently)
		// do NOT call next()
	}
}

func (c *Context) SetHelloCount(rw web.ResponseWriter, req *web.Request, next web.NextMiddlewareFunc) {
	c.HelloCount = 3
	fmt.Println(c.HelloCount)
	next(rw, req)
}

func (c *Context) SayHello(rw web.ResponseWriter, req *web.Request) {
	fmt.Fprint(rw, strings.Repeat("Hello ", c.HelloCount), "World!")
}

func main() {
	router := web.New(Context{}). // Create your router
					Middleware(web.LoggerMiddleware).     // Use some included middleware
					Middleware(web.ShowErrorsMiddleware). // ...
					Middleware((*Context).SetHelloCount). // Your own middleware!
					Get("/", (*Context).SayHello)         // Add a route
	http.ListenAndServe("127.0.0.1:3000", router) // Start the server!
}

repository: quchunguang/trygo

repo_name: quchunguang/trygo


text:
# SPDX-License-Identifier: MIT
require mion-onie-image.inc
require recipes-core/images/mion-image-core.inc
ONLPV="onlpv2"
IMAGE_INSTALL_append = " \
    ${ONLPV} \
    packagegroup-onl-python2 \
"

repository: NetworkGradeLinux/meta-mion

repo_name: NetworkGradeLinux/meta-mion

branch_name: refs/heads/dunfell

gha_language: C


text:
package mina

import "testing"

func TestCheckSignature(t *testing.T) {
	signature := "9723a3c9be77cf53abab266547322daa2547e509"
	sessionKey := "Hj84aljX3iEU6+DAChvPjg=="
	rawData := `{"nickName":"solarhell","gender":1,"language":"zh_CN","city":"Nanjing","province":"Jiangsu","country":"China","avatarUrl":"https://wx.qlogo.cn/mmopen/vi_32/Q0j4TwGTfTI5J2lPp4NaUXibU2U6icHZ0lZf2j1QJhHIh89tPP2j1pKMB5Ax91RslrevFm1jMS5v1lDS4zmCSE3A/132"}`
	ok := CheckSignature(signature, sessionKey, rawData)
	if !ok {
		t.Error("error CheckSignature")
	}
}

func TestDecryptUserInfo(t *testing.T) {
	sessionKey := "tiihtNczf5v6AKRyjwEUhQ=="
	encryptedData := "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"
	iv := "r7BXXKkLb8qrSNn05n0qiA=="

	_, err := DecryptUserInfo(sessionKey, encryptedData, iv)
	if err != nil {
		t.Error("error DecryptUserInfo", err)
	}
}

repository: ToPeas/mina

repo_name: ToPeas/mina


text:
package protocol

import (
	"testing"
)

//TODO! Add a log file with Record batch data to recover this tests.
func TestRecordBatchDecodeKafka011(t *testing.T) {
	/* 	b, err := ioutil.ReadFile("kafka_011.log")
	   	if err != nil {
	   		t.Errorf(err.Error())
	   	}
	   	var rb RecordBatch
	   	if err = Decode0(b, &rb); err != nil {
	   		t.Errorf(err.Error())
	   		return
	   	}
	   	fmt.Println(rb.Records[0])
	   	firstRecordValue := rb.Records[0].Value
	   	require.Equal(t, string(firstRecordValue), "magnus", "The two words should be the same.") */

}

repository: navono/jocko

repo_name: navono/jocko


text:
@Article{tabima2018populations,
  title = {Populations of Phytophthora rubi show little differentiation and high rates of migration among states in the Western United States},
  author = {Javier F Tabima and Michael D Coffey and Inga A Zazada and Niklaus J Gr{\"u}nwald},
  journal = {Molecular Plant-Microbe Interactions},
  volume = {31},
  number = {6},
  pages = {614--622},
  year = {2018},
  date = {2018-01-01},
}


text:
SECTION = "devel/chicken"
DESCRIPTION = "neo4j REST client"
LICENSE = "BSD"
LIC_FILES_CHKSUM = "file://neo4j.meta;md5=b48e458c4402c8845adf50383dd0be13"
DEPENDS_append_class-cross = " chicken-egg-alist-lib-cross chicken-egg-http-client-cross chicken-egg-intarweb-cross chicken-egg-json-cross chicken-egg-matchable-cross chicken-egg-medea-cross chicken-egg-setup-helper-cross chicken-egg-uri-common-cross"
DEPENDS_append_class-crosssdk = " chicken-egg-alist-lib-crosssdk chicken-egg-http-client-crosssdk chicken-egg-intarweb-crosssdk chicken-egg-json-crosssdk chicken-egg-matchable-crosssdk chicken-egg-medea-crosssdk chicken-egg-setup-helper-crosssdk chicken-egg-uri-common-crosssdk"
DEPENDS_append_class-nativesdk = " nativesdk-chicken-egg-alist-lib nativesdk-chicken-egg-http-client nativesdk-chicken-egg-intarweb nativesdk-chicken-egg-json nativesdk-chicken-egg-matchable nativesdk-chicken-egg-medea nativesdk-chicken-egg-setup-helper nativesdk-chicken-egg-uri-common chicken-egg-alist-lib-crosssdk chicken-egg-http-client-crosssdk chicken-egg-intarweb-crosssdk chicken-egg-json-crosssdk chicken-egg-matchable-crosssdk chicken-egg-medea-crosssdk chicken-egg-setup-helper-crosssdk chicken-egg-uri-common-crosssdk"
DEPENDS = " chicken-egg-alist-lib chicken-egg-http-client chicken-egg-intarweb chicken-egg-json chicken-egg-matchable chicken-egg-medea chicken-egg-setup-helper chicken-egg-uri-common chicken-egg-alist-lib-cross chicken-egg-http-client-cross chicken-egg-intarweb-cross chicken-egg-json-cross chicken-egg-matchable-cross chicken-egg-medea-cross chicken-egg-setup-helper-cross chicken-egg-uri-common-cross"
RDEPENDS_${PN} = " chicken-egg-alist-lib chicken-egg-http-client chicken-egg-intarweb chicken-egg-json chicken-egg-matchable chicken-egg-medea chicken-egg-setup-helper chicken-egg-uri-common"

SRC_URI = "http://code.call-cc.org/egg-tarballs/4/neo4j/neo4j-${PV}.tar.gz"

SRC_URI[md5sum] = "60f91019ce4df5e30d23c557aee4e0dc"
SRC_URI[sha256sum] = "df825c67c59309f1cf6c819a7ed0bac977bbe5ea96f42d6074cf12ea783c1eb3"

S = "${WORKDIR}/neo4j-${PV}"

inherit chicken_install

BBCLASSEXTEND = "cross crosssdk nativesdk"

repository: OSSystems/meta-chicken

repo_name: OSSystems/meta-chicken


text:
package main

import (
	"log"

	"github.com/lc/subjs/runner/subjs"
)

func main() {
	opts := subjs.ParseOptions()
	runner := subjs.New(opts)
	err := runner.Run()
	if err != nil {
		log.Fatalf("Error running subjs: %s", err)
	}
}

repository: bbhunter/subjs

repo_name: bbhunter/subjs


text:
@proceedings{ws-2019-narrative,
    title = "Proceedings of the First Workshop on Narrative Understanding",
    editor = "Bamman, David  and
      Chaturvedi, Snigdha  and
      Clark, Elizabeth  and
      Fiterau, Madalina  and
      Iyyer, Mohit",
    month = jun,
    year = "2019",
    address = "Minneapolis, Minnesota",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W19-2400",
}
@inproceedings{cho-etal-2019-towards,
    title = "Towards Coherent and Cohesive Long-form Text Generation",
    author = "Cho, Woon Sang  and
      Zhang, Pengchuan  and
      Zhang, Yizhe  and
      Li, Xiujun  and
      Galley, Michel  and
      Brockett, Chris  and
      Wang, Mengdi  and
      Gao, Jianfeng",
    booktitle = "Proceedings of the First Workshop on Narrative Understanding",
    month = jun,
    year = "2019",
    address = "Minneapolis, Minnesota",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W19-2401",
    doi = "10.18653/v1/W19-2401",
    pages = "1--11",
}
@inproceedings{jahan-finlayson-2019-character,
    title = "Character Identification Refined: A Proposal",
    author = "Jahan, Labiba  and
      Finlayson, Mark",
    booktitle = "Proceedings of the First Workshop on Narrative Understanding",
    month = jun,
    year = "2019",
    address = "Minneapolis, Minnesota",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W19-2402",
    doi = "10.18653/v1/W19-2402",
    pages = "12--18",
}
@inproceedings{shree-etal-2019-deep,
    title = "Deep Natural Language Understanding of News Text",
    author = "Shree, Jaya  and
      Liu, Emily  and
      Gordon, Andrew  and
      Hobbs, Jerry",
    booktitle = "Proceedings of the First Workshop on Narrative Understanding",
    month = jun,
    year = "2019",
    address = "Minneapolis, Minnesota",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W19-2403",
    doi = "10.18653/v1/W19-2403",
    pages = "19--27",
}
@inproceedings{palshikar-etal-2019-extraction,
    title = "Extraction of Message Sequence Charts from Narrative History Text",
    author = "Palshikar, Girish  and
      Pawar, Sachin  and
      Patil, Sangameshwar  and
      Hingmire, Swapnil  and
      Ramrakhiyani, Nitin  and
      Bedi, Harsimran  and
      Bhattacharyya, Pushpak  and
      Varma, Vasudeva",
    booktitle = "Proceedings of the First Workshop on Narrative Understanding",
    month = jun,
    year = "2019",
    address = "Minneapolis, Minnesota",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W19-2404",
    doi = "10.18653/v1/W19-2404",
    pages = "28--36",
}
@inproceedings{ippolito-etal-2019-unsupervised,
    title = "Unsupervised Hierarchical Story Infilling",
    author = "Ippolito, Daphne  and
      Grangier, David  and
      Callison-Burch, Chris  and
      Eck, Douglas",
    booktitle = "Proceedings of the First Workshop on Narrative Understanding",
    month = jun,
    year = "2019",
    address = "Minneapolis, Minnesota",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W19-2405",
    doi = "10.18653/v1/W19-2405",
    pages = "37--43",
}
@inproceedings{roemmele-2019-identifying,
    title = "Identifying Sensible Lexical Relations in Generated Stories",
    author = "Roemmele, Melissa",
    booktitle = "Proceedings of the First Workshop on Narrative Understanding",
    month = jun,
    year = "2019",
    address = "Minneapolis, Minnesota",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W19-2406",
    doi = "10.18653/v1/W19-2406",
    pages = "44--52",
}

repository: emorynlp/nlprankings

repo_name: emorynlp/nlprankings

gha_license_id: NOASSERTION

gha_language: TeX


text:
@InProceedings{wua15,
  supplementary = {Supplementary:wua15-supp.pdf},
  title = {An Online Learning Algorithm for Bilinear Models},
  author = {Yuanbin Wu and Shiliang Sun},
  pages = {890-898},
  abstract = {We investigate the bilinear model, which is a matrix form linear model with the rank 1 constraint. A new online learning algorithm is proposed to train the model parameters. Our algorithm runs in the manner of online mirror descent, and gradients are computed by the power iteration. To analyze it, we give a new second order approximation of the squared spectral norm, which helps us to get a regret bound. Experiments on two sequential labelling tasks give positive results.},
}

repository: mreid/papersite

repo_name: mreid/papersite


text:
DESCRIPTION = "Python Qt4 Bindings"
HOMEPAGE = "http://riverbankcomputing.co.uk"
AUTHOR = "Phil Thomson @ riverbank.co.uk"
SECTION = "devel/python"
LICENSE = "GPLv2 & GPLv3 & GPL_EXCEPTION"
LIC_FILES_CHKSUM = "\
    file://GPL_EXCEPTION.TXT;md5=b73b0be471db679533dc94781c14af58 \
    file://GPL_EXCEPTION_ADDENDUM.TXT;md5=c1e04ec2aa0911061005a801abf81e40 \
    file://OPENSOURCE-NOTICE.TXT;md5=6ad9123620cc04a22c394753ad4767d7 \
    file://LICENSE.GPL2;md5=276c6b9cad5f85a3af3534299825feff \
    file://LICENSE.GPL3;md5=eda942b9c6ba7eb0f40fee79e94950d5 \
"

DEPENDS = "sip-native python-sip"
RDEPENDS_${PN} = "python-core"

PYQT_OE_VERSION = "Qt_4_8_3"
PR = "r1"

SRC_URI = "\
    ${SOURCEFORGE_MIRROR}/pyqt/PyQt-x11-gpl-${PV}.tar.gz \
    file://pyqt-generated.patch;apply=no \
"
SRC_URI[md5sum] = "514e1f9597771dc732ba75ba9fa5c6b6"
SRC_URI[sha256sum] = "a350f9e5c6d8062671c0f29bf1a70824719b18175ce8372c29bf7c1eda44b18d"
S = "${WORKDIR}/PyQt-x11-gpl-${PV}"

# arm and mips machines need some extra patches
SRC_URI_append_arm = "\
    file://qreal_float_support.diff \
"

SRC_URI_append_mipsel = "\
    file://qreal_float_support.diff \
"

inherit qt4x11 sip distutils-base

PARALLEL_MAKE = ""

QMAKE_PROFILES = "pyqt.pro"
# NOTE: has to match with MIN(qt version we have in OE, last known Qt version by SIP/PyQt)
EXTRA_SIPTAGS = "-tWS_X11 -t${PYQT_OE_VERSION} -xVendorID -xPyQt_SessionManager -xPyQt_Accessibility"
EXTRA_OEMAKE = " MAKEFLAGS= "

# arm and mips need extra params for the qreal issue
EXTRA_SIPTAGS_append_arm = " -x PyQt_qreal_double"
EXTRA_SIPTAGS_append_mipsel = " -x PyQt_qreal_double"

SIP_MODULES = "QtCore QtDeclarative QtGui QtNetwork QtSql QtSvg QtXml QtWebKit"
MAKE_MODULES = "qpy ${SIP_MODULES}"

EXTRA_QMAKEVARS_POST += "\
    INCLUDEPATH+=${OE_QMAKE_INCDIR_QT}/Qt \
    INCLUDEPATH+=${STAGING_INCDIR}/${PYTHON_DIR} \
    INCLUDEPATH+=../qpy/QtCore \
    INCLUDEPATH+=../qpy/QtGui \
    INCLUDEPATH+=../qpy/QtDeclarative \
    INCLUDEPATH+=${OE_QMAKE_INCDIR_QT}/QtCore \
    INCLUDEPATH+=${OE_QMAKE_INCDIR_QT}/QtGui \
    INCLUDEPATH+=${OE_QMAKE_INCDIR_QT}/QtDeclarative \
    INCLUDEPATH+=${OE_QMAKE_INCDIR_QT}/QtWebKit \
    INCLUDEPATH+=${OE_QMAKE_INCDIR_QT}/QtNetwork \
"
FIX_QREAL = "\
"

do_generate_prepend() {
    for i in ${FIX_QREAL}; do
        sed -i -e s,qreal,float,g sip/$i
    done
}

do_configure_prepend() {
    printf "TEMPLATE=subdirs\nSUBDIRS=${MAKE_MODULES}\n" >pyqt.pro
    printf "TEMPLATE=subdirs\nSUBDIRS=QtCore QtDeclarative QtGui\n" >qpy/qpy.pro
    ln -sf ./qpycore.pro qpy/QtCore/QtCore.pro
    ln -sf ./qpydeclarative.pro qpy/QtDeclarative/QtDeclarative.pro
    ln -sf ./qpygui.pro qpy/QtGui/QtGui.pro
    echo "INCLUDEPATH+=${S}/QtCore" >>qpy/QtCore/QtCore.pro
    echo "INCLUDEPATH+=${S}/QtGui" >>qpy/QtGui/QtGui.pro
    echo "INCLUDEPATH+=${S}/QtDeclarative" >>qpy/QtDeclarative/QtDeclarative.pro
    echo "LIBS+=-L../qpy/QtGui/ -lqpygui" >>QtGui/QtGui.pro
    echo "LIBS+=-L../qpy/QtCore/ -lqpycore" >>QtCore/QtCore.pro
    echo "LIBS+=-L../qpy/QtDeclarative/ -lqpydeclarative" >>QtDeclarative/QtDeclarative.pro
    # hack for broken generated code (duplicated sipCpp declaration).
    patch -p1 < ${WORKDIR}/pyqt-generated.patch || echo "pyqt-generated.patch failed to apply, probably reexecuting do_configure, ignoring that"
}

do_install() {
    install -d ${D}${libdir}/${PYTHON_DIR}/site-packages/PyQt4
    install -d ${D}${datadir}/sip/qt/
    for module in ${SIP_MODULES}
    do
        install -m 0644 ${S}/sip/${module}/*.sip ${D}${datadir}/sip/qt/
        echo "from PyQt4.${module} import *\n" >> ${D}${libdir}/${PYTHON_DIR}/site-packages/PyQt4/Qt.py
        install -m 0755 ${module}/lib${module}.so ${D}${libdir}/${PYTHON_DIR}/site-packages/PyQt4/${module}.so
    done
    cp -pPR elementtree ${D}${libdir}/${PYTHON_DIR}/site-packages/PyQt4/
    cp __init__.py ${D}${libdir}/${PYTHON_DIR}/site-packages/PyQt4/
}

FILES_${PN} = "${libdir}/${PYTHON_DIR}/site-packages ${datadir}/sip/qt/"

repository: ExorEmbedded/exor-workspace

repo_name: ExorEmbedded/exor-workspace

gha_language: Python


text:
package api

import (
	"net/http"

	"github.com/stefanprodan/podinfo/pkg/version"
)

// Version godoc
// @Summary Version
// @Description returns podinfo version and git commit hash
// @Tags HTTP API
// @Produce json
// @Router /version [get]
// @Success 200 {object} api.MapResponse
func (s *Server) versionHandler(w http.ResponseWriter, r *http.Request) {
	result := map[string]string{
		"version": version.VERSION,
		"commit":  version.REVISION,
	}
	s.JSONResponse(w, r, result)
}

repository: kingdonb/podinfo

repo_name: kingdonb/podinfo


text:
package main

import (
	"flag"
	"fmt"
	"fresh/runner"
	"os"
	"path/filepath"
)

func main() {
	//configPath := flag.String("c", "", "config file path")
	//configFile := os.Getenv("GOPATH") + "\\fresh.conf"
	configFile := filepath.Join(os.Getenv("GOPATH"), "fresh.conf")
	configPath := flag.String("c", configFile, "config file path")
	flag.Parse()
	//fmt.Println(configFile)

	if *configPath != "" {
		if _, err := os.Stat(*configPath); err != nil {
			fmt.Printf("Can't find config file `%s`\n", *configPath)
			os.Exit(1)
		} else {
			os.Setenv("RUNNER_CONFIG_PATH", *configPath)
		}
	}
	runner.Start()
}

repository: ilaorou/fresh

repo_name: ilaorou/fresh


text:
package endpoint

import (
	"github.com/DaoYoung/ginrester"
	"ginrester-example/model"
)

type TeacherController struct {
	ginrester.Controller
}
func (action *TeacherController) IsRestRoutePk() bool {
	return true
}
func (action *TeacherController) model() ginrester.ResourceInterface {
	return &(model.Teacher{})
}
func (action *TeacherController) modelSlice() interface{} {
	return &[]model.Teacher{}
}
func (action TeacherController) Rester() (actionPtr *TeacherController) {
	action.Init(&action)
	return  &action
}

repository: DaoYoung/ginrester-example

repo_name: DaoYoung/ginrester-example