bluuebunny/crossref_metadata_2025 huggingface dataset:
Plant Epidemics, Models and Analysis
Authors: Madden Laurence V. , Hughes G.
Published: September 2014

Plants are susceptible to many diseases; fungal, bacterial, viral, and other forms of epidemics occur commonly in agricultural systems, resulting in substantial crop yield reductions. There are two primary ways of measuring plant disease, incidence and severity. Plant disease incidence can be defined as the number of diseased plants, or plant parts expressed as a proportion of the total number of plants, or plant parts, assessed. Plant disease incidence is a binary variable, because individuals are either diseased or not. Plant disease severity, on the other hand, can be defined as the area or volume of plant tissue that is diseased, usually relative to the total plant tissue. It is a continuous variable, typically bounded by 0 and 1. In this article, emphasis is placed on incidence. Statistical issues regarding plant diseases in crops or natural systems concern the characterization of spatial patterns of disease, estimation of rates of disease increase over time, and rates of spatial spread. There is a variety of statistical tools available to quantify spatial pattern of disease incidence, which can be categorized based on the general type of analysis – point pattern or geostatistical analysis – or on whether the data consist of mapped or unmapped observations.
Point Processes, Spatial
Authors: Guttorp Peter M. , Brillinger David R. , Schoenberg Frederic Paik
Published: September 2014

The general theory of point processes has usually been focused on temporal developments. The special case of events that occur in space (or, more precisely, on a plane) has developed some particular approaches, usually assuming spatial stationarity and isotropy (i.e. the distribution of the process is invariant under translations and rotations, respectively). This article focuses on this type of process. Points, or events, take place at spatial locations, and each event is identified with its location.
Population Ecology
Authors: Dixon Philip M.
Published: September 2014

An ecological population is the collection of individuals of a particular species in a specific geographic area. Population ecology is the study of the numbers of individuals in a population and how and why that number changes. This article describes commonly used quantitative models for change in population size.
Remote Sensing
Authors: Shao Guofan
Published: September 2014

Remote sensing is both a science and an art. Remote sensing has been involved from airborne to spaceborne applications since the 1960s. A variety of sensors are used to record both the visible and the invisible, such as infrared (IR), parts of the spectrum in the field of remote sensing. Depending on the number of spectral bands used, remote sensing includes panchromatic (one band), multispectral (several bands), and hyperspectral (dozens to hundreds of bands) remote sensing; depending on the source of energy/radiation, remote sensing can be passive or active. The ultimate goal of remote sensing is to extract information from remotely sensed data about the material properties of the earth's surface and of the atmosphere, together with their geographical relationships. Numerous approaches are available to extract information from remotely sensed data/imagery. Thematic maps derived with remote sensing methods contain errors, which can be assessed with reference data. It is important to use thematic maps with relatively high classification accuracy to avoid wrong conclusions or decision making based on the maps.
Resource Selection
Authors: Nielson Ryan M. , Thomas Dana L. , Mcdonald Lyman L.
Published: September 2014

Field studies designed to compare resource (e.g., food or habitat) use and availability are commonly called resource selection studies. The motivation for conducting selection studies and the factors influencing resource selection are briefly described. Common study designs and statistical methods for assessing resource selection are presented.
R
ipley's
K
Function
Authors: Dixon Philip M.
Published: September 2014

Ripley's K function summarizes spatial point process data. It can be used to describe a set of locations, test hypotheses about patterns, and estimate parameters in a spatial point process model. For a stationary point process,
K
(
t
) is the expected number of additional points within distance
t
of a focal point divided by the intensity of the process. A univariate version is used for one set of locations and a multivariate version is used when points can be labeled by a small number of groups. This article reviews the properties of Ripley's K function and two related functions, then illustrates the computation and interpretation using data on the locations of trees in a swamp hardwood forest.
Risk Assessment, Seismological
Authors: Özel Gamze
Published: September 2014

Seismic risk is usually defined as the probability of exceeding a specified level of loss due to earthquakes for a set of goods within a reference period of time. Usually it is measured by considering the convolution of three main factors: hazard (probability of earthquakes), vulnerability (probability of damage, given the earthquake), and exposure (probability of loss given the damage). Thus, the seismic risk in a geographical region depends on many uncertain variables pertaining to the three main factors listed above. Some of the uncertainties are reducible through deeper investigation, while others reflect intrinsic randomness and are therefore unavoidable. Seismic risk assessment (SRA) is very important for public safety and hazards mitigation. It is also important for the correct determination of earthquake insurance premiums, and for understanding the social and psychological effects of earthquakes. This study represents an extensive review and evaluation of SRA methodology. SRA strategy, source parameters, attenuation, and local site effects are explained in detail. Global and national seismic hazard maps relating to seismic risk are presented. A variety of references concerned with the problem SRA are given.
Space‐Time Covariance Models
Authors: Gneiting Tilmann , Schlather Martin
Published: September 2014

Geostatistical approaches to modeling spatiotemporal data rely on flexible space–time covariance models. The area has been in vigorous development recently, and we review constructions of nonseparable spatiotemporal covariance functions that are based on geometric anisotropy, Fourier inversion, completely monotone functions, and dynamic physical models.
Spatial Optimization
Authors: Hof John
Published: September 2014

This article describes an emerging methodology that captures spatial relationships between different land areas in the process of maximizing an objective function subject to resource constraints. It discusses adjacency constraints and direct approaches. Adjacency constraints are utilized when scheduling timber harvests with legal or regulatory restrictions on the effective size of harvest area. Adjacency relationships are important because, for example, if two seemingly legal‐size clearcuts occur within a short time of each other in adjacent areas, then the effective size of the clearcut may not be legal. Direct approaches include the actual ecological spatial relationships of concern. An example is provided that accounts for wildlife habitat fragmentation in optimally placing timber harvests. The land area is divided into cells and choice variables are defined to represent complete scheduled management prescriptions for each cell. Wildlife population levels are then determined by a combination of potential growth, dispersal, and spatially located carrying capacities determined by the management prescription allocations. Other examples of this type of direct spatial optimization are also cited.
Spatially Constrained Sampling
Authors: Stein Alfred
Published: September 2014

This article describes sampling in the presence of spatial constraints. The technique has been developed on the basis of simulated annealing. It is applicable for a range of environmental sampling and monitoring techniques. After introducing the technique, two specific examples are given. An outlook toward further developments is given.
Species Distribution, Monitoring Changes in
Authors: Yoccoz Nigel G.
Published: September 2014

Changes in species distributions constitute strong evidence that global change is affecting ecosystems and biodiversity. Expansion of invasive species and retraction of endangered species are examples of environmental issues that need to be understood and addressed. Monitoring range shifts require that we can accurately estimate the state(s) of the system – that is, the present and past distributions – its rate of change, and assess the underlying causes. Existing monitoring programs differ in terms of data quality and coverage of the environmental space, and very few have considered different sources of errors as well as alternative explanations of observed changes. Modeling species distributions is needed to derive alternative predictions of future changes. The design of monitoring programs should assess the assumptions
and
the predictions of these models.
Species Overlap
Authors: Gerow Kenneth
Published: September 2014

Species overlap measures the degree to which two species assemblages share common species. There is an abundance of well‐studied indices of species overlap. Some are based on presence/absence of data; more popular ones take relative abundance of species into account. Several important indices are described in this article, as well as an entrée to relevant literature.
Temporal Change
Authors: Esterby Sylvia
Published: September 2014

The study of temporal change in environmental quality indicators is motivated by the need to know if the state of the environment has deteriorated or, in some cases, if it has improved as a result of the removal or lessening of stress on the system. The data available for study of temporal change are observational, and usually it is not even possible to relate there to observational data on the level of the stressor. Thus, statements about the change in the quality indicator are made on the basis of measurements and analysis, where other effects have been removed as much as possible from the term corresponding to change over time.
Tessellations
Authors: Schoenberg Frederic Paik
Published: September 2014

A
tessellation
may be defined as a division of a space into convex polygonal regions; divisions of the
plane
(

R
2

) are most often discussed. While geometrists centuries ago reserved the term tessellation merely for divisions of the plane into
regular
polygons of equal size, most authors now define tessellations very broadly so as to include any arrangements of nonoverlapping shapes covering

R
d

, as well as partitions of other metric spaces.
Thresholds, Ecological
Authors: Toms Judith D.
Published: September 2014

Ecological thresholds occur when the relationship between the response and explanatory variables is nonlinear, changing abruptly at one or more values. Such thresholds may be continuous or discontinuous, and different methods for estimating the location and number of thresholds have been developed for each type. For continuous thresholds, methods based on piecewise regression are preferred. Discontinuous thresholds can be transformed using the cumulative sum, resulting in transformed data with continuous thresholds, and piecewise regression techniques are then used for inference. Alternatively, Bayesian change‐point analysis can be used for inference. Special methods have been developed for detecting thresholds in spatial data.
Time Series, Ecological
Authors: Solow Andrew R.
Published: September 2014

The most common situation in which time series data are the central object of ecological analysis is in population dynamics/population modeling. Let
X

t

be the size or density of a population in period
t
. A general deterministic model of the dynamics of this population is the first‐order nonlinear difference equation:
X

t

 = 
X

t
−1

F
(
X

t
−1

) where
F
is a nonnegative function.
Time Series, Periodic
Authors: Lund Robert B.
Published: September 2014

This entry overviews time series with periodic autocovariance structures. Such series often arise in the environmental sciences. Here, extensions to the class of covariance stationary time series are introduced and used to model and describe the autocovariance periodicities. Detection of autocovariance periodicities is considered. A series of monthly averaged temperatures from Griffin, Georgia (United States) is used to illustrate aspects of the discourse.
Trace Level Detection
Authors: Little Tom Tadfor , Miller Guthrie , Martz Harry F. , Inkret William C.T. , Schillaci Mario E.
Published: September 2014

An important component of protecting individuals from the hazards of radiation exposure is to be able to determine whether radionuclides have been taken into the body, and in what quantities. For example, a urine sample from an individual who works with plutonium can be analyzed by α spectroscopy or mass spectroscopy to determine if plutonium is present in the sample, and hence to make an inference about possible plutonium intakes in the individual's history. Often, the quantities of plutonium that one seeks to detect are comparable to the measurement uncertainties. Hence, statistical considerations are a very important aspect of the detection methodology.
Trawl Surveys
Authors: Nordahl Victor , Clark Steve
Published: September 2014

Trawl surveys for fishery resources are conducted throughout the world by government and non‐government agencies. Modern fishery management requires standard time series of data on management units or ‘stocks’ and their response to exploitation: trends in abundance and biomass; spawning success; biological parameters; distribution; and environmental factors that can be provided only through standardized sampling programs. Trawl surveys provide the opportunity for controlled sampling in space and time.
Validation Study: Introduction
Authors: Spiegelman Donna
Published: September 2014

Validation studies obtain information on measurement errors in exposures and other covariates used in epidemiological studies by comparing the conventional exposure measurements with ‘gold standard’ measurements.
Water Quality Modeling
Authors: Whitehead Paul G.
Published: September 2014

In addition to being major sources of water, river systems are used as the principal disposal pathways for industrial, agricultural, and domestic effluent. As demand for water increases and water quality deteriorates, there is a requirement for effective decision making techniques which can be applied to solve water quality management problems. Over the past century, increasing effort has been devoted to the development of suitable techniques, largely by engineers, system analysts, and scientists. As long ago as 1912 the Royal Commission on Environmental Pollution in the UK proposed a simple 1 to 8 ratio for effluent discharge to river flow in an attempt to clean up UK rivers. In the USA major developments by Streeter and Phelps led to the dissolved oxygen (DO) and biochemical oxygen demand (BOD) equations that enable steady‐state and dynamic modeling of oxygen balances in rivers. Major studies in the area of water quality modeling were undertaken in the US (e.g. Great Lakes, Delaware Study), the UK (e.g. Trent Study and Bedford Case Study), and in Australia (Peel–Harvey Inlet), and these all evolved new techniques to address major water quality problems.
Wildlife Ecology
Authors: Bowyer R. Terry , Stewart Kelley M. , Monteith Kevin L. , Long Ryan A.
Published: September 2014

Studies in wildlife ecology often involve species that are hunted, trapped, or are of additional economic or aesthetic importance to humans, including species that are rare, threatened, or endangered. The focus of the discipline is on the population rather than the individual; consequently, population ecology is central to wildlife conservation and management. Wildlife ecology has its philosophical and scientific beginnings in the early works of Aldo Leopold. Modern wildlife ecology often applies ecological theory to management and conservation of animals, but also includes theoretical studies on species that are considered wildlife. Wildlife ecology has become increasingly quantitative over time, and often employs capture‐recapture methods to estimate population size, survival, and other life‐history characteristics. Quantitative methods used to study wildlife include, but are not limited to, estimates of abundance, population viability analysis, home‐range estimation, movements, migration, spatial distributions, and landscape metrics. Radio telemetry is widely used to conduct research on wildlife. Habitat selection, stable isotope analysis, genetics, and behavioral sampling also play important roles in studies of wildlife.
Fate and Transport Models: Overview
Authors: Raun Loren
Published: September 2014

The use of environmental contaminant fate and transport models stems from the need to predict a concentration of contaminant at a spatial location separate from the source at a specified temporal point. The models simulate a simplification of the real‐world scenario. A prediction of this sort is used to support decisions in a wide range of hazardous waste contaminant source scenarios, from small and localized to major industrial. The level of complexity of the model chosen is contingent upon the configuration of the source, the temporal question, the end use needs, and the availability of field data. The theoretical basis for the most common models, the methods used to solve the equations, and the general use of the models to predict the fate and transport of contaminants in groundwater are reviewed. Further, the assumptions, varying levels of model complexity, and sources of uncertainty are discussed.
Receptor and Hybrid Modeling Tools
Authors: Vedantham Ram , Norris Gary , Duvall Rachelle
Published: September 2014

Practical and economical plans to reduce air pollution require models that relate the sources of airborne pollution to concentrations at sampling sites. In receptor models, samples of airborne pollution are subjected to extensive chemical analysis. Contributing sources leave chemical fingerprints in the sample. The amount of pollution coming from each source can be estimated if the chemical fingerprints of the sources are known. Thus, receptor models do not require any knowledge of emission rates or meteorological observations that are very important to atmospheric dispersion models. However, receptor models do rely on the observed concentrations of chemical species in the atmosphere. These species must be conserved during transport between the source and the receptor. Chemical elements are good candidates for receptor modeling since these are often immutable under ordinary conditions and relatively easily measured.
Similarity Theory
Authors: Sorbjan Zbigniew
Published: September 2014

A general method of finding universal relationships between physical variables is described. The approach is illustrated by several examples, such as finding the period of an ideal pendulum, velocity profile near a flat surface, and characteristic of the atmospheric surface layer.
LAD
Estimation with Applications in Time Series Analysis
Authors: Davis Richard A. , Wu Rongning
Published: September 2014

In this article, we are concerned with least absolute deviation (LAD) estimation applied to linear regression and linear time series models. LAD estimation is widely used in statistical modeling and analysis. Compared to classical least squares (LS), LAD is a robust estimation procedure and is typically more efficient when handling heavy‐tailed data. We provide a selective overview on its developments in linear regression and time series models. This overview includes a description of a basic method for establishing the asymptotic properties of the LAD estimator for finite variance autoregressive moving average (ARMA) models. Efficiency of LAD estimation relative to LS estimation as well as computational issues are also discussed.
Long‐Range Dependence
Authors: Robinson Peter. M.
Published: September 2014

Developments in research on stationary and nonstationary time series with long range dependence are reviewed.
Recursive Residuals
Authors: Frühwirth‐Schnatter Sylvia
Published: September 2014

Recursive residuals are used for model diagnostics, especially for time series models of continuous observations. By model diagnostics one means checking properties residuals should have under the assumption that the data were generated by the model under investigation. This check can be exploratory or formal. What distinguishes diagnostics based on recursive residuals from more conventional methods is the way the residuals are defined in a recursive manner from one‐step ahead predictive densities.
Space‐Time Kalman Filter
Authors: Cressie Noel , Wikle Christopher K.
Published: September 2014

The Kalman filter arose out of R.E. Kalman's interest in applying the concept of state vectors to the Wiener filtering problem. The success of this method was evident in early applications to trajectory estimation and control of spacecraft; it was so successful, in fact, that the Kalman filter quickly became an essential component of modern control systems theory and practice. This initial success led to the propagation of Kalman‐filtering ideas to other scientific disciplines, within which the methodology was adapted to suit numerous state–space oriented problems. Kalman filtering (of spatial data) is still an active area of research in the atmospheric and oceanic sciences.
Trend Analysis
Authors: Harvey Andrew
Published: September 2014

The question of defining a trend is one which has exercised the minds of statisticians for many years. In much of the statistical literature, a trend is conceived of as that part of a series which changes relatively slowly over time. Viewed in terms of prediction, the estimated trend is that part of the series which when extrapolated gives the clearest indication of the future long‐term movements in the series. Trend analysis is best carried out by means of unobserved‐component, or structural, time‐series models. The trend components in structural time‐series models are always set up in such a way that their forecast functions indicate the long‐term movements in the series, and the trend within the series can be obtained by signal extraction methods.
Trend Detecting
Authors: Woodward Wayne A.
Published: September 2014

This article discusses the problem of testing for trend in time series data, which is a difficult problem because, among other things, there is not a unified definition of trend. A variety of trend definitions are given and the distinction between deterministic and random trends is discussed. Simulated realizations with random trends are shown along with the global temperature data, and the issues related to deciding whether an apparent trend is deterministic or random are discussed. We examine classical tests for linear trend and discuss the inflated observed significance levels associated with many of these tests. Several tests are presented that have been developed to better control the observed significance level. Also discussed is the problem of using nonparametric methods to test for more general types of trend, such as monotonic trends, that may have no known functional form.
Z
ero‐
I
nflated
C
ount
T
ime
S
eries
Authors: Ray Bonnie K. , Thomas Sarah J.
Published: September 2014

This articles describes an observation‐driven approach to modeling univariate time series of counts that have an overabundance of zeros. A series of daily counts of excess pollution levels observed at air monitoring stations in and around Houston, TX is used to illustrate the ideas.
Multifunctional Luminescent Down‐Shifting Fluoropolymer Coatings: A Straightforward Strategy to Improve the UV‐Light Harvesting Ability and Long‐Term Outdoor Stability of Organic Dye‐Sensitized Solar Cells
Authors: Griffini Gianmarco , Bella Federico , Nisic Filippo , Dragonetti Claudia , Roberto Dominique , Levi Marinella , Bongiovanni Roberta , Turri Stefano
Published: September 2014

A new multifunctional coating for photovoltaic cells incorporating light‐management, UV‐protection, and easy‐cleaning capabilities is presented. Such coating consists of a new photocurable fluorinated polymer embedding a luminescent europium complex that acts as luminescent down‐shifting (LDS) material converting UV photons into visible light. The combination of this system with ruthenium‐free organic dye‐sensitized solar cells (DSSCs) gives a 70% relative increase in power conversion efficiency as compared with control uncoated devices, which is the highest efficiency enhancement reported to date on organic DSSC systems by means of a polymeric LDS layer. Long‐term (>2000 h) weathering tests in real outdoor conditions reveal the excellent stabilizing effect of the new coating on DSSC devices, which fully preserve their initial performance. This excellent outdoor stability is attributed to the combined action of the luminescent material that acts as UV‐screen and the highly photostable, hydrophobic fluoropolymeric carrier that further prevents photochemical and physical degradation of the solar cell components. The straightforward approach presented to simultaneously improve performance and outdoor stability of DSSC devices may be readily extended to a large variety of sensitizer/luminophore combinations, thus enabling the fabrication of highly efficient and extremely stable DSSCs in an easy and versatile fashion.
Fluorene‐based boronic acids as fluorescent chemosensor for monosaccharides at physiological pH
Authors: Hosseinzadeh Rahman , Mohadjerani Maryam , Pooryousef Mona
Published: September 2014

Two fluorene‐based boronic acids, 9,9‐dimethyl‐9H‐fluoren‐2‐yl‐2‐boronic acid (1) and 9,9‐dimethyl‐9H‐fluoren‐2,7‐diyl‐2,7‐diboronic acid (2), were synthesized and their sensing abilities for detection of D‐monosaccharides were investigated by fluorescence at physiological pH. It was found that both boronic acids 1 and 2 have high selectivity and sensitivity for D‐fructose with stability constant of 47.2 and 412.9, respectively. The sensor 2 showed a linear response toward D‐fructose in the concentration range from 5 × 10–5 to 10–1 mol L–1 with the detection limit of 2 × 10–5 mol L–1. Copyright © 2014 John Wiley & Sons, Ltd.
Specific Modulation of Protein Activity by Using a Bioorthogonal Reaction
Authors: Warner John B. , Muthusamy Anand K. , Petersson E. James
Published: September 2014

Unnatural amino acids with bioorthogonal reactive groups have the potential to provide a rapid and specific mechanism for covalently inhibiting a protein of interest. Here, we use mutagenesis to insert an unnatural amino acid containing an azide group (Z) into the target protein at positions such that a “click” reaction with an alkyne modulator (X) will alter the function of the protein. This bioorthogonally reactive pair can engender specificity of X for the Z‐containing protein, even if the target is otherwise identical to another protein, allowing for rapid target validation in living cells. We demonstrate our method using inhibition of the Escherichia coli enzyme aminoacyl transferase by both active‐site occlusion and allosteric mechanisms. We have termed this a “clickable magic bullet” strategy, and it should be generally applicable to studying the effects of protein inhibition, within the limits of unnatural amino acid mutagenesis.
A study on the absorption of ammonia into water in a rotor‐stator reactor
Authors: Li Yingwen , Sun Baochang , Zeng Zequan , Song Yunhua , Chen Jianming , Chu Guangwen , Chen Jianfeng , Shao Lei
Published: September 2014

This article presents experimental and modelling studies on the absorption of NH3 into water in a rotor‐stator reactor (RSR). The influences of operating parameters such as the rotation speed of rotor, liquid flow rate, and gas flow rate on the overall volumetric mass transfer coefficient (Kya) of NH3 were investigated. It was found that Kya increased with an increasing rotation speed, liquid flow rate, and gas flow rate. A correlation to predict the Kya of NH3 in the RSR was established and found to be in agreement with the experimental data with deviations within 10 %. A comparison was made between the Kya of NH3 in the RSR and RPB, and the result showed that Kya of NH3 in the RSR was 13 % higher than that in the RPB, thus signifying that the RSR has better intensification effect for mass transfer limited processes than the RPB.
Two New Triterpenoids from Lycopodium japonicum Thunb.
Authors: Wang Xiaojing , Yu Dequan , Yu Shishan
Published: September 2014

Ten serratene‐type triterpenoids including two new ones, named 3β‐hydroxyserrat‐14‐en‐21β‐yl‐formate (1) and 21β‐hydroxyserrat‐14‐en‐3β‐yl‐formate (2), were isolated from Lycopodium japonicum Thunb. Their structures were established by means of spectroscopic analysis. Both of these two new compounds are formates of serratene‐type triterpenoids.
Micro/macro viability analysis of individual‐based models: Investigation into the viability of a stylized agricultural cooperative
Authors: Martin Sophie , Alvarez Isabelle , Kant Jean‐Daniel
Published: September 2014

The mathematical viability theory proposes methods and tools to study at a global level how controlled dynamical systems can be confined in a desirable subset of the state space. Multilevel viability problems are rarely studied since they induce combinatorial explosion (the set of N agents each evolving in a p‐dimensional state space, can evolve in a Np dimensional state space). In this article, we propose an original approach which consists in solving first local viability problems and then studying the real viability of the combination of the local strategies, by simulation where necessary. In this article, we consider as multilevel viability problem a stylized agricultural cooperative which has to keep a minimum of members. Members have an economical constraint and some members have a simple model of the functioning of the cooperative and make assumptions on other members' behavior, especially proviable agents which are concerned about their own viability. In this framework, the model assumptions allow us to solve the local viability problem at the agent level. At the cooperative level, considering mixture of agents, simulation results indicate if and when including proviable agents increases the viability of the whole cooperative. © 2014 Wiley Periodicals, Inc. Complexity 21: 276–296, 2015
Preserving, augmenting, and creating cold‐water thermal refugia in rivers: concepts derived from research on the Miramichi River, New Brunswick (Canada)
Authors: Kurylyk Barret L. , MacQuarrie Kerry T. B. , Linnansaari Tommi , Cunjak Richard A. , Curry R. Allen
Published: September 2014

Summer water temperatures are rising in many river systems in North America, and this warming trend is projected to intensify in the coming decades. Cold‐water fish may alleviate thermal stress in summer by aggregating in discrete cold‐water plumes that provide thermal refuge from high ambient river temperatures. Reliance on cold‐water thermal refugia is expected to increase in a warming climate, and many river reaches already lack suitable thermal refugia as a result of an absence of thermal diversity. A comprehensive fish management strategy could proactively address this imminent threat to cold‐water fish populations across North America by preserving existing thermal refugia, augmenting thermal anomalies to improve performance as refugia, and creating new thermal refugia in uniformly warm river reaches. We provide practical recommendations on how these measures can be accomplished based on insight derived from recent research focused on the Miramichi River, New Brunswick. Opportunities include limiting land use change, construction aggregate extraction (e.g. sand and gravel pits), and groundwater pumping/consumption. Existing thermal anomalies can be enhanced by controlling advective thermal mixing between cold‐water tributaries and the river mainstem flow, installing riparian shading, and adding temporary structures for protection from avian predators. New refugia can be created by temporarily pumping groundwater to discrete points within the river during periods of thermal stress. These concepts are discussed in the context of a comprehensive thermal refugia management strategy. Copyright © 2014 John Wiley & Sons, Ltd.
Critical conditions for natural gas charging and delineation of effective gas source rocks for tight sandstone reservoirs
Authors: Jiang Fujie , Pang Xiongqi , Guo Fengtao , Guo Jigang
Published: September 2014

Although it has been shown that the potential of tight‐sand gas resources is large, the research into the mechanisms of hydrocarbon charging of tight sandstone reservoirs has been relatively sparse. Researchers have found that there is a force balance during hydrocarbon charging, but discriminant models still have not been established. Based on the force balance conditions observed during gas migration from source rocks to tight sandstone reservoirs, a calculation formula was established. A formula for identifying effective source rocks was developed with the gas expulsion intensity as the discrimination parameter. The critical gas expulsion intensity under conditions of various burial depths, temperatures, and pressures can be obtained using the calculation formula. This method was applied in the Jurassic tight sandstone reservoirs of the eastern Kuqa Depression, Tarim Basin, and it was calculated that the critical expulsion intensity range from 6.05 × 108 m3/km2 to 10.07 × 108 m3/km2. The critical gas charging force first increases with depth and later decreases with greater depths. The distribution range of effective gas source rocks and total expelled gas volume can be determined based on this threshold. This method provides new insight into and method for predicting favourable tight‐sand gas‐bearing regions and estimating their resource potentials. Copyright © 2014 John Wiley & Sons, Ltd.
Differences in long‐term survival among liver transplant recipients and the general population: A population‐based nordic study
Authors: Åberg Fredrik , Gissler Mika , Karlsen Tom H. , Ericzon Bo‐Göran , Foss Aksel , Rasmussen Allan , Bennet William , Olausson Michael , Line Pål‐Dag , Nordin Arno , Bergquist Annika , Boberg Kirsten Muri , Castedal Maria , Pedersen Christian Ross , Isoniemi Helena
Published: September 2014

Dramatic improvement in first‐year outcomes post‐liver transplantation (LT) has shifted attention to long‐term survival, where efforts are now needed to achieve improvement. Understanding the causes of premature death is a prerequisite for improving long‐term outcome. Overall and cause‐specific mortality of 3,299 Nordic LT patients (1985‐2009) having survived 1 year post‐LT were divided by expected rates in the general population, adjusted for age, sex, calendar date, and country to yield standardized mortality ratios (SMRs). Data came from the Nordic Liver‐Transplant Registry and WHO mortality‐indicator database. Stagnant patient survival rates >1 year post‐LT were 21% lower at 10 years than expected survival for the general population. Overall SMR for death before age 75 (premature mortality) was 5.8 (95% confidence interval [CI] 5.4‐6.3), with improvement from 1985‐1999 to 2000‐2010 in hepatitis C (HCV) (SMR change 23.1‐9.2), hepatocellular carcinoma (HCC) (SMR 38.4‐18.8), and primary sclerosing cholangitis (SMR 11.0‐4.2), and deterioration in alcoholic liver disease (8.3‐24.0) and acute liver failure (ALF) (5.9‐7.6). SMRs for cancer and liver disease (recurrent or transplant‐unrelated disease) were elevated in all indications except primary biliary cirrhosis (PBC). Absolute mortality rates underestimated the elevated premature mortality from infections (SMR 22‐693) and kidney disease (SMR 13‐45) across all indications, and from suicide in HCV and ALF. SMR for cardiovascular disease was significant only in PBC and alcoholic liver disease, owing to high mortality in the general population. Transplant‐specific events caused 16% of deaths. Conclusion: standardized premature mortality provided an improved picture of long‐term post‐LT outcome, showing improvement over time in some indications, not revealed by overall absolute mortality rates. Causes with high premature mortality (infections, cancer, kidney and liver disease, and suicide) merit increased attention in clinical patient follow‐up and future research. (Hepatology 2015;61:668‐677)
It Takes Three to Tango: Exploring the Interplay among Training Intensity, Job Autonomy, and Supervisor Support in Predicting Knowledge Sharing
Authors: Buch Robert , Dysvik Anders , Kuvaas Bård , Nerstad Christina G. L.
Published: September 2014

This study explored whether the relationship between perceived training intensity and knowledge sharing is prone to combined moderating influences. We operationalized perceived training intensity as a challenge stressor, in accordance with the challenge‐hindrance framework of work stressors. The results of a study of 129 employees from three Norwegian service industries revealed a positive relationship between perceived training intensity and supervisor‐rated knowledge sharing for employees reporting high levels of perceived job autonomy and high levels of perceived supervisor support. In contrast, we found a negative relationship between perceived training intensity and supervisor‐rated knowledge sharing for employees reporting high levels of perceived job autonomy and low levels of perceived supervisor support. These findings suggest that supervisors are of vital importance in facilitating knowledge sharing among employees in settings where developmental challenges are prevalent and perceptions of job autonomy are high. Implications for future research and practice are also discussed. © 2014 Wiley Periodicals, Inc.
Radical Propagation Kinetics of N‐Vinylpyrrolidone in Organic Solvents Studied by Pulsed‐Laser Polymerization–Size‐Exclusion Chromatography (PLP–SEC)
Authors: Uhelská Lucia , Chorvát Dušan , Hutchinson Robin A. , Santanakrishnan Sandhya , Buback Michael , Lacík Igor
Published: September 2014

Pulsed‐laser polymerization with subsequent analysis of the polymer molar mass distribution by size‐exclusion chromatography, PLP–SEC, is used to measure the propagation rate coefficient, kp, of N‐vinylpyrrolidone (NVP) in a series of organic solvents, varying the NVP concentration from 5 to 100 wt% and varying the temperature between –5 and +80 °C. In contrast to the 20‐fold increase observed in aqueous solution upon decreasing the NVP concentration from bulk to dilute conditions, the kp values of NVP in butyl acetate, iso‐propyl acetate, N‐ethylpyrrolidone, and N‐ethylformamide stay within 20% of the bulk value and exhibit no significant dependence on monomer concentration. The kp behavior of NVP in methanol and n‐butanol is intermediate between the one in water and in the other organic solvents, with kp increasing by about a factor of 2 upon lowering the monomer concentration from bulk to 5 wt% NVP. The activation energies for propagation in organic solvents agree within experimental uncertainty with the value reported for bulk NVP. The data demonstrate that hydrogen bonding is responsible for the increase in kp upon dilution, with this effect being much stronger in an aqueous environment than in a solution of alcohol.

image
Understanding chicken walks on n × n grid: Hamiltonian paths, discrete dynamics, and rectifiable paths
Authors: Rao Arni S.R. Srinivasa , Tomley Fiona , Blake Damer
Published: September 2014

Understanding animal movements and modeling the routes they travel can be essential in studies of pathogen transmission dynamics. Pathogen biology is also of crucial importance, defining the manner in which infectious agents are transmitted. In this article, we investigate animal movement with relevance to pathogen transmission by physical rather than airborne contact, using the domestic chicken and its protozoan parasite Eimeria as an example. We have obtained a configuration for the maximum possible distance that a chicken can walk through straight and nonoverlapping paths (defined in this paper) on square grid graphs. We have obtained preliminary results for such walks which can be practically adopted and tested as a foundation to improve understanding of nonairborne pathogen transmission. Linking individual nonoverlapping walks within a grid‐delineated area can be used to support modeling of the frequently repetitive, overlapping walks characteristic of the domestic chicken, providing a framework to model fecal deposition and subsequent parasite dissemination by fecal/host contact. We also pose an open problem on multiple walks on finite grid graphs. These results grew from biological insights and have potential applications. © 2014 The Authors. Mathematical Methods in the Applied Sciences published by John Wiley & Sons Ltd.
Antidepressant treatment and suicide attempts and self‐inflicted injury in children and adolescents
Authors: Gibbons Robert D. , Coca Perraillon Marcelo , Hur Kwan , Conti Rena M. , Valuck Robert J. , Brent David A.
Published: September 2014

Purpose

In the 2004, FDA placed a black box warning on antidepressants for risk of suicidal thoughts and behavior in children and adolescents. The purpose of this paper is to examine the risk of suicide attempt and self‐inflicted injury in depressed children ages 5–17 treated with antidepressants in two large observational datasets taking account time‐varying confounding.

Methods

We analyzed two large US medical claims databases (MarketScan and LifeLink) containing 221,028 youth (ages 5–17) with new episodes of depression, with and without antidepressant treatment during the period of 2004–2009. Subjects were followed for up to 180 days. Marginal structural models were used to adjust for time‐dependent confounding.

Results

For both datasets, significantly increased risk of suicide attempts and self‐inflicted injury were seen during antidepressant treatment episodes in the unadjusted and simple covariate adjusted analyses. Marginal structural models revealed that the majority of the association is produced by dynamic confounding in the treatment selection process; estimated odds ratios were close to 1.0 consistent with the unadjusted and simple covariate adjusted association being a product of chance alone.

Conclusions

Our analysis suggests antidepressant treatment selection is a product of both static and dynamic patient characteristics. Lack of adjustment for treatment selection based on dynamic patient characteristics can lead to the appearance of an association between antidepressant treatment and suicide attempts and self‐inflicted injury among youths in unadjusted and simple covariate adjusted analyses. Marginal structural models can be used to adjust for static and dynamic treatment selection processes such as that likely encountered in observational studies of associations between antidepressant treatment selection, suicide and related behaviors in youth. Copyright © 2014 John Wiley & Sons, Ltd.
Quantitative phosphoproteomics reveals crosstalk between phosphorylation and O‐GlcNAc in the DNA damage response pathway
Authors: Zhong Jun , Martinez Marissa , Sengupta Srona , Lee Albert , Wu Xinyan , Chaerkady Raghothama , Chatterjee Aditi , O'Meally Robert N. , Cole Robert N. , Pandey Akhilesh , Zachara Natasha E.
Published: September 2014

The modification of intracellular proteins by monosaccharides of O‐linked β‐N‐acetylglucosamine (O‐GlcNAc) is an essential and dynamic PTM of metazoans. The addition and removal of O‐GlcNAc is catalyzed by the O‐GlcNAc transferase (OGT) and O‐GlcNAcase, respectively. One mechanism by which O‐GlcNAc is thought to mediate proteins is by regulating phosphorylation. To provide insight into the pathways regulated by O‐GlcNAc, we have utilized SILAC‐based quantitative proteomics to carry out comparisons of site‐specific phosphorylation in OGT wild‐type and Null cells. Quantitation of the phosphoproteome demonstrated that of 5529 phosphoserine, phosphothreonine, and phosphotyrosine sites, 232 phosphosites were upregulated and 133 downregulated in the absence of O‐GlcNAc. Collectively, these data suggest that deletion of OGT has a profound effect on the phosphorylation of cell cycle and DNA damage response proteins. Key events were confirmed by biochemical analyses and demonstrate an increase in the activating autophosphorylation event on ATM (Ser1987) and on ATM's downstream targets p53, H2AX, and Chk2. Together, these data support widespread changes in the phosphoproteome upon removal of O‐GlcNAc, suggesting that O‐GlcNAc regulates processes such as the cell cycle, genomic stability, and lysosomal biogenesis. All MS data have been deposited in the ProteomeXchange with identifier PXD001153 (http://proteomecentral.proteomexchange.org/dataset/PXD001153).
The Effect of Autocorrelation on the Hotelling T2 Control Chart
Authors: Vanhatalo Erik , Kulahci Murat
Published: September 2014

One of the basic assumptions for traditional univariate and multivariate control charts is that the data are independent in time. For the latter, in many cases, the data are serially dependent (autocorrelated) and cross‐correlated because of, for example, frequent sampling and process dynamics. It is well known that the autocorrelation affects the false alarm rate and the shift‐detection ability of the traditional univariate control charts. However, how the false alarm rate and the shift‐detection ability of the Hotelling T2 control chart are affected by various autocorrelation and cross‐correlation structures for different magnitudes of shifts in the process mean is not fully explored in the literature. In this article, the performance of the Hotelling T2 control chart for different shift sizes and various autocorrelation and cross‐correlation structures are compared based on the average run length using simulated data. Three different approaches in constructing the Hotelling T2 chart are studied for two different estimates of the covariance matrix: (i) ignoring the autocorrelation and using the raw data with theoretical upper control limits; (ii) ignoring the autocorrelation and using the raw data with adjusted control limits calculated through Monte Carlo simulations; and (iii) constructing the control chart for the residuals from a multivariate time series model fitted to the raw data. To limit the complexity, we use a first‐order vector autoregressive process and focus mainly on bivariate data. © 2014 The Authors. Quality and Reliability Engineering International Published by John Wiley & Sons Ltd.