bluuebunny/crossref_metadata_2025_split huggingface dataset:
A unified encyclopedia of human functional DNA elements through fully automated annotation of 164 human cell types
Authors: Libbrecht Maxwell W. , Rodriguez Oscar , Weng Zhiping , Bilmes Jeffrey A. , Hoffman Michael M. , Noble William S. 
Published: November 2016

AbstractSemi-automated genome annotation methods such as Segway enable understanding of chromatin activity. Here we present chromatin state annotations of 164 human cell types using 1,615 genomics data sets. To produce these annotations, we developed a fully-automated annotation strategy in which we train separate unsupervised annotation models on each cell type and use a machine learning classifier to automate the state interpretation step. Using these annotations, we developed a measure of the importance of each genomic position called the “conservation-associated activity score,” which we use to aggregate information across cell types into a multi-cell type view. The aggregated conservation-associated activity score provides a measure of importance directly attributable to a specific activity in a specific set of cell types. In contrast to evolutionary conservation, this measure is not biased to detect only elements shared with related species. Using the conservation-associated activity score, we combined all our annotations into a single, cell type-agnostic encyclopedia that catalogs all human transcriptional and regulatory elements, enabling easy and intuitive interpretation of the effect of genome variants on phenotype, such as in disease-associated, evolutionarily conserved or positively selected loci. These resources, including cell type-specific annotations, encyclopedia, and a visualization server, are available athttp://noble.gs.washington.edu/proj/encyclopedia.Author SummaryGenome annotation algorithms are an effective class of tools for understanding the function of the genome. These algorithms take as input a set of genome-wide measurements about the activity at each base pair in a given tissue, such as where a given protein is binding or how accessible the DNA is to being read by a protein. The genome is then partitioned and each segment is assigned a label such that positions with the same label exhibit similar patterns in the input data. Such annotations are widely used for many applications, such as to understand the mechanism of impact of a given genetic variant. Here we present, to our knowledge, the most comprehensive set of genome annotations created so far, encompassing 164 human cell types and including 1,615 genomics data sets. These comprehensive annotations are made possible by a strategy that automates the previous interpretation step. Furthermore, we present several methodological innovations that make these genome annotations more useful.
Beyond excitation/inhibition imbalance in multidimensional models of neural circuit changes in brain disorders
Authors: O’Donnell Cian , Tiago Gonçalves J. , Portera-Cailliau Carlos , Sejnowski Terrence J. 
Published: November 2016

AbstractA leading theory holds that neurodevelopmental brain disorders arise from imbalances in excitatory and inhibitory (E/I) brain circuitry. However, it is unclear whether this onedimensional model is rich enough to capture the multiple neural circuit alterations underlying brain disorders. Here we combined computational simulations with analysis ofin vivo2-photon Ca2+imaging data from somatosensory cortex ofFmr1knock-out (KO) mice, a model of Fragile-X Syndrome, to test the E/I imbalance theory. We found that: 1) The E/I imbalance model cannot account for joint alterations in the observed neural firing rates and correlations; 2) Neural circuit function is vastly more sensitive to changes in some cellular components over others; 3) The direction of circuit alterations inFmr1KO mice changes across development. These findings suggest that the basic E/I imbalance model should be updated to higher-dimensional models that can better capture the multidimensional computational functions of neural circuits.
Application of PSO algorithm to choose the best scenario for energy demand forecast of residential and commercial sectors in Iran
Authors: Nazari Hesam , Kazemi Aliyeh 
Published: November 2016

Purpose
This paper aims to select the best scenario for energy demand forecast of residential and commercial sectors in Iran by using particle swarm optimization algorithm.

Design/methodology/approach
In this study, using variables affecting energy demand of residential and commercial sectors in Iran, the future status of energy demand in these sectors is predicted. Using the particle swarm optimization algorithm, both linear and exponential forms of energy demand equations were studied under 72 different scenarios with various variables. The data from 1968 to 2011 were applied for model development and the appropriate scenario choice.

Findings
An exponential model with inputs including total value added minus that of the oil sector, value of made buildings, total number of households and consumer energy price index is the most suitable model. Finally, energy demand of residential and commercial sectors is estimated up to the year 2032. Results show that the energy demand of the sectors will achieve a level of about 1,718 million barrels of oil equivalent per year by 2032.

Originality/value
To the best of our knowledge in this study a suitable model is selected for energy demand forecast of residential and commercial sectors by evaluation of various models with different variables as inputs.
Impact of crime on spatial analysis of house prices: evidence from a UK city
Authors: McIlhatton David , McGreal William , Taltavul de la Paz Paloma , Adair Alastair 
Published: November 2016

Purpose
There is a lack of understanding in the literature on the spatial relationships between crime and house price. This paper aims to test the impact of spatial effects in the housing market, how these are related to the incidence of crime and whether effects vary by the type of crime.

Design/methodology/approach
The analysis initially explores univariate and bivariate spatial patterns in crime and house price data for the Belfast Metropolitan Area using Moran’s I and Local Indicator Spatial Association (LISA) models, and secondly uses spatial autoregression models to estimate the role of crime on house prices. A spatially weighted two-stage least-squares model is specified to analyse the joint impact of crime variables. The analysis is cross sectional, based on a panel of data.

Findings
The paper illustrates that the pricing impact of crime is complex and varies by type of crime, property type and location. It is shown that burglary and theft are associated with higher-income neighbourhoods, whereas violence against persons, criminal damage and drugs offences are mainly associated with lower-priced neighbourhoods. Spatial error effects are reduced in models based on specific crime variables.

Originality/value
The originality of this paper is the application of spatial analysis in the study of the impact of crime upon house prices. Criticisms of hedonic price models are based on unexplained error effects; the significance of this paper is the reduction of spatial error effects achievable through the analysis of crime data.
The impact of residential development on nearby housing prices
Authors: Kurvinen Antti Tapio , Vihola Jaakko 
Published: November 2016

PurposeEven as multi-story apartment building development proposals in existing neighbourhoods represent a substantial component of policy debate at local planning boards, there is limited evidence for the impact of such residential developments on surrounding apartment values. This paper aims to address the void in knowledge, and the impact of multi-story apartment building developments on apartment values in residential high-rise areas located outside city and district centres is investigated in Helsinki Metropolitan Area, Finland.Design/methodology/approachWhether a multi-story apartment building development is followed by an increase in housing values depends on both positive and negative externalities. To specify valuation effects of proximate development projects, advanced research design combining matched sample methodology and hedonic-based difference-in-difference approach is used.FindingsIt appears from the analysis that completion of a single multi-story apartment building has an immediate positive impact on apartment values within 300 metre radius, while there is no statistically significant impact on price trend.Research limitations/implicationsThis paper studies apartment values only in Helsinki Metropolitan Area, Finland, and it is important to notice that local regulations and market conditions may have a notable impact on the outcomes.Originality/valueThis study is the first of its kind to provide with statistically significant evidence for positive impacts from multi-story apartment building development in Finnish residential high-rise areas and may have a crucial role in helping to dispel prejudices related to such developments.
The quantitative easing effect on the stock market of the USA, the UK and Japan
Authors: Lima Luiz , Vasconcelos Claudio Foffano , Simão Jose , de Mendonça Helder Ferreira 
Published: November 2016

PurposeThe purpose of this paper is to analyze if the unconventional monetary policy, known as quantitative easing (QE) practiced by central banks in the USA, the UK, and Japan was effective to increase the market share after subprime crisis.Design/methodology/approachIn order to analyze the effect of the QE on the stock markets of the USA, the UK, and Japan, the authors use an ARDL model to find the long-run relationship among the variables.FindingsThe findings denote that the QE implemented by the central banks in the USA, Japan, and the UK had a positive impact on their stock markets.Originality/valueThe results of the paper give some new insights about the conduction of monetary policy when the interest rates are close to zero.
Diversity and competition influence tree allometric relationships – developing functions for mixed‐species forests
Authors: Forrester David Ian , Benneter Adam , Bouriaud Olivier , Bauhus Jürgen 
Published: November 2016

Summary

Promoting mixed‐species forests is an important strategy for adaptation and risk reduction in the face of global change. Concurrently, a main challenge in ecology is to quantify the effects of species diversity on ecosystem functioning. In forests, the effects of individual tree species on ecosystem functions depend largely on their dimensions, which are commonly predicted using allometric equations. However, little is known about how diversity influences allometry or how to incorporate this effect into allometric equations. Ignoring the effects of interspecific interactions on allometric relationships may result in severely biased predictions.

This study examined the effects of tree‐species diversity, competition and tree social status on crown‐projection area (cpa), height (h) and live‐crown length (lcl) of trees using a European‐wide data set containing 17 target species and 12 939 trees. The cpa, h and lcl were predicted as functions of stem diameter at 1·3 m, tree‐species diversity, tree height relative to the stand mean height (rh) and a competition index (CI) that accounted for stand density and interspecific differences in competitive ability based on species‐specific wood density or shade tolerance.

Averaged across species, diameter had the greatest effect on cpa and lcl, followed by the competition index, while rh had the greatest effect on lcl. Tree‐species diversity had the smallest effect on cpa, h and lcl. Interspecific variability in cpa, h or lcl responses to diversity, CI, or rh was sometimes related to wood density or shade tolerance.

Synthesis. This study shows the strong influence of stand structure and species composition on allometric relationships. These influences can be quantified using measures of competition, tree‐species diversity and relative tree height so that general equations can be developed for a given species to be applied to a wide range of species compositions and stand structures. This new approach will greatly improve predictions of biomass and carbon stocks in structurally and compositionally diverse forests.
An evolutionary game theoretical model shows the limitations of the additive partitioning method for interpreting biodiversity experiments
Authors: Vermeulen Peter J. , van Ruijven Jasper , Anten Niels P. R. , van der Werf Wopke 
Published: November 2016

Summary

The relationship between diversity and ecosystem functioning is often analysed by partitioning the change in species performance in mixtures into a complementarity effect (CE) and a selection effect (SE). There is continuing ambiguity in the literature on the interpretation of these effects, mainly in their relationship to ecological mechanisms and processes.

Here, we present the emergence of complementarity and selection effects in the results of an evolutionary game theoretical model for plant competition which is exclusively based on competition for light. Eight plant strategies, differing only in the time of onset of flowering, were played against one another to determine the relationship between plant trait differences and CE vs. SE.

We show that competitive exclusion may occur even in the presence of a positive CE, i.e. when CE > 0. CE was highest at intermediate differences in flowering time. Increasing trait differences may, therefore, increase CE without leading to coexistence.

SE was strongly dependent on which of the strategies was paired. SE was mostly positive if one of the players was early flowering (with low seed yield) and the other strategy had higher monoculture yields. SE was mostly negative if one of the players was late flowering, leading to low monoculture yield for this strategy, but to high gains when competing with strategies that produce less leaf area. The average SE was negative over all pairs.

Synthesis. These results show that CE may be positive if the species interaction is beneficial for only one of the two competitors, and the sign of SE depends critically on the underlying mechanism for performance in monoculture. Positive complementarity may go hand in hand with competitive exclusion, while widely different outcomes in SE are possible within a single mechanistic background. Consequently, the way SE changes with increasing richness are not only related to a sampling/selection effect but also by the way the interacting species affect the competitive environment. Interpreting the additive partitioning method with a set notion in mind about the driving mechanisms could lead to incorrect conclusions on how species richness effects drive ecosystem functioning.
Phenotypic variation in food utilization in an outbreak insect herbivore
Authors: Quezada‐García Roberto , Fuentealba Álvaro , Bauce Éric 
Published: November 2016

AbstractThe effects of nutrition may have subtantial impact on insect evolution by shaping different components of phenotypes. The key to undestanding this evolutionary process is to know how nutritional condition affects additive and nonadditive components of the phenotype. However, this is poorly understood in outbreaking insects. We investigated the additive and nonadditive variation present in food utilization traits in spruce budworm individuals subjected to chronic nutritional stress. A total of 160 full‐sib families of spruce budworm (Choristoneura fumiferana Clem.) were raised under laboratory conditions, feeding on 2 diets (high and low energy) during 3 generations. Variables tested were pupal mass, consumption rate (RCR), growth rate (RGR), approximate digestibility (AD), the efficiency of conversion of digested food (ECD) and the efficiency of conversion of ingested food (ECI). Our results show that all traits tested presented a high percentage of nonadditive effects that modulate phenotype expression. We found a significant impact of family × diet interaction on pupal mass, RGR and ECD. Furthermore, these traits exhibited the greatest heritability. There was no evidence of presence of maternal effects. The results revealed that food utilization traits may evolve through epigenetics effects, such as phenotypic plasticity. This information can be used by modellers to improve forecast of spruce budworm population dynamics.
Decomposing functional diversity
Authors: Scheiner Samuel M. , Kosman Evsey , Presley Steven J. , Willig Michael R. 
Published: November 2016

Summary

One aspect of biodiversity, functional diversity, reflects the functional role of species within a community as measured by species characteristics. We present a new metric, functional trait dispersion, based on the concept of species distinctiveness measured as the distance among species in the multidimensional space defined by trait values. This metric can be decomposed into components of species richness, functional evenness and mean dispersion, and into parts that measure diversity within and among subgroups.

Using an appropriate distance measure, mean dispersion (M′) is calculated as the average distance among all possible pairs of species. Functional evenness [qE(T)] is derived from Hill diversity based on the proportional distances between pairs of species and species richness (S). Functional trait dispersion [qD(TM)] is then computed as 1 + (S−1) × qE(T) × M′. It has a range of [1,S] and measures the effective number of functionally distinct species for a given level of species dispersion.

Using constructed data, we demonstrate that qD(TM) captures appropriate ecological properties such that a community with greater species richness, greater dispersal in trait space or greater mean dispersion has greater functional diversity. Functional trait dispersion can also provide measures of within‐community dispersion and the effective number of functionally distinctive compartments (groups of communities with similar functional structure). Using empirical data of bats along an elevational gradient in Peru, we demonstrate that functional trait dispersion and its components provide insights about gradients of biodiversity.

Functional trait dispersion comports to reasonable criteria for a metric of functional diversity and can be decomposed in a variety of ways that facilitate understanding of patterns of variation. Other metrics of functional diversity neither integrate all three diversity components, nor can many be decomposed into variation within and among subgroups. Because functional trait dispersion measures properties of distance and the effective number of functionally distinct species, it can be used in conjunction with other biodiversity metrics that are based on species identity, abundance or phylogenetic relatedness to inform management and the preservation of biodiversity.
Monitoring of plant–environment interactions by high‐throughput FTIR spectroscopy of pollen
Authors: Bağcıoğlu Murat , Kohler Achim , Seifert Stephan , Kneipp Janina , Zimmermann Boris 
Published: November 2016

Summary

Fourier transform infrared (FTIR) spectroscopy enables chemical analysis of pollen samples for plant phenotyping to study plant–environment interactions, such as influence of climate change or pathogens. However, current approach, such as microspectroscopy and attenuated total reflection spectroscopy, does not allow for high‐throughput protocols. This study at hand suggests a new spectroscopic method for high‐throughput characterization of pollen.

Samples were measured as thin films of pollen fragments using a Bruker FTIR spectrometer with a high‐throughput eXTension (HTS‐XT) unit employing 384‐well plates. In total, 146 pollen samples, belonging to 31 different pollen species of Fagaceae and Betulaceae and collected during three consecutive years (2012–2014) at locations in Croatia, Germany and Norway, were analysed. Critical steps in the sample preparation and measurement, such as variabilities between technical replicates, between microplates and between spectrometers, were studied.

Measurement variations due to sample preparation, microplate holders and instrumentation were low, and thus allowed differentiation of samples with respect to phylogeny and biogeography. The spectral variability for a range of Fagales species (Fagus, Quercus, Betula, Corylus, Alnus and Ostrya) showed high‐species‐specific differences in pollen's chemical composition due to either location or year. Statistically significant inter‐annual and locational differences in the pollen spectra indicate that pollen chemical composition has high phenotypic plasticity and is influenced by local climate conditions. The variations in composition are connected to lipids, proteins, carbohydrates and sporopollenins that play crucial roles in cold and desiccation tolerance, protection against UV radiation and as material and energy reserves.

The results of this study demonstrate the value of high‐throughput FTIR approach for the systematic collection of data on ecosystems. The novel FTIR approach offers fast, reliable and economical screening of large number of samples by semi‐automated methodology. The high‐throughput approach could provide crucial understanding on plant–climate interactions with respect to biochemical variation within genera, species and populations.
Quantitative ornithology with a commercial marine radar: standard‐target calibration, target detection and tracking, and measurement of echoes from individuals and flocks
Authors: Urmy Samuel S. , Warren Joseph D. 
Published: November 2016

Summary

Marine surveillance radars are commonly used for radar ornithology, but they are rarely calibrated. This prevents them from measuring the radar cross‐sections (RCS) of the birds under study. Furthermore, if the birds are aggregated too closely for the radar to resolve them individually, the bulk volume reflectivity cannot be translated into a numerical density.

We calibrated a commercial off‐the‐shelf marine radar, using a standard spherical target of known RCS. Once calibrated, the radar was used to measure the RCS of common and roseate terns (Sterna hirundo L. and Sterna dougallii Montagu) tracked from a land‐based installation at their breeding colony on Great Gull Island, NY, USA. We also integrated echoes from flocks of terns, comparing these total flock cross‐sections with visual counts from photos taken at the same time as the radar measurements.

The radar's calibration parameters were determined with 1% error. RCS measurements made after calibration were expected to be accurate within ±2 dB. Mean tern RCS was estimated at −28 dB relative to one square meter (dBsm), agreeing in magnitude with a simple theoretical model. RCS was 3–4 dB higher when birds’ aspect angles were broadside to the radar beam compared with head‐ or tail‐on. Integrated flock cross‐section was linearly related to the number of birds. The slope of this line, an independent estimate of RCS, was −32 dBsm, within an order of magnitude of the estimate from individual birds, and near the middle of the frequency distribution of RCS values.

These results indicate that a calibrated marine radar can count the birds in an aggregation via echo integration. Field calibration of marine radars is practical, enables useful measurements, and should be done more often.