bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sapling: Accelerating Suffix Array Queries with Learned Data Models
Authors: Kirsche Melanie , Das Arun , Schatz Michael C. 
Published: January 2020

AbstractMotivationAs genomic data becomes more abundant, efficient algorithms and data structures for sequence alignment become increasingly important. The suffix array is a widely used data structure to accelerate alignment, but the binary search algorithm used to query it requires widespread memory accesses, causing a large number of cache misses on large datasets.ResultsHere we present Sapling, an algorithm for sequence alignment which uses a learned data model to augment the suffix array and enable faster queries. We investigate different types of data models, providing an analysis of different neural network models as well as providing an open-source aligner with a compact, practical piecewise linear model. We show that Sapling outperforms both an optimized binary search approach and multiple existing read aligners on a wide collection of genomes, including human, bacteria, and plants, speeding up the algorithm by more than a factor of two while adding less than 1% to the suffix array’s memory footprint.Availability and implementationThe source code and tutorial are available open-source athttps://github.com/mkirsche/sapling.Supplementary InformationSupplementary notes and figures are available online.
Effect of relative humidity on corrosion of Q235 carbon steel under thin electrolyte layer in simulated marine atmosphere
Authors: Song Qingqing , Wang Xudong , Pan Boyang , Wan Lei 
Published: January 2020

PurposeThe purpose of this paper is to obtain the environmental factor, which has the greatest effect on the corrosion rate of Q235 carbon steel under thin electrolyte layer, and to analyze the effect of this factor on the corrosion morphology, corrosion products and polarization process of Q235 carbon steel.Design/methodology/approachAn electrochemical device, which can be used under thin electrolyte layer is designed to measure the corrosion current in different environments. Response surface methodology (RSM) is introduced to analyze the effect of environmental factors on corrosion rate. Scanning electron microscope (SEM) and X-ray diffraction (XRD) technique are used to analyze the results. The Tafel slopes of anode and cathode in different humidity and solution are calculated by least square method.FindingsThe three environmental factors are ranked according to importance, namely, humidity, temperature and chloride ion deposition rate. In a high humidity environment, the relative content ofα-FeOOH in the corrosion product is high and the relative content ofβ-FeOOH is low. The higher the humidity, the lower the degree of anodic blockage, whereas the degree of cathodic blockage is independent of humidity. The above experiments confirm the effectiveness and efficiency of the device, indicating it can be used for the screening of corrosive environmental factors.Originality/valueIn this paper, an electrochemical device under thin film is designed, which can simulate atmospheric corrosion well. Subsequent SEM and XRD confirmed the reliability of the data measured by this device. The introduction of a scientific RSM can overcome the limitations of orthogonal experiments and more specifically and intuitively analyze the effects of environmental factors on corrosion rates.
Corporate foresight for strategic innovation management: the case of a Russian service company
Authors: Calof Jonathan , Meissner Dirk , Vishnevskiy Konstantin 
Published: January 2020

Purpose
This paper aims to provide a detailed case study of a corporate foresight for innovation (CFI) project done by the Higher School of Economics’ (HSE) (Moscow, Russia) corporate foresight (CF) unit for a large state-owned Russian service company. It demonstrates how CFI methods lead to recommendations and how these recommendations result in decisions.

Design/methodology/approach
Drawing from being part of the project team, review of the project documents and interviews, the case describes a multi-phased CFI project which incorporated several CF methods. Techniques used for the project itself included grand challenges and trend analysis, analysis of best practices through use of benchmarking and horizon scanning, interviews, expert panels, wild card and weak signals analysis, cross impact analysis, SWOT and backcasting. The project used a broad-base of secondary information, expert panels consisting of company experts and HSE CF team personnel, interviews with senior management and an extensive literature review using HSE’s propriety iFORA system.

Findings
In all 17 CFI recommendation and over 100 implementation recommendations were made; 94 per cent of the CFI recommendations were accepted with most implemented at the time this case was written. The case also identifies five enabling factors that collectively both helped the CFI project and led to a high rate of recommendation acceptance and one factor that hindered CFI project success.

Practical implications
The case study provides detailed information and insight that can help others in conducting CF for innovation projects and establishes a link between CF methods and innovation-based recommendations and subsequent decisions.

Originality/value
In-depth case studies that show academe and practitioners how CFI leads to recommendations and is linked to subsequent decisions have been identified as a gap in the literature. This paper therefore seeks to address this need by presenting a detailed CF case for a corporate innovation project.
Choice of the regularization parameter for the Cauchy problem for the Laplace equation
Authors: Joachimiak Magda 
Published: January 2020

PurposeIn this paper, the Cauchy-type problem for the Laplace equation was solved in the rectangular domain with the use of the Chebyshev polynomials. The purpose of this paper is to present an optimal choice of the regularization parameter for the inverse problem, which allows determining the stable distribution of temperature on one of the boundaries of the rectangle domain with the required accuracy.Design/methodology/approachThe Cauchy-type problem is ill-posed numerically, therefore, it has been regularized with the use of the modified Tikhonov and Tikhonov–Philips regularization. The influence of the regularization parameter choice on the solution was investigated. To choose the regularization parameter, the Morozov principle, the minimum of energy integral criterion and the L-curve method were applied.FindingsNumerical examples for the function with singularities outside the domain were solved in this paper. The values of results change significantly within the calculation domain. Next, results of the sought temperature distributions, obtained with the use of different methods of choosing the regularization parameter, were compared. Methods of choosing the regularization parameter were evaluated by the normNmax.Practical implicationsCalculation model described in this paper can be applied to determine temperature distribution on the boundary of the heated wall of, for instance, a boiler or a body of the turbine, that is, everywhere the temperature measurement is impossible to be performed on a part of the boundary.Originality/valueThe paper presents a new method for solving the inverse Cauchy problem with the use of the Chebyshev polynomials. The choice of the regularization parameter was analyzed to obtain a solution with the lowest possible sensitivity to input data disturbances.
Appraising conjugate heat transfer, heatlines visualization and entropy generation of Ag-MgO/H2O hybrid nanofluid in a partitioned medium
Authors: Ferhi Mokhtar , Djebali Ridha 
Published: January 2020

Purpose
This paper aims to perform the lattice Boltzmann simulation of conjugate natural convection heat transfer, heat flow visualization via heatlines approach and entropy generation in a partitioned medium filled with Ag-MgO (15-85%)/water.

Design/methodology/approach
The lattice Boltzmann method (LBM) is used to predict the dynamic and thermal behaviors. Experimental correlations for dynamic viscosity and thermal conductivity versus solid volume fraction are used. The study is conducted for the ranges of Rayleigh number 103 ≤ Ra ≤ 106, the partitioner thickness 0.01 ≤ δ ≤ 0.9, its position 0.15 ≤ Xs ≤ 0.85 and the hybrid nano-suspensions volume fraction 0% ≤ ϕ ≤ 2%.

Findings
The effects of varying of controlling parameters on the convective flow patterns, temperature contours, heat transfers, the heatlines and the entropy generation are presented. It has been found that the maximum rate of heat transfer enhancement occurs for low Ra numbers (103) and is close to 13.52%. The solid thickness d and its horizontal position Xs have a substantial influence on the heat transfer rate, flow structure, heatline, total entropy generation and Bejan number. Besides, the maximum heat transfer is detected for high Ra and δ ≈ 1 and the percentage of augmentation is equal to 65.55% for ϕ = 2%. According to the horizontal position, the heat transfer remains invariant for Ra = 103 and takes a maximum value near the active walls for Ra ≥ 104. The total entropy generation increases with Ra and decreases with ϕ for Ra = 106. The increase of ϕ from 0 to 2% leads to a reduction in close to 40.76%. For this value of Ra, the entropy is the maximum for δ = 0.4 and Xs = 0.35 and Xs = 0.65%. Moreover, as the Ra increases the Bejan number undergoes a decrease. The Bejan number is the maximum for Ra = 103 independently to δ and Xs. The superior thermal performance manifests at low Ra and high value of δ independently to the positions of the conducting body.

Originality/value
The originality of this paper is to analyze the hybrid nano-additive effects on the two-dimensional conjugate natural convection in a partitioned medium using the LBM. The experimental correlations used for the effective thermal conductivity and dynamic viscosity give credibility to our study. Different approaches such as heatlines and entropy generation are used.
Analysis of factors influencing AM application in food sector using ISM
Authors: Palaniappan Arun , Vinodh S. , Ranganathan Rajesh 
Published: January 2020

PurposeThe purpose of this paper is to report the analysis of factors influencing additive manufacturing (AM) application in the food domain.Design/methodology/approachBased on literature review, 16 factors are being considered in the study. Interpretive structural modelling is used as a modelling approach. The derived structural model indicates the dominant factors. Matriced’ impacts croises-multipication applique and classment (cross-impact matrix multiplication applied to classification) (MICMAC) analysis is being done to group the factors.FindingsBased on the study, it has been found that raw material usage, the shelf life of food, demand for the food and accuracy are dominant factors. MICMAC analysis indicated that number of driving, dependent and linkage factors are 6, 4 and 4, respectively.Research limitations/implicationsIn the present study, 16 factors are being considered. In future, additional factors could be considered to deal with advancements in the food domain.Practical implicationsThe study has been executed in discussion with practitioners in AM, and hence derived inferences have practical validity. Food making has become more agile with 3D printer and has become sensitive to customer demand.Social implicationsSocial implications are primarily highlighted by the aspect of controlling the exact amount of nutrients corresponding to the application of food. In certain commercial applications, people can customize their shape and ingredients to be injected into the food.Originality/valueThe development of a model for the analysis of factors influencing AM in the food domain is the original contribution of the authors.
Multigenerational exposure to elevated temperatures leads to a reduction in standard metabolic rate in the wild
Authors: Pilakouta Natalie , Killen Shaun S. , Kristjánsson Bjarni K. , Skúlason Skúli , Lindström Jan , Metcalfe Neil B. , Parsons Kevin J. 
Published: January 2020

Abstract

In light of global climate change, there is a pressing need to understand and predict the capacity of populations to respond to rising temperatures. Metabolic rate is a key trait that is likely to influence the ability to cope with climate change. Yet, empirical and theoretical work on metabolic rate responses to temperature changes has so far produced mixed results and conflicting predictions.

Our study addresses this issue using a novel approach of comparing fish populations in geothermally warmed lakes and adjacent ambient‐temperature lakes in Iceland. This unique ‘natural experiment’ provides repeated and independent examples of populations experiencing contrasting thermal environments for many generations over a small geographic scale, thereby avoiding the confounding factors associated with latitudinal or elevational comparisons. Using Icelandic sticklebacks from three warm and three cold habitats, we measured individual metabolic rates across a range of acclimation temperatures to obtain reaction norms for each population.

We found a general pattern for a lower standard metabolic rate (SMR) in sticklebacks from warm habitats when measured at a common temperature, as predicted by Krogh's rule. Metabolic rate differences between warm‐ and cold‐habitat sticklebacks were more pronounced at more extreme acclimation temperatures, suggesting the release of cryptic genetic variation upon exposure to novel conditions, which can reveal hidden evolutionary potential. We also found a stronger divergence in metabolic rate between thermal habitats in allopatry than sympatry, indicating that gene flow may constrain physiological adaptation when dispersal between warm and cold habitats is possible.

In sum, our study suggests that fish may diverge toward a lower SMR in a warming world, but this might depend on connectivity and gene flow between different thermal habitats.

A free Plain Language Summary can be found within the Supporting Information of this article.
Consumption of red maple in anticipation of beech mast‐seeding drives reproduction in eastern chipmunks
Authors: Tissier Mathilde L. , Réale Denis , Garant Dany , Bergeron Patrick 
Published: January 2020

Abstract

Understanding the determinants of reproduction is a central question in evolutionary ecology. In pulsed‐resource environments, the reproduction and population dynamics of seed consumers are driven by pulsed production of seeds by trees or mast‐seeding. In Southern Québec, eastern chipmunks Tamias striatus exclusively reproduce during the summer before and the spring after a mast‐seeding event of American beech. They thus seem to anticipate beech mast by reproducing during early summer, so that juveniles can emerge at the time of maximum beechnut abundance during late summer.

However, the cues allowing chipmunks to anticipate beech mast remain unknown, and the existence of the anticipation process itself has been questioned. To tackle those issues, we investigated the links between the nutritional ecology and reproduction of adult chipmunks and compared their spring diet in mast‐ versus post‐mast years.

We monitored female reproductive status (N = 446), analysed cheek pouch contents at capture (n = 3,761 captures) and recorded seed production by deciduous trees on three different sites in Mont‐Sutton from 2006 to 2018.

Results revealed a systematic shift in chipmunk diet towards red maple seeds in springs preceding a beech mast, with red maple seeds composing more than 77% of chipmunk diet. However, red maple consumption was unrelated to red maple production, but was related to beech seed production in the upcoming fall. We also found that red maple consumption best predicted the proportion of females in summer oestrus.

Our results confirm that chipmunks anticipate beech mast‐seeding and highlight a key role of red maple consumption in that anticipation. Results also suggest that red maple seeds may contain nutrients or secondary plant components essential to sustain or trigger the summer reproduction in chipmunks, which allow them to remain synchronized with pulsed productions of both red maple and beech and improve their fitness.
Combining species distribution models and value of information analysis for spatial allocation of conservation resources
Authors: Raymond Calla V. , McCune Jenny L. , Rosner‐Katz Hanna , Chadès Iadine , Schuster Richard , Gilbert Benjamin , Bennett Joseph R. 
Published: January 2020

AbstractManagers often have incomplete information to make decisions about threatened species management, and lack the time or funding needed to obtain complete information. Value of information (VOI) analysis can assist managers in deciding whether to manage using current information or monitor to reduce uncertainty before managing. However, VOI analysis has not yet been applied to spatial allocation of monitoring resources across a landscape.Here, we demonstrate how to make the best use of data from species distribution models (SDMs) and VOI analysis to assess the value of land protection decisions for single and multiple‐species objectives across a heterogeneous landscape. Our method determines the situations where one should monitor before protecting the land, and those where one should act based on current incomplete information. Further, we prioritize land planning units based on cost‐effectiveness (expected number of occurrences protected per dollar spent) and identify properties to target for monitoring or immediate conservation.In a single species case study, we found that the optimal decision was to act based on current information when the prior probability of detecting an occurrence in a survey was low. When probability of detection was high, it was most effective to monitor the majority of units. In a multi‐species case study, monitoring was only optimal in 50% of cases, due to high inferred probability of at least one occurrence of a threatened species in many units. When compared to a simulation where units were monitored by default, using VOI to determine which units were monitored or prioritized for immediate conservation led to an increase in the expected number of occurrences protected.Synthesis and applications. Using a combination of species distribution models and value of information analysis can assist managers in efficiently distributing limited resources for protected area allocation. Our results suggest that if managers can use value of information to monitor more efficiently, it can lead to protecting a greater number of threatened species occurrences.
A newly recorded Rickettsia of the Torix group is a recent intruder and an endosymbiont in the whitefly Bemisia tabaci
Authors: Wang Hua‐Ling , Lei Teng , Wang Xiao‐Wei , Maruthi M. N. , Zhu Dan‐Tong , Cameron Stephen L. , Rao Qiong , Shan Hong‐Wei , Colvin John , Liu Yin‐Quan , Liu Shu‐Sheng 
Published: January 2020

SummaryThe bacterium Rickettsia is found widely in phytophagous insects and often exerts profound effects on the phenotype and fitness of its hosts. Here, we decrypt a new, independent, phylogenetically ancient Torix Rickettsia endosymbiont found constantly in a laboratory line of an economically important insect Asia II 7, a putative species of the Bemisia tabaci whitefly complex (Hemiptera: Aleyrodidae), and occasionally in field whitefly populations. This new Rickettsia distributes throughout the body of its whitefly host. Genetically, compared to Rickettsia_bellii_MEAM1 found earlier in whiteflies, the new Rickettsia species has more gene families and pathways, which may be important factors in shaping specific symbiotic relationships. We propose the name ‘Candidatus Rickettsia_Torix_Bemisia_tabaci (RiTBt)’ for this new endosymbiont associated with whiteflies. Comparative genomic analyses indicate that RiTBi may be a relatively recent intruder in whiteflies given its low abundance in the field and relatively larger genome compared to Rickettsia_bellii_MEAM1.
The Base Rate Study: Developing Base Rates for Risk Factors and Indicators for Engagement in Violent Extremism
Authors: Clemmow Caitlin , Schumann Sandy , Salman Nadine L. , Gill Paul 
Published: January 2020

AbstractImprovements have been made in identifying the prevalence of risk factors/indicators for violent extremism. A consistent problem is the lack of base rates. How to develop base rates is of equal concern. This study has two aims: (i) compare two methods for developing base rates; the Unmatched Count Technique (UCT) and direct questioning, (ii) generate base rates in a general population sample and compare these to a sample of lone‐actor terrorists (n = 125). We surveyed 2108 subjects from the general population. Participants were recruited from an online access panel and randomly assigned to one of three conditions; direct survey, control, or UCT. Survey items were based on a lone‐actor terrorist codebook developed from the wider literature. Direct questioning was more suitable under our study conditions where UCT resulted in deflation effects. Comparing the base rates identified a number of significant differences: (i) lone‐actor terrorists demonstrated propensity indicators related to a cognitive susceptibility, and a crime‐ and/or violence‐supportive morality more often; the general sample demonstrated protective factors more often, (ii) lone‐actor terrorists demonstrated situational indicators related to a crime‐ and/or violence‐supportive morality more often, whereas the general sample experienced situational stressors more often, (iii) lone‐actor terrorists demonstrated indicators related to exposure to extremism more often. Results suggest there are measurable differences in the prevalence of risk factors between lone‐actor terrorists and the general population. However, no single factor “predicts” violent extremism. This bears implications for our understanding of the interrelation of risk and protective factors, and for the risk assessment of violent extremism.