bluuebunny/crossref_metadata_2025_split huggingface dataset:
Area collapse algorithm computing new curve of 2D geometric objects
Authors: Buczek Michał Mateusz 
Published: March 2018

Abstract
The processing of cartographic data demands human involvement. Up-to-date algorithms try to automate a part of this process. The goal is to obtain a digital model, or additional information about shape and topology of input geometric objects. A topological skeleton is one of the most important tools in the branch of science called shape analysis. It represents topological and geometrical characteristics of input data. Its plot depends on using algorithms such as medial axis, skeletonization, erosion, thinning, area collapse and many others. Area collapse, also known as dimension change, replaces input data with lower-dimensional geometric objects like, for example, a polygon with a polygonal chain, a line segment with a point.
The goal of this paper is to introduce a new algorithm for the automatic calculation of polygonal chains representing a 2D polygon. The output is entirely contained within the area of the input polygon, and it has a linear plot without branches. The computational process is automatic and repeatable. The requirements of input data are discussed. The author analyzes results based on the method of computing ends of output polygonal chains. Additional methods to improve results are explored. The algorithm was tested on real-world cartographic data received from BDOT/GESUT databases, and on point clouds from laser scanning. An implementation for computing hatching of embankment is described.
Accuracy assessment of TanDEM-X IDEM using airborne LiDAR on the area of Poland
Authors: Woroszkiewicz Małgorzata , Ewiak Ireneusz , Lulkowska Paulina 
Published: March 2018

Abstract
The TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-X) mission launched in 2010 is another programme – after the Shuttle Radar Topography Mission (SRTM) in 2000 – that uses space-borne radar interferometry to build a global digital surface model. This article presents the accuracy assessment of the TanDEM-X intermediate Digital Elevation Model (IDEM) provided by the German Aerospace Center (DLR) under the project “Accuracy assessment of a Digital Elevation Model based on TanDEM-X data” for the southwestern territory of Poland. The study area included: open terrain, urban terrain and forested terrain. Based on a set of 17,498 reference points acquired by airborne laser scanning, the mean errors of average heights and standard deviations were calculated for areas with a terrain slope below 2 degrees, between 2 and 6 degrees and above 6 degrees. The absolute accuracy of the IDEM data for the analysed area, expressed as a root mean square error (Total RMSE), was 0.77 m.
Geovisualisation as a process of creating complementary visualisations: static two-dimensional, surface three-dimensional, and interactive
Authors: Horbiński Tymoteusz , Medyńska-Gulij Beata 
Published: March 2018

Abstract
In the following paper, geovisualisation will be applied to one spatial phenomenon and understood as a process of creating complementary visualisations: static two-dimensional, surface three-dimensional, and interactive. The central challenge that the researchers faced was to find a method of presenting the phenomenon in a multi-faceted way. The main objective of the four-stage study was to show the capacity of the contemporary software for presenting geographical space from various perspectives while maintaining the standards of cartographic presentation and making sure that the form remains attractive for the user. The correctness, effectiveness, and usefulness of the proposed approach was analysed on the basis of a geovisualisation of natural aggregate extraction in the Gniezno district in the years 2005–2015. For each of the three visualisations, the researchers planned a different range of information, different forms of graphic and cartographic presentation, different use and function, but as far as possible the same accessible databases and the same free technologies. On the basis of the final publication, the researchers pointed out the advantages of the proposed workflow and the correctness of the detailed flowchart.
Design-Based Estimation with Record-Linked Administrative Files and a Clerical Review Sample
Authors: Dasylva Abel 
Published: March 2018

Abstract
This article looks at the estimation of an association parameter between two variables in a finite population, when the variables are separately recorded in two population registers that are also imperfectly linked. The main problem is the occurrence of linkage errors that include bad links and missing links. A methodology is proposed when clerical-reviews may reliably determine the match status of a record-pair, for example using names, demographic and address information. It features clerical-reviews on a probability sample of pairs and regression estimators that are assisted by a statistical model of comparison outcomes in a pair. Like other regression estimators, this estimator is design-consistent regardless of the model validity. It is also more efficient when the model holds.
Administrative Data Quality: Investigating Record-Level Address Accuracy in the Northern Ireland Health Register
Authors: Foley Brian , Shuttleworth Ian , Martin David 
Published: March 2018

Abstract
Many national statistical institutes (NSIs) are seeking to supplement or replace their traditional population census with a methodology underpinned by administrative sources. Health service register data are key in this regard owing to their high population coverage; it is therefore important to improve understanding of data quality in this administrative source. This study investigated the factors associated with record-level address data mismatch between the Northern Ireland (NI) Health Card Registration System (HCRS) and the 2011 Census, using the NI Longitudinal Study (NILS). Address information in the form of anonymised Unique Property Reference Number (XUPRN) was available for circa 334,000 NILS members with census returns in 2001 and 2011, which provided a benchmark to assess XUPRN accuracy in their linked HCRS record for comparable time points. Multinomial logistic regression revealed a significantly greater likelihood of address mismatch in the HCRS for: males; young adults; individuals with no limiting long-term illness; migrants in the year prior to each census; and residents of communal establishments. Identification of population groups affected by poor quality address information in administrative sources can assist NSIs with the development and implementation of methodological improvements to ensure that official population statistics generated from these sources are fit for purpose.
Calibration Weighting for Nonresponse with Proxy Frame Variables (So that Unit Nonresponse Can Be Not Missing at Random)
Authors: Kott Phillip S. , Liao Dan 
Published: March 2018

Abstract
When adjusting for unit nonresponse in a survey, it is common to assume that the response/nonresponse mechanism is a function of variables known either for the entire sample before unit response or at the aggregate level for the frame or population. Often, however, some of the variables governing the response/nonresponse mechanism can only be proxied by variables on the frame while they are measured (more) accurately on the survey itself. For example, an address-based sampling frame may contain area-level estimates for the median annual income and the fraction home ownership in a Census block group, while a household’s annual income category and ownership status are reported on the survey itself for the housing units responding to the survey. A relatively new calibration-weighting technique allows a statistician to calibrate the sample using proxy variables while assuming the response/ nonresponse mechanism is a function of the analogous survey variables. We will demonstrate how this can be done with data from the Residential Energy Consumption Survey National Pilot, a nationally representative web-and-mail survey of American households sponsored by the U.S. Energy Information Administration.
Using Social Network Information for Survey Estimation
Authors: Suesse Thomas , Chambers Ray 
Published: March 2018

Abstract
Model-based and model-assisted methods of survey estimation aim to improve the precision of estimators of the population total or mean relative to methods based on the nonparametric Horvitz-Thompson estimator. These methods often use a linear regression model defined in terms of auxiliary variables whose values are assumed known for all population units. Information on networks represents another form of auxiliary information that might increase the precision of these estimators, particularly if it is reasonable to assume that networked population units have similar values of the survey variable. Linear models that use networks as a source of auxiliary information include autocorrelation, disturbance, and contextual models. In this article we focus on social networks, and investigate how much of the population structure of the network needs to be known for estimation methods based on these models to be useful. In particular, we use simulation to compare the performance of the best linear unbiased predictor under a model that ignores the network with model-based estimators that incorporate network information. Our results show that incorporating network information via a contextual model seems to be the most appropriate approach. We also show that one does not need to know the full population network, but that knowledge of the partial network linking the sampled population units to the non-sampled population units is necessary. Finally, we also provide an estimator for the mean-squared error to make an informed decision about using the contextual information, as well as the results showing that this adaptive strategy leads to higher precision.
An Overview of Population Size Estimation where Linking Registers Results in Incomplete Covariates, with an Application to Mode of Transport of Serious Road Casualties
Authors: Heijden Peter G.M. van der , Smith Paul A. , Cruyff Maarten , Bakker Bart 
Published: March 2018

Abstract
We consider the linkage of two or more registers in the situation where the registers do not cover the whole target population, and relevant categorical auxiliary variables (unique to one of the registers; although different variables could be present on each register) are available in addition to the usual matching variable(s). The linked registers therefore do not contain full information on either the observations (often individuals) or the variables. By treating this as a missing data problem it is possible to construct a linked data set, adjusted to estimate the part of the population missed by both registers, and containing completed covariate information for all the registers. This is achieved using an Expectation-Maximization (EM)-algorithm. We elucidate the properties of this approach where the model is appropriate and in situations corresponding with real applications in official statistics, and also where the model conditions are violated. The approach is applied to data on road accidents in the Netherlands, where the cause of the accident is denoted by the police and by the hospital. Here the cause of the accident denoted by the police is considered as missing information for the statistical units only registered by the hospital, and the other way around. The method needs to be widely applied to give a better impression of the range of problems where it can be beneficial.
The roles of givenness and type of referring expression in the comprehension of word order in Russian-speaking children
Authors: Sauermann Antje , Gagarina Natalia 
Published: March 2018

AbstractComprehension of sentences in the non-canonical word order usually poses problems for preschoolers (e.g., Slobin, Dan I. and Thomas G. Bever. 1982. Children use canonical sentence schema: A crosslinguistic study of word order and inflections.Cognition12. 229–265). These problems may be modulated by information structure, such as the presence of an appropriate context licensing the non-canonical word order and the type of referring expression. We examined the impact of the given-new order, induced by a context sentence, and the type of referring expression realizing the given referent (NP vs. pronoun) on the comprehension of SVO and OVS sentences in monolingual Russian-speaking 4- to 5-year-olds and adults. Children and adults showed high comprehension accuracy for SVO and OVS sentences, with accuracy rates above 80 % for OVS sentences. Context and the type of referring expression had no effect. Compared to a similar experiment conducted in German, Russian-speaking children outperformed their German-speaking peers. This difference may result from the earlier acquisition of the case system and a stronger given-before-new preference in Russian compared to German. Our data suggest that as soon as children rely more on morphological information during processing and employ adult-like processing strategies, their offline comprehension performance depends less on contextual and information structure factors.
Toward an infrastructure for data-driven multimodal communication research
Authors: Steen Francis F. , Hougaard Anders , Joo Jungseock , Olza Inés , Cánovas Cristóbal Pagán , Pleshakova Anna , Ray Soumya , Uhrig Peter , Valenzuela Javier , Woźny Jacek , Turner Mark 
Published: March 2018

Abstract
Research into the multimodal dimensions of human communication faces a set of distinctive methodological challenges. Collecting the datasets is resource-intensive, analysis often lacks peer validation, and the absence of shared datasets makes it difficult to develop standards. External validity is hampered by small datasets, yet large datasets are intractable. Red Hen Lab spearheads an international infrastructure for data-driven multimodal communication research, facilitating an integrated cross-disciplinary workflow. Linguists, communication scholars, statisticians, and computer scientists work together to develop research questions, annotate training sets, and develop pattern discovery and machine learning tools that handle vast collections of multimodal data, beyond the dreams of previous researchers. This infrastructure makes it possible for researchers at multiple sites to work in real-time in transdisciplinary teams. We review the vision, progress, and prospects of this research consortium.
A review on modeling and control of olefin polymerization in fluidized-bed reactors
Authors: Abbasi Mohammad Reza , Shamiri Ahmad , Hussain Mohamed Azlan 
Published: March 2018

AbstractThis is a detailed review on olefin polymerization models, and the most recent process control approaches used to control these nonlinear systems are presented. Great focus has been given to the various approaches of fluidized-bed reactor (FBR) modeling. Currently, there has yet to be a single model that blends these modeling aspects together into one single formulation. In this article, the classification of models works by looking at their assumption in considering the phases inside the system. Researchers have been unraveling vast information to narrate in detail the relations between various variables that can be found in FBRs. Although it is not difficult to understand about the basics of modeling polymer properties, a gap exists for future researchers to justify in detail the phenomena and reduce the gap between model predictions and the actual data. The various controlling approaches to control these FBRs have also been reviewed and categorized depending on the method they used to control significant parameters of this nonlinear system. The progress that can be expected in this field leads to the creation of more efficient reactors and minimizing waste.
Functional MRI Responses to Passive, Active, and Observed Touch in Somatosensory and Insular Cortices of the Macaque Monkey
Authors: Sharma Saloni , Fiave Prosper A. , Nelissen Koen 
Published: March 2018

Neurophysiological data obtained in primates suggests that merely observing others' actions can modulate activity in the observer's motor cortices. In humans, it has been suggested that these multimodal vicarious responses extend well beyond the motor cortices, including somatosensory and insular brain regions, which seem to yield vicarious responses when witnessing others' actions, sensations, or emotions (Gazzola and Keysers, 2009). Despite the wealth of data with respect to shared action responses in the monkey motor system, whether the somatosensory and insular cortices also yield vicarious responses during observation of touch remains largely unknown. Using independent tactile and motor fMRI localizers, we first mapped the hand representations of two male monkeys' primary (SI) and secondary (SII) somatosensory cortices. In two subsequent visual experiments, we examined fMRI brain responses to (1) observing a conspecific's hand being touched or (2) observing a human hand grasping or mere touching an object or another human hand. Whereas functionally defined “tactile SI” and “tactile SII” showed little involvement in representing observed touch, vicarious responses for touch were found in parietal area PFG, consistent with recent observations in humans (Chan and Baker, 2015). Interestingly, a more anterior portion of SII, and posterior insular cortex, both of which responded when monkeys performed active grasping movements, also yielded visual responses during different instances of touch observation.SIGNIFICANCE STATEMENTCommon coding of one's own and others' actions, sensations, and emotions seems to be widespread in the brain. Although it is currently unclear to what extent human somatosensory cortices yield vicarious responses when observing touch, even less is known about the presence of similar vicarious responses in monkey somatosensory cortex. We therefore localized monkey somatosensory hand representations using fMRI and investigated whether these regions yield vicarious responses while observing various instances of touch. Whereas “tactile SI and SII” did not elicit responses during touch observation, a more anterior portion of SII, in addition to area PFG and posterior insular cortex, all of which responded during monkeys' own grasping movements, yielded vicarious responses during observed touch.
Kainate Receptors Inhibit Glutamate Release Via Mobilization of Endocannabinoids in Striatal Direct Pathway Spiny Projection Neurons
Authors: Marshall John J. , Xu Jian , Contractor Anis 
Published: March 2018

Kainate receptors are members of the glutamate receptor family that function by both generating ionotropic currents through an integral ion channel pore and coupling to downstream metabotropic signaling pathways. They are highly expressed in the striatum, yet their roles in regulating striatal synapses are not known. Using mice of both sexes, we demonstrate that GluK2-containing kainate receptors expressed in direct pathway spiny projection neurons (dSPNs) inhibit glutamate release at corticostriatal synapses in the dorsolateral striatum. This inhibition requires postsynaptic kainate-receptor-mediated mobilization of a retrograde endocannabinoid (eCB) signal and activation of presynaptic CB1 receptors. This pathway can be activated during repetitive 25 Hz trains of synaptic stimulation, causing short-term depression of corticostriatal synapses. This is the first study to demonstrate a role for kainate receptors in regulating eCB-mediated plasticity at the corticostriatal synapse and demonstrates an important role for these receptors in regulating basal ganglia circuits.SIGNIFICANCE STATEMENTTheGRIK2gene, encoding the GluK2 subunit of the kainate receptor, has been linked to several neuropsychiatric and neurodevelopmental disorders including obsessive compulsive disorder (OCD). Perseverative behaviors associated with OCD are known to result from pathophysiological changes in the striatum and kainate receptor knock-out mice have striatal-dependent phenotypes. However, the role of kainate receptors in striatal synapses is not known. We demonstrate that GluK2-containing kainate receptors regulate corticostriatal synapses by mobilizing endocannabinoids from direct pathway spiny projection neurons. Synaptic activation of GluK2 receptors during trains of synaptic input causes short-term synaptic depression, demonstrating a novel role for these receptors in regulating striatal circuits.
JIP1-Mediated JNK Activation Negatively Regulates Synaptic Plasticity and Spatial Memory
Authors: Morel Caroline , Sherrin Tessi , Kennedy Norman J. , Forest Kelly H. , Avcioglu Barutcu Seda , Robles Michael , Carpenter-Hyland Ezekiel , Alfulaij Naghum , Standen Claire L. , Nichols Robert A. , Benveniste Morris , Davis Roger J. , Todorovic Cedomir 
Published: March 2018

The c-Jun N-terminal kinase (JNK) signal transduction pathway is implicated in learning and memory. Here, we examined the role of JNK activation mediated by the JNK-interacting protein 1 (JIP1) scaffold protein. We compared male wild-type mice with a mouse model harboring a point mutation in theJip1gene that selectively blocks JIP1-mediated JNK activation. These male mutant mice exhibited increased NMDAR currents, increased NMDAR-mediated gene expression, and a lower threshold for induction of hippocampal long-term potentiation. The JIP1 mutant mice also displayed improved hippocampus-dependent spatial memory and enhanced associative fear conditioning. These results were confirmed using a second JIP1 mutant mouse model that suppresses JNK activity. Together, these observations establish that JIP1-mediated JNK activation contributes to the regulation of hippocampus-dependent, NMDAR-mediated synaptic plasticity and learning.SIGNIFICANCE STATEMENTThe results of this study demonstrate that c-Jun N-terminal kinase (JNK) activation induced by the JNK-interacting protein 1 (JIP1) scaffold protein negatively regulates the threshold for induction of long-term synaptic plasticity through the NMDA-type glutamate receptor. This change in plasticity threshold influences learning. Indeed, mice with defects in JIP1-mediated JNK activation display enhanced memory in hippocampus-dependent tasks, such as contextual fear conditioning and Morris water maze, indicating that JIP1-JNK constrains spatial memory. This study identifies JIP1-mediated JNK activation as a novel molecular pathway that negatively regulates NMDAR-dependent synaptic plasticity and memory.