bluuebunny/crossref_metadata_2025_split huggingface dataset:
Morphological constraints on cerebellar granule cell combinatorial diversity
Authors: Gilmer Jesse I. , Person Abigail L. 
Published: November 2017

AbstractCombinatorial expansion by the cerebellar granule cell layer (GCL) is fundamental to theories of cerebellar contributions to motor control and learning. Granule cells sample approximately four mossy fiber inputs and are thought to form a combinatorial code useful for pattern separation and learning. We constructed a spatially realistic model of the cerebellar granule cell layer and examined how GCL architecture contributes to granule cell (GrC) combinatorial diversity. We found that GrC combinatorial diversity saturates quickly as mossy fiber input diversity increases, and that this saturation is in part a consequence of short dendrites, which limit access to diverse inputs and favor dense sampling of local inputs. This local sampling also produced GrCs that were combinatorially redundant, even when input diversity was extremely high. In addition, we found that mossy fibers clustering, which is a common anatomical pattern, also led to increased redundancy of GrC input combinations. We related this redundancy to hypothesized roles of temporal expansion of GrC information encoding in service of learned timing, and show that GCL architecture produces GrC populations that support both temporal and combinatorial expansion. Finally, we used novel anatomical measurements from mice of either sex to inform modeling of sparse and filopodia-bearing mossy fibers, finding that these circuit features uniquely contribute to enhancing GrC diversification and redundancy. Our results complement information theoretic studies of granule layer structure and provide insight into the contributions of granule layer anatomical features to afferent mixing.Significance StatementCerebellar granule cells are among the simplest neurons, with tiny somata and on average just four dendrites. These characteristics, along with their dense organization, inspired influential theoretical work on the granule cell layer (GCL) as a combinatorial expander, where each granule cell represents a unique combination of inputs. Despite the centrality of these theories to cerebellar physiology, the degree of expansion supported by anatomically realistic patterns of inputs is unknown. Using modeling and anatomy, we show that realistic input patterns constrain combinatorial diversity by producing redundant combinations, which nevertheless could support temporal diversification of like-combinations, suitable for learned timing. Our study suggests a neural substrate for producing high levels of both combinatorial and temporal diversity in the GCL.
Functional Connectomics from Data: Probabilistic Graphical Models for Neuronal Network of C. elegans
Authors: Liu Hexuan , Kim Jimin , Shlizerman Eli 
Published: November 2017

AbstractWe propose a data-driven approach to represent neuronal network dynamics as a Probabilistic Graphical Model (PGM). Our approach learns the PGM structure by employing dimension reduction to network response dynamics evoked by stimuli applied to each neuron separately. The outcome model captures how stimuli propagate through the network and thus represents functional dependencies between neurons, i.e., functional connectome. The benefit of using a PGM as the functional connectome is that posterior inference can be done efficiently and circumvent the complexities in direct inference of response pathways in dynamic neuronal networks. In particular, posterior inference reveals the relations between known stimuli and downstream neurons or allows to query which stimuli are associated with downstream neurons. For validation and as an example for our approach we apply our methodology to a model ofCaenorhabiditis elegansnervous system which structure and dynamics are well-studied. From its dynamical model we collect time series of the network response and use singular value decomposition to obtain a low-dimensional projection of the time series data. We then extract dominant patterns in each data matrix to get pairwise dependency information and create a graphical model for the full somatic nervous system. The PGM enables us to obtain and verify underlying neuronal pathways dominant for known behavioral scenarios and to detect possible pathways for novel scenarios.
Processive movement of Actin by Biased Polymerization: A new paradigm of Axonal Transport
Authors: Chakrabarty Nilaj , Dubey Pankaj , Tang Yong , Ganguly Archan , Ladt Kelsey , Leterrier Christophe , Jung Peter , Roy Subhojit 
Published: November 2017

ABSTRACTClassic pulse-chase studies have shown that actin is conveyed in slow axonal transport, but the mechanistic basis for this movement is unknown. Recently, we reported that axonal actin was surprisingly dynamic, with focal assembly/dis-assembly events (“hotspots”) and elongating polymers along the axon-shaft (“trails”). Using a combination of live imaging, super-resolution microscopy, and modeling, here we explore how these axonal actin dynamics can lead to processive transport. We found abundant actin nucleation, along with a slow, anterogradely-biased flow of actin in axon-shafts. Starting with first principles of monomer/filament assembly – and incorporating imaging data – we generated a quantitative model simulating axonal hotspots and trails. Our simulations predict that the axonal actin dynamics indeed lead to an anterogradely-biased flow of the population, at rates consistent with slow transport. Collectively, the data point to a surprising scenario where local assembly and biased polymerization generate the slow axonal transport of actin. This mechanism is distinct from polymer-sliding, and seems well suited to convey highly dynamic cytoskeletal cargoes.AcknowledgementsThis work was supported by an NIH grant to SR (R01NS075233). The authors thank Stephanie Gupton (UNC) for the Mena/Vasp constructs.
REMAP: An online remote sensing application for land cover classification and monitoring
Authors: Murray Nicholas J. , Keith David A. , Simpson Daniel , Wilshire John H. , Lucas Richard M. 
Published: November 2017

ABSTRACTRecent assessments of progress towards global conservation targets have revealed a paucity of indicators suitable for assessing the changing state of ecosystems. Moreover, land managers and planners are often unable to gain timely access to maps they need to support their routine decision-making. This deficiency is partly due to a lack of suitable data on ecosystem change, driven mostly by the considerable technical expertise needed to make ecosystem maps from remote sensing data.We have developed a free and open-access online remote sensing and environmental modelling application, REMAP (the remote ecosystem monitoring and assessment pipeline;https://remap-app.org) that enables volunteers, managers, and scientists with little or no experience in remote sensing to develop high-resolution classified maps of land cover and land use change over time.REMAP utilizes the geospatial data storage and analysis capacity of the Google Earth Engine, and requires only spatially resolved training data that define map classes of interest (e.g., ecosystem types). The training data, which can be uploaded or annotated interactively within REMAP, are used in a random forest classification of up to 13 publicly available predictor datasets to assign all pixels in a focal region to map classes. Predictor datasets available in REMAP represent topographic (e.g. slope, elevation), spectral (Landsat Archive image composites) and climatic variables (precipitation, temperature) that can inform on the distribution of ecosystems and land cover classes.The ability of REMAP to develop and export high-quality classified maps in a very short (<10 minute) time frame represents a considerable advance towards globally accessible and free application of remote sensing technology. By enabling access to data and simplifying remote sensing classifications, REMAP can catalyse the monitoring of land use and change to support environmental conservation, including developing inventories of biodiversity, identifying hotspots of ecosystem diversity, ecosystem-based spatial conservation planning, mapping ecosystem loss at local scales, and supporting environmental education initiatives.
Prediction of Epileptic Seizures based on Mean Phase Coherence
Authors: Aggarwal Gorish , Gandhi Tapan K. 
Published: November 2017

AbstractAround 1-2 % of the world's population suffers from epilepsy and 20 % of that vulnerable mass can't be cured through surgery or medicine. Epileptic seizures often occur unpredictably and may cause serious damage to the patient in adverse situations, for e.g. getting a seizure while driving or crossing a road can be fatal. In such a scenario, a reliable mechanism to predict the onset of seizure beforehand is much desirable. In this study, A reliable real-time technique for prediction of epileptic seizures is presented. Mean Phase Coherence (MPC), as a measure of phase synchronization, is used to predict impending seizures in a multi-channel EEG data. It was found that during the pre-ictal stages, MPC values and thus phase synchronization between various channels was found to drop significantly below the level in a non-ictal EEG signal. The range of the prediction horizon for seizures varied from 4-10 mins and prediction of impending seizure attack is possible for 8 out of 10 test cases.
Evaluation of TRPM8 and TRPA1 participation in dental pulp sensitivity to cold stimulation
Authors: Michot Benoit , Lee Caroline , Podborits Eugene , Gibbs Jennifer L. 
Published: November 2017

AbstractSensory neurons innervating the dental pulp have unique morphological and functional characteristics compared to neurons innervating other tissues. Stimulation of dental pulp afferents whatever the modality or intensity of the stimulus, even light mechanical stimulation that would not activate nociceptors in other tissues, produces an intense pain. These specific sensory characteristics could involve receptors of the Transient Receptor Potential channels (TRP) family. In this study, we evaluated 1) the expression of TRPA1 and TRPM8 receptors in trigeminal ganglion neurons innervating the dental pulp compared to sensory neurons innervating the oral mucosa or the skin of the face, and 2) the involvement of these receptors in dental pulp sensitivity to cold stimulation. We showed a similar expression of TRPM8 and CGRP in sensory neurons innervating the dental pulp, the skin or the buccal mucosa. On the contrary, TRPA1 was expressed in a higher proportion of neurons innervating the mucosa (43%) than in neurons innervating the dental pulp (19%) or the skin (24%). Moreover, neurons innervating the dental pulp had a higher proportion of large neurons (24%) compared to neurons innervating the skin (8%) or the mucosa (10%). The evaluation of trigeminal ganglion neuron sensitivity to TRPM8 agonist, TRPA1 agonist and cold stimulation, showed that a significant proportion of neurons innervating the skin (10%) or the mucosa (37%) were sensitive to cold stimulation but insensitive to TRPM8 and TRPA1 activation. Similarly, the application of a cold stimulation on the tooth induced an overexpression of cFos in the trigeminal nucleus that was not prevented by administration of a TRPA1 antagonist or the genetic deletion of TRPM8. However, the pretreatment with the local anesthetic carbocaine abolish the cold-induced cFos overexpression. In conclusion, the unique sensory characteristics of the dental pulp would be independent to TRPA1 and TRPM8 expression and functionality.
Genomic LOCI Modulating Retinal Ganglion Cell Death Following Elevated IOP in the Mouse
Authors: Struebing Felix L. , King Rebecca , Li Ying , Bailey Jessica N. Cooke ,   NEIGHBORHOOD consortium, Wiggs Janey L. , Geisert Eldon E. 
Published: November 2017

AbstractThe present study was designed to identify genomic loci modulating the susceptibility of retinal ganglion cells (RGC) to elevated intraocular pressure (IOP) in the BXD recombinant inbred mouse strain set. IOP was elevated by injecting magnetic microspheres into the anterior chamber and blocking the trabecular meshwork using a handheld magnet to impede drainage. The IOP was then measured over the next 21 days. Only animals with IOP greater than 25 mmHg for two consecutive days or an IOP above 30 mmHg on a single day after microsphere-injection were used in this study. On day 21, mice were sacrificed and the optic nerve was processed for histology. Axons were counted for both the injected and the control eye in 49 BXD strains, totaling 181 normal counts and 191 counts associated with elevated IOP. The axon loss for each strain was calculated and the data were entered into genenetwork.org. The average number of normal axons in the optic nerve across all strains was 54,788 ± 16% (SD), which dropped to 49,545 ± 20% in animals with artificially elevated IOP. Interval mapping demonstrated a relatively similar genome-wide map for both conditions with a suggestive Quantitative Trait Locus (QTL) on proximal Chromosome 3. When the relative axon loss was used to generate a genome-wide interval map, we identified one significant QTL (p<0.05) on Chromosome 18 between 53.6 and 57 Mb. Within this region, the best candidate gene for modulating axon loss wasAldh7a1. Immunohistochemistry demonstrated ALDH7A1 expression in mouse RGCs.ALDH7A1variants were not significantly associated with glaucoma in the NEIGHBORHOOD GWAS dataset, but this enzyme was identified as part of the butanoate pathway previously associated with glaucoma risk. Our results suggest that genomic background influences susceptibility to RGC degeneration and death in an inducible glaucoma model.
An opportunity space odyssey: historical exploration of demand-driven entrepreneurial innovation
Authors: Hunt Richard A. 
Published: November 2017

Purpose
One of the crucial questions confronting strategy and entrepreneurship scholars continues to be: where do new industry sectors come from? Extant literature suffers from a supply-side “skew” that focuses unduly on the role of heroic figures and celebrity CEOs, at the expense of demand-side considerations. In response, the purpose of this paper is to examine societal demand for entrepreneurial innovations. Employing historical data spanning nearly a century, the author assess more completely the role of latent demand-side signaling in driving the quantity and diversity of entrepreneurial innovation.

Design/methodology/approach
Applying the methods of historical econometrics, this study employs historical artifacts and cliometric models to analyze textual data in drawn from three distinctive sources: Popular Science Monthly magazine, from its founding in 1872 to 1969; periodicals, newsletters, club minutes, films and radio transcripts from the Science Society, from 1921 to 1969; and programs and news accounts from the US National High School Science Fair, from 1950 to 1969. In total, 2,084 documents containing 33,720 articles and advertisements were coded for content related to pure science, applied science and commercialized science.

Findings
Three key findings are revealed: vast opportunity spaces often exist prior to being occupied by individuals and firms; societal preferences play a vital role in determining the quantity and diversity of entrepreneurial activity; and entrepreneurs who are responsive to latent demand-side signals are likely to experience greater commercial success.

Research limitations/implications
This study intentionally draws data from three markedly different textual sources. The painstaking process of triangulation reveals heretofore unobserved latencies that invite fresh perspectives on innovation discovery and diffusion.

Originality/value
This paper constitutes the most panoramic investigation to-date of the influence wielded by latent demand-side forces in the discovery and commercialization of innovation.
Psychometric evaluation of need-based quality of work life scale in an Indian sample
Authors: Rastogi Mansi , Rangnekar Santosh , Rastogi Renu 
Published: November 2017

Purpose
The purpose of this paper is to examine the psychometric properties of the need-based measure of quality of work life (QWL) in the Indian context.

Design/methodology/approach
The need-based QWL instrument was validated using the 380 samples collected from public and private sector employees working in India. The data were obtained via self-administered structured questionnaires. The data were examined conducting exploratory and confirmatory factor analyses with the help of SPSS AMOS (version 21).

Findings
The two-factor model confirmed the superiority over the seven-factor model in the Indian context. The results are strongly supported by the extant literature in organizational behavior domain.

Originality/value
Despite being the second highest populated country and one of the largest skill labor facilitator to the work economy, India lags behind in well-being-related studies as compared to its Western and Asian counterparts. This study has validated and simplified the complex need-based QWL measure in the Indian context. This is easily understandable that QWL instrument is believed to encourage the well-being research in India.
Predicting post-training implementation of a parenting intervention
Authors: Kerns Suzanne E.U. , McCormick Erin , Negrete Andrea , Carey Cathea , Haaland Wren , Waller Scott 
Published: November 2017

Purpose
While evidence-based parenting interventions (EBPIs) are proven effective at addressing numerous emotional and behavioral health challenges for children and youth, and reduce rates of child maltreatment, they are often not well implemented in the real-world settings. Even with the state-of-the art training, many practitioners do not deliver the intervention, or do so at a reduced capacity. The purpose of this paper is to examine system-contextual implementation factors that predict timely initiation of use of an EBPI (i.e. within the first six months following training). A secondary purpose is to document additional impacts of training.

Design/methodology/approach
Repeated measures were used to collect predictors and the dependent variable. The relationship between participant characteristics and use of the Triple P program was estimated using exact logistic regression.

Findings
The results from 37 practitioners across three communities indicated approximately 54 percent delivered the intervention with at least one family within the first six months following training. Practitioner self-efficacy immediately following training and general attitudes toward evidence-based practices were the most significant predictors of timely use of the model. The vast majority of practitioners, regardless of implementation status, generalized learning from the training to other aspects of their work.

Originality/value
Prospective examination of the predictive value of implementation factors helps to refine targeted approaches to support implementation.
Understanding the effects of task and topical knowledge in the evaluation of websites as information patch
Authors: Lee Helena , Pang Natalie 
Published: November 2017

PurposeThe purpose of this paper is to examine the role of task and user’s topic familiarity in the evaluation of information patch (websites).Design/methodology/approachAn experimental study was conducted in a computer laboratory to examine users’ information seeking and foraging behaviour. In total, 160 university students participated in the research. Two types of task instructions, specifically defined and non-specifically defined (general) task types were administered. Mixed methods approach involving both quantitative and qualitative thematic coding were adopted, from the data of the questionnaire surveys and post-experiment interviews.FindingsIn the context of task attributes, users who conducted information seeking task with specifically defined instructions, as compared to the non-specifically defined instructions, demonstrated stricter credibility evaluations. Evidence demonstrated the link between topical knowledge and credibility perception. Users with topical knowledge applied critical credibility assessments than users without topical knowledge. Furthermore, the evidential results supported that the level of difficulty and knowledge of the topic or subject matter associated with users’ credibility evaluations. Users who have lesser or no subject knowledge and who experienced difficulty in the information search tended to be less diagnostic in their appraisal of the information patch (website or webpages). Users equipped with topical knowledge and who encountered less difficulty in the search, exhibited higher expectation and evaluative criteria of the information patch.Research limitations/implicationsThe constraints of time in the lab experiment, carried out in the presence of and under the observation of the researcher, may affect users’ information seeking behaviour. It would be beneficial to consider users’ information search gratifications and motivations in studying information evaluations and foraging patterns. There is scope to investigate users’ proficiency such as expert or novice, and individual learning styles in assessing information credibility.Practical implicationsPast studies on information evaluation, specifically credibility is often associated with users’ characteristics, source, or contents. This study sheds light on the context of task type, task difficulty and topical knowledge in affecting users’ information judgement.Originality/valueOne of the scarce studies in relating task orientation, task difficulty and topical knowledge to information evaluations.
Making choices: developing digital research frameworks for information management
Authors: Burke Maria 
Published: November 2017

Purpose
The purpose of this paper is to suggest a digital research framework that can be applied to many of the areas that encompass the discipline of information management.

Design/methodology/approach
This communication proposes a new “Triple A” framework that allows the researcher to progress digital ideas by asking a series of staged questions. This is a progressive model consisting of three stages of acquaintance, adaption and application bounded by three major influencing issues of culture, communication and context. The Triple A framework is aimed to be flexible to apply to most styles of research yet robust enough to offer useful insights.

Findings
The model devised will assist (information management) researchers with choices of research approaches. It may be that early career researchers or those undertaking a postgraduate research will find this framework especially helpful to clarify thoughts and direction. The model aims to be useful and, whilst no doubt will be built on in future research, it is offered as foundation, an initial starting point, as those who work and study in information management fields endeavor to make new choices in our digitally managed information world.

Originality/value
The originality and value of this work is the proposition of a new model that will allow researchers to impose structure on ideas and encourage the viewing of work from a multi-disciplinary perspective within the growing and evolving digital areas.