bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using natural language processing and machine learning to classify health literacy from secure messages: The ECLIPPSE study
Authors: Balyan Renu , Crossley Scott A. , Brown William , Karter Andrew J. , McNamara Danielle S. , Liu Jennifer Y. , Lyles Courtney R. , Schillinger Dean 
Published: September 2018

AbstractLimited health literacy can be a barrier to healthcare delivery, but widespread classification of patient health literacy is challenging. We applied natural language processing and machine learning on a large sample of 283,216 secure messages sent from 6,941 patients to their clinicians for this study to develop and validate literacy profiles as indicators of patients’ health literacy. All patients were participants in Kaiser Permanente Northern California’s DISTANCE Study. We created three literacy profiles, comparing performance of each literacy profile against a gold standard of patient self-report. We also analyzed associations between the literacy profiles and patient demographics, health outcomes and healthcare utilization. T-tests were used for numeric data such as A1C, Charlson comorbidity index and healthcare utilization rates, and chi-square tests for categorical data such as sex, race, continuous medication gaps and severe hypoglycemia. Literacy profiles varied in their test characteristics, with C-statistics ranging from 0.61-0.74. Relationships between literacy profiles and health outcomes revealed patterns consistent with previous health literacy research: patients identified via literacy profiles as having limited health literacy were older and more likely minority; had poorer medication adherence and glycemic control; and higher rates of hypoglycemia, comorbidities and healthcare utilization. This research represents the first successful attempt to use natural language processing and machine learning to measure health literacy. Literacy profiles offer an automated and economical way to identify patients with limited health literacy and a greater vulnerability to poor health outcomes.
Frame Rate Up-Conversion in Echocardiography Images, Using Manifold-Learning and Image Registration
Authors: Daneshi A. , Behnam H. , Sani Z. Alizadeh 
Published: September 2018

ABSTRACTIn this paper, we propose a new temporal frame interpolation algorithm for frame rate up-conversion (FRUC) in echocardiography images. This algorithm employs a combination of dimension reduction techniques and image registration to increase frame rate.If the distance between two successive frames of a video be great, motion jerkiness will appear between them and visual quality of the video will decrease. Some parts of heart have a very high speed motion, and echocardiography videos, obtained by available systems can’t take enough number of frames to show them well. So, to achieve an echocardiography image set with a better visual quality, more frames are necessary between two frames at a great distance. Here, we use dimension reduction techniques to find out the number of suitable frames between two consecutive frames to show the fast motions better, but don’t take much time. We project images to a 3-dimentional space by this way. Greater difference between the frames, results greater distance between corresponding embedded points. Thus, the distance between the embedded points is a scale for the suitable number of frames, needed between two successive frames. These frames are produced with the registration techniques.On the other hand, heart doesn’t have a constant speed during a cycle, but echocardiography images are recorded with constant speed. So, frames at a greater distance show fast motions of the heart, and frames at a lower distance show slow motions of the heart. While, we put unequal number of frames between successive frames, and in this way remove temporal coordination of the image set. To solve this problem, we put efficient number of linear average of available frames, in places that the number of inserted frames in between available frames is less than maximum to obtain an equal number of frames between all successive frames.
Learning Protein Structural Fingerprints under the Label-Free Supervision of Domain Knowledge
Authors: Min Yaosen , Liu Shang , Lou Chenyao , Cui Xuefeng 
Published: September 2018

AbstractFinding homologous proteins is the indispensable first step in many protein biology studies. Thus, building highly efficient “search engines” for protein databases is a highly desired function in protein bioinformatics. As of August 2018, there are more than 140,000 protein structures in PDB, and this number is still increasing rapidly. Such a big number introduces a big challenge for scanning the whole structure database with high speeds and high sensitivities at the same time. Unfortunately, classic sequence alignment tools and pairwise structure alignment tools are either not sensitive enough to remote homologous proteins (with low sequence identities) or not fast enough for the task. Therefore, specifically designed computational methods are required for quickly scanning structure databases for homologous proteins.Here, we propose a novel ContactLib-DNN method to quickly scan structure databases for homologous proteins. The core idea is to build structure fingerprints for proteins, and to perform alignment-free comparisons with the fingerprints. Specifically, the fingerprints are low-dimensional vectors representing the contact groups within the proteins. Notably, the Cartesian distance between two fingerprint vectors well matches the RMSD between the two corresponding contact groups. This is done by using RMSD as the domain knowledge to supervise the deep neural network learning. When comparing to existing methods, ContactLib-DNN achieves the highest average AUROC of 0.959. Moreover, the best candidate found by ContactLib-DNN has a probability of 70.0% to be a true positive. This is a significant improvement over 56.2%, the best result produced by existing methods.GitHub: https://github.com/Chenyao2333/contactlib/Index Termshomologous proteins, protein structures, remote protein homolog detection, alignment-free comparisons
Expanded Analysis of thePantoea stewartiisubsp.stewartiiDC283 Complete Genome Reveals Plasmid-borne Virulence Factors
Authors: Duong Duy An , Stevens Ann M. , Jensen Roderick V. 
Published: September 2018

ABSTRACTPantoea stewartiisubsp.stewartii, a Gram-negative proteobacterium, causes Stewart’s wilt disease in corn. Bacterial transmission to plants occurs primarily via the corn flea beetle insect vector, which is native to North America.P. stewartiiDC283 is the wild-type reference strain most used to study pathogenesis. Previously the complete genome ofP. stewartiiwas released. Here, the method whereby the genome was assembled is described in greater detail. Data from a matepair library preparation with 3.5 kilobase insert size and high-throughput sequencing from the MiSeq Illumina platform, together with the available incomplete genome sequence of AHIE00000000.1 (containing 65 contigs) was used. This work resulted in the complete assembly of one circular chromosome, ten circular plasmids and one linear phage fromP. stewartiiDC283. A high number of sequences encoding repetitive transposases (> 400) were found in the complete genome. The separation of plasmids from genomic DNA revealed that two Type III secretion systems inP. stewartiiDC283 are located on two separate mega-plasmids. Interestingly, the assembly identified a previously unknown 66-kb region in a location interior to a contig in the previous reference genome. Overall, a novel approach was successfully utilized to fully assemble a prokaryotic genome that contains large numbers of repetitive sequences and multiple plasmids, which resulted in some interesting biological findings.
Context-dependent multiplexing by individual VTA dopamine neurons
Authors: Yves Kremer , Jérôme Flakowski , Clément Rohner , Christian Lüscher 
Published: September 2018

AbstractDopamine (DA) neurons of the ventral tegmental area (VTA) track external cues and rewards to generate a reward prediction error (RPE) signal during Pavlovian conditioning. Here we explored how RPE is implemented for a self-paced, operant task in freely moving mice. The animal could trigger a reward-predicting cue by remaining in a specific location of an operant box for a brief time before moving to a spout for reward collection. In vivo single-unit recordings revealed phasic responses to the cue and reward in correct trials, while with failures the activity paused, reflecting positive and negative error signals of a reward prediction. In addition, a majority of VTA DA neurons also encoded parameters of the goal-directed action (e.g. movement velocity, acceleration, distance to goal and licking) by changes in tonic firing rate. Such multiplexing of individual neurons was only apparent while the mouse was engaged in the task. We conclude that a multiplexed internal representation during the task modulates VTA DA neuron activity, indicating a multimodal prediction error that shapes behavioral adaptation of a self-paced goal-directed action.
Effect of economic vulnerability on entrepreneurial competencies among Malaysian micro-entrepreneurs
Authors: Al Mamun Abdullah , Muniady Rajennd A/L , Ibrahim Mohd Asrul Hery Bin , Nawi Noorshella Binti Che 
Published: September 2018

Purpose
This study aims to investigate the impact of economic vulnerability upon entrepreneurial competencies (i.e. commitment competency, conceptual competency, opportunity recognition competency, organizing competency, relationship competency and strategic competency) among respondents from varied development initiatives established by the eKasih program (National Poverty Data Bank) in Peninsular Malaysia.

Design/methodology/approach
Upon adopting the cross-sectional design, data were randomly gathered from selected 300 micro-entrepreneurs from the list of development organizations available in the eKasih (National Poverty Data Bank), located at four states in Peninsular Malaysia. The quantitative data were gathered by performing structured interview sessions from September until November 2017.

Findings
The outcomes of the study displayed that economic vulnerability has a significantly negative effect upon commitment, opportunity recognition, organizing and strategic competency. On the other hand, the results showcased that economi c vulnerability has a significantly positive effect on competency, but insignificantly positive impact upon conceptual competency.

Originality/value
These study outcomes appear to extend the scope of the resource-based view, apart from enriching the existing entrepreneurial competency literature, particularly within the Malaysian context. Hence, it is recommended that the government of Malaysia and development organizations should focus on maximizing the level of competency among micro-entrepreneurs as a viable approach to decrease the effect of economic vulnerability.
Spinoffs versus non-spinoff entrepreneurs
Authors: Park Ye Jin , Park Young Won 
Published: September 2018

PurposeThe purpose of this study is to explore the role of spinoff entrepreneurs in the post-bubble Japan and ultimately to facilitate policy reforms that benefit entrepreneurs most in need of support.Design/methodology/approachThis study adopts a survey of Japanese entrepreneurs from 2003 to 2013. Exploiting the survey questions, the authors separate spinoff startups from the non-spinoff startups. Using this data set, this study first performs a logistic regression, followed by a chi-squared independence test between spinoff startups and firm performance.FindingsThis study finds that while both human and social capital predict the probability of a firm’s positive performance, industry experience was the strongest predictor for the probability of performance.Originality/valueAs Garvin (1983) stated, most research on spinoffs are limited to both industry type and location. The theoretical contribution of this study is to broaden the applicability of current entrepreneurship theories by considering industries beyond technological startups. The practical value of this study is to begin evaluating policies and their interaction effect with cultural context.
Structural reliability and stochastic finite element methods
Authors: Aldosary Muhannad , Wang Jinsheng , Li Chenfeng 
Published: September 2018

PurposeThis paper aims to provide a comprehensive review of uncertainty quantification methods supported by evidence-based comparison studies. Uncertainties are widely encountered in engineering practice, arising from such diverse sources as heterogeneity of materials, variability in measurement, lack of data and ambiguity in knowledge. Academia and industries have long been researching for uncertainty quantification (UQ) methods to quantitatively account for the effects of various input uncertainties on the system response. Despite the rich literature of relevant research, UQ is not an easy subject for novice researchers/practitioners, where many different methods and techniques coexist with inconsistent input/output requirements and analysis schemes.Design/methodology/approachThis confusing status significantly hampers the research progress and practical application of UQ methods in engineering. In the context of engineering analysis, the research efforts of UQ are most focused in two largely separate research fields: structural reliability analysis (SRA) and stochastic finite element method (SFEM). This paper provides a state-of-the-art review of SRA and SFEM, covering both technology and application aspects. Moreover, unlike standard survey papers that focus primarily on description and explanation, a thorough and rigorous comparative study is performed to test all UQ methods reviewed in the paper on a common set of reprehensive examples.FindingsOver 20 uncertainty quantification methods in the fields of structural reliability analysis and stochastic finite element methods are reviewed and rigorously tested on carefully designed numerical examples. They include FORM/SORM, importance sampling, subset simulation, response surface method, surrogate methods, polynomial chaos expansion, perturbation method, stochastic collocation method, etc. The review and comparison tests comment and conclude not only on accuracy and efficiency of each method but also their applicability in different types of uncertainty propagation problems.Originality/valueThe research fields of structural reliability analysis and stochastic finite element methods have largely been developed separately, although both tackle uncertainty quantification in engineering problems. For the first time, all major uncertainty quantification methods in both fields are reviewed and rigorously tested on a common set of examples. Critical opinions and concluding remarks are drawn from the rigorous comparative study, providing objective evidence-based information for further research and practical applications.
Optimization of process parameters of powder mixed EDM for high carbon high chromium alloy steel (D2 steel) through GRA approach
Authors: Singh Kanwal Jit 
Published: September 2018

Purpose
The purpose of this paper is to investigate the process parameters and optimise the machining input parameter of powder mixed electric discharge machining for high carbon high chromium alloy steel (D2 steel) for the industrial application. Grey relational analysis approach has been used to obtain the multiple performance output response.

Design/methodology/approach
In this experimental work, input parameters, namely, pulse on-time, discharge current, tool material and grit size, are selected. The design of the experiment has been constructed with the help of MINITAB 7 Software, in which L16 orthogonal array has been preferred for the experimentation. The effect of input parameters, namely, material removal rate, tool wear rate and surface roughness, is investigated. Grey relational analysis and analysis of variance are performed to optimise the input parameters and better output results.

Findings
In this experimentation, there is an increment of tool wear rate by 64.49 per cent, material removal rate by 47.14 per cent and surface roughness by 35.82 per cent.

Practical implications
A lot of practical applications have been found in many different material processing industries like metallurgy, machinery, electronics, transportation, military science, agricultural machinery, etc. These practical applications have brought forward definite and noticeable economic benefits.

Originality/value
The reader is given a general overview on the machining investigation and optimisation of processes parameters through the grey theory approach. It gives a new framework to investigate the problems where multiple input machining variable and various output responses are obtained in single optimised parameters.
Turbulent natural convection combined with surface thermal radiation in a square cavity with local heater
Authors: Miroshnichenko Igor , Sheremet Mikhail , Chamkha Ali J. 
Published: September 2018

Purpose
The purpose of this paper is to conduct a numerical analysis of transient turbulent natural convection combined with surface thermal radiation in a square cavity with a local heater.

Design/methodology/approach
The domain of interest includes the air-filled cavity with cold vertical walls, adiabatic horizontal walls and isothermal heater located on the bottom cavity wall. It is assumed in the analysis that the thermophysical properties of the fluid are independent of temperature and the flow is turbulent. Surface thermal radiation is considered for more accurate analysis of the complex heat transfer inside the cavity. The governing equations have been discretized using the finite difference method with the non-uniform grid on the basis of the special algebraic transformation. Turbulence was modeled using the k–ε model. Simulations have been carried out for different values of the Rayleigh number, surface emissivity and location of the heater.

Findings
It has been found that the presence of surface radiation leads to both an increase in the average total Nusselt number and intensive cooling of such type of system. A significant intensification of convective flow was also observed owing to an increase in the Rayleigh number. It should be noted that a displacement of the heater from central part of the bottom wall leads to significant modification of the thermal plume and flow pattern inside the cavity.

Originality/value
An efficient numerical technique has been developed to solve this problem. The originality of this work is to analyze unsteady turbulent natural convection combined with surface thermal radiation in a square air-filled cavity in the presence of a local isothermal heater. The results would benefit scientists and engineers to become familiar with the analysis of turbulent convective–radiative heat transfer in enclosures with local heaters, and the way to predict the heat transfer rate in advanced technical systems, in industrial sectors including transportation, power generation, chemical sectors and electronics.
Herbarium specimens reveal increasing herbivory over the past century
Authors: Meineke Emily K. , Classen Aimée T. , Sanders Nathan J. , Jonathan Davies T. 
Published: September 2018

Abstract

Predicting how ecological interactions will respond to global change is a major challenge. Plants and their associated insect herbivores compose much of macroscopic diversity, yet how their interactions have been altered by recent environmental change remains underexplored.

To address this gap, we quantified herbivory on herbarium specimens of four plant species with records extending back 112 years. Our study focused on the northeastern US, where temperatures have increased rapidly over the last few decades. This region also represents a range of urban development, a form of global change that has shown variable effects on herbivores in the past studies.

Herbarium specimens collected in the early 2000s were 23% more likely to be damaged by herbivores than those collected in the early 1900s. Herbivory was greater following warmer winters and at low latitudes, suggesting that climate warming may drive increasing insect damage over time. In contrast, human population densities were negatively associated with herbivore damage.

To explore whether changes in insect occurrence or abundance might explain shifts in herbivory, we used insect observational records to build climate occupancy models for lepidopteran herbivores (butterflies and moths) of our focal plant species.

These models show that higher winter temperatures were associated with higher probability of insect herbivore presence, while urbanization was associated with reduced probability of herbivore presence, supporting a link between insect herbivore occurrence and herbivory mediated through environment.

Synthesis. Using a temporal record of plant herbivory that spans over a century, we show that both temperature and urbanization influence insect damage to plants, but in very different ways. Our results indicate that damage to plants by insect herbivores will likely continue to increase through time in the northeastern US as global temperatures rise, but that urbanization may disrupt local effects of winter warming on herbivory by excluding certain herbivores. These changes may scale to shape ecosystem processes that are driven by herbivory, including plant productivity.
Construct validity and responsiveness of the functional Tactile Object Recognition Test for children with cerebral palsy
Authors: Taylor Susan , Girdler Sonya , Parsons Richard , McLean Belinda , Falkmer Torbjorn , Carey Leeanne , Blair Eve , Elliott Catherine 
Published: September 2018

Background/aimThe functional Tactile Object Recognition Test (fTORT) is a measure of haptic object recognition capacity recently adapted for use with children with neurological impairment. The current study aimed to investigate preliminary evidence of construct validity and responsiveness of the fTORT and its association with a measure of upper limb activity.MethodsA cross‐sectional study of 28 children with spastic hemiplegic cerebral palsy (CP) (mean age 10 years 8 months; SD two years four months; 16 male) and 39 typically developing (TD) children (mean age 11 years; SD two years nine months; 19 male) was utilised to investigate construct validity and association between measures. Sixteen children with CP (mean age 10 years 10 months; SD two years 8 months; 9 male) who were randomly allocated to either a treatment (n = 6) or control group (n = 10) were assessed at four time points to assess test responsiveness.ResultsThere was a very significant difference (P value <0.0001) indicating greater haptic object recognition ability for the TD group (n = 39; median: 40; range: 33–42) than the group with CP (n = 28; median: 32.5; range: 3–41). fTORT scores demonstrated a significant association with scores on the activity measure (Pearson's r: 0.68; P = 0.0001). There were no significant changes over time in fTORT scores (P = 0.22) and no significant difference between the treatment and control groups (P = 0.47).ConclusionThe fTORT demonstrated preliminary construct validity, and was positively associated with an upper limb activity measure but scores did not change significantly following somatosensory training. This preliminary paper supports further research and future psychometric knowledge about the tool.