The ‘hookability’of multimodal impact captions

The use of captions has grown in recent years in both traditional and new media, particularly in terms of the diversity of style, content, and function. Impact captions have emerged as a popular form of captions for hearing viewers and contain rich multimodal information which is employed to capture viewer attention and enhance engagement, particularly in situations where there is competition for viewer attention. Drawing upon relevance theory, we argue how impact captions could effectively attract and hold visual attention owing to their balance between processing effort and contextual effects. This exploratory study employs a dual-task paradigm and uses authentic materials and viewing situations to further examine the ability of multimodal impact captions to attract and retain overt visual attention amongst a small sample of TV viewers. Our results provide novel insight into the apparent highly individualised efficacy of impact captions, where we identify several variables of interest in participants’ viewing behaviours. We conclude with a discussion of the study’s contributions, limitations, and an outline for future work.

The impact of online reviews on renters' perceived trust in property information

Using cognitive consistency theory, we explored the mechanisms of prospective renters' cognitive processing and cognitive outcomes of reviewing rental listing information on the Internet. We conducted an eye-movement experiment with 102 prospective renters to investigate the mechanisms influencing their cognitive processing and outcomes, via a 2 (comment form: subjective, objective) × 2 (risk preference: risk avoider, risk preference) factorial design. The results show that (a) subjective reviews required more cognitive processing effort than did objective reviews, but the perceived trust level of subjective reviews was lower; (b) risk-averse (vs. risk-inclined) participants put more cognitive effort into processing listing information, but their perceived trust in the listing information was lower; and (c) participants' perceived trust in listing information was mainly influenced by the display attributes of the webpage, rather than the review information. Our results will help Internet rental companies understand tenants' information concerns and enhance their online display pages in a targeted manner.

Transferability of a Machine Learning-Based Model of Hourly Traffic Volume Estimation—Florida and New Hampshire Case Study

This paper focuses on the problem of model transferability for machine learning models used to estimate hourly traffic volumes. The presented findings enable not only an increase in the accuracy of existing models but also, simultaneously, reduce the cost of data needed for training the models—making statewide traffic volume estimation more economically feasible. Previous research indicates that machine learning volume estimation models that leverage GPS probe data can provide transportation agencies with accurate estimates of hourly traffic volumes—which are fundamental for both operational and planning purposes—and do so with a higher level of accuracy than the prevailing profiling method. However, this approach requires a large dataset for model calibration (i.e., input and continuous count station data), which involves significant monetary investment and data-processing effort. This paper proposes solutions, which allow the model to be prepared using a much smaller dataset, given that a previously collected dataset, which may be gathered in a different place and time period, exists. Based on a broad selection of experiments, the results indicate that the proposed approach is capable of achieving similar model performance while collecting data for a 5 times shorter time period and utilizing 1/4 of the number of continuous count stations. These findings will help reduce the cost of preparing and maintaining the traffic volume models and render the traffic volume estimations more financially appealing.

Guidelines for a Morphometric Analysis of Prokaryotic and Eukaryotic Cells by Scanning Electron Microscopy

The invention of a scanning electron microscopy (SEM) pushed the imaging methods and allowed for the observation of cell details with a high resolution. Currently, SEM appears as an extremely useful tool to analyse the morphology of biological samples. The aim of this paper is to provide a set of guidelines for using SEM to analyse morphology of prokaryotic and eukaryotic cells, taking as model cases Escherichia coli bacteria and B-35 rat neuroblastoma cells. Herein, we discuss the necessity of a careful sample preparation and provide an optimised protocol that allows to observe the details of cell ultrastructure (≥ 50 nm) with a minimum processing effort. Highlighting the versatility of morphometric descriptors, we present the most informative parameters and couple them with molecular processes. In this way, we indicate the wide range of information that can be collected through SEM imaging of biological materials that makes SEM a convenient screening method to detect cell pathology.

Detection of Movement Intention in EEG-Based Brain-Computer Interfaces Using Fourier-Based Synchrosqueezing Transform

Patients with motor impairments need caregivers’ help to initiate the operation of brain-computer interfaces (BCI). This study aims to identify and characterize movement intention using multichannel electroencephalography (EEG) signals as a means to initiate BCI systems without extra accessories/methodologies. We propose to discriminate the resting and motor imagery (MI) states with high accuracy using Fourier-based synchrosqueezing transform (FSST) as a feature extractor. FSST has been investigated and compared with other popular approaches in 28 healthy subjects for a total of 6657 trials. The accuracy and f-measure values were obtained as 99.8% and 0.99, respectively, when FSST was used as the feature extractor and singular value decomposition (SVD) as the feature selection method and support vector machines as the classifier. Moreover, this study investigated the use of data that contain certain amount of noise without any preprocessing in addition to the clean counterparts. Furthermore, the statistical analysis of EEG channels with the best discrimination (of resting and MI states) characteristics demonstrated that F4-Fz-C3-Cz-C4-Pz channels and several statistical features had statistical significance levels, [Formula: see text], less than 0.05. This study showed that the preparation of the movement can be detected in real-time employing FSST-SVD combination and several channels with minimal pre-processing effort.

Knowledge is a river and education is like a stairway: An eye movement study on how L2 speakers process metaphors and similes

Very little is known about the processes underlying second language (L2) speakers’ understanding of written metaphors and similes. Moreover, most of the theories on figurative language comprehension do not consider reader-related factors. In the study, we used eye-tracking to examine how native Finnish speakers (N = 63) read written English nominal metaphors (“education is a stairway”) and similes (“education is like a stairway”). Identical topic–vehicle pairs were used in both conditions. After reading, participants evaluated familiarity of each pair. English proficiency was measured using the Bilingual-language Profile Questionnaire and the Lexical Test for Advanced Learners of English. The results showed that readers were more likely to regress within metaphors than within similes, indicating that processing metaphors requires more processing effort than processing similes. The familiarity of a metaphor and L2 English proficiency modulated this effect. The results are discussed in the light of current theories on figurative language processing.

Sans Forgetica is Not the “Font” of Knowledge: Disfluent Fonts are Not Always Desirable Difficulties

Subsequent recall is improved if students try to recall target material during study (self-testing) versus simply re-reading it. This effect is consistent with the notion of “desirable difficulties.” If the learning experience involves difficulties that induce extra effort, then retention may be improved. Not all difficulties are desirable, however. Difficult-to-read ( disfluent) typefaces yield inconsistent results. A new disfluent font, Sans Forgetica, was developed and alleged to promote deeper processing and improve learning. Although it would be invaluable if changing the font could enhance learning, the few studies on Sans Forgetica have been inconsistent, and focused on short retention intervals (0–5 minutes). We investigated a 1-week interval to increase practical relevance and because some benefits only manifest after a delay. A testing-effect manipulation was also included. Students ( N = 120) learned two passages via different methods (study then re-study vs. study then self-test). Half the students saw the passages in Times New Roman and half in Sans Forgetica. Recall test scores were higher for passages learned via self-testing than restudying, but the effect of font and the interaction were nonsignificant. We suggest that disfluency increases the local (orthographic) processing effort on each word but slowed reading might impair relational processing across words. In contrast, testing and generation effect manipulations often engage relational processing (question: answer; cue: target)—yielding subsequent benefits on cued-recall tests. We elaborate this suggestion to reconcile conflicting results across studies.

Personal Achievement Goals, Learning Strategies, and Perceived IT Affordances

What people perceive when they interact with technologies are not the features and functionalities of the technology but rather the behaviors it affords them. Affordance perception determines how organizational information technology (IT) is used by employees and the benefits they provide to organizations and their members. In this article, we explain how employees who pursue different personal goals and use various learning strategies come to perceive different IT affordances. We identify three distinct pathways: (1) performance-avoidance goals are positively associated with surface processing, which leads to perceptions of common in-role IT affordances; (2) performance-approach goals are positively associated with surface processing and effort regulation and these learning strategies lead to perceptions of common and specialized in-role IT affordances; and (3) mastery goals are associated with deep processing, effort regulation, and peer learning, which are positively associated with perceptions of specialized in-role and extra-role IT affordances. By identifying the different pathways to perceived affordances, the article identifies potential interventions that can help managers steer employees toward certain affordances and away from other, less desirable affordances.

The influence of semantic relevance on the discernment of product appearance and function

Background This study investigated the impact of semantic relevance on the ability to comprehend the appearance and function of a product, as presented in images. Methods The images used the constructs of Simile, Metaphor and Analogy to correspond to congruent, related and incongruent semantic structures, and measured the amplitude of Event-Related Potentials (ERPs) to compare these images with Landscape images. Sixteen participants with design-related educational backgrounds were invited to join in the ERP experiment. Results The results found that the image depicting the Metaphor showed a stronger N600 amplitude in the right anterior region of the brain than the Landscape image and the Analogy image induced a stronger N600 effect in the left anterior and right anterior part of the brain than the Landscape image. However, the Simile image did not trigger the N600. The N600 was triggered when the meaning of the Metaphor and Analogy being presented could not be understood. This indicates that a greater processing effort to comprehend them than was required for Simile. Analogy has a wider N600 distribution than Metaphor in the anterior area, suggesting that Analogy would require higher-level thinking processes and more complex semantic processing mechanisms than Metaphor. Conclusions The N600 implicated that an assessment method to detect the semantic relationship between appearance and function of a product would assist in determining whether a symbol was suitable to be associated with a product.

The remediation of textile wastewater using solid Bauxite Residue waste as a potential Fenton catalyst in the fluidized bed Fenton process

The synergistic relationship between the reactor and the catalysts has gained immense popularity in the field of Chemical Engineering due to their wide application. Catalytic processes have evolved over the decades from expensive commercial catalysts to low-cost solid waste catalysts for the sustainable development and reduction of their impacts on the environment. This alternative use of solid waste can greatly decrease the cost of wastewater treatment and addresses solid wastes issues. Bauxite Residue (BR) is one such waste from alumina-based industries with excellent catalytic properties. The fluid dynamics of fluidized bed technology improves profoundly the hydrodynamics and mass transfer of the heterogeneous Fenton process. This paper presents the preparation of the catalyst with minimum processing effort. It was characterized and factors affecting the degradation efficiency of synthetic dye wastewater were investigated. The optimum conditions for the eosin yellow dye were observed at a pH of five, oxidant concentration of 30 mM, catalyst dosage of 4 g/L. The removal efficiency at these optimum conditions was observed to be 91%. The residence time distribution (RTD) study was aimed to determine the behavior of the reactor using the mean residence time, variance, and dispersion number for the fluidized bed reactor.