Communication Overload in Online Communities in Higher Education

This paper presents part of a research project on the use of information technology by students and teachers to communicate with each other in online community contexts of higher education institutions. The part of this project which investigated whether the number of messages exchanged, and the effort required to process them are a source of communication overload is the focus of the paper. The research was conducted at a Portuguese university, was supported by an analysis model, and data were collected through an online questionnaire. Descriptive statistics and inference tests were used to analyse a validated data sample of n = 570 students and n = 172 teachers. The results show that students and teachers generally perceive communication overload when using communication technologies to communicate with each other. This perception is particularly relevant when using email, and inference tests show that it is higher for teachers than for students

The Use of ICT for Communication between Teachers and Students in the Context of Higher Education Institutions

Recently, the communication paradigm has been changing in society in the higher education context because of the ease of access to the Internet and the high number of mobile devices. Thus, universities have increased their interest in accepting different and sophisticated communication technologies to improve student participation in the educational process. This study aimed to assess how students and teachers use communication technologies to communicate with each other and what their expectations, satisfaction, and attitudes regarding the results of this use are. An analysis model was used in a case study at the University of Aveiro to support the study. Data were obtained through an online questionnaire, which collected 570 responses from students and 172 responses from teachers. These data were processed through descriptive statistics techniques and inference tests (t-tests). The primary outcomes are that publishing and sharing technologies and electronic mail are the most commonly used communication technologies by students and teachers, suggesting that their use will not decline soon. However, other communication technologies were also revealed to be widely used and accepted, with excellent levels of confirmation of expectation.

Biopolymer Degradation Analysis: Accelerated Life Testing Study to Characterize Polylactic Acid Durability

While the degradation of Polylactic Acid (PLA) has been studied for several years, results regarding the mechanism for determining degradation are not completely understood. Through accelerated degradation testing, data can be extrapolated and modeled to test parameters such as temperature, voltage, time, and humidity. Accelerated lifetime testing is used as an alternative to experimentation under normal conditions. The methodology to create this model consisted of fabricating series of ASTM specimens using extrusion and injection molding. These specimens were tested through accelerated degradation; tensile and flexural testing were conducted at different points of time. Nonparametric inference tests for multivariate data are presented. The results indicate that the effect of the independent variable or treatment effect (time) is highly significant. This research intends to provide a better understanding of biopolymer degradation. The findings indicated that the proposed statistical models can be used as a tool for characterization of the material regarding the durability of the biopolymer as an engineering material. Having multiple models, one for each individual accelerating variable, allow deciding which parameter is critical in the characterization of the material.

Ergonomic evaluation in community pharmacies

Background The risk of a health professional contracting work-related diseases is about 1.5 times greater than the risk of all other workers. For this reason, the present study focused on community pharmacies, aiming ergonomic risks, which allows a more personalized intervention individualized in an assessment and control of ergonomic risks. Methods We proposed as an objective of this study, to evaluate the ergonomic risks to which the workers of the community pharmacies are exposed. This study was of the Descriptive-Correlational, Analytical type, and of a transversal nature where the working conditions in pharmacies of the municipality of Coimbra were evaluated. The sample being represented by 15 workers. A questionnaire was carried out and the KIM and RULA methodologies were applied for ergonomic evaluation. The results were evaluated using the IBM SPSS Statistics version 26.0 program using descriptive tests and inference tests. Results The ergonomic assessment indicated greater risk of exposure in the task of replacing goods, the perception of workers proved to be positive in relation to existing non-conformities. There were no statistically significant differences in psychosocial and ergonomic risks between men and women. Conclusion The ergonomic conditions of the workplace for the professionals in community pharmacies are unfavourable in some points. However, if they try to adapt the workplace to the worker considering ergonomic aspects, they will promote well-being and thus guarantee better performance for their professionals and consequent increase in productivity

The Accessible Museum: Towards an Understanding of International Audio Description Practices in Museums

Introduction: Audio description (AD) in museums is crucial for making them accessible for people with visual impairments. Nevertheless, there are limited museum-specific AD guidelines currently available. This research examines current varied international practitioner perspectives on museum AD, focusing on imagery, meaning, emotion and degrees of objectivity, and the regional differences (Europe and United States) in AD traditions, in order to better understand how AD can be used to enhance access to museums. Methods: Forty-two museum describers from 12 countries responded to a questionnaire requiring fixed-choice and free-text responses about the purpose and construction of museum AD. Results: Inference tests showed that European describers agreed more strongly than American describers that AD should “explore meaning” ( U = 91.00 , N1 = 24, N2 = 14, p = .03), and “create an emotional experience” ( U = 89.50, N1 = 24, N2 = 14, p = .03), rating the use of cognitive prompts as more important ( U = 85.50, N1 = 21, N2 = 14, p = .04). Qualitative data enriched this understanding by exploring participant responses on the themes of mental imagery, objectivity and interpretation and cognitive prompts. This highlighted broader agreement between regions on mental imagery, but more acceptance of interpretation in AD from the European respondents. Discussion: American and European describers’ opinions differ regarding the purpose of AD: whether it is about conveying visual information or whether broader interpretations should be incorporated into descriptions for audiences with visual impairments. Implications for practitioners: These findings indicate that further discussion is needed regarding the purpose of museum AD and, in particular, the way in which objectivity is contextualized. They raise questions about AD providing visual information and/or seeking to address a wider museum experience, including the stimulation of curiosity or emotion.

A Structured Approach to Evaluating Life Course Hypotheses: Moving Beyond Analyses of Exposed Versus Unexposed in the Omics Context

The structured life course modeling approach (SLCMA) is a theory-driven analytic method that empirically compares multiple prespecified life course hypotheses characterizing time-dependent exposure-outcome relationships to determine which theory best fits the observed data. In this study, we performed simulations and empirical analyses to evaluate the performance of the SLCMA when applied to genome-wide DNA methylation (DNAm). Using simulations, we compared five statistical inference tests used with SLCMA (n=700), assessing the family-wise error rate, statistical power, and confidence interval coverage to determine whether inference based on these tests was valid in the presence of substantial multiple testing and small effects, two hallmark challenges of inference from omics data. In the empirical analyses, we evaluated the time-dependent relationship of childhood abuse with genome-wide DNAm (n=703). In simulations, selective inference and max-|t|-test performed best: both controlled family-wise error rate and yielded moderate statistical power. Empirical analyses using SLCMA revealed time-dependent effects of childhood abuse on DNAm. Our findings show that SLCMA, applied and interpreted appropriately, can be used in high-throughput settings to examine time-dependent effects underlying exposure-outcome relationships over the life course. We provide recommendations for applying the SLCMA in omics settings and encourage researchers to move beyond analyses of exposed versus unexposed.

Systemic Investigation of Promoter-wide Methylome and Genome Variations in Gout

Current knowledge of gout centers on hyperuricemia. Relatively little is known regarding the pathogenesis of gouty inflammation. To investigate the epigenetic background of gouty inflammation independent of hyperuricemia and its relationship to genetics, 69 gout patients and 1455 non-gout controls were included. Promoter-wide methylation was profiled with EPIC array. Whole-genome sequencing data were included for genetic and methylation quantitative trait loci (meQTL) analyses and causal inference tests. Identified loci were subjected to co-methylation analysis and functional localization with DNase hypersensitivity and histone marks analysis. An expression database was queried to clarify biologic functions of identified loci. A transcription factor dataset was integrated to identify transcription factors coordinating respective expression. In total, seven CpG loci involved in interleukin-1β production survived genetic/meQTL analyses, or causal inference tests. None had a significant relationship with various metabolic traits. Additional analysis suggested gouty inflammation, instead of hyperuricemia, provides the link between these CpG sites and gout. Six (PGGT1B, INSIG1, ANGPTL2, JNK1, UBAP1, and RAPTOR) were novel genes in the field of gout. One (CNTN5) was previously associated with gouty inflammation. Transcription factor mapping identified several potential transcription factors implicated in the link between differential methylation, interleukin-1β production, and gouty inflammation. In conclusion, this study revealed several novel genes specific to gouty inflammation and provided enhanced insight into the biological basis of gouty inflammation.

Mediterranean nekton traits: distribution, relationships and significance for marine ecology monitoring and management

Biological traits are increasingly used in order to study aspects of ecology as they are related to the organisms’ fitness. Here we analyze a dataset of 23 traits regarding the life cycle, distribution, ecology and behavior of 235 nektonic species of the Mediterranean Sea in order to evaluate the distribution of traits, identify rare ones, detect relationships between trait pairs and identify species functional groups. Trait relationships were tested using correlation and non-linear regression for continuous traits, parametric and non-parametric inference tests for pairs of continuous-categorical traits and cooccurrence testing for categorical traits. The findings have significant implications concerning the potential effects of climate change (e.g., through the relationships of the trait of optimal temperature), fisheries or habitat loss (from the relationships of traits related to tolerance ranges). Furthermore, some unexpected relationships are documented, like the inversely proportional relationship between longevity and age at maturity as a percentage of life span. Associations between functional traits show affinities derived from phylogenetic constraints or life strategies; however, relationships among functional and ecological traits can indicate the potential environmental filtering that acts on functional traits. In total, 18 functional groups were identified by Hill-Smith ordination and hierarchical clustering and were characterized by their dominant traits. For the assessment of the results, we first evaluate the importance of each trait at the level of population, community, ecosystem and landscape and then propose the traits that should be monitored for the regulation and resilience of ecosystem functioning and the management of the marine ecosystems.

Deriving star cluster parameters with convolutional neural networks

Context. Convolutional neural networks (CNNs) have been established as the go-to method for fast object detection and classification of natural images. This opens the door for astrophysical parameter inference on the exponentially increasing amount of sky survey data. Until now, star cluster analysis was based on integral or resolved stellar photometry, which limit the amount of information that can be extracted from individual pixels of cluster images. Aims. We aim to create a CNN capable of inferring star cluster evolutionary, structural, and environmental parameters from multiband images and to demonstrate its capabilities in discriminating genuine clusters from galactic stellar backgrounds. Methods. A CNN based on the deep residual network (ResNet) architecture was created and trained to infer cluster ages, masses, sizes, and extinctions with respect to the degeneracies between them. Mock clusters placed on M 83 Hubble Space Telescope images utilizing three photometric passbands (F336W, F438W, and F814W) were used. The CNN is also capable of predicting the likelihood of the presence of a cluster in an image and quantifying its visibility (S/N). Results. The CNN was tested on mock images of artificial clusters and has demonstrated reliable inference results for clusters of ages ≲100 Myr, extinctions AV between 0 and 3 mag, masses between 3 × 103 and 3 × 105 M⊙, and sizes between 0.04 and 0.4 arcsec at the distance of the M 83 galaxy. Real M 83 galaxy cluster parameter inference tests were performed with objects taken from previous studies and have demonstrated consistent results.

A structured approach to evaluating life course hypotheses: Moving beyond analyses of exposed versus unexposed in the omics context

BackgroundLife course epidemiology provides a framework for studying the effects of time-varying exposures on health outcomes. The structured life course modeling approach (SLCMA) is a theory-driven analytic method that empirically compares multiple prespecified life course hypotheses characterizing time-dependent exposure-outcome relationships to determine which theory best fits the observed data. However, the statistical properties of inference methods used with the SLCMA have not been investigated with high-dimensional omics outcomes.MethodsWe performed simulations and empirical analyses to evaluate the performance of the SLCMA when applied to genome-wide DNA methylation (DNAm). In the simulations, we compared five statistical inference tests used by SLCMA (n=700). For each, we assessed the familywise error rate (FWER), statistical power, and confidence interval coverage to determine whether inference based on these tests was valid in the presence of substantial multiple testing and small effect sizes, two hallmark challenges of inference from omics data. In the empirical analyses, we applied the SLCMA to evaluate the time-dependent relationship of childhood abuse with genome-wide DNAm (n=703).ResultsIn the simulations, selective inference and max-|t|-test performed best: both controlled FWER and yielded moderate statistical power. Empirical analyses using SLCMA revealed time-dependent effects of childhood abuse on DNA methylation.ConclusionsOur findings show that SLCMA, applied and interpreted appropriately, can be used in the omics setting to examine time-dependent effects underlying exposure-outcome elationships over the life course. We provide recommendations for applying the SLCMA in high-throughput settings, which we hope will encourage researchers to move beyond analyses of exposed versus unexposed.Key messagesThe structured life course modeling approach (SLCMA) is an effective approach to directly compare life course theories and can be scaled-up in the omics context to examine nuanced relationships between environmental exposures over the life course and biological processes.Of the five statistical inference tests assessed in simulations, we recommend the selective inference method and max-|t|-test for post-selection inference in omics applications of the SLCMA.In an empirical example, we revealed time-dependent effects of childhood abuse on DNA methylation using the SLCMA, with improvement in statistical power when accounting for covariates by applying the Frisch-Waugh-Lovell (FWL) theorem.Researchers should assess p-values in parallel with effects sizes and confidence intervals, as triangulating multiple forms of statistical evidence can strengthen inferences and point to new directions for replication.