Helping children to get along: teachers’ strategies for dealing with bullying in primary schools

This brief report describes a small scale qualitative interview study with primary school teachers in England, investigating their perceptions of bullying and strategies to prevent and manage it. Findings showed that much intervention work was situationally dependent, with teachers making subtle judgements about when and how to intervene. Prevention and intervention work centred on empathy development, and teaching children skills to help them nurture effective social relationships. We suggest that this holistic approach to bullying enables teachers to address multiple agendas aligned towards promoting children’s social and emotional learning

Dietary Fiber Intake Predicts 10-Yr Weight Change in 7,804 U.S. Adults

Although the relationship between dietary fiber intake and obesity has been examined many times, studies evaluating the association between fiber consumption and long-term weight gain are rare. This is unfortunate because it is weight gain over time that drives the development of obesity. PURPOSE: This study was conducted to determine the relationship between dietary fiber intake and weight change over a 10-yr period in 7,804 U.S. men and women, 36-70 years old. METHODS: Data from the National Health and Nutrition Examination Survey (NHANES) were used to answer the research question. Because subjects were randomly selected, the results are generalizable to the U.S. adult population within the same age-range. Weight change (kg) over the previous 10 years was measured by subtracting self-reported, baseline body weight 10-yrs earlier from current measured body weight. Percent weight change was calculated by dividing 10-yr weight change (kg) by baseline body weight. Dietary fiber intake was assessed by taking the average of two 24-hr dietary recall interview results (midnight to midnight) administered by trained technicians, the first in-person and the second via telephone. Fiber consumption was expressed as grams consumed per 1000 kcal. Multiple regression was used to determine the linear relationship between fiber intake and percent weight change. Demographic covariates included age, sex, and race/ethnicity. Lifestyle covariates included total physical activity, smoking, alcohol use, and whether the participant was on a special diet. Potential mediating variables were controlled using partial correlation. RESULTS: After controlling for the demographic covariates, the association between fiber intake and percent 10-yr weight change was linear and inverse (F=19.2, PCONCLUSION: The more dietary fiber U.S. men and women consume, the less weight they tend to gain over 10 years

Bifurcated polarization rotation in bismuth-based piezoelectrics

ABO3 perovskite-type solid solutions display a large variety of structural and physical properties, which can be tuned by chemical composition or external parameters such as temperature, pressure, strain, electric, or magnetic fields. Some solid solutions show remarkably enhanced physical properties including colossal magnetoresistance or giant piezoelectricity. It has been recognized that structural distortions, competing on the local level, are key to understanding and tuning these remarkable properties, yet, it remains a challenge to experimentally observe such local structural details. Here, from neutron pair-distribution analysis, a temperature-dependent 3D atomic-level model of the lead-free piezoelectric perovskite Na0.5Bi0.5TiO3 (NBT) is reported. The statistical analysis of this model shows how local distortions compete, how this competition develops with temperature, and, in particular, how different polar displacements of Bi3+ cations coexist as a bifurcated polarization, highlighting the interest of Bi-based materials in the search for new lead-free piezoelectrics

The effects of dietary fibres on the behaviour and growth of colonic epithelial cells in vivo and in vitro

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Parents’ perceptions of their children’s physical activity during the COVID-19 pandemic

Background COVID-19 has drastically changed the everyday lives of children, including limiting interactions with peers, loss of regularly organized activities, and closure of schools and recreational facilities. While COVID-19 protocols are in place to reduce viral transmission, they have affected children’s access to physical activity opportunities. The purpose of this study was to understand how COVID-19 has affected children’s engagement in physical activity and to identify strategies that can support children’s return to physical activity programming in public places. Methods Parents of past participants in the Grade 5 ACT-i-Pass Program in London, Ontario, Canada were invited to participate in a semi-structured interview online (in November and December 2020) via Microsoft Teams. The script was comprised of questions about their child’s physical activity levels (before, current, and anticipated following COVID-19), lifestyle changes due to COVID-19, and what service providers can do to assist children’s return to public programming. Interviews were transcribed in Microsoft Teams, reviewed by a member of the research team, and analyzed in NVivo 12 using thematic analysis. Results Twenty-seven parents participated in an interview. Four themes and two subthemes were identified during analysis: (1) modifications to everyday life (a. activity options available and b. altered social environment), (2) safety in public spaces, (3) accessibility of activities, and (4) utilizing outdoor spaces. Conclusions COVID-19 protocols have decreased children’s physical activity levels due to the loss of their regular activities, recreational spaces, and peer support. Implementing facility and activity-specific health protocols, providing outdoor activity options, and offering a variety of activity types, times, and locations are three strategies recommended by parents to help facilitate their children’s return to public recreational places. Due to the negative consequences of physical inactivity on children’s health and well-being, service providers need to implement programming and safety protocols that support children’s engagement in physical activity throughout the remainder of, and the years following, the COVID-19 pandemic

Parents’ report of canadian elementary school children’s physical activity and screen time during the COVID-19 pandemic: A longitudinal study

COVID-19 public health protocols have altered children’s daily routines, limiting their physical activity opportunities. The purpose of this study was to examine how the COVID-19 pandemic affected children’s (ages 10–12 years) physical activity and screen time, and to explore the impact of gender, socioeconomic status (SES), and public health constraints (i.e., facility use and social interaction) on the changes in children’s health behaviors. Online surveys were disseminated to parents at two time points: before COVID-19 (May 2019 to February 2020) and during COVID-19 (November to December 2020). Wilcoxon signed-rank tests were used to assess changes in physical activity and screen time, and for subgroup analyses. Parents (n = 95) reported declines in children’s physical activity (Z = −2.53, p. = 0.01, d = 0.18), and increases in weekday (Z = −4.61, p \u3c 0.01, d = 0.33) and weekend screen time (Z = −3.79, p \u3c 0.01, d = 0.27). Significant changes in physical activity and screen time behaviors were identified between gender, SES, and facility use groups. All social interaction groups underwent significant changes in screen time. Overall, COVID-19 protocols have negatively influenced children’s physical activity and screen time. Due to the negative consequences of inactivity and excessive screen time, resources must be made available to support families during the pandemic

Combining heterogeneous sources of data for the reverse-engineering of gene regulatory networks

Gene Regulatory Networks (GRNs) represent how genes interact in various cellular processes by describing how the expression level, or activity, of genes can affect the expression of the other genes. Reverse-engineering GRN models can help biologists understand and gain insight into genetic conditions and diseases. Recently, the increasingly widespread use of DNA microarrays, a high-throughput technology that allows the expression of thousands of genes to be measured simultaneously in biological experiments, has led to many datasets of gene expression measurements becoming publicly available and a subsequent explosion of research in the reverse-engineering of GRN models. However, microarray technology has a number of limitations as a data source for the modelling of GRNs, due to concerns over its reliability and the reproducibility of experimental results. The underlying theme of the research presented in this thesis is the incorporation of multiple sources and different types of data into techniques for reverse-engineering or learning GRNs from data. By drawing on many data sources, the resulting network models should be more robust, accurate and reliable than models that have been learnt using a single data source. This is achieved by focusing on two main strands of research. First, the thesis presents some of the earliest work in the incorporation of prior knowledge that has been generated from a large body of scientific papers, for Bayesian network based GRN models. Second, novel methods for the use of multiple microarray datasets to produce Bayesian network based GRN models are introduced. Empirical evaluations are used to show that the incorporation of literature-based prior knowledge and combining multiple microarray datasets can provide an improvement, when compared to the use of a single microarray dataset, for the reverse-engineering of Bayesian network based GRN models.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Comparative Outcomes of Autologous Chondrocyte Implantation and Osteochondral Allograft Transplantation with Patellar Realignment for Patellar Instability with Associated Cartilage Defects

Abstract Background: Articular cartilage pathology can stem from a spectrum of etiologies including osteochondritis dissecans, avascular necrosis, degenerative joint disease, and injury resulting from recurrent instability of the patella. Hypothesis/Purpose: The purpose of this study was to identify differences in clinical and functional outcomes in patients treated with either ACI or OCA transplantation for chondral defects with concomitant MPFL reconstruction and tibia tubercle osteotomy. Study Design: Retrospective Cohort Study Methods: A retrospective review identified patients who underwent autologous chondrocyte implantation (ACI) or osteochondral allograft (OCA) transplantation with concomitant medial patellofemoral ligament (MPFL) reconstruction and tibia tubercle osteotomy (TTO). Outcome measures included the Knee Injury and Osteoarthritis Outcome Score for Joint Replacement (KOOS JR), International Knee Documentation Committee (IKDC) evaluation, and Short Form Health Survey (SF-12) physical scores, all collected a minimum of 2 years after surgery. Defect location, size, complications, and rate of subsequent surgery were determined. Results: Eighteen patients (11 ACI and 7 OCA) were included in this study to analyze clinical and functional outcomes following surgical correction of 23 chondral defects (ACI n=12, OCA n=10). Defects had comparable baseline characteristics in each group including size measured during index arthroscopy (3.34 cm2 vs 4.03 cm2, P = .351), Outerbridge classification (54.8% grade 4 vs 60.0% grade 4, P = 1.000), and AMADEUS score (47.1 vs 58.6, P = .298). Postoperative outcomes were comparable including revision rate (15.4% vs 10.0%, P=1.000) and 2-year IKDC scores (74.2 vs 51.2, P = .077). However, ACI did have significantly higher 2-year KOOS JR (85.1 vs 63.7, P = .031) and SF-12 scores (54.1 vs 42.6, P = .007) compared to OCA. Conclusion: ACI or OCA transplantation for chondral defects with concomitant MPFL reconstruction and TTO can be safely performed in an outpatient setting with functional and clinical outcomes being comparable. Functional scores including KOOS JR and SF-12 were shown to be significantly higher at 2-year follow-up in the ACI cohort, however, postoperative IKDC scores, rates of revisions, and clinical evaluations were comparable between cohorts

Understanding the Impact of Product Characteristics on Groups’ Collaboration During a Dissection Task

Background: Experiential design opportunities are valuable for helping engineering students realize three-dimensional implications of theoretical concepts taught in the classroom. However, research on effective hands-on task design in the context of undergraduate group problem solving is relatively limited. While some tasks may include three-dimensional representation of task content, there is still much to be understood about how hands-on tasks influence students’ collaboration. Purpose/Hypothesis: To understand the impact of product characteristics on learning outcomes for undergraduate engineering students during a collaborative dissection task, we observed 16 students for collaboration quality as they worked in groups of four to reverse-engineer products through physical deconstruction and modeling in computer-aided design (CAD). Design/Method: We used a multiple-case study format to qualitatively analyze the groups. Ethnographic observations were recorded during three dissection sessions for each group. To understand groups’ experiences during the task, we coded our observations for behaviors that included collaborating versus going off-task, tendency to interact verbally, dividing into subgroups versus working as a whole group, and engaging in dissection and other physical interaction with the product. Results: We observed that dissection product characteristics impacted group collaboration, which in turn may have influenced the quality of their final modeling scores. These findings are supported by a positive relationship between participation in dissection and task scores. Conclusions: The study indicates that task products can impact the quality of collaboration and, in turn, students’ performance. More specifically, the nuances imposed by product characteristics can directly impact group interactions. Task products should be selected with attention to how characteristics may impact students’ opportunities to engage and interact

Consensus and meta-analysis regulatory networks for combining multiple microarray gene expression datasets

Microarray data is a key source of experimental data for modelling gene regulatory interactions from expression levels. With the rapid increase of publicly available microarray data comes the opportunity to produce regulatory network models based on multiple datasets. Such models are potentially more robust with greater confidence, and place less reliance on a single dataset. However, combining datasets directly can be difficult as experiments are often conducted on different microarray platforms, and in different laboratories leading to inherent biases in the data that are not always removed through pre-processing such as normalisation. In this paper we compare two frameworks for combining microarray datasets to model regulatory networks: pre- and post-learning aggregation. In pre-learning approaches, such as using simple scale-normalisation prior to the concatenation of datasets, a model is learnt from a combined dataset, whilst in post-learning aggregation individual models are learnt from each dataset and the models are combined. We present two novel approaches for post-learning aggregation, each based on aggregating high-level features of Bayesian network models that have been generated from different microarray expression datasets. Meta-analysis Bayesian networks are based on combining statistical confidences attached to network edges whilst Consensus Bayesian networks identify consistent network features across all datasets. We apply both approaches to multiple datasets from synthetic and real (Escherichia coli and yeast) networks and demonstrate that both methods can improve on networks learnt from a single dataset or an aggregated dataset formed using a standard scale-normalisation