The influence of core qualities of novice primary school teachers on their pedagogical practice.

Doctoral Degree. University of KwaZulu-Natal, Edgewood.This study explored the deployment of the core qualities of Novice Teachers in facing challenges within the Mauritian context. The main purpose of this study was to gain a deeper understanding of the role of core qualities in how the average novice teacher adapts to the challenges they encounter in their first year as credentialed primary school teachers. Research literature used in this study has indicated that although novice teachers are often unprepared to meet the contextual challenges they encounter, many still adapt and survive. This is contrary to most the literature on novice teachers which tends to portray them in negative terms. Korthagen’s core qualities derived from the field of positive psychology and the onion model proved useful in helping to understand how novice teachers adapt and survive their first year of practice as credentialed teachers. This research study was located within an interpretivist narrative inquiry design. Three novice teacher participants teaching in various schools were purposively selected for the study. All participants have studied for their professional qualification at the Mauritius Institute of Education. Given the exploratory nature of the study because little is known about core qualities, a qualitative research approach was used for the generation of data. This included conversational interviews with the participants which lasted over a period of three years. Data gathering produced narratives for each participant which were presented in first and third person to both capture the voices of the participants and also analyse their teaching practices using the analytics of the study namely the personal biography of the participants; the education experience of the participants in becoming a teacher; their teaching practices that illuminates the core qualities that they deploy in their teaching practices and their reflections on their teaching practices based on their interview processes. Analysis of the stories in the study identified three themes humanistic core qualities, much of which resonate with my theoretical framework that guided this study, professional core qualities that delve into the knowledge and training received in their training programme to become a teacher and contextual core qualities that I introduce as framing their teaching practices. Key findings that emerge from the analysis in the chapter reveal that because there is a disjuncture between being theoretically prepared to teach and the reality of the classroom, novice teachers default to three core qualities namely the humanistic core quality of empathy and compassion, the professional core qualities of knowledge and planning and contextual core qualities of regulatory frameworks that forces them to find alternate and more humane approaches to promote teaching and learning. Furthermore, the findings also reveal that the process followed by novice teachers in coping with their first teaching experience is reflection, going back to their basket of alternatives and adaptation of selected vi alternatives to their classroom context. Those finding are theorized with respect to the theoretical framework and pertinent literature and an evolutionary adaptation model is proposed

The effect of rapid cooling on the fat phase of chocolate

The aim of the project was to understand the science behind rapid cooling of chocolate used in the Frozen Cone® process. Differential scanning calorimetry was used to study the effect of slow and rapid cooling on tempered chocolate. On rapid cooling, lower melting polymorphs of cocoa butter were generated. Upon heating these recrystallised into the more stable Form V. Results were confirmed by similar observations with tempered chocolate fats. A hypothesis was formed whereby upon rapid cooling, lower melting polymorphs nucleate and grow at the expense of Form V nuclei produced during tempering. Upon subsequent warming, these polymorphs melt and recrystallise into Form V. Rapid cooling on untempered chocolate did not show any recrystallisation during warming; proving that tempering is required for the formation of Form V crystals in the final matrix. These results were confirmed by temperature-controlled X-ray diffraction on cocoa butter and chocolate fats. The polymorph generated upon rapid cooling was identified as Form I. This co-existed and eventually transformed to Form II and Form V upon warming. X-ray results showed that following rapid cooling, Form V crystals created during tempering did not grow until above 5 °C. Direct contact cooling at different temperatures was carried out to mimic the Frozen Cone® process. It was found that above -15 °C, the adhesion of the sample to the holder increases and seems to be correlated to the presence of Form II. These results suggest that the molecular structure and adhesive property of the polymorphs formed at specific temperatures are important for the release of chocolate. Stepscan differential scanning calorimetry was used to separate the simultaneous melting and recrystallisation events occurring in chocolate following slow and rapid cooling, by deconvoluting the total heat flow into reversing and non-reversing components. The general applicability and limitations of Stepscan DSC are also discussed

Differential regulation of amidase- and formamidase-mediated ammonia production by the Helicobacter pylori fur repressor.

The production of high levels of ammonia allows the human gastric pathogen Helicobacter pylori to survive the acidic conditions in the human stomach. H. pylori produces ammonia through urease-mediated degradation of urea, but it is also able to convert a range of amide substrates into ammonia via its AmiE amidase and AmiF formamidase enzymes. Here data are provided that demonstrate that the iron-responsive regulatory protein Fur directly and indirectly regulates the activity of the two H. pylori amidases. In contrast to other amidase-positive bacteria, amidase and formamidase enzyme activities were not induced by medium supplementation with their respective substrates, acrylamide and formamide. AmiE protein expression and amidase enzyme activity were iron-repressed in H. pylori 26695 but constitutive in the isogenic fur mutant. This regulation was mediated at the transcriptional level via the binding of Fur to the amiE promoter region. In contrast, formamidase enzyme activity was not iron-repressed but was significantly higher in the fur mutant. This effect was not mediated at the transcriptional level, and Fur did not bind to the amiF promoter region. These roles of Fur in regulation of the H. pylori amidases suggest that the H. pylori Fur regulator may have acquired extra functions to compensate for the absence of other regulatory systems

Development of Bioinformatics Infrastructure for Genomics Research in H3Africa

Background: Although pockets of bioinformatics excellence have developed in Africa, generally, large-scale genomic data analysis has been limited by the availability of expertise and infrastructure. H3ABioNet, a pan-African bioinformatics network, was established to build capacity specifically to enable H3Africa (Human Heredity and Health in Africa) researchers to analyze their data in Africa. Since the inception of the H3Africa initiative, H3ABioNet’s role has evolved in response to changing needs from the consortium and the African bioinformatics community. Objectives: H3ABioNet set out to develop core bioinformatics infrastructure and capacity for genomics research in various aspects of data collection, transfer, storage, and analysis. Methods and Results: Various resources have been developed to address genomic data management and analysis needs of H3Africa researchers and other scientific communities on the continent. NetMap was developed and used to build an accurate picture of network performance within Africa and between Africa and the rest of the world, and Globus Online has been rolled out to facilitate data transfer. A participant recruitment database was developed to monitor participant enrollment, and data is being harmonized through the use of ontologies and controlled vocabularies. The standardized metadata will be integrated to provide a search facility for H3Africa data and biospecimens. Because H3Africa projects are generating large-scale genomic data, facilities for analysis and interpretation are critical. H3ABioNet is implementing several data analysis platforms that provide a large range of bioinformatics tools or workflows, such as Galaxy, the Job Management System, and eBiokits. A set of reproducible, portable, and cloud-scalable pipelines to support the multiple H3Africa data types are also being developed and dockerized to enable execution on multiple computing infrastructures. In addition, new tools have been developed for analysis of the uniquely divergent African data and for downstream interpretation of prioritized variants. To provide support for these and other bioinformatics queries, an online bioinformatics helpdesk backed by broad consortium expertise has been established. Further support is provided by means of various modes of bioinformatics training. Conclusions: For the past 4 years, the development of infrastructure support and human capacity through H3ABioNet, have significantly contributed to the establishment of African scientific networks, data analysis facilities, and training programs. Here, we describe the infrastructure and how it has affected genomics and bioinformatics research in Africa

Endoscopic image analysis using Deep Convolutional GAN and traditional data

One big challenge encountered in the medical field is the availability of only limited annotated datasets for research. On the other hand, medical image annotation requires a lot of input from medical experts. It is noticed that machine learning and deep learning are producing better results in the area of image classification. However, these techniques require large training datasets, which is the major concern for medical image processing. Another issue is the unbalanced nature of the different classes of data, leading to the under-representation of some classes. Data augmentation has emerged as a good technique to deal with these challenges. In this work, we have applied traditional data augmentation and Generative Adversarial Network (GAN) on endoscopic esophagus images to increase the number of images for the training datasets. Eventually we have applied two deep learning models namely ResNet50 and VGG16 to extract and represent the relevant cancer features. The results show that the accuracy of the model increases with data augmentation and GAN. In fact, GAN has achieved the highest accuracy, that is, 94% over non-augmented training set and traditional data augmentation for VGG16

Development of an ensemble CNN model with explainable AI for the classification of gastrointestinal cancer

The implementation of AI assisted cancer detection systems in clinical environments has faced numerous hurdles, mainly because of the restricted explainability of their elemental mechanisms, even though such detection systems have proven to be highly effective. Medical practitioners are skeptical about adopting AI assisted diagnoses as due to the latter's inability to be transparent about decision making processes. In this respect, explainable artificial intelligence (XAI) has emerged to provide explanations for model predictions, thereby overcoming the computational black box problem associated with AI systems. In this particular research, the focal point has been the exploration of the Shapley additive explanations (SHAP) and local interpretable model-agnostic explanations (LIME) approaches which enable model prediction explanations. This study used an ensemble model consisting of three convolutional neural networks(CNN): InceptionV3, InceptionResNetV2 and VGG16, which was based on averaging techniques and by combining their respective predictions. These models were trained on the Kvasir dataset, which consists of pathological findings related to gastrointestinal cancer. An accuracy of 96.89% and F1-scores of 96.877% were attained by our ensemble model. Following the training of the ensemble model, we employed SHAP and LIME to analyze images from the three classes, aiming to provide explanations regarding the deterministic features influencing the model's predictions. The results obtained from this analysis demonstrated a positive and encouraging advancement in the exploration of XAI approaches, specifically in the context of gastrointestinal cancer detection within the healthcare domain

A Novel Competency Framework for Effective Mentoring

PCF10 Sub-theme: Inspiring Innovations [POSTER] // Mentoring is important for learner success. Effective mentoring requires the acquisition of specific and adequate competencies (knowledge, skills and dispositions) for mentors to perform their roles towards their mentees in a confident, coherent and consistent manner. However, our experiences have shown the existence of skills gaps and divergent mentoring practices across schools in the Mauritian context. // To address the shortcomings, we designed and developed a novel competency framework for mentoring that is part of a micro-credential for online learning and as capacity building initiative. The framework seeks to bring a shift in the way mentoring is practiced in Mauritius, with focus on reciprocal learning. // The mentoring competency framework (MCF) consists of four professional domains underpinned by six key drivers, namely, research, rethink, respond, re-align, revisit and reflect, which we consider as critical elements to inform effective mentoring practices. This poster describes each domain of the MCF. The first domain, Professional Identity, focuses on a commitment of mentors to engage with theories on mentoring and reflection on mentoring practices. The second one, Professional Knowledge and Skills, lays emphasis on subject-specific competencies. The third and fourth domains are Professional Relationships and Dispositions which highlight the importance of collaboration, communication, problem-solving, values and ethics. // Paper ID 919

Proposed minimum information guideline for kidney disease—research and clinical data reporting: a cross-sectional study

Objective This project aimed to develop and propose a standardised reporting guideline for kidney disease research and clinical data reporting, in order to improve kidney disease data quality and integrity, and combat challenges associated with the management and challenges of ‘Big Data’. Methods A list of recommendations was proposed for the reporting guideline based on the systematic review and consolidation of previously published data collection and reporting standards, including PhenX measures and Minimal Information about a Proteomics Experiment (MIAPE). Thereafter, these recommendations were reviewed by domain-specialists using an online survey, developed in Research Electronic Data Capture (REDCap). Following interpretation and consolidation of the survey results, the recommendations were mapped to existing ontologies using Zooma, Ontology Lookup Service and the Bioportal search engine. Additionally, an associated eXtensible Markup Language schema was created for the REDCap implementation to increase user friendliness and adoption. Results The online survey was completed by 53 respondents; the majority of respondents were dual clinician-researchers (57%), based in Australia (35%), Africa (33%) and North America (22%). Data elements within the reporting standard were identified as participant-level, study-level and experiment-level information, further subdivided into essential or optional information. Conclusion The reporting guideline is readily employable for kidney disease research projects, and also adaptable for clinical utility. The adoption of the reporting guideline in kidney disease research can increase data quality and the value for long-term preservation, ensuring researchers gain the maximum benefit from their collected and generated data. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial

Genomic Research Data Generation, Analysis and Sharing – Challenges in the African Setting

International audienceGenomics is the study of the genetic material that constitutes the genomes of organisms. This genetic material can be sequenced and it provides a powerful tool for the study of human, plant and animal evolutionary history and diseases. Genomics research is becoming increasingly commonplace due to significant advances in and reducing costs of technologies such as sequencing. This has led to new challenges including increasing cost and complexity of data. There is, therefore, an increasing need for computing infrastructure and skills to manage, store, analyze and interpret the data. In addition, there is a significant cost associated with recruitment of participants and collection and processing of biological samples, particularly for large human genetics studies on specific diseases. As a result, researchers are often reluctant to share the data due to the effort and associated cost. In Africa, where researchers are most commonly at the study recruitment, determination of phenotypes and collection of biological samples end of the genomic research spectrum, rather than the generation of genomic data, data sharing without adequate safeguards for the interests of the primary data generators is a concern. There are substantial ethical considerations in the sharing of human genomics data. The broad consent for data sharing preferred by genomics researchers and funders does not necessarily align with the expectations of researchers, research participants, legal authorities and bioethicists. In Africa, this is complicated by concerns about comprehension of genomics research studies, quality of research ethics reviews and understanding of the implications of broad consent, secondary analyses of shared data, return of results and incidental findings. Additional challenges with genomics research in Africa include the inability to transfer, store, process and analyze large-scale genomics data on the continent, because this requires highly specialized skills and expensive computing infrastructure which are often unavailable. Recently initiatives such as H3Africa and H3ABioNet which aim to build capacity for large-scale genomics projects in Africa have emerged. Here we describe such initiatives, including the challenges faced in the generation, analysis and sharing of genomic data and how these challenges are being overcome

Prospects for the Improvement of Energy Performance in Agroindustry Using Phase Change Materials

This work was partially supported by the Fundação para a Ciência e Tecnologia, UIDB/00066/2020 (CTS – Center of Technology and Systems).The use of Phase Change Materials (PCMs), able to store latent heat, represents an opportunity to improve energy efficiency in the agroindustry by means of thermal energy storage. PCMs provide higher energy density then sensible heat storage mediums, thus paving the way to multiple applications, like supporting the integration of renewables or allowing for new storage architectures, decentralized and directly installed in the chain production equipment, creating e.g. the opportunity to recover and value low-grade operational heat sub-products. Such new and decentralized architecture, not currently applied in agroindustry, is proposed in this work. A chocolate tempering machine using an organic PCM is conceived and analyzed using ANSYS Fluent software for computational fluid dynamics simulations, comparing the main aspects in the storage capacity and discharging process with a conventional sensitive heat storage solution that uses water. PCMs allows improving the stored energy, keeping the chocolate in the working temperature after being tempered for more than four times longer than using only hot water. If the PCMs are charged by renewables, the self-consumption ratio can be improved while providing energy flexibility to the user.authorsversionpublishe