Search results for: activity learning

Authors: Zarah M. Bello, Nathan Baddoo, Mariana Lilley, Paul Wernick

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In this paper, we present findings from a multi-part study to evaluate candidate elements reflecting the level of digital capability maturity (DCM) in higher education and the relationship between these elements. We will use these findings to propose a model of DCM for educational institutions. We suggest that the success of learning in higher education is dependent in part on the level of maturity of digital capabilities of institutions as well as the abilities of learners and those who support the learning process. It is therefore important to have a good understanding of the elements that underpin this maturity as well as their impact and interactions in order to better exploit the benefits that technology presents to the modern learning environment and support its continued improvement. Having identified ten candidate elements of digital capability that we believe support the level of a University’s maturity in this area as well as a number of relevant stakeholder roles, we conducted two studies utilizing both quantitative and qualitative research methods. In the first of these studies, 85 electronic questionnaires were completed by various stakeholders in a UK university, with a 100% response rate. We also undertook five in-depth interviews with management stakeholders in the same university. We then utilized statistical analysis to process the survey data and conducted a textual analysis of the interview transcripts. Our findings support our initial identification of candidate elements and support our contention that these elements interact in a multidimensional manner. This multidimensional dynamic suggests that any proposal for improvement in digital capability must reflect the interdependency and cross-sectional relationship of the elements that contribute to DCM. Our results also indicate that the notion of DCM is strongly data-centric and that any proposed maturity model must reflect the role of data in driving maturity and improvement. We present these findings as a key step towards the design of an operationalisable DCM maturity model for universities.

Keywords: digital capability, elements, maturity, maturity framework, university

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Authors: Manami Masuda, Mariko Era, Takayoshi Kawahara, Takahide Kanyama, Hiroshi Morita

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Objectives: Fatty acid salts are a type of anionic surfactant and are produced from fatty acids and alkali. Moreover, fatty acid salts are known to have potent antibacterial activities. Acanthamoeba is ubiquitously distributed in the environment including sea water, fresh water, soil and even from the air. Although generally free-living, Acanthamoeba can be an opportunistic pathogen, which could cause a potentially blinding corneal infection known as Acanthamoeba keratitis. So, in this study, we evaluated the anti-amoeba activity of fatty acid salts and fatty acids to Acanthamoeba castellanii ATCC 30010. Materials and Methods: The antibacterial activity of 9 fatty acid salts (potassium butyrate (C4K), caproate (C6K), caprylate (C8K), caprate (C10K), laurate (C12K), myristate (C14K), oleate (C18:1K), linoleate (C18:2K), linolenate (C18:3K)) tested on cells of Acanthamoeba castellanii ATCC 30010. Fatty acid salts (concentration of 175 mM and pH 10.5) were prepared by mixing the fatty acid with the appropriate amount of KOH. The amoeba suspension mixed with KOH with a pH adjusted solution was used as the control. Fatty acids (concentration of 175 mM) were prepared by mixing the fatty acid with Tween 80 (20 %). The amoeba suspension mixed with Tween 80 (20 %) was used as the control. The anti-amoeba method, the amoeba suspension (3.0 × 104 cells/ml trophozoites) was mixed with the sample of fatty acid potassium (final concentration of 175 mM). Samples were incubated at 30°C, for 10 min, 60 min, and 180 min and then the viability of A. castellanii was evaluated using plankton counting chamber and trypan blue stainings. The minimum inhibitory concentration (MIC) against Acanthamoeba was determined using the two-fold dilution method. The MIC was defined as the minimal anti-amoeba concentration that inhibited visible amoeba growth following incubation (180 min). Results: C8K, C10K, and C12K were the anti-amoeba effect of 4 log-unit (99.99 % growth suppression of A. castellanii) incubated time for 180 min against A. castellanii at 175mM. After the amoeba, the suspension was mixed with C10K or C12K, destroying the cell membrane had been observed. Whereas, the pH adjusted control solution did not exhibit any effect even after 180 min of incubation with A. castellanii. Moreover, C6, C8, and C18:3 were the anti-amoeba effect of 4 log-unit incubated time for 60 min. C4 and C18:2 exhibited a 4-log reduction after 180 min incubation. Furthermore, the minimum inhibitory concentration (MIC) was determined. The MIC of C10K, C12K and C4 were 2.7 mM. These results indicate that C10K, C12K and C4 have high anti-amoeba activity against A. castellanii and suggest C10K, C12K and C4 have great potential for antimi-amoeba agents.

Keywords: Fatty acid salts, anti-amoeba activities, Acanthamoeba, fatty acids

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Authors: Francesca Perri

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This paper describes a proposal for a teachers’ training course, focused on the introduction of corpora in the EFL didactics (English as a foreign language) of some Italian secondary schools. The training course is conceived as a part of a TEDD participant’s five months internship. TEDD (Technologies for Education: diversity and devices) is an advanced course held by the Department of Engineering and Information Technology at the University of Trento, Italy. Its main aim is to train a selected, heterogeneous group of graduates to engage with the complex interdependence between education and technology in modern society. The educational approach draws on a plural coexistence of various theories as well as socio-constructivism, constructionism, project-based learning and connectivism. TEDD educational model stands as the main reference source to the design of a formative course for EFL teachers, drawing on the digitalization of didactics and creation of learning interactive materials for L2 intermediate students. The training course lasts ten hours, organized into five sessions. In the first part (first and second session) a series of guided and semi-guided activities drive participants to familiarize with corpora through the use of a digital tools kit. Then, during the second part, participants are specifically involved in the realization of a ML (Mistakes Laboratory) where they create, develop and share digital activities according to their teaching goals with the use of corpora, supported by the digital facilitator. The training course takes place into an ICT laboratory where the teachers work either individually or in pairs, with a computer connected to a wi-fi connection, while the digital facilitator shares inputs, materials and digital assistance simultaneously on a whiteboard and on a digital platform where participants interact and work together both synchronically and diachronically. The adoption of good ICT practices is a fundamental step to promote the introduction and use of Corpus Linguistics in EFL teaching and learning processes, in fact dealing with corpora not only promotes L2 learners’ critical thinking and orienteering versus wild browsing when they are looking for ready-made translations or language usage samples, but it also entails becoming confident with digital tools and activities. The paper will explain reasons, limits and resources of the pedagogical approach adopted to engage EFL teachers with the use of corpora in their didactics through the promotion of digital practices.

Keywords: digital didactics, education, language learning, teacher training

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Authors: Ka Lei Au

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The Dalcroze method has been emerging in music classrooms, and music teachers are encouraged to integrate music and movement in their teaching. Music programs in colleges in Hong Kong have been introducing method courses such as Orff and Dalcroze method in music teaching as teacher’s education program. Since the targeted students of the course are music teachers who are making the decision of what approach to use in their classroom, their perception is significantly valued to identify how this approach is applicable in their teaching in regards to the teaching and learning culture and environment. This qualitative study aims to explore how the Dalcroze method as a teacher’s education course is perceived by music teachers from three aspects: 1) application in music teaching, 2) self-enhancement, 3) expectation. Through the lens of music teachers, data were collected from 30 music teachers who are taking the Dalcroze method course in music teaching in Hong Kong by the survey. The findings reveal the value and their intention of the Dalcroze method in Hong Kong. It also provides a significant reference for better development of such courses in the future in adaption to the culture, teaching and learning environment and teacher’s, student’s and parent’s perception of this approach.

Keywords: Dalcroze method, music teaching, perception, self-enhancement, teacher’s education

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Authors: Leah Ning

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This paper discusses the development of a machine learning algorithm that accurately detects metastatic breast cancer (cancer has spread elsewhere from its origin part) in selected images that come from pathology scans of lymph node sections. Being able to develop an accurate artificial intelligence (AI) algorithm would help significantly in breast cancer diagnosis since manual examination of lymph node scans is both tedious and oftentimes highly subjective. The usage of AI in the diagnosis process provides a much more straightforward, reliable, and efficient method for medical professionals and would enable faster diagnosis and, therefore, more immediate treatment. The overall approach used was to train a convolution neural network (CNN) based on a set of pathology scan data and use the trained model to binarily classify if a new scan were benign or malignant, outputting a 0 or a 1, respectively. The final model’s prediction accuracy is very high, with 100% for the train set and over 70% for the test set. Being able to have such high accuracy using an AI model is monumental in regard to medical pathology and cancer detection. Having AI as a new tool capable of quick detection will significantly help medical professionals and patients suffering from cancer.

Keywords: breast cancer detection, AI, machine learning, algorithm

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Authors: Bryan Young, Andrew Wodehouse, Marion Sheridan

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The availability of working memory has long been identified as a critical aspect of an instructional design. Many conventional instructional procedures impose irrelevant or unrelated cognitive loads on the learner due to the fact that they were created without contemplation, or understanding, of cognitive work load. Learning to physically operate traditional products can be viewed as a learning process akin to any other. As such, many of today's products, such as cars, boats, and planes, which have traditional controls that predate modern user-centered design techniques may be imposing irrelevant or unrelated cognitive loads on their operators. The goal of the research was to investigate the fundamental relationships between physical inputs, resulting actions, and learnability. The results showed that individuals can quickly adapt to input/output reversals across dimensions, however, individuals struggle to cope with the input/output when the dimensions are rotated due to the resulting increase in cognitive load.

Keywords: cognitive load theory, instructional design, physical product interactions, usability design

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Authors: Klaus Peter Scherer, Daniel Knöll, Constantin Rieder

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Problem and Purpose: Intelligent systems are available and helpful to support the human being decision process, especially when complex surgical eye interventions are necessary and must be performed. Normally, such a decision support system consists of a knowledge-based module, which is responsible for the real assistance power, given by an explanation and logical reasoning processes. The interview based acquisition and generation of the complex knowledge itself is very crucial, because there are different correlations between the complex parameters. So, in this project (semi)automated self-learning methods are researched and developed for an enhancement of the quality of such a decision support system. Methods: For ophthalmic data sets of real patients in a hospital, advanced data mining procedures seem to be very helpful. Especially subgroup analysis methods are developed, extended and used to analyze and find out the correlations and conditional dependencies between the structured patient data. After finding causal dependencies, a ranking must be performed for the generation of rule-based representations. For this, anonymous patient data are transformed into a special machine language format. The imported data are used as input for algorithms of conditioned probability methods to calculate the parameter distributions concerning a special given goal parameter. Results: In the field of knowledge discovery advanced methods and applications could be performed to produce operation and patient related correlations. So, new knowledge was generated by finding causal relations between the operational equipment, the medical instances and patient specific history by a dependency ranking process. After transformation in association rules logically based representations were available for the clinical experts to evaluate the new knowledge. The structured data sets take account of about 80 parameters as special characteristic features per patient. For different extended patient groups (100, 300, 500), as well one target value as well multi-target values were set for the subgroup analysis. So the newly generated hypotheses could be interpreted regarding the dependency or independency of patient number. Conclusions: The aim and the advantage of such a semi-automatically self-learning process are the extensions of the knowledge base by finding new parameter correlations. The discovered knowledge is transformed into association rules and serves as rule-based representation of the knowledge in the knowledge base. Even more, than one goal parameter of interest can be considered by the semi-automated learning process. With ranking procedures, the most strong premises and also conjunctive associated conditions can be found to conclude the interested goal parameter. So the knowledge, hidden in structured tables or lists can be extracted as rule-based representation. This is a real assistance power for the communication with the clinical experts.

Keywords: an expert system, knowledge-based support, ophthalmic decision support, self-learning methods

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Authors: Adria Rae Abigail R. Eda, Arvin C. Diesmos, Vance T. Vredenburg, Merab A. Chan

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Mitigating strategies using symbiotic cutaneous bacteria is one of the major concerns in the conservation of amphibian population. Batrachochytrium dendrobatidis is the causative agent of chytridiomycosis associated with mass mortality and amphibian extinctions worldwide. In the Philippines, there is a lack of study on the cutaneous bacteria of Philippine amphibians that may have beneficial effects to ward off the deadly fungal infection. In this study, cutaneous bacteria from frogs were isolated and examined for anti-B. dendrobatidis activity. Eight species of frogs were collected at Mt. Palay-palay Mataas na Gulod National Park in Cavite, a site positive for the presence of B. dendrobatidis. Bacteria were isolated from the skin of frogs by swabbing the surfaces of the body and inoculated in Reasoner´s 2A (R2A) agar. Isolated bacteria were tested for potential inhibitory properties against B. dendrobatidis through zoospore inhibition assay. Results showed that frog cutaneous bacteria significantly inhibited the growth of B. dendrobatidis in vitro. By means of 16S rRNA gene primers, the anti-B. dendrobatidis bacteria were identified to be Enterobacter sp., Alcaligenes faecalis and Pseudomonas sp. Cutaneous bacteria namely Enterobacter sp. (isolates PLd33 and PCv4) and Pseudomonas (isolate PLd31) remarkably cleared the growth of B. dendrobatidis zoospore in 1% tryptone agar. Therefore, frog cutaneous bacteria inhibited B. dendrobatidis in vitro and could possibly contribute to the immunity and defense of frogs against the lethal chytridiomycosis.

Keywords: Batrachochytrium dendrobatidis, cutaneous bacteria, frogs, zoospore inhibition assay

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Authors: Bhuyain Mobarok Hossain

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Image classification and localization research is currently an important strategy in the field of computer vision. The evolution and advancement of deep learning and convolutional neural networks (CNN) have greatly improved the capabilities of object detection and image-based classification. Target detection is important to research in the field of computer vision, especially in video surveillance systems. To solve this problem, we will be applying a convolutional neural network of multiple scales at multiple locations in the image in one sliding window. Most translation networks move away from the bounding box around the area of interest. In contrast to this architecture, we consider the problem to be a classification problem where each pixel of the image is a separate section. Image classification is the method of predicting an individual category or specifying by a shoal of data points. Image classification is a part of the classification problem, including any labels throughout the image. The image can be classified as a day or night shot. Or, likewise, images of cars and motorbikes will be automatically placed in their collection. The deep learning of image classification generally includes convolutional layers; the invention of it is referred to as a convolutional neural network (CNN).

Keywords: image classification, object detection, localization, particle filter

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Authors: Essam Mansour

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The key purpose of this study is to provide first-hand information about beggars in Egypt, especially from the perspective of their information seeking behaviour including their information needs. The researcher tries to investigate the information-seeking behaviour of Egyptian beggars with regard to their thoughts, perceptions, motivations, attitudes, habits, preferences as well as challenges that may impede their use of information. The research methods used were an adapted form of snowball sampling of a heterogeneous demographic group of participants in the beggary activity in Egypt. This sampling was used to select focus groups to explore a range of relevant issues. Data on the demographic characteristics of the Egyptian beggars showed that they tend to be men, mostly with no formal education, with an average age around 30s, labeled as low-income persons, mostly single and mostly Muslims. A large number of Egyptian beggars were seeking for information to meet their basic needs as well as their daily needs, although some of them were not able to identify their information needs clearly. The information-seeking behaviour profile of a very large number of Egyptian beggars indicated a preference for informal sources of information over formal ones to solve different problems and meet the challenges they face during their beggary activity depending on assistive devices, such as mobile phones. The high degree of illiteracy and the lack of awareness about the basic rights of information as well as information needs were the most important problems Egyptian beggars face during accessing information. The study recommended further research to be conducted about the role of the library in the education of beggars. It also recommended that beggars’ awareness about their information rights should be promoted through educational programs that help them value the role of information in their life.

Keywords: user studies, information-seeking behaviour, information needs, information sources, beggars, Egypt

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Authors: Hoa Pham

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The literature on language teaching and second language acquisition has been largely driven by monolingual ideology with a common assumption that a second language (L2) is best taught and learned in the L2 only. The current study challenges this assumption by reporting learners' positive perceptions of tertiary level teachers' code switching practices in Vietnam. The findings of this study contribute to our understanding of code switching practices in language classrooms from a learners' perspective. Data were collected from student participants who were working towards a Bachelor degree in English within the English for Business Communication stream through the use of focus group interviews. The literature has documented that this method of interviewing has a number of distinct advantages over individual student interviews. For instance, group interactions generated by focus groups create a more natural environment than that of an individual interview because they include a range of communicative processes in which each individual may influence or be influenced by others - as they are in their real life. The process of interaction provides the opportunity to obtain the meanings and answers to a problem that are "socially constructed rather than individually created" leading to the capture of real-life data. The distinct feature of group interaction offered by this technique makes it a powerful means of obtaining deeper and richer data than those from individual interviews. The data generated through this study were analysed using a constant comparative approach. Overall, the students expressed positive views of this practice indicating that it is a useful teaching strategy. Teacher code switching was seen as a learning resource and a source supporting language output. This practice was perceived to promote student comprehension and to aid the learning of content and target language knowledge. This practice was also believed to scaffold the students' language production in different contexts. However, the students indicated their preference for teacher code switching to be constrained, as extensive use was believed to negatively impact on their L2 learning and trigger cognitive reliance on the L1 for L2 learning. The students also perceived that when the L1 was used to a great extent, their ability to develop as autonomous learners was negatively impacted. This study found that teacher code switching was supported in certain contexts by learners, thus suggesting that there is a need for the widespread assumption about the monolingual teaching approach to be re-considered.

Keywords: codeswitching, L1 use, L2 teaching, learners’ perception

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Authors: Warda Khan, Remo Lachmann, Adarsh S. Garakahally

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The increasing complexity of software and its applicability in a wide range of industries, e.g., automotive, call for enhanced quality assurance techniques. Test automation is one option to tackle the prevailing challenges by supporting test engineers with fast, parallel, and repetitive test executions. A high degree of test automation allows for a shift from mundane (manual) testing tasks to a more analytical assessment of the software under test. However, a high initial investment of test resources is required to establish test automation, which is, in most cases, a limitation to the time constraints provided for quality assurance of complex software systems. Hence, a computer-aided creation of automated test cases is crucial to increase the benefit of test automation. This paper proposes the application of machine learning for the generation of automated test cases. It is based on supervised learning to analyze test specifications and existing test implementations. The analysis facilitates the identification of patterns between test steps and their implementation with test automation components. For the test case generation, this approach exploits historical data of test automation projects. The identified patterns are the foundation to predict the implementation of unknown test case specifications. Based on this support, a test engineer solely has to review and parameterize the test automation components instead of writing them manually, resulting in a significant time reduction for establishing test automation. Compared to other generation approaches, this ML-based solution can handle different writing styles, authors, application domains, and even languages. Furthermore, test automation tools require expert knowledge by means of programming skills, whereas this approach only requires historical data to generate test cases. The proposed solution is evaluated using various multi-label evaluation criteria (EC) and two small-sized real-world systems. The most prominent EC is ‘Subset Accuracy’. The promising results show an accuracy of at least 86% for test cases, where a 1:1 relationship (Multi-Class) between test step specification and test automation component exists. For complex multi-label problems, i.e., one test step can be implemented by several components, the prediction accuracy is still at 60%. It is better than the current state-of-the-art results. It is expected the prediction quality to increase for larger systems with respective historical data. Consequently, this technique facilitates the time reduction for establishing test automation and is thereby independent of the application domain and project. As a work in progress, the next steps are to investigate incremental and active learning as additions to increase the usability of this approach, e.g., in case labelled historical data is scarce.

Keywords: machine learning, multi-class, multi-label, supervised learning, test automation

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Authors: Shahed, Tala, Ahlam, Marah, Sara, Shaden

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Research on fear of crime has shown that there are many influences on it, including gender, age, and geographic location. For example, women are more afraid of crime than men. The campus has a high crime rate and fear of crime due to many hiding places and blind spots; women are more likely than men to be victims of certain types of crime, such as rape and verbal and sexual harassment. And it became clear that older female students have a different perception of the place over time and other knowledge and fear of it, another study at Hashemite University. This study aims to understand better how the environment affects the negative experiences of female students and how their age and familiarity environment affects their sense of safety. This study also examines whether CPTED can be used to help prevent crime. The Broken Windows Theory also states that crime occurs in areas with overt indications of criminal activity, antisocial behavior, and civil unrest. This is related to the principle of CPTED maintenance and monitoring, activity support, regional development, and access control. Given their increased vulnerability to harassment, “sexual harassment” can refer to different behaviors. On campuses, harassment was happening everywhere, but it was most prevalent in "blind spots" that were out of sight and deserted. This study uses a methodology based on quantitative data that depends on putting a number on the amount of a particular phenomenon that exists in the world. The main finding shows how CPTED works in an academic context and what adjustments need to be made.

Keywords: Hashmite University, CPTED, crime prevention, university campus, fear of crime, female faer, broken window theory

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Authors: R. L. Shirole, N. L. Shirole, R. B. Patil, M. N. Saraf

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The present investigation aimed to elucidate the probable mechanism of antiasthmatic action of essential oil of Pistacia integerrima J.L. Stewart ex Brandis galls (EOPI). EOPI was investigated for its potential antiasthmatic action using in vitro antiallergic assays mast cell degranulation and soyabean lipoxidase enzyme activit, and spasmolytic action using isolated guinea pig ileum preparation. In vivo studies included lipopolysaccharide-induced bronchial inflammation in rats and airway hyperresponsiveness in ovalbumin in sensitized guinea pigs using spirometry. Data was analysed by GraphPad Prism 5.01 and results were expressed as means ± SEM. P < 0.05 was considered to be significant. EOPI inhibits 5-lipoxidase enzyme activity, DPPH scavenging activity and erythropoietin- induced angiogenesis. It showed dose dependent anti-allergic activity by inhibiting compound 48/80 induced mast cell degranulation. The finding that essential oil induced inhibition of transient contraction of acetylcholine in calcium free medium, and relaxation of S-(-)-Bay 8644-precontracted isolated guinea pig ileum jointly suggest that suggesting that the L-subtype Cav channel is involved in spasmolytic action of EOPI. Treatment with EOPI dose dependently (7.5, 15 and 30 mg/kg i.p.) inhibited lipopolysaccharide- induced increased in total cell count, neutrophil count, nitrate-nitrite, total protein, albumin levels in bronchoalveolar fluid and myeloperoxidase levels in lung homogenates. Mild diffused lesions involving focal interalveolar septal, intraluminal infiltration of neutrophils were observed in EOPI (7.5 &15 mg/kg) pretreated while no abnormality was detected in EOPI (30 mg/kg) and roflumilast (1mg/kg) pretreated rats. Roflumilast was used as standard. EOPI reduced the respiratory flow due to gasping in ovalbumin sensitized guinea pigs. The study demonstrates the effectiveness of EOPI in bronchial asthma possibly related to its ability to inhibit L-subtype Cav channel, mast cell stabilization, antioxidant, angiostatic and through inhibition of 5-lipoxygenase enzyme.

Keywords: asthma, lipopolysaccharide, spirometry, Pistacia integerrima J.L. Stewart ex Brandis, essential oil

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Authors: Intan Azura Mokhtar, Yaacob Ibrahim

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In recent years, learning about sustainable development and sustainability has become an increasingly significant component in universities’ degree programmes and curricula. As the world comes together and races to fulfil the 17 United Nations’ sustainable development goals (SDGs) by the year 2030, our educational curricula and landscapes simultaneously evolve to integrate lessons and opportunities for sustainable development and sustainability to redefine our university education and set the trajectory for our young people to take the lead in co-creating solutions for a better world. In this paper, initiatives and projects that revolved around themes of sustainable development and sustainability in a young university in Singapore are discussed. These initiatives and projects were curated by a new centre in the university that focuses on community leadership, social innovation, and service learning and was led by the university’s academic staff. The university’s undergraduate students were also involved in these initiatives and projects and played an active role in reaching out to and engaging members of different segments of the community – to better understand their needs and concerns and to co-create with them relevant and sustainable solutions that generate positive social impact.

Keywords: singapore, sustainable development, sustainability, undergraduate education

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Authors: Dr. Luigi Iannacci

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This research critically explores the current educational landscape with respect to special education and dominant deficit/medical model discourses that continue to forward unresponsive problematic approaches to teaching students with disabilities. Asset-oriented perspectives and social/critical models of disability are defined and explicated in order to offer alternatives to these dominant discourses. To that end, a framework that draws on Brian Camborne’s conditions of learning and applications of his work in relation to instruction conceptualize learning conditions and their significance to students with special needs. Methodologically, the research is designed as Critical Narrative Inquiry (CNI). Critical incidents, interviews, documents, artefacts etc. are drawn on and narratively constructed to explore how disability is presently configured in language, discourses, pedagogies and interactions with students deemed disabled. This data was collected using ethnographic methods and as such, through participant-observer field work that occurred directly in classrooms. This narrative approach aims to make sense of complex classroom interactions and ways of reconceptualizing approaches to students with special needs. CNI is situated in the critical paradigm and primarily concerned with culture, language and participation as issues of power in need of critique with the intent of change in the direction of social justice. Research findings highlight the ways in which Cambourne’s learning conditions, such as demonstration, approximation, engagement, responsibility, immersion, expectation, employment (transfer, use), provide a clear understanding of what is central to and constitutes a responsive and inclusive this instructional frame. Examples of what each of these conditions look like in practice are therefore offered in order to concretely demonstrate the ways in which various pedagogical choices and questions can enable classroom spaces to be responsive to the assets and challenges students with special needs have and experience. These particular approaches are also illustrated through an exploration of multiliteracies theory and pedagogy and what this research and approach allows educators to draw on, facilitate and foster in terms of the ways in which students with special needs can make sense of and demonstrate their understanding of skills, content and knowledge. The contextual information, theory, research and instructional frame focused on throughout this inquiry ultimately demonstrate what inclusive classroom spaces and practice can look like. These perspectives and conceptualizations are in stark contrast to dominant deficit driven approaches that ensure current pedagogically impoverished teaching focused on narrow, limited and limiting understandings of special needs learners and their ways of knowing and acquiring/demonstrating knowledge.

Keywords: asset-oriented approach, social/critical model of disability, conditions for learning and teaching, students with special needs

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Authors: Stefano Zappacosta, Cristiano Bove, Maria Carmela Marinelli, Paola di Lauro, Katarina Spasenovic, Lorenzo Ostano, Giuseppe Aiello, Marco Pietrosanto

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This paper proposes a novel neural network approach for assessing flood hazard mapping. The core of the model is a machine learning component fed by frequency ratios, namely statistical correlations between flood event occurrences and a selected number of topographic properties. The proposed hybrid model can be used to classify four different increasing levels of hazard. The classification capability was compared with the flood hazard mapping River Basin Plans (PAI) designed by the Italian Institute for Environmental Research and Defence, ISPRA (Istituto Superiore per la Protezione e la Ricerca Ambientale). The study area of Piemonte, an Italian region, has been considered without loss of generality. The frequency ratios may be used as a standalone block to model the flood hazard mapping. Nevertheless, the mixture with a neural network improves the classification power of several percentage points, and may be proposed as a basic tool to model the flood hazard map in a wider scope.

Keywords: flood modeling, hazard map, neural networks, hydrogeological risk, flood risk assessment

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Authors: Muhammad Abdul Latif, Edijanti Goenarwo , Intan Rahmania Eka

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Diarrhea is one of the leading causes of morbidity and mortality in many countries, as well as responsible for the deaths of millions of people each year. Previous research showed that the leaves, bark, and root bark of kedondong contains saponins, tannins, and flavonoids. Tannins have anti-diarrheal effects that work as the freeze of protein / astrigen, and may inhibit the secretion of chloride over the tannate bonding between protein in the intestines. Chemical compounds of flavonoids also have an effect as anti-diarrheal block receptors Cl ˉ in intestinal thus reducing the secretion of Cl ˉ to the intestinal lume. This research aims to know the anti-diarrheal activity of extracts kedondong leaf in mice Balb/C strain males in vivo. This research also proves kedondong leaves as an anti-diarrhea through trial efficacy of kedondong leaves as antisekretori and antimotilitas. This research using post-test only controlled group design. Analysis of statistical data normality and homogenity were tested by Kolmogorov Smirnov. If the data obtained homogenous then using ANOVA test. This research using ethanolic extracts kedondong leaf 200, 400 and 800 mg/kg BW to prove there is anti-motility became five treatment groups. The result showed dose of ethanolic extracts kedondong leaf 800 mg/kg BW have significant value (p < 0.005). The conclusion from this extracts kedondong leaf research 800 mg/kg BW have pharmacological effects as antimotility on Balb/C strain male mice.

Keywords: anti-diarrhea, anti-motility, castrol oil, kedondong leaf

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Authors: Abdul Karim Zulkarnain, Marchaban, Subagus Wahyono, Ratna Asmah Susidarti

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Mahkota Dewa contains phalerin which has activity as sun screen. In this study, 13 formulations of cream oil in water (o/w) were prepared and tested for their physical characteristics. The physical characteristics were then used for determining the optimum formula. This study aimed to explore the physical stability of optimized formulation of cream, its sun protecting factor (SPF) values using in vitro and in vivo tests. The optimum formula of o/w cream were prepared based on Simplex Lattice Design (LSD) method using software Design Expert®. The formulation of o/w cream were varied based on the proportion of cetyl alcohol, mineral oil and tween 80. The difference of physical characteristic of optimum and predicted formula was tested using t-test with significant level of 95%. The optimum formula of o/w cream was the formula which consists of cetyl alcohol 9.71%, mineral oil, 29%, and tween 80 3.29. Based on t-test, there was no significant difference of physical characteristics of optimum and predicted formulation. Viscosity, spread power, adhesive power, and separation volume ratio of o/w at week 0-4 were relatively stable. The o/w creams were relatively stable at extreme temperature. The o/w creams from mahkota dewa, phalerin, and benzophenone have SPF values of 21.32, 33.12, and 42.49, respectively. The formulas did not irritate the skin based on in vivo test.

Keywords: cream, stability, In vitro, In vivo

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Authors: Slava Kalyuga, Sujanya Sombatteera

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In multimedia learning, written text is often transformed into spoken (narrated) text. This transient information may overwhelm limited processing capacity of working memory and inhibit learning instead of improving it. The paper reviews recent empirical studies in modality and verbal redundancy effects within a cognitive load framework and outlines conditions under which negative effects of transiency may occur. According to the modality effect, textual information accompanying pictures should be presented in an auditory rather than visual form in order to engage two available channels of working memory – auditory and visual - instead of only one of them. However, some studies failed to replicate the modality effect and found differences opposite to those expected. Also, according to the multimedia redundancy effect, the same information should not be presented simultaneously in different modalities to avoid unnecessary cognitive load imposed by the integration of redundant sources of information. However, a few studies failed to replicate the multimedia redundancy effect too. Transiency of information is used to explain these controversial results.

Keywords: cognitive load, transient information, modality effect, verbal redundancy effect

Procedia PDF Downloads 367

Authors: Amtul Jamil Sami

Abstract:

Apis mellifera is an insect of immense economic importance lives on rich carbohydrate diet including cellulose, nectar, honey and pollen. The carbohydrate metabolism in A mellifera has not been understood fully, as there are no data available, on the functional expression of cellulase gene. The cellulose hydrolyzing enzyme is required for the digestion of pollen cellulose wall, to release the important nutrients (amino acids, minerals, vitamins etc.) from the pollen. A dissection of Apis genome had revealed that there is one gene present for the expression of endo-beta-1,4-glucanase, for cellulose hydrolysis. In the presented work, functional expression of endo-beta-1,4 glucanase gene is reported. Total soluble proteins of the honey bee were isolated and were tested cellulose hydrolyzing enzyme activity, using carboxy-methyl cellulose, as a substrate. A mellifera proteins were able to hydrolyze carboxy-methyl cellulose, confirming its endo- type mode of action. Endo beta-1,4 glucanase enzyme was only present in the gut tissues, no activity was detected in the salivary glands. The pH optima of the enzyme were in the acidic pH range of 4-5-5-0, indicating its metabolic role in the acidic stomach of A mellifera. The reported enzyme is unique, as endo-beta- 1,4 glucanase was able to generate non reducing sugar, as an end product. The results presented, are supportive to the information that the honey bee is capable of producing its novel endo-beta-1,4 glucanase. Further it could be helpful, in understanding, the carbohydrate metabolism in A mellifera.

Keywords: honey bees, Endo-beta 1, 4- glucanase, Apis mellifera, functional expression

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Authors: H. Minor-Pérez, A. M. Mota-Silva, S. Ortiz-Barrios

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Substances of vegetable origin with antioxidant capacity have a high potential for application on the conservation of some foods, can prevent or reduce for example oxidation of lipids. However a food is a complex system whose wide variety of components wich can reduce or eliminate this antioxidant capacity. The antioxidant activity can be determined with the ABTS technique. The radical ABTS+ is generated from the acid 2, 2´ - Azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS). This radical is a composite color bluish-green, stable and with a spectrum of absorption into the UV-visible. The addition of antioxidants causes discoloration, value that can be reported as a percentage of inhibition of the cation radical ABTS+. The objective of this study was evaluated the effect of the combination of the pH and the essential oil of cinnamon (EOC) on inhibition of the radical ABTS+, using statistical design of central point (Design Expert) to obtain mathematical models that describe this phenomenon. Were evaluated 17 treatments with combinations of pH 5, 6 and 7 (citrate-phosphate buffer) and the concentration of essential oil of cinnamon (C): 0 µg/mL, 100 µg/mL and 200 µg/mL. The samples were analyzed using the ABTS technique. The reagent was dissolved in methanol 80% to standardized the absorbance to 0.7 +/- 0.1 at 754 nm. Then samples were mixed with reagent standardized ABTS and after 1 min and 7 min absorbance was read for each treatment at 754 nm. Was used a curve pattern with vitamin C and reported the values as inhibition (%) of radical ABTS+. The statistical analysis shows the experimental results were adjusted to a quadratic model, to the times of 1 min and 7 min. This model describes the influence of the factors investigated independently: pH and cinnamon essential oil (µg/mL) and the effect of the interaction between pH*C, as well as the square of the pH2 and C2. The model obtained was Y = 10.33684 - 3.98118*pH + 1.17031*C + 0.62745*pH2 - 3.26675*10-3*C2 - 0.013112*pH*C, where Y is the response variable. The coefficient of determination was 0.9949 for 1 min. The equation was obtained at 7 min and = - 10.89710 + 1.52341*pH + 1.32892*C + 0.47953*pH2 - 3.56605*10- *C2 - 0.034687*pH*C. The coefficient of determination was 0.9970. This means that only 1% of the total variation is not explained by the developed models. At 100 µg/mL of EOC was obtained an inhibition percentage of 80%, 84% and 97% for the pH values of 5,6 and 7 respectively, while a value of 200 µg/mL the inhibition (%) was very similar for the treatments. In these values of pH was obtained an inhibition close 97%. In conclusion the pH does not have a significant effect on the antioxidant capacity, while the concentration of EOC was decisive for the antioxidant capacity. The authors acknowledge the funding provided by the CONACYT for the project 131998.

Keywords: antioxidant activity, ABTS technique, essential oil of cinnamon, mathematical models

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Authors: Tiah Rachmatiah, Subaryanti

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Plants of Lauraceae family are known to contain many chemical compounds which have potential bioactivity such as alkaloids, flavonoids, lactones, terpenes, etc. Actinodaphne macrophylla and Nectandra angustifolia are two species from Lauraceae. A previous study on the crude alkaloidal extract from the bark of Act. macrophylla and n-hexane extract from the bark of N. angustifolia showed antiplasmodial activity against Plasmodium falciparum. The study was continued to find antiplasmodial active compounds from the two extracts. The materials were obtained from Bogor Botanical Garden, West Java, Indonesia. Crude alkaloidal extract of Act. macrophylla was prepared by maceration in dichloromethane after moistened with NH4OH 25% and n-hexane extract of N. angustifolia was prepared by maceration in n-hexane. A major compound was isolated by column chromatography using silica gel and a mixture of CH2Cl2 and methanol as a gradient solvent system for the alkaloidal extract and mixture of n-hexane and ethyl acetate for n-hexane extract. Fine white needle crystals were obtained from the alkaloidal extract and rod crystals from n-hexane extract. Molecular structure of the compounds was determined by analysis of spectra of NMR, IR, MS and compared by references. In vitro bioactivity test of the compound was performed against Plasmodium falciparum. The results showed that the bark of Act. macrophylla contained an aporphine alkaloid, actinodaphnine, that had activity against P. falciparum with IC50 value of 0.095 µg/mL and the bark of N. angustifolia contained a lignan compound, sesamine, with IC50 of 0.122 µg/mL.

Keywords: actinodaphne macrophylla, alkaloid, antiplasmodial, lauraceae, lignan, nectandra angustifolia

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Authors: Patsara Sirikamonsin, Sathapath Kilaso

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This research aims to study the media and information demand for public relations in Salaya, Nakhonpathom. The research objectives are: 1. to research on conflicts of communication and seeking solutions and improvements of media information in Salaya, Nakhonpathom; 2. to study about opinions and demand for media information to reach out the improvements of people communications among Salaya, Nakhonpathom; 3. to explore the factors related to relationship and behaviors on obtaining media information for public relations among Salaya, Nakhonpathom. The research is conducted by questionnaire which is interpreted by statistical analysis concluding with analysis, frequency, percentage, average and standard deviations. The research results demonstrate: 1. The conflicts of communications among Salaya, Nakhonpathom are lacking equipment and technological knowledge and public relations. 2. Most people have demand on media improvements for vastly broadcasting public relations in order to nourish the social values. This research intentionally is to create the infographic media which are easily accessible, uncomplicated and popular, in the present.

Keywords: media and information, the public relation printed media, local learning resource

Procedia PDF Downloads 143

Authors: Shazia Mannan, Zunera Khalid, Hammad-Ul-Mubeen

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Wingless type Mouse mammary tumor virus (MMTV) Integration site-10B (Wnt10B) is an important member of the Wnt protein family that functions as cellular messenger in paracrine manner. Aberrant Wnt10B activity is the cause of several abnormalities including cancers of breast, cervix, liver, gastric tract, esophagus, pancreas as well as physiological problems like obesity, and osteoporosis. The objective of this study was to determine the possible inhibitors against aberrant expression of Wnt10B in order to prevent and treat the physiological disorders associated with it. Wnt10B3D structure was predicted by using comparative modeling and then analyzed by PROCHECK, Verify3D, and Errat. The model having 84.54% quality value was selected and acylated to satisfy the hydrophobic nature of Wnt10B. For search of inhibitors, virtual screening was performed on Natural Products (NP) database. The compounds were filtered and ligand-based screening was performed using the antagonist for mouse Wnt-3A. This resulted in a library of 272 unique compounds having most potent drug like activities for Wnt-4. Out of the 271 molecules analyzed three small molecules ZINC35442871, ZINC85876388, and ZINC00754234 having activity against Wnt4 abbarent expression were found common through docking experiment of Wnt10B. It is concluded that the three molecules ZINC35442871, ZINC85876388, and ZINC00754234 can be considered as lead compounds for performing further drug designing experiments against aberrant Wnt expressions.

Keywords: Wnt10B inhibitors, comparative computational studies, proto-oncogene, molecular docking

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Authors: Theoni Soublis

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The COVID-19 pandemic created a severe interruption in teaching and learning in K-12 schools. It is essential that educational researchers, teachers, and administrators understand the long term effects that COVID-19 had on a variety of stakeholders in education. This investigation aims to analyze the research since the beginning of the pandemic that focuses specifically on teacher retention, resilience, and training. The results of this investigation will help to inform future research in order to better understand how the institution of education can continue to be prepared and to better prepare for future significant shifts in the modalities of instruction. The results of this analysis will directly impact the field of education as it will broaden the scope of understanding regarding how COVID- 19 impacted teaching and learning. The themes that will emerge from the data analysis will directly inform policy makers, administrators, and researchers about how to best implement training and curriculum design in order to support teacher effectiveness this in the classroom. Educational researchers have written about how teacher morale plummeted and how many teachers reported early burnout and higher stress levels. Teachers’ stress and anxiety soared during the COVID-19 pandemic, but so has their resilience and dedication to the field of education. This research aims to understand how public-school teachers overcame teaching obstacles presented to them during COVID-19. Research has been conducted to identify a variety of information regarding the impact the pandemic has had on K-12 teachers, students, and families. This research aims to understand how teachers continued to pursue their teaching objectives without significant training of effective online instruction methods. Not many educators even heard of the video conferencing platform Zoom before the spring of 2020. Researchers are interested in understanding how teachers used their expertise, prior knowledge, and training to institute immediate and effective online learning environments, what types of relationships did teachers build with students while teaching 100% remotely, and how did relationships change with students while teaching remotely? Furthermore, did the teacher-student relationship propel teacher resolve to be successful while teaching during a pandemic. Recent world events have significantly impacted the field of public-school teaching. The pandemic forced teachers to shift their paradigm about how to maintain high academic expectations, meet state curriculum standards, and assess students learning gains to make data-informed decisions while simultaneously adapting modes of instruction through multiple outlets with little to no training on remote, synchronous, asynchronous, virtual, and hybrid teaching. While it would be very interesting to study how teaching positively impacted students learning during the pandemic, I am more interested in understanding how teaches stayed the course and maintained their mental health while dealing with the stress and pressure of teaching during COVID-19.

Keywords: teacher retention, COVID-19, teacher education, teacher moral

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Authors: Rosa Tsegaye Aga, Xuan Jiang, Pavel Vazquez Faci, Siqing Liu, Simon Rayner, Endalkachew Alemu, Markos Abebe

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Tuberculosis (TB) is a major cause of disease globally. In most cases, TB is treatable and curable, but only with the proper treatment. There is a time when drug-resistant TB occurs when bacteria become resistant to the drugs that are used to treat TB. Current strategies to identify drug-resistant TB bacteria are laboratory-based, and it takes a longer time to identify the drug-resistant bacteria and treat the patient accordingly. But machine learning (ML) and data science approaches can offer new approaches to the problem. In this study, we propose to develop an ML-based model to predict the antibiotic resistance phenotypes of TB isolates in minutes and give the right treatment to the patient immediately. The study has been using the whole genome sequence (WGS) of TB isolates as training data that have been extracted from the NCBI repository and contain different countries’ samples to build the ML models. The reason that different countries’ samples have been included is to generalize the large group of TB isolates from different regions in the world. This supports the model to train different behaviors of the TB bacteria and makes the model robust. The model training has been considering three pieces of information that have been extracted from the WGS data to train the model. These are all variants that have been found within the candidate genes (F1), predetermined resistance-associated variants (F2), and only resistance-associated gene information for the particular drug. Two major datasets have been constructed using these three information. F1 and F2 information have been considered as two independent datasets, and the third information is used as a class to label the two datasets. Five machine learning algorithms have been considered to train the model. These are Support Vector Machine (SVM), Random forest (RF), Logistic regression (LR), Gradient Boosting, and Ada boost algorithms. The models have been trained on the datasets F1, F2, and F1F2 that is the F1 and the F2 dataset merged. Additionally, an ensemble approach has been used to train the model. The ensemble approach has been considered to run F1 and F2 datasets on gradient boosting algorithm and use the output as one dataset that is called F1F2 ensemble dataset and train a model using this dataset on the five algorithms. As the experiment shows, the ensemble approach model that has been trained on the Gradient Boosting algorithm outperformed the rest of the models. In conclusion, this study suggests the ensemble approach, that is, the RF + Gradient boosting model, to predict the antibiotic resistance phenotypes of TB isolates by outperforming the rest of the models.

Keywords: machine learning, MTB, WGS, drug resistant TB

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Authors: D. Nagalakshmi, S. Parashuramulu K. Sadasiva Rao, G. Aruna, L. Vikram

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The zinc (Zn) is the second most abundant trace element in mammals and birds, forming structural component of over 300 enzymes, playing an important role in anti-oxidant defense, immune response and reproduction. Organic trace minerals are more readily absorbed from the digestive tract and more biologically available compared with its inorganic salt. Thus, the present study was undertaken on 60 adult female Sprague Dawley rats (275±2.04 g) for experimental duration of 12 weeks to investigate the effect of dietary Zn supplementation from various organic sources on immunity, reproduction, oxidative defense mechanism and blood biochemical profile. The rats were randomly allotted to 30 replicates (2 per replicate) which were in turn randomly allotted to 5 dietary treatments varying in Zn source i.e., one inorganic source (Zn carbonate) and 4 organic sources (Zn-proteinate, Zn-propionate, Zn-amino acid complex and Zn-methionine) so as to supply NRC recommended Zn concentration (12 ppm Zn). Supplementation of organic Zn had no effect on various haematological and serum biochemical constituents compared to inorganic Zn fed rats. The TBARS and protein carbonyls concentration in liver indicative of oxidative stress was comparable between various organic and inorganic groups. The glutathione reductase activity in haemolysate (P<0.05) and reduced glutathione concentration in liver (P<0.01) was higher when fed organic Zn and RBC catalase activity was higher (P<0.01) on Zn methionine compared to other organic sources tested and the inorganic source. The humoral immune response assessed as antibody titres against sheep RBC was higher (P<0.05) when fed organic sources of zinc compared to inorganic source. The cell mediated immune response expressed as delayed type hypersensitivity reaction was higher (P<0.05) in rats fed Zn propionate with no effect of other organic Zn sources. The serum progesterone concentration was higher (P<0.05) in rats fed organic Zn sources compared to inorganic zinc. The data on ovarian folliculogenesis indicated that organic Zn supplementation increased (P<0.05) the number of graafian follicles and corpus luteum with no effect on primary, secondary and tertiary follicle number. The study indicated that rats fed organic sources of Zn had higher antioxidant enzyme activities, immune response and serum progesterone concentration with higher number of mature follicles. Though the effect of feeding various organic sources were comparable, rats fed zinc methionine had higher antioxidant activity and cell mediated immune response was higher in rats on Zn propionate.

Keywords: organic zinc, immune, rats, reproductive

Procedia PDF Downloads 273

Authors: Maja S. Todorovic

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This paper aims to promote entrepreneurial storytelling by exploring new ideas and learning practices. An entrepreneur needs to be a ‘storyteller’, an ‘epic hero’, capable of offering an emotional connection to his audience, a character with whom audience can identify with, rejoice, suffer, celebrate, fail – simply experience everything. In other words, a successful entrepreneur is giving tangible experience through his business story and that’s what makes his story and business alive. Use of mythology, eulogy, metaphor, epic, fairytales and cartoons, permeated with humor and sudden twists is a winning recipe for a business story that captures attention. In the business case of the Greenesignit! Card game, (educational and brainstorming tool for development of sustainable products) we will demonstrate how an entrepreneur successfully used visual narrative to communicate his story and at the same time as a vehicle to transmute his message in learning tool and product development.

Keywords: animating narrative, entrepreneur, Greeneisgnit! card game, visual storytelling

Procedia PDF Downloads 379

Authors: Minh Huynh, Aaron Heuser, Luke Patterson, Chris Zhang, Mason Miller, Daniel Wang, Sandeep Shetty, Mike Trinh, Abigail Miller, Adaeze Enekwechi, Tenille Daniels, Lu Huynh

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Machine learning and text analytics have been used to analyze child abuse, cyberbullying, domestic abuse and domestic violence, and hate speech. However, to the authors’ knowledge, no research to date has used these methods to study elder abuse in nursing homes or skilled nursing facilities from field inspection reports. We used machine learning and text analytics methods to analyze 356,000 inspection reports, which have been extracted from CMS Form-2567 field inspections of US nursing homes and skilled nursing facilities between 2016 and 2021. Our algorithm detected occurrences of the various types of abuse, including physical abuse, psychological abuse, verbal abuse, sexual abuse, and passive and active neglect. For example, to detect physical abuse, our algorithms search for combinations or phrases and words suggesting willful infliction of damage (hitting, pinching or burning, tethering, tying), or consciously ignoring an emergency. To detect occurrences of elder neglect, our algorithm looks for combinations or phrases and words suggesting both passive neglect (neglecting vital needs, allowing malnutrition and dehydration, allowing decubiti, deprivation of information, limitation of freedom, negligence toward safety precautions) and active neglect (intimidation and name-calling, tying the victim up to prevent falls without consent, consciously ignoring an emergency, not calling a physician in spite of indication, stopping important treatments, failure to provide essential care, deprivation of nourishment, leaving a person alone for an inappropriate amount of time, excessive demands in a situation of care). We further compare the prevalence of abuse before and after Covid-19 related restrictions on nursing home visits. We also identified the facilities with the most number of cases of abuse with no abuse facilities within a 25-mile radius as most likely candidates for additional inspections. We also built an interactive display to visualize the location of these facilities.

Keywords: machine learning, text analytics, elder abuse, elder neglect, nursing home abuse

Procedia PDF Downloads 134