Search results for: young children with learning disabilities
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 11517

Search results for: young children with learning disabilities

6357 The Role of Rapid Maxillary Expansion in Managing Obstructive Sleep Apnea in Children: A Literature Review

Authors: Suleman Maliha, Suleman Sidra

Abstract:

Obstructive sleep apnea (OSA) is a sleep disorder that can result in behavioral and psychomotor impairments in children. The classical treatment modalities for OSA have been continuous positive airway pressure and adenotonsillectomy. However, orthodontic intervention through rapid maxillary expansion (RME) has also been commonly used to manage skeletal transverse maxillary discrepancies. Aim and objectives: The aim of this study is to determine the efficacy of rapid maxillary expansion in paediatric patients with obstructive sleep apnea by assessing pre and post-treatment mean apnea-hypopnea index (AHI) and oxygen saturations. Methodology: Literature was identified through a rigorous search of the Embase, Pubmed, and CINAHL databases. Articles published from 2012 onwards were selected. The inclusion criteria consisted of patients aged 18 years and under with no systemic disease, adenotonsillar surgery, or hypertrophy who are undergoing RME with AHI measurements before and after treatment. In total, six suitable papers were identified. Results: Three studies assessed patients pre and post-RME at 12 months. The first study consisted of 15 patients with an average age of 7.5 years. Following treatment, they found that RME resulted in both higher oxygen saturations (+ 5.3%) and improved AHI (- 4.2 events). The second study assessed 11 patients aged 5–8 years and also noted improvements, with mean AHI reduction from 6.1 to 2.4 and oxygen saturations increasing from 93.1% to 96.8%. The third study reviewed 14 patients aged 6–9 years and similarly found an AHI reduction from 5.7 to 4.4 and an oxygen saturation increase from 89.8% to 95.5%. All modifications noted in these studies were statistically significant. A long-term study reviewed 23 patients aged 6–12 years post-RME treatment on an annual basis for 12 years. They found that the mean AHI reduced from 12.2 to 0.4, with improved oxygen saturations from 78.9% to 95.1%. Another study assessed 19 patients aged 9-12 years at two months into RME and four months post-treatment. Improvements were also noted at both stages, with an overall reduction of the mean AHI from 16.3 to 0.8 and an overall increase in oxygen saturations from 77.9% to 95.4%. The final study assessed 26 children aged 7-11 years on completion of individual treatment and found an AHI reduction from 6.9 to 5.3. However, the oxygen saturation remained stagnant at 96.0%, but this was not clinically significant. Conclusion: Overall, the current evidence suggests that RME is a promising treatment option for paediatric patients with OSA. It can provide efficient and conservative treatment; however, early diagnosis is crucial. As there are various factors that could be contributing to OSA, it is important that each case is treated on its individual merits. Going forward, there is a need for more randomized control trials with larger cohorts being studied. Research into the long-term effects of RME and potential relapse amongst cases would also be useful.

Keywords: orthodontics, sleep apnea, maxillary expansion, review

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6356 Factors Impeding Learners’ Use of the Blackboard System in Kingdom of Saudi Arabia

Authors: Omran Alharbi, Victor Lally

Abstract:

In recent decades, a number of educational institutions around the world have come to depend on technology such as the Blackboard system to improve their educational environment. On the other hand, there are many factors that delay the usage of this technology, especially in developing nations such as Saudi Arabia. The goal of this study was to investigate learner’s views of the use of Blackboard in one Saudi university in order to gain a comprehensive view of the factors that delay the implementation of technology in Saudi institutions. This study utilizes a qualitative approach, with data being collected through semi-structured interviews. Six participants from different disciplines took part in this study. The findings indicated that there are two levels of factors that affect students’ use of the Blackboard system. These are factors at the institutional level, such as lack of technical support and lack of training support, which lead to insufficient training related to the Blackboard system. The second level of factors is at the individual level, for example, a lack of teacher motivation and encouragement. In addition, students do not have sufficient levels of skills or knowledge related to how to use the Blackboard in their learning. Conclusion: learners confronted and faced two main types of factors (at the institution level and individual level) that delayed and impeded their learning. Institutions in KSA should take steps and implement strategies to remove or reduce these factors in order to allow students to benefit from the latest technology in their learning.

Keywords: blackboard, factors, KSA, learners

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6355 Undernutrition Among Children Below Five Years of Age in Uganda: A Deep Dive into Space and Time

Authors: Vallence Ngabo Maniragaba

Abstract:

This study aimed at examining the variations of undernutrition among children below 5 years of age in Uganda. The approach of spatial and spatiotemporal analysis helped in identifying cluster patterns, hot spots and emerging hot spots. Data from the 6 Uganda Demographic and Health Surveys spanning from 1990 to 2016 were used with the main outcome variable being undernutrition among children <5 years of age. All data that were relevant to this study were retrieved from the survey datasets and combined with the 214 shape files for the districts of Uganda to enable spatial and spatiotemporal analysis. Spatial maps with the spatial distribution of the prevalence of undernutrition, both in space and time, were generated using ArcGIS Pro version 2.8. Moran’s I, an index of spatial autocorrelation, rules out doubts of spatial randomness in order to identify spatially clustered patterns of hot or cold spot areas. Furthermore, space-time cubes were generated to establish the trend in undernutrition as well as to mirror its variations over time and across Uganda. Moreover, emerging hot spot analysis was done to help identify the patterns of undernutrition over time. The results indicate a heterogeneous distribution of undernutrition across Uganda and the same variations were also evident over time. Moran’s I index confirmed spatial clustered patterns as opposed to random distributions of undernutrition prevalence. Four hot spot areas, namely; the Karamoja, the Sebei, the West Nile and the Toro regions were significantly evident, most of the central parts of Uganda were identified as cold spot clusters, while most of Western Uganda, the Acholi and the Lango regions had no statistically significant spatial patterns by the year 2016. The spatio-temporal analysis identified the Karamoja and Sebei regions as clusters of persistent, consecutive and intensifying hot spots, West Nile region was identified as a sporadic hot spot area while the Toro region was identified with both sporadic and emerging hotspots. In conclusion, undernutrition is a silent pandemic that needs to be handled with both hands. At 31.2 percent, the prevalence is still very high and unpleasant. The distribution across the country is nonuniform with some areas such as the Karamoja, the West Nile, the Sebei and the Toro regions being epicenters of undernutrition in Uganda. Over time, the same areas have experienced and exhibited high undernutrition prevalence. Policymakers, as well as the implementers, should bear in mind the spatial variations across the country and prioritize hot spot areas in order to have efficient, timely and region-specific interventions.

Keywords: undernutrition, spatial autocorrelation, hotspots analysis, geographically weighted regressions, emerging hotspots analysis, under-fives, Uganda

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6354 A Convolutional Deep Neural Network Approach for Skin Cancer Detection Using Skin Lesion Images

Authors: Firas Gerges, Frank Y. Shih

Abstract:

Malignant melanoma, known simply as melanoma, is a type of skin cancer that appears as a mole on the skin. It is critical to detect this cancer at an early stage because it can spread across the body and may lead to the patient's death. When detected early, melanoma is curable. In this paper, we propose a deep learning model (convolutional neural networks) in order to automatically classify skin lesion images as malignant or benign. Images underwent certain pre-processing steps to diminish the effect of the normal skin region on the model. The result of the proposed model showed a significant improvement over previous work, achieving an accuracy of 97%.

Keywords: deep learning, skin cancer, image processing, melanoma

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6353 Linking Enhanced Resting-State Brain Connectivity with the Benefit of Desirable Difficulty to Motor Learning: A Functional Magnetic Resonance Imaging Study

Authors: Chien-Ho Lin, Ho-Ching Yang, Barbara Knowlton, Shin-Leh Huang, Ming-Chang Chiang

Abstract:

Practicing motor tasks arranged in an interleaved order (interleaved practice, or IP) generally leads to better learning than practicing tasks in a repetitive order (repetitive practice, or RP), an example of how desirable difficulty during practice benefits learning. Greater difficulty during practice, e.g. IP, is associated with greater brain activity measured by higher blood-oxygen-level dependent (BOLD) signal in functional magnetic resonance imaging (fMRI) in the sensorimotor areas of the brain. In this study resting-state fMRI was applied to investigate whether increase in resting-state brain connectivity immediately after practice predicts the benefit of desirable difficulty to motor learning. 26 healthy adults (11M/15F, age = 23.3±1.3 years) practiced two sets of three sequences arranged in a repetitive or an interleaved order over 2 days, followed by a retention test on Day 5 to evaluate learning. On each practice day, fMRI data were acquired in a resting state after practice. The resting-state fMRI data was decomposed using a group-level spatial independent component analysis (ICA), yielding 9 independent components (IC) matched to the precuneus network, primary visual networks (two ICs, denoted by I and II respectively), sensorimotor networks (two ICs, denoted by I and II respectively), the right and the left frontoparietal networks, occipito-temporal network, and the frontal network. A weighted resting-state functional connectivity (wRSFC) was then defined to incorporate information from within- and between-network brain connectivity. The within-network functional connectivity between a voxel and an IC was gauged by a z-score derived from the Fisher transformation of the IC map. The between-network connectivity was derived from the cross-correlation of time courses across all possible pairs of ICs, leading to a symmetric nc x nc matrix of cross-correlation coefficients, denoted by C = (pᵢⱼ). Here pᵢⱼ is the extremum of cross-correlation between ICs i and j; nc = 9 is the number of ICs. This component-wise cross-correlation matrix C was then projected to the voxel space, with the weights for each voxel set to the z-score that represents the above within-network functional connectivity. The wRSFC map incorporates the global characteristics of brain networks measured by the between-network connectivity, and the spatial information contained in the IC maps measured by the within-network connectivity. Pearson correlation analysis revealed that greater IP-minus-RP difference in wRSFC was positively correlated with the RP-minus-IP difference in the response time on Day 5, particularly in brain regions crucial for motor learning, such as the right dorsolateral prefrontal cortex (DLPFC), and the right premotor and supplementary motor cortices. This indicates that enhanced resting brain connectivity during the early phase of memory consolidation is associated with enhanced learning following interleaved practice, and as such wRSFC could be applied as a biomarker that measures the beneficial effects of desirable difficulty on motor sequence learning.

Keywords: desirable difficulty, functional magnetic resonance imaging, independent component analysis, resting-state networks

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6352 Improvement of Visual Acuity in Patient Undergoing Occlusion Therapy

Authors: Rajib Husain, Mezbah Uddin, Mohammad Shamsal Islam, Rabeya Siddiquee

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Purpose: To determine the improvement of visual acuity in patients undergoing occlusion therapy. Methods: This was a prospective hospital-based study of newly diagnosed of amblyopia seen at the pediatric clinic of Chittagong Eye Infirmary & Training Complex. There were 32 refractive amblyopia subjects were examined & questionnaire was piloted. Included were all patients diagnosed with refractive amblyopia between 5 to 8 years, without previous amblyopia treatment, and whose parents were interested to participate in the study. Patients diagnosed with strabismic amblyopia were excluded. Patients were first corrected with the best correction for a month. When the VA in the amblyopic eye did not improve over a month, then occlusion treatment was started. Occlusion was done daily for 6-8 h together with vision therapy. The occlusion was carried out for three months. Results: Out of study 32 children, 31 of them have a good compliance of amblyopic treatment whereas one child has poor compliance. About 6% Children have amblyopia from Myopia, 7% Hyperopia, 32% from myopic astigmatism, 42% from hyperopic astigmatism and 13% have mixed astigmatism. The mean and Standard deviation of present average VA was 0.452±0.275 Log MAR and after an intervention of amblyopia therapy with vision therapy mean and Standard deviation VA was 0.155±0.157 Log MAR. Out of total respondent 21.85% have BCVA in range from (0-.2) log MAR, 37.5% have BCVA in range from (0.22-0.5) log MAR, 35.95% have in range from (0.52-0.8) log MAR, 4.7% have in range from (0.82-1) log MAR and after intervention of occlusion therapy with vision therapy 76.6% have VA in range from (0-.2) log MAR, 21.85% have VA in range from (0.22-0.5) log MAR, 1.5% have in range from (0.52-0.8) log MAR. Conclusion: Amblyopia is a most important factor in pediatric age group because it can lead to visual impairment. Thus, this study concludes that occlusion therapy with vision therapy is probably one of the best treatment methods for amblyopic patients (age 5-8 years), and compliance and age were the most critical factor predicting a successful outcome.

Keywords: amblyopia, occlusion therapy, vision therapy, eccentric fixation, visuoscopy

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6351 Power Quality Modeling Using Recognition Learning Methods for Waveform Disturbances

Authors: Sang-Keun Moon, Hong-Rok Lim, Jin-O Kim

Abstract:

This paper presents a Power Quality (PQ) modeling and filtering processes for the distribution system disturbances using recognition learning methods. Typical PQ waveforms with mathematical applications and gathered field data are applied to the proposed models. The objective of this paper is analyzing PQ data with respect to monitoring, discriminating, and evaluating the waveform of power disturbances to ensure the system preventative system failure protections and complex system problem estimations. Examined signal filtering techniques are used for the field waveform noises and feature extractions. Using extraction and learning classification techniques, the efficiency was verified for the recognition of the PQ disturbances with focusing on interactive modeling methods in this paper. The waveform of selected 8 disturbances is modeled with randomized parameters of IEEE 1159 PQ ranges. The range, parameters, and weights are updated regarding field waveform obtained. Along with voltages, currents have same process to obtain the waveform features as the voltage apart from some of ratings and filters. Changing loads are causing the distortion in the voltage waveform due to the drawing of the different patterns of current variation. In the conclusion, PQ disturbances in the voltage and current waveforms indicate different types of patterns of variations and disturbance, and a modified technique based on the symmetrical components in time domain was proposed in this paper for the PQ disturbances detection and then classification. Our method is based on the fact that obtained waveforms from suggested trigger conditions contain potential information for abnormality detections. The extracted features are sequentially applied to estimation and recognition learning modules for further studies.

Keywords: power quality recognition, PQ modeling, waveform feature extraction, disturbance trigger condition, PQ signal filtering

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6350 Predicting Match Outcomes in Team Sport via Machine Learning: Evidence from National Basketball Association

Authors: Jacky Liu

Abstract:

This paper develops a team sports outcome prediction system with potential for wide-ranging applications across various disciplines. Despite significant advancements in predictive analytics, existing studies in sports outcome predictions possess considerable limitations, including insufficient feature engineering and underutilization of advanced machine learning techniques, among others. To address these issues, we extend the Sports Cross Industry Standard Process for Data Mining (SRP-CRISP-DM) framework and propose a unique, comprehensive predictive system, using National Basketball Association (NBA) data as an example to test this extended framework. Our approach follows a holistic methodology in feature engineering, employing both Time Series and Non-Time Series Data, as well as conducting Explanatory Data Analysis and Feature Selection. Furthermore, we contribute to the discourse on target variable choice in team sports outcome prediction, asserting that point spread prediction yields higher profits as opposed to game-winner predictions. Using machine learning algorithms, particularly XGBoost, results in a significant improvement in predictive accuracy of team sports outcomes. Applied to point spread betting strategies, it offers an astounding annual return of approximately 900% on an initial investment of $100. Our findings not only contribute to academic literature, but have critical practical implications for sports betting. Our study advances the understanding of team sports outcome prediction a burgeoning are in complex system predictions and pave the way for potential profitability and more informed decision making in sports betting markets.

Keywords: machine learning, team sports, game outcome prediction, sports betting, profits simulation

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6349 Towards Developing a Self-Explanatory Scheduling System Based on a Hybrid Approach

Authors: Jian Zheng, Yoshiyasu Takahashi, Yuichi Kobayashi, Tatsuhiro Sato

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In the study, we present a conceptual framework for developing a scheduling system that can generate self-explanatory and easy-understanding schedules. To this end, a user interface is conceived to help planners record factors that are considered crucial in scheduling, as well as internal and external sources relating to such factors. A hybrid approach combining machine learning and constraint programming is developed to generate schedules and the corresponding factors, and accordingly display them on the user interface. Effects of the proposed system on scheduling are discussed, and it is expected that scheduling efficiency and system understandability will be improved, compared with previous scheduling systems.

Keywords: constraint programming, factors considered in scheduling, machine learning, scheduling system

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6348 Factors Afecting the Academic Performance of In-Service Students in Science Educaction

Authors: Foster Chilufya

Abstract:

This study sought to determine factors that affect academic performance of mature age students in Science Education at University of Zambia. It was guided by Maslow’s Hierarchy of Needs. The theory provided relationship between achievement motivation and academic performance. A descriptive research design was used. Both Qualitative and Quantitative research methods were used to collect data from 88 respondents. Simple random and purposive sampling procedures were used to collect from the respondents. Concerning factors that motivate mature-age students to choose Science Education Programs, the following were cited: need for self-actualization, acquisition of new knowledge, encouragement from friends and family members, good performance at high school and diploma level, love for the sciences, prestige and desire to be promoted at places of work. As regards factors that affected the academic performance of mature-age students, both negative and positive factors were identified. These included: demographic factors such as age and gender, psychological characteristics such as motivation and preparedness to learn, self-set goals, self esteem, ability, confidence and persistence, student prior academic performance at high school and college level, social factors, institutional factors and the outcomes of the learning process. In order to address the factors that negatively affect academic performance of mature-age students, the following measures were identified: encouraging group discussions, encouraging interactive learning process, providing a conducive learning environment, reviewing Science Education curriculum and providing adequate learning materials. Based on these factors, it is recommended that, the School of Education introduces a program in Science Education specifically for students training to be teachers of science. Additionally, introduce majors in Physics Education, Biology Education, Chemistry Education and Mathematics Education relevant to what is taught in high schools.

Keywords: academic, performance, in-service, science

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6347 Development of an Automatic Computational Machine Learning Pipeline to Process Confocal Fluorescence Images for Virtual Cell Generation

Authors: Miguel Contreras, David Long, Will Bachman

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Background: Microscopy plays a central role in cell and developmental biology. In particular, fluorescence microscopy can be used to visualize specific cellular components and subsequently quantify their morphology through development of virtual-cell models for study of effects of mechanical forces on cells. However, there are challenges with these imaging experiments, which can make it difficult to quantify cell morphology: inconsistent results, time-consuming and potentially costly protocols, and limitation on number of labels due to spectral overlap. To address these challenges, the objective of this project is to develop an automatic computational machine learning pipeline to predict cellular components morphology for virtual-cell generation based on fluorescence cell membrane confocal z-stacks. Methods: Registered confocal z-stacks of nuclei and cell membrane of endothelial cells, consisting of 20 images each, were obtained from fluorescence confocal microscopy and normalized through software pipeline for each image to have a mean pixel intensity value of 0.5. An open source machine learning algorithm, originally developed to predict fluorescence labels on unlabeled transmitted light microscopy cell images, was trained using this set of normalized z-stacks on a single CPU machine. Through transfer learning, the algorithm used knowledge acquired from its previous training sessions to learn the new task. Once trained, the algorithm was used to predict morphology of nuclei using normalized cell membrane fluorescence images as input. Predictions were compared to the ground truth fluorescence nuclei images. Results: After one week of training, using one cell membrane z-stack (20 images) and corresponding nuclei label, results showed qualitatively good predictions on training set. The algorithm was able to accurately predict nuclei locations as well as shape when fed only fluorescence membrane images. Similar training sessions with improved membrane image quality, including clear lining and shape of the membrane, clearly showing the boundaries of each cell, proportionally improved nuclei predictions, reducing errors relative to ground truth. Discussion: These results show the potential of pre-trained machine learning algorithms to predict cell morphology using relatively small amounts of data and training time, eliminating the need of using multiple labels in immunofluorescence experiments. With further training, the algorithm is expected to predict different labels (e.g., focal-adhesion sites, cytoskeleton), which can be added to the automatic machine learning pipeline for direct input into Principal Component Analysis (PCA) for generation of virtual-cell mechanical models.

Keywords: cell morphology prediction, computational machine learning, fluorescence microscopy, virtual-cell models

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6346 Comprehensive Review of Adversarial Machine Learning in PDF Malware

Authors: Preston Nabors, Nasseh Tabrizi

Abstract:

Portable Document Format (PDF) files have gained significant popularity for sharing and distributing documents due to their universal compatibility. However, the widespread use of PDF files has made them attractive targets for cybercriminals, who exploit vulnerabilities to deliver malware and compromise the security of end-user systems. This paper reviews notable contributions in PDF malware detection, including static, dynamic, signature-based, and hybrid analysis. It presents a comprehensive examination of PDF malware detection techniques, focusing on the emerging threat of adversarial sampling and the need for robust defense mechanisms. The paper highlights the vulnerability of machine learning classifiers to evasion attacks. It explores adversarial sampling techniques in PDF malware detection to produce mimicry and reverse mimicry evasion attacks, which aim to bypass detection systems. Improvements for future research are identified, including accessible methods, applying adversarial sampling techniques to malicious payloads, evaluating other models, evaluating the importance of features to malware, implementing adversarial defense techniques, and conducting comprehensive examination across various scenarios. By addressing these opportunities, researchers can enhance PDF malware detection and develop more resilient defense mechanisms against adversarial attacks.

Keywords: adversarial attacks, adversarial defense, adversarial machine learning, intrusion detection, PDF malware, malware detection, malware detection evasion

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6345 Constructing Notation for Music Learning in Athletes: Identifying Key Concepts in Music and Body Movements

Authors: Fung Chiat Loo, Fung Ying Loo

Abstract:

This paper discusses, suggests, and constructs a notation system to facilitate the learning and understanding of the two aspects of music and movement in a sports routine. This model serves to provide a simple and logical notation that does not require training in both music and choreography. Notation is an important medium in many art forms, particularly in music and dance, transmitting information that cannot easily be expressed using words or language. Another field that is closely associated with dance and music is sports routine, which equally requires choreography and music. However, from the perspective of music, it is common to observe many incongruencies appearing between the music used and the choreography that impede an optimal perception of the performance. The concept of the notation proceeds with a discussion and review of existing dance notations that could contribute to sports routines, along with rules and a code of points in selected sports routines. The author's involvement as an insider of numerous musical theatre productions also contributed to this study. The notation constructed includes time (tempo), significances of musical accents, direction, and phrasing, along with significances of movements (jump, punch, shape). It is believed that the level of congruence between music and movement will provide optimal visualization, and in that, the notation serves to provide adequate information on both entities for the understanding of athletes and coaches.

Keywords: notation, choreography, music learning, sports routines, congruence

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6344 Immersive Block Scheduling in Higher Education: A Case Study in Curriculum Reform and Increased Student Success

Authors: Thomas Roche, Erica Wilson, Elizabeth Goode

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Universities across the globe are considering how to effect meaningful change in their higher education (HE) delivery in the face of increasingly diverse student cohorts and shifting student learning preferences. This paper reports on a descriptive case study of whole-of-institution curriculum reform at one regional Australian university, where more traditional 13-week semesters were replaced with a 6-week immersive block model drawing on active learning pedagogy. Based on a synthesis of literature in best practice HE pedagogy and principles, the case study draws on student performance data and senior management staff interviews (N = 5) to outline the key changes necessary for successful HE transformation to deliver increased student pass rates and retention. The findings from this case study indicate that an institutional transformation to an immersive block model requires both a considered change in institutional policy and process as well as the appropriate resourcing of roles, governance committees, technical solutions, and, importantly, communities of practice. Implications for practice at higher education institutions considering reforming their curriculum model are also discussed.

Keywords: student retention, immersive scheduling, block model, curriculum reform, active learning, higher education pedagogy, higher education policy

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6343 On the Use of Machine Learning for Tamper Detection

Authors: Basel Halak, Christian Hall, Syed Abdul Father, Nelson Chow Wai Kit, Ruwaydah Widaad Raymode

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The attack surface on computing devices is becoming very sophisticated, driven by the sheer increase of interconnected devices, reaching 50B in 2025, which makes it easier for adversaries to have direct access and perform well-known physical attacks. The impact of increased security vulnerability of electronic systems is exacerbated for devices that are part of the critical infrastructure or those used in military applications, where the likelihood of being targeted is very high. This continuously evolving landscape of security threats calls for a new generation of defense methods that are equally effective and adaptive. This paper proposes an intelligent defense mechanism to protect from physical tampering, it consists of a tamper detection system enhanced with machine learning capabilities, which allows it to recognize normal operating conditions, classify known physical attacks and identify new types of malicious behaviors. A prototype of the proposed system has been implemented, and its functionality has been successfully verified for two types of normal operating conditions and further four forms of physical attacks. In addition, a systematic threat modeling analysis and security validation was carried out, which indicated the proposed solution provides better protection against including information leakage, loss of data, and disruption of operation.

Keywords: anti-tamper, hardware, machine learning, physical security, embedded devices, ioT

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6342 Developing Digital Skills in Museum Professionals through Digital Education: International Good Practices and Effective Learning Experiences

Authors: Antonella Poce, Deborah Seid Howes, Maria Rosaria Re, Mara Valente

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The Creative Industries education contexts, Museum Education in particular, generally presents a low emphasis on the use of new digital technologies, digital abilities and transversal skills development. The spread of the Covid-19 pandemic has underlined the importance of these abilities and skills in cultural heritage education contexts: gaining digital skills, museum professionals will improve their career opportunities with access to new distribution markets through internet access and e-commerce, new entrepreneurial tools, or adding new forms of digital expression to their work. However, the use of web, mobile, social, and analytical tools is becoming more and more essential in the Heritage field, and museums, in particular, to face the challenges posed by the current worldwide health emergency. Recent studies highlight the need for stronger partnerships between the cultural and creative sectors, social partners and education and training providers in order to provide these sectors with the combination of skills needed for creative entrepreneurship in a rapidly changing environment. Considering the above conditions, the paper presents different examples of digital learning experiences carried out in Italian and USA contexts with the aim of promoting digital skills in museum professionals. In particular, a quali-quantitative research study has been conducted on two international Postgraduate courses, “Advanced Studies in Museum Education” (2 years) and “Museum Education” (1 year), in order to identify the educational effectiveness of the online learning strategies used (e.g., OBL, Digital Storytelling, peer evaluation) for the development of digital skills and the acquisition of specific content. More than 50 museum professionals participating in the mentioned educational pathways took part in the learning activity, providing evaluation data useful for research purposes.

Keywords: digital skills, museum professionals, technology, education

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6341 Investigating Iraqi EFL Undergraduates' Performance in the Production of Number Forms in English

Authors: Adnan Z. Mkhelif

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The production of number forms in English tends to be problematic for Iraqi learners of English as a foreign language (EFL), even at the undergraduate level. To help better understand and consequently address this problem, it is important to identify its sources. This study aims at: (1) statistically analysing Iraqi EFL undergraduates' performance in the production of number forms in English; (2) classifying learners' errors in terms of their possible major causes; and (3) outlining some pedagogical recommendations relevant to the teaching of number forms in English. It is hypothesized in this study that (1) Iraqi EFL undergraduates still face problems in the production of number forms in English and (2) errors pertaining to the context of learning are more numerous than those attributable to the other possible causes. After reviewing the literature available on the topic, a written test comprising 50 items has been constructed and administered to a randomly chosen sample of 50 second-year college students from the Department of English, College of Education, Wasit University. The findings of the study showed that Iraqi EFL undergraduates still face problems in the production of number forms in English and that the possible major sources of learners’ errors can be arranged hierarchically in terms of the percentages of errors to which they can be ascribed as follows: (1) context of learning (50%), (2) intralingual transfer (37%), and (3) interlingual transfer (13%). It is hoped that the implications of the study findings will be beneficial to researchers, syllabus designers, as well as teachers of English as a foreign/second language.

Keywords: L2 number forms, L2 vocabulary learning, productive knowledge, proficiency

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6340 Applying the Extreme-Based Teaching Model in Post-Secondary Online Classroom Setting: A Field Experiment

Authors: Leon Pan

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The first programming course within post-secondary education has long been recognized as a challenging endeavor for both educators and students alike. Historically, these courses have exhibited high failure rates and a notable number of dropouts. Instructors often lament students' lack of effort in their coursework, and students often express frustration that the teaching methods employed are not effective. Drawing inspiration from the successful principles of Extreme Programming, this study introduces an approach—the Extremes-based teaching model — aimed at enhancing the teaching of introductory programming courses. To empirically determine the effectiveness of the model, a comparison was made between a section taught using the extreme-based model and another utilizing traditional teaching methods. Notably, the extreme-based teaching class required students to work collaboratively on projects while also demanding continuous assessment and performance enhancement within groups. This paper details the application of the extreme-based model within the post-secondary online classroom context and presents the compelling results that emphasize its effectiveness in advancing the teaching and learning experiences. The extreme-based model led to a significant increase of 13.46 points in the weighted total average and a commendable 10% reduction in the failure rate.

Keywords: extreme-based teaching model, innovative pedagogical methods, project-based learning, team-based learning

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6339 Enhancing Chinese Foreign Language Teachers’ Intercultural Competence: An Action Research Study

Authors: Wei Hing Rosenkvist

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In the past few decades, concerns and demands of promoting student intercultural communicative competence in foreign language education have been increasing along with the rapid growth of information technologies and globalization in the 21st century. In Sweden, related concepts such as internationalization, global citizenship, multiculturalism, and intercultural communication, are also keywords that would be found in the written learning objectives of foreign language education at all levels. Being one of the leading higher institutes in distance education in Europe, Dalarna University clearly states that after completion of the teacher education program, students shall understand the needs for integrating internationalization, intercultural and global perspective in teaching and learning in Swedish schools and implement their studies to promote education in an international and global context. Even though many teachers and educators agree with the institutes’ mission and vision about the importance of internationalization and the need to increase student understanding of intercultural and global perspectives, they might find this objective unattainable and restricted due to the nature of the subject and their knowledge of intercultural competence. When conducting a comprehensive Chinese language course for the students who are going to become Chinese foreign language teachers, the researcher found that all the learning objectives are linguistic oriented while grammatical components dominate the entire course. Apparently, there is a gap between the learning objectives of the course and the DU’s mission of fostering an international learner with intercultural and globalized perspectives. How to include this macro-learning objective in a foreign language course is a great challenge to the educator. Although scholars from different academic domains have provided different theoretical frameworks and approaches for developing student intercultural competence, research that focuses on the didactic perspectives of developing student intercultural competence in teaching Chinese as a foreign language education (CFL) is limited, and practical examples are rare. This challenge has motivated the researcher to conduct an action research study that aims at integrating DU’s macro-learning objective in a current CFL course through different didactic practices to develop the student's intercultural competence. This research study aims to, firstly, illustrate the cross-cultural knowledge integrated into the present Chinese language course for developing intercultural competence. Secondly, it investigates different didactic means that can be utilized to deliver cross-cultural knowledge to student teachers in the present course without generating dramatic disturbance of the syllabus. Thirdly, it examines the effectiveness of these didactic means in enhancing student-teacher intercultural competence regarding the need for integrating and implementing internationalization, intercultural and global perspectives in teaching and learning in Swedish schools. Last but not least, it intends to serve as a practical example for developing the student teachers’ intercultural competence in foreign language education in DU and fill in the research gap of this academic domain worldwide.

Keywords: action research, intercultural competence, Chinese as a foreign language education, teacher education

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6338 Continuous Improvement of Teaching Quality through Course Evaluation by the Students

Authors: Valerie Follonier, Henrike Hamelmann, Jean-Michel Jullien

Abstract:

The Distance Learning University in Switzerland (UniDistance) is offering bachelor and master courses as well as further education programs. The professors and their assistants work at traditional Swiss universities and are giving their courses at UniDistance following a blended learning and flipped classroom approach. A standardized course evaluation by the students has been established as a component of a quality improvement process. The students’ feedback enables the stakeholders to identify areas of improvement, initiate professional development for the teaching teams and thus continuously augment the quality of instruction. This paper describes the evaluation process, the tools involved and how the approach involving all stakeholders helps forming a culture of quality in teaching. Additionally, it will present the first evaluation results following the new process. Two software tools have been developed to support all stakeholders in the process of the semi-annual formative evaluation. The first tool allows to create the survey and to assign it to the relevant courses and students. The second tool presents the results of the evaluation to the stakeholders, providing specific features for the teaching teams, the dean, the directorate and EDUDL+ (Educational development unit distance learning). The survey items were selected in accordance with the e-learning strategy of the institution and are formulated to support the professional development of the teaching teams. By reviewing the results the teaching teams become aware of the opinion of the students and are asked to write a feedback for the attention of their dean. The dean reviews the results of the faculty and writes a general report about the situation of the faculty and the possible improvements intended. Finally, EDUDL+ writes a final report summarising the evaluation results. A mechanism of adjustable warnings allows it to generate quality indicators for each module. These are summarised for each faculty and globally for the whole institution in order to increase the vigilance of the responsible. The quality process involves changing the indicators regularly to focus on different areas each semester, to facilitate the professional development of the teaching teams and to progressively augment the overall teaching quality of the institution.

Keywords: continuous improvement process, course evaluation, distance learning, software tools, teaching quality

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6337 An Intelligent Tutoring System Enriched with 3D Virtual Reality for Dentistry Students

Authors: Meltem Eryılmaz

Abstract:

With the emergence of the COVID-19 infection outbreak, the socio-cultural, political, economic, educational systems dynamics of the world have gone through a major change, especially in the educational field, specifically dentistry preclinical education, where the students must have a certain amount of real-time experience in endodontics and other various procedures. The totality of the digital and physical elements that make our five sense organs feel as if we really exist in a virtual world is called virtual reality. Virtual reality, which is very popular today, has started to be used in education. With the inclusion of developing technology in education and training environments, virtual learning platforms have been designed to enrich students' learning experiences. The field of health is also affected by these current developments, and the number of virtual reality applications developed for students studying dentistry is increasing day by day. The most widely used tools of this technology are virtual reality glasses. With virtual reality glasses, you can look any way you want in a world designed in 3D and navigate as you wish. With this project, solutions that will respond to different types of dental practices of students who study dentistry with virtual reality applications are produced. With this application, students who cannot find the opportunity to work with patients in distance education or who want to improve themselves at home have unlimited trial opportunities. Unity 2021, Visual Studio 2019, Cardboard SDK are used in the study.

Keywords: dentistry, intelligent tutoring system, virtual reality, online learning, COVID-19

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6336 Embracing Diverse Learners: A Way Towards Effective Learning

Authors: Mona Kamel Hassan

Abstract:

Teaching a class of diverse learners poses a great challenge not only for foreign and second language teachers, but also for teachers in different disciplines as well as for curriculum designers. Thus, to contribute to previous research tackling language diversity, the current paper shares the experience of teaching a reading, writing and vocabulary building course to diverse Arabic as a Foreign Language learners in their advanced language proficiency level. Diversity is represented in students’ motivation, their prior knowledge, their various needs and interests, their level of anxiety, and their different learning styles and skills. While teaching this course the researcher adopted the universal design for learning (UDL) framework, which is a means to meet the various needs of diverse learners. UDL stresses the importance of enabling the entire diverse students to gain skills, knowledge, and enthusiasm to learn through the employment of teaching methods that respond to students' individual differences. Accordingly, the educational curriculum developed for this course and the teaching methods employed is modified. First, the researcher made the language curriculum vivid and attractive to inspire students' learning and to keep them engaged in their learning process. The researcher encouraged the entire students, from the first day, to suggest topics of their interest; political, social, cultural, etc. The authentic Arabic texts chosen are those that best meet students’ needs, interests, lives, and sociolinguistic issues, together with the linguistic and cultural components. In class and under the researcher’s guidance, students dig into these topics to find solutions for the tackled issues while working with their peers. Second, to gain equal opportunities to demonstrate learning, role-playing was encouraged to give students the opportunity to perform different linguistic tasks, to reflect and share their diverse interests and cultural backgrounds with their peers. Third, to bring the UDL into the classroom, students were encouraged to work on interactive, collaborative activities through technology to improve their reading and writing skills and reinforce their mastery of the accumulated vocabulary, idiomatic expressions, and collocations. These interactive, collaborative activities help to facilitate student-student communication and student-teacher communication and to increase comfort in this class of diverse learners. Detailed samples of the educational curriculum and interactive, collaborative activities developed, accompanied by methods of teaching employed to teach these diverse learners, are presented for illustration. Results revealed that students are responsive to the educational materials which are developed for this course. Therefore, they engaged in the learning process and classroom activities and discussions effectively. They also appreciated their instructor’s willingness to differentiate the teaching methods to suit students of diverse background knowledge, learning styles, level of anxiety, etc. Finally, the researcher believes that sharing this experience in teaching diverse learners will help both language teachers and teachers in other disciplines to develop a better understanding to meet their students' diverse needs. Results will also pave the way for curriculum designers to develop educational material that meets the needs of diverse learners.

Keywords: teaching, language, diverse, learners

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6335 Research on Strategies of Building a Child Friendly City in Wuhan

Authors: Tianyue Wan

Abstract:

Building a child-friendly city (CFC) contributes to improving the quality of urbanization. It also forms a local system committed to fulfilling children's rights and development. Yet, the work related to CFC is still at the initial stage in China. Therefore, taking Wuhan, the most populous city in central China, as the pilot city would offer some reference for other cities. Based on the analysis of theories and practice examples, this study puts forward the challenges of building a child-friendly city under the particularity of China's national conditions. To handle these challenges, this study uses four methods to collect status data: literature research, site observation, research inquiry, and semantic differential (SD). And it adopts three data analysis methods: case analysis, geographic information system (GIS) analysis, and analytic hierarchy process (AHP) method. Through data analysis, this study identifies the evaluation system and appraises the current situation of Wuhan. According to the status of Wuhan's child-friendly city, this study proposes three strategies: 1) construct the evaluation system; 2) establish a child-friendly space system integrating 'point-line-surface'; 3) build a digitalized service platform. At the same time, this study suggests building a long-term mechanism for children's participation and multi-subject supervision from laws, medical treatment, education, safety protection, social welfare, and other aspects. Finally, some conclusions of strategies about CFC are tried to be drawn to promote the highest quality of life for all citizens in Wuhan.

Keywords: action plan, child friendly city, construction strategy, urban space

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6334 Revitalization of Sign Language through Deaf Theatre: A Linguistic Analysis of an Art Form Which Combines Physical Theatre, Poetry, and Sign Language

Authors: Gal Belsitzman, Rose Stamp, Atay Citron, Wendy Sandler

Abstract:

Sign languages are considered endangered. The vitality of sign languages is compromised by its unique sociolinguistic situation, in which hearing parents that give birth to deaf children usually decide to cochlear implant their child. Therefore, these children don’t acquire their natural language – Sign Language. Despite this, many sign languages, such as Israeli Sign Language (ISL) are thriving. The continued survival of similar languages under threat has been associated with the remarkable resilience of the language community. In particular, deaf literary traditions are central in reminding the community of the importance of the language. One example of a deaf literary tradition which has received increased popularity in recent years is deaf theatre. The Ebisu Sign Language Theatre Laboratory, developed as part of the multidisciplinary Grammar of the Body Research Project, is the first deaf theatre company in Israel. Ebisu Theatre combines physical theatre and sign language research, to allow for a natural laboratory to analyze the creative use of the body. In this presentation, we focus on the recent theatre production called ‘Their language’ which tells of the struggle faced by the deaf community to use their own natural language in the education system. A thorough analysis unravels how linguistic properties are integrated with the use of poetic devices and physical theatre techniques in this performance, enabling wider access by both deaf and hearing audiences, without interpretation. Interviews with the audience illustrate the significance of this art form which serves a dual purpose, both as empowering for the deaf community and educational for the hearing and deaf audiences, by raising awareness of community-related issues.

Keywords: deaf theatre, empowerment, language revitalization, sign language

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6333 Effect of Zingerone on High-Fructose Diet-Indeuced Metabolic Derangements in Growing Sprague-Dawley Rats

Authors: Nondumiso Lushozi, Busisani Lembede, Eliton Chivandi

Abstract:

Consumption of fructose increases the risk of obesity, nonalcoholic fatty liver disease (NAFLD) and metabolic syndrome in children. Zingerone which is found in ginger has antidiabetic and antiobesogenic properties. Therefore, the aim of the study was to investigate the potential of orally administered zingerone to protect growing Sprague-Dawley rats (mimicking growing children) against high-fructose diet-induced metabolic derangements. Forty, 21-day old female Sprague-Dawley rats were randomly allocated and administered the following four treatments for 12 weeks: group I: standard rat chow (SR) + plain water (PW) + plain gelatine cube (PC). group II: SR + 20% (w/v) fructose solution (FS) + PC. group III: SR + FS + 100 mg/kg/day of fenofibrate in gelatine cube. group IV: SR+ FS + 20 mg/kg/day of zingerone in gelatine cube. The rats’ triglyceride, cholesterol, insulin & adiponectin concentration, visceral fat liver lipid content, homoeostasis model assessment of insulin resistance (HOMA-IR) and ability to handle glucose were determined. Oral administration of zingerone significantly increased (P<0.001) visceral fat and liver lipid content (P<0.001), respectively. Results from the study revealed that administration of 20% fructose solution did not induce metabolic dysfunction, however the zingerone treatment increased visceral fat and liver lipid content, all these lipid abnormalities are typical features of the metabolic syndrome, therefore the current study suggests that zingerone has no effect on metabolic dysfunction in adolescent females.

Keywords: antidiabetic, metabolic syndrome, zingerone, antiobesogenic

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6332 Dependency on Social Media and Psychological Well-Being among Young Adults: Case Study of University Students in Pakistan

Authors: Ghazala Yasmeen, Zahid Yousaf

Abstract:

Frequent social media use has significantly changed people's life and communication styles during the last two decades. Social media use has multiple dimensions, and there are nuanced relationships between it and how it affects different societal subgroups. With the increased popularity and rapid growth of social networking sites, people are experiencing potential social media addiction, which causes severe mental health problems. How social media is dramatically influencing the lives and mental health of its users, and particularly of the students, creating psychological issues, e.g., isolation, depression, and anxiety, will be the primary objective of this study. This research will address the problems confronted by many students who are regular social media users and can undergo mental distress. This study aims to explore how social media use can lead to isolation, depression, and anxiety. This research will also investigate the effects of cyber-bullying on social, emotional, and psychological wellbeing. For this purpose, the researcher will use the survey technique as a method of inquiry. Ryff's theory of Psychological wellbeing will be used as a theoretical framework to explore the association between social media addiction and psychological effects among users. For data collection, the researcher will use the quantitative research method through a survey questionnaire from three universities in Pakistan from the public and private sectors. This study will imply a two-stage random sampling technique. At first, the researcher will select 20% of students from universities. In the second stage, 20% of students using different social networking sites will be chosen, and draw a representative sample from these will be. The intended study will use questionnaires comprising two portions. The first section will consist of social media engagement by the students, following impacts on their mental health and reported attitude towards psychological wellbeing. This study will spotlight the considerations of parents, educationists, and policymakers to take measures against the devastating effects of cyber-crimes on young adults.

Keywords: anxiety, depression, isolation, social media, wellbeing

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6331 Education For Social Justice: A Comparative Study of University Teachers' Conceptions and Practice

Authors: Digby Warren, Jiri Kropac

Abstract:

This comparative study seeks to develop a deeper understanding of what is meant by “education for social justice” (ESJ) - an aspiration articulated by universities, though often without much definition. The research methodology involved thematic analysis of data from in-depth interviews with academics (voluntary participants) in different disciplines and institutions in the UK, Czech Republic and other EU countries. The interviews explored lecturers’ conceptions of ESJ, their practice of it, and associated challenges and enabling factors. Main findings are that ESJ is construed as provision of equitable and conscientising education opportunities that run across the whole higher education (HE) journey, from widening access to HE to stimulating critical learning and awareness that can empower graduates to transform their lives and societies. Teaching practice featured study of topics related to social justice; collaborative and creative learning activities, and assignments offering choice and connection to students’ realities. Student responses could be mixed, occasionally resistant, but mostly positive in terms of gaining increased confidence and awareness of equality and social responsibility. Influences at the macro, meso and mico level could support or limit scope for ESJ. Overall, the study highlights the strong, values-based commitment of HE teachers to facilitating student learning engagement, wellbeing and development towards building a better world.

Keywords: higher education, social justice, inclusivity, diversity

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6330 Role of Machine Learning in Internet of Things Enabled Smart Cities

Authors: Amit Prakash Singh, Shyamli Singh, Chavi Srivastav

Abstract:

This paper presents the idea of Internet of Thing (IoT) for the infrastructure of smart cities. Internet of Thing has been visualized as a communication prototype that incorporates myriad of digital services. The various component of the smart cities shall be implemented using microprocessor, microcontroller, sensors for network communication and protocols. IoT enabled systems have been devised to support the smart city vision, of which aim is to exploit the currently available precocious communication technologies to support the value-added services for function of the city. Due to volume, variety, and velocity of data, it requires analysis using Big Data concept. This paper presented the various techniques used to analyze big data using machine learning.

Keywords: IoT, smart city, embedded systems, sustainable environment

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6329 Ageing Gingiva: A New Hope for Autologous Stem Cell Therapy

Authors: Ankush M. Dewle, Suditi Bhattacharya, Prachi R. Abhang, Savita Datar, Ajay J. Jog, Rupesh K. Srivastava, Geetanjali Tomar

Abstract:

Objectives: The aim of this study was to investigate the quality of mesenchymal stem cells (MSCs) obtained from ageing gingival tissues, in order to suggest their potential role in autologous stem cell therapy for old individuals. Methods: MSCs were isolated from gingival tissues of young (18-45 years) and old (above 45 years) donors by enzymatic digestion. MSCs were analysed for cfu-f, surface marker expression by flow-cytometry and multilineage differentiation potential. The angiogenic potential was compared in a chick embryo yolk sac membrane model. The aging and differentiation markers including SA-β-galactosidase and p21 respectively were analysed by staining and flow-cytometry analysis. Additionally, osteogenic markers such as glucocorticoid receptor (GR), vitamin D receptor (VDR) were measured by flow-cytometry and RT-qPCR was performed for quantification of osteogenic gene expression. Alizarin Red S and alkaline phosphatase (ALP) activity were also quantitated. Results: Gingival MSCs (GMSCs) from both the age groups were similar in their morphology and displayed cfu-f. They had similar expression of MSC surface markers and p21, comparable rate of proliferation and differentiated to all the four lineages. GMSCs from young donors had a higher adipogenic differentiation potential as compared to the old GMSCs. Moreover, these cells did not display a significant difference in ALP activity probably due to comparable expression of GR, VDR, and osteogenic genes. Conclusions: Ageing of GMSCs occurs at a much slower rate than stem cells from other sources. Thus we suggest GMSCs as an excellent candidate for autologous stem cell therapy in degenerative diseases of elderly individuals. Clinical Significance: GMSCs could help overcome the setbacks in clinical implementation of autologous stem cell therapy for regenerative medicine in all age group of patient.

Keywords: bone regeneration, cell therapy, senescence, stem cell

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6328 Ultrasonographic Manifestation of Periventricular Leukomalacia in Preterm Neonates at Teaching Hospital Peradeniya, Sri Lanka

Authors: P. P. Chandrasekera, P. B. Hewavithana, S. Rosairo, M. H. M. N. Herath, D. M. R. D. Mirihella

Abstract:

Periventricular Leukomalacia (PVL) is a White Matter Injury (WMI) of preterm neonatal brain. Objectives of the study were to assess the neuro-developmental outcome at one year of age and to determine a good protocol of cranial ultrasonography to detect PVL. Two hundred and sixty four preterm neonates were included in the study. Series of cranial ultrasound scans were done by using a dedicated neonatal head probe 4-10 MHz of Logic e portable ultrasound scanner. Clinical history of seizures, abnormal head growth (hydrocephalus or microcephaly) and developmental milestones were assessed and neurological examinations were done until one year of age. Among live neonates, 57% who had cystic PVL (Grades2 and 3) manifested as cerebral palsy. In conclusion cystic PVL has permanent neurological disabilities like cerebral palsy. Good protocol of real time cranial ultrasonography to detect PVL is to perform scans at least once a week until one month and at term (40 weeks of gestation).

Keywords: cerebral palsy, cranial ultrasonography, Periventricular Leukomalacia, preterm neonates

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