Search results for: academic learning stress

Authors: Marta Fonseca, Pedro Marvão, Beatriz Oliveira, Bruno Heleno, Pedro Carreiro-Martins, Nuno Neuparth, António Rendas

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Background: Concept maps (CMs) visually represent hierarchical connections among related ideas. They foster logical organization and clarify idea relationships, potentially aiding medical students in critical thinking (to think clearly and rationally about what to do or what to believe). However, there are inconsistent claims about the use of CMs in undergraduate medical education. Our three research questions are: 1) What studies have been published on concept mapping in undergraduate medical education? 2) What was the impact of CMs on students’ critical thinking? 3) How and why have these interventions had an educational impact? Methods: Eight databases were systematically searched (plus a manual and an additional search were conducted). After eliminating duplicate entries, titles, and abstracts, and full-texts were independently screened by two authors. Data extraction and quality assessment of the studies were independently performed by two authors. Qualitative and quantitative data were integrated using mixed-methods. The results were reported using the structured approach to the reporting in healthcare education of evidence synthesis statement and BEME guidance. Results: Thirty-nine studies were included from 26 journals (19 quantitative, 8 qualitative and 12 mixed-methods studies). CMs were considered as a tool to promote critical thinking, both in the perception of students and tutors, as well as in assessing students’ knowledge and/or skills. In addition to their role as facilitators of knowledge integration and critical thinking, CMs were considered both teaching and learning methods. Conclusions: CMs are teaching and learning tools which seem to help medical students develop critical thinking. This is due to the flexibility of the tool as a facilitator of knowledge integration, as a learning and teaching method. The wide range of contexts, purposes, and variations in how CMs and instruments to assess critical thinking are used increase our confidence that the positive effects are consistent.

Keywords: concept map, medical education, undergraduate, critical thinking, meaningful learning

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Authors: Lana Burmistrova

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Introduction: The influence of visual impairments on several cognitive processes used in the music learning process is an increasingly important area in special education and cognitive musicology. Many children have several visual impairments due to the refractive errors and irreversible inhibitors. However, based on the compensatory neuroplasticity and functional reorganization, congenitally blind (CB) and early blind (EB) individuals use several areas of the occipital lobe to perceive and process auditory and tactile information. CB individuals have greater memory capacity, memory reliability, and less false memory mechanisms are used while executing several tasks, they have better working memory (WM) and short-term memory (STM). Blind individuals use several strategies while executing tactile and working memory n-back tasks: verbalization strategy (mental recall), tactile strategy (tactile recall) and combined strategies. Methods and design: The aim of the pilot study was to substantiate similar tendencies while executing attention, memory and combined auditory tasks in blind and sighted individuals constructed for this study, and to investigate attention, memory and combined mechanisms used in the music learning process. For this study eight (n=8) blind and eight (n=8) sighted individuals aged 13-20 were chosen. All respondents had more than five years music performance and music learning experience. In the attention task, all respondents had to identify pitch changes in tonal and randomized melodic pairs. The memory task was based on the mismatch negativity (MMN) proportion theory: 80 percent standard (not changed) and 20 percent deviant (changed) stimuli (sequences). Every sequence was named (na-na, ra-ra, za-za) and several items (pencil, spoon, tealight) were assigned for each sequence. Respondents had to recall the sequences, to associate them with the item and to detect possible changes. While executing the combined task, all respondents had to focus attention on the pitch changes and had to detect and describe these during the recall. Results and conclusion: The results support specific features in CB and EB, and similarities between late blind (LB) and sighted individuals. While executing attention and memory tasks, it was possible to observe the tendency in CB and EB by using more precise execution tactics and usage of more advanced periodic memory, while focusing on auditory and tactile stimuli. While executing memory and combined tasks, CB and EB individuals used passive working memory to recall standard sequences, active working memory to recall deviant sequences and combined strategies. Based on the observation results, assessment of blind respondents and recording specifics, following attention and memory correlations were identified: reflective attention and STM, reflective attention and periodic memory, auditory attention and WM, tactile attention and WM, auditory tactile attention and STM. The results and the summary of findings highlight the attention and memory features used in the music learning process in the context of blindness, and the tendency of the several attention and memory types correlated based on the task, strategy and individual features.

Keywords: attention, blindness, memory, music learning, strategy

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Authors: Aaditya U. Jhamb

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Due to the current energy crisis that many countries are battling, energy-efficient buildings are the subject of extensive research in the modern technological era because of growing worries about energy consumption and its effects on the environment. The paper explores 8 factors that help determine energy efficiency for a building: (relative compactness, surface area, wall area, roof area, overall height, orientation, glazing area, and glazing area distribution), with Tsanas and Xifara providing a dataset. The data set employed 768 different residential building models to anticipate heating and cooling loads with a low mean squared error. By optimizing these characteristics, machine learning algorithms may assess and properly forecast a building's heating and cooling loads, lowering energy usage while increasing the quality of people's lives. As a result, the paper studied the magnitude of the correlation between these input factors and the two output variables using various statistical methods of analysis after determining which input variable was most closely associated with the output loads. The most conclusive model was the Decision Tree Regressor, which had a mean squared error of 0.258, whilst the least definitive model was the Isotonic Regressor, which had a mean squared error of 21.68. This paper also investigated the KNN Regressor and the Linear Regression, which had to mean squared errors of 3.349 and 18.141, respectively. In conclusion, the model, given the 8 input variables, was able to predict the heating and cooling loads of a residential building accurately and precisely.

Keywords: energy efficient buildings, heating load, cooling load, machine learning models

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Authors: Gideon Baffoe

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The concept of neighbourhood remains highly relevant in urban studies. However, until now, no attempt has been made to statistically chart the field. This study aims to provide a macroscopic overview using bibliometric analysis of the main characteristics of neighbourhood research in order to understand the academic landscape. The study analyses the emergence and evolution of the concept of neighbourhood in published research, conceptual and intellectual structures as well as scholarship collaboration. It is found that topics related to the local economy of neighbourhoods are sparse, suggesting a major gap in the literature.

Keywords: neighbourhood, global south, bibliometric analysis, scholarship

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Authors: V. W. Kamgang, A. Van Der Goot, N. C. Bennett, A. Ganswindt

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The roan antelope (Hippotragus equinus) is the second largest antelope species in Africa. These past decades, populations of roan antelope are declining drastically throughout Africa. This situation resulted in the development of intensive breeding programmes for this species in Southern African, where they are popular game ranching herbivores in with increasing numbers in captivity. Nowadays, avoidance of stress is important when managing wildlife to ensure animal welfare. In this regard, a non-invasive approach to monitor the adrenocortical function as a measure of stress would be preferable, since animals are not disturbed during sample collection. However, to date, a non-invasive method has not been established for the roan antelope. In this study, we validated a non-invasive technique to monitor the adrenocortical function in this species. Herein, we performed an adrenocorticotropic hormone (ACTH) stimulation test at Lapalala reserve Wilderness, South Africa, using adult captive roan antelopes to determine the stress-related physiological responses. Two individually housed roan antelope (a male and a female) received an intramuscular injection with Synacthen depot (Norvatis) loaded into a 3ml syringe (Pneu-Dart) at an estimated dose of 1 IU/kg. A total number of 86 faecal samples (male: 46, female: 40) were collected 5 days before and 3 days post-injection. All samples were then lyophilised, pulverized and extracted with 80% ethanol (0,1g/3ml) and the resulting faecal extracts were analysed for immunoreactive faecal glucocorticoid metabolite (fGCM) concentrations using five enzyme immunoassays (EIAs); (i) 11-oxoaetiocholanolone I (detecting 11,17 dioxoandrostanes), (ii) 11-oxoaetiocholanolone II (detecting fGCM with a 5α-pregnane-3α-ol-11one structure), (iii) a 5α-pregnane-3β-11β,21-triol-20-one (measuring 3β,11β-diol CM), (iv) a cortisol and (v) a corticosterone. In both animals, all EIAs detected an increase in fGCM concentration 100% post-ACTH administration. However, the 11-oxoaetiocholanolone I EIA performed best, with a 20-fold increase in the male (baseline: 0.384 µg/g, DW; peak: 8,585 µg/g DW) and a 17-fold in the female (baseline: 0.323 µg/g DW, peak: 7,276 µg/g DW), measured 17 hours and 12 hours post-administration respectively. These results are important as the ability to assess adrenocortical function non-invasively in roan can now be used as an essential prerequisite to evaluate the effects of stressful circumstances; such as variation of environmental conditions or reproduction in other to improve management strategies for the conservation of this iconic antelope species.

Keywords: adrenocorticotropic hormone challenge, adrenocortical function, captive breeding, non-invasive method, roan antelope

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Authors: Yingwei Hou, Tao Liu, Yong Pang

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The paper explored the three-dimensional deformation of mussel plaques anchor to wet polydimethylsiloxane (PDMS) substrates under tension stress with different angles. Mussel plaques exhibiting natural adhesive structures, have attracted significant attention for their remarkable adhesion properties. Understanding their behavior under mechanical stress, particularly in a three-dimensional context, holds immense relevance for biomimetic material design and bio-inspired adhesive development. This study employed a novel approach to investigate the 3D deformation of the PDMS substrates anchored by mussel plaques subjected to controlled tension. Utilizing our customized stereo digital image correlation technique and mechanical mechanics analyses, we found the distributions of the displacement and resultant force on the substrate became concentrated under the plaque. Adhesion and sucking mechanisms were analyzed for the mussel plaque-substrate system under tension until detachment. The experimental findings were compared with a developed model using finite element analysis and the results provide new insights into mussels’ attachment mechanism. This research not only contributes to the fundamental understanding of biological adhesion but also holds promising implications for the design of innovative adhesive materials with applications in fields such as medical adhesives, underwater technologies, and industrial bonding. The comprehensive exploration of mussel plaque behavior in three dimensions is important for advancements in biomimicry and materials science, fostering the development of adhesives that emulate nature's efficiency.

Keywords: adhesion mechanism, mytilus edulis, mussel plaque, stereo digital image correlation

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Authors: Afsaneh Jasmine Majidi

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Language testing is an important part of language teaching experience and language learning process as it presents assessment strategies for teachers to evaluate the efficiency of teaching and for learners to examine their outcomes. However, language testing is demanding and challenging because it should provide the opportunity for proper and objective decision. In addition to all the efforts test designers put to design valid and reliable tests, there are some other determining factors which are even more complex and complicated. These factors affect the educational system, individuals, and society, and the impact of the tests vary according to the scope of the test. Seemingly, the impact of a simple classroom assessment is not the same as that of high stake tests such as International English Language Testing System (IELTS). As the importance of the test increases, it affects wider domain. Accordingly, the impacts of high stake tests are reflected not only in teaching, learning strategies but also in society. Testing experts use the term ‘washback’ or ‘impact’ to define the different effects of a test on teaching, learning, and community. This paper first looks at the theoretical background of ‘washback’ and ‘impact’ in language testing by reviewing of relevant literature in the field and then investigates washback effects of IELTS test of on Iranian IELTS teachers and students. The study found significant relationship between the washback effect of IELTS test and teaching strategies of Iranian IELTS teachers as well as performance of Iranian IELTS candidates and their community.

Keywords: high stake tests, IELTS, Iranian Candidates, language testing, test impact, washback

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Authors: Fatna Benmessaoud, Mohammed Cheikh, Vencent Velay, Vanessa Vedal, Farhad Rezai-Aria, Christine Boher

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The global mechanical behavior of materials is strongly linked to their microstructure, especially their crystallographic texture and their grains morphology. These material aspects determine the mechanical fields character (heterogeneous or homogeneous), thus, they give to the global behavior a degree of anisotropy according the initial microstructure. For these reasons, the prediction of global behavior of materials in relationship with the microstructure must be performed with a multi-scale approach. Therefore, multi-scale modeling in the context of crystal plasticity is widely used. In this present contribution, a phenomenological elasto-viscoplastic model developed in the crystal plasticity context and finite element method are used to investigate the effects of crystallographic texture and grains sizes on global behavior of a polycrystalline equiaxed Ti-6Al-4V alloy. The constitutive equations of this model are written on local scale for each slip system within each grain while the strain and stress mechanical fields are investigated at the global scale via finite element scale transition. The beta phase of Ti-6Al-4V alloy modeled is negligible; its percent is less than 10%. Three families of slip systems of alpha phase are considered: basal and prismatic families with a burgers vector and pyramidal family with a burgers vector. The twinning mechanism of plastic strain is not observed in Ti-6Al-4V, therefore, it is not considered in the present modeling. Nine representative elementary volumes (REV) are generated with Voronoi tessellations. For each individual equiaxed grain, the own crystallographic orientation vis-à-vis the loading is taken into account. The meshing strategy is optimized in a way to eliminate the meshing effects and at the same time to allow calculating the individual grain size. The stress and strain fields are determined in each Gauss point of the mesh element. A post-treatment is used to calculate the local behavior (in each grain) and then by appropriate homogenization, the macroscopic behavior is calculated. The developed model is validated by comparing the numerical simulation results with an experimental data reported in the literature. It is observed that the present model is able to predict the global mechanical behavior of Ti-6Al-4V alloy and investigate the microstructural parameters' effects. According to the simulations performed on the generated volumes (REV), the macroscopic mechanical behavior of Ti-6Al-4V is strongly linked to the active slip systems family (prismatic, basal or pyramidal). The crystallographic texture determines which family of slip systems can be activated; therefore it gives to the plastic strain a heterogeneous character thus an anisotropic macroscopic mechanical behavior. The average grains size influences also the Ti-6Al-4V mechanical proprieties, especially the yield stress; by decreasing of the average grains size, the yield strength increases according to Hall-Petch relationship. The grains sizes' distribution gives to the strain fields considerable heterogeneity. By increasing grain sizes, the scattering in the localization of plastic strain is observed, thus, in certain areas the stress concentrations are stronger than other regions.

Keywords: microstructural parameters, multi-scale modeling, crystal plasticity, Ti-6Al-4V alloy

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Authors: Kelli G. Thorup, Kristopher A. Blee

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Climate change enhances the occurrence of extreme weather: wildfires, drought, rising summer temperatures, all of which dramatically decline forest growth and increase tree mortality in the mixed-conifer forests of Sierra Nevada, California. However, microbiota living in mutualistic relations with plant rhizospheres have been found to mitigate the effects of suboptimal environmental conditions. The goal of this research is to isolate native beneficial bacteria, plant-growth promoting rhizobacteria (PGPR), that can alleviate heat stress in Pinus ponderosa seedlings. Bacteria were isolated from the rhizosphere of Pinus ponderosa juveniles located in mixed-conifer stand and further characterized for PGP potential based on their ability to produce key growth regulatory phytohormones including auxin, cytokinin, and gibberellic acid. Out of ten soil samples taken, sixteen colonies were isolated and qualitatively confirmed to produce indole-3-acetic acid (auxin) using Salkowski’s reagent. Future testing will be conducted to quantitatively assess phytohormone production in bacterial isolates. Furthermore, bioassays will be performed to determine isolates abilities to increase tolerance in heat-stressed Pinus ponderosa seedlings. Upon completion of this research, a PGPR could be utilized to support the growth and transplantation of conifer seedlings as summer temperatures continue to rise due to the effects of climate change.

Keywords: conifer, heat-stressed, phytohormones, Pinus ponderosa, plant-growth promoting rhizobacteria

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Authors: W. Zekri

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This paper explores Zohra Drif’s memoir, Inside the Battle of Algiers, which narrates her desires as a student to become a revolutionary activist. She exemplified, in her narrative, the different roles, she and her fellows performed as combatants in the Casbah during the Algerian Revolution 1954-1962. This book review aims to evaluate the concept of women’s agency through education and language learning, and its impact on empowering women’s desires. Close-reading method and thematic analysis are used to explore the text. The analysis identified themes that refine the meaning of agency which are social and cultural supports, education, and language proficiency. These themes aim to contribute to the representation in Inside the Battle of Algiers of a woman guerrilla who engaged herself to perform national acts of resistance.

Keywords: agency, education, learning, women

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Authors: J. A. Marañón, L. Lozano C. De Los Santos, L. Martínez-Campesino, E. Caballero-Garrido, F. Galán-Estella

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Urinary incontinence (UI) is a significant health problem with considerable social and economic impact. An estimated 30% of women aged 30 to 60 years old have urinary incontinence (UI), while more than 50% of community-dwelling older women have the condition. Stress urinary incontinence and overactive bladder are the common types of incontinence The prevalence of stress and mixed (stress and urge) incontinence is higher than urge incontinence, but the latter is more likely to require treatment. In women, moderate and severe have a prevalence ranging from about 12% to 17% The objectives of this study was to examine the effect of the supplementation of tablets containing Dropsordry in women with urge urinary incontinence (UUI). Dropsordry is a novel active containing phytoestrogens from SOLGEN, the high genistin soy bean extract and pyrogallol plus polyphenols from standarized pumpkin seed extract,. The study was a single-center, not randomiized open prospective, study. 28 women with urinary incontinence ≥45 years were enrolled in this study (45-62 y. old age . Mean 52 y old). Items related to UI symptoms, were previously collected (T0) and these ítems were reviewed at the final of the study – 8 weeks. (T2). The presence of UI was previously diagnosed using the International Continence Society standards (ICS). Relationships between presence of UI and potential related factors as diabetes were also explored. Daily urinary test control was performed during the 8 weeks of treatment. Daily dosage was 1 g/ day (500 mg twice per day) from 0 to 4 week (T1), following a 500 mg/day daily intake from 4 to 8 week (T2). After eight weeks of treatment, the urgency grade score was reduced a 24,7%. The total urge episodes was reduced a 46%. Surprisingly there was no a significant change in daytime urinations (< 5%), however nocturia was reduced a 69,35%. Strenght Urinary Incontinence (SUI) was also tested showing a remarkably 52,17% reduction. Moreover the use of daily pantyliners was reduced a 66,25%. In addition, it was performed a panel test survey with quests when subjects of the study were enrolled (T0) and the same quests was performed after 8 weeks of supplementation (T2). 100% of the enrolled women fullfilled the ICIQ-SF quest (Spanish versión) and they were also questioned about the effects they noticed in response to taking the supplement and the change in quality of life. Interestingly no side effects were reported. There was a 96,2% of subjective satisfaction and a 85,8% objective score in the improvement of quality of life. CONCLUSION: the combination of High genistin isoflavones and pumpkin seed pyrogallol in Dropsordry tablets seems to be a safe and highly effective supplementation for the relieve of the urinary incontinence symptoms and a better quality of life in perimenopause women .

Keywords: isoflavones, pumpkin, menopause, incontinence, genistin

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Authors: Ahmed I. Alutabi, Naghmeh Dezhabad, Sudhakar Ganti

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Data centers have been growing in size and dema nd continuously in the last two decades. Planning for the deployment of resources has been shallow and always resorted to over-provisioning. Data center operators try to maximize the availability of their services by allocating multiple of the needed resources. One resource that has been wasted, with little thought, has been energy. In recent years, programmable resource allocation has paved the way to allow for more efficient and robust data centers. In this work, we examine the predictability of resource usage in a data center environment. We use a number of models that cover a wide spectrum of machine learning categories. Then we establish a framework to guarantee the client service level agreement (SLA). Our results show that using prediction can cut energy loss by up to 55%.

Keywords: machine learning, artificial intelligence, prediction, data center, resource allocation, green computing

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Authors: Todd Zhou, Mikhail Yurochkin

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Out-of-distribution (OOD) detection is receiving increasing amounts of attention in the machine learning research community, boosted by recent technologies, such as autonomous driving and image processing. This newly-burgeoning field has called for the need for more effective and efficient methods for out-of-distribution generalization methods. Without accessing the label information, deploying machine learning models to out-of-distribution domains becomes extremely challenging since it is impossible to evaluate model performance on unseen domains. To tackle this out-of-distribution detection difficulty, we designed a model selection pipeline algorithm and developed a model selection framework with different impurity and randomness measurements to evaluate and choose the best-performing models for out-of-distribution data. By exploring different randomness scores based on predicted probabilities, we adopted the out-of-distribution entropy and developed a custom-designed score, ”CombinedScore,” as the evaluation criterion. This proposed score was created by adding labeled source information into the judging space of the uncertainty entropy score using harmonic mean. Furthermore, the prediction bias was explored through the equality of opportunity violation measurement. We also improved machine learning model performance through model calibration. The effectiveness of the framework with the proposed evaluation criteria was validated on the Folktables American Community Survey (ACS) datasets.

Keywords: model selection, domain generalization, model fairness, randomness measurements, bias index

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Authors: Sevana Daneghian, Leila Chodari, Sahar Mehranfar, Shadi Mohammadpour-Asl, Diman Mahdi

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Sarcopenia is an age-related muscle disease. Lack of antioxidant protection, and cumulative oxidative damage to skeletal muscle are recognized mechanisms. Curcumin is a hormetin as it has a stimulating effect in low doses and an inhibitory effect in high doses. The purpose of this study was to examine the effects of four weeks of curcumin supplementation in presarcopenic and sarcopenic rats, and likelihood of potential negative effects while co-exist with sarcopenia. The rats were divided into 7 groups: young sham rats, 18 months old; presarcopenic control, supplemented with 400 and 1500 mg/kg/day, 24 months old; Sarcopenia control, sarcopenia supplemented with 400 and 1500 mg/kg/day. MDA levels were significantly reduced in the low-dose pre-sarcopenic group compared to the control group. Compared to the corresponding control groups, SOD levels decreased in the groups treated with low-dose presarcopenic supplementation and increased in the high-dose sarcopenic supplemented. GPx levels increased at both doses only in the sarcopenic group compared to the control group. SIRT-1 only increased at low doses in the sarcopenic groups and PGC-1α in both pre-sarcopenia groups compared to the corresponding control. IGF-1 increased compared to the control group at both doses in the pre-sarcopenic group and at high doses in sarcopenic group. Considering the hormetic effects of curcumin, it can be argued that, curcumin supplementation has some positive effects not only at low but also at high doses in both groups. This means that the high doses of curcumin have no negative synergistic effects in addition to oxidative stress during sarcopenia and high-dose supplementation in patients already suffering from high oxidative stress due to sarcopenia is safe and could be considered hormetic.

Keywords: curcumin, hormesis, sarcopenia, muscular atrophy, PGC protein, Sirtuins

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Authors: Vesile Evrim, Aliyu Awwal

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Today as in the other domains, there are an enormous number of political transcripts available in the Web which is waiting to be mined and used for various purposes such as statistics and recommendations. Therefore, automatically determining the political orientation on these transcripts becomes crucial. The methodologies used by machine learning algorithms to do the automatic classification are based on different features such as Linguistic. Considering the ideology differences between Liberals and Conservatives, in this paper, the effect of Personality Traits on political orientation classification is studied. This is done by considering the correlation between LIWC features and the BIG Five Personality Traits. Several experiments are conducted on Convote U.S. Congressional-Speech dataset with seven benchmark classification algorithms. The different methodologies are applied on selecting different feature sets that constituted by 8 to 64 varying number of features. While Neuroticism is obtained to be the most differentiating personality trait on classification of political polarity, when its top 10 representative features are combined with several classification algorithms, it outperformed the results presented in previous research.

Keywords: politics, personality traits, LIWC, machine learning

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Authors: Dasom Kim, William Xiu Shun Wong, Yoonjin Hyun, Donghoon Lee, Minji Paek, Sungho Byun, Namgyu Kim

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There have been many researches on document classification for classifying voluminous documents automatically. Through document classification, we can assign a specific category to each unlabeled document on the basis of various machine learning algorithms. However, providing labeled documents manually requires considerable time and effort. To overcome the limitations, the semi-supervised learning which uses unlabeled document as well as labeled documents has been invented. However, traditional document classifiers, regardless of supervised or semi-supervised ones, cannot sufficiently explain the reason or the process of the classification. Thus, in this paper, we proposed a methodology to visualize major topics and class components of each document. We believe that our methodology for visualizing topics and classes of each document can enhance the reliability and explanatory power of document classifiers.

Keywords: data mining, document classifier, text mining, topic modeling

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Authors: Chirine Dannaoui, Maya Antoun

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This paper explores the intricate dynamics of play-based early childhood education (ECE) and the impact of professional development on teachers implementing play-based pedagogy, particularly in the context of vulnerable Syrian refugee children in Lebanon. By utilizing qualitative methodologies, including classroom observations and in-depth interviews with five early childhood educators and a field manager, this study delves into the challenges and transformations experienced by teachers in adopting play-based learning strategies. The research unveils the critical role of continuous and context-specific professional development in empowering teachers to implement play-based pedagogies effectively. When appropriately supported, it emphasizes how such educational approaches significantly enhance children's cognitive, social, and emotional development in crisis-affected environments. Key findings indicate that despite diverse educational backgrounds, teachers show considerable growth in their pedagogical skills through targeted professional development. This growth is vital for fostering a learning environment where vulnerable children can thrive, particularly in humanitarian settings. The paper also addresses educators' challenges, including adapting to play-based methodologies, resource limitations, and balancing curricular requirements with the need for holistic child development. This study contributes to the discourse on early childhood education in crisis contexts, emphasizing the need for sustainable, well-structured professional development programs. It underscores the potential of play-based learning to bridge educational gaps and contribute to the healing process of children facing calamity. The study highlights significant implications for policymakers, educators, schools, and not-for-profit organizations engaged in early childhood education in humanitarian contexts, stressing the importance of investing in teacher capacity and curriculum reform to enhance the quality of education for children in general and vulnerable ones in particular.

Keywords: play-based learning, professional development, vulnerable children, early childhood education

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Authors: Kwangmin Joo

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Automatic detection of lumbar vertebrae and classification method is proposed for evaluating the degree of disc narrowing. Prior to classification, deep learning based segmentation is applied to detect individual lumbar vertebra. M-net is applied to segment five lumbar vertebrae and fine-tuning segmentation is employed to improve the accuracy of segmentation. Using the features extracted from previous step, clustering technique, k-means clustering, is applied to estimate the degree of disc space narrowing under four grade scoring system. As preliminary study, techniques proposed in this research could help building an automatic scoring system to diagnose the severity of disc narrowing from X-ray images.

Keywords: Disc space narrowing, Degenerative disc disorders, Deep learning based segmentation, Clustering technique

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Authors: Ghazala Hcini, Imen Jdey, Hela Ltifi

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Malaria disease should be considered and handled as a potential restorative catastrophe. One of the most challenging tasks in the field of microscopy image processing is due to differences in test design and vulnerability of cell classifications. In this article, we focused on applying deep learning to classify patients by identifying images of infected and uninfected cells. We performed multiple forms, counting a classification approach using the Hue, Saturation, Value (HSV) color space. HSV is used since of its superior ability to speak to image brightness; at long last, for classification, a convolutional neural network (CNN) architecture is created. Clusters of focus were used to deliver the classification. The highlights got to be forbidden, and a few more clamor sorts are included in the information. The suggested method has a precision of 99.79%, a recall value of 99.55%, and provides 99.96% accuracy.

Keywords: deep learning, convolutional neural network, image classification, color transformation, HSV color, malaria diagnosis, malaria cells images

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Authors: Sandhya Manjunath

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The World Association for Sport Management (WASM) was established in 2012, and its mission is "to facilitate sport management research, teaching, and learning excellence and professional practice worldwide". As the field of sport management evolves, it have seen increasing globalization of not only the sport product but many educators have also internationalized courses and curriculums. Curricula should reflect globally recognized issues and disseminate specific intercultural knowledge, skills, and practices, but regional disparities still exist. For example, while India has some of the most ardent sports fans and events in the world, sport management education programs and the development of a proper curriculum in India are still in their nascent stages, especially in comparison to the United States and Europe. Using the extant literature on professionalization and institutional theory, this study aims to investigate the source of knowledge and professionalism of sports managers in India with limited sport management education programs and to subsequently develop a conceptual framework that addresses any gaps or disparities across regions. This study will contribute to WASM's (2022) mission statement of research practice worldwide, specifically to fill the existing disparities between regions. Additionally, this study may emphasize the value of higher education among professionals entering the workforce in the sport industry. Most importantly, this will be a pioneer study highlighting the social issue of limited sport management higher education programs in India and improving professional research practices. Sport management became a field of study in the 1980s, and scholars have studied its professionalization since this time. Dowling, Edwards, & Washington (2013) suggest that professionalization can be categorized into three broad categories of organizational, systemic, and occupational professionalization. However, scant research has integrated the concept of professionalization with institutional theory. A comprehensive review of the literature reveals that sports industry research is progressing in every country worldwide at its own pace. However, there is very little research evidence about the Indian sports industry and the country's limited higher education sport management programs. A growing need exists for sports scholars to pursue research in developing countries like India to develop theoretical frameworks and academic instruments to evaluate the current standards of qualified professionals in sport management, sport marketing, venue and facilities management, sport governance, and development-related activities. This study may postulate a model highlighting the value of higher education in sports management. Education stakeholders include governments, sports organizations and their representatives, educational institutions, and accrediting bodies. As these stakeholders work collaboratively in developed countries like the United States and Europe and developing countries like India, they simultaneously influence the professionalization (i.e., organizational, systemic, and occupational) of sport management education globally. The results of this quantitative study will investigate the current standards of education in India and the source of knowledge among industry professionals. Sports industry professionals will be randomly selected to complete the COSM survey on PsychData and rate their perceived knowledge and professionalism on a Likert scale. Additionally, they will answer questions involving their competencies, experience, or challenges in contributing to Indian sports management research. Multivariate regression will be used to measure the degree to which the various independent variables impact the current knowledge, contribution to research, and professionalism of India's sports industry professionals. This quantitative study will contribute to the limited academic literature available to Indian sports practitioners. Additionally, it shall synthesize knowledge from previous work on professionalism and institutional knowledge, providing a springboard for new research that will fill the existing knowledge gaps. While a further empirical investigation is warranted, our conceptualization contributes to and highlights India's burgeoning sport management industry.

Keywords: sport management, professionalism, source of knowledge, higher education, India

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Authors: Bhawna Chandravanshi, Ramesh Bhonde

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In the present study, we focused on the improvisation of islet survival in hypoxia. The Islet-like cell aggregates (ICAs) derived from Wharton's jelly mesenchymal stem cells (WJ-MSC) were cultured with and without WJ-MSC for 48h in hypoxia and normoxia and tested for their direct trophic effect on β cell survival. The WJ MSCs themselves secreted insulin upon glucose challenge and expressed the pancreatic markers at both transcription and translational level (C-peptide, Insulin, Glucagon and Glut 2). Direct contact of MSCs with ICAs facilitate the highest viability under hypoxia as evidenced by fluorescein diacetate/propidium iodide and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. The cytokine analysis of the co-cultured ICAs revealed amplification of anti-inflammatory cytokine-like TGFβ and TNFα accompanied by depletion of pro-inflammatory cytokines. The increment in VEGF and PDGFa was also seen showing their ability to vascularize upon transplantation. This was further accompanied by reduction in total reactive oxygen species, nitric oxide, and super oxide ions and down-regulation of Caspase3, Caspase8, p53 and up regulation of Bcl2 confirming prevention of apoptosis in ICAs. There was a significant reduction in the expression of p38 protein in the presence of MSCs making the ICAs responsive to glucose. Taken together our data demonstrate for the first time that the WJ-MSC expressed pancreatic markers and their supplementation protected engineered islets against hypoxia, oxidative stress, and inflammatory cytokines by inhibiting p38 MAPK protein.

Keywords: hypoxia, islet-like cell aggregates, inflammatory cytokines, oxidative stress

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Authors: Ayyaz Hussain, Tariq Sadad

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Breast cancer (BC) is one of the widespread ailments among females globally. The early prognosis of BC can decrease the mortality rate. Exact findings of benign tumors can avoid unnecessary biopsies and further treatments of patients under investigation. However, due to variations in images, it is a tough job to isolate cancerous cases from normal and benign ones. The machine learning technique is widely employed in the classification of BC pattern and prognosis. In this research, a deep convolution neural network (DCNN) called AlexNet architecture is employed to get more discriminative features from breast tissues. To achieve higher accuracy, K-nearest neighbor (KNN) classifiers are employed as a substitute for the softmax layer in deep learning. The proposed model is tested on a widely used breast image database called MIAS dataset for experimental purposes and achieved 99% accuracy.

Keywords: breast cancer, DCNN, KNN, mammography

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Authors: Nitin Pipralia, Amit Kmar Sinha, Gudrun de Boeck

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Atmospheric carbon dioxide (CO2) concentrations have been increasing since the beginning of the industrial revolution due to combustion of fossils fuel and many anthropogenic means. As the number of scenarios assembled by the International Panel on Climate Change (IPCC) predict a rise of pCO2 from today’s 380 μatm to approximately 900 μatm until the year 2100 and a further rise of up to 1900 μatm by the year 2300. A rise in pCO2 results in more dissolution in ocean surface water which lead to cange in water pH, This phenomena of decrease in ocean pH due to increase on pCO2 is ocean acidification is considered a potential threat to the marine ecosystems and expected to affect fish as well as calcerious organisms. The situation may get worste when the stress of salinity adds on, due to migratory movement of fishes, where fish moves to different salinity region for various specific activities likes spawning and other. Therefore, to understand the interactive impact of these whole range of two important environmental abiotic stresses (viz. pCO2 ranging from 380 μatm, 900 μatm and 1900 μatm, along with salinity gradients of 32ppt, 10 ppt and 2.5ppt) on the ecophysiologal performance of fish, we investigated various biological adaptive response in European sea bass (Dicentrarchus labrax), a model estuarine teleost. Overall, we hypothesize that effect of ocean acidification would be exacerbate with shift in ambient salinity. Oxygen consumption, ammonia metabolism, iono-osmoregulation, energy budget, ion-regulatory enzymes, hormones and pH amendments in plasma were assayed as the potential indices of compensatory responses.

Keywords: ocean acidification, sea bass, pH climate change, salinity

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Authors: Paula Escudeiro, Nuno Escudeiro, Márcia Campos, Francisca Escudeiro

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In today's world, technical and scientific knowledge plays a vital role in education, research, and employment. Deaf students face unique challenges in educational settings, particularly when it comes to understanding technical and scientific terminology. The reliance on written and spoken languages can create barriers for deaf individuals who primarily communicate using sign language. This lack of accessibility can hinder their learning experience and compromise equity in education. To address this issue, the TechWhiz project has been developed as a comprehensive glossary of scientific and technical concepts explained in sign language. By providing deaf students with access to education in their first language, TechWhiz aims to enhance their learning achievements and promote inclusivity while also fostering equity in education for all students.

Keywords: deaf students, technical and scientific knowledge, automatic sign language, inclusive education

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Authors: M. Cabral, A. Verdin, G. Garçon, A. Touré, C. Diop, M. Fall, S. Bouhsina, D. Dewaele, F.Cazier, A. Tall Dia, P. Shirali, A. Diouf

Abstract:

This case-control study dealt with the health adverse effects within the population neighboring the Mbeubeuss waste dump, which is located near the district of Malika (Diamalaye II) in Dakar (Senegal). All the household and industrial waste arising from Dakar are stored in this open landfill without being covered and are therefore possible sources of Pb and Cd contaminated air emissions and lixiviates. The objective of this study is part of improving the health of the population neighboring Mbeubeuss by determining Pb and Cd concentrations both in environment and humans, and studying possible renal function alterations within the adults. Soil and air samples were collected in the control site (Darou Salam) and the waste dump neighboring site (Diamalaye II). Control and exposed adults were recruited as living in Darou Salam (n = 52) and in Diamalaye II (n = 77). Pb and Cd concentrations in soil, air and biological samples were determined. Moreover, we were interested in analyzing some impregnation (zinc protoporphyrin, d-aminolevulinic acid dehydratase) and oxidative stress biomarkers (malonedialdehyde, gluthatione status), in addition to several nephrotoxicity parameters (creatinuria, proteinuria, lactate dehydrogenase, CC16 protein, glutathione S-transferase-alpha and retinol binding protein) in blood and/or urine. The results showed the significant Pb and Cd contamination of the soil and air samples derived from the landfill, and therefore of the neighboring population of adults. This critical exposure to environmental Pb and Cd had some harmful consequences for their health, as shown by the reported oxidative stress and nephrotoxicity signs.

Keywords: Pb and Cd environmental exposure, impregnation markers, landfill, nephrotoxicity markers

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Authors: Julianne Macmullen

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Due to advances in technology and early detection and treatment of cancer, many cancer patients are surviving longer than five years post-diagnosis. Most cancer patients suffer from depression, anxiety, and post-traumatic stress disorder (PTSD) at some point during diagnosis, treatment, and survivorship. A subgroup of patients will continue to suffer from depression and PTSD and require early intervention. Support groups provide patients with the emotional and informational support they require while also giving survivors a sense of community, friendship, and purpose. This type of support is recognized by researchers to improve the quality of life while also decreasing depression and PTSD symptoms. The gaps in the literature include cultural diversity, minorities, and support groups involving cancer types other than breast cancer. Another gap in the literature includes the perceptions of cancer patients as well as longitudinal studies to determine the relationships between support groups and decreased depression and PTSD rates over time. Future research is required to fill the gaps in the literature mentioned previously. Future research is also needed to analyze the difference in age groups and different types of support groups such as professionally-led, peer-led, and online. Implications for practice involve providers assessing for the symptoms of depression and PTSD in order to offer prompt treatment and support services to those patients. In conclusion, social support by way of support groups improves the quality of life, gives survivors a sense of purpose to help others while also gaining the support they need, and reduces the rate of depressive episodes related to PTSD.

Keywords: cancer survivor, survivorship, post-traumatic stress disorder (PTSD), depression, support groups

Procedia PDF Downloads 158

Authors: Nathenal Thomas

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In the food chain and in many other agricultural products, corn, also known as maize, which goes by the scientific name Zea mays subsp, is a widely produced agricultural product. Corn has the highest adaptability. It comes in many different types, is employed in many different industrial processes, and is more adaptable to different agro-climatic situations. In Ethiopia, maize is among the most widely grown crop. Small-scale corn farming may be a household's only source of food in developing nations like Ethiopia. The aforementioned data demonstrates that the country's requirement for this crop is excessively high, and conversely, the crop's productivity is very low for a variety of reasons. The most damaging disease that greatly contributes to this imbalance between the crop's supply and demand is the corn disease. The failure to diagnose diseases in maize plant until they are too late is one of the most important factors influencing crop output in Ethiopia. This study will aid in the early detection of such diseases and support farmers during the cultivation process, directly affecting the amount of maize produced. The diseases in maize plants, such as northern leaf blight and cercospora leaf spot, have distinct symptoms that are visible. This study aims to detect the most frequent and degrading maize diseases using the most efficiently used subset of machine learning technology, deep learning so, called Image Processing. Deep learning uses networks that can be trained from unlabeled data without supervision (unsupervised). It is a feature that simulates the exercises the human brain goes through when digesting data. Its applications include speech recognition, language translation, object classification, and decision-making. Convolutional Neural Network (CNN) for Image Processing, also known as convent, is a deep learning class that is widely used for image classification, image detection, face recognition, and other problems. it will also use this algorithm as the state-of-the-art for my research to detect maize diseases by photographing maize leaves using a mobile phone.

Keywords: CNN, zea mays subsp, leaf blight, cercospora leaf spot

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Authors: Chantana Insra

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The research objective focuses on creating a prototype media of the tactile texture of muscles for educational institutes to help visually impaired students learn massage extra learning materials further than the ordinary curriculum. This media is designed as an extra learning material. The population in this study was 30 blinded students between 4th - 6th grades who were able to read Braille language. The research was conducted during the second semester in 2012 at The Bangkok School for the Blind. The method in choosing the population in the study was purposive sampling. The methodology of the research includes collecting data related to visually impaired people, the production of the tactile texture media, human anatomy and Thai traditional massage from literature reviews and field studies. This information was used for analyzing and designing 14 tactile texture pictures presented to experts to evaluate and test the media.

Keywords: blind, tactile texture, muscle, visual arts and design

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Authors: Penelope Paliadelis, Asheley Jones, Glenn Campbell

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This paper discusses the development of co-designed capability frameworks for two large multinational organizations led by a university department. The aim was to create evidence-based, integrated capability frameworks that could define, identify, and measure human skill capabilities independent of specific work roles. The frameworks capture and cluster human skills required in the workplace and capture their application at various levels of mastery. Identified capability gaps inform targeted learning opportunities for workers to enhance their employability skills. The paper highlights the value of this evidence-based framework development process in capturing, defining, and assessing desired human-focused capabilities for organizational growth and success.

Keywords: capability framework, human skills, work-integrated learning, credentialing, digital badging

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Authors: Shivani Singh, Shantanu Nakhare, Kalyani Nair, Rohan Shetty

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As social networking is growing at a rapid pace today it is vital that we work on improving its management. Research has shown that the content present in online social networks may have significant influence on impressionable minds. If such platforms are misused, it will lead to negative consequences. Detecting insults or inappropriate messages continues to be one of the most challenging aspects of Online Social Networks (OSNs) today. We address this problem through a Machine Learning Based Soft Text Classifier approach using Support Vector Machine algorithm. The proposed system acts as a screening mechanism the alerts the user about such messages. The messages are classified according to their subject matter and each comment is labeled for the presence of profanity and insults.

Keywords: machine learning, online social networks, soft text classifier, support vector machine

Procedia PDF Downloads 486