Search results for: academic learning stress
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 12229

Search results for: academic learning stress

8119 Do Women with Endometriosis Have Higher Perceived Stress Levels than Healthy Women?

Authors: Jodie Hughes

Abstract:

Endometriosis affects 1 in 10 individuals that were born female globally. Endometriosis incidence rates peak between 30-40 year of age, in young women and adolescents it is a rarely suspected and often ill-diagnosed. The average cost of endometriosis is €9,579 per woman. More than 75% of women have reported being absent from work due to endometriosis, with 40% of women becoming unemployed due to the disease. 46% of patients with endometriosis need to have appointments with upward of five doctors to gain a correct diagnosis. Quantitative data were collected by way of an online PSS-10 survey that included demographic questions from two sample groups of females, group 1 was females with endometriosis, group 2 were healthy women. The data were scored using Cohens scoring system, overall scores were input to SPSS. A non-parametric Mann-Whitney U test and ANOVA was used to ascertain any differences between the PSS-10 scores of the two groups. A significance level of P<0.05 was adopted. Four women were invited to take part in a semi structured interview that was recorded, transcribed and coded using interpretive phenomenological analysis (IPA) using NVivo 12. Results showed that the PSS-10 scores were significantly higher in women with endometriosis compared to healthy women with a p=<0.005. Endometriosis affects all aspects of a patient’s life, to adequately diagnose and treat the condition and improve HRQoL there needs to be better understanding of the clinical symptoms and how they impact the lives of patients.

Keywords: endometriosis, HRQoL, perceived stress, women

Procedia PDF Downloads 118
8118 The Identification of Instructional Approach for Enhancing Competency of Autism, Attention Deficit Hyperactivity Disorder and Learning Disability Groups

Authors: P. Srisuruk, P. Narot

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The purpose of this research were 1) to develop the curriculum and instructional approach that are suitable for children with autism, attention deficit hyperactivity disorder and learning disability as well as to arrange the instructional approach that can be integrated into inclusive classroom 2) to increase the competency of the children in these group. The research processes were to a) study related documents, b) arrange workshops to clarify fundamental issues in developing core curriculum among the researchers and experts in curriculum development, c) arrange workshops to develop the curriculum, submit it to the experts for criticism and editing, d) implement the instructional approach to examine its effectiveness, e) select the schools to participate in the project and arrange training programs for teachers in the selected school, f) implement the instruction approach in the selected schools in different regions. The research results were 1) the core curriculum to enhance the competency of children with autism, attention deficit hyperactivity disorder and learning disability , and to be used as a guideline for teachers, and these group of children in order to arrange classrooms for students with special needs to study with normal students, 2) teaching and learning methods arranged for students with autism, attention deficit, hyperactivity disorder and learning disability to study with normal students can be used as a framework for writing plans to help students with parallel problems by developing teaching materials as part of the instructional approach. However, the details of how to help the students in each skill or content differ according to the demand of development as well as the problems of individual students or group of students. Furthermore; it was found that most of target teacher could implement the instructional approach based on the guideline model developed by the research team. School in each region does not have much difference in their implementation. The good point of the developed instructional model is that teacher can construct a parallel lesson plan. So teacher did not fell that they have to do extra work it was also shown that students in regular classroom enjoyed studying with the developed instructional model as well.

Keywords: instructional approach, autism, attention deficit hyperactivity disorder, learning disability

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8117 Language Services as a Means of Language Repository for Tuition Support and Facilitation of Learning in Institution of Higher Learning

Authors: Mzamani Aaron Mabasa

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The research study examines the reality that the Language Services Directorate can be considered a language repository hub. The study postulates that multilingual education guided by language policy implementation can improve student performance and pass rate. Various documents in the form of style guides, glossaries and tutorial letters may be used to enable students to understand complex words, sentences, phrases and paragraphs when technical vocabularies are used. This paper addresses the way in which quality assurance can transform South African official languages, including Sign Language, as mandated by the Language Policy for Higher Education. The paper further emphasizes that Language Services is unique in the sense that it involves all South African officials as tools for student support and facilitation of learning. This is in line with the Constitution of the Republic of South Africa (1996) and the Unisa Language Policy of 2023, which declares the status, parity and esteem of these official languages regarding usage in formal function domains, namely education, economy, social and politics. The aim of this paper is to ensure that quality assurance is ultimately accomplished in terms of teaching and learning standards. Eventually, all South African languages can be used for official domains to achieve functional multilingualism. This paper furthermore points out that content analysis as a research instrument as far as a qualitative approach is concerned may be used as a data collection technique.

Keywords: repository, multilingualism, policy, education

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8116 Real-Time Kinetic Analysis of Labor-Intensive Repetitive Tasks Using Depth-Sensing Camera

Authors: Sudip Subedi, Nipesh Pradhananga

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The musculoskeletal disorders, also known as MSDs, are common in construction workers. MSDs include lower back injuries, knee injuries, spinal injuries, and joint injuries, among others. Since most construction tasks are still manual, construction workers often need to perform repetitive, labor-intensive tasks. And they need to stay in the same or an awkward posture for an extended time while performing such tasks. It induces significant stress to the joints and spines, increasing the risk of getting into MSDs. Manual monitoring of such tasks is virtually impossible with the handful of safety managers in a construction site. This paper proposes a methodology for performing kinetic analysis of the working postures while performing such tasks in real-time. Skeletal of different workers will be tracked using a depth-sensing camera while performing the task to create training data for identifying the best posture. For this, the kinetic analysis will be performed using a human musculoskeletal model in an open-source software system (OpenSim) to visualize the stress induced by essential joints. The “safe posture” inducing lowest stress on essential joints will be computed for different actions involved in the task. The identified “safe posture” will serve as a basis for real-time monitoring and identification of awkward and unsafe postural behaviors of construction workers. Besides, the temporal simulation will be carried out to find the associated long-term effect of repetitive exposure to such observed postures. This will help to create awareness in workers about potential future health hazards and encourage them to work safely. Furthermore, the collected individual data can then be used to provide need-based personalized training to the construction workers.

Keywords: construction workers’ safety, depth sensing camera, human body kinetics, musculoskeletal disorders, real time monitoring, repetitive labor-intensive tasks

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8115 Experimental Studies of the Reverse Load-Unloading Effect on the Mechanical, Linear and Nonlinear Elastic Properties of n-AMg6/C60 Nanocomposite

Authors: Aleksandr I. Korobov, Natalia V. Shirgina, Aleksey I. Kokshaiskiy, Vyacheslav M. Prokhorov

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The paper presents the results of an experimental study of the effect of reverse mechanical load-unloading on the mechanical, linear, and nonlinear elastic properties of n-AMg6/C60 nanocomposite. Samples for experimental studies of n-AMg6/C60 nanocomposite were obtained by grinding AMg6 polycrystalline alloy in a planetary mill with 0.3 wt % of C60 fullerite in an argon atmosphere. The resulting product consisted of 200-500-micron agglomerates of nanoparticles. X-ray coherent scattering (CSL) method has shown that the average nanoparticle size is 40-60 nm. The resulting preform was extruded at high temperature. Modifications of C60 fullerite interferes the process of recrystallization at grain boundaries. In the samples of n-AMg6/C60 nanocomposite, the load curve is measured: the dependence of the mechanical stress σ on the strain of the sample ε under its multi-cycle load-unloading process till its destruction. The hysteresis dependence σ = σ(ε) was observed, and insignificant residual strain ε < 0.005 were recorded. At σ≈500 MPa and ε≈0.025, the sample was destroyed. The destruction of the sample was fragile. Microhardness was measured before and after destruction of the sample. It was found that the loading-unloading process led to an increase in its microhardness. The effect of the reversible mechanical stress on the linear and nonlinear elastic properties of the n-AMg6/C60 nanocomposite was studied experimentally by ultrasonic method on the automated complex Ritec RAM-5000 SNAP SYSTEM. In the n-AMg6/C60 nanocomposite, the velocities of the longitudinal and shear bulk waves were measured with the pulse method, and all the second-order elasticity coefficients and their dependence on the magnitude of the reversible mechanical stress applied to the sample were calculated. Studies of nonlinear elastic properties of the n-AMg6/C60 nanocomposite at reversible load-unloading of the sample were carried out with the spectral method. At arbitrary values of the strain of the sample (up to its breakage), the dependence of the amplitude of the second longitudinal acoustic harmonic at a frequency of 2f = 10MHz on the amplitude of the first harmonic at a frequency f = 5MHz of the acoustic wave is measured. Based on the results of these measurements, the values of the nonlinear acoustic parameter in the n-AMg6/C60 nanocomposite sample at different mechanical stress were determined. The obtained results can be used in solid-state physics, materials science, for development of new techniques for nondestructive testing of structural materials using methods of nonlinear acoustic diagnostics. This study was supported by the Russian Science Foundation (project №14-22-00042).

Keywords: nanocomposite, generation of acoustic harmonics, nonlinear acoustic parameter, hysteresis

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8114 Exploring Mtb-Mle Practices in Selected Schools in Benguet, Philippines

Authors: Jocelyn L. Alimondo, Juna O. Sabelo

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This study explored the MTB-MLE implementation practices of teachers in one monolingual elementary school and one multilingual elementary school in Benguet, Philippines. It used phenomenological approach employing participant-observation, focus group discussion and individual interview. Data were gathered using a video camera, an audio recorder, and an FGD guide and were treated through triangulation and coding. From the data collected, varied ways in implementing the MTB-MLE program were noted. These are: Teaching using a hybrid first language, teaching using a foreign LOI, using translation and multilingual instruction, and using L2/L3 to unlock L1. However, these practices come with challenges such as the a conflict between the mandated LOI and what pupils need, lack of proficiency of teachers in the mandated LOI, facing unreceptive parents, stagnation of knowledge resulting from over-familiarity of input, and zero learning resulting from an incomprehensible language input. From the practices and challenges experienced by the teachers, a model of MTB-MLE approach, the 3L-in-one approach, to teaching was created to illustrate the practice which teachers claimed to be the best way to address the challenges besetting them while at the same time satisfying the academic needs of their pupils. From the findings, this paper concludes that despite the challenges besetting the teachers, they still displayed creativity in coming up with relevant teaching practices, the unreceptiveness of some teachers and parents sprung from the fact that they do not understand the real concept of MTB-MLE, greater challenges are being faced by teachers in multilingual school due to the diverse linguistic background of their clients, and the most effective approach in implementing MTB-MLE is the multilingual approach, allowing the use of the pupils’ mother tongue, L2 (Filipino), L3 (English), and other languages familiar to the students.

Keywords: MTB-MLE Philippines, MTB-MLE model, first language, multilingual instruction

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8113 Implementation of Risk Management System to Improve the Quality of Higher Education Institutes

Authors: Muhammad Wasif, Asif Ahmed Shaikh, Sarosh Hashmat Lodi, Muhammad Aslam Bhutto, Riazuddin

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Risk Management System is quite popular in profit- based organizations, health and safety and project management fields since the last few decades. But due to rapidly changing environment and requirement of ISO 9001:2015 standards, public-sector institution, especially higher education institutes are also performing risk assessment to monitor the performance of the institution and aligning it with the latest benchmark. In this context, NED University of Engineering and Technology performed research and developed a Standard Operating Procedure (SOP) for the risk assessment, its monitoring and control. In this research, risks are broken into the four sources, namely; Internal Academics Risks, External Academics Risks, Internal Non-academic Risks, External Non-academic Risks. Risks are identified by the management at all levels. Severity and likelihood of the risks are assigned based on the previous audit results and the customer complains. Risk Ratings are calculated to orderly arrange the risk according to the Risk Rating, and controls for the risks are designed, which are assigned to the responsible person. At the end of the article, result and analysis on the different sources of risk are discussed in details and the conclusion is drawn. Discussion on few sample risks are presented in this article. Hence it is presented in the research that the Risk Management System can be applied in a Higher Education Institute to effectively control the risks which might affect the scope and Quality Management System of an organization.

Keywords: higher education, quality management system, risk assessment, risk management

Procedia PDF Downloads 294
8112 Comparing Machine Learning Estimation of Fuel Consumption of Heavy-Duty Vehicles

Authors: Victor Bodell, Lukas Ekstrom, Somayeh Aghanavesi

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Fuel consumption (FC) is one of the key factors in determining expenses of operating a heavy-duty vehicle. A customer may therefore request an estimate of the FC of a desired vehicle. The modular design of heavy-duty vehicles allows their construction by specifying the building blocks, such as gear box, engine and chassis type. If the combination of building blocks is unprecedented, it is unfeasible to measure the FC, since this would first r equire the construction of the vehicle. This paper proposes a machine learning approach to predict FC. This study uses around 40,000 vehicles specific and o perational e nvironmental c onditions i nformation, such as road slopes and driver profiles. A ll v ehicles h ave d iesel engines and a mileage of more than 20,000 km. The data is used to investigate the accuracy of machine learning algorithms Linear regression (LR), K-nearest neighbor (KNN) and Artificial n eural n etworks (ANN) in predicting fuel consumption for heavy-duty vehicles. Performance of the algorithms is evaluated by reporting the prediction error on both simulated data and operational measurements. The performance of the algorithms is compared using nested cross-validation and statistical hypothesis testing. The statistical evaluation procedure finds that ANNs have the lowest prediction error compared to LR and KNN in estimating fuel consumption on both simulated and operational data. The models have a mean relative prediction error of 0.3% on simulated data, and 4.2% on operational data.

Keywords: artificial neural networks, fuel consumption, friedman test, machine learning, statistical hypothesis testing

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8111 Survey Study of Integrative and Instrumental Motivation in English Language Learning of First Year Students at Naresuan University International College (NUIC), Thailand

Authors: Don August G. Delgado

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Foreign Language acquisition without enough motivation is tough because it is the force that drives students’ interest or enthusiasm to achieve learning. In addition, it also serves as the students’ beacon to achieve their goals, desires, dreams, and aspirations in life. Since it plays an integral factor in language learning acquisition, this study focuses on the integrative and instrumental motivation levels of all the first year students of Naresuan University International College. The identification of their motivation level and inclination in learning the English language will greatly help all NUIC lecturers and administrators to create a project or activities that they will truly enjoy and find worth doing. However, if the findings of this study will say otherwise, this study can also show to NUIC lecturers and administrators how they can help and transform NUIC freshmen on becoming motivated learners to enhance their English proficiency levels. All respondents in this study received an adopted and developed questionnaire from different researches in the same perspective. The questionnaire has 24 questions that were randomly arranged; 12 for integrative motivation and 12 for instrumental motivation. The questionnaire employed the five-point Likert scale. The tabulated data were analyzed according to its means and standard deviations using the Standard Deviation Calculator. In order to interpret the motivation level of the respondents, the Interpretation of Mean Scores was utilized. Thus, this study concludes that majority of the NUIC freshmen are neither integratively motivated nor instrumentally motivated students.

Keywords: motivation, integrative, foreign language acquisition, instrumental

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8110 Engaging Medical Students in Research through Student Research Mentorship Programme

Authors: Qi En Han, Si En Wai, Eugene Quek

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As one of the two Academic Medical Centres (AMCs) in Singapore, SingHealth Duke-NUS AMC strives to improve patients’ lives through excellent clinical care, research and education. These efforts are enhanced with the establishment of Academic Clinical Programmes (ACPs). Each ACP brings together specialists in a particular discipline from different institutions to maximize the power of shared knowledge and resources. Initiated by Surgery ACP, the student research mentorship programme is a programme designed to facilitate engagement between medical students and the surgical faculty. The programme offers mentors not only the opportunity to supervise research but also to nurture future clinician scientists. In turn, medical students acquire valuable research experience which may be useful in their future careers. The programme typically lasts one year, depending on the students’ commitment. Surgery ACP matches students’ research interests with the mentor's area of expertise whenever possible. Surgery ACP organizes informal tea sessions to bring students and prospective mentors together. Once a match is made, the pair is required to submit a project proposal which includes the title, proposed start and end dates, ethical and biosafety considerations and project details. The mentees either think of their own research question with guidance from the mentors or join an existing project. The mentees may participate in data collection, data analysis, manuscript writing and conference presentation. The progress of each research project is monitored through half-yearly progress report. The mentees report problems encountered or changes made to existing proposal on top of the progress made. A total of 18 mentors were successfully paired with 36 mentees since 2013. Currently, there are 23 on-going and 13 completed projects. The mentees are encouraged to present their projects at conferences and to publish in peer-reviewed journals. Six mentees have presented their completed projects at local or international conferences and one mentee has her work published. To further support student research, Surgery ACP organized a Research Day in 2015 to recognize their research efforts and to showcase their wide-range of research. Surgery ACP recognizes that early exposure of medical students to research is important in developing them into clinician scientists. As interest in research take time to develop and are usually realized during various research attachments, it is crucial that programmes such as the student research mentorship programme exist. Surgery ACP will continue to build on this programme.

Keywords: academic clinical programme, clinician scientist, medical student, mentoring

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8109 Experimental and Numerical Investigation on Deformation Behaviour of Single Crystal Copper

Authors: Suman Paik, P. V. Durgaprasad, Bijan K. Dutta

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A study combining experimental and numerical investigation on the deformation behaviour of single crystals of copper is presented in this paper. Cylindrical samples were cut in specific orientations from high purity copper single crystal and subjected to uniaxial compression loading at quasi-static strain rate. The stress-strain curves along two different crystallographic orientations were then extracted. In order to study and compare the deformation responses, a single crystal plasticity model incorporating non-Schmid effects was developed assuming cross-slip plays an important role in orientation of the material. By making use of crystal plasticity finite element method, the model was applied to investigate the orientation dependence of the stress-strain behaviour of two crystallographic orientations. Finally, details of slip activities of deformed crystals were investigated by linking the orientation of slip lines with the theoretical traces of possible crystallographic planes. The experimentally determined active slip modes were matched with those determined by simulations.

Keywords: crystal plasticity, modelling, non-Schmid effects, finite elements, finite strain

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8108 A Risk Assessment Tool for the Contamination of Aflatoxins on Dried Figs Based on Machine Learning Algorithms

Authors: Kottaridi Klimentia, Demopoulos Vasilis, Sidiropoulos Anastasios, Ihara Diego, Nikolaidis Vasileios, Antonopoulos Dimitrios

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Aflatoxins are highly poisonous and carcinogenic compounds produced by species of the genus Aspergillus spp. that can infect a variety of agricultural foods, including dried figs. Biological and environmental factors, such as population, pathogenicity, and aflatoxinogenic capacity of the strains, topography, soil, and climate parameters of the fig orchards, are believed to have a strong effect on aflatoxin levels. Existing methods for aflatoxin detection and measurement, such as high performance liquid chromatography (HPLC), and enzyme-linked immunosorbent assay (ELISA), can provide accurate results, but the procedures are usually time-consuming, sample-destructive, and expensive. Predicting aflatoxin levels prior to crop harvest is useful for minimizing the health and financial impact of a contaminated crop. Consequently, there is interest in developing a tool that predicts aflatoxin levels based on topography and soil analysis data of fig orchards. This paper describes the development of a risk assessment tool for the contamination of aflatoxin on dried figs, based on the location and altitude of the fig orchards, the population of the fungus Aspergillus spp. in the soil, and soil parameters such as pH, saturation percentage (SP), electrical conductivity (EC), organic matter, particle size analysis (sand, silt, clay), the concentration of the exchangeable cations (Ca, Mg, K, Na), extractable P, and trace of elements (B, Fe, Mn, Zn and Cu), by employing machine learning methods. In particular, our proposed method integrates three machine learning techniques, i.e., dimensionality reduction on the original dataset (principal component analysis), metric learning (Mahalanobis metric for clustering), and k-nearest neighbors learning algorithm (KNN), into an enhanced model, with mean performance equal to 85% by terms of the Pearson correlation coefficient (PCC) between observed and predicted values.

Keywords: aflatoxins, Aspergillus spp., dried figs, k-nearest neighbors, machine learning, prediction

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8107 The Contribution of Experience Scapes to Building Resilience in Communities: A Comparative Case Study Approach in Germany and the Netherlands

Authors: Jorn Fricke, Frans Melissen

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Citizens in urban areas are prone to increased levels of stress due to urbanization, inadequate and overburdened infrastructure and services, and environmental degradation. Moreover, communities are fragile and subject to shocks and stresses through various social and political processes. A loss of (a sense of) community is often seen as related to increasing political and civic disintegration. Feelings of community can manifest themselves in various ways but underlying all these manifestations is the need for trust between people. One of the main drivers of trust between individuals is (shared) experiences. It is these shared experiences that may play an important role in building resilience, i.e., the ability of a community and its members to adapt to and deal with stresses, as well as ensure the ongoing development of a community. So far, experience design, as a discipline and academic field, has mainly focused on designing products or services. However, people-to-people experiences are the ones that play a pivotal role in building inclusiveness, safety, and resilience in communities. These experiences represent challenging objects of design as they develop in an interactive space of spontaneity, serendipity, and uniqueness that is based on intuition, freedom of expression, and interaction. Therefore, there is a need for research to identify which elements are required in designing the social and physical environment (or ‘experience scape’) to increase the chance for people-to-people experiences to be successful and what elements are required for these experiences to help in building resilience in urban communities that can resist shocks and stresses. By means of a comparative case study approach in urban areas in Germany and the Netherlands, using a range of qualitative research methods such as in-depth interviews, focus groups, participant observation, storytelling techniques, and life stories, this research identifies relevant actors and their roles in creating building blocks of optimal experience scrapes for building resilience in communities.

Keywords: community development, experiences, experience scapes, resilience

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8106 Indigenous Learning of Animal Metaphors: The ‘Big Five’ in King Shaka’s Praise-Poems

Authors: Ntandoni Gloria Biyela

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During traditional times, there were no formal institutions of learning as they are today, where children attend classes to acquire or develop knowledge. This does not mean that there was no learning in indigenous African societies. Grandparents used to tell their grandchildren stories or teach them educational games around the fireplace, which this study refers to as a ‘traditional classroom’. A story recreated in symbolic or allegorical way, forms a base for a society’s beliefs, customs, accepted norms and language learning. Through folklore narratives, a society develops its own self awareness and education. So narrative characters, especially animals may be mythical products of the pre-literate folklore world and thus show the closeness that the Zulu society had with the wildlife. Oral cultures strive to create new facets of meaning by the use of animal metaphors to reflect the relationship of humans with the animal realm and to contribute to the language learning or literature in cross-cultural studies. Although animal metaphors are widespread in Zulu language because of the Zulu nation’s traditional closeness to wildlife, little field-research has been conducted on the social behavior of animals on the way in which their characteristics were transferred with precision to depictions of King Shaka’s behavior and activities during the amalgamation of Nguni clans into a Zulu kingdom. This study attempts to fill the gap by using first-hand interviews with local informants in areas traditionally linked to the king in KwaZulu-Natal province, South Africa. Departing from the conceptual metaphor theory, the study concentrates on King Shaka’s praise-poems in which the praise-poet describes his physical and dispositional characteristics through bold animal metaphors of the ‘Big Five’; namely, the lion, the leopard, the buffalo, the rhinoceros and the elephant, which are often referred to as Zulu royal favorites. These metaphors are still learnt by young and old in the 21st century because they reflect the responsibilities, status, and integrity of the king and the respect in which he is held by his people. They also project the crescendo growth of the Zulu nation, which, through the fulfillment of his ambitions, grew from a small clan to a mighty kingdom.

Keywords: animal, indigenous, learning, metaphor

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8105 Quadratic Convective Flow of a Micropolar Fluid in a Non-Darcy Porous Medium with Convective Boundary Condition

Authors: Ch. Ramreddy, P. Naveen, D. Srinivasacharya

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The objective of the present study is to investigate the effect of nonlinear temperature and concentration on the mixed convective flow of micropolar fluid over an inclined flat plate in a non-Darcy porous medium in the presence of convective boundary condition. In order to analyze all the essential features, the transformed nonlinear conservation equations are worked out numerically by spectral method. By insisting the comparison between vertical, horizontal and inclined plates, the physical quantities of the flow and its characteristics are exhibited graphically and quantitatively with various parameters. An increase in the coupling number and inclination of angle tend to decrease the skin friction, mass transfer rate and the reverse change is there in wall couple stress and heat transfer rate. The nominal effect on the wall couple stress and skin friction is encountered whereas the significant effect on the local heat and mass transfer rates are found for high enough values of Biot number.

Keywords: convective boundary condition, micropolar fluid, non-darcy porous medium, non-linear convection, spectral method

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8104 Identifying Degradation Patterns of LI-Ion Batteries from Impedance Spectroscopy Using Machine Learning

Authors: Yunwei Zhang, Qiaochu Tang, Yao Zhang, Jiabin Wang, Ulrich Stimming, Alpha Lee

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Forecasting the state of health and remaining useful life of Li-ion batteries is an unsolved challenge that limits technologies such as consumer electronics and electric vehicles. Here we build an accurate battery forecasting system by combining electrochemical impedance spectroscopy (EIS) -- a real-time, non-invasive and information-rich measurement that is hitherto underused in battery diagnosis -- with Gaussian process machine learning. We collect over 20,000 EIS spectra of commercial Li-ion batteries at different states of health, states of charge and temperatures -- the largest dataset to our knowledge of its kind. Our Gaussian process model takes the entire spectrum as input, without further feature engineering, and automatically determines which spectral features predict degradation. Our model accurately predicts the remaining useful life, even without complete knowledge of past operating conditions of the battery. Our results demonstrate the value of EIS signals in battery management systems.

Keywords: battery degradation, machine learning method, electrochemical impedance spectroscopy, battery diagnosis

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8103 Summer STEM Camp for Elementary Students: A Conduit to Pre-Service Teacher Training to Learn How to Include a Makerspace for an Inclusive Classroom

Authors: Jennifer Gallup, Beverly Ray, Esther Ntuli

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Many students such as students from linguistically or culturally diverse backgrounds and those with a disability remain chronically underrepresented in higher level science and mathematics disciplines as well as many hands-on-lab-based activities due to the need for remedial reading and mathematics instruction. Makerspace labs can be a conduit for supporting inclusive learning for these students through hands-on active learning strategies that support equitable access to STEM disciplines. Makerspace is a physical space where individuals gather to create, invent, innovate, and learn while using hands-on materials such as 2D and 3D printers, software programs, electronics, and other tools and supplies. Makerspaces are emerging across many P-12 settings; however, many teachers enter the field not prepared to harness the power inherent in a makerspace, especially for those with disabilities and differing needs. This paper offers suggestions on teaching pre-service teachers and practicing teachers how to incorporate a makerspace into their professional practice through guided instruction and hands-on practice. Recommendations for interested stakeholders are included as well.

Keywords: STEM learning, technology, autism, students with disabilities, makerspace

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8102 Assessing Arterial Blockages Using Animal Model and Computational Fluid Dynamics

Authors: Mohammad Al- Rawi, Ahmad Al- Jumaily

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This paper investigates the effect of developing arterial blockage at the abdominal aorta on the blood pressure waveform at an externally accessible location suitable for invasive measurements such as the brachial and the femoral arteries. Arterial blockages are created surgically within the abdominal aorta of healthy Wistar rats to create narrowing resemblance conditions. Blood pressure waveforms are measured using a catheter inserted into the right femoral artery. Measurements are taken at the baseline healthy condition as well as at four different severities (20%, 50%, 80% and 100%) of arterial blockage. In vivo and in vitro measurements of the lumen diameter and wall thickness are taken using Magnetic Resonance Imaging (MRI) and microscopic techniques, respectively. These data are used to validate a 3D computational fluid dynamics model (CFD) which is developed to generalize the outcomes of this work and to determine the arterial stress and strain under the blockage conditions. This work indicates that an arterial blockage in excess of 20% of the lumen diameter significantly influences the pulse wave and reduces the systolic blood pressure at the right femoral artery. High wall shear stress and low circumferential strain are also generated at the blockage site.

Keywords: arterial blockage, pulse wave, atherosclerosis, CFD

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8101 Cultivation of High-value Patent from the Perspective of Knowledge Diffusion: A Case Study of the Power Semiconductor Field

Authors: Lin Qing

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[Objective/Significance] The cultivation of high-value patents is the focus and difficulty of patent work, which is of great significance to the construction of a powerful country with intellectual property rights. This work should not only pay attention to the existing patent applications, but also start from the pre-application to explore the high-value technical solutions as the core of high-value patents. [Methods/processes] Comply with the principle of scientific and technological knowledge diffusion, this study studies the top academic conference papers and their cited patent applications, taking the power semiconductor field as an example, using facts date show the feasibility and rationality of mining technology solutions from high quality research results to foster high value patents, stating the actual benefits of these achievements to the industry, giving patent protection suggestions for Chinese applicants comparative with field situation. [Results/Conclusion] The research shows that the quality of citation applications of ISPSD papers is significantly higher than the field average level, and the ability of Chinese applicants to use patent protection related achievements needs to be improved. This study provides a practical and highly targeted reference idea for patent administrators and researchers, and also makes a positive exploration for the practice of the spirit of breaking the five rules.

Keywords: high-value patents cultivation, technical solutions, knowledge diffusion, top academic conference papers, intellectual property information analysis

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8100 Investigate and Compare the Characteristics of Entrepreneurship among Students in Senior Secondary Schools in the Academic

Authors: Khalil Aryanfar, Shahrzad Sanjari, Pariya Gholipor, Elmira Hafez

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The present study aimed to investigate and compare the characteristics of entrepreneurship among students in senior secondary schools in the academic year 2008-2009 in Tabriz city. Research employed survey method respectively. The study population consisted of all students in the senior branch of theoretical, technical, professional and vocational (1033 patients) were included. Sample size of 493 was calculated according to Morgan table. Sampling method was random cluster and stratified sampling. Data collected by researcher made questionnaire based on the theory of MC clleland (1963) and Brvkhavs (1980). These tools would indicators be for achievement, Independence, disposition, creativity, risk-taking, self-control, tolerance for ambiguity, team work approach in the future. To determine the psychometric properties of the questionnaire, content validity of the survey was approved by relevant experts. In addition, to estimate the internal consistency of Cronbach's alpha coefficient was calculated for 84% of total inventory. Collected data Using mean, standard deviation and were analyzed by ANOVA. The results showed that there is a significant difference between students' entrepreneurial potential fields of theoretical, technical, professional and vocational level (0/01).

Keywords: entrepreneurship, achievement motivation, risk taking, creativity, self-control, independence, tolerance of ambiguity, foresight

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8099 R Data Science for Technology Management

Authors: Sunghae Jun

Abstract:

Technology management (TM) is important issue in a company improving the competitiveness. Among many activities of TM, technology analysis (TA) is important factor, because most decisions for management of technology are decided by the results of TA. TA is to analyze the developed results of target technology using statistics or Delphi. TA based on Delphi is depended on the experts’ domain knowledge, in comparison, TA by statistics and machine learning algorithms use objective data such as patent or paper instead of the experts’ knowledge. Many quantitative TA methods based on statistics and machine learning have been studied, and these have been used for technology forecasting, technological innovation, and management of technology. They applied diverse computing tools and many analytical methods case by case. It is not easy to select the suitable software and statistical method for given TA work. So, in this paper, we propose a methodology for quantitative TA using statistical computing software called R and data science to construct a general framework of TA. From the result of case study, we also show how our methodology is applied to real field. This research contributes to R&D planning and technology valuation in TM areas.

Keywords: technology management, R system, R data science, statistics, machine learning

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8098 Songwriting in the Postdigital Age: Using TikTok and Instagram as Online Informal Learning Technologies

Authors: Matthias Haenisch, Marc Godau, Julia Barreiro, Dominik Maxelon

Abstract:

In times of ubiquitous digitalization and the increasing entanglement of humans and technologies in musical practices in the 21st century, it is to be asked, how popular musicians learn in the (post)digital Age. Against the backdrop of the increasing interest in transferring informal learning practices into formal settings of music education the interdisciplinary research association »MusCoDA – Musical Communities in the (Post)Digital Age« (University of Erfurt/University of Applied Sciences Clara Hoffbauer Potsdam, funded by the German Ministry of Education and Research, pursues the goal to derive an empirical model of collective songwriting practices from the study of informal lelearningf songwriters and bands that can be translated into pedagogical concepts for music education in schools. Drawing on concepts from Community of Musical Practice and Actor Network Theory, lelearnings considered not only as social practice and as participation in online and offline communities, but also as an effect of heterogeneous networks composed of human and non-human actors. Learning is not seen as an individual, cognitive process, but as the formation and transformation of actor networks, i.e., as a practice of assembling and mediating humans and technologies. Based on video stimulated recall interviews and videography of online and offline activities, songwriting practices are followed from the initial idea to different forms of performance and distribution. The data evaluation combines coding and mapping methods of Grounded Theory Methodology and Situational Analysis. This results in network maps in which both the temporality of creative practices and the material and spatial relations of human and technological actors are reconstructed. In addition, positional analyses document the power relations between the participants that structure the learning process of the field. In the area of online informal lelearninginitial key research findings reveal a transformation of the learning subject through the specific technological affordances of TikTok and Instagram and the accompanying changes in the learning practices of the corresponding online communities. Learning is explicitly shaped by the material agency of online tools and features and the social practices entangled with these technologies. Thus, any human online community member can be invited to directly intervene in creative decisions that contribute to the further compositional and structural development of songs. At the same time, participants can provide each other with intimate insights into songwriting processes in progress and have the opportunity to perform together with strangers and idols. Online Lelearnings characterized by an increase in social proximity, distribution of creative agency and informational exchange between participants. While it seems obvious that traditional notions not only of lelearningut also of the learning subject cannot be maintained, the question arises, how exactly the observed informal learning practices and the subject that emerges from the use of social media as online learning technologies can be transferred into contexts of formal learning

Keywords: informal learning, postdigitality, songwriting, actor-network theory, community of musical practice, social media, TikTok, Instagram, apps

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8097 Improved Computational Efficiency of Machine Learning Algorithm Based on Evaluation Metrics to Control the Spread of Coronavirus in the UK

Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

Abstract:

The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning archetypal that could forecast COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organisation (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data is split into 8:2 ratio for training and testing purposes to forecast future new COVID cases. Support Vector Machines (SVM), Random Forests, and linear regression algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID cases is evaluated. Random Forest outperformed the other two Machine Learning algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n=30. The mean square error obtained for Random Forest is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis Random Forest algorithm can perform more effectively and efficiently in predicting the new COVID cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest

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8096 An Image Segmentation Algorithm for Gradient Target Based on Mean-Shift and Dictionary Learning

Authors: Yanwen Li, Shuguo Xie

Abstract:

In electromagnetic imaging, because of the diffraction limited system, the pixel values could change slowly near the edge of the image targets and they also change with the location in the same target. Using traditional digital image segmentation methods to segment electromagnetic gradient images could result in lots of errors because of this change in pixel values. To address this issue, this paper proposes a novel image segmentation and extraction algorithm based on Mean-Shift and dictionary learning. Firstly, the preliminary segmentation results from adaptive bandwidth Mean-Shift algorithm are expanded, merged and extracted. Then the overlap rate of the extracted image block is detected before determining a segmentation region with a single complete target. Last, the gradient edge of the extracted targets is recovered and reconstructed by using a dictionary-learning algorithm, while the final segmentation results are obtained which are very close to the gradient target in the original image. Both the experimental results and the simulated results show that the segmentation results are very accurate. The Dice coefficients are improved by 70% to 80% compared with the Mean-Shift only method.

Keywords: gradient image, segmentation and extract, mean-shift algorithm, dictionary iearning

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8095 Neuroprotective Effect of Chrysin on Thioacetamide-Induced Hepatic Encephalopathy in Rats: Role of Oxidative Stress and TLR-4/NF-κB Pathway

Authors: S. A. El-Marasy, S. A. El Awdan, R. M. Abd-Elsalam

Abstract:

This study aimed to investigate the possible neuroprotective effect of chrysin on thioacetamide (TAA)-induced hepatic encephalopathy in rats. Also, the effect of chrysin on motor impairment, cognitive deficits, oxidative stress, neuroinflammation, apoptosis and histopathological damage was assessed. Male Wistar rats were randomly allocated into five groups. The first group received the vehicle (distilled water) for 21 days and is considered as normal group. While the second one received intraperitoneal dose of TAA (200 mg/kg) at three alternative days during the third week of the experiment to induce HE and is considered as control group. The other three groups were orally administered chrysin for 21 days (25, 50, 100 mg/kg) and starting from day 17; rats received intraperitoneal dose of TAA (200 mg/kg) at three alternative days. Then behavioral, biochemical, histopathological and immunohistochemical analyses were assessed. Then behavioral, biochemical, histopathological and immunohistochemical analyses were assessed. Chrysin reversed TAA-induced motor coordination in rotarod test, cognitive deficits in object recognition test (ORT) and attenuated serum ammonia, hepatic liver enzymes, reduced malondialdehyde (MDA), elevated reduced glutathione (GSH), reduced nuclear factor kappa B (NF-κB), tumor necrosis factor-alpha (TNF-α) and Interleukin-6 (IL-6) brain contents. Chrysin administration also reduced Toll-4 receptor (TLR-4) gene expression, caspase-3 protein expression, hepatic necrosis and astrocyte swelling. This study depicts that chrysin exerted neuroprotective effect in TAA-induced HE rats, evidenced by improvement of cognitive deficits, motor incoordination and histopathological changes such as astrocyte swelling and vacuolization; hallmarks in HE, via reducing hyperammonemia, ameliorating hepatic function, in addition to its anti-oxidant, inactivation of TLR-4/NF-κB inflammatory pathway, and anti-apoptotic effects.

Keywords: chrysin, hepatic encephalopathy, oxidative stress, rats, thioacetamide, TLR4/NF-κB pathway

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8094 Thermal Comfort Study of School Buildings in South Minahasa Regency Case Study: SMA Negeri 1 Amurang, Indonesia

Authors: Virgino Stephano Moniaga

Abstract:

Thermal comfort inside a building can affect students in their learning process. The learning process of students can be improved if the condition of the classrooms is comfortable. This study will be conducted in SMA Negeri 1 Amurang which is a senior high school building located in South Minahasa Regency. Based on preliminary survey, generally, students were not satisfied with the existing level of comfort, which subsequently affected the teaching and learning process in the classroom. The purpose of this study is to analyze the comfort level of classrooms occupants and recommend building design solutions that can improve the thermal comfort of classrooms. In this study, three classrooms will be selected for thermal comfort measurements. The thermal comfort measurements will be taken in naturally ventilated classrooms. The measured data comprise of personal data (clothing and students activity), air humidity, air temperature, mean radiant temperature and air flow velocity. Simultaneously, the students will be asked to fill out a questionnaire that asked about the level of comfort that was felt at the time. The results of field measurements and questionnaires will be analyzed based on the PMV and PPD indices. The results of the analysis will decide whether the classrooms are comfortable or not. This study can be continued to obtain a more optimal design solution to improve the thermal comfort of the classrooms. The expected results from this study can improve the quality of teaching and learning process between teachers and students which can further assist the government efforts to improve the quality of national education.

Keywords: classrooms, PMV, PPD, thermal comfort

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8093 Biomedical Definition Extraction Using Machine Learning with Synonymous Feature

Authors: Jian Qu, Akira Shimazu

Abstract:

OOV (Out Of Vocabulary) terms are terms that cannot be found in many dictionaries. Although it is possible to translate such OOV terms, the translations do not provide any real information for a user. We present an OOV term definition extraction method by using information available from the Internet. We use features such as occurrence of the synonyms and location distances. We apply machine learning method to find the correct definitions for OOV terms. We tested our method on both biomedical type and name type OOV terms, our work outperforms existing work with an accuracy of 86.5%.

Keywords: information retrieval, definition retrieval, OOV (out of vocabulary), biomedical information retrieval

Procedia PDF Downloads 476
8092 Digital Transformation in Developing Countries, A Study into Building Information Modelling Adoption in Thai Design and Engineering Small- and Medium-Sizes Enterprises

Authors: Prompt Udomdech, Eleni Papadonikolaki, Andrew Davies

Abstract:

Building information modelling (BIM) is the major technological trend amongst built environment organisations. Digitalising businesses and operations, BIM brings forth a digital transformation in any built environment industry. The adoption of BIM presents challenges for organisations, especially small- and medium-sizes enterprises (SMEs). The main problem for built-environment SMEs is the lack of project actors with adequate BIM competences. The research highlights learning in projects as the key and explores into the learning of BIM in projects of designers and engineers within Thai design and engineering SMEs. The study uncovers three impeding attributes, which are: a) lack of English proficiency; b) unfamiliarity with digital technologies; and c) absence of public standards. This research expands on the literature on BIM competences and adoption.

Keywords: BIM competences and adoption, digital transformation, learning in projects, SMEs, and developing built environment industry

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8091 EECS: Reimagining the Future of Technology Education through Electrical Engineering and Computer Science Integration

Authors: Yousef Sharrab, Dimah Al-Fraihat, Monther Tarawneh, Aysh Alhroob, Ala’ Khalifeh, Nabil Sarhan

Abstract:

This paper explores the evolution of Electrical Engineering (EE) and Computer Science (CS) education in higher learning, examining the feasibility of unifying them into Electrical Engineering and Computer Science (EECS) for the technology industry. It delves into the historical reasons for their separation and underscores the need for integration. Emerging technologies such as AI, Virtual Reality, IoT, Cloud Computing, and Cybersecurity demand an integrated EE and CS program to enhance students' understanding. The study evaluates curriculum integration models, drawing from prior research and case studies, demonstrating how integration can provide students with a comprehensive knowledge base for industry demands. Successful integration necessitates addressing administrative and pedagogical challenges. For academic institutions considering merging EE and CS programs, the paper offers guidance, advocating for a flexible curriculum encompassing foundational courses and specialized tracks in computer engineering, software engineering, bioinformatics, information systems, data science, AI, robotics, IoT, virtual reality, cybersecurity, and cloud computing. Elective courses are emphasized to keep pace with technological advancements. Implementing this integrated approach can prepare students for success in the technology industry, addressing the challenges of a technologically advanced society reliant on both EE and CS principles. Integrating EE and CS curricula is crucial for preparing students for the future.

Keywords: electrical engineering, computer science, EECS, curriculum integration of EE and CS

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8090 Role of Maternal Astaxanthin Supplementation on Brain Derived Neurotrophic Factor and Spatial Learning Behavior in Wistar Rat Offspring’s

Authors: K. M. Damodara Gowda

Abstract:

Background: Maternal health and nutrition are considered as the predominant factors influencing brain functional development. If the mother is free of illness and genetic defects, maternal nutrition would be one of the most critical factors affecting the brain development. Calorie restrictions cause significant impairment in spatial learning ability and the levels of Brain Derived Neurotrophic Factor (BDNF) in rats. But, the mechanism by which the prenatal under-nutrition leads to impairment in brain learning and memory function is still unclear. In the present study, prenatal Astaxanthin supplementation on BDNF level, spatial learning and memory performance in the offspring’s of normal, calorie restricted and Astaxanthin supplemented rats was investigated. Methodology: The rats were administered with 6mg and 12 mg of astaxanthin /kg bw for 21 days following which acquisition and retention of spatial memory was tested in a partially-baited eight arm radial maze. The BDNF level in different regions of the brain (cerebral cortex, hippocampus and cerebellum) was estimated by ELISA method. Results: Calorie restricted animals treated with astaxanthin made significantly more correct choices (P < 0.05), and fewer reference memory errors (P < 0.05) on the tenth day of training compared to offsprings of calorie restricted animals. Calorie restricted animals treated with astaxanthin also made significantly higher correct choices (P < 0.001) than untreated calorie restricted animals in a retention test 10 days after the training period. The mean BDNF level in cerebral cortex, Hippocampus and cerebellum in Calorie restricted animals treated with astaxanthin didnot show significant variation from that of control animals. Conclusion: Findings of the study indicated that memory and learning was impaired in the offspring’s of calorie restricted rats which was effectively modulated by astaxanthin at the dosage of 12 mg/kg body weight. In the same way the BDNF level at cerebral cortex, Hippocampus and Cerebellum was also declined in the offspring’s of calorie restricted animals, which was also found to be effectively normalized by astaxanthin.

Keywords: calorie restiction, learning, Memory, Cerebral cortex, Hippocampus, Cerebellum, BDNF, Astaxanthin

Procedia PDF Downloads 220