Search results for: learning behaviour

Authors: Jian-Jun Gao

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Repetition is used for a variety of functions in conversation. When young children first learn to speak, they often repeat words from the adult’s recent utterance with the learning and social function. The objective of this study was to ascertain whether the repetitions are equivalent in indicating attention to new words and the initial repeat of information in conversation. Based on the observation of naturally occurring language use in Taiwan Corpus of Child Mandarin (TCCM), the results in this study provided empirical support to the previous findings that children are more likely to repeat new words they are offered than to repeat new information. When children get older, there would be a drop in the repetition of both new words and new information.

Keywords: acquisition, corpus, mandarin, new words, new information, repetition

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Authors: Wilhelmina van den Berg

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Through intentionally developing the Register Continuum and the Functional Model of Language in the secondary history classroom, teachers can effectively build a teaching and learning cycle geared towards literacy improvement and EAL differentiation. Developing an understanding of and engaging students in the field, tenor, and tone of written and spoken language, allows students to build the foundation for greater academic achievement due to integrated literacy skills in the history classroom. Building a variety of scaffolds during lessons within these models means students can improve their academic language and communication skills.

Keywords: academic language, EAL, functional model of language, international baccalaureate, literacy skills

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Authors: A. C. Kumbharkhane

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Time domain dielectric relaxation microwave spectroscopy (TDRMS) is a term used to describe a technique of observing the time dependant response of a sample after application of time dependant electromagnetic field. A TDRMS probes the interaction of a macroscopic sample with a time dependent electrical field. The resulting complex permittivity spectrum, characterizes amplitude (voltage) and time scale of the charge-density fluctuations within the sample. These fluctuations may arise from the reorientation of the permanent dipole moments of individual molecules or from the rotation of dipolar moieties in flexible molecules, like polymers. The time scale of these fluctuations depends on the sample and its relative relaxation mechanism. Relaxation times range from some picoseconds in low viscosity liquids to hours in glasses, Therefore the TDRS technique covers an extensive dynamical process. The corresponding frequencies range from 10-4 Hz to 1012 Hz. This inherent ability to monitor the cooperative motion of molecular ensemble distinguishes dielectric relaxation from methods like NMR or Raman spectroscopy, which yield information on the motions of individual molecules. Recently, we have developed and established the TDR technique in laboratory that provides information regarding dielectric permittivity in the frequency range 10 MHz to 30 GHz. The TDR method involves the generation of step pulse with rise time of 20 pico-seconds in a coaxial line system and monitoring the change in pulse shape after reflection from the sample placed at the end of the coaxial line. There is a great interest to study the dielectric relaxation behaviour in liquid systems to understand the role of hydrogen bond in liquid system. The intermolecular interaction through hydrogen bonds in molecular liquids results in peculiar dynamical properties. The dynamics of hydrogen-bonded liquids have been studied. The theoretical model to explain the experimental results will be discussed.

Keywords: microwave, time domain reflectometry (TDR), dielectric measurement, relaxation time

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Authors: Badli Shah Mohd Yusoff, Khairur Rijal Jamaludin, Rozetta Dollah

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The emerging of reverse logistics and product recovery management is an important concept in reconciling economic and environmental objectives through recapturing values of the end of life product returns. End of life products contains valuable modules, parts, residues and materials that can create value if recovered efficiently. The main objective of this study is to explore and develop a model to recover as much of the economic value as reasonably possible to find the optimality of return acquisition and sorting to meet demand and maximize profits over time. In this study, the benefits that can be obtained for remanufacturer is to develop demand forecasting of used products in the future with uncertainty of returns and quality of products. Formulated based on a generic disassembly tree, the proposed model focused on three reverse logistics activity, namely refurbish, remanufacture and disposal incorporating all plausible means quality levels of the returns. While stricter sorting policy, constitute to the decrease amount of products to be refurbished or remanufactured and increases the level of discarded products. Numerical experiments carried out to investigate the characteristics and behaviour of the proposed model with mathematical programming model using Lingo 16.0 for medium-term planning of return acquisition, disassembly (refurbish or remanufacture) and disposal activities. Moreover, the model seeks an analysis a number of decisions relating to trade off management system to maximize revenue from the collection of use products reverse logistics services through refurbish and remanufacture recovery options. The results showed that full utilization in the sorting process leads the system to obtain less quantity from acquisition with minimal overall cost. Further, sensitivity analysis provides a range of possible scenarios to consider in optimizing the overall cost of refurbished and remanufactured products.

Keywords: core acquisition, end of life, reverse logistics, quality uncertainty

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Authors: Eda Üstünel, Seval Karacabey

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The students, who are enrolled in German Preparatory Language Programme at the School of Foreign Languages, Muğla Sıtkı Koçman University, Turkey, learn German as a foreign language for two semesters in an academic year. Although the language programme is a skills-based one, the students lack German speaking skills due to their fear of making language mistakes while speaking in German. This problem of incompetency in German speaking skills exists also in their four-year departmental study at the Faculty of Education. In order to address this problem we design German speaking activities, which are extra-curricular activities. With the help of these activities, we aim to lead Turkish students of German language to speak in the target language, to improve their speaking skills in the target language and to create a stress-free atmosphere and a meaningful learning environment to communicate in the target language. In order to achieve these aims, an ERASMUS+ exchange staff (a German trainee teacher of German as a foreign language), who is from Schwabisch Gmünd University, Germany, conducted out-of-class German speaking activities once a week for three weeks in total. Each speaking activity is lasted for one and a half hour per week. 7 volunteered students of German preparatory language programme attended the speaking activity for three weeks. The activity took place at a cafe in the university campus, that’s the reason, we call it as an out-of-class activity. The content of speaking activity is not related to the topics studied at the units of coursebook, that’s the reason, we call this activity as extra-curricular one. For data collection, three tools are used. A questionnaire, which is an adapted version of Sabo’s questionnaire, is applied to seven volunteers. An interview session is then held with each student on individual basis. The interview questions are developed so as to ask students to expand their answers that are given at the questionnaires. The German trainee teacher wrote fieldnotes, in which the teacher described the activity in the light of her thoughts about what went well and which areas were needed to be improved. The results of questionnaires show that six out of seven students note that such an acitivity must be conducted by a native speaker of German. Four out of seven students emphasize that they like the way that the activities are designed in a learner-centred fashion. All of the students point out that they feel motivated to talk to the trainee teacher in German. Six out of seven students note that the opportunity to communicate in German with the teacher and the peers enable them to improve their speaking skills, the use of grammatical rules and the use of vocabulary.

Keywords: Learning a Foreign Language, Speaking Skills, Teaching German as a Foreign Language, Turkish Learners of German Language

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Authors: Su-Lien Liao

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Most of college students in Taiwan do not have sufficient English proficiency to express themselves in written English. Teachers spent a lot of time correcting students’ English writing, but the results are not satisfactory. This study aims to use blogs as a teaching and learning tool in written English. Before applying peer assessment, students should be trained to be good reviewers. The teacher starts the course by posting the error analysis of students’ first English composition on blogs as the comment models for students. Then the students will go through the process of drafting, composing, peer response and last revision on blogs. Evaluation Questionnaires and interviews will be conducted at the end of the course to see the impact and students’ perception for the course.

Keywords: blog, peer assessment, English writing, error analysis

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Authors: Mohammad K. Abedin, Mohammad Shahjahan, Zeenat Sultana, Tawfique Jahan, Jesmin Akter

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To strengthen social and behavior change communication (SBCC) capacity of Ministry of Health and Family Welfare (MoHFW) of the Government of Bangladesh, BCCP/BKMI developed two eLearning courses providing opportunities for professional development of SBCC Program Managers who have no access to training or refreshers training. The two eLearning courses – Message and Material Development (MMD) and Monitoring and Evaluation (MandE) of SBCC programs – went online in September 2015, where all users could register their participation so results could be monitored. Methodology: To assess the uses of these courses a randomly selected sample was collected to run a pre and post-test analyses and a phone survey were conducted. Systematic random sampling was used to select a sample of 75 MandE and 25 MMD course participants from a sampling frame of 179 and 51 respectively. Results: As of September 2016, more than 179 learners have completed the MandE course, and 49 learners have completed the MMD course. The users of these courses are program managers, university faculty members, and students. Encouraging results were revealed from the analysis of pre and post-test scores and a phone survey three months after course completion. Test scores suggested a substantial increase in knowledge. The pre-test scores findings suggested that about 19% learners scored high on the MandE. The post-test scores finding indicated a high score (92%) of the sample across 4 modules of MandE. For MMD course in pre-test scoring, 30% of the learners scored high, and 100% scored high at the post-test. It was found that all the learners in the phone survey have discussed the courses. Most of the sharing occurred with colleagues and friends, usually through face to face (70%) interaction. The learners reported that they did recommend the two courses to concerned people. About 67% MandE and 76% MMD learners stated that the concepts that they had to learn during the course were put into practice in their work settings. The respondents for both MandE and MMD courses have provided a valuable set of suggestions that would further strengthen the courses. Conclusions: The study showed that the initiative offered ample opportunities to build capacity in various ways in which the eLearning courses were used. It also highlighted the importance of scaling up these efforts to further strengthen the outcomes.

Keywords: e-learning course, message & material development, monitoring & evaluation, social and behavior change communication

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Authors: Ebtehal Qulisy, Geoffrey Dougherty, Kholoud Hothan, Mylene Dandavino

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Background: For more than 200 years, journal clubs (JCs) have been used to teach the fundamentals of critical appraisal and evidence-based practice (EBP). However, JCs curricula face important challenges, including poor sustainability, insufficient time to prepare for and conduct the activities, and lack of trainee skills and self-efficacy with critical appraisal. Andragogy principles and modern technology could help EBP be taught in more relevant, modern, and interactive ways. Method: We propose a fresh educational activity to teach EBP. Educational sessions are designed to encourage collaborative and experiential learning and do not require advanced preparation by the participants. Each session lasts 60 minutes and is adaptable to in-person, virtual, or hybrid contexts. Sessions are structured around a worksheet and include three educational objectives: “1. Identify a Clinical Conundrum”, “2. Compare and Contrast Current Guidelines”, and “3. Choose a Recent Journal Article”. Sessions begin with a short presentation by a facilitator of a clinical scenario highlighting a “grey-zone” in pediatrics. Trainees are placed in groups of two to four (based on the participants’ number) of varied training levels. The first task requires the identification of a clinical conundrum (a situation where there is no clear answer but only a reasonable solution) related to the scenario. For the second task, trainees must identify two or three clinical guidelines. The last task requires trainees to find a journal article published in the last year that reports an update regarding the scenario’s topic. Participants are allowed to use their electronic devices throughout the session. Our university provides full-text access to major journals, which facilitated this exercise. Results: Participants were a convenience sample of trainees in the inpatient services at the Montréal Children’s Hospital, McGill University. Sessions were conducted as a part of an existing weekly academic activity and facilitated by pediatricians with experience in critical appraisal. There were 28 participants in 4 sessions held during Spring 2022. Time was allocated at the end of each session to collect participants’ feedback via a self-administered online survey. There were 22 responses, were 41%(n=9) pediatric residents, 22.7%(n=5) family medicine residents, 31.8%(n=7) medical students, and 4.5%(n=1) nurse practitioner. Four respondents participated in more than one session. The “Satisfied” rates were 94.7% for session format, 100% for topic selection, 89.5% for time allocation, and 84.3% for worksheet structure. 60% of participants felt that including the sessions during the clinical ward rotation was “Feasible.” As per self-efficacy, participants reported being “Confident” for the tasks as follows: 89.5% for the ability to identify a relevant conundrum, 94.8% for the compare and contrast task, and 84.2% for the identification of a published update. The perceived effectiveness to learn EBP was reported as “Agreed” by all participants. All participants would recommend this session for further teaching. Conclusion: We developed a modern approach to teach EBP, enjoyed by all levels of participants, who also felt it was a useful learning experience. Our approach addresses known JCs challenges by being relevant to clinical care, fostering active engagement but not requiring any preparation, using available technology, and being adaptable to hybrid contexts.

Keywords: medical education, journal clubs, post-graduate teaching, andragogy, experiential learning, evidence-based practice

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Authors: Kefaya Qaddoum

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The aim of this study is to predict breast cancer and to construct a supportive model that will stimulate a more reliable prediction as a factor that is fundamental for public health. In this study, we utilize general regression neural networks (GRNN) to replace the normal predictions with prediction periods to achieve a reasonable percentage of confidence. The mechanism employed here utilises a machine learning system called conformal prediction (CP), in order to assign consistent confidence measures to predictions, which are combined with GRNN. We apply the resulting algorithm to the problem of breast cancer diagnosis. The results show that the prediction constructed by this method is reasonable and could be useful in practice.

Keywords: neural network, conformal prediction, cancer classification, regression

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Authors: Zehra Buyuktuncer, Aylin H. Büyükkaragöz, Tuğçe N. Balcı, Nevin Ergun

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Background: Undergoing rigid dietary habits for enhancing athletic performance could lead to eating disorders. High prevalence of eating disorders among female athletes has been already reported. However, the risk of disordered eating among disabled athletes is not known. A better knowledge of the different eating behaviors and their prevalence in disabled athletes would be helpful to understand interactions between eating and health. This study aimed to examine the cognitive restraint, uncontrolled eating and emotional eating behaviors in a disabled athlete population. Method: A total of 70 disabled Turkish national athletes (33 female, 37 male) from 5 sport branches (soccer, weight lifting, shooting, table tennis and basketball) were involved in the study. The cognitive restraint, uncontrolled eating and emotional eating behaviors were assessed using the revised version of Three Factor Eating Questionnaire-R18 (TFEQ-R18). The questionnaires were conducted by dietitian during the preparation camps of athletes. Body weight, height and waist circumference (WC) were measured; and body composition was analyzed by bioelectrical impedance analysis method. Results: The TFEQ scales showed a cognitive dietary restraint score of 13.9±4.2, uncontrolled eating score of 17.7±5.8 and emotional eating score of 4.9±2.5. The mean score of total TFEQ-R18 was 36.5±8.62. Neither total TFEQ-R18 score nor subscale scores differed significantly by gender or sport branches (p>0.05, for each). The scores were also similar in BMI groups (n=63; p>0.05). Total TFEQ, uncontrolled eating and emotional eating scores were significantly higher among the athletes with congenital disabilities compared to the scores of the athletes with acquired disabilities (p<0.05, for each). Moreover, the cognitive dietary restraint score was significantly high in athletes who would like to lose weight (p=0.009). Conclusion: Disabled athletes might have a risk of disordered eating. The different eating behaviors among disabled athletes should be assessed using validated tools to develop personalized nutritional strategies for those athletes.

Keywords: disabled athletes, eating behaviour, three-factor eating questionnaire-r18, body composition

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Authors: Jessica Gu, Yu Chen

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Knowledge Management (KM) is undoubtable crucial to organizational value creation, learning, and adaptation. Although the rapidly growing KM domain has been fueled with full-fledged methodologies and technologies, studies on KM evolution that bridge the organizational performance and adaptation to the organizational environment are still rarely attempted. In particular, creation (or generation) and diffusion (or share/exchange) of knowledge are of the organizational primary concerns on the problem-solving perspective, however, the optimized distribution of knowledge creation and diffusion endeavors are still unknown to knowledge workers. This research proposed an agent-based model of knowledge creation and diffusion in an organization, aiming at elucidating how the intertwining knowledge flows at microscopic level lead to optimized organizational performance at macroscopic level through evolution, and exploring what exogenous interventions by the policy maker and endogenous adjustments of the knowledge workers can better cope with different environmental conditions. With the developed model, a series of simulation experiments are conducted. Both long-term steady-state and time-dependent developmental results on organizational performance, network and structure, social interaction and learning among individuals, knowledge audit and stocktaking, and the likelihood of choosing knowledge creation and diffusion by the knowledge workers are obtained. One of the interesting findings reveals a non-monotonic phenomenon on organizational performance under turbulent environment while a monotonic phenomenon on organizational performance under a stable environment. Hence, whether the environmental condition is turbulence or stable, the most suitable exogenous KM policy and endogenous knowledge creation and diffusion choice adjustments can be identified for achieving the optimized organizational performance. Additional influential variables are further discussed and future work directions are finally elaborated. The proposed agent-based model generates evidence on how knowledge worker strategically allocates efforts on knowledge creation and diffusion, how the bottom-up interactions among individuals lead to emerged structure and optimized performance, and how environmental conditions bring in challenges to the organization system. Meanwhile, it serves as a roadmap and offers great macro and long-term insights to policy makers without interrupting the real organizational operation, sacrificing huge overhead cost, or introducing undesired panic to employees.

Keywords: knowledge creation, knowledge diffusion, agent-based modeling, organizational performance, decision making evolution

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Authors: Mansoureh Ghiasabadi Farahani, Samira Kalantary, Sara Taghi-Pour, Mahboubeh Shamsi

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Nowadays, the development of computers technology and its recent applications provide access to new types of data, which have not been considered by the traditional data analysts. Two particularly interesting characteristics of such data sets include their huge size and streaming nature .Incremental learning techniques have been used extensively to address the data stream classification problem. This paper presents a concise survey on the obstacles and the requirements issues classifying data streams with using decision tree. The most important issue is to maintain a balance between accuracy and efficiency, the algorithm should provide good classification performance with a reasonable time response.

Keywords: big data, data streams, classification, decision tree

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Authors: Gohar Marikyan

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This article is about investigating how to effectively use visuals in teaching introductory mathematics. The analysis showed the use of visuals in teaching introductory mathematics can be an effective tool for enhancing students’ learning and engagement in mathematics. The use of visuals was particularly effective for teaching concepts of numbers, operations with whole numbers, and properties of operations. The analysis also provides strong evidence that the effectiveness of visuals varied depending on the way the visuals are used. Furthermore, the analysis revealed that the use of visuals in mathematics instruction had a positive impact on student’s attitudes toward mathematics, with students showing higher levels of motivation and enjoyment in mathematics classes.

Keywords: analytical thinking skills, instructional strategies with visuals, introductory mathematics, student engagement and motivation

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Authors: I. Kerti, G. Sezen, S. Daglilar

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This present work is focused on studying to improve low wetting behaviour between liquid metal and ceramic particles. Ceramic particles like SiC and B4C have attracted great attention because of their usability as reinforcement for composite materials. However, poor wettability of particles is one of the major drawbacks of metal matrix composite production. Various methods have been studied to enhance the wetting properties between ceramic materials and metal substrates during ceramic reinforced metal matrix composites. Among these methods, autocatalytic nickel deposition is a unique process for the enhancement of the surface properties of ceramic particles. In fact, it is difficult to obtain continuous and uniform metallic coating on ceramic powders. In this study deposition of nickel boron layer on ceramic particles via autocatalytic plating in borohydride baths were investigated. Firstly, powders with different particle sizes were sensitized and activated respectively in order to ensure catalytic properties. Following the pre-treatment operations, particles were transferred into the coating bath containing nickel sulphate or nickel chloride as the Ni2+ source. The results show that a better bonding and uniform coating layer were obtained for Ni-B coatings with the Ni2+ source of NiCl2.6H2O as compared to NiSO4.6H2O. With the progress of the time, both particle surfaces are completely covered by a continuous and thin nickel boron layer. The surface morphology of the coatings that were analysed using scanning electron microscopy (SEM) show that SiC and B4C particles both distributed and different thickness of Ni-B nanolayers have been successfully coated onto the particles. The particles were mounted into a polimeric resin and polished in order to observe the thickness and the continuity of the coating layer. The composition of the coating layers were also evaluated by EDS analyses. The SEM morphologies and the EDS results of the coatings at different reaction times were adopted for detailed discussion of the Ni-B electroless plating mechanism.

Keywords: boron carbide, electroless coating, nickel boron deposition, silicon carbide

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Authors: Lamia Emam

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The attractiveness of entrepreneurship education stems from its perceived value as a venue through which students can develop an entrepreneurial mindset, skill set, and practice, which may not necessarily lead to them starting a new business, but could, more importantly, be manifested as a life skill that could be applied to all types of organizations and career endeavors. This, in turn, raises important questions about what happens in our classrooms; our role as educators, the role of students, center of learning, and the instructional approach; all of which eventually contribute to achieving the desired EE outcomes. With application to an undergraduate entrepreneurship course -Entrepreneurship as Practice- the current paper aims to explore the effect of entrepreneurship education on the development of students’ general entrepreneurial tendencies. Towards that purpose, the researcher herein uses a pre-test and post-test quasi-experimental research design where the Durham University General Enterprising Tendency Test (GET2) is administered to the same group of students before and after course delivery. As designed and delivered, the Entrepreneurship as Practice module is a highly applied and experiential course where students are required to develop an idea for a start-up while practicing the entrepreneurship-related knowledge, mindset, and skills that are taught in class, both individually and in groups. The course is delivered using a combination of short lectures, readings, group discussions, case analysis, guest speakers, and, more importantly, actively engaging in a series of activities that are inspired by diverse methods for developing successful and innovative business ideas, including design thinking, lean-start up and business feasibility analysis. The instructional approach of the course particularly aims at developing the students' critical thinking, reflective, analytical, and creativity-based problem-solving skills that are needed to launch one’s own start-up. The analysis and interpretation of the experiment’s outcomes shall simultaneously incorporate the views of both the educator and students. As presented, the study responds to the rising call for the application of experimental designs in entrepreneurship in general and EE in particular. While doing so, the paper presents an educator’s perspective of EE to complement the dominant stream of research which is constrained to the students’ point of view. Finally, the study sheds light on EE in the MENA region, where the study is applied.

Keywords: entrepreneurship education, andragogy and heutagogy, scholarship of teaching and learning, experiment

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Authors: Briony Gray, Glenn Simpson, Hajira Dambha-Miller, Andrew Farmer

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Multimorbidity may be strongly affected by a variety of conditions, factors, and variables requiring higher demands on health and social care services, infrastructure, and expenses. Holding one or more conditions increases one’s risk for development of future conditions; with patients over 65 years old at highest risk. Psychosocial factors such as anxiety and depression are rising exponentially globally, which has been amplified by the COVID19 pandemic. These are highly correlated and predict poorer outcomes when held in coexistence and increase the likelihood of comorbid physical health conditions. While possible future reform of social and healthcare systems may help to alleviate some of these mounting pressures, there remains an urgent need to better understand the potential role health behaviours and psychosocial conditions - such as anxiety and depression – may have on aging populations. Using the UK healthcare scene as a lens for analysis, this study uses big data collected in the UK Longitudinal Study of Aging (ELSA) to examine the role of anxiety and depression in ageing populations (65yrs+). Using logistic regression modelling, results identify the 10 most significant variables correlated with both anxiety and depression from data categorised into the areas of health behaviour, psychosocial, socioeconomic, and life satisfaction (each demonstrated through literature review to be of significance). These are compared with wider global research findings with the aim of better understanding the areas in which social and healthcare reform can support multimorbidity interventions, making suggestions for improved patient-centred care. Scope of future research is outlined, which includes analysis of 59 total multimorbidity variables from the ELSA dataset, going beyond anxiety and depression.

Keywords: multimorbidity, health behaviours, patient centred care, psychosocial factors

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Authors: Sahar El-Achkar, Mizan Ahmad

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Poor adaptation of developmental milestones over the lifespan can significantly impact emotional experiences and Satisfaction with Life (SWL) post-retirement. Thus, it is important to understand how adaptive behaviour over the life course can predict emotional experiences. Broadly emotional experiences are either Positive Affect (PA) or Negative Affect (NA). This study sought to explore the impact of successful adaptation of developmental milestones throughout one’s life on emotional experiences and satisfaction with life following retirement. A cross-sectional self-report survey was completed by 132 Australian retirees between the ages 55 and 70 years. Three hierarchical regression models were fitted, controlling for age and gender, to predict PA, NA, and SWL. The full model predicting PA was statistically significant overall, F (8, 121) = 17.97, p < .001, account for 57% of the variability in PA. Industry/Inferiority were significantly predictive of PA. The full model predicting NA was statistically significant overall, F (8, 121) = 12.00, p < .001, accounting for 51% of the variability in NA. Age and Trust/Mistrust were significantly predictive of NA. The full model predicting NA was statistically significant overall, F (8, 121) = 12.00, p < .001, accounting for 51% of the variability in NA. Age and Trust/Mistrust were significantly predictive of NA. The full model predicting SWL, F (8, 121) = 11.05, p < .001, accounting for 45% of the variability in SWL. Trust/Mistrust and Ego Integrity/Despair were significantly predictive of SWL. A sense of industry post-retirement is important in generating PA. These results highlight that individuals presenting with adaptation and identity issues are likely to present with adjustment challenges and unpleasant emotional experiences post-retirement. This supports the importance of identifying and understanding the benefits of successful adaptation and development throughout the lifespan and its significance for the self-concept. Most importantly, the quality of lives of many may be improved, and the future risk of continued poor emotional experiences and SWL post-retirement may be mitigated. Specifically, the clinical implications of these findings are that they support the promotion of successful adaption over the life course and healthy ageing.

Keywords: adaptation, development, negative affect, positive affect, retirement, satisfaction with life

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Authors: Afshin Shahbazi, Hadi Shadi Naghadeh, Ahmad Khodadadi Darban

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In the Magnetically Assisted Chemical Separation (MACS) process, tiny ferromagnetic particles coated with solvent extractant are used to selectively separate radionuclides and hazardous metals from aqueous waste streams. The contaminant-loaded particles are then recovered from the waste solutions using a magnetic field. In the present study, Cyanex272 or C272 (bis (2,4,4-trimethylpentyl) phosphinic acid) coated magnetic particles are being evaluated for the possible application in the extraction of Thorium (IV) from nuclear waste streams. The uptake behaviour of Th(IV) from nitric acid solutions was investigated by batch studies. Adsorption of Thorium (IV) from aqueous solution onto adsorbent was investigated in a batch system. Adsorption isotherm and adsorption kinetic studies of Thorium (IV) onto nanoparticles coated Cyanex272 were carried out in a batch system. The factors influencing Thorium (IV) adsorption were investigated and described in detail, as a function of the parameters such as initial pH value, contact time, adsorbent mass, and initial Thorium (IV) concentration. Magnetically Assisted Chemical Separation (MACS) process adsorbent showed best results for the fast adsorption of Th (IV) from aqueous solution at aqueous phase acidity value of 0.5 molar. In addition, more than 80% of Th (IV) was removed within the first 2 hours, and the time required to achieve the adsorption equilibrium was only 140 minutes. Langmuir and Frendlich adsorption models were used for the mathematical description of the adsorption equilibrium. Equilibrium data agreed very well with the Langmuir model, with a maximum adsorption capacity of 48 mg.g-1. Adsorption kinetics data were tested using pseudo-first-order, pseudo-second-order and intra-particle diffusion models. Kinetic studies showed that the adsorption followed a pseudo-second-order kinetic model, indicating that the chemical adsorption was the rate-limiting step.

Keywords: Thorium (IV) adsorption, MACS process, magnetic nanoparticles, Cyanex272

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Authors: H. Dakhlaoui, D. Ruelland, Y. Tramblay, Z. Bargaoui

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To evaluate the impact of climate change on water resources at the catchment scale, not only future projections of climate are necessary but also robust rainfall-runoff models that are able to be fairly reliable under changing climate conditions. This study aims at assessing the robustness of three conceptual rainfall-runoff models (GR4j, HBV and IHACRES) on five basins in Northern Tunisia under long-term climate variability. Their robustness was evaluated according to a differential split sample test based on a climate classification of the observation period regarding simultaneously precipitation and temperature conditions. The studied catchments are situated in a region where climate change is likely to have significant impacts on runoff and they already suffer from scarcity of water resources. They cover the main hydrographical basins of Northern Tunisia (High Medjerda, Zouaraâ, Ichkeul and Cap bon), which produce the majority of surface water resources in Tunisia. The streamflow regime of the basins can be considered as natural since these basins are located upstream from storage-dams and in areas where withdrawals are negligible. A 30-year common period (1970‒2000) was considered to capture a large spread of hydro-climatic conditions. The calibration was based on the Kling-Gupta Efficiency (KGE) criterion, while the evaluation of model transferability is performed according to the Nash-Suttfliff efficiency criterion and volume error. The three hydrological models were shown to have similar behaviour under climate variability. Models prove a better ability to simulate the runoff pattern when transferred toward wetter periods compared to the case when transferred to drier periods. The limits of transferability are beyond -20% of precipitation and +1.5 °C of temperature in comparison with the calibration period. The deterioration of model robustness could in part be explained by the climate dependency of some parameters.

Keywords: rainfall-runoff modelling, hydro-climate variability, model robustness, uncertainty, Tunisia

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Authors: Mohd Sabri Minhat, Nurul Adilla Mohd Subha

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The 1MWth PUSPATI TRIGA Reactor (RTP) in Malaysia Nuclear Agency has been operating more than 35 years. The existing core power control is using conventional controller known as Feedback Control Algorithm (FCA). It is technically challenging to keep the core power output always stable and operating within acceptable error bands for the safety demand of the RTP. Currently, the system could be considered unsatisfactory with power tracking performance, yet there is still significant room for improvement. Hence, a new design core power control is very important to improve the current performance in tracking and regulating reactor power by controlling the movement of control rods that suit the demand of highly sensitive of nuclear reactor power control. In this paper, the proposed Model Predictive Control (MPC) law was applied to control the core power. The model for core power control was based on mathematical models of the reactor core, MPC, and control rods selection algorithm. The mathematical models of the reactor core were based on point kinetics model, thermal hydraulic models, and reactivity models. The proposed MPC was presented in a transfer function model of the reactor core according to perturbations theory. The transfer function model-based predictive control (TFMPC) was developed to design the core power control with predictions based on a T-filter towards the real-time implementation of MPC on hardware. This paper introduces the sensitivity functions for TFMPC feedback loop to reduce the impact on the input actuation signal and demonstrates the behaviour of TFMPC in term of disturbance and noise rejections. The comparisons of both tracking and regulating performance between the conventional controller and TFMPC were made using MATLAB and analysed. In conclusion, the proposed TFMPC has satisfactory performance in tracking and regulating core power for controlling nuclear reactor with high reliability and safety.

Keywords: core power control, model predictive control, PUSPATI TRIGA reactor, TFMPC

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Authors: Utkarsh A. Mishra, Ankit Bansal

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At high temperature, radiative heat transfer is the dominant mode of heat transfer. It is governed by various phenomena such as photon emission, absorption, and scattering. The solution of the governing integrodifferential equation of radiative transfer is a complex process, more when the effect of participating medium and wavelength properties are taken into consideration. Although a generic formulation of such radiative transport problem can be modeled for a wide variety of problems with non-gray, non-diffusive surfaces, there is always a trade-off between simplicity and accuracy of the problem. Recently, solutions of complicated mathematical problems with statistical methods based on randomization of naturally occurring phenomena have gained significant importance. Photon bundles with discrete energy can be replicated with random numbers describing the emission, absorption, and scattering processes. Photon Monte Carlo (PMC) is a simple, yet powerful technique, to solve radiative transfer problems in complicated geometries with arbitrary participating medium. The method, on the one hand, increases the accuracy of estimation, and on the other hand, increases the computational cost. The participating media -generally a gas, such as CO₂, CO, and H₂O- present complex emission and absorption spectra. To model the emission/absorption accurately with random numbers requires a weighted sampling as different sections of the spectrum carries different importance. Importance sampling (IS) was implemented to sample random photon of arbitrary wavelength, and the sampled data provided unbiased training of MC estimators for better results. A better replacement to uniform random numbers is using deterministic, quasi-random sequences. Halton, Sobol, and Faure Low-Discrepancy Sequences are used in this study. They possess better space-filling performance than the uniform random number generator and gives rise to a low variance, stable Quasi-Monte Carlo (QMC) estimators with faster convergence. An optimal supervised learning scheme was further considered to reduce the computation costs of the PMC simulation. A one-dimensional plane-parallel slab problem with participating media was formulated. The history of some randomly sampled photon bundles is recorded to train an Artificial Neural Network (ANN), back-propagation model. The flux was calculated using the standard quasi PMC and was considered to be the training target. Results obtained with the proposed model for the one-dimensional problem are compared with the exact analytical and PMC model with the Line by Line (LBL) spectral model. The approximate variance obtained was around 3.14%. Results were analyzed with respect to time and the total flux in both cases. A significant reduction in variance as well a faster rate of convergence was observed in the case of the QMC method over the standard PMC method. However, the results obtained with the ANN method resulted in greater variance (around 25-28%) as compared to the other cases. There is a great scope of machine learning models to help in further reduction of computation cost once trained successfully. Multiple ways of selecting the input data as well as various architectures will be tried such that the concerned environment can be fully addressed to the ANN model. Better results can be achieved in this unexplored domain.

Keywords: radiative heat transfer, Monte Carlo Method, pseudo-random numbers, low discrepancy sequences, artificial neural networks

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Authors: P. Serrão, E. Costa, A. Ribeiro, V. Infante

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The characteristic sonority of the Portuguese guitar is in great part what makes Fado so distinguishable from other traditional song styles. The Portuguese guitar is a pear-shaped plucked chordophone with six courses of double strings. This study compares the two types of plain strings available for Portuguese guitar and used by the musicians. One is stainless steel spring wire, the other is high carbon spring steel (music wire). Some musicians mention noticeable differences in sound quality between these two string materials, such as a little more brightness and sustain in the steel strings. Experimental tests were performed to characterize string tension at pitch; mechanical strength and tuning stability using the universal testing machine; dimensional control and chemical composition analysis using the scanning electron microscope. The string dynamical behaviour characterization experiments, including frequency response, inharmonicity, transient response, damping phenomena and were made in a monochord test set-up designed and built in-house. Damping factor was determined for the fundamental frequency. As musicians are able to detect very small damping differences, an accurate a characterization of the damping phenomena for all harmonics was necessary. With that purpose, another improved monochord was set and a new system identification methodology applied. Due to the complexity of this task several adjustments were necessary until obtaining good experimental data. In a few cases, dynamical tests were repeated to detect any evolution in damping parameters after break-in period when according to players experience a new string sounds gradually less dull until reaching the typically brilliant timbre. Finally, each set of strings was played on one guitar by a distinguished player and recorded. The recordings which include individual notes, scales, chords and a study piece, will be analysed to potentially characterize timbre variations.

Keywords: damping factor, music wire, portuguese guitar, string dynamics

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Authors: Omkar Gaonkar, Indumathi Nambi, Suresh G. Kumar

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The functional and morphological aspects of soil structure determine the soil quality. The dispersion of colloidal soil particles, especially the clay fraction and rupture of soil aggregates, both of which play an important role in soil structure development, lead to degradation of soil quality. The main objective of this work was to determine the effect of the behaviour of soil colloids on the agricultural soil structure and quality. The effect of commercial humic acid and soil natural organic matter on the electrical and structural properties of the soil colloids was also studied. Agricultural soil, belonging to the sandy loam texture class from northern part of India was considered in this study. In order to understand the changes in the soil quality in the presence and absence of humic acids, the soil fabric and structure was analyzed by X-ray diffraction (XRD), Fourier Transform Infrared (FTIR) Spectroscopy and Scanning Electron Microscopy (SEM). Electrical properties of natural soil colloids in aqueous suspensions were assessed by zeta potential measurements at varying pH values with and without the presence of humic acids. The influence of natural organic matter was analyzed by oxidizing the natural soil organic matter with hydrogen peroxide. The zeta potential of the soil colloids was found to be negative in the pH range studied. The results indicated that hydrogen peroxide treatment leads to deflocculation of colloidal soil particles. In addition, the humic acids undergoes effective adsorption onto the soil surface imparting more negative zeta potential to the colloidal soil particles. The soil hydrophilicity decreased in the presence of humic acids which was confirmed by surface free energy determination. Thus, it can be concluded that the presence of humic acids altered the soil fabric and structure, thereby affecting the soil quality. This study assumes significance in understanding soil aggregation and the interactions at soil solid-liquid interface.

Keywords: humic acids, natural organic matter, zeta potential, soil quality

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Authors: Florentina Hahaianu, Mihaela Negrescu

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The analysis of the positive and negative effects of technology use and abuse in Generation Z comes as a necessity in order to understand their ever-changing emotional development needs. The article quantitatively analyzes the findings of a sociological questionnaire on a group of students in social sciences. It aimed to identify the changes generated by the use of digital resources in the emotional intelligence development. Among the outcomes of our study we include a predilection for IT related activities – be they social, learning, entertainment, etc. which undermines the manifestation of emotional intelligence, especially the reluctance to face-to-face interaction. In this context, the issue of emotional intelligence development comes into focus as a solution to compensate for the undesirable effects that contact with technology has on this generation.

Keywords: digital resources, emotional intelligence, generation Z, students

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Authors: Ahmet Faruk Akyuz, Hasan Sakir Bilge

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Depth estimation using stereo images is a challenging problem in computer vision. Many different studies have been carried out to solve this problem. With advancing machine learning, tackling this problem is often done with neural network-based solutions. The images used in these studies are mostly in the visible spectrum. However, the need to use the Infrared (IR) spectrum for depth estimation has emerged because it gives better results than visible spectra in some conditions. At this point, we recommend using thermal-thermal (IR) image pairs for depth estimation. In this study, we used two well-known networks (PSMNet, FADNet) with minor modifications to demonstrate the viability of this idea.

Keywords: thermal stereo matching, deep neural networks, CNN, Depth estimation

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Authors: Al Ameen H., Rakesh P.

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To improve the combustion efficiency of fuels and to reduce the emissions of pollutants as well as to improve heat transfer characteristics of fuels, both non-metallic and metallic nanoparticles can be added into it. By varying the concentration and size of nano particles added into the fuels, behaviour of droplet combustion and hence heat generated can be altered. In case of solid or liquid fuels, surface area of the fuel in contact with oxidizer(gaseous) is small because of higher density compared to gases. If the surface area of fuel exposed to the oxidizer is very small, then the combustion will not occur, because the combustion rate is proportional to the surface area of fuel droplet. To avoid such instance there is a way to increase the exposed surface area. To increase the specific surface area available for reaction, the particle size can be reduced. If the additives are solid then by reducing the particles size the specific surface area of liquid fuel can be increased. For the liquid fuels the exposed surface area available for combustion can be increased by suspending nanoparticles. Addition of non-metallic and metallic nanoparticles in fuels improves its combustion efficiency by enhancing the thermo-physical properties. The burn rate constants and temperatures of Kerosene-Oxygen combustion for fuel droplet sizes of 50μm, 75μm, 100μm and 125μm under varying concentrations of 25%, 50%, 75% and 100% are studied numerically and its characteristic velocities are determined. Later the burn rate constants of fuel with concentrations of 0.5%, 1.0% and 2.0% by weight of aluminium nanoparticles are added. The spray combustion characteristics of such nano-fuel has improved the combustion temperature by the addition of aluminium nanoparticles. Thus, aluminium nanoparticles have improved burn rate and characteristic velocity of Kerosene-Oxygen combustion. An increase of 40% in characteristic velocity is observed.

Keywords: burn rate, characteristic velocity, combustion, thermo-physical properties

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Authors: Laura Santagostini, Vittoria Guglielmi

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The meaning of the word 'Nature' (literally 'that which is about to be born') has accompanied researchers throughout their study of the environment and has led to the design of technical means to improve the properties of the soil, modifying its structure and/or consistency, thus favouring the emergence and growth of plants. These include soil improvers, i.e. any substance, natural or synthetic, mineral or organic, capable of modifying and improving the chemical, physical, biological and mechanical properties and characteristics of the soil. In particular, GCSCs (Green Composted Soil Conditioners) are soil conditioners produced through a controlled process of transforming selected organic green waste materials, such as clippings from the maintenance of ornamental greenery, crop residues and other plant waste. The use of GCSC in horticulture, fruit growing, industrial cultivation and nursery gardening is an active way to return organic carbon to the soil, thus limiting CO2 emissions and the production of greenhouse gases, and also to limit the environmental impact of peat extraction, which is normally used in these areas of application. With a view to distinguish between GCSC and peats and to assess what further contributions GCSC can provide to the soil and growing plants, we studied the behaviour of the two substrates by chromatographic techniques. After treating the individual soil improvers with different solvents, used individually or by applying a polarity gradient, the extracts obtained were analysed by HPLC and LCMS in order to assess their composition mainly from a qualitative point of view. Data obtained show in GCSC the presence of polyphenolic derivatives attributable to the degradation of plant material and potentially useful for the development and growth of young plants, while commercial peat-based products only sporadically showed the presence of recognisable molecules, confirming the lower complexity of the matrix under analysis. These results allowed us to distinguish the two different types of soil conditioner based on their chromatographic profiles.

Keywords: chromatographic profile, HPLC, polyphenols, soil conditioners

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Authors: Gwendolyn Royal-Smith

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Cocaine ranks as one of the world’s most addictive and commonly abused stimulant drugs. Recent evidence indicates that the abuse of cocaine has risen so quickly among females that this group now accounts for about 40 percent of all users in the United States. Neuropsychological studies have demonstrated that specific neural activation patterns carry higher risks for neurocognitive and executive function in cocaine addicted females thereby increasing their vulnerability for poorer treatment outcomes and more frequent post-treatment relapse when compared to males. This study examined secondary data with a convenience sample of 164 cocaine addicted male and females to assess neurocognitive and executive function. The principal objective of this study was to assess whether individual performance on the Stroop Word Color Task is predictive of treatment success by gender. A second objective of the study evaluated whether individual performance employing neurocognitive measures including the Stroop Word-Color task, the Rey Auditory Verbal Learning Test (RALVT), the Iowa Gambling Task, the Wisconsin Card Sorting Task (WISCT), the total score from the Barratte Impulsiveness Scale (Version 11) (BIS-11) and the total score from the Frontal Systems Behavioral Scale (FrSBE) test demonstrated differences in neurocognitive and executive function performance by gender. Logistic regression models were employed utilizing a covariate adjusted model application. Initial analyses of the Stroop Word color tasks indicated significant differences in the performance of males and females, with females experiencing more challenges in derived interference reaction time and associate recall ability. In early testing including the Rey Auditory Verbal Learning Test (RALVT), the number of advantageous vs disadvantageous cards from the Iowa Gambling Task, the number of perseverance errors from the Wisconsin Card Sorting Task (WISCT), the total score from the Barratte Impulsiveness Scale (Version 11) (BIS-11) and the total score from the Frontal Systems Behavioral Scale, results were mixed with women scoring lower in multiple indicators in both neurocognitive and executive function.

Keywords: cocaine addiction, gender, neuropsychology, neurocognitive, executive function

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Authors: Yiqiao Yin

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Many scholars and educators have dedicated their lives in K12 education system and there has been an exploding amount of attention to implement technical foundations for Artificial Intelligence Education for high school and precollege level students. This paper focuses on the development and use of resources to support K-12 education in Artificial Intelligence (AI). The author and his team have more than three years of experience coaching students from pre-college level age from 15 to 18. This paper is a culmination of the experience and proposed online tools, software demos, and structured activities for high school students. The paper also addresses a portfolio of AI concepts as well as the expected learning outcomes. All resources are provided with online videos and Github repositories for immediate use.

Keywords: K12 education, AI4ALL, pre-college education, pre-college AI

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Authors: Alemu Moges Belay, Torgeir Welo, Jan Ola Strandhagen

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Lean has long been linked with manufacturing, but its application claimed also by other functions such as product development and services. However, there is a challenge on understanding and defining lean in each function context. This paper aims to investigate the literature that focus mainly on PD process improvement, obtain better understanding and redefine LPD in systematic way. In addition to that, the paper attempts to summarize various proposed transformation strategies, definitions, identifying features of manufacturing and product development that would help to redefining lean in product development context. Finally we redefine LPD in organized way that encompasses different steps such as stage gate, communication and information, events, learning, innovation, knowledge and value creation.

Keywords: lean, lean manufacturing, lean product development, transformation, strategies

Procedia PDF Downloads 461