Search results for: active learning

Authors: Sonia Lippke, Eric Rost, Volker Cihlar

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Objective: To examine the interrelation of physical activity with work-related variables in older individuals to determine pathways to promote the maintenance of an aging workforce’s ability and motivation to work. Design/methodology/approach: An interview-study was conducted with N=5,002 community-dwelling people aged 55 to 70 years (for T1). N=2,501 (50%) were interviewed 3 years later again (T2). Correlation-, Chi²-, MANOVA and moderated mediation analyses were performed. Findings: The less people worked, the more physically active they were. Working was only related to calendar age but not to subjective age. Men and women only differed in working hours and an interaction of gender and pension regarding working hours and subjective health revealed: Controlled for calendar age, the amount of worked hours while receiving pension was about the same in men and women, however, men worked significantly more hours if they did not receive pension. The relationship between physical activity and worked hours was mediated by life investment and subjective health in women, and by subjective health in men. Practical implications: Developing good health through performing physical activity should be done as part of work-place health promotion or by work organization and HR management to enable, and motivate older individuals to work even when receiving pension. Thus, such initiates should not only offered for younger and middle aged employees. Physical activity and company-facilitated sports activities can be an integral part in this. Originality/value: This is the first study testing these mechanisms in this age group, indicating the importance of not only understanding physical activity as a time challenge to work but also the potential to protect workability and to work aside from receiving pension.

Keywords: life investment, moderated mediation, physical activity, older workers, subjective health

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Authors: Bandi Aruna

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The increase of multidrug-resistant pathogens and the restriction on the use of antibiotics due to its side effects have drawn attention to the search for possible alternatives. Bacteriocins are ribosomally synthesized antimicrobial peptides that are active against Gram-positive and Gram-negative bacteria. The bacteriocins from lactic acid bacteria represent an important application of these peptides as clinical drugs or as food biopreservatives. The present study describes the isolation of bacteriocin producing lactic acid bacteria (LAB) from fermented batter of green gram and bengal gram using Man, Rogosa and Sharpe (MRS) media. The bacteriocin produced by these organisms inhibited the growth of Staphylococcus aureus, Escherichia coli, Klebsiella species, Pseudomonas aeruginosa, The isolates G1, G2 were isolated from green gram; B1 and B2 were isolated from fermented bengal gram batter. G1 and G2 were identified as Lactobacillus casie and B1 and B2 were identified as Streptococcus species. Antimicrobial activity of the bacteriocin produced by these strains was studied by agar well diffusion method. Bacteriocins produced by the Lactobacillus casie and Streptococcus secies retained their antagonistic property at pH of 5 and pH of 7. Exposure of bacteriocin to UV light for 4 min showed antibacterial activity. The antagonistic property was observed even at 100°C demonstrating stability at higher temperatures of the bacteriocin. The bacteriocins were stable for a period of 15 days at 27°C. The bacteriocins of G1, G2, and B2 exhibited highest antagonistic activity at pH of 5 and B1 at pH of 7. Therefore, the bacteriocins of the isolates may find important application in controlling the food-borne pathogens.

Keywords: Keywords: Antibacterial activity, Lactic acid bacteria, Bacteriocin

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Authors: Omer Altaf, Liam Wotherspoon, Rolando Orense

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The Wairau Plains are located in the north-east of the South Island of New Zealand in the region of Marlborough. The region is cut by many active crustal faults such as the Wairau, Awatere, and Clarence faults, which give rise to frequent seismic events. This paper presents the preliminary results of the overall project in which liquefaction-induced ground damage maps are developed in the Wairau Plains based on the Ministry of Business, Innovation and Employment NZ guidance. A suite of maps has been developed in relation to the level of details that was available to inform the liquefaction hazard mapping. Maps at the coarsest level of detail make use of regional geologic information, applying semi-quantitative criteria based on geological age, design peak ground accelerations and depth to the water table. The next level of detail incorporates higher resolution surface geomorphologic characteristics to better delineate potentially liquefiable and non-liquefiable deposits across the region. The most detailed assessment utilised CPT sounding data to develop ground damage response curves for areas across the region and provide a finer level of categorisation of liquefaction vulnerability. Linking these with design level earthquakes defined through NZGS guidelines will enable detailed classification to be carried out at CPT investigation locations, from very low through to high liquefaction vulnerability. To update classifications to these detailed levels, CPT investigations in geomorphic regions are grouped together to provide an indication of the representative performance of the soils in these areas making use of the geomorphic mapping outlined above.

Keywords: hazard, liquefaction, mapping, seismicity

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Authors: Vadim Makarov, Stewart T.Cole

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PBTZ169 is novel drug candidate with high efficacy in animals models, and its combination treatment of PBTZ169 with BDQ and pyrazinamide was shown to be more efficacious than the standard treatment for tuberculosis in a mouse model. The target of PBTZ169 is famous DprE1, an essential enzyme in cell wall biosynthesis. The crystal structure of the DprE1-PBTZ169 complex reveals formation of a semimercaptal adduct with Cys387 in the active site and explains the irreversible inactivation of the enzyme. Furthermore, this drug candidate demonstrated during preclinical research ‘drug like’ properties what made it an attractive drug candidate to treat tuberculosis in humans. During first clinical trials several cohorts of the healthy volunteers were treated by the single doses of PBTZ169 as well as two weeks repeated treatment was chosen for two maximal doses. As expected PBTZ169 was well tolerated, and no significant toxicity effects were observed during the trials. The study of the metabolism shown that human metabolism of PBTZ169 is very different from microbial or animals compound transformation. So main pathway of microbial, mice and less rats metabolism connected with reduction processes, but human metabolism mainly connected with oxidation processes. Due to this difference we observed several metabolites of PBTZ169 in humans with antitubercular activity, and now we can conclude that animal antituberculosis activity of PBTZ169 is a result not only activity of the drug itself, but it is a result of the sum activity of the drug and its metabolites. Direct antimicrobial plasma activity was studied, and such activity was observed for 24 hours after human treatment for some doses. This data gets high chance for good efficacy of PBTZ169 in human for treatment TB infection. Second phase of clinical trials was started summer of 2017 and continues to the present day. Available data will be presented.

Keywords: clinical trials, DprE1, PBTZ169, metabolism

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Authors: M. Pellerone, S. G. Razza, L. Miano, A. Miccichè, M. Adamo

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The teacher’s attitude plays a decisive role in promoting the development of the non-native or disabled student and counteracting hypothetical negative attitudes and prejudice towards those who are “different”.The objective of the present research is to measure the relationship between teachers’ prejudices towards disabled and/or immigrant students as predictors of teaching-learning strategies. A cross-sectional study involved 200 Italian female teachers who completed an anamnestic questionnaire, the Assessment Teaching Scale, the Italian Modern and Classical Prejudices Scale towards people with ID, and the Pettigrew and Meertens’ Blatant Subtle Prejudice Scale. Confirming research hypotheses, data underlines the predictive role of prejudice on teaching strategies, and in particular on the socio-emotional and communicative-relational dimensions. Results underline that general training appears necessary, especially for younger generations of teachers.

Keywords: disabled students, immigrant students, instructional competence, prejudice, teachers

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Authors: Ramūnas Antanaitis, Lina Anskienė, Robertas Stoškus

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This study was conducted during 2021.05.01 – 2021.08.31 at the Lithuanian University of health sciences and one Lithuanian dairy farm with 500 dairy cows (55.911381565736, 21.881321760608195). Average calving – 50 cows per month. Cows (n=20) in the treatment group (TG) were fed with feed supplement Optipartum C+ 200 (Enzymes: Alfa- Amylase 57 Units; Beta-Glucanase 107 Units) from 21 days before calving till 30 days after calving with feeding rate 200g/cow/day. Cows in the control group (CG) were fed a feed ration without feed supplement. Measurements started from 6 days before calving and continued till 21 days after calving. The following indicators were registered: with the RumiWatch System: Rumination time; Eating time; Drinking time; Rumination chews; Eating chews; Drinking gulps; Bolus; Chews per minute; Chews per bolus. With SmaXtec system - the temperature, pH of the contents of cows' reticulorumens and cows' activity. According to our results, we found that feeding of cows, from 21 days before calving to 30 days after calving, with a feed supplement with alfa- amylase and beta-glucanase (Optipartum C+ 200) (with dose 200g/cow/day) can produce an increase in: 9% rumination time and eating time, 19% drinking time, 11% rumination chews, 16% eating chews,13% number of boluses per rumination, 5% chews per minute and 16% chews per bolus. We found 1.28 % lower reiticulorumen pH and 0.64% lower reticulorumen temperature in cows fed with the supplement compared with control group cows. Also, cows feeding with enzymes were 8.80% more active.

Keywords: Alfa-Amylase, Beta-Glucanase, cows, in-line, sensors

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Authors: H. E. M. W. G. M. K. Ekanayake, J. Dharmasena

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Natural Landscape fragmentation and habitat loss are emerging issues in Sri Lanka, which is due to rapid urban development and inadequate concern of managing Landscape connectivity. Urban Wetlands are the most vulnerable ecosystem effects from the fragmentation. Therefore, management of landscape connectivity with proper analysis and understanding has become a most important measure for urban wetland habitats. This study aimed to introduce spatial planning strategy to identify and locate landscape developments appropriately in order to restore landscape connectivity. Therefore, the study focuses on understanding the relationship between habitat patch metrics and landscape connectivity with reference to Colombo wetlands. Geographic Information Systems (GIS) was used to measure the wetland patch metrics; Patch area, Total edge, Perimeter-area ratio, Core area index and Inter-patch distances. Further, GIS-enabled least-cost path tool was used to measure the Landscape connectivity and calculate the number of species flow paths per wetland patch. According to the research findings; increasing the patch area, maintaining a mean perimeter-area ratio and core area index also reducing the inter-patch distances could enhance the landscape connectivity. Further, this study introduces three patch typologies; ‘active patches,' ‘open patches’ and ‘closed patches’ that severs to landscape connectivity in different levels. In the end, the study proposes a strategy for Landscape Architects to select most suitable locations to implement ecological based landscape developments with adjacent to the existing urban habitat in order to enhance habitat patch metrics and to restore the landscape connectivity.

Keywords: landscape fragmentation, urban wetlands, landscape connectivity, patch metrics

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Authors: Mairo Musa Galadima, Phoebe Mshelia

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In Nigeria, the national policy of education stipulates that the kindergarten primary schools and the legislature are to use the three popular Nigerian Languages namely: Hausa, Igbo and Yoruba. However, the English language seems to be preferred and this calls for this paper. Attempts were made to draw out the challenges faced by learners in understanding English speech sounds and using them to communicate effectively in English; using 5(five) selected secondary school in Bauchi. It was discover that challenges abound in the wrong use of stress and intonation, transfer of phonetic features from their first language. Others are inadequate qualified teachers and relevant materials including text-books. It is recommended that teachers of English should lay more emphasis on the teaching of supra-segmental features and should be encouraged to go for further studies, seminars and refresher courses.

Keywords: kindergarten, stress, phonetic and intonation, Nigeria

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Authors: Elena Kokkoni, Prasanna Kannappan, Ashkan Zehfroosh, Effrosyni Mavroudi, Kristina Strother-Garcia, James C. Galloway, Jeffrey Heinz, Rene Vidal, Herbert G. Tanner

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Early immobility affects the motor, cognitive, and social development. Current pediatric rehabilitation lacks the technology that will provide the dosage needed to promote mobility for young children at risk. The addition of socially assistive robots in early interventions may help increase the mobility dosage. The aim of this study is to examine the feasibility of an early intervention paradigm where non-walking infants experience independent mobility while socially interacting with robots. A dynamic environment is developed where both the child and the robot interact and learn from each other. The environment involves: 1) a range of physical activities that are goal-oriented, age-appropriate, and ability-matched for the child to perform, 2) the automatic functions that perceive the child’s actions through novel activity recognition algorithms, and decide appropriate actions for the robot, and 3) a networked visual data acquisition system that enables real-time assessment and provides the means to connect child behavior with robot decision-making in real-time. The environment was tested by bringing a two-year old boy with Down syndrome for eight sessions. The child presented delays throughout his motor development with the current being on the acquisition of walking. During the sessions, the child performed physical activities that required complex motor actions (e.g. climbing an inclined platform and/or staircase). During these activities, a (wheeled or humanoid) robot was either performing the action or was at its end point 'signaling' for interaction. From these sessions, information was gathered to develop algorithms to automate the perception of activities which the robot bases its actions on. A Markov Decision Process (MDP) is used to model the intentions of the child. A 'smoothing' technique is used to help identify the model’s parameters which are a critical step when dealing with small data sets such in this paradigm. The child engaged in all activities and socially interacted with the robot across sessions. With time, the child’s mobility was increased, and the frequency and duration of complex and independent motor actions were also increased (e.g. taking independent steps). Simulation results on the combination of the MDP and smoothing support the use of this model in human-robot interaction. Smoothing facilitates learning MDP parameters from small data sets. This paradigm is feasible and provides an insight on how social interaction may elicit mobility actions suggesting a new early intervention paradigm for very young children with motor disabilities. Acknowledgment: This work has been supported by NIH under grant #5R01HD87133.

Keywords: activity recognition, human-robot interaction, machine learning, pediatric rehabilitation

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Authors: Jennifer Holbein, Maritza Wiedel

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Background: Aging is associated with an increased risk of falls in older adults, and as a result, falls have become public health crises. However, the incidence of falls can be reduced through healthy aging and the implementation of a regular exercise and strengthening program. Public health and healthcare professionals authorize the use of evidence‐based, exercise‐focused fall interventions, but there are major obstacles to translating and disseminating research findings into healthcare practices. The purpose of this study was to assess the feasibility of an intervention, A Matter of Balance, in terms of demand, acceptability, and implementation into current exercise programs. Subjects: Seventy-five participants from rural communities, above the age of sixty, were randomized to an intervention or attention-control of the standardized senior fitness test. Methods: Subject completes the intervention, which combines two components: (1) motivation and (2) fall-reducing physical activities with protocols derived from baseline strength and balanced assessments. Participants (n=75) took part in the program after completing baseline functional assessments as well as evaluations of their personal knowledge, health outcomes, demand, and implementation interventions. After 8-weeks of the program, participants were invited to complete follow-up assessments with results that were compared to their baseline functional analyses. Out of all the participants in the study who complete the initial assessment, approximately 80% are expected to maintain enrollment in the implemented prescription. Furthermore, those who commit to the program should show mitigation of fall risk upon completion of their final assessment.

Keywords: aging population, exercise, falls, functional assessment, healthy aging

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Authors: O. S. Ebrahim, K. O. Shawky, M. O. S. Ebrahim, P. K. Jain

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Induction Motor (IM) driving pump is the main consumer of electricity in a typical fluid transportation system (FTS). It was illustrated that changing the connection of the stator windings from delta to star at no load could achieve noticeable active and reactive energy savings. This paper proposes a supervisory hysteresis liquid-level control with three-state energy saving mode (ESM) for IM in FTS including storage tank. The IM pump drive comprises modified star/delta switch and hydromantic coupler. Three-state ESM is defined, along with the normal running, and named analog to computer ESMs as follows: Sleeping mode in which the motor runs at no load with delta stator connection, hibernate mode in which the motor runs at no load with a star connection, and motor shutdown is the third energy saver mode. A logic flow-chart is synthesized to select the motor state at no-load for best energetic cost reduction, considering the motor thermal capacity used. An artificial neural network (ANN) state estimator, based on the recurrent architecture, is constructed and learned in order to provide fault-tolerant capability for the supervisory controller. Sequential test of Wald is used for sensor fault detection. Theoretical analysis, preliminary experimental testing and, computer simulations are performed to show the effectiveness of the proposed control in terms of reliability, power quality and energy/coenergy cost reduction with the suggestion of power factor correction.

Keywords: ANN, ESM, IM, star/delta switch, supervisory control, FT, reliability, power quality

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Authors: Jiahe Liu, HongyangYu, Feng Qian, Miao Luo

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This study aimed to address the problem of improving the confidence of key points by fusing multi-view information, thereby estimating human posture more accurately. We first obtained multi-view image information and then used the MvP algorithm to fuse this multi-view information together to obtain a set of high-confidence human key points. We used these as the input for the Spatio-Temporal Graph Convolution (ST-GCN). ST-GCN is a deep learning model used for processing spatio-temporal data, which can effectively capture spatio-temporal relationships in video sequences. By using the MvP algorithm to fuse multi-view information and inputting it into the spatio-temporal graph convolution model, this study provides an effective method to improve the accuracy of human posture estimation and provides strong support for further research and application in related fields.

Keywords: multi-view, pose estimation, ST-GCN, joint fusion

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Authors: Harukuni Tokuda, Takanari Arai, Xu FengHao, Nobutaka Suzuki

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In our continuous search for anti-tumor promoting, chemopreventive active potency from natural source material, a kind of healthy tea, Gromwell seed (Coix lachryma-jobi) ext., and including compounds Monoolein and Trilinolein have been screened using the in vitro synergistic assay indicated by inhibitory effects on the induction of Epstein-Barr virus early antigen (EBV-EA) by TPA. In assay, Gromwell seed aqueous extract and hot aqueous extract exhibited the potential inhibitory effects on EBV-EA activation without strong cytotoxicity on Raji cells. In our experimental system, the inhibitory effects of both Gromwell extracts and compounds were greater than that of beta-carotene, which is known anti-tumor promoting agent and/or chemopreventive agent. These compounds were evaluated for their in vitro inhibitory effect on EBV-EA activation induced by TPA. The percentages of the inhibition of TPA-induced EBV-EA activation for these materials were 60% and 30% at concentration 100 μg. Based on the results obtained in vitro, we studied the inhibitory effect of compounds, in an in vivo two-stage carcinogenesis test of mouse skin papilloma using DMBA as an initiator and TPA as a potential promoter. The control animals showed a 100% incidence of papilloma at 20 weeks after DMBA-TPA tumor promotion, while treatment with compounds reduced the percentage of number of tumor to 60 % after 20 weeks. Results from in vitro and in vivo studies showing chemopreventive activity against TPA promoting stage and these data support the effective potency of carcinogenic stage in clinical evaluation of integrative oncology.

Keywords: gromwell seed, medicinal plant, chemoprevention, pharmaceutical medicine

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Authors: Mohammed A. Elhaj, Jamal S. Yassin

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Owing to the lack of synchronization between the solar energy availability and the heat demands in a specific application, the energy storing sub-system is necessary to maintain the continuity of thermal process. The present work is dealing with an active solar heating storing system in which an air solar collector is connected to storing unit where this energy is distributed and provided to the heated space in a controlled manner. The solar collector is a box type absorber where the air flows between a number of vanes attached between the collector absorber and the bottom plate. This design can improve the efficiency due to increasing the heat transfer area exposed to the flowing air, as well as the heat conduction through the metal vanes from the top absorbing surface. The storing unit is a packed bed type where the air is coming from the air collector and circulated through the bed in order to add/remove the energy through the charging / discharging processes, respectively. The major advantage of the packed bed storage is its high degree of thermal stratification. Numerical solution of the packed bed energy storage is considered through dividing the bed into a number of equal segments for the bed particles and solved the energy equation for each segment depending on the neighbor ones. The studied design and performance parameters in the developed simulation model including, particle size, void fraction, etc. The final results showed that the collector efficiency was fluctuated between 55%-61% in winter season (January) under the climatic conditions of Misurata in Libya. Maximum temperature of 52ºC is attained at the top of the bed while the lower one is 25ºC at the end of the charging process of hot air into the bed. This distribution can satisfy the required load for the most house heating in Libya.

Keywords: solar energy, thermal process, performance, collector, packed bed, numerical analysis, simulation

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Authors: Haider Javed Uppal, Javed Yunas Uppal

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In today's globalized world, it is necessary to develop a form of music that is able to evoke equal emotional responses among people from diverse cultural backgrounds. Indigenous cultures throughout history have developed their own music cognition, specifically in terms of the connections between music and mood. With the advancements in artificial intelligence technologies, it has become possible to analyze and categorize music features such as timbre, harmony, melody, and rhythm and relate them to the resulting mood effects experienced by listeners. This paper presents a model that utilizes a screenshot translator to convert music from different origins into waveforms, which are then analyzed using machine learning and information retrieval techniques. By connecting these waveforms with Thayer's matrix of moods, a mood classifier has been developed using fuzzy logic algorithms to determine the emotional impact of different types of music on listeners from various cultures.

Keywords: cognition, world music, artificial intelligence, Thayer’s matrix

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Authors: Girish Prayag, Wantanee Suntikul, Elizabeth Agyeiwaah

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Current research on dark tourism largely follows residents’ perspectives with limited evaluations of tourists’ experiences. Unravelling the case of a dark heritage site in Elmina, Ghana, this paper develops a theoretical model to understand the relationships among four constructs namely, motivation, tourism impacts, place attachment, and satisfaction. Based on a sample of 414 domestic tourists, PLS-SEM confirmed several relationships and inter-relationships among the four constructs. For example, motivation had a positive relationship with perceptions of positive and negative tourism impacts suggesting that the more tourists were motivated to visit the site for cultural/learning experiences, the more positive and negative tourism impacts they perceived. Implications for dark tourism and heritage site management are offered.

Keywords: dark tourism, motivation, place attachment, tourism impacts

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Authors: Mubashra Khalid, Saadia Amir

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This study initiated to explore the empirical relationship between psychological effects of economic recession on the educated youth in Pakistan. The diminishing economic resources during recession can create certain psychological consequences on the physical and cognitive aspects of the individuals. It may generate symptoms like aggression, depression, anxiety, frustration, stress and physical health related problems among the young generation. The sample of the study was consisted of 300 students belonging to six public sector universities of the Punjab province of Pakistan. Two hypotheses were advanced in this study regarding the relationship between recession and its effects on educated youth. The findings of the research represent that a significant relationship exists between decrease in employment opportunities and growing rate of aggression among educated youth and a significant association was found between economic instability and its influence on the learning abilities of the students during recession.

Keywords: psychological effects, recession, educated youth

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Authors: Ahmed Amin Mousa, Gehan Azam

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The current study presents an electronic test to measure teaching skills. This test is a part of the admission system of the Faculty of Education for Early Childhood, Cairo University. The test has been prepared to evaluate university students who apply for admission the Faculty. It measures some social and physiological skills which are important for successful teachers, such as emotional adjustment and problem solving; moreover, the extent of their love for children and their capability to interact with them. The test has been approved by 13 experts. Finally, it has been introduced to 1,100 students during the admission system of the academic year 2016/2017. The results showed that most of the applicants have an auditory learning style. In addition, 97% of them have the minimum requirement skills for teaching children.

Keywords: electronic test, performance, early childhood, skills, teacher student

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Authors: Kawinphat Lertpongmanee

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The purposes of this study were (1) investigate the English language learning motivation and the attainment of their English proficiency, (2) to find out how motivation and motivational variables of the high and low proficiency subjects are related to their English proficiency. The respondents were 80 fourth-year from Faculty of Management Sciences students in Rajabhat Suansunadha University. The instruments used for data collection were questionnaires. The statistically analyzed by using the SPSS program for frequency, percentage, arithmetic mean, standard deviation (SD), t-test, one-way analysis of variance (ANOVA), and Pearson correlation coefficient. The findings of this study are summarized as there was a significant difference in overall motivation between high and low proficiency groups of subjects at .05 (p < .05), but not in overall motivational variables. Additionally, the high proficiency group had a significantly higher level of intrinsic motivation than did the low proficiency group at .05 (p < .05).

Keywords: English language proficiency, faculty of management sciences, motivation factors, proficiency subjects

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Authors: Marc Solé, Francesc Giné, Magda Valls, Nina Bijedic

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What people say on social media has turned into a rich source of information to understand social behavior. Specifically, the growing use of Twitter social media for political communication has arisen high opportunities to know the opinion of large numbers of politically active individuals in real time and predict the global political tendencies of a specific country. It has led to an increasing body of research on this topic. The majority of these studies have been focused on polarized political contexts characterized by only two alternatives. Unlike them, this paper tackles the challenge of forecasting Spanish political trends, characterized by multiple political parties, by means of analyzing the Twitters Users political tendency. According to this, a new strategy, named Tweets Analysis Strategy (TAS), is proposed. This is based on analyzing the users tweets by means of discovering its sentiment (positive, negative or neutral) and classifying them according to the political party they support. From this individual political tendency, the global political prediction for each political party is calculated. In order to do this, two different strategies for analyzing the sentiment analysis are proposed: one is based on Positive and Negative words Matching (PNM) and the second one is based on a Neural Networks Strategy (NNS). The complete TAS strategy has been performed in a Big-Data environment. The experimental results presented in this paper reveal that NNS strategy performs much better than PNM strategy to analyze the tweet sentiment. In addition, this research analyzes the viability of the TAS strategy to obtain the global trend in a political context make up by multiple parties with an error lower than 23%.

Keywords: political tendency, prediction, sentiment analysis, Twitter

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Authors: Yingjeng James Li, Yun Jyun Ou, Chih Chi Hsu, Chiao-Chih Hu

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A fuel cell is a device that produces electric power by reacting fuel and oxidant electrochemically. There is no pollution produced from a fuel cell if hydrogen is employed as the fuel. Therefore, a fuel cell is considered as a zero emission device and is a source of green power. A membrane electrode assembly (MEA) is the key component of a fuel cell. It is, therefore, beneficial to develop MEAs with high performance. In this study, an MEA for proton exchange membrane fuel cell (PEMFC) was prepared from a 15-micron thick reinforced PEM. The active area of such MEA is 25 cm2. Carbon supported platinum (Pt/C) was employed as the catalyst for both anode and cathode. The platinum loading is 0.6 mg/cm2 based on the sum of anode and cathode. Commercially available carbon papers coated with a micro porous layer (MPL) serve as gas diffusion layers (GDLs). The original thickness of the GDL is 250 μm. It was compressed down to 163 μm when assembled into the single cell test fixture. Polarization curves were taken by using eight different test conditions. At our standard test condition (cell: 70 °C; anode: pure hydrogen, 100%RH, 1.2 stoic, ambient pressure; cathode: air, 100%RH, 3.0 stoic, ambient pressure), the cell current density is 1250 mA/cm2 at 0.6 V, and 2400 mA/cm2 at 0.4 V. At self-humidified condition and cell temperature of 55 °C, the cell current density is 1050 mA/cm2 at 0.6 V, and 2250 mA/cm2 at 0.4 V. Hydrogen crossover rate of the MEA is 0.0108 mL/min*cm2 according to linear sweep voltammetry experiments. According to the MEA’s Pt loading and the cyclic voltammetry experiments, the Pt electrochemical surface area is 60 m2/g. The ohmic part of the impedance spectroscopy results shows that the membrane resistance is about 60 mΩ*cm2 when the MEA is operated at 0.6 V.

Keywords: fuel cell, membrane electrode assembly, proton exchange membrane, reinforced

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Authors: Shukran M. Dadayev

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To author's best knowledge, in this paper, the Basic Properties and Research methods of a Fundamental Particle is studied for the first time. That's to say, Fundamental Particle has not been discovered in the Nature yet. Because Fundamental Particle consists of specific Physical, Geometrical and Internal bases. Geometrical and Internal characteristics that are considered significant for the elementary and fundamental particles aren’t basic properties, characteristics or criteria of a Fundamental Particle. Of course, completely new Physical and Visual experimental methods of Quantum mechanics and Behavioral-Physical investigations of Particles are needed to study and discover the Fundamental Particle. These are new Physical, Visual and Behavioral-Physical experimental methods for describing and discovering the Fundamental Particle in the Nature and Microworld. Fundamental Particle consists of the same Energy-Mass-Motion system and a symmetry of Energy-Mass-Motion. Fundamental Particle supplies each of the elementary particles with the same Energy-Mass-Motion system at the same time and regulates each of the particles. Fundamental Particle gives Energy, Mass and Motion to each particles at the same time, each of the Particles consists of acquired Energy-Mass-Motion system and symmetry. Energy, Mass, Motion given by the Fundamental Particle to the particles are Symmetrical Equivalent and they remain in their primary shapes in all cases. Fundamental Particle gives Energy-Mass-Motion system and symmetry consisting of different measures and functions to each of the particles. The Motion given by the Fundamental Particle to the particles is Gravitation, Gravitational Interaction not only gives Motion, but also cause Motion by attracting. All Substances, Fields and Cosmic objects consist of Energy-Mass-Motion. The Field also includes specific Mass. They are always Energetic, Massive and Active. Fundamental Particle establishes the bases of the Nature. Supplement and Regulating of all the particles existing in the Nature belongs to Fundamental Particle.

Keywords: basic properties of a fundamental particle, behavioral-physical and visual methods, energy-mass-motion system and symmetrical equivalence, fundamental particle

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Authors: Ginés Hernández-Cánovas, Mª Camino Ramón-Llorens, Johanna Koëter-Kant

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This paper uses a survey data-set of 837 Spanish SMEs to analyze the association between borrower discouragement and prior firm´s strategic decisions, while controlling for firm and owner characteristics. While existing literature has neglected factors limiting the demand for resources by an overreliance on arguments which attempt to explain the existence of discouraged borrowers solely in terms of lack of access to supply of credit. The objective of this paper is to show that factors limiting the demand for resources and, therefore, reducing the availability of funds, can be traced back to the firm manager´s decision. Our hypothesis is that managers that undertake strategic decisions seeking growth or improvement in their business performance participate more in the banking market than those showing contentment with their current business situation. Our results shows that SMEs that undertake an active role in research and development activities and that achieve improvements in the operating performance of their business are less likely to be discouraged from applying for a loan. Who needs credit and who applies for credit is important for firms, prospective lenders and policymakers interested in the financial health of these firms. Credit constrained firms are less likely to invest in R&D and to introduce new products, possibly harming long-term economic growth. Knowing how important borrower discouragement is in Europe, is important for judging the priority which should be attached to government policies aimed at reducing its effects. For example, policy makers could encourage the transparency about credit eligibility and conditions in order to reduce discouragement.

Keywords: discouragement, financial constraints, SMEs financing

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Authors: Guilherme Ribeiro, Alexandre Oliveira, Antonio Ferreira, Shyam Visweswaran, Gregory Cooper

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Patient-specific models are instance-based learning algorithms that take advantage of the particular features of the patient case at hand to predict an outcome. We introduce two patient-specific algorithms based on decision tree paradigm that use AUC as a metric to select an attribute. We apply the patient specific algorithms to predict outcomes in several datasets, including medical datasets. Compared to the patient-specific decision path (PSDP) entropy-based and CART methods, the AUC-based patient-specific decision path models performed equivalently on area under the ROC curve (AUC). Our results provide support for patient-specific methods being a promising approach for making clinical predictions.

Keywords: approach instance-based, area under the ROC curve, patient-specific decision path, clinical predictions

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Authors: Krzysztof Pomorski

Abstract:

In the given work we present universal mathematical framework for modeling of cattle farm system that can set and validate various hypothesis that can be tested against experimental data. The presented work is preliminary but it is expected to be valid tool for future deeper analysis that can result in new class of prediction methods allowing early detection of cow dieseaes as well as cow performance. Therefore the presented work shall have its meaning in agriculture models and in machine learning as well. It also opens the possibilities for incorporation of certain class of biological models necessary in modeling of cow behavior and farm performance that might include the impact of environment on the farm system. Particular attention is paid to the model of coupled oscillators that it the basic building hypothesis that can construct the model showing certain periodic or quasiperiodic behavior.

Keywords: coupled ordinary differential equations, cattle farm system, numerical methods, stochastic differential equations

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Authors: Kunal Shah, Swati Patel

Abstract:

Many real world problems involve data which can be considered as multi-label data streams. Efficient methods exist for multi-label classification in non streaming scenarios. However, learning in evolving streaming scenarios is more challenging, as the learners must be able to adapt to change using limited time and memory. Classification is used to predict class of unseen instance as accurate as possible. Multi label classification is a variant of single label classification where set of labels associated with single instance. Multi label classification is used by modern applications, such as text classification, functional genomics, image classification, music categorization etc. This paper introduces the task of multi-label classification, methods for multi-label classification and evolution measure for multi-label classification. Also, comparative analysis of multi label classification methods on the basis of theoretical study, and then on the basis of simulation was done on various data sets.

Keywords: binary relevance, concept drift, data stream mining, MLSC, multiple window with buffer

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Authors: D. S. Denchuk, O. M. Zamyatina, M. G. Minin, M. A. Soloviev, K. V. Bogrova

Abstract:

The article considers invention activity in Russia and worldwide, its modern state, and the impact of innovative engineering activity on the national economy of the considered countries. It also analyses the historical premises of modern engineer-ing invention. The authors explore the development of engineering invention at an engineer-ing university, the creation of particular environment for scientific and technical creativity of students on the example of Elite engineering education program at Tomsk Polytechnic University, Russia. It is revealed that for the successful de-velopment of engineering invention in a higher education institution it is neces-sary to apply a learning model that develops the creative potential of a student, which is, in its turn, inseparably connected with the ability to generate new ideas in engineering. Such academic environment can become a basis for revealing stu-dents' creativity.

Keywords: engineering invention, scientific and technical creativity, students, project-based approach

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Authors: Carla Nardelli, Jérome Holtzmann, Céline Baeyens, Catherine Bortolon

Abstract:

Background. Emotion regulation (ER) is a process associated with difficulties in mental health. Given its transdiagnostic features, its improvement could facilitate the recovery of various psychological issues. A limit of current studies is the lack of knowledge regarding whether available interventionsimprove ER flexibility (i.e., the ability to implement ER strategies in line with contextual demands), even though this capacity has been associated with better mental health and well-being. Therefore, the aim of the study is to test the efficacy of a 9-weeks ER group program (the Affect Regulation Training-ART), using the most appropriate measures (i.e., experience sampling method) in a student population. Plus, the goal of the study is to explore the potential mediative role of ER flexibility on mental health improvement. Method. This Randomized Controlled Trial will comparethe ER program group to an active control group (a relaxation program) in 100 participants. To test the mediative role of ER flexibility on mental health, daily measures will be used before, during, and after the interventions to evaluate the extent to which participants are flexible in their ER. Expected outcomes. Using multilevel analyses, we expect an improvement in anxious-depressive symptomatology for both groups. However, we expect the ART group to improve specifically on ER flexibility ability and the last to be a mediative variable on mental health. Conclusion. This study will enhance knowledge on interventions for students and the impact of interventions on ER flexibility. Also, this research will improve knowledge on ecological measures for assessing the effect of interventions. Overall, this project represents new opportunities to improve ER skills to improve mental health in undergraduate students.

Keywords: emotion regulation flexibility, experience sampling method, psychological intervention, emotion regulation skills

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Authors: Ananya Ananya, Karthik Rao

Abstract:

Accurate segmentation of knee cartilage in 3-D magnetic resonance (MR) images for quantitative assessment of volume is crucial for studying and diagnosing osteoarthritis (OA) of the knee, one of the major causes of disability in elderly people. Radiologists generally perform this task in slice-by-slice manner taking 15-20 minutes per 3D image, and lead to high inter and intra observer variability. Hence automatic methods for knee cartilage segmentation are desirable and are an active field of research. This paper presents design and experimental evaluation of 2D convolutional neural networks based fully automated methods for knee cartilage segmentation in 3D MRI. The architectures are validated based on 40 test images and 60 training images from SKI10 dataset. The proposed methods segment 2D slices one by one, which are then combined to give segmentation for whole 3D images. Proposed methods are modified versions of U-net and dilated convolutions, consisting of a single step that segments the given image to 5 labels: background, femoral cartilage, tibia cartilage, femoral bone and tibia bone; cartilages being the primary components of interest. U-net consists of a contracting path and an expanding path, to capture context and localization respectively. Dilated convolutions lead to an exponential expansion of receptive field with only a linear increase in a number of parameters. A combination of modified U-net and dilated convolutions has also been explored. These architectures segment one 3D image in 8 – 10 seconds giving average volumetric Dice Score Coefficients (DSC) of 0.950 - 0.962 for femoral cartilage and 0.951 - 0.966 for tibia cartilage, reference being the manual segmentation.

Keywords: convolutional neural networks, dilated convolutions, 3 dimensional, fully automated, knee cartilage, MRI, segmentation, U-net

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Authors: Jovanca Smith, Derek Gay

Abstract:

All universities possess a standard by which students are assessed and administered into their programs. This paper considers the effect of the educational history of students, as measured by specific subject grades in Caribbean examinations, on overall performance in introductory engineering math and mechanics courses. Results reflect a correlation between the highest grade in the Caribbean examinations with a higher probability of successful advancement in the university courses. Alternatively, lower entrance grades are commensurate with underperformance in the university courses. Results also demonstrate that students matriculating with the Caribbean examinations will not necessarily possess a significant advantage over students entering through an alternative route, and while previous educational background of students is a significant indicator of tentative performance in the University level math and mechanics courses, it is not the sole factor.

Keywords: bimodal distribution, differential learning, engineering education, entrance qualification

Procedia PDF Downloads 357