Search results for: balance training

Authors: Qinghua Xing, Xinyi Tao, Haisheng Wang, Baisuo Zhao

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The first true anaerobic, halophilic alkali thermophile, Natranaerobius thermophilus DSM 18059T, serves as a valuable model for studying cellular adaptations to saline, alkaline and thermal extremes. To uncover the adaptive strategies employed by N. thermophilus in coping with these challenges, we conducted a comprehensive iTRAQ-based quantitative proteomic analysis under different conditions of salinity (3.5 M vs. 2.5 M Na+), pH (pH 9.6 vs. pH 8.6), and temperature (52°C vs. 42°C). The increased intracellular accumulation of glycine betaine, through both synthesis and transport, plays a critical role in N. thermophilus' adaptation to these combined stresses. Under all three stress conditions, the up-regulation of Trk family proteins responsible for K+ transport is observed. Intracellular K+ concentration rises in response to salt and pH levels. Multiple types of Na+/H+ antiporter (NhaC family, Mrp family and CPA family) and a diverse range of FOF1-ATP synthase are identified as vital components for maintaining ionic balance under different stress conditions. Importantly, proteins involved in amino acid metabolism, carbohydrate metabolism, ABC transporters, signaling and chemotaxis, as well as biological macromolecule repair and protection, exhibited significant up-regulation in response to these extreme conditions. These metabolic pathways emerge as critical factors in N. thermophilus' adaptation mechanisms under extreme environmental stress. To validate the proteomic data, ddPCR analysis confirmed changes in mRNA expression, thereby corroborating the up-regulation and down-regulation patterns of 19 co-up-regulated and 36 key proteins under saline, alkaline and thermal stresses. This research enriches our understanding of the complex regulatory systems that enable polyextremophiles to survive in combined extreme conditions.

Keywords: polyextremophiles, natranaerobius thermophilus, saline- alkaline- thermal stresses, combined extremes

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Authors: Takeo Shibata, Arihito Endo, Akemi Kunimatsu, Chika Hiraga, Yoko Shimizu

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Introduction: Yuzawa Town, located in the Niigata prefecture of Japan, is famous for its hot springs. A health promotion program, Yuzawa family health plan, was initiated in 2002. It has been held for fifteen years. We evaluated the profiles of brushing teeth in adults. Subjects: 368 questionnaires were corrected from people who live in Yuzawa town. The range of age was between nineteen and sixty-four years old. Methods: Mann-Whitney’s U test and Kruskal-Wallis test were used to evaluate significant differences in frequencies of brushing teeth per a day. Chi-square test and the adjusted residuals were used to evaluate when they brush their teeth. Results: Women showed greater frequencies of brushing teeth per a day than men. No difference was shown by age. Construction workers showed fewer frequencies of brushing teeth. Specialized technicians, clerical workers, and housewives showed greater frequencies. People who know Yuzawa family health plan, take a regular life, or take a breakfast every day showed greater frequencies. People who think not healthy, don’t care a balance of foods, don’t take yearly health check-up, or smoke showed fewer frequencies. After breakfast, women and specialized technicians showed greater frequencies, and construction workers and self-employed workers showed fewer frequencies. After lunch, clerical workers and specialized technicians showed greater frequencies. There was no significant difference at after waking up, after dinner, and before going to bed. Construction workers showed a lower rate of having a marital partner and having information of health. Conclusion: Gender and occupational differences were shown in frequencies of brushing teeth per a day. A promotion of teeth brushing for male, especially construction workers and self-employed workers, is needed.

Keywords: health promotion, Yuzawa family health plan, brushing teeth, occupational difference

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Authors: Sahana Selladurai, Christine DeWolf

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Lung surfactant comprises a lipid-protein film that coats the alveolar surface and serves to prevent alveolar collapse upon repeated breathing cycles. Exposure of lung surfactant to high concentrations of airborne pollutants, for example tropospheric ozone in smog, can chemically modify the lipid and protein components. These chemical changes can impact the film functionality by decreasing the film’s collapse pressure (minimum surface tension attainable), altering it is mechanical and flow properties and modifying lipid reservoir formation essential for re-spreading of the film during the inhalation process. In this study, we use Langmuir monolayers spread at the air-water interface as model membranes where the compression and expansion of the film mimics the breathing cycle. The impact of ozone exposure on model lung surfactant films is measured using a Langmuir film balance, Brewster angle microscopy and a pendant drop tensiometer as a function of film and sub-phase composition. The oxidized films are analyzed using mass spectrometry where lipid and protein oxidation products are observed. Oxidation is shown to reduce surface activity, alter line tension (and film morphology) and in some cases visibly reduce the viscoelastic properties of the film when compared to controls. These reductions in functionality of the films are highly dependent on film and sub-phase composition, where for example, the effect of oxidation is more pronounced when using a physiologically relevant buffer as opposed to water as the sub-phase. These findings can lead to a better understanding on the impact of continuous exposure to high levels of ozone on the mechanical process of breathing, as well as understanding the roles of certain lung surfactant components in this process.

Keywords: lung surfactant, oxidation, ozone, viscoelasticity

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Authors: Heba Elbibas, Esra Gnijeewa, Zedan Hatush

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This paper presents research on occupational safety in construction projects, where the importance of safety management in projects was studied, including the preparation of a safety plan and program for each project and the identification of the responsibilities of each party to the contract. The research consists of two parts: 1-Field visits: which were field visits to three construction projects, including building projects, road projects, and tower installation. The safety level of these projects was evaluated through a checklist that includes the most important safety elements in terms of the application of these items in the projects. 2-Preparation of a questionnaire: which included supervisors and engineers and aimed to determine the level of awareness and commitment of different project categories to safety standards. The results showed the following: i) There is a moderate occupational safety policy. ii) The preparation and storage of maintenance reports are not fully complied with. iii) There is a moderate level of training on occupational safety for project workers. iv) The company does not impose penalties on safety violators permanently. v) There is a moderate policy for equipment and machinery safety. vi) Self-injuries occur due to (fatigue, lack of attention, deliberate error, and emotional factors), with a rate of 82.4%.

Keywords: management, safety, occupational safety, classification

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Authors: Carmen Axisa, Louise Nash, Patrick Kelly, Simon Willcock

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Introduction: Doctors experience high levels of burnout, stress and psychiatric morbidity. This can affect the health of the doctor and impact patient care. Study Aims: To evaluate the effectiveness of a workshop intervention to promote wellbeing for Australian Physician Trainees. Methods: A workshop was developed in consultation with specialist clinicians to promote health and wellbeing for physician trainees. The workshop objectives were to improve participant understanding about factors affecting their health and wellbeing, to outline strategies on how to improve health and wellbeing and to encourage participants to apply these strategies in their own lives. There was a focus on building resilience and developing long term healthy behaviours as part of the physician trainee daily lifestyle. Trainees had the opportunity to learn practical strategies for stress management, gain insight into their behaviour and take steps to improve their health and wellbeing. The workshop also identified resources and support systems available to trainees. The workshop duration was four and a half hours including a thirty- minute meal break where a catered meal was provided for the trainees. Workshop evaluations were conducted at the end of the workshop. Sixty-seven physician trainees from Adult Medicine and Paediatric training programs in Sydney Australia were randomised into intervention and control groups. The intervention group attended a workshop facilitated by specialist clinicians and the control group did not. Baseline and post intervention measurements were taken for both groups to evaluate the impact and effectiveness of the workshop. Forty-six participants completed all three measurements (69%). Demographic, personal and self-reported data regarding work/life patterns was collected. Outcome measures include Depression Anxiety Stress Scale (DASS), Professional Quality of Life Scale (ProQOL) and Alcohol Use Disorders Identification Test (AUDIT). Results: The workshop was well received by the physician trainees and workshop evaluations showed that the majority of trainees strongly agree or agree that the training was relevant to their needs (96%) and met their expectations (92%). All trainees strongly agree or agree that they would recommend the workshop to their medical colleagues. In comparison to the control group we observed a reduction in alcohol use, depression and burnout but an increase in stress, anxiety and secondary traumatic stress in the intervention group, at the primary endpoint measured at 6 months. However, none of these differences reached statistical significance (p > 0.05). Discussion: Although the study did not reach statistical significance, the workshop may be beneficial to physician trainees. Trainees had the opportunity to share ideas, gain insight into their own behaviour, learn practical strategies for stress management and discuss approach to work, life and self-care. The workshop discussions enabled trainees to share their experiences in a supported environment where they learned that other trainees experienced stress and burnout and they were not alone in needing to acquire successful coping mechanisms and stress management strategies. Conclusion: These findings suggest that physician trainees are a vulnerable group who may benefit from initiatives that promote wellbeing and from a more supportive work environment.

Keywords: doctors' health, physician burnout, physician resilience, wellbeing workshop

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Authors: Abdulla Rahil, Rupert Gammon, Neil Brown

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The rapid growth of renewable energy sources and their integration into the grid have been motivated by the depletion of fossil fuels and environmental issues. Unfortunately, the grid is unable to cope with the predicted growth of renewable energy which would lead to its instability. To solve this problem, energy storage devices could be used. Electrolytic hydrogen production from an electrolyser is considered a promising option since it is a clean energy source (zero emissions). Choosing flexible operation of an electrolyser (producing hydrogen during the off-peak electricity period and stopping at other times) could bring about many benefits like reducing the cost of hydrogen and helping to balance the electric systems. This paper investigates the price of hydrogen during flexible operation compared with continuous operation, while serving the customer (hydrogen filling station) without interruption. The optimization algorithm is applied to investigate the hydrogen station in both cases (flexible and continuous operation). Three different scenarios are tested to see whether the off-peak electricity price could enhance the reduction of the hydrogen cost. These scenarios are: Standard tariff (1 tier system) during the day (assumed 12 p/kWh) while still satisfying the demand for hydrogen; using off-peak electricity at a lower price (assumed 5 p/kWh) and shutting down the electrolyser at other times; using lower price electricity at off-peak times and high price electricity at other times. This study looks at Derna city, which is located on the coast of the Mediterranean Sea (32° 46′ 0 N, 22° 38′ 0 E) with a high potential for wind resource. Hourly wind speed data which were collected over 24½ years from 1990 to 2014 were in addition to data on hourly radiation and hourly electricity demand collected over a one-year period, together with the petrol station data.

Keywords: hydrogen filling station off-peak electricity, renewable energy, off-peak electricity, electrolytic hydrogen

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Authors: Nur Aisyah Jalalludin, Arwindra Rizqiawan, Goro Fujita

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In this study, we aim to demonstrate a microgrid system experimental simulation for an easy understanding of a large-scale microgrid system. This model is required for industrial training and learning environments. However, in order to create an exact representation of a microgrid system, the laboratory-scale system must fulfill the requirements of a grid-connected inverter, in which power values are assigned to the system to cope with the intermittent output from renewable energy sources. Aside from that, during changes in load capacity, the grid-connected system must be able to supply power from the utility grid side and microgrid side in a balanced manner. Therefore, droop control is installed in the inverter’s control board to maintain equal power sharing in both sides. This power control in a stand-alone condition and droop control in a grid-connected condition must be implemented in order to maintain a stabilized system. Based on the experimental results, power control and droop control can both be applied in the system by comparing the experimental and reference values.

Keywords: droop control, droop characteristic, grid-connected inverter, microgrid, power control

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Authors: J. Balaraju, M. Govinda Raj, C. S. N. Murthy

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Every industry is constantly looking for enhancement of its day to day production and productivity. This can be possible only by maintaining the men and machinery at its adequate level. Prediction of performance characteristics plays an important role in performance evaluation of the equipment. Analytical and statistical approaches will take a bit more time to solve complex problems such as performance estimations as compared with software-based approaches. Keeping this in view the present study deals with an Artificial Neural Network (ANN) modelling of a Load-Haul-Dump (LHD) machine to predict the performance characteristics such as reliability, availability and preventive maintenance (PM). A feed-forward-back-propagation ANN technique has been used to model the Levenberg-Marquardt (LM) training algorithm. The performance characteristics were computed using Isograph Reliability Workbench 13.0 software. These computed values were validated using predicted output responses of ANN models. Further, recommendations are given to the industry based on the performed analysis for improvement of equipment performance.

Keywords: load-haul-dump, LHD, artificial neural network, ANN, performance, reliability, availability, preventive maintenance

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Authors: Muhammad Umair Ahmed, Aftab Shoukat

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Today the global economy has become one of the key strategies in dealing with environmental issues. To allow for a round economy, organizations have begun to work to improve their sustainability management. The contribution of green resource management to the transformation of the global economy has not been investigated. The purpose of the study was to evaluate the effects of green labor management on the global economy, environmental and economic performance, and the organisation's environmental dignity. We strongly evaluate the different roles of the various processes of green personnel management (i.e., green recruitment, training, and engagement green, as well as green performance management and reward) in organizational operations. We are also investigating the leadership role of CEO Ethical. Our outcome will have a positive impact on the performance of the organization. Green Human Resource Management contributes to the evolution of a roundabout economy without the influence of different external factors such as market demand and commitment. Finally, the results of our research will provide a few aspects for future research, both academic and human.

Keywords: sustainability, green human resource management, circular economy, human capital

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Authors: Faruk Inaltekin, Imran Gurakan

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This paper will aim to discuss the importance of value-added services provided by Science and Technology Parks for entrepreneurship development in Turkey. Entrepreneurship is vital subject for all countries. It has not only fostered economic development but also promoted innovation at local and international levels. To foster high tech entrepreneurship ecosystem, Technopark (Science and Technology Park/STP) concept was initiated with the establishment of Silicon Valley in the 1950s. The success and rise of Silicon Valley led to the spread of technopark activities. Developed economies have been setting up projects to plan and build STPs since the 1960s and 1970s. To promote the establishment of STPs, necessary legislations were made by Ministry of Science, Industry, and Technology in 2001, Technology Development Zones Law (No. 4691) and it has been revised in 2016 to provide more supports. STPs’ basic aim is to provide customers high-quality office spaces with various 'value added services' such as business development, network connections, cooperation programs, investor/customers meetings and internationalization services. For this aim, STPs should help startups deal with difficulties in the early stages and to support mature companies’ export activities in the foreign market. STPs should support the production, commercialization and more significantly internationalization of technology-intensive business and foster growth of companies. Nowadays within this value-added services, internationalization is very popular subject in the world. Most of STPs design clusters or accelerator programs in order to support their companies in the foreign market penetration. If startups are not ready for international competition, STPs should help them to get ready for foreign market with training and mentoring sessions. These training and mentoring sessions should take a goal based approach to working with companies. Each company has different needs and goals. Therefore the definition of ‘success' varies for each company. For this reason, it is very important to create customized value added services to meet the needs of startups. After local supports, STPs should also be able to support their startups in foreign market. Organizing well defined international accelerator program plays an important role in this mission. Turkey is strategically placed between key markets in Europe, Russia, Central Asia and the Middle East. Its population is young and well educated. So both government agencies and the private sectors endeavor to foster and encourage entrepreneurship ecosystem with many supports. In sum, the task of technoparks with these and similar value added services is very important for developing entrepreneurship ecosystem. The priorities of all value added services are to identify the commercialization and growth obstacles faced by entrepreneurs and get rid of them with the one-to-one customized services. Also, in order to have a healthy startup ecosystem and create sustainable entrepreneurship, stakeholders (technoparks, incubators, accelerators, investors, universities, governmental organizations etc.) should fulfill their roles and/or duties and collaborate with each other. STPs play an important role as bridge for these stakeholders & entrepreneurs. STPs always should benchmark and renew services offered to how to help the start-ups to survive, develop their business and benefit from these stakeholders.

Keywords: accelerator, cluster, entrepreneurship, startup, technopark, value added services

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Authors: Go Woon Kwak, Siyoung Jun, Soyun Maeng, Haeyoung Lee

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Entry is an education platform used in South Korea, created to help students learn to program, in which they can learn to code while playing. Using the online version of the entry, teachers can easily assign programming homework to the student and the students can make programs simply by linking programming blocks. However, the programs may be made by others, so that the authors of the programs should be identified. In this paper, as the first step toward author identification of entry programs, we present an artificial neural network based classification approach to identify genders of authors of a program written in an entry. A neural network has been trained from labeled training data that we have collected. Our result in progress, although preliminary, shows that the proposed approach could be feasible to be applied to the online version of entry for gender identification of authors. As future work, we will first use a machine learning technique for age identification of entry programs, which would be the second step toward the author identification.

Keywords: artificial intelligence, author identification, deep neural network, gender identification, machine learning

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Authors: Adrián P. Gómez Mañas

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Autonomous vehicles have already transformed urban policies and cities. This is the main assumption of our research, which aims to understand how the representations of the possible arrival of autonomous vehicles already transform priorities or actions in transport and more largely, urban policies. This research is done within the framework of a Ph.D. doctorate directed by Professor Xavier Desjardins at the Sorbonne University of Paris. Our hypotheses are: (i) the perspectives, representations, and imaginaries on autonomous vehicles already affect the stakeholders of urban policies; (ii) the discourses on the opportunities or threats of autonomous vehicles reflect the current strategies of the stakeholders. Each stakeholder tries to integrate a discourse on autonomous vehicles that allows them to change as little as possible their current tactics and strategies. The objective is to eventually make a comparison between three different cases: Paris, United Arab Emirates, and Bogota. We chose those territories because their contexts are very different, but they all have important interests in mobility and innovation, and they all have started to reflect on the subject of self-driving mobility. The main methodology used is to interview actors of the metropolitan area (local officials, leading urban and transport planners, influent experts, and private companies). This work is supplemented with conferences, official documents, press articles, and websites. The objective is to understand: 1) What they know about autonomous vehicles and where does their knowledge come from; 2) What they expect from autonomous vehicles; 3) How their ideas about autonomous vehicles are transforming their action and strategy in managing daily mobility, investing in transport, designing public spaces and urban planning. We are going to present the research and some preliminary results; we will show that autonomous vehicles are often viewed by public authorities as a lever to reach something else. We will also present that speeches are very influenced by local context (political, geographical, economic, etc.), creating an interesting balance between global and local influences. We will analyze the differences and similarities between the three cases and will try to understand which are the causes.

Keywords: autonomous vehicles, self-driving mobility, urban planning, urban mobility, transport, public policies

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Authors: Ezayra Dubria, Leonora Yambao

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Mother Tongue–Based Multilingual Education (MTB-MLE) is a salient part of the recent reform in the country’s Education system which is the implementation of the K to 12 Basic Education Program. Its importance is highlighted by the passing of Republic Act 10523, otherwise known as the ‘Enhanced Basic Education Act of 2013’. However, teachers, especially new teachers encounter problems in using mother tongue as medium of instruction. Fortunately, teachers are able to create strategies which address these problems. Specifically, this paper gathered the viewpoints of teachers in using mother tongue and analyzed the different problems and strategies used. The problems encountered by teachers are lack of instructional materials written in mother tongue, especially books, lack of vocabulary, lack of teacher training, and influences of social media to learners. The strategies which address these problems are translation of literary pieces and other instructional materials, vocabulary enrichment through the use of word-of-the-day and picture-word association, remedial class, storytelling, differentiated instruction, explicit teaching, individual and group activities, and utilization of multilingual teaching.

Keywords: mother tongue-based instruction, multilingualism, problems, strategies

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Authors: Yalong Jiang, Zheru Chi

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In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.

Keywords: CNN, convolutional neural network, capsule network, capacity optimization, character recognition, data augmentation, semantic segmentation

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Authors: Mubarak Suliman, Mohamed Hassan

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Detection of downed conductors occurring with high fault resistance (reaching kilo-ohms) has always been a challenge, especially in countries like Saudi Arabia, on which earth resistivity is very high in general (reaching more than 1000 Ω-meter). The new approaches for the detection of resistive and high impedance faults are based on the analysis of the fault current waveform. These methods are still under research and development, and they are currently lacking security and dependability. The other approach is communication-based solutions which depends on voltage measurement at the end of overhead line branches and communicate the measured signals to substation feeder relay or a central control center. However, such a detection method is costly and depends on the availability of communication medium and infrastructure. The main objective of this research is to utilize the available standard protection schemes to increase the probability of detection of downed conductors occurring with a low magnitude of fault currents and at the same time avoiding unwanted tripping in healthy conditions and feeders. By specifying the operating region of the faulty feeder, use of tripping curve for discrimination between faulty and healthy feeders, and with proper selection of core balance current transformer (CBCT) and voltage transformers with fewer measurement errors, it is possible to set the pick-up of sensitive earth fault current to minimum values of few amps (i.e., Pick-up Settings = 3 A or 4 A, …) for the detection of earth faults with fault resistance more than (1 - 2 kΩ) for 13.8kV overhead network and more than (3-4) kΩ fault resistance in 33kV overhead network. By implementation of the outcomes of this study, the probability of detection of downed conductors is increased by the utilization of existing schemes (i.e., Directional Sensitive Earth Fault Protection).

Keywords: sensitive earth fault, zero sequence current, grounded system, resistive fault detection, healthy feeder

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Authors: Bahia Braktia, Belkacem Braktia

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Collaborative writing is now an established pedagogical technique in higher education. Since most educators do not have training in the design, execution, and evaluation of writing assignments, implementing such tasks has proven difficult. This paper firstly proposes a framework for a collaborative writing assignment based on a literature study and adopting a writing-to-learn concept. It then describes the research undertaken and shows how this framework is implemented in an economics course, at an Algerian university, with undergraduate students. Finally, using a mixed methods design, it examines the students’ perceptions of what they have learned about collaborative writing. Preliminary results show that group assignments will always be a challenge, but with careful planning and structure, a collaborative writing assignment can be used effectively to help students improve their analytical and critical thinking abilities, research and group work skills, as well as writing proficiency. Students have a positive experience of working in a team and identified a wide variety of different team skills that they have learned through the process.

Keywords: collaborative writing, research assignment, students’ perception, survey

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Authors: Azadeh Bashiri

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Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary.

Keywords: asthma, data mining, Artificial Neural Network, intelligent system

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Authors: Chung Yan Natalia Yeung, Man Kit Indy Ho, Kin Yu Stan Chan, Ho Pui Kipper Lam, Man Wah Genie Tong, Tze Chung Jim Luk

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Excessive foot pronation is a well-known risk factor of knee and foot injuries such as patellofemoral pain, patellar and Achilles tendinopathy, and plantar fasciitis. Low-Dye taping (LDT) application is not uncommon for basketball players to control excessive foot pronation for pain control and injury prevention. The primary potential benefits of using LDT include providing additional supports to medial longitudinal arch and restricting the excessive midfoot and subtalar motion in weight-bearing activities such as running and landing. Meanwhile, restrictions provided by the rigid tape may also potentially limit functional joint movements and sports performance. Coaches and athletes need to weigh the potential benefits and harmful effects before making a decision if applying LDT technique is worthwhile or not. However, the influence of using LDT on basketball-related performance such as explosive and reactive strength is not well understood. Therefore, the purpose of this study was to investigate the change of drop jump (DJ) and countermovement jump (CMJ) performance before and after LDT application for collegiate male basketball players. In this within-subject crossover study, 12 healthy male basketball players (age: 21.7 ± 2.5 years) with at least 3-year regular basketball training experience were recruited. Navicular drop (ND) test was adopted as the screening and only those with excessive pronation (ND ≥ 10mm) were included. Participants with recent lower limb injury history were excluded. Recruited subjects were required to perform both ND, DJ (on a platform of 40cm height) and CMJ (without arms swing) tests in series during taped and non-taped conditions in the counterbalanced order. Reactive strength index (RSI) was calculated by using the flight time divided by the ground contact time measured. For DJ and CMJ tests, the best of three trials was used for analysis. The difference between taped and non-taped conditions for each test was further calculated through standardized effect ± 90% confidence intervals (CI) with clinical magnitude-based inference (MBI). Paired samples T-test showed significant decrease in ND (-4.68 ± 1.44mm; 95% CI: -3.77, -5.60; p < 0.05) while MBI demonstrated most likely beneficial and large effect (standardize effect: -1.59 ± 0.27) in LDT condition. For DJ test, significant increase in both flight time (25.25 ± 29.96ms; 95% CI: 6.22, 44.28; p < 0.05) and RSI (0.22 ± 0.22; 95% CI: 0.08, 0.36; p < 0.05) were observed. In taped condition, MBI showed very likely beneficial and moderate effect (standardized effect: 0.77 ± 0.49) in flight time, possibly beneficial and small effect (standardized effect: -0.26 ± 0.29) in ground contact time and very likely beneficial and moderate effect (standardized effect: 0.77 ± 0.42) in RSI. No significant difference in CMJ was observed (95% CI: -2.73, 2.08; p > 0.05). For basketball players with pes planus, applying LDT could substantially support the foot by elevating the navicular height and potentially provide acute beneficial effects in reactive strength performance. Meanwhile, no significant harmful effect on CMJ was observed. Basketball players may consider applying LDT before the game or training to enhance the reactive strength performance. However since the observed effects in this study could not generalize to other players without excessive foot pronation, further studies on players with normal foot arch or navicular height are recommended.

Keywords: flight time, pes planus, pronated foot, reactive strength index

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Authors: Ali Obaid Alyami

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In Saudi Arabia, the pandemic of Coronavirus (COVID-19) has been affecting administrative contracts in many different ways. Lots of planned projects were stopped temporarily or implemented partially. Many contractors have suffered financial struggles and the absence of manpower. These administrative contracts are governed by Government Tenders and Procurement Law (GTPL) which was issued by a royal decree in 2019. This law addresses some challenges that could be stumbling blocks in the way of implementing a contract. One significant challenge is emergency circumstances that occur during the implementation of an administrative contract. The law provides some solutions for this disruption, but these solutions may not compensate for the whole damages that contractors suffer. This study will use the doctrinal methodology to analyze the rules of law and their application to the research problem. Most importantly, the issue that arises in this research is the possibility of governmental entities’ consideration, in administrative contracts, of the pandemic Coronavirus (COVID-19) as an emergency circumstance. This study points out the conditions for applying the theory of emergency circumstances on administrative contracts in addition to the definition of the theory and analyzing its elements. The other significant question is the limits on governmental entities to make a change in an administrative contract to achieve contractual rebalancing. GPTL and its implementing regulation set the conditions and limits of contractual rebalancing. However, this study finds that although GTPL provides rules for contractual rebalancing, there are some other mechanisms that contractors may take to fully compensate for the damages. For instance, when the loss cannot be minimized by GTPL, contractors might file lawsuits before the administrative judiciary. The study concludes that GTPL is a very comprehensive law system that stipulates specific rules for contractual rebalance and treats the emergency circumstances that obstruct the performance of administrative contracts.

Keywords: administrative contracts, emergency circumstances, balance of contract, administrative judiciary, government tenders, procurement law

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Authors: J. Byimana, I. A. Muhire, J. E. Nzabahimana, A. Nyombayire

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Introduction: A successful cardiopulmonary resuscitation during a sudden cardiac arrest can be delayed by different components including new hospital setting, lack of adequate training, lack of pre-established resuscitation team and ineffective communication and lead to an unexpected outcome which is death. The main objective of the study was to assess the readiness of resuscitation teams during cardiac arrest and the organizational approaches that would best support their functioning in a new hospital facility, and to detect any factor that may have contributed to responses. This study analyses the readiness of Resuscitation Team (RT) during cardiac arrest. —Material and methods: A prospective Analytic design was carried out at a newly established United Nations level 2 hospital facility, on four RTM (resuscitation team member). A semi structured questionnaire was used to collect data. —Results: This study highlights indicate that the response time during cardiac arrest simulation meet both American heart association (AHA) and European resuscitation council guidelines. The study offers useful evidence about the impact of a new facility on RTM performance and provides an exposure of staff to emergency events within the Work setting.

Keywords: cardiac arrest, code blue, simulation, resuscitation team member

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Authors: Majno Ajbani

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Difficulties in teaching and learning English pronunciation in Sindh province, Pakistan Abstract Sindhi language is widely spoken in Sindh province, and it is one of the difficult languages of the world. Sindhi language has fifty-two alphabets which have caused a serious issue in learning and teaching of English pronunciation for teachers and students of Colleges and Universities. This study focuses on teachers’ and students’ need for extensive training in the pronunciation that articulates the real pronunciation of actual words. The study is set to contribute in the sociolinguistic studies of English learning communities in this region. Data from 200 English teachers and students was collected by already tested structured questionnaire. The data was analysed using SPSS 20 software. The data analysis clearly demonstrates the higher range of inappropriate pronunciations towards English learning and teaching. The anthropogenic responses indicate 87 percentages teachers and students had an improper pronunciation. This indicates the substantial negative effects on academic and sociolinguistic aspects. It is suggested an improper speaking of English, based on rapid changes in geopolitical and sociocultural surroundings.

Keywords: alphabets, pronunciation, sociolinguistic, anthropogenic, imprudent, malapropos

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Authors: Soni Nopembri

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The objective of this research is to evaluate the implementation of teaching games for Understanding model by conducting action to physical education teacher who have got long teaching experience. The research applied Participatory Action Research. The subjects of this research were 19 physical education teachers who had got training of Teaching Games for Understanding. Data collection was conducted intensively through a questionnaire, in-depth interview, Focus Group Discussion (FGD), observation, and documentation. The collected data was analysis zed qualitatively and quantitatively. The result showed that physical education teachers had got an appropriate interpretation on TGfU model. Some indicators that were the focus of this research indicated this points; they are: (1) physical education teachers had good understanding toward TGfU model, (2) PE teachers’ competence in applying TGfU model on Physical Education at school were adequate, though some improvement were needed, (3) the influence factors in the implementation of TGfU model, in sequence, were teacher, facilities, environment, and students factors, (4) PE teachers’ perspective toward TGfU model were positively good, although some teachers were less optimistic toward the development of TGfU model in the future.

Keywords: TGfU, physical education teacher, teaching games, FGD

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Authors: Antonio Horta, Renato Marinho, Raimir Holanda

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Considered as an evolution of the Blockchain, the Ethereum platform, besides allowing transactions of its cryptocurrency named Ether, it allows the programming of decentralised applications (DApps) and smart contracts. However, this functionality into blockchains has raised other types of threats, and the exploitation of smart contracts vulnerabilities has taken companies to experience big losses. This research intends to figure out the number of contracts that are under risk of being drained. Through a deep investigation, more than two hundred thousand smart contracts currently available in the Ethereum platform were scanned and estimated how much money is at risk. The experiment was based in a query run on Google Big Query in July 2022 and returned 50,707,133 contracts published on the Ethereum platform. After applying the filtering criteria, the experimentgot 430,584 smart contracts to download and analyse. The filtering criteria consisted of filtering out: ERC20 and ERC721 contracts, contracts without transactions, and contracts without balance. From this amount of 430,584 smart contracts selected, only 268,103 had source codes published on Etherscan, however, we discovered, using a hashing process, that there were contracts duplication. Removing the duplicated contracts, the process ended up with 20,417 source codes, which were analysed using the open source SAST tool smartbugswith oyente and securify algorithms. In the end, there was nearly $100,000 at risk of being drained from the potentially vulnerable smart contracts. It is important to note that the tools used in this study may generate false positives, which may interfere with the number of vulnerable contracts. To address this point, our next step in this research is to develop an application to test the contract in a parallel environment to verify the vulnerability. Finally, this study aims to alert users and companies about the risk on not properly creating and analysing their smart contracts before publishing them into the platform. As any other application, smart contracts are at risk of having vulnerabilities which, in this case, may result in direct financial losses.

Keywords: blockchain, reentrancy, static application security testing, smart contracts

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Authors: Iva Košek Bartošová, Andrea Jokešová, Eva Kozlová, Helena Matějová

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The paper presents results of a research team from Faculty of Education, University of Hradec Králové in the Czech Republic. It introduces with the most reading methods used in the 1^st classes of a primary school and presents results of a pilot research focused on mastering reading techniques and the quality of reading comprehension of pupils in the first half of a school year during training in teaching reading by an analytic-synthetic method and by a genetic method. These methods of practicing reading skills are the most used ones in the Czech Republic. During the school year 2015/16 there has been a measurement made of two groups of pupils of the 1^st year and monitoring of quantitative and qualitative parameters of reading pupils’ outputs by several methods. Both of these methods are based on different theoretical basis and each of them has a specific educational and methodical procedure. This contribution represents results during a piloting project and draws pilot conclusions which will be verified in the subsequent broader research at the end of the school year of the first class of primary school.

Keywords: analytic-synthetic method of reading, genetic method of reading, reading comprehension, reading literacy, reading methods, reading speed

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Authors: Dawit Abay Tesfamariam

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Ethiopia’s Climate- Resilient Green Economy (ECRGE) strategy focuses mainly on generating and proper utilization of renewable energy (RE). Nonetheless, the current electricity generation of the country is dominated by hydropower. The data collected in 2016 by Ethiopian Electric Power (EEP) indicates that the intermittent RE sources from solar and wind energy were only 8 %. On the other hand, the EEP electricity generation plan in 2030 indicates that 36.1 % of the energy generation share will be covered by solar and wind sources. Thus, a case study was initiated to model and compute the balance and consumption of electricity in three different scenarios: 2016, 2025, and 2030 using the EnergyPLAN Model (EPM). Initially, the model was validated using the 2016 annual power-generated data to conduct the EnergyPLAN (EP) analysis for two predictive scenarios. The EP simulation analysis using EPM for 2016 showed that there was no significant excess power generated. Thus, the EPM was applied to analyze the role of energy storage in RE in Ethiopian grid systems. The results of the EP simulation analysis showed there will be excess production of 402 /7963 MW average and maximum, respectively, in 2025. The excess power was in the three rainy months of the year (June, July, and August). The outcome of the model also showed that in the dry seasons of the year, there would be excess power production in the country. Consequently, based on the validated outcomes of EP indicates, there is a good reason to think about other alternatives for the utilization of excess energy and storage of RE. Thus, from the scenarios and model results obtained, it is realistic to infer that if the excess power is utilized with a storage system, it can stabilize the grid system and be exported to support the economy. Therefore, researchers must continue to upgrade the current and upcoming storage system to synchronize with potentials that can be generated from renewable energy.

Keywords: renewable energy, power, storage, wind, energy plan

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Authors: Zhaoxin Luo, Michael Zhu

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In natural languages, there are always complex semantic hierarchies. Obtaining the feature representation based on these complex semantic hierarchies becomes the key to the success of the model. Several RNN models have recently been proposed to use latent indicators to obtain the hierarchical structure of documents. However, the model that only uses a single-layer latent indicator cannot achieve the true hierarchical structure of the language, especially a complex language like Chinese. In this paper, we propose a deep layered model that stacks arbitrarily many RNN layers equipped with latent indicators. After using EM and training it hierarchically, our model solves the computational problem of stacking RNN layers and makes it possible to stack arbitrarily many RNN layers. Our deep hierarchical model not only achieves comparable results to large pre-trained models on the Chinese short text classification problem but also achieves state of art results on the Chinese long text classification problem.

Keywords: nature language processing, recurrent neural network, hierarchical structure, document classification, Chinese

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Authors: Tengqin Han

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Delinquency has been a crucial factor in economics throughout the years. Commonly seen in credit card and mortgage, it played one of the crucial roles in causing the most recent financial crisis in 2008. In each case, a delinquency is a sign of the loaner being unable to pay off the debt, and thus may cause a lost of property in the end. Individually, one case of delinquency seems unimportant compared to the entire credit system. China, as an emerging economic entity, the national strength and economic strength has grown rapidly, and the gross domestic product (GDP) growth rate has remained as high as 8% in the past decades. However, potential risks exist behind the appearance of prosperity. Among the risks, the credit system is the most significant one. Due to long term and a large amount of balance of the mortgage, it is critical to monitor the risk during the performance period. In this project, about 300,000 mortgage account data are analyzed in order to develop a predictive model to predict the probability of delinquency. Through univariate analysis, the data is cleaned up, and through bivariate analysis, the variables with strong predictive power are detected. The project is divided into two parts. In the first part, the analysis data of 2005 are split into 2 parts, 60% for model development, and 40% for in-time model validation. The KS of model development is 31, and the KS for in-time validation is 31, indicating the model is stable. In addition, the model is further validation by out-of-time validation, which uses 40% of 2006 data, and KS is 33. This indicates the model is still stable and robust. In the second part, the model is improved by the addition of macroeconomic economic indexes, including GDP, consumer price index, unemployment rate, inflation rate, etc. The data of 2005 to 2010 is used for model development and validation. Compared with the base model (without microeconomic variables), KS is increased from 41 to 44, indicating that the macroeconomic variables can be used to improve the separation power of the model, and make the prediction more accurate.

Keywords: delinquency, mortgage, model development, model validation

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Authors: Md. Abu Sufian, Robiqul Islam, Imam Hossain Shajid, Mahesh Hanumanthu, Jarasree Varadarajan, Md. Sipon Miah, Mingbo Niu

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Coronary Heart Disease (CHD) remains a principal cause of global morbidity and mortality, characterized by atherosclerosis—the build-up of fatty deposits inside the arteries. The study introduces an innovative methodology that leverages cloud-based platforms like AWS Live Streaming and Artificial Intelligence (AI) to early detect and prevent CHD symptoms in web applications. By employing novel simulation processes and AI algorithms, this research aims to significantly mitigate the health and societal impacts of CHD. Methodology: This study introduces a novel simulation process alongside a multi-phased model development strategy. Initially, health-related data, including heart rate variability, blood pressure, lipid profiles, and ECG readings, were collected through user interactions with web-based applications as well as API Integration. The novel simulation process involved creating synthetic datasets that mimic early-stage CHD symptoms, allowing for the refinement and training of AI algorithms under controlled conditions without compromising patient privacy. AWS Live Streaming was utilized to capture real-time health data, which was then processed and analysed using advanced AI techniques. The novel aspect of our methodology lies in the simulation of CHD symptom progression, which provides a dynamic training environment for our AI models enhancing their predictive accuracy and robustness. Model Development: it developed a machine learning model trained on both real and simulated datasets. Incorporating a variety of algorithms including neural networks and ensemble learning model to identify early signs of CHD. The model's continuous learning mechanism allows it to evolve adapting to new data inputs and improving its predictive performance over time. Results and Findings: The deployment of our model yielded promising results. In the validation phase, it achieved an accuracy of 92% in predicting early CHD symptoms surpassing existing models. The precision and recall metrics stood at 89% and 91% respectively, indicating a high level of reliability in identifying at-risk individuals. These results underscore the effectiveness of combining live data streaming with AI in the early detection of CHD. Societal Implications: The implementation of cloud-based AI for CHD symptom detection represents a significant step forward in preventive healthcare. By facilitating early intervention, this approach has the potential to reduce the incidence of CHD-related complications, decrease healthcare costs, and improve patient outcomes. Moreover, the accessibility and scalability of cloud-based solutions democratize advanced health monitoring, making it available to a broader population. This study illustrates the transformative potential of integrating technology and healthcare, setting a new standard for the early detection and management of chronic diseases.

Keywords: coronary heart disease, cloud-based ai, machine learning, novel simulation techniques, early detection, preventive healthcare

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Authors: Bonchan Koo, Junhee Han, Dohyung Lee

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The research attempts to evaluate the accuracy and efficiency of a design optimization procedure which combines wavelets-based solution algorithm and proper orthogonal decomposition (POD) database management technique. Aerodynamic design procedure calls for high fidelity computational fluid dynamic (CFD) simulations and the consideration of large number of flow conditions and design constraints. Even with significant computing power advancement, current level of integrated design process requires substantial computing time and resources. POD reduces the degree of freedom of full system through conducting singular value decomposition for various field simulations. For additional efficiency improvement of the procedure, adaptive wavelet technique is also being employed during POD training period. The proposed design procedure was applied to the optimization of wing aerodynamic performance. Throughout the research, it was confirmed that the POD/wavelets design procedure could significantly reduce the total design turnaround time and is also able to capture all detailed complex flow features as in full order analysis.

Keywords: POD (Proper Orthogonal Decomposition), wavelets, CFD, design optimization, ROM (Reduced Order Model)

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Authors: Chanpen Meenakorn

Abstract:

This research aimed to examine the relationships between customer expectations and service quality management of Banpaew Hospital Samutsakorn in Thailand. The study sample consisted of 360 customers in patient unit. Data were collected using self-administered questionnaire. Descriptive statistics used were percentage, mean, and standard deviation. The analytical statistics comprised Pearson’s product moment correlation coefficient analysis. The result showed that service quality of nurses was very good with sustainable development trend. Physical evidence was at a high level, and the process and personal were rated at a high level. Additional, the study suggested that head nurse should be encouraged to improve service quality management, management training. Nurse administrators should create an appropriate nursing department climate, and provide necessary resources in the department. In addition, the nurse administrators should continuously follow up the results of customer expectations and focus on patients/customers, process management, information and knowledge management, and evaluation of service quality also.

Keywords: Banpaew Hospital, Customer Expectations, Service Provided, Samutsakorn

Procedia PDF Downloads 310