Search results for: Content independent features

Authors: Dalila Lino

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The power of play for learning and development in early childhood education is beyond question. The main goal of this study is to analyse how three contemporary early childhood pedagogical approaches, the High Scope, the Modern School Movement (MEM) and the Pedagogy of Participation integrate play in their curriculum development. From this main goal the following objectives emerged: (i) to characterize how play is integrated in the daily routine of the pedagogical approaches under study; (ii) to analyse the teachers’ role during children’s playing situations; (iii) to identify the types of play that children are more often involved. The methodology used is the qualitative approach and is situated under the interpretative paradigm. Data is collected through semi-structured interviews to 30 preschool teachers and through observations of typical daily routines. The participants are 30 Portuguese preschool classrooms attending children from 3 to 6 years and working with the High Scope curriculum (10 classrooms), the MEM (10 classrooms) and the Pedagogy of Participation (10 classrooms). The qualitative method of content analysis was used to analyse the data. To ensure confidentiality, no information is disclosed without participants' consent, and the interviews were transcribed and sent to the participants for a final revision. The results show that there are differences how play is integrated and promoted in the three pedagogical approaches. The teachers’ role when children are at play varies according the pedagogical approach adopted, and also according to the teachers’ understanding about the meaning of play. The study highlights the key role that early childhood curriculum models have to promote opportunities for children to play, and therefore to be involved in meaningful learning.

Keywords: curriculum models, early childhood education, pedagogy, play

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Authors: Matteo Gentilucci, Marco Materazzi, Gilberto Pambianchi

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Climate change is an increasingly central issue in the world, because it affects many of human activities. In this context regional studies are of great importance because they sometimes differ from the general trend. This research focuses on a small area of central Italy which overlooks the Adriatic Sea, the province of Macerata. The aim is to analyze space-based climate changes, for precipitation and temperatures, in the last 3 climatological standard normals (1961-1990; 1971-2000; 1981-2010) through GIS software. The data collected from 30 weather stations for temperature and 61 rain gauges for precipitation were subject to quality controls: validation and homogenization. These data were fundamental for the spatialization of the variables (temperature and precipitation) through geostatistical techniques. To assess the best geostatistical technique for interpolation, the results of cross correlation were used. The co-kriging method with altitude as independent variable produced the best cross validation results for all time periods, among the methods analysed, with 'root mean square error standardized' close to 1, 'mean standardized error' close to 0, 'average standard error' and 'root mean square error' with similar values. The maps resulting from the analysis were compared by subtraction between rasters, producing 3 maps of annual variation and three other maps for each month of the year (1961/1990-1971/2000; 1971/2000-1981/2010; 1961/1990-1981/2010). The results show an increase in average annual temperature of about 0.1°C between 1961-1990 and 1971-2000 and 0.6 °C between 1961-1990 and 1981-2010. Instead annual precipitation shows an opposite trend, with an average difference from 1961-1990 to 1971-2000 of about 35 mm and from 1961-1990 to 1981-2010 of about 60 mm. Furthermore, the differences in the areas have been highlighted with area graphs and summarized in several tables as descriptive analysis. In fact for temperature between 1961-1990 and 1971-2000 the most areally represented frequency is 0.08°C (77.04 Km² on a total of about 2800 km²) with a kurtosis of 3.95 and a skewness of 2.19. Instead, the differences for temperatures from 1961-1990 to 1981-2010 show a most areally represented frequency of 0.83 °C, with -0.45 as kurtosis and 0.92 as skewness (36.9 km²). Therefore it can be said that distribution is more pointed for 1961/1990-1971/2000 and smoother but more intense in the growth for 1961/1990-1981/2010. In contrast, precipitation shows a very similar shape of distribution, although with different intensities, for both variations periods (first period 1961/1990-1971/2000 and second one 1961/1990-1981/2010) with similar values of kurtosis (1st = 1.93; 2nd = 1.34), skewness (1st = 1.81; 2nd = 1.62 for the second) and area of the most represented frequency (1st = 60.72 km²; 2nd = 52.80 km²). In conclusion, this methodology of analysis allows the assessment of small scale climate change for each month of the year and could be further investigated in relation to regional atmospheric dynamics.

Keywords: climate change, GIS, interpolation, co-kriging

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Authors: Przemyslaw Brzyski, Stanislaw Fic

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Hydrated lime, because of the life cycle (return to its natural form as a result of the setting and hardening) has a positive environmental impact. The lime binder is used in mortars. Lime is a slow setting binder with low mechanical properties. The aim of the study was to evaluate the possibility of improving the properties of the lime binder by using different pozzolanic materials as partial replacement of hydrated lime binder. Pozzolan materials are the natural or industrial waste, so do not affect the environmental impact of the lime binder. The following laboratory tests were performed: the analysis of the physical characteristics of the tested samples of lime mortars (bulk density, porosity), flexural and compressive strength, water absorption and the capillary rise of samples and consistency of fresh mortars. As a partial replacement of hydrated lime (in the amount of 10%, 20%, 30% by weight of lime) a metakaolin, silica fume, and zeolite were used. The shortest setting and hardening time showed mortars with the addition of metakaolin. All additives noticeably improved strength characteristic of lime mortars. With the increase in the amount of additive, the increase in strength was also observed. The highest flexural strength was obtained by using the addition of metakaolin in an amount of 20% by weight of lime (2.08 MPa). The highest compressive strength was obtained by using also the addition of metakaolin but in an amount of 30% by weight of lime (9.43 MPa). The addition of pozzolan caused an increase in the mortar tightness which contributed to the limitation of absorbability. Due to the different surface area, pozzolanic additives affected the consistency of fresh mortars. Initial consistency was assumed as plastic. Only the addition of silica fume an amount of 20 and 30% by weight of lime changed the consistency to the thick-plastic. The conducted study demonstrated the possibility of applying lime mortar with satisfactory properties. The features of lime mortars do not differ significantly from cement-based mortar properties and show a lower environmental impact due to CO₂ absorption during lime hardening. Taking into consideration the setting time, strength and consistency, the best results can be obtained with metakaolin addition to the lime mortar.

Keywords: lime, binder, mortar, pozzolan, properties

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Authors: Pinar Sali, Esim Gursoy, Ebru Atak Damar

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Teachers’ awareness of and involvement in educational research (ER) is regarded as an indispensable aspect of professional growth and development. It is also believed to be a catalyst for effective teaching and learning. This strong emphasis on the significance of teacher research engagement has sparked inquiry into how teachers construe ER and whether or not they practice it. However, there seems to exist a few researches on teachers’ perceptions of and experience with ER in the field of English Language Teaching (ELT). The present study thus attempts to fill this gap in the ELT literature and aims to unearth English language teachers’ perceptions of ER. Understanding these perceptions would undoubtedly aid in the development of strategies to promote teacher interest and involvement in research. The participants of the present study are 70 English language teachers in public and private schools in Turkey. A mixed-method approach has been used in the study. Both qualitative and quantitative data have been gathered by means of a questionnaire consisting of two parts. The first part of the questionnaire consists of 20 close-ended items of Teachers’ Attitude Scale Towards Educational Research (TASTER). The second part of the questionnaire has been developed by the researchers via an extensive literature review and consists of a mixture of close- and open-ended questions. In addition, 15 language teachers have been interviewed for an in-depth understanding of the results. Descriptive statistics and dual comparisons have been employed for the quantitative data, and the qualitative data have been analyzed by means of content analysis. The present study provides intriguing information as to the English language teachers’ perceptions of the usefulness and practicality of ER as well as the value they attain to it. The findings are discussed in relation to language teacher education. The research has implications for the teacher education process, teacher trainers and policy makers.

Keywords: attitudes toward educational research, educational research, language teachers, teacher research

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Authors: Lilla Szabó Hangya, Szilvia Jambori

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The comfort zone is less studied area in the field of psychology. One of the most important definitions is that comfort zone is a psychological state in which things feel familiar to a person with low level of anxiety and stress. But the validity of comfort zone does not confirm till now. The aim of our pilot research is to test which psychological factors could determine how young adults behave during their decision process to stay in one’s comfort zone or to leave it. Every person has a number of comfort zones, so we are not able to measure it directly, only those personality traits which predict if someone leaves his comfort zone easier or harder. In our study at first we wanted to clarify the meaning of comfort zone. 110 young adults (male: 37, female: 73; ages from 18 to 70, average age: 26,6) took part in the study. Beside their demographic datas we asked them what does the comfort zone mean for them. The results showed that the meaning of the comfort zone can be grouped in five dimensions: comfort (49,6 %), leaving it-change (8,1%), ambivalent feelings (10,6%), related to other people (10,6%), pursuit of self-realization (16,8%). Our results demonstrated age related characteristics. For young people at the age of 19 the comfort zone is related to other people, because during adolescents peer relationships become more important. Subjects at the age 20-30 answered that the comfort zone means comfort and stability for them. Their life becomes stable for a while, they are studying or working. But at the age of 25, when they finish university, most of them answered comfort zone means a changing process for them. On the other hand for subjects at the age of 27 the means of the comfort zone is pursuit of self-realization. After that period at the age of 31 when they have families and stable job the stability will also dominant. We saw that the comfort zone has much more meaning besides a pleasant psychological trait. Further we would like to determine which psychological factors relate to comfort zone, and what kind of personality traits could predict leaving or staying in one’s comfort zone. We want to observe the relationship between comfort zone and subjective well-being, life satisfaction self-efficacy or self-esteem.

Keywords: comfort zone, development, personality trait, young adults

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Authors: Diwei Lin, Amanda Tan, Rajinder Singh-Rai

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We present the first reported case of a concomitant Leydig cell tumor (LCT) and paratesticular leiomyoma in an adult male with a known history of bilateral cryptorchidism. An 80-year-old male presented with a 2-month history of a left testicular lump associated with mild discomfort and a gradual increase in size on a background of bilateral cryptorchidism requiring multiple orchidopexy procedures as a child. Ultrasound confirmed a lesion suspicious for malignancy and he proceeded to a left radical orchidectomy. Histopathological assessment of the left testis revealed a concomitant testicular LCT with malignant features and paratesticular leiomyoma. Leydig cell tumors (LCTs) are the most common pure testicular sex cord-stromal tumors, accounting for up to 3% of all testicular tumors. They can occur at almost any age, but are noted to have a bi-modal distribution, with a peak incidence at 6 to 10 and at 20 to 50 years of age. LCT’s are often hormonally active and can lead to feminizing or virilizing syndromes. LCT’s are usually regarded as benign but can rarely exhibit malignant traits. Paratesticular tumours are uncommon and their reported prevalence varies between 3% and 16%. They occur in a complex anatomical area which includes the contents of the spermatic cord, testicular tunics, epididymis and vestigial remnants. Up to 90% of paratesticular tumours are believed to originate from the spermatic cord, though it is often difficult to definitively ascertain the exact site of origin. Although any type of soft-tissue neoplasm can be found in the paratesticular region, the most common benign tumors reported are lipomas of the spermatic cord, adenomatoid tumours of the epididymis and leiomyomas of the testis. Genetic studies have identified potential mutations that could potentially cause LCTs, but there are no known associations between concomitant LCTs and paratesticular tumors. The presence of cryptorchidism in adults with both LCTs and paratesticular neoplasms individually has been previously reported and it appears intuitive that cryptorchidism is likely to be associated with the concomitant presentation in this case report. This report represents the first documented case in the literature of a unilateral concomitant LCT and paratesticular leiomyoma on a background of bilateral cryptorchidism.

Keywords: testicular cancer, leydig cell tumour, leiomyoma, paratesticular neoplasms

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Authors: Rabbia Idrees, Ananda Maiti, Saurabh Garg, Muhammad Bilal Amin

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IoT devices are the basic building blocks of IoT network that generate enormous volume of real-time and high-speed data to help organizations and companies to take intelligent decisions. To integrate this enormous data from multisource and transfer it to the appropriate client is the fundamental of IoT development. The handling of this huge quantity of devices along with the huge volume of data is very challenging. The IoT devices are battery-powered and resource-constrained and to provide energy efficient communication, these IoT devices go sleep or online/wakeup periodically and a-periodically depending on the traffic loads to reduce energy consumption. Sometime these devices get disconnected due to device battery depletion. If the node is not available in the network, then the IoT network provides incomplete, missing, and inaccurate data. Moreover, many IoT applications, like vehicle tracking and patient tracking require the IoT devices to be mobile. Due to this mobility, If the distance of the device from the sink node become greater than required, the connection is lost. Due to this disconnection other devices join the network for replacing the broken-down and left devices. This make IoT devices dynamic in nature which brings uncertainty and unreliability in the IoT network and hence produce bad quality of data. Due to this dynamic nature of IoT devices we do not know the actual reason of abnormal data. If data are of poor-quality decisions are likely to be unsound. It is highly important to process data and estimate data quality before bringing it to use in IoT applications. In the past many researchers tried to estimate data quality and provided several Machine Learning (ML), stochastic and statistical methods to perform analysis on stored data in the data processing layer, without focusing the challenges and issues arises from the dynamic nature of IoT devices and how it is impacting data quality. A comprehensive review on determining the impact of dynamic nature of IoT devices on data quality is done in this research and presented a data quality model that can deal with this challenge and produce good quality of data. This research presents the data quality model for the sensors monitoring water quality. DBSCAN clustering and weather sensors are used in this research to make data quality model for the sensors monitoring water quality. An extensive study has been done in this research on finding the relationship between the data of weather sensors and sensors monitoring water quality of the lakes and beaches. The detailed theoretical analysis has been presented in this research mentioning correlation between independent data streams of the two sets of sensors. With the help of the analysis and DBSCAN, a data quality model is prepared. This model encompasses five dimensions of data quality: outliers’ detection and removal, completeness, patterns of missing values and checks the accuracy of the data with the help of cluster’s position. At the end, the statistical analysis has been done on the clusters formed as the result of DBSCAN, and consistency is evaluated through Coefficient of Variation (CoV).

Keywords: clustering, data quality, DBSCAN, and Internet of things (IoT)

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Authors: Uraib Sharaha, Guy Beck, Joseph Kapelushnik, Adam H. Agbaria, Itshak Lapidot, Shaul Mordechai, Ahmad Salman, Mahmoud Huleihel

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Infectious diseases cause a significant burden on the public health and the economic stability of societies all over the world for several centuries. A reliable detection of the causative agent of infection is not possible based on clinical features, since some of these infections have similar symptoms, including fever, sneezing, inflammation, vomiting, diarrhea, and fatigue. Moreover, physicians usually encounter difficulties in distinguishing between viral and bacterial infections based on symptoms. Therefore, there is an ongoing need for sensitive, specific, and rapid methods for identification of the etiology of the infection. This intricate issue perplex doctors and researchers since it has serious repercussions. In this study, we evaluated the potential of the mid-infrared spectroscopic method for rapid and reliable identification of bacterial and viral infections based on simple peripheral blood samples. Fourier transform infrared (FTIR) spectroscopy is considered a successful diagnostic method in the biological and medical fields. Many studies confirmed the great potential of the combination of FTIR spectroscopy and machine learning as a powerful diagnostic tool in medicine since it is a very sensitive method, which can detect and monitor the molecular and biochemical changes in biological samples. We believed that this method would play a major role in improving the health situation, raising the level of health in the community, and reducing the economic burdens in the health sector resulting from the indiscriminate use of antibiotics. We collected peripheral blood samples from young 364 patients, of which 93 were controls, 126 had bacterial infections, and 145 had viral infections, with ages lower than18 years old, limited to those who were diagnosed with fever-producing illness. Our preliminary results showed that it is possible to determine the infectious agent with high success rates of 82% for sensitivity and 80% for specificity, based on the WBC data.

Keywords: infectious diseases, (FTIR) spectroscopy, viral infections, bacterial infections.

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Authors: Ayedh Alqahtani

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Many construction firms in Saudi Arabia dedicated to building projects agree that the most important factor in the real estate market is the value that they can give to their customer. These firms understand the value of their client in different ways. Value can be defined as the size of the building project in relationship to the cost or the design quality of the materials utilized in finish work or any other features of building rooms such as the bathroom. Value can also be understood as something suitable for the money the client is investing for the new property. A quality tool is required to support companies to achieve a solution for the building project and to understand and manage the customer’s needs. Quality Function Development (QFD) method will be able to play this role since the main difference between QFD and other conventional quality management tools is QFD a valuable and very flexible tool for design and taking into the account the VOC. Currently, organizations and agencies are seeking suitable models able to deal better with uncertainty, and that is flexible and easy to use. The primary aim of this research project is to incorporate customer’s requirements in the conceptual design of construction projects. Towards this goal, QFD is selected due to its capability to integrate the design requirements to meet the customer’s needs. To develop QFD, this research focused upon the contribution of the different (significantly weighted) input factors that represent the main variables influencing QFD and subsequent analysis of the techniques used to measure them. First of all, this research will review the literature to determine the current practice of QFD in construction projects. Then, the researcher will review the literature to define the current customers of residential projects and gather information on customers’ requirements for the design of the residential building. After that, qualitative survey research will be conducted to rank customer’s needs and provide the views of stakeholder practitioners about how these needs can affect their satisfy. Moreover, a qualitative focus group with the members of the design team will be conducted to determine the improvements level and technical details for the design of residential buildings. Finally, the QFD will be developed to establish the degree of significance of the design’s solution.

Keywords: quality function development, construction projects, Saudi Arabia, quality tools

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Authors: Mohammad Saber Eslamlou

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Morphology of Islamic cities has been extensively studied by researchers of Islamic cities and different theories could be found about it. In this regard, there exist much difference in method of analysis, classification, recognition, confrontation and comparative method of urban morphology. The present paper aims to examine the previous methods, approaches and insights and that how Dr. Giulia Annalinda Neglia dealt with the analysis of morphology of Islamic cities. Neglia is assistant professor in University of Bari, Italy (UNIBA) who has published numerous papers and books on Islamic cities. I introduce her works in the field of morphology of Islamic cities. And then, her thoughts, insights and research methodologies are presented and analyzed in critical perspective. This is a qualitative research on her written works, which have been classified in three major categories. The first category consists mainly of her works on morphology and physical shape of Islamic cities. The results of her works’ review suggest that she has used Moratoria typology in investigating morphology of Islamic cities. Moreover, overall structure of the cities under investigation is often described linear; however, she’s against to define a single framework for the recognition of morphology in Islamic cities. She states that ‘to understand the physical complexity and irregularities in Islamic cities, it is necessary to study the urban fabric by typology method, focusing on transformation processes of the buildings’ form and their surrounding open spaces’ and she believes that fabric of each region in the city follows from the principles of an specific period or urban pattern, in particular, Hellenistic and Roman structures. Furthermore, she believes that it is impossible to understand the morphology of a city without taking into account the obvious and hidden developments associated with it, because form of building and their surrounding open spaces are written history of the city.

Keywords: city, Islamic city, Giulia Annalinda Neglia, morphology

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Authors: Warda Khan, Remo Lachmann, Adarsh S. Garakahally

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The increasing complexity of software and its applicability in a wide range of industries, e.g., automotive, call for enhanced quality assurance techniques. Test automation is one option to tackle the prevailing challenges by supporting test engineers with fast, parallel, and repetitive test executions. A high degree of test automation allows for a shift from mundane (manual) testing tasks to a more analytical assessment of the software under test. However, a high initial investment of test resources is required to establish test automation, which is, in most cases, a limitation to the time constraints provided for quality assurance of complex software systems. Hence, a computer-aided creation of automated test cases is crucial to increase the benefit of test automation. This paper proposes the application of machine learning for the generation of automated test cases. It is based on supervised learning to analyze test specifications and existing test implementations. The analysis facilitates the identification of patterns between test steps and their implementation with test automation components. For the test case generation, this approach exploits historical data of test automation projects. The identified patterns are the foundation to predict the implementation of unknown test case specifications. Based on this support, a test engineer solely has to review and parameterize the test automation components instead of writing them manually, resulting in a significant time reduction for establishing test automation. Compared to other generation approaches, this ML-based solution can handle different writing styles, authors, application domains, and even languages. Furthermore, test automation tools require expert knowledge by means of programming skills, whereas this approach only requires historical data to generate test cases. The proposed solution is evaluated using various multi-label evaluation criteria (EC) and two small-sized real-world systems. The most prominent EC is ‘Subset Accuracy’. The promising results show an accuracy of at least 86% for test cases, where a 1:1 relationship (Multi-Class) between test step specification and test automation component exists. For complex multi-label problems, i.e., one test step can be implemented by several components, the prediction accuracy is still at 60%. It is better than the current state-of-the-art results. It is expected the prediction quality to increase for larger systems with respective historical data. Consequently, this technique facilitates the time reduction for establishing test automation and is thereby independent of the application domain and project. As a work in progress, the next steps are to investigate incremental and active learning as additions to increase the usability of this approach, e.g., in case labelled historical data is scarce.

Keywords: machine learning, multi-class, multi-label, supervised learning, test automation

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Authors: Azizah M. Nahari, Peter Doerner

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Phosphate (Pi) is one of the essential macronutrients in plant growth and development, and it plays a central role in metabolic processes in plants, particularly photosynthesis and respiration. Limitation of crop productivity by Pi is widespread and is likely to increase in the future. Applications of Pi fertilizers have improved soil Pi fertility and crop production; however, they have also caused environmental damage. Therefore, in order to reduce dependence on unsustainable Pi fertilizers, a better understanding of phosphate use efficiency (PUE) is required for engineering nutrient-efficient crop plants. Enhanced Pi efficiency can be achieved by improved productivity per unit Pi taken up. We aim to identify, by using association mapping, general features of the most important loci that contribute to increased PUE to allow us to delineate the physiological pathways involved in defining this trait in the model plant Arabidopsis. As PUE is in part determined by the efficiency of uptake, we designed a hydroponic system to avoid confounding effects due to differences in root system architecture leading to differences in Pi uptake. In this system, 18 parental lines and 217 lines of the MAGIC population (a Multiparent Advanced Generation Inter-Cross) grown in high and low Pi availability conditions. The results showed revealed a large variation of PUE in the parental lines, indicating that the MAGIC population was well suited to identify PUE loci and pathways. 2 of 18 parental lines had the highest PUE in low Pi while some lines responded strongly and increased PUE with increased Pi. Having examined the 217 MAGIC population, considerable variance in PUE was found. A general feature was the trend of most lines to exhibit higher PUE when grown in low Pi conditions. Association mapping is currently in progress, but initial observations indicate that a wide variety of physiological processes are involved in influencing PUE in Arabidopsis. The combination of hydroponic growth methods and genome-wide association mapping is a powerful tool to identify the physiological pathways underpinning complex quantitative traits in plants.

Keywords: hydroponic system growth, phosphate use efficiency (PUE), Genome-wide association mapping, MAGIC population

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Authors: Lixin Zhao, Genmao Zhou

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Traditional acid in-situ leaching (ISL) is not suitable for the sandstone uranium deposit with low permeability and high content of carbonate minerals, because of the blocking of calcium sulfate precipitates. Another factor influences the uranium acid in-situ leaching is that the pyrite in ore rocks will react with oxidation reagent and produce lots of sulfate ions which may speed up the precipitation process of calcium sulphate and consume lots of oxidation reagent. Due to the advantages such as less chemical reagent consumption and groundwater pollution, CO₂+O₂ in-situ leaching method has become one of the important research areas in uranium mining. China is the second country where CO₂+O₂ ISL has been adopted in industrial uranium production of the world. It is shown that the CO₂+O₂ ISL in China has been successfully developed. The reaction principle, technical process, well field design and drilling engineering, uranium-bearing solution processing, etc. have been fully studied. At current stage, several uranium mines use CO₂+O₂ ISL method to extract uranium from the ore-bearing aquifers. The industrial application and development potential of CO₂+O₂ ISL method in China are summarized. By using CO₂+O₂ neutral leaching technology, the problem of calcium carbonate and calcium sulfate precipitation have been solved during uranium mining. By reasonably regulating the amount of CO₂ and O₂, related ions and hydro-chemical conditions can be controlled within the limited extent for avoiding the occurrence of calcium sulfate and calcium carbonate precipitation. Based on this premise, the demand of CO₂+O₂ uranium leaching has been met to the maximum extent, which not only realizes the effective leaching of uranium, but also avoids the occurrence and precipitation of calcium carbonate and calcium sulfate, realizing the industrial development of the sandstone type uranium deposit.

Keywords: CO₂+O₂ ISL, industrial production, well field layout, uranium processing

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Authors: Hossam Ali-Hassan, Michael Bliemel

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This poster reflects upon our experiences using INNOV8, IBM’s Business Process Management (BPM) simulation game, in online MBA and undergraduate MIS classes over a period of 2 years. The game is designed to gives both business and information technology players a better understanding of how effective BPM impacts an entire business ecosystem. The game includes three different scenarios: Smarter Traffic, which is used to evaluate existing traffic patterns and re-route traffic based on incoming metrics; Smarter Customer Service where players develop more efficient ways to respond to customers in a call centre environment; and Smarter Supply Chains where players balance supply and demand and reduce environmental impact in a traditional supply chain model. We use the game as an experiential learning tool, where students have to act as managers making real time changes to business processes to meet changing business demands and environments. The students learn how information technology (IT) and information systems (IS) can be used to intelligently solve different problems and how computer simulations can be used to test different scenarios or models based on business decisions without having to actually make the potentially costly and/or disruptive changes to business processes. Moreover, when students play the three different scenarios, they quickly see how practical process improvements can help meet profitability, customer satisfaction and environmental goals while addressing real problems faced by municipalities and businesses today. After spending approximately two hours in the game, students reflect on their experience from it to apply several BPM principles that were presented in their textbook through the use of a structured set of assignment questions. For each final scenario students submit a screenshot of their solution followed by one paragraph explaining what criteria you were trying to optimize, and why they picked their input variables. In this poster we outline the course and the module’s learning objectives where we used the game to place this into context. We illustrate key features of the INNOV8 Simulation Game, and describe how we used them to reinforce theoretical concepts. The poster will also illustrate examples from the simulation, assignment, and learning outcomes.

Keywords: experiential learning, business process management, BPM, INNOV8, simulation, game

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Authors: Misha Teimouri

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Our world has been transformed by the use of the internet and the constant flow of information. While this transmission has its benefits, it has also added significant challenges to family relations, primarily in the field of parenting and children's digital lives. Screens, speed, and connectedness are the words that characterize the lives of today's digital generation; it's as if the entire world is in their pockets at all times. Parents attempt to regulate and control their children's internet use in the hopes of maximizing the advantages and minimizing the disadvantages of their children's internet use; however, given that children spend more time online, particularly ever since the pandemic, children's cyber-aggression has become an issue for them. Children may externalize their behavior online, bully others, send anger/hatred/resist messages, share violent and bloody content, and engage in sexting. These types of online aggression make parenting more difficult, especially for digital immigrant parents compared to digital native parents. In response to these challenges, this study investigated the level of cyber aggression among children, as well as the effects of digi-parenting (active, monitoring, restrictive, and warm and supportive) on children's cyber-aggression (sexual, verbal, visual) as victims or aggressors. The study also determined whether there were any differences in parenting styles between digital natives (DN) and digital immigrants. In accordance with the study, boys and older children are more likely to engage in cyber aggression as aggressors, whereas girls and younger children are more likely to engage as victims. Warmth and supportive digiparenting have a greater impact on children's cyber-aggression (sexual, verbal, and visual) as victims or aggressors. This study also found that, when compared to DI parents, DN parents are more successful at digi-parenting and reducing their children's exposure to cyber-aggression.

Keywords: digi-parenting, cyber-aggression, digital natives, digital immigrants, children's cyber-aggression (sexual, verbal, visual)

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Authors: Randa Alharbi, Vladislav Vyshemirsky

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Systems biology is an important field in science which focuses on studying behaviour of biological systems. Modelling is required to produce detailed description of the elements of a biological system, their function, and their interactions. A well-designed model requires selecting a suitable mechanism which can capture the main features of the system, define the essential components of the system and represent an appropriate law that can define the interactions between its components. Complex biological systems exhibit stochastic behaviour. Thus, using probabilistic models are suitable to describe and analyse biological systems. Continuous-Time Markov Chain (CTMC) is one of the probabilistic models that describe the system as a set of discrete states with continuous time transitions between them. The system is then characterised by a set of probability distributions that describe the transition from one state to another at a given time. The evolution of these probabilities through time can be obtained by chemical master equation which is analytically intractable but it can be simulated. Uncertain parameters of such a model can be inferred using methods of Bayesian inference. Yet, inference in such a complex system is challenging as it requires the evaluation of the likelihood which is intractable in most cases. There are different statistical methods that allow simulating from the model despite intractability of the likelihood. Approximate Bayesian computation is a common approach for tackling inference which relies on simulation of the model to approximate the intractable likelihood. Particle Markov chain Monte Carlo (PMCMC) is another approach which is based on using sequential Monte Carlo to estimate intractable likelihood. However, both methods are computationally expensive. In this paper we discuss the efficiency and possible practical issues for each method, taking into account the computational time for these methods. We demonstrate likelihood-free inference by performing analysing a model of the Repressilator using both methods. Detailed investigation is performed to quantify the difference between these methods in terms of efficiency and computational cost.

Keywords: Approximate Bayesian computation(ABC), Continuous-Time Markov Chains, Sequential Monte Carlo, Particle Markov chain Monte Carlo (PMCMC)

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Authors: Khadija Refouh

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Culture bound-expressions have been a bottleneck for Natural Language Processing (NLP) and comprehension, especially in the case of machine translation (MT). In the last decade, the field of machine translation has greatly advanced. Neural machine translation NMT has recently achieved considerable development in the quality of translation that outperformed previous traditional translation systems in many language pairs. Neural machine translation NMT is an Artificial Intelligence AI and deep neural networks applied to language processing. Despite this development, there remain some serious challenges that face neural machine translation NMT when translating culture bounded-expressions, especially for low resources language pairs such as Arabic-English and Arabic-French, which is not the case with well-established language pairs such as English-French. Machine translation of opaque idioms from English into French are likely to be more accurate than translating them from English into Arabic. For example, Google Translate Application translated the sentence “What a bad weather! It runs cats and dogs.” to “يا له من طقس سيء! تمطر القطط والكلاب” into the target language Arabic which is an inaccurate literal translation. The translation of the same sentence into the target language French was “Quel mauvais temps! Il pleut des cordes.” where Google Translate Application used the accurate French corresponding idioms. This paper aims to perform NMT experiments towards better translation of opaque idioms using high quality clean multilingual corpus. This Corpus will be collected analytically from human generated idiom translation. AutoML translation, a Google Neural Machine Translation Platform, is used as a custom translation model to improve the translation of opaque idioms. The automatic evaluation of the custom model will be compared to the Google NMT using Bilingual Evaluation Understudy Score BLEU. BLEU is an algorithm for evaluating the quality of text which has been machine-translated from one natural language to another. Human evaluation is integrated to test the reliability of the Blue Score. The researcher will examine syntactical, lexical, and semantic features using Halliday's functional theory.

Keywords: multilingual corpora, natural language processing (NLP), neural machine translation (NMT), opaque idioms

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Authors: Yijun Shao, Yan Cheng, Rashmee U. Shah, Charlene R. Weir, Bruce E. Bray, Qing Zeng-Treitler

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Deep neural network (DNN) models are being explored in the clinical domain, following the recent success in other domains such as image recognition. For clinical adoption, outcome prediction models require explanation, but due to the multiple non-linear inner transformations, DNN models are viewed by many as a black box. In this study, we developed a deep neural network model for predicting 1-year mortality of patients who underwent major cardio vascular procedures (MCVPs), using temporal image representation of past medical history as input. The dataset was obtained from the electronic medical data warehouse administered by Veteran Affairs Information and Computing Infrastructure (VINCI). We identified 21,355 veterans who had their first MCVP in 2014. Features for prediction included demographics, diagnoses, procedures, medication orders, hospitalizations, and frailty measures extracted from clinical notes. Temporal variables were created based on the patient history data in the 2-year window prior to the index MCVP. A temporal image was created based on these variables for each individual patient. To generate the explanation for the DNN model, we defined a new concept called impact score, based on the presence/value of clinical conditions’ impact on the predicted outcome. Like (log) odds ratio reported by the logistic regression (LR) model, impact scores are continuous variables intended to shed light on the black box model. For comparison, a logistic regression model was fitted on the same dataset. In our cohort, about 6.8% of patients died within one year. The prediction of the DNN model achieved an area under the curve (AUC) of 78.5% while the LR model achieved an AUC of 74.6%. A strong but not perfect correlation was found between the aggregated impact scores and the log odds ratios (Spearman’s rho = 0.74), which helped validate our explanation.

Keywords: deep neural network, temporal data, prediction, frailty, logistic regression model

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Authors: Issam A. Al-Khatib

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In order to achieve a significant reduction of waste amount flowing into landfills, it is important to first understand the composition of the solid municipal waste generated. Hence a detailed analysis of municipal solid waste composition has been conducted in Nablus city. The aim is to provide data on the potential recyclable fractions in the actual waste stream, with a focus on the plastic fraction. Hence, waste-sorting campaigns were conducted on mixed waste containers from five districts in Nablus city. The districts vary in terms of infrastructure and average income. The target is to obtain representative data about the potential quantity and quality of household plastic waste. The study has measured the composition of municipal solid waste collected/ transported by Nablus municipality. The analysis was done by categorizing the samples into eight primary fractions (organic and food waste, paper and cardboard, glass, metals, textiles, plastic, a fine fraction (<10 mm), and others). The study results reveal that the MSW stream in Nablus city has a significant bio- and organic waste fraction (about 68% of the total MSW). The second largest fraction is paper and cardboard (13.6%), followed by plastics (10.1%), textiles (3.2%), glass (1.9%), metals (1.8%), a fine fraction (0.5%), and other waste (0.3%). After this complete and detailed characterization of MSW collected in Nablus and taking into account the content of biodegradable organic matter, the composting could be a solution for the city of Nablus where the surrounding areas of Nablus city have agricultural activities and could be a natural outlet to the compost product. Different waste management options could be practiced in the future in addition to composting, such as energy recovery and recycling, which result in a greater possibility of reducing substantial amounts that are disposed of at landfills.

Keywords: developing countries, composition, management, recyclable, waste.

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Authors: Ahmad Almohana

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Technology has led to rapid changes in the world, and most importantly to education, particularly in the 21st century. Technology has enhanced teachers’ potential and has resulted in the provision of greater interaction and choices for learners. In addition, technology is helping to improve individuals’ learning experiences and building their capacity to read, listen, speak, search, analyse, memorise and encode languages, as well as bringing learners together and creating a sense of greater involvement. This paper has been organised in the following way: the first section provides a review of the literature related to the implementation of CALL (computer assisted learning language), and it explains CALL and its phases, as well as attempting to highlight and analyse Warschauer’s article. The second section is an attempt to describe the move from CALL to mobilised systems of edutainment, which challenge existing forms of teaching and learning. It also addresses the role of the teacher and the curriculum content, and how this is affected by the computerisation of learning that is taking place. Finally, an empirical study has been conducted to collect data from teachers in Saudi Arabia using quantitive and qualitative method tools. Connections are made between the area of study and the personal experience of the researcher carrying out the study with a methodological reflection on the challenges faced by the teachers of this same system. The major findings were that it is worth spelling out here that despite the circumstances in which students and lecturers are currently working, the participants revealed themselves to be highly intelligent and articulate individuals who were constrained from revealing this criticality and creativity by the system of learning and teaching operant in most schools.

Keywords: CALL, computer assisted learning language, EFL, English as a foreign language, ELT, English language teaching, ETL, enhanced technology learning, MALL, mobile assisted learning language

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Authors: Ankit Shah, R. K. Shrivastava

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Flood and drought are two main features of hydrology which affect the human life. Floods are natural disasters which cause millions of rupees’ worth of damage each year in India and the whole world. Flood causes destruction in form of life and property. An accurate estimate of the flood damage potential is a key element to an effective, nationwide flood damage abatement program. Also, the increase in demand of water due to increase in population, industrial and agricultural growth, has let us know that though being a renewable resource it cannot be taken for granted. We have to optimize the use of water according to circumstances and conditions and need to harness it which can be done by construction of hydraulic structures. For their safe and proper functioning of hydraulic structures, we need to predict the flood magnitude and its impact. Hydraulic structures play a key role in harnessing and optimization of flood water which in turn results in safe and maximum use of water available. Mainly hydraulic structures are constructed on ungauged sites. There are two methods by which we can estimate flood viz. generation of Unit Hydrographs and Flood Frequency Analysis. In this study, Regional Flood Frequency Analysis has been employed. There are many methods for estimating the ‘Regional Flood Frequency Analysis’ viz. Index Flood Method. National Environmental and Research Council (NERC Methods), Multiple Regression Method, etc. However, none of the methods can be considered universal for every situation and location. The Narmada basin is located in Central India. It is drained by most of the tributaries, most of which are ungauged. Therefore it is very difficult to estimate flood on these tributaries and in the main river. As mentioned above Artificial Neural Network (ANN)s and Multiple Regression Method is used for determination of Regional flood Frequency. The annual peak flood data of 20 sites gauging sites of Narmada Basin is used in the present study to determine the Regional Flood relationships. Homogeneity of the considered sites is determined by using the Index Flood Method. Flood relationships obtained by both the methods are compared with each other, and it is found that ANN is more reliable than Multiple Regression Method for the present study area.

Keywords: artificial neural network, index flood method, multi layer perceptrons, multiple regression, Narmada basin, regional flood frequency

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Authors: Addin Osman, Anwar Ali Yahya, Mohammed Basit Kamal

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Datasets or collections are becoming important assets by themselves and now they can be accepted as a primary intellectual output of a research. The quality and usage of the datasets depend mainly on the context under which they have been collected, processed, analyzed, validated, and interpreted. This paper aims to present a collection of program educational objectives mapped to student’s outcomes collected from self-study reports prepared by 32 engineering programs accredited by ABET. The manual mapping (classification) of this data is a notoriously tedious, time consuming process. In addition, it requires experts in the area, which are mostly not available. It has been shown the operational settings under which the collection has been produced. The collection has been cleansed, preprocessed, some features have been selected and preliminary exploratory data analysis has been performed so as to illustrate the properties and usefulness of the collection. At the end, the collection has been benchmarked using nine of the most widely used supervised multiclass classification techniques (Binary Relevance, Label Powerset, Classifier Chains, Pruned Sets, Random k-label sets, Ensemble of Classifier Chains, Ensemble of Pruned Sets, Multi-Label k-Nearest Neighbors and Back-Propagation Multi-Label Learning). The techniques have been compared to each other using five well-known measurements (Accuracy, Hamming Loss, Micro-F, Macro-F, and Macro-F). The Ensemble of Classifier Chains and Ensemble of Pruned Sets have achieved encouraging performance compared to other experimented multi-label classification methods. The Classifier Chains method has shown the worst performance. To recap, the benchmark has achieved promising results by utilizing preliminary exploratory data analysis performed on the collection, proposing new trends for research and providing a baseline for future studies.

Keywords: ABET, accreditation, benchmark collection, machine learning, program educational objectives, student outcomes, supervised multi-class classification, text mining

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Authors: Dagem Alemayehu, Samson Gebersilassie, Jan Frank

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Climate change is impacting nutrition through reducing food quantity and access, limiting dietary diversity, and decreased nutritional food content as well as strongly affecting seasonal rainfall in Ethiopia. Nevertheless, only a few data is available on the impacts of seasonality in Infant, and Young Child Feeding (IYCF) practices undernutrition among 6-23 months old children in different agro-ecological zones of poor resource settings of Ethiopia. Methods: Socio-demographic, anthropometry, and IYCF indicators were assessed in the harvest and lean seasons among children aged 6–23 months of age randomly selected from rural villages of lowland and midland agro-ecological zones. Results: Child stunting and underweight increased from prevalence of 32.8 % and 23.9 % (lowland &midland respectively) in the lean season to 36.1% and 33.8 % harvest seasons, respectively. The biggest increase in the prevalence of stunting and underweight between harvest and lean seasons was noted in the lowland zone. Wasting decreased from 11.6% lean to 8.5% harvest, with the biggest decline recorded in the midland zone. Minimum meal frequency, minimum acceptable diet, and poor dietary diversity increased considerably in harvest compared to a lean season in the lowland zone. Feeding practices and maternal age were predictors of wasting, while women's dietary diversity and children's age was a predictor of child dietary diversity in both seasons. Conclusion: There is seasonal variation in undernutrition and IYCF practices among children 6-23 months of age with more pronounced effect lowland agro-ecological zone.

Keywords: agroecology, seasonality, stunting, wasting

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Authors: Jacqueline Y. Thompson, Sam Watson, Lee Middleton, Karla Hemming

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Introduction: The odds ratio (estimated via logistic regression) is a well-established and common approach for estimating covariate-adjusted binary treatment effects when comparing a treatment and control group with dichotomous outcomes. Its popularity is primarily because of its stability and robustness to model misspecification. However, the situation is different for the relative risk and risk difference, which are arguably easier to interpret and better suited to specific designs such as non-inferiority studies. So far, there is no equivalent, widely acceptable approach to estimate an adjusted relative risk and risk difference when conducting clinical trials. This is partly due to the lack of a comprehensive evaluation of available candidate methods. Methods/Approach: A simulation study is designed to evaluate the performance of relevant candidate methods to estimate relative risks to represent conditional and marginal estimation approaches. We consider the log-binomial, generalised linear models (GLM) with iteratively weighted least-squares (IWLS) and model-based standard errors (SE); log-binomial GLM with convex optimisation and model-based SEs; log-binomial GLM with convex optimisation and permutation tests; modified-Poisson GLM IWLS and robust SEs; log-binomial generalised estimation equations (GEE) and robust SEs; marginal standardisation and delta method SEs; and marginal standardisation and permutation test SEs. Independent and identically distributed datasets are simulated from a randomised controlled trial to evaluate these candidate methods. Simulations are replicated 10000 times for each scenario across all possible combinations of sample sizes (200, 1000, and 5000), outcomes (10%, 50%, and 80%), and covariates (ranging from -0.05 to 0.7) representing weak, moderate or strong relationships. Treatment effects (ranging from 0, -0.5, 1; on the log-scale) will consider null (H0) and alternative (H1) hypotheses to evaluate coverage and power in realistic scenarios. Performance measures (bias, mean square error (MSE), relative efficiency, and convergence rates) are evaluated across scenarios covering a range of sample sizes, event rates, covariate prognostic strength, and model misspecifications. Potential Results, Relevance & Impact: There are several methods for estimating unadjusted and adjusted relative risks. However, it is unclear which method(s) is the most efficient, preserves type-I error rate, is robust to model misspecification, or is the most powerful when adjusting for non-prognostic and prognostic covariates. GEE estimations may be biased when the outcome distributions are not from marginal binary data. Also, it seems that marginal standardisation and convex optimisation may perform better than GLM IWLS log-binomial.

Keywords: binary outcomes, statistical methods, clinical trials, simulation study

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Authors: Shigdaf Mekuriaw, Firew Tegegne, A. Tsunekawa, Dereje Tewabe

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The purpose of this paper is to make a comprehensive review on the use of water hyacinth (Eichhornia crassipes) as a potential livestock feed and argue its utilization as complementary strategy to other control methods. Water Hyacinth is one of the most noxious plant invaders of rivers and lakes. Such weeds cause environmental disaster and interfere with economic and recreational activities such as water transportation and fishing. Economic impacts of the weed in seven African countries have been estimated at between 20-50 million US$ every year. It would, therefore, be prudent to suggest utilization as a complementary control method. The majority of people in developing countries are dependent on traditional and inefficient crop-livestock production system that constrains their ability to enhance economic productivity and quality of life. Livestock in developing countries faces shortage of feed, especially during the long dry seasons. Existing literature shows the use of water hyacinth as livestock and fish feed. The chemical composition of water hyacinth varies considerably. Due to its relatively high crude protein (CP) content (5.8-20.0%), water hyacinth can be considered as a potential protein supplement for livestock which commonly feed cereal crop residues whose contribution as source of feed is increasing in Africa. Though the effects of anti-nutritional factors (ANFs) present in water hyacinth is not investigated, their concentrations are not above threshold hinder its utilization as livestock feed. In conclusion, water hyacinth could provide large quantities of nutritious feed for animals. Like other feeds, water hyacinth may not be offered as a sole feed and based on existing literature its optimum inclusion level reaches 50%.

Keywords: Africa, livestock feed, water bodies, water hyacinth and weed control method

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Authors: Luo Guidong, Song Hang, Jim Song, Virginia Martin Torrejon

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Due to their excellent properties, polymer packaging foams have become increasingly essential in our current lifestyles. They are cost-effective and lightweight, with excellent mechanical and thermal insulation properties. However, they constitute a major environmental and health concern due to litter generation, ocean pollution, and microplastic contamination of the food chain. In recent years, considerable efforts have been made to develop more sustainable alternatives to conventional polymer packaging foams. As a result, biobased and compostable foams are increasingly becoming commercially available, such as starch-based loose-fill or PLA trays. However, there is still a need for bulk manufacturing of bio-foams planks for packaging applications as a viable alternative to their fossil fuel counterparts (i.e., polystyrene, polyethylene, and polyurethane). Gelatin is a promising biopolymer for packaging applications due to its biodegradability, availability, and biocompatibility, but its mechanical properties are poor compared to conventional plastics. However, as widely reported for other biopolymers, such as starch, the mechanical properties of gelatin-based bioplastics can be enhanced by formulation optimization, such as the incorporation of fibres from different crops, such as bamboo. This research aimed to produce gelatin-bamboo fibre foams by mechanical foaming and to study the effect of fibre content on the foams' properties and structure. As a result, foams with virtually no shrinkage, low density (<40 kg/m³), low thermal conductivity (<0.044 W/m•K), and mechanical properties comparable to conventional plastics were produced. Further work should focus on developing formulations suitable for the packaging of water-sensitive products and processing optimization, especially the reduction of the drying time.

Keywords: biobased and compostable foam, sustainable packaging, natural polymer hydrogel, cold chain packaging

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Authors: Walaa H. Salama, Azza M. Abdel-Aty, Afaf S. Fahmy

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Background: Egyptian Cobra; Naja haje (Elapidae) is one of most common snakes, widely distributed in Egypt and its envenomation causes multi-organ failure leading to rapid death. Thus, Different medicinal plants showed a protective effect against venom toxicity and may complement the conventional antivenom therapy. Aim: The present study was designed to assess both the antioxidant capacity of methanolic extract of rosemary leaves and evaluate the neutralizing ability of the extract against hepatotoxicity induced by Naja haje venom. Methods: The total phenolic and flavonoid contents and the antioxidant capacity of the methanolic rosemary extract were estimated by DPPH and ABTS Scavenging methods. In addition, the rosemary extract were assessed for anti-venom properties under in vitro and in vivo standard assays. Results: The rosemary extract had high total phenolic and flavonoid content as 12 ± 2 g of gallic acid equivalent per 100 gram of dry weight (g GAE/100g dw) and 5.5 ± 0.8 g of catechin equivalent per 100 grams of dry weight (g CE/100g dw), respectively. In addition, the rosemary extract showed high antioxidant capacity. Furthermore, The rosemary extract were inhibited in vitro the enzymatic activities of phospholipase A₂, L-amino acid oxidase, and hyaluronidase of the venom in a dose-dependent manner. Moreover, indirect hemolytic activity, hepatotoxicity induced by venom were completely neutralized as shown by histological studies. Conclusion: The phenolic compounds of rosemary extract with potential antioxidant activity may be considered as a promising candidate for future therapeutics in snakebite therapy.

Keywords: antioxidant activity, neutralization, phospholipase A₂ enzyme, snake venom

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Authors: Luísa P. Cruz-Lopes, Hugo Costa e Silva, Idalina Domingos, José Ferreira, Luís Teixeira de Lemos, Bruno Esteves

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The liquefaction process of cork based tree barks has led to an increase of interest due to its potential innovation in the lumber and wood industries. In this particular study the bark of Quercus cerris (Turkish oak) is used due to its appreciable amount of cork tissue, although of inferior quality when compared to the cork provided by other Quercus trees. This study aims to optimize alkaline catalysis liquefaction conditions, regarding several parameters. To better comprehend the possible chemical characteristics of the bark of Quercus cerris, a complete chemical analysis was performed. The liquefaction process was performed in a double-jacket reactor heated with oil, using glycerol and a mixture of glycerol/ethylene glycol as solvents, potassium hydroxide as a catalyst, and varying the temperature, liquefaction time and granulometry. Due to low liquefaction efficiency resulting from the first experimental procedures a study was made regarding different washing techniques after the filtration process using methanol and methanol/water. The chemical analysis stated that the bark of Quercus cerris is mostly composed by suberin (ca. 30%) and lignin (ca. 24%) as well as insolvent hemicelluloses in hot water (ca. 23%). On the liquefaction stage, the results that led to higher yields were: using a mixture of methanol/ethylene glycol as reagents and a time and temperature of 120 minutes and 200 ºC, respectively. It is concluded that using a granulometry of <80 mesh leads to better results, even if this parameter barely influences the liquefaction efficiency. Regarding the filtration stage, washing the residue with methanol and then distilled water leads to a considerable increase on final liquefaction percentages, which proves that this procedure is effective at liquefying suberin content and lignocellulose fraction.

Keywords: liquefaction, Quercus cerris, polyalcohol liquefaction, temperature

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Authors: Rossella Resi

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This paper describes a project carried out in an Italian school with English learning pupils combining three didactic tools which are attested to be relevant for the success of young learner’s language curriculum: the use of technology, the intralingual and interlingual mediation (according to CEFR) and the cultural dimension. Aim of this project was to test a technological hands-on translation activity like subtitling in a formal teaching context and to exploit its potential as motivational tool for developing listening and writing, translation and cross-cultural skills among language learners. The activities proposed involved the use of professional subtitling software called Aegisub and culture-specific films. The workshop was optional so motivation was entirely based on the pleasure of engaging in the use of a realistic subtitling program and on the challenge of meeting the constraints that a real life/work situation might involve. Twelve pupils in the age between 16 and 18 have attended the afternoon workshop. The workshop was organized in three parts: (i) An introduction where the learners were opened up to the concept and constraints of subtitling and provided with few basic rules on spotting and segmentation. During this session learners had also the time to familiarize with the main software features. (ii) The second part involved three subtitling activities in plenum or in groups. In the first activity the learners experienced the technical dimensions of subtitling. They were provided with a short video segment together with its transcription to be segmented and time-spotted. The second activity involved also oral comprehension. Learners had to understand and transcribe a video segment before subtitling it. The third activity embedded a translation activity of a provided transcription including segmentation and spotting of subtitles. (iii) The workshop ended with a small final project. At this point learners were able to master a short subtitling assignment (transcription, translation, segmenting and spotting) on their own with a similar video interview. The results of these assignments were above expectations since the learners were highly motivated by the authentic and original nature of the assignment. The subtitled videos were evaluated and watched in the regular classroom together with other students who did not take part to the workshop.

Keywords: ICT, L2, language learning, language mediation, subtitling

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Authors: Anteneh Wodaje Bayeh, Daniel Manaye Kabtamu, Chen-Hao Wang

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As one of the most promising electrochemical energy storage systems, vanadium redox flow batteries (VRFBs) have received increasing attention owing to their attractive features for largescale storage applications. However, their high production cost and relatively low energy efficiency still limit their feasibility. For practical implementation, it is of great interest to improve their efficiency and reduce their cost. One of the key components of VRFBs that can greatly influence the efficiency and final cost is the electrode, which provide the reactions sites for redox couples (VO²⁺/VO₂ + and V²⁺/V³⁺). Carbon-based materials are considered to be the most feasible electrode materials in the VRFB because of their excellent potential in terms of operation range, good permeability, large surface area, and reasonable cost. However, owing to limited electrochemical activity and reversibility and poor wettability due to its hydrophobic properties, the performance of the cell employing carbon-based electrodes remained limited. To address the challenges, we synthesized heteroatom-doped bimetallic oxide grown on the surface of carbon through the one-step approach. When applied to VRFBs, the prepared electrode exhibits significant electrocatalytic effect toward the VO²⁺/VO₂ + and V³⁺/V²⁺ redox reaction compared with that of pristine carbon. It is found that the presence of heteroatom on metal oxide promotes the absorption of vanadium ions. The controlled morphology of bimetallic metal oxide also exposes more active sites for the redox reaction of vanadium ions. Hence, the prepared electrode displays the best electrochemical performance with energy and voltage efficiencies of 74.8% and 78.9%, respectively, which is much higher than those of 59.8% and 63.2% obtained from the pristine carbon at high current density. Moreover, the electrode exhibit durability and stability in an acidic electrolyte during long-term operation for 1000 cycles at the higher current density.

Keywords: VRFB, VO²⁺/VO₂ + and V³⁺/V²⁺ redox couples, graphite felt, heteroatom-doping

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