Search results for: technology identification

Authors: Maryam Kiani

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This study focuses on the development of composite nanomaterials based on SiO2 and carbon black for oxygen reduction reaction (ORR) electrocatalysts in batteries and fuel cells. The aim was to explore the potential of these composite materials as efficient catalysts for ORR, which is a critical process in energy conversion devices. The SiO2/carbon black composite nanomaterials were synthesized using a facile and scalable method. The morphology, structure, and electrochemical properties of the materials were characterized using various techniques, including scanning electron microscopy (SEM), X-ray diffraction (XRD), and electrochemical measurements. The results demonstrated that the incorporation of SiO2 into the carbon black matrix enhanced the ORR performance of the composite material. The composite nanomaterials exhibited improved electrocatalytic activity, enhanced stability, and increased durability compared to pure carbon black. The presence of SiO2 facilitated the formation of active sites, improved electron transfer, and increased the surface area available for ORR. This study contributes to the advancement of battery and fuel cell technology by offering a promising approach for the development of high-performance ORR electrocatalysts. The SiO2/carbon black composite nanomaterials show great potential for improving the efficiency and durability of energy conversion devices, leading to more sustainable and efficient energy solutions.

Keywords: oxygen reduction reaction, batteries, fuel cells, electrrocatalyst

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Authors: Cheng-Yang Lee, Petrus Tang, Tzu-Hao Chang

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Copy number variations (CNVs) have played an important role in many kinds of human diseases, such as Autism, Schizophrenia and a number of cancers. Many diseases are found in genome coding regions and whole exome sequencing (WES) is a cost-effective and powerful technology in detecting variants that are enriched in exons and have potential applications in clinical setting. Although several algorithms have been developed to detect CNVs using WES and compared with other algorithms for finding the most suitable methods using their own samples, there were not consistent datasets across most of algorithms to evaluate the ability of CNV detection. On the other hand, most of algorithms is using command line interface that may greatly limit the analysis capability of many laboratories. We create a series of simulated WES datasets from UCSC hg19 chromosome 22, and then evaluate the CNV detective ability of 19 algorithms from OMICtools database using our simulated WES datasets. We compute the sensitivity, specificity and accuracy in each algorithm for validation of the exome-derived CNVs. After comparison of 19 algorithms from OMICtools database, we construct a platform to install all of the algorithms in a virtual machine like VirtualBox which can be established conveniently in local computers, and then create a simple script that can be easily to use for detecting CNVs using algorithms selected by users. We also build a table to elaborate on many kinds of events, such as input requirement, CNV detective ability, for all of the algorithms that can provide users a specification to choose optimum algorithms.

Keywords: whole exome sequencing, copy number variations, omictools, pipeline

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Authors: Caroline Denaes

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The ability to read is crucial for a successful path in school and in a social and professional context. Children with mild intellectual disability are confronted to serious difficulties in literacy. A lot of them do not read or are illiterate. Only one child out of five is able to acquire basic reading skills, which increases the likelihood to misfit in society, especially when these children grow up and cannot manage themselves in situations requiring higher reading levels. One way to help these children acquiring basic reading skills is to use analogical reasoning, as some researchers demonstrated that this mechanism is fundamental for any reading process. For this purpose, we developed computerized analogies displayed on a touch screen tablet. Analogies are comparisons that give children a framework they can use to understand new information. They work by comparing one thing to another in order to emphasize some mutual quality. If one of the items is unfamiliar, that mutual quality can help make it understandable, or it can cause the children to consider something familiar in some new way, such as transferring what they know about familiar words to help them identify unfamiliar words. In addition, using touch screen tablets represents several advantages: the ease of use, the relevance to this specific population and the appeal of a self-directed activity gives individuals and practitioners a modern tool that differs from the traditional paper-and-pencil material. In addition, the touch screen dimension is especially appropriate for children as assistive technology has been found to be more motivating that any other types of devices and improves the children’ attention span.

Keywords: literacy, intellectual disabilities, touch screen techonology, literacy skill

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Authors: Alfredo Fortunato, Carmelofrancesco Origlia, Sara Laurita, Rossella Nicoletti

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In the post-pandemic recovery phase of tourism, the role of a Destination Management Organization (DMO) as a coordinated management system of all the elements that make up a destination (attractions, access, marketing, human resources, brand, pricing, etc.) is also becoming relevant for local territories. The objective of a DMO is to maximize the visitor's perception of value and quality while ensuring the competitiveness and sustainability of the destination, as well as the long-term preservation of its natural and cultural assets, and to catalyze benefits for the local economy and residents. In carrying out the multiple functions to which it is called, the DMO can leverage a collective intelligence that comes from the ability to pool information, explicit and tacit knowledge, and relationships of the various stakeholders: policymakers, public managers and officials, entrepreneurs in the tourism supply chain, researchers, data journalists, schools, associations and committees, citizens, etc. The DMO potentially has at its disposal large volumes of data and many of them at low cost, that need to be properly processed to produce value. Based on these assumptions, the paper presents a conceptual framework for building an information system to support the DMO in the intelligent management of a tourist destination tested in an area of southern Italy. The approach adopted is data-informed and consists of four phases: (1) formulation of the knowledge problem (analysis of policy documents and industry reports; focus groups and co-design with stakeholders; definition of information needs and key questions); (2) research and metadatation of relevant sources (reconnaissance of official sources, administrative archives and internal DMO sources); (3) gap analysis and identification of unconventional information sources (evaluation of traditional sources with respect to the level of consistency with information needs, the freshness of information and granularity of data; enrichment of the information base by identifying and studying web sources such as Wikipedia, Google Trends, Booking.com, Tripadvisor, websites of accommodation facilities and online newspapers); (4) definition of the set of indicators and construction of the information base (specific definition of indicators and procedures for data acquisition, transformation, and analysis). The framework derived consists of 6 thematic areas (accommodation supply, cultural heritage, flows, value, sustainability, and enabling factors), each of which is divided into three domains that gather a specific information need to be represented by a scheme of questions to be answered through the analysis of available indicators. The framework is characterized by a high degree of flexibility in the European context, given that it can be customized for each destination by adapting the part related to internal sources. Application to the case study led to the creation of a decision support system that allows: •integration of data from heterogeneous sources, including through the execution of automated web crawling procedures for data ingestion of social and web information; •reading and interpretation of data and metadata through guided navigation paths in the key of digital story-telling; •implementation of complex analysis capabilities through the use of data mining algorithms such as for the prediction of tourist flows.

Keywords: collective intelligence, data framework, destination management, smart tourism

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Authors: Mubeshera Tufail

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The purpose of the study was to explore the experiences and challenges faced by teachers and students with Flipped Classroom Instruction (FCI) for an undergraduate course at university level. The Flipped Classroom lesson plan consisted of two components: one was out-of-class component consisting of learning material for reading for students and other was within-class component involving a class quiz, class activity and the feedback/further reading task. Besides, experiences, the research study also covered the adaptations made to improve their experiences with Flipped Classroom during the study. The phenomenological research strategy was used for this research study. The data consisted of weekly reflective journals documented by class teacher and students. The reflective journals were recorded by teacher and students while working in Flipped Classroom for an undergraduate course at university level. The main challenges highlighted by teacher were related to effort and time required for planning, time management and students' guidance for shift of their role from passive to independent learner. The main challenges found in reflective journals of students were personal computers issue, electricity and internet speed issue. It is recommended to adapt to some locally useful lesson planning and classroom management techniques to enhance the effectiveness of Flipped Classroom Instruction in an undergraduate university level course.

Keywords: flipped classroom instruction, undergraduate students, independent learner, technology-integrated classroom

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Authors: Aleksandra Bylinska, Samantha Slight-Webb, Kevin Thomas, Miles Smith, Susan Macwana, Nicolas Dominguez, Eliza Chakravarty, Joan T. Merrill, Judith A. James, Joel M. Guthridge

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Background: Systemic Lupus Erythematosus (SLE) is an interferon-related autoimmune disease characterized by B cell dysfunction. One of the main hallmarks is a loss of tolerance to self-antigens leading to increased levels of autoantibodies against nuclear components (ANAs). However, up to 20% of healthy ANA+ individuals will not develop clinical illness. SLE is more prevalent among women and minority populations (African, Asian American and Hispanics). Moreover, African Americans have a stronger interferon (IFN) signature and develop more severe symptoms. The exact mechanisms involved in ethnicity-dependent B cell dysregulation and the progression of autoimmune disease from ANA+ healthy individuals to clinical disease remains unclear. Methods: Peripheral blood mononuclear cells (PBMCs) from African (AA) and European American (EA) ANA- (n=12), ANA+ (n=12) and SLE (n=12) individuals were assessed by multimodal scRNA-Seq/CITE-Seq methods to examine differential gene signatures in specific B cell subsets. Library preparation was done with a 10X Genomics Chromium according to established protocols and sequenced on Illumina NextSeq. The data were further analyzed for distinct cluster identification and differential gene signatures in the Seurat package in R and pathways analysis was performed using Ingenuity Pathways Analysis (IPA). Results: Comparing all subjects, 14 distinct B cell clusters were identified using a community detection algorithm and visualized with Uniform Manifold Approximation Projection (UMAP). The proportion of each of those clusters varied by disease status and ethnicity. Transitional B cells trended higher in ANA+ healthy individuals, especially in AA. Ribonucleoprotein high population (HNRNPH1 elevated, heterogeneous nuclear ribonucleoprotein, RNP-Hi) of proliferating Naïve B cells were more prevalent in SLE patients, specifically in EA. Interferon-induced protein high population (IFIT-Hi) of Naive B cells are increased in EA ANA- individuals. The proportion of memory B cells and plasma cells clusters tend to be expanded in SLE patients. As anticipated, we observed a higher signature of cytokine-related pathways, especially interferon, in SLE individuals. Pathway analysis among AA individuals revealed an NRF2-mediated Oxidative Stress response signature in the transitional B cell cluster, not seen in EA individuals. TNFR1/2 and Sirtuin Signaling pathway genes were higher in AA IFIT-Hi Naive B cells, whereas they were not detected in EA individuals. Interferon signaling was observed in B cells in both ethnicities. Oxidative phosphorylation was found in age-related B cells (ABCs) for both ethnicities, whereas Death Receptor Signaling was found only in EA patients in these cells. Interferon-related transcription factors were elevated in ABCs and IFIT-Hi Naive B cells in SLE subjects of both ethnicities. Conclusions: ANA+ healthy individuals have altered gene expression pathways in B cells that might drive apoptosis and subsequent clinical autoimmune pathogenesis. Increases in certain regulatory pathways may delay progression to SLE. Further, AA individuals have more elevated activation pathways that may make them more susceptible to SLE.

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Authors: Yan-Lin Liu, Cheng-Ting Shih, Jay Wu

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Tablet devices have been introduced into the medical environment in recent years. The performance of display can be varied based on the use of different hardware specifications and types of display technologies. Therefore, the differences between tablet devices and medical diagnostic LCDs have to be verified to ensure that image quality is not jeopardized for clinical diagnosis in a picture archiving and communication system (PACS). In this study, a set of randomized object test patterns (ROTPs) were developed, which included randomly located spheres in abdominal CT images. Five radiologists were asked to independently review the CT images on different generations of iPads and a diagnostic monochrome medical LCD monitor. Receiver operating characteristic (ROC) analysis was performed by using a five-point rating scale, and the average area under curve (AUC) and average reading time (ART) were calculated. The AUC values for the second generation iPad, iPad mini, iPad Air, and monochrome medical monitor were 0.712, 0.717, 0.725, and 0.740, respectively. The differences between iPads were not significant. The ARTs were 177 min and 127 min for iPad mini and medical LCD monitor, respectively. A significant difference appeared (p = 0.04). The results show that the iPads were slightly inferior to the monochrome medical LCD monitor. However, tablet devices possess advantages in portability and versatility, which can improve the convenience of rapid diagnosis and teleradiology. With advances in display technology, the applicability of tablet devices and mobile devices may be more diversified in PACS.

Keywords: tablet devices, PACS, receiver operating characteristic, LCD monitor

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Authors: Li Chin Law, Epaminondas Mastorakos, Mohd Roslee Othman, Antonis Trakakis

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The paper introduces an alternative concept of carbon capture for shipping by using pre-combustion carbon capture technology (Pre-CCS), which was proven to be less energy intensive than post-combustion carbon capture from the engine exhaust. Energy assessment on amine-based post-combustion CCS on LNG-fuelled ships showed that the energy efficiency of CCS ships reduced from 48% to 36.6%. Then, an energy assessment was carried out to compare the power and heat requirements of the most used hydrogen production methods and carbon capture technologies. Steam methane reformer (SMR) was found to be 20% more energy efficient and achieved a higher methane conversion than auto thermal reaction and methane decomposition. Next, pressure swing adsorber (PSA) has shown a lower energy requirement than membrane separation, cryogenic separation, and amine absorption in pre-combustion carbon capture. Hence, an integrated system combining SMR and PSA (SMR-PSA) with waste heat integration (WHR) was proposed. This optimized SMR-based integrated system has achieved 65% of CO₂ reduction with less than 7-percentage point of energy penalty (41.7% of energy efficiency). Further integration of post-combustion CCS with the SMR-PSA integrated system improved carbon capture rate to 86.3% with 9-percentage points of energy penalty (39% energy efficiency). The proposed system was shown to be able to meet the carbon reduction targets set by International Maritime Organization (IMO) with certain energy penalties.

Keywords: shipping, decarbonisation, alternative fuels, low carbon, hydrogen, carbon capture

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Authors: Prince S. Campbell, Janine B. Adams, Melusi Thwala, Opeoluwa Oyedele, Paula E. Melariri

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Schistosomiasis is an infectious water-borne disease that holds substantial medical and veterinary importance and is transmitted by Schistosoma flatworms. The transmission and spread of the disease are geographically and temporally confined to water bodies (rivers, lakes, lagoons, dams, etc.) inhabited by its obligate intermediate host snails and human water contact. Human infection with the parasite occurs via skin penetration subsequent to exposure to water infested with schistosome cercariae. Environmental factors play a crucial role in the spread of the disease, as the survival of intermediate host snails is dependent on favourable conditions. These factors include physical and chemical components of water, including pH, salinity, temperature, electrical conductivity, dissolved oxygen, turbidity, water hardness, total dissolved solids, and velocity, as well as biological factors such as predator-prey interactions, competition, food availability, and the presence and density of aquatic vegetation. This study evaluated the physicochemical properties of the water bodies, vegetation type, distribution, and habitat presence of the snail intermediate host. A quantitative cross-sectional research design approach was employed in this study. Eight sampling sites were selected based on their proximity to residential areas. Snails and water physicochemical properties were collected over different seasons for 9 months. A simple dip method was used for surface water samples and measurements were done using multiparameter meters. Snails captured using a 300 µm mesh scoop net and predominant plant species were gathered and transported to experts for identification. Vegetation composition and cover were visually estimated and recorded at each sampling point. Data was analysed using R software (version 4.3.1). A total of 844 freshwater snails were collected, with Physa genera accounting for 95.9% of the snails. Bulinus and Biomphalaria snails, which serve as intermediate hosts for the disease, accounted for (0.9%) and (0.6%) respectively. Indicator macrophytes such as Eicchornia crassipes, Stuckenia pectinate, Typha capensis, and floating macroalgae were found in several water bodies. A negative and weak correlation existed between the number of snails and physicochemical properties such as electrical conductivity (r=-0.240), dissolved oxygen (r=-0.185), hardness (r=-0.210), pH (r=-0.235), salinity (r=-0.242), temperature (r=-0.273), and total dissolved solids (r=-0.236). There was no correlation between the number of snails and turbidity (r=-0.070). Moreover, there was a negative and weak correlation between snails and vegetation coverage (r=-0.127). Findings indicated that snail abundance marginally declined with rising physicochemical concentrations, and the majority of snails were located in regions with less vegetation cover. The reduction in Bulinus and Biomphalaria snail populations may also be attributed to other factors, such as competition among the snails. Snails of the Physa genus were abundant due to their noteworthy resilience in difficult environments. These snails have the potential to function as biological control agents in areas where the disease is endemic, as they outcompete other snails, including schistosomiasis intermediate host snails.

Keywords: intermediate host snails, physicochemical properties, schistosomiasis, vegetation type

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Authors: Debabrata Das, Preeti Mishra

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A two-phase anaerobic process combining biohydrogen followed by biomethane (biohythane technology) serves as an environment-friendly and economically sustainable approach for the improved valorization of organic wastes. Suitability of the pure cultures like Klebsiela pneumonia, C. freundii, B. coagulan, etc. and mixed acidogenic cultures for the biohydrogen production was already studied. The characteristics of organic wastes play a critical role in biohydrogen production. The choice of an appropriate combination of complementary organic wastes can vastly improve the bioenergy generation besides achieving the significant cost reduction. Suitability and economic viability of using the groundnut deoiled cake (GDOC), mustard deoiled cake (MDOC), distillers’ dried grain with soluble (DDGS) and algal biomass (AB) as a co-substrate were studied for a biohythane production. Results show that maximum gaseous energy of 20.7, 9.3, 16.7 and 15.6 % was recovered using GDOC, MDOC, DDGS and AB in the two stage biohythane production, respectively. Both GDOC and DDGS were found to be better co-substrates as compared to MDOC and AB in terms of hythane production, respectively. The maximum cumulative hydrogen and methane production of 150 and 64 mmol/L were achieved using GDOC. Further, 98 % reduction in substrate input cost (SIC) was achieved using the co-supplementation procedure.

Keywords: Biohythane, algal biomass, distillers’ dried grain with soluble (DDGS), groundnut deoiled cake (GDOC), mustard deoiled cake (MDOC)

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Authors: Elina Bakhtieva

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The variety of available digital tools, strategies and activities might confuse and disorient even an experienced marketer. This applies in particular to B2B companies, which are usually less flexible in uptaking of digital technology than B2C companies. B2B companies are lacking a framework that corresponds to the specifics of the B2B business, and which helps to evaluate a company’s capabilities and to choose an appropriate path. A B2B digital marketing maturity model helps to fill this gap. However, modern marketing offers no widely approved digital marketing maturity model, and thus, some marketing institutions provide their own tools. The purpose of this paper is building an optimized B2B digital marketing maturity model based on a SWOT (strengths, weaknesses, opportunities, and threats) analysis of existing models. The current study provides an analytical review of the existing digital marketing maturity models with open access. The results of the research are twofold. First, the provided SWOT analysis outlines the main advantages and disadvantages of existing models. Secondly, the strengths of existing digital marketing maturity models, helps to identify the main characteristics and the structure of an optimized B2B digital marketing maturity model. The research findings indicate that only one out of three analyzed models could be used as a separate tool. This study is among the first examining the use of maturity models in digital marketing. It helps businesses to choose between the existing digital marketing models, the most effective one. Moreover, it creates a base for future research on digital marketing maturity models. This study contributes to the emerging B2B digital marketing literature by providing a SWOT analysis of the existing digital marketing maturity models and suggesting a structure and main characteristics of an optimized B2B digital marketing maturity model.

Keywords: B2B digital marketing strategy, digital marketing, digital marketing maturity model, SWOT analysis

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Authors: M. Hadavi, Z. Hashemi

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Learning strategies play an important role in the development of language skills. Vocabulary learning strategies as the backbone of these strategies have become a major part of English language teaching. This study is a comparative analysis of Vocabulary Learning Strategies (VLS) use and preference among freshmen and senior EFL medical sciences students with different fields of study. 449 students (236 freshman and 213 seniors) participated in the study. 64.6% were female and 35.4% were male. The instrument utilized in this research was a questionnaire consisting of 41 items related to the students’ approach to vocabulary learning. The items were classified under eight sections as dictionary strategies, guessing strategies, study preferences, memory strategies, autonomy, note- taking strategies, selective attention, and social strategies. The participants were asked to answer each item with a 5-point Likert-style frequency scale as follows:1) I never or almost never do this, 2) I don’t usually do this, 3) I sometimes do this, 4) I usually do this, and 5)I always or almost always do this. The results indicated that freshmen students and particularly surgical technology students used more strategies compared to the seniors. Overall guessing and dictionary strategies were the most frequently used strategies among all the learners (p=0/000). The mean and standard deviation of using VLS in the students who had no previous history of participating in the private English language classes was less than the students who had attended these type of classes (p=0/000). Female students tended to use social and study preference strategies whereas male students used mostly guessing and dictionary strategies. It can be concluded that the senior students under instruction from the university have learned to rely on themselves and choose the autonomous strategies more, while freshmen students use more strategies that are related to the study preferences.

Keywords: vocabulary leaning strategies, medical sciences, students, linguistics

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Authors: Mei-Hui Liu

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This study examines the effectiveness of a blended professional development program on preservice EFL (English as a foreign language) teachers’ learning to teach speech acts with the advent of Information and Communication Technology, researchers and scholars underscore the significance of integrating online and face-to-face learning opportunities in the teacher education field. Yet, a paucity of evidence has been documented to investigate the extent to which such a blended professional learning model may impact real classroom practice and student learning outcome. This yearlong project involves various stakeholders, including 25 preservice teachers, 5 English professionals, and 45 secondary school students. Multiple data sources collected are surveys, interviews, reflection journals, online discussion messages, artifacts, and discourse completion tests. Relying on the theoretical lenses of Community of Inquiry, data analysis depicts the nature and process of preservice teachers’ professional development in this blended learning community, which triggers and fosters both face-to-face and synchronous/asynchronous online interactions among preservice teachers and English professionals (i.e., university faculty and in-service teachers). Also included is the student learning outcome after preservice teachers put what they learn from the support community into instructional practice. Pedagogical implications and research suggestions are further provided based on the research findings and limitations.

Keywords: blended professional development, preservice EFL teachers, speech act instruction, student learning outcome

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Authors: Salako Emmanuel Adekunle

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Computer education is referred to as the knowledge and ability to use computers and related technology efficiently, with a range of skills covering levels from basic use to advance. Computer continues to make an ever-increasing impact on all aspect of human endeavours such as education. With numerous benefits of computer education, what are the insights of students on computer education? This study investigated the perception of senior secondary school students on computer education in Federal Capital Territory (FCT), Abuja, Nigeria. A sample of 7500 senior secondary schools students was involved in the study, one hundred (100) private and fifty (50) public schools within FCT. They were selected by using simple random sampling technique. A questionnaire [PSSSCEQ] was developed and validated through expert judgement and reliability co-efficient of 0.84 was obtained. It was used to gather relevant data on computer education. Findings confirmed that the students in the FCT had positive perception on computer education. Some factors were identified that affect students’ perception on computer education. The null hypotheses were tested using t-test and ANOVA statistical analyses at 0.05 level of significance. Based on these findings, some recommendations were made which include competent teachers should be employed into all secondary schools; this will help students to acquire relevant knowledge in computer education, technological supports should be provided to all secondary schools; this will help the users (students) to solve specific problems in computer education and financial supports should be provided to procure computer facilities that will enhance the teaching and the learning of computer education.

Keywords: computer education, perception, secondary school, students

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Authors: Laila Habiballah, Ahmad Tubaishat

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Background: with the development of information and communication technology, using the internet as a source to obtain health information is increasing. Nursing students as future health care providers should have the skills of locating, evaluating and using online health information. This will enable them to help their patients and families to make informed decisions. Aim: this study has a two-fold aim. The first is to assess the eHealth literacy among nursing students in Jordan. The second aim is to explore the factors that have an effect on the eHealth literacy. Methods: this is a descriptive cross-sectional survey that conducted in two universities in Jordan; public and private one. A number of 541 students from both universities were completed the eHEALS scale, which is an instrument designed to measure the eHealth literacy. Some additional personal and demographical variable were collected to explore its effect on eHealth literacy. Results: Students have a high perceived level of e-Health literacy (M=3.62, SD=0.58). They are aware of the available online health resources, know how to search, locate, and use these resources. But, they do not have the skills to evaluate these resources and cannot differentiate between the high and low-quality resources. The results showed as well that type of university, type of students' admission, academic level, students' skills of using the internet, and the perception of usefulness and importance of internet have an effect on the eHealth literacy. While the age, gender, GPA, and the frequency of using the internet was no significant factors. Conclusion: This study represents a baseline reference for the eHealth literacy in Jordan. Students have some skills of eHealth literacy and other skills need to be improved. Nursing educators and administrators should integrate and incorporate the skills of eHealth literacy in the curriculum.

Keywords: eHealth, literacy, nursing, students, Jordan

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Authors: Zunaira Asif, Zhi Chen

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The sustainable measures on air quality management are recognized as one of the most serious environmental concerns in the mining region. The mining operations emit various types of pollutants which have significant impacts on the environment. This study presents a stochastic control strategy by developing the air pollution control model to achieve a cost-effective solution. The optimization method is formulated to predict the cost of treatment using linear programming with an objective function and multi-constraints. The constraints mainly focus on two factors which are: production of metal should not exceed the available resources, and air quality should meet the standard criteria of the pollutant. The applicability of this model is explored through a case study of an open pit metal mine, Utah, USA. This method simultaneously uses meteorological data as a dispersion transfer function to support the practical local conditions. The probabilistic analysis and the uncertainties in the meteorological conditions are accomplished by Monte Carlo simulation. Reasonable results have been obtained to select the optimized treatment technology for PM_2.5, PM₁₀, NO_x, and SO₂. Additional comparison analysis shows that baghouse is the least cost option as compared to electrostatic precipitator and wet scrubbers for particulate matter, whereas non-selective catalytical reduction and dry-flue gas desulfurization are suitable for NO_x and SO₂ reduction respectively. Thus, this model can aid planners to reduce these pollutants at a marginal cost by suggesting control pollution devices, while accounting for dynamic meteorological conditions and mining activities.

Keywords: air pollution, linear programming, mining, optimization, treatment technologies

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Authors: Anubhav Kumar Dwivedi, Arshad Khan, S. N. Tripathi, Manish Joshi, Gaurav Mishra, Dinesh Nath, Naveen Tiwari, B. K. Sapra

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In a nuclear reactor accident scenario, a large number of fission products may release to the piping system of the primary heat transport. The released fission products, mostly in the form of the aerosol, get deposited on the inner surface of the piping system mainly due to gravitational settling and thermophoretic deposition. The removal processes in the complex piping system are controlled to a large extent by the thermal-hydraulic conditions like temperature, pressure, and flow rates. These parameters generally vary with time and therefore must be carefully monitored to predict the aerosol behavior in the piping system. The removal process of aerosol depends on the size of particles that determines how many particles get deposit or travel across the bends and reach to the other end of the piping system. The released aerosol gets deposited onto the inner surface of the piping system by various mechanisms like gravitational settling, Brownian diffusion, thermophoretic deposition, and by other deposition mechanisms. To quantify the correct estimate of deposition, the identification and understanding of the aforementioned deposition mechanisms are of great importance. These mechanisms are significantly affected by different flow and thermodynamic conditions. Thermophoresis also plays a significant role in particle deposition. In the present study, a series of experiments were performed in the piping system of the National Aerosol Test Facility (NATF), BARC using metal aerosols (zinc) in dry environments to study the spatial distribution of particles mass and number concentration, and their depletion due to various removal mechanisms in the piping system. The experiments were performed at two different carrier gas flow rates. The commercial CFD software FLUENT is used to determine the distribution of temperature, velocity, pressure, and turbulence quantities in the piping system. In addition to the in-built models for turbulence, heat transfer and flow in the commercial CFD code (FLUENT), a new sub-model PBM (population balance model) is used to describe the coagulation process and to compute the number concentration along with the size distribution at different sections of the piping. In the sub-model coagulation kernels are incorporated through user-defined function (UDF). The experimental results are compared with the CFD modeled results. It is found that most of the Zn particles (more than 35 %) deposit near the inlet of the plenum chamber and a low deposition is obtained in piping sections. The MMAD decreases along the length of the test assembly, which shows that large particles get deposited or removed in the course of flow, and only fine particles travel to the end of the piping system. The effect of a bend is also observed, and it is found that the relative loss in mass concentration at bends is more in case of a high flow rate. The simulation results show that the thermophoresis and depositional effects are more dominating for the small and larger sizes as compared to the intermediate particles size. Both SEM and XRD analysis of the collected samples show the samples are highly agglomerated non-spherical and composed mainly of ZnO. The coupled model framed in this work could be used as an important tool for predicting size distribution and concentration of some other aerosol released during a reactor accident scenario.

Keywords: aerosol, CFD, deposition, coagulation

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Authors: W. Abu Rayyan, A. Singh, A. M. Al-Jaafreh, W. Abu Dayyih, M. Bustami, S. Salem, N. Seder, K. Schröppel

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Hyphal growth and the transcriptional regulation to the host environment are key issues during the pathogenesis of C. albicans. Tec1p is the C. albicans homolog of a TEA transcription factor family, which share a conserved DNA-binding TEA domain in their N-terminal. In order to define a structure-function relationship of the C. albicans Tec1p protein, we constructed several mutations on the N terminal, C terminal or in the TEA binding domain itself by homologous recombination technology. The modifications in the open reading frame of TEC1 were tested for reconstitution of the morphogenetic development of the tec1/tec1 mutant strain CaAS12. Mutation in the TEA consensus sequence did not confer transition to hyphae whereas the reconstitution of the full-length Tec1p has reconstituted hyphal development. A deletion in one of glutamine-rich regions either in the Tec1p N-terminal or the C-terminal in regions of 53-212 or 637–744 aa, respectively, did not restore morphological development in mutant CaAS12 strain. Whereas, the reconstitution with Tec1p mutants other than the glutamate-rich region has restored the morphogenetic switch. Additionally, the deletion of the glutamine-rich region has attenuated the invasive growth and the heat shock resistance of C. albicans. In conclusion, we show that a glutamine-rich region of Tec1p is essential for the hyphal development and mediating adaptation to the host environment of C. albicans.

Keywords: Candida albicans, morphogenetic development, TEA domain, hyphal formation, TEC1

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Authors: E. Mas de les Valls, M. Castells-Sanabra, R. Capdevila, N. Pla, Rosa M. Fernandez-Canti, V. de Medina, A. Mujal, C. Barahona, E. Velo, M. Vigo, M. A. Santos, T. Soto

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Absenteeism in universities, including polytechnical universities, is influenced by a variety of factors. Some factors overlap with those causing absenteeism in schools, while others are specific to the university and work-related environments. Indeed, these factors may stem from various sources, including students, educators, the institution itself, or even the alignment of degree curricula with professional requirements. In Spain, there has been an increase in absenteeism in polytechnical university studies, especially after the Covid crisis, posing a significant challenge for institutions to address. This study focuses on Universitat Politècnica de Catalunya• BarcelonaTech (UPC) and aims to quantify the current level of absenteeism and identify its main causes. The study is part of the teaching innovation project ASAP-UPC, which aims to minimize absenteeism through the redesign of teaching methodologies. By understanding the factors contributing to absenteeism, the study seeks to inform the subsequent phases of the ASAP-UPC project, which involve implementing methodologies to minimize absenteeism and evaluating their effectiveness. The study utilizes surveys conducted among students and polytechnical companies. Students' perspectives are gathered through both online surveys and in-person interviews. The surveys inquire about students' interest in attending classes, skill development throughout their UPC experience, and their perception of the skills required for a career in a polytechnical field. Additionally, polytechnical companies are surveyed regarding the skills they seek in prospective employees. The collected data is then analyzed to identify patterns and trends. This analysis involves organizing and categorizing the data, identifying common themes, and drawing conclusions based on the findings. This mixed-method approach has revealed that higher levels of absenteeism are observed in large student groups at both the Bachelor's and Master's degree levels. However, the main causes of absenteeism differ between these two levels. At the Bachelor's level, many students express dissatisfaction with in-person classes, perceiving them as overly theoretical and lacking a balance between theory, experimental practice, and problem-solving components. They also find a lack of relevance to professional needs. Consequently, they resort to using online available materials developed during the Covid crisis and attending private academies for exam preparation instead. On the other hand, at the Master's level, absenteeism primarily arises from schedule incompatibility between university and professional work. There is a discrepancy between the skills highly valued by companies and the skills emphasized during the studies, aligning partially with students' perceptions. These findings are of theoretical importance as they shed light on areas that can be improved to offer a more beneficial educational experience to students at UPC. The study also has potential applicability to other polytechnic universities, allowing them to adapt the surveys and apply the findings to their specific contexts. By addressing the identified causes of absenteeism, universities can enhance the educational experience and better prepare students for successful careers in polytechnical fields.

Keywords: absenteeism, polytechnical studies, professional skills, university challenges

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Authors: Yogesh C. Sharma, A. Seetharaman

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The decision-making process in humans is a complicated system influenced by a variety of intrinsic and extrinsic factors. Human decisions have a ripple effect on subsequent decisions. In this study, the scope of human decision making is limited to employees. In an organisation, a person makes a variety of decisions from the time they are hired to the time they retire. The goal of this research is to identify various elements that influence decision-making. In addition, the environment in which a decision is made is a significant aspect of the decision-making process. Employees in today's workplace use artificial intelligence (AI) systems for automation and decision augmentation. The impact of AI systems on the decision-making process is examined in this study. This research is designed based on a systematic literature review. Based on gaps in the literature, limitations and the scope of future research have been identified. Based on these findings, a research framework has been designed to identify various factors affecting employee decision making. Employee decision making is influenced by technological advancement, data-driven culture, human trust, decision automation-augmentation, and workplace motivation. Hybrid human-AI systems require the development of new skill sets and organisational design. Employee psychological safety and supportive leadership influences overall job satisfaction.

Keywords: employee decision making, artificial intelligence (AI) environment, human trust, technology innovation, psychological safety

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Authors: Marie-Therese Claes, Anett Hermann

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With the advent of the web and information technology since the end of the 20ᵗʰ century, digitalization has revolutionized our everyday life, from shopping and dating to education and transportation. The world of work is one of the areas that has been highly transformed by changing the time and spatial limits of the work. The expansion of the internet, wireless, and easily portable devices such as laptop computers and mobile phones has enabled us to work almost from any place at any time. As a result, telework, which started in the 1950s and elevated in the 1970s, steeply raised to a new level in 21ˢᵗ century. Telework consists of various forms of work done from outside the traditional workplace by using information technologies. The social distancing and lockdown measures that have been taken to reduce the spread of the virus in many countries worldwide resulted in an increasing number of teleworkers and made “working from home’’ synonymous with telework. Post-COVID-19, the number of teleworkers is still higher than before the pandemic period, and the interest in expanding teleworking has been growing too. Notwithstanding the advantages ushered by telework, it also has a number of drawbacks that negatively affect organizations and employees. The intention of this piece of work is not to indicate a causational relationship between telework and discrimination. Our aim is to indicate some unintended and/or unnoticed deleterious effects of telework in reinforcing discrimination and to instigate discussion on how to mitigate the effects. To do so, this insight indicates how telework reinforces traditional gender roles and how organizational culture towards telework and its access to employees at different levels of the organizational hierarchy opens the room for discrimination.

Keywords: mobile work, discrimination, gender roles, organizational culture

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Authors: Ramada R. Khasawneh, Mohammed Z. Allouh, Ejlal Abu-El Rub

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The quadriceps angle (Q angle), formed between the quadriceps muscles and the patella tendon, is considered clinically as a very important parameter which displays the biomechanical effect of the quadriceps muscle on the knee, and it is also regarded as a crucial factor for the proper posture and movement of the knee patella. This study had been conducted to measure the normal Q angle values range in the Arab nationalities and determine the correlation between Q angle values and several body parameters, including gender, height, weight, dominant side, and the condylar distance of the femur. The study includes 500 healthy Arab students from Yarmouk University and Jordan University of Science and Technology. The Q angle of those volunteers was measured using a universal manual Goniometer with the subjects in the upright weight-bearing position. It was found that the Q angle was greater in women than in men. The analysis of the data revealed an insignificant increase in the dominant side of the Q angle. In addition, the Q was significantly higher in the taller people of both sexes. However, the Q angle did not present any considerable correlation with weight in the study population; conversely, it was observed that there was a link with the condylar distance of the femur in both sexes. It was also noticed that the Q angle increased remarkably when there was an increase in the condylar distance. Consequently, it turned out that the gender, height, and the condylar distance were momentous factors that had an impact on the Q angle in our study samples. However, weight and dominance factors did not show to have any influence on the values in our study.

Keywords: Q angle, Jordanian, anatomy, condylar distance

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Authors: Simone Medio

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If we observe many modern cities from above, we are typically confronted with a sea of asphalt-clad flat rooftops. In contrast to the modernist expectation of a populated flat roof, flat rooftops in modern multi-story buildings are rarely used. On the contrary, they typify a desolate and abandoned landscape encouraging mechanical system allocation. Flat roof technology continues to be seen as a state-of-fact in most multi-storey building designs and its greening its prevalent environmental justification. This paper aims to seek a change in the approach to flat roofing. It makes a case for the opportunity at hand for architectonically resolute, sheltered, livable spaces that make a better use of the environment at rooftop level. The researcher is looking for the triggers that allow for that change to happen in the design process of case study buildings. The paper begins by exploring Han Slawick covered roof terrace in Amsterdam as a simple and essential example of transforming the flat roof in a usable, inhabitable space. It investigates the design challenges and the logistic, financial and legislative hurdles faced by the architect, and the outcomes in terms of building performance and occupant use and satisfaction. The researcher uses a grounded research methodology with direct interview process to the architect in charge of the building and the building user. Energy simulation tools and calculation of running costs are also used as further means of validating change.

Keywords: environmental design, flat rooftop persistence, roof re-habitation, tectonics

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Authors: Jehnming Lin

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The effects of the contact ball-lens on the soda lime glass in laser thermal cleavage with a cw Nd-YAG laser were investigated in this study. A contact ball-lens was adopted to generate a bending force on the crack formation of the soda-lime glass in the laser cutting process. The Nd-YAG laser beam (wavelength of 1064 nm) was focused through the ball-lens and transmitted to the soda-lime glass, which was coated with a carbon film on the surface with a bending force from a ball-lens to generate a tensile stress state on the surface cracking. The fracture was controlled by the contact ball-lens and a straight cutting was tested to demonstrate the feasibility. Experimental observations on the crack propagation from the leading edge, main section and trailing edge of the glass sheet were compared with various mechanical and thermal loadings. Further analyses on the stress under various laser powers and contact ball loadings were made to characterize the innovative technology. The results show that the distributions of the side crack at the leading and trailing edges are mainly dependent on the boundary condition, contact force, cutting speed and laser power. With the increase of the mechanical and thermal loadings, the region of the side cracks might be dramatically reduced with proper selection of the geometrical constraints. Therefore, the application of the contact ball-lens is a possible way to control the fracture in laser cleavage with improved cutting qualities.

Keywords: laser cleavage, stress analysis, crack visualization, laser

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Authors: Stelios A. Mitilineos, Nicolas-Alexander Tatlas, Georgia Korompili, Lampros Kokkalas, Stelios M. Potirakis

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Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS) is a widespread chronic disease that mostly remains undetected, mainly due to the fact that it is diagnosed via polysomnography which is a time and resource-intensive procedure. Screening the disease’s symptoms at home could be used as an alternative approach in order to alert individuals that potentially suffer from OSAHS without compromising their everyday routine. Since snoring is usually linked to OSAHS, developing a snore detector is appealing as an enabling technology for screening OSAHS at home using ubiquitous equipment like commodity microphones (included in, e.g., smartphones). In this context, this study developed a snore detection tool and herein present the approach and selection of specific sound features that discriminate snoring vs. environmental sounds, as well as the performance of the proposed tool. Furthermore, a Real-Time Snore Detector (RTSD) is built upon the snore detection tool and employed in whole-night sleep sound recordings resulting to a large dataset of snoring sound excerpts that are made freely available to the public. The RTSD may be used either as a stand-alone tool that offers insight to an individual’s sleep quality or as an independent component of OSAHS screening applications in future developments.

Keywords: obstructive sleep apnea hypopnea syndrome, apnea screening, snoring detection, machine learning, neural networks

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Authors: Nazli Hardy

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Multidisciplinary application of computer science, interactive database-driven web application, the Internet of Things (IoT) represents a digital ecosystem that has pervasive technological, social, and economic, impact on the human population. It is a long-term technology, and its development is built around the connection of everyday objects, to the Internet. It is estimated that by 2020, with billions of people connected to the Internet, the number of connected devices will exceed 50 billion, and thus IoT represents a paradigm shift in in our current interconnected ecosystem, a communication shift that will unavoidably affect people, businesses, consumers, clients, employees. By nature, in order to provide a cohesive and integrated service, connected devices need to collect, aggregate, store, mine, process personal and personalized data on individuals and corporations in a variety of contexts and environments. A significant factor in this paradigm shift is the necessity for secure and appropriate transmission, processing and storage of the data. Thus, while benefits of the applications appear to be boundless, these same opportunities are bounded by concerns such as trust, privacy, security, loss of control, and related issues. This poster and presentation look at a multi-factor authentication (MFA) mechanisms that need to change from the login-password tuple to an Identity and Access Management (IAM) model, to the more cohesive to Identity Relationship Management (IRM) standard. It also compares and contrasts messaging protocols that are appropriate for the IoT ecosystem.

Keywords: Internet of Things (IoT), authentication, protocols, survey

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Authors: Ji-Seok Koo, Hee‑Yong Kwon, Hui-Young Yun, Kyung-Hui Wang, Youn-Seo Koo

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This paper presents a forecasting system for PM2.5 levels in Seoul, South Korea, leveraging a combination of chemical transport modeling and ConvLSTM-DNN machine learning technology. Exposure to PM2.5 has known detrimental impacts on public health, making its prediction crucial for establishing preventive measures. Existing forecasting models, like the Community Multiscale Air Quality (CMAQ) and Weather Research and Forecasting (WRF), are hindered by their reliance on uncertain input data, such as anthropogenic emissions and meteorological patterns, as well as certain intrinsic model limitations. The system we've developed specifically addresses these issues by integrating machine learning and using carefully selected input features that account for local and distant sources of PM2.5. In South Korea, the PM2.5 concentration is greatly influenced by both local emissions and long-range transport from China, and our model effectively captures these spatial and temporal dynamics. Our PM2.5 prediction system combines the strengths of advanced hybrid machine learning algorithms, convLSTM and DNN, to improve upon the limitations of the traditional CMAQ model. Data used in the system include forecasted information from CMAQ and WRF models, along with actual PM2.5 concentration and weather variable data from monitoring stations in China and South Korea. The system was implemented specifically for Seoul's PM2.5 forecasting.

Keywords: PM2.5 forecast, machine learning, convLSTM, DNN

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Authors: Roman Khanferyan

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Endurance exercises and strenuous muscle activity are accompanied by multiple immune dysfunctions due to the activation of cytokines and chemokines synthesis. This study assesses changes in the synthesis of immune regulatory mediators in elite athletes during endurance sports activity. The concentrations of cytokines/chemokines (IL-2, IL-6, IL-8, IL-10, IL-18, MIP-1 beta, GRO-alpha, RANTES, SDF-1a, VEGF) in sera of hockey athletes (n=33) and in supernatants of 24-h cultivated peripheral blood mononuclear cells (PBMC) of boxers (n=6) assayed by ELISA and Luminex xMAP multiplex assays. Estimation of body composition studied by using bioimpedance technology. The dietary energy consumption per person has been estimated using an album of different sizes of portions of the most frequently consumed foods. It has been demonstrated that endurance sports activity enhances the secretions of most pro- and anti-inflammatory cytokines and chemokines in more than 2-6 fold. The study demonstrated that the high increase of more than 3-4 times in the concentration of IL-18 in sera of athletes (327.86 + 45.67 pg/ml) didn’t correlate with BMI (p=0.040) but demonstrated a low correlation with MMI (p=0.234) and BMR (p=0,231). The opposite impact on the concentration of IL-10 has been demonstrated in athletes. It has been shown a negative correlation between its concentration and BMI (p= - 0.251), MMI (p= - 0.327), and BMR (p= - 0.301). In vitro studies in boxers showed greater amounts of chemokines in the PBMC supernatants, including MIP-1β, GRO-α, RANTES, SDF-1α, and IL-8 (P<0.05). At the same time, healthy controls had greater supernatant levels of MCP-1, Eotaxin, and MIP-1α. The study demonstrated a high correlation between physical activity, usual athletes' diet, and consumption of specialized sports nutrition products.

Keywords: sport nutrition, cytokines, chemokines, endurace exercises

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Authors: Muhammad Habib, Xuefan Zhou, Lin Tang, Guoliang Xue, Fazli Akram, Dou Zhang

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Defect engineering approach is a well-established approach for the customization of functional properties of perovskite ceramics. In modern technology, the high multiferroic properties for elevated temperature applications are greatly demanding. In this work, the Bi-nonstoichiometric lead-free 0.67Biy-xSmxFeO3-0.33BaTiO3 ceramics (Sm-doped BF-BT for Bi-excess; y = 1.03 and Bi-deficient; y = 0.975 with x = 0.00, 0.04 and 0.08) were design for the high-temperature multiferroic property. Enhanced piezoelectric (d33  250 pC/N and d33* 350 pm/V) and magnetic properties (Mr  0.25 emu/g) with a high Curie temperature (TC  465 ℃) were obtained in the Bi-deficient pure BF-BT ceramics. With Sm-doping (x = 0.04), the TC decrease to 350 ℃ a significant improvement occurred in the d33* to 504 pm/V and 450 pm/V for Bi-excess and Bi-deficient compositions, respectively. The structural origin of the enhanced piezoelectric strain performance is related to the soft ferroelectric effect by Sm-doping and reversible phase transition from the short-range relaxor ferroelectric state to the long-range order under the applied electric field. However, a slight change occurs in the Mr 0.28 emu/g value with Sm-doping for Bi-deficient ceramics, whereas the Bi-excess ceramics shows completely paramagnetic behavior. Hence, the origin of high magnetic properties in the Bi-deficient BF-BT ceramics is mainly attributed to the proposed double exchange mechanism. We believe that this strategy will provide a new perspective for the development of lead-free multiferroic ceramics for high-temperature applications.

Keywords: BiFeO3-BaTiO3, lead-free piezoceramics, magnetic properties, defect engineering

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Authors: Rajvir Kaur, Jeewani Anupama Ginige

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With recent trends in Big Data and advancements in Information and Communication Technologies, the healthcare industry is at the stage of its transition from clinician oriented to technology oriented. Many people around the world die of cancer because the diagnosis of disease was not done at an early stage. Nowadays, the computational methods in the form of Machine Learning (ML) are used to develop automated decision support systems that can diagnose cancer with high confidence in a timely manner. This paper aims to carry out the comparative evaluation of a selected set of ML classifiers on two existing datasets: breast cancer and cervical cancer. The ML classifiers compared in this study are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and Artificial Neural Networks (ANN). The evaluation is carried out based on standard evaluation metrics Precision (P), Recall (R), F1-score and Accuracy. The experimental results based on the evaluation metrics show that ANN showed the highest-level accuracy (99.4%) when tested with breast cancer dataset. On the other hand, when these ML classifiers are tested with the cervical cancer dataset, Ensemble (Bagged Tree) technique gave better accuracy (93.1%) in comparison to other classifiers.

Keywords: artificial neural networks, breast cancer, classifiers, cervical cancer, f-score, machine learning, precision, recall

Procedia PDF Downloads 277