Search results for: grading scales

Authors: Bao Chen, Frederic Kuznik, Matthieu Horgnies, Kevyn Johannes, Vincent Morin, Edouard Gengembre

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The contradiction between energy consumption, environment protection, and social development is increasingly intensified during recent decade years. At the same time, as avoiding fossil-fuels-thirsty, people turn their view on the renewable green energy, such as solar energy, wind power, hydropower, etc. However, due to the unavoidable mismatch on geography and time for production and consumption, energy storage seems to be one of the most reasonable solutions to enlarge the use of renewable energies. Thermal energy storage (TES), a branch of energy storage solution, mainly concerns the capture, storage and consumption of thermal energy for later use in different scales (individual house, apartment, district, and city). In TES research field, sensible heat and latent heat storage have been widely studied and presented at an advanced stage of development. Compared with them, thermochemical energy storage is still at initial phase but provides a relatively higher theoretical energy density and a long shelf life without heat dissipation during storage. Among thermochemical energy storage materials, inorganic pure or composite compounds like micro-porous silica gel, SrBr₂ hydrate and MgSO₄-Zeolithe have been reported as promising to be integrated into thermal energy storage systems. However, the cost of these materials, one of main obstacles, may hinder the wide use of energy storage systems in real application scales (individual house, apartment, district and even city). New studies on ettringite show promising application for thermal energy storage since its high energy density and large resource from cementitious materials. Ettringite, or calcium trisulfoaluminate hydrate, of which chemical formula is 3CaO∙Al₂O₃∙3CaSO₄∙32H₂O, or C₆AS̅₃H₃₂ as known in cement chemistry notation, is one of the most important members of AFt group. As a common compound in hydrated cements, ettringite has been widely studied for its performances in construction but barely known as a thermochemical material. For this study, we summarize available data about the structure and properties of ettringite and its metastable phase (meta-ettringite), including the processes of hydration, thermal conversion and carbonation durability for thermal energy storage.

Keywords: building materials, ettringite, meta-ettringite, thermal energy storage

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Authors: Li Yongyi

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In order to explore the distribution of geological disasters within the expressway area of Shaanxi Province, the Analytic Hierarchy Process theory is applied based on the geographic information system technology platform, and the ground elevation, rainfall, vegetation coverage and other indicators are selected for analysis, and the expressway area is sensitive Sexual evaluation. The results show that the highway area disasters in Shaanxi Province are mainly distributed in the southern mountainous areas and are dominated by landslides; the disaster area ratio basically increases with the increase in ground elevation, surface slope, surface undulation, rainfall, and vegetation coverage. The increase in the distance from the river shows a decreasing trend; after grading the disaster sensitivity within 5km of the expressway, the extremely sensitive area, the highly sensitive area, the medium sensitive area, the low sensitive area, and the extremely low sensitive area respectively account for 8.17%、15.80%、22.99%、26.22%、26.82%. Highly sensitive road areas are mainly distributed in southern Shaanxi.

Keywords: highway engineering, sensitivity, analytic hierarchy process, geological hazard, road area

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Authors: Wei-Kuo Soong

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The forecasting of typhoon tracks remains a formidable challenge, primarily attributable to the paucity of observational data in the open sea and the intricate influence of weather systems at varying scales. This study investigates the case of Typhoon Hinnamnor in 2022, examining its trajectory and intensity fluctuations in relation to the interaction with a concurrent tropical cyclone and sea surface temperatures (SST). Utilizing the Weather Research and Forecasting Model (WRF), to simulate and analyze the interaction between Typhoon Hinnamnor and its environmental factors, shedding light on the mechanisms driving typhoon development and enhancing forecasting capabilities.

Keywords: typhoon, sea surface temperature, forecasting, WRF

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Authors: Siddhant Rao

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Studies estimate that there will be 266,120 new cases of invasive breast cancer and 40,920 breast cancer induced deaths in the year of 2018 alone. Despite the pervasiveness of this affliction, the current process to obtain an accurate breast cancer prognosis is tedious and time consuming. It usually requires a trained pathologist to manually examine histopathological images and identify the features that characterize various cancer severity levels. We propose MITOS-RCNN: a region based convolutional neural network (RCNN) geared for small object detection to accurately grade one of the three factors that characterize tumor belligerence described by the Nottingham Grading System: mitotic count. Other computational approaches to mitotic figure counting and detection do not demonstrate ample recall or precision to be clinically viable. Our models outperformed all previous participants in the ICPR 2012 challenge, the AMIDA 2013 challenge and the MITOS-ATYPIA-14 challenge along with recently published works. Our model achieved an F- measure score of 0.955, a 6.11% improvement in accuracy from the most accurate of the previously proposed models.

Keywords: breast cancer, mitotic count, machine learning, convolutional neural networks

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Authors: Michele Sinico

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The present research investigates the effect of symmetry on the perception of happiness and boredom in design products. Three experiments were carried out in order to verify the degree of the visual expressive value on different models of bookcases, wall clocks, and chairs. 60 participants directly indicated the degree of happiness and boredom using 7-point rating scales. The findings show that the participants acknowledged a different value of expressive quality in the different product models. Results show also that symmetry is not a significant constraint for an emotional design project.

Keywords: product experience, emotional design, symmetry, expressive qualities

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Authors: Yiming Jin, Yuanhao Gao

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In this paper, using the method of multiple scales, the second sub-harmonic resonance in vortex-induced vibrations (VIV) of a marine pipeline close to the seabed is investigated based on a developed wake oscillator model. The amplitude-frequency equations are also derived. It is found that the oscillation will increase all the time when both discriminants of the amplitude-frequency equations are positive while the oscillation will decay when the discriminants are negative.

Keywords: vortex-induced vibrations, marine pipeline, seabed, sub-harmonic resonance

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Authors: Fatma Khadra

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The objective of this research is to identify the acceptance of new technology in a sample of 150 Participants from Qatar University. Based on the Technology Acceptance Model (TAM), we used the Davis’s scale (1989) which contains two item scales for Perceived Usefulness and Perceived Ease of Use. The TAM represents an important theoretical contribution toward understanding how users come to accept and use technology. This model suggests that when people are presented with a new technology, a number of variables influence their decision about how and when they will use it. The results showed that participants accept more technology because flexibility, clarity, enhancing the experience, enjoying, facility, and useful. Also, results showed that younger participants accept more technology than others.

Keywords: new technology, perceived usefulness, perceived ease of use, technology acceptance model

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Authors: Ebenezer O. Olaniyi, Oyebade K. Oyedotun, Khashman Adnan

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In the food industry high quality production is required within a limited time to meet up with the demand in the society. In this research work, we have developed a model which can be used to replace the human operator due to their low output in production and slow in making decisions as a result of an individual differences in deciding the defective and healthy banana. This model can perform the vision attributes of human operators in deciding if the banana is defective or healthy for food production based. This research work is divided into two phase, the first phase is the image processing where several image processing techniques such as colour conversion, edge detection, thresholding and morphological operation were employed to extract features for training and testing the network in the second phase. These features extracted in the first phase were used in the second phase; the classification system phase where the multilayer perceptron using backpropagation neural network was employed to train the network. After the network has learned and converges, the network was tested with feedforward neural network to determine the performance of the network. From this experiment, a recognition rate of 97% was obtained and the time taken for this experiment was limited which makes the system accurate for use in the food industry.

Keywords: banana, food processing, identification system, neural network

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Authors: Minseock Seo

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Dental education consists of both theoretical and practical learning for students. When dental students encounter practical courses as a new educational experience, they must also learn to evaluate themselves. The aim of this study was to investigate the self-assessment scores of third-year dental students and compare with the scores graded by the faculty in preclinical endodontic practice in a dental school in Korea. Faculty- and student-assigned scores were calculated from preclinical endodontic practice performed on phantom patients. The students were formally instructed on grading procedures for endodontic treatment. After each step, each item was assessed by the student. The students’ self-assessment score was then compared to the score by the faculty. The students were divided into 4 groups by analyzing the scores of self-assessment and faculty-assessment and statistically analyzed by summing the theoretical and practical examination scores. In the theoretical exam score, the group who over-estimated their performance (H group) was lower than the group with lower evaluation (L group). When comparing the first and last score determined by the faculty, H groups didn’t show any improvement, while the other group did. In H group, the less improvement of the self-assessment, the higher the theoretical exam score. In L group, the higher improvement of the self-assessment, the better the theoretical exam score. The results point to the need to develop students’ self-insight with more exercises and practical training.

Keywords: dental students, endodontic, preclinical practice, self-assessment

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Authors: Amandeep Sharma, Digvaijay Verma, Ruplal Choudhary

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Food processing is an activity across the globe that help in better handling of agricultural produce, including dairy, meat, and fish. The operations carried out in the food industry includes raw material quality authenticity; sorting and grading; processing into various products using thermal treatments – heating, freezing, and chilling; packaging; and storage at the appropriate temperature to maximize the shelf life of the products. All this is done to safeguard the food products and to ensure the distribution up to the consumer. The approaches to develop predictive models based on mathematical or statistical tools or empirical models’ development has been reported for various milk processing activities, including plant maintenance and wastage. Recently AI is the key factor for the fourth industrial revolution. AI plays a vital role in the food industry, not only in quality and food security but also in different areas such as manufacturing, packaging, and cleaning. A new conceptual model was developed, which shows that smaller sample size as only spectra would be required to predict the other values hence leads to saving on raw materials and chemicals otherwise used for experimentation during the research and new product development activity. It would be a futuristic approach if these tools can be further clubbed with the mobile phones through some software development for their real time application in the field for quality check and traceability of the product.

Keywords: predictive modlleing, ann, ai, food

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Authors: Hina Kausher, Sangita Srivastava

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In India, there is a lack of standard, systematic sizing approach for producing readymade garments. Garments manufacturing companies use their own created size tables by modifying international sizing charts of ready-made garments. The purpose of this study is to tabulate the anthropometric data which covers the variety of figure proportions in both height and girth. 3,000 data has been collected by an anthropometric survey undertaken over females between the ages of 16 to 80 years from some states of India to produce the sizing system suitable for clothing manufacture and retailing. This data is used for the statistical analysis of body measurements, the formulation of sizing systems and body measurements tables. Factor analysis technique is used to filter the control body dimensions from a large number of variables. Decision tree-based data mining is used to cluster the data. The standard and structured sizing system can facilitate pattern grading and garment production. Moreover, it can exceed buying ratios and upgrade size allocations to retail segments.

Keywords: anthropometric data, data mining, decision tree, garments manufacturing, sizing systems, ready-made garments

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Authors: A. Peyvan, D. Li, J. Komperda, F. Mashayek

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Turbulence can be observed in a variety fluid motions in nature and industrial applications. Recent investment in high-speed aircraft and propulsion systems has revitalized fundamental research on turbulent flows. In these systems, capturing chaotic fluid structures with different length and time scales is accomplished through the Direct Numerical Simulation (DNS) approach since it accurately simulates flows down to smallest dissipative scales, i.e., Kolmogorov’s scales. The discontinuous spectral element method (DSEM) is a high-order technique that uses spectral functions for approximating the solution. The DSEM code has been developed by our research group over the course of more than two decades. Recently, the code has been improved to run large cases in the order of billions of solution points. Running big simulations requires a considerable amount of RAM. Therefore, the DSEM code must be highly parallelized and able to start on multiple computational nodes on an HPC cluster with distributed memory. However, some pre-processing procedures, such as determining global element information, creating a global face list, and assigning global partitioning and element connection information of the domain for communication, must be done sequentially with a single processing core. A separate code has been written to perform the pre-processing procedures on a local machine. It stores the minimum amount of information that is required for the DSEM code to start in parallel, extracted from the mesh file, into text files (pre-files). It packs integer type information with a Stream Binary format in pre-files that are portable between machines. The files are generated to ensure fast read performance on different file-systems, such as Lustre and General Parallel File System (GPFS). A new subroutine has been added to the DSEM code to read the startup files using parallel MPI I/O, for Lustre, in a way that each MPI rank acquires its information from the file in parallel. In case of GPFS, in each computational node, a single MPI rank reads data from the file, which is specifically generated for the computational node, and send them to other ranks on the node using point to point non-blocking MPI communication. This way, communication takes place locally on each node and signals do not cross the switches of the cluster. The read subroutine has been tested on Argonne National Laboratory’s Mira (GPFS), National Center for Supercomputing Application’s Blue Waters (Lustre), San Diego Supercomputer Center’s Comet (Lustre), and UIC’s Extreme (Lustre). The tests showed that one file per node is suited for GPFS and parallel MPI I/O is the best choice for Lustre file system. The DSEM code relies on heavily optimized linear algebra operation such as matrix-matrix and matrix-vector products for calculation of the solution in every time-step. For this, the code can either make use of its matrix math library, BLAS, Intel MKL, or ATLAS. This fact and the discontinuous nature of the method makes the DSEM code run efficiently in parallel. The results of weak scaling tests performed on Blue Waters showed a scalable and efficient performance of the code in parallel computing.

Keywords: computational fluid dynamics, direct numerical simulation, spectral element, turbulent flow

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Authors: Yun Chen, David Penton, Fazlul Karim, Santosh Aryal, Shahriar Wahid, Peter Taylor, Susan M. Cuddy

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Droughts have severely affected Afghanistan over the last four decades, leading to critical food shortages where two-thirds of the country’s population are in a food crisis. Long years of conflict have lowered the country’s ability to deal with hazards such as drought, which can rapidly escalate into disasters. Understanding the spatial and temporal distribution of droughts is needed to be able to respond effectively to disasters and plan for future occurrences. This study used Standardized Precipitation Evapotranspiration Index (SPEI) at monthly, seasonal, and annual temporal scales to map the spatiotemporal change dynamics of drought characteristics (distribution, frequency, duration, and severity) in Afghanistan. SPEI indices were mapped for river basins, disaggregated into 189 sub-catchments, using monthly precipitation and potential evapotranspiration derived from temperature station observations from 1980 to 2017. The results show these multi-dimensional drought characteristics vary along different years, change among sub-catchments, and differ across temporal scales. During the 38 years, the driest decade and period are the 2000s and 1999–2022, respectively. The 2000–01 water year is the driest, with the whole country experiencing ‘severe’ to ‘extreme’ drought, more than 53% (87 sub-catchments) suffering the worst drought in history, and about 58% (94 sub-catchments) having ‘very frequent’ drought (7 to 8 months) or ‘extremely frequent’ drought (9 to 10 months). The estimated seasonal duration and severity present significant variations across the study area and throughout the study period. The nation also suffered from recurring droughts with varying length and intensity in 2004, 2006, 2008, and, most recently, 2011. There is a trend towards increasing drought with longer duration and higher severity extending all over sub-catchments from southeast to north and central regions. These datasets and maps help to fill the knowledge gap on detailed sub-catchment scale meteorological drought characteristics in Afghanistan. The study findings improve our understanding of the influences of climate change on drought dynamics and can guide catchment planning for reliable adaptation to and mitigation against future droughts.

Keywords: SPEI, precipitation, evapotranspiration, climate extremes

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Authors: Bechir Hbibi, Lamine Mili

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Understanding the condition of comatose patients can be difficult, but it is crucial to their optimal treatment. Consequently, numerous scoring systems have been developed around the world to categorize patient states based on physiological assessments. Although validated and widely adopted by medical communities, these scores still present numerous limitations and obstacles. Even with the addition of additional tests and extensions, these scoring systems have not been able to overcome certain limitations, and it appears unlikely that they will be able to do so in the future. On the other hand, physiological tests are not the only way to extract ideas about comatose patients. EEG signal analysis has helped extensively to understand the human brain and human consciousness and has been used by researchers in the classification of different levels of disease. The use of EEG in the ICU has become an urgent matter in several cases and has been recommended by medical organizations. In this field, the EEG is used to investigate epilepsy, dementia, brain injuries, and many other neurological disorders. It has recently also been used to detect pain activity in some regions of the brain, for the detection of stress levels, and to evaluate sleep quality. In our recent findings, our aim was to use multifractal analysis, a very successful method of handling multifractal signals and feature extraction, to establish a state of awareness scale for comatose patients based on their electrical brain activity. The results show that this score could be instantaneous and could overcome many limitations with which the physiological scales stock. On the contrary, multifractal analysis stands out as a highly effective tool for characterizing non-stationary and self-similar signals. It demonstrates strong performance in extracting the properties of fractal and multifractal data, including signals and images. As such, we leverage this method, along with other features derived from EEG signal recordings from comatose patients, to develop a scale. This scale aims to accurately depict the vigilance state of patients in intensive care units and to address many of the limitations inherent in physiological scales such as the Glasgow Coma Scale (GCS) and the FOUR score. The results of applying version V0 of this approach to 30 patients with known GCS showed that the EEG-based score similarly describes the states of vigilance but distinguishes between the states of 8 sedated patients where the GCS could not be applied. Therefore, our approach could show promising results with patients with disabilities, injected with painkillers, and other categories where physiological scores could not be applied.

Keywords: coma, vigilance state, EEG, multifractal analysis, feature extraction

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Authors: A. Hidalgo, A. Desportes, E. Bonin, A. Kadaoui, T. Bouaricha

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Present paper is concerned with portfolio management with Black-Litterman (B-L) model. Considered stocks are exclusively limited to large companies stocks on US market. Results obtained by application of the model are presented. From analysis of collected Dow Jones stock data, remarkable explicit analytical expression of optimal B-L parameter τ, which scales dispersion of normal distribution of assets mean return, is proposed in terms of standard deviation of covariance matrix. Implementation has been developed in Matlab environment to split optimization in Markovitz sense from specific elements related to B-L representation.

Keywords: Black-Litterman, Markowitz, market data, portfolio manager opinion

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Authors: Hugo Reis, Isabel Rabiais

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The main purpose of the present study is to understand the nurse’s responsibility in preventing the septic shock in an oncological patient with febrile neutropenia submitted to chemotherapy. In order to do it, an integrative review of literature has been conducted. In the research done in many databases, it was concluded that only 7 out of 5202 articles compiled the entire inclusion standard present in the strict protocol of research, being this made up by all different methodologies. On the research done in the 7 articles it has resulted 8 text macro-units associated to different nursing interventions: ‘Health Education’; ‘Prophylactic Therapy Administration’; ‘Scales Utilization’; ‘Patient Evaluation’; ‘Environment Control’; ‘Performance of Diagnostic Auxiliary Exams’; ‘Protocol Enforcement/Procedure Guidelines’; ‘Antibiotic Therapy Administration’. Concerning the prevalence/result’s division there can be identified many conclusions: the macro-units ‘Patient Evaluation’, ‘Performance of Diagnostic Auxiliary Exams’, and ‘Antibiotic Therapy Administration’ present themselves to be the most prevalent in the research – 6 in 7 occurrences (approximately 85.7%). Next, the macro-unit ‘Protocol Enforcement/Procedure Guidelines’ presents itself as an important expression unit – being part of 5 out of the 7 analyzed studies (approximately 71.4%). The macro-unit ‘Health Education’, seems to be in the same way, an important expression unit – 4 out of the 7 (or approximately 57%). The macro-unit ‘Scales Utilization’, represents a minor part in the research done – it’s in only 2 out of the 7 cases (approximately 28.6%). On the other hand, the macro-units ‘Prophylactic Therapy Administration’ and ‘Environment Control’ are the two categories with fewer results in the research - 1 out of the 7 cases, the same as approximately 14.3% of the research results. Every research done to the macro-unit ‘Antibiotic Therapy Administration’ agreed to refer that the intervention should be strictly done, in a period of time less than one hour after diagnosing the fever, with the purpose of controlling the quick spread of infection – minimizing its seriousness. Identifying these interventions contributes, concluding that, to adopt strategies in order to prevent the phenomenon that represents a daily scenario responsible for the cost´s increase in health institutions, being at the same time responsible for the high morbidity rates and mortality increase associated with this specific group of patients.

Keywords: febrile neutropenia, oncology nursing, patient, septic shock

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Authors: Ehi E. Aimiuwu

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As of 2017, many researchers in educational journals are still wondering if students are effectively and efficiently engaged in active learning in the online learning environment. The goal of this qualitative single case study and narrative research is to explore if students are actively engaged in their online learning. Seven online students in the United States from LinkedIn and residencies were interviewed for this study. Eleven online learning techniques from research were used as a framework.  Data collection tools were used for the study that included a digital audiotape, observation sheet, interview protocol, transcription, and NVivo 12 Plus qualitative software.  Data analysis process, member checking, and key themes were used to reach saturation. About 85.7% of students preferred individual grading. About 71.4% of students valued professor’s interacting 2-3 times weekly, participating through posts and responses, having good internet access, and using email.  Also, about 57.1% said students log in 2-3 times weekly to daily, professor’s social presence helps, regular punctuality in work submission, and prefer assessments style of research, essay, and case study.  About 42.9% appreciated syllabus usefulness and professor’s expertise.

Keywords: class facilitation, course management, online teaching, online education, student engagement

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Authors: Dina A. Selim, Eman Shawky, Rasha M. Abu El-Khair

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In the current study, UPLC-MS/MS combined to chemometrics were applied on seven Sri Lankan tea grades; Orange Pekoe, Flowery Pekoe, Broken Orange Pekoe Fannings, Broken Orange Pekoe black tea, green tea, silver tips and golden tips white tea grades for their comprehensive metabolic profiling. Certain metabolites, namely, Theasensinin C and E, theaflavin and theacitrin appeared to be the main chemical markers of black tea type, catechin, epicatechin, epigallocatechin, methyl epigallocatechin were the main discriminatory markers of green tea type, while theanine, oolongotheanine and quercetin glycosides were the main chemical markers of white tea type. Theogalloflavin, epigallocatechin and flavonoid glycosides were the main down-accumulated metabolites while theaflavin gallate, and N-ethyl pyrrolidinone epicatechin were the chief up- accumulated metabolites between whole and broken black tea leave grades while puerin A and C and gallic acid was the main down- accumulated metabolites and N-ethyl pyrrolidinone epicatechin gallate was the main up-accumulated one between broken and fanning black tea grades.

Keywords: tea grading, Sri Lankan tea, chemometrics, metabolomics, chemical markers

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Authors: Genady Grabarnik, Serge Yaskolko

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Generative Artificial Intelligence (AI) has significantly expanded its applicability with the incorporation of Large Language Models (LLMs) and become a technology with promise to automate some areas that were very difficult to automate before. The paper describes the introduction of generative Artificial Intelligence into Introductory Computer and Data Science courses and analysis of effect of such introduction. The generative Artificial Intelligence is incorporated in the educational process two-fold: For the instructors, we create templates of prompts for generation of tasks, and grading of the students work, including feedback on the submitted assignments. For the students, we introduce them to basic prompt engineering, which in turn will be used for generation of test cases based on description of the problems, generating code snippets for the single block complexity programming, and partitioning into such blocks of an average size complexity programming. The above-mentioned classes are run using Large Language Models, and feedback from instructors and students and courses’ outcomes are collected. The analysis shows statistically significant positive effect and preference of both stakeholders.

Keywords: introductory computer and data science education, generative AI, large language models, application of LLMS to computer and data science education

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Authors: Noor Ismael, Somaya Malkawi, Sherin Al Awady, Taleb Ismael

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Background/Significance: Cancer is a serious health condition that affects individuals’ quality of life during and after the course of this condition. Children who have survived cancer and their caregivers may deal with residual physical, cognitive or social disabilities. There is little research on caregivers’ health and wellbeing after cancer. To the authors’ best knowledge; there is no specific research about how caregivers cope with everyday stressors after cancer. Therefore, this study aimed to explore the coping strategies that caregivers of children who have survived cancer utilize to overcome everyday stressors. Methods: This study utilized a descriptive survey design. The sample consisted of 103 caregivers, who visited the health and wellness clinic at a national cancer center (additional demographics are presented in the results). The sample included caregivers of children who were off cancer treatments for at least two years from the beginning of data collection. The institution’s internal review board approved this study. Caregivers who agreed to participate completed the survey. The survey collected caregiver reported demographic information and the Brief COPE which measures caregivers' frequency of engaging in certain coping strategies. The Brief COPE consisted of 14 coping sub-scales, which are self-distraction, active coping, denial, substance use, use of emotional support, use of instrumental support, behavioral disengagement, venting, positive reframing, planning, humor, acceptance, religion, and self-blame. Data analyses included calculating sub-scales’ scores for the fourteen coping strategies and analysis of frequencies of demographics and coping strategies. Results: The 103 caregivers who participated in this study were 62% mothers, 80% married, 45% finished high school, 50% do not work outside the house, and 60% have low family income. Result showed that religious coping (66%) and acceptance (60%) were the most utilized coping strategies, followed by positive reframing (45%), active coping (44%) and planning (43%). The least utilized coping strategies in our sample were humor (5%), behavioral disengagement (8%), and substance-use (10%). Conclusions: Caregivers of children who have survived cancer mostly utilize religious coping and acceptance in dealing with everyday stressors. Because these coping strategies do not directly solve stressors like active coping and planning coping strategies, it is important to support caregivers in choosing and implementing effective coping strategies. Knowing from our results that some caregivers may utilize substance use as a coping strategy, which has negative health effects on caregivers and their children, there must be direct interventions that target these caregivers and their families.

Keywords: caregivers, cancer, stress, coping

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Authors: Manjit Singh

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Multiscale entropy (MSE) is an extensively used index to provide a general understanding of multiple complexity of physiologic mechanism of heart rate variability (HRV) that operates on a wide range of time scales. Accurate selection of electrocardiogram (ECG) sampling frequency is an essential concern for clinically significant HRV quantification; high ECG sampling rate increase memory requirements and processing time, whereas low sampling rate degrade signal quality and results in clinically misinterpreted HRV. In this work, the impact of ECG sampling frequency on MSE based HRV have been quantified. MSE measures are found to be sensitive to ECG sampling frequency and effect of sampling frequency will be a function of time scale.

Keywords: ECG (electrocardiogram), heart rate variability (HRV), multiscale entropy, sampling frequency

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Authors: Sarah Triller, Ferdi Schüth

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The challenges encountered in upscaling the mechanochemical synthesis of high surface area α-alumina are investigated in this study. After lab-scale experiments in shaker mills and planetary ball mills, the optimization of reaction parameters of the conversion in the smallest vessel of a scalable mill, named Simoloyer, was developed. Furthermore, the future perspectives by scaling up the conversion in several steps are described. Since abrasion from the steel equipment can be problematic, the process was transferred to a ceramically lined mill, which solved the contamination problem. The recovered alpha-alumina shows a high specific surface area in all investigated scales.

Keywords: mechanochemistry, scale-up, ball milling, ceramic lining

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Authors: Ziyuan Wu, Yulong Jia, Xiang Zhang, Wanting Zhou, Lei Li

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The Internet of Things (IoT) is a rapidly evolving field involving a large number of interconnected embedded devices. In the design of embedded System-on-Chip (SoC), the key issues are power consumption, performance, and security. However, the easy-to-implement software and untrustworthy third-party IP cores may threaten the safety of hardware assets. Considering that illegal access and malicious attacks against SoC resources pass through the bus that integrates IPs, we propose a Lightweight Hardware Firewall (LHF) to protect SoC, which monitors and disallows the offending bus transactions based on physical addresses. Furthermore, under the LHF architecture, this paper refines two types of firewalls: Destination Hardware Firewall (DHF) and Source Hardware Firewall (SHF). The former is oriented to fine-grained detection and configuration, whose core technology is based on the method of dynamic grading units. In addition, we design the SHF based on static entries to achieve lightweight. Finally, we evaluate the hardware consumption of the proposed method by both Field-Programmable Gate Array (FPGA) and IC. Compared with the exciting efforts, LHF introduces a bus latency of zero clock cycles for every read or write transaction implemented on Xilinx Kintex-7 FPGAs. Meanwhile, the DC synthesis results based on TSMC 90nm show that the area is reduced by about 25% compared with the previous method.

Keywords: IoT, security, SoC, bus architecture, lightweight hardware firewall, FPGA

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Authors: Juzhong Tan, William Kerr

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Roasting is one critical procedure in chocolate processing, where special favors are developed, moisture content is decreased, and better processing properties are developed. Therefore, determination of roasting degree of cocoa bean is important for chocolate manufacturers to ensure the quality of chocolate products, and it also decides the commercial value of cocoa beans collected from cocoa farmers. The roasting degree of cocoa beans currently relies on human specialists, who sometimes are biased, and chemical analysis, which take long time and are inaccessible to many manufacturers and farmers. In this study, a self-made electronic nose system consists of gas sensors (TGS 800 and 2000 series) was used to detecting the gas generated by cocoa beans with a different roasting degree (0min, 20min, 30min, and 40min) and the signals collected by gas sensors were used to train a three-layers ANN. Chemical analysis of the graded beans was operated by traditional GC-MS system and the contents of volatile chemical compounds were used to train another ANN as a reference to electronic nosed signals trained ANN. Both trained ANN were used to predict cocoa beans with a different roasting degree for validation. The best accuracy of grading achieved by electronic nose signals trained ANN (using signals from TGS 813 826 820 880 830 2620 2602 2610) turned out to be 96.7%, however, the GC trained ANN got the accuracy of 83.8%.

Keywords: artificial neutron network, cocoa bean, electronic nose, roasting

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Authors: Meng-Ying Chiu, Yu-Fang Huang, Pei-Wei Wang, Yi-Ru Wang, Yi-Shuan Shao, Mei-Lien Chen

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Background: Organophosphate pesticides (OPs) are the most heavily used pesticides in agriculture in Taiwan. Therefore, they are commonly detected in general public including pregnant women and children. These compounds are proven endocrine disrupters that may affect the neural development in humans. The aim of this study is to assess the OPs exposure of children in 2 years of age and to examine the association between the exposure concentrations and neurodevelopmental effects in children. Methods: In a prospective cohort of 280 mother-child pairs, urine samples of prenatal and postnatal were collected from each participant and analyzed for metabolites of OPs by using gas chromatography-mass spectrometry. Six analytes were measured including dimethylphosphate (DMP), dimethylthiophosphate (DMTP), dimethyldithiophosphate (DMDTP), diethylphosphate (DEP), diethylthiophosphate (DETP), and diethyldithiophosphate (DEDTP). This study created a combined concentration measure for dimethyl compounds (DMs) consisting of the three dimethyl metabolites (DMP, DMTP, and DMDTP), for diethyl compounds (DEs) consisting of the three diethyl metabolites (DEP, DETP, and DEDTP) and six dialkyl phosphate (DAPs). The Bayley Scales of Infant and Toddler Development (Bayley-III) was used to assess children's cognitive behavior at 2 years old. The association between OPs exposure and Bayley-III scale score was determined by using the Mann-Whitney U test. Results: The measurements of urine samples are still on-going. This preliminary data are the report of 56 children aged 2 from the cohort. The detection rates for DMP, DMTP, DMDTP, DEP, DETP, and DEDTP are 80.4%, 69.6%, 64.3%, 64.3%, 62.5%, and 75%, respectively. After adjusting the creatinine concentrations of urine, the median (nmol/g creatinine) of urinary DMP, DMTP, DMDTP, DEP, DETP, DEDTP, DMs, DEs, and DAPs are 153.14, 53.32, 52.13, 19.24, 141.65, 192.17, 308.8, 311.6, and 702.11, respectively. The concentrations of urine are considerably higher than that in other countries. Children’s cognitive behavior was used three scales for Bayley-III, including cognitive, language and motor. In Mann-Whitney U test, the higher levels of DEs had significantly lower motor score (p=0.037), but no significant association was found between the OPs exposure levels and the score of either cognitive or language. Conclusion: The limited sample size suggests that Taipei children are commonly exposed to OPs and OPs exposure might affect the cognitive behavior of young children. This report will present more data to verify the results. The predictors of OPs concentrations, such as dietary pattern will also be included.

Keywords: biomonitoring, children, neurodevelopment, organophosphate pesticides exposure

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Authors: Xiaojie Jiang, Wei Cai, Yinxiao Xiang, Ni Zhang, Mengxin Ren, Xinzheng Zhang, Jingjun Xu

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Reflection phase of graphene plasmons (GPs) at an abrupt interface is very important, which determines the plasmon resonance of graphene structures of deep sub-wavelength scales. However, at an abrupt graphene edge, the reflection phase is always a constant, ΦR ≈ π/4. In this work, we show that the reflection phase of GPs can be efficiently changed through substrate design. Reflection phase of graphene plasmons (GPs) at an abrupt interface is very important, which determines the plasmon resonance of graphene structures of deep sub-wavelength scales. However, at an abrupt graphene edge, the reflection phase is always a constant, ΦR ≈ π/4. In this work, we show that the reflection phase of GPs can be efficiently changed through substrate design. Specifically, the reflection phase is no longer π/4 at the interface formed by placing a graphene sheet on different substrates. Moreover, tailorable reflection phase of GPs up to 2π variation can be further achieved by scattering GPs at a junction consisting of two such dielectric interfaces with various gap width acting as a Fabry-Perot cavity. Besides, the evolution of plasmon mode in graphene ribbons based on the interface reflection phase tuning is predicted, which is expected to be observed in near-field experiments with scattering-type scanning near-field optical microscopy (s-SNOM). Our work provides another way for in-plane plasmon control, which should find applications for integrated plasmon devices design using graphene.Specifically, the reflection phase is no longer π/4 at the interface formed by placing a graphene sheet on different substrates. Moreover, tailorable reflection phase of GPs up to 2π variation can be further achieved by scattering GPs at a junction consisting of two such dielectric interfaces with various gap width acting as a Fabry-Perot cavity. Besides, the evolution of plasmon mode in graphene ribbons based on the interface reflection phase tuning is predicted, which is expected to be observed in near-field experiments with scattering-type scanning near-field optical microscopy (s-SNOM). Our work provides a new way for in-plane plasmon control, which should find applications for integrated plasmon devices design using graphene.

Keywords: graphene plasmons, reflection phase tuning, plasmon mode tuning, Fabry-Perot cavity

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Authors: Geminne Manzano, Porfirio Aliño, Clairecynth Yu, Lilibeth Salvador-Reyes, Viviene Santiago

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Many marine benthic organisms produce secondary metabolites that serve as ecological roles to different biological and environmental factors. The secondary metabolites found in these organisms like algae, sponges, tunicates and worms exhibit variation at different scales. Understanding the chemical variation can be essential in deriving the evolutionary and ecological function of the secondary metabolites that may explain their patterns. Ecological surveys were performed on two collection sites representing from two Philippine marine biogeographic regions – in Oriental Mindoro located on the West Philippine Sea (WPS) and in Zamboanga del Sur located at Celebes Sea (CS), where a total of 39 Xestospongia sp. sponges were collected using SCUBA. The sponge samples were transported to the laboratory for taxonomic identification and chemical analysis. Biological and environmental factors were investigated to determine their relation to the abundance and distribution patterns and its spatial variability of their secondary metabolite production. Extracts were subjected to thin-layer chromatography and anti-proliferative assays to confirm the presence of Renieramycin-M and to test its cytotoxicity. The blue sponges were found to be more abundant on the WPS than in CS. Both the benthic community and the fish community in Oriental Mindoro, WPS and Zamboanga del Sur, CS sites are characterized by high species diversity and abundance and a very high biomass category. Environmental factors like depth and monsoonal exposure were also compared showing that wave exposure and depth are associated with the abundance and distribution of the sponges. Renieramycin-M presence using the TLC profiles between the sponge extracts from WPS and from CS showed differences in the Reniermycin-M presence and the presence of other functional groups were observed between the two sites. In terms of bioactivity, different responses were also exhibited by the sponge extracts coming from the different region. Different responses were also noted on its bioactivity depending on the cell lines tested. Exploring the influence of ecological parameters on the chemical variation can provide deeper chemical ecological insights in the knowledge and their potential varied applications at different scales. The results of this study provide further impetus in pursuing studies into patterns and processes of the chemical diversity of the Philippine blue sponge, Xestospongia sp. and the chemical ecological significance of the coral triangle.

Keywords: chemical ecology, porifera, renieramycin-m, spatial variability, Xestospongia sp.

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Authors: Lorato Itumeleng Kenosi

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Background: Negative attitudes towards the mentally ill are widespread and a course for concern as they have a detrimental impact on individuals affected by mental illness. A possible avenue for changing attitudes towards mental illness is through mental health literacy. In a college or university setting, an abnormal psychology course may be introduced in an attempt to change student’s attitudes towards the mentally ill. Objective: To determine if and how students’ attitudes towards the mentally ill change as a result of taking a course in abnormal psychology. Methods: Twenty nine (29) students were recruited from an abnormal psychology class at the University of Botswana. Attitude Scale for Mental Illness (ASMI) questionnaire was administered to participants at the beginning and end of the semester. SPSS was employed to analyze data. Pooled means were used to determine whether the student’s attitudes towards mental illness were negative or positive. A mean of 2.5 translated to negative attitude for both total attitude and attitudes in different domains of the scale. Paired sample t-test was then used to assess whether any changes noted in attitudes were statistically significant or not. Statistical significance was assumed at p < 0.05. Results: Students’ general attitude towards mental illness remained positive although the pooled mean value increased from 2.08 to 2.24. The change was not statistically significant. In relation to different sub scales, the values of the pooled means for all the sub scales showed an increase although the changes were not statistically significant except for the Stereotyping sub scale (p = 0.031). The stereotyping domain reflected a statistically significant change in student’s attitude from positive attitude to negative (X² = 2.06 to X² = 2.55). For the pessimistic prediction domain, students consistently showed a negative attitude (X² = 3.34 to X² = 3.55). The other 4 domains indicated that students had positive attitude toward mentally ill throughout. Discussion: Abnormal psychology students have a positive attitude towards the mentally ill generally. This could be attributed to the fact that all students in the abnormal psychology course are majoring in psychology and research has shown that interest in psychology can affect one’s attitude towards mental illness. The students continuously held the view that people with mental illness are unlikely to improve as evidenced by a high score for Pessimistic prediction domain for both pre and post-test. Students initially had no stereotyping attitude towards the mentally ill, but at the end of the course, they were of the opinion that people with mental illness can be defined in a certain behavioural pattern and mental ability. This results could be an indication that students have learnt well how to differentiate abnormal from normal behaviour not necessarily that students had developed a negative attitude. Conclusion: A course in abnormal psychology does have an impact on the students’ attitudes towards the mentally ill. The impact does not solely depend on knowledge of mental illness but also on several other factors such as contact with the mentally ill, interest in psychology, and teaching methods. However, it should be noted that sometimes improved knowledge in mental illness can be misunderstood for a negative attitude. For example, stereotyping attitudes may be a reflection of the ability to differentiate between abnormal and normal behaviour.

Keywords: attitudes, mental illness, psychopathology, students

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Authors: Samson Mil'shtein, Dhawal N. Asthana

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The presented heterostructure n-p-n bipolar transistor is comprised of Ge/GaAs heterojunctions consisting of 0.15µm thick emitter and 0.65µm collector junctions. High diffusivity of carriers in GaAs base was major motivation of current design. We avoided grading of the base which is common in heterojunction bipolar transistors, in order to keep the electron diffusivity as high as possible. The electrons injected into the 0.25µm thick p-type GaAs base with not very high doping (1017cm-3). The designed HBT enables cut off frequency on the order of 150GHz. The Ge/GaAs heterojunctions presented in our paper have proved to work better than comparable HBTs having GaAs bases and emitter/collector junctions made, for example, of AlGaAs/GaAs or other III-V compound semiconductors. The difference in lattice constants between Ge and GaAs is less than 2%. Therefore, there is no need of transition layers between Ge emitter and GaAs base. Significant difference in energy gap of these two materials presents new scope for improving performance of the emitter. With the complete structure being modelled and simulated using TCAD SILVACO, the collector/ emitter offset voltage of the device has been limited to a reasonable value of 63 millivolts by the dint of low energy band gap value associated with Ge emitter. The efficiency of the emitter in our HBT is 86%. Use of Germanium in the emitter and collector regions presents new opportunities for integration of this vertical device structure into silicon substrate.

Keywords: Germanium, Gallium Arsenide, heterojunction bipolar transistor, high cut-off frequency

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Authors: Zarina Chokparova, Ighor Uzhinsky

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Carbon dioxide emissions resulting from burning of the fossil fuels on large scales, such as oil industry or power plants, leads to a plenty of severe implications including global temperature raise, air pollution and other adverse impacts on the environment. Besides some precarious and costly ways for the alleviation of CO₂ emissions detriment in industrial scales (such as liquefaction of CO₂ and its deep-water treatment, application of adsorbents and membranes, which require careful consideration of drawback effects and their mitigation), one physically and commercially available technology for its capture and disposal is supersonic system for inertial extraction of CO₂ in after-combustion streams. Due to the flue gas with a carbon dioxide concentration of 10-15 volume percent being emitted from the combustion system, the waste stream represents a rather diluted condition at low pressure. The supersonic system induces a flue gas mixture stream to expand using a converge-and-diverge operating nozzle; the flow velocity increases to the supersonic ranges resulting in rapid drop of temperature and pressure. Thus, conversion of potential energy into the kinetic power causes a desublimation of CO₂. Solidified carbon dioxide can be sent to the separate vessel for further disposal. The major advantages of the current solution are its economic efficiency, physical stability, and compactness of the system, as well as needlessness of addition any chemical media. However, there are several challenges yet to be regarded to optimize the system: the way for increasing the size of separated CO₂ particles (as they are represented on a micrometers scale of effective diameter), reduction of the concomitant gas separated together with carbon dioxide and provision of CO₂ downstream flow purity. Moreover, determination of thermodynamic conditions of the vapor-solid mixture including specification of the valid and accurate equation of state remains to be an essential goal. Due to high speeds and temperatures reached during the process, the influence of the emitted heat should be considered, and the applicable solution model for the compressible flow need to be determined. In this report, a brief overview of the current technology status will be presented and a program for further evaluation of this approach is going to be proposed.

Keywords: CO₂ sequestration, converging diverging nozzle, fossil fuel power plant emissions, inertial CO₂ extraction, supersonic post-combustion carbon dioxide capture

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