Search results for: advanced anode

Authors: Sabri Sudirman, Yuan-Hua Hsu, Zwe-Ling Kong

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Male reproductive dysfunction is predominantly due to insulin resistance and hyperglycemia result in inflammation and oxidative stress. Furthermore, nanotechnology provides an alternative approach to improve the bioavailability of natural active food ingredients. Therefore, the aim of this study were to investigate nanoencapsulated triterpenoids from petri-dish cultured Antrodia cinnamomea (PAC) nanoparticles whether it could increase the bioavailability; in addition, the anti-inflammatory and anti-oxidative effects could more effectively ameliorate the reproductive function of diabetic male rats. First, PAC encapsulated in chitosan-silica nanoparticles (Nano-PAC) were prepared by biosilicification method. Scanning electron micrographs confirm the average particle size is about 30 nm, and the encapsulation efficiency is 83.7% by HPLC. Diabetic male Sprague-Dawley rats were induced by high fat diet (40% kcal from fat) and streptozotocin (35 mg/kg). Nano-PAC was administered by oral gavage in three doses (4, 8 and 20 mg/kg) for 6 weeks. Besides, metformin (300 mg/kg) and nanoparticles (Nano) were treated as the positive and negative control respectively. Results indicated that 4 mg/kg Nano-PAC administration for 6 weeks improved hyperglycemia, insulin resistance, and also reduced advanced glycation end products in plasma. In addition, 8 mg/kg Nano-PAC ameliorated morphological of testicular seminiferous tubules, sperm morphology and motility, reactive oxygen species production and mitochondrial membrane potential. Moreover, 20 mg/kg Nano-PAC restored reproductive endocrine system function and increased KiSS-1 level in plasma. In plasma or testis anti-oxidant superoxide dismutase, glutathione peroxidase and catalase were increased whereas malondialdehyde, as well as pro-inflammatory cytokines tumor necrosis factor-α, interleukin-6, and interferon-gamma, decreased. Most importantly, 8 mg/kg Nano-PAC down-regulated the oxidative stress induced c-Jun N-terminal kinase (JNK) signaling pathway. Our study successfully nanoencapsulated PAC to form nanoparticles and low-dose Nano-PAC improved diabetes-induced hyperglycemia, inflammation and oxidative stress to ameliorate the reproductive function of diabetic male rats.

Keywords: Antrodia cinnamomea, diabetes mellitus, male reproduction, nanoparticles

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Authors: Desplanches Maxime

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Accurate estimation of the remaining useful life of lithium-ion batteries for electronic devices is crucial. Data-driven methodologies encounter challenges related to data volume and acquisition protocols, particularly in capturing a comprehensive range of aging indicators. To address these limitations, we propose a hybrid approach that integrates an electrochemical model with state-of-the-art data analysis techniques, yielding a comprehensive database. Our methodology involves infusing an aging phenomenon into a Newman model, leading to the creation of an extensive database capturing various aging states based on non-destructive parameters. This database serves as a robust foundation for subsequent analysis. Leveraging advanced data analysis techniques, notably principal component analysis and t-Distributed Stochastic Neighbor Embedding, we extract pivotal information from the data. This information is harnessed to construct a regression function using either random forest or support vector machine algorithms. The resulting predictor demonstrates a 5% error margin in estimating remaining battery life, providing actionable insights for optimizing usage. Furthermore, the database was built from the Newman model calibrated for aging and performance using data from a European project called Teesmat. The model was then initialized numerous times with different aging values, for instance, with varying thicknesses of SEI (Solid Electrolyte Interphase). This comprehensive approach ensures a thorough exploration of battery aging dynamics, enhancing the accuracy and reliability of our predictive model. Of particular importance is our reliance on the database generated through the integration of the electrochemical model. This database serves as a crucial asset in advancing our understanding of aging states. Beyond its capability for precise remaining life predictions, this database-driven approach offers valuable insights for optimizing battery usage and adapting the predictor to various scenarios. This underscores the practical significance of our method in facilitating better decision-making regarding lithium-ion battery management.

Keywords: Li-ion battery, aging, diagnostics, data analysis, prediction, machine learning, electrochemical model, regression

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Authors: Henok Hailemariam, Frank Wuttke

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Collapsible soils are weak soils that appear to be stable in their natural state, normally dry condition, but rapidly deform under saturation (wetting), thus generating large and unexpected settlements which often yield disastrous consequences for structures unwittingly built on such deposits. In this study, a prediction model for the relative subsidence of stressed collapsible soils based on dielectric permittivity measurement is presented. Unlike most existing methods for soil subsidence prediction, this model does not require moisture content as an input parameter, thus providing the opportunity to obtain accurate estimation of the relative subsidence of collapsible soils using dielectric measurement only. The prediction model is developed based on an existing relative subsidence prediction model (which is dependent on soil moisture condition) and an advanced theoretical frequency and temperature-dependent electromagnetic mixing equation (which effectively removes the moisture content dependence of the original relative subsidence prediction model). For large scale sub-surface soil exploration purposes, the spatial sub-surface soil dielectric data over wide areas and high depths of weak (collapsible) soil deposits can be obtained using non-destructive high frequency electromagnetic (HF-EM) measurement techniques such as ground penetrating radar (GPR). For laboratory or small scale in-situ measurements, techniques such as an open-ended coaxial line with widely applicable time domain reflectometry (TDR) or vector network analysers (VNAs) are usually employed to obtain the soil dielectric data. By using soil dielectric data obtained from small or large scale non-destructive HF-EM investigations, the new model can effectively predict the relative subsidence of weak soils without the need to extract samples for moisture content measurement. Some of the resulting benefits are the preservation of the undisturbed nature of the soil as well as a reduction in the investigation costs and analysis time in the identification of weak (problematic) soils. The accuracy of prediction of the presented model is assessed by conducting relative subsidence tests on a collapsible soil at various initial soil conditions and a good match between the model prediction and experimental results is obtained.

Keywords: collapsible soil, dielectric permittivity, moisture content, relative subsidence

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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: Palash Soni, Vivek Kumar Gaba, Shubhankar Bhowmick, Bidyut Mazumdar

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Refrigeration technology is a fast developing field at the present era since it has very wide application in both domestic and industrial areas. It started from the usage of simple ice coolers to store food stuffs to the present sophisticated cold storages along with other air conditioning system. A variety of techniques are used to bring down the temperature below the ambient. Adsorption refrigeration technology is a novel, advanced and promising technique developed in the past few decades. It gained attention due to its attractive property of exploiting unlimited natural sources like solar energy, geothermal energy or even waste heat recovery from plants or from the exhaust of locomotives to fulfill its energy need. This will reduce the exploitation of non-renewable resources and hence reduce pollution too. This work is aimed to develop a model for a solar adsorption refrigeration system and to simulate the same for different operating conditions. In this system, the mechanical compressor is replaced by a thermal compressor. The thermal compressor uses renewable energy such as solar energy and geothermal energy which makes it useful for those areas where electricity is not available. Refrigerants normally in use like chlorofluorocarbon/perfluorocarbon have harmful effects like ozone depletion and greenhouse warming. It is another advantage of adsorption systems that it can replace these refrigerants with less harmful natural refrigerants like water, methanol, ammonia, etc. Thus the double benefit of reduction in energy consumption and pollution can be achieved. A thermodynamic model was developed for the proposed adsorber, and a universal MATLAB code was used to simulate the model. Simulations were carried out for a different operating condition for the silicagel-methanol working pair. Various graphs are plotted between regeneration temperature, adsorption capacities, the coefficient of performance, desorption rate, specific cooling power, adsorption/desorption times and mass. The results proved that adsorption system could be installed successfully for refrigeration purpose as it has saving in terms of power and reduction in carbon emission even though the efficiency is comparatively less as compared to conventional systems. The model was tested for its compliance in a cold storage refrigeration with a cooling load of 12 TR.

Keywords: adsorption, refrigeration, renewable energy, silicagel-methanol

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Authors: Mariangela Viviani, Daniele Germano, Simone Colace, Agostino Forestiero, Giuseppe Papuzzo, Sara Laurita

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Nowadays, people spend most of their time in closed environments, in offices, or at home. Therefore, secure and highly livable environmental conditions are needed to reduce the probability of aerial viruses spreading. Also, to lower the human impact on the planet, it is important to reduce energy consumption. Heating, Ventilation, and Air Conditioning (HVAC) systems account for the major part of energy consumption in buildings [1]. Devising systems to control and regulate the airflow is, therefore, essential for energy efficiency. Moreover, an optimal setting for thermal comfort and air quality is essential for people’s well-being, at home or in offices, and increases productivity. Thanks to the features of Artificial Intelligence (AI) tools and techniques, it is possible to design innovative systems with: (i) Improved monitoring and prediction accuracy; (ii) Enhanced decision-making and mitigation strategies; (iii) Real-time air quality information; (iv) Increased efficiency in data analysis and processing; (v) Advanced early warning systems for air pollution events; (vi) Automated and cost-effective m onitoring network; and (vii) A better understanding of air quality patterns and trends. We propose AIR SAFE, an IoT-based infrastructure designed to optimize air quality and thermal comfort in indoor environments leveraging AI tools. AIR SAFE employs a network of smart sensors collecting indoor and outdoor data to be analyzed in order to take any corrective measures to ensure the occupants’ wellness. The data are analyzed through AI algorithms able to predict the future levels of temperature, relative humidity, and CO₂ concentration [2]. Based on these predictions, AIR SAFE takes actions, such as opening/closing the window or the air conditioner, to guarantee a high level of thermal comfort and air quality in the environment. In this contribution, we present the results from the AI algorithm we have implemented on the first s et o f d ata c ollected i n a real environment. The results were compared with other models from the literature to validate our approach.

Keywords: air quality, internet of things, artificial intelligence, smart home

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Authors: Chahrazed Salhi, Ayoub Zeroual, Yasmina Hamitouche

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Soil water erosion poses a significant threat to the watersheds in Algeria today. The degradation of storage capacity in large dams over the past two decades, primarily due to erosion, necessitates a comprehensive understanding of the factors that contribute to soil erosion. The Isser watershed, located in the Northwestern region of Algeria, faces additional challenges such as recurrent droughts and the presence of delicate marl and clay outcrops, which amplify its susceptibility to water erosion. This study aims to employ advanced techniques such as Geographic Information Systems (GIS) and Remote Sensing (RS), in conjunction with the Canonical Correlation Analysis (CCA) method and Soil Water Assessment Tool (SWAT) model, to predict specific erosion patterns and analyze the key factors influencing erosion in the Isser basin. To accomplish this, an array of data sources including rainfall, climatic, hydrometric, land use, soil, digital elevation, and satellite data were utilized. The application of the SWAT model to the Isser basin yielded an average annual soil loss of approximately 16 t/ha/year. Particularly high erosion rates, exceeding 12 T/ha/year, were observed in the central and southern parts of the basin, encompassing 41% of the total basin area. Through Canonical Correlation Analysis, it was determined that vegetation cover and topography exerted the most substantial influence on erosion. Consequently, the study identified significant and spatially heterogeneous erosion throughout the study area. The impact of land topography on soil loss was found to be directly proportional, while vegetation cover exhibited an inverse proportional relationship. Modeling specific erosion for the Ladrat dam sub-basin estimated a rate of around 39 T/ha/year, thus accounting for the recorded capacity loss of 17.80% compared to the bathymetric survey conducted in 2019. The findings of this research provide valuable decision-support tools for soil conservation managers, empowering them to make informed decisions regarding soil conservation measures.

Keywords: Isser watershed, RS, CCA, SWAT, vegetation cover, topography

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Authors: Johanna Perdomo, Riki Lamont, Edmund Pickering, Naomi C. Paxton, Maria A. Woodruff

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Background: Tissue Engineering (TE) has combined advanced materials, such as biomaterials, to create affordable scaffolds and dynamic systems to generate stimulation of seeded cells on these scaffolds, improving and maintaining the cellular growth process in a cell culture. However, Few TE skin products have been clinically translated, and more research is required to produce highly biomimetic skin substitutes that mimic the native elasticity of skin in a controlled manner. Therefore, this work will be focused on the fabrication of a novel mechanical system to enhance the TE treatment approaches for the reparation of damaged tissue skin. Aims: To archive this, a soft robotic device will be created to emulate different deformation of skin stress. The design of this soft robot will allow the attachment of scaffolds, which will then be mechanically actuated. This will provide a novel and highly adaptable platform for dynamic cell culture. Methods: Novel, low-cost soft robot is fabricated via 3D printed moulds and silicone. A low cost, electro-mechanical device was constructed to actuate the soft robot through the controlled combination of positive and negative air pressure to control the different state of movements. Mechanical tests were conducted to assess the performance and calibration of each electronic component. Similarly, pressure-displacement test was performed on scaffolds, which were attached to the soft robot, applying various mechanical loading regimes. Lastly, digital image correlation test was performed to obtain strain distributions over the soft robot’s surface. Results: The control system can control and stabilise positive pressure changes for long hours. Similarly, pressure-displacement test demonstrated that scaffolds with 5µm of diameter and wavy geometry can displace at 100%, applying a maximum pressure of 1.5 PSI. Lastly, during the inflation state, the displacement of silicone was measured using DIC method, and this showed a parameter of 4.78 mm and strain of 0.0652. Discussion And Conclusion: The developed soft robot system provides a novel and low-cost platform for the dynamic actuation of tissue scaffolds with a target towards dynamic cell culture.

Keywords: soft robot, tissue engineering, mechanical stimulation, dynamic cell culture, bioreactor

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Authors: Nigatu Tadesse, Ying Liu, Juan Li, Hong Ming Liu

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Gastric carcinogenesis is a lengthy process of histopathological transition from normal to atrophic gastritis (AG) to intestinal metaplasia (GIM), dysplasia toward gastric cancer (GC). The stage of GIM identified as precancerous lesions with resistance to H-pylori eradication and recurrence after endoscopic surgical resection therapies. GIM divided in to two morphologically distinct phenotypes such as complete GIM bearing intestinal type morphology whereas the incomplete type has colonic type morphology. The incomplete type GIM considered to be the greatest risk factor for the development of GC. Studies indicated the expression of the caudal type homeobox 2 (CDX2) gene is responsible for the development of complete GIM but its progressive downregulation from incomplete metaplasia toward advanced GC identified as the risk for IM progression and neoplastic transformation. The downregulation of CDX2 gene have promoted cell growth and proliferation in gastric and colon cancers and ascribed in chemo-treatment inefficacies. CDX2 downregulated through promoter region hypermethylation in which the methylation frequency positively correlated with the dietary history of the patients, suggesting the role of diet as methyl carbon donor sources such as methionine. However, the metabolism of exogenous methionine is yet unclear. Targeting exogenous methionine metabolism has become a promising approach to limits tumor cell growth, proliferation and progression and increase treatment outcome. This review article discusses molecular alterations that could shed light on the potential of exogenous methionine metabolisms, such as gut microbiota alteration as sources of methionine to host cells, metabolic pathway signaling via PI3K/AKt/mTORC1-c-MYC to rewire exogenous methionine and signature of increased gene methylation index, cell growth and proliferation in GIM, with insights to new treatment avenue via targeting methionine metabolism, and the need for future integrated studies on molecular alterations and metabolomics to uncover altered methionine metabolism and characterization of CDX2 methylation in gastric intestinal metaplasia for potential therapeutic exploitation.

Keywords: altered methionine metabolism, Intestinal metaplesia, CDX2 gene, gastric cancer

Procedia PDF Downloads 86

Authors: J. J. Lee, S. R. Sung, E. J. Yum, S. C. Kim, B. H. Hyun, M. Her, H. S. Lee

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Canine brucellosis is a critical problem in dogs leading to reproductive diseases which are mainly caused by Brucella canis. There are, nonetheless, not clear symptoms so that it may go unnoticed in most of the cases. Serodiagnosis for canine brucellosis has not been confirmed. Moreover, it has substantial difficulties due to broad cross-reactivity between the rough cell wall antigens of B. canis and heterospecific antibodies present in normal, uninfected dogs. Thus, this study was conducted to characterize the immunogenic proteins in cytoplasmic antigen (CPAg) of B. canis, which defined the antigenic sensitivity of the humoral antibody responses to B. canis-infected dogs. In analysis of B. canis CPAg, first, we extracted and purified the cytoplasmic proteins from cultured B. canis by hot-saline inactivation, ultrafiltration, sonication, and ultracentrifugation step by step according to the sonicated antigen extract method. For characterization of this antigen, we checked the sort and range of each protein on SDS-PAGE and verified the immunogenic proteins leading to reaction with antisera of B. canis-infected dogs. Selected immunodominant proteins were identified using MALDI-MS/MS. As a result, in an immunoproteomic assay, several polypeptides in CPAg on one or two-dimensional electrophoresis (DE) were specifically reacted to antisera from B. canis-infected dogs but not from non-infected dogs. The polypeptides with approximate 150, 80, 60, 52, 33, 26, 17, 15, 13, 11 kDa on 1-DE were dominantly recognized by antisera from B. canis-infected dogs. In the immunoblot profiles on 2-DE, ten immunodominant proteins in CPAg were detected with antisera of infected dogs between pI 3.5-6.5 at approximate 35 to 10 KDa, without any nonspecific reaction with sera in non-infected dogs. Ten immunodominant proteins identified by MALDI-MS/MS were identified as superoxide dismutase, bacteroferritin, amino acid ABC transporter substrate-binding protein, extracellular solute-binding protein family3, transaldolase, 26kDa periplasmic immunogenic protein, Rhizopine-binding protein, enoyl-CoA hydratase, arginase and type1 glyceraldehyde-3-phosphate dehydrogenase. Most of these proteins were determined by their cytoplasmic or periplasmic localization with metabolism and transporter functions. Consequently, this study discovered and identified the prominent immunogenic proteins in B. canis CPAg, highlighting that those antigenic proteins may accomplish a specific serodiagnosis for canine brucellosis. Furthermore, we will evaluate those immunodominant proteins for applying to the advanced diagnostic methods with high specificity and accuracy.

Keywords: Brucella canis, Canine brucellosis, cytoplasmic antigen, immunogenic proteins

Procedia PDF Downloads 147

Authors: Susan Ka Yee Chow

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Effective clinical preceptorship is affecting students’ competence and fostering their growth in applying theoretical knowledge and skills in clinical settings. Any difference between the expected and actual learning experience will reduce nursing students’ interest in clinical practices and having a negative consequence with their clinical performance. This cross-sectional study is an attempt to compare the differences between preferred and actual preceptorship experience of final year nursing students, and to examine the relationship between the actual preceptorship experience and perceived clinical competence of the students in a tertiary institution. Participants of the study were final year bachelor nursing students of a self-financing tertiary institution in Hong Kong. The instruments used to measure the effectiveness of clinical preceptorship was developed by the participating institution. The scale consisted of five items in a 5-point likert scale. The questions including goals development, critical thinking, learning objectives, asking questions and providing feedback to students. The “Clinical Competence Questionnaire” by Liou & Cheng (2014) was used to examine students’ perceived clinical competences. The scale consisted of 47 items categorized into four domains, namely nursing professional behaviours; skill competence: general performance; skill competence: core nursing skills and skill competence: advanced nursing skills. There were 193 questionnaires returned with a response rate of 89%. The paired t-test was used to compare the differences between preferred and actual preceptorship experiences of students. The results showed significant differences (p<0.001) for the five questions. The mean for the preferred scores is higher than the actual scores resulting statistically significance. The maximum mean difference was accepted goal and the highest mean different was giving feedback. The Pearson Correlation Coefficient was used to examine the relationship. The results showed moderate correlations between nursing professional behaviours with asking questions and providing feedback. Providing useful feedback to students is having moderate correlations with all domains of the Clinical Competence Questionnaire (r=0.269 – 0.345). It is concluded that nursing students do not have a positive perception of the clinical preceptorship. Their perceptions are significantly different from their expected preceptorship. If students were given more opportunities to ask questions in a pedagogical atmosphere, their perceived clinical competence and learning outcomes could be improved as a result.

Keywords: clinical preceptor, clinical competence, clinical practicum, nursing students

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Authors: Mohamad Mahdi Namdari

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In today's rapidly changing and evolving business competition, companies and organizations require advanced and efficient tools to manage their markets and sales networks. Big data analysis, quick response in competitive markets, process and operations optimization, and forecasting customer behavior are among the concerns of executive managers. Artificial intelligence, as one of the emerging technologies, has provided extensive capabilities in this regard. The use of artificial intelligence in market and sales network management can lead to improved efficiency, increased decision-making accuracy, and enhanced customer satisfaction. Specifically, AI algorithms can analyze vast amounts of data, identify complex patterns, and offer strategic suggestions to improve sales performance. However, many companies are still distant from effectively leveraging this technology, and those that do face challenges in fully exploiting AI's potential in market and sales network management. It appears that the general public's and even the managerial and academic communities' lack of knowledge of this technology has caused the managerial structure to lag behind the progress and development of artificial intelligence. Additionally, high costs, fear of change and employee resistance, lack of quality data production processes, the need for updating structures and processes, implementation issues, the need for specialized skills and technical equipment, and ethical and privacy concerns are among the factors preventing widespread use of this technology in organizations. Clarifying and explaining this technology, especially to the academic, managerial, and elite communities, can pave the way for a transformative beginning. The aim of this research is to elucidate the capacities of artificial intelligence in market and sales network management, identify its opportunities and benefits, and examine the existing challenges and obstacles. This research aims to leverage AI capabilities to provide a framework for enhancing market and sales network performance for managers. The results of this research can help managers and decision-makers adopt more effective strategies for business growth and development by better understanding the capabilities and limitations of artificial intelligence.

Keywords: artificial intelligence, market management, sales network, big data analysis, decision-making, digital marketing

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Authors: Kyung Hwa Shin

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Primary school music education plays a crucial role in nurturing students' musical abilities and fostering a lifelong appreciation for music. As we embark on the 21st century, it becomes imperative to explore advanced approaches that can effectively engage and empower students in the realm of music. This study aims to shed light on the aspects of primary school music education in South Korea, with a specific focus on the incorporation of the Zoltán Kodály Concept. The Zoltán Kodály Concept, developed by Hungarian composer and educator Zoltán Kodály (Kodály, 1974) advocates for a holistic music education that integrates singing, movement, and music literacy. This concept has gained recognition worldwide for its effectiveness in developing musicianship and enhancing music learning experiences. This study will delve into the ways in which the Zoltán Kodály Concept has been adapted and implemented in the context of South Korean primary school music education. It will highlight the benefits of this approach in nurturing students' musical skills, fostering creativity, and promoting cultural understanding through music. Furthermore, it will enhance the delivery of the Kodály-based curriculum challenges posed by the 21st-century digital age. Drawing on this research, pedagogical practices, and case studies, this study will provide valuable insights into the practical applications of the Zoltán Kodály Concept in South Korean primary school music education. It will discuss the impact of this approach on student engagement, motivation, and achievement, as well as the role of teachers in facilitating effective implementation. Additionally, it will address the professional development opportunities available to music educators to enhance their pedagogical skills in line with the Kodály philosophy. Ultimately, it aims to inspire and empower educators, policymakers, and researchers to embrace the Zoltán Kodály Concept as a transformative and forward-thinking approach to primary school music education in the 21st century. By embracing current aspects and progressive methodologies, South Korea can continue to strengthen its music education system and cultivate a generation of musically literate and culturally enriched individuals.

Keywords: primary school music education, Zoltán Kodály concept, 21st century, South Korea, music literacy, pedagogy, curriculum

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Authors: M. Amparo Núñez-Andrés, Felipe Buill, Albert Prades

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More and more frequently, geomatics techniques such as terrestrial laser scanning or digital photogrammetry, either terrestrial or from drones, are being used to obtain digital terrain models (DTM) used for the monitoring of geological phenomena that cause natural disasters, such as landslides, rockfalls, debris-flow. One of the main multitemporal analyses developed from these models is the quantification of volume changes in the slopes and hillsides, either caused by erosion, fall, or land movement in the source area or sedimentation in the deposition zone. To carry out this task, it is necessary to filter the point clouds of all those elements that do not belong to the slopes. Among these elements, vegetation stands out as it is the one we find with the greatest presence and its constant change, both seasonal and daily, as it is affected by factors such as wind. One of the best-known indexes to detect vegetation on the image is the NVDI (Normalized Difference Vegetation Index), which is obtained from the combination of the infrared and red channels. Therefore it is necessary to have a multispectral camera. These cameras are generally of lower resolution than conventional RGB cameras, while their cost is much higher. Therefore we have to look for alternative indices based on RGB. In this communication, we present the results obtained in Georisk project (PID2019‐103974RB‐I00/MCIN/AEI/10.13039/501100011033) by using the GLI (Green Leaf Index) and ExG (Excessive Greenness), as well as the change to the Hue-Saturation-Value (HSV) color space being the H coordinate the one that gives us the most information for vegetation filtering. These filters are applied both to the images, creating binary masks to be used when applying the SfM algorithms, and to the point cloud obtained directly by the photogrammetric process without any previous filter or the one obtained by TLS (Terrestrial Laser Scanning). In this last case, we have also tried to work with a Riegl VZ400i sensor that allows the reception, as in the aerial LiDAR, of several returns of the signal. Information to be used for the classification on the point cloud. After applying all the techniques in different locations, the results show that the color-based filters allow correct filtering in those areas where the presence of shadows is not excessive and there is a contrast between the color of the slope lithology and the vegetation. As we have advanced in the case of using the HSV color space, it is the H coordinate that responds best for this filtering. Finally, the use of the various returns of the TLS signal allows filtering with some limitations.

Keywords: RGB index, TLS, photogrammetry, multispectral camera, point cloud

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Authors: Kayne Uriel K. Rodrigo, Jerriane Hillary Heart S. Marcial, Samuel C. Brillo

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Rice leaf diseases significantly impact yield production in rice-dependent countries, affecting their agricultural sectors. As part of precision agriculture, early and accurate detection of these diseases is crucial for effective mitigation practices and minimizing crop losses. Hence, this study proposes an enhancement to the Convolutional Neural Network (CNN), a widely-used method for Rice Leaf Disease Image Classification, by incorporating MobileViTV2—a recently advanced architecture that combines CNN and Vision Transformer models while maintaining fewer parameters, making it suitable for broader deployment on edge devices. Our methodology utilizes a publicly available rice disease image dataset from Kaggle, which was validated by a university structural biologist following the guidelines provided by the Philippine Rice Institute (PhilRice). Modifications to the dataset include renaming certain disease categories and augmenting the rice leaf image data through rotation, scaling, and flipping. The enhanced dataset was then used to train the MobileViTV2 model using the Timm library. The results of our approach are as follows: the model achieved notable performance, with 98% accuracy in both training and validation, 6% training and validation loss, and a Receiver Operating Characteristic (ROC) curve ranging from 95% to 100% for each label. Additionally, the F1 score was 97%. These metrics demonstrate a significant improvement compared to a conventional CNN-based approach, which, in a previous 2022 study, achieved only 78% accuracy after using 5 convolutional layers and 2 dense layers. Thus, it can be concluded that MobileViTV2, with its fewer parameters, outperforms traditional CNN models, particularly when applied to Rice Leaf Disease Image Identification. For future work, we recommend extending this model to include datasets validated by international rice experts and broadening the scope to accommodate biotic factors such as rice pest classification, as well as abiotic stressors such as climate, soil quality, and geographic information, which could improve the accuracy of disease prediction.

Keywords: convolutional neural network, MobileViTV2, rice leaf disease, precision agriculture, image classification, vision transformer

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Authors: Esmael Makarian, Ayub Elyasi, Fatemeh Saberi, Olusegun Stanley Tomomewo

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Geothermal reservoirs (GTRs) have garnered global recognition as a sustainable energy source. The Thermo-Hydro-Mechanical-Chemical (THMC) integration coupling proves to be a practical and effective method for optimizing production in GTRs. The study outcomes demonstrate that THMC coupling serves as a versatile and valuable tool, offering in-depth insights into GTRs and enhancing their operational efficiency. This is achieved through temperature analysis and pressure changes and their impacts on mechanical properties, structural integrity, fracture aperture, permeability, and heat extraction efficiency. Moreover, THMC coupling facilitates potential benefits assessment and risks associated with different geothermal technologies, considering the complex thermal, hydraulic, mechanical, and chemical interactions within the reservoirs. However, THMC-coupling utilization in GTRs presents a multitude of challenges. These challenges include accurately modeling and predicting behavior due to the interconnected nature of processes, limited data availability leading to uncertainties, induced seismic events risks to nearby communities, scaling and mineral deposition reducing operational efficiency, and reservoirs' long-term sustainability. In addition, material degradation, environmental impacts, technical challenges in monitoring and control, accurate assessment of resource potential, and regulatory and social acceptance further complicate geothermal projects. Addressing these multifaceted challenges is crucial for successful geothermal energy resources sustainable utilization. This paper aims to illuminate the challenges and opportunities associated with THMC coupling in enhanced geothermal systems. Practical solutions and strategies for mitigating these challenges are discussed, emphasizing the need for interdisciplinary approaches, improved data collection and modeling techniques, and advanced monitoring and control systems. Overcoming these challenges is imperative for unlocking the full potential of geothermal energy making a substantial contribution to the global energy transition and sustainable development.

Keywords: geothermal reservoirs, THMC coupling, interdisciplinary approaches, challenges and opportunities, sustainable utilization

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Authors: Leei Wong

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Changes in globalized contexts precipitate changing perceptions concerning linguistic politeness practices. Within these changing contexts, misunderstanding or stereotypification of politeness norms may lead to negative consequences such as hostility or even communication breakdown. With China’s rising influence, the country is offering a vast potential market for global economic development and diplomatic relations and opportunities for intercultural interaction, and many outside China are subsequently learning Chinese. These trends bring both opportunities and pitfalls for intercultural communication, including within the important field of politeness awareness. One internationally recognized benchmark for the study and classification of languages – the updated 2018 CEFR (Common European Framework of Reference for Language) Companion Volume New Descriptors (CEFR/CV) – classifies politeness as a B1 (or intermediate) level descriptor on the scale of Politeness Conventions. This provides some indication of the relevance of politeness awareness within new globalized contexts for fostering better intercultural communication. This study specifically examines Bald on record politeness strategies presented in current beginner TCAL textbooks used in Australian tertiary education through content-analysis. The investigation in this study involves the purposive sampling of commercial textbooks published in America and China followed by interpretive content analysis. The philosophical position of this study is therefore located within an interpretivist ontology, with a subjectivist epistemological perspective. It sets out with the aim to illuminate the characteristics of Chinese Bald on record strategies that are deemed significant in the present-world context through Chinese textbook writers and curriculum designers. The data reveals significant findings concerning politeness strategies in beginner stage curriculum, and also opens the way for further research on politeness strategies in intermediate and advanced level textbooks for additional language learners. This study will be useful for language teachers, and language teachers-in-training, by generating awareness and providing insights and advice into the teaching and learning of Bald on record politeness strategies. Authors of textbooks may also benefit from the findings of this study, as awareness is raised of the need to include reference to understanding politeness in language, and how this might be approached.

Keywords: linguistic politeness, higher education, Chinese language, additional language

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Authors: Riddhiman Sherlekar, Umang Paladia, Rachit Desai, Yash Patel

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The competitive scenario of the oil and gas market is a challenge for today’s plant designers to achieve designs that meet client expectations with shrinking budgets, safety requirements, and operating flexibility. Natural Gas Liquids have three main industrial uses. They can be used as fuels, or as petrochemical feedstock or as refinery blends that can be further processed and sold as straight run cuts, such as naphtha, kerosene and gas oil. NGL extraction is not a chemical reaction. It involves the separation of heavier hydrocarbons from the main gas stream through pressure as temperature reduction, which depending upon the degree of NGL extraction may involve cryogenic process. Previous technologies i.e. short cycle dry desiccant absorption, Joule-Thompson or Low temperature refrigeration, lean oil absorption have been giving results of only 40 to 45% ethane recoveries, which were unsatisfying depending upon the current scenario of down turn market. Here new technology has been suggested for boosting up the recoveries of ethane+ up to 95% and up to 99% for propane+ components. Cryogenic plants provide reboiling to demethanizers by using part of inlet feed gas, or inlet feed split. If the two stream temperatures are not similar, there is lost work in the mixing operation unless the designer has access to some proprietary design. The concept introduced in this process consists of reboiling the demethanizer with the residue gas, or residue gas split. The innovation of this process is that it does not use the typical inlet gas feed split type of flow arrangement to reboil the demethanizer or deethanizer column, but instead uses an open heat pump scheme to that effect. The residue gas compressor provides the heat pump effect. The heat pump stream is then further cooled and entered in the top section of the column as a cold reflux. Because of the nature of this design, this process offers the opportunity to operate at full ethane rejection or recovery. The scheme is also very adaptable to revamp existing facilities. This advancement can be proven not only in enhancing the results but also provides operational flexibility, optimize heat exchange, introduces equipment cost reduction, opens a future for the innovative designs while keeping execution costs low.

Keywords: deethanizer, demethanizer, residue gas, NGL

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Authors: Abeer Heider

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This paper explores and classifies the different kinds of avoidances that students commonly make in the acquisition of Arabic as a second/foreign language, and suggests specific strategies to help students lessen their avoidance trends in hopes of streamlining the learning process. Students most commonly use avoidance strategies in grammar, and word choice. These different types of strategies have different implications and naturally require different approaches. Thus the question remains as to the most effective way to help students improve their Arabic, and how teachers can efficiently utilize these techniques. It is hoped that this research will contribute to understand the role of avoidance in the field of the second language acquisition in general, and as a type of input. Yet some researchers also note that similarity between L1 and L2 may be problematic as well since the learner may doubt that such similarity indeed exists and consequently avoid the identical constructions or elements (Jordens, 1977; Kellermann, 1977, 1978, 1986). In an effort to resolve this issue, a case study is being conducted. The present case study attempts to provide a broader analysis of what is acquired than is usually the case, analyzing the learners ‘accomplishments in terms of three –part framework of the components of communicative competence suggested by Michele Canale: grammatical competence, sociolinguistic competence and discourse competence. The subjects of this study are 15 students’ 22th year who came to study Arabic at Qatar University of Cairo. The 15 students are in the advanced level. They were complete intermediate level in Arabic when they arrive in Qatar for the first time. The study used discourse analytic method to examine how the first language affects students’ production and output in the second language, and how and when students use avoidance methods in their learning. The study will be conducted through Fall 2015 through analyzing audio recordings that are recorded throughout the entire semester. The recordings will be around 30 clips. The students are using supplementary listening and speaking materials. The group will be tested at the end of the term to assess any measurable difference between the techniques. Questionnaires will be administered to teachers and students before and after the semester to assess any change in attitude toward avoidance and selectivity methods. Responses to these questionnaires are analyzed and discussed to assess the relative merits of the aforementioned strategies to avoidance and selectivity to further support on. Implications and recommendations for teacher training are proposed.

Keywords: the second language acquisition, learning languages, selectivity, avoidance

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Authors: Hsiu-Ling Hsu, En-Minh (John) Lan

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Pronunciation has received more and more language researchers’ and teachers’ attention because it is important for effective or even successful communication. How to consistently and correctly orally produce verbal morphology, such as English regular past tense inflection, has been a big challenge and troublesome for FL learners. The research aims to explore EFL (English as a foreign language) learners’ developmental trajectory of the inflectional morphology, that is, what mediating processes and strategies EFL learners use, to attain native-like prosodic structure of inflectional morphemes (e.g., –ed and –s suffixes) by comparing the differences among EFL learners at different English levels. This research adopted a self-repair analysis and Prosodic Transfer Hypothesis with three developmental stages as a theoretical framework. To answer the research questions, we conducted two experiments, grammatical tense test written production (Experiment 1) and read-aloud oral production (Experiment 2), and recruited 30 participants who were divided into three groups, low-, middle-, and advanced EFL learners. Experiment 1 was conducted to ensure that participants had learned the knowledge of forming the English regular past tense rules and Experiment 2 was carried out to compare the data across FL English learner groups at different English levels. The EFL learners’ self-repair data showed at least four interesting findings. First, low achievers were more sensitive to the plural suffix -s than the past tense suffix -ed. Middle achievers exhibited a greater responsiveness to the past tense suffix, while high achievers demonstrated equal sensitivity to both suffixes. Additionally, two strategies used by EFL English learners to produce verbs and nouns with inflectional morphemes were to delete internal syllable and to divide a four-syllable verb (e.g., ‘graduated’) into two prosodic structures (e.g., ‘gradu’ and ‘ated’ or ‘gradua’ and ‘ted’). Third, true vowel epenthesis was found only in the low EFL achievers. Moreover fortition (native-like sound) was observed in the low and middle EFL achievers. These findings and self-repair data disclosed mediating processes between the developmental stages and provided insight on how Taiwan EFL learners attained the adjunction prosodic structures of inflectional Morphemes in English.

Keywords: inflectional morphology, prosodic structure, developmental trajectory, strategies and mediating processes, English as a foreign language

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Authors: Joel F. Campbell, Bing Lin, Michael Obland, Susan Kooi, Tai-Fang Fan, Byron Meadows, Edward Browell, Wayne Erxleben, Doug McGregor, Jeremy Dobler, Sandip Pal, Christopher O'Dell, Ken Davis

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The Active Sensing of CO₂ Emissions over Nights, Days, and Seasons (ASCENDS) CarbonHawk Experiment Simulator (ACES) is a NASA Langley Research Center instrument funded by NASA’s Science Mission Directorate that seeks to advance technologies critical to measuring atmospheric column carbon dioxide (CO₂ ) mixing ratios in support of the NASA ASCENDS mission. The ACES instrument, an Intensity-Modulated Continuous-Wave (IM-CW) lidar, was designed for high-altitude aircraft operations and can be directly applied to space instrumentation to meet the ASCENDS mission requirements. The ACES design demonstrates advanced technologies critical for developing an airborne simulator and spaceborne instrument with lower platform consumption of size, mass, and power, and with improved performance. The Atmospheric Carbon and Transport – America (ACT-America) is an Earth Venture Suborbital -2 (EVS-2) mission sponsored by the Earth Science Division of NASA’s Science Mission Directorate. A major objective is to enhance knowledge of the sources/sinks and transport of atmospheric CO₂ through the application of remote and in situ airborne measurements of CO₂ and other atmospheric properties on spatial and temporal scales. ACT-America consists of five campaigns to measure regional carbon and evaluate transport under various meteorological conditions in three regional areas of the Continental United States. Regional CO₂ distributions of the lower atmosphere were observed from the C-130 aircraft by the Harris Corp. Multi-Frequency Fiber Laser Lidar (MFLL) and the ACES lidar. The airborne lidars provide unique data that complement the more traditional in situ sensors. This presentation shows the applications of CO₂ lidars in support of these science needs.

Keywords: CO₂ measurement, IMCW, CW lidar, laser spectroscopy

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Authors: Charbel Aoun, Loic Lagadec

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A Sensor Network (SN) is considered as an operation of two phases: (1) the observation/measuring, which means the accumulation of the gathered data at each sensor node; (2) transferring the collected data to some processing center (e.g., Fusion Servers) within the SN. Therefore, an underwater sensor network can be defined as a sensor network deployed underwater that monitors underwater activity. The deployed sensors, such as Hydrophones, are responsible for registering underwater activity and transferring it to more advanced components. The process of data exchange between the aforementioned components perfectly defines the Marine Observatory (MO) concept which provides information on ocean state, phenomena and processes. The first step towards the implementation of this concept is defining the environmental constraints and the required tools and components (Marine Cables, Smart Sensors, Data Fusion Server, etc). The logical and physical components that are used in these observatories perform some critical functions such as the localization of underwater moving objects. These functions can be orchestrated with other services (e.g. military or civilian reaction). In this paper, we present an extension to our MO meta-model that is used to generate a design tool (ArchiMO). We propose new constraints to be taken into consideration at design time. We illustrate our proposal with an example from the MO domain. Additionally, we generate the corresponding simulation code using our self-developed domain-specific model compiler. On the one hand, this illustrates our approach in relying on Enterprise Architecture (EA) framework that respects: multiple views, perspectives of stakeholders, and domain specificity. On the other hand, it helps reducing both complexity and time spent in design activity, while preventing from design modeling errors during porting this activity in the MO domain. As conclusion, this work aims to demonstrate that we can improve the design activity of complex system based on the use of MDE technologies and a domain-specific modeling language with the associated tooling. The major improvement is to provide an early validation step via models and simulation approach to consolidate the system design.

Keywords: smart sensors, data fusion, distributed fusion architecture, sensor networks, domain specific modeling language, enterprise architecture, underwater moving object, localization, marine observatory, NS-3, IMS

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Authors: Yi-Hsuan Gloria Lo

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The educational objective of vocational high schools (VHSs) is to equip VHS students with practical skills and knowledge that can be applied in the job-related market. However, with the increasing number of technological universities over the past two decades, the majority of VHS students have chosen to receive higher education rather than enter the job market. VHS English education has been confronting a dilemma: Should an English for specific purposes (ESP) approach, which aligns with the educational goal of VHS education, be taken or should an English for general purposes (EGP) approach, which prepares VHS students for advanced studies in universities, be followed? While ESP theorists proposed that that ESP can be taught to secondary learners, little was known about VHS students’ perspective on this ESP-versus-EGP dilemma. Scant research has investigated different facets of students’ needs (necessities, wants, and lacks) for both ESP and EGP in terms of the four language skills and the factors that contribute to any differences. To address the gap in the literature, 100 VHS students responded to statements related to their necessities, wants, and lacks in learning ESP and EGP on a 6-point Likert scale. Six VHS students were interviewed to tap into the reasons for different facets of the needs for learning EGP and ESP. The statistical analysis indicates that at this stage of learning English, VHS subjects believed that EGP was more necessary than ESP; EGP was more desirable than ESP. However, they reported that they were more lacking in ESP than in EGP learning. Regarding EGP, the results show that the VHS subjects rated speaking as their most necessary skill, speaking as the most desirable skill, and writing as the most lacking skill. A significant difference was found between perceived learning necessities and lacks and between perceived wants and lacks. No statistical difference was found between necessities and wants. In the aspect of ESP, the results indicate that the VHS subjects marked reading as their most necessary skill, speaking as the most desirable skill, and writing as the most lacking skill. A significant difference exists between their perceived necessities and lacks and between their wants and lacks. However, there is no statistically significant difference between their perceived lacks and wants. Despite the lack of a significant difference between learning necessities and wants, the qualitative interview data reveal that the reasons for their perceived necessities and wants were different. The findings of the study confirm previous research that demonstrates that ‘needs’ is a multiple and conflicting construct. What VHS students felt most lacking was not necessarily what they believed they should learn or would like to learn. Although no statistical difference was found, different reasons were attributed to their perceived necessities and wants. Both theoretical and practical implications have been drawn and discussed for ESP research in general and teaching ESP in VHSs in particular.

Keywords: vocational high schools (VHSs), English for General Purposes (EGP), English for Specific Purposes (ESP), needs analysis

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Authors: Su Chul Han, Seungwoo Park

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As the increasing incidence of cancer, the technology and modality of radiotherapy have advanced and the importance of preclinical model is increasing in the cancer research. Furthermore, the small animal dosimetry is an essential part of the evaluation of the relationship between the absorbed dose in preclinical small animal and biological effect in preclinical study. In this study, we carried out realistic modeling of the preclinical small animal phantom possible to verify irradiated dose using commercial software. The small animal phantom was modeling from 4D Digital Mouse whole body phantom. To manipulate Moby phantom in commercial software (Mimics, Materialise, Leuven, Belgium), we converted Moby phantom to DICOM image file of CT by Matlab and two- dimensional of CT images were converted to the three-dimensional image and it is possible to segment and crop CT image in Sagittal, Coronal and axial view). The CT images of small animals were modeling following process. Based on the profile line value, the thresholding was carried out to make a mask that was connection of all the regions of the equal threshold range. Using thresholding method, we segmented into three part (bone, body (tissue). lung), to separate neighboring pixels between lung and body (tissue), we used region growing function of Mimics software. We acquired 3D object by 3D calculation in the segmented images. The generated 3D object was smoothing by remeshing operation and smoothing operation factor was 0.4, iteration value was 5. The edge mode was selected to perform triangle reduction. The parameters were that tolerance (0.1mm), edge angle (15 degrees) and the number of iteration (5). The image processing 3D object file was converted to an STL file to output with 3D printer. We modified 3D small animal file using 3- Matic research (Materialise, Leuven, Belgium) to make space for radiation dosimetry chips. We acquired 3D object of realistic small animal phantom. The width of small animal phantom was 2.631 cm, thickness was 2.361 cm, and length was 10.817. Mimics software supported efficiency about 3D object generation and usability of conversion to STL file for user. The development of small preclinical animal phantom would increase reliability of verification of absorbed dose in small animal for preclinical study.

Keywords: mimics, preclinical small animal, segmentation, 3D printer

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Authors: Matthew Baucum

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With the increasing popularity of fMRI as an experimental method, psychology and neuroscience can greatly benefit from advanced techniques for summarizing and synthesizing large amounts of data from brain imaging studies. One promising avenue is automated meta-analyses, in which natural language processing methods are used to identify the brain regions consistently associated with certain semantic concepts (e.g. “social”, “reward’) across large corpora of studies. This study builds on this approach by demonstrating how, in fMRI meta-analyses, individual voxels can be treated as vectors in a semantic space and evaluated for their “proximity” to terms of interest. In this technique, a low-dimensional semantic space is built from brain imaging study texts, allowing words in each text to be represented as vectors (where words that frequently appear together are near each other in the semantic space). Consequently, each voxel in a brain mask can be represented as a normalized vector sum of all of the words in the studies that showed activation in that voxel. The entire brain mask can then be visualized in terms of each voxel’s proximity to a given term of interest (e.g., “vision”, “decision making”) or collection of terms (e.g., “theory of mind”, “social”, “agent”), as measured by the cosine similarity between the voxel’s vector and the term vector (or the average of multiple term vectors). Analysis can also proceed in the opposite direction, allowing word cloud visualizations of the nearest semantic neighbors for a given brain region. This approach allows for continuous, fine-grained metrics of voxel-term associations, and relies on state-of-the-art “open vocabulary” methods that go beyond mere word-counts. An analysis of over 11,000 neuroimaging studies from an existing meta-analytic fMRI database demonstrates that this technique can be used to recover known neural bases for multiple psychological functions, suggesting this method’s utility for efficient, high-level meta-analyses of localized brain function. While automated text analytic methods are no replacement for deliberate, manual meta-analyses, they seem to show promise for the efficient aggregation of large bodies of scientific knowledge, at least on a relatively general level.

Keywords: FMRI, machine learning, meta-analysis, text analysis

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Authors: Sumit Kanwar, Manisha Chand, Gregory Gilot

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Background: Septic arthritis of the shoulder has infrequently been discussed. Focus on infection of the untouched shoulder has not heretofore been described. We present four patients with glenohumeral septic arthritis. Methods: Case 1: A 59 year old male with left shoulder pain in the anterior, posterior and superior aspects. Case 2: A 60 year old male with fever, chills, and generalized muscle aches. Case 3: A 70 year old male with right shoulder pain about the anterior and posterior aspects. Case 4: A 55 year old male with global right shoulder pain, swelling, and limited ROM. Results: In case 1, the left shoulder was affected. Physical examination, swelling was notable, there was global tenderness with a painful range of motion (ROM). The lab values indicated an erythrocyte sedimentation rate (ESR) of 96, and a C-reactive protein (CRP) of 304.30. Imaging studies were performed and MRI indicated a high suspicion for an abscess with osteomyelitis of the humeral head. Our second case’s left arm was affected. He had swelling, global tenderness and painful ROM. His ESR was 38, CRP was 14.9. X-ray showed severe arthritis. Case 3 differed with the right arm being affected. Again, global tenderness and painful ROM was observed. His ESR was 94, and CRP was 10.6. X-ray displayed an eroded glenoid space. Our fourth case’s right shoulder was affected. He had global tenderness and painful, limited ROM. ESR was 108 and CRP was 2.4. X-ray was non-significant. Discussion: Monoarticular septic arthritis of the virgin glenohumeral joint is seldom diagnosed in clinical practice. Common denominators include elevated ESR, painful, limited ROM, and involvement of the dominant arm. The male population is more frequently affected with an average age of 57. Septic arthritis is managed with incision and drainage or needle aspiration of synovial fluid supplemented with 3-6 weeks of intravenous antibiotics. Due to better irrigation and joint visualization, arthroscopy is preferred. Open surgical drainage may be indicated if the above methods fail. Conclusion: If a middle-aged male presents with vague anterior or posterior shoulder pain, elevated inflammatory markers and a low grade fever, an x-ray should be performed. If this displays degenerative joint disease, the complete further workup with advanced imaging, such as an MRI, CT scan, or an ultrasound. If these imaging modalities display anterior space joint effusion with soft tissue involvement, we can suspect septic arthritis of the untouched glenohumeral joint and surgery is indicated.

Keywords: glenohumeral joint, identification, infection, septic arthritis, shoulder

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Authors: Jingwen Ou

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Writing for academic purposes in a second or foreign language poses a significant challenge for non-native speakers, particularly at the tertiary level, where English academic writing for L2 students is often hindered by difficulties in academic discourse, including vocabulary, academic register, and organization. The past two decades have witnessed a rising popularity in the application of the data-driven learning (DDL) approach in EAP writing instruction. In light of such a trend, this study aims to enhance the integration of DDL into English for academic purposes (EAP) writing classrooms by investigating the perception of Chinese college students regarding the use of corpus tools for improving EAP writing. Additionally, the research explores their corpus consultation behaviors during training to provide insights into corpus-assisted EAP instruction for DDL practitioners. Given the uprising popularity of DDL, this research aims to investigate Chinese university students’ use of corpus tools with three main foci: 1) the influence of corpus tools on learning behaviours, 2) the influence of corpus tools on students’ academic writing performance outcomes, and 3) students’ perceptions and potential perceptional changes towards the use of such tools. Three corpus tools, CQPWeb, Sketch Engine, and LancsBox X, are selected for investigation due to the scarcity of empirical research on patterns of learners’ engagement with a combination of multiple corpora. The research adopts a pre-test / post-test design for the evaluation of students’ academic writing performance before and after the intervention. Twenty participants will be divided into two groups: an intervention and a non-intervention group. Three corpus training workshops will be delivered at the beginning, middle, and end of a semester. An online survey and three separate focus group interviews are designed to investigate students’ perceptions of the use of corpus tools for improving academic writing skills, particularly the rhetorical functions in different essay sections. Insights from students’ consultation sessions indicated difficulties with DDL practice, including insufficiency of time to complete all tasks, struggle with technical set-up, unfamiliarity with the DDL approach and difficulty with some advanced corpus functions. Findings from the main study aim to provide pedagogical insights and training resources for EAP practitioners and learners.

Keywords: corpus linguistics, data-driven learning, English for academic purposes, tertiary education in China

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Authors: Sourabh Jain, S. S. Jain

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Intelligent transportation system (ITS) is the application of technologies for developing a user–friendly transportation system to extend the safety and efficiency of urban transportation systems in developing countries. These systems involve vehicles, drivers, passengers, road operators, managers of transport services; all interacting with each other and the surroundings to boost the security and capacity of road systems. The goal of urban corridor management using ITS in road transport is to achieve improvements in mobility, safety, and the productivity of the transportation system within the available facilities through the integrated application of advanced monitoring, communications, computer, display, and control process technologies, both in the vehicle and on the road. Intelligent transportation system is a product of the revolution in information and communications technologies that is the hallmark of the digital age. The basic ITS technology is oriented on three main directions: communications, information, integration. Information acquisition (collection), processing, integration, and sorting are the basic activities of ITS. In the paper, attempts have been made to present the endeavor that was made to interpret and evaluate the performance of the 27.4 Km long study corridor having eight intersections and four flyovers. The corridor consisting of six lanes as well as eight lanes divided road network. Two categories of data have been collected such as traffic data (traffic volume, spot speed, delay) and road characteristics data (no. of lanes, lane width, bus stops, mid-block sections, intersections, flyovers). The instruments used for collecting the data were video camera, stop watch, radar gun, and mobile GPS (GPS tracker lite). From the analysis, the performance interpretations incorporated were the identification of peak and off-peak hours, congestion and level of service (LOS) at midblock sections and delay followed by plotting the speed contours. The paper proposed the urban corridor management strategies based on sensors integrated into both vehicles and on the roads that those have to be efficiently executable, cost-effective, and familiar to road users. It will be useful to reduce congestion, fuel consumption, and pollution so as to provide comfort, safety, and efficiency to the users.

Keywords: ITS strategies, congestion, planning, mobility, safety

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Authors: Marion G. Ben-Jacob, David Wang

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There is a mathematics requirement for entry level college and university students, especially those who plan to study STEM (Science, Technology, Engineering and Mathematics). Most of them take College Algebra, and to continue their studies, they need to succeed in this course. Different pedagogical strategies are employed to promote the success of our students. There is, of course, the Traditional Method of teaching- lecture, examples, problems for students to solve. The Emporium Model, another pedagogical approach, replaces traditional lectures with a learning resource center model featuring interactive software and on-demand personalized assistance. This presentation will compare these two methods of pedagogy and the study done with its results on this comparison. Math is the foundation for science, technology, and engineering. Its work is generally used in STEM to find patterns in data. These patterns can be used to test relationships, draw general conclusions about data, and model the real world. In STEM, solutions to problems are analyzed, reasoned, and interpreted using math abilities in a assortment of real-world scenarios. This presentation will examine specific examples of how math is used in the different STEM disciplines. Math becomes practical in science when it is used to model natural and artificial experiments to identify a problem and develop a solution for it. As we analyze data, we are using math to find the statistical correlation between the cause of an effect. Scientists who use math include the following: data scientists, scientists, biologists and geologists. Without math, most technology would not be possible. Math is the basis of binary, and without programming, you just have the hardware. Addition, subtraction, multiplication, and division is also used in almost every program written. Mathematical algorithms are inherent in software as well. Mechanical engineers analyze scientific data to design robots by applying math and using the software. Electrical engineers use math to help design and test electrical equipment. They also use math when creating computer simulations and designing new products. Chemical engineers often use mathematics in the lab. Advanced computer software is used to aid in their research and production processes to model theoretical synthesis techniques and properties of chemical compounds. Mathematics mastery is crucial for success in the STEM disciplines. Pedagogical research on formative strategies and necessary topics to be covered are essential.

Keywords: emporium model, mathematics, pedagogy, STEM

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Authors: Magdalena Korytowska, Gunnar Lengstrand, Cecilia Larsson Wexell

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Background: Breast cancer (BC) is the most common cancer among women worldwide, and cases are continuing to increase in Sweden. Bone is the most common metastatic site in breast cancer patients, where > 65-75% of women with advanced breast cancer develop bone metastases during their disease. To prevent the skeletal-related events of metastases (e.g., pathological fractures, bone loss, cancer-induced bone pain, and hypercalcemia bone), two different classes of antiresorptive medications (AR), bisphosphonate and denosumab are typically administered every 3 to 4 weeks. Since 2015, adjuvant bisphosphonate treatment has been used every six months for three to five years in postmenopausal women for the prevention of skeletal metastases and improved survival. Methods: A case-control study was conducted to test the hypotheses that patients treated with high-dose AR are at higher risk of developing MRONJ than breast cancer patients with adjuvant bisphosphonate treatment at a lower dose. Medical and odontological data was collected between 2015-2020. Assessment of oral health and dental care before and during oncological treatment took place at the specialist clinic for Orofacial medicine linked to the specific hospital. Results: In total, 220 patients were included, 101 patients in the high-dose group and 119 patients in the adjuvant BP-treatment group. MRONJ was diagnosed in 13 patients (14%) in the high-dose group. The mandible was affected in most of the cases (84.6%), with a mean duration of high-dose treatment of 19.7 months. In 46.2% of cases, no dental cause of MRONJ could be identified. Overall, estrogen receptor-positive (ER+) BC was the most representative type in 172 patients (78.2%). However, this was 83.9% in the high-dose cases group. The most used drug was denosumab. Twenty-five patients (26.9%) switched their medication from ZOL to denosumab during their oncological treatment. Patients with ER+ breast cancer were reported in 88 patients (87.8%) in the adjuvant group that was treated with ZOL. Conclusions: MRONJ was diagnosed only in the high-dose AR group. Dental assessment and care of patients in the adjuvant group should be considered, with a recommendation to potentially prolong ZOL treatment from 3 to 5 years, with concomitant use of hormonal therapy in patients diagnosed with ER+ breast cancer to prevent bone loss induced by oncological treatment. A new referral for dental assessment is very important in the case of bone metastases when treatment with high dose AR will be required since it is associated with a higher risk of MRONJ.

Keywords: antiresorptive therapy, breast cancer, dental care, MRONJ

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