Search results for: clinical application
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 11637

Search results for: clinical application

1137 Tunable Crystallinity of Zinc Gallogermanate Nanoparticles via Organic Ligand-Assisted Biphasic Hydrothermal Synthesis

Authors: Sarai Guerrero, Lijia Liu

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Zinc gallogermanate (ZGGO) is a persistent phosphor that can emit in the near infrared (NIR) range once dopped with Cr³⁺ enabling its use for in-vivo deep-tissue bio-imaging. Such a property also allows for its application in cancer diagnosis and therapy. Given this, work into developing a synthetic procedure that can be done using common laboratory instruments and equipment as well as understanding ZGGO overall, is in demand. However, the ZGGO nanoparticles must have a size compatible for cell intake to occur while still maintaining sufficient photoluminescence. The nanoparticle must also be made biocompatible by functionalizing the surface for hydrophilic solubility and for high particle uniformity in the final product. Additionally, most research is completed on doped ZGGO, leaving a gap in understanding the base form of ZGGO. It also leaves a gap in understanding how doping affects the synthesis of ZGGO. In this work, the first step of optimizing the particle size via the crystalline size of ZGGO was done with undoped ZGGO using the organic acid, oleic acid (OA) for organic ligand-assisted biphasic hydrothermal synthesis. The effects of this synthesis procedure on ZGGO’s crystallinity were evaluated using Powder X-Ray Diffraction (PXRD). OA was selected as the capping ligand as experiments have shown it beneficial in synthesizing sub-10 nm zinc gallate (ZGO) nanoparticles as well as palladium nanocrystals and magnetite (Fe₃O₄) nanoparticles. Later it is possible to substitute OA with a different ligand allowing for hydrophilic solubility. Attenuated Total Reflection Fourier-Transform Infrared (ATR-FTIR) was used to investigate the surface of the nanoparticle to investigate and verify that OA had capped the nanoparticle. PXRD results showed that using this procedure led to improved crystallinity, comparable to the high-purity reagents used on the ZGGO nanoparticles. There was also a change in the crystalline size of the ZGGO nanoparticles. ATR-FTIR showed that once capped ZGGO cannot be annealed as doing so will affect the OA. These results point to this new procedure positively affecting the crystallinity of ZGGO nanoparticles. There are also repeatable implying the procedure is a reliable source of highly crystalline ZGGO nanoparticles. With this completed, the next step will be working on substituting the OA with a hydrophilic ligand. As these ligands effect the solubility of the nanoparticle as well as the pH that the nanoparticles can dissolve in, further research is needed to verify which ligand is best suited for preparing ZGGO for bio-imaging.

Keywords: biphasic hydrothermal synthesis, crystallinity, oleic acid, zinc gallogermanate

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1136 A Method for Evaluating Gender Equity of Cycling from Rawls Justice Perspective

Authors: Zahra Hamidi

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Promoting cycling, as an affordable environmentally friendly mode of transport to replace private car use has been central to sustainable transport policies. Cycling is faster than walking and combined with public transport has the potential to extend the opportunities that people can access. In other words, cycling, besides direct positive health impacts, can improve people mobility and ultimately their quality of life. Transport literature well supports the close relationship between mobility, quality of life, and, well being. At the same time inequity in the distribution of access and mobility has been associated with the key aspects of injustice and social exclusion. The pattern of social exclusion and inequality in access are also often related to population characteristics such as age, gender, income, health, and ethnic background. Therefore, while investing in transport infrastructure it is important to consider the equity of provided access for different population groups. This paper proposes a method to evaluate the equity of cycling in a city from Rawls egalitarian perspective. Since this perspective is concerned with the difference between individuals and social groups, this method combines accessibility measures and Theil index of inequality that allows capturing the inequalities ‘within’ and ‘between’ groups. The paper specifically focuses on two population characteristics as gender and ethnic background. Following Rawls equity principles, this paper measures accessibility by bikes to a selection of urban activities that can be linked to the concept of the social primary goods. Moreover, as growing number of cities around the world have launched bike-sharing systems (BSS) this paper incorporates both private and public bikes networks in the estimation of accessibility levels. Additionally, the typology of bike lanes (separated from or shared with roads), the presence of a bike sharing system in the network, as well as bike facilities (e.g. parking racks) have been included in the developed accessibility measures. Application of this proposed method to a real case study, the city of Malmö, Sweden, shows its effectiveness and efficiency. Although the accessibility levels were estimated only based on gender and ethnic background characteristics of the population, the author suggests that the analysis can be applied to other contexts and further developed using other properties, such as age, income, or health.

Keywords: accessibility, cycling, equity, gender

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1135 Advanced Compound Coating for Delaying Corrosion of Fast-Dissolving Alloy in High Temperature and Corrosive Environment

Authors: Lei Zhao, Yi Song, Tim Dunne, Jiaxiang (Jason) Ren, Wenhan Yue, Lei Yang, Li Wen, Yu Liu

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Fasting dissolving magnesium (DM) alloy technology has contributed significantly to the “Shale Revolution” in oil and gas industry. This application requires DM downhole tools dissolving initially at a slow rate, rapidly accelerating to a high rate after certain period of operation time (typically 8 h to 2 days), a contradicting requirement that can hardly be addressed by traditional Mg alloying or processing itself. Premature disintegration has been broadly reported in downhole DM tool from field trials. To address this issue, “temporary” thin polymers of various formulations are currently coated onto DM surface to delay its initial dissolving. Due to conveying parts, harsh downhole condition, and high dissolving rate of the base material, the current delay coatings relying on pure polymers are found to perform well only at low temperature (typical < 100 ℃) and parts without sharp edges or corners, as severe geometries prevent high quality thin film coatings from forming effectively. In this study, a coating technology combining Plasma Electrolytic Oxide (PEO) coatings with advanced thin film deposition has been developed, which can delay DM complex parts (with sharp corners) in corrosive fluid at 150 ℃ for over 2 days. Synergistic effects between porous hard PEO coating and chemical inert elastic-polymer sealing leads to its delaying dissolution improvement, and strong chemical/physical bonding between these two layers has been found to play essential role. Microstructure of this advanced coating and compatibility between PEO and various polymer selections has been thoroughly investigated and a model is also proposed to explain its delaying performance. This study could not only benefit oil and gas industry to unplug their High Temperature High Pressure (HTHP) unconventional resources inaccessible before, but also potentially provides a technical route for other industries (e.g., bio-medical, automobile, aerospace) where primer anti-corrosive protection on light Mg alloy is highly demanded.

Keywords: dissolvable magnesium, coating, plasma electrolytic oxide, sealer

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1134 Flipped Learning in Interpreter Training: Technologies, Activities and Student Perceptions

Authors: Dohun Kim

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Technological innovations have stimulated flipped learning in many disciplines, including language teaching. It is a specific type of blended learning, which combines onsite (i.e. face-to-face) with online experiences to produce effective, efficient and flexible learning. Flipped learning literally ‘flips’ conventional teaching and learning activities upside down: it leverages technologies to deliver a lecture and direct instruction—other asynchronous activities as well—outside the classroom to reserve onsite time for interaction and activities in the upper cognitive realms: applying, analysing, evaluating and creating. Unlike the conventional flipped approaches, which focused on video lecture, followed by face-to-face or on-site session, new innovative methods incorporate various means and structures to serve the needs of different academic disciplines and classrooms. In the light of such innovations, this study adopted ‘student-engaged’ approaches to interpreter training and contrasts them with traditional classrooms. To this end, students were also encouraged to engage in asynchronous activities online, and innovative technologies, such as Telepresence, were employed. Based on the class implementation, a thorough examination was conducted to examine how we can structure and implement flipped classrooms for language and interpreting training while actively engaging learners. This study adopted a quantitative research method, while complementing it with a qualitative one. The key findings suggest that the significance of the instructor’s role does not dwindle, but his/her role changes to a moderator and a facilitator. Second, we can apply flipped learning to both theory- and practice-oriented modules. Third, students’ integration into the community of inquiry is of significant importance to foster active and higher-order learning. Fourth, cognitive presence and competence can be enhanced through strengthened and integrated teaching and social presences. Well-orchestrated teaching presence stimulates students to find out the problems and voices the convergences and divergences, while fluid social presence facilitates the exchanges of knowledge and the adjustment of solutions, which eventually contributes to consolidating cognitive presence—a key ingredient that enables the application and testing of the solutions and reflection thereon.

Keywords: blended learning, Community of Inquiry, flipped learning, interpreter training, student-centred learning

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1133 Leveraging xAPI in a Corporate e-Learning Environment to Facilitate the Tracking, Modelling, and Predictive Analysis of Learner Behaviour

Authors: Libor Zachoval, Daire O Broin, Oisin Cawley

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E-learning platforms, such as Blackboard have two major shortcomings: limited data capture as a result of the limitations of SCORM (Shareable Content Object Reference Model), and lack of incorporation of Artificial Intelligence (AI) and machine learning algorithms which could lead to better course adaptations. With the recent development of Experience Application Programming Interface (xAPI), a large amount of additional types of data can be captured and that opens a window of possibilities from which online education can benefit. In a corporate setting, where companies invest billions on the learning and development of their employees, some learner behaviours can be troublesome for they can hinder the knowledge development of a learner. Behaviours that hinder the knowledge development also raise ambiguity about learner’s knowledge mastery, specifically those related to gaming the system. Furthermore, a company receives little benefit from their investment if employees are passing courses without possessing the required knowledge and potential compliance risks may arise. Using xAPI and rules derived from a state-of-the-art review, we identified three learner behaviours, primarily related to guessing, in a corporate compliance course. The identified behaviours are: trying each option for a question, specifically for multiple-choice questions; selecting a single option for all the questions on the test; and continuously repeating tests upon failing as opposed to going over the learning material. These behaviours were detected on learners who repeated the test at least 4 times before passing the course. These findings suggest that gauging the mastery of a learner from multiple-choice questions test scores alone is a naive approach. Thus, next steps will consider the incorporation of additional data points, knowledge estimation models to model knowledge mastery of a learner more accurately, and analysis of the data for correlations between knowledge development and identified learner behaviours. Additional work could explore how learner behaviours could be utilised to make changes to a course. For example, course content may require modifications (certain sections of learning material may be shown to not be helpful to many learners to master the learning outcomes aimed at) or course design (such as the type and duration of feedback).

Keywords: artificial intelligence, corporate e-learning environment, knowledge maintenance, xAPI

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1132 Implementing Simulation-Based Education as a Transformative Learning Strategy in Nursing and Midwifery Curricula in Resource-Constrained Countries: The Case of Malawi

Authors: Patrick Mapulanga, Chisomo Petros Ganya

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Purpose: This study aimed to investigate the integration of Simulation-Based Education (SBE) into nursing and midwifery curricula in resource-constrained countries using Malawi as a case study. The purpose of this study is to assess the extent to which SBE is mentioned in curricula and explore the associated content, assessment criteria, and guidelines. Methodology: The research methodology involved a desk study of nursing and midwifery curricula in Malawi. A comprehensive review was conducted to identify references to SBE by examining documents such as official curriculum guides, syllabi, and educational policies. The focus is on understanding the prevalence of SBE without delving into the specific content or assessment details. Findings: The findings revealed that SBE is indeed mentioned in the nursing and midwifery curricula in Malawi; however, there is a notable absence of detailed content and assessment criteria. While acknowledgement of SBE is a positive step, the lack of specific guidelines poses a challenge to its effective implementation and assessment within the educational framework. Conclusion: The study concludes that although the recognition of SBE in Malawian nursing and midwifery curricula signifies a potential openness to innovative learning strategies, the absence of detailed content and assessment criteria raises concerns about the practical application of SBE. Addressing this gap is crucial for harnessing the full transformative potential of SBE in resource-constrained environments. Areas for Further Research: Future research endeavours should focus on a more in-depth exploration of the content and assessment criteria related to SBE in nursing and midwifery curricula. Investigating faculty perspectives and students’ experiences with SBE could provide valuable insights into the challenges and opportunities associated with its implementation. Study Limitations and Implications: The study's limitations include reliance on desk-based analysis, which limits the depth of understanding regarding SBE implementation. Despite this constraint, the implications of the findings underscore the need for curriculum developers, educators, and policymakers to collaboratively address the gaps in SBE integration and ensure a comprehensive and effective learning experience for nursing and midwifery students in resource-constrained countries.

Keywords: simulation based education, transformative learning, nursing and midwifery, curricula, Malawi

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1131 The Role of Artificial Intelligence in Creating Personalized Health Content for Elderly People: A Systematic Review Study

Authors: Mahnaz Khalafehnilsaz, Rozina Rahnama

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Introduction: The elderly population is growing rapidly, and with this growth comes an increased demand for healthcare services. Artificial intelligence (AI) has the potential to revolutionize the delivery of healthcare services to the elderly population. In this study, the various ways in which AI is used to create health content for elderly people and its transformative impact on the healthcare industry will be explored. Method: A systematic review of the literature was conducted to identify studies that have investigated the role of AI in creating health content specifically for elderly people. Several databases, including PubMed, Scopus, and Web of Science, were searched for relevant articles published between 2000 and 2022. The search strategy employed a combination of keywords related to AI, personalized health content, and the elderly. Studies that utilized AI to create health content for elderly individuals were included, while those that did not meet the inclusion criteria were excluded. A total of 20 articles that met the inclusion criteria were identified. Finding: The findings of this review highlight the diverse applications of AI in creating health content for elderly people. One significant application is the use of natural language processing (NLP), which involves the creation of chatbots and virtual assistants capable of providing personalized health information and advice to elderly patients. AI is also utilized in the field of medical imaging, where algorithms analyze medical images such as X-rays, CT scans, and MRIs to detect diseases and abnormalities. Additionally, AI enables the development of personalized health content for elderly patients by analyzing large amounts of patient data to identify patterns and trends that can inform healthcare providers in developing tailored treatment plans. Conclusion: AI is transforming the healthcare industry by providing a wide range of applications that can improve patient outcomes and reduce healthcare costs. From creating chatbots and virtual assistants to analyzing medical images and developing personalized treatment plans, AI is revolutionizing the way healthcare is delivered to elderly patients. Continued investment in this field is essential to ensure that elderly patients receive the best possible care.

Keywords: artificial intelligence, health content, older adult, healthcare

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1130 Tick Infestation and its Implications on Health and Welfare of Cattle under Pastoral System in Nigeria

Authors: Alabi Olufemi, Adeyanju Taiwo, Oloruntoba Oluwasegun, Adeleye Bobola, Alabi Oyekemi

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The pastoral system is a predominant form of cattle production in Nigeria, characterized by extensive grazing on communal lands. However, this system is challenged by various factors, including tick infestation, which significantly affects cattle health and welfare hence this investigation which aims to provide an in-depth understanding of tick infestation in the context of Nigerian pastoral systems, emphasizing its impact on cattle health and welfare. The country harbors a diverse array of tick species that affect cattle. These ticks belong to different genera, including Rhipicephalus, Amblyomma, and Hyalomma, among others. Each species has unique characteristics, life cycles, and host preferences, contributing to the complexity of tick infestation dynamics in pastoral settings. Tick infestation has numerous detrimental effects on cattle health. The direct effects include blood loss, anemia, skin damage due to feeding, and the transmission of pathogens that cause diseases such as anaplasmosis, babesiosis, and theileriosis. Indirectly, tick infestation can lead to reduced productivity, weight loss, and increased susceptibility to other diseases.The welfare of cattle in Nigerian pastoral systems is significantly impacted by tick infestation. Infested cattle often exhibit signs of distress, including restlessness, reduced grazing activity, and altered behavior. Furthermore, the discomfort caused by tick bites can lead to chronic stress, compromising the overall welfare of the animals. Effective tick control is crucial for mitigating the impact of infestation on cattle health and welfare. Strategies such as acaricide application, pasture management, genetic selection for tick resistance cattle, and vaccination against tick-borne diseases are commonly used. Tick infestation presents a significant challenge to cattle production under the pastoral system in Nigeria. It not only impacts cattle health but also compromises their welfare. Addressing the issue of tick infestation requires a multifaceted approach that integrates effective control strategies with sustainable management practices. Further research is needed to develop tailored interventions that account for the unique characteristics of Nigerian pastoral systems, ultimately ensuring the well-being and productivity of cattle in these settings.

Keywords: tick infestation, pastoral system, welfare, cattle

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1129 In vitro and in vivo Anticancer Activity of Nanosize Zinc Oxide Composites of Doxorubicin

Authors: Emma R. Arakelova, Stepan G. Grigoryan, Flora G. Arsenyan, Nelli S. Babayan, Ruzanna M. Grigoryan, Natalia K. Sarkisyan

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Novel nanosize zinc oxide composites of doxorubicin obtained by deposition of 180 nm thick zinc oxide film on the drug surface using DC-magnetron sputtering of a zinc target in the form of gels (PEO+Dox+ZnO and Starch+NaCMC+Dox+ZnO) were studied for drug delivery applications. The cancer specificity was revealed both in in vitro and in vivo models. The cytotoxicity of the test compounds was analyzed against human cancer (HeLa) and normal (MRC5) cell lines using MTT colorimetric cell viability assay. IC50 values were determined and compared to reveal the cancer specificity of the test samples. The mechanistic study of the most active compound was investigated using Flow cytometry analyzing of the DNA content after PI (propidium iodide) staining. Data were analyzed with Tree Star FlowJo software using cell cycle analysis Dean-Jett-Fox module. The in vivo anticancer activity estimation experiments were carried out on mice with inoculated ascitic Ehrlich’s carcinoma at intraperitoneal introduction of doxorubicin and its zinc oxide compositions. It was shown that the nanosize zinc oxide film deposition on the drug surface leads to the selective anticancer activity of composites at the cellular level with the range of selectivity index (SI) from 4 (Starch+NaCMC+Dox+ZnO) to 200 (PEO(gel)+Dox+ZnO) which is higher than that of free Dox (SI = 56). The significant increase in vivo antitumor activity (by a factor of 2-2.5) and decrease of general toxicity of zinc oxide compositions of doxorubicin in the form of the above mentioned gels compared to free doxorubicin were shown on the model of inoculated Ehrlich's ascitic carcinoma. Mechanistic studies of anticancer activity revealed the cytostatic effect based on the high level of DNA biosynthesis inhibition at considerable low concentrations of zinc oxide compositions of doxorubicin. The results of studies in vitro and in vivo behavior of PEO+Dox+ZnO and Starch+NaCMC+Dox+ZnO composites confirm the high potential of the nanosize zinc oxide composites as a vector delivery system for future application in cancer chemotherapy.

Keywords: anticancer activity, cancer specificity, doxorubicin, zinc oxide

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1128 The Current Importance of the Rules of Civil Procedure in the Portuguese Legal Order: Between Legalism and Adequation

Authors: Guilherme Gomes, Jose Lebre de Freitas

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The rules of Civil Procedure that are defined in the Portuguese Civil Procedure Code of 2013 particularly their articles 552 to 626- represent the model that the legislator thought that would be more suitable for national civil litigation, from the moment the action is brought by the plaintiff to the moment when the sentence is issued. However, procedural legalism is no longer a reality in the Portuguese Civil Procedural Law. According to the article 547 of the code of 2013, the civil judge has a duty to adopt the procedure that better suits the circumstances of the case, whether or not it is the one defined by law. The main goal of our paper is to answer the question whether the formal adequation imposed by this article diminishes the importance of the Portuguese rules of Civil Procedure and their daily application by national civil judges. We will start by explaining the appearance of the abovementioned rules in the Civil Procedure Code of 2013. Then we will analyse, using specific examples that were obtained by the books we read, how the legal procedure defined in the abovementioned code does not suit the circumstances of some specific cases and is totally inefficient in some situations. After that, we will, by using the data obtained in the practical research that we are conducting in the Portuguese civil courts within the scope of our Ph.D. thesis (until now, we have been able to consult 150 civil lawsuits), verify whether and how judges and parties make the procedure more efficient and effective in the case sub judice. In the scope of our research, we have already reached some preliminary findings: 1) despite the fact that the legal procedure does not suit the circumstances of some civil lawsuits, there are only two situations of frequent use of formal adequation (the judge allowing the plaintiff to respond to the procedural exceptions deduced in the written defense and the exemption from prior hearing for the judges who never summon it), 2) the other aspects of procedural adequation (anticipation of the production of expert evidence, waiving of oral argument at the final hearing, written allegations, dismissal of the dispatch on the controversial facts and the examination of witnesses at the domicile of one of the lawyers) are still little used and 3) formal adequation tends to happen by initiative of the judge, as plaintiffs and defendants are afraid of celebrating procedural agreements in most situations. In short, we can say that, in the Portuguese legal order of the 21st century, the flexibility of the legal procedure, as it is defined in the law and applied by procedural subjects, does not affect the importance of the rules of Civil Procedure of the code of 2013.

Keywords: casuistic adequation, civil procedure code of 2013, procedural subjects, rules of civil procedure

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1127 Energy Storage Modelling for Power System Reliability and Environmental Compliance

Authors: Rajesh Karki, Safal Bhattarai, Saket Adhikari

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Reliable and economic operation of power systems are becoming extremely challenging with large scale integration of renewable energy sources due to the intermittency and uncertainty associated with renewable power generation. It is, therefore, important to make a quantitative risk assessment and explore the potential resources to mitigate such risks. Probabilistic models for different energy storage systems (ESS), such as the flywheel energy storage system (FESS) and the compressed air energy storage (CAES) incorporating specific charge/discharge performance and failure characteristics suitable for probabilistic risk assessment in power system operation and planning are presented in this paper. The proposed methodology used in FESS modelling offers flexibility to accommodate different configurations of plant topology. It is perceived that CAES has a high potential for grid-scale application, and a hybrid approach is proposed, which embeds a Monte-Carlo simulation (MCS) method in an analytical technique to develop a suitable reliability model of the CAES. The proposed ESS models are applied to a test system to investigate the economic and reliability benefits of the energy storage technologies in system operation and planning, as well as to assess their contributions in facilitating wind integration during different operating scenarios. A comparative study considering various storage system topologies are also presented. The impacts of failure rates of the critical components of ESS on the expected state of charge (SOC) and the performance of the different types of ESS during operation are illustrated with selected studies on the test system. The paper also applies the proposed models on the test system to investigate the economic and reliability benefits of the different ESS technologies and to evaluate their contributions in facilitating wind integration during different operating scenarios and system configurations. The conclusions drawn from the study results provide valuable information to help policymakers, system planners, and operators in arriving at effective and efficient policies, investment decisions, and operating strategies for planning and operation of power systems with large penetrations of renewable energy sources.

Keywords: flywheel energy storage, compressed air energy storage, power system reliability, renewable energy, system planning, system operation

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1126 Airborne CO₂ Lidar Measurements for Atmospheric Carbon and Transport: America (ACT-America) Project and Active Sensing of CO₂ Emissions over Nights, Days, and Seasons 2017-2018 Field Campaigns

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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1125 AI Predictive Modeling of Excited State Dynamics in OPV Materials

Authors: Pranav Gunhal., Krish Jhurani

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This study tackles the significant computational challenge of predicting excited state dynamics in organic photovoltaic (OPV) materials—a pivotal factor in the performance of solar energy solutions. Time-dependent density functional theory (TDDFT), though effective, is computationally prohibitive for larger and more complex molecules. As a solution, the research explores the application of transformer neural networks, a type of artificial intelligence (AI) model known for its superior performance in natural language processing, to predict excited state dynamics in OPV materials. The methodology involves a two-fold process. First, the transformer model is trained on an extensive dataset comprising over 10,000 TDDFT calculations of excited state dynamics from a diverse set of OPV materials. Each training example includes a molecular structure and the corresponding TDDFT-calculated excited state lifetimes and key electronic transitions. Second, the trained model is tested on a separate set of molecules, and its predictions are rigorously compared to independent TDDFT calculations. The results indicate a remarkable degree of predictive accuracy. Specifically, for a test set of 1,000 OPV materials, the transformer model predicted excited state lifetimes with a mean absolute error of 0.15 picoseconds, a negligible deviation from TDDFT-calculated values. The model also correctly identified key electronic transitions contributing to the excited state dynamics in 92% of the test cases, signifying a substantial concordance with the results obtained via conventional quantum chemistry calculations. The practical integration of the transformer model with existing quantum chemistry software was also realized, demonstrating its potential as a powerful tool in the arsenal of materials scientists and chemists. The implementation of this AI model is estimated to reduce the computational cost of predicting excited state dynamics by two orders of magnitude compared to conventional TDDFT calculations. The successful utilization of transformer neural networks to accurately predict excited state dynamics provides an efficient computational pathway for the accelerated discovery and design of new OPV materials, potentially catalyzing advancements in the realm of sustainable energy solutions.

Keywords: transformer neural networks, organic photovoltaic materials, excited state dynamics, time-dependent density functional theory, predictive modeling

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1124 Identifying Diabetic Retinopathy Complication by Predictive Techniques in Indian Type 2 Diabetes Mellitus Patients

Authors: Faiz N. K. Yusufi, Aquil Ahmed, Jamal Ahmad

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Predicting the risk of diabetic retinopathy (DR) in Indian type 2 diabetes patients is immensely necessary. India, being the second largest country after China in terms of a number of diabetic patients, to the best of our knowledge not a single risk score for complications has ever been investigated. Diabetic retinopathy is a serious complication and is the topmost reason for visual impairment across countries. Any type or form of DR has been taken as the event of interest, be it mild, back, grade I, II, III, and IV DR. A sample was determined and randomly collected from the Rajiv Gandhi Centre for Diabetes and Endocrinology, J.N.M.C., A.M.U., Aligarh, India. Collected variables include patients data such as sex, age, height, weight, body mass index (BMI), blood sugar fasting (BSF), post prandial sugar (PP), glycosylated haemoglobin (HbA1c), diastolic blood pressure (DBP), systolic blood pressure (SBP), smoking, alcohol habits, total cholesterol (TC), triglycerides (TG), high density lipoprotein (HDL), low density lipoprotein (LDL), very low density lipoprotein (VLDL), physical activity, duration of diabetes, diet control, history of antihypertensive drug treatment, family history of diabetes, waist circumference, hip circumference, medications, central obesity and history of DR. Cox proportional hazard regression is used to design risk scores for the prediction of retinopathy. Model calibration and discrimination are assessed from Hosmer Lemeshow and area under receiver operating characteristic curve (ROC). Overfitting and underfitting of the model are checked by applying regularization techniques and best method is selected between ridge, lasso and elastic net regression. Optimal cut off point is chosen by Youden’s index. Five-year probability of DR is predicted by both survival function, and Markov chain two state model and the better technique is concluded. The risk scores developed can be applied by doctors and patients themselves for self evaluation. Furthermore, the five-year probabilities can be applied as well to forecast and maintain the condition of patients. This provides immense benefit in real application of DR prediction in T2DM.

Keywords: Cox proportional hazard regression, diabetic retinopathy, ROC curve, type 2 diabetes mellitus

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1123 Using Health Literacy and Medico-Legal Guidance to Improve Restorative Dentistry Patient Information Leaflets

Authors: Hasneet K. Kalsi, Julie K. Kilgariff

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Introduction: Within dentistry, the process for gaining informed consent has become more complex. To consent for treatment, patients must understand all reasonable treatment options and associated risks and benefits. Consenting is therefore deeply embedded in health literacy. Patients attending for dental consultation are often presented with an array of information and choices, yet studies show patients recall less than half of the information provided immediately after. Appropriate and comprehensible patient information leaflets (PILs) may be useful aid memories. In 2016 the World Health Organisation set improving health literacy as a global priority. Soon after, Scotland’s 2017-2025 Making it Easier: A Health Literacy Action Plan followed. This project involved the review of Restorative PILs used within Dundee Dental Hospital to assess the Content and Readability. Method: The current PIL on Root Canal Treatment (RCT) was created in 2011. This predates the Montgomery vs. NHS Lanarkshire case, a ruling which significantly impacted dental consenting processes, as well as General Dental Council’s (GDC’s) Standards for the Dental Team and Faculty of General Dental Practice’s Good Practice Guidance on Clinical Examination and Record-Keeping. Current evidence-based guidance, including that stipulated by the GDC, was reviewed. A 20-point Essential Content Checklist was designed to conform to best practice guidance for valid consenting processes. The RCT leaflet was scored against this to ascertain if the content was satisfactory. Having ensured the content satisfied medicolegal requirements, health literacy considerations were reviewed regarding readability. This was assessed using McLaughlin’s Simple Measure of Gobbledygook (SMOG) formula, which identifies school stages that would have to be achieved to comprehend the PIL. The sensitivity of the results to alternative readability methods were assessed. Results: The PIL was not sufficient for modern consenting processes and reflected a suboptimal level of health literacy. Evaluation of the leaflet revealed key content was missing, including information pertaining to risks and benefits. Only five points out of the 20-point checklist were present. The readability score was 16, equivalent to a level 2 in National Adult Literacy Standards/Scottish Credit and Qualification Framework Level 5; 62% of Scottish adults are able to read to this standard. Discussion: Assessment of the leaflet showed it was no longer fit for purpose. Reasons include a lack of pertinent information, a text-heavy leaflet lacking flow, and content errors. The SMOG score indicates a high level of comprehension is required to understand this PIL, which many patients may not possess. A new PIL, compliant with medicolegal and health literacy guidance, was designed with patient-driven checklists, notes spaces for annotations/ questions and areas for clinicians to highlight important case-specific information. It has been tested using the SMOG formula. Conclusion: PILs can be extremely useful. Studies show that interactive use can enhance their effectiveness. PILs should reflect best practice guidance and be understood by patients. The 2020 leaflet designed and implemented aims to fulfill the needs of a modern healthcare system and its service users. It embraces and embeds Scotland’s Health Literacy Action Plan within the consenting process. A review of further leaflets using this model is ongoing.

Keywords: consent, health literacy, patient information leaflet, restorative dentistry

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1122 Deep Learning Based on Image Decomposition for Restoration of Intrinsic Representation

Authors: Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Kensuke Nakamura, Dongeun Choi, Byung-Woo Hong

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Artefacts are commonly encountered in the imaging process of clinical computed tomography (CT) where the artefact refers to any systematic discrepancy between the reconstructed observation and the true attenuation coefficient of the object. It is known that CT images are inherently more prone to artefacts due to its image formation process where a large number of independent detectors are involved, and they are assumed to yield consistent measurements. There are a number of different artefact types including noise, beam hardening, scatter, pseudo-enhancement, motion, helical, ring, and metal artefacts, which cause serious difficulties in reading images. Thus, it is desired to remove nuisance factors from the degraded image leaving the fundamental intrinsic information that can provide better interpretation of the anatomical and pathological characteristics. However, it is considered as a difficult task due to the high dimensionality and variability of data to be recovered, which naturally motivates the use of machine learning techniques. We propose an image restoration algorithm based on the deep neural network framework where the denoising auto-encoders are stacked building multiple layers. The denoising auto-encoder is a variant of a classical auto-encoder that takes an input data and maps it to a hidden representation through a deterministic mapping using a non-linear activation function. The latent representation is then mapped back into a reconstruction the size of which is the same as the size of the input data. The reconstruction error can be measured by the traditional squared error assuming the residual follows a normal distribution. In addition to the designed loss function, an effective regularization scheme using residual-driven dropout determined based on the gradient at each layer. The optimal weights are computed by the classical stochastic gradient descent algorithm combined with the back-propagation algorithm. In our algorithm, we initially decompose an input image into its intrinsic representation and the nuisance factors including artefacts based on the classical Total Variation problem that can be efficiently optimized by the convex optimization algorithm such as primal-dual method. The intrinsic forms of the input images are provided to the deep denosing auto-encoders with their original forms in the training phase. In the testing phase, a given image is first decomposed into the intrinsic form and then provided to the trained network to obtain its reconstruction. We apply our algorithm to the restoration of the corrupted CT images by the artefacts. It is shown that our algorithm improves the readability and enhances the anatomical and pathological properties of the object. The quantitative evaluation is performed in terms of the PSNR, and the qualitative evaluation provides significant improvement in reading images despite degrading artefacts. The experimental results indicate the potential of our algorithm as a prior solution to the image interpretation tasks in a variety of medical imaging applications. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: auto-encoder neural network, CT image artefact, deep learning, intrinsic image representation, noise reduction, total variation

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1121 The Use of Cross-cultural Approaches (CCAs) in Psychotherapy in Addressing Mental Health Issues Amongst Women of Ethnic Minority

Authors: Adaku Thelma Olatise

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Mental health disparities among women from diverse ethnic, cultural, and religious backgrounds remain a pressing concern, particularly as current psychotherapeutic models often fail to address the unique challenges these groups face. This is of particular concern since epidemiological studies across various countries and cultures consistently demonstrate higher prevalence rates of common mental disorders amongst these groups of women because of a lack of access to culturally oriented psychotherapeutic services. This literature review aims to examine how CCAs in psychotherapy can address the specific ethnic, cultural, and religious challenges women encounter in accessing mental health care. A search of relevant articles was conducted through PsycARTICLES and PubMed databases, using terms such as ‘mental health’, ‘women’, ‘culture’, and ‘ethnic minorities’. Supplementary searches on Google Scholar were also performed to capture literature not covered by traditional databases. While the importance of cross-cultural approaches in psychotherapy has become more apparent because people from diverse ethnic backgrounds inevitably perceive the world through different lenses, influencing their interpretations of human behavior and norms, there is a notable gap in the literature in understanding the influences of using of CCAs in psychotherapy amongst women of an ethnic minority. This gap not only reflects a poor understanding of the complex stressors faced by these women—such as familial, communal, and societal expectations—but also highlights the lack of support and culturally adapted interventions available to them. Even though scholars have posited that aligning treatment approaches with patients' cultural backgrounds is important to enhance therapeutic effectiveness, and the acknowledgment of culture is crucial in psychotherapy theory and practice. As well as the increasing global focus on psychotherapy applications that integrate non-Western practices, such as spiritual healing and community-based interventions, the adaptation of these approaches in mainstream mental health care has remained limited. This review found that the expectations and experiences of ethnic minority women were heavily influenced by family and community pressures. However, there were limited evidence-based, culturally oriented psychotherapeutic interventions tailored to ethnic minority women. This gap extends to inadequate representation of minority groups in clinical research, as well as a lack of culturally validated mental health outcome measures. Furthermore, studies have shown that psychotherapeutic models have largely been Western-oriented and Euro-centric because of socially constructed hierarchies. The origin of psychology from the Western world has predominantly reflected Western cultural traditions, shaped by historical, linguistic, and sociopolitical influences. These factors have led to a lack of recognition of therapeutic approaches from minority ethnic groups and the biases that emanate from hegemonic cultural beliefs and power dynamics influence the decisions about which psychotherapeutic modalities to integrate and practice. Therefore, this plethora of factors adds to the challenges women from ethnically and culturally diverse backgrounds face in accessing mental health services at the individual, familial, community, and societal levels. In conclusion, a cross-cultural approach is urgently needed within psychotherapy to address these challenges, ensuring that treatment frameworks are both culturally sensitive and gender responsive. Only by considering the lived experiences of minority women, particularly in relation to their cultural and religious contexts, can mental health services provide the appropriate care necessary to support their well-being.

Keywords: mental health, women, culture, ethnicity

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1120 A Unified Approach for Digital Forensics Analysis

Authors: Ali Alshumrani, Nathan Clarke, Bogdan Ghite, Stavros Shiaeles

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Digital forensics has become an essential tool in the investigation of cyber and computer-assisted crime. Arguably, given the prevalence of technology and the subsequent digital footprints that exist, it could have a significant role across almost all crimes. However, the variety of technology platforms (such as computers, mobiles, Closed-Circuit Television (CCTV), Internet of Things (IoT), databases, drones, cloud computing services), heterogeneity and volume of data, forensic tool capability, and the investigative cost make investigations both technically challenging and prohibitively expensive. Forensic tools also tend to be siloed into specific technologies, e.g., File System Forensic Analysis Tools (FS-FAT) and Network Forensic Analysis Tools (N-FAT), and a good deal of data sources has little to no specialist forensic tools. Increasingly it also becomes essential to compare and correlate evidence across data sources and to do so in an efficient and effective manner enabling an investigator to answer high-level questions of the data in a timely manner without having to trawl through data and perform the correlation manually. This paper proposes a Unified Forensic Analysis Tool (U-FAT), which aims to establish a common language for electronic information and permit multi-source forensic analysis. Core to this approach is the identification and development of forensic analyses that automate complex data correlations, enabling investigators to investigate cases more efficiently. The paper presents a systematic analysis of major crime categories and identifies what forensic analyses could be used. For example, in a child abduction, an investigation team might have evidence from a range of sources including computing devices (mobile phone, PC), CCTV (potentially a large number), ISP records, and mobile network cell tower data, in addition to third party databases such as the National Sex Offender registry and tax records, with the desire to auto-correlate and across sources and visualize in a cognitively effective manner. U-FAT provides a holistic, flexible, and extensible approach to providing digital forensics in technology, application, and data-agnostic manner, providing powerful and automated forensic analysis.

Keywords: digital forensics, evidence correlation, heterogeneous data, forensics tool

Procedia PDF Downloads 197
1119 Mathematical Modeling for Continuous Reactive Extrusion of Poly Lactic Acid Formation by Ring Opening Polymerization Considering Metal/Organic Catalyst and Alternative Energies

Authors: Satya P. Dubey, Hrushikesh A Abhyankar, Veronica Marchante, James L. Brighton, Björn Bergmann

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Aims: To develop a mathematical model that simulates the ROP of PLA taking into account the effect of alternative energy to be implemented in a continuous reactive extrusion production process of PLA. Introduction: The production of large amount of waste is one of the major challenges at the present time, and polymers represent 70% of global waste. PLA has emerged as a promising polymer as it is compostable, biodegradable thermoplastic polymer made from renewable sources. However, the main limitation for the application of PLA is the traces of toxic metal catalyst in the final product. Thus, a safe and efficient production process needs to be developed to avoid the potential hazards and toxicity. It has been found that alternative energy sources (LASER, ultrasounds, microwaves) could be a prominent option to facilitate the ROP of PLA via continuous reactive extrusion. This process may result in complete extraction of the metal catalysts and facilitate less active organic catalysts. Methodology: Initial investigation were performed using the data available in literature for the reaction mechanism of ROP of PLA based on conventional metal catalyst stannous octoate. A mathematical model has been developed by considering significant parameters such as different initial concentration ratio of catalyst, co-catalyst and impurity. Effects of temperature variation and alternative energies have been implemented in the model. Results: The validation of the mathematical model has been made by using data from literature as well as actual experiments. Validation of the model including alternative energies is in progress based on experimental data for partners of the InnoREX project consortium. Conclusion: The model developed reproduces accurately the polymerisation reaction when applying alternative energy. Alternative energies have a great positive effect to increase the conversion and molecular weight of the PLA. This model could be very useful tool to complement Ludovic® software to predict the large scale production process when using reactive extrusion.

Keywords: polymer, poly-lactic acid (PLA), ring opening polymerization (ROP), metal-catalyst, bio-degradable, renewable source, alternative energy (AE)

Procedia PDF Downloads 362
1118 Efficacy of Knowledge Management Practices in Selected Public Libraries in the Province of Kwazulu-Natal, South Africa

Authors: Petros Dlamini, Bethiweli Malambo, Maggie Masenya

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Knowledge management practices are very important in public libraries, especial in the era of the information society. The success of public libraries depends on the recognition and application of knowledge management practices. The study investigates the value and challenges of knowledge management practices in public libraries. Three research objectives informed the study: to identify knowledge management practices in public libraries, understand the value of knowledge management practices in public libraries, and determine the factors hampering knowledge management practices in public libraries. The study was informed by the interpretivism research paradigm, which is associated with qualitative studies. In that light, the study collected data from eight librarians and or library heads, who were purposively selected from public libraries. The study adopted a social anthropological approach, which thoroughly evaluated each participant's response. Data was collected from the respondents through telephonic semi-structured interviews and assessed accordingly. Furthermore, the study used the latest content concept for data interpretation. The chosen data analysis method allowed the study to achieve its main purpose with concrete and valid information. The study's findings showed that all six (100%) selected public libraries apply knowledge management practices. The findings of the study revealed that public libraries have knowledge sharing as the main knowledge management practice. It was noted that public libraries employ many practices, but each library employed its practices of choice depending on their knowledge management practices structure. The findings further showed that knowledge management practices in public libraries are employed through meetings, training, information sessions, and awareness, to mention a few. The findings revealed that knowledge management practices make the libraries usable. Furthermore, it has been asserted that knowledge management practices in public libraries meet users’ needs and expectations and equip them with skills. It was discovered that all participating public libraries from Umkhanyakude district municipality valued their knowledge management practices as the pillar and foundation of services. Noticeably, knowledge management practices improve users ‘standard of living and build an information society. The findings of the study showed that librarians should be responsible for the value of knowledge management practices as they are qualified personnel. The results also showed that 83.35% of public libraries had factors hampering knowledge management practices. The factors are not limited to shortage of funds, resources and space, and political interference. Several suggestions were made to improve knowledge management practices in public libraries. These suggestions include improving the library budget, increasing libraries’ building sizes, and conducting more staff training.

Keywords: knowledge management, knowledge management practices, storage, dissemination

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1117 An investigation of the High-frequency Isolation Performance of Quasi-Zero-Stiffness Vibration Isolators

Authors: Chen Zhang, Yongpeng Gu, Xiaotian Li

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Quasi-zero-stiffness (QZS) vibration isolation technology has garnered significant attention in both academia and industry, which enables ultra-low-frequency vibration isolation. In modern industries, such as shipbuilding and aerospace, rotating machinery generates vibrations over a wide frequency range, thus imposing more stringent requirements on vibration isolation technologies. These technologies must not only achieve ultra-low starting isolation frequencies but also provide effective isolation across mid- to high-frequency ranges. However, existing research on QZS vibration isolators primarily focuses on frequency ranges below 50 Hz. Moreover, studies have shown that in the mid-to high-frequency ranges, QZS isolators tend to generate resonance peaks that adversely affect their isolation performance. This limitation significantly restricts the practical applicability of QZS isolation technology. To address this issue, the present study investigates the high-frequency isolation performance of two typical QZS isolators: the mechanism type three-spring QZS isolator mechanism and the structure and bowl-shaped QZS isolator structure. First, the parameter conditions required to achieve quasi-zero stiffness characteristics for two isolators are derived based on static mechanical analysis. The theoretical transmissibility characteristics are then calculated using the harmonic balance method. Three-dimensional finite element models of two QZS isolators are developed using ABAQUS simulation software, and transmissibility curves are computed for the 0-500 Hz frequency range. The results indicate that the three-spring QZS mechanism exhibits multiple higher-order resonance peaks in the mid-to high-frequency ranges due to the higher-order models of the springs. Springs with fewer coils and larger diameters can shift the higher-order modals to higher frequencies but cannot entirely eliminate their occurrence. In contrast, the bowl-shaped QZS isolator, through shape optimization using a spline-based representation, effectively mitigates the generation of higher-order resonance modes, resulting in superior isolation performance in the mid-to high-frequency ranges. This study provides essential theoretical insights for optimizing the vibration isolation performance of QZS technologies in complex, wide-frequency vibration environments, offering significant practical value for their application.

Keywords: quasi-zero-stiffness, wide-frequency vibration, vibration isolator, transmissibility

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1116 Use of AI for the Evaluation of the Effects of Steel Corrosion in Mining Environments

Authors: Maria Luisa de la Torre, Javier Aroba, Jose Miguel Davila, Aguasanta M. Sarmiento

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Steel is one of the most widely used materials in polymetallic sulfide mining installations. One of the main problems suffered by these facilities is the economic losses due to the corrosion of this material, which is accelerated and aggravated by the contact with acid waters generated in these mines when sulfides come into contact with oxygen and water. This generation of acidic water, in turn, is accelerated by the presence of acidophilic bacteria. In order to gain a more detailed understanding of this corrosion process and the interaction between steel and acidic water, a laboratory experiment was carried out in which carbon steel plates were introduced into four different solutions for 27 days: distilled water (BK), which tried to assimilate the effect produced by rain on this material, an acid solution from a mine with a high Fe2+/Fe3+ (PO) content, another acid solution of water from another mine with a high Fe3+/Fe2+ (PH) content and, finally, one that reproduced the acid mine water with a high Fe2+/Fe3+ content but in which there were no bacteria (ST). Every 24 hours, physicochemical parameters were measured and water samples were taken to carry out an analysis of the dissolved elements. The results of these measurements were processed using an explainable AI model based on fuzzy logic. It could be seen that, in all cases, there was an increase in pH, as well as in the concentrations of Fe and, in particular, Fe(II), as a consequence of the oxidation of the steel plates. Proportionally, the increase in Fe concentration was higher in PO and ST than in PH because Fe precipitates were produced in the latter. The rise of Fe(II) was proportionally much higher in PH and, especially in the first hours of exposure, because it started from a lower initial concentration of this ion. Although to a lesser extent than in PH, the greater increase in Fe(II) also occurred faster in PO than in ST, a consequence of the action of the catalytic bacteria. On the other hand, Cu concentrations decreased throughout the experiment (with the exception of distilled water, which initially had no Cu, as a result of an electrochemical process that generates a precipitation of Cu together with Fe hydroxides. This decrease is lower in PH because the high total acidity keeps it in solution for a longer time. With the application of an artificial intelligence tool, it has been possible to evaluate the effects of steel corrosion in mining environments, corroborating and extending what was obtained by means of classical statistics. Acknowledgments: This work has been supported by MCIU/AEI/10.13039/501100011033/FEDER, UE, throughout the project PID2021-123130OB-I00.

Keywords: carbon steel, corrosion, acid mine drainage, artificial intelligence, fuzzy logic

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1115 Chinese Students’ Use of Corpus Tools in an English for Academic Purposes Writing Course: Influence on Learning Behaviour, Performance Outcomes and Perceptions

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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1114 A Decision-Support Tool for Humanitarian Distribution Planners in the Face of Congestion at Security Checkpoints: A Real-World Case Study

Authors: Mohanad Rezeq, Tarik Aouam, Frederik Gailly

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In times of armed conflicts, various security checkpoints are placed by authorities to control the flow of merchandise into and within areas of conflict. The flow of humanitarian trucks that is added to the regular flow of commercial trucks, together with the complex security procedures, creates congestion and long waiting times at the security checkpoints. This causes distribution costs to increase and shortages of relief aid to the affected people to occur. Our research proposes a decision-support tool to assist planners and policymakers in building efficient plans for the distribution of relief aid, taking into account congestion at security checkpoints. The proposed tool is built around a multi-item humanitarian distribution planning model based on multi-phase design science methodology that has as its objective to minimize distribution and back ordering costs subject to capacity constraints that reflect congestion effects using nonlinear clearing functions. Using the 2014 Gaza War as a case study, we illustrate the application of the proposed tool, model the underlying relief-aid humanitarian supply chain, estimate clearing functions at different security checkpoints, and conduct computational experiments. The decision support tool generated a shipment plan that was compared to two benchmarks in terms of total distribution cost, average lead time and work in progress (WIP) at security checkpoints, and average inventory and backorders at distribution centers. The first benchmark is the shipment plan generated by the fixed capacity model, and the second is the actual shipment plan implemented by the planners during the armed conflict. According to our findings, modeling and optimizing supply chain flows reduce total distribution costs, average truck wait times at security checkpoints, and average backorders when compared to the executed plan and the fixed-capacity model. Finally, scenario analysis concludes that increasing capacity at security checkpoints can lower total operations costs by reducing the average lead time.

Keywords: humanitarian distribution planning, relief-aid distribution, congestion, clearing functions

Procedia PDF Downloads 82
1113 Impact of Instrument Transformer Secondary Connections on Performance of Protection System: Experiences from Indian POWERGRID

Authors: Pankaj Kumar Jha, Mahendra Singh Hada, Brijendra Singh, Sandeep Yadav

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Protective relays are commonly connected to the secondary windings of instrument transformers, i.e., current transformers (CTs) and/or capacitive voltage transformers (CVTs). The purpose of CT and CVT is to provide galvanic isolation from high voltages and reduce primary currents and voltages to a nominal quantity recognized by the protective relays. Selecting the correct instrument transformers for an application is imperative: failing to do so may compromise the relay’s performance, as the output of the instrument transformer may no longer be an accurately scaled representation of the primary quantity. Having an accurately rated instrument transformer is of no use if these devices are not properly connected. The performance of the protective relay is reliant on its programmed settings and on the current and voltage inputs from the instrument transformers secondary. This paper will help in understanding the fundamental concepts of the connections of Instrument Transformers to the protection relays and the effect of incorrect connection on the performance of protective relays. Multiple case studies of protection system mal-operations due to incorrect connections of instrument transformers will be discussed in detail in this paper. Apart from the connection issue of instrument transformers to protective relays, this paper will also discuss the effect of multiple earthing of CTs and CVTs secondary on the performance of the protection system. Case studies presented in this paper will help the readers to analyse the problem through real-world challenges in complex power system networks. This paper will also help the protection engineer in better analysis of disturbance records. CT and CVT connection errors can lead to undesired operations of protection systems. However, many of these operations can be avoided by adhering to industry standards and implementing tried-and-true field testing and commissioning practices. Understanding the effect of missing neutral of CVT, multiple earthing of CVT secondary, and multiple grounding of CT star points on the performance of the protection system through real-world case studies will help the protection engineer in better commissioning the protection system and maintenance of the protection system.

Keywords: bus reactor, current transformer, capacitive voltage transformer, distance protection, differential protection, directional earth fault, disturbance report, instrument transformer, ICT, REF protection, shunt reactor, voltage selection relay, VT fuse failure

Procedia PDF Downloads 83
1112 Efficacy of Different Soil-Applied Fungicides to Manage Phytophthora Root Rot of Chili (Solanum annum) in Pakistan

Authors: Kiran Nawaz, Ahmad Ali Shahid, Sehrish Iftikhar, Waheed Anwar, Muhammad Nasir Subhani

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Chili (Solanum annum L.) attacks by many fungal pathogens, including members of Oomycetes which are responsible for root rot in different chili growing areas of the world. Oomycetes pathogens cause economic losses in different regions of the Pakistan. Most of the plant tissues, including roots, crowns, fruit, and leaves, are vulnerable to Phytophthora capsici. It is very difficult to manage the Phytophthora root rot of chili as many commercial varieties are tremendously vulnerable to P. capsici. The causal agent of the disease was isolated on corn meal agar (CMA) and identified on a morphological basis by using available taxonomic keys. The pathogen was also confirmed on the molecular basis through internal transcribed spacer region and with other molecular markers.The Blastn results showed 100% homology with already reported sequences of P. capsici in NCBI database. Most of the farmers have conventionally relied on foliar fungicide applications to control Phytophthora root rot in spite of their incomplete effectiveness. In this study, in vitro plate assay, seed soaking and foliar applications of 6 fungicides were evaluated against root rot of chili. In vitro assay revealed that significant inhibition of linear growth was obtained with Triflumizole at 7.0%, followed by Thiophanate methyl (8.9%), Etridiazole (6.0%), Propamocarb (5.9%) and 7.5% with Mefenoxam and Iprodione for P. capsici. The promising treatments of in vitro plate bioassay were evaluated in pot experiments under controlled conditions in the greenhouse. All fungicides were applied after at 6-day intervals. Results of pot experiment showed that all treatments considerably inhibited the percentage of P. capsici root rot incidence. In addition, application of seed soaking with all six fungicides combined with the foliar spray of the same components showed the significant reduction in root rot incidence. The combine treatments of all fungicides as in vitro bioassay, seed soaking followed by foliar spray is considered non-harmful control methods which have advantages and limitation. Hence, these applications proved effective and harmless for the management of soil-borne plant pathogens.

Keywords: blastn, bioassay, corn meal agar(CMA), oomycetes

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1111 Application of Ground-Penetrating Radar in Environmental Hazards

Authors: Kambiz Teimour Najad

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The basic methodology of GPR involves the use of a transmitting antenna to send electromagnetic waves into the subsurface, which then bounce back to the surface and are detected by a receiving antenna. The transmitter and receiver antennas are typically placed on the ground surface and moved across the area of interest to create a profile of the subsurface. The GPR system consists of a control unit that powers the antennas and records the data, as well as a display unit that shows the results of the survey. The control unit sends a pulse of electromagnetic energy into the ground, which propagates through the soil or rock until it encounters a change in material or structure. When the electromagnetic wave encounters a buried object or structure, some of the energy is reflected back to the surface and detected by the receiving antenna. The GPR data is then processed using specialized software that analyzes the amplitude and travel time of the reflected waves. By interpreting the data, GPR can provide information on the depth, location, and nature of subsurface features and structures. GPR has several advantages over other geophysical survey methods, including its ability to provide high-resolution images of the subsurface and its non-invasive nature, which minimizes disruption to the site. However, the effectiveness of GPR depends on several factors, including the type of soil or rock, the depth of the features being investigated, and the frequency of the electromagnetic waves used. In environmental hazard assessments, GPR can be used to detect buried structures, such as underground storage tanks, pipelines, or utilities, which may pose a risk of contamination to the surrounding soil or groundwater. GPR can also be used to assess soil stability by identifying areas of subsurface voids or sinkholes, which can lead to the collapse of the surface. Additionally, GPR can be used to map the extent and movement of groundwater contamination, which is critical in designing effective remediation strategies. the methodology of GPR in environmental hazard assessments involves the use of electromagnetic waves to create high of the subsurface, which are then analyzed to provide information on the depth, location, and nature of subsurface features and structures. This information is critical in identifying and mitigating environmental hazards, and the non-invasive nature of GPR makes it a valuable tool in this field.

Keywords: GPR, hazard, landslide, rock fall, contamination

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1110 Efficient Field-Oriented Motor Control on Resource-Constrained Microcontrollers for Optimal Performance without Specialized Hardware

Authors: Nishita Jaiswal, Apoorv Mohan Satpute

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The increasing demand for efficient, cost-effective motor control systems in the automotive industry has driven the need for advanced, highly optimized control algorithms. Field-Oriented Control (FOC) has established itself as the leading approach for motor control, offering precise and dynamic regulation of torque, speed, and position. However, as energy efficiency becomes more critical in modern applications, implementing FOC on low-power, cost-sensitive microcontrollers pose significant challenges due to the limited availability of computational and hardware resources. Currently, most solutions rely on high-performance 32-bit microcontrollers or Application-Specific Integrated Circuits (ASICs) equipped with Floating Point Units (FPUs) and Hardware Accelerated Units (HAUs). These advanced platforms enable rapid computation and simplify the execution of complex control algorithms like FOC. However, these benefits come at the expense of higher costs, increased power consumption, and added system complexity. These drawbacks limit their suitability for embedded systems with strict power and budget constraints, where achieving energy and execution efficiency without compromising performance is essential. In this paper, we present an alternative approach that utilizes optimized data representation and computation techniques on a 16-bit microcontroller without FPUs or HAUs. By carefully optimizing data point formats and employing fixed-point arithmetic, we demonstrate how the precision and computational efficiency required for FOC can be maintained in resource-constrained environments. This approach eliminates the overhead performance associated with floating-point operations and hardware acceleration, providing a more practical solution in terms of cost, scalability and improved execution time efficiency, allowing faster response in motor control applications. Furthermore, it enhances system design flexibility, making it particularly well-suited for applications that demand stringent control over power consumption and costs.

Keywords: field-oriented control, fixed-point arithmetic, floating point unit, hardware accelerator unit, motor control systems

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1109 Image Segmentation with Deep Learning of Prostate Cancer Bone Metastases on Computed Tomography

Authors: Joseph M. Rich, Vinay A. Duddalwar, Assad A. Oberai

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Prostate adenocarcinoma is the most common cancer in males, with osseous metastases as the commonest site of metastatic prostate carcinoma (mPC). Treatment monitoring is based on the evaluation and characterization of lesions on multiple imaging studies, including Computed Tomography (CT). Monitoring of the osseous disease burden, including follow-up of lesions and identification and characterization of new lesions, is a laborious task for radiologists. Deep learning algorithms are increasingly used to perform tasks such as identification and segmentation for osseous metastatic disease and provide accurate information regarding metastatic burden. Here, nnUNet was used to produce a model which can segment CT scan images of prostate adenocarcinoma vertebral bone metastatic lesions. nnUNet is an open-source Python package that adds optimizations to deep learning-based UNet architecture but has not been extensively combined with transfer learning techniques due to the absence of a readily available functionality of this method. The IRB-approved study data set includes imaging studies from patients with mPC who were enrolled in clinical trials at the University of Southern California (USC) Health Science Campus and Los Angeles County (LAC)/USC medical center. Manual segmentation of metastatic lesions was completed by an expert radiologist Dr. Vinay Duddalwar (20+ years in radiology and oncologic imaging), to serve as ground truths for the automated segmentation. Despite nnUNet’s success on some medical segmentation tasks, it only produced an average Dice Similarity Coefficient (DSC) of 0.31 on the USC dataset. DSC results fell in a bimodal distribution, with most scores falling either over 0.66 (reasonably accurate) or at 0 (no lesion detected). Applying more aggressive data augmentation techniques dropped the DSC to 0.15, and reducing the number of epochs reduced the DSC to below 0.1. Datasets have been identified for transfer learning, which involve balancing between size and similarity of the dataset. Identified datasets include the Pancreas data from the Medical Segmentation Decathlon, Pelvic Reference Data, and CT volumes with multiple organ segmentations (CT-ORG). Some of the challenges of producing an accurate model from the USC dataset include small dataset size (115 images), 2D data (as nnUNet generally performs better on 3D data), and the limited amount of public data capturing annotated CT images of bone lesions. Optimizations and improvements will be made by applying transfer learning and generative methods, including incorporating generative adversarial networks and diffusion models in order to augment the dataset. Performance with different libraries, including MONAI and custom architectures with Pytorch, will be compared. In the future, molecular correlations will be tracked with radiologic features for the purpose of multimodal composite biomarker identification. Once validated, these models will be incorporated into evaluation workflows to optimize radiologist evaluation. Our work demonstrates the challenges of applying automated image segmentation to small medical datasets and lays a foundation for techniques to improve performance. As machine learning models become increasingly incorporated into the workflow of radiologists, these findings will help improve the speed and accuracy of vertebral metastatic lesions detection.

Keywords: deep learning, image segmentation, medicine, nnUNet, prostate carcinoma, radiomics

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1108 Investigation of Several New Ionic Liquids’ Behaviour during ²¹⁰PB/²¹⁰BI Cherenkov Counting in Waters

Authors: Nataša Todorović, Jovana Nikolov, Ivana Stojković, Milan Vraneš, Jovana Panić, Slobodan Gadžurić

Abstract:

The detection of ²¹⁰Pb levels in aquatic environments evokes interest in various scientific studies. Its precise determination is important not only for the radiological assessment of drinking waters but also ²¹⁰Pb, and ²¹⁰Po distribution in the marine environment are significant for the assessment of the removal rates of particles from the ocean and particle fluxes during transport along the coast, as well as particulate organic carbon export in the upper ocean. Measurement techniques for ²¹⁰Pb determination, gamma spectrometry, alpha spectrometry, or liquid scintillation counting (LSC) are either time-consuming or demand expensive equipment or complicated chemical pre-treatments. However, one other possibility is to measure ²¹⁰Pb on an LS counter if it is in equilibrium with its progeny ²¹⁰Bi - through the Cherenkov counting method. It is unaffected by the chemical quenching and assumes easy sample preparation but has the drawback of lower counting efficiencies than standard LSC methods, typically from 10% up to 20%. The aim of the presented research in this paper is to investigate the possible increment of detection efficiency of Cherenkov counting during ²¹⁰Pb/²¹⁰Bi detection on an LS counter Quantulus 1220. Considering naturally low levels of ²¹⁰Pb in aqueous samples, the addition of ionic liquids to the counting vials with the analysed samples has the benefit of detection limit’s decrement during ²¹⁰Pb quantification. Our results demonstrated that ionic liquid, 1-butyl-3-methylimidazolium salicylate, is more efficient in Cherenkov counting efficiency increment than the previously explored 2-hydroxypropan-1-amminium salicylate. Consequently, the impact of a few other ionic liquids that were synthesized with the same cation group (1-butyl-3-methylimidazolium benzoate, 1-butyl-3-methylimidazolium 3-hydroxybenzoate, and 1-butyl-3-methylimidazolium 4-hydroxybenzoate) was explored in order to test their potential influence on Cherenkov counting efficiency. It was confirmed that, among the explored ones, only ionic liquids in the form of salicylates exhibit a wavelength shifting effect. Namely, the addition of small amounts (around 0.8 g) of 1-butyl-3-methylimidazolium salicylate increases the detection efficiency from 16% to >70%, consequently reducing the detection threshold by more than four times. Moreover, the addition of ionic liquids could find application in the quantification of other radionuclides besides ²¹⁰Pb/²¹⁰Bi via Cherenkov counting method.

Keywords: liquid scintillation counting, ionic liquids, Cherenkov counting, ²¹⁰PB/²¹⁰BI in water

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