Search results for: computational tool
555 Breast Cancer Metastasis Detection and Localization through Transfer-Learning Convolutional Neural Network Classification Based on Convolutional Denoising Autoencoder Stack
Authors: Varun Agarwal
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Introduction: With the advent of personalized medicine, histopathological review of whole slide images (WSIs) for cancer diagnosis presents an exceedingly time-consuming, complex task. Specifically, detecting metastatic regions in WSIs of sentinel lymph node biopsies necessitates a full-scanned, holistic evaluation of the image. Thus, digital pathology, low-level image manipulation algorithms, and machine learning provide significant advancements in improving the efficiency and accuracy of WSI analysis. Using Camelyon16 data, this paper proposes a deep learning pipeline to automate and ameliorate breast cancer metastasis localization and WSI classification. Methodology: The model broadly follows five stages -region of interest detection, WSI partitioning into image tiles, convolutional neural network (CNN) image-segment classifications, probabilistic mapping of tumor localizations, and further processing for whole WSI classification. Transfer learning is applied to the task, with the implementation of Inception-ResNetV2 - an effective CNN classifier that uses residual connections to enhance feature representation, adding convolved outputs in the inception unit to the proceeding input data. Moreover, in order to augment the performance of the transfer learning CNN, a stack of convolutional denoising autoencoders (CDAE) is applied to produce embeddings that enrich image representation. Through a saliency-detection algorithm, visual training segments are generated, which are then processed through a denoising autoencoder -primarily consisting of convolutional, leaky rectified linear unit, and batch normalization layers- and subsequently a contrast-normalization function. A spatial pyramid pooling algorithm extracts the key features from the processed image, creating a viable feature map for the CNN that minimizes spatial resolution and noise. Results and Conclusion: The simplified and effective architecture of the fine-tuned transfer learning Inception-ResNetV2 network enhanced with the CDAE stack yields state of the art performance in WSI classification and tumor localization, achieving AUC scores of 0.947 and 0.753, respectively. The convolutional feature retention and compilation with the residual connections to inception units synergized with the input denoising algorithm enable the pipeline to serve as an effective, efficient tool in the histopathological review of WSIs.Keywords: breast cancer, convolutional neural networks, metastasis mapping, whole slide images
Procedia PDF Downloads 125554 The Trumping of Science: Exploratory Study into Discrepancy between Politician and Scientist Sources in American Covid-19 News Coverage
Authors: Wafa Unus
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Science journalism has been vanishing from America’s national newspapers for decades. Reportage on scientific topics is limited to only a handful of newspapers and of those, few employ dedicated science journalists to cover stories that require this specialized expertise. News organizations' lack of readiness to convey complex scientific concepts to a mass populace becomes particularly problematic when events like the Covid-19 pandemic occur. The lack of coverage of Covid-19 prior to its onset in the United States, suggests something more troubling - that the deprioritization of reporting on hard science as an educational tool in favor of political frames of coverage, places dangerous blinders on the American public. This research looks at the disparity between voices of health and science experts in news articles and the voices of political figures, in order to better understand the approach of American newspapers in conveying expert opinion on Covid-19. A content analysis of 300 articles on Covid-19 by major newspapers in the United States between January 1st, 2020 and April 30th, 2020 illuminates this investigation. The Boston Globe, the New York Times, and the Los Angeles Times are included in the content analysis. Initial findings reveal a significant disparity in the number of articles that mention Anthony Fauci, the director of the National Institute Allergy and Infectious Disease, and the number that make reference to political figures. Covid-related articles in the New York Times that focused on health topics (as opposed to economic or social issues) contained the voices of 54 different politicians who were mentioned a total of 608 times. Only five members of the scientific community were mentioned a total of 24 times (out of 674 articles). In the Boston Globe, 36 different politicians were mentioned a total of 147 times, and only two members of the scientific community, one being Anthony Fauci, were mentioned a total of nine times (out of 423 articles). In the Los Angeles Times, 52 different politicians were mentioned a total of 600 times, and only six members of the scientific community were included and were mentioned a total of 82 times with Fauci being mentioned 48 times (out of 851 articles). Results provide a better understanding of the frames in which American journalists in Covid hotspots conveyed information of expert analysis on Covid-19 during one of the most pressing news events of the century. Ultimately, the objective of this study is to utilize the exploratory data to evaluate the nature, extent and impact of Covid-19 reporting in the context of trustworthiness and scientific expertise. Secondarily, this data will illuminate the degree to which Covid-19 reporting focused on politics over science.Keywords: science reporting, science journalism, covid, misinformation, news
Procedia PDF Downloads 209553 Interacting with Multi-Scale Structures of Online Political Debates by Visualizing Phylomemies
Authors: Quentin Lobbe, David Chavalarias, Alexandre Delanoe
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The ICT revolution has given birth to an unprecedented world of digital traces and has impacted a wide number of knowledge-driven domains such as science, education or policy making. Nowadays, we are daily fueled by unlimited flows of articles, blogs, messages, tweets, etc. The internet itself can thus be considered as an unsteady hyper-textual environment where websites emerge and expand every day. But there are structures inside knowledge. A given text can always be studied in relation to others or in light of a specific socio-cultural context. By way of their textual traces, human beings are calling each other out: hypertext citations, retweets, vocabulary similarity, etc. We are in fact the architects of a giant web of elements of knowledge whose structures and shapes convey their own information. The global shapes of these digital traces represent a source of collective knowledge and the question of their visualization remains an opened challenge. How can we explore, browse and interact with such shapes? In order to navigate across these growing constellations of words and texts, interdisciplinary innovations are emerging at the crossroad between fields of social and computational sciences. In particular, complex systems approaches make it now possible to reconstruct the hidden structures of textual knowledge by means of multi-scale objects of research such as semantic maps and phylomemies. The phylomemy reconstruction is a generic method related to the co-word analysis framework. Phylomemies aim to reveal the temporal dynamics of large corpora of textual contents by performing inter-temporal matching on extracted knowledge domains in order to identify their conceptual lineages. This study aims to address the question of visualizing the global shapes of online political discussions related to the French presidential and legislative elections of 2017. We aim to build phylomemies on top of a dedicated collection of thousands of French political tweets enriched with archived contemporary news web articles. Our goal is to reconstruct the temporal evolution of online debates fueled by each political community during the elections. To that end, we want to introduce an iterative data exploration methodology implemented and tested within the free software Gargantext. There we combine synchronic and diachronic axis of visualization to reveal the dynamics of our corpora of tweets and web pages as well as their inner syntagmatic and paradigmatic relationships. In doing so, we aim to provide researchers with innovative methodological means to explore online semantic landscapes in a collaborative and reflective way.Keywords: online political debate, French election, hyper-text, phylomemy
Procedia PDF Downloads 181552 A Finite Element Analysis of Hexagonal Double-Arrowhead Auxetic Structure with Enhanced Energy Absorption Characteristics and Stiffness
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Auxetic materials, as an emerging artificial designed metamaterial has attracted growing attention due to their promising negative Poisson’s ratio behaviors and tunable properties. The conventional auxetic lattice structures for which the deformation process is governed by a bending-dominated mechanism have faced the limitation of poor mechanical performance for many potential engineering applications. Recently, both load-bearing and energy absorption capabilities have become a crucial consideration in auxetic structure design. This study reports the finite element analysis of a class of hexagonal double-arrowhead auxetic structures with enhanced stiffness and energy absorption performance. The structure design was developed by extending the traditional double-arrowhead honeycomb to a hexagon frame, the stretching-dominated deformation mechanism was determined according to Maxwell’s stability criterion. The finite element (FE) models of 2D lattice structures established with stainless steel material were analyzed in ABAQUS/Standard for predicting in-plane structural deformation mechanism, failure process, and compressive elastic properties. Based on the computational simulation, the parametric analysis was studied to investigate the effect of the structural parameters on Poisson’s ratio and mechanical properties. The geometrical optimization was then implemented to achieve the optimal Poisson’s ratio for the maximum specific energy absorption. In addition, the optimized 2D lattice structure was correspondingly converted into a 3D geometry configuration by using the orthogonally splicing method. The numerical results of 2D and 3D structures under compressive quasi-static loading conditions were compared separately with the traditional double-arrowhead re-entrant honeycomb in terms of specific Young's moduli, Poisson's ratios, and specified energy absorption. As a result, the energy absorption capability and stiffness are significantly reinforced with a wide range of Poisson’s ratio compared to traditional double-arrowhead re-entrant honeycomb. The auxetic behaviors, energy absorption capability, and yield strength of the proposed structure are adjustable with different combinations of joint angle, struts thickness, and the length-width ratio of the representative unit cell. The numerical prediction in this study suggests the proposed concept of hexagonal double-arrowhead structure could be a suitable candidate for the energy absorption applications with a constant request of load-bearing capacity. For future research, experimental analysis is required for the validation of the numerical simulation.Keywords: auxetic, energy absorption capacity, finite element analysis, negative Poisson's ratio, re-entrant hexagonal honeycomb
Procedia PDF Downloads 84551 Using a Card Game as a Tool for Developing a Design
Authors: Matthias Haenisch, Katharina Hermann, Marc Godau, Verena Weidner
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Over the past two decades, international music education has been characterized by a growing interest in informal learning for formal contexts and a "compositional turn" that has moved from closed to open forms of composing. This change occurs under social and technological conditions that permeate 21st-century musical practices. This forms the background of Musical Communities in the (Post)Digital Age (MusCoDA), a four-year joint research project of the University of Erfurt (UE) and the University of Education Karlsruhe (PHK), funded by the German Federal Ministry of Education and Research (BMBF). Both explore songwriting processes as an example of collective creativity in (post)digital communities, one in formal and the other in informal learning contexts. Collective songwriting will be studied from a network perspective, that will allow us to view boundaries between both online and offline as well as formal and informal or hybrid contexts as permeable and to reconstruct musical learning practices. By comparing these songwriting processes, possibilities for a pedagogical-didactic interweaving of different educational worlds are highlighted. Therefore, the subproject of the University of Erfurt investigates school music lessons with the help of interviews, videography, and network maps by analyzing new digital pedagogical and didactic possibilities. In the first step, the international literature on songwriting in the music classroom was examined for design development. The analysis focused on the question of which methods and practices are circulating in the current literature. Results from this stage of the project form the basis for the first instructional design that will help teachers in planning regular music classes and subsequently reconstruct musical learning practices under these conditions. In analyzing the literature, we noticed certain structural methods and concepts that recur, such as the Building Blocks method and the pre-structuring of the songwriting process. From these findings, we developed a deck of cards that both captures the current state of research and serves as a method for design development. With this deck of cards, both teachers and students themselves can plan their individual songwriting lessons by independently selecting and arranging topic, structure, and action cards. In terms of science communication, music educators' interactions with the card game provide us with essential insights for developing the first design. The overall goal of MusCoDA is to develop an empirical model of collective musical creativity and learning and an instructional design for teaching music in the postdigital age.Keywords: card game, collective songwriting, community of practice, network, postdigital
Procedia PDF Downloads 59550 EQMamba - Method Suggestion for Earthquake Detection and Phase Picking
Authors: Noga Bregman
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Accurate and efficient earthquake detection and phase picking are crucial for seismic hazard assessment and emergency response. This study introduces EQMamba, a deep-learning method that combines the strengths of the Earthquake Transformer and the Mamba model for simultaneous earthquake detection and phase picking. EQMamba leverages the computational efficiency of Mamba layers to process longer seismic sequences while maintaining a manageable model size. The proposed architecture integrates convolutional neural networks (CNNs), bidirectional long short-term memory (BiLSTM) networks, and Mamba blocks. The model employs an encoder composed of convolutional layers and max pooling operations, followed by residual CNN blocks for feature extraction. Mamba blocks are applied to the outputs of BiLSTM blocks, efficiently capturing long-range dependencies in seismic data. Separate decoders are used for earthquake detection, P-wave picking, and S-wave picking. We trained and evaluated EQMamba using a subset of the STEAD dataset, a comprehensive collection of labeled seismic waveforms. The model was trained using a weighted combination of binary cross-entropy loss functions for each task, with the Adam optimizer and a scheduled learning rate. Data augmentation techniques were employed to enhance the model's robustness. Performance comparisons were conducted between EQMamba and the EQTransformer over 20 epochs on this modest-sized STEAD subset. Results demonstrate that EQMamba achieves superior performance, with higher F1 scores and faster convergence compared to EQTransformer. EQMamba reached F1 scores of 0.8 by epoch 5 and maintained higher scores throughout training. The model also exhibited more stable validation performance, indicating good generalization capabilities. While both models showed lower accuracy in phase-picking tasks compared to detection, EQMamba's overall performance suggests significant potential for improving seismic data analysis. The rapid convergence and superior F1 scores of EQMamba, even on a modest-sized dataset, indicate promising scalability for larger datasets. This study contributes to the field of earthquake engineering by presenting a computationally efficient and accurate method for simultaneous earthquake detection and phase picking. Future work will focus on incorporating Mamba layers into the P and S pickers and further optimizing the architecture for seismic data specifics. The EQMamba method holds the potential for enhancing real-time earthquake monitoring systems and improving our understanding of seismic events.Keywords: earthquake, detection, phase picking, s waves, p waves, transformer, deep learning, seismic waves
Procedia PDF Downloads 28549 A Dynamic Mechanical Thermal T-Peel Test Approach to Characterize Interfacial Behavior of Polymeric Textile Composites
Authors: J. R. Büttler, T. Pham
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Basic understanding of interfacial mechanisms is of importance for the development of polymer composites. For this purpose, we need techniques to analyze the quality of interphases, their chemical and physical interactions and their strength and fracture resistance. In order to investigate the interfacial phenomena in detail, advanced characterization techniques are favorable. Dynamic mechanical thermal analysis (DMTA) using a rheological system is a sensitive tool. T-peel tests were performed with this system, to investigate the temperature-dependent peel behavior of woven textile composites. A model system was made of polyamide (PA) woven fabric laminated with films of polypropylene (PP) or PP modified by grafting with maleic anhydride (PP-g-MAH). Firstly, control measurements were performed with solely PP matrixes. Polymer melt investigations, as well as the extensional stress, extensional viscosity and extensional relaxation modulus at -10°C, 100 °C and 170 °C, demonstrate similar viscoelastic behavior for films made of PP-g-MAH and its non-modified PP-control. Frequency sweeps have shown that PP-g-MAH has a zero phase viscosity of around 1600 Pa·s and PP-control has a similar zero phase viscosity of 1345 Pa·s. Also, the gelation points are similar at 2.42*104 Pa (118 rad/s) and 2.81*104 Pa (161 rad/s) for PP-control and PP-g-MAH, respectively. Secondly, the textile composite was analyzed. The extensional stress of PA66 fabric laminated with either PP-control or PP-g-MAH at -10 °C, 25 °C and 170 °C for strain rates of 0.001 – 1 s-1 was investigated. The laminates containing the modified PP need more stress for T-peeling. However, the strengthening effect due to the modification decreases by increasing temperature and at 170 °C, just above the melting temperature of the matrix, the difference disappears. Independent of the matrix used in the textile composite, there is a decrease of extensional stress by increasing temperature. It appears that the more viscous is the matrix, the weaker the laminar adhesion. Possibly, the measurement is influenced by the fact that the laminate becomes stiffer at lower temperatures. Adhesive lap-shear testing at room temperature supports the findings obtained with the T-peel test. Additional analysis of the textile composite at the microscopic level ensures that the fibers are well embedded in the matrix. Atomic force microscopy (AFM) imaging of a cross section of the composite shows no gaps between the fibers and matrix. Measurements of the water contact angle show that the MAH grafted PP is more polar than the virgin-PP, and that suggests a more favorable chemical interaction of PP-g-MAH with PA, compared to the non-modified PP. In fact, this study indicates that T-peel testing by DMTA is a technique to achieve more insights into polymeric textile composites.Keywords: dynamic mechanical thermal analysis, interphase, polyamide, polypropylene, textile composite
Procedia PDF Downloads 125548 Organic Matter Distribution in Bazhenov Source Rock: Insights from Sequential Extraction and Molecular Geochemistry
Authors: Margarita S. Tikhonova, Alireza Baniasad, Anton G. Kalmykov, Georgy A. Kalmykov, Ralf Littke
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There is a high complexity in the pore structure of organic-rich rocks caused by the combination of inter-particle porosity from inorganic mineral matter and ultrafine intra-particle porosity from both organic matter and clay minerals. Fluids are retained in that pore space, but there are major uncertainties in how and where the fluids are stored and to what extent they are accessible or trapped in 'closed' pores. A large degree of tortuosity may lead to fractionation of organic matter so that the lighter and flexible compounds would diffuse to the reservoir whereas more complicated compounds may be locked in place. Additionally, parts of hydrocarbons could be bound to solid organic matter –kerogen– and mineral matrix during expulsion and migration. Larger compounds can occupy thin channels so that clogging or oil and gas entrapment will occur. Sequential extraction of applying different solvents is a powerful tool to provide more information about the characteristics of trapped organic matter distribution. The Upper Jurassic – Lower Cretaceous Bazhenov shale is one of the most petroliferous source rock extended in West Siberia, Russia. Concerning the variable mineral composition, pore space distribution and thermal maturation, there are high uncertainties in distribution and composition of organic matter in this formation. In order to address this issue geological and geochemical properties of 30 samples including mineral composition (XRD and XRF), structure and texture (thin-section microscopy), organic matter contents, type and thermal maturity (Rock-Eval) as well as molecular composition (GC-FID and GC-MS) of different extracted materials during sequential extraction were considered. Sequential extraction was performed by a Soxhlet apparatus using different solvents, i.e., n-hexane, chloroform and ethanol-benzene (1:1 v:v) first on core plugs and later on pulverized materials. The results indicate that the studied samples are mainly composed of type II kerogen with TOC contents varied from 5 to 25%. The thermal maturity ranged from immature to late oil window. Whereas clay contents decreased with increasing maturity, the amount of silica increased in the studied samples. According to molecular geochemistry, stored hydrocarbons in open and closed pore space reveal different geochemical fingerprints. The results improve our understanding of hydrocarbon expulsion and migration in the organic-rich Bazhenov shale and therefore better estimation of hydrocarbon potential for this formation.Keywords: Bazhenov formation, bitumen, molecular geochemistry, sequential extraction
Procedia PDF Downloads 165547 Controllable Modification of Glass-Crystal Composites with Ion-Exchange Technique
Authors: Andrey A. Lipovskii, Alexey V. Redkov, Vyacheslav V. Rusan, Dmitry K. Tagantsev, Valentina V. Zhurikhina
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The presented research is related to the development of recently proposed technique of the formation of composite materials, like optical glass-ceramics, with predetermined structure and properties of the crystalline component. The technique is based on the control of the size and concentration of the crystalline grains using the phenomenon of glass-ceramics decrystallization (vitrification) induced by ion-exchange. This phenomenon was discovered and explained in the beginning of the 2000s, while related theoretical description was given in 2016 only. In general, the developed theory enables one to model the process and optimize the conditions of ion-exchange processing of glass-ceramics, which provide given properties of crystalline component, in particular, profile of the average size of the crystalline grains. The optimization is possible if one knows two dimensionless parameters of the theoretical model. One of them (β) is the value which is directly related to the solubility of crystalline component of the glass-ceramics in the glass matrix, and another (γ) is equal to the ratio of characteristic times of ion-exchange diffusion and crystalline grain dissolution. The presented study is dedicated to the development of experimental technique and simulation which allow determining these parameters. It is shown that these parameters can be deduced from the data on the space distributions of diffusant concentrations and average size of crystalline grains in the glass-ceramics samples subjected to ion-exchange treatment. Measurements at least at two temperatures and two processing times at each temperature are necessary. The composite material used was a silica-based glass-ceramics with crystalline grains of Li2OSiO2. Cubical samples of the glass-ceramics (6x6x6 mm3) underwent the ion exchange process in NaNO3 salt melt at 520 oC (for 16 and 48 h), 540 oC (for 8 and 24 h), 560 oC (for 4 and 12 h), and 580 oC (for 2 and 8 h). The ion exchange processing resulted in the glass-ceramics vitrification in the subsurface layers where ion-exchange diffusion took place. Slabs about 1 mm thick were cut from the central part of the samples and their big facets were polished. These slabs were used to find profiles of diffusant concentrations and average size of the crystalline grains. The concentration profiles were determined from refractive index profiles measured with Max-Zender interferometer, and profiles of the average size of the crystalline grains were determined with micro-Raman spectroscopy. Numerical simulation were based on the developed theoretical model of the glass-ceramics decrystallization induced by ion exchange. The simulation of the processes was carried out for different values of β and γ parameters under all above-mentioned ion exchange conditions. As a result, the temperature dependences of the parameters, which provided a reliable coincidence of the simulation and experimental data, were found. This ensured the adequate modeling of the process of the glass-ceramics decrystallization in 520-580 oC temperature interval. Developed approach provides a powerful tool for fine tuning of the glass-ceramics structure, namely, concentration and average size of crystalline grains.Keywords: diffusion, glass-ceramics, ion exchange, vitrification
Procedia PDF Downloads 266546 The Invaluable Contributions of Radiography and Radiotherapy in Modern Medicine
Authors: Sahar Heidary
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Radiography and radiotherapy have emerged as crucial pillars of modern medical practice, revolutionizing diagnostics and treatment for a myriad of health conditions. This abstract highlights the pivotal role of radiography and radiotherapy in favor of healthcare and society. Radiography, a non-invasive imaging technique, has significantly advanced medical diagnostics by enabling the visualization of internal structures and abnormalities within the human body. With the advent of digital radiography, clinicians can obtain high-resolution images promptly, leading to faster diagnoses and informed treatment decisions. Radiography plays a pivotal role in detecting fractures, tumors, infections, and various other conditions, allowing for timely interventions and improved patient outcomes. Moreover, its widespread accessibility and cost-effectiveness make it an indispensable tool in healthcare settings worldwide. On the other hand, radiotherapy, a branch of medical science that utilizes high-energy radiation, has become an integral component of cancer treatment and management. By precisely targeting and damaging cancerous cells, radiotherapy offers a potent strategy to control tumor growth and, in many cases, leads to cancer eradication. Additionally, radiotherapy is often used in combination with surgery and chemotherapy, providing a multifaceted approach to combat cancer comprehensively. The continuous advancements in radiotherapy techniques, such as intensity-modulated radiotherapy and stereotactic radiosurgery, have further improved treatment precision while minimizing damage to surrounding healthy tissues. Furthermore, radiography and radiotherapy have demonstrated their worth beyond oncology. Radiography is instrumental in guiding various medical procedures, including catheter placement, joint injections, and dental evaluations, reducing complications and enhancing procedural accuracy. On the other hand, radiotherapy finds applications in non-cancerous conditions like benign tumors, vascular malformations, and certain neurological disorders, offering therapeutic options for patients who may not benefit from traditional surgical interventions. In conclusion, radiography and radiotherapy stand as indispensable tools in modern medicine, driving transformative improvements in patient care and treatment outcomes. Their ability to diagnose, treat, and manage a wide array of medical conditions underscores their favor in medical practice. As technology continues to advance, radiography and radiotherapy will undoubtedly play an ever more significant role in shaping the future of healthcare, ultimately saving lives and enhancing the quality of life for countless individuals worldwide.Keywords: radiology, radiotherapy, medical imaging, cancer treatment
Procedia PDF Downloads 66545 Assessment of Serum Osteopontin, Osteoprotegerin and Bone-Specific Alp as Markers of Bone Turnover in Patients with Disorders of Thyroid Function in Nigeria, Sub-Saharan Africa
Authors: Oluwabori Emmanuel Olukoyejo, Ogra Victor Ogra, Bosede Amodu, Tewogbade Adeoye Adedeji
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Background: Disorders of thyroid function are the second most common endocrine disorders worldwide, with a direct relationship with metabolic bone diseases. These metabolic bone complications are often subtle but manifest as bone pains and an increased risk of fractures. The gold standard for diagnosis, Dual Energy X-ray Absorptiometry (DEXA), is limited in this environment due to unavailability, cumbersomeness and cost. However, bone biomarkers have shown prospects in assessing alterations in bone remodeling, which has not been studied in this environment. Aim: This study evaluates serum levels of bone-specific alkaline phosphatase (bone-specific ALP), osteopontin and osteoprotegerin biomarkers of bone turnover in patients with disorders of thyroid function. Methods: This is a cross-sectional study carried out over a period of one and a half years. Forty patients with thyroid dysfunctions, aged 20 to 50 years, and thirty-eight age and sex-matched healthy euthyroid controls were included in this study. Patients were further stratified into hyperthyroid and hypothyroid groups. Bone-specific ALP, osteopontin, and osteoprotegerin, alongside serum total calcium, ionized calcium and inorganic phosphate, were assayed for all patients and controls. A self-administered questionnaire was used to obtain data on sociodemographic and medical history. Then, 5 ml of blood was collected in a plain bottle and serum was harvested following clotting and centrifugation. Serum samples were assayed for B-ALP, osteopontin, and osteoprotegerin using the ELISA technique. Total calcium and ionized calcium were assayed using an ion-selective electrode, while the inorganic phosphate was assayed with automated photometry. Results: The hyperthyroid and hypothyroid patient groups had significantly increased median serum B-ALP (30.40 and 26.50) ng/ml and significantly lower median OPG (0.80 and 0.80) ng/ml than the controls (10.81 and 1.30) ng/ml respectively, p < 0.05. However, serum osteopontin in the hyperthyroid group was significantly higher and significantly lower in the hypothyroid group when compared with the controls (11.00 and 2.10 vs 3.70) ng/ml, respectively, p < 0.05. Both hyperthyroid and hypothyroid groups had significantly higher mean serum total calcium, ionized calcium and inorganic phosphate than the controls (2.49 ± 0.28, 1.27 ± 0.14 and 1.33 ± 0.33) mmol/l and (2.41 ± 0.04, 1.20 ± 0.04 and 1.15 ± 0.16) mmol/l vs (2.27 ± 0.11, 1.17 ± 0.06 and 1.08 ± 0.16) mmol/l respectively, p < 0.05. Conclusion: Patients with disorders of thyroid function have metabolic imbalances of all the studied bone markers, suggesting a higher bone turnover. The routine bone markers will be an invaluable tool for monitoring bone health in patients with thyroid dysfunctions, while the less readily available markers can be introduced as supplementary tools. Moreover, bone-specific ALP, osteopontin and osteoprotegerin were found to be the strongest independent predictors of metabolic bone markers’ derangements in patients with thyroid dysfunctions.Keywords: metabolic bone diseases, biomarker, bone turnover, hyperthyroid, hypothyroid, euthyroid
Procedia PDF Downloads 18544 Participatory Approach: A Tool for Improving Food Security and Empowering a Local Community in Chitima, Mozambique
Authors: Matias Hargreaves, Martin Del Valle, Diego Rodriguez, Riveros Jose Luis
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Trough years, all kind of social development projects have tried to solve social problems such as hunger, poverty, malnutrition, food insecurity, among others, with poor success. Both private and state initiatives have invested resources in several countries and communities. Nevertheless, most of these initiatives are scientific or external developers-centered, with a lack of local participation. This compromises the sustainability of any intervention and also leads to a poor empowerment of local community. The participatory approach aims to rescue and enhance the local knowledge since it recognizes that this kind of problems are better known by native actors. The objective of the study was to describe the role played by the community empowerment on food security improvement in the NGO “O Viveiro” (15°43'37.77"S; 32°46'27.53"E) and Barrio Broma village (15°43'58.78"S; 32°46'7.27"E) in Chitima, Mozambique. A center for training in goat livestock and orchard was build. A community orchard was co-constructed between foreign technicians and local actors. The prototype was installed in February, 2016 by the technician team and local community with 16 m2 as a nursery garden. Two orchard workshops were conducted in order to design a sustainable productive model which mixes both local and technological approaches. Two goat meat workshops were conducted in order to describe local methods and train the community to conduce their own techniques with high sanitary and productive standards. Technician team stayed in Mozambique until May, 2016. The quorum for the orchard workshops was 20 and 14 persons respectively, which represents 100% and 70%of the total requested quorum (20). For the goat meat workshops were 4 and 5 persons, which representa80% and 100% of the total requested quorum (5). Until August, 2016, the orchard is 3.219 m2 and it grows several vegetables as beans, chili pepper, garlic, onion, tomatoes, lettuce, sweet potato, yuca potato, cabbage, eggplant, papaya trees, mango, and cassava. The process of increasing in size and diversification of vegetables grown was led entirely by the local community. In connection with this, the local community started to harvest and began to sell the vegetable products at the local market. At the meat goat workshops, local participants rescued a local knowledge by describing and practicing a traditional way to process goat meat by drying it outdoors and then doing a smoked treatment. This information might contribute to describe the level of empowerment of this community, and thus give evidence of acceptance of foreign intervention for improving their own proceedings and traditions.Keywords: children malnutrition, food security, Local community, participatory approach
Procedia PDF Downloads 267543 The New World Kirkpatrick Model as an Evaluation Tool for a Publication Writing Programme
Authors: Eleanor Nel
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Research output is an indicator of institutional performance (and quality), resulting in increased pressure on academic institutions to perform in the research arena. Research output is further utilised to obtain research funding. Resultantly, academic institutions face significant pressure from governing bodies to provide evidence on the return for research investments. Research output has thus become a substantial discourse within institutions, mainly due to the processes linked to evaluating research output and the associated allocation of research funding. This focus on research outputs often surpasses the development of robust, widely accepted tools to additionally measure research impact at institutions. A publication writing programme, for enhancing research output, was launched at a South African university in 2011. Significant amounts of time, money, and energy have since been invested in the programme. Although participants provided feedback after each session, no formal review was conducted to evaluate the research output directly associated with the programme. Concerns in higher education about training costs, learning results, and the effect on society have increased the focus on value for money and the need to improve training, research performance, and productivity. Furthermore, universities rely on efficient and reliable monitoring and evaluation systems, in addition to the need to demonstrate accountability. While publishing does not occur immediately, achieving a return on investment from the intervention is critical. A multi-method study, guided by the New World Kirkpatrick Model (NWKM), was conducted to determine the impact of the publication writing programme for the period of 2011 to 2018. Quantitative results indicated a total of 314 academics participating in 72 workshops over the study period. To better understand the quantitative results, an open-ended questionnaire and semi-structured interviews were conducted with nine participants from a particular faculty as a convenience sample. The purpose of the research was to collect information to develop a comprehensive framework for impact evaluation that could be used to enhance the current design and delivery of the programme. The qualitative findings highlighted the critical role of a multi-stakeholder strategy in strengthening support before, during, and after a publication writing programme to improve the impact and research outputs. Furthermore, monitoring on-the-job learning is critical to ingrain the new skills academics have learned during the writing workshops and to encourage them to be accountable and empowered. The NWKM additionally provided essential pointers on how to link the results more effectively from publication writing programmes to institutional strategic objectives to improve research performance and quality, as well as what should be included in a comprehensive evaluation framework.Keywords: evaluation, framework, impact, research output
Procedia PDF Downloads 74542 Modeling Geogenic Groundwater Contamination Risk with the Groundwater Assessment Platform (GAP)
Authors: Joel Podgorski, Manouchehr Amini, Annette Johnson, Michael Berg
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One-third of the world’s population relies on groundwater for its drinking water. Natural geogenic arsenic and fluoride contaminate ~10% of wells. Prolonged exposure to high levels of arsenic can result in various internal cancers, while high levels of fluoride are responsible for the development of dental and crippling skeletal fluorosis. In poor urban and rural settings, the provision of drinking water free of geogenic contamination can be a major challenge. In order to efficiently apply limited resources in the testing of wells, water resource managers need to know where geogenically contaminated groundwater is likely to occur. The Groundwater Assessment Platform (GAP) fulfills this need by providing state-of-the-art global arsenic and fluoride contamination hazard maps as well as enabling users to create their own groundwater quality models. The global risk models were produced by logistic regression of arsenic and fluoride measurements using predictor variables of various soil, geological and climate parameters. The maps display the probability of encountering concentrations of arsenic or fluoride exceeding the World Health Organization’s (WHO) stipulated concentration limits of 10 µg/L or 1.5 mg/L, respectively. In addition to a reconsideration of the relevant geochemical settings, these second-generation maps represent a great improvement over the previous risk maps due to a significant increase in data quantity and resolution. For example, there is a 10-fold increase in the number of measured data points, and the resolution of predictor variables is generally 60 times greater. These same predictor variable datasets are available on the GAP platform for visualization as well as for use with a modeling tool. The latter requires that users upload their own concentration measurements and select the predictor variables that they wish to incorporate in their models. In addition, users can upload additional predictor variable datasets either as features or coverages. Such models can represent an improvement over the global models already supplied, since (a) users may be able to use their own, more detailed datasets of measured concentrations and (b) the various processes leading to arsenic and fluoride groundwater contamination can be isolated more effectively on a smaller scale, thereby resulting in a more accurate model. All maps, including user-created risk models, can be downloaded as PDFs. There is also the option to share data in a secure environment as well as the possibility to collaborate in a secure environment through the creation of communities. In summary, GAP provides users with the means to reliably and efficiently produce models specific to their region of interest by making available the latest datasets of predictor variables along with the necessary modeling infrastructure.Keywords: arsenic, fluoride, groundwater contamination, logistic regression
Procedia PDF Downloads 342541 Neuropsychiatric Outcomes of Intensive Music Therapy in Stroke Rehabilitation A Premilitary Investigation
Authors: Honey Bryant, Elvina Chu
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Stroke is the leading cause of disability in adults in Canada and directly related to depression, anxiety, and sleep disorders; with an estimated annual cost of $50 billion in health care. Strokes not only impact the individual but society as a whole. Current stroke rehabilitation does not include Music Therapy, although it has success in clinical research in the use of stroke rehabilitation. This study examines the use of neurologic music therapy (NMT) in conjunction with stroke rehabilitation to improve sleep quality, reduce stress levels, and promote neurogenesis. Existing research on NMT in stroke is limited, which means any conclusive information gathered during this study will be significant. My novel hypotheses are a.) stroke patients will become less depressed and less anxious with improved sleep following NMT. b.) NMT will reduce stress levels and promote neurogenesis in stroke patients admitted for rehabilitation. c.) Beneficial effects of NMT will be sustained at least short-term following treatment. Participants were recruited from the in-patient stroke rehabilitation program at Providence Care Hospital in Kingston, Ontario, Canada. All participants-maintained stroke rehabilitation treatment as normal. The study was spilt into two groups, the first being Passive Music Listening (PML) and the second Neurologic Music Therapy (NMT). Each group underwent 10 sessions of intensive music therapy lasting 45 minutes for 10 consecutive days, excluding weekends. Psychiatric Assessments, Epworth Sleepiness Scale (ESS), Hospital Anxiety & Depression Rating Scale (HADS), and Music Engagement Questionnaire (MusEQ), were completed, followed by a general feedback interview. Physiological markers of stress were measured through blood pressure measurements and heart rate variability. Serum collections reviewed neurogenesis via Brain-derived neurotrophic factor (BDNF) and stress markers of cortisol levels. As this study is still on-going, a formal analysis of data has not been fully completed, although trends are following our hypotheses. A decrease in sleepiness and anxiety is seen upon the first cohort of PML. Feedback interviews have indicated most participants subjectively felt more relaxed and thought PML was useful in their recovery. If the hypothesis is supported, larger external funding which will allow for greater investigation of the use of NMT in stroke rehabilitation. As we know, NMT is not covered under Ontario Health Insurance Plan (OHIP), so there is limited scientific data surrounding its uses as a clinical tool. This research will provide detailed findings of the treatment of neuropsychiatric aspects of stroke. Concurrently, a passive music listening study is being designed to further review the use of PML in rehabilitation as well.Keywords: music therapy, psychotherapy, neurologic music therapy, passive music listening, neuropsychiatry, counselling, behavioural, stroke, stroke rehabilitation, rehabilitation, neuroscience
Procedia PDF Downloads 107540 Landslide Susceptibility Analysis in the St. Lawrence Lowlands Using High Resolution Data and Failure Plane Analysis
Authors: Kevin Potoczny, Katsuichiro Goda
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The St. Lawrence lowlands extend from Ottawa to Quebec City and are known for large deposits of sensitive Leda clay. Leda clay deposits are responsible for many large landslides, such as the 1993 Lemieux and 2010 St. Jude (4 fatalities) landslides. Due to the large extent and sensitivity of Leda clay, regional hazard analysis for landslides is an important tool in risk management. A 2018 regional study by Farzam et al. on the susceptibility of Leda clay slopes to landslide hazard uses 1 arc second topographical data. A qualitative method known as Hazus is used to estimate susceptibility by checking for various criteria in a location and determine a susceptibility rating on a scale of 0 (no susceptibility) to 10 (very high susceptibility). These criteria are slope angle, geological group, soil wetness, and distance from waterbodies. Given the flat nature of St. Lawrence lowlands, the current assessment fails to capture local slopes, such as the St. Jude site. Additionally, the data did not allow one to analyze failure planes accurately. This study majorly improves the analysis performed by Farzam et al. in two aspects. First, regional assessment with high resolution data allows for identification of local locations that may have been previously identified as low susceptibility. This then provides the opportunity to conduct a more refined analysis on the failure plane of the slope. Slopes derived from 1 arc second data are relatively gentle (0-10 degrees) across the region; however, the 1- and 2-meter resolution 2022 HRDEM provided by NRCAN shows that short, steep slopes are present. At a regional level, 1 arc second data can underestimate the susceptibility of short, steep slopes, which can be dangerous as Leda clay landslides behave retrogressively and travel upwards into flatter terrain. At the location of the St. Jude landslide, slope differences are significant. 1 arc second data shows a maximum slope of 12.80 degrees and a mean slope of 4.72 degrees, while the HRDEM data shows a maximum slope of 56.67 degrees and a mean slope of 10.72 degrees. This equates to a difference of three susceptibility levels when the soil is dry and one susceptibility level when wet. The use of GIS software is used to create a regional susceptibility map across the St. Lawrence lowlands at 1- and 2-meter resolutions. Failure planes are necessary to differentiate between small and large landslides, which have so far been ignored in regional analysis. Leda clay failures can only retrogress as far as their failure planes, so the regional analysis must be able to transition smoothly into a more robust local analysis. It is expected that slopes within the region, once previously assessed at low susceptibility scores, contain local areas of high susceptibility. The goal is to create opportunities for local failure plane analysis to be undertaken, which has not been possible before. Due to the low resolution of previous regional analyses, any slope near a waterbody could be considered hazardous. However, high-resolution regional analysis would allow for more precise determination of hazard sites.Keywords: hazus, high-resolution DEM, leda clay, regional analysis, susceptibility
Procedia PDF Downloads 65539 Modeling Engagement with Multimodal Multisensor Data: The Continuous Performance Test as an Objective Tool to Track Flow
Authors: Mohammad H. Taheri, David J. Brown, Nasser Sherkat
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Engagement is one of the most important factors in determining successful outcomes and deep learning in students. Existing approaches to detect student engagement involve periodic human observations that are subject to inter-rater reliability. Our solution uses real-time multimodal multisensor data labeled by objective performance outcomes to infer the engagement of students. The study involves four students with a combined diagnosis of cerebral palsy and a learning disability who took part in a 3-month trial over 59 sessions. Multimodal multisensor data were collected while they participated in a continuous performance test. Eye gaze, electroencephalogram, body pose, and interaction data were used to create a model of student engagement through objective labeling from the continuous performance test outcomes. In order to achieve this, a type of continuous performance test is introduced, the Seek-X type. Nine features were extracted including high-level handpicked compound features. Using leave-one-out cross-validation, a series of different machine learning approaches were evaluated. Overall, the random forest classification approach achieved the best classification results. Using random forest, 93.3% classification for engagement and 42.9% accuracy for disengagement were achieved. We compared these results to outcomes from different models: AdaBoost, decision tree, k-Nearest Neighbor, naïve Bayes, neural network, and support vector machine. We showed that using a multisensor approach achieved higher accuracy than using features from any reduced set of sensors. We found that using high-level handpicked features can improve the classification accuracy in every sensor mode. Our approach is robust to both sensor fallout and occlusions. The single most important sensor feature to the classification of engagement and distraction was shown to be eye gaze. It has been shown that we can accurately predict the level of engagement of students with learning disabilities in a real-time approach that is not subject to inter-rater reliability, human observation or reliant on a single mode of sensor input. This will help teachers design interventions for a heterogeneous group of students, where teachers cannot possibly attend to each of their individual needs. Our approach can be used to identify those with the greatest learning challenges so that all students are supported to reach their full potential.Keywords: affective computing in education, affect detection, continuous performance test, engagement, flow, HCI, interaction, learning disabilities, machine learning, multimodal, multisensor, physiological sensors, student engagement
Procedia PDF Downloads 83538 Three Dimensional Computational Fluid Dynamics Simulation of Wall Condensation inside Inclined Tubes
Authors: Amirhosein Moonesi Shabestary, Eckhard Krepper, Dirk Lucas
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The current PhD project comprises CFD-modeling and simulation of condensation and heat transfer inside horizontal pipes. Condensation plays an important role in emergency cooling systems of reactors. The emergency cooling system consists of inclined horizontal pipes which are immersed in a tank of subcooled water. In the case of an accident the water level in the core is decreasing, steam comes in the emergency pipes, and due to the subcooled water around the pipe, this steam will start to condense. These horizontal pipes act as a strong heat sink which is responsible for a quick depressurization of the reactor core when any accident happens. This project is defined in order to model all these processes which happening in the emergency cooling systems. The most focus of the project is on detection of different morphologies such as annular flow, stratified flow, slug flow and plug flow. This project is an ongoing project which has been started 1 year ago in Helmholtz Zentrum Dresden Rossendorf (HZDR), Fluid Dynamics department. In HZDR most in cooperation with ANSYS different models are developed for modeling multiphase flows. Inhomogeneous MUSIG model considers the bubble size distribution and is used for modeling small-scaled dispersed gas phase. AIAD (Algebraic Interfacial Area Density Model) is developed for detection of the local morphology and corresponding switch between them. The recent model is GENTOP combines both concepts. GENTOP is able to simulate co-existing large-scaled (continuous) and small-scaled (polydispersed) structures. All these models are validated for adiabatic cases without any phase change. Therefore, the start point of the current PhD project is using the available models and trying to integrate phase transition and wall condensing models into them. In order to simplify the idea of condensation inside horizontal tubes, 3 steps have been defined. The first step is the investigation of condensation inside a horizontal tube by considering only direct contact condensation (DCC) and neglect wall condensation. Therefore, the inlet of the pipe is considered to be annular flow. In this step, AIAD model is used in order to detect the interface. The second step is the extension of the model to consider wall condensation as well which is closer to the reality. In this step, the inlet is pure steam, and due to the wall condensation, a liquid film occurs near the wall which leads to annular flow. The last step will be modeling of different morphologies which are occurring inside the tube during the condensation via using GENTOP model. By using GENTOP, the dispersed phase is able to be considered and simulated. Finally, the results of the simulations will be validated by experimental data which will be available also in HZDR.Keywords: wall condensation, direct contact condensation, AIAD model, morphology detection
Procedia PDF Downloads 292537 The Effects of Alpha-Lipoic Acid Supplementation on Post-Stroke Patients: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Authors: Hamid Abbasi, Neda Jourabchi, Ranasadat Abedi, Kiarash Tajernarenj, Mehdi Farhoudi, Sarvin Sanaie
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Background: Alpha lipoic acid (ALA), fat- and water-soluble, coenzyme with sulfuret content, has received considerable attention for its potential therapeutic role in diabetes, cardiovascular diseases, cancers, and central nervous disease. This investigation aims to evaluate the probable protective effects of ALA in stroke patients. Methods: Based on Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines, This meta-analysis was performed. The PICO criteria for this meta-analysis were as follows: Population/Patients (P: stroke patients); Intervention (I: ALA); Comparison (C: control); Outcome (O: blood glucose, lipid profile, oxidative stress, inflammatory factors).In addition, Studies that were excluded from the analysis consisted of in vitro, in vivo, and ex vivo studies, case reports, quasi-experimental studies. Scopus, PubMed, Web of Science, EMBASE databases were searched until August 2023. Results: Of 496 records that were screened in the title/abstract stage, 9 studies were included in this meta-analysis. The sample sizes in the included studies vary between 28 and 90. The result of risk of bias was performed via risk of bias (RoB) in randomized-controlled trials (RCTs) based on the second version of the Cochrane RoB assessment tool. 8 studies had a definitely high risk of bias. Discussion: To the best of our knowledge, The present meta-analysis is the first study addressing the effectiveness of ALA supplementation in enhancing post-stroke metabolic markers, including lipid profile, oxidative stress, and inflammatory indices. It is imperative to acknowledge certain potential limitations inherent in this study. First of all, type of treatment (oral or intravenous infusion) could alter the bioavailability of ALA. Our study had restricted evidence regarding the impact of ALA supplementation on included outcomes. Therefore, further research is warranted to develop into the effects of ALA specifically on inflammation and oxidative stress. Funding: The research protocol was approved and supported by the Student Research Committee, Tabriz University of Medical Sciences (grant number: 72825). Registration: This study was registered in the International prospective register of systematic reviews (PROSPERO ID: CR42023461612).Keywords: alpha-lipoic acid, lipid profile, blood glucose, inflammatory factors, oxidative stress, meta-analysis, post-stroke
Procedia PDF Downloads 59536 Salmonella Emerging Serotypes in Northwestern Italy: Genetic Characterization by Pulsed-Field Gel Electrophoresis
Authors: Clara Tramuta, Floris Irene, Daniela Manila Bianchi, Monica Pitti, Giulia Federica Cazzaniga, Lucia Decastelli
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This work presents the results obtained by the Regional Reference Centre for Salmonella Typing (CeRTiS) in a retrospective study aimed to investigate, through Pulsed-field Gel Electrophoresis (PFGE) analysis, the genetic relatedness of emerging Salmonella serotypes of human origin circulating in North-West of Italy. Furthermore, the goal of this work was to create a Regional database to facilitate foodborne outbreak investigation and to monitor them at an earlier stage. A total of 112 strains, isolated from 2016 to 2018 in hospital laboratories, were included in this study. The isolates were previously identified as Salmonella according to standard microbiological techniques and serotyping was performed according to ISO 6579-3 and the Kaufmann-White scheme using O and H antisera (Statens Serum Institut®). All strains were characterized by PFGE: analysis was conducted according to a standardized PulseNet protocol. The restriction enzyme XbaI was used to generate several distinguishable genomic fragments on the agarose gel. PFGE was performed on a CHEF Mapper system, separating large fragments and generating comparable genetic patterns. The agarose gel was then stained with GelRed® and photographed under ultraviolet transillumination. The PFGE patterns obtained from the 112 strains were compared using Bionumerics version 7.6 software with the Dice coefficient with 2% band tolerance and 2% optimization. For each serotype, the data obtained with the PFGE were compared according to the geographical origin and the year in which they were isolated. Salmonella strains were identified as follow: S. Derby n. 34; S. Infantis n. 38; S. Napoli n. 40. All the isolates had appreciable restricted digestion patterns ranging from approximately 40 to 1100 kb. In general, a fairly heterogeneous distribution of pulsotypes has emerged in the different provinces. Cluster analysis indicated high genetic similarity (≥ 83%) among strains of S. Derby (n. 30; 88%), S. Infantis (n. 36; 95%) and S. Napoli (n. 38; 95%) circulating in north-western Italy. The study underlines the genomic similarities shared by the emerging Salmonella strains in Northwest Italy and allowed to create a database to detect outbreaks in an early stage. Therefore, the results confirmed that PFGE is a powerful and discriminatory tool to investigate the genetic relationships among strains in order to monitoring and control Salmonellosis outbreak spread. Pulsed-field gel electrophoresis (PFGE) still represents one of the most suitable approaches to characterize strains, in particular for the laboratories for which NGS techniques are not available.Keywords: emerging Salmonella serotypes, genetic characterization, human strains, PFGE
Procedia PDF Downloads 99535 Predicting Blockchain Technology Installation Cost in Supply Chain System through Supervised Learning
Authors: Hossein Havaeji, Tony Wong, Thien-My Dao
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1. Research Problems and Research Objectives: Blockchain Technology-enabled Supply Chain System (BT-enabled SCS) is the system using BT to drive SCS transparency, security, durability, and process integrity as SCS data is not always visible, available, or trusted. The costs of operating BT in the SCS are a common problem in several organizations. The costs must be estimated as they can impact existing cost control strategies. To account for system and deployment costs, it is necessary to overcome the following hurdle. The problem is that the costs of developing and running a BT in SCS are not yet clear in most cases. Many industries aiming to use BT have special attention to the importance of BT installation cost which has a direct impact on the total costs of SCS. Predicting BT installation cost in SCS may help managers decide whether BT is to be an economic advantage. The purpose of the research is to identify some main BT installation cost components in SCS needed for deeper cost analysis. We then identify and categorize the main groups of cost components in more detail to utilize them in the prediction process. The second objective is to determine the suitable Supervised Learning technique in order to predict the costs of developing and running BT in SCS in a particular case study. The last aim is to investigate how the running BT cost can be involved in the total cost of SCS. 2. Work Performed: Applied successfully in various fields, Supervised Learning is a method to set the data frame, treat the data, and train/practice the method sort. It is a learning model directed to make predictions of an outcome measurement based on a set of unforeseen input data. The following steps must be conducted to search for the objectives of our subject. The first step is to make a literature review to identify the different cost components of BT installation in SCS. Based on the literature review, we should choose some Supervised Learning methods which are suitable for BT installation cost prediction in SCS. According to the literature review, some Supervised Learning algorithms which provide us with a powerful tool to classify BT installation components and predict BT installation cost are the Support Vector Regression (SVR) algorithm, Back Propagation (BP) neural network, and Artificial Neural Network (ANN). Choosing a case study to feed data into the models comes into the third step. Finally, we will propose the best predictive performance to find the minimum BT installation costs in SCS. 3. Expected Results and Conclusion: This study tends to propose a cost prediction of BT installation in SCS with the help of Supervised Learning algorithms. At first attempt, we will select a case study in the field of BT-enabled SCS, and then use some Supervised Learning algorithms to predict BT installation cost in SCS. We continue to find the best predictive performance for developing and running BT in SCS. Finally, the paper will be presented at the conference.Keywords: blockchain technology, blockchain technology-enabled supply chain system, installation cost, supervised learning
Procedia PDF Downloads 114534 Link People from Different Age Together: Attitude and Behavior Changes in Inter-Generational Interaction Program
Authors: Qian Sun, Dannie Dai, Vivian Lou
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Background: Changes in population structure and modernization have left traditional channels of achieving intergenerational solidarity in crisis. Policies and projects purposefully structuring intergenerational interaction are regarded as effective ways to enhance positive attitude changes between generations. However, few inter-generational interaction program has put equal emphasis on promoting positive changes on both attitude and behavior across generational groups. Objective: This study evaluated the effectiveness of an intergenerational interaction program which aims to facilitate positive attitude and behavioral interaction between both young and old individuals in Hong Kong. Method: A quasi-experimental design was adopted with the sample of 150 older participants and 161 young participants. Among 73 older and 78 young participants belong to experiment groups while 77 older participants and 84 young participants belong to control groups. The Age Group Evaluation and Description scale (AGED) was adopted to measure attitude toward young people by older participants and the Chinese version of Kogan’s Attitude towards Older People (KAOP) as well as Polizzi’s refined version of the Ageing Semantic Differential Scale (ASD) were used to measure attitude toward older people by the younger generation. The interpersonal behaviour of participants was assessed using Beglgrave’s behavioural observation tool. Six primary verbal or non-verbal interpersonal behaviours including smiles, looks, touches, encourages, initiated conversations and assists were identified and observed. Findings Effectiveness of attitude and behavior changes on both younger and older participants was confirmed in results. Compared with participants from the control group, experimental participants of elderly showed significant positive changes of attitudes toward the younger generation as assessed by AGED (F=138.34, p < .001). Moreover, older participants showed significant positive changes on three out of six behaviours (visual attention: t=2.26, p<0.05; initiate conversation: t=3.42, p<0.01; and touch: t=2.28, p<0.05). For younger participants, participants from experimental group showed significant positive changes in attitude toward older people (with F-score of 47.22 for KAOP and 72.75 for ASD, p<.001). Young participants also showed significant positive changes in two out of six behaviours (visual attention: t=3.70, p<0.01; initiate conversation: t=2.04, p<0.001). There is no significant relationship between attitude change and behaviour change in both older (p=0.86) and younger (p=0.22) groups. Conclusion: This study has brought practical implications for social work. The effective model of this program could assist social workers and allied professionals to design relevant projects for nurture intergenerational solidarity. Furthermore, insignificant results between attitude and behavior changes revealed that attitude change was not a strong predictor for behavior change, hence, intergenerational programs against age-stereotype should put equal emphasis on both attitudinal and behavioral aspects.Keywords: attitude and behaviour changes, intergenerational interaction, intergenerational solidarity, program design
Procedia PDF Downloads 239533 Advancing Women's Participation in SIDS' Renewable Energy Sector: A Multicriteria Evaluation Framework
Authors: Carolina Mayen Huerta, Clara Ivanescu, Paloma Marcos
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Due to their unique geographic challenges and the imperative to combat climate change, Small Island Developing States (SIDS) are experiencing rapid growth in the renewable energy (RE) sector. However, women's representation in formal employment within this burgeoning field remains significantly lower than their male counterparts. Conventional methodologies often overlook critical geographic data that influence women's job prospects. To address this gap, this paper introduces a Multicriteria Evaluation (MCE) framework designed to identify spatially enabling environments and restrictions affecting women's access to formal employment and business opportunities in the SIDS' RE sector. The proposed MCE framework comprises 24 key factors categorized into four dimensions: Individual, Contextual, Accessibility, and Place Characterization. "Individual factors" encompass personal attributes influencing women's career development, including caregiving responsibilities, exposure to domestic violence, and disparities in education. "Contextual factors" pertain to the legal and policy environment, influencing workplace gender discrimination, financial autonomy, and overall gender empowerment. "Accessibility factors" evaluate women's day-to-day mobility, considering travel patterns, access to public transport, educational facilities, RE job opportunities, healthcare facilities, and financial services. Finally, "Place Characterization factors" enclose attributes of geographical locations or environments. This dimension includes walkability, public transport availability, safety, electricity access, digital inclusion, fragility, conflict, violence, water and sanitation, and climatic factors in specific regions. The analytical framework proposed in this paper incorporates a spatial methodology to visualize regions within countries where conducive environments for women to access RE jobs exist. In areas where these environments are absent, the methodology serves as a decision-making tool to reinforce critical factors, such as transportation, education, and internet access, which currently hinder access to employment opportunities. This approach is designed to equip policymakers and institutions with data-driven insights, enabling them to make evidence-based decisions that consider the geographic dimensions of disparity. These insights, in turn, can help ensure the efficient allocation of resources to achieve gender equity objectives.Keywords: gender, women, spatial analysis, renewable energy, access
Procedia PDF Downloads 57532 A Multicriteria Evaluation Framework for Enhancing Women's Participation in SIDS Renewable Energy Sector
Authors: Carolina Mayen Huerta, Clara Ivanescu, Paloma Marcos
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Due to their unique geographic challenges and the imperative to combat climate change, Small Island Developing States (SIDS) are experiencing rapid growth in the renewable energy (RE) sector. However, women's representation in formal employment within this burgeoning field remains significantly lower than their male counterparts. Conventional methodologies often overlook critical geographic data that influence women's job prospects. To address this gap, this paper introduces a Multicriteria Evaluation (MCE) framework designed to identify spatially enabling environments and restrictions affecting women's access to formal employment and business opportunities in the SIDS' RE sector. The proposed MCE framework comprises 24 key factors categorized into four dimensions: Individual, Contextual, Accessibility, and Place Characterization. "Individual factors" encompass personal attributes influencing women's career development, including caregiving responsibilities, exposure to domestic violence, and disparities in education. "Contextual factors" pertain to the legal and policy environment, influencing workplace gender discrimination, financial autonomy, and overall gender empowerment. "Accessibility factors" evaluate women's day-to-day mobility, considering travel patterns, access to public transport, educational facilities, RE job opportunities, healthcare facilities, and financial services. Finally, "Place Characterization factors" enclose attributes of geographical locations or environments. This dimension includes walkability, public transport availability, safety, electricity access, digital inclusion, fragility, conflict, violence, water and sanitation, and climatic factors in specific regions. The analytical framework proposed in this paper incorporates a spatial methodology to visualize regions within countries where conducive environments for women to access RE jobs exist. In areas where these environments are absent, the methodology serves as a decision-making tool to reinforce critical factors, such as transportation, education, and internet access, which currently hinder access to employment opportunities. This approach is designed to equip policymakers and institutions with data-driven insights, enabling them to make evidence-based decisions that consider the geographic dimensions of disparity. These insights, in turn, can help ensure the efficient allocation of resources to achieve gender equity objectives.Keywords: gender, women, spatial analysis, renewable energy, access
Procedia PDF Downloads 77531 Design of an Ultra High Frequency Rectifier for Wireless Power Systems by Using Finite-Difference Time-Domain
Authors: Felipe M. de Freitas, Ícaro V. Soares, Lucas L. L. Fortes, Sandro T. M. Gonçalves, Úrsula D. C. Resende
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There is a dispersed energy in Radio Frequencies (RF) that can be reused to power electronics circuits such as: sensors, actuators, identification devices, among other systems, without wire connections or a battery supply requirement. In this context, there are different types of energy harvesting systems, including rectennas, coil systems, graphene and new materials. A secondary step of an energy harvesting system is the rectification of the collected signal which may be carried out, for example, by the combination of one or more Schottky diodes connected in series or shunt. In the case of a rectenna-based system, for instance, the diode used must be able to receive low power signals at ultra-high frequencies. Therefore, it is required low values of series resistance, junction capacitance and potential barrier voltage. Due to this low-power condition, voltage multiplier configurations are used such as voltage doublers or modified bridge converters. Lowpass filter (LPF) at the input, DC output filter, and a resistive load are also commonly used in the rectifier design. The electronic circuits projects are commonly analyzed through simulation in SPICE (Simulation Program with Integrated Circuit Emphasis) environment. Despite the remarkable potential of SPICE-based simulators for complex circuit modeling and analysis of quasi-static electromagnetic fields interaction, i.e., at low frequency, these simulators are limited and they cannot model properly applications of microwave hybrid circuits in which there are both, lumped elements as well as distributed elements. This work proposes, therefore, the electromagnetic modelling of electronic components in order to create models that satisfy the needs for simulations of circuits in ultra-high frequencies, with application in rectifiers coupled to antennas, as in energy harvesting systems, that is, in rectennas. For this purpose, the numerical method FDTD (Finite-Difference Time-Domain) is applied and SPICE computational tools are used for comparison. In the present work, initially the Ampere-Maxwell equation is applied to the equations of current density and electric field within the FDTD method and its circuital relation with the voltage drop in the modeled component for the case of lumped parameter using the FDTD (Lumped-Element Finite-Difference Time-Domain) proposed in for the passive components and the one proposed in for the diode. Next, a rectifier is built with the essential requirements for operating rectenna energy harvesting systems and the FDTD results are compared with experimental measurements.Keywords: energy harvesting system, LE-FDTD, rectenna, rectifier, wireless power systems
Procedia PDF Downloads 124530 Evaluation Method for Fouling Risk Using Quartz Crystal Microbalance
Authors: Natsuki Kishizawa, Keiko Nakano, Hussam Organji, Amer Shaiban, Mohammad Albeirutty
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One of the most important tasks in operating desalination plants using a reverse osmosis (RO) method is preventing RO membrane fouling caused by foulants found in seawater. Optimal design of the pre-treatment process of RO process for plants enables the reduction of foulants. Therefore, a quantitative evaluation of the fouling risk in pre-treated water, which is fed to RO, is required for optimal design. Some measurement methods for water quality such as silt density index (SDI) and total organic carbon (TOC) have been conservatively applied for evaluations. However, these methods have not been effective in some situations for evaluating the fouling risk of RO feed water. Furthermore, stable management of plants will be possible by alerts and appropriate control of the pre-treatment process by using the method if it can be applied to the inline monitoring system for the fouling risk of RO feed water. The purpose of this study is to develop a method to evaluate the fouling risk of RO feed water. We applied a quartz crystal microbalance (QCM) to measure the amount of foulants found in seawater using a sensor whose surface is coated with polyamide thin film, which is the main material of a RO membrane. The increase of the weight of the sensor after a certain length of time in which the sample water passes indicates the fouling risk of the sample directly. We classified the values as “FP: Fouling Potential”. The characteristics of the method are to measure the very small amount of substances in seawater in a short time: < 2h, and from a small volume of the sample water: < 50mL. Using some RO cell filtration units, a higher correlation between the pressure increase given by RO fouling and the FP from the method than SDI and TOC was confirmed in the laboratory-scale test. Then, to establish the correlation in the actual bench-scale RO membrane module, and to confirm the feasibility of the monitoring system as a control tool for the pre-treatment process, we have started a long-term test at an experimental desalination site by the Red Sea in Jeddah, Kingdom of Saudi Arabia. Implementing inline equipment for the method made it possible to measure FP intermittently (4 times per day) and automatically. Moreover, for two 3-month long operations, the RO operation pressure among feed water samples of different qualities was compared. The pressure increase through a RO membrane module was observed at a high FP RO unit in which feed water was treated by a cartridge filter only. On the other hand, the pressure increase was not observed at a low FP RO unit in which feed water was treated by an ultra-filter during the operation. Therefore, the correlation in an actual scale RO membrane was established in two runs of two types of feed water. The result suggested that the FP method enables the evaluation of the fouling risk of RO feed water.Keywords: fouling, monitoring, QCM, water quality
Procedia PDF Downloads 206529 Nutritional Education in Health Resort Institutions in the Face of Demographic and Epidemiological Changes in Poland
Authors: J. Woźniak-Holecka, T. Holecki, S. Jaruga
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Spa treatment is an important area of the health care system in Poland due to the increasing needs of the population and the context of historical conditions for this form of therapy. It extends the range of financing possibilities of the outlets and increases the potential of spa services, which is very important in the context of demographic and epidemiological changes. The main advantages of spa treatment services include its relatively wide availability, low risk of side effects, good patient tolerance, long-lasting curative effect and a relatively low cost. In addition, patients should be provided with a proper diet and enable participation in health education and health promotion classes aimed at health problems consistent with the treatment profile. Challenges for global health care systems include a sharp increase in spending on benefits, dynamic development of health technologies and growing social expectations. This requires extending the competences of health resort facilities for health promotion. Within each type of health resort institutions in Poland, nutritional education services are implemented, aimed at creating and consolidating proper eating habits. Choosing the right diet can speed up recovery or become one of the methods to alleviate the symptoms of chronic diseases. During spa treatment patient learns the principles of rational nutrition and adequate dietotherapy to his diseases. The aim of the project is to assess the frequency and quality of nutritional education provided to patients in health resort facilities in a nationwide perspective. The material for the study will be data obtained as part of an in-depth interview conducted among Heads of Nutrition Departments of selected institutions. The use of nutritional education in a health resort may be an important goal of implementing the state health policy as a useful tool to reduce the risk of diet-related diseases. Recognizing nutritional education in health resort institutions as a type of full-value health service can be effective system support for health policy, including seniors, due to demographic changes currently occurring in the Polish population. Furthermore, it is necessary to increase the interest and motivation of patients to follow the recommendations of nutritional education, because it will bring tangible benefits for the long-term effects of therapy and care should be taken for the form and methodology of nutrition education implemented in health resort institutions. Finally it is necessary to construct an educational offer in terms of selected groups of patients with the highest health needs: the elderly and the disabled. In conclusion, it can be said that the system of nutritional education implemented in polish health resort institutions should be subjected to global changes and strong systemic correction.Keywords: health care system, nutritional education, public health, spa and treatment
Procedia PDF Downloads 110528 Thermal Imaging of Aircraft Piston Engine in Laboratory Conditions
Authors: Lukasz Grabowski, Marcin Szlachetka, Tytus Tulwin
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The main task of the engine cooling system is to maintain its average operating temperatures within strictly defined limits. Too high or too low average temperatures result in accelerated wear or even damage to the engine or its individual components. In order to avoid local overheating or significant temperature gradients, leading to high stresses in the component, the aim is to ensure an even flow of air. In the case of analyses related to heat exchange, one of the main problems is the comparison of temperature fields because standard measuring instruments such as thermocouples or thermistors only provide information about the course of temperature at a given point. Thermal imaging tests can be helpful in this case. With appropriate camera settings and taking into account environmental conditions, we are able to obtain accurate temperature fields in the form of thermograms. Emission of heat from the engine to the engine compartment is an important issue when designing a cooling system. Also, in the case of liquid cooling, the main sources of heat in the form of emissions from the engine block, cylinders, etc. should be identified. It is important to redesign the engine compartment ventilation system. Ensuring proper cooling of aircraft reciprocating engine is difficult not only because of variable operating range but mainly because of different cooling conditions related to the change of speed or altitude of flight. Engine temperature also has a direct and significant impact on the properties of engine oil, which under the influence of this parameter changes, in particular, its viscosity. Too low or too high, its value can be a result of fast wear of engine parts. One of the ways to determine the temperatures occurring on individual parts of the engine is the use of thermal imaging measurements. The article presents the results of preliminary thermal imaging tests of aircraft piston diesel engine with a maximum power of about 100 HP. In order to perform the heat emission tests of the tested engine, the ThermaCAM S65 thermovision monitoring system from FLIR (Forward-Looking Infrared) together with the ThermaCAM Researcher Professional software was used. The measurements were carried out after the engine warm up. The engine speed was 5300 rpm The measurements were taken for the following environmental parameters: air temperature: 17 °C, ambient pressure: 1004 hPa, relative humidity: 38%. The temperatures distribution on the engine cylinder and on the exhaust manifold were analysed. Thermal imaging tests made it possible to relate the results of simulation tests to the real object by measuring the rib temperature of the cylinders. The results obtained are necessary to develop a CFD (Computational Fluid Dynamics) model of heat emission from the engine bay. The project/research was financed in the framework of the project Lublin University of Technology-Regional Excellence Initiative, funded by the Polish Ministry of Science and Higher Education (contract no. 030/RID/2018/19).Keywords: aircraft, piston engine, heat, emission
Procedia PDF Downloads 112527 Assessing Children’s Probabilistic and Creative Thinking in a Non-formal Learning Context
Authors: Ana Breda, Catarina Cruz
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Daily, we face unpredictable events, often attributed to chance, as there is no justification for such an occurrence. Chance, understood as a source of uncertainty, is present in several aspects of human life, such as weather forecasts, dice rolling, and lottery. Surprisingly, humans and some animals can quickly adjust their behavior to handle efficiently doubly stochastic processes (random events with two layers of randomness, like unpredictable weather affecting dice rolling). This adjustment ability suggests that the human brain has built-in mechanisms for perceiving, understanding, and responding to simple probabilities. It also explains why current trends in mathematics education include probability concepts in official curriculum programs, starting from the third year of primary education onwards. In the first years of schooling, children learn to use a certain type of (specific) vocabulary, such as never, always, rarely, perhaps, likely, and unlikely, to help them to perceive and understand the probability of some events. These are keywords of crucial importance for their perception and understanding of probabilities. The development of the probabilistic concepts comes from facts and cause-effect sequences resulting from the subject's actions, as well as the notion of chance and intuitive estimates based on everyday experiences. As part of a junior summer school program, which took place at a Portuguese university, a non-formal learning experiment was carried out with 18 children in the 5th and 6th grades. This experience was designed to be implemented in a dynamic of a serious ice-breaking game, to assess their levels of probabilistic, critical, and creative thinking in understanding impossible, certain, equally probable, likely, and unlikely events, and also to gain insight into how the non-formal learning context influenced their achievements. The criteria used to evaluate probabilistic thinking included the creative ability to conceive events classified in the specified categories, the ability to properly justify the categorization, the ability to critically assess the events classified by other children, and the ability to make predictions based on a given probability. The data analysis employs a qualitative, descriptive, and interpretative-methods approach based on students' written productions, audio recordings, and researchers' field notes. This methodology allowed us to conclude that such an approach is an appropriate and helpful formative assessment tool. The promising results of this initial exploratory study require a future research study with children from these levels of education, from different regions, attending public or private schools, to validate and expand our findings.Keywords: critical and creative thinking, non-formal mathematics learning, probabilistic thinking, serious game
Procedia PDF Downloads 19526 Suggestion of Methodology to Detect Building Damage Level Collectively with Flood Depth Utilizing Geographic Information System at Flood Disaster in Japan
Authors: Munenari Inoguchi, Keiko Tamura
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In Japan, we were suffered by earthquake, typhoon, and flood disaster in 2019. Especially, 38 of 47 prefectures were affected by typhoon #1919 occurred in October 2019. By this disaster, 99 people were dead, three people were missing, and 484 people were injured as human damage. Furthermore, 3,081 buildings were totally collapsed, 24,998 buildings were half-collapsed. Once disaster occurs, local responders have to inspect damage level of each building by themselves in order to certificate building damage for survivors for starting their life reconstruction process. At that disaster, the total number to be inspected was so high. Based on this situation, Cabinet Office of Japan approved the way to detect building damage level efficiently, that is collectively detection. However, they proposed a just guideline, and local responders had to establish the concrete and infallible method by themselves. Against this issue, we decided to establish the effective and efficient methodology to detect building damage level collectively with flood depth. Besides, we thought that the flood depth was relied on the land height, and we decided to utilize GIS (Geographic Information System) for analyzing the elevation spatially. We focused on the analyzing tool of spatial interpolation, which is utilized to survey the ground water level usually. In establishing the methodology, we considered 4 key-points: 1) how to satisfy the condition defined in the guideline approved by Cabinet Office for detecting building damage level, 2) how to satisfy survivors for the result of building damage level, 3) how to keep equitability and fairness because the detection of building damage level was executed by public institution, 4) how to reduce cost of time and human-resource because they do not have enough time and human-resource for disaster response. Then, we proposed a methodology for detecting building damage level collectively with flood depth utilizing GIS with five steps. First is to obtain the boundary of flooded area. Second is to collect the actual flood depth as sampling over flooded area. Third is to execute spatial analysis of interpolation with sampled flood depth to detect two-dimensional flood depth extent. Fourth is to divide to blocks by four categories of flood depth (non-flooded, over the floor to 100 cm, 100 cm to 180 cm and over 180 cm) following lines of roads for getting satisfaction from survivors. Fifth is to put flood depth level to each building. In Koriyama city of Fukushima prefecture, we proposed the methodology of collectively detection for building damage level as described above, and local responders decided to adopt our methodology at typhoon #1919 in 2019. Then, we and local responders detect building damage level collectively to over 1,000 buildings. We have received good feedback that the methodology was so simple, and it reduced cost of time and human-resources.Keywords: building damage inspection, flood, geographic information system, spatial interpolation
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