Search results for: modern analytical methods
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 18943

Search results for: modern analytical methods

17473 Hot Face of Cold War: 007 James Bond

Authors: Günevi Uslu Evren

Abstract:

Propaganda is one of the most effective methods for changing individual and mass opinions. Propaganda tries to get the message across to people or masses to effect rather than to provide objective information. There are many types of propaganda. Especially, political propaganda is a very powerful method that is used by states during in both war and peace. The aim of this method is to create a reaction against them by showing within the framework of internal and external enemies. Propaganda can be practiced by many different methods. Especially during the Cold War Era, the US and USSR have tried to create an ideological effect by using the mass media intensively. Cinema, which is located at the beginning of these methods, is the most powerful weapon to influence the masses. In this study, the historical process of the Cold War is examined. Especially, these propagandas that had been used by United States and The Soviet Union were investigated. The purposes of propaganda and construction methods were presented. Cold War events and relations between the US and the USSR during the Cold War will be discussed. Outlooks of two countries to each other during the Cold War, propaganda techniques used defectively during Cold War and how to use the cinema as a propaganda tool will be examined. The film "From Russia with Love, James Bond 007" that was filmed in Cold War were examined to explain how cinema was used as a propaganda tool in this context.

Keywords: cinema, cold war, James Bond, propaganda

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17472 Linguistic Analysis of the Concept ‘Relation’ in Russian and English Languages

Authors: Nadezhda Obvintceva

Abstract:

The article gives the analysis of the concept ‘relation’ from the point of view of its realization in Russian and English languages on the basis of dictionaries articles. The analysis reveals the main difference of representation of this concept in both languages. It is the number of lexemes that express its general meanings. At the end of the article the author gives an explanation of possible causes of the difference and touches upon the issue about analytical phenomena in the vocabulary.

Keywords: concept, comparison, lexeme, meaning, relation, semantics

Procedia PDF Downloads 495
17471 Photovoltaic Cells Characteristics Measurement Systems

Authors: Rekioua T., Rekioua D., Aissou S., Ouhabi A.

Abstract:

Power provided by the photovoltaic array varies with solar radiation and temperature, since these parameters influence the electrical characteristic (Ipv-Vpv) of solar cells. In Scientific research, there are different methods to obtain these characteristics. In this paper, we present three methods. A simulation one using Matlab/Simulink. The second one is the standard experimental voltage method and the third one is by using LabVIEW software. This latter is based on an electronic circuit to test PV modules. All details of this electronic schemes are presented and obtained results of the three methods with a comparison and under different meteorological conditions are presented. The proposed method is simple and very efficiency for testing and measurements of electrical characteristic curves of photovoltaic panels.

Keywords: photovoltaic cells, measurement standards, temperature sensors, data acquisition

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17470 Large Panel Technology Apartments of Yesterday and Today: Quality Aspects

Authors: Barbara Gronostajska

Abstract:

Currently, housing conditions of buildings executed in large panel technology are deteriorating. The article presents modernization solutions implemented throughout the variety of architectural activities (adding of balconies and staircases, connecting apartments) which guarantee very intriguing results that meet the needs and expectations of the modern society.

Keywords: housing estate, apartments, flats, modernization, plate blocks

Procedia PDF Downloads 478
17469 Intimate Partner Violence and the Risk of Children’s Growth and Development

Authors: Fatemeh Abdollahi, Munn-Sann Lye, Jamshid Yazdani Charati, Mehran Zarghami

Abstract:

Background: The negative consequences of intimate partner violence (IPV) on children have not been studied extensively. This study aimed to determine the prevalence of different types of IPV and its association with children’s growth and developmental problems. Methods: In a descriptive-analytical study, 596 mothers of one-year-old children referred to the primary health centers in Gonbad-e- Kavoos city were recruited (2018). The data were collected using the World Health Organization Domestic Violence, Ages and Stages Questionnaire-12 and the socio-economic, obstetrics, demographic and anthropometric characteristics related questionnaire. BMI Z-Score was categorized into three grades; thin (Z<-2), normal (-2≤Z<1), and overweight-obese (Z≥1). The data were analyzed using descriptive analysis, chi-square test, and regression. Results: The prevalence of physical, psychological, and sexual IPV was 7.4%, 29.5%, and 2.4%, respectively. Most of the children were of normal weight at one-year-old (91.7%). Similarly, the prevalence of overweight and obese was 13.3% and 8%, respectively. 2% of children had developmental problems at age one. There was a significant relationship between the father’s education and occupation and IPV and children’s delay in growth, respectively. There was no significant difference between BMI Z-Score and developmental disabilities in the children in women exposed and not exposed to all types of IPV. Conclusions: The prevalence of psychological IPV was common. IPV and children’s growth problems were influenced by the father’s socio-economic status. Preventing psychological IPV as a forerunner of other types of IPV and improving the economic situation may help in the reduction of these difficulties.

Keywords: children, development, growth, intimate partner violence

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17468 Persian Pistachio Nut (Pistacia vera L.) Dehydration in Natural and Industrial Conditions

Authors: Hamid Tavakolipour, Mohsen Mokhtarian, Ahmad Kalbasi Ashtari

Abstract:

In this study, the effect of various drying methods (sun drying, shade drying and industrial drying) on final moisture content, shell splitting degree, shrinkage and color change were studied. Sun drying resulted higher degree of pistachio nuts shell splitting on pistachio nuts relative other drying methods. The ANOVA results showed that the different drying methods did not significantly effects on color change of dried pistachio nut. The results illustrated that pistachio nut dried by industrial drying had the lowest moisture content. After the end of drying process, initially, the experimental drying data were fitted with five famous drying models namely Newton, Page, Silva et al., Peleg and Henderson and Pabis. The results indicated that Peleg and Page models gave better results compared with other models to monitor the moisture ratio’s pistachio nut in industrial drying and open sun (or shade drying) methods, respectively.

Keywords: industrial drying, pistachio, quality properties, traditional drying

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17467 On-Line Super Critical Fluid Extraction, Supercritical Fluid Chromatography, Mass Spectrometry, a Technique in Pharmaceutical Analysis

Authors: Narayana Murthy Akurathi, Vijaya Lakshmi Marella

Abstract:

The literature is reviewed with regard to online Super critical fluid extraction (SFE) coupled directly with supercritical fluid chromatography (SFC) -mass spectrometry that have typically more sensitive than conventional LC-MS/MS and GC-MS/MS. It is becoming increasingly interesting to use on-line techniques that combine sample preparation, separation and detection in one analytical set up. This provides less human intervention, uses small amount of sample and organic solvent and yields enhanced analyte enrichment in a shorter time. The sample extraction is performed under light shielding and anaerobic conditions, preventing the degradation of thermo labile analytes. It may be able to analyze compounds over a wide polarity range as SFC generally uses carbon dioxide which was collected as a by-product of other chemical reactions or is collected from the atmosphere as it contributes no new chemicals to the environment. The diffusion of solutes in supercritical fluids is about ten times greater than that in liquids and about three times less than in gases which results in a decrease in resistance to mass transfer in the column and allows for fast high resolution separations. The drawback of SFC when using carbon dioxide as mobile phase is that the direct introduction of water samples poses a series of problems, water must therefore be eliminated before it reaches the analytical column. Hundreds of compounds analysed simultaneously by simple enclosing in an extraction vessel. This is mainly applicable for pharmaceutical industry where it can analyse fatty acids and phospholipids that have many analogues as their UV spectrum is very similar, trace additives in polymers, cleaning validation can be conducted by putting swab sample in an extraction vessel, analysing hundreds of pesticides with good resolution.

Keywords: super critical fluid extraction (SFE), super critical fluid chromatography (SFC), LCMS/MS, GCMS/MS

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17466 Improve Closed Loop Performance and Control Signal Using Evolutionary Algorithms Based PID Controller

Authors: Mehdi Shahbazian, Alireza Aarabi, Mohsen Hadiyan

Abstract:

Proportional-Integral-Derivative (PID) controllers are the most widely used controllers in industry because of its simplicity and robustness. Different values of PID parameters make different step response, so an increasing amount of literature is devoted to proper tuning of PID controllers. The problem merits further investigation as traditional tuning methods make large control signal that can damages the system but using evolutionary algorithms based tuning methods improve the control signal and closed loop performance. In this paper three tuning methods for PID controllers have been studied namely Ziegler and Nichols, which is traditional tuning method and evolutionary algorithms based tuning methods, that are, Genetic algorithm and particle swarm optimization. To examine the validity of PSO and GA tuning methods a comparative analysis of DC motor plant is studied. Simulation results reveal that evolutionary algorithms based tuning method have improved control signal amplitude and quality factors of the closed loop system such as rise time, integral absolute error (IAE) and maximum overshoot.

Keywords: evolutionary algorithm, genetic algorithm, particle swarm optimization, PID controller

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17465 Gas Flow, Time, Distance Dynamic Modelling

Authors: A. Abdul-Ameer

Abstract:

The equations governing the distance, pressure- volume flow relationships for the pipeline transportation of gaseous mixtures, are considered. A derivation based on differential calculus, for an element of this system model, is addressed. Solutions, yielding the input- output response following pressure changes, are reviewed. The technical problems associated with these analytical results are identified. Procedures resolving these difficulties providing thereby an attractive, simple, analysis route are outlined. Computed responses, validating thereby calculated predictions, are presented.

Keywords: pressure, distance, flow, dissipation, models

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17464 A Stable Method for Determination of the Number of Independent Components

Authors: Yuyan Yi, Jingyi Zheng, Nedret Billor

Abstract:

Independent component analysis (ICA) is one of the most commonly used blind source separation (BSS) techniques for signal pre-processing, such as noise reduction and feature extraction. The main parameter in the ICA method is the number of independent components (IC). Although there have been several methods for the determination of the number of ICs, it has not been given sufficient attentionto this important parameter. In this study, wereview the mostused methods fordetermining the number of ICs and providetheir advantages and disadvantages. Further, wepropose an improved version of column-wise ICAByBlock method for the determination of the number of ICs.To assess the performance of the proposed method, we compare the column-wise ICAbyBlock with several existing methods through different ICA methods by using simulated and real signal data. Results show that the proposed column-wise ICAbyBlock is an effective and stable method for determining the optimal number of components in ICA. This method is simple, and results can be demonstrated intuitively with good visualizations.

Keywords: independent component analysis, optimal number, column-wise, correlation coefficient, cross-validation, ICAByblock

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17463 Investigation of Resilient Circles in Local Community and Industry: Waju-Traditional Culture in Japan and Modern Technology Application

Authors: R. Ueda

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Today global society is seeking resilient partnership in local organizations and individuals, which realizes multi-stakeholders relationship. Although it is proposed by modern global framework of sustainable development, it is conceivable that such affiliation can be found out in the traditional local community in Japan, and that traditional spirit is tacitly sustaining in modern context of disaster mitigation in society and economy. Then this research is aiming to clarify and analyze implication for the global world by actual case studies. Regional and urban resilience is the ability of multi-stakeholders to cooperate flexibly and to adapt in response to changes in the circumstances caused by disasters, but there are various conflicts affecting coordination of disaster relief measures. These conflicts arise not only from a lack of communication and an insufficient network, but also from the difficulty to jointly draw common context from fragmented information. This is because of the weakness of our modern engineering which focuses on maintenance and restoration of individual systems. Here local ‘circles’ holistically includes local community and interacts periodically. Focusing on examples of resilient organizations and wisdom created in communities, what can be seen throughout history is a virtuous cycle where the information and the knowledge are structured, the context to be adapted becomes clear, and an adaptation at a higher level is made possible, by which the collaboration between organizations is deepened and expanded. And the wisdom of a solid and autonomous disaster prevention formed by the historical community called’ Waju’ – an area surrounded by circle embankment to protect the settlement from flood – lives on in government efforts of the coastal industrial island of today. Industrial company there collaborates to create a circle including common evacuation space, road access improvement and infrastructure recovery. These days, people here adopts new interface technology. Large-scale AR- Augmented Reality for more than hundred people is expressing detailed hazard by tsunami and liquefaction. Common experiences of the major disaster space and circle of mutual discussion are enforcing resilience. Collaboration spirit lies in the center of circle. A consistent key point is a virtuous cycle where the information and the knowledge are structured, the context to be adapted becomes clear, and an adaptation at a higher level is made possible, by which the collaboration between organizations is deepened and expanded. This writer believes that both self-governing human organizations and the societal implementation of technical systems are necessary. Infrastructure should be autonomously instituted by associations of companies and other entities in industrial areas for working closely with local governments. To develop advanced disaster prevention and multi-stakeholder collaboration, partnerships among industry, government, academia and citizens are important.

Keywords: industrial recovery, multi-sakeholders, traditional culture, user experience, Waju

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17462 Exploring Gender-Base Salary Disparities and Equities Among University Presidents

Authors: Daniel Barkley, Jianyi Zhu

Abstract:

This study investigates base salary differentials and gender equity among university presidents across 427 U.S. colleges and universities. While endowments typically do not directly determine university presidents' base salaries, our analysis reveals a noteworthy pattern: endowments explain more than half of the variance in female university presidents' base salaries, compared to a mere 0.69 percent for males. Moreover, female presidents' base salaries tend to rise much faster than male base salaries with increasing university endowments. This disparate impact of endowments on base salaries implies an endowment threshold for achieving gender pay equity. We develop an analytical model predicting an endowment threshold for achieving gender equality and empirically estimate this equity threshold using data from over 427 institutions. Surprisingly, the fields of science and athletics have emerged as sources of gender-neutral base pay. Both male and female university presidents with STEM backgrounds command higher base salaries than those without such qualifications. Additionally, presidents of universities affiliated with Power 5 conferences consistently receive higher base salaries regardless of gender. Consistent with the theory of human capital accumulation, the duration of the university presidency incrementally raises base salaries for both genders but at a diminishing rate. Curiously, prior administrative leadership experience as a vice president, provost, dean, or department chair does not significantly influence base salaries for either gender. By providing empirical evidence and analytical models predicting an endowment threshold for achieving gender equality in base salaries, the study offers valuable insights for policymakers, university administrators, and other stakeholders. These findings hold crucial policy implications, informing strategies to promote gender equality in executive compensation within higher education institutions.

Keywords: higher education, endowments, base salaries, university presidents

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17461 Exploring Antimicrobial Resistance in the Lung Microbial Community Using Unsupervised Machine Learning

Authors: Camilo Cerda Sarabia, Fernanda Bravo Cornejo, Diego Santibanez Oyarce, Hugo Osses Prado, Esteban Gómez Terán, Belén Diaz Diaz, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

Abstract:

Antimicrobial resistance (AMR) represents a significant and rapidly escalating global health threat. Projections estimate that by 2050, AMR infections could claim up to 10 million lives annually. Respiratory infections, in particular, pose a severe risk not only to individual patients but also to the broader public health system. Despite the alarming rise in resistant respiratory infections, AMR within the lung microbiome (microbial community) remains underexplored and poorly characterized. The lungs, as a complex and dynamic microbial environment, host diverse communities of microorganisms whose interactions and resistance mechanisms are not fully understood. Unlike studies that focus on individual genomes, analyzing the entire microbiome provides a comprehensive perspective on microbial interactions, resistance gene transfer, and community dynamics, which are crucial for understanding AMR. However, this holistic approach introduces significant computational challenges and exposes the limitations of traditional analytical methods such as the difficulty of identifying the AMR. Machine learning has emerged as a powerful tool to overcome these challenges, offering the ability to analyze complex genomic data and uncover novel insights into AMR that might be overlooked by conventional approaches. This study investigates microbial resistance within the lung microbiome using unsupervised machine learning approaches to uncover resistance patterns and potential clinical associations. it downloaded and selected lung microbiome data from HumanMetagenomeDB based on metadata characteristics such as relevant clinical information, patient demographics, environmental factors, and sample collection methods. The metadata was further complemented by details on antibiotic usage, disease status, and other relevant descriptions. The sequencing data underwent stringent quality control, followed by a functional profiling focus on identifying resistance genes through specialized databases like Antibiotic Resistance Database (CARD) which contains sequences of AMR gene sequence and resistance profiles. Subsequent analyses employed unsupervised machine learning techniques to unravel the structure and diversity of resistomes in the microbial community. Some of the methods employed were clustering methods such as K-Means and Hierarchical Clustering enabled the identification of sample groups based on their resistance gene profiles. The work was implemented in python, leveraging a range of libraries such as biopython for biological sequence manipulation, NumPy for numerical operations, Scikit-learn for machine learning, Matplotlib for data visualization and Pandas for data manipulation. The findings from this study provide insights into the distribution and dynamics of antimicrobial resistance within the lung microbiome. By leveraging unsupervised machine learning, we identified novel resistance patterns and potential drivers within the microbial community.

Keywords: antibiotic resistance, microbial community, unsupervised machine learning., sequences of AMR gene

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17460 Simultaneous Determination of Six Characterizing/Quality Parameters of Biodiesels via 1H NMR and Multivariate Calibration

Authors: Gustavo G. Shimamoto, Matthieu Tubino

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The characterization and the quality of biodiesel samples are checked by determining several parameters. Considering a large number of analysis to be performed, as well as the disadvantages of the use of toxic solvents and waste generation, multivariate calibration is suggested to reduce the number of tests. In this work, hydrogen nuclear magnetic resonance (1H NMR) spectra were used to build multivariate models, from partial least squares (PLS) regression, in order to determine simultaneously six important characterizing and/or quality parameters of biodiesels: density at 20 ºC, kinematic viscosity at 40 ºC, iodine value, acid number, oxidative stability, and water content. Biodiesels from twelve different oils sources were used in this study: babassu, brown flaxseed, canola, corn, cottonseed, macauba almond, microalgae, palm kernel, residual frying, sesame, soybean, and sunflower. 1H NMR reflects the structures of the compounds present in biodiesel samples and showed suitable correlations with the six parameters. The PLS models were constructed with latent variables between 5 and 7, the obtained values of r(cal) and r(val) were greater than 0.994 and 0.989, respectively. In addition, the models were considered suitable to predict all the six parameters for external samples, taking into account the analytical speed to perform it. Thus, the alliance between 1H NMR and PLS showed to be appropriate to characterize and evaluate the quality of biodiesels, reducing significantly analysis time, the consumption of reagents/solvents, and waste generation. Therefore, the proposed methods can be considered to adhere to the principles of green chemistry.

Keywords: biodiesel, multivariate calibration, nuclear magnetic resonance, quality parameters

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17459 Effectiveness of Technology Enhanced Learning in Orthodontic Teaching

Authors: Mohammed Shaath

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Aims Technological advancements in teaching and learning have made significant improvements over the past decade and have been incorporated in institutions to aid the learner’s experience. This review aims to assess whether Technology Enhanced Learning (TEL) pedagogy is more effective at improving students’ attitude and knowledge retention in orthodontic training than traditional methods. Methodology The searches comprised Systematic Reviews (SRs) related to the comparison of TEL and traditional teaching methods from the following databases: PubMed, SCOPUS, Medline, and Embase. One researcher performed the screening, data extraction, and analysis and assessed the risk of bias and quality using A Measurement Tool to Assess Systematic Reviews 2 (AMSTAR-2). Kirkpatrick’s 4-level evaluation model was used to evaluate the educational values. Results A sum of 34 SRs was identified after the removal of duplications and irrelevant SRs; 4 fit the inclusion criteria. On Level 1, students showed positivity to TEL methods, although acknowledging that the harder the platforms to use, the less favourable. Nonetheless, the students still showed high levels of acceptability. Level 2 showed there is no significant overall advantage of increased knowledge when it comes to TEL methods. One SR showed that certain aspects of study within orthodontics deliver a statistical improvement with TEL. Level 3 was the least reported on. Results showed that if left without time restrictions, TEL methods may be advantageous. Level 4 shows that both methods are equally as effective, but TEL has the potential to overtake traditional methods in the future as a form of active, student-centered approach. Conclusion TEL has a high level of acceptability and potential to improve learning in orthodontics. Current reviews have potential to be improved, but the biggest aspect that needs to be addressed is the primary study, which shows a lower level of evidence and heterogeneity in their results. As it stands, the replacement of traditional methods with TEL cannot be fully supported in an evidence-based manner. The potential of TEL methods has been recognized and is already starting to show some evidence of the ability to be more effective in some aspects of learning to cater for a more technology savvy generation.

Keywords: TEL, orthodontic, teaching, traditional

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17458 Management of Diabetics on Hemodialysis

Authors: Souheila Zemmouchi

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Introduction: Diabetes is currently the leading cause of end-stage chronic kidney disease and dialysis, so it adds additional complexity to the management of chronic hemodialysis patients. These patients are extremely fragile because of their multiple cardiovascular and metabolic comorbidities. Clear and complete description of the experience: the management of a diabetic on hemodialysis is particularly difficult due to frequent hypoglycaemia and significant inter and perdialyticglycemic variability that is difficult to predict. The aim of our study is to describe the clinical-biological profile and to assess the cardiovascular risk of diabetics undergoing chronic hemodialysis, and compare them with non-diabetic hemodialysis patients. Methods: This cross-sectional, descriptive, and analytical study was carried out between January 01 and December 31, 2018, involving 309 hemodialysis patients spread over 4 centersThe data were collected prospectively then compiled and analyzed by the SPSS Version 10 software The FRAMINGHAM RISK SCORE has been used to assess cardiovascular risk in all hemodialysis patients Results: The survey involved 309 hemodialysis patients, including 83 diabetics, for a prevalence of 27% The average age 53 ± 10.2 years. The sex ratio is 1.5. 50% of diabetic hemodialysis patients retained residual diuresis against 32% in non-diabetics. In the group of diabetics, we noted more hypertension (70% versus 38% non-diabetics P 0.004), more intradialytichypoglycemia (15% versus 3% non-diabetics P 0.007), initially, vascular exhaustion was found in 4 diabetics versus 2 non-diabetics. 70% of diabetics with anuria had postdialytichyperglycemia. The study found a statistically significant difference between the different levels of cardiovascular risk according to the diabetic status. Conclusion: There are many challenges in the management of diabetics on hemodialysis, both to optimize glycemic control according to an individualized target and to coordinate comprehensive and effective care.

Keywords: hemodialysis, diabetes, chronic renal failure, glycemic control

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17457 Microchip-Integrated Computational Models for Studying Gait and Motor Control Deficits in Autism

Authors: Noah Odion, Honest Jimu, Blessing Atinuke Afuape

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Introduction: Motor control and gait abnormalities are commonly observed in individuals with autism spectrum disorder (ASD), affecting their mobility and coordination. Understanding the underlying neurological and biomechanical factors is essential for designing effective interventions. This study focuses on developing microchip-integrated wearable devices to capture real-time movement data from individuals with autism. By applying computational models to the collected data, we aim to analyze motor control patterns and gait abnormalities, bridging a crucial knowledge gap in autism-related motor dysfunction. Methods: We designed microchip-enabled wearable devices capable of capturing precise kinematic data, including joint angles, acceleration, and velocity during movement. A cross-sectional study was conducted on individuals with ASD and a control group to collect comparative data. Computational modelling was applied using machine learning algorithms to analyse motor control patterns, focusing on gait variability, balance, and coordination. Finite element models were also used to simulate muscle and joint dynamics. The study employed descriptive and analytical methods to interpret the motor data. Results: The wearable devices effectively captured detailed movement data, revealing significant gait variability in the ASD group. For example, gait cycle time was 25% longer, and stride length was reduced by 15% compared to the control group. Motor control analysis showed a 30% reduction in balance stability in individuals with autism. Computational models successfully predicted movement irregularities and helped identify motor control deficits, particularly in the lower limbs. Conclusions: The integration of microchip-based wearable devices with computational models offers a powerful tool for diagnosing and treating motor control deficits in autism. These results have significant implications for patient care, providing objective data to guide personalized therapeutic interventions. The findings also contribute to the broader field of neuroscience by improving our understanding of the motor dysfunctions associated with ASD and other neurodevelopmental disorders.

Keywords: motor control, gait abnormalities, autism, wearable devices, microchips, computational modeling, kinematic analysis, neurodevelopmental disorders

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17456 Automatic and High Precise Modeling for System Optimization

Authors: Stephanie Chen, Mitja Echim, Christof Büskens

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To describe and propagate the behavior of a system mathematical models are formulated. Parameter identification is used to adapt the coefficients of the underlying laws of science. For complex systems this approach can be incomplete and hence imprecise and moreover too slow to be computed efficiently. Therefore, these models might be not applicable for the numerical optimization of real systems, since these techniques require numerous evaluations of the models. Moreover not all quantities necessary for the identification might be available and hence the system must be adapted manually. Therefore, an approach is described that generates models that overcome the before mentioned limitations by not focusing on physical laws, but on measured (sensor) data of real systems. The approach is more general since it generates models for every system detached from the scientific background. Additionally, this approach can be used in a more general sense, since it is able to automatically identify correlations in the data. The method can be classified as a multivariate data regression analysis. In contrast to many other data regression methods this variant is also able to identify correlations of products of variables and not only of single variables. This enables a far more precise and better representation of causal correlations. The basis and the explanation of this method come from an analytical background: the series expansion. Another advantage of this technique is the possibility of real-time adaptation of the generated models during operation. Herewith system changes due to aging, wear or perturbations from the environment can be taken into account, which is indispensable for realistic scenarios. Since these data driven models can be evaluated very efficiently and with high precision, they can be used in mathematical optimization algorithms that minimize a cost function, e.g. time, energy consumption, operational costs or a mixture of them, subject to additional constraints. The proposed method has successfully been tested in several complex applications and with strong industrial requirements. The generated models were able to simulate the given systems with an error in precision less than one percent. Moreover the automatic identification of the correlations was able to discover so far unknown relationships. To summarize the above mentioned approach is able to efficiently compute high precise and real-time-adaptive data-based models in different fields of industry. Combined with an effective mathematical optimization algorithm like WORHP (We Optimize Really Huge Problems) several complex systems can now be represented by a high precision model to be optimized within the user wishes. The proposed methods will be illustrated with different examples.

Keywords: adaptive modeling, automatic identification of correlations, data based modeling, optimization

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17455 A Comparative Study of Deep Learning Methods for COVID-19 Detection

Authors: Aishrith Rao

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COVID 19 is a pandemic which has resulted in thousands of deaths around the world and a huge impact on the global economy. Testing is a huge issue as the test kits have limited availability and are expensive to manufacture. Using deep learning methods on radiology images in the detection of the coronavirus as these images contain information about the spread of the virus in the lungs is extremely economical and time-saving as it can be used in areas with a lack of testing facilities. This paper focuses on binary classification and multi-class classification of COVID 19 and other diseases such as pneumonia, tuberculosis, etc. Different deep learning methods such as VGG-19, COVID-Net, ResNET+ SVM, Deep CNN, DarkCovidnet, etc., have been used, and their accuracy has been compared using the Chest X-Ray dataset.

Keywords: deep learning, computer vision, radiology, COVID-19, ResNet, VGG-19, deep neural networks

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17454 Federal Bureau of Investigation Opposition to German Nationalist Organizations in the United States (1941-45)

Authors: Yaroslav Alexandrovich Levin

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In modern research on the history of the United States in World War II, it is quite popular to study the opposition of the American special services and, in particular, the Federal Bureau of Investigation (FBI) to various organizations of the German diasporas in new historical conditions. The appeal to traditional methods of historical research, comparative studies, and the principles of historicism will make it possible to more accurately trace the process of tightening the counterintelligence work of the Bureau and the close connection of concerns about the involvement of public organizations in the intelligence activities of the enemy. The broadcast of nationalist ideas by various communities of Germans under the auspices of their governments quickly attracted the attention of the FBI, which is in the process of consolidating its powers as the main US counterintelligence service. At the same time, the investigations and trials conducted by the John Edgar Hoover Department following these investigations often had an openly political color and increasingly consolidated the beginning of a political investigation in this service. This practice and its implementation ran into a tough contradiction between the legal norms of America, which proclaimed "democratic values," the right to freedom of speech, and the need to strengthen the internal security of the state and society in wartime. All these processes and the associated nuances and complexities are considered in specific examples of the work of federal agents against various pro-German organizations in the period 1941-45.

Keywords: World War II, internal security, countering extremism, counterintelligence, political investigation, FBI

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17453 Reviewing Privacy Preserving Distributed Data Mining

Authors: Sajjad Baghernezhad, Saeideh Baghernezhad

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Nowadays considering human involved in increasing data development some methods such as data mining to extract science are unavoidable. One of the discussions of data mining is inherent distribution of the data usually the bases creating or receiving such data belong to corporate or non-corporate persons and do not give their information freely to others. Yet there is no guarantee to enable someone to mine special data without entering in the owner’s privacy. Sending data and then gathering them by each vertical or horizontal software depends on the type of their preserving type and also executed to improve data privacy. In this study it was attempted to compare comprehensively preserving data methods; also general methods such as random data, coding and strong and weak points of each one are examined.

Keywords: data mining, distributed data mining, privacy protection, privacy preserving

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17452 Explanatory Variables for Crash Injury Risk Analysis

Authors: Guilhermina Torrao

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An extensive number of studies have been conducted to determine the factors which influence crash injury risk (CIR); however, uncertainties inherent to selected variables have been neglected. A review of existing literature is required to not only obtain an overview of the variables and measures but also ascertain the implications when comparing studies without a systematic view of variable taxonomy. Therefore, the aim of this literature review is to examine and report on peer-reviewed studies in the field of crash analysis and to understand the implications of broad variations in variable selection in CIR analysis. The objective of this study is to demonstrate the variance in variable selection and classification when modeling injury risk involving occupants of light vehicles by presenting an analytical review of the literature. Based on data collected from 64 journal publications reported over the past 21 years, the analytical review discusses the variables selected by each study across an organized list of predictors for CIR analysis and provides a better understanding of the contribution of accident and vehicle factors to injuries acquired by occupants of light vehicles. A cross-comparison analysis demonstrates that almost half the studies (48%) did not consider vehicle design specifications (e.g., vehicle weight), whereas, for those that did, the vehicle age/model year was the most selected explanatory variable used by 41% of the literature studies. For those studies that included speed risk factor in their analyses, the majority (64%) used the legal speed limit data as a ‘proxy’ of vehicle speed at the moment of a crash, imposing limitations for CIR analysis and modeling. Despite the proven efficiency of airbags in minimizing injury impact following a crash, only 22% of studies included airbag deployment data. A major contribution of this study is to highlight the uncertainty linked to explanatory variable selection and identify opportunities for improvements when performing future studies in the field of road injuries.

Keywords: crash, exploratory, injury, risk, variables, vehicle

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17451 Women’s Perceptions of DMPA-SC Self-Injection in Malawi

Authors: Mandayachepa C. Nyando, Lauren Suchman, Innocencia Mtalimanja, Address Malata, Tamanda Jumbe, Martha Kamanga, Peter Waiswa

Abstract:

Background: Subcutaneous depot medroxyprogesterone acetate (DMPA-SC) is a new innovation in contraceptive methods that allow users to inject themselves with a hormonal contraceptive in their own homes. Self-injection (SI) of DMPA-SC has the potential to improve the accessibility of family planning to women who want it and who are capable of injecting themselves. Malawi started implementing this new innovation in 2018. SI was incorporated into the DMPA-SC delivery strategy from its outset. Methodology: This study involved two districts in Malawi where DMPA-SC SI was rolled out: Mulanje and Ntchisi. We used a qualitative cross-sectional study design where 60 in-depth interviews were conducted with women of reproductive age group stratified as 15-45 age band. These included women who were SI users, non-users, and any woman who was on any contraceptive methods. The women participants were tape-recorded, and data were transcribed and then analysed using Dedoose software, where themes were categorised into mother and child themes. Results: Women perceived DMPA SC SI as uniquely private, convenient, and less painful when self-injected. In terms of privacy, women in Mulanje and Ntchisi especially appreciated that self-injecting allowed them to use covertly from partners. Some men do not allow their spouses to use modern contraceptive methods; hence women prefer to use them covertly. “… but I first reach out to men because the strongest power is answered by men (MJ015).” In addition, women reported that SI offers privacy from family/community and less contact with healthcare providers. These aspects of privacy were especially valued in areas where there is a high degree of mistrust around family planning and among those who feel judged or antagonized purchasing contraception, such as young unmarried women. Women also valued the convenience SI provided in terms of their ability to save time by injecting themselves at home rather than visiting a healthcare provider and having more reliable access to contraception, particularly in the face of stockouts. SI allows for stocking up on doses to accommodate shifting work schedules in case of future stockouts or hard times, such as the period of COVID-19, where there was a limitation in the movement of the people. Conclusion: Our findings suggest that SI may meet the needs of many women in Malawi as long as the barriers are eliminated. The barriers women mentioned include fear of self-inject and proper storage of the DMPA SC SI, and these barriers can be eliminated by proper training. The findings also set the scene for policy revision and direction at a national level and integrate the approach with national family planning strategies in Malawi. Findings provide insights that may guide future implementation strategies, strengthen non-clinic family planning access programs and stimulate continued research.

Keywords: family planning, Malawi, Sayana press, self-injection

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17450 Method of Nursing Education: History Review

Authors: Cristina Maria Mendoza Sanchez, Maria Angeles Navarro Perán

Abstract:

Introduction: Nursing as a profession, from its initial formation and after its development in practice, has been built and identified mainly from its technical competence and professionalization within the positivist approach of the XIX century that provides a conception of the disease built on the basis of to the biomedical paradigm, where the care provided is more focused on the physiological processes and the disease than on the suffering person understood as a whole. The main issue that is in need of study here is a review of the nursing profession's history to get to know how the nursing profession was before the XIX century. It is unclear if there were organizations or people with knowledge about looking after others or if many people survived by chance. The holistic care, in which the appearance of the disease directly affects all its dimensions: physical, emotional, cognitive, social and spiritual. It is not a concept from the 21st century. It is common practice, most probably since established life in this world, with the final purpose of covering all these perspectives through quality care. Objective: In this paper, we describe and analyze the history of education in nursing learning in terms of reviewing and analysing theoretical foundations of clinical teaching and learning in nursing, with the final purpose of determining and describing the development of the nursing profession along the history. Method: We have done a descriptive systematic review study, doing a systematically searched of manuscripts and articles in the following health science databases: Pubmed, Scopus, Web of Science, Temperamentvm and CINAHL. The selection of articles has been made according to PRISMA criteria, doing a critical reading of the full text using the CASPe method. A compliment to this, we have read a range of historical and contemporary sources to support the review, such as manuals of Florence Nightingale and John of God as primary manuscripts to establish the origin of modern nursing and her professionalization. We have considered and applied ethical considerations of data processing. Results: After applying inclusion and exclusion criteria in our search, in Pubmed, Scopus, Web of Science, Temperamentvm and CINAHL, we have obtained 51 research articles. We have analyzed them in such a way that we have distinguished them by year of publication and the type of study. With the articles obtained, we can see the importance of our background as a profession before modern times in public health and as a review of our past to face challenges in the near future. Discussion: The important influence of key figures other than Nightingale has been overlooked and it emerges that nursing management and development of the professional body has a longer and more complex history than is generally accepted. Conclusions: There is a paucity of studies on the subject of the review to be able to extract very precise evidence and recommendations about nursing before modern times. But even so, as more representative data, an increase in research about nursing history has been observed. In light of the aspects analyzed, the need for new research in the history of nursing emerges from this perspective; in order to germinate studies of the historical construction of care before the XIX century and theories created then. We can assure that pieces of knowledge and ways of care were taught before the XIX century, but they were not called theories, as these concepts were created in modern times.

Keywords: nursing history, nursing theory, Saint John of God, Florence Nightingale, learning, nursing education

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17449 Settlement of Group of Stone Columns

Authors: Adel Hanna, Tahar Ayadat, Mohammad Etezad, Cyrille Cros

Abstract:

A number of theoretical methods have been developed over the years to calculate the amount settlement of the soil reinforced with group of stone columns. The results deduced from these methods sometimes show large disagreement with the experimental observations. The reason of this divergence might be due to the fact that many of the previous methods assumed the deform shape of the columns which is different with the actual case. A new method to calculate settlement of the ground reinforced with group of stone columns is presented in this paper which overcomes the restrictions made by previous theories. This method is based on results deduced from numerical modeling. Results obtained from the model are validated.

Keywords: stone columns, group, soft soil, settlement, prediction

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17448 A Survey of Sentiment Analysis Based on Deep Learning

Authors: Pingping Lin, Xudong Luo, Yifan Fan

Abstract:

Sentiment analysis is a very active research topic. Every day, Facebook, Twitter, Weibo, and other social media, as well as significant e-commerce websites, generate a massive amount of comments, which can be used to analyse peoples opinions or emotions. The existing methods for sentiment analysis are based mainly on sentiment dictionaries, machine learning, and deep learning. The first two kinds of methods rely on heavily sentiment dictionaries or large amounts of labelled data. The third one overcomes these two problems. So, in this paper, we focus on the third one. Specifically, we survey various sentiment analysis methods based on convolutional neural network, recurrent neural network, long short-term memory, deep neural network, deep belief network, and memory network. We compare their futures, advantages, and disadvantages. Also, we point out the main problems of these methods, which may be worthy of careful studies in the future. Finally, we also examine the application of deep learning in multimodal sentiment analysis and aspect-level sentiment analysis.

Keywords: document analysis, deep learning, multimodal sentiment analysis, natural language processing

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17447 The Evolving Changes of Religious Behavior: an Exploratory Study on Guanyin Worship of Contemporary Chinese Societies

Authors: Judith Sue Hwa Joo

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Guanyin (Avalokiteśvara in Sanskrit), the Bodhisattva of Mercy and Compassion, is the most widely worshipped Buddhist Divinity in Chinese societies and is also believed by more than half of Asian populations across various countries. The most overwhelming reason for the popularity of Guanyin in Chinese societies is, according to the Lotus Sutra, that Guanyin would apperceive voices of those suffering from immense afflictions and troubles, and liberate them upon crying for his/her holy name with wholeheartedness. Its pervasive social influence has spanned more than two thousand years and is still deeply affecting the lives of most Chinese people. This study aimed to investigate whether Guanyin Worship has evolved and changed in modern Chinese societies across the Taiwan Strait. Taiwan and China, albeit having the same language and culture, have been territorially divided and governed by two different political regimes for over 70 years. It would be scientifically intriguing to unveil any substantial changes in religious behaviors in the context of Guanyin Worship. A comprehensive anonymous questionnaire survey in Chinese communities was conducted from October 2017 to May 2019 across various countries, mostly in China, Taiwan, and Hong Kong areas. Since the religious survey is officially prohibited in China, the study was difficult and could only be exercised by means of snowball sampling. Demographic data (age, sex, education, religious belief) were registered and Guanyin’s salvation functions under various confronting situations were investigated. Psychological dimensions of religious belief in Guanyin were probed in terms of the worship experience, the willingness of veneration, and egoistic or altruistic ideations. A literature review on documented functional attributes was carried out in parallel for comparison analyses with traditional roles. Effective 1123 out of 1139 samples were obtained. Statistical analysis revealed that Guanyin Worship is still commonly practiced and deeply rooted in the hearts of all Chinese people regardless of gender, age, education, and residential area, even though they may not enshrine Guanyin at home nowadays. The conventional roles of Guanyin Bodhisattva are still valid and best satisfy the real interests of lifestyles in modern times. When comparing the traditional Buddhist Sutra and the documented literature, the divine power of modern Guanyin has notably empowered to recover, protect and transform fetal and infant spirits due to the sexual liberation, increased abortion rate, gender awakening and enhanced female autonomy in the reproductive decision. However, the One-Child policy may have critically impacted the trajectory of Guanyin Worship so that people in China prevail over those in Taiwan praying for aborted lives or premature deaths. Furthermore, particularly in Hong Kong and Macao, Guanyin not only serves as the sea guardian for the fishermen but also additional services a new function as the God of Wealth. The divine powers and salvation functions of Guanyin are indeed evolving and expanding to comply with the modern psychosocial, cultural and societal needs. This study sheds light on the modernization process of the two-thousand-year-old Guanyin Worship of contemporary Chinese societies.

Keywords: Buddhism, Guanyin, religious behavior, salvation function

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17446 Comparison of Heuristic Methods for Solving Traveling Salesman Problem

Authors: Regita P. Permata, Ulfa S. Nuraini

Abstract:

Traveling Salesman Problem (TSP) is the most studied problem in combinatorial optimization. In simple language, TSP can be described as a problem of finding a minimum distance tour to a city, starting and ending in the same city, and exactly visiting another city. In product distribution, companies often get problems in determining the minimum distance that affects the time allocation. In this research, we aim to apply TSP heuristic methods to simulate nodes as city coordinates in product distribution. The heuristics used are sub tour reversal, nearest neighbor, farthest insertion, cheapest insertion, nearest insertion, and arbitrary insertion. We have done simulation nodes using Euclidean distances to compare the number of cities and processing time, thus we get optimum heuristic method. The results show that the optimum heuristic methods are farthest insertion and nearest insertion. These two methods can be recommended to solve product distribution problems in certain companies.

Keywords: Euclidean, heuristics, simulation, TSP

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17445 Colloquialism in Audiovisual Translation: English Subtitling of the Lebanese Film Capernaum as a Case Study

Authors: Fatima Saab

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This paper attempts to study colloquialism in audio-visual translation, with particular emphasis given to investigating the difficulties and challenges encountered by subtitlers in translating Lebanese colloquial into English. To achieve the main objectives of this study, ample and thorough cultural and translational analysis of examples drawn from the subtitled movie Capernaum are presented in order to identify the strategies used to overcome cultural barriers and differences and to show the process of decision-making by the translator. Also, special attention is given to explain the technicalities in translating subtitles and how they affect the translation process. The research is a descriptive analytical study whereby the writer sets out empirical observations, consisting of descriptive and analytical examination of the difficulties and problems associated with translating Arabic colloquialisms, specifically Lebanese, into English in the subtitled film, Capernaum. The research methodology utilizes a qualitative approach to group the selected data into the subtitling strategies presented by Gottlieb under the domesticating or foreignizing strategies according to Venuti's Model. It is shown that producing the same meanings to a foreign audience is not an easy task. The background of cultural elements and the stories that make up the history and mindset of the Lebanese and Arabic peoples leads to the use of the transfer and paraphrase methodologies most of the time (81% of the sample used for analysis). The research shows that translating and subtitling colloquialism needs special skills by the translators to overcome the challenges imposed by the limited presentation space as well as cultural differences. Translation of colloquial Arabic/Lebanese can be achieved to a certain extent and delivering the meaning and effect of the source language culture is accomplished in as much as the translator investigates and relates to the target culture.

Keywords: Lebanese colloquial, audio-visual translation, subtitling, Capernaum

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17444 Consecration from the Margins: El Anatsui in Venice and the Turbine Hall

Authors: Jonathan Adeyemi

Abstract:

Context: This study focuses on El Anatsui and his global acclaim in the art world despite his origins from the global artworld’s margins. It addresses the disparities in the treatment between Western and non-Western artists and questions whether Anatsui’s consecration is a result of exoticism or the growing consensus on decolonization. Research Aim: The aim of this study is to investigate how El Anatsui achieved global acclaim from the margins of the art world and determine if his consecration represents a mark of decolonization or the typical Western desire for exoticism. Methodology: The study utilizes a case study approach, literature analysis, and in-depth interviews. The artist, the organizers of the Venice Biennale, the relevant curators at Tate Modern London, and the October Gallery in London, and other galleries in Nigeria, which represent the artist were interviewed for data collection. Findings: The study seeks to determine the authenticity of the growing consensus on decolonization, inclusion, and diversity in the global artistic field. Preliminary findings show that domestic socio-economic and political factors debilitated the mechanisms for local validation in Nigeria, weakening the domestic foundation for international engagement. However, alternative systems of exhibition, especially in London and the USA contributed critically to providing the initial international visibility, which formed the foundation for his global acclaim. Out of the 21 winners of the Golden Lion for Lifetime Achievement since its inception at the 47th Venice Biennale in 1997, American artists have dominated with 10 recipients, 8 recipients from Europe, 2 recipients from Africa (2007 and 2015) and 1 from Asia. This aligns with Bourdieu’s concept of cultural and economic capital, which prevented Africa countries from participation until recently. Moreover, while the average age of recipients is 76 years, Anatsui received the award at the age of 71, while Malick Sidibé (Mali) was awarded at 72. Thus, the Venice Biennale award for El Anatsui incline more towards a commitment to decolonisation than exoticism. Theoretical Importance: This study contributes to the field by examining the dynamics of the art world's monopoly of legitimation and the role of national, ethnicity and cultural differences in the promotion of artists. It aims to challenge the Westernized hierarchy of valorization and consecration in the art world. The research supports Bourdieu’s artistic field theory, which emphasises the importance of cultural, economic and social capital in determining agents’ position and access to the field resources (symbolic capital). Bourdieu also established that dominated agents can change their position in the field’s hierarchy either by establishing or navigating alternative systems. Data Collection and Analysis Procedures: The opacity of art world’s operations places the required information within the purview of the insiders (agents). Thus, the study collects data through in-depth interviews with relevant and purposively selected individuals and organizations. The data was/will be analyzed using qualitative methods, such as thematic analysis and content analysis. The interpretive analytical approach adopted facilitated the construction of meanings that may not be apparent in the data or responses. Questions Addressed: The study addresses how El Anatsui achieved global acclaim despite being from the margins, whether his consecration represents decolonization or exoticism, and the extent to which the global artistic field embraces decolonization, inclusion, and diversity. Conclusion: The study will contribute to knowledge by providing insights into the extent of commitment to decolonization, inclusion, and diversity in the global artistic field. It also shed light on the mechanisms behind El Anatsui's rise to global acclaim and challenge Western-dominated artistic hierarchies.

Keywords: decolonisation, exorticism, artistic field, culture game

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