Search results for: cognitive and decision-making modeling

Authors: Torben Hansen, Lars Gronholdt, Alexander Josiassen, Anne Martensen

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Consumers often exhibit a bias in their knowledge; they often think that they know more or less than they do. The concept of 'knowledge over/underconfidence' (O/U) has in previous studies been used to investigate such knowledge bias. O/U appears as a combination of subjective and objective knowledge. Subjective knowledge relates to consumers’ perception of their knowledge, while objective knowledge relates to consumers’ absolute knowledge measured by objective standards. This separation leads to three scenarios: The consumer can either be knowledge calibrated (subjective and objective knowledge are similar), overconfident (subjective knowledge exceeds objective knowledge) or underconfident (objective knowledge exceeds subjective knowledge). Knowledge O/U is a highly useful concept in understanding consumer choice behavior. For example, knowledge overconfident individuals are likely to exaggerate their ability to make right choices, are more likely to opt out of necessary information search, spend less time to carry out a specific task than less knowledge confident consumers, and are more likely to show high financial trading volumes. Through the use of financial services as a case study, this study contributes to previous research by examining how consumer knowledge O/U affects two types of trust (broad-scope trust and narrow-scope trust) and consumer relationship satisfaction. Trust does not only concern consumer trust in individual companies (i.e., narrow.-scope confidence NST), but also concerns consumer confidence in the broader business context in which consumers plan and implement their behavior (i.e., broad scope trust, BST). NST is defined as "the expectation that the service provider can be relied on to deliver on its promises’, while BST is defined as ‘the expectation that companies within a particular business type can generally be relied on to deliver on their promises.’ This study expands our understanding of the interplay between consumer knowledge bias, consumer trust, and relationship marketing in two main ways: First, it is demonstrated that the more knowledge O/U a consumer becomes, the higher/lower NST and levels of relationship satisfaction will be. Second, it is demonstrated that BST has a negative moderating effect on the relationship between knowledge O/U and satisfaction, such that knowledge O/U has a higher positive/negative effect on relationship satisfaction when BST is low vs. high. The data for this study comprises 756 mutual fund investors. Trust is particularly important in consumers’ mutual fund behavior because mutual funds have important responsibilities in providing financial advice and in managing consumers’ funds.

Keywords: knowledge, cognitive bias, trust, customer-seller relationships, financial services

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Authors: Joana Beyer

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Background: Alzheimer’s disease (AD) is the predominant cause of dementia, characterized by progressive cognitive decline. Posterior cortical atrophy (PCA) is a less common variant of AD, primarily affecting younger individuals and presenting with visual, visuospatial, and visuoperceptual deficits, often leading to delayed diagnosis due to its atypical presentation. Case Presentation: We report the case of a 58-year-old woman referred to psychiatric services with a two-year history of progressive visuospatial decline, mild memory difficulties, and language impairments, notably anomia. Despite undergoing cataract and squint surgeries, her visual symptoms persisted, impacting her professional life as a music educator. The neuropsychological evaluation revealed profound visuoperceptual and visuospatial disturbances, with neuroimaging supporting a diagnosis of PCA. Treatment with Donepezil showed symptom improvement, highlighting the challenges and importance of early intervention and managing this atypical form of AD. Methods: The diagnostic process involved comprehensive physical, neuropsychological assessments, and neuroimaging, including MRI and F18 FDG PET CT, which demonstrated severe bilateral posterior cortical involvement. The case underscores the utility of these modalities in diagnosing PCA. Results: The initiation of Donepezil, an acetylcholinesterase inhibitor, resulted in symptom improvement, emphasizing the potential for AD treatments to benefit PCA patients. However, challenges in management, including treatment side effects and the necessity of multidisciplinary care, are discussed. Conclusion: This case highlights PCA's diagnostic challenges due to its atypical presentation and the broader implications for managing younger patients with early-onset dementia. It underscores the necessity for early recognition, comprehensive assessment, and tailored management strategies, including both pharmacological and non-pharmacological interventions, to improve patients' quality of life. Additionally, the case illustrates the need for expanding community memory services to accommodate younger patients with atypical forms of dementia, advocating for a more inclusive approach to dementia care.

Keywords: Alzheimer’s disease, posterior cortical atrophy, dementia, diagnosis, management, donepezil, early-onset dementia

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Authors: Zahid Ullah, Atlas Khan

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In today's data-driven world, the role of mathematics in bridging the gap between theory and applications is becoming increasingly vital. This abstract highlights the significance of mathematics as a powerful tool for analyzing, interpreting, and extracting meaningful insights from vast amounts of data. By integrating mathematical principles with real-world applications, researchers can unlock the full potential of data-driven decision-making processes. This abstract delves into the various ways mathematics acts as a bridge connecting theoretical frameworks to practical applications. It explores the utilization of mathematical models, algorithms, and statistical techniques to uncover hidden patterns, trends, and correlations within complex datasets. Furthermore, it investigates the role of mathematics in enhancing predictive modeling, optimization, and risk assessment methodologies for improved decision-making in diverse fields such as finance, healthcare, engineering, and social sciences. The abstract also emphasizes the need for interdisciplinary collaboration between mathematicians, statisticians, computer scientists, and domain experts to tackle the challenges posed by the data-driven landscape. By fostering synergies between these disciplines, novel approaches can be developed to address complex problems and make data-driven insights accessible and actionable. Moreover, this abstract underscores the importance of robust mathematical foundations for ensuring the reliability and validity of data analysis. Rigorous mathematical frameworks not only provide a solid basis for understanding and interpreting results but also contribute to the development of innovative methodologies and techniques. In summary, this abstract advocates for the pivotal role of mathematics in bridging theory and applications in a data-driven world. By harnessing mathematical principles, researchers can unlock the transformative potential of data analysis, paving the way for evidence-based decision-making, optimized processes, and innovative solutions to the challenges of our rapidly evolving society.

Keywords: mathematics, bridging theory and applications, data-driven world, mathematical models

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Authors: Sergio V Davalos, Alison L. Watkins

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User generated content (UGC) such as website post has data associated with it: time of the post, gender, location, type of device, and number of words. The text entered in user generated content (UGC) can provide a valuable dimension for analysis. In this research, each user post is treated as a collection of terms (words). In addition to the number of words per post, the frequency of each term is determined by post and by the sum of occurrences in all posts. This research focuses on one specific aspect of UGC: sentiment. Sentiment analysis (SA) was applied to the content (user posts) of two sets of political forums related to the US presidential elections for 2012 and 2016. Sentiment analysis results in deriving data from the text. This enables the subsequent application of data analytic methods. The SASA (SAIL/SAI Sentiment Analyzer) model was used for sentiment analysis. The application of SASA resulted with a sentiment score for each post. Based on the sentiment scores for the posts there are significant differences between the content and sentiment of the two sets for the 2012 and 2016 presidential election forums. In the 2012 forums, 38% of the forums started with positive sentiment and 16% with negative sentiment. In the 2016 forums, 29% started with positive sentiment and 15% with negative sentiment. There also were changes in sentiment over time. For both elections as the election got closer, the cumulative sentiment score became negative. The candidate who won each election was in the more posts than the losing candidates. In the case of Trump, there were more negative posts than Clinton’s highest number of posts which were positive. KNIME topic modeling was used to derive topics from the posts. There were also changes in topics and keyword emphasis over time. Initially, the political parties were the most referenced and as the election got closer the emphasis changed to the candidates. The performance of the SASA method proved to predict sentiment better than four other methods in Sentibench. The research resulted in deriving sentiment data from text. In combination with other data, the sentiment data provided insight and discovery about user sentiment in the US presidential elections for 2012 and 2016.

Keywords: sentiment analysis, text mining, user generated content, US presidential elections

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Authors: Zhang Qingzhong

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Though there exists an increasing number of research studies on the headquarters-subsidiary relationship, and within this context, there is a focus on subsidiaries' contributory role to multinational corporations (MNC), subsidiary autonomy, and the conditions under which autonomy exerts an effect on subsidiary performance still constitute a subject of debate in the literature. The objective of this research is to study the MNC subsidiary autonomy and performance relationship and the effect of subsidiary entrepreneurial orientation and trust on subsidiary autonomy in the China environment, a phenomenon that has not yet been studied. The research addresses the following three questions: (i) Is subsidiary autonomy associated with MNC subsidiary performance in the China environment? (ii) How do subsidiary entrepreneurship and its trust in headquarters affect the level of subsidiary autonomy and its relationship with subsidiary performance? (iii) Does subsidiary autonomy have a mediating effect on subsidiary performance with subsidiary’s entrepreneurship and trust in headquarters? In the present study, we have reviewed literature and conducted semi-structured interviews with multinational corporation (MNC) subsidiary senior executives in China. Building on our insights from the interviews and taking perspectives from four theories, namely the resource-based view (RBV), resource dependency theory, integration-responsiveness framework, and social exchange theory, as well as the extant articles on subsidiary autonomy, entrepreneurial orientation, trust, and subsidiary performance, we have developed a model and have explored the direct and mediating effects of subsidiary autonomy on subsidiary performance within the framework of the MNC. To test the model, we collected and analyzed data based on cross-industry two waves of an online survey from 102 subsidiaries of MNCs in China. We used structural equation modeling to test measurement, direct effect model, and conceptual framework with hypotheses. Our findings confirm that (a) subsidiary autonomy is positively related to subsidiary performance; (b) subsidiary entrepreneurial orientation is positively related to subsidiary autonomy; (c) subsidiary’s trust in headquarters has a positive effect on subsidiary autonomy; (d) subsidiary autonomy mediates the relationship between entrepreneurial orientation and subsidiary performance; (e) subsidiary autonomy mediates the relationship between trust and subsidiary performance. Our study highlights the important role of subsidiary autonomy in leveraging the resource of subsidiary entrepreneurial orientation and its trust relationship with headquarters to achieve high performance. We discuss the theoretical and managerial implications of the findings and propose directions for future research.

Keywords: subsidiary entrepreneurial orientation, trust, subsidiary autonomy, subsidiary performance

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Authors: María Dolores Caro, Eugenio M. Fedriani, Ángel F. Tenorio

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The transportation of dangerous goods by lorries throughout Europe must be done by using the roads conforming the European Road Transport Network. In this network, there are several parking areas where lorry drivers can park to rest according to the regulations. According to the "European Agreement concerning the International Carriage of Dangerous Goods by Road", parking areas where lorries transporting dangerous goods can park to rest, must follow several security stipulations to keep safe the rest of road users. At this respect, these lorries must be parked in adapted areas with strict and permanent surveillance measures. Moreover, drivers must satisfy several restrictions about resting and driving time. Under these facts, one may expect that there exist enough parking areas for the transport of this type of goods in order to obey the regulations prescribed by the European Union and its member countries. However, the already-existing parking areas are not sufficient to cover all the stops required by drivers transporting dangerous goods. Our main goal is, starting from the already-existing parking areas and the loading-and-unloading location, to provide an optimal answer to the following question: how many additional parking areas must be built and where must they be located to assure that lorry drivers can transport dangerous goods following all the stipulations about security and safety for their stops? The sense of the word “optimal” is due to the fact that we give a global solution for the location of parking areas throughout the whole European Road Transport Network, adjusting the number of additional areas to be as lower as possible. To do so, we have modeled the problem using graph theory since we are working with a road network. As nodes, we have considered the locations of each already-existing parking area, each loading-and-unloading area each road bifurcation. Each road connecting two nodes is considered as an edge in the graph whose weight corresponds to the distance between both nodes in the edge. By applying a new efficient algorithm, we have found the additional nodes for the network representing the new parking areas adapted for dangerous goods, under the fact that the distance between two parking areas must be less than or equal to 400 km.

Keywords: trans-european transport network, dangerous goods, parking areas, graph-based modeling

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Authors: M. Abuziarov

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The designed complex is intended for the numerical simulation of fast dynamic processes of interaction of heterogeneous environments susceptible to the significant formability. The main challenges in solving such problems are associated with the construction of the numerical meshes. Currently, there are two basic approaches to solve this problem. One is using of Lagrangian or Lagrangian Eulerian grid associated with the boundaries of media and the second is associated with the fixed Eulerian mesh, boundary cells of which cut boundaries of the environment medium and requires the calculation of these cut volumes. Both approaches require the complex grid generators and significant time for preparing the code’s data for simulation. In this codes these problems are solved using two grids, regular fixed and mobile local Euler Lagrange - Eulerian (ALE approach) accompanying the contact and free boundaries, the surfaces of shock waves and phase transitions, and other possible features of solutions, with mutual interpolation of integrated parameters. For modeling of both liquids and gases, and deformable solids the Godunov scheme of increased accuracy is used in Lagrangian - Eulerian variables, the same for the Euler equations and for the Euler- Cauchy, describing the deformation of the solid. The increased accuracy of the scheme is achieved by using 3D spatial time dependent solution of the discontinuity problem (3D space time dependent Riemann's Problem solver). The same solution is used to calculate the interaction at the liquid-solid surface (Fluid Structure Interaction problem). The codes does not require complex 3D mesh generators, only the surfaces of the calculating objects as the STL files created by means of engineering graphics are given by the user, which greatly simplifies the preparing the task and makes it convenient to use directly by the designer at the design stage. The results of the test solutions and applications related to the generation and extension of the detonation and shock waves, loading the constructions are presented.

Keywords: fluid structure interaction, Riemann's solver, Euler variables, 3D codes

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Authors: Tarek Duzan

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Fractures are a fundamental property of most reservoirs. Despite their abundance, they remain difficult to detect and quantify. The most effective characterization of fractured reservoirs is accomplished by integrating geological, geophysical, and engineering data. Detection of fractures and defines their relative contribution is crucial in the early stages of exploration and later in the production of any field. Because fractures could completely change our thoughts, efforts, and planning to produce a specific field properly. From the structural point of view, all reservoirs are fractured to some point of extent. North Gialo field is thought to be a naturally fractured reservoir to some extent. Historically, natural fractured reservoirs are more complicated in terms of their exploration and production efforts, and most geologists tend to deny the presence of fractures as an effective variable. Our aim in this paper is to determine the degree of fracturing, and consequently, our evaluation and planning can be done properly and efficiently from day one. The challenging part in this field is that there is no enough data and straightforward well testing that can let us completely comfortable with the idea of fracturing; however, we cannot ignore the fractures completely. Logging images, available well testing, and limited core studies are our tools in this stage to evaluate, model, and predict possible fracture effects in this reservoir. The aims of this study are both fundamental and practical—to improve the prediction and diagnosis of natural-fracture attributes in N. Gialo hydrocarbon reservoirs and accurately simulate their influence on production. Moreover, the production of this field comes from 2-phase plan; a self depletion of oil and then gas injection period for pressure maintenance and increasing ultimate recovery factor. Therefore, well understanding of fracturing network is essential before proceeding with the targeted plan. New analytical methods will lead to more realistic characterization of fractured and faulted reservoir rocks. These methods will produce data that can enhance well test and seismic interpretations, and that can readily be used in reservoir simulators.

Keywords: natural fracture, sandstone reservoir, geological, geophysical, and engineering data

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Authors: Sanaa Riaz

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Spirits occupy a world that simultaneously dwells between the divine and the earthly binary while speaking to all forces of nature, marginality, and extremity in between. This paper examines the conceptualizations, interactions with, and experience of spiritual beings in relation to the concept of self and social agency, defined as a continuum of cooperation leaving those involved with an enhanced or diminished perception of self-agency. To do justice to the diverse mythological and popular interpretations of spirit entities, ethnographic examples from Africa, in particular, will be used. An examination of the nature and role of spirits in Africa allows one to understand the ways in which colonial influences brought by Catholicism and Islam added to the pre-colonial repertoire and syncretic imaginations of spirits. A comprehensive framework to analyze spirits requires situating them as a cognitive configuration of humans to communicate with other humans and forces of nature to receive knowledge about the normative in social roles, conduct, and action. Understanding spirits also requires a rethinking of the concept of self as not one encapsulated in the individual but one representing positionalities in collective negotiations, adversity, and alliances. To use the postmodern understanding of identity as a far from a coherent collection of selves fluidly moving between and dialoguing with gravitational and contradictory social forces, benevolent and maleficent spirit forces represent how people make sense of their origin, physiological and ecological changes, subsistence, and political environment and social relations. A discussion on spirits requires examining the rituals and mediational forces and their performance that allow participants to tackle adversity, voicelessness and continue to work safely and morally for the collective good. Moreover, it is important to see the conceptualization of spirits in unison with sorcery and spirit possession, central to voodoo practices, also because they speak volumes about the experiences of slavery and marginalization. This paper has two motives: It presents a critical literature review of ethnographic accounts of spirit entities in African spiritual experiences to examine the ways in which spirits become mediums through which the self is conceptualized and asserted. Second, the paper highlights the ways in which spirits become a medium to represent political and sociocultural ambiguities and desires along a spectrum of social agencies, including joint agency, vicarious agency, and interfered agency.

Keywords: spirits, social agency, self, ethnographic case studies

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Authors: L. Guevara, Glória L. S., Corea E. E, A. Ramírez-Zamora M., Salinas-Martinez J. A., Angeles-Hernandez J. C.

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Mathematical models are useful for identifying the characteristics of sheep lactation curves to develop and implement improved strategies. However, the accuracy of these models is influenced by factors such as the recording regime, mainly the intervals between test day records (TDR). The current study aimed to evaluate the effect of different TDR intervals on the goodness of fit of the Wood model (WM) applied to dairy sheep lactations. A total of 4,494 weekly TDRs from 156 lactations of dairy crossbred sheep were analyzed. Three new databases were generated from the original weekly TDR data (7D), comprising intervals of 14(14D), 21(21D), and 28(28D) days. The parameters of WM were estimated using the “minpack.lm” package in the R software. The shape of the lactation curve (typical and atypical) was defined based on the WM parameters. The goodness of fit was evaluated using the mean square of prediction error (MSPE), Root of MSPE (RMSPE), Akaike´s Information Criterion (AIC), Bayesian´s Information Criterion (BIC), and the coefficient of correlation (r) between the actual and estimated total milk yield (TMY). WM showed an adequate estimate of TMY regardless of the TDR interval (P=0.21) and shape of the lactation curve (P=0.42). However, we found higher values of r for typical curves compared to atypical curves (0.9vs.0.74), with the highest values for the 28D interval (r=0.95). In the same way, we observed an overestimated peak yield (0.92vs.6.6 l) and underestimated time of peak yield (21.5vs.1.46) in atypical curves. The best values of RMSPE were observed for the 28D interval in both lactation curve shapes. The significant lowest values of AIC (P=0.001) and BIC (P=0.001) were shown by the 7D interval for typical and atypical curves. These results represent the first approach to define the adequate interval to record the regime of dairy sheep in Latin America and showed a better fitting for the Wood model using a 7D interval. However, it is possible to obtain good estimates of TMY using a 28D interval, which reduces the sampling frequency and would save additional costs to dairy sheep producers.

Keywords: gamma incomplete, ewes, shape curves, modeling

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Authors: Omid Giahi, Ebrahim Darvishi, Mahdi Akbarzadeh

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Introduction: Occupational low back pain (LBP) is one of the most prevalent work-related musculoskeletal disorders in which a lot of risk factors are involved that. The present study focuses on the relation between personal, psycho-social and occupational risk factors and LBP severity in industrial workers. Materials and Methods: This research was a case-control study which was conducted in Kurdistan province. 100 workers (Mean Age ± SD of 39.9 ± 10.45) with LBP were selected as the case group, and 100 workers (Mean Age ± SD of 37.2 ± 8.5) without LBP were assigned into the control group. All participants were selected from various industrial units, and they had similar occupational conditions. The required data including demographic information (BMI, smoking, alcohol, and family history), occupational (posture, mental workload (MWL), force, vibration and repetition), and psychosocial factors (stress, occupational satisfaction and security) of the participants were collected via consultation with occupational medicine specialists, interview, and the related questionnaires and also the NASA-TLX software and REBA worksheet. Chi-square test, logistic regression and structural equation modeling (SEM) were used to analyze the data. For analysis of data, IBM Statistics SPSS 24 and Mplus6 software have been used. Results: 114 (77%) of the individuals were male and 86 were (23%) female. Mean Career length of the Case Group and Control Group were 10.90 ± 5.92, 9.22 ± 4.24, respectively. The statistical analysis of the data revealed that there was a significant correlation between the Posture, Smoking, Stress, Satisfaction, and MWL with occupational LBP. The odds ratios (95% confidence intervals) derived from a logistic regression model were 2.7 (1.27-2.24) and 2.5 (2.26-5.17) and 3.22 (2.47-3.24) for Stress, MWL, and Posture, respectively. Also, the SEM analysis of the personal, psycho-social and occupational factors with LBP revealed that there was a significant correlation. Conclusion: All three broad categories of risk factors simultaneously increase the risk of occupational LBP in the workplace. But, the risks of Posture, Stress, and MWL have a major role in LBP severity. Therefore, prevention strategies for persons in jobs with high risks for LBP are required to decrease the risk of occupational LBP.

Keywords: industrial workers occupational, low back pain, occupational risk factors, psychosocial factors

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Authors: Abdulaziz F. Ettir, Ghait Bashir, Tarek S. Duzan

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A proper well planning is very vital to achieve any successful drilling program on the basis of preventing, overcome all drilling problems and minimize cost operations. Since the hydraulic system plays an active role during the drilling operations, that will lead to accelerate the drilling effort and lower the overall well cost. Likewise, an improperly designed hydraulic system can slow drill rate, fail to clean the hole of cuttings, and cause kicks. In most cases, common sense and commercially available computer programs are the only elements required to design the hydraulic system. Drilling optimization is the logical process of analyzing effects and interactions of drilling variables through applied drilling and hydraulic equations and mathematical modeling to achieve maximum drilling efficiency with minimize drilling cost. In this paper, practical software adopted in this paper to define drilling optimization models including four different optimum keys, namely Opti-flow, Opti-clean, Opti-slip and Opti-nozzle that can help to achieve high drilling efficiency with lower cost. The used data in this research from vertical and horizontal wells were recently drilled in Waha Oil Company fields. The input data are: Formation type, Geopressures, Hole Geometry, Bottom hole assembly and Mud reghology. Upon data analysis, all the results from wells show that the proposed program provides a high accuracy than that proposed from the company in terms of hole cleaning efficiency, and cost break down if we consider that the actual data as a reference base for all wells. Finally, it is recommended to use the established Optimization calculations software at drilling design to achieve correct drilling parameters that can provide high drilling efficiency, borehole cleaning and all other hydraulic parameters which assist to minimize hole problems and control drilling operation costs.

Keywords: optimum keys, namely opti-flow, opti-clean, opti-slip and opti-nozzle

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Authors: R. Sekula

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Epoxy composites are broadly used as an electrical insulation for the high voltage applications since only such materials can fulfill particular mechanical, thermal, and dielectric requirements. However, properties of the final product are strongly dependent on proper manufacturing process with minimized material failures, as too large shrinkage, voids and cracks. Therefore, application of proper materials (epoxy, hardener, and filler) and process parameters (mold temperature, filling time, filling velocity, initial temperature of internal parts, gelation time), as well as design and geometric parameters are essential features for final quality of the produced components. In this paper, an approach for three-dimensional modeling of all molding stages, namely filling, curing and post-curing is presented. The reactive molding simulation tool is based on a commercial CFD package, and include dedicated models describing viscosity and reaction kinetics that have been successfully implemented to simulate the reactive nature of the system with exothermic effect. Also a dedicated simulation procedure for stress and shrinkage calculations, as well as simulation results are presented in the paper. Second part of the paper is dedicated to recent developments on formulations of functional composites for electrical insulation applications, focusing on thermally conductive materials. Concepts based on filler modifications for epoxy electrical composites have been presented, including the results of the obtained properties. Finally, having in mind tough environmental regulations, in addition to current process and design aspects, an approach for product re-design has been presented focusing on replacement of epoxy material with the thermoplastic one. Such “design-for-recycling” method is one of new directions associated with development of new material and processing concepts of electrical products and brings a lot of additional research challenges. For that, one of the successful products has been presented to illustrate the presented methodology.

Keywords: curing, epoxy insulation, numerical simulations, recycling

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Authors: Sendy Ghirardi, Pau Rausell Köster

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The European Commission increasingly pushes cultural policies towards social outcomes and local and regional authorities also call for culture-driven strategies for local development and prosperity and therefore, the measurement of cultural participation becomes increasingly more significant for evidence-based policy-making processes. Cultural participation involves various kinds of social and economic spillovers that combine social and economic objectives of value creation, including social sustainability and respect for human values. Traditionally, from the economic perspective, cultural consumption is measured by the value of financial transactions in purchasing, subscribing to, or renting cultural equipment and content, addressing the market value of cultural products and services. The main sources of data are the household spending survey and merchandise trade survey, among others. However, what characterizes the cultural consumption is that it is linked with the hedonistic and affective dimension rather than the utilitarian one. In fact, nowadays, more and more attention is being paid to the social and psychological dimensions of culture. The aim of this work is to present a comprehensive approach to measure the impacts of cultural participation and cultural users’ behaviour, combining both socio-psychological and economic approaches. The model combines contingent evaluation techniques with the individual characteristic and perception analysis of the cultural experiences to evaluate the cognitive, aesthetic, emotive and social impacts of cultural participation. To investigate the comprehensive approach to measure the impact of the cultural events on individuals, the research has been designed on the basis of prior theoretical development. A deep literature methodology has been done to develop the theoretical model applied to the web platform to measure the impacts of cultural experience on individuals. The developed framework aims to become a democratic tool for evaluating the services that cultural or policy institutions can adopt through the use of an interacting platform that produces big data benefiting academia, cultural management and policies. The Au Culture is a prototype based on an application that can be used on mobile phones or any other digital platform. The development of the AU Culture Platform has been funded by the Valencian Innovation Agency (Government of the Region of Valencia) and it is part of the Horizon 2020 project MESOC.

Keywords: comprehensive approach, cultural participation, economic dimension, socio-psychological dimension

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Authors: Ansari Mohammad Reza, Hiroko Ono, Fakhrullah Sarwari

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Our world is fast heading toward being a predominantly urban planet. This can be a double-edged sword reality where it is as much frightening as it seems interesting. Moreover, a look to the current predictions and taking into the consideration the fact that about 90 percent of the coming urbanization is going to be absorbed by the towns and the cities of the developing countries of Asia and Africa, directly provide us the clues to assume a much more tragic ending to this story than to the happy one. Likewise, in a situation wherein most of these countries are still severely struggling to find the proper answer to their very first initial questions of urbanization—e.g. how to provide the essential structure for their cities, define the regulation, or even design the proper pattern on how the cities should be expanded—thus it is not weird to claim that most of the coming urbanization of the world is going to happen informally. This reality could not only bring the feature, landscape or the picture of the cities of the future under the doubt but at the same time provide the ground for the rise of a bunch of other essential questions of how the facilities would be distributed in these cities, or how fair will this pattern of distribution be. Kabul the capital of Afghanistan, as a city located in the developing world that its process of urbanization has been starting since 2001 and currently hold the position to be the fifth fastest growing city in the world, contained to a considerable slum ratio of 0.7—that means about 70 percent of its population is living in the informal areas—subsequently could be a very good case study to put this questions into the research and find out how the informal development of a city can lead to the unfair and unbalanced distribution of its facilities. Likewise, in this study we tried our best to first propose the ideal model for the fair distribution of the facilities in the Kabul city—where all the citizens have the same equal chance of access to the facilities—and then evaluate the situation of the city based on how fair the facilities are currently distributed therein. We subsequently did it by the comparative analysis between the existing facility rate in the formal and informal areas of the city to the one that was proposed as the fair ideal model.

Keywords: Afghanistan, facility distribution, formal settlements, informal settlements, Kabul

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Authors: Stephanie Duval

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The concept of educational success, combined with the overall development of the child in kindergarten, is at the center of current interests, both in research and in the environments responsible for the education of young children. In order to promote it, researchers emphasize the importance of studying the executive functions [EF] of children in preschool education. More precisely, the EFs, which refers to working memory [WM], inhibition, mental flexibility and planning, would be the pivotal element of the child’s educational success. In order to support the EFs of the child, and even his educational success, the quality of the environments is beginning to be explored more and more. The question that arises now is how to promote EFs for young children in the educational environment, in order to support their educational success? The objective of this study is to investigate the link between the quality of interactions in 5-year-old kindergarten and child’s EFs. The sample consists of 118 children (70 girls, 48 boys) in 12 classes. The quality of the interactions is observed from the Classroom Assessment Scoring System [CLASS], and the EFs (i.e., working memory, inhibition, cognitive flexibility, and planning) are measured with administered tests. The hypothesis of this study was that the quality of teacher-child interactions in preschool education, as measured by the CLASS, was associated with the child’s EFs. The results revealed that the quality of emotional support offered by adults in kindergarten, included in the CLASS tool, was positively and significantly related to WM and inhibition skills. The results also suggest that WM is a key skill in the development of EFs, which may be associated with the educational success of the child. However, this hypothesis remains to be clarified, as is the link with educational success. In addition, results showed that factors associated to the family (ex. parents’ income) moderate the relationship between the domain ‘instructional support’ of the CLASS (ex. concept development) and child’s WM skills. These data suggest a moderating effect related to family characteristics in the link between ‘quality of classroom interactions’ and ‘EFs’. This project proposes, as a future avenue, to check the distinctive effect of different environments (familial and educational) on the child’s EFs. More specifically, future study could examine the influence of the educational environment on EF skills, as well as whether or not there is a moderating effect of the family environment (ex. parents' income) on the link between the quality of the interactions in the classroom and the EFs of the children, as anticipated by this research.

Keywords: executive functions [EFs], environmental factors, quality of interactions, preschool education

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Authors: Mehdi Behbahani, Sebastian Rible, Charles Moulinec, Yvan Fournier, Mike Nicolai, Paolo Crosetto

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Computational Fluid Dynamics blood-flow simulations are increasingly used to develop and validate blood-contacting medical devices. This study shows that numerical simulations can provide additional and accurate estimates of relevant hemodynamic indicators (e.g., recirculation zones or wall shear stresses), which may be difficult and expensive to obtain from in-vivo or in-vitro experiments. The most recent FDA (Food and Drug Administration) benchmark consisted of a simplified centrifugal blood pump model that contains fluid flow features as they are commonly found in these devices with a clear focus on highly turbulent phenomena. The FDA centrifugal blood pump study is composed of six test cases with different volumetric flow rates ranging from 2.5 to 7.0 liters per minute, pump speeds, and Reynolds numbers ranging from 210,000 to 293,000. Within the frame of this study different turbulence models were tested including RANS models, e.g. k-omega, k-epsilon and a Reynolds Stress Model (RSM) and, LES. The partitioners Hilbert, METIS, ParMETIS and SCOTCH were used to create an unstructured mesh of 76 million elements and compared in their efficiency. Computations were performed on the JUQUEEN BG/Q architecture applying the highly parallel flow solver Code SATURNE and typically using 32768 or more processors in parallel. Visualisations were performed by means of PARAVIEW. Different turbulence models including all six flow situations could be successfully analysed and validated against analytical considerations and from comparison to other data-bases. It showed that an RSM represents an appropriate choice with respect to modeling high-Reynolds number flow cases. Especially, the Rij-SSG (Speziale, Sarkar, Gatzki) variant turned out to be a good approach. Visualisation of complex flow features could be obtained and the flow situation inside the pump could be characterized.

Keywords: blood flow, centrifugal blood pump, high performance computing, scalability, turbulence

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Authors: Humaira M. Khan, Kanwal Asif

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Ischemic stroke is a neurological disorder with a complex pathophysiology associated with motor, sensory and cognitive deficits. Major approaches developed to treat acute ischemic stroke fall into two categories, thrombolysis and neuroprotection. The objectives of this study were to evaluate the neuroprotective and anti-thrombolytic effects of Olea europaea (olive oil) and Malus domestica (apple cider vinegar) and their combination in rat stroke model. Furthermore, histopathological analysis was also performed to assess the severity of ischemia among treated and reference groups. Male albino rats (12 months age) weighing 300- 350gm were acclimatized and subjected to middle cerebral artery occlusion method for stroke induction. Olea europaea and Malus domestica was administered orally in dose of 0.75ml/kg and 3ml/kg and combination was administered at dose of 0.375ml/kg and 1.5ml/kg prophylactically for consecutive 21 days. Negative control group was dosed with normal saline whereas piracetam (250mg/kg) was administered as reference. Neuroprotective activity of standard piracetam, Olea europaea, Malus domestica and their combination was evaluated by performing functional outcome tests i.e. Cylinder, pasta, ladder run, pole and water maize tests. Rats were subjected to surgery after 21 days of treatment for analysis from stroke recovery. Olea europaea and Malus domestica in individual doses of 0.75ml/kg and 3ml/kg respectively showed neuroprotection by significant improvement in ladder run test (121.6± 0.92;128.2 ± 0.73) as compare to reference (125.4 ± 0.74). Both test doses showed significant neuroprotection as compare to reference (9.60 ± 0.50) in pasta test (8.40 ± 0.24;9.80 ± 0.37) whereas with cylinder test, experimental groups showed significant increase in movements (6.60 ± 0.24; 8.40 ± 0.24) in contrast to reference (7.80 ± 0.37).There was a decrease in percentage time taken f to reach the hidden maize in water maize test (56.80 ± 0.58;61.80 ± 0.66) at doses 0.75ml/kg and 3ml/kg respectively as compare to piracetam (59.40 ± 1.07). Olea europaea and Malus domestica individually showed significant reduction in duration of mobility (127.0 ± 0.44; 123.0 ± 0.44) in pole test as compare to piracetam (124.0 ± 0.70). Histopathological analysis revealed the significant extent of protection from ischemia after prophylactic treatments. Hence it is concluded that Olea europaea and Malus domestica are effective neuroprotective agents alone as compare to their combination.

Keywords: ischemia, Malus domestica, neuroprotection, Olea europaea

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Authors: Shishay Kidanu, Abdullah Alhaj

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Sinkholes in the karst terrain of Greene County, Missouri, pose significant geohazards, imposing challenges on construction and infrastructure development, with potential threats to lives and property. To address these issues, understanding the influencing factors and modeling sinkhole susceptibility is crucial for effective mitigation through strategic changes in land use planning and practices. This study utilizes geographic information system (GIS) software to collect and process diverse data, including topographic, geologic, hydrogeologic, and anthropogenic information. Nine key sinkhole influencing factors, ranging from slope characteristics to proximity to geological structures, were carefully analyzed. The Frequency Ratio method establishes relationships between attribute classes of these factors and sinkhole events, deriving class weights to indicate their relative importance. Weighted integration of these factors is accomplished using the Analytic Hierarchy Process (AHP) and the Weighted Linear Combination (WLC) method in a GIS environment, resulting in a comprehensive sinkhole susceptibility index (SSI) model for the study area. Employing Jenk's natural break classifier method, the SSI values are categorized into five distinct sinkhole susceptibility zones: very low, low, moderate, high, and very high. Validation of the model, conducted through the Area Under Curve (AUC) and Sinkhole Density Index (SDI) methods, demonstrates a robust correlation with sinkhole inventory data. The prediction rate curve yields an AUC value of 74%, indicating a 74% validation accuracy. The SDI result further supports the success of the sinkhole susceptibility model. This model offers reliable predictions for the future distribution of sinkholes, providing valuable insights for planners and engineers in the formulation of development plans and land-use strategies. Its application extends to enhancing preparedness and minimizing the impact of sinkhole-related geohazards on both infrastructure and the community.

Keywords: sinkhole, GIS, analytical hierarchy process, frequency ratio, susceptibility, Missouri

Procedia PDF Downloads 65

Authors: Marta Moczulska

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One of the most important aspects of human management in an organization is the work engagement. In spite of the different perspectives of engagement, it is possible to see that it is expressed in the activity of the individual involved in the performance of tasks, the functioning of the organization. At the same time is considered not only in behavioural but also cognitive and emotional dimensions. Previous studies were related to sources, predictors of engagement and determinants, including organizational ones. Attention was paid to the importance of needs (including belonging, success, development, sense of work), values (such as trust, honesty, respect, justice) or interpersonal relationships, especially with the supervisor. Taking them into account and theories related to human acting, behaviour in the organization, interactions, it was recognized that engagement can be shaped through cooperation and competition. It was assumed that to shape the work engagement, it is necessary to simultaneously cooperate and compete in order to reduce the weaknesses of each of these activities and strengthen the strengths. Combining cooperation and competition is defined as 'coopetition'. However, research conducted in this field is primarily concerned with relations between companies. Intra-organizational coopetition is mainly considered as competing organizational branches or units (cross-functional coopetition). Less attention is paid to competing groups or individuals. It is worth noting the ambiguity of the concepts of cooperation and rivalry. Taking into account the terms used and their meaning, different levels of cooperation and forms of competition can be distinguished. Thus, several types of intra-organizational coopetition can be identified. The article aims at defining the potential for work engagement through intra-organizational coopetition. The aim of research was to know how levels of cooperation in competition conditions influence engagement. It is assumed that rivalry (positive competition) between teams (the highest level of cooperation) is a type of coopetition that contributes to working engagement. Qualitative research will be carried out among students of the University of Zielona Gora, realizing various types of projects. The first research groups will be students working in groups on one project for three months. The second research group will be composed of students working in groups on several projects in the same period (three months). Work engagement will be determined using the UWES questionnaire. Levels of cooperation will be determined using the author's research tool. Due to the fact that the research is ongoing, results will be presented in the final paper.

Keywords: competition, cooperation, intra-organizational coopetition, work engagement

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Authors: Yunbin Deng

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Most existing applications of automatic speech recognition relies on cooperative subjects at a short distance to a microphone. Standoff speech recognition using microphone arrays can extend the subject to sensor distance somewhat, but it is still limited to only a few feet. As such, most deployed applications of standoff speech recognitions are limited to indoor use at short range. Moreover, these applications require air passway between the subject and the sensor to achieve reasonable signal to noise ratio. This study reports long range (50 feet) automatic speech recognition experiments using a Laser Doppler Vibrometer (LDV) sensor. This study shows that the LDV sensor modality can extend the speech acquisition standoff distance far beyond microphone arrays to hundreds of feet. In addition, LDV enables 'listening' through the windows for uncooperative subjects. This enables new capabilities in automatic audio and speech intelligence, surveillance, and reconnaissance (ISR) for law enforcement, homeland security and counter terrorism applications. The Polytec LDV model OFV-505 is used in this study. To investigate the impact of different vibrating materials, five parallel LDV speech corpora, each consisting of 630 speakers, are collected from the vibrations of a glass window, a metal plate, a plastic box, a wood slate, and a concrete wall. These are the common materials the application could encounter in a daily life. These data were compared with the microphone counterpart to manifest the impact of various materials on the spectrum of the LDV speech signal. State of the art deep neural network modeling approaches is used to conduct continuous speaker independent speech recognition on these LDV speech datasets. Preliminary phoneme recognition results using time-delay neural network, bi-directional long short term memory, and model fusion shows great promise of using LDV for long range speech recognition. To author’s best knowledge, this is the first time an LDV is reported for long distance speech recognition application.

Keywords: covert speech acquisition, distant speech recognition, DSR, laser Doppler vibrometer, LDV, speech intelligence surveillance and reconnaissance, ISR

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Authors: Rui Lin, Jimmy Xiangji Huang, Gary Spraakman

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This forthcoming systematic review will underscore the imperative of leveraging technology to mitigate social isolation in older adults, particularly in the context of unprecedented global challenges such as the COVID-19 pandemic. With the continual evolution of technology, it becomes crucial to scrutinize the efficacy of interventions and discern how they can alleviate social isolation and augment social well-being among the elderly. This review will strive to clarify the best methods for older adults to utilize cost-effective and user-friendly technology and will investigate how the adaptation and execution of such interventions can be fine-tuned to maximize their positive outcomes. The study will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to filter pertinent studies. We foresee conducting an analysis of articles and executing a narrative analysis to discover themes and indicators related to quality of life and, technology use and well-being. The review will examine how involving older adults at the community level, applying top practices from community-based participatory research, can establish efficient strategies to implement technology-based interventions designed to diminish social isolation and boost digital use self-efficacy. Applications based on mobile technology and virtual platforms are set to assume a crucial role not only in enhancing connections within families but also in connecting older adults to vital healthcare resources, fostering both physical and mental well-being. The review will investigate how technological devices and platforms can address the cognitive, visual, and auditory requirements of older adults, thus strengthening their confidence and proficiency in digital use—a crucial factor during enforced social distancing or self-isolation periods during pandemics. This review will endeavor to provide insights into the multifaceted benefits of technology for older adults, focusing on how tailored technological interventions can be a beacon of social and mental wellness in times of social restrictions. It will contribute to the growing body of knowledge on the intersection of technology and elderly well-being, offering nuanced understandings and practical implications for developing user-centric, effective, and inclusive technological solutions for older populations.

Keywords: older adults, health service delivery, digital health, social isolation, social well-being

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Authors: Yenny Paola Morales Cortés, Fabián Rico Rodríguez, Juan Carlos Serrato Bermúdez, Carlos Arturo Martínez Riascos

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Numerous benefits of galactooligosaccharides (GOS) as prebiotics have motivated the study of enzymatic processes for their production. These processes have special complexities due to several factors that make difficult high productivity, such as enzyme type, reaction medium pH, substrate concentrations and presence of inhibitors, among others. In the present work the production of galactooligosaccharides (with different degrees of polymerization: two, three and four) from lactose was studied. The study considers the formulation of a mathematical model that predicts the production of GOS from lactose using the enzyme β-galactosidase. The effect of pH in the reaction was studied. For that, phosphate buffer was used and with this was evaluated three pH values (6.0.6.5 and 7.0). Thus it was observed that at pH 6.0 the enzymatic activity insignificant. On the other hand, at pH 7.0 the enzymatic activity was approximately 27 times greater than at 6.5. The last result differs from previously reported results. Therefore, pH 7.0 was chosen as working pH. Additionally, the enzyme concentration was analyzed, which allowed observing that the effect of the concentration depends on the pH and the concentration was set for the following studies in 0.272 mM. Afterwards, experiments were performed varying the lactose concentration to evaluate its effects on the process and to generate the data for the adjustment of the mathematical model parameters. The mathematical model considers the reactions of lactose hydrolysis and transgalactosylation for the production of disaccharides and trisaccharides, with their inverse reactions. The production of tetrasaccharides was negligible and, because of that, it was not included in the model. The reaction was monitored by HPLC and for the quantitative analysis of the experimental data the Matlab programming language was used, including solvers for differential equations systems integration (ode15s) and nonlinear problems optimization (fminunc). The results confirm that the transgalactosylation and hydrolysis reactions are reversible, additionally inhibition by glucose and galactose is observed on the production of GOS. In relation to the production process of galactooligosaccharides, the results show that it is necessary to have high initial concentrations of lactose considering that favors the transgalactosylation reaction, while low concentrations favor hydrolysis reactions.

Keywords: β-galactosidase, galactooligosaccharides, inhibition, lactose, Matlab, modeling

Procedia PDF Downloads 343

Authors: Tan Xin Zhong Timothy, Chang Chen Jie Victor, Yew Kwan Tong, Lim Geok Peng Sandy

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Background: Leaders in crisis response teams such as Trauma Teams in hospitals are essential to the effective coordination and direction of the team. The response to emergency trauma situations must be accurate, rapid, and well executed. To this end, the team leader’s social, technical and leadership skills are essential factors that implicate the success of an emergency trauma intervention. While each emergency trauma case varies in severity and complexity, and the experience and expertise of team leaders may vary, it would be productive to identify certain coordinative and directive functions that improve the capacity for leading a team. Methods: This qualitative study of Trauma Team physicians in Singapore General Hospital (SGH) involved 50 in-depth interviews with doctors and nurses involved in Trauma Team activations, observations of Trauma Teams managing emergency patients, and reviews of audio/video recordings of 65 trauma activations. The interviews were conducted with doctors of various ranks across the relevant departments, 12 from the Emergency Department (ED), 11 from General Surgery (GS) and 8 from Orthopaedics, while the 6 nurses were from ED. In accordance with the grounded theory approach, the content of the interviews was coded and analysed in order to derive broad leadership themes that corresponded with certain behavioural traits exhibited by trauma team leaders, supplemented with the observational and audio/video data. Results: The leadership behaviours of the team leaders could be typified into three broad categories: team orientation, engagement and activeness. Team orientation corresponds with the source and form of cognitive responsibility, decision-making and informational contributions, divisible into individualistic and consultative sub-categories. Engagement refers to the type of activity that leaders prefer to engage in, and which implicates their attentional focus, divisible into participatory and supervisory sub-categories. Activeness is a function of the leader’s attitudes towards the behavioural regulation of the team, which manifests in inactivity or activity to augment or merely align with protocol. These factors are not exhaustive and are contextually sensitive, but collectively implicate a significant portion of the leadership activity observed in trauma teams.

Keywords: trauma team activations, critical event management, leadership, teamwork

Procedia PDF Downloads 313

Authors: Roxane A. Legaie, Kjiana E. Schwab, Caroline E. Gargett

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Studies looking at the changes in gene expression from RNAseq data often make use of linear models. It is also common practice to focus on a subset of data for a comparison of interest, leaving aside the samples not involved in this particular comparison. This work shows the importance of including all observations in the modeling process to better estimate variance parameters, even when the samples included are not directly used in the comparison under test. The human endometrium is a dynamic tissue, which undergoes cycles of growth and regression with each menstrual cycle. The mesenchymal stem cells (MSCs) present in the endometrium are likely responsible for this remarkable regenerative capacity. However recent studies suggest that MSCs also plays a role in the pathogenesis of endometriosis, one of the most common medical conditions affecting the lower abdomen in women in which the endometrial tissue grows outside the womb. In this study we compared gene expression profiles between MSCs and non-stem cell counterparts (‘non-MSC’) obtained from women with (‘E’) or without (‘noE’) endometriosis from RNAseq. Raw read counts were used for differential expression analysis using a linear model with the limma-voom R package, including either all samples in the study or only the samples belonging to the subset of interest (e.g. for the comparison ‘E vs noE in MSC cells’, including only MSC samples from E and noE patients but not the non-MSC ones). Using the full dataset we identified about 100 differentially expressed (DE) genes between E and noE samples in MSC samples (adj.p-val < 0.05 and |logFC|>1) while only 9 DE genes were identified when using only the subset of data (MSC samples only). Important genes known to be involved in endometriosis such as KLF9 and RND3 were missed in the latter case. When looking at the MSC vs non-MSC cells comparison, the linear model including all samples identified 260 genes for noE samples (including the stem cell marker SUSD2) while the subset analysis did not identify any DE genes. When looking at E samples, 12 genes were identified with the first approach and only 1 with the subset approach. Although the stem cell marker RGS5 was found in both cases, the subset test missed important genes involved in stem cell differentiation such as NOTCH3 and other potentially related genes to be used for further investigation and pathway analysis.

Keywords: differential expression, endometriosis, linear model, RNAseq

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Authors: Jiyoung Lee, Andrew D. Gershoff, Jerry Jisang Han

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Most extant research on consumer privacy concerns and their willingness to share personal data has focused on contextual factors (e.g., types of information collected, type of compensation) that lead to consumers’ personal information disclosure. Unfortunately, the literature lacks a clear understanding of how consumers’ incidental psychological needs may influence consumers’ decisions to share their personal information with companies or brands. In this research, we investigate how social exclusion, which is an increasing societal problem, especially since the onset of the COVID-19 pandemic, leads to increased information disclosure intentions for consumers. Specifically, we propose and find that when consumers become socially excluded, their desire for social connection increases, and this desire leads to a greater willingness to disclose their personal information with firms. The motivation to form and maintain interpersonal relationships is one of the most fundamental human needs, and many researchers have found that deprivation of belongingness has negative consequences. Given the negative effects of social exclusion and the universal need to affiliate with others, people respond to exclusion with a motivation for social reconnection, resulting in various cognitive and behavioral consequences, such as paying greater attention to social cues and conforming to others. Here, we propose personal information disclosure as another form of behavior that can satisfy such social connection needs. As self-disclosure can serve as a strategic tool in creating and developing social relationships, those who have been socially excluded and thus have greater social connection desires may be more willing to engage in self-disclosure behavior to satisfy such needs. We conducted four experiments to test how feelings of social exclusion can influence the extent to which consumers share their personal information with brands. Various manipulations and measures were used to demonstrate the robustness of our effects. Through the four studies, we confirmed that (1) consumers who have been socially excluded show greater willingness to share their personal information with brands and that (2) such an effect is driven by the excluded individuals’ desire for social connection. Our findings shed light on how the desire for social connection arising from exclusion influences consumers’ decisions to disclose their personal information to brands. We contribute to the consumer disclosure literature by uncovering a psychological need that influences consumers’ disclosure behavior. We also extend the social exclusion literature by demonstrating that exclusion influences not only consumers’ choice of products but also their decision to disclose personal information to brands.

Keywords: consumer-brand relationship, consumer information disclosure, consumer privacy, social exclusion

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Authors: Thomas Monahan, Nicolas Gorius, Thanh Nguyen

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Exoplanet atmospheric parameters retrieval is a complex, computationally intensive, inverse modeling problem in which an exoplanet’s atmospheric composition is extracted from an observed spectrum. Traditional Bayesian sampling methods require extensive time and computation, involving algorithms that compare large numbers of known atmospheric models to the input spectral data. Runtimes are directly proportional to the number of parameters under consideration. These increased power and runtime requirements are difficult to accommodate in space missions where model size, speed, and power consumption are of particular importance. The use of traditional Bayesian sampling methods, therefore, compromise model complexity or sampling accuracy. The Atmospheric Retrievals conditional Generative Adversarial Network (ARcGAN) is a deep convolutional generative adversarial network that improves on the previous model’s speed and accuracy. We demonstrate the efficacy of artificial intelligence to quickly and reliably predict atmospheric parameters and present it as a viable alternative to slow and computationally heavy Bayesian methods. In addition to its broad applicability across instruments and planetary types, ARcGAN has been designed to function on low power application-specific integrated circuits. The application of edge computing to atmospheric retrievals allows for real or near-real-time quantification of atmospheric constituents at the instrument level. Additionally, edge computing provides both high-performance and power-efficient computing for AI applications, both of which are critical for space missions. With the edge computing chip implementation, ArcGAN serves as a strong basis for the development of a similar machine-learning algorithm to reduce the downlinked data volume from the Compact Ultraviolet to Visible Imaging Spectrometer (CUVIS) onboard the DAVINCI mission to Venus.

Keywords: deep learning, generative adversarial network, edge computing, atmospheric parameters retrieval

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Authors: Guannan Ren, Thomas Mazzuchi, Shahram Sarkani

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Electric vehicle battery recycling has emerged as a critical process in the transition toward sustainable transportation. As the demand for electric vehicles continues to rise, so does the need to address the end-of-life management of their batteries. Electric vehicle battery recycling benefits resource recovery and supply chain stability by reclaiming valuable metals like lithium, cobalt, nickel, and graphite. The reclaimed materials can then be reintroduced into the battery manufacturing process, reducing the reliance on raw material extraction and the environmental impacts of waste. Current battery recycling rates are insufficient to meet the growing demands for raw materials. While significant progress has been made in electric vehicle battery recycling, many areas can still improve. Standardization of battery designs, increased collection and recycling infrastructures, and improved efficiency in recycling processes are essential for scaling up recycling efforts and maximizing material recovery. This work delves into key factors, such as regulatory frameworks, economic incentives, and technological processes, that influence the cost-effectiveness and efficiency of battery recycling systems. A system dynamics model that considers variables such as battery production rates, demand and price fluctuations, recycling infrastructure capacity, and the effectiveness of recycling processes is created to study how these variables are interconnected, forming feedback loops that affect the overall supply chain efficiency. Such a model can also help simulate the effects of stricter regulations on battery disposal, incentives for recycling, or investments in research and development for battery designs and advanced recycling technologies. By using the developed model, policymakers, industry stakeholders, and researchers may gain insights into the effects of applying different policies or process updates on electric vehicle battery recycling rates.

Keywords: environmental engineering, modeling and simulation, circular economy, sustainability, transportation science, policy

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Authors: Scott Andersen

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Perhaps simply and rather unadornedly, consciousness is having multiple goals for action and the continuously adjudication of such goals to implement action, referred to as the Maps of Meaning (MoM) Consciousness Theory. The MoM theory triangulates through three parallel corollaries, action (behavior), mechanism (morphology/pathophysiology), and goals (teleology). (1) An organism’s consciousness contains a fluid, nested goals. These goals are not intentionality, but intersectionality, embodiment meeting the world. i.e., Darwinian inclusive fitness or randomization, then survival of the fittest. These goals form via gradual descent under inclusive fitness, the goals being the abstraction of a ‘match’ between the evolutionary environment and organism. Human consciousness implements the brain efficiency hypothesis, genetics, epigenetics, and experience crystallize efficiencies, not necessitating best or objective but fitness, i.e., perceived efficiency based on one’s adaptive environment. These efficiencies are objectively arbitrary, but determine the operation and level of one’s consciousness, termed extreme thrownness. Since inclusive fitness drives efficiencies in physiologic mechanism, morphology and behavior (action) and originates one’s goals, embodiment is necessarily entangled to human consciousness as its the intersection of mechanism or action (both necessitating embodiment) occurring in the world that determines fitness. Perception is the operant process of consciousness and is the consciousness’ de facto goal adjudication process. Goal operationalization is fundamentally efficiency-based via one’s unique neuronal mapping as a byproduct of genetics, epigenetics, and experience. Perception involves information intake and information discrimination, equally underpinned by efficiencies of inclusive fitness via extreme thrownness. Perception isn’t a ‘frame rate,’ but Bayesian priors of efficiency based on one’s extreme thrownness. Consciousness and human consciousness is a modular (i.e., a scalar level of richness, which builds up like building blocks) and dimensionalized (i.e., cognitive abilities become possibilities as emergent phenomena at various modularities, like stratified factors in factor analysis). The meta dimensions of human consciousness seemingly include intelligence quotient, personality (five-factor model), richness of perception intake, and richness of perception discrimination, among other potentialities. Future consciousness research should utilize factor analysis to parse modularities and dimensions of human consciousness and animal models.

Keywords: consciousness, perception, prospection, embodiment

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Authors: Sungin Jeong

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This paper presents a linear oscillating generator of cylindrical type for hybrid electric vehicle application. The focus of the study is the suggestion of the optimal model and the design rule of the cylindrical linear oscillating generator with permanent magnet in the back-iron translator. The cylindrical topology is achieved using equivalent magnetic circuit considering leakage elements as initial modeling. This topology with permanent magnet in the back-iron translator is described by number of phases and displacement of stroke. For more accurate analysis of an oscillating machine, it will be compared by moving just one-pole pitch forward and backward the thrust of single-phase system and three-phase system. Through the analysis and comparison, a single-phase system of cylindrical topology as the optimal topology is selected. Finally, the detailed design of the optimal topology takes the magnetic saturation effects into account by finite element analysis. Besides, the losses are examined to obtain more accurate results; copper loss in the conductors of machine windings, eddy-current loss of permanent magnet, and iron-loss of specific material of electrical steel. The considerations of thermal performances and mechanical robustness are essential, because they have an effect on the entire efficiency and the insulations of the machine due to the losses of the high temperature generated in each region of the generator. Besides electric machine with linear oscillating movement requires a support system that can resist dynamic forces and mechanical masses. As a result, the fatigue analysis of shaft is achieved by the kinetic equations. Also, the thermal characteristics are analyzed by the operating frequency in each region. The results of this study will give a very important design rule in the design of linear oscillating machines. It enables us to more accurate machine design and more accurate prediction of machine performances.

Keywords: equivalent magnetic circuit, finite element analysis, hybrid electric vehicle, linear oscillating generator

Procedia PDF Downloads 190