18,231 research outputs found

    Meso-scale FDM material layout design strategies under manufacturability constraints and fracture conditions

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    In the manufacturability-driven design (MDD) perspective, manufacturability of the product or system is the most important of the design requirements. In addition to being able to ensure that complex designs (e.g., topology optimization) are manufacturable with a given process or process family, MDD also helps mechanical designers to take advantage of unique process-material effects generated during manufacturing. One of the most recognizable examples of this comes from the scanning-type family of additive manufacturing (AM) processes; the most notable and familiar member of this family is the fused deposition modeling (FDM) or fused filament fabrication (FFF) process. This process works by selectively depositing uniform, approximately isotropic beads or elements of molten thermoplastic material (typically structural engineering plastics) in a series of pre-specified traces to build each layer of the part. There are many interesting 2-D and 3-D mechanical design problems that can be explored by designing the layout of these elements. The resulting structured, hierarchical material (which is both manufacturable and customized layer-by-layer within the limits of the process and material) can be defined as a manufacturing process-driven structured material (MPDSM). This dissertation explores several practical methods for designing these element layouts for 2-D and 3-D meso-scale mechanical problems, focusing ultimately on design-for-fracture. Three different fracture conditions are explored: (1) cases where a crack must be prevented or stopped, (2) cases where the crack must be encouraged or accelerated, and (3) cases where cracks must grow in a simple pre-determined pattern. Several new design tools, including a mapping method for the FDM manufacturability constraints, three major literature reviews, the collection, organization, and analysis of several large (qualitative and quantitative) multi-scale datasets on the fracture behavior of FDM-processed materials, some new experimental equipment, and the refinement of a fast and simple g-code generator based on commercially-available software, were developed and refined to support the design of MPDSMs under fracture conditions. The refined design method and rules were experimentally validated using a series of case studies (involving both design and physical testing of the designs) at the end of the dissertation. Finally, a simple design guide for practicing engineers who are not experts in advanced solid mechanics nor process-tailored materials was developed from the results of this project.U of I OnlyAuthor's request

    The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions

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    The Metaverse offers a second world beyond reality, where boundaries are non-existent, and possibilities are endless through engagement and immersive experiences using the virtual reality (VR) technology. Many disciplines can benefit from the advancement of the Metaverse when accurately developed, including the fields of technology, gaming, education, art, and culture. Nevertheless, developing the Metaverse environment to its full potential is an ambiguous task that needs proper guidance and directions. Existing surveys on the Metaverse focus only on a specific aspect and discipline of the Metaverse and lack a holistic view of the entire process. To this end, a more holistic, multi-disciplinary, in-depth, and academic and industry-oriented review is required to provide a thorough study of the Metaverse development pipeline. To address these issues, we present in this survey a novel multi-layered pipeline ecosystem composed of (1) the Metaverse computing, networking, communications and hardware infrastructure, (2) environment digitization, and (3) user interactions. For every layer, we discuss the components that detail the steps of its development. Also, for each of these components, we examine the impact of a set of enabling technologies and empowering domains (e.g., Artificial Intelligence, Security & Privacy, Blockchain, Business, Ethics, and Social) on its advancement. In addition, we explain the importance of these technologies to support decentralization, interoperability, user experiences, interactions, and monetization. Our presented study highlights the existing challenges for each component, followed by research directions and potential solutions. To the best of our knowledge, this survey is the most comprehensive and allows users, scholars, and entrepreneurs to get an in-depth understanding of the Metaverse ecosystem to find their opportunities and potentials for contribution

    Soliton Gas: Theory, Numerics and Experiments

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    The concept of soliton gas was introduced in 1971 by V. Zakharov as an infinite collection of weakly interacting solitons in the framework of Korteweg-de Vries (KdV) equation. In this theoretical construction of a diluted soliton gas, solitons with random parameters are almost non-overlapping. More recently, the concept has been extended to dense gases in which solitons strongly and continuously interact. The notion of soliton gas is inherently associated with integrable wave systems described by nonlinear partial differential equations like the KdV equation or the one-dimensional nonlinear Schr\"odinger equation that can be solved using the inverse scattering transform. Over the last few years, the field of soliton gases has received a rapidly growing interest from both the theoretical and experimental points of view. In particular, it has been realized that the soliton gas dynamics underlies some fundamental nonlinear wave phenomena such as spontaneous modulation instability and the formation of rogue waves. The recently discovered deep connections of soliton gas theory with generalized hydrodynamics have broadened the field and opened new fundamental questions related to the soliton gas statistics and thermodynamics. We review the main recent theoretical and experimental results in the field of soliton gas. The key conceptual tools of the field, such as the inverse scattering transform, the thermodynamic limit of finite-gap potentials and the Generalized Gibbs Ensembles are introduced and various open questions and future challenges are discussed.Comment: 35 pages, 8 figure

    The impact of innovative technologies in construction activities on concrete debris recycling in China : a system dynamics-based analysis

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    As construction activities become more intensive in developing countries, increasing improperly managed construction and demolition waste (CDW) brings serious environmental impacts. Recycling is a beneficial way to dispose of CDW that reduces environmental impact and brings economic benefits, especially for concrete. China is the country that generates the most CDW in the world, but its domestic recycling rate is much lower than that of developed countries. While the efficient technologies in developed regions have helped them to achieve a well-established recycling industry, whether these innovative technologies can be used to improve the concrete debris recycling targets in developing regions is unclear. This study examines whether innovations currently widely used in construction activities and materials can have a positive effect on the recycling of End-of-Life concrete materials in China. Results from modeling system dynamics imply that the introduction of innovative technologies in the recycling system of concrete debris can probably contribute to CO2 reduction (3.6% reduction) and economic benefits (2.6 times increase, but mainly from landfill charges and fines) from 2022 to 2030. Prefabrication and 3D printing significantly impact recycled concrete production and CDW recycling, and they are recommended as a priority for promotion. In contrast, carbonation is not suggested for application due to its minor role. Nevertheless, since the market share of innovative technologies and the basic CDW recycling rates are currently low in China, fluctuations in their usage are hardly to have a substantial positive impact. We suggest that financial support from the government is needed for upcycling by recyclers and technology providers to improve the base recycling rate in order for innovative technologies to make an effective contribution to the sustainable construction industry, creating a win–win situation for both the economy and the environment of the recycling system

    Circadian variations in aortic stiffness, sympathetic vasoconstriction, and post-ischemic vasodilation in adults with and without type 2 diabetes.

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    The current literature reveals a lack of information on the circadian variations of some important cardiovascular risk factors related to the work of the heart or the capacity to provide blood and oxygen to various tissues. These factors include aortic stiffness, peripheral vasoconstrictor responsiveness, and post-ischemic vasodilation capacity. Furthermore, it is not clear whether the impact of an external stressor capable of activating the sympathetic nervous system could have greater repercussions on the cardiovascular system in the morning than in the evening. Given the higher incidence of acute cardiovascular events in the morning than in the evening, the studies undertaken in this thesis aim to investigate the circadian variations of these factors that are linked to cardiovascular risk, both at rest and during acute activation of the sympathetic nervous system. Type 2 diabetes (T2DM) is a condition that induces deleterious changes in cardiovascular function, impacting cardiovascular mortality and morbidity. Thus, the impact of diabetes will be evaluated. As a secondary purpose, considering the sex differences in the incidence and prognosis of cardiovascular disease, the effect of sex will be evaluated. Aortic stiffness proved not to be increased in the morning compared to the evening at specific times when the cardiovascular risk is significantly different, both at rest and during sympathetic activation. However, while healthy older women show similar aortic stiffness values compared to their male counterparts during acute stress, older women with T2DM reported greater aortic stiffness compared to men with T2DM. The post-ischemic forearm vasodilation is blunted in the morning compared to the evening in healthy elderly and such an attenuated vasodilation capacity impairs blood flow supply towards the ischemic area. The presence of T2DM does not affect vasodilation capacity and reactive hyperemia, but induces circadian variations in arterial pressure. The peripheral vasoconstriction triggered by a standardized sympathetic stressor is similar between morning and evening, regardless of the presence of T2DM and reduced baseline vascular conductance values in the morning. However, the peripheral vasoconstriction responsiveness is blunted in individuals with T2DM than in healthy ones as sympathetic activation induces vasodilation on the contralateral forearm in individuals with T2DM and vasoconstriction in healthy age-matched subjects. This finding highlights a neurovascular response to an external stressor altered by T2DM. Taken together, our findings suggest that the baseline state of constriction of the peripheral vascular tissue is greater in the morning than in the evening, but this fact is not due to greater sympathetic vasoconstriction responsiveness in the morning. Higher morning vasoconstriction at baseline however affects the capacity of a vascular tissue to dilate and, in turn, to supply blood to an ischemic tissue. Similar sympathetic vasoconstriction responsiveness between morning and evening is a likely factor explaining similar or lower values of central artery stiffness in the morning than in the evening, not only at rest but also during sympathetic excitation. Paradoxically, adults with T2DM report an increase in sympathetic-mediated dilatation capacity on the vascular tissue, which might be a defense mechanism that allows to reduce the central pressor response during sympathetic excitation

    Corporate Social Responsibility: the institutionalization of ESG

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    Understanding the impact of Corporate Social Responsibility (CSR) on firm performance as it relates to industries reliant on technological innovation is a complex and perpetually evolving challenge. To thoroughly investigate this topic, this dissertation will adopt an economics-based structure to address three primary hypotheses. This structure allows for each hypothesis to essentially be a standalone empirical paper, unified by an overall analysis of the nature of impact that ESG has on firm performance. The first hypothesis explores the evolution of CSR to the modern quantified iteration of ESG has led to the institutionalization and standardization of the CSR concept. The second hypothesis fills gaps in existing literature testing the relationship between firm performance and ESG by finding that the relationship is significantly positive in long-term, strategic metrics (ROA and ROIC) and that there is no correlation in short-term metrics (ROE and ROS). Finally, the third hypothesis states that if a firm has a long-term strategic ESG plan, as proxied by the publication of CSR reports, then it is more resilience to damage from controversies. This is supported by the finding that pro-ESG firms consistently fared better than their counterparts in both financial and ESG performance, even in the event of a controversy. However, firms with consistent reporting are also held to a higher standard than their nonreporting peers, suggesting a higher risk and higher reward dynamic. These findings support the theory of good management, in that long-term strategic planning is both immediately economically beneficial and serves as a means of risk management and social impact mitigation. Overall, this contributes to the literature by fillings gaps in the nature of impact that ESG has on firm performance, particularly from a management perspective

    Identifizierung prädiktiver und prognostischer Biomarker in unterschiedlichen Tumorkompartimenten des ösophagealen Adenokarzinoms

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    Das ösophageale Adenokarzinom zeigt eine global steigende Inzidenz und hat mit einer 5-Jahres-Überlebensrate von weniger als 25% eine schlechte Prognose. Personalisierte Therapieansätze sind selten und prognostische/prädiktive Biomarker des Tumormikromilieus sind unzureichend charakterisiert. Die kumulative Promotion nähert sich dieser Problematik in drei unterschiedlichen Schwerpunkten. 1. Zur Identifizierung Kompartiment-spezifischer Biomarker wurde eine Methode entwickelt, welche als kostengünstige Alternative zum sc-Seq Expressionsprofile individueller Zelltypen generiert. Dabei erfolgt die Extraktion der RNA nicht aus Einzelzellen, sondern aus flowzytometrisch-getrennten Zellkompartimenten. Die Separation der Proben in Epithelzellen, Immunzellen und Fibroblasten wurde durch verschiedene Verfahren validiert und eine suffiziente Ausbeute an RNA auch für kleine Gewebemengen gezeigt. 2. Biomarker des Immunzellkompartiments als therapeutische Angriffspunkte wurden in einem Patientenkollektiv von bis zu 551 Patienten auf ihre Bedeutung beim EAC überprüft. Es zeigte sich eine Expression der Immuncheckpoints LAG3, VISTA und IDO auf TILs durch IHC und RNA-Sonden basierte Verfahren in einem relevanten Anteil (LAG3: 11,4%, VISTA: 29%, IDO: 52,6%). Es konnte eine prognostisch günstige Bedeutung der VISTA, LAG3 und IDO Expression gezeigt werden. Durch den Vergleich von Genexpressionsprofilen aus therapienaiven und vorbehandelten Tumoren konnte zudem ein immunsuppressiver Effekt von neoadjuvanten Therapiekonzepten auf das Tumormikromilieu des EACs gezeigt werden. Dabei kam es zur verminderten Expression von Checkpoints und Anzahl TILs nach (Radio-) Chemotherapie. 3. Im Tumorzellkompartiment wurde die Rolle von Amplifikationen in ErbB-Rezeptor abhängigen Signalwegen durch FISH-Technik und Immunhistochemie evaluiert. Es fanden sich KRAS Amplifikationen in 17,1%, PIK3CA Amplifikationen in 5% sowie eine HER2/neu-Überexpression in 14,9% der untersuchten Tumore

    Rural income diversification in Ethiopia: Patterns, trends, and welfare impacts

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    Increased diversification of rural households into the rural non-farm economy is an important driver of economic growth and structural transformation in countries like Ethiopia where the vast majority of people live in rural areas and are largely dependent on seasonal agriculture. Some of the benefits of diversification include efficient utilization of asset endowments (e.g., labor during dry season) and reduction of risks. In this study we explore the: (i) patterns and trends of diversification, (ii) drivers of diversification including the association between rainfall risk/shocks and diversification, and (iii) welfare effects of diversification during the recent decade using three rounds of representative household data from the four main regions of Ethiopia. We used Cragg’s double-hurdle model, a method that considers the two-step decision making process in diversification (i.e., participation and extent of participation), to identify the determinants of diversification and a fixed-effect and instrumental variable (IV) approaches to understand the links between diversification and household welfare. The descriptive results show that rural households generally adopt a livelihood strategy dominated by farming and that the level of diversification has been stagnant over the period of analysis considered. More importantly, the vast majority of households continue to draw a substantial share of their income from crop production, followed by livestock. The income from non-farm activities accounts only between 17 percent and 23 percent of the total income. The econometrics results show that diversification is positively associated with credit access, membership in social insurance, ownership of mobile phone, relative measure of household wealth, and population density. Conversely, access to relatively large, fertile, and irrigable land discourages diversification into non-farm activities. The analysis on the association between rainfall risks and diversification indicates that rural households use income diversification both as risk mitigation and shock coping strategy. The results on the link between income diversification and household welfare indicate a positive association between diversification and household total consumption expenditure, dietary diversity score, and housing/roof quality. In sum, the results imply the need for a deliberate effort to expand the non-farm economy so as to tap its full potential for employment generation, income growth, and welfare improvements. A starting point could be for agricultural and rural development policies and investments to go beyond promotion of cereal crop production and facilitate participation in high value crop, livestock, aquaculture production. Incentivizing investments in value addition activities that can create and enrich upward and downward linkages in the midstream segment of agricultural value chains is another potential avenue to boost rural non-farm economy

    Model Diagnostics meets Forecast Evaluation: Goodness-of-Fit, Calibration, and Related Topics

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    Principled forecast evaluation and model diagnostics are vital in fitting probabilistic models and forecasting outcomes of interest. A common principle is that fitted or predicted distributions ought to be calibrated, ideally in the sense that the outcome is indistinguishable from a random draw from the posited distribution. Much of this thesis is centered on calibration properties of various types of forecasts. In the first part of the thesis, a simple algorithm for exact multinomial goodness-of-fit tests is proposed. The algorithm computes exact pp-values based on various test statistics, such as the log-likelihood ratio and Pearson\u27s chi-square. A thorough analysis shows improvement on extant methods. However, the runtime of the algorithm grows exponentially in the number of categories and hence its use is limited. In the second part, a framework rooted in probability theory is developed, which gives rise to hierarchies of calibration, and applies to both predictive distributions and stand-alone point forecasts. Based on a general notion of conditional T-calibration, the thesis introduces population versions of T-reliability diagrams and revisits a score decomposition into measures of miscalibration, discrimination, and uncertainty. Stable and efficient estimators of T-reliability diagrams and score components arise via nonparametric isotonic regression and the pool-adjacent-violators algorithm. For in-sample model diagnostics, a universal coefficient of determination is introduced that nests and reinterprets the classical R2R^2 in least squares regression. In the third part, probabilistic top lists are proposed as a novel type of prediction in classification, which bridges the gap between single-class predictions and predictive distributions. The probabilistic top list functional is elicited by strictly consistent evaluation metrics, based on symmetric proper scoring rules, which admit comparison of various types of predictions
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