Miracle-dz/UniFAR-FTUs huggingface dataset:
Krylov Projection Methods for Model Reduction

This dissertation focuses on e ciently forming reduced-order models for large, linear dynamic systems. Projections onto unions of Krylov subspaces lead to a class of reducedorder models known as rational interpolants. The cornerstone of this dissertation is a collection of theory relating Krylov projection to rational interpolation. Based on this theoretical framework, three algorithms for model reduction are proposed. The rst algorithm, dual rational Arnoldi, is a numerically reliable approach involving orthogonal projection matrices. The second, rational Lanczos, is an e cient generalization of existing Lanczos-based methods. The third, rational power Krylov, avoids orthogonalization and is suited for parallel or approximate computations. The performance of the three algorithms is compared via a combination of theory and examples. Independent of the precise algorithm, a host of supporting tools are also developed to form a complete model-reduction package. Techniques for choosing the matching frequencies, estimating the modeling error, insuring the model's stability, treating multiple-inputmultiple-output systems, implementing parallelism, and avoiding a need for exact factors of large matrix pencils are all examined to various degrees. iii DEDICATION To my wife, Kimberly. iv ACKNOWLEDGMENTS I would like to thank all those who supported me throughout my doctoral studies. Foremost on this list are my advisors, Professors Kyle Gallivan and Paul Van Dooren. Paul deserves the credit for starting me on my work in numerical linear algebra. His insights showed me what an interesting eld it can be. Many thanks go to Kyle for his support through the latter years of my doctoral research. His encouragement and humor are much appreciated. I also thank Drs. Danny Sorensen, Steve Ashby and Eli Chiprout for working with me at di erent times over the past three years. Each was an excellent host who contributed signi cantly to my education. Danny played a key role in my introduction to iterative Krylov methods. Steve pointed me in the direction of Davidson's method, an approach that implicitly touches many parts of this dissertation. Eli patiently led me through the basics of circuit analysis and asked many stimulating questions. My gratitude also goes out to my examination committee, Professors Bassam Bamieh, Farid Najm and M. Pai, for their time and comments. Professors Bamieh and Najm also deserve thanks for providing hours of classroom instruction. Finally, I thank the Department of Energy for its nancial support. This dissertation was supported in part by the Computational Science Graduate Fellowship Program of the O ce of Scienti c Computing in the Department of Energy. v TABLE OF CONTENTS CHAPTER PAGE
Suppression of the immune response in C3H/HeJ mice by protein-free lipopolysaccharides

The experiments described herein demonstrate the plaque-forming cell response of C3H/HeJ mice can be suppressed by a Boivin type lipopolysaccharide (LPS) and a deproteinized glycolipid. Suppression was observed both in vivo and in vitro, and could be transferred to normal cells in coculture experiments. This newly discovered effect of LPS in C3H/HeJ mice indicates that the adjuvant and inhibitory action of LPS may be distinct phenomena which are under different genetic regulation. Thus, the C3H/HeJ strain provides a convenient animal model for study of immunosuppression independent of the adjuvant effect.
A Framework for Privacy-Preserving Data Publishing Across Multiple Non-Colluding Adversaries

With the proliferation of online services there has been an increasing interest in distributing private user data to different third-party agents. The collection and storage of user data raises privacy considerations that often constrain user data sharing. Most work in privacy-aware data sharing has considered disclosing privacy preserving summaries of data that preserve the aggregate information about the data, but hide the individual user information. However, there are applications, including online advertising and crowdsourcing markets, where detailed and fine-grained information must be published. In this paper we consider a different data sharing paradigm where we are required to distribute a dataset to multiple third-parties. In particular, we address the problem of privacy-aware data partitioning, namely, the problem of splitting a sensitive dataset among k untrusted parties (adversaries). The goal is to maximize the overall utility derived by partitioning and distributing the dataset, while minimizing the total amount of sensitive information disclosed. More specifically, the data should be partitioned so that a third party cannot draw additional inferences about the private information, by linking together multiple pieces of information released to it. We formally define the problem of privacyaware data partitioning across k untrusted parties under the assumption of no collusion, and propose a novel data sharing scheme that minimizes the inferences each party can draw. We show that solving the problem is, in general, NP-hard, but for specific families of information disclosure functions, good approximate solutions can be found using relaxation techniques. Finally, we present a greedy randomized local search algorithm for solving the problem for generic families of information disclosure functions and provide an experimental evaluation of the different techniques presented in the paper.
The Algorithm of Objective Association Rules Mining Based on Binary

This paper proposes an algorithm of objective association rules used in data mining, which is suitable for mining some potential rules related to the given object from large data warehouse. The basic principle of algorithm is that the association rules were formed according to this especial information, which is mined with binary logic "and" operation from many attribute-values of database, where data have been expressed by binary. The theory of algorithm is quite simple. It is feasible and efficient to execute the algorithm. It is a practical significance to apply to the algorithm in some applicable domains to search especial objective association rules.
Numerical and experimental modeling of subnanosecond plasma closing switches in gases

In this paper, a 2D Finite Element Time Domain (FETD) model is presented for analyzing sub nanosecond plasma closing switches in gases, based on the Matlab Partial Differential Equation (PDE) toolbox. We will present the basic features of the model, as well as the results of validation studies on simple problems such as switch closure in an ideal, infinite, conically symmetric test volume. The physical model is then modified to simulate a test cell that had been previously used to collect experimental data. The dynamic channel current and its rate of the switch were evaluated based on the numerical model for different gases in different pressure regimes. The dynamics of the switch closure are greatly affected by the gas species and pressure used for insulation in the experiment.
Numerical Simulation and Role of Noise in the Cahn-Hilliard-Cook Equation below the Critical Dimension

Introducing stochastic or thermal noise into partial differential equations that would otherwise be deterministic is a useful technique for the analysis of ensemble simulations. It can also aid the unfreezing of structural growth barriers that occur in spatial growth systems. This article presents some modelling experiments using Cook’s noise term in the Cahn-Hilliard-Cook equation simulated on multi-dimensional spatial meshes. We show that below the critical dimension noise is actually necessary to enable long-term spatial growth behaviours that are sufficiently driven by surface tension effects in higher dimensions. We also discuss numerical methods for the study using finite differecing techniques.
Attenuated Neurodegenerative Disease Phenotype in Tau Transgenic Mouse Lacking Neurofilaments

Previous studies have shown that transgenic (Tg) mice overexpressing human tau protein develop filamentous tau aggregates in the CNS. The most abundant tau aggregates are found in spinal cord and brainstem in which they colocalize with neurofilaments (NFs) as spheroids in axons. To elucidate the role of NF subunit proteins in tau aggregate formation and to test the hypothesis that NFs are pathological chaperones in the formation of intraneuronal tau inclusions, we crossbred previously described tau (T44) Tg mice overexpressing the smallest human tau isoform with knock-out mice devoid of NFL (NFL−/−) or NFH (NFH−/−). Depletion of NF subunit proteins from the T44 mice (i.e., T44;NFL−/− and T44;NFH−/−), in particular NFL, resulted in a dramatic decrease in the total number of tau-positive spheroids in spinal cord and brainstem. Concomitant with the reduction in spheroid number, the bigenic mice showed delayed accumulation of insoluble tau protein in the CNS, increased viability, reduced weight loss, and improved behavioral phenotype when compared with the single T44 Tg mice. These results imply that NFs are pathological chaperones in the development of tau spheroids and suggest a role for NFs in the pathogenesis of neurofibrillary tau lesions in neurodegenerative disorders that contain both NFs and tau proteins.
Optimization of bodies with locally periodic microstructure by varying the periodicity pattern

This paper describes a numerical method to optimize elastic bodies featuring a locally periodic microscopic pattern. A new idea, of optimizing the periodicity cell itself, is considered. In previously published works, the authors have found that optimizing the shape and topology of the model hole gives a limited flexibility to the microstructure for adapting to the macroscopic loads. In the present study the periodicity cell varies during the optimization process, thus allowing the microstructure to adapt freely to the given loads. Our approach makes the link between the microscopic level and the macroscopic one. Two-dimensional linearly elastic bodies are considered, however the same techniques can be applied to three-dimensional bodies. Homogenization theory is used to describe the macroscopic (effective) elastic properties of the body. Numerical examples are presented, in which a cantilever is optimized for different load cases, one of them being multi-load. The problem is numerically heavy, since the optimization of the macroscopic problem is performed by optimizing in simultaneous hundreds or even thousands of periodic structures, each one using its own finite element mesh on the periodicity cell. Parallel computation is used in order to alleviate the computational burden.
A Brain Centred View of Psychiatric Comorbidity in Tinnitus: From Otology to Hodology

Introduction. Comorbid psychiatric disorders are frequent among patients affected by tinnitus. There are mutual clinical influences between tinnitus and psychiatric disorders, as well as neurobiological relations based on partially overlapping hodological and neuroplastic phenomena. The aim of the present paper is to review the evidence of alterations in brain networks underlying tinnitus physiopathology and to discuss them in light of the current knowledge of the neurobiology of psychiatric disorders. Methods. Relevant literature was identified through a search on Medline and PubMed; search terms included tinnitus, brain, plasticity, cortex, network, and pathways. Results. Tinnitus phenomenon results from systemic-neurootological triggers followed by neuronal remapping within several auditory and nonauditory pathways. Plastic reorganization and white matter alterations within limbic system, arcuate fasciculus, insula, salience network, dorsolateral prefrontal cortex, auditory pathways, ffrontocortical, and thalamocortical networks are discussed. Discussion. Several overlapping brain network alterations do exist between tinnitus and psychiatric disorders. Tinnitus, initially related to a clinicoanatomical approach based on a cortical localizationism, could be better explained by an holistic or associationist approach considering psychic functions and tinnitus as emergent properties of partially overlapping large-scale neural networks.
Managing Hybrid Main Memories with a Page-Utility Driven Performance Model

Hybrid memory systems comprised of dynamic random access memory (DRAM) and non-volatile memory (NVM) have been proposed to exploit both the capacity advantage of NVM and the latency and dynamic energy advantages of DRAM. An important problem for such systems is how to place data between DRAM and NVM to improve system performance. In this paper, we devise the first mechanism, called UBM (page Utility Based hybrid Memory management), that systematically estimates the system performance benefit of placing a page in DRAM versus NVM and uses this estimate to guide data placement. UBM’s estimation method consists of two major components. First, it estimates how much an application’s stall time can be reduced if the accessed page is placed in DRAM. To do this, UBM comprehensively considers access frequency, row buffer locality, and memory level parallelism (MLP) to estimate the application’s stall time reduction. Second, UBM estimates how much each application’s stall time reduction contributes to overall system performance. Based on this estimation method, UBM can determine and place the most critical data in DRAM to directly optimize system performance. Experimental results show that UBM improves system performance by 14% on average (and up to 39%) compared to the best of three state-of-the-art mechanisms for a large number of data-intensive workloads from the SPEC CPU2006 and Yahoo Cloud Serving Benchmark (YCSB) suites.
Organizational behavior: linking individuals and groups to organizational contexts.

THE ORGANIZATIONAL CONTEXT AS AN INFLUENCE ON GROUPS AND INDIVIDUALS . 198 Context as Opportunity and Constraint 198 Context as a Distal or Proximate Influence . 201 Context as Similar and Dissimilar 205 WHEN CONTEXTS HAVE MINIMAL INFLUENCE . 208 INDIVIDUALS AND GROUPS AS INFLUENCES ON ORGANIZATIONAL CONTEXTS 209 Powerful Individuals as an Influence on Organizations 210 Powerful Groups as an Influence on Organizations 215 A'dra;���ti! �;. ��������: . ���. �����:. ���. �. ���. �����. ��. ���. ������. �� 215 THE INTERACTIONS OF INDIVIDUALS AND GROUPS WITH THEIR ORGANIZATIONAL CONTEXTS . 217 The Homeless 218 Air Disaster 218 Nuclear Power Plant 219 HOW CAN WE PUT ORGANIZATIONS BACK INTO ORGANIZATIONAL BEHAVIOR? 220 Methodological Implications 220 Substantive Implications 222
Efficient simulation of systems with random uncertainty using interpolation

Formulas for interpolating between probability density and mass functions in spaces of arbitrary dimensionality are presented. These formulas are intended to be an alternative to repeating costly Monte Carlo simulations of systems with random uncertainty when some of the deterministic parameters are changed. It is found that the given formulas produce accurate results even with relatively coarse meshes. As the mesh is refined, the accuracy of the interpolated quantities increases; accordingly, in addition to the more complicated and robust interpolation formulas meant for the case of a coarse mesh, simplified versions that result in good accuracy with a fine mesh are also presented. Savings in computational effort up to a factor of one hundred are common even with the more complicated formulas, indicating that interpolation is a lucrative alternative to Monte Carlo simulation when the complete probability distribution, as opposed to only the low-order statistics, is needed. <<ETX>>
Survival extrapolation using the poly-Weibull model

Recent studies of (cost-) effectiveness in cardiothoracic transplantation have required estimation of mean survival over the lifetime of the recipients. In order to calculate mean survival, the complete survivor curve is required but is often not fully observed, so that survival extrapolation is necessary. After transplantation, the hazard function is bathtub-shaped, reflecting latent competing risks which operate additively in overlapping time periods. The poly-Weibull distribution is a flexible parametric model that may be used to extrapolate survival and has a natural competing risks interpretation. In addition, treatment effects and subgroups can be modelled separately for each component of risk. We describe the model and develop inference procedures using freely available software. The methods are applied to two problems from cardiothoracic transplantation.
Walker Parameter for Mean Stress Correction in Fatigue Testing of Al-7%Si-Mg Alloy Castings

In this study, performance of two existing Walker parameter estimation models has been investigated. Results show that those developed mainly for steel did not provide reasonable fits to experimental Walker parameters for fatigue data for Al-7%Si-Mg alloy castings in the literature. A strong relationship between the Walker parameter and the structural quality, quantified by the quality index, QT, was observed and an empirical equation to estimate the Walker parameter for these alloys was developed. These findings indicate that the Walker parameter is not an intrinsic material property and the structural quality of the specimens must be taken into account for mean stress correction in fatigue testing.
Positive Emotion and Impulsivity in Individuals with Bipolar I Disorder

of a dissertation at the University of Miami. Dissertation supervised by Professor Charles S. Carver. No. of pages in text. (200) Impulsivity as a symptom during mania is well documented, but less is known about the driving factors behind these impulsive acts. Perhaps this is because impulsivity is a term that encompasses multiple facets. There is evidence for a type of impulsivity in which extreme sensitivity to positive affective states can influence cognitive processes, such as error detection and identification of threatening cues. This can ultimately lead to engagement in impulsive actions during elevated mood states. Among people who are vulnerable to mania, positive moods have larger or more pervasive effects than they have on other people. While there is more conclusive evidence of impulsiveness among persons with BD (Bipolar Disorder) during mania, as compared to euthymia, it is less clear what specific mechanisms or mania symptoms perpetuate this effect. This study examined the possibility that positive emotion creates a greater processing bias among persons with BD than among other persons, such that neutral and negative stimuli are perceived less negatively. This study utilized multiple methods to measure the emotional response to threat--the motivational component with measurement of the affectmodulated eyeblink startle response, the arousal component with measurement of skin conductance levels, and the explicit appraisal component of emotional experience with self-report mood ratings. Twenty-two participants with BD and 25 control participants viewed a series of valenced pictures (negative, positive, neutral), underwent a cognitive speed task to induce a positive mood, and then viewed another series of valenced pictures. Acoustic startle probes were paired with the pictures at 2500ms and 4500ms. Skin conductance tonic levels, eyeblink startle amplitude, and eyeblink latency times were measured continuously through the laboratory session. BD participants had lower SCL tonic levels to the negative stimuli after the mood induction, compared to control participants. There was no group difference in eyeblink amplitude or in eyeblink latency. Several limitations, including issues with study methodology, recruitment bias, and validity of the IAPS stimuli, were reviewed. Future directions for research and clinical implications were discussed.
Stem Cell Mediation of Functional Recovery after Stroke in the Rat

Background Regenerative strategies of stem cell grafting have been demonstrated to be effective in animal models of stroke. In those studies, the effectiveness of stem cells promoting functional recovery was assessed by behavioral testing. These behavioral studies do, however, not provide access to the understanding of the mechanisms underlying the observed functional outcome improvement. Methodology/Principal Findings In order to address the underlying mechanisms of stem cell mediated functional improvement, this functional improvement after stroke in the rat was investigated for six months after stroke by use of fMRI, somatosensory evoked potentials by electrophysiology, and sensorimotor behavior testing. Stem cells were grafted ipsilateral to the ischemic lesion. Rigorous exclusion of spontaneous recovery as confounding factor permitted to observe graft-related functional improvement beginning after 7 weeks and continuously increasing during the 6-month observation period. The major findings were i) functional improvement causally related to the stem cells grafting; ii) tissue replacement can be excluded as dominant factor for stem cell mediated functional improvement; iii) functional improvement occurs by exclusive restitution of the function in the original representation field, without clear contributions from reorganization processes, and iv) stem cells were not detectable any longer after six months. Conclusions/Significance A delayed functional improvement due to stem cell implantation has been documented by electrophysiology, fMRI and behavioral testing. This functional improvement occurred without cells acting as a tissue replacement for the necrotic tissue after the ischemic event. Combination of disappearance of grafted cells after six months on histological sections with persistent functional recovery was interpreted as paracrine effects by the grafted stem cells being the dominant mechanism of cell activity underlying the observed functional restitution of the original activation sites. Future studies will have to investigate whether the stem cell mediated improvement reactivates the original representation target field by using original connectivity pathways or by generating/activating new ones for the stimulus.
Combining Market and Accounting-Based Models for Credit Scoring Using a Classification Scheme Based on Support Vector Machines

Combination of option-based model with accounting data for credit risk model.Application of market model to non-listed firms.Use of a novel additive support vector machines model. Credit risk rating is an important issue for both financial institutions and companies, especially in periods of economic recession. There are many different approaches and methods which have been developed over the years. The aim of this paper is to create a credit risk rating model, using a machine learning methodology that combines accounting data with the option-based approach of Black, Scholes, and Merton. The model is built on data for companies listed in the Greek stock exchange, but it is also shown to provide accurate results for non-listed firms as well. Linear and nonlinear support vector machines are used for model building, as well as an innovative additive modeling approach, which enables the construction of comprehensible and accurate credit scoring models.
Motion Control and Performance Evaluation of a Magnetic-Geared Dual-Rotor Motor in Hybrid Powertrain

The magnetic-geared dual-rotor motor (MGDRM) has been proposed as a power split device for several years, but there is not an evaluation work for an MGDRM in a real hybrid powertrain so far. As a pilot demo, an MGDRM-based hybrid powertrain with a real engine is built and tested in a real hybrid test bench. The closed-loop speed control is developed for the MGDRM, with which two pragmatic functions of the hybrid powertrain are realized by the MGDRM. First, the engine can be started by the MGDRM outer rotor no matter whether the vehicle is parked or traveling. Second, the torque coordination function of the MGDRM can help the engine to stabilize at a fixed work situation. This feature is the basement to adjust the operation and efficiency of engine. The power conversion efficiency map of the MGDRM is tested, based on which the performance of the power split in different operating situations can be evaluated.