Formal Multilevel Hierarchical Verification of Synchronous MOS Circuits

I have designed and implemented a system for the multilevel verification of synchronous MOS VLSI circuits. The system, called Silica Pithecus, accepts the schematic of an MOS circuit and a specification of the circuit's intended digital behavior. Silica Pithecus determines if the circuit meets its specification. If the circuit fails to meet its specification Silica Pithecus returns to the designer the reason for the failure. Unlike earlier verifiers which modelled primitives (e.g., transistors) as unidirectional digital devices, Silica Pithecus models primitives more realistically. Transistors are modelled as bidirectional devices of varying resistances, and nodes are modelled as capacitors. Silica Pithecus operates hierarchically, interactively, and incrementally. Major contributions of this research include a formal understanding of the relationship between different behavioral descriptions (e.g., signal, boolean, and arithmetic descriptions) of the same device, and a formalization of the relationship between the structure, behavior, and context of device. Given these formal structures my methods find sufficient conditions on the inputs of circuits which guarantee the correct operation of the circuit in the desired descriptive domain. These methods are algorithmic and complete. They also handle complex phenomena such as races and charge sharing. Informal notions such as races and hazards are shown to be derivable from the correctness conditions used by my methods.

Time-domain analysis of piezoelectric impedance-based structural health monitoring using multilevel wavelet decomposition

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Generating inclusive and sustainable growth: the role of policy and multilevel fiscal institutions

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A Multilevel Model with Time Series Components for the Analysis of Tribal Art Prices

In the present work we perform an econometric analysis of the Tribal art market. To this aim, we use a unique and original database that includes information on Tribal art market auctions worldwide from 1998 to 2011. In Literature, art prices are modelled through the hedonic regression model, a classic fixed-effect model. The main drawback of the hedonic approach is the large number of parameters, since, in general, art data include many categorical variables. In this work, we propose a multilevel model for the analysis of Tribal art prices that takes into account the influence of time on artwork prices. In fact, it is natural to assume that time exerts an influence over the price dynamics in various ways. Nevertheless, since the set of objects change at every auction date, we do not have repeated measurements of the same items over time. Hence, the dataset does not constitute a proper panel; rather, it has a two-level structure in that items, level-1 units, are grouped in time points, level-2 units. The main theoretical contribution is the extension of classical multilevel models to cope with the case described above. In particular, we introduce a model with time dependent random effects at the second level. We propose a novel specification of the model, derive the maximum likelihood estimators and implement them through the E-M algorithm. We test the finite sample properties of the estimators and the validity of the own-written R-code by means of a simulation study. Finally, we show that the new model improves considerably the fit of the Tribal art data with respect to both the hedonic regression model and the classic multilevel model.

Multilevel Analysis in Household Survey: An Application to Health Condition Data

The aim of this thesis is to apply multilevel regression model in context of household surveys. Hierarchical structure in this type of data is characterized by many small groups. In last years comparative and multilevel analysis in the field of perceived health have grown in size. The purpose of this thesis is to develop a multilevel analysis with three level of hierarchy for Physical Component Summary outcome to: evaluate magnitude of within and between variance at each level (individual, household and municipality); explore which covariates affect on perceived physical health at each level; compare model-based and design-based approach in order to establish informativeness of sampling design; estimate a quantile regression for hierarchical data. The target population are the Italian residents aged 18 years and older. Our study shows a high degree of homogeneity within level 1 units belonging from the same group, with an intraclass correlation of 27% in a level-2 null model. Almost all variance is explained by level 1 covariates. In fact, in our model the explanatory variables having more impact on the outcome are disability, unable to work, age and chronic diseases (18 pathologies). An additional analysis are performed by using novel procedure of analysis :"Linear Quantile Mixed Model", named "Multilevel Linear Quantile Regression", estimate. This give us the possibility to describe more generally the conditional distribution of the response through the estimation of its quantiles, while accounting for the dependence among the observations. This has represented a great advantage of our models with respect to classic multilevel regression. The median regression with random effects reveals to be more efficient than the mean regression in representation of the outcome central tendency. A more detailed analysis of the conditional distribution of the response on other quantiles highlighted a differential effect of some covariate along the distribution.

Arbitrary Waveform Multilevel Generator for High Voltage High Frequency Plasma Actuators

This dissertation presents the theory and the conducted activity that lead to the construction of a high voltage high frequency arbitrary waveform voltage generator. The generator has been specifically designed to supply power to a wide range of plasma actuators. The system has been completely designed, manufactured and tested at the Department of Electrical, Electronic and Information Engineering of the University of Bologna. The generator structure is based on the single phase cascaded H-bridge multilevel topology and is comprised of 24 elementary units that are series connected in order to form the typical staircase output voltage waveform of a multilevel converter. The total number of voltage levels that can be produced by the generator is 49. Each level is 600 V making the output peak-to-peak voltage equal to 28.8 kV. The large number of levels provides high resolution with respect to the output voltage having thus the possibility to generate arbitrary waveforms. Maximum frequency of operation is 20 kHz. A study of the relevant literature shows that this is the first time that a cascaded multilevel converter of such dimensions has been constructed. Isolation and control challenges had to be solved for the realization of the system. The biggest problem of the current technology in power supplies for plasma actuators is load matching. Resonant converters are the most used power supplies and are seriously affected by this problem. The manufactured generator completely solves this issue providing consistent voltage output independently of the connected load. This fact is very important when executing tests and during the comparison of the results because all measures should be comparable and not dependent from matching issues. The use of the multilevel converter for power supplying a plasma actuator is a real technological breakthrough that has provided and will continue to provide very significant experimental results.

Multilevel Latent Class Models with Dirichlet Mixing Distribution

Latent class analysis (LCA) and latent class regression (LCR) are widely used for modeling multivariate categorical outcomes in social sciences and biomedical studies. Standard analyses assume data of different respondents to be mutually independent, excluding application of the methods to familial and other designs in which participants are clustered. In this paper, we develop multilevel latent class model, in which subpopulation mixing probabilities are treated as random effects that vary among clusters according to a common Dirichlet distribution. We apply the Expectation-Maximization (EM) algorithm for model fitting by maximum likelihood (ML). This approach works well, but is computationally intensive when either the number of classes or the cluster size is large. We propose a maximum pairwise likelihood (MPL) approach via a modified EM algorithm for this case. We also show that a simple latent class analysis, combined with robust standard errors, provides another consistent, robust, but less efficient inferential procedure. Simulation studies suggest that the three methods work well in finite samples, and that the MPL estimates often enjoy comparable precision as the ML estimates. We apply our methods to the analysis of comorbid symptoms in the Obsessive Compulsive Disorder study. Our models' random effects structure has more straightforward interpretation than those of competing methods, thus should usefully augment tools available for latent class analysis of multilevel data.

Age and gender differences in health-related quality of life of children and adolescents in Europe: a multilevel analysis

OBJECTIVES: To determine age and gender differences in health-related quality of life (HRQOL) in children and adolescents across 12 European countries using a newly developed HRQOL measure (KIDSCREEN). METHODS: The KIDSCREEN-52 questionnaire was filled in by 21,590 children and adolescents aged 8-18 from 12 countries. We used multilevel regression analyses to model the hierarchical structure of the data. In addition, effect sizes were computed to test for gender differences within each age group. RESULTS: Children generally showed better HRQOL than adolescents (P < 0.001). While boys and girls had similar HRQOL at young age, girls' HRQOL declined more than boys' (P < 0.001) with increasing age, depending on the HRQOL scale. There was significant variation between countries both at the youngest age and for age trajectories. CONCLUSIONS: For the first time, gender and age differences in children's and adolescents' HRQOL across Europe were assessed using a comprehensive and standardised instrument. Gender and age differences exist for most HRQOL scales. Differences in HRQOL across Europe point to the importance of national contexts for youth's well-being.

Comparison of a traditional and a multilevel Cox Proportional Hazards model

Hierarchically clustered populations are often encountered in public health research, but the traditional methods used in analyzing this type of data are not always adequate. In the case of survival time data, more appropriate methods have only begun to surface in the last couple of decades. Such methods include multilevel statistical techniques which, although more complicated to implement than traditional methods, are more appropriate. ^ One population that is known to exhibit a hierarchical structure is that of patients who utilize the health care system of the Department of Veterans Affairs where patients are grouped not only by hospital, but also by geographic network (VISN). This project analyzes survival time data sets housed at the Houston Veterans Affairs Medical Center Research Department using two different Cox Proportional Hazards regression models, a traditional model and a multilevel model. VISNs that exhibit significantly higher or lower survival rates than the rest are identified separately for each model. ^ In this particular case, although there are differences in the results of the two models, it is not enough to warrant using the more complex multilevel technique. This is shown by the small estimates of variance associated with levels two and three in the multilevel Cox analysis. Much of the differences that are exhibited in identification of VISNs with high or low survival rates is attributable to computer hardware difficulties rather than to any significant improvements in the model. ^

Control of second-life hybrid battery energy storage system based on modular boost-multilevel buck converter

To fully utilize second-life batteries on the grid system, a hybrid battery scheme needs to be considered for several reasons: the uncertainty over using a single source supply chain for second-life batteries, the differences in evolving battery chemistry and battery configuration by different suppliers to strive for greater power levels, and the uncertainty of degradation within a second-life battery. Therefore, these hybrid battery systems could have widely different module voltage, capacity, and initial state of charge and state of health. In order to suitably integrate and control these widely different batteries, a suitable multimodular converter topology and an associated control structure are required. This paper addresses these issues proposing a modular boost-multilevel buck converter based topology to integrate these hybrid second-life batteries to a grid-tie inverter. Thereafter, a suitable module-based distributed control architecture is introduced to independently utilize each converter module according to its characteristics. The proposed converter and control architecture are found to be flexible enough to integrate widely different batteries to an inverter dc link. Modeling, analysis, and experimental validation are performed on a single-phase modular hybrid battery energy storage system prototype to understand the operation of the control strategy with different hybrid battery configurations.

Multilevel Governance and Accountability: Does Decentralization Promote Good Governance?

Today, the trend towards decentralization is far-reaching. Proponents of decentralization have argued that decentralization promotes responsive and accountable local government by shortening the distance between local representatives and their constituency. However, in this paper, I focus on the countervailing effect of decentralization on the accountability mechanism, arguing that decentralization, which increases the number of actors eligible for policy making and implementation in governance as a whole, may blur lines of responsibility, thus weakening citizens’ ability to sanction government in election. By using the ordinary least squares (OLS) interaction model based on historical panel data for 78 countries in the 2002 – 2010 period, I test the hypothesis that as the number of government tiers increases, there will be a negative interaction between the number of government tiers and decentralization policies. The regression results show empirical evidence that decentralization policies, having a positive impact on governance under a relatively simple form of multilevel governance, have no more statistically significant effects as the complexity of government structure exceeds a certain degree. In particular, this paper found that the presence of intergovernmental meeting with legally binding authority have a negative impact on governance when the complexity of government structure reaches to the highest level.

Use of posterior predictive assessments to evaluate model fit in multilevel logistic regression

Assessing the fit of a model is an important final step in any statistical analysis, but this is not straightforward when complex discrete response models are used. Cross validation and posterior predictions have been suggested as methods to aid model criticism. In this paper a comparison is made between four methods of model predictive assessment in the context of a three level logistic regression model for clinical mastitis in dairy cattle; cross validation, a prediction using the full posterior predictive distribution and two “mixed” predictive methods that incorporate higher level random effects simulated from the underlying model distribution. Cross validation is considered a gold standard method but is computationally intensive and thus a comparison is made between posterior predictive assessments and cross validation. The analyses revealed that mixed prediction methods produced results close to cross validation whilst the full posterior predictive assessment gave predictions that were over-optimistic (closer to the observed disease rates) compared with cross validation. A mixed prediction method that simulated random effects from both higher levels was best at identifying the outlying level two (farm-year) units of interest. It is concluded that this mixed prediction method, simulating random effects from both higher levels, is straightforward and may be of value in model criticism of multilevel logistic regression, a technique commonly used for animal health data with a hierarchical structure.

Changes In Chromatin Structure In Nih 3t3 Cells Induced By Valproic Acid And Trichostatin A.

Valproic acid (VPA) and trichostatin A (TSA) are known histone deacetylase inhibitors (HDACIs) with epigenetic activity that affect chromatin supra-organization, nuclear architecture, and cellular proliferation, particularly in tumor cells. In this study, chromatin remodeling with effects extending to heterochromatic areas was investigated by image analysis in non-transformed NIH 3T3 cells treated for different periods with different doses of VPA and TSA under conditions that indicated no loss of cell viability. Image analysis revealed chromatin decondensation that affected not only euchromatin but also heterochromatin, concomitant with a decreased activity of histone deacetylases and a general increase in histone H3 acetylation. Heterochromatin protein 1-α (HP1-α), identified immunocytochemically, was depleted from the pericentromeric heterochromatin following exposure to both HDACIs. Drastic changes affecting cell proliferation and micronucleation but not alteration in CCND2 expression and in ratios of Bcl-2/Bax expression and cell death occurred following a 48-h exposure of the NIH 3T3 cells particularly in response to higher doses of VPA. Our results demonstrated that even low doses of VPA (0.05 mM) and TSA (10 ng/ml) treatments for 1 h can affect chromatin structure, including that of the heterochromatin areas, in non-transformed cells. HP1-α depletion, probably related to histone demethylation at H3K9me3, in addition to the effect of VPA and TSA on histone H3 acetylation, is induced on NIH 3T3 cells. Despite these facts, alterations in cell proliferation and micronucleation, possibly depending on mitotic spindle defects, require a longer exposure to higher doses of VPA and TSA.

Matrix Metalloproteinases And Left Ventricular Function And Structure In Spinal Cord Injured Subjects.

Subjects with spinal cord injury (SCI) exhibit impaired left ventricular (LV) diastolic function, which has been reported to be attenuated by regular physical activity. This study investigated the relationship between circulating matrix metalloproteinases (MMPs) and tissue inhibitors of MMPs (TIMPs) and echocardiographic parameters in SCI subjects and the role of physical activity in this regard. Forty-two men with SCI [19 sedentary (S-SCI) and 23 physically-active (PA-SCI)] were evaluated by clinical, anthropometric, laboratory, and echocardiographic analysis. Plasmatic pro-MMP-2, MMP-2, MMP-8, pro-MMP-9, MMP-9, TIMP-1 and TIMP-2 levels were determined by enzyme-linked immunosorbent assay and zymography. PA-SCI subjects presented lower pro-MMP-2 and pro-MMP-2/TIMP-2 levels and improved markers of LV diastolic function (lower E/Em and higher Em and E/A values) than S-SCI ones. Bivariate analysis showed that pro-MMP-2 correlated inversely with Em and directly with E/Em, while MMP-9 correlated directly with LV mass index and LV end-diastolic diameter in the whole sample. Following multiple regression analysis, pro-MMP-2, but not physical activity, remained associated with Em, while MMP-9 was associated with LV mass index in the whole sample. These findings suggest differing roles for MMPs in LV structure and function regulation and an interaction among pro-MMP-2, diastolic function and physical activity in SCI subjects.

Growth Factor Stimulation Improves The Structure And Properties Of Scaffold-free Engineered Auricular Cartilage Constructs.

The reconstruction of the external ear to correct congenital deformities or repair following trauma remains a significant challenge in reconstructive surgery. Previously, we have developed a novel approach to create scaffold-free, tissue engineering elastic cartilage constructs directly from a small population of donor cells. Although the developed constructs appeared to adopt the structural appearance of native auricular cartilage, the constructs displayed limited expression and poor localization of elastin. In the present study, the effect of growth factor supplementation (insulin, IGF-1, or TGF-β1) was investigated to stimulate elastogenesis as well as to improve overall tissue formation. Using rabbit auricular chondrocytes, bioreactor-cultivated constructs supplemented with either insulin or IGF-1 displayed increased deposition of cartilaginous ECM, improved mechanical properties, and thicknesses comparable to native auricular cartilage after 4 weeks of growth. Similarly, growth factor supplementation resulted in increased expression and improved localization of elastin, primarily restricted within the cartilaginous region of the tissue construct. Additional studies were conducted to determine whether scaffold-free engineered auricular cartilage constructs could be developed in the 3D shape of the external ear. Isolated auricular chondrocytes were grown in rapid-prototyped tissue culture molds with additional insulin or IGF-1 supplementation during bioreactor cultivation. Using this approach, the developed tissue constructs were flexible and had a 3D shape in very good agreement to the culture mold (average error <400 µm). While scaffold-free, engineered auricular cartilage constructs can be created with both the appropriate tissue structure and 3D shape of the external ear, future studies will be aimed assessing potential changes in construct shape and properties after subcutaneous implantation.