Powertrain optimisation in a hybrid electric bus

This paper describes the use of a formal optimisation procedure to optimise a plug-in hybrid electric bus using two different case studies to meet two different performance criteria; minimum journey cost and maximum battery life. The approach is to choose a commercially available vehicle and seek to improve its performance by varying key design parameters. Central to this approach is the ability to develop a representative backward facing model of the vehicle in MATLAB/Simulink along with appropriate optimisation objective and penalty functions. The penalty functions being the margin by which a particular design fails to meet the performance specification. The model is validated against data collected from an actual vehicle and is used to estimate the vehicle performance parameters in a model-in-the-loop process within an optimisation routine. For the purposes of this paper, the journey cost/battery life over a drive cycle is optimised whilst other performance indices are met (or exceeded). Among the available optimisation methods, Powell's method and Simulated Annealing are adopted. The results show this method as a valid alternative modelling approach to vehicle powertrain optimisation. © 2012 IEEE.

Cooperative greedy pursuit strategies for sparse signal representation by partitioning

Cooperative Greedy Pursuit Strategies are considered for approximating a signal partition subjected to a global constraint on sparsity. The approach aims at producing a high quality sparse approximation of the whole signal, using highly coherent redundant dictionaries. The cooperation takes place by ranking the partition units for their sequential stepwise approximation, and is realized by means of i)forward steps for the upgrading of an approximation and/or ii) backward steps for the corresponding downgrading. The advantage of the strategy is illustrated by approximation of music signals using redundant trigonometric dictionaries. In addition to rendering stunning improvements in sparsity with respect to the concomitant trigonometric basis, these dictionaries enable a fast implementation of the approach via the Fast Fourier Transform

Association between body composition, circulating irisin and telomere length in healthy individuals and individuals with Type 2 diabetes

Aims: Obesity and Type 2 diabetes are associated with accelerated ageing. The underlying mechanisms behind this, however, are poorly understood. In this study, we investigated the association between circulating irisin - a novel my okine involved in energy regulation - and telomere length (TL) (a marker of aging) in healthy individuals and individuals with Type 2 diabetes. Methods: Eighty-two healthy people and 67 subjects with Type 2 diabetes were recruited to this cross-sectional study. Anthropometric measurements including body composition measured by biompedance were recorded. Plasma irisin was measured by ELISA on a fasted blood sample. Relative TL was determined using real-time PCR. Associations between anthropometric measures and irisin and TL were explored using Pearson’s bivariate correlations. Multiple regression was used to explore all the significant predictors of TL using backward elimination. Results: In healthy individuals chronological age was a strong negative predictor of TL (=0.552, p < 0.001). Multiple regression analysis using backward elimination (excluding age) revealed the greater relative TL could be predicted by greater total muscle mass(b = 0.046, p = 0.001), less visceral fat (b = =0.183, p < 0.001)and higher plasma irisin levels (b = 0.01, p = 0.027). There were no significant associations between chronological age, plasmairisin, anthropometric measures and TL in patients with Type 2diabetes (p > 0.1). Conclusion: These data support the view that body composition and plasma irisin may have a role in modulation of energy balance and the aging process in healthy individuals. This relationship is altered in individuals with Type 2 diabetes.

Strongly localized moving discrete dissipative breather-solitons in Kerr nonlinear media supported by intrinsic gain

We investigate the mobility of nonlinear localized modes in a generalized discrete Ginzburg-Landau-type model, describing a one-dimensional waveguide array in an active Kerr medium with intrinsic, saturable gain and damping. It is shown that exponentially localized, traveling discrete dissipative breather-solitons may exist as stable attractors supported only by intrinsic properties of the medium, i.e., in the absence of any external field or symmetry-breaking perturbations. Through an interplay by the gain and damping effects, the moving soliton may overcome the Peierls-Nabarro barrier, present in the corresponding conservative system, by self-induced time-periodic oscillations of its power (norm) and energy (Hamiltonian), yielding exponential decays to zero with different rates in the forward and backward directions. In certain parameter windows, bistability appears between fast modes with small oscillations and slower, large-oscillation modes. The velocities and the oscillation periods are typically related by lattice commensurability and exhibit period-doubling bifurcations to chaotically "walking" modes under parameter variations. If the model is augmented by intersite Kerr nonlinearity, thereby reducing the Peierls-Nabarro barrier of the conservative system, the existence regime for moving solitons increases considerably, and a richer scenario appears including Hopf bifurcations to incommensurately moving solutions and phase-locking intervals. Stable moving breathers also survive in the presence of weak disorder. © 2014 American Physical Society.

An integrated functional mapping and source localization platform for brain research

The premise of this dissertation is to create a highly integrated platform that combines the most current recording technologies for brain research through the development of new algorithms for three-dimensional (3D) functional mapping and 3D source localization. The recording modalities that were integrated include: Electroencephalography (EEG), Optical Topographic Maps (OTM), Magnetic Resonance Imaging (MRI), and Diffusion Tensor Imaging (DTI). This work can be divided into two parts: The first part involves the integration of OTM with MRI, where the topographic maps are mapped to both the skull and cortical surface of the brain. This integration process is made possible through the development of new algorithms that determine the probes location on the MRI head model and warping the 2D topographic maps onto the 3D MRI head/brain model. Dynamic changes of the brain activation can be visualized on the MRI head model through a graphical user interface. The second part of this research involves augmenting a fiber tracking system, by adding the ability to integrate the source localization results generated by commercial software named Curry. This task involved registering the EEG electrodes and the dipole results to the MRI data. Such Integration will allow the visualization of fiber tracts, along with the source of the EEG, in a 3D transparent brain structure. The research findings of this dissertation were tested and validated through the participation of patients from Miami Children Hospital (MCH). Such an integrated platform presented to the medical professionals in the form of a user-friendly graphical interface is viewed as a major contribution of this dissertation. It should be emphasized that there are two main aspects to this research endeavor: (1) if a dipole could be situated in time at its different positions, its trajectory may reveal additional information on the extent and nature of the brain malfunction; (2) situating such a dipole trajectory with respect to the fiber tracks could ensure the preservation of these fiber tracks (axons) during surgical interventions, preserving as a consequence these parts of the brain that are responsible for information transmission.

Three essays on labor liberalization and its effects on world economy

This dissertation consists of three theoretical essays on immigration, international trade and political economy. The first two essays analyze the political economy of immigration in developed countries. The third essay explores new ground on the effects of labor liberalization in developing countries. Trade economists have witnessed remarkable methodological developments in mathematical and game theoretical models during the last seventy years. This dissertation benefits from these advances to analyze economic issues related to immigration. The first essay applies a long run general equilibrium trade model similar to Krugman (1980), and blends it with the median voter ala-Mayer (1984) framework. The second essay uses a short run general equilibrium specific factor trade model similar to Jones (1975) and incorporates it with the median voter model similar to Benhabib (1997). The third essay employs a five stage game theoretical approach similar to Vogel (2007) and solves it by the method of backward induction. The first essay shows that labor liberalization is more likely to come about in societies that have more taste for varieties, and that workers and capital owners could share the same positive stance toward labor liberalization. In a dynamic model, it demonstrates that the median voter is willing to accept fewer immigrants in the first period in order to preserve her domestic political influence in the second period threatened by the naturalization of these immigrants. The second essay shows that the liberalization of labor depends on the host country's stock and distribution of capital, and the number of groups of skilled workers within each country. I demonstrate that the more types of goods both countries produce, the more liberal the host country is toward immigration. The third essay proposes a theory of free movement of goods and labor between two economies with imperfect labor contracts. The heart of my analysis lies in the determinants of talent development where individuals' decisions to emigrate are related to the fixed costs of emigration. Finally, free trade and labor affect income via an indirect effect on individuals' incentives to invest in the skill levels and a direct effect on the prices of goods.

Contemporary aspects of dividends: Before and during the financial crisis

The number of dividend paying firms has been on the decline since the popularity of stock repurchases in the 1980s, and the recent financial crisis has brought about a wave of dividend reductions and omissions. This dissertation examined the U.S. firms and American Depository Receipts that are listed on the U.S. equity exchanges according to their dividend paying history in the previous twelve quarters. While accounting for the state of the economy, the firm’s size, profitability, earned equity, and growth opportunities, it determines whether or not the firm will pay a dividend in the next quarter. It also examined the likelihood of a dividend change. Further, returns of firms were examined according to their dividend paying history and the state of the economy using the Fama-French three-factor model. Using forward, backward, and step-wise selection logistic regressions, the results show that firms with a history of regular and uninterrupted dividend payments are likely to continue to pay dividends, while firms that do not have a history of regular dividend payments are not likely to begin to pay dividends or continue to do so. The results of a set of generalized polytomous logistic regressions imply that dividend paying firms are more likely to reduce dividend payments during economic expansions, as opposed to recessions. Also the analysis of returns using the Fama-French three factor model reveals that dividend paying firms are earning significant abnormal positive returns. As a special case, a similar analysis of dividend payment and dividend change was applied to American Depository Receipts that trade on the NYSE, NASDAQ, and AMEX exchanges and are issued by the Bank of New York Mellon. Returns of American Depository Receipts were examined using the Fama-French two-factor model for international firms. The results of the generalized polytomous logistic regression analyses indicate that dividend paying status and economic conditions are also important for dividend level change of American Depository Receipts, and Fama-French two-factor regressions alone do not adequately explain returns for these securities.

A comprehensive study of bankruptcy prediction: Accounting ratios, market variables, and microstructure

Bankruptcy prediction has been a fruitful area of research. Univariate analysis and discriminant analysis were the first methodologies used. While they perform relatively well at correctly classifying bankrupt and nonbankrupt firms, their predictive ability has come into question over time. Univariate analysis lacks the big picture that financial distress entails. Multivariate discriminant analysis requires stringent assumptions that are violated when dealing with accounting ratios and market variables. This has led to the use of more complex models such as neural networks. While the accuracy of the predictions has improved with the use of more technical models, there is still an important point missing. Accounting ratios are the usual discriminating variables used in bankruptcy prediction. However, accounting ratios are backward-looking variables. At best, they are a current snapshot of the firm. Market variables are forward-looking variables. They are determined by discounting future outcomes. Microstructure variables, such as the bid-ask spread, also contain important information. Insiders are privy to more information that the retail investor, so if any financial distress is looming, the insiders should know before the general public. Therefore, any model in bankruptcy prediction should include market and microstructure variables. That is the focus of this dissertation. The traditional models and the newer, more technical models were tested and compared to the previous literature by employing accounting ratios, market variables, and microstructure variables. Our findings suggest that the more technical models are preferable, and that a mix of accounting and market variables are best at correctly classifying and predicting bankrupt firms. Multi-layer perceptron appears to be the most accurate model following the results. The set of best discriminating variables includes price, standard deviation of price, the bid-ask spread, net income to sale, working capital to total assets, and current liabilities to total assets.

Risk factors and associations for hepatitis C infection among Hispanic/Latino intravenous drug users in Miami-Dade County, Florida

Hepatitis C infection (HCV) continues to disproportionately affect Hispanics/Latinos in the United States. Hispanic/Latino intravenous drug users (IDUs), because of their risky injection and sexual behaviors, are prone to HCV infection and rapid transmission of the virus to others via several routes. With a prevalence rate of approximately 75% among IDUs, it is imperative that transmission of HCV be prevented in this population. This study aims to examine the associations between demographic, injection and sexual risk factors to HCV infection in a group Hispanic/Latino IDUs in Miami-Dade County, Florida. Preliminary unadjusted results in this sample reveal that age (OR=4.592, p=0.004), weekly injection (OR=5.171, p=0.000), daily injection frequency (OR=3.856, p=0.000) and use of a dirty needle (OR=2.320, p= 0.006) were all significantly associated with HCV infection. Being born outside the U.S. was significantly negatively associated with HCV infection (OR=0.349, p=0.004). Additionally, having two or more sex partners in the past three months (OR=0.472, p=0.014) was negatively associated with HCV infection. After adjusting for all other variables, older age (AOR=7.470, p=0.006), weekly injection (AOR=3.238, p=0.007) and daily injection frequency (AOR=2.625, p=0.010) were all significantly associated with HCV infection. Being born outside the U.S. (AOR=0.369, p=0.019) was a significant protective factor for HCV infection, along with having two or more sex partners in the past three months (AOR=0.481, p=0.037). When analyzing the significant variables in a backward regression model, having 2 or more sex partners in the past three months was not significant at the p

Are marginalized women being left behind? A population-based study of institutional deliveries in Karnataka, India

Background While India has made significant progress in reducing maternal mortality, attaining further declines will require increased skilled birth attendance and institutional delivery among marginalized and difficult to reach populations. Methods A population-based survey was carried out among 16 randomly selected rural villages in rural Mysore District in Karnataka, India between August and September 2008. All households in selected villages were enumerated and women with children 6 years of age or younger underwent an interviewer-administered questionnaire on antenatal care and institutional delivery. Results Institutional deliveries in rural areas of Mysore District increased from 51% to 70% between 2002 and 2008. While increasing numbers of women were accessing antenatal care and delivering in hospitals, large disparities were found in uptake of these services among different castes. Mothers belonging to general castes were almost twice as likely to have an institutional birth as compared to scheduled castes and tribes. Mothers belonging to other backward caste or general castes had 1.8 times higher odds (95% CI: 1.21, 2.89) of having an institutional delivery as compared to scheduled castes and tribes. In multivariable analysis, which adjusted for inter- and intra-village variance, Below Poverty Line status, caste, and receiving antenatal care were all associated with institutional delivery. Conclusion The results of the study suggest that while the Indian Government has made significant progress in increasing antenatal care and institutional deliveries among rural populations, further success in lowering maternal mortality will likely hinge on the success of NRHM programs focused on serving marginalized groups. Health interventions which target SC/ST may also have to address both perceived and actual stigma and discrimination, in addition to providing needed services. Strategies for overcoming these barriers may include sensitization of healthcare workers, targeted health education and outreach, and culturally appropriate community-level interventions. Addressing the needs of these communities will be critical to achieving Millennium Development Goal Five by 2015.

Algorithms for efficient transaction management and consistent queries in client -server semantic object-oriented parallel databases

Large read-only or read-write transactions with a large read set and a small write set constitute an important class of transactions used in such applications as data mining, data warehousing, statistical applications, and report generators. Such transactions are best supported with optimistic concurrency, because locking of large amounts of data for extended periods of time is not an acceptable solution. The abort rate in regular optimistic concurrency algorithms increases exponentially with the size of the transaction. The algorithm proposed in this dissertation solves this problem by using a new transaction scheduling technique that allows a large transaction to commit safely with significantly greater probability that can exceed several orders of magnitude versus regular optimistic concurrency algorithms. A performance simulation study and a formal proof of serializability and external consistency of the proposed algorithm are also presented.^ This dissertation also proposes a new query optimization technique (lazy queries). Lazy Queries is an adaptive query execution scheme which optimizes itself as the query runs. Lazy queries can be used to find an intersection of sub-queries in a very efficient way, which does not require full execution of large sub-queries nor does it require any statistical knowledge about the data.^ An efficient optimistic concurrency control algorithm used in a massively parallel B-tree with variable-length keys is introduced. B-trees with variable-length keys can be effectively used in a variety of database types. In particular, we show how such a B-tree was used in our implementation of a semantic object-oriented DBMS. The concurrency control algorithm uses semantically safe optimistic virtual "locks" that achieve very fine granularity in conflict detection. This algorithm ensures serializability and external consistency by using logical clocks and backward validation of transactional queries. A formal proof of correctness of the proposed algorithm is also presented. ^

An examination of Bernard Connor's The History of Poland (1698) and its depiction of the political, religious, and cultural history of the Polish-Lithuanian commonwealth

Connor was an Irish-born member of seventeenth-century English medical society who made an impact on medicine through his use of anatomy. This forward-thinking scientist also worked as a court physician for the Polish king John III Sobieski (1629- 1696) and published a history of that country. This thesis will examine Bernard Connor's 1698 publication The History of Poland to show that the Commonwealth was considered a vision of a progressive European parliamentary government that could serve as a model for a struggling English parliamentary government, thus supporting Larry Wolff and Maria Todorova's vision of the later eighteenth-century creation of the idea of a backward "eastern Europe."

Caratterizzazione, analisi a ritroso e di stabilità attuale di uno scorrimento traslativo in Marnoso Arenacea (Casola Valsenio, RA)

Il lavoro di tesi consiste nella caratterizzazione, nell’analisi a ritroso e di stabilità attuale di un fenomeno franoso avvenuto a Casola Valsenio, in provincia di Ravenna. La caratterizzazione è comprensiva di analisi geomorfologica dell’area, indagine sismo-stratigrafica e indagine geotecnica di laboratorio. Quindi è stato definito il meccanismo di rottura della frana e sono stati cartografati gli elementi morfologici costituenti l’area di frana. L’indagine geofisica si basa su tecniche ad onde di superficie e include misure tromografiche di rumore sismico ambientale e misure attive multicanale. Queste forniscono, rispettivamente, le curve H/V e gli spettri di velocità di fase e di gruppo, dalle quali è possibile ricavare informazioni di carattere stratigrafico. La caratterizzazione fisico meccanica del materiale pelitico marnoso, prelevato sul piano di scorrimento basale, include analisi granulometrica, determinazione dei limiti di consistenza e test di taglio anulare per ottenere il valore di angolo di attrito residuo. Le informazioni ottenute dalle indagini hanno consentito di definire il modello geologico tecnico del fenomeno, che viene rappresentato rispetto a quattro sezioni, tre relative alla situazione attuale e una relativa al versante prefrana. Sulla base di questi sono state condotte delle analisi a ritroso, che hanno consentito di ricavare le condizioni idrauliche del versante al momento della rottura, per differenti combinazioni di geometria del cuneo e diagramma di spinta dell’acqua. Grazie ai risultati ottenuti in modalità backward, sono state effettuate le analisi di stabilità della scarpata attuale, aventi lo scopo di determinare la distanza orizzontale tra scarpata e frattura di trazione che determinerebbe una situazione di instabilità. Infine sono state condotte analisi di sensitività rispetto ai parametri geometrici del cuneo, di resistenza del materiale e di riempimento idraulico della frattura dii trazione.

Riconoscimento real-time di gesture tramite tecniche di machine learning

Il riconoscimento delle gesture è un tema di ricerca che sta acquisendo sempre più popolarità, specialmente negli ultimi anni, grazie ai progressi tecnologici dei dispositivi embedded e dei sensori. Lo scopo di questa tesi è quello di utilizzare alcune tecniche di machine learning per realizzare un sistema in grado di riconoscere e classificare in tempo reale i gesti delle mani, a partire dai segnali mioelettrici (EMG) prodotti dai muscoli. Inoltre, per consentire il riconoscimento di movimenti spaziali complessi, verranno elaborati anche segnali di tipo inerziale, provenienti da una Inertial Measurement Unit (IMU) provvista di accelerometro, giroscopio e magnetometro. La prima parte della tesi, oltre ad offrire una panoramica sui dispositivi wearable e sui sensori, si occuperà di analizzare alcune tecniche per la classificazione di sequenze temporali, evidenziandone vantaggi e svantaggi. In particolare, verranno considerati approcci basati su Dynamic Time Warping (DTW), Hidden Markov Models (HMM), e reti neurali ricorrenti (RNN) di tipo Long Short-Term Memory (LSTM), che rappresentano una delle ultime evoluzioni nel campo del deep learning. La seconda parte, invece, riguarderà il progetto vero e proprio. Verrà impiegato il dispositivo wearable Myo di Thalmic Labs come caso di studio, e saranno applicate nel dettaglio le tecniche basate su DTW e HMM per progettare e realizzare un framework in grado di eseguire il riconoscimento real-time di gesture. Il capitolo finale mostrerà i risultati ottenuti (fornendo anche un confronto tra le tecniche analizzate), sia per la classificazione di gesture isolate che per il riconoscimento in tempo reale.

Biomechanical modeling of parotid glands morphing in head & neck radiation therapy treatments

Durante i trattamenti radioterapici dei pazienti oncologici testa-collo, le ghiandole parotidee (PGs) possono essere indebitamente irradiate a seguito di modificazioni volumetriche-spaziali inter/intra-frazione causate da fattori quali il dimagrimento, l’esposizione a radiazioni ionizzanti ed il morphing anatomico degli organi coinvolti nelle aree d’irraggiamento. Il presente lavoro svolto presso la struttura di Fisica Medica e di Radioterapia Oncologica dell’A.O.U di Modena, quale parte del progetto di ricerca del Ministero della Salute (MoH2010, GR-2010-2318757) “ Dose warping methods for IGRT and Adaptive RT: dose accumulation based on organ motion and anatomical variations of the patients during radiation therapy treatments ”, sviluppa un modello biomeccanico in grado di rappresentare il processo di deformazione delle PGs, considerandone la geometria, le proprietà elastiche e l'evoluzione durante il ciclo terapeutico. Il modello di deformazione d’organo è stato realizzato attraverso l’utilizzo di un software agli elementi finiti (FEM). Molteplici superfici mesh, rappresentanti la geometria e l’evoluzione delle parotidi durante le sedute di trattamento, sono state create a partire dai contorni dell’organo definiti dal medico radioterapista sull’immagine tomografica di pianificazione e generati automaticamente sulle immagini di setup e re-positioning giornaliere mediante algoritmi di registrazione rigida/deformabile. I constraints anatomici e il campo di forze del modello sono stati definiti sulla base di ipotesi semplificative considerando l’alterazione strutturale (perdita di cellule acinari) e le barriere anatomiche dovute a strutture circostanti. L’analisi delle mesh ha consentito di studiare la dinamica della deformazione e di individuare le regioni maggiormente soggette a cambiamento. Le previsioni di morphing prodotte dal modello proposto potrebbero essere integrate in un treatment planning system per metodiche di Adaptive Radiation Therapy.