In this work we calculate the binding energies and root-mean-square radii for A−body nuclear bound state systems, where A ≥ 3. To study three−body systems, we employ the three−dimensional differential Faddeev equations with nucleon-nucleon semi-realistic potentials. The equations are solved numerically. For this purpose, the equations are transformed into an eigenvalue equation via the orthogonal collocation procedure using triquintic Hermite splines. The resulting eigenvalue equation is solved using the Restarted Arnoldi Algorithm. Ground state binding energies of the 3H nucleus are determined. For A > 3, the Potential Harmonic Expansion Method is employed. Using this method, the Schr¨odinger equation is transformed into coupled Faddeev-like equations. The Faddeevlike amplitudes are expanded on the potential harmonic basis. To transform the resulting coupled differential equations into an eigenvalue equation, we employ again the orthogonal collocation procedure followed by the Gauss-Jacobi quadrature. The corresponding eigenvalue equation is solved using the Renormalized Numerov Method to obtain ground state binding energies and root-mean-square radii of closed shell nuclei 4He, 8Be, 12C, 16O and 40Ca. / Physics / M. Sc. (Physics)

2015年下半年開始，許多有關市場黑天鵝的新聞佈滿各大媒體版面，其中不乏「某恐慌指標創歷史新高」此類令投資人恐懼的標題。然事實上卻未見到各國股價指數有大幅修正的現象，以MSCI全球指數而言，下半年總計僅修正6.49%。為了探討這些不同於傳統VIX指數的恐慌指標是否會顯著影響股價指數的表現。本論文透過VAR、VECM以及ARDL模型，探討金價油價比、CBOE偏態指數、瑞士信貸CSFB指數以及泰德價差這四種恐慌指標對於當前全球前四大經濟體股價指數的關聯性。 美國是全世界經濟的領頭羊，其經濟情勢與全球每一個國家的榮景息息相關，美國股價指數的表現亦是相當受到全球投資人所關注的。故本論文首先透過探討這四種恐慌指標對於S&P 500指數的影響，再利用S&P 500指數領先各國股價指數的特性進一步得出結論。實證結果發現，S&P 500指數對於其他三個股價指數確實具有短期同向的影響，長期而言亦具有穩定的線性關係。另外，金價油價比無論在短期及長期下皆無法有效代理市場的恐慌程度而影響S&P 500指數；CBOE偏態指數與瑞士信貸CSFB指數在長期下得以領先S&P 500指數的變化，當該二指數走高，代表 S&P 500指數在近期的波段高點可能即將來臨，亦即隱含該二指數對於S&P 500指數具有領先同向變化的現象；泰德價差為市場用以衡量信用風險的指標之一，當泰德價差擴大，隱含市場風險貼水增加，不利股市發展，其與S&P 500指數則具有長期穩定的負向關係。本論文最後也針對這四種恐慌指標的預測能力進行探討，發現瑞士信貸CSFB指數在預測S&P 500指數的能力上，相對其他三種恐慌指標優異。 / There were so many hearsays about the potential black swan events dominating the news in the second half of 2015. Headlines were about some fear indicators hit historic high but, in realistic, world stock market did not be significantly influenced under this panic atmosphere. Take MSCI World Index for instance, the index dropped only 6.49% in the second half of 2015, which was relatively unreasonable under this condition. In order to find out whether or not the fluctuations of these fear indicators can significantly affect stock indexes, VAR, VAEM and ARDL model to discuss the relationships between 4 fear indicators and 4 stock indexes─gold to oil ratio, CBOE Skew Index, Credit Suisse Fear Barometer Index, TED spread, S&P 500 Index, MSCI Europe Index, SSE A Share Index and Nikkei 225 Index are adopted in this study. Global investors pay close attention to the performance of the U.S. Stock indexes as U.S. economy condition can affect the economies of the rest of the world. Consequently, we investigated the effects of 4 fear indicators to the S&P 500 Index then employed relationships between S&P 500 Index and other 3 stock indexes to do further discussion. The results show S&P 500 positively affects the performances of other 3 stock indexes in short term and has a steady relationship with each of them respectively in the long term. The changes of gold to oil ratio could not significantly influence the performance of S&P 500 Index no matter in the short term or the long term. CBOE Skew Index and CSFB Index have significant positive influences on S&P 500 and are leading indicators to S&P 500 Index. Lastly, TED spread has a steady negative relationship with S&P 500 in long term, and CSFB Index has the highest predictive power among the 4 fear indicators.

通常，在我們所取得的任意一組資料裡，由於內在特性的關係，往往會使資料自然形 成若干叢聚（Clusters）。叢聚分析（Cluster Analysis）的目的，就是如何藉由數 量的方法，找出這些自然形成的叢聚，俾便於往後資料的整理和分析。儘管界定叢聚 的角度，將因人、因事而有所不同。然而根本上，這就是一個尋找最佳解的方法，來 找出資料中的最理想分組，便成為一種自然而可行的嘗試。本文係就動態規劃、整數 規劃（整數規劃模式改以Subgradient Method求解）、暨分支定限法（Brandhand-bo und Method）如何處理叢聚分析問題，分別予以討論比較。

The purpose of this study was to determine whether: 1) Southwest Region TRIO high school students between the years 1991 - 2001 continued to college immediately after high school at rates significantly different than similar population students on national and state levels; and 2) immediate college continuation for this group was a function of social and economic characteristics including race, gender, parental education, and home-care environment. The sample included 414 TRIO program participants from Texas, Oklahoma, New Mexico, Louisiana, and Arkansas. Data on the 414 participants were gathered using an existing database containing demographic and post-secondary enrollment information on study participants. The findings of this study reveal Southwest Region TRIO students during this ten-year period continued to college immediately after high school at rates not significantly different than the national low-income population of students. Results indicate that when compared to all students in the five-state southwest region, the majority low-income, first-generation TRIO population continued to college at rates not significantly different than all-income students in the region. Findings of this study also revealed select social and economic characteristics were not predictors of immediate college continuation for this group. Finally, the study showed out-of-home care environment students continued to college at significantly higher rates than in-home care Southwest Region TRIO students.

This thesis presents three papers within the field of dynamic macroeconomics. The first paper, entitled “Medium-frequency cycles and the remarkable near trend-stationarity of output”, presents a dynamic stochastic general equilibrium model with endogenous growth, capable of reconciling the observed large medium-frequency fluctuations in output, with its long run (near) trend-stationarity. This requires a model in which standard business cycle shocks lead to highly persistent movements around trend, without significantly altering the trend itself. The robustness of the trend also requires that scale effects are eliminated both in the long and short runs. In an estimated version of the model, a financial-type shock to the stock of ideas emerges as the key driver of the medium frequency cycle. The second paper, entitled “Learning from learners”, is an intervention into two long running debates: the first, on whether learnability may be used to rule out explosive paths for inflation in New Keynesian models, and the second, into whether Taylor rule parameters may be identified from observing the data. We find that in an economy populated with traditional macroeconomic learners, Taylor rule parameters can always be identified by sophisticated econometric techniques. Furthermore, when all agents in the economy use such sophisticated techniques, stationary sunspot solutions are readily learnable, and there is no guarantee of convergence to a stationary solution even in the “determinate” case. This implies that learnability cannot be used for equilibrium selection. Finally, in the third paper, “Efficient simulation of DSGE models with inequality constraints” (joint with Michael Paetz), we present a new algorithm for the simulation of models subject to inequality constraints, such as the zero lower bound on nominal interest rates. Our algorithm is shown to deliver higher accuracy than all other non-global algorithms, and leading speed. We go on to provide a number of applications of our algorithm.

De nombreux problèmes en transport et en logistique peuvent être formulés comme des modèles de conception de réseau. Ils requièrent généralement de transporter des produits, des passagers ou encore des données dans un réseau afin de satisfaire une certaine demande tout en minimisant les coûts. Dans ce mémoire, nous nous intéressons au problème de conception de réseau avec coûts fixes et capacités. Ce problème consiste à ouvrir un sous-ensemble des liens dans un réseau afin de satisfaire la demande, tout en respectant les contraintes de capacités sur les liens. L'objectif est de minimiser les coûts fixes associés à l'ouverture des liens et les coûts de transport des produits. Nous présentons une méthode exacte pour résoudre ce problème basée sur des techniques utilisées en programmation linéaire en nombres entiers. Notre méthode est une variante de l'algorithme de branch-and-bound, appelée branch-and-price-and-cut, dans laquelle nous exploitons à la fois la génération de colonnes et de coupes pour la résolution d'instances de grande taille, en particulier, celles ayant un grand nombre de produits. En nous comparant à CPLEX, actuellement l'un des meilleurs logiciels d'optimisation mathématique, notre méthode est compétitive sur les instances de taille moyenne et supérieure sur les instances de grande taille ayant un grand nombre de produits, et ce, même si elle n'utilise qu'un seul type d'inégalités valides. / Many problems in transportation and logistics can be formulated as network design models. They usually require to transport commodities, passengers or data in a network to satisfy a certain demand while minimizing the costs. In this work, we focus on the multicommodity capacited fixed-charge network design problem which consists of opening a subset of the links in the network to satisfy the demand. Each link has a capacity and a fixed cost that is paid if it is opened. The objective is to minimize the fixed costs of the opened links and the transportation costs of the commodities. We present an exact method to solve this problem based on mixed integer programming techniques. Our method is a specialization of the branch-and-bound algorithm, called branch-and-price-and-cut, in which we use column generation and cutting-plane method to solve large-scale instances. We compare our method with CPLEX, currently one of the best solver. Numerical results show that our method is competitive on medium-scale instances and better on large-scale instances.

Le problème de conception de réseaux est un problème qui a été beaucoup étudié dans le domaine de la recherche opérationnelle pour ses caractéristiques, et ses applications dans des nombreux domaines tels que le transport, les communications, et la logistique. Nous nous intéressons en particulier dans ce mémoire à résoudre le problème de conception de réseaux avec coûts fixes et sans capacité, en satisfaisant les demandes de tous les produits tout en minimisant la somme des coûts de transport de ces produits et des coûts fixes de conception du réseau. Ce problème se modélise généralement sous la forme d’un programme linéaire en nombres entiers incluant des variables continues. Pour le résoudre, nous avons appliqué la méthode exacte de Branch-and-Bound basée sur une relaxation linéaire du problème avec un critère d’arrêt, tout en exploitant les méthodes de génération de colonnes et de génération de coupes. Nous avons testé la méthode de Branch-and-Price-and-Cut sur 156 instances divisées en cinq groupes de différentes tailles, et nous l’avons comparée à Cplex, l’un des meilleurs solveurs d’optimisation mathématique, ainsi qu’à la méthode de Branch-and- Cut. Notre méthode est compétitive et plus performante sur les instances de grande taille ayant un grand nombre de produits. / The network design problem has been studied extensively in the field of operational research given its characteristics and applications in many areas such as transportation, communications, and logistics. We are particularly interested in solving the multicommodity uncapacitated fixed-charge network design problem, with the aim of meeting the demands of all the products while minimizing the total cost of transporting commodities and designing the network. This problem is typically modeled as a linear integer program including continuous variables. To solve it, we applied the exact method of Branch-and-bound based on linear relaxation with a stopping criterion, while exploiting the column generation and cutting-plane methods. We tested our Branch-and-Price-and-Cut algorithm on 156 instances divided into five groups of different sizes, and we compared it with Cplex, one of the best mathematical optimization solvers. We compare it also with the Branch-and-Cut method. Numerical results show that our method is competitive and perform better especially on large-scale instances with many commodities.

Tumor diseases are severe problem worldwide with increasing number of patients suffering from various types of malignancies. Many of approved therapeutics cause serious side toxicities. Therefore, there are intensive efforts to improve cancer treatment protocols. The aim of this study was to deplete regulatory T (Treg) cells without affecting other immunocompetent cells playing a positive role in tumor eradication. Treg cells were reported to hamper anti-tumor immunity and promote tumor growth and survival. Thus, their selective elimination could lead to induction of anti-tumor responses and tumor rejection if combined with chemotherapy with selected N-(2- hydroxypropyl)methacrylamide (HPMA) copolymer-bound drug conjugates. Original approach was to deplete of Treg cells without the use of anti-CD25 mAb that has been widely exploited for Treg cell elimination; however, its long-term persistence in circulation together with inhibitory effect on activated effector cells (CD25+ ) are its main disadvantages. Thus, Treg cells were sensitized to cell cycle-specific cytostatic drugs via application of IL-2/anti-IL-2 JES6.1 mAb immunocomplexes that induce vigorous selective proliferation of this cell population. Subsequent application of cell cycle-specific cytostatics showed steep decrease of Treg cell...

L’objectif de ce travail est une approche pluridisciplinaire dans le but de comprendre l’impact des phénomènes microscopiques, l’interaction charge-matrice avec ou sans agent de couplage et la dispersion des charges sur les propriétés macroscopiques. La caractérisation de l’impact de la stratégie de mélange avec ou sans un agent de couplage, la cinétique, l’état final et les différents scénarii de dispersion possibles sont ainsi étudiés. L’incorporation de microperles de silice dans une matrice SBR est réalisée dans un mélangeur interne. Finalement, la silice est dispersée à l’échelle nanométrique (10-100 nm). Les nanocomposites obtenus sont alors caractérisés par des techniques complémentaires (spectroscopie mécanique, MET, mesure du taux d’élastomère lié à la charge) dans le but de caractériser quantitativement les interactions charge-matrice et charge-charge. L’outil rhéologique est un outil très sensible pour caractériser l’évolution de la dispersion de charges dans une matrice élastomère. En particulier, le module de conservation G’ montre un plateau significatif pour les faibles fréquences de déformation. Ce plateau est très sensible à l’état de dispersion ainsi qu’à la nature des interactions entre les charges. En couplant les mesures rhéologiques, l'analyse d'image faite sur des photos MET et la mesure du taux d’élastomère lié, il est possible d’établir un scénario de dispersion de la silice dans l'élastomère en fonction des conditions de mélange et de mettre en évidence les paramètres élémentaires de la dispersion impliqués. En complément, la modélisation de certains modules montre toute sa pertinence dans la caractérisation de la rupture des agglomérats ou de l’évolution des interactions charge-charge au cours du mélangeage. Enfin, la dimension fractale des réseaux de charges obtenus est déterminée à partir de nos descripteurs de la dispersion / Filler dispersion in an elastomeric matrix, states and mechanisms of dispersion had to be investigated throughout the mixing process. This work focuses on a multidisciplinary approach to understand how microscopic phenomena, like rubber-filler interaction or filler dispersions, affect macroscopic properties such as rheological behavior. The incorporation of silica is realized in an internal mixer under temperature control. Finally, silica is dispersed at the nanoscale (10-100 nm). Afterwards, nanocomposites are characterized using complementary techniques in order to discuss quantitatively the nature of rubber-filler and filler-filler interactions and their effect on rheological properties. Thus, the global evolution of dispersion during the mixing is understood through these various tests. Different mechanisms in the dispersion have been observed. First, intense particle size reduction occurs at the earliest mixing times. Then, the aggregate size does not change while the amount of physically bound rubber at the surface of aggregate increases and levels off. For some silica, a second dispersion stage has been observed after the diffusion of the elastomer to the core of the aggregates. Rheology has showed to be a very sensitive tool to characterize the evolution of the dispersion in the system. Particularly, the complex shear modulus exhibits a significant plateau (Ge), at low frequency, which is very sensitive to the dispersion state and the nature of the interaction between the fillers. There is a striking correlation between the value of plateau Ge and the bound rubber content. Finally, a dispersion scenario has been established and fundamental interaction parameters have been identified

Power limits on future high-performance computing (HPC) systems will constrain applications. However, HPC applications do not consume constant power over their lifetimes. Thus, applications assigned a fixed power bound may be forced to slow down during high-power computation phases, but may not consume their full power allocation during low-power I/O phases. This paper explores algorithms that leverage application semantics-phase frequency, duration and power needs-to shift unused power from applications in I/O phases to applications in computation phases, thus improving system-wide performance. We design novel techniques that include explicit staggering of applications to improve power shifting. Compared to executing without power shifting, our algorithms can improve average performance by up to 8% or improve performance of a single, high-priority application by up to 32%.