Elliptic flow of J/ψ\psi at forward rapidity in Pb-Pb collisions at 2.76 TeV with the ALICE experiment

We present the elliptic flow of inclusive J/$\psi$ measured in the $\mu^{+}\mu^{-}$ channel at forward rapidity ($2.5<y<4.0$), down to zero transverse momentum, in Pb-Pb collisions at $\sqrt{s_{_{\mathrm{NN}}}}=2.76$ TeV with the ALICE muon spectrometer. The $p_{\mathrm T}$ dependence of J/$\psi$ $v_2$ in non-central (20%-60%) Pb-Pb collisions at $\sqrt{s_{_{\mathrm{NN}}}}=2.76$ TeV is compared with existing measurements at RHIC and theoretical calculations. The centrality dependence of the $p_{\mathrm{T}}$-integrated elliptic flow, as well as the $p_{\mathrm{T}}$ dependence in several finer centrality classes is presented.Comment: Quark Matter 2012 proceeding

Endogenous Credit Constraints, Human Capital Investment and Optimal Tax Policy

This paper employs a two-period life-cycle model to derive the optimal tax policy when educational investments are subject to credit constraints. Credit constraints arise from the limited commitment of debitors to repay loans and are endogenously determined by private banks under the non-default condition that individuals can-not be better off by defaulting. We show that the optimal redistributive taxation trades the welfare gain of reducing borrowing demand and of changing the credit constraints against the efficiency costs of distorting education and labor supply. In addition, we compare the optimal taxation with that when credit constraints are taken as given. If income taxation decreases (increases) the borrowing limit, taking credit constraints as given leads to a too high (low) labor tax rate. Thus, ignoring the effects of tax policy on credit constraints overestimates (underestimates) the welfare effects of income taxation. Numerical examples show that income taxation tightens the credit constraints and the optimal tax rates are lower when credit constrains are endogenized. The intuition is that redistributive taxation reduces the incentive to invest in education and to work, thus exaggerating the moral hazard problems associated with credit constraints.labor taxation, human capital investment, credit constraints

Identified Particle Production in d+Au and p+p collisions at RHIC

The BRAHMS experiment at RHIC has measured the transverse momentum spectra of charged pions, kaons and (anti-)protons over a wide range of rapidity in d+Au and p+p collisions at $\sqrt{s_{NN}}=200$GeV. The nuclear modification factor $R_{dAu}$ at forward rapidities shows a clear suppression for $\pi^{+}$. The measured net-proton yields in p+p collisions are compared to PYTHIA and HIJING/B and seem to be better described by the latter.Comment: 4 pages, 3 figures, presented at the 19th International Conference on Ultra-Relativistic Nucleus-Nucleus Collisions, "Quark Matter 2006", Shanghai, China, November 14-20, 2006. to appear in the proceedings of Quark Matter 2006 as a special issue of Journal of Physics G: Nuclear and Particle Physic

Catalyzers for Social Insurance: Education Subsidies vs. Real Capital Taxation

To analyze the optimal social insurance package, we set up a two-period life-cycle model with risky human capital investment, where the government has access to labor taxation, education subsidies and capital taxation. Social insurance is provided by redistributive labor taxation. Moreover, both education subsidies and capital taxation are used as catalyzers to facilitate social insurance by mitigating distortions from labor taxation. We derive a Ramsey-rule for the optimal combination of these two instruments. Relative to capital taxation, optimal education subsidies increase in their relative effectiveness to boost labor supply and in households' underinvestment into education, but they decrease in their relative net distortions. For their absolute levels, indirect complementarity effects, i.e., influencing the effectiveness of the other instrument, do matter. Generally, a decrease in capital taxes should go along with an increase in education subsidies.Human Capital Investment, Education Subsidies, Capital Taxation, Risk, Social Insurance

Catalysts for Social Insurance: Education Subsidies vs. Real Capital Taxation

To analyze the optimal social insurance package, we set up a two-period life-cycle model with risky human capital investment in which the government has access to labor taxation, education subsidies and capital taxation. Social insurance is provided by redistributive labor taxation. Moreover, both education subsidies and capital taxation are used as catalysts to facilitate social insurance by mitigating distortions from labor taxation. We derive a Ramsey-rule for the optimal combination of these two instruments. Relative to capital taxation, optimal education subsidies increase with their relative effectiveness to boost labor supply and with households’ underinvestment into education, but they decrease with their relative net distortions. For the optimal absolute levels, indirect complementarity effects (i.e., influencing the effectiveness of the other instrument) do matter. Generally, a decrease in capital taxes should be accompanied by an increase in education subsidies.human capital investment, education subsidies, capital taxation, risk, social insurance

Optimal Taxation of Risky Human Capital

In a model with ex-ante homogenous households, earnings risk and a general earnings function, we derive the optimal linear labor tax rate and optimal linear education subsidies. The optimal income tax trades off social insurance against incentives to work and to invest in human capital. Education subsidies are not used for social insurance, but are only targeted at off-setting the distortions of the labor tax and internalizing a fiscal externality. Both optimal education subsidies and tax rates increase if labor and education are more complementary, since education subsidies indirectly lower labor tax distortions by stimulating labor supply. Optimal education subsidies (taxes) also correct non-tax distortions arising from missing insurance markets. Education subsidies internalize a positive (negative) fiscal externality if there is underinvestment (overinvestment) in education due to risk. Education policy unambiguously allows for more social insurance if education is a risky activity. However, if education hedges against labor market risk, optimal tax rates could be lower than without education subsidies.labor taxation, human capital investment, education subsidies, idiosyncratic risk, risk properties of human capital

Vector support for multicore processors with major emphasis on configurable multiprocessors

It recently became increasingly difficult to build higher speed uniprocessor chips because of performance degradation and high power consumption. The quadratically increasing circuit complexity forbade the exploration of more instruction-level parallelism (JLP). To continue raising the performance, processor designers then focused on thread-level parallelism (TLP) to realize a new architecture design paradigm. Multicore processor design is the result of this trend. It has proven quite capable in performance increase and provides new opportunities in power management and system scalability. But current multicore processors do not provide powerful vector architecture support which could yield significant speedups for array operations while maintaining arealpower efficiency. This dissertation proposes and presents the realization of an FPGA-based prototype of a multicore architecture with a shared vector unit (MCwSV). FPGA stands for Filed-Programmable Gate Array. The idea is that rather than improving only scalar or TLP performance, some hardware budget could be used to realize a vector unit to greatly speedup applications abundant in data-level parallelism (DLP). To be realistic, limited by the parallelism in the application itself and by the compiler\u27s vectorizing abilities, most of the general-purpose programs can only be partially vectorized. Thus, for efficient resource usage, one vector unit should be shared by several scalar processors. This approach could also keep the overall budget within acceptable limits. We suggest that this type of vector-unit sharing be established in future multicore chips. The design, implementation and evaluation of an MCwSV system with two scalar processors and a shared vector unit are presented for FPGA prototyping. The MicroBlaze processor, which is a commercial IP (Intellectual Property) core from Xilinx, is used as the scalar processor; in the experiments the vector unit is connected to a pair of MicroBlaze processors through standard bus interfaces. The overall system is organized in a decoupled and multi-banked structure. This organization provides substantial system scalability and better vector performance. For a given area budget, benchmarks from several areas show that the MCwSV system can provide significant performance increase as compared to a multicore system without a vector unit. However, a MCwSV system with two MicroBlazes and a shared vector unit is not always an optimized system configuration for various applications with different percentages of vectorization. On the other hand, the MCwSV framework was designed for easy scalability to potentially incorporate various numbers of scalar/vector units and various function units. Also, the flexibility inherent to FPGAs can aid the task of matching target applications. These benefits can be taken into account to create optimized MCwSV systems for various applications. So the work eventually focused on building an architecture design framework incorporating performance and resource management for application-specific MCwSV (AS-MCwSV) systems. For embedded system design, resource usage, power consumption and execution latency are three metrics to be used in design tradeoffs. The product of these metrics is used here to choose the MCwSV system with the smallest value

Promoting neurorestoration and reducing harm to bystander cells and neuroplasticity

Current treatment options for malignant brain tumors not only frequently fail to cure the disease due to local recurrence, but also may severely compromise quality of remaining life even when tumor mass is reduced in large part because they interfere with mechanisms of neuroplasticity and function of bystander tissue. The aims of this dissertation are to: (a) assess neurological impairments associated with rapid focal cortical tissue displacement; (b) evaluate the specific impact of conventional and novel treatments on neurorestoration while controlling tissue compression without the confound of related events linked to tumor physiology; (c) identify the behavioral change pattern during brain tumor progression and investigate the stealth nature of brain tumors; (d) demonstrate how anti-cancer treatments affect brain function especially when administered in the silent stages of brain tumors; and (e) develop treatment strategies that might improve therapeutic effectiveness and brain function. We adopted a new focal mass compression model providing rapid displacement of tissue in the underlying sensorimotor cortex, as well as the traditional rat and mouse glioma xenograft models that exhibit prominent tumor growth and invasion, given the varied aims and contexts of our different studies. Various conventional and novel brain tumor treatments were employed in this dissertation, including local and systemic chemotherapy, antiangiogenic agents, photodynamic therapy, and a glutamate antagonist. A neurorestorative therapy with atorvastatin was evaluated in its effects on functional recovery after photodynamic therapy. Functional outcomes were measured with an array of behavioral tests, which are sensitive to mild focal insults to the sensorimotor cortex and can detect recovery of function. Histopathological assessments consisted of Nissl staining, hematoxylin-andeosin (H&E) staining, and immunohistochemistry, depending on varied purposes, used in conjunction with a computer imaging analysis system. In clinical trials, functional outcome is as critical to gauging the success of a treatment as is patient survival time. Both preclinical screening of anti-cancer interventions for the ability to shrink tumors effectively with minimal disturbance of neuroplasticity and developing combination therapy with neurorestorative regimens following neurotoxic cancer treatments should allow for optimal promotion of plastic mechanisms in the remaining normal brain tissue.Institute for Neuroscienc