University of Rochester

About: University of Rochester is a education organization based out in Rochester, New York, United States. It is known for research contribution in the topics: Population & Laser. The organization has 63915 authors who have published 112762 publications receiving 5484122 citations. The organization is also known as: Rochester University.

Determination of jet energy calibration and transverse momentum resolution in CMS

Abstract: Measurements of the jet energy calibration and transverse momentum resolution in CMS are presented, performed with a data sample collected in proton-proton collisions at a centre-of-mass energy of 7TeV, corresponding to an integrated luminosity of 36pb−1. The transverse momentum balance in dijet and γ/Z+jets events is used to measure the jet energy response in the CMS detector, as well as the transverse momentum resolution. The results are presented for three different methods to reconstruct jets: a calorimeter-based approach, the ``Jet-Plus-Track'' approach, which improves the measurement of calorimeter jets by exploiting the associated tracks, and the ``Particle Flow'' approach, which attempts to reconstruct individually each particle in the event, prior to the jet clustering, based on information from all relevant subdetectors

Ambiguity, Information Quality, and Asset Pricing

Abstract: When ambiguity-averse investors process news of uncertain quality, they act as if they take a worst-case assessment of quality. As a result, they react more strongly to bad news than to good news. They also dislike assets for which information quality is poor, especially when the underlying fundamentals are volatile. These effects induce ambiguity premia that depend on idiosyncratic risk in fundamentals as well as skewness in returns. Moreover, shocks to information quality can have persistent negative effects on prices even if fundamentals do not change. FINANCIAL MARKET PARTICIPANTS ABSORB a large amount of news, or signals, every day. Processing a signal involves quality judgments: News from a reliable source should lead to more portfolio rebalancing than news from an obscure source. Unfortunately, judging quality itself is sometimes difficult. For example, stock picks from an unknown newsletter without a track record might be very reliable or entirely useless—it is simply hard to tell. Of course, the situation is different when investors can draw on a lot of experience that helps them interpret signals. This is true especially for “tangible” information, such as earnings reports, that lends itself to quantitative analysis. By looking at past data, investors may become quite confident about how well earnings forecast returns. This paper focuses on information processing when there is incomplete knowledge about signal quality. The main idea is that, when quality is difficult to judge, investors treat signals as ambiguous. They do not update beliefs in standard Bayesian fashion, but behave as if they have multiple likelihoods in mind when processing signals. To be concrete, suppose that θ is a parameter that an investor wants to learn. We assume that a signal s is related to the parameter by a family of likelihoods: s = θ + � , � ∼ N � 0, σ 2 s � , σ 2 s ∈ � σ 2

Distinct Patterns of Multiple Sclerosis Pathology Indicates Heterogeneity in Pathogenesis

Abstract: Multiple sclerosis is an inflammatory demyelinating disease of the central nervous system. The hallmark of its pathology is the demyelinated plaque with reactive glial scar formation. However, a detailed analysis of the patterns of demyelination, oligodendroglia cell pathology and the reaction of other tissue components suggests that the pathogenesis of myelin destruction in this disease may be heterogeneous. In this review we present a new classification scheme of lesional activity on the basis of the molecular composition of myelin degradation products in macrophages. When these criteria are used, different patterns of demyelination can be distinguished, including demyelination with relative preservation of oligodendrocytes, myelin destruction with concomitant and complete destruction of oligodendrocytes or primary destruction or disturbance of myelinating cells with secondary demyelination. Furthermore, in some cases a primary selective demyelination may be followed by a secondary oligodendrocyte loss in the established lesions. Finally, some extraordinarily severe conditions may result in destructive lesions with loss of myelin, oligodendrocytes, axons and astrocytes. This heterogeneity of plaque pathology is discussed in the context of recent experimental models of inflammatory demyelination, which show that different immunological pathways may lead to the formation of demyelinated plaques that reveal the diverse structural aspects described above. Our data indicate, that the demyelinated plaques of multiple sclerosis may reflect a common pathological end point of a variety of different immunological mechanisms of myelin destruction in this disease.

Constraint propagation algorithms for temporal reasoning

Abstract: This paper considers computational aspects of several temporal representation languages. It investigates an interval-based representation, and a point-based one. Computing the consequences of temporal assertions is shown to be computationally intractable in the interval-based representation, but not in the point-based one. However, a fragment of the interval language can be expressed using the point language and benefits from the tractability of the latter.