Policy Rules, Regime Switches, and Trend Inflation: An Empirical Investigation for the U.S.

This paper estimates Taylor rules featuring instabilities in policy parameters, switches in policy shocks' volatility, and time-varying trend inflation using post-WWII U.S. data. The model embedding the stochastic target performs better in terms of data-fit and identification of the changes in the FOMC's chairmanships. Policy breaks are found not to be synchronized with variations in policy shocks' volatilities. Finally, we detect a negative correlation between systematic monetary policy aggressiveness and inflation gap persistence.

Heavy-Quark Probes of the Quark-Gluon Plasma at RHIC

Thermalization and collective flow of charm (c) and bottom (b) quarks in ultra-relativistic heavy-ion collisions are evaluated based on elastic parton rescattering in an expanding quark-gluon plasma (QGP). We show that resonant interactions in a strongly interacting QGP (sQGP), as well as the effects of parton coalescence, can play an essential role in the interpretation of recent data from the Relativistic Heavy-Ion Collider (RHIC), and thus illuminate the nature of the sQGP and its hadronization. Our main assumption, motivated by recent findings in lattice computations of Quantum Chromodynamics, is the existence of D- and B-meson states in the sQGP, providing resonant cross sections for heavy quarks up to temperatures of sim 2 T_c. Pertinent drag and diffusion coefficients are implemented into a relativistic Langevin simulation to compute transverse-momentum spectra and azimuthal asymmetries (v_2) of b- and c-quarks in Au-Au collisions at RHIC. Hadronization into D- and B-mesons is calculated from a combination of coalescence with light quarks and fragmentation, and associated electron-decay spectra and v_2 are compared to recent RHIC data. We also comment on the relative importance of radiative and elastic energy loss of heavy quarks in the QGP.Comment: 4 pages, 3 figures, v2: 1 reference updated, v3: replaced comparison to data to more recent data, references added, contents unchange

Performance Bounds for Parameter Estimation under Misspecified Models: Fundamental findings and applications

Inferring information from a set of acquired data is the main objective of any signal processing (SP) method. In particular, the common problem of estimating the value of a vector of parameters from a set of noisy measurements is at the core of a plethora of scientific and technological advances in the last decades; for example, wireless communications, radar and sonar, biomedicine, image processing, and seismology, just to name a few. Developing an estimation algorithm often begins by assuming a statistical model for the measured data, i.e. a probability density function (pdf) which if correct, fully characterizes the behaviour of the collected data/measurements. Experience with real data, however, often exposes the limitations of any assumed data model since modelling errors at some level are always present. Consequently, the true data model and the model assumed to derive the estimation algorithm could differ. When this happens, the model is said to be mismatched or misspecified. Therefore, understanding the possible performance loss or regret that an estimation algorithm could experience under model misspecification is of crucial importance for any SP practitioner. Further, understanding the limits on the performance of any estimator subject to model misspecification is of practical interest. Motivated by the widespread and practical need to assess the performance of a mismatched estimator, the goal of this paper is to help to bring attention to the main theoretical findings on estimation theory, and in particular on lower bounds under model misspecification, that have been published in the statistical and econometrical literature in the last fifty years. Secondly, some applications are discussed to illustrate the broad range of areas and problems to which this framework extends, and consequently the numerous opportunities available for SP researchers.Comment: To appear in the IEEE Signal Processing Magazin

A Behavior-Driven Recommendation System for Stack Overflow Posts

Developers are often tasked with maintaining complex systems. Regardless of prior experience, there will inevitably be times in which they must interact with parts of the system with which they are unfamiliar. In such cases, recommendation systems may serve as a valuable tool to assist the developer in implementing a solution. Many recommendation systems in software engineering utilize the Stack Overflow knowledge-base as the basis of forming their recommendations. Traditionally, these systems have relied on the developer to explicitly invoke them, typically in the form of specifying a query. However, there may be cases in which the developer is in need of a recommendation but unaware that their need exists. A new class of recommendation systems deemed Behavior-Driven Recommendation Systems for Software Engineering seeks to address this issue by relying on developer behavior to determine when a recommendation is needed, and once such a determination is made, formulate a search query based on the software engineering task context. This thesis presents one such system, StackInTheFlow, a plug-in integrating into the IntelliJ family of Java IDEs. StackInTheFlow allows the user to intervi act with it as a traditional recommendation system, manually specifying queries and browsing returned Stack Overflow posts. However, it also provides facilities for detecting when the developer is in need of a recommendation, defined when the developer has encountered an error messages or a difficulty detection model based on indicators of developer progress is fired. Once such a determination has been made, a query formulation model constructed based on a periodic data dump of Stack Overflow posts will automatically form a query from the software engineering task context extracted from source code currently open within the IDE. StackInTheFlow also provides mechanisms to personalize, over time, the results displayed to a specific set of Stack Overflow tags based on the results previously selected by the user. The effectiveness of these mechanisms are examined and results based the collection of anonymous user logs and a small scale study are presented. Based on the results of these evaluations, it was found that some of the queries issued by the tool are effective, however there are limitations regarding the extraction of the appropriate context of the software engineering task yet to overcome

Hospital Acquired Infections in a large North Ugandan hospital

Introduction. Hospital care is a precious gift in Uganda, therefore little concern is given to hospital safety and very seldom Hospital Acquired Infection (HAI) risk is evaluated. Within a quality improvement hospital program the Board of Lacor Hospital, a large Missionary Hospital of north Uganda, ordered an HAI control program to be established. The first step of this program was an HAI prevalence survey whose results are presented in this paper. Methods. A one day prevalence survey was performed on patients admitted at least 48 hours before the survey: short training was offered to qualified nurses and hospital doctors. Lacking a suitable microbiological diagnostic service, clinical definitions of HAI were adopted. Questionnaires were completed by the nurses and data were analyzed and presented to the hospital personnel four days after the survey. A HAI control program was agreed and started soon after. Results. The hospital has 44.000 admissions yearly with 482 beds and main hospital specialties, 410 patients were surveyed. Overall HAI prevalence was 28%, more in surgery (47%) and less in pediatrics (21%). Blood stream infections were the most frequent, followed by surgical wound infections and Urinary Tract infections, several lower respiratory tract infections and few gastrointestinal one. HAI prevalence was associated with length of stay in hospital,intravenous cannulas, urinary catheters and emergency surgery. Patients with severe low nutrition status, anemia and complications of the main disease bringing them to hospital experienced higher HAI prevalence. Discussion. This paper shows that HAI can be measured also in absence of microbiological service and that Hospital staff are ready to evaluate this problem. This high HAI prevalence was not expected by the staff and has been a starting point for an hospital HAI control plan