Relativistic Effects in Electroweak Nuclear Responses

The electroweak response functions for inclusive electron scattering are calculated in the Relativistic Fermi Gas model, both in the quasi-elastic and in the $\Delta$ peak regions. The impact of relativistic kinematics at high momentum transfer is investigated through an expansion in the initial nucleonic momentum, which is however exact in the four-momentum of the exchanged boson. The same expansion is applied to the meson exchange currents in the particle-hole sector: it is shown that the non-relativistic currents can be corrected by simple kinematical factors to account for relativity. The left-right asymmetry measured via polarized electron scattering is finally evaluated in the quasi-elastic and $\Delta$ peaks.Comment: 9 pages, 3 figures, to appear in "Proceedings of the VIII Convegno su Problemi di Fisica Nucleare Teorica, 18-20 October 2000", World Scientifi

Transcriptomic effects of the non-steroidal anti-inflammatory drug Ibuprofen in the marine bivalve Mytilus galloprovincialis Lam

The transcriptomic effects of Ibuprofen (IBU) in the digestive gland tissue of Mytilus galloprovincialis Lam. specimens exposed at low environmental concentrations (250 ng L-1) are presented. Using a 1.7 K feature cDNA microarray along with linear models and empirical Bayes statistical methods 225 differentially expressed genes were identified in mussels treated with IBU across a 15-day period. Transcriptional dynamics were typical of an adaptive response with a peak of gene expression change at day 7 (177 features, representing about 11% of sequences available for analysis) and an almost full recovery at the end of the exposure period. Functional genomics by means of Gene Ontology term analysis unraveled typical mussel stress responses i.e. aminoglycan (chitin) metabolic processes but also more specific effects such as the regulation of NF-kappa B transcription factor activity. (C) 2016 Elsevier Ltd. All rights reserved

Optimal Dynamic Procurement Policies for a Storable Commodity with L\'evy Prices and Convex Holding Costs

In this paper we study a continuous time stochastic inventory model for a commodity traded in the spot market and whose supply purchase is affected by price and demand uncertainty. A firm aims at meeting a random demand of the commodity at a random time by maximizing total expected profits. We model the firm's optimal procurement problem as a singular stochastic control problem in which controls are nondecreasing processes and represent the cumulative investment made by the firm in the spot market (a so-called stochastic "monotone follower problem"). We assume a general exponential L\'evy process for the commodity's spot price, rather than the commonly used geometric Brownian motion, and general convex holding costs. We obtain necessary and sufficient first order conditions for optimality and we provide the optimal procurement policy in terms of a "base inventory" process; that is, a minimal time-dependent desirable inventory level that the firm's manager must reach at any time. In particular, in the case of linear holding costs and exponentially distributed demand, we are also able to obtain the explicit analytic form of the optimal policy and a probabilistic representation of the optimal revenue. The paper is completed by some computer drawings of the optimal inventory when spot prices are given by a geometric Brownian motion and by an exponential jump-diffusion process. In the first case we also make a numerical comparison between the value function and the revenue associated to the classical static "newsvendor" strategy.Comment: 28 pages, 3 figures; improved presentation, added new results and section

Checkpoint proteins come under scrutiny

Details are emerging of the interactions between the kinetochore and various spindle checkpoint proteins that ensure that sister chromatids are equally divided between daughter cells during cell division

Active-Learning Quality Improvement Training Curriculum for Faculty in Hospital Medicine

Background: There is a growing emphasis on teaching Quality Improvement (QI) to resident physicians and medical students. However, faculty with QI skills and knowledge is lacking at many academic medical centers.Active learning programs to improve faculty capacity for QI have shown positive outcomes. We sought to develop a QI curriculum for faculty within the Division of Hospital Medicine. Description of project/program/innovation: We conducted a needs assessment focus group for Hospital Medicine faculty at our academic medical center. Six faculty members participated and identified priorities and potential challenges. Based on the focus group feedback, we designed a 12-session curriculum that uses an active-learning approach to teach core concepts in QI and includes sessions on effectively mentoring and publishing QI (Table 1). Junior and senior faculty collaborated on curricular design and delivery, with the goal of developing junior faculty into effective QI teachers. Pre-assessment of QI knowledge, skills, and attitudes was conducted using a survey instrument and the revised Quality Improvement Knowledge Application Tool (QIKAT-R). Results: Eighteen faculty completed the pre-assessments (82% completion). At baseline, self-reported comfort was highest for “setting aims for a QI project” and lowest for “presenting results of a QI project”. The mean QIKAT-R score was 16.8 out of 27 (SD 4.5), with the lowest performance in the “setting aims” domain. To date, six sessions have been completed. The selected project focuses on improving hospitalized patients’ experiences around daily bedside rounding. Discussion: We have created a QI curriculum that seeks to address the gap in QI skills among hospitalists. Pre-assessments revealed poor correlation between self-reported comfort level and QIKAT-R scores within each domain, further highlighting educational opportunities. We plan to use feedback from this pilot to refine the curriculum and offer it to faculty in other specialties

Protein search for multiple targets on DNA

Protein-DNA interactions are crucial for all biological processes. One of the most important fundamental aspects of these interactions is the process of protein searching and recognizing specific binding sites on DNA. A large number of experimental and theoretical investigations have been devoted to uncovering the molecular description of these phenomena, but many aspects of the mechanisms of protein search for the targets on DNA remain not well understood. One of the most intriguing problems is the role of multiple targets in protein search dynamics. Using a recently developed theoretical framework we analyze this question in detail. Our method is based on a discrete-state stochastic approach that takes into account most relevant physical-chemical processes and leads to fully analytical description of all dynamic properties. Specifically, systems with two and three targets have been explicitly investigated. It is found that multiple targets in most cases accelerate the search in comparison with a single target situation. However, the acceleration is not always proportional to the number of targets. Surprisingly, there are even situations when it takes longer to find one of the multiple targets in comparison with the single target. It depends on the spatial position of the targets, distances between them, average scanning lengths of protein molecules on DNA, and the total DNA lengths. Physical-chemical explanations of observed results are presented. Our predictions are compared with experimental observations as well as with results from a continuum theory for the protein search. Extensive Monte Carlo computer simulations fully support our theoretical calculations