Expected Performance of the ATLAS Experiment - Detector, Trigger and Physics

A detailed study is presented of the expected performance of the ATLAS detector. The reconstruction of tracks, leptons, photons, missing energy and jets is investigated, together with the performance of b-tagging and the trigger. The physics potential for a variety of interesting physics processes, within the Standard Model and beyond, is examined. The study comprises a series of notes based on simulations of the detector and physics processes, with particular emphasis given to the data expected from the first years of operation of the LHC at CERN

Effects of Anacetrapib in Patients with Atherosclerotic Vascular Disease

BACKGROUND: Patients with atherosclerotic vascular disease remain at high risk for cardiovascular events despite effective statin-based treatment of low-density lipoprotein (LDL) cholesterol levels. The inhibition of cholesteryl ester transfer protein (CETP) by anacetrapib reduces LDL cholesterol levels and increases high-density lipoprotein (HDL) cholesterol levels. However, trials of other CETP inhibitors have shown neutral or adverse effects on cardiovascular outcomes. METHODS: We conducted a randomized, double-blind, placebo-controlled trial involving 30,449 adults with atherosclerotic vascular disease who were receiving intensive atorvastatin therapy and who had a mean LDL cholesterol level of 61 mg per deciliter (1.58 mmol per liter), a mean non-HDL cholesterol level of 92 mg per deciliter (2.38 mmol per liter), and a mean HDL cholesterol level of 40 mg per deciliter (1.03 mmol per liter). The patients were assigned to receive either 100 mg of anacetrapib once daily (15,225 patients) or matching placebo (15,224 patients). The primary outcome was the first major coronary event, a composite of coronary death, myocardial infarction, or coronary revascularization. RESULTS: During the median follow-up period of 4.1 years, the primary outcome occurred in significantly fewer patients in the anacetrapib group than in the placebo group (1640 of 15,225 patients [10.8%] vs. 1803 of 15,224 patients [11.8%]; rate ratio, 0.91; 95% confidence interval, 0.85 to 0.97; P=0.004). The relative difference in risk was similar across multiple prespecified subgroups. At the trial midpoint, the mean level of HDL cholesterol was higher by 43 mg per deciliter (1.12 mmol per liter) in the anacetrapib group than in the placebo group (a relative difference of 104%), and the mean level of non-HDL cholesterol was lower by 17 mg per deciliter (0.44 mmol per liter), a relative difference of -18%. There were no significant between-group differences in the risk of death, cancer, or other serious adverse events. CONCLUSIONS: Among patients with atherosclerotic vascular disease who were receiving intensive statin therapy, the use of anacetrapib resulted in a lower incidence of major coronary events than the use of placebo. (Funded by Merck and others; Current Controlled Trials number, ISRCTN48678192 ; ClinicalTrials.gov number, NCT01252953 ; and EudraCT number, 2010-023467-18 .)

Drons col·laboratius

La robòtica col·laborativa és senzillament robots dissenyats per dur a terme treballs de col·laboració amb els humans. Els robots col·laboratius o cobots són cada cop més utilitzats a les indústries. La robòtica col·laborativa és un dels àmbits d'actualitat en aquests moments. Però també és un dels més interessants en més d'un sentit. Com es comuniquen dos drons autònoms que col·laboren per fer una tasca? Com són aquests missatges que s'envien? Que poden fer que no podrien fer sols? Aquestes són algunes de les preguntes que ens volem respondre en aquest projecte. En aquest treball es presenta un disseny i implementació de dos drons terrestres que es comuniquen per col·laborar entre ells per resoldre una tasca.Collaborative robotics is simply robots designed to perform collaborative work with humans. Collaborative robots or cobots are increasingly used in industries. Collaborative robotics is one of the current topics now. But it is also one of the most interesting in more ways than one. How do two autonomous drones that collaborate to perform a task communicate? How are these messages sent? What can they do that they could not do alone? These are some of the questions we want to answer in this project. This work presents a design and implementation of two ground drones that communicate to collaborate with each other to solve a task.La robótica colaborativa es sencillamente robots diseñados para llevar a cabo trabajos de colaboración con los humanos. Los robots colaborativos o cobots son cada vez más utilizados en las industrias. La robótica colaborativa es uno de los ámbitos de actualidad. Pero también es uno de los más interesantes en más de un sentido. ¿Cómo se comunican drones autónomos que colaboran para hacer una tarea? ¿Cómo son estos mensajes que es envían? ¿Qué pueden hacer que no lo podrían hacer solos? Estas son algunas de las preguntas que queremos responder con este proyecto. En este trabajo se presenta un diseño e implementación de dos drones terrestres que se comunican para colaborar entre ellos para resolver una tarea

Explication and Definition of Mental Health Recovery: A Systematic Review

This review assessed the concordance of the literature on recovery with the definition and components of recovery developed by the Substance Abuse and Mental Health Services Administration (SAMHSA). Each SAMHSA identified recovery component was first explicated with synonyms and keywords and made mutually exclusive by authors. Inter-rater reliability was established on the coding of the presence of 17 recovery components and dimensions in 67 literature reviews on the recovery concept in mental health. The review indicated that concordance varied across SAMHSA components. The components of recovery with greatest concordance were: individualized/person centered, empowerment, purpose, and hope

Practical application of opt-out recruitment methods in two health services research studies

Background: Participant recruitment is an ongoing challenge in health research. Recruitment may be especially difficult for studies of access to health care because, even among those who are in care, people using services least often also may be hardest to contact and recruit. Opt-out recruitment methods (in which potential participants are given the opportunity to decline further contact about the study (opt out) following an initial mailing, and are then contacted directly if they have not opted out within a specified period) can be used for such studies. However, there is a dearth of literature on the effort needed for effective opt-out recruitment. Methods: In this paper we describe opt-out recruitment procedures for two studies on access to health care within the U.S. Department of Veterans Affairs. We report resource requirements for recruitment efforts (number of opt-out packets mailed and number of phone calls made). We also compare the characteristics of study participants to potential participants via t-tests, Fisher’s exact tests, and chi-squared tests. Results: Recruitment rates for our two studies were 12 and 21%, respectively. Across multiple study sites, we had to send between 4.3 and 9.2 opt-out packets to recruit one participant. The number of phone calls required to arrive at a final status for each potentially eligible Veteran (i.e. study participation or the termination of recruitment efforts) were 2.9 and 6.1 in the two studies, respectively. Study participants differed as expected from the population of potentially eligible Veterans based on planned oversampling of certain subpopulations. The final samples of participants did not differ statistically from those who were mailed opt-out packets, with one exception: in one of our two studies, participants had higher rates of mental health service use in the past year than did those mailed opt-out packets (64 vs. 47%). Conclusions: Our results emphasize the practicality of using opt-out methods for studies of access to health care. Despite the benefits of these methods, opt-out alone may be insufficient to eliminate non-response bias on key variables. Researchers will need to balance considerations of sample representativeness and feasibility when designing studies investigating access to care. Electronic supplementary material The online version of this article (doi:10.1186/s12874-017-0333-5) contains supplementary material, which is available to authorized users