Let's talk: public evaluation of large projects: variational inequialities, bilevel programming and complementarity. a survey

Large projects evaluation rises well known difficulties because -by definition- they modify the current price system; their public evaluation presents additional difficulties because they modify too existing shadow prices without the project. This paper analyzes -first- the basic methodologies applied until late 80s., based on the integration of projects in optimization models or, alternatively, based on iterative procedures with information exchange between two organizational levels. New methodologies applied afterwards are based on variational inequalities, bilevel programming and linear or nonlinear complementarity. Their foundations and different applications related with project evaluation are explored. As a matter of fact, these new tools are closely related among them and can treat more complex cases involving -for example- the reaction of agents to policies or the existence of multiple agents in an environment characterized by common functions representing demands or constraints on polluting emissions.

Adaption of Courses and Learning Environment to the User Context in dotLRN

The explosive growth of Internet during the last years has been reflected in the ever-increasing amount of the diversity and heterogeneity of user preferences, types and features of devices and access networks. Usually the heterogeneity in the context of the users which request Web contents is not taken into account by the servers that deliver them implying that these contents will not always suit their needs. In the particular case of e-learning platforms this issue is especially critical due to the fact that it puts at stake the knowledge acquired by their users. In the following paper we present a system that aims to provide the dotLRN e-learning platform with the capability to adapt to its users context. By integrating dotLRN with a multi-agent hypermedia system, online courses being undertaken by students as well as their learning environment are adapted in real time

Comparison of Work Scheduling Using Constraint Programming or Auctions

Business processes designers take into account the resources that the processes would need, but, due to the variable cost of certain parameters (like energy) or other circumstances, this scheduling must be done when business process enactment. In this report we formalize the energy aware resource cost, including time and usage dependent rates. We also present a constraint programming approach and an auction-based approach to solve the mentioned problem including a comparison of them and a comparison of the proposed algorithms for solving them

Assembling genes from predicted exons in linear time with dynamic programming

In a number of programs for gene structure prediction in higher eukaryotic genomic sequences, exon prediction is decoupled from gene assembly: a large pool of candidate exons is predicted and scored from features located in the query DNA sequence, and candidate genes are assembled from such a pool as sequences of nonoverlapping frame-compatible exons. Genes are scored as a function of the scores of the assembled exons, and the highest scoring candidate gene is assumed to be the most likely gene encoded by the query DNA sequence. Considering additive gene scoring functions, currently available algorithms to determine such a highest scoring candidate gene run in time proportional to the square of the number of predicted exons. Here, we present an algorithm whose running time grows only linearly with the size of the set of predicted exons. Polynomial algorithms rely on the fact that, while scanning the set of predicted exons, the highest scoring gene ending in a given exon can be obtained by appending the exon to the highest scoring among the highest scoring genes ending at each compatible preceding exon. The algorithm here relies on the simple fact that such highest scoring gene can be stored and updated. This requires scanning the set of predicted exons simultaneously by increasing acceptor and donor position. On the other hand, the algorithm described here does not assume an underlying gene structure model. Indeed, the definition of valid gene structures is externally defined in the so-called Gene Model. The Gene Model specifies simply which gene features are allowed immediately upstream which other gene features in valid gene structures. This allows for great flexibility in formulating the gene identification problem. In particular it allows for multiple-gene two-strand predictions and for considering gene features other than coding exons (such as promoter elements) in valid gene structures.

Applying recommendations to aligncompetences, methodology and assessment in Telematics, Computing and Electronic Engineering courses

The alignment between competences, teaching-learning methodologies and assessment is a key element of the European Higher Education Area. This paper presents the efforts carried out by six Telematics, Computer Science and Electronic Engineering Education teachers towards achieving this alignment in their subjects. In a joint work with pedagogues, a set of recommended actions were identified. A selection of these actions were applied and evaluated in the six subjects. The cross-analysis of the results indicate that the actions allow students to better understand the methodologies and assessment planned for the subjects, facilitate (self-) regulation and increase students’ involvement in the subjects.

Maternal side-effects after multiple courses of antenatal corticosteroids (MACS): the three-month follow-up of women in the randomized controlled trial of MACS for preterm birth study.

OBJECTIVE: A single course of antenatal corticosteroids (ACS) is associated with a reduction in respiratory distress syndrome and neonatal death. Multiple Courses of Antenatal Corticosteroids Study (MACS), a study involving 1858 women, was a multicentre randomized placebo-controlled trial of multiple courses of ACS, given every 14 days until 33+6 weeks or birth, whichever came first. The primary outcome of the study, a composite of neonatal mortality and morbidity, was similar for the multiple ACS and placebo groups (12.9% vs. 12.5%), but infants exposed to multiple courses of ACS weighed less, were shorter, and had smaller head circumferences. Thus for women who remain at increased risk of preterm birth, multiple courses of ACS (every 14 days) are not recommended. Chronic use of corticosteroids is associated with numerous side effects including weight gain and depression. The aim of this postpartum assessment was to ascertain if multiple courses of ACS were associated with maternal side effects. METHODS: Three months postpartum, women who participated in MACS were asked to complete a structured questionnaire that asked about maternal side effects of corticosteroid use during MACS and included the Edinburgh Postnatal Depression Scale. Women were also asked to evaluate their study participation. RESULTS: Of the 1858 women randomized, 1712 (92.1%) completed the postpartum questionnaire. There were no significant differences in the risk of maternal side effects between the two groups. Large numbers of women met the criteria for postpartum depression (14.1% in the ACS vs. 16.0% in the placebo group). Most women (94.1%) responded that they would participate in the trial again. CONCLUSION: In pregnancy, corticosteroids are given to women for fetal lung maturation and for the treatment of various maternal diseases. In this international multicentre randomized controlled trial, multiple courses of ACS (every 14 days) were not associated with maternal side effects, and the majority of women responded that they would participate in such a study again.

Expansion of undergraduate courses in nursing: dilemmas and contradictions facing the labor market

We sought to analyze, from the perspective of professors and students, the reasons and consequences of the expansion of undergraduate courses in nursing, discussing the dilemmas and the contradictions confronting the labor market. It was a qualitative study with data obtained from focus groups, conducted in 18 undergraduate nursing courses in the state of Minas Gerais, during the period of February to October of 2011. The narratives were submitted to critical discourse analysis. The results indicated that the education of the nurse was permeated by insecurity as to the future integration into the labor market. The insecurity translates into dilemmas that referred to employability and the precariousness of the working conditions. In this context, employment in the family health strategy emerges as a mirage. One glimpses the need for a political agenda with the purpose of discussion about education, the labor market and the determinants of these processes.

Teaching-service integration: implications and roles in experiences of Undergraduate Courses in Nursing

The study aimed at understanding the implications of the teaching-service integration to nursing education from the perspective of teachers, students and professionals in Primary Healthcare as well as identifying the roles of teachers and professionals who follow practical experiences in education. This is a case study of qualitative approach carried out in five undergraduate courses in Nursing in the state of Santa Catarina. A total of 22 teachers and 14 professionals were interviewed and five focus groups were conducted with students. Results are presented in two categories: Implications of the teaching-service integration to education in Nursing: contributing factors and intervening factors and Relationships established in the experiences: a unison speech and a dissonant practice. The contributions of the teaching-service integration are undeniable. Despite this belief, there are intervening factors that need to be on the agenda for discussion. The role of facilitator in education emerged strongly despite conflicting perceptions remain.

Improvement courses about violence prevention: the impact on health sector professionals

Uncontrolled intervention study that compared the effectiveness of two elective courses on Prevention and Assistance to violence victims for students and professionals of the Health Sector. The participants answered multiple-choice questions on the topic before and after the course. Statistical analyzes were performed by comparison of two proportions on STATA/IC. Regarding the overall index of correct answers,before and after, it was 54.8 and 58.4% in the 10h Course and the 69.6 and 79.2% in the 30h Course. The most effective course was the 30h Course, with strategies of case discussions and visits to assistance services to violence victims. There is a great necessity to include the discipline in the curriculum of healthcare courses permanently.



A randomized concave programming method for choice network revenue management

Models incorporating more realistic models of customer behavior, as customers choosing froman offer set, have recently become popular in assortment optimization and revenue management.The dynamic program for these models is intractable and approximated by a deterministiclinear program called the CDLP which has an exponential number of columns. However, whenthe segment consideration sets overlap, the CDLP is difficult to solve. Column generationhas been proposed but finding an entering column has been shown to be NP-hard. In thispaper we propose a new approach called SDCP to solving CDLP based on segments and theirconsideration sets. SDCP is a relaxation of CDLP and hence forms a looser upper bound onthe dynamic program but coincides with CDLP for the case of non-overlapping segments. Ifthe number of elements in a consideration set for a segment is not very large (SDCP) can beapplied to any discrete-choice model of consumer behavior. We tighten the SDCP bound by(i) simulations, called the randomized concave programming (RCP) method, and (ii) by addingcuts to a recent compact formulation of the problem for a latent multinomial-choice model ofdemand (SBLP+). This latter approach turns out to be very effective, essentially obtainingCDLP value, and excellent revenue performance in simulations, even for overlapping segments.By formulating the problem as a separation problem, we give insight into why CDLP is easyfor the MNL with non-overlapping considerations sets and why generalizations of MNL posedifficulties. We perform numerical simulations to determine the revenue performance of all themethods on reference data sets in the literature.

A new compact linear programming formulation for choice network revenue management

The choice network revenue management model incorporates customer purchase behavioras a function of the offered products, and is the appropriate model for airline and hotel networkrevenue management, dynamic sales of bundles, and dynamic assortment optimization.The optimization problem is a stochastic dynamic program and is intractable. A certainty-equivalencerelaxation of the dynamic program, called the choice deterministic linear program(CDLP) is usually used to generate dyamic controls. Recently, a compact linear programmingformulation of this linear program was given for the multi-segment multinomial-logit (MNL)model of customer choice with non-overlapping consideration sets. Our objective is to obtaina tighter bound than this formulation while retaining the appealing properties of a compactlinear programming representation. To this end, it is natural to consider the affine relaxationof the dynamic program. We first show that the affine relaxation is NP-complete even for asingle-segment MNL model. Nevertheless, by analyzing the affine relaxation we derive a newcompact linear program that approximates the dynamic programming value function betterthan CDLP, provably between the CDLP value and the affine relaxation, and often comingclose to the latter in our numerical experiments. When the segment consideration sets overlap,we show that some strong equalities called product cuts developed for the CDLP remain validfor our new formulation. Finally we perform extensive numerical comparisons on the variousbounds to evaluate their performance.