The psychosocial difficulties in brain disorders that explain short term changes in health outcomes.

BACKGROUND: This study identifies a set of psychosocial difficulties that are associated with short term changes in health outcomes across a heterogeneous set of brain disorders, neurological and psychiatric. METHODS: Longitudinal observational study over approximately 12 weeks with three time points of assessment and 741 patients with depression, bipolar disorders, multiple sclerosis, parkinson's disease, migraine, traumatic brain injury and stroke. The data on disability was collected with the checklist of the International Classification of Functioning, Disability and Health. The selected health outcomes were the Short Form 36 and the World Health Organization Disability Assessment Schedule. Multilevel models for change were applied controlling for age, gender and disease severity. RESULTS: The psychosocial difficulties that explain the variability and change over time of the selected health outcomes were energy and drive, sleep, and emotional functions, and a broad range of activities and participation domains, such as solving problems, conversation, areas of mobility and self-care, relationships, community life and recreation and leisure. CONCLUSIONS: Our findings are of interest to researchers and clinicians for interventions and health systems planning as they show that in addition to difficulties that are diagnostic criteria of these disorders, there are other difficulties that explain small changes in health outcomes over short periods of time.

Estudi de la comprensió i de les estratègies per resoldre problemes de suma i resta

Aquest treball de recerca estudia i analitza la comprensió i les estratègies utilitzades per alumnes de 2n de primària a l’hora de resoldre problemes aritmètics de suma i resta. Per aconseguir aquest propòsit, s’ha portat a terme el disseny i l’aplicació d’una prova individual de resolució de problemes, passada abans i després d’una intervenció educativa enfocada a millorar les dificultats detectades a l’hora de resoldre problemes. A partir de l’anàlisi de les dades obtingudes es verificarà si després de treballar el procés de resolució i d’incidir en les estratègies per resoldre problemes additius amb els alumnes millora la comprensió i les estratègies aparegudes s’adeqüen al tipus d’operació aritmètica que es demana.

Proceso de transformación de las concepciones del profesorado sobre la resolución de problemas matemáticos

The aim of this study is to analyze the transformation of Primary School teachers’ conceptions about mathematical problem solving. We performed a study with 18 teachers from three public schools: in each class (from 1º to 6º) there were two interventions, and we were interviewed teachers before and after them. The results have show identified changes in: 1) teacher’s expectations about students’ abilities; classroom management; perception of diversity; mathematical strategies used by students; communication in the classroom; causes of the problems encountered; and relevance process of problem solving in mathematics teaching. The transformation of teachers’ conceptions is due to the following factors: a) awareness of the practice; b) systematic reflection; c) the contrast between different ways to work solving problems in math class

A parameter-free approach for solving combinatorial optimization problems through biased randomization of efficient heuristics

This paper discusses the use of probabilistic or randomized algorithms for solving combinatorial optimization problems. Our approach employs non-uniform probability distributions to add a biased random behavior to classical heuristics so a large set of alternative good solutions can be quickly obtained in a natural way and without complex conguration processes. This procedure is especially useful in problems where properties such as non-smoothness or non-convexity lead to a highly irregular solution space, for which the traditional optimization methods, both of exact and approximate nature, may fail to reach their full potential. The results obtained are promising enough to suggest that randomizing classical heuristics is a powerful method that can be successfully applied in a variety of cases.

Solving Large Location-Allocation problems by Clustering and Simulated Annealing

Globalization involves several facility location problems that need to be handled at large scale. Location Allocation (LA) is a combinatorial problem in which the distance among points in the data space matter. Precisely, taking advantage of the distance property of the domain we exploit the capability of clustering techniques to partition the data space in order to convert an initial large LA problem into several simpler LA problems. Particularly, our motivation problem involves a huge geographical area that can be partitioned under overall conditions. We present different types of clustering techniques and then we perform a cluster analysis over our dataset in order to partition it. After that, we solve the LA problem applying simulated annealing algorithm to the clustered and non-clustered data in order to work out how profitable is the clustering and which of the presented methods is the most suitable

Algorithm optimization for solving crew scheduling problems

In this paper, we are proposing a methodology to determine the most efficient and least costly way of crew pairing optimization. We are developing a methodology based on algorithm optimization on Eclipse opensource IDE using the Java programming language to solve the crew scheduling problems.

Solving two production scheduling problems with sequence-dependent set-up times

In today’s competitive markets, the importance of goodscheduling strategies in manufacturing companies lead to theneed of developing efficient methods to solve complexscheduling problems.In this paper, we studied two production scheduling problemswith sequence-dependent setups times. The setup times areone of the most common complications in scheduling problems,and are usually associated with cleaning operations andchanging tools and shapes in machines.The first problem considered is a single-machine schedulingwith release dates, sequence-dependent setup times anddelivery times. The performance measure is the maximumlateness.The second problem is a job-shop scheduling problem withsequence-dependent setup times where the objective is tominimize the makespan.We present several priority dispatching rules for bothproblems, followed by a study of their performance. Finally,conclusions and directions of future research are presented.

Solving higher-dimensional continuous time stochastic control problems by value function regression

The paper develops a method to solve higher-dimensional stochasticcontrol problems in continuous time. A finite difference typeapproximation scheme is used on a coarse grid of low discrepancypoints, while the value function at intermediate points is obtainedby regression. The stability properties of the method are discussed,and applications are given to test problems of up to 10 dimensions.Accurate solutions to these problems can be obtained on a personalcomputer.

Environmental management problems, future generations and social decisions

The decisions of many individuals and social groups, taking according to well-defined objectives, are causing serious social and environmental problems, in spite of following the dictates of economic rationality. There are many examples of serious problems for which there are not yet appropriate solutions, such as management of scarce natural resources including aquifer water or the distribution of space among incompatible uses. In order to solve these problems, the paper first characterizes the resources and goods involved from an economic perspective. Then, for each case, the paper notes that there is a serious divergence between individual and collective interests and, where possible, it designs the procedure for solving the conflict of interests. With this procedure, the real opportunities for the application of economic theory are shown, and especially the theory on collective goods and externalities. The limitations of conventional economic analysis are shown and the opportunity to correct the shortfalls is examined. Many environmental problems, such as climate change, have an impact on different generations that do not participate in present decisions. The paper shows that for these cases, the solutions suggested by economic theory are not valid. Furthermore, conventional methods of economic valuation (which usually help decision-makers) are unable to account for the existence of different generations and tend to obviate long-term impacts. The paper analyzes how economic valuation methods could account for the costs and benefits enjoyed by present and future generations. The paper studies an appropriate consideration of preferences for future consumption and the incorporation of sustainability as a requirement in social decisions, which implies not only more efficiency but also a fairer distribution between generations than the one implied by conventional economic analysis.

Mutigrid preconditioner for nonconforming discretization of elliptic problems with jump coefficients

In this paper, we present a multigrid preconditioner for solving the linear system arising from the piecewise linear nonconforming Crouzeix-Raviart discretization of second order elliptic problems with jump coe fficients. The preconditioner uses the standard conforming subspaces as coarse spaces. Numerical tests show both robustness with respect to the jump in the coe fficient and near-optimality with respect to the number of degrees of freedom.

Empirical approaches to inequality of opportunity: principles, measures, and evidence

We put together the different conceptual issues involved in measuring inequality of opportunity, discuss how these concepts have been translated into computable measures, and point out the problems and choices researchers face when implementing these measures. Our analysis identifies and suggests several new possibilities to measure inequality of opportunity. The approaches are illustrated with a selective survey of the empirical literature on income inequality of opportunity.

ILS-ESP An efficient, simple, and parameter-free algorithm for solving the permutation flow-shop problem

From a managerial point of view, the more effcient, simple, and parameter-free (ESP) an algorithm is, the more likely it will be used in practice for solving real-life problems. Following this principle, an ESP algorithm for solving the Permutation Flowshop Sequencing Problem (PFSP) is proposed in this article. Using an Iterated Local Search (ILS) framework, the so-called ILS-ESP algorithm is able to compete in performance with other well-known ILS-based approaches, which are considered among the most effcient algorithms for the PFSP. However, while other similar approaches still employ several parameters that can affect their performance if not properly chosen, our algorithm does not require any particular fine-tuning process since it uses basic "common sense" rules for the local search, perturbation, and acceptance criterion stages of the ILS metaheuristic. Our approach defines a new operator for the ILS perturbation process, a new acceptance criterion based on extremely simple and transparent rules, and a biased randomization process of the initial solution to randomly generate different alternative initial solutions of similar quality -which is attained by applying a biased randomization to a classical PFSP heuristic. This diversification of the initial solution aims at avoiding poorly designed starting points and, thus, allows the methodology to take advantage of current trends in parallel and distributed computing. A set of extensive tests, based on literature benchmarks, has been carried out in order to validate our algorithm and compare it against other approaches. These tests show that our parameter-free algorithm is able to compete with state-of-the-art metaheuristics for the PFSP. Also, the experiments show that, when using parallel computing, it is possible to improve the top ILS-based metaheuristic by just incorporating to it our biased randomization process with a high-quality pseudo-random number generator.

Causes of subcontracting: Evidence from panel data on construction firms

This paper examines factors explaining subcontracting decisions in the construction industry. Rather than the more common cross-sectional analyses, we use panel data to evaluate the influence of all relevant variables. We design and use a new index of the closeness to small numbers situations to estimate the extent of hold-up problems. Results show that as specificity grows, firms tend to subcontract less. The opposite happens when output heterogeneity and the use of intangible assets and capabilities increase. Neither temporary shortage of capacity nor geographical dispersion of activities seem to affect the extent of subcontracting. Finally, proxies for uncertainty do not show any clear effect.

Earnings management in Spain. Some evidence from companies quoted in the Spanish stock exchange

After the accounting scandals that have taken place mainly in the UnitedStates during the last years, some Spanish leading authorities havedefended the idea that this kind of accounting problems cannot happen inSpain. They argue that accounting regulation in Europe, and specificallyin Spain, make more difficult the use of creative accounting practices.The objective of this paper is to identify some evidence about thesituacion in Spain. The study tries to demonstrate that some accountingpractices of several of the companies quoted in the Spanish Stock Exchangecould be qualified as earnings management.To carry out this study, the authors have analysed the accounts of the 35companies included in the stock market index IBEX 35. This index iscalculated with the share prices variations of the most importantcompanies quoted in the Spanish Stock Exchange.

R&D cooperation and spillovers: Some empirical evidence

This paper provides some first empirical evidence on the relationshipbetween R&D spillovers and R&D cooperation. The results suggest disentangling different aspects of know-how flows. Firms which rate incoming spillovers more importantly and who can limit outgoing spillovers by a more effective protection of know-how, are more likely to cooperate in R&D. Our analysis also finds that cooperating firms have higher incoming spillovers and higher protection of know-how, indicating that cooperation may serve as a vehicle to manage information flows. Our results thus suggest that on the one hand the information sharing and coordination aspects of incoming spillovers are crucial in understanding cooperation, while on the other hand, protection against outgoing spillovers is important for firms to engage in stable cooperative agreements by reducing free-rider problems. Distinguishing different types of cooperative partners reveals that while managing outgoing spillovers is less critical in alliances with non-commercial research partners than between vertically related partners, the incoming spillovers seem to be more critical in understanding the former type of R&D cooperation.