La dysménorrhée: un problème pour le pédiatre [Dysmenorrhea: a problem for the pediatrician?].

Dysmenorrhea is common in adolescent years, especially after the onset of ovulatory cycles, usually 2 to 3 years after menarche. Pain and symptoms are responsible for school absenteeism and interruption of sports and social activities. OBJECTIVES: This study aims to measure the prevalence of severe dysmenorrhea and its consequences on adolescent girls in Switzerland. Treatment of dysmenorrhea is discussed and recommendations for clinical practice are given. STUDY DESIGN: Cross sectional survey (SMASH 02) on a nationally representative sample of adolescents (n=7548; 3340 females), aged 16 to 20 years who attended post-mandatory education. A self-administered questionnaire was used to assess the severity of dysmenorrhea and its consequences on daily life pursuit of medical help and medications used. RESULTS: Among 3340 girls, 86.6% suffered from dysmenorrhea-related symptoms: 12.4% described having severe dysmenorrhea and 74.2% moderate dysmenorrhea. Girls with severe dysmenorrhea described heavier consequences on daily activities compared with girls without dysmenorrhea: 47.8% of girls with severe dysmenorrhea reported staying at home and 66.5% declared reducing their sportive activities. Yet, fewer than half have consulted a physician for this complaint and even fewer were treated properly. RECOMMENDATION: The pediatrician has a pivotal role in screening young patients for dysmenorrhea, as well as, educating and effectively treating adolescent girls with menstruation-associated symptoms. Non-steroidal anti-inflammatory drugs are considered the first-line of treatment for dysmenorrhea, and adolescents with symptoms that do not respond to this treatment for 3 menstrual periods should be offered combined oestroprogestative contraception and must be followed up, as non-responders may have an underlying organic pathology. CONCLUSION: Dysmenorrhea is a frequent health problem in adolescent years and adolescent care providers should be able to care for these patients in an efficient way.

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.

A mathematical excursion: From the three-door problem to a Cantor-type perfect set

We start with a generalization of the well-known three-door problem:the n-door problem. The solution of this new problem leads us toa beautiful representation system for real numbers in (0,1] as alternated series, known in the literature as Pierce expansions. A closer look to Pierce expansions will take us to some metrical properties of sets defined through the Pierce expansions of its elements. Finally, these metrical properties will enable us to present 'strange' sets, similar to the classical Cantor set.

Minimax lower bounds for the two-armed bandit problem

We obtain minimax lower bounds on the regret for the classicaltwo--armed bandit problem. We provide a finite--sample minimax version of the well--known log $n$ asymptotic lower bound of Lai and Robbins. Also, in contrast to the log $n$ asymptotic results on the regret, we show that the minimax regret is achieved by mere random guessing under fairly mild conditions on the set of allowable configurations of the two arms. That is, we show that for {\sl every} allocation rule and for {\sl every} $n$, there is a configuration such that the regret at time $n$ is at least 1 -- $\epsilon$ times the regret of random guessing, where $\epsilon$ is any small positive constant.

The P-median problem in a changing network: The case of Barcelona

In this paper a p--median--like model is formulated to address theissue of locating new facilities when there is uncertainty. Severalpossible future scenarios with respect to demand and/or the travel times/distanceparameters are presented. The planner will want a strategy of positioning thatwill do as ``well as possible'' over the future scenarios. This paper presents a discrete location model formulation to address this P--Medianproblem under uncertainty. The model is applied to the location of firestations in Barcelona.

Driver scheduling problem modelling

The Drivers Scheduling Problem (DSP) consists of selecting a set of duties for vehicle drivers, for example buses, trains, plane or boat drivers or pilots, for the transportation of passengers or goods. This is a complex problem because it involves several constraints related to labour and company rules and can also present different evaluation criteria and objectives. Being able to develop an adequate model for this problem that can represent the real problem as close as possible is an important research area.The main objective of this research work is to present new mathematical models to the DSP problem that represent all the complexity of the drivers scheduling problem, and also demonstrate that the solutions of these models can be easily implemented in real situations. This issue has been recognized by several authors and as important problem in Public Transportation. The most well-known and general formulation for the DSP is a Set Partition/Set Covering Model (SPP/SCP). However, to a large extend these models simplify some of the specific business aspects and issues of real problems. This makes it difficult to use these models as automatic planning systems because the schedules obtained must be modified manually to be implemented in real situations. Based on extensive passenger transportation experience in bus companies in Portugal, we propose new alternative models to formulate the DSP problem. These models are also based on Set Partitioning/Covering Models; however, they take into account the bus operator issues and the perspective opinions and environment of the user.We follow the steps of the Operations Research Methodology which consist of: Identify the Problem; Understand the System; Formulate a Mathematical Model; Verify the Model; Select the Best Alternative; Present the Results of theAnalysis and Implement and Evaluate. All the processes are done with close participation and involvement of the final users from different transportation companies. The planner s opinion and main criticisms are used to improve the proposed model in a continuous enrichment process. The final objective is to have a model that can be incorporated into an information system to be used as an automatic tool to produce driver schedules. Therefore, the criteria for evaluating the models is the capacity to generate real and useful schedules that can be implemented without many manual adjustments or modifications. We have considered the following as measures of the quality of the model: simplicity, solution quality and applicability. We tested the alternative models with a set of real data obtained from several different transportation companies and analyzed the optimal schedules obtained with respect to the applicability of the solution to the real situation. To do this, the schedules were analyzed by the planners to determine their quality and applicability. The main result of this work is the proposition of new mathematical models for the DSP that better represent the realities of the passenger transportation operators and lead to better schedules that can be implemented directly in real situations.

Metaheuristics for the bus-driver scheduling problem

We present new metaheuristics for solving real crew scheduling problemsin a public transportation bus company. Since the crews of thesecompanies are drivers, we will designate the problem by the bus-driverscheduling problem. Crew scheduling problems are well known and severalmathematical programming based techniques have been proposed to solvethem, in particular using the set-covering formulation. However, inpractice, there exists the need for improvement in terms of computationalefficiency and capacity of solving large-scale instances. Moreover, thereal bus-driver scheduling problems that we consider can present variantaspects of the set covering, as for example a different objectivefunction, implying that alternative solutions methods have to bedeveloped. We propose metaheuristics based on the following approaches:GRASP (greedy randomized adaptive search procedure), tabu search andgenetic algorithms. These metaheuristics also present some innovationfeatures based on and genetic algorithms. These metaheuristics alsopresent some innovation features based on the structure of the crewscheduling problem, that guide the search efficiently and able them tofind good solutions. Some of these new features can also be applied inthe development of heuristics to other combinatorial optimizationproblems. A summary of computational results with real-data problems ispresented.

Note on the blocking flow shop problem

We present some results attained with different algorithms for the Fm|block|Cmax problem using as experimental data the well-known Taillard instances.

Alcohol consumption in late adolescence and early adulthood - where is the problem?

Risky single-occasion drinking (RSOD) is more common in late adolescence and early adulthood (approximately between the ages of 16 and 30) than in any other period in life. This is also the age when young people in Switzerland and many other European countries are legally allowed to buy and drink alcohol, but they usually do not yet have adult responsibilities. This paper reviews evidence from the international literature and provides examples of studies conducted in Switzerland demonstrating that (a) RSOD is by far most prevalent on Saturday evenings followed by Friday evenings, usually because young people go out and do not have any work or study responsibilities the next day; (b) RSOD results from drinking in private before going out ("predrinking") and accelerating the pace of drinking (i.e. increasing the number of drinks consumed per hour); (c) RSOD is often not accidental but purposeful,. to seek excitement, to have fun and to feel the effects of alcohol; (d) RSOD occurs predominantly outside the home, mostly in bars, pubs, discos or at special events and festivals; (e) RSOD often results in intended and unintended injuries and other acute consequences, which are leading risk factors for mortality and morbidity in this age group. Effective prevention strategies should include attempts to reduce opportunities to engage in heavy drinking as well as strategies to reduce its harmful consequences.

Seizure semiology: an overview of the 'inverse problem'.

In clinical practice, a classification of seizures based on clinical signs and symptoms leads to an improved understanding of epilepsy-related issues and therefore strongly contributes to a better patient care. The inverse problem involves inferring the anatomical brain localization of a seizure from the scalp surface EEG, a concept we apply here to correlate seizure origin with seizure semiology. The spheres of sensorium, motor features, consciousness changes and autonomic alterations during ictal and postictal manifestations are reviewed, including several subdivisions used to better categorize particular features. Particular attention is given to behavioral features, as well as to features occurring in idiopathic generalized epileptic syndromes and psychogenic nonepileptic spells.

Rehabilitation of orbital cavity after total orbital exenteration using oculofacial prostheses anchored by osseointegrated dental implants posed as a one-step surgical procedure

BACKGROUND: Total orbital exenteration is a radical surgical procedure, which typically involves the removal of the entire contents of the orbit including the periorbita, leaving the patient with a deep orbital deformity and results in devastating cosmetic, functional, and psychological consequences requiring difficult and challenging procedures for oculoplastic surgeons. Oculofacial prostheses retained by endosseous dental implants present an attractive and viable alternative when aesthetic and functional demands are beyond the capacity of local reconstructive efforts. PATIENTS AND METHODS: A 72-year-old woman presenting a malignant melanoma of the right eyelids and a 77-year-old man presenting a sebaceous carcinoma of the left upper eyelid underwent a total exenteration followed by positioning of endosseous implants (Straumann system Dental implants) as an integrated one-step combined surgical procedure. The oculofacial prosthesis was placed after epithelialization of the orbital cavity. RESULTS: The implants were perfectly osseointegrated without any complications, providing sufficient retention of the prostheses. A satisfactory aesthetic outcome has been achieved for both patients. CONCLUSIONS: Oculofacial prostheses anchored by osseointegrated dental implants placed as one-step surgical procedure ensure an adequate aesthetic result as well as a considerably decreased rehabilitation time and present a satisfactory solution when reconstruction is not a suitable option.

Constitution, Diversification and Normalisation of a Health Problem: Organising the Fight against AIDS in Switzerland (1984-2005)

The article traces the formation, diversification and normalization of the AIDS cause in Switzerland. Particular emphasis is placed on interactions between the medical field, public authorities and associative space, the latter being understood as the place where individual and collective actors compete to define the cause. The authors argue that the major phases in the structuring of the struggle, the pace of state intervention and the creation of a multi-organizational field, can only be understood if one adopts a 'configurational perspective' attentive to the manner in which, in a given context and under the effect of particular constraints, key actors strategically interact and contribute to transforming their environment and their chances of reaching their goals. This approach takes into account the changing socio-biological characteristics of those who have committed themselves to the cause. In turn, internal movement divisions about how to respond to the epidemic as well as the changing perceptions of the disease have modified the opportunities for commitment, encouraging certain individual kinds of people and excluding others.

A hybrid algorithm combining metaheuristic with Monte Carlo simulation for solving the Stochastic Flow Shop problem

In this paper, a hybrid simulation-based algorithm is proposed for the StochasticFlow Shop Problem. The main idea of the methodology is to transform the stochastic problem into a deterministic problem and then apply simulation to the latter. In order to achieve this goal, we rely on Monte Carlo Simulation and an adapted version of a deterministic heuristic. This approach aims to provide flexibility and simplicity due to the fact that it is not constrained by any previous assumption and relies in well-tested heuristics.

A hybrid algorithm combining metaheuristic with Monte Carlo simulation for solving the Stochastic Flow Shop problem

In this paper, a hybrid simulation-based algorithm is proposed for the StochasticFlow Shop Problem. The main idea of the methodology is to transform the stochastic problem into a deterministic problem and then apply simulation to the latter. In order to achieve this goal, we rely on Monte Carlo Simulation and an adapted version of a deterministic heuristic. This approach aims to provide flexibility and simplicity due to the fact that it is not constrained by any previous assumption and relies in well-tested heuristics.

The continuous wavelet transform as a maximum entropy solution of the corresponding inverse problem

The continuous wavelet transform is obtained as a maximumentropy solution of the corresponding inverse problem. It is well knownthat although a signal can be reconstructed from its wavelet transform,the expansion is not unique due to the redundancy of continuous wavelets.Hence, the inverse problem has no unique solution. If we want to recognizeone solution as "optimal", then an appropriate decision criterion hasto be adopted. We show here that the continuous wavelet transform is an"optimal" solution in a maximum entropy sense.