Use of alternative and complementary therapies in labor and delivery care: a cross-sectional study of midwives" training in Catalan hospitals accredited as centers for normal birth

Background: The use of complementary and alternative medicine (CAM) and complementary and alternative therapies (CAT) during pregnancy is increasing. Scientific evidence for CAM and CAT in the field of obstetrics mainly covers pain relief in labor. Midwives are responsible for labor and delivery care: hence, their knowledge of CAM and CAT is important. The aims of this study are to describe the professional profile of midwives who provide care for natural childbirth in Catalan hospitals accredited as centers for normal birth, to assess midwives" level of training in CAT and their use of these therapies, and to identify specific resources for CAT in labor wards. Methods: A descriptive, cross-sectional, quantitative method was used to assess the level of training and use of CAT by midwives working at 28 hospitals in Catalonia, Spain, accredited as public normal birth centers. Results: Just under a third of midwives (30.4%) trained in CAT after completion of basic training. They trained in an average of 5.97 therapies (SD 3.56). The number of CAT in which the midwives were trained correlated negatively with age (r = - 0.284; p < 0.001) and with their time working at the hospital in years (r = - 0.136; p = 0.036). Midwives trained in CAT considered that the following therapies were useful or very useful for pain relief during labor and delivery: relaxation techniques (64.3%), hydrotherapy (84.8%) and the application of compresses to the perineum (75.9%). The availability of resources for providing CAT during normal birth care varied widely from center to center. Conclusions: Age may influence attitudes towards training. It is important to increase the number of midwives trained in CAM for pain relief during childbirth, in order to promote the use of CAT and ensure efficiency and safety. CAT resources at accredited hospitals providing normal childbirth care should also be standardized.

Use of alternative and complementary therapies in labor and delivery care: a cross-sectional study of midwives" training in Catalan hospitals accredited as centers for normal birth

Background: The use of complementary and alternative medicine (CAM) and complementary and alternative therapies (CAT) during pregnancy is increasing. Scientific evidence for CAM and CAT in the field of obstetrics mainly covers pain relief in labor. Midwives are responsible for labor and delivery care: hence, their knowledge of CAM and CAT is important. The aims of this study are to describe the professional profile of midwives who provide care for natural childbirth in Catalan hospitals accredited as centers for normal birth, to assess midwives" level of training in CAT and their use of these therapies, and to identify specific resources for CAT in labor wards. Methods: A descriptive, cross-sectional, quantitative method was used to assess the level of training and use of CAT by midwives working at 28 hospitals in Catalonia, Spain, accredited as public normal birth centers. Results: Just under a third of midwives (30.4%) trained in CAT after completion of basic training. They trained in an average of 5.97 therapies (SD 3.56). The number of CAT in which the midwives were trained correlated negatively with age (r = - 0.284; p < 0.001) and with their time working at the hospital in years (r = - 0.136; p = 0.036). Midwives trained in CAT considered that the following therapies were useful or very useful for pain relief during labor and delivery: relaxation techniques (64.3%), hydrotherapy (84.8%) and the application of compresses to the perineum (75.9%). The availability of resources for providing CAT during normal birth care varied widely from center to center. Conclusions: Age may influence attitudes towards training. It is important to increase the number of midwives trained in CAM for pain relief during childbirth, in order to promote the use of CAT and ensure efficiency and safety. CAT resources at accredited hospitals providing normal childbirth care should also be standardized.

Programa integral de atención a las personas mayores en una zona rural

We describe a community intervention program performed in three rural villages in the Alt Empordà region (Girona province). The study provides data on the services available to the elderly in a specific context, based on an initiative proposed by the villages, the local councils, and the elderly themselves. The program is a research-action plan which applies the participative and qualitative methodology characteristic of strategic planning. The study analyses how the initiative arose, the description of the process, and the different parts of the intervention program

L'Anatomia artística a l"Escola de Belles Arts de Barcelona. Els casos de Jeroni Faraudo (1823-1886) i de Tiberio Ávila (1843-1932)

[cat] Aquest article se centra en la significació i transcendència de l"assignatura d"Anatomia artística a l"Escola de Belles Arts de Barcelona durant la segona meitat del segle XIX i principis de segle XX. S"empren, com a fil conductor, les figures de Jeroni Faraudo i Condeminas (1823-1886) i de Tiberio Ávila Rodríguez (1843-1932), els dos primers professors que impartiren la matèria i que romanen, en l"actualitat, pràcticament inèdits. El coneixement de l"ideari de Faraudo i d"Ávila permet completar el panorama de l"evolució de les idees estètiques a la Catalunya del moment i, alhora, contribueix a la comprensió de l"erosió de la primacia de l"antic en l"aprenentatge oficial de les arts a Catalunya. [spa] Este artículo se centra en la significación y transcendencia de la asignatura de Anatomía artística en la Escuela de Bellas Artes de Barcelona durante la segunda mitad del siglo XIX y principios de siglo XX. Se emplean, como hilo conductor, las figuras de Gerónimo Faraudo Condeminas (1823-1886) y de Tiberio Ávila Rodríguez (1843-1932), los dos primeros profesores que impartieron la materia y que permanecen, en la actualidad, prácticamente inéditos. El conocimiento del ideario de Faraudo y de Ávila permite completar el panorama de la evolución de las ideas estéticas en la Cataluña del momento y, al mismo tiempo, contribuye a la comprensión de la erosión de la primacía del antiguo en el aprendizaje oficial de las artes en Cataluña. [eng]This article focuses on the subject of Artistic Anatomy at the Barcelona School of Fine Arts during the second half of the 19th and early 20th centuries, discussing its signification. The connecting thread of this article are Jeroni Faraudo i Condeminas (1823-1886) and Tiberio Ávila Rodríguez (1843-1932), its first two teachers, who remain nowadays practically unknown. The knowledge of their ideas completes the history of contemporary Catalan aesthetics and also contributes to the comprehension of the erosion in the primacy of the use of ancient models in the official artistic teaching in Catalonia.

Error models in hydrogeology applications

Notre consommation en eau souterraine, en particulier comme eau potable ou pour l'irrigation, a considérablement augmenté au cours des années. De nombreux problèmes font alors leur apparition, allant de la prospection de nouvelles ressources à la remédiation des aquifères pollués. Indépendamment du problème hydrogéologique considéré, le principal défi reste la caractérisation des propriétés du sous-sol. Une approche stochastique est alors nécessaire afin de représenter cette incertitude en considérant de multiples scénarios géologiques et en générant un grand nombre de réalisations géostatistiques. Nous rencontrons alors la principale limitation de ces approches qui est le coût de calcul dû à la simulation des processus d'écoulements complexes pour chacune de ces réalisations. Dans la première partie de la thèse, ce problème est investigué dans le contexte de propagation de l'incertitude, oú un ensemble de réalisations est identifié comme représentant les propriétés du sous-sol. Afin de propager cette incertitude à la quantité d'intérêt tout en limitant le coût de calcul, les méthodes actuelles font appel à des modèles d'écoulement approximés. Cela permet l'identification d'un sous-ensemble de réalisations représentant la variabilité de l'ensemble initial. Le modèle complexe d'écoulement est alors évalué uniquement pour ce sousensemble, et, sur la base de ces réponses complexes, l'inférence est faite. Notre objectif est d'améliorer la performance de cette approche en utilisant toute l'information à disposition. Pour cela, le sous-ensemble de réponses approximées et exactes est utilisé afin de construire un modèle d'erreur, qui sert ensuite à corriger le reste des réponses approximées et prédire la réponse du modèle complexe. Cette méthode permet de maximiser l'utilisation de l'information à disposition sans augmentation perceptible du temps de calcul. La propagation de l'incertitude est alors plus précise et plus robuste. La stratégie explorée dans le premier chapitre consiste à apprendre d'un sous-ensemble de réalisations la relation entre les modèles d'écoulement approximé et complexe. Dans la seconde partie de la thèse, cette méthodologie est formalisée mathématiquement en introduisant un modèle de régression entre les réponses fonctionnelles. Comme ce problème est mal posé, il est nécessaire d'en réduire la dimensionnalité. Dans cette optique, l'innovation du travail présenté provient de l'utilisation de l'analyse en composantes principales fonctionnelles (ACPF), qui non seulement effectue la réduction de dimensionnalités tout en maximisant l'information retenue, mais permet aussi de diagnostiquer la qualité du modèle d'erreur dans cet espace fonctionnel. La méthodologie proposée est appliquée à un problème de pollution par une phase liquide nonaqueuse et les résultats obtenus montrent que le modèle d'erreur permet une forte réduction du temps de calcul tout en estimant correctement l'incertitude. De plus, pour chaque réponse approximée, une prédiction de la réponse complexe est fournie par le modèle d'erreur. Le concept de modèle d'erreur fonctionnel est donc pertinent pour la propagation de l'incertitude, mais aussi pour les problèmes d'inférence bayésienne. Les méthodes de Monte Carlo par chaîne de Markov (MCMC) sont les algorithmes les plus communément utilisés afin de générer des réalisations géostatistiques en accord avec les observations. Cependant, ces méthodes souffrent d'un taux d'acceptation très bas pour les problèmes de grande dimensionnalité, résultant en un grand nombre de simulations d'écoulement gaspillées. Une approche en deux temps, le "MCMC en deux étapes", a été introduite afin d'éviter les simulations du modèle complexe inutiles par une évaluation préliminaire de la réalisation. Dans la troisième partie de la thèse, le modèle d'écoulement approximé couplé à un modèle d'erreur sert d'évaluation préliminaire pour le "MCMC en deux étapes". Nous démontrons une augmentation du taux d'acceptation par un facteur de 1.5 à 3 en comparaison avec une implémentation classique de MCMC. Une question reste sans réponse : comment choisir la taille de l'ensemble d'entrainement et comment identifier les réalisations permettant d'optimiser la construction du modèle d'erreur. Cela requiert une stratégie itérative afin que, à chaque nouvelle simulation d'écoulement, le modèle d'erreur soit amélioré en incorporant les nouvelles informations. Ceci est développé dans la quatrième partie de la thèse, oú cette méthodologie est appliquée à un problème d'intrusion saline dans un aquifère côtier. -- Our consumption of groundwater, in particular as drinking water and for irrigation, has considerably increased over the years and groundwater is becoming an increasingly scarce and endangered resource. Nofadays, we are facing many problems ranging from water prospection to sustainable management and remediation of polluted aquifers. Independently of the hydrogeological problem, the main challenge remains dealing with the incomplete knofledge of the underground properties. Stochastic approaches have been developed to represent this uncertainty by considering multiple geological scenarios and generating a large number of realizations. The main limitation of this approach is the computational cost associated with performing complex of simulations in each realization. In the first part of the thesis, we explore this issue in the context of uncertainty propagation, where an ensemble of geostatistical realizations is identified as representative of the subsurface uncertainty. To propagate this lack of knofledge to the quantity of interest (e.g., the concentration of pollutant in extracted water), it is necessary to evaluate the of response of each realization. Due to computational constraints, state-of-the-art methods make use of approximate of simulation, to identify a subset of realizations that represents the variability of the ensemble. The complex and computationally heavy of model is then run for this subset based on which inference is made. Our objective is to increase the performance of this approach by using all of the available information and not solely the subset of exact responses. Two error models are proposed to correct the approximate responses follofing a machine learning approach. For the subset identified by a classical approach (here the distance kernel method) both the approximate and the exact responses are knofn. This information is used to construct an error model and correct the ensemble of approximate responses to predict the "expected" responses of the exact model. The proposed methodology makes use of all the available information without perceptible additional computational costs and leads to an increase in accuracy and robustness of the uncertainty propagation. The strategy explored in the first chapter consists in learning from a subset of realizations the relationship between proxy and exact curves. In the second part of this thesis, the strategy is formalized in a rigorous mathematical framework by defining a regression model between functions. As this problem is ill-posed, it is necessary to reduce its dimensionality. The novelty of the work comes from the use of functional principal component analysis (FPCA), which not only performs the dimensionality reduction while maximizing the retained information, but also allofs a diagnostic of the quality of the error model in the functional space. The proposed methodology is applied to a pollution problem by a non-aqueous phase-liquid. The error model allofs a strong reduction of the computational cost while providing a good estimate of the uncertainty. The individual correction of the proxy response by the error model leads to an excellent prediction of the exact response, opening the door to many applications. The concept of functional error model is useful not only in the context of uncertainty propagation, but also, and maybe even more so, to perform Bayesian inference. Monte Carlo Markov Chain (MCMC) algorithms are the most common choice to ensure that the generated realizations are sampled in accordance with the observations. Hofever, this approach suffers from lof acceptance rate in high dimensional problems, resulting in a large number of wasted of simulations. This led to the introduction of two-stage MCMC, where the computational cost is decreased by avoiding unnecessary simulation of the exact of thanks to a preliminary evaluation of the proposal. In the third part of the thesis, a proxy is coupled to an error model to provide an approximate response for the two-stage MCMC set-up. We demonstrate an increase in acceptance rate by a factor three with respect to one-stage MCMC results. An open question remains: hof do we choose the size of the learning set and identify the realizations to optimize the construction of the error model. This requires devising an iterative strategy to construct the error model, such that, as new of simulations are performed, the error model is iteratively improved by incorporating the new information. This is discussed in the fourth part of the thesis, in which we apply this methodology to a problem of saline intrusion in a coastal aquifer.

Datos para la flora liquenica de CataluÑa. Liquenes epifilos

Se citan los táxones encontrados sobre hojas de Buxus sempervirens, haciendo un intento de clasificación según los trabajos de SANTESSON, 1952 y SERUSIAUX, 1977; a I d vez proponemos una relación-clasificación de los términos: epífito, foliícola, corticlcola y muscícola.

Algunos datos sobre las comunidades vegetales de la Fageda de Jorda (Olot)

A pocos kilómetros al este de Olot, entre la Costa de Pujou y el Puig de Sant Jordi de Sa Cot, el llano está cubierto en gran parte por hayedos frondosos. Ellos han merecido al paraje el nombre de Fageda de Jordá, al cual han dado celebridad ilustres poetas y pintores que encontraron allí, en condiciones de acceso excepcionalmente favorables, sin tener que realizar penosas ascensiones previas, toda la belleza de los grandes bosques de haya y la paz tranquila que reina en su interior, donde la luz tiene aquel tono roerá com d'aigua endinst de que nos habla MARAGALL.