Gestión óptima de embalses en avenidas incorporando al concepto de incertidumbre : aplicación a embalses con central hidroeléctrica

Esta tesis realiza una contribución metodológica al problema de la gestión óptima de embalses hidroeléctricos durante eventos de avenidas, considerando un enfoque estocástico y multiobjetivo. Para ello se propone una metodología de evaluación de estrategias de laminación en un contexto probabilístico y multiobjetivo. Además se desarrolla un entorno dinámico de laminación en tiempo real con pronósticos que combina un modelo de optimización y algoritmos de simulación. Estas herramientas asisten a los gestores de las presas en la toma de decisión respecto de cuál es la operación más adecuada del embalse. Luego de una detallada revisión de la bibliografía, se observó que los trabajos en el ámbito de la gestión óptima de embalses en avenidas utilizan, en general, un número reducido de series de caudales o hidrogramas para caracterizar los posibles escenarios. Limitando el funcionamiento satisfactorio de un modelo determinado a situaciones hidrológicas similares. Por otra parte, la mayoría de estudios disponibles en este ámbito abordan el problema de la laminación en embalses multipropósito durante la temporada de avenidas, con varios meses de duración. Estas características difieren de la realidad de la gestión de embalses en España. Con los avances computacionales en materia de gestión de información en tiempo real, se observó una tendencia a la implementación de herramientas de operación en tiempo real con pronósticos para determinar la operación a corto plazo (involucrando el control de avenidas). La metodología de evaluación de estrategias propuesta en esta tesis se basa en determinar el comportamiento de éstas frente a un espectro de avenidas características de la solicitación hidrológica. Con ese fin, se combina un sistema de evaluación mediante indicadores y un entorno de generación estocástica de avenidas, obteniéndose un sistema implícitamente estocástico. El sistema de evaluación consta de tres etapas: caracterización, síntesis y comparación, a fin de poder manejar la compleja estructura de datos resultante y realizar la evaluación. En la primera etapa se definen variables de caracterización, vinculadas a los aspectos que se quieren evaluar (seguridad de la presa, control de inundaciones, generación de energía, etc.). Estas variables caracterizan el comportamiento del modelo para un aspecto y evento determinado. En la segunda etapa, la información de estas variables se sintetiza en un conjunto de indicadores, lo más reducido posible. Finalmente, la comparación se lleva a cabo a partir de la comparación de esos indicadores, bien sea mediante la agregación de dichos objetivos en un indicador único, o bien mediante la aplicación del criterio de dominancia de Pareto obteniéndose un conjunto de soluciones aptas. Esta metodología se aplicó para calibrar los parámetros de un modelo de optimización de embalse en laminación y su comparación con otra regla de operación, mediante el enfoque por agregación. Luego se amplió la metodología para evaluar y comparar reglas de operación existentes para el control de avenidas en embalses hidroeléctricos, utilizando el criterio de dominancia. La versatilidad de la metodología permite otras aplicaciones, tales como la determinación de niveles o volúmenes de seguridad, o la selección de las dimensiones del aliviadero entre varias alternativas. Por su parte, el entorno dinámico de laminación al presentar un enfoque combinado de optimización-simulación, permite aprovechar las ventajas de ambos tipos de modelos, facilitando la interacción con los operadores de las presas. Se mejoran los resultados respecto de los obtenidos con una regla de operación reactiva, aun cuando los pronósticos se desvían considerablemente del hidrograma real. Esto contribuye a reducir la tan mencionada brecha entre el desarrollo teórico y la aplicación práctica asociada a los modelos de gestión óptima de embalses. This thesis presents a methodological contribution to address the problem about how to operate a hydropower reservoir during floods in order to achieve an optimal management considering a multiobjective and stochastic approach. A methodology is proposed to assess the flood control strategies in a multiobjective and probabilistic framework. Additionally, a dynamic flood control environ was developed for real-time operation, including forecasts. This dynamic platform combines simulation and optimization models. These tools may assist to dam managers in the decision making process, regarding the most appropriate reservoir operation to be implemented. After a detailed review of the bibliography, it was observed that most of the existing studies in the sphere of flood control reservoir operation consider a reduce number of hydrographs to characterize the reservoir inflows. Consequently, the adequate functioning of a certain strategy may be limited to similar hydrologic scenarios. In the other hand, most of the works in this context tackle the problem of multipurpose flood control operation considering the entire flood season, lasting some months. These considerations differ from the real necessity in the Spanish context. The implementation of real-time reservoir operation is gaining popularity due to computational advances and improvements in real-time data management. The methodology proposed in this thesis for assessing the strategies is based on determining their behavior for a wide range of floods, which are representative of the hydrological forcing of the dam. An evaluation algorithm is combined with a stochastic flood generation system to obtain an implicit stochastic analysis framework. The evaluation system consists in three stages: characterizing, synthesizing and comparing, in order to handle the complex structure of results and, finally, conduct the evaluation process. In the first stage some characterization variables are defined. These variables should be related to the different aspects to be evaluated (such as dam safety, flood protection, hydropower, etc.). Each of these variables characterizes the behavior of a certain operating strategy for a given aspect and event. In the second stage this information is synthesized obtaining a reduced group of indicators or objective functions. Finally, the indicators are compared by means of an aggregated approach or by a dominance criterion approach. In the first case, a single optimum solution may be achieved. However in the second case, a set of good solutions is obtained. This methodology was applied for calibrating the parameters of a flood control model and to compare it with other operating policy, using an aggregated method. After that, the methodology was extent to assess and compared some existing hydropower reservoir flood control operation, considering the Pareto approach. The versatility of the method allows many other applications, such as determining the safety levels, defining the spillways characteristics, among others. The dynamic framework for flood control combines optimization and simulation models, exploiting the advantages of both techniques. This facilitates the interaction between dam operators and the model. Improvements are obtained applying this system when compared with a reactive operating policy, even if the forecasts deviate significantly from the observed hydrograph. This approach contributes to reduce the gap between the theoretical development in the field of reservoir management and its practical applications.

Most central nervous system D2 dopamine receptors are coupled to their effectors by Go

We reported previously that Go-deficient mice develop severe neurological defects that include hyperalgesia, a generalized tremor, lack of coordination, and a turning syndrome somewhat reminiscent of unilateral lesions of the dopaminergic nigro-striatal pathway. By using frozen coronal sections of serially sectioned brains of normal and Go-deficient mice, we studied the ability of several G protein coupled receptors to promote binding of GTPγS to G proteins and the ability of GTP to promote a shift in the affinity of D2 dopamine receptor for its physiologic agonist dopamine. We found a generalized, but not abolished reduction in agonist-stimulated binding of GTPγS to frozen brain sections, with no significant left–right differences. Unexpectedly, the ability of GTP to regulate the binding affinity of dopamine to D2 receptors (as seen in in situ [35S]sulpiride displacement curves) that was robust in control mice, was absent in Go-deficient mice. The data suggest that most of the effects of the Gi/Go-coupled D2 receptors in the central nervous system are mediated by Go instead of Gi1, Gi2, or Gi3. In agreement with this, the effect of GTP on dopamine binding to D2 receptors in double Gi1 plus Gi2- and Gi1 plus Gi3-deficient mice was essentially unaffected.

User's manual for QUEWZ-92.

Texas Department of Transportation, Austin

Binomial leap methods for simulating stochastic chemical kinetics

This paper discusses efficient simulation methods for stochastic chemical kinetics. Based on the tau-leap and midpoint tau-leap methods of Gillespie [D. T. Gillespie, J. Chem. Phys. 115, 1716 (2001)], binomial random variables are used in these leap methods rather than Poisson random variables. The motivation for this approach is to improve the efficiency of the Poisson leap methods by using larger stepsizes. Unlike Poisson random variables whose range of sample values is from zero to infinity, binomial random variables have a finite range of sample values. This probabilistic property has been used to restrict possible reaction numbers and to avoid negative molecular numbers in stochastic simulations when larger stepsize is used. In this approach a binomial random variable is defined for a single reaction channel in order to keep the reaction number of this channel below the numbers of molecules that undergo this reaction channel. A sampling technique is also designed for the total reaction number of a reactant species that undergoes two or more reaction channels. Samples for the total reaction number are not greater than the molecular number of this species. In addition, probability properties of the binomial random variables provide stepsize conditions for restricting reaction numbers in a chosen time interval. These stepsize conditions are important properties of robust leap control strategies. Numerical results indicate that the proposed binomial leap methods can be applied to a wide range of chemical reaction systems with very good accuracy and significant improvement on efficiency over existing approaches. (C) 2004 American Institute of Physics.

UML approach to the generation of test sequences for Java-based concurrent systems

Starting with a UML specification that captures the underlying functionality of some given Java-based concurrent system, we describe a systematic way to construct, from this specification, test sequences for validating an implementation of the system. The approach is to first extend the specification to create UML state machines that directly address those aspects of the system we wish to test. To be specific, the extended UML state machines can capture state information about the number of waiting threads or the number of threads blocked on a given object. Using the SAL model checker we can generate from the extended UML state machines sequences that cover all the various possibilities of events and states. These sequences can then be directly transformed into test sequences suitable for input into a testing tool such as ConAn. As an illustration, the methodology is applied to generate sequences for testing a Java implementation of the producer-consumer system. © 2005 IEEE

Time scale analysis for fluidizedbedmeltgranulation-II: binder spreading rate

The spreading time of liquid binder droplet on the surface a primary particle is analyzed for Fluidized Bed Melt Granulation (FBMG). As discussed in the first paper of this series (Chua et al., in press) the droplet spreading rate has been identified as one of the important parameters affecting the probability of particles aggregation in FBMG. In this paper, the binder droplet spreading time has been estimated using Computational Fluid Dynamic modeling (CFD) based on Volume of Fluid approach (VOF). A simplified analytical solution has been developed and tested to explore its validity for predicting the spreading time. For the purpose of models validation, the droplet spreading evolution was recorded using a high speed video camera. Based on the validated model, a generalized correlative equation for binder spreading time is proposed. For the operating conditions considered here, the spreading time for Polyethylene Glycol (PEG1500) binder was found to fall within the range of 10-2 to 10-5 s. The study also included a number of other common binders used in FBMG. The results obtained here will be further used in paper III, where the binder solidification rate is discussed.

Wireless power charger for light electric vehicles

Wireless power transmission technology is gaining more and more attentions in city transportation applications due to its commensurate power level and efficiency with conductive power transfer means. In this paper, an inductively coupled wireless charging system for 48V light electric vehicle is proposed. The power stages of the system is evaluated and designed, including the high frequency inverter, the resonant network, full bridge rectifier, and the load matching converter. Small signal modeling and linear control technology is applied to the load matching converter for input voltage control, which effectively controls the wireless power flow. The prototype is built with a dsPIC digital signal controller; the experiments are carried out, and the results reveal nature performances of a series-series resonant inductive power charger in terms of frequency, air-gap length, power flow control, and efficiency issues.

Analysis and design of power management scheme for an on-board solar energy storage system

This paper investigates the power management issues in a mobile solar energy storage system. A multi-converter based energy storage system is proposed, in which solar power is the primary source while the grid or the diesel generator is selected as the secondary source. The existence of the secondary source facilitates the battery state of charge detection by providing a constant battery charging current. Converter modeling, multi-converter control system design, digital implementation and experimental verification are introduced and discussed in details. The prototype experiment indicates that the converter system can provide a constant charging current during solar converter maximum power tracking operation, especially during large solar power output variation, which proves the feasibility of the proposed design. © 2014 IEEE.

Bayesian Learning with Dependency Structures via Latent Factors, Mixtures, and Copulas

Bayesian methods offer a flexible and convenient probabilistic learning framework to extract interpretable knowledge from complex and structured data. Such methods can characterize dependencies among multiple levels of hidden variables and share statistical strength across heterogeneous sources. In the first part of this dissertation, we develop two dependent variational inference methods for full posterior approximation in non-conjugate Bayesian models through hierarchical mixture- and copula-based variational proposals, respectively. The proposed methods move beyond the widely used factorized approximation to the posterior and provide generic applicability to a broad class of probabilistic models with minimal model-specific derivations. In the second part of this dissertation, we design probabilistic graphical models to accommodate multimodal data, describe dynamical behaviors and account for task heterogeneity. In particular, the sparse latent factor model is able to reveal common low-dimensional structures from high-dimensional data. We demonstrate the effectiveness of the proposed statistical learning methods on both synthetic and real-world data.

Adhésion au traitement antidiabétique oral chez les adultes atteints de diabète de type 2 : déterminants et interventions visant à l'améliorer

Introduction : Le diabète de type 2 est une maladie évolutive débilitante et souvent mortelle qui atteint de plus en plus de personnes dans le monde. Le traitement antidiabétique non-insulinique (TADNI) notamment le traitement antidiabétique oral (TADO) est le plus fréquemment utilisé chez les adultes atteints de cette maladie. Toutefois, plusieurs de ces personnes ne prennent pas leur TADO tel que prescrit posant ainsi la problématique d’une adhésion sous-optimale. Ceci entraîne des conséquences néfastes aussi bien pour les patients que pour la société dans laquelle ils vivent. Il serait donc pertinent d’identifier des pistes de solution à cette problématique. Objectifs : Trois objectifs de recherche ont été étudiés : 1) Explorer la capacité de la théorie du comportement planifié (TCP) à prédire l’adhésion future au TADNI chez les adultes atteints de diabète de type 2, 2) Évaluer l’efficacité globale des interventions visant à améliorer l’adhésion au TADO chez les adultes atteints de diabète de type 2 et étudier l’influence des techniques de changement de comportement sur cette efficacité globale, et 3) Évaluer l’efficacité globale de l’entretien motivationnel sur l’adhésion au traitement médicamenteux chez les adultes atteints de maladie chronique et étudier l’influence des caractéristiques de cette intervention sur son efficacité globale. Méthodes : Pour l’objectif 1 : Il s’agissait d’une enquête web, suivie d’une évaluation de l’adhésion au TADNI sur une période de 30 jours, chez des adultes atteints de diabète de type 2, membres de Diabète Québec. L’enquête consistait à la complétion d’un questionnaire auto-administré incluant les variables de la TCP (intention, contrôle comportemental perçu et attitude) ainsi que d’autres variables dites «externes». Les informations relatives au calcul de l’adhésion provenaient des dossiers de pharmacie des participants transmis via la plateforme ReMed. Une régression linéaire multivariée a été utilisée pour estimer la mesure d’association entre l’intention et l’adhésion future au TADNI ainsi que l’interaction entre l’adhésion passée et l’intention. Pour répondre aux objectifs 2 et 3, deux revues systématiques et méta-analyses ont été effectuées et rapportées selon les lignes directrices de PRISMA. Un modèle à effets aléatoires a été utilisé pour estimer l’efficacité globale (g d’Hedges) des interventions et son intervalle de confiance à 95 % (IC95%) dans chacune des revues. Nous avons également quantifié l’hétérogénéité (I2 d’Higgins) entre les études, et avons fait des analyses de sous-groupe et des analyses de sensibilité. Résultats : Objectif 1 : Il y avait une interaction statistiquement significative entre l’adhésion passée et l’intention (valeur-p= 0,03). L’intention n’était pas statistiquement associée à l’adhésion future au TADNI, mais son effet était plus fort chez les non-adhérents que chez les adhérents avant l’enquête web. En revanche, l’intention était principalement prédite par le contrôle comportemental perçu à la fois chez les adhérents [β= 0,90, IC95%= (0,80; 1,00)] et chez les non-adhérents passés [β= 0,76, IC95%= (0,56; 0,97)]. Objectif 2 : L’efficacité globale des interventions sur l’adhésion au TADO était de 0,21 [IC95%= (-0,05; 0,47); I2= 82 %]. L’efficacité globale des interventions dans lesquelles les intervenants aidaient les patients et/ou les cliniciens à être proactifs dans la gestion des effets indésirables était de 0,64 [IC95%= (0,31; 0,96); I2= 56 %]. Objectif 3 : L’efficacité globale des interventions (basées sur l’entretien motivationnel) sur l’adhésion au traitement médicamenteux était de 0,12 [IC95%= (0,05; 0,20); I2= 1 %. Les interventions basées uniquement sur l’entretien motivationnel [β= 0,18, IC95%= (0,00; 0,36)] et celles dans lesquelles les intervenants ont été coachés [β= 0,47, IC95%= (0,03; 0,90)] étaient les plus efficaces. Aussi, les interventions administrées en face-à-face étaient plus efficaces que celles administrées par téléphone [β= 0,27, IC95%=(0,04; 0,50)]. Conclusion : Il existe un écart entre l’intention et l’adhésion future au TADNI, qui est partiellement expliqué par le niveau d’adhésion passée. Toutefois, il n’y avait pas assez de puissance statistique pour démontrer une association statistiquement significative entre l’intention et l’adhésion future chez les non-adhérents passés. D’un autre côté, quelques solutions au problème de l’adhésion sous-optimale au TADO ont été identifiées. En effet, le fait d’aider les patients et/ou les cliniciens à être proactifs dans la gestion des effets indésirables contribue efficacement à l’amélioration de l’adhésion au TADO chez les adultes atteints de diabète de type 2. Aussi, les interventions basées sur l’entretien motivationnel améliorent efficacement l’adhésion au traitement médicamenteux chez les adultes atteints de maladie chronique. L’entretien motivationnel pourrait donc être utilisé comme un outil clinique pour soutenir les patients dans l’autogestion de leur TADO.

Impact populationnel de la vaccination contre les virus du papillome humain : revue systématique et synthèse des prédictions de 16 modèles mathématiques dynamiques

Introduction: En 2015, 65 pays avaient des programmes de vaccination contre les VPH. La modélisation mathématique a joué un rôle crucial dans leur implantation. Objectifs: Nous avons réalisé une revue systématique et analysé les prédictions de modèles mathématiques de l’efficacité populationnelle de la vaccination sur la prévalence des VPH-16/18/6/11 chez les femmes et les hommes, afin d’évaluer la robustesse/variabilité des prédictions concernant l’immunité de groupe, le bénéfice ajouté par la vaccination des garçons et l’élimination potentielle des VPH-16/18/6/11. Méthodes: Nous avons cherché dans Medline/Embase afin d’identifier les modèles dynamiques simulant l’impact populationnel de la vaccination sur les infections par les VPH-16/18/6/11 chez les femmes et les hommes. Les équipes participantes ont réalisé des prédictions pour 19 simulations standardisées. Nous avons calculé la réduction relative de la prévalence (RRprev) 70 ans après l’introduction de la vaccination. Les résultats présentés correspondent à la médiane(10ème;90èmeperccentiles) des prédictions. Les cibles de la vaccination étaient les filles seulement ou les filles & garçons. Résultats: 16/19 équipes éligibles ont transmis leurs prédictions. Lorsque 40% des filles sont vaccinées, la RRprev du VPH-16 est 53%(46%;68%) chez les femmes et 36%(28%;61%) chez les hommes. Lorsque 80% des filles sont vaccinées, la RRprev est 93%(90%;100%) chez les femmes et 83%(75%;100%) chez les hommes. Vacciner aussi les garçons augmente la RRprev de 18%(13%;32%) chez les femmes et 35%(27%;39%) chez les hommes à 40% de couverture, et 7%(0%;10%) et 16%(1%;25%) à 80% de couverture. Les RRprev étaient plus élevées pour les VPH-18/6/11 (vs. VPH-16). Si 80% des filles & garçons sont vaccinés, les VPH-16/18/6/11 pourraient être éliminés. Interprétation: Même si les modèles diffèrent entre eux, les prédictions s’accordent sur: 1)immunité de groupe élevée même à basse couverture, 2)RRprev supérieures pour les VPH-18/6/11 (vs. VPH-16), 3)augmenter la couverture chez les filles a un meilleur impact qu’ajouter les garçons, 4)vacciner 80% des filles & garçons pourraient éliminer les VPH-16/18/6/11.

Gait Regulation for Bipedal Locomotion

This work explores regulation of forward speed, step length, and slope walking for the passive-dynamic class of bipedal robots. Previously, an energy-shaping control for regulating forward speed has appeared in the literature; here we show that control to be a special case of a more general time-scaling control that allows for speed transitions in arbitrary time. As prior work has focused on potential energy shaping for fully actuated bipeds, we study in detail the shaping of kinetic energy for bipedal robots, giving special treatment to issues of underactuation. Drawing inspiration from features of human walking, an underactuated kinetic-shaping control is presented that provides efficient regulation of walking speed while adjusting step length. Previous results on energetic symmetries of bipedal walking are also extended, resulting in a control that allows regulation of speed and step length while walking on any slope. Finally we formalize the optimal gait regulation problem and propose a dynamic programming solution seeded with passive-dynamic limit cycles. Observations of the optimal solutions generated by this method reveal further similarities between passive dynamic walking and human locomotion and give insight into the structure of minimum-effort controls for walking.

Batch cooling crystallization of xylitol produced by biotechnological route

BACKGROUND: This work deals with the xylitol production by biotechnological routes emphasizing the purification process using crystallization. RESULTS: Xylitol volumetric productivity of 0.665 g L(-1) h(-1) and yield of 0.7024 g g(-1) were obtained after 92 h fermentation. The fermented broth (61.3 g L(-1) xylitol) was centrifuged, treated and concentrated obtain a syrup (745.3 g L(-1) xylitol) which was crystallized twice, xylitol crystals with 98.5-99.2% purity being obtained. CONCLUSION: The hypothetical distribution obtained permits the determination of modeling parameters, which make possible the estimation of crystal dominant size from different initial experimental conditions. (C) 2008 Society of Chemical Industry

Estimation of lung cancer diagnosis and treatment costs based on a patient-level analysis in Catalonia (Spain)

Background: Assessing of the costs of treating disease is necessary to demonstrate cost-effectiveness and to estimate the budget impact of new interventions and therapeutic innovations. However, there are few comprehensive studies on resource use and costs associated with lung cancer patients in clinical practice in Spain or internationally. The aim of this paper was to assess the hospital cost associated with lung cancer diagnosis and treatment by histology, type of cost and stage at diagnosis in the Spanish National Health Service. Methods: A retrospective, descriptive analysis on resource use and a direct medical cost analysis were performed. Resource utilisation data were collected by means of patient files from nine teaching hospitals. From a hospital budget impact perspective, the aggregate and mean costs per patient were calculated over the first three years following diagnosis or up to death. Both aggregate and mean costs per patient were analysed by histology, stage at diagnosis and cost type. Results: A total of 232 cases of lung cancer were analysed, of which 74.1% corresponded to non-small cell lung cancer (NSCLC) and 11.2% to small cell lung cancer (SCLC); 14.7% had no cytohistologic confirmation. The mean cost per patient in NSCLC ranged from 13,218 Euros in Stage III to 16,120 Euros in Stage II. The main cost components were chemotherapy (29.5%) and surgery (22.8%). Advanced disease stages were associated with a decrease in the relative weight of surgical and inpatient care costs but an increase in chemotherapy costs. In SCLC patients, the mean cost per patient was 15,418 Euros for limited disease and 12,482 Euros for extensive disease. The main cost components were chemotherapy (36.1%) and other inpatient costs (28.7%). In both groups, the Kruskall-Wallis test did not show statistically significant differences in mean cost per patient between stages. Conclusions: This study provides the costs of lung cancer treatment based on patient file reviews, with chemotherapy and surgery accounting for the major components of costs. This cost analysis is a baseline study that will provide a useful source of information for future studies on cost-effectiveness and on the budget impact of different therapeutic innovations in Spain.

Variable speed drive in fan system monitoring

Fan systems are responsible for approximately 10% of the electricity consumption in industrial and municipal sectors, and it has been found that there is energy-saving potential in these systems. To this end, variable speed drives (VSDs) are used to enhance the efficiency of fan systems. Usually, fan system operation is optimized based on measurements of the system, but there are seldom readily installed meters in the system that can be used for the purpose. Thus, sensorless methods are needed for the optimization of fan system operation. In this thesis, methods for the fan operating point estimation with a variable speed drive are studied and discussed. These methods can be used for the energy efficient control of the fan system without additional measurements. The operation of these methods is validated by laboratory measurements and data from an industrial fan system. In addition to their energy consumption, condition monitoring of fan systems is a key issue as fans are an integral part of various production processes. Fan system condition monitoring is usually carried out with vibration measurements, which again increase the system complexity. However, variable speed drives can already be used for pumping system condition monitoring. Therefore, it would add to the usability of a variablespeed- driven fan system if the variable speed drive could be used as a condition monitoring device. In this thesis, sensorless detection methods for three lifetime-reducing phenomena are suggested: these are detection of the fan contamination build-up, the correct rotational direction, and the fan surge. The methods use the variable speed drive monitoring and control options for the detection along with simple signal processing methods, such as power spectrum density estimates. The methods have been validated by laboratory measurements. The key finding of this doctoral thesis is that a variable speed drive can be used on its own as a monitoring and control device for the fan system energy efficiency, and it can also be used in the detection of certain lifetime-reducing phenomena.