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Les douleurs abdominales en questions : Rôle physiopathologique de la sensibilité viscérale = Abdominal pain in question : The pathophysiological role of visceral sensitivity
The gut-brain axis refers to the network of nerve pathways that connect the myenteric plexus, the veritable "gut brain," to the central nervous system. Nearly 80% of these neurons are sensory neurons, and the afferent pathways that transmit information from the digestive tract to the central nervous system play a crucial role in the physiological regulation of digestive functions, as well as in certain pathological conditions. A large majority of these sensations remain unconscious and give rise to reflex responses. Only those requiring a conscious response reach the level of awareness in a normal state (hunger, thirst, the urge to defecate). In pathological situations, the same is true for painful sensations of digestive origin. Functional bowel disorders are a frequent reason for consultation. Their pathophysiology is now based on a model integrating the various etiological factors around the brain-gut axis. These patients frequently present with visceral hypersensitivity, which manifests as an increased perception of digestive sensations, notably the onset of pain in response to stimuli that are not painful in normal subjects. Recognizing the role of visceral hypersensitivity has made it possible to explain the mechanism of action of medications used to treat functional bowel disorders and paves the way for the development of new molecules acting on digestive afferents. In this book, we will describe the anatomical and physiological basis for understanding the concept of visceral sensitivity and the role of digestive afferents in the pathophysiology of acute and chronic abdominal pain, particularly irritable bowel syndrome.
Le dépistage du cancer du col de lutérus = Cervical cancer screening
Each year, cervical cancer kills approximately 1,000 people in France, making it the fifth leading cause of cancer death and the eighth most common cancer among women. While eradicating cervical cancer is not possible, a national screening campaign should significantly reduce its incidence. This campaign should be based, in particular, on the systematic use of Pap smears. Conventional Pap smears have already reduced the number of invasive cancers by more than 50%. Improving them requires optimizing their sensitivity. This book details the natural history of cervical cancer, its incidence and mortality, and the various aspects of screening: general principles, the French screening program, the different types of Pap smears, the role and contribution of the HPV test, the management of abnormal Pap smears, the role of colposcopy, and the follow-up of treated women. It is intended for all those involved in this screening : specialist interns and gynecologists, pathologists and biologists, public health physicians, but also general practitioners whose role in screening is privileged since they are at the forefront of medical demand.
Lapproccio e la gestione per processi in pneumologia = The process-based approach and management in pulmonology
The topics covered are highly relevant to the application of the methods and tools outlined in quality improvement programs. This is in an effort to enhance the specific skills of the pulmonologist, thus making him an effective and independent liaison with the relevant strategic management. With great sensitivity, the SIMeR (Italian Society of Respiratory Medicine) has chosen to sponsor this edition, the only one to date in the field of Pulmonology, whose contents are based on the proposals and work of the leaders of one of its most recently established Study Groups, the "Continuous Quality Improvement in Pulmonology" Study Group.
Clinical applications of mass spectrometry in drug analysis : Methods and protocols
This fully updated volume describes methods and protocols for a number of drugs and toxins in a stepwise manner. Exploring the versatility and flexibility of mass spectrometry, the book covers the advantages of this technology, which typically include elimination of the need for special reagents such as antibodies, increased sensitivity and specificity, and multi-component analysis enabling the screening of tens to hundreds of compounds in a single assay run. Written for the highly successful Methods in Molecular Biology series, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step and readily reproducible laboratory protocols, as well as tips on troubleshooting and avoiding known pitfalls.
Breast cancer chemosensitivity
In Breast Cancer Chemosensitivity, a group of world leading experts review critical aspects of resistance to systemic therapy in breast cancer patients. Beginning with a clinical overview of the problem Breast Cancer Chemosensitivity moves on to focus on the latest findings of molecular mechanisms of drug resistance. These include in-depth discussions on multidrug resistance by P-glycoprotein and the multidrug resistance protein family, resistance to therapeutic agent-induced apoptosis, cell cycle deregulation, deregulation of DNA repair, loss of tumor suppressor genes, integrin-mediated adhesion, insulin-like growth factors, epidermal growth factor, and ErbB2 in modulating breast cancer response to systemic therapy, especially, certain chemotherapeutic agents. Breast Cancer Chemosensitivity provides an example of using novel approaches for chemosensitization of breast cancer cells that gives readers an idea about the future direction in breast cancer treatment.
Bayesian Networks and Decision Graphs
Probabilistic graphical models and decision graphs are powerful modeling tools for reasoning and decision making under uncertainty. As modeling languages they allow a natural specification of problem domains with inherent uncertainty, and from a computational perspective they support efficient algorithms for automatic construction and query answering. This includes belief updating, finding the most probable explanation for the observed evidence, detecting conflicts in the evidence entered into the network, determining optimal strategies, analyzing for relevance, and performing sensitivity analysis. The book introduces probabilistic graphical models and decision graphs, including Bayesian networks and influence diagrams.It contians two parts. The first part focuses on probabilistic graphical models. Compared with the previous book, the new edition also includes a thorough description of recent extensions to the Bayesian network modeling language, advances in exact and approximate belief updating algorithms, and methods for learning both the structure and the parameters of a Bayesian network. The second part deals with decision graphs, and in addition to the frameworks described in the previous edition, it also introduces Markov decision processes and partially ordered decision problems.
Adaptive Scalarization Methods in Multiobjective Optimization
This book presents new adaptive solution methods for multiobjective optimization problems based on parameter dependent scalarizations. With the help of sensitivity results an adaptive parameter control is developed so that high-quality approximations of the efficient set are generated. These examinations are based on a general scalarization approach for arbitrary partial orderings defined by a closed pointed convex cone in the objective space. The application of the results to many other well-known scalarization methods is also presented. Background material of multiobjective optimization and scalarization approaches is concisely summarized at the beginning. The effectiveness of these new methods is demonstrated by test problems and a recent problem in intensity-modulated radiotherapy. The book concludes with a further application: a procedure for solving multiobjective bilevel optimization problems.
Malliavin Calculus for Lévy Processes with Applications to Finance
While the original works on Malliavin calculus aimed to study the smoothness of densities of solutions to stochastic differential equations, this book has another goal. It portrays the most important and innovative applications in stochastic control and finance, such as hedging in complete and incomplete markets, optimisation in the presence of asymmetric information and also pricing and sensitivity analysis. In a self-contained fashion, both the Malliavin calculus with respect to Brownian motion and general Lévy type of noise are treated. Besides, forward integration is included and indeed extended to general Lévy processes. The forward integration is a recent development within anticipative stochastic calculus that, together with the Malliavin calculus, provides new methods for the study of insider trading problems.
Leakage in Nanometer CMOS Technologies
It is essential for circuit and system designers to understand the components of leakage, sensitivity of leakage to different design parameters, and leakage mitigation techniques in nanometer technologies. This book provides an in-depth treatment of these issues for researchers and product designers.
Broadband Opto-Electrical Receivers in Standard CMOS
Broadband Opto-Electrical Receivers in Standard CMOS starts from the basic fundamentals, necessary for the design of opto-electronic interface circuits. The book continues with an in-depth analysis of the photodiode, transimpedance amplifier (TIA) and limiting amplifier (LA). To thoroughly understand the light detection mechanisms in silicon, first a one-dimensional and second a two-dimensional model is developed. Analytical design equations are derived to guide the design of the amplifying circuits. For the TIA, the focus lies on the sensitivity-speed trade-off. For the LA, a high gain-bandwidth is pursued. Several practical design examples reveal the subtleties and challenges encountered during the design of high-performance analog circuits.
Automatic Differentiation : Applications, Theory, and Implementations
This collection covers the state of the art in automatic differentiation theory and practice. Practitioners and students will learn about advances in automatic differentiation techniques and strategies for the implementation of robust and powerful tools. Computational scientists and engineers will benefit from the discussion of applications, which provide insight into effective strategies for using automatic differentiation for design optimization, sensitivity analysis, and uncertainty quantification.
Analytical Chemistry : Theoretical and Metrological Fundamentals
Fundamentals of Analytical Chemistry are usually presented as a sum of chemical and physical foundations, laws, axioms and equations for analytical methods and procedures. In contrast, this book delivers a practice-oriented, general guiding theory valid for all methods and techniques. Starting with a closer look to analytical signals and their dependencies, all the important figures of merit characterizing the power of analytical procedures and the reliability of analytical results are discussed and quantified, such as sensitivity, precision, accuracy and ruggedness. Elements of signal theory, information theory, statistics and fundamentals of calibration are also presented for this aim.
Analysis of seawater : A guide for the analytical and environmental chemist
It is only in the past few years that methods of adequate sensitivity have become available for true ultra-trace metal determinations in water. In the case of organics in seawater it has now become possible to resolve the complex mixtures of organics in seawater and achieve the required very low detection limits. Fortunately, the interest in micro-constituents in the seawater both from the environmental and the nutrient balance points of view has coincided with the availability of advanced instrumentation capable of meeting the analytical needs. This complete and up-to-date compilation of the currently employed proven methods for the chemical analysis of seawaters includes 45 tables and 48 figures.
Agriculture and Climate Beyond 2015 : A New Perspective on Future Land Use Patterns
Interactions between agriculture, climate and patterns of land use are complex. Major changes in agriculture, and land use patterns are foreseen in the next couple of decades in response to shifts in climate, greenhouse gas management initiatives, population growth and other forces. The book explores key interactions between changes in agriculture, patterns of land use and efforts to reduce greenhouse emissions from agriculture. The volume is based on inter-disciplinary science and policy interactions, exploring the way land use may aid in addressing or be affected by the onset of climate change and alterations in food demand. Future forces shaping land use decisions are examined, and its sensitivity to climate change is highlighted. Patterns of land use and the agricultural role in climate change mitigation are explored. Also, policy and social responses to the new perspectives on future land use patterns are identified. The perspective of the book is beyond the year 2015.
Advances in Variable Structure and Sliding Mode Control
Sliding Mode Control is recognized as an efficient tool to design controllers which are robust with respect to uncertainty. The resulting controllers have low sensitivity to plant parameters and perturbations and allow the possibility of decoupling the original plant system into two components of lower dimension. In addition many controllers ensure finite time convergence to the switching surface and can be straightforwardly implemented. However, in addition to this traditional area of exploitation, sliding mode concepts are being increasingly deployed for the design of observers for estimation and identification.
Advances in Probabilistic Graphical Models
This carefully edited book brings together in one volume some of the most important topics of current research in probabilistic graphical modelling, learning from data and probabilistic inference. This includes topics such as the characterisation of conditional independence, the sensitivity of the underlying probability distribution of a Bayesian network to variation in its parameters, the learning of graphical models with latent variables and extensions to the influence diagram formalism. In addition, attention is given to important application fields of probabilistic graphical models, such as the control of vehicles, bioinformatics and medicine.
Advances in Mathematical and Statistical Modeling
Enrique Castillo is a leading figure in several mathematical, statistical, and engineering fields, having contributed seminal work in such areas as statistical modeling, extreme value analysis, multivariate distribution theory, Bayesian networks, neural networks, functional equations, artificial intelligence, linear algebra, optimization methods, numerical methods, reliability engineering, as well as sensitivity analysis and its applications. Organized to honor Castillo's significant contributions, this volume is an outgrowth of the International Conference on Mathematical and Statistical Modeling and covers recent advances in the field. Also presented are applications to safety, reliability and life-testing, financial modeling, quality control, general inference, as well as neural networks and computational techniques.
Advances in Automatic Differentiation
Covers advances in automatic differentiation theory and practice. Computer scientists and mathematicians will learn about recent developments in automatic differentiation theory as well as mechanisms for the construction of robust and powerful automatic differentiation tools. Computational scientists and engineers will benefit from the discussion of various applications, which provide insight into effective strategies for using automatic differentiation for inverse problems and design optimization.
