Macaulay style formulas for sparse resultants

We present formulas for computing the resultant of sparse polyno- mials as a quotient of two determinants, the denominator being a minor of the numerator. These formulas extend the original formulation given by Macaulay for homogeneous polynomials.

A numerical characterization of hypersurface singularities

In this note we give a numerical characterization of hypersurface singularities in terms of the normalized Hilbert-Samuel coefficients, and we interpret this result from the point of view of rigid polynomials.

Influence of the menstrual cycle on the sweating response measured by direct calorimetry in women exposed to warm environmental conditions.

The whole body sweating response was measured at rest in eight women during the follicular (F) and the luteal (L) phases of the menstrual cycle. Subjects were exposed for 30-min to neutral (N) environmental conditions [ambient temperature (Ta) 28 degrees C] and then for 90-min to warm (W) environmental conditions (Ta, 35 degrees C) in a direct calorimeter. At the end of the N exposure, tympanic temperature (Tty) was 0.18 (SEM 0.06) degrees C higher in the L than in the F phase (P less than 0.05), whereas mean skin temperature (Tsk) was unchanged. During W exposure, the time to the onset of sweating as well as the concomitant increase in body heat content were similar in both phases. At the onset of sweating, the tympanic threshold temperature (Tty,thresh) was higher in the L phase [37.18 (SEM 0.08) degrees C] than in the F phase [36.95 (SEM 0.07) degrees C; P less than 0.01]. The magnitude of the shift in Tty,thresh [0.23 (SEM 0.07) degrees C] was similar to the L-F difference in Tty observed at the end of the N exposure. The mean skin threshold temperature was not statistically different between the two phases. The slope of the relationship between sweating rate and Tty was similar in F and L. It was concluded that the internal set point temperature of resting women exposed to warm environmental conditions shifted to a higher value during the L phase compared to the F phase of the menstrual cycle; and that the magnitude of the shift corresponded to the difference in internal temperature observed in neutral environmental conditions between the two phases.

New measurements of radial velocities in clusters of galaxies

Redshifts for 100 galaxies in 10 clusters of galaxies are presented based on data obtained between March 1984 and March 1985 from Calar Alto, La Palma, and ESO, and on data from Mauna Kea. Data for individual galaxies are given, and the accuracy of the velocities of the four instruments is discussed. Comparison with published data shows the present velocities to be shifted by + 4.0 km/s on average, with a standard deviation in the difference of 89.7 km/s, consistent with the rms of redshift measurements which range from 50-100 km/s.

Birth and rapid subcellular adaptation of a hominoid-specific CDC14 protein

Gene duplication was prevalent during hominoid evolution, yet little is known about the functional fate of new ape gene copies. We characterized the CDC14B cell cycle gene and the functional evolution of its hominoid-specific daughter gene, CDC14Bretro. We found that CDC14B encodes four different splice isoforms that show different subcellular localizations (nucleus or microtubule-associated) and functional properties. A microtubular CDC14B variant spawned CDC14Bretro through retroposition in the hominoid ancestor 18-25 million years ago (Mya). CDC14Bretro evolved brain-/testis-specific expression after the duplication event and experienced a short period of intense positive selection in the African ape ancestor 7-12 Mya. Using resurrected ancestral protein variants, we demonstrate that by virtue of amino acid substitutions in distinct protein regions during this time, the subcellular localization of CDC14Bretro progressively shifted from the association with microtubules (stabilizing them) to an association with the endoplasmic reticulum. CDC14Bretro evolution represents a paradigm example of rapid, selectively driven subcellular relocalization, thus revealing a novel mode for the emergence of new gene function

Time-lapse and probabilistic inversion strategies for plane-wave electromagnetic data.

L'utilisation efficace des systèmes géothermaux, la séquestration du CO2 pour limiter le changement climatique et la prévention de l'intrusion d'eau salée dans les aquifères costaux ne sont que quelques exemples qui démontrent notre besoin en technologies nouvelles pour suivre l'évolution des processus souterrains à partir de la surface. Un défi majeur est d'assurer la caractérisation et l'optimisation des performances de ces technologies à différentes échelles spatiales et temporelles. Les méthodes électromagnétiques (EM) d'ondes planes sont sensibles à la conductivité électrique du sous-sol et, par conséquent, à la conductivité électrique des fluides saturant la roche, à la présence de fractures connectées, à la température et aux matériaux géologiques. Ces méthodes sont régies par des équations valides sur de larges gammes de fréquences, permettant détudier de manières analogues des processus allant de quelques mètres sous la surface jusqu'à plusieurs kilomètres de profondeur. Néanmoins, ces méthodes sont soumises à une perte de résolution avec la profondeur à cause des propriétés diffusives du champ électromagnétique. Pour cette raison, l'estimation des modèles du sous-sol par ces méthodes doit prendre en compte des informations a priori afin de contraindre les modèles autant que possible et de permettre la quantification des incertitudes de ces modèles de façon appropriée. Dans la présente thèse, je développe des approches permettant la caractérisation statique et dynamique du sous-sol à l'aide d'ondes EM planes. Dans une première partie, je présente une approche déterministe permettant de réaliser des inversions répétées dans le temps (time-lapse) de données d'ondes EM planes en deux dimensions. Cette stratégie est basée sur l'incorporation dans l'algorithme d'informations a priori en fonction des changements du modèle de conductivité électrique attendus. Ceci est réalisé en intégrant une régularisation stochastique et des contraintes flexibles par rapport à la gamme des changements attendus en utilisant les multiplicateurs de Lagrange. J'utilise des normes différentes de la norme l2 pour contraindre la structure du modèle et obtenir des transitions abruptes entre les régions du model qui subissent des changements dans le temps et celles qui n'en subissent pas. Aussi, j'incorpore une stratégie afin d'éliminer les erreurs systématiques de données time-lapse. Ce travail a mis en évidence l'amélioration de la caractérisation des changements temporels par rapport aux approches classiques qui réalisent des inversions indépendantes à chaque pas de temps et comparent les modèles. Dans la seconde partie de cette thèse, j'adopte un formalisme bayésien et je teste la possibilité de quantifier les incertitudes sur les paramètres du modèle dans l'inversion d'ondes EM planes. Pour ce faire, je présente une stratégie d'inversion probabiliste basée sur des pixels à deux dimensions pour des inversions de données d'ondes EM planes et de tomographies de résistivité électrique (ERT) séparées et jointes. Je compare les incertitudes des paramètres du modèle en considérant différents types d'information a priori sur la structure du modèle et différentes fonctions de vraisemblance pour décrire les erreurs sur les données. Les résultats indiquent que la régularisation du modèle est nécessaire lorsqu'on a à faire à un large nombre de paramètres car cela permet d'accélérer la convergence des chaînes et d'obtenir des modèles plus réalistes. Cependent, ces contraintes mènent à des incertitudes d'estimations plus faibles, ce qui implique des distributions a posteriori qui ne contiennent pas le vrai modèledans les régions ou` la méthode présente une sensibilité limitée. Cette situation peut être améliorée en combinant des méthodes d'ondes EM planes avec d'autres méthodes complémentaires telles que l'ERT. De plus, je montre que le poids de régularisation des paramètres et l'écart-type des erreurs sur les données peuvent être retrouvés par une inversion probabiliste. Finalement, j'évalue la possibilité de caractériser une distribution tridimensionnelle d'un panache de traceur salin injecté dans le sous-sol en réalisant une inversion probabiliste time-lapse tridimensionnelle d'ondes EM planes. Etant donné que les inversions probabilistes sont très coûteuses en temps de calcul lorsque l'espace des paramètres présente une grande dimension, je propose une stratégie de réduction du modèle ou` les coefficients de décomposition des moments de Legendre du panache de traceur injecté ainsi que sa position sont estimés. Pour ce faire, un modèle de résistivité de base est nécessaire. Il peut être obtenu avant l'expérience time-lapse. Un test synthétique montre que la méthodologie marche bien quand le modèle de résistivité de base est caractérisé correctement. Cette méthodologie est aussi appliquée à un test de trac¸age par injection d'une solution saline et d'acides réalisé dans un système géothermal en Australie, puis comparée à une inversion time-lapse tridimensionnelle réalisée selon une approche déterministe. L'inversion probabiliste permet de mieux contraindre le panache du traceur salin gr^ace à la grande quantité d'informations a priori incluse dans l'algorithme. Néanmoins, les changements de conductivités nécessaires pour expliquer les changements observés dans les données sont plus grands que ce qu'expliquent notre connaissance actuelle des phénomenès physiques. Ce problème peut être lié à la qualité limitée du modèle de résistivité de base utilisé, indiquant ainsi que des efforts plus grands devront être fournis dans le futur pour obtenir des modèles de base de bonne qualité avant de réaliser des expériences dynamiques. Les études décrites dans cette thèse montrent que les méthodes d'ondes EM planes sont très utiles pour caractériser et suivre les variations temporelles du sous-sol sur de larges échelles. Les présentes approches améliorent l'évaluation des modèles obtenus, autant en termes d'incorporation d'informations a priori, qu'en termes de quantification d'incertitudes a posteriori. De plus, les stratégies développées peuvent être appliquées à d'autres méthodes géophysiques, et offrent une grande flexibilité pour l'incorporation d'informations additionnelles lorsqu'elles sont disponibles. -- The efficient use of geothermal systems, the sequestration of CO2 to mitigate climate change, and the prevention of seawater intrusion in coastal aquifers are only some examples that demonstrate the need for novel technologies to monitor subsurface processes from the surface. A main challenge is to assure optimal performance of such technologies at different temporal and spatial scales. Plane-wave electromagnetic (EM) methods are sensitive to subsurface electrical conductivity and consequently to fluid conductivity, fracture connectivity, temperature, and rock mineralogy. These methods have governing equations that are the same over a large range of frequencies, thus allowing to study in an analogous manner processes on scales ranging from few meters close to the surface down to several hundreds of kilometers depth. Unfortunately, they suffer from a significant resolution loss with depth due to the diffusive nature of the electromagnetic fields. Therefore, estimations of subsurface models that use these methods should incorporate a priori information to better constrain the models, and provide appropriate measures of model uncertainty. During my thesis, I have developed approaches to improve the static and dynamic characterization of the subsurface with plane-wave EM methods. In the first part of this thesis, I present a two-dimensional deterministic approach to perform time-lapse inversion of plane-wave EM data. The strategy is based on the incorporation of prior information into the inversion algorithm regarding the expected temporal changes in electrical conductivity. This is done by incorporating a flexible stochastic regularization and constraints regarding the expected ranges of the changes by using Lagrange multipliers. I use non-l2 norms to penalize the model update in order to obtain sharp transitions between regions that experience temporal changes and regions that do not. I also incorporate a time-lapse differencing strategy to remove systematic errors in the time-lapse inversion. This work presents improvements in the characterization of temporal changes with respect to the classical approach of performing separate inversions and computing differences between the models. In the second part of this thesis, I adopt a Bayesian framework and use Markov chain Monte Carlo (MCMC) simulations to quantify model parameter uncertainty in plane-wave EM inversion. For this purpose, I present a two-dimensional pixel-based probabilistic inversion strategy for separate and joint inversions of plane-wave EM and electrical resistivity tomography (ERT) data. I compare the uncertainties of the model parameters when considering different types of prior information on the model structure and different likelihood functions to describe the data errors. The results indicate that model regularization is necessary when dealing with a large number of model parameters because it helps to accelerate the convergence of the chains and leads to more realistic models. These constraints also lead to smaller uncertainty estimates, which imply posterior distributions that do not include the true underlying model in regions where the method has limited sensitivity. This situation can be improved by combining planewave EM methods with complimentary geophysical methods such as ERT. In addition, I show that an appropriate regularization weight and the standard deviation of the data errors can be retrieved by the MCMC inversion. Finally, I evaluate the possibility of characterizing the three-dimensional distribution of an injected water plume by performing three-dimensional time-lapse MCMC inversion of planewave EM data. Since MCMC inversion involves a significant computational burden in high parameter dimensions, I propose a model reduction strategy where the coefficients of a Legendre moment decomposition of the injected water plume and its location are estimated. For this purpose, a base resistivity model is needed which is obtained prior to the time-lapse experiment. A synthetic test shows that the methodology works well when the base resistivity model is correctly characterized. The methodology is also applied to an injection experiment performed in a geothermal system in Australia, and compared to a three-dimensional time-lapse inversion performed within a deterministic framework. The MCMC inversion better constrains the water plumes due to the larger amount of prior information that is included in the algorithm. The conductivity changes needed to explain the time-lapse data are much larger than what is physically possible based on present day understandings. This issue may be related to the base resistivity model used, therefore indicating that more efforts should be given to obtain high-quality base models prior to dynamic experiments. The studies described herein give clear evidence that plane-wave EM methods are useful to characterize and monitor the subsurface at a wide range of scales. The presented approaches contribute to an improved appraisal of the obtained models, both in terms of the incorporation of prior information in the algorithms and the posterior uncertainty quantification. In addition, the developed strategies can be applied to other geophysical methods, and offer great flexibility to incorporate additional information when available.

Small Cities, Neoliberal Governance and Sustainable Development in the Global South : A Conceptual Framework and Research Agenda

Development and environmental issues of small cities in developing countries have largely been overlooked although these settlements are of global demographic importance and often face a "triple challenge"; that is, they have limited financial and human resources to address growing environmental problems that are related to both development (e.g., pollution) and under-development (e.g., inadequate water supply). Neoliberal policy has arguably aggravated this challenge as public investments in infrastructure generally declined while the focus shifted to the metropolitan "economic growth machines". This paper develops a conceptual framework and agenda for the study of small cities in the global south, their environmental dynamics, governance and politics in the current neoliberal context. While small cities are governed in a neoliberal policy context, they are not central to neoliberalism, and their (environmental) governance therefore seems to differ from that of global cities. Furthermore, "actually existing" neoliberal governance of small cities is shaped by the interplay of regional and local politics and environmental situations. The approach of urban political ecology and the concept of rural-urban linkages are used to consider these socio-ecological processes. The conceptual framework and research agenda are illustrated in the case of India, where the agency of small cities in regard to environmental governance seems to remain limited despite formal political decentralization.

The abrupt climate change at the Eocene-Oligocene boundary and the emergence of South-East Asia triggered the spread of sapindaceous lineages.

Background and Aims Paleoclimatic data indicate that an abrupt climate change occurred at the Eocene-Oligocene (E-O) boundary affecting the distribution of tropical forests on Earth. The same period has seen the emergence of South-East (SE) Asia, caused by the collision of the Eurasian and Australian plates. How the combination of these climatic and geomorphological factors affected the spatio-temporal history of angiosperms is little known. This topic is investigated by using the worldwide sapindaceous clade as a case study. Methods Analyses of divergence time inference, diversification and biogeography (constrained by paleogeography) are applied to a combined plastid and nuclear DNA sequence data set. Biogeographical and diversification analyses are performed over a set of trees to take phylogenetic and dating uncertainty into account. Results are analysed in the context of past climatic fluctuations. Key Results An increase in the number of dispersal events at the E-O boundary is recorded, which intensified during the Miocene. This pattern is associated with a higher rate in the emergence of new genera. These results are discussed in light of the geomorphological importance of SE Asia, which acted as a tropical bridge allowing multiple contacts between areas and additional speciation across landmasses derived from Laurasia and Gondwana. Conclusions This study demonstrates the importance of the combined effect of geomorphological (the emergence of most islands in SE Asia approx. 30 million years ago) and climatic (the dramatic E-O climate change that shifted the tropical belt and reduced sea levels) factors in shaping species distribution within the sapindaceous clade.

Mass conservative three-dimensional water tracer distribution from Markov chain Monte Carlo inversion of time-lapse ground-penetrating radar data

Time-lapse geophysical measurements are widely used to monitor the movement of water and solutes through the subsurface. Yet commonly used deterministic least squares inversions typically suffer from relatively poor mass recovery, spread overestimation, and limited ability to appropriately estimate nonlinear model uncertainty. We describe herein a novel inversion methodology designed to reconstruct the three-dimensional distribution of a tracer anomaly from geophysical data and provide consistent uncertainty estimates using Markov chain Monte Carlo simulation. Posterior sampling is made tractable by using a lower-dimensional model space related both to the Legendre moments of the plume and to predefined morphological constraints. Benchmark results using cross-hole ground-penetrating radar travel times measurements during two synthetic water tracer application experiments involving increasingly complex plume geometries show that the proposed method not only conserves mass but also provides better estimates of plume morphology and posterior model uncertainty than deterministic inversion results.

Evaluation of arterial compliance-pressure curves. Effect of antihypertensive drugs.

A new high-precision ultrasonic device was developed to determine noninvasively arterial compliance as a function of blood pressure. Because of the nonlinear elastic properties of arterial walls, measurements of compliance can be appropriately compared only if obtained over a range of pressures. This apparatus was used to evaluate in a double-blind, parallel fashion the effect of three different antihypertensive drugs and of a placebo on radial artery compliance. Thirty-two normotensive volunteers were randomly allocated to an 8-day, once-a-day oral treatment with either a placebo, 100 mg atenolol, 20 mg nitrendipine, or 20 mg lisinopril. Blood pressure, heart rate, radial artery diameter, and arterial compliance were measured immediately before as well as 6 hours after dosing on the first and last days of the study. On the eighth day of administration, within 6 hours after dosing, lisinopril induced an acute increase in radial artery diameter, from 2.99 +/- 0.06 to 3.28 +/- 0.09 mm (mean +/- SEM, p less than 0.01). The compliance-pressure curve was shifted upward on day 1 (p less than 0.01) as well as on day 8 (p less than 0.05). None of the other drugs induced any significant modification of these parameters. Arterial compliance has a strong nonlinear dependency on intra-arterial pressure and therefore has to be defined as a function of pressure. Antihypertensive drugs acting by different mechanisms may have different effects on the mechanical properties of large arteries.

The therapeutic potential of immune cross-talk in leishmaniasis.

Veterans of infection, Leishmania parasites have been plaguing mammals for centuries, causing a morbidity toll second only to that of malaria as the most devastating protozoan parasitic disease in the world. Cutaneous leishmaniasis (CL) is, by far, the most prevalent form of the disease, with symptoms ranging from a single self-healing lesion to chronic metastatic leishmaniasis (ML). In an increasingly immunocompromised population, complicated CL is becoming a more likely outcome, characterized by severely inflamed, destructive lesions that are often refractory to current treatment. This is perhaps because our ageing arsenal of variably effective antileishmanial drugs may be directly or indirectly immunomodulatory and may thus have variable effects in each type and stage of CL. Indeed, widely differing immune biases are created by the various species of Leishmania, and these immunological watersheds are further shifted by extrinsic disturbances in immune homeostasis. For example, we recently showed that a naturally occurring RNA virus (Leishmania RNA virus (LRV)) within some Leishmania parasites creates hyperinflammatory cross-talk, which can predispose to ML: a case of immunological misfire that may require a different approach to immunotherapy, whereby treatments are tailored to underlying immune biases. Understanding the intersecting immune pathways of leishmaniasis and its co-infections will enable us to identify new drug targets, and thereby design therapeutic strategies that work by untangling the immunological cross-wires of pathogenic cross-talk.