Auguste Ott on Commercial Crises and Distributive Justice: An Early Input-Output Scheme

In 1851 the French Social economist Auguste Ott discussed the problem of gluts and commercial crises, together with the issue of distributive justice between workers in co-operative societies. He did so by means of a 'simple reproduction scheme' sharing some features with modern intersectoral transactions tables, in particular in terms of their graphical representation. This paper presents Ott's theory of crises (which was based on the disappointment of expectations) and the context of his model, and discusses its peculiarities, supplying a new piece for the reconstruction of the prehistory of input-output analysis.

Structured output SVM for remote sensing image classification

In the recent years, kernel methods have revealed very powerful tools in many application domains in general and in remote sensing image classification in particular. The special characteristics of remote sensing images (high dimension, few labeled samples and different noise sources) are efficiently dealt with kernel machines. In this paper, we propose the use of structured output learning to improve remote sensing image classification based on kernels. Structured output learning is concerned with the design of machine learning algorithms that not only implement input-output mapping, but also take into account the relations between output labels, thus generalizing unstructured kernel methods. We analyze the framework and introduce it to the remote sensing community. Output similarity is here encoded into SVM classifiers by modifying the model loss function and the kernel function either independently or jointly. Experiments on a very high resolution (VHR) image classification problem shows promising results and opens a wide field of research with structured output kernel methods.

A regional Industrial Symbiosis methodology and its implementation in Geneva, Switzerland

The Agenda 21 for the Geneva region is the results from a broad consultation process including all local actors. The article 12 stipulates that « the State facilitates possible synergies between economic activities in order to minimize their environmental impacts » thus opening the way for Industrial Ecology (IE) and Industrial Symbiosis (IS). An Advisory Board for Industrial Ecology and Industrial Symbiosis implementation was established in 2002 involving relevant government agencies. Regulatory and technical conditions for IS are studied in the Swiss context. Results reveal that the Swiss law on waste does not hinder by-product exchanges. Methodology and technical factors including geographic, qualitative, quantitative and economical aspects are detailed. The competition with waste operators in a highly developed recycling system is also tackled.The IS project develops an empirical and systematic method for detecting and implementing by-products synergies between industrial actors disseminated throughout the Geneva region. Database management tool for the treatment of input-output analysis data and GIS tools for detecting potentials industrial partners are constantly improved. Potential symbioses for 17 flows (including energy, water and material flows) are currently studied for implementation.

In vivo reprogramming of circuit connectivity in postmitotic neocortical neurons.

The molecular mechanisms that control how progenitors generate distinct subtypes of neurons, and how undifferentiated neurons acquire their specific identity during corticogenesis, are increasingly understood. However, whether postmitotic neurons can change their identity at late stages of differentiation remains unknown. To study this question, we developed an electrochemical in vivo gene delivery method to rapidly manipulate gene expression specifically in postmitotic neurons. Using this approach, we found that the molecular identity, morphology, physiology and functional input-output connectivity of layer 4 mouse spiny neurons could be specifically reprogrammed during the first postnatal week by ectopic expression of the layer 5B output neuron-specific transcription factor Fezf2. These findings reveal a high degree of plasticity in the identity of postmitotic neocortical neurons and provide a proof of principle for postnatal re-engineering of specific neural microcircuits in vivo.

Concept of fat balance in human obesity revisited with particular reference to de novo lipogenesis.

The measurement of fat balance (fat input minus fat output) involves the accurate estimation of both metabolizable fat intake and total fat oxidation. This is possible mostly under laboratory conditions and not yet in free-living conditions. In the latter situation, net fat retention/mobilization can be estimated based on precise and accurate sequential body composition measurements. In case of positive balance, lipids stored in adipose tissue can originate from dietary (exogenous) lipids or from nonlipid precursors, mainly from carbohydrates (CHOs) but also from ethanol, through a process known as de novo lipogenesis (DNL). Basic equations are provided in this review to facilitate the interpretation of the different subcomponents of fat balance (endogenous vs exogenous) under different nutritional circumstances. One difficulty is methodological: total DNL is difficult to measure quantitatively in man; for example, indirect calorimetry only tracks net DNL, not total DNL. Although the numerous factors (mostly exogenous) influencing DNL have been studied, in particular the effect of CHO overfeeding, there is little information on the rate of DNL in habitual conditions of life, that is, large day-to-day fluctuations of CHO intakes, different types of CHO ingested with different glycemic indexes, alcohol combined with excess CHO intakes, etc. Three issues, which are still controversial today, will be addressed: (1) Is the increase of fat mass induced by CHO overfeeding explained by DNL only, or by decreased endogenous fat oxidation, or both? (2) Is DNL different in overweight and obese individuals as compared to their lean counterparts? (3) Does DNL occur both in the liver and in adipose tissue? Recent studies have demonstrated that acute CHO overfeeding influences adipose tissue lipogenic gene expression and that CHO may stimulate DNL in skeletal muscles, at least in vitro. The role of DNL and its importance in health and disease remain to be further clarified, in particular the putative effect of DNL on the control of energy intake and energy expenditure, as well as the occurrence of DNL in other tissues (such as in myocytes) in addition to hepatocytes and adipocytes.

Uncertainty Quantification Of A Semi-Supervised Support Vector Regression Reservoir Model

Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. Recent advances in machine learning offer a novel approach to model spatial distribution of petrophysical properties in complex reservoirs alternative to geostatistics. The approach is based of semisupervised learning, which handles both ?labelled? observed data and ?unlabelled? data, which have no measured value but describe prior knowledge and other relevant data in forms of manifolds in the input space where the modelled property is continuous. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic geological features and describe stochastic variability and non-uniqueness of spatial properties. On the other hand, it is able to capture and preserve key spatial dependencies such as connectivity of high permeability geo-bodies, which is often difficult in contemporary petroleum reservoir studies. Semi-supervised SVR as a data driven algorithm is designed to integrate various kind of conditioning information and learn dependences from it. The semi-supervised SVR model is able to balance signal/noise levels and control the prior belief in available data. In this work, stochastic semi-supervised SVR geomodel is integrated into Bayesian framework to quantify uncertainty of reservoir production with multiple models fitted to past dynamic observations (production history). Multiple history matched models are obtained using stochastic sampling and/or MCMC-based inference algorithms, which evaluate posterior probability distribution. Uncertainty of the model is described by posterior probability of the model parameters that represent key geological properties: spatial correlation size, continuity strength, smoothness/variability of spatial property distribution. The developed approach is illustrated with a fluvial reservoir case. The resulting probabilistic production forecasts are described by uncertainty envelopes. The paper compares the performance of the models with different combinations of unknown parameters and discusses sensitivity issues.

Mice carrying ubiquitin-specific protease 2 (Usp2) gene inactivation maintain normal sodium balance and blood pressure.

Ubiquitylation plays an important role in the control of Na⁺ homeostasis by the kidney. It is well established that the epithelial Na⁺ channel ENaC is regulated by the ubiquitin-protein ligase NEDD4-2, limiting ENaC cell surface expression and activity. Ubiquitylation can be reversed by the action of deubiquitylating enzymes (DUBs). One such DUB, USP2-45, was identified previously as an aldosterone-induced protein in the kidney and is also a circadian output gene. In heterologous expression systems, USP2-45 binds to ENaC, deubiquitylates it, and enhances channel density and activity at the cell surface. Because the role of USP2-45 in renal Na⁺ transport had not been studied in vivo, we investigated here the effect of Usp2 gene inactivation in this process. We demonstrate first that USP2-45 protein has a rhythmic expression with a peak at ZT12. Usp2-KO mice did not show any differences from wild-type littermates with respect to the diurnal control of Na⁺ or K⁺ urinary excretion and plasma levels either on a standard diet or after acute and chronic changes to low- and high-Na⁺ diets, respectively. Moreover, they had similar aldosterone levels on either a low- or high-Na⁺ diet. Blood pressure measurements using telemetry did not reveal variations compared with control mice. Usp2-KO mice did not display alterations in expression of genes involved in sodium homeostasis or the ubiquitin system, as evidenced by transcriptome analysis in the kidney. Our data suggest that USP2 does not play a primary role in the control of Na⁺ balance or blood pressure.

Dynamic properties of human brain structure: learning-related changes in cortical areas and associated fiber connections.

Recent findings in neuroscience suggest that adult brain structure changes in response to environmental alterations and skill learning. Whereas much is known about structural changes after intensive practice for several months, little is known about the effects of single practice sessions on macroscopic brain structure and about progressive (dynamic) morphological alterations relative to improved task proficiency during learning for several weeks. Using T1-weighted and diffusion tensor imaging in humans, we demonstrate significant gray matter volume increases in frontal and parietal brain areas following only two sessions of practice in a complex whole-body balancing task. Gray matter volume increase in the prefrontal cortex correlated positively with subject's performance improvements during a 6 week learning period. Furthermore, we found that microstructural changes of fractional anisotropy in corresponding white matter regions followed the same temporal dynamic in relation to task performance. The results make clear how marginal alterations in our ever changing environment affect adult brain structure and elucidate the interrelated reorganization in cortical areas and associated fiber connections in correlation with improvements in task performance.

Dynamic models of viral replication and latency.

PURPOSE OF REVIEW: HIV targets primary CD4(+) T cells. The virus depends on the physiological state of its target cells for efficient replication, and, in turn, viral infection perturbs the cellular state significantly. Identifying the virus-host interactions that drive these dynamic changes is important for a better understanding of viral pathogenesis and persistence. The present review focuses on experimental and computational approaches to study the dynamics of viral replication and latency. RECENT FINDINGS: It was recently shown that only a fraction of the inducible latently infected reservoirs are successfully induced upon stimulation in ex-vivo models while additional rounds of stimulation make allowance for reactivation of more latently infected cells. This highlights the potential role of treatment duration and timing as important factors for successful reactivation of latently infected cells. The dynamics of HIV productive infection and latency have been investigated using transcriptome and proteome data. The cellular activation state has shown to be a major determinant of viral reactivation success. Mathematical models of latency have been used to explore the dynamics of the latent viral reservoir decay. SUMMARY: Timing is an important component of biological interactions. Temporal analyses covering aspects of viral life cycle are essential for gathering a comprehensive picture of HIV interaction with the host cell and untangling the complexity of latency. Understanding the dynamic changes tipping the balance between success and failure of HIV particle production might be key to eradicate the viral reservoir.

Influence of heart motion on cardiac output estimation by means of electrical impedance tomography: a case study.

Electrical impedance tomography (EIT) is a non-invasive imaging technique that can measure cardiac-related intra-thoracic impedance changes. EIT-based cardiac output estimation relies on the assumption that the amplitude of the impedance change in the ventricular region is representative of stroke volume (SV). However, other factors such as heart motion can significantly affect this ventricular impedance change. In the present case study, a magnetic resonance imaging-based dynamic bio-impedance model fitting the morphology of a single male subject was built. Simulations were performed to evaluate the contribution of heart motion and its influence on EIT-based SV estimation. Myocardial deformation was found to be the main contributor to the ventricular impedance change (56%). However, motion-induced impedance changes showed a strong correlation (r = 0.978) with left ventricular volume. We explained this by the quasi-incompressibility of blood and myocardium. As a result, EIT achieved excellent accuracy in estimating a wide range of simulated SV values (error distribution of 0.57 ± 2.19 ml (1.02 ± 2.62%) and correlation of r = 0.996 after a two-point calibration was applied to convert impedance values to millilitres). As the model was based on one single subject, the strong correlation found between motion-induced changes and ventricular volume remains to be verified in larger datasets.