Development and testing of advanced methods for the screening of Enhanced-Oil-Recovery techniques

Enhanced Oil Recovery (EOR) techniques must undergo preliminary laboratory and pilot testing before implementation to field-wide scale, and the whole evaluation process requires heavy investments. Hence forecasting EOR potential is a key decision-making element. A critical difference amongst EOR techniques resides in the oil-displacement mechanism upon which they are based. The effectiveness of these mechanisms depends on oil and reservoir properties. As such, similar EOR techniques are typically successful in fields sharing similar features. Here we implement and test a screening method aimed at estimating the optimal EOR technique for a target reservoir. Our approach relies on the information content tied to an exhaustive set of EOR field experiences. The basic screening criterion is the analogy with known reservoir settings in terms of oil and formation properties. Analogy is assessed by grouping fields into clusters: we rely on a Bayesian hierarchical clustering algorithm, whose main advantage is that the number of clusters is not set a priori but stems from data statistics. As a test bed, we perform a blind test of our screening approach by considering 2 fields operated by eni. Our predictions for analogy assessment are in agreement with the EOR techniques applied or planned in these fields

A Combined Raman Spectroscopy and Atomic Force Microscopy System for In Situ and Real-Time Measures in Electrochemical Cells

: An innovative and versatile set-up for in situ and real time measures in an electrochemical cell is described. An original coupling between micro-Raman spectroscopy and atomic force microscopy enables one to collect data on opaque electrodes. This system allows for the correlation of topographic images with chemical maps during the charge exchange occurring in oxidation/reduction processes. The proposed set-up plays a crucial role when reactions, both reversible and non-reversible, are studied step by step during electrochemical reactions and/or when local chemical analysis is required

4D Multimodal Nanomedicines Made of Nonequilibrium Au-Fe Alloy Nanoparticles

Several examples of nanosized therapeutic and imaging agents have been proposed to date, yet for most of them there is a low chance of clinical translation due to long-term in vivo retention and toxicity risks. The realization of nanoagents that can be removed from the body after use remains thus a great challenge. Here, we demonstrate that nonequilibrium gold–iron alloys behave as shape-morphing nanocrystals with the properties of self-degradable multifunctional nanomedicines. DFT calculations combined with mixing enthalpy-weighted alloying simulations predict that Au–Fe solid solutions can exhibit self-degradation in an aqueous environment if the Fe content exceeds a threshold that depends upon element topology in the nanocrystals. Exploiting a laser-assisted synthesis route, we experimentally confirm that nonequilibrium Au–Fe nanoalloys have a 4D behavior, that is, the ability to change shape, size, and structure over time, becoming ultrasmall Au-rich nanocrystals. In vivo tests show the potential of these transformable Au–Fe nanoalloys as efficient multimodal contrast agents for magnetic resonance imaging and computed X-ray absorption tomography and further demonstrate their self-degradation over time, with a significant reduction of long-term accumulation in the body, when compared to benchmark gold or iron oxide contrast agents. Hence, Au–Fe alloy nanoparticles exhibiting 4D behavior can respond to the need for safe and degradable inorganic multifunctional nanomedicines required in clinical translation.Instituto de Investigaciones Fisicoquímicas Teóricas y AplicadasInstituto de Física La Plat

Energy-pressure relation for low-dimensional gases

A particularly simple relation of proportionality between internal energy and pressure holds for scale-invariant thermodynamic systems (with Hamiltonians homogeneous functions of the coordinates), including classical and quantum \u2013 Bose and Fermi \u2013 ideal gases. One can quantify the deviation from such a relation by introducing the internal energy shift as the difference between the internal energy of the system and the corresponding value for scale-invariant (including ideal) gases. After discussing some general thermodynamic properties associated with the scale-invariance, we provide criteria for which the internal energy shift density of an imperfect (classical or quantum) gas is a bounded function of temperature. We then study the internal energy shift and deviations from the energy\u2013pressure proportionality in low-dimensional models of gases interpolating between the ideal Bose and the ideal Fermi gases, focusing on the Lieb\u2013Liniger model in 1d and on the anyonic gas in 2d. In 1d the internal energy shift is determined from the thermodynamic Bethe ansatz integral equations and an explicit relation for it is given at high temperature. Our results show that the internal energy shift is positive, it vanishes in the two limits of zero and infinite coupling (respectively the ideal Bose and the Tonks\u2013Girardeau gas) and it has a maximum at a finite, temperature-depending, value of the coupling. Remarkably, at fixed coupling the energy shift density saturates to a finite value for infinite temperature. In 2d we consider systems of Abelian anyons and non-Abelian Chern\u2013Simons particles: as it can be seen also directly from a study of the virial coefficients, in the usually considered hard-core limit the internal energy shift vanishes and the energy is just proportional to the pressure, with the proportionality constant being simply the area of the system. Soft-core boundary conditions at coincident points for the two-body wavefunction introduce a length scale, and induce a non-vanishing internal energy shift: the soft-core thermodynamics is considered in the dilute regime for both the families of anyonic models and in that limit we can show that the energy\u2013pressure ratio does not match the area of the system, opposed to what happens for hard-core (and in particular 2d Bose and Fermi) ideal anyonic gases

Targeted disruption of inducible nitric oxide synthase protects against aging, S-nitrosation, and insulin resistance in muscle of male mice

Accumulating evidence has demonstrated that S-nitrosation of proteins plays a critical role in several human diseases. Here, we explored the role of inducible nitric oxide synthase (iNOS) in the S-nitrosation of proteins involved in the early steps of the insulin-signaling pathway and insulin resistance in the skeletal muscle of aged mice. Aging increased iNOS expression and S-nitrosation of major proteins involved in insulin signaling, thereby reducing insulin sensitivity in skeletal muscle. Conversely, aged iNOS-null mice were protected from S-nitrosation–induced insulin resistance. Moreover, pharmacological treatment with an iNOS inhibitor and acute exercise reduced iNOS-induced S-nitrosation and increased insulin sensitivity in the muscle of aged animals. These findings indicate that the insulin resistance observed in aged mice is mainly mediated through the S-nitrosation of the insulin-signaling pathway

The Evanescent Bouquet of Individual Bear Fingerprint

The evanescent and invisible communication carried by chemical signals, pheromones, or signature mixtures or, as we prefer, the pheromonal individual fingerprint, between members of the same species is poorly studied in mammals, mainly because of the lack of identification of the molecules. The difference between pheromones and the pheromonal individual fingerprint is that the former generate stereotyped innate responses while the latter requires learning, i.e., different receivers can learn different signature mixtures from the same individual. Furthermore, pheromones are usually produced by a particular gland, while the pheromonal individual fingerprint is the entire bouquet produced by the entire secreting gland of the body. In the present study, we aim to investigate the pheromonal individual fingerprint of brown bears in northern Italy. We collected the entire putative pheromone bouquet from all production sites in free-ranging bears and analyzed the entire crude extract to profile the individual fingerprint according to species-, sex- and subjective-specific characteristics. We were able to putatively characterize the brown bears’ pheromonal individual fingerprints and compare them with the partial pheromone identifications published by other studies. This work is a step forward in the study of the complexity of chemical communication, particularly in a solitary endangered species

A Novel Enhanced-Oil-Recovery Screening Approach Based on Bayesian Clustering and Principal-Component Analysis

We present and test a new screening methodology to discriminate amongst alternative and competing Enhanced Oil Recovery (EOR) techniques to be considered for a given reservoir. Our work is motivated by the observation that, even if a considerable variety of EOR techniques have been successfully applied to extend oilfield production and lifetime, an EOR project requires extensive laboratory and pilot tests prior to field-wide implementation and preliminary assessment of EOR potential in a reservoir is critical in the decision-making process. Since similar EOR techniques may be successful in fields sharing some global features, as basic discrimination criteria we consider fluid (density and viscosity) and reservoir formation (porosity, permeability, depth and temperature) properties. Our approach is observation-driven and grounded on an exhaustive data-base which we compile upon considering worldwide EOR field experiences. A preliminary reduction of the dimensionality of the parameter space over which EOR projects are classified is accomplished through Principal Component Analysis (PCA). A screening of target analogs is then obtained by classification of documented EOR projects through a Bayesian clustering algorithm. Considering the cluster which comprises the EOR field under evaluation, an inter-cluster refinement is then accomplished by ordering cluster components on the basis of a weighted Euclidean distance from the target field in the (multidimensional) parameter space. Distinctive features of our methodology are that (a) all screening analyses are performed on the database projected onto the space of principal components, and (b) the fraction of variance associated with each principal component is taken as weight of the Euclidean distance we determine. As a test bed, we apply our approach on three fields operated by eni. These include light, medium and heavy-oil reservoirs, where Gas, Chemical and Thermal EOR projects have been respectively proposed. Our results are (a) conducive to the compilation of a broad and extensively usable data-base of EOR settings and (b) consistent with the field observations related to the three tested and already planned/implemented EOR methodologies, thus demonstrating the effectiveness of our approach

A New Bayesian Approach for Analogs Evaluation in Advanced EOR Screening

AbstractWe present and test a new screening methodology to discriminate amongst alternative and competing Enhanced Oil Recovery (EOR) techniques to be considered for a given reservoir. Our work is motivated by the observation that, even if a considerable variety of EOR techniques have been successfully applied to extend oilfield production and lifetime, an EOR project requires extensive laboratory and pilot tests prior to field-wide implementation and preliminary assessment of EOR potential in a reservoir is critical in the decision-making process. Since similar EOR techniques may be successful in fields sharing some global features, as basic discrimination criteria we consider fluid (density and viscosity) and reservoir formation (porosity, permeability, depth and temperature) properties. Our approach is observation-driven and grounded on an exhaustive data-base which we compile upon considering worldwide EOR field experiences. A preliminary reduction of the dimensionality of the parameter space over which EOR projects are classified is accomplished through Principal Component Analysis (PCA). A screening of target analogs is then obtained by classification of documented EOR projects through a Bayesian clustering algorithm. Considering the cluster which comprises the EOR field under evaluation, an inter-cluster refinement is then accomplished by ordering cluster components on the basis of a weighted Euclidean distance from the target field in the (multidimensional) parameter space. Distinctive features of our methodology are that (a) all screening analyses are performed on the database projected onto the space of principal components, and (b) the fraction of variance associated with each principal component is taken as weight of the Euclidean distance we determine. As a test bed, we apply our approach on three fields operated by eni. These include light, medium and heavy-oil reservoirs, where Gas, Chemical and Thermal EOR projects have been respectively proposed. Our results are (a) conducive to the compilation of a broad and extensively usable data-base of EOR settings and (b) consistent with the field observations related to the three tested and already planned/implemented EOR methodologies, thus demonstrating the effectiveness of our approach.</jats:p

The Use of Monensin for Ketosis Prevention in Dairy Cows during the Transition Period: A Systematic Review

Since the approval by the European Medicines Agency in 2013 of a monensin controlled-release capsule (CRC) for the prevention of ketosis in dairy cows, there has been widespread use across Europe. In recent decades, several papers have investigated the effects of monensin used as a CRC or as a feed additive to improve cattle energy metabolism and improve feed efficiency. Since the CRC is the only form of monensin permitted in Europe in dairy cows, the objective of this review was to report and summarize observations from the literature on the effects of this treatment in transition cows. The peer-reviewed literature published from 1997 was scanned, and papers written in English were evaluated for eligibility. Only papers evaluating the use of monensin in dairy cows for the prevention of ketosis during the transition period were reviewed. In total, 42 papers met the required criteria and were included in this review. The major findings focused on cow metabolism and health, rumen fermentation and milk production and quality. Overall, the review of the existing literature confirmed that monensin delivered as a CRC during the transition period has effects of different magnitude compared to other forms, doses or durations of administration. Studies agree on the antiketotic effects of this treatment, showing evidence of an increased propionate production in the rumen, reduced blood β-hydroxybutyrate, and improved liver function in treated cows, mainly resulting in reduced incidence of peripartum disease. On the contrary, the effects of CRC on ammonia production and rumen microflora are less robust than those reported for other forms. Of importance for the European market is the well-documented absence of any negative impact on milk and cheese production and composition using the CRC treatment