Geochemical modeling of magmatic gas scrubbing

The EQ3/6 software package, version 7.2 was successfully used to model scrubbing of magmatic gas by pure water at 0.1 MPa, in the liquid and liquid-plus-gas regions. Some post-calculations were necessary to account for gas separation effects. In these post-calculations, redox potential was considered to be fixed by precipitation of crystalline a-sulfur, a ubiquitous and precocious process. As geochemical modeling is constrained by conservation of enthalpy upon water-gas mixing, the enthalpies of the gas species of interest were reviewed, adopting as reference state the liquid phase at the triple point. Our results confirm that significant emissions of highly acidic gas species (SO2(g), HCl(g), and HF(g)) are prevented by scrubbing, until dry conditions are established, at least locally. Nevertheless important outgassing of HCl(g) can take place from acid, HCl-rich brines. Moreover, these findings support the rule of thumb which is generally used to distinguish SO2-, HCl-, and HF-bearing magmatic gases from SO2-, HCl-, and HF-free hydrothermal gases

Alterations in the self-renewal and differentiation ability of bone marrow mesenchymal stem cells in a mouse model of rheumatoid arthritis

Introduction: Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease primarily involving the synovium. Evidence in recent years has suggested that the bone marrow (BM) may be involved, and may even be the initiating site of the disease. Abnormalities in haemopoietic stem cells' (HSC) survival, proliferation and aging have been described in patients affected by RA and ascribed to abnormal support by the BM microenvironment. Mesenchymal stem cells (MSC) and their progeny constitute important components of the BM niche. In this study we test the hypothesis that the onset of inflammatory arthritis is associated with altered self-renewal and differentiation of bone marrow MSC, which alters the composition of the BM microenvironment. Methods: We have used Balb/C Interleukin-1 receptor antagonist knock-out mice, which spontaneously develop RA-like disease in 100% of mice by 20 weeks of age to determine the number of mesenchymal progenitors and their differentiated progeny before, at the start and with progression of the disease. Results: We showed a decrease in the number of mesenchymal progenitors with adipogenic potential and decreased bone marrow adipogenesis before disease onset. This is associated with a decrease in osteoclastogenesis. Moreover, at the onset of disease a significant increase in all mesenchymal progenitors is observed together with a block in their differentiation to osteoblasts. This is associated with accelerated bone loss. Conclusions: Significant changes occur in the BM niche with the establishment and progression of RA-like disease. Those changes may be responsible for aspects of the disease, including the advance of osteoporosis. An understanding of the molecular mechanisms leading to those changes may lead to new strategies for therapeutic intervention

Letters

www.elsevier.com/locate/dsw A branch and bound algorithm for the robust shortest path problem with interval data

Ant Colony System for a Dynamic Vehicle Routing Problem

An aboundant literature on vehicle routing problems is available. However, most of the work deals with static problems, where all data are known in advance, i.e. before the optimization has started. The technological advances of the last few years give rise to a new class of problems, namely the dynamic vehicle routing problems, where new orders are received as time progresses and must be dynamically incorporated into an evolving schedule. In this paper a dynamic vehicle routing problem is examined and a solving strategy, based on the Ant Colony System paradigm, is proposed. Some new public domain benchmark problems are defined, and the algorithm we propose is tested on them. Finally, the method we present is applied to a realistic case study, set up in the city of Lugano (Switzerland

Magnetic Reversal Time in Open Long Range Systems

Topological phase space disconnection has been recently found to be a general phenomenon in isolated anisotropic spin systems. It sets a general framework to understand the emergence of ferromagnetism in finite magnetic systems starting from microscopic models without phenomenological on-site barriers. Here we study its relevance for finite systems with long range interacting potential in contact with a thermal bath. We show that, even in this case, the induced magnetic reversal time is exponentially large in the number of spins, thus determining {\it stable} (to any experimental observation time) ferromagnetic behavior. Moreover, the explicit temperature dependence of the magnetic reversal time obtained from the microcanonical results, is found to be in good agreement with numerical simulations. Also, a simple and suggestive expression, indicating the Topological Energy Threshold at which the disconnection occurs, as a real energy barrier for many body systems, is obtained analytically for low temperature

Objective way to support embryo transfer: a probabilistic decision

STUDY QUESTION Is it feasible to identify factors that significantly affect the clinical outcome of IVF-ICSI cycles and use them to reliably design a predictor of implantation? SUMMARY ANSWER The Bayesian network (BN) identified top-history embryos, female age and the insemination technique as the most relevant factors for predicting the occurrence of pregnancy (AUC, area under curve, of 0.72). In addition, it could discriminate between no implantation and single or twin implantations in a prognostic model that can be used prospectively. WHAT IS KNOWN ALREADY The key requirement for achieving a single live birth in an IVF-ICSI cycle is the capacity to estimate embryo viability in relation to maternal receptivity. Nevertheless, the lack of a strong predictor imposes several restrictions on this strategy. STUDY DESIGN, SIZE, DURATION Medical histories, laboratory data and clinical outcomes of all fresh transfer cycles performed at the International Institute for Reproductive Medicine of Lugano, Switzerland, in the period 2006-2008 (n = 388 cycles), were retrospectively evaluated and analyzed. PARTICIPANTS/MATERIALS, SETTING, METHODS Patients were unselected for age, sperm parameters or other infertility criteria. Before being admitted to treatment, uterine anomalies were excluded by diagnostic hysteroscopy. To evaluate the factors possibly related to embryo viability and maternal receptivity, the class variable was categorized as pregnancy versus no pregnancy and the features included: female age, number of previous cycles, insemination technique, sperm of proven fertility, the number of transferred top-history embryos, the number of transferred top-quality embryos, the number of follicles >14 mm and the level of estradiol on the day of HCG administration. To assess the classifier, the indicators of performance were computed by cross-validation. Two statistical models were used: the decision tree and the BN. MAIN RESULTS AND THE ROLE OF CHOICE The decision tree identified the number of transferred top-history embryos, female age and the insemination technique as the features discriminating between pregnancy and no pregnancy. The model achieved an accuracy of 81.5% that was significantly higher in comparison with the trivial classifier, but the increase was so modest that the model was clinically useless for predictions of pregnancy. The BN could more reliably predict the occurrence of pregnancy with an AUC of 0.72, and confirmed the importance of top-history embryos, female age and insemination technique in determining implantation. In addition, it could discriminate between no implantation, single implantation and twin implantation with the AUC of 0.72, 0.64 and 0.83, respectively. LIMITATIONS, REASONS FOR CAUTION The relatively small sample of the study did not permit the inclusion of more features that could also have a role in determining the clinical outcome. The design of this study was retrospective to identify the relevant features; a prospective study is now needed to verify the validity of the model. WIDER IMPLICATIONS OF THE FINDINGS The resulting predictive model can discriminate with reasonable reliability between pregnancy and no pregnancy, and can also predict the occurrence of a single pregnancy or multiple pregnancy. This could represent an effective support for deciding how many embryos and which embryos to transfer for each couple. Due to its flexibility, the number of variables in the predictor can easily be increased to include other features that may affect implantation. STUDY FUNDING/COMPETING INTERESTS This study was supported by a grant, CTI Medtech Project Number: 9707.1 PFLS-L, Swiss Confederation. No competing interests are declare

Explicit Solution to the N-Body Calogero Problem

We solve the N-body Calogero problem, \ie N particles in 1 dimension subject to a two-body interaction of the form \half \sum_{i,j}[ (x_i - x_j)^2 + g/ {(x_i - x_j)^2}], by constructing annihilation and creation operators of the form $a_i^\mp =\frac 1 {\sqrt 2} (x _i \pm i\hat{p}_i )$, where $\hat{p}_i$ is a modified momentum operator obeying %!!!!!!! Heisenberg-type commutation relations with $x_i$, involving explicitly permutation operators. On the other hand, $D_j =i\,\hat{p}_j$ can be interpreted as a covariant derivative corresponding to a flat connection. The relation to fractional statistics in 1+1 dimensions and anyons in a strong magnetic field is briefly discussed.Comment: 6 p., latex, USITP-92-

Ant colony optimisation and local search for bin-packing and cutting stock problems

The Bin Packing Problem and the Cutting Stock Problem are two related classes of NP-hard combinatorial optimization problems. Exact solution methods can only be used for very small instances, so for real-world problems, we have to rely on heuristic methods. In recent years, researchers have started to apply evolutionary approaches to these problems, including Genetic Algorithms and Evolutionary Programming. In the work presented here, we used an ant colony optimization (ACO) approach to solve both Bin Packing and Cutting Stock Problems. We present a pure ACO approach, as well as an ACO approach augmented with a simple but very effective local search algorithm. It is shown that the pure ACO approach can compete with existing evolutionary methods, whereas the hybrid approach can outperform the best-known hybrid evolutionary solution methods for certain problem classes. The hybrid ACO approach is also shown to require different parameter values from the pure ACO approach and to give a more robust performance across different problems with a single set of parameter values. The local search algorithm is also run with random restarts and shown to perform significantly worse than when combined with ACO