Heat flow for Yang-Mills-Higgs fields, part I

The Yang-Mills-Higgs field generalizes the Yang-Mills field. The authors establish the local existence and uniqueness of the weak solution to the heat flow for the Yang-Mills-Higgs field in a vector bundle over a compact Riemannian 4-manifold, and show that the weak solution is gauge-equivalent to a smooth solution and there are at most finite singularities at the maximum existing time.

Effects of Non-Susceptible Hosts on the Infection with Trypanosoma cruzi of the Vector Triatoma infestans: an Experimental Model

We tested experimentally the effects of the presence of non-susceptible hosts on the infection with Trypanosoma cruzi of the vector Triatoma infestans. The experiment consisted in two treatments: with chickens, including two chickens (non-susceptible hosts) and two infected guinea pigs (susceptible hosts), and without chickens, including only two infected guinea pigs. The hosts were held unrestrained in individual metal cages inside a closed tulle chamber. A total of 200 uninfected T. infestans third instar nymphs were liberated in each replica, collected on day 14, and examined for infection and blood meal sources on day 32-36. The additional presence of chickens relative to infected guinea pigs: (a) significantly modified the spatial distribution of bugs; (b) increased significantly the likelihoods of having a detectable blood meal on any host and molting to the next instar; (c) did not affect the bugs' probability of death by predation; and (d) decreased significantly the overall percentage of T. infestans infected with T. cruzi. The bugs collected from inside or close to the guinea pigs' cages showed a higher infection rate (71-88%) than those collected from the chickens' cages (22-32%). Mixed blood meals on chickens and guinea pigs were detected in 12-21% of bugs. Although the presence of chickens would decrease the overall percentage of infected bugs in short term experiments, the high rate of host change of T. infestans would make this difference fade out if longer exposure times had been provided.

Textural classification of land cover using support vector machines: an empirical comparison with parametric, non parametric and hybrid classifiers in the Bolivian Amazon

Land cover classification is a key research field in remote sensing and land change science as thematic maps derived from remotely sensed data have become the basis for analyzing many socio-ecological issues. However, land cover classification remains a difficult task and it is especially challenging in heterogeneous tropical landscapes where nonetheless such maps are of great importance. The present study aims to establish an efficient classification approach to accurately map all broad land cover classes in a large, heterogeneous tropical area of Bolivia, as a basis for further studies (e.g., land cover-land use change). Specifically, we compare the performance of parametric (maximum likelihood), non-parametric (k-nearest neighbour and four different support vector machines - SVM), and hybrid classifiers, using both hard and soft (fuzzy) accuracy assessments. In addition, we test whether the inclusion of a textural index (homogeneity) in the classifications improves their performance. We classified Landsat imagery for two dates corresponding to dry and wet seasons and found that non-parametric, and particularly SVM classifiers, outperformed both parametric and hybrid classifiers. We also found that the use of the homogeneity index along with reflectance bands significantly increased the overall accuracy of all the classifications, but particularly of SVM algorithms. We observed that improvements in producer’s and user’s accuracies through the inclusion of the homogeneity index were different depending on land cover classes. Earlygrowth/degraded forests, pastures, grasslands and savanna were the classes most improved, especially with the SVM radial basis function and SVM sigmoid classifiers, though with both classifiers all land cover classes were mapped with producer’s and user’s accuracies of around 90%. Our approach seems very well suited to accurately map land cover in tropical regions, thus having the potential to contribute to conservation initiatives, climate change mitigation schemes such as REDD+, and rural development policies.

Learning wind fields with multiple kernels

This paper presents multiple kernel learning (MKL) regression as an exploratory spatial data analysis and modelling tool. The MKL approach is introduced as an extension of support vector regression, where MKL uses dedicated kernels to divide a given task into sub-problems and to treat them separately in an effective way. It provides better interpretability to non-linear robust kernel regression at the cost of a more complex numerical optimization. In particular, we investigate the use of MKL as a tool that allows us to avoid using ad-hoc topographic indices as covariables in statistical models in complex terrains. Instead, MKL learns these relationships from the data in a non-parametric fashion. A study on data simulated from real terrain features confirms the ability of MKL to enhance the interpretability of data-driven models and to aid feature selection without degrading predictive performances. Here we examine the stability of the MKL algorithm with respect to the number of training data samples and to the presence of noise. The results of a real case study are also presented, where MKL is able to exploit a large set of terrain features computed at multiple spatial scales, when predicting mean wind speed in an Alpine region.

Non invasive classification system of scoliosis curve types using least-squares support vector machines

Objective To determine scoliosis curve types using non invasive surface acquisition, without prior knowledge from X-ray data. Methods Classification of scoliosis deformities according to curve type is used in the clinical management of scoliotic patients. In this work, we propose a robust system that can determine the scoliosis curve type from non invasive acquisition of the 3D back surface of the patients. The 3D image of the surface of the trunk is divided into patches and local geometric descriptors characterizing the back surface are computed from each patch and constitute the features. We reduce the dimensionality by using principal component analysis and retain 53 components using an overlap criterion combined with the total variance in the observed variables. In this work, a multi-class classifier is built with least-squares support vector machines (LS-SVM). The original LS-SVM formulation was modified by weighting the positive and negative samples differently and a new kernel was designed in order to achieve a robust classifier. The proposed system is validated using data from 165 patients with different scoliosis curve types. The results of our non invasive classification were compared with those obtained by an expert using X-ray images. Results The average rate of successful classification was computed using a leave-one-out cross-validation procedure. The overall accuracy of the system was 95%. As for the correct classification rates per class, we obtained 96%, 84% and 97% for the thoracic, double major and lumbar/thoracolumbar curve types, respectively. Conclusion This study shows that it is possible to find a relationship between the internal deformity and the back surface deformity in scoliosis with machine learning methods. The proposed system uses non invasive surface acquisition, which is safe for the patient as it involves no radiation. Also, the design of a specific kernel improved classification performance.

Non-Born-Oppenheimer Dynamics of Hydrogen Molecules in Strong Laser-Fields

Die Arbeit behandelt die numerische Untersuchung von Wasserstoff-Moleküldynamik in starken Laserfeldern. Im Speziellen wird die Struktur von Ionisationsspektren bei Einfach-Photoionisation betrachtet. Korrelationen zwischen Elektron- und Kernbewegung werden identifiziert und mit Effekten in den Energiespektren in Verbindung gebracht. Dabei wird stets auf die Integration der zeitabhängigen Schrödingergleichung zurückgegriffen.

First-principles electronic theory of non-collinear magnetic order in transition-metal nanowires

The structural, electronic and magnetic properties of one-dimensional 3d transition-metal (TM) monoatomic chains having linear, zigzag and ladder geometries are investigated in the frame-work of first-principles density-functional theory. The stability of long-range magnetic order along the nanowires is determined by computing the corresponding frozen-magnon dispersion relations as a function of the 'spin-wave' vector q. First, we show that the ground-state magnetic orders of V, Mn and Fe linear chains at the equilibrium interatomic distances are non-collinear (NC) spin-density waves (SDWs) with characteristic equilibrium wave vectors q that depend on the composition and interatomic distance. The electronic and magnetic properties of these novel spin-spiral structures are discussed from a local perspective by analyzing the spin-polarized electronic densities of states, the local magnetic moments and the spin-density distributions for representative values q. Second, we investigate the stability of NC spin arrangements in Fe zigzag chains and ladders. We find that the non-collinear SDWs are remarkably stable in the biatomic chains (square ladder), whereas ferromagnetic order (q =0) dominates in zigzag chains (triangular ladders). The different magnetic structures are interpreted in terms of the corresponding effective exchange interactions J(ij) between the local magnetic moments μ(i) and μ(j) at atoms i and j. The effective couplings are derived by fitting a classical Heisenberg model to the ab initio magnon dispersion relations. In addition they are analyzed in the framework of general magnetic phase diagrams having arbitrary first, second, and third nearest-neighbor (NN) interactions J(ij). The effect of external electric fields (EFs) on the stability of NC magnetic order has been quantified for representative monoatomic free-standing and deposited chains. We find that an external EF, which is applied perpendicular to the chains, favors non-collinear order in V chains, whereas it stabilizes the ferromagnetic (FM) order in Fe chains. Moreover, our calculations reveal a change in the magnetic order of V chains deposited on the Cu(110) surface in the presence of external EFs. In this case the NC spiral order, which was unstable in the absence of EF, becomes the most favorable one when perpendicular fields of the order of 0.1 V/Å are applied. As a final application of the theory we study the magnetic interactions within monoatomic TM chains deposited on graphene sheets. One observes that even weak chain substrate hybridizations can modify the magnetic order. Mn and Fe chains show incommensurable NC spin configurations. Remarkably, V chains show a transition from a spiral magnetic order in the freestanding geometry to FM order when they are deposited on a graphene sheet. Some TM-terminated zigzag graphene-nanoribbons, for example V and Fe terminated nanoribbons, also show NC spin configurations. Finally, the magnetic anisotropy energies (MAEs) of TM chains on graphene are investigated. It is shown that Co and Fe chains exhibit significant MAEs and orbital magnetic moments with in-plane easy magnetization axis. The remarkable changes in the magnetic properties of chains on graphene are correlated to charge transfers from the TMs to NN carbon atoms. Goals and limitations of this study and the resulting perspectives of future investigations are discussed.

Non-steroidal anti-inflammatory drugs (NSAIDs) inhibit vascular smooth muscle cell proliferation via differential effects on the cell cycle

Abnormal vascular smooth muscle cell (VSMC) proliferation plays an important role in the pathogenesis of both atherosclerosis and restenosis. Recent studies suggest that high-dose salicylates, in addition to inhibiting cyclooxygenase activity, exert an antiproliferative effect on VSMC growth both in-vitro and in-vivo. However, whether all non-steroidal anti-inflammatory drugs (NSAIDs) exert similar anti proliferative effects on VSMCs, and do so via a common mechanism of action, remains to be shown. In this study, we demonstrate that the NSAIDs aspirin, sodium salicylate, diclofenac, ibuprofen, indometacin and sulindac induce a dose-dependent inhibition of proliferation in rat A10 VSMCs in the absence of significant cytotoxicity. Flow cytometric analyses showed that exposure of A10 cells to diclofenac, indometacin, ibuprofen and sulindac, in the presence of the mitotic inhibitor, nocodazole, led to a significant G0/G1 arrest. In contrast, the salicylates failed to induce a significant G1 arrest since flow cytometry profiles were not significantly different from control cells. Cyclin A levels were elevated, and hyperphosphorylated p107 was present at significant levels, in salicylate-treated A10 cells, consistent with a post-G1/S block, whereas cyclin A levels were low, and hypophosphorylated p107 was the dominant form, in cells treated with other NSAIDs consistent with a G1 arrest. The ubiquitously expressed cyclin-dependent kinase (CDK) inhibitors, p21 and p27, were increased in all NSAID-treated cells. Our results suggest that diclofenac, indometacin, ibuprofen and sulindac inhibit VSMC proliferation by arresting the cell cycle in the G1 phase, whereas the growth inhibitory effect of salicylates probably affects the late S and/or G2/M phases. Irrespective of mechanism, our results suggest that NSAIDs might be of benefit in the treatment of certain vasculoproliferative disorders.

Inhibition of vascular smooth muscle cell proliferation by non-steroidal anti-inflammatory drugs

Abnormal vascular smooth muscle cell (VSMC) proliferation is known to play an important role in the pathogenesis of atherosclerosis, restenosis and instent stenosis. Recent studies suggest that salicylates, in addition to inhibiting cyclooxygenase activity, exert an antiproliferative effect on VSMC growth both in vitro and in vivo. However, whether all non-steroidal anti-inflammatory drugs (NSAID) exert similar antiproliferative effects on VSMCs, and do so via a common mechanism of action, remains unknown. In the present study, we demonstrated that the NSAIDs, aspirin, ibuprofen and sulindac induced a dose-dependent inhibition of proliferation in rat A10 VSMCs (IC50 = 1666 mumol/L, 937 mumol/L and 520 mumol/L, respectively). These drugs did not show significant cytotoxic effects as determined by LDH release assay, even at the highest concentrations tested (aspirin, 5000 mumol/L; ibuprofen, 2500 mumol/L; and sulindac, 1000 mumol/L). Flow cytometric analyses showed that a 48 h exposure of A10 VSMCs to ibuprofen (1000 mumol/L) and sulindac (750 mumol/L) led to a significant G1 arrest (from 68.7 +/- 2.0% of cells in G1 to 76.6 +/- 2.2% and 75.8 +/- 2.2%, respectively, p < 0.05). In contrast, aspirin (2500 mumol/L) failed to induce a significant G1 arrest (68.1 +/- 5.2%). Clearer evidence of a G1 block was obtained by treatment of cells with the mitotic inhibitor, nocodazole (40 ng/ml), for the final 24 h of the experiment. Under these conditions, aspirin still failed to induce a G1 arrest (from 25.9 +/- 10.9% of cells in G1 to 19.6 +/- 2.3%) whereas ibuprofen and sulindac led to a significant accumulation of cells in G1(51.8% +/- 17.2% and 54.1% +/- 10.6%, respectively, p < 0.05). These results indicate that ibuprofen and sulindac inhibit VSMC proliferation by arresting the cell cycle in the G1 phase whereas the effect of aspirin appears to be independent of any special phase of the cell cycle. Irrespective of mechanism, our results suggest that NSAIDs might be of benefit to the treatment of vascular proliferative disorders.

Technologies for biological containment of GM and Non-GM crops

International Perspective The development of GM technology continues to expand into increasing numbers of crops and conferred traits. Inevitably, the focus remains on the major field crops of soybean, maize, cotton, oilseed rape and potato with introduced genes conferring herbicide tolerance and/or pest resistance. Although there are comparatively few GM crops that have been commercialised to date, GM versions of 172 plant species have been grown in field trials in 31 countries. European Crops with Containment Issues Of the 20 main crops in the EU there are four for which GM varieties are commercially available (cotton, maize for animal feed and forage, and oilseed rape). Fourteen have GM varieties in field trials (bread wheat, barley, durum wheat, sunflower, oats, potatoes, sugar beet, grapes, alfalfa, olives, field peas, clover, apples, rice) and two have GM varieties still in development (rye, triticale). Many of these crops have hybridisation potential with wild and weedy relatives in the European flora (bread wheat, barley, oilseed rape, durum wheat, oats, sugar beet and grapes), with escapes (sunflower); and all have potential to cross-pollinate fields non-GM crops. Several fodder crops, forestry trees, grasses and ornamentals have varieties in field trials and these too may hybridise with wild relatives in the European flora (alfalfa, clover, lupin, silver birch, sweet chestnut, Norway spruce, Scots pine, poplar, elm, Agrostis canina, A. stolonifera, Festuca arundinacea, Lolium perenne, L. multiflorum, statice and rose). All these crops will require containment strategies to be in place if it is deemed necessary to prevent transgene movement to wild relatives and non-GM crops. Current Containment Strategies A wide variety of GM containment strategies are currently under development, with a particular focus on crops expressing pharmaceutical products. Physical containment in greenhouses and growth rooms is suitable for some crops (tomatoes, lettuce) and for research purposes. Aquatic bioreactors of some non-crop species (algae, moss, and duckweed) expressing pharmaceutical products have been adopted by some biotechnology companies. There are obvious limitations of the scale of physical containment strategies, addressed in part by the development of large underground facilities in the US and Canada. The additional resources required to grow plants underground incurs high costs that in the long term may negate any advantage of GM for commercial productioNatural genetic containment has been adopted by some companies through the selection of either non-food/feed crops (algae, moss, duckweed) as bio-pharming platforms or organisms with no wild relatives present in the local flora (safflower in the Americas). The expression of pharmaceutical products in leafy crops (tobacco, alfalfa, lettuce, spinach) enables growth and harvesting prior to and in the absence of flowering. Transgenically controlled containment strategies range in their approach and degree of development. Plastid transformation is relatively well developed but is not suited to all traits or crops and does not offer complete containment. Male sterility is well developed across a range of plants but has limitations in its application for fruit/seed bearing crops. It has been adopted in some commercial lines of oilseed rape despite not preventing escape via seed. Conditional lethality can be used to prevent flowering or seed development following the application of a chemical inducer, but requires 100% induction of the trait and sufficient application of the inducer to all plants. Equally, inducible expression of the GM trait requires equally stringent application conditions. Such a method will contain the trait but will allow the escape of a non-functioning transgene. Seed lethality (‘terminator’ technology) is the only strategy at present that prevents transgene movement via seed, but due to public opinion against the concept it has never been trialled in the field and is no longer under commercial development. Methods to control flowering and fruit development such as apomixis and cleistogamy will prevent crop-to-wild and wild-to-crop pollination, but in nature both of these strategies are complex and leaky. None of the genes controlling these traits have as yet been identified or characterised and therefore have not been transgenically introduced into crop species. Neither of these strategies will prevent transgene escape via seed and any feral apomicts that form are arguably more likely to become invasives. Transgene mitigation reduces the fitness of initial hybrids and so prevents stable introgression of transgenes into wild populations. However, it does not prevent initial formation of hybrids or spread to non-GM crops. Such strategies could be detrimental to wild populations and have not yet been demonstrated in the field. Similarly, auxotrophy prevents persistence of escapes and hybrids containing the transgene in an uncontrolled environment, but does not prevent transgene movement from the crop. Recoverable block of function, intein trans-splicing and transgene excision all use recombinases to modify the transgene in planta either to induce expression or to prevent it. All require optimal conditions and 100% accuracy to function and none have been tested under field conditions as yet. All will contain the GM trait but all will allow some non-native DNA to escape to wild populations or to non-GM crops. There are particular issues with GM trees and grasses as both are largely undomesticated, wind pollinated and perennial, thus providing many opportunities for hybridisation. Some species of both trees and grass are also capable of vegetative propagation without sexual reproduction. There are additional concerns regarding the weedy nature of many grass species and the long-term stability of GM traits across the life span of trees. Transgene stability and conferred sterility are difficult to trial in trees as most field trials are only conducted during the juvenile phase of tree growth. Bio-pharming of pharmaceutical and industrial compounds in plants Bio-pharming of pharmaceutical and industrial compounds in plants offers an attractive alternative to mammalian-based pharmaceutical and vaccine production. Several plantbased products are already on the market (Prodigene’s avidin, β-glucuronidase, trypsin generated in GM maize; Ventria’s lactoferrin generated in GM rice). Numerous products are in clinical trials (collagen, antibodies against tooth decay and non-Hodgkin’s lymphoma from tobacco; human gastric lipase, therapeutic enzymes, dietary supplements from maize; Hepatitis B and Norwalk virus vaccines from potato; rabies vaccines from spinach; dietary supplements from Arabidopsis). The initial production platforms for plant-based pharmaceuticals were selected from conventional crops, largely because an established knowledge base already existed. Tobacco and other leafy crops such as alfalfa, lettuce and spinach are widely used as leaves can be harvested and no flowering is required. Many of these crops can be grown in contained greenhouses. Potato is also widely used and can also be grown in contained conditions. The introduction of morphological markers may aid in the recognition and traceability of crops expressing pharmaceutical products. Plant cells or plant parts may be transformed and maintained in culture to produce recombinant products in a contained environment. Plant cells in suspension or in vitro, roots, root cells and guttation fluid from leaves may be engineered to secrete proteins that may be harvested in a continuous, non-destructive manner. Most strategies in this category remain developmental and have not been commercially adopted at present. Transient expression produces GM compounds from non-GM plants via the utilisation of bacterial or viral vectors. These vectors introduce the trait into specific tissues of whole plants or plant parts, but do not insert them into the heritable genome. There are some limitations of scale and the field release of such crops will require the regulation of the vector. However, several companies have several transiently expressed products in clinical and pre-clinical trials from crops raised in physical containment.

Do the legs of magnetic clouds contain twisted flux-rope magnetic fields?

Magnetic clouds (MCs) are a subset of interplanetary coronal mass ejections (ICMEs) characterised primarily by a smooth rotation in the magnetic field direction indicative of the presence of a magnetic flux rope. Energetic particle signatures suggest MC flux ropes remain magnetically connected to the Sun at both ends, leading to widely used model of global MC structure as an extended flux rope, with a loop-like axis stretching out from the Sun into the heliosphere and back to the Sun. The time of flight of energetic particles, however, suggests shorter magnetic field line lengths than such a continuous twisted flux rope would produce. In this study, two simple models are compared with observed flux rope axis orientations of 196 MCs to show that the flux rope structure is confined to the MC leading edge. The magnetic cloud “legs,” which magnetically connect the flux rope to the Sun, are not recognisable as MCs and thus are unlikely to contain twisted flux rope fields. Spacecraft encounters with these non-flux rope legs may provide an explanation for the frequent observation of non-magnetic cloud ICMEs.

Conservative force fields in non-Gaussian statistics

In this Letter, we determine the kappa-distribution function for a gas in the presence of an external field of force described by a potential U(r). In the case of a dilute gas, we show that the kappa-power law distribution including the potential energy factor term can rigorously be deduced in the framework of kinetic theory with basis on the Vlasov equation. Such a result is significant as a preliminary to the discussion on the role of long range interactions in the Kaniadakis thermostatistics and the underlying kinetic theory. (C) 2008 Elsevier B.V. All rights reserved.

Indecomposable and noncrossed product division algebras over function fields of smooth p-adic curves

We construct indecomposable and noncrossed product division algebras over function fields of connected smooth curves X over Z(p). This is done by defining an index preserving morphism s: Br(<(K(X))over cap>)` --> Br(K(X))` which splits res : Br(K (X)) --> Br(<(K(X))over cap>), where <(K(X))over cap> is the completion of K (X) at the special fiber, and using it to lift indecomposable and noncrossed product division algebras over <(K(X))over cap>. (C) 2010 Elsevier Inc. All rights reserved.