Spin alignment measurements of the K*(0)(892) and phi(1020) vector mesons in heavy ion collisions at root S(NN)=200 GeV

We present the first spin alignment measurements for the K*(0)(892) and phi(1020) vector mesons produced at midrapidity with transverse momenta up to 5 GeV/c at root s(NN) = 200 GeV at RHIC. The diagonal spin-density matrix elements with respect to the reaction plane in Au+Au collisions are rho(00) = 0.32 +/- 0.04 (stat) +/- 0.09 (syst) for the K*(0) (0.8 < p(T) < 5.0 GeV/c) and rho(00) = 0.34 +/- 0.02 (stat) +/- 0.03 (syst) for the phi (0.4 < p(T) < 5.0 GeV/c) and are constant with transverse momentum and collision centrality. The data are consistent with the unpolarized expectation of 1/3 and thus no evidence is found for the transfer of the orbital angular momentum of the colliding system to the vector-meson spins. Spin alignments for K(*0) and phi in Au+Au collisions were also measured with respect to the particle's production plane. The phi result, rho(00) = 0.41 +/- 0.02 (stat) +/- 0.04 (syst), is consistent with that in p+p collisions, rho(00) = 0.39 +/- 0.03 (stat) +/- 0.06 (syst), also measured in this work. The measurements thus constrain the possible size of polarization phenomena in the production dynamics of vector mesons.

Expression of matrix metalloproteinase 2 (MMP-2) and tissue inhibitor of metalloproteinase 2 (TIMP-2) in medullary thyroid carcinoma: Prognostic implications

Background: Metalloproteinase 2 (MMP-2) and tissue inhibitor of metalloproteinase 2 (TIMP-2) participate in the degeneration of the extracellular matrix and are associated with carcinogenesis. MMP-2 is one of the main metalloproteinases active in neoplasia and is a marker of the malignant phenotype. Since the biological behavior of medullary thyroid carcinoma (MTC) varies widely, the present study was undertaken to determine if there is a correlation between the clinical evolution of MTC and the immunohistochemically detected expression of these enzymes in thyroid surgical specimens containing MTC. If so, their expression would be a novel indicator of the prognosis of MTC. Methods: Thirty-seven patients with MTC who had undergone thyroid surgery were followed for an average of 73 months. Immunohistochemical staining for metalloproteinase-related enzymes was performed in surgical paraffin blocks. The clinical status of the patients after surgery and at the end of the study period was characterized to determine correlations between these and the immunohistochemical markers. A value of p < 0.05 was considered statistically significant. Results: At the end of the study period, 15 patients (40.5%) were alive and without evidence of MTC, 17 (45.9%) had persistent MTC, and 5 (13.5%) had a relapse of their neoplasia. Four patients (10.8%) died during the course of the study. There was a significant correlation (p = 0.0005) between the immunohistochemical staining for MMP-2 and the clinical condition of the patients at the end of the study period, and a correlation between the state of apparent cure compared to persistence of MTC after thyroid surgery (p = 0.0207). No significant correlations were observed between either TIMP-2 expression or immune marking of metastatic lymph nodes and the clinical variables studied. Conclusion: Immunohistochemical expression of MMP-2 in thyroid surgical specimens from patients with MTC is a novel indicator of the prognosis of this cancer.

Lineage divergence detected in the malaria vector Anopheles marajoara (Diptera: Culicidae) in Amazonian Brazil

Background: Cryptic species complexes are common among anophelines. Previous phylogenetic analysis based on the complete mtDNA COI gene sequences detected paraphyly in the Neotropical malaria vector Anopheles marajoara. The ""Folmer region"" detects a single taxon using a 3% divergence threshold. Methods: To test the paraphyletic hypothesis and examine the utility of the Folmer region, genealogical trees based on a concatenated (white + 3' COI sequences) dataset and pairwise differentiation of COI fragments were examined. The population structure and demographic history were based on partial COI sequences for 294 individuals from 14 localities in Amazonian Brazil. 109 individuals from 12 localities were sequenced for the nDNA white gene, and 57 individuals from 11 localities were sequenced for the ribosomal DNA (rDNA) internal transcribed spacer 2 (ITS2). Results: Distinct A. marajoara lineages were detected by combined genealogical analysis and were also supported among COI haplotypes using a median joining network and AMOVA, with time since divergence during the Pleistocene (< 100,000 ya). COI sequences at the 3' end were more variable, demonstrating significant pairwise differentiation (3.82%) compared to the more moderate 2.92% detected by the Folmer region. Lineage 1 was present in all localities, whereas lineage 2 was restricted mainly to the west. Mismatch distributions for both lineages were bimodal, likely due to multiple colonization events and spatial expansion (similar to 798 - 81,045 ya). There appears to be gene flow within, not between lineages, and a partial barrier was detected near Rio Jari in Amapa state, separating western and eastern populations. In contrast, both nDNA data sets (white gene sequences with or without the retention of the 4th intron, and ITS2 sequences and length) detected a single A. marajoara lineage. Conclusions: Strong support for combined data with significant differentiation detected in the COI and absent in the nDNA suggest that the divergence is recent, and detectable only by the faster evolving mtDNA. A within subgenus threshold of >2% may be more appropriate among sister taxa in cryptic anopheline complexes than the standard 3%. Differences in demographic history and climatic changes may have contributed to mtDNA lineage divergence in A. marajoara.

Renyi entropy and parity oscillations of anisotropic spin-s Heisenberg chains in a magnetic field

Using the density matrix renormalization group, we investigate the Renyi entropy of the anisotropic spin-s Heisenberg chains in a z-magnetic field. We considered the half-odd-integer spin-s chains, with s = 1/2, 3/2, and 5/2, and periodic and open boundary conditions. In the case of the spin-1/2 chain we were able to obtain accurate estimates of the new parity exponents p(alpha)((p)) and p(alpha)((o)) that gives the power-law decay of the oscillations of the alpha-Renyi entropy for periodic and open boundary conditions, respectively. We confirm the relations of these exponents with the Luttinger parameter K, as proposed by Calabrese et al. [Phys. Rev. Lett. 104, 095701 (2010)]. Moreover, the predicted periodicity of the oscillating term was also observed for some nonzero values of the magnetization m. We show that for s > 1/2 the amplitudes of the oscillations are quite small and get accurate estimates of p(alpha)((p)) and p(alpha)((o)) become a challenge. Although our estimates of the new universal exponents p(alpha)((p)) and p(alpha)((o)) for the spin-3/2 chain are not so accurate, they are consistent with the theoretical predictions.

Quantum system under the actions of two counteracting baths: A model for the attenuation-amplification interplay

We analyze the dynamical behavior of a quantum system under the actions of two counteracting baths: the inevitable energy draining reservoir and, in opposition, exciting the system, an engineered Glauber's amplifier. We follow the system dynamics towards equilibrium to map its distinctive behavior arising from the interplay of attenuation and amplification. Such a mapping, with the corresponding parameter regimes, is achieved by calculating the evolution of both the excitation and the Glauber-Sudarshan P function. Techniques to compute the decoherence and the fidelity of quantum states under the action of both counteracting baths, based on the Wigner function rather than the density matrix, are also presented. They enable us to analyze the similarity of the evolved state vector of the system with respect to the original one, for all regimes of parameters. Applications of this attenuation-amplification interplay are discussed.

Support vector machines for detecting age-related changes in running kinematics

Age-related changes in running kinematics have been reported in the literature using classical inferential statistics. However, this approach has been hampered by the increased number of biomechanical gait variables reported and subsequently the lack of differences presented in these studies. Data mining techniques have been applied in recent biomedical studies to solve this problem using a more general approach. In the present work, we re-analyzed lower extremity running kinematic data of 17 young and 17 elderly male runners using the Support Vector Machine (SVM) classification approach. In total, 31 kinematic variables were extracted to train the classification algorithm and test the generalized performance. The results revealed different accuracy rates across three different kernel methods adopted in the classifier, with the linear kernel performing the best. A subsequent forward feature selection algorithm demonstrated that with only six features, the linear kernel SVM achieved 100% classification performance rate, showing that these features provided powerful combined information to distinguish age groups. The results of the present work demonstrate potential in applying this approach to improve knowledge about the age-related differences in running gait biomechanics and encourages the use of the SVM in other clinical contexts. (C) 2010 Elsevier Ltd. All rights reserved.

On the use of Gram matrix in observability analysis

This letter presents some notes on the use of the Gram matrix in observability analysis. This matrix is constructed considering the rows of the measurement Jacobian matrix as vectors, and it can be employed in observability analysis and restoration methods. The determination of nonredundant pseudo-measurements (normally injections pseudo-measurements) for merging observable islands into an observable (single) system is carried out analyzing the pivots of the Gram matrix. The Gram matrix can also be used to verify local redundancy, which is important in measurement system planning. Some numerical examples` are used to illustrate these features. Others features of the Gram matrix are under study.

Dynamic Imaging in Electrical Impedance Tomography of the Human Chest With Online Transition Matrix Identification

One of the electrical impedance tomography objectives is to estimate the electrical resistivity distribution in a domain based only on electrical potential measurements at its boundary generated by an imposed electrical current distribution into the boundary. One of the methods used in dynamic estimation is the Kalman filter. In biomedical applications, the random walk model is frequently used as evolution model and, under this conditions, poor tracking ability of the extended Kalman filter (EKF) is achieved. An analytically developed evolution model is not feasible at this moment. The paper investigates the identification of the evolution model in parallel to the EKF and updating the evolution model with certain periodicity. The evolution model transition matrix is identified using the history of the estimated resistivity distribution obtained by a sensitivity matrix based algorithm and a Newton-Raphson algorithm. To numerically identify the linear evolution model, the Ibrahim time-domain method is used. The investigation is performed by numerical simulations of a domain with time-varying resistivity and by experimental data collected from the boundary of a human chest during normal breathing. The obtained dynamic resistivity values lie within the expected values for the tissues of a human chest. The EKF results suggest that the tracking ability is significantly improved with this approach.

On the Filtering Problem for Continuous-Time Markov Jump Linear Systems with no Observation of the Markov Chain

We consider in this paper the optimal stationary dynamic linear filtering problem for continuous-time linear systems subject to Markovian jumps in the parameters (LSMJP) and additive noise (Wiener process). It is assumed that only an output of the system is available and therefore the values of the jump parameter are not accessible. It is a well known fact that in this setting the optimal nonlinear filter is infinite dimensional, which makes the linear filtering a natural numerically, treatable choice. The goal is to design a dynamic linear filter such that the closed loop system is mean square stable and minimizes the stationary expected value of the mean square estimation error. It is shown that an explicit analytical solution to this optimal filtering problem is obtained from the stationary solution associated to a certain Riccati equation. It is also shown that the problem can be formulated using a linear matrix inequalities (LMI) approach, which can be extended to consider convex polytopic uncertainties on the parameters of the possible modes of operation of the system and on the transition rate matrix of the Markov process. As far as the authors are aware of this is the first time that this stationary filtering problem (exact and robust versions) for LSMJP with no knowledge of the Markov jump parameters is considered in the literature. Finally, we illustrate the results with an example.

Linear minimum mean square filter for discrete-time linear systems with Markov jumps and multiplicative noises

In this paper we obtain the linear minimum mean square estimator (LMMSE) for discrete-time linear systems subject to state and measurement multiplicative noises and Markov jumps on the parameters. It is assumed that the Markov chain is not available. By using geometric arguments we obtain a Kalman type filter conveniently implementable in a recurrence form. The stationary case is also studied and a proof for the convergence of the error covariance matrix of the LMMSE to a stationary value under the assumption of mean square stability of the system and ergodicity of the associated Markov chain is obtained. It is shown that there exists a unique positive semi-definite solution for the stationary Riccati-like filter equation and, moreover, this solution is the limit of the error covariance matrix of the LMMSE. The advantage of this scheme is that it is very easy to implement and all calculations can be performed offline. (c) 2011 Elsevier Ltd. All rights reserved.

Circulating matrix metalloproteinase-8 (MMP-8) and MMP-9 are increased in chronic periodontal disease and decrease after non-surgical periodontal therapy

Background: Periodontal disease shares risk factors with cardiovascular diseases and other systemic inflammatory diseases. The present study was designed to assess the circulating matrix metalloproteinases (MMPs) from chronic periodontal disease patients and, subsequently, after periodontal therapy. Methods: We compared the plasma concentrations of MMP-2. MMP-3, MMP-8, MMP-9, tissue inhibitor of metalloproteinase-1 (TIMP-1) and TIMP-2, and total gelatinolytic activity in patients with periodontal disease (n =28) with those of control subjects (n = 22) before and 3 months after non-surgical periodontal therapy. Results: Higher plasma MMP-3, MMP-8, and MMP-9 concentrations were found in periodontal disease patients compared with healthy controls (all P<0.05), whereas MMP-2, TIMP-1, and TIMP-2 levels were not different. Treatment decreased plasma MMP-8 and MMP-9 concentrations by 35% and 39%, respectively (both P<0.02), while no changes were found in controls. MMP-2, MMP-3, TIMP-1, and TIMP-2 remained unaltered in both groups. Plasma gelatinolytic activity was higher in periodontal disease patients compared with controls (P<0.001) and decreased after periodontal therapy (P<0.05). Conclusions: This study showed increased circulating MMP-8 and MMP-9 levels and proteolytic activity in periodontal disease patients that decrease after periodontal therapy. The effects of periodontal therapy suggest that it may attenuate inflammatory chronic diseases. (C) 2009 Published by Elsevier B.V.

Differences in both matrix metalloproteinase 9 concentration and zymographic profile between plasma and serum with clot activators are due to the presence of amorphous silica or silicate salts in blood collection devices

Matrix metalloproteinases (MMPs) are promising diagnostic tools, and blood sampling/handling alters MMP concentrations between plasma and serum and between serum with and without clot activators. To explain the higher MMP-9 expression in serum collected with clot accelerators relative to serum with no additives and to plasma, we analyzed the effects of increasing amounts of silica and silicates (components of clot activators) in,citrate plasma, serum, and huffy coats collected in both plastic and glass tubes from 50 healthy donors, and we analyzed the effects of silica and silicate on cultured leukemia cells. The levels of MMP-2 did not show significant changes between glass and plastic tubes, between serum and plasma, between serum with and without clot accelerators, or between silica and silicate treatments. No modification of MMP-9 expression was obtained by the addition of silica or silicate to previously separated plasma and serum. Increasing the amounts of nonsoluble silica and soluble silicate added to citrate and empty tubes prior to blood collection resulted in increasing levels of MMP-9 relative to citrate plasma and serum. Silica and silicate added to buffy coats and leukemia cells significantly induced MMP-9 release/secretion, demonstrating that both silica and silicate induce the release of pro- and complexed MMP-9 forms. We recommend limiting the misuse of serum and avoiding the interfering effects of clot activators. (c) 2007 Elsevier Inc. All rights reserved.

Prospects for control of African trypanosomiasis by tsetse vector manipulation

The extensive antigenic variation phenomena African trypanosomes display in their mammalian host have hampered efforts to develop effective vaccines against trypanosomiasis. Human disease management aims largely to treat infected hosts by chemotherapy, whereas control of animal diseases relies on reducing tsetse populations as well as on drug therapy. The control strategies for animal diseases are carried out and financed by livestock owners, who have an obvious economic incentive. Sustaining largely insecticide-based control at a local level and relying on drugs for treatment of infected hosts for a disease for which there is no evidence of acquired immunity could prove extremely costly in the long run. It is more likely that a combination of several methods in an integrated, phased and area-wide approach would be more effective in controlling these diseases and subsequently improving agricultural output. New approaches that are environmentally acceptable, efficacious and affordable are clearly desirable for control of various medically and agriculturally important insects including tsetse. Here, Serap Aksoy and colleagues discuss molecular genetic approaches to modulate tsetse vector competence.

Modification of arthropod vector competence via symbiotic bacteria

Some of the world's most devastating diseases are transmitted by arthropod vectors. Attempts to control these arthropods are currently being challenged by the widespread appearance of insecticide resistance. It is therefore desirable to develop alternative strategies to complement existing methods of vector control. In this review, Charles Beard, Scott O'Neill, Robert Tesh, Frank Richards and Serap Aksoy present an approach for introducing foreign genes into insects in order to confer refractoriness to vector populations, ie. the inability to transmit disease-causing agents. This approach aims to express foreign anti-parasitic or anti-viral gene products in symbiotic bacteria harbored by insects. The potential use of naturally occurring symbiont-based mechanisms in the spread of such refractory phenotypes is also discussed.

A framework for electricity price spike analysis with advanced data mining methods

There are many techniques for electricity market price forecasting. However, most of them are designed for expected price analysis rather than price spike forecasting. An effective method of predicting the occurrence of spikes has not yet been observed in the literature so far. In this paper, a data mining based approach is presented to give a reliable forecast of the occurrence of price spikes. Combined with the spike value prediction techniques developed by the same authors, the proposed approach aims at providing a comprehensive tool for price spike forecasting. In this paper, feature selection techniques are firstly described to identify the attributes relevant to the occurrence of spikes. A simple introduction to the classification techniques is given for completeness. Two algorithms: support vector machine and probability classifier are chosen to be the spike occurrence predictors and are discussed in details. Realistic market data are used to test the proposed model with promising results.