Rapid assays for detection of glyphosate-resistant Lolium spp.

Diagnosing herbicide-resistant weed populations is the first step for herbicide resistance management. Monitoring the nature, distribution, and abundance of the resistant plants in fields demands efficient and effective screening tests. Different glyphosate resistant populations of Lolium multiflorum (VA) and L. rigidum (C) were used in assays for testing their effectiveness to detect herbicide resistance. According to a Petri dish bioassay 7 days after treatment (DAT), the VA and the C populations were 27 and 31 times more resistant to glyphosate than the susceptible populations, L. multiflorum (SM) and L. rigidum (SR), respectively. On a whole-plant bioassay (21 DAT), the VA and the C populations were 6 and 11 times more resistant to glyphosate than their respective susceptible populations. The susceptible populations accumulated 2.5 and 1.4-fold more shikimic acid 48 hours after treatment (HAT), than the resistant VA and C. Glyphosate gradually inhibited net photosynthesis in all populations but at 48-72 HAT the resistant plants recovered, whereas no recovery was detected in susceptible populations. All assays were capable of detecting the resistant populations and this may be useful for farmers and consultants as an effective tool to reduce the spread of the resistant populations through quicker implementation of alternative weed management practices. However, they differed in time, costs and equipments necessaries for successfully carrying on the tests. Regarding costs, the cheapest ones were Petri dish and whole-plant bioassays, but they are time-consuming methods as the major constraints are the collection of seeds from the field and at least some weeks to evaluate the resistance. The shikimic acid and net photosynthesis assays were the quickest ones but they demand sophisticated equipments which could restrict its use.

A Nonstationary Model of Newborn EEG

The detection of seizure in the newborn is a critical aspect of neurological research. Current automatic detection techniques are difficult to assess due to the problems associated with acquiring and labelling newborn electroencephalogram (EEG) data. A realistic model for newborn EEG would allow confident development, assessment and comparison of these detection techniques. This paper presents a model for newborn EEG that accounts for its self-similar and non-stationary nature. The model consists of background and seizure sub-models. The newborn EEG background model is based on the short-time power spectrum with a time-varying power law. The relationship between the fractal dimension and the power law of a power spectrum is utilized for accurate estimation of the short-time power law exponent. The newborn EEG seizure model is based on a well-known time-frequency signal model. This model addresses all significant time-frequency characteristics of newborn EEG seizure which include; multiple components or harmonics, piecewise linear instantaneous frequency laws and harmonic amplitude modulation. Estimates of the parameters of both models are shown to be random and are modelled using the data from a total of 500 background epochs and 204 seizure epochs. The newborn EEG background and seizure models are validated against real newborn EEG data using the correlation coefficient. The results show that the output of the proposed models has a higher correlation with real newborn EEG than currently accepted models (a 10% and 38% improvement for background and seizure models, respectively).

A matching pursuit-based signal complexity measure for the analysis of newborn EEG

This paper presents a new relative measure of signal complexity, referred to here as relative structural complexity, which is based on the matching pursuit (MP) decomposition. By relative, we refer to the fact that this new measure is highly dependent on the decomposition dictionary used by MP. The structural part of the definition points to the fact that this new measure is related to the structure, or composition, of the signal under analysis. After a formal definition, the proposed relative structural complexity measure is used in the analysis of newborn EEG. To do this, firstly, a time-frequency (TF) decomposition dictionary is specifically designed to compactly represent the newborn EEG seizure state using MP. We then show, through the analysis of synthetic and real newborn EEG data, that the relative structural complexity measure can indicate changes in EEG structure as it transitions between the two EEG states; namely seizure and background (non-seizure).

Quantitative PCR-ELAHA for the determination of retroviral vector transduction efficiency

Current methods to detect transduction efficiency during the routine use of integrating retroviral vectors in gene therapy applications may require the use of radioactivity and usually rely upon subjective determination of the results. We have developed two competitive quantitative assays that use an enzyme-linked, amplicon hybridization assay (ELAHA) to detect the products of PCR-amplified regions of transgene from cells transduced with Moloney murine leukemia virus vectors. The quantitative assays (PCR-ELAHA) proved to be simple, rapid, and sensitive, avoiding the need for Southern hybridization, complex histochemical stains, or often subjective and time-consuming tissue culture and immunofluorescence assays. The PCR-ELAHA systems can rapidly detect proviral DNA from any retroviral vector carrying the common selective and marker genes neomycin phosphotransferase and green fluorescent protein, and the methods described are equally applicable to other sequences of interest, providing a cheaper alternative to the evolving real-time PCR methods. The results revealed the number of copies of retrovector provirus present per stably transduced cell using vectors containing either one or both qPCR targets.

Chebyshev real wave packet propagation: H+O-2 (J=0) state-to-state reactive scattering calculations

In this paper we explore the relative performance of two recently developed wave packet methodologies for reactive scattering, namely the real wave packet Chebyshev domain propagation of Gray and Balint-Kurti [J. Chem. Phys. 108, 950 (1998)] and the Lanczos subspace wave packet approach of Smith [J. Chem. Phys. 116, 2354 (2002); Chem. Phys. Lett. 336, 149 (2001)]. In the former method, a modified Schrodinger equation is employed to propagate the real part of the wave packet via the well-known Chebyshev iteration. While the time-dependent wave packet from the modified Schrodinger equation is different from that obtained using the standard Schrodinger equation, time-to-energy Fourier transformation yields wave functions which differ only trivially by normalization. In the Lanczos subspace approach the linear system of equations defining the action of the Green operator may be solved via either time-dependent or time-independent methods, both of which are extremely efficient due to the simple tridiagonal structure of the Hamiltonian in the Lanczos representation. The two different wave packet methods are applied to three dimensional reactive scattering of H+O-2 (total J=0). State-to-state reaction probabilities, product state distributions, as well as initial-state-resolved cumulative reaction probabilities are examined. (C) 2002 American Institute of Physics.

The impact of Sinogram-Affirmed Iterative Reconstruction on patient dose and image quality compared to filtered back projection: a narrative review

Objective: Summarize all relevant findings in published literature regarding the potential dose reduction related to image quality using Sinogram-Affirmed Iterative Reconstruction (SAFIRE) compared to Filtered Back Projection (FBP). Background: Computed Tomography (CT) is one of the most used radiographic modalities in clinical practice providing high spatial and contrast resolution. However it also delivers a relatively high radiation dose to the patient. Reconstructing raw-data using Iterative Reconstruction (IR) algorithms has the potential to iteratively reduce image noise while maintaining or improving image quality of low dose standard FBP reconstructions. Nevertheless, long reconstruction times made IR unpractical for clinical use until recently. Siemens Medical developed a new IR algorithm called SAFIRE, which uses up to 5 different strength levels, and poses an alternative to the conventional IR with a significant reconstruction time reduction. Methods: MEDLINE, ScienceDirect and CINAHL databases were used for gathering literature. Eleven articles were included in this review (from 2012 to July 2014). Discussion: This narrative review summarizes the results of eleven articles (using studies on both patients and phantoms) and describes SAFIRE strengths for noise reduction in low dose acquisitions while providing acceptable image quality. Conclusion: Even though the results differ slightly, the literature gathered for this review suggests that the dose in current CT protocols can be reduced at least 50% while maintaining or improving image quality. There is however a lack of literature concerning paediatric population (with increased radiation sensitivity). Further studies should also assess the impact of SAFIRE on diagnostic accuracy.

Velocity estimation of moving ships using C-band SLC SAR data

A new algorithm for the velocity vector estimation of moving ships using Single Look Complex (SLC) SAR data in strip map acquisition mode is proposed. The algorithm exploits both amplitude and phase information of the Doppler decompressed data spectrum, with the aim to estimate both the azimuth antenna pattern and the backscattering coefficient as function of the look angle. The antenna pattern estimation provides information about the target velocity; the backscattering coefficient can be used for vessel classification. The range velocity is retrieved in the slow time frequency domain by estimating the antenna pattern effects induced by the target motion, while the azimuth velocity is calculated by the estimated range velocity and the ship orientation. Finally, the algorithm is tested on simulated SAR SLC data.

Reducing the number of membership functions in linguistic variables

Dissertation presented at Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia in fulfilment of the requirements for the Masters degree in Mathematics and Applications, specialization in Actuarial Sciences, Statistics and Operations Research

The impact of pharmaceutical policy measures: a structural-break approach

Pharmaceutical spending in many other countries has had a steep increase in the last decade. The Portuguese Government has adopted several measures to reduce pharmaceutical expenditure growth, ranging from increased co-payments to price decreases determined administratively. Promotion of generic consumption has also ranked high in political priorities. We assess the overall impact of the several policy measures on total pharmaceutical spending, using monthly data over the period January 1995 – August 2008. Endogenous structural breaks (time-series) methods were employed. Our findings suggest that policy measures aimed at controlling pharmaceutical expenditure have been, in general, unsuccessful. Two breaks were identified. Both coincide with administratively determined price decreases. Measures aimed at increasing competition in the market had no visible effect on the dynamics of Government spending in pharmaceutical products. In particular, the introduction of reference pricing had only a transitory effect of less than one year, with historical growth resuming quickly. The consequence of it is a transfer of financial burden from the Government to the patients, with no apparent effect on the dynamics of pharmaceutical spending. This strongly suggests that pharmaceutical companies have been able to adjust to policy measures, in order to sustain their sales. It remains a challenge for the future to identify firms’ strategies that supported continued growth of sales, despite the several policy measures adop

Visualizing control systems performance: A fractional perspective

This article presents a novel method for visualizing the control systems behavior. The proposed scheme uses the tools of fractional calculus and computes the signals propagating within the system structure as a time/frequency-space wave. Linear and nonlinear closed-loop control systems are analyzed, for both the time and frequency responses, under the action of a reference step input signal. Several nonlinearities, namely, Coulomb friction and backlash, are also tested. The numerical experiments demonstrate the feasibility of the proposed methodology as a visualization tool and motivate its extension for other systems and classes of nonlinearities.

Adaptive modeling and high quality spectral estimation for speech enhancement

In this work an adaptive modeling and spectral estimation scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for speech enhancement. Both speech and noise signals are modeled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. The model parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The speech enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. This approach is particularly useful as a pre-processing module for parametric based speech recognition systems that rely on spectral time dependent models. The system performance has been evaluated by a set of human listeners and by spectral distances. In both cases the use of this pre-processing module has led to improved results.

Kalman tracking linear predictor for vowel intelligibility enhancement on european portuguese HMM based speech synthesis

The recent developments on Hidden Markov Models (HMM) based speech synthesis showed that this is a promising technology fully capable of competing with other established techniques. However some issues still lack a solution. Several authors report an over-smoothing phenomenon on both time and frequencies which decreases naturalness and sometimes intelligibility. In this work we present a new vowel intelligibility enhancement algorithm that uses a discrete Kalman filter (DKF) for tracking frame based parameters. The inter-frame correlations are modelled by an autoregressive structure which provides an underlying time frame dependency and can improve time-frequency resolution. The system’s performance has been evaluated using objective and subjective tests and the proposed methodology has led to improved results.

Adaptive filtering for high quality HMM based speech synthesis

In this work an adaptive filtering scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for Hidden Markov Model (HMM) based speech synthesis quality enhancement. The objective is to improve signal smoothness across HMMs and their related states and to reduce artifacts due to acoustic model's limitations. Both speech and artifacts are modelled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. Themodel parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The quality enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. The system's performance has been evaluated using mean opinion score tests and the proposed technique has led to improved results.

Aminobenzocoumarinylmehtyl esters as photoactive precursors for the release of butyric acid

The evaluation of the photorelease of a carboxylic acid drug, using butyric acid as a representative model, was carried out by using 7-amino-4-chloromethyl-2-oxo-2Hnaphtho[1,2-b] pyran, an aminobenzocoumarin, and its mono- and di-methylated or ethylated derivatives. This study was intended to improve the release of butyric acid from benzocoumarins by the addition of an amino group to the heterocycle by applying the knowledge of second-generation coumarinylmethyl-based photoremovable protecting groups. Photolysis studies were performed on the resultant ester cages by irradiation in a photochemical reactor at 254, 300, 350 and 419 nm, using methanol/HEPES buffer 80:20 solutions as solvent. The data obtained showed that these new fluorescent aminobenzocoumarins are superior to all the previously tested benzocoumarins with the same or different ring fusions. As well as the photolysis, the photophysics of the compounds were characterised by both steady state and time-resolved methods.

Photoactivation of butyric acid from 6-aminobenzocoumarin cages

A new benzocoumarin bearing an amino group is proposed as a photocleavable protecting group for carboxylic acids. The novel heterocycle, 6-amino-4-chloromethyl-2-oxo-2H-naphtho[1,2-b]pyran was used in the preparation of ester conjugates of butyric acid, and of the corresponding mono- and di-methylated or ethylated derivatives. The photolability of the ester conjugates was studied by irradiation at selected wavelengths in methanol/HEPES buffer (80:20) solutions, and the release of butyric acid was followed with HPLC/UV and 1H NMR monitoring. Release of the carboxylic acid was faster for the monoalkylated derivatives (approximately within 20 min), at the longer wavelengths of irradiation (350 and 419 nm). The photophysics of the heterocyclic conjugates was also evaluated by both steady state and time-resolved methods.