Influence of separate and mixed experimental designs on reaction times to two simple visual stimuli

Testing contexts have been shown to critically influence experimental results in psychophysical studies. One of these contexts that show important modulation of the behavioral effects of different stimulatory conditions is the separate (blocked) or mixed presentation of these stimulatory conditions. The study presents evidence that the apparent discriminabilities of two target stimuli can change according to which of these two testing contexts is used. A cross inside a ring and a vertical line inside a ring were presented as go stimuli in a go/no-go reaction time task. In one experiment, each of these stimuli was presented to a different group of volunteers and in another experiment they were presented to the same group of volunteers, randomly mixed in the blocks of trials. Similar reaction times were obtained for the two stimuli in the first experiment, and different reaction times (faster for the cross) in the second experiment. The latter result indicates that the two stimuli have different discriminabilities from the no-go stimulus; the cross having greater discriminability. This difference is however masked, presumably by the adoption of specific compensatory attentional sets, in a separate testing context.

Design, construction and evaluation of a simple pressurized solvent extraction system

This work describes the construction and testing of a simple pressurized solvent extraction (PSE) system. A mixture of acetone:water (80:20), 80 ºC and 103.5 bar, was used to extract two herbicides (Diuron and Bromacil) from a sample of polluted soil, followed by identification and quantification by high-performance liquid chromatography coupled with diode array detector (HPLC-DAD). The system was also used to extract soybean oil (70 ºC and 69 bar) using pentane. The extracted oil was weighed and characterized through the fatty acid methyl ester analysis (myristic (< 0.3%), palmitic (16.3%), stearic (2.8%), oleic (24.5%), linoleic (46.3%), linolenic (9.6%), araquidic (0.3%), gadoleic (< 0.3%), and behenic (0.3%) acids) using high-resolution gas chromatography with flame ionization detection (HRGC-FID). PSE results were compared with those obtained using classical procedures: Soxhlet extraction for the soybean oil and solid-liquid extraction followed by solid-phase extraction (SLE-SPE) for the herbicides. The results showed: 21.25 ± 0.36% (m/m) of oil in the soybeans using the PSE system and 21.55 ± 0.65% (m/m) using the soxhlet extraction system; extraction efficiency (recovery) of herbicides Diuron and Bromacil of 88.7 ± 4.5% and 106.6 ± 8.1%, respectively, using the PSE system, and 96.8 ± 1.0% and 94.2 ± 3.9%, respectively, with the SLP-SPE system; limit of detection (LOD) and limit of quantification (LOQ) for Diuron of 0.012 mg kg-1 and 0.040 mg kg-1, respectively; LOD and LOQ for Bromacil of 0.025 mg kg-1 and 0.083 mg kg-1, respectively. The linearity used ranged from 0.04 to 1.50 mg L-1 for Diuron and from 0.08 to 1.50 mg L-1 for Bromacil. In conclusion, using the PSE system, due to high pressure and temperature, it is possible to make efficient, fast extractions with reduced solvent consumption in an inert atmosphere, which prevents sample and analyte decomposition.

Evaluation of a simple hyphenated system for flow injection solid-phase pre-concentration and capillary electrophoresis

In this work, the development and evaluation of a hyphenated flow injection-capillary electrophoresis system with on-line pre-concentration is described. Preliminary tests were performed to investigate the influence of flow rates over the analytical signals. Results revealed losses in terms of sensitivity of the FIA-CE system when compared to the conventional CE system. To overcome signal decrease and to make the system more efficient, a lower flow rate was set and an anionic resin column was added to the flow manifold in order to pre-concentrate the analyte. The pre-concentration FIA-CE system presented a sensitivity improvement of about 660% and there was only a small increase of 8% in total peak dispersion. These results have confirmed the great potential of the proposed system for many analytical tasks especially for low concentration samples.

Development and validation of a simple and rapid capillary zone electrophoresis method for determination of nnrti nevirapine in pharmaceutical formulations

A simple and fast capillary zone electrophoresis (CZE) method has been developed and validated for quantification of a non-nucleoside reverse transcriptase inhibitor (NNRTI) nevirapine, in pharmaceuticals. The analysis was optimized using 10 mmol L-1 sodium phosphate buffer pH 2.5, +25 kV applied voltage, hydrodynamic injection 0.5 psi for 5 s and direct UV detection at 200 µm. Diazepam (50.0 µg mL-1) was used as internal standard. Under these conditions, nevirapine was analyzed in approximately less than 2.5 min. The analytical curve presented a coefficient of correlation of 0.9994. Limits of detection and quantification were 1.4 µg mL-1 and 4.3 µg mL-1, respectively. Intra- and inter-day precision expressed as relative standard deviations were 1.4% and 1.3%, respectively and the mean recovery was 100.81%. The active pharmaceutical ingredient was subjected to hydrolysis (acid, basic and neutral) and oxidative stress conditions. No interference of degradation products and tablet excipients were observed. This method showed to be rapid, simple, precise, accurate and economical for determination of nevirapine in pharmaceuticals and it is suitable for routine quality control analysis since CE offers benefits in terms of quicker method development and significantly reduced operating costs.

A simple procedure for reliability assessment of thin composite plates against buckling

In some circumstances ice floes may be modeled as beams. In general this modeling supposes constant thickness, which contradicts field observations. Action of currents, wind and the sequence of contacts, causes thickness to vary. Here this effect is taken into consideration on the modeling of the behavior of ice hitting inclined walls of offshore platforms. For this purpose, the boundary value problem is first equated. The set of equations so obtained is then transformed into a system of equations, that is then solved numerically. For this sake an implicit solution is developed, using a shooting method, with the accompanying Jacobian. In-plane coupling and the dependency of the boundary terms on deformation, make the problem non-linear and the development particular. Deformation and internal resultants are then computed for harmonic forms of beam profile. Forms of giving some additional generality to the problem are discussed.

In silico analysis of Simple Sequence Repeats from chloroplast genomes of Solanaceae species

The availaibilty of chloroplast genome (cpDNA) sequences of Atropa belladonna, Nicotiana sylvestris, N tabacum, N tomentosiformis, Solanum bulbocastanum, S lycopersicum and S tuberosum, which are Solanaceae species, allowed us to analyze the organization of cpSSRs in their genic and intergenic regions In general, the number of cpSSRs in cpDNA ranged from 161 in S tuberosum to 226 in N tabacum, and the number of intergenic cpSSRs was higher than genic cpSSRs The mononucleotide repeats were the most frequent in studied species, but we also identified di-, tri-, tetra-, penta- and hexanucleotide repeats Multiple alignments of all cpSSRs sequence from Solanaceae species made the identification of nucleotide variability possible and the phylogeny was estimated by maximum parsimony Our study showed that the plastome database can be exploited for phylogenetic analyses and biotechnological approaches

A Simple and Fast Method for the Production and Characterization of Methylic and Ethylic Biodiesels from Tucum Oil via an Alkaline Route

A simple, fast, and complete route for the production of methylic and ethylic biodiesel from tucum oil is described. Aliquots of the oil obtained directly from pressed tucum (pulp and almonds) were treated with potassium methoxide or ethoxide at 40 degrees C for 40 min. The biodiesel form was removed from the reactor and washed with 0.1 M HCl aqueous solution. A simple distillation at 100 degrees C was carried out in order to remove water and alcohol species from the biodiesel. The oxidative stability index was obtained for the tucum oil as well as the methylic and ethylic biodiesel at 6.13, 2.90, and 2.80 h, for storage times higher than 8 days. Quality control of the original oil and of the methylic and ethylic biodiesels, such as the amount of glycerin produced during the transesterification process, was accomplished by the TLC, GC-MS, and FT-IR techniques. The results obtained in this study indicate a potential biofuel production by simple treatment of tucum, an important Amazonian fruit.

Entanglement and classical instabilities: Fingerprints of electron-hole-to-exciton phase transition in a simple model

We propose a schematic model to study the formation of excitons in bilayer electron systems. The phase transition is signalized both in the quantum and classical versions of the model. In the present contribution we show that not only the quantum ground state but also higher energy states, up to the energy of the corresponding classical separatrix orbit, ""sense"" the transition. We also show two types of one-to-one correspondences in this system: On the one hand, between the changes in the degree of entanglement for these low-lying quantum states and the changes in the density of energy levels; on the other hand, between the variation in the expected number of excitons for a given quantum state and the behavior of the corresponding classical orbit.

High density flux of Co nanoparticles produced by a simple gas aggregation apparatus

Gas aggregation is a well known method used to produce clusters of different materials with good size control, reduced dispersion, and precise stoichiometry. The cost of these systems is relatively high and they are generally dedicated apparatuses. Furthermore, the usual sample production speed of these systems is not as fast as physical vapor deposition devices posing a problem when thick samples are needed. In this paper we describe the development of a multipurpose gas aggregation system constructed as an adaptation to a magnetron sputtering system. The cost of this adaptation is negligible and its installation and operation are both remarkably simple. The gas flow for flux in the range of 60-130 SCCM (SCCM denotes cubic centimeter per minute at STP) is able to completely collimate all the sputtered material, producing spherical nanoparticles. Co nanoparticles were produced and characterized using electron microscopy techniques and Rutherford back-scattering analysis. The size of the particles is around 10 nm with around 75 nm/min of deposition rate at the center of a Gaussian profile nanoparticle beam.

Simple analytic model for astrophysical S factors

We propose a physically transparent analytic model of astrophysical S factors as a function of a center-of-mass energy E of colliding nuclei (below and above the Coulomb barrier) for nonresonant fusion reactions. For any given reaction, the S(E) model contains four parameters [two of which approximate the barrier potential, U(r)]. They are easily interpolated along many reactions involving isotopes of the same elements; they give accurate practical expressions for S(E) with only several input parameters for many reactions. The model reproduces the suppression of S(E) at low energies (of astrophysical importance) due to the shape of the low-r wing of U(r). The model can be used to reconstruct U(r) from computed or measured S(E). For illustration, we parametrize our recent calculations of S(E) (using the Sao Paulo potential and the barrier penetration formalism) for 946 reactions involving stable and unstable isotopes of C, O, Ne, and Mg (with nine parameters for all reactions involving many isotopes of the same elements, e. g., C+O). In addition, we analyze astrophysically important (12)C+(12)C reaction, compare theoretical models with experimental data, and discuss the problem of interpolating reliably known S(E) values to low energies (E less than or similar to 2-3 MeV).

Green Chemistry-Sensitive Analytical Procedure for Photometric Determination of Orthophosphate in River and Tap Water by Use of a Simple LED-Based Photometer

In the current work a Green Analytical Chemistry (GAC) procedure for photometric determination of orthophosphate in river water at mu g L-1 concentration level is described. The flow system module and the LED-based photometer were assembled together to constitute a compact unit in order to allow that a flow cell with optical path-length of 100mm was coupled to them. The photometric procedure based on the molybdenum blue method was implemented employing the multicommuted flow injection analysis approach, which provided facilities to allow reduction of reagent consumption and as well as waste generation. Aiming to prove the usefulness of the system, orthophosphate in river and tap waters was determined. Accuracy was ascertained by spiking samples with orthophosphate solution yielding recoveries ranging from 96% up to 107%. Other profitable features such as a wide linear response range between 10 to 800 mu g L-1 [image omitted]; a detection limit (3 sigma criterion) of 2.4 mu g L-1 [image omitted]; a relative standard deviation (n=7) of 2% using a typical water sample with concentration of 120 mu g L-1 [image omitted]; reagent consumption of 3.0mg ammonium molybdate, 0.3mg hydrazine sulfate, and 0.03mg stannous chloride per determination; a waste generation of 2.4mL per determination; and a sampling throughput of 20 determination per hours were also achieved.

Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study

Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

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.

Normal Versus Pathological Voice Signals Using Wavelet Analysis and Least Squares Support-Vector Machines

State of Sao Paulo Research Foundation (FAPESP)

Remote control of CNC machines using the CyberOPC communication system over public networks

During the last few years, the evolution of fieldbus and computers networks allowed the integration of different communication systems involving both production single cells and production cells, as well as other systems for business intelligence, supervision and control. Several well-adopted communication technologies exist today for public and non-public networks. Since most of the industrial applications are time-critical, the requirements of communication systems for remote control differ from common applications for computer networks accessing the Internet, such as Web, e-mail and file transfer. The solution proposed and outlined in this work is called CyberOPC. It includes the study and the implementation of a new open communication system for remote control of industrial CNC machines, making the transmission delay for time-critical control data shorter than other OPC-based solutions, and fulfilling cyber security requirements.