Analysis of simple hardware efficiency for temperature measurement in agriculture and environment

This work focuses basically on the design and analysis of simple and low cost hardware systems efficiency for temperature measurement in agricultural area. The main objective is to prove quantitatively, through statistical data analysis, to what extent a simple hardware designed with inexpensive components can be used safely in the indoor temperature measurement in farm buildings, such as greenhouses, warehouse or silos. To verify the of simple hardware efficiency, its data were compared with data from measurements with a high performance LabVIEW platform. This work proved that a simple hardware based on a microcontroller and the LM35 sensor can perform well. It presented a good accuracy but a relatively low precision that can be improved when performed some consecutive signal sampling and then used its average value. Although there are many papers that explain these components, this work has the distinction of presenting a data analysis in numerical form and using high performance systems to ensure critical data comparison.

Predicting Accurate and Actionable Static Analysis Warnings: An Experimental Approach

Static analysis tools report software defects that may or may not be detected by other verification methods. Two challenges complicating the adoption of these tools are spurious false positive warnings and legitimate warnings that are not acted on. This paper reports automated support to help address these challenges using logistic regression models that predict the foregoing types of warnings from signals in the warnings and implicated code. Because examining many potential signaling factors in large software development settings can be expensive, we use a screening methodology to quickly discard factors with low predictive power and cost-effectively build predictive models. Our empirical evaluation indicates that these models can achieve high accuracy in predicting accurate and actionable static analysis warnings, and suggests that the models are competitive with alternative models built without screening.

MATERIAL MODELING AND ANALYSIS FOR THE DEVELOPMENT OF A REALISTIC BLAST HEADFORM

Blast traumatic brain injury (BTBI) has become an important topic of study because of the increase of such incidents, especially due to the recent growth of improvised explosive devices (IEDs). This thesis discusses a project in which laboratory testing of BTBI was made possible by performing blast loading on experimental models simulating the human head. Three versions of experimental models were prepared – one having a simple geometry and the other two having geometry similar to a human head. For developing the head models, three important parts of the head were considered for material modeling and analysis – the skin, skull and brain. The materials simulating skin, skull and brain went through many testing procedures including dynamic mechanical analysis (DMA). For finding a suitable brain simulant, several materials were tested under low and high frequencies. Step response analysis, rheometry and DMA tests were performed on materials such as water based gels, oil based mixtures and silicone gels cured at different temperatures. The gelatins and silicone gels showed promising results toward their use as brain surrogate materials. Temperature degradation tests were performed on gelatins, indicating the fast degradation of gelatins at room temperature. Silicone gels were much more stable compared to the water based gels. Silicone gels were further processed using a thinner-type additive gel to bring the dynamic modulus values closer to those of human brain matter. The obtained values from DMA were compared to the values for human brain as found in literature. Then a silicone rubber brain mold was prepared to give the brain model accurate geometry. All the components were put together to make the entire head model. A steel mount was prepared to attach the head for testing at the end of the shock tube. Instrumentation was implemented in the head model to obtain effective results for understanding more about the possible mechanisms of BTBI. The final head model was named the Realistic Explosive Dummy Head or the “RED Head.” The RED Head offered potential for realistic experimental testing in blast loading conditions by virtue of its material properties and geometrical accuracy.

Complex networks analysis of language complexity

Methods from statistical physics, such as those involving complex networks, have been increasingly used in the quantitative analysis of linguistic phenomena. In this paper, we represented pieces of text with different levels of simplification in co-occurrence networks and found that topological regularity correlated negatively with textual complexity. Furthermore, in less complex texts the distance between concepts, represented as nodes, tended to decrease. The complex networks metrics were treated with multivariate pattern recognition techniques, which allowed us to distinguish between original texts and their simplified versions. For each original text, two simplified versions were generated manually with increasing number of simplification operations. As expected, distinction was easier for the strongly simplified versions, where the most relevant metrics were node strength, shortest paths and diversity. Also, the discrimination of complex texts was improved with higher hierarchical network metrics, thus pointing to the usefulness of considering wider contexts around the concepts. Though the accuracy rate in the distinction was not as high as in methods using deep linguistic knowledge, the complex network approach is still useful for a rapid screening of texts whenever assessing complexity is essential to guarantee accessibility to readers with limited reading ability. Copyright (c) EPLA, 2012

Evaluation of comprehensive two-dimensional gas chromatography coupled to rapid scanning quadrupole mass spectrometry for quantitative analysis

Comprehensive two-dimensional gas chromatography (GC x GC) is a powerful technique that provides excellent separation and identification of analytes in highly complex samples with considerable increase in GC peak capacities. However, since second dimension analyses are very fast, detectors with a rapid acquisition rate are required. Over the last years, quite a number of studies have discussed the potential and limitations of the combination GC x GC with a variety of quadrupole mass spectrometers. The present research focuses on the evaluation of qMS effectiveness at a 10,000-amu/s scan speed and 20-Hz scan frequency for the identification (full scan mode acquisition-TIC) and quantification (extracted ion chromatogram) of target pesticide residues in tomato samples. The following MS parameters have been evaluated: number of data points per peak, mass spectrum quality, peak skewing, and sensitivity. The validated proposed GC x GC/qMS method presented satisfactory results in terms of repeatability (coefficient of variation lower than 15%), accuracy (84-117%), and linearity (ranging from 25 to 500 ng/g), while significant enhancement in sensitivity was observed (a factor of around 10) under scan conditions. (C) 2012 Elsevier B.V. All rights reserved.

Analysis of noise in aircraft cabins through the VHF channel

Purpose - The purpose of this paper is to present a method to analyze the noise in aircraft cabins through the VHF Aeronautical Communication Channel, aimed at examining an environment that has the possibility of communication problems between the aircraft crew and the professionals responsible for the controls on land. Design/methodology/approach - This analysis includes equipment normally used for identification and comparison of electromagnetic noise, the cabin and the environment that are present in an airport, as well as equipment for frequency analysis and intensity of those signals. The analysis is done in a reverse way, eliminating situations that are not common in the examined environment, until the identification of the situation with the irregularity. Findings - According to the results, the implementation of the Fourier transform for noise analysis in the cabin was efficient. These results demonstrate that through this transformation, the noise sources can be identified in the environments in cases where there is much spectrum pollution. Research limitations/implications - This kind of noise analysis is important, considering the importance of having good accuracy in airport environment analysis. Originality/value - The paper presents the main trends in the future of aviation communications, and describes the new applications that aim to minimize problems with the current VHF channel.

Hypotheses, rationale, design, and methods for prognostic evaluation of cardiac biomarker elevation after percutaneous and surgical revascularization in the absence of manifest myocardial infarction. A comparative analysis of biomarkers and cardiac magnetic resonance. The MASS-V Trial

Background: Although the release of cardiac biomarkers after percutaneous (PCI) or surgical revascularization (CABG) is common, its prognostic significance is not known. Questions remain about the mechanisms and degree of correlation between the release, the volume of myocardial tissue loss, and the long-term significance. Delayed-enhancement of cardiac magnetic resonance (CMR) consistently quantifies areas of irreversible myocardial injury. To investigate the quantitative relationship between irreversible injury and cardiac biomarkers, we will evaluate the extent of irreversible injury in patients undergoing PCI and CABG and relate it to postprocedural modifications in cardiac biomarkers and long-term prognosis. Methods/Design: The study will include 150 patients with multivessel coronary artery disease (CAD) with left ventricle ejection fraction (LVEF) and a formal indication for CABG; 50 patients will undergo CABG with cardiopulmonary bypass (CPB); 50 patients with the same arterial and ventricular condition indicated for myocardial revascularization will undergo CABG without CPB; and another 50 patients with CAD and preserved ventricular function will undergo PCI using stents. All patients will undergo CMR before and after surgery or PCI. We will also evaluate the release of cardiac markers of necrosis immediately before and after each procedure. Primary outcome considered is overall death in a 5-year follow-up. Secondary outcomes are levels of CK-MB isoenzyme and I-Troponin in association with presence of myocardial fibrosis and systolic left ventricle dysfunction assessed by CMR. Discussion: The MASS-V Trial aims to establish reliable values for parameters of enzyme markers of myocardial necrosis in the absence of manifest myocardial infarction after mechanical interventions. The establishments of these indices have diagnostic value and clinical prognosis and therefore require relevant and different therapeutic measures. In daily practice, the inappropriate use of these necrosis markers has led to misdiagnosis and therefore wrong treatment. The appearance of a more sensitive tool such as CMR provides an unprecedented diagnostic accuracy of myocardial damage when correlated with necrosis enzyme markers. We aim to correlate laboratory data with imaging, thereby establishing more refined data on the presence or absence of irreversible myocardial injury after the procedure, either percutaneous or surgical, and this, with or without the use of cardiopulmonary bypass.

Flow injection analysis of free glycerol in biodiesel using a copper electrode as an amperometric detector

The main goal of this work was to develop a simple analytical method for quantification of glycerol based on the electrocatalytic oxidation of glycerol on the copper surface adapted in a flow injection system. Under optimal experimental conditions, the peak current response increases linearly with glycerol concentration over the range 60-3200 mg kg(-1) (equivalent to 3-160 mg L(-1) in solution). The repeatability of the electrode response in the flow injection analysis (FIA) configuration was evaluated as 5% (n = 10), and the detection limit of the method was estimated to be 5 mg kg(-1) in biodiesel (equivalent to 250 mu g L(-1) in solution) (S/N = 3). The sample throughput under optimised conditions was estimated to be 90 h(-1). Different types of biodiesel samples (B100), as in the types of vegetable oils or animal fats used to produce the fuels, were analysed (seven samples). The only sample pre-treatment used was an extraction of glycerol from the biodiesel sample containing a ratio of 5 mL of water to 250 mg of biodiesel. The proposed method improves the analytical parameters obtained by other electroanalytical methods for quantification of glycerol in biodiesel samples, and its accuracy was evaluated using a spike-and-recovery assay, where all the biodiesel samples used obtained admissible values according to the Association of Official Analytical Chemists. Crown Copyright (C) 2011 Published by Elsevier Ltd. All rights reserved.

Automated analysis of lidocaine and its metabolite in plasma by in-tube solid-phase microextraction coupled with LC-UV for pharmacokinetic study

A sensitive, selective, and reproducible in-tube solid-phase microextraction and liquid chromatographic (in-tube SPME/LC-UV) method for determination of lidocaine and its metabolite monoethylglycinexylidide (MEGX) in human plasma has been developed, validated, and further applied to pharmacokinetic study in pregnant women with gestational diabetes mellitus (GDM) subjected to epidural anesthesia. Important factors in the optimization of in-tube SPME performance are discussed, including the draw/eject sample volume, draw/eject cycle number, draw/eject flow rate, sample pH, and influence of plasma proteins. The limits of quantification of the in-tube SPME/LC method were 50 ng/mL for both metabolite and lidocaine. The interday and intraday precision had coefficients of variation lower than 8%, and accuracy ranged from 95 to 117%. The response of the in-tube SPME/LC method for analytes was linear over a dynamic range from 50 to 5000 ng/mL, with correlation coefficients higher than 0.9976. The developed in-tube SPME/LC method was successfully used to analyze lidocaine and its metabolite in plasma samples from pregnant women with GDM subjected to epidural anesthesia for pharmacokinetic study.

Assessment of the stereoselective fungal biotransformation of albendazole and its analysis by HPLC in polar organic mode

A high-performance liquid chromatographic method using polar organic mode was developed to analyze albendazole (ABZ), albendazole sulfone (ABZSO(2)) and the chiral and active metabolite albendazole sulfoxide (ABZSOX, ricobendazole) that was further applied in stereoselective fungal biotransformation studies. The chromatographic separation was performed on a Chiralpak AS column using acetonitrile:ethanol (97:3, v/v) plus 0.2% triethylamine and 0.2% acetic acid as the mobile phase at a flow rate of 0.5 mL min(-1). The present study employed hollow fiber liquid-phase microextraction as sample preparation. The method showed to be linear over the concentration range of 25-5000 ng mL(-1) for each ABZSOX enantiomer, 200-10,000 ng mL(-1) for ABZ and 50-1000 ng mL(-1) for ABZSO(2) metabolite with correlation coefficient (r)> 0.9934. The mean recoveries for ABZ, rac-ABZSOX and ABZSO(2) were, respectively, 9%, 33% and 20% with relative standard deviation below 10%. Within-day and between-day precision and accuracy assays for these analytes were studied at three concentration levels and were lower than 15%. This study opens the door regarding the possibility of using fungi in obtaining of the active metabolite ricobendazole. Nigrospora sphaerica (Sacc.) E. W. Mason (5567), Pestalotiopsis foedans (VR8), Papulaspora immersa Hotson (SS13) and Mucor rouxii were able to stereoselectively metabolize ABZ into its chiral metabolite. Among them, the fungus Mucor rouxii was the most efficient in the production of (+)-ABZSOX. (C) 2011 Elsevier B.V. All rights reserved.

rpb2 is a reliable reference gene for quantitative gene expression analysis in the dermatophyte Trichophyton rubrum

The selection of reference genes used for data normalization to quantify gene expression by real-time PCR amplifications (qRT-PCR) is crucial for the accuracy of this technique. In spite of this, little information regarding such genes for qRT-PCR is available for gene expression analyses in pathogenic fungi. Thus, we investigated the suitability of eight candidate reference genes in isolates of the human dermatophyte Trichophyton rubrum subjected to several environmental challenges, such as drug exposure, interaction with human nail and skin, and heat stress. The stability of these genes was determined by geNorm, NormFinder and Best-Keeper programs. The gene with the most stable expression in the majority of the conditions tested was rpb2 (DNA-dependent RNA polymerase II), which was validated in three T. rubrum strains. Moreover, the combination of rpb2 and chs1 (chitin synthase) genes provided for the most reliable qRT-PCR data normalization in T. rubrum under a broad range of biological conditions. To the best of our knowledge this is the first report on the selection of reference genes for qRT-PCR data normalization in dermatophytes and the results of these studies should permit further analysis of gene expression under several experimental conditions, with improved accuracy and reliability.

Discrimination of Basal Cell Carcinoma and Melanoma from Normal Skin Biopsies in Vitro Through Raman Spectroscopy and Principal Component Analysis

Objective: Raman spectroscopy has been employed to discriminate between malignant (basal cell carcinoma [BCC] and melanoma [MEL]) and normal (N) skin tissues in vitro, aimed at developing a method for cancer diagnosis. Background data: Raman spectroscopy is an analytical tool that could be used to diagnose skin cancer rapidly and noninvasively. Methods: Skin biopsy fragments of similar to 2 mm(2) from excisional surgeries were scanned through a Raman spectrometer (830 nm excitation wavelength, 50 to 200 mW of power, and 20 sec exposure time) coupled to a fiber optic Raman probe. Principal component analysis (PCA) and Euclidean distance were employed to develop a discrimination model to classify samples according to histopathology. In this model, we used a set of 145 spectra from N (30 spectra), BCC (96 spectra), and MEL (19 spectra) skin tissues. Results: We demonstrated that principal components (PCs) 1 to 4 accounted for 95.4% of all spectral variation. These PCs have been spectrally correlated to the biochemicals present in tissues, such as proteins, lipids, and melanin. The scores of PC2 and PC3 revealed statistically significant differences among N, BCC, and MEL (ANOVA, p < 0.05) and were used in the discrimination model. A total of 28 out of 30 spectra were correctly diagnosed as N, 93 out of 96 as BCC, and 13 out of 19 as MEL, with an overall accuracy of 92.4%. Conclusions: This discrimination model based on PCA and Euclidean distance could differentiate N from malignant (BCC and MEL) with high sensitivity and specificity.

A LED Based Photometer for Solid Phase Photometry: Zinc Determination in Pharmaceutical Preparation Employing a Multicommuted Flow Analysis Approach

In this work, a LED (light emitting diode) based photometer for solid phase photometry is described. The photometer was designed to permit direct coupling of a light source (LED) and a photodiode to a flow cell with an optical pathlength of 4 mm. The flow cell was filled with adsorbing solid phase material (C-18), which was used to immobilize the chromogenic reagent 1-(2-thiazolylazo)-2-naphthol (TAN). Aiming to allow accuracy assessment, samples were also analyzed employing ICP OES (inductively coupled plasma optical emission spectrometry) methodology. Applying the paired t-test at the 95% confidence level, no significant difference was observed. Other useful features were also achieved: linear response ranging from 0.05 to 0.85 mg L-1 Zn, limit of detection of 9 mu g L-1 Zn (3 sigma criterion), standard deviation of 1.4% (n = 10), sampling throughput of 36 determinations per h, and a waste generation and reagent consumption of 1.7 mL and of 0.03 mu g per determination, respectively.

Texture analysis of high resolution MRI allows discrimination between febrile and afebrile initial precipitating injury in mesial temporal sclerosis

A computational pipeline combining texture analysis and pattern classification algorithms was developed for investigating associations between high-resolution MRI features and histological data. This methodology was tested in the study of dentate gyrus images of sclerotic hippocampi resected from refractory epilepsy patients. Images were acquired using a simple surface coil in a 3.0T MRI scanner. All specimens were subsequently submitted to histological semiquantitative evaluation. The computational pipeline was applied for classifying pixels according to: a) dentate gyrus histological parameters and b) patients' febrile or afebrile initial precipitating insult history. The pipeline results for febrile and afebrile patients achieved 70% classification accuracy, with 78% sensitivity and 80% specificity [area under the reader observer characteristics (ROC) curve: 0.89]. The analysis of the histological data alone was not sufficient to achieve significant power to separate febrile and afebrile groups. Interesting enough, the results from our approach did not show significant correlation with histological parameters (which per se were not enough to classify patient groups). These results showed the potential of adding computational texture analysis together with classification methods for detecting subtle MRI signal differences, a method sufficient to provide good clinical classification. A wide range of applications of this pipeline can also be used in other areas of medical imaging. Magn Reson Med, 2012. (c) 2012 Wiley Periodicals, Inc.

EEG amplitude modulation analysis for semi-automated diagnosis of Alzheimer's disease

Recent experimental evidence has suggested a neuromodulatory deficit in Alzheimer's disease (AD). In this paper, we present a new electroencephalogram (EEG) based metric to quantitatively characterize neuromodulatory activity. More specifically, the short-term EEG amplitude modulation rate-of-change (i.e., modulation frequency) is computed for five EEG subband signals. To test the performance of the proposed metric, a classification task was performed on a database of 32 participants partitioned into three groups of approximately equal size: healthy controls, patients diagnosed with mild AD, and those with moderate-to-severe AD. To gauge the benefits of the proposed metric, performance results were compared with those obtained using EEG spectral peak parameters which were recently shown to outperform other conventional EEG measures. Using a simple feature selection algorithm based on area-under-the-curve maximization and a support vector machine classifier, the proposed parameters resulted in accuracy gains, relative to spectral peak parameters, of 21.3% when discriminating between the three groups and by 50% when mild and moderate-to-severe groups were merged into one. The preliminary findings reported herein provide promising insights that automated tools may be developed to assist physicians in very early diagnosis of AD as well as provide researchers with a tool to automatically characterize cross-frequency interactions and their changes with disease.