Pre-harvest cane burning and health: the association between school absences and burning sugarcane fields

The objective of this study was to investigate an association between pre-harvest sugarcane burning and respiratory diseases in children under five years of age. The following data were collected in five schools in the city of Araraquara, SP, Southeastern Brazil, between March and June 2009: daily records of absences and the reasons stated for these absences, total concentration of suspended particulate matter (µg/m3), and air humidity. The relationship between the percentage of school absences due to respiratory problems and the concentration of particulate matter in March and from April to June presented a distinct behavior: absences increased alongside the increase in particulate matter concentration. The use of school absences as indicators of this relationship is an innovative approach.

Comparison between monopolar and bipolar microsecond range pulsed electric fields in enhancement of apple juice extraction

The effect of monopolar and bipolar shaped pulses in additional yield of apple juice extraction is evaluated. The applied electric field strength, pulsewidth, and number of pulses are assessed for both pulse types, and divergences are analyzed. Variation of electric field strength is ranged from 100 to 1300 V/cm, pulsewidth from 20 to 300 mu s, and the number of pulses from 10 to 200, at a frequency of 200 Hz. Two pulse trains separated by 1 s are applied to apple cubes. Results are plotted against reference untreated samples for all assays. Specific energy consumption is calculated for each experiment as well as qualitative indicators for apple juice of total soluble dry matter and absorbance at 390-nm wavelength. Bipolar pulses demonstrated higher efficiency, and specific energetic consumption has a threshold where higher inputs of energy do not result in higher juice extraction when electric field variation is applied. Total soluble dry matter and absorbance results do not illustrate significant differences between application of monopolar and bipolar pulses, but all values are inside the limits proposed for apple juice intended for human consumption.

Treatment of patients with Schistosomiasis mansoni: a double blind clinical trial comparing praziquantel with oxamniquine

A double-blind clinical trial involving 120 patients with chronic schistosomiasis was carried out to compare the tolerability and efficacy of praziquantel and oxamniquine. The patients were randomly allocated into two groups. One was treated with praziquantel, 55 mg/kg of body weight CBWT), and the other one with oxamniquine, 15mg/kg bwt, administered in a single oral dose. The diagnosis and the parasitological follow-up was based on stool examinations by quantitative Kato-Katz method and on rectal biopsies. Side-effects — mainly dizziness, sleepness, abdominal distress, headache, nausea and diarrhea — were observed in 87% of the cases. Their incidence, intensity and duration were similar for both drugs but abdominal pain was significantly more frequent after praziquantel intake and severe dizziness was more commonly reported after oxamniquine. A significant increase of alanine-aminotransferase and y-glutamyltransferase was found with the latter drug and of total bilirubin with the former one. A total of 48 patients treated with praziquantel and 46 with oxamniquine completed with negative findings the required three post-treatment parasitological controls — three slides of each stool sample on the first, third and sixth month. The achieved cure rates were 79.2% and 84.8%, respectively, a difference without statistical significance. The non-cured cases showed a mean reduction in the number of eggs per gram of feces of 93.5% after praziquantel and of 84.1% after oxamniquine. This diference also was not significant. Five patients retreated with praziquantel were cured but only one out of three treated a second time with oxamniquine. These findings show that both drugs — despite their different chemical structures, pharmacological properties and mechanisms-of-action — induce similar side-effects as well as a comparable therapeutical efficacy, in agreement with the results reported from analogous investigations.

Control of predators in industrial scale microalgae cultures with Pulsed Electric Fields.

This work describes the utilization of Pulsed Electric Fields to control the protozoan contamination of a microalgae culture, in an industrial 2.7m3 microalgae photobioreactor. The contaminated culture was treated with Pulsed Electric Fields, PEF, for 6h with an average of 900V/cm, 65μs pulses of 50Hz. Working with recirculation, all the culture was uniformly exposed to the PEF throughout the assay. The development of the microalgae and protozoan populations was followed and the results showed that PEF is effective on the selective elimination of protozoa from microalgae cultures, inflicting on the protozoa growth halt, death or cell rupture, without affecting microalgae productivity. Specifically, the results show a reduction of the active protozoan population of 87% after 6h treatment and 100% after few days of normal cultivation regime. At the same time, microalgae growth rate remained unaffected. © 2014 Elsevier B.V.

Unmixing hyperspectral data: independent and dependent component analysis

The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.

Blind hyperspectral unmixing

This paper introduces a new hyperspectral unmixing method called Dependent Component Analysis (DECA). This method decomposes a hyperspectral image into a collection of reflectance (or radiance) spectra of the materials present in the scene (endmember signatures) and the corresponding abundance fractions at each pixel. DECA models the abundance fractions as mixtures of Dirichlet densities, thus enforcing the constraints on abundance fractions imposed by the acquisition process, namely non-negativity and constant sum. The mixing matrix is inferred by a generalized expectation-maximization (GEM) type algorithm. This method overcomes the limitations of unmixing methods based on Independent Component Analysis (ICA) and on geometrical based approaches. DECA performance is illustrated using simulated and real data.

Blind hyperspectral unmixing

Hyperspectral unmixing methods aim at the decomposition of a hyperspectral image into a collection endmember signatures, i.e., the radiance or reflectance of the materials present in the scene, and the correspondent abundance fractions at each pixel in the image. This paper introduces a new unmixing method termed dependent component analysis (DECA). This method is blind and fully automatic and it overcomes the limitations of unmixing methods based on Independent Component Analysis (ICA) and on geometrical based approaches. DECA is based on the linear mixture model, i.e., each pixel is a linear mixture of the endmembers signatures weighted by the correspondent abundance fractions. These abundances are modeled as mixtures of Dirichlet densities, thus enforcing the non-negativity and constant sum constraints, imposed by the acquisition process. The endmembers signatures are inferred by a generalized expectation-maximization (GEM) type algorithm. The paper illustrates the effectiveness of DECA on synthetic and real hyperspectral images.

Randomized, double-blind trial comparing indinavir alone, zidovudine alone and indinavir plus zidovudine in antiretroviral therapy-naive hiv-infected individuals with CD4 cell counts between 50 and 250/mm3

Treatment with indinavir has been shown to result in marked decreases in viral load and increases in CD4 cell counts in HIV-infected individuals. A randomized double-blind study to evaluate the efficacy of indinavir alone (800 mg q8h), zidovidine alone (200 mg q8h) or the combination was performed to evaluate progression to AIDS. 996 antiretroviral therapy-naive patients with CD4 cell counts of 50-250/mm3 were allocated to treatment. During the trial the protocol was amended to add lamivudine to the zidovudine-containing arms. The primary endpoint was time to development of an AIDS-defining illness or death. The study was terminated after a protocol-defined interim analysis demonstrated highly significant reductions in progression to a clinical event in the indinavir-containing arms, compared to the zidovudine arm (p<0.0001). Over a median follow-up of 52 weeks (up to 99 weeks), percent reductions in hazards for the indinavir plus zidovudine and indinavir groups compared to the zidovudine group were 70% and 61%, respectively. Significant reductions in HIV RNA and increases in CD4 cell counts were also seen in the indinavir-containing groups compared to the zidovudine group. Improvement in both CD4 cell count and HIV RNA were associated with reduced risk of disease progression. All three regimens were generally well tolerated.

The genetic basis of morphological change in convergent evolution of natural populations: identifying candidate genes behind convergent evolution in blind cavefish astyanax mexicanus

Dissertation presented to obtain the Ph.D. degree in Biology at the Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa.

Predictivity Strength of the Spatial Variability of Phenanthrene Sorption Across Two Sandy Loam Fields

Sorption is commonly agreed to be the major process underlying the transport and fate of polycyclic aromatic hydrocarbons (PAHs) in soils. However, there is still a scarcity of studies focusing on spatial variability at the field scale in particular. In order to investigate the variation in the field of phenanthrene sorption, bulk topsoil samples were taken in a 15 × 15-m grid from the plough layer in two sandy loam fields with different texture and organic carbon (OC) contents (140 samples in total). Batch experiments were performed using the adsorption method. Values for the partition coefficient K d (L kg−1) and the organic carbon partition coefficient K OC (L kg−1) agreed with the most frequently used models for PAH partitioning, as OC revealed a higher affinity for sorption. More complex models using different OC compartments, such as non-complexed organic carbon (NCOC) and complexed organic carbon (COC) separately, performed better than single K OC models, particularly for a subset including samples with Dexter n < 10 and OC <0.04 kg kg−1. The selected threshold revealed that K OC-based models proved to be applicable for more organic fields, while two-component models proved to be more accurate for the prediction of K d and retardation factor (R) for less organic soils. Moreover, OC did not fully reflect the changes in phenanthrene retardation in the field with lower OC content (Faardrup). Bulk density and available water content influenced the phenanthrene transport mechanism phenomenon.

Wii-Workouts on Chronic Pain, Physical Capabilities and Mood of Older Women: A Randomized Controlled Double Blind Trial

Chronic Low Back Pain (CLBP) is a public health problem and older women have higher incidence of this symptom, which affect body balance, functional capacity and behavior. The purpose of this study was to verifying the effect of exercises with Nintendo Wii on CLBP, functional capacity and mood of elderly. Thirty older women (68 ± 4 years; 68 ± 12 kg; 154 ± 5 cm) with CLBP participated in this study. Elderly individuals were divided into a Control Exercise Group (n = 14) and an Experimental Wii Group (n = 16). Control Exercise Group did strength exercises and core training, while Experimental Wii Group did ones additionally to exercises with Wii. CLBP, balance, functional capacity and mood were assessed pre and post training by the numeric pain scale, Wii Balance Board, sit to stand test and Profile of Mood States, respectively. Training lasted eight weeks and sessions were performed three times weekly. MANOVA 2 x 2 showed no interaction on pain, siting, stand-up and mood (P = 0.53). However, there was significant difference within groups (P = 0.0001). ANOVA 2 x 2 showed no interaction for each variable (P > 0.05). However, there were significant differences within groups in these variables (P < 0.05). Tukey's post-hoc test showed significant difference in pain on both groups (P = 0.0001). Wilcoxon and Mann-Whitney tests identified no significant differences on balance (P > 0.01). Capacity to Sit improved only in Experimental Wii Group (P = 0.04). In conclusion, physical exercises with Nintendo Wii Fit Plus additional to strength and core training were effective only for sitting capacity, but effect size was small.

DOUBLE-BLIND STUDY WITH TOPICAL ISOCONAZOLE AND TERBINAFINE FOR THE TREATMENT OF ONE PATIENT WITH BILATERAL Tinea nigra plantaris AND SUGGESTIONS FOR NEW DIFFERENTIAL DIAGNOSIS

The authors report a case of bilateral Tinea nigra plantaris treated through a double-blind study with the topical antifungal agents Isoconazole and Terbinafine. The objective of the study was to clinically compare the efficacy of these two topical antifungal agents on days 10, 20 and 30 of the treatment. No significant clinical differences were found, as all the plantar lesions regressed completely by the end of the treatment. Our conclusion was that in the case reported, the topical antifungal agents Isoconazole and Terbinafine demonstrated identical efficacy as a clinical cure. We also suggest the inclusion of injuries caused by arthropods of the Diplopoda Class in the differential diagnosis of Tinea nigra plantaris, due to the persistent acral hyperpigmentation.

Influence of abiotic stress factors on VOCs emission from Portuguese rice paddy fields: relation with increased climate change

Dissertação para obtenção do Grau de Mestre em Engenharia do Ambiente Perfil de Gestão de Sistemas Ambientais