953 resultados para Root to shoot ratio
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Experimental animal studies have shown that nicotine exposure during gestation alters the expression of fetal hypothalamic neuropeptides involved in the control of appetite. We aimed to determine whether the exposure to maternal smoking during gestation in humans is associated with an altered feeding behavior of the adult offspring. A longitudinal prospective cohort study was conducted including all births from Ribeirao Preto (Sao Paulo, Brazil) between 1978 and 1979. At 24 years of age, a representative random sample was re-evaluated and divided into groups exposed (n = 424) or not (n = 1586) to maternal smoking during gestation. Feeding behavior was analyzed using a food frequency questionnaire. Covariance analysis was used for continuous data and the chi(2) test for categorical data. Results were adjusted for birth weight ratio, body mass index, gender, physical activity and smoking, as well as maternal and subjects` schooling. Individuals exposed to maternal smoking during gestation ate more carbohydrates than proteins (as per the carbohydrate-to-protein ratio) than non-exposed individuals. There were no differences in the consumption of the macronutrients themselves. We propose that this adverse fetal life event programs the individual`s physiology and metabolism persistently, leading to an altered feeding behavior that could contribute to the development of chronic diseases in the long term.
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This study was designed to compare cutaneous mycoflora isolation and CD4+:CD8+ ratio in feline immunodeficiency virus (FIV)-infected cats with that in FIV-uninfected cats. Sixty cats were examined. Twenty-five were Fly-infected cats and 35 were RV-uninfected cats. All 60 cats were FeLV-negative. Fungi were speciated and immunophenotyping of peripheral CD4+ and CD8+ T lymphocytes was performed. At least one fungal colony was isolated from 22/25 (88%) FIV-infected cats. Among the FIV-uninfected cats fungal colonies were recovered from 13/35 (37%) specimens. Dermatophytes were recovered from 2/25 (8%) FIV-infected cats (one Microsporum gypseum, one Microsporum can is) and 3/35 (8.5%) FIV-uninfected cats (M gypseum). Malassezia species was the most commonly isolated organism from both groups of cats (51.6%). Malassezia species was more commonly isolated from FIV-infected cats than RV-uninfected cats (84% vs 28.6%). The CD4+ to CD8+ lymphocyte ratio for FIV-infected cats was significantly lower than the CD4+ to CD8+ ratio in the FIV-uninfected cats. The CD4+ to CD8+ lymphocyte ratio for FIV-infected cats with cutaneous overall fungal isolation was significantly lower than the CD4:CD8 lymphocyte ratio in the FIV-infected cats but without cutaneous fungal isolation. We can conclude that immunologic depletion due to retroviral infection might represent a risk factor to cutaneous fungal colonization in cats. (C) 2010 ISFM and AAFP. Published by Elsevier Ltd. All rights reserved.
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Although the cariostatic effects of CO(2) laser on enamel have been shown, its effects on root surface demineralization remains uncertain. The objectives of this in vitro research was to establish safe parameters for a pulsed 10.6 mu m CO(2) laser and to evaluate its effect on morphological features of the root surface, as well as on the reduction of root demineralization. Ninety-five human root surfaces were randomly divided into five groups: G1-No treatment (control); G2-2.5 J/cm(2); G3-4.0 J/cm(2); G4-5.0 J/cm(2); and G5-6.0 J/cm(2). Intrapulpal temperature was evaluated during root surface irradiation by a thermocouple and morphological changes were evaluated by SEM. After the surface treatment, the specimens were submitted to a 7-day pH-cycling model. Subsequently, the cross-sectional Knoop microhardness values were measured. For all irradiated groups, intrapulpal temperature changes were less than 1.5 degrees C. Scanning electron microscopy images indicated that fluences as low as 4.0 J/cm(2) were sufficient to induce morphological changes in the root surface. Additionally, for fluences reaching or exceeding 4.0 J/cm(2), laser-induced inhibitory effects on root surface demineralization were observed. It was concluded that laser energy density in the range of 4.0 to 6.0 J/cm(2) could be applied to a dental root to reduce demineralization of this surface without compromising pulp vitality.
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Fluctuations in estrogen and progesterone during the menstrual cycle can cause changes in body systems other than the reproductive system. For example, progesterone is involved in the regulation of fluid balance in the renal tubules and innervation of the diaphragm via the phrenic nerve. However, few significant changes in the responses of the cardiovascular and respiratory systems, blood lactate, bodyweight, performance and ratings of perceived exertion are evident across the cycle. Nevertheless, substantial evidence exists to suggest that increased progesterone levels during the luteal phase cause increases in both core and skin temperatures and alter the temperature at which sweating begins during exposure to both ambient and hot environments. As heat illness is characterised by a significant increase in body temperature, it is feasible that an additional increase in core temperature during the luteal phase could place females at an increased risk of developing heat illness during this time. In addition, it is often argued that physiological gender differences such as oxygen consumption, percentage body fat and surface area-to-mass ratio place females at a higher risk of heat illness than males. This review examines various physiological responses to heat exposure during the menstrual cycle at rest and during exercise, and considers whether such changes increase the risk of heat illness in female athletes during a particular phase of the menstrual cycle.
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Large values for the mass-to-light ratio (ϒ) in self-gravitating systems is one of the most important evidences of dark matter. We propose a expression for the mass-to-light ratio in spherical systems using MOND. Results for the COMA cluster reveal that a modification of the gravity, as proposed by MOND, can reduce significantly this value.
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Although the 12-lead electrocardiogram has become an essential medical and research tool, many current and envisaged applications would benefit from simpler devices, using 3-lead ECG configuration. This is particularly true for Ambient Assisted Living (in a broad perspective). However, the chest anatomy of female patients, namely during pregnancy, can hamper the adequate placement of a 3-lead ECG device and, very often, electrodes are placed below the chest rather than at the precise thoracic landmarks. Thus, the aim of this study was to compare the effect of electrode positioning on the ECG signal of pregnant women and provide guidelines for device development. The effect of breast tissue on the ECG signal was investigated by relating breast size with the signal-to-noise ratio, root mean square and R-wave amplitude. Results show that the 3-lead ECG should be placed on the breast rather than under the breast and indicate positive correlation between breast size and signal-to-noise ratio.
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ABSTRACT The indiscriminate use of mineral fertilizers in papaya orchards has increased production costs, and the use of arbuscular mycorrhizal fungi is a promising alternative to reduce such expenses. Therefore, the present research aimed at studying the efficiency of arbuscular mycorrhizal fungi (AMF) on dry matter and nutrient accumulation in Sunrise Solo papaya seedlings, by applying doses of P2O5 (triple superphosphate) that are harmful to the symbiosis. The experiment was carried out in a protected environment and was set up in a randomized block design with four replications, and consisted of four P2O5 doses (0, 672, 1386 and 2100 mg dm-3), three mycorrhizal fungi species (Gigaspora margarita, Entrophospora colombiana and Scutellospora heterogama) and the control treatment (mycorrhiza-free). Shoot and root dry matter as well as nitrogen, phosphorus and potassium contents in leaf and root tissues were assessed. Mycorrhizal inoculation promoted a 30% increase in shoot dry matter in relation to the control treatment. Mycorrhizal fungi promoted increases in leaf and root nitrogen content up to 672 mg dm-3 P2O5. Inoculation of E. colombiana favored the highest gains in root and shoot dry matter. P2O5 fertilization increased foliar and root phosphorus content.
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ABSTRACT Soybean cultivation is increasing rapidly in the region of Alto Vale do Itajaí, State of Santa Catarina, where there is a predominance of silt soils. The objective of this work was to evaluate the content of primary macronutrients in shoots and shoot and root vegetative growth of soybean (Glicine max L. Merrill) grown in a silt-loam soil under different compactation densities and moisture levels. A randomized block design in a 4x4 factorial arrangement was used, with four compactation densities: 1.00; 1.20; 1.40 and 1.60 Mg m-3, and four soil moisture levels: 0.130; 0.160; 0.190 and 0.220 kg kg-1 and four replications. Each pot consisted of the overlapping of three 150-mm PVC rings, where soil was maintained in the higher and lower part of the pot with a density of 1.00 Mg m-3 and in the intermediate ring, the compactation densities were increased. Values of soil density higher than 120 Mg m-3 negatively affected N, P and K uptake by soybean plants, as well as the plant mass of the shoots and roots. The higher levels of soil moisture reduced the compaction effect and promoted better absorption of P and K.
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The volatiles from Coriandrum sativum L., Satureja montana L., Santolina chamaecyparissus L., and Thymus vulgaris L. were isolated by hydrodistillation (essential oil) and supercritical fluid extraction (volatile oil). Their effect on seed germination and root and shoot growth of the surviving seedlings of four crops (Zea mays L., Triticum durum L., Pisum sativum L., and Lactuca sativa L.) and two weeds (Portulaca oleracea L. and Vicia sativa L.) was investigated and compared with those of two synthetic herbicides, Agrocide and Prowl. The volatile oils of thyme and cotton lavender seemed to be promising alternatives to the synthetic herbicides because they were the least injurious to the crop species. The essential oil of winter savory, on the other hand, affected both crop and weeds and can be appropriate for uncultivated fields.
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Aim - A quantative primary study to determine whether increasing source to image distance (SID), with and without the use of automatic exposure control (AEC) for antero-posterior (AP) pelvis imaging, reduces dose whilst still producing an image of diagnostic quality. Methods - Using a computed radiography (CR) system, an anthropomorphic pelvic phantom was positioned for an AP examination using the table bucky. SID was initially set at 110 cm, with tube potential set at a constant 75 kVp, with two outer chambers selected and a fine focal spot of 0.6 mm. SID was then varied from 90 cm to 140 cm with two exposures made at each 5 cm interval, one using the AEC and another with a constant 16 mAs derived from the initial exposure. Effective dose (E) and entrance surface dose (ESD) were calculated for each acquisition. Seven experienced observers blindly graded image quality using a 5-point Likert scale and 2 Alternative Forced Choice software. Signal-to-Noise Ratio (SNR) was calculated for comparison. For each acquisition, femoral head diameter was also measured for magnification indication. Results - Results demonstrated that when increasing SID from 110 cm to 140 cm, both E and ESD reduced by 3.7% and 17.3% respectively when using AEC and 50.13% and 41.79% respectively, when the constant mAs was used. No significant statistical (T-test) difference (p = 0.967) between image quality was detected when increasing SID, with an intra-observer correlation of 0.77 (95% confidence level). SNR reduced slightly for both AEC (38%) and no AEC (36%) with increasing SID. Conclusion - For CR, increasing SID significantly reduces both E and ESD for AP pelvis imaging without adversely affecting image quality.
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Electrocardiographic (ECG) signals are emerging as a recent trend in the field of biometrics. In this paper, we propose a novel ECG biometric system that combines clustering and classification methodologies. Our approach is based on dominant-set clustering, and provides a framework for outlier removal and template selection. It enhances the typical workflows, by making them better suited to new ECG acquisition paradigms that use fingers or hand palms, which lead to signals with lower signal to noise ratio, and more prone to noise artifacts. Preliminary results show the potential of the approach, helping to further validate the highly usable setups and ECG signals as a complementary biometric modality.
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Background and aim: Cardiorespiratory fitness (CRF) and diet have been involved as significant factors towards the prevention of cardio-metabolic diseases. This study aimed to assess the impact of the combined associations of CRF and adherence to the Southern European Atlantic Diet (SEADiet) on the clustering of metabolic risk factors in adolescents. Methods and Results: A cross-sectional school-based study was conducted on 468 adolescents aged 15-18, from the Azorean Islands, Portugal. We measured fasting glucose, insulin, total cholesterol (TC), HDL-cholesterol, triglycerides, systolic blood pressure, waits circumference and height. HOMA, TC/HDL-C ratio and waist-to-height ratio were calculated. For each of these variables, a Z-score was computed by age and sex. A metabolic risk score (MRS) was constructed by summing the Z scores of all individual risk factors. High risk was considered when the individual had 1SD of this score. CRF was measured with the 20 m-Shuttle-Run- Test. Adherence to SEADiet was assessed with a semi-quantitative food frequency questionnaire. Logistic regression showed that, after adjusting for potential confounders, unfit adolescents with low adherence to SEADiet had the highest odds of having MRS (OR Z 9.4; 95%CI:2.6e33.3) followed by the unfit ones with high adherence to the SEADiet (OR Z 6.6; 95% CI: 1.9e22.5) when compared to those who were fit and had higher adherence to SEADiet.
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Hyperspectral remote sensing exploits the electromagnetic scattering patterns of the different materials at specific wavelengths [2, 3]. Hyperspectral sensors have been developed to sample the scattered portion of the electromagnetic spectrum extending from the visible region through the near-infrared and mid-infrared, in hundreds of narrow contiguous bands [4, 5]. The number and variety of potential civilian and military applications of hyperspectral remote sensing is enormous [6, 7]. Very often, the resolution cell corresponding to a single pixel in an image contains several substances (endmembers) [4]. In this situation, the scattered energy is a mixing of the endmember spectra. A challenging task underlying many hyperspectral imagery applications is then decomposing a mixed pixel into a collection of reflectance spectra, called endmember signatures, and the corresponding abundance fractions [8–10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. Linear mixing model holds approximately when the mixing scale is macroscopic [13] and there is negligible interaction among distinct endmembers [3, 14]. If, however, the mixing scale is microscopic (or intimate mixtures) [15, 16] and the incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [17], the linear model is no longer accurate. Linear spectral unmixing has been intensively researched in the last years [9, 10, 12, 18–21]. It considers that a mixed pixel is a linear combination of endmember signatures weighted by the correspondent abundance fractions. Under this model, and assuming that the number of substances and their reflectance spectra are known, hyperspectral unmixing is a linear problem for which many solutions have been proposed (e.g., maximum likelihood estimation [8], spectral signature matching [22], spectral angle mapper [23], subspace projection methods [24,25], and constrained least squares [26]). In most cases, the number of substances and their reflectances are not known and, then, hyperspectral unmixing falls into the class of blind source separation problems [27]. Independent component analysis (ICA) has recently been proposed as a tool to blindly unmix hyperspectral data [28–31]. ICA is based on the assumption of mutually independent sources (abundance fractions), which is not the case of hyperspectral data, since the sum of abundance fractions is constant, implying statistical dependence among them. This dependence compromises ICA applicability to hyperspectral images as shown in Refs. [21, 32]. In fact, ICA finds the endmember signatures by multiplying the spectral vectors with an unmixing matrix, which minimizes the mutual information among sources. If sources are independent, ICA provides the correct unmixing, since the minimum of the mutual information is obtained only when sources are independent. This is no longer true for dependent abundance fractions. Nevertheless, some endmembers may be approximately unmixed. These aspects are addressed in Ref. [33]. Under the linear mixing model, the observations from a scene are in a simplex whose vertices correspond to the endmembers. Several approaches [34–36] have exploited this geometric feature of hyperspectral mixtures [35]. Minimum volume transform (MVT) algorithm [36] determines the simplex of minimum volume containing the data. The method presented in Ref. [37] is also of MVT type but, by introducing the notion of bundles, it takes into account the endmember variability usually present in hyperspectral mixtures. The MVT type approaches are complex from the computational point of view. Usually, these algorithms find in the first place the convex hull defined by the observed data and then fit a minimum volume simplex to it. For example, the gift wrapping algorithm [38] computes the convex hull of n data points in a d-dimensional space with a computational complexity of O(nbd=2cþ1), where bxc is the highest integer lower or equal than x and n is the number of samples. The complexity of the method presented in Ref. [37] is even higher, since the temperature of the simulated annealing algorithm used shall follow a log( ) law [39] to assure convergence (in probability) to the desired solution. Aiming at a lower computational complexity, some algorithms such as the pixel purity index (PPI) [35] and the N-FINDR [40] still find the minimum volume simplex containing the data cloud, but they assume the presence of at least one pure pixel of each endmember in the data. 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. PPI algorithm uses the minimum noise fraction (MNF) [41] as a preprocessing step to reduce dimensionality and to improve the signal-to-noise ratio (SNR). The algorithm then projects every spectral vector onto skewers (large number of random vectors) [35, 42,43]. The points corresponding to extremes, for each skewer direction, are stored. A cumulative account records the number of times each pixel (i.e., a given spectral vector) is found to be an extreme. The pixels with the highest scores are the purest ones. N-FINDR algorithm [40] is based on the fact that in p spectral dimensions, the p-volume defined by a simplex formed by the purest pixels is larger than any other volume defined by any other combination of pixels. This algorithm finds the set of pixels defining the largest volume by inflating a simplex inside the data. ORA SIS [44, 45] is a hyperspectral framework developed by the U.S. Naval Research Laboratory consisting of several algorithms organized in six modules: exemplar selector, adaptative learner, demixer, knowledge base or spectral library, and spatial postrocessor. The first step consists in flat-fielding the spectra. Next, the exemplar selection module is used to select spectral vectors that best represent the smaller convex cone containing the data. The other pixels are rejected when the spectral angle distance (SAD) is less than a given thresh old. The procedure finds the basis for a subspace of a lower dimension using a modified Gram–Schmidt orthogonalizati on. The selected vectors are then projected onto this subspace and a simplex is found by an MV T pro cess. ORA SIS is oriented to real-time target detection from uncrewed air vehicles using hyperspectral data [46]. In this chapter we develop a new algorithm to unmix linear mixtures of endmember spectra. First, the algorithm determines the number of endmembers and the signal subspace using a newly developed concept [47, 48]. Second, the algorithm extracts the most pure pixels present in the data. Unlike other methods, this algorithm is completely automatic and unsupervised. To estimate the number of endmembers and the signal subspace in hyperspectral linear mixtures, the proposed scheme begins by estimating sign al and noise correlation matrices. The latter is based on multiple regression theory. The signal subspace is then identified by selectin g the set of signal eigenvalue s that best represents the data, in the least-square sense [48,49 ], we note, however, that VCA works with projected and with unprojected data. The extraction of the end members exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. As PPI and N-FIND R algorithms, VCA also assumes the presence of pure pixels in the data. The algorithm iteratively projects data on to a direction orthogonal to the subspace spanned by the endmembers already determined. The new end member signature corresponds to the extreme of the projection. The algorithm iterates until all end members are exhausted. VCA performs much better than PPI and better than or comparable to N-FI NDR; yet it has a computational complexity between on e and two orders of magnitude lower than N-FINDR. The chapter is structure d as follows. Section 19.2 describes the fundamentals of the proposed method. Section 19.3 and Section 19.4 evaluate the proposed algorithm using simulated and real data, respectively. Section 19.5 presents some concluding remarks.
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A plant growth-promoting bacterial (PGPB) strain SC2b was isolated from the rhizosphere of Sedum plumbizincicola grown in lead (Pb)/zinc (Zn) mine soils and characterized as Bacillus sp. based on (1) morphological and biochemical characteristics and (2) partial 16S ribosomal DNA sequencing analysis. Strain SC2b exhibited high levels of resistance to cadmium (Cd) (300 mg/L), Zn (730 mg/L), and Pb (1400 mg/L). This strain also showed various plant growth-promoting (PGP) features such as utilization of 1-aminocyclopropane-1-carboxylate, solubilization of phosphate, and production of indole-3-acetic acid and siderophore. The strain mobilized high concentration of heavy metals from soils and exhibited different biosorption capacity toward the tested metal ions. Strain SC2b was further assessed for PGP activity by phytagar assay with a model plant Brassica napus. Inoculation of SC2b increased the biomass and vigor index of B. napus. Considering such potential, a pot experiment was conducted to assess the effects of inoculating the metal-resistant PGPB SC2b on growth and uptake of Cd, Zn and Pb by S. plumbizincicola in metal-contaminated agricultural soils. Inoculation with SC2b elevated the shoot and root biomass and leaf chlorophyll content of S. plumbizincicola. Similarly, plants inoculated with SC2b demonstrated markedly higher Cd and Zn accumulation in the root and shoot system, indicating that SC2b enhanced Cd and Zn uptake by S. plumbizincicola through metal mobilization or plant-microbial mediated changes in chemical or biological soil properties. Data demonstrated that the PGPB Bacillus sp. SC2b might serve as a future biofertilizer and an effective metal mobilizing bioinoculant for rhizoremediation of metal polluted soils.
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Breast cancer is the most common type of cancer among women all over the world. An important issue that is not commonly addressed in breast cancer imaging literature is the importance of imaging the underarm region—where up to 80% of breast cancer cells can metastasise to. The first axillary lymph nodes to receive drainage from the primary tumour in the breast are called Sentinel Node. If cancer cells are found in the Sentinel Node, there is an increased risk of metastatic breast cancer which makes this evaluation crucial to decide what follow-up exams and therapy to follow. However, non-invasive detection of cancer cells in the lymph nodes is often inconclusive, leading to the surgical removal of too many nodes which causes adverse side-effects for patients. Microwave Imaging is one of the most promising non-invasive imaging modalities for breast cancer early screening and monitoring. This novel study tests the feasibility of imaging the axilla region by means of the simulation of an Ultra-Wideband Microwave Imaging system. Simulations of such system are completed in several 2D underarm models that mimic the axilla. Initial imaging results are obtained by means of processing the simulated backscattered signals by eliminating artefacts caused by the skin and beamforming the processed signals in order to time-align all the signals recorded at each antenna. In this dissertation several image formation algorithms are implemented and compared by visual inspection of the resulting images and through a range of performance metrics, such as Signal-to-Clutter Ratio and FullWidth Half Maximum calculations. The results in this study showed that Microwave Imaging is a promising technique that might allow to identify the presence and location of metastasised cancer cells in axillary lymph nodes, enabling the non-invasive evaluation of breast cancer staging.