827 resultados para Motion pictures in agriculture


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The CGIAR Research Program on Aquatic Agricultural Systems (AAS) has developed its Gender Research in Development Strategy centered on a transformative approach. Translating this strategy into actual research and development practice poses a considerable challenge, as not much (documented) experience exists in the agricultural sector to draw on, and significant innovation is required. A process of transformative change requires reflecting on multiple facets and dimensions simultaneously. This working paper is a collation of think pieces, structured around broad the mes and topics, reflecting on what works (and what does not) in the application of gender transformative approaches in agriculture and other sectors, and seeking to stimulate a discussion on the way forward for CGIAR Research Programs (CRPs) and other programs to build organizational capacities and partnerships.

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Background: The emergence of agriculture about 10,000 years ago marks a dramatic change in human evolutionary history. The diet shift in agriculture societies might have a great impact on the genetic makeup of Neolithic human populations. The regionally restricted enrichment of the class I alcohol dehydrogenase sequence polymorphism (ADH1BArg47His) in southern China and the adjacent areas suggests Darwinian positive selection on this genetic locus during Neolithic time though the driving force is yet to be disclosed. Results: We studied a total of 38 populations (2,275 individuals) including Han Chinese, Tibetan and other ethnic populations across China. The geographic distribution of the ADH1B*47His allele in these populations indicates a clear east-to-west cline, and it is dominant in south-eastern populations but rare in Tibetan populations. The molecular dating suggests that the emergence of the ADH1B*47His allele occurred about 10,000 similar to 7,000 years ago. Conclusion: We present genetic evidence of selection on the ADH1BArg47His polymorphism caused by the emergence and expansion of rice domestication in East Asia. The geographic distribution of the ADH1B*47His allele in East Asia is consistent with the unearthed culture relic sites of rice domestication in China. The estimated origin time of ADH1B*47His allele in those populations coincides with the time of origin and expansion of Neolithic agriculture in southern China.

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Environmental. factors that affect the growth and microcystin production of microcystis have received worldwide attention because of the hazards microcystin poses to environmental safety and public health. Nevertheless, the effects of organic anthropogenic pollution on microcystis are rarely discussed. Gibberellin A(3) (GA(3)) is a vegetable hormone widely used in agriculture and horticulture that can contaminate water as an anthropogenic pollutant. Because of its common occurrence, we studied the effects of GA3 on growth and microcystin production of Microcystis aeruginosa (M. aeruginosa) PCC7806 with different concentrations (0.001-25mg/L) in batch culture. The control was obtained without gibberellin under the same culture conditions. Growth, estimated by dry weight and cell number, increased after the GA3 treatment. GA3 increased the amounts of chlorophyll a, phycocyanin and cellular-soluble protein in the cells of M. aeruginosa PCC7806, but decreased the accumulation of water-soluble carbohydrates. In addition, GA3 was observed to affect nitrogen absorption of the test algae, but to have no effect on the absorption of phosphorus. The amount of microcystin measured by enzyme-Linked immunosorbent assay (ELISA) increased in GA3 treatment groups, but the stimulatory effects were different in different culture phases. It is suggested that GA3 increases M. aeruginosa growth by stimulating its absorbance of nitrogen and increasing its ability to use carbohydrates, accordingly increasing cellular pigments and thus finally inducing accumulation of protein and microcystin. (C) 2007 Elsevier GmbH. All rights reserved.

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In conventional metals, there is plenty of space for dislocations-line defects whose motion results in permanent material deformation-to multiply, so that the metal strengths are controlled by dislocation interactions with grain boundaries(1,2) and other obstacles(3,4). For nano-structured materials, in contrast, dislocation multiplication is severely confined by the nanometre-scale geometries so that continued plasticity can be expected to be source-controlled. Nano-grained polycrystalline materials were found to be strong but brittle(5-9), because both nucleation and motion of dislocations are effectively suppressed by the nanoscale crystallites. Here we report a dislocation-nucleation-controlled mechanism in nano-twinned metals(10,11) in which there are plenty of dislocation nucleation sites but dislocation motion is not confined. We show that dislocation nucleation governs the strength of such materials, resulting in their softening below a critical twin thickness. Large-scale molecular dynamics simulations and a kinetic theory of dislocation nucleation in nano-twinned metals show that there exists a transition in deformation mechanism, occurring at a critical twin-boundary spacing for which strength is maximized. At this point, the classical Hall-Petch type of strengthening due to dislocation pile-up and cutting through twin planes switches to a dislocation-nucleation-controlled softening mechanism with twin-boundary migration resulting from nucleation and motion of partial dislocations parallel to the twin planes. Most previous studies(12,13) did not consider a sufficient range of twin thickness and therefore missed this strength-softening regime. The simulations indicate that the critical twin-boundary spacing for the onset of softening in nano-twinned copper and the maximum strength depend on the grain size: the smaller the grain size, the smaller the critical twin-boundary spacing, and the higher the maximum strength of the material.

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C-13 and H-1 relaxation times were measured as a function of temperature in two magnetic fields for dilute solutions of phenolphthalein poly(ether sulfone) (PES-C) in deuterated chloroform. The spin-lattice relaxation times were interpreted in terms of segmental motion characterized by the sharp cutoff model of Jones and Stockmayer (J. S. model). The phenyl group rotation is treated as a stochastic diffusion by the J. S. model. The restricted butterfly motion of the phenyl group attached to the cardo ring in PES-C is mentioned but is not discussed in detail in this work. Correlation times for the segmental motion are in the picosecond range which indicates the high flexibility of PES-C chains. The correlation time for the phenyl group internal rotation is similar to that of the segmental motion. The temperature dependence of these motions is weak. The apparent activation energy of the motions considered is less than 10 kJ/mol. The simulating results for PES are also reasonable considering the differences in structure compared with PES-C. The correlation times and the apparent activation energy obtained using the J. S. model for the main chain motion of PES-C are the same as those obtained using the damped orientational diffusion model and the conformational jump model.

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Three kinds of high-performance polyimides 1 (poly(ketone-imide) PKI), 2 (poly(ether-imide) PEI) and 3 (poly(oxy-imide) POI) were studied using nuclear magnetic resonance (NMR). The NMR spectra of the polyimides were assigned according to the comprehensive consideration of the substitution effect of different substituting groups, viz. distortionless enhancement by polarization transfer (DEPT), no nuclear Overhauser effect (NNE), analysis of relaxation time, and two-dimensional correlated spectroscopy (COSY) techniques. The structural units of these three polyimides were determined. Carbon-13 and proton relaxation times for PEI and PKI were interpreted in terms of segmental motion characterized by the sharp cutoff model of Jones and Stockmayer (JS model) and anisotropic group rotation such as phenyl group rotation and methyl group rotation. Correlation times for the main-chain motion are in the tens of picosecond range which indicates the high flexibility of polyimide chains. Correlation times for phenyl group and methyl group rotations are more than 1 order of magnitude lower and approximately 1 order of magnitude higher than that of the main chain, respectively.

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C.M. Onyango, J.A. Marchant and R. Zwiggelaar, 'Modelling uncertainty in agricultural image analysis', Computers and Electronics in Agriculture 17 (3), 295-305 (1997)

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This paper analyses the asymptotic properties of nonlinear least squares estimators of the long run parameters in a bivariate unbalanced cointegration framework. Unbalanced cointegration refers to the situation where the integration orders of the observables are different, but their corresponding balanced versions (with equal integration orders after filtering) are cointegrated in the usual sense. Within this setting, the long run linkage between the observables is driven by both the cointegrating parameter and the difference between the integration orders of the observables, which we consider to be unknown. Our results reveal three noticeable features. First, superconsistent (faster than √ n-consistent) estimators of the difference between memory parameters are achievable. Next, the joint limiting distribution of the estimators of both parameters is singular, and, finally, a modified version of the ‘‘Type II’’ fractional Brownian motion arises in the limiting theory. A Monte Carlo experiment and the discussion of an economic example are included.

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A novel technique to detect and localize periodic movements in video is presented. The distinctive feature of the technique is that it requires neither feature tracking nor object segmentation. Intensity patterns along linear sample paths in space-time are used in estimation of period of object motion in a given sequence of frames. Sample paths are obtained by connecting (in space-time) sample points from regions of high motion magnitude in the first and last frames. Oscillations in intensity values are induced at time instants when an object intersects the sample path. The locations of peaks in intensity are determined by parameters of both cyclic object motion and orientation of the sample path with respect to object motion. The information about peaks is used in a least squares framework to obtain an initial estimate of these parameters. The estimate is further refined using the full intensity profile. The best estimate for the period of cyclic object motion is obtained by looking for consensus among estimates from many sample paths. The proposed technique is evaluated with synthetic videos where ground-truth is known, and with American Sign Language videos where the goal is to detect periodic hand motions.

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How do visual form and motion processes cooperate to compute object motion when each process separately is insufficient? A 3D FORMOTION model specifies how 3D boundary representations, which separate figures from backgrounds within cortical area V2, capture motion signals at the appropriate depths in MT; how motion signals in MT disambiguate boundaries in V2 via MT-to-Vl-to-V2 feedback; how sparse feature tracking signals are amplified; and how a spatially anisotropic motion grouping process propagates across perceptual space via MT-MST feedback to integrate feature-tracking and ambiguous motion signals to determine a global object motion percept. Simulated data include: the degree of motion coherence of rotating shapes observed through apertures, the coherent vs. element motion percepts separated in depth during the chopsticks illusion, and the rigid vs. non-rigid appearance of rotating ellipses.

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When brain mechanism carry out motion integration and segmentation processes that compute unambiguous global motion percepts from ambiguous local motion signals? Consider, for example, a deer running at variable speeds behind forest cover. The forest cover is an occluder that creates apertures through which fragments of the deer's motion signals are intermittently experienced. The brain coherently groups these fragments into a trackable percept of the deer in its trajectory. Form and motion processes are needed to accomplish this using feedforward and feedback interactions both within and across cortical processing streams. All the cortical areas V1, V2, MT, and MST are involved in these interactions. Figure-ground processes in the form stream through V2, such as the seperation of occluding boundaries of the forest cover from the boundaries of the deer, select the motion signals which determine global object motion percepts in the motion stream through MT. Sparse, but unambiguous, feauture tracking signals are amplified before they propogate across position and are intergrated with far more numerous ambiguous motion signals. Figure-ground and integration processes together determine the global percept. A neural model predicts the processing stages that embody these form and motion interactions. Model concepts and data are summarized about motion grouping across apertures in response to a wide variety of displays, and probabilistic decision making in parietal cortex in response to random dot displays.

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How do visual form and motion processes cooperate to compute object motion when each process separately is insufficient? Consider, for example, a deer moving behind a bush. Here the partially occluded fragments of motion signals available to an observer must be coherently grouped into the motion of a single object. A 3D FORMOTION model comprises five important functional interactions involving the brain’s form and motion systems that address such situations. Because the model’s stages are analogous to areas of the primate visual system, we refer to the stages by corresponding anatomical names. In one of these functional interactions, 3D boundary representations, in which figures are separated from their backgrounds, are formed in cortical area V2. These depth-selective V2 boundaries select motion signals at the appropriate depths in MT via V2-to-MT signals. In another, motion signals in MT disambiguate locally incomplete or ambiguous boundary signals in V2 via MT-to-V1-to-V2 feedback. The third functional property concerns resolution of the aperture problem along straight moving contours by propagating the influence of unambiguous motion signals generated at contour terminators or corners. Here, sparse “feature tracking signals” from, e.g., line ends, are amplified to overwhelm numerically superior ambiguous motion signals along line segment interiors. In the fourth, a spatially anisotropic motion grouping process takes place across perceptual space via MT-MST feedback to integrate veridical feature-tracking and ambiguous motion signals to determine a global object motion percept. The fifth property uses the MT-MST feedback loop to convey an attentional priming signal from higher brain areas back to V1 and V2. The model's use of mechanisms such as divisive normalization, endstopping, cross-orientation inhibition, and longrange cooperation is described. Simulated data include: the degree of motion coherence of rotating shapes observed through apertures, the coherent vs. element motion percepts separated in depth during the chopsticks illusion, and the rigid vs. non-rigid appearance of rotating ellipses.

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Traditional motion capture techniques, for instance, those employing optical technology, have long been used in the area of rehabilitation, sports medicine and performance analysis, where accurately capturing bio-mechanical data is of crucial importance. However their size, cost, complexity and lack of portability mean that their use is often impractical. Low cost MEMS inertial sensors when combined and assembled into a Wireless Inertial Measurement Unit (WIMU) present a possible solution for low cost and highly portable motion capture. However due to the large variability inherent to MEMS sensors, such a system would need extensive characterization to calibrate each sensor and ensure good quality data capture. A completely calibrated WIMU system would allow for motion capture in a wider range of real-world, non-laboratory based applications. Calibration can be a complex task, particularly for newer, multi-sensing range capable inertial sensors. As such we present an automated system for quickly and easily calibrating inertial sensors in a packaged WIMU, demonstrating some of the improvements in accuracy attainable.