The goal of this study was to define an empirical model to calculate the leafareainrice from linear leaf measure in genotypes used by farmers in Brazil. Through the leaf dimensions it is possible to identify the final crop yield from the LAI. Therefore, the leaves shape is closely related to the production of photoassimilates that will be converted into grain yield. Field experiments were carried out in four counties of Rio Grande do Sul with twelve-three varieties of ricein four growing seasons. We measured the length and width of leaves to construct the model. The relationship between leafarea and linear dimensions was shaped using a linear model for each genotype, and general model grouping all genotypes. The model accuracy was measure following statistics: Root Mean Square Error, BIAS, modified index of agreement and coefficient r. The non-destructive method for individual leaves was appropriate for estimating the leafareainrice. Moreover, the general equation was estimated and canbe used for all modern genotypes of ricein Brazil.
Determination of leafarea is important in different areas of researching with plants (Pedro Junior et al. 1986). Knowledge of leafarea is fundamental in studies of plant growth because it is one of the most important characteristics in the evaluation of vegetal growth (Portela 1999, Bhatt and Chanda 2003, Bianco et al. 2008a,b, 2009). Leafarea estimation canbe performed by different methods, so that non- destructive methods are more interesting to be used because there is no need to collect the plant, or parts of plants, for measurement. Among non-destructive methods for leafarea estimation, the determination of mathematical equations relating leaf linear dimensions is the most used methods (Bianco et al. 2002, 2004, 2007a,b, 2008a,b, 2009, Duarte et al. 2009).
Fuzzy logic depends upon the context that cannot bedefined precisely and is a form of knowledge representation suitable for notions. It is a Problem-solving control system methodology. We move to fuzzy due to the following reasons. Conceptually fuzzy logic is easy to understand, Fuzzy reasoning mathematical concepts are simple. Fuzzy logic does not need any far-reaching approach, it in an intuitive approach. It need not start any thing from scratch and flexible with any system and easily layer on more functionality. Even on careful inspection most things are imprecise when looked closely but fuzzy logic tolerates on imprecise data. Rather than tacking it onto the end fuzzy reasoning builds this understanding into the process. Fuzzy system canbe created to match any set of input-output data, nonlinear functions of arbitrary complexity canbe modeled in fuzzy logic. Fuzzy logic toolbox software has a technique like Adaptive Neuro-Fuzzy Inference Systems(ANFIS), which is an adaptive technique which ease the above process. Neural networks is in direct contrast with fuzzy logic which generates opaque data taking training data as input with impenetrable models, fuzzy logic rely on the experience of people who already understand the system thus built on top of the experienced experts. A fuzzy system does not replace conventional control methods in turn blend with the conventional control techniques. It simplifies their implementation and augments them in many cases. Fuzzy logic is the basis for human communication thus based on natural language. Many other statements about fuzzy logic are underpinned by this observation, because it is easy to use and built on the structures of qualitative description used in everyday language. A fuzzy logic system (FLS) is defined as the nonlinear mapping of an input data set to a scalar output data. A FLS as in figure 2.1 consists of four main parts: fuzzifer, rules, inference engine, and defuzzfier.
The models were generated using length (L), width (W) and the product of length versus width (L.W) as independent variables, and the measured LA as dependent variable. Linear, quadratic, exponential and power models were obtained using the program Sigma Plot®. Models with distinction between ovate and lanceolate leaves were generated using 186 ovate leaves and 117 lanceolate leaves, while models without such distinction were generated using 303 mixed leaves. The aim was to identify which independent variable is best correlated with LA and whether a general modelcanbe used to determine canola LA or if it is necessary to use one model for each type of leaf. The slope was estimated by forcing the line to pass through the origin (null intercept), because it is more correct according to Richter et al. (2014), since if there are no linear dimensions, there is no leafarea.
In the validation of the models based on the 1200 leaves collected in the first experiment, the linear, power, quadratic, and cubic models in function of LW product were also the ones that best fit the established criteria: linear coefficient closer to zero, angular coefficient closer to one, Pearson linear correlation coefficient and coefficient of determination closer to one, besides the lower absolute mean error, and square root of mean square error and Willmott’s index d closer to one (Table 3). Thus, it is indicated that the models of dwarf pigeon pea leafarea estimation in function of the product of the central leaflet length times the width should be preferentially used when the higher accuracy is the objective in relation to the other models that are based only on length or width of the central leaflet, as confirmed by Schwab et al. (2014) and Schmildt et al. (2015). However, the power model based on the width of the central leaflet canbe used, with a small reduction of accuracy, but being less laborious, since only one measured variable is required.
This research aimed to determine an equation to estimate the leafarea of Erythroxylum simonis using the length and width of leaf blades. Two hundred leaf blades of this species were collected in Mata do Pau-Ferro, a State Park located in Areia, PB, Brazil. Regression analyses were used to determine the estimation equations. The linear, linear without intercept, quadratic, cubic, power and exponential statistical models were used. The criteria used for model selection were based on an examination of the coefficient of determination, the Akaike information criterion and standard error of the estimate. All the equations presented canbe used to estimate the leafarea of E. simonis. From a practical point of view, the linear regression equation without intercept involving the product between length and width is recommended, using the equation Y=0.6426*LW, which corresponds to 64.26% of the product between length and width, with a coefficient of determination of 0.9936.
In this study, the regression equation that best represented an estimation of the leafarea for C. canephora was the linear model i =0.6723+0.6779x i , where xi is the product of the longest length along the main rib and the greatest width of the leaf blade (L.W). Establishing this relationship involved destructive analysis of the leaves. It should be noted that the removal or destruction of the leaves is necessary only to determine allometric relationships. Once this mathematical expression has been established, the leafarea of clonal varieties of C. canephora in other studies canbe estimated without detaching the leaves, using only a ruler or a pocket tape measure to get the longest length and greatest width of the leaf blade. Antunes et al. (2008), when studying the Conilon 513 and CC 3580
ABSTRACT - The aim of this study was to evaluate estimations of leafareain rapeseed (Brassica napus L.) and the potential for application to different genotypes, environmental conditions and types of crop management. In experiments conducted during 2013, 2014, 2016 and 2017, three genotypes of rapeseed, five doses of nitrogen and three sowing dates were used. Leaves were randomly collected from different plants and positions on the plants. The leafarea (LA), and maximum width (W) and length (L) were determined for each leaf, and the product of L and W (LxW) was calculated. Fifty-six equations for estimating LA in rapeseed, where the independent variables were W, L or LxW, were compiled from the bibliography and evaluated in this work. The evaluation was made using the following statistics: significance of the linear (a) and angular (b) coefficients of the regression around the 1:1 line, concordance index (d), bias index (BIAS), mean absolute error (MAE), mean relative error (MRE), random mean squared error (MSE r ) and systematic mean squared error (MSE s ). Only 11 equations showed the a and b coefficients as not being different from 0 and 1 respectively. However, only 10 were suitable, as they displayed the lowest values for d, BIAS, MAE and RME, and the MSE s was smaller than the MSE r . The MAE ranged from 5.4 cm² to 16.2 cm², well within the error range for generating the equations. LA in rapeseed canbe estimated by general biometric equations without considering the specificity of the genotype or the morphological type of the leaf.
Peaks were observed in the UV-visible spectrum for media where PA14 was grown, either alone or as part of the polymicrobial infection model (figure 5). These changes were observed at 315 nm, 368 nm and 698 nm, and correspond to the absorbance peaks of pyocyanin found at 238 nm, 316 nm, 347 nm, 368 nm and 690 nm . It is clear therefore from the UV-visible spectrum that pyocyanin is present within the ASM media following the growth of P. aeruginosa at 69 hours. We investigated the impact that pyocyanin had on the measured impedance by firstly measuring the impedance of pyocyanin alone in ASM at different concentrations, from 1000 m M to 10 m M. Only a slight change in the impedance was seen at low frequencies and high concentrations of pyocyanin (1000 m M to approximately 500 m M), which was unrepresentative of the changes observed when the impedance of a culture containing PA14 (alone or polymicrobial) was measured (data not shown). We reasoned that this could be because the pyocyanin existed in its oxidised form and therefore no reduced pyocyanin was available to balance the redox reaction at each electrode. Alternatively, pyocyanin could have been just one of multiple electroactive compounds that transferred electrons in a chain, with the compounds at an appropriate redox potential compared to the electrode causing the change in impedance. An alternative situation was explored, were pyocyanin was added directly to a late log culture of P. aeruginosa and S. aureus in order to assess the effect it had on the impedance. Cultures of P. aeruginosa (PA14) and S. aureus (RN4220) were grown in ASM microaerophilically overnight to late log phase in 24 well plates. After measuring the impedance of the media, and the impedance of the late log phase cultures, pyocyanin was added to the cultures at concentrations of 100 m M and 300 m M and a further impedance measurement was immediately carried out. The results indicated a clear change in the impedance for each of the electrode chambers (figure 6), similar to the changes in phase observed through the growth of PA14 and the polymicrobial infection model. It was noticed when similar experiments were carried out in LB media that the blue pigment resulting from the addition of pyocyanin changed from blue to clear in all but the top layer of each of the cultures. On shaking, the pyocyanin was rapidly oxidised and returned to its original blue pigment, before gradually being reduced again. This was apparent after five minutes for the culture of S. aureus while P. aeruginosa took longer to lose its pigment and did so to a lesser degree.
Highly reproducible 2-DE patterns with high resolution were obtained from leaf sheaths and roots of JHCA, GLA4 and their hybrid F 1 . Over 1,200 and 1,000 protein spots were reproducibly detected in 2-DE patterns for leaf sheaths and roots, respectively. Typical 2-DE separation of proteins from hybrid F 1 samples is shown in Figure 1. The differential protein spots among JHCA, GLA4 and hybrid F 1 samples of leaf sheaths and roots are shown in Figure 2A-B. Following a detailed analysis with PDQuest 7.1 software, a total of 30 and 31 spots were detected from leaf sheaths and roots, respectively, with differential expression levels in 2-DE maps among the two parents and hybrid F 1 . Furthermore, all these differentially expressed proteins were found in the hybrid F 1 . They were assigned numbers with L (L1 to L30) for leaf sheath and R (R1 to R31) for roots in 2-DE maps of the hybrid F 1 . The distribution of protein variants in the 2-DE maps is also shown in Figure 1. These polymorphic proteins canbe divided into qualitative and quantitative variations (Table 1 and Figure 2). As shown in Figure 2A, spots L10 and L11 both showed qualitative variation patterns with presence/ absence variations (P/As). They both showed ‘absence’ in JHCA but ‘presence’ in GLA4 and showed ‘presence’ in the hybrid F 1 . Therefore, ‘P’ is dominant over ‘A’, and P/As are monogenic and dominant molecular markers. Spots L7-L8 in Figure 2C and spots L29-L30 in Figure 2D also exhibited qualitative variations with P/A character. As shown in Figure 2E, spot L27 showed quantitative variation (qV) in the relative abundance. The relative abundance of spot L27 was ‘high’ in JHCA but ‘low’ in GLA4 and ‘high’ in the hybrid F 1 . Therefore, a high amount was dominant over a low amount, and qVs were also monogenic and dominant molecular markers.
Leafarea changes affect solar radiation interception (K*), interception efficiency (ε int ) and extinction coefficient (k) of an orange tree top (cv. Pêra-Rio). In order to measure radiation transmitted through the crown a mobile sensor was horizontally installed below the crown and 0.65 m from the trunk, moving around it at 3 rpm. The model used for k determination (Monsi & Saeki theory) was assessed with independent data to estimate K*. With absence of leaves, it was detected an intense interference of trunk and branches on ε int , with a minimum value of 0.52. The results were also distinct in obtaining k, when the best fit was found
Fluidization is an operation by which a bed of solid particles acquires fluid like properties by passing a gas or liquid through it Their liquid like behavior and continuous movement of particles allow for good heat transfer and temperature control. The .occurrence of gas bypass or broadening of the residence time distribution due to bubble formation , coalescence and growth is unwanted for heterogeneous state attained . To negate these effects control over the number or size of bubbles is needed. There are different ways to accomplish this ,such as baffles or special gas distributors (for example a fractal injector ) in the bed or effect of superimposed fields for the particles exhibiting the specific properties.
According to Field and Jörg, the Dutch law of corporate liability, unlike English Law, “rests on those who have the power to control the general practices of the corporation. … It was not necessary to identify any individual as responsible for the sloppy supervision: it could be seen simply as a collective failure by management.” (1978:167) This reinforces French’s arguments that corporate intentions and responsibility canbe investigated within a system of rules and commands, which are determined by corporate policy. But in English law, at present, there is neither the political nor the legal will to undertake such prosecution, a reluctance one can see yet again in the aftermath of the rail crash in Hatfield on 17 October 2000. Four people have been killed and many others injured. Gerald Corbett, Railtrack’s chief executive during the inquiry refused to accept that the rail industry’s safety problems were due to management failure. He said, “it’s more of a system rather than a management failure… . (Harper 2001a:4) When Robert Owen, QC, counsel for the inquiry asked him who has responsible for the crash he answered: “I think it’s me. It’s clear in the public’s mind that they think it’s me (ibid).” Three months later it was confirmed that Railtrack was aware of the unsafe conditions of the track but had failed to act to remedy the situation till after the disaster. The report published by the HSE revealed that “the Hatfield track was so bad at the point of the crash that it shattered into 300 pieces, like a sheet of glass, and was therefore the direct cause of the accident.” (Harper 2001b:1)
Similar to this one, there is interviewee E who also works in a startup, with a flat structure, described the organization’s leadership as “very close, of learning and trust”. Furthermore, such leadership has influenced E to become more self-sufficient in the working tasks, leading to the sense of empowerment and a “faster growth of the team members”, just like interviewee D. This canbe seen on Yukl’s findings (2013) on the relation of empowerment and the level of autonomy and individual growth, which is a positive and increasing relation, especially in a smaller organizational environment like a startup. Moreover, what interviewee E values and perceives as a successful leadership practice is to have a holistic view of all the team members their individual and collective needs, just like Van, V. M., & Ahuja, A. (2010) and Kaiser (2008) tell us on the basic notions of leadership and the role of the leader as a potentiator for common good. On the last question, interviewee E didn’t have a very positive view on holacracy and its effectiveness on the operations of a organization and highlighted the importance of having someone in charge of taking final decisions and an overview of what is happening in different tasks or roles. However, E justified these statements based on the need for having someone capable of leading the organization forward and on the same direction, while defining and setting the rhythm for reaching “the next steps”. This means that E wouldn’t feel comfortable in a framework such as a holacracy and, clearly would prefer to bein a position of having someone to rely on and to lead the way, which matches the majority of the first interviewees, who also value guidance as a leadership trait. This, of course, while having still the possibility of ownsership and an empowered figured in the team.
“Can there be a feminist aesthetic?” analyzes the difficulty of finding an ontological posi- tion from which to write about photography created by women. It interrogates the discomfort of inhabiting, socially, and in art and literature, the position of the embodied feminine, and seeks through aesthetic analysis to mine this discomfort. The essay argues that despite the social and intellectual discomfort of articulating a space of the feminine, in that this space is always already coded as oppressed, there is a value in interpreting photography created by women through the lens of feminist resistance. The article concedes that defining the word woman is always a risk, in that the term reflects manifold and contradictory embodied experiences. And yet, within this avowed risk emerges the only space of possible resistance to oppression, the opportunity to cre- ate a rearrangement of the visible so that the category of the oppressed woman, however phantas- matic, is re-envisioned as sovereign. However, each act of re-envisioning woman must be cultur- ally specific. Hence, the essay concludes with an interpretation of Ethiopian photographer Aida Muluneh’s series of images Dinkinesh (or, “you are beautiful”), evoking the remains of an Ethio- pian hominid that were long considered to be the oldest of human ancestors. Muluneh reclaims this distant ancestor as Ethiopian, dressing her in an extravagant red gown, using photography to re-envision Dinkinesh’s fall into history, granting this ancestor the power to haunt modernity.
The excellent performance of one gene in survival prediction immediately raises the question whether this gene was included in all studies. If this were not the case, then the gene would not be present in the merged data set, which could explain the rather disappointing prediction accuracy figures obtained after merging. Indeed, this gene was absent in a number of data sets. In one other data set where it was present, its performance as a single-gene signature in risk prediction was consistently high (GSE1992, AUC = 0.68, HR = 3.24, P-value = 0.008, CI = 1.36–7.72). The influence of this gene could also explain the good performance obtained after merging selectively the sets GSE4335 and GSE1992 (see above). A possible reason that adding the Vijver data set did not improve the prediction accuracy might be due to the fact that this gene was absent in the original Vijver study. As expected, the Cox coefficient of this gene was negative for all data sets in which it was present, meaning low risk associated with high expression levels. The case of CYB5D1 suggests that the absence of key risk or survival genes from some microarray platforms may in general be a major limiting factor in data merging, demonstrated here on the specific example of survival prediction for breast cancer patients.
torsion of the tendril must remain constant, and the twisting causes the formation of two helices, where the handedness of one helix cancels the opposite handedness of the other, keeping the total twist constant. The model proposed by Goriely et al. describes the hand reversal of helical twist for elastic and slender filaments. While the filament is under tension, it is twisted in a linear configuration. If the applied tension is released, eventually the linear shape becomes unstable, and the value of the tension at which the transition from a straight line to a helical structure happens is known as the critical tension. The release of the elastic energy of the filament leads to a change from the linear shape to the formation of two helices, of reverse handedness, by rotation of the perversion. The number of turns in the helices is a function of the applied tension as the rotation of the perversion results in an increased number of turns in the helices. The value of the critical tension is given by = K/ξȞ, where K UHSUHVHQWVWKHLQWULQVLFFXUYDWXUHRIWKHILODPHQWDQGī = 1/(1 + ıPHDVXUHVWKHUHODWLRQEHWZHHQWKH bending and rotation coefficients, ZLWK ı UHSUHVHQWLQJ WKH 3RLVVRQ FRHIILFLHQW ,Q WKH FDVH RI SODQW tendrils, the differential growth of diverse areas in the tendril is responsible for the intrinsic curvature of the system. Recently, it was reported that the intrinsic curvature of some old plant tendrils species can occur via asymmetric contraction of an internal fiber ribbon of specialized cells, which generates different shrinkages of the inside relative to the outside tendril ribbon, allowing its overwinding, rather than unwinding, under tension .
Pathological diagnosis is the medical specialty that deals with the examination of gross and microscopic lesions (Miller et al., 2009). It also consists in the further microscopic study of tissues and cells, in order to provide a complementary means for diagnosis. The solid background of expertise is constructed based on medical literature, educational programs, training activities, meetings, technical rules and the cognitive skills of the pathologist which allows him to describe lesions, interpret histological slides and make decisions. In this long and complex process, the pathologist takes into account the animal data, clinical history (including physical exam), results of other complementary exams (including biochemical analysis and x-rays), using a strategy to arrive at a diagnosis which is not qualitatively different from those used by clinicians (Pena & Andrade-Filho, 2009).
ABSTRACT: The objective of this study was to create a single mathematical equation able to estimate the leafarea of different cassava cultivars from one lineal dimension without destroying any plant tissue. Two hundred leaves per cultivar from ten cultivars were used to calibrate the model and more than one hundred leaves per cultivar were used to test its predictive capacity as independent data. All equations were the result of the nonlinear correlation between the leafarea and the length of its central lobe. To validate it as a “general” equation, another set of five cultivars were used. A “specific” equation for each cultivar was also calibrated to compare with the “general” equation’s performance. Cultivar Vassourinha has remarkably different leaf morphology from the other nine cultivars, making the “general” equation’s tendency line deviate and lowering its coefficient of determination. Therefore, one more equation was generated excluding that cultivar and, as a result, it was not possible to estimate the leafarea from all the cultivars using only the “general” equation. The “general without Vassourinha” equation has a high accuracy level when estimating leafarea of the other nine cultivars, plus the extra five cultivars that were included to validate the general equation; all of them present similar leaf morphology. Due to its importance, Vassourinha cultivar’s “specific” equation should be used when estimating leafarea for this cultivar or other cultivars with similar leaf morphology.