Processes of nitrogen loss from fertilizers applied to flooded rice fields on a calcareous soil in north-central China

Losses of nitrogen were investigated after applications of ammonium bicarbonate and urea to flooded rice at transplanting. Ammonia (NH₃) volatilization was determined by direct micrometeorological methods, and total loss of fertilizer nitrogen (N) was measured by¹⁵N balance. All the loss appeared to be in gaseous forms, since there was no evidence of leaching and runoff was prevented. The difference between N loss and NH₃ loss was thus assumed to be denitrification loss.Both NH₃ volatilization and denitrification losses were large, being 39% and 33%, respectively, of the ammonium bicarbonate N, and 30% and 33%, respectively, of the urea N applied by farmers' methods.Ammonia fluxes from the field fertilized with ammonium bicarbonate were very high for two days, and then declined rapidly as the NH₃ source in the floodwater diminished. Moderate fluxes from the field fertilized with urea continued over 6 days, but calculations showed that NH₃ transfer from floodwater to atmosphere was retarded during the middle period of the experiment, particularly on day 2 when a thick algal scum appeared on the water surface. The results indicate that this algal mass obstructed the transport of NH₃ across the water-air interface until the scum was dispersed by wind action. Nevertheless, the prolonged NH₃ losses on the urea treatment were due primarily to high floodwater pH values promoted by the strong algal growth during the daylight hours.Nitrogen-15 balance studies showed that incorporation of fertilizer into drained soil substantially increased recoveries of fertilizer N in rice plants and soil compared with incorporation of fertilizer in the presence of standing floodwater. Ammonia loss measurements on these treatments when urea was applied suggested that the improvement in fertilizer N efficiency was due mainly to reductions in NH₃ loss.     

Estimates of soil phosphorus for different soil series

Over a range of soil series, the responses to applied P were measured with Swedish turnips and potatoes in field experiments and with oats in a pot experiment. Phosphorus was extracted from soil samples, taken before the experiments were started, by acetic acid, Morgan's, bicarbonate, resin and lactate methods. The relationships between the amounts of soil P extracted and the responses to applied P showed that curved models, using reciprocals or logarithms of soil P, were generally superior to linear and quadratic models especially for the field experiment data. Including loss-on-ignition in the model significantly improved the relationships for some soil series.Reciprocal and logarithmic models were used to determine the ranges for classifying soil P into three classes and to calculate responses to soil P at each site. For the experiments with Swedish turnips, soil P and calculated responses were allocated to three classes and compared with the corresponding classification of the actual field responses. Using different ranges of critical values for classifying soil P for a specific series is shown to be at least as important as using the best method of extraction. The results illustrate how the reliability of a three-class system for predicting the P status of these acid, Scottish soils can be increased by using different class intervals for soil P for different series.     

Combined electromechanical dynamic fracture behavior of lead zirconate titanate (PZT)

Coupon specimens of poled and depoled lead zirconate titanate (PZT) are examined under combined stress wave and electric loading conditions. Mode-I crack initiation and fracture behavior is examined using ultrahigh-speed imaging and two-dimensional digital image correlation. The dynamic critical stress intensity factor () is extracted using measured displacement fields ahead of the impulsively loaded crack tip, and compared between poled and depoled plates that were either under no electric field, positive 0.46 kV/mm electric field, or negative 0.46 kV/mm electric field. Poled specimens had a poling direction and applied electric field direction normal to the crack front. The addition of an electric field resulted in a crack-enhancing effect, where the dynamic fracture toughness of poled specimens under 0.46 kV/mm was almost half that of samples with no electric field. Depoled samples experienced almost no change in dynamic fracture toughness with the addition of an electric field.     

Relation between saliva flow and flavor release from chewing gum

The objective of this study was to investigate whether or not parotid saliva flow is a significant determinant of flavor release from chewing gum. Cherry-flavored gum with 3 concentrations of citric acid (0.5, 1, and 2%) acting as a sialagogue was evaluated for sweetness and cherry flavor in duplicate by 13 subjects, using a computerized system for simultaneous time-intensity (TI) measurements and unilateral collection of parotid saliva. With increased acidity in the gum, maximum intensity of, and area under, the cherry flavor curve increased (p < 0.001), whereas total duration of sweetness decreased (p < 0.05). Large interindividual differences were found for parotid saliva flow in response to chewing gum. Mean unilateral parotid saliva flows in response to stimulation with water and gum with 0.5, 1, and 2% citric acid were 0.07, 0.30, 0.36, and 0.44 g/min, respectively. There was a significant positive correlation between saliva flow and time to reach maximum intensity of sweetness (p < 0.05) and of cherry flavor (p < 0.01), with "high-flow" subjects taking longer to reach maximum intensity than "low-flow" subjects for both attributes. We conclude that parotid saliva flow may affect the rate of flavor release, but not how much nor for how long flavor is released.     

A method to evaluate direct and indirect design dependencies between components in a product architecture

Methods for evaluating the strength of design dependencies in a product architecture have been widely studied in the literature; however, evaluating the effects of direct and indirect interactions between components/modules remains a challenge. In fact, indirect connections between components/modules are often overlooked in many cases when evaluating design dependencies. Having a more consistent way of defining a product architecture that considers both its direct and indirect connections is important, especially when analyzing redesign complexity and change propagation. In this study, we propose a systematic method to evaluate direct and indirect design dependencies between components in product architectures. Interfaces are classified into six different types based on a thorough review of the literature, and a method for evaluating design dependencies is introduced to estimate the relative importance of interfaces directly from a set of comparable products. Using an electrical circuit analogy, the proposed method can quantify both direct and indirect design dependencies between components within a product architecture. We compare design dependency results for different wireless computer mice to validate the effectiveness of the proposed method. The results show that using the proposed design dependency measure including direct and indirect effects provides more reliable design dependency results.     

Physicochemical characterization of an antagonistic human interleukin-6 dimer

A noncovalently bound dimeric form of recombinant human IL-6 interleukin-6 (IL-6D) was shown to be an antagonist for IL-6 activity, in a STAT3 tyrosine phosphorylation assay using HepG2 cells, under conditions where it does not dissociate into monomeric IL-6 (IL-6M). The fluorescence from Trp157, the single tryptophan residue in the primary sequence of IL-6, is altered in IL-6D, where the wavelength maximum is blue-shifted by 3 nm and the emission intensity is reduced by 30%. These data suggest that Trp157 is close to, but not buried by, the dimer interface. Both IL-6D and IL-6M are compact molecules, as determined by sedimentation velocity analysis, and contain essentially identical levels of secondary and tertiary structure, as determined by far- and near-UV CD, respectively. IL-6D and IL-6M show the same susceptibility to limited proteolytic attack, and exhibit identical far-UV CD-monitored urea-denaturation profiles with the midpoint of denaturation occurring at 6.0 +/- 0.1 M urea. However, IL-6D was found to dissociate prior to the complete unfolding of the protein, with a midpoint of dissociation of 3 M urea, suggesting that dissociation and dimerization occur when the protein is in a partially unfolded state. Based on these results, we suggest that IL-6D is a metastable domain-swapped dimer, comprising two monomeric units where identical helices from each protein chain are swapped through the loop regions at the "top" of the protein (i.e., the region of the protein most distal from the N- and C-termini). Such an arrangement would account for the antagonistic activity of IL-6D. In this model, receptor binding site I, which comprises residues in the A/B loop and the C-terminus of the protein, is free to bind the IL-6 receptor. However, site III, which includes Trp157 and residues in the C/D loop and N-terminal end of helix D, and perhaps site II, which comprises residues in the A and C helices, are no longer able to bind the signal transducing component of the IL-6 receptor complex, gp130.     

3D Shape Matching and Inspection Using Geometric Features and Relational Learning

In this paper we consider the problem of matching 3D sensed data with models and inspection for defects where the correspondence between models and data needs to be solved in robust and efficient ways. We explore the use of machine learning (in particular, relational learning) as an efficient method for solving correspondence (and so, pose estimation) as well as automatically generating rules for acceptable shape variations from training data. As an additional but necessary issue, we also consider the use of view-independent covariance methods for the extraction of surface features used to determine shape signatures which correspond to curvature-like surface attributes. Such features are utilized in the relational learning model.     

Tween consumers: catalog clothing purchase behavior

The purpose of this study was to compare the catalog shopping behavior of students in their tween years (i.e., between childhood and adolescence; ages 12-14) with that of older students (ages 15-18). Junior high and high school students who had purchased clothing from a catalog in the past 12 months responded to a questionnaire that examined the label information sought and product-specific attributes considered. Results indicated that tweens were more concerned with style, brand names, and the latest fashion than were older students. This finding was especially interesting, as these attributes all relate to status; the tweens were more interested than the older students in wearing the latest fashions, being in style, and gaining the prestige of wearing brand-name clothing. This supports previous findings indicating that the tween years are a time when peer pressure and "fitting in" are very important.     

Identity metamorphoses in digital disruption: a relational theory of identity

Digital technologies have disrupted a variety of organizations; however, Information Systems research has yet to explore in-depth why this may be occurring or the implications of this process for those involved. In this paper we present an exemplary case of digital technology disruption in a newspaper company – an organization in the midst of an identity crisis. On the basis of ethnographic data, we explore the changes that resulted from the introduction of the digital medium, and how this has led to the evolution of the newspaper, as well as the metamorphosis of identities of the company, the company’s practitioners, and the consumers of the company’s content. Our findings suggest that shifts in the evolutionary trajectory of an organization can be traced to the rate and nature of identity metamorphoses among its key actors. Hence, in order to navigate and adapt to digital disruptions, we argue that an ongoing strategic renegotiation of the identities of all the actors involved is not only possible, but is required for an organization’s survival. In doing so, we provide a relational theory of identity.