Power Function Model Research Articles

Variation in the seston C:N ratio of the Arctic Ocean and pan-Arctic shelves

Studying more than 3600 observations of particulate organic carbon (POC) and particulate organic nitrogen (PON), we evaluate the applicability of the classic Redfield C:N ratio (6.6) and the recently proposed Sterner ratio (8.3) for the Arctic Ocean and pan-Arctic shelves. The confidence intervals for C:N ranged from 6.43 to 8.82, while the average C:N ratio for all observations was 7.4. In general, neither the Redfield or Sterner ratios were applicable, with the Redfield ratio being too low and the Sterner ratio too high. On a regional basis, all northern high latitude regions had a C:N ratio significantly higher than the Redfield ratio, except the Arctic Ocean (6.6), Chukchi (6.4) and East Siberian (6.5) Seas. The latter two regions were influenced by nutrient-rich Pacific waters, and had a high fraction of autotrophic (i.e. algal-derived) material. The C:N ratios of the Laptev (7.9) and Kara (7.5) Seas were high, and had larger contributions of terrigenous material. The highest C:N ratios were in the North Water (8.7) and Northeast Water (8.0) polynyas, and these regions were more similar to the Sterner ratio. The C:N ratio varied between regions, and was significantly different between the Atlantic (6.7) and Arctic (7.9) influenced regions of the Barents Sea, while the Atlantic dominated regions (Norwegian, Greenland and Atlantic Barents Seas) were similar (6.7–7). All observations combined, and most individual regions, showed a pattern of decreasing C:N ratios with increasing seston concentrations. This meta-analysis has important implications for ecosystem modelling, as it demonstrated the striking temporal and spatial variability in C:N ratios and challenges the common assumption of a constant C:N ratio. The non-constant stoichiometry was believed to be caused by variable contributions of autotrophs, heterotrophs and detritus to seston, and a significant decrease in C:N ratios with increasing Chlorophyll a concentrations supports this view. This study adds support to the use of a power function model, where the exponent is system-specific, but we suggest a general Arctic relationship, where POC=7.4 PON0.89.

Constructing 'Proper' ROCs Using Weighted Power Functions

Background: Receiver operating characteristic (ROC) analysis is the standard method for describing the accuracy of diagnostic systems where the decision task involves distinguishing between two mutually exclusive possibilities. The popular binormal curve-fitting model usually produces ROCs that are improper in that they do not have the ever-decreasing slope required by signal detection theory. Not infrequently, binormal ROCs have visible hooks that falsely imply worse-than-chance diagnostic differentiation where the curve lies below the no-information diagonal. Objective: To present and evaluate a two-parameter, weighted power function (WPF) model that always results in a proper ROC curve with a positive, monotonically decreasing slope. Design/Method: Computer simulation study comparing results from binormal and WPF models. Results: The WPF model produces ROC curves that are less biased and closer to the true values than curves obtained using the binormal model. The better performance of the WPF model follows from its design constraint as a necessarily proper ROC. Conclusions: The WPF model fits a broader variety of data sets than previously published power function models while maintaining straightforward relationships among the original decision variable, specific operating points, ROC curve contours, and model parameters. Compared to other proper ROC models, the WPF model is distinctive in its simplicity, and it avoids the flaws of the conventional binormal ROC model.

Desorption behaviour of lead in two calcareous soils as affected by Pb level without and with compost supply

A laboratory study was performed to investigate the influence of soil texture (sandy loam vs. clay loam), Pb supply (as Pb(NO3)2 without or with compost) and Pb levels on the extraction of available Pb by diethylene triamine pentaacetic acid (DTPA) and its desorption patterns at ten shaking periods. The soils were polluted with five Pb levels without or with compost and incubated for 1 month. Kinetic models commonly used to study the release of the nutrients were used in this study. Results showed that Power function model described the pattern of Pb desorption better than other models. The amount of extracted Pb increased as the Pb levels increased and was found to be higher in sandy loam soil treated with Pb without compost than that of clay loam soil treated with Pb with compost. The a value (Pb desorption constant) was the highest in sandy loam soil amended with Pb without compost. The lowest value of a, however, was observed in clay loam soil amended with Pb with compost. The ab coefficient (initial desorption rate of Pb) was higher in sandy loam than clay loam soil, demonstrating higher initial release rates of Pb in the coarser-textured soil. Addition of Pb without compost resulted in a higher increase in ab value in comparison with Pb with compost, in both the soils.

Role of chelating agents on release kinetics of metals and their uptake by maize from chromated copper arsenate-contaminated soil

Kinetic aspects of metal release were investigated to understand the effects of synthetic chelating agents (EDTA, EDDS and NTA) and low molecular weight (LMW) organic acids (oxalic and citric acids) on the release kinetics of Cr, Cu and As in chromated copper arsenate (CCA)-contaminated soil, as well as their uptake by maize (Zea mays L.). The results showed that the release of metals from soil was better described by parabolic diffusion, power function or simple Elovich model than by the first- and second-order models, indicating a heterogeneous diffusion of metals. Synthetic chelating agents afforded a higher release of Cu than that of LMW organic acids, whereas citric acid was the most effective chelating agent for Cr and As release. The most effective treatments for stimulating metal uptake in plant shoots were EDDS for Cu, EDTA for Cr, and citric acid for As, as indicated by the removal efficiencies of 0.046%, 0.036%, and 0.004%, respectively. However, Zea mays is not an attractive species for chelate-enhanced phytoremediation of CCA-contaminated soils due to its low phytoextraction rate, even in the presence of chelating agents and ligands.

Pre-classification improves relationships between water clarity, light attenuation, and suspended particulates in turbid inland waters

Relationships between water clarity, light attenuation, and concentration of suspended particulates are important in water optics and remote sensing, but are not well described yet, especially for optically complex turbid inland waters. In this study, based on 3-year data from Chinese lakes (Lake Taihu, Lake Chaohu, and Three Gorges reservoir), we propose a new approach to describe the inter-relationships of these bio-optical variables. This approach includes a pre-classification step of the waters into three types based on a semi-analytical parameter C s before establishing the relationships. Our results showed that the pre-classification of waters increased model accuracies both for Z SD (Secchi depth) versus K d (diffuse attenuation coefficient) and K d versus TSM (total suspended matter concentration). The quasi-theoretical model described better the relationship between Z SD and K d than the empirical model. For the K d versus TSM relationship, linear models proved suitable for the Type 2 and Type 3 waters, whereas the power function model gave a better fit for the Type 1 water. Testing of the proposed relations with an independent dataset showed mean absolute percentage errors (MAPE) mostly below 30%. The findings of this study clarify the relationships between Z SD, K d, and TSM, and improve our bio-optical understanding of complex turbid inland waters.

Copper desorption kinetics in wheat (Triticum aestivum L.) rhizosphere in some sewage sludge amended soils

Rhizosphere has different chemical and biological properties from bulk soils. Information about copper (Cu) desorption characteristics in the rhizosphere soils is limited. The objectives of this study were to determine Cu desorption characteristics and the correlation of its parameters with Cu extracted by DTPA-TEA, AB-DTPA and Mehlich 3 in bulk and rhizosphere amended soils with sewage sludge (10 g of sewage sludge was added to 1 kg soil) under greenhouse conditions in a rhizobox. The kinetics of Cu desorption in the rhizosphere and bulk was determined by successive extraction with DTPA-TEA in a period of 1 to 504 h at 25 ± 1 °C. The results showed that Cu extracted using several chemical extractants in the rhizosphere were significantly (P < 0.05) lower than in the bulk amended soils. In addition, Cu extracted using successive extraction in the rhizosphere were significantly (P < 0.01) lower than in the bulk soils. The best model for describing extraction data for the bulk and rhizosphere soils was the parabolic diffusion equation. Desorption kinetics of Cu conformed fairly well to first order and power function models. The results indicated that Cu diffusion rate in the wheat rhizosphere soils lower than in the bulk soils. Cu desorption rate in parabolic diffusion ranged from 0.326 to 0.580 mg kg−1 h−1/2 in the bulk soils, while it ranged from 0.282 to 0.490 mg kg−1 h−1/2 in the rhizosphere soils. Significant correlation (P < 0.05) between determine R values of parabolic diffusion and Cu desorption during 504 h with extracted Cu using DTPA-TEA, AB-DTPA and Mehlich 3 were found in the bulk and the rhizosphere soils. The results of this research revealed that Cu desorption characteristics in the wheat rhizosphere soils are quite different from bulk soils amended with sewage sludge.

Restoration in soil and plant properties in landslide damaged forest ecosystem

The pattern of natural restoration in soil and plant components was studied in five landslide-damaged (1-58-year-old) sites in the tropical moist sal (Shorea robusta) forest ecosystem of Nepal Himalaya .Rate of restoration in soil properties was faster in the early successional stages (1-15 year) than late stages while plant biomass recovered rapidly after 15-year age. Based on the recovery in ecosystem properties; the 58- year-old landslide damaged site demonstrated the re-establishment of an ecosystem showing closer affinity with the mature sal forest. On the basis of best fit power function models it was concluded that the estimated times for the 58-year old site to reach the level of undisturbed matured sal forest would be about 30-35 years for microbial biomass (C and N) and plant biomass and about 100-150 year for soil organic Carbon and total N. Higher accumulation of soil microbial biomass, plant biomass and high N-mineralization rate at late successional stages indicated the re-establishment of an ecosystem with enriched soil and restitution of nutrient cycling during the course of ecosystem restoration DOI: http://dx.doi.org/10.3126/njbs.v2i0.7488 Nepalese Journal of Biosciences 2 : 40-45 (2012)

Removal of heavy metal ions from aqueous solutions with multi-walled carbon nanotubes: Kinetic and thermodynamic studies

Multi-walled carbon nanotubes were used successfully for the removal of Copper(II), Lead(II), Cadmium(II), and Zinc(II) from aqueous solution. The results showed that the % adsorption increased by raising the solution temperature due to the endothermic nature of the adsorption process. The kinetics of Cadmium(II), Lead(II), Copper(II), and Zinc(II) adsorption on Multi-walled carbon nanotubes were analyzed using the fraction power function model, Lagergren pseudo-first-order, pseudo-second-order, and Elovich models, and the results showed that the adsorption of heavy metal ions was a pseudo-second-order process, and the adsorption capacity increased with increasing solution temperature. The binding of the metal ions by the carbon nanotubes was evaluated from the adsorption capacities and was found to follow the following order: Copper(II) > Lead(II) > Zinc(II) > Cadmium(II). The thermodynamics parameters were calculated, and the results showed that the values of the free energies were negative for all metals ions, which indicated the spontaneity of the adsorption process, and this spontaneity increased by raising the solution temperature. The change in entropy values were positives, indicating the increase in randomness due to the physical adsorption of heavy metal ions from the aqueous solution to the carbon nanotubes’ surface. Although the enthalpy values were positive for all metal ions, the free energies were negative, and the adsorption was spontaneous, which indicates that the heavy metal adsorption of Multi-walled carbon nanotubes was an entropy-driving process.

Sorptive removal of ciprofloxacin hydrochloride from simulated wastewater using sawdust: Kinetic study and effect of pH

The present work describes dynamic uptake of the antibiotic drug ciprofloxacin hydrochloride (CH), by using a cost-effective agricultural by-product . sawdust (SD). The sawdust was characterised by FTIR and SEM analysis. The sorbent particles were highly porous with average pore diameter of nearly 10 &#402;&#202;m. The optimum pH and solid/liquid ratio for sorption of CH were found to be 5.8 and 2.0, respectively. The dynamic drug uptake data was applied to various kinetic models and their order of fitness was found to be pseudo second order &gt; Elovich equation &gt; power function model, as indicated by their regression values. The experimental equilibrium uptake values (qe) were in close agreement with those evaluated from the pseudo second order equation for initial sorbate concentrations of 10 and 20 mg&#129;E.-1 at 33&#129;&#8249;C. The drug uptake mechanism was found to be attractive non-electrostatic interactions, involving H-bonding interactions between H atoms and other electronegative species such as F, O and N of the drug molecule. The mechanism is discussed on the basis of pHpzc of sawdust and zwitterionic nature of drug CH. Mass transfer analysis was carried out using the drug uptake data obtained with sorbate concentrations of 10 and 20 mg&#129;E.-1. The used sorbent could be regenerated using 1.0 mol&#129;E.-1 HCl solution with a regeneration efficiency of nearly 85%.

Comparative study of metal micronutrients release from two calcareous soils

Adsorption and release are the most influential reactions controlling zinc (Zn), manganese (Mn) and copper (Cu) availability in soils. Characteristics of native Zn, Mn and Cu release by ethylenediaminetetraacetic acid (EDTA) in two calcareous soils for periods from 1 min to 24 h were studied. The pattern of Zn, Mn and Cu release from both soils fitted well with power function, Elovich and parabolic diffusion models. The magnitude and rate of release was greatest for Mn, followed by Zn and Cu, respectively. This trend suggests a higher ability of the studied soils to replenish soil solution Mn, compared with Zn and Cu. The results showed that higher Mn release in clay soil compared with sandy loam soil was considerably related to higher initial Mn release rates in the former compared with the latter. However, Cu release rates of the two soils at initial times were not significantly different. Higher Cu release in clay soil was, therefore, attributed tohigher Cu release rates at subsequent time intervals. It is assumed that the different Zn release rates of these soils were due to consistent differences in Zn release rates throughout the release periods.

반복하중에 따른 철도 노반재료의 소성침하예측

If the railways consisting of soil subgrade is applied to repetitive loading, elastic deformation and plastic deformation will occur at the same time. So the repeat traffic loading condition should be considered to predict the long-term deformation on railway roadbed. In this study, laboratory data from the repeated load triaxial tests and cylinder model test were used to predict accumulated settlement on railway foundation and results were analyed based on the nonliear models and stress state considered. It has proposed predict model using power function model on plastic settlement of roadbed materials.

A predictive model for the formation potential of dichloroacetamide, a nitrogenous disinfection by-product formed during chlorination

Nitrogenous disinfection by-products have increasingly become a public health concern in the drinking water industry because they have been found to be more geno- and cytotoxic than most of the currently regulated disinfection by-products. Dichloroacetamide, a nitrogenous disinfection by-product which is formed during chlorination in water treatment, has increasingly received attention due to its elevated genotoxicity and cytotoxicity relative to the currently regulated disinfection by-products. In this study, a power function model with parameters of dissolved organic nitrogen, dissolved organic carbon, bromide, soluble microbial products, and aromatic proteins was developed to successfully predict dichloroacetamide formation potential. The inclusion of soluble microbial product and aromatic protein into the model significantly improved the prediction, suggesting that soluble microbial product and aromatic protein play a significant role in the formation of dichloroacetamide. Additionally, the performance of the predictive model appeared to be somewhat affected by the characteristics of raw water used to develop the model.

Potassium release kinetics and its correlation with pinto bean (Phaseolus vulgaris) plant indices

The rate of potassium (K) release from soils is a dynamic process, and it is important to the evaluation of soil K availability to plant. The objectives of this study were to determine K release characteristics and the correlation of these parameters with bean plant indices in surface soils of 15 calcareous soils. The kinetics of K release was determined by successive extraction with 0.01 mol/L CaCl&lt;sub&gt;2&lt;/sub&gt; in a period of 2&amp;ndash;2017 h at 25 &amp;plusmn; 1&amp;deg;C. The results showed that the cumulative K&amp;rlm; release ranged from 111 to 411 mg/kg. A plot of cumulative amount of K released showed a discontinuity in slope at 168 h. Thus, two equations were applied to segments of the total reaction time (2 to 168 and 168 to 2017 h). The amounts of K released during 2&amp;ndash;168 and 168&amp;ndash;2017 h ranged from 55 to 299 and 44 to 119 mg/kg, respectively. Release kinetics of K conformed fairly well to parabolic diffusion, simplified Elovich and power function models in two segments. Potassium released after 2&amp;ndash;168 and 168&amp;ndash;2017 h and K release rate constants were significantly correlated (P &amp;lt; 0.05) with bean plant indices, while correlation between K extracted by using 1 mol/L NH&lt;sub&gt;4&lt;/sub&gt;OAc (ammonium acetate) and plant indices was not significant. The results of this research showed that information obtained from K release studies in laboratory and kinetics equation parameters can help to estimate the K supplying power of soils. &amp;nbsp;

The species–area relationship: an exploration of that ‘most general, yet protean pattern’1

The species–area relationship: an exploration of that ‘most general, yet protean pattern’¹

Does watershed size affect simple mathematical relationships between flow velocity and discharge rate at watershed outlets on the Loess Plateau of China

Summary An empirical power function model of V = kQ m has been used worldwide to describe the relationship between flow velocity ( V , m s −1 ) and discharge rate ( Q , m 3 s −1 ) for rill and open channel flows. However, it has seldom been applied to watershed outlet channels taking into account the impacts of watershed size. In this study, observed data from four experimental watersheds of different sizes, ranging from about 1 to 100 km 2 , were used to verify the stability of the power function model for use at a watershed level on the Loess Plateau. An alternative logarithmic function model of V = e ln Q + d was also tested. Results showed that the constant parameters in both model types were impacted by watershed size, which are inherently directly related to the size of the outlet channels. The constants k and d , which represent flow velocity for unit discharge rate, were negatively correlated with watershed size. However, the exponential constants m and e , which determine the rate of change in flow velocity with respect to discharge rate, were shown to be independent of watershed size. Furthermore, soil and water conservation land use management on the Loess Plateau was also shown to indirectly affect the flow velocity–discharge rate relationship in the smallest watersheds (1 km 2 ). The study indicated that, although the performance of the logarithmic function model was acceptable, the power function model generally performed better over a larger range of flow velocity values and was better able to represent the flow velocity–discharge rate relationship in the unique context of the Loess Plateau.

Estimation of stand variables in Pinus radiata D. Don plantations using different LiDAR pulse densities

This study aimed to verify the validity of linear, power function and exponential models to estimate stand variables in Galician Atlantic forests of Pinus radiata D. Don using Light Detection and Ranging (LiDAR). These forests differ in structure and species composition from boreal forests, in which this methodology is fully developed. The models tested use LiDAR-derived canopy height and intensity distribution metrics as explanatory variables to predict the following stand attributes: mean height, dominant height, stand basal area, stand volume, stand crown biomass, stand stem biomass and stand aboveground biomass. Exponential models performed best in most cases, with goodness-of-fit statistics similar to those reported in the international literature for boreal forests. The coefficient of determination ranged from 0.44 (for stand crown biomass) to 0.87 (for dominant height), and the root mean square error/mean·100 ranged from 8.2 per cent (for dominant height) to 31.6 per cent (for stand stem biomass). Model precision did not essentially vary after reducing 94 per cent of the original point cloud, i.e. when laser pulse density was reduced from 8 pulses m−2 to only 0.5 pulses m−2.

A Virtual Model for Civil Building Electric Control Based on Matlab Controller

The purpose of this study is correct and effective model predictive control (MPC), in reduce energy demand and cost of buildings in power network and use pricing -- a demand and charges. A virtual model, for a single floor, the article commercial buildings equipped with variable air volume (VAV) based on Energyplus cooling system. Real-time data between the realization of the switch Energyplus and Matlab into building control virtual test bed (BCVTB) as a middleware. System identification technology is to realize get zone temperature and the power function model, which is used in the MPC framework. With economic target, target function is formulated as a linear programming problem and solves the problem. In the rush hour pre-cooling effect and independent cooling unloaded from building thermal mass in supply and demand can be observed during a consecutive weekly simulation. The MPC brings the cost comparison, the control strategy and other are preprogrammed baseline.

Creep Rate and Creep Model of Rockfill

Due to the test duration restriction, not only the creep strain but also the creep rate should be considered to establish the creep model of the rockfill. The creep rate decides whether the creep model deviates from the actual strain after the test duration. Both the same confining pressure loading and the constant stress ratio loading ways were adopted in this study. In the creep test, the Lianghekou mixture, the Zuoxiagou rockfill and the Xiaolangdi rockfill were used, and their creep characteristics and the creep rate were analyzed. Both the creep strain and the creep rate of the rockfills followed the linear relationship with the time in a double logarithmic coordinate. Therefore a power function model is suitable to describe the creep

Remote Sensing Dynamic Estimation of Grass Production in Xilinguole, Inner Mongolia

The monitoring of grass production is not only an important measurement index for researching the spatial dynamic patterns of grassland resources,but also an important basis for the optimal use of grassland resources and for monitoring the balance between grassland forage supply and livestock demand.A total of 371 grassland investigation and remote sensing(RS) data of MODIS-NDVI from 2005-2009 were used to establish a relational model between grass production and RS data.The temporal and spatial distributions of grass production in Xilinguole,Inner Mongolia were simulated and analyzed.The main conclusions are as follows:(1) Each model equation had good relativity,among which the power function model was the most appropriate for the calculation of grass production.Through reservation quadrat data,the accuracy of the production estimation model was 78%.It was feasible for the power function model to be applied for RS monitoring.(2) Grass production in the Xilinguole grassland amounted to an average of 34550000 tons over five years,equivalent to 11120000 tons of hay,and the dry weight per unit area was 567.23 kg/hm2.The spatial distribution of grass production showed a "high east and low west" pattern.(3) An obvious fluctuation in grass production appeared during 2005-2009.The range of hay was 8000000-14000000 tons,and the coefficient of variation was 20.42%.(4) There were greater differences in the single grass yield and the annual variation of different grass types.There were lower grass yields and greater annual variation in desert grassland,and higher grass yields and relatively lesser annual variation in meadow grassland.The spatial and temporal variation of grass yields also had the close relation with the major climate factors(precipitation,temperature,etc.),especially with the influence of precipitation.This research provides a reference for the protection and utilization of grassland resources.

Study on Crown of Main Coniferous Species in Natural Secondary Forest

2638 branch samples are gained from the 14 sample spots and the data of 50 parse trees in the spots investigated by Muling Forestry Bureau in 2008. The type of the curve are determined by the observation of the radius(r) of various kinds of trees and the scatter diagram graph of crown depth (lx) . This paper is to use power function, single formula, parabola and hyperbolic function models to fit. Through the comparison of the results of fitting, it is found that the fitting effect of the average crow of Korean pine is the best whose correlation coefficient achieves 0.58, and for parabola, spruce and fir are the best respectively with correlation coefficient 0.69 and 0.72; The same model is applied to fit the outside shape of the three species and the result is similar with that of average crown: hyperbolic function of Korean pine is the best and parabola of spruce and fir are the best. After test, it is found that forecast accuracy of model is higher. Average crown of Korean pine is 95.7% and outside crown is 92.1%; Average crown of fir is 94.9% and outside crown is ：95.9%; Average crown of Spruce is 96.0% and outside crown is 95.4%. From the point of comprehensive results, the fitting of crown shape model is better and the model chosen can better describe the crown shape of the main conifer species in Muling area, achieving the desired objectives.