A Simplified Evaluation Procedure of the Scale of Fluctuation Combined Recurrence Averaging and Weighted Linear Regression

The divergence of properties from one location to another within a soil mass is termed spatial variability, which traditionally includes three parameters the mean, the standard deviation, and the scale of fluctuation, in order to stochastically describe a soil property. Among them, determining the scale of fluctuation in the evaluation of spatial variability of soil profiles is not easy due to soil condition complexity. A simplified procedure is presented in the paper to determine the scale of fluctuation combined recurrence averaging and weighted linear regression. The alternative approach utilizes widely usable spreadsheet to solve the problem more directly and efficiently.

The mean value concept in mono-linear regression of multi-variables and its application to trace studies in geosciences

IEECAS SKLLQG

Numerical estimate of the stability curve for the flow past a rotating cylinder

It is demonstrated that the primary instability of the wake of a two-dimensional circular cylinder rotating with constant angular velocity can be qualitatively well described by the Landau equation. The coefficients of the Landau equation are determined by means of numerical simulations for the Navier-Stokes equations. The critical Reynolds numbers, which depend on the angular velocity of the cylinder, are evaluated correctly by linear regression. (C) 2004 American Institute of Physics.

SCALING OF LIMB PROPORTIONS AND LIMB BONE DIAMETERS IN 3 SPECIES OF CHINESE SNUB-NOSED LANGURS (GENUS RHINOPITHECUS)

In this study, aspects of the structural mechanics of the upper and lower limbs of the three Chinese species of Rhinopithecus were examined. Linear regression and reduced major axis (RMA) analyses of natural log-transformed data were used to examine the dimensions of limb bones and other relationships to body size and locomotion. The results of this study suggest that: (1) the allometry exponents of the lengths of long limbs deviate from isometry, being moderately negative, while the shaft diameters (both sagittal and transverse) show significantly positive allometry; (2) the sagittal diameters of the tibia and ulna show extremely significantly positive allometry - the relative enlargement of the sagittal, as opposed to transverse, diameters of these bones suggests that the distal segments of the fore- and hindlimbs of Rhinopithecus experience high bending stresses during locomotion; (3) observations of Rhinopithecus species in the field indicate that all species engage in energetic leaping during arboreal locomotion. The limbs experience rapid and dramatic decelerations upon completion of a leap. We suggest that these occasional decelerations produce high bending stresses in the distal limb segments and so account for the hypertrophy of the sagittal diameters of the ulna and tibia.

Effect of water temperature on the growth performance and digestive enzyme activities of Chinese longsnout catfish (Leiocassis longirostris Gunther)

The present study was carried out to investigate the influence of water temperature on the growth performance and digestive enzyme (pepsin, trypsin and lipase) activities of Chinese longsnout catfish. Triplicate groups of Chinese longsnout catfish (35.6 +/- 0.48 g, mean +/- SE) were reared at different water temperatures (20, 24, 28 and 32 degrees C). The feeding rate (FR), specific growth rate (SGR) and feed efficiency ratio (FER) were significantly affected by water temperatures and regression relationships between water temperature and FI, SGR as well as FER were expressed as FR=-0.016T2+0.91T-10.88 (n=12, R2=0.8752), SGR=-0.026T2+1.39T-17.29 (n=12, R2=0.7599) and FER=-0.013T2+0.70T-8.43 (n=12, R2=0.7272). Based on these, the optimum temperatures for FR, SGR and FER were 27.66, 26.69 and 26.44 degrees C respectively. The specific activities of digestive enzymes at 24 or 28 degrees C were significantly higher than that at 20 or 32 degrees C. In addition, there was a significant linear regression between FR or SGR and specific activities of pepsin and lipase, which indicated that pepsin and lipase played important roles in regulating growth through nutrient digestion in Chinese longsnout catfish.

Relationships between Testate Amoebae Assemblages (Protozoa) and Geographic Factors in Yunnan Plateau Lakes, China

Knowledge of the effect of geographic factors on the assemblages of protozoan testate amoebae is still limited, despite there having been a number of studies on this fauna. We applied statistical analyses to data on the distribution of testate amoebae from nine major lakes in the Yunnan Plateau, southwest China. Cluster analysis, based on community structure, separated the lakes into two groups - the oligotrophic/mesotrophic lakes and the hypercutrophic lakes - confirming the idea that the testate amoebae assemblages in lakes are closely related to the trophic status. Additionally, within the oligotrophic/mesotrophic lakes, there was distinct geographic clustering. Linear regression analysis and the Mantel test both revealed that similarity of species composition decreased with increasing geographic distance among the oligotrophic/mesotrophic lakes.

Phytoplankton biomass in relation to nutrients and zooplankton in thirty subtropical lakes adjacent to the Yangtze River, China

A total of 30 shallow lakes, located along the middle and lower reaches of the Yangtze River, were studied to assess the relative importance of nutrients and zooplankton biomass in determining the phytoplankton biomass in subtropical China. Zooplankton biomass and nutrients both varied greatly in these lakes. Factor analysis and multiple linear regression showed that phytoplankton biomass was positively correlated with TN, NH4+, NO3- and TP, while it did not show any negative relationship to zooplankton biomass. Meanwhile, the phytoplankton biomass showed contrary relationships to the mass ratio of TN/TP in spring and summer, suggesting that in nutrient-richer lakes the dominant phytoplankton species have different preferences for TN/TP ratio. The insignificant top-down control of phytoplankton biomass may be attributed to the dominance of small-sized crustaceans and low crustacean biomass resulting from cyanobacterial dominance and planktivorous fish predation as well as other factors. Thus, it is likely that nutrients were more important than zooplankton biomass in explaining the total variance of phytoplaDkton biomass in these subtropical lakes.

Geographical distribution of testate amoebae in Tibet and northwestern Yunnan and their relationships with climate

In Asia, especially in China, our knowledge of the distribution of testate amoebae is still limited. In this paper, the geographical distribution of testate amoebae in Tibetan Plateau and northwestern Yunnan Plateau, southwest China and their relationships with the climatic factors have been studied. We found testate amoebae shifted in the most dominant species and increased in species (or genus) richness from northwest to southeast. Further, the linear regression analyses revealed that both species richness and genus richness have higher positive correlations with the mean temperature of the warmest month and annual mean precipitation as contrasted with the mean altitude, which showed weak negative correlation. This indicates that the temperature and precipitation are more significant influences on the richness than the altitude. The cluster analysis based on the community structure, defined by Sorenson's coefficient matrix, suggested four groups from the 10 physiographical regions. This geographical distribution pattern was also closely related with the climatic regionalization. The present climatic regionalization pattern of the study area originated from the uplift of Tibetan Plateau and mainly occurred in or after the late Pleistocene. Therefore, the geographical distribution of testate amoebae in our study area may have experienced complicated and drastic changes corresponding to the variation of the climate caused by the geological events.

Correcting the systematic error of the density functional theory calculation: the alternate combination approach of genetic algorithm and neural network

The alternate combinational approach of genetic algorithm and neural network (AGANN) has been presented to correct the systematic error of the density functional theory (DFT) calculation. It treats the DFT as a black box and models the error through external statistical information. As a demonstration, the AGANN method has been applied in the correction of the lattice energies from the DFT calculation for 72 metal halides and hydrides. Through the AGANN correction, the mean absolute value of the relative errors of the calculated lattice energies to the experimental values decreases from 4.93% to 1.20% in the testing set. For comparison, the neural network approach reduces the mean value to 2.56%. And for the common combinational approach of genetic algorithm and neural network, the value drops to 2.15%. The multiple linear regression method almost has no correction effect here.

Pressure drops of single and two-phase flows through T-type microchannel mixers

In this paper, preliminary experimental results are presented on pressure drop characteristics of single and two-phase flows through two T-type rectangular microchannel mixers with hydraulic diameters of 528 and 333 mum, respectively. It is shown that both N-2 and water single-phase laminar flows in microchannels, with consideration of experimental uncertainties, are consistent with classic theory, if additional effects, such as entrance effects that will interfere with the interpretation of experimental results, are eliminated by carefully designing the experiments. The obtained pressure drop data of N-2-water two-phase flow in micromixers are analyzed and compared with existing flow pattern-independent models. It is found that the Lockhart-Martinelli method generally underpredicts the frictional pressure drop. Thereafter, a modified correlation of C value in the Chisholm's equation based on linear regression of experimental data is proposed to provide a better prediction of the two-phase frictional pressure drop. Also among the homogeneous flow models investigated, the viscosity correlation of McAdams indicates the best performance in correlating the frictional pressure drop data (mean deviations within +/-20% for two micromixers both). Finally it is suggested that systematic studies are still required to accurately predict two-phase frictional performance in microchannels. (C) 2004 Elsevier B.V. All rights reserved.

Prediction of soil organic carbon partition coefficients by soil column liquid chromatography

To avoid the limitation of the widely used prediction methods of soil organic carbon partition coefficients (K-OC) from hydrophobic parameters, e.g., the n-octanol/water partition coefficients (K-OW) and the reversed phase high performance liquid chromatographic (RP-HPLC) retention factors, the soil column liquid chromatographic (SCLC) method was developed for K-OC prediction. The real soils were used as the packing materials of RP-HPLC columns, and the correlations between the retention factors of organic compounds on soil columns (k(soil)) and K-OC measured by batch equilibrium method were studied. Good correlations were achieved between k(soil) and K-OC for three types of soils with different properties. All the square of the correlation coefficients (R-2) of the linear regression between log k(soi) and log K-OC were higher than 0.89 with standard deviations of less than 0.21. In addition, the prediction of K-OC from K-OW and the RP-HPLC retention factors on cyanopropyl (CN) stationary phase (k(CN)) was comparatively evaluated for the three types of soils. The results show that the prediction of K-OC from k(CN) and K-OW is only applicable to some specific types of soils. The results obtained in the present study proved that the SCLC method is appropriate for the K-OC prediction for different types of soils, however the applicability of using hydrophobic parameters to predict K-OC largely depends on the properties of soil concerned. (C) 2004 Elsevier B.V. All rights reserved.

Using HPLC retention parameters to estimate fish bioconcentration factors of organic compounds

Reversed-phase high performance liquid chromatography (RP-HPLC) was employed to develop predictive models for fish bioconcentration factors (BCF) of organic compounds. Estimation of BCF from RP-HPLC retention parameters on octadecyl-bonded silica gel (ODS), cyanopropyl-bonded silica gel (CN), and phenyl-bonded silica gel (Ph) columns were investigated. The results show that, for a set of compounds belonging to different chemical classes, the CN stationary phase is the best one among the three columns and better than n-octanol/water model for BCF estimation. A multi-column RP-HPLC model, using the retention parameters on the CN and Ph columns as the variables of multiple linear regression equations, was further evaluated to estimate BCF of organic compounds belonging to different chemical classes, and the results show that the multi-column RP-HPLC model is better than that of any single RP-HPLC column for BCF estimation.

Modeling the effect of ozone loss on photobleaching of chromophoric dissolved organic matter in the St. Lawrence estuary

Temporal trends in total ozone for the St. Lawrence estuary were estimated from ground-based measurements at the NOAA/CMDL station in Caribou, Maine. Linear regression analysis showed that from 1979 to 1999 total ozone has decreased by about 3.3% per decade on an annual basis and ≤6.2% per decade on a monthly basis relative to unperturbed (pre-CFC) levels. The influence of increased ultraviolet-B (280–320 nm) radiation associated with ozone depletion on water column photochemical processes was evaluated by modeling the photobleaching of chromophoric dissolved organic material (CDOM). Linear regression analysis showed small (<0.5% per decade), but statistically significant upward trends in maximum noontime photobleaching rates. Most notably, positive trends in relative rates for May, June, and July, when maximum absolute rates are expected, were predicted. A global model based on TOMS ozone data revealed increases in photobleaching of ≤3% per decade at high latitudes in the Southern Hemisphere. Radiation amplification factors for increases in photochemically weighted UV (280–400 nm) in response to ozone depletion were estimated at 0.1 and 0.08 for photobleaching of CDOM absorbance at 300 and 350 nm, respectively. Application of the laboratory-based model to conditions that more closely resembled those in situ were variable with both overestimation and underestimation of measured rates. The differences between modeled rates and observed rates under quasi-natural conditions were as large or larger than the predicted increases due to ozone depletion. These comparisons suggest that biological activity and mixing play an important, but as yet ill-defined, role in modifying photochemical processes.

Study on QSPR of alcohols with a novel edge connectivity index F-m

A novel edge degree f(i) for heteroatom and multiple bonds in molecular graph is derived on the basis of the edge degree delta(e(r)). A novel edge connectivity index F-m is introduced. The multiple linear regression by using the edge connectivity index F-m and alcohol-type parameter delta, alcohol-distance parameter L can provide high-quality QSPR models for the normal boiling points (BPs), molar volumes (MVs), molar refraction (MRs), water solubility(log(1/S)) and octanol/water partition (logP) of alcohols with up to 17 non-hydrogen atoms. The results imply that these physical properties may be expressed as a liner combination of the edge connectivity index and alcohol-type parameter, 6, alcohol-distance parameter, L. For the models of the five properties, the correlation coefficient r and the standard errors are 0.9969,3.022; 0.9993, 1.504; 0.9992, 0.446; 0.9924,0.129 and 0.9973,0.123 for BPs, MVs, MRs, log(1/S) and logP, respectively. The cross-validation by using the leave-one-out method demonstrates the models to be highly reliable from the point of view of statistics.

Applications of the method of three-dimensional projection of a molecule in quantitative structure-activity relationship of phenol derivatives

Five variables for phenol derivatives were calculated by molecular projection in three-dimensional space which were combined with eight quantum-chemical parameters and three Am indices. These variables were selected by using leaps-and-bounds regression analysis. Multiple linear regression analysis and artificial neural networks' were performed, and the results obtained by using. artificial neural networks are superior than that obtained by using multiple linear regression.