Precise estimation of root biomass is important for understanding carbon stocks and dynamics in forests. Traditionally, biomass estimates are based on allometric scaling relationships between stem diameter and coarse root biomass calculated using linear regression (LR) on log-transformed data. Recently, it has been suggested that nonlinear regression (NLR) is a preferable fitting method for scaling relationships. But while this claim has been contested on both theoretical and empirical grounds, and statistical methods have been developed to aid in choosing between the two methods in particular cases, few studies have examined the ramifications of erroneously applying NLR. Here, we use direct measurements of 159 trees belonging to three locally dominant species in east China to compare the LR and NLR models of diameter-root biomass allometry. We then contrast model predictions by estimating stand coarse root biomass based on census data from the nearby 24-ha Gutianshan forest plot and by testing the ability of the models to predict known root biomass values measured on multiple tropical species at the Pasoh Forest Reserve in Malaysia. Based on likelihood estimates for model error distributions, as well as the accuracy of extrapolative predictions, we find that LR on log-transformed data is superior to NLR for fitting diameter-root biomass scaling models. More importantly, inappropriately using NLR leads to grossly inaccurate stand biomass estimates, especially for stands dominated by smaller trees.
Estimation of age from microscopic examination of human bone utilizes bone remodeling. This allows 2 regression equation to be determined in a specific population based on the variation in osteon turnover in different populations. The aim of this study was to provide age estimation for Malaysian males. Ground undecalcified cross sections were prepared from long limb bones of 50 deceased males aged between 21 and 78 years. Ten microstructural parameters were measured and subjected to multivariate regression analysis. Results showed that osteon count had the highest correlation with age (R = 0.43), and age was estimated to be within 10.94 years of the true value in 98% of males. Cross validation of the equation on 50 individuals showed close correspondence of true ages with estimated ages. Further studies are needed to validate and expand these results.
Youth–adult partnership (Y–AP) has emerged as a key practice for enacting two features of effective developmental settings: supportive adult relationships and support for efficacy and mattering. Previous studies have shown that when youth, supported by adults, actively participate in organizational and community decision making they are likely to show greater confidence and agency, empowerment and critical consciousness, and community connections. Most of the extant research on Y–AP is limited to qualitative studies and the identification of organizational best practices. Almost all research focuses on Western sociocultural settings. To address these gaps, 299 youth, age 15 to 24, were sampled from established afterschool and community programs in Malaysia to explore the contribution of Y–AP (operationalized as having two components: youth voice in decision-making and supportive adult relationships) to empowerment, agency and community connections. As hypothesized, hierarchical regressions indicated that program quality (Y–AP, safe environment and program engagement) contributed to agency, empowerment and community connections beyond the contribution of family, school and religion. Additionally, the Y–AP measures contributed substantially more variance than the other measures of program quality on each outcome. Interaction effects indicated differences by age for empowerment and agency but not for community connections. The primary findings in this inquiry replicate those found in previous interview and observational-oriented studies. The data suggests fertile ground for future research while demonstrating that Y–AP may be an effective practice for positive youth development outside of Western settings.
The main objective of this paper was to determine the utility of various anthropometric measures to assess total and regional body fatness using dual-energy X-ray absorptiometry (DXA) as the criterion in 454 adolescent boys and girls aged 12-19 years. Multivariable regression analyses of gender-specific and gender-combined models were used to determine anthropometric measures on DXA-derived body fatness models, after adjusting for known confounding biological factors. Partial correlation analyses, after adjusting for age, pubertal growth status and ethnicity in boys and girls, showed that body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-height ratio (WhtR) were significantly correlated with total body fat (TBF), percent body fat (%BF), android region fat (ARF) and trunk fat (TF) (all p<0.0001). BMI was the greatest independent determinant, contributing 43.8%-80.9% of the total variance for DXA-derived body fatness models. Results confirmed that a simple anthropometric index such as the BMI is a good surrogate indicator of body fat levels in Malay and Chinese adolescents.
Mixotrophic metabolism was evaluated as an option to augment the growth and lipid production of marine microalga Tetraselmis sp. FTC 209. In this study, a five-level three-factor central composite design (CCD) was implemented in order to enrich the W-30 algal growth medium. Response surface methodology (RSM) was employed to model the effect of three medium variables, that is, glucose (organic C source), NaNO3 (primary N source), and yeast extract (supplementary N, amino acids, and vitamins) on biomass concentration, X(max), and lipid yield, P(max)/X(max). RSM capability was also weighed against an artificial neural network (ANN) approach for predicting a composition that would result in maximum lipid productivity, Pr(lipid). A quadratic regression from RSM and a Levenberg-Marquardt trained ANN network composed of 10 hidden neurons eventually produced comparable results, albeit ANN formulation was observed to yield higher values of response outputs. Finalized glucose (24.05 g/L), NaNO3 (4.70 g/L), and yeast extract (0.93 g/L) concentration, affected an increase of X(max) to 12.38 g/L and lipid a accumulation of 195.77 mg/g dcw. This contributed to a lipid productivity of 173.11 mg/L per day in the course of two-week cultivation.
Crimes forecasting is an important area in the field of criminology. Linear models, such as regression and econometric models, are commonly applied in crime forecasting. However, in real crimes data, it is common that the data consists of both linear and nonlinear components. A single model may not be sufficient to identify all the characteristics of the data. The purpose of this study is to introduce a hybrid model that combines support vector regression (SVR) and autoregressive integrated moving average (ARIMA) to be applied in crime rates forecasting. SVR is very robust with small training data and high-dimensional problem. Meanwhile, ARIMA has the ability to model several types of time series. However, the accuracy of the SVR model depends on values of its parameters, while ARIMA is not robust to be applied to small data sets. Therefore, to overcome this problem, particle swarm optimization is used to estimate the parameters of the SVR and ARIMA models. The proposed hybrid model is used to forecast the property crime rates of the United State based on economic indicators. The experimental results show that the proposed hybrid model is able to produce more accurate forecasting results as compared to the individual models.
Relationships between six calcifying plankton groups and pH are explored in a highly biologically productive and data-rich area of the central North Sea using time-series datasets. The long-term trends show that abundances of foraminiferans, coccolithophores, and echinoderm larvae have risen over the last few decades while the abundances of bivalves and pteropods have declined. Despite good coverage of pH data for the study area there is uncertainty over the quality of this historical dataset; pH appears to have been declining since the mid 1990s but there was no statistical connection between the abundance of the calcifying plankton and the pH trends. If there are any effects of pH on calcifying plankton in the North Sea they appear to be masked by the combined effects of other climatic (e.g. temperature), chemical (nutrient concentrations) and biotic (predation) drivers. Certain calcified plankton have proliferated in the central North Sea, and are tolerant of changes in pH that have occurred since the 1950s but bivalve larvae and pteropods have declined. An improved monitoring programme is required as ocean acidification may be occurring at a rate that will exceed the environmental niches of numerous planktonic taxa, testing their capacities for acclimation and genetic adaptation.
The synthesis of fatty acid ethyl esters (FAEEs) by a two-step in situ (reactive) esterification/transesterification from Jatropha curcas L. (JCL) seeds using microwave system has been investigated. Free fatty acid was reduced from 14% to less than 1% in the first step using H2SO4 as acid catalyst after 35 min of microwave irradiation heating. The organic phase in the first step was subjected to a second reaction by adding 5 N KOH in ethanol as the basic catalyst. Response surface methodology (RSM) based on central composite design (CCD) was utilized to design the experiments and analyze the influence of process variables (particles seed size, time of irradiation, agitation speed and catalyst loading) on conversion of triglycerides (TGs) in the second step. The highest triglycerides conversion to fatty acid ethyl esters (FAEEs) was 97.29% at the optimum conditions:<0.5mm seed size, 12.21 min irradiation time, 8.15 ml KOH catalyst loading and 331.52 rpm agitation speed in the 110 W microwave power system.
Candlenut oil was extracted using supercritical CO(2) (SC-CO(2)) with an optimization of parameters, by the response surface methodology. The ground candlenut samples were treated in 2 different ways, that is, dried in either a heat oven (sample moisture content of 2.91%) or dried in a vacuum oven (sample moisture content of 1.98%), before extraction. An untreated sample (moisture content of 4.87%) was used as a control. The maximum percentage of oil was extracted from the heat-oven-dried sample (77.27%), followed by the vacuum-oven-dried sample (74.32%), and the untreated sample (70.12%). At an SC-CO(2) pressure of 48.26 Mpa and 60 min of extraction time, the optimal temperatures for extraction were found to be 76.4 °C, 73.9 °C, and 70.6 °C for the untreated, heat-oven-dried, and vacuum-oven-dried samples, respectively. The heat-oven-dried sample contains the highest percentage of linoleic acid, followed by the untreated and vacuum-oven-dried samples. The antiradical activity of candlenut oil corresponded to an IC(50) value of 30.37 mg/mL.
This study aimed to identify the significant factors that give large effects on the efficiency of Cu(II) extraction from aqueous solutions by soybean oil-based organic solvents using fractional factorial design. Six factors (mixing time (t), di-2-ethylhexylphosphoric acid concentration ([D2EHPA]), organic to aqueous phase ratio (O:A), sodium sulfate concentration ([Na(2)SO(4)]), equilibrium pH (pH(eq)) and tributylphosphate concentration ([TBP])) affecting the percentage extraction (%E) of Cu(II) were investigated. A 2(6-1) fractional factorial design was applied and the results were analyzed statistically. The results show that only [D2EHPA], pH(eq) and their second-order interaction ([D2EHPA] × pH(eq)) influenced the %E significantly. Regression models for %E were developed and the adequacy of the reduced model was examined. The results of this study indicate that fractional factorial design is a useful tool for screening a large number of variables and reducing the number of experiments.
Psychological well-being as one of the most important indicators of successful aging has received substantial attention in the gerontological literature. Prior studies show that sociodemographic factors influencing elderly's psychological well-being are multiple and differ across cultures. The aim of this study was to identify significant sociodemographic predictors of psychological well-being among Malay elders.
Several equations have been used to predict lung function standard results for different populations. It is important lung function evaluations use appropriate standards for the study population. The objective of this study was to develop a prediction equation for lung function test results for the Malaysian population. Spirometry was performed among 5,708 subjects and 1,483 healthy, lifetime never smoked subjects (386 males and 1,097 females). Prediction equations were derived for both men and women for FVC and FEV1 results. The equations were validated on new subjects (n = 532, 222 males and 310 females) who met the same inclusion and exclusion criteria as the main cohort. There was a positive correlation between the measured values and the values derived from the new prediction equations (0.62 for FEV1 and between 0.66 and 0.67 for FVC; both p < 0.05) for both men and women with a smaller bias and limit of agreement compared to the published reference equations of ECCS, Knudson, Crapo and NHANES III. The reference equations derived from local spirometry data were more appropriate than generally used equations based on data from previous studies in different population.
Malay is a consistent alphabetic orthography with complex syllable structures. The focus of this research was to investigate word recognition performance in order to inform reading interventions for low-progress early readers. Forty-six Grade 1 students were sampled and 11 were identified as low-progress readers. The results indicated that both syllable awareness and phoneme blending were significant predictors of word recognition, suggesting that both syllable and phonemic grain-sizes are important in Malay word recognition. Item analysis revealed a hierarchical pattern of difficulty based on the syllable and the phonic structure of the words. Error analysis identified the sources of errors to be errors due to inefficient syllable segmentation, oversimplification of syllables, insufficient grapheme-phoneme knowledge and inefficient phonemic code assembly. Evidence also suggests that direct instruction in syllable segmentation, phonemic awareness and grapheme-phoneme correspondence is necessary for low-progress readers to acquire word recognition skills. Finally, a logical sequence to teach grapheme-phoneme decoding in Malay is suggested.
The constituents in a food emulsion interact with each other, either physically or chemically, determining the overall physico-chemical and organoleptic properties of the final product. Thus, the main objective of present study was to investigate the effect of emulsion components on beverage emulsion properties.
A linear quantitative structure activity relationship (QSAR) model is presented for modeling and predicting the inhibition of HIV-1 integrase. The model was produced by using the stepwise multiple linear regression technique on a database that consists of 67 recently discovered 1,3,4-oxadiazole substituted naphthyridine derivatives. The developed QSAR model was evaluated for statistical significance and predictive power. The key conclusion of this study is that valence connectivity index order 1, lowest unoccupied molecular orbital and dielectric energy significantly affect the inhibition of HIV-1 integrase activity by 1,3,4-oxadiazole substituted naphthyridine derivatives. The selected physicochemical descriptors serve as a first guideline for the design of novel and potent antagonists of HIV-1 integrase.
There are few empirical data, particularly collected simultaneously from multiple sites, on extinctions resulting from human-driven land-use change. Southeast Asia has the highest deforestation rate in the world, but the resulting losses of biological diversity remain poorly documented. Between November 2006 and March 2008, we conducted bird surveys on six landbridge islands in Malaysia and Indonesia. These islands were surveyed previously for birds in the early 1900 s, when they were extensively forested. Our bird inventories of the islands were nearly complete, as indicated by sampling saturation curves and nonparametric true richness estimators. From zero (Pulau Malawali and Pulau Mantanani) to 15 (Pulau Bintan) diurnal resident landbird species were apparently extirpated since the early 1900 s. Adding comparable but published extinction data from Singapore to our regression analyses, we found there were proportionally fewer forest bird extinctions in areas with greater remaining forest cover. Nevertheless, the statistical evidence to support this relationship was weak, owing to our unavoidably small sample size. Bird species that are restricted to the Indomalayan region, lay few eggs, are heavier, and occupy a narrower habitat breadth, were most vulnerable to extinction on Pulau Bintan. This was the only island where sufficient data existed to analyze the correlates of extinction. Forest preservation and restoration are needed on these islands to conserve the remaining forest avifauna. Our study of landbridge islands indicates that deforestation may increasingly threaten Southeast Asian biodiversity.
The mu rhythm is an electroencephalogram (EEG) signal located at the central region of the brain that is frequently used for studies concerning motor activity. Quite often, the EEG data are contaminated with artifacts and the application of blind source separation (BSS) alone is insufficient to extract the mu rhythm component. We present a new two-stage approach to extract the mu rhythm component. The first stage uses second-order blind identification (SOBI) with stationary wavelet transform (SWT) to automatically remove the artifacts. In the second stage, SOBI is applied again to find the mu rhythm component. Our method is first compared with independent component analysis with discrete wavelet transform (ICA-DWT) as well as SOBI-DWT, ICA-SWT, and regression method for artifact removal using simulated EEG data. The results showed that the regression method is more effective in removing electrooculogram (EOG) artifacts, while SOBI-SWT is more effective in removing electromyogram (EMG) artifacts as compared to the other artifact removal methods. Then, all the methods are compared with the direct application of SOBI in extracting mu rhythm components on simulated and actual EEG data from ten subjects. The results showed that the proposed method of SOBI-SWT artifact removal enhances the extraction of the mu rhythm component.