Multiple Square Research Articles

Effect of globalization on global dental caries trend.

Risk factors such as smoking and sugar intake threaten the health of human being at an individual national level as well as at a global level. The globalization affect health indirectly through macro and micro-level factors. This study aimed to identify the global trend of dental caries according to countries national income level, and to examine the role of globalization, health services, obesity, and sugar consumption on dental caries. Data for 160 countries were collected for the time period of the 1990s to 2010s. The final sample included 46 countries with complete data (21 high income countries (HIC) and 25 middle and low income countries (MLIC)). The main dependent variable was the mean decayed, missing, and filled teeth (DMFT) index of 12-year-olds as an indicator of dental caries. Globalization was a main independent variable which was measured by economic growth, urbanization and economic freedom. Other independent variables were health services, obesity and sugar consumption. The data were analyzed first using repeated measures analysis of variance to compare dental caries trends in HIC and MLIC. Then, using multiple linear regression and partial least squares structural equation modeling (PLS-SEM), the relationships between globalization, health services, obesity, sugar consumption, and dental caries were examined. The results of PLS-SEM revealed that globalization was associated with lower DMFT in HIC. The global dental caries trend had a declined pattern, but this pattern has been attenuated in MLIC after the new millennium. There is a need for policy change and regulations on sugar trade especially in MLIC to diminish the adverse consequences of globalization, and to improve population dental health.

Estimating purple-soil moisture content using Vis-NIR spectroscopy

Soil moisture is essential for plant growth in terrestrial ecosystems. This study investigated the visible-near infrared (Vis-NIR) spectra of three subgroups of purple soils (calcareous, neutral, and acidic) from western Chongqing, China, containing different water contents. The relationship between soil moisture and spectral reflectivity (R) was analyzed using four spectral transformations, and estimation models were established for estimating the soil moisture content (SMC) of purple soil based on stepwise multiple linear regression (SMLR) and partial least squares regression (PLSR). We found that soil spectra were similar for different moisture contents, with reflectivity decreasing with increasing moisture content and following the order neutral > calcareous > acidic purple soil (at constant moisture content). Three of the four spectral transformations can highlight spectral sensitivity to SMC and significantly improve the correlation between the reflectance spectra and SMC. SMLR and PLSR methods provide similar prediction accuracy. The PLSR-based model using a first-order reflectivity differential (R’) is more effective for estimating the SMC, and gave coefficient of determination root mean square errors of validation (RMSEV), and ratio of performance to inter-quartile distance (RPIQ) values of 0.946, 1.347, and 6.328, respectively, for the calcareous purple soil, and 0.944, 1.818, and 6.569, respectively, for the acidic purple soil. For neutral purple soil, the best prediction was obtained using the SMLR method with R’ transformation, yielding R2v, RMSEV and RPIQ values of 0.973, 0.888 and 8.791, respectively. In general, PLSR is more suitable than SMLR for estimating the SMC of purple soil.

Hypoxia-Associated Changes in Striatal Tonic Dopamine Release: Real-Time in vivo Measurements With a Novel Voltammetry Technique.

Introduction Striatal tonic dopamine increases rapidly during global cerebral hypoxia. This phenomenon has previously been studied using microdialysis techniques which have relatively poor spatio-temporal resolution. In this study, we measured changes in tonic dopamine during hypoxia (death) in real time with high spatio-temporal resolution using novel multiple cyclic square wave voltammetry (MCSWV) and conventional fast scan cyclic voltammetry (FSCV) techniques.MethodsMCSWV and FSCV were used to measure dopamine release at baseline and during hypoxia induced by euthanasia, with and without prior alpha-methyl-p-tyrosine (AMPT) treatment, in urethane anesthetized male Sprague-Dawley rats.ResultsBaseline tonic dopamine levels were found to be 274.1 ± 49.4 nM (n = 5; mean ± SEM). Following intracardiac urethane injection, the tonic levels increased to a peak concentration of 1753.8 ± 95.7 nM within 3.6 ± 0.6 min (n = 5), followed by a decline to 50.7 ± 21.5 nM (n = 4) at 20 min. AMPT pre-treatment significantly reduced this dopamine peak to 677.9 ± 185.7 nM (n = 3). FSCV showed a significantly higher (p = 0.0079) peak dopamine release of 6430.4 ± 1805.7 nM (n = 5) during euthanasia-induced cerebral hypoxia.ConclusionMCSWV is a novel tool to study rapid changes in tonic dopamine release in vivo during hypoxia. We found a 6-fold increase in peak dopamine levels during hypoxia which was attenuated with AMPT pre-treatment. These changes are much lower compared to those found with microdialysis. This could be due to improved estimation of baseline tonic dopamine with MCSWV. Higher dopamine response measured with FSCV could be due to an increased oxidation current from electroactive interferents.

Preference study of four alternative silage fodders from the Mediterranean region in Murciano-Granadina goats

Abstract In Mediterranean countries, large quantities of by-products are generated from artichoke and broccoli crops, as well as large masses of common reed due to the cleaning of riverbeds. They have traditionally been applied directly in animal feed, especially for small ruminants, without undergoing any preservation process. Their inclusion in diets would allow three benefits: feeding animals with materials containing high nutrient contents all year round (not only in the crop season) in a well-balanced ration, lowering the feeding costs and reducing the amount of residues and their elimination cost for producers. Through the silage process, these feedstuffs can be preserved to ensure year-round availability. The aim of this short-term preference trial was to evaluate the goats' preference among four different ensiled feedstuffs and to study the relationship between animal preference and the silage composition. The four alternative silage-feedstuffs were offered to four nulliparous Murciano-Granadina goats (34.9 ± 1.9 kg) in a multiple square or cafeteria design. The feedstuffs tested were artichoke bracts (Cynara scolymus), artichoke plant, a 50:50 mixture of broccoli by-product (Brassica oleracea, var. Italica) and artichoke bracts, and common reed (Phragmites australis). To determine preference, data were collected on feed intake and the time each animal spent eating each feedstuff for four hours each day. Macrocomposition and some functional and chemical characteristic silages were analysed. The relation between DM intake and chemical composition of the tested feedstuffs was determined using correlation and regression analyses. The artichoke bracts silage presented the highest cumulative intake at 4 hours (3.26 g DM/kg BW); being different from artichoke plant silage (2.17 g DM/kg BW), the second most consumed. Broccoli + artichoke and common reed silage intake was significantly lower than those of the other two feeds (0.36 and 0.67 g DM/kg BW, respectively). The strongest correlations between DM intake after 4 hours (g of DM) and the nutritional and chemical characteristics of the silages were found with digestible energy (r = 0.60, P

Response of turbulent pipeflow to multiple square bar roughness elements at high Reynolds number

The response and recovery of turbulent pipeflow over multiple square bar roughness elements with periodic and staggered patterns are examined at a Reynolds number of 1.56 × 105. The square bar roughness elements have a height of h/D = 0.05 and 0.1. Two, three, and four periodically separated bar elements are considered using the smaller height of 0.05, along with one with staggered separation between four tandem elements. An asymptotic trend in response and recovery is observed with three bar roughness elements, after which no substantial variations occur with additional elements. The three elements in the pipe increase the rate of turbulent diffusion compared to cases with a smaller number of elements, which leads to a faster recovery. The separation patterns have negligible effects on the overall recovery or response as long as the elements are positioned outside the recirculation zone formed by the upstream element.

Analisa Faktor-Faktor Makroekonomi Terhadap Kinerja Investasi Saham Periode 2010 – 2012

This study discusses the macroeconomic effect on the performance of mutual fund shares. Macroeconomic variables used are economic growth, inflation, bank interest rates, and exchange rates, while the performance of mutual fund shares calculated using the Sharpe ratio. This study uses the data in the form of panel data with quarterly time series ranging between 2010-2012. The equation used is multiple regression equation Ordinary Least Square (OLS). After performing the classical assumption, and normality of the data, the results of the study showed that partially there are significant macroeconomic variables consist of exchange rate, inflation, and economic growth that influence the performance of mutual fund shares quarterly in period 2010-2012. While the bank's interest rate variable has no significant effect on the performance of mutual fund shares. However, the macroeconomic variables affect the performance of mutual fund shares simultaneously. Therefore the ultimate findings of this study is that macroeconomic variables only affect the performance of mutual funds in the amount of 35.3%, while the remaining 64.7% is influenced by other factors, especially the internal factors of mutual fund shares

Does financial inclusion predict a lower risk of loneliness in later life? Evidence from the AgeHeaPsyWel-HeaSeeB study 2016–2017

Objective For many older people, loneliness represents a common source of impaired quality of life particularly in the context of poor access to financial services. This article examines the association between financial inclusion and loneliness in older adults and explores the moderating effects of gender and physical activity in this association. Methods One thousand two-hundred participants completed the Short Form Revised UCLA Loneliness Scale assessing loneliness during 2016–2017 Aging, Health, Psychological Well-being and Health-seeking Behavior (AgeHeaPsyWel-HeaSeeB) Study. Financial inclusion was assessed using an 8-item Financial Instrument Scale. Results Multiple ordinary least squares (OLS) regressions showed that increases in financial inclusion were associated with decreases in loneliness in the total sample (β = −0.679, p < 0.001) and in women (β = −0.787, p < 0.001) but not in men (β = −0.594, p = 0.084). The negative effect of financial inclusion on loneliness was pronounced among those who engaged in physical activity (β = −0.646, p < 0.042). Conclusions Findings underscore the importance of financial inclusion for loneliness in later life particularly among older women and those who engage in physical activity. Encouraging and strengthening financial inclusion may crucially improve psychological health and emotional well-being among aging adults.

Development of a coarse-grained lipid model, LIME 2.0, for DSPE using multistate iterative Boltzmann inversion and discontinuous molecular dynamics simulations

We suggest an improved version of the intermediate resolution implicit solvent model for lipids, LIME, that was previously developed for use with discontinuous molecular dynamics (DMD) simulations. LIME gets its geometrical and energy parameters between bonded and nonbonded pairs of coarse-grained (CG) sites from atomistic simulations. The improved model, LIME 2.0, uses multiple square wells rather than the single square well used in original LIME to obtain intermolecular interactions that more faithfully mimic those from atomistic simulations. The multi-state iterative Boltzmann inversion (MS-IBI) scheme is used to determine the interaction parameters. This means that a single set of interaction parameters between coarse-grained sites can be used to represent the lipid bilayers at different temperatures. The physical properties of CG DSPE lipid bilayer are calculated using CG simulations and compared to atomistic simulations results to verify the improved model. The phase transition temperature of the lipid bilayer is measured accurately and the lipid translocation phenomenon, “flip-flop” is observed through CG simulation. These results suggest that CG parameterization using multiple square-wells and the MS-IBI scheme is well suited to the study of lipid bilayers across a range of temperatures with DMD simulations.

Determining Factors Affecting Nurses' Acceptance of a Care Plan System Using a Modified Technology Acceptance Model 3: Structural Equation Model With Cross-Sectional Data.

BackgroundHealth information technology is used in nursing practice worldwide, and holistic patient care planning can serve as a guide for nursing practice to ensure quality in patient-centered care. However, few studies have thoroughly analyzed users’ acceptance of care plan systems to establish individual plans.ObjectiveBased on the technology acceptance model 3 (TAM3), a user technology acceptance model was established to explore what determines the acceptance of care plan systems by users in clinical settings.MethodsCross-sectional quantitative data were obtained from 222 nurses at eight hospitals affiliated with public organizations in Taiwan. Using the modified TAM3, the collected data were employed to analyze the determinants of user acceptance of a care plan system through structural equation modeling (SEM). We also employed moderated multiple regression analysis and partial least squares–SEM to test the moderating effects.ResultsWe verified all significant effects from the use of a care plan system among bivariate patterns in the modified TAM3, except for moderating effects. Our results revealed that the determinants of perceived usefulness and perceived ease of use significantly influenced perceived usefulness and perceived ease of use, respectively. The results also indicated that nurses’ perceptions of subjective norm (path coefficient=.25, P<.001), perceived ease of use (path coefficient=.32, P<.001), and perceived usefulness (path coefficient=.31, P<.001) had significantly positive effects on their behavioral intention to use the care plan system, accounting for 69% of the total explained variance.ConclusionsBy exploring nurses’ acceptance of a care plan system, this study revealed relationships among the variables in TAM3. Our results confirm that the modified TAM3 is an innovative assessment instrument that can help managers understand nurses’ acceptance of health information technology in nursing practice to enhance the adoption of health information technology.

Effect of lubricant oil on boiling heat transfer and flow patterns of R32 inside a multiport tube

This study experimentally investigated the boiling flow patterns, local heat transfer coefficients, and pressure drops of R32/lubricant oil mixtures flowing inside a horizontal multiport extruded tube having rectangular minichannels. The experiments were carried out in a mass flux range of 50–400 kg m−2 s−1, heat flux range of 5–40 kW m−2, and oil circulation up to 3.7 wt% at an evaporation temperature of 15 °C. The boiling flow patterns were visualized by using a setup that consisted of horizontal multiple square minichannels, each with a hydraulic diameter of 1.0 mm. The heat transfer coefficients of the R32/oil mixtures were lower compared with those of pure R32 and decreased with increasing oil concentration at lower heat fluxes, while they were higher for conditions of higher heat flux and low vapor quality. In addition, the heat transfer coefficients of the mixtures significantly decreased at a lower mass flux and in a higher vapor quality region. The frictional pressure drops of the R32/oil mixtures was higher compared with that of pure R32 and increased with increasing mass flux, vapor quality, and oil concentration. The effect of oil concentration on the pressure drop was significant at the higher vapor quality region. Furthermore, the pressure drops increased with increasing heat flux for lower to middle vapor quality, in contrast to pure refrigerants.

A Multispectral Spectroscopic Based Sensing System for Quality Parameters Measurement in Raw Milk Samples

Lactometer is used to monitor milk quality at various dairy centers but this may lead towards incorrect results because it requires human intervention and exact temperature correction as well as overall process is time-consuming. Presented work proposes the multispectral based spectroscopic approach along with the comparative study of different chemometric and artificial neural network (ANN) based techniques to measure different milk quality parameters. A multispectral spectroscopic sensing module has been designed using off the shelf components and further interfaced with 8-bit microcontroller based embedded system to produce three different spectrums of transmittance and scattering at +90 degree and –90 degree over the wavelength range of 340–1030 nm. Data acquisition process has been performed for 150 milk samples (cow, buffalo, and mix) collected from the bulk milk cooling center (BMC), Jaipur. Different statistical modeling techniques such as principle component regression (PCR), multiple linear regression (MLR) and partial least square regression (PLSR) have been implemented to develop correlation models between extracted features and target milk parameters. Implemented techniques have been compared based on the accuracy of their prediction models and it has been observed that PLSR shows better results compared to other two techniques. ANN-based modeling approach also has been explored to improve the accuracy of results. Five different artificial neural networks (ANN) based modeling techniques (LevenbergMarquardt, Bayesian regulation, scaled conjugate gradient, gradient descent and resilient) have been used to predict targeted milk quality parameters. Out of them, Gradient descent modeling technique performs better to predict fat content of the milk (R2 = 0.96198), Bayesian regulation performs better to predict lactose content (R2 = 0.90594) and others (solid non-fat (SNF), protein) are just satisfactory (R2 = 0.76077 for SNF using scaled conjugate gradient, R2 = 0.41935 for protein using Levenberg Marquardt). Produced results are validated with the MilkoScan FT1 system installed at Rajasthan Corporation of Dairy Federation (RCDF), Jaipur and it has been observed that results presented higher order of coefficient of determination as mentioned above (except protein, S.N.F.). A smartphone-based android application also has been developed to acquire data from the embedded system using Bluetooth protocol and transfer to cloud with the location information for further analysis.

Culture, Social Support, and Diabetes Empowerment Among American Indian Adults Living With Type 2 Diabetes.

OBJECTIVE | Type 2 diabetes represents a major health disparity for many American Indian/Alaska Native (AIAN) communities, in which prevalence rates are more than double that of the general U.S. population. Diabetes is a major indicator for other comorbidities, including the leading cause of death for AIANs (i.e., cardiovascular disease). This study investigated associations between protective factors (social support and cultural factors) and self-reported empowerment to manage illness. DESIGN AND METHODS | Participants were drawn from a random sample of tribal clinic records. Data included results from computer-assisted personal interviews with 192 American Indian adults with a diagnosis of type 2 diabetes living on or near a reservation. Community Research Councils, developed at each of the five partnering Anishinaabe reservations, oversaw protocols and procedures in this community-based participatory research collaboration. RESULTS | Multiple ordinary least squares regression models determined that general social support and diabetes-specific social support are positively related to diabetes empowerment. These associations persisted when both social support measures were added to the model, indicating independent effects of different types of social support. Cultural identity and cultural practices were positively related to diabetes empowerment in bivariate analyses; however, both measures dropped from statistical significance after accounting for all other covariates. An interaction term revealed a moderation effect through which cultural identity amplified the positive relationship between social support and diabetes empowerment. CONCLUSION | Results moderately support policy and risk-reduction efforts aiming at expanding social support networks into multiple domains and reinforcing cultural identity and cultural practices.

Rapid detection and prediction of chlortetracycline and oxytetracycline in animal feed using surface-enhanced Raman spectroscopy (SERS)

Surface-enhanced Raman spectroscopy (SERS) was examined to explore the feasibility of SERS technique to develop a rapid, non-destructive, and reliable spectroscopic method for qualitative and quantitative analysis of chlortetracycline (CTC) and oxytetracycline (OTC) in animal feed. Study samples were prepared by spiking tetracycline-free animal feed at different concentration ranges. In several Raman shift regions including characteristic peaks, spectral variation and Raman intensity difference among CTC and OTC groups at different concentrations were clearly visualized, depending on the type of tetracycline. The k-nearest neighbor (KNN) and linear discriminant analysis (LDA) models yielded excellent correct classification rates while showing no or only one misclassification of spiked samples as false-negative. The first two canonical variables in the chemometric modes for classification accounted for more than 95% variation in SERS spectra. Of the models developed for predicting CTC and OTC concentrations, multiple linear regression (MLR) and partial least squares regression (PLSR) models for CTC quantification showed outstanding model performance and ability, with coefficient of determination (r2) (>0.94), low predictive error rate (<10.0 mg/kg), and acceptable linear regression slope (close to 1.0). The slightly lower predictive power and model performance were observed in MLR and PLSR models for OTC quantification. The findings and implications from this study indicate that SERS can be an alternative or supplementary analytical technique with acceptable sensitivity and accuracy to existing standard chemical methods for rapid determination of select tetracyclines in animal feeds, serving as an excellent screening system for real-time monitoring of tetracycline contaminated feed samples.

Personal safety and improvements concerns in public places

PurposeCrime in public places is an increasing concern for the police, users of public places and the general public at large. Significantly, users of public transport facilities consistently perceive their risks from crime to be considerably higher, hurting levels of patronage. The aim of this study is to examine concerns for personal safety and measures that could improve sense of personal safety in a Nigerian public transport facility. This study further examines whether respondents’ perceptions determine frequent use of this public place. Explanatory factors are personal safety and place improvements concerns ratings.Design/methodology/approachThe study adopted a case study. The selection of this was accomplished using carefully defined criteria in previous studies. The research process consists of three steps the on-site assessment, objective insecurity assessment and subjective insecurity survey. Both quantitative and qualitative data were collected. Quantitative data were explored using mean ranking, percentages and correlation, whereas qualitative information was analysed using narrative techniques of reporting. To define the major determinants of the frequent use of this public place, a multiple ordinary least squares regression was constructed for variables in the correlation model.FindingsResults show that places within the site are not designed to meet crime prevention through environmental design strategies, as 625 crimes were documented with thefts well above other listed crimes. Respondents exhibited a significant level of concern for their safety across all the factors enumerated while the most important improvements concern was enhancements to lighting. Generally, findings suggest that there is still much to be done to improve elements of surveillance, access control, territoriality, image management and activity support on the site. Regression model shows that efforts to enhance perceived safety of users would have major significance on the frequent use of this facility.Practical implicationsPolicies on public place developments should be mainly in terms of tackling the environmental design of car parks and the effects of darkness at night time. This should involve improvement of lighting and the installation of CCTV, security camera as well as constant maintenance of bushes, vegetation, plants, trees and other elements of the landscape. Furthermore, the aesthetics of the site has to be attractive to users. The site and its closest surroundings have to be well-maintained and cared for. Besides, place lines and private areas must be defined with plants, pavement treatments, short walls or fences.Originality/valuePrevious studies on safety and security of public transport places, particularly rail facility, have mainly concentrated on the relations between fear of crime, perceived safety and place improvement concerns. To the best of authors’ knowledge, no study till date has explored how they correlate to the patronage of the transport facility, particularly in the sub-Saharan nations. This study contributes to existing literature having revealed perceived personal safety and transport place improvements concerns to be another important dimension of rail transport patronage in the Nigerian context.

Causality Nexus Between Electricity Consumption and Growth in Nigeria Manufacturing Sector

The study examined the causal relationship between electricity consumption and manufacturing sector’s growth in Nigeria using time series data covering the period 1986 – 2017. Multiple least square regression method was used to capture the effect of electricity consumption and other variables on manufacturing sector’s growth, with the aid of Eview software. Granger causality test was conducted to examine the direction of causality between electricity consumption and manufacturing sector’s growth. The study found that electricity consumption has positive and significant effect on the growth of the manufacturing sector. Also, the study revealed an evidence of unidirectional causality from manufacturing sector’s growth to electricity consumption. It was also infered from the trend analysis that Electricity Consumption in Nigeria has a positive and direct impact on the growth of Nigeria Manufacturing Sector. Since the study shows how electricity is vital to manufacturing sector, any impediment to electricity will grossly affect manufacturing sector’s growth. To enhance sustainable growth in manufacturing sector, appropriate reforms must come up to ensure stable electricity in Nigeria. Keywords: Electricity consumption, Causality, Trend analysis, Manufacturing sector. DOI: 10.7176/RHSS/10-6-04 Publication date: March 31 st 2020

Research on Photoelectric Detection and Identification System Based on ThreeStage Multiple Innovation Recursive Least Squares Algorithm

Research on Photoelectric Detection and Identification System Based on ThreeStage Multiple Innovation Recursive Least Squares Algorithm

Structural characterization of 8 MeV 11B implanted diamond

Boron is the most effective dopant element in diamond and the capability to introduce high densities of boron makes ion implantation a potential key technology to verify superconductivity in diamond. However, its optimization involves many experimental parameters (i.e. ion energy, fluence, current, annealing times and temperature) and the effectiveness of B implantation to induce superconductivity in diamond is still to be demonstrated. So far, a limited number of works in the range of high (i.e. >5 MeV) B ion energies have been carried, despite the promising perspective offered by deep implantation to fabricate sub-superficial superconductive structures in diamond. To this scope, in the present work, we report on the study of the structural effects of high-energy boron ion irradiation on diamond. Monocrystalline diamond sample was irradiated with an 8 MeV 11B microbeam across multiple square areas, characterized by a different combination of fluences and ion currents. After the implantation, the sample was characterized by Raman spectroscopy and Atomic Force Microscopy to assess its structural modifications and the related surface swelling. Significant variations related to the irradiation condition have been determined.

A New Equation for Calculation of Low-Density Lipoprotein Cholesterol in Patients With Normolipidemia and/or Hypertriglyceridemia

Low-density lipoprotein cholesterol (LDL-C), a key cardiovascular disease marker, is often estimated by the Friedewald or Martin equation, but calculating LDL-C is less accurate in patients with a low LDL-C level or hypertriglyceridemia (triglyceride [TG] levels ≥400 mg/dL). To design a more accurate LDL-C equation for patients with a low LDL-C level and/or hypertriglyceridemia. Data on LDL-C levels and other lipid measures from 8656 patients seen at the National Institutes of Health Clinical Center between January 1, 1976, and June 2, 1999, were analyzed by the β-quantification reference method (18 715 LDL-C test results) and were randomly divided into equally sized training and validation data sets. Using TG and non-high-density lipoprotein cholesterol as independent variables, multiple least squares regression was used to develop an equation for very low-density lipoprotein cholesterol, which was then used in a second equation for LDL-C. Equations were tested against the internal validation data set and multiple external data sets of either β-quantification LDL-C results (n = 28 891) or direct LDL-C test results (n = 252 888). Statistical analysis was performed from August 7, 2018, to July 18, 2019. Concordance between calculated and measured LDL-C levels by β-quantification, as assessed by various measures of test accuracy (correlation coefficient [R2], root mean square error [RMSE], mean absolute difference [MAD]), and percentage of patients misclassified at LDL-C treatment thresholds of 70, 100, and 190 mg/dL. Compared with β-quantification, the new equation was more accurate than other LDL-C equations (slope, 0.964; RMSE = 15.2 mg/dL; R2 = 0.9648; vs Friedewald equation: slope, 1.056; RMSE = 32 mg/dL; R2 = 0.8808; vs Martin equation: slope, 0.945; RMSE = 25.7 mg/dL; R2 = 0.9022), particularly for patients with hypertriglyceridemia (MAD = 24.9 mg/dL; vs Friedewald equation: MAD = 56.4 mg/dL; vs Martin equation: MAD = 44.8 mg/dL). The new equation calculates the LDL-C level in patients with TG levels up to 800 mg/dL as accurately as the Friedewald equation does for TG levels less than 400 mg/dL and was associated with 35% fewer misclassifications when patients with hypertriglyceridemia (TG levels, 400-800 mg/dL) were categorized into different LDL-C treatment groups. The new equation can be readily implemented by clinical laboratories with no additional costs compared with the standard lipid panel. It will allow for more accurate calculation of LDL-C level in patients with low LDL-C levels and/or hypertriglyceridemia (TG levels, ≤800 mg/dL) and thus should improve the use of LDL-C level in cardiovascular disease risk management.

Prediction of Soil Nutrients Based on Topographic Factors and Remote Sensing Index in a Coal Mining Area, China

(1) Background: Coal mining operations caused severe land subsidence and altered the distributions of soil nutrients that influenced by multiple environmental factors at different scales. However, the prediction performances for soil nutrients based on their scale-specific relationships with influencing factors remains undefined in the coal mining area. The objective of this study was to establish prediction models of soil nutrients based on their scale-specific relationships with influencing factors in a coal mining area. (2) Methods: Soil samples were collected based on a 1 × 1 km regular grid, and contents of soil organic matter, soil available nitrogen, soil available phosphorus, and soil available potassium were measured. The scale components of soil nutrients and the influencing factors collected from remote sensing and topographic factors were decomposed by two-dimensional empirical mode decomposition (2D-EMD), and the predictions for soil nutrients were established using the methods of multiple linear stepwise regression or partial least squares regression based on original samples (MLSROri or PLSROri), partial least squares regression based on bi-dimensional intrinsic mode function (PLSRBIMF), and the combined method of 2D-EMD, PLSR, and MLSR (2D-EMDPM). (3) Results: The correlation types and correlation coefficients between soil nutrients and influencing factors were scale-dependent. The variances of soil nutrients at smaller scale were stochastic and non-significantly correlated with influencing factors, while their variances at the larger scales were stable. The prediction performances in the coal mining area were better than those in the non-coal mining area, and 2D-EMDPM had the most stable performance. (4) Conclusions: The scale-dependent predictions can be used for soil nutrients in the coal mining areas.

Soft - sensing modeling based on ABC - MLSSVM inversion for marine low - temperature alkaline protease MP fermentation process

BackgroundAiming at the characteristics of nonlinear, multi-parameter, strong coupling and difficulty in direct on-line measurement of key biological parameters of marine low-temperature protease fermentation process, a soft-sensing modeling method based on artificial bee colony (ABC) and multiple least squares support vector machine (MLSSVM) inversion for marine protease fermentation process is proposed.MethodsFirstly, based on the material balance and the characteristics of the fermentation process, the dynamic “grey box” model of the fed-batch fermentation process of marine protease is established. The inverse model is constructed by analyzing the inverse system existence and introducing the characteristic information of the fermentation process. Then, the inverse model is identified off-line using MLSSVM. Meanwhile, in order to reduce the model error, the ABC algorithm is used to correct the inverse model. Finally, the corrected inverse model is connected in series to the marine alkaline protease MP fermentation process to form a composite pseudo-linear system, thus, real-time on-line prediction of key biological parameters in fermentation process can be realized.ResultsTaking the alkaline protease MP fermentation process as an example, the simulation results demonstrate that the soft-sensing modeling method can solve the real-time prediction problem of key biological parameters in the fermentation process on-line, and has higher accuracy and generalization ability than the traditional soft-sensing method of support vector machine.ConclusionsThe research provides a new method for soft-sensing modeling of key biological parameters in fermentation process, which can be extended to soft-sensing modeling of general nonlinear systems.