Linear Correlation Model Research Articles

Quantification of trace elements in molten aluminum with randomized impurity concentrations using laser-induced breakdown spectroscopy

An industrial molten metal chemical analyzer based on laser-induced breakdown spectroscopy (LIBS) has been used to perform concentration analysis of important trace elements (Fe,Si,Cr,Mn,Ti, 20-3000 ppm) in liquid aluminum. In order to rule out accidental correlations between different elements in the spectral analysis, the impurity concentration of the measured samples was fully randomized. Reference concentration measurements were performed using arc-spark optical emission spectroscopy (spark-OES) on solid samples cast from the full volume of the LIBS-analyzed melt. For elements Fe, Cr, Mn and Ti, correlation coefficients and prediction uncertainty of LIBS measurements, using a linear correlation model, are shown to be determined mainly by random measurement error, which was of the order of 1% for both the LIBS analysis and the spark-OES analysis for concentrations above 100 ppm for all of the investigated elements. In the case of silicon, we postulate that inhomogeneous solidification is leading to a reduced absolute accuracy of spark-OES reference measurements and a corresponding increase in the minimum prediction uncertainty. The results confirm that LIBS analysis of molten aluminum can be used for on-line process control in the aluminum industry by providing measurement accuracy comparable of current industry-standard laboratory analysis methods.

KORELASI DIAMETER TAJUK AERIAL DAN DIAMETER BATANG SETINGGI DADA (130 CM) BERBASIS CITRA DRONE DI KAWASAN HUTAN DENGAN TUJUAN KHUSUS (KHDTK) MANDIANGIN KALIMANTAN SELATAN

Many developed remote sensing to estimate the potential of the forest, one of them using drones, but important parameters such as stem diameter as high. The aim of this study was to determine the correlation model of aerial canopy diameter with chest diameter at the drone based tree. This research was conducted from February to April 2019 in Kawasan Hutan dengan Tujuan Khusus (KHDTK) Mandiangin, Lambung Mangkurat University, South Kalimantan. Air canopy diameter measurements were carried out on drone images in three density classes identified from the NDVI analysis, while breast diameter at breast height was carried out on land. The results of this study are the formation of a positive linear correlation model between stem diameter and aerial canopy diameter with the equation y꞊ 7.0627x - 6.4252 with a coefficient of determination (R2) = 0.6984 and a correlation coefficient (r) of 0.83. This shows that diameter at breast height affects the aerial canopy diameter of 83%

Updating Geometrically Nonlinear Reduced-Order Models Using Nonlinear Modes and Harmonic Balance

Nonlinear reduced-order models are being investigated for use as digital twins for advanced aircraft and spacecraft. In concept, the digital twin would be tuned to accurately describe the behavior of the vehicle, and then it would be updated as the vehicle is modified or ages. Unfortunately, the linear model correlation and validation techniques that are commonly used in the aerospace industry are not valid for nonlinear models, so a new set of tools is needed. This work presents an algorithm to update geometrically nonlinear reduced-order models using nonlinear normal modes as a correlation metric. The nonlinear normal modes serve as a strong metric to correlate the numerical models because they can be extracted from experiments, and they describe the dynamics of the nonlinear system over a range of amplitudes and are independent of the loading applied to the system. This paper presents a novel method of computing analytical gradients of nonlinear normal mode solutions with respect to system parameters using the multiharmonic balance method. The procedure is first tested using numerical simulations and then applied to tune the reduced-order model of a curved beam based on nominal blueprints and idealized boundary conditions to match a nonlinear normal mode that has been measured experimentally from a three-dimensional printed test specimen.

Water balance theory is more than 340 years old

This article shows that there occur systematic errors and omissions in water management design while using the existing water balance equation by Perrault (De l'origine des fontainesm, 1674). The existing balance equation does not include all water balance parameters. Such parameters as infiltration capacity of the bedrock and loss by runoff recession are meant here. In order to calculate water balance parameters more precisely, the author of the article presents the linear correlation model (Iofin in Bull Admir Makarov State Univ Marit Inland Shipp 3:18–27, 2013). The core of the model is the linear correlation equation which shows the dependence between the river runoff depth and precipitation depth in the river basin. The members of the equation are supported by the genetic runoff theory (Befany in Issues of regional hydrology, Peakflow UMKVO, Kiev, 1989). The point is that the part of the graph which is placed on the x-axis before the beginning of the runoff is related to the absorption into the soil. The part of the graph which is placed on the x-axis after the beginning of the runoff is related to the loss by runoff recession. This loss results in specific water movement down the slope. The part of the graph on the y-axis represents the river runoff depth loss by infiltration into the ground water. Every type of the slope runoffs contains these parts of the graph. The article contains mathematical expressions for perched and banked-upslope runoffs. In addition, the method of least rectangles introduced by Alekseev (In: Errors of measurement and empirical relationships. Gidrometeoizdat, Leningrad, 1962) is used in the work while graphing. This method differs from the method of least squares because it takes into account any deviation from the middle both in y-direction and x-direction. Such an approach helps to receive more precise correlation parameters. As for the method of least squares, it takes into account deviation from the middle in one direction only. The usage of the three methods together—the linear correlation model, the genetic runoff theory and the method of least rectangles—helps to calculate the necessary water balance parameters and to introduce the complete water balance equation.

Water balance of several subarctic catchment areas

The scientific article by American hydrologists (Bolton et al. in Water balance dynamics of three small catchments in a Sub-Arctic boreal forest, 2004. https://pdfs.semanticscholar.org/c06b/7bad86cc15c5625fef0d847748bd9468f989.pdf) which is devoted to the water balance of three subarctic catchment areas, evoked great interest and encouraged to continue research in this field. The article deals with water balance elements of three small subarctic catchment areas near Fairbanks, Alaska, USA, published on the Internet (Bolton et al. 2004). The catchment area under study is Cariboo-Pocker Creek (CACPC). It is 48 km to the north of Fairbanks, Alaska. CACPC is situated in the tundra, its territory is 101.5 km2 and the soil below the surface of the ground is always frozen. Three catchment areas within CACPC are: C-2 (5.2 km2), C-3 (5.7 km2) and C-4 (11.4 km2). The catchment areas consist of 3%, 53% and 19% of permafrost, respectively. Taking into consideration the information from the American research, it turned out to be rather interesting to compare some water balance parameters presented in the article with those which are calculated with the help of a new method (Iofin in Proceedings of VI all-Russia hydrology congress, vol 1, pp 62–67, 2004). This new method is based on the linear-correlation theory and linear-correlation equation of water balance. This method has an effect in the catchment areas where hydrological observations are not carried out. Apart from this comparison, it is also of great interest to calculate the value of infiltration capacity in permafrost areas. It is also compelling to learn how accurately evapotranspiration in permafrost areas with lack of observations can be calculated with the help of rather popular Priestley–Taylor equation. The accuracy of calculation of evapotranspiration in a number of regions in the temperate zone made by Russian scientists with the help of different existing empirical formulae was under consideration. It is proved to be unsatisfactory. We had a rare opportunity to use basic data from the permafrost area and to calculate infiltration capacity and evapotranspiration. The comparison of the values of evapotranspiration shows that the calculations made with the help of the linear-correlation model (LCM) and Priestley–Taylor equation differ considerably.

Numerical Simulation of the Influence of Flow Velocity on Granite Temperature Field Under Thermal Shock

Under thermal shock, the heat conduction between granite and fluid will lead to the redistribution of rock temperature field, while indoor thermal shock test cannot determine the distribution rule of temperature field inside granite accurately. In order to explore the influence of fluid velocity on the thermal shock process of granite, the temperature field and flow field is numerically simulated by COMSOL. The results show that heat transfer between granite and fluid is in the form of waves. In the process of heat conduction, the internal temperature and heat balance time of granite are greater than those of rock surface. The time of heat balance in rock provides reference for the design of indoor thermal shock test. After thermal shock, the temperature of granite is lower than the initial temperature. With the increase of fluid velocity, the thermal equilibrium time of granite decreases, and the final rock stable temperature decreases. According to the relationship between velocity and granite temperature, a linear correlation model between velocity and maximum instantaneous thermal shock velocity is proposed. It is also verified that the thermal fluid–solid coupling model of granite under thermal shock is feasible to simulate the heat conduction and temperature distribution in granite.

Comparative In Vitro and In Vivo Evaluation of Fenofibric Acid as an Antihyperlipidemic Drug.

Fenofibric acid (FA) is antihyperlipidemic agent and commercially available as a tablet formulation that weighs 840 mg for 105 mg of active substance. A new formulation with less inactive substance was developed as an alternative to the conventional formulation. The purpose of this study was to evaluate the dissolution and the relative bioavailability of the surface solid dispersion (SSD) and conventional formulations of FA by comparing them with the reference formulation in its commercial tablets. The in vitro-in vivo correlation among these tablet formulations was also evaluated. The dissolution study was performed in phosphate buffer pH 6.8 and biorelevant fasted state simulated intestinal fluid. Dissolution efficiency and mean dissolution time (MDT) were used to compare the dissolution profiles. The bioavailability study, using nine healthy volunteers, was conducted based on a single-dose, fasted, randomized, crossover design. The in vivo performance was compared using the pharmacokinetic parameters Cmax, Tmax, AUC0-72, and AUC0-∞. A linear correlation model was tested using MDT and mean residence time (MRT). The results indicated that there were significant differences in the dissolution performances but no significant differences among the mean Cmax, Tmax, AUC0-72, or AUC0-∞ estimated from the SSD, conventional, and reference formulations. A poor correlation was found between MRT and MDT of the three formulations. The SSD formulation led to an instantaneous dissolution of the drug due to the presence of the polymer and the physical structure of the SSD. The conventional formulation could not achieve rapid dissolution despite its satisfying the requirement for immediate drug release dosage form. Both formulations could be considered bioequivalent with the reference. The in vitro dissolution behavior of FA using a single medium did not reflect their in vivo properties in the fasted condition. There was no correlation between the in vitro dissolution and the in vivo bioavailability of FA in this condition.

Dynamic monitoring of desertification in Naiman Banner based on feature space models with typical surface parameters derived from LANDSAT images

AbstractNaiman Banner is one of the most typical semi‐arid vulnerable ecological zones that is characterized by vegetation degradation and severe desertification. Previous studies mostly utilized a single feature space or only the linear correlation model to monitor desertification. In this study, the optimal monitoring model that fully considers the multiple feature spaces and the nonlinear relationship between surface parameters in Naiman Banner was determined, and then the spatial–temporal evolution patterns of the desertification from 1989 to 2017 were analyzed. The results showed that: (a) The albedo–normalized difference vegetation index point‐to‐point model was applicable to areas with high‐vegetation coverage, whereas the albedo–modified soil‐adjusted vegetation index (MSAVI) linear model had better applicability in areas with relatively low vegetation coverage. Considering the surface cover, the desertification monitoring index based on albedo‐MSAVI linear model had the best applicability. (b) During 1989–2017, the total desertification area percentage of Naiman County decreased from 90.85% in 1989 to 63.35% in 2017, showing a significant downward trend. (c) During the past 30 years, the desertification process was significantly influenced by human activities, such as ‘Three‐North’ Shelterbelt, Returning Farmland to Forestry, and Returning Farmland to Grassland (d) The desertification levels of unused land and grassland with low coverage was relatively high, whereas the desertification degree of cultivated and forest lands was low. These results can be used as an effective reference for the remote sensing monitoring and evaluation of desertification and can provide data and decision support for the ecological restoration of the region.

Technical and economic viability of manual harvesting coffee yield maps

Precision coffee growing is a concept that implies the use of precision agriculture techniques in coffee plantations. For the coffee growing, the precision electronic resources coupled to the harvesters are very scarce. Thereby, the harvest of coffee plantations that compose the grid sampling for generation of thematic maps can be performed manually. The aim of the present study was to generate a linear regression model to estimate the time required to harvest, estimate the labor costs to harvest manually the georeferenced sample points for generation of coffee yield maps. The study was performed in a coffee area of 56 hectares using two sampling points per hectare, totaling 112 points, being evaluated four coffee plants for each point. The manual harvest of the points was performed by four rural workers with experience in the coffee harvest. Afterwards, the collected volume was measured by a graduated container and the times were obtained by the digital stopwatch. Based on the data obtained in the field, a linear correlation model was established between the harvest time of each sampling point and the yield of the point, whose R² value was 78.27, cost was R$ 8.92 per point. These results are relevant for estimating the amount of labor force required to generate manually harvest yield maps according to the producer’s coffee yield estimate, contributing to the closure of the precision coffee growing cycle. Key words: Precision agriculture; crop mapping; field efficiency; costs.

Establishment of a Linear Correlation Model of Central Venous Blood Oxygen Saturation and Lactate in Sepsis

Introduction: Studies have shown that there is a complex relationship between lactate and ScvO2. Methods: A retrospective study was carried out in 37 intensive care patients with sepsis or septic shock. The relationship between lactate and ScvO2 was explored with correlation analysis and simple linear modelling. Results: Lactate and ScvO2 were significantly correlated in patients with septic shock (r2 = 0.46, p = 0.001; y = -4.11x+ 82.62), but not in sepsis. y Significant correlation between these parameters was also found in the group of patients who went on to die (r2 = 0.67, p < 0.01; y = -3.70x + 78.61), but not in patients who survived. Conclusions: In sepsis, the correlation between ScvO2 and lactate is not constant over the sepsis course and may be dynamic. In the resuscitation of sepsis and/or septic shock, changes in ScvO2 requires further study.

Measuring the liquid limit of soils using different fall-cone apparatuses: A statistical analysis

The fall-cone test allows estimating the liquid limit of clayey soils in the laboratory. Due to its reliability and simplicity, several versions of the equipment have been developed around the world. The main variations between these versions include differences in the weight and geometrical dimensions of the cones. This study explores the measuring of liquid limit using eight types of fall-cone apparatuses, including a proposed one with new configuration. A several number of tests on a natural soil from the lacustrine deposits of Bogotá and industrial Kaolin were conducted. The liquid limit results of all implemented cones in this study against values obtained in the same soils from the conventional percussion-cup (or Casagrande method) using a linear correlation model were compared. On the other hand, data was validated and interpreted by means of a statistical approach, which allowed estimating the repeatability of the methods. Conclusions focused on the similarities between the eight cone configurations and conventional percussion-cup test addressing the descriptive exploration, analysis of variance, two-by-two comparisons and correlation between testing methods.

Temporal progression of foliar plant diseases in corn hybrids

The environment’s impact on foliar disease growth in annual crops and the various types of differentiation must be investigated to adapt effective disease control strategies. We studied the temporal progression of foliar disease complexes in 14 commercial corn (Zea mays L.) hybrids during the 2015/2016 crop season (Ipameri, Goiás, Brazil). The experiment consisted of 10 blocks and evaluated foliar disease severity using a diagrammatic scale. The evaluations occurred at 47, 53, 59, 74, 81 and 95 days after planting. At each time point, a plant was chosen randomly from each block (10 plants total), and the diseases causing foliar damage were identified. The areas under the disease progression curves (AUDPCs) and yields were calculated. Dependent variables were evaluated using a principal component analysis to study relationships between the hybrids and the disease severity on each leaf (biplot). Heatmaps were used to determine which leaves demonstrated the greatest disease severity and temporal disease progression, and an adjusted linear correlation model was used to predict yield relative to AUDPC. The foliar disease complex consisted of helmintosporiosis, common rust, macrospora leaf spot, cercosporiosis and maize white spot. The Ns90PRO© hybrid showed limited disease progression and; therefore, was considered more resistant and consequently had a lower AUDPC value. The Dow2B610PW© hybrid showed greater disease progression. Agroceres7098PRO2© had a greater yield and consequently a lower AUDPC value, while Lg6050PRO2© had a lower yield and a higher AUDPC value. In general, the more advanced the phenological stage, the more severe the leaf disease; however, disease progression (from plant base to plant tip) was genotype- dependent.

Preference of Co over Al for substitution of Fe in goethite (α-FeOOH) structure: Mechanism revealed from EXAFS, XPS, DFT and linear free energy correlation model

Goethite is the most stable iron hydroxide mineral in geological environments, and it is usually crystallized with more than one type of substituent. However, the synergetic or antagonistic effects of coexisting cations on substitution for lattice Fe in gothite are unclear. In this study, a series of Co-, Al-, and Co + Al co-substituted goethite samples were synthesized at room temperature and then investigated by powder XRD, X-ray photoelectron spectroscopy (XPS), X-ray absorption fine structure spectroscopy (XAFS), density function theory (DFT) calculations, and acid dissolution experiments. All the obtained samples were pure goethite, except the one with a high total content of Co + Al that contained a portion of 2-line ferrihydrite. Lattice parameter a of Co + Al co-substituted goethite was linearly decreased with the final Co content, lattice parameter b and calculated crystal density had the best negatively linear relationships with Al content while lattice parameter c, cell volume, average edge-sharing Fe − Me (Me = Fe, Al, and Co) distances along c⁎ and b⁎ axis (E′ and E) and average corner-sharing Fe − Me (DC) distances had the best linear correlations with the total contents of Co + Al. Aluminum and Co were found to be evenly distributed in goethite structure, and both reduced the mineral particle size. Co coexisted in a mixed valance of +2 and +3, and the proportion of Co3+ increased with the increase of Co content in Co-substituted goethite owing to relatively high electric potential energy and decreased with the increase of coexisting Al3+ content in Co + Al co-substituted goethites because of relatively low alkalinity in local environments around Co2+. Incorporation of Co greatly promoted the mineral dissolution in 2 M HCl solution at 298 K. Fe K-edge EXAFS analysis indicated almost constant local order around Fe in these samples. Coexisting Al had almost no effect on Co incorporation into goethite structure but Co suppressed Al substitution for lattice Fe. This preference of Co over Al to substitute for Fe was explained by the predicted partition coefficients (Kd) of common trivalent substituents in goethite by using the linear free energy relationship. It highlights the necessity to take into consideration not only the substituent physical properties (size and charge) but also their chemical properties (chemical bonding energy and chemical potential). These results enhanced our understanding of the incorporation of exotic cations into the iron oxide structures and the mutual effects of coexisting cations on substitution for lattice Fe.

Investigation of the mechanical performance of fiber-modified ceramic composites using finite element method

Ceramic materials are widely used in impact safekeeping systems. Ceramic is a heterogeneous material; its characteristics depend considerably both on specifications of its ingredients and the material structure completely. The finite element method (FEM) can be a useful tool for strength computation of these materials. In this paper, the mechanical properties of the ceramic composites are investigated, and the mechanical performance modeling of fiber-fortified ceramic matrix composites (CMC) is expressed by the instance of aluminum oxide fibers in a matrix composite based on alumina. The starting point of the modeling is an infrastructure (primary cell) that contains a micromechanical size, the statistical analysis characteristics of the matrix, fiber-matrix interface, fiber, and their reciprocal influences. The numeral assessment of the model is done using the FEM. The numerical results of composite elastic modulus were computed based on the amount of the added fibers and the porosity was evaluated for empirical data of samples with a similar composition. Various scanning electron microscope (SEM) images were used for each sample to specify the porosity. Also, the unit cell method presumed that the porous ceramic substance is manufactured from an array of fundamental units, each with the same composition, material characteristic, and cell geometry. The results showed that when the material consists of different pores and fibers, the amount of Young’s modulus reduces with the increment of porosity. The linear correlation model of elasticity versus porosity value from experimental data was derived by MATLAB curve fitting. The experimental data from the mechanical test and numerical values were in good agreement.

Relationships between structural features and reactivities of coal-chars prepared in CO2 and H2O atmospheres

Under various combustion process, CO2 and H2O both have important effects in the evolution of the structures and reactivities of chars. The purpose of this study is to investigate the characteristics of coal char after reacted under the atmospheres containing CO2 and H2O in the temperature range of 500–1000 °C. Micro-Raman and FT-IR spectrometer were used to reveal the evolution of char structural characteristic, and char reactivities were measured at isothermal condition under 70%CO2/30%O2 atmosphere on a thermogravimetric analyzer (TGA). The experimental results indicate that 700 °C was the initial temperature for additional weight loss of char which caused by H2O and CO2 gasification, and the influences of H2O gasification were obviously more drastic than that of CO2 gasification along with lower char yield under H2O containing atmospheres. It was found that more O-containing functional groups contained in the chars which prepared in CO2 and H2O atmospheres and the addition of CO2 accelerated the condensation of aromatic rings in the char, which means a more aromatic structure in char, that is, less aromatic monomers and greater condensation of them in cluster. Condensation of H2O-char and CO2/H2O-char greatly decreased at 500–700 °C and then drastically increased at 700–1000 °C. The positive correlation between the Raman parameters (I(Gr + Vr + Vl)/ID) and the char reactivity parameters (R20, R50, R80, and Rmax) was observed, which can be represented by different linear correlation model under different atmospheres.

Dependency Between Protein\u2013Protein Interactions and Protein Variability and Evolutionary Rates in Vertebrates: Observed Relationships and Stochastic Modeling

Recent developments in sequencing and growth of bioinformatics resources provide us with vast depositories of protein network and single nucleotide polymorphism data. It allows us to re-examine, on a larger and more comprehensive scale, the relationship between protein–protein interactions and protein variability and evolutionary rates. This relationship has remained far from unambiguously resolved for quite a long time, reflecting shifting analysis approaches in the literature, and growing data availability. In this study, we utilized several public genomic databases to investigate this relationship in human, mouse, pig, chicken, and zebrafish. We observed strong non-linear relationship patterns (tending towards convex decreasing function shapes) between protein variability and the density of corresponding protein–protein interactions across all five species. To investigate further, we carried out stochastic simulations, modeling the interplay between protein connectivity and variability. Our results indicate that a simple negative linear correlation model, often suggested (or tacitly assumed) in the literature, as either a null or an alternative hypothesis, is not a good fit with the observed data. After considering different (but still relatively simple, and not overfitting) simulation models, we found that a convex decreasing protein variability–connectivity function (specifically, exponential decay) led to a much better fit with the real data. We conclude that simple correlation models might be inadequate for describing protein variability–connectivity interplay in vertebrates; they often tend towards false negatives (showing no more than marginal linear or rank correlation where there are in fact strong non-random patterns).

Assessment of scoring functions and in silico parameters for AChE-ligand interactions as a tool for predicting inhibition potency

In this study, 68 crystal structures of complexes between acetylcholinesterase (AChE, EC 3.1.1.7) and its ligands, deposited in the PDB, were analyzed by scoring the functions: LigScore1, LigScore2, PLP1, PLP2, Jain, PMF and PMF04. The scores derived from scoring functions were correlated with an inhibition constant for each ligand (Ki or IC50) in a broad range 10−3 – 10−12 M. The linear correlation model resulted in the highest coefficient of determination (r2) for the PLP2 function, 0.591. The LigScore1 function resulted in the lowest r2 value of 0.226. The PubChem database was the source of in silico computed ligand properties which were then correlated with an inhibition constant for each ligand. For the purposes of this study, two additional non-PubChem parameters were evaluated: total and relative number of sp2 hybridized atoms in the ligand. A high coefficient of determination (r2 > 0.5) was calculated for the following parameters: the number of heavy atoms, molecular mass, and number of atoms with sp2 hybridization. The PLP2 scoring function is a good candidate for drug discovery related to AChE, although a better scoring function could be developed with a higher number of crystal structures of AChE complexes and more reliable kinetic data.

Estimation of global solar radiation, sunshine hour distribution and clearness index in Enugu, Nigeria

The concept of solar energy and its applications in this present day world would come to be one of the solutions to our present Nigerian problem of instability and epileptic power supply. In the study, the baseline data for mean monthly sunshine hours ( S ) and global solar radiation ( H ) for Enugu (6.7 0 N, 7.6 0 E) were obtained from the Nigeria Metrological Agency (NIMET), Oshodi Lagos Nigeria and spanned 1996 to 2010. The data for global solar radiation were measured with a Gunn-Bellani radiometer. The average sunshine hour for the period of study was estimated to be 5.67 hours; the Angstrom constants a and b of Angstrom-type correlation used in estimating monthly average global solar radiation was estimated to be 0.27 and 0.58 respectively; a linear regression correlation model was developed for Enugu. The result of global solar radiation was found to be 14.44 MJm -2 day -1 thereafter subjected to statistical tests [ MBE , RMSE , MPE ] and proved to be good estimates with previous literatures reviewed. The value of clearness index ( K T ) was estimated to range from 0.43 to 0.61 showing Enugu as so a partly clear sky city. Keywords: Global solar radiation, Sunshine hour distribution, Clearness Index Enugu

Association between selected trace elements and body mass index and waist circumference: A cross sectional study

BackgroundThe prevalence of obesity has increased worldwide. Abnormal plasma level of some trace elements may be associated with obesity. The present study was designed to compare the plasma level of zinc, phosphate, calcium and magnesium with the degree of body mass index and waist circumference. Material and methodsIn this cross sectional study 149 persons (20–60 years old) from March 2014 till April 2017 were included. Definition of central obesity was waist circumference (WC)≥ 102 cm and ≥88 cm in men and women, respectively. Also BMI categorized to: normal weight: 18.50–24.99, overweight: 25.00–29.99 and obese: ≥30 kg/m2 respectively.Mg, Ca, P and Zinc in plasma was checked after12 h fasting in each persons. Comparison between the level of Mg, P, Ca and Zinc by three categories of BMI or waist circumference performed. The data were analyzed by independent T-test and one-way ANOVA. Scheffe method was used to determine post-hoc pair-wise comparisons. The relationship between BMI and concentration of elements was detected by linear correlation and Cubic model. A p ≤ 0.05 were considered statistically significant. Statistical analyses were executed by SPSS version 20. ResultsIn this study, 32.2% male and remainder female, mean age of 42.26 ± 13.03 were participated. 40.9% were normal and 59.1% obese base on waist circumference. Also 24.8% normal,44.3% overweight and remainder was obese according to BMI. Obese subjects base on waist circumference had significantly lower serum Zinc(pvalue:0.002), Ca (pvalue:0.0001)and Mg(pvalue:0.042) concentration. Whereas, P concentration was significantly higher in obese cases in comparison with normal subjects(pvalue:0.012). Also normal cases had significantly higher serum Zinc (pvalue: 0.0001), Ca (pvalue:0.0001), and Mg(pvalue:0.006) concentration compared to overweight and obese subjects according to BMI categorizes. ConclusionInverse correlation present between plasma zinc, calcium and magnesium level and BMI and waist circumference, but positive correlation seen between P level and waist circumference. Further studies are needed to evaluate the effect of dietary or supplemental interventions on obesity and central obesity.

Estimation of Global Solar Radiation and Clearness Index in Coast of Gulf of Guinea, Nigeria

The concept of solar energy and its applications in present day would come to be one of the solutions to our Nigerian problem of instability and epileptic power supply. In this study, data for mean monthly sunshine hours and global solar radiation for Ikeja, Lagos state capital (6.580N, 3.320E) were obtained from Nigeria Metrological Agency (NiMeT), Oshodi Lagos, Nigeria and spanned 1996 to 2010. The data for global solar radiation were measured using a Gunn-Bellani radiometer. A linear regression correlation model was developed for Ikeja and other surrounding area in south-western part of Nigeria with similar meteorological conditions. The results of estimated global solar radiation ranged from 5.1 MJm-2 day-1 on average for August and 13.1 MJm-2 day-1 for March for Lagos. The Angstrom constants a and b of Angstrom-type correlation to estimate monthly average global solar radiation was estimated to be 0.25 and 0.63 respectively. The result for global solar radiation were then subjected to statistical tests [MBE, RMSE, MPE] and proved to be good estimates. The value of clearness index was also estimated to range from 0.31 to 0.59 showing Lagos as a partly clear sky city.