scholarly journals Development of an Analytical Model for the Extraction of Manganese from Marine Nodules

Metals ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 903 ◽  
Author(s):  
Saldaña ◽  
Toro ◽  
Castillo ◽  
Hernández ◽  
Trigueros ◽  
...  
Keyword(s):  
Particle Size ◽  
Analytical Model ◽  
Value Chain ◽  
Analytical Models ◽  
Copper Extraction ◽  
Independent Variables ◽  
Dependent Variables ◽  
Extended Value ◽  
Mn Recovery ◽  
By Products

Multivariable analytical models provide a descriptive (albeit approximate) mathematical relationship between a set of independent variables and one or more dependent variables. The current work develops an analytical model that extends a design of experiments for the leaching of manganese from marine nodules, using sulfuric acid (H2SO4) in the presence of iron-containing tailings, which are both by-products of conventional copper extraction. The experiments are configured to address the effect of time, particle size, acid concentration, Fe2O3/MnO2 ratio, stirring speed and temperature, under typical industrial conditions. The recovery of manganese has been modeled using a first order differential equation that accurately fits experimental results, noting that Fe2O3/MnO2 and temperature are the most critical independent variables, while the particle size is the least influential (under typical conditions). This study obtains representative fitting parameters, that can be used to explore the incorporation of Mn recovery from marine nodules, as part of the extended value chain of copper sulfide processing.

scholarly journals Development of an empirical model for copper extraction from chalcocite in chloride media

2020 ◽  
Vol 74 (5) ◽  
pp. 285-292
Author(s):  
Manuel Saldaña ◽  
Freddy Rodríguez ◽  
Anyelo Rojas ◽  
Kevin Pérez ◽  
Palma Angulo
Keyword(s):  
Copper Sulfide ◽  
Mining Industry ◽  
Chloride Concentration ◽  
Analytical Models ◽  
Quadratic Model ◽  
Copper Extraction ◽  
Multivariate Models ◽  
Independent Variables ◽  
Dependent Variables ◽  
Optimization Methodology

Multivariate models are a useful tool when studying the effects of independent variables on one or more dependent variables, since this approach allows modeling of the dynamics of complex systems based on simple analytical models with considerable certainty. Due to the decrease in the copper oxide mineral grades, leaching of copper sulfide minerals (secondary sulfides) has positioned itself as a benchmark of operation for the Chilean mining industry. The present work proposes the study of the effects of sulfuric acid, chloride concentration and time on the extraction of copper from sulfuric minerals (chalcocite), considering an experimental design, the surface optimization methodology and the adjustment of a quadratic model. The experimental data were adjusted by multiple regression analysis and were statistically analyzed. A model was developed to represent the copper extraction from the Cu2S mineral as a function of the statistically significant variables (chloride concentration and time) that contribute to explain the variation of the response variable under the set of parameters sampled.

INFLUENCE OF SELECTED VARIABLES ON FABRICATION OF MUPIROCIN LOADED PLGA NANOCARRIERS

INDIAN DRUGS ◽  
2017 ◽  
Vol 54 (05) ◽  
pp. 67-71
Author(s):  
R. K Panik ◽  
◽  
M. R Singh ◽  
D. Singh
Keyword(s):  
Particle Size ◽  
Surfactant Concentration ◽  
Drug Loading ◽  
Entrapment Efficiency ◽  
Plga Nanoparticles ◽  
Independent Variables ◽  
Nanoprecipitation Method ◽  
Dependent Variables ◽  
Effective Delivery ◽  
Polymer Ratio

Aim of the study was to develop PLGA nanoparticles (PLGA-NP) of mupirocin (MP) and to study the effect of independent variables in order to optimize the formulation for effective delivery. Drug loaded PLGA-NPs were successfully prepared by nanoprecipitation method and characterized by mean particle size, zeta potential, entrapment efficiency, drug loading, drug release, TEM, and DSC study. Independent variables like drug-polymer ratio, surfactant concentration, and stirring speed showed significant effect on the dependent variables like particle size, entrapment efficiency and drug loading. The ANOVA results showed that selected independent variables had a significant effect on the preparation of mupirocin loaded PLGA-NP.

scholarly journals Development and Optimization of Acriflavine-Loaded Polycaprolactone Nanoparticles Using Box–Behnken Design for Burn Wound Healing Applications

Polymers ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 101
Author(s):  
Touseef Nawaz ◽  
Muhammad Iqbal ◽  
Barkat Ali Khan ◽  
Asif Nawaz ◽  
Talib Hussain ◽  
...  
Keyword(s):  
Particle Size ◽  
Wound Healing ◽  
Encapsulation Efficiency ◽  
Burst Release ◽  
Burn Wound ◽  
Box Behnken Design ◽  
Independent Variables ◽  
Morphological Studies ◽  
Dependent Variables

Nanoparticles are used increasingly for the treatment of different disorders, including burn wounds of the skin, due to their important role in wound healing. In this study, acriflavine-loaded poly (ε-caprolactone) nanoparticles (ACR-PCL-NPs) were prepared using a double-emulsion solvent evaporation method. All the formulations were prepared and optimized by using a Box–Behnken design. Formulations were evaluated for the effect of independent variables, i.e., poly (ε-caprolactone) (PCL) amount (X1), stirring speed of external phase (X2), and polyvinyl alcohol (PVA) concentration (X3), on the formulation-dependent variables (particle size, polydispersity index (PDI), and encapsulation efficiency) of ACR-PCL-NPs. The zeta potential, PDI, particle size, and encapsulation efficiency of optimized ACR-PCL-NPs were found to be −3.98 ± 1.58 mV, 0.270 ± 0.19, 469.2 ± 5.6 nm, and 71.9 ± 5.32%, respectively. The independent variables were found to be in excellent correlation with the dependent variables. The release of acriflavine from optimized ACR-PCL-NPs was in biphasic style with the initial burst release, followed by a slow release for up to 24 h of the in vitro study. Morphological studies of optimized ACR-PCL-NPs revealed the smooth surfaces and spherical shapes of the particles. Thermal and FTIR analyses revealed the drug–polymer compatibility of ACR-PCL-NPs. The drug-treated group showed significant re-epithelialization, as compared to the controlled group.

scholarly journals Formulation and Optimization of Sustained Release Stavudine Microspheres Using Response Surface Methodology

2011 ◽  
Vol 2011 ◽  
pp. 1-7 ◽  
Author(s):  
Sanjay Dey ◽  
Soumen Pramanik ◽  
Ananya Malgope
Keyword(s):  
Particle Size ◽  
Drug Release ◽  
Entrapment Efficiency ◽  
Sustained Drug Release ◽  
Independent Variables ◽  
Optimum Formulation ◽  
Dependent Variables ◽  
High Entrapment Efficiency ◽  
Full Factorial

The aim of the current study was to formulate and optimize the formulation on the basis of in vitro performance of microsphere. A full factorial design was employed to study the effect of independent variables, polymer-to-drug ratio () and stirring speed (), on dependent variables, encapsulation efficiency, particle size, and time to 80% drug release. The best batch exhibited a high entrapment efficiency of 70% and mean particle size 290 μm. The drug release was also sustained for more than 12 hours. The study helped in finding the optimum formulation with excellent sustained drug release.

scholarly journals FORMULATION AND EVALUATION OF MOISTURIZING CREAM CONTAINING SUNFLOWER WAX

2018 ◽  
Vol 10 (11) ◽  
pp. 54 ◽  
Author(s):  
Avish D. Maru ◽  
Swaroop R. Lahoti
Keyword(s):  
Particle Size ◽  
Stearic Acid ◽  
Physicochemical Parameters ◽  
Research Work ◽  
Independent Variables ◽  
Dependent Variables ◽  
Full Factorial ◽  
32 Full Factorial Design ◽  
Sunflower Wax

Objective: The main objective of the present investigation was to design, prepare and evaluate moisturizing cream using sunflower wax.Methods: In the present work 32 full factorial design was applied to study the effect of varying concentration of independent variables stearic acid (X1) and sunflower wax (X2) on dependent variables viscosity and spreadability. All of the prepared formulations of moisturizing cream were evaluated for its physicochemical parameters. Further, the optimized formulation and selected commercial moisturizer compared and evaluated for its physicochemical parameters like pH, particle size, spreadability, viscosity and in vitro occlusivity test.Results: Nine different formulations of the moisturizing cream were prepared and all the findings obtained were within the prescribed limit. When compared to the prototype formulation of cream, the formulation MF5 showed good viscosity, in vitro occlusivity and spreadability. From the nine different formulations, MF5 containing 2 % stearic acid and 2 % sunflower was chosen as the optimized formula. Optimization was done on the basis of in vitro occlusivity studies and physicochemical parameters.Conclusion: The results obtained in this research work clearly showed a promising potential of moisturizing cream containing a specific ratio of stearic acid and sunflower wax as emulsifiers. Thus it can be concluded that sunflower wax is incorporated in the moisturizing cream, to avail of its cosmetic benefits.

ANALISA PENGARUH IKLIM ORGANISASI DAN KOMPETENSI TERHADAP KINERJA PEGAWAI PT HUTAMA KARYA

2018 ◽  
Vol 5 (1) ◽  
Author(s):  
Erik Wardhana, MM.
Keyword(s):  
Organizational Climate ◽  
Employee Performance ◽  
Sampling Technique ◽  
Simple Random Sampling ◽  
Free Variable ◽  
Independent Variables ◽  
Dependent Variables ◽  
Correlational Approach ◽  
Survey Research Methods ◽  
The Relationship

This study entitled "Analysis of Effect of Climate Organization and Competence Againt Employee PT. Hutama Karya ". The purpose of this study was to obtain information on the relationship between the free variable that organizational climate (X1) and competence (X2) with the dependent variable is employee performance (Y), either partially or simultaneously, This study used survey research methods with the correlational approach and predictive, which aims for the relationship and influence between independent and dependent variables. The sampling technique can be done randomly (simple random sampling) of 852 employees, which is considered to resprentatif is 89 people. And to solve problems, to analyze and examine the relationship and influence between the independent variables on the dependent variable used models kausalistik through regression analysis with SPSS 14.0

PENGARUH PERSONAL BACKGROUND, POLITICAL BACKGROUND DAN PENGEATAHUAN DEWAN TENTANG ANGGARAN TERHADAP PERAN DPRD DALAM PENGAWASAN KEUANGAN DAERAH

2008 ◽  
Author(s):  
Yesi Mutia Basri ◽  
Rosliana Rosliana
Keyword(s):  
Multivariate Analysis ◽  
Significant Influence ◽  
Political Activity ◽  
Primary Data ◽  
Financial Control ◽  
Independent Variables ◽  
Dependent Variables ◽  
Political Background ◽  
Activity Dependent

This research aim to examine the influence of personal background, political background, and council budget knowledge towards the role of DPRD on region financial control. This research is motivated by the fact that individual background will effect to individual behavior on political activity. Dependent variables in this research are personal background, political background, and council budges knowledge towards the role of DPRD on region financial control Independent variables are the role of DPRD on region financial control in planning, implementing, and responsibility steps. The data in this research consist of primary data that taken from questionnaires distributed directly to respondents. The collected are from 34 Respondents that members of DPRD at Pekanbaru. Hypothesis of this research are examine by using Multivariate Analysis of Variances (MANOVA). The result of this research HI personal background political background and budget knowledge have significant influence toward the role of DPRD on region financial control in planning steps.H2 personal background, politico I background and budget knowledge have no significant influence toward the role of DPRD on region financial control in Implementing steps. H3 personal background political background and budget knowledge have no significant influence toward the role of DPRD on region financial control in Controlling steps.

Application of Plakett-Burman Screening Design in Optimization of Process Parameters for Formulation of Canaglifozin Nanosuspension

2020 ◽  
Vol 13 (6) ◽  
pp. 5208-5216
Author(s):  
Nisha Patel ◽  
Hitesh A Patel
Keyword(s):  
Particle Size ◽  
Particle Diameter ◽  
Spherical Shape ◽  
Water Soluble ◽  
Pareto Chart ◽  
Independent Variables ◽  
Mean Particle Size ◽  
Screening Design ◽  
Stirring Time ◽  
Response Variables

In this study, we sought to improve the dissolution characteristics of a poorly water-soluble BCS class IV drug canaglifozin, by preparing nanosuspension using media milling method. A Plackett–Burman screening design was employed to screen the significant formulation and process variables. A total of 12 experiment were generated by design expert trial version 12 for screening 5 independent variables namely the amount of stabilizer in mg (X1), stirring time in hr (X2), amt of Zirconium oxide beads in gm (X3), amount of drug in mg (X4) and stirring speed in rpm (X5) while mean particle size in nm (Y1) and drug release in 10 min. were selected as the response variables. All the regression models yielded a good fit with high determination coefficient and F value. The Pareto chart depicted that all the independent variables except the amount of canaglifozin had a significant effect (p<0.001) on the response variables. The mathematical model for mean particle size generated from the regression analysis was given by mean particle size = +636.48889 -1.28267 amt of stabilizer(X1) -4.20417 stirring time (X2) -7.58333 amt of ZrO2 beads(X3) -0.105556 amt of drug(X4) -0.245167 stirring speed(X5) (R2=0.9484, F ratio=22.07, p<0.001). Prepared canaglifozin nanosuspension exemplified a significant improvement (p<0.05) in the release as compared to pure canaglifozin and marketed tablet with the optimum formulation releasing almost 80% drug within first 10min. Optimized nanosuspension showed spherical shape with surface oriented stabilizer molecules and a mean particle diameter of 120.5 nm. There was no change in crystalline nature after formulation and it was found to be chemically stable with high drug content.

scholarly journals Weight Feedback-Based Harmonic MDG-Ensemble Model for Prediction of Traffic Accident Severity

2021 ◽  
Vol 11 (11) ◽  
pp. 5072
Author(s):  
Byung-Kook Koo ◽  
Ji-Won Baek ◽  
Kyung-Yong Chung
Keyword(s):  
Traffic Accidents ◽  
Average Rate ◽  
Modern Society ◽  
Rate Of Change ◽  
Weighted Voting ◽  
Independent Variables ◽  
Dependent Variables ◽  
Accident Severity ◽  
Harmonic Average ◽  
Bagging Method

Traffic accidents are emerging as a serious social problem in modern society but if the severity of an accident is quickly grasped, countermeasures can be organized efficiently. To solve this problem, the method proposed in this paper derives the MDG (Mean Decrease Gini) coefficient between variables to assess the severity of traffic accidents. Single models are designed to use coefficient, independent variables to determine and predict accident severity. The generated single models are fused using a weighted-voting-based bagging method ensemble to consider various characteristics and avoid overfitting. The variables used for predicting accidents are classified as dependent or independent and the variables that affect the severity of traffic accidents are predicted using the characteristics of causal relationships. Independent variables are classified as categorical and numerical variables. For this reason, a problem arises when the variation among dependent variables is imbalanced. Therefore, a harmonic average is applied to the weights to maintain the variables’ balance and determine the average rate of change. Through this, it is possible to establish objective criteria for determining the severity of traffic accidents, thereby improving reliability.

scholarly journals A Student’s Guide to the Classification and Operationalization of Variables in the Conceptualization and Design of a Clinical Study: Part 1

2021 ◽  
Vol 43 (2) ◽  
pp. 177-179 ◽  
Author(s):  
Chittaranjan Andrade
Keyword(s):  
Clinical Study ◽  
Significant Relationship ◽  
Research Experience ◽  
Process Variables ◽  
Know How ◽  
Independent Variables ◽  
Cause And Effect ◽  
Confounding Variables ◽  
Dependent Variables ◽  
The Relationship

Students without prior research experience may not know how to conceptualize and design a study. This article explains how an understanding of the classification and operationalization of variables is the key to the process. Variables describe aspects of the sample that is under study; they are so called because they vary in value from subject to subject in the sample. Variables may be independent or dependent. Independent variables influence the value of other variables; dependent variables are influenced in value by other variables. A hypothesis states an expected relationship between variables. A significant relationship between an independent and dependent variable does not prove cause and effect; the relationship may partly or wholly be explained by one or more confounding variables. Variables need to be operationalized; that is, defined in a way that permits their accurate measurement. These and other concepts are explained with the help of clinically relevant examples.

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