Analytical Authentication of Butter Using Fourier Transform Infrared Spectroscopy Coupled with Chemometrics

Fourier Transform Infrared (FT-IR) spectroscopy coupled with chemometrics was used to distinguish between butter samples and non-butter samples. Further, quantification of the content of margarine in adulterated butter samples was investigated. Fingerprinting region (1400-800 cm–1) was used to develop unsupervised pattern recognition (Principal Component Analysis, PCA), supervised modeling (Soft Independent Modelling by Class Analogy, SIMCA), classification (Partial Least Squares Discriminant Analysis, PLS-DA) and regression (Partial Least Squares Regression, PLS-R) models. PCA of the fingerprinting region shows a clustering of the two sample types. All samples were classified in their rightful class by SIMCA approach; however, nine adulterated samples (between 1% and 30% w/w of margarine) were classified as belonging both at the butter class and at the non-butter one. In the two-class PLS-DA model’s (R2 = 0.73, RMSEP, Root Mean Square Error of Prediction = 0.26% w/w) sensitivity was 71.4% and Positive Predictive Value (PPV) 100%. Its threshold was calculated at 7% w/w of margarine in adulterated butter samples. Finally, PLS-R model (R2 = 0.84, RMSEP = 16.54%) was developed. PLS-DA was a suitable classification tool and PLS-R a proper quantification approach. Results demonstrate that FT-IR spectroscopy combined with PLS-R can be used as a rapid, simple and safe method to identify pure butter samples from adulterated ones and to determine the grade of adulteration of margarine in butter samples.

Associations between Surrogate Insulin Resistance Indices and the Risk of Metabolic Syndrome in Children

A well-defined insulin resistance (IR) is one of the requirements for the good understanding and evaluation of metabolic syndrome (MetS). However, underlying causes for the development of IR are not clear. Endothelial dysfunction also participates in the pathogenesis of this disease. IR indices are being determined in various obesity groups and also in diagnosing MetS. Components of MetS have been well established and used in adult studies. However, there are some ambiguities particularly in the field of pediatrics. The aims of this study were to compare the performance of fasting blood glucose (FBG), one of MetS components, with some other IR indices and check whether FBG may be replaced by some other parameter or ratio for a better evaluation of pediatric MetS. Five-hundred and forty-nine children were involved in the study. Five groups were constituted. Groups 109, 40, 100, 166, 110, 24 children were included in normal-body mass index (N-BMI), overweight (OW), obese (OB), morbid obese (MO), MetS with two components (MetS2) and MetS with three components (MetS3) groups, respectively. Age and sex-adjusted BMI percentiles tabulated by World Health Organization were used for the classification of obesity groups. MetS components were determined. Aside from one of the MetS components-FBG, eight measures of IR [homeostatic model assessment of IR (HOMA-IR), homeostatic model assessment of beta cell function (HOMA-%β), alanine transaminase-to-aspartate transaminase ratio (ALT/AST), alanine transaminase (ALT), insulin (INS), insulin-to-FBG ratio (INS/FBG), the product of fasting triglyceride and glucose (TyG) index, McAuley index] were evaluated. Statistical analyses were performed. A p value less than 0.05 was accepted as the statistically significance degree. Mean values for BMI of the groups were 15.7 kg/m2, 21.0 kg/m2, 24.7 kg/m2, 27.1 kg/m2, 28.7 kg/m2, 30.4 kg/m2 for N-BMI, OW, OB, MO, MetS2, MetS3, respectively. Differences between the groups were significant (p < 0.001). The only exception was MetS2-MetS3 couple, in spite of an increase detected in MetS3 group. Waist-to-hip circumference ratios significantly differed only for N-BMI vs, OB, MO, MetS2; OW vs MO; OB vs MO, MetS2 couples. ALT and ALT/AST did not differ significantly among MO-MetS2-MetS3. HOMA-%β differed only between MO and MetS2. INS/FBG, McAuley index and TyG were not significant between MetS2 and MetS3. HOMA-IR and FBG were not significant between MO and MetS2. INS was the only parameter, which showed statistically significant differences between MO-MetS2, MO-MetS3, and MetS2-MetS3. In conclusion, these findings have suggested that FBG presently considered as one of the five MetS components, may be replaced by INS during the evaluation of pediatric morbid obesity and MetS.

Elimination of Low Order Harmonics in Multilevel Inverter Using Nature-Inspired Metaheuristic Algorithm

Nature-inspired metaheuristic algorithms, particularly those founded on swarm intelligence, have attracted much attention over the past decade. Firefly algorithm has appeared in approximately seven years ago, its literature has enlarged considerably with different applications. It is inspired by the behavior of fireflies. The aim of this paper is the application of firefly algorithm for solving a nonlinear algebraic system. This resolution is needed to study the Selective Harmonic Eliminated Pulse Width Modulation strategy (SHEPWM) to eliminate the low order harmonics; results have been applied on multilevel inverters. The final results from simulations indicate the elimination of the low order harmonics as desired. Finally, experimental results are presented to confirm the simulation results and validate the efficaciousness of the proposed approach.

Probabilistic Life Cycle Assessment of the Nano Membrane Toilet

Developing countries are nowadays confronted with great challenges related to domestic sanitation services in view of the imminent water scarcity. Contemporary sanitation technologies established in these countries are likely to pose health risks unless waste management standards are followed properly. This paper provides a solution to sustainable sanitation with the development of an innovative toilet system, called Nano Membrane Toilet (NMT), which has been developed by Cranfield University and sponsored by the Bill & Melinda Gates Foundation. The particular technology converts human faeces into energy through gasification and provides treated wastewater from urine through membrane filtration. In order to evaluate the environmental profile of the NMT system, a deterministic life cycle assessment (LCA) has been conducted in SimaPro software employing the Ecoinvent v3.3 database. The particular study has determined the most contributory factors to the environmental footprint of the NMT system. However, as sensitivity analysis has identified certain critical operating parameters for the robustness of the LCA results, adopting a stochastic approach to the Life Cycle Inventory (LCI) will comprehensively capture the input data uncertainty and enhance the credibility of the LCA outcome. For that purpose, Monte Carlo simulations, in combination with an artificial neural network (ANN) model, have been conducted for the input parameters of raw material, produced electricity, NOX emissions, amount of ash and transportation of fertilizer. The given analysis has provided the distribution and the confidence intervals of the selected impact categories and, in turn, more credible conclusions are drawn on the respective LCIA (Life Cycle Impact Assessment) profile of NMT system. Last but not least, the specific study will also yield essential insights into the methodological framework that can be adopted in the environmental impact assessment of other complex engineering systems subject to a high level of input data uncertainty.

Sustainable Intensification of Agriculture in Victoria’s Food Bowl: Optimizing Productivity with the use of Decision-Support Tools

A participatory and engaged approach is key in connecting agricultural managers to sustainable agricultural systems to support and optimize production in Victoria’s food bowl. A sustainable intensification (SI) approach is well documented globally, but participation rates amongst Victorian farmers is fragmentary, and key outcomes and implementation strategies are poorly understood. Improvement in decision-support management tools and a greater understanding of the productivity gains available upon implementation of SI is necessary. This paper reviews the current understanding and uptake of SI practices amongst farmers in one of Victoria’s premier food producing regions, the Goulburn Broken; and it spatially analyses the potential for this region to adapt to climate change and optimize food production. A Geographical Information Systems (GIS) approach is taken to develop an interactive decision-support tool that can be accessible to on-ground agricultural managers. The tool encompasses multiple criteria analysis (MCA) that identifies factors during the construction phase of the tool, using expert witnesses and regional knowledge, framed within an Analytical Hierarchy Process. Given the complexities of the interrelations between each of the key outcomes, this participatory approach, in which local realities and factors inform the key outcomes and help to strategies for a particular region, results in a robust strategy for sustainably intensifying production in key food producing regions. The creation of an interactive, locally embedded, decision-support management and education tool can help to close the gap between farmer knowledge and production, increase on-farm adoption of sustainable farming strategies and techniques, and optimize farm productivity.

Qualitative Data Analysis for Health Care Services

This study was designed enable application of multivariate technique in the interpretation of categorical data for measuring health care services satisfaction in Turkey. The data was collected from a total of 17726 respondents. The establishment of the sample group and collection of the data were carried out by a joint team from The Ministry of Health and Turkish Statistical Institute (Turk Stat) of Turkey. The multiple correspondence analysis (MCA) was used on the data of 2882 respondents who answered the questionnaire in full. The multiple correspondence analysis indicated that, in the evaluation of health services females, public employees, younger and more highly educated individuals were more concerned and complainant than males, private sector employees, older and less educated individuals. Overall 53 % of the respondents were pleased with the improvements in health care services in the past three years. This study demonstrates the public consciousness in health services and health care satisfaction in Turkey. It was found that most the respondents were pleased with the improvements in health care services over the past three years. Awareness of health service quality increases with education levels. Older individuals and males would appear to have lower expectancies in health services.

Development of Energy Benchmarks Using Mandatory Energy and Emissions Reporting Data: Ontario Post-Secondary Residences

Governments are playing an increasingly active role in reducing carbon emissions, and a key strategy has been the introduction of mandatory energy disclosure policies. These policies have resulted in a significant amount of publicly available data, providing researchers with a unique opportunity to develop location-specific energy and carbon emission benchmarks from this data set, which can then be used to develop building archetypes and used to inform urban energy models. This study presents the development of such a benchmark using the public reporting data. The data from Ontario’s Ministry of Energy for Post-Secondary Educational Institutions are being used to develop a series of building archetype dynamic building loads and energy benchmarks to fill a gap in the currently available building database. This paper presents the development of a benchmark for college and university residences within ASHRAE climate zone 6 areas in Ontario using the mandatory disclosure energy and greenhouse gas emissions data. The methodology presented includes data cleaning, statistical analysis, and benchmark development, and lessons learned from this investigation are presented and discussed to inform the development of future energy benchmarks from this larger data set. The key findings from this initial benchmarking study are: (1) the importance of careful data screening and outlier identification to develop a valid dataset; (2) the key features used to develop a model of the data are building age, size, and occupancy schedules and these can be used to estimate energy consumption; and (3) policy changes affecting the primary energy generation significantly affected greenhouse gas emissions, and consideration of these factors was critical to evaluate the validity of the reported data.

A Cognitive Measurement of Complexity and Comprehension for Object-Oriented Code

Inherited complexity is one of the difficult tasks in software engineering field. Further, it is said that there is no physical laws or standard guidelines suit for designing different types of software. Hence, to make the software engineering as a matured engineering discipline like others, it is necessary that it has its own theoretical frameworks and laws. Software designing and development is a human effort which takes a lot of time and considers various parameters for successful completion of the software. The cognitive informatics plays an important role for understanding the essential characteristics of the software. The aim of this work is to consider the fundamental characteristics of the source code of Object-Oriented software i.e. complexity and understandability. The complexity of the programs is analyzed with the help of extracted important attributes of the source code, which is further utilized to evaluate the understandability factor. The aforementioned characteristics are analyzed on the basis of 16 C++ programs by distributing them to forty MCA students. They all tried to understand the source code of the given program and mean time is taken as the actual time needed to understand the program. For validation of this work, Briand’s framework is used and the presented metric is also evaluated comparatively with existing metric which proves its robustness.

Using Simulation Modeling Approach to Predict USMLE Steps 1 and 2 Performances

The prediction models for the United States Medical Licensure Examination (USMLE) Steps 1 and 2 performances were constructed by the Monte Carlo simulation modeling approach via linear regression. The purpose of this study was to build robust simulation models to accurately identify the most important predictors and yield the valid range estimations of the Steps 1 and 2 scores. The application of simulation modeling approach was deemed an effective way in predicting student performances on licensure examinations. Also, sensitivity analysis (a/k/a what-if analysis) in the simulation models was used to predict the magnitudes of Steps 1 and 2 affected by changes in the National Board of Medical Examiners (NBME) Basic Science Subject Board scores. In addition, the study results indicated that the Medical College Admission Test (MCAT) Verbal Reasoning score and Step 1 score were significant predictors of the Step 2 performance. Hence, institutions could screen qualified student applicants for interviews and document the effectiveness of basic science education program based on the simulation results.

Refractive Index, Excess Molar Volume and Viscometric Study of Binary Liquid Mixture of Morpholine with Cumene at 298.15 K, 303.15 K, and 308.15 K

Experimental data of refractive index, excess molar volume and viscosity of binary mixture of morpholine with cumene over the whole composition range at 298.15 K, 303.15 K, 308.15 K and normal atmospheric pressure have been measured. The experimental data were used to compute the density, deviation in molar refraction, deviation in viscosity and excess Gibbs free energy of activation as a function of composition. The experimental viscosity data have been correlated with empirical equations like Grunberg- Nissan, Herric correlation and three body McAllister’s equation. The excess thermodynamic properties were fitted to Redlich-Kister polynomial equation. The variation of these properties with composition and temperature of the binary mixtures are discussed in terms of intermolecular interactions.

Evaluation of Research in the Field of Energy Efficiency and MCA Methods Using Publications Databases

Energy is a fundamental component in sustainability, the access and use of this resource is related with economic growth, social improvements, and environmental impacts. In this sense, energy efficiency has been studied as a factor that enhances the positive impacts of energy in communities; however, the implementation of efficiency requires strong policy and strategies that usually rely on individual measures focused in independent dimensions. In this paper, the problem of energy efficiency as a multi-objective problem is studied, using scientometric analysis to discover trends and patterns that allow to identify the main variables and study approximations related with a further development of models to integrate energy efficiency and MCA into policy making for small communities.

Models of State Organization and Influence over Collective Identity and Nationalism in Spain

The main objective of this paper is to establish the relationship between models of state organization and the various types of collective identity expressed by the Spanish. The question of nationalism and identity ascription in Spain has always been a topic of special importance due to the presence in that country of territories where the population emits very different opinions of nationalist sentiment than the rest of Spain. The current situation of sovereignty challenge of Catalonia to the central government exemplifies the importance of the subject matter. In order to analyze this process of interrelation, we use a secondary data mining by applying the multiple correspondence analysis technique (MCA). As a main result a typology of four types of expression of collective identity based on models of State organization are shown, which are connected with the party position on this issue.

Application of Interferometric Techniques for Quality Control of Oils Used in the Food Industry

The purpose of this project is to propose a quick and environmentally friendly alternative to measure the quality of oils used in food industry. There is evidence that repeated and indiscriminate use of oils in food processing cause physicochemical changes with formation of potentially toxic compounds that can affect the health of consumers and cause organoleptic changes. In order to assess the quality of oils, non-destructive optical techniques such as Interferometry offer a rapid alternative to the use of reagents, using only the interaction of light on the oil. Through this project, we used interferograms of samples of oil placed under different heating conditions to establish the changes in their quality. These interferograms were obtained by means of a Mach-Zehnder Interferometer using a beam of light from a HeNe laser of 10mW at 632.8nm. Each interferogram was captured, analyzed and measured full width at half-maximum (FWHM) using the software from Amcap and ImageJ. The total of FWHMs was organized in three groups. It was observed that the average obtained from each of the FWHMs of group A shows a behavior that is almost linear, therefore it is probable that the exposure time is not relevant when the oil is kept under constant temperature. Group B exhibits a slight exponential model when temperature raises between 373 K and 393 K. Results of the t-Student show a probability of 95% (0.05) of the existence of variation in the molecular composition of both samples. Furthermore, we found a correlation between the Iodine Indexes (Physicochemical Analysis) and the Interferograms (Optical Analysis) of group C. Based on these results, this project highlights the importance of the quality of the oils used in food industry and shows how Interferometry can be a useful tool for this purpose.

Comparative Study between Classical P-Q Method and Modern Fuzzy Controller Method to Improve the Power Quality of an Electrical Network

This article presents two methods for the compensation of harmonics generated by a nonlinear load. The first is the classic method P-Q. The second is the controller by modern method of artificial intelligence specifically fuzzy logic. Both methods are applied to a shunt Active Power Filter (sAPF) based on a three-phase voltage converter at five levels NPC topology. In calculating the harmonic currents of reference, we use the algorithm P-Q and pulse generation, we use the intersective PWM. For flexibility and dynamics, we use fuzzy logic. The results give us clear that the rate of Harmonic Distortion issued by fuzzy logic is better than P-Q.

Application of Statistical Approach for Optimizing CMCase Production by Bacillus tequilensis S28 Strain via Submerged Fermentation Using Wheat Bran as Carbon Source

Biofuels production has come forth as a future technology to combat the problem of depleting fossil fuels. Bio-based ethanol production from enzymatic lignocellulosic biomass degradation serves an efficient method and catching the eye of scientific community. High cost of the enzyme is the major obstacle in preventing the commercialization of this process. Thus main objective of the present study was to optimize composition of medium components for enhancing cellulase production by newly isolated strain of Bacillus tequilensis. Nineteen factors were taken into account using statistical Plackett-Burman Design. The significant variables influencing the cellulose production were further employed in statistical Response Surface Methodology using Central Composite Design for maximizing cellulase production. The optimum medium composition for cellulase production was: peptone (4.94 g/L), ammonium chloride (4.99 g/L), yeast extract (2.00 g/L), Tween-20 (0.53 g/L), calcium chloride (0.20 g/L) and cobalt chloride (0.60 g/L) with pH 7, agitation speed 150 rpm and 72 h incubation at 37oC. Analysis of variance (ANOVA) revealed high coefficient of determination (R2) of 0.99. Maximum cellulase productivity of 11.5 IU/ml was observed against the model predicted value of 13 IU/ml. This was found to be optimally active at 60oC and pH 5.5.

Angiographic Evaluation of ETT (Treadmill) Positive Patients in a Tertiary Care Hospital of Bangladesh

To evaluate the factors which predetermine the coronary artery disease in patients having positive Exercise Tolerance Test (ETT) that is treadmill results and coronary artery findings. This descriptive study was conducted at Department of Cardiology, Ibrahim Cardiac Hospital & Research Institute, Dhaka, Bangladesh from 1st January, 2014 to 31st August, 2014. All patients who had done ETT (treadmill) for chest pain diagnosis were studied. One hundred and four patients underwent coronary angiogram after positive treadmill result. Patients were divided into two groups depending upon the angiographic findings, i.e. true positive and false positive. Positive treadmill test patients who have coronary artery involvement these are called true positive and who have no involvement they are called false positive group. Both groups were compared with each other. Out of 104 patients, 81 (77.9%) patients had true positive ETT and 23 (22.1%) patients had false positive ETT. The mean age of patients in positive ETT was 53.46± 8.06 years and male mean age was 53.63±8.36 years and female was 52.87±7.0 years. Sixty nine (85.19%) male patients and twelve (14.81%) female patients had true positive ETT, whereas 15 (65.21%) males and 8 (34.79%) females had false positive ETT, this was statistically significant (p

Spatial Time Series Models for Rice and Cassava Yields Based On Bayesian Linear Mixed Models

This paper proposes a linear mixed model (LMM) with spatial effects to forecast rice and cassava yields in Thailand at the same time. A multivariate conditional autoregressive (MCAR) model is assumed to present the spatial effects. A Bayesian method is used for parameter estimation via Gibbs sampling Markov Chain Monte Carlo (MCMC). The model is applied to the rice and cassava yields monthly data which have been extracted from the Office of Agricultural Economics, Ministry of Agriculture and Cooperatives of Thailand. The results show that the proposed model has better performance in most provinces in both fitting part and validation part compared to the simple exponential smoothing and conditional auto regressive models (CAR) from our previous study.

Synthesis of Magnesium Borates from the Slurries of Magnesium Wastes by Microwave Energy

In this research, it is aimed not only microwave synthesis of magnesium borates but also evaluation of magnesium wastes. Synthesis process can be described with the reaction of Mg wastes and boric acid using microwave energy. X-Ray Diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FT-IR) were applied to synthesized minerals. According to XRD results, magnesium borate hydrate mixtures were obtained as mcallisterite (pdf# = 01-070-1902, Mg2(B6O7(OH)6)2.9(H2O)) at higher crystallinity properties was achieved at the mole ratio raw material 1:1. Also, other kinds of magnesium borate hydrates were obtained at lower crystallinity such as admontite (pdf # = 01-076-0540, MgO(B2O3)3.7(H2O)), inderite (pdf # = 01-072-2308, 2MgO.3B2O3.15(H2O)) and magnesium borate hydrates (pdf # = 01-076-0539, MgO(B2O3)3.6(H2O)). FT-IR spectrums indicated that minor changes were seen at the band values of characteristic stretching in each experiment. At the end of experiments it is seen that using microwave energy may contribute positive effects to design of synthesis process such as reducing reaction time and products at higher crystallinity.

Electronic Nose Based On Metal Oxide Semiconductor Sensors as an Alternative Technique for the Spoilage Classification of Oat Milk

The aim of the present study was to develop a rapid method for electronic nose for online quality control of oat milk. Analysis by electronic nose and bacteriological measurements were performed to analyze spoilage kinetics of oat milk samples stored at room temperature and refrigerated conditions for up to 15 days. Principal component analysis (PCA), Discriminant Factorial Analysis (DFA) and Soft Independent Modelling by Class Analogy (SIMCA) classification techniques were used to differentiate the samples of oat milk at different days. The total plate count (bacteriological method) was selected as the reference method to consistently train the electronic nose system. The e-nose was able to differentiate between the oat milk samples of varying microbial load. The results obtained by the bacteria total viable countsshowed that the shelf-life of oat milk stored at room temperature and refrigerated conditions were 20hrs and 13 days, respectively. The models built classified oat milk samples based on the total microbial population into “unspoiled” and “spoiled”.

Combined Hydrothermal Synthesis of Zinc and Magnesium Borates at 100oC Using ZnO, MgO and H3BO3

Magnesium borate(MB) istechnical ceramic for high heat-resisting, corrosion-resisting, super mechanical strength, superinsulation, light weight, high strength, and high coefficient of elasticity. Zinc borate (ZB) can be used as multi-functional synergistic additives with flame retardant additives in polymers. The most important properties are low solubility in water and high dehydration temperature. ZB dehydrates above 290°C and anhydrous ZB has thermal resistance about 400°C. In this study, the raw materials of ZnO, MgO and H3BO3 were used with mole ratio of 1:1:9. With the starting materials hydrothermal method was applied at a temperature of 100oC. The reaction time was determined as 30, 60, 90 and 120 minutes after some preliminary experiments. After the synthesis, the crystal structure and the morphology of the products were examined by X-Ray Diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FT-IR). As a result, the forms of Zinc Oxide Borate Hydrate [Zn3B6O12.3.5H2O], Admontite [MgO(B2O3)3.7(H2O)] and Mcallisterite [Mg2(B6O7(OH)6)2.9(H2O)] were synthesized.