Application of FTIR Spectroscopy for Quantitative Analysis of Blood Serum: A Preliminary Study

The aim of this study was to analyze the possibility of simultaneous determination of the concentration of components from the characteristics of FTIR spectra using the example of a model blood serum. To prepare model solutions, a set of freeze-dried control sera based on bovine blood serum was used, certified for approximately 38 parameters. Based on the values of the absorbance and areas of absorption bands in the FTIR spectra of model solutions, a regression equation was constructed by solving a nonlinear problem using the generalized reduced gradient method. By using the absorbance of the absorption bands at 1717 and 3903 cm−1 and the areas of the absorption bands at 616, 3750, and 3903 cm−1, it is possible to simultaneously determine the concentrations of 38 components with an error of less than 0.1%. The results obtained confirm the potential clinical use of FTIR spectroscopy as a reagent-free express method for the analysis of blood serum. However, its practical implementation requires additional research, in particular, analysis of real blood serum samples and validation of the method.

PERFORMANCE INDEX MODEL OF GROUNDWATER IRRIGATION SYSTEMS

This research will develop a groundwater irrigation system performance index model with the aim of identifying the groundwater irrigation system performance index; this information can be used by stakeholders to determine management steps. The research location is in Gunungkidul Regency and includes surrounding areas — acknowledging that the karst aquifer has complex characteristics and non-karst aquifer, namely high heterogeneity as a result of the formation of a groundwater flow system through fractures which eventually becomes completely underground runoff. Screening for the variables was carried out using the smart-PLS (Partial Least Square) tool, which was then analyzed using the GRG (Generalized Reduced Gradient) method which is useful for solving non-linear equations. In this research, it examines the physical aspects, social aspects and management aspects as variables. The groundwater irrigation system performance index model examines 3 (three) variables, namely physical aspects, social aspects, and management aspects, then 11 (eleven) dimensions and 42 (forty two) indicators. The analysis using PLS SEM using smart PLS tools determined that the 3 (three) variables, 11 (eleven) dimensions and 30 (thirty) indicators are interrelated and effective. Whereas by using GRG (Generalized Reduced Gradient) analysis with the solver tool in Microsoft Excel, the most influential weights were obtained from the physical aspects, namely physical infrastructure (0.5782), geological conditions (0.2311), water quality (0.1286) and recharge area conditions (0.0475); the social aspects that obtained the most influential weight are socio-cultural (0.7471) and economy (0.2529); the management aspects that obtained the most influential weights are budgeting (0.2534), plant productivity (0.2270), WUA organizational conditions (0.2090), JIAT management organizational conditions (0.1987) and spatial planning directives (0.0674). In general, the weight of the influence of groundwater irrigation performance for these three aspects is 0.6686 physical aspects, 0.0856 social aspects and 0.2458 management aspects which are formulated into a performance index model for groundwater irrigation systems "Kautsar", namely IL = 0.6686 physical IL + 0.0856 social IL + 0.2458 IL management. For development, further research is needed on the performance index model of the groundwater irrigation system using Geography Information System (GIS) and a software application on android, iOS, or windows operation systems. A groundwater irrigation system performance index that consists of these three aspects is unique and has never been assembled in previous studies; it conveniently allow the user to determine survey results immediately.

Penerapan Model Exponential Smoothing berbasis Metode Evolutionary pada Kasus COVID-19 dan DBD di Bojonegoro

Latar Belakang: COVID-19 menjadi perhatian utama di Bojonegoro karena kasus terinfeksi meningkat sampai akhir tahun 2020. Selain itu, wabah demam berdarah dengue (DBD) juga perlu diantisipasi di musim penghujan agar tidak meningkat bersamaan dengan wabah COVID-19.Tujuan: Mengembangkan model exponential smoothing berbasis metode evolutionary untuk meramalkan banyaknya kasus terinfeksi COVID-19 dan DBD di Bojonegoro.Metode: Penelitian diawali dengan pembuatan aplikasi peramalan model exponential smoothing dengan metode evolutionary dan pemrograman Visual Basic yang dikembangkan di Excel dan Solver. Koefisien-koefisien model dioptimasi secara iteratif dengan metode evolutionary dan metode generalized reduced gradient. Model tersebut dievaluasi kinerjanya dengan nilai mean absolute percentage error (MAPE), mean absolute deviation (MAD), dan mean squared error (MSE). Sumber data penelitian menggunakan data sekunder dari Dinas Kesehatan Bojonegoro yang berisi data harian kasus terinfeksi COVID-19 dan data bulanan kasus DBD.Hasil: Model double exponential smoothing berbasis metode generalized reduced gradientmenghasilkan kesalahan model peramalan yang lebih kecil untuk nilai MAPE, MAD, dan MSE. Hasil peramalan menunjukkan bahwapeningkatan terjadi pada periode ke depan untuk kasus terinfeksi COVID-19 yang lebih besar dibandingkan DBD.Kesimpulan: Aplikasi peramalan model exponential smoothing dapat menjadi altenatif dalam meramalkan banyaknya kasus terinfeksi COVID-19 dan DBD di Bojonegoro.

New Refrigerant Molecules from Structure Optimization

In the present work, various objective functions were formulated and optimized using the mixed integer nonlinear programming and the generalized reduced gradient nonlinear method from the solver tool of Microsoft® Excel 2016, respectively. The CH3FO2, C2H4F2O, CH2F2O2, CH2F2O, C3H4F2, and the C2H2F2O molecules were found to meet structural feasibility constraints and physical properties from refrigerant molecules and have not previously been reported in the literature. These new refrigerants present global warming potential values similar to that from the R-134a and Freon 12 refrigerants and null ozone depletion potential. Moreover, these molecules are normally flammable, as similar as to R-134a refrigerant. The CH3FO2, C2H4F2O, CH2F2O2, C2H2F2O, and CH2F2O show toxicity values similar to R-134a and Freon 12 refrigerants.

Multi-Objective Optimization and Finite Element Method Combined with Optimization via Monte Carlo Simulation in a Stamping Process under Uncertainty

The Response Surface Methodology (RSM), which uses a quadratic empirical function as an approximation to the original function and allows the identification of relationships between independent variables xi and dependent variables ys associated with multiple responses, stands out. The main contribution of the present study is to propose an innovative procedure for the optimization of experimental problems with multiple responses, which considers the insertion of uncertainties in the coefficients of the obtained empirical functions in order to adequately represent real situations. This new procedure, which combines RSM with the Finite Elements (FE) method and the Monte Carlo Simulation Optimization (OvMCS), was applied to a real stamping process of a Brazilian multinational automotive company. For RSM with multiple responses, were compared the results obtained using the agglutination methods: Compromise Programming, Desirability Function (DF), and the Modified Desirability Function (MDF). The functions were optimized by applying the Generalized Reduced Gradient (GRG) algorithm, which is a classic procedure widely adopted in this type of experimental problem, without the uncertainty in the coefficients of independent factors. The advantages offered by this innovative procedure are presented and discussed, as well as the statistical validation of its results. It can be highlighted, for example, that the proposed procedure reduces, and sometimes eliminates, the need for additional confirmation experiments, as well as a better adjustment of factor values and response variable values when comparing to the results of RSM with classic multiple responses. The new proposed procedure added relevant and useful information to the managers responsible for the studied stamping process. Moreover, the proposed procedure facilitates the improvement of the process, with lower associated costs.

A model for fi nding the optimal routes for a combined route container train

The article is devoted to the development of the model for finding an optimal route for a combined route container train (CRCT), i.e. a train with a designated route and schedule, en route from the initial to the final station without reforming of a rolling stock, but carrying out cargo handling operations for loading/unloading containers at intermediate stops of the route. It is proposed to call the optimal route of a CRCT, which provides the minimum delivery time while ensuring the targeted train loading on each section and with a set value of demand for container transportation at each point of the route. A software implementation of the model in the MS Excel environment is proposed using the built-in generalized reduced gradient algorithm.