scholarly journals Mathematical models for correlating electrical parameters and milk adulterants

2020 ◽  
Vol 2 (1) ◽  
pp. 27-33
Author(s):  
Wesley Nascimento
Keyword(s):  
Sodium Chloride ◽  
Sodium Bicarbonate ◽  
Mathematical Models ◽  
Phase Angle ◽  
Linear Models ◽  
Raw Milk ◽  
Milk Analysis ◽  
Electrical Parameters ◽  
Electrical Measurements ◽  
Non Destructive

This work presents mathematical models obtained from electrical measurements to control of milk quality and detection of adulterations, especially by ethanol, sodium chloride and sodium bicarbonate. These substances may cause changes in the electrical properties of raw milk. Electrical measurements are non-destructive and fast techniques. The proposed models correlate the addition of the mentioned substances with measurements of conductance and phase angle at a fixed frequency of 100 Hz. Linear models were proposed from the data and the independence, normality, lack of adjustment and homoscedasticity were verified. The detection limits obtained based on conductance were 0.01 %, 0.03 g/L and 2.1 g/L for samples adulterated with ethanol, sodium chloride and sodium bicarbonate, respectively. The limits for measurements based on the phase angle were 0.4%, 1.3 g/L and 16.4 g/L, respectively. The results demonstrated that the proposed models may be a powerful tool to improve milk analysis methodologies.

scholarly journals Non-destructive evaluation of the leaf area of garlic crop using mathematical models

2020 ◽  
Vol 36 (5) ◽  
Author(s):  
Felipe Augusto Reis Gonçalves ◽  
Marcelo de Paula Senoski ◽  
Thiago Picinatti Raposo ◽  
Leonardo Angelo de Aquino ◽  
Maria Elisa de Sena Fernandes
Keyword(s):  
Linear Regression ◽  
Mathematical Models ◽  
Leaf Area ◽  
Dry Matter ◽  
Linear Models ◽  
Coefficient Of Determination ◽  
Length Width ◽  
Number Of Leaves ◽  
Non Destructive

Growth measurements such as leaf area (LA) and dry matter (DM) are important in experiments about plants population, fertilization, irrigation and others parameters of cultivation, in garlic crop. The LA and DM are commonly defined as destructive, lengthy and cause loss of plants in the experimental units. The objective of this study was to fit mathematical models using linear models that estimate the leaf area and dry matter of garlic plants - variety Ito. For that, garlic plants were collected at 30, 45, 60, 75, 90, 115 and 120 days after planting. The measurements of width (W), length (L) of leaves, LA, DM, pseudostem diameter (PD), number of leaves per plant (NL) and height (H) were determined in each time. The models were fitted to estimate the LA or DM as function of the variables W, L, L*W, PD and LA. The statistical analysis of the linear regression, coefficient of determination of the linear regression (R2), root mean square error (RMSE), modified concordance index (d1) and the BIAS index were verified to determine the most representative models. It`s possible to estimate the LA and the leaf DM of garlic plants using the variables: length, width, pseudostem diameter and height of plants.

In FAB 300mm Wafer Level Atomic Force Probe Characterization

2012 ◽  
Author(s):  
Terence Kane
Keyword(s):  
Electrical Characterization ◽  
Dark Field ◽  
Wafer Level ◽  
Electrical Measurements ◽  
Manufacturing Line ◽  
Atomic Force ◽  
Monitoring Tools ◽  
Voltage Contrast ◽  
The Cost ◽  
Non Destructive

Abstract A 300mm wafer atomic force prober (AFP) has been installed into IBM’s manufacturing line to enable rapid, nondestructive electrical identification of defects. Prior to this tool many of these defects could not detected until weeks or months later. Moving failure analysis to the FAB provides a means of complementing existing FAB inspection and defect review tools as well as providing independent, non-destructive electrical measurements at an early point in the manufacturing cycle [1] Once the wafer sites are non destructively AFP characterized, the wafer is returned to its front opening unified pod (FOUP) carrier and may be reintroduced into the manufacturing line without disruption for further inspection or processing. Whole wafer atomic force probe electrical characterization has been applied to 32nm, 28nm, 20nm and 14nm node technologies. In this paper we explore the cost benefits of performing non-destructive AFP measurements on whole wafers. We have found the methodology of employing a whole wafer AFP tool complements existing in-line manufacturing monitoring tools such as brightfield/dark field optical inspection, SEM in-line inspection and in-line E-beam voltage contrast inspection (EBI).

scholarly journals Effect of sodium bicarbonate supplementation on the renin-angiotensin system in patients with chronic kidney disease and acidosis: a randomized clinical trial

2020 ◽  
Author(s):  
Dominique M. Bovée ◽  
Lodi C. W. Roksnoer ◽  
Cornelis van Kooten ◽  
Joris I. Rotmans ◽  
Liffert Vogt ◽  
...  
Keyword(s):  
Chronic Kidney Disease ◽  
Sodium Chloride ◽  
Kidney Disease ◽  
Sodium Bicarbonate ◽  
Renin Angiotensin System ◽  
Ammonium Excretion ◽  
Angiotensin System ◽  
Renin Angiotensin ◽  
Endothelin 1 ◽  
Plasma Bicarbonate

Abstract Background Acidosis-induced kidney injury is mediated by the intrarenal renin-angiotensin system, for which urinary renin is a potential marker. Therefore, we hypothesized that sodium bicarbonate supplementation reduces urinary renin excretion in patients with chronic kidney disease (CKD) and metabolic acidosis. Methods Patients with CKD stage G4 and plasma bicarbonate 15–24 mmol/l were randomized to receive sodium bicarbonate (3 × 1000 mg/day, ~ 0.5 mEq/kg), sodium chloride (2 × 1,00 mg/day), or no treatment for 4 weeks (n = 15/arm). The effects on urinary renin excretion (primary outcome), other plasma and urine parameters of the renin-angiotensin system, endothelin-1, and proteinuria were analyzed. Results Forty-five patients were included (62 ± 15 years, eGFR 21 ± 5 ml/min/1.73m2, plasma bicarbonate 21.7 ± 3.3 mmol/l). Sodium bicarbonate supplementation increased plasma bicarbonate (20.8 to 23.8 mmol/l) and reduced urinary ammonium excretion (15 to 8 mmol/day, both P < 0.05). Furthermore, a trend towards lower plasma aldosterone (291 to 204 ng/L, P = 0.07) and potassium (5.1 to 4.8 mmol/l, P = 0.06) was observed in patients receiving sodium bicarbonate. Sodium bicarbonate did not significantly change the urinary excretion of renin, angiotensinogen, aldosterone, endothelin-1, albumin, or α1-microglobulin. Sodium chloride supplementation reduced plasma renin (166 to 122 ng/L), and increased the urinary excretions of angiotensinogen, albumin, and α1-microglobulin (all P < 0.05). Conclusions Despite correction of acidosis and reduction in urinary ammonium excretion, sodium bicarbonate supplementation did not improve urinary markers of the renin-angiotensin system, endothelin-1, or proteinuria. Possible explanations include bicarbonate dose, short treatment time, or the inability of urinary renin to reflect intrarenal renin-angiotensin system activity. Graphic abstract

Effect of sodium bicarbonate and sodium chloride on aggregation and conformation of pork myofibrillar protein

2021 ◽  
Vol 350 ◽  
pp. 129233
Author(s):  
Yan-ping Li ◽  
Xue-hua Zhang ◽  
Fei Lu ◽  
Zhuang-Li Kang
Keyword(s):  
Sodium Chloride ◽  
Sodium Bicarbonate ◽  
Myofibrillar Protein

MATHEMATICAL MODELS OF GEOFILTRRATION AND GEOMIGRATION IN POROUS MEDIA WITH FRACTAL STRUCTURE

2020 ◽  
Vol 6 (3) ◽  
pp. 21-27
Author(s):  
R.A. Yusupov ◽  
◽  
Sh.S. Axrolov ◽  
N.M. Mirzanova ◽  
A.N. Nasiriddinov ◽  
...  
Keyword(s):  
Porous Media ◽  
Mathematical Models ◽  
Linear Models ◽  
Fractal Structure ◽  
Fractal Structures

In this study 2-D linear models are coming from generalised, Boussinesq eqution describing geofiltration in soils with fractal structures are presented. In this study are presented too mathematical models geomigration of contaminations with groundwater in classical way and in soils with fractal structures.

Comparison of various multivariate models to estimate structural properties by means of non-destructive techniques (NDTs) in Pinus sylvestris L. timber

Holzforschung ◽  
2019 ◽  
Vol 73 (4) ◽  
pp. 331-338
Author(s):  
Antonio Villasante ◽  
Guillermo Íñiguez-González ◽  
Lluis Puigdomenech
Keyword(s):  
Pinus Sylvestris ◽  
Linear Models ◽  
Longitudinal Vibration ◽  
Modulus Of Rupture ◽  
Coefficient Of Determination ◽  
Pullout Resistance ◽  
Density Prediction ◽  
Learning Software ◽  
Artificial Neural Network Ann ◽  
Non Destructive

AbstractThe predictability of modulus of elasticity (MOE), modulus of rupture (MOR) and density of 120 samples of Scots pine (Pinus sylvestrisL.) were investigated using various non-destructive variables (such as time of flight of stress wave, natural frequency of longitudinal vibration, penetration depth, pullout resistance, visual grading and concentrated knot diameter ratio), and based on multivariate algorithms, applying WEKA as machine learning software. The algorithms used were: multivariate linear regression (MLR), Gaussian, Lazy, artificial neural network (ANN), Rules and decision Tree. The models were quantified based on the root-mean-square error (RMSE) and the coefficient of determination (R2). To avoid model overfitting, the modeling was built and the results validated via the so-called 10-fold cross-validation. MLR with the “greedy method” for variable selection based on the Akaike information metric (MLRak) significantly reduced the RMSE of MOR and MOE compared to univariate linear regressions (ULR). However, this reduction was not significant for density prediction. The predictability of MLRak was not improved by any other of the tested algorithms. Specifically, non-linear models, such as multilayer perceptron, did not contribute any significant improvements over linear models. Finally, MLRak models were simplified by discarding the variables that produce the lowest RMSE increment. The resulted models could be even further simplified without significant RMSE increment.

Sign in / Sign up

Export Citation Format

Share Document