Establishment of metrological parameters of the method for measuring the protein mass fraction in fish food products by the Kjeldahl method

In laboratory practice, there are many protein quantification methods, and all of them have their own advantages and disadvantages. The most common and widely used method for the protein analysis in food products, including fish, is the Kjeldahl method. However, the current standards for measurement methods for the determination of the protein content in fish food products do not provide for the use of devices that meet the modern level of technical development, and also do not contain metrological indicators that guarantee the reliability of the results obtained. The aim of the study was to substantiate the method for measuring the protein mass fraction in fish food products by the Kjeldahl method on an automatic analyzer and to establish metrological parameters. The assessment of the quality indicators of the Kjeldahl measuring method was carried out using a Kjeltec System 2300 Nitrogen Analyzer (Foss Analytical AB, Sweden) in the form of a characteristic of the measurement error and its components, which will provide results with the required accuracy.

α-Linolenic Acid and Risk of Heart Failure: A Meta-Analysis

Background: The α-linolenic acid is a plant origin n-3 fatty acid that may reduce the risk of cardiovascular disease. However, the effect of α-linolenic acid (ALA) on the risk of heart failure (HF) remains unclear. In this meta-analysis, we aimed to determine the role of ALA in the risk of incident HF.Methods: Electronic databases were searched for studies up to August 10, 2021. Studies were included for meta-analysis if the adjusted risk of HF in different dietary intake or circulating levels of ALA was reported. We used the random-effects model to calculate the estimated hazard ratios (HRs) and 95% CI for higher ALA.Results: A total of 6 studies (7 cohorts) comprising 135,270 participants were included for meta-analysis. After a median follow-up duration of 10 years, 5,905 cases of HF were recorded. No significant heterogeneity was observed among all the included studies. Random-effects model analyses showed that there was no significant association between ALA and the risk of incident HF, either assessed as quintiles (highest quintile vs. lowest quintile: HR = 0.95, 95% CI = 0.86–1.06) or per 1 SD increment (HR = 0.99, 95% CI = 0.95–1.01). Furthermore, we did not observe any association between ALA and the risk of HF in subgroup analyses performed according to age, sex, follow-up duration, and measuring method of ALA.Conclusions: We found no association between ALA and the risk of incident HF, suggesting that ALA might not be effective in the prevention of HF.

Deep learning-based automated characterization of crosscut tests for coatings via image segmentation

A manual scratch test to measure the scratch resistance of coatings applied to a certain substrate is usually used to test the adhesion of a coating. Despite its significant amount of subjectivity, the crosscut test is widely considered to be the most practical measuring method for adhesion strength with a good reliability. Intelligent software tools help to improve and optimize systems combining chemistry, engineering based on high-throughput formulation screening (HTFS) technologies and machine learning algorithms to open up novel solutions in material sciences. Nevertheless, automated testing often misses the link to quality control by the human eye that is sensitive in spotting and evaluating defects as it is the case in the crosscut test. In this paper, we present a method for the automated and objective characterization of coatings to drive and support Chemistry 4.0 solutions via semantic image segmentation using deep convolutional networks. The algorithm evaluated the adhesion strength based on the images of the crosscuts recognizing the delaminated area and the results were compared with the traditional classification rated by the human expert.

Validation of a Novel Boxing Monitoring System to Detect and Analyse the Centre of Pressure Movement on the Boxer’s Fist

The examination of force distribution and centre of pressure (CoP) displacement is a common method to analyse motion, load, and load distribution in biomechanical research. In contrast to gait analysis, the force progression in boxing punches is a new field of investigation. The centre of pressure displacement and distribution of forces on the surface of the fist during a boxing punch is of great interest and crucial to understanding the effect of the punch on the biological structures of the hand as well as the technical biomechanical aspects of the punching action. This paper presents a new method to display the CoP progression on the boxer’s fist Therefore, this study presents the validation of the developed novel boxing monitoring system in terms of CoP displacement. In addition, the CoP progression of different punching techniques in boxing is analysed on the athlete’s fist. The accuracy of the examination method of the CoP course was validated against the gold standard of a Kistler force plate. High correlations were detected between the developed sensor system and the force plate CoP with a Pearson correlation coefficient ranging from 0.93 to 0.97. The information obtained throughout the experimental study is of great importance in order to gain further knowledge into the technical execution of boxing punches as well as to provide a novel measuring method for determining CoP on the surface of the fist, to improve the understanding of the etiology of boxing-related hand injuries.

Application of an automated complex resistance and phase difference measuring method for rheographic studies of human cardiovascular system

The structure of an automated system for measuring the complex resistance of the human body and the phase difference is proposed. It is used in the rheographic method for diagnosing human cardiovascular system diseases using a multilevel microcontroller structure. The metrological analysis of the automated system made it possible to achieve an increase in the measurement accuracy both by reducing the methodological and instrumental components of measurement errors. The relative basic measurement error does not exceed ± 0.5%.

Real-time profilometry by bicolor grating video projection

A novel real-time 2+1 three-dimensional(3D) measuring method based on bicolor grating video projection is proposed. Firstly, only two frames of bicolor gratings, in which the red channels are two sinusoidal fringes with a shifting phase of π/2 and the blue channels are the same background light equivalent to the DC component of the two sinusoidal fringes are encoded and arranged alternatively to synthesize into a repetitive bicolor grating video, While this video is projected onto the measured object, the real-time bicolor deformed pattern video can be recorded by using a color CMOS camera, and the bicolor deformed pattern sequence at different moments can be extracted by computer processing, so that the 2+1 algorithm can be used to accomplish real-time 3D measurement of moving object. Before measuring, we used the same method to design two sinusoidal fringes with a difference of π in their red channels, respectively, to calibrate the sensitivity ratio between the red and blue channels of the CMOS camera, which can effectively eliminate the chromaticity imbalance between R and B channels and reduce the color crosstalk. Experimental results and analysis confirm the feasibility and effectiveness of the proposed method. Because the proposed method needs a repetitive bicolor grating video synthesized with only two-frame bicolor gratings to be projected, the 3D measurement acquisition speed and real-time accuracy will be improved compared with the traditional 2+1 3D measuring method.

An Inverse Method for Measuring Elastoplastic Properties of Metallic Materials Using Bayesian Model and Residual Imprint from Spherical Indentation

In this paper, an inverse method is proposed for measuring the elastoplastic properties of metallic materials using a spherical indentation experiment. In the new method, the elastoplastic parameters are correlated with sub-space coordinates of indentation imprints using proper orthogonal decomposition (POD), and inverse identification of material properties is solved using a statistical Bayesian framework. The advantage of the method is that model parameters in the numerical optimization process are treated as the stochastic variables, and potential uncertainties can be considered. The posterior results obtained from the measuring method can provide valuable probabilistic information of the estimated elastoplastic properties. The proposed method is verified by the application on 2099-T83 Al-Li alloys. Results indicate that posterior distribution of material parameters exhibits more than one peak region when indentation load is not large enough. In addition, using the weighting imprints under different loads can facilitate the uniqueness in identification of elastoplastic parameters. The influence of the weighting coefficient on posterior identification results is analyzed. The elastoplastic properties identified by indentation and tensile experiment show good agreement. Results indicate that the established measuring method is effective and reliable.