Constant Calibration Research Articles

Лиофилизированные микроорганизмы как основа биочувствительного элемента БПК-биосенсора

Previously created laboratory models and commercially available BOD biosensors are usually formed using the biomass of microorganisms obtained by centrifugation of the culture fluid. In this work we developed and tested BOD biosensors based on lyophilized bacteria Paracoccus yeei VKM V-3302 and yeast Debaryomyces hansenii VKM Y-2482. The use of a lyophilized form of microorganisms makes it possible to switch to a new analysis format – the use of easily replaceable biosensitive elements with a short service life. It will simplify the introduction of BOD biosensors in environmental laboratories, enterprises and organizations involved in the routine determination of BOD using a methodology based on a 5-day sample incubation. The long shelf life (up to 2 years), low cost and easy applying of a dry preparation to the electrode will greatly facilitate the transportation of biosensitive elements to the end user, allow analysis in the field and at any time and will not require constant calibration of a sensor. It has been shown that the lyophilization process does not lead to significant changes in the metabolic activity of microorganisms. The biosensors are characterized by high sensitivity (the lower limit of BOD5 determination is 0.5 mgO2/dm3), convergence of results (4.5%) and are not inferior to existing analogs in terms of basic characteristics. They make it possible to analyze water samples classified as “pure” (BOD5 range 0.05–0.5 mg/dm3) and obtain results with a high correlation (R=0.9951) to the standard method. Thus, the use of bacteria P. yeei and yeast D. hansenii in a lyophilized form as part of the sensitive elements of BOD biosensors makes it possible to use them in prototypes of biosensors for mass production.

Challenges in Ground-Penetrating Radar Application in Structural Elements: Determination of the Dielectric Constant of Glued Laminated Timber Case Study

In this paper, some of the basic information on Ground-Penetrating Radar (GPR), its applications (especially in the field of civil engineering) and limitations are presented. As a non-destructive technique, GPR is a powerful tool for the investigation of structures and structural members, roads, geological layers, archaeological sites and many more. The technology is based on electromagnetic radiation in the UHF/VHF range (10 MHz to 3 GHz). The choice of the frequency depends on the intended use, depth and size of the target and medium where the target is located. Joined with other testing methods (ultrasound method, dynamic methods with forced or ambient vibrations, electrical conductivity testing, etc.), GPR can provide a deep insight into the investigated object. However, like many other non-destructive methods, the choice of input parameters may affect the results. In this regard, a case study presented in this paper demonstrates not only different applications of GPR in civil engineering but also the determination (calibration) of one of those input parameters: the dielectric constant of glued laminated timber. The challenge here was not only to investigate the influence of the direction of measurements with regards to the direction of the fibers but also to acknowledge the contribution of the test antenna used during testing and dielectric constant calibration.

Inspection of wind turbine bolted connections using the ultrasonic phased array system

This study explores the inspection of bolted connections in wind turbines, specifically focusing on the application of Phased Array Ultrasonic Testing (PAUT). The research comprises four sections: Acoustoelastic Constant calibration, high tension investigation on bolts, blind tests on larger bolts, and Finite Element Analysis (FEA) verification. The methodology shows accurate results for stress while the bolt is under operative loads, and produces a clear indication of when it is above these loads and beginning to deform. PAUT emerges as a promising tool for bolt inspection, offering multiple imaging modes for simultaneous stress monitoring and defect detection. The study advocates for PAUT as a robust method to enhance wind turbine safety, longevity, and future in-situ testing.

Development of a Smartwatch with Gas and Environmental Sensors for Air Quality Monitoring.

In recent years, there has been a growing interest in developing portable and personal devices for measuring air quality and surrounding pollutants, partly due to the need for ventilation in the aftermath of COVID-19 situation. Moreover, the monitoring of hazardous chemical agents is a focus for ensuring compliance with safety standards and is an indispensable component in safeguarding human welfare. Air quality measurement is conducted by public institutions with high precision but costly equipment, which requires constant calibration and maintenance by highly qualified personnel for its proper operation. Such devices, used as reference stations, have a low spatial resolution since, due to their high cost, they are usually located in a few fixed places in the city or region to be studied. However, they also have a low temporal resolution, providing few samples per hour. To overcome these drawbacks and to provide people with personalized and up-to-date air quality information, a personal device (smartwatch) based on MEMS gas sensors has been developed. The methodology followed to validate the performance of the prototype was as follows: firstly, the detection capability was tested by measuring carbon dioxide and methane at different concentrations, resulting in low detection limits; secondly, several experiments were performed to test the discrimination capability against gases such as toluene, xylene, and ethylbenzene. principal component analysis of the data showed good separation and discrimination between the gases measured.

Hydrodynamic function and spring constant calibration of FluidFM micropipette cantilevers

Fluidic force microscopy (FluidFM) fuses the force sensitivity of atomic force microscopy with the manipulation capabilities of microfluidics by using microfabricated cantilevers with embedded fluidic channels. This innovation initiated new research and development directions in biology, biophysics, and material science. To acquire reliable and reproducible data, the calibration of the force sensor is crucial. Importantly, the hollow FluidFM cantilevers contain a row of parallel pillars inside a rectangular beam. The precise spring constant calibration of the internally structured cantilever is far from trivial, and existing methods generally assume simplifications that are not applicable to these special types of cantilevers. In addition, the Sader method, which is currently implemented by the FluidFM community, relies on the precise measurement of the quality factor, which renders the calibration of the spring constant sensitive to noise. In this study, the hydrodynamic function of these special types of hollow cantilevers was experimentally determined with different instruments. Based on the hydrodynamic function, a novel spring constant calibration method was adapted, which relied only on the two resonance frequencies of the cantilever, measured in air and in a liquid. Based on these results, our proposed method can be successfully used for the reliable, noise-free calibration of hollow FluidFM cantilevers.

A unique numerical iterative approach for modelling individual phase stress-strain curves in dual phase steel

Understanding the effects of martensite volume fractions (V m) in dual phase (DP) steel resulting from heat treatment is crucial for designing structures for mechanical impact resistance and optimizing manufacturing processes. DP steel’s material behaviour depends heavily on its microstructure properties. While stress-strain curves for individual phases in DP steels are often determined using empirical models, extensive experimental data is required to establish empirical model constants. This research aims to achieve two main objectives: firstly, to calibrate stress-strain curves for pure ferrite and pure martensite using limited experimental data using micromechanical adaptive iteration algorithm (MAIA). This calibration involves using stress-strain data from DP steels with varying V m during the calibration stage and additional data for verification. Secondly, to conduct a comprehensive sensitivity analysis of MAIA to assess its capabilities and limitations. Microstructure-based finite element (FE) models, simulated with ABAQUS/Standard, are employed to predict stress-strain curves under uniaxial tensile test conditions. The MAIA approach successfully calculated ferrite and martensite stress-strain curves that could predict plastic behaviour of DP steel with different V m, which agreed with experimental work. Key advantages of this approach include avoiding complex 3D microstructure geometries and requiring only two experimentally obtained stress-strain curves with different Vm for material constant calibration, along with another curve for validation. However, the experimental data selected for calibration must have a V m difference between 20%–50% and one of the DP steels must have a low martensite volume fraction. The FE micromechanical model could capture the effect of softening of martensite phase and strengthening of ferrite phase as compared to its bulk properties for DP steel. The effect of V m on strain hardening rate was also successfully captured. This technique comes with obvious shortcomings, such as excluding crystal plasticity behaviour, and change in chemical composition within the individual phase with varying martensite volume fraction.

Calculation of dielectric constant calibration characteristics of sensors using the method of moments

This research is devoted to the issues of further development of methods of experimental measurement of dielectric characteristics of solid materials, liquids and liquid–gas media, which are foam structures. In recent decades, foam structures have gradually filled and supplanted traditional dielectric materials. There are still no scientific and metrology-based methods and devices for correct measurements of foam. In the paper, the method of moments (MoM) is employed for resonator measurements. The obtained results for a wide range of dielectric constants from 1 to 80 are interesting for determining the sensitivity of measurements, the influence of frequency measurement errors, and determining the number of measurement points.

Variable microfluidic dosing valve for gas chromatography

Miniaturization coupled with the introduction of microfluidic systems and devices into the chromatograph hardware is one of the main approaches to the creation of modern gas chromatographic equipment. For variable sample dosing in automatic mode, a microfluidic dosing valve based on microelectromechanical systems was developed. The manufactured device provides multi-point calibration with a single calibration gas mixture. Two methods for constructing a calibration dependence were implemented using the developed dosing device: a calibrated loop for 250 μl taken as a constant dosing loop and calibration solutions (gas mixtures of propane in helium (GSO 10463–2014) with concentrations of 0.0025, 0.025, 0.25, 0.5б and 1.25 % vol.) were used in the first method, whereas in the second one a variable dosing provided by the developed microfluidic dosing valve which consisted in the possibility of introducing a different amount of the calibration gas mixture of propane in helium (2.5 % vol.) into the chromatographic column due to changing the time of sample injection at a constant pressure was implemented. The experiment was carried out on a PIA gas microchromatograph with a MEMS column (a sectional plane of 1 × 1 mm and a 1-m channel) with a Carbopak B adsorbent. It is shown that the use of the developed dosing device as part of the PIA gas microchromatograph makes it possible to carry out a metrologically assured quantitative analysis.

Study on the Method of Extracting Plasma Lines Based on Sanya Incoherent Scatter Radar

The plasma lines observed by Sanya incoherent scatter radar (SYISR) are dependent on the enhancement of Langmuir waves due to superthermal photoelectrons generated by solar EUV radiation. The plasma line power spectrum can be obtained using long-pulse and alternating-code transmission signals during the period from sunrise to noon almost every day. For the power spectrum of the long pulse, the CLEAN algorithm that has been applied in this field is used to verify the feasibility of this method for SYISR in only a few cases. However, it is difficult to deal with alternating code with such a low SNR using the general deconvolution method. The irreversible-migration filtering (IMF) method has been developed to separate signal noise from the measurements of the alternating code. Some experimental results from the SYISR measurements validate the excellent performance of the IMF method for alternating code. Additionally, an example observation of the electron density with a high time and range resolution is derived. The results show that plasma line detection can be a powerful new observational capability for SYISR as an ionospheric experimental mode for ionospheric calibration, when possible, which can be simultaneously measured with the ion line for constant radar calibration in the standard fitting of the ion line.

Multi-Modal and Self-Reconstruction Conditioning Circuit of Semiconductor Gas Sensors

Semiconductor gas sensors (chemiresistors) have been widely used in many fields. The emerging novel gas sensors usually have large initial resistance and ultra-high sensitivity, and their resistance value may change significantly during the response process. It is difficult for conventional front-end conditioning circuits to meet the requirements of large measurement range and high accuracy. Meanwhile, the circuit needs to be compatible with several forms of signals generated from different types of sensors, such as voltage, current, and resistance. This study designs a front-end conditioning circuit that is compatible with various types of gas sensors and can adjust the measurement range in real time. The circuit has different functional states, which can realize four functions: constant voltage measurement, constant current measurement, electrochemical measurement, and parameter calibration. The modal transformation of the circuit is controlled by a multiplexer, which can perform automatic transformation according to software instructions. Our work provides a flexible circuit framework composed of different functional units, with the characteristics of multi-modal and self-reconstruction. It is suitable for designing integrated or fixed-function circuits and is convenient for miniaturization and cost reduction.

Nonzero-Order Resonances in Single-Beam Spin-Exchange Relaxation-Free Magnetometers

Zero-field optically pumped magnetometers operating in the spin-exchange relaxation-free (SERF) regime have been extensively studied, and usually depend on zeroth-order parametric resonance to measure the magnetic field. However, the studies conducted on this topic lack thorough analyses and in-depth discussion of nonzero-order magnetic resonances in single-beam SERF magnetometers. In this paper, we analyzed the nonzero-order resonance, especially the first-order resonance, based on a single-beam SERF magnetometer, and discussed its various applications. A comprehensive theoretical analysis and experiments were conducted with respect to multiple functions, including nonzero finite magnetic field measurements, spin polarization measurement, and in situ coil constant calibration. The results showed that first-order resonance can be utilized for nonzerofinite magnetic field measurements, and the spin polarization of alkali-metal atoms can be determined by measuring the slowing-down factor using the resonance condition. Furthermore, acquiring the first-order resonance point at an equivalent zero pump light power through fitting offers an approach for quick and precise in situ coil constant calibration. This study contributes to the applications of SERF magnetometers in nonzero finite magnetic fields.

On the Ion Line Calibration by Plasma Line in ISR Measurements

The radar constant calibration in incoherent scatter radar ion line processing is essential for the data quality and was not paid enough attention in previous studies. In this investigation, based on several experiments made by the newly built Sanya incoherent scatter radar (SYISR), we made and evaluated the ion line calibration by plasma line both in case study and statistically. The calibration factor had local time and altitude variations, due to the corresponding variations of the transmitted power, the radar gain, and the noise temperature. We obtained a mean calibration factor of 1.35 by the simultaneous measured plasma line and ion line electron density and applied it to a one-month ion line observation calibration. Through a co-located ionosonde measured foF2 evaluation, the calibration decreased the mean deviation from −1.92 MHz (−18%) to −0.33 MHz (−3%), which resulted in much better agreement between the ion line foF2 after calibration and the ionosonde results. The existed deviations between after calibration and ionosonde results were due to the uncertainties either in the used calibration factor or the ionosonde measurements. An empirical Te/Ti usage in raw electron density estimation and ignoring the seasonal and short-term variations of the effecting factors might influence the calibration performance. Using the to-be-completed SYISR Tristatic System, the performance of plasma line calibration technique is expected to be improved in the future.

Unpredictable and monetized contact with the police: Race, avoidance behaviors, and modified activity spaces

AbstractExponential growth in order maintenance policing and associated misdemeanor sanctions have led to disproportionate consequences for people of color. Using data from qualitative interviews with individuals in the metropolitan St. Louis, Missouri, region, the current study documents the racialized and monetized nature of police contact. This work extends extant scholarship by considering how minor contact with the police shapes individual avoidance behaviors and activity spaces, places where people work and live. We consider how the combination of monetary sanctions, warrants, incarceration, and overpolicing in the region affects avoidance behaviors, particularly for people of color. Our findings suggest that the frequently unpredictable nature of police contacts and the parochial and often profit‐focused structure of policing organizations in the region leads individuals to modify the ways in which they move through the region and, for some, to isolate. Narratives reflect the need for constant calibration of behaviors and decisions, as well as the legacy that police contact and monetary sanctions can have on everyday routines.

Dispersed fringe cophasing method based on principal component analysis.

With the success of the Webb telescope, dispersed fringe sensing (DFS), with the significant merit of a large capture range, is proving to be a promising cophasing approach for a large-aperture segmented telescope. In this Letter, a novel, to the best of our knowledge, piston error extraction method based on principal component analysis (PCA) technology is proposed. In this method, all the one-dimension intensity distributions along the dispersion axis for different interference positions are regarded as a set of random phase-shifted interference signals. PCA technology is utilized to obtain its corresponding continuous principal phase and the piston error could be directly estimated proportionally from the slope of the phase-wavenumber line. This method avoids nonlinear operations, similar to Shi's traditional framework; no active move is needed for fine cophasing, and the method is also free of characteristic constant calibration in sidelobe peak displacement- and slope-based methods. Preliminary simulations of the method's coarse-then-fine cophasing ability with high accuracy are presented here to show its potential.

FishRecGAN: An End to End GAN Based Network for Fisheye Rectification and Calibration

We propose an end-to-end deep learning approach to rectify fisheye images and simultaneously calibrate camera intrinsic and distortion parameters. Our method consists of two parts: a Quick Image Rectification Module developed with a Pix2Pix GAN and Wasserstein GAN (W-Pix2PixGAN), and a Calibration Module with a CNN architecture. Our Quick Rectification Network performs robust rectification with good resolution, making it suitable for constant calibration in camera-based surveillance equipment. To achieve highquality calibration, we use the straightened output from the Quick Rectification Module as a guidance-like semantic feature map for the Calibration Module to learn the geometric relationship between the straightened feature and the distorted feature. We train and validate our method with a large synthesized dataset labeled with well-simulated parameters applied to a perspective image dataset. Our solution has achieved robust performance in high-resolution with a significant PSNR value of 22.343. 1

Comparing and combining data from immune assays based on left-censored multivariate normal model assuming common assay differences across settings.

In vaccine research towards the prevention of infectious diseases, immune response biomarkers serve as an important tool for comparing and ranking vaccine candidates based on their immunogenicity and predicted protective effect. However, analyses of immune response outcomes can be complicated by differences across assays when immune response data are acquired from multiple groups/laboratories. Motivated by a real-world problem to accommodate the use of two different neutralization assays in COVID-19 vaccine trials, we propose methods based on left-censored multivariate normal model assuming common assay differences across settings, to adjust for differences between assays with respect to measurement error and the lower limit of detection. Our proposed methods integrate external paired-sample data with bridging assumptions to achieve two objectives, both using pooled data acquired from different assays: (i) comparing immunogenicity between vaccine regimens, and (ii) evaluating correlates of risk. In simulation studies, for the first objective, our method leads to unbiased calibrated assay mean with good coverage of bootstrap confidence interval, as well as valid test for immunogenicity comparison, while the alternative method assuming constant calibration model between assays leads to biased estimate of assay mean with undercoverage problem and invalid test with inflated type-I error; for the second objective, in the presence of noticeable left-censoring rate, our proposed method can drastically outperform the existing method that ignores left-censoring, in terms of reduced bias and improved precision. We apply the proposed methods to SARS-CoV-2 spike-pseudotyped virus neutralization assay data generated in vaccine and convalescent samples by two different laboratories.

Emissivity constraints for calibration constant models of multi-wavelength pyrometers

The previous true temperature inversion method of multi-wavelength pyrometer based on calibration constant needs to construct a large number of emissivity samples for calculation. It does not fully consider the properties of the measured target. Hence, it is difficult to be applied to high-speed measurement. This paper demonstrates the intrinsic relationship between the calibration constant and emissivity, which is universally applicable to all measured targets. The simulation results show that the calculation speed is increased by 15.47–22.84%, and the calculation accuracy remains unchanged after adding constraints. In practical experiments, the calculation speed is increased by 10.66–18.06%. The experimental results fully show that the constraint method proposed in this paper can effectively improve the calculation speed without changing the accuracy of the constant calibration model. The measurement results of the rocket plume temperature fully reveal the potential application value of the calibration constant constraint algorithm.

Расчет температур при чистовом фрезеровании жаропрочного сплава марки ХН56ВМКЮ-ВД

Introduction. One of the most important tasks in cutting metals and alloys is the control of the temperature factor, since temperature is one of the limitations in determining cutting conditions. This approach makes it possible to determine rational (in some cases, optimal) milling modes. Experimental methods for determining the temperature are labor-consuming, costly and not always available. The labor-consuming nature lies in the need for constant adjustment of experimental equipment due to changing cutting conditions, electrical insulation of the tool and workpiece, the appearance of parasitic electrical micro-voltage (if we are talking about temperature measurement methods with thermocouples), constant calibration of instruments and selection of thermal radiation coefficients (if we are talking about non-contact measurement methods). In this regard, there is a need for a theoretical determination of temperatures during milling with minimal use of experimental data. The purpose of the work: to develop a method for theoretical calculation of temperature during milling (cutting) of nickel-based heat-resistant materials on the example of 56% Ni -Cr-W Mo-Co-Al alloy (56% Ni, 0.1% C, 10% Cr, 6.5% W, 6% Al, 6.5% Mo, 0.6% Si, 13 % Co, 1% Fe). Research methodology. To determine theoretically the cutting temperatures, a mathematical model is formed that takes into account the mechanical and thermophysical properties of the material being processed and its change depending on the temperature variations during milling, the geometry of the cutting tool and the features of the schematization of the milling process. The experimental part of the study is carried out on a console milling machine KFPE-250 with a CNC system Mayak-610. The 56% Ni -Cr-W Mo-Co-Al material is processed with a Seco JS513050D2C.0Z3-NXT cutter with different speeds and feeds. The temperature is measured using a Fluke Ti400 thermal imager. Results and discussion. A theoretical model for calculating the temperature (for the group of 77% Ni - Cr - Ti - Al - B, 66% Ni - Cr - Mo - W - Ti - Al, 73% Ni-Cr-Mo-Nb-Ti-Al and 56% Ni -Cr-W Mo-Co-Al alloys) during milling of heat-resistant nickel-based alloys is developed, which makes it possible to predict the temperature value at the face and flank of the tool when changing cutting conditions (speed, feed, depth, cutting tool geometry), as well as the cutting temperature. An analysis of the experimental and theoretically predicted values of the cutting temperature showed a satisfactory agreement between the corresponding values.

Modified approximate quantitative spectral analysis of rocks

Two main methods of approximate quantitative atomic emission spectral analysis have traditionally been developed in the Central Laboratory of the Karpinsky All-Russian Research Geological Institute (VSEGEI): evaporation from the channel of carbon electrodes and a more efficient spill method. When comparing these two methods for introducing a sample into the arc discharge, two factors should be taken into account: the amount of material entering the discharge and the completeness of evaporation of chemical elements. A sample weighing about 40 mg is almost completely evaporated from the channel of a carbon electrode. The spill-injection method provides a uniform supply of a large powder sample (400 – 500 mg) into the arc discharge. The first method of analysis is well suited for determination of volatile and nonvolatile elements, whereas the second method provides stable conditions for evaporation and excitation during all the time when the sample is supplied into the discharge. The spill-injection method is more sensitive to changes in the bulk composition of the sample and the particle size of the sample material compared to evaporation from the electrode channel. These are the main factors affecting the magnitude of the systematic error in determining the concentrations of semi-volatile elements. The errors that make up the total error of approximate quantitative atomic emission spectral analysis are systematically analyzed in spectral laboratories. Comparison of the results of analysis of the same samples (state standard samples) with the results of chemical methods over a period of several years revealed that the maximum contribution to the total error is attributed to the visual assessment of the content and visual interpolation, as well as to a discrepancy in interpretation of results after a long time, etc. The impact of various errors has been reduced through the use of the MAES analyzer and the wide capabilities of the Atom software, which offer a correct consideration of the background with the option of individual settings, the use of coefficients accounting for the interference effect, and the possibility of analysis by several analytical lines of each chemical element thus allowing the use of constant calibration curves for a wide range of rock compositions.

Energy imparted and ionization yield in nanometre-sized volumes

In radiation physics, the biological effectiveness of radiation is generally estimated from the energy imparted to a sensitive volume of given size. However, measurements of this quantity are carried out almost exclusively with ionization-based techniques, by converting the ionization charge signal to energy imparted by means of a constant calibration factor, independent of particle type and energy. This procedure is reliable when the tissue-equivalent size of the sensitive volume is of the order of 1 μm and larger, since in this case the number of radiation-induced collisions is high and the distribution of energy transfer per single collision is masked by the multiple averaging. However, its reliability can be called into question when the size of the sensitive volume is decreased to the nanometre scale, as it is the case in experimental nanodosimetry. For this reason, the present study investigates the relationship between the two stochastic quantities energy imparted and ionization yield, calculated by Monte Carlo simulations in spherical sensitive volumes with diameter ranging from 100 nm down to 1 nm. The analysis was carried out for protons and carbon ions in the energy range from 1 to 100 MeV/u, crossing liquid-water sensitive spheres along their diameter. Simulations were done by means of the Geant4-DNA Monte Carlo code, with two different physics lists. A strong correlation between the energy imparted and the ionization yield was found, which comprises not only their mean values, but their entire stochastic distributions, even when the diameter of the sensitive volume is as small as 1 nm.