Calibration Relationship Research Articles

Determination of Fluorine by Ion-Selective Electrode and High-Resolution Continuum Source Graphite Furnace Molecular Absorption Spectrometry with Respect to Animal Feed Safety.

Fluorine, depending on its concentration and chemical form, is essential or toxic to humans and animals. Therefore, it is crucial to be able to determine it reliably. In this study, fluorine was determined in animal feed after extraction with HCl (gastric juice simulation). The standard potentiometric method with a fluoride-selective electrode (ISE) and newly developed high-resolution continuum source graphite furnace molecular absorption spectrometry (HR-CS GFMAS) method was applied. Feed samples turned out to be a challenge for HR-CS GFMAS. Chemical interferences (formation of competing molecules, CaF, GaCl, and GaP, instead of the target GaF molecule) and spectral effects (including a phosphorous molecule spectrum and atomic lines) were identified. An additional difficulty was caused by reagent contamination with F and memory effects. Difficulties were eliminated/reduced. The quality of ISE analysis was multi-directionally verified (including comprehensive proficiency testing). A risk of inaccuracy at low F concentration, where the calibration relationship is nonlinear, was investigated. The results of both methods were consistent, which confirms the accuracy of the methods and informs that the extracted fluorine is in fluoride form. The results of extensive ISE tests conducted in Poland in 2021-2023 have shown that, in most cases, the fluoride content is significantly lower than the threshold values.

Determination of Inorganic Arsenic Species in Drinking Water by Cloud Point Extraction Coupled with Ultraviolet-Visible Spectrophotometry

A novel method has been developed for accurately quantifying arsenic species, including As(III), As(V), and total inorganic arsenic, in drinking water. The technique combines ultraviolet-visible spectrophotometry with cloud point extraction (UV/CPE), ensuring high sensitivity and selectivity. The methodology relies on complex formation between As(III) and Pyronin B in the presence of tartaric acid. The resulting complex is efficiently extracted into the surfactant-rich phase consisting of 5.0% (v/v) Triton X-114. Under optimized conditions, a linear calibration relationship from 3 to 500 µg/L is obtained. The method offers low detection and quantification limits of 1.04 and 3.48 µg/L, respectively, with a corresponding relative standard deviation below 5% for 11 replicates. Furthermore, spiked samples demonstrated excellent recovery values from 95.1% to 102.3%. The accuracy was verified by the analysis of the standard reference material SRM 1643e (trace elements in water), revealing no significant differences at the 95% confidence level. The approach was successfully utilized for the quantification of As(III), As(V), and total inorganic arsenic in commercial and domestic drinking water.

Dual-Channel Mapping–Gas Column Concentration Inversion Method Based on Multispectral Imaging

Infrared multispectral imaging technology can achieve the long-distance, wide-ranging and fast detection of target gas, and has been widely used in the fields of dangerous-gas detection and environmental monitoring. However, due to the difficulty in acquiring background radiation as well as atmospheric disturbance and noise interference in the detection process, the quantitative detection of gas concentration has become a difficult problem to solve. Therefore, this paper proposes an inversion method for gas column concentration based on infrared multispectral imaging technology. Firstly, infrared background radiation images of the non-target gas absorption spectrum band were collected and converted into background radiation images of the target gas absorption spectrum band according to the dual-channel mapping relationship. Then, combined with the gas radiation images of the target gas absorption spectrum band, the column concentration distribution of the gas was obtained by using the measured calibration relationship between absorbance and column concentration. Experiments of gas detection in different environments were carried out, and the column concentration distribution of the target gas was inverted using this method; the results showed that the average relative error of the inversion of the gas column concentration was 4.84%, which enables the quantitative detection of gas column concentration in a complex environment.

Classification and evaluation for nearside/backside defect via magnetic flux leakage: A dual probe design with SVM and PSO intelligence algorithms

In automated magnetic flux leakage (MFL) applications, the defect location on the nearside/backside of the tested specimen is often unknown, posing challenges for evaluating defect parameters due to varying calibration relationships. To address this, we propose a combined scheme of defect classification followed by parameter evaluation for testing steel plates with nearside/backside defects. The innovative design of dual probes, featuring lift-off difference, is used for signal acquisition and analysis. An efficient defect classification is achieved through a PSO-SVM neural network, and defect parameter evaluation involves solving the inverse problem using a particle swarm intelligence algorithm. MFL signal from steel plates with circular hole defects of different sizes were tested using a self-developed system and dual probes. Finite element analysis, alongside experimental data, explores the change in MFL signal. Defect classification and parameter evaluation, based on experimental signals and simulations, confirm the effectiveness of scheme in quantitatively assessing defect parameters with an evaluation accuracy within 0.3 mm. This scheme serves as a reference for intelligent testing and evaluation using MFL signals.

Electroanalytical Determination of Trimetazidine in Pharmaceuticals and Synthetic Urine Using an Anodically Treated Boron-Doped Diamond (BDD) Electrode and Square Wave Voltammetry (SWV)

Trimetazidine dihydrochloride is an anti-ischemic agent widely used in the treatment of coronary artery disease, more specifically in the treatment of angina. Here is reported a simple and sensitive electroanalytical methodology for quantifying trimetazidine in pharmaceutical and synthetic urine samples using square-wave voltammetry. The influence of anodic and cathodic treatments on boron-doped diamond (BDD) was evaluated. The best results for trimetazidine were obtained using a BDD treated anodically at +3.0 V versus Ag(s)/AgCl(s)/Cl-(aq., saturated KCl) for 300 s in 0.1 mol L−1 H2SO4. The determination of trimetazidine was carried out in Britton-Robinson buffer at pH 3. Trimetazidine oxidation reveals two well-defined irreversible oxidation peaks. A calibration relationship was obtained from 0.35 mg L-1 to 2.6 mg L−1 (R2 = 0.997). Limits of detection and quantification for trimetazidine were 5.63 x 10−9 and 1.88 x 10−8 mol L−1, respectively. Recovery values were between 97 and 101 % and 96.8 and 99.8 % in pharmaceutical and synthetic urine.

Over-30-GeV intense laser phase-locked direct electron acceleration

When an intense laser obliquely irradiates a solid, a pre-pulse will first ionize the solid surface, followed by the main pulse interacting with the plasma and ultimately being reflected by the plasma. Simultaneously, certain electrons within the plasma will be trapped in the accelerating phase of the laser field, subsequently gaining effective acceleration within the field, this phenomenon is known as phase-locked electron acceleration. Given the current intense lasers' electric field intensity nearing the TV/m range, electrons could potentially acquire energy levels on the order of hundreds of GeV or even TeV, provided they stay in the accelerating phase of the laser field long enough. Here, we initially use PIC (Particle-in-Cell) simulations to simulate the interaction process between laser pulses and plasma, thereby obtaining the properties of phase-locked electrons. In order to reduce computational demands, we turn to use a three-dimensional (3D) test particle model to calculate the subsequent interactions of these electrons with the reflected laser field. By this model, we obtain the data of the locked-phase electrons after having interacted with the reflected laser (Fig. (a)). Furthermore, we use this model to calculate the dynamical behavior of electrons under different initial conditions (Fig. (b)). Under the laser intensity of <inline-formula><tex-math id="M1">\begin{document}$ {a}_{0}=350 $\end{document}</tex-math></inline-formula>(<inline-formula><tex-math id="M2">\begin{document}$ {a}_{0} $\end{document}</tex-math></inline-formula> is the normalized laser vector potential), the energy of the electrons directly accelerated by the laser is enhanced to 32 GeV. In contrast, under the same laser intensity, the energy of the electrons accelerated by ponderomotive force is only 0.35 GeV. The research findings indicate that the strong laser with peak power around 10 PW can directly accelerate electrons to approximately 30 GeV. Additionally, this study outlines the optimal initial conditions for injecting electrons into the laser field and the final electron energy within the phase-locked acceleration mechanism, thereby establishing a calibration relationship with the laser field intensity. Given the continual enhancement of laser intensity and the potential application of the laser phase-locked electron acceleration mechanism to positron acceleration, this research holds promise for its implementation in fields such as miniaturized positron-electron colliders and high-energy gamma-ray sources.

SPECTROSCOPIC INVESTIGATIONS OF POLARIS FIELD STARS

We present the results of an analysis of 28 spectra of 18 Polaris field A–G V stars obtained in 2016–2023. Derived radial velocities and Teff along with distances and reddenings from the Gaia DR3 catalog allowed us to calculate radii of the stars and compare them with calibration relationships “Spectral type – Luminosity” for MS stars. As a result, radii and distances for 9 stars were found overestimated compared to those determined photometrically. Therefore, the DR3 distances are unreliable and should be revisited. According to our data for these stars and their photometric distances, 15 objects belong to a possible old open cluster that is currently dissolved in the Polaris field at a distance ∼70–110pc, while two objects belong to the thick disk, and one belongs to a possible another star group located at a distance of 130 pc.

Study on Calibration Method for the Count of Living Algal Cells Detection Based on Variable Fluorescence in Ballast Water.

In the monitoring the discharge of ballast water, the count of living algal cells is of utmost significant. Variable fluorescence, denoted as Fv, stands as an optimal parameter for photosynthetic fluorescence, efficiently charactering the living algal cells count, unaffected by the ballast waters' complex background fluorescence environment. This study deeply investigates the quantitative relationship between Fv and the count of living algal cells. Observations indicate that single cell fluorescence yield (abbreviated as SCF) varies significantly across different algae species, leading to considerable errors in quantifying living algal cell count in ballast water with unknown components using the calibration relationship between Fv and the cell count. Thus, correcting SCF prior to calibration becomes necessary. The paper proposes an innovative SCF correction method based on cell cross-sectional area and an eμ factor (where μ is the expected value of the functional absorption cross-section of PSII) This method mitigates the influence of cell size and species differences on quantifying the living algal cell count. Correction operation trials revealed that dividing the SCF measurement by cell cross-sectional area and multiplying by eμ enhanced the correction effect. Comparative experiments demonstrated marked improvement: Relative errors (REs) for Chlorella pyrenoidosa and Chlorella marine, both belonging to the Chlorophyta group, fell from 92.1% and 90.6% to 37.2% and 9.5% respectively post-correction. Similarly, REs for Thalassiosira weissflogii and Nitzschia closterium minutissima, from the Bacillariophyta group, decreased from 74.7% and 68.1% to 14.3% and 19.1% respectively. The RE of Peridinium from the Pyrrophyta group dropped from 28.4% to 12.1%. The results underscore the effectiveness of cell cross-sectional area and eμ in correcting SCF, thus offering a novel correction method for swift and precise measurement of living algal cell count in ballast water, based on variable fluorescence.

Assigning harvested waterfowl to geographic origin using feather δ2H isoscapes: What is the best analytical approach?

Establishing links between breeding, stopover, and wintering sites for migratory species is important for their effective conservation and management. Isotopic assignment methods used to create these connections rely on the use of predictable, established relationships between the isotopic composition of environmental hydrogen and that of the non-exchangeable hydrogen in animal tissues, often in the form of a calibration equation relating feather (δ2Hf) values derived from known-origin individuals and amount-weighted long-term precipitation (δ2Hp) data. The efficacy of assigning waterfowl to moult origin using stable isotopes depends on the accuracy of these relationships and their statistical uncertainty. Most current calibrations for terrestrial species in North America are done using amount-weighted mean growing-season δ2Hp values, but the calibration relationship is less clear for aquatic and semi-aquatic species. Our objective was to critically evaluate current methods used to calibrate δ2Hp isoscapes to predicted δ2Hf values for waterfowl. Specifically, we evaluated the strength of the relationships between δ2Hp values from three commonly used isoscapes and known-origin δ2Hf values three published datasets and one collected as part of this study, also grouping these data into foraging guilds (dabbling vs diving ducks). We then evaluated the performance of assignments using these calibrations by applying a cross-validation procedure. It remains unclear if any of the tested δ2Hp isoscapes better predict surface water inputs into food webs for foraging waterfowl. We found only marginal differences in the performance of the tested known-origin datasets, where the combined foraging-guild-specific datasets showed lower assignment precision and model fit compared to data for individual species. We recommend the use of the more conservative combined foraging-guild-specific datasets to assign geographic origin for all dabbling duck species. Refining these relationships is important for improved waterfowl management and contributes to a better understanding of the limitations of assignment methods when using the isotope approach.

Combining accelerometry with allometry for estimating daily energy expenditure in joules when in-lab calibration is unavailable

BackgroundAll behaviour requires energy, and measuring energy expenditure in standard units (joules) is key to linking behaviour to ecological processes. Animal-borne accelerometers are commonly used to infer proxies of energy expenditure, termed ‘dynamic body acceleration’ (DBA). However, converting acceleration proxies (m/s2) to standard units (watts) involves costly in-lab respirometry measurements, and there is a lack of viable substitutes for empirical calibration relationships when these are unavailable.MethodsWe used past allometric work quantifying energy expenditure during resting and locomotion as a function of body mass to calibrate DBA. We used the resulting ‘power calibration equation’ to estimate daily energy expenditure (DEE) using two models: (1) locomotion data-based linear calibration applied to the waking period, and Kleiber’s law applied to the sleeping period (ACTIWAKE), and (2) locomotion and resting data-based linear calibration applied to the 24-h period (ACTIREST24). Since both models require locomotion speed information, we developed an algorithm to estimate speed from accelerometer, gyroscope, and behavioural annotation data. We applied these methods to estimate DEE in free-ranging meerkats (Suricata suricatta), and compared model estimates with published DEE measurements made using doubly labelled water (DLW) on the same meerkat population.ResultsACTIWAKE’s DEE estimates did not differ significantly from DLW (t(19) = − 1.25; P = 0.22), while ACTIREST24’s estimates did (t(19) = − 2.38; P = 0.028). Both models underestimated DEE compared to DLW: ACTIWAKE by 14% and ACTIREST by 26%. The inter-individual spread in model estimates of DEE (s.d. 1–2% of mean) was lower than that in DLW (s.d. 33% of mean).ConclusionsWe found that linear locomotion-based calibration applied to the waking period, and a ‘flat’ resting metabolic rate applied to the sleeping period can provide realistic joule estimates of DEE in terrestrial mammals. The underestimation and lower spread in model estimates compared to DLW likely arise because the accelerometer only captures movement-related energy expenditure, whereas DLW is an integrated measure. Our study offers new tools to incorporate body mass (through allometry), and changes in behavioural time budgets and intra-behaviour changes in intensity (through DBA) in acceleration-based field assessments of daily energy expenditure.

Optimization of the number and locations of the calibration stations needed to monitor soil moisture using distributed temperature sensing systems: A proof-of-concept study

The single-probe heat-pulse (SPHP) technique combined with the Fiber-optic Distributed Temperature Sensing (DTS) technology can offer novel high-resolution measurements of soil moisture (θ) over spatial scales ranging from several centimeters to several kilometers. However, the key limitation of this method is in obtaining the calibration relationship between θ and soil thermal conductivity (λ) across a specific field. In a previous study, a new methodology using a Gaussian processes model was presented to account for the spatial variability in the λ-θ relationship. The model aggregated θ measurements from soil moisture sensors scattered over the SPHP transect with the corresponding DTS λ measurements at their locations. In this study, a novel methodology is tested to optimize the number and locations of soil moisture sensors required to account for the spatial variability of the λ-θ relationship to achieve higher accuracy from the SPHP technique. The proposed methodology utilizes hierarchical clustering to analyze the information contained in the spatial structure of the SPHP measurements as the soil dries from a nearly-saturated condition. The proposed methodology was tested using data from a field in Oklahoma. Monte-Carlo simulation was performed to validate the performance of the proposed methodology. The predictions obtained from the proposed methodology resulted in θ measurements accuracy comparable to those obtained from the 10% best Monte-Carlo iterations of randomly assigned soil moisture locations. This study demonstrates that the proposed methodology is more efficient than the traditional practice of randomly spreading calibration soil moisture sensors along the SPHP transect.

A Radiometric Block Adjustment Method for Unmanned Aerial Vehicle Images Considering the Image Vignetting

Unmanned aerial vehicles (UAVs) equipped with different sensors can provide data with high spatiotemporal resolution and have broad application prospects. During the flight of the UAV, changes in illumination, exposure time, etc., will cause different degrees of radiometric differences between images, resulting in a calibration relationship established on a single image that cannot be applied to other images; in addition, the vignetting effect also significantly changes the brightness distribution inside an image, thus posing challenges for radiometric calibration of UAV images. In this paper, based on block adjustment (BA), we proposed a radiometric block adjustment model under the consideration of vignetting and the light-dark differences between images. The proposed method requires only a small number of calibration blankets, thus reducing the complexity of the experiment. The results from two study areas showed that the proposed method could compensate for vignetting to a certain extent and the radiometric consistency of the two datasets was improved from 12.9%~21.8% to 4.7%~12.7%. Validated using ground samples, the mean RMSE and MRPE of all five bands were 0.054, 21.8%, and 0.037, 20.4% in the two study areas, respectively. The total uncertainty was less than 8.1%. When there were obvious light-dark differences between images, such as in the visible light bands, our method could significantly improve the accuracy of the radiometric calibration.

The relationship of retinal vessel calibres with cardiovascular risk factors in apparently healthy young eyes

AbstractPurpose: Although retinal vascular calibre has been linked to increased cardiovascular (CV) risk, it remains unclear whether retinal vascular morphologic changes are already evident in young adults and correlate with modifiable CV risk factors. The purpose of this study was to explore the relationship of retinal arteriolar and venular calibre with CV risk factors and ocular parameters in healthy young subjects.Methods: A cross‐sectional study was performed in 52 apparently healthy subjects (mean 21.6 ± 2.2 years of age). Retinal vascular calibres were measured from fundus photographs using semi‐automated imaging software and expressed as central retinal arteriolar (CRAE) or venular (CRVE) equivalent and arterio‐venous ratio (AVR). CV risk factors and ocular parameters were assessed. Forward stepwise multiple linear regression analysis was used to detect the independent relationship between retinal vascular calibre and CV and ocular parameters.Results: Means for CRAE and CRVE were 191 ± 15.4 μm and 209 ± 15.8 μm respectively. The mean CRAE but not CRVE was significantly higher in women than in men (p = 0.009). Systolic blood pressure (SBP) and spherical equivalent were significant contributing factors to CRAE (SBP: p < 0.001; SE: p = 0.021). However, CRVE was not significantly predicted by CV risk factors or ocular parameters. SBP was the only one independent contributor to AVR (p = 0.018).Conclusions: In young adults, higher SBP was found to be related to narrower retinal arterioles, but not to retinal venules. Sex and other confounding CV or ocular factors had no effect on the relationship of SBP and retinal vessel calibre.

Initial Drift Correction and Spectral Calibration of MarSCoDe Laser-Induced Breakdown Spectroscopy on the Zhurong Rover

The Mars Surface Composition Detector (MarSCoDe) carried by the Zhurong rover of China’s Tianwen-1 mission uses Laser-Induced Breakdown Spectroscopy (LIBS) to detect and analyze the material composition on Martian surfaces. As one extraterrestrial remote LIBS system, it is necessary to adopt effective and reliable preprocessing methods to correct the spectral drift caused by the changes in environmental conditions, to ensure the analysis accuracy of LIBS scientific data. This paper focuses on the initial spectral drift correction and estimates the accuracy of on-board wavelength calibration on the LIBS calibration target measured by the MarSCoDe LIBS. There may be two cases during the instrument launch and landing, as well as the long-term operation: (a) the initial wavelength calibration relationship can still apply to the on-board LIBS measurement; and (b) the initial wavelength calibration relationship has been changed, and a new on-board calibration is needed to establish the current relationship. An approach of matching based on global iterative registration (MGR) is presented in respect to case (a). It is also compared with the approach of particle swarm optimization (PSO) for case (b). Furthermore, their accuracy is estimated with the comparison to the National Institute of Standards and Technology (NIST) database. The experimental results show that the proposed approach can effectively correct the drift of the on-board LIBS spectrum. The the root-mean-square error (RMSE) of the internal accord accuracy for three channels is 0.292, 0.223 and 0.247 pixels, respectively, compared with the corrected Ti-alloy spectrum and the NIST database, and the RMSE of the external accord accuracy is 0.232, 0.316 and 0.229 pixels, respectively, for other samples. The overall correction accuracy of the three channels is better than one-third of the sampling interval.

Assessing the predictive capability of the empirical Shale Gouge Ratio–buoyancy pressure calibration: implications for estimating CO 2 column heights

Abstract Current workflows for estimating the maximum height of sequestrated CO 2 trapped by fault-rock seal are based on an empirically derived predictive relationship between fault-zone shale content estimated using the Shale Gouge Ratio (SGR) algorithm and buoyancy pressure. The predictive capability of this relationship has been assessed using observed in-place column height data from 25 fault-bounded traps containing gas or oil only. Two-thirds of gas-only traps have an observed trapped column that is more than 67% of the maximum predicted column height. By contrast, only 14% of oil-only traps have an observed column height of more than 67% of the maximum predicted column height. The existing SGR–buoyancy pressure calibration relationship is more optimal for low density (<450 kg m −3 ) buoyant fluids but is less so for higher density fluids (>650 kg m −3 ) such as oil. A new SGR–buoyancy pressure relationship has been derived for oil-only data. Fault seal envelopes for oil-only data exhibit a ‘reclined’ trend which implies a limited increase in seal strength and hence column height, with increasing SGR. As sequestrated CO 2 is likely to have fluid properties (interfacial tension, wettability and density) similar to that of oil in the subsurface, an empirical calibration relationship based on oil-only data should be used as a first-order predictor for CO 2 column heights.

Toward a general calibration of the Swiss plate geophone system for fractional bedload transport

Abstract. Substantial uncertainties in bedload transport predictions in steep streams have encouraged intensive efforts towards the development of surrogate monitoring technologies. One such system, the Swiss plate geophone (SPG), has been deployed and calibrated in numerous steep channels, mainly in the Alps. Calibration relationships linking the signal recorded by the SPG system to the intensity and characteristics of transported bedload can vary substantially between different monitoring stations, likely due to site-specific factors such as flow velocity and bed roughness. Furthermore, recent flume experiments on the SPG system have shown that site-specific calibration relationships can be biased by elastic waves resulting from impacts occurring outside the plate boundaries. Motivated by these findings, we present a hybrid calibration procedure derived from flume experiments and an extensive dataset of 308 direct field measurements at four different SPG monitoring stations. Our main goal is to investigate the feasibility of a general, site-independent calibration procedure for inferring fractional bedload transport from the SPG signal. First, we use flume experiments to show that sediment size classes can be distinguished more accurately using a combination of vibrational frequency and amplitude information than by using amplitude information alone. Second, we apply this amplitude–frequency method to field measurements to derive general calibration coefficients for 10 different grain-size fractions. The amplitude–frequency method results in more homogeneous signal responses across all sites and significantly improves the accuracy of fractional sediment flux and grain-size estimates. We attribute the remaining site-to-site discrepancies to large differences in flow velocity and discuss further factors that may influence the accuracy of these bedload estimates.

A new measurement method for mixing and segregation of binary mixture by combining gas cutting-off method and ECVT

Binary mixture fluidization is an important operation type of fluidized bed. The regularity of mixing and segregation of binary mixture is the key to process research and development. In this paper, a new experimental method for the measurement of mixing and segregation of binary mixture is proposed by combining gas cutting-off method and Electrical Capacitance Volume Tomography (ECVT). While inheriting the advantage of high applicability of gas cutting-off method, this method can be of high spatial resolution with the application of ECVT. This combination can not only obtain detailed particle component distribution information, but also reduce the experimental labor intensity. Based on the measuring principle of ECVT and Maxwell Garnett mixing model, the calibration relationship between voxel value and particle mixing ratio was deduced. An experimental binary mixture system was employed to validate the calibration relationship. The result showed that the calculated calibration curve was in good agreement with the experimental calibration curve, which indicates the rationality and feasibility of the method. On this basis, mixing process of the same particle system was quantitatively characterized and analyzed at a given air flow rate. • A new measurement method for mixing and segregation of binary mixtures was developed. • High resolution of ECVT and high application of gas-cutting method were combined. • Measuring principle was mathematically derived for isotropic binary mixture. • Mixing process of experimental binary particle system was visually studied.

An improved model and field calibration technique for measuring liquid water content in unfrozen and frozen soils with dielectric probes

AbstractDielectric soil moisture probes can be used to obtain frequently logged field observations of volumetric water content, but because this is an indirect method, it is challenging to ensure that you have a suitable calibration relationship and parameters. Challenges are associated with (a) limitations in the probes’ ability to accurately measure the soil bulk dielectric constant and (b) limitations in obtaining reliable direct observations to calibrate the probe against, due to the spatial heterogeneity in the field. Furthermore, in soils that freeze, we do not have a robust approach to account for the effect of ice on the instrument. In this study, we propose a calibration relationship for all dielectric probes that is physically based, parsimonious, accounts for errors in the bulk dielectric constant, and quantifies the uncertainty in the liquid water content caused by the presence of ice. We show that our relationship has a better performance and more realistic parameter values than existing approaches. To calibrate a dielectric probe in the field, we show that it is necessary to account for spatial heterogeneity in samples taken for calibration. There is value in taking simultaneous measurements of the bulk dielectric constant (using the same dielectric probe as is being calibrated) and gravimetric samples for water content at a number of points in space. Taking too few samples is likely to be misinformative—we show that it is better to not calibrate the probe at all than to calibrate it with too few data points.

Calibration of polyvinylidene fluoride (PVDF) stress gauges under high-impact dynamic compression by machine learning

Calibration of stress gauges is of great importance for understanding the behaviors of materials under high dynamic impacts. However, commonly used calibration models have little transferability due to ignoring the influences of the gauge parameters. In this work, we propose a systematic approach that can generate effective and transferable calibration models including multiple independent variables by machine learning. Specifically, we conduct high-impact dynamic compression experiments using polyvinylidene fluoride (PVDF) stress gauges with two different thicknesses and varying remnant polarizations at shock levels from 0.3 to 10 GPa. To best characterize the comprehensive calibration relationship, we select a set of five features (combined by strain, remnant polarization, and film thickness) by feature engineering and use Lasso with the bagging ensemble as an algorithm to train the machine learning model. For comparison, we also propose semiempirical models that calibrate PVDF gauges effectively, but without including thickness and remnant polarization. Our results show that the machine learning model is more precise and more reasonable in physics. The predicted dependences of the calibration curves on remnant polarization and film thickness by the machine learning model are qualitatively consistent with the physics scenario. This work reveals the potential of machine learning methods to improve gauge calibration for better performance and transferability. The method used in this work is applicable to the calibration of any stress gauges with multiple variables.

FLUORESCENT DETECTION OF NITROBENZENE VAPORS VIA FLUOROPHORE-DOPED POLYSTYRENE MATERIALS

Integration of fluorescent substances into polymeric matrices can improve their sensory properties and photostability. In this work, fluorescent materials based on fluorophore-doped polystyrene were obtained and characterized as sensors towards the ecotoxicant nitrobenzene in gas phase. Melamine-formaldehyde foam has been proposed as a permeable substrate for the sensor material deposition applicable for gas-phase measurements. The effect on sensor properties of the porous material surface obtained via Breath Figure pore generation technique was investigated. Limits of detection and calibration relationships of obtained materials towards nitrobenzene were evaluated by materials exposure to low concentrations of nitrobenzene vapors. The sorption properties of polystyrene allow the retention of the quencher near the fluorophore, leading to improved detection limits compared with pure fluorophores. Obtaining a porous surface of the polymer material by the Breath Figure technique increases the scale of its fluorescence quenching by vapors. Detection limits (down to 0.45 ppm) and detectable concentration ranges (0.5 - 371.6 ppm) have been experimentally established. The relative standard deviations of the fluorescent signal of polymer materials do not exceed 13.3 % for a number of concentrations in the detectable range. The applicability of the calibration linear relationship of the logarithm of the fluorescent signal on the logarithm of the nitrobenzene vapor concentration is shown. Fluorescence signal measurements were performed using the original sensor element and the luminescence detector employing an array of fluorescent materials. The developed device is simple in application, portable, automated, and in combination with the used polymeric materials allows detection of nitrobenzene vapors in concentrations 2.5 times lower than the maximum permissible level.