Calibration Formula Research Articles

A wearable real-time particulate monitor demonstrates that soaking hay reduces dust exposure.

Affordable particulate matter (PM) monitors suitable for use on horses will facilitate the evaluation of PM mitigation methods and improve the management of equine asthma. Calibrate a real-time wearable PM monitor (Black Beauty [BB]) and compare the PM exposures of horses fed dry or soaked hay. Laboratory calibration; complete cross-over feed trial. Side-by-side sampling with BB monitors and tapered element oscillating microbalances (TEOMs) was performed under varying concentrations of PM from alfalfa hay. Linear regression was used to derive a calibration formula for each unit based on TEOM PM measurements. Precision was evaluated by calculating the coefficient of variation and pairwise correlation coefficients between three BB monitors. PM exposure was measured at the breathing zone of 10 horses for 8 h after they were fed dry or soaked hay. Repeated measures generalised linear models were constructed to determine the effect of hay treatment and measurement duration (initial 20-min vs. 8-h) upon exposure to PM with diameters smaller than or equal to 10 μm (PM10) and 2.5 μm (PM2.5). BB monitor PM2.5 and PM10 measurements were linearly correlated with TEOM data (coefficient of determination r2 > 0.85 and r2 > 0.90 respectively), but underestimated PM2.5 mass concentrations by a factor of 4 and PM10 concentrations by a factor of 44. Measures from the three BB monitors had a coefficient of variation <15% and pairwise r > 0.98. Feeding soaked hay significantly reduced average PM2.5 exposures (20-min: dry: 160 μg/m3, soaked: 53 μg/m3, p < 0.0001; 8-h: dry: 76 μg/m3, soaked: 31 μg/m3, p = 0.0008) and PM10 exposures (20-min: dry: 2829 μg/m3, soaked: 970 μg/m3, p < 0.0001; 8-h: dry: 1581 μg/m3, soaked: 488 μg/m3, p = 0.008). No health outcome measures were collected. With appropriate corrections, the BB monitor can be used to estimate horse PM exposure. While 20-min measurements yielded higher estimates of exposure than 8-h measurements, both intervals demonstrate that soaking hay reduces PM exposures by more than 50%.

Development and in situ application of actively heated fiber Bragg grating cable for soil water content measurement

The actively heated fiber-optic (AHFO) technology has emerged as a frontier and hotspot in soil water content measurement, offering advantages such as easy installation, large-scale distributed measurement capability, and resistance to electromagnetic interference. However, current AHFO water content sensors fail to simultaneously achieve high precision, applicability for deep soil, and automated real-time monitoring, thereby limiting their development and application. Therefore, this study introduces a novel actively heated fiber Bragg grating (AH-FBG) cable. Laboratory tests were conducted to assess the heating uniformity of the AH-FBG cable and to establish the temperature characteristic value (Tt) – soil water content (θ) calibration formula for water content measurement. Subsequently, AH-FBG cables were deployed for in situ soil water content monitoring in a test pit on the Loess Plateau. Through two-year monitoring data verified the accuracy of the AH-FBG cable and elucidated the spatiotemporal distribution of in situ loess water content. Laboratory results demonstrated superior heating uniformity of AH-FBG cable, with a Tt standard deviation of approximately 0.3 °C. In the field, the AH-FBG cable exhibited excellent performance in soil water content measurement, achieving a high accuracy of 0.023 cm3/cm3. Further analysis revealed that the θ fluctuation predominantly occurred within a 10 m depth from the soil surface, with an overall upward trend over the two-year monitoring period; the response of shallow θ to precipitation was significant but exhibited increasing hysteresis with depth; frequent precipitation significantly enhanced water infiltration depth. This study provides technical guidance for high-precision, quasi-distributed, automated and real-time water content measurement of deep soil.

Performance of Soil Moisture Sensors at Different Salinity Levels: Comparative Analysis and Calibration.

Soil dielectric sensors have been widely used to obtain real-time soil moisture data, which are important for water resource management. However, soluble salts in the soil significantly affect the accuracy of these sensor measurements. Therefore, it is crucial to select suitable soil dielectric sensors for soil moisture measurements at different salinity levels. Eight mainstream sensors (EC-5, 5TE, Teros12, Hydra-probe II, TDR315L, TDR315H, TDR305H, and CS655) were selected and tested at four different soil salinity levels (EC1:5 = 3.0, 1.5, 1.0, and 0.75 dS·m-1). The measured values using the factory calibration formulas were compared at six soil moisture levels. The results showed that the measured soil moisture values from various sensors exhibited varying degrees of overestimation, which increased with increasing salinity. Only EC-5 did not exhibit distortion at high-salinity levels, with the measured values showing a good linear trend compared to the standard values. Mutational distortion of the measured apparent dielectric permittivity occurred in TDR315L, TDR315H, Hydra-probe II, and 5TE at EC1:5 = 3.0 dS·m-1. Insensitive distortion of the measured apparent dielectric permittivity occurred in Teros12 and TDR305H at EC1:5 = 3.0 dS·m-1 as well as in Teros12, TDR305H, 5TE and Hydra-probe II at EC1:5 = 1.5 dS·m-1. All tested sensors performed reasonably well at EC1:5 ≤ 1.0 dS·m-1. Seven sensors (excluding CS655) were calibrated within the distortion threshold. The soil moisture accuracy using the calibrated formulas could reach ±0.02 cm3·cm-3. At EC1:5 ≤ 1.0 dS·m-1, most sensors in this study could be applied with the factory calibration formulas. TDR series, EC-5, 5TE and Teros12 were recommended after calibration for EC1:5 > 1.0 dS·m-1. For extremely high soil salinity levels, the TDR series and EC-5 may be the best choices.

An evaluation of sample size requirements for developing risk prediction models with binary outcomes

BackgroundRisk prediction models are routinely used to assist in clinical decision making. A small sample size for model development can compromise model performance when the model is applied to new patients. For binary outcomes, the calibration slope (CS) and the mean absolute prediction error (MAPE) are two key measures on which sample size calculations for the development of risk models have been based. CS quantifies the degree of model overfitting while MAPE assesses the accuracy of individual predictions.MethodsRecently, two formulae were proposed to calculate the sample size required, given anticipated features of the development data such as the outcome prevalence and c-statistic, to ensure that the expectation of the CS and MAPE (over repeated samples) in models fitted using MLE will meet prespecified target values. In this article, we use a simulation study to evaluate the performance of these formulae.ResultsWe found that both formulae work reasonably well when the anticipated model strength is not too high (c-statistic < 0.8), regardless of the outcome prevalence. However, for higher model strengths the CS formula underestimates the sample size substantially. For example, for c-statistic = 0.85 and 0.9, the sample size needed to be increased by at least 50% and 100%, respectively, to meet the target expected CS. On the other hand, the MAPE formula tends to overestimate the sample size for high model strengths. These conclusions were more pronounced for higher prevalence than for lower prevalence. Similar results were drawn when the outcome was time to event with censoring. Given these findings, we propose a simulation-based approach, implemented in the new R package ‘samplesizedev’, to correctly estimate the sample size even for high model strengths. The software can also calculate the variability in CS and MAPE, thus allowing for assessment of model stability.ConclusionsThe calibration and MAPE formulae suggest sample sizes that are generally appropriate for use when the model strength is not too high. However, they tend to be biased for higher model strengths, which are not uncommon in clinical risk prediction studies. On those occasions, our proposed adjustments to the sample size calculations will be relevant.

AGE ESTIMATION USING DIAPHYSEAL LONG BONE LENGTHS IN A NON-ADULT SKELETAL SAMPLE FROM GONUR DEPE, TURKMENISTAN

Introduction. The aim of this study is to provide group-specific regression equations for age estimation of immature human skeletal remains younger than 12 years of age from the diaphyseal length of the six long bones. Further, to compare inverse and classical calibration models for age estimation and the suitability of previously published regression methods for archaeological and present-day populations in relation to the analyzed sample. Materials and methods. The studied sample consists of 128 non-adult individuals from Gonur Depe – the major BMAC site in Turkmenistan (2300–1500 BCE). Regression formulae were obtained for each of the six long bones, separately for entire sample (0–12 years of age) and for two subsamples below and above 2 years of age. For each equation the coefficient of determination (R2) and F-statistics were calculated. Residuals were tested for normality of distribution, autocorrelation, homoscedasticity, and the equality of mean to zero (one-sample t-test). Comparison between inverse and classical calibration was provided using paired samples t-test. To assess the applicability of other regression formulae to the studied sample both the mean residuals (MR) and mean of the absolute value of the residuals (MAR) were calculated, as an estimate of bias and accuracy respectively. Results. All regression models showed a strong statistical significance and high R2 value. The slope coefficients of the regression lines of diaphyseal length upon age are greater for the upper limb bones both in the entire sample and two subsamples separately. The lower limb bones are characterized by lower growth rates. In contrast to the inverse calibration, for the classical model the mean standard errors (MSE) were smaller for the upper limb bones rather than for the lower limb bones. For the lower limb bones the standard error of the estimate (SE) was generally smaller in inverse formulae. Comparison of both models for the femur however shows their equal performance. For the exception of proposed and classical calibration formulae all inverse models for femur diaphyseal length show consistent differences from zero in relation to the studied sample. Discussion. The inverse and classical calibration models as a technique for age estimation using diaphyseal long bone lengths are both equally applicable in the studied sample. It is recommended to use the equations for the lower limb bones in the inverse model and for the upper limb bones in the classical model. The Gonur Depe population is characterized by relatively higher growth rates of the upper limb bones and distal limb segments relative to the proximal ones. Most of the previously published inverse calibration models are not recommended for uncritically use due to the high risk of obtaining biased estimates on samples that are different chronologically and/or territorially.

New Calibration Formula for Radar–Rainfall Relationships Analysis

New Calibration Formula for Radar–Rainfall Relationships Analysis

Exploring a New Physical Scenario of Virtual Water Molecules in the Application of Measuring Virtual Trees Using Computational Virtual Measurement

Our previous studies discussed the potential of measuring virtual trees using computational virtual measurement (CVM). CVM is a general methodology that employs observational techniques in lieu of mathematical processing. The advantage of CVM lies in its ability to circumvent mathematical assumptions of tree shapes at the algorithmic level. However, due to the current computational limitations of desktop computers, the previously developed CVM application, namely, virtual water displacement (VWD), could only act as a primary theoretical testimonial using an idealized point cloud of a tree. The key problem was that simulating a massive number of virtual water molecules (VMMs) consumed most of the computational resources. As a consequence, an unexpected empirical formula for volume calibration had to be applied to the output measurement results. Aiming to create a more realistic simulation of what occurs when water displacement is used to measure tree volume in the real world, in this study, we developed a new physical scenario for VWMs. This new scenario, namely, a flood area mechanism (FAM), employed footprints of VWMs instead of quantifying VWM counts. Under a FAM, the number of VMMs was reduced to a few from several thousands, making the empirical mathematical process (of the previously developed physical scenario of VWMs) unnecessary. For the same ideal point clouds as those used in our previous studies, the average volume overestimations were found to be 6.29% and 2.26% for three regular objects and two artificial stems, respectively. Consequently, we contend that FAM represents a closer approximation to actual water displacement methods for measuring tree volume in nature. Therefore, we anticipate that the VWD method will eventually utilize the complete tree point cloud with future advancements in computing power. It is necessary to develop methods such as VWD and more CVM applications for future applications starting now.

The discrepancy in timing between synchronous signals and visual stimulation should not be underestimated.

Response latency is a critical parameter in studying human behavior, representing the time interval between the onset of stimulus and the response. However, different time between devices can introduce errors. Serial port synchronization signal can mitigate this, but limited information is available regarding their accuracy. Optical signals offer another option, but the difference in the positioning of optical signals and visual stimuli can introduce errors, and there have been limited reports of error reduction. This study aims to investigate methods for reducing the time errors. We used the Psychtoolbox to generate visual stimuli and serial port synchronization signals to explore their accuracy. Subsequently, we proposed a calibration formula to minimize the error between optical signals and visual stimuli. The findings are as follows: Firstly, the serial port synchronization signal presenting precedes visual stimulation, with a smaller lead time observed at higher refresh rates. Secondly, the lead time increases as the stimulus position deviates to the right and downwards. In Linux and IOPort(), serial port synchronization signals exhibited greater accuracy. Considering the poor accuracy and the multiple influencing factors associated with serial port synchronization signals, it is recommended to use optical signals to complete time synchronization. The results indicate that under the darkening process, the time error is -0.23 ~ 0.08 ms (mean). This calibration formula can help measure the response latency accurately. This study provides valuable insights for optimizing experimental design and improving the accuracy of response latency. Although it only involves visual stimuli, the methods and results of this study can still serve as a reference.

Validity and Reproducibility of Food Group-Based Food Frequency Questionnaires in Assessing Sugar-Sweetened Beverage Consumption Habits among Chinese Middle-School Students.

Assessing the intake of sugar-sweetened beverages (SSBs) is crucial for reducing obesity; however, a simple but relatively accurate method for determining added sugar consumption among school adolescents is lacking. The aim of this study was to evaluate the reproducibility and validity of a food group-based food frequency questionnaire (FG-FFQ) for SSBs in assessing SSB consumption and added sugar among middle-school students. A total of 242 school students completed the FG-FFQs twice and four discontinuous 24-h dietary records (24HDR) over a three-month period. A weighted average approach was used to obtain the average sugar content in the sugary drink food group (FG). Correlation coefficient, weighted kappa statistic, misclassification analysis, and Bland-Altman plot were used to evaluate the validity and reproducibility of the FG-FFQ. Linear regression was utilized to obtain the calibration formulas. The average content of added sugar in sugary drink FG was 8.1 g/100 mL. SSB consumption frequency, consumption amount, and added sugar had correlation coefficients of 0.81, 0.87, and 0.87, respectively, in the validity analysis (p < 0.05). The majority of scatter plots were covered by 95% confidence intervals in the Bland-Altman bias analysis. The intra-class correlation coefficient of SSB consumption frequency and Spearman correlation coefficient of SSB consumption amount and added sugar were 0.74, 0.81, and 0.90, respectively, in the reproducibility analysis (p < 0.05). Results produced by the FG-FFQ calibration formula were more comparable to 24HDR. The FG-FFQ for SSB consumption showed acceptable validity and reproducibility, making it a viable instrument for epidemiological studies on sugary drinks in adolescents.

Thermoelastic Stress Analysis in the Presence of Biaxial Stresses in Titanium: Effect of the Mean Stress on Errors in Stress Evaluation

BackgroundThermoelastic Stress Analysis (TSA) is a contactless technique capable of estimating superficial stresses on components subjected to dynamic loads. Surface stresses can be obtained by means of calibration methods that require the assessment of the thermoelastic constants. However, these methods can lead to errors in stress evaluation in those materials where the effect of the mean stress on the thermoelastic signal cannot be neglected (e.g., titanium).ObjectiveThe aim is the development of an analytic formulation of error made in first stress invariant amplitude evaluation for a biaxial stress state, when neglecting mean stress effect.MethodsBy considering the general theory of thermoelastic stress analysis accounting for the mean stress effect, the formulation of the thermoelastic effect in the presence of a biaxial stress state was obtained. The results were compared to those obtained by a numerical simulation and the proposed formulation has been validated for titanium by means of experimental tests.ResultsFirstly, the new formulation of thermoelastic temperature variations accounting for mean stress effect in presence of a biaxial stress state was provided. Secondly, an error analysis provided an analytical formulation for the error made in case mean stress effect is neglected for different case studies.ConclusionsThe error in stress evaluation can be considered as the error originating from the use of an incorrect calibration formula (traditional one)”. The new analytical formulation accounting for the general theory of thermoelastic stress analysis allows to account for the mean stress on titanium in the presence of a uniaxial and biaxial stress states and to evaluate the error made in neglecting such a second order effect when using TSA.

Distributed Temperature Sensor Calibration Algorithm

The paper considers various calibrating algorithm approaches of a distributed fiber-optic temperature sensor in order to modify the two-point calibration algorithm and improve the accuracy of converting a reflectogram into a thermogram. As a modification, it is proposed to use an additional feature of the original signal based on its first derivative. A scheme for constructing a generalized heuristic calibration formula that takes into account multiple features of the reflectogram is proposed. The accuracy of the two-point and modified (three-point) algorithms was evaluated on thermostated regions of the optical line. It is shown that the modified calibration algorithm makes it possible to achieve greater accuracy compared to the two-point one. So, for the region thermostated at –50 °C, the standard deviation for the modified algorithm is 0.08 °C, for the two-point algorithm 0.26 °C.

Heat generation and transfer simulation of a high temperature heat pipe under induction heating based on a coupled model

High temperature heat pipes are highly efficient heat transfer devices, and induction heating is often utilized in their performance tests. However, issues exist in evaluating the equivalence between induction heating and surface heating encountered in typical application scenarios, and in quantifying the accurate input heat flux of induction heating. In order to identify the key influencing factors and investigate their effects on heat generation and transfer within high temperature heat pipes under induction heating, a finite element thermal-electrical coupled model is developed based on the pseudo wick thermal conductivity model and electromagnetic theory. The effects of frequency (10 kHz, 100 kHz, 300 kHz), loaded current (10 ∼ 890A), cooling coefficient (10 ∼ 250Wm-2K−1) and temperature (300 ∼ 1000 K) are investigated. Over 98% of the induction heat is found to be generated in the evaporator section, with a considerable proportion generated in the annular channel (38 ∼ 52%) and the capillary wick (23 ∼ 26%) at low frequency (10 kHz). The wall temperature of the evaporator section is slightly lower than the temperature of the annular flow channel or even the capillary wick at weak cooling boundary conditions (<130Wm-2K−1@10 kHz, <50Wm-2K−1@100 kHz, <30Wm-2K−1@300 kHz). Quantitative calibration formulas of induction heat are established in relation to frequency, current, and temperature via two sets of quadratic polynomial fitting. The results can be used as reference for design and evaluation of transient and steady-state tests of heat pipes under induction heating.

Correction: A confirmatory study of the calibration formula between liver iron concentration (LIC) and R2* values in thalassemia patients

Correction: A confirmatory study of the calibration formula between liver iron concentration (LIC) and R2* values in thalassemia patients

A confirmatory study of the calibration formula between liver iron concentration (LIC) and R2* values in thalassemia patients

A confirmatory study of the calibration formula between liver iron concentration (LIC) and R2* values in thalassemia patients

A Study of the Pulsation Properties of 57 Non-Blazhko Ab-type RR Lyrae Stars with Homogeneous Metallicities from the LAMOST–Kepler/K2 Survey

Homogeneous metallicities and continuous high-precision light curves play key roles in studying the pulsation properties of RR Lyrae stars. By cross matching LAMOST DR6 with the Kepler and K2 fields, we have determined seven and 50 non-Blazhko RRab stars, respectively, that have homogeneous metallicities determined from low-resolution spectra of the LAMOST–Kepler/K2 survey. The Fourier decomposition method is applied to the light curves of these stars provided by the Kepler space-based telescope to determine the fundamental pulsation periods and parameters. The calculated amplitude ratios of R 21, R 31 and the phase differences of ϕ 21, ϕ 31 are consistent with the parameters of RRab stars in both globular clusters and the Large Magellanic Cloud. We find a linear relationship between the phase differences ϕ 21 and ϕ 31, which is in good agreement with the results in the literature. As far as the amplitude, we find that the amplitude of primary frequency A 1 and the total amplitude A tot follow either a cubic or linear relationship. For the rise time, we do not find its relevance with the period of the fundamental pulsation mode P1, or A tot and ϕ 21. However, it might follow a linear relationship with R 31. Based on the homogeneous metallicities, we have derived a new calibration formula for the period–ϕ 31–[Fe/H] relation, which agrees well with previous studies.

Spatially adaptive calibrations of airbox PM2.5 data.

The Taiwan air quality monitoring network (TAQMN) and the AirBox network both monitor PM2.5 in Taiwan. The TAQMN, managed by Taiwan's Environmental Protection Administration (EPA), provides high-quality PM2.5 measurements at 77 monitoring stations. The AirBox network launched more recently consists of low-cost, small internet-of-things (IoT) microsensors (i.e., AirBoxes) at thousands of locations. While the AirBox network provides broad spatial coverage, its measurements are unreliable and require calibrations. However, applying a universal calibration procedure to all AirBoxes does not work well because the calibration line varies with local factors, including the chemical compositions of PM2.5 , which are not homogeneous in space. Therefore, different calibrations are needed at different locations to adapt to their local environments. Unfortunately, AirBoxes and EPA locations are misaligned, challenging the calibration task. In this paper, we propose a spatial model with spatially varying coefficients to account for the heterogeneity in the data. Our method gives spatially adaptive calibrations of AirBoxes and produces accurate PM2.5 concentration estimates with their error bars at any location, incorporating two types of measurements. In addition, the proposed method is robust to outliers, requires no colocated data, and provides calibration formulas for new AirBoxes once they are added to the network. We illustrate our approach using hourly PM2.5 data in 2020. After the calibration, the results show that the PM2.5 prediction improves by about 38%-68% in root-mean-squared prediction error. Once the calibration formulas are established, we can obtain reliable PM2.5 values even if we ignore EPAdata.

Remote Calibration Technology in Target RCS Time Domain Outfield Measurement

In this paper, a new method of remote calibration in time domain measurement of outfield RCS is proposed. Based on the basic principle of RCS time domain measurement and the characteristics of time domain system, the difference in time and frequency domain measurement is analyzed. The frequency domain remote calibration formula is extended to the time domain by time-frequency transform. Through the analysis of the time domain echo signal of the calibration body in the correction formula and the experimental verification of the calibration sphere echo signal, the influence of the calibration body size and measurement distance on the time domain echo signal and spectrum of the calibration body is given. The typical targets are measured by using the time domain system, and the results of time domain remote calibration, theoretical simulation, and frequency domain measurement are compared. The results show that the error between the time domain remote calibration results and the theoretical simulation results is not more than 1 dB at the −25 dB level. In the outfield measurement, this scheme can fully reflect the advantages of time domain measurement of wide frequency bands and low environmental requirements.

Calibration Method of Normal Critical Damping Ratio in Particle Discrete Element Rock Model

The calibration of dynamic mesoscopic parameters such as the normal critical damping ratio will directly affect the simulation results when wave velocity dynamic analysis is carried out on the particle discrete element rock model. This paper presents a fast calibration method for the normal critical damping ratio in the particle discrete element model. Firstly, the relationship between the normal critical damping ratio and the model energy attenuation rate is quantitatively analyzed based on the fundamental theory of discrete particle elements and energy conservation law. Then, based on the rock model with determined macroscopic mechanical parameters, the elastic longitudinal wave test is carried out to study the influence of the model energy attenuation rate with a normal critical damping ratio. The theoretical formula is modified according to the numerical results. Finally, the calibration formula of the normal critical damping ratio in the discrete particle element model is given. It is a new method to calibrate the normal critical damping ratio of the discrete particle model quickly and conveniently by using the theory of discrete particle elements and energy. It can provide a reference for constructing an accurate particle discrete element rock model.

Calibration Method of Normal Critical Damping Ratio in Particle Discrete Element Rock Model

The calibration of dynamic mesoscopic parameters such as the normal critical damping ratio will directly affect the simulation results when wave velocity dynamic analysis is carried out on the particle discrete element rock model. This paper presents a fast calibration method for the normal critical damping ratio in the particle discrete element model. Firstly, the relationship between the normal critical damping ratio and the model energy attenuation rate is quantitatively analyzed based on the fundamental theory of discrete particle elements and energy conservation law. Then, based on the rock model with determined macroscopic mechanical parameters, the elastic longitudinal wave test is carried out to study the influence of the model energy attenuation rate with a normal critical damping ratio. The theoretical formula is modified according to the numerical results. Finally, the calibration formula of the normal critical damping ratio in the discrete particle element model is given. It is a new method to calibrate the normal critical damping ratio of the discrete particle model quickly and conveniently by using the theory of discrete particle elements and energy. It can provide a reference for constructing an accurate particle discrete element rock model.

La2Zr2O7:Pr3+ nanoparticles for luminescence thermometry based on a single parameter over a wide temperature range of 620 K

Luminescence thermometry based on the variation of the fluorescence intensity ratio (FIR) of rare-earth materials has become fascinating owing to their applicability in chemically and electromagnetically harsh environments. Relevant to their practical applicability, a wide temperature sensing range is urgently required for luminescent thermometric materials besides possessing a high relative sensitivity. Herein, we have demonstrated that pyrochlore La 2 Zr 2 O 7 :Pr 3+ (LZOP) nanoparticles (NPs) can serve as a promising optical temperature sensing material over a wide temperature range of 620 K. Specifically, we have taken advantage of the intervalence charge transfer state (IVCT) of Pr 3+ doping ion for luminescence temperature sensing and confirmed excellent optical thermometric performance from the LZOP NPs in a temperature sensing range of 85–705 K. The thermal sensing here could be measured by exploiting one thermometric parameter, i.e. the FIR between 1 D 2 → 3 H 4 and 3 P 0 → 3 H 4 transitions of Pr 3+ , and thus we only need to use one calibration formula for the whole temperature range. A maximum relative sensitivity of> 0.4%·K −1 from 165 to 205 K and a low temperature uncertainty of 1.21 K at 185 K is obtained. Based on the proposed configurational coordinate diagrams, A high-lying IVCT state was demonstrated to be the cause for slow thermal quenching at high temperatures, which broadened the working range of our thermometric sensing materials. This work provides a useful inspiration for exploring appropriate host materials with slow thermal-quenching channels to develop optical thermometric materials over a wide temperature sensing range. • Synthesized La 2 Zr 2 O 7 :0.1%Pr 3+ (LZOP) NPs by a low temperature molten salt method. • Demonstrated an excitation band at ~256 nm from the 4f-5d and IVCT transitions. • Confirmed their wide range thermal sensing potential using a single parameter.