Reliable Method For Estimation Research Articles

Simultaneous Estimation of Lamivudine, Didanosine and Efavirenz in Bulk and their Formulation by UPLC

Objectives: To develop a simple, rapid, reliable and precise RP-UPLC method for the simultaneous estimation of lamivudine, didanosine and efavirenz in bulk and its tablet dosage forms. Materials and Methods: The chromatographic separation was achieved by using Zorbax SB Cyano (150x4.6mm ID) 1.7μm column, isocratic mobile phase consists; Ammonium acetate Buffer pH 4.5: Acetonitrile (55:45) %v/v with a flow rate of 1.0 ml/min. The detection was carried out at 274 nm. The current method was validated according to the ICH guidelines for accuracy, precision, linearity, specificity, robustness and ruggedness. Results: The retention times obtained for lamivudine, didanosine and efavirenz were 2.584, 4.228 and 5.206 min respectively. The calibration curves of peak area versus concentration, were linear from 15-45μg/mL, 30-90μg/ mL and 20-60μg/mL for lamivudine, didanosine and efavirenz and had regression coefficient (R2) 0.999. Limit of detection were found to be 1.7, 3.3, 3.8 μg/ml and limit of quantification were found to be 5.1, 6.7, 11.5 μg/ ml respectively for lamivudine, didanosine and efavirenz. The % assay of the marketed dosage form was found to be 100.2, 100.4 and 100.6 for lamivudine, didanosine and efavirenz. Conclusion: The experimental study results revealed the suitability of proposed method that can be used for simultaneous estimation of lamivudine, didanosine and efavirenz in bulk and their pharmaceutical formulations for routine quality control analysis.

Re-examination of Critical-angle Reflectometry Used in Ultrasonic Non-destructive Testing For Estimating Material Anisotropy

Seismic critical-angle reflectometry (SCR) can hardly be regarded as a reliable standalone method for anisotropic parameter estimation of strata in seismic exploration, but ultrasound critical-angle reflectometry (UCR) is useful in ultrasonic non-destructive testing (NDT) and medical ultrasound for the estimation of anisotropy in media. Therefore, there is a conflict between using critical-angle reflectometry (CR) in seismic exploration and applications of ultrasound. This study aims to find the reason as to why CR is useful in ultrasonic NDT and medical ultrasound but unreliable in seismic exploration for anisotropy estimation of media. The results of the study show that the critical angle can be accurately determined from the maximum amplitude of the reflections for a plane wave as used in ultrasonic NDT and medical ultrasound and thus the anisotropy of the medium can be successfully estimated by UCR. However, for the spherical waves used in seismic exploration, the maximum amplitude of the reflections is shifted towards post-critical offsets and the shift of the maximum amplitude relative to the critical point depends not only on the frequency and model parameters but also the azimuth. Therefore, SCR cannot currently be regarded as a reliable standalone method for the anisotropic parameter estimation of strata.

Relationship between Critical Gap and Certain Geometrical Parameters in Roundabouts

Gap-acceptance method is one of the classical methods used to analyze capacity of roundabouts. Critical gap has a privileged role in this approach. Different driver behavior and local rules of traffic has a key role in implementing it in the local standard for capacity calculation in each country. Therefore, a reliable method for estimation of critical gap at a certain location can be of great importance. This paper presents the first steps of an experimental investigation and analysis on whether it is possible to find correlation between video-based gap acceptance data and certain design parameters of roundabouts in Hungary. Ten single lane roundabouts of different size were recorded for hours in different locations in and around Budapest to assess gap acceptance data and relate it to certain design parameters like diameter, distance of neighboring entries, entry width, width of splitter island, number of entries over time, and entry angle – or any combination of those. Using only a linear approach, strong positive correlation was found between measured critical gap and distance between legs. There is correlation (not so strong however) between critical gap and (approach) entry width as well as splitter island width, and enough data were examined to say that there is no correlation between central island diameter and critical gap.

Wound age estimation based on next-generation sequencing: Fitting the optimal index system using machine learning

Accurate estimation of the wound age is critical in investigating intentional injury cases. Establishing objective and reliable biological indicators to estimate wound age is still a significant challenge in forensic medicine. Therefore, exploring an objective, flexible, and reliable index system selection method for wound age estimation based on next-generation sequencing gene expression profiles is necessary. We randomly divided 63 Sprague-Dawley rats into a control group, seven experimental groups (n = 7 per group), and an external validation group. After rats in the experimental and external validation groups suffered contusions, we sacrificed them at 4, 8, 12, 16, 20, 24, and 48 h after contusion, respectively. We selected 54 genes with the most significant changes between adjacent time points after contusion and defined set A. The Hub genes with time-related expression patterns were set B, C, and D through next-generation sequencing and bioinformatics analysis. Four different machine learning classification algorithms, including logistic regression, support vector machine, multi-layer perceptron, and random forest were used to compare and verify the efficiency of four index systems to estimate the wound age. The best combination for wound age estimation is the Genes ascribed to set A combined with the random forest classification algorithm. The accuracy of external verification was 85.71%. Only one rat was incorrectly classified (4 h post-injury incorrectly classified as 8 h). This study demonstrated the potential advantage of the index system selection based on next-generation sequencing and bioinformatics analysis for wound age estimation.

First application of the Integrated Karst Aquifer Vulnerability (IKAV) method – potential and actual vulnerability in Yucatán, Mexico

Abstract. Groundwater vulnerability maps are important decision support tools for water resource protection against pollution and helpful in minimizing environmental damage. However, these tools carry a high subjectivity along the multiple steps taken for the development of such maps. Additionally, the theoretical model on which they are based does not consider other important parameters, such as pollutant concentration or pollutant residence time in a given section of the aquifer, solely focusing on the theoretical travel time of a pollutant particle from a release point towards a target. In this work, an integrated methodology for the evaluation of potential (intrinsic) and actual vulnerability is presented. This integrated method, named Integrated Karst Aquifer Vulnerability (IKAV), was developed after the analysis of several study cases around the world and the application of multiple intrinsic groundwater vulnerability methods in a selected study area. Also, a solute transport model served as the basis to define additional parameters for vulnerability analysis for areas severely affected by anthropogenic practices. However, the focus of the transport model must not be mistaken to be hazards and risk mapping. A defined workflow and several criteria for parameters and attributes selection, rating and weighting, and vulnerability classification are presented here. The first application of the IKAV method was carried out in the Yucatán karst, demonstrating to be a reliable method for vulnerability estimation. Results demonstrated the scope of the IKAV method in highlighting important regional conditions, minimizing the subjectivity, and expanding the analysis of vulnerability.

Critical Gap in Roundabouts – A Short Comparison of Estimation Methods

Gap-acceptance method is one of the classical methods used to analyze the capacity of roundabouts. Critical gap has a privileged role in this approach. Different driver behavior and local rules of traffic have key role in implementing gap-acceptance method into the local standard for capacity calculation in each country. Therefore, a reliable method for estimation of critical gap at a certain location can be of great importance. This paper presents an experimental investigation and analysis on whether it is possible to find differences between estimating critical gap using video-based gap acceptance data of roundabouts in Hungary. Three single lane roundabouts of different size were recorded for hours in different locations in Budapest and Érd to assess gap acceptance data. Three different methods or models were used to estimate critical gap and no significant differences were found between their results.

Reliability Assessment Method Based on Condition Information by Using Improved Proportional Covariate Model

If sufficient historical failure life data exist, the failure distribution of the system can be estimated to identify the system initial hazard function. The conventional proportional covariate model (PCM) can reveal the dynamic relationship between the response covariates and the system hazard rate. The system hazard rate function can be constantly updated by the response covariates through the basic covariate function (BCF). Under the circumstances of sparse or zero failure data, the key point of the PCM reliability assessment method is to determine the proportional factor between covariates and the hazard rate for getting BCF. Being devoid of experiments or abundant experience of the experts, it is very hard to determine the proportional factor accurately. In this paper, an improved PCM (IPCM) is put forward based on the logistic regression model (LRM). The salient features reflecting the equipment degradation process are extracted from the existing monitoring signals, which are considered as the input of the LRM. The equipment state data defined by the failure threshold are considered as the output of the LRM. The initial reliability can be first estimated by LRM. Combined with the responding covariates, the initial hazard function can be calculated. Then, it can be incorporated into conventional PCM to implement the reliability estimation process on other equipment. The conventional PCM and the IPCM methods are respectively applied to aero-engine rotor bearing reliability assessment. The comparative results show that the assessing accuracy of IPCM is superior to the conventional PCM for small failure sample. It provides a new method for reliability estimation under sparse or zero failure data conditions.

The application of the distributed-order time fractional Bloch model to magnetic resonance imaging

It is now well known that the magnetic resonance imaging (MRI) signal decay deviates from the classical mono-exponential relaxation. This deviation is referred to in the literature as anomalous relaxation. The modelling of this anomalous relaxation can provide a better understanding of MRI magnetization. The purpose of this work is to investigate the utility of the distributed-order time fractional Bloch equations to describe anomalous relaxation processes in human brain MRI data. Two choices of continuous distribution weight functions, which are parameterised by their mean μ and standard deviation σ, are studied to investigate their impact on the model solution behaviour. An implicit numerical method implemented on a graded mesh is proposed to solve the model and the stability and convergence analysis are presented. We also derive semi-analytical solutions of the fully coupled Bloch equations using the Laplace transform technique to assess the accuracy of the numerical scheme. Furthermore, three different voxel models of continuous distribution weight functions, namely a single continuous probability distribution (model 1), two distinct continuous probability distributions (model 2) and a mixture of two continuous probability distributions (model 3), are applied to the in vivo human brain MRI data, and a feasible and reliable parameter estimation method based on a modified hybrid Nelder-Mead simplex search and particle swarm optimization is presented to perform the voxel-level temporal fitting of the MRI data. The application of these distributed-order time fractional Bloch models highlights the validity of the proposed models, and based on the mean square error we conclude that models 2 and 3 might be more suitable than model 1 to characterize anomalous relaxation processes in human brain MRI data.

RP-HPLC method development and validation for the simultaneous estimation of dolutegravir, emtricitabine, and tenofovir alafenamide in tablet dosage form

Antiretroviral combination therapy regimens comprising of a nucleoside reverse transcriptase inhibitor (Emtricitabine, EMC), integrase inhibitor (Dolutegravir, DTG), and nucleotide reverse transcriptase inhibitor (Tenofovir Alafenamide, TAF) are frequently prescribed for HIV patients. The objective of this research was to establish and validate a precise and reliable method for the simultaneous estimation of DTG, EMC, and TAF, respectively in a marketed tablet dosage form using RP-HPLC system. RP-HPLC (Jasco) method was developed using Qualisil-5 BDS C18 column (250 mm × 4 mm, 5 μm). The mobile phase consists of acetonitrile: orthophosphoric acid (0.1%) adjusted in water pH 4.7 with triethylamine in the composition of 43:57 v/v at a flow rate of 1.2 mL/min using UV detection at 271 nm at ambient column temperature, keeping the injection volume 20 μL. The retention times of DTG, EMC, and TAF were found to be 8.321 mins, 2.210 mins, and 4.089 mins, respectively. All the criteria for the validation (linearity, accuracy, precision, and robustness) were observed to be within the acceptation range. The described method was linear over a concentration range of 2-12 μg/mL, 8-48 μg/mL, and 1-6 μg/mL for the assay of DTG, EMC, and TAF, respectively with r2 values of 0.999 in each case. High recovery of ~99.5% was observed in all cases with a % RSD of <2.This method was successfully developed to estimate the concentration of DTG, EMC, and TAF in tablet dosage form simultaneously owing to high precision, reproducibility, and accuracy attributes.. Keywords: RP-HPLC, Dolutegravir, Emtricitabine, Tenofovir Alafenamide, Simultaneous estimation, Validation.

EVALUATION OF ANTEGONIAL ANGLE, ANTEGONIAL DEPTH AND GONIAL ANGLE IN SEX PREDICTION IN THE TURKISH PEDIATRIC POPULATION OF THE EASTERN MEDITERRANEAN REGION

AIM: In this study, it was examined whether antegonial angle (AGA), antegonial depth (AGD), and gonial angle (GA) are associated with sex in a Turkish pediatric sample to be able to determine a reliable method for sex estimation in children. METHODS: The study was retrospectively carried out on panoramic radiographs previously taken for children’s dental treatments for different reasons. An oral and maxillofacial radiologist measured AGA, AGD, and GA on the right and left sides on panoramic radiographs, and their mean values were calculated. RESULTS: The mean age of 197 children was 11.5±1.28 years. The results revealed that AGA and AGD significantly differed between the children by sex. However, it was not the case for GA by sex. CONCLUSION: Overall, it was concluded that AGA and AGD can be used to estimate sex in the Turkish pediatric population from the Eastern Mediterranean region; nevertheless, GA is not reliable.

Reliability Analysis with Wiener-Transmuted Truncated Normal Degradation Model for Linear and Non-Negative Degradation Data

The degradation rates of many engineering systems are always positive in practical applications. In some cases, the degradation process is approximately linear, such as train wheel wear degradation and an increase in the operating current of laser devices. In this paper we introduce a degradation modeling and reliability estimation method based on the Wiener process with a transmuted-truncated normal distribution (TTND). The TTND is employed to characterize unit-to-unit variability due to its flexibility in capturing symmetry and the asymmetrical behavior of the drift variable of the Wiener process. A Wiener process with TTND is applied to model the degradation processes of the deteriorating systems in two cases. In the first case, we assume that the degradation process is unaffected by measurement uncertainties, whereas in the second case, the measurement uncertainties are considered. The exact and explicit expressions of PDFs and the reliability functions are derived based on the concept of first hitting time. The Gibbs sampling technique and the Metropolis–Hastings algorithm are employed to obtain the Bayesian estimates of the model’s parameters. The efficiency and the feasibility of the presented approach are demonstrated through numerical examples, with Monte Carlo simulation and a practical application with laser degradation data. Furthermore, deviance information criteria (DIC) are used to compare the proposed model and some existing models. The result indicated that the proposed approach provided better reliability estimation results.

Simultaneous Method Development and Validation of Anastrozole Along with Piperine: Degradation Studies and Degradants Characterization Using LC-QTOF-ESI-MS Along with In-silico ADMET Predictions.

Anastrozole (ATZ) is a selective non-steroidal inhibitor widely used for the treatment of breast cancer in post-menopausal women. ATZ exerts its biological activity by inhibiting the enzyme aromatase, which is responsible for converting androgens to estrogens. Piperine (PIP), a natural alkaloid and the main component of black pepper, is used as a bioenhancer and for combating a variety of health issues ranging from upset stomach to dental problems. ATZ has been reported to have poor water solubility and less bioavailability. The novel combination of ATZ and PIP was proposed to enhance the bioavailability of both the compounds. However, there are no reported studies on the simultaneous estimation of ATZ and PIP as well as stability studies to explore their potential interactions and degradation profiling. A simple, accurate, precise, robust, sensitive, reliable, and economic analytical method for the simultaneous estimation of ATZ and PIP was developed using acetonitrile and water (60:40) as the mobile phase. Forced degradation studies and characterization of degradants were performed, and degradants were identified for molecular weight using LC-QTOF-ESI-MS; the structures of degradants were confirmed with mass accuracy measurements. The mechanism of each degradant has also been described in more detail in the manuscript. A total of fourteen degradants were characterized and reported for their good human oral absorption. A precise, robust, accurate, cheap, and sensitive RP-HPLC-DAD simultaneous method for the estimation of ATZ and PIP has been developed. From the future point of view, there is huge scope to conduct pharmacological, pharmacodynamic, and drug-herb interaction studies based on this fruitful outcome. All the degradants may be screened against MDR-resistant breast cancer in the future to check their potential as a drug target.

New White Method of Parameters and Reliability Estimation for Transmuted Power Function Distribution

In this paper, an estimate has been made for parameters and the reliability function for Transmuted power function (TPF) distribution through using some estimation methods as proposed new technique for white, percentile, least square, weighted least square and modification moment methods. A simulation was used to generate random data that follow the (TPF) distribution on three experiments (E1 , E2 , E3) of the real values of the parameters, and with sample size (n=10,25,50 and 100) and iteration samples (N=1000), and taking reliability times (0< t < 0) . Comparisons have been made between the obtained results from the estimators using mean square error (MSE). The results showed the percentile estimator is the best in (E1, E2) but modification moment is the best in (E3) .

The Relation Between Photoconductivity Threshold and Open-Circuit Voltage in Organic Solar Cells

Abstract Most of the solar cell parameters (short-circuit current, fill factor, power conversion efficiency) can only be determined by creating and measuring the solar cell. However, there is an empirical relation that links energy level values of the materials in the active layer to an open-circuit voltage (Uoc) of the solar cell. Due to a variety of possible methods used to determine energy level values and the dispersion of obtained results, this estimate is not always correct. Even if correct energy level values are obtained for separate materials, energy level shift takes place at the interfaces when two materials are mixed. That is why a simple and reliable experimental method for Uoc estimation is required. Usually, photoconductivity is used to obtain the energy gap between molecule ionization energy and electron affinity of a single material. When two materials are mixed, direct charge transfer from donor to acceptor molecule can be observed. The threshold energy (ECT) shows the real difference between donor molecule ionization energy and acceptor molecule electron affinity. This difference should correspond to the Uoc. The present study makes the comparison between the open-circuit voltage estimated from material energy level values, the obtained ECT values for various donor:acceptor systems, and the real Uoc obtained from solar cell measurements. Strong correlation between ECT and Uoc is obtained and the photoconductivity measurements can be used in the estimation of Uoc.

A reliable estimation method for mining lithium-ion battery

Power battery SOC (state of charge, SOC) is one of the important decision-making factors of energy management. Accurate estimation plays an important role in optimizing vehicle energy management and improving the utilization of power battery energy. The key to accurate estimation of SOC is to determine circuit model parameters and estimation methods. The research object of this article is lithium manganese oxide battery for mining (LiMn2O4). The experiments of multiplying power, temperature and HPPC (hybrid pulse power characteristic, HPPC) are carried out. A self-tuning calculation method of dynamic system is proposed, and the dynamic self-tuning model based on second-order RC is established. At the same time, in view of the shortcoming that the UKF (Unscented Kalman Filter, UKF) algorithm cannot estimate the noise in real time, In order to improve the accuracy of battery SOC estimation, an adaptive square root unscented Kalman filter (ASR-UKF) algorithm is proposed, which can make the noise statistical characteristics follow the estimation results for adaptive adjustment. Finally, the constant current and dynamic conditions are tested. The results show that the maximum change rate of model parameters with magnification is 76%, and the maximum change rate with temperature is 73.7%. The analysis of dynamic characteristics is a key factor to improve the accuracy of SOC estimation; ASR-UKF Compared with the UKF algorithm, the error is reduced by 78% under constant current conditions and 85.7% under dynamic conditions. The reliability and real-time performance of the algorithm can be obtained by comparing the simulation data with the actual data. The conclusions of this paper can be used as a theoretical basis, which can be used for model analysis of lithium batteries for mining and estimation of internal state variables.

Relative Estimation Method of DOV Based on Double-Alignment of SINS

Deflection of the vertical (DOV) has become a significant error source in inertial navigation systems (INS) and meantime widely used in geodesy, exploration, geoid refinement et.al. Hence, the efficient and reliable method for DOV estimation is crucial for those fields. In this paper, an ingenious and efficient method, the relative estimation means based on double-alignment (RE-DA), is proposed, which mainly includes attitude tracking of normal and orientation for plumb line two processes. Firstly, the influence mechanism of DOV in initial alignment based on the inertial method was briefly introduced and the conclusion was clarified that the alignment result, attitude matrix, was with respect to the plumb line. Moreover, the method for attitude tracking of normal based on the strapdown inertial navigation system and odometer integrated navigation (SINS/OD) using the Kalman filter was investigated. Finally, the process of the pro-posed RE-DA method was specifically introduced. In verifying the pro-posed method, several repeated land-vehicle experiments were conducted, where the statistical results show that the root means square (RMS) of the estimation values are 0.73ʺ and 0.69ʺ respectively, which provides a novel means for DOV high-efficient estimation.

Comparison of artificial neural network with compatible biomass model for predicting aboveground biomass of individual tree

Forest biomass is an important index in forest development planning and forest resource monitoring. In order to provide a more efficient and low-biased method for estimating individual tree biomass, we introduced artificial neural network here. We used the data of aboveground biomass of 101 Larix olgensis trees harvested from the Dongzhelenghe Forest Farm in Heilongjiang Province to develop four aggregation model systems (AMS), based on different combination of the variables (diameter at breast height, tree height, crown width). The weighted functions were used to eliminate heteroscedasticity. Then, we trained artificial neural network (ANN) biomass model based on the optimal combination. The models were tested by the leave-one-out cross-validation method to compare the accuracy of the two biomass estimation methods. The results showed that biomass model based on only one variable, diameter at breast height, could accurately estimate the biomass of L. olgensis. Adding two indices, tree height and crown width, could improve the fitting performance of models, with AMS4 performing the best among the four addictive model systems. The biomass models developed by the two methods both could estimate biomass at tree level accurately, with the coefficient of determination (R2) of each component was higher than 0.87. Compared with the AMS4, R2 of leaf biomass model was about 0.05 higher, and that of other organs were also about 0.01 higher in artificial neural network model system. In addition, the root mean square error (RMSE) and other indicators were also significantly smaller. For example, the RMSE of tree stem and aboveground biomass were smaller by 2.135 kg and 3.908 kg, respectively. The model's validation statistics mean relative error (MRE) performed better. In general, ANN was a flexible and reliable biomass estimation method, which was worthy consideration when predicting tree component biomass or aboveground biomass.

Model-free analysis of molecular orientation in amorphous organic semiconductor films for understanding its formation dynamics: Methods and systematic investigation

To achieve high-performance organic light-emitting diodes (OLEDs), various amorphous organic semiconductor materials were developed, and the higher-order structure of their films and their formation dynamics were investigated. In particular, their molecular orientations were widely analyzed because it significantly affects optical and electrical properties of the OLEDs. However, conventional methods of the analysis of the orientation order parameter ( S ) need the construction of an anisotropic optical model, which brings a certain degree of analytical error and thus makes it difficult to assess the slight changes in S values arising from differences in experimental conditions. In this study, we present a simple model-free analytical method to estimate S values, named "QACIOS", that avoids the significant analytical errors and applies to various OLED materials, including materials that easily crystallize. In applying the method to UV/visible and IR spectral regions, the S values of electronic and vibrational transition dipole moments in the films can be simply estimated. The orientations of functional groups in single-layer and multilayer samples are obtainable separately, and in situ measurements are also demonstrated. Furthermore, we present a systematic analysis of the dependence of S on experimental conditions during sample fabrication such as deposition rate, substrate temperature, and substrate surface. From this analysis, the difference in formation dynamics of the molecular orientation of two structural isomers of OLED materials is quantitatively clarified, further demonstrating the usefulness of the method. A model-free simple analytical method by quantitative absorbance comparison with an isotropically oriented standard (QACIOS) is applied to systematic investigation of orientations of long molecular axis and functional groups in amorphous organic semiconductor films and their formation dynamics. • A model-free simple analytical method for reliable estimation of orientation order parameter is proposed and applied to many kinds of amorphous OLED materials. • Orientation analysis of functional groups in single-layer and multilayer samples are performed. • The difference in formation dynamics of molecular orientation of two OLED isomers is clarified quantitatively. • The method can be a commonly-used standard method for orientation analysis of OLED films.

Estimation of state-of-power capability for lithium-ion battery considering limiting conditions recalibration

ABSTRACT As one of the most significant deciding factors for energy management systems (EMSs) and battery management systems (BMSs) in electrified vehicles, battery state-of-power (SOP) estimation is an area of interest in battery research. Battery model parameters change obviously under the limiting working condition of SOP, and the available maximum current and state-of-charge (SOC) have to be updated for accurate SOP estimation. This paper tries to contribute to the existing literature as follows: Based on Thevenin model, recursive least-square (RLS) and H-infinity filter algorithm are adopted for parameter identification and SOC estimation for a recalibration purpose to improve the prediction of battery SOP under variable degradation. Multi-constraints are firstly adopted to calculate the limiting current, and the response function of capacity loss-temperature-discharge rate is brought back to correct the actual capacity at this current for the revised limiting current with consideration of weight distribution ratio. Finally, the experiment verifies that the final maximum charging-discharging current modifies the initial calculation value by 5% and 4%, and realizes the more accurate online SOP estimation. This method provides a more accurate and reliable SOP estimation method for electric vehicles.

Biochar stability scores from analytical pyrolysis (Py-GC-MS)

The long-term stability of biochar in soil is key for carbon capture and storage and soil amelioration. Yet, its assessment is hampered by the long time-horizons needed to actually probe biochar’s stability. Therefore, quick and reliable estimation methods are sought. Analytical pyrolysis (Py-GC-MS) offers a quick tool to predict biochar’s stability in soil, if adequate and validated metrics can be extracted from it. This work derives and validates stability scores from biochar pyrograms and advanced data analysis. The stability scores were benchmarked by comparison with other stability metrics (Edinburgh stability tool, fixed carbon content and atomic H/C ratio). Calibration of the stability scores with these stability metrics had an R2 between 0.61 and 0.95; validation resulted in R2 between 0.59 and 0.72. Overall, this work illustrates how Py-GC-MS can lead to simple and adequate predictors of biochar stability.