Soil and Plant Nutrient Analysis with a Portable XRF Probe Using a Single Calibration

A portable X-ray fluorescence probe (pXRF) is a tool that is used to measure many elements quickly and efficiently in various samples, without any pretreatment. However, each type of sample generally requires different calibrations to be accurate. To overcome this, our work evaluated the efficacy of determining several elements in forage plant samples using the ‘Soil Nutrient and Metal’ calibration in a commercially available pXRF probe, envisioning that a single calibration can be used to measure samples of different matrixes. For this, the net intensity of the pXRF probe was determined in place of the concentration values that are obtained directly from measurements. Elemental concentrations (P, K, Ca, Mg, S, Cu, Fe, Zn, and Mn) from forage plant samples, collected across Oklahoma, US, were assessed in a representative number of ‘modeling’ and ‘validation’ (independent dataset) samples. Linear regression (LR) associated with the d-index, polynomial regression (PR), and power regression (PwR) were tested for predictions, producing many statistical parameters associated with the models that were used for comparison goals. The pXRF elemental data provided highly reliable predictions of K, S, Zn, and Mn regardless of the regression model. Although all models can be reliable in prediction of Ca and Fe concentrations, the PwR provided better root mean square error (RMSE) values. The predictions of Mg concentrations were less reliable, although highly significant; however, the P and Cu predictions were not acceptable. Our work successfully showed that, once established, a single calibration curve that covers a wide range of concentrations of several elements in soils and plant tissues enables both soil and plant samples to be analyzed. This suggests that manufacturers can develop a new calibration model for a commercially available pXRF probe that covers a wide variety of heterogeneous samples.

Development of a Universal Measurement Process Framework

Calibration software has largely been developed with a direct measurement comparison method at the forefront. While adequate for many routine calibration processes, over time this approach becomes insufficient for more complex calibrations and often leads to the creation of special tests, add-ons, and various types of workarounds which are neither ideal nor sustainable over the long term. In some cases, these inadequacies initiate the development of a completely new and separate calibration software designed to specifically address a single calibration discipline or measurement problem. This paper discusses a complete and universal measurement process framework which is not only capable of accommodating routine and complex calibration scenarios alike, but also allows the use of various comparisons such as direct, indirect, ratio, differential, transfer, and substitution measurement comparison techniques. Additionally, the framework generates a comprehensive set of records to include; all original observations, calculations, corrections, conversions, environmental factors, and measurement results, allowing for step-by-step auditing of every measurement performed. Although primarily intended for use within calibration software which can facilitate automated, semi-automated, and manual calibrations - this approach may also be utilized entirely outside of software in any calibration scenario

EMG-informed neuromusculoskeletal models accurately predict knee loading measured using instrumented implants

<p>We investigated three different methods for simulating neuromusculoskeletal (NMS) control to generate estimates of knee joint loading which were compared to in-vivo measured loads. The major contributions of this work to the literature are in generalizing EMG-informed and probabilistic methods for modelling NMS control.</p> <p>A single calibration function for EMG-informed NMS modelling was identified which accurately estimated knee loads for multiple people across multiple trials. Using a stochastic approach to NMS modelling, we investigated the range of possible solutions for knee joint loading during walking, showing the method's generalizability and capability to generate solutions which encompassed the measured knee loads. Through this stochastic approach, we were able to show that a single degree of freedom planar knee is suited to estimating total knee loading, but is insufficient for estimating the directional components of load.</p> <p> </p>

EMG-informed neuromusculoskeletal models accurately predict knee loading measured using instrumented implants

<p>We investigated three different methods for simulating neuromusculoskeletal (NMS) control to generate estimates of knee joint loading which were compared to in-vivo measured loads. The major contributions of this work to the literature are in generalizing EMG-informed and probabilistic methods for modelling NMS control.</p> <p>A single calibration function for EMG-informed NMS modelling was identified which accurately estimated knee loads for multiple people across multiple trials. Using a stochastic approach to NMS modelling, we investigated the range of possible solutions for knee joint loading during walking, showing the method's generalizability and capability to generate solutions which encompassed the measured knee loads. Through this stochastic approach, we were able to show that a single degree of freedom planar knee is suited to estimating total knee loading, but is insufficient for estimating the directional components of load.</p> <p> </p>

Feasibility of Continuous Ketone Monitoring in Subcutaneous Tissue using a Ketone Sensor

Background: The feasibility of measuring β-hydroxybutyrate in ISF using a continuous ketone monitoring (CKM) sensor using a single calibration without further adjustments over 14 days is described. Methods: A CKM sensor was developed using wired enzyme technology with β-hydroxybutyrate dehydrogenase chemistry. In vitro characterization of the sensor was performed in phosphate buffered saline at 37°C. In vivo performance was evaluated in 12 healthy participants on low carbohydrate diets, who wore 3 ketone sensors on the back of their upper arms to continuously measure ketone levels over 14 days. Reference capillary ketone measurements were performed using Precision Xtra® test strips at least 8 times a day. Results: The sensor is stable over 14 days and has a linear response over the 0-8 mM range. The operational stability of the sensor is very good with a 2.1% signal change over 14 days. The first human study of the CKM sensor demonstrated that the sensor can continuously track ketones well through the entire 14 days of wear. The performance with a single retrospective calibration of the sensor showed 82.4% of data pairs within 0.225 mM/20% and 91.4% within 0.3 mM/30% of the capillary ketone reference (presented as mM at <1.5 mM and as percentage at or above 1.5 mM). This suggests that the sensor can be used with a single calibration for the 14 days of use. Conclusions: Measuring ketones in ISF using a continuous ketone sensor is feasible. Additional studies are required to evaluate the performance in intended patient populations, including conditions of ketosis and diabetic ketoacidosis.

Transformation functions in electrothermal atomic absorption spectrometry

The problem of calibration of an analytical instrument and analysis procedure with an unknown composition and origin of the analyzed sample are considered. The transformation functions of the Zeeman atomic absorption spectrometer with electrothermal atomization have been investigated. The method for establishing a two-parameter transformation function of the spectrometer using a single calibration sample is proposed and the possibility of measuring the analyte concentration in a real sample using the refined transformation function of the spectrometer is considered.

Improvement of Hargreaves–Samani Reference Evapotranspiration Estimates with Local Calibration

Improving irrigation water management is an important asset when facing increased water shortages. The Hargreaves–Samani (HS) method is a simple method that can be used as an alternative to the Penman–Monteith (PM) method, which requires only temperature measurements for estimating reference evapotranspiration (ETo). However, the applicability of this method relies on its calibration to local meteorological specificities. The objective of this study was to investigate the effects of local calibration on the performance of the HS equation. The study was carried out for the middle portion of the São Francisco River Basin (MSFB), Brazil, and considered four calibration approaches: A1—single calibration for the entire MSFB; A2—separate calibration by clusters of months; A3—by clusters of stations; and A4—for all contexts resulting by combining A2 and A3. Months from the wet season showed larger improvements by the calibration of the HS model, since mean air temperature and its daily range showed stronger correlations to ETo. On the other hand, the months from the dry season and stations from the eastern region of MSFB performed poorly regardless of the calibration approach adopted. This occurred because, in those cases, ETo presented larger correlation to variables that are missing in the HS equation, and the use of the full PM equation seems unavoidable.