Calibration Equations Research Articles

A simple electrochemical immunosensor based on MWCNTs-COOH/Fc-COOH@CoAl-LDH, nanocomposite for sensitive detection of the tumor marker CA724

A novel label-free electrochemical immunosensor for the ultrasensitive determination of cancer antigen (CA724) was developed using a novel composite of CoAl layered double hydroxides (CoAl-LDH) and carboxyl-functionalized multiwall carbon nanotubes (MWCNTs-COOH) as platform and ferrocenecarboxylic acid (Fc-COOH) as signal label. The MWCNTs-COOH/Fc-COOH@CoAl-LDH composite was prepared by a convenient and simple one-step ultrasonic method, and various characterization techniques consisting of scanning electron microscopy (SEM), transimission electronic microscopy (TEM), TEM-Mapping, fourier transform infrared (FT-IR), X-ray diffraction (XRD) and X-ray photoelectronic energy spectrum (XPS) were applied to study the size and morphological features. Due to its large specific surface area and multilayer structure, the CoAl-LDH can be post-doped to embed a large amount of signal probe to realize the amplification of the internal reference signal Fc. In addition, the higher conductivity of MWCNTs-COOH compensates for the deficiency of CoAl-LDH, which effectively strengthened the electron transfer efficiency of electrochemical signaling substances. The optimal experimental conditions were detected to be 2.5 mmol of Fc-COOH, 4.0 mg/mL of concentration, pH 6.0, incubation time of 40 min, and incubation temperature of 37 ℃. Under optimal conditions, the fabricated sensor exhibits linearity in a wide dynamic range covering the physiological concentration, from 0.001 to 100 U/mL and the limit of detection (LOD) was 0.03962 mU/mL, the calibration equation is stated as △I = 7.76363 log10CCA724 + 40.50351 (R2 = 0.99674). The sensor is successfully detects trace levels of CA724 in human serum with excellent recovery rates ranging from 100.52 %-102.30 %, proving the synergy of MWCNTs-COOH/Fc-COOH@CoAl-LDH as a promising platform for electrochemical sensing for clinical detection of other disease markers.

From dishwasher to river: how to adapt a low-cost turbidimeter for water quality monitoring.

This study presents the process of design and development of a low-cost turbidimeter for monitoring water quality, facilitating rigorous spatial-temporal variability analysis within large-scale hydrological systems. We propose a low-cost optical turbidimeter, modifying the existent SEN0189 turbidity sensor, Arduino boards, and additional sensors for temperature compensation. We compared a low-cost system with high-tech sensors, modifying the original low-cost SEN0189 probe for enhanced environmental performance. The three-step methodological framework involved prototype development, compensation for environmental factors, and preparation for future field deployment. Calibration equations with a high coefficient of determination and a temperature correction equation were established. We made adaptations to overcome field deployment challenges, including a 3-D printed sensor case, defining the relationship between measurement uncertainty and energy consumption, and specifying field installation guidelines. In summary, this study presents a comprehensive approach to a low-cost optical turbidity system, demonstrating its potential for accurate and affordable field deployment. We aim to address the critical need for sustainable inland water management tools, making this system a valuable contribution to environmental monitoring practices. We also aim to inspire similar development of open-source monitoring systems within our community.

Associations between milk infrared-predicted plasma biomarkers of stress resilience and fertility in dairy cattle: insights for enhancing breeding programs and herd management

Fertility is a crucial aspect of dairy herd efficiency and sustainability. Among factors influencing fertility in dairy cattle, metabolic stress and systemic inflammation of animals are of main relevance, especially in the postpartum stage when ovarian activity begins and cows are inseminated. Our study aimed to infer the associations between milk infrared-predicted blood biomarkers of stress resilience and fertility traits, namely the interval from calving to first service (iCF), days open (DO), and the pregnancy rate at first service (PRF) in a multi-breed population of 89,097 dairy cows. The blood metabolites (15 blood biomarkers related to hepatic damage and function, oxidative stress, and inflammation/innate immunity) were predicted using milk Fourier-transform mid-infrared (MIR) spectroscopy. A gradient boosting machine (GBM) approach with leave-one-batch-out cross-validation (R2 range from 0.45 to 0.82) was implemented to an independent calibration database of 1,367 lactating cows reared in 5 herds. Calibration equations were then applied to a population database of 1,799,186 MIR milk spectral data, that were then merged with fertility data collected by the Breeders Federation of Alto Adige (Bolzano province, Italy) generating a final database of 285,145 records. The 2 databases were merged according to the milk test day (and thus the MIR spectrum) closest to the date of insemination. The interval fertility traits were fitted as the hazard of either receiving the first service after calving at time t for iCF or becoming pregnant after calving at time t for DO in a Cox proportional-hazards model. Statistical analyses were performed including in the model the number of lactations, year of calving, and herd as fixed effects. The independent effect of the MIR-based predictions of metabolites was also included with each metabolite evaluated separately and discretized into 7 levels based on percentiles. Pregnancy rate at first service, on the other hand, was analyzed using logistic regression and the same explanatory variables. The metabolites linked to liver function and damage, such as aspartate aminotransferase, total bilirubin, and alkaline phosphatase, had a relevant influence on iCF and DO in terms of the hazard ratio (HR). Relevant results were also obtained for the biomarkers related to oxidative stress and inflammation/innate immunity. Specifically, increasing levels of ceruloplasmin, total reactive oxygen metabolites, and advanced oxidation protein products resulted in a relevant decrease in the HR of cows becoming pregnant. The logistic regression analysis did not reveal any significant effect of the aforementioned biomarkers on PRF, indicating that the effects of the stress response mainly concern the resumption of the ovarian cycle after calving. The results for the associations of the predicted biomarkers of the stress response with iCF and DO were consistent with expected physiological patterns. In conclusion, the predicted biomarkers investigated revealed to be promising novel phenotypes for assessing animal health and welfare, in the view of enhancing fertility in dairy cattle also through selective breeding, thus improving the overall efficiency of dairy herds.

Examination of the Dry Density Importances in TDR Use and of the ASTM D6780 Standard Based on a New Calibration Procedure

Abstract The use of time domain reflectometry (TDR) to monitor soil water content at either field or laboratory scales is highly common. Regarding the soil dry density, ρd, effect on the TDR application, three main approaches are found in the literature: (1) Ignore the density issue and use calibration to evaluate the water content regardless of the density. This approach is basic, yet common. (2) Include soil density in the calibration equation and use calibration for the water content as a function of both the TDR output and soil density. In this approach, the soil density should be provided from an independent source. (3) Determined ρd from the TDR waveform. In this case both water content and ρd are set from the TDR analysis. In cases where the ρd is not available, in order to use TDR for water content measurement, a decision has to be made whether to address the density issue although it requires resources, or to neglect it. This article reviews this issue and validates the density effect using an efficient TDR calibration methodology. A calibration scheme that controls ρd of the specimen has been developed and applied. The methodology creates continuous calibration curves over a range of volumetric water content from a single test specimen. Based on the results, it has been demonstrated that the soil density has a major effect on the TDR output and it cannot be ignored. In addition, this article presents a unique examination of ASTM D6780, Standard Test Methods for Water Content and Density of Soil In Situ by Time Domain Reflectometry (TDR). The ASTM dry density estimation was found to provide reliable results; however, the gravimetric water contents estimation gives unsatisfactory results, especially for low densities.

17O-excess of grass leaf phytoliths across the North American prairies records late-growing season daytime relative humidity

Because it is an important climate parameter, an accurate proxy is required for the reconstruction of past Relative Humidity (RH). Triple oxygen isotopes of grass-leaf phytoliths have a high potential for this purpose. A strong correlation between RH and 17O-excess of grass leaf phytoliths has been previously demonstrated from calibration experiments in growth chambers and at natural Sub-Saharan African and Mediterranean sites. Here we focus on the potential of 17O-excess of grass leaf phytoliths as a proxy of RH across the North American Great Plains. We tested the relationship between the 17O-excess of naturally grown Calamovilfa longifolia phytoliths and RH for different periods of the grass growing season. The results show that 17O-excess of leaf phytoliths has a strong correlation with late-growing season (July–August) daytime RH, which varies from 29 to 72 % across North America. The correlation can be expressed as: 17O-excessleaf phytoliths = 4.14(±0.47) × RH (%) – 497(±26) (R2 = 0.85, p-value<0.0001), which is statistically equal to the previous calibration equation (Alexandre et al., 2018; Outrequin et al., 2021). To use the 17O-excess of bulk phytoliths from buried soils and sediments as a quantitative proxy of past RH, future calibration studies on soil phytoliths are needed to evaluate the contribution of non-transpiring phytoliths. The 17O-excess of stem water, which was determined by 17O-excess of stem phytoliths, shows similar values to the 17O-excess of precipitation in North America without evaporation, which therefore does not affect the 17O-excess of leaf phytoliths in North America. These results demonstrate that the 17O-excess of phytoliths is a promising proxy for regional growing season RH.

Comparison of Classical and Inverse Calibration Equations in Chemical Analysis.

Chemical analysis adopts a calibration curve to establish the relationship between the measuring technique's response and the target analyte's standard concentration. The calibration equation is established using regression analysis to verify the response of a chemical instrument to the known properties of materials that served as standard values. An adequate calibration equation ensures the performance of these instruments. There are two kinds of calibration equations: classical equations and inverse equations. For the classical equation, the standard values are independent, and the instrument's response is dependent. The inverse equation is the opposite: the instrument's response is the independent value. For the new response value, the calculation of the new measurement by the classical equation must be transformed into a complex form to calculate the measurement values. However, the measurement values of the inverse equation could be computed directly. Different forms of calibration equations besides the linear equation could be used for the inverse calibration equation. This study used measurement data sets from two kinds of humidity sensors and nine data sets from the literature to evaluate the predictive performance of two calibration equations. Four criteria were proposed to evaluate the predictive ability of two calibration equations. The study found that the inverse calibration equation could be an effective tool for complex calibration equations in chemical analysis. The precision of the instrument's response is essential to ensure predictive performance. The inverse calibration equation could be embedded into the measurement device, and then intelligent instruments could be enhanced.

Coral Sr/Ca-SST calibration: SST records from Kenyan corals

To better understand the seasonal variability in SST in Kenyan coral reef ecosystems, Sr/Ca ratios have been measured in Kenyan coral skeletons as proxies of SST, and a new Sr/Ca = f(SST) calibration was established: Sr/Ca = − 0.053 (± 0.006) *SST + 10.43 (± 0.16). The slope was within the margins of − 0.04 and − 0.08 mmolmol−1 °C of previously published Sr/Ca-SST calibration equations. A reliability test revealed that the present calibration equation reproduces a previously published calibration equation developed for Kenyan corals. This calibration was applied to corals collected in reef ecosystems under different natural and anthropogenic influences: Tana Delta Ziwayu Island, Watamu National Marine Park, and Shimon Mupunguti Marine Reserve. Using the developed Sr/Ca-thermometry, the reconstructed Sr/Ca-SST revealed that reefs from the southern basin of the Kenyan Indian Ocean are exposed to warmer SSTs than reefs in the northern Basin are. Additionally, the results revealed that the seasonal variability on SST increased moving toward the southern basin of the Kenyan Indian Ocean. We use the local instrument SST as an SST reference, which is aligned against the Sr/Ca seasonal signals recorded in SMR3-18 (the nearest coral site), and the intensity of the third global coral bleaching (April and May 2016) is affirmed.

Development and construction of a cost-effective non-contact instrument for measuring the dielectric constant of liquids.

This research presents the development and construction of a cost-effective instrument, designed to measure the dielectric constant of liquids by employing a non-contact method that relies on determining the capacitance of a cell containing the liquid and its relaxation frequency. This instrument utilizes an astable multi-vibrator integrated with a resistance-capacitor network, in which the cell housing the liquid of interest functions as a capacitor element of the oscillator. The frequency of the generated oscillations is meticulously recorded using a seven-digit frequency meter with a resolution of 1Hz. The cell was filled with an array of pure liquids with known dielectric constants, and their frequencies were subsequently recorded at ambient temperatures. An equation was fitted to the frequency-dielectric constant curve, which was used as a calibration equation to determine the dielectric constant of subsequent liquids. In addition to pure liquids, dielectric constants for solvent mixtures of varying mole fractions were also calculated using the previously established calibration equation. Our results demonstrated excellent frequency stability of the instrument, and the obtained dielectric constant values displayed significant consistency with both the experimental data and predictions made by computational methodologies. This suggests that the constructed instrument exhibits a high level of accuracy in measuring the dielectric constant of both pure and mixed liquids, establishing its potential utility in relevant research and industrial applications.

New calibration equation of NTC thermistor for high-precision temperature measurement in narrow temperature ranges

The study proposed a new equation of NTC thermistor which was suitable for efficient calibration in narrow temperature ranges. The equation required only two calibration points to achieve millikelvin(mK) level temperature measurement in narrow temperature range of 5 degrees Celsius. To confirm the performance of the equation, fourteen NTC thermistors were calibrated in the temperature ranges of −5 to 0 ℃, 0 to 5 ℃, and 20 to 25 ℃, respectively. The results demonstrated that the new equation achieved average residuals of 0.28 mK in the narrow temperature range of 5 degrees Celsius. Additionally, the deviation from the commonly used Hoge equation for NTC thermistors was within 0.60 mK. These findings validated the feasibility of using two calibration points to achieve high-precision temperature measurement in narrow temperature ranges and offered a new approach for high-precision temperature measurement.

Mesoscale soil moisture measurements along the rover route using the mobile cosmic-ray neutron sensing in the eastern Tibetan Plateau

Water resources in the soil play an essential role in hydrological processes and ecosystem functions on the Tibetan Plateau. However, accurately measuring soil moisture distribution in this region presents challenges due to the diverse ecosystem types, complex terrain, and harsh environmental conditions. In this study, we introduce an approach for estimating mesoscale soil moisture in the Qilian Mountains (QLM) region of the eastern Tibetan Plateau using a cosmic-ray neutron rover. Soil moisture estimates derived from neutron count rates, newly adjusted by vegetation effects, demonstrated good agreement with soil moisture measurements obtained through soil sampling at 26 calibration sites across the region (RMSE = 0.025 g g−1). The calibration parameter N0_NDVI was 443 cpm in the QLM. Utilizing NDVI as vegetation correction method showed potential improvements in the accuracy of converting neutron counts to soil moisture across the diverse mountainous ecosystem types. The newly developed calibration equation provided a high-precision, high spatial resolution soil moisture transect across various landscapes measured by the rover. The average mesoscale soil moisture along the rover route varied by ecosystem types, with values of 0.10 g/g in deserts, 0.17 g/g in grasslands, 0.13 g/g in forests, 0.18 g/g in subalpine shrublands, and 0.20 g/g in croplands. Land cover types emerged as crucial determinants of mesoscale soil moisture variability in the QLM region. These findings offer valuable mesoscale soil moisture data and new insights into soil water information at the transect scale across diverse ecosystem types in the Tibetan Plateau.

Experimental and theoretical research on deformation monitoring of distributed piezoelectric inclinometer tube

To improve horizontal displacement monitoring in geotechnical engineering, researchers have focused on developing distributed, automated, and cost-effective inclinometers capable of long-term monitoring. However, existing technologies cannot fully satisfy these requirements. This study proposes a novel piezoelectric inclinometer tube that incorporates a sensor-enabled piezoelectric geocable (SPGC), which was mounted along the surfaces of three tubes made of different materials. The distributed strain along the inclinometer tube was measured using the impedance–strain effect of the SPGC, and a deflection curve was obtained. The results of the failure test showed that the piezoelectric inclinometer tube remained within its measurement range before breaking. Furthermore, the placement of the SPGC on the outer surface of the tube demonstrated superior monitoring effectiveness under bending deformation, providing qualitative insights into the deformation and fracture behavior of the tube. Loading and unloading tests demonstrated excellent reproducibility of strain in the piezoelectric inclinometer tube. Among the tested materials, the inclinometer tube made of acrylonitrile butadiene styrene exhibited acceptable elasticity, large bending displacement, and a high strain transfer rate, making it ideal for monitoring significant deformations in rock and soil. A linear calibration equation was established for the normalized impedance change–strain relationship of the piezoelectric inclinometer tube through calibration tests. Furthermore, a theoretical model was derived to convert the normalized impedance change to the deflection of the piezoelectric inclinometer tube using the finite difference method. Theoretical and experimental values were significantly consistent, with strain and deflection measurement accuracies of 10 με and 0.1 mm, respectively, and an average calculation error of less than 4%. These results are expected to improve the distributed monitoring of horizontal displacement in rock and soil.

Evaluation of a Multivariate Calibration Model for the WET Sensor That Incorporates Apparent Dielectric Permittivity and Bulk Soil Electrical Conductivity

The measurement of apparent dielectric permittivity (εs) by low-frequency capacitance sensors and its conversion to the volumetric water content of soil (θ) through a factory calibration is a valuable tool in precision irrigation. Under certain soil conditions, however, εs readings are substantially affected by the bulk soil electrical conductivity (ECb) variability, which is omitted in default calibration, leading to inaccurate θ estimations. This poses a challenge to the reliability of the capacitance sensors that require soil-specific calibrations, considering the ECb impact to ensure the accuracy in θ measurements. In this work, a multivariate calibration equation (multivariate) incorporating both εs and ECb for the determination of θ by the capacitance WET sensor (Delta-T Devices Ltd., Cambridge, UK) is examined. The experiments were conducted in the laboratory using the WET sensor, which measured θ, εs, and ECb simultaneously over a range of soil types with a predetermined actual volumetric water content value (θm) ranging from θ = 0 to saturation, which were obtained by wetting the soils with four water solutions of different electrical conductivities (ECi). The multivariate model’s performance was evaluated against the univariate CAL and the manufacturer’s (Manuf) calibration methods with the Root Mean Square Error (RMSE). According to the results, the multivariate model provided the most accurate θ estimations, (RMSE ≤ 0.022 m3m−3) compared to CAL (RMSE ≤ 0.027 m3m−3) and Manuf (RMSE ≤ 0.042 m3m−3), across all the examined soils. This study validates the effects of ECb on θ for the WET and recommends the multivariate approach for improving the capacitance sensors’ accuracy in soil moisture measurements.

An Integrated Hydrogeophysical Approach for Unsaturated Zone Monitoring Using Time Domain Reflectometry, Electrical Resistivity Tomography and Ground Penetrating Radar

Continuous measurements of soil moisture in the deeper parts of the unsaturated zone remain an important challenge. This study examines the development of an integrated system for the continuous and 3-D monitoring of the vadose zone processes in a cost- and energy-efficient way. This system comprises TDR, ERT and GPR geophysical techniques. Their capacities to adequately image subsurface moisture changes with continuous and time-lapse measurements are assessed during an artificial infiltration experiment conducted in a characteristic urban site with anthropogenic fills and much compaction. A 3-D array was designed for each method to expand the information of a single TDR probe and obtain a broader image of the subsurface. Custom spatial TDR probes installed in boreholes made with a percussion drilling instrument were used for soil moisture measurements. Moisture profiles along the probes were estimated with a numerical one-dimensional inversion model and a standard calibration equation. High conductivity water used during all infiltration tests led to the detection of the flow by all techniques. Preferential flow was present throughout the experiment and imaged sufficiently by all methods. Overall, the integrated approach conceals each method’s weaknesses and provides a reliable 3-D view of the subsurface. The results suggest that this approach can be used to monitor the unsaturated zone at even greater depths.

A Prototype That Improves the Interpretation of Soil Moisture by Using the BGT-SEC Z2 Sensor

The amount of water required to irrigate, is essential in agricultural planning. In Mexico the water required for irrigation is generally not estimated when it is carried out despite several estimation methods being available (direct and indirect). However, some methods can be very expensive, requiring preparation time to use them or time to obtain the results. One of the methods involves using sensors based on relative permittivity. This method have been widely used in agriculture because they show the percentage of water contained in the substrate. However, this value helps the producer know the soil moisture status of their crop in percentage units but does not tell them how much water needs to be added to each plant in liters. Knowing this value could help reduce water losses due to infiltration, thereby increasing the crop area. Therefore, it was developed a device capable of recommending the amount of water in v/v (volume of water/volume of soil) required to irrigate a crop. The prototype device was based on the BGT-SEC Z2&amp;lt;SUP&amp;gt;TM&amp;lt;/SUP&amp;gt; sensor and the ATMEGA 2560&amp;lt;SUP&amp;gt;TM&amp;lt;/SUP&amp;gt; microcontroller. The obtained device was calibrated and a specific model was developed for two types of soil: sandy (with an RMSE of 0.0107) and loamy (with an RMSE of 0.00556). With factory calibration, a RMSE value of 0.0339 was found for the loamy soil and 0.0278 for the sandy soil. In addition, the sensor was tested on strawberry plants with pots covered with and without plastic mulch (using loamy soil). The results on the strawberry plants, indicated that water consumption was best explained by the specific calibration equation for loamy soil covered with plastic mulch (67.8 mL RMSE) and without plastic mulch (82.8 mL RMSE). Finally, it was found that at least two measurements are required to obtain soil moisture average in plastic mulch strawberry pots and 6 measurements in pots without plastic mulch. With the above, it is concluded that the device developed in this study performed adequately during experiments and the sensor worked continuously without failing.

377 Developing visible near-infrared spectroscopy calibration equations to predict the chemical composition of feces and nutrient digestibility based on pig fecal spectra

377 Developing visible near-infrared spectroscopy calibration equations to predict the chemical composition of feces and nutrient digestibility based on pig fecal spectra

A NOVEL COST-EFFECTIVE PRESSURE SENSOR BASED FLOOD MONITORING SYSTEM WITH IOT

Floods are one of the most frequent and destructive natural hazards in the world. Early warning and flood monitoring is beneficial in the response and preparedness for this hazard. This paper presents a novel, low-cost flood monitoring system for disaster prevention, based on a pressure sensor. The system comprises a state-of-the-art microcontroller, a pressure sensor, and a security element. It is connected to an Internet of Things (IoT) cloud service, allowing for further data processing, interaction, and storage. The sensor data is processed to provide real-time flood measurements. The calibration data obtained from the designed system demonstrates a linear correlation between the water level and the sensor output. Additionally, the system was able to provide flood level measurements with an average error of 4.08% using the calibration equation, whereas a 4.40% error was obtained when using theoretical equations to determine the flood height.

Parametric optimization for estimating beta detection efficiency in thin plastic scintillation detector

A condenser air removal system plays a crucial role in radiation monitoring within nuclear power plants, specifically for detecting potential leaks of radioactive material from primary-to-secondary systems. This system assesses the leakage rate (LR) by measuring the emission of β particles from noble gases using a thin plastic scintillation (TPS) detector, which is specifically designed for counting purposes. Among the factors used in LR calculation, the detection efficiency (k) must be experimentally determined in advance. However, this is challenging because of the limitations posed by radiation safety regulations. Moreover, simulation-based calculations are difficult to achieve because only a portion of the β-ray energy is transferred in the TPS detectors, resulting in a lack of prior energy information. To overcome these challenges, this study employed a multi-objective parameter optimization technique to simultaneously calculate the parameters required for the β-ray detection response function and energy calibration equation. Subsequently, k values were calculated using the optimization results. The optimization performance was demonstrated by comparing the measured spectra of the TPS detector with the spectra obtained from the Monte Carlo N-particle simulation. Furthermore, we confirmed that the calculated k values agreed with the reference values.

Precision Calibration and Linearity Assessment of Thin Film Force-Sensing Resistors

In this study, we thoroughly analyzed the linearity and repeatability of force-sensing resistor (FSR) sensors through static load tests to ensure their reliability. The novelty of this research lies in its comprehensive evaluation and direct comparison of two widely used FSR sensors, i.e., Flexiforce A201-1 and Interlink FSR-402, under various loading conditions by employing a robust calibration methodology. This study provides detailed insights into the sensors’ performances, offering practical calibration equations that enhance measurement precision and reliability, which have not been extensively documented in previous studies. Our results demonstrate that the linearity of thin film FSR sensors is highly accurate, closely resembling a straight line. We employed M1 Class weights, applying loads ranging from 20 g to 300 g. The resistance of the FSR sensors, which varies with the applied load, was measured using a voltage divider circuit and an analog-to-digital converter of a microcontroller. MATLAB was used to calculate the average output voltage for each applied load and fixed resistance. Additionally, we examined the relationships among load, FSR sensor resistance, and conductivity. Our research indicates that with precise calibration, thin film FSR sensors can be highly reliable for force measurement applications.

Multi-site phantomless bone mineral density from clinical quantitative computed tomography in males.

Volumetric bone mineral density (vBMD) is commonly assessed using QCT. Although standard vBMD calculation methods require phantom rods that may not be available, internal-reference phantomless (IPL) and direct measurements of Hounsfield units (HU) can be used to calculate vBMD in their absence. Yet, neither approach has been systemically assessed across skeletal sites, and HU need further validation as a vBMD proxy. This study evaluated the accuracy of phantomless methods, including IPL and regression-based phantomless (RPL) calibration using HU to calculate vBMD, compared to phantom-based (PB) methods. vBMD from QCT scans of 100 male post-mortem human subjects (PMHS) was calculated using site-specific PB calibration at multiple skeletal sites throughout the body. A development sample of 50/100 PMHS was used to determine site-specific reference material density for IPL calibration and RPL equations. Reference densities and equations from the development sample were used to calculate IPL and RPL vBMD on the remaining 50/100 PMHS for method validation. PB and IPL/RPL vBMD were not significantly different (p > .05). Univariate regressions between PB and IPL/RPL vBMD were universally significant (p < 0.05), except for IPL Rad-30 (p = 0.078), with a percent difference across all sites of 6.97% ± 5.95% and 5.22% ± 4.59% between PB and IPL/RPL vBMD, respectively. As vBMD increased, there were weaker relationships and larger differences between PB vBMD and IPL/RPL vBMD. IPL and RPL vBMD had strong relationships with PB vBMD across sites (R2 = 97.99, R2 = 99.17%, respectively), but larger residual differences were found for IPL vBMD. As the accuracy of IPL/RPL vBMD varied between sites, phantomless methods should be site-specific to provide values more comparable to PB vBMD. Overall, this study suggests that RPL calibration may better represent PB vBMD compared to IPL calibration, increases the utility of opportunistic QCT, and provides insight into bone quality and fracture risk.

Implementation of Linear Regression Method for Calibration and Temperature Measurement on PT100 Temperature Sensor

The PT100 temperature sensor, a type RTD (resistance temperature detector), is widely employed in industries, particularly for steam boiler temperature regulation. Precise temperature measurement is vital for operational efficiency and safety maintenance. Utilizing linear regression for calibrating and measuring temperature with the PT100 sensor integrated with Arduino Uno and LCD I2C is proposed to enhance accuracy. Testing involved assembling the PT100 sensor with Arduino Uno and LCD I2C. Test data were employed for linear regression to derive the calibration equation. Measurements were conducted by comparing PT100 sensor readings with a digital thermometer across a temperature range of 30ºC to 75ºC at 5ºC intervals, with each temperature point tested five times. Results exhibit good accuracy in temperature measurement with the PT100 sensor, featuring low error and percentage error. The standard deviation indicates consistent measurement. Integration of the PT100 temperature sensor with Arduino Uno and LCD I2C, coupled with linear regression for calibration, yields a precise temperature measurement system. Testing against a digital thermometer demonstrates highly accurate outcomes. This developed system finds application in high-precision temperature measurement for steam boiler operations.