Correlation R2 Research Articles

Adjusting for the effect of IV contrast on automated CT body composition measures during the portal venous phase.

Fully-automated CT-based algorithms for quantifying numerous biomarkers have been validated for unenhanced abdominal scans. There is great interest in optimizing the documentation and reporting of biophysical measures present on all CT scans for the purposes of opportunistic screening and risk profiling. The purpose of this study was to determine and adjust the effect of intravenous (IV) contrast on these automated body composition measures at routine portal venous phase post-contrast imaging. Final study cohort consisted of 1,612 older adults (mean age, 68.0 years; 594 women) all imaged utilizing a uniform CT urothelial protocol consisting of pre-contrast, portal venous, and delayed excretory phases. Fully-automated CT-based algorithms for quantifying numerous biomarkers, including muscle and fat area and density, bone mineral density, and solid organ volume were applied to pre-contrast and portal venous phases. The effect of IV contrast upon these body composition measures was analyzed. Regression analyses, including square of the Pearson correlation coefficient (r2), were performed for each comparison. We found that simple, linear relationships can be derived to determine non-contrast equivalent values from the post-contrast CT biomeasures. Excellent positive linear correlation (r2 = 0.91-0.99) between pre- and post-contrast values was observed for all automated soft tissue measures, whereas moderate positive linear correlation was observed for bone attenuation (r2 = 0.58-0.76). In general, the area- and volume-based measurement require less adjustment than attenuation-based measures, as expected. Fully-automated quantitative CT-biomarker measures at portal venous phase abdominal CT can be adjusted to a non-contrast equivalent using simple, linear relationships.

Assessing soil productivity potential in arid region using remote sensing vegetation indices

Remote sensing techniques offer practical benefits, particularly in sensitive ecosystems or areas with limited accessibility. However, field surveys allow for more accurate and detailed information about soil properties and productivity. Therefore, it is often recommended to combine remote sensing techniques with field surveys in order to obtain comprehensive and reliable results. The underlying basis of this study involves analyzing vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Soil Adjusted Vegetation Index (SAVI), as indicators of soil productivity. By utilizing biomass density as an additional indicator, the study aims to provide valuable insights into the productivity potential of agricultural areas. The results demonstrate a positive association between the Soil Productivity Rating (SPR) and wheat yield values for the year 2022, as evidenced by a coefficient of determination (r2) value of 0.8214. This value indicates a moderately strong correlation between the SPR classes and wheat yields. Throughout the Ripening period, the NDVI and EVI indices exhibited a relatively strong correlation coefficient (r2 = 0.987 and 0.873, respectively). On the other hand, the SAVI index displayed moderate to strong accuracy in estimating crop yield, with a coefficient of determination (r2) ranging from 0.819 to 0.908. These results suggest that the NDVI index serves as the most dependable predictor of yield during all vegetation periods. This study provides a comprehensive understanding of soil productivity, but further research using controlled trial patterns with differential reference plants is needed for validation and improvement.

Prediction of flow stress in Mg-3Dy alloy based on constitutive equation and PSO-SVR model

Abstract This study conducted hot compression experiments on as-cast Mg-3Dy alloy under deformation parameters of 380-470℃ and 0.001-1s-1. The microstructure of the alloy was observed using EBSD, and the flow stress of the Mg-3Dy alloy was predicted using the Arrhenius model and the particle swarm optimization-support vector regression (PSO-SVR) model. The organizational analysis results showed that the main recrystallization mechanism in the alloy is the discontinuous dynamic recrystallization (DDRX) mechanism. The generation of twins in the alloy was mostly the result of local stress action. The optimal processing window for this alloy was determined to be 380-470 °C and 0.001-0.01 s-1 through the thermal processing map. The prediction accuracies of the Arrhenius model and PSO-SVR model were evaluated using the correlation coefficient R2 and mean squared error MSE. The results showed that the PSO-SVR model significantly outperforms the Arrhenius model in prediction accuracy, with R2 value of 0.99982 and MSE of 0.074.

Terrestrial Ecosystem Model in R (TEMIR) version 1.0: simulating ecophysiological responses of vegetation to atmospheric chemical and meteorological changes

Abstract. The newly developed offline land ecosystem model Terrestrial Ecosystem Model in R (TEMIR) version 1.0 is described here. This version of the model simulates plant ecophysiological (e.g., photosynthetic and stomatal) responses to varying meteorological conditions and concentrations of CO2 and ground-level ozone (O3) based on prescribed meteorological and atmospheric chemical inputs from various sources. Driven by the same meteorological data used in the GEOS-Chem chemical transport model, this allows asynchronously coupled experiments with GEOS-Chem simulations with unique coherency for investigating biosphere–atmosphere chemical interactions. TEMIR agrees well with FLUXNET site-level gross primary productivity (GPP) in terms of both the diurnal and monthly cycles (correlation coefficients R2>0.85 and R2>0.8, respectively) for most plant functional types (PFTs). Grass and shrub PFTs have larger biases due to generic model representations. The model performs best when driven by local site-level meteorology rather than reanalyzed gridded meteorology. Simulation using gridded meteorology agrees well for annual GPP in seasonality and spatial distribution with a global average of 134 Pg C yr−1. Application of Monin–Obukhov similarity theory to infer canopy conditions from gridded meteorology does not improve model performance, predicting an increase of +7 % in global GPP. Present-day O3 concentrations simulated by GEOS-Chem and an O3 damage scheme at high sensitivity show a 2 % reduction in global GPP with prominent reductions of up to 15 % in eastern China and the eastern USA. Regional correlations are generally unchanged when O3 is present and biases are reduced, especially for regions with high O3 damage. An increase in atmospheric CO2 concentration of 20 ppmv from the level in 2000 to the level in 2010 modestly decreases O3 damage due to reduced stomatal uptake, consistent with ecophysiological understanding. Our work showcases the utility of this version of TEMIR for evaluating biogeophysical responses of vegetation to changes in atmospheric composition and meteorological conditions.

Influence of Leaf Area Index Inversion and the Light Transmittance Mechanism in the Apple Tree Canopy

Light plays a crucial role in the growth of fruit trees, influencing not only nutrient absorption but also fruit appearance. Therefore, understanding fruit tree canopy light transmittance is essential for agricultural and forestry practices. However, traditional measurement methods, such as using a canopy analyzer, are time-consuming, labor-intensive, and susceptible to external influences, lacking convenience and automation. To address this issue, we propose a novel method based on point clouds to estimate light transmittance, with the Leaf Area Index (LAI) serving as the central link. Focusing on apple trees, we utilized handheld LiDAR for three-dimensional scanning of the canopy, acquiring point cloud data. Determining the optimal voxel size at 0.015 m via standardized point cloud mean spacing, we applied the Voxel-based Canopy Profile method (VCP) to estimate LAI. Subsequently, we established a function model between LAI and canopy light transmittance using a deep neural network (DNN), achieving an overall correlation coefficient R2 of 0.94. This model was then employed to estimate canopy light transmittance in dwarfed and densely planted apple trees. This approach not only provides an evaluation standard for pruning effects in apple trees but also represents a critical step towards visualizing and intelligentizing light transmittance.

Impacts of socioeconomic and environmental factors on neoplasms incidence rates using machine learning and GIS: a cross-sectional study in Iran

Neoplasm is an umbrella term used to describe either benign or malignant conditions. The correlations between socioeconomic and environmental factors and the occurrence of new-onset of neoplasms have already been demonstrated in a body of research. Nevertheless, few studies have specifically dealt with the nature of relationship, significance of risk factors, and geographic variation of them, particularly in low- and middle-income communities. This study, thus, set out to (1) analyze spatiotemporal variations of the age-adjusted incidence rate (AAIR) of neoplasms in Iran throughout five time periods, (2) investigate relationships between a collection of environmental and socioeconomic indicators and the AAIR of neoplasms all over the country, and (3) evaluate geographical alterations in their relative importance. Our cross-sectional study design was based on county-level data from 2010 to 2020. AAIR of neoplasms data was acquired from the Institute for Health Metrics and Evaluation (IHME). HotSpot analyses and Anselin Local Moran's I indices were deployed to precisely identify AAIR of neoplasms high- and low-risk clusters. Multi-scale geographically weight regression (MGWR) analysis was worked out to evaluate the association between each explanatory variable and the AAIR of neoplasms. Utilizing random forests (RF), we also examined the relationships between environmental (e.g., UV index and PM2.5 concentration) and socioeconomic (e.g., Gini coefficient and literacy rate) factors and AAIR of neoplasms. AAIR of neoplasms displayed a significant increasing trend over the study period. According to the MGWR, the only factor that significantly varied spatially and was associated with the AAIR of neoplasms in Iran was the UV index. A good accuracy RF model was confirmed for both training and testing data with correlation coefficients R2 greater than 0.91 and 0.92, respectively. UV index and Gini coefficient ranked the highest variables in the prediction of AAIR of neoplasms, based on the relative influence of each variable. More research using machine learning approaches taking the advantages of considering all possible determinants is required to assess health strategies outcomes and properly formulate policy planning.

Bivalirudin Monitoring in Pediatric Ventricular Assist Device and Extracorporeal Membrane Oxygenation: Analysis of Single-Center Retrospective Cohort Data 2018-2022.

The activated partial thromboplastin time (aPTT) is the most frequently used monitoring assay for bivalirudin in children and young adults on mechanical circulatory support including ventricular assist devices (VADs) and extracorporeal membrane oxygenation (ECMO). However, intrinsic variability of the aPTT complicates management and risks bleeding or thrombotic complications. We evaluated the utility and reliability of a bivalirudin-calibrated dilute thrombin time (Bival dTT) assay for bivalirudin monitoring in this population. Retrospective analysis of clinical data (including aPTT, dilute thrombin time [dTT]) and results of residual plasma samples from VAD patients were assessed in two drug-calibrated experimental assays. One assay (Bival dTT) was validated for clinical use in VAD patients, and subsequently used by clinicians in ECMO patients. Pearson correlation and simple linear regression were used to determine R2 correlation coefficients between the different laboratory parameters using Statistical Package for Social Sciences (Armonk, NY). ICUs at Cincinnati Children's Hospital Medical Center. Children on VAD or ECMO support anticoagulated with bivalirudin. None. One hundred fifteen plasma samples from 11 VAD patients were analyzed. Both drug-calibrated experimental assays (anti-IIa and Bival dTT) showed excellent correlation with each other (R2 = 0.94) and with the dTT (R2 = 0.87), but poor correlation with aPTT (R2 = 0.1). Bival dTT was selected for validation in VAD patients. Subsequently, clinically ordered results (105) from 11 ECMO patients demonstrated excellent correlation between the Bival dTT and the standard dTT (R2 = 0.86) but very poor correlation with aPTT (R2 = 0.004). APTT is unreliable and correlates poorly with bivalirudin's anticoagulant effect in ECMO and VAD patients. A drug-calibrated Bival dTT offers superior reliability and opportunity to standardize results across institutions. Additional studies are needed to determine an appropriate therapeutic range and correlation with clinical outcomes.

A study of the migration behavior of formaldehyde in different concentrations of ethanol in paper food materials.

To ensure the safety of food contact materials, a liquid chromatography method was established to determine the migration of formaldehyde in paper packaging with various food simulants (10%, 25%, 50%, 75%, and 95% ethanol by volume) and to investigate the migration behavior of formaldehyde after various durations and with various materials. The results showed that the method has good linearity with a correlation coefficient of R2 > 0.9990, a detection limit of 0.0011 ~ 0.0027mg L-1, and a spiked recovery of 89.7 ~ 103.2% in the range of formaldehyde determination; the migration of formaldehyde in all six paper contact materials showed a trend of gradual increase with time until equilibrium was reached. At the same time and temperature, the migration of formaldehyde in paper packaging was the highest in low-concentration ethanol. With the same food simulants and materials, the maximum migration of formaldehyde in printed materials was greater than that in nonprinted materials; with different materials and the same food simulant, the thickness value was higher, with the use of water-based ink as a printing material, and the maximum migration value of formaldehyde by offset printing technology was low.

Phase angle and impedance ratio as meta-inflammation biomarkers after a colon cleansing protocol in a group of overweight young women.


Blood C-reactive protein (CRP) and the electrical bioimpedance (EBI) variables phase angle (PhA) and impedance ratio (IR) have been proposed as biomarkers of metainflammation in overweight/obesity. CRP involves taking blood samples, while PhA and IR imply a less-than-2-minute-non-invasive procedure. In this study, values for these variables and percent body fat mass (PBFM) were obtained and compared immediately before and immediately after a colon cleansing protocol (CCP), aimed at modulating intestinal microbiota, as well as along a period of 8 weeks after it.
Methods:
20 female volunteers (20.9-24.9 years old) participated: 12 in an overweight group (OG), and 8 in a lean group (LG). The OG was divided in two subgroups (n=6, each): control (SCG) and experimental (SEG). The ESG underwent a 6-day colon cleansing protocol (CCP) at week 2, while 5 volunteers in the CSG underwent it at week 9.
Results:
Pre/post-CCP mean values for the variables in the OG were: PBF (34.3/31.3%), CRP (3.7/0.6 mg/dL), PhA (6.9/7.5°) and IR*10 (0.78/0.77). Calculated R2 correlation factors among these variables are all above 0.89). The favorable changes first seen in the SEG were still present 8 weeks after the CCP.
Conclusion:
a) the CCP drastically lowers meta-inflammation, b) EBIS can be used to measure metainflammation, before and after treatment, c) for microbiota modulation, CCP could be a good alternative to more drastic procedures like fecal microbiota transplantation; d) reestablishing eubiosis by CCP could be an effective coadjutant in the treatment of overweight young adult overweight women.&#xD.

Determination of major drive of ozone formation and improvement of O3 prediction in typical North China Plain based on interpretable random forest model

O3 pollution in China has become prominent in recent years, and it has become one of the most challenging issues in air pollution control. We used data on atmospheric pollutants and meteorology from 2019 to 2021 to build an interpretable random forest (RF) model, applying this model to predict O3 concentration in 2022 in five cities in the Southwest North China Plain. The model was also used to identify and explain the influence of various factors on O3 formation. The correlation coefficient R2 between the predicted O3 concentration and observed O3 concentration was 0.82, the MAE was 15.15 μg/m3, and the RMSE was 20.29 μg/m3, indicating that the model can effectively predict O3 concentration in the studying area. The results of correlation analysis, feature importance, and the driving factor analysis from SHapley Additive exPlanations (SHAP) model indicated that temperature (T), NO2, and relative humidity (RH) are the top three features affecting O3 prediction, while the weights of wind speed and wind direction were relatively low. Thus, O3 in the southwestern region of Henan may mainly come from the formation of local photochemical activities. The dominant factors behind O3 also varied in different seasons. In spring and autumn, O3 pollution is more likely to occur under high NO2 concentration and high-temperature conditions, while in summer, it is more likely to occur under high-temperature and precipitation-free weather. In winter, NO2 is the dominant factor in O3 formation. Finally, the interpretable RF model is used to predict future O3 concentration based on features provided by Community Multiscale Air Quality (CMAQ) and Weather Research & Forecast (WRF) model, and the simulation performance of CMAQ on O3 concentration is enhanced to a certain extent, improving the prediction of future O3 pollution situations and guiding pollution control.

Consecutive high-performance removal of Cu2+ metal ions and Deltamethrin using multifunctional pyrolysis cuttlebone/cotton fabric nanocomposite

A simple technique was developed for the modification of cotton materials that is inexpensive, environmentally friendly, and very effective. Waste Cotton fabrics (WCFs) are loaded with propolis extract (PE) for Cu2+ removal. Then, Cu2+ underwent a pyrolysis process with modified cuttlebone (CB) at 900 °C for 5 h. The surface of the prepared materials was characterized using X-ray diffraction (XRD), scanning electron microscopy with energy-dispersive X-ray (SEM-EDX), Fourier transform infrared (FTIR), BET, particle sizes, thermogravimetric analysis (TGA) and zeta potential analysis. The Cu2+ metal ions from an aqueous solution were removed using WCFs/PE, and DLM was subsequently removed using pyro WCFs/PE/Cu/CB. The as-prepared NPs exhibited the face-centered cubic structure of WCFs/PE/Cu/CB with crystallite sizes ranging from 386.70 to 653.10 nm. FTIR spectra revealed that CB was present on the surface of the resulting WCFs/PE/Cu. SEM revealed the dispersion of a uniformly flower-like morphology over a large area. Sorption studies were performed based on parameters that included pH, dose, contact time, and initial concentration. The adsorption isotherm and the kinetic studies of the DLM adsorption process were applied at a pH of 5.0 and a temperature of 25 °C using several isotherms and kinetic models. The results revealed qmax (20.51 mg/g) with R2 = 0.97, the Langmuir isotherm that best matches the experimental data. Hence, the Langmuir isotherm suggests that it is the model that best describes sorption on homogenous surfaces or surface-supporting sites with various affinities. The correlation coefficient R2, χ2, adjusted correlation coefficient, and error functions like root mean square (RMSE), normalized root mean square error (NRMES), and mean absolute error (MAE) were used to evaluate the best-fit models to the experimental adsorption data. Moreover, cost estimation for the prepared adsorbent WCFs/PE/Cu showed that it costs approximately 3 USD/g, which is a cheap adsorbent compared to other similar adsorbents reported in the literature. The examined WCFs/PE have significant applicability potential for Cu2+-laden wastewater treatment due to their superior Cu2+ metal ions adsorption capability and reusability.The cytotoxicity and safety study showed that at higher concentrations, it resulted in much less cell viability. Additionally, the removal efficiency of Cu2+ metal ions from synthetic, realistic industrial wastewater using WCFs/PE reached up to 96.29 %, demonstrating good adsorption capability. Thus, there is a huge possibility of accomplishing this and performing well. This study paves the way for the reuse and valorization of selected adsorbents following circular economy principles.Two green metrics were applied, the Analytical Eco-scale and the Analytical GREEnness Calculator (AGREE).

Determine the pharmacokinetics (half-life, volume of distribution and clearance) of AMB-FUBINACA in rats plasma using GC–MS / MS

BackgroundSeveral novel synthetic cannabinoids, including methyl 2-(1-(4-fluorobenzyl)-1Hindazole-3-carboxamido)-3-methylbutanoate (AMB-FUBINACA), have recently surfaced on the illicit drug market. To determine the pharmacokinetic properties (half-life, volume of distribution, and clearance) of AMB-FUBINACA in rats plasma, a straightforward, quick, and highly sensitive analytical approach was developed. MethodsEighteen Wistar rats were divided into two groups: one control (saline vehicle) and one treatment group (AMB-FUBINACA at 50 mg/kg). Blood samples (400 μL) were withdrawn via catheters immediately before (t = 0) and at 30, 60, 90, 120, and 240 min following injection. Samples were collected into 1 mL tuberculin syringes, then transferred to 1.5 mL plastic tubes containing 5 μl of 1000 IU/mL K3-EDTA (Thomas Scientific). Place the EDTA tubes containing samples in a centrifuge and spin at 1000 g for 10 min at 4 °C. The top layer is the plasma fraction, which is decanted into cryovials and stored at −20 °C until analysis. The gas chromatography tandem mass spectrometry (GC–MS/MS) method was optimized and validated, combined with liquid-liquid extraction, to analyze AMB-FUBINACA in rat plasma. ResultsThe research method successfully met the validation requirements set by the FDA, demonstrating selectivity and linear calibration curves within a concentration range of 0.5–1000 ng/ml. The correlation coefficient (r2) was determined to be 0.99, indicating a strong linear relationship. The analyte's limit of quantitation (LOQ) was determined to be 1–5 ng/mL. Subsequently, the method was successfully applied to investigate the pharmacokinetics of AMB-FUBINACA in rats' blood samples. Following oral administration, AMB-FUBINACA was rapidly absorbed, with a plasma half-life (t1/2) of 5.91 h, a volume of distribution (Vd) of 203.13 l, and a plasma clearance of 23.81122 L/h. ConclusionThese findings contribute to the understanding of AMB-FUBINACA's pharmacokinetics and pharmacodynamics.

Per- and polyfluoroalkyl substances (PFAS) exposure in plasma and their blood–brain barrier transmission efficiency–A pilot study

Per- and polyfluoroalkyl substances (PFAS) have been shown to penetrate the blood–brain barrier (BBB) and accumulate in human brain. The BBB transmission and accumulation efficiency of PFAS, as well as the potential health risks from human co-exposure to legacy and emerging PFAS due to differences in transport efficiency, need to be further elucidated. In the present pilot study, 23 plasma samples from glioma patients were analyzed for 17 PFAS. The concentrations of PFAS in six paired brain tissue and plasma samples were used to calculate the BBB transmission efficiency of PFAS (RPFAS). This RPFAS analysis was conducted with utmost care and consideration amid the limited availability of valuable paired samples. The results indicated that low molecular weight PFAS, including short-chain and emerging PFAS, may have a greater potential for accumulation in brain tissue than long-chain PFAS. As an alternative to perfluorooctane sulfonic acid (PFOS), 6:2 chlorinated polyfluorinated ether sulfonate (6:2 Cl-PFESA) exhibited brain accumulation potential similar to that of PFOS, suggesting it may not be a suitable substitute concerning health risk in brain. The BBB transmission efficiencies of perfluorooctanoic acid, PFOS, and 6:2 Cl-PFESA showed similar trends with age, which may be an important factor influencing the entry of exogenous compounds into the brain. A favorable link between perfluorooctane sulfonamide (FOSA) and the development and/or progression of glioma may be implicated by a strong positive correlation (r2 = 0.94; p < 0.01) between RFOSA and Ki-67 (a molecular marker of glioma). However, a causal relationship between RFOSA and glioma incidence were not established in the present study. The present pilot study conducted the first examination of BBB transmission efficiency of PFAS from plasma to brain tissue and highlighted the importance of reducing and/or controlling exposure to PFAS.

Development and Validation of a Novel Surface Defect Index (SDI) Method for the Effective Quality Evaluation of Concrete Surfaces

Concrete defects have a significant impact on concrete constructions. These defects should be considered not only aesthetic defects but also structural defects. In this study, a novel Surface Defect Index (SDI) method was developed to quantify the defect volume according to liquids’ penetrating properties by applying ready-mixed plaster (RMP). The SDI refers to the volumetric proportion of all apparent and unapparent defects in a given area of concrete, and it is expressed as a percentage of the total volume affected by defects. The proposed SDI method was validated and tested under various controlled defect configurations. Regardless of the specific characteristics of each defect configuration, the SDI method consistently demonstrated a high level of consistency, repeatability, and reproducibility, with coefficients of variation (CVr and CVR) below 5% and with correlation coefficients of R2 = 0.9968. The method succeeded in assessing the surface quality levels through the SDI, demonstrating a significant correlation between this index and the volume of defects. The proposed index was tested on real concrete surfaces, affirming its efficacy in accurately quantifying the volume of surface defects; thus, it can provide an important metric for quality control. Moreover, it provides an excellent evaluation of the quality of concrete surfaces.

Online Two-Dimensional Liquid Chromatography for Determination of Selected Flavonoids in Wine Samples

     The development of two-dimensional chromatography systems is crucial in many scientific fields as it provides improved separation efficiency and selectivity of complex mixtures. By separating compounds based on two independent properties, these systems can offer a more detailed understanding of sample composition. This increased level of detail is particularly useful in industries such as pharmaceuticals, environmental analysis, and proteomics, where complex mixtures with similar properties need to be differentiated. A new chromatography system with two dimensions was developed to separate and quantify specific flavonoids in German wine samples. The first dimension used a homemade hydrophilic interaction liquid chromatographic column, while the second dimension used a reversed-phase liquid chromatographic column. This 2D ZIC-HILIC x RP technique was able to address the problem of peak overlapping that commonly occurs in one-dimensional liquid chromatography, especially for natural products. The study presents analytical and statistical data for both techniques, and suggests that the use of two-dimensional chromatography can improve the resolution of conventional one-dimensional liquid chromatography. In a conventional ZIC-HILIC-HPLC system, apigenin and naringenin were detected together but were successfully separated and measured using a 2DLC system. The limits of detection (LOD) for apigenin and naringenin were found to be 0.0705 µg/mL and 0.1300 µg/mL, respectively, while the limits of quantification (LOQ) were 0.2136 µg/mL and 0.3939 µg/mL, respectively. The recovery rate for both compounds was over 99%, with a relative standard deviation (RSD) of less than 1.5%. The linearity range for both compounds was between 0.005 µg/mL to 10 µg/mL, and the correlation coefficient (r2) was determined to be 0.9998. For hesperidin and rutin, the LOD and LOQ were found to be 0.0336 µg/mL and 0.1018 µg/mL, and 0.0120 µg/mL and 0.0363 µg/mL, respectively. The linearity range for both compounds was between 0.005 µg/mL to 12 µg/mL, and the correlation coefficient (r2) was determined to be 0.9999.

Clinical validation of a capnodynamic method for measuring end-expiratory lung volume in critically ill patients

RationaleEnd-expiratory lung volume (EELV) is reduced in mechanically ventilated patients, especially in pathologic conditions. The resulting heterogeneous distribution of ventilation increases the risk for ventilation induced lung injury. Clinical measurement of EELV however, remains difficult.ObjectiveValidation of a novel continuous capnodynamic method based on expired carbon dioxide (CO2) kinetics for measuring EELV in mechanically ventilated critically-ill patients.MethodsProspective study of mechanically ventilated patients scheduled for a diagnostic computed tomography exploration. Comparisons were made between absolute and corrected EELVCO2 values, the latter accounting for the amount of CO2 dissolved in lung tissue, with the reference EELV measured by computed tomography (EELVCT). Uncorrected and corrected EELVCO2 was compared with total CT volume (density compartments between − 1000 and 0 Hounsfield units (HU) and functional CT volume, including density compartments of − 1000 to − 200HU eliminating regions of increased shunt. We used comparative statistics including correlations and measurement of accuracy and precision by the Bland Altman method.Measurements and main resultsOf the 46 patients included in the final analysis, 25 had a diagnosis of ARDS (24 of which COVID-19). Both EELVCT and EELVCO2 were significantly reduced (39 and 40% respectively) when compared with theoretical values of functional residual capacity (p < 0.0001). Uncorrected EELVCO2 tended to overestimate EELVCT with a correlation r2 0.58; Bias − 285 and limits of agreement (LoA) (+ 513 to − 1083; 95% CI) ml. Agreement improved for the corrected EELVCO2 to a Bias of − 23 and LoA of (+ 763 to − 716; 95% CI) ml. The best agreement of the method was obtained by comparison of corrected EELVCO2 with functional EELVCT with a r2 of 0.59; Bias − 2.75 (+ 755 to − 761; 95% CI) ml. We did not observe major differences in the performance of the method between ARDS (most of them COVID related) and non-ARDS patients.ConclusionIn this first validation in critically ill patients, the capnodynamic method provided good estimates of both total and functional EELV. Bias improved after correcting EELVCO2 for extra-alveolar CO2 content when compared with CT estimated volume. If confirmed in further validations EELVCO2 may become an attractive monitoring option for continuously monitor EELV in critically ill mechanically ventilated patients.Trial registration: clinicaltrials.gov (NCT04045262).

Pengaruh Harga dan Kualitas Pelayanan Terhadap Minat Beli Konsumen pada Pakaian Distro di Bandar Lampung

Business actors in the clothing distribution industry must pay attention to the needs, desires, and expectations of consumers in order to cultivate strong purchasing interest. Therefore, effective strategies are required to attract consumers' interest in purchasing clothing products at distros. This study aims to empirically examine the influence of price and service quality on the buying interest of consumers purchasing distro clothing in Bandar Lampung. A quantitative approach was employed, with the population consisting of clothing consumers in the city of Bandar Lampung. The accidental sampling technique was utilized to select samples, with 96 consumer respondents who purchased distro clothing in the city of Bandar Lampung. Data were collected through various methods, including literature review, documentation, observation, interviews, and questionnaires. Data analysis was conducted using multiple linear regression tests, correlation coefficient tests, t tests, F tests, and R² tests. The results showed that price and service quality significantly influence the buying interest of consumers at distro clothing stores in Bandar Lampung. Together, these variables also significantly influence consumers' buying interest. The simultaneous F test results indicated that price and service quality together significantly influence consumers' buying interest at distro clothing stores in Bandar Lampung, with price and service quality contributing 26.9% to consumers' buying interest at distro clothing stores in Bandar Lampung.

A Design Method for an SVM-Based Humidity Sensor for Grain Storage.

One of the crucial factors in grain storage is appropriate moisture content, which plays a significant role in reducing storage losses and ensuring quality. However, currently available humidity sensors on the market fail to meet the demands of modern large-scale grain storage in China in terms of price, size, and ease of implementation. Therefore, this study aims to develop an economical, efficient, and easily deployable grain humidity sensor suitable for large-scale grain storage environments. Simultaneously, it constructs humidity calibration models applicable to three major grain crops: millet, rice, and wheat. Starting with the probe structure, this study analyzes the ideal probe structure for grain humidity sensors. Experimental validations are conducted using millet, rice, and wheat as experimental subjects to verify the accuracy of the sensor and humidity calibration models. The experimental results indicate that the optimal length of the probe under ideal conditions is 0.67 m. Humidity calibration models for millet, rice, and wheat are constructed using SVM models, with all three models achieving a correlation coefficient R2 greater than 0.9. The measured data and model-calculated data show a linear relationship, closely approximating y = x, with R2 values of all three fitted models above 0.9. In conclusion, this study provides reliable sensor technological support for humidity monitoring in large-scale grain storage and processing, with extensive applications in grain storage and grain safety management.

Vortex-assisted dispersive micro-solid-phase extraction using silica-supported Fe2O3-modified khat (Catha edulis) biochar nanocomposite followed by GC-MS for the determination of organochlorine pesticides in juice samples

In this paper, dispersive micro-solid phase extraction technique was developed for the purpose of extracting and preconcentrating organochlorine pesticide residues in juice samples before their separation and quantitative analysis by gas chromatography-mass spectrometry. A sorbent composed of a silica-supported Fe2O3-modified khat leftover biochar nanocomposite (SiO2-Fe2O3-KLBNC) was implemented in the process. To improve the dispersion of the sorbent in the solution, vortex mixer was employed. Experimental parameters influencing the performance of the method were optimized, and the optimal conditions were established. With these conditions, linear dynamic ranges ranged from 0.003 to 100.0 ng/mL were achieved, with a correlation coefficient (r2) ≥ 0.9981. The limits of detection and quantification, determined by signal-to-noise ratios of 3 and 10, respectively, were found to be in the ranges of 0.001–0.006 ng/mL and 0.003–0.020 ng/mL. Intra- and inter-day precision, values ranging from 0.3–4.8% and 1.7–5.2% were obtained, respectively. The matrix-matched extraction recoveries demonstrated favorable outcomes, falling within the range of 83.4–108.3%. The utilization of khat leftover as an adsorbent in contemporary sample preparation methodologies offers a cost-effective alternative to the currently available, yet expensive, adsorbents. This renders it economically viable, particularly in resource-constrained regions, and is anticipated to witness widespread adoption in the coming future.

Length-weight relationships and biometry analysis of saddled seabream, Oblada melanurus (Linnaeus, 1758) in İzmir Bay (Central Aegean Sea of Türkiye)

The present study presents length-weight, length-length, length-girth relationships, and biometry of male and female specimens of saddled seabream, Oblada melanurus(Linnaeus, 1758), in the Turkish Aegean Sea. The length-length and length-weight relationships were calculated by measuring 516 individuals. The total length values of all male and female O. melanurus specimens were in the range of 17.2-30.7 and 18.5-30.0 cm, respectively, and the mean values were 21.84±2.04 and 22.44±2.12 cm, respectively. The length-weight relationships were W=0.0110TL3.057 for males, W=0.0114TL3.043 for females, and W=0.0089TL3.122 for all the specimens. The results denoted a high correlation (r²=0.966; p&lt;0.001) in the length-length relationships. Furthermore, 287 individuals (105 females and 182 males) were examined for length-girth relationships and biometric analyses. Ten morphometric characters were analyzed to analyze biometry. In conclusion, no statistically significant differences were determined in morphology between the sexes (p&lt;0.05).