Fully connected-convolutional (FC-CNN) neural network based on hyperspectral images for rapid identification of P. ginseng growth years.

P. ginseng is a precious traditional Chinese functional food, which is used for both medicinal and food purposes, and has various effects such as immunomodulation, anti-tumor and anti-oxidation. The growth year of P. ginseng has an important impact on its medicinal and economic values. Fast and nondestructive identification of the growth year of P. ginseng is crucial for its quality evaluation. In this paper, we propose a FC-CNN network that incorporates spectral and spatial features of hyperspectral images to characterize P. ginseng from different growth years. The importance ranking of the spectra was obtained using the random forest method for optimal band selection. Based on the hyperspectral reflectance data of P. ginseng after radiometric calibration and the images of the best five VNIR bands and five SWIR bands selected, the year-by-year identification of P. ginseng age and its identification experiments for food and medicinal purposes were conducted, and the FC-CNN network and its FCNN and CNN branch networks were tested and compared in terms of their effectiveness in the identification of P. ginseng growth years. It has been experimentally verified that the best year-by-year recognition was achieved by utilizing images from five visible and near-infrared important bands and all spectral curves, and the recognition accuracy of food and medicinal use reached 100%. The FC-CNN network is significantly better than its branching model in the effect of edible and medicinal identification. The results show that for P. ginseng growth year identification, VNIR images have much more useful information than SWIR images. Meanwhile, the FC-CNN network utilizing the spectral and spatial features of hyperspectral images is an effective method for the identification of P. ginseng growth year.

Understanding the processes, practices and influences of calibration on feedback literacy in higher education marking: A qualitative study.

BACKGROUND: In the University setting, striving for consistency and reliability of assessment evaluation is essential to reducing the impact of marking variations. Marking processes such as consensus calibration have the potential to reduce issues which arise from the influence of markers professional knowledge and experience, as well as fixed and acquired marking habits. Furthermore, the influence of marker feedback which supports learning development is associated with the feedback literacy of both the teacher and the student. A gap is currently present in the literature as these practices are not discussed together. OBJECTIVES: To explore how nursing academics perceive and understand calibration practices and associated feedback literacy. DESIGN: Theoretical underpinnings in participatory and person-centred research methodology supported the critical ontological perspective of this study where the intent of the research was to explore the reality that exists within the context where the research was conducted. SETTING: A single School of Nursing in an Australian University with six campuses spanning metropolitan, regional and rural sites. PARTICIPANTS: Nursing academics and casual tutors with various levels of experience in assessment marking and feedback. METHODS: Semi-structured group interviews that were analysed using reflexive thematic analysis. RESULTS: Four overarching themes were identified; rubrics, calibration, feedback and justice. CONCLUSION: Calibration improves staff cohesion, fosters better practices and consistency, and permits nuanced interpretation of assessments while maintaining uniformity. Enhanced feedback literacy that integrates principles of equity, justice, and learner-centeredness is required. Fundamentally calibration guides educators toward holistic approaches that foster consistency, equity, and thorough feedback practices.

MEMS strapdown inertial attitude measurement system using rotational modulation technology.

Attitude determination involves the integration of methodologies and systems for estimating the time varying attitude of moving objects. Strapdown Inertial Attitude Measurement System (SIAMS) is among the most widely used navigation systems. The development of cost effective Micro Electro Mechanic System (MEMS) based inertial sensors has made attitude measurement system more affordable. However, MEMS sensors suffer from various errors that have to be calibrated and compensated to get acceptable attitude results. Given the auto-compensation of inertial sensor bias in rotation error modulation, the objective of this paper is to develop a MEMS-based rotary SIAMS, in which the significant sensor bias is automatically compensated by rotating the IMU, to offer comparable performance with respect to a tactical-grade Inertial Measurement Unit (IMU). With the analysis of the relationship between the MEMS error and misalignment, a MEMS calibration model is derived, and a combined calibration method of multi position rotation is applied to estimate the deterministic sensor errors such as bias, scale factor, and misalignment. Simulation and experiment results indicate that the proposed method can further modulate and compensate the MEMS errors, thereby improving the MEMS attitude accuracy.

Rapid screening and evaluation of natural antioxidants from leaf, stem, and root of Artemisia argyi by online liquid microextraction combined with HPLC-based antioxidant assay system coupled with calibration quantitative analysis.

To reveal the utilization value of leaf, stem, and root of Artemisia argyi, a rapid online liquid microextraction combined with a high-performance liquid chromatography coupled with 2,2-nitrogen-di (3-ethyl-benzothiazole-6-sulfonic acid) diammonium salt antioxidant assay system was established for analysis of antioxidants in the leaf, stem, and root of A. argyi, and a calibration quantitative method of antioxidant activity with equivalent chlorogenic acid was proposed. Thirty-three positive peaks were identified; among them, 12 compounds were found that possess good antioxidant activity including eleven organic acids (components 2-4, 8, 11-14, 17, 19, and 21) and one flavonoids (component 22). The proposed calibration quantitative method avoided the influence of content of compound and compared the extent of radical scavenging capacity of five antioxidant compounds, which were ranked as follow: 3,5-dicaffeoylquinic acid > 3,4-dicaffeoylquinic acid ≈ 4,5-dicaffeoylquinic acid > 1,4-dicaffeoylquinic acid > chlorogenic acid. In conclusion, this study provided composition and biological potential for the future development of the leaf, stem, and root of A. argyi. It is believed that the online liquid microextraction combined with high-performance liquid chromatography based antioxidant assay system can be widely used for the rapid screening of natural antioxidant components in the different parts of natural products.

A Simple UV Spectrophotometric Method Based on Continuous Wavelet Transform and Multivariate Calibration Model for the Concurrent Analysis of Three Water-Soluble Vitamins in Fertility Supplements.

BACKGROUND: Owing to the presence of overlapping spectra in pharmaceutical components, classical spectrophotometry is hard for concurrent determination. The advance of chemometrics along with UV-Vis spectrophotometry has contributed to solving this problem. OBJECTIVE: In this study, a fast, easy, precise, accurate, low-cost, and eco-friendly spectrophotometric technique was introduced and validated for the simultaneous analysis of vitamin B6, vitamin B12, and vitamin C in fertility supplements for men and women using continuous wavelet transform (CWT) and partial least squares (PLS) techniques without using time-consuming extraction process and organic solvents. METHOD: In the CWT method, the zero-crossing technique was applied to obtain the optimum points for plotting calibration curves for each component. The validation of both methods was evaluated by analyzing several mixtures with different concentrations. The efficiency of the proposed methods was also surveyed on commercial capsules. RESULTS: Wavelet families, including Symlet (sym2) at 230, Biorthogonal (bior1.3) at 378 nm, and Daubechies (db2) at 261, were considered for vitamins B6, B12, and C, respectively. The linear range was found to be 8-20, 8-20, and 10-25 µg/mL with the coefficient of determination (R2) equal to 0.9982, 0.9978, and 0.9701 for B6, B12, and C, respectively. Low limit of detection (LOD) (<0.09 µg/mL) and limit of quantification (LOQ) <0.9 µg/mL were achieved. The mean recovery values in synthetic mixtures were from 98.38 to 98.89% and from 99.83 to 99.99%, where root-mean-square error (RMSE) of not more than 0.4 and 0.05 using the CWT and PLS methods, respectively. CONCLUSIONS: The obtained results from the commercial capsules, applying the suggested techniques, were compared to those yielded by the high-performance liquid chromatography (HPLC) method using the analysis of variance (ANOVA) test. According to the results, there are no significant differences, and they were in good agreement. According to all the mentioned cases, the proposed approaches can replace the time-consuming and costly HPLC method in quality control laboratories. HIGHLIGHTS: Green spectrophotometry coupling chemometrics methods were proposed. Simultaneous determination of three water-soluble vitamins in fertility supplements was done using these approaches. Rapidity, simplicity, low cost, and accuracy are the benefits of the proposed methods. A HPLC technique was used as a reference method to compare with the chemometrics methods.

National Survey of the Bone Densitometry Evaluation Process Within an Integrated Healthcare System.

BACKGROUND: To assess the current state of bone mineral density evaluation services via dual energy x-ray absorptiometry (DXA) provided to Veterans with fracture risk through the development and administration of a nationwide survey of facilities in the Veterans Health Administration. METHODOLOGY: The Bone Densitometry Survey was developed by convening a Work Group of individuals with expertise in bone densitometry and engaging the Work Group in an iterative drafting and revision process. Once completed, the survey was beta tested, administered through REDCap, and sent via e-mail to points of contact at 178 VHA facilities. RESULTS: Facility response rate was 31 % (56/178). Most DXA centers reported positively to markers of readiness for their bone densitometers: less than 10 years old (n=35; 63 %); in "excellent" or "good" condition (n=44; 78 %, 32 % and 46 %, respectively); and perform phantom calibration (n=43; 77 %). Forty-one DXA centers (73 %) use intake processes that have been shown to reduce errors. Thirty-seven DXA centers (66 %) reported their technologists receive specialized training in DXA, while 14 (25 %) indicated they receive accredited training. Seventeen DXA centers (30 %) reported performing routine precision assessment. CONCLUSIONS: Many DXA centers reported using practices that meet minimal standards for DXA reporting and preparation; however, the lack of standardization, even within an integrated healthcare system, indicates an opportunity for quality improvement to ensure consistent high quality bone mineral density evaluation of Veterans.

[Discrete element simulation study of mixing process of Guizhi Fuling Capsules: parameter calibration].

The mixing process is a critical link in the formation of oral solid preparations of traditional Chinese medicine. This paper took the extract powder of Guizhi Fuling Capsules and Paeonol powder as research objects. The angle of repose, loose packing density, and particle size of the two powders were measured to calibrate discrete element simulation parameters for the mixing process. The discrete element method was used to calibrate the simulated solid density of Paeonol powder and extract powder of Guizhi Fuling Capsules based on the Hertz-Mindlin with JKR V2 contact model and particle scaling. The Plackett-Burman experimental design was used to screen out the critical contact parameters that had a significant effect on the simulation of the angle of repose. The regression model between the critical contact parameters and the simulated angle of repose was established by the Box-Behnken experimental design, and the critical contact parameters of each powder were optimized based on the regression model. The best combination of critical contact parameters of the extract powder of Guizhi Fuling Capsules was found to be 0.51 for particle-particle static friction coefficient, 0.31 for particle-particle rolling friction coefficient, and 0.64 for particle-stainless steel static friction coefficient. For Paeonol powder, the best combination of critical contact parameters was 0.4 for particle-particle static friction coefficient and 0.19 for particle-particle rolling friction coefficient. The best combination of contact parameters between Paeonol powder and extract powder of Guizhi Fuling Capsules was 0.27 for collision recovery coefficient, 0.49 for static friction coefficient, and 0.38 for rolling friction coefficient. The verification results show that the relative error between the simulated value and the measured value of the angle of repose of the two single powders is less than 1%, while the relative error between the simulated value and the measured value of the angle of repose of the mixed powder with a mass ratio of 1∶1 is less than 4%. These research results provide reliable physical property simulation data for the mixed simulation experiment of extract powder of Guizhi Fuling Capsules and Paeonol powder.

Understanding calibration of deep neural networks for medical image classification.

Background and Objective - In the field of medical image analysis, achieving high accuracy is not enough; ensuring well-calibrated predictions is also crucial. Confidence scores of a deep neural network play a pivotal role in explainability by providing insights into the model's certainty, identifying cases that require attention, and establishing trust in its predictions. Consequently, the significance of a well-calibrated model becomes paramount in the medical imaging domain, where accurate and reliable predictions are of utmost importance. While there has been a significant effort towards training modern deep neural networks to achieve high accuracy on medical imaging tasks, model calibration and factors that affect it remain under-explored. Methods - To address this, we conducted a comprehensive empirical study that explores model performance and calibration under different training regimes. We considered fully supervised training, which is the prevailing approach in the community, as well as rotation-based self-supervised method with and without transfer learning, across various datasets and architecture sizes. Multiple calibration metrics were employed to gain a holistic understanding of model calibration. Results - Our study reveals that factors such as weight distributions and the similarity of learned representations correlate with the calibration trends observed in the models. Notably, models trained using rotation-based self-supervised pretrained regime exhibit significantly better calibration while achieving comparable or even superior performance compared to fully supervised models across different medical imaging datasets. Conclusion - These findings shed light on the importance of model calibration in medical image analysis and highlight the benefits of incorporating self-supervised learning approach to improve both performance and calibration.

Rapid and Versatile Biosensing of Liposome Encapsulation Efficiency Using Electrical Conductivity Sensor.

Liposomes are prominent nanosystems for drug delivery, with potential extending beyond isolated drugs. Ethanol-aqueous plant extracts can be encapsulated within liposomes to protect bioactive compounds (secondary metabolites) from rapid oxidation and enable sustained release. Determining which compound classes are present in each extract and the encapsulation efficiency (EE) of these extracts in liposomes is crucial for nanocarrier functionality. This involves assessing the ratio of bioactive substances within liposomes to the total content. However, quantifying EE for non-isolated compounds poses challenges due to the need for advanced analytical equipment and biosensing approaches. This study introduces an innovative method for EE quantification, using a conductivity electrode (k = 0.842/cm) to establish an EE biosensing technology. By correlating dynamic light scattering (DLS), zeta potential (ZP), and electrical conductivity (Cnd) data with the conductivity meter's calibration curve, a robust relationship between the free extract concentration and Cnd (r2 ≥ 0.950) was established. Lavender-loaded liposomes demonstrated an EE of 56.33%, while wormwood and oregano formulations exhibited high EEs of 94.33% and 91.70%, respectively. In contrast, sage-loaded liposomes exhibited an inadequate EE, encapsulating only approximately 0.57% of the extract. The straightforward quantification of the free extract within liposome formulations, compared to more complex approaches, could facilitate EE determination and support future characterizations.

A Novel Evaluation Method for SLAM-Based 3D Reconstruction of Lumen Panoramas.

Laparoscopy is employed in conventional minimally invasive surgery to inspect internal cavities by viewing two-dimensional images on a monitor. This method has a limited field of view and provides insufficient information for surgeons, increasing surgical complexity. Utilizing simultaneous localization and mapping (SLAM) technology to reconstruct laparoscopic scenes can offer more comprehensive and intuitive visual feedback. Moreover, the precision of the reconstructed models is a crucial factor for further applications of surgical assistance systems. However, challenges such as data scarcity and scale uncertainty hinder effective assessment of the accuracy of endoscopic monocular SLAM reconstructions. Therefore, this paper proposes a technique that incorporates existing knowledge from calibration objects to supplement metric information and resolve scale ambiguity issues, and it quantifies the endoscopic reconstruction accuracy based on local alignment metrics. The experimental results demonstrate that the reconstructed models restore realistic scales and enable error analysis for laparoscopic SLAM reconstruction systems. This suggests that for the evaluation of monocular SLAM three-dimensional (3D) reconstruction accuracy in minimally invasive surgery scenarios, our proposed scheme for recovering scale factors is viable, and our evaluation outcomes can serve as criteria for measuring reconstruction precision.

Innovative receiving phase for Chemcatcher® passive sampler for phosphorus in the water environment: Calibration of sampling rate by water temperature and pH.

Passive sampling is a technique for monitoring orthophosphate (PO4-P) in the water environment. Compared with traditional grab sampling followed by PO4-P quantification, kinetic-type passive samplers such as Chemcatcher® express representative concentrations of PO4-P as time-weighted average concentrations (CTWA). They can also potentially evaluate much lower PO4-P concentrations, but the available receiving phases of Chemcatcher® used for PO4-P were extremely limited. We developed a new receiving phase, the PSfZS sheet, comprising a zirconium sulfate-surfactant micelle mesostructure and polysulfone matrix. We examined its performance in terms of PO4-P sorption characteristics, PO4-P selectivity, and PO4-P sampling rate (Rs). Its capacity was adequate (12.0 µg-P/cm2) and selectivity for PO4-P uptake was good. The Rs for PO4-P increased with increasing water temperature (8.1-29.1 °C) and decreasing pH (4.1-9.7) in a laboratory calibration, and ranged from 5.27 × 10-2 L/d to 1.66 × 10-1 L/d. We placed the samplers in a municipal wastewater treatment plant, a shallow eutrophic lake, and an oligotrophic caldera lake. The Rs in the deployment sites was calibrated by monitored water temperature and pH. The estimated CTWA of PO4-P in the municipal wastewater treatment plant was similar to the averaged concentration of soluble reactive phosphorus determined by multiple grab samplings. In the lake deployments, we found that the new sampler can quantify CTWA values of PO4-P below 10 µg/L, and thus it provides more technical monitoring options and contributes to the conservation and management of the water environment.

Measuring PROMIS pain interference in German patients with chronic conditions: calibration, validation, and cross-cultural use of item parameters.

PURPOSE: To calibrate the item parameters of the German PROMIS® Pain interference (PROMIS PI) items using an item-response theory (IRT) model and investigate psychometric properties of the item bank. METHODS: Forty items of the PROMIS PI item bank were collected in a convenience sample of 660 patients, which were recruited during inpatient rheumatological treatment or outpatient psychosomatic medicine visits in Germany. Unidimensionality, monotonicity, and local independence were tested as required for IRT analyses. Unidimensionality was examined using confirmatory factor analyses (CFA) and exploratory factor analysis (EFA). Unidimensional and bifactor graded-response IRT models were fitted to the data. Bifactor indices were used to investigate whether multidimensionality would lead to biased scores. To evaluate convergent and discriminant validity, the item bank was correlated with legacy pain instruments. Potential differential item functioning (DIF) was examined for gender, age, and subsample. To investigate whether U.S. item parameters may be used to derive T-scores in German patients, T-scores based on previously published U.S. and newly estimated German item parameters were compared with each other after adjusting for sample specific differences. RESULTS: All items were sufficiently unidimensional, locally independent, and monotonic. Whereas the fit of the unidimensional IRT model was not acceptable, a bifactor IRT model demonstrated acceptable fit. Explained common variance and Omega hierarchical suggested that using the unidimensional model would not lead to biased scores. One item demonstrated DIF between subsamples. High correlations with legacy pain instruments supported construct validity of the item bank. T-scores based on U.S. and German item parameters were similar suggesting that U.S. parameters could be used in German samples. CONCLUSION: The German PROMIS PI item bank proved to be a clinically valid and precise instrument for assessing pain interference in patients with chronic conditions.

On-line monitoring of total sugar during kombucha fermentation process by near-infrared spectroscopy: Comparison of linear and non-linear multiple calibration methods.

Kombucha is widely recognized for its health benefits, and it facilitates high-quality transformation and utilization of tea during the fermentation process. Implementing on-line monitoring for the kombucha production process is crucial to promote the valuable utilization of low-quality tea residue. Near-infrared (NIR) spectroscopy, together with partial least squares (PLS), backpropagation neural network (BPANN), and their combination (PLS-BPANN), were utilized in this study to monitor the total sugar of kombucha. In all, 16 mathematical models were constructed and assessed. The results demonstrate that the PLS-BPANN model is superior to all others, with a determination coefficient (R2p) of 0.9437 and a root mean square error of prediction (RMSEP) of 0.8600 g/L and a good verification effect. The results suggest that NIR coupled with PLS-BPANN can be used as a non-destructive and on-line technique to monitor total sugar changes.

Unintentional macular injury following high-energy cosmetic laser calibration.

Unwelcome hair has become a significant issue encountered in our society by young people, particularly young women. Hair removal has been achieved through various methods, both mechanical, with intense pulse light therapy and laser photoablation of hair follicles using various energy delivery systems. There is a relative paucity of clinical trials comparing the safety and efficacy of various hair removal modalities. A comparative study between alexandrite, diode, and intense pulsed light (IPL) was conducted and found similar safety profile across all three modalities. Several adverse effects have been noted as a result of this therapy. Laser-assisted hair removal can lead to ocular anterior segment and/or retinal injury. A laser beam directed toward the eye may easily penetrate both the eyelid or the cornea and cause catastrophic ocular injury. Unfortunately, regulation and licensing of the use of laser-assisted hair removal devices has not yet been well elucidated nor standardized across Australia. There are few cases in the literature reporting retinal burns following inadvertent laser injury, with even fewer directly involving the macula. We report a case of unilateral anterior uveitis and a macular defect following inadvertent laser exposure, leading to photophobia and pain, and reduced visual acuity.

Calibration of an acute toxicity model for the marine crustacean, Artemia franciscana, nauplii to support oil spill effect assessments.

Oil spill risk and impact assessments rely on time-dependent toxicity models to predict the hazard of the constituents that comprise crude oils and petroleum substances. Dissolved aromatic compounds (ACs) are recognized as a primary driver of aquatic toxicity in surface spill exposure scenarios. However, limited time-dependent toxicity data are available for different classes of ACs to calibrate such models. This study examined the acute toxicity of 14 ACs and 3 binary AC mixtures on Artemia franciscana nauplii at 25 °C. Toxicity tests for 3 ACs were also conducted at 15 °C to evaluate the role of temperature on toxicity. The ACs investigated represented parent and alkylated homocyclic and nitrogen-, sulfur- and oxygen-containing heterocyclic structures with octanol-water partition coefficients (log Kow) ranging from 3.2 to 6.6. Passive dosing was used to expose and maintain concentrations in toxicity tests which were confirmed using fluorometry, and independently validated for 6 ACs using GC-MS analysis. Mortality was assessed at 6, 24, and 48 h to characterize the time course of toxicity. No mortality was observed for the most hydrophobic AC tested, 7,12-dimethylbenz[a]anthracene, due to apparent water solubility constraints. Empirical log LC50 s for the remaining ACs were fit to a linear regression with log Kow to derive a critical target lipid body burden (CTLBB) based on the target lipid model. The calculated 48 h CTLBB of 47.1 ± 8.1 µmol/g octanol indicates that Artemia nauplii exhibited comparable sensitivity to other crustaceans. A steep concentration-response was found across all compounds as evidenced by a narrow range (1.0-3.1) in the observed LC50 /LC10 ratio. Differences in toxicokinetics were noted, and no impacts of temperature-dependence of AC toxicity were found. Toxicity data obtained for individual ACs yielded acceptable predictions of observed binary AC mixture toxicity. Results from this study advance toxicity models used in oil spill assessments.

EEG changes during passive movements improve the motor imagery feature extraction in BCIs-based sensory feedback calibration.

Objective.This work proposes a method for two calibration schemes based on sensory feedback to extract reliable motor imagery (MI) features, and provide classification outputs more correlated to the user's intention.Method.After filtering the raw electroencephalogram (EEG), a two-step method for spatial feature extraction by using the Riemannian covariance matrices (RCM) method and common spatial patterns is proposed here. It uses EEG data from trials providing feedback, in an intermediate step composed of bothkth nearest neighbors and probability analyses, to find periods of time in which the user probably performed well the MI task without feedback. These periods are then used to extract features with better separability, and train a classifier for MI recognition. For evaluation, an in-house dataset with eight healthy volunteers and two post-stroke patients that performed lower-limb MI, and consequently received passive movements as feedback was used. Other popular public EEG datasets (such as BCI Competition IV dataset IIb, among others) from healthy subjects that executed upper-and lower-limbs MI tasks under continuous visual sensory feedback were further used.Results.The proposed system based on the Riemannian geometry method in two-steps (RCM-RCM) outperformed significantly baseline methods, reaching average accuracy up to 82.29%. These findings show that EEG data on periods providing passive movement can be used to contribute greatly during MI feature extraction.Significance.Unconscious brain responses elicited over the sensorimotor areas may be avoided or greatly reduced by applying our approach in MI-based brain-computer interfaces (BCIs). Therefore, BCI's outputs more correlated to the user's intention can be obtained.

NIR quantitative model trans-scale calibration from small scale to pilot scale via directed DOSC-SBC algorithm.

In order to solve the problem of inapplicability of NIR quantitative models due to the large difference between the modeling samples and the samples to be tested, Directed DOSC-SBC（DDOSC-SBC）algorithm is proposed in this paper based on Direct Orthogonal Signal Correction combined with Slope/Bias Correction (DOSC-SBC) algorithm. To obtain the suitable spectral matrix transfer parameters for the test set during DDOSC spectral preprocessing, several representative test samples in the test set were selected, then the spectral systematic errors between the modeling set and the test set were corrected with the SBC method in order to realize the trans-scale prediction of the NIR quantitative model. NIR data and the critical quality attributes（CQAs）were detected in the small scale and pilot scale pharmaceutical process of the fluidized bed granulation of dextrin and water extraction of honeysuckle. After the small scale model was calibrated via the directed DOSC-SBC algorithm which was guided by representative pilot scale samples, the small scale model was able to predict the pilot scale test samples more accurately. The NIR quantitative model trans-scale calibration from small scale to pilot scale was also successfully realized with a RPD value higher than 3.5 and RSEP value lower than 10%. DDOSC-SBC algorithm is a successful model trans-scale calibrated method that can be applied to NIR real-time monitoring of CQAs in the preparation process of Chinese herbal medicine.

Extended high-frequency bone conduction audiometry Calibration of bone conductor transducers in the conventional and extended high-frequency range.

OBJECTIVE: To monitor ototoxicity, air conduction (AC) extended high frequency (EHF) thresholds can be measured up to 16 kHz. However, conductive hearing loss might influence these results. This is unfortunate because the EHF thresholds are important to follow the impact of ototoxic medication during therapy. Therefore a suitable bone conduction (BC) transducer and norm values for EHF BC measurements are needed. DESIGN: In this study three different BC transducers were used: the B71 (Radioear), the KH70 (Präcitronic), and the KLH96 (Westra). Hearing thresholds were measured from 0.125 to 16 kHz using AC transducers (Telephonics TDH39, Sennheiser HDA200), and BC thresholds from 0.25 to 8 kHz with the B71, and from 0.25 to 16 kHz with the KLH96 and KH70. STUDY SAMPLE: 60 ears of 30 normal hearing subjects were measured. RESULTS: The KLH96 showed the highest output for the high frequencies, and distortion measurements were similar to the KH70. The results show that EHF measurements are possible using the KLH96 and KH70 bone conductors. CONCLUSION: EHF BC measurements are reliable when using the KLH96 and KH70 bone conductors. The extended force sensitivity of the used artificial mastoid should be determined for a proper EHF BC calibration.

Method of reference samples preparation for X-ray fluorescence analysis.

The study focuses on the development of a new procedure for the preparation of reference samples with a given concentration for X-ray fluorescence analysis by adding certain volume of analyzed elements solutions with a known concentration to certified reference rock materials and further fusion with borate fluxes. The presented method of preparing emitters allows not only to obtain samples with the required concentrations for the elements to be determined, but also to preserve the influence that other elements have on the analytical signal. A set of 12 certified reference samples of rocks was used to construct calibration dependencies. The preparation of multicomponent modified reference samples (MRS) was carried out on the basis of certified reference materials (CRM) included in the set for constructing calibration curves. The concentration dependences on the analytical signal were established for the main oxides (SiO2, TiO2, Al2O3, TFe2O3, MnO, MgO, CaO, Na2O, K2O, P2O5) and minor elements (Cr, Cu, Ba, Ni, Sr, V, Zr, and Zn) using an X-ray fluorescence spectrometer with wavelength dispersion. With the help of modified reference samples, the calibration curves were expanded and supplemented both for major oxides (P2O5, MnO) and for minor elements (Zn, Sr). Also, in the course of the research, a comparison was made of the homogeneity of the emitters obtained according to the MRS preparation procedure presented in the work and reference samples (RS) made of CRM prepared according to the standard method for rocks, and the composition of inclusions on the surface of the fused disks was determined.

Colorimetric determination of peroxide value in vegetable oils using a paper based analytical device.

Peroxide value (PV) is one of the most typically used quality parameters to monitor lipid oxidation. Here, a simple paper-based analytical device (PAD) has been developed to determine PV in vegetable oils. The analysis is based on setting up the iodometric titration, where hydroperoxides in the oil are reacted with excess iodide ions to generate iodine molecules, on the paper substrate. The device is composed of two paper layers acting as reaction and detection zones, aligned in a metallic mold. A well-defined inverse logarithmic calibration curve was established between the measured PV by the official iodometric method (ISO;3960, 2017) and the color intensity of PAD. It offered a working range of 0.01-30.0 meq/Kg. The limit of detection of 0.015 meq/Kg demonstrated enough sensitivity of the method to estimate peroxide value in edible oils. On-site and visual detection, low cost, simplicity, and less solvent consumption are advantages of the proposed device.