Method For Quantitative Assessment Research Articles

Development of a method for computer processing of fractographic images to assess the cohesion of inclusions to the matrix in the weld metal after its operational degradation and hydrogenation

In this paper, the method for automated processing of digital fractographic SEM images based on the modified local Otsu approach was developed. The effectiveness of the developed method was demonstrated. The method is used to identify inclusions or their traces at the bottom of dimples in weld metal fractures with subsequent assessment of their quantity. It is assumed that a decrease in the cohesion of inclusions to the matrix is one of the signs of damage to the weld metal at the microstructural level. Consequently, the more inclusions were found at the bottom of ductile fracture dimples, the stronger their connection with the matrix and, accordingly, the less damage in the weld metal. The effect of operational degradation of the weld metal on a circumferential weld on thick pipes of thermal power plant steam pipelines is analyzed. For this purpose, the features of cohesion of inclusions with the matrix in the weld metal in the initial state and after operation on the main steam pipeline for 23 years were compared. The influence of hydrogen (absorbed by the weld metal during long-term operation, as well as during its additional electrolytic charging) on the cohesion of inclusions in its structure with the surrounding matrix is also considered. A decrease in cohesion between these two components of the weld metal structure under the influence of all analized factors is shown. Thus, a method for quantitative assessment of fractographic features caused by the decohesion of inclusions from the matrix developed on the basis of analysis and computer processing of scanning electron microscope images, can be used to assess the operational damage of the weld metal at the microscopic level.

Investigation of Quantitative Assessment Techniques for Supply-Regulation Capability in Multi-Scenario New-Type Power Systems

This paper offers an in-depth investigation into various quantitative assessment methods used to quantify the supply regulation capacity in new types of power systems under different conditions. As new forms of energy, including renewables, are increasingly becoming the predominant sources of power systems, the traditional systems are undergoing transformative modifications to efficiently address the issue of power generation and consumption fluctuations. In this regard, this paper proposes an original framework that combines advanced statistical methods and machine learning. The primary purpose of the framework is to identify the level of resilience and flexible adaptability of new power systems. The paper presents the results of the simulations and real-world applications of the proposed measurement methods in enhancing power supply reliability and efficiency in all conditions. The implications based on the results will be beneficial to policymakers and other specialists who are making decisions involving designing and optimizing modern power systems. Furthermore, the paper aims to contribute to the existing discussion by providing further insights into the effectiveness of the proposed methods of measurement.

Iron overload syndrome. Ethiopatogenesis. magnetic resonance imaging techniques for quantitative assessment of iron overload status: a review

INTRODUCTION: The development of iron overload syndrome may be due to both hereditary and acquired factors. The danger of this condition is manifested in the irreversible loss of parenchymatous pool as a result of cirrhotic transformation and marked fibrosis, caused by the consequent accumulation of iron complexes, of such important internal organs as the liver and heart. The amount of iron in the body is assessed by detecting serum ferritin concentration or by measuring liver and heart iron concentration by biopsy (LIC — liver iron concentration; HIC — heart iron concentration). Insufficient diagnostic significance of the serum ferritin concentration criterion, as well as the invasiveness and traumatization of biopsies, are limitations to the widespread use of these methods.OBJECTIVE: The purpose of this review is to present the main etio-pathogenetic factors of iron overload, the impact of this metabolic disorder on the body, and to reflect the basic principles of diagnosis and the leading role of quantitative MRI in the assessment of iron overload of vital internal organs.MATERIALS AND METHODS: Performed literature search in Russian and English languages for the period from 2001 to 2022 years in Medline/PubMed, RINC/Elibrary, CyberLeninka, Google Scholar databases by keywords: iron overload syndrome, liver, liver cirrhosis, ferritin, hemosiderin, MR diagnostics iron overload, MR relaxometry, R2*/T2*, thesaurismoses, magnetic resonance tomography, SIR (signal intensity ratio), LIC (liver iron concentration), biopsy, chronic diffuse liver diseases, DIOS.RESULTS: The final analysis included 27 publications devoted to various etio-pathogenetic aspects of iron overload syndrome. The forms of iron complexes residence in liver parenchymatous tissue are presented. Characteristics of MR-signal behavior depending on the severity of inhomogeneity of the magnetic field created by iron complexes are characterized. The areas of application of magnetic resonance imaging scanning modes for detection and quantitative diagnostics of iron overload are reflected.CONCLUSION: The ferritin-iron complex, also called ferrihydride, has high paramagnetic properties that provide high contrast MR images in the state of tissue iron overload. The leading methods for quantitative assessment of iron overload are the signal intensity ratio (SIR) method and T2*/R2*-relaxometry. Advantages and disadvantages of these methods, consisting in the limits of determining the degree of overload, make it possible to cover a wide range of overload values by complementing each other. Also the influence of parenchyma architectonics disturbances and concomitant accumulation diseases contribute to the formation of diagnostic inaccuracies. Therefore, the development of complex qualitative-quantitative MR diagnostics in order to isolate highly selective biomarkers will play an important role in MR diagnostics of iron overload syndrome.

Health Risk Assessment from Exposure to Ambient Volatile Organic Compounds (VOCs) at a Truck Tire Factory in the Yangtze River Delta, China

Occupational health risk assessments of exposure to VOCs still need to be extensively studied to improve the safety standards in the industry. Based on the monitoring of organic pollutants at various workstations in a truck tire factory in Jiangsu Province, both semi-quantitative and quantitative health risk assessment methods were employed to assess health risk levels. The findings indicated that VOCs were categorized into five classes, which included alkanes, aromatics, halocarbons, carbon disulfide, and oxygenated volatile organic compounds (OVOCs). The highest concentration of total volatile organic compounds (TVOCs) was found in shaping workshop; alkanes were the most abundant class (74.2%), followed by aromatics (24.02%) and OVOCs (1.96%). Although the results of the semi-quantitative risk assessment showed that most of the organic compounds had low R values, various kinds of VOCs were detected; particularly, many harmful organic compounds (such as toluene, ethyl benzene) were detected in all the sampling sites. The quantitative risk in the calendering and vulcanizing workshop exceeded the acceptable level; both the carcinogenic risk of ethylbenzene in the tire-strip storage room, and trichloroethylene and perchloroethylene in the calendering workshop were unacceptable. Thus, the calendering and vulcanizing processes in rubber tire manufacturing should be priority-controlled processes.

Quantitative risk assessment of a spill fire caused by the continuously leaked fuel in a sealed ship engine room

There are a large number of high-temperature heat sources in a ship engine room. Once the oil leakage occurs, it is likely to be ignited and form a spreading and burning spill fire. In this paper, spill fire experiments are conducted in a model-scale ship engine room to investigate their characteristic parameters. The quantitative models of flame height and thermal radiant surface emission power applicable to such fires are verified by the experimental data. Based on that, the classical quantitative risk assessment method is adopted to assess the risk of spill fires using thermal radiation hazard as the main reference, and a detailed framework for quantitative risk assessment of spill fires in ship engine room is established, which includes hazard identification, probability of failure calculation, consequence assessment, and risk quantification. The possible causes of spill fire accidents are briefly analyzed based on the bow-tie model. In cases where thermal threats above the risk threshold for larger leakage rates (70 mL/min), the probability method outperforms the threshold method in terms of accuracy in risk quantification. Additionally, the variation of thermal radiation with combustion diameter is analyzed, and some recommendations for fire emergency rescue are presented.

Assessment of the Adsorption Activity of Bacterial Cells Using Yersinia pseudotuberculosis Model

Currently, the Russian Anti-Plague Institute “Microbe” produces diagnostic immunoglobulins used in laboratory diagnostics of plague pathogen. One of the important stages in obtaining this category of drugs is the process of adsorption and removal of cross-reacting antibodies to increase the specificity of the drug. For this purpose, inactivated cells of Yersinia pseudotuberculosis strains are used.The aim of the work was to assess the possibility of using immunochemical methods to analyze the adsorption properties of bacterial cells, followed by an assessment of the impact of cultivation method and conditions, and the variant of the strain used on the adsorption properties of bacterial cells.Materials and methods. Cultivation was carried out on solid and liquid nutrient media; cells were inactivated by temperature and chemical exposure. Adsorption activity was assessed using immunoblotting and inhibitory enzyme-linked immunosorbent assay. Statistical processing of the results was performed using two-factor analysis of variance.Results and discussion. The suitability of immunoblotting and inhibitory ELISA methods for qualitative and quantitative assessment of the adsorption properties of bacterial cells has been demonstrated. It has been established that the adsorption properties of bacterial cells are influenced by the method of inactivation and the application of substrate feeding; the method of cultivation does not affect the adsorption properties of cells.

Results of Quantitative and Qualitative Assessment of Color Vision in Patients with Congenital Partial Atrophy of the Optic Nerve

Background. Congenital partial atrophy of the optic nerve is one of the main causes of blindness and low vision in patients with fundus pathology, and the study of color vision is important in diagnosis and monitoring visual functions in patients with this disease.Purpose: to study the possibilities of using the own developed method of quantitative and qualitative assessment of color vision in patients with partial optic nerve atrophy.Materials and methods. 55 patients aged from 8 to 20 years with congenital partial atrophy of the optic nerve (PAON) with a typical fundus pattern and EFI indicators for this disease were observed. The control group included 116 people of the same age without fundus pathology and with normal visual acuity. To study color vision in both groups, the classic FarnsworthMunsell Dichotomous D15 Test and the own developed method for quantitative and qualitative assessment of color vision were used.Results. The method developed by us made it possible to identify color perception disorders of varying severity in the majority (about 90 %) of patients with PAON. In the control group, no color perception disorders were detected in more than 70 % of the subjects. Quantitative assessment of color vision conducted using the method developed by us demonstrates significantly higher indicators of the total error of perception of color tones in patients with PAON (35.6 ± 3.2 degrees for a better-seeing eye and 39.9 ± 3.3 degrees for a worse-seeing eye) in comparison with the subjects of the control group (6.2 ± 1.1 degrees for a better-seeing eye and 7.5 ± 1.3 degrees for a worse-seeing eye). The severity of color perception disorders in patients with PAON does not depend on age, but has a significant inverse relationship with visual acuity. In the group of patients with PAON, when examining both better-seeing eye and worse-seeing eye, perception disorders of all color tones are detected with a slight predominance of disorders of perception of red, green and blue. The method developed by us has sufficiently higher sensitivity and specificity in comparison with the classic Farnsworth-Mansell D-15 test.Conclusion. The method developed by us makes it possible to effectively carry out a quantitative and qualitative assessment of the state of color perception in patients with PAON.

Assessment of the resistance of landscapes of the Altai Republic
 to anthropogenic impacts

Currently, there are many points of view on assessing the resistance of landscapes to anthropogenic impact, but there are no generally accepted methods for quantitative assessment of the emergent properties of geosystems. Various methods and approaches have been developed that are based on indices of sustainability and well-being, as well as classification models, the vast majority of which are based on a score-index approach. The work provides an integral assessment of the environmental sustainability of the landscapes of the Altai Republic, which is based on a number of physical and geographical factors that influence the stability of the existing geosystems. The most important among them are: relief (especially the steepness of slopes), vegetation cover, soils, density of the river network, water balance and land types. As a result, it was established that there is a general pattern - with increasing altitude above sea level, the ecological sustainability of landscapes decreases. Against the background of this pattern, flattened areas of intermountain basins stand out, where stability increases somewhat. Thus, in the north-west of the republic, landscapes of high environmental sustainability predominate, which are succeded by less stable landscapes of the central regions, and on the slopes of the North and South Chuysky, Katunsky ridges, the Tabyn-Bogdo-Ola massif, the ecological sustainability of landscapes is noticeably reduced.

A quantitative blind area risks assessment method for safe driving assistance

The task of driving in complex and occluded environments presents significant challenges, as it requires the perception and prediction of one’s surrounding environment. This is especially important as blind spots, or areas that are difficult to directly detect due to occlusion by surrounding vehicles or obstacles, which can pose a serious risk of accidents. To address this issue, this study proposes a method called “Uncertainty Shadow Safety”, which aims to evaluate the potential risk of invisible areas surrounding the ego vehicle based on the combination of static road information and the presence of traffic participants. The proposed system calculates the “shadow uncertainty” of a non-visible road area based on its physical properties and the probabilities of various traffic participants being present in that area. It then performs a quantitative assessment of the potential risk from various directions, taking into account the surrounding anomalous movement states. Simulation tests were conducted in various scenarios to demonstrate the feasibility and effectiveness of the Uncertainty Shadow Safety system. The advanced warning provided by the system to potential risks in invisible areas can help to reduce the likelihood of collisions and improve driving safety for both human drivers and autonomous vehicles.

Quantitative assessment method of new energy output uncertainty based on the prediction error

With a high percentage of distributed new energy sources connected to the power system, the power grid needs to reserve a larger margin to deal with the uncertainty of renewable energy outputs, leading to an increase in the cost of controlling the margins for the safe operation of the power grid. In order to reduce costs and increase efficiency, a quantitative assessment of new energy output uncertainty is needed. In this paper, a quantitative assessment method of new energy output uncertainty based on the prediction error is proposed, which makes use of a graph database to efficiently obtain massive new energy historical data, uses the clustering in quest (CLIQUE) algorithm to cluster the new energy historical data, and calculates the renewable energy real power confidence interval based on a given new energy power prediction, taking account of the impact of prediction errors caused by the new energy uncertainty and realizing the quantitative description of new energy output uncertainty. Finally, the method is calculated and analyzed together with the actual example data to verify the practical effect of the method.

Assessment of the Level of Digitalization of the Organization’s Human Resource Management

The actual problem of assessing the level of digitalization of the human resource management system in modern organizations is considered. The author proposes a method for a comprehensive quantitative assessment of the degree of implementation of digital technologies in personnel processes based on a number of indicators and an index approach. This technique is illustrated by the example of the analysis of HR digitalization of a Belarusian IT company. The proposed system of indicators makes it possible to assess the current state of HR digital transformation and develop recommendations for its further development. The research uses general scientific and economic methods of analysis, interpretive structural modeling, modeling using Markov processes, as well as statistical methods of grouping and classifications. The methodology has practical value.

Deep Learning-based Thigh Muscle Investigation Using MRI For Prosthetic Development for Patients Undergoing Total Knee Replacement (TKR).

A prosthetic device is designed based on the quantitative analysis of muscle MRI which will improve the muscle control achieved with functional electrical stimulation/ guided robotic exoskeletons. Electromyography (EMG) provides muscle functionality information while MRI provides the physiological and functionality of muscles. The sensor feedbacks were used for the bionic prosthesis, but the length of muscle using image processing was not correlated. To investigate and perform qualitative and quantitative assessment of thigh muscle using MRI. The objective of the work is to improve the existing VAG signal classification method to diagnose abnormality using MRI for patients undergoing Total knee replacement (TKR). A deep learning method for qualitative and quantitative assessment of thigh muscle is done using MRI. In existing prosthetic devices, electrical measurements of a person's muscles are obtained using surface or implantable electrodes. Several methods were used for the classification and diagnostic processes. The existing methods have drawbacks in feature extraction and require experts to design the system. This work combines medical image processing and orthopaedic prosthetics to develop a therapeutic method. This design provides much more precise control of prosthetic limbs using the image processing technique. The hybrid CNN swarm-based method measures the muscle structure and functions. Along with the sensor readings, these details are combined for prosthetic control. The implementation was carried out in MATLAB, Sketchuppro, and Arduino IDE. A combined swarm intelligence and deep learning method were proposed for qualitative and quantitative assessment of thigh muscle. The prosthetic device choice was done from the scanned MRI image like Humerus-T prosthetics, segmental prosthesis and arthrodesis prosthesis. The investigation was done for the Total knee replacement (TKR) approach.

A classification and quantitative assessment method for internal and external surface defects in pipelines based on ASTC-Net

Classification and size quantification of defects on both the internal and external surfaces of pipelines are critical to pipeline integrity assessment. However, defect classification is challenging because of the similarities of defect signals on the internal and external surfaces. In addition, most existing size quantification methods are not sufficiently accurate. To solve these problems, this paper proposes a classification and quantitative evaluation method based on an asymmetric student–teacher with a classifier network (ASTC-Net). First, a novel approach for expanding defect magnetic flux leakage (MFL) data is validated through experiments and simulations. Second, ASTC-Net is built to address the problem of defect classification and quantification. Finally, the superiority of the method is verified by experiments. The results show that this approach pioneers the accurate classification of defects on both internal and external surfaces by achieving an accuracy of 99.41%. Furthermore, a high-precision quantitative assessment of defect size is realized, with length, width, and depth errors of only 0.35 mm, 0.34 mm, and 0.41% of the wall thickness, respectively. These experimental results clearly demonstrate that this method has exceptionally high accuracy in defect classification and quantification, offering vast prospects for its application in pipeline MFL evaluation.

Prediction of pathological complete response in locally advanced head and neck squamous cell carcinoma treated with neoadjuvant chemo-immunotherapy using volumetric multisequence MRI histogram analysis.

This study aimed to develop a multisequence MRI-based volumetric histogram metrics model for predicting pathological complete response (pCR) in advanced head and neck squamous cell carcinoma (HNSCC) patients undergoing neoadjuvant chemo-immunotherapy (NCIT) and compare its predictive performance with AJCC staging and RECIST 1.1 criteria. Twenty-four patients with locally advanced HNSCC from a prospective phase II trial were enrolled for analysis. All patients underwent pre- and post-NCIT MRI examinations from which whole-tumor histogram features were extracted, including T1WI, T2WI, enhanced T1WI (T1Gd), diffusion-weighted imaging (DWI) sequences, and their corresponding apparent diffusion coefficient (ADC) maps. The pathological results divided the patients into pathological complete response (pCR) and non-pCR (N-pCR) groups. Delta features were calculated as the percentage change in histogram features from pre- to post-treatment. After data reduction and feature selection, logistic regression was used to build prediction models. ROC analysis was performed to assess the diagnostic performance. Eleven of 24 patients achieved pCR. Pre_T2_original_firstorder_Minimum, Post_ADC_original_firstorder_MeanAbsoluteDeviation, and Delta_T1Gd_original_firstorder_Skewness were associated with achieving pCR after NCIT. The Combined_Model demonstrated the best predictive performance (AUC 0.95), outperforming AJCC staging (AUC 0.52) and RECIST 1.1 (AUC 0.72). The Pre_Model (AUC 0.83) or Post-Model (AUC 0.83) had a better predictive ability than AJCC staging. Multisequence MRI-based volumetric histogram analysis can non-invasively predict the pCR status of HNSCC patients undergoing NCIT. The use of histogram features extracted from pre- and post-treatment MRI exhibits promising predictive performance and offers a novel quantitative assessment method for evaluating pCR in HNSCC patients receiving NCIT.

Benefits and approaches of incorporating land–sea interactions into coastal spatial planning: evidence from Xiamen, China

As the land–sea interface, the coastal zone has become an increasingly key life-support system. However, it is also highly threatened by exposure to both ocean- and land-based human activities. The interdependencies of the land and sea systems require the integration of land and sea spatial planning to achieve sustainable development of coastal zones. There are different forms of land–sea spatial management integration globally. Whether a form can positively impact and how different institutional settings affect outcomes need further explanation. Therefore, this study explores the reasons for China’s planning integration through institutional reform by using the Graph Model for Conflicts Resolution and establishes a quantitative contradiction assessment method to examine whether this top-down institutional approach has played a role at the urban level. The results show that the planning of Xiamen city after reform has a lower total contradiction value, grid cell average and cell maximum value. This progress is made possible by unifying the land–sea spatial planning departments. The equilibrium solution of the Graph Model for Conflicts Resolution indicates that due to the different preferences of the land–sea management departments and the central-local governments, it is challenging to implement the Land–sea Coordination policy under separate land–sea management. By integrating land–sea management departments, deep-seated sectoral interests between horizontal departments do not remain. The impacts on integrated management of divergences in preferences of different vertical governments can be reduced. The research results provide a universal method for the contradiction evaluation and a management reference for other regions that want to integrate land–sea coordination into urban spatial planning.

MIVES MULTI-CRITERIA FRAMEWORK TO SUSTAINABILITY INDEX OF DESIGN FOR MANUFACTURE AND ASSEMBLY

Embracing sustainable strategies that consider Design for Manufacture and Assembly (DfMA) has become a rapidly growing trend in urban development. Continued uncertainty on the sustainability assessment of design could drive a series of indecisive decision-making among design alternatives, further disrupting the potential opportunities toward sustainable DfMA. However, there is a lack of research on sustainable design assessments for DfMA and establishing a sustainable index. This research establishes an integrated value model for the sustainability assessment framework and DfMA sustainability index to address this challenge. This model integrates Building Information Modelling (BIM) with MIVES, a customisable Multi-Criteria Decision Making (MCDM) tool. The pilot case of this framework is the retrofit of a commercial building’s façade system, which demonstrated the capability of the proposed framework. Data collection and analysis include the comparisons between five design alternatives. This research furthers previous studies and has three-fold significance: 1) Establishing reasonable multi-criteria for the sustainable DfMA indices; 2) Adapting the MIVES approach for comparative analysis across three building phases to make it compatible with DfMA; 3) developing a quantitative analysis method for sustainable design assessment of DfMA in the construction industry.

A small-sample time-series signal augmentation and analysis method for quantitative assessment of bradykinesia in Parkinson's disease

Patients with Parkinson's disease (PD) usually have varying degrees of bradykinesia, and the current clinical assessment is mainly based on the Movement Disorder Society Unified PD Rating Scale, which can hardly meet the needs of objectivity and accuracy. Therefore, this paper proposed a small-sample time series classification method (DTW-TapNet) based on dynamic time warping (DTW) data augmentation and attentional prototype network. Firstly, for the problem of small sample sizes of clinical data, a DTW-based data merge method is used to achieve data augmentation. Then, the time series are dimensionally reorganized using random grouping, and convolutional operations are performed to learn features from multivariate time series. Further, attention mechanism and prototype learning are introduced to optimize the distance of the class prototype to which each time series belongs to train a low-dimensional feature representation of the time series, thus reducing the dependency on data volume. Clinical experiments were conducted to collect motion capture data of upper and lower limb movements from 36 patients with PD and eight healthy controls. For the upper limb movement data, the proposed method improved the classification accuracy, weighted precision, and kappa coefficient by 8.89%-15.56%, 9.22%-16.37%, and 0.13-0.23, respectively, compared with support vector machines, long short-term memory, and convolutional prototype network. For the lower limb movement data, the proposed method improved the classification accuracy, weighted precision, and kappa coefficient by 8.16%-20.41%, 10.01%-23.73%, and 0.12-0.28, respectively. The experiments and results show that the proposed method can objectively and accurately assess upper and lower limb bradykinesia in PD.

Comparative analysis of tabular and software methods of quantitative assessment of metamorphopsia

BACKGROUND: Identifying and evaluating the severity of patients complaints of metamorphopsia is an important component of the pre- and postoperative management of patients with vitreomacular interface conditions. To diagnose metamorphopsia, the Amsler grid is used, which allows to detect changes, but does not allow to quantify them. The authors of this article have developed a special software program for quantitative evaluation of metamorphopsia.
 AIM: The aim is to comparatively evaluate tabular and programmatic methods of metamorphopsia assessment.
 MATERIALS AND METHODS: The study involved 36 patients (36 eyes) divided into two groups: “macular hole” (20 patients, 20 eyes) and “epiretinal fibrosis” (16 patients, 16 eyes). Quantitative assessment of metamorphopsia was performed by two methods: tabular — using printed tables, which are an analog of M-CHARTS, and software — using the developed computer program.
 RESULTS: When comparing the integral parameters of the two methods using the Bland–Altman analysis, the results were highly comparable: the mean value of the difference between the PMs determined by the tabular and program methods was only –0.020°; the 95% confidence interval ranged from 0.277° to 0.235°, with 34 (94.4%) cases out of 36 falling within this range.
 CONCLUSIONS: The program and tabular methods of metamorphopsia examination are interchangeable and provide reasonably accurate quantification of metamorphopsia. The developed program is available on-line (https://mntk.ru/specialists/nauka-sotr/diag_meta/) and can be recommended for widespread clinical use.

An Ultra-Performance Liquid Chromatography-Tandem Mass Spectrometric Method for the Simultaneous Determination of Eighteen Marker Compounds in the Traditional Herbal Formula Bopyeo-Tang.

Bopyeo-tang (BPT), comprising six medicinal plants, has been used for the treatment of respiratory diseases such as pulmonary fibrosis and chronic obstructive pulmonary disease. In this study, we developed and validated a quantitative method for the quality assessment of BPT using ultra-performance liquid chromatography with tandem mass spectrometry (UPLC-MS/MS). Eighteen marker compounds were separated on an Acquity UPLC BEH C18 reversed-phase column (2.1 mm × 100 mm, 1.7 μm) via gradient elution with a 0.1% aqueous formic acid-acetonitrile mobile phase. The multiple-reaction monitoring mode was used to improve analysis speed and accuracy. The coefficients of determination, limits of detection, and limits of quantitation of the 18 marker compounds were 0.9991-0.9996, 0.36-24.45 μg/L, and 1.07-73.35 μg/L, respectively. The recovery was 85.19-110.25%, and the relative standard deviation of precision was ≤9.01%. When applied to a typical BPT sample, the method revealed a range of concentrations from below the quantitative limit (one compound only) to a maximum of 3.20 mg/freeze-dried g. This method will be used for quality control of BPT preparations.

The Method for Quantitative Assessment of Sand-Drift Rate along the Southeastern Fringe of the Taklimakan Desert

The Method for Quantitative Assessment of Sand-Drift Rate along the Southeastern Fringe of the Taklimakan Desert