Value Determination Method Research Articles

Determination method and application of variable T2 cutoff value in nuclear magnetic logging

Abstract Nuclear magnetic resonance logging (NMR) is a new logging technology. By inversion of relaxation time T2 spectrum, pore characteristics can be directly measured, independent of the influence of rock skeleton minerals, and parameters such as effective porosity, movable fluid porosity, bound water porosity, pore size distribution and permeability can be calculated. The key parameter for calculating fine pore structure is the critical relaxation time of bound water and mobile fluid, namely the T2 cutoff value. The current T2 cutoff value is a fixed value based on the T2 mean value corresponding to the flowable porosity (permeability contribution porosity) in the mercury injection experimental data. However, according to the analysis of mercury injection data, there are differences in the flowable porosity of cores with the same porosity and permeability under the same pressure difference. Based on the synchronous data of nuclear magnetic logging and core mercury injection experiment, this paper establishes a variable T2 cutoff value determination method, which significantly improves the interpretation accuracy of nuclear magnetic logging and lays a foundation for the important application of nuclear magnetic logging in reservoir fine description.

Review on convective and radiation heat transfer between bridges and external environments

The heat exchange between bridges and external environments is the primary cause of the temperature effect on bridges. The complexity of the two-phase (gas–solid) heat transfer mechanism, the diversity of the surface characteristics of bridge materials, and the uncertainties of the environment in which bridges are located make the numerical calculation of the heat exchange between bridges and external environments difficult. Several studies have been conducted by scholars around the world. In this work, the research on convective and radiative heat exchange between bridges and external environments is surveyed, analyzed, and summarized. The influencing factors and calculation methods of bridge temperature are examined, and the convective heat transfer and radiation mechanisms, theoretical calculations, and experimental measurement methods used to investigate the relation between bridges and external environments are summarized and analyzed. The value determination methods for convective heat transfer and radiation absorption coefficients in the calculation of the bridge temperature field are summarized. In addition, the problems and shortcomings of current research are evaluated, and future research directions are identified and discussed.

A Low-Speed Position Sensorless Scheme From Standstill for Low-Cost SRM Drives Based on Triple Current Slope Difference Threshold

In this paper, a triple current slope difference threshold based low-speed sensorless scheme for low-cost SRM drives is proposed. Firstly, slope based methods, including the current slope difference method, are proposed and the advantages in terms of anti-interference ability over traditional instantaneous value based methods have been clarified. Secondly, the traditional single/double threshold methods and corresponding outgoing/incoming phase injection types are introduced and comprehensively compared. The limitations of conventional methods while adopted in low-cost SRM drives are stated. Accordingly, to solve the problem that the current cannot be obtained during the demagnetization stage in the resistor-based current sampling scheme, the triple current slope difference threshold method is proposed, whose 3 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rd</sup> threshold indicates the zero-current position. Thirdly, a general threshold value determination method considering the three-phase unbalanced inductances is proposed, which only requires the unsaturated inductance vs. rotor position characteristics that is very easy to be obtained. The proposed method only needs to store six threshold values in the microprocessor and needs no complex calculations and additional hardware, which can be realized in low-cost drive systems. Finally, the experiments of both the steady-state and starting transient-state under over-load conditions are implemented to verify the feasibility and accuracy of the proposed method.

Improved Multi-objective Particle Swarm Optimization in Software Engineering Supervision

In the 21st century, the software industry has achieved great development. The development complexity and volume of software projects are also continuously increasing. The design of software engineering supervision network plans is becoming increasingly important. In response to the poor optimization performance and poor convergence and distribution of optimal solutions in existing network planning algorithms, the Pareto optimal solution set construction method, global extremum selection method, and fitness value determination method of multi-objective particle swarm optimization algorithm are improved to enhance the convergence and distribution of the algorithm. Traditional methods only optimize one or two objectives of network planning, resulting in inconsistency with actual engineering. A multi-objective model based on resources, duration, cost, and quality is established for comprehensive optimization. Based on the results, the Pareto optimal solution curves obtained by the proposed algorithm on three classic test functions are consistent with the actual theoretical Pareto frontier curves. The proposed method is applied to engineering project examples. 10 solutions that meet the schedule requirements are obtained. Most engineering projects have a quality of over 80%, which verifies the practicality of the algorithm. The algorithm has achieved good results in optimizing engineering quality. Therefore, this model has the ability to consider various indicators such as resources and costs to obtain software engineering quality improvement plans. It has certain application potential.

Improved Initial Orbit Determination Based on the Gooding Method of Low Earth Orbit Space Debris Using Space-Based Observations

Initial orbit determination (IOD), as a basis for initial orbit association and accurate orbit determination (OD), has a crucial role in the process of obtaining space debris orbit information. Among the traditional methods, the Gooding method has better convergence and stability. In this study, the Gooding method is enhanced to solve the issues discovered. A novel initial orbit determination (IOD) method is developed using the proposed improvement measures of the single-parameter initial value determination (SIVD) method, the fitted-curve noise suppression method, the restricted corrective value solution method, the removal of trivial solutions, etc. The experimental results verify the effectiveness of the improved method. The success rate of the initial orbit determination reached 99%, and the accuracy of the solved orbit parameters was significantly improved, especially the semi-major axis (SMA) error of less than 50 km, accounting for 88% of the total. It can be seen that the method meets the demand of space-based space debris cataloging for initial orbit association and can serve in the field of space situational awareness, which has important practical significance and application potential.

Improved Method of Background Value Determination for Sb and Cd in Freshwater Sediment—Insights from Controlling Factors on Spatial Variability

Variability in the distribution of natural total Sb and Cd in freshwater sediments leads to difficulties in background value (BV) determination. This study aimed to establish a method to determine BV more accurately by investigating the vertical distribution of Sb and Cd in sediment cores collected from a typical river in alluvial plain in China and revealed the factors that control the variation of Sb and Cd BV, which has not been studied in alluvial freshwater sediment. The results suggested that uncontaminated samples for BV calculation should be determined by statistical analysis as human and natural disturbance led to high variation in contamination depth, from <5 cm to >55 cm. The sequential chemical extraction method showed a considerable amount of non-residual fractions of Sb and Cd, which accounted for 48% and 43% of the total, respectively. Acid extractable Cd (16%) was associated to the limestone geology in the area. Fine particles which governed by sedimentary environment contained more natural Sb and Cd, as strong positive correlation was found between clay content and Sb concentration (r = 0.89, p < 0.01), as well as Cd concentration (r = 0.54, p < 0.01). Based on these findings, a method combined with standard deviation and geochemical method was established to calculate the BV of Sb and Cd, and counter maps were made to cover the variation of BV in the Taipu river sediment. The pollution level has been evaluated by the geoaccumulation index more accurately.

System State Determination using Database-Driven Control Data

The database-driven (DD) PID control is a method of using a database to adjust PID parameters. System input/output data are stored in the database. The DD-PID control can be expected to expand the technology to smart systems such as state determination. In this paper, a state value determination method using the operation results of the DD-PID control is newly proposed. The proposed method has the same data structure as the DD-PID control and can determine the current system state value based on a DD approach. In addition, the proposed method improves accuracy by using logit transformations near the upper and lower limits of the system state value range. The effectiveness of the proposed method is verified by a numerical simulation.

Microscale Combustion Calorimetry as a New Method of Composition and Heating Value Determination of Miscanthus - An Early View

Microscale Combustion Calorimetry as a New Method of Composition and Heating Value Determination of Miscanthus - An Early View

IMPROVED QUANTITATION OF LOW PEROXIDE VALUE IN HIGHLY REFINED OIL INTENDED FOR USE DURING EMBRYO CULTURE USING A COMMERCIALLY AVAILABLE METHOD

The objective is to evaluate whether the peroxide value (POV) determination method of an oil intended for use for embryo culture can be optimized for precise quantitation of low concentrations of peroxide.

A method for in-situ measurement of calorific value of coal: a numerical study

Coal calorific value is an important indicator in the combustion optimization of power plants and the calculation of operating efficiency. Hence, the in-situ measurement of the coal calorific value is needed. This study developed an in-situ calorific value determination method and established the related model. The feasibility was evaluated by investigating the impacts of the gas flow rate, coal mass and wall thickness on measurement processes and measurement results. Additionally, the effect of ending the measurement early on the measurement error was studied in order to speed up the measurement. The comparison results between the presented calorimeter and the bomb calorimeter show the performance gap. However, measurement time and measurement error can be reduced by increasing the gas flow rate and coal mass and shortening the length of measurement. Applying this calorimeter is a feasible path to measure the calorific value of coal in-situ.

Viral Dynamics and Real-Time RT-PCR Ct Values Correlation with Disease Severity in COVID-19.

Real-time RT-PCR is considered the gold standard confirmatory test for coronavirus disease 2019 (COVID-19). However, many scientists disagree, and it is essential to understand that several factors and variables can cause a false-negative test. In this context, cycle threshold (Ct) values are being utilized to diagnose or predict SARS-CoV-2 infection. This practice has a significant clinical utility as Ct values can be correlated with the viral load. In addition, Ct values have a strong correlation with multiple haematological and biochemical markers. However, it is essential to consider that Ct values might be affected by pre-analytic, analytic, and post-analytical variables such as collection technique, specimen type, sampling time, viral kinetics, transport and storage conditions, nucleic acid extraction, viral RNA load, primer designing, real-time PCR efficiency, and Ct value determination method. Therefore, understanding the interpretation of Ct values and other influential factors could play a crucial role in interpreting viral load and disease severity. In several clinical studies consisting of small or large sample sizes, several discrepancies exist regarding a significant positive correlation between the Ct value and disease severity in COVID-19. In this context, a revised review of the literature has been conducted to fill the knowledge gaps regarding the correlations between Ct values and severity/fatality rates of patients with COVID-19. Various databases such as PubMed, Science Direct, Medline, Scopus, and Google Scholar were searched up to April 2021 by using keywords including “RT-PCR or viral load”, “SARS-CoV-2 and RT-PCR”, “Ct value and viral load”, “Ct value or COVID-19”. Research articles were extracted and selected independently by the authors and included in the present review based on their relevance to the study. The current narrative review explores the correlation of Ct values with mortality, disease progression, severity, and infectivity. We also discuss the factors that can affect these values, such as collection technique, type of swab, sampling method, etc.

The simple method of vegetable oils and oleochemical products acid value determination

Acid value is one of the key technical characteristic of vegetable oils and oleochemicals, obtaining on its basis. The existing standard methods of acid value measurement are relatively complicated and have some disadvantages. There are including utilization of the significant amounts of solvents, throwing out as wastes, and necessity in special equipment for determination. Also, a special issue is visual indication of the equivalence point of indicator transfer from acid to alkali form for intensive colored oils’ samples. Visual indication of the color transfer of phenol-phthalein as indicator (from colorless to pink) is quite difficult. The color transfer of thymolphthalein (from yellow to green) in such condition is not determined. Using of alkali blue 6B is complicated by the necessity of use ethanol and aromatic compounds mixture. In current work the rapid and simple method of acid value determination was proposed. It consists in alkali-acid titration of the sample by sodium butoxide solution in n-butanol with bromothymol blue, n-butanol is also using as solvent. The method was tested on 3 series of the mixtures of the refined sunflower oil and free fatty acids (distilled fatty acids of sunflower and rapeseed oils and chemical grade oleic acid). The fatty acid content in tested mixtures was in range 1-50 % wt. Some disadvantages of traditional methods, such as the necessity of mixed solvents’ and relatively complicated laboratory equipment use, titration in a hot state, effect of temperature changes in the laboratory and difficulties with visual indication of color transfer, were overcame. Proposed method requires only the simplest laboratory glassware (conic flasks, non-calibrated pipettes, hermetically sealed glass vessels for titrant) and technical laboratory scales (weighting accuracy ±0.01 g). The method allows to determine the acid value in wide range of samples, including the samples with intense coloration. The relatively high accuracy of acid value determination was shown. The method sensitivity is 0.02-0.10 mg KOH/g. The time for analyze is enough short (about 5-15 minutes).

Comparison of the NMR and the Acid Value Determination Methods for Quality Control of Input Polysorbates

Polysorbates (PS) are the most common non-ionic surfactants used in protein formulations. Their degradation has been studied intensively in recent years. Ester bond hydrolysis is one of many pathways of PS degradation that can lead to accumulation of free fatty acids (FFAs) and particle formation. The distribution and quantity of FFAs in PSs impacts directly on product quality. Characterization of input PS is highly relevant, because the initial content of FFAs differs greatly between manufacturers. The purpose of this study was to set up a quick and simple analytical method for the quantitative evaluation of FFAs in PS. The content of FFAs was measured for selected PS 20 and 80, using two methods, 1H nuclear magnetic resonance spectroscopy (1H NMR) and the European pharmacopoeia method for determining acid value (IA). These methods have been evaluated using the method of standard addition and, based on the results, they are interchangeable. It was concluded that 1H NMR is a useful tool for quality control of input PS and a rapid method for indicating the rate of PS degradation by hydrolysis and oxidation. Further, a newly discovered impurity in PS raw material, the long chain ketone 12-tricosanone, can be identified using 1H NMR.

A rare disease patient/caregiver perspective on fair pricing and access to gene-based therapies.

Gene-based therapies are changing the landscape of medicine for patients with rare diseases. These one-time, potentially curative treatments pose a challenge in the US healthcare model, where high prices and insurance coverage variation may prevent patients from receiving life-altering therapies. Questioning of high prices occurs when patients, payers, and policy makers hold divergent views on the value and uncertainty of therapies. The key for patients is that high prices need to be justified, and companies need to partner authentically with patients. Companies should not automatically assume that the combination of the "gene therapy" label and a small patient population justifies high prices. To speed up the development process and potentially reduce costs, patients want the industry to improve clinical trial efficiency by sharing data, including natural history studies and failed trial results. From the patient perspective, current value assessment frameworks disadvantage people with disabilities, may not accurately reflect patients' and societal views, and omit necessary factors such as impact on caregivers, lost productivity, and the future value of innovation. Value determination methods need to provide fair incentives and outcomes to industry, payers, regulators, and especially patients-the courageous pioneers who need equitable and sustainable access to life-changing gene-based therapies.

An extended MULTIMOORA method for probabilistic linguistic multi-criteria group decision-making based on prospect theory

The development of social economy has rendered the decision-making environment more complex. To better adapt to the environment and solve practical decision-making problems, this study uses the probabilistic linguistic terms set (PLTS) to describe qualitative information, which can not only provide every possible evaluation value, but can also yield the weight or proportion of these values. Based on the PLTS, we propose a probabilistic linguistic-dependent weighted average (PLDWA) operator; then, we establish the prospect theory-based multi-objective optimization by ratio analysis plus the full multiplicative form (MULTIMOORA) method (PT-MULTIMOORA) and extend it to the probabilistic linguistic information (PLI) environment. Moreover, we propose a final value determination method for the PT-MULTIMOORA method. Based on the combination of the PLDWA operator and the PT-MULTIMOORA method, we develop a novel approach to solve multiple criteria group decision making (MCGDM) problems with PLI. Two practical cases are demonstrated to verify the feasibility and superiority of the proposed method.

Spectral clustering algorithm using density-sensitive distance measure with global and local consistencies

Spectral clustering algorithm (SC) has recently received great attention for its high performance in large-scale data clustering and simplicity in implementation. However, previous studies have demonstrated that the commonly used distance measures in SC cannot simultaneously consider global and local consistencies and are sensitive to various noises. As a result, the obtained similarity matrices are unable to capture the actual data structure and thus produce poor clustering results, especially when the data exhibits nonlinear and local manifold structures characteristics. In order to address those limitations, we present a spectral clustering algorithm using density-sensitive distance measure with global and local consistencies in this paper. In the presented algorithm, a novel manifold distance with exponential term and scaling factor is introduced as the pairwise similarity measure. By modifying its exponential term and scaling factor, we can flexibly adjust the ratio of the similarities between the data within the same manifold to the similarities between the data across different manifolds. This flexible adjustment is beneficial to the obtained similarity matrix more accurately reflecting the global and local consistencies of data structures. In addition, to eliminate the effect of noises on the clustering performance, we also incorporate the relative density sensitive term into the distance measure to take into account the local distribution characteristics of the data. Finally, to further improve clustering performance, we provide the SC-based k value determination method for k nearest neighbors (KNN) graph. In the experimental part, the effect of parameters on the performance of the proposed technique is discussed and some suggestions about the determination of the parameters are given. Theoretical analysis and experimental results on several synthetic datasets, UCI benchmark datasets and generated large MNIST handwritten digits datasets demonstrate that the proposed approach is superior to other existing spectral clustering techniques with good robustness.

Comparative analysis of calorific values of selected agricultural wastes

Energy used for domestic application are expensive and beyond the reach of the rural poor. An alternative energy source is therefore a welcome development. This research work was aimed at determining the calorific values of Corn cob, Rice husk and Sawdust agricultural wastes materials. Standard method of calorific value determination involving the use of Bomb Calorimeter was adopted. From the investigation, the calorific value of Rice husk, Sawdust and Corn cob are 2938.86 Kcal/kg, 3155.30 Kcal/kg and 3227.78 KcaI/kg respectively. The agricultural materials were further subjected to briquetting and the calorific values determined to be 2092.48Kcal/kg, 2379.76Kcal/kg and 2923.36Kcal.kg for Rice husk, Sawdust and Corn cob briquettes respectively. The agricultural wastes met the minimum standard calorific value which range from 1500cal/kg – 1670Kcal/kg. The selected wastes have calorific values in the following decreasing order: Corn cob> Sawdust> Rice husk; and the corresponding briquettes is in the order: Corn cob>Sawdust >Rice husk. The selected wastes however, have lesser calorific values when briquetted. If agricultural wastes are used in place of firewood, this development will minimize deforestation which leads to desert encroachment and soil degradation.Keywords: Agricultural waste, calorifuc value, corn cob, Rice husk and saw dust

Data inversion method for dual-frequency Doppler lidar based on Fabry-Perot etalon quad-edge technique

In order to realize the accurate inversion of lidar data, the calibration method for the ratio of Fabry-Perot etalon (FPE) transmission to reflection curve is given, and the reliability of the method is verified by simulation test. The effective ratio of FPE transmission to reflection for the actual atmospheric detection is analyzed, and a nonlinear iterative algorithm for simultaneous inversion of wind field and backscatter ratio, as well as the specific iterative steps, initial value determination methods and corresponding error formula of parameters are proposed. The simulation results show that no matter whether the backscatter ratio Rβ is small or large, the iterative process is always convergent and the correct inversion results can be obtained. The value of Rβ has a great influence on the convergence rate of its own, but has little effect on the wind speed convergence rate. The smaller Rβ is, the faster convergence rate of Rβ is, vice versa. Error analysis inferred that under the shot-noise limit, the radial wind speed measurement error decreases rapidly with the increase of Rβ for 1 <Rβ < 2, decreases slowly with the increase of Rβ for Rβ > 2; if the total number of backscattering photons of 50,000 received by telescope is assumed, the backscatter ratio measurement error increases with the increase of Rβ; within the wind speed measurement dynamic range of ±25 m/s, the radial wind speed error is below 2m/s and the backscatter ratio relative error is less than 4.1% when 1.1 <Rβ < 10.

Thermal treatment of technical sucrose solutions of beet and cane origin

In the production of sugar from mixed syrups containing feedstock from beet and cane origin the non-sugar fraction plays an equally important role as in processing of material from a single source. However, the consequences of the resulting mixed non-sugar fraction on processes such as impurity, mainly colorants, incorporation and chemical reactions have not been studied yet. In this contribution the results of a study elucidating the kinetics of colorants formation in mixed syrups on thermal stress are given. It is found that the relative increase of syrup color value with respect to the starting value behaves quite systematic for wide range of mixed syrups. In all syrups the color values increase linearly with exposure time. The rate of increase is the highest for beet syrups. The generation rate increases with temperature in line with Arrhenius’ law. Different to earlier work no promoting effect of increased dry matter contents could be found. Furthermore, a model, assuming a first order reaction, to predict the color generation in mixed syrups based on the information of the pure syrups was formulated. This model is in essence generating data that match the experimental data within the range of the accuracy of the color value determination method. In conclusion the data suggest that there is no excess color generation on thermal stress due mixing of the non-sugar materials from different sources.

Prediction of Edible-oil Iodine Values Based on Raman and near Infrared Spectroscopy

Based on Raman and near infrared spectroscopy (NIR), the modeling of edible-oil iodine value was conducted following chemometrics and support vector machine regression (SVR). The Raman and NIR spectral data of 44 oil samples were collected and preprocessed. The preprocessed spectral data at characteristic wavelengths were extracted with CARS and iPLS methods. Parameter optimization was performed following the grid search algorithm (GS), for the SVR iodine value prediction models. The results show that all the models built could predict the iodine values to some extent. An NIR-MSC-iPLS-SVR model exhibited the greatest stability and its correlation coefficient R of the prediction set reached 97.69%. The results show that NIR has more advantages in the fast prediction of iodine values and can be utilized to manufacture portable spectral instruments for edible-oil iodine-value determination. Vegetable oils can afford human body unsaturated fatty acids, vitamins, and other nutrients [1]. Wherein, the unsaturated fatty acids can ensure the physiological function of cells, reduce cholesterol contents, and perfect blood circulation [2]. The unsaturated fatty acid content can be indicated by unsaturation degree and iodine value (iodine number). The iodine value refers to the grams of iodine consumed in the addition reaction of 100 g of oil. The higher the iodine value is, the greater the unsaturation degree is, and the higher the unsaturated fatty acid content is. The iodine value determination methods include Wijs method (national standard), high-performance liquid chromatography (HPLC) method, and so forth [3-4]. Wherein, the Wijs method is precise and commonly used. Nevertheless, because the sample and titrant solution are immiscible, at the end point of titration, the color change is too slow. And, the method is tedious and requires a large amount of hazardous organic solvents [5-6]. Compared with the Wijs method, the spectral method is fast, efficient, and free of sample pretreatment. Hence, it has been increasingly used in oil and food industries [7]. Yu Yanbo et al. [8] used near infrared spectroscopy (NIR) technology to build a prediction model for the prediction of contents of 4 fatty acids in vegetable oils. María Á. Carmona et al. [9] identified oils and determined iodine values based on Raman spectroscopy.