Setting Method Research Articles

The Use of Extracorporeal Membrane Oxygenation (ECMO) and Protective Mechanical Ventilation in the Treatment of Acute Respiratory Failure

Acute respiratory failure (ARF) affects 2 million people in the United States each year. The ARF's hallmark is a heterogeneous injury, with normal tissue intermingled with a large volume of low compliance and collapsed tissue. Mechanical ventilation is necessary to oxygenate and ventilate those patients but if set inappropriately can cause ventilator-induced lung injury (VILI). To avoid VILI, extracorporeal membrane oxygenation (ECMO) can replace the pulmonary function of gas exchange . The optimal method of mechanical ventilation for the patient on ECMO is unknown. Rest the Lung Approach (RLA) buys time for the lung to heal in the collapsed state. Open Lung Approach (OLA) attempts to open the entire lung very quickly. ARDS-related mortality has not been further reduced using the RLA and even it increases with OLA. Thus, the Mechanical Breath Profile (MBP) component of time would play a critical role in both lung opening and collapses. The Time-Controlled Adaptive Ventilation (TCAV) method of setting and adjusting the Airway Pressure Release Ventilation (APRV) mode uses an extended time at inspiration to open viscoelastic lung tissue and a very brief expiratory time to prevent re-collapse during exhalation. The expiratory time is personalized and adaptive as it is set by changes in respiratory system compliance (CRS). The TCAV method is a novel Stabilize the Lung Approach (SLA). We postulate that the SLA TCAV method would be a highly lung-protective ventilation strategy that would protect from VILI and gradually reopen the lung allowing the patient to be liberated from ECMO.

Hierarchical structure optimal setting approach for production indexes of the rolling heating furnace temperature field

In order to improve the optimal setting temperature problem to achieve the global optimum of product performance, costs and benefits. In this article, a hierarchical structure optimal setting approach of production indexes for the rolling heating furnace temperature field (RHFTF) is proposed. It is composed of three layers with different functions to obtain the temperature control setting model of the RHFTF. In the first layer, the bi-feature Gaussian mixture model clustering (BFGMMC) algorithm of loading plan is proposed to optimize the setting of a limited number of slabs. In the second layer, the type-2 fuzzy rule interpolation (T2FRI) setting method is developed to obtain the optimal setting curve. Meanwhile, an improved KH (Kóczy-Hirota) α-cut distance (IKHCD) algorithm is proposed to get the miss information between any two adjacent interpolation points. In the third layer, knowledge feedforward compensation of rule matrices (KFCRM) algorithm is presented to improve the anti-interference ability of the setting model. The results of the study can demonstrate that the proposed method improves the accuracy of the model and optimizes the control strategy. Furthermore, the experimental results show that the proposed method meets the process technical requirements.

Forming of the structure of binder film in waterglass mixtures depending on the setting method

Forming of the structure of binder film in waterglass mixtures depending on the setting method

Formation of Goal-Setting Skills as an Integral Component of a Teacher’s Professional Development

The article reveals the concept of goal-setting. In defining the concept of a goal, we proceed from the fact that the goal should express the planned results of activities. The goal-setting ability is considered as a system-forming skill both in the preparation of future teachers and in the improvement of professional competencies of practical teachers. The purpose of the article is to present the results of a study on the justification and development of the content of teaching teachers aimed at the formation of goal–setting skills. The methodology of the research is a system-activity approach, in which the results of education are considered as a system-forming component. In the analysis of psychological, pedagogical and methodological literature, the concept of goals in teaching was clarified, generalized areas of goal-setting – subject and meta-subject– were identified, problems of the formation of professional competencies of teachers in terms of goal-setting and ways to solve them were identified. The identification of problems in the formation of goal-setting skills occurred both on the basis of the analysis of literature, written works of teachers and students, and in the process of observing their practical activities. As the main methodology for the formation of goal–setting skills, the SMART method was chosen– the method of setting “smart” goals. In the process of teaching mathematics teachers at advanced training courses, as well as teaching students– future teachers, training aimed at developing goal-setting skills using the SMART methodology was conducted as an approbation. In conclusion, conclusions are drawn about the expediency of organizing special training in goal-setting skills for both future teachers and working teachers as part of professional development.

The Impact of Economic Growth Target Constraints on Environmental Pollution: Evidence from China.

Economic growth target (EGT) has become an essential tool for macroeconomic administration all around the world. This study examines the effect and mechanisms of EGT on environmental pollution (EP) by using economic growth target data from provincial Government Work Reports in China from 2003-2019. The conclusions denote that EGT significantly aggravates regional EP, and it still stands after robustness tests and instrumental variable (IV) estimation. The result of mediating effect shows that EGT aggravates EP mainly from three ways: investment surge, technological innovation, and resource allocation. The result of the moderating effect shows that government's fiscal space positively adjusts the effect of EGT on EP, while environmental regulation negatively adjusts the effect of EGT on EP. The heterogeneity test reflects that the effect of EGT on EP is more significant on provinces that adopt a "hard constraint" setting method and fulfill EGT. Our study provides a reference to better balance the link between EGT and sustainable development for the government department.

3-D modelling and analysis of superparamagnetic effects in ATEM based on the FDFD

SUMMARY Superparamagnetic (SPM) effects lead to 1/t power-law delay approximately during the middle and late periods of transient electromagnetic responses. Ignoring SPM effects can produce large errors and cause incorrect data interpretation. Furthermore, because of the non-linearity of the Chikazumi magnetic susceptibility model, it is difficult to discretize the model in the time domain. Therefore, developing an algorithm for 3-D modelling of SPM effects in the time domain directly is difficult. In view of the above problems, we propose a 3-D modelling method of SPM effects for airborne transient electromagnetic (ATEM) data. We also introduce the widely used Chikazumi magnetic susceptibility model into the finite-difference frequency-domain (FDFD) method. According to the mapping relations between the magnetic field intensity and the magnetic permeability on the grid after discretization, we re-establish the scientific matrix of the magnetic permeability. And we adopt arithmetic averaging of the two adjacent cubes’ magnetic permeability as the magnetic permeability in boundary, which is a different setting method with the electrical conductivity. The 3-D modelling of SPM effects is successfully realized, and its maximum relative error is less than 7 per cent. We subsequently analyse the intrinsic properties of the abnormal magnetic medium, as well as the effect of the SPM unit's parameters, such as the depth, thickness, electrical conductivity, zero-frequency magnetic susceptibility, and the height of the receiver, on the response. Then, we calculate the SPM responses of 3-D magnetic bodies and analyse the influence of magnetic susceptibility and electrical conductivity on magnetite responses. The present study can provide theoretical guidance for ATEM detection in magnetic media and lay a foundation for 3-D inversion of SPM effects.

Therapeutic Effect of Tendon Bone Setting Technique and Sports Training on Joint Injury.

Purpose In this study, we observe the therapeutic influence on tendon and bone setting technique, combined with sports training on joint injury. Methods Using the random number method, 50 research objects with joint injuries were divided into two groups: treatment group and control group, and each group had 25 cases. The treatment group was combined with sports training with tendon and bone setting technique, and the control group was given intermediate frequency electrotherapy combined with forearm brace fixation. The scores of visual analogue scale (VAS), forearm pronation and postrotation activity, integral electromyogram (iEMG), and research object-rated wrist evaluation (PRWE) were evaluated and compared before and after treatment, and the curative effect observation (blind method was used in the evaluation process) and research object satisfaction were evaluated. Results After the treatment, the VAS score of two groups decreased, forearm pronation and pronation activity increased, iEMG value increased, and PRWE scale score decreased (p < 0.05), and compared with the control group, the treatment group's curative effect was better (p < 0.05), and compared with the control group, treatment group's total effective rate was higher (p < 0.05). Conclusion The method of tendon and bone setting combined with sports training could effectively reduce the pain of research objects with joint injury, improve the rotation range of the forearm, increase the recruitment of the pronator muscles, and improve the wrist function of the research objects, and the curative effect was better than that of medium frequency electrotherapy combined with forearm brace fixation.

The Effect of the Securities Transaction Tax Rate Cut on the Liquidity in KRX

This study evaluated the impact of the securities transaction tax rate cut implemented in 2019 on the liquidity of the stock market. The empirical results are summarized as follows. First, cutting the transaction tax rate affects trading volume rather than spread or price. Additionally, this liquidity improvement more strongly affects low liquid stocks in the period before the transaction tax rate cut. Second, in low liquid stocks that showed effects in trading volume, individuals and foreigners took the leadership in overall trading. Third, liquidity improvement persisted not only in the short term immediately after the transaction tax rate cut, but also until the second half of the sample period. These empirical results show the differing effect of the transaction tax on improving liquidity by liquidity level and a limited effect in low-liquidity stocks. As investors trading low-liquidity stocks with high tax elasticity were sensitive to the burden of transaction costs, the effect of transaction tax cuts was strong, while such effects could not be found in stocks with high liquidity. These empirical results provide practical implications for the level of transaction costs and the method of setting as a means to revitalize market liquidity.

Rheological and Mechanical Properties of Resin-Based Materials Applied in Dental Restorations.

Resin-based materials have been prevalent for dental restorations over the past few decades and have been widely used for a variety of direct and indirect procedures. Typically, resin-based dental materials are required to be flowable or moldable before setting and can provide adequate mechanical strength after setting. The setting method may include, but is not limited to, light-curing, self-curing or heating. In this review, based on different indications of resin-based dental materials (e.g., dental filling composite, dental bonding agent, resin luting cement), their rheological and mechanical properties were reviewed. Viscous and flexible properties were focused on for materials before setting, while elastic properties and mechanical strength were focused on for materials after setting. At the same time, the factors that may affect their rheological and mechanical properties were discussed. It is anticipated that the insightful information and prospections of this study will be useful to the future development and fabrication of resin-based dental restorative materials.

Know thyself: Development and validation of self-awareness of teaching skills (SATS) measuring instrument for medical teachers

Background Self-awareness is measured previously in the higher education however not specifically in relation to ‘effectiveness of teaching’ thus leaving a gap in the literature. Aim To develop and validate an instrument for medical teachers to measure the self-awareness of their teaching. Methods This was an instrument development multiphase mixed-method study design, based on Brookfield’s four lenses theory. The instrument was validated after administering content validity, cognitive pretesting, confirmatory factor analysis and reliability analysis. Contrasting groups’ method of standard setting was used to determine the cut-off scores for the levels of self-awareness of medical teachers. Results A 26-item preliminary draft instrument was reduced to a 19-item final instrument having four themes, that is; self-reflection, communication with students, student feedback, and peer review. Content Validity Scale was 0.92. Confirmatory factor analysis yielded a model with a good-to-excellent fit and an internal consistency of 0.85. The cut-off values were calculated to be 79%, 70%, 59%, and 53% for excellent, good, average and poor self-awareness of teaching skills respectively. Conclusion The Self-awareness of the teaching skills instrument has excellent validity and good reliability in measuring the self-awareness of teaching skills of medical teachers.

Subgroup discovery in non-inferiority trials.

Approaches and guidelines for performing subgroup analysis to assess heterogeneity of treatment effect in clinical trials have been the topic of numerous papers in the statistical and clinical literature, but have been discussed predominantly in the context of conventional superiority trials. Concerns about treatment heterogeneity are the same if not greater in non-inferiority (NI) trials, especially since overall similarity between two treatment arms in a successful NI trial could be due to the existence of qualitative interactions that are more likely when comparing two active therapies. Even in unsuccessful NI trials, subgroup analyses can yield important insights about the potential reasons for failure to demonstrate non-inferiority of the experimental therapy. Recent NI trials have performed a priori subgroup analyses using standard statistical tests for interaction, but there is increasing interest in more flexible machine learning approaches for post-hoc subgroup discovery. The performance and practical application of such methods in NI trials have not been systematically explored, however. We considered the Virtual Twin method for the NI setting, an algorithm for subgroup identification that combines random forest with classification and regression trees, and conducted extensive simulation studies to examine its performance under different NI trial conditions and to devise decision rules for selecting the final subgroups. We illustrate the utility of the method with data from a NI trial that was conducted to compare two acupuncture treatments for chronic musculoskeletal pain.

An inexpensive retrospective standard setting method based on item facilities

BackgroundStandard setting is one of the most challenging aspects of assessment in high-stakes healthcare settings. The Angoff methodology is widely used, but poses a number of challenges, including conceptualisation of the just-passing candidate, and the time-cost of implementing the method. Cohen methodologies are inexpensive and rapid but rely on the performance of an individual candidate. A new method of standard setting, based on the entire cohort and every item, would be valuable.MethodsWe identified Borderline candidates by reviewing their performance across all assessments in an academic year. We plotted the item scores of the Borderline candidates in comparison with Facility for the whole cohort and fitted curves to the resulting distribution.ResultsIt is observed that for any given Item, an equation of the formy ≈ C. eFxwhere y is the Facility of Borderline candidates on that Item, x is the observed Item Facility of the whole cohort, and C and F are constants, predicts the probable Facility for Borderline candidates over the test, in other words, the cut score for Borderline candidates. We describe ways of estimating C and F in any given circumstance, and suggest typical values arising from this particular study: that C = 12.3 and F = 0.021.ConclusionsC and F are relatively stable, and that the equationy = 12.3. e0.021xcan rapidly be applied to the item Facility for every item. The average value represents the cut score for the assessment as a whole. This represents a novel retrospective method based on test takers.Compared to the Cohen method which draws on one score and one candidate, this method draws on all items and candidates in a test. We propose that it can be used to standard set a whole test, or a particular item where the predicted Angoff score is very different from the observed Facility.

Constructive Geometric Models with Imaginary Objects

The article is devoted to the consideration of a number of theoretical questions of projective geometry related to specifying and displaying imaginary objects, especially, conics. The lack of development of appropriate constructive schemes is a significant obstacle to the study of quadratic images in three-dimensional space and spaces of higher order. The relationship between the two circles, established by the inversion operation with respect to the other two circles, in particular, one of which is imaginary, allows obtain a simple and effective method for indirect setting of imaginary circles in a planar drawing. The application of the collinear transformation to circles with an imaginary radius also makes it possible to obtain unified algorithms for specifying and controlling imaginary conics along with usual real second-order curves. As a result, it allows eliminate exceptional situations that arise while solving problems with quadratic images in spaces of second and higher order.

Differential current integral based bipolar short-circuit protection method for DC distribution network with blocking converters

The transient characteristics of the bipolar short-circuit fault on a loop DC distribution network with blocking converters are studied in this paper. A protection principle based on the integrals of the line differential current is proposed after analyzing the characteristics of the line differential current during an internal fault and an external fault. The protection criterion and setting method are also presented. Moreover, after analyzing the adaptability of the proposed protection method under the circumstance where the converters cannot be blocked promptly due to large transition resistance, a criterion for quick blocking is given. The proposed protection method demonstrates such advantages as high anti-transition resistance, none-susceptibility to converter blocking and low sampling frequency requirement, thus can provide selective and reliable protection for the DC distribution network with blocking converters. The proposed protection method is validated by a loop DC distribution network model with blocking converters in PSCAD/EMTDC.

KEMAMPUAN PEMECAHAN MASALAH SISWA PADA MATERI PROGRAM LINEAR MELALUI TAHAPAN NEWMAN

The purpose of this article is to describe students' problem-solving abilities in completing linear programs through the Newman stages. This article uses qualitative. Data collection was obtained from the method of setting, testing, and interviewing. There are 36 students in class IX PS 2 as the subject of this article. The subject's abilities are categorized as high, medium, and low. Descriptive analysis was obtained from 9 students who represented each level. Test the validity of the data by triangulation. The results of the analysis obtained an average problem-solving ability using the Newman stage, namely the ability to read problems 85.6% classified well, the ability to solve problems 80% classified well, the ability to transform 82.59% classified well, the ability to process 73.3% classified good, the ability to solve answers 67.7% classified sufficiently. Of the 8 levels of ability obtained by 8 high-skilled students require new procedures well in solving problems, 24 capable students are having difficulty in the process of problem transformation, and 4 low-ability students are unable to handle new procedures.Keywords: problem-solving ability, Newman's procedure

Nonparametric empirical Bayesian method for noncontractual setting of customer-base analysis

In the noncontractual setting of customer-base analysis, heterogeneity parameters in purchase model and lifetime model are usually assumed to follow some familiar parametric distribution such as gamma or log-normal distribution. But, in many applications, these assumptions may be questionable because the true distributions of heterogeneity parameters are usually unknown. To this end, this paper relaxes these assumptions imposed on heterogeneity parameters to develop a nonparametric approach to purchase model and lifetime model, in which unknown distributions of heterogeneity parameters are approximated by a truncated Dirichlet process prior. A nonparametric empirical Bayesian method is developed to obtain Bayesian estimations of unknown parameters in the proposed nonparametric models. The blocked Gibbs sampler is presented to draw observations required for Bayesian inference from the corresponding posterior distributions of the components of parameters. Extensive simulation studies and a CDNOW data set are presented to illustrate the newly developed methodologies.

Pricing for Heterogeneous Products: Analytics for Ticket Reselling

We develop a framework for estimating price sensitivity in applications such as ticket reselling. This framework allows us to estimate heterogeneous price sensitivity that we subsequently embed in a price optimization model for ticket reselling. Due to the heterogeneous nature of tickets, the unique market conditions at the time each ticket is listed, and the sparsity of available tickets, demand estimation needs to be done at the individual ticket level. We introduce a double/orthogonalized machine learning method for a classification setting that allows us to isolate the causal effects of price on the outcome by removing the conditional effect of the ticket and market features. Furthermore, we introduce a novel loss function which can be easily incorporated into off the shelf machine learning algorithms, including gradient boosted trees and neural networks. We also show how in the presence of hidden confounding variables instrumental variables can be incorporated. Using a wide range of synthetic data sets, we show this approach beats state-of-the-art machine learning approaches for estimating price sensitivity in our setting, and prove analytical properties for this estimator. We then develop an optimization model for selling tickets on a secondary market, in which we incorporate the heterogeneous price sensitivity model. Leveraging data from a major ticket reseller, we show significant potential for impact in practice. More broadly, this paper develops a novel methodology for estimating heterogeneous treatment effects in classification settings that can be applied to other settings such as personalized pricing and estimating intervention effects in healthcare applications.

Incorporating nocturnal UAV side-view images with VIIRS data for accurate population estimation: a test at the urban administrative district scale

ABSTRACTIn contrast to daytime remote sensing used for observing the Earth, night-time light remote sensing with satellites primarily assesses human activity using urban parameters such as building lights or lighted highways to help determine population density and other habitation characteristics. One limitation to conventional night-time remote sensing is that light emitted from high-rise buildings, for example, is not easily detected because of optical geometry as satellite sensors are generally pointed in only a downward direction. Furthermore, satellite sensors often receive weak optical signals because of streetlights reflected from the Earth’s surface. As a result, accurate information on night-time human activity cannot be gathered from existing satellite remote-sensing methods. To address this, a new method for night-time remote setting is presented. Specifically, an unmanned aerial vehicle (UAV) is used to capture panoramic images of night-time light and processed to reveal side-view light spot information from urban buildings. This dataset was used to predict population density alone, and with the Visible Infrared Imaging Radiometer Suite (VIIRS) data by simple multiple linear regression. The results confirm that nocturnal UAV side-view data or VIIRS data alone can be used to estimate population density, while the combination of the two significantly increases the accuracy of population density estimation compared against estimating population density using nocturnal UAV side-view data or VIIRS data alone. This outcome suggests that multi-angular night-time remote-sensing data sources increase the accuracy of urban population density estimation. One reason for this may be that the side-view night-time data and orthophoto data infer urban population density from different agent variables: building occupancy is a proxy of side-view night-time data, while density of illuminated road network is that of orthophoto data.

DESIGN AND DEVELOPMENT OF INTERLEAVED BOOST CONVERTER AS A POWER QUALITY IMPROVEMENT IN ONE PHASE ROTARY WITH INDUCTIVE AND RESISTIVE LOADS

The unidirectional voltage source is obtained through an uncontrolled 220 Volt single phase full wave rectifier circuit. Installation of large amount capacitors as a filter affect input waveform. Due to the harmonics distort sinusoidal input voltage from the PLN grid. The difference in voltage waveforms and input currents that occur can affect the value of the resulting factor. Based on this problem, a study was made on theimprovement of power factors using a series of Interleaved Boost Converter which functioned as a series of Power Factor Correction (PFC) and voltage regulators with a setting method using Fuzzy logic. This Interleaved Boost Converter circuit is made to work in the condition of the Discontinues Conduction Mode (DCM) so that any load that is supplied to the circuit will make the system resistive. So, it is expected that thevoltage and input current waveforms will produce a factor value close to the unity value. The results of this study are the Interleaved Boost Converter series that can be used as a Power Factor Correction circuit and also as a voltage regulator. It improves power factor from 0.9 to 0.93.

The setting and optimization of quick queue with customer loss

At the peak of a service system, customers may hesitate and even leave in the face of unavoidable queuing. This phenomenon not only affects the customer's satisfaction, but also causes the loss of the company's revenue. This paper establishes a fluid model of customer queuing behavior for the customer losses. The goal is to reduce the customer losses, and the setting and optimization method of quick queue in random service systems is studied. We construct two queuing models, in which one includes only regular queues and the other includes both regular and quick queues. We analyze the queuing systems, and describe the different forms of the objective function based on the fluid model of customer behavior. Then we compare and analyze the impact of the adoption of quick queues on the performance of the service system during peak period, and design a calculation method to obtain the optimal value for setting the number of quick queues. Thus, the overall performance of the system is optimized. Finally, we take the setting and optimization of quick queue in the supermarket service system as an example, which verifies the validity of the proposed method, and shows the reference value of this method to management practice.