Regression discontinuity design and its applications to Science of Science:A survey

Purpose:With the availability of large-scale scholarly datasets,scientists from various domains hope to understand the underlying mechanisms behind science,forming a vibrant area of inquiry in the emerging“science of science”field.As the results from the science of science often has strong policy implications,understanding the causal relationships between variables becomes prominent.However,the most credible quasi-experimental method among all causal inference methods,and a highly valuable tool in the empirical toolkit,Regression Discontinuity Design(RDD)has not been fully exploited in the field of science of science.In this paper,we provide a systematic survey of the RDD method,and its practical applications in the science of science.Design/methodology/approach:First,we introduce the basic assumptions,mathematical notations,and two types of RDD,i.e.,sharp and fuzzy RDD.Second,we use the Web of Science and the Microsoft Academic Graph datasets to study the evolution and citation patterns of RDD papers.Moreover,we provide a systematic survey of the applications of RDD methodologies in various scientific domains,as well as in the science of science.Finally,we demonstrate a case study to estimate the effect of Head Start Funding Proposals on child mortality.Findings:RDD was almost neglected for 30 years after it was first introduced in 1960.Afterward,scientists used mathematical and economic tools to develop the RDD methodology.After 2010,RDD methods showed strong applications in various domains,including medicine,psychology,political science and environmental science.However,we also notice that the RDD method has not been well developed in science of science research.Research Limitations:This work uses a keyword search to obtain RDD papers,which may neglect some related work.Additionally,our work does not aim to develop rigorous mathematical and technical details of RDD but rather focuses on its intuitions and applications.Practical implications:This work proposes how to use the RDD method in science of science research.Originality/value:This work systematically introduces the RDD,and calls for the awareness of using such a method in the field of science of science.

Optimization design of resistance spot welding parameters of magnesium alloy

By means of the quadratic regression combination design process, the regression equations of nugget diameter and tensile shear load of spot welded joint were established. Effects of welding parameters on the nugget diameter and the tensile shear load were investigated. The results show that effect of welding current on nugget diameter is the most evident. And higher welding current will result in bigger nugget diameter. Besides, interaction effect of electrode force and welding current on tensile shear load is the most evident compared with others. The optimum welding parameters corresponding to the maximum of tensile shear load have been obtained by programming using Matlab software, which is 4, 7 kN electrode force, 28 kA welding current and 4 cycle welding time. Under the condition of the optimum welding parameters, the joint having no visible defects can be obtained, nugget diameter and tensile shear load being 6. 8 mm and 3 256 N, respectively.

肥料三要素对六龄参根产量影响的数量分析

本文针对长白山区低肥力白浆土壤，在三因素五水平最优回归设计田间试验的基础上，应用多元统计分析的方法，建立了氮磷钾三种肥料对六龄参根产量影响的肥料效应数学模型。通过对此模型的数学分析，得知氮磷钾三种肥料对六龄参根的产量均有显著影响。其综合增产效应依次为NK＞N＞K＞P，而三种肥料的线性增产效应依次为N＞K＞P。当三种肥料在一定条件下单独使用时，其增产效应依次为N＞K＞P。同时确定了最高产量施肥量和最大利润施肥量，由等产线确定了合理施肥区。

Some recent developments in modeling quantile treatment effects

This paper provides a selective review of the recent developments on econometric/statistical modeling in quantile treatment effects under both selection on observables and on unobservables.First,we discuss identification,estimation and inference of quantile treatment effects under the framework of selection on observables.Then,we consider the case where the treatment variable is endogenous or self-selected,for which an instrumental variable method provides a powerful tool to tackle this problem.Finally,some extensions are discussed to the data-rich environments,to the regression discontinuity design,and some other approaches to identify quantile treatment effects are also discussed.In particular,some future research works in this area are addressed.

Optimization of synergistic drug combinations of different sparganins against blood stasis syndrome

Background:Blood stasis syndrome is one of the major syndromes in the development of chronic conditions in traditional Chinese medicine.Blood stasis syndrome is closely related to microcirculation dysfunction and thrombosis.Trigonaceae,as a representative traditional Chinese medicine for promoting blood circulation and removing blood stasis,there are many studies on its anticoagulant,antiplatelet aggregation and antithrombotic effects.Methods:Optimization of sparganin compounds,comprising sparganin A,sparganin B,and sparganin C for the characterization of drug pair effects against blood stasis syndrome was carried out.Ternary quadratic regression orthogonal combination design was carried out in a mouse model of blood stasis syndrome.The concentrations of thromboxane B2,plasminogen activator inhibitor 1,fibrinogen,and endothelin 1 were evaluated by enzyme linked immunosorbent assay.Thymus,hepatic,and spleen indices were also assessed.The outcomes of the evaluations aided in identifying optimum parameter values for the most favorable precipitation against blood stasis syndrome.Subsequently,Cytoscape 3.7.1 was used for network pharmacology to predict the key targets of sparganins and disease.Results:After sparganin A,sparganin B,and sparganin C treatment,hepatic had a downward trend,while spleen indices and thymus had an upward trend.Compared with the model group,thromboxane B2,endothelin 1,plasminogen activator inhibitor 1,and fibrinogen were decreased(P<0.05).The blood stasis syndrome model regression equation was extremely significant,and the correlation coefficient of R was 0.939,indicating that sparganin A,sparganin B and sparganin C were positively correlated at all levels.According to the dosage of these three factors and test results,the equation was fitted and the maximum values of the three sparganin in the corresponding dose range were obtained as follows:A=0.2982 mg/10g,B=0.1438 mg/10g,C=0.0417 mg/10g.Thus,the optimum parameters were found to be 0.298:0.144:0.042 for synergistic drug combinations of sparganin compounds sparganin A,sparganin B,and sparganin C in blood stasis syndrome.The possible key targets of sparganins included matrix metalloproteinase 9,plasminogen,proto-oncogene tyrosine-protein kinase src,and akt serine/threonine kinase 1 in blood stasis syndrome.Conclusion:Our study for the first time found two novel cyclic peptide compounds sparganin B and sparganin C have an anti-blood stasis effect,and speculated sparganins key targets included matrix metalloproteinase 9,plasminogen,proto-oncogene tyrosine-protein kinase src,and akt serine/threonine kinase 1 in blood stasis syndrome.

Influence of geometric design characteristics on safety under heterogeneous traffic flow

This paper focuses on analysing the influence of geometric design characteristics on traffic safety using bi-directional data on a divided roadway operated under heterogeneous traffic conditions in India. The study was carried out on a four lane divided inter-city highway in plain and rolling terrain. Statistical modelling approach by Poisson regression and Negative binomial regression were used to assess the safety performance as occurrence of crashes are random events and to identify the influence of the geometric design variables on the crash frequency. Negative binomial regression model was found to be more suitable to identify the variables contributing to road crashes. The study enabled better understanding of the factors related to road geometrics that influence road crash frequency. The study also established that operating speed has a significant contribution to the total number of crashes. Negative binomial models are found to be appropriate to predict road crashes on divided roadways under heterogeneous traffic conditions.

An Optimal Wet Friction Plate Inspired by Biological Surface Patterns

It is found that many biological organisms exhibit superior adhesion characteristics in wet environments. It has been observed that the foot pads of tree frogs and katydids are consist of a number of closely arranged polygons, most of them are hexagonal. In this paper, the common structure of two kinds of biological foot pad was extracted to model the bionic surface structure of friction plates. The friction plate prototypes were also prepared. Through the multivariate orthogonal regression design, the optimum parameter combination of the friction performances of the prototypes of the bionic plates has been obtained. The hexagonal circumcircle size is 10 mm, the groove width is 1 mm, and the hexagonal diagonal angle is 90~. Then the maximum static friction coefficient, dynamic friction coefficient and wear amount of the optimal friction plate were tested and compared with the control group friction plates. The comparative analysis of the experiment findings demonstrated that the bionic structure with hexagonal ring grooves can significantly improve the friction performance of the friction plates.

Mechanism of Slag Composition Change During Electroslag Remelting Process

The mass loss rate of CaF2-CaO-Al2O3-SiO2-MgO slag system originated from ANF-6 was studied with CaF2, CaO, Al2O3, SiO2 or MgO content as variables. The method of quadratic regression orthogonal design was used for the design and analysis of the experiment. The experimental results indicated that mass loss rate of slag can be increased by 6% with CaF2 changing from 50%to 65%. Mass loss increases with SiO2 , Al2O3 and MgO adding and decreases with CaO content increasing. Because of the reaction between oxide and fluoride in the slag pool, apparent mass loss of CaF2-Al2O3 CaO-SiO2 MgO slag system appears at melting point. This will cause obvious composition change of electroslag. In addition, the segregation occurs in the slag skin forming process. This is another reason causing the composition change of electroslag.

Maximal Moment Inequality for Partial Sums of Strong Mixing Sequences and Application

Some maximal moment inequalities for partial sums of the strong mixing random variable sequence are established. These inequalities use moment sums as up-boundary and improve the corre- sponding ones obtained by Shao （1996）. To show the application of the inequalities, we apply them to discuss the asymptotic normality of the weight function estimate for the fixed design regression model.