To comprehensively study the physical properties of inductively coupled plasma (ICP), a finite element method (FEM) simulation model of ICP is developed using the well-established COMSOL software. To benchmark the validation of the FEM model, two key physical parameters, the electron density and the electron temperature of the ICP plasma, are precisely measured by the state-of-the-art laser Thomson scattering diagnostic approach. For low-pressure plasma such as ICP, the local pressure in the generator tube is difficult to measure directly. The local gas pressure in the ICP tube has been calibrated by comparing the experimental and simulation results of the maximum electron density. And on this basis, the electron density and electron temperature of ICP under the same gas pressure and absorbed power have been compared by experiments and simulations. The good agreement between the experimental and simulation data of these two key physical parameters fully verifies the validity of the ICP FEM simulation model. The experimental verification of the ICP FEM simulation model lays a foundation for further study of the distribution of various physical quantities and their variation with pressure and absorption power, which is beneficial for improving the level of ICP-related processes.

A deep ice core was drilled at Dome A, Antarctic Plateau, East Antarctica, which started with the installation of a casing in January 2012 and reached 800.8 m in January 2017. To date, a total of 337 successful ice-core drilling runs have been conducted, including 118 runs to drill the pilot hole. The total drilling time was 52 days, of which eight days were required for drilling down and reaming the pilot hole, and 44 days for deep ice coring. The average penetration depths of individual runs were 1 and 3.1 m for the pilot hole drilling and deep ice coring, respectively. The quality of the ice cores was imperfect in the brittle zone (650−800 m). Some of the troubles encountered are discussed for reference, such as armoured cable knotting, screws falling into the hole bottom, and damaged parts, among others.

Although many studies on budgetary outcomes of state politics focus on budget sizes, budget trade-off studies focus on budget composition. This study examines the role of state politics in explaining budget trade-offs. We apply Peterson's typology to analyze budget trade-offs among developmental, allocational, redistributive, and educational expenditures. We focus on the roles of partisan and ideological factors and their interactive effects with institutional limits. Results show that politics matters. The Democratic Party and liberal citizen ideology increase state spending in redistribution relative to other categories, while the Republican Party shifts state budgets toward developmental spending. Partisan effects increase when tax and expenditure limits become less restrictive. Using more recent data and improved measurements, this study explains trade-offs among theoretically meaningful expenditure categories with a comprehensive model while providing a test of Peterson's typology.

Scholars have consistently shown that learning of successful policies in other states leads to higher likelihood of policy adoption. This study extends this finding two ways. First, policy learning can also lead to more comprehensive adoption of successful policies. Second, the effect of policy learning on policy comprehensiveness is conditional on lobbying by interest groups, an alternative source of information about policy success. To test these hypotheses, we conduct a directed dyad-year analysis using a dataset on American state drunk driving regulations from 1983 to 2000. The results show that more comprehensive policy adoption by states is positively related to policy success in other states when lobbying by Mothers Against Drunk Driving (MADD) is relatively low. Moreover, lobbying by MADD increases policy comprehensiveness when policy success is relatively low. This study advances the literature by examining the conditional effects of lobbying on the relationship between policy learning and policy reinvention.