Rent-Seeking and the Volume of Tax Laws: The Tax Cuts and Jobs Act of 2017

Taxes have a significant impact on individuals and firms. Unfortunately, complexity in the tax law has led to economic inefficiency due to inefficient use of tax breaks and increased audits and related penalties. Part of such complexity is driven by the sheer volume of tax law. To explain this phenomenon, we model tax law volume as a function of wealth transfers from the rent seeking/theory of regulation literature. Our models predict that both overall volume and the number of specific terms (defined by words in our specific “dictionary”) is higher for groups receiving tax breaks, and lower for more heavily taxed groups. The specific terms attempt to control for free riding across groups, and to limit tax breaks within groups. Using textual analysis, these predictions are supported in tests using the Tax Cuts and Jobs Act of 2017. Also, consistent with theory, we find that tax breaks are given to relatively smaller groups, and tax increases are spread across relatively larger groups

Signal estimation in cognitive satellite networks for satellite-based industrial internet of things

Satellite industrial Internet of Things (IIoT) plays an important role in industrial manufactures without requiring the support of terrestrial infrastructures. However, due to the scarcity of spectrum resources, existing satellite frequency bands cannot satisfy the demand of IIoT, which have to explore other available spectrum resources. Cognitive satellite networks are promising technologies and have the potential to alleviate the shortage of spectrum resources and enhance spectrum efficiency by sharing both spectral and spatial degrees of freedom. For effective signal estimations, multiple features of wireless signals are needed at receivers, the transmissions of which may cause considerable overhead. To mitigate the overhead, part of parameters, such as modulation order, constellation type, and signal to noise ratio (SNR), could be obtained at receivers through signal estimation rather than transmissions from transmitters to receivers. In this article, a grid method is utilized to process the constellation map to obtain its equivalent probability density function. Then, binary feature matrix of the probability density function is employed to construct a cost function to estimate the modulation order and constellation type for multiple quadrature amplitude modulation (MQAM) signal. Finally, an improved M 2 M ∞ method is adopted to realize the SNR estimation of MQAM. Simulation results show that the proposed method is able to accurately estimate the modulation order, constellation type, and SNR of MQAM signal, and these features are extremely useful in satellite-based IIoT

Research on Random Fatigue Load Model of Highway Bridge by Vehicle Traffic Based on GMM

Highway bridges have often suffered accidents due to fatigue damage. This paper studies the influence of vehicle operating state on the fatigue performance of bridges. Based on GMM method and K-S test in information statistics, this paper proposes an improved Gaussian hybrid modelling method, and studies the various parameters of vehicle operating state on beam bridge fatigue, such as the impact of the damage and its fatigue life assessment. On this basis, the fatigue cumulative damage formula of multi-vehicle upper bridge is proposed. The traffic load of Shandong JiNan-QingDao expressway has been GMMly analysed by GMM. The Gaussian mixture model is used to fit the vehicle load probability function by standard fatigue vehicle model. Based on the expressway, the vehicle fatigue has been established to facilitate the fatigue load and evaluate the fatigue life. Gradually this paper helps to improve the accuracy and convenience of the probability model, which is conducive to the establishment of a scientific and efficient load probability model for road vehicles

Forced vibration frequency response for a permanent magnetic planetary gear

The time and frequency forced responses for the permanent magnetic planetary gear drive were computed and analyzed. The influence of air gap between sun gear and planetary gear to frequency forced responses is discussed. Results show that the changes of air gap have obvious effects on the low frequency vibration amplitude of elements. When air gap is too large or too small, it will seriously affects the dynamic performance of the system. So, selecting rational system structure parameters is very important, which can avoid system elements generating larger vibration

Multi-microjoule GaSe-based mid-infrared optical parametric amplifier with an ultra-broad idler spectrum covering 4.2-16 {\mu}m

We report a multi-microjoule, ultra-broadband mid-infrared optical parametric amplifier based on a GaSe nonlinear crystal pumped at ~2 {\mu}m. The generated idler pulse has a flat spectrum spanning from 4.5 to 13.3 {\mu}m at -3 dB and 4.2 to 16 {\mu}m in the full spectral range, with a central wavelength of 8.8 {\mu}m. The proposed scheme supports a sub-cycle Fourier-transform-limited pulse width. A (2+1)-dimensional numerical simulation is employed to reproduce the obtained idler spectrum. To our best knowledge, this is the broadest -3 dB spectrum ever obtained by optical parametric amplifiers in this spectral region. The idler pulse energy is ~3.4 {\mu}J with a conversion efficiency of ~2% from the ~2 {\mu}m pump to the idler pulse.Comment: 5 pages, 5 figure