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This article conducts a benefit-cost analysis of a child allowance. Through a systematic literature review of the highest quality evidence on the causal effects of cash and near-cash transfers, this article produces core estimates on the benefits and costs per child and per adult of increasing household income by $1000, which can be used for any cash or near-cash program that increases household income. We then apply these estimates to three child allowance proposals, with the main proposal converting the $2000 Child Tax Credit in the federal income tax code into a fully refundable and more generous child allowance of $3600 per child ages 0–5 and $3000 per child ages 6–17, as enacted for 1 year in the American Rescue Plan. Aggregate costs and benefits are estimated via micro-simulation. Our estimates indicate that making the $2000 Child Tax Credit fully refundable and increasing benefits to $3000/$3600 would cost $97 billion per year and generate social benefits of $929 billion per year. Sensitivity analyses indicate that the results are robust to alternative assumptions and that each of the three child allowance proposals produces a very strong to an extraordinarily strong return for the U.S. population.

Workers with mental illness may be uniquely affected by the labor market impacts of the pandemic. The authors used data from the National Health Interview Survey (2016-2018) to categorize workers by employment in essential or nonessential industries and by the feasibility of working remotely. Workers with psychological distress prepandemic were less likely than those without psychological distress to have occupations where remote work was feasible. These individuals may face higher risk of exposure to the virus and, if they are nonessential workers, higher risk of unemployment. Efforts that facilitate safe, continued connection to the workforce may be of value to workers with preexisting mental illnesses.

Recently, research theorizing bilinguals’ fluid and transcending language practices has flourished. As the strategic use of more than one named language in meaning-making begins to gain validation, educators and researchers have explored the pedagogical implications of such practices in the understanding and education of bilinguals. Aligning with these explorations, this article presents a case study of a bilingual scholar’s meaning-making practice. Relying on a translanguaging lens and a multilingual perspective on creativity, I document how Professor Wang, a Chinese-American anthropologist, utilizes his full communication toolkit to navigate the academic activities of teaching, researching and writing. The findings suggest Wang translanguages to achieve the purpose of culture learning and representation. Particularly, translanguaging creativity emerges as perceived boundaries between named languages are crossed. This study of an experienced bilingual aims to inform our understanding of how to support emergent bilinguals in reaching their full learning potential in our schools.

Nonlinear vibration energy harvesting has been mainstream research owing to its characteristics of broadband and high-output. However, the majority of existing energy harvesters are independent nonlinear structures, or one nonlinear structure combined with a linear structure. This article proposed the method that introducing internal nonlinear resonance structure to traditional nonlinear cantilever beam, improving the performance of it in low frequency effectively. Comparison experiments demonstrate that this method can promote energy harvesting with respect to an increase in the working frequency bandwidth by a factor of 4.4. Moreover, the maximum average power density is increased to 3570%. Based on the governing equations, the numerical simulations are implemented, which shows that internal beam with magnet has better performance than internal beam without magnet and its maximum amplitude can be increased by a factor of 7.8. Besides, two internal beams with magnets have the ability of frequency tuning as well. The experiment results and the numerical simulation validate that the superiority of double nonlinear structure, which provides a design idea for energy harvester subsequently.

Vibration energy harvesters with bistable characteristics, which can convert mechanical energy to electric energy, are typically cantilever beams with magnetic repulsion. In order to enhance their low-frequency performance, a seesaw-type approach has been proposed, which can make the structure overcome the potential barrier more easily. In this paper, we establish electromechanical coupling equations of the whole system, and prove that the internal beam delivers mechanical energy to the primary beam based on time-domain analysis. Meanwhile, frequency-domain analysis and solutions are conducted to investigate the dynamical and electrical behaviors of the system based on the adjustment of different parameters. We find that both the mechanical and electrical responses are enhanced gradually with the decrease of the relative damping coefficient within the bounds of the discussion. And the maximum response amplitude can be increased by a factor of 11.3 just by adjusting the position of the internal beam. Furthermore, the length of the internal beam can affect the responses of the system visibly and regularly, and the maximum response amplitude remains unchanged when changing the length of the internal beam from 80 to 100 mm. All of this suggests that the mechanisms of a seesaw-type energy harvester will provide guidance for designing a more appropriate structure, depending on different applications.

The modal-learning displacement–strain transformation has been proved to be able to predict the strain of the typical uniform beam. However, as the complexity of the structure increases, for example, the shape of the beam cross-section changes. The typical displacement–strain transformation is no longer applicable due to the unknown mode function. To further explore this issue, the hypergeometric and Meijer-G functions are used to establish the mode shape function with good structural adaptability. A displacement–strain transformation method based on the hypergeometric and Meijer-G functions is proposed to predict the dynamic strain of the variable cross-section beam. Experiment results demonstrate that the proposed method can solve the problem of full-field strain prediction for beams with variable sections and boost the displacement–strain transformation’s theoretical calculation accuracy. Under sinusoidal excitation and random excitation, the strain prediction accuracy reaches 99.69% and 99.25%, respectively. This approach simplifies the preprocessing of the structure, and provides a welcome boost to developing the displacement–strain transformation method in full-field strain measurement.

Harvesting the ambient broadband vibrational energy is the ultimate objective of multi-stable vibration energy harvesters. The potential energy of a multi-stable system has more potential wells corresponding stable equilibrium states than a linear energy harvester, and the lower excitation energy is required to overcome the potential barriers to broaden the working bandwidth. However, for traditional multi-stable harvesters, increasing the number of stable equilibrium states to improve energy harvesting efficiency in random frequency bands is difficult. Without the need of external magnets generating static magnetic field, we propose an annularly-distributed poly-stable array which makes stable equilibrium states grow exponentially in maximum number. The experiments indicate that, comparing with a corresponding linear energy harvester, the working frequency bandwidth widened to 283%, the power density increased by a factor of 577 and the electric field energy raised to 133%. The proposed array shows the superiority in broadband vibrational energy harvesting and provides a solution collecting the abundant energy renewable in nature.