Kimberly Wang

Intervention studies with developmental samples are difficult to implement, in particular when targeting demographically diverse communities. Online studies have the potential to examine the efficacy of highly scalable interventions aimed at enhancing development, and to address some of the barriers faced by underrepresented communities for participating in developmental research. During the COVID-19 pandemic, we executed a fully remote randomized controlled trial language intervention with third and fourth grade students from diverse backgrounds across the United States. Using this as a case study, we discuss both challenges and solutions to conducting an intensive online intervention through the various phases of the study, including recruitment, data collection, and fidelity of intervention implementation. We provide comprehensive suggestions and takeaways, and conclude by summarizing some important tradeoffs for researchers interested in carrying out such studies.

We report the design and characterization of a CMOS pixel direct charge sensor, Topmetal-II-, fabricated in a standard 0.35 μm CMOS Integrated Circuit process. The sensor utilizes exposed metal patches on top of each pixel to directly collect charge. Each pixel contains a low-noise charge-sensitive preamplifier to establish the analog signal and a discriminator with tunable threshold to generate hits. The analog signal from each pixel is accessible through time-shared multiplexing over the entire array. Hits are read out digitally through a column-based priority logic structure. Tests show that the sensor achieved a <15e- analog noise and a 200e- minimum threshold for digital readout per pixel. The sensor is capable of detecting both electrons and ions drifting in gas. These characteristics enable its use as the charge readout device in future Time Projection Chambers without gaseous gain mechanism, which has unique advantages in low background and low rate-density experiments.