Task Programming: Learning Data Efficient Behavior Representations.

Specialized domain knowledge is often necessary to accurately annotate training sets for in-depth analysis, but can be burdensome and time-consuming to acquire from domain experts. This issue arises prominently in automated behavior analysis, in which agent movements or actions of interest are detected from video tracking data. To reduce annotation effort, we present TREBA: a method to learn annotation-sample efficient trajectory embedding for behavior analysis, based on multi-task self-supervised learning. The tasks in our method can be efficiently engineered by domain experts through a process we call "task programming", which uses programs to explicitly encode structured knowledge from domain experts. Total domain expert effort can be reduced by exchanging data annotation time for the construction of a small number of programmed tasks. We evaluate this trade-off using data from behavioral neuroscience, in which specialized domain knowledge is used to identify behaviors. We present experimental results in three datasets across two domains: mice and fruit flies. Using embeddings from TREBA, we reduce annotation burden by up to a factor of 10 without compromising accuracy compared to state-of-the-art features. Our results thus suggest that task programming and self-supervision can be an effective way to reduce annotation effort for domain experts.

Non-functionalized carbon nanotube binding with hemoglobin.

Carbon nanotube has a high potential to be used as a biosensor and drug carrier. However, its binding behavior with proteins needs to be studied before the full potential of carbon nanotube in biological studies can be realized. Although many studies have been conducted to characterize the affinity of functionalized carbon nanotube to various types of proteins, our present study for the first time reported that hemoglobin can bind with non-functionalized carbon nanotube, and this binding can be identified by Raman spectrum. Further, this binding has not changed Raman luminescence with specific excitation and emission wavelengths. The immediate application of these findings is to use non-functionalized carbon nanotube as a biosensor to measure H(2)S in blood in which hemoglobin takes about 37% of the total blood volume. Other potential uses of non-functionalized carbon nanotube to bind selective groups of proteins are also hinted.