Accurate flight trajectory prediction is a crucial and challenging task in air traffic control, especially for maneuver operations. Modern data-driven methods are typically formulated as a time series forecasting task and fail to retain high accuracy. Meantime, as the primary modeling method for time series forecasting, frequency-domain analysis is underutilized in the flight trajectory prediction task. In this work, an innovative wavelet transform-based framework is proposed to perform time-frequency analysis of flight patterns to support trajectory forecasting. An encoder-decoder neural architecture is developed to estimate wavelet components, focusing on the effective modeling of global flight trends and local motion details. A real-world dataset is constructed to validate the proposed approach, and the experimental results demonstrate that the proposed framework exhibits higher accuracy than other comparative baselines, obtaining improved prediction performance in terms of four measurements, especially in the climb and descent phase with maneuver control. Most importantly, the time-frequency analysis is confirmed to be effective to achieve the flight trajectory prediction task.

Polymerization in living systems has become an effective strategy to regulate cell functions and behavior. However, the requirement of high concentrations of monomers, the existence of complicated intracorporal interferences, and the demand for extra external stimulations hinder their further biological applications. Herein, a nanocompartment-confined strategy that provides a confined and secluded environment for monomer enrichment and isolation is developed to achieve high polymerization efficiency, reduce the interference from external environment, and realize broad-spectrum polymerizations in living systems. For exogenous photopolymerization, the light-mediated free-radical polymerization of sodium 4-styrenesulfonate induces a 2.7-fold increase in the reaction rate with the protection of a confined environment. For endogenous hydrogen peroxide-responsive polymerization, p‑aminodiphenylamine hydrochloride embedded in a nanocompartment not only performs a 6.4-fold higher reaction rate than that of free monomers, but also activates an effective second near-infrared photoacoustic imaging-guided photothermal immunotherapy at tumor sites. This nanocompartment-confined strategy breaks the shackles of conventional polymerization, providing a universal platform for in vivo synthesis of polymers with diverse structures and functions.

A lack of composable and tunable gene regulators has hindered efforts to engineer non-model bacteria and consortia. Toward addressing this, we explore the broad-host potential of small transcription activating RNA (STAR) and propose a design strategy to achieve tunable gene control. First, we demonstrate that STARs optimized for E. coli function across different Gram-negative species and can actuate using phage RNA polymerase, suggesting that RNA systems acting at the level of transcription are portable. Second, we explore an RNA design strategy that uses arrays of tandem and transcriptionally fused RNA regulators to precisely alter regulator concentration from 1 to 8 copies. This provides a simple means to predictably tune output gain across species and does not require access to large regulatory part libraries. Finally, we show RNA arrays can be used to achieve tunable cascading and multiplexing circuits across species, analogous to the motifs used in artificial neural networks.