Multiscale Functional and Molecular Photoacoustic Tomography

Photoacoustic tomography (PAT) combines rich optical absorption contrast with the high spatial resolution of ultrasound at depths in tissue. The high scalability of PAT has enabled anatomical imaging of biological structures ranging from organelles to organs. The inherent functional and molecular imaging capabilities of PAT have further allowed it to measure important physiological parameters and track critical cellular activities. Integration of PAT with other imaging technologies provides complementary capabilities and can potentially accelerate the clinical translation of PAT

Photoacoustic Tomography: Principles and Advances

Photoacoustic tomography (PAT) is an emerging imaging modality that shows great potential for preclinical research and clinical practice. As a hybrid technique, PAT is based on the acoustic detection of optical absorption from either endogenous chromophores, such as oxy-hemoglobin and deoxy-hemoglobin, or exogenous contrast agents, such as organic dyes and nanoparticles. Because ultrasound scatters much less than light in tissue, PAT generates high-resolution images in both the optical ballistic and diffusive regimes. Over the past decade, the photoacoustic technique has been evolving rapidly, leading to a variety of exciting discoveries and applications. This review covers the basic principles of PAT and its different implementations. Strengths of PAT are highlighted, along with the most recent imaging results

Active Flow Control for Bluff Body Drag Reduction Using Reinforcement Learning with Partial Measurements

Active flow control for drag reduction with reinforcement learning (RL) is performed in the wake of a 2D square bluff body at laminar regimes with vortex shedding. Controllers parameterized by neural networks are trained to drive two blowing and suction jets. RL with full observability (sensors in the wake) successfully discovers a control policy which reduces the drag by suppressing the vortex shedding in the wake. However, a non-negligible performance degradation (~50\% less drag reduction) is observed when the controller is trained with partial measurements (sensors on the body). To mitigate this effect, we propose a dynamic, energy-efficient, maximum entropy RL control scheme. First, an energy-efficiency-based reward function is proposed to optimize the energy consumption of the controller while maximising drag reduction. Second, the controller is trained with an augmented state consisting of both current and past observations and actions, which can be formulated as a nonlinear autoregressive exogenous model, to alleviate the partial observability problem. Third, maximum entropy RL algorithms which promote exploration and exploitation in a sample efficient way are used and discover near-optimal policies in the challenging case of partial measurements. Complete stabilisation of the vortex shedding is achieved in the near wake using only surface pressure measurements on the rear of the body, resulting in similar drag reduction as in the case with wake sensors. The proposed approach opens new avenues for dynamic flow control using partial measurements for realistic configurations

Integration of persistent Laplacian and pre-trained transformer for protein solubility changes upon mutation

Protein mutations can significantly influence protein solubility, which results in altered protein functions and leads to various diseases. Despite of tremendous effort, machine learning prediction of protein solubility changes upon mutation remains a challenging task as indicated by the poor scores of normalized Correct Prediction Ratio (CPR). Part of the challenge stems from the fact that there is no three-dimensional (3D) structures for the wild-type and mutant proteins. This work integrates persistent Laplacians and pre-trained Transformer for the task. The Transformer, pretrained with hunderds of millions of protein sequences, embeds wild-type and mutant sequences, while persistent Laplacians track the topological invariant change and homotopic shape evolution induced by mutations in 3D protein structures, which are rendered from AlphaFold2. The resulting machine learning model was trained on an extensive data set labeled with three solubility types. Our model outperforms all existing predictive methods and improves the state-of-the-art up to 15%

Fabrication of cell patches using biodegradable scaffolds with a hexagonal array of interconnected pores (SHAIPs)

Cell patches are widely used for healing injuries on the surfaces or interfaces of tissues such as those of epidermis and myocardium. Here we report a novel type of porous scaffolds made of poly(d,l-lactic-co-glycolic acid) for fabricating cell patches. The scaffolds have a single layer of spherical pores arranged in a unique hexagonal pattern and are therefore referred to as “scaffolds with a hexagonal array of interconnected pores (SHAIPs)”. SHAIPs contain both uniform pores and interconnecting windows that can facilitate the exchange of biomacromolecules, ensure homogeneous cell seeding, and promote cell migration. As a proof-of-concept demonstration, we have created skeletal muscle patches with a thickness of approximately 150 μm using SHAIPs. The myoblasts seeded in the scaffolds maintained high viability and were able to differentiate into multi-nucleated myotubes. Moreover, neovasculature could efficiently develop into the patches upon subcutaneous implantation in vivo

Export Destination, Skill Utilization and Skill Premium in Chinese Manufacturing sector

This paper analyzes the link between export destination, skill utilization and skill premium. We develop the mechanism behind these links: the difference in quality valuation of the product across exporting destinations and the distribution of level of skill among the skilled workers in the labor market. Theory suggest that the consumers in the high income countries value the quality of the same product more than their counterparts in middle or low income countries. To produce a higher quality product, a firm needs not only more skilled workers but also higher quality skilled workers. To attract and keep the higher quality worker, firm needs to incentivize her by providing higher wage as compared to the firms that would be exporting to middle or low income countries. We test this theory using cross-section of more than 160,000 single product Chinese Manufacturing firms survey data, of which nearly 22,000 are exporting to more than 200 countries across the world. We find that firms exporting to high income countries pay higher average wages, hire more skilled workers, defined by education level, and pay higher skill premium as compared to firms exporting to middle or low income countries or selling domestically. Similar to the recent literature, we also didn’t find the impact of exporting per se on the proportion of skilled workers or the skill premium in the firm

Export Destination, Skill Utilization and Skill Premium in Chinese Manufacturing sector

This paper analyzes the link between export destination, skill utilization and skill premium. We develop the mechanism behind these links: the difference in quality valuation of the product across exporting destinations and the distribution of level of skill among the skilled workers in the labor market. Theory suggest that the consumers in the high income countries value the quality of the same product more than their counterparts in middle or low income countries. To produce a higher quality product, a firm needs not only more skilled workers but also higher quality skilled workers. To attract and keep the higher quality worker, firm needs to incentivize her by providing higher wage as compared to the firms that would be exporting to middle or low income countries. We test this theory using cross-section of more than 160,000 single product Chinese Manufacturing firms survey data, of which nearly 22,000 are exporting to more than 200 countries across the world. We find that firms exporting to high income countries pay higher average wages, hire more skilled workers, defined by education level, and pay higher skill premium as compared to firms exporting to middle or low income countries or selling domestically. Similar to the recent literature, we also didn’t find the impact of exporting per se on the proportion of skilled workers or the skill premium in the firm