Diffusion Model-Augmented Behavioral Cloning

Imitation learning addresses the challenge of learning by observing an expert's demonstrations without access to reward signals from environments. Most existing imitation learning methods that do not require interacting with environments either model the expert distribution as the conditional probability p(a|s) (e.g., behavioral cloning, BC) or the joint probability p(s, a) (e.g., implicit behavioral cloning). Despite its simplicity, modeling the conditional probability with BC usually struggles with generalization. While modeling the joint probability can lead to improved generalization performance, the inference procedure can be time-consuming and it often suffers from manifold overfitting. This work proposes an imitation learning framework that benefits from modeling both the conditional and joint probability of the expert distribution. Our proposed diffusion model-augmented behavioral cloning (DBC) employs a diffusion model trained to model expert behaviors and learns a policy to optimize both the BC loss (conditional) and our proposed diffusion model loss (joint). DBC outperforms baselines in various continuous control tasks in navigation, robot arm manipulation, dexterous manipulation, and locomotion. We design additional experiments to verify the limitations of modeling either the conditional probability or the joint probability of the expert distribution as well as compare different generative models

A Novel Adaptive Elite-Based Particle Swarm Optimization Applied to VAR Optimization in Electric Power Systems

Particle swarm optimization (PSO) has been successfully applied to solve many practical engineering problems. However, more efficient strategies are needed to coordinate global and local searches in the solution space when the studied problem is extremely nonlinear and highly dimensional. This work proposes a novel adaptive elite-based PSO approach. The adaptive elite strategies involve the following two tasks: (1) appending the mean search to the original approach and (2) pruning/cloning particles. The mean search, leading to stable convergence, helps the iterative process coordinate between the global and local searches. The mean of the particles and standard deviation of the distances between pairs of particles are utilized to prune distant particles. The best particle is cloned and it replaces the pruned distant particles in the elite strategy. To evaluate the performance and generality of the proposed method, four benchmark functions were tested by traditional PSO, chaotic PSO, differential evolution, and genetic algorithm. Finally, a realistic loss minimization problem in an electric power system is studied to show the robustness of the proposed method

A kirigami-enabled electrochromic wearable variable-emittance device for energy-efficient adaptive personal thermoregulation

For centuries, people have put effort to improve the thermal performance of clothing to adapt to varying temperatures. However, most clothing we wear today only offers a single-mode insulation. The adoption of active thermal management devices, such as resistive heaters, Peltier coolers, and water recirculation, is limited by their excessive energy consumption and form factor for long-term, continuous, and personalized thermal comfort. In this paper, we developed a wearable variable-emittance (WeaVE) device, enabling the tunable radiative heat transfer coefficient to fill the missing gap between thermoregulation energy efficiency and controllability. WeaVE is an electrically driven, kirigami-enabled electrochromic thin-film device that can effectively tune the midinfrared thermal radiation heat loss of the human body. The kirigami design provides stretchability and conformal deformation under various modes and exhibits excellent mechanical stability after 1,000 cycles. The electronic control enables programmable personalized thermoregulation. With less than 5.58 mJ/cm2 energy input per switching, WeaVE provides 4.9°C expansion of the thermal comfort zone, which is equivalent to a continuous power input of 33.9 W/m2. This nonvolatile characteristic substantially decreases the required energy while maintaining the on-demand controllability, thereby providing vast opportunities for the next generation of smart personal thermal managing fabrics and wearable technologies

Improved Breath Phase and Continuous Adventitious Sound Detection in Lung and Tracheal Sound Using Mixed Set Training and Domain Adaptation

Previously, we established a lung sound database, HF_Lung_V2 and proposed convolutional bidirectional gated recurrent unit (CNN-BiGRU) models with adequate ability for inhalation, exhalation, continuous adventitious sound (CAS), and discontinuous adventitious sound detection in the lung sound. In this study, we proceeded to build a tracheal sound database, HF_Tracheal_V1, containing 11107 of 15-second tracheal sound recordings, 23087 inhalation labels, 16728 exhalation labels, and 6874 CAS labels. The tracheal sound in HF_Tracheal_V1 and the lung sound in HF_Lung_V2 were either combined or used alone to train the CNN-BiGRU models for respective lung and tracheal sound analysis. Different training strategies were investigated and compared: (1) using full training (training from scratch) to train the lung sound models using lung sound alone and train the tracheal sound models using tracheal sound alone, (2) using a mixed set that contains both the lung and tracheal sound to train the models, and (3) using domain adaptation that finetuned the pre-trained lung sound models with the tracheal sound data and vice versa. Results showed that the models trained only by lung sound performed poorly in the tracheal sound analysis and vice versa. However, the mixed set training and domain adaptation can improve the performance of exhalation and CAS detection in the lung sound, and inhalation, exhalation, and CAS detection in the tracheal sound compared to positive controls (lung models trained only by lung sound and vice versa). Especially, a model derived from the mixed set training prevails in the situation of killing two birds with one stone.Comment: To be submitted, 31 pages, 6 figures, 5 table

MG63 Osteoblast-Like Cells Exhibit Different Behavior when Grown on Electrospun Collagen Matrix versus Electrospun Gelatin Matrix

Electrospinning is a simple and efficient method of fabricating a non-woven polymeric nanofiber matrix. However, using fluorinated alcohols as a solvent for the electrospinning of proteins often results in protein denaturation. TEM and circular dichroism analysis indicated a massive loss of triple-helical collagen from an electrospun collagen (EC) matrix, and the random coils were similar to those found in gelatin. Nevertheless, from mechanical testing we found the Young's modulus and ultimate tensile stresses of EC matrices were significantly higher than electrospun gelatin (EG) matrices because matrix stiffness can affect many cell behaviors such as cell adhesion, proliferation and differentiation. We hypothesize that the difference of matrix stiffness between EC and EG will affect intracellular signaling through the mechano-transducers Rho kinase (ROCK) and focal adhesion kinase (FAK) and subsequently regulates the osteogenic phenotype of MG63 osteoblast-like cells. From the results, we found there was no significant difference between the EC and EG matrices with respect to either cell attachment or proliferation rate. However, the gene expression levels of OPN, type I collagen, ALP, and OCN were significantly higher in MG63 osteoblast-like cells grown on the EC than in those grown on the EG. In addition, the phosphorylation levels of Y397-FAK, ERK1/2, BSP, and OPN proteins, as well as ALP activity, were also higher on the EC than on the EG. We further inhibited ROCK activation with Y27632 during differentiation to investigate its effects on matrix-mediated osteogenic differentiation. Results showed the extent of mineralization was decreased with inhibition after induction. Moreover, there is no significant difference between EC and EG. From the results of the protein levels of phosphorylated Y397-FAK, ERK1/2, BSP and OPN, ALP activity and mineral deposition, we speculate that the mechanism that influences the osteogenic differentiation of MG63 osteoblast-like cells on EC and EG is matrix stiffness and via ROCK-FAK-ERK1/2

Managing cardiac arrest with refractory ventricular fibrillation in the emergency department: Conventional cardiopulmonary resuscitation versus extracorporeal cardiopulmonary resuscitation

AbstractAimRefractory ventricular fibrillation, resistant to conventional cardiopulmonary resuscitation (CPR), is a life threatening rhythm encountered in the emergency department. Although previous reports suggest the use of extracorporeal CPR can improve the clinical outcomes in patients with prolonged cardiac arrest, the effectiveness of this novel strategy for refractory ventricular fibrillation is not known. We aimed to compare the clinical outcomes of patients with refractory ventricular fibrillation managed with conventional CPR or extracorporeal CPR in our institution.MethodThis is a retrospective chart review study from an emergency department in a tertiary referral medical center. We identified 209 patients presenting with cardiac arrest due to ventricular fibrillation between September 2011 and September 2013. Of these, 60 patients were enrolled with ventricular fibrillation refractory to resuscitation for more than 10min. The clinical outcome of patients with ventricular fibrillation received either conventional CPR, including defibrillation, chest compression, and resuscitative medication (C-CPR, n=40) or CPR plus extracorporeal CPR (E-CPR, n=20) were compared.ResultsThe overall survival rate was 35%, and 18.3% of patients were discharged with good neurological function. The mean duration of CPR was longer in the E-CPR group than in the C-CPR group (69.90±49.6min vs 34.3±17.7min, p=0.0001). Patients receiving E-CPR had significantly higher rates of sustained return of spontaneous circulation (95.0% vs 47.5%, p=0.0009), and good neurological function at discharge (40.0% vs 7.5%, p=0.0067). The survival rate in the E-CPR group was higher (50% vs 27.5%, p=0.1512) at discharge and (50% vs 20%, p=0. 0998) at 1 year after discharge.ConclusionsThe management of refractory ventricular fibrillation in the emergency department remains challenging, as evidenced by an overall survival rate of 35% in this study. Patients with refractory ventricular fibrillation receiving E-CPR had a trend toward higher survival rates and significantly improved neurological outcomes than those receiving C-CPR