Adaptive Tuning of Robotic Polishing Skills based on Force Feedback Model

Acquiring human skills offers an efficient approach to tackle complex task planning challenges. When performing a learned skill model for a continuous contact task, such as robot polishing in an uncertain environment, the robot needs to be able to adaptively modify the skill model to suit the environment and perform the desired task. The environmental perturbation of the polishing task is mainly reflected in the variation of contact force. Therefore, adjusting the task skill model by providing feedback on the contact force deviation is an effective way to meet the task requirements. In this study, a phase-modulated diagonal recurrent neural network (PMDRNN) is proposed for force feedback model learning in the robotic polishing task. The contact between the tool and the workpiece in the polishing task can be considered a dynamic system. In comparison to the existing feedforward neural network phase-modulated neural network (PMNN), PMDRNN combines the diagonal recurrent network structure with the phase-modulated neural network layer to improve the learning performance of the feedback model for dynamic systems. Specifically, data from real-world robot polishing experiments are used to learn the feedback model. PMDRNN demonstrates a significant reduction in the training error of the feedback model when compared to PMNN. Building upon this, the combination of PMDRNN and dynamic movement primitives (DMPs) can be used for real-time adjustment of skills for polishing tasks and effectively improve the robustness of the task skill model. Finally, real-world robotic polishing experiments are conducted to demonstrate the effectiveness of the approach.Comment: This paper has been accepted by The 2023 IEEE International Conference on Robotics and Biomimetics (IEEE ROBIO 2023

CG-fusion CAM: Online segmentation of laser-induced damage on large-aperture optics

Online segmentation of laser-induced damage on large-aperture optics in high-power laser facilities is challenged by complicated damage morphology, uneven illumination and stray light interference. Fully supervised semantic segmentation algorithms have achieved state-of-the-art performance, but rely on plenty of pixel-level labels, which are time-consuming and labor-consuming to produce. LayerCAM, an advanced weakly supervised semantic segmentation algorithm, can generate pixel-accurate results using only image-level labels, but its scattered and partially under-activated class activation regions degrade segmentation performance. In this paper, we propose a weakly supervised semantic segmentation method with Continuous Gradient CAM and its nonlinear multi-scale fusion (CG-fusion CAM). The method redesigns the way of back-propagating gradients and non-linearly activates the multi-scale fused heatmaps to generate more fine-grained class activation maps with appropriate activation degree for different sizes of damage sites. Experiments on our dataset show that the proposed method can achieve segmentation performance comparable to that of fully supervised algorithms

Burden of carbon monoxide poisoning in China, 1990–2019: A systematic analysis of data from the global burden of disease study 2019

BackgroundCarbon monoxide (CO) poisoning is one of the most common toxic occupational diseases, but related data in China are scarce. A better understanding of the burden of CO poisoning is essential for improving its management.MethodsA systematic analysis of data from the Global Burden of Disease (GBD) Study 2019 was conducted. Following the general analytical strategy used in the GBD Study 2019, the sex- and age-specific incidence and mortality rates of CO poisoning and disability-adjusted life years (DALYs) due to CO poisoning in China were analyzed. Estimated average annual percentage changes (AAPCs) in age-standardized rates were calculated by joinpoint regression analysis. The effects of age, period and cohort on the incidence of CO poisoning and DALYs due to CO poisoning were estimated by an age-period-cohort model.ResultsThe age-standardized incidence and mortality rates as well as DALYs of CO poisoning per 100,000 population were estimated to be 21.82 [95% uncertainty interval (UI): 15.05–29.98], 0.93 (95% UI: 0.63–1.11), and 40.92 (95% UI: 28.43–47.85), respectively, in 2019. From 1990 to 2019, the AAPCs in the age-standardized incidence significantly increased in both males and females, while the age-standardized mortality rates and DALYs significantly decreased in both males and females. The incidence of CO poisoning peaked in individuals aged 15–19 years. Males had a higher burden of CO poisoning than females. The age effect showed that the relative risks (RRs) of incident CO poisoning decreased with age among males and females and that individuals aged 15–24 years had the highest RRs. The RRs of incident CO poisoning increased with time. The cohort effect showed that the incidence increased in successive birth cohorts.ConclusionsThe incidence of CO poisoning in China increased from 1990 to 2019. More attention should be given to improving the burden of CO poisoning in Chinese adolescents. The results of this study can be used by health authorities to inform preventative measures to reduce the burden of CO poisoning

Hematoporphyrin monomethyl ether-mediated photodynamic effects on THP-1 cell-derived macrophages

a b s t r a c t Photodynamic therapy (PDT) has been shown to attenuate atherosclerotic plaque progression and decrease macrophage-infiltration. The effectiveness of PDT depends strongly on the type of photosensitizers. Hematoporphyrin monomethyl ether (HMME) is a promising second-generation porphyrin-related photosensitizer for PDT. This study is designed to characterize effects of HMME-based PDT on THP-1 cellderived macrophages and define the cell-death pathway. HMME was identified to accumulate in the macrophages by fluorescence microscopy and confocal scanning laser microscope. Our data demonstrated that the intensity of laser-induced HMME fluorescence in macrophages steadily increased with the increasing incubation concentration of HMME. The survival rate of macrophages determined by MTT assay decreased with the increasing HMME concentration and irradiation time. HMME-based PDT induced macrophage apoptosis via caspase-9 and caspase-3 activation pathway detected by caspase fluorescent assay kit and flow cytometer. The PDT increased the number of apoptotic macrophages by 14-fold at 12 h post irradiation by 9 J/cm 2 635 nm diode laser. These results imply that photodynamic therapy with HMME may therefore be a useful clinical treatment for unstable atherosclerotic plaques

A multi-wavelength mid-IR laser based on BaGa4Se7 optical parametric oscillators

A multi-wavelength mid-IR laser consisting of 3.05 μm, 4.25 μm, and 5.47 μm BaGa4Se7(BGSe)optical parametric oscillators (OPOs) switched by DKDP electro-optic switches with one 10 Hz/7.6 ns pumping wave is demonstrated. Maximum energies at 3.05 μm, 4.25 μm, and 5.47 μm are 1.35 mJ, 1.03 mJ, and 0.56 mJ, respectively, corresponding to optical-to-optical conversion efficiencies of 9.4%, 7.6%, and 4.2%. To the best of our knowledge, this study is the first of generation of three mid-IR wavelength lasers using electro-optic switches. Furthermore, this study provides a viable solution for a high-energy or high-power, compact, or even portable multi-wavelength mid-IR laser device that employs a single pumping wave

The Protective Effect of Magnesium Lithospermate B on Hepatic Ischemia/Reperfusion via Inhibiting the Jak2/Stat3 Signaling Pathway

Acute inflammation is an important component of the pathogenesis of hepatic ischemia/reperfusion injury (HIRI). Magnesium lithospermate B (MLB) has strong neuroprotective and cardioprotective effects. The purpose of this study was to determine whether MLB had underlying protective effects against hepatic I/R injury and to reveal the potential mechanisms related to the hepatoprotective effects. In this study, we first examined the protective effect of MLB on HIRI in mice that underwent 1 h ischemia followed by 6 h reperfusion. MLB pretreatment alleviated the abnormal liver function and hepatocyte damage induced by I/R injury. We found that serum inflammatory cytokines, including IL-6, IL-1β, and TNF-α, were significantly decreased by MLB during hepatic ischemia/reperfusion (I/R) injury, suggesting that MLB may alleviate hepatic I/R injury via inhibiting inflammatory signaling pathways. Second, we investigated the protein level of p-Jak2/Jak2 and p-Stat3/Stat3 using Western blotting and found that MLB could significantly inhibit the activation of the Jak2/Stat3 signaling pathway, which was further verified by AG490 in a mouse model. Finally, the effect of MLB on the Jak2/Stat3 pathway was further assessed in an in vitro model of RAW 264.7 cells; 1 µg/ml LPS induced the secretion of inflammatory mediators, including IL-6, TNF-α, and activation of the Jak2/Stat3 signaling pathway. MLB significantly inhibited the abnormal secretion of inflammatory factors and the activation of the Jak2/Stat3 signaling pathway in RAW264.7 cells. In conclusion, MLB was found for the first time to reduce inflammation induced by hepatic I/R via suppressing the Jak2/Stat3 pathway

End-to-end multimodal 16-day hatching eggs classification

Sixteen-day hatching eggs are divided into fertile eggs, waste eggs, and recovered eggs. Because different categoriesmayhave the same characteristics, they are difficult to classify. Fewexisting algorithms can successfully solve this problem. To this end, we propose an end-to-end deep learning network structure that uses multiple forms of signals. First, we collect the photoplethysmography (PPG) signal of the hatching eggs to obtain heartbeat information and photograph hatching eggs with a camera to obtain blood vessel pictures. Second, we use two different network structures to process the two kinds of signals: Temporal convolutional networks are used to process heartbeat information, and convolutional neural networks (CNNs) are used to process blood vessel pictures. Then, we combine the two feature maps and use the long short-term memory (LSTM) network to model the context and recognize the type of hatching eggs. The system is then trained with our dataset. The experimental results demonstrate that the proposed end-to-end multimodal deep learning network structure is significantly more accurate than using a single modal network. Additionally, the method successfully solves the 16-day hatching egg classification problem

Effect of aging process on combustion and mechanical performance of nitroguanidine propellants

The effect of different aging times (1 day, 3 days, 5 days and 7 days) on the combustion performance and mechanical properties of nitroguanidine propellants was studied.Through the mechanical properties test of impact and compression and closed bomb test of the prepared propellants, it was found that the relative steepness of the propellants aged for 3 days under normal and low temperature conditions was all less than 1;Under normal and low temperature conditions, the impact strength of propellants aged for 5 days was the largest;Propellants aged for 7 days had the highest compressive strength at low temperatures and propellants aged for 1 day had the highest compression rate at low temperatures.Comprehensive research results show that aging time of three days has a better improvement in the combustion performance and mechanical properties of the propellants