Dexterous manipulation, especially dexterous grasping, is a primitive and crucial ability of robots that allows the implementation of performing human-like behaviors. Deploying the ability on robots enables them to assist and substitute human to accomplish more complex tasks in daily life and industrial production. A comprehensive review of the methods based on point cloud and deep learning for robotics dexterous grasping from three perspectives is given in this paper. As a new category schemes of the mainstream methods, the proposed generation-evaluation framework is the core concept of the classification. The other two classifications based on learning modes and applications are also briefly described afterwards. This review aims to afford a guideline for robotics dexterous grasping researchers and developers.
Large language models (LLMs) are excellent few-shot learners. They can perform a wide variety of tasks purely based on natural language prompts provided to them. These prompts contain data of a specific downstream task -- often the private dataset of a party, e.g., a company that wants to leverage the LLM for their purposes. We show that deploying prompted models presents a significant privacy risk for the data used within the prompt by instantiating a highly effective membership inference attack. We also observe that the privacy risk of prompted models exceeds fine-tuned models at the same utility levels. After identifying the model's sensitivity to their prompts -- in the form of a significantly higher prediction confidence on the prompted data -- as a cause for the increased risk, we propose ensembling as a mitigation strategy. By aggregating over multiple different versions of a prompted model, membership inference risk can be decreased.
Abstract Background Curcumin, as a lipid-lowering drug, has been reported to be effective in the treatment of breast cancer. However, the underlying molecular mechanisms have not been completely investigated. Methods MTT assay was used to determine the effect of curcumin on survival rate of MCF-7 cells. The effects of curcumin on tumor growth were observed in animal models of breast cancer. The positive reactions of Caspase-1, IL-1β and IL-18 were detected by immunohistochemistry. LC3, p62, CTSB, ASC, Pro-Caspase-1, GSDMD, NLRP3, Caspase-1, GSDMD-N, IL-1β and IL-18 were determined by Western blot in vitro and vivo. The release of extracellular IL-1β and IL-18 was determined by ELISA. LDH release was measured. The expression level of CTSB in cytoplasm were determined by immunofluorescence assay. Cell proliferation, cell migration and tube formation assays were used to determine the abilities of cells. In this study, NLRP3 inflammasome inhibitor MCC950, cathepsin B inhibitor CA-074 ME and autophagy inhibitor 3-MA were used to act on cells to investigate the role of NLRP3 inflammasome, cathepsin B and autophagy in curcumin-induced pyroptosis of MCF-7 breast cancer cells. Results In mouse model of breast cancer, we observed that curcumin treatment significantly induced cell autophagy and pyroptosis. In human breast cancer MCF-7 cells, we found that curcumin induced pyroptotic cell death was dependent on the activation of NLRP3/Caspase-1/GSDMD signaling pathway, which was CTSB-dependent. In addition, curcumin-induced cell autophagy caused lysosomal rupture and CTSB release. Furthermore, NLRP3 inhibitor (MCC950) significantly suppressed curcumin-induced pyroptosis, as well as CTSB inhibitor (CA074 Me) and autophagy inhibitor (3-MA). Besides, we also found that curcumin suppressed cell proliferation, cell migration and tube formation, which could be reversed by inhibitors. Conclusions In summary, our results demonstrated that curcumin induced MCF-7 cell pyroptosis by the activation of autophagy/CTSB/NLRP3/Caspase-1/GSDMD signaling pathway. These findings offer novel insights into the potential molecular mechanisms of curcumin in treatment of breast cancer.
Introduction: Our previous studies have demonstrated that the upregulation of renal CD81 (cluster of differentiation 81), contributes to the sustained hypertension observed in LPS-preeclampsia rats with kidney injuries. Candesartan (Can) lowers blood pressure by selectively blocking type 1 angiotensin II receptors and results in acute kidney injury (AKI) when used together with dietary sodium restriction. Various cell deaths including apoptosis and necrosis are involved in the pathogenesis of AKI. Hypothesis: Renal CD81 may increased in candesartan/low salt diet(LS+Can) model via activation of apoptosis. Methods: Male SD rats aged 8-10 weeks were fed with LS (0.01% NaCl) or normal salt diets (NS, 0.8% NaCl) (6-10rats/group) respectively for 7 days.All rats were intraperitoneally injected with candesartan (1mg/kg/d) simultaneously.Systolic blood pressure(SBP) was monitored with tail-cuff method.The rats were sacrificed by over-anesthesia after the samples of blood and urine (metabolic cage) were collected.The kidneys were immediately removed for immunoblotting, and TUNEL(TdT-mediated dUTP Nick-End Labeling) measurements.P<0.05 was considered significant for 2 group comparison with t-test. Results: Compared with rats on NS+Can, the serum creatinine (20.3±0.3 vs 50.8±4.2 mmol/L) and BUN(4.05±0.2 vs 18.6±2.5 mmol/L) were more than doubled in LS+Can rats ;Creatinine clearance was decreased (100±4.1 vs 40.8±3.7ml/min); systolic blood pressures was lowered slightly (101.7±1.7 vs 88.9±2.7mmHg, n=7-8). Renal CD81 protein abundance by immunoblotting was increased (258.8±52.4,% of control, n=6/group,p<0.05, same as below).At the same time, there were increases in apoptosis-associated proteins including bax(312.6±71.5),caspase-3(124.6±6) ,cleaved caspase3(133.8±9.6) in Can+LS group.The rate of tunel-positive cells was elevated in the Can+LS group. (100.0±8.5 vs 482.72±59.4,p<0.05,n=10/group).However, necrosis-related inflammatory factors, including Interleukin-6,tumor necrosis factor-α, were not affected in the rat kidneys from LS+Can treated rats. Conclusions: Our findings suggest that Increased CD81 may be associated with enhanced apoptosis in rat kidneys with acute kidney injuries.
For improving the range accuracy of LFMCW Radar with triangle wave modulation, frequency estimation performance of Jacobsen algorithm and Quinn algorithm are discussed. When the signal frequency is close to the midpoint of two neighboring discrete frequencies, Jacobsen algorithm has poor accuracy, while Quinn algorithm has good one. A novel combined algorithm named J-Quinn algorithm is proposed. Firstly, Jacobsen algorithm is employed for coarse frequency estimation. Secondly, the signal frequency is shifted to the midpoint of two neighboring discrete frequencies, and then Quinn algorithm is employed for fine frequency estimation. The simulation shows that J-Quinn algorithm has higher range accuracy and good stability. Ranging experiments are performed with LFMCW Radar, and the results show that range error can be diminished to 0.04m, so the ranging performance is improved.
LFM signal is widely used in the domain of radar, sonar and communication. Both reliability and real-time is important for parameter estimation. The Fractional Fourier Transform exists problem of large calculation and bad real-time performance. To solve the problem, we use the Energy Barycenter Correction Method based on Nuttall window, combining with the idea of descending dimension. This method accomplish the task of turning two-dimensional search into one-dimensional search and get accurate estimates of frequency modulation ratio. At last, we use the method of the Fractional Fourier Transform to estimate Initial Frequency. So the real-time performance can be ensured, and the estimation accuracy can be improved. The simulation results show the validity and accuracy of the method, and the method has certain engineering application value.
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