Application of stimuli-responsive nanomedicines for the treatment of ischemic stroke

Ischemic stroke (IS) refers to local brain tissue necrosis which is caused by impaired blood supply to the carotid artery or vertebrobasilar artery system. As the second leading cause of death in the world, IS has a high incidence and brings a heavy economic burden to all countries and regions because of its high disability rate. In order to effectively treat IS, a large number of drugs have been designed and developed. However, most drugs with good therapeutic effects confirmed in preclinical experiments have not been successfully applied to clinical treatment due to the low accumulation efficiency of drugs in IS areas after systematic administration. As an emerging strategy for the treatment of IS, stimuli-responsive nanomedicines have made great progress by precisely delivering drugs to the local site of IS. By response to the specific signals, stimuli-responsive nanomedicines change their particle size, shape, surface charge or structural integrity, which enables the enhanced drug delivery and controlled drug release within the IS tissue. This breakthrough approach not only enhances therapeutic efficiency but also mitigates the side effects commonly associated with thrombolytic and neuroprotective drugs. This review aims to comprehensively summarize the recent progress of stimuli-responsive nanomedicines for the treatment of IS. Furthermore, prospect is provided to look forward for the better development of this field

A survey of practical adversarial example attacks

Abstract Adversarial examples revealed the weakness of machine learning techniques in terms of robustness, which moreover inspired adversaries to make use of the weakness to attack systems employing machine learning. Existing researches covered the methodologies of adversarial example generation, the root reason of the existence of adversarial examples, and some defense schemes. However practical attack against real world systems did not appear until recent, mainly because of the difficulty in injecting a artificially generated example into the model behind the hosting system without breaking the integrity. Recent case study works against face recognition systems and road sign recognition systems finally abridged the gap between theoretical adversarial example generation methodologies and practical attack schemes against real systems. To guide future research in defending adversarial examples in the real world, we formalize the threat model for practical attacks with adversarial examples, and also analyze the restrictions and key procedures for launching real world adversarial example attacks

Analytical Model of a Multi-Step Straightening Process for Linear Guideways Considering Neutral Axis Deviation

The cross-sectional shape of a linear guideway has been processed before the straightening process. The cross-section features influence not only the position of the neutral axis, but also the applied and residual stresses along the longitudinal direction, especially in a multi-step straightening process. This paper aims to present an analytical model based on elasto-plastic theory and three-point reverse bending theory to predict straightening stroke and longitudinal stress distribution during the multi-step straightening process of linear guideways. The deviation of the neutral axis is first analyzed considering the asymmetrical features of the cross-section. Owing to the cyclic loading during the multi-step straightening process, the longitudinal stress curves are then calculated using the linear superposition of stresses. Based on the cross-section features and the superposition of stresses, the bending moment is corrected to improve the predictive accuracy of the multi-step straightening process. Finite element analysis, as well as straightening experiments, have been performed to verify the applicability of the analytical model. The proposed approach can be implemented in the multi-step straightening process of linear guideways with similar cross-sectional shape to improve the straightening accuracy

Visual-Based Multi-Section Welding Path Generation Algorithm

As an important form of additive manufacturing, welding is widely used in steel components welding work of construction, shipbuilding and other fields. In this study, an intelligent welding path generation algorithm based on multi-section interpolation is proposed in order to deal with non-standard multi-pass welding grooves which are difficult to be handled by automatic welding equipment in the construction site. Firstly, the non-standard grooves are classified and the reasons for their occurrence are discussed. Secondly, an automatic welding additive manufacturing system framework is discussed and an appropriate detection method is selected. Then, combining with the welding standard of non-standard grooves and the characteristics of the welding process, a multi-section interpolation-based welding path generation algorithm is proposed. Finally, a visual experiment platform was built to detection the typical non-standard groove and the welding experiment is implemented to verify the feasibility of the algorithm. According to the path generated by the algorithm, the welded steel components test plate meets the actual engineering standard after quality inspection. The experimental results and simulation results conclude the algorithm can be used to generate the welding path of the non-standard groove