Functional control structure model for the complex systems and its application in system safety analysis

The safety problem for the complex system is regarded as a control problem other than probability one, where the overall functional control structure model of the complex system could be configured in terms of the relationships among their functional labels. The hazards are due to the unsafe control actions (UCA), or the malfunctional control action (MCA). Meanwhile, UCA and MCA are due to the error feedback information (EFI), the error environment variables (EEV), the error state variables (ESE), the error command inputs (ECI), the error working modes (EWM), and the error process models (EPM), etc. Every function or component would be described as 10 labels, which are the input command (IC), the feedback to the upper level (FU), the control action (CA), the feedback from the lower levels (FL), the external input command (EC), the process model (PM), other related state variable (SV), the precondition (PC), the resource and the executing condition (RE) of the system, and the environment variable (EV). The aircraft wheel brake system’s control structure model is given to show its effectiveness

Saliency Based Opportunitstic Search for Object Part Extraction and Labeling

We study the task of object part extraction and labeling, which seeks to understand objects beyond simply identifiying their bounding boxes. We start from bottom-up segmentation of images and search for correspondences between object parts in a few shape models and segments in images. Segments comprising different object parts in the image are usually not equally salient due to uneven contrast, illumination conditions, clutter, occlusion and pose changes. Moreover, object parts may have different scales and some parts are only distinctive and recognizable in a large scale. Therefore, we utilize a multi-scale shape representation of objects and their parts, figural contextual information of the whole object and semantic contextual information for parts. Instead of searching over a large segmentation space, we present a saliency based opportunistic search framework to explore bottom-up segmentation by gradually expanding and bounding the search domain.We tested our approach on a challenging statue face dataset and 3 human face datasets. Results show that our approach significantly outperforms Active Shape Models using far fewer exemplars. Our framework can be applied to other object categories

Surface-SOS:Self-Supervised Object Segmentation via Neural Surface Representation

Self-supervised Object Segmentation (SOS) aims to segment objects without any annotations. Under conditions of multi-camera inputs, the structural, textural and geometrical consistency among each view can be leveraged to achieve fine-grained object segmentation. To make better use of the above information, we propose Surface representation based Self-supervised Object Segmentation (Surface-SOS), a new framework to segment objects for each view by 3D surface representation from multi-view images of a scene. To model high-quality geometry surfaces for complex scenes, we design a novel scene representation scheme, which decomposes the scene into two complementary neural representation modules respectively with a Signed Distance Function (SDF). Moreover, Surface-SOS is able to refine single-view segmentation with multi-view unlabeled images, by introducing coarse segmentation masks as additional input. To the best of our knowledge, Surface-SOS is the first self-supervised approach that leverages neural surface representation to break the dependence on large amounts of annotated data and strong constraints. These constraints typically involve observing target objects against a static background or relying on temporal supervision in videos. Extensive experiments on standard benchmarks including LLFF, CO3D, BlendedMVS, TUM and several real-world scenes show that Surface-SOS always yields finer object masks than its NeRF-based counterparts and surpasses supervised single-view baselines remarkably.</p

New Developments in Aromatic Halogenation, Borylation, and Cyanation

Several green procedures have been developed for synthesizing functionalized aromatics: i) AuCl3-catalyzed halogenation of aromatic compounds, including aryl boronates; ii) Fe2O3-catalyzed direct aromatic C–H bond borylation; iii) Pd-catalyzed direct cyanation of indoles; iv) direct conversion of arylamines to pinacol boronates

Experimental study of PLLA/INH slow release implant fabricated by three dimensional printing technique and drug release characteristics in vitro

BACKGROUND: Local slow release implant provided long term and stable drug release in the lesion. The objective of this study was to fabricate biodegradable slow release INH/PLLA tablet via 3 dimensional printing technique (3DP) and to compare the drug release characteristics of three different structured tablets in vitro. METHODS: Three different drug delivery systems (columnar-shaped tablet (CST), doughnut-shaped tablet (DST) and multilayer doughnut-shaped tablet (MDST)) were manufactured by the three dimensional printing machine and isoniazid was loaded into the implant. Dynamic soaking method was used to study the drug release characteristics of the three implants. MTT cytotoxicity test and direct contact test were utilized to study the biocompatibility of the implant. The microstructures of the implants’ surfaces were observed with electron microscope. RESULTS: The PLLA powder in the tablet could be excellently combined through 3DP without disintegration. Electron microscope observations showed that INH distributed evenly on the surface of the tablet in a “nest-shaped” way, while the surface of the barrier layer in the multilayer doughnut shaped tablet was compact and did not contain INH. The concentration of INH in all of the three tablets were still higher than the effective bacteriostasis concentration (Isoniazid: 0.025 ~ 0.05 μg/ml) after 30 day’s release in vitro. All of the tablets showed initial burst release of the INH in the early period. Drug concentration of MDST became stable and had little fluctuation starting from the 6th day of the release. Drug concentration of DST and CST decreased gradually and the rate of decrease in concentration was faster in DST than CST. MTT cytotoxicity test and direct contact test indicated that the INH-PLLA tablet had low cytotoxicity and favorable biocompatibility. CONCLUSIONS: Three dimensional printing technique was a reliable technique to fabricate complicated implants. Drug release pattern in MDST was the most stable among the three implants. It was an ideal drug delivery system for the antibiotics. Biocompatibility tests demonstrated that the INH-PLLA implant did not have cytotoxicity. The multilayer donut-shaped tablet provided a new constant slow release method after an initial burst for the topical application of the antibiotic