Safety Verification for Neural Networks Based on Set-boundary Analysis

Neural networks (NNs) are increasingly applied in safety-critical systems such as autonomous vehicles. However, they are fragile and are often ill-behaved. Consequently, their behaviors should undergo rigorous guarantees before deployment in practice. In this paper we propose a set-boundary reachability method to investigate the safety verification problem of NNs from a topological perspective. Given an NN with an input set and a safe set, the safety verification problem is to determine whether all outputs of the NN resulting from the input set fall within the safe set. In our method, the homeomorphism property of NNs is mainly exploited, which establishes a relationship mapping boundaries to boundaries. The exploitation of this property facilitates reachability computations via extracting subsets of the input set rather than the entire input set, thus controlling the wrapping effect in reachability analysis and facilitating the reduction of computation burdens for safety verification. The homeomorphism property exists in some widely used NNs such as invertible NNs. Notable representations are invertible residual networks (i-ResNets) and Neural ordinary differential equations (Neural ODEs). For these NNs, our set-boundary reachability method only needs to perform reachability analysis on the boundary of the input set. For NNs which do not feature this property with respect to the input set, we explore subsets of the input set for establishing the local homeomorphism property, and then abandon these subsets for reachability computations. Finally, some examples demonstrate the performance of the proposed method.Comment: 19 pages, 7 figure

Verifying Safety of Neural Networks from Topological Perspectives

Neural networks (NNs) are increasingly applied in safety-critical systems such as autonomous vehicles. However, they are fragile and are often ill-behaved. Consequently, their behaviors should undergo rigorous guarantees before deployment in practice. In this paper, we propose a set-boundary reachability method to investigate the safety verification problem of NNs from a topological perspective. Given an NN with an input set and a safe set, the safety verification problem is to determine whether all outputs of the NN resulting from the input set fall within the safe set. In our method, the homeomorphism property and the open map property of NNs are mainly exploited, which establish rigorous guarantees between the boundaries of the input set and the boundaries of the output set. The exploitation of these two properties facilitates reachability computations via extracting subsets of the input set rather than the entire input set, thus controlling the wrapping effect in reachability analysis and facilitating the reduction of computation burdens for safety verification. The homeomorphism property exists in some widely used NNs such as invertible residual networks (i-ResNets) and Neural ordinary differential equations (Neural ODEs), and the open map is a less strict property and easier to satisfy compared with the homeomorphism property. For NNs establishing either of these properties, our set-boundary reachability method only needs to perform reachability analysis on the boundary of the input set. Moreover, for NNs that do not feature these properties with respect to the input set, we explore subsets of the input set for establishing the local homeomorphism property and then abandon these subsets for reachability computations. Finally, some examples demonstrate the performance of the proposed method.Comment: 25 pages, 11 figures. arXiv admin note: substantial text overlap with arXiv:2210.0417

Critical Role of Tumor Necrosis Factor Signaling in Mesenchymal Stem Cell-Based Therapy for Autoimmune and Inflammatory Diseases

Mesenchymal stem cells (MSCs) have been broadly used as a therapy for autoimmune disease in both animal models and clinical trials. MSCs inhibit T effector cells and many other immune cells, while activating regulatory T cells, thus reducing the production of pro-inflammatory cytokines, including tumor necrosis factor (TNF), and repressing inflammation. TNF can modify the MSC effects via two TNF receptors, i.e., TNFR1 in general mediates pro-inflammatory effects and TNFR2 mediates anti-inflammatory effects. In the central nervous system, TNF signaling plays a dual role, which enhances inflammation via TNFR1 on immune cells while providing cytoprotection via TNFR2 on neural cells. In addition, the soluble form of TNFR1 and membrane-bound TNF also participate in the regulation to fine-tune the functions of target cells. Other factors that impact TNF signaling and MSC functions include the gender of the host, disease course, cytokine concentrations, and the length of treatment time. This review will introduce the fascinating progress in this aspect of research and discuss remaining questions and future perspectives

Model Predictive Control with Reach-avoid Analysis

In this paper we investigate the optimal controller synthesis problem, so that the system under the controller can reach a specified target set while satisfying given constraints. Existing model predictive control (MPC) methods learn from a set of discrete states visited by previous (sub-)optimized trajectories and thus result in computationally expensive mixed-integer nonlinear optimization. In this paper a novel MPC method is proposed based on reach-avoid analysis to solve the controller synthesis problem iteratively. The reach-avoid analysis is concerned with computing a reach-avoid set which is a set of initial states such that the system can reach the target set successfully. It not only provides terminal constraints, which ensure feasibility of MPC, but also expands discrete states in existing methods into a continuous set (i.e., reach-avoid sets) and thus leads to nonlinear optimization which is more computationally tractable online due to the absence of integer variables. Finally, we evaluate the proposed method and make comparisons with state-of-the-art ones based on several examples

Spatial pattern variation of artificial sand-binding vegetation based on UAV imagery and its influencing factors in an oasis–desert transitional zone

The spatial pattern of vegetation can reflect the impacts of the environment on plants and the response of plants to the environment, which can promote a deep understanding of the potential driving mechanisms of vegetation evolution and community maintenance. A sand-binding vegetation system without irrigation has been implemented in the oasis–desert transitional zone since the 1970 s, where the annual precipitation has been approximately 120 mm. While the mobile dunes have been effectively stabilized, a patchy pattern of sand-binding vegetation has been observed. However, we do not understand why the pattern of sand-binding vegetation changed from the initial uniform distribution to the current patchy pattern. In this study, low-altitude UAV remote sensing technology and imaging-based quantification techniques were used to explore the effects of biotic and abiotic factors on the spatial patterns of sand-binding vegetation over 50 years. The spatial pattern of Haloxylon ammodendron changed gradually from a uniform distribution to an aggregated distribution, and the degree of patch fragmentation of H. ammodendron at the landscape scale gradually increased with the age of the sand-binding vegetation. The artificial sand-binding vegetation composed of H. ammodendron showed discontinuous change in which the system state reached a transition point after 30 years and changed to another state after 40 years. There were no significant correlations between the landscape indices and soil water content in the shallow layers (0–10 cm, 10–50 cm), while the soil water content in the 50–100 cm layers was significantly negatively correlated with the class area, percentage of landscape, largest patch index, percentage of like adjacencies and aggregation index and was positively correlated with the normalized landscape shape index. The soil water content in the 100–200 cm layers was positively correlated with the number of patches and patch density. Competition intensity at the individual level had a more significant effect on the area-type indices, and competition intensity at the population level had a more significant effect on the clustering-type indices. Finally, we found that the soil water content in deep layers and competition are the main drivers of the H. ammodendron spatial pattern change from a uniform pattern to a patchy pattern. These findings enrich theory on the self-organization of vegetation in arid and semiarid environments and have important theoretical and practical significance for the establishment and management of artificial vegetation in arid areas

Synthesis and antifungal properties of 6-amino-6-deoxyinulin, a kind of precursors for facile chemical modifications of inulin

Inulin, a kind of abundant, water-soluble, renewable polysaccharide, is mainly extracted from such low-requirement crops as Jerusalem artichoke, chicory, and yacon. The objective of this study was to modify inulin at its primary hydroxyls to give 6-amino-6-deoxyinulin, allowing for the facile chemical manipulation of inulin to encourage the employment of this currently underutilized biodegradable and environmentally benign resource. Additionally, its antifungal properties against two strains of phytopathogens. Cladosporium cucumerinum (Ell.) et Arthur and Fusarium oxysporum sp. Cucumis sativus L. were also evaluated by hypha measurement in vitro and the inhibitory indices against these two fungi were 60.1% and 53.3% at 1000 mu g/mL, respectively. Because 6-amino-6-deoxyinulin is easy to prepare and exhibits improved potential activities, this material may represent an attractive new platform for chemical modifications of inulin. (C) 2011 Elsevier Ltd. All rights reserved

DataSheet_1_Response of maize yield and nitrogen recovery efficiency to nitrogen fertilizer application in field with various soil fertility.docx

Appropriate nitrogen (N) management system is essential for effective crop productivity and minimizing agricultural pollution. However, the underlying mechanistic understanding of how N fertilizer regulates crop yield via soil properties in soils with different fertilities remains unresolved. Here, we used a field experiment that spanned 3 cropping seasons to evaluate the grain yield (GY), aboveground biomass and N recovery efficiency (NRE) after treatment with five N fertilizer application rates (N0, N75, N112, N150, and N187) in soils with three levels of fertility. Our results indicated that the highest GY across low, moderate, and high fertility soils were 1.5 t hm-2 (N150), 4.9 t hm-2 (N187), and 5.4 t hm-2 (N112), respectively. The highest aboveground biomass and NRE were observed at N150 for all three levels of soil fertility, while only the N uptake by aboveground biomass of low and high fertility soils decreased at N187, confirming that excessive N fertilization results in a further decline in crop N uptake. The relationship between GY, NRE and N fertilizer application rates fit the unary quadratic polynomial model. To achieve a balance between grain production and environmental benefits in N fertilizer, appropriate N fertilizer rates were determined to be 97.5 kg hm-2, 140 kg hm-2 and 131 kg hm-2 for low, moderate and high fertility soils, respectively. Structural equation modeling suggested that GY was significant correlated with soil microbial biomass carbon (SMBC) and N directly in low fertility field, with SMBC directly in moderate fertility field, and via SOC and NO3–N in high fertility field. Therefore, a soil-based management strategy for N fertilizers could enhance food security while reducing agricultural N fertilizer inputs to mitigate environmental impacts.</p

Mesenchymal Stromal Cells Increase the Natural Killer Resistance of Circulating Tumor Cells via Intercellular Signaling of cGAS‐STING‐IFNβ‐HLA

Abstract Circulating tumor cells (CTCs) shed from primary tumors must overcome the cytotoxicity of immune cells, particularly natural killer (NK) cells, to cause metastasis. The tumor microenvironment (TME) protects tumor cells from the cytotoxicity of immune cells, which is partially executed by cancer‐associated mesenchymal stromal cells (MSCs). However, the mechanisms by which MSCs influence the NK resistance of CTCs remain poorly understood. This study demonstrates that MSCs enhance the NK resistance of cancer cells in a gap junction‐dependent manner, thereby promoting the survival and metastatic seeding of CTCs in immunocompromised mice. Tumor cells crosstalk with MSCs through an intercellular cGAS‐cGAMP‐STING signaling loop, leading to increased production of interferon‐β (IFNβ) by MSCs. IFNβ reversely enhances the type I IFN (IFN‐I) signaling in tumor cells and hence the expression of human leukocyte antigen class I (HLA‐I) on the cell surface, protecting the tumor cells from NK cytotoxicity. Disruption of this loop reverses NK sensitivity in tumor cells and decreases tumor metastasis. Moreover, there are positive correlations between IFN‐I signaling, HLA‐I expression, and NK tolerance in human tumor samples. Thus, the NK‐resistant signaling loop between tumor cells and MSCs may serve as a novel therapeutic target

Definitive Endodermal Cells Supply an in vitro Source of Mesenchymal Stem/Stromal Cells

Abstract Mesenchymal stem/Stromal cells (MSCs) have great therapeutic potentials, and they have been isolated from various tissues and organs including definitive endoderm (DE) organs, such as the lung, liver and intestine. MSCs have been induced from human pluripotent stem cells (hPSCs) through multiple embryonic lineages, including the mesoderm, neural crest, and extraembryonic cells. However, it remains unclear whether hPSCs could give rise to MSCs in vitro through the endodermal lineage. Here, we report that hPSC-derived, SOX17+ definitive endoderm progenitors can further differentiate to cells expressing classic MSC markers, which we name definitive endoderm-derived MSCs (DE-MSCs). Single cell RNA sequencing demonstrates the stepwise emergence of DE-MSCs, while endoderm-specific gene expression can be elevated by signaling modulation. DE-MSCs display multipotency and immunomodulatory activity in vitro and possess therapeutic effects in a mouse ulcerative colitis model. This study reveals that, in addition to the other germ layers, the definitive endoderm can also contribute to MSCs and DE-MSCs could be a cell source for regenerative medicine