D Zhao

This paper proposes IDEAL, a phenomenological information-theoretic ontology of art: art is interiority deliberately externalized aesthetically and lossily. Against expressionist, symbolic, institutional, historical-intentionalist, and anti-definitional accounts, I argue that prior theories often mistake one component of the artistic process for arthood itself. IDEAL locates the origin of arthood in the creation side of a creation-and-reception chain: a conscious interior payload is mapped into external form through aesthetic encoding, becoming available for partial reconstruction by an audience. The theory distinguishes art from ordinary communication, utilitarian design, natural beauty, biological display, and unconscious expression, while explaining difficult cases such as Paleolithic cave painting, Duchamp’s Fountain, outsider art, forgeries, functional objects, AI-generated artifacts, and “Is It Cake?” Beauty, expression, symbolism, institutional context, and historical relation are not competing essences of art, but different roles within a deeper ontological structure.

The behavior of somatic stem cells is regulated by their niche. Interaction between hematopoietic stem cells (HSCs) and their niches are a representative model to understand stem cell‐niche interplay. Here, we provide an overview of crosstalk between HSCs and their niches in bone marrow and extramedullary organs following the life journey of HSCs from emergence, development, maturation until aging. We highlight the unique differences of HSC niches in different life stages within various organs focusing on recent literature to propose new speculations and hypotheses.

The cGAS‐STING signaling pathway plays a pivotal role in sensing cytosolic DNA and initiating innate immune responses against various threats, with disruptions in this pathway being associated with numerous immune‐related disorders. Therefore, precise regulation of the cGAS‐STING signaling is crucial to ensure appropriate immune responses. Recent research, including ours, underscores the importance of protein condensation in driving the activation and maintenance of innate immune signaling within the cGAS‐STING pathway. Consequently, targeting condensation processes in this pathway presents a promising approach for modulating the cGAS‐STING signaling and potentially managing associated disorders. In this review, we provide an overview of recent studies elucidating the role and regulatory mechanism of protein condensation in the cGAS‐STING signaling pathway while emphasizing its pathological implications. Additionally, we explore the potential of understanding and manipulating condensation dynamics to develop novel strategies for mitigating cGAS‐STING‐related disorders in the future.

The business environment is increasingly uncertain due to the rapid development of disruptive information technologies, the changing global economy, and the COVID-19 pandemic. This brings great uncertainties to investors to predict the performance changes and risks of companies. This research proposes a sequential data-based framework that aggregates data from multiple sources including both structured and unstructured data to predict the performance changes. It leverages data generated from the early risk warning system in China stock market to measure and predict organization performance changes based on the risk warning status changes of public companies. Different from the models in existing literature that focus on the prediction of risk warning of companies, our framework predicts a portfolio of organization performance changes, including business decline and recovery, thus helping investors to not only predict public company risks, but also discover investment opportunities. By incorporating sequential data, our framework achieves 92.3% macro-F1 value on real-world data from listed companies in China, outperforming other static models.

Examining the effect of hedge fund activism on gender diversity, we find that the number of female directors decreases after a firm is targeted by hedge fund activism. Using the employment history data from BoardEx, we find that activist hedge funds are more likely to appoint people with finance backgrounds to the boards of target firms. And the newly appointed finance background directors are almost all male because of the lack of diversity in the finance industry. The lack of gender diversity of the hedge funds’ networks and the lack of qualified female directors in the local area also help explain the impact of hedge fund activism on gender diversity on the board.

Based on the evolutionary game theory, this article constructs a quartet evolutionary game model for debt restructuring with the participation of asset management companies; studies the interactive mechanism of complex behaviors among the government, banks, asset management companies, and enterprises; and analyzes the stability of the strategies of each game subject. It also analyzes the stability of the equilibrium points in the system and finds the stable points that maximize the interests of each subject. Research shows that the government chooses to give specific support, banks choose debt-to-equity swaps, asset management companies choose to provide liquidity, and enterprises choose to work hard, which can better promote the debt restructuring process. Finally, using Matlab2018 software to analyze the impact of each essential element in the debt restructuring on the stability of system evolution, the research results provide a basis for the successful debt restructuring of the enterprises.

Subgraph matching on a large graph has become a popular research topic in the field of graph analysis, which has a wide range of applications including question answering and community detection. However, traditional edge-cutting strategy destroys the structure of indivisible knowledge in a large RDF graph. On the premise of load-balancing on subgraph division, a dominance-partitioned strategy is proposed to divide a large RDF graph without compromising the knowledge structure. Firstly, a dominance-connected pattern graph is extracted from a pattern graph to construct a dominance-partitioned pattern hypergraph, which divides a pattern graph as multiple fish-shaped pattern subgraphs. Secondly, a dominance-driven spectrum clustering strategy is used to gather the pattern subgraphs into multiple clusters. Thirdly, the dominance-partitioned subgraph matching algorithm is designed to conduct all isomorphic subgraphs on a cluster-partitioned RDF graph. Finally, experimental evaluation verifies that our strategy has higher time-efficiency of complex queries, and it has a better scalability on multiple machines and different data scales.