Technological collaboration has become an important means of sharing technological risks and advancing key technological breakthroughs. However, existing studies often overlook patent value heterogeneity in technology representation and insufficiently integrate multiple technological drivers of collaboration, while also lacking effective modeling of their dynamic evolution. This study proposes a Dynamic Multi-View Graph Neural Network model based on Semantic and Quality fusion (SQ-DMVGNN). A semantic-quality fusion module is designed to project applicants’ textual semantic features and multidimensional quality attributes into a unified high-dimensional vector space, thereby capturing both technological semantics and patent quality. Then, the proposed framework constructs a dynamic multi-view graph structures to systematically decouple and integrate technological similarity, complementarity, and strategic trend, while modeling their evolution across time slices. Through the proposed framework, SQ-DMVGNN more accurately captures the multidimensional technological relationships underlying collaborations driven by high-quality technological resources, thereby improving both the performance and interpretability of collaboration prediction in dynamic environments. This study selects the representative semiconductor industry as empirical data, obtaining a total of 668,790 non-duplicated invention patents. Experimental results demonstrate that integrating patent quality into technological portfolios enables a more precise differentiation of technological heterogeneity among organizations. Compared with baseline methods grounded in different principles, the proposed model generally achieves near-optimal performance across major evaluation metrics, particularly in AUC, AP, MRR, and Hits@K. Ablation studies not only validate the effectiveness of each auxiliary view, temporal module, and patent quality, but also investigate model substitutions. Moreover, our work conducts parameter sensitivity analyses across different modules, verifying the stability of technological knowledge extraction and collaboration prediction.
Given a graph F, a hypergraph is called a Berge-F if it can be obtained by expanding each edge of F into a hyperedge containing it. Let Mk denote the matching of size k. Kang, Ni, and Shan [12] determined the Turán number of Berge-Mk. Our main result shows that if an r-uniform hypergraph H on n vertices has nearly as many edges as the extremal in their theorem without containing Berge-Mk, then H must be structurally close to certain well-specified graphs. Meanwhile, our result also implies several stability results, such as the stability version of the well-known Erdős-Gallai theorem (Erdős and Gallai, 1959 [5]).
Gallium (Ga)-based biomaterials have emerged as versatile therapeutic platforms owing to the iron-mimicking properties and broad biological activities of gallium. Coordination engineering regulates Ga speciation, stability, transport, and therapeutic activation; however, optimizing individual physicochemical properties does not necessarily improve biological performance. Excessive coordination stability may restrict ligand exchange and therapeutic activation, whereas insufficient stability may cause premature dissociation, nonspecific exposure, and reduced target delivery.In this Review, we propose Biological Accessibility as a multidimensional, time-dependent property describing the spatiotemporal availability of biologically active gallium species to relevant biological environments, cells, and molecular or tissue targets throughout the therapeutic lifecycle. We first examine ligand chemistry, coordination thermodynamics, ligand-exchange kinetics, gallium speciation under physiological conditions, and disease-responsive coordination evolution. We then review representative coordination-engineered gallium platforms and their applications in antibacterial therapy, immunomodulation, cancer treatment, bone regeneration, bioimaging, and theranostics, highlighting coordination-regulated transport, localization, cellular accessibility, activation, retention, and clearance. Building on these advances, we develop a dynamic framework linking continuous coordination evolution with Biological Accessibility across systemic, pathological, and intracellular environments. We further discuss Therapeutic and Off-target Accessibility, disease-specific accessibility windows, mechanistic attribution of biological functions, quantitative evaluation, in vivo coordination evolution, predictive modeling, artificial intelligence-assisted design, biosafety, and clinical translation. This framework provides a conceptual basis for accessibility-guided design of next-generation gallium biomaterials and broader coordination-engineered therapeutic systems.
Rapid urbanization and unprecedented population mobility in China have intensified the need to understand the drivers of migrants’ settlement decisions. Despite the central role of daily mobility in shaping urban experiences, little is known about how transportation convenience perceptions and travel modes influence long-term settlement intentions. This study addresses this gap by developing a multi-dimensional behavioral‑perceptual framework of transportation convenience, moving beyond single‑dimension perceptual or amenity‑based approaches. Crucially, it further examines how the effects of these perceptions vary across travel modes (walking, biking, metro, bus, and car), an aspect largely overlooked in prior research. Using the 2022 City Health Examination Survey, covering 240,177 migrants across 57 Chinese cities, and employing multi-level mixed-effects models, we examine the associations between transportation perceptions, travel modes, and settlement intentions. Findings show that more positive perceptions of transportation convenience are positively associated with settlement intentions, including the walk environment (β = 0.124, P < 0.01), riding environment (β = 0.090, P < 0.01), public transport interchanges (β = 0.131, P < 0.01), road congestion (β = 0.097, P < 0.01), and commuting time (β = 0.089, P < 0.01). The influence of transportation perceptions varies across travel modes, with active travellers (walkers and cyclists) most sensitive, public transit users moderately sensitive, and car users least sensitive. This gradient reflects how daily mobility conditions intersect with economic capacity, lifestyle, and urban integration experiences. The study contributes to theory by operationalizing behavioral attitudes in a multi-dimensional mobility framework and provides actionable guidance for urban planners. Optimizing transport infrastructure, enhancing neighborhood amenities, and tailoring interventions to specific travel modes can strengthen migrants’ sense of belonging and promote inclusive, sustainable urban development.
As a zero-carbon carrier with high energy density, the efficient utilization of hydrogen is a key pathway for achieving deep industrial decarbonization. This urgently requires the synergistic conversion of chemical and thermal energy within a multi-energy complementary framework. This study proposes a novel combined power and steam system that couples a PEMFC with a flash heat pump. The system utilizes the pressure energy from the cathode exhaust to drive a turbine for auxiliary power generation and recovers the waste heat from both the anode and cathode exhausts to preheat the reactant gases. Simultaneously, the heat pump recovers the waste heat from the cooling channel, achieving internal energy cascade utilization through an economizer and a preheater. Furthermore, a cascaded optimization method integrating data-driven modeling, feature attribution analysis, and multi-objective decision-making is established to identify the system operating conditions. The results indicate that the coefficients of determination for the surrogate models all approach 1.00, verifying the high reliability of the data-driven approach in predicting the performance of the cogeneration system. Feature attribution analysis further indicates that the current and stack temperature show the highest relative importance for the power generation efficiency and cost distribution of the PEMFC, whereas the compressor discharge pressure and make-up water flow rate act as the primary factors influencing the heating capacity and economic performance of the heat pump. The case study demonstrates that under the selected operating conditions, the cogeneration system delivers 76.96 kW of net power and 390.92 kg/h of high-temperature steam, achieving a comprehensive energy efficiency of 0.89. Moreover, the LCOE for the PEMFC and the LCOH for the heat pump are reduced to $476.75/MWh and $1.32 × 10-2/kg, respectively. Consequently, the proposed method effectively bridges operating variables and performance indicators to trade-off energy efficiency and economic viability, thereby providing theoretical guidance for low-grade PEMFC waste heat cascade utilization and advanced cogeneration system development.
