National Science Center

<strong class="journal-contentHeaderColor">Abstract.</strong> Tropospheric ozone (O₃) pollution in warm seasons has become the key air-quality issue in the Guanzhong Basin (GZB), threatening human health despite prior successes in particulate matter control. Understanding how O₃ formation regimes (OFR) and secondary aerosol (SA) formation regimes (SAFR) evolve with time and space is critical for designing coordinated control strategies. Long-term near-surface observations (2014&ndash;2024) are combined with high-resolution WRF-Chem simulations for May&ndash;August 2022, employing scenario-based EKMA curves and source-apportionment diagnostics to resolve sectoral contributions. Results indicate a sub-seasonal OFR progression from VOCs-limited in early summer to transitional in midsummer and NO_X-limited in late summer, with anthropogenic contribution to the maximum daily averaged 8-h (MDA8) O₃ increasing from 32.8 % in May to 55.2 % in July and biogenic share peaking 18.7 % in July. SAFR follows a distinct cycle with NO_X-limited in May, VOCs-limited in June, and transitional behavior thereafter. Traffic and industrial emissions are the dominate anthropogenic divers for both O₃ and SA. These patterns highlight phases of synergistic control, where anthropogenic VOCs mitigation in June and NO_X mitigation in August maximize co-benefits while minimizing trade-offs. This study integrated dynamic OFR/SAFR diagnostics with sectoral emission inventories can provide insights into pathways toward seasonally adaptive, city-specific air quality management in the GZB.

This commentary concerns the resolution of the Supreme Administrative Court of 10 July 2025, file reference II GSK 432/25, which specifically addresses the legal nature of the Prime Minister’s countersignature granted in relation to official acts issued by the President of the Republic of Poland. The Supreme Administrative Court wrongly found, a limine, that it is an act subject to administrative court review, and therefore the complaint in this regard is admissible. Adopting the above position has fa-reaching consequences, namely the possibility of discontinuing administrative court proceedings pursuant to Article 161 § 1 item 3 of the Law on Administrative Court Procedure, withdrawing the previously granted countersignature pursuant to Article 54 § 3 of the Law on Administrative Court Procedure, and granting the Prime Minister the status of a public administration body in this respect. This ruling, in the opinion of the author of the commentary, may lead to an imbalance in the activities of the President of the Republic of Poland and the Council of Ministers in the broadly understood executive and an increase in the state of legal and political uncertainty when issuing official acts requiring the signature of the Prime Minister.

This study employs an industry-specific patent classification methodology (ISPCM) and conducts complex network analysis across temporal, industrial, and spatial dimensions to examine China’s new energy vehicle (NEV) patent collaboration network and to uncover the mechanisms underlying China’s global rise in the NEV sector. The results demonstrate the effectiveness of the ISPCM and reveal a three-phase growth pattern that is driven by policy initiatives and market expansion. Domestic entities dominate the patent landscape, with a noticeable shift from invention patents to utility model patents, which reflects a focus on application-oriented innovation. The collaboration network exhibits a heavy-tailed characteristic, and it forms an oligopolistic structure in which state-owned enterprises (SOEs) act as “innovation orchestrators,” while private firms concentrate on specialized R&amp;D. Across the industrial chain, the component segment forms the largest network, the complete vehicle segment comprises the smallest network, and the aftermarket is clustered around battery recycling. A clear divide between domestic and foreign entities suggests potential decoupling risks. The findings reveal a dual-circulation innovation model that combines state-led coordinated research with market-driven independent research, offering valuable insights for sustainable industrial transformation.

<strong class="journal-contentHeaderColor">Abstract.</strong> Styrene is the second most efficient aromatic compound in the formation of secondary organic aerosol (SOA) after toluene. Recent experiments have identified C₇ and C₈ series compounds as the main components of SOA in the photooxidation of styrene. However, their molecular structures and formation pathways remain largely uncharacterized. Herein, the formation mechanisms of highly oxidized products from the multi-generation &middot;OH oxidation of styrene are studied using the quantum chemistry methods. The calculations show that the multi-generation &middot;OH oxidation mechanisms of styrene are modulated by RO₂ and RO radicals. For the first generation &middot;OH oxidation, the addition of OH radicals to the C<em>_&beta;</em>-site of vinyl group is the dominant pathway, and the main C₇- and C₈-products are benzaldehyde, 1^st-ROOH (C₈H₁₀O₃) and 1^st-RONO₂ (C₈H₉NO₃). For the second generation &middot;OH oxidation, OH-addition reaction occurring at the <em>ortho</em>-position of 1^st-ROOH and 1^st-RONO₂ has a significant dominance. The peroxide bicyclic peroxy radicals (BPR) can react with HO₂&middot;and NO to form the C₈-products 2^nd-ROOH (C₈H₁₂O₈) and 2nd-RONO2 (C₈H₁₀N₂O₁₀). The formed peroxide bicyclic alkoxy radical (BAR) can proceed either the ring-opening reactions to form the multifunctionalized dicarbonyls and ketene-enols, or the cyclization reactions to generate the highly oxidized C₆-epoxides with the branching ratios of ~30 %. For the third generation &middot;OH oxidation, <em>syn</em>-OH-addition occurring at the C=C double bond of 2^nd-ROOH and 2^nd-RONO₂ has the smallest barrier. The major C₈-products are the multifunctionalized hydroperoxides and organic nitrates. The volatility of the multi-generation &middot;OH oxidation products significantly decreases with increasing the number of &middot;OH oxidation steps.

Zinc-ion hybrid capacitors, combining the advantages of zinc-ion batteries and supercapacitors, have amazing potential for large-scale energy storage. However, the construction of carbon cathode suitable for zinc anode kinetics and capacity is still a key challenge, hampering the development of industrialization. Inspired by the structure of the Juncus, carbon nanofibers are fabricated from crop straw via electrospinning and in situ bilayer network structure growth. The size compatibility between nanopores and solvated [Zn (H2O)6]2+ enhances ultrafast ion and electron transport for the zinc-ion storage. Moreover, interconnected pores and excellent specific surface area ensure highly efficient charge delivery at high mass loadings. The biomimetic carbon nanofibers deliver exceptional capacity (268.3 mAh g-1), battery-quality energy density (215Wh kg-1), and superior cyclic stability (96.15% retention rate after 75000 cycles at 20 A g-1), surpassing commercial porous carbon electrodes. Insights into the zinc-ion storage behavior testify that the optimal pore size for zinc-ion storage ranging to be 0.87-3.80nm, bilayer carbon network structure, and reversible surface physical/chemical interaction enable remarkable energy storage capability. This work provides simple approach for preparing efficient thick electrodes and offers valuable insights into the charge storage mechanism of zinc-ion hybrid capacitors.

Synthesis of myocardial infarction enhancement (MIE) images without contrast agents (CAs) has shown great potential to advance myocardial infarction (MI) diagnosis and treatment. It provides results comparable to late gadolinium enhancement (LGE) images, thereby reducing the risks associated with CAs and streamlining clinical workflows. The existing knowledge-and-data-driven approach has made progress in addressing the complex challenges of synthesizing MIE images (i.e., invisible myocardial scars and high inter-individual variability) but still has limitations in the interpretability of kinematic inference, morphological knowledge integration, and kinematic-morphological fusion, thereby reducing the transparency and reliability of the model and causing information loss during synthesis. In this paper, we proposed a knowledge-driven interpretative conditional diffusion model (K-ICDM), which learns kinematic and morphological information from non-enhanced cardiac MR images (CINE sequence and T1 sequence) guided by cardiac knowledge, enabling the synthesis of MIE images. Importantly, our K-ICDM introduces three key innovations that address these limitations, thereby providing interpretability and improving synthesis quality. (1) A novel cardiac causal intervention that generates counterfactual strain to intervene in the inference process from motion maps to abnormal myocardial information, thereby establishing an explicit relationship and providing the clear causal interpretability. (2) A knowledge-driven cognitive combination strategy that utilizes cardiac signal topology knowledge to analyze T1 signal variations, enabling the model to understand how to learn morphological features, thus providing interpretability for morphology capture. (3) An information-specific adaptive fusion strategy that integrates kinematic and morphological information into the conditioning input of the diffusion model based on their specific contributions and adaptively learns their interactions, thereby preserving more detailed information. Experiments on a broad MI dataset with 315 patients show that our K-ICDM achieves state-of-the-art performance in contrast-free MIE image synthesis, improving structural similarity index measure (SSIM) by at least 2.1% over recent methods. These results demonstrate that our method effectively overcomes the limitations of existing methods in capturing the complex relationship between myocardial motion and scar distribution and integrating of static and dynamic sequences, thus enabling the accurate synthesis of subtle scar boundaries.