Search Results (7,048)

A working-state model is proposed for the MnOx–Na₂WO₄/SiO₂ catalyst in oxidative coupling of methane (OCM), where a Na₂WO₄-rich surface environment forms an adaptive interphase that buffers the effective interfacial oxygen chemical potential and stabilizes cooperative MnO_x/Na–WO_x/Mn–O–W motifs. A thermodynamic-kinetic scheme is developed that relates (1) reaction-induced surface enrichment (structural stabilization), (2) oxygen spillover (damping of local oxygen gradients), and (3) Mn ↔ W redox exchange as an electron-oxygen buffer channel. Ex situ XPS/EDS/EPR data indicate a dynamically stratified near-surface region with chemically heterogeneous environments of Mn, W, and O. The W 4f region remains dominated by the W⁶⁺ contribution in the presence of a minor reduced component after OCM. In oxygen-deficient mixtures (CH₄/O₂ > 4), interfacial reconstruction becomes more pronounced: Mn-centered Mars–van Krevelen chemistry determines CH₄ activation and oxygen exchange, while the Na₂WO₄-rich phase ensures fast ion/oxygen transport. Observation of the EPR signal from W⁵⁺ ions in the tungstate matrix indicates the existence of reduced W intermediates at low oxygen potential. Optimization of C₂ selectivity and stability is suggested to require maintaining the catalyst within the selective window of effective interfacial μO by adjusting CH₂/O₂ and contact time, as well as controlling the architecture of the Na–W–O/MnO_x interfacial region. Full article

Background: Microbiome-oriented therapies, including fecal microbiota transplantation (FMT), phage therapy, and live biotherapeutic products (LBPs), represent a promising direction in modern biomedicine for addressing antimicrobial resistance (AMR), recurrent Clostridioides difficile infection (rCDI), and dysbiosis-associated conditions. Despite encouraging clinical outcomes, their integration into routine clinical practice remains limited due to regulatory heterogeneity and unresolved ethical challenges. Objective: This review aims to analyze international regulatory approaches to microbiome-based therapies and to identify key bioethical issues associated with their clinical application. Main content: The paper summarizes current scientific evidence and regulatory frameworks governing microbiome therapies in the United States, the European Union, Ukraine, and selected Asia-Pacific countries. Particular attention is given to differences in classification, approval pathways, and safety requirements. The review also examines major ethical concerns, including informed consent, donor screening, biosafety, data protection, and equitable access to innovative treatments. Conclusions: The analysis demonstrates that microbiome therapies have significant potential for improving clinical outcomes and supporting antimicrobial stewardship. However, their broader implementation requires the harmonization of regulatory frameworks, strengthening of biosafety standards, and development of clear ethical guidelines. International cooperation and accumulation of clinical evidence are essential for the safe and effective integration of microbiome-based interventions into healthcare systems. Full article

Aiming at the problems of the severe active–reactive power coupling, insufficient adaptive inertia–damping regulation, and degraded dynamic performance of virtual synchronous generators (VSGs) under the operating conditions of a weak grid, high resistance-to-reactance ratio, and large power angle, this paper proposes a cooperative control strategy that combines reactive power feedforward decoupling with adaptive damping–inertia regulation. First, a small-signal power model of the VSG is established, and a dynamic relative gain array is employed to quantitatively analyze the effects of the resistance-to-reactance ratio and power angle on power coupling characteristics, revealing that large power angles and high resistance-to-reactance ratios significantly aggravate active–reactive power coupling. Based on this analysis, a reactive-power-oriented feedforward decoupling strategy is designed to suppress the cross-coupling between reactive power and power angle while preserving the intrinsic inertia support characteristics of the active power loop. Eigenvalue migration analysis further demonstrates that the proposed reactive-power-oriented decoupling provides higher damping ratios and larger stability margins than conventional full active–reactive power decoupling. Furthermore, a deep deterministic policy gradient-based adaptive damping–inertia control method is developed by incorporating frequency deviation, power fluctuation, voltage deviation, and coupling degree into the state space, enabling the online coordinated optimization of virtual inertia and damping coefficients. The hardware-in-the-loop experimental results verify that the proposed strategy effectively suppresses active–reactive power coupling, reduces power overshoot and oscillation, enhances frequency support capability and dynamic response speed, and maintains superior stability under weak grid conditions. Sensitivity analysis under grid impedance estimation errors further confirms its strong robustness against parameter uncertainty, while tests under composite disturbance scenarios demonstrate excellent transient performance. The proposed strategy provides an effective solution for improving the grid-connected operation performance and adaptability of VSGs in low-inertia power systems. Full article

With the increasing penetration of distributed renewable energy, coordinated operation between distribution networks and multiple integrated energy microgrids (IEMs) has become increasingly important for improving operational economy and maintaining system security. To address the insufficient integration of network constraints, P2P energy sharing, and contribution-based benefit allocation, this paper proposes a hybrid game-based optimal scheduling model for multi-IEM systems under distribution network constraints. In the upper level, a Stackelberg game is established between the distribution system operator (DSO) and the multi-IEM alliance to coordinate electricity trading and distribution network operation. In the lower level, an asymmetric Nash bargaining-based cooperative game is developed to enable peer-to-peer (P2P) energy sharing and allocate cooperative benefits according to the actual energy-sharing contributions of individual IEMs. Furthermore, a distributed solution framework combining the Success-History Adaptive Differential Evolution (SHADE) algorithm and an improved alternating direction method of multipliers (ADMM) is adopted to preserve data privacy and improve computational efficiency. Case studies based on the modified IEEE 33-bus distribution system demonstrate that the proposed method eliminates voltage violations and reduces network losses by 9.0%. Meanwhile, the proposed cooperative mechanism decreases the total operating cost of the IEM alliance by 7815.8 CNY and yields a more contribution-consistent profit allocation among participating microgrids. In addition, the improved ADMM reduces computation time by 42.1% compared with the conventional serial ADMM. The results demonstrate the effectiveness of the proposed method in enhancing distribution network security, promoting renewable energy sharing, and improving the economic performance of multi-IEM systems. Full article

Accurate and consistent self-localization is essential for multi-UAV aerial missions in complex dynamic environments. However, communication constraints and heterogeneous sensor reliability variations often lead to cumulative localization errors and degraded robustness in conventional fusion frameworks. To address these challenges, this paper proposes a distributed cooperative localization framework integrating deep temporal feature learning, heterogeneous multi-sensor fusion, and consistency-aware distributed state estimation. First, an LSTM-based staged fusion strategy is designed to integrate VIO, GPS, and UWB measurements for accurate single-UAV localization. Second, a Squeeze-and-Excitation LSTM Self-Attention (SE-LSTM-SA) network is developed to adaptively recalibrate heterogeneous sensor channels and enhance temporal feature extraction under dynamic sensing conditions. Finally, a consistency-aware distributed fusion mechanism based on the Labeled Multi-Bernoulli (LMB) framework is introduced to improve inter-UAV state consistency through iterative local-neighbor information exchange. Experiments conducted on the XTDrone platform demonstrate that the proposed framework achieves superior localization accuracy compared with traditional EKF and conventional LSTM-based methods. Specifically, the proposed method achieves lower RMSE, MAE, and Maximum Prediction Error (MaxPE), while significantly improving global consistency performance. Experimental results demonstrate that the proposed framework provides accurate and consistent localization performance for multi-UAV systems in complex dynamic environments. Full article

Under carbon peaking and neutrality goals, building integrated with photovoltaics and energy storage system clusters (BIPECs) enable efficient on-site renewable energy use and can act as dispatch units for the public grid. However, BIPECs face significant uncertainties and are still under development. This study proposes a decentralized cooperative power dispatch model coupling a multi-agent proximal policy optimization (MAPPO) algorithm and offline digital twin (ODT) technology to optimize the photovoltaic (PV) power consumption of clusters despite limited data availability. An integrated BIPEC energy system model is established, and by leveraging the multi-agent system model of the BIPEC, the decentralized dispatch problem is converted into a fully cooperative multi-agent reinforcement learning (MARL) problem. A simulation-assisted ODT framework constructs a digital environment for MAPPO to augment data, conduct MAPPO training, and optimize the reward function, thereby obtaining power dispatch strategies. The results show that the proposed optimization model can obtain dispatch strategies that reflect a high degree of collaboration, reducing the cumulative power supply from the public grid by 0.55–2.56% per month compared to the non-cooperative self-generating and self-using strategy. This study presents the application of MARL in BIPECs by introducing a decentralized collaborative power dispatch methodology for building clusters, enhancing building energy efficiency and facilitating flexible collaborative power dispatch. Full article

The Engineering-Procurement-Construction (EPC) general contracting model has emerged as the dominant delivery method for large-scale infrastructure and industrial projects in China. However, contemporary EPC project cost control remains plagued by critical industry challenges, including fragmented cross-stage coordination, pervasive data silos, and the shallow integration of digital technologies into core management processes. This study considers three key stakeholders—government regulators, project owners, and EPC general contractors—and develops a tripartite evolutionary game model to analyze the strategic interactions underlying intelligent cost control in EPC projects. We examine the evolutionary stability of each stakeholder’s strategy selection, explore how various factors influence tripartite strategic choices, and further investigate the stability of equilibrium points in the game system. The key findings are summarized as follows: (1) Strengthening government incentives and penalties simultaneously promotes owners’ investment in intelligent cost control systems and general contractors’ active collaborative cost management. However, excessive incentive intensity undermines the government’s regulatory effectiveness. (2) Establishing a revenue-sharing mechanism for excess cost savings fully stimulates the spontaneous cooperation willingness of owners and general contractors, serving as the cornerstone for market-oriented operation of intelligent cost control. (3) Reducing owners’ intelligent construction investment costs and general contractors’ collaborative control costs effectively addresses practical implementation barriers and accelerates the digital upgrading of engineering cost management. Finally, numerical simulations are performed using MATLAB R2020b to validate theoretical findings. Full article

Waveform agility improves anti-reconnaissance and anti-jamming capability in diverse inverse synthetic aperture radar (ISAR) scenarios, but it also breaks the phase variation assumptions used for conventional coherent processing. For cooperative bistatic ISAR radars, the problem is further complicated by the bistatic geometry and phase evolution induced by synchronization. This paper develops a joint coherent integration method for a cooperative bistatic radar with simultaneous pulse width (PW) and pulse repetition interval (PRI) agility. Firstly, we establish and analyze a bistatic geometric model to reveal key integration problems under agile waveforms, and then derive the coherent processing interval (CPI) local polynomial description for bistatic delay, Doppler and acceleration. On this basis, the matched filter response of each agile pulse is analyzed under the fixed-bandwidth assumption with linear frequency modulation (LFM), showing that PW agility produces a compressed peak displacement and an additional deterministic phase term, whereas PRI agility converts slow-time coherent integration into a nonuniformly sampled spectral estimation problem. To solve this problem, a joint fast and slow-time compensation route is derived, together with a bistatic-specific parameter design method that connects coherent integration tolerances with the bistatic angle and the observable projection vector. Finally, we test the performance of the proposed joint integration method in multiple scenarios and verify its effectiveness and robustness, which enhances detection performance and resolution for target localization. Full article

Pediatric phlebotomy is a common invasive procedure frequently associated with pain, anxiety, and fear, which may negatively affect children’s cooperation and overall healthcare experiences. Virtual reality (VR) has emerged as a promising non-pharmacological intervention capable of providing immersive distraction and emotional engagement during painful medical procedures. The aim of this systematic review was to evaluate the effectiveness of immersive VR in reducing pain perception and anxiety-related outcomes among pediatric patients undergoing phlebotomy procedures. This review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The research question was developed using the PICO framework. Randomized controlled trials and comparative controlled studies published between January 2020 and September 2025 were identified through systematic searches of PubMed and the Cochrane Central Register of Controlled Trials (CENTRAL). Studies involving children and adolescents aged 4–17 years undergoing phlebotomy or venipuncture procedures were eligible for inclusion. A total of six studies comprising 557 pediatric participants were included in the review. The VR interventions involved immersive and interactive environments, including educational simulations, animated scenarios, and game-based experiences delivered through head-mounted displays. Four studies reported statistically significant reductions in pain and/or anxiety among participants exposed to VR compared with control groups, whereas two studies found no significant differences. Across the included studies, VR interventions were generally well accepted by children, parents, and healthcare professionals, with only mild and transient adverse effects reported. However, substantial heterogeneity was observed regarding clinical settings, VR technologies, intervention protocols, and outcome assessment methods. The current evidence suggests that immersive VR is a promising adjunctive strategy for reducing pain and anxiety during pediatric phlebotomy procedures. Nevertheless, the available evidence remains limited by methodological heterogeneity and relatively small sample sizes. Future research should focus on larger, well-designed randomized controlled trials using standardized intervention protocols and outcome measures to support evidence-based implementation of VR in pediatric clinical practice. Full article

Background: Foot degloving injuries are associated with extensive soft-tissue disruption, compromised perfusion, and a high risk of flap necrosis. Hyperbaric oxygen therapy (HBOT) is known to enhance tissue oxygenation and support flap survival; however, its application in pediatric patients may be limited due to poor cooperation, intolerance to chamber-based treatment, and limited accessibility. Case Presentation: A 7-year-old girl presented with a crush injury to the left foot after being run over by a vehicle, resulting in severe soft-tissue damage. Evaluation revealed a dorsal foot degloving injury, a proximal phalanx fracture of the great toe, and dislocations of the fourth proximal interphalangeal and fifth distal interphalangeal joints. Emergency surgery included open reduction, K-wire fixation, debridement, and artificial dermal grafting using Pelnac. On postoperative day 1, the flap showed signs of compromised perfusion. As HBOT was not feasible, topical oxygen therapy using Natrox was applied continuously for 17 days. Serial wound assessments demonstrated gradual improvement in flap viability. Although ischemic changes developed in the toes, necrosis remained superficial and was successfully managed with local debridement and dressings. Residual skin defects with partial necrosis were treated with split-thickness skin grafting, which healed without major complications. The patient resumed ambulation after splint removal. Conclusions: In pediatric patients with compromised flaps in whom HBOT is not feasible, topical oxygen therapy may serve as a practical adjunctive treatment option. Although its independent effect cannot be established in a single case, this report suggests its potential role in flap salvage and in limiting tissue necrosis. Full article

Small and medium-sized enterprises (SMEs) are particularly vulnerable when crisis support systems are delayed, unreliable, or difficult to access. This study examines how South African SMEs maintained strategic continuity during COVID-19 by developing the concept of relational substitution, defined as a process in which owner-managers compensate for weak formal support by internalizing continuity work within the employment relationship. The study is based on a secondary qualitative analysis of 16 semi-structured interviews with SME owners in the Western Cape, South Africa, complemented by a targeted evidence review to inform boundary-condition assessment. The findings show that owner-managers assembled relational continuity bundles that combined labor flexibility, retention intent, transparent communication, and visible well-being support. Owners presented these bundles as efforts to sustain cooperation, trust, and operational functioning when enacted through fairness logics such as voice, transparency, equal sacrifice, and relational care. The study contributes to SME resilience and management and organization studies by distinguishing relational substitution from sustainable human resource management, organizational justice, relational leadership, and institutional fragility, and by specifying the firm-level and institutional conditions under which this mechanism is more likely to support strategic continuity. Full article

The study examines the evolution, knowledge structure, and trends in snowmelt runoff prediction models. It identifies research hotspots, future directions, and offers a theoretical basis for accurate simulation and prediction. Utilizing CiteSpace software, 556 core Chinese and English publications from 2010 to 2025 were visually analyzed. Research on snowmelt runoff simulation shows: (1) Chinese publications are prominent in core journals like “Journal of Glaciology and Geocryology,” while English publications appear in high-impact journals like “Water Resources Research.” (2) Institutions like the University of Chinese Academy of Sciences, the Northwest Institute of Eco-Environment and Resources, and the University of California have formed a cross-regional research network. (3) International collaboration involves 42 countries, with a focus on China, the United States, and India. However, domestic institutional cooperation needs improvement. (4) Research trends in snowmelt runoff simulation have progressed from empirical statistics to remote sensing and model-driven physical mechanisms, and now to the integration of artificial intelligence with physical models. (5) The Chinese literature focuses on cold regions, while the English literature emphasizes intelligent modeling. This shift indicates a move towards “physical–intelligent” hybrid modeling. Future research should address challenges like model applicability in data-scarce areas, improving interpretability of complex models, quantifying uncertainties, and developing physically constrained deep learning models. Collaboration among institutions is crucial for enhancing water resource management and disaster warning systems in cold regions. Full article

Antibiotic-resistant bacteria are widely distributed and threaten public health. Photocatalytic antimicrobial technology can effectively inactivate multidrug-resistant bacteria without readily inducing resistance. We previously showed that oxygen-rich vacancy Bi₂MoO₆ (OBM) exhibits excellent activity against methicillin-resistant Staphylococcus aureus (MRSA), but the underlying molecular mechanisms remain poorly understood. Here, we employed integrated transcriptomics and metabolomics, with qRT-PCR validation, to systematically elucidate the antibacterial mechanism of OBM against MRSA. OBM treatment induced profound transcriptional and metabolic alterations: 231 differentially expressed genes and 206 differentially abundant metabolites were identified. Functional enrichment analysis revealed cooperative involvement in multiple critical pathways, including inhibition of amino acid biosynthesis and protein translation, disruption of cell wall and membrane integrity, induction of oxidative stress, collapse of energy metabolism (suppression of oxidative phosphorylation and impaired ATP synthesis), and imbalance in nucleotide metabolism (down-regulation of DNA helicase and mismatch repair genes, dysregulation of purine/pyrimidine metabolism). These findings demonstrate that OBM photocatalytically inactivates MRSA through a multi-target systemic attack at both the transcriptional and metabolic levels, providing a novel theoretical foundation for the development of photocatalytic materials aimed at controlling MRSA and other drug-resistant bacteria. Full article

The Graduate Student Evolutionary Algorithm (GSEA) has demonstrated promising optimization capability in several engineering tasks; however, its performance may deteriorate when dealing with high-dimensional and complex multimodal problems due to insufficient adaptive search behavior, weak diversity preservation, and stagnation during later optimization stages. To alleviate these limitations, this paper proposes a Multi-Strategy Improved Graduate Student Evolutionary Algorithm (MIGSEA) for numerical optimization and artistic image multi-threshold segmentation. First, an adaptive mentor-guided learning mechanism is introduced to dynamically regulate the influence of mentors and peers throughout the optimization process, enabling a more effective transition from global exploration to local exploitation. Second, an elite–random cooperative learning strategy is designed to combine high-quality solution guidance with stochastic perturbation, thereby improving population diversity and enhancing the ability to escape local optima. Third, a stagnation-aware local refinement mechanism is developed to activate adaptive neighborhood search when the optimization process becomes trapped, which further accelerates convergence and improves solution precision. To verify the effectiveness of the proposed algorithm, MIGSEA is evaluated on the IEEE CEC2017 and CEC2020 benchmark suites and compared with 11 advanced metaheuristic algorithms under identical experimental conditions. Experimental results demonstrate that MIGSEA achieves competitive optimization accuracy, convergence speed, robustness, and statistical superiority in most benchmark functions. Furthermore, MIGSEA is applied to Otsu-based artistic image multi-threshold segmentation using multiple benchmark images with different threshold levels. Quantitative evaluation based on PSNR, FSIM, and SSIM, together with visual analysis, confirms that the proposed method can generate more accurate and visually consistent segmentation results than existing competitors. Overall, the proposed MIGSEA provides an effective and robust optimization framework for both benchmark optimization and practical image segmentation applications. Full article

As part of the development of sustainable forest management, it is important to identify the risk of reduced availability of commercial forests, assess the adaptation of companies to new conditions, and analyze measures that allow them to adapt to the changing market situation. The aim of this research was to confirm or refute the hypothesis that forest service plants in Poland are at an increased risk of operating under the planned exclusion of 20% of State Forests’ area from commercial use. A direct survey method was used for the study. The results of the study indicated that most companies (65%) plan to reduce employment due to restrictions on forest area, which is a result of difficulties in the labor market in the forestry sector. A significant proportion of respondents (82%) perceive the exclusion of part of the forests from commercial use as a threat to their business, with as many as 41% assessing this threat as very high. A total of 31% of companies assess their ability to adapt to change as poor or very poor, which raises concerns about the future of their business. A significant proportion of respondents (77%) indicated that the uncertainty surrounding the rules for excluding forest land could negatively affect their investment decisions. The study results showed that changes in business risk, responsiveness to change, and adaptability associated with the planned forest exclusion policy were independent of company size, the form of inter-company cooperation, or employment levels. A wide range of issues that must be addressed to maintain sustainable forest management were identified, including concerns related to the perceived or anticipated reduction in employment under a planned exclusion scenario. Full article