Hunan University of Humanities, Science and Technology

The yellow-spined bamboo locust ( Ceracris kiangsu ) is one of the most destructive forest pests in China, causing severe damage to bamboo forests across multiple provinces. Understanding the relationship between its gut microbiota and environmental factors is crucial for revealing its ecological adaptability and migration potential. This study used 16S rRNA high-throughput sequencing to analyze gut bacterial communities of C. kiangsu from six geographically distinct populations in China. The results showed that Firmicutes and Proteobacteria were the dominant phyla, while bacterial diversity and composition varied significantly among populations. Precipitation and sunshine duration were identified as the main environmental factors most strongly associated with microbial community structure. These findings suggest that environmental conditions are strongly associated with variation in the gut microbiota of C. kiangsu , potentially affecting its adaptability and outbreak dynamics. This research provides new insights into the ecological mechanisms underlying pest distribution and offers a microbiome-based foundation for developing sustainable control strategies to reduce the agricultural and forestry losses caused by this species.

Under the background of deepening media integration and diversification of audience demand, large-scale events and art festivals are facing challenges such as the weakening effect of single-channel marketing, the fragmentation of audience reach, and the insufficient efficiency of value transformation. Based on the theories of integrated marketing communication (IMC), multi-channel marketing and word-of-mouth communication, from the perspective of online and offline omni-channel synergy, this paper analyzes the impact of online and offline omni-channel Synergy on marketing performance, analysis of advertising, public relations, social media, offline activities, word-of-mouth communication five channels of function and synergy pain points, to construct an integrated communication system with "The same goal, the same source of content, data exchange, and mutual feeding of effect". Combined with the typical cases of the Olympic Games, Wuzhen Drama Festival and Beijing Marathon, this paper reveals the differences in channel coordination of different types and scales of activities, and puts forward landing suggestions from the dimensions of organization, content, data and risk. The study fills the gap of existing "Channel isolation analysis", and provides theoretical and practical reference for event organizers to optimize resource allocation and improve marketing efficiency.

ABSTRACT As the world transitions toward a digital economy, innovative mechanisms supported by digital transformation drastically reduce greenhouse gas emissions and improve environmental quality. This study investigates the co‐evolution of industrial enterprises and governments' behavior toward a low‐carbon transition by leveraging digital economy initiatives and green technological innovation. Anchored in government low‐carbon policies, we develop a strategic evolutionary game model that captures the dynamic interactions between industrial enterprises that choose technological innovation and the government's promotion of digital economy strategies. Numerical simulations conducted in MATLAB reveal how enterprises' emission‐reduction behavior responds to varying incentives, costs, and policy interventions. The results highlight three key insights. Firstly, the interaction between governments and enterprises forms an adaptive equilibrium, in which mutually reinforcing strategies accelerate the development of the digital economy and green innovation. Secondly, the willingness of industrial enterprises to reduce CO 2 emissions is highly sensitive to the clarity of subsidies, cost constraints, and social benefits; weak incentives or ambiguous policies lead to insufficient reductions. Thirdly, multiple drivers—including emission‐reduction costs, government subsidies, additional innovation expenses, social benefits, and potential economic gains—jointly shape strategic choices. By integrating game‐theoretic modeling with simulation analysis, this study offers both strategic and policy‐oriented pathways for promoting sustainable industrial transformation. Conclusively, it contributes to advancing low‐carbon governance by providing actionable insights toward the development of the digital economy and green innovation, which will ensure sustainable policy futures.

As edge devices grow smarter and application scenarios become more diverse, users' demands for lower latency and higher efficiency in data storage and processing have risen sharply. Individual edge devices and nodes are no longer sufficient to meet these expanding storage requirements. Consequently, developing efficient, low-latency, and cost-effective solutions for collaborative storage across edge devices and nodes has become a critical challenge. In this paper, we present a framework for the transaction and pricing of storage resources in an edge computing environment involving multiple edge service providers, to address trust and incentive issues in storage resource collaboration. Firstly, we propose a secure and decentralized storage resource trading mechanism by leveraging blockchain technology and smart contracts. We introduce Proof of Transaction Expectation (PoTE), an efficient, reliable, and lightweight consensus mechanism, to ensure transaction transparency, openness, and non-repudiation. Secondly, we introduce a game theory-based storage resource pricing model, where a leader interacts with multiple followers to optimize profits while maintaining service quality. To address dynamic pricing and storage resource allocation problems under incomplete information, we propose the Stackelberg Game Approach based on Multi-Agent Reinforcement Learning (SGA-MARL), which formulates the optimal pricing and trading share decisions in the two-stage Stackelberg game as a stochastic Markov Decision Process (MDP). Simulations and prototype testing validate the effectiveness of the proposed system, with results showing that the PoTE consensus achieves up to 40% higher throughput than Proof-of-Work while reducing latency by over 50% compared to PBFT, and the SGA-MARL algorithm improves leader profit by approximately 30% and resource satisfaction rates by over 80% compared to baseline methods like MA-PPO and DQN.

Polygonatum cyrtonema Hua, commonly known as Huangjing, is a traditional Chinese medicinal and edible plant prized for its roots. In recent years, P. cyrtonema Hua root rot disease has frequently occurred in China, significantly affecting both yield and medicinal quality. In October 2024, a severe outbreak of root rot was observed in P. cyrtonema Hua cultivation fields located in Hecheng District, Huaihua City, China (N27°40’22”, E109°55’9”), where the cultivation area over 200 hectares. The disease incidence reached approximately 42.5%, posing a significant threat to local production. Symptoms on the infected roots appeared brown, water-soaked lesions, causing soft rot and eventually leaf yellowing and wilting to death. (Fig.1-B, C). To isolate the causal organism, rotted root tissues were surface-sterilized with 75% ethanol (1 min), 2% NaClO (3 min), rinsed four times with sterile distilled water, blotted dry on sterile filter paper. Tissue fragments (1×1 cm) from lesion margins were plated on potato dextrose agar (PDA), then incubated at 28°C in darkness for 3 days. Hyphal sections from colony edges were transferred to new PDA plates. From a total of 25 diseased root samples, 80 tissue segments were plated. This process resulted in the isolation and purification of 42 fungal isolates.The isolate, HJBK 4-9 was selected for further characterization. The colonies exhibited concentric rings, white mycelium with a slight yellow pigment on the reverse side. Sporulation was induced by culturing on carnation leaf agar (CLA) at 25°C in darkness (Yang et al. 2024). These microspores were oval, colorless, aseptate and slightly curved, with (5.8−12.5) μm× (2.2−3.8) μm in size. Fungal mycelia were used for PCR, using the following primer sets: ITS1/ITS4 (Hao et al. 2023), EF1/EF2 (O'Donnell et al. 1998), and β 2a/2b (Glass and Donaldson.1995) respectively. PCR products of the isolate were sequenced. Sequences were deposited in GenBank (ITS, PV249395; TUB2, PX130413; EF-1α, PX130414). BLASTn searches revealed that the strain was 99.81% (KP689232.1) for ITS, 99.36% (ON209102.1) for TUB2 and 99.28% (PP394350.1) for EF-1α. The isolate was identified as C. rosea based on the morphological characteristics and molecular phylogeny. To test pathogenicity, 6 pieces of healthy roots of P. cyrtonema Hua were pin-pricked with a sterile needle and spray-inoculated with 50μL of spore suspension per root (2×107conidia/mL). Another 6 pieces of healthy roots were pin-pricked with a sterile needle and inoculated with sterile water, and served as controls. All roots were kept in an artificial climate chamber controlled conditions (26°C and 60% relative humidity). After 15 days, most inoculated roots turned brown and partially rotten (Fig.1-D), similar to the field symptoms, whereas the control remained symptomless. The pathogen was reisolated from all inoculated roots only and confirmed as C. rosea based on morphology and sequence analysis. To our knowledge, this is the first report of C. rosea causing root rot of P. cyrtonema Hua in China. The finding may be helpful to the control and prevention of root rot disease of P. cyrtonema Hua.