Competitive Relationship Research Articles

Dynamic Double Event-Triggered Anti-Disturbance Tracking Control for a 2-DOF Small Unmanned Helicopter.

This article devises a new dynamic double event-triggered anti-disturbance tracking control scheme for a 2-degree of freedom (DOF) laboratory helicopter subject to external time-varying disturbances and load fluctuation by using the generalized proportional-integral observer technique. The helicopter system is separated into two subsystems in the proposed control method, i.e., the pitch subsystem and the yaw subsystem. Each subsystem includes a discrete-time dynamic double event-triggering mechanism (DDETM), and the control laws of the two subsystems are independent of each other. There are two triggering conditions in the designed double triggering mechanism: one is designed based on the system states and the other is based on the lumped disturbance estimation. These two triggering conditions form a competitive relationship such that the controller updates the control signal as long as one of the triggering conditions is satisfied. Theoretical analysis is provided for achieving the better communication and control performance of the proposed DDETM-based robust control method. Through rigorous stability analysis, it is proved that the closed-loop hybrid system is globally ultimately bounded. At last, numerical simulations show that the suggested control strategy not only reduces the event-triggering number, but also improves the initial dynamic performance of the system.

Targeting DNM1L/DRP1-FIS1 axis inhibits high-grade glioma progression by impeding mitochondrial respiratory cristae remodeling

BackgroundThe dynamics of mitochondrial respiratory cristae (MRC) and its impact on oxidative phosphorylation (OXPHOS) play a crucial role in driving the progression of high-grade glioma (HGG). However, the underlying mechanism remains unclear.MethodsIn the present study, we employed machine learning-based transmission electron microscopy analysis of 7141 mitochondria from 54 resected glioma patients. Additionally, we conducted bioinformatics analysis and multiplex immunohistochemical (mIHC) staining of clinical glioma microarrays to identify key molecules involved in glioma. Subsequently, we modulated the expression levels of mitochondrial dynamic-1-like protein (DNM1L/DRP1), and its two receptors, mitochondrial fission protein 1 (FIS1) and mitochondrial fission factor (MFF), via lentiviral transfection to further investigate the central role of these molecules in the dynamics of glioblastoma (GBM) cells and glioma stem cells (GSCs). We then evaluated the potential impact of DNM1L/DRP1, FIS1, and MFF on the proliferation and progression of GBM cells and GSCs using a combination of CCK-8 assay, Transwell assay, Wound Healing assay, tumor spheroid formation assay and cell derived xenograft assay employing NOD/ShiLtJGpt-Prkdcem26Cd52Il2rgem26Cd22/Gpt (NCG) mouse model. Subsequently, we validated the ability of the DNM1L/DRP1-FIS1 axis to remodel MRC structure through mitophagy by utilizing Seahorse XF analysis technology, mitochondrial function detection, MRC abundance detection and monitoring dynamic changes in mitophagy.ResultsOur findings revealed that compared to low-grade glioma (LGG), HGG exhibited more integrated MRC structures. Further research revealed that DNM1L/DRP1, FIS1, and MFF played pivotal roles in governing mitochondrial fission and remodeling MRC in HGG. The subsequent validation demonstrated that DNM1L/DRP1 exerts a positive regulatory effect on FIS1, whereas the interaction between MFF and FIS1 demonstrates a competitive inhibition relationship. The down-regulation of the DNM1L/DRP1-FIS1 axis significantly impaired mitophagy, thereby hindering the remodeling of MRC and inhibiting OXPHOS function in glioma, ultimately leading to the inhibition of its aggressive progression. In contrast, MFF exerts a contrasting effect on MRC integrity, OXPHOS activity, and glioma progression.ConclusionsThis study highlights that the DNM1L/DRP1-FIS1 axis stabilizes MRC structures through mitophagy in HGG cells while driving their OXPHOS activity ultimately leading to robust disease progression. The inhibition of the DNM1L/DRP1-FIS1 axis hinders MRC remodeling and suppresses GBM progression. We propose that down-regulation of the DNM1L/DRP1-FIS1 axis could be a potential therapeutic strategy for treating HGG.

Integrative approaches to improve litchi (Litchi chinensis Sonn.) plant health using bio-transformations and entomopathogenic fungi

Bio-transformations refer to the chemical modifications made by an organism on a chemical compound that often involves the interaction of plants with microbes to alter the chemical composition of soil or plant. Integrating bio-transformations and entomopathogenic fungi into litchi cultivation can enhance symbiotic relationships, microbial enzymatic activity in rhizosphere, disease suppression and promote overall plant health. The integration of biological formulations and entomopathogenic fungi can significantly influence growth, nutrient dynamics, physiology, and rhizosphere microbiome of air-layered litchi (Litchi chinensis Sonn.) saplings. Biological modifications included, K-mobilizers, AM fungi, Pseudomonas florescence and Azotobacter chroococcum along with Metarhizium, entomopathogenic fungi have been used. The treatments included, T1-Litchi orchard soil + sand (1:1); T2-Sand + AM fungi + Azotobacter chroococcum (1:2:1); T3-Sand + Pseudomonas florecence + K-mobilizer (1:1:1); T4- AM fungi + K-mobilizers (1:1); T5, P. Florecence + A. chroococcum + K-mobilizer (1:1:1); T6-Sand + P. florecence (1:2) and T7-Uninoculated control for field performance. Treatments T4-T6 were further uniformly amended with drenching of Metarrhizium in rhizosphere. T2 application significantly increased resident microbe survival, total chlorophyll content and root soil ratio in seedlings. A. chroococcum, Pseudomonas, K-mobilizers and AM fungi increased in microbial biomass of 2.59, 3.39, 2.42 and 2.77 times, respectively. Acidic phosphatases, dehydrogenases and alkaline phosphatases were increased in rhizosphere. Leaf nutrients reflected through DOP were considerably altered by T2 treatment. Based on Eigen value, PCA-induced changes at biological modifications showed maximum total variance. The study inferred that the bio-transformations through microbial inoculants and entomopathogenic fungi could be an encouraging strategy to enhance the growth of plants, health and productivity. Such practices align well with the goals of sustainable agriculture through biological means by reducing dependency on chemical inputs. By delving into these aspects, the research gaps including microbial processes, competitive and symbiotic relationships, resistance in microbes and how complex interactions among bio-transformations, entomopathogenic fungi and microbes can significantly impact the health and productivity of litchi. Understanding and harnessing these interactions can lead to more effective and sustainable farming practices.

A Secure and Fair Federated Learning Framework Based on Consensus Incentive Mechanism

Federated learning facilitates collaborative computation among multiple participants while safeguarding user privacy. However, current federated learning algorithms operate under the assumption that all participants are trustworthy and their systems are secure. Nonetheless, real-world scenarios present several challenges: (1) Malicious clients disrupt federated learning through model poisoning and data poisoning attacks. Although some research has proposed secure aggregation methods to address this issue, many methods have inherent limitations. (2) Clients may refuse or passively participate in the training process due to considerations of self-interest, and may even interfere with the training process due to competitive relationships. To overcome these obstacles, we have devised a reliable federated framework aimed at ensuring secure computing throughout the entirety of federated task processes. Initially, we propose a method for detecting malicious models to safeguard the integrity of model aggregation. Furthermore, we have proposed a fair contribution assessment method and awarded the right to write blocks to the creator of the optimal model, ensuring the active participation of participants in both local training and model aggregation. Finally, we establish a computational framework grounded in blockchain and smart contracts to uphold the integrity and fairness of federated tasks. To assess the efficacy of our framework, we conduct simulations involving various types of client attacks and contribution assessment scenarios using multiple open-source datasets. Results from these experiments demonstrate that our framework effectively ensures the credibility of federated tasks while achieving impartial evaluation of client contributions.

Tourists’ Perceptual Positioning of Brand Equity and Competitive Relationships in Organic Agricultural Tourism

In the face of a highly competitive tourism market, when tourists hold positive brand equity towards a destination, it enhances the destination’s ability to differentiate itself from competitors. This study focuses on the brand equity of organic agricultural tourism, using multidimensional scaling (MDS) to explore the factor structure of brand equity and the perceptual positioning of various tourism destination brands. The research targets tourists engaging in organic agricultural tourism in the Hualien and Taitung regions, with 220 valid questionnaires collected. The research findings indicate the following: 1. Among the 22 brand equity items, “loyalty to organic agricultural tourism”, “awareness of organic agricultural products”, “quality of organic agricultural products”, “environmental sustainability”, “image of healthy tourism”, and “recognition of organic agricultural development” scored the highest. 2. The analysis revealed that the brand equity factors are ranked in the following order: BIHS, BACI, BPQ, BLO, and BAW. 3. Through MDS analysis, the five organic agricultural tourism destinations were categorized into high, medium, and low brand equity groups, illustrating the differentiated competitive relationships among these destinations. The top three factors influencing the brand perceptual maps were BAW, BIHS, and BPQ. The results of this study can serve as a reference for future research on brand equity in organic agricultural tourism and provide a scientific basis for the practical application of shaping brand equity and formulating competitive strategies.

Solvent Effects on Spin-Orbit Charge-Transfer Intersystem Crossing in Aryl-Substituted Boron-dipyrromethene Donor-Acceptor Dyads.

In heavy-atom-free organic molecules, the rate of triplet generation through charge recombination, as dictated by the El-Sayed rule, can be enhanced by 101-102 times compared with the rate of spontaneous spin flipping between π-π* orbitals. This mechanism is known as the spin-orbit charge-transfer intersystem crossing (SOCT-ISC). Within the framework of the SOCT-ISC mechanism, facilitating the generation of charge-separated (CS) states and suppressing the spin-allowed direct charge recombination to the ground state are pivotal for maximizing the efficiency of generating localized triplet states. Herein, a series of orthogonal aryl-substituted boron-dipyrromethene dyads were studied by time-resolved spectroscopy to unravel the multichannel competitive relationships in the SOCT-ISC mechanism. The energy level of the electron donor and the stabilization of the solvent effect to the charge-transfer state are reflected in the Gibbs free energy changes of the electron transfer and recombination reactions, leading to significantly different triplet quantum yields. Additionally, solvation-induced electronic coupling changes in excited states lead to the fact that the spin-allowed charge recombination rate cannot be well simply predicted by the Marcus inverted region but has to consider the specific excited-state dynamics in optimizing the proportion of triplet generation channels based on charge recombination.

Rare earth recycling and remanufacturing: Impacts on oligopoly markets and industry development from a closed-loop supply chain perspective

The recycling of rare earth elements (REEs) yielded a dual benefit by alleviating supply constraints and contributing to environmental preservation. Independent recyclers (IRs), upon extracting REEs from waste materials, not only supplied the recovered REEs to the REE conglomerates but also engaged in competitive relationships by remanufacturing REE products. This study established a closed-loop supply framework, allowing the IR flexibly to choose between remanufacturing or direct sales strategies. Using the Cournot model under inequation constraints and real market data, to explores the impact of REE acquisition prices and recycling technologies on the closed-loop supply chain (CLSC) and society. The results indicated that: (1) The recycling mode and technology do not affect market share. Compared to the IR, REE conglomerate exhibit significant monopolistic advantages, occupying at least 85.1% of the market share, which can increase to a maximum of 98% as acquisition prices rise. (2) The acquisition price of recycled REE has an “inverse U-shaped” relationship with the profits of REE conglomerate and a positive relationship with the profits of IR. (3) The recovery rate is negatively related to the profits of REE conglomerate and positively related to the profits of IR. Increasing the REE recovery rate will enhance the profitability of the IR. (4) In terms of social effects, higher acquisition price of recycled REE continuously reduce consumer surplus and social welfare. Although the REE recovery rate does not affect consumer surplus, it has a significant positive impact on social welfare.

Pressure-induced extreme anisotropic behavior of thermoelectric properties in crystalline β-CuSCN

Applying hydrostatic pressure has emerged as a promising strategy for regulating the properties of thermoelectric materials, particularly in the case of β-CuSCN, which has garnered attention due to its ultra-low thermal conductivity and potential applications in thermoelectric devices. Herein, we investigate the intrinsic mechanism governing the electron-thermal transport properties of β-CuSCN under hydrostatic pressure. It was found that ZT decreased by 30 % along the in-plane direction while increasing by 24 % along the out-of-plane direction following the application of hydrostatic pressure, respectively. Our results reveal that the competitive relationship between pressure-driven effects on phonon dynamics and electronic structure influences the thermoelectric properties of β-CuSCN. For the transport mechanism, the compression alters phonon dispersion by enhancing atomic interactions, which leads to an increase in lattice thermal conductivity. On the other hand, despite strong coupling between electrical transport parameters, a net increase in power factor is achieved through pressure-induced bandgap narrowing. As a result, the thermoelectric properties demonstrate contrary variation tendency along the in-plane and out-of-plane directions. Our research deepens our understanding of transport behavior under extreme pressure conditions and provides valuable insights into the fundamental relationship between structural deformation and thermoelectric performance.

Theoretical reaction kinetics predictions for acetone and ketene with NH2 radicals: Implications on acetone/ammonia kinetic modeling

The cross-reaction kinetics of acetone/ketene (CH3COCH3/CH2CO) + amino (NH2) radicals are first theoretically reported for a wide range of conditions (T = 300–2500 K and P = 0.1–100 atm) in this work. The high-level electronic structure method CCSD(T)/cc-pVnZ(n = T, Q)//B3LYP-D3BJ/6–311++G(d,p) is used to explore the potential energy profiles on which the temperature- and pressure-dependence kinetic behaviors of the title reactions are characterized using the Rice-Ramsperger-Kassel-Marcus/Master Equation (RRKM/ME) theory. Corrections of the one-dimensional hindered rotor approximation and asymmetric Eckart tunneling effect are also included in the rate constant calculations. Furthermore, this work delves into the competitive relationships among the H-abstraction, NH2 addition and addition-dissociation reaction pathways. For CH3COCH3 + NH2, the H-abstraction reaction of CH3COCH3 is highly favored over the addition-dissociation reaction and other isomerization channels. For CH2CO + NH2, the reaction channel of addition-dissociation to form CH2NH2 + CO under low temperature conditions is more advantageous, while the H-abstraction reaction plays a dominant role under combustion conditions (T ≥ 1000 K). To reveal the impact of the studied reaction kinetics on model predictions, the rate constants of dominant reaction channels calculated in this work are incorporated into a kinetic model for the auto-ignition, oxidation and pyrolysis of CH3COCH3/NH3 mixtures. The simulated results show that the effect of the updated rate constants on ignition delay time is mainly at low temperatures and the promotion effect of CH3COCH3 addition on the ignition of NH3 presents a nonlinear enhancement. The updated rate constants can also accelerate the consumption of CH3COCH3 and CH2CO formation, while also influence the concentration distributions of other significant species (e.g., NH3, CO). Therefore, the cross-reaction kinetics of CH3COCH3/CH2CO + NH2 are critical in controlling the fuel consumption, important intermediate formation and ignition delay time of CH3COCH3/NH3 mixtures.

Oxygen precipitation behavior and its influence on phosphorus gettering in Czochralski silicon

This study investigates the effects of single-step and two-step annealing processes on the formation of oxygen precipitates and their impact on metal impurity gettering in gallium-doped monocrystalline silicon. The research focuses on the competitive relationship between internal gettering by oxygen precipitates and external gettering through phosphorus diffusion. Experimental results show that two-step annealing generates larger and more abundant oxygen precipitates, enhancing the internal gettering effect and reducing the recovery of minority carrier lifetime after phosphorus gettering. Despite this, phosphorus diffusion gettering remains effective in improving minority carrier lifetime, although the degree of improvement depends on the size and quantity of oxygen precipitates. These findings offer valuable insights for optimizing the fabrication process of silicon-based solar cells.

Останется ли цена ключевым фактором формирования конкурентных стратегий в период цифровизации?

Having a significant impact on separate commodity markets, digitalization affects competitive relationship within these markets. The competitive strategies’ formation in the digital economy has a very specific nature. This concerns primarily the prices’ formation and the occurrence of pricing violations of competition rules. In this article different aspects of digitalization’s impact on pricing condition are examined; the author of the article proves that despite the specifics of price formation in separate commodity markets, primarily price in the digital markets is still the main mechanism of competitive struggle and pricing violation of competition rules can still have an extremely negative impact on these markets.

Is Shanghai a rival to Seoul? Analysis on complementary and competitive relationships in trade

Despite the continuous expansion of trade and investment agreements between China and South Korea, little is known about the distribution of benefits and losses stemming from synergy and competition at the regional level. This paper aims to investigate the complementary and competitive interactions among 14 economic regions of the two countries concerning bilateral export scale. Using a Dendrinos-Sonis model based on a zero-sum structure, we analyzed the interregional trade patterns between the two countries from 2002 to 2022. The evidence shows that the growth of Seoul metropolitan area is complementary to the growth of Shanghai metropolitan area in terms of regioinal export share, but not vice versa. Central Area in South Korea exhibits widespread complementarity, while Beijing metropolitan leans towards competition.

Prediction of outflow temperature of reservoir based on theory-guided machine learning models and optimization of operation for improving outflow temperature

The proportion of hydropower within the energy-resource structure is gradually increasing. However, the construction of reservoirs inevitably leads to ecological and environmental issues, especially the release of low-temperature water in summer and its detrimental effects on fish spawning and reproduction. These issues can be alleviated by optimizing the reservoir operation scheme, but the large amount of time required for predicting the reservoir outflow temperature emerges as the primary constraint. In this study, we considered Pubugou (PBG) Reservoir and proposed an efficient and high-precision prediction method for reservoir outflow temperature based on theory-guided machine learning (TGML) algorithms. This method was applied to the multi-objective optimization of the reservoir operations, and an optimization operation plan was proposed to improve the outflow temperature. The research results indicate that the LightGBM machine learning model shows good predictive performance, with a maximum deviation of no more than 1 °C in predicting the outflow temperature. There is a significant competitive relationship between reservoir power generation and the outflow temperature. Compared with the current operational scheme, the maximum power operation plan results in a 4.4% increase in total power generation but causes the average outflow temperature during the fish spawning period to decrease by 0.1 °C. The total power generation of the improved outflow temperature operation scheme was 0.8% lower than that of the actual scheme, but the average outflow temperature during fish spawning increased by 0.2 °C. Properly increasing the discharge flow from the reservoir and lowering the water level can thus help alleviate the issue of outflow temperature.

Performance Analysis and Rapid Optimization of Vehicle ORC Systems Based on Numerical Simulation and Machine Learning

The organic Rankine cycle (ORC) system is an important technology for recovering energy from the waste heat of internal combustion engines, which is of significant importance for the improvement of fuel utilization. This study analyses the performance of vehicle ORC systems and proposes a rapid optimization method for enhancing vehicle ORC performance. This study constructed a numerical simulation model of an internal combustion engine-ORC waste heat recovery system based on GT-Suite software v2016. The impact of key operating parameters on the performance of two organic Rankine cycles: the simple organic Rankine cycle (SORC) and the recuperative organic Rankine cycle (RORC) was investigated. In order to facilitate real-time prediction and optimization of system performance, a data-driven rapid prediction model of the performance of the waste heat recovery system was constructed based on an artificial neural network. Meanwhile, the NSGA-II multi-objective algorithm was used to investigate the competitive relationship between different performance objective functions. Furthermore, the optimal operating parameters of the system were determined by utilizing the TOPSIS method. The results demonstrate that the highest thermal efficiencies of the SORC and RORC are 6.21% and 8.61%, respectively, the highest power outputs per unit heat transfer area (POPAs) are 6.98 kW/m2 and 8.99 kW/m2, respectively, the lowest unit electricity production costs (EPC) are 7.22 × 10−2 USD/kWh and 3.15 × 10−2 USD/kWh, respectively, and the lowest CO2 emissions are 2.85 ton CO2,eq and 3.11 ton CO2,eq, respectively. The optimization results show that the RORC exhibits superior thermodynamic and economic performance in comparison to the SORC, yet inferior environmental performance.

Regulation of drought stress on nutrient cycle and metabolism of rhizosphere microorganisms in desert riparian forest

Microbial communities in desert riparian forest ecosystems have developed unique adaptive strategies to thrive in harsh habitats shaped by prolonged exposure to abiotic stressors. However, the influence of drought stress on the functional and metabolic characteristics of soil rhizosphere microorganisms remains unknown. Therefore, this study aimed to investigate the effects of drought stress on soil biogeochemistry and metabolism and analyze the relationship between the biogeochemical cycle processes and network of differentially-expressed metabolites. Using metagenomics and metabolomics, this study explored the microbial functional cycle and differential metabolic pathways within desert riparian forests. The predominant biogeochemical cycles in the study area were the Carbon and Nitrogen cycles, comprising 78.90 % of C, N, Phosphorus, Sulfur and Iron cycles. Drought led to increased soil C fixation, reduced C degradation and methane metabolism, weakened denitrification, and decreased N fixation. Furthermore, drought can disrupt iron homeostasis and reduce its absorption. The differential metabolic pathways of drought stress include flavonoid biosynthesis, arachidonic acid metabolism, steroid hormone biosynthesis, and starch and sucrose degradation. Network analysis of functional genes and metabolism revealed a pronounced competitive relationship between the C cycle and metabolic network, whereas the Fe cycle and metabolic network promoted each other, optimizing resource utilization. Partial least squares analysis revealed that drought hindered the expression and metabolic processes and functional genes, whereas the rhizosphere environment facilitated metabolic expression and the functional genes. The rhizosphere effect primarily promoted metabolic processes indirectly through soil enzyme activities. The integrated multi-omics analysis further revealed that the effects of drought and the rhizosphere play a predominant role in shaping soil functional potential and the accumulation of metabolites. These insights deepen our comprehension of desert riparian forest ecosystems and offer strong support for the functionality of nutrient cycling and metabolite dynamics.

Between Delivery and Luck: Projectification of Academic Careers and Conflicting Notions of Worth at the Postdoc Level

AbstractThis paper investigates how early career academics interpret and respond to institutional demands structured by projectification. Developing a ‘frame analytic’ approach, it explores projectification as a process constituted at the level of meaning-making. Building on 35 in-depth interviews with fixed-term scholars in political science and history, the findings show that respondents jointly referred to competition and delivery in order to make sense of their current situation. Forming what I call the project frame, these interpretive orientations were legitimized by various organizational routines within the studied departments, feeding into a dominant regime of valuation and accumulation. However, while the content of the project frame is well-defined, attempts to align with it vary, indicating the importance of disciplines and academic age when navigating project-based careers. Furthermore, this way of framing academic work and careers provokes tensions and conflicts that junior scholars try to manage. To curb their competitive relationship and enable cooperation, respondents emphasized the outcome of project funding as ‘being lucky.’ They also drew on imagined futures to envision alternative scripts of success and worth. Both empirically and conceptually, the article contributes to an understanding of academic career-making as a kind of pragmatic problem-solving, centered on navigating multiple career pressures and individual aspirations.

Molecular cross-talk among human intestinal bifidobacteria as explored by a human gut model.

Bifidobacteria are well known as common and abundant colonizers of the human gut and are able to exert multiple beneficial effects on their host, although the cooperative and competitive relationships that may occur among bifidobacterial strains are still poorly investigated. Therefore, to dissect possible molecular interactions among bifidobacterial species that typically colonize the human gut, three previously identified bifidobacterial prototypes, i.e., B. bifidum PRL2010, B. breve PRL2012, and B. longum PRL2022 were cultivated individually as well as in bi- and tri-association in a human gut-simulating medium. Transcriptomic analyses of these co-associations revealed up-regulation of genes predicted to be involved in the production of extracellular structures including pili (i.e., flp pilus assembly TadE protein gene), exopolysaccharides (i.e., GtrA family protein gene) and teichoic acids (i.e., ABC transporter permease), along with carbohydrate, amino acid and vitamin metabolism-related genes (i.e., exo-alpha-sialidase; beta-galactosidase and pyridoxamine kinase), suggesting that co-cultivation of bifidobacteria induces a response, in individual bifidobacterial strains, aimed at enhancing their proliferation and survival, as well as their ability to cooperate with their host to promote their persistence. Furthermore, exposure of the selected prototypes to human cell line monolayers unveiled the ability of the bifidobacterial tri-association to communicate with their host by increasing the expression of genes involved in adherence to/interaction with intestinal human cells. Lastly, bifidobacterial tri-association promoted the transcriptional upregulation of genes responsible for maintaining the integrity and homeostasis of the intestinal epithelial barrier.

Predefined-time convergence strategies for multi-cluster games in hybrid heterogeneous systems

This paper explores the problem of (generalized) Nash equilibrium search in multi-cluster games with heterogeneous dynamics and multiple constraints. Within this research framework, each agent acquires information solely through local interactions with its neighbors and forms clusters based on similarity of interests. These clusters manifest dual relationships of cooperation and competition: agents within the same cluster enhance decision-making capabilities through cooperation, while different clusters compete to maximize their respective benefits. To delve into these complex interactions among clusters and the learning and evolution processes among agents, four distributed control algorithms suitable for various scenario requirements are designed and implemented. These algorithms ensure that each agent converges to a Nash equilibrium (NE) or generalized Nash equilibrium (GNE) of the multi-cluster system within predefined time points. Finally, we apply these algorithms to the connectivity control problem of unmanned aerial vehicle swarms with diverse dynamics, validating the theoretical results through comprehensive simulations.

Invasive Studies of Dandelion and other Alien Species Based on Predictive Models

Taraxacum officinale is a plant commonly known as the dandelion. It is a perennial herb native to Eurasia but has been introduced to other parts of the world and is now considered a weed in many areas. Dandelions are used in traditional medicine to treat various ailments and are also used as a food source in some cultures. However, some people regard it as an invasive species, which is a species that is harmful to the biological chain. Some suggest a reason: the dandelion's reproductive rate and ability to survive are so strong that it can easily encroach on the territory of other species, causing their numbers to decline.To protect the whole ecosystem, we need to protect other species from being invaded by dandelions. Therefore, the first problem analyzed is the spread of dandelions, and the main idea for the first problem is the Sprawl prediction-based model. The influence of different environmental factors on the spread of dandelions was considered to predict the number of dandelions after a certain time.The second model is the Logistic model, which considers the competition relationship and also uses MATLAB to draw the image. Showing the relationship between the number of dandelions and that of another species. With some knowledge of the spread and a detailed analysis of the danger of dandelions to other species, we hypothesized two main species and counted their numbers to determine the impact of dandelions. Finally, our group inquired about the concept of invasive species to further analyze whether dandelions fit.

Hotel demand forecasting with multi-scale spatiotemporal features

Accurate demand forecasting is critical to hotel revenue management and related decision-making. Considering the heterogeneity and dynamics of spatial effects across different time scales, this study introduces a novel model which can deeply extract these features to improve the forecasting performance of hotel demand. Specifically, the model constructs input variables with different periodicities and then integrates a Transformer neural network and long short-term memory to extract multi-scale and dynamic spatiotemporal features to generate accurate forecasts. The effectiveness of the model is verified through an empirical case in Xiamen, China. Results suggest our model significantly outperforms benchmarks in terms of accuracy and robustness. The findings extend the application of spatial-temporal modeling in hotel demand forecasting. Hotel managers can use our forecasts to optimize operations, improve revenues, and control risks. The extracted spatiotemporal features can also help managers examine cooperation and competition relationships with neighbor hotels.