Complexity最新文献

This article presents a method of constructing counter-examples and a complete counter-example to the linear programming model alleged to be the solution to the traveling salesman problem. The counter-example is checked against the model proposed by Diaby et al. However, it applies to all similar formulations of the TSP problem.

Although the model in question was published in 2006, and there were several discussions regarding its correctness, the counter-example was never presented.

The presented counter-example is a regular graph, and the aim was not to have an example with the least possible size; therefore, the focus was on clarity. The counter-example has, therefore, 366 nodes in two main clusters, each node (in the main part) having exactly four connections to other nodes in the cluster.

In our statistical analysis, we have discovered that the distance distribution (referring to Euclidean distance) of many real networks follows certain patterns, especially the distances between connected nodes obey a scale-free distribution. However, the classic BA model does not exhibit this characteristic. Furthermore, existing network models are mostly evolved based on degree-preference mechanisms, without considering the potential influence of factors such as edge weights like spatial geographical factors on node-edge connections in real networks. Taking distance-weighted preferences as an example, this study proposes a network evolution model based on distance preference connections as the fundamental mechanism. By applying probability theory and mean-field theory, the model’s degree distribution is calculated to be exponential, with a clustering coefficient greater than that of the BA model and consistent with data from some real networks. Our model reveals that this distance preference mechanism may be the fundamental mechanism underlying the emergence of high clustering in real networks. Additionally, by incorporating degree-preference connection mechanisms, the model is further analyzed and improved to better match actual network evolution behaviors. The research results provide a possible explanation for resolving the controversy surrounding the scale-free nature of networks.

Many organisms, ranging from modern humans to extinct species, exhibit movement patterns that can be described by Lévy walk dynamics. It has been demonstrated that such behavior enables optimal foraging when resource distribution is sparse. Here, we analyze a dataset of football player trajectories, recorded during the matches of the Japanese football league, to elucidate the presence of statistical signatures of Lévy walks, such as the heavy-tailed distribution of distances traveled between significant turns and the characteristic superdiffusive behavior. We conjecture that the competitive environment of a football game leads to bursty movement dynamics reminiscent of that observed in hunter-gathering populations and more broadly in any biological organisms foraging for resources, whose exact distribution is unknown to them. Apart from analyzing individual players’ movements, we investigate the dynamics of the whole team by studying the movements of its center of mass (team’s centroid). Remarkably, the trajectory of the centroid also exhibits Lévy walk properties, marking the first instance of such type of motion observed at the group level. Our work concludes with a comparative analysis of different teams and some discussion on the relevance of our findings to sports science and science more generally.

Due to the significant tension–compression asymmetry of rocks, the disparity between the results of Brazilian splitting tests and those derived from the linear elastic constitutive theory has been a topic of extensive discussion. In order to delve into the stress–strain field evolution and crack propagation process of Brazilian splitting tests under tension–compression varying modulus constitutive models, finite element software was employed. By means of self-developed subroutines, a method was employed to control the rock’s tension and compression with different modulus. Comparative analysis was conducted to scrutinize the distinctions between linear elastic constitutive models and variational modulus constitutive models. The results elucidate that under the variational modulus constitutive model: (1) Stress concentration in the x-direction does not occur at the center of the rock but is offset toward the two sides of the rock loading end, with stress peaks similar to linear elasticity; (2) under the variable modulus constitutive model, shear effects are pronounced at both ends of the rock loading axis, and initial cracks in the rock originate near the two sides of the loading end, forming initial cracks of tensile-shear mixed mode; and (3) due to the influence of shear stresses at both ends of the rock loading, the ultimate load of the rock is lower than that of a linear elastic structure, and the calculated tensile strength is lower than the true strength of the rock.

Rapid urbanization and inadequate transportation infrastructure in developing countries have led to complex, unsustainable travel patterns and adverse environmental impacts. This study employs structural equation modeling (SEM) to explore the interplay between land use patterns and travel behavior in Rajshahi, Bangladesh. Analyzing data from 1298 respondents, we uncovered intricate relationships between sociodemographic, economic, and spatial factors. The SEM revealed that economic characteristics had the highest total effect (0.674) on travel behavior, followed by land use (0.521). Notably, accessibility negatively correlated with economic (−0.70) and sociodemographic factors (−0.91). The residential environment emerged as the most significant land use indicator, with a weight of 1.820. Our analysis found that 31% of trips used easy bikes, while 23% were on foot. The employment rate positively impacted economic characteristics (1.270), despite the considerable weight of total household income (0.874). Key findings indicate that economic characteristics and land use patterns are the primary drivers of travel behavior, highlighting the need for integrated urban planning. This study provides a nuanced understanding of urban complexity, offering valuable insights for sustainable transportation planning in developing cities. By elucidating the nonlinear interactions between various urban elements, our research contributes to the growing field of complex systems analysis in urban transportation contexts.

Through theoretical analysis and empirical test, the following conclusions are drawn: Firstly, the benchmark test proves that transfer payments (TPs) significantly promote regional TFP. Secondly, the conclusions of this paper are still valid after using the system GMM model and instrumental variable method to deal with the endogeneity problem. Thirdly, heterogeneity analysis shows that TPs have a greater impact on TFP in the central and western regions, and general TPs and special TPs significantly promote regional TFP. Fourthly, mechanism analysis shows that TPs promote regional TFP through two channels: narrowing the financial gap between local governments and reducing the vertical fiscal imbalance between central and local governments. Because the balanced distribution of financial resources means the effective supply of public goods, all regions have the conditions to optimize the allocation of resources and improve the efficiency of resource use. Based on this, it is still necessary to implement the TPs system. Also, there is a need to optimize the TP rules.

Conventional synergy theory explains the inhibitory effects of drug combinations at specific times. Determining the magnitude of inhibition is crucial for exploring the synergy effect. In the results of previous studies, the Chou–Talalay multiple drug effect analysis demonstrated that the combination of a mutant oncolytic herpes virus (G207) and the chemotherapeutic agent (paclitaxel) is the most effective strategy for treating anaplastic thyroid cancer, compared to other combinations such as G207 and NV1023 or paclitaxel and doxorubicin. However, the mechanism behind the synergy effect of G207 and paclitaxel remains unknown, and measuring the synergy effect over time is challenging and expensive. In this study, we formulated a mathematical model to quantify the synergy of G207, paclitaxel, and both over time using the dataset. We conducted a Bayesian estimation of tumor cell proliferation over 16 days using Markov chain Monte Carlo sampling. The Bliss independence was incorporated into the model to compare the observed and expected responses to combination therapy. The expected antitumor effect was significantly lower than the experimental data, suggesting a synergistic effect. Our result showed that the antitumor effect was influenced by the rate of inhibition of tumor growth and the absolute growth delay. Additionally, we found that combination therapy achieved an additional 24% antitumoral effect and a 12-day delay in cell growth. This modeling approach suggests the possibility of quantifying synergistic effects.

The recent progress in the fields of sensor miniaturization, light materials, automatic control, and battery management systems has opened up new opportunities for low-cost unmanned aerial vehicles (UAVs), such as quadrotors. In fact, quadrotors have transitioned from a primarily military application to being widely used almost everywhere. Evidently, controlling such robots requires a deep understanding of their dynamic behavior and the use of robust strategies to accomplish the flight missions without compromising users’ safety. This study presents a comprehensive survey of control strategies for unmanned quadrotors. In our examination, the performance assessment of widely used control algorithms is discussed. Furthermore, the concept of model-based design is presented as a solution for bridging the gap between simulation and experimental validation of control systems. It is anticipated that the present study will provide the reader with a clear vision of quadrotor UAV control theory.

Image encryption schemes are predominantly software-based. Only a select few have been implemented in real-life communication systems. This paper introduces a novel chaotic image encryption scheme based on a modified Z-order curve, a modified Josephus problem, and an improved Vigenère cipher–based ribonucleic acid (RNA) operation. It is implemented and assessed within a light-fidelity (Li-Fi) infrastructure, comprising two core components: software and hardware. The software component manages data encryption and decryption, while the hardware ensures efficient data transmission. The proposed encryption scheme starts with a pixel-level permutation based on an improved Z-order curve, applicable to rectangular images, optimizing efficiency and increasing permutation ability. This is followed by a bit-level permutation using a modified Josephus problem, which enhances the diversity of generated sequences and introduces additional dislocation effects. Subsequently, a Vigenère cipher–based RNA operation serves for diffusion alongside basic RNA operations and the cipher block chaining (CBC) mode. Theoretical analyses and experimental findings demonstrate that the proposed encryption scheme is highly robust, outperforming several existing cryptosystems. Moreover, owing to its successful implementation, the proposed encryption scheme signifies a compelling stride toward bolstering secure visible light communication systems.

This article investigates the finite-time (FT) boundedness problem for the time delay (TD) Takagi–Sugeno fuzzy model (TSFM) with conformable derivative (CD) and in the presence of certain actuator faults. Through the reconstruction of an appropriate Lyapunov–Krasovskii functional, some sufficient conditions expressed by the linear matrix inequalities (LMIs) are given to ensure the FT boundedness of the proposed model not only during regular operation but also when encountering certain actuator faults. Finally, a numerical example and an inverted pendulum system are presented to illustrate our theoretical results.