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The purpose of this paper is to design a flying wheel-legged humanoid robot (FWLR), endowing the robot with flight capability to improve the obstacle-crossing ability of the wheel-legged humanoid robot. A flight control method using thrust-vector-control (TVC) under constant thrust strength is proposed, which reduces the performance requirements on the response speed of thrusters.

To endow the robot with flight capability, three sets of thrusters are installed at the robot’s back and two arm ends to provide flight lift and the direction of thrust can be changed through the arm swing. According to the robot configuration, this paper established a linearized dynamic model and proposed a constant-strength-thrust-vector-control (CSTVC) framework enabling the robot to achieve flight without thrust intensity change.

With the proposed modeling method and CSTVC framework, FWLR can inhibit attitude and position drift during takeoff and hovering, and has certain adaptability to takeoff attitude. Finally, FWLR reached a flying height up to 1 m under a 30 kg large self-weight with fixed thrust strength.

The design, modeling and flight control method proposed in this paper enables a human-sized wheel-legged humanoid robot to achieve takeoff and hovering for the first time. The movement range of wheel-legged humanoid robot is extended to the air, thereby enhancing its application value in emergency tasks such as disaster search-and-rescue.

This contribution investigates the numerical solution of Volterra integral equations with auto-convolution of the third kind (AVIE). The numerical method applied in this investigation employs a collocation method based on the moving least squares (MLS) approximation. The MLS approximation is an effective way of approximating an unknown function by taking a disordered dataset. This method is a mesh-free approach since it does not require background interpolation or approximation cells, and is independent of domain geometry. The proposed method reduces the solution of third-kind AVIEs to the solution of systems of algebraic equations. By employing the Gauss–Legendre integration formula, we can estimate all the integrals of these equations. The applicability and validity of this method are demonstrated by numerical experiments, and its efficiency and robustness are proven by comparison with existing methods.

The numerical method applied in this study uses a collocation method based on moving least squares (MLS) approximation. This method is a mesh-free approach since it requires no background interpolation or approximation cells and is independent of domain geometry. Using the Gauss–Legendre integration formula, we can estimate all the integrals of these equations.

The authors declare that they have no known competing financial interests.

The manuscript has not been copyrighted or published previously and is not under consideration for publication elsewhere.

While the average cost of debt capital can be calculated from historical financial statement data by dividing the interest paid each year by the total level of debt, this average cost of debt provides little information regarding the true cost of acquiring additional debt capital, and hence, its use is potentially problematic in financial decision-making. This study focuses on the linkage between observed changes in the average interest rates calculated from financial statements (balance sheet and income statement) and the marginal cost of borrowing or the cost of acquiring new debt. Motivated by the capital asset pricing model (CAPM), the marginal cost of capital is modeled as a function of a risk-free interest rate (the return on Moody’s Aaa bonds), returns on the S\&P stock index capturing overall market returns and a portfolio of agricultural stocks to represent farm sector-specific risks.

Using a unique dataset constructed from United States Department of Agriculture (USDA) state-level Financial Performance of the Farm Sector data for the years 1960 through 2003 and state-level Agricultural Resource Management Survey (ARMS) data for the years 2003–2014 and Bayesian methods, we model the observed interest rate as an autoregressive function controlling for changes in debt and key rates of return in the general economy.

The results indicate that the marginal interest rate is a function of the Aaa corporate bond rate and the stock market. We also find evidence of a negative relationship between returns to a portfolio of agricultural stocks and the marginal interest rate. Overall, the findings suggest that the imputed interest rate frequently misrepresents the marginal cost of debt capital.

Most farm financial datasets allow for the analysis of the farm firm’s average interest rate. However, farmers make decisions based on the marginal cost of credit – the interest rate on a newly issued note. This study estimates this marginal interest rate for the 15 states for which the ARMS data are representative for the years 1960 through 2014 and compares the estimated marginal interest rate with the imputed average interest rate.

The purpose of this paper is to investigate the existence, uniqueness and stability of solutions to a class of Riemann–Liouville fractional differential equations with anti-periodic boundary conditions of variable order (R-LFDEAPBCVO). The study utilizes standard fixed point theorems (FiPoTh) to establish the existence and uniqueness of solutions. Additionally, the Ulam-Hyers-Rassias (Ul-HyRa) stability of the considered problem is examined. The obtained results are supported by an illustrative example. This research contributes to the understanding of fractional differential equations with variable order and anti-periodic boundary conditions, providing valuable insights for further studies in this field.

This paper (1) defines the Riemann–Liouville fractional differential equations with anti-periodic boundary conditions of variable order (R-LFDEAPBCVO); (2) discusses the existence and uniqueness of solutions to these equations using standard FiPoTh; (3) investigates the stability of the considered problem using the Ul-HyRa stability concept (Ul-HyRa); (4) provides a detailed explanation of the design and methodology used to obtain the results and (5) supports the obtained results with a relevant example.

The authors confirm that no funds, grants or any other form of financial support were received during the preparation of this manuscript.

The originality/value of our paper lies in its contribution to the field of fractional differential equations. Specifically, we address the existence, uniqueness and stability of solutions to a class of Riemann–Liouville fractional differential equations with anti-periodic boundary conditions of variable order. By utilizing standard FiPoTh and investigating Ul-HyRa stability, we provide novel insights into this problem. The results obtained are supported by an example, further enhancing the credibility and applicability of your findings. Overall, our paper adds to the existing knowledge and understanding of Riemann–Liouville fractional differential equations with anti-periodic boundary conditions, making it valuable to the scientific community.

This study investigates the implications of country-level aggregate sales decline on firms’ cost stickiness and explores how legal systems and cultural dimensions moderate this relationship.

We analyze an international sample of firms from 39 countries over the 2003–2022 period using regression analysis to examine the relationship between aggregate sales decline and firms’ cost behavior.

Our findings reveal that country-level aggregate sales decline reduces firms’ cost stickiness, in contrast to the extensively documented positive association between firm-level sales decline and cost stickiness. This reduction in cost stickiness is statistically and economically significant, regardless of whether firms individually experience consecutive sales declines. Moreover, the impact is significantly stronger for firms in common-law countries, countries with long-term orientation and countries with higher levels of individualism.

The study is the first multinational study to examine the effect of aggregate sales decline on cost stickiness. The study also offers insights into the role of legal systems and cultural dimensions in moderating this relationship.

This article examines the relationship between service quality and earnings management in Brazilian electricity distributors.

Service quality was measured using the Global Continuity Performance Indicator, as released by the Brazilian Electricity Regulatory Agency (ANEEL). To measure earnings management, the models by Dechow et al. (1995), Kothari et al. (2005), and Pae (2005) were used.

The results show that lower service quality is related to greater opportunism in management through earnings management. Furthermore, the study shows that managing earnings can distort the true economic and financial position of companies with low operational performance.

The research enhances comprehension regarding the correlation between service quality, measured by the Global Continuity Performance Indicator, and earnings management within a distinct industrial and regulatory framework. This could establish a foundation for prospective studies delving into analogous relationships across diverse sectors or regions.

The findings offer insights for regulatory authorities to promote higher standards in the generation of informational quality, which can impact the quality of services.

Enhancing the quality of electrical service through more responsible management practices leads to increased consumer satisfaction, driven by improvements in the continuity of energy supply.

A gap exists in the literature due to the lack of studies examining the relationship between the quality of electrical service, measured by the continuity index, and opportunistic management practices through earnings management.

The purpose of studying the impact of crude oil and natural gas prices on the Vietnamese stock market is to understand the relationship between energy prices and the overall performance of the financial markets. As Vietnam is an energy-dependent country, fluctuations in crude oil and natural gas prices can significantly affect various industries, including manufacturing, inflation, transportation, energy production and economic growth. These sectors are often sensitive to changes in energy costs, which can lead to shifts in corporate profitability and investor sentiment. By analyzing how crude oil and natural gas prices influence the Vietnamese stock market, policymakers and investors can provide deeper insights into the economic risks and opportunities related to energy price volatility. This paper can also provide valuable information for decision-making in sectors such as economic forecasting, risk management and investment strategies.

Using monthly data from January 2006 to March 2024, data were collected from the Vietnamese stock market and the OPEC organization for oil prices, while data on natural gas were obtained from the EIA. The data were analyzed using vector error correction (VEC) model, impulse response function, variance decomposition test and asymmetric reactions method; the study tries to ascertain the short-term and long-term dynamic relationships between the shocks of the crude oil price and natural gas prices and their effects on the movement of the stock price. In addition, the GARCH model is applied to measure the volatility of crude oil and natural gas prices.

Crude oil price shocks have a statistically significant impact on most Vietnamese real stock market indices, except for the utility and consumer indices and some energy companies. Conversely, natural gas price shocks do not significantly affect on Vietnamese stock market indices, except for the energy index and some energy companies. Some “important” of both crude oil price and natural gas price shocks tend to depress the stock returns of energy companies. An increase in both crude oil and natural gas volatility can lead to heightened speculation in certain indices, particularly the energy and industrial indices, as well as in some energy companies. This heightened speculation often results in elevated of their stock returns.

This study provides valuable insights into the field of study examining how fluctuations in the prices of oil and gas, particularly during major crisis periods such as global financial crisis, COVID-19 pandemic and the Russo-Ukrainian War, affect financial markets.

Accurate prediction of port cargo throughput within Free Trade Zones (FTZs) can optimize resource allocation, reduce environmental pollution, enhance economic benefits and promote sustainable transportation development.

This paper introduces a novel self-adaptive grey multivariate prediction modeling framework (FARDCGM(1,N)) to forecast port cargo throughput in China, addressing the challenges posed by mutations and time lag characteristics of time series data. The model explores policy-driven mechanisms and autoregressive time lag terms, incorporating policy dummy variables to capture deviations in system development trends. The inclusion of autoregressive time lag terms enhances the model’s ability to describe the evolving system complexity. Additionally, the fractional-order accumulative generation operation effectively captures data features, while the Grey Wolf Optimization algorithm determines optimal nonlinear parameters, enhancing the model’s robustness.

Verification using port cargo throughput forecasts for FTZs in Shanghai, Guangdong and Zhejiang provinces demonstrates the FARDCGM(1,N) model’s remarkable accuracy and stability. This innovative model proves to be an excellent forecasting tool for systematically analyzing port cargo throughput under external interventions and time lag effects.

A novel self-adaptive grey multivariate modeling framework, FARDCGM(1,N), is introduced for accurately predicting port cargo throughput, considering policy-driven impacts and autoregressive time-lag effects. The model incorporates the GWO algorithm for optimal parameter selection, enhancing adaptability to sudden changes. It explores the dual role of policy variables in influencing system trends and the impact of time lag on dynamic response rates, improving the model’s complexity handling.

The purpose of this study is to (1) improve the spectral features of the second-order uniformly non-oscillatory (UNO) slope limiters, and (2) numerical simulation of the unified-form of generalized fully-coupled saturated thermo-poro-elastic systems in the axisymmetric cylindrical coordinate via cell-adaptive Kurganov-Tadmor (KT) central high-resolution scheme using the UNO limiters.

(1) The spectral features of the UNO limiter are improved by compression-adaptive MINMOD (MM) limiters, achieved by blending different types of MM limiters to achieve less numerical dissipation and dispersion. These blended MM limiters preserve the total variation diminishing (TVD) feature over non-uniform non-centered cells. Also, the spectral features of the central schemes using the UNO limiters are investigated. (2) For the thermo-poro-elastic problem, corresponding first-order hyperbolic system is provided, including flux, source, diffusion and nonlinear terms. Where, there are different interacting components in the source and flux terms. The nonlinear terms are also considered by the Picard-like linearization concept.

Compression-adaptive UNO limiters would be stable over adapted cells with centered and non-centered cells. The benchmarks confirm that both spectral features and numerical accuracy are improved. For the generalized thermo-poro-elastic problem, corresponding responses including the shock waves can properly be captured.

Studying heat effects (e.g. hot fluid or freezing) and explosions on tunnels. Also, the UNO limiters could be used for simulations of various systems of conservation laws.

This study examines the impact of environmental, social and governance (ESG) performance on cross-region investment in China.

This study utilized firm-level data from the China Stock Market and Accounting Research database covering 2009 to 2021, comprising 3,600 Chinese listed firms. Cross-region investment activities were measured using data on establishing subsidiaries across regional borders obtained from the TianYanCha website. Besides, this study also implemented the instrumental variables (IV) and difference-in-differences approach to address potential endogeneity issues. The panel Poisson and panel negative binomial models are used for robustness tests.

The findings indicate that companies with better ESG performance are more likely to establish cross-region subsidiaries, positively affecting cross-regional investment activities. Strong ESG performance reduces financing constraints, enhances information transparency and improves corporate reputation and resource allocation efficiency, thereby increasing cross-regional investment. Well-established ESG performance also helps overcome judicial barriers. Moreover, cross-region investments driven by ESG are less motivated by tax avoidance, pollution transfer and management self-interest.

We focus on listed companies in China, which may limit the applicability of our conclusions to other regions. Our measurement of cross-region investment might also underestimate its extent due to diverse investment methods. We suggest two future research directions: first, studies could explore the future performance of ESG-facilitated cross-region investments; second, further analysis could assess whether corporate ESG performance effectively dismantles administrative barriers and mitigates market segmentation.

Under China’s distinctive market segmentation phenomenon, this study fills a gap by providing new causal evidence of the role of managerial performance in mitigating capital flow boundaries.