Search results

Oil is crucial for industrial development. This paper investigates the impacts of oil price changes on China's industrial growth and examines whether the impacts are asymmetric. The estimations can help determine how oil price shocks are transmitted throughout the economy.

This paper adopts West Texas Intermediate (WTI) crude oil price and industrial sector output and uses monthly data. The recently developed nonlinear autoregressive distributed lag (NARDL) model is employed to illustrate the effects in both the short term and long term. Importantly, under NARDL framework, this paper examines whether the impacts are asymmetric by decomposing oil price shocks into their positive and negative partial sums.

The empirical results prove clear evidence of asymmetries in the short term, long term or both terms. Specifically, some sectors benefit from, rather than suffer from higher oil prices, even some energy-intensive sectors, i.e. C31 (Smelting and Pressing of Ferrous Metals) and C32 (Smelting and Pressing of Non-ferrous Metals). However, the effects on some other energy-intensive sectors appear insignificant. Additionally, the results prove significantly negative responses in some sectors in the long term, and most of these sectors are in the top half of the ranking by energy consumptions.

This paper studies the economic responses at a disaggregated level by employing industry-level data. NARDL method is used to decompose oil price changes into their increases and decreases and investigate the asymmetries in the impacts of oil price changes.

The need for an efficient enterprise risk management (ERM) has never been greater than today when organisations face complex and interconnected risks targeting their business models. Macroeconomics and geopolitical uncertainties, digital transformations of industries and sectors, cybersecurity, and climate change, among other trends, present significant uncertainties. This article aims to analyse the scientific papers on research specific to ERM and review the links between the researched area and market or corporate governance topics. Risk management is underdeveloped in many organisations; the current standard for risk management is a reactive approach. It is usually treated in isolation rather than as a core competency and a strategic asset. As a result, risk management processes are ineffective and seen as adding value to decision-making and responding to uncertainties. Based on the literature, the scope is to set up the framework for future research on ERM by building a bibliometric analysis and examining articles collected from the Web of Science Core Collection database. The study identified the essential research on this topic based on the citations of the papers and the author’s countries with the highest number of publications and citations. VOSviewer software analysed the ERM system based on keywords, citations, geographical distribution, and authorships. The research proves a strong connection between the ERM and corporate governance topics considering the stage where most countries are regarding this subject.

Thermopile infrared (IR) detectors are one of the most important IR devices. Considering that the surface area of conventional four-end-beam (FEB)-based thermopile devices cannot be effectively used and the performance of this type of devices is relatively low, this paper aims to present a double-end-beam (DEB)-based thermopile device with high duty cycle and performance. The paper aims to discuss these issues.

Numerical analysis was conducted to show the advantages of the DEB-based thermopile devices.

Structural size of the DEB-based thermopiles may be further scaled down and maintain relatively higher responsivity and detectivity when compared with the FEB-based thermopiles. The authors characterized the thermoelectric properties of the device proposed in this paper, which achieves a responsivity of 1,151.14 V/W, a detectivity of 4.15 × 108 cm Hz1/2/W and a response time of 14.46 ms sensor based on DEB structure.

The paper proposed a micro electro mechanical systems (MEMS) thermopile infrared sensor based on double-end-beam structure.

This paper aims to study the sensitivity enhancement effect of the gold nanorod on fiber surface plasmon resonance (SPR) sensor. It proposes modeling the sensing effects of fiber SPR sensor decorated with metal nanoparticles. By using simulation and experiment, the sensitivity enhancement effect of the gold nanorod was studied and demonstrated.

The paper opted for an exploratory study using simulation approach of finite-difference time-domain. Specifically, the effect of ratios and aspect ratios of gold nanorod on sensing performance are investigated theoretically. Based on the mathematical models, the validation experiments by using the gold nanorod with the aspect ratios of 5.1 were done to verify the sensitivity enhancement effect of the gold nanorod.

In conclusion, it is evident that with the increases of the aspect ratios, the sensing sensitivity of the refractive index increases first, then gradually stabilizes or decreases. After parameter optimization, the ratios and aspect ratios of gold nanorod are chosen to be 8 nm and 12.5, respectively, which makes the optimal refractive index sensitivity of 4465.53 nm/RIU be realized. In addition, the validation experiments by using the gold nanorod with the aspect ratios of 5.1 verify the sensitivity enhancement effect of the gold nanorods.

This paper proposes and demonstrates a new method for the sensitivity enhancement of fiber SPR sensor. After parameter optimization, the maximum sensitivity of 4465.53 nm/RIU was achieved by using 8 nm gold nanorods with the aspect ratios of 12.5. To verify the sensitivity enhancement of the gold nanorods, the authors also did the validation experiments. The testing results indicated that after the decoration of the gold nanorods, the sensitivity of the sensing probe increases from 2190.57 nm/RIU to 2693.24 nm/RIU, which demonstrates the sensitivity enhancement effect of the gold nanorods.

In this article, the elementary notions and aggregation operations of single-valued neutrosophic parameterized complex fuzzy hypersoft set (sv-NPCFHSS) are characterized initially. Then by using matrix version of sv-NPCFHSS, a decision-support system is constructed for the evaluation of real estate residential projects by observing various risk factors.

Two approaches are utilized in this research: set-theoretic approach and algorithmic approach. The first approach is used to investigate the notions of sv-NPCFHSS and its some aggregations whereas the second approach is used to propose an algorithm for designing its decision-support system by using the aggregation operations like reduced fuzzy matrix, decision matrix, etc. of sv-NPCFHSS. The adopted algorithm is validated in real estate scenario for the selection of residential project by observing various risk factors to avoid any expected investment loss.

The proposed approach is more flexible and reliable as it copes with the shortcomings of literature on sv-neutrosophic set, sv-neutrosophic soft set and other fuzzy soft set-like structures by considering hypersoft setting, complex setting and neutrosophic setting collectively.

It has limitations for complex intuitionistic fuzzy hypersoft set, complex neutrosophic hypersoft set and other complex neutrosophic hypersoft set-like models.

The scope of this research may cover a wide range of applications in several fields of mathematical sciences like artificial intelligence, optimization, MCDM, theoretical computer science, soft computing, mathematical statistics etc.

The proposed model bears the characteristics of most of the relevant existing fuzzy soft set-like models collectively and fulfills their limitations.

As wheeled mobile robots find increasing use in outdoor applications, it becomes more important to reduce energy consumption to perform more missions efficiently with limit energy supply. The purpose of this paper is to survey the current state-of-the-art on energy-efficient motion planning (EEMP) for wheeled mobile robots.

The use of wheeled mobile robots has been increased to replace humans in performing risky missions in outdoor applications, and the requirement of motion planning with efficient energy consumption is necessary. This study analyses a lot of motion planning technologies in terms of energy efficiency for wheeled mobile robots from 2000 to present. The dynamic constraints play a key role in EEMP problem, which derive the power model related to energy consumption. The surveyed approaches differ in the used steering mechanisms for wheeled mobile robots, in assumptions on the structure of the environment and in computational requirements. The comparison among different EEMP methods is proposed in optimal, computation time and completeness.

According to lots of literature in EEMP problem, the research results can be roughly divided into online real-time optimization and offline optimization. The energy consumption is considered during online real-time optimization, which is computationally expensive and time-consuming. The energy consumption model is used to evaluate the candidate motions offline and to obtain the optimal energy consumption motion. Sometimes, this optimization method may cause local minimal problem and even fail to track. Therefore, integrating the energy consumption model into the online motion planning will be the research trend of EEMP problem, and more comprehensive approach to EEMP problem is presented.

EEMP is closely related to robot’s dynamic constraints. This paper mainly surveyed in EEMP problem for differential steered, Ackermann-steered, skid-steered and omni-directional steered robots. Other steering mechanisms of wheeled mobile robots are not discussed in this study.

The survey of performance of various EEMP serves as a reference for robots with different steering mechanisms using in special scenarios.

This paper analyses a lot of motion planning technologies in terms of energy efficiency for wheeled mobile robots from 2000 to present.

The purpose of this study is to examine how the quality management of small and medium-sized enterprises (SMEs) impacts their supply chain financing performance (SCFP). This study also investigates the mediating roles of organisational dependence between quality management and the SCFP of SMEs, as well as the moderating role of environmental dynamics.

Questionnaires were administered to 248 financial managers responsible for supply chain finance (SCF) in SMEs in China. Data analysis techniques used include necessary condition analysis and multiple regression analysis.

Research findings show that, in SCF, the quality management of SMEs positively predicts their SCFP through the mediation of the organisational dependence of the focal enterprises in the supply chain network. Environmental dynamics are also found to moderate the relationship between quality management and SCFP through the organisational dependence of capital providers.

To the best of our knowledge, this is the first study to explore the relationships between SMEs' quality management and their SCFP. Also, this study provides a new theoretical lens through which to study SCF by introducing signalling theory.

Currently, China’s economy is in the critical phase of transforming economic development patterns and replacing old growth drivers with new ones. Whether it can successfully overcome the “middle-income trap” has become a significant issue attracting wide attention.

Driven by underlying digital technologies such as artificial intelligence, blockchain, cloud computing and big data, the fourth industrial revolution featuring the booming digital economy has provided significant opportunities for China’s economy to “overtake” and overcome the “middle-income trap”. The transformation of economic development pattern, the optimization of industrial structure, and the change of growth drivers, brought by the deep integration of digital and real economies are the keys to leaping over the “middle-income trap”.

From the supply side, the digital economy can improve the quality and efficiency of the supply side and promote the supply-side structural reform and economic growth from the following three aspects: First, promote the quality, efficiency and diversification of the supply system; second, promote networking, opening-up and synergy in the innovation system and third, promote the socialization, modularization and flexibility of production pattern. From the demand side, the digital economy can boost the new drivers of the “troika” of economic growth consisting of consumption, exports and investment by changing the market investment direction, promoting consumption upgrade and fostering export strengths. However, once these two attributes interact with each other, especially when data is combined with capital, the most adhesive factor in the market economy, a series of new social relations will then be produced based on the technical attribute, resulting in significant adjustments in social relations, involving both positive and negative externalities.

To overcome the “middle-income trap”, it is necessary to adapt to the laws of economic evolution and promote a fundamental change in economic growth drivers; boost the high-quality development of the digital economy by strengthening the support role of data in the digital economy; and accelerate digital industrialization and industrial digitalization to realize the integration of digital and real economies.

This paper aims to clarify the relationship between the performance of the metal nanoparticles and the sensitivity of the fiber surface plasma resonance (SPR) sensor. It proposes modeling the sensing effects of a single-mode fiber SPR sensor with a cone angle structure decorated with metal nanoparticles. This study uses the metal nanoparticles to the realize enhanced sensitivity of refractive index sensing.

This paper opted for an exploratory study using a simulation approach of finite-difference time-domain (FDTD). Specifically, the effect of size, the material and the shape of the metal nanoparticle on sensing performance are investigated theoretically.

In conclusion, it is evident that the localized SPR (LSPR) effect weakens as the diameter of the gold nanosphere increases, the SPR effect enhances and the SPR sensitivity increases first and then decreases. The metal nanoparticle with the different materials and different shapes also have different LSPR and SPR sensitivity and wavelength length dynamic range. The investigation shows that, by changing parameters, the reflection spectra of the fiber SPR sensor exhibit an obvious transition from LSPR to SPR characteristics, and enhanced sensitivity of the refractive index is realized.

This paper fulfills an identified need to study how the sensitivity of the fiber SPR sensor can be enhanced by the metal nanoparticle. After the optimization of parameters, the sensitivity of 5,140 nm/RIU is achieved, which provides a new research direction for sensitivity enhancement of fiber SPR sensor.