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Innovation ability has become one of the core elements in the pursuit of China’s green growth, and high-tech industries are playing a leading role in technological innovation in China. With the rapid development of China’s high-tech industries, their innovation efficiency has attracted widespread attention. This article aims to illustrate a shared inputs two-stage network Data Envelopment Analysis (DEA), to measure the innovation efficiency of high-tech industries in China’s 29 provinces from 1999 to 2018. The results indicate that there are obvious differences in the innovation efficiency of the provinces. The technology development efficiency, the technical transformation efficiency, and the overall innovation efficiency of the developed east coast provinces are generally higher than those of the backward central and western provinces. This article further applies the spatial econometrics model to analyze the factors influencing the innovation efficiency of high-tech industries. We have found that government support, R&D input intensity, industries aggregation, economic extroversion, and the level of development of the modern service industries cause varying degrees of impact on innovation efficiency.

A range of optical fibre-based sensors for the measurement of ethanol, primarily in aqueous solution, have been developed and are reviewed here. The sensing approaches can be classified into four groups according to the measurement techniques used, namely absorption (or absorbance), external interferometric, internal fibre grating and plasmonic sensing. The sensors within these groupings can be compared in terms of their characteristic performance indicators, which include sensitivity, resolution and measurement range. Here, particular attention is paid to the potential application areas of these sensors as ethanol production is globally viewed as an important industrial activity. Potential industrial applications are highlighted in the context of the emergence of the internet of things (IoT), which is driving widespread utilization of these sensors in the commercially significant industrial and medical sectors. The review concludes with a summary of the current status and future prospects of optical fibre ethanol sensors for industrial use.

AbstractPreparation of uniform, spherical Li4Ti5O12 with high tap density is significant to achieve a high volumetric energy density in lithium‐ion batteries. Herein, Li4Ti5O12 microspheres with variable tap density and tunable size distribution were synthesized by a newly designed industrial spray‐drying approach. The slurry concentration, sintering time, sintering conditions after spraying, and the effect of lithium/titanium molar ratio on the lithium‐ion (Li+) storage capability were investigated. A narrow particle size distribution of around 10 μm and a high tap density close to 1.4 g cm−3 of the Li4Ti5O12 spheres can be obtained under the optimized conditions. The Li4Ti5O12 spheres can deliver a much higher capacity of 168 mAh g−1 at a rate of 1 C and show a high capacity retention of 97.7 % over 400 cycles. The synthetic conditions are confirmed to be critical for improving the electron conductivity and Li+ diffusivity by adjusting the crystal and spatial structures. As‐prepared high‐performance Li4Ti5O12 is an ideal electrode for lithium‐ion batteries or capacitors; meanwhile, the presented approach is also applicable for preparing other kind of spherical materials.

A GIS-based method is proposed to identify critical links in urban road networks. This study utilizes a geographic information system (GIS) to evaluate the distribution of road infrastructure, road density, and network accessibility at the micro, meso, and macro levels. At the micro level, GIS is used to assess the distribution of public facilities along the roads. At the meso level, a city’s road density distribution is evaluated. At the macro level, a spatial barrier model and a transportation network model are constructed to assess the network accessibility. An inverse distance weighting method is employed to interpolate the accessibility. Furthermore, a network topology is established, and the entropy method is utilized to evaluate the sections comprehensively. The sections are ranked based on the evaluation results to identify the critical links in the urban road network. The road-network data and points of interest (POI) data from the Anning District in Lanzhou are selected for a case study, and the results indicate that the top five critical links have scores of 0.641, 0.571, 0.570, 0.519, and 0.508, respectively. Considering the three indicators enhances the accuracy of critical section identification, demonstrating the effectiveness of the proposed method. Visualizing each indicator using GIS 10.7 provides a new approach to identifying critical links in urban road networks and offers essential theoretical support for urban planning.

This study uses the structured–pragmatics–situational case study approach to explore the intrinsic mechanism of enterprise digital enablement using affordance theory and how traditional enterprises enable customers to participate in value co-creation through information technology, then realize business model innovation and maintain continuous consumption. The study revealed the following: (1) Product affordance drives customers’ original willingness to engage in value co-creation in four dimensions: economy, reliability, uniqueness, and selectivity; (2) The visibility, convenience, association, and persistence of the platform affordance enhance users’ abilities to engage in value co-creation; (3) The interaction of affordance, structural enablement, and digital enablement drives the interaction of willingness and capability to engage in value co-creation; and (4) User participation behaviors in value co-creation can be divided into three dimensions (informational, actionable, and attitudinal participation)and four stages. The findings explain how traditional enterprises use IT enablement to promote business model innovation of customer participation in value co-creation and enrich the theories of digital enablement. The conclusions reveal the managerial implications of the ways, paths, and mechanism of business model innovation by IT enabling customers to participate in value co-creation.

The present study measured the relative efficiency of five major commercial ports in West Africa, using three different Data Envelopment Analysis (DEA) methods, the CCR, BCC, and Windows I-C methods over the years 2005-2016. Seven input variables and one output variable were used in the model analysis. The CCR and BCC methods were used to evaluate the technical and scale efficiency while the Windows I-C method provided a comprehensive ranking of the studied ports. The results showed that the scale efficiency score of 89.53% indicated that on average the production scale of the ports had deviated from the most productive scale size (MPSS) by 10.47%. These results revealed that the source of the overall inefficiency is due to scale rather than pure technical inefficiency. Hence, in order to improve the overall efficiency, the two scaled inefficient ports of Abidjan and Cotonou should adjust their scale of operations. Then, further investigations were conducted to detect correlations between various variables used in this study. The research found that the absence of any correlation for non-significant variables and negative correlation for the significant variables throughout time resulted from the fact that these variables were not fully utilized. Meaning that they were not efficiently used to boost the container throughput on a scale basis, the research also found that a pandemic or insecurity could easily impact seaports activities with the case of the Ebola outbreak which strucked the West African region from the year 2013 to 2016, or the terrorism threats which prevailed in the region around the year 2012. Thus, for ports to stand out in the present fiercely competitive environment, ports authorities ought to analyze their operational scale to identify whether or not the production size is fitting before further port capacity expansion.

Advanced airborne equipment liquid cooling system presents the development trend of multiple pumps in parallel, centralised heat dissipation and high efficiency circulation, but this type of system has the characteristics of many variable parameters and strong non-linearity, which makes the system operation and control become extraordinarily complex, posing a serious challenge to the system performance. Although some progress has been made in the current optimization of liquid cooling system performance, there are still gaps such as insufficient consideration of the multi-objective optimization problem and limited optimization effect. To fill this research gap, this study takes minimum specific energy consumption, minimum flow deviation and minimum impeller load as the optimization objectives, establishment of multi-objective optimization model for liquid-cooled power unit, the optimal solution set of the Pareto model is solved using the multi-objective grey wolf optimization algorithm (MOGWO), and the optimal solution set is substituted for the optimal solution, and the evaluation indexes are designed in combination with the actual working conditions to obtain the optimal schedule. By example analysis, the optimized system under variable operating conditions, the impeller load and specific energy consumption decreased by 16.88% and 3.64% respectively, while the rise in flow deviation was controlled within 0.76%. The newly established optimisation model effectively mitigates potential safety hazards during system operation. Finally, by combining all the indicators, three scheduling options are provided under variable operating conditions, focusing on reliability and economy, overall balance and high-precision flow, respectively, in order to adapt to the diversified requirements of different operating environments.

The vehicle will generate an amount of current while the electric vehicle just starting to regeneratively brake. In order to avoid the impact of high current on the traction battery, a novel electrohydraulic hybrid electric vehicle has been proposed. The main power source is supplied by the electric drive system, and the hydraulic system performs the auxiliary drive system that fully exerts the advantages of the electric drive system and the hydraulic drive system. A proper regenerative braking control strategy is presented, and the control parameters are determined by the fuzzy optimization algorithm. The simulation analysis built the model through the united simulation of AMESim and MATLAB/Simulink. The results illustrated that the optimized control strategy can reduce battery consumption by 1.22% under NEDC-operating conditions.