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To offer a realistic foundation for urban cultural construction planning, we want to investigate the distribution features of Shanghai's cultural functional elements and examine the distribution patterns in urban space.

In this research, we managed to gather POI geographic data, refined and categorized them to integrate eight categories of cultural functional elements, observed the density and agglomeration, distribution direction and hot and cold spots of overall and each type of cultural functional elements using geospatial analysis methods and then investigated the factors influencing cultural functional elements using geographic detectors.

Our research shows apparent differences between regions and most cultural functional elements are found in the inner city. Second, there are hot and cold spots in the way different cultural functional elements are spread out. Its geographic structure is primarily influenced by third-party traffic service capacity and available time.

This work provides a benchmark for cultural planning in Shanghai by establishing the spatial aggregation impact of cultural functional elements.

Using attribution theory, this study examined the effects of situational factors [time budget pressure (TBP), organisational ethical culture (OEC) and quality control procedures (QCPs)] and dispositional factors [auditor professional commitment (APC) and internal locus of control (ILOC)] on audit quality threatening behaviour (AQTB). In addition, it observed the moderating role of religiosity in the relationship between situational and dispositional factors and AQTB.

A total of 189 external auditors responded to the survey questionnaire. This study employed structural equation modelling via SmartPLS to analyse the proposed model.

The results documented that the OEC and QCPs situational factors were negatively related to the incidence of AQTB, whilst TBP was positively linked to the incidence of AQTB. Dispositional factors APC and ILOC were negatively connected to AQTB. Furthermore, the findings recorded the moderating effect of religiosity on most of the situational and dispositional factors related to AQTB.

Regulators and accounting firms' efforts to promote high audit quality (AQ) may consider the theological/religious lens and reinforce ethical culture and quality control to reduce AQTB.

The findings provide further insights into situational and dispositional factors that may cause or impede the incidence of AQTB in auditing practices, as well as the moderating role of religiosity in curbing AQTB.

The purpose of this paper is to highlight the use of big data through patentometric insights for R&D decision-making.

This study assesses the inventive activity through ‘big data’ patents, registered by inventors worldwide, using WIPO Patentscope database. The objective is to use the insights from patentometrics for R&D decision-making. The data from WIPO PatentScope (https://patentscope.wipo.int/search/en/search.jsf) was searched for current patent scenario in area of ‘big data’. The data was further organized and cleaned using the Google ‘OpenRefine’. Data was pre-processed to remove all null values. Cleaned data was analyzed using programming language ‘R’, MS Excel (charts and Pivot tables) and free data visualization tool called ‘Tableau Public’, to get insights for R&D decision-making.

The key insights included trends (patents with years of publication), top technologies trending the current space, top organizations leading in these technologies and the top inventors who are publishing patents in these technologies through leading organizations were drawn. Details in Section 5 in the paper.

Global patent data is multi-lingual and spreads across a set of multiple databases. Domain experts may be required to assess, identify and extract the relevant information for analysis and visualization of multi-lingual distributed data sets. Government organizations generally have multi-dimensional goals that may be more toward societal benefits. On the other hand, the commercial companies are more focused on profit. Therefore, the performance management process has to be really effective because it is critical for getting value in the government sector.

Insights from patent analytics serve as the important input to R&D managers as well as policymakers to assess the global needs to plan the national orientation according to the global market. This will help further for R&D projects prioritization, planning, budget allocations, human capital planning and other gamut of R&D management and decision-making.

Facilitation for R&D institutions (government as well as private) to formulate the research strategy for the domains or research areas to delve into. R&D decisions will be completely data-driven making them more accurate, reliable, valid and informed. These insights are very relevant for policymakers as well to facilitate the need assessment to determine the National priorities, make improvements in meeting societal country-level challenges during the resource allocation at top and subsequently at all other levels.

Data analytics of global patents in “big data” till 2019 to get insights to facilitate R&D decision-making.

In order to improve the computation efficiency of the four-point rainflow algorithm, a one-stage extraction four-point rainflow algorithm is proposed based on a novel data preprocessing method.

In this new algorithm, the procedure of cycle counting is simplified by introducing the data preprocessing method. The high efficiency of new algorithm makes it a preferable candidate in fatigue life online estimation of structural health monitoring systems.

According to the data preprocessing method, in the process of cycle extraction, all equivalent cycles can be extracted at just one stage instead of two stages in the four-point rainflow algorithm, where the cycle extraction has to be performed from the doubled residue. Besides, there are no residues in the new algorithm. The extensive numerical simulation results demonstrate that the accuracy of new algorithm is the same as that of the four-point rainflow algorithm. Moreover, a comparative study based on a long input data sequence shows that the computation efficiency of the new algorithm is 42% higher than that of the four-point rainflow algorithm.

This merit of new algorithm makes it preferable in some application scenarios where fatigue life estimation needs to be accomplished online based on massive measured data. And it may attribute to preprocessing of input data sequence before data processing, which provides beneficial guidance to improve the efficiency of existing algorithms.

This paper aims to examine the impact of host country corruption on foreign direct investment (FDI) from China to developing countries in Africa. With the opposing arguments that corruption is detrimental to or instrumental in FDI and mixed empirical evidence, this paper contributes to the literature by providing new evidence on the issue. Additionally, little research has been done on the impact of corruption on FDI made by developing country multinationals to developing countries. This paper fills a void in this area.

Based on the published literature, as well as China and Africa contexts, the authors develop hypotheses that host countries with low corruption receive more FDI and resource-seeking investments weaken the relationship. The annual stock of Chinese FDI in 35 African countries, host country corruption data and other control variables from 2007 to 2015 are collected. Feasible generalized least squares models are used to test the hypotheses. Additional robustness tests are also conducted.

The findings support the hypotheses. Specifically, Chinese investors make more investments in host countries with low corruption except for resource-seeking investments in resource-rich host counties. The results are statistically significant accounting for various control variables. The results of the robustness tests show that the main findings are robust.

First, this study provides new evidence on the impact of corruption on FDI. Second, this study also fills a void by examining FDI from a developing country, China to other developing countries in Africa. Finally, this study also has a practical implication for Chinese multinationals investing in Africa.

The paper aims to present a new thought for design of a thrown robot based on flexible structures. The aim of the design is to reduce the weight and improve the anti-impact capability for mini thrown robot.

A mass-spring wheeled robot model is proposed and an impact analysis is given in this paper. Some principia were derived for configuration design and material choice to get a light and robust thrown reconnaissance robot. Based on the theoretical analysis, flexible elements like flexure hinges or rubber shell were utilized to build two generation of robots that both showed excellent performances of anti-impact ability.

A second-generation thrown robot (2,050 g) was developed, which could survive dropping from the height of 6 m more than 10 times without apparent damage.

The method based on the flexible structure provides the thrown robot with high survivability from impact, as well as light weight. It can be used in the design of the mini thrown reconnaissance robot at low cost.

The purpose of this study is to optimize the operational efficiency of the entire system by developing a reasonable maintenance strategy for wind turbines that improves component reliability and safety while reducing maintenance costs.

A hybrid incomplete preventive maintenance (PM) model based on boundary intensity process is established to give dynamic PM intervals for wind turbines using an iterative method with reliability as a constraint; the selection method of PM and replacement is given based on the cost-effectiveness ratio, which in turn determines the optimal number of PM for wind turbines.

The reliability is used to obtain the components’ maintenance cycle, and the cost-effectiveness ratio is used to select the number of maintenance times, thus, getting the optimal maintenance strategy. The validity of this paper’s method is verified by arithmetic cases, which provides a new method for formulating a reasonable PM strategy for wind turbines.

The wind turbine preventive maintenance strategy for Boundary intensity process proposed in this paper can scientifically formulate the maintenance strategy, optimize the cost-effectiveness per unit of time of the wind power generation system, and solve the problems of difficulty in formulating a reasonable maintenance strategy for the wind turbine components and high operation and maintenance costs.

In this paper, the authors describe the failure pattern by a Boundary intensity process, establish a hybrid incomplete PM model by introducing a failure intensity increment factor and an age reduction factor and establish a maintenance strategy optimization model with comprehensive consideration of reliability and cost-effectiveness ratio. Finally, the validity of the model in this paper is verified by arithmetic case analysis.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0153/

In order to improve the computation efficiency of the four-point rainflow algorithm, a new fast four-point rainflow cycle counting algorithm (FFRA) using a novel loop iteration mode is proposed.

In this new algorithm, the loop iteration mode is simplified by reducing the number of iterations, tests and deletions. The high efficiency of the new algorithm makes it a preferable candidate in fatigue life online estimation of structural health monitoring systems.

The extensive simulation results show that the extracted cycles by the new FFRA are the same as those by the four-point rainflow cycle counting algorithm (FRA) and the three-point rainflow cycle counting algorithm (TRA). Especially, the simulation results indicate that the computation efficiency of the FFRA has improved an average of 12.4 times compared to the FRA and an average of 8.9 times compared to the TRA. Moreover, the equivalence of cycle extraction results between the FFRA and the FRA is proved mathematically by utilizing some fundamental properties of the rainflow algorithm. Theoretical proof of the efficiency improvement of the FFRA in comparison to the FRA is also given.

This merit makes the FFRA preferable in online monitoring systems of structures where fatigue life estimation needs to be accomplished online based on massive measured data. It is noticeable that the high efficiency of the FFRA attributed to the simple loop iteration, which provides beneficial guidance to improve the efficiency of existing algorithms.