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Based on the theoretical viewpoints of criminal geography and environmental criminology, this research uses spatial multi-criteria decision-making methods. In the process of spatial decision-making and optimization of police resources, researchers fully consider the dynamic application of Geographic Information System (GIS) and the effects of spatial prevention and control.

Researchers use an integrated method combining Policing Geographic Information System (PGIS) and multi-criteria decision analysis (MCDA). On the one hand, police GIS has an excellent visual data analysis platform and integrated decision support system in data management, spatial analysis, data exploration and regression analysis. On the other hand, through the design of the indicator system, the quantification of indicators, the determination of weights, comprehensive evaluation and sensitivity analysis, MCDA can select the best plan from a large number of alternatives. When joining MCDA, the spatial dimension will bring the research results closer to the real world.

The study finds that the crime of burglary is affected to a certain extent by the distribution of police forces, the location of police units. Another important finding of this research is the correlation between more precise preventive measures and the crime of burglary.

From a practical point of view, this research would help advance the role of police units and law enforcement agencies in preventing burglary crimes and provide experience for the allocation of regional police resources.

Quality failures in grid infrastructure construction would cause large-scale collapses in power supply and additional expenditures by reworks and repairs. Learning from quality failures (LFQF) extracts experience from previous quality events and converts them into preventive measures to reduce or eliminate future construction quality issues. This study aims to investigate the influence factors of LFQF in the construction of grid infrastructure.

The related factors of LFQF, including quality management (QM) practices, quality rectification, and individual learning, were identified by reviewing literature about organizational learning and extracting experience from previous failures. A questionnaire survey was distributed to the grid companies in North, Northeast, Northwest, East, Central, and Southwest China. 381 valid responses collected and analyzed using structural equation modeling (SEM) to test the influence of these factors on LFQF.

The SEM results support that QM practices positively affect individual learning and LFQF. Quality rectification indirectly impacts LFQF via individual learning, while the results did not support the direct link between quality rectification and LFQF.

The findings strengthen practical insights into extracting experience from poor-quality issues and continuous improvement. The contributory factors of LFQF found in this study benefit the practitioners by taking effective measures to enhance organizational learning capability and improve the long-term construction quality performance in the grid infrastructure industry.

Existing research about the application of LFQF still stays at the explorative and conceptual stage. This study investigates the related factors of LFQF, including QM practices, quality rectification, and individual learning, extending the model development of learning from failures (LFF) in construction QM.

This paper aims to guide the implementation of noise reduction measures in hoistway and reduce the aerodynamic noise generated by elevator operation, this paper aims to propose an aerodynamic noise analysis method that can solve the flow field in hoistway.

A turbulence-acoustic model solving the flow field in a hoistway and a numerical wind hoistway model of the ultra-high-speed elevator were established by using large eddy simulation (LES) and Curle acoustic theory.

The characteristics of pulsating flow field and aerodynamic noise around ultra-high-speed elevator are analyzed. The asymmetric characteristics of the flow field could be observed using the turbulent kinetic energy and the instantaneous vortexes in the wind hoistway model. Vortex shedding, air flow separation and recombination around the car were the key factors for aerodynamic noise generation. The sound pressure level was approximately linear to the logarithm of car speed. The increase of car deflection angle in a certain range would reduce the peak frequency of wake noise and increase the sound pressure level (SPL) value.

This paper provides important guidance for researches studying the aerodynamic noise in the hoistway and the technical personnel that look for the reduction measures, which greatly improves the shortcomings in the numerical simulation of the aerodynamic noise of the hoistway.

This study aims to using Fourier transform infrared (FTIR) spectroscopy, Raman spectroscopy and scanning electron microscope/energy dispersive Xray spectrometer to identify different automotive coatings for forensic purpose.

Two four-layered samples in a hit-and-run case were compared layer by layer with three different methods. FTIR spectroscopy was used to primarily identify the organic and inorganic compositions. Raman spectrum and scanning electron microscope/energy dispersive Xray spectrometer (SEM-EDS) were further used to complement the FTIR results.

Two weak and tiny peaks in one layer found between two samples by FTIR, Raman microscope and SEM-EDS verified the result of differences. The study used the three instruments in combination and found it’s effective in sensing coatings, especially in the inorganic additives.

Using these three instruments in combination is more accurate than individually in multilayered coating analysis for forensic purpose.

The three different instruments all present unique information on the composition, and provided similar and mutually verifiable results on the two samples.

With this method, scientists could identify and discriminate important coating evidences with tiny but characteristic differences.

Drawing upon strengths-based inclusive work theory, this study explores how strengths-based leadership promotes employee career sustainability, particularly in the absence of protean career orientation (PCO), with career adaptability as a mediator.

A three-wave survey of 329 Chinese employees tested the moderated mediation model. Hypotheses were assessed using SPSS 26.0 and Mplus 8.3.

Strengths-based leadership positively influences career adaptability, leading to greater career sustainability. The effect is stronger when PCO is low, highlighting the compensatory role of strengths-based leadership.

The present paper extends the existing literature on strengths-based leadership and unveils that strength-based leadership can compensate for a lack of PCO. Also, it augments strengths-based inclusive work theory and provides meaningful insights to cultivate employee career sustainability.

The cross-sectional design and self-reported data limit causal conclusions. Future research should use longitudinal methods and diverse cultural contexts to improve generalizability.

As an increasingly important variable in the career field, career sustainability has received particular attention, yet few empirical studies have been conducted to examine its antecedents. The authors propose a moderated mediation model based on the goal-setting theory and the wise proactivity perspective for exploring when and how self-goal setting can influence career sustainability.

The authors use a time-lagged design and collect three waves of data from 1,260 teachers in basic education schools in China. The authors test the proposed hypotheses with SPSS 26.0 and Mplus 8.3.

The results show that self-goal setting positively relates to career sustainability and that career crafting plays a mediating role in this relationship. This relationship is strengthened when perceived organizational goal clarity is high.

The authors extend the application scenarios of the goal-setting theory to the field of career research and find out that self-goal setting is also a self-initiated and wise antecedent of career sustainability. From a wise proactivity perspective, the authors examine the mediating mechanism of career crafting to make positive career outcomes. Furthermore, the authors consider the impact of perceived organizational goal clarity as a boundary condition and broaden the understanding of “when to wise proactivity” from the goal-setting theory.

This study aims to investigate the predictive role of team personality composition in facilitating shared leadership through team member exchange (TMX), while also to examine the moderating effect of organizational culture.

The authors conducted a two-stage online survey and selected the customer service teams, claims teams and financial teams of 26 Chinese insurance companies as the research samples. The authors finally obtained validated questionnaires from 107 teams with 457 members. The hypothesized relationships were tested using SPSS 25.0 and Mplus.

The results indicate that both team relationship-oriented and task-oriented personality composition have significant positive effects on shared leadership with team-member exchange serving as a full mediator for both paths. As a boundary condition, organizational culture (i.e. including internal integration values and external adaptation values) has a moderating effect on the influence of TMX on shared leadership.

The study investigates the predictive role of team personality composition on shared leadership, which complements the empirical studies of shared leadership antecedents in the literature. Drawing on social exchange perspective, the authors find out that TMX serves as a mediator between team personality composition and shared leadership. The authors also identify the moderating effect of organizational culture on the emergence of shared leadership. The research emphasizes the contextual boundary condition in this process.

The differential magnetic gradient tensor system is usually constructed from the three-axis magnetic sensor array. While the effects of measurement error, sensor performance and baseline distance on localization performance of such systems have been widely reported, the research about the effect of spatial design of sensor array is less presented. This paper aims to provide a spatial design method of sensor array and corresponding optimization strategy to localization based on magnetic tensor gradient to get the optimum design of the sensor array. Based on the results of simulation, magnetic localization systems constructed from the proposed array and the traditional array have been built to carry out a localization experiment. The results of experiment have verified the effectiveness of magnetic localization based on the proposed array.

The authors focus on the localization of the magnetic target based on magnetic gradient by using three-axis magnetic sensor array and combine a design method with corresponding optimization strategy to get the optimum design of the sensor array.

This paper provides an array design and optimization method for magnetic target localization based on magnetic gradient to improve the localization performance.

In this paper, the authors focus on the magnetic localization based on magnetic gradient by using three-axis magnetic sensors and study the effect of the spatial design of sensor array on localization performance.

This paper aims to provide a review of different types of non-wearable human identification sensors which can be applied for smart home environment.

The authors performed a systematic review to assess and compare different types of non-wearable and non-intrusive human identification sensors used in smart home environment. The literature research adds up to 5,567 records from 2000 to 2016, out of which 40 articles were screened and selected for this review.

In this review, the authors classified non-wearable human identification technologies into four main groups, namely, object-based, footstep-based, body shape-based and gait-based identification technologies. Assessing these four group of identification technologies showed that the maturity of non-wearable identification is not high and most of these technologies are verified in a lab environment. Additionally, footstep-based identification is the most popular identification approach listed in the literature.

This study contributes to the literature on human identification technologies in several ways. This paper identifies the state-of-the-art regarding non-wearable technologies which can be used in smart home environment. Moreover, the results of this paper can provide a better understanding of advantages and disadvantages of the non-wearable identification technologies.

To deepen the structural reform of the financial system on the supply side and mitigate associated risks in the economic and financial fields, with significant practical implications for FinTech development.

Based on microdata of listed companies, this paper constructs multi-level indicators of FinTech development. Robustness tests include alternative measures of the degree of long-term use of short-term debts, sample adjustments and heterogeneity in firm characteristics and regional differences.

FinTech can significantly alleviate the long-term use of short-term corporate debt, although there are heterogeneous effects. The alleviation effect is more pronounced for state-owned enterprises, non-technology-intensive enterprises and other companies with lower levels of short-term debt maturity. Additionally, in regions with high capital mismatch and high levels of financial development, FinTech exhibits a significant suppressive effect on the long-term use of short-term corporate debt.

The paper suggests promoting the diversification of FinTech products, emphasizing the importance of inclusive finance through FinTech, and driving China’s economic transformation and high-quality development.

By constructing a theoretical analysis framework of “FinTech—corporate investment and financing term mismatch,” this paper provides a multi-level estimation of the factors influencing FinTech’s impact on the long-term use of short-term corporate debt. This framework aids in developing a more dialectical and objective understanding of the economic effects of FinTech’s development.