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In recent decades, the field of robotic mapping has witnessed widespread research and development in light detection and ranging (LiDAR)-based simultaneous localization and mapping (SLAM) techniques. This paper aims to provide a significant reference for researchers and engineers in robotic mapping.

This paper focused on the research state of LiDAR-based SLAM for robotic mapping as well as a literature survey from the perspective of various LiDAR types and configurations.

This paper conducted a comprehensive literature review of the LiDAR-based SLAM system based on three distinct LiDAR forms and configurations. The authors concluded that multi-robot collaborative mapping and multi-source fusion SLAM systems based on 3D LiDAR with deep learning will be new trends in the future.

To the best of the authors’ knowledge, this is the first thorough survey of robotic mapping from the perspective of various LiDAR types and configurations. It can serve as a theoretical and practical guide for the advancement of academic and industrial robot mapping.

In recent years, the incidence of cardiovascular disease has continued to rise, and early screening and prevention are especially critical. Phonocardiography (PCG) and electrocardiography (ECG), as simple, cost-effective and non-invasive tests, are important tools for clinical analysis. However, it is difficult to fully reflect the complexity of the cardiovascular system using PCG or ECG tests alone. Combining the multimodal signals of PCG and ECG can provide complementary information to improve the detection accuracy. Therefore, the purpose of this paper is to propose a multimodal signal classification method based on continuous wavelet transform and improved ResNet18.

The classification method is based on the ResNet18 backbone, and the ResNet18 network is improved by embedding the global grouped coordinate attention mechanism module and the improved bidirectional feature pyramid network. Firstly, a data acquisition system was built using a MEMS-integrated PCG-ECG sensor to construct a private data set. Second is the time-frequency transformation of PCG and ECG synchronized signals on public and private data sets using continuous wavelet transform. Finally, the time-frequency images are categorized.

The global grouped coordinate attention mechanism and bidirectional feature pyramid network modules proposed in this paper significantly enhance the model’s performance. On public data sets, the method achieves precision, sensitivity, specificity, accuracy and F1 score of 97.96%, 98.51%, 97.58%, 98.08% and 98.23%, respectively, which represent improvements of 3.54%, 3.92%, 4.18%, 4.03% and 3.72% compared to ResNet18. Additionally, it demonstrates a clear advantage over existing mainstream algorithms. On private data sets, the method’s five metrics are 98.15%, 98.76%, 98.08%, 98.42% and 98.45%, further validating the model’s generalization ability.

The method proposed in this paper not only improves the accuracy and efficiency of the test but also provides an effective solution for early screening and prevention of cardiovascular diseases.

The wheel wear of high-speed trains is the main concern in the operation process of the high-speed trains. Wheel reprofile usually adopts the thin flange wheel profiles for the economic wheel reprofile strategy; however, the wheel wear evolution law of the thin flange wheel profile is not clear. The purpose of this paper mainly researches the wheel wear evolution law of thin flange wheel profile and the influence factors of thin flange wheel.

To solve this problem, this paper analyzed the wheel-rail contact relationship and established a vehicle dynamic model of high-speed train. The Jendel wheel wear model was used to analyze the evolution of thin flange wheel wear and rail deviation affecting wheel wear under thin flange wheel profiles.

Due to the consistency of the tread area, the distribution of wheel-rail contact points for thin flange wheels in the tread area is close. As the wheel flange increases, wheel wear also increases. Thin flange wheel profiles reduce wheel wear to a certain extent. The maximum wheel wear depths with rail deviations of −0.4 mm, 0 mm and 0.4 mm are 0.9844 mm, 1.077 mm and 1.142 mm, respectively. The negative rail deviation suppresses wheel wear, but the positive rail deviation increases wheel wear.

The evolution of wheel wear for thin flange wheels after reprofiling is not clear. This paper analyzed the wear characteristics of thin flange wheel wear and rail deviation affecting wheel wear under thin flange wheels.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2024-0401/

This paper aims to examine how the law may play a role in mediation by paying special attention to how the law is excluded from and included in the process of court mediation in China.

Hundred model court mediation cases selected by the Supreme People’s Court of China were analysed and reviewed.

The law is relevant in Chinese-style court mediation in four ways: first, judge-mediators are intended to use mediation to avoid resolving legal difficulties or challenges; second, judge-mediators consult the law to anticipate the losing party and the potential negative effects that might result from the adjudication; third, judge-mediators refer to the law to propose a mediation scheme or plan to guide the parties to settle; and fourth, judge-mediators would use the law as a bargaining chip in various ways to induce the parties to settle.

Standards should be set out for the use of law in the mediation process to standardise judge-mediators’ actions, to ensure that the law is not used coercively to push settlement, which would undermine the parties’ self-determination in mediation.

This paper provides an original understanding of how law affects the process, the outcomes and, ultimately, the nature of settlements that parties achieve through court mediation in China. This study contributes to the literature that argues that ethical norms and legal standards should be set to direct those legal evaluations.

This paper aims to investigate the preparation of AlN and Al₂O₃, as well as the effect of nano-AlN and nano-Al₂O₃, on friction and wear properties of copper-steel clad plate immersed in the lubricants.

Nano-AlN or nano-Al₂O₃ (0.1, 0.2, 0.3, 0.4 and 0.5 Wt.%) functional fluids were prepared. Their tribological properties were tested by an MRS-10A four-ball friction tester and a ball-on-plate configuration, and scanning electron microscope observed the worn surface of the plate.

An increase in nano-AlN and Al₂O₃ content enhances the extreme pressure and anti-wear performance of the lubricant. The best performance is achieved at 0.5 Wt.% of nano-AlN and 0.3 Wt.% of nano-Al₂O₃ with PB of 834 N and 883 N, a coefficient of friction (COF) of approximately 0.07 and 0.06, respectively. Furthermore, the inclusion of nano-AlN and nano-Al₂O₃ particles in the lubricant enhances its extreme pressure performance and reduces wear, leading to decreased wear spot depth. The lubricating effect of the nano-Al₂O₃ lubricant on the surface of the copper-steel composite plate is slightly superior to that of the nano-AlN lubricant, with a COF reaching 0.07. Both lubricants effectively fill and lubricate the holes on the surface of the copper-steel composite plate.

AlN and Al₂O₃ as water-based lubricants have excellent lubrication performance and can reduce the COF. It can provide some reference for the practical application of nano-water-based lubricants.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2023-0255/