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This work aims to evaluate the influence of rheological properties of building materials on the bonding quality and ultimate tensile strength in the fused deposition modeling (FDM) process, through the investigation of parts printed by semi-crystalline and amorphous resins. Little information is currently available about the influence of the crystalline nature on FDM-printed part quality.

Semi-crystalline polyamide 12 and amorphous acrylonitrile butadiene styrene (ABS) were used to assess the influence of rheological properties on bonding quality and the tensile strength, by varying three important process parameters: materials, liquefier temperature and raster orientation. A fractography of both tensile and freeze-fractured samples was also investigated.

The rheological properties, mainly the melt viscosity, were found to have a significant influence on the bonding quality of fused filaments. Better bonding quality and higher tensile strength of FDM parts printed with semi-crystalline PA12, as compared with amorphous ABS, are suggested to be a result of higher initial sintering rates owing to the lower melt viscosity of PA12 at low shear rates. Near-full dense PA12 parts were obtained by FDM.

This project provides a variety of data and insight regarding the effect of materials properties on the mechanical performance of FDM-printed parts. The results showed that FDM technique allows the production of PA12 parts with adequate mechanical performance, overcoming the greatest limitation of a dependence on amorphous thermoplastics as a feedstock for the production of prototypes.

The purpose of this paper is to study and report the effects of silver (Ag) content, glass phase particle size and Ag/antimony-doped tin oxide (ATO) particle size on the properties of ATO thick film resistor pastes, especially on the microstructure, square resistance, temperature coefficient of resistance (TCR), resistance temperature curve and other properties of the pastes.

Thick film resistor pastes with different Ag content, glass phase particle size and ATO particle size were printed on stainless steel substrates by screen printing technology, and a series of Ag/ATO thick film resistors (TFRs) were obtained after high-temperature sintering. The electrical properties of TFRs were evaluated. The microstructure development, square resistance, TCR and other properties of the developed TFRs were evaluated with the change in Ag content and the particle size.

The results show that with the increase of Ag content, the square resistance of the pastes decreases and the TCR increases. The change rate of resistance after resintering is less than 4%, and the pastes show excellent antiaging properties. Meanwhile, with the increase of the particle size of the glass phase, the square resistance decreases first and then increases, and the TCR increases first and then decreases, which has little effect on the conductive behavior. The increase in ATO particle size leads to an increase in the square resistance of TFRs and a decrease in the TCR.

This paper provides a useful evaluation of the square resistance, TCR and other properties of Ag/ATO thick film resistor pastes, which are related to the Ag content, glass phase particle size and ATO particle size of the developed TFRs. The thick film resistor pastes with zero TCR can be obtained using Ag/ATO as the functional phase without Pd or Pt.

Considering that a meet between high-speed trains can generate aerodynamic loads, this study aims to investigate the effect of high-speed train meet on wheel wear at different speeds to provide a more accurate wheel wear model and a new idea for reducing wheel wear.

The train speed was set at 250, 300, 350 and 400 km/h separately, and a vehicle system dynamics model was constructed using the parameters of an actual high-speed train on a line. The aerodynamic forces arising from constant-speed train meet were then applied as additional excitation. Semi-Hertzian theory and Kalker’s simplified theory were used to solve the wheel/rail contact problems. The wheel wear was calculated using Archard wear model. The effect of train meet on wheel wear was analyzed for the whole train, different cars and different axles.

According to the results, all wheels show a wear increase in the case of one train meet, compared to the case of no train meet. At 250, 300, 350 and 400 km/h, the total wheel wear increases by 4.45%, 4.91%, 7.57% and 5.71%, respectively, over the entire operational period. The change in speed has a greater impact on wheel wear increase in the head and tail cars than in the middle car. Moreover, the average wear increase in front-axle wheels is 1.04–2.09 times that in rear-axle wheels on the same bogie.

The results will help to analyze wheel wear more accurately and provide theoretical guidance for wheel repair and maintenance from the perspective of high-speed train meet.

At present, there is a lot of focus on the impact of high-speed train meet on the dynamic performance of vehicles. However, little research is available on the influence of train meet on wheel wear. In this study, a vehicle dynamics model was constructed and the aerodynamic forces generated during high-speed train meet were applied as additional excitation. The effect of train meet on wheel wear was analyzed for the whole train, different cars and different axles. The proposed method can provide a more accurate basis for wear prediction and wheel repair.

The CL60 steel wheels of subway vehicles operating on specific lines require frequent refurbishment due to rapid wear and tear. Considering this issue, MoS₂-based and graphite-based solid lubricants are used to reduce the wear rate of subway wheels and extend their service life.

Under laboratory conditions, the effect of MoS₂-based and graphite-based solid lubricants on the friction and wear performance of subway wheels and rails was evaluated using a modified GPM-60 wear testing machine.

Under laboratory conditions, MoS₂-based solid lubricants have the best effect in reducing wheel/rail wear, compared to the control group without lubrication, at 2 × 105 revolutions, the total wheel-rail wear decreased by 95.07%. However, when three types of solid lubricants are used separately, the hardness evolution of the wheel-rail contact surface exhibits different characteristics.

The research results provide important support for improving the lifespan of wheel and rail, extending the service cycle of wheel and rail, reducing the operating costs of subway systems, improving the safety of subway systems and providing wear reduction maintenance for other high wear mechanical components.

The experiment was conducted through the design and modification of a GPM-60 testing machine for wear testing. The experiment simulated the wheel-rail contact situation under actual subway operation and evaluated the effects of three different solid lubricants, MoS₂-based and graphite-based, on the wear performance and surface hardening evolution of subway wheel-rail.

The CL60 steel wheels of metro vehicles running on a specific line need frequent reprofiling due to rapid wear. Considering this problem, a new material for metro wheels was designed. The friction and wear properties of the new material were studied, to reduce the wear rate and extend the service life of metro wheels.

Wheel specimens made of the two steel materials were tested using a GPM-60 wear tester under laboratory conditions. A field test was conducted on a specific metro line to track the wear in wheels made of the new material and CL60 steel wheels.

Under the laboratory conditions, the wear loss in the new material was 24.44% lower than that in CL60 steel. The field test revealed that compared to CL60 steel wheels, the new CL60 steel wheels showed a 19.42% decrease in tread wear on average. The field measurements for the wheels made of the new material are consistent with the results of laboratory simulation, suggesting relatively high wear resistance of the new material.

The results of the study can provide guidance on how to properly select steel material for metro wheels to avoid rapid wear and frequent reprofiling and reduce operating costs.

A new material for metro wheels was designed and developed by optimizing the content of Cr, Si, Mn, V and other elements. This material proved to have better wear resistance in both laboratory and field testing.

Metro wheels running on different lines can undergo wear at different positions. This paper aims to investigate the effects of wheel wear at two typical positions, i.e. wheel flange and tread, on the dynamic performance of metro vehicles and analyzes the differences, with an aim of providing theoretical support on wheel reprofiling for different metro lines.

Wheel profile data were measured on two actual metro lines, denoted A and B. It was observed that wheel wear on Lines A and B was concentrated on flanges and treads, respectively. A metro vehicle dynamics model was built using multibody dynamics software SIMPACK. Then it was applied to analyze the differences in effects of wheel wear at different positions on vehicle dynamic performance (VDP) for various speeds (50, 60 and 70 km/h) and line conditions (straight line, R1000m, R600m and R300m curves). Critical speed and vibration acceleration were used as indicators of VDP during linear motion (on straight track), while VDP during curvilinear motion (on curved track) was evaluated in terms of wheel/rail lateral force, wheel/rail vertical force, derailment coefficient and wheel unloading rate.

First, compared to wheel profile with tread wear, wheel profile with flange wear showed better performance during linear motion. When the distance traveled reached 8 × 104 and 14 × 104 km, the vehicle’s critical speed was 12.2 and 21.6% higher, respectively. The corresponding vertical and lateral vibration accelerations were 59.7 and 74.8% lower. Second, compared to wheel profile with flange wear, that with tread wear showed better performance during curvilinear motion, with smaller wheel/rail lateral force, derailment coefficient and wheel unloading rate. When the vehicle speed was 50, 60 and 70 km/h, the maximum difference in the three indicators between the two wheel profiles was 40.2, 44.7 and 23.1%, respectively. For R1000m, R600m and R300m curves, the corresponding maximum difference was 45.7, 69.0 and 44.4%, respectively.

The results of the study can provide a guidance and theoretical support on wheel reprofiling for different metro lines. On lines with large proportions of curved sections, metro vehicles are more prone to wheel flange wear and have poorer dynamic performance during curvilinear motion. Therefore, more attention should be paid to flange lubrication and maintenance for such lines. On lines with higher proportions of straight sections, metro vehicles are more prone to tread wear and have poorer performance on straight sections. So, tread maintenance and service requires more attention for such lines.

Existing research has focused primarily on the effects of wheel wear on VDP, but fails to consider the differences in the effects of wheel wear at different positions on VDP. In actual metro operation, the position of wheel wear can vary significantly between lines. Based on measured positions of wheel wear, this paper examines the differences in the effects of wheel wear at two typical positions, i.e. tread and flange, on VDP in detail.

Purpose: This chapter aims to examine machine learning (ML) models for predicting credit card fraud (CCF).

Need for the study: With the advance of technology, the world is increasingly relying on credit cards rather than cash in daily life. This creates a slew of new opportunities for fraudulent individuals to abuse these cards. As of December 2020, global card losses reached $28.65billion, up 2.9% from $27.85 billion in 2018, according to the Nilson 2019 research. To safeguard the safety of credit card users, the credit card issuer should include a service that protects customers from potential risks. CCF has become a severe threat as internet buying has grown. To this goal, various studies in the field of automatic and real-time fraud detection are required. Due to their advantageous properties, the most recent ones employ a variety of ML algorithms and techniques to construct a well-fitting model to detect fraudulent transactions. When it comes to recognising credit card risk is huge and high-dimensional data, feature selection (FS) is critical for improving classification accuracy and fraud detection.

Methodology/design/approach: The objectives of this chapter are to construct a new model for credit card fraud detection (CCFD) based on principal component analysis (PCA) for FS and using supervised ML techniques such as K-nearest neighbour (KNN), ridge classifier, gradient boosting, quadratic discriminant analysis, AdaBoost, and random forest for classification of fraudulent and legitimate transactions. When compared to earlier experiments, the suggested approach demonstrates a high capacity for detecting fraudulent transactions. To be more precise, our model’s resilience is constructed by integrating the power of PCA for determining the most useful predictive features. The experimental analysis was performed on German credit card and Taiwan credit card data sets.

Findings: The experimental findings revealed that the KNN achieved an accuracy of 96.29%, recall of 100%, and precision of 96.29%, which is the best performing model on the German data set. While the ridge classifier was the best performing model on Taiwan Credit data with an accuracy of 81.75%, recall of 34.89, and precision of 66.61%.

Practical implications: The poor performance of the models on the Taiwan data revealed that it is an imbalanced credit card data set. The comparison of our proposed models with state-of-the-art credit card ML models showed that our results were competitive.

The impact of specific investments to performance has mixed arguments. This paper aims to clarify how and under what conditions specific investments made by manufacturer tailored to supplier affect the new product development (NPD) performance of the manufacturer itself.

This study develops a moderated mediation model, testing the roles of supplier involvement and information technology (IT) implementation by regression and bootstrap analyses from 378 NPD projects.

The results show both physical and human specific investments positively affect NPD performance. IT implementation strengthens the mediated role of supplier involvement, i.e. the mediator role of supplier involvement between specific investments and NPD performance link is significantly weaker while IT implementation is lower.

The findings contribute to identify IT implementation and supplier involvement as two important constructs, together demonstrating how and when specific investments affect NPD performance.

China was the only developing country that participated in the human genome project and contributed 1 per cent of human genome sequencing in 2000. And it finished rice genome sequencing independently in 2002. China’s biomedical industry, however, remains largely an academic affair. The industry is characterized by its inability to support and commercialize innovative research, which in turn has resulted in the prevalence of generic drugs. Managers of Chinese firms have been focusing on the shortterm profits that can be generated by generics rather than the longer‐term potential profits arising from innovative research. But the viability of such short‐cut strategy is now called into question as the IPR infringements will mean hefty fines to the violators in the wake of China’s WTO accession. There is hence an urgent need to make the timely transformation from academic affair to commercialization. This paper examines the reasons why biomedical industry remains largely an academic affair in China by stacking China against the key success factors of biomedical industry in the world. It then suggests the ways to make the transformation by filling the gap between basic research and commercial products and cultivating the necessary business environment for biomedical drugs in China.

The rapid development of information technology, epitomized by AIGC and the metaverse, presents unprecedented challenges to techno-ethics, exposing society to significant risks and uncertainties. A systematic investigation and discussion of the construction of techno-ethical order become crucial under the paradigm of risk society theory. The selection of conditions and pathways for constructing a techno-ethical order under the risk society theory paradigm becomes an unavoidable and vital issue.

Drawing on risk society theory, this study employs scientometrics and qualitative comparative analysis (QCA) to empirically analyze the key factors and conditional pathways in the construction of techno-ethical order. Initially, a quantitative analysis is conducted on 1,490 thematic literature retrieved from CNKI and WoS to identify the hot topics and core concepts in techno-ethical research. Subsequently, QCA configuration analysis is applied to calculate eight evaluation indicators and their weights from the perspectives of government, society and individuals. Finally, the study explores the mechanisms of the impact of these indicators’ weights on the construction of techno-ethical order.

The analysis of factor weights and pathways indicates that the selection of pathways for constructing techno-ethical order is influenced both by the inherent development patterns of technology and societal systems and cultural values. Literature metrics analysis reveals an overall trend of sustained growth in techno-ethical research, indicating an unprecedented prosperity in this field. Alongside technological advancements, keywords related to “artificial intelligence” play a crucial role in current techno-ethical research. Configuration analysis demonstrates that conditional variables from the dimensions of government, society and individuals form a configuration pathway, influencing and synergistically impacting the overall level of techno-ethical order construction. Attention should be given to the mutual constraints and synergistic effects of factors related to technological development, societal systems and cultural values.

This study, grounded in the risk society theory paradigm, quantitatively explores the key factors and pathways of techno-ethical order construction in academic texts, expanding new perspectives, providing novel insights, establishing innovative methodologies and extending new boundaries in the field. Further enrichment of the dataset and in-depth discussions are warranted for continued advancement.