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The purpose of this paper is to study the wear evolution of metro wheels under the conditions of different track sequences, track composition and vehicle load and then to predict wheel wear and to guide its maintenance.

By using the SIMPACK and MATLAB software, numerical simulation analysis of metro wheel wear is carried out based on Hertz theory, the FASTSIM algorithm and the Archard model. First of all, the vehicle dynamics model is established to calculate the motion relationship and external forces of wheel-rail in the SIMPACK software. Then, the normal force of wheel-rail is solved based on Hertz theory, and the tangential force of wheel-rail is calculated based on the FASTSIM algorithm through the MATLAB software. Next, in the MATLAB software, the wheel wear is calculated based on the Archard model, and a new wheel profile is obtained. Finally, the new wheel profile is re-input into the vehicle system dynamics model in the SIMPACK software to carry out cyclic calculation of wear.

The results show that the setting order of different curves has an obvious influence on wear when the proportion of the straight track and the curve is fixed. With the increase in running mileage, the severe wear zone is shifted from tread to flange root under the condition of the sequence-type track, but the wheel wear distribution is basically stable for the unit-type track, and their wear growth rates become closer. In the tracks with different straight-curved ratio, the more proportion the curved tracks occupy, the closer the severe wear zone is shifted to flange root. At the same time, an increase in weight of the vehicle load will aggravate the wheel wear, but it will not change the distribution of wheel wear. Compared with the measured data of one city B type metro in China, the numerical simulation results of wheel wear are nearly the same with the measured data.

These results will be helpful for metro tracks planning and can predict the trend of wheel wear, which has significant importance for the vehicle to do the repair operation. At the same time, the security risks of the vehicle are decreased economically and effectively.

At present, many scholars have studied the influence of metro tracks on wheel wear, but mainly focused on a straight line or a certain radius curve and neglected the influence of track sequence and track composition. This study is the first to examine the influence of track sequence on metro wheel wear by comparing the sequence-type track and unit-type track. The results show that the track sequence has a great influence on the wear distribution. At the same time, the influence of track composition on wheel wear is studied by comparing different straight-curve ratio tracks; therefore, wheel wear can be predicted integrally under different track conditions.

When Russia invaded Ukraine on February 24, 2022, Ukrainian President Volodymyr Zelenskyy confronted the aggressors on the military front while galvanising Ukrainians and fighting a parallel war on the information battlefield. This study examines Zelenskyy’s communication strategy in the first 100 days of the conflict and his use of mainstream media to share the Ukrainian story globally. It also aims to provide an opportunity in modern history to explore communication led by a head of state.

This case study focuses on Zelenskyy’s external communication with the global mainstream media and evaluates his 77 official speeches and interview transcripts within the first 100 days. Using the inductive categorisation approach (Berg, 2009), a comprehensive dataset analysis was made to distill the different message types, media platforms used, target audiences and any embedded rhetorical elements. These were evaluated using the stakeholder theory (Freeman, 2002), mediating the media model (Pang, 2010) and information vacuum (Pang, 2013; Woon and Pang, 2017) as the study’s theoretical lens.

Zelenskyy focused on four key audience groups in the first 100 days of the conflict and scaffolded his audience engagement at different points in time. He tailored his rhetoric specifically to the country of his audiences and dominated the information space by using first-person accounts to connect with audiences, ensuring disinformation and alternate narratives were debunked. His use of “direct video press release” enabled mainstream media globally to report him as they were a ready form of information subsidy.

This study contributed to understanding Zelenskyy’s efforts in identifying targeted audiences and his curated communication strategy. Zelenskyy understood the prevailing contexts of his messages, saturated the information space on multiple platforms and sought to eliminate countervailing narratives, particularly from Russia, from forming in the information vacuum (Pang, 2013). As this study was focused on how he leveraged mainstream media, future studies could examine how he leveraged social media that were harnessed in communication. Zelenskyy’s verbal and non-verbal cues could also be examined to understand how this may influence stakeholder perceptions.

The study found practical lessons to show how Zelenskyy engaged with different audiences who could directly and indirectly influence Ukraine’s defence against Russian aggression and aligned his communication with his national strategic objectives even as the conflict unfolded. These can serve as a foundational framework for national leaders navigating crises in today’s information landscape and provide valuable insights into effective leadership and crisis communication.

Few studies have examined how a leader communicates in times of crises, specifically one of such scale with international involvement. This study is a nascent attempt to do so, with the hope that it would provide critical insights into effective media communication and lay the groundwork for future research in this evolving field.

AlSi10Mg alloy is commonly used in laser powder bed fusion due to its printability, relatively high thermal conductivity, low density and good mechanical properties. However, the thermal conductivity of as-built materials as a function of processing (energy density, laser power, laser scanning speed, support structure) and build orientation, are not well explored in the literature. This study aims to elucidate the relationship between processing, microstructure, and thermal conductivity.

The thermal conductivity of laser powder bed fusion (L-PBF) AlSi10Mg samples are investigated by the flash diffusivity and frequency domain thermoreflectance (FDTR) techniques. Thermal conductivities are linked to the microstructure of L-PBF AlSi10Mg, which changes with processing conditions. The through-plane exceeded the in-plane thermal conductivity for all energy densities. A co-located thermal conductivity map by frequency domain thermoreflectance (FDTR) and crystallographic grain orientation map by electron backscattered diffraction (EBSD) was used to investigate the effect of microstructure on thermal conductivity.

The highest through-plane thermal conductivity (136 ± 2 W/m-K) was achieved at 59 J/mm³ and exceeded the values reported previously. The in-plane thermal conductivity peaked at 117 ± 2 W/m-K at 50 J/mm³. The trend of thermal conductivity reducing with energy density at similar porosity was primarily due to the reduced grain size producing more Al-Si interfaces that pose thermal resistance. At these interfaces, thermal energy must convert from electrons in the aluminum to phonons in the silicon. The co-located thermal conductivity and crystallographic grain orientation maps confirmed that larger colonies of columnar grains have higher thermal conductivity compared to smaller columnar grains.

The thermal properties of AlSi10Mg are crucial to heat transfer applications including additively manufactured heatsinks, cold plates, vapor chambers, heat pipes, enclosures and heat exchangers. Additionally, thermal-based nondestructive testing methods require these properties for applications such as defect detection and simulation of L-PBF processes. Industrial standards for L-PBF processes and components can use the data for thermal applications.

To the best of the authors’ knowledge, this paper is the first to make coupled thermal conductivity maps that were matched to microstructure for L-PBF AlSi10Mg aluminum alloy. This was achieved by a unique in-house thermal conductivity mapping setup and relating the data to local SEM EBSD maps. This provides the first conclusive proof that larger grain sizes can achieve higher thermal conductivity for this processing method and material system. This study also shows that control of the solidification can result in higher thermal conductivity. It was also the first to find that the build substrate (with or without support) has a large effect on thermal conductivity.

The purpose of this paper is to investigate the dependence of dark current on threading dislocations (TDs) in relaxed Ge layer for Ge/Si heterojunction photodetectors.

The analysis of the effects of TDs is based on SRH generation and recombination mechanism used in two‐dimensional drift‐diffusion numerical simulation.

It is found that the TDs in Ge layer acting as the recombination centers lead to large dark current densities of devices, and the recombination rate is affected by the impurity out‐diffusion from Si substrate. Besides, the TDs, being the acceptor‐like defects simultaneously, form band barrier at Si/Ge interface with lightly doped Si substrates, thus limiting the minority carrier transport and resulting in low dark current densities.

The simulation results are excellently consistent with the experimental data and indicate that the reduction of threading dislocation densities (TDDs), especially in Ge buffer layer, dramatically decreases dark currents densities of Ge/Si photodetectors. The investigation can be applied to imbue devices with desired characteristics.

The quality and quantity of data are vital for the effectiveness of problem solving. Nowadays, big data analytics, which require managing an immense amount of data rapidly, has attracted more and more attention. It is a new research area in the field of information processing techniques. It faces the big challenges and difficulties of a large amount of data, high dimensionality, and dynamical change of data. However, such issues might be addressed with the help from other research fields, e.g., swarm intelligence (SI), which is a collection of nature-inspired searching techniques. The paper aims to discuss these issues.

In this paper, the potential application of SI in big data analytics is analyzed. The correspondence and association between big data analytics and SI techniques are discussed. As an example of the application of the SI algorithms in the big data processing, a commodity routing system in a port in China is introduced. Another example is the economic load dispatch problem in the planning of a modern power system.

The characteristics of big data include volume, variety, velocity, veracity, and value. In the SI algorithms, these features can be, respectively, represented as large scale, high dimensions, dynamical, noise/surrogates, and fitness/objective problems, which have been effectively solved.

In current research, the example problem of the port is formulated but not solved yet given the ongoing nature of the project. The example could be understood as advanced IT or data processing technology, however, its underlying mechanism could be the SI algorithms. This paper is the first step in the research to utilize the SI algorithm to a big data analytics problem. The future research will compare the performance of the method and fit it in a dynamic real system.

Based on the combination of SI and data mining techniques, the authors can have a better understanding of the big data analytics problems, and design more effective algorithms to solve real-world big data analytical problems.

This study was inspired by research of strategists on strategic innovation (SI), aiming to provide a unique model to enhance the digitization of small and medium-sized enterprises (SMEs) in Bangladesh to fill the gap toward a digital economy.

A survey was used to collect data from 180 SMEs in the manufacturing industry for this research. The results indicate that strategic innovativeness (SI), human capital (HC), infrastructure and technology and resistance to change significantly influence the digitalization in Bangladesh SMEs.

The link between SI and SMEs' digitalization in Bangladesh is mediated by HC. The results show that HC plays a big role in the connection between SI and the digitalization of SMEs. This study may be valuable for SMEs managers, researchers and policymakers in Bangladesh and other developing nations, who want to learn more about SI in adopting digitalization.

The specialized knowledge and abilities of strategists allow them to establish parallels between the past and present, enabling them to make a sustained forecast about the digital economy. This study encourages small and medium-sized businesses to develop their SI and advance their HC, which could further deject resistance to change toward enhancing and adopting digitalization in SMEs sectors.

Sets out the US laws that give women protection from discrimination when pregnant. Defines the scope of pregnancy disability and outlines the responsibilities that employers have under the law. Focuses on pregnancy regulations in California, describing the provisions made for pregnancy leave, the medical certification needed, the right to reinstatement, the employer’s right to transfer a pregnant employee, and the pregnant employee’s right to transfer. Sets down the policy developed by UCLA concerning pregnancy discrimination. Briefly outlines the evidence a woman would need to show to win a case of discrimination because of pregnancy.

High-speed turnouts are more complex in structure and thus may cause abnormal vibration of high-speed train car body, affecting driving safety and passenger riding experience. Therefore, it is necessary to analyze the data characteristics of continuous hunting of high-speed trains passing through turnouts and propose a diagnostic method for engineering applications.

First, Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) is performed to determine the first characteristic component of the car body’s lateral acceleration. Then, the Short-Time Fourier Transform (STFT) is performed to calculate the marginal spectra. Finally, the presence of a continuous hunting problem is determined based on the results of the comparison calculations and diagnostic thresholds. To improve computational efficiency, permutation entropy (PE) is used as a fast indicator to identify turnouts with potential problems.

Under continuous hunting conditions, the PE is less than 0.90; the ratio of the maximum peak value of the signal component to the original signal peak value exceeded 0.7, and there is an energy band in the STFT time-frequency map, which corresponds to a frequency distribution range of 1–2 Hz.

The research results have revealed the lateral vibration characteristics of the high-speed train’s car body during continuous hunting when passing through turnouts. On this basis, an effective diagnostic method has been proposed. With a focus on practical engineering applications, a rapid screening index for identifying potential issues has been proposed, significantly enhancing the efficiency of diagnostic processes.

This paper aims to review recent advances and applications of abrasive processes for microelectronics fabrications.

More than 80 patents and journal and conference articles published recently are reviewed. The topics covered are chemical mechanical polishing (CMP) for semiconductor devices, key/additional process conditions for CMP, and polishing and grinding for microelectronics fabrications and fan-out wafer level packages (FOWLPs).

Many reviewed articles reported advanced CMP for semiconductor device fabrications and innovative research studies on CMP slurry and abrasives. The surface finish, sub-surface damage and the strength of wafers are important issues. The defects on wafer surfaces induced by grinding/polishing would affect the stability of diced ultra-thin chips. Fracture strengths of wafers are dependent on the damage structure induced during dicing or grinding. Different thinning processes can reduce or enhance the fracture strength of wafers. In the FOWLP technology, grinding or CMP is conducted at several key steps. Challenges come from back-grinding and the wafer warpage. As the Si chips of the over-molded FOWLPs are very thin, wafer grinding becomes critical. The strength of the FOWLPs is significantly affected by grinding.

This paper attempts to provide an introduction to recent developments and the trends in abrasive processes for microelectronics manufacturing. With the references provided, readers may explore more deeply by reading the original articles. Original suggestions for future research work are also provided.

Turbomachinery, including pumps, are mainly designed to extract/produce energy from/to the flow. A major challenge in the numerical simulation of turbomachinery is the inlet flow rate, which is routinely treated as a known boundary condition for simulation purposes but is properly a dependent output of the solution. As a consequence, the results from numerical simulations may be erroneous due to the incorrect specification of the discharge flow rate. Moreover, the transient behavior of the pumps in their initial states of startup and final states of shutoff phases has not been studied numerically. This paper aims to develop a coupled procedure for calculating the transient inlet flow rate as a part of the solution via application of the control volume method for linear momentum. Large eddy simulation of a four-blade axial hydraulic pump is carried out to calculate the forces at every time step. The sharp interface immersed boundary method is used to resolve the flow around the complex geometry of the propeller, stator and the pipe casing. The effect of the spurious pressure fluctuations, inherent in the sharp interface immersed boundary method, is damped by local time-averaging of the forces. The developed code is validated by comparing the steady-state volumetric flow rate with the experimental data provided by the pump manufacturer. The instantaneous and time-averaged flow fields are also studied to reveal the flow pattern and turbulence characteristics in the pump flow field.

The authors use control volume analysis for linear momentum to simulate the discharge rate as part of the solution in a large eddy simulation of an axial hydraulic pump. The linear momentum balance equation is used to update the inlet flow rate. The sharp interface immersed boundary method with dynamic Smagorinsky sub-grid stress model and a proper wall model is used.

The steady-state volumetric flow rate has been computed and validated by comparing to the flow rate specified by the manufacturer at the simulation conditions, which shows a promising result. The instantaneous and time averaged flow fields are also studied to reveal the flow pattern and turbulence characteristics in the pump flow field.

An approach is proposed for computing the volumetric flow rate as a coupled part of the flow solution, enabling the simulation of turbomachinery at all phases, including the startup/shutdown phase. To the best of the authors’ knowledge, this is the first large eddy simulation of a hydraulic pump to calculate the transient inlet flow rate as a part of the solution rather than specifying it as a fixed boundary condition. The method serves as a numerical framework for simulating problems incorporating complex shapes with moving/stationary parts at all regimes including the transient start-up and shut-down phases.