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The tender documents, an essential data source for internet-based logistics tendering platforms, incorporate massive fine-grained data, ranging from information on tenderee, shipping location and shipping items. Automated information extraction in this area is, however, under-researched, making the extraction process a time- and effort-consuming one. For Chinese logistics tender entities, in particular, existing named entity recognition (NER) solutions are mostly unsuitable as they involve domain-specific terminologies and possess different semantic features.

To tackle this problem, a novel lattice long short-term memory (LSTM) model, combining a variant contextual feature representation and a conditional random field (CRF) layer, is proposed in this paper for identifying valuable entities from logistic tender documents. Instead of traditional word embedding, the proposed model uses the pretrained Bidirectional Encoder Representations from Transformers (BERT) model as input to augment the contextual feature representation. Subsequently, with the Lattice-LSTM model, the information of characters and words is effectively utilized to avoid error segmentation.

The proposed model is then verified by the Chinese logistic tender named entity corpus. Moreover, the results suggest that the proposed model excels in the logistics tender corpus over other mainstream NER models. The proposed model underpins the automatic extraction of logistics tender information, enabling logistic companies to perceive the ever-changing market trends and make far-sighted logistic decisions.

(1) A practical model for logistic tender NER is proposed in the manuscript. By employing and fine-tuning BERT into the downstream task with a small amount of data, the experiment results show that the model has a better performance than other existing models. This is the first study, to the best of the authors' knowledge, to extract named entities from Chinese logistic tender documents. (2) A real logistic tender corpus for practical use is constructed and a program of the model for online-processing real logistic tender documents is developed in this work. The authors believe that the model will facilitate logistic companies in converting unstructured documents to structured data and further perceive the ever-changing market trends to make far-sighted logistic decisions.

Many emerging economy firms are under foreign owners' pressure to embrace the challenges of addressing corporate social responsibility (CSR) and consider adopting sustainability initiatives. However, it is not clear how foreign ownership plays a role to enable or inhibit these emerging economy firms from translating sustainability initiatives into improved financial performance. Utilizing neo-institutional theory, the authors argue that emerging economy firms that voluntarily report sustainability gain legitimacy in the eyes of shareholders and improve stock market performance. However, emerging economy firms may not have the resources to reconcile the internal stakeholders' various legitimacy requirements to promote sustainability practices, resulting in a negative association with accounting performance. Foreign ownership attenuates the relationship between sustainability reporting and firm performance due to the different legitimacy requirements in foreign markets.

To test the study’s hypotheses, the authors collected and analyzed a large sample of publicly listed firms between 2010 and 2016 in Taiwan where the types of foreign ownership include foreign trust funds, foreign financial institutions and other foreign legal entities. Regression analyses were conducted to investigate whether the firms that report their sustainable practices have better financial performance, including stock market performance and accounting performance. Additionally, a three-step procedure was employed to address the endogeneity issue with a binary explanatory variable.

The positive stock market reaction to the emerging economy firms' voluntary sustainability reporting supports legitimacy gained among investors. By contrast, sustainability reporting has a negative association with accounting performance due to the difficulty of reconciling different legitimacy requirements among various stakeholders in emerging economies. Further, foreign ownership, particularly the trust fund, exhibits a negative moderating effect on the relationship between sustainability reporting in aligning corporate practices with sustainable development goals (SDGs) and the company's stock market performance.

By examining the less tested contingent role played by foreign ownership in the emerging economy firms' sustainability reporting, the authors provide insights into the influence exerted by different types of foreign ownership on firms' financial performances beyond previous studies that focus on family ownership, state ownership, or managerial ownership in emerging economies. The findings shed light on corporate sustainability strategy and foreign direct investment policies for an emerging economy.

The electromechanical brake system is leading the latest development trend in railway braking technology. The tolerance stack-up generated during the assembly and production process catalyzes the slight geometric dimensioning and tolerancing between the motor stator and rotor inside the electromechanical cylinder. The tolerance leads to imprecise brake control, so it is necessary to diagnose the fault of the motor in the fully assembled electromechanical brake system. This paper aims to present improved variational mode decomposition (VMD) algorithm, which endeavors to elucidate and push the boundaries of mechanical synchronicity problems within the realm of the electromechanical brake system.

The VMD algorithm plays a pivotal role in the preliminary phase, employing mode decomposition techniques to decompose the motor speed signals. Afterward, the error energy algorithm precision is utilized to extract abnormal features, leveraging the practical intrinsic mode functions, eliminating extraneous noise and enhancing the signal’s fidelity. This refined signal then becomes the basis for fault analysis. In the analytical step, the cepstrum is employed to calculate the formant and envelope of the reconstructed signal. By scrutinizing the formant and envelope, the fault point within the electromechanical brake system is precisely identified, contributing to a sophisticated and accurate fault diagnosis.

This paper innovatively uses the VMD algorithm for the modal decomposition of electromechanical brake (EMB) motor speed signals and combines it with the error energy algorithm to achieve abnormal feature extraction. The signal is reconstructed according to the effective intrinsic mode functions (IMFS) component of removing noise, and the formant and envelope are calculated by cepstrum to locate the fault point. Experiments show that the empirical mode decomposition (EMD) algorithm can effectively decompose the original speed signal. After feature extraction, signal enhancement and fault identification, the motor mechanical fault point can be accurately located. This fault diagnosis method is an effective fault diagnosis algorithm suitable for EMB systems.

By using this improved VMD algorithm, the electromechanical brake system can precisely identify the rotational anomaly of the motor. This method can offer an online diagnosis analysis function during operation and contribute to an automated factory inspection strategy while parts are assembled. Compared with the conventional motor diagnosis method, this improved VMD algorithm can eliminate the need for additional acceleration sensors and save hardware costs. Moreover, the accumulation of online detection functions helps improve the reliability of train electromechanical braking systems.

The marketisation of higher education fosters the notion of students as consumers, highlighting the shifting dynamics of student–teacher relationships. This paper aims to contribute to ongoing discussions about students as consumers and their involvement in pedagogical practices. We explore students’ experiences in short-term study abroad (SA) programmes that involve collaborative learning, examining how a consumerism-oriented approach affects students’ perceptions of their pedagogical identities and student–teacher pedagogical relationships.

A qualitative exploratory study was conducted to capture students’ rich and subjective perceptions and experiences. The data were gathered through semi-structured interviews with 15 Chinese undergraduate students who participated in a short-term SA programme at a UK university. Following data translation and transcription, a thematic analysis approach facilitated our exploration.

Chinese students engage in SA programmes as a strategic investment in personal growth and transformation, with their consumer-oriented identity fostering a mutually beneficial relationship with educators and group members. This consumer mindset appears to enhance active student engagement and, to some extent, create reciprocal student–teacher interactions through power sharing and collaborative involvement.

This study presents empirical data exploring the impact of consumer identity on the dynamics of student–teacher relationships in the SA context. It provides recommendations for implementing pedagogical approaches designed to mediate the influence of consumerism on student engagement, particularly in shaping collaborative student–teacher relationships. This study offers insights for future research on the effects of consumerism in higher education within cross-cultural contexts.

1) The OE-MLPG penalty meshfree method is developed to solve cracked structure.(2) Smartening the numerical meshfree method by combining the particle swarm optimization (PSO) optimization algorithms and Voronoi computational geometric algorithm. (3). Selection of base functions, finding optimal penalty factor and distribution of appropriate nodal points to the accuracy of calculation in the meshless local Petrov–Galekrin (MLPG) meshless method.

Using appropriate shape functions and distribution of nodal points in local domains and sub-domains and choosing an approximation or interpolation method has an effective role in the application of meshless methods for the analysis of computational fracture mechanics problems, especially problems with geometric discontinuity and cracks. In this research, computational geometry technique, based on the Voronoi diagram (VD) and Delaunay triangulation and PSO algorithm, are used to distribute nodal points in the sub-domain of analysis (crack line and around it on the crack plane).

By doing this process, the problems caused by too closeness of nodal points in computationally sensitive areas that exist in general methods of nodal point distribution are also solved. Comparing the effect of the number of sentences of basic functions and their order in the definition of shape functions, performing the mono-objective PSO algorithm to find the penalty factor, the coefficient, convergence, arrangement of nodal points during the three stages of VD implementation and the accuracy of the answers found indicates, the efficiency of V-E-MLPG method with Ns = 7 and ß = 0.0037–0.0075 to estimation of 3D-stress intensity factors (3D-SIFs) in computational fracture mechanics.

The present manuscript is a continuation of the studies (Ref. [33]) carried out by the authors, about; feasibility assessment, improvement and solution of challenges, introduction of more capacities and capabilities of the numerical MLPG method have been used. In order to validate the modeling and accuracy of calculations, the results have been compared with the findings of reference article [34] and [35].