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The purpose of this paper is to examine the cost of equity capital for foreign firms listed in the US stock exchanges during 2004‐2009, a period that the Securities and Exchange Commission (SEC) shifted from requiring foreign issuers to comply with the US GAAP reconciliations to permitting the choice of IFRS in financial reporting.

The cost of equity of foreign firms in the IFRS reporting period was compared to that in the US GAAP reconciliation period. Also, the cost of equity of foreign firms was compared to that of matched US firms during the two periods.

The results show that the cost of equity in foreign firms is higher during the IFRS reporting period (2007‐2009) than the US GAAP reconciliation period (2004‐2006); foreign firms exhibit a constantly higher cost of equity than that of matched US firms in both periods; and the size of cost of equity difference remains the same with respect to the regulatory change. Further, it is shown that the change in foreign firms' cost of equity is affected by their home country's IFRS use.

Bonding theory suggests a reduced cost of capital for foreign firms cross‐listed in the USA because US listings require more substantial disclosure. The paper finds evidence that the SEC's waiver of US GAAP reporting does appear to reduce the bonding benefits for cross‐listed foreign firms, particularly those from IFRS adoption countries.

High residual stress caused by the high temperature gradient brings undesired effects such as shrinkage and cracking in selective laser melting (SLM). The purpose of this study is to predict the residual stress distribution and the effect of process parameters on the residual stress of selective laser melted (SLMed) Inconel 718 thin-walled part.

A three-dimensional (3D) indirect sequentially coupled thermal–mechanical finite element model was developed to predict the residual stress distribution of SLMed Inconel 718 thin-walled part. The material properties dependent on temperature were taken into account in both thermal and mechanical analyses, and the thermal elastic–plastic behavior of the material was also considered.

The residual stress changes from compressive stress to tensile stress along the deposition direction, and the residual stress increases with the deposition height. The maximum stress occurs at both ends of the interface between the part and substrate, while the second largest stress occurs near the top center of the part. The residual stress increases with the laser power, with the maximum equivalent stress increasing by 21.79 per cent as the laser power increases from 250 to 450 W. The residual stress decreases with an increase in scan speed with a reduction in the maximum equivalent stress of 13.67 per cent, as the scan speed increases from 500 to 1,000 mm/s. The residual stress decreases with an increase in layer thickness, and the maximum equivalent stress reduces by 33.12 per cent as the layer thickness increases from 20 to 60µm.

The residual stress distribution and effect of process parameters on the residual stress of SLMed Inconel 718 thin-walled part are investigated in detail. This study provides a better understanding of the residual stress in SLM and constructive guidance for process parameters optimization.

High temperature gradient induces high residual stress, producing an important effect on the part manufacturing during laser powder bed fusion (LPBF). The purpose of this study is to investigate the effect of the molten pool mode on the thermal stress of Ti-6Al-4V alloy during different deposition processes.

A coupled thermal-mechanical finite element model was built. The developed model was validated by comparing the numerical results with the experimental data in the maximum molten pool temperature, the molten pool dimension and the residual stress described in the previous work.

For the single-track process, the keyhole mode caused an increase in both the maximum stress and the high-stress area compared with the conduction mode. For the multitrack process, a lower tensile stress around the scanning track and a higher compressive stress below the scanning track were found in the keyhole mode. For the multilayer process, the stress along the scanning direction at the middle of the part changed from tensile stress to compressive stress with the increase in the deposition layer number. As the powder layer number increased, the stress along the scanning direction near the top surface of the part decreased while the stress along the deposition direction obviously increased, indicating that the stress along the deposition direction became the dominant stress. The keyhole mode can reduce the residual stress near the top of the part, and the conduction mode was more likely to produce a low residual stress near the bottom of the part.

The results provide a systematic understanding of thermal stress during the LPBF process.

The purpose of this paper is to investigate the effect of the Q‐switching parameters on the sintering behavior of laser micro sintering Cu‐based metal powder, using Q‐switched 1064 nm Nd‐YAG laser.

An experimental study has been performed. Metal powder mixture with Cu and Cu‐P alloy powders has been utilized. Q‐switching duration of 15 μs∼25 μs, rate of 25 kHz∼45 kHz have been used.

The results show that as the Q‐switching rate and duration increases, the peak laser power decreases and the densification enhances. However, an optimal peak laser power exists and if the peak laser power is too low, the density of the sample is also low. The densification regime of laser micro‐sintering is not only caused by the liquid phase filling the pores, but is also caused by the Cu powder migrating and by coalescence, e.g. including initial stage and intermediate stage of the traditional furnace liquid phase sintering. However, the degree of these stages depends on the peak power and input laser energy.

The effect of the Q‐switching parameters on sintering behavior of laser micro sintering Cu‐based metal powder using Q‐switched 1064 nm Nd‐YAG laser has been obtained. It is found that the densification behavior is Q‐switching parameters dependent, although the average laser power is same. The densification regime of laser micro‐sintering includes initial stage and intermediate stage of the traditional furnace liquid phase sintering, but the degree is Q‐switching parameters dependent.

To fabricate high performance parts, this paper aims to systematically study the pores characteristics and their formation mechanisms in selective laser melting (SLM) AlSi10Mg.

Cubes of 10 × 10 × 5 mm were manufactured in different laser power, scan speed and scan space. Optical microscope (OM) and scanning electron microscopes (SEM) were used to observe morphology of pores.

Round or irregular pores were found in SLMed AlSi10Mg parts. All the round pores have smooth inner walls and locate in the melt pool. The formation mechanisms of the round pores are contributed to the evaporation of elements in the melt pool, H₂O, high laser energy input and hollow powder. Irregular pores have rough inner walls. Big scan space, unevenness of the upper surface, large layer thickness, spatter and oxide are the main reasons of generating irregular pores which outside the melt pool. Instability of keyhole leads to the irregular pores locate in the bottom of keyhole mode melt pool.

Relationship between pores and melt pool were studied systematically for the first time. Researches of pores characteristics and their formation mechanisms in SLMed AlSi10Mg would be a valuable reference for researchers to obtain an important insight into and control the defect in SLMed Al alloy.

Selective laser melting (SLM) is a promising additive manufacturing technology in the field of complex parts’ fabrication. High temperature gradient and residual stress are vital problems for the development of SLM technology. The purpose of this paper is to investigate the influence of substrate characteristics on the residual stress of SLMed Inconel 718 (IN718).

The SLMed IN718 samples were fabricated on the substrates with different characteristics, including pre-compression stress, materials and pre-heating. The residual stress at the center of the top surface was measured and compared through Vickers micro-indentation.

The results indicate that the residual stress reduces when the substrate contains pre-compression stress before the SLM process starts. Both substrate thermal expansion coefficient and thermal conductivity affect the residual stress. In addition to reducing the difference of thermal expansion coefficient between the substrate and the deposited material, the substrate with low thermal conductivity can also decrease the residual stress. Substrate pre-heating at 150°C reduces nearly 42.6 per cent residual stress because of the reduction of the temperature gradient.

The influence of substrate characteristics on the residual stress has been studied. The investigation results can help to control the residual stress generated in SLM processing.

Principles of epigenesis that provide a foundation for research into chronic medical disorders are increasingly being applied in the context of mental health. The purpose of this paper is to consider recent research evidence for epigenetic influences in the pathogenesis of depression, and the putative links with stress biology during exposure to chronic stress, with the aim of placing this into a context of potential new therapeutics.

Substantive reviews published during the last ten years were identified in a search of the Pubmed database in September 2010 using the terms “epigenetics” or “epigenesis” with “mental health”, “mood disorder”, “depression”, stress', “chronic stress” or “environment”, supplemented by hand‐searching of citations in the reviews.

Epigenetic mechanisms are both heritable and acquired, and their impact on the underlying genome helps explain individual vulnerability and patterns of occurrence of depression.

The paper shows that this relatively new field of research is in its infancy, and the influence of adverse environments (i.e. stressors) on genetic/epigenetic predisposition has promise for the advent of novel therapeutics based on epigenetic manipulation.

This paper reflects on the evolution of China's drug distribution industry from the planned economy era to the most recent dramatic shift, with a major focus on the analysis of the government's efforts of centralizing the drug distribution channel through adoption of e‐bidding platforms. In a broader sense, the Chinese government's effort is a showcase of the so‐called “Chinese model” of implementing institutional change: the government initiates a project and counts on its fiat to gain compliance and support from the involved stakeholders. The purpose of this paper is to analyse the limitations and problems of this mode of implementing institutional change.

The analytical framework draws upon Williamson's theory of the mechanism of governance and insights from new institutional economics on institutional changes. The information used in this study is based on the authors' more than 40 interviews with a variety of pharmaceutical industry stakeholders, including government agencies, hospitals, pharmaceutical manufacturers, distributors, and electronic bidding platforms providers.

The failure of implementing third party electronic platforms based drug procurement practices shows the importance of aligning the mode of governing transactions with the macro level institutional environment and the micro level individual behavioral traits, and the government's decision of taking over the ownership of transaction platforms has further corroborated this logic.

This paper is an effort to analyze the logic behind the Chinese model of implementing institutional change: the government initiates a project and counts on its fiat to gain compliance and support from the involved stakeholders. From the academic perspective, this paper contributes to literature on the analysis of the interaction of technology adoption and institutional change.

Intent detection (ID) and slot filling (SF) are two important tasks in natural language understanding. ID is to identify the main intent of a paragraph of text. The goal of SF is to extract the information that is important to the intent from the input sentence. However, most of the existing methods use sentence-level intention recognition, which has the risk of error propagation, and the relationship between intention recognition and SF is not explicitly modeled. Aiming at this problem, this paper proposes a collaborative model of ID and SF for intelligent spoken language understanding called ID-SF-Fusion.

ID-SF-Fusion uses Bidirectional Encoder Representation from Transformers (BERT) and Bidirectional Long Short-Term Memory (BiLSTM) to extract effective word embedding and context vectors containing the whole sentence information respectively. Fusion layer is used to provide intent–slot fusion information for SF task. In this way, the relationship between ID and SF task is fully explicitly modeled. This layer takes the result of ID and slot context vectors as input to obtain the fusion information which contains both ID result and slot information. Meanwhile, to further reduce error propagation, we use word-level ID for the ID-SF-Fusion model. Finally, two tasks of ID and SF are realized by joint optimization training.

We conducted experiments on two public datasets, Airline Travel Information Systems (ATIS) and Snips. The results show that the Intent ACC score and Slot F1 score of ID-SF-Fusion on ATIS and Snips are 98.0 per cent and 95.8 per cent, respectively, and the two indicators on Snips dataset are 98.6 per cent and 96.7 per cent, respectively. These models are superior to slot-gated, SF-ID NetWork, stack-Prop and other models. In addition, ablation experiments were performed to further analyze and discuss the proposed model.

This paper uses word-level intent recognition and introduces intent information into the SF process, which is a significant improvement on both data sets.

Intent detection and slot filling are two important tasks in question comprehension of a question answering system. This study aims to build a joint task model with some generalization ability and benchmark its performance over other neural network models mentioned in this paper.

This study used a deep-learning-based approach for the joint modeling of question intent detection and slot filling. Meanwhile, the internal cell structure of the long short-term memory (LSTM) network was improved. Furthermore, the dataset Computer Science Literature Question (CSLQ) was constructed based on the Science and Technology Knowledge Graph. The datasets Airline Travel Information Systems, Snips (a natural language processing dataset of the consumer intent engine collected by Snips) and CSLQ were used for the empirical analysis. The accuracy of intent detection and F1 score of slot filling, as well as the semantic accuracy of sentences, were compared for several models.

The results showed that the proposed model outperformed all other benchmark methods, especially for the CSLQ dataset. This proves that the design of this study improved the comprehensive performance and generalization ability of the model to some extent.

This study contributes to the understanding of question sentences in a specific domain. LSTM was improved, and a computer literature domain dataset was constructed herein. This will lay the data and model foundation for the future construction of a computer literature question answering system.