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Depression has become one of the most serious and prevalent mental health problems worldwide. The rise and popularity of social networks such as microblogs provides a wealth of psychological data for early depression detection. Language use patterns reflect emotional states and psychological traits. Differences in language use between depressed and general users may help predict and diagnose early depression. Existing work focuses on depression detection using users' social textual emotion expressions, with less psychology-related knowledge.

In this paper, we propose an RNN-capsule-based depression detection method for microblog users that improves depression detection accuracy in social texts by combining textual emotional information with knowledge related to depression pathology. Specifically, we design a multi-classification RNN capsule that enhances emotion expression features in utterances and improves classification performance of depression-related emotional features. Based on user emotion annotations over time, we use integrated learning to detect depression in a user’s social text by combining the analysis results with components such as emotion change vector, emotion causality analysis, depression lexicon and the presence of surprising emotions.

In our experiments, we test the accuracy of RNN capsules for emotion classification tasks and then validate the effectiveness of different depression detection components. Finally, we achieved 83% depression detection accuracy on real datasets.

The paper overcomes the limitations of social text-based depression detection by incorporating more psychological background knowledge to enhance the early detection success rate of depression.

The purpose of this paper is to evaluate multinational enterprises’ (MNEs) performance and impact in contexts beyond their own internal objectives.

Based on an “eclectic” paradigm and the range of motivations, the framework is designed around three layers of evaluation: “efficiency” as static optimisation, “growth and development” as the dynamics of change on a purely economic view; political/economic sphere in terms of the outcomes of “distribution”, and “sovereignty” on the more purely political concern of how MNEs may undermine countries’ policy independence.

MNE and national economies have to use current sources of competitiveness efficiently while addressing the necessity to reinforce and refocus them through time. Within these broad agendas, significant interactions and outcomes reflect a range of contingencies conditioned by both MNE objectives and hosts’ competitive status.

The paper concerns economics and MNE role in globalisation. The paper defines a framework of four generic evaluative issues of MNE performance, which subsume a wider range of important but more niche concerns.

This study aims to examine how the political career concerns of top executives affect corporate environmental practices.

Based on rent-seeking theory, this work uses empirical analysis to investigate the impact of top executives’ political connection and political promotion on corporate environmental information disclosure (EID). Data were collected from Chinese listed firms in heavily polluting industries in the Shanghai Stock Market in 2014–2016.

The results reveal that the highly politically connected top executives are more likely to be promoted in their political positions than their counterparts. However, the firms under the management of these highly politically connected executives show low level of EID. The results suggest that the political motivations of top executives with political connection hinders corporate EID.

This paper extends literature system about the impact of executives' rent-seeking on corporate EID by examining the informal mechanisms in terms of political connection and political promotion. It provides insights for studies of corporate environmental strategies and governmental environmental responsibility.

Previous studies have reached inconsistent conclusions on foreign direct investment (FDI) technology spillovers and corporate innovation. The main purpose of this paper is to explore the technological spillover effects of FDI from the microperspective of firm linkages induced by geographic distance. Further analysis is conducted on the impact and mechanism of this spillover on the innovation quality of Chinese enterprises. The conclusions drawn from this paper can guide Chinese enterprises' foreign capital utilization and innovation strategy choices.

Using the data of China's A-share listed companies from 2009 to 2019, this paper explores the role of FDI technology spillover in enterprise innovation quality through a two-way fixed-effect model. The robustness of the results is proven by substituting variables, adding industry fixed effects and excluding high-profit groups, and further using the two-stage least squares (2SLS) method to alleviate the empirical endogeneity problem.

These findings indicate that FDI technology spillover based on geographic proximity has a positive impact on the innovation quality of Chinese enterprises. However, there are different impacts for different types of enterprises. FDI technology spillover has a positive impact on the innovation quality of non-state-owned enterprises (non-SOEs) and small- and medium-sized enterprises (SMEs), while it has no effect on state-owned enterprises (SOEs) and large enterprises. The authors also find that the degree of financing constraints and R&D investment are important transmission mechanisms between FDI technology spillover and enterprise innovation quality.

This study ignores industry characteristics when considering foreign enterprises around Chinese enterprises. In fact, technology spillover effects differ across industries. When the authors matched microdata to regions, only the provincial level was considered. Therefore, there is still room for further research. In future research, the authors should consider industry characteristics and group foreign enterprises and Chinese enterprises in the same industry and in different industries to explore industry differences in technology spillover. In addition, when matching corporate data to regions, the authors can match to the city level and draw city-level conclusions.

This study is different from previous studies that focus on the quantity of enterprise innovation or innovation output. The authors focus on the role of technological spillovers in the quality of Chinese enterprise innovation, enriching research in the field of enterprise innovation quality. In addition, the current FDI technology spillover indicators are technically difficult to measure at the micro level. The authors draw inspiration from the theory of the geographical structure of financial supply and combine the creation methods of macro and micro indicators in existing articles in other fields. The authors ingeniously construct a new FDI technical spillover indicator. This indicator combines the commonly used regional FDI technology spillover with the geographic proximity of enterprises at the microlevel by constructing an interaction term between the two. This indicator not only alleviates the endogeneity problem to a certain extent but also has implications for future research in the field of FDI technology spillovers at the micro level.

(1) FDI technology spillovers are an effective way to improve the innovation quality of local enterprises, especially for non-SOEs and SMEs. Therefore, The authors suggest that in the context of dual circulation, the Chinese government should continue to open wider to the outside world and encourage foreign enterprises to invest in China. (2) In future development, managers of SOEs and large enterprises should create an innovation incentive mechanism. Moreover, they should change their vertical management structure and make full use of their policy advantages and budget advantages to increase innovation activities. In the process of acquiring technology spillovers, enterprises need to solve their own financing constraints.

First, this study solves a technical problem. It is technically difficult to measure the current FDI technical spillover indicators at the micro level. This study innovatively constructs a new FDI technology spillover indicator that combines regional FDI technology spillovers with the microperspective of the geographical proximity of enterprises. This approach not only alleviates certain endogeneity problems in the empirical evidence but also enriches relevant research in the field of technology spillover. In addition, this study focuses on the impact and mechanism of this spillover, which addresses the current research gap among previous studies that mainly focus on innovation quantity and ignore innovation quality.

This study aims to regarding the application of traditional pulse frequency modulation control full-bridge LLC resonant converters in wide output voltage fields such as on-board chargers, there are issues with wide frequency adjustment ranges and low conversion efficiency.

To address these issues, this paper proposes a fixed-frequency pulse width modulation (PWM) control strategy for a full-bridge LLC resonant converter, which adjusts the gain by adjusting the duty cycle of the switches. In the full-bridge LLC converter, the two switches of the lower bridge arm are controlled by a fixed-frequency and fixed duty cycle, with their switching frequency equal to the resonant frequency, whereas the two switches of the upper bridge arm are controlled by a fixed-frequency PWM to adjust the output voltage. The operation modes of the converter are analyzed in detail, and a mathematical model of the converter is established. The gain characteristics of the converter under the fixed-frequency PWM control strategy are deeply analyzed, and the conditions for implementing zero-voltage switching (ZVS) soft switching in the converter are also analyzed in detail. The use of fixed-frequency PWM control simplifies the design of resonant parameters, and the fixed-frequency control is conducive to the design of magnetic components.

According to the fixed-frequency PWM control strategy proposed in this paper, the correctness of the control strategy is verified through simulation and the development and testing of a 500-W experimental prototype. Test results show that the primary side switches of the converter achieve ZVS and the secondary side rectifier diodes achieve zero-current switching, effectively reducing the switching losses of the converter. In addition, the control strategy reduces the reactive circulating current of the converter, and the peak efficiency of the experimental prototype can reach 95.2%.

The feasibility of the fixed-frequency PWM control strategy was verified through experiments, which has significant implications for improving the efficiency of the converter and simplifying the design of resonant parameters and magnetic components in wide output voltage fields such as on-board chargers.

The modernization of China’s economy is an integral part of Chinese-style modernization. According to the principle of unifying theoretical, historical and practical logic, theoretically explaining the modernization of China’s economy is both a political necessity and a higher scientific requirement.

Following this evolutionary line – from modes of production to the general economic development mechanism and then to patterns of economic operation and development – this paper employs the principal contradiction analysis method to offer an interpretation of China’s economic modernization from the broad Marxist political economy perspective.

In economic terms, “get organized” primarily refers to the development and mutual promotion of team-based and market-based division of labor organizations, as discussed by Karl Marx. “Get organized” (specifically the development of team-based division of labor organizations) acts as the engine of China’s economic modernization and serves as the historical logical starting point. Division of labor is the theoretical logical starting point for interpreting China’s economic modernization. The two of them are congruent, achieving the unity of theoretical and historical logic at the starting point. The development and mutual promotion of these “two types of division of labor” inherently generate the general mechanism of economic development first comprehensively discussed by Marx and Friedrich Engels, which involves the division of labor development and market expansion accumulating cyclically and reinforcing each other. This mechanism drives both the high-speed and high-quality development of China’s economic modernization.

The broad Marxist political economy paradigm facilitates explaining China’s economic modernization theoretically, historically and practically with unified logic. “Get organized” serves as both the engine and the realization mechanism of this modernization, with the Communist Party of China (CPC) consistently being the core force of this organizational effort.

This study explores how chatbot gender and symbolic service recovery may improve the satisfaction of angry customers in the context of service failures. It provides a strategy for companies to deploy chatbots effectively in customer anger.

This research relies upon a systematic literature review to propose three hypotheses, and we recruit 826 participants to examine the effect of chatbot gender on angry customers through one lab study and one field study.

This research shows that female chatbots are more likely to increase the satisfaction of angry customers than male chatbots in service failure scenarios. In addition, symbolic recovery (apology vs. appreciation) moderates the effect of chatbot gender on angry customers. Specifically, male (vs. female) chatbots are more effective in increasing the satisfaction of angry customers when using the apology method, whereas female (vs. male) chatbots are more effective when using the appreciation method.

The rapid advancements in artificial intelligence technology have significantly enhanced the effectiveness of chatbots as virtual agents in the field of interactive marketing. Previous research has concluded that chatbots can reduce negative customer feedback following a service failure. However, these studies have primarily focused on the level of chatbot anthropomorphism and the design of conversational texts, rather than the gender of chatbots. Therefore, this study aims to bridge that gap by examining the effect of chatbot gender on customer feedback, specifically focusing on angry customers following service failures.

This study examines whether and how the age-inverse relationship between the chief executive officer (CEO) and the top management team (TMT) affects corporate misconduct in China’s construction industry. Drawing on social identity theory, we propose that the age-inverse relationship in CEO–TMT may diminish their social identity and further decrease the likelihood of corporate misconduct in construction firms.

Using a longitudinal dataset of firms in China’s construction industry covering the years 2003 through 2021, this study adopted a logit regression model with fixed effects.

The results show that the age-inverse relationship in CEO–TMT is negatively related to corporate misconduct. Further investigations suggest that performance feedback moderates the relationship between the age-inverse relationship in CEO–TMT and corporate misconduct. Firms with an age-inverse relationship between CEOs and TMTs are more likely to engage in fraudulent behavior when performance is above aspirations and less likely to commit fraud when performance is below aspirations.

The sample of this study is limited to China’s construction firms. Drawing on social identity theory, this study explores the relationship between the age-inverse relationship and corporate misconduct in China’s construction industry, which enriches the antecedents of corporate misconduct and contributes to CEO–TMT interface research within construction firms.

This study provides a guideline for construction firms on how to regulate and reduce misconduct. It will offer insights into human resource arrangements within the management of construction firms in an aging context.

Considering that few studies explore fraudulent behavior of construction companies at the upper echelon level, this study focuses on a novel and new antecedent (i.e. age-inverse relationship in CEO–TMT) and its boundary conditions. The findings extend the research on corporate misconduct and strategic leadership in the construction industry.

This study aims to address the degradation and damage of traditional bridge expansion joints by proposing a seamless expansion joint device based on polyurethane elastomer (PUE).

A series of laboratory experiments were conducted to evaluate the performance of PUE, including elasticity recovery, interfacial bonding and hygrothermal aging tests. Indoor model tests were also designed to analyze PUE's performance in actual bridge expansion structures. Based on these evaluations, the design of a seamless PUE expansion joint structure was completed.

The study reveals that PUE achieves optimal interfacial bond strength with PUC at −30°C after 7 h of curing and adhesive application, with a tensile strength of 9.2 MPa. PUE's elongation at break exceeds 3% at −30°C and retains its toughness and tensile strength after hygrothermal aging. When the beam end rotation reaches 0.0144 rad, PUE maintains a linear elastic state. With a groove width of 340 mm, PUE can withstand compressive displacements over 40 mm and tensile displacements up to 60 mm.

The findings highlight the excellent elasticity recovery and toughness characteristics of PUE, demonstrating the significant improvement in durability of the PUE seamless expansion joint structure and the rationality of the groove width calculation method based on the elongation at break of PUE. The broader impact of this study lies in its potential to innovate the design and maintenance strategies of bridge expansion joints.

The purpose of this paper is to improve the existing paradigm of edge computing to maintain a balanced energy usage.

The new greedy algorithm is proposed to balance the energy consumption in edge computing.

The new greedy algorithm can balance energy more efficiently than the random approach by an average of 66.59 percent.

The results are shown in this paper which are better as compared to existing algorithms.