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The purpose of this paper is to test if the digital economy improves the quality of life of our residents. Furthermore, if this finding is confirmed, what would be the mechanism behind its effect? Does the impact of the digital economy on quality of life vary according to its level of development?

A comprehensive index of the digital economy, income gap and quality of life was constructed empirically based on data from 220 cities in China from 2011–2020. A multi-dimensional empirical analysis was conducted in this paper.

The analysis of the pathways of action shows that narrowing the income gap is an important mechanism through which the digital economy actively contributes to the quality of life. The results of the threshold model show that the “marginal effect” of the digital economy on quality of life is non-linear and increasing. The results show that after a series of robustness tests, including instrumental variables, the digital economy still significantly enhances people’s quality of life.

This paper reveals the intrinsic link between the digital economy and quality of life and provides a theoretical basis for further improving people’s well-being.

Encouraging the development of the digital economy is a useful way to improve the quality of life by narrowing the income gap.

Data analysis of the digital economy from 2011–2020 in China to get an insight into what would be the mechanism behind the digital economy improving the quality of life of our residents.

Employing the conceptual framework of play themes, this study examined and reported the product categories that presented branded entertainment the most, the different types and features of branded entertainment, and how various play themes were incorporated in branded entertainment in the context of Facebook brand profile pages. The major findings were consistent with the conceptual framework and literature on branded entertainment. Some unexpected findings were also provided and discussed. The line between entertainment and marketing communication has become increasingly blended or even erased during recent years, particularly in the Internet context. Researchers and practitioners are highly interested in the marketing potential of branded entertainment since it may boost brand awareness and build strong consumer‐brand relationships. Little academic research to date has been conducted to systematically study branded entertainment on the Internet. This study is a nascent attempt to understand branded entertainment in user‐centered social networking websites (SNWs), since young users are shifting away from other online media to SNWs. Branded entertainment may help marketers gather segmented yet fun‐seeking SNW users and deliver nonintrusive marketing messages to them.

The purpose of this paper is to obtain the combination of working parameters suitable for pulsating negative pressure shale shaker through simulation, which is conducive to efficient recovery of clean drilling fluid and relatively dry cuttings.

Shale shaker is still one of the main equipment in solid–solid and solid–liquid separation processes in drilling industry. This research is based on a new drilling fluids circulation treatment device, namely pulsating negative pressure shale shaker. In this work, a numerical study of particle flow and separation in the pulsating negative pressure shale shaker is carried out by coupling computational fluid dynamics/discrete element method (CFD-DEM). The effect of vibration parameters and negative pressure parameters are studied in terms of conveyance velocity and percent through screen.

The results show that, conveyance velocity of particle is mainly affected by vibration parameters, negative pressure in pulsating form can effectively prevent cuttings from sticking to the screen. Vibration parameters and pulsating airflow velocity peak have great influence on percent through screen, while vibration frequency and screen slope have influence on the time when the percent through screen reaches stability.

In this paper, the authors put forward a new kind of drilling waste fluid treatment equipment, and focused on the study of particle movement law. The results have important guiding significance for the selection of structural design parameters and rational use of equipment. In addition, the new device provides a new idea for solid–liquid separation method, which is one of the hot topics in current research.

In the case of Poiret & Anor v Seychelles Pension Fund & Anor (2022), the Court of Appeal, the highest court in Seychelles, took judicial notice of the fact that “[c]ommon law relationships are more prevalent in our society than those between married persons.” In this chapter, the author discusses the law relating to common law marriages in Seychelles by focusing on the following issues: the right to form a family (as a background to understanding common law marriages); requirements for a valid common law marriage; and the rights of parties in a common law marriage. These rights include “court granted” rights and “statutory rights” such as property rights (parties invoking the claim of unjust enrichment in the 1979 Civil Code and property orders and succession under the 2021 Civil Code at the dissolution of common law marriages). I also deal with the remedy of unjust enrichment in the context of the 2021 Civil Code; marital privilege (in case where one of the parties in a common law relationship is accused of committing an offence); and termination of a common law marriage. The author demonstrates the measures taken by courts and the legislators to protect some of the rights of people in common law marriages. The author suggests ways in which courts can interpret the relevant provisions of the 2021 Civil Code. Where necessary, the author highlights how courts or legislators in some African countries such as Kenya, Mauritius, Malawi, Tanzania, Sierra Leone, Ghana, Zambia, South Africa, Namibia, Rwanda, and Uganda have approached some of the issues above.

Drug repurposing involves the identification of new applications for existing drugs. Owing to the enormous rise in the costs of pharmaceutical R&D, several pharmaceutical companies are leveraging repurposing strategies. Parkinson's disease is the second most common neurodegenerative disorder worldwide, affecting approximately 1–2 percent of the human population older than 65 years. This study proposes a literature-based drug repurposing strategy in Parkinson's disease.

The literature-based drug repurposing strategy proposed herein combined natural language processing, network science and machine learning methods for analyzing unstructured text data and producing actional knowledge for drug repurposing. The approach comprised multiple computational components, including the extraction of biomedical entities and their relationships, knowledge graph construction, knowledge representation learning and machine learning-based prediction.

The proposed strategy was used to mine information pertaining to the mechanisms of disease treatment from known treatment relationships and predict drugs for repurposing against Parkinson's disease. The F1 score of the best-performing method was 0.97, indicating the effectiveness of the proposed approach. The study also presents experimental results obtained by combining the different components of the strategy.

The drug repurposing strategy proposed herein for Parkinson's disease is distinct from those existing in the literature in that the drug repurposing pipeline includes components of natural language processing, knowledge representation and machine learning for analyzing the scientific literature. The results of the study provide important and valuable information to researchers studying different aspects of Parkinson's disease.

The prediction of by-product gas is an important guarantee for the full utilization of resources. The purpose of this research is to predict gas consumption to provide a basis for gas dispatch and reduce the production cost of enterprises.

In this paper, a new method using the ensemble empirical mode decomposition (EEMD) and the back propagation neural network is proposed. Unfortunately, this method does not achieve the ideal prediction. Further, using the advantages of long short-term memory (LSTM) neural network for long-term dependence, a prediction method based on EEMD and LSTM is proposed. In this model, the gas consumption series is decomposed into several intrinsic mode functions and a residual term (r(t)) by EEMD. Second, each component is predicted by LSTM. The predicted values of all components are added together to get the final prediction result.

The results show that the root mean square error is reduced to 0.35%, the average absolute error is reduced to 1.852 and the R-squared is reached to 0.963.

A new gas consumption prediction method is proposed in this paper. The production data collected in the actual production process is non-linear, unstable and contains a lot of noise. But the EEMD method has the unique superiority in the analysis data aspect and may solve these questions well. The prediction of gas consumption is the result of long-term training and needs a lot of prior knowledge. Relying on LSTM can solve the problem of long-term dependence.

This study aims to perform flow simulations inside the acinus with fine alveolar pores (Kohn pores) using hexagonal cells and bottom-up geometric modeling, which enabled the elimination of invalid voids using previous top-bottom methods and spherical or circular cells.

Regular hexagonal cells were used to construct alveoli with no gaps via tessellation. Some hexagonal cells were fused to eliminate the inner boundaries to represent the structure of the bronchial tree. For the remaining hexagonal cells, the side lengths of the shared walls were adjusted to construct alveolar pores. Periodic moving boundaries with the same phase were set for all walls to describe synchronous contraction and expansion of the bronchi and alveoli.

More realistic flow characteristics in the distal lung were obtained. The effects of pore size and the mechanism of auxiliary ventilation of alveolar pores were revealed.

To the best of the authors’ knowledge, this is the first numerical simulation study on the function of multiple alveolar pores at the level of pulmonary acini, which will be helpful for simulating the dynamic process of cough and sputum excretion in the future.

The majority of emerging adults in the United States spend time in cohabiting unions. Prior research has suggested that higher levels of sexual non-exclusivity may exist among those in cohabiting relationships compared to marital unions. Although these basic patterns have been explored in prior work, research examining the potential reasons why levels of sexual non-exclusivity differ by union status has been limited. Drawing on a relational perspective and using the fifth wave of data from the Toledo Adolescent Relationships Study (TARS), the present study found that higher levels of sexual non-exclusivity in cohabiting relationships were explained by intimate relationship characteristics and sexual histories rather than sociodemographic factors, partner heterogamy, or partner- and couple-level drug use. These findings highlighted that understanding the higher rates of sexually non-exclusive experiences in cohabiting relationships, compared to marital relationships, requires attention to specific dynamics of the intimate partnership and prior relational experiences of both partners. The study concluded that cohabitation has a unique place in emerging adults’ relationship landscape and may set the groundwork for future relationship functioning.

The legalization of same-sex marriage changed the parenting landscape for LGBTQ parents in a variety of ways. Parenthood is presumably different now that same-sex marriage is officially legal. Experiences among LGBTQ couples in the post-legalization of same-sex marriage era raise questions about the context of growing recognition and cultural acceptance of same-sex relationships. I conducted in-depth interviews with LGBTQ parents to learn how they navigate parenting and the construction of parenting roles in the context of a society that has legalized same-sex marriage, yet still is rooted in heteronormative notions of family and parenthood. Specifically, I ask: How do LGBTQ couples construct and make sense of their roles as parents, particularly within the contemporary context of the legalization of same-sex marriage? Understanding the contexts that shape LGBTQ parents’ experiences aids in not only understanding the lives of LGBTQ parents and their families better, but also developing a deeper understanding of contemporary parenting identities and experiences more broadly.

The purpose of this paper is to analyze the ability of turbulence models to model the flow field in the runner of a Francis turbine. Although the complex flow in the turbine can be simulated by CFD models, the prediction accuracy still needs to be improved. The choice of the turbulence model is one key tool that affects the prediction accuracy of numerical simulations.

This study used the SST k-w and RNG k-e turbulence models, which can both accurately predict complex flow fields in numerical simulations, to simulate the flow in the entire flow passage of a Francis turbine with the results compared against experimental data for the performance and blade pressure distribution in the turbine to evaluate the applicability of the turbulence models.

The results show that the SST k-w turbulence model more accurately predicts the turbine performance than the RNG turbulence model. However, the blade surface pressures predicted by the SST k-w turbulence model were basically identical to those predicted by the RNG k-e turbulence model, with both accurately predicting the experimental data.

Due to the lack of space, the method used to measure the blade surface pressure distributions is not introduced in this paper.

Turbine performance and flow field pressure in the runner, which are the basis of turbine preliminary performance judgment and optimization through CFD, can be used to judge the rationality of the turbine runner design. The paper provides an evidence for the turbulence selection in numerical simulation to predict turbine performance and flow field pressure in the runner and improves the CFD prediction accuracy.

This paper fulfils a test of the flow field pressure in the runner, which provide an evidence for judge the adaptability of turbulence model on the flow field in runner. And this paper also provides important evaluations of two turbulence models for modeling the flow field pressure distribution in the runner of a Francis turbine to improve the accuracy of CFD models for predicting turbine performance.