Sustainable management of family life and finance in the context of digital capabilities - data flow dynamics.

In recent years, biorefining Municipal Solid Waste (MSW) has gained attention as a promising solution to the challenges of waste management and resource shortages, while also advancing sustainability goals. This research focuses on the European Union, analyzing the material flow and sustainability of biorefining systems and evaluating their impact on society, the economy, and the natural environment. The final products of the integrated material recovery processes, including recycling (18.

Spatial domains identification in spatial transcriptomics using modality-aware and subspace-enhanced graph contrastive learning.

Spatial transcriptomics (ST) technologies have emerged as an effective tool to identify the spatial architecture of tissues, facilitating a comprehensive understanding of organ function and the tissue microenvironment. Spatial domain identification is the first and most critical step in ST data analysis, which requires thoughtful utilization of tissue microenvironment and morphological priors. Here, we propose a graph contrastive learning framework, GRAS4T, which combines contrastive learning and a subspace analysis model to accurately distinguish different spatial domains by capturing the tissue microenvironment through self-expressiveness of spots within the same domain.

Classification of Infant Crying Sounds Using SE-ResNet-Transformer.

Recently, emotion analysis has played an important role in the field of artificial intelligence, particularly in the study of speech emotion analysis, which can help understand one of the most direct ways of human emotional communication-speech. This study focuses on the emotion analysis of infant crying. Within cries lies a variety of information, including hunger, pain, and discomfort.

A dynamic authorizable ciphertext image retrieval algorithm based on security neural network inference.

In this paper, we propose a dynamic authorizable ciphertext image retrieval scheme based on secure neural network inference that effectively enhances the security of image retrieval while preserving privacy. To ensure the privacy of the original image and enable feature extraction without decryption operations, we employ a secure neural network for feature extraction during the index construction stage of encrypted images. Additionally, we introduce a dynamic authenticatable ciphertext retrieval algorithm to enhance system flexibility and security by enabling users to quickly and flexibly retrieve authorized images.

A machine learning algorithm to explore the drivers of carbon emissions in Chinese cities.

As the world's largest energy consumer and carbon emitter, the task of carbon emission reduction is imminent. In order to realize the dual-carbon goal at an early date, it is necessary to study the key factors affecting China's carbon emissions and their non-linear relationships. This paper compares the performance of six machine learning algorithms to that of traditional econometric models in predicting carbon emissions in China from 2011 to 2020 using panel data from 254 cities in China.

Optimal environmental investment strategies for enterprise green technology innovation: An empirical study based on multiple drive models.

Enterprise green technology innovation (GTI) is vital for global sustainable development. However, the optimal strategies are needed to understand how environmental investments (EIs) impact enterprise GTI. This study adopts multiple drive models to explore the impact of EIs on the GTI of A-share listed enterprises in China from 2008 to 2022.

Digital finance and sustainable development: Evidence from developing nations.

Objectives: This paper investigates the role of digital finance in promoting environmental sustainability within a group of 52 developing economies from 2010 to 2019. Specifically, it examines whether digital finance effectively contributes reducing CO emissions in these nations.

Methods: This paper is a quantitative study which employs the IV-GMM (instrumental variable generalized methods of moment) approach that tackles any potential endogeneity.

Enhancing water security: Statistical measurement and spatiotemporal analysis.

Water security is essential for ensuring energy security, sustainable development, and human survival. However, due to a series of challenges, including rising water demand, environmental pollution, and water resource shortages, the global water security situation remains concerning and poses a threat to global sustainable development. To assess water security in China, this study uses data from 30 provinces in China from 2012 to 2021.

The characteristics of the new dual-cycle development pattern and systemic financial risk based on TVP-SVAR and MS-VAR model analyses.

The new development pattern of the dual cycle is an important strategic deployment by the Chinese government in response to the complex and changing economic environment and a new stage of economic development. Based on the perspective of this new dual-cycle development pattern, this paper explores the time-varying nonlinear relationship between this new development pattern and systemic financial risk by constructing two models: the TVP-SVAR-SV and the MS-VAR. The empirical results show that, first, there was a significant negative impulse response effect between the new dual-cycle development pattern and systemic financial risk.

Research on comprehensive evaluation & development of aesthetic education based on PCA and CEM model.

Aesthetic education, conveyed through public art courses, serves as a vital form of humanistic literacy education. It represents an effective approach to fostering innovative and creative thinking among college students. In order to effectively analyze the aesthetic education work of 46 universities, an aesthetic education index evaluation system is constructed, involving indicators including faculty strength, curriculum setting, teaching management, artistic practice, and teaching support.

The impacts of basic medical insurance for urban-rural residents on the perception of social equity in China.

Background: Based on CSS 2019 data, this article analyzes the impact of Basic Medical Insurance for Urban and Rural Residents (BMIUR) on perceived social equity of residents.

Method: Using the CSS data of 2019, this article analyzes the influence of BMIUR on the perception of social equity of residents, on the basis of 2SLS model and mediating effect model.

Results: We find that BMIUR has a significantly positive impact on the perception of social equity.

Culture and effectiveness of distance restriction policies: evidence from the COVID-19 pandemic.

Natural disasters bring indelible negative impacts to human beings, and people usually adopt some strategies to alleviate such impacts. However, the same strategies may have different effects in different countries (or regions), which is rarely paid attention by the academic community. In the context of COVID-19, we examine the effect of distance restriction policies (DRP) on reducing human mobility and thus inhibiting the spread of the virus.

Fast Three-Dimensional Profilometry with Large Depth of Field.

By applying a high projection rate, the binary defocusing technique can dramatically increase 3D imaging speed. However, existing methods are sensitive to the varied defocusing degree, and have limited depth of field (DoF). To this end, a time-domain Gaussian fitting method is proposed in this paper.

Preference of Chinese food production enterprises to government regulatory Information--A choice experiment approach.

In recent years, despite the fact that the Chinese government is closely monitoring food safety, the perception of food production enterprises is not obvious. The reason is that information asymmetry hinders the effective transmission of regulatory information to food production enterprises. In the present research, a choice test is conducted to explore the preference of decision-makers for the information on government regulations in 224 food production enterprises with violations.

Can co-ordination advancement of two-way FDI improve resource misallocation? Evidence from 285 cities in China.

During the past 40 years of reform and opening-up, the implementation of an unbalanced enhancement strategy has led to severe resource misallocation, making the mitigation and rectification of this misallocation an urgent issue. This paper utilizes urban data from China between 2006 and 2020 to examine the impact of two-way foreign direct investment (FDI) on resource misallocation, as well as the pathways through which coordinated advancement of two-way FDI affects resource misallocation. After undergoing a series of robustness and endogeneity tests, the conclusion remains stable.

Inter-provincial embodied carbon emission space and industrial transfer paths in China.

To bolster the dual-circulation development model and green economy, this study delves into the spatiotemporal dynamics of implied carbon transfer in China's inter-provincial and inter-industrial trade, emphasizing its significance for the "dual carbon" objectives. Utilizing multi-regional input-output data from 2012, 2015, and 2017, we employed the multi-region input-output model to gauge embodied carbon transfers across 31 provinces and 28 industries. The Structural Decomposition Analysis (SDA) model further decomposed the growth of trade-related carbon emissions.

Regional policy options for carbon peaking in the Yangtze River Delta under uncertainty.

The Yangtze River Delta (YRD) region plays a crucial role in achieving China's carbon peaking goal. However, due to uncertainties surrounding future economic growth, energy consumption, energy structure, and population, the attainment of carbon peaking in this region remains uncertain. To address this issue, this study utilized the generalized Divisia index method to analyze the driving factors of carbon emissions, including economy, energy, investment, and population.

The influence of carbon emission trading on the optimization of regional energy structure.

The optimization of the energy structure is a crucial element in the development of green and low-carbon economies and societies. Market-based environmental regulations, such as carbon emissions trading, play a significant role in facilitating this transition. This study analyzes panel data from 30 provinces in China from 2007 to 2020.

Impact mechanism of social-related social media use on the job performance of caregivers of older adults.

This study investigated the impact mechanism of social-related social media use on the job performance of caregivers of older adults through mental health and analyzed gender differences. A total of 358 valid questionnaires were collected and analyzed using SPSS and Smart PLS. The results showed that mental health plays an important role in the relationship between social-related social media use and job performance.

Dynamics of a Cournot game with bounded rational firms and various scale effects.

In this paper, we focus on a dynamic Cournot game in the market with a nonlinear (isoelastic) demand function. In our model, there are N competing firms featured by nonlinear cost functions, which enhances our model's resemblance to real-world scenarios. Firstly, we focus on the homogeneous case where firms' marginal costs change at equal rates.

A first-principles study on the promising thermoelectric properties of SnX (X = S, Se, Te) compounds.

SnSe has emerged as an outstanding thermoelectric material due to its exceptional performance. In this study, first-principles calculations are employed to investigate the thermoelectric properties of materials within the SnX family, where X can be either S, Se, or Te. Initially, we assessed the stability of SnX (X = S, Se, Te).

Impact of carbon emission trading system on green technology innovation of energy enterprises in China.

China proposed establishing a carbon emission trading market in its 12th Five-Year Plan to reduce carbon dioxide emissions through market mechanisms, promote the development of science and technology and help China become an environment-friendly country. To examine the impact of carbon emission trading on green technology innovation in Chinese energy enterprises, data from 1993 to 2020 were collected from 494 A-share-listed energy enterprises. Enterprises located in the pilot area of carbon emissions trading were assigned to the treatment group, while those in the non-pilot area were assigned to the control group.