Driving job satisfaction through inclusive knowledge management: a focus on learning and communication in diverse workplaces.

Background: This study examines the impact of knowledge management practices (KMP) on job satisfaction, focusing on the mediating roles of learning opportunities and communication quality. It aims to provide insights into how effectively KMP can enhance employee satisfaction in Pakistan's IT sector.

Method: The research utilizes cross-sectional data collected from 345 IT sector employees in Pakistan.

Intelligent shipping: integrating autonomous maneuvering and maritime knowledge in the Singapore-Rotterdam Corridor.

Designing safe and reliable routes is the core of intelligent shipping. However, existing methods for industrial use are inadequate, primarily due to the lack of considering company preferences and ship maneuvering characteristics. To address these challenges, here we introduce a methodological framework that integrates maritime knowledge and autonomous maneuvering model.

Utilizing large-scale human mobility data to identify determinants of physical activity.

Analyzing the habits of exercisers is crucial for developing targeted interventions that can effectively promote long-term physical activity behavior. While much of existing literature has focused on individual-level factors, there is a growing recognition of the importance of examining how broader determinants impact physical activity. In this study, we analyze large-scale human mobility data from over 20 million individuals to investigate how visits to various locations, such as cafes and restaurants, influence visits to fitness centers.

Intellectual capital, digital transformation and firms' financial performance: Evidence from ecological protection and environmental governance industry in China.

As the pace of enterprise digital transformation accelerates, intellectual capital (IC) has become a core driving force of gaining market competitive advantages and enhancing value creation capabilities. The paper aims to investigate the impact of IC and its components on financial performance of Chinese ecological protection and environmental governance companies during 2018-2021. In addition, the moderating effect of digital transformation between them is examined.

Deep eutectic solvent induced silver-gel as a flexible SERS substrate for sensitive detection of antibiotics under low temperature conditions.

Antibiotic residues pose a significant threat to global health. Traditional detection methods for antibiotics are cumbersome, time-consuming and often incapable of achieving non-destructive detection at low temperatures. This research introduces a groundbreaking innovation in antibiotic detection: a flexible Surface-Enhanced Raman Scattering substrate based on a silver composite deep eutectic solvent (DES) gel, specifically engineered for low-temperature antibiotic detection.

ESG introduction mechanism of construction firms based on Bayesian network coupled with machine learning: Evidence from Zhengzhou.

Chinese construction enterprises are at a pivotal point in their transition to sustainable development, with Environmental, Social, and Governance (ESG) emerging as a key driver. However, limited understanding of ESG mechanisms hampers effective management strategies. To address this challenge, this study constructs an ESG introduction mechanism framework based on Bayesian networks and machine learning algorithms.

The synergies of air quality monitoring program: Information disclosure and pollution control.

To deal with the increasingly severe climate crisis and environmental pollution, China launched a nationwide real-time air quality monitoring program in three batches, a milestone moment in its environmental governance history. Using the time-varying difference-in-differences model, this study explores the synergies of this program across 284 cities from 2009 to 2019. The findings are as follows: (1) With environmental information disclosed, the national air quality monitoring program can reduce the outdoor fine particulate matter concentration by an overall effect of 3.

Do market-based environmental regulations always promote enterprise green innovation commercialization?

Motivated by increasingly strengthened market-based environmental regulations, enterprises intend to pursue both pollution reduction and competitive edge through developing green innovation. Although the volume of green innovation has increased substantially, some of them are not successfully commercialized to pay rewards for enterprises. Hence, how market-based environmental regulations affect enterprise green innovation commercialization is urgently to be explored.

Zero-Shot Traffic Identification with Attribute and Graph-Based Representations for Edge Computing.

With the proliferation of mobile terminals and the rapid growth of network applications, fine-grained traffic identification has become increasingly challenging. Methods based on machine learning and deep learning have achieved remarkable results, but they heavily rely on the distribution of training data, which makes them ineffective in handling unseen samples. In this paper, we propose AG-ZSL, a zero-shot learning framework based on traffic behavior and attribute representations for general encrypted traffic classification.

Effects of Calcium-Oxide-Modified Biochar on the Anaerobic Digestion of Vacuum Blackwater.

The increasing global population and urbanization have led to significant challenges in waste management, particularly concerning vacuum blackwater (VBW), which is the wastewater generated from vacuum toilets. Traditional treatment methods, such as landfilling and composting, often fall short in terms of efficiency and sustainability. Anaerobic digestion (AD) has emerged as a promising alternative, offering benefits such as biogas production and digestate generation.

Tailoring Structural, Emulsifying, and Interfacial Properties of Rice Bran Protein Through Limited Enzymatic Hydrolysis After High-Hydrostatic-Pressure Pretreatment.

We carried out limited enzymatic hydrolysis with trypsin on rice bran protein (RBP) pretreated by high hydrostatic pressure (HHP) in this study. The effects of the degree of hydrolysis (DH) on the structural and emulsifying properties were investigated. The results indicated that the molecular structure of RBP changed after limited enzymatic hydrolysis.

The intelligent brain and the energy heart: Synergistic evolution of artificial intelligence and energy storage technology in China.

In the context of China's ongoing industrial revolution and technological transformation, there is a growing demand for advanced energy management solutions and the increasing role of artificial intelligence in various industries. This paper aims to explore how artificial intelligence (AI) and Energy Storage Technology (EST) interact and co-evolve. Utilizing a full-sample Granger causality test, we identified significant interactions between AI and EST.

Can strengthening digital infrastructure enhance productivity in the cultural industry? evidence from Tibet.

This study, grounded in the Total Factor Productivity (TFP) theoretical framework, examines the impact of digital infrastructure on the productivity of Tibet's cultural industry from 2011 to 2021. It aims to uncover how the innovative allocation of production factors can enhance new-quality productivity. The core aspect of new-quality productivity is the improvement of TFP, with digital infrastructure promoting the cultural industry's development by optimizing industrial agglomeration, improving logistics efficiency, and reducing the urban-rural consumption gap.

The Mechanisms of Inclusive Leadership on Newcomers' Proactive Socialization Behaviors-An Exploration Based on the Proactive Motivation Model.

This study advances newcomers' socialization research by identifying and investigating the antecedents of newcomers' proactive behaviors, a perspective often overlooked within the current studies, which primarily focuses on the outcomes of such behaviors. Based on the proactive motivation model, our core hypothesis is that inclusive leadership allows newcomers to experience psychological changes in control beliefs (can-do motivation), state promotion focus (reason-to motivation), and positive affect (energized-to motivation), which are stimulated following proactive behaviors. We further consider an individual values variable-individual power distance orientation-as the boundary condition on the influence of inclusive leadership.

Approach or Avoidance? The Mechanisms Underlying the Impact of Community Goal Orientation on Residents' Waste Separation Recycling Behaviors.

Amidst the vigorous pursuit of sustainable development, the significance of community management has become increasingly evident. This study, anchored in goal orientation theory, delineated a conceptual model that elucidated the influence of community goal orientation on residents' waste separation recycling behaviors. Utilizing a longitudinal study design combined with self-report methods, data comprising 871 paired observations from 166 residents were collected and analyzed via multilevel structural equation modeling to test the proposed hypotheses.

Analysis of the Spatiotemporal Heterogeneity and Influencing Factors of Regional Economic Resilience in China.

This study estimates regional economic resilience in China from 2000 to 2022, focusing on economic resistance resilience, recovery resilience, and reorientation resilience. The entropy method, kernel density estimation, and spatial Durbin model are applied to examine the spatiotemporal evolution and influencing factors. The results show significant spatial clustering, with stronger resilience in the east and weaker resilience in the west.

A Task-Related EEG Microstate Clustering Algorithm Based on Spatial Patterns, Riemannian Distance, and a Deep Autoencoder.

Background: The segmentation of electroencephalography (EEG) signals into a limited number of microstates is of significant importance in the field of cognitive neuroscience. Currently, the microstate analysis algorithm based on global field power has demonstrated its efficacy in clustering resting-state EEG. The task-related EEG was extensively analyzed in the field of brain-computer interfaces (BCIs); however, its primary objective is classification rather than segmentation.

Satisfied with the worst health outcomes or unsatisfied with the best: explaining the divergence between good patient-reported outcomes and low satisfaction and vice versa among knee arthroplasty patients - a retrospective cohort study.

Objectives: Total knee arthroplasty (TKA) is an effective treatment for patients with end-stage knee osteoarthritis but some patients exhibit a discrepancy between patient-reported outcomes (PROs) and patient satisfaction (PS). This study aims to identify predictors for patients reporting unfavorable PROs but high PS and vice versa.

Materials And Methods: This retrospective cohort study categorized patients from nine German hospitals into four groups based on (i) whether they achieved a minimal clinically important difference (MCID) in knee functionality, measured with a joint-specific PRO from admission to 12-month post-surgery; and (ii) whether they were satisfied at 12 months post-surgery.

Retraction Note: Assessment of green economic efficiency in China using analytical hierarchical process (AHP).

[This retracts the article DOI: 10.1007/s00500-021-06507-5.].

Modern Technology's role in accounting cost calculation of industrial enterprises: Informatization as a key strategy to improve management efficiency.

The study aims to address challenges encountered by modern industrial enterprises, including inefficient accounting cost calculation, delayed information acquisition, and untimely management decisions. By comprehensively applying modern management, information technology, and cost control methods, this study constructs a real-time cost control model to optimize industrial enterprises. Firstly, the model employs mixed integer linear programming (MILP) to optimize production processes through mathematical modeling.

Is digital-green synergy the future of carbon emission performance?

Amid the new industrial revolution, digital technology and green finance play pivotal roles in shifting towards a low-carbon economy. This paper establishes a coherent research framework by integrating digital technology, green financing, and carbon emission performance. Utilizing a multifaceted dataset that combines provincial panel data with corporate listings databases, this study evaluates the development of green finance using a hybrid weighing methodology that merges the analytical hierarchy process (AHP) with the spatial-temporal entropy weight method.

Europe's extra-territorial mineral trade and clean energy metamorphosis in a landscape of multifaceted risks.

Despite modest reserves of energy transition minerals (ETMs) like copper, nickel, and aluminium, European nations largely depend on imports, a dynamic often marred by financial uncertainties, price volatility, and geopolitical tensions. The purpose of this study is to investigate the response of extra-territorial ETM imports to the clean energy objectives of 24 European nations, taking into account financial stress, mineral price volatility, and geopolitical instability. We analyse monthly data from January 2005 to October 2022, using the quantiles via moments (QvM) and the linear models multiway fixed effects (LMFE) approaches to account for heterogeneity, spatial dependence, heteroscedasticity, and endogeneity in the data.

How digital leadership adds affective commitment of new generation employees: an affective events perspective.

How do leaders' responses to the digital era affect new generation employees' affective commitment? As digital leaders have led to new ways of distributing digital resources and building virtual relationships, employees are facing a shift in the way of interaction, which influences their affective response to organizations. This study aims to understand how digital leaders interact with new generation employees to influence changes in employees' affective commitment to organizations. We have developed a chain mediating model and tested it on data collected from 408 new generation employees working in China.