Search Results (298)

The efficient recovery of rhenium (Re), a critical metal in high-tech industries, is essential to address its growing demand and reduce reliance on primary mining. In this study, we developed novel anion-exchange resins for the selective adsorption and recovery of Re(VII) ions from acidic solutions, simulating industrial by-products. The resins were synthesized from a vinylbenzyl chloride-co-divinylbenzene copolymer modified with aliphatic, heterocyclic, and aromatic weakly basic amines, selected from among bis(3-aminopropyl)amine (BAPA), 1-(2-pyrimidinyl)piperazine (PIP), thiosemicarbazide (TSC), 2-amino-3-hydroxypyridine (AHP), 1-(2-hydroxyethyl)piperazine (HEP), 4-amino-2,6-dihydroxypyrimidine (AHPI), and 2-thiazolamine (TA). The adsorption of Re on BAPA, PIP, and HEP resins obeyed the Langmuir model, and the resins exhibited high adsorption capacities, with maximum values reaching 435.4 mg Re g⁻¹ at pH 6. Furthermore, strong selectivity for ReO₄⁻ ions over competing species, including Mo, Cu, and V, was noted in solutions simulating the leachates of the by-products of Cu-Mo ores. Additionally, complete elution of Re was possible. The developed resins turned out to be highly suitable for the continuous-flow-mode adsorption of ReO₄⁻, revealing outstanding adsorption capacities before reaching column breakthrough. In this context, the novel anion-exchange resins developed offer a reference for further Re recovery strategies. Full article

The study investigates the contribution of technology (TECH), quantified by Internet penetration, in influencing tourism performance (TP) among the top ten touristic nations in Europe: France, Spain, Italy, Turkey, the United Kingdom, Germany, Greece, Austria, Portugal, and the Netherlands. Using panel data from 2000–2022, the study includes additional structural controls like environment quality, gross domestic production (GDP) per capita, exchange rate (ER), and safety index (SI). The Method of Moments Quantile Regression (MMQR) is employed to capture heterogeneous effects at different levels of TP, and Driscoll–Kraay standard error (DKSE) correction is employed to make the analysis robust against autocorrelation as well as cross-sectional dependence. Spectral–Granger causality tests are also conducted to check short- and long-run dynamics in the relationships. Empirical results are that TECH and SI are important in TP at all quantiles, but with stronger effects for lower-performing countries. Environmental quality (EQ) and GDP per capita (GDPPC) exert increasing impacts at upper quantiles, suggesting their importance in sustaining high-level tourism economies. ER effects are limited and primarily short-term. The findings highlight the need for integrated digital, environmental, and economic policies to achieve sustainable tourism development. The paper contributes to tourism research by providing a comprehensive, frequency-sensitive, and distributional analysis of macroeconomic determinants of tourism in highly developed European tourist destinations. Full article

This study investigates the effectiveness of the Xsens motion capture system in performing ergonomic analysis compared to traditional manual assessments by experts in the specific environment of assembly lines. A comprehensive literature review emphasizes the need to investigate the reliability of new, promising high-tech systems. The main objective was therefore to compare the Ergonomic Assessment Worksheet (EAWS) assessment approach performed with Xsens motion capture technology and Process Simulate V16 software with the manual method using EAWS digital prepared by experts in the controlled workflow. The greatest value of the research conducted lies in the novel integration of the state-of-the-art Xsens motion capture technology with the Process Simulate V16 software environment and the use of the licensed EAWS ergonomic method and Methods-Time Measurement Universal Analyzing System (MTM-UAS). The results are presented in the form of a case study. The results show a large similarity between the whole-body results and a large difference in the upper limb results, confirming the initial benefits of the Xsens equipment but also pointing to the need to verify its reliability on larger samples. The study highlights the potential of integrating Xsens motion capture data into ergonomic assessments and tuning of the assembly line to increase productivity and worker safety. Full article

Amid the rapid development of the digital economy, data elements—emerging as a new type of production factor—are gradually becoming a key resource for enhancing corporate efficiency and promoting high-quality development. The marketization of data elements is also steadily progressing and playing an increasingly important role. Based on data from Chinese A-share listed companies spanning 2007 to 2023, this study systematically evaluates the impact of data element marketization on corporate investment efficiency using a Double Machine Learning approach. The findings reveal that data element marketization significantly improves investment efficiency. Mechanism analysis further demonstrates that such improvement is primarily driven by reduced information dispersion, enhanced risk-bearing capacity, and improved operational efficiency. Heterogeneity analysis indicates that these effects are more pronounced for firms in high-tech industries, high growth potential firms, enterprises located in regions with strong digital infrastructure, and firms experiencing overinvestment problems. This study provides empirical evidence on how the marketization of data elements in China enhances economic outcomes, improving corporate investment decisions, which could serve as a reference for other countries undergoing digital transformation. Full article

In recent years, with the development of science and technology and the transformation of economic structures, rubidium and cesium have gradually become indispensable rare metal resources as important materials for high-tech industries. However, the relationship between supply and demand of resources is unbalanced, industrial demand is much higher than production, and the rubidium and cesium resources in hard rock minerals such as traditional pegmatite minerals are no longer enough to support global scientific and technological upgrading. There is therefore an urgent need to expand sources of resource extraction and recovery to meet market demand. This paper summarizes the current feasible technologies for extracting rubidium and cesium from pegmatite minerals, silicate minerals, salt lake brines and other potential resources. Full article

The rapid development and adoption of artificial intelligence (AI) technology has sparked debates about its implications for labor markets, yet the micro-level relationship between AI and labor share remains underexplored. Based on the theory of skill-biased technological change, this study aims to examine whether AI technology increases labor share by labor structure upgrading at the enterprise level. Using panel data for China’s listed companies from 2012 to 2022, this study tests this relationship using a two-way fixed effects model. The empirical results reveal that AI technology significantly increases labor share, with labor structure upgrading playing a mediating role in this relationship. Heterogeneity analysis reveals that the influence of AI technology on labor share is stronger for enterprises characterized by low labor market rigidity, high labor market supply, and talent policy support in external environments, as well as among labor-intensive, high-tech, and non-state-owned enterprises. Notably, this study finds that advancements in AI technology have achieved mutually beneficial outcomes of improving labor share and enhancing total factor productivity. Our research findings provide detailed empirical evidence for enterprises to formulate and implement AI strategies. Full article

Greenhouse horticulture plays an important role globally by producing nutritious fruits and vegetables with high resource use efficiency. Modern greenhouses are large-scale high-tech production factories that are increasingly data-driven, and where climate and irrigation control are gradually becoming more autonomous. This is enabled by technological developments and driven by shortages in skilled labor and the demand for improved resource use efficiency. In the Autonomous Greenhouse Challenge, it has been shown that controlling greenhouse cultivation can be done efficiently with intelligent algorithms. For an optimal strategy, however, it is essential that control algorithms properly account for crop responses, which requires appropriate sensors, reliable data, and accurate models. This paper presents the results of the 4th Autonomous Greenhouse Challenge, in which international teams developed six intelligent algorithms that fully controlled a dwarf tomato cultivation, a crop that is well-suited for robotic harvesting, but for which little prior cultivation data exists. Nevertheless, the analysis of the experiment showed that all teams managed to obtain a profitable strategy, and the best algorithm resulted a production equivalent to 45 kg/m²/year, higher than in the commercial practice of high-wire cherry tomato growing. The predominant factor was found to be the much higher plant density that can be achieved in the applied growing system. More difficult challenges were found to be related to measuring crop status to determine the harvest moment. Finally, this experiment shows the potential for novel greenhouse cultivation systems that are inherently well-suited for autonomous control, and results in a unique and rich dataset to support future research. Full article

Lithium, a critical element for clean energy and modern technologies, plays an indispensable role in advancing renewable energy storage, electric vehicles, and high-tech industries. The rapidly growing demand for lithium, along with its limited global production, has led to concerns about the sustainability of current extraction and processing technologies for efficient lithium recovery. This comprehensive review explores global trends in lithium processing, focusing on spodumene beneficiation and extraction techniques. While highlighting well-established conventional processes, such as dense media separation (DMS), flotation, high-temperature roasting, and acid or alkali treatment, it underscores the environmental and economic challenges of these processes, particularly when applied to low-grade lithium ores, which are increasingly being targeted to meet lithium demand. Innovative methods, such as microwave irradiation, are also explored for their potential to improve process efficiency, reduce energy consumption, and minimize environmental impact, offering promising pathways to overcome the limitations of traditional lithium recovery techniques. A significant contribution of this review is its focus on the largely untapped lithium resources of Kazakhstan, presenting geological insights and the potential for sustainable development. By addressing knowledge gaps and integrating technological, eco-friendly, and regional development perspectives, this study provides valuable insights for advancing lithium processing toward more sustainable and circular practices aligned with global climate and resource efficiency goals. Full article

The growing demand for sustainable food production has driven significant advancements in modern agriculture, including increasing interest in Controlled Environment Agriculture (CEA), a high-tech solution designed to provide fresh, local, and organic products. Although the integration of various technologies in agriculture continues to expand, many opportunities remain to improve environmental performance and operational efficiency. Recent advancements in Remote Sensing (RS) and Machine Learning (ML) offer promising tools for enhancing resource efficiency, improving sustainability, and optimizing processes across various agricultural settings. This study presents a bibliometric analysis of the application of Remote Sensing and Machine Learning in agriculture, highlighting publication trends, influential research contributions, and emerging themes in this interdisciplinary field. While the majority of the analyzed literature addresses general agricultural modernization, the growing relevance of RS and ML in artificial climate facilities and controlled environments has been evident in more recent research. Furthermore, we explore how RS and ML technologies contribute to real-time monitoring, precision agriculture, and decision-making in agriculture. Full article

Niobium, with its unique properties, plays a key role in high-tech industries, but its recovery from secondary sources remains poorly studied. The kinetics of niobium leaching from niobium-containing middlings obtained via the water treatment of dust chamber sublimations of titanium chlorinators is considered in this study. The leaching process was conducted using a fluoride–sulphuric acid solution. The experiments were performed at 25–90 °C in agitation mode. Kinetic data were analysed using compression-core and mixed-control models, which made it possible to establish the limiting stages of the process. A mixed mechanism, including a chemical reaction on the surface and diffusion through a layer of products with an activation energy of 30.05 kJ/mol, was established. The niobium recovery degree increased from 35.25 to 93.5% as the temperature increased, highlighting its effect on the process. The insoluble residue, rich in titanium, and the liquid phase with niobium and zirconium have the potential for further processing. The results provide the basis to optimise technologies intended to recover niobium from man-made raw materials, contributing to an increase in resource efficiency. Full article

New-quality productivity and industrial structure upgrading has become a primary area of concern with respect to regional economic transformation and sustainable development. Based on static panel data of 108 prefecture-level-and-above cities in the Yangtze River Economic Belt from 2013 to 2022, the projection pursuit model, coupling coordination degree model, and obstacle degree model were used to study the spatiotemporal patterns and key obstacle factors in the coupling of new-quality productivity and levels of industrial upgrading. Results show the following: (1) The average coupling coordination degree increased from 0.42 in 2013 to 0.53 in 2022, exhibiting a three-stage trend of “initial advancement, rapid growth, and high-level fluctuation”. (2) Regionally, a gradient pattern of “downstream leading, midstream following, and upstream catching up” persists, but regional gaps have narrowed significantly. (3) Spatially, the coupling coordination level shows a pattern of “high in the east, low in the west, led by the core, and breakthrough in the local area”, with significant positive aggregation characteristics. (4) The main obstacle factors across the entire area include digital patents (7.03%), green patents (7.03%), and the number of high-tech enterprises (6.96%), but the weights of the obstacle factors vary greatly across different areas. These findings provide scientific support for green transformation, regional integration, and sustainability-oriented industrial policy design in the Yangtze River Economic Belt. Full article

This study examines the impact of structural characteristics of agricultural holdings on their agricultural performance and contribution to rural development in EU countries over the past decade to identify potential measures to enhance rural development. The results of the paired samples t-test reveal a structural shift in EU agriculture between 2010 and 2020 toward larger, more productive, and capital-intensive farms alongside a decline in small-scale and subsistence farming, improved agricultural incomes, and rural economic growth. However, persistent challenges such as rural depopulation, declining employment, and ongoing poverty remain. A cluster analysis identified five distinct agricultural models and reflects some notable transitions: Eastern European countries increasingly moved toward mixed farming (e.g., Latvia, Lithuania, and Hungary) or large-scale commercial farming (e.g., the Czech Republic, Estonia, and Slovakia), subsistence and small-scale farming became more concentrated in Bulgaria and Romania, and Western and Northern countries maintained high levels of modernization, with Ireland progressing and the Netherlands standing out as a distinct high-tech agricultural model. The five distinct agricultural clusters identified underline the need for regionally tailored policies. Hierarchical regression shows that while improvements in agricultural performance, particularly increased labor productivity, contribute to rural GDP per capita growth, they have a limited impact on rural poverty. Therefore, enhancing sustainable rural development requires more comprehensive and integrated strategies that not only promote productivity-driven agricultural reforms and innovation in advanced systems but also address the specific needs of lagging countries through structural transformation, capacity building, and targeted support. Full article

In the era of new productive forces, the efficient utilization of industrial land in high-tech zones is critical for fostering technological innovation, intelligent manufacturing, and green development. However, constrained by limited land reserves, inefficient stock utilization, and sluggish industrial upgrading, high-tech zones must establish a scientific early warning mechanism for industrial land redevelopment. This study constructs a four-tier early warning system (normal, alert, warning, and response) based on three key dimensions: enterprise life cycle, enterprise–park compatibility, and industrial land use efficiency. Using the Jinan High-Tech Zone as a case study, this study conducts an empirical analysis of 360 industrial land parcels from 2020 to 2022, employing DEA, fixed effects models, GIS visualization, and MCDA methods. The results indicate a strong correlation between enterprise life cycle and land use efficiency, with significant spatial differentiation in enterprise–park compatibility. Efficient land use is concentrated in areas with well-defined functions and high industrial agglomeration. This study identifies 360 land use scenarios, with 12% classified as normal, 28% requiring monitoring, 52% requiring optimization, and 8% necessitating redevelopment. Based on these findings, a “warning–monitoring–regulation” closed-loop management model is proposed, providing decision-making support for dynamic land optimization and sustainable development in high-tech zones. Full article

The global and domestic divisions of labor have had a great influence on the economy and environment in China during the last decade. With the refinement of production processes, national value chains (NVCs) coexist with global value chains (GVCs), enabling regions to participate in dual value chains (DVCs) simultaneously. This study calculates the NVCs and GVCs participation of manufacturing sectors in China’s provinces. On this basis, this research adopts a fixed effects model to analyze the impact of GVCs and NVCs participation and their interaction effect on manufacturing upgrades and green development. The results show, first, that significant regional differences in GVCs participation exist among provinces in China. In comparison, provincial NVCs participation demonstrates fewer regional differences. Second, there are significant sectoral differences of GVCs participation in China’s manufacturing industry—high-tech manufacturing is more embedded than other manufacturing industries. The sectoral differences in NVCs participation are relatively small. Third, GVCs and NVCs participation and their interaction effect have significantly promoted the upgrading and green development of manufacturing sectors in provinces of China, and this impact exhibits significant heterogeneity across regions, industries, and NVCs participation modes. The conclusions of this study provide empirical evidence and policy recommendations for the upgrading and green development of China’s manufacturing industry. Full article

As a critical raw material, tungsten plays a broad role in machining, electronics, aerospace, and other high-tech industries. The extraction of tungsten from tungsten concentrates is a prerequisite for the production of high-purity products. Approximately 70% of China’s tungsten resources are in the form of scheelite. The extraction method of low-quality scheelite is crucial for the production application of the tungsten process as resources of high-quality wolframite are gradually being depleted. This article systematically reviews the processes and challenges faced in the hydrometallurgical process of scheelite concentrates and provides useful insights. Typical leaching processes for scheelite concentrate have shown excellent leaching efficiencies, with tungsten trioxide (WO₃) recoveries exceeding 90%. Alkaline leaching processes are promising, but temperature and pressure are crucial for this method. The sintering–leaching process is energy-consuming and costly. Meanwhile, leaching with hydrochloric acid (HCl) or sulfuric acid (H₂SO₄) often results in the formation of tungstic acid (H₂WO₄) on the mineral surface, which inhibits further leaching and leads to a low extraction rate. In contrast, the mixed-acid leaching method is more promising, with recovery close to 100%, a short process, and low-cost, and the acid leaching solution is recyclable. Full article