Search Results (125)

This study presents a detailed and comprehensive investigation into the macro-scale performance, strength gain mechanisms, environment and economic performance of graphene oxide (GO)-enhanced low-emission concrete. A comprehensive experimental program evaluated fresh and hardened properties, including slump retention, bleeding, air content, compressive, flexural, and tensile strength, drying shrinkage, and elastic modulus. Scanning Electron Microscopy (SEM), energy-dispersive spectroscopy (EDS), Thermogravimetric analysis (TGA) and proton nuclear magnetic resonance (¹H-NMR) was employed to examine microstructural evolution and early age water retention, confirming GO’s role in accelerating cement hydration and promoting C-S-H formation. Optimal performance was achieved at 0.05% GO (by binder weight), resulting in a 25% increase in 28-day compressive strength without compromising workability. This outcome is attributed to a tailored, non-invasive mixing strategy, wherein GO was pre-dispersed during synthesis and subsequently blended without the use of invasive mixing methods such as high shear mixing or ultrasonication. Fourier-transform infrared (FTIR) spectroscopy further validated the chemical compatibility of GO and PCE and confirmed the compatibility and efficiency of the admixture. Sustainability metrics, including embodied carbon and strength-normalized cost indices (USD/MPa), indicated that, although GO increased material cost, the overall cost-performance ratio remained competitive at breakeven GO prices. Enhanced efficiency also led to lower net embodied CO₂ emissions. By integrating mechanical, microstructural, and environmental analyses, this study demonstrates GO’s multifunctional benefits and provides a robust basis for its industrial implementation in sustainable infrastructure. Full article

Ni-based catalysts have been widely used in catalytic reactions by researchers due to their advantages such as abundant resources, high catalytic activity and lower prices than precious metals. However, the problems of easy agglomeration and poor dispersion of Ni-based catalysts have hindered their large-scale application. Therefore, it is necessary to select a suitable preparation method to reduce the agglomeration of the catalyst and improve its dispersion. In this paper, the Ni-NiAl₂O₄/tourmaline composite material was prepared by using the microwave hydrothermal reduction method. The most favorable conditions for preparing NiAl₂O₄/tourmaline are as follows: using TEOA as the additive, the microwave hydrothermal temperature is 220 °C, the calcination temperature is 800 °C, and the addition amount of tourmaline is 7.4 wt.%. NiAl₂O₄ has a good dispersion over the surface of tourmaline support and the optimal NiAl₂O₄/tourmaline catalyst exhibits a specific surface area of 106.5 m²/g. Metallic nickel was reduced at 650 °C to further obtain Ni-NiAl₂O₄/tourmaline composites. Finally, the Ni-NiAl₂O₄/tourmaline composites showed significantly improved catalytic dry reforming of methane (DRM) activity compared to Ni-NiAl₂O₄ sample under low-temperature conditions (500–600 °C), meaning that the tourmaline carrier could effectively optimize the low-temperature catalytic performance of Ni-NiAl₂O₄. Full article

With the rapid development of e-commerce, Return Freight Insurance (RFI) has emerged as a vital tool for retailers and customers to mitigate the financial burden posed by high return rates in online shopping. This paper investigates the strategic decision-making of RFI providers (insurers), examining whether they should offer fixed-compensation insurance at a lower price or full-coverage insurance at a higher price under varying market conditions. Specifically, we develop game-theoretic models to analyze insurers’ strategic decisions in both monopoly and duopoly markets, accounting for customer return cost and product mismatch probability heterogeneity. Our findings reveal that in a monopoly market, when customer return costs are relatively low and concentrated, insurers benefit from offering fixed compensation insurance (i.e., pre-set reimbursement amounts) at a lower price to attract a broader customer base. By contrast, when return costs are more dispersed and higher, full-coverage insurance (which reimburses actual freight costs) becomes more profitable, as the insurer can utilize its flexible pricing power to attract higher-paying customer segments. In a duopoly market, customer return cost heterogeneity significantly influences market equilibrium. When heterogeneity is high, full-coverage insurance dominates, as insurers can leverage precise market segmentation to justify higher premiums. Conversely, when return costs are more uniform, fixed compensation insurance is preferred for its affordability, appealing to a wider range of customers. Full article

This study investigates whether and how the complexity of derivative use influences the stock price crash risk in China’s capital market, a critical question given the growing use of derivatives in emerging economies where governance structures and disclosure standards vary widely. While prior research has examined the binary effects of derivative usage, limited attention has been paid to the multidimensional complexity of such instruments and its informational consequences. Using a novel hand-collected dataset of annual reports from Chinese A-share-listed firms between 2010 and 2023, we develop and implement new indicators that capture both the economic complexity (diversity and scale) and accounting complexity (reporting dispersion and fair-value hierarchy) of derivative use. Our analysis shows that higher complexity is associated with a significantly lower likelihood of stock price crashes. This effect is especially pronounced in non-state-owned firms and those with weaker internal-control systems, suggesting that derivative complexity can enhance information transparency and serve as a substitute for other governance mechanisms. These findings challenge the conventional view that complexity necessarily increases opacity and highlight the importance of disclosure quality and institutional context in shaping the market consequences of financial innovation. Full article

Residential mobility within cities reflects the spatio-temporal patterns of individual or household relocation behaviors and serves as an effective tool for interpreting urban socio-spatial differentiation from a micro-level perspective. Newly employed college graduates (NECGs) have become the second-largest migrating population in China. This study selects Guangzhou, a megacity, as the study area and utilizes data from the “Guangzhou New Citizens’ Residential Mobility Survey” conducted in 2023. It applies spatio-temporal systems and the spatio-temporal path method based on time geography to explore the residential mobility trajectories of NECGs in Guangzhou. In addition, the study uses a logistic regression model to explore the influencing factors. The findings indicate that NECGs frequently move across districts, showing no significant patterns of concentration or dispersion. However, residential location choices vary considerably across educational levels and household registration natures (Hukou), and as the duration of residence in Guangzhou increases, the probability of residential mobility among NECGs across all educational levels shows a declining trend. Specifically, marital status (life course attributes), housing prices and medical facilities (housing attributes), and job type (socioeconomic attributes) emerge as critical factors influencing residential mobility. By providing a foundation for urban planning policies, this study aims to support the settlement and well-being of NECGs while promoting high-quality urban development in Guangzhou. Full article

With the continuous integration of globalization and financial markets, the linkage of global financial risks has increased significantly. This study examines the risk spillover effects and transmission dynamics among the financial markets in G20 countries, which together represent over 80% of global GDP. With increasing globalization and the interconnectedness of financial markets, understanding risk transmission mechanisms has become critical for effective risk management. Previous research has primarily focused on price volatility to measure financial risks, often overlooking other critical dimensions such as liquidity, credit, and operational risks. This paper addresses this gap by utilizing the vector autoregressive (VAR) model to explore the spillover effects and the temporal and spatial characteristics of risk transmission. Specifically, we employ global and local Moran indices to analyze spatial dependencies across markets. Our findings reveal that the risk linkages among the G20 financial markets exhibit significant time-varying characteristics, with spatial risk distribution showing weaker dispersion. By constructing a comprehensive financial risk index system and applying a network-based spillover analysis, this study enhances the measurement of financial market risk and uncovers the complex transmission pathways between sub-markets and countries. These results not only deepen our understanding of global financial market dynamics but also provide valuable insights for the design of effective cross-border financial regulatory policies. The study’s contributions lie in enriching the empirical literature on multi-dimensional financial risks, advancing policy formulation by identifying key risk transmission channels, and supporting international risk management strategies through the detection and mitigation of potential contagion effects. Full article

This study analyses how the intensive use of short-term rentals (STRs) in the tourism sector contributes to the transformation and touristification of rural areas in mature tourist destinations, using the island of Mallorca, Spain, as a case study. Based on growth machine theory, the analysis innovatively examines the factors driving the expansion of STRs in rural spaces, with a focus on economic, social, and territorial dynamics. The research hypothesis is that the proliferation of STRs acts as a key element in rural touristification. Using a combination of spatial and temporal indicators, the study identifies patterns of intensification and dispersion of STRs in rural areas, offering a comparison with other Mediterranean destinations, particularly in Spain. The results show that STRs have generated significant spatial impacts, leading to the displacement of agricultural land use and increasing tensions within local communities, mainly due to rising housing prices. The study highlights the need to implement spatial planning policies that restrain the uncontrolled expansion of STRs, ensure sustainable tourism planning, and promote housing policies that protect residents from the negative effects of touristification. Various scenarios for the evolution of STRs are proposed depending on their regulation. Full article

Despite free access to complete information regarding hotel quality and reference prices, consumers perceive significant price differences across different online platforms. We explore how perceived price dispersion on online travel agency platforms influences consumer purchase intention through mental account theory and propose a psychological mechanism explaining why consumers may tolerate and even embrace price discrepancies. Study 1 employs a scenario-based experiment that manipulates differing levels of price dispersion for the same hotel booking, demonstrating that higher PPD significantly amplifies perceived transaction utility and, in turn, acquisition utility. Study 2 corroborates these findings through an online survey with judgment sampling, highlighting that consumers—despite access to comprehensive OTA information—are often motivated, rather than deterred, by price discrepancies; multiple variable combinations were tested to ensure robust findings. This study challenges traditional marketing theories suggesting that price dispersion signals market unfairness and reduces consumers’ purchasing intention; instead, it mentally stimulates consumers. This perception enhances transaction and acquisition utility, positively impacting purchase intention. We also offer a robust model for mechanism study and provide insights for leveraging price dispersion as a cost-less promotional strategy, potentially increasing consumer engagement without additional marketing expenditure. We contribute to the literature by integrating the mental account theory into the context of online marketplaces and developing a price dispersion model with psychological utility in the consumer decision-making process. Full article

This study identified the main factors affecting car selection decisions through discrete choice experiments based on a large dataset collected in four European countries in 2023 using stated choice questionnaires. The choice set includes six current and popular car powertrains with factors related to vehicle features, user characteristics, and specific geographical contexts, which can influence the adoption of vehicles with electrified powertrains. An easily applicable multinomial logit model was first proposed to explore the effects of selected attributes and the model’s ability to reproduce user preferences with different incentive policies, geographical contexts, and energy prices. A mixed logit model and a segmented multinomial logit model were introduced to consider the sample’s heterogeneity. The first captures the preference dispersion among respondents related to incentives and operational costs. The second, which specifically classifies users based on car market segments, showed a greater variation in factors related to the purchase cost and battery range. The models estimate the weight of nine factors, offering support for targeted policy recommendations. Cost-related factors confirm their relevance in choices, and the analysis shows that users who want to enhance their vehicle range by 1 km are willing to pay approximately EUR 80. Full article

This study investigates the water rights markets across various regions of Chile, encompassing a wide range of geographic and climatic conditions. Utilizing 10,345 transaction records from 1990 to 2014 provided by the national authority for the regulation of utilities, this dataset covers data from 12 of the 15 regions of Chile at the time and 26 basins across the country. The comprehensive nature of this study, which has not been previously achieved with such a reliable and extensive dataset, aims to analyze price determinants in these markets. This novel approach allows us to understand the global performance of water markets. Key considerations include climatic variables such as annual precipitation and maximum temperatures, regional GDP per capita, and factors like mining industrialization level, transaction size, rurality index, and the existence of scarcity decrees. Employing a hedonic model, particularly a quantile model with robust errors, the research assesses the impact of these variables on observed prices. The findings reveal market heterogeneity with variables such as precipitation, geopolitical, and demographic characteristics, industrialization, and transaction volume significantly influence water rights prices. Interestingly, water scarcity decrees, intended to minimize drought damages, paradoxically resulted in lower water right prices. The study also highlights a predominant corporate presence and sector-specific purchasing geographic patterns, particularly in the agricultural and mining sectors. These insights are critical for ecosystem services valuation and for informing sustainable water resource management in the face of climate change and natural resource governance challenges. Full article

Carbon price forecasting and pricing are critical for stabilizing carbon markets, mitigating investment risks, and fostering economic development. This paper presents an advanced decomposition-integration framework which seamlessly integrates econometric models with machine learning techniques to enhance carbon price forecasting. First, the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) method is employed to decompose carbon price data into distinct modal components, each defined by specific frequency characteristics. Then, Lempel–Ziv complexity and dispersion entropy algorithms are applied to analyze these components, facilitating the identification of their unique frequency attributes. The framework subsequently employs GARCH models for predicting high-frequency components and a gated recurrent unit (GRU) neural network optimized by the grey wolf algorithm for low-frequency components. Finally, the optimized GRU model is utilized to integrate these predictive outcomes nonlinearly, ensuring a comprehensive and precise forecast. Empirical evidence demonstrates that this framework not only accurately captures the diverse characteristics of different data components but also significantly outperforms traditional benchmark models in predictive accuracy. By optimizing the GRU model with the grey wolf optimizer (GWO) algorithm, the framework enhances both prediction stability and adaptability, while the nonlinear integration approach effectively mitigates error accumulation. This innovative framework offers a scientifically rigorous and efficient tool for carbon price forecasting, providing valuable insights for policymakers and market participants in carbon trading. Full article

Chloride binding technology can effectively reduce the content of free chloride ions in seawater (used for cementitious materials), thereby extending the service life of seawater concrete structures. Currently, affordable and highly dispersed nanomaterials that can enhance the chloride binding capability of seawater cement are finite. This paper presents the first experimental study on N-doped graphene quantum dots (NGQDs), an innovative carbon nanomaterial with low price and high dispersibility, to strengthen the mechanical and chloride binding capabilities of seawater cement. Concretely, NGQDs are prepared through the hydrothermal process. The morphology and structure of NGQDs are measured by TEM, AFM, FTIR, and XPS. And the strengths and chloride binding performance of different specimens are analyzed by compressive/flexural strength tests and chloride adsorption equilibrium tests. The phase compositions of various specimens are analyzed by XRD, TGA/DTG, and SEM. The consequences indicate that the unique structure of the prepared NGQDs endows them with excellent water solubility and dispersibility. Notably, the introduction of NGQDs enhances the mechanical performance of seawater cement and 0.05 wt.% NGQDs have the greatest improvement effect. The compressive and flexural strengths of seawater cement containing 0.05 wt.% NGQDs increase by 8.21% and 25.77% after 28 d curing, respectively. Additionally, the seawater cement containing 0.2 wt.% NGQDs have the best chloride binding capability and are 41.08% higher than the blank group. More importantly, the chloride binding mechanism is that NGQDs accelerate seawater cement hydration, resulting in an increased formation of hydrated calcium silicate (C–S–H) and Friedel’s salt (Fs), thereby strengthening the physisorption and chemical combination of chloride. This study highlights an inexpensive and highly dispersible nanomaterial to heighten the stability of seawater concrete structures, opening up a new path for the better utilization of seawater resources. Full article

According to the Host Manipulation Hypothesis, parasites modify the phenotype of their host to enhance host–host transmission and thereby increase fitness. Metacercarial infection of some amphibians changes host behavior, including locomotion, and thereby enhances predation by the definitive host. To further test this hypothesis, it is first necessary to determine whether a parasite actually modifies a host’s phenotype. In the southern Appalachian Mountains of the US, metacercariae of the trematode Metagonimoides oregonensis (Price, 1931) encyst in the musculature of its second intermediate host, the salamander Desmognathus amphileucus Bishop, 1941. Metacercarial infections of musculature in fish negatively affect host swimming performance. Therefore, we tested the hypothesis that infection by M. oregonensis affects walking in the aquatic larvae of D. amphileucus. We compared this mode of locomotion between infected and uninfected larvae by placing them in 1 m troughs of water and allowing them to wander freely until they stopped. Non-parametric (Kaplan–Meier) survival analysis determined that infected salamanders stopped significantly sooner than uninfected ones. Because infected salamanders move less, the presence of this parasite may contribute to genetic divergence in these salamanders by slowing dispersal and concomitant gene flow. Our results suggest that macroparasites can potentially modify a host’s behavior with biological consequences beyond enhancement of parasite transmission. Full article

Direct Methanol Fuel Cell (DMFC) is a powerful system for generating electrical energy for various applications. However, there are several limitations that hinder the commercialization of DMFCs, such as the expense of platinum (Pt) at market price, sluggish methanol oxidation reaction (MOR) due to carbon monoxide (CO) formation, and slow electrooxidation kinetics. This work introduces carbon nanocages (CNCs) that were obtained through the pyrolysis of polypyrrole (Ppy) as the carbon source. The CNCs were characterized using BET, XRD, HRTEM, TEM, SEM, and FTIR techniques. The CNCs derived from the Ppy source, pyrolyzed at 750 °C, exhibited the best morphologies with a high specific surface area of 416 m²g⁻¹, allowing for good metal dispersion. Subsequently, PtRu catalyst was doped onto the CNC-Ppy750 support using chemical reduction and microwave-assisted methods. In electrochemical tests, the PtRu/CNC-Ppy750 electrocatalyst demonstrated improved CO tolerance and higher performance in MOR compared to PtRu-supported commercial carbon black (CB), with values of 427 mA mg⁻¹ and 248 mA mg⁻¹, respectively. The superior MOR performance of PtRu/CNC-Ppy750 was attributed to its high surface area of CNC support, uniform dispersion of PtRu catalyst, and small PtRu nanoparticles on the CNC. In DMFC single-cell tests, the PtRu/CNC-Ppy750 exhibited higher performance, approximately 1.7 times higher than PtRu/CB. In conclusion, the PtRu/CNC-PPy750 represents a promising electrocatalyst candidate for MOR and anodic DMFC applications. Full article

With the development of an energy sector based on renewable primary sources, structural changes are emerging for the entire national energy system. Initially, it was estimated that energy generation based on fossil fuels would decrease until its disappearance. However, the evolution of ${CO}_2$ capture capacity leads to a possible coexistence for a certain period with the renewable energy sector. The paper develops this concept of the coexistence of the two systems, with the positioning of green hydrogen not only within the renewable energy sector but also as a transformation vector for carbon dioxide captured in the form of synthetic fuels, such as $C{H}_4$ and $C{H}_{3}OH$. The authors conducted pilot-scale research on ${CO}_2$ capture with green $H_2$, both for pure (captured) ${CO}_2$ and for ${CO}_2$ found in combustion gases. The positive results led to the respective recommendation. The research conducted by the authors meets the strict requirements of the current energy phase, with the authors considering that wind and solar energy alone are not sufficient to meet current energy demand. The paper also analyzes the economic aspects related to price differences for energy produced in the two sectors, as well as their interconnection. The technical aspect, as well as the economic aspect, of storage through various other solutions besides hydrogen has been highlighted. The development of the renewable energy sector and its demarcation from the fossil fuel energy sector, even with the transcendent vector represented by green hydrogen, leads to the deepening of dispersion aspects between the electricity sector and the thermal energy sector, a less commonly mentioned aspect in current works, but of great importance. The purpose of this paper is to highlight energy challenges during the current transition period towards climate neutrality, along with solutions proposed by the authors to be implemented in this phase. The current stage of combustion of the $C{H}_4-H_2$ mixture imposes requirements for the capture of the resulting ${CO}_2$. Full article