Artiles
Open Access
Article
28 July 2026Digital Economy and Regional Carbon Equity: Evidence from Chinese Cities
Regional carbon equity reflects the spatial alignment between carbon-emission responsibility and ecological carrying capacity, and represents an important dimension for understanding the distributive consequences of low-carbon transitions. As the digital economy becomes increasingly embedded in resource allocation, technological innovation, and environmental governance, whether and how it reshapes regional carbon equity remains insufficiently examined. Using panel data for 281 Chinese cities from 2010 to 2023, this study constructs a city-level carbon equity index and employs two-way fixed-effects models, mechanism tests, and a spatial Durbin model to investigate the effect of the digital economy on carbon equity, its transmission channels, and its spatial spillover effects. The results show that carbon equity in Chinese cities has improved slowly over time, although regional disparities remain pronounced and significant “high–high” and “low–low” spatial clustering patterns persist. The digital economy significantly improves urban carbon equity, with the strongest effect observed in central China. Mechanism tests indicate that the digital economy enhances carbon equity mainly by promoting industrial structure upgrading, stimulating green technological innovation, and strengthening market integration. Further spatial analysis shows that the digital economy improves carbon equity within local cities but exerts a negative spillover effect on neighboring cities, revealing a spatial pattern of “local promotion and neighboring suppression”. This study extends the literature on the environmental consequences of the digital economy by introducing a regional carbon equity perspective. It provides policy implications for optimizing the spatial allocation of digital resources, improving interregional coordination in low-carbon governance, and advancing a more equitable low-carbon transition.
Open Access
Article
28 July 2026Selective Interfacial Separation of Lithium-Ion Battery Cathodes by a Chelator-Engineered Deep Eutectic Solvent: Foil Liberation, Black-Mass Purity, and Process Windows
Direct recycling of spent lithium-ion batteries requires selective dissociation of the cathode coating on the aluminum current collectors while minimizing cross-contamination of the recovered fractions. In this study, a chelator-based deep eutectic solvent (ChelaDES) made of levulinyl hydroxamic acid, glyceric acid, and trimethyl (2-methoxyethyl) ammonium chloride was designed as a low-temperature solvent for the selective interfacial separation of LCO, LFP, and NCA cathodes. The method uses four complementary key performance indicators (KPIs) as interfacial separation performance measures: active material removal, mass removed per unit area, bare-Al exposure, and delamination severity score. LCO showed the fastest response, reaching 93.7% active-material removal and >99% bare-Al exposure at 90 °C for 60 min. NCA showed intermediate behavior, reaching approximately 92.5% removal and 82% bare-Al exposure, while LFP exhibited threshold-controlled delamination, reaching 90.8% removal but only 66% bare-Al exposure under the same conditions. Among the kinetic models tested, the PSO-Arrhenius model provided the best overall fit for process comparison, giving apparent activation energies of 25.5, 26.5, and 28.5 kJ·mol−1 for LCO, NCA, and LFP, respectively. A strong correlation was observed for all chemistries between the removed mass per area and bare-Al exposure, which proves to be a useful, rapid quantitative proxy of foil liberation. Further purification studies with SEM-EDXS, XPS, and TGA/DTG suggested that the recovered black mass contained minimal impurities with minimal Al/Cu carryover (<0.1 wt%) and that the aluminum foil remained largely intact. Process heatmaps define the chemistry-specific operating windows, demonstrating that selective interfacial weakening, not bulk dissolution, controls separation. The process, therefore, acts as an upstream selective delamination and purification step, producing cleaner recovered black mass while preserving the current collector.
Open Access
Article
28 July 2026A Framework for Quantifying Autonomy in Robotic Systems
Although autonomous functioning facilitates the deployment of robotic systems in operating domains that support limited to no human oversight, establishing correspondence between task requirements and a system’s autonomous performance is still an open challenge. Several techniques for characterizing operating domains and/or quantifying autonomy have been proposed over the last three decades, however, to our knowledge, these have no discernment of sub-mode features of variation of autonomy, and some are based on metrics that are susceptible to the Goodhart’s law. This paper introduces a capability-based quantitative autonomy assessment framework for fully autonomous systems. The formulation of the framework started by establishing robot task characteristics from which three autonomy metrics, namely an essential capability set, reliability, and responsiveness, were derived. The characteristics were founded on the realization that robots ultimately replace human skilled workers, from which a relationship between human job and robot task characteristics was established. Additionally, mathematical formulations relating metrics to autonomy are also presented. To emphasize the fact that autonomy is not just a question of existence, but also one of performance of a capability, the framework represents it as a two-part measure, of level and degree of autonomy. Usage of the framework has been demonstrated on two case studies, namely an autonomous vehicle at an on-road dynamic driving task and the DARPA Subterranean Challenge analysis. The framework provides not only a tool for quantifying autonomy and monitoring the integrity of systems, but also a regulatory interface and common language for autonomous systems’ developers and users.
Open Access
Article
24 July 2026Lanthanum-Modified Activated Alumina for Selective Removal of Fluoride from Phosphogypsum Leachate
Fluoride-rich phosphogypsum leachate is a challenging industrial wastewater because of its low pH, high ionic strength, and the presence of competing anions. In this study, lanthanum-modified activated alumina (La-AA) was prepared and evaluated as a selective adsorbent for the removal of fluoride from complex phosphate-industry wastewater. The results showed that La modification improved the adsorption performance of activated alumina, and the 10% La-AA sample exhibited the best fluoride removal behavior among the tested materials. Kinetic and thermodynamic analyses indicated that fluoride adsorption on La-AA was more favorable than on pristine activated alumina and proceeded spontaneously and endothermically under the tested conditions. In competitive adsorption tests, La-AA maintained better fluoride uptake than unmodified activated alumina in the presence of chloride, sulfate, and phosphate, demonstrating improved matrix tolerance. When applied to authentic phosphogypsum leachate, the optimized La-AA reduced fluoride concentration from 9.67 mg·L−1 to 0.58 mg·L−1, below the WHO guideline value. These results suggest that La modification is a practical strategy to improve the selectivity and applicability of activated alumina for fluoride removal in complex industrial process water.
Open Access
Article
24 July 2026Statistical Theatre: Misinterpretation of Quantitative Evidence in the Courtroom
The increasing use of quantitative evidence in legal proceedings reflects a broader shift towards data-informed forms of proof. Statistical analyses, probability estimates, and forensic calculations are frequently presented as objective indicators of truth; however, their evidential value depends not on the mathematics itself, but on how the relationships they describe are interpreted. This paper examines the misinterpretation of quantitative evidence in courtroom settings, arguing that numerical outputs are often treated as conclusions rather than as components of structured inference. Focusing on conditional probability, the prosecutor’s fallacy, base rate neglect, witness testimony, and DNA evidence, the paper demonstrates how common errors arise from a failure to engage with the conditional and relational nature of probabilistic reasoning. Consistent with earlier work highlighting the interpretive limits of quantitative evidence, the analysis of key cases, including the Sally Clark case and People v Collins, together with contemporary examples drawn from forensic science and algorithmic decision-making, demonstrates how numerical evidence can assume persuasive authority that exceeds its probative value when underlying assumptions are not made explicit.Building on established scholarship concerning the persuasive authority of numerical evidence, expert testimony, and probabilistic reasoning in legal decision-making, this paper proposes the Statistical Theatre Model to describe situations in which quantitative evidence acquires persuasive force independent of its inferential value.The paper further considers cognitive and institutional factors that contribute to these errors and argues that improvement lies not in increased mathematical complexity, but in greater conceptual clarity. In addition to identifying common interpretive failures, the paper proposes practical reforms to improve the communication and evaluation of quantitative evidence by experts, lawyers, judges, and jurors. In doing so, it highlights the importance of aligning the presentation of quantitative evidence with the interpretive demands of legal decision-making. Statistical evidence must remain a tool of inference rather than an unwarranted source of certainty.
Open Access
Review
24 July 2026Highly Efficient Nanocomposites of Silica/Polyacrylamide Hybrids with Silver Nanoparticles for Various Modern Nanotechnologies
This paper presents a review of studies devoted to the synthesis, characterization, structure, properties, and functionality of grafted silica/polyacrylamide “core-corona” hybrids as effective nanoreactors and silver nanoparticle (AgNP) carriers for modern nanotechnologies. The evidence and features of direct low-temperature radical polymerization of acrylamide from the unmodified surface of SiO2 nanoparticles are considered in the context of the manifestation of dynamic matrix effects. A simple and reliable method for determining the number and length of grafted PAAm chains is indicated. Using a number of hybrid samples, the effect of these parameters on the particle size, surface charge, height, and permeability of the PAAm “corona” is demonstrated. A two-level fractal structure of hybrids in the bulk state and two morphological forms of their particles in aqueous solutions are established. Based on the proposed approach, the kinetics, mechanism of in situ synthesis, and the yield of AgNPs in hybrid solutions are characterized depending on the concentration of reagents and the “corona” structure. Considerable attention is paid to the possible application of AgNP/hybrid nanocomposites in promising nanotechnologies: in the production of biocidal hygienic materials and textiles, in wound healing, agriculture, fish farming and poultry farming, as well as anti-cancer agents.
Open Access
Article
24 July 2026The Threshold Effect and Mechanism of Environmental Tax Driving Agricultural Innovation and Productivity Development
This study defines environmental tax as a flexible policy instrument that promotes the green and efficient transformation of agricultural production and enhances agricultural innovation productivity; in line with China’s institutional context, it is continuously measured using pollution discharge fees before 2018 and Environmental Protection Tax revenue after the implementation of the Environmental Protection Tax Law in 2018. This paper uses panel data from 30 provinces in China to empirically test the magnitude, direction, and mechanism of environmental taxes on the development of agricultural innovation productivity using a two-way fixed effects model, heterogeneity test model, mediation effect model, moderation effect model, and threshold effect model. The study finds that environmental taxes can significantly promote the development of agricultural innovation productivity. Furthermore, by analyzing geographical locations and functional Positioning of Agricultural Production, it is found that environmental taxes exhibit differentiated characteristics in driving agricultural innovation productivity; Mediation effect tests revealed that environmental taxes promote agricultural innovation productivity by suppressing agricultural carbon emissions; moderation effect tests showed that agricultural industrial structure upgrading plays a positive moderating role in the promotion of agricultural innovation productivity by environmental taxes; The threshold analysis identifies a single carbon-emission threshold: when agricultural carbon emissions exceed the threshold, the productivity-enhancing effect of environmental tax becomes stronger. Heterogeneity tests further show that the effect is most evident in central China and major grain-producing areas, while the western region faces stronger compliance-cost pressure. The study contributes by integrating the compliance-cost, Porter-hypothesis, and nonlinear-threshold perspectives into one agricultural setting and by clarifying the policy boundary under which environmental taxation can foster agricultural innovation productivity.
Open Access
Review
24 July 2026How Does Intelligent Construction Drive Prefabricated Construction from Synergistic Mechanisms to Engineering Applications
As the construction industry shifts toward industrialization, digitalization, intelligence, and low-carbon development, prefabricated intelligent construction has emerged as a key pathway for enhancing efficiency, quality control, resource utilization, and full life-cycle management. Yet existing studies remain largely confined to single-technology applications, local process optimization, or isolated engineering cases, lacking a systematic grasp of the field’s development trajectory, knowledge structure, research hotspots, and future challenges. Addressing this gap, this study presents a bibliometric review aimed at clarifying the research evolution, core knowledge domains, technological frontiers, and application-oriented challenges in prefabricated intelligent construction. Based on the Web of Science Core Collection, 583 journal articles published from 2015 to 2025 were retained after standardized search and screening. Using VOSviewer and bibliometrix, the study analyzed publication trends, subject distribution, national and institutional collaboration, author networks, keyword co-occurrence, thematic clustering, and research frontiers. Compared with traditional narrative reviews, this approach integrates quantitative bibliometric analysis with thematic content interpretation, constructing a panoramic and dynamic analytical framework for the field. Research shows that prefabricated intelligent construction underwent a leap from initial exploration to rapid expansion during 2015–2025, with publications and citations from 2023–2025 accounting for 76.16% and 84.07% of the total sample, respectively, establishing it as an active research frontier. In the global landscape, China contributes prominently in output volume, while Australia, the United States, the United Kingdom, and Germany demonstrate relatively high per-publication impact. The disciplinary structure is dominated by engineering, construction, and building technology, supported by multidisciplinary intersections, forming three major research hotspots: the integration of prefabricated construction and intelligent technologies, process innovation and intelligent equipment, and structural performance and engineering applications. In essence, this field represents a full life-cycle construction paradigm arising from the deep coupling of industrialization, digitalization, intelligence, and performance control. Future breakthroughs are needed in four dimensions: full life-cycle data standards, digital twin-driven closed-loop platforms, equipment–process collaborative optimization, and multi-scenario engineering validation to drive the transition toward large-scale application.
Open Access
Review
23 July 2026Sustainable Business Models in Agri-Food Systems: A Systematic Review of Environmental Performance, Economic Resilience and Sustainability Trade-Offs
Sustainable transformation of agri-food systems has become increasingly important as environmental pressures intensify, resource availability declines, and global food demand rises. This study presents a structured review of sustainable business models in agri-food systems, examining their contributions to environmental performance, economic resilience, and sustainability trade-offs. Approximately 60 academic publications published between 2010 and 2024 were analyzed to evaluate theoretical foundations, sectoral applications, and enabling mechanisms, including digitalization, circular economy practices, and governance frameworks. Unlike previous studies focused on specific sustainability practices or sectors, this review provides an integrated assessment of environmental performance, economic resilience, and sustainability trade-offs within sustainable agri-food business models. The findings indicate that sustainable business models integrate ecological considerations into value creation, improve resource efficiency, and strengthen resilience across sectors such as aquaculture, dairy, and wine production. Sustainability outcomes are shaped by tensions among economic growth, ecological limits, and social equity, resulting in uneven and context-dependent outcomes. Digitalization and circular economy approaches create opportunities for innovation, resource optimization, and value recovery, but also introduce challenges related to energy consumption, data governance, unequal access, and implementation costs. Stakeholder engagement, performance measurement, and supportive institutions emerge as critical drivers of sustainability transitions. Thus, sustainable business models can enhance environmental performance and economic resilience, although their effectiveness depends on governance quality, equitable access to innovation, and the management of environmental, economic, and social trade-offs.
Open Access
Review
23 July 2026Sepsis-Induced Cardiomyopathy and Acute Respiratory Distress Syndrome
Sepsis remains the leading cause of acute respiratory distress syndrome (ARDS) and cardiovascular dysfunction in the ICU. Sepsis-induced cardiomyopathy (SCM) and sepsis-associated ARDS frequently coexist and share overlapping mechanisms, including cytokine-driven injury, endothelial disruption, microvascular dysfunction, and mitochondrial abnormalities. Despite their clinical relevance, these entities are often evaluated in isolation, overlooking the integrated heart-lung interactions that characterize severe sepsis and ARDS. This narrative review synthesizes current evidence on the shared pathophysiology and diagnostic approach to cardiomyopathy and lung injury in sepsis-associated ARDS, emphasizing the physiologic links that unify these syndromes. We review the immunologic, endothelial, and metabolic mechanisms that drive concurrent myocardial depression and alveolocapillary injury, with particular attention to microcirculatory failure, autonomic dysregulation, and mechanical ventilation-associated cardiopulmonary interactions. We then review diagnostic tools, including echocardiography, lung ultrasound, CT imaging, biomarkers, and advanced hemodynamic monitoring, and highlight the impact of integrated assessment on accurate phenotyping and management. Cardiomyopathy and ARDS in sepsis arise from common pathophysiologic drivers and should be understood as a unified cardiopulmonary phenotype rather than isolated organ failures. Early multimodal detection is critical for optimizing management strategies and improving outcomes.
