Herein, a colorimetric and smartphone dual-channel sensor has been constructed for the sensitive detection of acetone based on a chemically driven redox-cycling reactive system. In the redox-cycling system, o-phenylenediamine (OPD) acted as the colorimetric substrate. Initially, colorless OPD was oxidized by Cu2+ ions to generate Cu+ ions and light yellow 2,3-diaminophenazine (DAP). The Fenton-like reaction between hydrogen peroxide (H2O2) and generated Cu+ ions initiated the production of Cu2+ ions and hydroxyl radicals (·OH). The resulting ·OH and reproduced Cu2+ ions could further catalyze other OPD molecules, leading to the formation of more light yellow DAP molecules, with a distinct ultraviolet absorption peak appearing at 440nm. And this process continued until all OPD was completely consumed in the cycling reaction system. Interestingly, acetone was introduced into the redox-cycling system, leading to a colorless solution and a reduction of absorbance intensity at 440nm. Based on this phenomenon, a colorimetric sensor with excellent sensitivity and selectivity has been designed for the visual detection of acetone. The sensor exhibited a linear correlation with acetone concentrations within the range of 2μM to 5mM, achieving a detection limit of 0.5μM. Notably, RGB color space analysis was performed for the quantitative detection of acetone with the assistance of a smartphone. The results were in good agreement with the data obtained via UV-visible absorption spectroscopy. Furthermore, the strategy realized therapid detection of acetone in real tap water, river water, and lake water samples.

Lysine-reactive tag system for cell-surface protein labeling via N-acyl-N-alkyl sulfonamide chemistry.

ABSTRACT Waterborne latex films are promising environmentally benign materials for coating and adhesive applications; however, achieving sufficient mechanical strength remains a challenge. We previously developed a reactive latex system composed of hydroxyl group‐containing acrylic latex (AL) particles and blocked polyisocyanate (BPI) nanoparticles, which undergo in situ urethane crosslinking through the reaction between hydroxyl and isocyanate groups upon heating. In this study, we systematically examined the effect of the NCO/OH molar ratio, defined as the ratio of isocyanate groups in BPI nanoparticles to hydroxyl groups in AL particles, on the structure formation, thermal transitions, and mechanical behavior of the resulting polyurethane films. Cross‐sectional electron microscopy revealed interdiffusion between AL and BPI nanoparticles above their respective glass transition temperatures, leading to homogeneous polyurethane networks. Films prepared with NCO/OH ratios between 0.75 and 1.0 exhibited a well‐balanced combination of flexibility and surface hardness, whereas deviations from this range resulted in brittle or excessively soft structures. Films at an NCO/OH ratio of 1.0 also showed high optical transparency and excellent solvent resistance. These results elucidate the structure–property relationships governing crosslinked polyurethane latex films and provide molecular‐level insight into designing waterborne coatings.

Abstract Elevated levels of reactive oxygen species play an integral role in chronic inflammation. Current treatments for chronic inflammation often ignore reactive oxygen species and instead focus on symptom control or immunosuppression. However, by controlling reactive oxygen species in inflammatory environments, cyclic inflammation can be reduced. Combining reactive oxygen species scavenging delivery systems with stealth coatings can help avoid the innate immune system and enable targeted delivery to sites of inflammation without causing further oxidative stress. For this purpose, poly(propylene sulfide) nanoparticles were synthesized utilizing two different surfactants, Pluronic F‐127 and sucrose monolaurate, adding stealth properties to the coatings of the reactive oxygen species scavenging nanoparticles. Characterization of the nanoparticles demonstrated the surfactant coatings did not affect the scavenging abilities nor the cytocompatibility of the materials. Degradation of the nanoparticles related to the sulfide groups and disulfide bond interactions with reactive oxygen species was also analyzed. Moreover, proinflammatory cytokine secretion from macrophages exposed to the nanoparticles was investigated to determine immune response evasion. Results obtained showed little to no activation of macrophages exposed to nanoparticle formulations in regard to MCP‐1 cytokine release. However, there is room for improvement using glycerol‐based coatings with regard to protecting cells from reactive oxygen species exposure and reducing macrophage activation in relation to IL‐6 and TNF‐alpha. Overall, the nanoparticles investigated have the capabilities to improve inflammatory disease treatments by not only targeting delivery of therapeutics to the site of inflammation, but also avoiding excess immune response recruitment due to incorporation of stealth coatings.

The relevance of this study is determined by the need for new technological solutions to enhance the productivity of wells producing heavy and highly viscous crude oil. The work investigates multicomponent Al–Ga–In–Sn alloys as reactive systems capable of generating heat and hydrogen upon contact with water. The focus is placed on optimizing melting parameters and assessing how alloy composition and structural features affect reactivity. Phase composition was analyzed by X-ray diffraction, microstructure by SEM-EDX, and elemental composition by XRF. The results show that the hydrogen generation rate and heat release depend on melting temperature, holding time, and ratios of activating metals, as well as the physicochemical properties of the formation water, particularly salinity and pH. Reaction enthalpy and conversion efficiency were quantified. The highest hydrogen output and thermal effect were observed for the following compositions—90 wt.% Al, 5 wt.% Ga, 2.5 wt.% In, 2.5 wt.% Sn; and 85 wt.% Al, 5 wt.% Ga, 5 wt.% In, 5 wt.% Sn (825 °C, 30 min). Rapid heat and gas release is attributed to the eutectic structure and micro-galvanic interaction, which eliminate the induction period. These findings demonstrate the potential of such alloys for in situ heating, enhanced oil recovery, and autonomous hydrogen-energy applications.

Multi-scale investigation of long-term performance of permeable reactive barrier systems subjected to (bio)passivation.

Electrokinetic dual-cathode permeable reactive barrier system: Efficient Cr(VI) removal and Cr(III)/Fe(III) resource recovery from contaminated soil

A study of effect of physical properties on the impact of drop on a liquid pool for an immiscible reactive system

Rapid urbanization and population growth have escalated municipal solid waste (MSW) challenges, rendering traditional, reactive management systems inefficient and environmentally unsustainable. Digital Twin (DT) technology—dynamic virtual replicas of physical systems—offers a transformative solution for real-time monitoring and simulation, yet its application in MSW management remains nascent. This study proposes a comprehensive conceptual framework for integrating DT technology into municipal waste operations to enhance efficiency and sustainability. The methodology outlines a four-layer architecture integrating IoT sensors, AI-driven predictive modeling, and simulation tools to optimize the entire waste lifecycle. The proposed framework facilitates optimized routing, predictive maintenance, and energy analysis. The results suggest that implementing this model can significantly lower operational costs, mitigate greenhouse gas emissions, and support circular economy principles by enabling scenario testing and data-driven decision-making. Despite existing technical and economic barriers, the study concludes that DTs provide a vital pathway toward resilient, smart urban waste systems and recommends future real-world pilot studies to validate quantitative environmental and economic benefits.

We present a simulation-based framework to characterize the solvation and aqueous-phase reactivity of nitric oxide (NO) and nitrogen dioxide (NO2) in water. Using Continuous Fractional Component Monte Carlo (CFCMC) simulations, we compute Henry coefficients and chemical potentials of NO and NO2, while molecular dynamics (MD) simulations provide diffusion coefficients for NO. The results for NO are quantitatively in agreement with the experimental data when using the Saji force field. For NO2, we model the chemical equilibrium involving hydrolysis and acid-base reactions that generate HNO2, HNO3, NO2-, NO3-, and H3O+. By combining the chemical potentials obtained via CFCMC with a thermodynamic equilibrium model, we resolve the temperature- and pressure-dependent speciation and pH of the system. The model captures a transition from nitrous to nitric species with increasing temperature and predicts ionic distributions and pH shifts under varying NOx gas fluxes. This work provides a transferable methodology to connect molecular simulations with chemical speciation in reactive aqueous systems.

Supply chains are increasingly exposed to volatility, uncertainty, complexity, and ambiguity, rendering traditional reactive planning approaches inadequate for sustaining operational performance and resilience. While intelligent automation has been widely promoted as a transformative force in supply chain management, empirical evidence explaining how it enables a shift from reactive to proactive planning remains fragmented. This study addresses this gap by developing and testing a simulation-based primary research model that examines the performance implications of intelligent automation enabled proactive supply chain planning. Drawing on dynamic capabilities theory and resilience perspectives, the study constructs a scenario-based simulation framework comparing reactive planning systems with proactive planning architectures supported by predictive analytics, machine learning driven forecasting, and automated decision execution. Primary data are generated through repeated simulation runs under varying demand volatility and disruption scenarios. The results demonstrate that proactive planning systems consistently outperform reactive counterparts in terms of forecasting accuracy, lead-time stability, and disruption recovery speed. The findings further indicate that intelligent automation enhances sensing, seizing, and reconfiguring capabilities, enabling anticipatory decision-making rather than ex post corrective actions. By providing simulation-based evidence, this study contributes to supply chain theory by clarifying the mechanisms through which intelligent automation drives proactive planning and resilience. From a managerial perspective, the results offer actionable insights into sequencing automation investments and aligning digital capabilities with planning processes. The study advances the literature by positioning intelligent automation not merely as an efficiency tool, but as a strategic enabler of proactive and adaptive supply chain planning.

In this study, the reactive primary-secondary antioxidant covulcanized MC@AB/NBR composites were successfully prepared for the first time to address the issues of thermo-oxidative aging susceptibility and migration of antioxidant in NBR. The primary-secondary antioxidants, featuring unsaturated double bonds and sulfide ether structures, optimize the NBR cross-link network, promote vulcanization, and enhance mechanical properties. Specifically, the vulcanization rate increases from 10.6 min-1 to 12.6 min-1, and the elongation at break improves from 386.51% to 600.86%. The synergistic effect between the aniline structure of the primary antioxidant and the sulfide structure of the secondary antioxidant enhances thermo-oxidative aging resistance, with the aging coefficient increasing from 0.095 ± 0.004 to 0.774 ± 0.027 after aging at 121 °C for 120 h, superior to many commercial antioxidant systems. Concurrently, characterization methods including oxidation induction time (OIT), temperature of oxidative exothermic peak (T o), thermo-oxidative degradation kinetics and SEM of fractured cross-section have demonstrated the remarkable thermo-oxidative aging and degradation resistance of the reactive antioxidant MC@AB system. The mechanism reveal that the primary antioxidant MC releases hydrogen radicals to scavenge carbon-chain and peroxyl radicals, while the sulfide ether structure of secondary antioxidant AB degrades generated unstable hydroperoxides into stable alcohols, thereby terminating the thermo-oxidative aging chain reaction. The MC@AB system enhances aging resistance of NBR composites by reducing molecular chain unsaturation to strengthen stability and inhibiting aging via scavenging free radical and degrading hydroperoxide. This strategy offers a novel approach for designing long-term high-temperature-resistant rubber materials.

A modified optimization method for reactive power compensation in nonlinear traction power-supply systems is presented. The proposed approach, based on the Lagrange multiplier technique, simultaneously determines the optimal capacity and installation locations of compensating capacitor banks while accounting for existing capacitive reactance and preinstalled devices. Unlike traditional methods, the developed model explicitly considers the nonlinear and time-varying load behavior typical of traction power networks. The objective function minimizes active power losses and total system costs under voltage-quality constraints. Numerical experiments demonstrate that the proposed algorithm can reduce power losses by up to 30 %, ensuring improved voltage stability and energy efficiency. The approach is computationally efficient and can be integrated into real-time reactive power control systems for traction substations.

RELEVANCE. A reliable mathematical description of the processes accompanying unsteady flows of reacting combustible gas mixtures is relevant for a wide range of tasks related to furnace technology and heat generating plants. The development of a tool for numerical simulation of boiler processes will make it possible to predict the modes and operating conditions of their elements in order to improve the technical and economic performance of the installation as a whole. PURPOSE. Development of a mathematical model describing threedimensional unsteady flows of a reacting mixture of gases in combustion chambers, boiler bundles and flues of boiler units. The possibility of applying S.K. Godunov's method to numerical modeling of processes in furnace devices and convective elements of a boiler unit is considered. METHODS. The complexity of modeling furnace processes is related to their nonstationarity, the complexity of the configuration of the computational domain, which requires solving the problem in a three-dimensional formulation, the course of the combustion process and the presence of associated heat exchange processes with boiler elements. Therefore, the mathematical model describing the flows of a reacting mixture of gases in combustion chambers, boiler bundles and flues of boiler units includes three-dimensional unsteady NavierStokes equations of energy and turbulence. The process of natural gas combustion in a firebox is described within the framework of a simple chemically reactive system (SCRS). To account for the combustion process, it is proposed to add to the energy transfer equation a source equivalent to diffusion combustion under the assumptions of SCRS. To numerically implement a mathematical model of processes in boiler elements, the S.K. Godunov method was used in combination with the MUSCL scheme, which provides a second-order approximation of difference equations. RESULTS and DISCUSSIONS. A mathematical model suitable for calculating the processes of hydrodynamics and heat and mass transfer in water-tube boiler units has been developed and numerically implemented. Using the developed application software package, a number of calculations were performed for the KV-GM-1,25-115 hot water tube boiler. CONCLUSION. The proposed approach to solving the problem of developing a model suitable for numerical analysis of combustion processes makes it possible to obtain a universal tool for calculating and designing heat generating plants, which can be used to determine the parameters of thermal and gas-dynamic processes in boiler units. This will make it possible to improve existing structures or develop new ones with improved technical and economic characteristics, as well as identify and resolve local problems that interfere with boiler operation and are not solved using engineering calculation methods.

Objective: This study aimed to examine the relationships between borderline personality disorder and emotional reactivity and reinforcement sensitivity systems through multidimensional analyses. Specifically, it was aimed to evaluate the mediating roles of the emotional reactivity in the relationships between borderline personality disorder and behavioral inhibition system and also the freeze. Method: A total of 601 adults, 80% female (n = 481) and 20% male (n = 120), aged between 18 and 53 (M = 22.51, SD = 4.11), participated in the study. Based on the data obtained from the participants, the relationships among the personality disorder dimensions, reinforcement sensitivity systems (behavioral inhibition system, behavioral activation system, and fight-flight-freeze system), and emotional reactivity subdimensions were assessed using Pearson correlation-based and Gaussian partial correlation-based network analyses. Based on centrality measures obtained from the network analysis, the most influential variables were identified. Then, the mediating roles of the emotional reactivity subdimensions in the relationships between borderline personality disorder and the behavioral inhibition system and the freeze system were tested using PROCESS Macro Model 4. Results: Gaussian graphical model findings indicated that borderline personality disorder occupies a central position within the network structure and that both the behavioral inhibition system and the freeze system established strong relationships with the emotional reactivity dimensions. Mediation analyses revealed that the negative activation and negative intensity subdimensions had a significant mediating role in the relationship between borderline personality disorder traits and both motivational systems. Conclusion: The findings demonstrate the theoretical and clinical importance of considering the interaction between reinforcement sensitivity systems and negative emotional reactivity in the emergence and maintenance processes of borderline personality disorder.

ABSTRACT In the past few years, the evolution of artificial intelligence (AI), particularly generative AI (GenAI) and large language models (LLMs), has made human‐computer interactions more frequent, easier, and faster than ever before. This brings numerous benefits in terms of enhancing efficiency, accessibility, and convenience in various sectors from banking to health. AI tools and solutions applied in computers and communication devices support decision‐making processes and managing operations of users on the individual level as well as organisationally, including resource allocation, workflow automation, and real‐time data analysis. However, the current use of AI carries a substantial environmental footprint due to its reliance on high‐computational cloud resources. In such a context, this paper introduces the concept of agentic environments, a sustainability‐oriented AI framework that goes beyond reactive systems by leveraging GenAI, multi‐agent systems, and edge computing to minimize the negative impact of technology. These types of environments can contribute to the optimization of resource use, enhanced quality of life, and prioritization of sustainability while at the same time safeguarding user privacy through decentralized, edge‐driven AI solutions. Based on both secondary and primary data gathered during a focus group and semi‐structured interviews with AI professionals from leading technology companies, the authors provide a conceptual framework of agentic environments and discuss it in the context of three lenses, including personal sphere, professional and commercial use, and urban operations. The findings include the potential of agentic environments to foster sustainable ecosystems, mainly due to the optimisation of resource usage and securing the privacy of data. The study outlines recommendations for implementing edge‐driven deployment models to reduce dependency on currently widely applied high‐energy cloud solutions.

ABSTRACT The growing complexity of cyber threats, driven by intelligent malware and adaptive intrusion techniques, has exposed the limitations of conventional, reactive cybersecurity systems. To address this challenge, this paper presents a Lightweight Neuromorphic‐Temporal Graph Framework (LNTGF) that combines neuromorphic intelligence with temporal graph reasoning to achieve proactive and self‐adaptive defense in IoT and 5G/6G environments. The proposed framework employs spiking neural networks (SNNs) to perform real‐time, low‐power anomaly detection at the network edge, while contextually modulated temporal graph neural networks (CMTGNNs) model the evolving relationships between connected devices and threats. This dual‐layer design allows the system to anticipate attack patterns, adjust security policies dynamically, and mitigate risks before compromise occurs. Experiments using benchmark IoT datasets demonstrate 96.3% detection accuracy, 28% faster mitigation response, and a 65% reduction in energy consumption compared with existing models. The results confirm that integrating neuromorphic adaptability with graph‐based temporal intelligence offers an effective path toward scalable, energy‐efficient, and predictive cybersecurity. The proposed framework marks a step forward in designing intelligent defense architectures capable of learning, reasoning, and evolving alongside the threats they confront.

Vertically oriented patterns with desired physicochemical properties fabricated via directed self-assembly of high-χ block copolymers (BCPs) are critical for enhancing device performance, particularly in semiconductors. However, the lack of chemical structural tunability and challenges in vertically orienting the conventional high-χ BCPs have impeded practical applications. This study introduces poly(methyl methacrylate-block-(pentafluorophenyl acrylate-gradient-styrene)), a novel reactive polymer gradient-random block containing BCP (GRC-BCP) system. This unique system provides structural expandability through post-polymerization modifications. Moreover, using the tailored gradient block structure, vertically oriented patterns can be realized on diverse substrates without surface neutralization. Vertically oriented patterns with precisely controlled linewidths ranging from 7 to 13nm are successfully achieved in organosilicon and organotin GRC-BCPs, synthesized via this system. Furthermore, this work demonstrates that the organosilicon GRC-BCP can be applied as a highly robust photoresist height enhancer for extreme ultraviolet lithography. After Si deep etching, this work obtains Si patterns with an aspect ratio of 5.78 at 13nm half-pitch, line edge roughness of 1.05nm, and line width roughness of 1.66nm. Offering efficient synthesis and broad utility, the reactive polymer GRC-BCP system is expected to be expanded to various applications as a platform material where vertically oriented patterns with applicable functionalities are essential.

This study analyzed the relationship between Suspended Sediment Concentration (SSC), rainfall, and water discharge in four large basins that drain entirely cratonic areas: Negro, Branco, and Tapajós, in the Amazon basin, and Congo, in Central Africa. We analyzed 1,323 samples of suspended sediment concentration (SSC) combined with precipitation and discharge data. A combination of statistical correlation parameters, time lag analysis, and hysteresis evaluation were calculated to identify the main controls on the SSC of cratonic rivers. Results indicate strong heterogeneity in sediment dynamics among the rivers. The Branco River displayed linear relationships between SSC and hydrological variables, moderate clockwise hysteresis and no lag, confirming a hydrologically reactive system with rapid sediment mobilization. In contrast, the Negro and Tapajós Rivers showed low linear correlations and moderate to high lag values, suggesting non-linear sediment responses associated with dilution, storage and geomorphological controls. However, the Negro River exhibited moderate anticlockwise hysteresis (HI = −0.20), negative lag values and low partial correlation, suggesting delayed sediment response, floodplain storage and dilution during high flows. The Congo River exhibited strong partial correlation with rainfall but lacked hysteresis and presented long lag values (−8 to −10 months), indicating that SSC responds predominantly at interannual climatic scales rather than to annual discharge cycles. Geological differences among basins proved crucial: rivers draining deeply weathered cratonic areas (Negro, Tapajós and Congo) showed dissipated sediment signals, whereas the Branco River, partially draining erodible Quaternary deposits, exhibited strong hydrological coupling. By combining multiple approaches, the study provides a framework for understanding sediment transport in cratonic rivers and contributes to sediment budgeting, climate-change assessments and geomorphological modeling in tropical basins.

The study analyzes vendor management together with cost reduction approaches in procurement through a case study focused on Ericsson. The research base analyzes three theoretical views to build foundational understanding about optimizing vendor relationships which include Principal-Agent Theory and Transaction Cost Economics and Resource Dependence Theory. The paper analyzes performance-tracking methods combined with risk control techniques and data-based decision support mechanisms sustainability practices and supply chain management approaches. The Findings states that Ericsson achieves enhanced efficiency and resilience through its implementation of advanced analytics as well as proactive and reactive risk management systems and collaborative supplier relationships. The research acknowledges that successful cost savings efforts still face obstacles when trying to maintain sustainability alongside innovation. The discussion ends by giving academic and industrial stakeholders guidance about integrating procurement approaches for dynamic global markets